Phosphoribosylpyrophosphate synthetase as a metabolic valve advances Methylobacterium/Methylorubrum phyllosphere colonization and plant growth.

The proficiency of phyllosphere microbiomes in efficiently utilizing plant-provided nutrients is pivotal for their successful colonization of plants. The methylotrophic capabilities of Methylobacterium/Methylorubrum play a crucial role in this process. However, the precise mechanisms facilitating efficient colonization remain elusive. In the present study, we investigate the significance of methanol assimilation in shaping the success of mutualistic relationships between methylotrophs and plants. A set of strains originating from Methylorubrum extorquens AM1 are subjected to evolutionary pressures to thrive under low methanol conditions. A mutation in the phosphoribosylpyrophosphate synthetase gene is identified, which converts it into a metabolic valve. This valve redirects limited C1-carbon resources towards the synthesis of biomass by up-regulating a non-essential phosphoketolase pathway. These newly acquired bacterial traits demonstrate superior colonization capabilities, even at low abundance, leading to increased growth of inoculated plants. This function is prevalent in Methylobacterium/Methylorubrum strains. In summary, our findings offer insights that could guide the selection of Methylobacterium/Methylorubrum strains for advantageous agricultural applications.

Functional diversity of bacterial microbiota associated with the toxigenic benthic dinoflagellate Prorocentrum.

Interactions between bacterial microbiota and epibenthic species of the dinoflagellate Prorocentrum may define the onset and persistence of benthic harmful algal blooms (bHABs). Chemical ecological interactions within the dinoflagellate phycosphere potentially involve a complex variety of organic molecules, metabolites, and toxins, including undefined bioactive compounds. In this study, the bacterial diversity and core members of the dinoflagellate-associated microbiota were defined from 11 strains of three epibenthic Prorocentrum species, representing three geographically disjunct locations within Mexican coastal waters. Microbiota profiles in stable monoclonal Prorocentrum cultures were obtained by sequencing amplicons of the V3-V4 region of the 16S rRNA gene. Thirteen classes of bacteria were identified among dinoflagellate clones, where Alphaproteobacteria, Gammaproteobacteria, and Bacteroidia were consistently dominant. The bacterial community structure exhibited significantly different grouping by the location of origin of dinoflagellate clones. No significant diversity difference was found among free-living or unattached bacteria in the dinoflagellate culture medium (M) compared with those in closer association with the dinoflagellate host cells (H). Twelve taxa were defined as core members of the bacterial assemblage, representing the genera Algiphilus, Cohaesibacter, Labrenzia, Mameliella, Marinobacter, Marivita, Massilia, Muricauda, Roseitalea, and an unclassified member of the Rhodobacteraceae. The core members are inferred to significantly contribute to primary and secondary metabolic functions, but no direct correlation with dinoflagellate toxigenicity was apparent. Overall the bacterial profile and implied gene functionality indicated a suite of positive interactions, suggesting either mutualism or commensalism with the dinoflagellate. The further characterization and interpretation of specific gene functions and interactions between bacteria and dinoflagellates, such as epibenthic members of genus Prorocentrum, are key to understanding their role in toxigenesis and bHAB development.

CViewer: a Java-based statistical framework for integration of shotgun metagenomics with other omics datasets.

BACKGROUND: Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, the latter of which then helps retrieve their function based on annotated gene products, mRNA, protein, and metabolites. Within the context of a specific hypothesis, additional modalities are often included, to give host-microbiome interaction. For example, in human-associated microbiome projects, it has become increasingly common to include host immunology through flow cytometry. Whilst there are plenty of software approaches available, some that utilize marker-based and assembly-based approaches, for downstream statistical analyses, there is still a dearth of statistical tools that help consolidate all such information in a single platform. By virtue of stringent computational requirements, the statistical workflow is often passive with limited visual exploration. RESULTS: In this study, we have developed a Java-based statistical framework ( https://github.com/KociOrges/cviewer ) to explore shotgun metagenomics data, which integrates seamlessly with conventional pipelines and offers exploratory as well as hypothesis-driven analyses. The end product is a highly interactive toolkit with a multiple document interface, which makes it easier for a person without specialized knowledge to perform analysis of multiomics datasets and unravel biologically relevant patterns. We have designed algorithms based on frequently used numerical ecology and machine learning principles, with value-driven from integrated omics tools which not only find correlations amongst different datasets but also provide discrimination based on case-control relationships. CONCLUSIONS: CViewer was used to analyse two distinct metagenomic datasets with varying complexities. These include a dietary intervention study to understand Crohn's disease changes during a dietary treatment to include remission, as well as a gut microbiome profile for an obesity dataset comparing subjects who suffer from obesity of different aetiologies and against controls who were lean. Complete analyses of both studies in CViewer then provide very powerful mechanistic insights that corroborate with the published literature and demonstrate its full potential. Video Abstract.

