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Fecal microbiota transplantation (FMT) is highly effective against recurrent Clostridioides difficile infection and is considered a promising treatment for other microbiome-related disorders, but a comprehensive understanding of microbial engraftment dynamics is lacking, which prevents informed applications of this therapeutic approach. Here, we performed an integrated shotgun metagenomic systematic meta-analysis of new and publicly available stool microbiomes collected from 226 triads of donors, pre-FMT recipients and post-FMT recipients across eight different disease types. By leveraging improved metagenomic strain-profiling to infer strain sharing, we found that recipients with higher donor strain engraftment were more likely to experience clinical success after FMT (P = 0.017) when evaluated across studies. Considering all cohorts, increased engraftment was noted in individuals receiving FMT from multiple routes (for example, both via capsules and colonoscopy during the same treatment) as well as in antibiotic-treated recipients with infectious diseases compared with antibiotic-naïve patients with noncommunicable diseases. Bacteroidetes and Actinobacteria species (including Bifidobacteria) displayed higher engraftment than Firmicutes except for six under-characterized Firmicutes species. Cross-dataset machine learning predicted the presence or absence of species in the post-FMT recipient at 0.77 average AUROC in leave-one-dataset-out evaluation, and highlighted the relevance of microbial abundance, prevalence and taxonomy to infer post-FMT species presence. By exploring the dynamics of microbiome engraftment after FMT and their association with clinical variables, our study uncovered species-specific engraftment patterns and presented machine learning models able to predict donors that might optimize post-FMT specific microbiome characteristics for disease-targeted FMT protocols.

The pks island is one of the most prevalent pathogenicity islands among the Escherichia coli strains that colonize the colon of colorectal carcinoma (CRC) patients. This pathogenic island encodes the production of a nonribosomal polyketide-peptide named colibactin, which induces double-strand breaks in DNA molecules. Detection or even depletion of this pks -producing bacteria could help to understand the role of these strains in the context of CRC. In this work, we performed a large-scale in silico screening of the pks cluster in more than 6,000 isolates of E. coli . The results obtained reveal that not all the pks -detected strains could produce a functional genotoxin and, using antibodies against pks -specific peptides from surface cell proteins, a methodology for detection and depletion of pks + bacteria in gut microbiotas was proposed. With our method, we were able to deplete a human gut microbiota of this pks + strains, opening the door to strain-directed microbiota modification and intervention studies that allow us to understand the relation between these genotoxic strains and some gastrointestinal diseases. IMPORTANCE The human gut microbiome has also been hypothesized to play a crucial role in the development and progression of colorectal carcinoma (CRC). Between the microorganisms of this community, the Escherichia coli strains carrying the pks genomic island were shown to be capable of promoting colon tumorigenesis in a colorectal cancer mouse model, and their presence seems to be directly related to a distinct mutational signature in patients suffering CRC. This work proposes a novel method for the detection and depletion of pks -carrying bacteria in human gut microbiotas. In contrast to methods based on probes, this methodology allows the depletion of low-abundance bacterial strains maintaining the viability of both targeted and non-targeted fractions of the microbiota, allowing the study of the contribution of these pks -carrying strains to different diseases, such as CRC, and their role in other physiological, metabolic or immune processes.

The human microbiome is an integral component of the human body and a co-determinant of several health conditions1,2. However, the extent to which interpersonal relations shape the individual genetic makeup of the microbiome and its transmission within and across populations remains largely unknown3,4. Here, capitalizing on more than 9,700 human metagenomes and computational strain-level profiling, we detected extensive bacterial strain sharing across individuals (more than 10 million instances) with distinct mother-to-infant, intra-household and intra-population transmission patterns. Mother-to-infant gut microbiome transmission was considerable and stable during infancy (around 50% of the same strains among shared species (strain-sharing rate)) and remained detectable at older ages. By contrast, the transmission of the oral microbiome occurred largely horizontally and was enhanced by the duration of cohabitation. There was substantial strain sharing among cohabiting individuals, with 12% and 32% median strain-sharing rates for the gut and oral microbiomes, and time since cohabitation affected strain sharing more than age or genetics did. Bacterial strain sharing additionally recapitulated host population structures better than species-level profiles did. Finally, distinct taxa appeared as efficient spreaders across transmission modes and were associated with different predicted bacterial phenotypes linked with out-of-host survival capabilities. The extent of microorganism transmission that we describe underscores its relevance in human microbiome studies5, especially those on non-infectious, microbiome-associated diseases., This work was supported by the European Research Council (ERC-STG project MetaPG-716575 and ERC-CoG microTOUCH-101045015) to N.S. and by EMBO ALTF 593–2020 to M.V.-C. The work was also partially supported by MIUR ‘Futuro in Ricerca’ (grant no. RBFR13EWWI_001) to N.S., by the European H2020 programme (ONCOBIOME-825410 project, MASTER-818368 project, and IHMCSA-964590) to N.S., by the National Cancer Institute of the National Institutes of Health (1U01CA230551) to N.S., by the Premio Internazionale Lombardia e Ricerca 2019 to N.S., by the Simons Foundation (award ID 648614) to E.D. and N.S., and by the European Research Council (ERC-STG project Mami-639226) to M.C.C

