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The exponential increase in publicly available sequencing data and genomic resources necessitates the development of highly efficient methods for data processing and analysis. Locality-sensitive hashing techniques have successfully transformed large datasets into smaller, more manageable sketches while maintaining comparability using metrics such as Jaccard and containment indices. However, fixed-size sketches encounter difficulties when applied to divergent datasets. Scalable sketching methods, such as sourmash, provide valuable solutions but still lack resource-efficient, tailored indexing. Our objective is to create lighter sketches with comparable results while enhancing efficiency. We introduce the concept of Fractional Hitting Sets, a generalization of Universal Hitting Sets, which cover a specified fraction of the k-mer space. In theory and practice, we demonstrate the feasibility of achieving such coverage with simple but highly efficient schemes. By encoding the covered k-mers as super-k-mers, we provide a space-efficient exact representation that also enables optimized comparisons. Our novel tool, supersampler, implements this scheme, and experimental results with real bacterial collections closely match our theoretical findings. In comparison to sourmash, supersampler achieves similar outcomes while utilizing an order of magnitude less space and memory and operating several times faster. This highlights the potential of our approach in addressing the challenges presented by the ever-expanding landscape of genomic data. supersampler is an open-source software and can be accessed at https://github.com/TimRouze/supersampler. The data required to reproduce the results presented in this manuscript is available at https://github.com/TimRouze/supersampler/experiments. [ABSTRACT FROM AUTHOR]

The world is changing due to factors like bioterrorism, massive environmental changes, globalization of trade and commerce, growing urbanization, changing climate, and pollution. Numerous diseases have emerged because of these factors, especially in companion and food-producing animals. Numerous pathogens have established themselves in naïve populations, harming reproduction, productivity, and health. Bioinformatics is considered a valuable tool in infectious disease research, as it provides a comprehensive overview of the identification of pathogens, their genetic makeup, and their evolutionary relationship. Therefore, there is an urgent need for a novel bioinformatics approach to help decipher and model viral epidemiology and informatics on domestic animals and livestock. With significant advancements in bioinformatics and NGS, researchers can now identify contigs, which are contiguous sequences of DNA that are assembled from overlapping fragments, assemble a complete genome, perform phylogenetic analysis to diagnose, investigate the risk of viral diseases in animals, handle and share large biological datasets across various species. Additionally, multi-omics data integration further deepens our understanding of homology, divergence, mutations, and evolutionary relationships, providing a comprehensive perspective on the molecular mechanisms driving animal pathogens infections. This review aims to reveal the importance of utilizing the multidisciplinary areas of bioinformatics, genomics, proteomics, transcriptomics, metabolomics, and metagenomics and their roles in studying viral infectious diseases in veterinary medicine that will eventually improve the health of animals. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has underscored the importance of virus surveillance in public health and wastewater-based epidemiology (WBE) has emerged as a non-invasive, cost-effective method for monitoring SARS-CoV-2 and its variants at the community level. Unfortunately, current variant surveillance methods depend heavily on updated genomic databases with data derived from clinical samples, which can become less sensitive and representative as clinical testing and sequencing efforts decline. In this paper, we introduce HERCULES (High-throughput Epidemiological Reconstruction and Clustering for Uncovering Lineages from Environmental SARS-CoV-2), an unsupervised method that uses long-read sequencing of a single 1 Kb fragment of the Spike gene. HERCULES identifies and quantifies mutations and lineages without requiring database-guided deconvolution, enhancing the detection of novel variants. We evaluated HERCULES on Norwegian wastewater samples collected from July 2022 to October 2023 as part of a national pilot on WBE of SARS-CoV-2. Strong correlations were observed between wastewater and clinical sample data in terms of prevalence of mutations and lineages. Furthermore, we found that SARS-CoV-2 trends in wastewater samples were identified one week earlier than in clinical data. Our results demonstrate HERCULES' capability to identify new lineages before their detection in clinical samples, providing early warnings of potential outbreaks. The methodology described in this paper is easily adaptable to other pathogens, offering a versatile tool for environmental surveillance of new emerging pathogens. [ABSTRACT FROM AUTHOR]

Background: Maintaining gut health is a persistent and unresolved challenge in the poultry industry. Given the critical role of gut health in chicken performance and welfare, there is a pressing need to identify effective gut health intervention (GHI) strategies to ensure optimal outcomes in poultry farming. In this study, across three broiler production cycles, we compared the metagenomes and performance of broilers provided with ionophores (as the control group) against birds subjected to five different GHI combinations involving vaccination, probiotics, prebiotics, essential oils, and reduction of ionophore use. Results: Using a binning strategy, 84 (≥ 75% completeness, ≤ 5% contamination) metagenome-assembled genomes (MAGs) from 118 caecal samples were recovered and annotated for their metabolic potential. The majority of these (n = 52, 61%) had a differential response across all cohorts and are associated with the performance parameter — European poultry efficiency factor (EPEF). The control group exhibited the highest EPEF, followed closely by the cohort where probiotics are used in conjunction with vaccination. The use of probiotics B, a commercial Bacillus strain-based formulation, was determined to contribute to the superior performance of birds. GHI supplementation generally affected the abundance of microbial enzymes relating to carbohydrate and protein digestion and metabolic pathways relating to energy, nucleotide synthesis, short-chain fatty acid synthesis, and drug-transport systems. These shifts are hypothesised to differentiate performance among groups and cycles, highlighting the beneficial role of several bacteria, including Rikenella microfusus and UBA7160 species. Conclusions: All GHIs are shown to be effective methods for gut microbial modulation, with varying influences on MAG diversity, composition, and microbial functions. These metagenomic insights greatly enhance our understanding of microbiota-related metabolic pathways, enabling us to devise strategies against enteric pathogens related to poultry products and presenting new opportunities to improve overall poultry performance and health. 7L1xU6sKvy1sLntC7jPKeb Video Abstract [ABSTRACT FROM AUTHOR]

Background: An accurate diagnosis of septic versus reactive or autoimmune arthritis remains clinically challenging. A multi-omics strategy comprising metagenomic and proteomic technologies were undertaken for children diagnosed with presumed septic arthritis to advance clinical diagnoses and care for affected individuals. Methods: Twelve children with suspected septic arthritis were prospectively enrolled to compare standard of care tests with a rapid multi-omics approach. The multi-omics combined bacterial 16S rRNA metagenomics, single cell transcriptomics, and proteomics on knee joint fluid specimens. The diagnostic value of the multi-omics was ascertained relative to standard of care culture and PCR-negative results. Results: Ten children with suspected primary septic arthritis and two with acute hematogenous osteomyelitis (AHO) diagnoses were assessed. Joint fluid bacterial cultures were positive for 6/12 (50%) patients, consistent with elevated inflammatory markers (IL-4, IL-6, IL-17A, TNF-a, etc.). Metagenomic bacterial sequencing results were 100% concordant with the culture results. Six patients were culture- and PCR-negative. Multiomics analyses of the 6 culture negative patients established that 2/6 culture-negative children had inflammatory arthritis with potential Juvenile idiopathic arthritis (JIA) and 1 had post-Streptococcal Reactive Arthritis. The children without any bacteremia had autoantibodies (IgGs) in the joint-fluid targeting several nuclear antigens (i.e., dsDNA, histones, Jo-1, scl-70, Ro/SS-A, SmDs, CENP-A along with non-nuclear antigens i.e. Albumin, Collagens, Myosin, Laminin, etc. Single cell transcriptomics confirmed an abundance of CD4+ follicular helper T (Tfh), CD8 + T cells and B cells in the autoantibody positive subjects. The combination of 16S DNA sequencing (p = 0.006), cytokine assays (p = 0.009) and autoantibody profiling (p = 0.02) were significantly distinct between those children with and without infections. This improved the diagnostic confidence for 9 of 12 (75%) children, key for treatment decisions. Conclusions: The multiomics approach rapidly identified children with bacterial or autoimmune inflammatory conditions, improving diagnostic and treatment strategies for those with presumptive septic arthritis. [ABSTRACT FROM AUTHOR]

