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).

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.

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.

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.

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.

Microfluidic droplet platform for ultrahigh-throughput single-cell screening of biodiversity.

Ultrahigh-throughput screening (uHTS) techniques can identify unique functionality from millions of variants. To mimic the natural selection mechanisms that occur by compartmentalization in vivo, we developed a technique based on single-cell encapsulation in droplets of a monodisperse microfluidic double water-in-oil-in-water emulsion (MDE). Biocompatible MDE enables in-droplet cultivation of different living species. The combination of droplet-generating machinery with FACS followed by next-generation sequencing and liquid chromatography-mass spectrometry analysis of the secretomes of encapsulated organisms yielded detailed genotype/phenotype descriptions. This platform was probed with uHTS for biocatalysts anchored to yeast with enrichment close to the theoretically calculated limit and cell-to-cell interactions. MDE-FACS allowed the identification of human butyrylcholinesterase mutants that undergo self-reactivation after inhibition by the organophosphorus agent paraoxon. The versatility of the platform allowed the identification of bacteria, including slow-growing oral microbiota species that suppress the growth of a common pathogen, Staphylococcus aureus, and predicted which genera were associated with inhibitory activity.

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.

Genome analysis of E. coli isolated from Crohn's disease patients.

BACKGROUND: Escherichia coli (E. coli) has been increasingly implicated in the pathogenesis of Crohn's disease (CD). The phylogeny of E. coli isolated from Crohn's disease patients (CDEC) was controversial, and while genotyping results suggested heterogeneity, the sequenced strains of E. coli from CD patients were closely related. RESULTS: We performed the shotgun genome sequencing of 28 E. coli isolates from ten CD patients and compared genomes from these isolates with already published genomes of CD strains and other pathogenic and non-pathogenic strains. CDEC was shown to belong to A, B1, B2 and D phylogenetic groups. The plasmid and several operons from the reference CD-associated E. coli strain LF82 were demonstrated to be more often present in CDEC genomes belonging to different phylogenetic groups than in genomes of commensal strains. The operons include carbon-source induced invasion GimA island, prophage I, iron uptake operons I and II, capsular assembly pathogenetic island IV and propanediol and galactitol utilization operons. CONCLUSIONS: Our findings suggest that CDEC are phylogenetically diverse. However, some strains isolated from independent sources possess highly similar chromosome or plasmids. Though no CD-specific genes or functional domains were present in all CD-associated strains, some genes and operons are more often found in the genomes of CDEC than in commensal E. coli. They are principally linked to gut colonization and utilization of propanediol and other sugar alcohols.

State of the Art of Chromosome 18-Centric HPP in 2016: Transcriptome and Proteome Profiling of Liver Tissue and HepG2 Cells.

A gene-centric approach was applied for a large-scale study of expression products of a single chromosome. Transcriptome profiling of liver tissue and HepG2 cell line was independently performed using two RNA-Seq platforms (SOLiD and Illumina) and also by Droplet Digital PCR (ddPCR) and quantitative RT-PCR. Proteome profiling was performed using shotgun LC-MS/MS as well as selected reaction monitoring with stable isotope-labeled standards (SRM/SIS) for liver tissue and HepG2 cells. On the basis of SRM/SIS measurements, protein copy numbers were estimated for the Chromosome 18 (Chr 18) encoded proteins in the selected types of biological material. These values were compared with expression levels of corresponding mRNA. As a result, we obtained information about 158 and 142 transcripts for HepG2 cell line and liver tissue, respectively. SRM/SIS measurements and shotgun LC-MS/MS allowed us to detect 91 Chr 18-encoded proteins in total, while an intersection between the HepG2 cell line and liver tissue proteomes was ∼66%. In total, there were 16 proteins specifically observed in HepG2 cell line, while 15 proteins were found solely in the liver tissue. Comparison between proteome and transcriptome revealed a poor correlation (R2 ≈ 0.1) between corresponding mRNA and protein expression levels. The SRM and shotgun data sets (obtained during 2015-2016) are available in PASSEL (PASS00697) and ProteomeExchange/PRIDE (PXD004407). All measurements were also uploaded into the in-house Chr 18 Knowledgebase at http://kb18.ru/protein/matrix/416126 .

Chromosome 18 transcriptoproteome of liver tissue and HepG2 cells and targeted proteome mapping in depleted plasma: update 2013.