Metagenomic assembly enables new organism discovery from microbial communities, but it can only capture few abundant organisms from most metagenomes. Here we present MetaPhlAn 4, which integrates information from metagenome assemblies and microbial isolate genomes for more comprehensive metagenomic taxonomic profiling. From a curated collection of 1.01 M prokaryotic reference and metagenome-assembled genomes, we define unique marker genes for 26,970 species-level genome bins, 4,992 of them taxonomically unidentified at the species level. MetaPhlAn 4 explains ~20% more reads in most international human gut microbiomes and >40% in less-characterized environments such as the rumen microbiome and proves more accurate than available alternatives on synthetic evaluations while also reliably quantifying organisms with no cultured isolates. Application of the method to >24,500 metagenomes highlights previously undetected species to be strong biomarkers for host conditions and lifestyles in human and mouse microbiomes and shows that even previously uncharacterized species can be genetically profiled at the resolution of single microbial strains.

The identification of the protospacer adjacent motif (PAM) sequences of Cas9 nucleases is crucial for their exploitation as genome editing tools. Here we interrogated a massively expanded dataset of metagenome and virome assemblies for accurate and comprehensive PAM predictions, in order to identify novel Cas9s selected for their PAM requirements. As a test bed we selectively isolated a Cas9 which uses a PAM sequence corresponding to a disease-causing mutation, P23H in the RHO gene. Our PAM prediction pipeline will be instrumental to generate a Cas9 nuclease repertoire responding to any PAM requirement leading towards a natural PAM-free genome editing toolbox.

A growing body of evidence supports the notion that the gut microbiome plays an important role in cancer immunity. However, the underpinning mechanisms remain to be fully elucidated. One attractive hypothesis envisages that among the T cells elicited by the plethora of microbiome proteins a few exist that incidentally recognize neo-epitopes arising from cancer mutations (“molecular mimicry (MM)” hypothesis). To support MM, the human probiotic Escherichia coli Nissle was engineered with the SIINFEKL epitope (OVA-E.coli Nissle) and orally administered to C57BL/6 mice. The treatment with OVA-E.coli Nissle, but not with wild type E. coli Nissle, induced OVA-specific CD8+ T cells and inhibited the growth of tumors in mice challenged with B16F10 melanoma cells expressing OVA. The microbiome shotgun sequencing and the sequencing of TCRs from T cells recovered from both lamina propria and tumors provide evidence that the main mechanism of tumor inhibition is mediated by the elicitation at the intestinal site of cross-reacting T cells, which subsequently reach the tumor environment. Importantly, the administration of Outer Membrane Vesicles (OMVs) from engineered E. coli Nissle, as well as from E. coli BL21(DE3)ΔompA, carrying cancer-specific T cell epitopes also elicited epitope-specific T cells in the intestine and inhibited tumor growth. Overall, our data strengthen the important role of MM in tumor immunity and assign a novel function of OMVs in host-pathogen interaction. Moreover, our results pave the way to the exploitation of probiotics and OMVs engineered with tumor specific-antigens as personalized mucosal cancer vaccines.

A large body of data both in animals and humans demonstrates that the gut microbiome plays a fundamental role in cancer immunity and in determining the efficacy of cancer immunotherapy. In this work, we have investigated whether and to what extent the gut microbiome can influence the antitumor activity of neo-epitope-based cancer vaccines in a BALB/c-CT26 cancer mouse model. Similarly to that observed in the C57BL/6-B16 model, Bifidobacterium administration per se has a beneficial effect on CT26 tumor inhibition. Furthermore, the combination of Bifidobacterium administration and vaccination resulted in a protection which was superior to vaccination alone and to Bifidobacterium administration alone, and correlated with an increase in the frequency of vaccine-specific T cells. The gut microbiome analysis by 16S rRNA gene sequencing and shotgun metagenomics showed that tumor challenge rapidly altered the microbiome population, with Muribaculaceae being enriched and Lachnospiraceae being reduced. Over time, the population of Muribaculaceae progressively reduced while the Lachnospiraceae population increased—a trend that appeared to be retarded by the oral administration of Bifidobacterium. Interestingly, in some Bacteroidales, Prevotella and Muribaculacee species we identified sequences highly homologous to immunogenic neo-epitopes of CT26 cells, supporting the possible role of “molecular mimicry” in anticancer immunity. Our data strengthen the importance of the microbiome in cancer immunity and suggests a microbiome-based strategy to potentiate neo-epitope-based cancer vaccines.

