RefSeq microbial genomes database: new representation and annotation strategy

Identification of a dCache-type chemoreceptor in Campylobacter jejuni that specifically mediates chemotaxis towards methyl pyruvate

The foodborne pathogenic bacterium Campylobacter jejuni utilizes chemotaxis to assist in the colonization of host niches. A key to revealing the relationship among chemotaxis and pathogenicity is the discovery of signaling molecules perceived by the chemoreceptors. The C. jejuni chemoreceptor Tlp11 is encoded by the highly infective C. jejuni strains. In the present study, we report that the dCache-type ligand-binding domain (LBD) of C. jejuni ATCC 33560 Tlp11 binds directly to novel ligands methyl pyruvate, toluene, and quinoline using the same pocket. Methyl pyruvate elicits a strong chemoattractant response, while toluene and quinoline function as the antagonists without triggering chemotaxis. The sensory LBD was used to control heterologous proteins by constructing chimeras, indicating that the signal induced by methyl pyruvate is transmitted across the membrane. In addition, bioinformatics and experiments revealed that the dCache domains with methyl pyruvate-binding sites and ability are widely distributed in the order Campylobacterales. This is the first report to identify the class of dCache chemoreceptors that bind to attractant methyl pyruvate and antagonists toluene and quinoline. Our research provides a foundation for understanding the chemotaxis and virulence of C. jejuni and lays a basis for the control of this foodborne pathogen.

Saccharomyces cerevisiae derived postbiotic alters gut microbiome metabolism in the human distal colon resulting in immunomodulatory potential in vitro

The yeast-based postbiotic EpiCor is a well-studied formulation, consisting of a complex mixture of bioactive molecules. In clinical studies, EpiCor postbiotic has been shown to reduce intestinal symptoms in a constipated population and support mucosal defense in healthy subjects. Anti-inflammatory potential and butyrogenic properties have been reported in vitro, suggesting a possible link between EpiCor's gut modulatory activity and immunomodulation. The current study used a standardized in vitro gut model, the Simulator of the Human Intestinal Microbial Ecosystem (SHIME®), to obtain a deeper understanding on host-microbiome interactions and potential microbiome modulation following repeated EpiCor administration. It was observed that EpiCor induced a functional shift in carbohydrate fermentation patterns in the proximal colon environment. Epicor promoted an increased abundance of Bifidobacterium in both the proximal and distal colon, affecting overall microbial community structure. Co-occurrence network analysis at the phylum level provided additional evidence of changes in the functional properties of microbial community promoted by EpiCor, increasing positive associations between Actinobacteria with microbes belonging to the Firmicutes phylum. These results, together with a significant increase in butyrate production provide additional support of EpiCor benefits to gut health. Investigation of host-microbiome interactions confirmed the immunomodulatory potential of the applied test product. Specific microbial alterations were observed in the distal colon, with metabotyping indicating that specific metabolic pathways, such as bile acid and tryptophan metabolism, were affected following EpiCor supplementation. These results, especially considering many effects were seen distally, further strengthen the position of EpiCor as a postbiotic with health promoting functionality in the gut, which could be further assessed in vivo.

Hound: a novel tool for automated mapping of genotype to phenotype in bacterial genomes assembled de novo

Increasing evidence suggests that microbial species have a strong within species genetic heterogeneity. This can be problematic for the analysis of prokaryote genomes, which commonly relies on a reference genome to guide the assembly process. Differences between reference and sample genomes will therefore introduce errors in final assembly, jeopardizing the detection from structural variations to point mutations-critical for genomic surveillance of antibiotic resistance. Here we present Hound, a pipeline that integrates publicly available tools to assemble prokaryote genomes de novo, detect user-given genes by similarity to report mutations found in the coding sequence, promoter, as well as relative gene copy number within the assembly. Importantly, Hound can use the query sequence as a guide to merge contigs, and reconstruct genes that were fragmented by the assembler. To showcase Hound, we screened through 5032 bacterial whole-genome sequences isolated from farmed animals and human infections, using the amino acid sequence encoded by blaTEM-1, to detect and predict resistance to amoxicillin/clavulanate which is driven by over-expression of this gene. We believe this tool can facilitate the analysis of prokaryote species that currently lack a reference genome, and can be scaled either up to build automated systems for genomic surveillance or down to integrate into antibiotic susceptibility point-of-care diagnostics.

Genome-wide association study reveals serovar-associated genetic loci in Riemerella anatipestifer

BACKGROUND

The disease caused by Riemerella anatipestifer (R. anatipestifer, RA) results in large economic losses to the global duck industry every year. Serovar-related genomic variation, such as the O-antigen and capsular polysaccharide (CPS) gene clusters, has been widely used for serotyping in many gram-negative bacteria. RA has been classified into at least 21 serovars based on slide agglutination, but the molecular basis of serotyping is unknown. In this study, we performed a pan-genome-wide association study (Pan-GWAS) to identify the genetic loci associated with RA serovars.

RESULTS

The results revealed a significant association between the putative CPS synthesis gene locus and the serological phenotype. Further characterization of the CPS gene clusters in 11 representative serovar strains indicated that they were highly diverse and serovar-specific. The CPS gene cluster contained the key genes wzx and wzy, which are involved in the Wzx/Wzy-dependent pathway of CPS synthesis. Similar CPS loci have been found in some other species within the family Weeksellaceae. We have also shown that deletion of the wzy gene in RA results in capsular defects and cross-agglutination.

CONCLUSIONS

This study indicates that the CPS synthesis gene cluster of R. anatipestifer is a serotype-specific genetic locus. Importantly, our finding provides a new perspective for the systematic analysis of the genetic basis of the R anatipestifer serovars and a potential target for establishing a complete molecular serotyping scheme.

New algorithms for structure informed genome rearrangement

We define two new computational problems in the domain of perfect genome rearrangements, and propose three algorithms to solve them. The rearrangement scenarios modeled by the problems consider Reversal and Block Interchange operations, and a PQ-tree is utilized to guide the allowed operations and to compute their weights. In the first problem, [Formula: see text] ([Formula: see text]), we define the basic structure-informed rearrangement measure. Here, we assume that the gene order members of the gene cluster from which the PQ-tree is constructed are permutations. The PQ-tree representing the gene cluster is ordered such that the series of gene IDs spelled by its leaves is equivalent to that of the reference gene order. Then, a structure-informed genome rearrangement distance is computed between the ordered PQ-tree and the target gene order. The second problem, [Formula: see text] ([Formula: see text]), generalizes [Formula: see text], where the gene order members are not necessarily permutations and the structure informed rearrangement measure is extended to also consider up to [Formula: see text] and [Formula: see text] gene insertion and deletion operations, respectively, when modelling the PQ-tree informed divergence process from the reference gene order to the target gene order. The first algorithm solves [Formula: see text] in [Formula: see text] time and [Formula: see text] space, where [Formula: see text] is the maximum number of children of a node, n is the length of the string and the number of leaves in the tree, and [Formula: see text] and [Formula: see text] are the number of P-nodes and Q-nodes in the tree, respectively. If one of the penalties of [Formula: see text] is 0, then the algorithm runs in [Formula: see text] time and [Formula: see text] space. The second algorithm solves [Formula: see text] in [Formula: see text] time and [Formula: see text] space, where [Formula: see text] is the maximum number of children of a node, n is the length of the string, m is the number of leaves in the tree, [Formula: see text] and [Formula: see text] are the number of P-nodes and Q-nodes in the tree, respectively, and allowing up to [Formula: see text] deletions from the tree and up to [Formula: see text] deletions from the string. The third algorithm is intended to reduce the space complexity of the second algorithm. It solves a variant of the problem (where one of the penalties of [Formula: see text] is 0) in [Formula: see text] time and [Formula: see text] space. The algorithm is implemented as a software tool, denoted MEM-Rearrange, and applied to the comparative and evolutionary analysis of 59 chromosomal gene clusters extracted from a dataset of 1487 prokaryotic genomes.

Bioinformatic approaches for studying the microbiome of fermented food

High-throughput DNA sequencing-based approaches continue to revolutionise our understanding of microbial ecosystems, including those associated with fermented foods. Metagenomic and metatranscriptomic approaches are state-of-the-art biological profiling methods and are employed to investigate a wide variety of characteristics of microbial communities, such as taxonomic membership, gene content and the range and level at which these genes are expressed. Individual groups and consortia of researchers are utilising these approaches to produce increasingly large and complex datasets, representing vast populations of microorganisms. There is a corresponding requirement for the development and application of appropriate bioinformatic tools and pipelines to interpret this data. This review critically analyses the tools and pipelines that have been used or that could be applied to the analysis of metagenomic and metatranscriptomic data from fermented foods. In addition, we critically analyse a number of studies of fermented foods in which these tools have previously been applied, to highlight the insights that these approaches can provide.

