Snapper: high-sensitive detection of methylation motifs based on Oxford Nanopore reads.

MOTIVATION: The Oxford Nanopore technology has a great potential for the analysis of methylated motifs in genomes, including whole-genome methylome profiling. However, we found that there are no methylation motifs detection algorithms, which would be sensitive enough and return deterministic results. Thus, the MEME suit does not extract all Helicobacter pylori methylation sites de novo even using the iterative approach implemented in the most up-to-date methylation analysis tool Nanodisco. RESULTS: We present Snapper, a new highly sensitive approach, to extract methylation motif sequences based on a greedy motif selection algorithm. Snapper does not require manual control during the enrichment process and has enrichment sensitivity higher than MEME coupled with Tombo or Nanodisco instruments that was demonstrated on H.pylori strain J99 studied earlier by the PacBio technology and on four external datasets representing different bacterial species. We used Snapper to characterize the total methylome of a new H.pylori strain A45. At least four methylation sites that have not been described for H.pylori earlier were revealed. We experimentally confirmed the presence of a new CCAG-specific methyltransferase and inferred a gene encoding a new CCAAK-specific methyltransferase. AVAILABILITY AND IMPLEMENTATION: Snapper is implemented using Python and is freely available as a pip package named "snapper-ont." Also, Snapper and the demo dataset are available in Zenodo (10.5281/zenodo.10117651).

FunFun: ITS-based functional annotator of fungal communities.

The study of individual fungi and their communities is of great interest to modern biology because they might be both producers of useful compounds, such as antibiotics and organic acids, and pathogens of various diseases. And certain features associated with the functional capabilities of fungi are determined by differences in gene content. Information about gene content is most often taken from the results of functional annotation of the whole genome. However, in practice, whole genome sequencing of fungi is rarely performed. At the same time, usually sequence amplicons of the ITS region to identify fungal taxonomy. But in the case of amplicon sequencing there is no way to perform a functional annotation. Here, we present FunFun, the instrument that allows to evaluate the gene content of an individual fungus or mycobiome from ITS sequencing data. FunFun algorithm based on a modified K-nearest neighbors algorithm. As input, the program can use ITS1, ITS2, or a full-size ITS cluster (ITS1-5.8S-ITS2). FunFun was realized as a pip-installed command line instrument and validated using a shuffle-split approach. The developed instrument can be very useful in the fungal community comparing and estimating functional capabilities of fungi under study. Also, the program can predict with high accuracy the most variable functions.

Consistent Stool Metagenomic Biomarkers Associated with the Response To Melanoma Immunotherapy.

The human gut microbiome plays an important role in both health and disease. Recent studies have demonstrated a strong influence of the gut microbiome composition on the efficacy of cancer immunotherapy. However, available studies have not yet succeeded in finding reliable and consistent metagenomic markers that are associated with the response to immunotherapy. Therefore, the reanalysis of the published data may improve our understanding of the association between the composition of the gut microbiome and the treatment response. In this study, we focused on melanoma-related metagenomic data, which are more abundant than are data from other tumor types. We analyzed the metagenomes of 680 stool samples from 7 studies that were published earlier. The taxonomic and functional biomarkers were selected after comparing the metagenomes of patients showing different treatment responses. The list of selected biomarkers was also validated on additional metagenomic data sets that were dedicated to the influence of fecal microbiota transplantation on the response to melanoma immunotherapy. According to our analysis, the resulting cross-study taxonomic biomarkers included three bacterial species: Faecalibacterium prausnitzii, Bifidobacterium adolescentis, and Eubacterium rectale. 101 groups of genes were identified to be functional biomarkers, including those potentially involved in the production of immune-stimulating molecules and metabolites. Moreover, we ranked the microbial species by the number of genes encoding functionally relevant biomarkers that they contained. Thus, we put together a list of potentially the most beneficial bacteria for immunotherapy success. F. prausnitzii, E. rectale, and three species of bifidobacteria stood out as the most beneficial species, even though some useful functions were also present in other bacterial species. IMPORTANCE In this study, we put together a list of potentially the most beneficial bacteria that were associated with a responsiveness to melanoma immunotherapy. Another important result of this study is the list of functional biomarkers of responsiveness to immunotherapy, which are dispersed among different bacterial species. This result possibly explains the existing irregularities between studies regarding the bacterial species that are beneficial to melanoma immunotherapy. Overall, these findings can be utilized to issue recommendations for gut microbiome correction in cancer immunotherapy, and the resulting list of biomarkers might serve as a good stepping stone for the development of a diagnostic test that is aimed at predicting patients' responses to melanoma immunotherapy.