Biodiversity Analysis of Metaproteomics Samples with Unipept: A Comprehensive Tutorial.

Metaproteomics has become a crucial omics technology for studying microbiomes. In this area, the Unipept ecosystem, accessible at https://unipept.ugent.be , has emerged as a valuable resource for analyzing metaproteomic data. It offers in-depth insights into both taxonomic distributions and functional characteristics of complex ecosystems. This tutorial explains essential concepts like Lowest Common Ancestor (LCA) determination and the handling of peptides with missed cleavages. It also provides a detailed, step-by-step guide on using the Unipept Web application and Unipept Desktop for thorough metaproteomics analyses. By integrating theoretical principles with practical methodologies, this tutorial empowers researchers with the essential knowledge and tools needed to fully utilize metaproteomics in their microbiome studies.

Analysis of the northern pitcher plant (Sarracenia purpurea L.) phytotelm bacteriome throughout a temperate region growing season.

The insectivorous Northern Pitcher Plant, Sarracenia purpurea, recruits a dynamic biotic community in the rainwater collected by its pitcher-shaped leaves. Insect capture and degradation within the pitcher fluid (phytotelma) has been well documented as a mechanism for supplementing the plant's nitrogen, phosphorous, and micronutrient requirements. Metagenomic studies have shown a diverse microbiome in this phytotelm environment, including taxa that contribute metabolically to prey digestion. In this investigation, we used high-throughput 16S rDNA sequencing and bioinformatics to analyze the S. purpurea phytotelm bacteriome as it changes through the growing season (May-September) in plants from the north-central region of the species' native range. Additionally, we used molecular techniques to detect and quantify bacterial nitrogenase genes (nifH) in all phytotelm samples to explore the hypothesis that diazotrophy is an additional mechanism of supplying biologically available nitrogen to S. purpurea. The results of this study indicate that while prokaryote diversity remains relatively stable in plants at different locations within our region, diversity changes significantly as the growing season progresses. Furthermore, nifH genes were detected at biologically significant concentrations in one hundred percent of samples, suggesting that nitrogen fixation may be an important contributor to the S. purpurea nutrient budget.

Exploring the Relationship between MicroRNAs, Intratumoral Microbiota, and Breast Cancer Progression in Patients with and without Metastasis.

Breast cancer (BC) continues to pose a significant burden on global cancer-related morbidity and mortality, primarily driven by metastasis. However, the combined influence of microRNAs (miRNAs) and intratumoral microbiota on BC metastasis remains largely unexplored. In this study, we aimed to elucidate the interplay between intratumoral microbiota composition, miRNA expression profiles, and their collective influence on metastasis development in BC patients by employing 16S rRNA sequencing and qPCR methodologies. Our findings revealed an increase in the expression of miR-149-5p, miR-20b-5p, and miR-342-5p in metastatic breast cancer (Met-BC) patients. The Met-BC patients exhibited heightened microbial richness and diversity, primarily attributed to diverse pathogenic bacteria. Taxonomic analysis identified several pathogenic and pro-inflammatory species enriched in Met-BC, contrasting with non-metastatic breast cancer (NonMet-BC) patients, which displayed an enrichment in potential probiotic and anti-inflammatory species. Notably, we identified and verified a baseline prognostic signature for metastasis in BC patients, with its clinical relevance further validated by its impact on overall survival. In conclusion, the observed disparities in miRNA expression and species-level bacterial abundance suggest their involvement in BC progression. The development of a prognostic signature holds promise for metastasis risk assessment, paving the way for personalized interventions and improved clinical outcomes in BC patients.

Analysis of the Diversity and Functional Potential of Bacterial Communities in Tuberculomas.

