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News Article | April 17, 2017
Site: www.chromatographytechniques.com

Waste diversion is an essential goal for labs and cleanrooms, as well as virtually every other kind of facility. It can be achieved through a variety of ways, such as source reduction, reuse, composting and recycling. In 2014, more than 89 million tons of municipal solid waste were recycled and composted, providing an annual reduction of over 181 million metric tons of carbon dioxide equivalent emissions, comparable to the annual emissions from over 38 million passenger cars, according to the Environmental Protection Agency (EPA). The benefits of recycling are well known: •    Reduces the amount of waste sent to landfills and incinerators •    Conserves natural resources such as timber, water and minerals •    Prevents pollution by reducing the need to collect new raw materials •    Saves energy •    Reduces greenhouse gas emissions that contribute to global climate change •    Helps sustain the environment for future generations As recycling becomes the norm, rather than the exception, in labs and cleanrooms, facilities are getting pretty good at recycling primary commodities such as cardboard, paper, plastic and aluminum. But to get to a higher level of diversion and potentially reach the holy grail of zero waste, other non-traditional or secondary commodities must also be diverted from landfill, and recycled and repurposed into usable products and durable goods. Glove and apparel recycling is a relatively new form of recycling that is beginning to gain traction in lab and cleanroom settings. In 2011, Kimberly-Clark Professional launched The RightCycle Program, the first large-scale recycling effort for non-hazardous lab and cleanroom waste. Since then, the program has diverted more than 350 tons of waste from landfill. RightCycle removes gloves, masks, garments, shoe covers and other apparel accessories from the waste stream. The products are collected and shipped to domestic recycling centers, where they are turned into nitrile pellets that are then used to create eco-responsible consumer products and durable goods. As long as gloves, garments and accessories (such as masks, hoods, shoe covers and hairnets) do not contain bio-hazardous materials, they can be safely recycled and turned into items such as: lawn furniture, flowerpots and planters, shelving, totes and storage bins. It all adds up Gloves are ubiquitous in labs and cleanrooms, and workers can go through several pairs in the course of a day. While this is necessary to protect both the worker and the process, the amount of waste can add up. Consider these statistics: •    One university estimated that nearly 30 percent of its waste stream came from laboratory and research buildings.   •    A University of Washington lab waste audit found that 22 percent of its research waste consisted of nitrile gloves.   •    A University of California Santa Cruz (UCSC) laboratory waste assessment found that nitrile gloves made up a majority of laboratory waste destined for landfill. Because of this, many labs are participating in The RightCycle Program. The environmental benefits of glove and apparel recycling programs are evident. They take commonly used and essential lab and cleanroom products out of the solid waste stream, significantly reducing waste generation. Putting glove recycling into practice The University of Washington and UCSC now participate in The RightCycle Program, as does the Illinois Sustainable Technology Center (ISTC) at the University of Illinois and Purdue University. ISTC is a division of the Prairie Research Institute at the University of Illinois Urbana-Champaign. Its mission is to drive statewide economic growth through sustainability. To fulfill that mission, ISTC conducts scientific research and, in the process, uses a lot of gloves. “We conducted a waste audit to see how we could go to zero waste in our own building and realized that gloves were about 10 percent of our total waste by weight,” said Shantanu Pai, ISTC assistant sustainability researcher. “We were already effectively recycling other items—glass, aluminum, paper and cardboard.” With RightCycle, ISTC was able to reach 89 percent compliance for gloves in its labs—even higher than the rate for paper and cardboard recycling. It then decided to take the program a step further, piloting it in the university’s main dining hall and achieving an estimated diversion rate of 90 percent. It is in the process of expanding the effort to all dining facilities and campus labs. In fact, the university has purchased a storage container to house the gloves so shipments can be made just once a year. Since implementing The RightCycle program in 2013, the center and the university have diverted 4,945 pounds from landfills. “RightCycle has had a huge impact on our activities and our sustainability metrics,” said Kevin O’Brien, Director of the Illinois Sustainable Technology Center. “If you ever used gloves as part of your laboratory work, you quickly appreciate the value this program brings from a sustainability perspective.” Purdue University Across its campus in the course of a year, Purdue University uses approximately 360,000 disposable gloves. That’s a lot of trash—3.5 tons to be exact, all of which would normally wind up in a landfill. The university, based in West Lafayette, Ind., has won numerous awards for sustainability. Its efforts extend to many different areas—recycling, planning management, landscaping and green construction. With a diversion rate goal of 85 percent, the university is always seeking new and different ways to reduce its solid waste stream. In 2014, Purdue University added glove recycling to its list of sustainability accomplishments when it adopted The RightCycle program. Since November 2014, the chemistry department at Purdue University has diverted 8,163 pounds of lab gloves from landfills. Michael Gulich, director of campus master planning and sustainability, is looking to expand the program to other campus labs as well as food preparation areas. “Once you address cans, bottles, paper and cardboard recycling, you get into smaller niche streams,” he said. “We have some addressed very well, such as electronics waste and landscape debris. Previously, gloves didn’t have a solution. Anything that increases our diversion rate is good.” Other participants University laboratories aren’t the only facilities that have adopted this innovative recycling solution. Cell Signaling Technology (CST), a life sciences company, uses about 200,000 pairs of gloves each year. Reducing its environmental footprint has long been a core company value, so finding a way to reduce the volume of glove waste was important. CST began researching The RightCycle Program in 2013, and made its first recycling shipment in 2015. The program has helped CST reduce the costs of trash removal and move closer to its goal of zero waste to landfill. “We’re glad to have made an impact on our waste profile and to have our lab gloves repurposed for safe practical purposes,” said Sustainability Coordinator Elias Witman. “And it was fun for our employees to see our recycled gloves come back to CST in the form of a flying disc, which was tossed around after a company meeting.” Since joining The RightCycle Program, Cell Signaling Technology has recycled approximately 150,000 pairs of gloves. “The RightCycle Program is highly visible and practical,” Witman added. “People see it and want to participate. Programs like this can help shape a culture of sustainability in the lab and yield positive impacts for the planet.”


News Article | May 17, 2017
Site: www.nature.com

The Cdh5(PAC)-CreERT2 transgenic mice (iECre) were a gift from R. H. Adams39. Krit1fl/fl and Ccm2fl/fl animals have been previously described40, 41. Tlr4fl/fl, Cd14−/−, Ai14 (R26-LSL-RFP), and R26-CreERT2 animals42, 43, 44, 45 were obtained from the Jackson Laboratories. The Slco1c1(BAC)-CreERT2 transgenic mice have been previously described18. All experimental animals were maintained on a mixed 129/SvJ, C57BL/6J, DBA/2J genetic background unless specifically described. C57BL/6J and timed pregnant Swiss Webster mice were purchased from Charles River Laboratories. Germ-free Swiss Webster mice were purchased from Taconic. Breeding pairs between two and ten months of age were used to generate the neonatal CCM mouse model pups. Mice were housed in a specific pathogen-free facility where cages were changed on a weekly basis; ventilated cages, bedding, food, and acidified water (pH 2.5–3.0) were autoclaved before use, ambient temperature maintained at 23 °C, and 5% Clidox-S was used as a disinfectant. Experimental breeding cages were randomly housed on three different racks in the vivarium, and all cages were kept on automatic 12-h light/dark cycles. The University of Pennsylvania Institutional Animal Care and Use Committee (IACUC) approved all animal protocols, and all procedures were performed in accordance with these protocols. A group of the resistant Ccm2ECKO colony was exported to the Centenary Institute, Sydney, Australia, where the mice were permanently maintained as an inbred colony in a quarantine facility. After several generations, this colony uniformly converted