Bioinformatics Solutions Inc.

Waterloo, Canada

Bioinformatics Solutions Inc.

Waterloo, Canada
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Matthews M.L.,Scripps Research Institute | He L.,Scripps Research Institute | He L.,Bioinformatics Solutions Inc. | Horning B.D.,Scripps Research Institute | And 6 more authors.
Nature Chemistry | Year: 2017

Activity-based protein profiling (ABPP) serves as a chemical proteomic platform to discover and characterize functional amino acids in proteins on the basis of their enhanced reactivity towards small-molecule probes. This approach, to date, has mainly targeted nucleophilic functional groups, such as the side chains of serine and cysteine, using electrophilic probes. Here we show that reverse-polarity' (RP)-ABPP using clickable, nucleophilic hydrazine probes can capture and identify protein-bound electrophiles in cells. Using this approach, we demonstrate that the pyruvoyl cofactor of S-adenosyl-L-methionine decarboxylase (AMD1) is dynamically controlled by intracellular methionine concentrations. We also identify a heretofore unknown modification - an N-terminally bound glyoxylyl group - in the poorly characterized protein secernin-3. RP-ABPP thus provides a versatile method to monitor the metabolic regulation of electrophilic cofactors and discover novel types of electrophilic modifications on proteins in human cells. © The Author(s) 2017.


Davis S.,University of Oxford | Charles P.D.,University of Oxford | He L.,Bioinformatics Solutions Inc. | Mowlds P.,Thermo Fisher Scientific | And 2 more authors.
Journal of Proteome Research | Year: 2017

The "deep" proteome has been accessible by mass spectrometry for some time. However, the number of proteins identified in cells of the same type has plateaued at ∼8000-10"000 without ID transfer from reference proteomes/data. Moreover, limited sequence coverage hampers the discrimination of protein isoforms when using trypsin as standard protease. Multienzyme approaches appear to improve sequence coverage and subsequent isoform discrimination. Here we expanded proteome and protein sequence coverage in MCF-7 breast cancer cells to an as yet unmatched depth by employing a workflow that addresses current limitations in deep proteome analysis in multiple stages: We used (i) gel-aided sample preparation (GASP) and combined trypsin/elastase digests to increase peptide orthogonality, (ii) concatenated high-pH prefractionation, and (iii) CHarge Ordered Parallel Ion aNalysis (CHOPIN), available on an Orbitrap Fusion (Lumos) mass spectrometer, to achieve 57% median protein sequence coverage in 13"728 protein groups (8949 Unigene IDs) in a single cell line. CHOPIN allows the use of both detectors in the Orbitrap on predefined precursor types that optimizes parallel ion processing, leading to the identification of a total of 179"549 unique peptides covering the deep proteome in unprecedented detail. © 2017 American Chemical Society.


Lusi E.A.,University College Dublin | Maloney D.,Bioinformatics Solutions Inc. | Caicci F.,University of Padua | Guarascio P.,St Camillo Hospital of Rome
F1000Research | Year: 2017

Background: Mimiviruses or giant viruses that infect amoebas have the ability to retain the Gram stain, which is usually used to colour bacteria. There is some evidence suggesting that Mimiviruses can also infect human cells. Guided by these premises, we performed a routine Gram stain on a variety of human specimens to see if we could detect the same Gram positive blue granules that identify Mimiviruses in the amoebas. Methods: We analysed 24 different human specimens (liver, brain, kidney, lymph node and ovary) using Gram stain histochemistry, electron microscopy immunogold, high resolution mass spectrometry and protein identification. Results: We detected in the human cells Gram positive granules that were distinct from bacteria. The fine blue granules displayed the same pattern of the Gram positive granules that diagnose Mimiviruses in the cytoplasm of the amoebas. Electron microscopy confirmed the presence of human Mimiviruses-like structures and mass spectrometry identified histone H4 peptides, which had the same footprints as giant viruses. However, some differences were noted: the Mimivirus-like structures identified in the human cells were ubiquitous and manifested a distinct mammalian retroviral antigenicity. Conclusions: Our main hypotheses are that the structures could be either giant viruses having a retroviral antigenicity or ancestral cellular components having a viral origin. However, other possible alternatives have been proposed to explain the nature and function of the newly identified structures. © 2017 Lusi EA et al.


Zhang Z.,Bioinformatics Solutions Inc. | Lin H.,University of Waterloo | Ma B.,University of Waterloo
Nucleic Acids Research | Year: 2010

High-throughput next-generation sequencing technologies pose increasing demands on the efficiency, accuracy and usability of data analysis software. In this article, we present ZOOM Lite, a software for efficient reads mapping and result visualization. With a kernel capable of mapping tens of millions of Illumina or AB SOLiD sequencing reads efficiently and accurately, and an intuitive graphical user interface, ZOOM Lite integrates reads mapping and result visualization into a easy to use pipeline on desktop PC. The software handles both single-end and paired-end reads, and can output both the unique mapping result or the top N mapping results for each read. Additionally, the software takes a variety of input file formats and outputs to several commonly used result formats. The software is freely available at http://bioinfor.com/zoom/lite/. © The Author(s) 2010. Published by Oxford University Press.