Background: The evolving infant gut microbiome influences host immune development and later health outcomes. Early antibiotic exposure could impact microbiome development and contribute to poor outcomes. Here, we use a prospective longitudinal birth cohort of n = 323 healthy term African American children to determine the association between antibiotic exposure and the gut microbiome through shotgun metagenomics sequencing as well as bile acid profiles through liquid chromatography-mass spectrometry. Results: Stool samples were collected at ages 4, 12, and 24 months for antibiotic-exposed (n = 170) and unexposed (n = 153) participants. A short-term substudy (n = 39) collected stool samples at first exposure, and over 3 weeks following antibiotics initiation. Antibiotic exposure (predominantly amoxicillin) was associated with minimal microbiome differences, whereas all tested taxa were modified by breastfeeding. In the short-term substudy, we observed microbiome differences only in the first 2 weeks following antibiotics initiation, mainly a decrease in Bifidobacterium bifidum. The differences did not persist a month after antibiotic exposure. Four species were associated with infant age. Antibiotic exposure was not associated with an increase in antibiotic resistance gene abundance or with differences in microbiome-derived fecal bile acid composition. Conclusions: Short-term and long-term gut microbiome perturbations by antibiotic exposure were detectable but substantially smaller than those associated with breastfeeding and infant age. [ABSTRACT FROM AUTHOR]

Background: The pathogenesis of non-alcoholic fatty liver disease (NAFLD) with a global prevalence of 30% is multifactorial and the involvement of gut bacteria has been recently proposed. However, finding robust bacterial signatures of NAFLD has been a great challenge, mainly due to its co-occurrence with other metabolic diseases. Results: Here, we collected public metagenomic data and integrated the taxonomy profiles with in silico generated community metabolic outputs, and detailed clinical data, of 1206 Chinese subjects w/wo metabolic diseases, including NAFLD (obese and lean), obesity, T2D, hypertension, and atherosclerosis. We identified highly specific microbiome signatures through building accurate machine learning models (accuracy = 0.845–0.917) for NAFLD with high portability (generalizable) and low prediction rate (specific) when applied to other metabolic diseases, as well as through a community approach involving differential co-abundance ecological networks. Moreover, using these signatures coupled with further mediation analysis and metabolic dependency modeling, we propose synergistic defined microbial consortia associated with NAFLD phenotype in overweight and lean individuals, respectively. Conclusion: Our study reveals robust and highly specific NAFLD signatures and offers a more realistic microbiome-therapeutics approach over individual species for this complex disease. 52kJtbHzG-_bG9FwJ6R5EK Video Abstract [ABSTRACT FROM AUTHOR]

Background: Huge phages (genome size ≥ 200 kb) have been detected in diverse habitats worldwide, infecting a variety of prokaryotes. However, their evolution and adaptation strategy in soils remain poorly understood due to the scarcity of soil-derived genomes. Results: Here, we conduct a size-fractioned (< 0.22 μm) metagenomic analysis across a 130-year chronosequence of a glacier foreland in the Tibetan Plateau and discovered 412 novel viral operational taxonomic units (vOTUs) of huge phages. The phylogenomic and gene-shared network analysis gained insights into their unique evolutionary history compared with smaller phages. Their communities in glacier foreland revealed a distinct pattern between the early (≤ 41 years) and late stages (> 41 years) based on the macrodiveristy (interspecies diversity) analysis. A significant increase in the diversity of huge phages communities following glacier retreat were observed according to current database. The phages distributed across sites within late stage demonstrated a remarkable higher microdiversity (intraspecies diversity) compared to other geographic range such as the intra early stage, suggesting that glacial retreat is key drivers of the huge phage speciation. Alongside the shift in huge phage communities, we also noted an evolutionary and functional transition between the early and late stages. The identification of abundant CRISPR-Cas12 and type IV restriction-modification (RM) systems in huge phages indicates their complex mechanisms for adaptive immunity. Conclusions: Overall, this study unravels the importance of climate change in shaping the composition, evolution, and function of soil huge phage communities, and such further understanding of soil huge phages is vital for broader inclusion in soil ecosystem models. 36NkSuBhymqeFDHZtwigi8 Video Abstract [ABSTRACT FROM AUTHOR]

Background: Accurate and comprehensive identification of enteropathogens, causing infectious gastroenteritis, is essential for optimal patient treatment and effective isolation processes in health care systems. Traditional diagnostic techniques are well established and optimised in low-cost formats. However, thorough testing for a wider range of causal agents is time consuming and remains limited to a subset of pathogenic organisms. Metagenomic next-generation sequencing (mNGS) allows the identification of all pathogens in a sample in a single test, without a reliance on culture or introduction of target selection bias. This study aims to determine the ability to routinely apply mNGS testing, in comparison to traditional culture or polymerase chain reaction (PCR) based tests, for the identification of causal pathogens for gastrointestinal infections. Results: The performance of mNGS, PCR and microscopy, culture and sensitivity (MCS) assays was established using 2,619 prospectively collected faecal samples from patients with symptomology indicative of infectious gastroenteritiss. Commonly experienced pathogens including Aeromonas spp, Campylobacter spp, Salmonella spp and Giardia spp, in single and co-infected patients, were used to establish test outcomes. When testing for these organisms, using the combined result from either or both PCR and MCS testing as the comparator, the mNGS assay had clinically acceptable sensitivity (89.2–100%). Further, the mNGS assay detected 14 additional enteropathogens, that were either not detected or not tested, by initial PCR/MCS testing. Conclusions: The advantage of mNGS compared to other syndromic testing systems is the broad range of detectable targets and the ability to interrogate samples without clinician informed or assay specific bias. With the development of newer sequencing assays, it is now feasible to test for a wide range of target organisms in a sample using a single mNGS test. Overall, the mNGS based approach enabled pathogen detection that was comparable to conventional diagnostics and was shown to have the potential to be extended for the detection of many pathogens and genes of clinical interest. In conclusion, the mNGS assay offers an easy, sample to answer workflow with rapid detection of enteropathogens and has the potential to improve diagnosis, therapy and infection control precautions. [ABSTRACT FROM AUTHOR]

Background: Seawater microbes (bacteria and archaea) play essential roles in coral reefs by facilitating nutrient cycling, energy transfer, and overall reef ecosystem functioning. However, environmental disturbances such as degraded water quality and marine heatwaves, can impact these vital functions as seawater microbial communities experience notable shifts in composition and function when exposed to stressors. This sensitivity highlights the potential of seawater microbes to be used as indicators of reef health. Microbial indicator analysis has centered around measuring the taxonomic composition of seawater microbial communities, but this can obscure heterogeneity of gene content between taxonomically similar microbes, and thus, microbial functional genes have been hypothesized to have more scope for predictive potential, though empirical validation for this hypothesis is still pending. Using a metagenomics study framework, we establish a functional baseline of seawater microbiomes across offshore Great Barrier Reef (GBR) sites to compare the diagnostic value between taxonomic and functional information in inferring continuous physico-chemical metrics in the surrounding reef. Results: Integrating gene-centric metagenomics analyses with 17 physico-chemical variables (temperature, salinity, and particulate and dissolved nutrients) across 48 reefs revealed that associations between microbial functions and environmental parameters were twice as stable compared to taxonomy-environment associations. Distinct seasonal variations in surface water chemistry were observed, with nutrient concentrations up to threefold higher during austral summer, explained by enhanced production of particulate organic matter (POM) by photoautotrophic picocyanobacteria, primarily Synechococcus. In contrast, nutrient levels were lower in winter, and POM production was also attributed to Prochlorococcus. Additionally, heterotrophic microbes (e.g., Rhodospirillaceae, Burkholderiaceae, Flavobacteriaceae, and Rhodobacteraceae) were enriched in reefs with elevated dissolved organic carbon (DOC) and phytoplankton-derived POM, encoding functional genes related to membrane transport, sugar utilization, and energy metabolism. These microbes likely contribute to the coral reef microbial loop by capturing and recycling nutrients derived from Synechococcus and Prochlorococcus, ultimately transferring nutrients from picocyanobacterial primary producers to higher trophic levels. Conclusion: This study reveals that functional information in reef-associated seawater microbes more robustly associates with physico-chemical variables than taxonomic data, highlighting the importance of incorporating microbial function in reef monitoring initiatives. Our integrative approach to mine for stable seawater microbial biomarkers can be expanded to include additional continuous metrics of reef health (e.g., benthic cover of corals and macroalgae, fish counts/biomass) and may be applicable to other large-scale reef metagenomics datasets beyond the GBR. D4ZFkyo-_x3xtsAViMg6HS Video Abstract [ABSTRACT FROM AUTHOR]