Summary We subjected human paleofeces dating from the Bronze Age to the Baroque period (18th century AD) to in-depth microscopic, metagenomic, and proteomic analyses. The paleofeces were preserved in the underground salt mines of the UNESCO World Heritage site of Hallstatt in Austria. This allowed us to reconstruct the diet of the former population and gain insights into their ancient gut microbiome composition. Our dietary survey identified bran and glumes of different cereals as some of the most prevalent plant fragments. This highly fibrous, carbohydrate-rich diet was supplemented with proteins from broad beans and occasionally with fruits, nuts, or animal food products. Due to these traditional dietary habits, all ancient miners up to the Baroque period have gut microbiome structures akin to modern non-Westernized individuals whose diets are also mainly composed of unprocessed foods and fresh fruits and vegetables. This may indicate a shift in the gut community composition of modern Westernized populations due to quite recent dietary and lifestyle changes. When we extended our microbial survey to fungi present in the paleofeces, in one of the Iron Age samples, we observed a high abundance of Penicillium roqueforti and Saccharomyces cerevisiae DNA. Genome-wide analysis indicates that both fungi were involved in food fermentation and provides the first molecular evidence for blue cheese and beer consumption in Iron Age Europe., Graphical abstract, Highlights • Gut microbiome and diet of European salt miners determined using paleofeces • Until the Baroque, the microbiome resembled that of modern non-Westernized people • Food-fermenting fungi in Iron Age feces indicates blue cheese and beer consumption, Maixner et al. describe the gut microbiome and diet of European salt miners using paleofeces dating from the Bronze Age to the Baroque period. This analysis provides evidence for recent changes in the gut microbiome due to industrialization and for the consumption of fermented food and beverages in Iron Age Europe.

This work describes a new procedure that allows the targeted modification of the human gut microbiota by using antibodies raised against bacterial surface-associated proteins specific to the microorganism of interest. To this end, a polyclonal antibody recognising the surface-associated protein Surface Layer Protein A of Lactobacillus acidophilus DSM20079 was developed. By conjugating this antibody with fluorescent probes and magnetic particles, we were able to specifically identify this bacterium both in a synthetic, and in real gut microbiotas by means of a flow cytometry approach. Further, we demonstrated the applicability of this antibody to deplete complex human gut microbiotas from L. acidophilus in a single step. L. acidophilus was found to interact with other bacteria both in synthetic and in real microbiotas, as reflected by its concomitant depletion together with other species. Further optimization of the procedure including a trypsin step enabled to achieve the selective and complete isolation of this species. Depleting a single species from a gut microbiota, using antibodies recognizing specific cell surface elements of the target organism, will open up novel ways to tackle research on the specific immunomodulatory and metabolic contributions of a bacterium of interest in the context of a complex human gut microbiota, including the investigation into therapeutic applications by adding/depleting a key bacterium. This represents the first work in which an antibody/flow-cytometry based application enabled the targeted edition of human gut microbiotas, and represents the basis for the design of precision microbiome-based therapies., Our work is supported by the Spanish "Programa Estatal de Investigacian, Desarrollo e Inovacion Orientada a los Retos de la Sociedad" (grant AGL2016-78311-R and contract BES-2017-080978, funded by AEI/FEDER, UE), the Asociación Española Contra el Cáncer (AECC; Grant PS-2016) and by the Asturias Regional Plan I + D + i for research groups (FICYT-IDI/2018/000236, funded by PCTI Gobierno del Principado de Asturias/FEDER, UE).

