Phylogenies of the 16S rRNA gene and its hypervariable regions lack concordance with core genome phylogenies

Screening, molecular identification, and evaluation the effects of indigenous Plant Growth-Promoting Rhizobacteria on growth indices and nutrient uptake of chamomile (Matricaria chamomilla) under saline conditions

Introduction

Salinity is a major issue affecting agricultural lands, leading to reduced crop productivity and soil degradation. One approach to mitigate the effects of salinity is utilizing PGPR. This study aimed to isolate and identify indigenous PGPR from rhizosphere soil and evaluate their effects on the growth indices of chamomile under saline conditions.

Methods

Forty-five rhizosphere soil samples were collected from agricultural fields in Beyram, Iran. The PGPR were isolated and identified using standard phenotypic, biochemical, and molecular assays. Plant growth-promoting traits were applied for PGPR strain screening. The effects of selected PGPR strains on the growth indices and nutrient uptake of chamomile under saline conditions were evaluated in a greenhouse experiment.

Results and discussion

A total of 181 bacterial isolates were identified from the 45 soil samples, belonging to eight genera and 13 species. Seven species, including B. cereus, P. fluorescens, P. syringae, A. radiotolerans, P. phenanthrenivorans, P. alcaliphila, and L. macroides, possessing all five growth-promoting characteristics, were selected for further experiments. PGPR treatments significantly improved chamomile's growth, biochemical parameters, and nutrient uptake under different salinity levels. The P1 treatment at 2 dS.m-1 salinity had the highest root (16.75 cm) and shoot length (32.91 cm), along with dry root (0.089 g) and shoot weight (1.67 g). Biochemical improvements included higher chlorophyll and essential oil content with P2 at 2 dS.m-1. Increased salinity decreased overall plant growth and nutrient uptake. The indigenous PGPR strains showed promising potential to enhance chamomile growth and nutrient status under salt stress, offering a sustainable strategy for improving crop productivity in saline-affected regions.

Design and validation of universal and taxon-specific 16S rRNA qPCR primers for detection of freshwater harmful algal bloom-forming cyanobacteria

Freshwater harmful algal bloom-forming cyanobacteria have become an increasingly prominent global concern from both environmental and human health perspectives. To enable and facilitate timely decision making in taking preventative and mitigative measures, rapid, accurate, sensitive and quantitative tools are needed for the detection and monitoring of toxin-producing cyanobacteria. Here we report the development of taxon-specific quantitative polymerase chain reaction (qPCR) primers capable of distinguishing 10 cyanobacterial genera or clade from non-target groups as well as a new set of universal primers capable of amplifying all cyanobacteria species. When evaluated by 4 stringent metrics and primer-template mismatches, these de novo designed qPCR primers outperformed published primers in amplifying the 16S rRNA gene of their target strains among the collection of 16 in-house cyanobacterial strains belonging to 10 genera. The 10 best-performing designed primers were validated using field samples from three field locations with historically documented HAB events. The field validation results corroborated with both microscopic observations and Nanopore sequencing of full-length 16S amplicons. Our study demonstrated the effectiveness of our design-screen-evaluation-validation pipeline in developing taxon-specific qPCR primers for detecting and quantifying group-specific target populations and their promising application to field HABs samples. With the advancement of massive parallel sequencing technologies and bioinformatic tools, a community-wide 16S full-length sequencing run can provide a panoramic view of the genetic diversity and site-specific variant info about the target taxa of interest, enabling the fast development of new taxon-specific qPCR assays and their refinement or modification to adapt to site-specific genetic variations in field samples.

Antimicrobial and anticancer activity of Streptomyces ambofaciens (Myt 8) and S. globisporus ONU 1019 (Myt 11) secondary metabolites isolated from the Odesa Bay, the Black Sea: An in vitro study

We investigated the antimicrobial and anticancer capacity of secondary metabolites from six strains of marine actinobacteria belonging to the genus Streptomyces. Bacteria strains were isolated from the Black Sea and identified using 16S rRNA gene sequencing. Exometabolites were extracted using ethyl acetate. Antagonistic activity was investigated by agar block-diffusion method against ten strains of indicator microorganisms. The anticancer activities of the extracts were assessed on murine cholangiocarcinoma (CCA) cells while normal mouse fibroblasts CBA-310 served as a control. The extracts were tested as monotherapy or in combination with a standard chemotherapeutic drug for CCA, gemcitabine. Cell proliferation and viability were assessed using crystal violet and cell counting kit-8 assays. The induction of cellular senescence was investigated by senescence-associated β-galactosidase assay. Fluorescence-activated cell sorting analysis was used to determine cellular apoptosis and necroptosis. Liquid chromatography-mass spectrometry (LC-MS/MS) analysis was used to define the main players in the extracts. Streptomyces strains showed antagonistic activity against at least one indicator microorganism. Two extracts, S. ambofaciens (Myt 8) and S. globisporus ONU 1019 (Myt 11), displayed anticancer activity. Extracts Myt 8 and Myt 11 alone or in combination with low doses of gemcitabine inhibited CCA cells in a time and dose-dependent manner and induced early apoptosis and cellular senescence. LC-MS/MS analysis identified daidzein, germicidin, staurosporine alpha-curcumene, and alpha-calacorene - with potential antibacterial and anticancer effects. Streptomyces extracts showed antimicrobial and anticancer properties, potentially reducing chemotherapy doses for CCA. These findings suggest a dual therapeutic role against infections and CCA, warranting further in vivo studies.

Advanced computational tools, artificial intelligence and machine-learning approaches in gut microbiota and biomarker identification

The microbiome of the gut is a complex ecosystem that contains a wide variety of microbial species and functional capabilities. The microbiome has a significant impact on health and disease by affecting endocrinology, physiology, and neurology. It can change the progression of certain diseases and enhance treatment responses and tolerance. The gut microbiota plays a pivotal role in human health, influencing a wide range of physiological processes. Recent advances in computational tools and artificial intelligence (AI) have revolutionized the study of gut microbiota, enabling the identification of biomarkers that are critical for diagnosing and treating various diseases. This review hunts through the cutting-edge computational methodologies that integrate multi-omics data-such as metagenomics, metaproteomics, and metabolomics-providing a comprehensive understanding of the gut microbiome's composition and function. Additionally, machine learning (ML) approaches, including deep learning and network-based methods, are explored for their ability to uncover complex patterns within microbiome data, offering unprecedented insights into microbial interactions and their link to host health. By highlighting the synergy between traditional bioinformatics tools and advanced AI techniques, this review underscores the potential of these approaches in enhancing biomarker discovery and developing personalized therapeutic strategies. The convergence of computational advancements and microbiome research marks a significant step forward in precision medicine, paving the way for novel diagnostics and treatments tailored to individual microbiome profiles. Investigators have the ability to discover connections between the composition of microorganisms, the expression of genes, and the profiles of metabolites. Individual reactions to medicines that target gut microbes can be predicted by models driven by artificial intelligence. It is possible to obtain personalized and precision medicine by first gaining an understanding of the impact that the gut microbiota has on the development of disease. The application of machine learning allows for the customization of treatments to the specific microbial environment of an individual.

Impact of Soil Microbiomes on Mung Bean Cultivation: Insights from 16S rRNA Metagenomics

Cyclic nutrient processes, soil health maintenance, and plant development are contingent upon soil microbiomes. The microbial makeup of the soil of Maruthupandiyar College, Thanjavur, is assessed using 16S rRNA gene sequencing. QIIME2, in conjunction with the SILVA database, analyzed the sequencing data to examine microbial diversity and composition. The experimental results revealed a diverse array of bacteria in soil physicochemical properties. The alpha and beta diversity assessment revealed significant microbial community complexity and distribution patterns disparities. The research revealed bacterial groups associated with biological nitrogen fixing, suggesting their potential to enhance mung bean growth. The current study illustrates the significance of microbial interactions in soil for sustaining soil fertility and enhancing crop output. Research findings provide essential insights into improving the sustainability of tropical agriculture through intentional microbial management to create sustainable soil health systems.

The research on the identification, taxonomy, and comparative genomics analysis of nine Bacillus velezensis strains significantly contributes to microbiology, genetics, bioinformatics, and biotechnology

Introduction

Next-generation sequencing (NGS) has played a pivotal role in the advancement of taxonomics, allowing for the accurate identification, differentiation, and reclassification of several bacteria species. Bacillus velezensis is a Gram-positive, facultatively aerobic, spore-forming bacterium known for its antimicrobial and antifungal properties. Strains of this species are highly relevant in agriculture, biotechnology, the food industry, and biomedicine.

Methods

In this study, we characterized the genomes of nine Bacillus strains isolated from soil in the state of Bahia (Brazil) using NGS with Illumina platform. Identification was performed by Average Nucleotide Identity (ANI) and digital DNA-DNA hybridization (dDDH) analyses, which revealed a match between the genomic information of the isolates and B. velezensis NRRL B-41580, with a variation of 89.3% to 91.8% by dDDH in TYGS and 95% to 98.04% by ANI in GTDBtk.

Results and discussion

Two strains, BAC144 and BAC1273, exhibited high similarity to B. amyloliquefaciens subsp. plantarum FZB42. However, the latter strain was subsequently reclassified as B. velezensis. The division pattern observed during identification was confirmed in the phylogenomic analysis, where BAC144 and BAC1273 clustered with Bacillus amyloliquefaciens subsp. plantarum, while the other strains clustered with B. velezensis NRRL B-41580, forming a clade with high genetic similarity, with a bootstrap value of 100%. Furthermore, a synteny analysis demonstrated greater conservation among the strains from this study compared to the reference strain, with the formation of distinct collinear groups. The pangenome analysis revealed an open pangenome, highlighting the genetic diversity within the species. Based on this analysis, a functional annotation was performed to compare exclusive gene repertoires across groups, uncovering distinct adaptations and functional profiles. The identification of bacterial strains belonging to this species is of great importance due to their high applicability. The strains identified in this study underscore the need for more robust taxonomic technologies to accurately classify prokaryotes, which are subject to constant evolutionary changes, requiring the reclassification of several species within the genus Bacillus, many of which are heterotypic synonyms of B. velezensis like Bacillus oryzicola, B. amyloliquefaciens subsp. plantarum and Bacillus methylotrophicus.