Objective: The World Health Organization (WHO) has declared antimicrobial resistance (AMR) as one of the top threats to global public health. While AMR surveillance of human clinical isolates is well-established in many countries, the increasing threat of AMR has intensified efforts to detect antibiotic resistance genes (ARGs) accurately and sensitively in environmental samples, wastewater, animals, and food. Using five ARGs and the 16S rRNA gene, we compared quantitative PCR (qPCR) and metagenomic sequencing (MGS), two commonly used methods to uncover the wastewater resistome. We compared both methods by evaluating ARG detection through a municipal wastewater treatment chain. Results: Our results demonstrate that qPCR was more sensitive than MGS, particularly in diluted samples with low ARG concentrations such as oxidation pond water. However, MGS was potentially more specific and has less risk of off-target binding in concentrated samples such as raw sewage. MGS analysis revealed multiple subtypes of each gene which could not be distinguished by qPCR; these subtypes varied across different sample types. Our findings affect the conclusions that can be drawn when comparing different sample types, particularly in terms of inferring removal rates or origins of genes. We conclude that both methods appear suitable to profile the resistome of wastewater and other environmental samples, depending on the research question and type of sample. [ABSTRACT FROM AUTHOR]

Background: Accurate classification of host phenotypes from microbiome data is crucial for advancing microbiome-based therapies, with machine learning offering effective solutions. However, the complexity of the gut microbiome, data sparsity, compositionality, and population-specificity present significant challenges. Microbiome data transformations can alleviate some of the aforementioned challenges, but their usage in machine learning tasks has largely been unexplored. Results: Our analysis of over 8500 samples from 24 shotgun metagenomic datasets showed that it is possible to classify healthy and diseased individuals using microbiome data with minimal dependence on the choice of algorithm or transformation. Presence-absence transformations performed comparably to abundance-based transformations, and only a small subset of predictors is necessary for accurate classification. However, while different transformations resulted in comparable classification performance, the most important features varied significantly, which highlights the need to reevaluate machine learning–based biomarker detection. Conclusions: Microbiome data transformations can significantly influence feature selection but have a limited effect on classification accuracy. Our findings suggest that while classification is robust across different transformations, the variation in feature selection necessitates caution when using machine learning for biomarker identification. This research provides valuable insights for applying machine learning to microbiome data and identifies important directions for future work. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorder (ASD) is a persistent neurodevelopmental disorder affecting brains of children. Mounting evidences support the associations between gut microbial dysbiosis and ASD, whereas detailed mechanisms are still obscure. Methods: Here we probed the potential roles of gut microbiome in ASD using fecal metagenomics and metabolomics. Results: Children with ASD were found to be associated with augmented serum cytokines milieu, especially TNFα. Metagenomic analysis generated 29 differential species and 18 dysregulated functional pathways such as Bifidobacterium bifidum, Segatella copri, and upregulated 'Sphingolipid metabolism' in children with ASD. Metabolomics revealed steroid hormone dysgenesis in children with ASD with lower abundances of metabolites such as estriol, estradiol and deoxycorticosterone. A three-way association analysis showed positive correlations between TNFα and microbial function potentials such as 'Bacterial toxins' and 'Lysosome', indicating the contribution of microbial dysbiosis to neuroinflammation. TNFα also correlated positively with 'Sphingolipid metabolism', which further showed negative correlations with metabolites estriol and deoxycorticosterone. Such results, in consistent with current findings, revealed the contribution of increased TNFα to upregulated sphingolipid metabolism, which further impaired steroid hormone biosynthesis. Conclusion: Our study proposed the gut microbial 'TNFα-sphingolipids-steroid hormones' axis in children with ASD, which may provide new perspectives for developing gut microbiome-based treatments in the future. [ABSTRACT FROM AUTHOR]

Background: Amplicon sequencing of kingdom-specific tags such as 16S rRNA gene for bacteria and internal transcribed spacer (ITS) region for fungi are widely used for investigating microbial communities. So far most human studies have focused on bacteria while studies on host-associated fungi in health and disease have only recently started to accumulate. To enable cost-effective parallel analysis of bacterial and fungal communities in human and environmental samples, we developed a method where 16S rRNA gene and ITS1 amplicons were pooled together for a single Illumina MiSeq or HiSeq run and analysed after primer-based segregation. Taxonomic assignments were performed with Blast in combination with an iterative text-extraction-based filtration approach, which uses extensive literature records from public databases to select the most probable hits that were further validated by shotgun metagenomic sequencing. Results: Using 50 vaginal samples, we show that the combined run provides comparable results on bacterial composition and diversity to conventional 16S rRNA gene amplicon sequencing. The text-extraction-based taxonomic assignment-guided tool provided ecosystem-specific bacterial annotations that were confirmed by shotgun metagenomic sequencing (VIRGO, MetaPhlAn, Kraken2). Fungi were identified in 39/50 samples with ITS sequencing while in the metagenome data fungi largely remained undetected due to their low abundance and database issues. Co-abundance analysis of bacteria and fungi did not show strong between-kingdom correlations within the vaginal ecosystem of healthy women. Conclusion: Combined amplicon sequencing for bacteria and fungi provides a simple and cost-effective method for simultaneous analysis of microbiota and mycobiota within the same samples. Conventional metagenomic sequencing does not provide sufficient fungal genome coverage for their reliable detection in vaginal samples. Text extraction-based annotation tool facilitates ecosystem-specific characterization and interpretation of microbial communities by coupling sequence homology to microbe metadata readily available through public databases. 2qy3B9u1zc9EewFyPFTHi4 Video Abstract [ABSTRACT FROM AUTHOR]

Background: Studies have reported clinical heterogeneity between right-sided colon cancer (RCC) and left-sided colon cancer (LCC). However, none of these studies used multi-omics analysis combining genetic regulation, microbiota, and metabolites to explain the site-specific difference. Methods: Here, 494 participants from a 16S rRNA gene sequencing cohort (50 RCC, 114 LCC, and 100 healthy controls) and a multi-omics cohort (63 RCC, 79 LCC, and 88 healthy controls) were analyzed. 16S rRNA gene, metagenomic sequencing, and metabolomics analyses of fecal samples were evaluated to identify tumor location-related bacteria and metabolites. Whole-exome sequencing (WES) and transcriptome sequencing (RNA-seq) were conducted to obtain the mutation burden and genomic expression pattern. Results: We found unique profiles of the intestinal microbiome, metabolome, and host genome between RCC and LCC. The bacteria Flavonifractor plautii (Fp) and Fusobacterium nucleatum, the metabolites L-phenylalanine, and the host genes PHLDA1 and WBP1 were the key omics features of RCC; whereas the bacteria Bacteroides sp. A1C1 (B.A1C1) and Parvimonas micra, the metabolites L-citrulline and D-ornithine, and the host genes TCF25 and HLA-DRB5 were considered the dominant omics features in LCC. Multi-omics correlation analysis indicated that RCC-enriched Fp was related to the accumulation of the metabolite L-phenylalanine and the suppressed WBP1 signal in RCC patients. In addition, LCC-enriched B.A1C1 was associated with the accumulation of the metabolites D-ornithine and L-citrulline as well as activation of the genes TCF25, HLA-DRB5, and AC079354.1. Conclusion: Our findings identify previously unknown links between intestinal microbiota alterations, metabolites, and host genomics in RCC vs. LCC, suggesting that it may be possible to treat colorectal cancer (CRC) by targeting the gut microbiota–host interaction. EBEnjMWs8zdx83po8jPsMq Video Abstract [ABSTRACT FROM AUTHOR]