The dynamics of lung microbiota in tuberculosis remains poorly understood. Sequencing of variable regions of the 16S rRNA gene from surgically excised tuberculosis foci and biopsy specimens of normal lung tissue allowed characterization of the diversity and predictive potential of bacterial communities. Taxonomic diversity indices attested to differences in the structure of microbial communities between "healthy" lungs and tuberculomas. The microbial composition of "healthy" lungs varied in taxonomic diversity and was presented by both gram-positive and gram-negative bacteria with sufficiently similar metabolic potential. The microbiota of the examined tuberculomas consisted of Mycobacterium tuberculosis in 99.9% of cases. A significant part of the metabolic pathways predicted by PICRUSt2 included cholesterol catabolism, sulfate assimilation, and various pathways for the biosynthesis of cell wall components.

Microbial diversity and ecological complexity emerging from environmental variation and horizontal gene transfer in a simple mathematical model.

BACKGROUND: Microbiomes are generally characterized by high diversity of coexisting microbial species and strains, and microbiome composition typically remains stable across a broad range of conditions. However, under fixed conditions, microbial ecology conforms with the exclusion principle under which two populations competing for the same resource within the same niche cannot coexist because the less fit population inevitably goes extinct. Therefore, the long-term persistence of microbiome diversity calls for an explanation. RESULTS: To explore the conditions for stabilization of microbial diversity, we developed a simple mathematical model consisting of two competing populations that could exchange a single gene allele via horizontal gene transfer (HGT). We found that, although in a fixed environment, with unbiased HGT, the system obeyed the exclusion principle, in an oscillating environment, within large regions of the phase space bounded by the rates of reproduction and HGT, the two populations coexist. Moreover, depending on the parameter combination, all three major types of symbiosis were obtained, namely, pure competition, host-parasite relationship, and mutualism. In each of these regimes, certain parameter combinations provided for synergy, that is, a greater total abundance of both populations compared to the abundance of the winning population in the fixed environment. CONCLUSIONS: The results of this modeling study show that basic phenomena that are universal in microbial communities, namely, environmental variation and HGT, provide for stabilization and persistence of microbial diversity, and emergence of ecological complexity.

Familial clustering of dysbiotic oral and fecal microbiomes in juvenile dermatomyositis.

Juvenile dermatomyositis (JDM) is a rare immune-mediated disease of childhood with putative links to microbial exposures. In this multi-center, prospective, observational cohort study, we evaluated whether JDM is associated with discrete oral and gut microbiome signatures. We generated 16S rRNA sequencing data from fecal, saliva, supragingival, and subgingival plaque samples from JDM probands (n = 28). To control for genetic and environmental determinants of microbiome community structure, we also profiled microbiomes of unaffected family members (n = 27 siblings, n = 26 mothers, and n = 17 fathers). Sample type (oral-vs-fecal) and nuclear family unit were the predominant variables explaining variance in microbiome diversity, more so than having a diagnosis of JDM. The oral and gut microbiomes of JDM probands were more similar to their own unaffected siblings than they were to the microbiomes of other JDM probands. In a sibling-paired within-family analysis, several potentially immunomodulatory bacterial taxa were differentially abundant in the microbiomes of JDM probands compared to their unaffected siblings, including Faecalibacterium (gut) and Streptococcus (oral cavity). While microbiome features of JDM are often shared by unaffected family members, the loss or gain of specific fecal and oral bacteria may play a role in disease pathogenesis or be secondary to immune dysfunction in susceptible individuals.

Deep metagenomic sequencing unveils novel SAR202 lineages and their vertical adaptation in the ocean.

SAR202 bacteria in the Chloroflexota phylum are abundant and widely distributed in the ocean. Their genome coding capacities indicate their potential roles in degrading complex and recalcitrant organic compounds in the ocean. However, our understanding of their genomic diversity, vertical distribution, and depth-related metabolisms is still limited by the number of assembled SAR202 genomes. In this study, we apply deep metagenomic sequencing (180 Gb per sample) to investigate microbial communities collected from six representative depths at the Bermuda Atlantic Time Series (BATS) station. We obtain 173 SAR202 metagenome-assembled genomes (MAGs). Intriguingly, 154 new species and 104 new genera are found based on these 173 SAR202 genomes. We add 12 new subgroups to the current SAR202 lineages. The vertical distribution of 20 SAR202 subgroups shows their niche partitioning in the euphotic, mesopelagic, and bathypelagic oceans, respectively. Deep-ocean SAR202 bacteria contain more genes and exhibit more metabolic potential for degrading complex organic substrates than those from the euphotic zone. With deep metagenomic sequencing, we uncover many new lineages of SAR202 bacteria and their potential functions which greatly deepen our understanding of their diversity, vertical profile, and contribution to the ocean's carbon cycling, especially in the deep ocean.