Metatranscriptomic analysis of the gut microbiome of black soldier fly larvae reared on lignocellulose-rich fiber diets unveils key lignocellulolytic enzymes

Recently, interest in the black soldier fly larvae (BSFL) gut microbiome has received increased attention primarily due to their role in waste bioconversion. However, there is a lack of information on the positive effect on the activities of the gut microbiomes and enzymes (CAZyme families) acting on lignocellulose. In this study, BSFL were subjected to lignocellulose-rich diets: chicken feed (CF), chicken manure (CM), brewers' spent grain (BSG), and water hyacinth (WH). The mRNA libraries were prepared, and RNA-Sequencing was conducted using the PCR-cDNA approach through the MinION sequencing platform. Our results demonstrated that BSFL reared on BSG and WH had the highest abundance of Bacteroides and Dysgonomonas. The presence of GH51 and GH43_16 enzyme families in the gut of BSFL with both α-L-arabinofuranosidases and exo-alpha-L-arabinofuranosidase 2 were common in the BSFL reared on the highly lignocellulosic WH and BSG diets. Gene clusters that encode hemicellulolytic arabinofuranosidases in the CAZy family GH51 were also identified. These findings provide novel insight into the shift of gut microbiomes and the potential role of BSFL in the bioconversion of various highly lignocellulosic diets to fermentable sugars for subsequent value-added products (bioethanol). Further research on the role of these enzymes to improve existing technologies and their biotechnological applications is crucial.

Soil microbial gene expression in an agricultural ecosystem varies with time and neonicotinoid seed treatments

Neonicotinoids, a class of systemic insecticides, have been widely used for decades against various insect pests. Previous studies have reported non-target effects of neonicotinoids on some beneficial macro- and micro-organisms. Considering the crucial role the soil microbiota plays in sustaining soil fertility, it is critical to understand how neonicotinoid exposure affects the microbial taxonomic composition and gene expression. However, most studies to date have evaluated soil microbial taxonomic compositions or assessed microbial functions based on soil biochemical analysis. In this study, we have applied a metatranscriptomic approach to quantify the variability in soil microbial gene expression in a 2 year soybean/corn crop rotation in Quebec, Canada. We identified weak and temporally inconsistent effects of neonicotinoid application on soil microbial gene expression, as well as a strong temporal variation in soil microbial gene expression among months and years. Neonicotinoid seed treatment altered the expression of a small number of microbial genes, including genes associated with heat shock proteins, regulatory functions, metabolic processes and DNA repair. These changes in gene expression varied during the growing season and between years. Overall, the composition of soil microbial expressed genes seems to be more resilient and less affected by neonicotinoid application than soil microbial taxonomic composition. Our study is among the first to document the effects of neonicotinoid seed treatment on microbial gene expression and highlights the strong temporal variability of soil microbial gene expression and its responses to neonicotinoid seed treatments.

Social Diversification Driven by Mobile Genetic Elements

Social diversification in microbes is an evolutionary process where lineages bifurcate into distinct populations that cooperate with themselves but not with other groups. In bacteria, this is frequently driven by horizontal transfer of mobile genetic elements (MGEs). Here, the resulting acquisition of new genes changes the recipient's social traits and consequently how they interact with kin. These changes include discriminating behaviors mediated by newly acquired effectors. Since the producing cell is protected by cognate immunity factors, these selfish elements benefit from selective discrimination against recent ancestors, thus facilitating their proliferation and benefiting the host. Whether social diversification benefits the population at large is less obvious. The widespread use of next-generation sequencing has recently provided new insights into population dynamics in natural habitats and the roles MGEs play. MGEs belong to accessory genomes, which often constitute the majority of the pangenome of a taxon, and contain most of the kin-discriminating loci that fuel rapid social diversification. We further discuss mechanisms of diversification and its consequences to populations and conclude with a case study involving myxobacteria.

CriSNPr, a single interface for the curated and de novo design of gRNAs for CRISPR diagnostics using diverse Cas systems

CRISPR-based diagnostics (CRISPRDx) have improved clinical decision-making, especially during the COVID-19 pandemic, by detecting nucleic acids and identifying variants. This has been accelerated by the discovery of new and engineered CRISPR effectors, which have expanded the portfolio of diagnostic applications to include a broad range of pathogenic and non-pathogenic conditions. However, each diagnostic CRISPR pipeline necessitates customized detection schemes based on the fundamental principles of the Cas protein used, its guide RNA (gRNA) design parameters, and the assay readout. This is especially relevant for variant detection, a low-cost alternative to sequencing-based approaches for which no in silico pipeline for the ready-to-use design of CRISPRDx currently exists. In this manuscript, we fill this lacuna using a unified web server, CriSNPr (CRISPR-based SNP recognition), which provides the user with the opportunity to de novo design gRNAs based on six CRISPRDx proteins of choice (Fn/enFnCas9, LwCas13a, LbCas12a, AaCas12b, and Cas14a) and query for ready-to-use oligonucleotide sequences for validation on relevant samples. Furthermore, we provide a database of curated pre-designed gRNAs as well as target/off-target for all human and SARS-CoV-2 variants reported thus far. CriSNPr has been validated on multiple Cas proteins, demonstrating its broad and immediate applicability across multiple detection platforms. CriSNPr can be found at http://crisnpr.igib.res.in/.

Polar localization of CheO under hypoxia promotes Campylobacter jejuni chemotactic behavior within host

Campylobacter jejuni is a food-borne zoonotic pathogen of worldwide concern and the leading cause of bacterial diarrheal disease. In contrast to other enteric pathogens, C. jejuni has strict growth and nutritional requirements but lacks many virulence factors that have evolved for pathogenesis or interactions with the host. It is unclear how this bacterium has adapted to an enteric lifestyle. Here, we discovered that the CheO protein (CJJ81176_1265) is required for C. jejuni colonization of mice gut through its role in chemotactic control of flagellar rotation in oxygen-limiting environments. CheO interacts with the chemotaxis signaling proteins CheA and CheZ, and also with the flagellar rotor components FliM and FliY. Under microaerobic conditions, CheO localizes at the cellular poles where the chemosensory array and flagellar machinery are located in C. jejuni and its polar localization depends on chemosensory array formation. Several chemoreceptors that mediate energy taxis coordinately determine the bipolar distribution of CheO. Suppressor screening for a ΔcheO mutant identified that a single residue variation in FliM can alleviate the phenotype caused by the absence of CheO, confirming its regulatory role in the flagellar rotor switch. CheO homologs are only found in species of the Campylobacterota phylum, mostly species of host-associated genera Campylobacter, Helicobacter and Wolinella. The CheO results provide insights into the complexity of chemotaxis signal transduction in C. jejuni and closely related species. Importantly, the recruitment of CheO into chemosensory array to promote chemotactic behavior under hypoxia represents a new adaptation strategy of C. jejuni to human and animal intestines.

Bacteria use chemotaxis to navigate their flagellar motility towards or away from a variety of environmental stimuli. For many pathogens, chemotactic motility plays an important role in infection and disease. Understanding the mechanism of chemotaxis behavior in pathogens can help the development of therapeutic strategies by interfering with chemotactic signal transduction. In this study, we identified a novel chemotaxis protein CheO in Campylobacter jejuni, a leading cause of human gastroenteritis worldwide. We demonstrated that CheO is directly involved in chemotactic control of the flagellar motor switch, the reason that it is required for colonization of different animal models. We also provide evidences that CheO is responsive to environmental oxygen variation, with a more prominent role in energy taxis under low oxygen levels. Therefore, CheO presents a novel mechanism for C. jejuni adaptation to hypoxia conditions such as those existing in human and animal intestines. Targeting CheO and other chemotaxis regulators could reduce the survival of C. jejuni within hosts and in the food chain.

Benchmarking Community-Wide Estimates of Growth Potential from Metagenomes Using Codon Usage Statistics

Trait inference from mixed-species assemblages is a central problem in microbial ecology. Frequently, sequencing information from an environment is available, but phenotypic measurements from individual community members are not. With the increasing availability of molecular data for microbial communities, bioinformatic approaches that map metagenome to (meta)phenotype are needed. Recently, we developed a tool, gRodon, that enables the prediction of the maximum growth rate of an organism from genomic data on the basis of codon usage patterns. Our work and that of other groups suggest that such predictors can be applied to mixed-species communities in order to derive estimates of the average community-wide maximum growth rate. Here, we present an improved maximum growth rate predictor designed for metagenomes that corrects a persistent GC bias in the original gRodon model for metagenomic prediction. We benchmark this predictor with simulated metagenomic data sets to show that it has superior performance on mixed-species communities relative to earlier models. We go on to provide guidance on data preprocessing and show that calling genes from assembled contigs rather than directly from reads dramatically improves performance. Finally, we apply our predictor to large-scale metagenomic data sets from marine and human microbiomes to illustrate how community-wide growth prediction can be a powerful approach for hypothesis generation. Altogether, we provide an updated tool with clear guidelines for users about the uses and pitfalls of metagenomic prediction of the average community-wide maximal growth rate. IMPORTANCE Microbes dominate nearly every known habitat, and therefore tools to survey the structure and function of natural microbial communities are much needed. Metagenomics, in which the DNA content of an entire community of organisms is sequenced all at once, allows us to probe the genetic diversity contained in a habitat. Yet, mapping metagenomic information to the actual traits of community members is a difficult and largely unsolved problem. Here, we present and validate a tool that allows users to predict the average maximum growth rate of a microbial community directly from metagenomic data. Maximum growth rate is a fundamental characteristic of microbial species that can give us a great deal of insight into their ecological role, and by applying our community-level predictor to large-scale metagenomic data sets from marine and human-associated microbiomes, we show how community-wide growth prediction can be a powerful approach for hypothesis generation.