Introduction: Rice root gall is a severe infection caused by the rice root-knot nematode Meloidogyne graminicola. Overuse of chemical nematicides intensifies the need for a suitable biocontrol agent. Nematode infestation in plants alters the associated microbiome; however, their correlations need to be better understood. Hence, this work aimed to unravel the changes in indigenous endophytic bacterial community composition of rice root because of infection caused by M. graminicola and also to identify dominant bacteria strains as a potential biological control agent. Material & Methods: The endophytic bacterial community of non-infected rice root and gall was analysed using a 16 S rRNA gene-based metagenomics approach. The dominant endophytic bacterial community was further isolated and screened for its PGP and nematicidal activity using bacterial cell suspension and culture filtrate to identify a potential biocontrol agent. Result and Discussion: Our results show that nematode infection has altered the bacterial community composition, and a distinct community existed between gall and non-infected roots. This shift in the microbial community is associated with reduced species richness due to infection. We also observed that a few endophytic genera like Chryseobacterium, Rhizobium, Gemmata, and Pseudomonas that were unique to gall are reported to have been associated either with nematode or may have been recruited by plants as a growth promoter to combat nematode infection. Other bacterial endophytes that are specific to the non-infected root microbiome, like Delftia, Bacillus, Pantoea, Acidovorax, and Azorhizobium, are hypothesised to remain associated with rice seeds, and they possess biological control/plant growth promotion abilities. Further, after screening all isolates, Enterobacter sp. strain SSNI 8 isolated from a non-infected root was evaluated for its efficiency in acting as a nematicidal agent against M. graminicola, and we found that the strain showed 90% nematode mortality with its culture filtrate which may possess some secondary metabolites antagonistic to the nematode. Conclusion: Overall, this study provided a comprehensive view of endophytes associated with gall in non-infected roots and identified a potential biocontrol agent. [ABSTRACT FROM AUTHOR]

Great Bay Estuary (GBE), within the rapidly warming Gulf of Maine, has experienced significant ecological shifts this century due to naturalization of invasive species. The range expansion of the American blue crab (Callinectes sapidus) currently underway from the mid-Atlantic northward brings the possibility of similar ecological shifts. This study accounts recent trapping and diet analysis of C. sapidus in GBE. Diet is an important component of understanding how the blue crab range expansion may affect GBE ecosystem functions. Across all sites and trap types, 27 blue crabs were captured. Metagenomic analysis of shotgun sequencing techniques were used on the gut contents of blue crabs captured. Most specimens had > 50% Eukaryote sequences. Overall results of this gut content study confirm a mixed diet indicative of an opportunistic feeder. Using metagenomics to analyze the diet of blue crabs as they establish viable populations in GBE will be a useful tool for predicting how these range expanding organisms are interacting within this important estuarine ecosystem, which will promote sustainable development by informing end users who may be affected by these crabs to help them meet their needs in the present and future. This project falls within Global Goal SDG14: Life Below Water. [ABSTRACT FROM AUTHOR]

Background: Tramway Ridge, a geothermal Antarctic Specially Protected Area (elevation 3340 m) located near the summit of Mount Erebus, is home to a unique community composed of cosmopolitan surface-associated micro-organisms and abundant, poorly understood subsurface-associated microorganisms. Here, we use shotgun metagenomics to compare the functional capabilities of this community to those found elsewhere on Earth and to infer in situ diversity and metabolic capabilities of abundant subsurface taxa. Results: We found that the functional potential in this community is most similar to that found in terrestrial hydrothermal environments (hot springs, sediments) and that the two dominant organisms in the subsurface carry high rates of in situ diversity which was taken as evidence of potential endemicity. They were found to be facultative anaerobic heterotrophs that likely share a pool of nitrogenous organic compounds while specializing in different carbon compounds. Conclusions: Metagenomic insights have provided a detailed understanding of the microbe-based ecosystem found in geothermally heated fumaroles at Tramway Ridge. This approach enabled us to compare Tramway Ridge with other microbial systems, identify potentially endemic taxa and elucidate the key metabolic pathways that may enable specific organisms to dominate the ecosystem. [ABSTRACT FROM AUTHOR]

Introduction: The intestinal microbiota plays a crucial role in health and disease. This study aimed to assess the composition and functional diversity of the intestinal microbiota in donkeys and cows by examining samples collected from different segments of the digestive tract using two distinct techniques: direct swab sampling and faecal sampling. Results: In this study, we investigated and compared the effects of multiple factors on the composition and function of the intestinal microbial community. Approximately 300 GB of metagenomic sequencing data from 91 samples obtained from various segments of the digestive tract were used, including swabs and faecal samples from monogastric animals (donkeys) and polygastric animals (cows). We assembled 4,004,115 contigs for cows and 2,938,653 contigs for donkeys, with a total of 9,060,744 genes. Our analysis revealed that, compared with faecal samples, swab samples presented a greater abundance of Bacteroidetes, whereas faecal samples presented a greater abundance of Firmicutes. Additionally, we observed significant variations in microbial composition among different digestive tract segments in both animals. Our study identified key bacterial species and pathways via different methods and provided evidence that multiple factors can influence the microbial composition. These findings provide new insights for the accurate characterization of the composition and function of the gut microbiota in microbiome research. Conclusions: The results obtained by both sampling methods in the present study revealed that the composition and function of the intestinal microbiota in donkeys and cows exhibit species-specific and region-specific differences. These findings highlight the importance of using standardized sampling protocols to ensure accurate and consistent characterization of the intestinal microbiota in various animal species. The implications and underlying mechanisms of these associations provide multiple perspectives for future microbiome research. [ABSTRACT FROM AUTHOR]

Background: The application of '-omics' technologies to study bacterial vaginosis (BV) has uncovered vast differences in composition and scale between the vaginal microbiomes of healthy and BV patients. Compared to amplicon sequencing and shotgun metagenomic approaches focusing on a single or few species, investigating the transcriptome of the vaginal microbiome at a system-wide level can provide insight into the functions which are actively expressed and differential between states of health and disease. Results: We conducted a meta-analysis of vaginal metatranscriptomes from three studies, split into exploratory (n = 42) and validation (n = 297) datasets, accounting for the compositional nature of sequencing data and differences in scale between healthy and BV microbiomes. Conducting differential expression analyses on the exploratory dataset, we identified a multitude of strategies employed by microbes associated with states of health and BV to evade host cationic antimicrobial peptides (CAMPs); putative mechanisms used by BV-associated species to resist and counteract the low vaginal pH; and potential approaches to disrupt vaginal epithelial integrity so as to establish sites for adherence and biofilm formation. Moreover, we identified several distinct functional subgroups within the BV population, distinguished by genes involved in motility, chemotaxis, biofilm formation and co-factor biosynthesis. After defining molecular states of health and BV in the validation dataset using KEGG orthology terms rather than community state types, differential expression analysis confirmed earlier observations regarding CAMP resistance and compromising epithelial barrier integrity in healthy and BV microbiomes and also supported the existence of motile vs. non-motile subgroups in the BV population. These findings were independent of the enzyme classification system used (KEGG or EggNOG). Conclusions: Our findings highlight a need to focus on functional rather than taxonomic differences when considering the role of microbiomes in disease and identify pathways for further research as potential BV treatment targets. CwG4qJAdVu5eAuU4jPyBus Video Abstract [ABSTRACT FROM AUTHOR]

Introduction: Colonisation and infection with Carbapenem-resistant Enterobacterales (CRE) in healthcare settings poses significant risks, especially for vulnerable patients. Genomic analysis can be used to trace transmission routes, supporting antimicrobial stewardship and informing infection control strategies. Here we used genomic analysis to track the movement and transmission of CREs within clinical and environmental samples. Methods: 25 isolates were cultured from clinical patient samples or swabs, that tested positive for OXA-48-like variants using the NG-Test® CARBA-5 test and whole genome sequenced (WGS) using Oxford Nanopore Technologies (ONT). 158 swabs and 52 wastewater samples were collected from the ward environment. 60 isolates (matching clinical isolate genera; Klebsiella, Enterobacter, Citrobacter and Escherichia) were isolated from the environmental samples using selective agar. Metagenomic sequencing was undertaken on 36 environmental wastewater and swab samples. Results: 21/25 (84%) clinical isolates had > 1 blaOXA gene and 19/25 (76%) harboured > 1 blaNDM gene. Enterobacterales were most commonly isolated from environmental wastewater samples 27/52 (51.9%), then stick swabs 5/43 (11.6%) and sponge swabs 5/115 (4.3%). 11/60 (18%) environmental isolates harboured > 1 blaOXA gene and 1.9% (1/60) harboured blaNDM-1. blaOXA genes were found in 2/36 (5.5%) metagenomic environmental samples. Conclusions: Potential for putative patient-patient and patient-ward transmission was shown. Metagenomic sampling needs optimization to improve sensitivity. [ABSTRACT FROM AUTHOR]