Identification and Genetic Characterization of MERS-Related Coronavirus Isolated from Nathusius' Pipistrelle (Pipistrellus nathusii) near Zvenigorod (Moscow Region, Russia).

Being diverse and widely distributed globally, bats are a known reservoir of a series of emerging zoonotic viruses. We studied fecal viromes of twenty-six bats captured in 2015 in the Moscow Region and found 13 of 26 (50%) samples to be coronavirus positive. Of P. nathusii (the Nathusius' pipistrelle), 3 of 6 samples were carriers of a novel MERS-related betacoronavirus. We sequenced and assembled the complete genome of this betacoronavirus and named it MOW-BatCoV strain 15-22. Whole genome phylogenetic analysis suggests that MOW-BatCoV/15-22 falls into a distinct subclade closely related to human and camel MERS-CoV. Unexpectedly, the phylogenetic analysis of the novel MOW-BatCoV/15-22 spike gene showed the closest similarity to CoVs from Erinaceus europaeus (European hedgehog). We suppose MOW-BatCoV could have arisen as a result of recombination between ancestral viruses of bats and hedgehogs. Molecular docking analysis of MOW-BatCoV/15-22 spike glycoprotein binding to DPP4 receptors of different mammals predicted the highest binding ability with DPP4 of the Myotis brandtii bat (docking score -320.15) and the E. europaeus (docking score -294.51). Hedgehogs are widely kept as pets and are commonly found in areas of human habitation. As this novel bat-CoV is likely capable of infecting hedgehogs, we suggest hedgehogs can act as intermediate hosts between bats and humans for other bat-CoVs.

Streptocinnamides A and B, Depsipeptides from Streptomyces sp. KMM 9044.

The bacterium Streptomyces sp. KMM 9044 from a sample of marine sediment collected in the northwestern part of the Sea of Japan produces highly chlorinated depsiheptapeptides streptocinnamides A (1) and B (2), representatives of a new structural group of antibiotics. The structures of 1 and 2 were determined using nuclear magnetic resonance and mass spectrometry studies and confirmed by a series of chemical transformations. Streptocinnamide A potently inhibits Micrococcus sp. KMM 1467, Arthrobacter sp. ATCC 21022, and Mycobacterium smegmatis MC2 155.

BioCAT: Search for biosynthetic gene clusters producing nonribosomal peptides with known structure.

Nonribosomal peptides are a class of secondary metabolites synthesized by multimodular enzymes named nonribosomal peptide synthetases and mainly produced by bacteria and fungi. NMR, LC-MS/MS and other analytical methods allow to determine a peptide structure precisely, but it is often not a trivial task to find natural producers of them. There are cases when potential producers should be found among hundreds of strains, for instance, when analyzing metagenomic data. We have developed BioCAT, a tool designed for finding biosynthetic gene clusters which may produce a given nonribosomal peptide when the structure of an interesting nonribosomal peptide has already been found. BioCAT unites the antiSMASH software and the rBAN retrosynthesis tool but some improvements were added to both gene cluster and peptide structure analysis. The main feature of the method is an implementation of a position-specific score matrix to store specificities of nonribosomal peptide synthetase modules, which has increased the alignment sensitivity in comparison with more strict approaches developed earlier. We tested the method on a manually curated nonribosomal peptide producers database and compared it with competing tools GARLIC and Nerpa. Finally, we showed the method's applicability on several external examples.

Deep Functional Profiling of Wild Animal Microbiomes Reveals Probiotic Bacillus pumilus Strains with a Common Biosynthetic Fingerprint.

