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This work supports the massive presence of potential immunomodulatory peptides in the human gut metaproteome. These peptides were identified through the MAHMI database as potentially anti-inflammatory, and sixteen of them synthesized for characterize their mechanism of action. From them, peptide HM14 was encrypted in an extracellular protein produced by Bifidobacterium longum, a common member of the human microbiota, and displayed the highest anti-inflammatory capability. Molecular mechanism of action of HM14 pointed to a specific interaction between this immunomodulatory peptide and antigen presenting cells, which resulted in a higher formation of iTreg cells. Moreover, HM14 was effective in decreasing pro-inflammatory parameters in PBMCs isolated from a cohort of Crohn’s patients. Finally, non-targeted metabolomics confirmed the ability of HM14 to modulate the metabolic activity of PBMCs to fulfil its energy and biosynthetic requirements. Overall, our combined in silico/multiomics approach supports the human gut metaproteome as a source for immunomodulatory peptides.

This work presents a novel in silico approach to the prediction and characterization of the glycolytic capacities of the beneficial intestinal bacterium Faecalibacterium prausnitzii. Available F. prausnitzii genomes were explored taking the glycolytic capacities of F. prausnitzii SL3/3 and F. prausnitzii L2-6 as reference. The comparison of the generated glycolytic profiles offered insights into the particular capabilities of F. prausnitzii SL3/3 and F. prausnitzii L2-6 as well as the potential of the rest of strains. Glycoside hydrolases were mostly detected in the pathways responsible for the starch and sucrose metabolism and the biosynthesis of secondary metabolites, but this analysis also identified some other potentially interesting, but still uncharacterized activities, such as several hexosyltransferases and some hydrolases. Gene neighborhood maps offered additional understanding of the genes coding for relevant glycoside hydrolases. Although information about the carbohydrate preferences of F. prausnitzii is scarce, the in silico metabolic predictions were consistent with previous knowledge about the impact of fermentable sugars on the growth promotion and metabolism of F. prausnitzii. So, while the predictions still need to be validated using culturing methods, the approach holds the potential to be reproduced and scaled to accommodate the analysis of other strains (or even families and genus) as well as other metabolic activities. This will allow the exploration of novel methodologies to design or obtain targeted probiotics for F. prausnitzii and other strains of interest.

Advances in the field of genome sequencing have enabled a comprehensive analysis and annotation of the dynamics of the protein inventory of cells. This has been proven particularly rewarding for microbial cells, for which the majority of proteins are already accessible to analysis through automatic metagenome annotation. The large-scale in silico screening of proteomes and metaproteomes is key to uncover bioactivities of translational, clinical and biotechnological interest, and to help assign functions to certain proteins, such as those predicted as hypothetical. This work introduces a new method for the prediction of the bioactivity potential of proteomes/metaproteomes, supporting the discovery of functionally relevant proteins based on prior knowledge. This methodology complements functional annotation enrichment methods by allowing the assignment of functions to proteins annotated as hypothetical/putative/uncharacterised, as well as and enabling the detection of specific bioactivities and the recovery of proteins from defined taxa. This work shows how the new method can be applied to screen proteome and metaproteome sets to obtain predictions of clinical or biotechnological interest based on reference datasets. Notably, with this methodology, the large information files obtained after DNA sequencing or protein identification experiments can be associated for translational purposes that, in cases such as antibiotic-resistance pathogens or foodborne diseases, may represent changes in how these important and global health burdens are approached in the clinical practice. Finally, the Sequence-based Expert-driven pRoteome bioactivity Prediction EnvironmENT, a public Web service implemented in Scala functional programming style, is introduced as means to ensure broad access to the method as well as to discuss main implementation issues, such as modularity, extensibility and interoperability.

[Background] Transcriptomics profiling aims to identify and quantify all transcripts present within a cell type or tissue at a particular state, and thus provide information on the genes expressed in specific experimental settings, differentiation or disease conditions. RNA-Seq technology is becoming the standard approach for such studies, but available analysis tools are often hard to install, configure and use by users without advanced bioinformatics skills. [Methods] Within reason, DEWE aims to make RNA-Seq analysis as easy for non-proficient users as for experienced bioinformaticians. DEWE supports two well-established and widely used differential expression analysis workflows: using Bowtie2 or HISAT2 for sequence alignment; and, both applying StringTie for quantification, and Ballgown and edgeR for differential expression analysis. Also, it enables the tailored execution of individual tools as well as helps with the management and visualisation of differential expression results. [Results] DEWE provides a user-friendly interface designed to reduce the learning curve of less knowledgeable users while enabling analysis customisation and software extension by advanced users. Docker technology helps overcome installation and configuration hurdles. In addition, DEWE produces high quality and publication-ready outputs in the form of tab-delimited files and figures, as well as helps researchers with further analyses, such as pathway enrichment analysis. [Conclusions] The abilities of DEWE are exemplified here by practical application to a comparative analysis of monocytes and monocyte-derived dendritic cells, a study of clinical relevance. DEWE installers and documentation are freely available at https://www.sing-group.org/dewe.

