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.

Th22 Cells Are a Major Contributor to the Mycobacterial CD4+ T Cell Response and Are Depleted During HIV Infection.

HIV-1 infection substantially increases the risk of developing tuberculosis (TB). Mechanisms such as defects in the Th1 response to Mycobacterium tuberculosis in HIV-infected persons have been widely reported. However, Th1-independent mechanisms also contribute to protection against TB. To identify a broader spectrum of defects in TB immunity during HIV infection, we examined IL-17A and IL-22 production in response to mycobacterial Ags in peripheral blood of persons with latent TB infection and HIV coinfection. Upon stimulating with mycobacterial Ags, we observed a distinct CD4+ Th lineage producing IL-22 in the absence of IL-17A and IFN-γ. Mycobacteria-specific Th22 cells were present at high frequencies in blood and contributed up to 50% to the CD4+ T cell response to mycobacteria, comparable in magnitude to the IFN-γ Th1 response (median 0.91% and 0.55%, respectively). Phenotypic characterization of Th22 cells revealed that their memory differentiation was similar to M. tuberculosis-specific Th1 cells (i.e., predominantly early differentiated CD45RO+CD27+ phenotype). Moreover, CCR6 and CXCR3 expression profiles of Th22 cells were similar to Th17 cells, whereas their CCR4 and CCR10 expression patterns displayed an intermediate phenotype between Th1 and Th17 cells. Strikingly, mycobacterial IL-22 responses were 3-fold lower in HIV-infected persons compared with uninfected persons, and the magnitude of responses correlated inversely with HIV viral load. These data provide important insights into mycobacteria-specific Th subsets in humans and suggest a potential role for IL-22 in protection against TB during HIV infection. Further studies are needed to fully elucidate the role of IL-22 in protective TB immunity.

SARS-CoV-2 Antigens Expressed in Plants Detect Antibody Responses in COVID-19 Patients.

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has swept the world and poses a significant global threat to lives and livelihoods, with 115 million confirmed cases and at least 2.5 million deaths from Coronavirus disease 2019 (COVID-19) in the first year of the pandemic. Developing tools to measure seroprevalence and understand protective immunity to SARS-CoV-2 is a priority. We aimed to develop a serological assay using plant-derived recombinant viral proteins, which represent important tools in less-resourced settings. Methods: We established an indirect ELISA using the S1 and receptor-binding domain (RBD) portions of the spike protein from SARS-CoV-2, expressed in Nicotiana benthamiana. We measured antibody responses in sera from South African patients (n = 77) who had tested positive by PCR for SARS-CoV-2. Samples were taken a median of 6 weeks after the diagnosis, and the majority of participants had mild and moderate COVID-19 disease. In addition, we tested the reactivity of pre-pandemic plasma (n = 58) and compared the performance of our in-house ELISA with a commercial assay. We also determined whether our assay could detect SARS-CoV-2-specific IgG and IgA in saliva. Results: We demonstrate that SARS-CoV-2-specific immunoglobulins are readily detectable using recombinant plant-derived viral proteins, in patients who tested positive for SARS-CoV-2 by PCR. Reactivity to S1 and RBD was detected in 51 (66%) and 48 (62%) of participants, respectively. Notably, we detected 100% of samples identified as having S1-specific antibodies by a validated, high sensitivity commercial ELISA, and optical density (OD) values were strongly and significantly correlated between the two assays. For the pre-pandemic plasma, 1/58 (1.7%) of samples were positive, indicating a high specificity for SARS-CoV-2 in our ELISA. SARS-CoV-2-specific IgG correlated significantly with IgA and IgM responses. Endpoint titers of S1- and RBD-specific immunoglobulins ranged from 1:50 to 1:3,200. S1-specific IgG and IgA were found in saliva samples from convalescent volunteers. Conclusion: We demonstrate that recombinant SARS-CoV-2 proteins produced in plants enable robust detection of SARS-CoV-2 humoral responses. This assay can be used for seroepidemiological studies and to measure the strength and durability of antibody responses to SARS-CoV-2 in infected patients in our setting.

Disruption of maternal gut microbiota during gestation alters offspring microbiota and immunity.

BACKGROUND: Early life microbiota is an important determinant of immune and metabolic development and may have lasting consequences. The maternal gut microbiota during pregnancy or breastfeeding is important for defining infant gut microbiota. We hypothesized that maternal gut microbiota during pregnancy and breastfeeding is a critical determinant of infant immunity. To test this, pregnant BALB/c dams were fed vancomycin for 5 days prior to delivery (gestation; Mg), 14 days postpartum during nursing (Mn), or during gestation and nursing (Mgn), or no vancomycin (Mc). We analyzed adaptive immunity and gut microbiota in dams and pups at various times after delivery. RESULTS: In addition to direct alterations to maternal gut microbial composition, pup gut microbiota displayed lower α-diversity and distinct community clusters according to timing of maternal vancomycin. Vancomycin was undetectable in maternal and offspring sera, therefore the observed changes in the microbiota of stomach contents (as a proxy for breastmilk) and pup gut signify an indirect mechanism through which maternal intestinal microbiota influences extra-intestinal and neonatal commensal colonization. These effects on microbiota influenced both maternal and offspring immunity. Maternal immunity was altered, as demonstrated by significantly higher levels of both total IgG and IgM in Mgn and Mn breastmilk when compared to Mc. In pups, lymphocyte numbers in the spleens of Pg and Pn were significantly increased compared to Pc. This increase in cellularity was in part attributable to elevated numbers of both CD4+ T cells and B cells, most notable Follicular B cells. CONCLUSION: Our results indicate that perturbations to maternal gut microbiota dictate neonatal adaptive immunity.