News Article | May 8, 2017
Parkinson's is a chronic, degenerative neurological disorder that affects one in 100 people over age 60. Recent research indicates that as many as one million Americans, and more than five million people worldwide, live with Parkinson's disease. In 2016, ATCC released three cell lines for investigating biological processes associated with LRRK2, a key Parkinson's disease genetic target. The Michael J. Fox Foundation funded the production and validation of these cell lines. ATCC also continues to work with MJFF to provide additional research tools, and is currently working on the production, validation, storage and future distribution of Parkin-expressing HeLa cells, which will be available later in 2017. "Research tools and reference reagents enable scientists to gain insight into the mechanisms of disease, and are critical in the development of new treatments," said Dr. Raymond Cypess, ATCC's Chairman and CEO. "These tools and reagents are also critical in recruiting scientists to work in specific disease areas. As partners to the scientific community for more than 90 years, ATCC is proud to join MJFF at ISBER to discuss the significance of these tools and the need to increase access and availability for the global research community." "The Michael J. Fox Foundation's collaboration with ATCC delivers vital pre-clinical tools to the Parkinson's research community to address field-wide challenges and advance disease understanding," said Nicole Polinski, Ph.D., associate director of research programs at MJFF. "We are pleased to join ATCC at ISBER to highlight the importance of these tools in developing therapeutic strategies and speeding PD research." About ATCC ATCC is a leader in biological materials management supporting the scientific community and government with research and development, products, and services in support of global health issues. With a history of innovation spanning more than 90 years, ATCC offers the world's largest and most diverse collection of human and animal cell lines, microorganisms, biological products, and standards. ATCC is a non-profit organization with headquarters in Manassas, Va. For more information about ATCC, visit us at www.atcc.org. To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/atcc-and-the-michael-j-fox-foundation-for-parkinsons-research-to-facilitate-workshop-at-isber-annual-meeting-300453151.html
News Article | February 19, 2017
WASHINGTON, D.C., Feb. 19, 2017 - One year after the Global Biological Standards Institute (GBSI) issued its Reproducibility2020 challenge and action plan for the biomedical research community, the organization reports encouraging progress toward the goal to significantly improve the quality of preclinical biological research by year 2020. "Reproducibility2020 Report: Progress and Priorities," posted today on bioRxiv, identifies action and impact that has been achieved by the life science research community and outlines priorities going forward. The report is the first comprehensive review of the steps being taken to improve reproducibility since the issue became more widely known in 2012. "By far the greatest progress over these few years has been in stakeholders recognizing the severity of the problem and the importance of taking active steps for improvement," said Leonard P. Freedman, PhD, president of GBSI. "Every stakeholder group is now addressing the issues, including journals, NIH, private funders, academicians and industry. That's crucial because there is not one simple fix--it is a community-wide problem and a community-wide effort to achieve solutions." The report addresses progress in four major components of the research process: study design and data analysis, reagents and reference materials, laboratory protocols, and reporting and review. Moreover, it identifies the following broad strategies as integral to the continued improvement of reproducibility in biomedical research: 1) drive quality and ensure greater accountability through strengthened journal and funder policies; 2) create high quality online training and proficiency testing and make them widely accessible; 3) engage the research community in establishing community-accepted standards and guidelines in specific scientific areas; and 4) enhance open access to data and methodologies. Research community stakeholders have responded with innovation and policy. The community is taking more steps to work together and to tackle the complexities of the reproducibility problem. The report highlights tangible examples of community-led actions from implementing new funding guidelines and accountability to tackling industry-wide research standards and incentives for compliance. The lessons learned from these early efforts will assist all stakeholders seeking to scale up or replicate successful initiatives. "We are confident that continued transparent, global, multi-stakeholder engagement is the way forward to better, more impactful science," says Freedman. "We are calling on all stakeholders - individuals and organizations alike - to take action to improve reproducibility in the preclinical life sciences by joining an existing effort, replicating successful policies and practices, providing resources to replication efforts and taking on new opportunities." The report contains specific actions that each stakeholder group can take to enhance reproducibility. In its leadership role, GBSI will: Freedman introduced the new report at the AAAS 2017 Annual Meeting today during the session, "Rigor and Reproducibility One Year Later: How Has the Biomedical Community Responded?," hosted by GBSI. Freedman was joined by panelists Michael S. Lauer, M.D. of NIH; William G. Kaelin Jr., M.D. of the Dana-Farber Cancer Institute; and Judith Kimble University of Wisconsin-Madison. "The research culture, particularly at academic institutions, must also seek greater balance between the pressures of career advancement and advancing rigorous research through standards and best practices," said Freedman, noting a major challenge still facing the community. "Additional leadership and community-wide support will be needed and we believe that the many initiatives described in this report add needed momentum to this emerging culture shift in science. "The preclinical research community is full of talented, motivated people who care deeply about producing high-quality science. We are optimistic about the potential to improve reproducibility, and look forward to continuing to contribute to the effort." GBSI is an independent non-profit organization dedicated to enhancing the quality of biomedical research by advocating best practices and standards to accelerate the translation of research breakthroughs into life-saving therapies. GBSI was founded by ATCC. For more information, visit GBSI.org and Twitter @GBSIorg.
News Article | February 15, 2017
No statistical methods were used to predetermine sample size. The experiments were not randomized. The investigators were not blinded to allocation during experiments and outcome assessment. Cell lines used in this study were obtained from American Type Culture Collection (ATCC) and cultured under standard conditions. HCT116 cells were authenticated by karyotyping. All cell lines were confirmed to be free of mycoplasma contamination. EGFP was PCR amplified from EGFP-hAGO2 (Addgene catalogue number 21981) and cloned into pMSCV-Puro (Clontech) using the BglII and XhoI restriction sites. The puromycin resistance cassette was then removed by EcoRI and ClaI digestion and replaced with an insert containing eight imperfect miR-19 binding sites (modelled from ref. 39), synthesized as a gBlock (IDT) (sequence in Supplementary Table 8). For the EGFP-only reporter, the puromycin resistance cassette was removed by EcoRI and ClaI digestion followed by re-ligation after filling-in overhangs. Reporters for miR-16 and miR-200c were generated by replacing the puromycin cassette in the pMSCV-Puro vector containing EGFP by digesting with EcoRI and ClaI and ligating in oligonucleotides containing single miRNA binding sites (sequences in Supplementary Table 8). Multiple cloning cycles were performed using MfeI and ClaI to generate the final reporters containing eight total binding sites. MSCV-EGFP, MSCV-EGFP-miR-19, MSCV-EGFP-miR-16, and MSCV-EGFP-miR-200 retrovirus was generated by first seeding 6 × 105 cells per well in a six-well dish. The following day, cells were transfected using 1 μg of plasmid (MSCV-EGFP or MSCV-EGFP-miR-19), 3 μl of FuGENE HD (Promega), and 200 μl Opti-MEM (Thermo Fisher) per well according to the manufacturer’s instructions. Media were changed the next day. Two days after transfection, media were collected and passed through a 0.45 μm SFCA sterile filter. Recipient HCT116 cells were transduced overnight at a multiplicity of infection (MOI) of approximately 0.2 using media supplemented with 8 μg/ml polybrene (EMD Millipore). Cells expressing EGFP were enriched by FACS and single-cell clonal lines were derived. Heterogeneous knockout cell populations were generated using lentiCRISPR v2 (Addgene catalogue number 52961) or lentiCRISPR-hygro. lentiCRISPR-hygro was constructed by replacing the puromycin resistance open reading frame (ORF) in lentiCRISPR v2 with a hygromycin resistance ORF. A silent mutation was introduced into a BsmBI restriction site within the hygromycin resistance ORF to prevent fragmentation of the vector when cloning sgRNA oligonucleotides. sgRNA sequences (Supplementary Table 8) were cloned as described previously12. An sgRNA targeting an irrelevant gene (PPID) or a non-targeting guide were used as negative controls. To generate active lentivirus, 6 × 105 293T cells were first seeded in six-well dishes and transfected the following day using a 5:3:2 ratio of lentiCRISPR:psPAX2 (Addgene catalogue number 12260):pMD2.G (Addgene catalogue number 12259) using FuGENE HD and 1 μg of total plasmid per well. Media were changed the next day. Two days after transfection, media were collected and passed through a 0.45 μm SFCA sterile filter. Media containing the virus were diluted 1:1 with fresh media and used to transduce recipient cells overnight in a final polybrene concentration of 8 μg/ml. Media were changed 24 h later, and cells were split into fresh media containing 1 μg/ml puromycin 48 h after transduction. To generate clonal knockout lines, single-cell cloning was performed after infection with lentiCRISPR v2, lentiCRISPR-hygro, or after transient transfection of PX330 (Addgene catalogue number 42230) targeting the gene of interest. lentiCRISPR v2-derived clones were used in Figs 2d, 4d, e and 5a, e and Extended Data Figs 2, 4e, 5c, and 9a, b. A lentiCRISPR-hygro derived ANKRD52–/– clone was used in Fig. 2e. PX330-derived clones were used in Figs 2a, f and Extended Data Figs 3, 4c, 6, 7, 8c, d, 9a, b, d and 10. Three hundred thousand reporter cells were seeded per well in six-well dishes. Cells were transfected the following day with a mixture of inhibitors for miR-19a and miR-19b at 5 nM each (MiRIDIAN microRNA Hairpin Inhibitors, GE Dharmacon) using Lipofectamine RNAiMAX (Thermo Fisher). Fluorescence was assessed by flow cytometry 48 h after transfection. Lentiviral sgRNA library production. The human GeCKO v2 library was obtained from Addgene (catalogue number 1000000048) and amplified according to the provided instructions. Plasmid was purified from bacterial pellets using a Qiagen Plasmid Maxi Kit. Active lentivirus was prepared in 293T cells by first seeding 3.2 × 106 cells per 10-cm dish. GeCKO library A and library B were prepared independently using 15 dishes per library. The day after seeding, each dish was transfected using 10 μg of total plasmid (5:3:2 ratio of GeCKO library:psPAX2:pMD2.G), 30 μl of FuGENE HD, and 900 μl of Opti-MEM. Medium was exchanged the following day. Media collections at 48 and 72 h after transfection were pooled before filtering through a 0.45 μm SFCA sterile filter. Aliquots of the library were snap frozen on dry ice and ethanol before being stored at −80 °C. Library titre was determined as described12. Transduction of reporter cell lines with lentiCRISPR library. Genome-wide CRISPR–Cas9 screens using HCT116EGFP-miR-19, HCT116EGFP, or ANKRD52–/– HCT116EGFP-miR-19 cells were performed using both GeCKO v2 libraries A and B. Biological replicates were performed for all screens. For each transduction, five 12-well plates were seeded with 5 × 105 reporter cells per well. An overnight transduction was performed the following day by diluting virus to an MOI of 0.2–0.4 in 8 μg/ml polybrene. Cells were then trypsinized and pooled before being plated into fresh medium in six 15-cm dishes. Forty-eight hours later, cells were trypsinized, pooled, counted, and seeded into five 15-cm dishes with 1 μg/ml puromycin using 2.4 × 107 cells per dish. In parallel, a small aliquot of cells was used to confirm that an MOI of 0.2–0.4 was achieved. Cells were passaged for 12–14 days before sorting. At every passage, 1 × 107 cells were seeded per dish into four 15-cm dishes with medium containing puromycin. At least 2 × 107 cells were transduced with each library for each screen, corresponding to ~300× or greater coverage. Cell sorting. Two days before sorting, ten 15-cm dishes with 1.2 × 107 cells per dish were seeded for each library–reporter pair. Samples were prepared for FACS by trypsinization in 0.25% trypsin-EDTA (Thermo Fisher) for 7 min. Cells were dissociated by pipetting up and down approximately 20 times with a P1000 pipet to minimize doublets. Dissociated cells were pipetted directly into media, pelleted at 300g for 5 min, and washed once with PBS. Cells were resuspended at 1.4 × 107 cells per millilitre in PBS supplemented with 3% FBS. Cells were sorted at the University of Texas Southwestern Flow Cytometry Core Facility using a MoFlo cell sorter (Beckman Coulter). The brightest or dimmest 0.5% of cells were collected on the basis of EGFP fluorescence. Cell sorting was performed on approximately 9 × 107 cells, and typical yields ranged from 2 × 105 to 3 × 105 sorted bright/dim cells. Cells were pelleted at 300g and frozen at −80 °C for genomic DNA (gDNA) extraction. Unsorted cells were similarly collected. Genomic DNA extraction. gDNA was extracted from the unsorted cells using a Qiagen DNeasy Blood & Tissue Kit according to the manufacturer’s instructions. Extractions were performed on 4 × 107 cells using 5 × 106 cells per column to ensure enough gDNA for 300× coverage of the library. DNA was eluted by adding 125 μl of water to each column. The same eluate was added back to the column for a second elution. The DNA concentration in the final eluate was assessed using a Qubit dsDNA BR assay kit (Thermo Fisher). To facilitate maximum recovery of gDNA from the sorted cells, a previously described method40 was used with the following modifications: sorted cell pellets were resuspended in 500 μl of tissue lysis buffer, consisting of 460 μl of STE buffer (1 mM EDTA (pH 8.0), 10 mM Tris-HCl (pH 8.0), 100 mM NaCl) supplemented with 10 μl of 0.5 M EDTA, 10 μl of proteinase K (10 mg/ml in TE buffer containing 10 mM Tris-HCl (pH 8.0) and 1 mM EDTA), and 20 μl of 10% SDS. Pellets were digested overnight at 55 °C while shaking at 1,000 r.p.m. on a Thermomixer (Eppendorf). The following day, 5 μl of 2 mg/ml RNase A was added to each tube and incubated at 37 °C for 1 h while shaking at 1,000 r.p.m. Extractions were performed with an equal volume of pH 7.9-buffer saturated phenol, followed by phenol:chloroform:isoamyl alcohol (25:24:1), followed by chloroform. Twenty micrograms of glycogen (Roche) and 1.5 ml of 100% ethanol were added to each tube and DNA was precipitated at −80 °C for 1 h followed by centrifugation at 18,000g for 10 min at 4 °C. Pellets were washed with 1 ml of 75% ethanol, dried, and resuspended in 21 μl of water by incubating at 37 °C for a minimum of 4 h. DNA concentration was determined with the Qubit dsDNA BR assay kit. Sequencing library preparation. Methods to prepare PCR amplicon libraries for deep sequencing were adapted from a previously published protocol12. All primer sequences are provided in Supplementary Table 8. For unsorted cells, an initial round of PCR (PCR I) was performed using 6.6 μg of gDNA per 100 μl PCR reaction. To maintain 300× coverage, 20 reactions were assembled for each sample. For sorted cells, all extracted gDNA for a given sample was distributed into two 100 μl reactions. In both cases, 18 cycles of amplification were performed using Herculase II Fusion polymerase (Agilent). All reactions for a given sample from PCR I were then pooled together and a second round of PCR (PCR II) was performed to add the necessary adapters for Illumina sequencing. Owing to variable PCR efficiency between samples, the cycle number for PCR II was adjusted so that each library was amplified in a 50 μl reaction to a common endpoint with respect to DNA quantity (approximately 50 ng of DNA library in a 50 μl PCR sample). DNA was purified for sequencing using AMPure XP beads (Agencourt) according to the manufacturer’s instructions with the following modifications: each 50 μl PCR II reaction was mixed with 25 μl of beads and incubated for 5 min. Magnetic separation was used to collect the supernatant. The supernatant was mixed with 90 μl of beads and incubated for 5 min. The supernatant was collected and discarded. Beads were washed twice with 200 μl of 70% ethanol and then dried for approximately 12 min. Bound DNA was eluted from the beads using 40 μl of water. Next-generation sequencing. Before sequencing, all DNA libraries were analysed using a Bioanalyzer High Sensitivity DNA Analysis Kit (Agilent). Library concentration was then determined by qPCR using a KAPA Library Quantification Kit for Illumina platforms. All samples were sequenced on an Illumina HiSeq 2500 or a NextSeq 500 with 75 bp single reads. Approximately 15 million to 20 million reads were sequenced per library. Sequencing data analysis. A reference file for all sgRNAs in the library was acquired from Addgene, and identical sgRNAs targeting more than one protein-coding gene were removed. Demultiplexed FASTQ files were mapped to the reference file using Bowtie 2 requiring unique alignments with no mismatches. Normalized read counts were calculated as described previously12. Screen hits were identified using RIGER16 with the following parameters: log(fold-change ranking), 1 × 106 permutations, second-best rank (SBR) scoring algorithm. RNA was extracted from cells using a miRNeasy Mini Kit (Qiagen) with an on-column DNase digestion. cDNA was generated using either the SuperScript IV First-Strand Synthesis System (Thermo Fisher) or MultiScribe Reverse Transcriptase (Thermo Fisher). SYBR Green assays were performed using SYBR Green PCR Master Mix (Applied Biosystems) with custom primer pairs or qRT–PCR assays for mature miRNAs or mRNAs were performed using pre-designed assays and the TaqMan Universal Master Mix II (Applied Biosystems). Primer sequences and catalogue numbers provided in Supplementary Table 8. A custom Taqman assay was designed for pri-miR-17-92 (sequences provided in Supplementary Table 8). For all co-immunoprecipitation assays, 3.2 × 106 293T cells were seeded 1 day before transfection. Cells were transfected using FuGENE HD with 10 μg of total plasmid. Media were changed the following day. Cells were harvested 48 h after transfection. Cells were washed once, scraped in PBS, and lysed on ice for 10 min in 1 ml of lysis buffer composed of 25 mM Tris-HCl (pH 8.0), 150 mM NaCl, 2 mM MgCl , 0.5% NP-40, 1 mM DTT, and a protease inhibitor cocktail (cOmplete EDTA-free, Roche). Lysates were spun at 10,000g for 10 min. Supernatants were collected and diluted with 0.5 volumes of fresh lysis buffer. One and a half microlitres of immunoprecipitation antibody (anti-V5 (Invitrogen catalogue number 46-0705) or anti-HA (Cell Signaling catalogue number 2367S)) were added to each sample and rotated at 4 °C for 30 min. Thirty microlitres of washed Dynabeads Protein G (Thermo Fisher) were added to each sample and incubated for 6 h. RNase A (Thermo Fisher) was added to a final concentration of 20 μg/ml where indicated. Samples were washed four times in ice-cold lysis buffer. Fifty microlitres of 2× Laemmli sample buffer were added to each sample and aliquots were used for western blot analysis. Antibodies used for western blotting included anti-HA (2367S, Cell Signaling), anti-V5 (46-0705, Invitrogen), anti-AGO2 (SAB4200085, Sigma), anti-GAPDH (2118S, Cell Signaling), anti-α-tubulin (T6199-200UL, Sigma), anti-BRD4 (13440S, Cell Signaling), anti-CTNNB1 (9587S, Cell Signaling), anti-POU2F1 (8157S, Cell Signaling), anti-ANKRD52 (A302-372A, Bethyl), and anti-CSNK1A1 (sc-6477, Santa Cruz). SDS–PAGE gels (7%) were supplemented with Phos-tag AAL solution (Wako) according to the manufacturer’s recommendations. Gels were run at 100 V in an XCELL SureLOCK Mini-Cell (Invitrogen) until the dye front completely exited the gel. Gels were incubated in transfer buffer supplemented with 1 mM EDTA for 10 min. Gels were then soaked in normal transfer buffer for 10 min. Proteins were transferred to a nitrocellulose membrane and standard western blotting procedures were subsequently followed. For lambda phosphatase treatments, lysates were generated as described in the co-immunoprecipitation assays. Lysate (50 μl) was mixed with 10× MnCl buffer and 10× reaction buffer provided with the lambda protein phosphatase kit (NEB). Samples treated with enzyme received 1 μl of purified lambda protein phosphatase. Incubations were performed for 45 min at 30 °C, and samples were subjected to chloroform–methanol precipitation41 before Phos-tag electrophoresis. Endogenous AGO2 was purified from ANKRD52+/+ and ANKRD52–/– HCT116 cells. AGO2–/– cells were used as a control. Ten million cells were seeded per 15-cm dish, and eight dishes were used per cell line. AGO2 was immunoprecipitated using methods adapted from an established protocol42 with 100 μl of Dynabeads Protein G loaded with 18 μg of anti-AGO2 antibody (SAB4200085, Sigma) per purification. Immunoprecipitation eluates were resuspended in 5× Laemmli sample buffer. FH-AGO2 constructs (WT, T830A, S824A/T830A) were stably expressed using MSCV-puro in ANKRD52–/– cells. Ten million cells were seeded per 15-cm dish, and eight dishes were used per cell line. Media were changed 48 h later. Cells were scraped in PBS 72 h after plating. Lysates were generated using methods similar to the co-immunoprecipitation assays, with the exception that a phosphatase inhibitor cocktail (PhosStop, Roche) was included and lysate supernatants were diluted with one volume of lysis buffer. Proteins were immunoprecipitated using 100 μl of Dynabeads Protein G loaded with 20 μg of anti-Flag antibody (F1804, Sigma). Beads were rotated at 4 °C for 3 h. Beads were washed five times in lysis buffer. Proteins were eluted using 70 μl of 2× Laemmli sample buffer per 100 μl of beads. Purified AGO2 proteins were separated by SDS–PAGE and stained using InstantBlue (Expedeon). Gel slices containing AGO2 bands were reduced by DTT, alkylated by iodoacetic acid, and digested with trypsin (Trypsin Gold; Promega). The digestion was stopped by adding formic acid, followed by peptide extraction in acetonitrile. Extracted peptides were desalted by C18 ZipTip (Millipore). Peptide mixtures were separated by C-18 resin (100 Å, 3 μm, MICHROM Bioresources) in-house packed into a silica capillary emitter (100 μm ID, 100 mm resin length). LC gradient was generated by a Dionex Ultimate 3000 nanoLC system (Thermo Scientific), with mobile phase A: 0.1% formic acid and B: 0.1% formic acid in acetonitrile. Mobile phase gradient: 2% B at 0–15 min, 30% B at 81 min, 35% B at 85 min, 40% B at 87 min, 60% B at 95 min, 80% B at 96–107 min and 2% B at 108–120 min. Flow rate: 600 nl/min at 0–13.5 min, 250 nl/min at 13.5–120 min. Peptide eluents were sprayed online with a nano-electrospray ion source (Thermo Scientific) at spray voltage of 1.5 kV and capillary temperature of 250 °C. High-resolution MS analysis was performed on a QExactive Quadrupole-Orbitrap Hybrid mass spectrometer (Thermo Scientific), operating in data-dependent mode with dynamic exclusion of 30 s. Full-scan MS was acquired at an m/z range of 300–1650, resolution of 70,000, and automatic gain control target of 3 × 106 ions. The top 15 most intense ions were subsequently selected for higher-energy collisional dissociation fragmentation at resolution of 17,500, collision energy of 27 eV, and automatic gain control target of 1 × 105 ions. Proteome data analysis used Mascot (Matrix Science) and Proteome Discoverer (1.4, Thermo Scientific). The raw data were searched against the human proteome database (Uniprot, UP000005640) plus common contaminants. Static modification was cysteine carbamidomethylation; variable modifications were serine or threonine phosphorylation, methionine oxidation, and glutamine or asparagine deamination. Precursor mass tolerance was 20 p.p.m. and fragment mass tolerance, 0.05 Da. The maximum number of miscleavage sites allowed was 2. After peptide identification, precursor ion intensities were quantified manually in XCalibur using extracted ion chromatogram. Sequences of all primers used for cloning are provided in Supplementary Table 8. Flag–HA-AGO2 (FH-AGO2) was PCR amplified from pIRES-neo-Flag/HA AGO2 (Addgene catalogue number 10822) and subcloned into pcDNA3.1+. FH-AGO2 mutants were generated using a QuikChange II XL Site-Directed Mutagenesis Kit (Agilent) or by cloning customized gBlocks (IDT) into the parental pcDNA3.1+ vector containing FH-AGO2 (sequence of all mutants provided in Supplementary Table 8). Stable expression of wild-type or mutant FH-AGO2 was achieved in one of two ways. In one, constructs were subcloned into pMSCV-puro (Clontech). In another, stable expression of AGO2 for RNA-seq and eCLIP experiments was achieved by cloning individual mutants into a modified pLJM1-EGFP vector (Addgene catalogue number 19319) where EGFP was resected using AgeI and BsrGI before blunt-end ligation. AGO2 constructs were introduced at the EcoRI cloning site. Flag–HA-AGO1 was subcloned from pIRESneo-Flag/HA AGO1 (Addgene catalogue number 10820) into pMSCV-PIG (Addgene catalogue number 21654). V5-tagged ANKRD52 (corresponding to NP_775866.2) was constructed by PCR amplification from HCT116 cDNA followed by cloning into pcDNA3.1+. cDNA clones for human PPP6C and CSNK1A1 were obtained from the Invitrogen Ultimate ORF LITE Library (Clone ID IOH7224 and IOH59150, respectively) and subcloned into pCAGIG (Addgene catalogue number 11159) using Gateway LR Clonase (Thermo Fisher). For tethering assays, a 5× BoxB sequence adapted from a previous report32 was designed as a gBlock (IDT) and cloned in the XbaI site of pGL3-Control (Promega) (sequence in Supplementary Table 8). For the λN constructs, a gBlock containing the λN peptide sequence with an HA tag32 was subcloned into pcDNA3.1-FH-AGO2, replacing the Flag–HA tag. To generate control plasmid expressing λN-HA peptide alone, the λN-HA sequence was PCR amplified and cloned into pcDNA3.1+. Active lentivirus was generated using FH-AGO2 mutants (WT, 5XA, S828A, and empty vector) cloned into a modified pLJM1 vector with EGFP resected. A viral packaging protocol analogous to that used for the lentiCRISPR lentivirus preparations was used. Recipient ANKRD52–/– HCT116EGFP-miR-19 cells were transduced at an MOI of approximately 0.2. Transduced cells were selected in puromycin for at least 10 days, before use in flow cytometry experiments (Fig. 2f). For experiments involving endogenous AGO2, HCT116EGFP-miR-19 cells were used. For analysis of FH-AGO2 miRNA or mRNA binding, cells stably expressing the indicated wild-type or mutant FH-AGO2 protein were first generated by infecting AGO2–/– HCT116 cells with MSCV retroviruses. Then, for each immunoprecipitation sample, 6 × 106 cells were seeded per 10-cm dish. Cells were harvested 48 h later by scraping in PBS. Pelleted cells were resuspended in 1 ml of a lysis buffer consisting of 25 mM Tris-HCl (pH 8.0), 150 mM NaCl, 2 mM MgCl , 0.5% NP-40, 1 mM DTT, a protease inhibitor cocktail (cOmplete, EDTA-free, Roche), and 250 U/ml Recombinant RNasin Ribonuclease Inhibitor (Promega). Cells were lysed on ice for 10 min. Samples were spun at 10,000g for 10 min. Supernatant fractions were retained. Protein concentration was determined using a Bio-Rad DC Protein Assay Kit, and all samples were adjusted to the same concentration with lysis buffer. Dynabeads Protein G (Thermo Fisher) were prepared by pre-incubating with 1.5 μg of antibody (either anti-Flag (F1804, Sigma) or anti-AGO2 (SAB4200085, Sigma)) and pre-blocking with 0.5 mg/ml BSA, 0.5 mg/ml yeast tRNA, and 0.2 mg/ml heparin. Each sample was incubated with 25 μl of prepared Dynabeads Protein G for 3 h at 4 °C. Samples were washed three times in lysis buffer. Captured protein was eluted from the beads using either 2.5 mg/ml 3× Flag peptide (Sigma) or 3.5 mg/ml AGO2 peptide (sequence derived from ref. 42, synthesized at the University of Texas Southwestern Protein Chemistry Technology Core) dissolved in lysis buffer. Eighty per cent of the eluate was harvested for RNA extraction and 20% was diluted with 2× Laemmli sample buffer for western blot analysis. For each immunoprecipitation, qRT–PCR assays were performed to determine input and immunoprecipitation levels for mature miRNAs and mRNA targets of interest. Western blot analysis determined the relative amount of AGO2 in the immunoprecipitation eluate. RNA quantity as a percentage of input was determined for all immunoprecipitation eluates and then normalized to the relative amount of protein captured in each eluate. Experiments to capture AGO2 loaded with miRNA were adapted from a previously published method30. ANKRD52+/+ and ANKRD52–/– HCT116EGFP-miR-19 cells were seeded at 1.35 × 107 cells per dish in six 15-cm dishes per cell line. Forty-eight hours later, cells from each dish were scraped in PBS, pelleted, and lysed on ice for 10 min in 1 ml of a buffer containing 25 mM Tris-HCl (pH 8.0), 150 mM NaCl, 2 mM MgCl , 0.5% NP-40, 1 mM DTT, a protease inhibitor cocktail (cOmplete, EDTA-free, Roche), a phosphatase inhibitor cocktail (PhosStop, Roche), and 250 U/ml Recombinant RNasin Ribonuclease Inhibitor (Promega). Lysates were spun at 10,000g for 10 min and supernatants were further diluted with one volume of lysis buffer. To assess binding of AGO2 to the target mimic, 1.8 ml of each lysate was incubated with 50 μl of washed Dynabeads MyOne Streptavidin C1 (Thermo Fisher) pre-loaded with 300 pmol of wild-type or mutant RNA oligonucleotide (Supplementary Table 8) and pre-blocked with 1 mg/ml BSA, 0.5 mg/ml yeast tRNA, and 0.2 mg/ml heparin. To assess AGO2 phosphorylation after immunoprecipitation, 1.8 ml of each lysate was incubated with 50 μl of washed Dynabeads Protein G (Thermo Fisher) pre-incubated with 5 μl of anti-AGO2 antibody (SAB4200085, Sigma42) and pre-blocked as noted previously. Lysates were incubated with beads for 3 h at room temperature. Beads were washed four times in lysis buffer before 50 μl of 2× Laemmli sample buffer was added. Phos-tag electrophoresis was performed on captured protein complexes and on input protein samples subjected to chloroform–methanol precipitation41. The 293T cells were seeded in 24-well plates using 7.5 × 104 cells per well. Cells were transfected the following day using FuGENE HD and 301 ng of total plasmid. Each transfection consisted of 1 ng of phRL-SV40 (Promega), 20 ng of pGL3-Control or pGL3-BoxB, 150 ng of pcDNA3.1+ (expressing tethered or untethered proteins), and 130 ng of empty pcDNA3.1+. Cells were harvested 24 h later for luciferase activity assays using a Dual-Luciferase Reporter Assay System (Promega). Firefly luciferase activity was normalized to Renilla luciferase activity in each well to control for variation in transfection efficiency. Biological triplicates were performed for each transfection. ANKRD52–/– HCT116EGFP-miR-19 cells were seeded in six-well dishes at 6 × 105 cells per well. The following day, cells were treated with 10, 50, or 200 nM rapamycin for 72 h (fresh medium with rapamycin was exchanged at 48 h). Cells were harvested in 2× Laemmli sample buffer at the experimental endpoint. AGO2–/– cells were infected with MSCV retroviral constructs to stably express FH-AGO2WT or FH-AGO25XA. FH-AGO2-expressing cells were seeded using 1.5 × 107 cells per dish in 15-cm dishes with three dishes per cell line. Lysates were generated using methods similar to the co-immunoprecipitation assays, with the exception that 2 ml of lysis buffer was used per dish. Lysates were diluted with one volume of lysis buffer. FH-AGO2 was immunoprecipitated using 9 μg of anti-Flag antibody (F1804, Sigma) and 150 μl of washed Dynabeads. Samples were rotated at 4 °C overnight. Beads were washed three times with lysis buffer and then treated with lambda protein phosphatase (NEB) for 45 min. Beads were washed three times with lysis buffer and then resuspended in 100 μl reaction buffer composed of 25 mM Tris-HCl (pH 7.5), 10 mM MgCl , 2.5 mM DTT, 0.01% Triton X-100, 0.5 mg/ml BSA, 0.5 mM EGTA, 0.5 mM Na VO , 5 mM β-glycerophosphate, 170 ng of recombinant CSNK1A1 (PV3850, Thermo Fisher), and 200 μM [γ-32P]ATP (SA = 100–500 c.p.m./pmol). Reactions were incubated at 37 °C for 2 h. Beads were separated and mixed with 50 μl of 2× Laemmli sample buffer. SDS–PAGE was performed, and gels were stained using SimplyBlue SafeStain (Invitrogen). 32P signal was detected using a phosphor screen (GE Healthcare) and Typhoon FLA 7000 (GE Healthcare). In vitro CSNK1A1 kinase assays were performed using assay conditions adapted from the manufacturer’s recommendations (Recombinant CSNK1A1, PV3850, Thermo Fisher). All reactions were performed in a 50 μl volume for 90 min at 30 °C. Assay buffer was composed of 25 mM Tris-HCl (pH 7.5), 10 mM MgCl , 2.5 mM DTT, 0.01% Triton X-100, 0.5 mg/ml BSA, 0.5 mM EGTA, 0.5 mM Na VO , 5 mM β-glycerophosphate, 1 mM peptide (Supplementary Table 8), 170 ng of recombinant CSNK1A1, and 200 μM [γ-32P]ATP (SA = 100–500 c.p.m./pmol). Reactions were terminated using 75 mM H PO and spotted onto P81 phosphocellulose squares. Samples were washed four times in 75 mM H PO for 5 min per wash and immersed in acetone for 5 min before drying. 