We report the results obtained in 2012-2013 by the Russian Consortium for the Chromosome-centric Human Proteome Project (C-HPP). The main scope of this work was the transcriptome profiling of genes on human chromosome 18 (Chr 18), as well as their encoded proteome, from three types of biomaterials: liver tissue, the hepatocellular carcinoma-derived cell line HepG2, and blood plasma. The transcriptome profiling for liver tissue was independently performed using two RNaseq platforms (SOLiD and Illumina) and also by droplet digital PCR (ddPCR) and quantitative RT-PCR. The proteome profiling of Chr 18 was accomplished by quantitatively measuring protein copy numbers in the three types of biomaterial (the lowest protein concentration measured was 10(-13) M) using selected reaction monitoring (SRM). In total, protein copy numbers were estimated for 228 master proteins, including quantitative data on 164 proteins in plasma, 171 in the HepG2 cell line, and 186 in liver tissue. Most proteins were present in plasma at 10(8) copies/µL, while the median abundance was 10(4) and 10(5) protein copies per cell in HepG2 cells and liver tissue, respectively. In summary, for liver tissue and HepG2 cells a "transcriptoproteome" was produced that reflects the relationship between transcript and protein copy numbers of the genes on Chr 18. The quantitative data acquired by RNaseq, PCR, and SRM were uploaded into the "Update_2013" data set of our knowledgebase (www.kb18.ru) and investigated for linear correlations.

RNA-Seq gene expression profiling of HepG2 cells: the influence of experimental factors and comparison with liver tissue.

BACKGROUND: Human hepatoma HepG2 cells are used as an in vitro model of the human liver. High-throughput transcriptomic sequencing is an advanced approach for assessing the functional state of a tissue or cell type. However, the influence of experimental factors, such as the sample preparation method and inter-laboratory variation, on the transcriptomic profile has not been evaluated. RESULTS: The whole-transcriptome sequencing of HepG2 cells was performed using the SOLiD platform and validated using droplet digital PCR. The gene expression profile was compared to the results obtained with the same sequencing method in another laboratory and using another sample preparation method. We also compared the transcriptomic profile HepG2 cells with that of liver tissue. Comparison of the gene expression profiles between the HepG2 cell line and liver tissue revealed the highest variation, followed by HepG2 cells submitted to two different sample preparation protocols. The lowest variation was observed between HepG2 cells prepared by two different laboratories using the same protocol. The enrichment analysis of the genes that were differentially expressed between HepG2 cells and liver tissue mainly revealed the cancer-associated gene signature of HepG2 cells and the activation of the response to chemical stimuli in the liver tissue. The HepG2 transcriptome obtained with the SOLiD platform was highly correlated with the published transcriptome obtained with the Illumina and Helicos platforms, with moderate correspondence to microarrays. CONCLUSIONS: In the present study, we assessed the influence of experimental factors on the HepG2 transcriptome and identified differences in gene expression between the HepG2 cell line and liver cells. These findings will facilitate robust experimental design in the fields of pharmacology and toxicology. Our results were supported by a comparative analysis with previous HepG2 gene expression studies.

Genome-wide Mycobacterium tuberculosis variation (GMTV) database: a new tool for integrating sequence variations and epidemiology.

BACKGROUND: Tuberculosis (TB) poses a worldwide threat due to advancing multidrug-resistant strains and deadly co-infections with Human immunodeficiency virus. Today large amounts of Mycobacterium tuberculosis whole genome sequencing data are being assessed broadly and yet there exists no comprehensive online resource that connects M. tuberculosis genome variants with geographic origin, with drug resistance or with clinical outcome. DESCRIPTION: Here we describe a broadly inclusive unifying Genome-wide Mycobacterium tuberculosis Variation (GMTV) database, (http://mtb.dobzhanskycenter.org) that catalogues genome variations of M. tuberculosis strains collected across Russia. GMTV contains a broad spectrum of data derived from different sources and related to M. tuberculosis molecular biology, epidemiology, TB clinical outcome, year and place of isolation, drug resistance profiles and displays the variants across the genome using a dedicated genome browser. GMTV database, which includes 1084 genomes and over 69,000 SNP or Indel variants, can be queried about M. tuberculosis genome variation and putative associations with drug resistance, geographical origin, and clinical stages and outcomes. CONCLUSIONS: Implementation of GMTV tracks the pattern of changes of M. tuberculosis strains in different geographical areas, facilitates disease gene discoveries associated with drug resistance or different clinical sequelae, and automates comparative genomic analyses among M. tuberculosis strains.