First report of Pseudomonas viridiflava causing fruit rot on sweet cherry trees in Chile

Chile is an important producers of sweet cherry (Prunus avium L.), with a total of 356,385 t exported in the 2021 to 2022 season. The production area includes most of the country's regions. Bacterial samples were isolated in 2017 and 2018 from 18 commercial sweet cherry orchards with canker disease. From one of this samples collected in the spring of 2018, was isolated the strain A2M176 from buds of trees that presented canker and gomosis in Malloa locality (34°23' 46'' S 71°01' 39'' W). The strain produced fluorescent pigment on King's B agar medium. Is oxidase and arginine dihydrolase negative, potato soft rot positive and showed a slight degree of tobacco hypersensitivity. It was able to growth up to 0.8 mM (200 ppm) of CuSO4·5H2O. The strain A2M176 was deposited in the Colección Chilena de Recursos Genéticos Microbianos (CChRGM) under the no. RGM 3342. The DNA of this strain was extracted from a pure culture using silica spin columns (Epoch Life Science Inc., Sugar Land, USA). The complete DNA was sequenced using HiSeq with 150 bp paired-end at GENEWIZ (New York, USA). Raw data was checked using FASTQC and trimmed with BBDuk. The genome was assembled using Unicycler v0.4.9 with defaulf settings and annotated with Prokaryotic Genome Annotation Pipeline (PGAP) v4.3. The reads and genomes were uploaded to GenBank under the BioProyect no. PRJNA750090, BioSample no. SAMN26870984 and assembly no. GCA_022936465.1. The sequenced genome was compared through Average Nucleotide Identity algorithm (ANI) using FastANI v1.33 to compare with closest complete genome available on NCBI. The strain A2M176 was identified as P. viridiflava with ANI value of 98.06% with the strain p22.E7 (GCF_900585495). Maximum likelihood phylogenetic estimation clustered strain A2M176 with other P. viridiflava strains with 95% bootstrap. The pathogenicity of the strain was tested inoculating immature cherry fruits with a needle with a bacterial suspension (1x108 CFU/ml). The inoculated fruits were placed at room temperature in a humid chamber for 10 d. Soft rot lesions were observed, which appeared at 6 days post-inoculation (DPI). The control fruits treated with sterile water did not show symptoms. Further analyses in the genome of strain A2M176 led to identify genes related to pathogenicity, such as the effector gene avrE and the regulator gen HrpL, suggesting the pathogenic capacity of the strain. Also, there were identify genes of two known Pseudomonas copper resistance mechanisms, the cus and cop operon. These genes were found part of the copABCDns cluster similar to what was observed in Pseudomonas from Mango. Presence of P. viridiflava strains causing fruit rot in P. avium is not surprising, since P. viridiflava has a wide host range and causes a variety of symptoms in different plant parts, including stems, leaves, and blossoms. P. viridiflava represents one of the multiple phylogroups found within the P. syringae species complex.  To our knowledge, this is the first report of a strain of P. viridiflava copper resistant causing infection on sweet cherries in Chile.

DciA Helicase Operators Exhibit Diversity across Bacterial Phyla

A fundamental requirement for life is the replication of an organism's DNA. Studies in Escherichia coli and Bacillus subtilis have set the paradigm for DNA replication in bacteria. During replication initiation in E. coli and B. subtilis, the replicative helicase is loaded onto the DNA at the origin of replication by an ATPase helicase loader. However, most bacteria do not encode homologs to the helicase loaders in E. coli and B. subtilis. Recent work has identified the DciA protein as a predicted helicase operator that may perform a function analogous to the helicase loaders in E. coli and B. subtilis. DciA proteins, which are defined by the presence of a DUF721 domain (termed the DciA domain herein), are conserved in most bacteria but have only been studied in mycobacteria and gammaproteobacteria (Pseudomonas aeruginosa and Vibrio cholerae). Sequences outside the DciA domain in Mycobacterium tuberculosis DciA are essential for protein function but are not conserved in the P. aeruginosa and V. cholerae homologs, raising questions regarding the conservation and evolution of DciA proteins across bacterial phyla. To comprehensively define the DciA protein family, we took a computational evolutionary approach and analyzed the domain architectures and sequence properties of DciA domain-containing proteins across the tree of life. These analyses identified lineage-specific domain architectures among DciA homologs, as well as broadly conserved sequence-structural motifs. The diversity of DciA proteins represents the evolution of helicase operation in bacterial DNA replication and highlights the need for phylum-specific analyses of this fundamental biological process. IMPORTANCE Despite the fundamental importance of DNA replication for life, this process remains understudied in bacteria outside Escherichia coli and Bacillus subtilis. In particular, most bacteria do not encode the helicase-loading proteins that are essential in E. coli and B. subtilis for DNA replication. Instead, most bacteria encode a DciA homolog that likely constitutes the predominant mechanism of helicase operation in bacteria. However, it is still unknown how DciA structure and function compare across diverse phyla that encode DciA proteins. In this study, we performed computational evolutionary analyses to uncover tremendous diversity among DciA homologs. These studies provide a significant advance in our understanding of an essential component of the bacterial DNA replication machinery.

Natural Competence in the Filamentous, Heterocystous Cyanobacterium Chlorogloeopsis fritschii PCC 6912

Lateral gene transfer plays an important role in the evolution of genetic diversity in prokaryotes. DNA transfer via natural transformation depends on the ability of recipient cells to actively transport DNA from the environment into the cytoplasm, termed natural competence, which relies on the presence of type IV pili and other competence proteins. Natural competence has been described in cyanobacteria for several organisms, including unicellular and filamentous species. However, natural competence in cyanobacteria that differentiate specialized cells for N₂-fixation (heterocysts) and form branching or multiseriate cell filaments (termed subsection V) remains unknown. Here, we show that genes essential for natural competence are conserved in subsection V cyanobacteria. Furthermore, using the replicating plasmid pRL25C, we experimentally demonstrate natural competence in a subsection V organism: Chlorogloeopsis fritschii PCC 6912. Our results suggest that natural competence is a common trait in cyanobacteria forming complex cell filament morphologies.

IMPORTANCE Cyanobacteria are crucial players in the global biogeochemical cycles, where they contribute to CO₂- and N₂-fixation. Their main ecological significance is the primary biomass production owing to oxygenic photosynthesis. Cyanobacteria are a diverse phylum, in which the most complex species differentiate specialized cell types and form true-branching or multiseriate cell filament structures (termed subsection V cyanobacteria). These bacteria are considered a peak in the evolution of prokaryotic multicellularity. Among others, species in that group inhabit fresh and marine water habitats, soil, and extreme habitats such as thermal springs. Here, we show that the core genes required for natural competence are frequent in subsection V cyanobacteria and demonstrate for the first time natural transformation in a member of subsection V. The prevalence of natural competence has implications for the role of DNA acquisition in the genome evolution of cyanobacteria. Furthermore, the presence of mechanisms for natural transformation opens up new possibilities for the genetic modification of subsection V cyanobacteria.

Comparative Genomics of Lactiplantibacillus plantarum: Insights Into Probiotic Markers in Strains Isolated From the Human Gastrointestinal Tract and Fermented Foods

Lactiplantibacillus (Lpb.) plantarum is a versatile species commonly found in a wide variety of ecological niches including dairy products and vegetables, while it may also occur as a natural inhabitant of the human gastrointestinal tract. Although Lpb. plantarum strains have been suggested to exert beneficial properties on their host, the precise mechanisms underlying these microbe–host interactions are still obscure. In this context, the genome-scale in silico analysis of putative probiotic bacteria represents a bottom–up approach to identify probiotic biomarkers, predict desirable functional properties, and identify potentially detrimental antibiotic resistance genes. In this study, we characterized the bacterial genomes of three Lpb. plantarum strains isolated from three distinct environments [strain IMC513 (from the human GIT), C904 (from table olives), and LT52 (from raw-milk cheese)]. A whole-genome sequencing was performed combining Illumina short reads with Oxford Nanopore long reads. The phylogenomic analyses suggested the highest relatedness between IMC513 and C904 strains which were both clade 4 strains, with LT52 positioned within clade 5 within the Lpb. plantarum species. The comparative genome analysis performed across several Lpb. plantarum representatives highlighted the genes involved in the key metabolic pathways as well as those encoding potential probiotic features in these new isolates. In particular, our strains varied significantly in genes encoding exopolysaccharide biosynthesis and in contrast to strains IMC513 and C904, the LT52 strain does not encode a Mannose-binding adhesion protein. The LT52 strain is also deficient in genes encoding complete pentose phosphate and the Embden–Meyerhof pathways. Finally, analyses using the CARD and ResFinder databases revealed that none of the strains encode known antibiotic resistance loci. Ultimately, the results provide better insights into the probiotic potential and safety of these three strains and indicate avenues for further mechanistic studies using these isolates.

Ustilago maydis Metabolic Characterization and Growth Quantification with a Genome-Scale Metabolic Model

Ustilago maydis is an important plant pathogen that causes corn smut disease and serves as an effective biotechnological production host. The lack of a comprehensive metabolic overview hinders a full understanding of the organism’s environmental adaptation and a full use of its metabolic potential. Here, we report the first genome-scale metabolic model (GSMM) of Ustilago maydis (iUma22) for the simulation of metabolic activities. iUma22 was reconstructed from sequencing and annotation using PathwayTools, and the biomass equation was derived from literature values and from the codon composition. The final model contains over 25% annotated genes (6909) in the sequenced genome. Substrate utilization was corrected by BIOLOG phenotype arrays, and exponential batch cultivations were used to test growth predictions. The growth data revealed a decrease in glucose uptake rate with rising glucose concentration. A pangenome of four different U. maydis strains highlighted missing metabolic pathways in iUma22. The new model allows for studies of metabolic adaptations to different environmental niches as well as for biotechnological applications.

