Reversed-phase chromatography with multiple fraction concatenation strategy for proteome profiling of human MCF10A cells

Complementary PTM Profiling of Drug Response in Human Gastric Carcinoma by Immunoaffinity and IMAC Methods with Total Proteome Analysis

Gaining insight into normal cellular signaling and disease biology is a critical goal of proteomic analyses. The ability to perform these studies successfully to extract the maximum value and discovery of biologically relevant candidate biomarkers is therefore of primary importance. Many successful studies in the past have focused on total proteome analysis (changes at the protein level) combined with phosphorylation analysis by metal affinity enrichment (changes at the PTM level). Here, we use the gastric carcinoma cell line MKN-45 treated with the c-Met inhibitor SU11274 and PKC inhibitor staurosporine to investigate the most efficient and most comprehensive strategies for both total protein and PTM analysis. Under the conditions used, total protein analysis yielded few changes in response to either compound, while analysis of phosphorylation identified thousands of sites that changed differentially between the two treatments. Both metal affinity and antibody-based enrichments were used to assess phosphopeptide changes, and the data generated by the two methods was largely complementary (non-overlapping). Label-free quantitation of peptide peak abundances was used to accurately determine fold-changes between control and treated samples. Protein interaction network analysis allowed the data to be placed in a biologically relevant context, and follow-up validation of selected findings confirmed the accuracy of the proteomic data. Together, this study provides a framework for start-to-finish proteomic analysis of any experimental system under investigation to maximize the value of the proteomic study and yield the best chance for uncovering actionable target candidates.

Serum Proteome Profiles in Stricturing Crohn's Disease: A Pilot Study

BACKGROUND

Crohn's disease (CD) is a form of inflammatory bowel disease with different described behaviors, including stricture. At present, there are no laboratory studies that can differentiate stricturing CD from other phenotypes of inflammatory bowel disease. We performed a pilot study to examine differences in the proteome among patients with stricturing CD, nonstricturing CD, and ulcerative colitis.

METHODS

Serum samples were selected from the Ocean State Crohn's and Colitis Area Registry, an established cohort of patients with inflammatory bowel disease. Patients with CD with surgically resected stricture were matched with similar patients with CD without known stricture and with ulcerative colitis. Serum samples from each patient were digested and analyzed using liquid chromatography-mass spectrometry to characterize the proteome. Statistical analyses were performed to identify peptides and proteins that can differentiate CD with stricture.

RESULTS

Samples from 9 patients in each group (27 total patients) were analyzed. Baseline demographic characteristics were similar among the 3 groups. We quantified 7668 peptides and 897 proteins for analysis. Receiver operating characteristic analysis identified a subset of peptides with an area under the curve greater than 0.9, indicating greater separation potential. Partial least squares discriminant analysis was able to distinguish among the three groups with up to 70% accuracy by peptides and up to 80% accuracy by proteins. We identified the significantly different proteins and peptides and determined their function based on previously published literature.

CONCLUSIONS

The serum of patients with stricturing CD, nonstricturing CD, and ulcerative colitis is distinguishable through proteomic analysis. Some of the proteins that differentiate the stricturing phenotype have been implicated in complement activation, fibrinolytic pathways, and lymphocyte adhesion.

Dynamic Proteomics: In Vivo Proteome-Wide Measurement of Protein Kinetics Using Metabolic Labeling

Control of biosynthetic and catabolic rates of polymers, including proteins, stands at the center of phenotype, physiologic adaptation, and disease pathogenesis. Advances in stable isotope-labeling concepts and mass spectrometric instrumentation now allow accurate in vivo measurement of protein synthesis and turnover rates, both for targeted proteins and for unbiased screening across the proteome. We describe here the underlying principles and operational protocols for measuring protein dynamics, focusing on metabolic labeling with (2)H2O (heavy water) combined with tandem mass spectrometric analysis of mass isotopomer abundances in trypsin-generated peptides. The core principles of combinatorial analysis (mass isotopomer distribution analysis or MIDA) are reviewed in detail, including practical advantages, limitations, and technical procedures to ensure optimal kinetic results. Technical factors include heavy water labeling protocols, optimal duration of labeling, clean up and simplification of sample matrices, accurate quantitation of mass isotopomer abundances in peptides, criteria for adequacy of mass spectrometric abundance measurements, and calculation algorithms. Some applications are described, including the noninvasive "virtual biopsy" strategy for measuring molecular flux rates in tissues through measurements in body fluids. In addition, application of heavy water labeling to measure flux lipidomics is noted. In summary, the combination of stable isotope labeling, particularly from (2)H2O, with tandem mass spectrometric analysis of mass isotopomer abundances in peptides, provides a powerful approach for characterizing the dynamics of proteins across the global proteome. Many applications in research and clinical medicine have been achieved and many others can be envisioned.

Exploring G protein-coupled receptor signaling networks using SILAC-based phosphoproteomics

The type 1 parathyroid hormone receptor (PTH1R) is a key regulator of calcium homeostasis and bone turnover. Here, we employed SILAC-based quantitative mass spectrometry and bioinformatic pathways analysis to examine global changes in protein phosphorylation following short-term stimulation of endogenously expressed PTH1R in osteoblastic cells in vitro. Following 5min exposure to the conventional agonist, PTH(1-34), we detected significant changes in the phosphorylation of 224 distinct proteins. Kinase substrate motif enrichment demonstrated that consensus motifs for PKA and CAMK2 were the most heavily upregulated within the phosphoproteome, while consensus motifs for mitogen-activated protein kinases were strongly downregulated. Signaling pathways analysis identified ERK1/2 and AKT as important nodal kinases in the downstream network and revealed strong regulation of small GTPases involved in cytoskeletal rearrangement, cell motility, and focal adhesion complex signaling. Our data illustrate the utility of quantitative mass spectrometry in measuring dynamic changes in protein phosphorylation following GPCR activation.

Discovery of novel vitamin D-regulated proteins in INS-1 cells: a proteomic approach

BACKGROUND

Experimental evidence indicates that vitamin D may have a beneficial role in pancreatic β-cell function. Global gene expression studies have shown that the active metabolite 1,25-dihydroxyvitamin D3 [1,25-(OH)2 D3 ] modulates genes involved in ion transport, lipid metabolism and insulin secretion.