Molecular identification of Halomonas AZ07 and its multifunctional enzymatic activities to degrade Pyropia yezoensis under high-temperature condition.

BACKGROUND: Pyropia yezoensis a commercially important red seaweed species, is susceptible to various microorganisms infections, among which bacterial infections are the most prominent ones. Pyropia yezoensis is often affected by harmful bacterial communities under high temperatures that can lead to its degradation and economic losses. The current study aimed to explore Pyropia yezoensis-associated microbiota and further identify potential isolates, which can degrade Pyropia yezoensis under high-temperature conditions. METHODS AND RESULTS: The 16S rRNA gene sequencing was used to identify the agarolytic bacterial species. The results showed that Chromohalobacter sp. strain AZ6, Pseudoalteromonas sp. strain AZ, Psychrobacter sp. strain AZ3, Vibrio sp. strain AZ, and Halomonas sp. strain AZ07 exhibited algicidal properties as these strains were more abundant at high temperature (25 °C). Among the five isolated strains, the potential isolate Halomonas sp. strain AZ07 showed high production of agarolytic enzymes, including lipase, protease, cellulase, and amylase. This study confirmed that the isolated strain could produce these four different enzymes. The strain Halomonas AZ07 was co-treated with Pyropia yezoensis cells under two different temperature environments, including 13 °C and 25 °C. The degradation of Pyropia yezoensis occurred at the optimum temperature of 25 °C and effectively degraded their cell wall, proteins, lipids, and carbohydrates. CONCLUSION: The successful cultivation of Pyropia yezoensis in coastal farm environments is dependent on specific temperature and environmental factors, and lower temperatures have been observed to be particularly beneficial for the survival and growth of Pyropia yezoensis. The temperature below 13 °C was confirmed to be the best niche for the symbiotic relationship of microbiota associated with Pyropia yezoensis for its growth, development, and production.

Comparative metagenomic analysis from Sundarbans ecosystems advances our understanding of microbial communities and their functional roles.

The Sundarbans mangrove, located at the mouth of the Ganges and Brahmaputra Rivers, is the world's largest tidal mangrove forest. These mangroves are also one of the most striking sources of microbial diversity, essential in productivity, conservation, nutrient cycling, and rehabilitation. Hence, the main objective of this study was to use metagenome analysis and provide detailed insight into microbial communities and their functional roles in the Sundarbans mangrove ecosystem. A comparative analysis was also done with a non-mangrove region of the Sundarbans ecosystem to assess the capability of the environmental parameters to explain the variation in microbial community composition. The study found several dominant bacteria, viz., Alphaproteobacteria, Actinomycetota, Bacilli, Clostridia, Desulfobacterota, Gammaproteobacteria, and Nitrospira, from the mangrove region. The mangrove sampling site reports several salt-tolerant bacteria like Alkalibacillus haloalkaliphilus, Halomonas anticariensis, and Salinivibrio socompensis. We found some probiotic species, viz., Bacillus clausii, Lactobacillus curvatus, Vibrio mediterranei and Vibrio fluvialis, from the Sundarbans mangrove. Nitrifying bacteria in Sundarbans soils were Nitrococcus mobilis, Nitrosococcus oceani, Nitrosomonas halophila, Nitrospirade fluvii, and others. Methanogenic archaea, viz., Methanoculleus marisnigri, Methanobrevibacter gottschalkii, and Methanolacinia petrolearia, were highly abundant in the mangroves as compared to the non-mangrove soils. The identified methanotrophic bacterial species, viz., Methylobacter tundripaludum, Methylococcus capsulatus, Methylophaga thiooxydans, and Methylosarcina lacus are expected to play a significant role in the degradation of methane in mangrove soil. Among the bioremediation bacterial species identified, Pseudomonas alcaligenes, Pseudomonas mendocina, Paracoccus denitrificans, and Shewanella putrefaciens play a significant role in the remediation of environmental pollution. Overall, our study shows for the first time that the Sundarbans, the largest mangrove ecosystem in the world, has a wide range of methanogenic archaea, methanotrophs, pathogenic, salt-tolerant, probiotic, nitrifying, and bioremediation bacteria.

