Engineering topics
Publications and source records attributed to Monroe, Matthew E.
Interactive plots (in HTML/javascript) as supplemental files for the paper titled: Proteogenomic Characterization of Ovarian High-Grade Serous Cancer Implicates Mitotic Kinases, Replication Stress in Observed Chromosomal Instability. The plots represent the differential expression of proteins (File 1) and phosphopeptides (File 2) comparing tumor to normal tissue.
MultiAlign is a free software tool that aligns multiple liquid chromatography-mass spectrometry datasets to one another by clustering mass and LC elution features across datasets. Applicable to both label-free proteomics and metabolomics comparative analyses, the software can be operated in several modes. Clustered features can be matched to a reference database to identify analytes, used to generate abundance profiles, linked to tandem mass spectra based on parent precursor masses, and culled for targeted liquid chromatography-tandem mass spectrometric analysis. MultiAlign is also capable of tandem mass spectral clustering to describe proteome structure and find similarity in subsequent sample runs.
Cultures of the cyanobacterial genus Cyanothece have been shown to produce high levels of biohydrogen. These strains are diazotrophic and undergo pronounced diurnal cycles when grown under N2-fixing conditions in light-dark cycles. We seek to better understand the way in which proteins respond to these diurnal changes and we performed quantitative proteome analysis of Cyanothece ATCC 51142 and PCC 7822 grown under 8 different nutritional conditions. Nitrogenase expression was limited to N2-fixing conditions, and in the absence of glycerol, nitrogenase gene expression was linked to the dark period. However, glycerol induced expression of nitrogenase during part of the light period, together with cytochrome c oxidase (Cox), glycogen phosphorylase (Glp), and glycolytic and pentose-phosphate pathway (PPP) enzymes. This indicated that nitrogenase expression in the light was facilitated via higher respiration and glycogen breakdown. Key enzymes of the Calvin cycle were inhibited in Cyanothece ATCC 51142 in the presence of glycerol under H2 producing conditions, suggesting a competition between these sources of carbon. However, in Cyanothece PCC 7822, the Calvin cycle still played a role in cofactor recycling during H2 production. Our data comprise the first comprehensive profiling of proteome changes in Cyanothece PCC 7822, and allows an in-depth comparative analysis of major physiological and biochemical processes that influence H2-production in both the strains. Our results revealed many previously uncharacterized proteins that may play a role in nitrogenase activity and in other metabolic pathways and may provide suitable targets for genetic manipulation that would lead to improvement of large scale H2 production.
Multiheme c-type cytochromes (proteins with covalently attached heme c moieties) play important roles in extracellular metal respiration in dissimilatory metal-reducing bacteria. Liquid chromatography-tandem mass spectrometry-(LC-MS/MS) characterization of c-type cytochromes is hindered by the presence of multiple heme groups, since the heme c modified peptides are typically not observed, or if observed, not identified. Using a recently reported histidine affinity chromatography (HAC) procedure, we enriched heme c tryptic peptides from purified bovine heart cytochrome c, a bacterial decaheme cytochrome, and subjected these samples to LC-MS/MS analysis. Enriched bovine cytochrome c samples yielded three- to six-fold more confident peptide-spectrum matches to heme-c containing peptides than unenriched digests. In unenriched digests of the decaheme cytochrome MtoA from Sideroxydans lithotrophicus ES-1, heme c peptides for four of the ten expected sites were observed by LC-MS/MS; following HAC fractionation, peptides covering nine out of ten sites were obtained. Heme c peptide spiked into E. coli lysates at mass ratios as low as 10-4 was detected with good signal-to-noise after HAC and LC-MS/MS analysis. In addition to HAC, we have developed a proteomics database search strategy that takes into account the unique physicochemical properties of heme c peptides. The results suggest that accounting for the double thioether link between heme c and peptide, and the use of the labile heme fragment as a reporter ion, can improve database searching results. The combination of affinity chromatography and heme-specific informatics yielded increases in the number of peptide-spectrum matches of 20-100-fold for bovine cytochrome c.
Human serum glycan profiling with mass spectrometry (MS) has been employed to study several disease conditions and is demonstrating promise for e.g. clinical biomarker discovery. However, the poor glycan ionization efficiency and the large dynamic range of glycan concentrations in human sera hinder comprehensive profiling. In particular, large glycans are problematic because they are present at low concentrations and prone to fragmentation. Here we show that the sub-ambient pressure ionization with nanoelectrospray (SPIN)-MS can expand the serum glycome profile when compared with the conventional atmospheric pressure electrospray ionization (ESI)-MS with a heated capillary inlet. Notably, the ions generated by the SPIN interface were observed at higher charge states for 50% of the annotated glycans. Out of a total of 130 detected glycans, 34 were only detected with the SPIN-MS, resulting in improved coverage of glycan families as well as of glycans with larger numbers of labile monosaccharides.