METHODS

We employed stable isotope labelling by amino acids in cell culture in combination with liquid chromatography-tandem mass spectrometry to quantitatively assess the impact of two vitamin D metabolites, 1,25-(OH)2 D3 and 25-hydroxyvitamin D3 [25-(OH)D3 ], on global protein expression on a model rat β-cell line, insulinoma-derived INS-1 cells.

RESULTS

Although treatment with 1,25-(OH)2 D3 resulted in 31 differentially expressed proteins, 25-(OH)D3 had no impact on protein expression. Of these 31 proteins, 29 were upregulated, whereas two showed a decrease in abundance. Proteins whose expression levels markedly increased in the presence of 1,25-(OH)2 D3 included Crat, Hmgn2, Protein Tmsbl1 and Gdap1. One of the most important findings in this study is upregulation of proteins implicated in insulin granule motility and insulin exocytosis, suggesting a positive effect on insulin secretion. Moreover, modulation of several membrane transport proteins suggests that 1,25-(OH)2 D3 has an impact on the homeostatic regulation of ions, which is critical for most functions in the β-cell.

CONCLUSIONS

In this study, we discovered a number of novel 1,25-(OH)2 D3 -regulated proteins, which may contribute to a better understanding of the reported beneficial effects of vitamin D on pancreatic β-cells. All in all, our findings should pave the way for future studies providing insights into molecular mechanisms by which 1,25-(OH)2 D3 regulates protein expression in pancreatic β-cells.

The impact of fertilization on the chicken egg yolk plasma and granule proteome 24 hours post-lay at room temperature: capitalizing on high-pH/low-pH reverse phase chromatography in conjunction with tandem mass tag (TMT) technology

Chicken egg yolk is a rich source of nutrients providing high quality proteins, vitamins, minerals, carotenoids and antioxidants. Chicken egg yolk, recovered from whole egg within 24 hours post-lay has been utilized as a starting material in the preparation of a dietary supplement that has been demonstrated to lead to gains in muscle mass in a human clinical study. Further, an oil derived from chicken egg yolk has been utilized as a topical agent to treat third degree burn injury. The molecular changes that take place in fertilized, chicken egg yolk during the first 24 hours post-lay are not well understood. By studying how the protein composition of egg yolk varies with fertility status, one can utilize this knowledge to develop egg yolk-based products that have been optimized for specific applications. In this study, a direct quantitative comparison was made between the proteome of fertilized chicken egg yolk and the proteome of unfertilized chicken egg yolk, both maintained at 20 °C and analyzed within 24 hours post-lay. Egg yolk proteins from each fertility state were digested with trypsin, labeled with distinct chemical labels (tandem mass tag reagents) and then combined in a 1 : 1 ratio. A TMT-labeled tryptic digest derived from chicken egg yolk proteins (fertilized and unfertilized) was separated using high-pH/low-pH reverse-phase chromatography and analyzed using mass spectrometry. 225 protein identifications were made from this TMT-labeled tryptic digest based on a minimum of 2 unique peptides observed per protein. 9 proteins increased in abundance in fertilized egg yolk relative to unfertilized egg yolk and 9 proteins decreased in abundance in fertilized egg yolk relative to unfertilized egg yolk. Some proteins that increased in abundance in fertilized egg yolk play an important role in angiogenesis (pleiotrophin, histidine rich glycoprotein) and defense against pathogens (mannose-binding lectin, β-defensin 11, serum amyloid P-component, ovostatin). Based on this study, fertilized chicken egg yolk may be more useful as a starting material relative to unfertilized chicken egg yolk for the purpose of enriching or isolating proteins with pro-angiogenic and anti-microbial properties.

Detecting Significant Changes in Protein Abundance

We review and demonstrate how an empirical Bayes method, shrinking a protein's sample variance towards a pooled estimate, leads to far more powerful and stable inference to detect significant changes in protein abundance compared to ordinary t-tests. Using examples from isobaric mass labeled proteomic experiments we show how to analyze data from multiple experiments simultaneously, and discuss the effects of missing data on the inference. We also present easy to use open source software for normalization of mass spectrometry data and inference based on moderated test statistics.

The Impact II, a Very High-Resolution Quadrupole Time-of-Flight Instrument (QTOF) for Deep Shotgun Proteomics

Hybrid quadrupole time-of-flight (QTOF) mass spectrometry is one of the two major principles used in proteomics. Although based on simple fundamentals, it has over the last decades greatly evolved in terms of achievable resolution, mass accuracy, and dynamic range. The Bruker impact platform of QTOF instruments takes advantage of these developments and here we develop and evaluate the impact II for shotgun proteomics applications. Adaption of our heated liquid chromatography system achieved very narrow peptide elution peaks. The impact II is equipped with a new collision cell with both axial and radial ion ejection, more than doubling ion extraction at high tandem MS frequencies. The new reflectron and detector improve resolving power compared with the previous model up to 80%, i.e. to 40,000 at m/z 1222. We analyzed the ion current from the inlet capillary and found very high transmission (>80%) up to the collision cell. Simulation and measurement indicated 60% transfer into the flight tube. We adapted MaxQuant for QTOF data, improving absolute average mass deviations to better than 1.45 ppm. More than 4800 proteins can be identified in a single run of HeLa digest in a 90 min gradient. The workflow achieved high technical reproducibility (R2 > 0.99) and accurate fold change determination in spike-in experiments in complex mixtures. Using label-free quantification we rapidly quantified haploid against diploid yeast and characterized overall proteome differences in mouse cell lines originating from different tissues. Finally, after high pH reversed-phase fractionation we identified 9515 proteins in a triplicate measurement of HeLa peptide mixture and 11,257 proteins in single measurements of cerebellum—the highest proteome coverage reported with a QTOF instrument so far.

Systematic evaluation of label-free and super-SILAC quantification for proteome expression analysis

RATIONALE

Advanced implementations of mass spectrometry (MS)-based proteomics allow for comprehensive proteome expression profiling across many biological samples. The outcome of such studies critically depends on accurate and precise quantification, which has to be ensured for high-coverage proteome analysis possible on fast and sensitive mass spectrometers such as quadrupole orbitrap instruments.

METHODS

We conducted ultra-high-performance liquid chromatography (UHPLC)/MS experiments on a Q Exactive to systematically compare label-free proteome quantification across six human cancer cell lines with quantification against a shared reference mix generated by stable isotope labeling with amino acids in cell culture (super-SILAC).