Functional Redundancy in Soil Microbial Community Based on Metagenomics Across the Globe

Understanding the contribution of soil microbial communities to ecosystem processes is critical for predicting terrestrial ecosystem feedbacks under changing climate. Our current understanding lacks a consistent strategy to formulate the linkage between microbial systems and ecosystem processes due to the presumption of functional redundancy in soil microbes. Here we present a global soil microbial metagenomic analysis to generalize patterns of microbial taxonomic compositions and functional potentials across climate and geochemical gradient. Our analyses show that soil microbial taxonomic composition varies widely in response to climate and soil physicochemical gradients, while microbial functional attributes based on metagenomic gene abundances are redundant. Among 17 climate zones, microbial taxonomic compositions were more distinct than functional potentials, as climate and edaphic properties showed more significant influence on microbial taxonomic compositions than on functional potentials. Microbial taxonomies formed a larger and more complex co-occurrence network with more module structures than functional potentials. Functional network was strongly inter-connected among different categories, whereas taxonomic network was more positively interactive in the same taxonomic groups. This study provides strong evidence to support the hypothesis of functional redundancy in soil microbes, as microbial taxonomic compositions vary to a larger extent than functional potentials based on metagenomic gene abundances in terrestrial ecosystems across the globe.

Comparative Analysis and Data Provenance for 1,113 Bacterial Genome Assemblies

The availability of public genomics data has become essential for modern life sciences research, yet the quality, traceability, and curation of these data have significant impacts on a broad range of microbial genomics research. While microbial genome databases such as NCBI’s RefSeq database leverage the scalability of crowd sourcing for growth, genomics data provenance and authenticity of the source materials used to produce data are not strict requirements. Here, we describe the de novo assembly of 1,113 bacterial genome references produced from authenticated materials sourced from the American Type Culture Collection (ATCC), each with full genomics data provenance relating to bioinformatics methods, quality control, and passage history. Comparative genomics analysis of ATCC standard reference genomes (ASRGs) revealed significant issues with regard to NCBI’s RefSeq bacterial genome assemblies related to completeness, mutations, structure, strain metadata, and gaps in traceability to the original biological source materials. Nearly half of RefSeq assemblies lack details on sample source information, sequencing technology, or bioinformatics methods. Deep curation of these records is not within the scope of NCBI’s core mission in supporting open science, which aims to collect sequence records that are submitted by the public. Nonetheless, we propose that gaps in metadata accuracy and data provenance represent an “elephant in the room” for microbial genomics research. Effectively addressing these issues will require raising the level of accountability for data depositors and acknowledging the need for higher expectations of quality among the researchers whose research depends on accurate and attributable reference genome data.

IMPORTANCE The traceability of microbial genomics data to authenticated physical biological materials is not a requirement for depositing these data into public genome databases. This creates significant risks for the reliability and data provenance of these important genomics research resources, the impact of which is not well understood. We sought to investigate this by carrying out a comparative genomics study of 1,113 ATCC standard reference genomes (ASRGs) produced by ATCC from authenticated and traceable materials using the latest sequencing technologies. We found widespread discrepancies in genome assembly quality, genetic variability, and the quality and completeness of the associated metadata among hundreds of reference genomes for ATCC strains found in NCBI’s RefSeq database. We present a comparative analysis of de novo-assembled ASRGs, their respective metadata, and variant analysis using RefSeq genomes as a reference. Although assembly quality in RefSeq has generally improved over time, we found that significant quality issues remain, especially as related to genomic data and metadata provenance. Our work highlights the importance of data authentication and provenance for the microbial genomics community, and underscores the risks of ignoring this issue in the future.

Transcriptional responses of Trichodesmium to natural inverse gradients of Fe and P availability

The filamentous diazotrophic cyanobacterium Trichodesmium is responsible for a significant fraction of marine di-nitrogen (N₂) fixation. Growth and distribution of Trichodesmium and other diazotrophs in the vast oligotrophic subtropical gyres is influenced by iron (Fe) and phosphorus (P) availability, while reciprocally influencing the biogeochemistry of these nutrients. Here we use observations across natural inverse gradients in Fe and P in the North Atlantic subtropical gyre (NASG) to demonstrate how Trichodesmium acclimates in situ to resource availability. Transcriptomic analysis identified progressive upregulation of known iron-stress biomarker genes with decreasing Fe availability, and progressive upregulation of genes involved in the acquisition of diverse P sources with decreasing P availability, while genes involved in N₂ fixation were upregulated at the intersection under moderate Fe and P availability. Enhanced N₂ fixation within the Fe and P co-stressed transition region was also associated with a distinct, consistent metabolic profile, including the expression of alternative photosynthetic pathways that potentially facilitate ATP generation required for N₂ fixation with reduced net oxygen production. The observed response of Trichodesmium to availability of both Fe and P supports suggestions that these biogeochemically significant organisms employ unique molecular, and thus physiological responses as adaptations to specifically exploit the Fe and P co-limited niche they construct.

Role of mobile genetic elements in the global dissemination of the carbapenem resistance gene blaNDM

The mobile resistance gene blaNDM encodes the NDM enzyme which hydrolyses carbapenems, a class of antibiotics used to treat some of the most severe bacterial infections. The blaNDM gene is globally distributed across a variety of Gram-negative bacteria on multiple plasmids, typically located within highly recombining and transposon-rich genomic regions, which leads to the dynamics underlying the global dissemination of blaNDM to remain poorly resolved. Here, we compile a dataset of over 6000 bacterial genomes harbouring the blaNDM gene, including 104 newly generated PacBio hybrid assemblies from clinical and livestock-associated isolates across China. We develop a computational approach to track structural variants surrounding blaNDM, which allows us to identify prevalent genomic contexts, mobile genetic elements, and likely events in the gene's global spread. We estimate that blaNDM emerged on a Tn125 transposon before 1985, but only reached global prevalence around a decade after its first recorded observation in 2005. The Tn125 transposon seems to have played an important role in early plasmid-mediated jumps of blaNDM, but was overtaken in recent years by other elements including IS26-flanked pseudo-composite transposons and Tn3000. We found a strong association between blaNDM-carrying plasmid backbones and the sampling location of isolates. This observation suggests that the global dissemination of the blaNDM gene was primarily driven by successive between-plasmid transposon jumps, with far more restricted subsequent plasmid exchange, possibly due to adaptation of plasmids to their specific bacterial hosts.

Long-term spatiotemporal variation of antimicrobial resistance genes within the Serratia marcescens population and transmission of S. marcescens revealed by public whole-genome datasets

The development of antimicrobial resistance (AMR) is accelerated by the selective pressure exerted by the widespread use of antimicrobial drugs, posing an increasing danger to public health. However, long-term spatiotemporal variation in AMR genes in microorganisms, particularly in bacterial pathogens in response to antibiotic consumption, is not fully understood. Here, we used the NCBI RefSeq database to collect 478 whole-genome sequences for Serratia marcescens ranging from 1961 up to 2019, to document global long-term AMR trends in S. marcescens populations. In total, 100 AMR gene subtypes (16 AMR gene types) were detected in the genomes of S. marcescens populations. We identified 3 core resistance genes in S. marcescens genomes, and a high diversity of AMR genes was observed in S. marcescens genomes after corresponding antibiotics were discovered and introduced into clinical practice, suggesting the adaptation of S. marcescens populations to challenges with therapeutic antibiotics. Our findings indicate spatiotemporal variation of AMR genes in S. marcescens populations in relation to antibiotic consumption and suggest the potential transmission of S. marcescens isolates harboring AMR genes among countries and between the environment and the clinic, representing a public health threat that necessitates international solidarity to overcome.

Microbiota of the prostate tumor environment investigated by whole-transcriptome profiling

Background

With over 350,000 estimated deaths worldwide in 2018, prostate cancer (PCa) continues to be a major health concern and a significant cause of cancer-associated mortality among men. While cancer in general is considered a disease of the human genome, there is a growing body of evidence suggesting that changes to the healthy microbiota could play a vital role in cancer development, progression, and/or treatment outcome.

Methods

Using a metatranscriptomic approach, we annotated the microbial reads obtained from total RNA sequencing of 106 prostate tissue samples from 94 PCa patients (discovery cohort). We investigated microbial dysbiosis associated with PCa by systematically comparing the microbiomes between benign and malignant tissue samples, between less vs. more-aggressive PCa, and between patients who had biochemical recurrence as opposed to those who did not. We further performed differential gene expression and cell type enrichment analysis to explore the host transcriptomic and cellular responses to selected microbial genera. A public dataset (GSE115414) of total RNA sequencing reads from 24 prostate tissue samples (8 benign and 16 malignant) served as the validation cohort.

Results

We observed decreased species diversity and significant under-representation of Staphylococcus saprophyticus and Vibrio parahaemolyticus, as well as significant over-abundance of Shewanella in malignant as compared to benign prostate tissue samples in both the discovery (p < 0.01) and validation (p < 0.05) cohorts. In addition, we identified Microbacterium species (p < 0.01) to be significantly over-abundant in pathologically advanced T3 tumors compared to T2 in the discovery cohort. Malignant samples having high vs. low Shewanella counts were associated with downregulated Toll-like receptor signaling pathways and decreased enrichment of dendritic cells. Malignant samples having low vs. high V. parahaemolyticus counts were enriched for olfactory transduction and drug metabolism pathways. Finally, malignant samples were enriched for M1 and M2 macrophages as compared to benign tissue samples.

