DNA Methylation Modifications Associated with Chronic Fatigue Syndrome

Chronic Fatigue Syndrome (CFS), also known as myalgic encephalomyelitis, is a complex multifactorial disease that is characterized by the persistent presence of fatigue and other particular symptoms for a minimum of 6 months. Symptoms fail to dissipate after sufficient rest and have major effects on the daily functioning of CFS sufferers. CFS is a multi-system disease with a heterogeneous patient population showing a wide variety of functional disabilities and its biological basis remains poorly understood. Stable alterations in gene function in the immune system have been reported in several studies of CFS. Epigenetic modifications have been implicated in long-term effects on gene function, however, to our knowledge, genome-wide epigenetic modifications associated with CFS have not been explored. We examined the DNA methylome in peripheral blood mononuclear cells isolated from CFS patients and healthy controls using the Illumina HumanMethylation450 BeadChip array, controlling for invariant probes and probes overlapping polymorphic sequences. Gene ontology (GO) and network analysis of differentially methylated genes was performed to determine potential biological pathways showing changes in DNA methylation in CFS. We found an increased abundance of differentially methylated genes related to the immune response, cellular metabolism, and kinase activity. Genes associated with immune cell regulation, the largest coordinated enrichment of differentially methylated pathways, showed hypomethylation within promoters and other gene regulatory elements in CFS. These data are consistent with evidence of multisystem dysregulation in CFS and implicate the involvement of DNA modifications in CFS pathology.     

Large-scale Top-down Proteomics of the Human Proteome: Membrane Proteins,Mitochondria, and Senescence

Top-down proteomics is emerging as a viable method for the routine identification of hundreds to thousands of proteins. In this work we report the largest top-down study to date, with the identification of 1,220 proteins from the transformed human cell line H1299 at a false discovery rate of 1%. Multiple separation strategies were utilized, including the focused isolation of mitochondria, resulting in significantly improved proteome coverage relative to previous work. In all, 347 mitochondrial proteins were identified, including ∼50% of the mitochondrial proteome below 30 kDa and over 75% of the subunits constituting the large complexes of oxidative phosphorylation. Three hundred of the identified proteins were found to be integral membrane proteins containing between 1 and 12 transmembrane helices, requiring no specific enrichment or modified LC-MS parameters. Over 5,000 proteoforms were observed, many harboring post-translational modifications, including over a dozen proteins containing lipid anchors (some previously unknown) and many others with phosphorylation and methylation modifications. Comparison between untreated and senescent H1299 cells revealed several changes to the proteome, including the hyperphosphorylation of HMGA2. This work illustrates the burgeoning ability of top-down proteomics to characterize large numbers of intact proteoforms in a high-throughput fashion.Although traditional bottom-up approaches to mass-spectrometry-based proteomics are capable of identifying thousands of protein groups from a complex mixture, proteolytic digestion can result in the loss of information pertaining to post-translational modifications and sequence variants (1, 2). The recent implementation of top-down proteomics in a high-throughput format using either Fourier transform ion cyclotron resonance (3–5) or Orbitrap instruments (6, 7) has shown an increasing scale of applicability while preserving information on combinatorial modifications and highly related sequence variants. For example, the identification of over 500 bacterial proteins helped researchers find covalent switches on cysteines (7), and over 1,000 proteins were identified from human cells (3). Such advances have driven the detection of whole protein forms, now simply called proteoforms (8), with several laboratories now seeking to tie these to specific functions in cell and disease biology (9–11).The term “proteoform” denotes a specific primary structure of an intact protein molecule that arises from a specific gene and refers to a precise combination of genetic variation, splice variants, and post-translational modifications. Whereas special attention is required in order to accomplish gene- and variant-specific identifications via the bottom-up approach, top-down proteomics routinely links proteins to specific genes without the problem of protein inference. However, the fully automated characterization of whole proteoforms still represents a significant challenge in the field. Another major challenge is to extend the top-down approach to the study of whole integral membrane proteins, whose hydrophobicity can often limit their analysis via LC-MS (5, 12–16). Though integral membrane proteins are often difficult to solubilize, the long stretches of sequence information provided from fragmentation of their transmembrane domains in the gas phase can actually aid in their identification (5, 13).In parallel to the early days of bottom-up proteomics a decade ago (17–21), in this work we brought the latest methods for top-down proteomics into combination with subcellular fractionation and cellular treatments to expand coverage of the human proteome. We utilized multiple dimensions of separation and an Orbitrap Elite mass spectrometer to achieve large-scale interrogation of intact proteins derived from H1299 cells. For this focus issue on post-translational modifications, we report this summary of findings from the largest implementation of top-down proteomics to date, which resulted in the identification of 1,220 proteins and thousands more proteoforms. We also applied the platform to H1299 cells induced into senescence by treatment with the DNA-damaging agent camptothecin.     