32P incorporation was assessed by Cerenkov counting. The linear form of ciRS-7 was constructed by amplifying the endogenous ciRS-7 locus from human genomic DNA (Roche) by PCR (Phusion Polymerase, Thermo Scientific) using primer sequences described previously36 (Supplementary Table 8). The PCR fragment was then cloned into the HindIII and NotI cloning sites of pcDNA3.1+ (Invitrogen). To generate the ciRS-7 construct capable of circularization, an ~800-bp region upstream of the splice acceptor was amplified using previously described primers36 (Supplementary Table 8) and inserted in the inverse orientation downstream of the linear ciRS-7 sequence at the XhoI cloning site of pcDNA3.1+. The effect of ciRS-7 expression on AGO2 phosphorylation was assessed through co-transfection experiments. Cells were seeded at a density of 9 × 105 cells per well in six-well dishes. Cells were transfected according to the manufacturer’s recommendations using Lipofectamine 2000 (Thermo Fisher). Where indicated, each well received 2 μg of plasmid and 10 nM miRNA mimics (miRIDIAN miRNA mimics, GE Dharmacon). Cells were harvested 28 h later for western blot analysis. Parental HCT116EGFP-miR-19, AGO2–/– HCT116EGFP-miR-19, ANKRD52–/– HCT116EGFP-miR-19, and ANKRD52–/–;CSNK1A1–/– HCT116EGFP-miR-19 cells were used for RNA-seq. Three independent clonal AGO2–/–, ANKRD52–/–, and ANKRD52–/–;CSNK1A1–/– knockout cell lines and three biological triplicates of parental cells were sequenced. Five hundred thousand cells were seeded per well in six-well dishes. Cells were harvested 48 h later, and RNA was extracted using a RNeasy Mini Kit (Qiagen) with an on-column DNase digestion. Sequencing libraries were generated using a TruSeq Stranded mRNA LT Sample Prep Kit (Illumina) and run on a NextSeq 500 using a NextSeq 500/550 High Output v2 Kit, 75 cycle (Illumina). AGO2–/– HCT116EGFP-miR-19 cells generated using PX330 were reconstituted with either empty pLJM1 vector (with EGFP previously resected), FH-AGO2-WT (AGO2WT), or FH-AGO2-5XA (AGO25XA). Biological triplicates for each cell line were seeded with 5.0 × 105 cells per well in six-well dishes. Cells were collected 48 h later, and RNA was extracted using a miRNeasy Mini Kit (Qiagen) with an on-column DNase digestion. Sequencing libraries were generated using a TruSeq Stranded Total RNA with Ribo-Zero Human/Mouse/Rat Low-throughput (LT) kit (Illumina) and run as performed in the previous RNA-seq experiment. Quality assessment of the RNA-seq data was done using the NGS-QC-Toolkit43 with default settings. Quality-filtered reads generated by the tool were then aligned to the human reference genome hg19 (for AGO2–/–, ANKRD52–/–, and ANKRD52–/–;CSNK1A1–/– RNA-seq experiments) or hg38 (for FH-AGO2 reconstitution experiments) using the TopHat2 (version 2.0.12) aligner44 using default settings. Read counts obtained from featureCounts45 were used as input for edgeR (version 3.8.6)46 for differential expression analysis. Genes with FDR ≤ 0.05 were regarded as differentially expressed for comparisons of each sample group. Cell culture, library preparation, and deep sequencing. AGO2–/– cells or AGO2–/– cells reconstituted with FH-AGO2WT or FH-AGO25XA via lentiviral expression (described above) were seeded in 15-cm dishes with five dishes per cell line at 1.0 × 107 cells per dish. Cells were cultured for 48 h and subsequently ultraviolet crosslinked at 400 mJ/cm2. Aliquots of 2.0 × 107 cells were then frozen at −80 °C. eCLIP was performed using the frozen samples as previously described37, using anti-Flag antibody for immunoprecipitations (F1804, Sigma). For each cell line, duplicate input and immunoprecipitation samples were prepared and sequenced. The RiL19 RNA adaptor (Supplementary Table 8) was used as the 3′ RNA linker for all samples. PAGE-purified DNA oligonucleotides were obtained from Sigma for the PCR library amplification step (Supplementary Table 8). PCR amplification was performed using between 11 and 15 cycles for all samples. Paired-end sequencing was performed on a NextSeq 500 using a NextSeq 500/550 High Output v2 Kit, 75 cycle (Illumina). Mapping deep sequencing reads. Adapters were trimmed from original reads using Cutadapt (version 1.9.1)47 with default settings. Next, the randomer sequence from the rand103Tr3 linker (Supplementary Table 8) was trimmed and recorded. TopHat2 (version 2.0.12)44 was used to align mate 2 to hg38. Only the uniquely mapped reads were retained. PCR duplicates were then removed using the randomer information with an in-house script. All reads remaining after PCR duplicate removal were regarded as usable reads and used for cluster calling. eCLIP cluster calling and annotation. eCLIP clusters were identified using a previously described method6 with the following modifications. Genome coverage by usable reads was determined at nucleotide resolution for each data set, and regions of continuous coverage greater than expected from a Poisson noise distribution were identified (P ≤ 0.001). For each region, read counts were obtained using Bedtools (version 2.17)48. If 50% of a read overlapped a region on the same strand, it was counted as a read covering that region. For each region, normalization to total usable reads was performed and a fold change between immunoprecipitation and input samples was calculated. Significant CLIP clusters in each data set were defined by (1) the presence of significantly greater coverage in the region than expected by chance on the basis of the Poisson distribution, and (2) log (fold change) of normalized reads in the cluster was ≥2 comparing immunoprecipitation to input. The final CLIP clusters for FH-AGO2WT and FH-AGO25XA were identified by first identifying significant clusters present in both experimental replicates. A region was considered to be present in both replicates if it occurred on the same strand and the replicate clusters overlapped by at least one-third of their total length. Significant clusters from both replicates were then merged to define the final cluster length. Lastly, all clusters identified in the AGO2–/– samples were subtracted to generate the final CLIP cluster calls (Supplementary Table 7). Clusters were annotated on the basis of their genomic locations (Ensembl GRCh38.85) if 55% of the cluster overlapped with a given genomic region. If a cluster was assigned to multiple annotations, the annotation was selected using the following priority: CDS exon > 3′ UTR > 5′ UTR > protein-coding gene intron > noncoding RNA exon > noncoding RNA intron > intergenic. Identification of active miRNA seed families and calculation of CLIP coverage at miRNA binding sites. Active miRNAs in HCT116 were identified using an approach similar to that described previously6 with the following modifications. The top 100 most highly expressed miRNAs in HCT116 cells were identified on the basis of a previously published small RNA sequencing experiment in this cell line49 and collapsed to 66 7-nucleotide seed families with identical sequence from nucleotides 2–8. Eight-nucleotide binding sites for these seeds, defined as in ref. 3, were identified in the 3′ UTRs of all expressed genes (FPKM > 0) using seqMap (version 1.0.12)50. The locations were then transformed to genomic coordinates and extended 10 nucleotides upstream and downstream to obtain a seed match region (excluding sites on exon–exon junctions). The numbers of crosslinking sites in these seed match regions for each miRNA seed family in FH-AGO2WT CLIP data were counted, normalized to the total usable reads in each replicate library, and averaged across replicates. To determine the significance cut-off, all possible 8-nucleotide sequences except for known miRNA seeds and those with four consecutive A, C, G, or T nucleotides were used to generate a null distribution. These background 8-nucleotide sequences were divided into 13 groups with 1,000 8-nucleotide sequences in the first 12 groups and 678 8-nucleotide sequences in the final group. CLIP crosslinking to each 8-nucleotide sequence in expressed 3′ UTRs was quantified as described above for actual miRNA seeds. An mRNA seed family was considered to be active in HCT116 cells if it obtained more crosslinking events than expected by chance, defined by the average number of crosslinking events from each of the 13 background 8-nucleotide groups above which P < 0.01. On the basis of this analysis, 15 active miRNA seed families were identified (representative miRNA: miR-423-5p, miR-17-5p, miR-200a-3p, miR-19a-3p, miR-23a-3p, miR-148a-3p, miR-221-3p, miR-125-5p, miR-182-5p, miR-21-5p, miR-30a-5p, miR-25-3p, let-7a-5p, miR-27a-3p, miR-24-3p). To quantify CLIP coverage of miRNA binding sites in FH-AGO2WT and FH-AGO25XA CLIP data (Fig. 6c), 8-, 7-, and 6-nucleotide binding sites, defined as in ref. 3, for all active miRNAs were identified within FH-AGO2WT CLIP clusters in 3′ UTRs using seqMap. Clusters with only a single type of binding site (8, 7, and 6 nucleotides) were identified. If an 8-nucleotide binding site was identified, this site was excluded from 7- or 6-nucleotide categories. Likewise, 7-nucleotide sites were excluded from the 6-nucleotide sites. Clusters were further filtered for those that were present in transcripts with FPKM > 0 in both FH-AGO2WT and FH-AGO25XA cell lines, yielding 228, 89, and 80 clusters containing 6, 7, or 8 nucleotides, respectively. For each cluster with a given type of binding site, CLIP coverage was calculated by determining the average number of CLIP reads in the cluster in each replicate normalized to the total number of reads in all clusters in each replicate, divided by FPKM of the transcript. The final reported CLIP coverage is the average of both replicates. To quantify CLIP coverage of miRNA binding sites in FH-AGO25XA-unique clusters versus FH-AGO2WT/FH-AGO25XA-common clusters (Extended Data Fig. 10e), 8-, 7-, and 6-nucleotide binding sites for all active miRNAs were identified within each class of CLIP cluster. Windows around each site were then extended 10 nucleotides upstream and downstream to obtain a seed match region. The numbers of crosslinking sites within these regions were counted and normalized to the total number of reads in clusters of each class (FH-AGO25XA-unique or FH-AGO2WT/FH-AGO25XA-common) to derive the CLIP coverage used to draw the CDF plots. CLIP coverage of FH-AGO25XA rescued versus non-rescued transcripts. Genes whose repression in AGO2–/– cells was rescued by FH-AGO25XA were defined by first identifying the genes that were significantly upregulated in AGO2–/– cells compared with parental HCT116 (FDR ≤ 0.05), then, among these genes, those that were significantly downregulated in FH-AGO25XA versus AGO2–/– (FDR ≤ 0.05). All other genes upregulated in AGO2–/– cells were considered not-rescued. The FH-AGO2WT CLIP coverage for each gene in these classes was calculated as the sum of all reads in CLIP clusters in a given 3′ UTR, normalized to total reads in all clusters, divided by the FPKM of the transcript. The final reported CLIP coverage (Extended Data Fig. 10d) is the average of both FH-AGO2WT replicates. mRNA half-life analysis. Half-lives of transcripts with FH-AGO25XA CLIP clusters in their 3′ UTRs were obtained from a previously published study38. Genes that had half-lives assigned to more than one RefSeq mRNA isoform were removed to avoid ambiguity. Genes in the top quartile of half-lives were defined as having a long half-life (n = 273) and genes in the bottom quartile of half-lives were defined as having a short half-life (n = 274). The total numbers of CLIP reads in clusters in a given 3′ UTR were obtained for each replicate, and edgeR (version 3.8.6)46 was used to calculate the normalized fold change of CLIP coverage comparing FH-AGO25XA with FH-AGO2WT (Extended Data Fig. 10f). All high-throughput sequencing data generated in the course of this study (CRISPR–Cas9 screens, RNA-seq, eCLIP) have been deposited in Gene Expression Omnibus under accession number GSE89946. All other data are available from the corresponding author upon reasonable request.
News Article | February 15, 2017
No statistical methods were used to predetermine sample size. Affinity-purified antibodies against total and Ser886 and Ser999 phospho-sites of EPRS were generated as described7, 31. Antibody against phospho-Ser was from Meridian Life Science. Antibodies specific for the C terminus of S6K1 and N terminus of S6K2 were purchased from Abcam and LifeSpan, respectively. Antibodies against PKA, DMPK, PKN, GAPDH, caveolin1, CD36/FAT, GLUT4, His-tag, β-actin and FATP1, FATP3, and FATP4 were from Santa Cruz. Antibody specific for FABP4 and FABP5 were from R&D and for FABPpm/GOT2 was from GeneTex. All other antibodies and rapamycin were from Cell Signaling. SignalSilence siRNAs targeting RSK1, AKT and S6K1 were from Cell Signaling, and those targeting raptor and rictor were from Santa Cruz. The 3′-UTR-specific duplex siRNAs, 5′-UGAUACGAAGAUCUUCUCAG-3′ and 5′-GCCUAAAUUAACAGUGGAA-3′, targeting mouse EPRS were from Origene. Smart pool siRNA targeting the coding sequence of mouse FATP1 (SLC27a1) was from Dharmacon and 3′-UTR-specific trilencer siRNA targeting human S6K1 was from Origene. Recombinant wild-type and Ser-to-Ala (S886A and S999A) mutant His-tagged linker proteins spanning Pro683 to Asn1023 of human EPRS were expressed and purified as described7, 8. Recombinant active S6K1 (ref. 32) and RSK1–3 were from Cell Signaling; Akt1 and Akt2 were from EMD Millipore. Mouse EPRS domains ERS (Met1 to Gln682), linker (Pro683 to Asn1023), and PRS (Leu1024 to Tyr1512) were cloned into pcDNA3 vector with an N terminus Flag tag using full-length mouse EPRS cDNA (Origene) as template. Flag-tagged mouse wild-type linker and linker with Ser999-to-Ala (S999A) and Ser999-to-Asp (S999D) mutations were generated as described33. Full-length human S6K1 cDNA in pCMV6-entry vector was purchased from Origene and recloned, deleting the 23-amino acid N terminus nuclear localization signal, and adding an in-frame upstream 6-His tag and a downstream Myc tag in pcDNA3. Specific Thr389-to-Ala (T389A) and Thr389-to-Glu (T389E) mutations were introduced using primers with the desired mutation and GENEART Site-Directed Mutagenesis System (Invitrogen). Human U937 monocytic cells (CRL 1593.2; ATCC authenticated by STR DNA profiling) were cultured in RPMI 1640 medium and 10% fetal bovine serum (FBS) with penicillin and streptomycin at 37 °C in 5% CO . Bone-marrow-derived macrophages (BMDM) were flushed from femur and tibia marrows of S6K1−/−S6K2−/−, and double-knockout S6K1−/−S6K2−/− mice (from G. Thomas and S. Kozma), and then cultured for one week in RPMI 1640 medium containing 10% FBS and 20% L929 cell-conditioned medium at 37 °C in 5% CO . 1 × 107 cells were treated with 500 U ml−1 IFNγ (R&D) for up to 24 h, as described previously34, 35. 3T3-L1 fibroblasts (CL-173; ATCC-certified) were cultured in high glucose containing Dulbecco’s modified Eagle’s medium (DMEM), 10% FBS and antibiotics/antimycotic at 37 °C in 10% CO to near 75% confluence. Confluent fibroblasts were induced to differentiate in medium containing DMEM and 10% FBS supplemented with 1× solutions of insulin:dexamethasone:3-isobutyl-1-methylxanthine (Cayman). After 72 h, the medium was replaced with 10% FBS and DMEM containing only insulin and maintained for a week with 3 changes in the same medium. Adipocytes were maintained in DMEM medium with 10% calf serum and antibiotics/antimycotic for at least 3 d before utilization. Differentiated adipocytes were serum-deprived for 4 h followed by treatment with 100 nM insulin (Sigma-Aldrich) for 4 h, or as indicated. Cell lysates were prepared using Phosphosafe Extraction buffer (Novagen) supplemented with protease inhibitors. As certified U937 monocytes and 3T3-L1 fibroblasts were directly procured from ATCC, they were not subjected to any further testing for contamination. Primary adipocytes from white adipose tissue (WAT) were prepared as described14, 36. Briefly, after mouse sacrifice, fat pads were removed and minced in Krebs-Ringer-bicarbonate-HEPES (KRBH) buffer (pH 7.4) containing 10 mM sodium bicarbonate, 30 mM HEPES, 200 nM adenosine, and 1% fatty acid-free bovine serum albumin (BSA, Sigma). WATs were digested with collagenase (2 mg g−1) in KRBH buffer at 37 °C for 1 h. Digested WATs were suspended in DMEM supplemented with 10% FBS, and filtered through 100-μm mesh cell strainer (BD Falcon) to remove undigested material. The cell suspension was incubated for 10 min at room temperature, and adipocytes collected from the floating layer after centrifugation. Adipocytes were incubated for 1 h at room temperature with gentle shaking and washed three times with DMEM. Differentiated human adipocytes in adipocyte maintenance medium were obtained from Cell Applications. Adipocytes were maintained in DMEM medium with 10% calf serum and antibiotics/antimycotic for 2 d before utilization, and 5 × 106 cells were serum-deprived for 4 h followed by treatment with 100 nM insulin for 4 h. Hepatocytes were isolated by collagenase perfusion of mouse livers and cells seeded for 4 h on collagen-coated 6-well plates (1 × 106 cells per well) in Williams’ medium E with 10% FBS, 25 mM HEPES, 100 nM insulin, and 100 nM triiodothyronine37, 38, 39. Cells were cultured for 48 h in serum-free Williams medium E with two medium changes. Before experiments, hepatocytes were pre-incubated overnight in serum-, insulin-, and triiodothyronine-free DMEM, and then with 100 nM insulin. Adult mouse cardiac cells were isolated by sequential plating using non-perfusion adult cardiomyocyte isolation kit (Cellutron)40. After isolation, 1 × 106 cardiac cells were incubated for 24 h in serum containing AS medium, and then with serum-free AW medium for another 24 h. Before experiments, cells were incubated for 4 h in serum-free DMEM, and then with 100 nM insulin. All studies using cultured cells were repeated at least three times. The number of replicates was estimated from comparable published studies that gave statistically significant results. U937 cells (1 × 107), PBMs and differentiated 3T3-L1 adipocytes (5 × 106 cells for both) were transfected with endotoxin-free plasmid DNAs or siRNAs (target-specific and scrambled control) using nucleofector (100 μl solution V for U937 cells and PBMs and 100 μl solution L for 3T3-L1 adipocytes) from Amaxa nucleofection kit (Lonza) following the manufacturer’s protocol. Transfected cells were immediately transferred to pre-warmed Opti-MEM media for 6 h and then to RPMI 1640 (for U937 cells and PBMs) and DMEM (for 3T3-L1 adipocytes) containing 10% FBS supplemented with penicillin, streptomycin, and geneticin (G418; 20 μg ml−1) for 18 to 24 h before treatment with insulin and inhibitors. Cell lysates or purified active kinases were pre-incubated with recombinant EPRS linker (wild-type and mutant) for 5 min in kinase assay buffer (50 mM Tris-HCl (pH 7.6), 1 mM dithiotheitol, 10 mM MgCl , 1 mM CaCl , and phosphatase inhibitor cocktail)7, 8, 33. Phosphorylation was initiated by addition of 5 μCi [γ-32P]ATP (Perkin-Elmer) for 15 min, and terminated using SDS gel-loading buffer and heat denaturation. Phosphorylated proteins were detected after resolution on Tris-glycine SDS–PAGE, fixation in 40% methanol and 10% acetic acid, and autoradiography. Immunoblot with anti-His tag antibody to detect EPRS linker served as control. To assay kinase activity using peptide substrates, 50 μM of synthetic peptides were phosphorylated with 1 μCi [γ-32P]ATP in kinase assay buffer. Equal volumes were spotted onto P81-phosphocellulose squares, washed in 0.5% H PO , and 32P incorporation determined by scintillation counting. U937 cell lysates were pre-cleared using protein A-sepharose, and target AGC kinase members and a non-member, MK2 were immunoprecipitated by incubation with specific antibodies for 4 h. The immunocomplex was captured by incubating with protein A-sepharose beads for 4 h, and washed three times with kinase assay buffer supplemented with 0.1% Triton X-100. The immunocomplex was resuspended in kinase assay buffer and used to phosphorylate EPRS linker as above, and 32P incorporation into peptide substrates was determined by scintillation counting41. Target peptides for S6K1, RSK1, MSK1, SGK494, NDR1, MRCKα, CRIK, RSKL1, ROCK1 and 2 (RRRLSSLRA), GRK2 (CKKLGEDQAEEISDDLLEDSLSDEDE), LATS1 (CKKRNRRLSVA), MAST1 (KKSRGDYMTMQIG), PRKX (RRRLSFAEPG), DMPK (KKSRGDYMTMQIG), and PDK1 (KTFCGTPEYLAPEVRREPRILSEEEQEMFRDFDYIADWC) were from SignalChem; for MK2 (KKLNRTLSVA) from Enzo Life Sciences; for PKA (RRKASGP), SGK1/AKT (RPRAATF), PKC/PKN (HPLSRTLSVAAKK), PKG, (RKISASEFDRPLR), and Cdk5 (PKTPKKAKKL) were from Santa Cruz. All mice were housed in microisolator cages (maximum 5 per cage of same-sex littermates) and maintained in climate/temperature- and photoperiod-controlled