to lesion susceptibility. Cages were changed on a weekly basis; ventilated cages, bedding, food and acidified water (pH 2.5–3.0) were autoclaved before use. Ambient temperature was maintained between 22–26 °C, and 80% ethanol and F10SC (1:125 dilution of the concentrate, a quaternary ammonium compound) were used as disinfectants. Experimental breeding cages were randomly distributed throughout the vivarium, and all cages were kept on 12-h light/dark cycles. The Sydney Local Health District Animal Welfare Committee approved all animal ethics and protocols. All experiments were conducted under the guidelines/regulations of Centenary Institute and the University of Sydney. Germ-free Swiss Webster mice were purchased from Taconic and directly transferred into sterile isolators (Class Biologically Clean Ltd) under the care of the Penn Gnotobiotic Mouse Facility. Food, bedding and water (non-acidified) were autoclaved before transfer into the sterile isolators. Ventilated cages were changed weekly, and all cages in the vivarium were kept under 12-h light/dark cycles. Microbiology testing (aerobic and anaerobic culture, 16S qPCR) was performed every ten days and faecal samples were sent to Charles Rivers Laboratories for pathology testing on a quarterly basis. Further details regarding the sterile C-section fostering can be found below. The University of Pennsylvania Institutional Animal Care and Use Committee (IACUC) approved all animal protocols, and all procedures were performed in accordance with these protocols. For all neonatal CCM mouse model experiments, at one day post-birth (P1), pups were intragastrically injected by 30-gauge needle with 40 μg of 4-hydroxytamoxifen (4OHT, Sigma Aldrich, H7904) dissolved in a 9% ethanol/corn oil (volume/volume) vehicle (50 μl total volume per injection). This solution was freshly prepared from pre-measured, 4OHT powder for every injection. Before injection, the pup skin was sanitized using ethanol wipes. The P1 time point was defined by checking experimental breeding pairs every evening for new litters. The following morning (P1), pups were injected with 4OHT. All experimental pups were subjected to this induction regimen. For the Tlr4 rescue experiment (Fig. 2), and all lineage-tracing experiments, an additional dose of 40 μg 4OHT was intragastrically delivered at P2 (P1+2, two total doses). Pups were then harvested as previously described9 at the specified time points. Tissue samples were fixed in 4% formaldehyde overnight, dehydrated in 100% ethanol, and embedded in paraffin. 5-μm-thick sections were used for haematoxylin and eosin (H&E) and immunohistochemistry staining. The following antibodies were used for immunostaining: rat anti-PECAM (1:20, Histo Bio Tech DIA-310), rabbit anti-pMLC2 (1:200, Cell Signaling 3674S), goat anti-KLF4 (1:100, R&D AF3158), and rabbit anti-RFP (1:50, Rockland 600-401-379). Littermate control and experimental animal sections were placed on the same slide and immunostained at the same time under identical conditions. Images were taken at the same time using the same exposure times and colour channels, and were subsequently overlaid using ImageJ. Intra-abdominal abscesses were dissected and triturated in 500 μl of SOC medium. Drops of the mixture were placed on a microscope slide, briefly exposed to heat, and Gram staining was performed using a kit from Sigma Aldrich (77730) following the manufacturer’s protocol. Eyes from euthanized P17 mice were removed and fixed overnight in cold 4% PFA/PBS solution. The following day, retinas were dissected, cut into petals, and stained with isolectin-B4 conjugated to Alexa488 fluorophore (Thermo Fisher I21411) as previously described46. The retinas were then whole-mounted on microscopy slides in a flat, four-petal shape for fluorescence imaging. B. fragilis was purchased directly from the ATCC (strain 25285) and grown in chopped meat glucose (CMG) broth (Anaerobe Systems AS-813) under anaerobic conditions at 37 °C. Autoclaved, degassed caecal contents (ACC) were generated by collecting caecal contents from the colons of euthanized adult mice between 2–8 months of age. Caecal contents were then autoclaved and pulverized in an equal volume of CMG broth. This slurry was filtered through a 70-μm nylon strainer and degassed overnight in the anaerobic chamber. 1 ml of CMG broth was inoculated with B. fragilis and grown overnight to an optical density of between 0.8 and 1.0. An equal volume of ACC was mixed with the overnight bacterial culture. 100 μl of this B. fragilis–ACC mixture was injected intraperitoneally into five-day-old pups with a 31-gauge needle. Control littermates were simultaneously injected intraperitoneally with 100 μl of ACC alone. Pups were harvested at P17. Spleen weight was measured immediately after dissection, and all tissue was subsequently processed as described above. LPS from E. coli O127:B8 was purchased from Sigma (L3129) and administered to the low-lesion-penetrance, resistant Ccm2ECKO neonatal CCM disease model. At P5, a 3 μg dose of LPS dissolved in sterile PBS was administered retro-orbitally in a total 30 μl volume by 31-gauge needle. At P10, a 5 μg dose of LPS was administered retro-orbitally in a total 50 μl volume by 31-gauge needle. Control animals were identically injected with PBS alone. Pups were euthanized and brains dissected at specified time points. Peptidoglycan from Bacillus subtilis (a Gram-positive gut commensal) was purchased from Invivogen (tlrl-pgnb3) and administered to the resistant Ccm2ECKO neonatal CCM disease model under identical conditions as the LPS experiments. Poly(I:C) was purchased from Invivogen (tlrl-picw) and administered to the resistant Ccm2ECKO neonatal CCM disease model under identical conditions as the LPS experiments. Mouse IL-1β was purchased from Genscript (Z02988) and administered to the resistant Ccm2ECKO neonatal CCM disease model. At P5, a 5 ng dose of IL-1β dissolved in sterile PBS was administered retro-orbitally in a total 30 μl volume by 31-gauge needle. At P10, an 8-ng dose of IL-1β was administered retro-orbitally in a total 50 μl volume by 31-gauge needle. Control animals were identically injected with PBS alone. Pups were euthanized and brains dissected at specified time points. Mouse TNFα was purchased from Genscript (Z02918) and administered to the resistant Ccm2ECKO neonatal CCM disease model under identical conditions as the IL-1β experiments. For all experiments using microCT quantification of CCM lesion volume, brains were harvested and immediately placed in 4% PFA/PBS fixative. Brains remained in fixative until staining with non-destructive, iodine contrast and subsequent microCT imaging performed as previously described47. All tissue processing, imaging and volume quantification were performed in a blinded manner by investigators at the University of Chicago without any knowledge of experimental details. We blinded samples at three distinct points in the analysis. First, neonatal CCM model pups were injected with 4OHT without knowledge of genotypes. Second, hindbrains from genotyped animals were given randomized, de-identified labels to provide for blinded microCT scanning by an independent operator. Third, randomized microCT image stacks were analysed in a blinded manner by individuals not involved in any prior experimental steps. Mice were anaesthetized with Avertin and underwent intra-cardic perfusion with 10 ml of cold PBS. The brain was separated from the brainstem, and the cerebellum was separated from the remaining brain and processed in parallel. The tissue was minced with scissors, placed in digestion buffer (RPMI, 20 mM HEPES, 10% FCS, 1 mM CaCl , 1 mM MgCl , 0.05 mg ml−1 Liberase (Sigma), 0.02 mg ml−1 DNase I (Sigma)), and incubated for 40 min at 37 °C with shaking at 200 r.p.m. The mixture was passed through a 100-μm strainer and washed with FACS buffer (PBS, 1% FBS). Cells were resuspended in 4 ml of 40% Percoll (GE Healthcare) and overlaid on 4 ml of 67% Percoll. Gradients were centrifuged at 400g for 20 min at 4 °C and cells at the interface were collected, washed with 10 ml of FACS buffer, and stained for flow cytometric analysis. Neonatal P10 mice were anaesthetized with Avertin and underwent intracardiac puncture/blood draw using a 27-gauge needle/syringe coated with 0.5 M EDTA, pH 8.0 immediately before use. Cells were pelleted by centrifugation at 300g for 5 min at 4 °C. Serum was removed and red blood cells were lysed using ACK lysis buffer. Spleens were dissected in parallel, hand-homogenized using a mini-pestle and red blood cells were lysed using ACK lysis buffer. Cells from both sets of tissues were passed through a 70-μm cell-strainer, pelleted and resuspended in FACS buffer (PBS, 2% FBS, 0.1% NaN ) for immunostaining and subsequent FACS analysis. Cells were isolated from the indicated tissues. Single-cell suspensions were stained with CD16/32 and with indicated fluorochrome-conjugated antibodies. Live/Dead Fixable Violet Cell Stain Kit (Invitrogen) was used to exclude non-viable cells. Multi-laser, flow cytometry analysis procedures were performed at the University of Pennsylvania Flow Cytometry and Cell Sorting Facility using BD LSRII cell analysers running FACSDiva software (BD Biosciences). Two-laser, flow cytometry analyses