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Abstract We performed a longitudinal shotgun metagenomic investigation of the plaque microbiome associated with peri-implant diseases in a cohort of 91 subjects with 320 quality-controlled metagenomes. Through recently improved taxonomic profiling methods, we identified the most discriminative species between healthy and diseased subjects at baseline, evaluated their change over time, and provided evidence that clinical treatment had a positive effect on plaque microbiome composition in patients affected by mucositis and peri-implantitis.

Summary: Background: Neuroblastoma is the most frequent extracranial solid tumour in children, accounting for ∼15% of deaths due to cancer in childhood. The most common clinical presentation are abdominal tumours. An altered gut microbiome composition has been linked to multiple cancer types, and reported in murine models of neuroblastoma. Whether children with neuroblastoma display alterations in gut microbiome composition remains unexplored. Methods: We assessed gut microbiome composition by shotgun metagenomic profiling in an observational cross-sectional study on 288 individuals, consisting of patients with a diagnosis of neuroblastoma at disease onset (N = 63), healthy controls matching the patients on the main covariates of microbiome composition (N = 94), healthy siblings of the patients (N = 13), mothers of patients (N = 59), and mothers of the controls (N = 59). We examined taxonomic and functional microbiome composition and mother-infant strain transmission patterns. Findings: Patients with neuroblastoma displayed alterations in gut microbiome composition characterised by reduced microbiome richness, decreased relative abundances of 18 species (including Phocaeicola dorei and Bifidobacterium bifidum), enriched protein fermentation and reduced carbohydrate fermentation potential. Using machine learning, we could successfully discriminate patients from controls (AUC = 82%). Healthy siblings did not display such alterations but resembled the healthy control group. No significant differences in maternal microbiome composition nor mother-to-offspring transmission were detected. Interpretation: Patients with neuroblastoma display alterations in taxonomic and functional gut microbiome composition, which cannot be traced to differential maternal seeding. Follow-up research should include investigating potential causal links. Funding: Italian Ministry of Health Ricerca Corrente and Ricerca Finalizzata 5 per mille (to MPonzoni); Fondazione Italiana Neuroblastoma (to MPonzoni); European Research Council (ERC-StG project MetaPG-716575 and ERC-CoG microTOUCH-101045015 to NS); the European H2020 program ONCOBIOME-825410 project (to NS); the National Cancer Institute of the National Institutes of Health 1U01CA230551 (to NS); the Premio Internazionale Lombardia e Ricerca 2019 (to NS); the MIUR Progetti di Ricerca di Rilevante Interesse Nazionale (PRIN) Bando 2017 Grant 2017J3E2W2 (to NS); EMBO ALTF 593-2020 and Knowledge Generation Project from the Spanish Ministry of Science and Innovation (PID2022-139328OA-I00) (to MV-C).

Cas9 proteins require a target-adjacent sequence, the PAM, in order to cleave DNA. Here the authors develop a pipeline to accurately predict PAM sequences in order to facilitate the identification of Cas9s targeting specific sequences, including mutations.

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.

Abstract Malignant bile duct obstruction is typically treated by biliary stenting, which however increases the risk of bacterial infections. Here, we analyzed the microbial content of the biliary stents from 56 patients finding widespread microbial colonization. Seventeen of 36 prevalent stent species are common oral microbiome members, associate with disease conditions when present in the gut, and include dozens of biofilm- and antimicrobial resistance-related genes. This work provides an overview of the microbial communities populating the stents.

ABSTRACT 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.

Summary: Mouse models are key tools for investigating host-microbiome interactions. However, shotgun metagenomics can only profile a limited fraction of the mouse gut microbiome. Here, we employ a metagenomic profiling method, MetaPhlAn 4, which exploits a large catalog of metagenome-assembled genomes (including 22,718 metagenome-assembled genomes from mice) to improve the profiling of the mouse gut microbiome. We combine 622 samples from eight public datasets and an additional cohort of 97 mouse microbiomes, and we assess the potential of MetaPhlAn 4 to better identify diet-related changes in the host microbiome using a meta-analysis approach. We find multiple, strong, and reproducible diet-related microbial biomarkers, largely increasing those identifiable by other available methods relying only on reference information. The strongest drivers of the diet-induced changes are uncharacterized and previously undetected taxa, confirming the importance of adopting metagenomic methods integrating metagenomic assemblies for comprehensive profiling.

Abstract 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.

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.

Abstract 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 DSM20079T 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.