Endophytic Diversity in Vitis vinifera with Different Vineyard Managements and Vitis sylvestris Populations from Northern Italy: A Comparative Study of Culture-Dependent and Amplicon Sequencing Methods

This study aimed to investigate the endophytic microbial populations associated with wild and domesticated grapevines using both culture-based and culture-independent methods. Through culture-based methods, 148 endophytes were identified. The dominant fungal species included Aureobasidium pullulans, Alternaria alternata, and Cladosporium allicinum, while predominant bacterial species were Ralstonia pikettii, Nocardia niigatensis, and Sphingomonas echinoides. Culture-independent methods employed metagenomic techniques to explore microbial biodiversity, focusing on targeted amplification of bacterial 16S rRNA as well as fungal ITS and 26S rRNA gene regions. The main bacterial species identified included Halomonas sp., Sphingomonas sp. and Massilia sp., whereas the fungal population was dominated by Cladosporium sp., Malassezia sp. and Mucor sp. The findings revealed that vineyard management practices did not lead to statistically significant variations in microbial communities. The consistent presence of these genera across all samples suggests that they are stable components of the grapevine endophytic microbiota, remaining relatively unaffected by external environmental factors.

Rhodococcus parequi sp. nov., a new species isolated from equine farm soil closely related to the pathogen Rhodococcus equi

We present the description of the new species, Rhodococcus parequi, found during phylogenomic investigations of a global collection of strains identified as Rhodococcus (Prescottella) equi. Strain PAM 2766T was isolated from horse-breeding farm soil in Normandy, France, and was indistinguishable from R. equi based on the usual identification tests. Whole-genome phylogenetic analyses located PAM 2766T in the same Rhodococcus sublineage as R. equi, together with Rhodococcus agglutinans, Rhodococcus defluvii, Rhodococcus soli, Rhodococcus subtropicus, Rhodococcus spongiicola and Rhodococcus xishaensis. PAM 2766T is most closely related to, but sufficiently distinct from, R. equi DSM 20307 T to be considered a separate species. The average nt identity (ANI) and average aa identity (AAI) values are 88.60% and 92.35, respectively, well below the species cutoff. The PAM 2766T draft genome is ~5.3 Mb in size with 68.98% G+C mol content. PAM 2766T is strictly aerobic and non-motile and produces smooth, creamy to buff-coloured colonies very similar to those of R. equi. It phenotypically differs from the latter by the ability to grow at 5 °C, a strongly positive urease test at 24 h and specificities in the carbon and nitrogen source utilization profile as determined by phenotype microarray screens. Our data indicate that PAM 2766T belongs to a novel species, for which the name Rhodococcus parequi sp. nov. is proposed. R. parequi was avirulent in macrophage infection assays and is assumed to be non-pathogenic. The type strain is PAM 2766T (=CETC 30995T=NCTC 14987T).

Genome-wide analyses provide insights into genetic variation, phylo- and co-phylogenetic relationships, and biogeography of the entomopathogenic nematode genus Heterorhabditis

Multigene, genus-wide phylogenetic studies have uncovered the limited taxonomic resolution power of commonly used gene markers, particularly of rRNA genes, to discriminate closely related species of the nematode genus Heterorhabditis. In addition, conflicting tree topologies are often obtained using the different gene markers, which limits our understanding of the phylo- and co-phylogenetic relationships and biogeography of the entomopathogenic nematode genus Heterorhabditis. Here we carried out phylogenomic reconstructions using whole nuclear and mitochondrial genomes, and whole ribosomal operon sequences, as well as multiple phylogenetic reconstructions using various single nuclear and mitochondrial genes. Using the inferred phylogenies, we then investigated co-phylogenetic relationships between Heterorhabditis and their Photorhabdus bacterial symbionts and biogeographical patterns. Robust, well-resolved, and highly congruent phylogenetic relationships were reconstructed using both whole nuclear and mitochondrial genomes. Similarly, whole ribosomal operon sequences proved valuable for phylogenomic reconstructions, though they have limited value to discriminate closely related species. In addition, two mitochondrial genes, the cytochrome c oxidase subunit I (cox-1) and the NADH dehydrogenase subunit 4 (nad-4), and two housekeeping genes, the fanconi-associated nuclease 1 (fan-1) and the serine/threonine-protein phosphatase 4 regulatory subunit 1 (ppfr-1), provided the most robust phylogenetic reconstructions compared to other individual genes. According to our findings, whole nuclear and/or mitochondrial genomes are strongly recommended for reconstructing phylogenetic relationships of the genus Heterorhabditis. If whole nuclear and/or mitochondrial genomes are unavailable, a combination of nuclear and mitochondrial genes can be used as an alternative. Under these circumstances, sequences of multiple conspecific isolates in a genus-wide phylogenetic context should be analyzed to avoid artefactual species over-splitting driven by the high intraspecific sequence divergence of mitochondrial genes and to avoid artefactual species lumping driven by the low interspecific sequence divergence of some nuclear genes. On the other hand, we observed that the genera Heterorhabditis and Photorhabdus exhibit diverse biogeographic patterns, ranging from cosmopolitan species to potentially endemic species, and show high phylogenetic congruence, although host switches have also occurred. Our study contributes to a better understanding of the biodiversity and phylo- and co-phylogenetic relationships of an important group of biological control agents and advances our efforts to develop more tools that are compatible with sustainable and eco-friendly agricultural practices.

Isolation optimization and screening of halophilic enzymes and antimicrobial activities of halophilic archaea from the high-altitude, hypersaline Da Qaidam Salt Lake, China

AIM

The aim of this study is to increase the diversity of culturable halophilic archaea by comparing various isolation conditions and to explore the application of halophilic archaea for enzyme-producing activities and antimicrobial properties.

METHODS AND RESULTS

We systematically compared the isolation performance of various archaeal and bacterial media by isolating halophilic archaea from the Da Qaidam Salt Lake, a magnesium sulfate subtype hypersaline lake on the Qinghai-Tibet Plateau, China, using multiple enrichment culture and gradient dilution conditions. A total of 490 strains of halophilic archaea were isolated, which belonged to five families and 11 genera within the order Halobacteriales of the class Halobacteria of the phylum Euryarchaeota. The 11 genera consisted of nine known genera and two potentially new genera, the former including Halorubrum, Natranaeroarchaeum, Haloplanus, Haloarcula, Halorhabdus, Halomicrobium, Halobacterium, Natrinema, and Haloterrigene. Halorubrum was the dominant genus with a relative abundance of 78.98%. By comparing different culture conditions, we found that bacterial media 2216E and R2A showed much better isolation performance than all archaeal media, and enrichment culture after 60 d and dilution gradients of 10-1 and 10-2 were best fitted for halophilic archaea cultivation. The screening of 40 halophilic archaeal strains of different species indicated that these halophilic archaea had great extracellular enzyme activities, including amylase (62.5%), esterase (50.0%), protease (27.5%), and cellulase (15.0%), and possessed great antimicrobial activities against human pathogens. A total of 34 strains exhibited antimicrobial activity against four or more pathogens, and 19 strains exhibited antimicrobial activity against all six pathogens.

CONCLUSIONS

The diversity of culturable halophilic archaea was significantly increased by enrichment culture and selection of bacterial media, and screening of representative strains showed that halophilic archaea have multiple extracellular enzyme activities and broad-spectrum antimicrobial activity against human pathogens.

Flavobacterium magnesitis sp. nov. and Flavobacterium zubiriense sp. nov., two novel Flavobacterium species isolated from alkaline magnesite residues

Three bacterial strains, designated FZUC8N2.13T, FBOR7N2.3T and FZUR7N2.5, were isolated from distinct magnesite residues in Spain. Phylogenetic and phylogenomic analysis places them within the genus Flavobacterium. Strains FBOR7N2.3T and FZUR7N2.5 share 100% of similarity in the 16S rRNA gene sequence, and both are most closely related to Flavobacterium cellulosilyticum AR-3-4T with which they share 97.5% of 16S rRNA gene similarity. Strain FZUC8N2.13T forms a distinct lineage most closely related to Flavobacterium lacustre IMCC36792T with 97.7% 16S rRNA gene similarity. The closest phylogenomic neighbours of these three strains are Flavobacterium flevense DSM 1076T, 'Flavobacterium undicola' BBQ-18T and Flavobacterium commune PK15T. The average nucleotide identity and digital DNA-DNA hybridization values between the three strains and closest members of the genus Flavobacterium are below the threshold values of 95% and 70%, respectively. Strains FZUC8N2.13T, FBOR7N2.3T and FZUR7N2.5 stain Gram-negative, are rod-shaped and form yellow colonies. Optimum growth occurs at 25 °C and pH 7. The genomic G+C contents are 33.4 mol% for strain FZUC8N2.13T and 33.2 mol% for strains FBOR7N2.3T and FZUR7N2.5. The major isoprenoid quinone is menaquinone 6. The major fatty acids are summed feature 3 (C16 : 1 ω7c and/or C16 : 1 ω6c) (22.6-31.1%), iso-C15 : 0 (13.6-16.2 %) and anteiso-C15 : 0 (8.7-10.5%). The polar lipids consist of two aminolipids, two aminophospholipids and one glycolipid. The phylogenetic, phylogenomic, phenotypic and chemotaxonomic data indicate that FZUC8N2.13T, FBOR7N2.3T and FZUR7N2.5 are distinct from the described species of Flavobacterium and should be classified as novel species, for which we propose the names Flavobacterium zubiriense for strain FZUC8N2.13T (=UCCCB 179T=CECT 30977T) and Flavobacterium magnesitis for strains FBOR7N2.3T (=UCCCB 178T=CECT 30976T) and FZUR7N2.5 (=UCCCB 216=CECT 31036).