barrier rooms (22 ± 0.5 °C, 12–12 h dark–light cycle) with unrestricted access to water and standard rodent diet (Harlan Teklad 2918) deriving 24, 18 and 58 kcal% from protein, fat and carbohydrate, respectively. Mice were fed standard rodent diet unless otherwise indicated. The number of animals used in each experiment was estimated from examination of comparable published studies that gave statistically significant results. All mouse studies were performed in compliance with procedures approved by the Cleveland Clinic Lerner Research Institute Institutional Animal Care and Use Committee. Genetically-modified EPRS phospho-deficient S999A and phospho-mimetic S999D knock-in mice were generated (Xenogen Biosciences, Taconic). The RP23-86H18 BAC clone from mouse chromosome 1 containing full-length mouse Eprs gene was used to generate 5′ and 3′ homology arms, the knock-in region for the gene targeting vector, and Southern blot probes for screening targeted events. The homology arms and the knock-in region were generated by high-fidelity PCR, and cloned into the pCR4.0 vector. The S999A and S999D mutations (TCA to GCA or GAT, respectively) in exon 20 were introduced by PCR-based site-directed mutagenesis. The final vector also contained Frt sequences flanking the Neo expression cassette for positive embryonic stem cell selection, and a DTA expression cassette for negative selection. The targeting vector was electroporated into C57BL/6 embryonic stem cells and screened with G418. Positive expanded clones with confirmed mutation were selected. Neo was deleted by Flp electroporation, and blastocysts injected. Male chimaeras were bred with C57BL/6 wild-type females, and resulting F1 heterozygotes interbred to generate homozygotes in C57BL/6 background. Genotyping was done using forward primer 5′-CAGCATAAGAACAGTTGCCAAATAAAGG-3′ and reverse primer 5′-TTCTTGAACACACACATGCACAGACTC-3′. For all experiments the wild-type (EprsS/S), EprsA/A and EprsD/D were generated exclusively by breeding heterozygotes (EprsS/A and EprsS/D), and most experiments shown use male mice unless otherwise indicated. Mice were not randomized and studies were performed unblinded with respect to mouse genotype. S6K1−/− mice in C57BL/6 background were generated at the National Jewish Medical and Research Centre (Denver, Colorado) by blastocyst injection of embryonic stem cells with targeted disruption of the S6K1 gene as described previously19, 42. Briefly, neomycin (Neo) selection cassette was inserted to disrupt the exon corresponding to amino acids 207–237 in the catalytic domain of S6K1, thereby frame-shifting the downstream coding region. S6K1−/− mice exhibited phenotypes consistent with the previously reported mice that were generated by similar approach that is, replacing the catalytic domains of S6K1 with a Neo selection cassette9, 20. EprsD/DS6K1−/− and EprsS/SS6K1−/− were generated by EprsS/DS6K1−/− × EprsS/DS6K1−/− crosses. Mice wild-type for both Eprs and S6K1 genes (EprsS/SS6K1+/+) were generated from crosses of S6K1+/− heterozygotes. Male and female mice of EprsS/S and EprsA/A genotypes were recruited (n = 212 total mice) exclusively from crosses of heterozygotes (EprsS/A). All mice were housed in microisolator cages (maximum 5 per cage of same-sex littermates) with routine cage maintenance as above. Weaned mice (>21 days), born between June 2010 and December 2012 from 40 heterozygous parents, were monitored daily and weighed biweekly for the entire duration of their life. Mice that spontaneously developed conditions common in the C57BL/6 strain, such as malocclusion and hydrocephalus, were sacrificed and excluded from the study43. Assessments of deterioration in general health and quality of individual life were made in consultation with veterinary services of the Biological Resources Unit (BRU) of the Cleveland Clinic Lerner Research Institute. Severely sick and moribund mice that were judged to not survive another 48 h were euthanized with this date considered date of death, and included in the longevity analysis. Mice euthanized owing to imminent death include 11.5% (6 out of 52) male and 11.1% (6 out of 54) female of EprsS/S genotype, and 7.7% (4 out of 52) male and 9.3% (5 out of 54) female of EprsA/A genotype. Longevity was analysed by Kaplan–Meier survival curves from 212 mice (52 male and 54 female of each genotype, EprsS/S and EprsA/A) using known birth and death dates. Statistical differences were evaluated by log-rank Mantel–Cox and Gehan–Breslow–Wilcoxon tests using GraphPad Prism 5. Male and female mice of EprsS/S and EprsD/D genotypes were recruited (n = 89 total mice) exclusively from crosses of heterozygotes (EprsS/D). All weaned mice (>21 days born between February, 2011 and September, 2014 from 23 EprsS/D parents) were housed in microisolator cages (maximum 5 per cage of same-sex littermates) with routine cage maintenance and health monitoring as above. Mice killed owing to imminent death (as described above) include 8.7% (2 out of 23) male and 9.5% (2 out of 21) female of EprsS/S genotype, and 8.3% (2 out of 24) male and 4.8% (1 out of 21) female of EprsA/A genotype. Longevity was analysed by Kaplan–Meier survival curves from 89 mice (23, 21 male and 24, 21 male of genotype, EprsS/S and EprsA/A, respectively) using known birth and death dates and statistical analysis, as above. Male and female mice of S6K1+/+ and S6K1−/− genotypes were recruited (n = 112 total mice) exclusively from crosses of heterozygotes (S6K1+/−). All weaned mice (>21 days born between February 2011 and December 2013 from 23 S6K1+/− parents) were housed in microisolator cages (maximum 5 per cage of same-sex littermates) with routine cage maintenance and health monitoring as above. Mice killed owing to imminent death (as described above) include 13.8% (4 out of 29) male and 10.3% (3 out of 29) female of S6K1+/+ genotype, and 14.3% (4 out of 28) male and 14.3% (3 out of 21) female of S6K1−/− genotype. Longevity estimation was analysed by Kaplan–Meier survival curves from 112 mice (29, 29 male and 28, 26 female of genotype, S6K1+/+ and S6K1−/−, respectively) using known birth and death dates and statistical analysis as above. Univariate and multivariate CPH regression models were performed to analyse the effects of 4 variables; genotype, date of birth (DOB), gender, and parental identity (PID), on longevity of mice recruited for the study. The independent variables were fitted as categorical variables in the model. Genotype and gender were coded as binary variables. DOB and PID were coded as multiple categories. For CPH regression analysis of EprsS/S and EprsA/A mice (n = 212), the data were coded as follows: genotype, EprsS/S (1) and EprsA/A (0); gender, male (0) and female (1). On the basis of unique occurrences, DOB and PID were categorized into 79 (0–78, 0 being the DOB for oldest mice in the study) and 40 (1–40) categories, respectively. Oldest DOB category represents the reference for DOB. PID-1 was considered reference for PID variable. Models were fit using Cox proportional hazards regression in R package ‘survival’ using coxph function. Univariate model was built fitting each of the four variables individually and multivariate model was built fitting all four variables simultaneously. For CPH regression analysis of EprsS/S and EprsD/D mice (n = 89), the data were coded as follows: genotype, EprsS/S (1) and EprsD/D (0); gender, male (0) and female (1). On the basis of unique occurrences, DOB and PID were categorized into 38 (0–37, 0 being the DOB for oldest mice in the study) and 23 (1–23) categories, respectively. For CPH regression analysis of S6K1+/+ and S6K1−/− mice (n = 112), the data were coded as follows: genotype, S6K1+/+ (1) and S6K1−/− (0); gender, male (0) and female (1). On the basis of unique occurrences, DOB and PID were categorized into 36 (0–35, 0 being the DOB for oldest mice in the study) and 23 (1–23) categories, respectively. Scanning electron microscopy was performed by the Cleveland Clinic Imaging Core. WAT from 20-week-old male mice was fixed using 2.5% glutaraldehyde and 4% paraformaldehyde in phosphate-buffered saline (PBS) overnight at 4 °C. Tissues were washed three times in PBS followed by post-fixation with 1% osmium tetroxide in PBS for 1 h at 4 °C. Finally, the tissues were dehydrated through graded alcohol (50, 70, 90, and 100%), twice in ethanol:hexamethyldisilizane (HMDS; 1:1), and three times in 100% HMDS for 10 min each, and dried at room temperature. Samples were mounted on aluminium stubs and coated with palladium-gold using a sputter-coater, and viewed at X500 magnification with a Jeol JSM 5310 Electron Microscope (EOL). Adipose tissues from 20-week-old male mice were fixed in formalin, dehydrated in ethanol, embedded in paraffin, and cut at 5-μm thickness. Sections were deparaffinized, rehydrated, and stained with haematoxylin and eosin by the Cleveland Clinic Histology Core. Stained tissues were visualized with Leica DM2500 microscope, captured with Micropublisher 5.0 RTV digital camera (QImaging) using a 5X objective lens for magnification, and QCapture Pro 6.0 (QImaging) software for image acquisition. Adipocytes from 100 mg EWAT of 20-week male mice were isolated as described above and suspended in DMEM. Cells were counted in a haemocytometer. Basal lipolysis in primary adipocytes from EprsS/S, EprsA/A, and EprsD/D EWAT was measured by glycerol release using adipolysis assay kit (Cayman). Fatty acid oxidation in EWAT of 20-week-old male mice was performed as described13, 44. Explants were placed in an Erlenmeyer flask (Kimble-chase Kontes) containing the reaction mixture (DMEM with 0.1 μCi of [14C]oleic acid, 100 mM l-carnitine, and 0.2% fat-free BSA), and conditioned for 5 min in a 37 °C CO incubator. The flask was sealed with a rubber stopper containing a centre-well (Kimble-chase Kontes) fitted with a loosely folded filter paper moistened with 0.2 ml of 1 N NaOH, and incubated for 5 h at 37 °C. 14CO in the filter paper was trapped by addition of 200 μl of perchloric acid to the reaction mixture followed by incubation at 55 °C for 1 h. Radioactivity in the filter paper was determined by scintillation counting. At 16 weeks, mice were individually housed and given standard rodent diet and water ad libitum. Cumulative food intake was measured by weighing the mouse and food every second day for 30 consecutive days. Intraperitoneal glucose tolerance test (GTT) and insulin tolerance test (ITT) in EprsS/S, EprsA/A, and EprsD/D mice were determined as described22, 39. Briefly, GTT was done after an overnight (12 h) fast followed by peritoneal injection of glucose (2 mg g−1 body weight, Sigma). ITT was performed in 6-h fasted mice by injection of 0.75 U kg−1 body weight of insulin (Sigma). Blood glucose was determined using a commercial glucometer (Contour, Bayer). Serum triglycerides, free fatty acids, glucose, and insulin in 12-h fasted and in 1-h post-prandial (fed) mice were determined using commercially available kits. Serum triglycerides, free fatty acids, and glucose kits were from Wako. Insulin was determined using enzyme-linked immunoassay-based, ultra-sensitive mouse insulin kit (Crystal). Determination of serum β-hydroxybutyrate (for ketone body analysis) from 6-h fasted mice was done using colorimetric assay kit from Cayman. White blood cell counts in blood freshly collected by cardiac puncture in the presence of 10 mM EDTA were determined using Advia hematology system. Lipid content in mouse faeces was determined after extraction with chloroform:methanol (2:1)45, 46. GAIT system activity in insulin-treated adipocytes was determined by in vitro translation of capped poly(A)-tailed Luc-Cp GAIT and T7 gene 10 reporter RNAs as described35, 47. Gel-purified RNAs were incubated with lysates from U937 monocytes and differentiated 3T3-L1 adipocytes in the presence of rabbit reticulocyte lysate and [35S]methionine. Translation of the two transcripts was determined following resolution on 10% SDS–PAGE and autoradiography. Cytokine levels in mouse serum (100 μg protein) were determined using mouse cytokine antibody array C3 kit (RayBiotech). Mouse liver triglyceride content was determined by measurement of glycerol following saponification in ethanolic KOH (2:1, ethanol: 30% KOH)48. For assessment of total neutral lipid, freshly isolated liver slices were frozen in OCT, 5-μm sections stained with Oil Red O, and analysed by densitometry using NIH image J as described49. Mouse energy metabolism was determined by indirect calorimetry using the Oxymax CLAMS system (Columbus Instruments) in the Rodent Behavioural Core of the Cleveland Clinic Lerner Research Institute. Mice were housed individually in CLAMS cages and allowed to acclimate for 48 h with unrestricted excess to food and water. Thereafter, O consumption (VO ), CO release, RER and heat generation were recorded for 24 h spanning a single light–dark cycle. Adipocytes from 500 mg WAT from wild-type and EprsA/A mice were labelled with 150 μCi of 32P-orthophosphate (MP Biomedicals) in phosphate-free DMEM medium in absence or presence of insulin (100 nM) for 4 h. EPRS was immunoprecipitated with antibodies cross-linked to protein A-sepharose beads (Sigma) in 50 mM Tris-HCl (pH 7.6), 150 mM NaCl, 1% Triton X-100, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS, and protease/phosphatase inhibitor cocktail. Immunoprecipitated beads were washed with 50 mM Tris-HCl (pH 7.6), 150 mM NaCl, and 0.1% Triton X-100, and then in 50 mM Tris-HCl (pH 7.6) and 150 mM NaCl. 32P incorporation in immunoprecipitated proteins was determined by Tris-glycine SDS–PAGE, fixation and autoradiography. Adipocytes (0.25 × 106 cells) were pre-incubated in serum-free DMEM for 4 h. Subsequently, the medium was supplemented with 2.5 μCi [14C]Glu or [14C]Pro (Perkin-Elmer), and cells incubated for additional 6 h. Adipocytes were lysed and 14C incorporation determined by trichloroacetic acid-precipitation and scintillation counting. Mouse adipocytes (0.25 × 106 cells) were pre-incubated in methionine-free RPMI medium (Invitrogen) with 10% FBS for 30 min. [35S]Met/Cys (250 μCi, Perkin-Elmer) was added and incubated at 37 °C with 5% CO for 15 min. Labelled cells were lysed in RIPA buffer (Thermo Fisher) and analysed by Tris-glycine SDS–PAGE, fixation and autoradiography. Cell lysates or immunoprecipitates were denatured in Laemmli sample buffer (Bio-Rad) and resolved on Tris-glycine SDS–PAGE (10, 12, or 15% polyacrylamide) prepared using 37.5:1 acrylamide:bis-acrylamide stock solution (National Diagnostics). After transfer to polyvinyl difluoride membrane, the membranes were probed with target-specific antibody, followed by incubation with horseradish peroxidase conjugated secondary antibody and detection with Amersham ECL prime western blotting detection reagent (GE Healthcare). Immunoblots shown are typical of experiments independently done at least three times. Pre-cleared cell lysates (1 mg) were incubated with antibody cross-linked to protein A-sepharose beads in detergent-free buffer containing 50 mM Tris-HCl (pH 7.6), 150 mM NaCl, and EDTA-free protease/phosphatase inhibitor cocktail. Immunoprecipitates were analysed by Tris-glycine SDS–PAGE and immunoblotting either after washing the beads three times in the same buffer or after elution, followed by neutralization with 0.2 M glycine-HCl (pH 2.6) or 50 mM Tris-HCl (pH 8.5), respectively. Fatty acid uptake assay kit (QBT, Molecular Devices) that utilizes fluorescent bodipy-C , a LCFA analogue, was used to determine fatty acid uptake50. Differentiated 3T3-L1 adipocytes were plated at 5 × 104 cells per well in a 96-well plate. Adipocytes were first incubated in serum-free Hank’s balanced salt (HBS) solution for 4 h, and then with 100 nM insulin and bodipy-C for an additional 4 h. After 30 min, relative fluorescence was read at 485 nm excitation and 515 nm emission wavelength in bottom-read mode (SpectraMax GeminiEM, Molecular Devices). LCFA uptake was also determined in differentiated 3T3-L1 adipocytes as cellular accumulation of [14C]oleate (Perkin-Elmer). Adipocytes (10,000 cells) were seeded in a 24-well plate in DMEM with 10% calf serum overnight. Cells were serum-deprived for 4 h, treated with 100 nM insulin for 3.5 h, and then with 50 μM of [14C]oleate in HBS containing 0.1% fatty acid-free BSA for 30 min51, 52. Cells were washed extensively in cold HBS with 0.1% fatty acid-free BSA to remove unincorporated [14C]oleate, lysed in RIPA buffer (Thermo Fisher), and centrifuged at 2000 rpm for 5 min. Supernatant radioactivity was determined by scintillation counting and normalized to protein. LCFA uptake by mouse WAT, hepatocytes, cardiac cells, BMDM, and soleus muscle strips were measured using essentially the same method13. Adipocytes from wild-type and mutant mice were pre-incubated for 4 h in serum- and glucose-free DMEM and then rinsed with Krebs-Ringer buffer containing 20 mM HEPES (pH 7.4), 5 mM sodium phosphate, 1 mM MgSO , 1 mM CaCl , 136 mM NaCl, and 4.7 mM KCl53, 54. Adipocytes were incubated for 4 h in the presence of 1 μCi of [14C]2-deoxy-d-glucose (DG; Perkin-Elmer) and 100 nM insulin in the same buffer supplemented with 100 mM unlabelled 2-DG (Sigma). Uptake was stopped using ice-cold PBS containing 50 μM cytochalasin, followed by four washes with PBS. Lysate radioactivity was determined by scintillation counting. Membrane fraction from differentiated 3T3-L1 adipocytes was isolated by phase partitioning using Mem-PER Eukaryotic Membrane Protein Extraction Reagent Kit (Thermo-Scientific). Plasma membrane fractions from 3T3-L1 adipocytes were prepared as described14. Differentiated 3T3-L1 adipocytes were washed in buffer containing 250 mM sucrose, 10 mM Tris (pH 7.4), and 0.5 mM EDTA. Lysates were prepared by homogenization in the same buffer supplemented with protease and phosphatase inhibitor cocktail, and centrifuged at 16,000g for 20 min at 4 °C. The re-suspended pellet was layered onto a solution containing 1.12 M sucrose, 10 mM Tris (pH 7.4), and 0.5 mM EDTA, and centrifuged at 150,000g for 20 min at 4 °C. The resulting pellet was suspended in RIPA buffer (Sigma) and plasma membrane was obtained by centrifugation at 74,000g for 20 min at 4 °C. All data generated are included in the published article and in the supplementary information files. Additional statistical data sets generated are available from the corresponding author upon request.