Background: Numerous studies have highlighted the impact of bacterial communities on the quality and safety of raw ewe milk-derived cheeses. Despite reported differences in the microbiota among cheese types and even producers, to the best of our knowledge, no study has comprehensively assessed all potential microbial sources and their contributions to any raw ewe milk-derived cheese, which could suppose great potential for benefits from research in this area. Here, using the Protected Designation of Origin Idiazabal cheese as an example, the impact of the environment and practices of artisanal dairies (including herd feed, teat skin, dairy surfaces, and ingredients) on the microbiomes of the associated raw milk, whey, and derived cheeses was examined through shotgun metagenomic sequencing. Results: The results revealed diverse microbial ecosystems across sample types, comprising more than 1300 bacterial genera and 3400 species. SourceTracker analysis revealed commercial feed and teat skin as major contributors to the raw milk microbiota (45.6% and 33.5%, respectively), being a source of, for example, Lactococcus and Pantoea, along with rennet contributing to the composition of whey and cheese (17.4% and 41.0%, respectively), including taxa such as Streptococcus, Pseudomonas_E or Lactobacillus_H. Functional analysis linked microbial niches to cheese quality- and safety-related metabolic pathways, with brine and food contact surfaces being most relevant, related to genera like Brevibacterium, Methylobacterium, or Halomonas. With respect to the virulome (virulence-associated gene profile), in addition to whey and cheese, commercial feed and grass were the main reservoirs (related to, e.g., Brevibacillus_B or CAG-196). Similarly, grass, teat skin, or rennet were the main contributors of antimicrobial resistance genes (e.g., Bact-11 or Bacteriodes_B). In terms of cheese aroma and texture, apart from the microbiome of the cheese itself, brine, grass, and food contact surfaces were key reservoirs for hydrolase-encoding genes, originating from, for example, Lactococcus, Lactobacillus, Listeria or Chromohalobacter. Furthermore, over 300 metagenomic assembled genomes (MAGs) were generated, including 60 high-quality MAGs, yielding 28 novel putative species from several genera, e.g., Citricoccus, Corynebacterium, or Dietzia. Conclusion: This study emphasizes the role of the artisanal dairy environments in determining cheese microbiota and, consequently, quality and safety. BtzRqvysXYp6yqc11nP1jY Video Abstract [ABSTRACT FROM AUTHOR]

Background: Culture-independent diagnostic tests are gaining popularity as tools for detecting pathogens in food. Shotgun sequencing holds substantial promise for food testing as it provides abundant information on microbial communities, but the challenge is in analyzing large and complex sequencing datasets with a high degree of both sensitivity and specificity. Falsely classifying sequencing reads as originating from pathogens can lead to unnecessary food recalls or production shutdowns, while low sensitivity resulting in false negatives could lead to preventable illness. Results: We used simulated and published shotgun sequencing datasets containing Salmonella-derived reads to explore the appearance and mitigation of false positive results using the popular taxonomic annotation softwares Kraken2 and Metaphlan4. Using default parameters, Kraken2 is sensitive but prone to false positives, while Metaphlan4 is more specific but unable to detect Salmonella at low abundance. We then developed a bioinformatic pipeline for identifying and removing reads falsely identified as Salmonella by Kraken2 while retaining high sensitivity. Carefully considering software parameters and database choices is essential to avoiding false positive sample calls. With well-chosen parameters plus additional steps to confirm the taxonomic origin of reads, it is possible to detect pathogens with very high specificity and sensitivity. [ABSTRACT FROM AUTHOR]

Background: Deadwood decomposition is an essential ecological process in forest ecosystems, playing a key role in nutrient cycling and carbon sequestration by enriching soils with organic matter. This process is driven by diverse microbial communities encompassing specialized functions in breaking down organic matter, but the specific roles of individual microorganisms in this process are still not fully understood. Results: Here, we characterized the deadwood microbiome in a natural mixed temperate forest in Central Europe using PacBio HiFi long-read sequencing and a genome-resolved transcriptomics approach in order to uncover key microbial contributors to wood decomposition. We obtained high quality assemblies, which allowed attribution of complex microbial functions such as nitrogen fixation to individual microbial taxa and enabled the recovery of metagenome-assembled genomes (MAGs) from both abundant and rare deadwood bacteria. We successfully assembled 69 MAGs (including 14 high-quality and 7 single-contig genomes) from 4 samples, representing most of the abundant bacterial phyla in deadwood. The MAGs exhibited a rich diversity of carbohydrate-active enzymes (CAZymes), with Myxococcota encoding the highest number of CAZymes and the full complement of enzymes required for cellulose decomposition. For the first time we observed active nitrogen fixation by Steroidobacteraceae, as well as hemicellulose degradation and chitin recycling by Patescibacteria. Furthermore, PacBio HiFi sequencing identified over 1000 biosynthetic gene clusters, highlighting a vast potential for secondary metabolite production in deadwood, particularly in Pseudomonadota and Myxococcota. Conclusions: PacBio HiFi long-read sequencing offers comprehensive insights into deadwood decomposition processes by advancing the identification of functional features involving multiple genes. It represents a robust tool for unraveling novel microbial genomes in complex ecosystems and allows the identification of key microorganisms contributing to deadwood decomposition. [ABSTRACT FROM AUTHOR]

Snails of the genus Bithynia, whose primary habitat is slow-flowing ponds and ditches, serve as the first intermediate hosts of liver fluke. Currently, approximately 200 million individuals worldwide are at risk of liver fluke infection, yet questions still persist regarding the taxonomic identification of Bithynia genus, a crucial player in the transmission of this disease. Accurate taxonomic classification of the Bithynia genus could significantly enhance current understanding of the disease's transmission mechanisms. In this article we comprehensively review the extensive research conducted on Bithynia genus, spanning past inquiries up to the latest findings. The primary emphasis is placed on exploring the taxonomic identification of this genus within various technological settings. We then present a consolidated analysis of the morphological taxonomic identification methods, highlighting their strengths and limitations. We also introduce a novel perspective on the future direction of identification and classification efforts for the members of this genus, emphasizing the crucial role Bithynia plays in the epidemiological cycle of liver fluke transmission. We conclude by urging researchers to prioritize the significance of the members of this genus in the epidemiological cycle of liver fluke transmission and in control measures for disease dissemination, within the context of the vector organisms. [ABSTRACT FROM AUTHOR]

Background: Approximately 3.7 billion years ago, microbial life may have emerged in phosphate-rich salty ponds. Surprisingly, analogs of these environments are present in alkaline lake systems, recognized as highly productive biological ecosystems. In this study, we investigate the microbial ecology of two Canadian soda lake sediment systems characterized by naturally high phosphate levels. Results: Using a comprehensive approach involving geochemistry, metagenomics, and amplicon sequencing, we discovered that groundwater infiltration into Lake Goodenough sediments supported stratified layers of microbial metabolisms fueled by decaying mats. Effective degradation of microbial mats resulted in unexpectedly low net productivity. Evaporation of water from Last Chance Lake and its sediments led to saturation of brines and a habitat dominated by inorganic precipitation reactions, with low productivity, low organic matter turnover and little biological uptake of phosphorus, leading to high phosphate concentrations. Highly alkaline brines were found to be dominated by potentially dormant spore-forming bacteria. These saturated brines also hosted potential symbioses between Halobacteria and Nanoarchaeaota, as well as Lokiarchaea and bacterial sulfate reducers. Metagenome-assembled genomes of Nanoarchaeaota lacked strategies for coping with salty brines and were minimal for Lokiarchaea. Conclusions: Our research highlights that modern analogs for origin-of-life conditions might be better represented by soda lakes with low phosphate concentrations. Thus, highly alkaline brine environments could be too extreme to support origin of life scenarios. These findings shed light on the complex interplay of microbial life in extreme environments and contribute to our understanding of early Earth environments. [ABSTRACT FROM AUTHOR]