Molecular characterization of vaginal microbiota using a new 22-species qRT-PCR test to achieve a relative-abundance and species-based diagnosis of bacterial vaginosis.

Background: Numerous bacteria are involved in the etiology of bacterial vaginosis (BV). Yet, current tests only focus on a select few. We therefore designed a new test targeting 22 BV-relevant species. Methods: Using 946 stored vaginal samples, a new qPCR test that quantitatively identifies 22 bacterial species was designed. The distribution and relative abundance of each species, α- and ß-diversities, correlation, and species co-existence were determined per sample. A diagnostic index was modeled from the data, trained, and tested to classify samples into BV-positive, BV-negative, or transitional BV. Results: The qPCR test identified all 22 targeted species with 95 - 100% sensitivity and specificity within 8 hours (from sample reception). Across most samples, Lactobacillus iners, Lactobacillus crispatus, Lactobacillus jensenii, Gardnerella vaginalis, Fannyhessea (Atopobium) vaginae, Prevotella bivia, and Megasphaera sp. type 1 were relatively abundant. BVAB-1 was more abundant and distributed than BVAB-2 and BVAB-3. No Mycoplasma genitalium was found. The inter-sample similarity was very low, and correlations existed between key species, which were used to model, train, and test a diagnostic index: MDL-BV index. The MDL-BV index, using both species and relative abundance markers, classified samples into three vaginal microbiome states. Testing this index on our samples, 491 were BV-positive, 318 were BV-negative, and 137 were transitional BV. Although important differences in BV status were observed between different age groups, races, and pregnancy status, they were statistically insignificant. Conclusion: Using a diverse and large number of vaginal samples from different races and age groups, including pregnant women, the new qRT-PCR test and MDL-BV index efficiently diagnosed BV within 8 hours (from sample reception), using 22 BV-associated species.

Metagenomic insights into microbial community structure and metabolism in alpine permafrost on the Tibetan Plateau.

Permafrost, characterized by its frozen soil, serves as a unique habitat for diverse microorganisms. Understanding these microbial communities is crucial for predicting the response of permafrost ecosystems to climate change. However, large-scale evidence regarding stratigraphic variations in microbial profiles remains limited. Here, we analyze microbial community structure and functional potential based on 16S rRNA gene amplicon sequencing and metagenomic data obtained from an ∼1000 km permafrost transect on the Tibetan Plateau. We find that microbial alpha diversity declines but beta diversity increases down the soil profile. Microbial assemblages are primarily governed by dispersal limitation and drift, with the importance of drift decreasing but that of dispersal limitation increasing with soil depth. Moreover, genes related to reduction reactions (e.g., ferric iron reduction, dissimilatory nitrate reduction, and denitrification) are enriched in the subsurface and permafrost layers. In addition, microbial groups involved in alternative electron accepting processes are more diverse and contribute highly to community-level metabolic profiles in the subsurface and permafrost layers, likely reflecting the lower redox potential and more complicated trophic strategies for microorganisms in deeper soils. Overall, these findings provide comprehensive insights into large-scale stratigraphic profiles of microbial community structure and functional potentials in permafrost regions.

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an extensible framework with two new deep learning models (i.e., FunTrans and FunRep), structured databases, and supporting resources for achieving highly accurate (Accuracy > 0.99, F1-score > 0.97) and fine-grained classification of antibiotic resistance genes (ARGs) and virulence factor genes. Using an experimentally confirmed dataset of ARGs comprising remote homologous sequences as the test set, our framework achieves by-far-the-best performance in the discovery of new ARGs from human gut (F1-score: 0.6948), wastewater (0.6072), and soil (0.5445) microbiomes, beating the state-of-the-art bioinformatics tools and sequence alignment-based (F1-score: 0.0556-0.5065) and domain-based (F1-score: 0.2630-0.5224) annotation approaches. Furthermore, our framework is implemented as a lightweight, privacy-preserving, and plug-and-play neural network module, facilitating its versatility and accessibility to developers and users worldwide. We anticipate widespread utilization of FunGeneTyper (https://github.com/emblab-westlake/FunGeneTyper) for precise classification of protein-coding gene functions and the discovery of numerous valuable enzymes. This advancement will have a significant impact on various fields, including microbiome research, biotechnology, metagenomics, and bioinformatics.