News Article | February 22, 2017
No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. Animal experiments were neither randomized nor blinded. All animals used in this study (ADicerKO, Dicerlox/lox, or C57BL/6) were males and 6 months of age unless specifically indicated otherwise. All animal experiments were conducted in accordance with IRB protocols with respect to live vertebrate experimentation. Human serum was obtained from human subjects after obtaining IRB approval and patients were given informed consent. Mouse and human sera were centrifuged at 1,000g for 5 min and then at 10,000g for 10 min to remove whole cells, cell debris and aggregates. The serum was subjected to 0.1-μm filtration and ultracentrifuged at 100,000g for 1 h. Pelleted vesicles were suspended in 1× PBS, ultracentrifuged again at 100,000g for washing, resuspended in 1× PBS and prepared for electron microscopy and immune-electron microscopy or miRNA extraction. All in vitro experiments were carried out using exosome-free FBS. AML-12 cells were acquired from ATCC (cat no. CRL-2254) and were tested for mycoplasma contamination. Dicerfl/fl brown preadipocytes were generated as previously described16. For exosome loading, exosome preparations were isolated and diluted with PBS to final volume of 100 μl. Exosome electroporation was carried out by using a variation of a previously described technique45. Exosome preparations were mixed with 200 μl phosphate-buffered sucrose (272 mM sucrose 7 mM, K HPO ) with 10 nΜ of a miRNA mimic, and the mixture was pulsed at 500 mV with 250 μF capacitance using a Bio-Rad Gene Pulser (Bio-Rad). Electroporated exosomes were resuspended in a total volume of 500 μl PBS and added to the target cells. Isolated exosomes were subjected to immune-electron microscopy using standard techniques7. In brief, exosome suspensions were fixed with 2% glutaraldehyde supplemented with 0.15 M sodium cacodylate and post-fixed with 1% OsO . They were then dehydrated with ethanol and embedded in Epon 812. Samples were sectioned, post-stained with uranyl acetate and lead citrate, and examined with an electron microscope. For immune-electron microscopy, cells were fixed with a solution of 4% paraformaldehyde, 2% glutaraldehyde and 0.15 M sodium cacodylate and processed as above. Sections were probed with anti-CD63 (Santa Cruz Biotechnology, sc15363) or anti-CD9 (Abcam, ab92726) antibodies (or rabbit IgG as a control) and visualized with immunogold-labelled secondary antibodies. Immuno-electron microscopy analysis revealed that the isolated exosomes were 50–200 nM in diameter and stained positively for the tetraspanin exosome markers CD63 and CD9 (ref. 46). Exosomal concentration was assessed using the EXOCET ELISA assay (System Biosciences), which measured the esterase activity of cholesteryl ester transfer protein (CETP) activity. CETP is known to be enriched in exosomal membranes. The assay was calibrated using a known isolated exosome preparation (System Biosciences). Additionally, exosome preparations were subjected to the qNano system employing tunable resistive pulse sensing technology (IZON technologies) to measure the number and size distribution of exosomes. For total serum miRNA isolation, 100 μl of serum was obtained from ADicerKO mice or Lox littermates and miRNAs were isolated using an Exiqon miRCURY Biofluid RNA isolation kit following the manufacturer’s protocol. RNA was isolated from exosomal preparations using TRIzol, following the manufacturer’s protocol (Life Sciences). Subsequently, 50 ng of exosomal RNA was subjected to reverse transcription into cDNA by using a mouse miRNome profiler kit (System Biosciences). qPCR was then performed in 6-μl reaction volumes containing cDNA along with universal primers for each miRNA and SYBR Green PCR master mix (Bio-Rad). In line with previous research, for all serum and exosomal miRNA quantitative PCR reactions the C values were normalized using U6 snRNA as an internal control. To estimate miRNA abundance in fat tissue, data were normalized using the global average of expressed C values per sample47, as the snRNA U6 was differentially expressed between depots. For all quantitative PCR reactions involving gene expression calculations for FGF21, normalization was carried out by using the TATA-binding protein as an internal control. Differential expression analysis of the high-throughput −ΔC values was done using the Bioconductor limma package48 in R (www.r-project.org). Fold differences in comparisons were expressed as 2−ΔΔC . Ct Principal component analysis plots were created using R with the ggplot2 package. A detection threshold was set to C = 34 for all mouse miRNA PCR reactions; no threshold was used for human miRNA PCR, according to the manufacturer’s recommendation (System Biosciences). An miRNA was plotted only if its raw C value was ≤34 in at least three samples, except for the brown pre-adipocyte and 4-week-old mouse experiments, in which the raw C only had to be ≤34 twice. miRNA −ΔC values were Z scored and heatmaps were created by Cluster 3.0 and TreeView programs as previously described49. Fat tissue transplantation was carried out as previously described50. In brief, 10-week-old male Lox donor mice (C57BL/6 males) were killed, and their inguinal, epididymal, and BAT fat depots were isolated, cut into several 20-mg pieces and transplanted into 10-week-old male ADicerKO mice (n = 5 male mice per group). Each recipient ADicerKO mice received the equivalent transplanted fat mass of two donor Lox control mice. Transplanted mice received post-surgical analgesic intraperitoneal injections (buprenorphine, 50 mg/kg) for 7 days. At day 12, a glucose tolerance test was performed after a 16-h fast by intraperitoneal injection of 2 g/kg glucose. All mice were killed after 14 days. All procedures were conducted in accordance with Institutional Animal Care and Use Committee regulations. An adenoviral Fgf21 3′ UTR reporter was created by cloning the 3′ UTR of Fgf21 into the pMir-Report vector. Subsequently, the luciferase-tagged 3′ UTR fragment was cloned into the adenoviral vector pacAd5-CMV-IRES-GFP, creating an adenovirus bearing the Fgf21 3′UTR reporter. Hsa-miR-302f-3′-UTR was created by cloning the synthesized Luc-miR-302f-3′-UTR fragment (Genescript) into the Viral Power Adenoviral Expression System (Invitrogen). In vitro bioluminescence was measured using a dual luciferase kit (Promega). Eight-week-old male ADicerKO or wild-type mice were injected intravenously with adenovirus bearing the 3′-UTR of Fgf21 fused to the luciferase gene to create two groups of liver-reporter mice—one with a ADicerKO background and one with a wild-type background. One day later, a third group of ADicerKO mice, which had also been injected intravenously with an adenovirus bearing the 3′-UTR of Fgf21 fused to the luciferase gene, were injected intravenously with exosomes isolated from the serum of wild-type mice. After 24 h, in vivo luminescence of the Fgf21 3′ UTR was measured using the IVIS imaging system (Perkin Elmer) by administering d-luciferin (20 mg/kg) according to the manufacturer’s protocol (Perkin Elmer). For the second group, 8-week-old male ADicerKO or wild-type mice were also transfected with adenovirus bearing the 3′ UTR of Fgf21 fused to the luciferase gene by intravenous injection. After 1 day, mice received an intravenous injection of exosomes isolated from the serum of either ADicerKO mice or ADicerKO mice reconstituted in vitro with 10 nM miR-99b by electroporation. Twenty-four hours later, in vivo luminescence was measured using the IVIS imaging system by administering d-luciferin (20 mg/kg) according to the manufacturer’s protocol (Perkin Elmer). Protocol 1. On day 0, adenovirus bearing either pre-hsa_miR-302f or lacZ mRNA (as a control) was injected directly into the BAT of 8-week-old male C57BL/6 mice. Hsa_miR-302f is human-specific and does not have a mouse homologue. This procedure was conducted under ketamine-induced anaesthesia. Four days later, the same mice were injected intravenously with an adenovirus bearing the 3′ UTR of miR-302f in-frame with the luciferase gene, thereby transducing the liver tissue of the mouse with this human 3′ UTR miRNA reporter. Suppression of the 3′ UTR miR-302f reporter would occur only if there was communication between the BAT-produced miRNA and the liver. In vivo luminescence was measured on day 6 using the IVIS imaging system as described above. Protocol 2. To assess specifically the role of exosomal miR-302f in the regulation of its target reporter in the liver, two separate cohorts of 8-week-old male C57BL/6 mice were generated. One cohort was injected with adenovirus bearing pre-miR-302f or lacZ directly into the BAT (the donor cohort); the second cohort was transfected with an adenovirus bearing the 3′ UTR reporter of this miR-302f in the liver, as described for Protocol 1 (the acceptor cohort). Serum was obtained on days 3 and 6 from the donor cohorts; the exosomes were isolated and then injected intravenously into the acceptor mice the next day (days 4 and 7). On day 8, in vivo luminescence was measured in the acceptor mice using the IVIS imaging system as described above. To test for the presence of adenovirus in the liver and BAT of C57BL/6 mice, 100 mg tissue was homogenized in 1 ml sterile 1× PBS. The homogenate was spun down and 150 μl cleared supernatant was used to isolate adenoviral DNA using the Nucleospin RNA and DNA Virus kit, following the manufacturer’s protocol (Takara). PCR was performed on 2 μl isolated adenoviral DNA using SYBR green to detect lacZ or miR-302f amplicons. For all PCR data obtained in the fat-tissue-transplantation experiment, an miRNA was considered to be present only if its mean C in the wild-type group was <34. We then identified those miRNAs that were significantly decreased in ADicerKO serum. For an miRNA to be considered restored after transplantation by a particular depot it had to be significantly increased from ADicerKO serum with a mean C < 34 and its C had to be more than 50% of the way from ADicerKO to the wild type on the C scale. ANOVA tests were followed by two-tailed Dunn’s post-hoc analysis or Tukey’s multiple comparisons test to identify statistically significant comparisons. All t-tests and Mann–Whitney U-tests were two-tailed. P values less than 0.05 were considered significant. All ANOVA, t-tests, and area-under-the-curve calculations were carried out in GraphPad Prism 5.0. For miRDB analysis (http://www.mirdb.org), a search by target gene was performed against the mouse database. A target score of 85 was set to exclude potential false-positive interacting miRNAs. All high-throughput qRT–PCR data (raw C values), the code used to analyse them (in the free statistical software R), and its output (including supplementary tables, tables used to generate heatmaps, and statements in the text) can be freely downloaded and reproduced from https://github.com/jdreyf/fat-exosome-microrna. All other data are available from the corresponding author upon reasonable request.
News Article | February 24, 2017
“A case of mistaken identity” may drive the plot of the latest spy film or crime novel, but it’s only a tale of trouble for geneticists, oncologists, drug manufacturers and others working with mouse cell lines, one of the most commonly used laboratory model systems for genetic research. Cell lines that have been contaminated or misidentified due to poor laboratory technique and human error lead to inaccurate research studies, retracted publications and wasted resources. In fact, many scientific funding organizations, such as the National Institutes of Health, now require scientists to verify their cell lines for identity and quality before research grants are awarded. To help address this challenge, the National Institute of Standards and Technology (NIST) is working with partners to design tools, establish datasets, and further develop and standardize NIST’s system to authenticate mouse cell lines. One of the first milestones in this effort is the recently granted U.S. patent (No. 9,556,482(link is external)) for an authentication method using NIST-identified short tandem repeat (STR) markers─tiny repeating segments of DNA found between genes─for mouse cell lines. The method can be used to verify that a cell line is derived from a particular mouse in the same way forensic experts can confirm the identify of a person using DNA evidence. Once upcoming interlaboratory tests of the STR markers are completed, this will become the world’s first validated method for the authentication of mouse cell lines. The new NIST authentication method uses STR markers that are non-coding (that is, do not provide instructions for protein production the way genes do) DNA segments with a specific sequence of nucleotide bases─the four key components of DNA known as adenine, cytosine, guanine and thymine. Each STR is considered a separate marker for genetic matching because the number of times it is repeated is unique to an individual within a species. For example, a cell line may have one STR sequence─such as G-A-T-A─that repeats five times, another─say G-T-A-T─six times, a third seven times and so on. If another cell line has a high percentage of the same STR sequences in the same numbers, it is considered likely that they share a common ancestry. Misidentified human cell lines and the disruption they cause have been documented for decades. For example, two tainted cell lines were responsible for invalidating approximately $700 million of research studies and some 7,000 publications between the late-1950s and mid-1960s(link is external). The International Cell Line Authentication Committee(link is external), a volunteer group that monitors and raises awareness of authentication issues, currently lists nearly 500 misidentified human cell lines in its database. Fortunately, there are now standards and public databases that labs can use to confirm the identity of their human cell lines. In contrast, the extent of misidentification in mouse cell lines is unknown and there are currently no guidelines for authenticating them, said NIST microbiologist Jamie Almeida. “That is why NIST has been working on STR markers that are unique, easy to interpret and capable of distinguishing between different mouse cell lines,” Almeida said. “Additionally, we have partnered with the ATCC(link is external) [formerly the American Type Culture Collection], a global leader in biological materials management and standards, to further develop the STR technology for authentication and establish the Mouse Cell Line Authentication Consortium. The consortium is made up of organizations that have agreed to work with NIST and ATCC to test and validate the patented authentication method using the NIST-identified STR markers.” The consortium also will create a consensus standard to unify how authentication is performed across laboratories and will establish a public database that defines which STR profiles identify which mouse cell lines. “In the future, we hope to see the NIST-identified mouse STR markers and authentication method incorporated into a commercially available assay kit,” Almeida said. “The proposed kit, combined with a consensus standard and a cell line database, would provide researchers worldwide with the tools needed to ensure the identity of their mouse cell lines.” The new mouse cell line authentication method using the NIST-identified STR markers is available for licensing for research and non-exclusive commercial purposes through the agency’s Technology Partnerships Office.
News Article | February 23, 2017
A fluorescent microscope image of NIH 3T3 fibroblast cells, a commonly used mouse cell line. Microtubules within the cell appear green while the nuclei show as red. NIST and partners are developing tools, datasets and a standardized authentication method to ensure the identity of mouse cell lines used in research. Credit: Jan Schmoranzer, Leibniz-Institut für Molekulare Pharmakologie "A case of mistaken identity" may drive the plot of the latest spy film or crime novel, but it's only a tale of trouble for geneticists, oncologists, drug manufacturers and others working with mouse cell lines, one of the most commonly used laboratory model systems for genetic research. Cell lines that have been contaminated or misidentified due to poor laboratory technique and human error lead to inaccurate research studies, retracted publications and wasted resources. In fact, many scientific funding organizations, such as the National Institutes of Health, now require scientists to verify their cell lines for identity and quality before research grants are awarded. To help address this challenge, the National Institute of Standards and Technology (NIST) is working with partners to design tools, establish datasets, and further develop and standardize NIST's system to authenticate mouse cell lines. One of the first milestones in this effort is the recently granted U.S. patent (No. 9,556,482) for an authentication method using NIST-identified short tandem repeat (STR) markers—tiny repeating segments of DNA found between genes—for mouse cell lines. The method can be used to verify that a cell line is derived from a particular mouse in the same way forensic experts can confirm the identify of a person using DNA evidence. Once upcoming interlaboratory tests of the STR markers are completed, this will become the world's first validated method for the authentication of mouse cell lines. The new NIST authentication method uses STR markers that are non-coding (that is, do not provide instructions for protein production the way genes do) DNA segments with a specific sequence of nucleotide bases—the four key components of DNA known as adenine, cytosine, guanine and thymine. Each STR is considered a separate marker for genetic matching because the number of times it is repeated is unique to an individual within a species. For example, a cell line may have one STR sequence—such as G-A-T-A—that repeats five times, another—say G-T-A-T—six times, a third seven times and so on. If another cell line has a high percentage of the same STR sequences in the same numbers, it is considered likely that they share a common ancestry. Misidentified human cell lines and the disruption they cause have been documented for decades. For example, two tainted cell lines were responsible for invalidating approximately $700 million of research studies and some 7,000 publications between the late-1950s and mid-1960s . The International Cell Line Authentication Committee, a volunteer group that monitors and raises awareness of authentication issues, currently lists nearly 500 misidentified human cell lines in its database. Fortunately, there are now standards and public databases that labs can use to confirm the identity of their human cell lines. In contrast, the extent of misidentification in mouse cell lines is unknown and there are currently no guidelines for authenticating them, said NIST microbiologist Jamie Almeida. "That is why NIST has been working on STR markers that are unique, easy to interpret and capable of distinguishing between different mouse cell lines," Almeida said. "Additionally, we have partnered with the ATCC [formerly the American Type Culture Collection], a global leader in biological materials management and standards, to further develop the STR technology for authentication and establish the Mouse Cell Line Authentication Consortium. The consortium is made up of organizations that have agreed to work with NIST and ATCC to test and validate the patented authentication method using the NIST-identified STR markers." The consortium also will create a consensus standard to unify how authentication is performed across laboratories and will establish a public database that defines which STR profiles identify which mouse cell lines. "In the future, we hope to see the NIST-identified mouse STR markers and authentication method incorporated into a commercially available assay kit," Almeida said. "The proposed kit, combined with a consensus standard and a cell line database, would provide researchers worldwide with the tools needed to ensure the identity of their mouse cell lines." Explore further: A call for consensus standards to ensure the quality of cell lines
News Article | February 22, 2017