were performed at the University of Pennsylvania iPS Cell Core using BD Accuri C6 instruments. FlowJo software (v.10 TreeStar) was used for data analysis and graphics rendering. All fluorochrome-conjugated antibodies used are listed as follows (Clone, Company, Catalog Number): CD11b (M1/70, Biolegend, 101255); CD11c (N418, Biolegend, 117318); CD16/32 (93, Biolegend, 101319); CD16/32 (93, eBiosciences, 56D0161D80); CD19 (6D5, Biolegend, 115510); CD3ε (145D2C11, Biolegend, 100304); CD4 (GK1.5, Biolegend, 100406); CD45 (30-F11, Biolegend, 103121 or 103151), CD8a (53D6.7, Biolegend, 100725); Foxp3 (FJK-16 s, eBiosciences, 50-5773-82); Ly-6G (1A8, Biolegend, 127624); Live/Dead (N/A, Thermofisher, LD34966); NK1.1 (PK136, Biolegend, 108745); RORγt (B2D, eBiosciences, 12-6981-82); Siglec-F (E50D2440, BD, 562757); TCRγδ (UC7-13D5, Biolegend, 107504) At the specified time points, cerebellar endothelial cells were isolated through enzymatic digestion followed by separation using magnetic-activated cell sorting by anti-CD31-conjugated magnetic beads (MACS MS system, Miltenyl Biotec), as previously described9. Lung endothelial cells were isolated through enzymatic digestion, as previously described, followed by separation using anti-CD31-conjugated magnetic beads and the MACS MS system48. Isolated endothelial cells were pelleted and total RNA was extracted using the RNeasy Micro kit (Qiagen 74004). For qPCR analysis, cDNA was synthesized from 300 ng to 500 ng total RNA using the SuperScript VILO cDNA Synthesis Kit and Master Mix (Thermo Fisher 11755050). Real-time PCR was performed with Power SYBR Green PCR Master Mix (Thermo Fisher 4368577) using the primers listed (all mouse): Gapdh forward: 5′-AAATGGTGAAGGTCGGTGTGAACG-3′; Gapdh reverse: 5′-ATCTCCACTTTGCCACTGC-3′; Klf2 forward: 5′-CGCCTCGGGTTCATTTC-3′; Klf2 reverse: 5′-AGCCTATCTTGCCGTCCTTT-3′; Klf4 forward: 5′-GTGCCCCGACTAACCGTTG-3′; Klf4 reverse: 5′-GTCGTTGAACTCCTCGGTCT-3′; Krit1 forward: 5′-CCGACCTTCTCCCCTTGAAC-3′; Krit1 reverse: 5′-TCTTCCACAACGCTGCTCAT-3′; Il1b forward: 5′-GCAACTGTTCCTGAACTCAACT-3′; Il1b reverse: 5′-ATCTTTTGGGGTCCGTCAACT-3′; Sele forward: 5′-ATGCCTCGCGCTTTCTCTC-3′; Sele reverse: 5′-GTAGTCCCGCTGACAGTATGC-3′; Tlr4 forward: 5′-ACTGGGGACAATTCACTAGAGC-3′; Tlr4 reverse: 5′-GAGGCCAATTTTGTCTCCACA-3′. As part of the Brain Vascular Malformation Consortium (BVMC) CCM study (Project 1), a large cohort of familial CCM individuals with identical KRIT1(Q455X) mutations were enrolled between 2009–2014 at the University of New Mexico. All study protocols were approved by the Institutional Review Boards at the University of New Mexico and University of California San Francisco (UCSF) and all procedures were performed in accordance with these protocols. Prior to participation in the study, written informed consent was obtained from every patient and properly documented by UNM investigators. At study enrollment, participants received a neurological examination and 3T MRI imaging using a volume T1 acquisition (MPRAGE, 1-mm slice reconstruction) and axial TSE T2, T2 gradient recall, susceptibility-weighted, and FLAIR sequences. Lesion counting by the neuroradiologist was based on concurrent evaluation of axial susceptibility-weighted imaging with 1.5-mm reconstructed images and axial T2 gradient echo 3-mm images. Participants also provided blood or saliva samples for genetic studies. Genomic DNA was extracted using standard protocols. De-identified samples were normalized, plated on 96-well plates, and genotyped at the UCSF Genomics Core Facility using the Affymetrix Axiom Genome-wide LAT1 Human Array. Affymetrix Genotyping Console (GTC) 4.1 Software package was used to generate quality control metrics and genotype calls. All samples had genotyping call rates of ≥ 97% and were further checked for sample mix-ups (sex check, Mendelian errors and cryptic relatedness), resulting in 188 samples for genetic analysis. 21 candidate genes were further examined in the TLR4 and MEKK3–KLF2/4 signalling pathways (TLR4, CD14, MD-2, LBP, MYD88, TICAM1, TIRAP, TRAF1-6, MAP3K3, MEK5, ERK5, MEF2C, KLF2, KLF4, ADAMTS4, ADAMTS5) including 467 SNPs within 20 kb upstream or downstream of each gene locus using UCSC Genome Browser coordinates (GRCh37/hg19). Because total lesion counts are highly right-skewed, raw counts were log-transformed and analysis was performed on residuals (adjusted for age at enrollment and sex). To identify genotypes associated with log-transformed residual counts, linear regression analysis was implemented using QFAM family-based association tests for quantitative traits (PLINK v1.07 software), with stringent multiple testing correction (Bonferroni correction for the number of SNPs tested within each gene) given that some SNPs on the Affymetrix array were in linkage disequilibrium with each other, that is, statistically correlated with R2 > 0.8. The Fehrmann dataset used for eQTL lookups consisted of peripheral blood samples from the UK and the Netherlands49, 50. Samples were genotyped with Illumina HumanHap300, HumanHap370 or 610 Quad platforms. Genotypes were input by Impute v2 (ref. 51) using the GIANT 1000G p1v3 integrated call set for all ancestries as a reference52. Gene expression levels were measured by Illumina HT12v3 arrays. Gene expression pre-processing involved quantile normalization, log transformation, probe centring and scaling, population stratification correction (first four genetic multi-dimensional scaling components were removed from gene expression data) and correction for unknown confounders (first 20 gene expression principal components not associated with genetic variants were removed from gene expression data). Identification of potential sample mix-ups was conducted by MixupMapper21 and finally 1,227 samples remained. All pre-processing steps were performed with the QTL mapping pipeline v1.2.4D (https://github.com/molgenis/systemsgenetics/tree/master/eqtl-mapping-pipeline - downloading-the-software). These results are corroborated by an independently conducted GTEX Consortium study (http://www.gtexportal.org/home/snp/rs10759930 and http://www.gtexportal.org/home/snp/rs778587). TAK-242 was purchased from EMD Millipore (614316) and administered to the neonatal CCM disease model. Five, seven and nine days after birth, a 60-μg dose of TAK-242 was dissolved in DMSO/sterile intralipid (Sigma, I141) vehicle and administered retro-orbitally in a total volume of 30 μl. Control animals were identically injected with sterile DMSO/intralipid vehicle alone. Pups were euthanized and brains dissected 10 days after birth. LPS-RS ultrapure was purchased from Invivogen (tlrl-prslps) and administered to the neonatal CCM disease model. Starting at P5, a 20 μg dose dissolved in sterile PBS was administered retro-orbitally in a total volume of 30 μl every 24 h. Control animals were identically injected with sterile PBS alone. Pups were euthanized and brains dissected 10 days after birth. Experimental breeding pairs of mice, yielding susceptible neonatal CCM pups, were identified by induction of a neonatal CCM litter and evaluation of lesion burden. These breeding pairs then underwent timed matings and at E14.5, both male and female adult mice received antibiotic-laced drinking water mixed with 40 g l−1 of sucralose and red food colouring. Antibiotic water was replaced daily. The following antibiotics were mixed with 0.22-μm-filtered water: penicillin (500 mg l−1), neomycin (500 mg l−1), streptomycin (500 mg l−1), metronidazole (1 g l–1) and vancomycin (1 g l−1). Antibiotics were purchased from the Hospital of the University of Pennsylvania pharmacy. The neonatal CCM model was induced as described above. At P10, pups were euthanized and antibiotic water switched to normal drinking water. Experimental breeding pairs were then mated to obtain third generation, post-antibiotic pups. Co-housed, susceptible Krit1fl/fl females underwent evening–morning timed matings with a single susceptible Krit1ECKO male. Upon detection of a plug in the morning, the females were subsequently separated into singly-housed cages. At E14.5, female mice were received either vancomycin (1 g l−1)-laced or untreated (vehicle) sterile-filtered drinking water, changed daily. The drinking water was further mixed with 40 g l−1 sucralose and red food colouring. Pups were harvested at P11. The entire neonatal gut was dissected, snap-frozen on dry ice, and stored at −80 °C. The QIAamp DNA Stool Mini Kit (Qiagen 51504 or 51604) was used to extract bacterial DNA from the neonatal gut. Before commencing the standard Qiagen protocol, the frozen gut was mixed in the included stool lysis buffer and homogenized with a 5 mm stainless steel bead in a TissueLyser LT (Qiagen 69980) at 50 Hz for 10 min at 4 °C. Concentration of the extracted DNA was equalized and 16 ng of DNA was used per qPCR reaction with universal bacterial 16S rRNA gene primers53, two different sets of previously characterized Bacteroidetes s24-7 primers54, 55, and Firmicutes primers56. Universal 16S rRNA forward: 5′-ACTGAGAYACGGYCCA-3′; universal 16S rRNA reverse: 5′-TTACCGCGGCTGCTGGC-3′; Bacteroidetes s24-7 rRNA set 1 forward: 5′-GGAGAGTACCCGGAGAAAAAGC-3′; Bacteroidetes s24-7 rRNA set 1 reverse: 5′-TTCCGCATACTTCTCGCCCA-3′; Bacteroidetes s24-7 rRNA set 2 forward: 