Background: DPANN archaea, including Woesearchaeota, encompass a large fraction of the archaeal diversity, yet their genomic diversity, lifestyle, and role in natural microbiomes remain elusive. With an archaeal assemblage naturally enriched in Woesearchaeota and steep vertical geochemical gradients, Lake Dziani Dzaha (Mayotte) provides an ideal model to decipher their in-situ activity and ecology. Results: Using genome-resolved metagenomics and phylogenomics, we identified highly diversified Woesearchaeota populations and defined novel halophilic clades. Depth distribution of these populations in the water column showed an unusual double peak of abundance, located at two distinct chemoclines that are hotspots of microbial diversity in the water column. Genome-centric metatranscriptomics confirmed this vertical distribution and revealed a fermentative activity, with acetate and lactate as end products, and active cell-to-cell processes, supporting strong interactions with other community members at chemoclines. Our results also revealed distinct Woesearchaeota ecotypes, with different transcriptional patterns, contrasted lifestyles, and ecological strategies, depending on environmental/host conditions. Conclusions: This work provides novel insights into Woesearchaeota in situ activity and metabolism, revealing invariant, bimodal, and adaptative lifestyles among halophilic Woesearchaeota. This challenges our precepts of an invariable host-dependent metabolism for all the members of this taxa and revises our understanding of their contributions to ecosystem functioning and microbiome assemblage. Bo26ccZX9sY8C76pvHyDey Video Abstract [ABSTRACT FROM AUTHOR]

Background: Previous studies have shown that microbial communities differ in obese and lean individuals, and dietary fiber can help reduce obesity-related conditions through diet-gut microbiota interactions. However, the mechanisms by which dietary fibers shape the gut microbiota still need to be elucidated. In this in vitro study, we examined how apple fibers affect lean and obese microbial communities on a global scale. We employed a high-throughput micro-matrix bioreactor system and a multi-omics approach to identify the key microorganisms and metabolites involved in this process. Results: Initially, metagenomics and metabolomics data indicated that obese and lean microbial communities had distinct starting microbial communities. We found that obese microbial community had different characteristics, including higher levels of Ruminococcus bromii and lower levels of Faecalibacterium prausnitzii, along with an increased Firmicutes:Bacteroides ratio. Afterward, we exposed obese and lean microbial communities to an apple as a representative complex food matrix, apple pectin as a soluble fiber, and cellulose as an insoluble fiber. Dietary fibers, particularly apple pectin, reduced Acidaminococcus intestini and boosted Megasphaera and Akkermansia in the obese microbial community. Additionally, these fibers altered the production of metabolites, increasing beneficial indole microbial metabolites. Our results underscored the ability of apple and apple pectin to shape the obese gut microbiota. Conclusion: We found that the obese microbial community had higher branched-chain amino acid catabolism and hexanoic acid production, potentially impacting energy balance. Apple dietary fibers, especially pectin, influenced the obese microbial community, altering both species and metabolites. Notably, the apple pectin feeding condition affected species like Klebsiella pneumoniae and Bifidobacterium longum. By using genome-scale metabolic modeling, we discovered a mutualistic cross-feeding relationship between Megasphaera sp. MJR8396C and Bifidobacterium adolescentis. This in vitro study suggests that incorporating apple fibers into the diets of obese individuals can help modify the composition of gut bacteria and improve metabolic health. This personalized approach could help mitigate the effects of obesity. 1sSYKieb1FyPG4CFVZT5AP Video Abstract [ABSTRACT FROM AUTHOR]

Background: Microbiomes, essential to ecosystem processes, face strong selective forces that can drive rapid evolutionary adaptation. However, our understanding of evolutionary processes within natural systems remains limited. We investigated evolution in response to naturally occurring selenium in soils of different geological parental materials on the Western Slope of Colorado. Our study focused on examining changes in gene frequencies within microbial communities in response to selenium exposure. Results: Despite expectations of taxonomic composition shifts and increased gene content changes at high-selenium sites, we found no significant alterations in microbial diversity or community composition. Surprisingly, we observed a significant increase in differentially abundant genes within high-selenium sites. Conclusions: These findings are suggestive that selection within microbiomes primarily drives the accumulation of genes among existing microbial taxa, rather than microbial species turnover, in response to strong stressors like selenium. Our study highlights an unusual system that allows us to examine evolution in response to the same stressor annually in a non-model system, contributing to understanding microbiome evolution beyond model systems. [ABSTRACT FROM AUTHOR]

Background: Therapeutic targets supported by genetic evidence from genome-wide association studies (GWAS) show higher probability of success in clinical trials. GWAS is a powerful approach to identify links between genetic variants and phenotypic variation; however, identifying the genes driving associations identified in GWAS remains challenging. Integration of molecular quantitative trait loci (molQTL) such as expression QTL (eQTL) using mendelian randomization (MR) and colocalization analyses can help with the identification of causal genes. Careful interpretation remains warranted because eQTL can affect the expression of multiple genes within the same locus. Methods: We used a combination of genomic features that include variant annotation, activity-by-contact maps, MR, and colocalization with molQTL to prioritize causal genes across 4,611 disease GWAS and meta-analyses from biobank studies, namely FinnGen, Estonian Biobank and UK Biobank. Results: Genes identified using this approach are enriched for gold standard causal genes and capture known biological links between disease genetics and biology. In addition, we find that eQTL colocalizing with GWAS are statistically enriched for corresponding disease-relevant tissues. We show that predicted directionality from MR is generally consistent with matched drug mechanism of actions (> 85% for approved drugs). Compared to the nearest gene mapping method, genes supported by multi-omics evidences displayed higher enrichment in approved therapeutic targets (risk ratio 1.75 vs. 2.58 for genes with the highest level of support). Finally, using this approach, we detected anassociation between the IL6 receptor signal transduction gene IL6ST and polymyalgia rheumatica, an indication for which sarilumab, a monoclonal antibody against IL-6, has been recently approved. Conclusions: Combining variant annotation, activity-by-contact maps, and molQTL increases performance to identify causal genes, while informing on directionality which can be translated to successful target identification and drug development. [ABSTRACT FROM AUTHOR]

Objective: The influence of different faecal collection methods on metagenomic analyses remains under discussion, and there is no general agreement on which collection method is preferable for gut microbiome research. We compared faecal samples collected in tubes without preservatives with those containing 10 mL of 96% ethanol for gut microbiome research when the timeframe from defecation to freezing at – 80 °C was up to 24 h. We aimed to compare the collection methods on faeces from participants with inflammatory and non-inflammatory gastrointestinal disorders and healthy controls to investigate the most suitable method when considering data yield, human fraction of sequencing reads, and ease of use. We also examined the faecal sample homogeneity. Results: Faeces collected in tubes without preservatives resulted in more sequencing reads compared to faeces collected in tubes with 96% ethanol and were also easier to handle. The human fraction of total reads in faeces collected in ethanol from participants with inflammatory bowel disease was higher than all other samples. DNA extraction and sequencing from two different locations in the same faecal sample gave similar results and showed sample homogeneity. [ABSTRACT FROM AUTHOR]

Background: The gut microbiome modulates the effects of diet on host health, but it remains unclear which specific foods and microbial features interact to influence risk of depression. To understand this interplay, we leveraged decades of dietary and depression data from a longitudinal cohort of women (n = 32,427), along with fecal metagenomics and plasma metabolomics from a substudy (n = 207) nested in this cohort, as well as an independent validation cohort of men (n = 307). Results: We report that citrus intake and its components are prospectively associated with a lower risk of depression and altered abundance of 15 gut microbial species, including enriched Faecalibacterium prausnitzii. In turn, we found a lower abundance of F. prausnitzii and its metabolic pathway, S-adenosyl-L-methionine (SAM) cycle I in participants with depression. To explore causality, we found that lower SAM production by F. prausnitzii may decrease intestinal monoamine oxidase A gene expression implicated in serotonin and dopamine synthesis. Conclusions: These data underscore the role of diet in the prevention of depression and offer a plausible explanation for how the intestinal microbiome modulates the influence of citrus on mental health. ELPzvN5keGYhLtpEkepcja Video Abstract [ABSTRACT FROM AUTHOR]