No statistical methods were used to predetermine sample size. Idelalisib (CAL-101, GS-1101; PI3Kδ inhibitor), duvelisib (IPI-145, INK1197; PI3Kγδ dual inhibitor), AS-604850 (PI3Kγ inhibitor) and ibrutinib (inhibitor of Bruton’s tyrosine kinase) were purchased from Selleckchem and all used at 1 μM concentration in most experiments. In some experiments, inhibitors were used at 0.1 μM or 0.5 μM concentrations, as indicated in the corresponding figure legend. Wild-type mice, c-myc25×I-SceI and c-myc25×I-SceIAicda−/− in the 129S2 mice background. All mice carrying the 25×I-SceI cassette were heterozygous for the modified c-myc allele containing the I-SceI cassette and were previously described9, 31. At least three independent mice of the same sex (females) and similar age (8–12 weeks) were used for each experiment with B cells. No mice were excluded from the analysis and no randomization or blinding method was used. Animal experiments were performed under protocols approved by the Institutional Animal Care and Use Committee (IACUC) of Boston Children’s Hospital (protocol 16-01-3093R) or by the Italian Ministry of Health for the University of Torino (approval no. 143/2013-B). They were housed and maintained in the specific-pathogen-free facility at Boston Children’s Hospital. Human leukaemia/lymphoma cell lines MEC1 (Chronic Lymphocytic Leukaemia), JeKo-1 and Mino (Mantle Cell Lymphoma), and GM06990 (EBV-immortalized lymphoblastoid B-cell line) were cultured in RPMI 1640 medium (Thermo Fisher Scientific) supplemented with 10% fetal bovine serum (FBS), penicillin-streptomycin (100 units per ml) and l-glutamine (2 mM). All cell lines tested negative for mycoplasma contamination. Cell lines were authenticated as they were purchased from ATCC (JeKo-1, Mino), DSMZ (MEC1) or the Coriell Institute (GM06990). For experiments with PI3K inhibitors, cells were plated in 6-well plates at a concentration of 5 × 105 cells per ml. Cells were collected at the indicated time points for RNA or protein isolation or flow cytometry analysis or after 4 days of treatment to isolate genomic DNA for HTGTS libraries. DNA before and after therapy from patients with CLL (untreated n = 8; idelalisib n = 10; ibrutinib n = 10; total 56 samples) was extracted from peripheral blood samples. Samples from idelalisib-treated patients were collected in the 99–224 CLL repository approved by the Dana-Farber Cancer Institute Institutional Review Board. Ibrutinib-treated patients were enrolled on a phase 2, open-label, single-centre, investigator-initiated study approved by the National Heart, Lung, and Blood Institutional Review Board at the National Institutes of Health (registered at http://www.clinicaltrials.gov, NCT01500733). All patients provided written informed consent. All cases were diagnosed according to the International guidelines and consented according to internal protocols. Details of treatment and sample collection for each patient are summarized in Supplementary Table 6. Splenic mouse B cells were isolated from mice by immunomagnetic depletion with anti-CD43 MicroBeads (Invitrogen) as previously described9. Briefly, all the non-B cells were depleted with anti-CD43 MicroBeads combined with Dynabeads Biotin Binder (Invitrogen); naive B cells were cultured at a concentration of 5 × 105 cells per ml in RPMI medium supplemented with 15% FBS, penicillin-streptomycin (100 units per ml), l-glutamine (2 mM), anti-CD40 (1 μg ml−1, eBioscience) and recombinant mouse IL-4 (20 ng ml−1; PeproTech). The purity of B-cell population was typically 96–98% in all experiments, as documented by flow cytometric analysis of B220 expression in enriched cells. Cells were collected after 4 days of treatment with inhibitors to isolate genomic DNA for HTGTS libraries and targeted re-sequencing experiments. For RNA and protein extraction, cells were collected at the indicated time points. Class switch recombination (CSR) was measured by staining with PE-labelled anti-mouse IgG (BD Biosciences) and Cy5-PE-labelled anti-mouse B220 (eBiosciences). Data acquisition was performed using a FACSVerse flow cytometer (BD biosciences). For immunization, sheep blood in Alsever’s solution (BD) were washed with PBS and re-suspended in PBS at a concentration of 1 × 109 sheep red blood cells per ml. 8–12-week-old mice were immunized by intraperitoneal injection of 2 × 108 sheep red blood cells in a 200 ml volume. After 5 days, a booster injection was performed using fivefold more sheep red blood cells. On day 6 and for 7 consecutive days, animals were daily administered vehicle (0.5% carboxymethylcellulose, 0.05% Tween 80 in ultra-pure water) or idelalisib or duvelisib (10 mg per kg per day) by oral gavage. Spleens were collected at the end of treatment, placed on ice, washed in PBS to remove residual blood, cut into small pieces, crushed and physically dissociated using a Falcon cell strainer, and subjected to hypotonic lysis of erythrocytes. Mouse germinal centre B cells were isolated from the spleens of immunized mice by immunomagnetic depletion: first non-B-cells were depleted with anti-CD43 MicroBeads; next enriched B cells were incubated with a cocktail of biotinylated antibodies specific for CD11c (eBiosciences) and IgD (eBiosciences) to remove dendritic cells and mature naive B cells, respectively, as previously reported32. Enrichment of the germinal B cells was evaluated with PE-labelled anti-mouse GL7 (eBiosciences) and Cy5-PE-labelled anti-mouse B220 (eBiosciences). 8-week-old female BALB/cAnNCrl mice were purchased from Charles River and housed in the University of Torino mouse facility under a protocol approved by the Italian Ministry of Health. Commercial pristane (2,6,10,14-tetramethylpentadecane) was purchased from Sigma. Pristane was administered by two 0.5 ml i.p. injections given 70 days apart, as previously described22. The mice were divided into four different groups: vehicle group (0.5% carboxymethylcellulose, 0.05% Tween 80 in ultra-pure water) and idelalisib or duvelisib or ibrutinib groups. Drugs were administered by oral gavage (10 mg per kg per day) for 70 days (5 days a week). Mice underwent follow-up assessment for the development of ascites and were killed when they reached a point of distress. Several tissues, including peritoneal tumour nodules, inflammatory granuloma, liver, spleen, intestine, were processed for histologic analysis. For histology, tissues and tumour nodules were fixed in 10% formalin over-night and transferred to 70% ethanol and embedded in paraffin. 4-μm-thick sections were stained with haematoxylin and eosin to evaluate the distribution of clusters of atypical plasma cells. Plasma cell tumours were diagnosed by finding clusters of 10 or more hyperchromatic, atypical plasma cells in hystology specimens, as previously reported22. PCR for Igh–c-myc translocations was performed on 500 ng of genomic DNA extracted from ascites by adapting protocols previously described33, 34. Briefly, we performed two rounds of PCR with Phusion High-Fidelity DNA Polymerase (Thermo Fisher Scientific) using primers listed in Supplementary Table 7. All PCR reactions were performed with appropriate positive controls (genomic DNA obtained from mouse B cells activated in vitro and treated with PI3Kδ inhibitors) and negative controls (DNA from Aicda−/− mouse B cells). PCR conditions were 98 °C for 30 s followed by 25 cycles (98 °C, 10 s; 62 °C, 30 s; 72 °C, 4 min) for both the first and second round. PCR amplicons were purified and sequenced to confirm Igh–c-myc translocations. Whole-cell extracts were obtained from purified mouse B cells or cell lines treated with 1 μM PI3K inhibitors using GST-FISH buffer (10 mM MgCl , 150 mM NaCl, 1% NP-40, 2% Glycerol, 1 mM EDTA, 25 mM HEPES (pH 7.5)) supplemented with protease inhibitors (Roche), 1 mM phenylmethanesulfonylfluoride (PMSF), 10 mM NaF and 1 mM Na VO . Extracts were cleared by centrifugation at 12,000 r.p.m. for 15 min. The supernatants were collected and assayed for protein concentration using the Bio-Rad protein assay method. 20 μg of proteins were loaded on 12% Mini-PROTEIN TGX gels (BIO-RAD), transferred on nitrocellulose membrane (GE Healthcare), blocked with 5% skimmed milk (BIO-RAD). Primary antibodies for immunoblotting included: rat monoclonal anti-mouse-AID (mAID-2 clone, eBioScience, catalogue no. 14-5959-82), mouse monoclonal anti-human-AID (ZA001, Life Technologies, catalogue no. 39-2500), rabbit monoclonal anti-PI3K π110δ (Ψ387, Abcam, catalogue no. 32401), rabbit polyclonal anti-β−actin (Sigma, catalogue no. A2066), rabbit monoclonal anti-phospho-AKT (S473) (D9E, Cell Signaling Technology, catalogue no. 4060), rabbit monoclonal anti-AKT (pan) (C67E7, Cell Signaling Technology, catalogue no. 4691). Membranes were developed with ECL solution (GE Healthcare). AID protein abundance was measured by ImageJ software and normalized for the β-actin intensity of the corresponding lane. Total RNA was isolated from primary mouse B cells and human lymphoma cells by TRIzol (Life Technologies). Before cDNA synthesis, 1 μg of total RNA was treated with 5 U μl−1 RNase-free recombinant DNase I (Roche). cDNA was transcribed using iScript cDNA synthesis kit following the manufacturer’s instructions (Biorad). All quantitative RT–PCR experiments were performed in triplicate on ICycler iQ Real-Time PCR Detection System (Bio-Rad Laboratories) with SYBR green dye. Primer pairs are listed in Supplementary Table 7. Expression levels for individual transcripts were normalized against β-actin for murine samples or HuPO for human samples. Fold change in transcript levels were calculated as fold change over untreated cells. Retroviral supernatants were prepared from Phoenix packaging cells transfected with retroviral vectors. The pMX-I-SceI vector has been previously described9, PI3Kδ retroviruses (wild-type PI3K p110δ (denoted as p110δWT) and PI3K p110δ(E1021K)) were provided by K. Okkenhaug and F. Garcon (The Babraham Institute, UK)13. Briefly, Phoenix-ECO cells, a second-generation retrovirus-producer cell line, were maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% FBS, penicillin-streptomycin (100 units per ml) and l-glutamine (2 mM). To generate retroviral particle, 3.5 × 106 Phoenix-ECO cells were plated per 10-cm dish. The following day, cells were transfected by calcium phosphate transfection method with 10 μg of each plasmid and 5 μg of pCL-Eco retrovirus packaging plasmid. The media was changed 8 h after transfection. The viral supernatant was collected 48 h after transfection, passed through a 0.45 μm filter, pooled and used either fresh or snap-frozen. For transduction, one volume of viral supernatant with polybrene (6 μg ml−1) was added to mouse B cells after 24 h of activation with anti-CD40 plus IL-4, as previously described9. Plates were spun for 1.5 h at 2,400 r.p.m. and incubated overnight. Cells were washed and plated at a concentration of 5 × 105 cells per ml. On day 4 of stimulation, transduction efficiency was evaluated by measuring the percentage of transduced cells by enhanced green fluorescence protein expression (typical range was 50% to 85% of transduced cells). PI3K inhibitors were added at time of transduction and then maintained for the whole duration of the activation. CSR was evaluated by staining with Cy5-PE-labelled anti-mouse B220 (eBiosciences) and PE-labelled anti-mouse IgG (BD Biosciences). Data acquisition was performed using a FACSVerse flow cytometer (BD biosciences). CSR ranged between 15% and 40% for retrovirus-transduced B cells. DNA was isolated from cells at day 4 of culture according to standard methods for HTGTS libraries. For SpCas9 expression and generation of single guide RNA (sgRNA), the 20-nt target sequences were selected to precede a 5′-NGG protospacer-adjacent motif (PAM) sequence. The two c-MYC-targeting sgRNAs (1 and 2) and the AICDA sgRNA were designed with the CRISPR design tool from F. Zhang laboratory (http://crispr.mit.edu/). Oligonucleotides were purchased from Integrated DNA technology (IDT), annealed and cloned into the BsmbI-BsmBI sites downstream from the human U6 promoter in LentiCRISPR v2 plasmid (Addgene, 52961). Oligonucleotides used in this study for cloning are listed in Supplementary Table 7. HEK293FT cells (Invitrogen) were maintained in 10% FBS-containing DMEM. To generate lentiviral particles, 5.5 × 106 HEK293FT cells were plated per 10 cm dish. The following day, cells were transfected by calcium phosphate transfection method with 7.2 μg of lentiCRISPR v2 plasmid, 3.6 μg of VSVG, 3.6 μg of RSV-REV, and 3.6 μg of PMDLg/pPRE. The media was changed 8 h after transfection. The viral supernatant was collected 36 h after transfection, passed through a 0.45 μm filter, pooled and used either fresh or snap-frozen. For transduction of JeKo-1 and MEC1 with c-MYC CRISPR/Cas9 lentiviruses, a total number of 4 × 105 human neoplastic cells were plated into 6-well plates, at a concentration of 2 × 105 cells per ml. Lentiviral transduction was performed adding lentiviral supernatant, spinning for 1.5 h at 2,400 r.p.m. in the presence of polybrene (6 μg ml−1). The viral supernatant was exchanged for fresh medium 8 h later. PI3K inhibitors were added 8 h before the infection and after washing. After 48 h, cells were selected with 0.2 μg ml−1 of puromycin to enrich for transduced cells. The cells were collected after 3 days from the puromycin addition. Genomic DNA was extracted as previously described for HTGTS libraries. To generate the AID-knockout MEC-1 cell line, MEC-1 cells were transduced with AID CRISPR/Cas9 lentivirus according to the protocol described above. After 48 h from transduction cells were selected with 0.2 μg ml−1 of puromycin for 3 days. The selected cells were seeded as single colonies in 96-well plates by serial dilutions. After 3–4 weeks of culture, cells derived from each colony were used to assess AID-knockout by western blotting and genomic sequencing of the sgRNA target region. The genomic region flanking the CRISPR target sites was PCR amplified (Surveyor primers are listed in Supplementary Table 7), and products were purified using PCR purification kit (QIAGEN) following the manufacturer’s protocol. 400 ng total of the purified PCR products were mixed with 2 μl 10× Taq DNA Polymerase PCR buffer (Life Technologies) and ultra-pure water to a final volume of 20 μl, and subjected to a re-annealing process to enable heteroduplex formation: 95 °C for 10 min, 95 °C to 85 °C ramping at –2 °C per s, 85 °C to 25 °C at –0.25 °C per s, and 25 °C hold for 1 min. After re-annealing, products were treated with Surveyor nuclease and Surveyor enhancer S (Transgenomics) following the manufacturer’s recommended protocol, and analysed on 2% high-resolution agarose gel (Sigma Aldrich). Gels were stained with ethidium bromide (Sigma Aldrich) and imaged with a Gel Doc gel imaging system (Bio-rad). Quantification was based on relative band intensities. Indel percentage was determined by the formula, 100 × (1 – (1 – (b + c) / (a + b + c)) 1 / 2), where a is the integrated intensity of the undigested PCR product, and b and c are the integrated intensities of each cleavage products. DNA was prepared from mouse and human B cells at day 4 of culture using rapid lysis buffer containing 10 μg ml−1 Proteinase K and incubation at 56 °C overnight, followed by standard isopropanol extraction, wash in ethanol 70% and resuspension in TE buffer. HTGTS libraries were generated by emulsion-mediated PCR (EM–PCR) methods as previously described9. In brief, genomic DNA was digested overnight with HaeIII frequent cutter enzyme. HaeIII-generated blunt ends were A-tailed with Klenow polymerase (3′–5′ exo-; New England Biolabs). An asymmetric adaptor (composed of an upper linker and a lower 3′-modified linker) was then ligated to fragmented DNA. To remove the unrearranged I-SceI cassettes or the unrearranged endogenous c-myc locus, ligation reactions were digested with both EcoRV and XbaI. In the first round of PCR, DNA was amplified using a biotinylated forward primer and an adaptor-specific reverse primer and Phusion polymerase (Thermo-Scientific). 20 PCR cycles were performed in the following conditions: 98 °C for 10 s, 58 °C for 30 s, and 72 °C for 30 s. Multiple reactions were performed in generating large-scale libraries. Biotinylated PCR products were isolated using the Dynabeads MyOne Streptavidin C1 kit (Invitrogen), followed by an additional 2-h-digestion with blocking enzymes was performed. PCR products were eluted from the beads by 30 min incubation at 65 °C in 95% formamide/10 mM EDTA and purified. The purified products were then amplified in a second round with em-PCR in an oil-surfactant mixture. The emulsion mixture was divided into individual aliquots and PCR was performed using the following conditions: 20 cycles of 94 °C for 30 s, 60 °C for 30 s, and 72 °C for 1 min. Following PCR, the products were pooled and centrifuged in a table-top centrifuge for 5 min at 14,000 r.p.m. to separate the phases and the oil layer was removed. The sample was then extracted three times with diethyl ether and DNA was re-purified. The third, non-emulsion, round of PCR (10 cycles) was performed with the same primers as in round 2, but with the addition of linkers and barcodes for Illumina Mi-seq sequencing. PCR products were size-fractionated for DNA fragments between 300 and 800 base pairs on a 1% agarose gel, column purified (QIAGEN) before loading onto Illumina Mi-seq machine for sequencing. Nucleotide sequences of junctions were generated by Mi-seq (Illumina NS500 SE150) sequencing at the Molecular Biology Core Facilities of the Dana-Farber Cancer Institute. At least three independent libraries were generated and analysed for each experimental condition (Supplementary Table 1). Oligonucleotide primers used for mouse and human libraries preparation are listed in Supplementary Table 7. First, we applied prinseq 0.2 (ref. 35) to remove sequences with exact PCR duplicates, mean quality score <20 and length <50. Next, reads for each experimental condition were demultiplexed by designed barcode, and then filtered by the presence of the primer plus additional 5 downstream bases as bait portion. Barcodes and primers used are listed in Supplementary Tables 1, 7. Lastly, the barcode, primer and bait portion of the remained sequences were masked for alignment analysis. The sequences for each experiment were aligned and filtered as previously described9. Briefly, we aligned sequences to the mouse reference genome (GRCm37/mm9) or human genome (GRCh38/hg38) using BLAT, and then filtered artificial junctions by removing PCR repeats (reads with same junction position in alignment to the reference genome and a start position in the read less than 3 bp apart), invalid alignments (including alignment scores <30, reads with multiple alignments having a score difference <4 and alignments having 10-nucleotide gaps) and ligation artefacts (for example, random HaeIII restriction sites ligated to bait breaksite). Translocation junction position was determined on the basis of the genomic position of the 5′ end of the aligned read. Translocation junctions data from similar size biological replicates were pooled for hotspots identification. First, we employed SICER 1.1 (ref. 36) to identify candidate regions where HTGTS junctions were significantly enriched against genome-wide background. The parameters used were as follows: window size, 1,000; gap size, 2,000; e-value, 0.000001; redundancy, 1; effective genome fraction, 0.77 for mouse or 0.74 for human. Next, we eliminated from analysis the following hotspots: (1) hotspots in the region ± 4 Mb around Myc bait breaksite including the Pvt1 gene as previously described9; (2) hotspots with junctions number less than 5; (3) hotspots with strand bias. We used the following entropy formula to measure strand bias as S = –P × log (P) – (1 – P) × log (1 – P), where P is the percentage of junctions from the plus stand, and 1 – P is the percentage of junctions from the minus strand. If P or 1 – P were <10% (entropy S < 0.47), we eliminated the hotspot for a strand bias; (4) hotspots without significant enrichment against the local background. The local background P value was calculated by Poisson distribution against the region that surrounds the hotspot (± 3 times the size of the hotspot). Bonferroni correction was used to adjust P value for multiple tests. We set adjusted P = 0.01 as significance level. For JeKo-1, owing to its complex karyotype37, which increases the local noise level, we set more stringent criteria for hotspot identification, including adjust P < 0.00001 and region size <30 kb. Hotspots from different experiments that partially overlapped were merged to define common hotspot regions that were used as reference to compare junction frequency between different experiments. Translocation junction frequencies in hotspots were normalized to reads per million (RPM). In box plot for fold-change comparison, to avoid ‘division by zero’ error, 0 was replaced with 1, and then normalized to corresponding RPM in library. For clustering heat map, the RPM was transformed into a log value, and then median centred. The genome-wide translocation circle plots were made using Circos tool38. Translocation junction distributions were visualized by IGV 2.3.6 (ref. 39). For translocation frequency distribution around ConvT or SE centres, centres were defined as the central bp position of the ConvT or SE region, as we previously defined10. Regions ± 4 Mb around the I-SceI c-myc breaksite on chromosome 15 and the IgH S regions on chromosome 12 were excluded in the analysis of junctions around TSS, ConvT or SE centres. For SE analysis, hotspots embedded within two adjacent SEs with centre-to-centre distance <100 kb were excluded because it was not possible to univocally assign them with one of the two SEs. All ChIP–seq data used in this study were obtained from previously published data including SE10, AID17, Spt5 and Pol II20. Statistical significance of differential junction frequency in hotspots were performed using SICER 1.1 (ref. 36) with the following parameters: window size, 1,000; gap size, 2,000; e-value, 0.000001; effective genome fraction, 0.77 (mouse) or 0.74 (human); and FDR = 0.01 or FDR = 0.1. Nuclei were isolated at day 2 from B cells activated with anti-CD40 plus IL-4 and treated with PI3K inhibitors, as previously described9. GRO-seq libraries were sequenced on the Hi-seq 2,000 platform with single-end reads and analysed as follows: GRO-seq data were aligned using Bowtie software40 mouse reference genome (GRCm37/mm9). Uniquely mapped, non-redundant sequence reads were retained. Next, we used HOMER software to count reads and calculate the nascent RNA expression levels as RPKM (reads per 1,000 bp per million mapped reads) in whole genes or in focal translocation clusters, and to identify transcripts from both strands of chromosomes41. The ConvT region was defined as sense and antisense transcription overlaps that were longer than 100 bp10. Statistical analysis for differential expression and log fold-change calculation were performed using DESeq2 (ref. 42) in whole genes or in focal translocation clusters. The MA-plot of log fold-changes against mean of normalized counts were generated by function plotMA in R package DESeq2 (ref. 42). Phusion High Fidelity DNA polymerase (Thermo-Scientific) was used to amplify selected regions from template genomic DNA. Oligonucleotide primers are listed in Supplementary Table 7: amplification conditions for each gene are available on request. Amplification products were purified using PCR purification kit (QIAGEN) and GEL extraction kit (QIAGEN) following the manufacturer’s protocol and sequenced bi-directionally in a Mi-seq (Illumina NS500) sequencing platform at the Molecular Biology Core Facilities of the Dana-Farber Cancer Institute. For SHM calculations, mouse and human intragenic and intergenic regions were targeted re-sequenced with primers indicated in Supplementary Table 7. Sequences with mean quality score <20 and length <50 were removed. Samples with less than 100 reads were excluded from analysis. The remained sequences were used to calculate mutation rate. Sequences obtained from each designed region were aligned to the reference sequence using BLASTN with alignment length >200. Mutations were calculated after filtering steps, as previously described43. Briefly, mutations first had to pass a Neighbourhood Quality Standard criteria requiring a minimum Phred score of 30 for the mutation itself, and 20 for the five adjacent bases on either side. Mutations that were within five bases of more than two additional mutations were excluded. Mutations within two bases of a deletion or insertion were also excluded. In addition, bases with mutation rate >0.01 were excluded as a result of overwhelming influence of sequence error or SNP, of which bases with mutation rate >0.2 were further regarded as SNP and were excluded. Finally, the average base mutation rate of 1– 200 bp passing the above criteria were calculated from forward sequence, as well as reverse sequences if applicable. For average base mutation rates of C-to-T or G-to-A transitions, only C or G bp sites we counted. Mutations on the VB1-8 productive allele were performed and analysed as recently described19. Source code for genomic event analysis tools (GEAT) developed in our laboratory to perform the analysis is available at https://github.com/geatools/geat. All sequencing data has been deposited in the Gene Expression Omnibus database under accession number GSE77788. Source Data for figures are provided with the online version of the paper.