5′-CCAGCAGCCGCGGTAATA-3′; Bacteroidetes s24-7 rRNA set 2 reverse: 5′-CGCATTCCGCATACTTCTC-3′; Firmicutes rRNA forward: 5′-TGAAACTYAAAGGAATTGACG-3′; Firmicutes rRNA reverse: 5′-ACCATGCACCACCTGTC-3′. Evening–morning timed matings to generate donor susceptible or resistant females yielding Krit1ECKO or Ccm2ECKO pups were performed and timed pregnant Swiss Webster females (Charles River 024) served as foster mothers. To prevent delivery of the pups, at E16.5, donor females were injected subcutaneously with 100 μl of a 15 μg ml−1 solution of medroxyprogesterone (Sigma Aldrich, M1629) dissolved in DMSO. The morning of E19.5, the donor mother was euthanized by cervical dislocation and submerged in a warm sterile solution of 1% VirkonS/PBS (weight/volume) for one minute. The uterus was then dissected in a sterile laminar flow hood, submerged in a warm sterile solution of 1% VirkonS/PBS for one minute and quickly rinsed with warm sterile PBS. Pups were then removed from the uterus and fostered to the Swiss Webster recipient female. The following morning, induction of the neonatal CCM model was performed as described above. Timed matings were performed using germ-free Swiss Webster mice housed in sterile isolators under care of the University of Pennsylvania Gnotobiotic Mouse Facility. Simultaneous evening–morning timed matings were also performed using co-housed, susceptible Krit1fl/fl females and Krit1ECKO males previously characterized to yield CCM-susceptible pups. Medroxyprogesterone was administered to donor females and the sterile C-section was performed at E19.5 as described in the previous section. The intact uterus was passed through a J-tube filled with warm 1% VirkonS/PBS that was hermetically sealed to the sterile isolator. Pups were dissected from the uterus inside the sterile isolator and fostered to the recipient germ-free Swiss Webster mother. Approximately one week later, faecal samples were collected for microbiology testing. Germ-free status was further confirmed by 16S qPCR of bacterial DNA isolated from maternal faeces and neonatal guts. Fresh faecal pellets were collected from experimental females yielding susceptible or resistant pups one day after harvesting the pups to determine phenotypic severity. Collection was performed between 16:00 and 18:00, pellets were immediately snap-frozen on dry ice, and stored at −80 °C. DNA was extracted from stool samples using the Power Soil htp kit (Mo Bio Laboratories) following the manufacturer’s protocol. Library preparation was performed by using previously described barcoded primers targeting the V1/V2 region of the 16S rRNA gene57. PCR reactions were performed in quadruplicate using AccuPrime Taq DNA Polymerase High Fidelity (Invitrogen). Each PCR reaction consisted of 0.4 μM primers, 1× AccuPrime Buffer II, 1 U Taq, and 25 ng DNA. PCRs were run using the following parameters: 95 °C for 5 min; 20 cycles of 95 °C for 30 s, 56 °C for 30 s, and 72 °C for 90 s; and 72 °C for 8 min. Quadruplicate PCR reactions were pooled and products were purified using AMPureXP beads (Beckman-Coulter). Equimolar amounts from each sample were pooled to produce the final library. Positive and negative controls were carried through the amplification, purification and pooling procedures. Negative controls were used to assess reagent contamination and consisted of extraction blanks and DNA-free water. Positive controls were used to assess amplification and sequencing quality and consisted of gBlock DNA (Integrated DNA Technologies) containing non-bacterial 16S rRNA gene sequences flanked by bacterial V1 and V2 primer binding sites. Paired-end 2 × 250 bp sequence reads were obtained from the MiSeq (Illumina) using the 500 cycle v2 kit (Illumina). Sequence data were processed using QIIME version 1.9.1 (ref. 58). Read pairs were joined to form a complete V1/V2 amplicon sequence. Resulting sequences were quality filtered and demultiplexed. Operational taxonomic units (OTUs) were selected by clustering reads at 97% sequence similarity59. Taxonomy was assigned to each OTU with a 90% sequence similarity threshold using the Greengenes reference database60. A phylogenetic tree was inferred from the OTU data using FastTree61. The phylogenetic tree was then used to calculate weighted and unweighted UniFrac distances between each pair of samples in the study62, 63. Microbiome compositional differences were visualized using principle coordinates analysis (PCoA). Community-level differences between mice genetic background as well as disease susceptibility groups were assessed using a PERMANOVA test64 of weighted and unweighted UniFrac distances. To assess significance in the PERMANOVA test, each cage was randomly re-assigned to groups 9,999 times. Differential abundance was assessed for taxa present in at least 80% of the samples, using generalized linear mixed-effects models. For tests of taxon abundance, the cage was modelled as a random effect, as previous research has established that the faecal microbiota of mice are correlated within cages65. The P values were corrected for multiple testing using Benjamini–Hochberg method. Sample sizes were estimated on the basis of our previous experience with the neonatal CCM model and lesion volume quantification by microCT9. Using 40 historically collected, susceptible Krit1ECKO and Ccm2ECKO P10 brains, we calculated a sample standard deviation of 0.250 mm3. Between Krit1ECKO and Ccm2ECKO genotypes, an F-test to compare variances confirmed no significant difference (P = 0.340). Thus, for a two-group comparison of lesion volumes, each sample group requires seven animals for a desired statistical power of 95% (β = 0.05), and a conventional significance threshold of 5% (α = 0.05) assuming an effect size of 50% (0.5) and equal standard deviations between sample groups. These predictive calculations were corroborated by our recent publication in which larger effect sizes (>90%) were found to be statistically significant with four to five samples per group9. All experimental and control animals were littermates and none were excluded from analysis at the time of harvest. Experimental animals were lost or excluded at two pre-defined points: (i) failure to properly inject 4OHT and observation of significant leakage; (ii) death before P10 because of injection or chaos. Given the early time points, no attempt was made to distinguish or segregate results based on neonatal genders. P values were calculated as indicated in figure legends using an unpaired, two-tailed Student’s t-test; one-way ANOVA with multiple comparison corrections (Holm–Sidak or Bonferroni); PERMANOVA; or linear mixed effects modelling. As indicated in the figure legends, the standard error of the mean (s.e.m.), 95% confidence interval, or boxplot is shown. All relevant data are available from the authors upon reasonable request.


News Article | May 24, 2017
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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. All animal experiments were performed under the approval of Weill Cornell Medicine Institutional Animal Care and Use Committee. We used Runx1-IRES-GFP (Runx1tm4Dow) mice, provided by J. Downing (St Jude Hospital). These were crossed with Rosa26 rtTa mice (B6.Cg-Gt(ROSA)26Sortm1(rtTA*M2)Jae/J, Jackson laboratory, strain 006965) to produce Runx1-IRES-GFP;Rosa26-rtTa mice (referred to as Runx1), and maintained as heterozygous for both Runx1-IRES-GFP and rtTa. Floxed Cxcr4 mice were obtained from Y.-R. Zou (Feinstein Institute for Medical Research). Floxed Cxcr4 mice were crossed with Runx1-IRES-GFP;Rosa26-rtTa mice to produce Cxcr4fl/fl;Runx1-IRES-GFP+/−;Rosa26-rtTa mice. Rag1−/− mice with the genotype of B6.129S7-Rag1tm1Mom/J were obtained from the Jackson Laboratory (strain 002216). For rEC-HSPC transplantation, we used CD45.1+ congenic 10–12-week-old male recipients (B6.SJL-Ptprca Pepcb/BoyJ). These mice are referred here as CD45.1+ recipients, Jackson Laboratory, strain 002014. All cell preparations were routinely tested for mycoplasma contamination. To distinguish between vascular mECs and lymphatic endothelial cells, we performed intravital staining by injecting 25 μg of anti-VE-cadherin-AF647 antibody (clone BV13, Biolegend) retro-orbitally in 8–10-week-old male C57BL/6J (CD45.2+) mice under anaesthesia 8 min before they were killed and the organs harvested. For flow cytometry and cell sorting, organs, including lungs, brain, kidney and liver were minced and incubated with collagenase A (25 mg ml−1), dispase II (25 mg ml−1), and DNase (250 μg ml−1) (Roche) at 37 °C for 20–30 min to create a single-cell suspension. Cells were filtered through a 40-μm filter immediately before counter staining. The single-cell suspension was first blocked with an antibody against CD16/32 (2.4G2) before antibody staining with anti-mouse CD31-PE-Cy7 (390, Biolegend), anti-mouse TER119 (TER119) and anti-mouse CD45 (30-F11). Haematopoietic and erythroid cells were removed via CD45 and TER119 gate exclusion, and adult mouse endothelial cells (mECs) were defined and sorted as VEcad+CD31+CD45−TER119− cells. Resulting adult mEC cultures were cultured on fibronectin-coated (Sigma-Aldrich) plates in mEC media. Purity of mECs and absence of contaminating haematopoietic cells were confirmed by flow cytometry and confocal