The biodiversity of microorganisms is maintained by intricate nets of interactions between competing species. Impaired functionality of human microbiomes correlates with their reduced biodiversity originating from aseptic environmental conditions and antibiotic use. Microbiomes of wild animals are free of these selective pressures. Microbiota provides a protecting shield from invasion by pathogens in the wild, outcompeting their growth in specific ecological niches. We applied ultrahigh-throughput microfluidic technologies for functional profiling of microbiomes of wild animals, including the skin beetle, Siberian lynx, common raccoon dog, and East Siberian brown bear. Single-cell screening of the most efficient killers of the common human pathogen Staphylococcus aureus resulted in repeated isolation of Bacillus pumilus strains. While isolated strains had different phenotypes, all of them displayed a similar set of biosynthetic gene clusters (BGCs) encoding antibiotic amicoumacin, siderophore bacillibactin, and putative analogs of antimicrobials including bacilysin, surfactin, desferrioxamine, and class IId cyclical bacteriocin. Amicoumacin A (Ami) was identified as a major antibacterial metabolite of these strains mediating their antagonistic activity. Genome mining indicates that Ami BGCs with this architecture subdivide into three distinct families, characteristic of the B. pumilus, B. subtilis, and Paenibacillus species. While Ami itself displays mediocre activity against the majority of Gram-negative bacteria, isolated B. pumilus strains efficiently inhibit the growth of both Gram-positive S. aureus and Gram-negative E. coli in coculture. We believe that the expanded antagonistic activity spectrum of Ami-producing B. pumilus can be attributed to the metabolomic profile predetermined by their biosynthetic fingerprint. Ultrahigh-throughput isolation of natural probiotic strains from wild animal microbiomes, as well as their metabolic reprogramming, opens up a new avenue for pathogen control and microbiome remodeling in the food industry, agriculture, and healthcare.

UniqPy: A tool for estimation of short-chain fatty acids composition by gas-chromatography/mass-spectrometry with headspace extraction.

Short-chain fatty acids are metabolites widely presented in many natural sources, including human feces and blood. Estimation of their composition is a common procedure, usually performed using nuclear magnetic resonance or gas chromatography with a flame ionization detector. However, the commonly used methods often depend on specific sample preparation, such as filtration and homogenization. The gas-chromatography/mass-spectrometry (GC/MS) method with headspace extraction allows sample preparation to be kept to a minimum regardless of the physical state of the sample, which can be potentially useful in metabolomics research of complex natural samples such as blood or feces. In this work, we have demonstrated the applicability of Headspace GC-MS for estimating short chain fatty acid (SCFA) composition. The main problem here is the complex, non-linear dependence between the composition of the compounds in the source phase and the relative pressures in the vapor phase, which are directly measured by this method. We have implemented a thermodynamic model that performs the reverse transformation of relative abundances in the vapor phase to relative concentrations in the liquid phase, and have tested it on some synthetic SCFA mixtures. The developed method is available as a pip package called UniqPy and can be used to describe liquid-vapor equilibrium for any multicomponent system if a sufficient amount of training data is provided. The gas chromatography method with headspace extraction in conjunction with the UniqPy data transformation showed satisfactory quantification accuracy for propionic acid, butyric acid, isobutyric acid, and valeric acid (R-squared > 0.96). The applicability of the method was additionally demonstrated on a series of fecal samples.

The effects of Levilactobacillus brevis on the physiological parameters and gut microbiota composition of rats subjected to desynchronosis.