Molecular analyses indicate profuse bacterial diversity in primary and post- treatment endodontic infections within a cohort from the United Arab Emirates-A preliminary study.

OBJECTIVE: Endodontic microbiota appears to undergo evolutionary changes during disease progression from inflammation to necrosis and post-treatment. The aim of this study was to compare microbiome composition and diversity in primary and post-treatment endodontic infections from a cohort of patients from the UAE. DESIGN: Intracanal samples were collected from primarily infected (n = 10) and post-treatment infected (n = 10) root canals of human teeth using sterile paper points. Bacterial DNA was amplified from seven hypervariable regions (V2-V4 and V6-V9) of the 16S rRNA gene, then sequenced using next-generation sequencing technology. The data was analyzed using appropriate bioinformatic tools. RESULTS: Analyses of all the samples revealed eight major bacterial phyla, 112 genera and 260 species. Firmicutes was the most representative phylum in both groups and was significantly more abundant in the post-treatment (54.4%) than in primary (32.2%) infections (p>0.05). A total of 260 operational taxonomic units (OTUs) were identified, of which 126 (48.5%) were shared between the groups, while 83 (31.9%) and 51 (19.6%) disparate species were isolated from primary and post-treatment infections, respectively. A significant difference in beta, but not alpha diversity was noted using several different indices (p< 0.05). Differential abundance analysis indicated that, Prevotella maculosa, Streptococcus constellatus, Novosphigobium sediminicola and Anaerococcus octavius were more abundant in primary infections while Enterrococcus faecalis, Bifidobacterium dentium, Olsenella profusa and Actinomyces dentalis were more abundant in post-treatment infections (p <0.05). CONCLUSION: Significant differences in the microbiome composition and diversity in primary and post-treatment endodontic infections were noted in our UAE cohort. Such compositional differences of microbiota at various stages of infection could be due to both intrinsic and extrinsic factors impacting the root canal ecosystem during disease progression, as well as during their therapeutic management. Identification of the key microbiota in primarily and secondarily infected root canals can guide in the management of these infections.

Genomic representativeness and chimerism in large collections of SAGs and MAGs of marine prokaryoplankton.

BACKGROUND: Single amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) are the predominant sources of information about the coding potential of uncultured microbial lineages, but their strengths and limitations remain poorly understood. Here, we performed a direct comparison of two previously published collections of thousands of SAGs and MAGs obtained from the same, global environment. RESULTS: We found that SAGs were less prone to chimerism and more accurately reflected the relative abundance and the pangenome content of microbial lineages inhabiting the epipelagic of the tropical and subtropical ocean, as compared to MAGs. SAGs were also better suited to link genome information with taxa discovered through 16S rRNA amplicon analyses. Meanwhile, MAGs had the advantage of more readily recovering genomes of rare lineages. CONCLUSIONS: Our analyses revealed the relative strengths and weaknesses of the two most commonly used genome recovery approaches in environmental microbiology. These considerations, as well as the need for better tools for genome quality assessment, should be taken into account when designing studies and interpreting data that involve SAGs or MAGs. Video Abstract.

Shotgun metagenomic insights into secondary metabolite biosynthetic gene clusters reveal taxonomic and functional profiles of microbiomes in natural farmland soil.

Antibiotic resistance is a worldwide problem that imposes a devastating effect on developing countries and requires immediate interventions. Initially, most of the antibiotic drugs were identified by culturing soil microbes. However, this method is prone to discovering the same antibiotics repeatedly. The present study employed a shotgun metagenomics approach to investigate the taxonomic diversity, functional potential, and biosynthetic capacity of microbiomes from two natural agricultural farmlands located in Bekeka and Welmera Choke Kebelle in Ethiopia for the first time. Analysis of the small subunit rRNA revealed bacterial domain accounting for 83.33% and 87.24% in the two selected natural farmlands. Additionally, the analysis showed the dominance of Proteobacteria representing 27.27% and 28.79% followed by Actinobacteria making up 12.73% and 13.64% of the phyla composition. Furthermore, the analysis revealed the presence of unassigned bacteria in the studied samples. The metagenome functional analysis showed 176,961 and 104, 636 number of protein-coding sequences (pCDS) from the two samples found a match with 172,655 and 102, 275 numbers of InterPro entries, respectively. The Genome ontology annotation suggests the presence of 5517 and 3293 pCDS assigned to the "biosynthesis process". Numerous Kyoto Encyclopedia of Genes and Genomes modules (KEGG modules) involved in the biosynthesis of terpenoids and polyketides were identified. Furthermore, both known and novel Biosynthetic gene clusters, responsible for the production of secondary metabolites, such as polyketide synthases, non-ribosomal peptide synthetase, ribosomally synthesized and post-translationally modified peptides (Ripp), and Terpene, were discovered. Generally, from the results it can be concluded that the microbiomes in the selected sampling sites have a hidden functional potential for the biosynthesis of secondary metabolites. Overall, this study can serve as a strong preliminary step in the long journey of bringing new antibiotics to the market.

