Microbial Genomes Research Articles

Evaluation of the gut microbiome associated with COVID-19

IntroductionIn 2019, a new virus from the coronavirus family called SARS-CoV-2, infected populations throughout the world. Coronavirus disease 2019 (COVID-19), an illness induced by this virus, attacks vital organs in the body, such as the respiratory system and the gastrointestinal tract. Recent studies have confirmed changes in the gut microbiome caused by the COVID-19 disease. We examined the alteration of the gut microbiome in COVID-19 patients compared to healthy individuals. Materials and methodsin this study, the 16s metagenomics dataset, publicly available in the Sequence Read Archive (SRA) database, was used for analysis (accession number PRJNA636824). The analysis processes were performed using the CLC Microbial Genomics Module 20.1.1 (Qiagen). At first, the sequence reads of samples were trimmed and classified into operational taxonomic units (OTUs) with 97% similarity and then assigned to the Greengenes reference database (v138). Differential abundance analysis was used to determine statistically significant differences in OTUs between COVID-19 and healthy groups. Next, biodiversity analyses including the alpha diversity (intragroup diversity) and beta diversity (intergroup diversity) using defined indexes were estimated. Then, the co-occurrence network at the species level was constructed using the Pearson correlation coefficient calculation between pairs of OTUs in R software and visualized using Cytoscape software. Ultimately, the hub OTUs at the species level were identified using the cytoHubba plugin of Cytoscape based on Maximal Clique Centrality (MCC) algorithm. ResultsThe results of the metagenomic analysis revealed that the intestinal microbiome in healthy individuals has a higher biodiversity compared to COVID-19 patients. Indeed, healthy people also have a higher percentage of beneficial bacteria such as bifidobacteria adolescentis compared to COVID-19 patients; in contrast, COVID-19 patients have higher levels of opportunistic and pathogenic bacteria such as Streptococcus anginosus than healthy people. Also, by constructing a co-occurrence network at the species level, Bifidobacterium longum in the healthy group and Veillonella parvulain the COVID-19 group were found as hub species. ConclusionThe results of this study shed light on the relationship between the gut microbiome and COVID-19. These results could be helpful for understanding the pathogenesis, clinical features, and treatment of COVID-9.

From Genomics to Metagenomics in the Era of Recent Sequencing Technologies.

Metagenomics, also known as environmental genomics, is the study of the genomic content of a sample of organisms obtained from a common habitat. Metagenomics and other "omics" disciplines have captured the attention of researchers for several decades. The effect of microbes in our body is a relevant concern for health studies. Through sampling the sequences of microbial genomes within a certain environment, metagenomics allows study of the functional metabolic capacity of a community as well as its structure based upon distribution and richness of species. Exponentially increasing number of microbiome literatures illustrate the importance of sequencing techniques which haveallowed the expansion of microbial research into areas, including the human gut, antibiotics, enzymes, and more. This chapter illustrates how metagenomics field has evolved with the progress of sequencing technologies.Further, from this chapter, researchers will be able to learn about all current options for sequencing techniques and comparison of their cost and read statistics, which will be helpful for planning their own studies.

KMCP: accurate metagenomic profiling of both prokaryotic and viral populations by pseudo-mapping.

The growing number of microbial reference genomes enables the improvement of metagenomic profiling accuracy but also imposes greater requirements on the indexing efficiency, database size and runtime of taxonomic profilers. Additionally, most profilers focus mainly on bacterial, archaeal and fungal populations, while less attention is paid to viral communities. We present KMCP (K-mer-based Metagenomic Classification and Profiling), a novel k-mer-based metagenomic profiling tool that utilizes genome coverage information by splitting the reference genomes into chunks and stores k-mers in a modified and optimized Compact Bit-Sliced Signature Index for fast alignment-free sequence searching. KMCP combines k-mer similarity and genome coverage information to reduce the false positive rate of k-mer-based taxonomic classification and profiling methods. Benchmarking results based on simulated and real data demonstrate that KMCP, despite a longer running time than all other methods, not only allows the accurate taxonomic profiling of prokaryotic and viral populations but also provides more confident pathogen detection in clinical samples of low depth. The software is open-source under the MIT license and available at https://github.com/shenwei356/kmcp. Supplementary data are available at Bioinformatics online.