Genome-resolved analysis of Serratia marcescens strain SMTT infers niche specialization as a hydrocarbon-degrader

Bacteria that are chronically exposed to high levels of pollutants demonstrate genomic and corresponding metabolic diversity that complement their strategies for adaptation to hydrocarbon-rich environments. Whole genome sequencing was carried out to infer functional traits of Serratia marcescens strain SMTT recovered from soil contaminated with crude oil. The genome size (Mb) was 5,013,981 with a total gene count of 4,842. Comparative analyses with carefully selected S. marcescens strains, 2 of which are associated with contaminated soil, show conservation of central metabolic pathways in addition to intra-specific genetic diversity and metabolic flexibility. Genome comparisons also indicated an enrichment of genes associated with multidrug resistance and efflux pumps for SMTT. The SMTT genome contained genes that enable the catabolism of aromatic compounds via the protocatechuate para-degradation pathway, in addition to meta-cleavage of catechol (meta-cleavage pathway II); gene enrichment for aromatic compound degradation was markedly higher for SMTT compared to the other S. marcescens strains analysed. Our data presents a valuable genetic inventory for future studies on strains of S. marcescens and provides insights into those genomic features of SMTT with industrial potential.

Wise Roles and Future Visionary Endeavors of Current Emperor: Advancing Dynamic Methods for Longitudinal Microbiome Meta-Omics Data in Personalized and Precision Medicine

Understanding the etiological complexity of diseases requires identifying biomarkers longitudinally associated with specific phenotypes. Advanced sequencing tools generate dynamic microbiome data, providing insights into microbial community functions and their impact on health. This review aims to explore the current roles and future visionary endeavors of dynamic methods for integrating longitudinal microbiome multi-omics data in personalized and precision medicine. This work seeks to synthesize existing research, propose best practices, and highlight innovative techniques. The development and application of advanced dynamic methods, including the unified analytical frameworks and deep learning tools in artificial intelligence, are critically examined. Aggregating data on microbes, metabolites, genes, and other entities offers profound insights into the interactions among microorganisms, host physiology, and external stimuli. Despite progress, the absence of gold standards for validating analytical protocols and data resources of various longitudinal multi-omics studies remains a significant challenge. The interdependence of workflow steps critically affects overall outcomes. This work provides a comprehensive roadmap for best practices, addressing current challenges with advanced dynamic methods. The review underscores the biological effects of clinical, experimental, and analytical protocol settings on outcomes. Establishing consensus on dynamic microbiome inter-studies and advancing reliable analytical protocols are pivotal for the future of personalized and precision medicine.

TreeWave: command line tool for alignment-free phylogeny reconstruction based on graphical representation of DNA sequences and genomic signal processing

BACKGROUND

Genomic sequence similarity comparison is a crucial research area in bioinformatics. Multiple Sequence Alignment (MSA) is the basic technique used to identify regions of similarity between sequences, although MSA tools are widely used and highly accurate, they are often limited by computational complexity, and inaccuracies when handling highly divergent sequences, which leads to the development of alignment-free (AF) algorithms.

RESULTS

This paper presents TreeWave, a novel AF approach based on frequency chaos game representation and discrete wavelet transform of sequences for phylogeny inference. We validate our method on various genomic datasets such as complete virus genome sequences, bacteria genome sequences, human mitochondrial genome sequences, and rRNA gene sequences. Compared to classical methods, our tool demonstrates a significant reduction in running time, especially when analyzing large datasets. The resulting phylogenetic trees show that TreeWave has similar classification accuracy to the classical MSA methods based on the normalized Robinson-Foulds distances and Baker's Gamma coefficients.

CONCLUSIONS

TreeWave is an open source and user-friendly command line tool for phylogeny reconstruction. It is a faster and more scalable tool that prioritizes computational efficiency while maintaining accuracy. TreeWave is freely available at https://github.com/nasmaB/TreeWave .

On the diversity, phylogeny and biogeography of cable bacteria

Cable bacteria have acquired a unique metabolism, which induces long-distance electron transport along their centimeter-long multicellular filaments. At present, cable bacteria are thought to form a monophyletic clade with two described genera. However, their diversity has not been systematically investigated. To investigate the phylogenetic relationships within the cable bacteria clade, 16S rRNA gene sequences were compiled from literature and public databases (SILVA 138 SSU and NCBI GenBank). These were complemented with novel sequences obtained from natural sediment enrichments across a wide range of salinities (2-34). To enable taxonomic resolution at the species level, we designed a procedure to attain full-length 16S rRNA gene sequences from individual cable bacterium filaments using an optimized nested PCR protocol and Sanger sequencing. The final database contained 1,876 long 16S rRNA gene sequences (≥800 bp) originating from 92 aquatic locations, ranging from polar to tropical regions and from intertidal to deep sea sediments. The resulting phylogenetic tree reveals 90 potential species-level clades (based on a delineation value of 98.7% 16S rRNA gene sequence identity) that reside within six genus-level clusters. Hence, the diversity of cable bacteria appears to be substantially larger than the two genera and 13 species that have been officially named up to now. Particularly brackish environments with strong salinity fluctuations, as well as sediments with low free sulfide concentrations and deep sea sediments harbor a large pool of novel and undescribed cable bacteria taxa.

Acinetobacter corruptisaponis sp. nov., Isolated from a Spoiled Bath Lotion

Strain DM2021935T representing a novel Acinetobacter species was isolated from a spoiled bath lotion in Guangdong, China. Based on 16S rRNA gene phylogenetic analysis, strain DM2021935T was closely related to 'Acinetobacter thutiue' VNH17T, Acinetobacter junii CIP 64.5 T, and Acinetobacter tibetensis Y-23 T. Cells of strain DM2021935T were Gram-stain-negative, non-spore-forming, strictly aerobic, catalase-positive, oxidase-negative, α-hemolytic, and non-motile. Strain DM2021935T exhibited growth in 1-3% (w/v) NaCl at temperatures ranging from 4 to 37 °C and tolerated pH levels from 6.0 to 8.0. The predominant fatty acids in strain DM2021935T are C12:0, C16:0, C18:1 ω9c, and summed feature 3. Polar lipid profiles included glycolipids, phospholipids, phosphatidylethanolamine, and phosphatidyl-N-methylethanolamine. The identified respiratory quinones were ubiquinone Q-8 and Q-9. The genomic size of DM2021935T comprised 4.15 Mb, consisting of one chromosome (3,827,633 bp) and two plasmids (241,357 and 83,010 bp). The G + C content was 41.8%. The average nucleotide identity, average amino acid identity, and digital DNA-DNA hybridization values between strain DM2021935T and phylogenetically related type strains were below the species delineation thresholds (72.2-95.4, 53.1-87.0, and 20.4-66.4%, respectively). AntiSMASH analysis identified four gene clusters: non-ribosomal peptide synthetase, non-alpha poly-amino group acids, YcaO cyclodehydratase, and aryl polyene biosynthesis. Based on genotypic data, strain DM2021935T represents a novel species within the genus Acinetobacter. The proposed name for the novel species is Acinetobacter corruptisaponis sp. nov. (type strain DM2021935T = KCTC 92772 T = GDMCC 1.3703 T).

16S rRNA phylogeny and clustering is not a reliable proxy for genome-based taxonomy in Streptomyces

Streptomyces is among the most extensively studied genera of bacteria but its complex taxonomy remains contested and is suspected to contain significant species-level misclassification. Resolving the classification of Streptomyces would benefit many areas of applied microbiology that rely on an accurate ground truth for grouping of related organisms, including comparative genomics-based searches for novel antimicrobials. We survey taxonomic conflicts between 16S rRNA and whole genome-based Streptomyces classifications using 2276 publicly available Streptomyces genome assemblies and 48 981 publicly available full-length 16S rRNA Streptomyces sequences from silva, Greengenes, Ribosomal Database Project (RDP), and NCBI (National Centre for Biotechnology Information) databases. We construct a full-length 16S gene tree for 14 239 distinct Streptomyces sequences that resolves three major lineages of Streptomyces, but whose topology is not consistent with existing taxonomic assignments. We use these sequence data to delineate 16S and whole genome landscapes for Streptomyces, demonstrating that 16S and whole-genome classifications are frequently in disagreement, and that 16S zero-radius Operational Taxonomic Units (zOTUs) are often inconsistent with Average Nucleotide Identity (ANI)-based taxonomy. Our results strongly imply that 16S rRNA sequence data does not map to taxonomy sufficiently well to delineate Streptomyces species routinely. We propose that alternative marker sequences should be adopted by the community for classification and metabarcoding. Insofar as Streptomyces taxonomy has been determined or supported by 16S sequence data and may in parts be in error, we also propose that reclassification of the genus by alternative approaches may benefit the Streptomyces community.

Whole genome-based comparative analysis of the genus Streptomyces reveals many misclassifications

Streptomyces species are experts in the production of bioactive secondary metabolites; however, their taxonomy has fallen victim of the tremendous interest shown by the scientific community, evident in the discovery of numerous synonymous in public repositories. Based on genomic data from NCBI Datasets and nomenclature from the LPSN database, we compiled a dataset of 600 Streptomyces species along with their annotations and metadata. To pinpoint the most suitable taxonomic classification method, we conducted a comprehensive assessment comparing multiple methodologies, including analysis of 16S rRNA, individual housekeeping genes, multilocus sequence analysis (MLSA), and Fast Average Nucleotide Identity (FastANI) on a subset of 409 species with complete data. Due to insufficient resolution of 16S rRNA and inconsistency observed in individual housekeeping genes, we performed a more in-depth analysis, comparing only FastANI and MLSA, which expanded our dataset to include 502 species. With FastANI validated as the preferred method, we conducted pairwise analysis on the entire dataset identifying 59 non-unique species among the 600, and subsequently refined the dataset to 541 unique species. Additionally, we collected data on 724 uncharacterized Streptomyces strains to investigate the uniqueness potential of the unannotated fraction of the Streptomyces genus. Utilizing FastANI, 289 strains could be successfully classified into one of the 541 Streptomyces species. KEY POINTS: • Evaluation of taxonomic classification methods for Streptomyces species. • Whole genome analysis, specifically FastANI, has been chosen as preferred method. • Various reclassifications are proposed within the Streptomyces genus.