Preterm birth is a global health issue impacting both mothers and children. However, the etiology of preterm birth is not clearly understood. From our recent finding that premature decidual senescence with terminal differentiation is a cause of preterm birth in mice with uterine Trp53 deletion, encoding p53 protein, led us to explore other potential factors that are related to preterm birth. Utilizing proteomics approaches, here we show that 183 candidate proteins cause significant changes in decidua with Trp53 deletion as compared to normal decidua. Functional categorization of these proteins unveiled new pathways that are influenced by p53. In particular, downregulation of a cluster of antioxidant proteins in p53 deficient decidua suggests that increased oxidative stress could be one cause of preterm birth in mice with uterine deletion of Trp53.
O-Linked N-Acetylglucosamine (O-GlcNAc) is a reversible post-translational modification of Ser and Thr residues on cytosolic and nuclear proteins found in all higher eukaryotes. Aberrant O-GlcNAc modification of brain proteins has been linked to Alzheimer's disease (AD). However, understanding specific functions of O-GlcNAcylation in AD has been impeded by the difficulty in characterization of O-GlcNAc sites on proteins. In this study, we modified a chemical/enzymatic photochemical cleavage approach for enriching O-GlcNAcylated peptides in samples containing {approx}100 {micro}g of tryptic peptides from mouse cerebrocortical brain tissue. A total of 274 O-GlcNAcylated proteins were identified. Of these 168 were not previously known to be modified by O-GlcNAc. Overall, 458 O-GlcNAc sites on Ser and Thr residues in 195 proteins were identified. Many of the modified residues are either known phosphorylation sites or located in close proximity to known phosphorylation sites. These findings support the proposed regulatory crosstalk between O-GlcNAcylation and phosphorylation. This study produced the most comprehensive O-GlcNAc proteome of mammalian brain tissue with both protein identification and O-GlcNAc site assignment. Interestingly, we observed O-{beta}-GlcNAc on EGF-like repeats in the extracellular domains of five membrane proteins, thus representing the first evidence for extracellular O-GlcNAcylation in mammalian systems by the ER-resident O-GlcNAc transferase (EOGT). We also report a GlcNAc-{beta}-1,3-Fuc-{alpha}-1-O-Thr modification on the EGF-like repeat of the Versican core protein, a novel substrate of Fringe {beta}1,3-N-acetylglucosaminyltransferases.
Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. To date, the perceived value of manual curation for genome annotations is not offset by the real cost and time associated with the process. In order to balance the large number of sequences generated, the annotation process is now performed almost exclusively in an automated fashion for most genome sequencing projects. One possible way to reduce errors inherent to automated computational annotations is to apply data from 'omics' measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. This approach does require additional experimental and bioinformatics methods to include omics technologies; however, the approach is readily automatable and can benefit from rapid developments occurring in those research domains as well. The annotation process can be improved by experimental validation of transcription and translation and aid in the discovery of annotation errors. Here the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species, as is becoming common in sequencing efforts. Transcriptomic and proteomic data derived from three highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 previously incorrect protein-coding sequences (e.g., observed frameshifts, extended start sites, and translated pseudogenes) within the three current Yersinia genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, and a transcriptional regulator, among other proteins, most of which are annotated as hypothetical, that were missed during annotation.
Protein glycosylation is known to play an essential role in both cellular functions and the secretory pathways; however, little information is available on the dynamics of glycosylated N-linked glycosites of fungi. Herein we present the first extensive mapping of glycosylated N-linked glycosites in industrial strain Aspergillus niger by applying an optimized solid phase enrichment of glycopeptide protocol using hydrazide modified magnetic beads. The enrichment protocol was initially optimized using mouse plasma and A. niger secretome samples, which was then applied to profile N-linked glycosites from both the secretome and whole cell lysates of A. niger. A total of 847 unique N-linked glycosites and 330 N-linked glycoproteins were confidently identified by LC-MS/MS. Based on gene ontology analysis, the identified N-linked glycoproteins in the whole cell lysate were primarily localized in the plasma membrane, endoplasmic reticulum, golgi apparatus, lysosome, and storage vacuoles. The identified N-linked glycoproteins are involved in a wide range of biological processes including gene regulation and signal transduction, protein folding and assembly, protein modification and carbohydrate metabolism. The extensive coverage of glycosylated N-linked glycosites along with identification of partial N-linked glycosylation in those enzymes involving in different biochemical pathways provide useful information for functional studies of N-linked glycosylation and their biotechnological applications in A. niger.