The GEN-ERA toolbox: unified and reproducible workflows for research in microbial genomics.

Microbial culture collections play a key role in taxonomy by studying the diversity of their strains and providing well-characterized biological material to the scientific community for fundamental and applied research. These microbial resource centers thus need to implement new standards in species delineation, including whole-genome sequencing and phylogenomics. In this context, the genomic needs of the Belgian Coordinated Collections of Microorganisms were studied, resulting in the GEN-ERA toolbox. The latter is a unified cluster of bioinformatic workflows dedicated to both bacteria and small eukaryotes (e.g., yeasts). This public toolbox allows researchers without a specific training in bioinformatics to perform robust phylogenomic analyses. Hence, it facilitates all steps from genome downloading and quality assessment, including genomic contamination estimation, to tree reconstruction. It also offers workflows for average nucleotide identity comparisons and metabolic modeling. Nextflow workflows are launched by a single command and are available on the GEN-ERA GitHub repository (https://github.com/Lcornet/GENERA). All the workflows are based on Singularity containers to increase reproducibility. The toolbox was developed for a diversity of microorganisms, including bacteria and fungi. It was further tested on an empirical dataset of 18 (meta)genomes of early branching Cyanobacteria, providing the most up-to-date phylogenomic analysis of the Gloeobacterales order, the first group to diverge in the evolutionary tree of Cyanobacteria. The GEN-ERA toolbox can be used to infer completely reproducible comparative genomic and metabolic analyses on prokaryotes and small eukaryotes. Although designed for routine bioinformatics of culture collections, it can also be used by all researchers interested in microbial taxonomy, as exemplified by our case study on Gloeobacterales.

Miniature CRISPR-Cas12f1-Mediated Single-Nucleotide Microbial Genome Editing Using 3'-Truncated sgRNA.

The CRISPR-Cas system has been used as a convenient tool for genome editing because the nuclease that cuts the target DNA and the guide RNA that recognizes the target are separated into modules. Cas12f1, which has a smaller size than that of other Cas nucleases, is easily loaded into vectors and is emerging as a new genome editing tool. In this study, AsCas12f1 was used to negatively select only Escherichia coli cells obtained by oligonucleotide-directed genome editing. Although double-, triple-, and quadruple-base substitutions were accurately and efficiently performed in the genome, the performance of single-base editing was poor. To resolve this limitation, we serially truncated the 3'-end of sgRNAs and determined the maximal truncation required to maintain the target DNA cleavage activity of Cas12f1. Negative selection of single-nucleotide-edited cells was efficiently performed with the maximally 3'-truncated sgRNA-Cas12f1 complex in vivo. Moreover, Sanger sequencing showed that the accuracy of single-nucleotide substitution, insertion, and deletion in the microbial genome was improved. These results demonstrated that a truncated sgRNA approach could be widely used for accurate CRISPR-mediated genome editing.

A Customized Monkeypox Virus Genomic Database (MPXV DB v1.0) for Rapid Sequence Analysis and Phylogenomic Discoveries in CLC Microbial Genomics.

Monkeypox has been a neglected, zoonotic tropical disease for over 50 years. Since the 2022 global outbreak, hundreds of human clinical samples have been subjected to next-generation sequencing (NGS) worldwide with raw data deposited in public repositories. However, sequence analysis for in-depth investigation of viral evolution remains hindered by the lack of a curated, whole genome Monkeypox virus (MPXV) database (DB) and efficient bioinformatics pipelines. To address this, we developed a customized MPXV DB for integration with "ready-to-use" workflows in the CLC Microbial Genomics Module for whole genomic and metagenomic analysis. After database construction (218 MPXV genomes), whole genome alignment, pairwise comparison, and evolutionary analysis of all genomes were analyzed to autogenerate tabular outputs and visual displays (collective runtime: 16 min). The clinical utility of the MPXV DB was demonstrated by using a Chimpanzee fecal, hybrid-capture NGS dataset (publicly available) for metagenomic, phylogenomic, and viral/host integration analysis. The clinically relevant MPXV DB embedded in CLC workflows proved to be a rapid method of sequence analysis useful for phylogenomic exploration and a wide range of applications in translational science.