Impact of diet change on the gut microbiome of common marmosets (Callithrix jacchus)

Gastrointestinal diseases are the most frequently reported clinical problems in captive common marmosets (Callithrix jacchus), often affecting the health and welfare of the animal and ultimately their use as a research subject. The microbiome has been shown to be intimately connected to diet and gastrointestinal health. Here, we use shotgun metagenomics and untargeted metabolomics in fecal samples of common marmosets collected before, during, and after a dietary transition from a biscuit to a gel diet. The overall health of marmosets, measured as weight recovery and reproductive outcome, improved after the diet transition. Moreover, each marmoset pair had significant shifts in the microbiome and metabolome after the diet transition. In general, we saw a decrease in Escherichia coli and Prevotella species and an increase in Bifidobacterium species. Untargeted metabolic profiles indicated that polyamine levels, specifically cadaverine and putrescine, were high after diet transition, suggesting either an increase in excretion or a decrease in intestinal reabsorption at the intestinal level. In conclusion, our data suggest that Bifidobacterium species could potentially be useful as probiotic supplements to the laboratory marmoset diet. Future studies with a larger sample size will be beneficial to show that this is consistent with the diet change.

IMPORTANCE

Appropriate diet and health of the common marmoset in captivity are essential both for the welfare of the animal and to improve experimental outcomes. Our study shows that a gel diet compared to a biscuit diet improves the health of a marmoset colony, is linked to increases in Bifidobacterium species, and increases the removal of molecules associated with disease. The diet transition had an influence on the molecular changes at both the pair and time point group levels, but only at the pair level for the microbial changes. It appears to be more important which genes and functions present changed rather than specific microbes. Further studies are needed to identify specific components that should be considered when choosing an appropriate diet and additional supplementary foods, as well as to validate the benefits of providing probiotics. Probiotics containing Bifidobacterium species appear to be useful as probiotic supplements to the laboratory marmoset diet, but additional work is needed to validate these findings.

Comparison of the full-length sequence and sub-regions of 16S rRNA gene for skin microbiome profiling

The skin microbiome plays a pivotal role in human health by providing protective and functional benefits. Furthermore, its inherent stability and individual specificity present novel forensic applications. These aspects have sparked considerable research enthusiasm among scholars across various fields. However, the selection of specific 16S rRNA hypervariable regions for skin microbiome studies is not standardized and should be validated through extensive research tailored to different research objectives and targeted bacterial taxa. Notably, third-generation sequencing (TGS) technology leverages the full discriminatory power of the 16S gene and enables more detailed and accurate microbial community analyses. Here, we conducted full-length 16S sequencing of 141 skin microbiota samples from multiple human anatomical sites using the PacBio platform. Based on this data, we generated derived 16S sub-region data through an in silico experiment. Comparisons between the 16S full-length and the derived variable region data revealed that the former can provide superior taxonomic resolution. However, even with full 16S gene sequencing, limitations arise in achieving 100% taxonomic resolution at the species level for skin samples. Additionally, the capability to resolve high-abundance bacteria (TOP30) at the genus level remains generally consistent across different 16S variable regions. Furthermore, the V1-V3 region offers a resolution comparable with that of full-length 16S sequences, in comparison to other hypervariable regions studied. In summary, while acknowledging the benefits of full-length 16S gene analysis, we propose the targeting of specific sub-regions as a practical choice for skin microbial research, especially when balancing the accuracy of taxonomic classification with limited sequencing resources, such as the availability of only short-read sequencing or insufficient DNA.IMPORTANCESkin acts as the primary barrier to human health. Considering the different microenvironments, microbial research should be conducted separately for different skin regions. Third-generation sequencing (TGS) technology can make full use of the discriminatory power of the full-length 16S gene. However, 16S sub-regions are widely used, particularly when faced with limited sequencing resources including the availability of only short-read sequencing and insufficient DNA. Comparing the 16S full-length and the derived variable region data from five different human skin sites, we confirmed the superiority of the V1-V3 region in skin microbiota analysis. We propose the targeting of specific sub-regions as a practical choice for microbial research.

Augmenting bacterial similarity measures using a graph-based genome representation

Relationships between bacterial taxa are traditionally defined using 16S rRNA nucleotide similarity or average nucleotide identity. Improvements in sequencing technology provide additional pairwise information on genome sequences, which may provide valuable information on genomic relationships. Mapping orthologous gene locations between genome pairs, known as synteny, is typically implemented in the discovery of new species and has not been systematically applied to bacterial genomes. Using a data set of 378 bacterial genomes, we developed and tested a new measure of synteny similarity between a pair of genomes, which was scaled onto 16S rRNA distance using covariance matrices. Based on the input gene functions used (i.e., core, antibiotic resistance, and virulence), we observed varying topological arrangements of bacterial relationship networks by applying (i) complete linkage hierarchical clustering and (ii) K-nearest neighbor graph structures to synteny-scaled 16S data. Our metric improved clustering quality comparatively to state-of-the-art average nucleotide identity metrics while preserving clustering assignments for the highest similarity relationships. Our findings indicate that syntenic relationships provide more granular and interpretable relationships for within-genera taxa compared to pairwise similarity measures, particularly in functional contexts.

IMPORTANCE

Given the prevalence and necessity of the 16S rRNA measure in bacterial identification and analysis, this additional analysis adds a functional and synteny-based layer to the identification of relatives and clustering of bacteria genomes. It is also of computational interest to model the bacterial genome as a graph structure, which presents new avenues of genomic analysis for bacteria and their closely related strains and species.

AMRomics: a scalable workflow to analyze large microbial genome collections

Whole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Recent methods have been implemented to integrate individual genomes into large collections of specific bacterial populations and are widely employed for systematic genomic surveillance. However, they do not scale well when the population expands and turnaround time remains the main issue for this type of analysis. Here, we introduce AMRomics, an optimized microbial genomics pipeline that can work efficiently with big datasets. We use different bacterial data collections to compare AMRomics against competitive tools and show that our pipeline can generate similar results of interest but with better performance. The software is open source and is publicly available at https://github.com/amromics/amromics under an MIT license.

Genome-resolved metagenomics: a game changer for microbiome medicine

Recent substantial evidence implicating commensal bacteria in human diseases has given rise to a new domain in biomedical research: microbiome medicine. This emerging field aims to understand and leverage the human microbiota and derivative molecules for disease prevention and treatment. Despite the complex and hierarchical organization of this ecosystem, most research over the years has relied on 16S amplicon sequencing, a legacy of bacterial phylogeny and taxonomy. Although advanced sequencing technologies have enabled cost-effective analysis of entire microbiota, translating the relatively short nucleotide information into the functional and taxonomic organization of the microbiome has posed challenges until recently. In the last decade, genome-resolved metagenomics, which aims to reconstruct microbial genomes directly from whole-metagenome sequencing data, has made significant strides and continues to unveil the mysteries of various human-associated microbial communities. There has been a rapid increase in the volume of whole metagenome sequencing data and in the compilation of novel metagenome-assembled genomes and protein sequences in public depositories. This review provides an overview of the capabilities and methods of genome-resolved metagenomics for studying the human microbiome, with a focus on investigating the prokaryotic microbiota of the human gut. Just as decoding the human genome and its variations marked the beginning of the genomic medicine era, unraveling the genomes of commensal microbes and their sequence variations is ushering us into the era of microbiome medicine. Genome-resolved metagenomics stands as a pivotal tool in this transition and can accelerate our journey toward achieving these scientific and medical milestones.

Short-term dietary fiber interventions produce consistent gut microbiome responses across studies

The composition of the human gut microbiome varies tremendously among individuals, making the effects of dietary or treatment interventions difficult to detect and characterize. The consumption of fiber is important for gut health, yet the specific effects of increased fiber intake on the gut microbiome vary across studies. The variation in study outcomes might be due to inter-individual (or inter-population) variation or to the details of the interventions including the types of fiber, length of study, size of cohort, and molecular approaches. Thus, to identify generally (on average) consistent fiber-induced responses in the gut microbiome of healthy individuals, we re-analyzed 16S rRNA sequencing data from 21 dietary fiber interventions from 12 human studies, which included 2,564 fecal samples from 538 subjects across all interventions. Short-term increases in dietary fiber consumption resulted in highly consistent gut bacterial community responses across studies. Increased fiber consumption explained an average of 1.5% of compositional variation (vs 82% of variation attributed to the individual), reduced alpha-diversity, and resulted in phylogenetically conserved responses in relative abundances among bacterial taxa. Additionally, we identified bacterial clades, at approximately the genus level, that were highly consistent in their response (on average, increasing or decreasing in their relative abundance) to dietary fiber interventions across the studies.

IMPORTANCE

Our study is an example of the power of synthesizing and reanalyzing 16S rRNA microbiome data from many intervention studies. Despite high inter-individual variation of the composition of the human gut microbiome, dietary fiber interventions cause a consistent response both in the degree of change and the particular taxa that respond to increased fiber.