Comprehensive Analysis of Individual Variation in the Urinary Proteome Revealed Significant Gender Differences

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Highlights

• •Comprehensive analysis of inter-individual variation of normal urinary proteome.
• •Significant gender differences were observed.
• •Proteins increased in female urine are enriched in immunological pathways.
• •Estimated reference intervals of proteins as the baseline for biomarker discovery.

     

Simultaneous Quantification of Protein Expression and Modifications by Top-down Targeted Proteomics: A Case of the Sarcomeric Subproteome

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Highlights

• •A new strategy for simultaneous quantification of protein expression and modification.
• •This top-down LC/MS-based method shows high reproducibility and high throughput.
• •Quantification at the intact protein level with results comparable to Western blot.
• •This top-down proteomics method is applicable to different species and tissues.

     

Glycoprofiling of the Human Salivary Proteome

Introduction  Glycosylation is an important component for a number of biological processes and is perhaps the most abundant and complicated of the known post-translational modifications found on proteins. Methods  This work combines two-dimensional (2-D) polyacrylamide gel electrophoresis and lectin blotting to map the salivary glycome and mass spectrometry to identity the proteins that are associated with the glycome map. A panel of 15 lectins that recognize six sugar-specific categories was used to visualize the type and extent of glycosylation in saliva from two healthy male individuals. Lectin blots were compared to 2-D gels stained either with Sypro Ruby (protein stain) or Pro-Q Emerald 488 (glycoprotein stain). Results  Each lectin shows a distinct pattern, even those belonging to the same sugar-specific category. In addition, the glycosylation profiles generated from the lectin blots show that most salivary proteins are glycosylated and that the profiles are more widespread than is demonstrated by the glycoprotein-stained gel. Finally, the coreactivity between lectins was measured to determine what types of glycan structures are associated with one another and also the population variation of the lectin reactivity for 66 individuals were reported. Conclusions  This starting 2-D gel glycosylation reference map shows that the scientifically accepted, individual oligosaccharide variability is not limited to a few large glycoproteins such as MUC5B, but are found on most members of the salivary proteome. Finally, in order to see the full range of oligosaccharide distribution, multiple reagents or lectins are needed. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Agonists of Orally Expressed TRP Channels Stimulate Salivary Secretion and Modify the Salivary Proteome

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Highlights

• •Salivary secretion was increased by mouth rinsing with TRP channel agonists.
• •The salivary proteome varied over time and was changed by TRP channel stimulation.
• •Immunoreactive Cystatin S was increased in saliva after TRPV1 stimulation.