Reference-based read clustering improves the de novo genome assembly of microbial strains

Constructing accurate microbial genome assemblies is necessary to understand genetic diversity in microbial genomes and its functional consequences. However, it still remains as a challenging task especially when only short-read sequencing technologies are used. Here, we present a new read-clustering algorithm, called RBRC, for improving de novo microbial genome assembly, by accurately estimating read proximity using multiple reference genomes. The performance of RBRC was confirmed by simulation-based evaluation in terms of assembly contiguity and the number of misassemblies, and was successfully applied to existing fungal and bacterial genomes by improving the quality of the assemblies without using additional sequencing data. RBRC is a very useful read-clustering algorithm that can be used (i) for generating high-quality genome assemblies of microbial strains when genome assemblies of related strains are available, and (ii) for upgrading existing microbial genome assemblies when the generation of additional sequencing data, such as long reads, is difficult.

Metabolomics and Genomics Enable the Discovery of a New Class of Nonribosomal Peptidic Metallophores from a Marine Micromonospora.

Although microbial genomes harbor an abundance of biosynthetic gene clusters, there remain substantial technological gaps that impair the direct correlation of newly discovered gene clusters and their corresponding secondary metabolite products. As an example of one approach designed to minimize or bridge such gaps, we employed hierarchical clustering analysis and principal component analysis (hcapca, whose sole input is MS data) to prioritize 109 marine Micromonospora strains and ultimately identify novel strain WMMB482 as a candidate for in-depth "metabologenomics" analysis following its prioritization. Highlighting the power of current MS-based technologies, not only did hcapca enable the discovery of one new, nonribosomal peptide bearing an incredible diversity of unique functional groups, but metabolomics for WMMB482 unveiled 16 additional congeners via the application of Global Natural Product Social molecular networking (GNPS), herein named ecteinamines A-Q (1-17). The ecteinamines possess an unprecedented skeleton housing a host of uncommon functionalities including a menaquinone pathway-derived 2-naphthoate moiety, 4-methyloxazoline, the first example of a naturally occurring Ψ[CH2NH] "reduced amide", a methylsulfinyl moiety, and a d-cysteinyl residue that appears to derive from a unique noncanonical epimerase domain. Extensive in silico analysis of the ecteinamine (ect) biosynthetic gene cluster and stable isotope-feeding experiments helped illuminate the novel enzymology driving ecteinamine assembly as well the role of cluster collaborations or "duets" in producing such structurally complex agents. Finally, ecteinamines were found to bind nickel, cobalt, zinc, and copper, suggesting a possible biological role as broad-spectrum metallophores.

Analysis of Ancient Microbial DNA.

The development of next-generation sequencing has led to a breakthrough in the analysis of ancient genomes, and the subsequent genomic analyses of ancient human skeletal remains have revolutionized our understanding of human evolution. This research led to the discovery of a new hominin lineage, and demonstrated multiple admixture events with more distantly related archaic human populations such as Neandertals and Denisovans over the last 100,000years. Moreover, it has also yielded novel insights into the evolution of ancient pathogens. The analysis of ancient microbial genomes enables the study of their recent evolution, presently covering the last several millennia. These spectacular results have been obtained despite the degradation of DNA that takes place after the death of the host and increases with time. This cumulative degradation results in very short ancient DNA molecules, low in quantity, and highly prone to contamination by modern DNA molecules, especially from human and animal DNA present in reagents used in downstream biomolecular analyses. Finally, the minute amounts of ancient molecules are further diluted in environmental DNA from the soil microorganisms that colonize bones and teeth. Thus, ancient skeletal remains can share DNA profiles with environmental samples, and the identification of ancient microbial genomes among the more recent, presently poorly characterized, environmental microbiome is particularly challenging. Here, we describe the methods developed and/or in use in our laboratory to produce reliable and reproducible paleogenomic results from ancient skeletal remains that can be used to identify the presence of ancient microbiota.

Analyzing Prokaryotic Transcriptomics in the Light of Genome Data with the MicroScope Platform.