BACKGROUND: All living organisms have developed during evolution complex time-keeping biological clocks that allowed them to stay attuned to their environments. Circadian rhythms cycle on a near 24 h clock. These encompass a variety of changes in the body ranging from blood hormone levels to metabolism, to the gut microbiota composition and others. The gut microbiota, in return, influences the host stress response and the physiological changes associated with it, which makes it an important determinant of health. Lactobacilli are traditionally consumed for their prophylactic and therapeutic benefits against various diseases, namely, the inflammatory bowel syndrome, and even emerged recently as promising psychobiotics. However, the potential role of lactobacilli in the normalization of circadian rhythms has not been addressed. RESULTS: Two-month-old male rats were randomly divided into three groups and housed under three different light/dark cycles for three months: natural light, constant light and constant darkness. The strain Levilactobacillus brevis 47f was administered to rats at a dose of 0.5 ml per rat for one month and The rats were observed for the following two months. As a result, we identified the biomarkers associated with intake of L. brevis 47f. Changing the light regime for three months depleted the reserves of the main buffer in the cell-reduced glutathione. Intake of L. brevis 47f for 30 days restored cellular reserves of reduced glutathione and promoted redox balance. Our results indicate that the levels of urinary catecholamines correlated with light/dark cycles and were influenced by intake of L. brevis 47f. The gut microbiota of rats was also influenced by these factors. L. brevis 47f intake was associated with an increase in the relative abundance of Faecalibacterium and Roseburia and a decrease in the relative abundance of Prevotella and Bacteroides. CONCLUSIONS: The results of this study show that oral administration of L. brevis 47f, for one month, to rats housed under abnormal lightning conditions (constant light or constant darkness) normalized their physiological parameters and promoted the gut microbiome's balance.

Novel Klebsiella pneumoniae K23-Specific Bacteriophages From Different Families: Similarity of Depolymerases and Their Therapeutic Potential.

Antibiotic resistance is a major public health concern in many countries worldwide. The rapid spread of multidrug-resistant (MDR) bacteria is the main driving force for the development of novel non-antibiotic antimicrobials as a therapeutic alternative. Here, we isolated and characterized three virulent bacteriophages that specifically infect and lyse MDR Klebsiella pneumoniae with K23 capsule type. The phages belonged to the Autographiviridae (vB_KpnP_Dlv622) and Myoviridae (vB_KpnM_Seu621, KpS8) families and contained highly similar receptor-binding proteins (RBPs) with polysaccharide depolymerase enzymatic activity. Based on phylogenetic analysis, a similar pattern was also noted for five other groups of depolymerases, specific against capsule types K1, K30/K69, K57, K63, and KN2. The resulting recombinant depolymerases Dep622 (phage vB_KpnP_Dlv622) and DepS8 (phage KpS8) demonstrated narrow specificity against K. pneumoniae with capsule type K23 and were able to protect Galleria mellonella larvae in a model infection with a K. pneumoniae multidrug-resistant strain. These findings expand our knowledge of the diversity of phage depolymerases and provide further evidence that bacteriophages and phage polysaccharide depolymerases represent a promising tool for antimicrobial therapy.

Separation of Donor and Recipient Microbial Diversity Allows Determination of Taxonomic and Functional Features of Gut Microbiota Restructuring following Fecal Transplantation.

Fecal microbiota transplantation (FMT) is currently used in medicine to treat recurrent clostridial colitis and other intestinal diseases. However, neither the therapeutic mechanism of FMT nor the mechanism that allows the donor bacteria to colonize the intestine of the recipient has yet been clearly described. From a biological point of view, FMT can be considered a useful model for studying the ecology of host-associated microbial communities. FMT experiments can shed light on the relationship features between the host and its gut microbiota. This creates the need for experimentation with approaches to metagenomic data analysis which may be useful for the interpretation of observed biological phenomena. Here, the recipient intestine colonization analysis tool (RECAST) novel computational approach is presented, which is based on the metagenomic read sorting process per their origin in the recipient's post-FMT stool metagenome. Using the RECAST algorithm, taxonomic/functional annotation, and machine learning approaches, the metagenomes from three FMT studies, including healthy volunteers, patients with clostridial colitis, and patients with metabolic syndrome, were analyzed. Using our computational pipeline, the donor-derived and recipient-derived microbes which formed the recipient post-FMT stool metagenomes (successful microbes) were identified. Their presence is well explained by a higher relative abundance in donor/pre-FMT recipient metagenomes or other metagenomes from the human population. In addition, successful microbes are enriched with gene groups potentially related to antibiotic resistance, including antimicrobial peptides. Interestingly, the observed reorganization features are universal and independent of the disease. IMPORTANCE We assumed that the enrichment of successful gut microbes by lantibiotic/antibiotic resistance genes can be related to gut microbiota colonization resistance by third-party microbe phenomena and resistance to bacterium-derived or host-derived antimicrobial substances. According to this assumption, competition between the donor-derived and recipient-derived microbes as well as host immunity may play a key role in the FMT-related colonization and redistribution of recipient gut microbiota structure.