microscopy. Human umbilical vein endothelial cells (HUVECs) were isolated as described29, 40 and cultured in endothelial cell growth medium. Once endothelial cells were transduced with lentiviral vectors expressing E4ORF1 gene they were then cultured in human endothelial cell media (M199 (Sigma, M4530), 10% FBS (Omega Scientific, FB07), 50 μg ml−1 endothelial mitogen (Alfa Aesar J65416), and 100 μg ml−1 heparin (Sigma, H3393)11, 13, 28, 29. E4ORF1 confers endothelial cells with the capacity to survive in the absence of serum and exogenous growth factors, while sustaining the pre-determined endothelial cell signatures and repertoire of the pro-haematopoietic angiocrine factors. The aforementioned conversion experiments with FGRS transduction of endothelial cells would not be possible without use of HUVEC-E4ORF1 vascular-niche cells (VN-ECs) as reprogramming in the presence of serum there is no conversion of endothelial cells into haematopoietic cells9. Thus, because E4ORF1 allows endothelial cells to survive and perform as inductive vascular-niche cells, this platform enables FGRS-driven conversion of adult endothelial cells without the supplementation with xenobiotic factors, serum or exogenous angiogenic growth factors. Both serum and angiogenic growth factors could interfere with and complicate the conversion of the endothelial cells into haematopoietic cells, by aberrantly interfering with the survival, self-renewal and expansion of the converted endothelial cells into haematopoietic cells (rEC-HSPCs and rEC-HSCs). Indeed, in the presence of serum the conversion of endothelial cells to HSPCs or HSCs is completely blocked9. All niche-dependent experiments described herein were performed by using HUVEC-derived E4ORF1+ endothelial cells (VN-ECs, HUVEC-E4ORF1, Angiocrine Bioscience)11, 13, 19, 28, 29 as a vascular-niche feeder monolayer, except as specifically noted. Open reading frames (Fosb: NM_008036.2, Gfi1: NM_010278.1, Runx1 (Runx1b isoform): NM_001111022.2, Sfpi1: BC003815.1) were cloned into pLVx TET-3G lentiviral plasmid. Lentiviruses (LV) were produced were cloned into doxycycline-inducible pLVx TET-3G lentiviral plasmids. Lentiviral vectors expressing Cxcl12 (NM_001012477.2) were obtained from Cyagen (pLV(Exp)-Neo-EF1A>mCxcl12:IRES:EBFP). Viral particles were produced in the HEK 293T Lenti-X cell line (Clontech, 632180) using Lenti-X packaging single shot (Clontech, 631275) following the manufacturer’s instructions, and titred using Lenti-X p24 Rapid Titer Kit (Clontech, 632200). Transduction was carried out in 6-well plates. Doxycycline (dox) (Sigma-Aldrich) was added at a concentration of 1 μg ml−1 for FGRS transgene induction. Adult mECs were directly converted into haematopoietic cells by conditional enforced expression of transcription factors followed by replating onto a serum-free inductive vascular niche (VN-ECs, HUVEC-E4ORF1). Purified populations of VEcad+CD31+CD45−TER119− mECs were cultured in the mEC growth medium, consisting of DMEM:Ham’s F-12 (Sigma, D6421) supplemented with 20% FBS (Omega Scientific, FB07), 20 mM HEPES (Invitrogen, 15630080), 100 μg ml−1 heparin (Sigma, H3393), 50 μg ml−1 endothelial mitogen (Alfa Aesar J65416) and 5 μM SB431542 (R&D, 1614), in a humidified incubator at 37 °C, 5% CO and normoxia 5% O . Then, adult mECs were transduced with doxycycline-inducible TET-3G lentiviral vectors for a combination of transcription factors and the reverse tetracycline-controlled trans-activator—FosB, Gfi1, Runx1, Spi1 (FGRS), and rtTA—and maintained in mEC media for 3 days. FGRS-ECs were then selected for rtTA expression by puromycin resistance. 72 h after puromycin selection, FGRS expression was induced by adding 1 μg ml−1 dox in mEC media for 48 h. Dox was added every 24 h. FGRS-ECs were then reseeded onto confluent VN-EC monolayers supplemented with conversion media (StemSpan SFEM, STEMCELL Technologies, 09650), 10% KnockOut Serum Replacement (Invitrogen, 10828028), 10 ng ml−1 hFGF-2 (bFGF, Peprotech, 100-18), 50 ng ml−1 mouse c-Kit ligand (SCF, Peprotech, 250-03). Conversion media was then replaced every 48 h. Adult organs, including lung, brain, liver and kidney VEcad+CD31+CD45− (C57BL/6J CD45.2 background) mECs were purified to remove contaminating lymphoid endothelial cells and haematopoietic cells. After cultivation for 30 days, pure populations of mECs were then used for direct conversion into HSPCs (rEC-HSPCs) and HSCs (rEC-HSCs), as described above. Adult lung mECs, devoid of any haematopoietic cells, were primarily used to assess the capacity of the rEC-HSPC and rEC-HSCs to reconstitute primary and secondary, clonal and serial haematopoietic transplantations. On day 28, FGRS-ECs and residual VN-ECs were transplanted at 8.0 × 105 cells per recipient into lethally irradiated (950 cGy) congenic recipients. Dox was not administered in the drinking water to ensure no exogenous FGRS expression during the transplant. Serial transplantation from reprogrammed adult lung mECs to HSPCs experiments were performed by transplanting 1.0 × 107 unfractionated bone marrow cells into secondary recipients (CD45.1+ or Rag1−/−). Serial transplantation of unfractionated whole bone marrow cells (WBM) from C57BL/6J (CD45.2+) were used as controls. In all transplant experiments, peripheral blood and bone marrow analysis was performed at 4-week intervals with antibodies against c-Kit/CD117 (2B8), Sca-1/Ly-6A (D7), CD48 (HM48-1), and CD150 (mShad150). Lineage antibody cocktail included: CD41 (MWReg30) TER119 (TER119), B220 (RA3-6B2), CD11b (M1/70), Gr1 (RB6-8C5), CD3 (17A2), CD4 (GK1.5), CD8 (YTS156.7.7), CD44 (IM7), CD62l (MEL-14), CD25 (3C7), FoxP3 (150D), TCRγδ (GL3), CD45.1 (A20), CD45.2 (104), and DAPI to discriminate and eliminate dead cells from analysis. All antibodies were obtained from Biolegend unless mentioned. For calculation of competitive repopulating units (CRU), recipient mice were transplanted with limiting dilutions of donor-LKS cells (1 to 4,500) together with 500,000 recipient-derived bone marrow cells. Mice were bled every 4 weeks and killed after 16 weeks. Multi-lineage myelo-lymphoid donor-derived contribution in the peripheral blood was assessed using flow cytometry analysis. HSC-CRU frequency and statistical significance was determined using ELDA software (http://bioinf.wehi.edu.au/software/elda/). Samples were permeabilized in PBST and blocked in 5% donkey serum. Samples were incubated for 2 h in primary antibodies blocking solution, washed 3 times in PBS and incubated in secondary antibodies (Jackson Laboratories) for 1 h. Following washing, some sections were counterstained for nucleic acids by DAPI (Invitrogen) before mounting and imaging by confocal microscopy. The primary antibodies used for immunostaining are listed in the previous section. All imaging was performed using a Zeiss 710 META confocal microscope. At least 100 ng of total RNA from both freshly harvested and cultured cells was isolated (phenol-chloroform separation of TRIzol LS) and purified using Qiagen RNeasy Mini Kit. RNA quality was verified using an Agilent Technologies 2100 Bioanalyzer. RNA library preps were prepared and multiplexed using Illumina TruSeq RNA Library Preparation Kit v2 (non-stranded and poly-A selection) and 10 nM of cDNA was used as input for high-throughput sequencing via Illumina’s HiSeq 2500 producing 51 bp paired-end reads. Sequencing reads were de-multiplexed (bcl2fastq v2.17), checked for quality (FastQC v0.11.5), and trimmed/filtered when appropriate (Trimmomatic v0.36). The resultant high-quality reads were mapped (TopHat2 v2.1.0; Bowtie2 v2.2.6) to the transcriptome sequence reference of the UCSC mm10 genome build. Unique and multi-mapped reads were then assembled into transcripts, and abundance measures (FPKM values) quantified (Cufflinks v2.2.1). All subsequent transcriptome data analysis utilized the estimated measurements of transcripts abundance (that is, FPKMs). Genes with FPKM < 1 were filtered out, and log -transformed FPKM values were used for principal component analysis and hierarchical clustering. Transcriptome-wide and gene-set-specific analysis of the RNA-seq expression dataset were summarized and represented in the forms of scatter plots, dendrograms, and heatmaps. TCR repertoire analysis on RNA-seq reads were performed by custom BLAST-mapping. The reads were submitted for nucleotide BLAST-mapping against custom databases comprising TCR Vα genes, Vβ genes, Cα genes, and Cβ genes downloaded from IMGT (http://www.imgt.org). A table of the counts of reads meeting BLAST-expected value cutoffs for each α and β variable and constant gene was formulated for each sample and normalized to counts per million sequenced reads. The Relative Shannon Index was calculated using the Shannon entropy of the counts of TCR Vβ genes normalized by the logarithm of the number of different Vβ genes occurring in each sample and P values showing differences in the Relative Shannon Index were calculated using the Wilcoxon rank-sum test. Heatmaps and clustering were then performed in R using ‘heatmap.2’ function from gplots package. RNA was isolated from CD45.2+CD3+CD8+ and CD45.2+CD3+CD4+ sorted T lymphocytes from peripheral blood (1 × 105 cells) with TRIzol (Invitrogen; 15596-026). The diversity of CDR3 regions for 24 