Unicellular cyanobacteria of the genus Cyanothece are recognized for their ability to execute nitrogen (N2)-fixation in the dark and photosynthesis in the light. Systems-wide dynamic proteomic profiling with mass spectrometry (MS) analysis reveals fundamental insights into the control and regulation of these functions. To expand upon the current knowledge of protein expression patterns in Cyanothece ATCC51142, we performed quantitative proteomic analysis using partial ("unsaturated") metabolic labeling and high mass accuracy LC-MS analysis. This dynamic proteomic profiling identified 721 actively synthesized proteins with significant temporal changes in expression throughout the light-dark cycles, of which 425 proteins matched with previously characterized cycling transcripts. The remaining 296 proteins contained a cluster of proteins uniquely involved in DNA replication and repair, protein degradation, tRNA synthesis and modification, transport and binding, and regulatory functions. Analysis of protein functions revealed that the expression of nitrogenase in the dark is mediated by higher respiration and glycogen metabolism. We have also shown that Cyanothece ATCC51142 utilizes alternative pathways for carbon (C) and nitrogen (N) acquisition, particularly, aspartic acid and glutamate as substrates of C and N, respectively. Utilization of phosphoketolase (PHK) pathway for the conversion of xylulose-5P to pyruvate and acetyl-P likely constitutes an alternative strategy to compensate higher ATP and NADPH demand. In conclusion, this study provides a deeper insight into how Cyanothece ATCC51142 modulates cellular functions to accommodate photosynthesis and N2-fixation within the single cell.
Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify coding regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.
High-throughput proteomics is rapidly evolving to require high mass measurement accuracy for a variety of different applications. Increased mass measurement accuracy in bottom-up proteomics specifically allows for an improved ability to distinguish and characterize detected MS features, which may in turn be identified by, e.g., matching to entries in a database for both precursor and fragmentation mass identification methods. Many tools exist with which to score the identification of peptides from LC-MS/MS measurements or to assess matches to an accurate mass and time (AMT) tag database, but these two calculations remain distinctly unrelated. Here we present a statistical method, Statistical Tools for AMT tag Confidence (STAC), which extends our previous work incorporating prior probabilities of correct sequence identification from LC-MS/MS, as well as the quality with which LC-MS features match AMT tags, to evaluate peptide identification confidence. Compared to existing tools, we are able to obtain significantly more high-confidence peptide identifications at a given false discovery rate and additionally assign confidence estimates to individual peptide identifications. Freely available software implementations of STAC are available in both command line and as a Windows graphical application.
Non-enzymatic glycation of proteins is implicated in diabetes mellitus and its related complications. In this report, we extend our previous development and refinement of proteomics-based methods for the analysis of non-enzymatically glycated proteins to comprehensively identify glycated proteins in normal and diabetic human plasma and erythrocytes. Using immunodepletion, enrichment, and fractionation strategies, we identified 7749 unique glycated peptides, corresponding to 3742 unique glycated proteins. Semi-quantitative comparisons revealed a number of proteins with glycation levels significantly increased in diabetes relative to control samples and that erythrocyte proteins are more extensively glycated than plasma proteins. A glycation motif analysis revealed amino acids that are favored more than others in the protein primary structures in the vicinity of the glycation sites in both sample types. The glycated peptides and corresponding proteins reported here provide a foundation for the potential identification of novel markers for diabetes, glycemia, or diabetic complications.
Tandem mass spectrometry (MS/MS) experiments yield multiple, nearly identical spectra of the same peptide in various laboratories, but proteomics researchers typically do not leverage the unidentified spectra produced in other labs to decode spectra they generate. We propose a spectral archives approach that clusters MS/MS datasets, representing similar spectra by a single consensus spectrum. Spectral archives extend spectral libraries by analyzing both identified and unidentified spectra in the same way and maintaining information about peptide spectra that are common across species and conditions. Thus archives offer both traditional library spectrum similarity-based search capabilities along with new ways to analyze the data. By developing a clustering tool, MS-Cluster, we generated a spectral archive from ~1.18 billion spectra that greatly exceeds the size of existing spectral repositories. We advocate that publicly available data should be organized into spectral archives rather than be analyzed as disparate datasets, as is mostly the case today.