Conclusions

The results from this exploratory study support the existence of an important biological link between the prostate microbiota and PCa development/progression. Our results highlight Shewanella, V. parahaemolyticus, and Microbacterium sp. as interesting candidates for further investigation of their association with PCa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01011-3.

Dysbiotic microbes and how to find them: a review of microbiome profiling in prostate cancer

The role of the microbiota in human health and disease is well established, including its effects on several cancer types. However, the role of microbial dysbiosis in prostate cancer development, progression, and response to treatment is less well understood. This knowledge gap could perhaps be implicated in the lack of better risk stratification and prognostic tools that incorporate risk factors such as bacterial infections and inflammatory signatures. With over a decade’s research investigating associations between microbiome and prostate carcinogenesis, we are ever closer to finding the crucial biological link between the two. Yet, definitive answers remain elusive, calling for continued research into this field. In this review, we outline the three frequently used NGS based analysis methodologies that are used for microbiome profiling, thereby serving as a quick guide for future microbiome research. We next provide a detailed overview of the current knowledge of the role of the human microbiome in prostate cancer development, progression, and treatment response. Finally, we describe proposed mechanisms of host-microbe interactions that could lead to prostate cancer development, progression or treatment response.

Extracting phylogenetic dimensions of coevolution reveals hidden functional signals

Despite the structural and functional information contained in the statistical coupling between pairs of residues in a protein, coevolution associated with function is often obscured by artifactual signals such as genetic drift, which shapes a protein's phylogenetic history and gives rise to concurrent variation between protein sequences that is not driven by selection for function. Here, we introduce a background model for phylogenetic contributions of statistical coupling that separates the coevolution signal due to inter-clade and intra-clade sequence comparisons and demonstrate that coevolution can be measured on multiple phylogenetic timescales within a single protein. Our method, nested coevolution (NC), can be applied as an extension to any coevolution metric. We use NC to demonstrate that poorly conserved residues can nonetheless have important roles in protein function. Moreover, NC improved the structural-contact predictions of several coevolution-based methods, particularly in subsampled alignments with fewer sequences. NC also lowered the noise in detecting functional sectors of collectively coevolving residues. Sectors of coevolving residues identified after application of NC were more spatially compact and phylogenetically distinct from the rest of the protein, and strongly enriched for mutations that disrupt protein activity. Thus, our conceptualization of the phylogenetic separation of coevolution provides the potential to further elucidate relationships among protein evolution, function, and genetic diseases.

Production of mannosylerythritol lipids: biosynthesis, multi-omics approaches, and commercial exploitation

Compilation of resources regarding MEL biosynthesis, key production parameters; available omics resources and current commercial applications, for smut fungi known to produce MELs.

Candida albicans Isolates 529L and CHN1 Exhibit Stable Colonization of the Murine Gastrointestinal Tract

Candida albicans is a pathobiont that colonizes multiple niches in the body including the gastrointestinal (GI) tract but is also responsible for both mucosal and systemic infections. Despite its prevalence as a human commensal, the murine GI tract is generally refractory to colonization with the C. albicans reference isolate SC5314. Here, we identify two C. albicans isolates, 529L and CHN1, that stably colonize the murine GI tract in three different animal facilities under conditions where SC5314 is lost from this niche. Analysis of the bacterial microbiota did not show notable differences among mice colonized with the three C. albicans strains. We compared the genotypes and phenotypes of these three strains and identified thousands of single nucleotide polymorphisms (SNPs) and multiple phenotypic differences, including their ability to grow and filament in response to nutritional cues. Despite striking filamentation differences under laboratory conditions, however, analysis of cell morphology in the GI tract revealed that the three isolates exhibited similar filamentation properties in this in vivo niche. Notably, we found that SC5314 is more sensitive to the antimicrobial peptide CRAMP, and the use of CRAMP-deficient mice modestly increased the ability of SC5314 to colonize the GI tract relative to CHN1 and 529L. These studies provide new insights into how strain-specific differences impact C. albicans traits in the host and advance CHN1 and 529L as relevant strains to study C. albicans pathobiology in its natural host niche. IMPORTANCE Understanding how fungi colonize the GI tract is increasingly recognized as highly relevant to human health. The animal models used to study Candida albicans commensalism commonly rely on altering the host microbiome (via antibiotic treatment or defined diets) to establish successful GI colonization by the C. albicans reference isolate SC5314. Here, we characterize two C. albicans isolates that can colonize the murine GI tract without antibiotic treatment and can therefore be used as tools for studying fungal commensalism. Importantly, experiments were replicated in three different animal facilities and utilized three different mouse strains. Differential colonization between fungal isolates was not associated with alterations in the bacterial microbiome but rather with distinct responses to CRAMP, a host antimicrobial peptide. This work emphasizes the importance of C. albicans intraspecies variation as well as host antimicrobial defense mechanisms in defining the outcome of commensal interactions.

Increase in antimicrobial resistance in Escherichia coli in food animals between 1980 and 2018 assessed using genomes from public databases

BACKGROUND

Next-generation sequencing has considerably increased the number of genomes available in the public domain. However, efforts to use these genomes for surveillance of antimicrobial resistance have thus far been limited and geographically heterogeneous. We inferred global resistance trends in Escherichia coli in food animals using genomes from public databases.

METHODS

We retrieved 7632 E. coli genomes from public databases (NCBI, PATRIC and EnteroBase) and screened for antimicrobial resistance genes (ARGs) using ResFinder. Selection bias towards resistance, virulence or specific strains was accounted for by screening BioProject descriptions. Temporal trends for MDR, resistance to antimicrobial classes and ARG prevalence were inferred using generalized linear models for all genomes, including those not subjected to selection bias.

RESULTS

MDR increased by 1.6 times between 1980 and 2018, as genomes carried, on average, ARGs conferring resistance to 2.65 antimicrobials in swine, 2.22 in poultry and 1.58 in bovines. Highest resistance levels were observed for tetracyclines (42.2%-69.1%), penicillins (19.4%-47.5%) and streptomycin (28.6%-56.6%). Resistance trends were consistent after accounting for selection bias, although lower mean absolute resistance estimates were associated with genomes not subjected to selection bias (difference of 3.16%±3.58% across years, hosts and antimicrobial classes). We observed an increase in extended-spectrum cephalosporin ARG blaCMY-2 and a progressive substitution of tetB by tetA. Estimates of resistance prevalence inferred from genomes in the public domain were in good agreement with reports from systematic phenotypic surveillance.

CONCLUSIONS

Our analysis illustrates the potential of using the growing volume of genomes in public databases to track AMR trends globally.

Draft Genome Sequence of a Basidiomycetous Yeast, Ustilago shanxiensis CBS 10075, Which Produces Mannosylerythritol Lipids

The basidiomycetous yeast Ustilago shanxiensis CBS 10075, which was isolated from a wilting leaf in China, produces mannosylerythritol lipid (MEL) biosurfactants. Here, we report the draft genome sequence of U. shanxiensis CBS 10075, which was 21.7 Mbp in size, with a GC content of 52.55%, comprising 65 scaffolds.

Salinity Drives Functional and Taxonomic Diversities in Global Water Metagenomes

A tight association between microbial function and taxonomy is the basis of functional prediction based on taxonomy, but such associations have been controversial in water biomes largely due to the probable prevalence of functional redundancy. However, previous studies on this topic used a relatively coarse resolution of ecosystem functioning, potentially inflating the estimated functional redundancy. Thus, a comprehensive evaluation of the association between high-resolution functional traits and taxonomic diversity obtained from fresh and saline water metagenomic data is urgently needed. Here, we examined 938 functionally and taxonomically annotated water metagenomes obtained worldwide to scrutinize the connection between function and taxonomy, and to identify the key driver of water metagenomes function or taxonomic composition at a global scale. We found that pairwise similarity of function was significantly associated with taxonomy, though taxonomy had higher global dissimilarity than function. Classification into six water biomes resulted in greater variation in taxonomic compositions than functional profiles, as the key regulating factor was salinity. Fresh water microbes harbored distinct functional and taxonomic structures from microbes in saline water biomes, despite that taxonomy was more susceptible to gradient of geography and climate than function. In summary, our results find a significant relationship between taxonomic diversity and microbial functioning in global water metagenomes, although microbial taxonomic compositions vary to a larger extent than functional profiles in aquatic ecosystems, suggesting the possibility and necessity for functional prediction of microorganisms based on taxonomy in global aquatic ecosystems.

Ancestral sequences of a large promiscuous enzyme family correspond to bridges in sequence space in a network representation

Evolutionary relationships of protein families can be characterized either by networks or by trees. Whereas trees allow for hierarchical grouping and reconstruction of the most likely ancestral sequences, networks lack a time axis but allow for thresholds of pairwise sequence identity to be chosen and, therefore, the clustering of family members with presumably more similar functions. Here, we use the large family of arylsulfatases and phosphonate monoester hydrolases to investigate similarities, strengths and weaknesses in tree and network representations. For varying thresholds of pairwise sequence identity, values of betweenness centrality and clustering coefficients were derived for nodes of the reconstructed ancestors to measure the propensity to act as a bridge in a network. Based on these properties, ancestral protein sequences emerge as bridges in protein sequence networks. Interestingly, many ancestral protein sequences appear close to extant sequences. Therefore, reconstructed ancestor sequences might also be interpreted as yet-to-be-identified homologues. The concept of ancestor reconstruction is compared to consensus sequences, too. It was found that hub sequences in a network, e.g. reconstructed ancestral sequences that are connected to many neighbouring sequences, share closer similarity with derived consensus sequences. Therefore, some reconstructed ancestor sequences can also be interpreted as consensus sequences.