Culture-independent analyses of microbial communities have progressed dramatically in the last decade, particularly due to advances in methods for biological profiling via shotgun metagenomics. Opportunities for improvement continue to accelerate, with greater access to multi-omics, microbial reference genomes, and strain-level diversity. To leverage these, we present bioBakery 3, a set of integrated, improved methods for taxonomic, strain-level, functional, and phylogenetic profiling of metagenomes newly developed to build on the largest set of reference sequences now available. Compared to current alternatives, MetaPhlAn 3 increases the accuracy of taxonomic profiling, and HUMAnN 3 improves that of functional potential and activity. These methods detected novel disease-microbiome links in applications to CRC (1262 metagenomes) and IBD (1635 metagenomes and 817 metatranscriptomes). Strain-level profiling of an additional 4077 metagenomes with StrainPhlAn 3 and PanPhlAn 3 unraveled the phylogenetic and functional structure of the common gut microbe Ruminococcus bromii, previously described by only 15 isolate genomes. With open-source implementations and cloud-deployable reproducible workflows, the bioBakery 3 platform can help researchers deepen the resolution, scale, and accuracy of multi-omic profiling for microbial community studies.

Background Akkermansia muciniphila is a human gut microbe with a key role in the physiology of the intestinal mucus layer and reported associations with decreased body mass and increased gut barrier function and health. Despite its biomedical relevance, the genomic diversity of A. muciniphila remains understudied and that of closely related species, except for A. glycaniphila, unexplored. Results We present a large-scale population genomics analysis of the Akkermansia genus using 188 isolate genomes and 2226 genomes assembled from 18,600 metagenomes from humans and other animals. While we do not detect A. glycaniphila, the Akkermansia strains in the human gut can be grouped into five distinct candidate species, including A. muciniphila, that show remarkable whole-genome divergence despite surprisingly similar 16S rRNA gene sequences. These candidate species are likely human-specific, as they are detected in mice and non-human primates almost exclusively when kept in captivity. In humans, Akkermansia candidate species display ecological co-exclusion, diversified functional capabilities, and distinct patterns of associations with host body mass. Analysis of CRISPR-Cas loci reveals new variants and spacers targeting newly discovered putative bacteriophages. Remarkably, we observe an increased relative abundance of Akkermansia when cognate predicted bacteriophages are present, suggesting ecological interactions. A. muciniphila further exhibits subspecies-level genetic stratification with associated functional differences such as a putative exo/lipopolysaccharide operon. Conclusions We uncover a large phylogenetic and functional diversity of the Akkermansia genus in humans. This variability should be considered in the ongoing experimental and metagenomic efforts to characterize the health-associated properties of A. muciniphila and related bacteria.

Culture-independent analyses of microbial communities have advanced dramatically in the last decade, particularly due to advances in methods for biological profiling via shotgun metagenomics. Opportunities for improvement continue to accelerate, with greater access to multi-omics, microbial reference genomes, and strain-level diversity. To leverage these, we present bioBakery 3, a set of integrated, improved methods for taxonomic, strain-level, functional, and phylogenetic profiling of metagenomes newly developed to build on the largest set of reference sequences now available. Compared to current alternatives, MetaPhlAn 3 increases the accuracy of taxonomic profiling, and HUMAnN 3 improves that of functional potential and activity. These methods detected novel disease-microbiome links in applications to CRC (1,262 metagenomes) and IBD (1,635 metagenomes and 817 metatranscriptomes). Strain-level profiling of an additional 4,077 metagenomes with StrainPhlAn 3 and PanPhlAn 3 unraveled the phylogenetic and functional structure of the common gut microbe Ruminococcus bromii, previously described by only 15 isolate genomes. With open-source implementations and cloud-deployable reproducible workflows, the bioBakery 3 platform can help researchers deepen the resolution, scale, and accuracy of multi-omic profiling for microbial community studies.

Supplementary data to this article can be found online at https:// doi.org/10.1016/j.jff.2020.103969., 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 Crohns 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., Our work is supported by the Spanish “Programa Estatal de Investigación. Desarrollo e Innovación Orientada a los Retos de la Sociedad” (grants AGL2013-44761-P and AGL2016-78311-R); the Asociación Española Contra el Cancer (“Obtención de péptidos bioactivos contra el Cáncer Colo-Rectal a partir de secuencias genéticas de microbiomas intestinales”, Grant PS-2016), by the Asturias Regional Plan I + D + i for research groups (FYCYT-IDI/2018/000236) and by the Autonomic “Investigadores Emerxentes do Sistema Universitario de Galicia” (Grant EM2014/046). This work was partially supported by the Consellería de Educación. Universidades e Formación Profesional (Xunta de Galicia) under the scope of the strategic funding of ED431C2018/55-GRC Competitive Reference Group. Finally, the authors wish to thank Jaume Morales and Rubén García form Agilent Technologies for technical support., info:eu-repo/semantics/publishedVersion