Large-scale genome sequencing and the increasingly massive use of high-throughput approaches produce a vast amount of new information that completely transforms our understanding of thousands of microbial species occurring in our environment. However, despite the development of powerful bioinformatics approaches, full interpretation of the content of these genomes remains a difficult task. To address this challenge, the MicroScope platform has been developed. It is an integrated Web platform for management, annotation, comparative analysis, and visualization of microbial genomes ( https://mage.genoscope.cns.fr/microscope ). Launched in 2005, the platform has been under continuous development and provides analyzes for complete and ongoing genome projects together with metabolic network reconstruction and transcriptomic experiments allowing users to improve the understanding of gene functions. MicroScope platform is widely used by microbiologists from academia and industry all around the world for collaborative studies and expert annotation. It enables collaborative work in a rich comparative genomic context and improves community-based curation efforts. Here, we describe the protocol to follow for the integration and analysis of transcriptomics data in the Microscope platform. The chapter reviews each key step from the experimental design to the analysis and interpretation of the experiment data and results. The integration of transcriptomics data gives a dynamic view of the genome by allowing the users to improve the understanding of gene functions by interpreting them in the light of regulatory cell processes. Moreover, they can also contribute to the refinement of genome annotation through the discovery of new genes and help to fill metabolic gaps.

Improved Assembly of Metagenome-Assembled Genomes and Viruses in Tibetan Saline Lake Sediment by HiFi Metagenomic Sequencing.

With the development and reduced costs of high-throughput sequencing technology, environmental dark matter, such as novel metagenome-assembled genomes (MAGs) and viruses, is now being discovered easily. However, due to read length limitations, MAGs and viromes often suffer from genome discontinuity and deficiencies in key functional elements. Here, by applying long-read sequencing technology to sediment samples from a Tibetan saline lake, we comprehensively analyzed the performance of high-fidelity (HiFi) reads and the possibility of integration with short-read next-generation sequencing (NGS) data. In total, 207 full-length nonredundant 16S rRNA gene sequences and 19 full-length nonredundant 18S rRNA genes were directly obtained from HiFi reads, which greatly surpassed the retrieval performance of NGS technology. We carried out a cross-sectional comparison among multiple assembly strategies, referred to as 'NGS', 'Hybrid (NGS+HiFi)', and 'HiFi'. Two MAGs and 29 viruses with circular genomes were reconstructed using HiFi reads alone, indicating the great power of the 'HiFi' approach to assemble high-quality microbial genomes. Among the 3 strategies, the 'Hybrid' approach produced the highest number of medium/high-quality MAGs and viral genomes, while the ratio of MAGs containing 16S rRNA genes was significantly improved in the 'HiFi' assembly results. Overall, our study provides a practical metagenomic resolution for analyzing complex environmental samples by taking advantage of both the short-read and HiFi long-read sequencing methods to extract the maximum amount of information, including data on prokaryotes, eukaryotes, and viruses, via the 'Hybrid' approach. IMPORTANCE To expand the understanding of microbial dark matter in the environment, we did the first comparative evaluation of multiple assembly strategies based on high-throughput short-read and HiFi data from lake sediments metagenomic sequencing. The results demonstrated great improvement of the 'Hybrid' assembly method (short-read next-generation sequencing data plus HiFi data) in the recovery of medium/high-quality MAGs and viral genomes. Further analysis showed that HiFi data is important to retrieve the complete circular prokaryotic and viral genomes. Meanwhile, hundreds of full-length 16S/18S rRNA genes were assembled directly from HiFi data, which facilitated the species composition studies of complex environmental samples, especially for understanding micro-eukaryotes. Therefore, the application of the latest HiFi long-read sequencing could greatly improve the metagenomic assembly integrity and promote environmental microbiome research.

Navigating and expanding the roadmap of natural product genome mining tools.

