Humoral immunoprofiling identifies novel biomarkers and an immune suppressive autoantibody phenotype at the site of disease in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous cancer, with minimal response to therapeutic intervention and with 85% of cases diagnosed at an advanced stage due to lack of early symptoms, highlighting the importance of understanding PDAC immunology in greater detail. Here, we applied an immunoproteomic approach to investigate autoantibody responses against cancer-testis and tumor-associated antigens in PDAC using a high-throughput multiplexed protein microarray platform, comparing humoral immune responses in serum and at the site of disease in order to shed new light on immune responses in the tumor microenvironment. We simultaneously quantified serum or tissue IgG and IgA antibody isotypes and subclasses in a cohort of PDAC, disease control and healthy patients, observing inter alia that subclass utilization in tumor tissue samples was predominantly immune suppressive IgG4 and inflammatory IgA2, contrasting with predominant IgG3 and IgA1 subclass utilization in matched sera and implying local autoantibody production at the site of disease in an immune-tolerant environment. By comparison, serum autoantibody subclass profiling for the disease controls identified IgG4, IgG1, and IgA1 as the abundant subclasses. Combinatorial analysis of serum autoantibody responses identified panels of candidate biomarkers. The top IgG panel included ACVR2B, GAGE1, LEMD1, MAGEB1 and PAGE1 (sensitivity, specificity and AUC values of 0.933, 0.767 and 0.906). Conversely, the top IgA panel included AURKA, GAGE1, MAGEA10, PLEKHA5 and XAGE3aV1 (sensitivity, specificity, and AUC values of 1.000, 0.800, and 0.954). Assessment of antigen-specific serum autoantibody glycoforms revealed abundant sialylation on IgA in PDAC, consistent with an immune suppressive IgA response to disease.

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.

Age, Disease Severity and Ethnicity Influence Humoral Responses in a Multi-Ethnic COVID-19 Cohort

The COVID-19 pandemic has affected all individuals across the globe in some way. Despite large numbers of reported seroprevalence studies, there remains a limited understanding of how the magnitude and epitope utilization of the humoral immune response to SARS-CoV-2 viral anti-gens varies within populations following natural infection. Here, we designed a quantitative, multi-epitope protein microarray comprising various nucleocapsid protein structural motifs, including two structural domains and three intrinsically disordered regions. Quantitative data from the microarray provided complete differentiation between cases and pre-pandemic controls (100% sensitivity and specificity) in a case-control cohort (n = 100). We then assessed the influence of disease severity, age, and ethnicity on the strength and breadth of the humoral response in a multi-ethnic cohort (n = 138). As expected, patients with severe disease showed significantly higher antibody titers and interestingly also had significantly broader epitope coverage. A significant increase in antibody titer and epitope coverage was observed with increasing age, in both mild and severe disease, which is promising for vaccine efficacy in older individuals. Additionally, we observed significant differences in the breadth and strength of the humoral immune response in relation to ethnicity, which may reflect differences in genetic and lifestyle factors. Furthermore, our data enabled localization of the immuno-dominant epitope to the C-terminal structural domain of the viral nucleocapsid protein in two independent cohorts. Overall, we have designed, validated, and tested an advanced serological assay that enables accurate quantitation of the humoral response post natural infection and that has revealed unexpected differences in the magnitude and epitope utilization within a population.

The cyanobacterial lectin, microvirin-N, enhances the specificity and sensitivity of lipoarabinomannan-based TB diagnostic tests

Tuberculosis (TB) is one of the top ten causes of death globally, despite being treatable. The eradication of TB disease requires, amongst others, diagnostic tests with high specificity and sensitivity that will work at the point of care (POC) in low-resource settings. The TB surface glycolipid antigen, mannose-capped lipoarabinomannan (ManLAM) currently serves as the only POC molecular diagnostic biomarker suitable for use in low cost immunoassays. Here, we demonstrate the high affinity and exceptional specificity of microvirin-N (MVN), a 14.3 kDa cyanobacterial lectin, toward H37Rv TB ManLAM and utilize it to develop a novel on-bead ELISA. MVN binds to ManLAM with sub-picomolar binding affinity, but does not bind to other variants of LAM expressed by non-pathogenic mycobacteria - a level of binding specificity and affinity that current commercially available anti-LAM antibodies cannot achieve. An on-bead ELISA was subsequently developed using MVN-functionalized magnetic beads which allows for the specific capture of ManLAM from human urine with a limit of detection (LOD) of 1.14 ng mL-1 and no cross-reactivity when tested with PILAM, a variant of LAM found on non-pathogenic mycobacteria.

Comparison between the proteome of Escherichia coli single colony and during liquid culture

Most bacterial proteomic studies done to date utilise bacterial cells harvested from liquid culture media. However, it is widely accepted that many important determinants associated with virulence and host cell adhesion are exclusively expressed during growth on solid media, as a crude mimic of true biofilms. Here, we compare the observed proteome of Escherichia coli K12 from isolated single colonies on solid media with those observed at different growth phases in liquid culture; i.e. early-log, mid-log, early-, mid- and late-stationary growth phases. A total of 2044 protein groups covering approximately 47% of the total proteome were identified across all studied conditions, including 1650 proteins identified from single colonies and 1679 proteins from liquid cultured cells. Label-free quantitative analysis revealed that the E. coli proteome of single colonies on a solid agar differs from that observed in liquid culture. Notably, the presence of proteins in the Suf-operon that are involved in iron mobilisation and swarming motility was associated exclusively with single colony profiles, whereas proteins involved in motility such as motA, motB, fliH, flip, fliD and fliJ were associated exclusively with cells grown in liquid culture. The data presented here provide a valuable resource for understanding the role of key proteins within microenvironments surrounding E. coli single colonies. SIGNIFICANCE: To date, most proteomics studies have used E. coli cells harvested from liquid culture media even though many important determinants associated with virulence and host cell adhesion are exclusively expressed during growth on solid media. In this study, we compare the observed proteome of E. coli K12 from isolated single colonies on solid media with those observed at different growth phases in liquid culture; i.e. early-log, mid-log, early-, mid- and late-stationary growth phases. By using label-free quantitative analysis we demonstrate that the E. coli proteome of single colonies on a solid agar differs from that observed in liquid culture with an overlap of 68% of proteins between the two culture conditions. Our analysis further reveal the presence of proteins in the Suf-operon that are involved in iron mobilisation and swarming motility was associated exclusively with single colony profiles. While those proteins involved in motility such as motA, motB, fliH, flip, fliD and fliJ were associated exclusively with cells grown in liquid culture. By comparison to E. coli proteomic data available on liquid culture and solid media, this research represents a first effort to describe the differential expression of key E. coli proteins within microenvironments surrounding single colonies.

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.

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 (mc²155), 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 mc²155 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.