Structure-Aware Mycobacterium tuberculosis Functional Annotation Uncloaks Resistance, Metabolic, and Virulence Genes

Accurate and timely functional genome annotation is essential for translating basic pathogen research into clinically impactful advances. Here, through literature curation and structure-function inference, we systematically update the functional genome annotation of Mycobacterium tuberculosis virulent type strain H37Rv. First, we systematically curated annotations for 589 genes from 662 publications, including 282 gene products absent from leading databases. Second, we modeled 1,711 underannotated proteins and developed a semiautomated pipeline that captured shared function between 400 protein models and structural matches of known function on Protein Data Bank, including drug efflux proteins, metabolic enzymes, and virulence factors. In aggregate, these structure- and literature-derived annotations update 940/1,725 underannotated H37Rv genes and generate hundreds of functional hypotheses. Retrospectively applying the annotation to a recent whole-genome transposon mutant screen provided missing function for 48% (13/27) of underannotated genes altering antibiotic efficacy and 33% (23/69) required for persistence during mouse tuberculosis (TB) infection. Prospective application of the protein models enabled us to functionally interpret novel laboratory generated pyrazinamide (PZA)-resistant mutants of unknown function, which implicated the emerging coenzyme A depletion model of PZA action in the mutants’ PZA resistance. Our findings demonstrate the functional insight gained by integrating structural modeling and systematic literature curation, even for widely studied microorganisms. Functional annotations and protein structure models are available at https://tuberculosis.sdsu.edu/H37Rv in human- and machine-readable formats.

IMPORTANCEMycobacterium tuberculosis, the primary causative agent of tuberculosis, kills more humans than any other infectious bacterium. Yet 40% of its genome is functionally uncharacterized, leaving much about the genetic basis of its resistance to antibiotics, capacity to withstand host immunity, and basic metabolism yet undiscovered. Irregular literature curation for functional annotation contributes to this gap. We systematically curated functions from literature and structural similarity for over half of poorly characterized genes, expanding the functionally annotated Mycobacterium tuberculosis proteome. Applying this updated annotation to recent in vivo functional screens added functional information to dozens of clinically pertinent proteins described as having unknown function. Integrating the annotations with a prospective functional screen identified new mutants resistant to a first-line TB drug, supporting an emerging hypothesis for its mode of action. These improvements in functional interpretation of clinically informative studies underscore the translational value of this functional knowledge. Structure-derived annotations identify hundreds of high-confidence candidates for mechanisms of antibiotic resistance, virulence factors, and basic metabolism and other functions key in clinical and basic tuberculosis research. More broadly, they provide a systematic framework for improving prokaryotic reference annotations.

Multidrug Resistance Dynamics in Salmonella in Food Animals in the United States: An Analysis of Genomes from Public Databases

The number of bacterial genomes deposited each year in public databases is growing exponentially. However, efforts to use these genomes to track trends in antimicrobial resistance (AMR) have been limited thus far. We used 22,102 genomes from public databases to track AMR trends in nontyphoidal Salmonella in food animals in the United States. In 2018, genomes deposited in public databases carried genes conferring resistance, on average, to 2.08 antimicrobial classes in poultry, 1.74 in bovines, and 1.28 in swine. This represents a decline in AMR of over 70% compared to the levels in 2000 in bovines and swine, and an increase of 13% for poultry. Trends in resistance inferred from genomic data showed good agreement with U.S. phenotypic surveillance data (weighted mean absolute difference ± standard deviation, 5.86% ± 8.11%). In 2018, resistance to 3rd-generation cephalosporins in bovines, swine, and poultry decreased to 9.97% on average, whereas in quinolones and 4th-generation cephalosporins, resistance increased to 12.53% and 3.87%, respectively. This was concomitant with a decrease of bla_CMY-2 but an increase in bla_CTX-M-65 and gyrA D87Y (encoding a change of D to Y at position 87). Core genome single-nucleotide polymorphism (SNP) phylogenies show that resistance to these antimicrobial classes was predominantly associated with Salmonella enterica serovar Infantis and, to a lesser extent, S. enterica serovar Typhimurium and its monophasic variant I 4,[5],12:i:−, whereas quinolone resistance was also associated with S. enterica serovar Dublin. Between 2000 and 2018, trends in serovar prevalence showed a composition shift where S. Typhimurium decreased while S. Infantis increased. Our findings illustrate the growing potential of using genomes in public databases to track AMR in regions where sequencing capacities are currently expanding.

IMPORTANCE Next-generation sequencing has led to an exponential increase in the number of genomes deposited in public repositories. This growing volume of information presents opportunities to track the prevalence of genes conferring antimicrobial resistance (AMR), a growing threat to the health of humans and animals. Using 22,102 public genomes, we estimated that the prevalence of multidrug resistance (MDR) in the United States decreased in nontyphoidal Salmonella isolates recovered from bovines and swine between 2000 and 2018, whereas it increased in poultry. These trends are consistent with those detected by national surveillance systems that monitor resistance using phenotypic testing. However, using genomes, we identified that genes conferring resistance to critically important antimicrobials were associated with specific MDR serovars that could be the focus for future interventions. Our analysis illustrates the growing potential of public repositories to monitor AMR trends and shows that similar efforts could soon be carried out in other regions where genomic surveillance is increasing.

Stable Soil Microbial Functional Structure Responding to Biodiversity Loss Based on Metagenomic Evidences

Anthropogenic disturbances and global climate change are causing large-scale biodiversity loss and threatening ecosystem functions. However, due to the lack of knowledge on microbial species loss, our understanding on how functional profiles of soil microbes respond to diversity decline is still limited. Here, we evaluated the biotic homogenization of global soil metagenomic data to examine whether microbial functional structure is resilient to significant diversity reduction. Our results showed that although biodiversity loss caused a decrease in taxonomic species by 72%, the changes in the relative abundance of diverse functional categories were limited. The stability of functional structures associated with microbial species richness decline in terrestrial systems suggests a decoupling of taxonomy and function. The changes in functional profile with biodiversity loss were function-specific, with broad-scale metabolism functions decreasing and typical nutrient-cycling functions increasing. Our results imply high levels of microbial physiological versatility in the face of significant biodiversity decline, which, however, does not necessarily mean that a loss in total functional abundance, such as microbial activity, can be overlooked in the background of unprecedented species extinction.

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns

Despite the wide perception that microbes have rapid growth rates, many environments like seawater and soil are often dominated by microorganisms that can only grow very slowly. Our knowledge about growth is necessarily biased toward easily culturable organisms, which tend to be those that grow fast, because microbial growth rates have traditionally been measured using laboratory growth experiments. However, how are potential growth rates distributed in nature? Using genomic data, we predicted the growth rates of over 200,000 organisms, including many as yet uncultivated species. These data reveal how current culture collections are strongly biased toward fast-growing organisms. Finally, we noticed a bimodal distribution of maximal growth rates, suggesting a natural division of microbial growth strategies into two classes.

Maximal growth rate is a basic parameter of microbial lifestyle that varies over several orders of magnitude, with doubling times ranging from a matter of minutes to multiple days. Growth rates are typically measured using laboratory culture experiments. Yet, we lack sufficient understanding of the physiology of most microbes to design appropriate culture conditions for them, severely limiting our ability to assess the global diversity of microbial growth rates. Genomic estimators of maximal growth rate provide a practical solution to survey the distribution of microbial growth potential, regardless of cultivation status. We developed an improved maximal growth rate estimator and predicted maximal growth rates from over 200,000 genomes, metagenome-assembled genomes, and single-cell amplified genomes to survey growth potential across the range of prokaryotic diversity; extensions allow estimates from 16S rRNA sequences alone as well as weighted community estimates from metagenomes. We compared the growth rates of cultivated and uncultivated organisms to illustrate how culture collections are strongly biased toward organisms capable of rapid growth. Finally, we found that organisms naturally group into two growth classes and observed a bias in growth predictions for extremely slow-growing organisms. These observations ultimately led us to suggest evolutionary definitions of oligotrophy and copiotrophy based on the selective regime an organism occupies. We found that these growth classes are associated with distinct selective regimes and genomic functional potentials.

Blockage of bacterial FimH prevents mucosal inflammation associated with Crohn's disease

BACKGROUND

An Escherichia coli (E. coli) pathotype with invasive properties, first reported by Darfeuille-Michaud and termed adherent-invasive E. coli (AIEC), was shown to be prevalent in up to half the individuals with Crohn's Disease (CD), suggesting that these bacteria could be involved in the pathophysiology of CD. Among the genes related to AIEC pathogenicity, fim has the potential to generate an inflammatory reaction from the intestinal epithelial cells and macrophages, as it interacts with TLR4, inducing the production of inflammatory cytokines independently of LPS. Therefore, targeting the bacterial adhesion of FimH-expressing bacteria seems a promising therapeutic approach, consisting of disarming bacteria without killing them, representing a selective strategy to suppress a potentially critical trigger of intestinal inflammation, without disturbing the intestinal microbiota.