Drift of the Subgingival Periodontal Microbiome during Chronic Periodontitis in Type 2 Diabetes Mellitus Patients.

Since periodontitis and type 2 diabetes mellitus are complex diseases, a thorough understanding of their pathogenesis requires knowing the relationship of these pathologies with other disorders and environmental factors. In this study, the representability of the subgingival periodontal microbiome of 46 subjects was studied by 16S rRNA gene sequencing and shotgun sequencing of pooled samples. We examined 15 patients with chronic periodontitis (CP), 15 patients with chronic periodontitis associated with type 2 diabetes mellitus (CPT2DM), and 16 healthy subjects (Control). The severity of generalized chronic periodontitis in both periodontitis groups of patients (CP and CPT2DM) was moderate (stage II). The male to female ratios were approximately equal in each group (22 males and 24 females); the average age of the subjects was 53.9 ± 7.3 and 54.3 ± 7.2 years, respectively. The presence of overweight patients (Body Mass Index (BMI) 30-34.9 kg/m2) and patients with class 1-2 obesity (BMI 35-45.9 kg/m2) was significantly higher in the CPT2DM group than in patients having only chronic periodontitis or in the Control group. However, there was no statistically significant difference in all clinical indices between the CP and CPT2DM groups. An analysis of the metagenomic data revealed that the alpha diversity in the CPT2DM group was increased compared to that in the CP and Control groups. The microbiome biomarkers associated with experimental groups were evaluated. In both groups of patients with periodontitis, the relative abundance of Porphyromonadaceae was increased compared to that in the Control group. The CPT2DM group was characterized by a lower relative abundance of Streptococcaceae/Pasteurellaceae and a higher abundance of Leptotrichiaceae compared to those in the CP and Control groups. Furthermore, the CP and CPT2DM groups differed in terms of the relative abundance of Veillonellaceae (which was decreased in the CPT2DM group compared to CP) and Neisseriaceae (which was increased in the CPT2DM group compared to CP). In addition, differences in bacterial content were identified by a combination of shotgun sequencing of pooled samples and genome-resolved metagenomics. The results indicate that there are subgingival microbiome-specific features in patients with chronic periodontitis associated with type 2 diabetes mellitus.

Gene Networks Underlying the Resistance of Bifidobacterium longum to Inflammatory Factors.

As permanent residents of the normal gut microbiota, bifidobacteria have evolved to adapt to the host's immune response whose priority is to eliminate pathogenic agents. The mechanisms that ensure the survival of commensals during inflammation and maintain the stability of the core component of the normal gut microbiota in such conditions remain poorly understood. We propose a new in vitro approach to study the mechanisms of resistance to immune response factors based on high-throughput sequencing followed by transcriptome analysis. This approach allowed us to detect differentially expressed genes associated with inflammation. In this study, we demonstrated that the presence of the pro-inflammatory cytokines IL-6 and TNFα to the growth medium of the B. longum subsp. longum GT15 strain changes the latter's growth rate insignificantly while affecting the expression of certain genes. We identified these genes and performed a COG and a KEGG pathway enrichment analysis. Using phylogenetic profiling we predicted the operons of genes whose expression was triggered by the cytokines TNFα and IL-6 in vitro. By mapping the transcription start points, we experimentally validated the predicted operons. Thus, in this study, we predicted the genes involved in a putative signaling pathway underlying the mechanisms of resistance to inflammatory factors in bifidobacteria. Since bifidobacteria are a major component of the human intestinal microbiota exhibiting pronounced anti-inflammatory properties, this study is of great practical and scientific relevance.

Identification of Clinically Significant Prostate Cancer by Combined PCA3 and AMACR mRNA Detection in Urine Samples.