     

Defining Proximity Proteome of Histone Modifications by Antibody-mediated Protein A-APEX2 Labeling

Proximity labeling catalyzed by promiscuous enzymes, such as APEX2, has emerged as a powerful approach to characterize multiprotein complexes and protein–protein interactions. However, current methods depend on the expression of exogenous fusion proteins and cannot be applied to identify proteins surrounding post-translationally modified proteins. To address this limitation, we developed a new method to label proximal proteins of interest by antibody-mediated protein A-ascorbate peroxidase 2 (pA-APEX2) labeling (AMAPEX). In this method, a modified protein is bound in situ by a specific antibody, which then tethers a pA-APEX2 fusion protein. Activation of APEX2 labels the nearby proteins with biotin; the biotinylated proteins are then purified using streptavidin beads and identified by mass spectrometry. We demonstrated the utility of this approach by profiling the proximal proteins of histone modifications including H3K27me3, H3K9me3, H3K4me3, H4K5ac, and H4K12ac, as well as verifying the co-localization of these identified proteins with bait proteins by published ChIP-seq analysis and nucleosome immunoprecipitation. Overall, AMAPEX is an efficient method to identify proteins that are proximal to modified histones.     

A 19-kb CpG Island Associated with Single-minded Gene 2 in Down Syndrome Chromosomal Region

To help in isolating the genes involved in Down syndrome, wesought CpG islands in 4 Mb cosmid/PAC contigs spanning mostof the 21q.22.2 band using seven rare cutting enzymes. A strikingfeature was observed upstream of hSIM2 where at least 41 rare-cuttingsites were clustered within a 20-kb region. To investigate thestructure of the cluster, a cosmid containing hSIM2 was submittedto shotgun sequencing. Sequence analysis revealed that the clusterwas a long CpG island extending 19, 128 nucleotides which includesin the first and second exons of hSIM2. Taken together withour observation in which the CpG islands were concentrated within1.2 Mb around hSIM2, we propose that this region functions asan R-band, and the cluster provides a unique element for markingof DNA for the spatial and temporal expression of the hSIM2locus.     

Protein Dynamics Associated with Failed and Rescued Learning in the Ts65Dn Mouse Model of Down Syndrome

Down syndrome (DS) is caused by an extra copy of human chromosome 21 (Hsa21). Although it is the most common genetic cause of intellectual disability (ID), there are, as yet, no effective pharmacotherapies. The Ts65Dn mouse model of DS is trisomic for orthologs of ∼55% of Hsa21 classical protein coding genes. These mice display many features relevant to those seen in DS, including deficits in learning and memory (L/M) tasks requiring a functional hippocampus. Recently, the N-methyl-D-aspartate (NMDA) receptor antagonist, memantine, was shown to rescue performance of the Ts65Dn in several L/M tasks. These studies, however, have not been accompanied by molecular analyses. In previous work, we described changes in protein expression induced in hippocampus and cortex in control mice after exposure to context fear conditioning (CFC), with and without memantine treatment. Here, we extend this analysis to Ts65Dn mice, measuring levels of 85 proteins/protein modifications, including components of MAP kinase and MTOR pathways, and subunits of NMDA receptors, in cortex and hippocampus of Ts65Dn mice after failed learning in CFC and after learning was rescued by memantine. We show that, compared with wild type littermate controls, (i) of the dynamic responses seen in control mice in normal learning, >40% also occur in Ts65Dn in failed learning or are compensated by baseline abnormalities, and thus are considered necessary but not sufficient for successful learning, and (ii) treatment with memantine does not in general normalize the initial protein levels but instead induces direct and indirect responses in approximately half the proteins measured and results in normalization of the endpoint protein levels. Together, these datasets provide a first view of the complexities associated with pharmacological rescue of learning in the Ts65Dn. Extending such studies to additional drugs and mouse models of DS will aid in identifying pharmacotherapies for effective clinical trials.     

Post-Translational Modifications in sperm Proteome: The Chemistry of Proteome diversifications in the Pathophysiology of male factor infertility