COVID-2019 has progressed in around 10-15% of patients to an acute respiratory distress syndrome characterized by extensive pulmonary inflammation and elevated production of pro-inflammatory cytokines. Neutrophil activation seems to be crucial in the initiation and perpetuation of this exacerbated lung inflammation. However, the precise mechanisms by which this activation occurs remain yet elusive. To this end, this in silico study tried to identify potential proinflammatory inducing peptides (PIPs) produced by the action of the elastase released in neutrophil-extracellular traps over SARS-CoV-2 particles. We found nine potential PIPs exclusive from the SARS-CoV-2, showing homology against T cell recognition epitopes. Moreover, 78 percent of these exclusive PIPs were found produced by the enzymatic cleavage on the spike glycoproteins, suggesting that high PIP concentrations might be released following SARS-CoV-2 huge replication rate. Therefore, these PIPs might play a role in the exacerbated inflammatory response observed in some patients.

Diarrhoea is one of the most burdensome and common adverse events of chemotherapeutics, and has no standardised therapy to date. Increasing evidence suggests that the gut microbiome can influence the development of chemotherapy-induced diarrhoea. Here we report findings from a randomised clinical trial of faecal microbiota transplantation (FMT) to treat diarrhoea induced by tyrosine kinase inhibitors (TKI) in patients with metastatic renal cell carcinoma (ClinicalTrials.gov number: NCT04040712). The primary outcome is the resolution of diarrhoea four weeks after the end of treatments. Twenty patients are randomised to receive FMT from healthy donors or placebo FMT (vehicle only). Donor FMT is more effective than placebo FMT in treating TKI-induced diarrhoea, and a successful engraftment is observed in subjects receiving donor faeces. No serious adverse events are observed in both treatment arms. The trial meets pre-specified endpoints. Our findings suggest that the therapeutic manipulation of gut microbiota may become a promising treatment option to manage TKI-dependent diarrhoea., Tyrosine kinase inhibitors (TKIs) have improved the clinical outcomes of patients with metastatic renal cell carcinoma (mRCC), however TKI-related diarrhoea is a common and serious adverse effect. Here the authors show in a randomized clinical trial that faecal microbiota transplantation from healthy donors can improve TKI-induced diarrhoea in patients with mRCC.

Lactobacillus genus includes both probiotic and representative strains of the human gut microbiota. Independent studies have reported on the anti-inflammatory properties of different Lactobacillus strains, although we are far from understanding the underlying molecular interplay. In this work we show that a daily administration of Lactobacillus acidophilus DSM20079T (DSM20079) to healthy piglets resulted in plasmatic increases of the anti-inflammatory IL10, whilst IL12 and the pro-inflammatory ratio IL12+TNF/IL10 decreased. The extracellular protein fraction of DSM20079 was identified as the responsible for the crosstalk interaction that elicited these tolerogenic effects. This strain was able to activate innate immune pathways in dendritic cells and to decrease the production of pro-inflammatory cytokines in both CD4+/CD8+ T cell subsets in healthy donors and in Crohns Disease patients. The tolerogenic effect exerted by the extracellular proteins of this strain suggests their potential use as coadjutant for therapeutic applications targeting chronic inflammatory illnesses., Our work is supported by the Spanish “Programa Estatal de Investigación, Desarrollo e Inovación Orientada a los Retos de la Sociedad” (grant AGL2016-78311-R); the Asociación Española Contra el Cancer (“Obtención de péptidos bioactivos contra el Cáncer ColoRectal a partir de secuencias genéticas de microbiomas intestinales”, Grant PS-2016) and by the Asturias Regional Plan I+D+i for research groups (FYCYT-IDI/2018/000236). This study was also supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER006684). SING group thanks CITI (Centro de Investigación, Transferencia e Innovación) from University of Vigo for hosting its IT infrastructure. LJR was supported by the Principado de Asturias, PCTI 2018–2020 (GRUPIN: IDI2018-000237) and FEDER. This work was partially supported by the Consellería de Educación, Universidades e Formación Profesional (Xunta de Galicia) under the scope of the strategic funding of ED431C2018/55-GRC Competitive Reference Group., info:eu-repo/semantics/publishedVersion

[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., This work was supported by the Spanish “Programa Estatal de Investigación, Desarrollo e Inovación Orientada a los Retos de la Sociedad” (grant AGL2013-44039R); the Asociación Española Contra el Cancer (“Obtención de péptidos bioactivos contra el Cáncer Colo-Rectal a partir de secuencias genéticas de microbiomas intestinales”, grant PS-2016); the Consellería de Educación, Universidades e Formación Profesional (Xunta de Galicia) under the scope of the strategic funding of ED431C2018/55-GRC Competitive Reference Group; the Portuguese Foundation for Science and Technology under the scope of the strategic funding of UID/BIO/04469/2019 unit; and the Asturias Regional Plan I + D + i for research groups (FYCYT-IDI/2018/000236). H. López-Fernández is supported by a post-doctoral fellowship from Xunta de Galicia (ED481B 2016/068-0).