TCR Vβ regions was assessed with the TCRExpress Quantitative Analysis Kit (Biomed Immunotech; H0533) per the manufacturer’s instructions. BALB/c peripheral blood cells were labelled with the fluorescent membrane dye PKH26 (Sigma, PKH26GL) to distinguish them from effector cells (FGRS-CD45.2+CD3+CD8+ T cells) upon FACS analysis according to the manufacturer’s instructions. Wells of 24-well culture plates were seeded with 1 × 104 dye-labelled BALB/c peripheral blood cells; 2–3 h later, 500 μl of FGRS-CD45.2+CD3+CD8+ T cells pre-activated for 8 h with anti-CD3/CD28 beads according to the manufacturer’s instructions (Miltenyi, 130-097-627), as described in ref. 41. Reactions were performed in presence of 10 U ml−1 of IL-2 with effector:target ratios of 1:2, 1:5, 1:10, 1:25, 1:50, 1 :100. Samples were analysed using a SORP-LSR2 flow cytometer (BD Biosciences). All cytotoxicity assays were performed in triplicate. Dead target cells were defined as PKH26−DAPI+CD45.2− cells. Mice transplanted with either rEC-HSPCs or WBM mononuclear haematopoietic cells were injected with full-length chicken OVA emulsified in complete Freund’s adjuvant (CFA) subcutaneously at two sites on the back, injecting 0.1 mg at each site. A booster injection of OVA emulsified in incomplete Freund’s adjuvant (IFA) was administered 14 days after immunization with ovalbumin/CFA emulsion. The booster is given as a single subcutaneous injection with 0.1 ml of IFA emulsion, at one site on the back. (1) Adult mECs were purified by multicolour flow cytometry to eliminate contaminating lymphatic endothelial cells, pericytes, mesenchymal, and especially haematopoietic cells. To rule out the possibility of contamination with host-derived haematopoietic cells, freshly sorted mECs (8 × 105 cells from the CD45.2 strain) were transplanted into lethally irradiated (950 cGy) 10 to 12 weeks CD45.1+ male recipients with 500,000 radio-protective CD45.1+ bone marrow haematopoietic cells. CD45.1+ recipient mice were assessed for CD45.2+ engraftment with contaminating HSPCs cells, as described above in section transplantation assays. (2) To demonstrate that the freshly isolated mEC expansion culture conditions, not supplemented with haematopoietic cytokines, will prevent proliferation or survival of any contaminating haematopoietic cells, limiting dilutions of CD45.2+ wild-type LKS-SLAM cells were introduced into mEC expansion cultures. In these experiments LKS-SLAM cells were transduced with FGRS transgenes to rule out the possibility that these factors will enhance LKS-SLAM cell survival and expansion and seeded in limiting dilution on top of mEC–VN-EC co-culture. As per conversion protocol, these cultures were grown in mEC media (absent haematopoietic cytokines) for 4 weeks. ‘Contaminated’ mEC–VN-EC co-cultures were then grown in conversion media for 28 days. The resulting cultures were transplanted into three lethally irradiated (950 cGy) CD45.1+ male recipient mice with 500,000 CD45.1+ bone marrow haematopoietic cells to demonstrate that LKS-SLAM cells could not survive such haematopoietic intolerant culture conditions. (3) Purified mECs were expanded for conversion experiments routinely for 30 days in mEC media in complete absence of haematopoietic cytokines. Then, mECs were transduced with dox-inducible FGRS transgenes but were never exposed to dox (no-dox) and therefore never expressed FGRS transgenes. 8 × 105 cultured no-dox FGRS-transgene-transduced 30-day-expanded mECs were transplanted into lethally irradiated (950 cGy) recipient mice in a rescue dose setting to rule out existence of any contaminating haematopoietic cells. Recipient CD45.1+ transplanted mice were assessed for survival. (4) It is possible that if any host HSPCs could survive the intolerant 30 days of mEC culturing, upon FGRS transduction these contaminating HSPCs might revert to functional HSPCs or HSCs. To disprove this possibility, and mimic the standard procedure used in isolation of adult mouse lung mECs, we re-expressed FGRS in terminally differentiated CD45.2+ haematopoietic cells (TER119+, Gr1+CD11b+, B220+, CD3+) isolated from lungs of CD45.2+ rEC-HSPC week 16 secondary engrafted recipients. To this end, 150,000 terminally differentiated CD45.2+ (TER119+, Gr1+CD11b+, B220+, CD3+) were cultured for 28 days in conversion media in presence of doxycycline in co-culture with VN-ECs. Resulting cultures were transplanted into three lethally irradiated (950 cGy) CD45.1+ male recipient mice with 500,000 radio-protective bone marrow haematopoietic cells. Then, the recipient CD45.1+ transplanted mice were assessed for CD45.2+ engraftment as described above in the section on transplantation assays. (5) If host HSPC contamination contributes to rEC-HSPCs and rEC-HSCs, then there should be no hierarchical FGRS-dependence induction, specification or expansion phases during rEC-HSPC generation. In addition, within the first 8 days of culture (induction phase), the contaminating HSPCs should give rise to engraftable HSPCs. To assess this, dox-on FGRS-transduced mECs were passaged through stepwise shutting-off FGRS expression either during the induction, specification or expansion phases. The number of rEC-HSCs and rEC-HSPCs at each stage were then quantified, as described above. Adult lung mECs (VEcad+CD31+CD45−) were isolated from Runx1-IRES-GFP mice. VN-ECs were discriminated from Runx1-IRES-GFP-FGRS-ECs by anti-human CD31 (hCD31). Expression of VEcad and CD45 in Runx1-IRES-GFP-FGRS-ECs and derivatives were monitored during endothelial cell to haematopoietic cell reprogramming. Adult mECs were treated with different small molecules at their known IC on mouse endothelial cells (CXCR4 antagonist, AMD3100 = 44 μmol l−1; CXCR7 agonist, TC14012 = 350 nmol l−1; BMP antagonist, Noggin = 0.5 μg ml−1; TGFβ antagonist, SB431542 = 10 μmol l−1). Toxicity of each small molecule was assessed by annexin V/DAPI staining 48 h after the first treatment, as well as population-doubling time. Relative CD45+ percentages were then acquired by flow cytometry at day 28. Adult lung mECs were generated from Runx1-IRES-GFP-Cxcr4fl/fl. Cxcr4−/− endothelial cells were generated by transduction with LV-CMV-Cre-Puro lentivirus (SignaGen, SL100272) followed by 7 days of puromycin selection. Cxcr4fl/fl and Cxcr4−/− endothelial cells were transduced with FGRS along with VN-EC induction and converted. Then, the frequency and functionality of the emerging CD45+ rEC-HSPCs and rEC-HSCs were assessed, as described above, by performing phenotypic flow cytometry. We analysed recipient organ architecture and histological profile after 20 weeks of primary or secondary transplantation for any evidence of malignant alterations. For each organ, including bone marrow, lung, kidney, spleen, liver, intestine and brain, Wright–Giemsa, Masson and PicroSirius Red staining were performed on 10-μm paraffin-embedded sections (Histoserv). All images were acquired using a colour CCD camera. The primer (Integrated DNA) sets used to detect each sequence were as follows. B1 repeated sequence: 5′-GTGGTGGCGCACGCCT-3′ and 5′-TAGCCCTGGCTGTCCTGGAA-3′; LTR: 5′-TCCACAGATCAAGGATATCTTGTC-3′. Reactions contained 1× Taqman universal master mix (Perkin-Elmer), 300 nM forward primer, 300 nM reverse primer, 100 nM probe primer and 100−500 ng of template DNA in a 30-μl volume. After initial incubations at 50 °C for 2 min and 95 °C for 10 min, 40 cycles of amplification were carried out at 15 s at 95 °C followed by 1 min 30 s at 60 °C. PCR products were then analysed on a 4% TBE–EtBR gel. All data are presented as either median ± s.e.m., mean ± s.d., or mean ± s.e.m. (as indicated in figure legends). The data presented in the figures reflect multiple independent experiments performed on different days using different mice. Unless otherwise mentioned, most of the data presented in figure panels are based on at least three independent experiments. The significance of differences was determined using a two-tailed Student’s t-test, unless otherwise stated. P > 0.05 was considered not significant; *P < 0.05; **P < 0.01; ***P < 0.001. In all the figures, n refers to the number of mice when applicable. All statistical analyses were performed using Graphpad Prism software. No animals were excluded from analyses. Sample sizes were selected on the basis of previous experiments. Unless otherwise indicated, results are based on three independent experiments to guarantee reproducibility of findings. The RNA sequencing dataset was submitted to the Gene Expression Omnibus database with accession number GSE88840. Source Data for this study are included in the online version of the paper. Single-cell RNA-seq datasets for embryonic day 11 (E11) aorta–gonad–mesonephros endothelium, E11 CD201− pre-HSC type 1, E11 CD201+ pre-HSC type 1, E11 CD201+ pre-HSC type 2, E12.5 fetal liver HSCs (lin−Sca-1+Mac1loCD201+), E14.5 fetal liver HSCs (lin−CD45+CD150+CD48−CD201−), adult bone marrow HSCs (LKS-SLAM) were obtained from ref. 31 (GSE67120); the LKS-SLAM RNA-seq datasets were obtained from ref. 32 (GSE60808); embryonic-stem-cell-derived endothelial cells, embryonic stem cell RNA-seq datasets were obtained from ref. 42. A step-by-step protocol describing in vitro conversion of endothelial cells into HSCs can be found at Protocol Exchange43.