Alterations of the bile microbiome is associated with progression-free survival in pancreatic ductal adenocarcinoma patients.

BACKGROUND: Patients with pancreatic ductal adenocarcinoma (PDAC) display an altered oral, gastrointestinal, and intra-pancreatic microbiome compared to healthy individuals. However, knowledge regarding the bile microbiome and its potential impact on progression-free survival in PDACs remains limited. METHODS: Patients with PDAC (n = 45), including 20 matched pairs before and after surgery, and benign controls (n = 16) were included prospectively. The characteristics of the microbiomes of the total 81 bile were revealed by 16  S-rRNA gene sequencing. PDAC patients were divided into distinct groups based on tumor marker levels, disease staging, before and after surgery, as well as progression free survival (PFS) for further analysis. Disease diagnostic model was formulated utilizing the random forest algorithm. RESULTS: PDAC patients harbor a unique and diverse bile microbiome (PCoA, weighted Unifrac, p = 0.038), and the increasing microbial diversity is correlated with dysbiosis according to key microbes and microbial functions. Aliihoeflea emerged as the genus displaying the most significant alteration among two groups (p < 0.01). Significant differences were found in beta diversity of the bile microbiome between long-term PFS and short-term PFS groups (PCoA, weighted Unifrac, p = 0.005). Bacillota and Actinomycetota were identified as altered phylum between two groups associated with progression-free survival in all PDAC patients. Additionally, we identified three biomarkers as the most suitable set for the random forest model, which indicated a significantly elevated likelihood of disease occurrence in the PDAC group (p < 0.0001). The area under the receiver operating characteristic (ROC) curve reached 80.8% with a 95% confidence interval ranging from 55.0 to 100%. Due to the scarcity of bile samples, we were unable to conduct further external verification. CONCLUSION: PDAC is characterized by an altered microbiome of bile ducts. Biliary dysbiosis is linked with progression-free survival in all PDACs. This study revealed the alteration of the bile microbiome in PDACs and successfully developed a diagnostic model for PDAC.

Linking the composition of cryoconite prokaryotic communities in the Arctic, Antarctic, and Central Caucasus with their chemical characteristics.

Cryoconites are the deposits on the surface of glaciers that create specific ecological niches for the development of microorganism communities. The sediment material can vary in origin, structure, and nutrient content, creating local variations in the growth conditions. An additional factor of variability is the location of the glaciers, as they are found in different climatic zones in the high mountain regions and closer to the poles. Here, using the analysis of amplicon sequencing of the 16S rRNA gene, we studied the taxonomic composition of the prokaryotic communities from glaciers from remote regions, including the Arctic (Mushketova on the Severnaya Zemlya, IGAN in Polar Ural), Antarctic (Pimpirev on the Livingstone Island) and Central Caucasus (Skhelda and Garabashi) and connected it with the variation of the physicochemical characteristics of the substrate: pH, carbon, nitrogen, macro- and microelements. The cryoconite microbiomes were comprised of specific for this environment phyla (mostly Pseudomonadota, Cyanobacteria, Bacteroidota, Acidobacteriota, and Actinobacteriota), but each glacier had a unique taxonomic imprint. The core microbiome between regions was composed of only a few ASVs, among which the most likely globally distributed ones attributed to Polaromonas sp., Rhodoferax sp., Cryobacterium sp., and Hymenobacter frigidus. The WGSNA defined clusters of co-occurring ASVs between microbiomes, that significantly change their abundance corresponding with the variation of chemical parameters of cryoconites, but do not fully coincide with their regional separation. Thus, our work demonstrates that the chemical characteristics of the sediment material can explain the variation in the cryoconite prokaryotic community which is not always linked to geographic isolation.