Fecal microbiota transplantation: current challenges and future landscapes

SUMMARYGiven the importance of gut microbial homeostasis in maintaining health, there has been considerable interest in developing innovative therapeutic strategies for restoring gut microbiota. One such approach, fecal microbiota transplantation (FMT), is the main "whole gut microbiome replacement" strategy and has been integrated into clinical practice guidelines for treating recurrent Clostridioides difficile infection (rCDI). Furthermore, the potential application of FMT in other indications such as inflammatory bowel disease (IBD), metabolic syndrome, and solid tumor malignancies is an area of intense interest and active research. However, the complex and variable nature of FMT makes it challenging to address its precise functionality and to assess clinical efficacy and safety in different disease contexts. In this review, we outline clinical applications, efficacy, durability, and safety of FMT and provide a comprehensive assessment of its procedural and administration aspects. The clinical applications of FMT in children and cancer immunotherapy are also described. We focus on data from human studies in IBD in contrast with rCDI to delineate the putative mechanisms of this treatment in IBD as a model, including colonization resistance and functional restoration through bacterial engraftment, modulating effects of virome/phageome, gut metabolome and host interactions, and immunoregulatory actions of FMT. Furthermore, we comprehensively review omics technologies, metagenomic approaches, and bioinformatics pipelines to characterize complex microbial communities and discuss their limitations. FMT regulatory challenges, ethical considerations, and pharmacomicrobiomics are also highlighted to shed light on future development of tailored microbiome-based therapeutics.

Changes in the Gastrointestinal Microbiota Induced by Proton Pump Inhibitors-A Review of Findings from Experimental Trials

The use of proton pump inhibitors (PPIs) has increased considerably in many Western countries, and there is concern that numerous conditions and diseases associated with PPI use may be adverse events. The main function of gastric acid is to defend the organism against orally ingested microorganisms, and there is also concern that alterations not only in the gastric microbiome but also the downstream intestinal microbiome may increase the risk of disease or alter the course of preexisting disease. The current study is a systematic review of the available evidence from experimental trials investigating the effects of PPIs on the gastrointestinal microbiota by next-generation sequencing. Thirteen studies were identified. The effects of PPIs were seen on alterations in diversity and richness in some of the studies, while a larger proportion of the studies detected alterations at various taxonomic levels. The general finding was that PPI use caused an increase in bacteria normally found in the oral microbiota in both the upper and lower GI tract. The most consistent taxonomic alterations seemed to be increases in oral flora along the axis Streptococcaceae and Streptococcus at genus level and various Streptococcus spp., as well as Veillonellaceae, Veillonella and Haemophilus.

A survey of Wolbachia infection in brachyceran flies from Iran

Wolbachia is a maternally inherited intracellular bacterium that is considered to be the most plentiful endosymbiont found in arthropods. It reproductively manipulates its host to increase the chances of being transmitted to the insect progeny; and it is currently used as a means of suppressing disease vector populations or controlling vector-borne diseases. Studies of the dissemination and prevalence of Wolbachia among its arthropod hosts are important for its possible use as a biological control agent. The molecular identification of Wolbachia relies on different primers sets due to Wolbachia strain variation. Here, we screened for the presence of Wolbachia in a broad range of Brachycera fly species (Diptera), collected from different regions of Iran, using nine genetic markers (wsp, ftsZ, fbpA, gatB, CoxA, gltA, GroEL dnaA, and 16s rRNA), for detecting, assessing the sensitivity of primers for detection, and phylogeny of this bacterium. The overall incidence of Wolbachia among 22 species from six families was 27.3%. The most commonly positive fly species were Pollenia sp. and Hydrotaea armipes. However, the bacterium was not found in the most medically important flies or in potential human disease vectors, including Musca domestica, Sarcophaga spp., Calliphora vicinia, Lucilia sericata, and Chrysomya albiceps. The primer sets of 16s rRNA with 53.0% and gatB with 52.0% were the most sensitive primers for detecting Wolbachia. Blast search, phylogenetic, and MLST analysis of the different locus sequences of Wolbachia show that all the six distantly related fly species likely belonging to supergroup A. Our study showed some primer sets generated false negatives in many of the samples, emphasizing the importance of using different loci in detecting Wolbachia. The study provides the groundwork for future studies of a Wolbachia-based program for control of flies.

Harnessing the intragenomic variability of rRNA operons to improve differentiation of Vibrio species

Although the 16S rRNA gene is frequently used as a phylogenetic marker in analysis of environmental DNA, this marker often fails to distinguish closely related species, including those in the genus Vibrio. Here, we investigate whether inclusion and analysis of 23S rRNA sequence can help overcome the intrinsic weaknesses of 16S rRNA analyses for the differentiation of Vibrio species. We construct a maximum likelihood 16S rRNA gene tree to assess the use of this gene to identify clades of Vibrio species. Within the 16S rRNA tree, we identify the putative informative bases responsible for polyphyly, and demonstrate the association of these positions with tree topology. We demonstrate that concatenation of 16S and 23S rRNA genes increases the number of informative nucleotide positions, thereby overcoming ambiguities in 16S rRNA-based phylogenetic reconstructions. Finally, we experimentally demonstrate that this approach considerably improves the differentiation and identification of Vibrio species in environmental samples.

Advances in Culturomics Research on the Human Gut Microbiome: Optimizing Medium Composition and Culture Techniques for Enhanced Microbial Discovery

Despite considerable advancements achieved using next-generation sequencing technologies in exploring microbial diversity, several species of the gut microbiome remain unknown. In this transformative era, culturomics has risen to prominence as a pivotal approach in unveiling realms of microbial diversity that were previously deemed inaccessible. Utilizing innovative strategies to optimize growth and culture medium composition, scientists have successfully cultured hard-to-cultivate microbes. This progress has fostered the discovery and understanding of elusive microbial entities, highlighting their essential role in human health and disease paradigms. In this review, we emphasize the importance of culturomics research on the gut microbiome and provide new theories and insights for expanding microbial diversity via the optimization of cultivation conditions.

Genomic and environmental controls on Castellaniella biogeography in an anthropogenically disturbed subsurface

Castellaniella species have been isolated from a variety of mixed-waste environments including the nitrate and multiple metal-contaminated subsurface at the Oak Ridge Reservation (ORR). Previous studies examining microbial community composition and nitrate removal at ORR during biostimulation efforts reported increased abundances of members of the Castellaniella genus concurrent with increased denitrification rates. Thus, we asked how genomic and abiotic factors control the Castellaniella biogeography at the site to understand how these factors may influence nitrate transformation in an anthropogenically impacted setting. We report the isolation and characterization of several Castellaniella strains from the ORR subsurface. Five of these isolates match at 100% identity (at the 16S rRNA gene V4 region) to two Castellaniella amplicon sequence variants (ASVs), ASV1 and ASV2, that have persisted in the ORR subsurface for at least 2 decades. However, ASV2 has consistently higher relative abundance in samples taken from the site and was also the dominant blooming denitrifier population during a prior biostimulation effort. We found that the ASV2 representative strain has greater resistance to mixed metal stress than the ASV1 representative strains. We attribute this resistance, in part, to the large number of unique heavy metal resistance genes identified on a genomic island in the ASV2 representative genome. Additionally, we suggest that the relatively lower fitness of ASV1 may be connected to the loss of the nitrous oxide reductase (nos) operon (and associated nitrous oxide reductase activity) due to the insertion at this genomic locus of a mobile genetic element carrying copper resistance genes. This study demonstrates the value of integrating genomic, environmental, and phenotypic data to characterize the biogeography of key microorganisms in contaminated sites.

The overlooked evolutionary dynamics of 16S rRNA revises its role as the "gold standard" for bacterial species identification

The role of 16S rRNA has been and largely remains crucial for the identification of microbial organisms. Although 16S rRNA could certainly be described as one of the most studied sequences ever, the current view of it remains somewhat ambiguous. While some consider 16S rRNA to be a variable marker with resolution power down to the strain level, others consider them to be living fossils that carry information about the origin of domains of cellular life. We show that 16S rRNA is clearly an evolutionarily very rigid sequence, making it a largely unique and irreplaceable marker, but its applicability beyond the genus level is highly limited. Interestingly, it seems that the evolutionary rigidity is not driven by functional constraints of the sequence (RNA-protein interactions), but rather results from the characteristics of the host organism. Our results suggest that, at least in some lineages, Horizontal Gene Transfer (HGT) within genera plays an important role for the evolutionary non-dynamics (stasis) of 16S rRNA. Such genera exhibit an apparent lack of diversification at the 16S rRNA level in comparison to the rest of a genome. However, why it is limited specifically and solely to 16S rRNA remains enigmatic.

Uncovering the boundaries of Campylobacter species through large-scale phylogenetic and nucleotide identity analyses

Campylobacter species are typically helical shaped, Gram-negative, and non-spore-forming bacteria. Species in this genus include established foodborne and animal pathogens as well as emerging pathogens. The accumulation of genomic data from the Campylobacter genus has increased exponentially in recent years, accompanied by the discovery of putative new species. At present, the lack of a standardized species boundary complicates distinguishing established and novel species. We defined the Campylobacter genus core genome (500 loci) using publicly available Campylobacter complete genomes (n = 498) and constructed a core genome phylogeny using 2,193 publicly available Campylobacter genomes to examine inter-species diversity and species boundaries. Utilizing 8,440 Campylobacter genomes representing 33 species and 8 subspecies, we found species delineation based on an average nucleotide identity (ANI) cutoff of 94.2% is consistent with the core genome phylogeny. We identified 60 ANI genomic species that delineated Campylobacter species in concordance with previous comparative genetic studies. All pairwise ANI genomic species pairs had in silico DNA-DNA hybridization scores of less than 70%, supporting their delineation as separate species. We provide the tool Campylobacter Genomic Species typer (CampyGStyper) that assigns ANI genomic species to query genomes based on ANI similarities to medoid genomes from each ANI genomic species with an accuracy of 99.96%. The ANI genomic species definitions proposed here allow consistent species definition in the Campylobacter genus and will facilitate the detection of novel species in the future.IMPORTANCEIn recent years, Campylobacter has gained recognition as the leading cause of bacterial gastroenteritis worldwide, leading to a substantial rise in the collection of genomic data of the Campylobacter genus in public databases. Currently, a standardized Campylobacter species boundary at the genomic level is absent, leading to challenges in detecting emerging pathogens and defining putative novel species within this genus. We used a comprehensive representation of genomes of the Campylobacter genus to construct a core genome phylogenetic tree. Furthermore, we found an average nucleotide identity (ANI) of 94.2% as the optimal cutoff to define the Campylobacter species. Using this cutoff, we identified 60 ANI genomic species which provided a standardized species definition and nomenclature. Importantly, we have developed Campylobacter Genomic Species typer (CampyGStyper), which can robustly and accurately assign these ANI genomic species to Campylobacter genomes, thereby aiding pathogen surveillance and facilitating evolutionary and epidemiological studies of existing and emerging pathogens in the genus Campylobacter.