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TCR transgenic mice (B6.Cg-Tg(TcraY1,TcrbY1)416Tev/J)12, Cre-ERT2 (B6.129-Gt(ROSA)26Sortm1(cre/ERT2)Tyj/J), Alb-Cre (B6.Cg-Tg(Alb-cre)21Mgn/J), TCR-OT1 (C57BL/6-Tg(TcraTcrb)1100Mjb/J), Ly5.1 (B6.SJL-Ptprca Pepcb/BoyJ), and C57BL/6J Thy1.1 mice were purchased from The Jackson Laboratory. TCR mice were crossed to Thy.1.1 mice to generate TCR Thy.1.1 mice. TCR-OT1 were crossed to Ly5.1 mice to generate TCR-OT1 Ly5.1 mice. AST (Albumin-floxStop-SV40 large T antigen (TAG))33 were crossed to Cre-ERT2 or Alb-Cre mice to obtain AST-Cre-ERT2 and AST-Alb-Cre mice, respectively6. Both female and male mice were used for studies. Mice were age- and sex-matched and between 1.5–3 months old when used for experiments. Animals were assigned randomly to experimental groups. All mice were bred and maintained in the animal facility at Memorial Sloan Kettering Cancer Center (MSKCC). Experiments were performed in compliance with the MSKCC Institutional Animal Care and Use Committee (IACUC) regulations. Fluorochrome-conjugated antibodies were purchased from BD Biosciences, eBioscience, Biolegend, and Cell Signaling Technology. Tamoxifen (Sigma) stock solution was prepared by warming tamoxifen in 1 ml sterile corn oil at 50 °C for 15 min, then further diluted in corn oil to obtain the stock concentration (5 mg ml−1 in corn oil). A single dose of tamoxifen (1 mg) was administered intraperitoneally (i.p.) into AST-Cre-ERT2 mice. Intracellular cytokine staining was performed using the Cytofix/Cytoperm Plus kit (BD Biosciences) per the manufacturer’s instructions. In brief, T cells were mixed with 2 × 106 congenically marked splenocytes and incubated with Tag-I peptide (0.5 μg ml−1) or OVA peptide (0.1 μg ml−1) for 4–5 h at 37 °C in the presence of GolgiPlug (brefeldin A). After staining for cell-surface molecules, the cells were fixed, permeabilized, and stained with antibodies against IFNγ (XMG1.2) and TNFα (MP6-XT22). Flow cytometric analysis was performed using Fortessa and LSR FACS analysers (BD Biosciences); cells were sorted using BD FACS Aria (BD Biosciences) at the MSKCC Flow Core Facility. Flow data were analysed with FlowJo v. 10 software (Tree Star Inc.). The Listeria monocytogenes (Lm) ΔactA ΔinlB strain13 expressing the Tag-I epitope (SAINNYAQKL, SV40 large T antigen ) was generated by Aduro Biotech as previously described34. Experimental vaccination stocks were prepared by growing bacteria to early stationary phase, washing in phosphate buffered saline, formulated at approximately 1 × 1010 colony-forming units (c.f.u.) ml−1, and stored at −80 °C. Mice were infected i.p. with 5 × 106 c.f.u. of LmTAG. For the generation of effector and memory TCR CD8+ T cells, 105 CD8+ splenocytes from TCR Thy1.1 transgenic mice were adoptively transferred into B6 (Thy1.2) mice; one day later, mice were infected with 5 × 106 c.f.u. LmTAG. Effector TCR CD8+ T cells were isolated from the spleens of B6 host mice and analysed 5 or 7 days after LmTAG immunization; memory TCR CD8+ T cells were isolated from spleens of B6 host mice and analysed at least 2–3 months after LmTAG immunization. For the transfer of naive TCR T cells into AST-Cre-ERT2 mice, 1 × 105 to 2.5 × 106 CD8+ splenocytes from TCR Thy1.1 transgenic mice were adoptively transferred into AST-Cre-ERT2 mice; 1 day later, mice were treated with 1 mg tamoxifen and donor T cells isolated for subsequent analyses. For memory TCR transfer experiments (3–4) × 104 TCR Thy1.1+CD44hiCD62Lhi sorted central memory CD8 T cells were adoptively transferred into AST-Alb-Cre mice; one day later, mice were infected with 5 × 106 c.f.u. LmTAG (105 central memory T cells were sorted and transferred for experiments without subsequent listeria immunization). 5 × 105 to 1 × 106 B16 tumour cells expressing OVA (full-length or cytosolic as previously described35) were injected into C57BL/6J wild-type mice. Once tumours were established (1–2 weeks later) naive Ly5.1 congenically marked TCR CD8 T cells were adoptively transferred and isolated from tumours at indicated time points. Tumour volumes did not exceed the permitted volumes specified by the MSKCC IACUC protocol. The B16 cell line was obtained from ATCC. It was tested negative for all rodent pathogens including Mycoplasma pulmonis. Spleens were mechanically disrupted with the back of a 3-ml syringe, filtered through a 70-μm strainer, and red blood cells were lysed with ammonium chloride potassium buffer. Cells were washed twice with cold RPMI 1640 media supplemented with 2 μM glutamine, 100 U ml−1 penicillin/streptomycin, and 5–10% FCS (cRPMI). Liver tissue was mechanically disrupted to a single-cell suspension using a 150 μ metal mesh and glass pestle in ice-cold 3% FCS/HBSS and passed through a 70-μm strainer. The liver homogenate was spun down at 400g for 5 min at 4 °C, and the pellet was resuspended in 30 ml 3% FCS/HBSS, 500 μl (500 U) heparin, and 17 ml Percoll (GE), mixed by inversion, and spun at 500g for 10 min at 4 °C. Pellet was lysed with ammonium chloride potassium buffer and cells were further processed for downstream applications. TCR or TCR cells were isolated from tumours at various time points after transfer and cultured in vitro in the presence of IL-15 (100 ng ml−1) in cRPMI for 3–4 days. Naive TCR (Thy1.1+) cells were transferred into AST-Cre-ERT2 (Thy1.2+) mice which were treated with tamoxifen one day later. On days 2–9, mice were treated with the calcineurin inhibitor FK506 (Prograf, 5 mg ml−1) (2.5 mg per kg per mouse i.p. once daily) alone, or in combination with the GSK3β inhibitor TWS119 (Sigma; 0.75 mg per mouse i.p. once daily; days 5–8). Control mice were treated with PBS and/or DMSO. Human tumour samples and healthy donor peripheral blood lymphocytes were obtained as per protocols approved by the MSKCC Institutional Review Board (IRB), and all patient and healthy donors provided informed consent. Peripheral blood lymphocytes were flow-sorted for naive, effector memory-like and central memory-like phenotypes as described in Extended Data Fig. 10a. Human melanoma and lung tumours were mechanically disrupted as described for solid tumours in mice, and CD45RO+PDhiCD8+ T cells were flow-sorted for subsequent ATAC-seq analysis. Statistical analyses on flow cytometric data were performed using unpaired two-tailed Student’s t tests (Prism 6.0, GraphPad Software). A P value of <0.05 was considered statistically significant. Mouse samples: replicate samples were isolated from spleens or livers and sorted as follows. (i) Naive TCR Thy1.1+ T cells were sorted by flow cytometry (CD8+CD44lo) from spleens of TCR Thy1.1 transgenic mice. (ii) Day 5 and day 7 effector, and memory TCR Thy1.1+ T cells were sorted by flow cytometry (CD8+Thy1.1+) from spleens of infected B6 (Thy1.2) host mice (see above) 5 and 7 days or 2–3 months after listeria infection. (iii) TCR Thy1.1+ T cells from pre/early malignant liver lesions: naive TCR Thy1.1+ T cells were adoptively transferred into AST-Cre-ERT2 mice. 1 day later, mice were given 1 mg tamoxifen i.p. At given time points after tamoxifen treatment, T cells were isolated and sorted (CD8+Thy1.1+) from livers as described above. (iv) TCR Thy1.1+ memory T cells from established hepatocellular carcinomas in AST-Alb-Cre mice: TCR memory T cells were isolated from tumours and flow sorted (CD8+Thy1.1+) as described above. Human samples: samples were flow-sorted as described in Extended Data Fig. 10a. After flow-sorting, all samples for downstream ATAC-seq analysis were frozen in 10% DMSO/FCS and stored at −80 °C; samples for RNA-seq were directly sorted into Trizol and frozen and stored at −80 °C. RNA from sorted cells was extracted using RNeasy mini kit (Qiagen) as per instructions provided by the manufacturer. After ribogreen quantification and quality control of Agilent BioAnalyzer, 6–15 ng of total RNA was amplified (12 cycles) using the SMART-seq V4 (Clontech) ultralow input RNA kit for sequencing. 10 ng of amplified cDNA was used to prepare Illumina hiseq libraries with the Kapa DNA library preparation chemistry (Kapa Biosystems) using 8 cycles of PCR. Samples were barcoded and run on a Hiseq 2500 1T in a 50 bp/50 bp Paired end run, using the TruSeq SBS Kit v3 (Illumina). An average of 51 million paired reads were generated per sample and the percent of mRNA bases was 62.5% on average. Chromatin profiling was performed by ATAC-seq as described previously11. In brief, 12,000 to 50,000 cells were washed in cold PBS and lysed. Transposition was performed at 42 °C for 45 min. After purification of the DNA with the MinElute PCR purification kit (Qiagen), material was amplified for 5 cycles. Additional PCR cycles were evaluated by real time PCR. Final product was cleaned by Ampure Beads at a 1.5× ratio. Libraries were sequenced on a Hiseq 2500 1T in a 50 bp/50 bp Paired end run, using the TruSeq SBS Kit v3 (Illumina). An average of 47 × 106 paired reads was generated per sample. Raw ATAC-seq reads were trimmed and filtered for quality using Trim Galore! v0.4.0 (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/), powered by CutAdapt v1.8.1 (http://dx.doi.org/10.14806/ej.17.1.200) and FastQC v0.11.3 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Paired-end reads were aligned using Bowtie2 v2.2.5 (ref. 36) against either mm10 or hg38 and non-uniquely mapping reads were removed. To correct for the fact that the Tn5 transposase binds as a dimer and inserts two adapters in the Tn5 tagmentation step37, all positive-strand reads were shifted 4 bp downstream and all negative-strand reads were shifted 5 bp upstream to centre the reads on the transposon binding event11. We then pooled the shifted reads by sample type and identified peaks using MACS2 (ref. 38) with a threshold of FDR-corrected P < 1 × 10−2 using the Benjamini–Hochberg procedure for multiple hypothesis correction. As called peaks may be caused by noise in the assay and not reflect true chromatin accessibility, we calculated an irreproducible discovery rate (IDR)39 for all pairs of replicates across a cell type. The IDR is an estimate of the threshold where two ranked lists of results, in this case peak calls ranked by P value, no longer represent reproducible events. Using this measure, we excluded peaks that were not