RESULTS

Single-shot experiments identified on average about 5000 proteins in the label-free compared to about 3500 in super-SILAC experiments. Label-free quantification was slightly less precise than super-SILAC in replicate measurements, verifying previous results obtained for lower proteome coverage. Due to the higher number of quantified proteins, more significant differences were detected in label-free cell line comparisons, whereas a higher percentage of quantified proteins was identified as differentially expressed in super-SILAC experiments. Additional label-free replicate analyses effectively compensated for lower precision of quantification. Finally, peptide fractionation by high pH reversed-phase chromatography prior to LC/MS analysis further increased the robustness and precision of label-free quantification in conjunction with higher proteome coverage.

CONCLUSIONS

Our results benchmark and highlight the utility of label-free proteome quantification for applications such as target and biomarker discovery on state-of-the-art UHPLC/MS workflows.

Multiplexed, Quantitative Workflow for Sensitive Biomarker Discovery in Plasma Yields Novel Candidates for Early Myocardial Injury

We have developed a novel plasma protein analysis platform with optimized sample preparation, chromatography, and MS analysis protocols. The workflow, which utilizes chemical isobaric mass tag labeling for relative quantification of plasma proteins, achieves far greater depth of proteome detection and quantification while simultaneously having increased sample throughput than prior methods. We applied the new workflow to a time series of plasma samples from patients undergoing a therapeutic, "planned" myocardial infarction for hypertrophic cardiomyopathy, a unique human model in which each person serves as their own biologic control. Over 5300 proteins were confidently identified in our experiments with an average of 4600 proteins identified per sample (with two or more distinct peptides identified per protein) using iTRAQ four-plex labeling. Nearly 3400 proteins were quantified in common across all 16 patient samples. Compared with a previously published label-free approach, the new method quantified almost fivefold more proteins/sample and provided a six- to nine-fold increase in sample analysis throughput. Moreover, this study provides the largest high-confidence plasma proteome dataset available to date. The reliability of relative quantification was also greatly improved relative to the label-free approach, with measured iTRAQ ratios and temporal trends correlating well with results from a 23-plex immunoMRM (iMRM) assay containing a subset of the candidate proteins applied to the same patient samples. The functional importance of improved detection and quantification was reflected in a markedly expanded list of significantly regulated proteins that provided many new candidate biomarker proteins. Preliminary evaluation of plasma sample labeling with TMT six-plex and ten-plex reagents suggests that even further increases in multiplexing of plasma analysis are practically achievable without significant losses in depth of detection relative to iTRAQ four-plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments.

Synechococcus elongatus UTEX 2973, a fast growing cyanobacterial chassis for biosynthesis using light and CO₂

Photosynthetic microbes are of emerging interest as production organisms in biotechnology because they can grow autotrophically using sunlight, an abundant energy source, and CO₂, a greenhouse gas. Important traits for such microbes are fast growth and amenability to genetic manipulation. Here we describe Synechococcuselongatus UTEX 2973, a unicellular cyanobacterium capable of rapid autotrophic growth, comparable to heterotrophic industrial hosts such as yeast. Synechococcus UTEX 2973 can be readily transformed for facile generation of desired knockout and knock-in mutations. Genome sequencing coupled with global proteomics studies revealed that Synechococcus UTEX 2973 is a close relative of the widely studied cyanobacterium Synechococcuselongatus PCC 7942, an organism that grows more than two times slower. A small number of nucleotide changes are the only significant differences between the genomes of these two cyanobacterial strains. Thus, our study has unraveled genetic determinants necessary for rapid growth of cyanobacterial strains of significant industrial potential.

Urine, peritoneal fluid and omental fat proteomes of reproductive age women: Endometriosis-related changes and associations with endocrine disrupting chemicals

Endometriosis, ectopic growth of the uterine lining (endometrium), which affects 6-11% of reproductive age women, is associated with pelvic pain and infertility. We investigated the peritoneal fluid (PF), urine and omental fat (OF) proteomes of women with endometriosis vs. individuals with no surgically visualized endometriosis. All participants were enrolled in the NICHD-funded ENDO Study. A two-step proteomic study was performed. The first, a broad survey, employed a semi-quantitative gel LC-mass spectrometry (MS) workflow: SDS PAGE fractionation, trypsin digestion and LC-MS/MS. The results showed sample integrity but failed to detect any differences between women with and without endometriosis. The second step was a quantitative analysis of OF samples. We employed another sample set (n=30) from women ± disease and isobaric mass-tag (iTRAQ) chemistry to label peptides and 2D LC-MS/MS for protein identification and quantification. Three proteins-matrix metalloproteinase-9, neutrophil elastase, and FAM49B-were significantly lower in abundance in samples from women with endometriosis. Interestingly, neutrophil elastase and FAM49B levels were associated with higher levels of a subset of endocrine disrupting chemicals (EDCs) that were previously measured in the same samples. The results of these experiments showed the feasibility of associating endometriosis with changes in the OF protein repertoire and EDC levels.

BIOLOGICAL SIGNIFICANCE

Endometriosis, pathological growth of the uterine lining, is associated with significant morbidities, including pain and infertility. However, the causes of this common condition are poorly understood. This study determined whether endometriosis was associated with changes in the protein composition of peritoneal fluid, urine and/or omental fat. A protein of unknown function (FAM49B) and two proteinases (metalloproteinase-9, neutrophil elastase) were down regulated in OF samples from women with versus without endometriosis. These findings suggested proteinase imbalances at sites that were distant from the endometriotic lesions. Additionally, FAM49B and neutrophil elastase levels were associated with higher levels of a subset of environmental chemicals that were quantified in the same samples, suggesting other possible associations. Thus, this work generated hypotheses that will be tested in further studies.

A versatile reversed phase-strong cation exchange-reversed phase (RP–SCX–RP) multidimensional liquid chromatography platform for qualitative and quantitative shotgun proteomics

We developed a novel online MDLC platform that integrates a dual-trap configuration and two separation technologies into a single automated commercial platform.

Organoid models of human and mouse ductal pancreatic cancer

Pancreatic cancer is one of the most lethal malignancies due to its late diagnosis and limited response to treatment. Tractable methods to identify and interrogate pathways involved in pancreatic tumorigenesis are urgently needed. We established organoid models from normal and neoplastic murine and human pancreas tissues. Pancreatic organoids can be rapidly generated from resected tumors and biopsies, survive cryopreservation, and exhibit ductal- and disease-stage-specific characteristics. Orthotopically transplanted neoplastic organoids recapitulate the full spectrum of tumor development by forming early-grade neoplasms that progress to locally invasive and metastatic carcinomas. Due to their ability to be genetically manipulated, organoids are a platform to probe genetic cooperation. Comprehensive transcriptional and proteomic analyses of murine pancreatic organoids revealed genes and pathways altered during disease progression. The confirmation of many of these protein changes in human tissues demonstrates that organoids are a facile model system to discover characteristics of this deadly malignancy.

An integrated approach for genome annotation of the eukaryotic thermophile Chaetomium thermophilum

The thermophilic fungus Chaetomium thermophilum holds great promise for structural biology. To increase the efficiency of its biochemical and structural characterization and to explore its thermophilic properties beyond those of individual proteins, we obtained transcriptomics and proteomics data, and integrated them with computational annotation methods and a multitude of biochemical experiments conducted by the structural biology community. We considerably improved the genome annotation of Chaetomium thermophilum and characterized the transcripts and expression of thousands of genes. We furthermore show that the composition and structure of the expressed proteome of Chaetomium thermophilum is similar to its mesophilic relatives. Data were deposited in a publicly available repository and provide a rich source to the structural biology community.

Systematic optimization of long gradient chromatography mass spectrometry for deep analysis of brain proteome

The development of high-resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC-MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse-phase long column (100 μm × 150 cm, 5 μm C18 beads) coupled to Q Exactive MS. The column was capable of achieving a peak capacity of ∼700 in a 720 min gradient of 10-45% acetonitrile. The optimal loading level was ∼6 μg of peptides, although the column allowed loading as many as 20 μg. Gas-phase fractionation of peptide ions further increased the number of peptide identification by ∼10%. Moreover, the combination of basic pH LC prefractionation with the long gradient LC-MS/MS platform enabled the identification of 96,127 peptides and 10,544 proteins at 1% protein false discovery rate in a post-mortem brain sample of Alzheimer's disease. Because deep RNA sequencing of the same specimen suggested that ∼16,000 genes were expressed, the current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC-MS/MS platform were also discussed.

A chemical proteomics approach for global analysis of lysine monomethylome profiling

Methylation of lysine residues on histone proteins is known to play an important role in chromatin structure and function. However, non-histone protein substrates of this modification remain largely unknown. An effective approach for system-wide analysis of protein lysine methylation, particularly lysine monomethylation, is lacking. Here we describe a chemical proteomics approach for global screening for monomethyllysine substrates, involving chemical propionylation of monomethylated lysine, affinity enrichment of the modified monomethylated peptides, and HPLC/MS/MS analysis. Using this approach, we identified with high confidence 446 lysine monomethylation sites in 398 proteins, including three previously unknown histone monomethylation marks, representing the largest data set of protein lysine monomethylation described to date. Our data not only confirms previously discovered lysine methylation substrates in the nucleus and spliceosome, but also reveals new substrates associated with diverse biological processes. This method hence offers a powerful approach for dynamic study of protein lysine monomethylation under diverse cellular conditions and in human diseases.

Compact variant-rich customized sequence database and a fast and sensitive database search for efficient proteogenomic analyses

In proteogenomic analysis, construction of a compact, customized database from mRNA-seq data and a sensitive search of both reference and customized databases are essential to accurately determine protein abundances and structural variations at the protein level. However, these tasks have not been systematically explored, but rather performed in an ad-hoc fashion. Here, we present an effective method for constructing a compact database containing comprehensive sequences of sample-specific variants--single nucleotide variants, insertions/deletions, and stop-codon mutations derived from Exome-seq and RNA-seq data. It, however, occupies less space by storing variant peptides, not variant proteins. We also present an efficient search method for both customized and reference databases. The separate searches of the two databases increase the search time, and a unified search is less sensitive to identify variant peptides due to the smaller size of the customized database, compared to the reference database, in the target-decoy setting. Our method searches the unified database once, but performs target-decoy validations separately. Experimental results show that our approach is as fast as the unified search and as sensitive as the separate searches. Our customized database includes mutation information in the headers of variant peptides, thereby facilitating the inspection of peptide-spectrum matches.

Application of clinical proteomics in acute respiratory distress syndrome

Acute Respiratory Distress Syndrome (ARDS) is a devastating cause of hypoxic respiratory failure, which continues to have high mortality. It is expected that a comprehensive systems- level approach will identify global and complex changes that contribute to the development of ARDS and subsequent repair of the damaged lung. In the last decade, powerful genome-wide analytical and informatics tools have been developed, that have provided valuable insights into the mechanisms of complex diseases such as ARDS. These tools include the rapid and precise measure of gene expression at the proteomic level. This article reviews the contemporary proteomics platforms that are available for comprehensive studies in ARDS. The challenges of various biofluids that could be investigated and some of the studies performed are also discussed.

Melatonin regulates proteomic changes during leaf senescence in Malus hupehensis

Despite the relationship between melatonin and aging, the overall changes and regulation of proteome profiling by long-term melatonin exposure during leaf senescence is not well understood. In this study, leaf senescence in Malus hupehensis plants was delayed when exogenous melatonin was regularly applied to the roots for 2 months compared with natural leaf senescence. Proteins of samples 0 and 50 day for both treatments were extracted and labeled with TMT regents before being examined via NanoLC-MS/MS. The proteomics data showed that 622 and 309 proteins were altered by senescence and melatonin, respectively. Our GO analysis by Blast2GO revealed that most of the altered proteins that are involved in major metabolic processes exhibited hydrolase activity and were mainly located in the plastids. These proteins were classified into several senescence-related functional categories, including degradation of macromolecules, redox and stress responses, transport, photosynthesis, development, and other regulatory proteins. We found that melatonin treatment led to the downregulation of proteins that are normally upregulated during senescence. The melatonin-related delay in senescence might have occurred due to the altering of proteins involved in processes associated with senescence. And as well, there are many unknown regulatory proteins possibly being involved in the melatonin's function. This study is the first to demonstrate changes at the proteome level in response to exogenous melatonin in plants. Our findings provide a set of informative and fundamental data about the role of melatonin in apple leaf senescence.

SAHA regulates histone acetylation, Butyrylation, and protein expression in neuroblastoma

Emerging evidence suggests that suberoylanilide hydroxamic acid (SAHA), a clinically approved HDAC inhibitor for cutaneous T-cell lymphoma, shows promising clinical benefits in neuroblastoma, the most common extra cranial solid neoplasm with limited choice of therapeutic intervention. However, the molecular mechanism under which the compound exerts its antitumor effect remains elusive. Here we report a quantitative proteomics study that determines changes of protein expression, histone lysine acetylation, and butyrylation in response to SAHA treatment. We detected and quantified 28 histone lysine acetylation and 18 histone lysine butyrylation marks, most of which are dramatically induced by SAHA. Importantly, we identified 11 histone Kbu sites as novel histone marks in human cells. Furthermore, quantitative proteomic analysis identified 5426 proteins, among which 510 proteins were up-regulated and 508 proteins were down-regulated (significant p value <0.05). The subsequent bioinformatics analysis identified distinct SAHA-response gene ontology (GO) categories and signaling pathways, including cellular metabolism and DNA-dependent pathways. Our study therefore reveals new histone epigenetic marks and offers key insights into the molecular mechanism by which SAHA regulates proteomic changes in neuroblastoma cells and identifies biomarker candidates for SAHA.

Aromatic inhibitors derived from ammonia-pretreated lignocellulose hinder bacterial ethanologenesis by activating regulatory circuits controlling inhibitor efflux and detoxification

Efficient microbial conversion of lignocellulosic hydrolysates to biofuels is a key barrier to the economically viable deployment of lignocellulosic biofuels. A chief contributor to this barrier is the impact on microbial processes and energy metabolism of lignocellulose-derived inhibitors, including phenolic carboxylates, phenolic amides (for ammonia-pretreated biomass), phenolic aldehydes, and furfurals. To understand the bacterial pathways induced by inhibitors present in ammonia-pretreated biomass hydrolysates, which are less well studied than acid-pretreated biomass hydrolysates, we developed and exploited synthetic mimics of ammonia-pretreated corn stover hydrolysate (ACSH). To determine regulatory responses to the inhibitors normally present in ACSH, we measured transcript and protein levels in an Escherichia coli ethanologen using RNA-seq and quantitative proteomics during fermentation to ethanol of synthetic hydrolysates containing or lacking the inhibitors. Our study identified four major regulators mediating these responses, the MarA/SoxS/Rob network, AaeR, FrmR, and YqhC. Induction of these regulons was correlated with a reduced rate of ethanol production, buildup of pyruvate, depletion of ATP and NAD(P)H, and an inhibition of xylose conversion. The aromatic aldehyde inhibitor 5-hydroxymethylfurfural appeared to be reduced to its alcohol form by the ethanologen during fermentation, whereas phenolic acid and amide inhibitors were not metabolized. Together, our findings establish that the major regulatory responses to lignocellulose-derived inhibitors are mediated by transcriptional rather than translational regulators, suggest that energy consumed for inhibitor efflux and detoxification may limit biofuel production, and identify a network of regulators for future synthetic biology efforts.

Quantitative proteomic analysis reveals posttranslational responses to aneuploidy in yeast

Aneuploidy causes severe developmental defects and is a near universal feature of tumor cells. Despite its profound effects, the cellular processes affected by aneuploidy are not well characterized. Here, we examined the consequences of aneuploidy on the proteome of aneuploid budding yeast strains. We show that although protein levels largely scale with gene copy number, subunits of multi-protein complexes are notable exceptions. Posttranslational mechanisms attenuate their expression when their encoding genes are in excess. Our proteomic analyses further revealed a novel aneuploidy-associated protein expression signature characteristic of altered metabolism and redox homeostasis. Indeed aneuploid cells harbor increased levels of reactive oxygen species (ROS). Interestingly, increased protein turnover attenuates ROS levels and this novel aneuploidy-associated signature and improves the fitness of most aneuploid strains. Our results show that aneuploidy causes alterations in metabolism and redox homeostasis. Cells respond to these alterations through both transcriptional and posttranscriptional mechanisms.

DOI:http://dx.doi.org/10.7554/eLife.03023.001

Nearly all tumor cells contain abnormal number of chromosomes. This state is called aneuploidy, and can also cause embryos to be miscarried, or to be born with severe developmental disorders.

Proteins are produced from the genes contained within chromosomes, and so cells with too many chromosomes produce too many of some proteins. How do these cells cope with this excess? Previous work identified one strategy where a gene called UBP6 is mutated to prevent it from working correctly. The UBP6 gene normally encodes a protein that removes a small tag (called ubiquitin) from other proteins. This tag normally marks other proteins that should be degraded; thus, if UBP6 is not working, more proteins are broken down.

Dephoure et al. investigated the effect of aneuploidy on the proteins produced by 12 different types of yeast cell, which each had an extra chromosome. In general, the amount of each protein produced by these yeast increased depending on the number of extra copies of the matching genes found on the extra chromosome. However, this was not the case for around 20% of the proteins, which were found in lower amounts than expected. Dephoure et al. revealed that this was not because fewer proteins were made, but because more were broken down. These proteins may be targeted for degradation because they are unstable, as many of these proteins need to bind to other proteins to keep them stable—but these stabilizing proteins are not also over-produced.

Aneuploidy in cells also has other effects, including changing the cells' metabolism so that the cells grow more slowly and do not respond as well to stress. However, Dephoure et al. found that, as well as reducing the number of proteins produced, deleting the UBP6 gene also increased the fitness of the cells. Targeting the protein encoded by the UBP6 gene, or others that also stop proteins being broken down, could therefore help to reduce the negative effects of aneuploidy for a cell. Whether targeting these genes or proteins could also help to treat the diseases and disorders that result from aneuploidy, such as Alzheimer's and Huntington's disease, remains to be investigated.

DOI:http://dx.doi.org/10.7554/eLife.03023.002

Identification of putative biomarkers for HIV-associated neurocognitive impairment in the CSF of HIV-infected patients under cART therapy determined by mass spectrometry

We identified and measured proteins in the cerebral spinal fluid (CSF) involved in HIV-associated neurological disorders. Protein levels were determined by mass spectrometry (MS) in pooled CSF taken from three patient groups (human immunodeficiency virus (HIV)-1-infected patients that developed HIV-associated neurocognitive disorders (HANDs), HIV-1-infected patients without HAND, and healthy controls). Pools were generated from 10 patients each per group. CSF from individual patient groups were digested with trypsin and separately labeled using with isobaric tags for relative and absolute quantitation (iTRAQ). After combining all samples in one, peptides were extensively fractionated by offline two-dimensional separation and identified by tandem MS. One hundred and ninety three proteins were deemed to be interpretable for quantitation based on permutation tests with a 95 % confidence interval with a p value ≤ 0.05. Using a cutoff of 1.5-fold for upregulation and 0.6 for downregulation, 16 proteins were differentially expressed in HIV + HAND (reporter p value ≤0.05) with seven of them previously described as HIV-interacting proteins: endoplasmin, mitochondrial damage mediator-BH3-interacting domanin death agonist, orosomucoid, apolipoprotein E, metalloproteinase inhibitor 2, peroxiredoxin-2, and the nuclear protein, ruvB-like 2. Several previously unidentified proteins with possible neurological implication in HIV patients include forming-binding protein 1, C-reactive protein, leukocyte-associated immunoglobulin receptor 1, renin receptor, mediator of RNA polymerase II transcription subunit 14, multimerin-2, alpha-N-acetylglucosaminidase, caldesmon, and cadherin EGF LAG G-type receptor. Our results suggest that not only a few but possibly a combination of biomarkers that are highly correlated can predict neurocognitive status in HIV-infected patients and might be involved in monocyte or macrophage activation.

A method to determine lysine acetylation stoichiometries

Lysine acetylation is a common protein posttranslational modification that regulates a variety of biological processes. A major bottleneck to fully understanding the functional aspects of lysine acetylation is the difficulty in measuring the proportion of lysine residues that are acetylated. Here we describe a mass spectrometry method using a combination of isotope labeling and detection of a diagnostic fragment ion to determine the stoichiometry of protein lysine acetylation. Using this technique, we determined the modification occupancy for ~750 acetylated peptides from mammalian cell lysates. Furthermore, the acetylation on N-terminal tail of histone H4 was cross-validated by treating cells with sodium butyrate, a potent deacetylase inhibitor, and comparing changes in stoichiometry levels measured by our method with immunoblotting measurements. Of note we observe that acetylation stoichiometry is high in nuclear proteins, but very low in mitochondrial and cytosolic proteins. In summary, our method opens new opportunities to study in detail the relationship of lysine acetylation levels of proteins with their biological functions.

A draft map of the human proteome

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here, we present a draft map of the human proteome using high resolution Fourier transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples including 17 adult tissues, 7 fetal tissues and 6 purified primary hematopoietic cells resulted in identification of proteins encoded by 17,294 genes accounting for ~84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream ORFs. This large human proteome catalog (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Estimating influence of cofragmentation on peptide quantification and identification in iTRAQ experiments by simulating multiplexed spectra

Isobaric tag-based quantification such as iTRAQ and TMT is a promising approach to mass spectrometry-based quantification in proteomics as it provides wide proteome coverage with greatly increased experimental throughput. However, it is known to suffer from inaccurate quantification and identification of a target peptide due to cofragmentation of multiple peptides, which likely leads to under-estimation of differentially expressed peptides (DEPs). A simple method of filtering out cofragmented spectra with less than 100% precursor isolation purity (PIP) would decrease the coverage of iTRAQ/TMT experiments. In order to estimate the impact of cofragmentation on quantification and identification of iTRAQ-labeled peptide samples, we generated multiplexed spectra with varying degrees of PIP by mixing the two MS/MS spectra of 100% PIP obtained in global proteome profiling experiments on gastric tumor-normal tissue pair proteomes labeled by 4-plex iTRAQ. Despite cofragmentation, the simulation experiments showed that more than 99% of multiplexed spectra with PIP greater than 80% were correctly identified by three different database search engines-MODa, MS-GF+, and Proteome Discoverer. Using the multiplexed spectra that have been correctly identified, we estimated the effect of cofragmentation on peptide quantification. In 74% of the multiplexed spectra, however, the cancer-to-normal expression ratio was compressed, and a fair number of spectra showed the "ratio inflation" phenomenon. On the basis of the estimated distribution of distortions on quantification, we were able to calculate cutoff values for DEP detection from cofragmented spectra, which were corrected according to a specific PIP and probability of type I (or type II) error. When we applied these corrected cutoff values to real cofragmented spectra with PIP larger than or equal to 70%, we were able to identify reliable DEPs by removing about 25% of DEPs, which are highly likely to be false positives. Our experimental results provide useful insight into the effect of cofragmentation on isobaric tag-based quantification methods. The simulation procedure as well as the corrected cutoff calculation method could be adopted for quantifying the effect of cofragmentation and reducing false positives (or false negatives) in the DEP identification with general quantification experiments based on isobaric labeling techniques.

The proteome and phosphoproteome of Neurospora crassa in response to cellulose, sucrose and carbon starvation

Improving cellulolytic enzyme production by plant biomass degrading fungi holds great potential in reducing costs associated with production of next-generation biofuels generated from lignocellulose. How fungi sense cellulosic materials and respond by secreting enzymes has mainly been examined by assessing function of transcriptional regulators and via transcriptional profiling. Here, we obtained global proteomic and phosphoproteomic profiles of the plant biomass degrading filamentous fungus Neurospora crassa grown on different carbon sources, i.e. sucrose, no carbon, and cellulose, by performing isobaric tags for relative and absolute quantification (iTRAQ)-based LC-MS/MS analyses. A comparison between proteomes and transcriptomes under identical carbon conditions suggests that extensive post-transcriptional regulation occurs in N. crassa in response to exposure to cellulosic material. Several hundred amino acid residues with differential phosphorylation levels on crystalline cellulose (Avicel) or carbon-free medium vs sucrose medium were identified, including phosphorylation sites in a major transcriptional activator for cellulase genes, CLR1, as well as a cellobionic acid transporter, CBT1. Mutation of phosphorylation sites on CLR1 did not have a major effect on transactivation of cellulase production, while mutation of phosphorylation sites in CBT1 increased its transporting capacity. Our data provides rich information at both the protein and phosphorylation levels of the early cellular responses to carbon starvation and cellulosic induction and aids in a greater understanding of the underlying post-transcriptional regulatory mechanisms in filamentous fungi.

High-throughput absolute quantification of proteins using an improved two-dimensional reversed-phase separation and quantification concatemer (QconCAT) approach

Stable isotope dilution-selective reaction monitoring-mass spectrometry (SID-SRM-MS) has been widely used for the absolute quantitative analysis of proteins. However, when performing the large-scale absolute quantification of proteins from a more complex tissue sample, such as mouse liver, in addition to a high-throughput approach for the preparation and calibration of large amounts of stable-isotope-labelled internal standards, a more powerful separation method prior to SRM analysis is also urgently needed. To address these challenges, a high-throughput absolute quantification strategy based on an improved two-dimensional reversed-phase (2D RP) separation and quantification concatemer (QconCAT) approach is presented in this study. This strategy can be used to perform the simultaneous quantification of hundreds of proteins from mouse liver within one week of total MS measurement time. By using calibrated synthesised peptides from the protein glutathione S-transferase (GST), large amounts of GST-tagged QconCAT internal standards corresponding to hundreds of proteins can be accurately and rapidly quantified. Additionally, using an improved 2D RP separation method, a mixture containing a digested sample and QconCAT standards can be efficiently separated and absolutely quantified. When a maximum gradient of 72 min is employed in the first LC dimension, resulting in 72 fractions, identification and absolute quantification experiments for all fractions can be completed within one week of total MS measurement time. The quantification approach developed here can further extend the dynamic range and increase the analytical sensitivity of SRM analysis of complex tissue samples, thereby helping to increase the coverage of absolute quantification in a whole proteome.

In Silico Proteome Cleavage Reveals Iterative Digestion Strategy for High Sequence Coverage

In the postgenome era, biologists have sought to measure the complete complement of proteins, termed proteomics. Currently, the most effective method to measure the proteome is with shotgun, or bottom-up, proteomics, in which the proteome is digested into peptides that are identified followed by protein inference. Despite continuous improvements to all steps of the shotgun proteomics workflow, observed proteome coverage is often low; some proteins are identified by a single peptide sequence. Complete proteome sequence coverage would allow comprehensive characterization of RNA splicing variants and all posttranslational modifications, which would drastically improve the accuracy of biological models. There are many reasons for the sequence coverage deficit, but ultimately peptide length determines sequence observability. Peptides that are too short are lost because they match many protein sequences and their true origin is ambiguous. The maximum observable peptide length is determined by several analytical challenges. This paper explores computationally how peptide lengths produced from several common proteome digestion methods limit observable proteome coverage. Iterative proteome cleavage strategies are also explored. These simulations reveal that maximized proteome coverage can be achieved by use of an iterative digestion protocol involving multiple proteases and chemical cleavages that theoretically allow 92.9% proteome coverage.

Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels

Protein abundance and phosphorylation convey important information about pathway activity and molecular pathophysiology in diseases including cancer, providing biological insight, informing drug and diagnostic development, and guiding therapeutic intervention. Analyzed tissues are usually collected without tight regulation or documentation of ischemic time. To evaluate the impact of ischemia, we collected human ovarian tumor and breast cancer xenograft tissue without vascular interruption and performed quantitative proteomics and phosphoproteomics after defined ischemic intervals. Although the global expressed proteome and most of the >25,000 quantified phosphosites were unchanged after 60 min, rapid phosphorylation changes were observed in up to 24% of the phosphoproteome, representing activation of critical cancer pathways related to stress response, transcriptional regulation, and cell death. Both pan-tumor and tissue-specific changes were observed. The demonstrated impact of pre-analytical tissue ischemia on tumor biology mandates caution in interpreting stress-pathway activation in such samples and motivates reexamination of collection protocols for phosphoprotein analysis.

Expanding proteome coverage with orthogonal-specificity α-lytic proteases

Bottom-up proteomics studies traditionally involve proteome digestion with a single protease, trypsin. However, trypsin alone does not generate peptides that encompass the entire proteome. Alternative proteases have been explored, but most have specificity for charged amino acid side chains. Therefore, additional proteases that improve proteome coverage through cleavage at sequences complementary to trypsin's may increase proteome coverage. We demonstrate the novel application of two proteases for bottom-up proteomics: wild type α-lytic protease (WaLP) and an active site mutant of WaLP, M190A α-lytic protease (MaLP). We assess several relevant factors, including MS/MS fragmentation, peptide length, peptide yield, and protease specificity. When data from separate digestions with trypsin, LysC, WaLP, and MaLP were combined, proteome coverage was increased by 101% relative to that achieved with trypsin digestion alone. To demonstrate how the gained sequence coverage can yield additional post-translational modification information, we show the identification of a number of novel phosphorylation sites in the Schizosaccharomyces pombe proteome and include an illustrative example from the protein MPD2 wherein two novel sites are identified, one in a tryptic peptide too short to identify and the other in a sequence devoid of tryptic sites. The specificity of WaLP and MaLP for aliphatic amino acid side chains was particularly valuable for coverage of membrane protein sequences, which increased 350% when the data from trypsin, LysC, WaLP, and MaLP were combined.

Metabolic reprogramming during purine stress in the protozoan pathogen Leishmania donovani

The ability of Leishmania to survive in their insect or mammalian host is dependent upon an ability to sense and adapt to changes in the microenvironment. However, little is known about the molecular mechanisms underlying the parasite response to environmental changes, such as nutrient availability. To elucidate nutrient stress response pathways in Leishmania donovani, we have used purine starvation as the paradigm. The salvage of purines from the host milieu is obligatory for parasite replication; nevertheless, purine-starved parasites can persist in culture without supplementary purine for over three months, indicating that the response to purine starvation is robust and engenders parasite survival under conditions of extreme scarcity. To understand metabolic reprogramming during purine starvation we have employed global approaches. Whole proteome comparisons between purine-starved and purine-replete parasites over a 6–48 h span have revealed a temporal and coordinated response to purine starvation. Purine transporters and enzymes involved in acquisition at the cell surface are upregulated within a few hours of purine removal from the media, while other key purine salvage components are upregulated later in the time-course and more modestly. After 48 h, the proteome of purine-starved parasites is extensively remodeled and adaptations to purine stress appear tailored to deal with both purine deprivation and general stress. To probe the molecular mechanisms affecting proteome remodeling in response to purine starvation, comparative RNA-seq analyses, qRT-PCR, and luciferase reporter assays were performed on purine-starved versus purine-replete parasites. While the regulation of a minority of proteins tracked with changes at the mRNA level, for many regulated proteins it appears that proteome remodeling during purine stress occurs primarily via translational and/or post-translational mechanisms.

Leishmania, the cause of a deadly spectrum of diseases in humans, surmounts a number of environmental challenges, including changes in the availability of salvageable nutrients, to successfully colonize its host. Adaptation to environmental stress is clearly of significance in parasite biology, but the underlying mechanisms are not well understood. To simulate the response to periodic nutrient scarcity in vivo, we have induced purine starvation in vitro. Purines are essential for growth and viability, and serve as the major energy currency of cells. Leishmania cannot synthesize purines and must salvage them from the surroundings. Extracellular purine depletion in culture induces a robust survival response in Leishmania, whereby growth arrests, but parasites persist for months. To profile the events that enable endurance of purine starvation, we used shotgun proteomics. Our data suggest that purine starvation induces extensive proteome remodeling, tailored to enhance purine capture and recycling, reduce energy expenditures, and maintain viability of the metabolically active, non-dividing population. Through global and targeted approaches, we reveal that proteome remodeling is multifaceted, and occurs through an array of responses at the mRNA, translational, and post-translational level. Our data provide one of the most inclusive views of adaptation to microenvironmental stress in Leishmania.

Proteogenomic analysis of pathogenic yeast Cryptococcus neoformans using high resolution mass spectrometry

Background

Cryptococcus neoformans, a basidiomycetous fungus of universal occurrence, is a significant opportunistic human pathogen causing meningitis. Owing to an increase in the number of immunosuppressed individuals along with emergence of drug-resistant strains, C. neoformans is gaining importance as a pathogen. Although, whole genome sequencing of three varieties of C. neoformans has been completed recently, no global proteomic studies have yet been reported.

Results

We performed a comprehensive proteomic analysis of C. neoformans var. grubii (Serotype A), which is the most virulent variety, in order to provide protein-level evidence for computationally predicted gene models and to refine the existing annotations. We confirmed the protein-coding potential of 3,674 genes from a total of 6,980 predicted protein-coding genes. We also identified 4 novel genes and corrected 104 predicted gene models. In addition, our studies led to the correction of translational start site, splice junctions and reading frame used for translation in a number of proteins. Finally, we validated a subset of our novel findings by RT-PCR and sequencing.

Conclusions

Proteogenomic investigation described here facilitated the validation and refinement of computationally derived gene models in the intron-rich genome of C. neoformans, an important fungal pathogen in humans.

The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics

Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a "hub" protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of monitoring these urinary proteins for the specific and sensitive noninvasive diagnosis of acute renal allograft rejection.

Activated ClpP kills persisters and eradicates a chronic biofilm infection

Chronic infections are difficult to treat with antibiotics but are caused primarily by drug-sensitive pathogens. Dormant persister cells that are tolerant to killing by antibiotics are responsible for this apparent paradox. Persisters are phenotypic variants of normal cells and pathways leading to dormancy are redundant, making it challenging to develop anti-persister compounds. Biofilms shield persisters from the immune system, suggesting that an antibiotic for treating a chronic infection should be able to eradicate the infection on its own. We reasoned that a compound capable of corrupting a target in dormant cells will kill persisters. The acyldepsipeptide antibiotic (ADEP4) has been shown to activate the ClpP protease, resulting in death of growing cells. Here we show that ADEP4-activated ClpP becomes a fairly nonspecific protease and kills persisters by degrading over 400 proteins, forcing cells to self-digest. Null mutants of clpP arise with high probability, but combining ADEP4 with rifampicin produced complete eradication of Staphylococcus aureus biofilms in vitro and in a mouse model of a chronic infection. Our findings indicate a general principle for killing dormant cells-activation and corruption of a target, rather than conventional inhibition. Eradication of a biofilm in an animal model by activating a protease suggests a realistic path towards developing therapies to treat chronic infections.

Proteomic analysis of cervical vaginal fluid proteins among women in recurrent preterm labor

OBJECTIVE

Proteomic analysis of four cervical-vaginal fluid (CVF) proteins to identify biomarkers of recurrent preterm birth (rPTB) in at-risk women prior to onset of preterm labor.

METHODS

Nested case control study from 2007 to 2011 of women with prior spontaneous preterm birth(s) (PTB) who underwent serial CVF sampling. Mass spectrometry analysis was used and ELISA analysis was performed to validate candidates.

RESULTS

108 patients were enrolled and 10 cases and 20 gestational age matched controls were analyzed after exclusions. Of 748 CVF proteins identified, 72 had statistically significant (p < 0.05) expression differences and 38 were highly differentially expressed (p < 0.01). Four candidate proteins were abundant and involved in immune/inflammatory response, but ELISA analysis did not confirm altered expression patterns.

CONCLUSION

The lack of confirmation of potential biomarkers identified by mass spectrometry and ELISA demonstrates the challenges of validating PTB biomarkers and suggests that a panel of biomarkers would improve the predictive value of CVF testing.

Large-scale identification of ubiquitination sites by mass spectrometry

Ubiquitination is essential for the regulation of cellular protein homeostasis. It also has a central role in numerous signaling events. Recent advances in the production and availability of antibodies that recognize the Lys-ɛ-Gly-Gly (K-ɛ-GG) remnant produced by trypsin digestion of proteins having ubiquitinated lysine side chains have markedly improved the ability to enrich and detect endogenous ubiquitination sites by mass spectrometry (MS). The following protocol describes the steps required to complete a large-scale ubiquitin experiment for the detection of tens of thousands of distinct ubiquitination sites from cell lines or tissue samples. Specifically, we present detailed, step-by-step instructions for sample preparation, off-line fractionation by reversed-phase chromatography at pH 10, immobilization of an antibody specific to K-ɛ-GG to beads by chemical cross-linking, enrichment of ubiquitinated peptides using these antibodies and proteomic analysis of enriched samples by LC-tandem MS (MS/MS). Relative quantification can be achieved by performing stable isotope labeling by amino acids in cell culture (SILAC) labeling of cells. After cell or tissue samples have been prepared for lysis, the described protocol can be completed in ∼5 d.