Accurately clustering biological sequences in linear time by relatedness sorting

Clustering biological sequences into similar groups is an increasingly important task as the number of available sequences continues to grow exponentially. Search-based approaches to clustering scale super-linearly with the number of input sequences, making it impractical to cluster very large sets of sequences. Approaches to clustering sequences in linear time currently lack the accuracy of super-linear approaches. Here, I set out to develop and characterize a strategy for clustering with linear time complexity that retains the accuracy of less scalable approaches. The resulting algorithm, named Clusterize, sorts sequences by relatedness to linearize the clustering problem. Clusterize produces clusters with accuracy rivaling popular programs (CD-HIT, MMseqs2, and UCLUST) but exhibits linear asymptotic scalability. Clusterize generates higher accuracy and oftentimes much larger clusters than Linclust, a fast linear time clustering algorithm. I demonstrate the utility of Clusterize by accurately solving different clustering problems involving millions of nucleotide or protein sequences.

Heterogeneous lineage-specific arginine deiminase expression within dental microbiome species

Arginine catabolism by the bacterial arginine deiminase system (ADS) has anticariogenic properties through the production of ammonia, which modulates the pH of the oral environment. Given the potential protective capacity of the ADS pathway, the exploitation of ADS-competent oral microbes through pre- or probiotic applications is a promising therapeutic target to prevent tooth decay. To date, most investigations of the ADS in the oral cavity and its relation to caries have focused on indirect measures of activity or on specific bacterial groups, yet the pervasiveness and rate of expression of the ADS operon in diverse mixed microbial communities in oral health and disease remain an open question. Here, we use a multivariate approach, combining ultra-deep metatranscriptomic sequencing with paired metataxonomic and in vitro citrulline quantification to characterize the microbial community and ADS operon expression in healthy and late-stage cavitated teeth. While ADS activity is higher in healthy teeth, we identify multiple bacterial lineages with upregulated ADS activity on cavitated teeth that are distinct from those found on healthy teeth using both reference-based mapping and de novo assembly methods. Our dual metataxonomic and metatranscriptomic approach demonstrates the importance of species abundance for gene expression data interpretation and that patterns of differential expression can be skewed by low-abundance groups. Finally, we identify several potential candidate probiotic bacterial lineages within species that may be useful therapeutic targets for the prevention of tooth decay and propose that the development of a strain-specific, mixed-microbial probiotic may be a beneficial approach given the heterogeneity of taxa identified here across health groups.

IMPORTANCE

Tooth decay is the most common preventable chronic disease, affecting more than two billion people globally. The development of caries on teeth is primarily a consequence of acid production by cariogenic bacteria that inhabit the plaque microbiome. Other bacterial strains in the oral cavity may suppress or prevent tooth decay by producing ammonia as a byproduct of the arginine deiminase metabolic pathway, increasing the pH of the plaque biofilm. While the benefits of arginine metabolism on oral health have been extensively documented in specific bacterial groups, the prevalence and consistency of arginine deiminase system (ADS) activity among oral bacteria in a community context remain an open question. In the current study, we use a multi-omics approach to document the pervasiveness of the expression of the ADS operon in both health and disease to better understand the conditions in which ADS activity may prevent tooth decay.

Lentzea sokolovensis sp. nov., Lentzea kristufekii sp. nov. and Lentzea miocenica sp. nov., rare actinobacteria from Miocene lacustrine sediment of the Sokolov Coal Basin, Czech Republic

The taxonomic position of three actinobacterial strains, BCCO 10_0061T, BCCO 10_0798T, and BCCO 10_0856T, recovered from bare soil in the Sokolov Coal Basin, Czech Republic, was established using a polyphasic approach. The multilocus sequence analysis based on 100 single-copy genes positioned BCCO 10_0061T in the same cluster as Lentzea waywayandensis, strain BCCO 10_0798T in the same cluster as Lentzea flaviverrucosa, Lentzea californiensis, Lentzea violacea, and Lentzea albidocapillata, and strain BCCO 10_0856T clustered together with Lentzea kentuckyensis and Lentzea alba. Morphological and chemotaxonomic characteristics of these strains support their assignment to the genus Lentzea. In all three strains, MK-9(H4) accounted for more than 80 % of the isoprenoid quinone. The diagnostic diamino acid in the cell-wall peptidoglycan was meso-diaminopimelic acid. The whole-cell sugars were rhamnose, ribose, mannose, glucose, and galactose. The major fatty acids (>10 %) were iso-C15 : 0, anteiso-C15 : 0, iso-C16 : 0, and C16 : 0. The polar lipids were diphosphatidylglycerol, methyl-phosphatidylethanolamine, phosphatidylethanolamine, hydroxy-phosphatidylethanolamine, phosphatidylglycerol, and phosphatidylinositol. The genomic DNA G+C content of strains (mol%) was 68.8 for BCCO 10_0061T, 69.2 for BCCO 10_0798T, and 68.5 for BCCO 10_0856T. The combination of digital DNA-DNA hybridization results, average nucleotide identity values and phenotypic characteristics of BCCO 10_0061T, BCCO 10_0798T, and BCCO 10_0856T distinguishes them from their closely related strains. Bioinformatic analysis of the genome sequences of the strains revealed several biosynthetic gene clusters (BGCs) with identities >50 % to already known clusters, including BGCs for geosmin, coelichelin, ε-poly-l-lysine, and erythromycin-like BGCs. Most of the identified BGCs showed low similarity to known BGCs (<50 %) suggesting their genetic potential for the biosynthesis of novel secondary metabolites. Based on the above results, each strain represents a novel species of the genus Lentzea, for which we propose the name Lentzea sokolovensis sp. nov. for BCCO 10_0061T (=DSM 116175T), Lentzea kristufekii sp. nov. for BCCO 10_0798T (=DSM 116176T), and Lentzea miocenica sp. nov. for BCCO 10_0856T (=DSM 116177T).

EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology

The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies.

Refining the taxonomy of the order Hyphomicrobiales (Rhizobiales) based on whole genome comparisons of over 130 type strains

The alphaproteobacterial order Hyphomicrobiales consists of 38 families comprising at least 152 validly published genera as of January 2024. The order Hyphomicrobiales was first described in 1957 and underwent important revisions in 2020. However, we show that several inconsistencies in the taxonomy of this order remain and we argue that there is a need for a consistent framework for defining families within the order. We propose a common genome-based framework for defining families within the order Hyphomicrobiales, suggesting that families represent monophyletic groups in core-genome phylogenies that share pairwise average amino acid identity values above ~75 % when calculated from a core set of 59 proteins. Applying this framework, we propose the formation of four new families and to reassign the genera Salaquimonas, Rhodoblastus, and Rhodoligotrophos into Salaquimonadaceae fam. nov., Rhodoblastaceae fam. nov., and Rhodoligotrophaceae fam. nov., respectively, and the genera Albibacter, Chenggangzhangella, Hansschlegelia, and Methylopila into Methylopilaceae fam. nov. We further propose to unify the families Bartonellaceae, Brucellaceae, Phyllobacteriaceae, and Notoacmeibacteraceae as Bartonellaceae; the families Segnochrobactraceae and Pseudoxanthobacteraceae as Segnochrobactraceae; the families Lichenihabitantaceae and Lichenibacteriaceae as Lichenihabitantaceae; and the families Breoghaniaceae and Stappiaceae as Stappiaceae. Lastly, we propose to reassign several genera to existing families. Specifically, we propose to reassign the genus Pseudohoeflea to the family Rhizobiaceae; the genera Oricola, Roseitalea, and Oceaniradius to the family Ahrensiaceae; the genus Limoniibacter to the emended family Bartonellaceae; the genus Faunimonas to the family Afifellaceae; and the genus Pseudochelatococcus to the family Chelatococcaceae. Our data also support the recent proposal to reassign the genus Prosthecomicrobium to the family Kaistiaceae.

Modeling the mosaic structure of bacterial genomes to infer their evolutionary history

The chronology and phylogeny of bacterial evolution are difficult to reconstruct due to a scarce fossil record. The analysis of bacterial genomes remains challenging because of large sequence divergence, the plasticity of bacterial genomes due to frequent gene loss, horizontal gene transfer, and differences in selective pressure from one locus to another. Therefore, taking advantage of the rich and rapidly accumulating genomic data requires accurate modeling of genome evolution. An important technical consideration is that loci with high effective mutation rates may diverge beyond the detection limit of the alignment algorithms used, biasing the genome-wide divergence estimates toward smaller divergences. In this article, we propose a novel method to gain insight into bacterial evolution based on statistical properties of genome comparisons. We find that the length distribution of sequence matches is shaped by the effective mutation rates of different loci, by the horizontal transfers, and by the aligner sensitivity. Based on these inputs, we build a model and show that it accounts for the empirically observed distributions, taking the Enterobacteriaceae family as an example. Our method allows to distinguish segments of vertical and horizontal origins and to estimate the time divergence and exchange rate between any pair of taxa from genome-wide alignments. Based on the estimated time divergences, we construct a time-calibrated phylogenetic tree to demonstrate the accuracy of the method.