Natural products are structurally highly diverse and exhibit a wide array of biological activities. As a result, they serve as an important source of new drug leads. Traditionally, natural products have been discovered by bioactivity-guided fractionation. The advent of genome sequencing technology has resulted in the introduction of an alternative approach towards novel natural product scaffolds: Genome mining. Genome mining is an in-silico natural product discovery strategy in which sequenced genomes are analyzed for the potential of the associated organism to produce natural products. Seemingly universal biosynthetic principles have been deciphered for most natural product classes that are used to detect natural product biosynthetic gene clusters using pathway-encoded conserved key enzymes, domains, or motifs as bait. Several generations of highly sophisticated tools have been developed for the biosynthetic rule-based identification of natural product gene clusters. Apart from these hard-coded algorithms, multiple tools that use machine learning-based approaches have been designed to complement the existing genome mining tool set and focus on natural product gene clusters that lack genes with conserved signature sequences. In this perspective, we take a closer look at state-of-the-art genome mining tools that are based on either hard-coded rules or machine learning algorithms, with an emphasis on the confidence of their predictions and potential to identify non-canonical natural product biosynthetic gene clusters. We highlight the genome mining pipelines' current strengths and limitations by contrasting their advantages and disadvantages. Moreover, we introduce two indirect biosynthetic gene cluster identification strategies that complement current workflows. The combination of all genome mining approaches will pave the way towards a more comprehensive understanding of the full biosynthetic repertoire encoded in microbial genome sequences.

Complex host/symbiont integration of a multi-partner symbiotic system in the eusocial aphid Ceratovacuna japonica.

Some hemipteran insects rely on multiple endosymbionts for essential nutrients. However, the evolution of multi-partner symbiotic systems is not well-established. Here, we report a co-obligate symbiosis in the eusocial aphid, Ceratovacuna japonica. 16S rRNA amplicon sequencing unveiled co-infection with a novel Arsenophonus sp. symbiont and Buchnera aphidicola, a common obligate endosymbiont in aphids. Both symbionts were housed within distinct bacteriocytes and were maternally transmitted. The Buchnera and Arsenophonus symbionts had streamlined genomes of 432,286bp and 853,149bp, respectively, and exhibited metabolic complementarity in riboflavin and peptidoglycan synthesis pathways. These anatomical and genomic properties were similar to those of independently evolved multi-partner symbiotic systems, such as Buchnera-Serratia in Lachninae and Periphyllus aphids, representing remarkable parallelism. Furthermore, symbiont populations and bacteriome morphology differed between reproductive and soldier castes. Our study provides the first example of co-obligate symbiosis in Hormaphidinae and gives insight into the evolutionary genetics of this complex system.

Genotyping Microbial Communities with MIDAS2: From Metagenomic Reads to Allele Tables.

The Metagenomic Intra-Species Diversity Analysis System 2 (MIDAS2) is a scalable pipeline that identifies single nucleotide variants and gene copy number variants in metagenomes using comprehensive reference databases built from public microbial genome collections (metagenotyping). MIDAS2 is the first metagenotyping tool with functionality to control metagenomic read mapping filters and to customize the reference database to the microbial community, features that improve the precision and recall of detected variants. In this article we present four basic protocols for the most common use cases of MIDAS2, along with supporting protocols for installation and use. In addition, we provide in-depth guidance on adjusting command line parameters, editing the reference database, optimizing hardware utilization, and understanding the metagenotyping results. All the steps of metagenotyping, from raw sequencing reads to population genetic analysis, are demonstrated with example data in two downloadable sequencing libraries of single-end metagenomic reads representing a mixture of multiple bacterial species. This set of protocols empowers users to accurately genotype hundreds of species in thousands of samples, providing rich genetic data for studying the evolution and strain-level ecology of microbial communities. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Species prescreening Basic Protocol 2: Download MIDAS reference database Basic Protocol 3: Population single nucleotide variant calling Basic Protocol 4: Pan-genome copy number variant calling Support Protocol 1: Installing MIDAS2 Support Protocol 2: Command line inputs Support Protocol 3: Metagenotyping with a custom collection of genomes Support Protocol 4: Metagenotyping with advanced parameters.

Demystifying Bacteriocins of Human Microbiota by Genome Guided Prospects: An Impetus to Rekindle the Antimicrobial Research.

The human microbiome is a reservoir of potential bacteriocins that can counteract multidrug resistant bacterial pathogens. Unlike antibiotics, bacteriocins selectively inhibit a spectrum of competent bacteria and are said to safeguard gut commensals, reducing the chance of dysbiosis. Bacteriocinogenic probiotics or bacteriocins of human origin will be more pertinent in human physiological conditions for therapeutic applications to act against invading pathogens. Recent advancement in the omics approach enables the mining of diverse and novel bacteriocins by identifying biosynthetic gene clusters from the human microbial genome, pangenome or shotgun metagenome, which is a breakthrough in the discovery line of novel bacteriocins. This review summarizes the most recent trends and therapeutic potential of bacteriocins of human microbial origin, the advancement in the in silico algorithms and databases in the discovery of novel bacteriocin, and how to bridge the gap between the discovery of bacteriocin genes from big datasets and their in vitro production. Besides, the later part of the review discussed the various impediments in their clinical applications and possible solution to bring them into the frontline therapeutics to control infections, thereby meeting the challenges of global antimicrobial resistance.