PURPOSE: Preclinical evaluation of PCA3 and AMACR transcript simultaneous detection in urine to diagnose clinical significant prostate cancer (prostate cancer with Gleason score ≥7) in a Russian cohort. PATIENTS AND METHODS: We analyzed urine samples of patients with a total serum PSA ≥2 ng/mL: 31 men with prostate cancer scheduled for radical prostatectomy, 128 men scheduled for first diagnostic biopsy (prebiopsy cohort). PCA3, AMACR, PSA and GPI transcripts were detected by multiplex reverse transcription quantitative polymerase chain reaction, and the results were used for scores for calculation and statistical analysis. RESULTS: There was no significant difference between clinically significant and nonsignificant prostate cancer PCA3 scores. However, there was a significant difference in the AMACR score (patients scheduled for radical prostatectomy p=0.0088, prebiopsy cohort p=0.029). We estimated AUCs, optimal cutoffs, sensitivities and specificities for PCa and csPCa detection in the prebiopsy cohort by tPSA, PCA3 score, PCPT Risk Calculator and classification models based on tPSA, PCA3 score and AMACR score. In the clinically significant prostate cancer ROC analysis, the PCA3 score AUC was 0.632 (95%CI: 0.511-0.752), the AMACR score AUC was 0.711 (95%CI: 0.617-0.806) and AUC of classification model based on the PCA3 score, the AMACR score and total PSA was 0.72 (95%CI: 0.58-0.83). In addition, the correlation of the AMACR score with the ratio of total RNA and RNA of prostate cells in urine was shown (tau=0.347, p=6.542e-09). Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. CONCLUSION: The AMACR score is a good predictor of clinically significant prostate cancer. Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Evaluation of the AMACR score and classification models based on it for clinically significant prostate cancer detection with larger samples and a follow-up analysis is promising.

Phigaro: high-throughput prophage sequence annotation.

SUMMARY: Phigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated 'prophage genome maps' and marks possible transposon insertion spots inside prophages. It is applicable for mining prophage regions from large metagenomic datasets. AVAILABILITY AND IMPLEMENTATION: Source code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Deep Functional Profiling Facilitates the Evaluation of the Antibacterial Potential of the Antibiotic Amicoumacin.

The global spread of antibiotic resistance is forcing the scientific community to find new molecular strategies to counteract it. Deep functional profiling of microbiomes provides an alternative source for the discovery of novel antibiotic producers and probiotics. Recently, we implemented this ultrahigh-throughput screening approach for the isolation of Bacillus pumilus strains efficiently producing the ribosome-targeting antibiotic amicoumacin A (Ami). Proteomics and metabolomics revealed essential insight into the activation of Ami biosynthesis. Here, we applied omics to boost Ami biosynthesis, providing the optimized cultivation conditions for high-scale production of Ami. Ami displayed a pronounced activity against Lactobacillales and Staphylococcaceae, including methicillin-resistant Staphylococcus aureus (MRSA) strains, which was determined using both classical and massive single-cell microfluidic assays. However, the practical application of Ami is limited by its high cytotoxicity and particularly low stability. The former is associated with its self-lactonization, serving as an improvised intermediate state of Ami hydrolysis. This intramolecular reaction decreases Ami half-life at physiological conditions to less than 2 h, which is unprecedented for a terminal amide. While we speculate that the instability of Ami is essential for Bacillus ecology, we believe that its stable analogs represent attractive lead compounds both for antibiotic discovery and for anticancer drug development.

Shifts in the Human Gut Microbiota Structure Caused by Quadruple Helicobacter pylori Eradication Therapy.

The human gut microbiome plays an important role both in health and disease. Use of antibiotics can alter gut microbiota composition, which can lead to various deleterious events. Here we report a whole genome sequencing metagenomic/genomic study of the intestinal microbiota changes caused by Helicobacter pylori (HP) eradication therapy. Using approaches for metagenomic data analysis we revealed a statistically significant decrease in alpha-diversity and relative abundance of Bifidobacterium adolescentis due to HP eradication therapy, while the relative abundance of Enterococcus faecium increased. We have detected changes in general metagenome resistome profiles as well: after HP eradication therapy, the ermB, CFX group, and tetQ genes were overrepresented, while tetO and tetW genes were underrepresented. We have confirmed these results with genome-resolved metagenomic approaches. MAG (metagenome-assembled genomes) abundance profiles have changed dramatically after HP eradication therapy. Focusing on ermB gene conferring resistance to macrolides, which were included in the HP eradication therapy scheme, we have shown a connection between antibiotic resistance genes (ARGs) and some overrepresented MAGs. Moreover, some E. faecium strains isolated from stool samples obtained after HP eradication have manifested greater antibiotic resistance in vitro in comparison to other isolates, as well as the higher number of ARGs conferring resistance to macrolides and tetracyclines.