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., This work was supported by the Spanish “Programa Estatal de Investigación, Desarrollo e Inovación Orientada a los Retos de la Sociedad” (grant AGL2013-44039R); the Asociación Española Contra el Cancer (“Obtención de péptidos bioactivos contra el Cáncer Colo-Rectal a partir de secuencias genéticas de microbiomas intestinales”, grant PS-2016). This study was also supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER006684). SING group thanks CITI (Centro de Investigación, Transferencia e Innovación) from University of Vigo for hosting its IT infrastructure.

Chemoprevention is the use of natural and/or synthetic substances to block, reverse, or retard the process of carcinogenesis. In this field, the use of antitumor peptides is of interest as, (i) these molecules are small in size, (ii) they show good cell diffusion and permeability, (iii) they affect one or more specific molecular pathways involved in carcinogenesis, and (iv) they are not usually genotoxic. We have checked the Web of Science Database (23/11/2015) in order to collect papers reporting on bioactive peptide (1691 registers), which was further filtered searching terms such as "antiproliferative," "antitumoral," or "apoptosis" among others. Works reporting the amino acid sequence of an antiproliferative peptide were kept (60 registers), and this was complemented with the peptides included in CancerPPD, an extensive resource for antiproliferative peptides and proteins. Peptides were grouped according to one of the following mechanism of action: inhibition of cell migration, inhibition of tumor angiogenesis, antioxidative mechanisms, inhibition of gene transcription/cell proliferation, induction of apoptosis, disorganization of tubulin structure, cytotoxicity, or unknown mechanisms. The main mechanisms of action of those antiproliferative peptides with known amino acid sequences are presented and finally, their potential clinical usefulness and future challenges on their application is discussed.

Flow cytometry (FC) is a very popular technique for to the study of different eukaryotic cell phenotypes. In addition, FC has many applications in the field of food microbiology, although the few number of specific molecules that can be potentially targeted with fluorescence-conjugated antibodies limits its potential applications. The present work represents a step forward in the application of FC for detection of specific foodborne or probiotic bacteria by using fluorescent antibodies binding specific surface-associated protein. To illustrate this novel approach, we have used a monoclonal and polyclonal antibodies targeting cell-wall hydrolase (CWH), one of the major surface-associated proteins of the probiotic Lactobacillus rhamnosus GG. In order to verify the specific union of the antibodies to this surface protein, ten different bacterial strains belonging to different bacteria species taxonomically related and no related to L. rhamnosus, were tested. The optimal conditions for bacteria detection corresponded to a final suspension of 5E107 bacteria in exponential phase of growth using FC buffer, without freezing, without adding extra BSA to the FC buffer and without fixing bacteria. Our results showed that GG strain was detected using the polyclonal anti-CWH serum in a higher extent (91.62%) than the rest of strains (L. casei 393: 64.49%; L. amylovorus: 46.13%, E. coli: 45.13%; L. acidophilus DSM20079T: 35.83%; B. longum NCIMB8809: 33.68%; L. gasseri BM7/10: 32.41%; L. reuteri DSM21016: 29.26%; L. plantarum NCIMB8826: 26.33% and L. delbruekii: 22.52%). The percentage of L. rhamnosus labeled with the monoclonal antibody was 53.06, which contrasted with the 91.62% labeled with the polyclonal antibody. The low affinity of the monoclonal antibody was perhaps due to the lack of immunogenicity of the single epitope chosen for antibody generation (CWHp). The high efficiency observed for the polyclonal anti-CWH serum is maybe a consequence of being constituted by a mixture of antibodies that recognizes different epitopes in the L. rhamnosus GG protein. With this proof of concept, we have shown for the first time that foodborne or probiotic bacteria can be specifically detected using antibodies targeting adequate molecules present on their surface.