He L.,University of Waterloo | Xin L.,Bioinformatics Solutions Inc. | Shan B.,Bioinformatics Solutions Inc. | Lajoie G.A.,University of Western Ontario | Ma B.,University of Waterloo
Journal of Proteome Research | Year: 2014

Glycosylation is one of the most commonly observed post-translational modifications (PTMs) in eukaryotes. It is believed that more than 50% eukaryotic proteins are glycosylated. To reveal the biological functions of protein-linked glycans involved in numerous biological processes, the high-throughput identification of both glycoproteins and the attached glycan structures becomes fundamentally important. Tandem mass spectrometry (MS/MS) is an effective method for glycoproteomic analysis because of its high sensitivity and selectivity. Two experimental approaches exist to obtain MS/MS spectral data of glycopeptides. One consists of isolating glycans from glycopeptides and generating MS/MS spectra of the glycans and peptides separately. The other approach produces spectra directly from intact glycopeptides. The latter approach has the advantage of retaining the glycosylation site information. However, the spectral data cannot be readily analyzed because of the lack of software specifically designed for the identification of intact glycopeptides. To address this need, we developed a novel software tool, GlycoMaster DB, to assist the automated and high-throughput identification of intact N-linked glycopeptides from MS/MS spectra. The software simultaneously searches a protein sequence database and a glycan structure database to find the best pair of peptide and glycan for each input spectrum. GlycoMaster DB can analyze mass spectral data produced with HCD/ETD mixed fragmentation, where HCD spectra are used to identify glycans and ETD spectra are used to determine peptide sequences. When only HCD spectra are available, GlycoMaster DB can still help to identify the glycans, and a list of possible peptide sequences are reported according to the accurate precursor mass and the N-linked glycopeptide sequon. GlycoMaster DB is freely accessible at http://www-novo.cs.uwaterloo.ca:8080/GlycoMasterDB. © 2014 American Chemical Society.


Han X.,University of Waterloo | He L.,University of Waterloo | Xin L.,Bioinformatics Solutions Inc. | Shan B.,Bioinformatics Solutions Inc. | Ma B.,University of Waterloo
Journal of Proteome Research | Year: 2011

Tandem mass spectrometry (MS/MS) has been routinely used to identify peptides from a protein sequence database. To identify post-translationally modified peptides, most existing software requires the specification of a few possible modifications. However, such knowledge of possible modifications is not always available. In this paper, we describe a new algorithm for identifying modified peptides without requiring the user to specify the possible modifications; instead, all modifications from the Unimod database are considered. Meanwhile, several new techniques are employed to avoid the exponential growth of the search space, as well as to control the false discoveries due to this unrestricted search approach. Finally, a software tool, PeaksPTM, has been developed and already achieved a stronger performance than competitive tools for unrestricted identification of post-translational modifications. © 2011 American Chemical Society.


Liu X.,University of Waterloo | Shan B.,Bioinformatics Solutions Inc | Shan B.,University of Western Ontario | Xin L.,Bioinformatics Solutions Inc | And 2 more authors.
BMC Bioinformatics | Year: 2010

Background: Tandem mass spectrometry (MS/MS) has become the primary way for protein identification in proteomics. A good score function for measuring the match quality between a peptide and an MS/MS spectrum is instrumental for the protein identification. Traditionally the to-be-measured peptides are fragmented with the collision induced dissociation (CID) method. More recently, the electron transfer dissociation (ETD) method was introduced and has proven to produce better fragment ion ladders for larger and more basic peptides. However, the existing software programs that analyze ETD MS/MS data are not as advanced as they are for CID.Results: To take full advantage of ETD data, in this paper we develop a new score function to evaluate the match between a peptide and an ETD MS/MS spectrum. Experiments on real data demonstrated that this newly developed score function significantly improved the de novo sequencing accuracy of the PEAKS software on ETD data.Conclusion: A new and better score function for ETD MS/MS peptide identification was developed. The method used to develop our ETD score function can be easily reused to train new score functions for other types of MS/MS data. © 2010 Liu et al; licensee BioMed Central Ltd.


Zhang J.,Bioinformatics Solutions Inc. | Xin L.,Bioinformatics Solutions Inc. | Shan B.,Bioinformatics Solutions Inc. | Chen W.,Bioinformatics Solutions Inc. | And 7 more authors.
Molecular and Cellular Proteomics | Year: 2012

Many software tools have been developed for the automated identification of peptides from tandem mass spectra. The accuracy and sensitivity of the identification software via database search are critical for successful proteomics experiments. A new database search tool, PEAKS DB, has been developed by incorporating the de novo sequencing results into the database search. PEAKS DB achieves significantly improved accuracy and sensitivity over two other commonly used software packages. Additionally, a new result validation method, decoy fusion, has been introduced to solve the issue of overconfidence that exists in the conventional target decoy method for certain types of peptide identification software. © 2012 by The American Society for Biochemistry and Molecular Biology, Inc.


Zhang J.,Bioinformatics Solutions Inc.
Molecular & cellular proteomics : MCP | Year: 2012

Many software tools have been developed for the automated identification of peptides from tandem mass spectra. The accuracy and sensitivity of the identification software via database search are critical for successful proteomics experiments. A new database search tool, PEAKS DB, has been developed by incorporating the de novo sequencing results into the database search. PEAKS DB achieves significantly improved accuracy and sensitivity over two other commonly used software packages. Additionally, a new result validation method, decoy fusion, has been introduced to solve the issue of overconfidence that exists in the conventional target decoy method for certain types of peptide identification software.


Trademark
Bioinformatics Solutions Inc. | Date: 2011-06-28

Bioinformatics Software for analyzing data acquired from mass spectrometry instruments for the purpose of identifying protein glycosylation.

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