Background: Plant-soil feedback arises from microbial legacies left by plants in the soil. Grafting is a common technique used to prevent yield declines in monocultures. Yet, our understanding of how grafting alters the composition of soil microbiota and how these changes affect subsequent crop performance remains limited. Our experiment involved monoculturing ungrafted and grafted watermelons to obtain conditioned soils, followed by growing the watermelons on the conditioned soils to investigate plant-soil feedback effects. Results: Ungrafted plants grew better in soil previously conditioned by a different plant (heterospecific soil) while grafted plants grew better in soil conditioned by the same plant (conspecific soil). We demonstrated experimentally that these differences in growth were linked to changes in microorganisms. Using a supervised machine learning algorithm, we showed that differences in the relative abundance of certain genera, such as Rhizobium, Chryseobacterium, Fusarium, and Aspergillus, significantly influenced the conspecific plant-soil feedback. Metabolomic analyses revealed that ungrafted plants in heterospecific soil enriched arginine biosynthesis, whereas grafted plants in conspecific soil increased sphingolipid metabolism. Elsewhere, the metagenome-assembled genomes (MAGs) of ungrafted plants identified in heterospecific soil include Chryseobacterium and Lysobacter, microorganisms having been prominently identified in earlier research as contributors to plant growth. Metabolic reconstruction revealed the putative ability of Chryseobacterium to convert D-glucono-1,5-lactone to gluconic acid, pointing to distinct disease-suppressive mechanisms and hence distinct microbial functional legacies between grafted and ungrafted plants. Conclusions: Our findings show a deep impact of the soil microbial reservoir on plant growth and suggest the necessity to protect and improve this microbial community in agricultural soils. The work also suggests possibilities of optimizing microbiota-mediated benefits through grafting herein, a way that "engineered" soil microbial communities for better plant growth. BP591-gZtAk87jMPWFVThJ Video Abstract [ABSTRACT FROM AUTHOR]

Background: Rotaviruses are the major etiological agents of gastroenteritis and diarrheal outbreaks in plenty of mammalian species. The genus Rotavirus is highly diverse and currently comprises nine genetically distinct species, and four of them (A, B, C, and H) are common for humans and pigs. There is a strong necessity to comprehend phylogenetic relationships among rotaviruses from different host species to assess interspecies transmission, specifically between humans and livestock. To reveal the genetic origin of rotaviruses from Russian pig farms, nanopore-based metagenomic sequencing was performed on the PCR-positive specimens. Methods: Samples were selected among the cases submitted to routine diagnostic or monitoring studies to the Laboratory of Biochemistry and Molecular Biology of "Federal Scientific Center VIEV" (Moscow, Russia). The selected positive samples were genotyped using nanopore sequencing method. Results: Five porcine RVA isolates were completely sequenced, and genotype analysis revealed various porcine G/P genogroups: G2, G3, G4, G5, G11 and P[6], P[7], P[13], P[23], P[27] with a typical backbone constellation I5-R1-C1-M1-A8-N1-T1/7-E1-H1. The RVB isolate was detected in combination with RVA in a rectal swab from a diseased pig in Krasnoyarsk Krai. It was characterized by the following genogroups: G15-P[X]-I11-R4-C4-M4-A8-N10-T4-E4-H7. The first complete porcine RVC genome from Russia was obtained with genomic constellation G6-P[5]-I14-R1-C1-M1-A7-N9-T6-E1-H1, and the phylogenetic analysis revealed putative novel genotype group for the VP6 gene-I14. Additionally, the first porcine kobuvirus isolate from Russia was phylogenetically characterized. Conclusions: The applied nanopore sequencing method successfully genotyped the RV isolates and additionally revealed co-circulated species. The study demonstrates high genetic variability of Russian RVA isolates in VP4/VP7 genes and phylogenetically describes local RVB and RVC. Complete characterization of genomic segments is a crucial methodology in tracing the rotavirus's evolution and evaluating interspecies transmissions. [ABSTRACT FROM AUTHOR]

Background: The gut microbiota (GM) has proven to be essential for both physical health and mental wellbeing, yet the forces that ultimately shape its composition remain opaque. One critical force known to affect the GM is the social environment. Prior work in humans and free-ranging non-human primates has shown that cohabitation and frequent social interaction can lead to changes in GM composition. However, it is difficult to assess the direction of causation in these studies, and interpretations are complicated by the influence of uncontrolled but correlated factors, such as shared diet. Results: We performed a 15-month longitudinal investigation wherein we disentangled the impacts of diet and social living conditions on GM composition in a captive cohort of 13 male cynomolgus macaques. The animals were in single housing for the first 3 months of the study initially with a variable diet. After baseline data collection they were placed on a controlled diet for the remainder of the study. Following this diet shift the animals were moved to paired housing for 6 months, enabling enhanced social interaction, and then subsequently returned to single housing at the end of our study. This structured sequencing of diet and housing changes allowed us to assess their distinct impacts on GM composition. We found that the early dietary adjustments led to GM changes in both alpha and beta diversity, whereas changes in social living conditions only altered beta diversity. With respect to the latter, we found that two particular bacterial families — Lactobacillaceae and Clostridiaceae — demonstrated significant shifts in abundance during the transition from single housing to paired housing, which was distinct from the shifts we observed based on a change in diet. Conversely, we found that other bacteria previously associated with sociality were not altered based on changes in social living conditions but rather only by changes in diet. Conclusions: Together, these findings decouple the influences that diet and social living have on GM composition and reconcile previous observations in the human and animal literatures. Moreover, the results indicate biological alterations of the gut that may, in part, mediate the relationship between sociality and wellbeing. [ABSTRACT FROM AUTHOR]

Background: Porcine ear necrosis (PEN) is characterized by dry crusts on the ear tip. The crusts often progress to moist and bloody lesions and may lead to partial loss of the ear tissue. The cause and pathophysiology of PEN are unknown. Skin infections, systemic infections, or ear biting have been suggested as a cause of PEN, but no proper evidence has been shown. The behavioural factor has not yet been investigated, therefore this study evaluated the importance of oral manipulations in the occurrence of PEN in nursery pigs. Three farms affected by PEN were visited weekly, and the prevalence and severity were recorded. Video recordings of the animals were performed, and the behaviour was evaluated. The presence of pathogens in the lesions and histological alterations were also analysed. Results: The highest percentage of pigs with PEN lesions in the farms ranged between 58 and 93%, with most lesions being of mild to moderate severity. The first ear lesions occurred about 1–2 weeks after an increase in the number of ear manipulations in the pens. The frequency of the ear manipulations clearly changed over time, and the number of oral ear manipulation behaviour significantly differed (P < 0.05) between pigs in pens with high and low PEN prevalence. Increased ear manipulation behaviour was significantly related to a subsequent increase in PEN lesions (OR = 4.3; P < 0.001). Metagenomic investigation of lesion scrapings revealed a variety of pathogens mostly with low abundance, where microscopic alterations were found mainly in the epidermis. Conclusions: Oral manipulation of the ear pinnae by pen mates was followed by the development of PEN lesions one to two weeks later. This suggests that the behaviour played an important role in the PEN lesions formation in the nursery pigs of the three farms. Bacteria found in PEN lesions most probably were secondary to initial external skin damage, but their relevance needs to be investigated further. [ABSTRACT FROM AUTHOR]

Glucocorticoids (GCs) are key inducers of osteonecrosis, yet not all patients treated with GCs develop glucocorticoid-associated osteonecrosis (GAON). The factors mediating this relationship are unclear. Studies have shown that gut microbiota and their metabolites influence bone metabolism, but their role in GAON is unclear. This study aimed to explore the connection between GAON and gut microbiota. Through bidirectional Mendelian randomization analysis, we identified 14 gut microbial taxa, including Lachnospiraceae (IVW, P = 0.011), associated with GAON. RNA-seq analysis revealed that GAON differentially expressed genes (DEGs) were enriched for intestinal inflammatory response mechanisms. We then compared patients who developed GAON (17 cases), those who did not (GAnON, 15 cases), and those untreated with GCs (Blank, 15 cases) for gut microbiota composition, short-chain fatty acids (SCFAs), and serum inflammatory factors. Our findings indicated a decrease in Lachnospiraceae abundance (GAON 17.13%, GAnON 12.51%, Blank 24.52%) in GC-treated patients. Serum inflammatory factors (IL-17 A, IL-33, and TNF-α) associated with GAON (59.603 ± 12.147, 89.337 ± 20.714, 42.584 ± 9.185) showed significant differences between Blank (1.446 ± 0.683, 11.534 ± 4.705, 4.682 ± 1.48) and GAnON (25.353 ± 8.181, 32.527 ± 7.352, 12.49 ± 3.217) groups, with a negative correlation between these factors and Lachnospiraceae levels. Butyric acid levels in SCFAs varied among groups (P<0.01) and correlated with Lachnospiraceae and inflammatory factors. Controlled experiments in GAON rats demonstrated butyric acid's osteoprotective role in GAON development (P<0.01). In conclusion, our study suggests that reduced Lachnospiraceae and butyric acid levels, along with increased inflammation due to GCs use, contribute to GAON. Butyric acid may mediate the effects of Lachnospiraceae and inflammation. Butyrate supplementation could potentially reduce GAON incidence, offering a novel approach for its clinical management. [ABSTRACT FROM AUTHOR]