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Forensic microbiome research is a field with a wide range of applications and a number of protocols have been developed for its use in this area of research. As individuals host radically different microbiota, the human microbiome is expected to become a new biomarker for forensic identification. To achieve an effective use of this procedure an understanding of factors which can alter the human microbiome and determinations of stable and changing elements will be critical in selecting appropriate targets for investigation. The 16S rRNA gene, which is notable for its conservation and specificity, represents a potentially ideal marker for forensic microbiome identification. Gene sequencing involving 16S rRNA is currently the method of choice for use in investigating microbiomes. While the sequencing involved with microbiome determinations can generate large multi-dimensional datasets that can be difficult to analyze and interpret, machine learning methods can be useful in surmounting this analytical challenge. In this review, we describe the research methods and related sequencing technologies currently available for application of 16S rRNA gene sequencing and machine learning in the field of forensic identification. In addition, we assess the potential value of 16S rRNA and machine learning in forensic microbiome science.

Comparative genomic analysis of Microcystis strain diversity using conserved marker genes

Microcystis-dominated cyanobacterial harmful algal blooms (cyanoHABs) have a global impact on freshwater environments, affecting both wildlife and human health. Microcystis diversity and function in field samples and laboratory cultures can be determined by sequencing whole genomes of cultured isolates or natural populations, but these methods remain computationally and financially expensive. Amplicon sequencing of marker genes is a lower cost and higher throughput alternative to characterize strain composition and diversity in mixed samples. However, the selection of appropriate marker gene region(s) and primers requires prior understanding of the relationship between single gene genotype, whole genome content, and phenotype. To identify phylogenetic markers of Microcystis strain diversity, we compared phylogenetic trees built from each of 2,351 individual core genes to an established phylogeny and assessed the ability of these core genes to predict whole genome content and bioactive compound genotypes. We identified single-copy core genes better able to resolve Microcystis phylogenies than previously identified marker genes. We developed primers suitable for current Illumina-based amplicon sequencing with near-complete coverage of available Microcystis genomes and demonstrate that they outperform existing options for assessing Microcystis strain composition. Results showed that genetic markers can be used to infer Microcystis gene content and phenotypes such as potential production of bioactive compounds , although marker performance varies by bioactive compound gene and sequence similarity. Finally, we demonstrate that these markers can be used to characterize the Microcystis strain composition of laboratory or field samples like those collected for surveillance and modeling of Microcystis-dominated cyanobacterial harmful algal blooms.

Robust demarcation of the family Peptostreptococcaceae and its main genera based on phylogenomic studies and taxon-specific molecular markers

The family Peptostreptococcaceae, which contains 15 genera including Clostridioides, presently lacks proper circumscription. Using 52 available genomes for Peptostreptococcaceae species, we report comprehensive phylogenomic and comparative analyses to reliably discern their evolutionary relationships. In phylogenetic trees based on core genome proteins and 16S rRNA gene sequences, the examined species formed a strongly supported clade designated as Peptostreptococcaceae sensu stricto. This clade encompassed the genera Peptostreptococcus (type genus), Asaccharospora, Clostridioides, Intestinibacter, Paeniclostridium, Paraclostridium, Peptacetobacter, Romboutsia and Terrisporobacter, and two misclassified species (viz. Eubacterium tenue and 'Clostridium dakarense'). The distinctness of this clade is strongly supported by eight identified conserved signature indels (CSIs), which are specific for the species from this clade. Based on the robust evidence provided by presented studies, we are proposing the emendment of family Peptostreptococcaceae to only the genera within the Peptostreptococcaceae sensu stricto clade. We also report 67 other novel CSIs, which reliably demarcate different Peptostreptococcaceae species clades and clarify the classification of some misclassified species. Based on the consistent evidence obtained from different presented studies, we are making the following proposals to clarify the classification of Peptostreptococcaceae species: (i) transfer of Eubacterium tenue, Paeniclostridium ghonii and Paeniclostridium sordellii as comb. nov. into the genus Paraclostridium; (ii) transfer of Clostridioides mangenotii as a comb. nov. into Metaclostridioides gen. nov.; (iii) classification of 'Clostridium dakarense' as a novel species Faecalimicrobium dakarense gen. nov., sp. nov. (type strain FF1T; genome and 16S rRNA accession numbers GCA_000499525.1 and KC517358, respectively); (iv) transfer of two misclassified species, Clostridium paradoxum and Clostridium thermoalcaliphilum, into Alkalithermobacter gen. nov.; and (v) proposals for two novel families, Peptoclostridiaceae fam. nov. and Tepidibacteraceae fam. nov., to accommodate remaining unclassified Peptostreptococcaceae genera. The described CSIs specific for different families and genera provide novel and reliable means for the identification, diagnostics and biochemical studies on these bacteria.

A universal and constant rate of gene content change traces pangenome flux to LUCA

Prokaryotic genomes constantly undergo gene flux via lateral gene transfer, generating a pangenome structure consisting of a conserved core genome surrounded by a more variable accessory genome shell. Over time, flux generates change in genome content. Here, we measure and compare the rate of genome flux for 5655 prokaryotic genomes as a function of amino acid sequence divergence in 36 universally distributed proteins of the informational core (IC). We find a clock of gene content change. The long-term average rate of gene content flux is remarkably constant across all higher prokaryotic taxa sampled, whereby the size of the accessory genome-the proportion of the genome harboring gene content difference for genome pairs-varies across taxa. The proportion of species-level accessory genes per genome, varies from 0% (Chlamydia) to 30%-33% (Alphaproteobacteria, Gammaproteobacteria, and Clostridia). A clock-like rate of gene content change across all prokaryotic taxa sampled suggest that pangenome structure is a general feature of prokaryotic genomes and that it has been in existence since the divergence of bacteria and archaea.

Multicenter evaluation of gut microbiome profiling by next-generation sequencing reveals major biases in partial-length metabarcoding approach

Next-generation sequencing workflows, using either metabarcoding or metagenomic approaches, have massively contributed to expanding knowledge of the human gut microbiota, but methodological bias compromises reproducibility across studies. Where these biases have been quantified within several comparative analyses on their own, none have measured inter-laboratory reproducibility using similar DNA material. Here, we designed a multicenter study involving seven participating laboratories dedicated to partial- (P1 to P5), full-length (P6) metabarcoding, or metagenomic profiling (MGP) using DNA from a mock microbial community or extracted from 10 fecal samples collected at two time points from five donors. Fecal material was collected, and the DNA was extracted according to the IHMS protocols. The mock and isolated DNA were then provided to the participating laboratories for sequencing. Following sequencing analysis according to the laboratories' routine pipelines, relative taxonomic-count tables defined at the genus level were provided and analyzed. Large variations in alpha-diversity between laboratories, uncorrelated with sequencing depth, were detected among the profiles. Half of the genera identified by P1 were unique to this partner and two-thirds of the genera identified by MGP were not detected by P3. Analysis of beta-diversity revealed lower inter-individual variance than inter-laboratory variances. The taxonomic profiles of P5 and P6 were more similar to those of MGP than those obtained by P1, P2, P3, and P4. Reanalysis of the raw sequences obtained by partial-length metabarcoding profiling, using a single bioinformatic pipeline, harmonized the description of the bacterial profiles, which were more similar to each other, except for P3, and closer to the profiles obtained by MGP. This study highlights the major impact of the bioinformatics pipeline, and primarily the database used for taxonomic annotation. Laboratories need to benchmark and optimize their bioinformatic pipelines using standards to monitor their effectiveness in accurately detecting taxa present in gut microbiota.

A gut microbiome signature for HIV and metabolic dysfunction-associated steatotic liver disease

Introduction

Metabolic dysfunction-associated steatotic liver disease (MASLD), has emerged as an increasingly recognized problem among people living with HIV (PLWH). The gut-liver axis is considered to be strongly implicated in the pathogenesis of MASLD. We aimed to characterize the gut microbiota composition in PLWH and MASLD and compare it with that of two control groups: PLWH without MASLD and individuals with MASLD without HIV infection.

Methods

We collected clinical data and stool samples from participants. Bacterial 16S rRNA genes were amplified, sequenced, and clustered into operational taxonomic unit. Alpha diversity was studied by Shannon and Simpson indexes. To study how different the gut microbiota composition is between the different groups, beta diversity estimation was evaluated by principal coordinate analysis (PCoA) using Bray-Curtis dissimilarity. To further analyze differences in microbiome composition we performed a linear discriminant analysis (LDA) effect size (LEfSe).

Results

We included 30 HIV+MASLD+, 30 HIV+MASLD- and 20 HIV-MASLD+ participants. Major butyrate producers, including Faecalibacterium, Ruminococcus, and Lachnospira dominated the microbiota in all three groups. Shannon's and Simpson's diversity metrics were higher among MASLD+ individuals (Kruskal-Wallis p = 0.047). Beta diversity analysis showed distinct clustering in MASLD-, with MASLD+ participants overlapping regardless of HIV status (ADONIS significance <0.001). MASLD was associated with increased homogeneity across individuals, in contrast to that observed in the HIV+NAFDL- group, in which the dispersion was higher (Permanova test, p value <0.001; ANOSIM, p value <0.001). MASLD but not HIV determined a different microbiota structure (HIV+MASLD- vs. HIV+MASLD+, q-value = 0.002; HIV-MASLD+ vs. HIV+MASLD+, q-value = 0.930; and HIV-MASLD+ vs. HIV+MASLD-, q-value < 0.001). The most abundant genera in MASLD- were Prevotella, Bacteroides, Dialister, Acidaminococcos, Alloprevotella, and Catenibacterium. In contrast, the most enriched genera in MASLD+ were Ruminococcus, Streptococcus, Holdemanella, Blautia, and Lactobacillus.