News Article | March 1, 2017
The following antibodies and reagents were from BD Biosciences or eBiosciences: monoclonal antibodies (mAb) to CD11b-pacific-blue (M1/70), CD11c-APC, F4/80-FITC, CD3-pacific-blue, CD4-FITC, CD40-PE, CD80-PE, CD86-PE, CD40L-PE, CD69-PE, C5aR1-PE, and their corresponding isotypes antibodies (rat IgG2b pacific blue, Armenian hamster IgG-APC, rat IgG2a-PE, rat IgG2b PE), Fc blocking antibodies, and Cytofix/Cytopermkit. Anti-phospho-LAT (Tyr191), and anti-LAT clone 11B.12 were from Upstate cell signaling solutions. Rabbit GCS-specific antibody was from Abbiotec LLC. Rabbit affinity-purified GC-specific antibody was from Glycobiotech GmbH. The C5aR antagonist A8(Δ71−73) (C5aRA) was generated as described14. ELISA kits for the detection of human and mouse C5a and cytokines (IFNγ, TNF, IL-1β, IL-6, IL-12p40, IL-12p70, IL-17A/F, IL-23 and CCL18) were from R&D System or eBiosciences. Proteome Profiler A was from R&D System, anti-Profiler A, Bio-Rad Molecular Imager Gel Doc. Liberase Cl was from Roche. DNase (DNase), Diethanolamine (DEA), p-Nitrophenylphosphate (PNPP), MgCl , goat anti-mouse IgG2a, DNase-I kit, and anti-β actin antibody were from Sigma. Alkaline phosphatase-conjugated antibodies to mouse (IgG1, IgG2a/c, IgG2b, and IgG3), human IgG isotypes (IgG1, IgG2, IgG3, and IgG4), and rabbit IgG were from Southern Biotech. Tween 20, Nunc plates, Aminolink Plus Coupling Resin, and BCA protein assay reagents were from Thermo Scientific, RIPA buffer containing sodium orthovanadate and protease inhibitors were from Roche Diagnostics. GM-CSF and M-CSF were from Peprotech. Conduritol B epoxide (CBE) was from Calbiochem. Anti-CD11c, anti-CD11b and anti-CD4 microbeads were from Miltenyi Biotec. Horseradish peroxidase (HRP)-conjugated anti-rabbit and anti-mouse IgG and biotinylated protein ladder detection pack were from Cell Signaling Technology Inc. GC and C12-GC standards were from Matreya, LLC and Avanti Polar lipids, Inc. The 4–12% BisTris gel, sample loading, reducing, running buffer, standard protein molecular weight marker, iBlot 2 dry blotting system, iBind western system, and enzyme-linked chemiluminescence (ECL) chemiluminescent substrate reagent kit, RPMI, DMEM, BSA, FBS, penicillin, streptomycin, HEPES, sodium pyruvate, Trizol, Gel apparatus, Xcell SureLock, and TRIzol reagent were from Invitrogen, Life Technology. RNeasy plus mini kit was from Qiagen. The U937 (ATCC CRL-1593.2TM) cell line, dimethylsulfoxide, and growth medium were from American Type Culture Collection. The U937 cell line has been thoroughly tested and authenticated by the supplier through DNA profiling. It has not been tested for mycoplasma contamination. High capacity RNA-cDNA kit, Taqman universal mastermixII, human and mouse pre-developed primer/probe sets for UGCG/Ugcg and Hypoxanthin phosphoribosyltransferase 1 (HPRT1/hprt) and the real-time PCR system (7500 fast) were from Applied Biosystem, Life Technology and Thermo Fisher Scientific, Inc. (NYSE: TMO). OCT freezing medium was from Sakura Finetek and Vectashield was from Vector Laboratories. The Fortessa-I, -II, and LSRII flow cytometers were from BD Biosciences. FCS Express software version 4 was from DeNovo Software. The plate reader was from Molecular Devices. The D409V/null mice (Gba19V/−) and wild-type controls were both on the mixed FVB/C57BL 6J/129SvEvBrd (50:25:25) backgrounds. Male and female mice were used at 20–24 weeks of age7. To directly assess the role of C5aR1-mediated effects, Gba19V/− mice were backcrossed to C5aR1-deficient mice for at least 10 generations. Out of these backcrosses, we generated double mutant mice (Gba19V/−C5ar1−/−) and Gba19V/−, wild-type and C5ar1−/− background-matched littermates. To assess the role of C5aR1, C5aR2 and FcγRs in pharmacologically induced Gaucher disease, wild-type mice and those lacking C5aR1, C5aR2, and activating FcγRs (Fcer1g−/−) or the inhibitory FcγRIIB (Fcgr2b−/−) of both sexes were used at ~12 weeks of age. Mice were bred and maintained in the specific-pathogen free facility at the Cincinnati Children’s Research foundation. Mice of the appropriate genotype were randomly assigned to groups. No specific randomization was performed. The investigators were not blinded to allocation during experiments and outcome assessment. Animal care was provided in accordance with National Institute of Health guidelines and was approved by Cincinnati Children’s Hospital Medical Center IACUC. Frozen sera from human patients with untreated Gaucher disease (n = 10) and healthy volunteers (n = 15) were de-identified. Patients with Gaucher disease were diagnosed at Cincinnati Children’s Hospital Medical Center. They did not receive any specific-enzyme therapy or substrate reduction therapy for Gaucher disease and are designated as untreated. The study was approved by the ethics committee at Cincinnati Children’s Hospital Medical Center. Protocols for human studies were approved by the Institutional Review Board, and patients with Gaucher disease and controls gave written, informed consent for the use of their serum for the studies described here. To assess the effect of genetic or pharmacological targeting of C5aR1 on the inflammatory response in Gaucher disease, wild-type (n = 10) and C5ar1−/− mice (n = 10) were treated with CBE, which is an irreversible inhibitor of acid β-glucosidase21. More specifically, both mouse strains were injected i.p. with 100 mg CBE per kg body weight or vehicle (PBS) per day for up to 60 days, which was the termination point of these experiments. After 60 days of the indicated treatment with CBE, immune cells (macrophages, DCs, and T cells) were purified from lung of these mouse strains and used for measurement of GC, costimulatory molecules, and several of the proinflammatory cytokines. In additional experiments, wild-type (n = 15) or Gba19V/− mice (n = 15) were injected with 100 μl of the C5aRA A8(Δ71−73) (i.p. 0.5 mg per kg) or vehicle (100 μl, PBS) on five consecutive days. Five days after the final C5aRA treatment, liver, spleen and lung were separated and measured for GC accumulation. In addition, DCs and CD4+ T cells were purified from the lung of the indicated mouse strains, co-cultured and measured for costimulatory molecule expression and the production of proinflammatory cytokines. Liver, spleen and lung of vehicle- or CBE-treated wild-type or C5ar1−/− mice were homogenized in 1% sodium taurocholate/1% Triton X-100. The protein concentrations of cells from such tissue lysates were determined by BCA assay using BSA as standard. GCase activities were determined fluorometrically with 4MU-Glc in 0.25% Na taurocholate and 0.25% Triton X-100 as described7. Liver, spleen, lung and bone marrow were collected aseptically. Single-cell suspensions from liver and lung were obtained from minced pieces that were treated with Liberase Cl (0.5 mg ml−1) and DNase (0.5 mg ml−1) in RPMI (45 min, 37 °C). Single-cell suspensions from spleen were obtained by grinding and then filtration through a 70-μm cell strainer. Similar suspensions of liver and lung were obtained from minced pieces that were treated with Liberase Cl (0.5 mg ml−1) and DNase (0.5 mg ml−1) in RPMI (45 min, 37 °C). For bone marrow cells, femurs, tibias and humeri were flushed with sterile PBS, followed by red blood cell lysis (155 mM NH Cl, 10 mM NaHCO , 0.1 mM EDTA), passage through a strainer. Cells were then pelleted by centrifugation at 350g. Viable cells were counted using a Neubauer chamber and trypan blue exclusion. DCs, macrophages and CD4+ T lymphocytes were purified from single-cell suspensions of liver, spleen and lung using CD11c, CD11b and CD4 (L3T4) microbeads according to the manufacturer’s protocol. The purity of the cells was ~90–95%. Bone marrow cells were used to differentiate macrophage as described22. Briefly, fresh bone marrow cells were stimulated with M-CSF (10 ng ml−1) in complete DMEM (FBS 10% + 100 U ml−1 penicillin, 100 μg ml−1 streptomycin, 10 mM HEPES and 1 mM sodium pyruvate). Cells were seeded in six-well tissue culture plates and incubated at 37 °C in a 5% CO atmosphere. Five days after cell seeding, supernatants were discarded and the attached cells were washed with 10 ml of sterile PBS. 10 ml of ice-cold PBS were added to each plate and incubated at 4 °C for 10 min. The macrophages were detached by gently pipetting the PBS across the dish. The cells were centrifuged at 200g for 5 min and resuspended in 10 ml of complete DMEM. The cells were counted, seeded and cultured for 12 h before they were used for further experiments. DCs were differentiated from bone marrow cells as described22. Briefly, bone marrow was flushed from the long bones of the limbs and depleted of red cells with ammonium chloride. Such bone marrow cells were plated in six-well plates (106 cells per ml, 3 ml per well) in RPMI 1640 medium supplemented with FBS (10%) and 100 U ml–1 penicillin, 100 μg ml−1 streptomycin, 10 mM HEPES and 1 mM sodium pyruvate and 10 ng ml−1 recombinant murine GM-CSF at days 0, 2, 4 and 6. Floating cells were gently removed and fresh medium was added. At day 7, nonadherent cells and loosely adherent proliferating DC aggregates were collected, counted, seeded and cultured for 12 h before they were used. Tissue cells were identified by flow cytometry. First, they were suspended in PBS containing 1% BSA. After incubation (15 min, 4 °C) with FcγR-blocking antibody 2.4G2, cells were stained (45 min, 4 °C) with the following antibodies to identify antigen-presenting cells and T cells: CD4 for T cells; CD11b and F4/80 for macrophages; and CD11b and CD11c for DCs. Cells were also stained with the respective isotype antibodies as controls. Macrophages were first identified by their typical FSC/SSC pattern, and F4/80 and CD11b expression. DCs were identified as CD11c+CD11b+ cells. Further, CD40, CD80 CD86 and C5aR1 expression was determined in tissue DCs. T cells were first characterized by their FSC/SSC pattern and CD3 staining. CD3+ T cells were further stained for CD4, CD40L and CD69 expression. A total of 106 events were acquired for each cell type isolated from the different organs. Specific surface expression was assessed relative to the expression of the corresponding isotype control antibody. Lipids were extracted from tissues (5 mg; liver, spleen, and lung), purified macrophages, DCs, CD4+ T lymphocytes, U937 cells and GC-specific IgG2a by chloroform and methanol1, 22. GC and GS species in IgG2a isolates were quantified by ESI-LC–MS/MS using a Waters Quattro Micro API triple quadrupole mass spectrometer interfaced with Acquity UPLC system7. Calibration curves were built for the GC species (C16:0, C18:0, C24:1) using C12-GC as standard. Quantification of GCs with various fatty acid chain lengths were realized by using the curve of each GC species with closest number of chain length. The total GCs in the tissues and purified IgG2a were normalized to 1 mg of tissue and protein, and immune cells to 1 × 106 cells. C5a concentrations were determined in sera or culture supernatants from bone-marrow-derived macrophages and DCs (each of 106 cells per 200 μl of complete RPMI media) of wild-type and Gba19V/− (n = 15 per group) mice, CBE-treated and CBE-untreated wild-type and C5ar1−/− mice (n = 10 per of group), as well as in sera obtained from patients with untreated Gaucher disease (n = 10) and healthy control humans (n = 15) by commercial ELISA kits according to the manufacturer’s instructions. C5aR1 expression in macrophages and DCs purified from liver, spleen and lung of wild-type or Gba19V/− mice was evaluated by flow cytometry using a C5aR1-specific antibody. For detection of cytokines and chemokines, blood from CBE-treated and CBE-untreated wild-type and C5ar1−/− mice (n = 10 per group) was obtained by cardiac puncture. Sera were isolated after one-hour incubation at room temperature. Sera were diluted 1:10 with sterile PBS and used for detection of cytokines and chemokines with Proteome Profiler A Densitometry, which was performed with a Bio-Rad Molecular Imager Gel Doc system. To assess the effect of C5a on GC-induced costimulatory molecule expression, DCs and CD4+ T cells purified from lungs of Gba19V/− mice and background-matched wild-type mice (n = 15 per group) were stimulated ex vivo in the presence or absence of different C5a concentrations (0, 8, 16 and 32 nM) for 24 h at 37 °C. DCs and CD4+ T cells were purified from liver, spleen and lung of CBE-treated C5ar1−/− and background-matched wild-type mice (n = 10 per group) and stained with CD40-, CD80- and CD86- (DCs) or CD40L- and CD69-specific antibodies (CD4+ T cells). To assess the effect of C5a on GC-induced cytokine and chemokine production, DCs and CD4+ T cells (1:2.5 ratio), purified from lungs of Gba19V/− mice and background-matched wild-type mice (n = 15 per group), were cocultured in the presence and absence of C5a (32 nM) for 48 h in complete medium. In additional experiments, indicated ratios (1:25) of DCs and CD4+ T cells, purified from lungs of CBE-treated and untreated wild-type and C5ar1−/− mice (n = 10 per each group), were cocultured for 48 h in complete medium. Supernatant of these experiments were used to determine IFNγ, TNF, IL-1β, IL-6, IL-12p40, IL-12p70, IL-17A/F and IL-23 by ELISA. To determine the levels of GC-specific IgG antibodies in mice and patients with Gaucher disease, 10 μg of GC were dissolved in 1 ml of methanol and water to a final concentration of 10 μg ml−1. 100 ml of this GC solution (1 μg per well) were used to coat a 96-well ELISA plate. GC-coated plates were kept overnight at room temperature followed by three washings with PBS containing 1% Tween-20 (PBST). Test sera (100 μl; 1:100) isolated from wild-type and Gba19V/− mice (n = 15 per group), CBE-treated and untreated wild-type mice (n = 10 per group), as well as healthy humans (n = 15) and untreated patients with Gaucher (n = 10), and GC-specific IgG control antibody were loaded into the lipid-coated wells, followed by incubation for 1.5 h at room temperature. These plates were then washed three times with PBST and subsequently incubated with alkaline phosphatase-conjugated rat anti-mouse IgG1 (1:500 in PBS), IgG2a/c (1:1,000 in PBS), IgG2b (1:1,000 in PBS) or IgG3 (1:1,000 in PBS) or alkaline phosphatase-conjugated mouse anti-human IgG1, IgG2 (each 1:1,000 in PBS), IgG3 and IgG4 (each 1:500 in PBS) in triplicates. Then, the plates were incubated for 1.5 h at room temperature followed by two washing steps with PBST and one with 10 mM DEA. 100 ml of 1 mg ml−1 PNPP in 10 mM DEA containing 5 mM MgCl was added to each well and incubated for 30 min at room temperature in the dark. Finally, plates were read at 405 nm to detect the GC-specific IgG antibodies. To determine GS- and GC-specific IgG IC formation, IgG2a was purified from pooled sera that were prepared from wild-type and Gba19V/− mice (n = 15 per group). Briefly, pooled mouse sera (5–10 ml) were incubated with goat anti-mouse IgG2a (25–50 μg) that had been immobilized on 2 ml of Aminolink Plus coupling resin overnight at 4 °C according to the manufacturer’s instructions. After several washing steps with working buffer (20 mM PBS, pH 7.4), bound IgG2a antibody fractions were finally eluted using 3 ml of elution buffer (50 mM Gly–HCl, pH 2.8). The eluted fractions were then used to determine GS and GC species bound to IgG2a and to quantify them with an ESI-LC–MS/MS system as above. Protein separation of purified IgG2a was performed using a 12% NuPAGE Bis-Tris Mini gel and reducing SDS–PAGE system according to the manufacturer’s instruction. Briefly, 4 μl of IgG2a (2.5 mg ml−1) was mixed with 16 μl of reducing buffer, (for example, 5 μl of NuPAGE LDS Sample Buffer 4×, 2 μl of NuPAGE Reducing Agent 10×, and 13 μl of deionized water) and then boiled for 5 min in a water bath. 10 μg of protein were applied to each lane and PAGE (130–180 mA) was run for 1 h at room temperature. The gel was then stained with Coomassie blue R250 using standard techniques. A minimum of two sections from CBE-treated and CBE-untreated wild-type and C5ar1−/− mice (n = 10 per group), as well as C5aRA-treated and vehicle-treated wild-type and Gba19V/− mouse strains (n = 15 per group) were examined from each tissue. Liver, spleen and bone were collected after the mice had been perfused with PBS and the tissues fixed in 10% formalin or 4% paraformaldehyde, and processed for paraffin and frozen blocks, respectively. Paraffin sections of indicated tissues were stained with haematoxylin and eosin (H&E), whereas frozen sections were stained with rat anti-mouse CD68 (1:100) followed by biotinylated goat anti-rat and streptavidin-conjugated antibodies as described previously7, 23. To determine whether GC induces complement activation in Gaucher disease, we used freshly isolated liver, spleen and lung from CBE-treated and untreated wild-type and C5ar1−/− mice (n = 10 per group). These tissues were embedded in OCT freezing medium and snap-frozen in liquid nitrogen and eventually stored at −80 °C until use. Tissues were then sectioned at 5–7 μm and fixed with cold acetone and permeablized with 0.2% Triton X-100 in PBS. Tissue sections were blocked with 2% BSA and counter-stained with FITC-conjugated antibody to mouse C3/C3b (2 μg ml−1) and its isotype control overnight at 4 °C. Tissues were washed and coverslipped with Vectashield. Immunofluorescence images were captured with a Zeiss Apotome microscope (AxioV200). To investigate the direct effect of GC immune complexes on C5a release in Gaucher disease, macrophages (106 cells per 200 μl of complete RPMI media) purified from lung tissues of Gba19V/− mice (n = 15) were ex vivo stimulated in the presence or absence of GC (0.25, 0.5 and 1.0 μg) and anti-GC IgG (25 μg) for 2 h. Supernatants were used to determine C5a concentrations by ELISA. To evaluate the effect of GC immune complexes on C5a secretion in vivo, wild-type and Gba19V/− mice were injected i.p. with vehicle (ethanol), GC, anti-GC IgG or GC immune complexes (n = 15 per group). After 2 h, serum and peritoneal lavage fluid were collected and C5a was measured by ELISA according to the manufacturer’s instructions. After incubation of lung-derived F4/80+CD11b+ macrophages (5 × 106) from wild-type and Gba19V/− mice (n = 15 per group) with GC (1.0 μg), anti-GC IgG (25 μg of anti-GC IgG), GC immune complex or vehicle (1 μl methanol) per ml of media for 5 min at 37 °C, cells were collected and pellets were lysed with 1× RIPA buffer containing sodium orthovanadate and protease inhibitors. Protein concentrations were determined in cell lysates using BCA protein assay. Each 10 μg of cell lysates were loaded on an 10% SDS–PAGE and transferred onto a PVDF membrane and probed with antibodies to phosphorylated LAT (pLAT; 1:200) and non-phosphorylated LAT (linker of T cell activation; 1:1,000) using the iBlot 2 Gel transfer device and iBind western system according to the manufacturer’s instruction. pLAT and LAT (both ~36/38 kDa) proteins were visualized using anti-rabbit and anti-mouse secondary antibodies conjugated to HRP (1:1,000) and the Novex ECL chemiluminescent substrate reagent kit. Total RNA was extracted from mouse lung, liver, spleen and U937 macrophage-like cells using TRIzol reagent according to the manufacturer’s instructions. Reverse transcription was performed using the High capacity RNA to cDNAKit and qPCR was performed using Taqman assay reagents, primer/probes sets for both human and mouse UGCG/Ugcg and HPRT1/hprt. Amplifications were done using the ABI 7500 Real-Time PCR System and the calculations and analysis were based on the comparative C method24. For protein expression of GCS, mouse lung homogenates were lysed using mammalian protein extraction reagent. Protein concentration was determined by BCA according to the manufacturer’s instructions. Equal amounts of proteins (20 μg per lane) were loaded onto NuPAGE 4–12% Bis-Tris gradient SDS–PAGE. The mouse proteins were transferred to Hybond-ECL PVDF membranes and immunoblotted using iBind western blotting system with antibodies to mouse GCS diluted 1:100 with iBind solution and incubated over night at 4 °C. The GCS signals were detected using a HRP-conjugated anti-rabbit IgG (1:1,000) and ECL detection reagent as described25 with β-actin as a loading control. The intensities of protein bands were quantified using an NIH Image J. The GCS expression in the different treatment groups is depicted as the GCS/β-actin ratio normalized against the 100% value assigned to the wild-type group. To assess whether GC immune complexes causes C5a generation in patients with Gaucher disease, sera prepared from healthy humans (n = 15) and untreated patients with Gaucher disease (n = 10) were diluted 1:10,000 with saline and used to identify C5a by ELISA according to the manufacturer’s instructions. To determine the direct effect of GC immune complexes on C5a production and proinflammatory cytokine release in human Gaucher disease, the human macrophage-like cell line U937 (106 cells per 200 μl of complete RPMI media) was treated with CBE at 37 °C and 5% CO for 72 h. These cells were then stimulated in the presence or absence of GC (1 μg), anti-GC IgG (25 μg) or GC immune complex. Supernatants were used to determine C5a, CCL18, TNF, IL-1β, IL-6 and IL-23 concentrations by ELISA. All quantitative experiments were repeated at least three times. The sample sizes in all animal studies were estimated on the basis of effect sizes present in pilot studies to ensure we had sufficient power. The number of animals used in each experiment is outlined in the relevant sections in the Methods. An unpaired Student’s t-test (for two groups) or one-way analysis of variance (ANOVA) (for more than two groups) were used to determine significant differences between groups (Graph Pad Prism). To ensure that the statistical inference was appropriate, we evaluated the normality of the data distribution. Between group differences in many of the variables made, the overall distributions of many of the measures were non-normal. However, evaluation with non-parametric tests supported the inference of the parametric tests suggesting that the parametric tests were robust to these deviations from normality. For t- tests of the 40 cytokines, a simple Bonferroni correction is not appropriate as there is a high degree of correlation between the cytokines (average pairwise rho = 0.76). Thus, we employed a correlation corrected Bonferroni adjustment in SISA (http://www.quantitativeskills.com/sisa/calculations/bonfer.htm) resulting in a significance threshold of 0.021. As two conditions were considered for these 40 cytokines, the final correction was 0.021 / 2 = 0.0105. For the ANOVA, rather than considering all possible pairs of comparisons, we focused on a restricted set of a priori comparisons. Specifically, we performed analysis to determine the effect of (1) genotype, (2) C5aRA treatment, and (3) GCase targeting. Within each of these specific tests, we applied Bonferroni correction on the basis of the number of a priori comparisons made. For analyses, which were not pre-specified, the Bonferroni comparison was made on the number of possible comparisons. All data in the bar graphs are reported as mean ± s.d. *P < 0.05, **P < 0.01, ***P < 0.001 denote the uncorrected P values, with the significance thresholds denoted in the figure legend if multiple testing corrections were applied. The data generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