RESULTS

We analyzed the metagenomic composition of the gut microbiome of 358 patients with CD from two different cohorts and characterized the presence of FimH-expressing bacteria. To assess the pathogenic role of FimH, we used human intestinal explants and tested a specific FimH blocker to prevent bacterial adhesion and associated inflammation. We observed a significant and disease activity-dependent enrichment of Enterobacteriaceae in the gut microbiome of patients with CD. Bacterial FimH expression was functionally confirmed in ileal biopsies from 65% of the patients with CD. Using human intestinal explants, we further show that FimH is essential for adhesion and to trigger inflammation. Finally, a specific FimH-blocker, TAK-018, inhibits bacterial adhesion to the intestinal epithelium and prevents inflammation, thus preserving mucosal integrity.

CONCLUSIONS

We propose that TAK-018, which is safe and well tolerated in humans, is a promising candidate for the treatment of CD and in particular in preventing its recurrence. Video abstract.

Plastic waste: Status, degradation and microbial management options for Africa

This paper presents a review of synthetic polymer (notably plastic) wastes profiles in Africa, their current management status, and better options. Data revealed that of the approximated 86.14 million metric tonnes and 31.5 million metric tonnes of primary polymers and plastics, respectively, and an estimated 230 million metric tonnes of plastic components imported between 1990 and 2017, about 17 million metric tonnes are mismanaged. Leading African nations on the plastic wastes generator table in increasing order are Tunisia (6.9%), Morocco (9.6%), Algeria (11.2%), South Africa (11.6%), Nigeria (16.9%), and the chief is Egypt (18.4%). The volume of plastic wastes generated in Africa directly correlates with her increasing population status, however, the current treatment options have major drawbacks (high energy and technological input, high demand for space, and creation of obnoxious by-products). Ineffective regulations, poor monitoring, and slow adoption of veritable practices by governments are responsible for the steady increase in plastic volume in the African landscapes and environments. In Nigeria, only about 9% and 12% of the total generated wastes are recycled and incinerated. The remainder bulk is either discarded into waste dumps (and a few available landfills) or natural environments. There is a paucity of standard plastic biodegradative work by African scientists, and only a few works show detection of competent synthetic plastic degrading microbes globally. Asides from the ills of possible omission of core degraders, there is a need for researchers to follow standard degradation procedures to arrive at efficient, reproducible, and generally accepted outcomes utilizable on a larger scale. Thus, metagenomic search on the vast African urban and rural plastisphere is the best isolation option.

Analysis on the prokaryotic microbiome in females and embryonic cell cultures of Rhipicephalus sanguineus tropical and temperate lineages from two specific localities in Brazil

Two lineages of Rhipicephalus sanguineus are known in Brazil: the temperate or southern and the tropical or northern populations. The distribution patterns of both lineages of R. sanguineus have epidemiological implications that can affect vectorial competence concerning Ehrlichia canis, the agent of canine monocytic ehrlichiosis. Intending to identify the microbiomes of both lineages and compare microorganisms in R. sanguineus, we used the 16S rRNA (V4-V5 region) gene-based metataxonomic approach, through NGS sequencing on the MiSeq Illumina platform. We selected specimens of females from the environment and samples of primary embryonic cell cultures, from both lineages, and this was the first study to investigate the prokaryotic microbiome in tick cell cultures. The results showed that many bacterial taxa detected in the samples were typical members of the host environment. A significant diversity of microorganisms in R. sanguineus females and in embryonic cell cultures from both lineages was found, with emphasis on the presence of Coxiella in all samples, albeit in different proportions. The Coxiella species present in the two lineages of ticks may be different and may have co-evolved with them, thus driving different patterns of interactions between ticks and the pathogens that they can harbor or transmit to vertebrate hosts.

Approximate search for known gene clusters in new genomes using PQ-trees

Gene clusters are groups of genes that are co-locally conserved across various genomes, not necessarily in the same order. Their discovery and analysis is valuable in tasks such as gene annotation and prediction of gene interactions, and in the study of genome organization and evolution. The discovery of conserved gene clusters in a given set of genomes is a well studied problem, but with the rapid sequencing of prokaryotic genomes a new problem is inspired. Namely, given an already known gene cluster that was discovered and studied in one genomic dataset, to identify all the instances of the gene cluster in a given new genomic sequence. Thus, we define a new problem in comparative genomics, denoted PQ-Tree Search that takes as input a PQ-tree T representing the known gene orders of a gene cluster of interest, a gene-to-gene substitution scoring function h, integer arguments \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_T$$\end{document}dT and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_S$$\end{document}dS, and a new sequence of genes S. The objective is to identify in S approximate new instances of the gene cluster; These instances could vary from the known gene orders by genome rearrangements that are constrained by T, by gene substitutions that are governed by h, and by gene deletions and insertions that are bounded from above by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_T$$\end{document}dT and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_S$$\end{document}dS, respectively. We prove that PQ-Tree Search is NP-hard and propose a parameterized algorithm that solves the optimization variant of PQ-Tree Search in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$O^*(2^{\gamma })$$\end{document}O∗(2γ) time, where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma$$\end{document}γ is the maximum degree of a node in T and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$O^*$$\end{document}O∗ is used to hide factors polynomial in the input size. The algorithm is implemented as a search tool, denoted PQFinder, and applied to search for instances of chromosomal gene clusters in plasmids, within a dataset of 1,487 prokaryotic genomes. We report on 29 chromosomal gene clusters that are rearranged in plasmids, where the rearrangements are guided by the corresponding PQ-trees. One of these results, coding for a heavy metal efflux pump, is further analysed to exemplify how PQFinder can be harnessed to reveal interesting new structural variants of known gene clusters.

Comparative Genomics of Closely Related Tetragenococcus halophilus Strains Elucidate the Diversity and Microevolution of CRISPR Elements

Tetragenococcus halophilus – a halophilic lactic acid bacterium – is frequently used as a starter culture for manufacturing fermented foods. Tetragenococcus is sometimes infected with bacteriophages during fermentation for soy sauce production; however, bacteriophage infection in starter bacteria is one of the major causes of fermentation failure. Here, we obtained whole-genome sequences of the four T. halophilus strains YA5, YA163, YG2, and WJ7 and compared them with 18 previously reported genomes. We elucidated five types of clustered regularly interspaced short palindromic repeat (CRISPR) loci in seven genomes using comparative genomics with a particular focus on CRISPR elements. CRISPR1 was conserved in the four closely related strains 11, YA5, YA163, and YG2, and the spacer sequences were partially retained in each strain, suggesting that partial deletions and accumulation of spacer sequences had occurred independently after divergence of each strain. The host range for typical bacteriophages is narrow and strain-specific thus these accumulation/deletion events may be responsible for differences in resistance to bacteriophages between bacterial strains. Three CRISPR elements, CRISPR1 in strains 11, YA5, YA163, and YG2, CRISPR2 in strain WJ7, and CRISPR2 in strain MJ4, were inserted in almost the same genomic regions, indicating that several independent insertions had occurred in this region. As these elements belong to class 1 type I-C CRISPR group, the results suggested that this site is a hotspot for class 1, type I-C CRISPR loci insertion. Thus, T. halophilus genomes may have acquired strain-specific bacteriophage-resistance through repeated insertion of CRISPR loci and accumulation/deletion events of their spacer sequences.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.

Heterogenous Susceptibility to R-Pyocins in Populations of Pseudomonas aeruginosa Sourced from Cystic Fibrosis Lungs

Bacteriocins are proteinaceous antimicrobials produced by bacteria that are active against other strains of the same species. R-type pyocins are phage tail-like bacteriocins produced by Pseudomonas aeruginosa Due to their antipseudomonal activity, R-pyocins have potential as therapeutics in infection. P. aeruginosa is a Gram-negative opportunistic pathogen and is particularly problematic for individuals with cystic fibrosis (CF). P. aeruginosa organisms from CF lung infections develop increasing resistance to antibiotics, making new treatment approaches essential. P. aeruginosa populations become phenotypically and genotypically diverse during infection; however, little is known of the efficacy of R-pyocins against heterogeneous populations. R-pyocins vary by subtype (R1 to R5), distinguished by binding to different residues on the lipopolysaccharide (LPS). Each type varies in killing spectrum, and each strain produces only one R-type. To evaluate the prevalence of different R-types, we screened P. aeruginosa strains from the International Pseudomonas Consortium Database (IPCD) and from our biobank of CF strains. We found that (i) R1-types were the most prevalent R-type among strains from respiratory sources, (ii) a large number of strains lack R-pyocin genes, and (iii) isolates collected from the same patient have the same R-type. We then assessed the impact of intrastrain diversity on R-pyocin susceptibility and found a heterogenous response to R-pyocins within populations, likely due to differences in the LPS core. Our work reveals that heterogeneous populations of microbes exhibit variable susceptibility to R-pyocins and highlights that there is likely heterogeneity in response to other types of LPS-binding antimicrobials, including phage.IMPORTANCE R-pyocins have potential as alternative therapeutics against Pseudomonas aeruginosa in chronic infection; however, little is known about the efficacy of R-pyocins in heterogeneous bacterial populations. P. aeruginosa is known to become resistant to multiple antibiotics and to evolve phenotypic and genotypic diversity over time; thus, it is particularly difficult to eradicate in chronic cystic fibrosis (CF) lung infections. In this study, we found that P. aeruginosa populations from CF lungs maintain the same R-pyocin genotype but exhibit heterogeneity in susceptibility to R-pyocins from other strains. Our findings suggest there is heterogeneity in response to other types of LPS-binding antimicrobials, such as phage, highlighting the necessity of further studying the potential of LPS-binding antimicrobial particles as alternative therapies in chronic infections.