This work reports on a large-scale potential neuropeptide activity screening in human gut microbiomes deposited in public databases. In our experimental approach, the sequences of the bioactive peptides collected in the MAHMI database, mainly predicted as immunomodulatory or antitumoral, were crossed with those of the neuroactive/digestive peptides. From 91,325,790 potential bioactive peptides, only 581 returned a match when crossed against the 5949 neuroactive peptides from the NeuroPep database and the 15 digestive hormones. Relevant bacterial taxa, such as Ruminococcus sp., Clostridium sp. were found among the main producers of the matching sequences, and many of the matches corresponded to adiponectin and the hormone produced by adipocites, which is involved in glucose homeostasis. These results show, for the first time, the presence of potentially bioactive peptides produced by gut microbiota members over the nervous cells, most notably, peptides with already predicted immunomodulatory or anti-inflammatory activity. Classical (Lactobacillus sp.) and next-generation (Faecalibacterium sp.) probiotics are shown to produce these peptides, which are proposed as a potential mechanism of action of psychobiotics. Our previous experimental results showed that many of these peptides were active when incubated with immune cells, such as dendritic cells, so their effect over the nervous system innervating the gut mucosa holds significant potential and should be explored., This work was supported by the Spanish “Programa Estatal de Investigación, Desarrollo e Inovación Orientada a los Retos de la Sociedad” (Grant AGL2016-78311-R); the Asociación Española Contra el Cancer (“Obtención de péptidos bioactivos contra el Cáncer Colo-Rectal a partir de secuencias genéticas de microbiomas intestinales”, grant PS-2016). This study was also supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER006684). SING group thanks CITI (Centro de Investigación, Transferencia e Innovación) from University of Vigo for hosting its IT infrastructure. This work was partially supported by the Asturias Regional Plan I+D+i for research groups (FYCYT-IDI/2018/000236) and by the Consellería de Educación, Universidades e Formación Profesional (Xunta de Galicia) under the scope of the strategic funding of ED431C2018/55-GRC Competitive Reference Group.

The human gut microbiome impacts several aspects of human health and disease, including digestion, drug metabolism and the propensity to develop various inflammatory, autoimmune and metabolic diseases. Many of the molecular processes that play a role in the activity and dynamics of the microbiota go beyond species and genic composition and thus, their understanding requires advanced bioinformatics support. This article aims to provide an up-to-date view of the resources and software tools that are being developed and used in human gut microbiome research, in particular data integration and systems-level analysis efforts. These efforts demonstrate the power of standardized and reproducible computational workflows for integrating and analysing varied omics data and gaining deeper insights into microbe community structure and function as well as host-microbe interactions.

Peptidome similarity analysis enables researchers to gain insights into differential peptide profiles, providing a robust tool to discriminate strain-specific peptides, true intra-species differences among biological replicates or even microorganism-phenotype variations. However, no in silico peptide fingerprinting software existed to facilitate such phylogeny inference. Hence, we developed the Peptidomes for Phylogenies (P4P) web tool, which enables the survey of similarities between microbial proteomes and simplifies the process of obtaining new biological insights into their phylogeny. P4P can be used to analyze different peptide datasets, i.e. bacteria, viruses, eukaryotic species or even metaproteomes. Also, it is able to work with whole proteome datasets and experimental mass-to-charge lists originated from mass spectrometers. The ultimate aim is to generate a valid and manageable list of peptides that have phylogenetic signal and are potentially sample-specific. Sample-to-sample comparison is based on a consensus peak set matrix, which can be further submitted to phylogenetic analysis. P4P holds great potential for improving phylogenetic analyses in challenging taxonomic groups, biomarker identification or epidemiologic studies. Notably, P4P can be of interest for applications handling large proteomic datasets, which it is able to reduce to small matrices while maintaining high phylogenetic resolution. The web server is available at http://sing-group.org/p4p., Spanish ‘Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad’ [AGL2013-44039R]; Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020[POCI-01-0145-FEDER-006684];INOU16-05project from the University of Vigo; Fundación AECC. Funding for open access charge: Spanish ‘Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad’ [AGL2013-44039R]., info:eu-repo/semantics/publishedVersion

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., This work was funded by the Grant AGL2013-44039-R from the Spanish “Plan Estatal de I + D+I”, and the Grant EM2014/046 from the “Plan Galego de investigación, innovación e crecemento 2011-2015”. Borja Sánchez was recipient of a Ramón y Cajal postdoctoral contract from the Spanish Ministry of Economy and Competitiveness. This work was also partially funded by the [14VI05] Contract-Programme from the University of Vigo and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273) and the European Union’s Seventh Framework Programme FP7/REGPOT-2012-2013.1 under grant agreement n° 316265, BIOCAPS.