News Article | February 15, 2017
The discovery cohort consisted of 147 studies comprising 458,927 adult individuals of the following ancestries: (1) European descent (n = 381,625); (2) African (n = 27,494); (3) South Asian (n = 29,591); (4) East Asian (n = 8,767); (5) Hispanic (n = 10,776) and (6) Saudi Arabian (n = 695). All participating institutions and coordinating centres approved this project, and informed consent was obtained from all subjects. Discovery meta-analysis was carried out in each ancestry group (except the Saudi Arabian) separately as well as in the All group. Validation was undertaken in individuals of European ancestry only (Supplementary Tables 1–3). Conditional analyses were undertaken only in the European descent group (106 studies, n = 381,625). The SNPs we identify are available from the NCBI dbSNP database of short genetic variations (https://www.ncbi.nlm.nih.gov/projects/SNP/). No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. Height (in centimetres) was corrected for age and the genomic principal components (derived from GWAS data, the variants with a MAF > 1% on ExomeChip (http://genome.sph.umich.edu/wiki/Exome_Chip_Design), or ancestry-informative markers available on the ExomeChip), as well as any additional study-specific covariates (for example, recruiting centre), in a linear regression model. For studies with non-related individuals, residuals were calculated separately by sex, whereas for family-based studies sex was included as a covariate in the model. Additionally, residuals for case/control studies were calculated separately. Finally, residuals were subject to inverse normal transformation. The majority of studies followed a standardized protocol and performed genotype calling using the designated manufacturer’s software, which was then followed by zCall30. For ten studies participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, the raw intensity data for the samples from seven genotyping centres were assembled into a single project for joint calling11. Study-specific quality-control measures of the genotyped variants was implemented before association analysis (Supplementary Tables 1–2). Individual cohorts were analysed separately for each ancestry population, with either RAREMETALWORKER (http://genome.sph.umich.edu/wiki/RAREMETALWORKER) or RVTEST (http://zhanxw.github.io/rvtests/), to associate inverse normal transformed height data with genotype data taking potential cryptic relatedness (kinship matrix) into account in a linear mixed model. These software are designed to perform score-statistics based rare-variant association analysis, can accommodate both unrelated and related individuals, and provide single-variant results and variance-covariance matrix. The covariance matrix captures linkage disequilibrium relationships between markers within 1 Mb, which is used for gene-level meta-analyses and conditional analyses31. Single-variant analyses were performed for both additive and recessive models (for the alternate allele). The individual study data were investigated for potential existence of ancestry population outliers based on the 1000 Genome Project phase 1 ancestry reference populations. A centralized quality control procedure implemented in EasyQC32 was applied to individual study association summary statistics to identify outlying studies: (1) assessment of possible problems in height transformation; (2) comparison of allele frequency alignment against 1000 Genomes Project phase 1 reference data to pinpoint any potential strand issues; and (3) examination of quantile–quantile plots per study to identify any problems arising from population stratification, cryptic relatedness and genotype biases. We excluded variants if they had a call rate <95%, Hardy–Weinberg equilibrium P < 1 × 10−7, or large allele frequency deviations from reference populations (>0.6 for all ancestry analyses and >0.3 for ancestry-specific population analyses). We also excluded from downstream analyses markers not present on the Illumina ExomeChip array 1.0, variants on the Y chromosome or the mitochondrial genome, indels, multiallelic variants, and problematic variants based on the Blat-based sequence alignment analyses. Meta-analyses were carried out in parallel by two different analysts at two sites. We conducted single-variant meta-analyses in a discovery sample of 458,927 individuals of different ancestries using both additive and recessive genetic models (Extended Data Fig. 1 and Supplementary Tables 1–4). Significance for single-variant analyses was defined at an array-wide level (P < 2 × 10−7, Bonferroni correction for 250,000 variants). The combined additive analyses identified 1,455 unique variants that reached array-wide significance (P < 2 × 10−7), including 578 non-synonymous and splice-site variants (Supplementary Tables 5–7). Under the additive model, we observed a high genomic inflation of the test statistics (for example, a λ of 2.7 in European ancestry studies for common markers, Extended Data Fig. 2 and Supplementary Table 8), although validation results (see below) and additional sensitivity analyses (see below) suggested that it is consistent with polygenic inheritance as opposed to population stratification, cryptic relatedness, or technical artefacts (Extended Data Fig. 2). The majority of these 1,455 association signals (1,241; 85.3%) were found in the European ancestry meta-analysis (85.5% of the discovery sample size) (Extended Data Fig. 2). Nevertheless, we discovered eight associations within five loci in our all-ancestry analyses that are driven by African studies (including one missense variant in the growth hormone gene GH1 (rs151263636), Extended Data Fig. 3), three height variants found only in African studies, and one rare missense marker associated with height in South Asians only (Supplementary Table 7). We observed a marked genomic inflation of the test statistics even after adequate control for population stratification (linear mixed model) arising mainly from common markers; λ in European ancestry was 1.2 and 2.7 for all and common markers, respectively (Extended Data Fig. 2 and Supplementary Table 8). Such inflation is expected for a highly polygenic trait like height, and is consistent with our very large sample size3, 33. To confirm this, we applied the recently developed linkage disequilibrium score regression method to our height ExomeChip results34, with the caveats that the method was developed (and tested) with >200,000 common markers available. We restricted our analyses to 15,848 common variants (MAF ≥ 5%) from the European-ancestry meta-analysis, and matched them to pre-computed linkage disequilibrium scores for the European reference dataset34. The intercept of the regression of the χ2 statistics from the height meta-analysis on the linkage disequilibrium score estimates that the inflation in the mean χ2 is due to confounding bias, such as cryptic relatedness or population stratification. The intercept was 1.4 (s.e.m. = 0.07), which is small when compared to the λ of 2.7. Furthermore, we also confirmed that the linkage disequilibrium score regression intercept is estimated upward because of the small number of variants on the ExomeChip and the selection criteria for these variants (that is, known GWAS hits). The ratio statistic of (intercept − 1)/(mean χ2 − 1) is 0.067 (s.e.m. = 0.012), well within the normal range34, suggesting that most of the inflation (~93%) observed in the height association statistics is due to polygenic effects (Extended Data Fig. 2). Furthermore, to exclude the possibility that some of the observed associations between height and rare and low-frequency variants could be due to allele calling problems in the smaller studies, we performed a sensitivity meta-analysis with primarily European ancestry studies totalling >5,000 participants. We found very concordant effect sizes, suggesting that smaller studies do not bias our results (Extended Data Fig. 2). The RAREMETAL R package35 and the GCTA v1.24 (ref. 36) software were used to identify independent height association signals across the European descent meta-analysis results. RAREMETAL performs conditional analyses by using covariance matrices in order to distinguish true signals from those driven by linkage disequilibrium at adjacent known variants. First, we identified the lead variants (P < 2 × 10−7) based on a 1-Mb window centred on the most significantly associated variant and performed linkage disequilibrium pruning (r2 < 0.3) to avoid downstream problems in the conditional analyses due to co-linearity. We then conditioned on the linkage disequilibrium-pruned set of lead variants in RAREMETAL and kept new lead signals at P < 2 × 10−7. The process was repeated until no additional signal emerged below the pre-specified P-value threshold. The use of a 1-Mb window in RAREMETAL can obscure dependence between conditional signals in adjacent intervals in regions of extended linkage disequilibrium. To detect such instances, we performed joint analyses using GCTA with the ARIC and UK ExomeChip reference panels, both of which comprise >10,000 individuals of European descent. With the exception of a handful of variants in a few genomic regions with extended linkage disequilibrium (for example, the HLA region on chromosome 6), the two pieces of software identified the same independent signals (at P < 2 × 10−7). To discover new height variants, we conditioned the height variants found in our ExomeChip study on the previously published GWAS height variants3 using the first release of the UK Biobank imputed dataset and regression methodology implemented in BOLT-LMM37. Because of the difference between the sample size of our discovery set (n = 458,927) and the UK Biobank (first release, n = 120,084), we applied a threshold of P < 0.05 to declare a height variant as independent in this analysis. We also explored an alternative approach based on approximate conditional analysis36. This latter method (SSimp) relies on summary statistics available from the same cohort, thus we first imputed summary statistics38 for exome variants, using summary statistics from a previous study3. Conversely, we imputed the top variants from this study3 using the summary statistics from the ExomeChip. Subsequently, we calculated effect sizes for each exome variant conditioned on the top variants of this study3 in two ways. First, we conditioned the imputed summary statistics of the exome variant on the summary statistics of the top variants that fell within 5 Mb of the target ExomeChip variant. Second, we conditioned the summary statistics of the ExomeChip variant on the imputed summary statistics of the hits of this study3. We then selected the option that yielded a higher imputation quality. For poorly tagged variants ( < 0.8), we simply used up-sampled HapMap summary statistics for the approximate conditional analysis. Pairwise SNP-by-SNP correlations were estimated from the UK10K data (TwinsUK39 and ALSPAC40 studies, n = 3,781). Several studies, totalling 252,501 independent individuals of European ancestry, became available after the completion of the discovery analyses, and were thus used for validation of our experiment. We validated the single-variant association results in eight studies, totalling 59,804 participants, genotyped on the ExomeChip using RAREMETAL31. We sought additional evidence for association for the top signals in two independent studies in the UK (UK Biobank) and Iceland (deCODE), comprising 120,084 and 72,613 individuals, respectively. We used the same quality control and analytical methodology as described above. Genotyping and study descriptions are provided in Supplementary Tables 1–3. For the combined analysis, we used the inverse-variance-weighted fixed effects meta-analysis method using METAL41. Significant associations were defined as those with a combined meta-analysis (discovery and validation) P < 2 × 10−7. We considered 81 variants with suggestive association in the discovery analyses (2 × 10−7 < P ≤ 2 × 10−6). Of those 81 variants, 55 reached significance after combining discovery and replication results based on a P < 2 × 10−7 (Supplementary Table 9). Furthermore, recessive modelling confirmed seven new independent markers with a P < 2 × 10−7 (Supplementary Table 10). One of these recessive signals is due to a rare X-linked variant in the AR gene (rs137852591, MAF = 0.21%). Because of its frequency, we only tested hemizygous men (we did not identify homozygous women for the minor allele) so we cannot distinguish between a true recessive mode of inheritance or a sex-specific effect for this variant. To test the independence and integrate all height markers from the discovery and validation phase, we used conditional analyses and GCTA ‘joint’ modelling36 in the combined discovery and validation set. This resulted in the identification of 606 independent height variants, including 252 non-synonymous or splice-site variants (Supplementary Table 11). If we consider only the initial set of lead SNPs with P < 2 × 10−7, we identified 561 independent variants. Of these 561 variants (selected without the validation studies), 560 have concordant direction of effect between the discovery and validation studies, and 548 variants have a P < 0.05 (466 variants with P < 8.9 × 10−5, Bonferroni correction for 561 tests), suggesting a very low false discovery rate (Supplementary Table 11). For the gene-based analyses, we applied two different sets of criteria to select variants, based on coding variant annotation from five prediction algorithms (PolyPhen2 HumDiv and HumVar, LRT, MutationTaster and SIFT)42. The mask labelled ‘broad’ included variants with a MAF < 0.05 that are nonsense, stop-loss, splice site, as well as missense variants that are annotated as damaging by at least one program mentioned above. The mask labelled ‘strict’ included only variants with a MAF < 0.05 that are nonsense, stop-loss, splice-site, as well as missense variants annotated as damaging by all five algorithms. We used two tests for gene-based testing, namely the SKAT43 and VT44 tests. Statistical significance for gene-based tests was set at a Bonferroni-corrected threshold of P < 5 × 10−7 (threshold for 25,000 genes and four tests). The gene-based discovery results were validated (same test and variants, when possible) in the same eight studies genotyped on the ExomeChip (n = 59,804 participants) that were used for the validation of the single-variant results (see above, and Supplementary Tables 1–3). Gene-based conditional analyses were performed in RAREMETAL. We accessed ExomeChip data from GIANT (BMI, waist:hip ratio), GLGC (total cholesterol, triglycerides, HDL-cholesterol, LDL-cholesterol), IBPC (systolic and diastolic blood pressure), MAGIC (glycaemic traits), REPROGEN (age at menarche and menopause), and DIAGRAM (type 2 diabetes) consortia. For coronary artery disease, we accessed 1000 Genomes Project-imputed GWAS data released by CARDIoGRAMplusC4D45. DEPICT (http://www.broadinstitute.org/mpg/depict/) is a computational framework that uses probabilistically defined reconstituted gene sets to perform gene set enrichment and gene prioritization15. For a description of gene set reconstitution, refer to refs 15, 46. In brief, reconstitution was performed by extending pre-defined gene sets (such as Gene Ontology terms, canonical pathways, protein-protein interaction subnetworks and rodent phenotypes) with genes co-regulated with genes in these pre-defined gene set using large-scale microarray-based transcriptomics data. In order to adapt the gene set enrichment part of DEPICT for ExomeChip data (https://github.com/RebeccaFine/height-ec-depict), we made two principal changes. First, because DEPICT for GWAS incorporates all genes within a given linkage disequilibrium block around each index SNP, we modified DEPICT to take as input only the gene directly impacted by the coding SNP. Second, we adapted the way DEPICT adjusts for confounders (such as gene length) by generating null ExomeChip association results using Swedish ExomeChip data (Malmö Diet and Cancer (MDC), All New Diabetics in Scania (ANDIS), and Scania Diabetes Registry (SDR) cohorts, n = 11,899) and randomly assigning phenotypes from a normal distribution before conducting association analysis (see Supplementary Information). For the gene set enrichment analysis of the ExomeChip data, we used significant non-synonymous variants statistically independent of known GWAS hits (and that were present in the null ExomeChip data; see Supplementary Information for details). For gene set enrichment analysis of the GWAS data, we used all loci with a non-coding index SNP and that did not contain any of the novel ExomeChip genes. In visualizing the analysis, we used affinity propagation clustering47 to group the most similar reconstituted gene sets based on their gene memberships (see Supplementary Information). Within a ‘meta-gene set’, the best P value of any member gene set was used as representative for comparison. DEPICT for ExomeChip was written using the Python programming language and the code can be found at https://github.com/RebeccaFine/height-ec-depict. We also applied the PASCAL (http://www2.unil.ch/cbg/index.php?title=Pascal) pathway analysis tool16 to association summary statistics for all coding variants. In brief, the method derives gene-based scores (both SUM and MAX statistics) and subsequently tests for the over-representation of high gene scores in predefined biological pathways. We used standard pathway libraries from KEGG, REACTOME and BIOCARTA, and also added dichotomized (Z score > 3) reconstituted gene sets from DEPICT15. To accurately estimate SNP-by-SNP correlations even for rare variants, we used the UK10K data (TwinsUK39 and ALSPAC40 studies, n = 3781). To separate the contribution of regulatory variants from the coding variants, we also applied PASCAL to association summary statistics of only regulatory variants (20 kb upstream, gene body excluded) from a previous study3. In this way, we could classify pathways driven principally by coding, regulatory or mixed signals. For the generation of STC2 mutants (R44L and M86I), wild-type STC2 cDNA contained in pcDNA3.1/Myc-His(−) (Invitrogen)23 was used as a template. Mutagenesis was carried out using Quickchange (Stratagene), and all constructs were verified by sequence analysis. Recombinant wild-type STC2 and variants were expressed in human embryonic kidney (HEK) 293T cells (293tsA1609neo, ATCC CRL-3216) maintained in high-glucose DMEM supplemented 10% fetal bovine serum, 2 mM glutamine, nonessential amino acids, and gentamicin. The cells are routinely tested for mycoplasma contamination. Cells (6 × 106) were plated onto 10-cm dishes and transfected 18 h later by calcium phosphate co-precipitation using 10 μg plasmid DNA. Medium was collected 48 h after transfection, cleared by centrifugation, and stored at −20 °C until use. Protein concentrations (58–66 nM) were determined by TRIFMA using antibodies described previously23. PAPP-A was expressed stably in HEK293T cells as previously reported48. Expressed levels of PAPP-A (27.5 nM) were determined by a commercial ELISA (AL-101, Ansh Labs). Culture supernatants containing wild-type STC2 or variants were adjusted to 58 nM, added an equal volume of culture supernatant containing PAPP-A corresponding to a 2.1-fold molar excess, and incubated at 37 °C. Samples were taken at 1, 2, 4, 6, 8, 16, and 24 h and stored at −20 °C. Specific proteolytic cleavage of 125I-labeled IGFBP-4 is described in detail elsewhere49. In brief, the PAPP-A–STC2 complex mixtures were diluted (1:190) to a concentration of 72.5 pM PAPP-A and mixed with pre-incubated 125I-IGFBP4 (10 nM) and IGF-1 (100 nM) in 50 mM Tris-HCl, 100 mM NaCl, 1 mM CaCl . Following 1 h incubation at 37 °C, reactions were terminated by the addition of SDS–PAGE sample buffer supplemented with 25 mM EDTA. Substrate and co-migrating cleavage products were separated by 12% non-reducing SDS–PAGE and visualized by autoradiography using a storage phosphor screen (GE Healthcare) and a Typhoon imaging system (GE Healthcare). Band intensities were quantified using ImageQuant TL 8.1 software (GE Healthcare). STC2 and covalent complexes between STC2 and PAPP-A were blotted onto PVDF membranes (Millipore) following separation by 3–8% SDS–PAGE. The membranes were blocked with 2% Tween-20, and equilibrated in 50 mM Tris-HCl, 500 mM NaCl, 0.1% Tween-20; pH 9 (TST). For STC2, the membranes were incubated with goat polyclonal anti-STC2 (R&D systems, AF2830) at 0.5 μg ml−1 in TST supplemented with 2% skimmed milk for 1 h at 20 °C. For PAPP-A–STC2 complexes, the membranes were incubated with rabbit polyclonal anti-PAPP-A50 at 0.63 μg ml−1 in TST supplemented with 2% skimmed milk for 16 h at 20 °C. Membranes were washed with TST and subsequently incubated with polyclonal rabbit anti-goat IgG[en rule]horseradish peroxidase (DAKO, P0449) or polyclonal swine anti-rabbit IgG[en rule]horseradish peroxidase (DAKO, P0217), respectively, diluted 1:2,000 in TST supplemented with 2% skimmed milk for 1 h at 20 °C. Following washing with TST, membranes were developed using enhanced chemiluminescence (ECL Prime, GE Healthcare). Images were captured using an ImageQuant LAS 4000 instrument (GE Healthcare). Summary genetic association results are available on the GIANT website (http://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium).