MetaNovo: An open-source pipeline for probabilistic peptide discovery in complex metaproteomic datasets.

BACKGROUND: Microbiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focused search sequence databases based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing only targets the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. Here we describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored sequence databases for target-decoy searches directly at the proteome level, enabling metaproteomic analyses without prior expectation of sample composition or metagenomic data generation and compatible with standard downstream analysis pipelines. RESULTS: We compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome sequence database-but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic sequence database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying an experimental sample contaminant without prior expectation. CONCLUSIONS: By estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence databases to search. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic sequence database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself.

Pro-MAP: a robust pipeline for the pre-processing of single channel protein microarray data.

BACKGROUND: The central role of proteins in diseases has made them increasingly attractive as therapeutic targets and indicators of cellular processes. Protein microarrays are emerging as an important means of characterising protein activity. Their accurate downstream analysis to produce biologically significant conclusions is largely dependent on proper pre-processing of extracted signal intensities. However, existing computational tools are not specifically tailored to the nature of these data and lack unanimity. RESULTS: Here, we present the single-channel Protein Microarray Analysis Pipeline, a tailored computational tool for analysis of single-channel protein microarrays enabling biomarker identification, implemented in R, and as an interactive web application. We compared four existing background correction and normalization methods as well as three array filtering techniques, applied to four real datasets with two microarray designs, extracted using two software programs. The normexp, cyclic loess, and array weighting methods were most effective for background correction, normalization, and filtering respectively. CONCLUSIONS: Thus, here we provided a versatile and effective pre-processing and differential analysis workflow for single-channel protein microarray data in form of an R script and web application ( https://metaomics.uct.ac.za/shinyapps/Pro-MAP/ .) for those not well versed in the R programming language.

A pilot study to show that asymptomatic sexually transmitted infections alter the foreskin epithelial proteome.

There is limited data on the role of asymptomatic STIs (aSTIs) on the risk of human immunodeficiency virus (HIV) acquisition in the male genital tract (MGT). The impact of foreskin removal on lowering HIV acquisition is well described, but molecular events leading to HIV acquisition are unclear. Here, in this pilot study, we show that asymptomatic urethral infection with Chlamydia trachomatis (CT) significantly impacts the foreskin proteome composition. We developed and optimized a shotgun liquid chromatography coupled tandem mass spectrometry (MS)-based proteomics approach and utilized this on foreskins collected at medical male circumcision (MMC) from 16 aSTI+ men and 10 age-matched STI- controls. We used a novel bioinformatic metaproteomic pipeline to detect differentially expressed (DE) proteins. Gene enrichment ontology analysis revealed proteins associated with inflammatory and immune activation function in both inner and outer foreskin from men with an aSTI. Neutrophil activation/degranulation and viral-evasion proteins were significantly enriched in foreskins from men with aSTI, whereas homotypic cell-cell adhesion proteins were enriched in foreskin tissue from men without an aSTI. Collectively, our data show that asymptomatic urethral sexually transmitted infections result in profound alterations in epithelial tissue that are associated with depletion of barrier integrity and immune activation.

A mass spectrometry-based approach for the identification of Kpnß1 binding partners in cancer cells.

Karyopherin beta 1 (Kpnß1) is the principal nuclear importer of cargo proteins and plays a role in many cellular processes. Its expression is upregulated in cancer and essential for cancer cell viability, thus the identification of its binding partners might help in the discovery of anti-cancer therapeutic targets and cancer biomarkers. Herein, we applied immunoprecipitation coupled to mass spectrometry (IP-MS) to identify Kpnß1 binding partners in normal and cancer cells. IP-MS identified 100 potential Kpnß1 binding partners in non-cancer hTERT-RPE1, 179 in HeLa cervical cancer, 147 in WHCO5 oesophageal cancer and 176 in KYSE30 oesophageal cancer cells, including expected and novel interaction partners. 38 binding proteins were identified in all cell lines, with the majority involved in RNA metabolism. 18 binding proteins were unique to the cancer cells, with many involved in protein translation. Western blot analysis validated the interaction of known and novel binding partners with Kpnß1 and revealed enriched interactions between Kpnß1 and select proteins in cancer cells, including proteins involved in cancer development, such as Kpnα2, Ran, CRM1, CCAR1 and FUBP1. Together, this study shows that Kpnß1 interacts with numerous proteins, and its enhanced interaction with certain proteins in cancer cells likely contributes to the cancer state.

Identification of Novel Physiological Substrates of Mycobacterium bovis BCG Protein Kinase G (PknG) by Label-free Quantitative Phosphoproteomics.

Mycobacterial Ser/Thr kinases play a critical role in bacterial physiology and pathogenesis. Linking kinases to the substrates they phosphorylate in vivo, thereby elucidating their exact functions, is still a challenge. The aim of this work was to associate protein phosphorylation in mycobacteria with important subsequent macro cellular events by identifying the physiological substrates of PknG in Mycobacterium bovis BCG. The study compared the phosphoproteome dynamics during the batch growth of M. bovis BCG versus the respective PknG knock-out mutant (ΔPknG-BCG) strains. We employed TiO2 phosphopeptide enrichment techniques combined with label-free quantitative phosphoproteomics workflow on LC-MS/MS. The comprehensive analysis of label-free data identified 603 phosphopeptides on 307 phosphoproteins with high confidence. Fifty-five phosphopeptides were differentially phosphorylated, of these, 23 phosphopeptides were phosphorylated in M. bovis BCG wild-type only and not in the mutant. These were further validated through targeted mass spectrometry assays (PRMs). Kinase-peptide docking studies based on a published crystal structure of PknG in complex with GarA revealed that the majority of identified phosphosites presented docking scores close to that seen in previously described PknG substrates, GarA, and ribosomal protein L13. Six out of the 22 phosphoproteins had higher docking scores than GarA, consistent with the proteins identified here being true PknG substrates. Based on protein functional analysis of the PknG substrates identified, this study confirms that PknG plays an important regulatory role in mycobacterial metabolism, through phosphorylation of ATP binding proteins and enzymes in the TCA cycle. This work also reinforces PknG's regulation of protein translation and folding machinery.

Proteomic comparison of three clinical diarrhoeagenic drug-resistant Escherichia coli isolates grown on CHROMagar™STEC media.

Shiga-toxin-producing Escherichia coli (STEC) and enteropathogenic Escherichia coli (EPEC) are key diarrhoea-causing foodborne pathogens. We used proteomics to characterize the virulence and antimicrobial resistance protein profiles of three clinical pathogenic E. coli isolates (two EPEC [one resistant to ciprofloxacin] and one STEC) cultured on CHROMagar™STEC solid media after minimal laboratory passage. We identified 4767 unique peptides from 1630 protein group across all three clinical E. coli strains. Label-free proteomic analysis allowed the identification of virulence and drug resistance proteins that were unique to each of the clinical isolates compared in this study. The B subunit of Shiga toxin, ToxB, was uniquely detected in the STEC strain while several other virulence factors including SheA, OmpF, OmpC and OmpX were significantly more abundant in the STEC strain. The ciprofloxacin resistant EPEC isolate possessed reduced levels of key virulence proteins compared to the ciprofloxacin susceptible EPEC and STEC strains. Parallel reaction monitoring assays validated the presence of biologically relevant proteins across biologically-replicated cultures. Propagation of clinical isolates on a relevant solid medium followed by mass spectrometry analysis represents a convenient means to quantify virulence factors and drug resistance determinants that might otherwise be lost through extensive in vitro passage in enteropathogenic bacteria. SIGNIFICANCE: Through the use of quantitative proteomics, we have characterized the virulence and antimicrobial resistance attributes of three clinically isolated, pathogenic E. coli strains cultured on solid media. Our results provide new, quantitative data on the expressed proteomes of these tellurite-resistant, diarrhoeagenic E. coli strains and reveal a subset of antimicrobial resistance and virulence proteins that are differentially abundant between these clinical strains. Our quantitative proteomics-based approach should thus have applicability in microbiological diagnostic labs for the identification of pathogenic/drug resistant E. coli in the future.

Global proteome and phosphoproteome dynamics indicate novel mechanisms of vitamin C induced dormancy in Mycobacterium smegmatis.

Vitamin C has been found to affect mycobacteria in multiple ways, including increasing susceptibility to antimicrobial drugs, inducing dormancy, and having a bactericidal effect. However, the regulatory events mediating vitamin C related adaptations remain largely elusive. Ser/Thr/Tyr protein phosphorylation plays an important regulatory role in mycobacteria, contributing to environmental adaptation, including dormancy and drug resistance. This study utilised the model organism, Mycobacterium smegmatis, and TiO2 phosphopeptide enrichment combined with mass spectrometry-based proteomics methods to elucidate the mycobacterial signalling and regulatory response to sub-lethal concentrations of vitamin C. After initial validation of peptide spectra, 224 non-redundant phosphosites in 154 proteins were retained with high confidence. Data analysis revealed that 30 peptides were differentially phosphorylated with Vitamin C treatment, including novel phosphosites found on both PknG and GarA. Of these significant proteins, we validated 11 by parallel reaction monitoring of high-confidence phosphopeptides. Interestingly, 17/30 phosphopeptides were annotated as part of transmembrane proteins, suggesting that it is likely vitamin C triggers typical signal transduction events in which the protein periplasmic domain perceives environmental signals and the cytoplasmic domain is then phosphorylated. Finally, the diverse nature of phosphorylated proteins involved in signalling, transport, and carbohydrate biosynthesis indicates the extent of such regulatory phosphorylation events. BIOLOGICAL SIGNIFICANCE: Our findings provide new mechanistic insight into a coordinated network of signalling and regulatory responses to sub-lethal vitamin C in Mycobacterium smegmatis and provide evidence that vitamin C is able to act as a novel extracellular signalling molecule. Vitamin C treatment caused changes in both the proteome and phosphoproteome associated with response to oxidative stress, a shift in metabolic regulation and progression toward dormancy, as well as phospho-dependent activation of specific secretory pathways and activation of specific two component and Ser/Thr/Tyr protein kinase activities. This study confirms the potential of vitamin C as convenient means to study aspects of mycobacterial dormancy, including those regulated at post-translational level.

Time-Dependent, HIV-Tat-Induced Perturbation of Human Neurons In Vitro: Towards a Model for the Molecular Pathology of HIV-Associated Neurocognitive Disorders.

A significant proportion of human immunodeficiency virus type 1 (HIV)-positive individuals are affected by the cognitive, motor and behavioral dysfunction that characterizes HIV-associated neurocognitive disorders (HAND). While the molecular etiology of HAND remains largely uncharacterized, HIV transactivator of transcription (HIV-Tat) is thought to be an important etiological cause. Here we have used mass spectrometry (MS)-based discovery proteomics to identify the quantitative, cell-wide changes that occur when non-transformed, differentiated human neurons are treated with HIV-Tat over time. We identified over 4000 protein groups (false discovery rate <0.01) in this system with 131, 118 and 45 protein groups differentially expressed at 6, 24 and 48 h post treatment, respectively. Alterations in the expression of proteins involved in gene expression and cytoskeletal maintenance were particularly evident. In tandem with proteomic evidence of cytoskeletal dysregulation we observed HIV-Tat induced functional alterations, including a reduction of neuronal intrinsic excitability as assessed by patch-clamp electrophysiology. Our findings may be relevant for understanding in vivo molecular mechanisms in HAND.

A temporal proteome dynamics study reveals the molecular basis of induced phenotypic resistance in Mycobacterium smegmatis at sub-lethal rifampicin concentrations.

In the last 40 years only one new antitubercular drug has been approved, whilst resistance to current drugs, including rifampicin, is spreading. Here, we used the model organism Mycobacterium smegmatis to study mechanisms of phenotypic mycobacterial resistance, employing quantitative mass spectrometry-based proteomics to investigate the temporal effects of sub-lethal concentrations of rifampicin on the mycobacterial proteome at time-points corresponding to early response, onset of bacteriostasis and early recovery. Across 18 samples, a total of 3,218 proteins were identified from 31,846 distinct peptides averaging 16,250 identified peptides per sample. We found evidence that two component signal transduction systems (e.g. MprA/MprB) play a major role during initial mycobacterial adaptive responses to sub-lethal rifampicin and that, after dampening an initial SOS response, the bacteria supress the DevR (DosR) regulon and also upregulate their transcriptional and translational machineries. Furthermore, we found a co-ordinated dysregulation in haeme and mycobactin synthesis. Finally, gradual upregulation of the M. smegmatis-specific rifampin ADP-ribosyl transferase was observed which, together with upregulation of transcriptional and translational machinery, likely explains recovery of normal growth. Overall, our data indicates that in mycobacteria, sub-lethal rifampicin triggers a concerted phenotypic response that contrasts significantly with that observed at higher antimicrobial doses.

TB-IRIS: Proteomic analysis of in vitro PBMC responses to Mycobacterium tuberculosis and response modulation by dexamethasone.

Paradoxical tuberculosis-associated immune reconstitution inflammatory syndrome (TB-IRIS) occurs in 8-54% of South African patients undergoing treatment for tuberculosis/human immunodeficiency virus co-infection. Improved TB-IRIS molecular pathogenesis understanding would enhance risk stratification, diagnosis, prognostication, and treatment. We assessed how TB-IRIS status and dexamethasone influence leukocyte proteomic responses to Mycobacterium tuberculosis (Mtb). Patient blood was obtained three weeks post-anti-retroviral therapy initiation. Isolated mononuclear cells were stimulated ex vivo with heat-killed Mtb in the presence/absence of dexamethasone. Mass spectrometry-based proteomic comparison of TB-IRIS and non-IRIS patient-derived cells facilitated generation of hypotheses regarding pathogenesis. Few represented TB-IRIS-group immune-related pathways achieved significant activation, with relative under-utilisation of "inter-cellular interaction" and "Fcγ receptor-mediated phagocytosis" (but a tendency towards apoptosis-related) pathways. Dexamethasone facilitated significant activation of innate-related pathways. Differentially-expressed non-IRIS-group proteins suggest focused and co-ordinated immunological pathways, regardless of dexamethasone status. Findings suggest a relative deficit in TB-IRIS-group responses to and clearance of Mtb antigens, ameliorated by dexamethasone.

Quantitative proteomic analysis of HIV-1 Tat-induced dysregulation in SH-SY5Y neuroblastoma cells.

Despite affecting up to 70% of HIV-positive patients and being the leading cause of dementia in patients under 40 years, the molecular mechanisms involved in the onset of HIV-associated neurocognitive disorders (HAND) are not well understood. To address this, we performed SILAC-based quantitative proteomic analysis on HIV-Tat treated SH-SY5Y neuroblastoma cells. Isolated protein was fractionated by SDS-PAGE and analyzed by nLC-MS/MS on an Orbitrap Velos. Using MaxQuant, we identified and quantified 3077 unique protein groups, of which 407 were differentially regulated. After applying an additional standard deviation-based cutoff, 29 of these were identified as highly significantly and stably dysregulated. GO term analysis shows dysregulation in both protein translation machinery as well as cytoskeletal regulation that have both been implicated in other dementias. In addition, several key cytoskeletal regulatory proteins such as ARHGEF17, the Rho GTPase, SHROOM3, and CMRP1 are downregulated. Together, these data demonstrate that HIV-Tat can dysregulate neuronal cytoskeletal regulatory proteins that could lead to the major HAND clinical manifestation-synapse loss.

Proteogenomic Analysis of Mycobacterium smegmatis Using High Resolution Mass Spectrometry.

Biochemical evidence is vital for accurate genome annotation. The integration of experimental data collected at the proteome level using high resolution mass spectrometry allows for improvements in genome annotation by providing evidence for novel gene models, while validating or modifying others. Here, we report the results of a proteogenomic analysis of a reference strain of Mycobacterium smegmatis (mc(2)155), a fast growing model organism for the pathogenic Mycobacterium tuberculosis-the causative agent for Tuberculosis. By integrating high throughput LC/MS/MS proteomic data with genomic six frame translation and ab initio gene prediction databases, a total of 2887 ORFs were identified, including 2810 ORFs annotated to a Reference protein, and 63 ORFs not previously annotated to a Reference protein. Further, the translational start site (TSS) was validated for 558 Reference proteome gene models, while upstream translational evidence was identified for 81. In addition, N-terminus derived peptide identifications allowed for downstream TSS modification of a further 24 gene models. We validated the existence of six previously described interrupted coding sequences at the peptide level, and provide evidence for four novel frameshift positions. Analysis of peptide posterior error probability (PEP) scores indicates high-confidence novel peptide identifications and shows that the genome of M. smegmatis mc(2)155 is not yet fully annotated. Data are available via ProteomeXchange with identifier PXD003500.

Comparative Ser/Thr/Tyr phosphoproteomics between two mycobacterial species: the fast growing Mycobacterium smegmatis and the slow growing Mycobacterium bovis BCG.

Ser/Thr/Tyr protein phosphorylation plays a critical role in regulating mycobacterial growth and development. Understanding the mechanistic link between protein phosphorylation signaling network and mycobacterial growth rate requires a global view of the phosphorylation events taking place at a given time under defined conditions. In the present study we employed a phosphopeptide enrichment and high throughput mass spectrometry-based strategy to investigate and qualitatively compare the phosphoproteome of two mycobacterial model organisms: the fast growing Mycobacterium smegmatis and the slow growing Mycobacterium bovis BCG. Cells were harvested during exponential phase and our analysis detected a total of 185 phospho-sites in M. smegmatis, of which 106 were confidently localized [localization probability (LP) = 0.75; PEP = 0.01]. By contrast, in M. bovis BCG the phosphoproteome comprised 442 phospho-sites, of which 289 were confidently localized. The percentage distribution of Ser/Thr/Tyr phosphorylation was 39.47, 57.02, and 3.51% for M. smegmatis and 35, 61.6, and 3.1% for M. bovis BCG. Moreover, our study identified a number of conserved Ser/Thr phosphorylated sites and conserved Tyr phosphorylated sites across different mycobacterial species. Overall a qualitative comparison of the fast and slow growing mycobacteria suggests that the phosphoproteome of M. smegmatis is a simpler version of that of M. bovis BCG. In particular, M. bovis BCG exponential cells exhibited a much more complex and sophisticated protein phosphorylation network regulating important cellular cycle events such as cell wall biosynthesis, elongation, cell division including immediately response to stress. The differences in the two phosphoproteomes are discussed in light of different mycobacterial growth rates.

Comparative reevaluation of FASP and enhanced FASP methods by LC-MS/MS.

Filter-aided sample preparation is a proteomic technique for the preparation and on column proteolysis of proteins. Recently an enhanced FASP protocol was developed that uses deoxycholic acid (DCA) and that reportedly enhances trypsin proteolysis, resulting in increases cytosolic and membrane protein representation. FASP and eFASP were re-evaluated by ultra-high-performance liquid chromatography coupled to a quadrupole mass filter Orbitrap analyzer (Q Exactive). Although there was no difference in trypsin activity, 14,099 and 13,414 peptides, describing 1723 and 1793 protein groups, from Escherichia coli K12 were identified using FASP and eFASP, respectively. Characterization of the physicochemical properties of identified peptides showed no significant differences other than eFASP extracting slightly more basic peptides. At the protein level, both methods extracted essentially the same number of hydrophobic transmembrane helix-containing proteins as well as proteins associated with the cytoplasm or the cytoplasmic and outer membranes. By employing state-of-the-art LC-MS/MS shot gun proteomics, our results indicate that FASP and eFASP showed no significant differences at the protein level. However, because of the slight differences in selectivity at the physicochemical level of peptides, these methods can be seen to be somewhat complementary for analyses of complex peptide mixtures.