BackgroundThe spermatozoa undergo a series of changes in the epididymis to mature after their release from the testis and subsequently in the female reproductive tract after ejaculation to get capacitated and achieve fertilization potential. Despite having a silenced protein synthesis machinery, the dynamic change in protein profile of the spermatozoa is attributed either to acquisition of new proteins via vescicular transport or to several post-translational modifications (PTMs) occurring on the already expressed protein complement.Scope of reviewIn this review emphasis is given on the PTMs already reported on the human sperm proteins under normal and pathologic conditions with particular reference to sperm function such as motility and fertilization. An attempt has been made to summarize different protocols and methods used for analysis of PTMs on sperm proteins and the newer trends those were emerging.Major conclusionsDeciphering the differential occurrence of PTM on protein at ultrastructural level would give us a better insight of structure-function relationship of the particular protein. Protein with multiple PTMs could be used to generate the complex interaction network involved in a physiological function of a sperm. It can be speculated that crosstalk between different PTMs occurring either on same/ other proteins actually regulate the protein stability and activity both in physiological and pathological states.General significanceThe analytical prospective of various PTMs reported in human spermatozoa and their relevance to sperm function particularly in various pathophysiological states, would pave way for development of biomarkers for diagnosis, prognosis and therapeutic intervention of male infertility.     

Distinct Protein Classes in Human Red Cell Proteome Revealed by Similarity of Phylogenetic Profiles

The minimal set of proteins necessary to maintain a vertebrate cell forms an interesting core of cellular machinery. The known proteome of human red blood cell consists of about 1400 proteins. We treated this protein complement of one of the simplest human cells as a model and asked the questions on its function and origins. The proteome was mapped onto phylogenetic profiles, i.e. vectors of species possessing homologues of human proteins. A novel clustering approach was devised, utilising similarity in the phylogenetic spread of homologues as distance measure. The clustering based on phylogenetic profiles yielded several distinct protein classes differing in phylogenetic taxonomic spread, presumed evolutionary history and functional properties. Notably, small clusters of proteins common to vertebrates or Metazoa and other multicellular eukaryotes involve biological functions specific to multicellular organisms, such as apoptosis or cell-cell signaling, respectively. Also, a eukaryote-specific cluster is identified, featuring GTP-ase signalling and ubiquitination. Another cluster, made up of proteins found in most organisms, including bacteria and archaea, involves basic molecular functions such as oxidation-reduction and glycolysis. Approximately one third of erythrocyte proteins do not fall in any of the clusters, reflecting the complexity of protein evolution in comparison to our simple model. Basically, the clustering obtained divides the proteome into old and new parts, the former originating from bacterial ancestors, the latter from inventions within multicellular eukaryotes. Thus, the model human cell proteome appears to be made up of protein sets distinct in their history and biological roles. The current work shows that phylogenetic profiles concept allows protein clustering in a way relevant both to biological function and evolutionary history.     

Heterogeneity of Pancreatic Cancer Metastases in a Single Patient Revealed by Quantitative Proteomics