Conclusions

We found a microbiome signature linked to MASLD, which had a greater influence on the overall structure of the gut microbiota than HIV status alone.

Microbial symbionts are shared between ants and their associated beetles

The transmission of microbial symbionts across animal species could strongly affect their biology and evolution, but our understanding of transmission patterns and dynamics is limited. Army ants (Formicidae: Dorylinae) and their hundreds of closely associated insect guest species (myrmecophiles) can provide unique insights into interspecific microbial symbiont sharing. Here, we compared the microbiota of workers and larvae of the army ant Eciton burchellii with those of 13 myrmecophile beetle species using 16S rRNA amplicon sequencing. We found that the previously characterized specialized bacterial symbionts of army ant workers were largely absent from ant larvae and myrmecophiles, whose microbial communities were usually dominated by Rickettsia, Wolbachia, Rickettsiella and/or Weissella. Strikingly, different species of myrmecophiles and ant larvae often shared identical 16S rRNA genotypes of these common bacteria. Protein-coding gene sequences confirmed the close relationship of Weissella strains colonizing army ant larvae, some workers and several myrmecophile species. Unexpectedly, these strains were also similar to strains infecting dissimilar animals inhabiting very different habitats: trout and whales. Together, our data show that closely interacting species can share much of their microbiota, and some versatile microbial species can inhabit and possibly transmit across a diverse range of hosts and environments.

Comparison of Oral Microbial Composition and Determinants Encoding Antimicrobial Resistance in Dogs and Their Owners

Consolidated studies on animal, human, and environmental health have become very important for understanding emerging zoonotic diseases and the spread of antimicrobial resistance (AMR). The aim of this study was to analyse the oral microbiomes of healthy dogs and their owners, including determinants of AMR. Shotgun metagenomic sequencing detected 299 bacterial species in pets and their owners, from which 70 species were carried by dogs and 229 species by humans. Results demonstrated a unique microbial composition of dogs and their owners. At an order level, Bacteroidales were the most prevalent oral microbiota of dogs with significantly lower prevalence in their owners where Actinomycetales and Lactobacillales predominated. Porphyromonas and Corynebacterium were the most prevalent genera in dogs, whereas Streptococcus and Actinomyces were in animal owners. The resistances to macrolides, tetracyclines, lincosamides and Cfx family A class broad-spectrum β-lactamase were detected in both animal and human microbiomes. Resistance determinants to amphenicols, aminoglycosides, sulphonamides, and quaternary ammonium compounds were detected exceptionally in dogs. In conclusion, the study demonstrated different bacterial composition in oral microbiomes of healthy dogs without clinical signs of periodontal disease and their owners. Due to the low numbers of the samples tested, further investigations with an increased number of samples should be performed.

Phenotypic and Genomic Characterization of Streptomyces pakalii sp. nov., a Novel Species with Anti-Biofilm and Anti-Quorum Sensing Activity in ESKAPE Bacteria

The increasing number of infections caused by antimicrobial multi-resistant microorganisms has led to the search for new microorganisms capable of producing novel antibiotics. This work proposes Streptomyces pakalii sp. nov. as a new member of the Streptomycetaceae family. The strain ENCB-J15 was isolated from the jungle soil in Palenque National Park, Chiapas, Mexico. The strain formed pale brown, dry, tough, and buried colonies in the agar with no diffusible pigment in GAE (glucose-asparagine-yeast extract) medium. Scanning electron micrographs showed typical mycelium with long chains of smooth and oval-shaped spores (3-10 m). The strain grew in all of the International Streptomyces Project (ISP)'s media at 28-37 °C with a pH of 6-9 and 0-10% NaCl. S. pakalii ENCB-J15 assimilated diverse carbon as well as organic and inorganic nitrogen sources. The strain also exhibited significant inhibitory activity against the prodigiosin synthesis of Serratia marcescens and the inhibition of the formation and destruction of biofilms of ESKAPE strains of Acinetobacter baumannii and Klebsiella pneumoniae. The draft genome sequencing of ENCB-J15 revealed a 7.6 Mb genome with a high G + C content (71.6%), 6833 total genes, and 6746 genes encoding putative proteins. A total of 26 accessory clusters of proteins associated with carbon sources and amino acid catabolism, DNA modification, and the antibiotic biosynthetic process were annotated. The 16S rRNA gene phylogeny, core-proteome phylogenomic tree, and virtual genome fingerprints support that S. pakalii ENCB-J15 is a new species related to Streptomyces badius and Streptomyces globisporus. Similarly, its average nucleotide identity (ANI) (96.4%), average amino acid identity (AAI) (96.06%), and virtual DNA-DNA hybridization (67.3%) provide evidence to recognize it as a new species. Comparative genomics revealed that S. pakalli and its closest related species maintain a well-conserved genomic synteny. This work proposes Streptomyces pakalii sp. nov. as a novel species that expresses anti-biofilm and anti-quorum sensing activities.

Oral and Gut Microbiota Dysbiosis is Associated with Mucositis Severity in Autologous Hematopoietic Stem Cell Transplantation: Evidence from an Asian Population

Mucositis is a debilitating complication of hematopoietic stem cell transplantation (HSCT). It is unclear how changes in the composition of microbiota, which are modulated by geographical location and ethnicity, may influence immune regulation leading to the development of mucositis, and the study of both oral and gut microbiota in a single population of autologous HSCT in the Asian region is lacking. The present study aimed to characterize the oral and gut microbiota changes, and the impact on both oral and lower gastrointestinal (GI) mucositis, with associated temporal changes in a population of adult recipients of autologous HSCT. Autologous HSCT recipients age ≥18 years were recruited from Hospital Ampang, Malaysia, between April 2019 and December 2020. Mucositis assessments were conducted daily, and blood, saliva, and fecal samples were collected prior to conditioning, on day 0, and at 7 days and 6 months post-transplantation. Longitudinal differences in alpha diversity and beta diversity were determined using the Wilcoxon signed-rank test and permutational multivariate analysis of variance, respectively. Changes in relative abundances of bacteria across time points were assessed using the microbiome multivariate analysis by linear models function. The combined longitudinal effects of clinical, inflammatory, and microbiota variables on mucositis severity were measured using the generalized estimating equation. Among the 96 patients analyzed, oral mucositis and diarrhea (representing lower GI mucositis) occurred in 58.3% and 95.8%, respectively. Alpha and beta diversities were significantly different between sample types (P < .001) and across time points, with alpha diversity reaching statistical significance at day 0 in fecal samples (P < .001) and at day +7 in saliva samples (P < .001). Diversities normalized to baseline by 6 months post-transplantation. Significant microbiota, clinical, and immunologic factors were associated with increasing mucositis grades. Increasing relative abundances of saliva Paludibacter, Leuconostoc, and Proteus were associated with higher oral mucositis grades, whereas increasing relative abundances of fecal Rothia and Parabacteroides were associated with higher GI mucositis grades. Meanwhile, increasing relative abundances of saliva Lactococcus and Acidaminococcus and fecal Bifidobacterium were associated with protective effects against worsening oral and GI mucositis grades, respectively. This study provides real-world evidence and insights into the dysbiosis of the microbiota in patients exposed to conditioning regimen during HSCT. Independent of clinical and immunologic factors, we demonstrated significant associations between relative bacteria abundances with the increasing severity of oral and lower GI mucositis. Our findings offer a potential rationale to consider the inclusion of preventive and restorative measures targeting oral and lower GI dysbiosis as interventional strategies to ameliorate mucositis outcome in HSCT recipients.

Early Divergence and Gene Exchange Highways in the Evolutionary History of Mesoaciditogales

The placement of a nonhyperthermophilic order Mesoaciditogales as the earliest branching clade within the Thermotogota phylum challenges the prevailing hypothesis that the last common ancestor of Thermotogota was a hyperthermophile. Yet, given the long branch leading to the only two Mesoaciditogales described to date, the phylogenetic position of the order may be due to the long branch attraction artifact. By testing various models and applying data recoding in phylogenetic reconstructions, we observed that early branching of Mesoaciditogales within Thermotogota is strongly supported by the conserved marker genes assumed to be vertically inherited. However, based on the taxonomic content of 1,181 gene families and a phylogenetic analysis of 721 gene family trees, we also found that a substantial number of Mesoaciditogales genes are more closely related to species from the order Petrotogales. These genes contribute to coenzyme transport and metabolism, fatty acid biosynthesis, genes known to respond to heat and cold stressors, and include many genes of unknown functions. The Petrotogales comprise moderately thermophilic and mesophilic species with similar temperature tolerances to that of Mesoaciditogales. Our findings hint at extensive horizontal gene transfer (HGT) between, or parallel independent gene gains by, the two ecologically similar lineages and suggest that the exchanged genes may be important for adaptation to comparable temperature niches.

Bacillus pfraonensis sp. nov., a new strain isolated from a probiotic feed additive with low cytotoxicity and antimicrobial activity

Probiotic products containing living microorganisms are gaining popularity, increasing the importance of their taxonomic status. A Bacillus-like isolate, 70 b, cultured from a probiotic feed additive, was ambiguity in taxonomic assignment and could be a novel member of Bacillus cereus group. The results of colony and cellular morphology, physiological and biochemical analysis mainly including growth performance, carbon source utilization, and rMLST and MLST were not conclusive. Fatty acids profile and molecular genetic analysis especially ANI, DDH, and core genome SNPs-based phylogenetic tree confirmed 70 b as one novel species of B. cereus group and proposed as Bacillus pfraonensis sp. nov. Comparative genomic analysis revealed the genetic differences between 70 b and other species of B. cereus group. Pseudomycoicidin was identified in 70 b. 70 b was active against multidrug-resistant pathogenic strains MRSA. The findings support 70 b is a novel species with low cytotoxicity and antimicrobial activity, and provides a better understanding of its unique characteristics and probiotic potential, and exploration of bioactive potential.