Abstract - Brain development and spinal cord regeneration require neurite sprouting and growth cone navigation in response to extension and collapsing factors present in the extracellular environment. These external guidance cues control neurite growth cone extension and retraction processes through intracellular protein phosphorylation of numerous cytoskeletal, adhesion, and polarity complex signaling proteins. However, the complex kinase/substrate signaling networks that mediate neuritogenesis have not been investigated. Here, we compare the neurite phosphoproteome under growth and retraction conditions using neurite purification methodology combined with mass spectrometry. More than 4000 non-redundant phosphorylation sites from 1883 proteins have been annotated and mapped to signaling pathways that control kinase/phosphatase networks, cytoskeleton remodeling, and axon/dendrite specification. Comprehensive informatics and functional studies revealed a compartmentalized ERK activation/deactivation cytoskeletal switch that governs neurite growth and retraction, respectively. Our findings provide the first system-wide analysis of the phosphoprotein signaling networks that enable neurite growth and retraction and reveal an important molecular switch that governs neuritogenesis.
Two dimensional liquid chromatography (2D LC) is commonly used for shotgun proteomics to improve the analysis dynamic range. Reversed phase liquid chromatography (RPLC) has been routinely employed as the second dimensional separation prior to the mass spectrometric analysis. Construction of 2D separation with RP-RP arises a concern for the separation orthogonality. In this study, we applied a novel concatenation strategy to improve the orthogonality of 2D RP-RP formed by low pH (i.e., pH 3) and high pH (i.e., pH 10) RPLC. We confidently identified 3753 proteins (18570 unique peptides) and 5907 proteins (37633 unique peptides) from low pH RPLC-RP and high pH RPLC-RP, respectively, for a trypsin-digested human MCF10A cell sample. Compared with SCX-RP, the high pH-low pH RP-RP approach resulted in 1.8-fold and 1.6-fold in the number of peptide and protein identifications, respectively. In addition to the broader identifications, the High pH-low pH RP-RP approach has advantages including the improved protein sequence coverage, the simplified sample processing, and the reduced sample loss. These results demonstrated that the concatenation high pH-low pH RP-RP strategy is an attractive alternative to SCX for 2D LC shotgun proteomic analysis.
Independent, greedy collection of data events using simple heuristics results in massive over-sampling of the prominent data features in large-scale studies over what should be achievable through “intelligent,” online acquisition of such data. As a result, data generated are more aptly described as a collection of a large number of small experiments rather than a true large-scale experiment. Nevertheless, achieving “intelligent,” online control requires tight interplay between state-of-the-art, data-intensive computing infrastructure developments and analytical algorithms. In this paper, we propose a Software Architecture for Mass spectrometry-based Proteomics coupled with Liquid chromatography Experiments (SAMPLE) to develop an “intelligent” online control and analysis system to significantly enhance the information content from each sensor (in this case, a mass spectrometer). Using online analysis of data events as they are collected and decision theory to optimize the collection of events during an experiment, we aim to maximize the information content generated during an experiment by the use of pre-existing knowledge to optimize the dynamic collection of events.
Background: High doses of ionizing radiation result in biological damage, however the precise relationships between long term health effects, including cancer, and low dose exposures remain poorly understood and are currently extrapolated using high dose exposure data. Identifying the signaling pathways and individual proteins affected at the post-translational level by radiation should shed valuable insight into the molecular mechanisms that regulate dose dependent responses to radiation. Principle Findings: We have identified 6845 unique phosphopeptides (2566 phosphoproteins) from control and irradiated (2 and 50 cGy) primary human skin fibroblasts one hour post-exposure. Dual statistical analyses based on spectral counts and peak intensities identified 287 phosphopeptides (from 231 proteins) and 244 phosphopeptides (from 182 proteins) that varied significantly following exposure to 2 and 50 cGy respectively. This screen identified phosphorylation sites on proteins with known roles in radiation responses including TP53BP1 as well as previously unidentified radiation responsive proteins such as the candidate tumor suppressor SASH1. Bioinformatics analyses suggest that low and high doses of radiation affect both overlapping and unique biological processes and suggest a role of MAP kinase and protein kinase A (PKA) signaling in the radiation response as well as differential regulation of p53 networks at low and high doses of radiation. Conlcusions: Our results represent the most comprehensive analysis of the phosphoproteomes of human primary fibroblasts exposed to multiple doses of ionizing radiation published to date and provides a basis for the systems level identification of biological processes, molecular pathways and individual proteins regulated in a dose dependent manner by ionizing radiation. Further study of these modified proteins and affected networks should help to define the molecular mechanisms that regulate biological responses to radiation at different radiation doses and elucidate the impact of low dose radiation exposure on human health.