Gut Microbiome Studies in Livestock: Achievements, Challenges, and Perspectives

The variety and makeup of the gut microbiome are frequently regarded as the primary determinants of health and production performances in domestic animals. High-throughput DNA/RNA sequencing techniques (NGS) have recently gained popularity and permitted previously unheard-of advancements in the study of gut microbiota, particularly for determining the taxonomic composition of such complex communities. Here, we summarize the existing body of knowledge on livestock gut microbiome, discuss the state-of-the-art in sequencing techniques, and offer predictions for next research. We found that the enormous volumes of available data are biased toward a small number of globally distributed and carefully chosen varieties, while local breeds (or populations) are frequently overlooked despite their demonstrated resistance to harsh environmental circumstances. Furthermore, the bulk of this research has mostly focused on bacteria, whereas other microbial components such as protists, fungi, and viruses have received far less attention. The majority of these data were gathered utilizing traditional metabarcoding techniques that taxonomically identify the gut microbiota by analyzing small portions of their genome (less than 1000 base pairs). However, to extend the coverage of microbial genomes for a more precise and thorough characterization of microbial communities, a variety of increasingly practical and economical shotgun techniques are currently available.

Long-Read Sequencing Improves Recovery of Picoeukaryotic Genomes and Zooplankton Marker Genes from Marine Metagenomes.

Long-read sequencing offers the potential to improve metagenome assemblies and provide more robust assessments of microbial community composition and function than short-read sequencing. We applied Pacific Biosciences (PacBio) CCS (circular consensus sequencing) HiFi shotgun sequencing to 14 marine water column samples and compared the results with those for short-read metagenomes from the corresponding environmental DNA samples. We found that long-read metagenomes varied widely in quality and biological information. The community compositions of the corresponding long- and short-read metagenomes were frequently dissimilar, suggesting higher stochasticity and/or bias associated with PacBio sequencing. Long reads provided few improvements to the assembly qualities, gene annotations, and prokaryotic metagenome-assembled genome (MAG) binning results. However, only long reads produced high-quality eukaryotic MAGs and contigs containing complete zooplankton marker gene sequences. These results suggest that high-quality long-read metagenomes can improve marine community composition analyses and provide important insight into eukaryotic phyto- and zooplankton genetics, but the benefits may be outweighed by the inconsistent data quality. IMPORTANCE Ocean microbes provide critical ecosystem services, but most remain uncultivated. Their communities can be studied through shotgun metagenomic sequencing and bioinformatic analyses, including binning draft microbial genomes. However, most sequencing to date has been done using short-read technology, which rarely yields genome sequences of key microbes like SAR11. Long-read sequencing can improve metagenome assemblies but is hampered by technological shortcomings and high costs. In this study, we compared long- and short-read sequencing of marine metagenomes. We found a wide range of long-read metagenome qualities and minimal improvements to microbiome analyses. However, long reads generated draft genomes of eukaryotic algal species and provided full-length marker gene sequences of zooplankton species, including krill and copepods. These results suggest that long-read sequencing can provide greater genetic insight into the wide diversity of eukaryotic phyto- and zooplankton that interact as part of and with the marine microbiome.

Intake of slow-digesting carbohydrates is related to changes in the microbiome and its functional pathways in growing rats with obesity induced by diet.