The human gastrointestinal tract (GIT) is a very complex ecosystem involving a continuous interaction between nutrients, host cells and microorganisms. Recently, we have discovered a new family of immunomodulatory peptides that are encrypted within the sequence of a precise extracellular protein, which is secreted by the lactic acid bacterium Lactobacillus plantarum (Patent WO 2013034795 A1) (1). The genetic information about commensal/probiotic bacteria and gut microbiomes that is present in public repositories is huge, with only a list of 10 million unique bacterial proteins available mainly from the METAHIT and HMP projects (http://gigadb.org/dataset/100064). Our aim is to explore these 10 million unique proteins to obtain information on encrypted peptides which might have immunomodulatory bioactivity on host cells. With this in mind we have developed the MAHMI (Mechanism of Action of the Human Microbiome) database, a unique resource that provides comprehensive information about the sequence of potential immunomodulatory and antiproliferative peptides encrypted in the proteins produced by the human gut microbiota. Fifteen peptides were chosen by its potential immunomodulatory bioactivity. Selected peptides were assayed in vitro at a final concentration of 10 µg/mL using monocyte derived cells (Mo-DCs). Our bioinformatics/in vitro methodology allowed selection of new inmunomodulatory peptides encrypted in the human intestinal bacteria metaproteome. HM14 signaled through an unknown receptor, and imprinted anti-inflammatory traits in immune cells as evidenced by RNASeq and flow cytometry. The mechanisms used by this kind of peptides may be useful for the treatment of inflammatory diseases

[Introduction] Bifidobacteria and lactobacilli include both probiotic strains and representative microorganisms of the human gut microbiota, and their presence has been associated to a proper immune development and maturation. In addition, several independent works report the anti-inflammatory properties of several strains of those groups. However, we are far from understanding the molecular interplay behind/supporting these beneficial interactions. [Objective] To study the effect of different fractions of lactobacilli and bifidobacteria in human peripheral blood mononuclear cells (PBMCs) isolated from healthy donors and patients with Inflammatory Bowel Disease (IBD) at the time of diagnosis. [Methods] The fractions were obtained from strains of Bifidobacterium longum NCIMB 8809, Lactobacillus rhamnosus GG and Lactobacillus acidophilus DSM 20079: DNA, surface-associated proteins, whole cell soluble extract and extracellular proteins. Different concentrations of the fractions were incubated with PBMCs, and key T-cell cytokines, T regulatory cell differentiation and RNASeq of CD4+ cells were performed. [Results] Among the extracts, extracellular proteins from L. acidophilus DSM 20079 increased IL-2 production by PBMCs isolated from healthy donors, and were able to increment the proportion of functional T regulatory cells. Data on the signaling mechanisms involved were obtained by RNASeq of CD4+ Th cell subpopulations. Finally, this fraction decreased drastically the production of the pro-inflammatory mediator TNF-alpha and induced increments of IL-12 in PBMCs isolated from IBD patients at the diagnosis. [Conclusions] Extracellular proteins from strain L. acidophilus DSM 20079 had a positive impact on the immunological status of both healthy donors and IBD patients. This fraction will be on the basis of new clinical studies focused in the immunomodulation of the human host targeting pro-inflammatory effectors and the T-cell regulatory response. This fraction may repres

[Background] The wide range of potential applications has made the Basic Local Alignment Search Tool (BLAST) a ubiquitous tool in the field of Molecular Biology. Within this context, it is increasingly appealing to embed BLAST services within larger Web applications. [Results] This work introduces BlasterJS viewer, a new JavaScript library for the lightweight development of Web-based applications supporting the visualisation of BLAST outputs. BlasterJS detaches from similar data viewers by focusing on the visual and interactive display of sequence similarity results and being completely independent of BLAST services. BlasterJS is compatible with the text outputs generated by the BLAST family of programs, namely BLASTp, BLASTn, BLASTx, tBLASTn, and tBLASTx, and works in all major Web browsers. Furthermore, BlasterJS is available through the EBI’s BioJS registry 5, which extends its potential use to a wider scope of bioinformatics applications. [Conclusions] BlasterJS is new Javascript library that enables easy and seamless integration of visual and interactive representations of BLAST outputs in Web-based applications supporting sequence similarity search. BlasterJS is free accessible at http://sing-group.org/blasterjs/.

The Mechanism of Action of the Human Microbiome (MAHMI) database is a unique resource that provides comprehensive information about the sequence of potential immunomodulatory and antiproliferative peptides encrypted in the proteins produced by the human gut microbiota. Currently, MAHMI database contains over 300 hundred million peptide entries, with detailed information about peptide sequence, sources and potential bioactivity. The reference peptide data section is curated manually by domain experts. The in silico peptide data section is populated automatically through the systematic processing of publicly available exoproteomes of the human microbiome. Bioactivity prediction is based on the global alignment of the automatically processed peptides with experimentally validated immunomodulatory and antiproliferative peptides, in the reference section. MAHMI provides researchers with a comparative tool for inspecting the potential immunomodulatory or antiproliferative bioactivity of new amino acidic sequences and identifying promising peptides to be further investigated. Moreover, researchers are welcome to submit new experimental evidence on peptide bioactivity, namely, empiric and structural data, as a proactive, expert means to keep the database updated and improve the implemented bioactivity prediction method. Bioactive peptides identified by MAHMI have a huge biotechnological potential, including the manipulation of aberrant immune responses and the design of new functional ingredients/foods based on the genetic sequences of the human microbiome. Hopefully, the resources provided by MAHMI will be useful to those researching gastrointestinal disorders of autoimmune and inflammatory nature, such as Inflammatory Bowel Diseases. MAHMI database is routinely updated and is available free of charge.