reproducible (IDR < 5 × 10−3) across at least one pair of replicates in each mouse or human cell type. Peaks found reproducibly in each mouse cell type were combined to create a genome-wide atlas of accessible chromatin regions. Reproducible peaks from different samples were merged if they overlapped by more than 75%. To create the atlas of accessible peaks for the human samples, reproducible peaks from the normal human cell types (HN, HCM, and HEM) and the tumour-derived cells (PD1hi) were combined. There was greater variation between the human TIL samples than between T cell samples from healthy donors; this led to fewer reproducible peaks being called in the TIL samples. Like the mouse atlas, peaks overlapping by more than 75% were merged in the human atlas. Numbers of called peaks and reproducible peaks for each sample type are listed in Supplementary Data. The RefSeq transcript annotations of the hg38 version of the human genome and the mm10 version of the mouse genome were used to define the genomic location of transcription units. For genes with multiple gene models, the longest transcription unit was used for the gene locus definition. ATAC peaks located in the body of the transcription unit, together with the 2-kb regions upstream of the TSS and downstream of the 3′ end, were assigned to the gene. If a peak was found in the overlap of the transcription units of two genes, one of the genes was chosen arbitrarily. Intergenic peaks were assigned to the gene with a TSS or 3′ end that was closest to the peak. In this way, each peak was unambiguously assigned to one gene. Peaks were annotated as promoter peaks if they were within 2 kb of a transcription start site. Non-promoter peaks were annotated as intergenic, intronic or exonic according to the relevant RefSeq transcript annotation. We found a total of 75,689 reproducible ATAC-seq peaks in the mouse samples. Examining genomic locations, 39.6% of the peaks were found in introns, 36.3% were found in intergenic regions, 22.1% were found in promoters and 2.1% were found in exons. In the human samples, we found a total of 42,104 reproducible ATAC-seq peaks. Among these peaks, 34.0% were found in introns, 29.9% were found in intergenic regions, 34.0% were found in promoters, and 2.0% were found in exons. Chromosome-wide genomic coverage for all (autosomal) chromosomes and all samples was examined and no systemic bias was observed. PCA plots were generated using read counts against all mouse or human atlas peaks. These read counts were processed using the variance-stabilizing transformation built into the DESeq2 package40. Reads aligning to atlas peak regions were counted using the summarizeOverlaps function of the R packages GenomicAlignments v1.2.2 and GenomicRanges v1.18.4 (ref. 41). Differential accessibility of these peaks was then calculated for all pairwise comparisons of cell types using DESeq2 v1.6.3 (ref. 40). The ATAC-seq peak heat maps were created by pooling the DESeq size-factor normalized read counts per atlas peak across replicates of ATAC-seq data and binning the region ±1 kb around the peak summit in 20 bp bins. To improve visibility, bins with read counts greater than the 75th percentile + 1.5 × IQR were capped at that value. All analysis was performed using the original uncapped read counts. Genome coverage plots were generated for each replicate of ATAC-seq and RNA-seq by calculating genome-wide coverage of aligned reads using the bedtools function genomecov42. For ATAC-seq samples, this coverage was calculated after shifting the reads to account for the Tn5-induced bias. The coverage values were then normalized using DESeq2-derived size factors and replicates were combined to create one signal track for each sample type. ATAC-seq and RNA-seq coverage plots were generated using the Integrated Genomics Viewer (Broad)43. Using the MEME44-curated CisBP45 transcription factor binding motif (TFBM) reference, we scanned the mouse ATAC-seq peak atlas with FIMO46 to find peaks likely to contain each TFBM (P < 10−4). The MEME cisBP reference for direct and inferred motifs for Mus musculus was curated by the MEME suite developers as follows: to reduce redundancy, for each transcription factor a single motif was selected according to the following precedence rules. The direct motif was chosen if there was one, otherwise the inferred motif with the highest DNA binding domain (DBD) similarity (according to CisBP) to a transcription factor in another species with a direct motif was chosen. If there was more than one direct motif or inferred motif with the highest DBD similarity, a motif was chosen according to its provenance (CisBP ‘Motif_Type’ attribute) in the following order: ChIP-seq, HocoMoco, DeBoer11, PBM, SELEX, B1H, High-throughput Selex CAGE, PBM:CSA:DIP-chip, ChIP-chip, COMPILED, DNaseI footprinting. Each motif thus determined was linked to a single transcription factor in the CisBP database, following the same precedence rules. The final reference contained 718 motifs between 6 and 30 bp in width (average width, 10.7 bp). Transcription factors with similar FIMO-predicted target peaks were combined into transcription factor families. Similarity of predicted target peak sets was measured using the Jaccard index (size of intersection/size of union). Transcription factors with Jaccard indices greater than 0.7 were combined for further analyses. Relative transcription factor accessibility was calculated using two one-sided Wilcoxon rank-sign tests comparing the distributions of peak heights for peaks containing FIMO-predicted transcription factor binding sites. Peak height was defined as the maximum observed number of reads overlapping at any point in the defined peak region. ATAC-seq footprints containing FIMO-predicted transcription factor binding sites (P < 1 × 10−4) were selected. Positive- and negative-strand ATAC-seq cut sites were counted 100 bp up- and down-stream of the centre of the motif site in each of the selected peaks. The mean number of ATAC-seq cut sites across matching atlas peaks was then plotted to generate the footprint figures. In these plots, each gene is represented by a stack of diamonds corresponding accessible chromatin regions of the same gene. The bottom-most peak in this stack corresponds to the log fold change in expression of the gene. The diamonds are coloured according to the accessibility change of their ATAC-seq peak with blue indicating closing and red indicating opening. The colour scale was based on the rank-order of the peak accessibility changes. In Extended Data Fig. 6d, the colour scale ranges from a log fold change of −3.92 to 4.96 (L14/L7). The UCSC liftOver tool47 was used to convert the mouse ATAC-seq peak atlas from mm10 coordinates to hg38 coordinates. The converted mouse atlas was then compared to the human atlas and 20,642 mouse peaks were within 100 bp of a human peak. We compared the results from the UCSC liftover tool and an alternative method, bnMapper48, and confirmed that the set of peaks mapped by bnMapper and by the UCSC liftOver tool was nearly identical (57,383 out of 75,689 by liftOver and 58,299 out of 75,689 by bnMapper). Additionally, all 57,223 peaks mapped to hg38 by both tools were mapped to the same chromosomal positions. The majority of these conserved peaks were found in promoter regions (56.4%), whereas relatively fewer were found in intergenic (22.4%), intronic (19.6%), and exonic (1.5%) regions. For non-promoter peaks conserved between human and mouse, Spearman correlations of log (FC) were calculated between human N and human EM, CM or PD1hi TIL versus log (FC) between mouse N and functional E5, E7, M and dysfunctional L5 to L60. Raw ATAC-seq reads were trimmed and filtered for quality using Trim Galore! v0.4.0 (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/), powered by CutAdapt v1.8.1 (http://dx.doi.org/10.14806/ej.17.1.200) and FastQC v0.11.3 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Paired-end reads were aligned using STAR49 against either mm10 or hg38. The RefSeq transcript annotations of the hg38 version of the human genome and the mm10 version of the mouse genome were used for the genomic location of transcription units. Reads aligning to annotated exon regions were counted using the summarizeOverlaps function of the R packages GenomicAlignments v1.2.2 and GenomicRanges v1.18.4 (ref. 41). Differential expression of genes across cell types was calculated using DESeq2 v1.6.3 (ref. 40). FDR correction of 0.05 was imposed unless otherwise stated. A log fold change cutoff of 1 was used in some analyses as indicated. Enrichment of gene ontology terms in sets of ATAC-seq peaks was calculated using GREAT (Genomic Regions Enrichment of Annotations Tool) using default parameters50. The full ATAC-seq atlas was used as the background set. To identify membrane proteins that distinguished early (L5–L7) from late (L14–L60) dysfunctional TST, RNA-seq data was analysed for genes contained within the gene ontology category 0016020 (membrane proteins). The top 50 most up- and downregulated genes (size-factor normalized RPKM) when compared between L5–L7 and L14–L60 were plotted in a heat map (row-normalized). Protein expression was assessed by flow cytometry for those membrane proteins for which monoclonal antibodies were available. Mouse targets (clone; supplier): CD5 (53-7.3; eBioscience), CD30L (RM153; eBioscience), CD38 (90; Biolegend), and CD101 (Moushi101; eBioscience). Human targets: CD5 (L17F12; Biolegend), CD38 (HB7; eBioscience), CD101 (BB27; Biolegend). No statistical methods were used to predetermine sample size. The investigators were not blinded to allocation during experiments and outcome assessment. Mice or human samples were excluded if donor or tumour-infiltrating CD8 T cells could not be found. All data generated and supporting the findings of this study are available within the paper. The RNA-seq and ATAC-seq data have been deposited in the Gene Expression Omnibus (GEO Super-Series accession number GSE89309 (GSE89307 for RNA-seq, GSE89308 for ATAC-seq). Source Data for Figs 1 and Extended Data Figs 1, 3 and 7 are provided with the online version of the paper. Additional information and materials will be made available upon request.

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