The gastrointestinal tract of mammals hosts a high and diverse number of different microorganisms, known as intestinal microbiota. Many probiotics were originally isolated from the gastrointestinal tract, and they were defined by the Food and Agriculture Organization of the United Nations (FAO)/WHO as “live microorganisms which when administered in adequate amounts confer a health benefit on the host.” Probiotics exert their beneficial effects on the host through four main mechanisms: interference with potential pathogens, improvement of barrier function, immunomodulation and production of neurotransmitters, and their host targets vary from the resident microbiota to cellular components of the gut–brain axis. However, in spite of the wide array of beneficial mechanisms deployed by probiotic bacteria, relatively few effects have been supported by clinical data. In this regard, different probiotic strains have been effective in antibiotic‐associated diarrhea or inflammatory bowel disease for instance. The aim of this review was to compile the molecular mechanisms underlying the beneficial effects of probiotics, mainly through their interaction with the intestinal microbiota and with the intestinal mucosa. The specific benefits discussed in this paper include among others those elicited directly through dietary modulation of the human gut microbiota., Research in our lab is funded by Grants AGL2013‐44039‐R and AGL2013‐44761‐P from the Spanish “Plan Estatal de I+D+I.” Part of the authors is also partially funded by the [15VI013] Contract‐Programme from the University of Vigo and the Agrupamento INBIOMED from DXPCTSUG‐FEDER unha maneira de facer Europa (2012/273). B. S. was recipient of a Ramón y Cajal postdoctoral contract from the Spanish Ministry of Economy and Competitiveness.

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.fm.2016.06.015., Bifidobacteria are gut commensal microorganisms belonging to the Actinobacteria group. Some specific strains of Bifidobacterium animalis subsp. lactis are used in functional foods as they are able to exert health-promoting effects in the human host. Due to the limited genetic variability within this subspecies, it is sometimes difficult for a manufacturer to properly track its strain once included in dairy products or functional foods. In this paper, we present a peptidome-based analysis in which the proteomes of a set of B. animalis subsp. lactis strains were digested in silico with human gut endopeptidases. The molecular masses were compared along all the strains to detect strain-specific peptides. These peptides may be interesting towards the development of methodologies for strain identification in the final product., This research was funded by Grant AGL2013-44039-R from the Spanish “Plan Estatal de IþDþI”, and by Grant EM2014/046 from the “Plan Galego de investigaci on, innovaci on e crecemento 2011e2015”. Borja S anchez was recipient of a Ram on y Cajal postdoctoral contract from the Spanish Ministry of Economy and Competitiveness (RYC-2012-10052). This work was also partially funded by the [14VI05] Contract- Programme from the Unixikversity of Vigo and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273). The research leading to these results has also received funding from the European Union’s Seventh Framework Programme FP7/REGPOT-2012-2013.1 under grant agreement no 316265, BIOCAPS. This document reflects only the author’s views and the European Union is not liable for any use that may be made of the information contained herein.

Typical bacterial strain differentiation methods are often challenged by high genetic similarity between strains. To address this problem, we introduce a novel in silico peptide fingerprinting method based on conventional wet-lab protocols that enables the identification of potential strain-specific peptides. These can be further investigated using in vitro approaches, laying a foundation for the development of biomarker detection and application-specific methods. This novel method aims at reducing large amounts of comparative peptide data to binary matrices while maintaining a high phylogenetic resolution. The underlying case study concerns the Bacillus cereus group, namely the differentiation of Bacillus thuringiensis, Bacillus anthracis and Bacillus cereus strains. Results show that trees based on cytoplasmic and extracellular peptidomes are only marginally in conflict with those based on whole proteomes, as inferred by the established Genome-BLAST Distance Phylogeny (GBDP) method. Hence, these results indicate that the two approaches can most likely be used complementarily even in other organismal groups. The obtained results confirm previous reports about the misclassification of many strains within the B. cereus group. Moreover, our method was able to separate the B. anthracis strains with high resolution, similarly to the GBDP results as benchmarked via Bayesian inference and both Maximum Likelihood and Maximum Parsimony. In addition to the presented phylogenomic applications, whole-peptide fingerprinting might also become a valuable complementary technique to digital DNA-DNA hybridization, notably for bacterial classification at the species and subspecies level in the future., This research was funded by Grant AGL2013-44039-R from the Spanish “Plan Estatal de I+D+I”, and by Grant EM2014/046 from the “Plan Galego de investigación, innovación e crecemento 2011-2015”. BS was recipient of a Ramón y Cajal postdoctoral contract from the Spanish Ministry of Economy and Competitiveness. This work was also partially funded by the [14VI05] Contract-Programme from the University of Vigo and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273). The research leading to these results has also received funding from the European Union's Seventh Framework Programme FP7/REGPOT-2012-2013.1 under grant agreement n° 316265, BIOCAPS