Long-term impact of fecal transplantation in healthy volunteers.

BACKGROUND: Fecal microbiota transplantation (FMT) has been recently approved by FDA for the treatment of refractory recurrent clostridial colitis (rCDI). Success of FTM in treatment of rCDI led to a number of studies investigating the effectiveness of its application in the other gastrointestinal diseases. However, in the majority of studies the effects of FMT were evaluated on the patients with initially altered microbiota. The aim of our study was to estimate effects of FMT on the gut microbiota composition in healthy volunteers and to monitor its long-term outcomes. RESULTS: We have performed a combined analysis of three healthy volunteers before and after capsule FMT by evaluating their general condition, adverse clinical effects, changes of basic laboratory parameters, and several immune markers. Intestinal microbiota samples were evaluated by 16S rRNA gene and shotgun sequencing. The data analysis demonstrated profound shift towards the donor microbiota taxonomic composition in all volunteers. Following FMT, all the volunteers exhibited gut colonization with donor gut bacteria and persistence of this effect for almost ∼1 year of observation. Transient changes of immune parameters were consistent with suppression of T-cell cytotoxicity. FMT was well tolerated with mild gastrointestinal adverse events, however, one volunteer developed a systemic inflammatory response syndrome. CONCLUSIONS: The FMT leads to significant long-term changes of the gut microbiota in healthy volunteers with the shift towards donor microbiota composition and represents a relatively safe procedure to the recipients without long-term adverse events.

Ultrahigh-throughput functional profiling of microbiota communities.

Microbiome spectra serve as critical clues to elucidate the evolutionary biology pathways, potential pathologies, and even behavioral patterns of the host organisms. Furthermore, exotic sources of microbiota represent an unexplored niche to discover microbial secondary metabolites. However, establishing the bacterial functionality is complicated by an intricate web of interactions inside the microbiome. Here we apply an ultrahigh-throughput (uHT) microfluidic droplet platform for activity profiling of the entire oral microbial community of the Siberian bear to isolate Bacillus strains demonstrating antimicrobial activity against Staphylococcus aureus Genome mining allowed us to identify antibiotic amicoumacin A (Ami) as responsible for inhibiting the growth of S. aureus Proteomics and metabolomics revealed a unique mechanism of Bacillus self-resistance to Ami, based on a subtle equilibrium of its deactivation and activation by kinase AmiN and phosphatase AmiO, respectively. We developed uHT quantitative single-cell analysis to estimate antibiotic efficacy toward different microbiomes and used it to determine the activity spectra of Ami toward human and Siberian bear microbiota. Thus, uHT microfluidic droplet platform activity profiling is a powerful tool for discovering antibiotics and quantifying external influences on a microbiome.

Draft genomes of Enterococcus faecium strains isolated from human feces before and after eradication therapy against Helicobacter pylori.

The abundance of Enterococci in the human intestinal microbiota environment is usually < 0.1% of the total bacterial fraction. The multiple resistance to antibiotics of the opportunistic Enterococcus spp. is alarming for the world medical community because of their high prevalence among clinically significant strains of microorganisms. Enterococci are able to collect different mobile genetic elements and transmit resistance to antibiotics to wide range of Gram-positive and Gram-negative species of microorganisms, including the transmission of vancomycin resistance to methicillin-resistant strains of Staphylococcus aureus. The number of infections caused by antibiotics resistant strains of Enterococcus spp. is increasing. Here we present a draft genomes of Enterococcus faecium strains. These strains were isolated from human feces before and after (1 month) Helicobacter pylori eradication therapy. The samples were subject to whole-genome sequencing using Illumina HiSeq. 2500 platform. The data is available at NCBI https://www.ncbi.nlm.nih.gov/bioproject/PRJNA412824.