Abstract Background Shared tasks and community challenges represent key instruments to promote research, collaboration and determine the state of the art of biomedical and chemical text mining technologies. Traditionally, such tasks relied on the comparison of automatically generated results against a so-called Gold Standard dataset of manually labelled textual data, regardless of efficiency and robustness of the underlying implementations. Due to the rapid growth of unstructured data collections, including patent databases and particularly the scientific literature, there is a pressing need to generate, assess and expose robust big data text mining solutions to semantically enrich documents in real time. To address this pressing need, a novel track called “Technical interoperability and performance of annotation servers” was launched under the umbrella of the BioCreative text mining evaluation effort. The aim of this track was to enable the continuous assessment of technical aspects of text annotation web servers, specifically of online biomedical named entity recognition systems of interest for medicinal chemistry applications. Results A total of 15 out of 26 registered teams successfully implemented online annotation servers. They returned predictions during a two-month period in predefined formats and were evaluated through the BeCalm evaluation platform, specifically developed for this track. The track encompassed three levels of evaluation, i.e. data format considerations, technical metrics and functional specifications. Participating annotation servers were implemented in seven different programming languages and covered 12 general entity types. The continuous evaluation of server responses accounted for testing periods of low activity and moderate to high activity, encompassing overall 4,092,502 requests from three different document provider settings. The median response time was below 3.74 s, with a median of 10 annotations/document. Most of the servers showed great reliability and stability, being able to process over 100,000 requests in a 5-day period. Conclusions The presented track was a novel experimental task that systematically evaluated the technical performance aspects of online entity recognition systems. It raised the interest of a significant number of participants. Future editions of the competition will address the ability to process documents in bulk as well as to annotate full-text documents.

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.

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.

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+TNFα/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 Crohn’s 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.

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.

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/.

Scientific studies focused on the role of the human microbiome over human health have generated billions of gigabits of genetic information during the last decade. Nowadays integration of all this information in public databases and development of pipelines allowing us to biotechnologically exploit this information are urgently needed. Prediction of the potential bioactivity of the products encoded by the human gut microbiome, or metaproteome, is the first step for identifying proteins responsible for the molecular interaction between microorganisms and the immune system. We have recently published the Mechanism of Action of the Human Microbiome (MAHMI) database (http://www.mahmi.org), conceived as a resource compiling peptide sequences with a potential immunomodulatory activity. Fifteen out of the 300 hundred million peptides contained in the MAHMI database were synthesized. These peptides were identified as being encrypted in proteins produced by gut microbiota members, they do not contain cleavage points for the major intestinal endoproteases and displayed high probability to have immunomodulatory bioactivity. The bacterial peptides FR-16 and LR-17 encrypted in proteins from Bifidobacterium longum DJ010A and Bifidobacterium fragilis YCH46 respectively, showed the higher immune modulation capability over human peripheral blood mononuclear cells. Both peptides modulated the immune response toward increases in the Th17 and decreases in the Th1 cell response, together with an induction of IL-22 production. These results strongly suggest the combined use of bioinformatics and in vitro tools as a first stage in the screening of bioactive peptides encrypted in the human gut metaproteome.

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.

Abstract Whilst most individuals with SARS-CoV-2 infection have relatively mild disease, managed in the community, it was noted early in the pandemic that individuals with cardiovascular risk factors were more likely to experience severe acute disease, requiring hospitalisation. As the pandemic has progressed, increasing concern has also developed over long symptom duration in many individuals after SARS-CoV-2 infection, including among the majority who are managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined. Here, we examine post-illness metabolomic profiles, using nuclear magnetic resonance (Nightingale Health Oyj), and gut-microbiome profiles, using shotgun metagenomic sequencing (Illumina Inc), in 2561 community-dwelling participants with SARS-CoV-2. Illness duration ranged from asymptomatic (n = 307) to Post-COVID Syndrome (n = 180), and included participants with prolonged non-COVID-19 illnesses (n = 287). We also assess a pre-established metabolomic biomarker score, previously associated with hospitalisation for both acute pneumonia and severe acute COVID-19 illness, for its association with illness duration. We found an atherogenic-dyslipidaemic metabolic profile, including biomarkers such as fatty acids and cholesterol, was associated with longer duration of illness, both in individuals with and without SARS-CoV-2 infection. Greater values of a pre-existing metabolomic biomarker score also associated with longer duration of illness, regardless of SARS-CoV-2 infection. We found no association between illness duration and gut microbiome profiles in convalescence. This highlights the potential role of cardiometabolic dysfunction in relation to the experience of long duration symptoms after symptoms of acute infection, both COVID-19 as well as other illnesses.