The main cause of insulin resistance in childhood is obesity, which contributes to future comorbidities as in adults. Although high-calorie diets and lack of exercise contribute to metabolic disease development, food quality rather than the quantity of macronutrients is more important than food density. The purpose of the present study was to examine the effects of changing the quality of carbohydrates from rapidly to slowly digestible carbohydrates on the composition of the gut microbiota and the profiles of the functional pathways in growing rats with obesity due to a high-fat diet (HFD). During the course of 4 weeks, rats growing on an HFD-containing carbohydrates with different digestive rates were fed either HFD-containing carbohydrates with a rapid digestion rate (OBE group) or HFD-containing carbohydrates with a slow digestion rate (OBE-ISR group). A non-obese group (NOB) was included as a reference, and rats were fed on a rodent standard diet (AIN93G). An analysis of gut microbiota was conducted using 16S rRNA-based metagenomics; a linear mixed-effects model (LMM) was used to determine changes in abundance between baseline and 4 weeks of treatment, and functional pathways were identified. Gut microbiota composition at bacterial diversity and relative abundance, at phylum and genus levels, and functional profiles were analyzed by integrating the Integrated Microbial Genomes (IMG) database. The groups showed comparable gut microbiota at baseline. At the end of the treatment, animals from the ISR group exhibited differences at the phylum levels by decreasing the diversity of Fisher's index and Firmicutes (newly named as Bacillota), and increasing the Pielou's evenness and Bacteroidetes (newly named as Bacteroidota); at the genus level by increasing Alistipes, Bifidobacterium, Bacteroides, Butyricimonas, Lachnoclostridium, Flavonifractor, Ruminiclostridium 5, and Faecalibaculum and decreasing Muribaculum, Blautia, and Ruminiclostridium 9. Remarkably, relative abundances of genera Tyzzerella and Angelakisella were higher in the OBE group compared to NOB and OBE-ISR groups. In addition, some microbiota carbohydrate metabolism pathways such as glycolysis, glucuronic acid degradation, pentose phosphate pathway, methanogenesis, and fatty acid biosynthesis exhibited increased activity in the OBE-ISR group after the treatment. Higher levels of acetate and propionate were found in the feces of the ISR group compared with the NOB and OBE groups. The results of this study demonstrate that replacing rapidly digestible carbohydrates with slowly digestible carbohydrates within an HFD improve the composition of the gut microbiota. Consequently, metabolic disturbances associated with obesity may be prevented.

Prokaryotic and viral genomes recovered from 787 Japanese gut metagenomes revealed microbial features linked to diets, populations, and diseases

We reconstructed 19,084 prokaryotic and 31,395 viral genomes from 787 Japanese gut metagenomes as Japanese metagenome-assembled genomes (JMAG) and Japanese Virus Database (JVD), which are large microbial genome datasets for a single population. Population-specific enrichment of the Bacillus subtilis and β-porphyranase among the JMAG could derive from the Japanese traditional food natto (fermented soybeans) and nori (laver), respectively. Dairy-related Enterococcus_B lactis and Streptococcus thermophilus were nominally associated with the East Asian-specific missense variant rs671:G>A in ALDH2, which was associated with dairy consumption. Of the species-level viral genome clusters in the JVD, 62.9% were novel. The β crAss-like phage composition was low among the Japanese but relatively high among African and Oceanian peoples. Evaluations of the association between crAss-like phages and diseases showed significant disease-specific associations. Our large catalog of virus-host pairs identified the positive correlation between the abundance of the viruses and their hosts.

Mining elements of siderophore chirality encoded in microbial genomes.

The vast majority of bacteria require iron to grow. A significant iron acquisition strategy is the production of siderophores, which are secondary microbial metabolites synthesized to sequester iron(III). Siderophore structures encompass a variety of forms, of which highly modified peptidic siderophores are of interest herein. State-of-the-art genome mining tools, such as antiSMASH (antibiotics & Secondary Metabolite Analysis SHell), hold the potential to predict and discover new peptidic siderophores, including a combinatoric suite of triscatechol siderophores framed on a triserine-ester backbone of the general class, (DHB-l/d CAA-l Ser)3 (CAA, cationic amino acid). Siderophores with l/d Arg, l/d Lys and l Orn, but not d Orn, were predicted in bacterial genomes. Fortuitously the d Orn siderophore was identified, yet its lack of prediction highlights the limitation of current genome mining tools. The full combinatoric suite of these siderophores, which form chiral iron(III) complexes, reveals stereospecific coordination chemistry encoded in microbial genomes. The chirality embedded in this suite of Fe(III)-siderophores raises the question of whether the relevant siderophore-mediated iron acquisition pathways are stereospecific and selective for ferric siderophore complexes of a defined configuration.