Many patients with pancreatic cancer have metastases to distant organs at the time of initial presentation. Recent studies examining the evolution of pancreatic cancer at the genetic level have shown that clonal complexity of metastatic pancreatic cancer is already initiated within primary tumors, and organ-specific metastases are derived from different subclones. However, we do not yet understand to what extent the evolution of pancreatic cancer contributes to proteomic and signaling alterations. We hypothesized that genetic heterogeneity of metastatic pancreatic cancer results in heterogeneity at the proteome level. To address this, we employed a model system in which cells isolated from three sites of metastasis (liver, lung, and peritoneum) from a single patient were compared. We used a SILAC-based accurate quantitative proteomic strategy combined with high-resolution mass spectrometry to analyze the total proteome and tyrosine phosphoproteome of each of the distal metastases. Our data revealed distinct patterns of both overall proteome expression and tyrosine kinase activities across the three different metastatic lesions. This heterogeneity was significant because it led to differential sensitivity of the neoplastic cells to small molecule inhibitors targeting various kinases and other pathways. For example, R428, a tyrosine kinase inhibitor that targets Axl receptor tyrosine kinase, was able to inhibit cells derived from lung and liver metastases much more effectively than cells from the peritoneal metastasis. Finally, we confirmed that administration of R428 in mice bearing xenografts of cells derived from the three different metastatic sites significantly diminished tumors formed from liver- and lung-metastasis-derived cell lines as compared with tumors derived from the peritoneal metastasis cell line. Overall, our data provide proof-of-principle support that personalized therapy of multiple organ metastases in a single patient should involve the administration of a combination of agents, with each agent targeted to the features of different subclones.Approximately half of the patients with pancreatic cancer are initially diagnosed with metastases to distal sites, with the commonest sites being the liver, lung, and peritoneum (1). Therapeutic strategies against metastases could help reduce the high mortality rates associated with this cancer (2). Understanding the nature of metastatic pancreatic cancer at a systems level can enable the discovery of potential targets for the development of targeted therapies.Pancreatic cancer has been shown to be a genetically evolving and heterogeneous disease (3–5). Clonal diversity and evolution of cancer genomes have also been demonstrated based on the isolation of distinct clonal populations purified directly from patient biopsies by means of flow cytometry followed by genomic characterization (6). A number of reports have documented the adoption of a proteomic approach for the discovery of potential biomarkers in pancreatic cancer (7, 8). However, these studies generally assume pancreatic cancers to be homogeneous, and the emphasis is placed on identifying molecules that are common across a broad array of tumors. There is a lack of studies systematically examining the proteomic changes or signaling pathways across pancreatic cancers to dissect the nature of the heterogeneity of each clone. An excellent setting in which the heterogeneity of tumors can be studied systematically is in a patient harboring metastases to several distant sites. To this end, we chose cells isolated from three metastatic pancreatic lesions of a single patient. The exomes of each tumor site were previously sequenced to study the progression of pancreatic cancer, and the results showed that all cell lines were identical for the genetic status of driver mutations (e.g. KRAS, TP53, and SMAD4) (9). Our hypothesis was that a better understanding of the proteomic consequences of the heterogeneity derived from genetic changes, and possibly other types of alterations, might provide additional opportunities to identify therapeutic targets.In order to precisely quantify differences across the proteomes of multiple metastatic pancreatic cancer lesions, we employed a SILAC-based¹ quantitative proteomics strategy combined with high-resolution mass spectrometry (10, 11). Based on changes observed at the whole-proteome level, we found that a class of cell surface receptors showed significant enrichment with the highest alteration of their expression among the three metastatic pancreatic cancer cell lines examined (i.e. peritoneum, lung, and liver). Because the total protein levels provide information about the static levels of proteins and not their activity per se, we decided to examine the activation of phosphorylation-driven pathways, many of which are activated by cell surface receptors. To globally examine tyrosine phosphorylation-based signaling pathways, we carried out mass spectrometric analysis of purified tyrosine phosphorylated peptides enriched using anti-phosphotyrosine antibodies. As a result, we observed differential activation of tyrosine kinases in the three different sites of metastases. For example, Axl receptor tyrosine kinase was found to be hyperphosphorylated in lung and liver metastases relative to peritoneal metastasis. Expression of Axl receptor tyrosine kinase in primary and matched pancreatic cancers on tissue microarrays was validated by immunohistochemistry. Given such unique patterns of activation of pathways, it was possible that tumors derived from different sites could show differences in their sensitivity to pathway inhibitors. To test this, we performed experiments in which we screened cell lines derived from each metastatic site against a panel of small molecule inhibitors. We observed that the three metastatic pancreatic cancers had differential sensitivities to different inhibitors. For example, cells derived from the peritoneal metastasis were highly sensitive to lapatinib, whereas greater sensitivity to the Axl inhibitor R428 was observed in the lung metastasis cell line. Finally, we showed that treatment of mice bearing xenografts from these different pancreatic cancer cell lines with R428, an inhibitor of Axl receptor tyrosine kinase, led to reduction of tumors with evidence of activation of Axl.     