Long-term dissemination of CTX-M-5-producing hypermutable Salmonella enterica serovar typhimurium sequence type 328 strains in Russia, Belarus, and Kazakhstan.

In this paper, we present evidence of long-term circulation of cefotaxime-resistant clonally related Salmonella enterica serovar Typhimurium strains over a broad geographic area. The genetic relatedness of 88 isolates collected from multiple outbreaks and sporadic cases of nosocomial salmonellosis in various parts of Russia, Belarus, and Kazakhstan from 1996 to 2009 was established by multilocus tandem-repeat analysis (MLVA) and multilocus sequence typing (MLST). The isolates belong to sequence type 328 (ST328) and produce CTX-M-5 ß-lactamase, whose gene is carried by highly related non-self-conjugative but mobilizable plasmids. Resistance to nalidixic acid and low-level resistance to ciprofloxacin is present in 37 (42%) of the isolates and in all cases is determined by various single point mutations in the gyrA gene quinolone resistance-determining region (QRDR). Isolates of the described clonal group exhibit a hypermutable phenotype that probably facilitates independent acquisition of quinolone resistance mutations.

Microbial Signatures in COVID-19: Distinguishing Mild and Severe Disease via Gut Microbiota.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has significantly impacted global healthcare, underscoring the importance of exploring the virus's effects on infected individuals beyond treatments and vaccines. Notably, recent findings suggest that SARS-CoV-2 can infect the gut, thereby altering the gut microbiota. This study aimed to analyze the gut microbiota composition differences between COVID-19 patients experiencing mild and severe symptoms. We conducted 16S rRNA metagenomic sequencing on fecal samples from 49 mild and 43 severe COVID-19 cases upon hospital admission. Our analysis identified a differential abundance of specific bacterial species associated with the severity of the disease. Severely affected patients showed an association with Enterococcus faecium, Akkermansia muciniphila, and others, while milder cases were linked to Faecalibacterium prausnitzii, Alistipes putredinis, Blautia faecis, and additional species. Furthermore, a network analysis using SPIEC-EASI indicated keystone taxa and highlighted structural differences in bacterial connectivity, with a notable disruption in the severe group. Our study highlights the diverse impacts of SARS-CoV-2 on the gut microbiome among both mild and severe COVID-19 patients, showcasing a spectrum of microbial responses to the virus. Importantly, these findings align, to some extent, with observations from other studies on COVID-19 gut microbiomes, despite variations in methodologies. The findings from this study, based on retrospective data, establish a foundation for future prospective research to confirm the role of the gut microbiome as a predictive biomarker for the severity of COVID-19.

Chromosome 18 transcriptome profiling and targeted proteome mapping in depleted plasma, liver tissue and HepG2 cells.

The final goal of the Russian part of the Chromosome-centric Human Proteome Project (C-HPP) was established as the analysis of the chromosome 18 (Chr 18) protein complement in plasma, liver tissue and HepG2 cells with the sensitivity of 10(-18) M. Using SRM, we have recently targeted 277 Chr 18 proteins in plasma, liver, and HepG2 cells. On the basis of the results of the survey, the SRM assays were drafted for 250 proteins: 41 proteins were found only in the liver tissue, 82 proteins were specifically detected in depleted plasma, and 127 proteins were mapped in both samples. The targeted analysis of HepG2 cells was carried out for 49 proteins; 41 of them were successfully registered using ordinary SRM and 5 additional proteins were registered using a combination of irreversible binding of proteins on CN-Br Sepharose 4B with SRM. Transcriptome profiling of HepG2 cells performed by RNAseq and RT-PCR has shown a significant correlation (r = 0.78) for 42 gene transcripts. A pilot affinity-based interactome analysis was performed for cytochrome b5 using analytical and preparative optical biosensor fishing followed by MS analysis of the fished proteins. All of the data on the proteome complement of the Chr 18 have been integrated into our gene-centric knowledgebase ( www.kb18.ru ).

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.

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.

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.