Biotechnological and Ecological Potential of Micromonospora provocatoris sp. nov., a Gifted Strain Isolated from the Challenger Deep of the Mariana Trench

A Micromonospora strain, isolate MT25^T, was recovered from a sediment collected from the Challenger Deep of the Mariana Trench using a selective isolation procedure. The isolate produced two major metabolites, n-acetylglutaminyl glutamine amide and desferrioxamine B, the chemical structures of which were determined using 1D and 2D-NMR, including ¹H-¹⁵N HSQC and ¹H-¹⁵N HMBC 2D-NMR, as well as high resolution MS. A whole genome sequence of the strain showed the presence of ten natural product-biosynthetic gene clusters, including one responsible for the biosynthesis of desferrioxamine B. Whilst 16S rRNA gene sequence analyses showed that the isolate was most closely related to the type strain of Micromonospora chalcea, a whole genome sequence analysis revealed it to be most closely related to Micromonospora tulbaghiae 45142^T. The two strains were distinguished using a combination of genomic and phenotypic features. Based on these data, it is proposed that strain MT25^T (NCIMB 15245^T, TISTR 2834^T) be classified as Micromonospora provocatoris sp. nov. Analysis of the genome sequence of strain MT25^T (genome size 6.1 Mbp) revealed genes predicted to responsible for its adaptation to extreme environmental conditions that prevail in deep-sea sediments.

Genomics as a potential tool to unravel the rhizosphere microbiome interactions on plant health

Intense agricultural practices to meet rising food demands have caused ecosystem perturbations. For sustainable crop production, biological agents are gaining attention, but exploring their functional potential on a multi-layered complex ecosystem like the rhizosphere is challenging. This review explains the significance of genomics as a culture-independent molecular tool to understand the diversity and functional significance of the rhizosphere microbiome for sustainable agriculture. It discusses the recent significant studies in the rhizosphere environment carried out using evolving techniques like metagenomics, metatranscriptomics, and metaproteomics, their challenges, constraints infield application, and prospective solutions. The recent advances in techniques such as nanotechnology for the development of bioformulations and visualization techniques contemplating environmental safety were also discussed. The need for development of metagenomic data sets of regionally important crops, their plant microbial interactions and agricultural practices for narrowing down significant data from huge databases have been suggested. The role of taxonomical and functional diversity of soil microbiota in understanding soil suppression and part played by the microbial metabolites in the process have been analyzed and discussed in the context of 'omics' approach. 'Omics' studies have revealed important information about microbial diversity, their responses to various biotic and abiotic stimuli, and the physiology of disease suppression. This can be translated to crop sustainability and combinational approaches with advancing visualization and analysis methodologies fix the existing knowledge gap to a huge extend. With improved data processing and standardization of the methods, details of plant-microbe interactions can be successfully decoded to develop sustainable agricultural practices.

A comprehensive metagenomics framework to characterize organisms relevant for planetary protection

BACKGROUND

Clean rooms of the Space Assembly Facility (SAF) at the Jet Propulsion Laboratory (JPL) at NASA are the final step of spacecraft cleaning and assembly before launching into space. Clean rooms have stringent methods of air-filtration and cleaning to minimize microbial contamination for exoplanetary research and minimize the risk of human pathogens, but they are not sterile. Clean rooms make a selective environment for microorganisms that tolerate such cleaning methods. Previous studies have attempted to characterize the microbial cargo through sequencing and culture-dependent protocols. However, there is not a standardized metagenomic workflow nor analysis pipeline for spaceflight hardware cleanroom samples to identify microbial contamination. Additionally, current identification methods fail to characterize and profile the risk of low-abundance microorganisms.

RESULTS

A comprehensive metagenomic framework to characterize microorganisms relevant for planetary protection in multiple cleanroom classifications (from ISO-5 to ISO-8.5) and sample types (surface, filters, and debris collected via vacuum devices) was developed. Fifty-one metagenomic samples from SAF clean rooms were sequenced and analyzed to identify microbes that could potentially survive spaceflight based on their microbial features and whether the microbes expressed any metabolic activity or growth. Additionally, an auxiliary testing was performed to determine the repeatability of our techniques and validate our analyses. We find evidence that JPL clean rooms carry microbes with attributes that may be problematic in space missions for their documented ability to withstand extreme conditions, such as psychrophilia and ability to form biofilms, spore-forming capacity, radiation resistance, and desiccation resistance. Samples from ISO-5 standard had lower microbial diversity than those conforming to ISO-6 or higher filters but still carried a measurable microbial load.

CONCLUSIONS

Although the extensive cleaning processes limit the number of microbes capable of withstanding clean room condition, it is important to quantify thresholds and detect organisms that can inform ongoing Planetary Protection goals, provide a biological baseline for assembly facilities, and guide future mission planning. Video Abstract.

The Phosin PptA Plays a Negative Role in the Regulation of Antibiotic Production in Streptomyces lividans

In Streptomyces, antibiotic biosynthesis is triggered in phosphate limitation that is usually correlated with energetic stress. Polyphosphates constitute an important reservoir of phosphate and energy and a better understanding of their role in the regulation of antibiotic biosynthesis is of crucial importance. We previously characterized a gene, SLI_4384/ppk, encoding a polyphosphate kinase, whose disruption greatly enhanced the weak antibiotic production of Streptomyces lividans. In the condition of energetic stress, Ppk utilizes polyP as phosphate and energy donor, to generate ATP from ADP. In this paper, we established that ppk is co-transcribed with its two downstream genes, SLI_4383, encoding a phosin called PptA possessing a CHAD domain constituting a polyphosphate binding module and SLI_4382 encoding a nudix hydrolase. The expression of the ppk/pptA/SLI_4382 operon was shown to be under the positive control of the two-component system PhoR/PhoP and thus mainly expressed in condition of phosphate limitation. However, pptA and SLI_4382 can also be transcribed alone from their own promoter. The deletion of pptA resulted into earlier and stronger actinorhodin production and lower lipid content than the disruption of ppk, whereas the deletion of SLI_4382 had no obvious phenotypical consequences. The disruption of ppk was shown to have a polar effect on the expression of pptA, suggesting that the phenotype of the ppk mutant might be linked, at least in part, to the weak expression of pptA in this strain. Interestingly, the expression of phoR/phoP and that of the genes of the pho regulon involved in phosphate supply or saving were strongly up-regulated in pptA and ppk mutants, revealing that both mutants suffer from phosphate stress. Considering the presence of a polyphosphate binding module in PptA, but absence of similarities between PptA and known exo-polyphosphatases, we proposed that PptA constitutes an accessory factor for exopolyphosphatases or general phosphatases involved in the degradation of polyphosphates into phosphate.

Rapid transcriptional and metabolic adaptation of intestinal microbes to host immune activation

The gut microbiota produces metabolites that regulate host immunity, thereby impacting disease resistance and susceptibility. The extent to which commensal bacteria reciprocally respond to immune activation, however, remains largely unexplored. Herein, we colonized mice with four anaerobic symbionts and show that acute immune responses result in dramatic transcriptional reprogramming of these commensals with minimal changes in their relative abundance. Transcriptomic changes include induction of stress-response mediators and downregulation of carbohydrate-degrading factors such as polysaccharide utilization loci (PULs). Flagellin and anti-CD3 antibody, two distinct immune stimuli, induced similar transcriptional profiles, suggesting that commensal bacteria detect common effectors or activate shared pathways when facing different host responses. Immune activation altered the intestinal metabolome within 6 hours, decreasing luminal short-chain fatty acid and increasing aromatic metabolite concentrations. Thus, intestinal bacteria, prior to detectable shifts in community composition, respond to acute host immune activation by rapidly changing gene transcription and immunomodulatory metabolite production.

Gut microbiota profiles and fecal beta-glucuronidase activity in kidney transplant recipients with and without post-transplant diarrhea

Post-transplant diarrhea is a common complication after solid organ transplantation and is frequently attributed to the widely prescribed immunosuppressant mycophenolate mofetil (MMF). Given recent work identifying the relationship between MMF toxicity and gut bacterial β-glucuronidase activity, we evaluated the relationship between gut microbiota composition, fecal β-glucuronidase activity, and post-transplant diarrhea. We recruited 97 kidney transplant recipients and profiled the gut microbiota in 273 fecal specimens using 16S rRNA gene sequencing. We further characterized fecal β-glucuronidase activity in a subset of this cohort. Kidney transplant recipients with post-transplant diarrhea had decreased gut microbial diversity and decreased relative gut abundances of 12 genera when compared to those without post-transplant diarrhea (adjusted p value < .15, Wilcoxon rank sum test). Among the kidney transplant recipients with post-transplant diarrhea, those with higher fecal β-glucuronidase activity had a more prolonged course of diarrhea (≥7 days) compared to patients with lower fecal β-glucuronidase activity (91% vs 40%, p = .02, Fisher's exact test). Our data reveal post-transplant diarrhea as a complex phenomenon with decreased gut microbial diversity and commensal gut organisms. This study further links commensal bacterial metabolism with an important clinical outcome measure, suggesting fecal β-glucuronidase activity could be a novel biomarker for gastrointestinal-related MMF toxicity.