A Quantitative Proteomics Analysis of Subcellular Proteome Localization and Changes Induced by DNA Damage

A major challenge in cell biology is to identify the subcellular distribution of proteins within cells and to characterize how protein localization changes under different cell growth conditions and in response to stress and other external signals. Protein localization is usually determined either by microscopy or by using cell fractionation combined with protein blotting techniques. Both these approaches are intrinsically low throughput and limited to the analysis of known components. Here we use mass spectrometry-based proteomics to provide an unbiased, quantitative, and high throughput approach for measuring the subcellular distribution of the proteome, termed “spatial proteomics.” The spatial proteomics method analyzes a whole cell extract created by recombining differentially labeled subcellular fractions derived from cells in which proteins have been mass-labeled with heavy isotopes. This was used here to measure the relative distribution between cytoplasm, nucleus, and nucleolus of over 2,000 proteins in HCT116 cells. The data show that, at steady state, the proteome is predominantly partitioned into specific subcellular locations with only a minor subset of proteins equally distributed between two or more compartments. Spatial proteomics also facilitates a proteome-wide comparison of changes in protein localization in response to a wide range of physiological and experimental perturbations, shown here by characterizing dynamic changes in protein localization elicited during the cellular response to DNA damage following treatment of HCT116 cells with etoposide. DNA damage was found to cause dissociation of the proteasome from inhibitory proteins and assembly chaperones in the cytoplasm and relocation to associate with proteasome activators in the nucleus.Many previous studies on organelle proteomics have provided a detailed list of the protein contents of organelles, substructures, or compartments isolated from cells (1–5). Such studies have also used quantitative proteomics in the high throughput assignment of proteins to subcellular compartments using methods such as protein correlation profiling (3, 6), recording the number of ions detected per protein (1, 2), or localization of organelle proteins by isotope tagging (7, 8). However, interpretation of the resulting protein inventory is complicated by the dynamic nature of organelle proteomes and by the fact that many proteins are not exclusive to one compartment but instead partition between separate subcellular locations (9, 10). This is illustrated by our previous studies of the human nucleolar proteome that have identified over 4,000 proteins that can co-purify reproducibly with nucleoli isolated from human cells but many of which are either present in low abundance in nucleoli and/or also have functions in other cellular locations (11). This highlights the importance of not only identifying the presence of a protein in any specific cellular organelle or structure but also measuring its relative abundance in different locations and assessing how this subcellular localization can change between different compartments under different cell growth and physiological conditions.Stable isotope labeling with amino acids in cell culture (SILAC)1 is the use of stable isotopic atoms along with mass spectrometry for quantitative mass spectrometry analysis (12, 13). This method allows quantitative analyses of proteins by comparison of the mass of light and heavier forms of the same peptide from a given protein, arising from the presence of heavier, stable isotopes such as ¹³C, ²H, and ¹⁵N. These stable isotopes are incorporated in proteins by in vivo labeling, i.e. growing the cells in specialized media where specific amino acids, typically arginine and lysine, are replaced with corresponding heavy isotope-substituted forms in which either all carbons or carbons, hydrogens, or nitrogens are isotope-labeled (14). Cleavage at the substituted arginine or lysine by trypsin generates a peptide with a shift in mass relative to the control (i.e. unsubstituted) peptide, and this can easily be resolved by mass spectrometry. The ratio of intensities of the “light” and “heavy” peptide signals identified by mass spectrometry directly correlates with the relative amount of the cognate protein from each sample. This method has been widely used for both relative quantification of protein levels after exposure of cells to drugs and inhibitors and for the identification of specific protein interaction partners (15–18).Here we used a quantitative and high throughput MS-based approach we term “spatial proteomics,” which both measures the relative intracellular localization of proteins and facilitates a comparison of changes in their subcellular localization under different conditions. This approach allows the rapid assignment of the cellular localization of proteins using common fractionation techniques. The major advantage of such a technique over other MS-based localization techniques such as protein correlation profiling or localization of organelle proteins by isotope tagging is that it provides a direct quantitative measurement of what fraction of each protein is localized to each cellular compartment, whereas the other techniques associate proteins showing similar profiles in a density centrifugation gradient while not describing the relative fraction of proteins in all locations. The spatial proteomics approach thus facilitates the comparison of protein localization under different conditions. We applied this spatial proteomics technique to determine the subcellular localization of over 2,000 proteins in HCT116 cells and then compared changes in localization following exposure to the topoisomerase inhibitor etoposide.     

A Review of the Salivary Proteome and Peptidome and Saliva-derived Peptide Therapeutics

Saliva is a glandular secretion that is vital in the maintenance of healthy oral tissues. In this review we outline the high abundance salivary proteins, summarise the status of the salivary proteome and peptidome, the genetic origin and recognised functions of these proteins, the diseases associated with salivary disorders, and the emerging saliva-derived peptide therapeutics. Different proteomic approaches have reported the identification of over 1,300 proteins in saliva. However there are fewer than 100 high abundance proteins, identified by multiple methods including, two-dimensional polyacrylamide gel electrophoresis and HPLC combined with mass spectrometry. Analysis of the genes coding for the salivary proteins demonstrated a non-uniform chromosomal distribution with chromosome 4 having the largest proportion of genes expressed in salivary glands. Several diseases are associated with salivary disorders including Sjögren’s syndrome, Prader-Willi syndrome, dental caries and stress related disorders. Saliva as a diagnostic medium for various biochemical tests has provided a non-invasive and accessibility advantage over other more regularly tested body fluids such as blood and urine. To-date the emerging saliva-based therapeutics include artificial salivas and antimicrobial agents based on histatins and mucins.     

Confetti: A Multiprotease Map of the HeLa Proteome for Comprehensive Proteomics

Bottom-up proteomics largely relies on tryptic peptides for protein identification and quantification. Tryptic digestion often provides limited coverage of protein sequence because of issues such as peptide length, ionization efficiency, and post-translational modification colocalization. Unfortunately, a region of interest in a protein, for example, because of proximity to an active site or the presence of important post-translational modifications, may not be covered by tryptic peptides. Detection limits, quantification accuracy, and isoform differentiation can also be improved with greater sequence coverage. Selected reaction monitoring (SRM) would also greatly benefit from being able to identify additional targetable sequences. In an attempt to improve protein sequence coverage and to target regions of proteins that do not generate useful tryptic peptides, we deployed a multiprotease strategy on the HeLa proteome. First, we used seven commercially available enzymes in single, double, and triple enzyme combinations. A total of 48 digests were performed. 5223 proteins were detected by analyzing the unfractionated cell lysate digest directly; with 42% mean sequence coverage. Additional strong-anion exchange fractionation of the most complementary digests permitted identification of over 3000 more proteins, with improved mean sequence coverage. We then constructed a web application (https://proteomics.swmed.edu/confetti) that allows the community to examine a target protein or protein isoform in order to discover the enzyme or combination of enzymes that would yield peptides spanning a certain region of interest in the sequence. Finally, we examined the use of nontryptic digests for SRM. From our strong-anion exchange fractionation data, we were able to identify three or more proteotypic SRM candidates within a single digest for 6056 genes. Surprisingly, in 25% of these cases the digest producing the most observable proteotypic peptides was neither trypsin nor Lys-C. SRM analysis of Asp-N versus tryptic peptides for eight proteins determined that Asp-N yielded higher signal in five of eight cases.Mass-spectrometry based proteomics provides various tools to detect and quantify changes in protein expression or post-translational modifications (PTMs).¹ In bottom-up proteomics, these analyses typically involve using peptides derived from the tryptic digestion of proteins. Although trypsin is a robust enzyme and provides peptides suitable for mass spectrometry, not all sequences are detectable by this approach (1). Sequences may be missed because of the limited number and uneven distribution of lysine and arginine residues throughout a protein sequence. Tryptic coverage of interesting regions of sequence, such as trans-membrane domains that may contain notable PTMs, is often incomplete (2). Sequence coverage greater than that offered by trypsin is a requirement for many studies (3).Missing sequence coverage can also adversely affect analysis by selected reaction monitoring (SRM). Although SRM has emerged in recent years as a highly sensitive and accurate method for protein detection and quantification (4), it is sometimes hampered by the limited number of targetable peptides (primarily tryptic peptides) available in public databases. Improving amino acid sequence coverage would provide more targets for SRM assay development, facilitating protein quantification and the ability to target specific isoforms or sequence regions of interest.Fractionation is commonly employed to increase protein identifications and improve sequence coverage, but introduces a number of complexities. Separation of proteins or peptides significantly increases the number of samples to analyze and the amount of data to process. Species may be present in multiple fractions or in different fractions in different runs, which makes quantitative analysis with techniques like SRM difficult. However, SRM has sufficient sensitivity that peptides identified in fractionated discovery experiments are often targetable in whole lysate (5).One approach to increase sequence coverage without fractionation or purification is to use proteases other than trypsin for digestion (6, 7). In recent years, there has been a surge in the use of alternative proteases to improve sequence coverage. Biringer et al. demonstrated in 2006 that combining the MS data from tryptic and Glu-C digestions of human cerebrospinal fluid (CSF) resulted in increased protein identifications. Sequence coverage also improved versus individual enzyme digests, though this was shown only for the 38 most confidently identified proteins (8). In 2010, Swaney et al. expanded the multi-enzyme approach to five specific proteases (trypsin, Lys-C, Arg-C, Asp-N, and Glu-C) and showed that although this method only modestly increases the number of protein IDs, it significantly increases the average sequence coverage (from 24.5% to 43.4%) (9). The most comprehensive coverage of a human cell line to date was reported by Nagaraj et al., in which in-depth proteomics with two levels of prefractionation and analysis using trypsin, Lys-C, and Glu-C was carried out for the HeLa cell line. A total of 10,255 proteins and 166,420 peptides were identified (10). However, none of these studies investigated the use of consecutive enzymatic digestion on a sample.The Mann laboratory recently introduced a strategy, using consecutive digestion in conjunction with filter-aided sample preparation (FASP), for two-step and three-step digestions with various combinations of trypsin, Lys-C, Glu-C, Arg-C, and Asp-N (11). The consecutive use of Lys-C and trypsin enabled the identification of up to 40% more proteins and phosphorylation sites in comparison to trypsin alone. However, a systematic study of all common commercially available proteases for comprehensive mapping of the human proteome has not yet been performed.These prior studies have clearly shown the ability of tandem and parallel protease digestion to improve protein ID and sequence coverage. However, their focus has been either to improve the number of protein identifications or to improve the sequence coverage of few targets. In an effort to provide a resource for targeting as much of the amino acid sequence in a human cell line as possible, we conducted a comprehensive study in which seven commercially available enzymes were used individually and in combination. First, we digested HeLa lysate with a total of 48 single, double, and triple enzyme combinations. Across these combinations we detected 5223 proteins with an average of 42% sequence coverage by analyzing the total cell lysate digest without fractionation. We then selected the best five complementary digests for each of Orbitrap elite collision induced dissociation (CID) and Q exactive higher-energy CID (HCD) analyses. A strong-anion exchange fractionation strategy was applied to these best digests, from which we were able to identify 8470 proteins with 40.3% mean sequence coverage. Combining all digests, both unfractionated and SAX, gave 8539 proteins with 44.7% mean coverage. These data are now publically available (https://proteomics.swmed.edu/confetti) and can be queried using a simple web interface to discover the enzyme or combination of enzymes required to yield a peptide spanning a certain region of interest on a protein.Finally, we performed a proof-of-concept experiment to demonstrate that SRM assays using nontryptic peptides are viable, and in some cases more sensitive than tryptic assays. Though tryptic peptides are generally sufficient for protein quantification by SRM we believe there will be increased use of nontryptic SRM as coverage of specific regions of sequence becomes more important. For example, bio-marker studies considering the presence of specific PTMs rather than general protein abundance are increasingly common. Truly comprehensive PTM studies require access to the nontryptic proteome.