Biology subjects

Ulyantsev, V. I.

Publications and source records attributed to Ulyantsev, V. I..

4 recordsLinked to original sources

bioRxiv2023

Systemic Metabolic Depletion of Intestine Microbiome Undermines Melanoma Immunotherapy Effectiveness

Immunotherapy has proven to be a boon for patients grappling with metastatic melanoma, significantly enhancing their clinical condition and overall quality of life. A compelling connection was discovered between the composition of the intestinal microbiome and the effectiveness of immunotherapy substantiated in both animal models and human patients. Nonetheless, the precise biological mechanisms through which gut microbes influence melanoma treatment outcomes remain poorly understood. This study conducted a high-resolution metagenomic meta-analysis, employing cutting-edge bioinformatics techniques including genome-resolved metagenomics, strain profiling, comparative genomics, and metabolic reconstruction. According to the obtained results, the systemic metabolic depletion of the gut microbiome causes a lack of response to immunotherapy. Specifically, the presence of bacteria adept at utilizing polysaccharides, as well as those responsible for cobalamin, amino acids, and fatty acids production, decreased in patients who experienced unfavorable treatment outcomes. In contrast, patients who had successful outcomes after immunotherapy exhibited a prevalence of amino acids and cobalamin prototrophs, while autotrophy in these substances characterized the microbiomes of patients with unsuccessful outcomes. The metabolic reconstruction of short-chain fatty acid biosynthesis pathways did not differentiate bacteria linked to treatment outcomes based on their ability to produce acetate, butyrate, or propionate. However, the cobalamin-dependent Wood-Ljungdahl pathway of acetate synthesis was directly associated with immunotherapy effectiveness.

bioinformatics↗

bioRxiv2022

Reproducible stool metagenomic biomarkers linked to the melanoma immunotherapy positive outcome

The human gut microbiome plays an important role both in humans health and disease. Recent studies have shown the undeniable influence of gut microbiota composition on cancer immunotherapy efficacy. However, these researches show a lack of consensus in defining reproducible metagenomic markers for a positive immunotherapy outcome. Accordingly, extended published data re-analysis may help reveal clearer associations between the composition of the gut microbiota and treatment response. In this study, we analyzed 358 stool metagenomes from 5 studies published earlier: 210 metagenomes from melanoma patients with positive immunotherapy outcome, 148 metagenomes from melanoma patients with negative immunotherapy outcome. The biomarkers were selected by the group comparison of patients stool samples with different treatment responses (47 responders vs 55 non-responders, 102 metagenomes). Selected biomarkers were verified using the available data describing the influence of the fecal microbiota transplantation on melanoma immunotherapy outcomes (9 donors, 6 responders, 19 non-responders, 256 metagenomes). According to our analysis, the resulting cross-study reproducible taxonomic biomarkers correspond to 12 Firmicutes, 4 Bacteroidetes, and 3 Actinobacteria. 140 gene groups were identified as reproducible functional biomarkers, including those potentially involved in production of immune-stimulating molecules and metabolites. In addition, we ranked taxonomic biomarkers by the number of functional biomarkers found in their metagenomic context. In other words, we predicted a list of the potential "most beneficial" bacteria for a positive response to melanoma immunotherapy. The obtained results can be used to make recommendations for the gut microbiota correction in cancer immunotherapy, and the resulting list of biomarkers can be considered for potential diagnostic ways for predicting melanoma immunotherapy outcome. Another important point is the functional biomarkers of positive immunotherapy outcome are distributed in different bacterial species that can explain the lack of consensus of defining melanoma immunotherapy beneficial species between different studies.

bioinformatics↗

bioRxiv2020

Gut microbiota alterations due to fecal transplant

BackgroundFecal microbiota transplantation (FMT) is currently used to treat recurrent clostridial colitis and other diseases. However, neither the therapeutic mechanism of the FMT nor the mechanism that allows the donor bacteria to colonize the intestine of the recipient has yet been described. Moreover, FMT is a great model for studying the ecology of host-associated microbial communities. This creates the need for experimentation with approaches to metagenomic data analysis which may be useful to the interpretation of observed biological phenomena. MethodsHere the RECAST (Recipient intestinE Colonisation AnalysiS Tool) computational approach is presented, which is based on the shotgun reads sorting process in accordance with their origin in recipient metagenome. Using the RECAST algorithm, taxonomic/functional annotation, and machine learning, the shotgun metagenomic data from three FMT studies including healthy volunteers, patients with clostridial colitis and metabolic syndrome were analyzed. ResultsAccording to the analysis results, the colonizing and remaining microbial diversity in the post-FMT recipient metagenomic samples is clearly separated from the non-colonizers and lost. It is well explained by higher relative abundance in donor/pre-FMT recipient, Human Microbiome project metagenomes, and taxonomy. Moreover, the colonizing and remaining microbes are associated with lantibiotic and tetracyclines resistance genes. ConclusionBased on obtained results, the previously proposed "core" human gut microbiome concept may be elaborated. The top microbes of gut microbiota form "cores", which, moreover, are mutually integrable between humans. Also, we assume that redistribution of microbial diversity in post-FMT recipients metagenomes is due to competition of donor/recipient microbes and to host immunity. The associations of top gut microbes with lantibiotic/antibiotic resistance can be related to gut microbiota colonization resistance phenomena or anthropogenic impact.

bioinformatics↗

bioRxiv2017

MetaCherchant - an algorithm for analyzing genomicenvironment of antibiotic resistance genein gut microbiota

Antibiotic resistance is an important global public health problem. Human gut human microbiota is an accumulator of resistance genes potentially providing them to pathogens. It is important to develop tools for identifying the mechanisms of how resistance is transmitted between gut microbial species and pathogens. We developed MetaCherchant - an algorithm for extracting the genomic environment of antibiotic resistance genes from metagenomic data in the form of a graph. The algorithm was validated on simulated datasets and applied to new \"shotgun\" metagenomes of gut microbiota from patients with Helicobacter pylori who underwent antibiotic therapy. Genomic context was reconstructed for several dominant resistance genes; taxonomic annotation of the context showed the species carrying the genes. Application of MetaCherchant in differential mode produced specific graph structures suggesting the evidence of possible resistance gene transmission within a mobile element that occurred as a result of the antibiotic therapy. MetaCherchant is a promising tool giving researchers an opportunity to get an insight into dynamics of resistance transmission in vivo based on metagenomic data.

bioinformatics↗