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

BackgroundMicrobiome 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.ResultsWe 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.ConclusionsBy 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

Additional file 1: of Disruption of maternal gut microbiota during gestation alters offspring microbiota and immunity

Figure S1. (A) Shannon α-diversity of maternal fecal microbiota. (B) of maternal fecal microbial β-diversity based on Bray Curtis distance. (C) Relative abundance at phyla level in dams. (D) PCoA of both pup and dam stool microbiota in different cages. Results were combined from two independent experiments. Related to Fig. 1. Figure S2. Maternal gut microbiota and breast milk microbiota influence pup gut microbiota. Genital tract samples were collected day 4 post delivery from dams (A) Principal coordinate analysis by Bray-Curtis dissimilarity of genital tract microbiota. (B) Pie charts showing representative pie charts of maternal source of bacteria in individual infant mice gut. Data representative of two independent experiments. n = 4 genital tract samples per group or 4–6 pups per group. *p < 0.05. Related to Fig. 2. Table S1. Vancomycin levels in serum of dams and pups measured by the Abbott ELISA technique. Levels across all groups were below the detection limit of 3 μg/ml. Related to Fig. 1. (DOCX 773 kb

Afri-Can Forum 2

CITATION: Mukudu, H., et al. 2016. Afri-Can Forum 2. BMC Infectious Diseases, 16:315, doi:10.1186/s12879-016-1466-6.The original publication is available at https://bmcinfectdis.biomedcentral.comENGLISH ABSTRACT: We are pleased to present peer reviewed forum proceedings of the 2nd synchronicity forum of GHRI/CHVIfunded Canadian and African HIV prevention and vaccine teams Forum objectives ∙GHRI-funded capacity building and HIV prevention research teams presented highlights of achievements ∙Teams discussed how to jointly build on achievements for sustainability ∙Provided an opportunity for inter-team collaboration, synchronize best approach to capacity building, mentoring of new researchers and building leadership ∙Provided opportunities for informal discussions and networking among the teams. ∙Teams learnt about recent advances in the area of African regulatory and ethics review process ∙The forum proceedings was a special supplement in an openaccess journal was producedhttps://bmcinfectdis.biomedcentral.com/articles/supplements/volume-16-supplement-2Publisher's versio