Motivation: Accurate determination and quantification of the taxonomic composition of microbial communities, especially at the species level, is one of the major issues in metagenomics. This is primarily due to the limitations of commonly used 16S rRNA reference databases, which either contain a lot of redundancy or a high percentage of sequences with missing taxonomic information. This may lead to erroneous identifications and, thus, to inaccurate conclusions regarding the ecological role and importance of those microorganisms in the ecosystem. Results: The current study presents MIMt, a new 16S rRNA database for archaea and bacteria's identification, encompassing 47 001 sequences, all precisely identified at species level. In addition, a MIMt2.0 version was created with only curated sequences from RefSeq Targeted loci with 32 086 sequences. MIMt aims to be updated twice a year to include all newly sequenced species. We evaluated MIMt against Greengenes, RDP, GTDB and SILVA in terms of sequence distribution and taxonomic assignments accuracy. Our results showed that MIMt contains less redundancy, and despite being 20 to 500 times smaller than existing databases, outperforms them in completeness and taxonomic accuracy, enabling more precise assignments at lower taxonomic ranks and thus, significantly improving species-level identification. [ABSTRACT FROM AUTHOR]

Background: Aquaculture and salmon farming can cause environmental problems due to the pollution of the surrounding waters with nutrients, solid wastes and chemicals, such as antibiotics, which are used for disease control in the aquaculture facilities. Increasing antibiotic resistance in human-impacted environments, such as coastal waters with aquaculture activity, is linked to the widespread use of antibiotics, even at sub-lethal concentrations. In Chile, the world's second largest producer of salmon, aquaculture is considered the primary source of antibiotics residues in the coastal waters of northern Patagonia. Here, we evaluated whether the structure and diversity of marine bacterial community, the richness of antibiotic resistance bacteria and the frequency of antibiotic resistance genes increase in communities from the surface seawater of an area with salmon farming activities, in comparison with communities from an area without major anthropogenic disturbance. Results: The taxonomic structure of bacterial community was significantly different between areas with and without aquaculture production. Growth of the culturable fraction under controlled laboratory conditions showed that, in comparison with the undisturbed area, the bacterial community from salmon farms displayed a higher frequency of colonies resistant to the antibiotics used by the salmon industry. A higher adaptation to antibiotics was revealed by a greater proportion of multi-resistant bacteria isolated from the surface seawater of the salmon farming area. Furthermore, metagenomics data revealed a significant higher abundance of antibiotic resistant genes conferring resistance to 11 antibiotic families in the community from salmon farms, indicating that the proportion of bacteria carrying the resistance determinants was overall higher in salmon farms than in the undisturbed site. Conclusions: Our results revealed an association between bacterial communities and antibiotic resistance from surface seawater of a coastal area of Chile. Although the total bacterial community may appear comparable between sites, the cultivation technique allowed to expose a higher prevalence of antibiotic resistant bacteria in the salmon farming area. Moreover, we demonstrated that metagenomics (culture-independent) and phenotypic (culture-dependent) methods are complementary to evaluate the bacterial communities' risk for antibiotic resistance, and that a human—influenced environment (such as salmon farms) can potentiate bacteria to adapt to environmental stresses, such as antibiotics. [ABSTRACT FROM AUTHOR]

Amphibians represent a diverse group of tetrapods, marked by deep divergence times between their three systematic orders and families. Studying amphibian biology through the genomics lens increases our understanding of the features of this animal class and that of other terrestrial vertebrates. The need for amphibian genomic resources is more urgent than ever due to the increasing threats to this group. Amphibians are one of the most imperiled taxonomic groups, with approximately 41% of species threatened with extinction due to habitat loss, changes in land use patterns, disease, climate change, and their synergistic effects. Amphibian genomic resources have provided a better understanding of ontogenetic diversity, tissue regeneration, diverse life history and reproductive modes, anti-predator strategies, and resilience and adaptive responses. They also serve as essential models for studying broad genomic traits, such as evolutionary genome expansions and contractions, as they exhibit the widest range of genome sizes among all animal taxa and possess multiple mechanisms of genetic sex determination. Despite these features, genome sequencing of amphibians has significantly lagged behind that of other vertebrates, primarily due to the challenges of assembling their large, repeat-rich genomes and the relative lack of societal support. The emergence of long-read sequencing technologies, combined with advanced molecular and computational techniques that improve scaffolding and reduce computational workloads, is now making it possible to address some of these challenges. To promote and accelerate the production and use of amphibian genomics research through international coordination and collaboration, we launched the Amphibian Genomics Consortium (AGC, https://mvs.unimelb.edu.au/amphibian-genomics-consortium) in early 2023. This burgeoning community already has more than 282 members from 41 countries. The AGC aims to leverage the diverse capabilities of its members to advance genomic resources for amphibians and bridge the implementation gap between biologists, bioinformaticians, and conservation practitioners. Here we evaluate the state of the field of amphibian genomics, highlight previous studies, present challenges to overcome, and call on the research and conservation communities to unite as part of the AGC to enable amphibian genomics research to "leap" to the next level. [ABSTRACT FROM AUTHOR]

Background: Metagenomics, the whole genome sequencing of microbial communities, has provided insight into complex ecosystems. It has facilitated the discovery of novel microorganisms, explained community interactions and found applications in various fields. Advances in high-throughput and third-generation sequencing technologies have further fuelled its popularity. Nevertheless, managing the vast data produced and addressing variable dataset quality remain ongoing challenges. Another challenge arises from the number of assembly and binning strategies used across studies. Comparing datasets and analysis tools is complex as it requires the quantitative assessment of metagenome quality. The inherent limitations of metagenomic sequencing, which often involves sequencing complex communities, mean community members are challenging to interrogate with traditional culturing methods leading to many lacking reference sequences. MIMAG standards aim to provide a method to assess metagenome quality for comparison but have not been widely adopted. Results: To address the need for simple and quick metagenome quality assignation, here we introduce the pipeline MAGqual (Metagenome-Assembled Genome qualifier) and demonstrate its effectiveness at determining metagenomic dataset quality in the context of the MIMAG standards. Conclusions: The MAGqual pipeline offers an accessible way to evaluate metagenome quality and generate metadata on a large scale. MAGqual is built in Snakemake to ensure readability and scalability, and its open-source nature promotes accessibility, community development, and ease of updates. MAGqual is built in Snakemake, R, and Python and is available under the MIT license on GitHub at https://github.com/ac1513/MAGqual. EB_9RbKd3CYdEq3zCTHKaq Video Abstract [ABSTRACT FROM AUTHOR]

Background: Aquatic viruses act as key players in shaping microbial communities. In polar environments, they face significant challenges such as limited host availability and harsh conditions. However, due to the restricted accessibility of these ecosystems, our understanding of viral diversity, abundance, adaptations, and host interactions remains limited. Results: To fill this knowledge gap, we studied viruses from atmosphere-close aquatic ecosystems in the Central Arctic and Northern Greenland. Aquatic samples for virus-host analysis were collected from ~60 cm depth and the submillimeter surface microlayer (SML) during the Synoptic Arctic Survey 2021 on icebreaker Oden in the Arctic summer. Water was sampled from a melt pond and open water before undergoing size-fractioned filtration, followed by genome-resolved metagenomic and cultivation investigations. The prokaryotic diversity in the melt pond was considerably lower compared to that of open water. The melt pond was dominated by a Flavobacterium sp. and Aquiluna sp., the latter having a relatively small genome size of 1.2 Mb and the metabolic potential to generate ATP using the phosphate acetyltransferase-acetate kinase pathway. Viral diversity on the host fraction (0.2–5 µm) of the melt pond was strikingly limited compared to that of open water. From the 1154 viral operational taxonomic units (vOTUs), of which two-thirds were predicted bacteriophages, 17.2% encoded for auxiliary metabolic genes (AMGs) with metabolic functions. Some AMGs like glycerol-3-phosphate cytidylyltransferase and ice-binding like proteins might serve to provide cryoprotection for the host. Prophages were often associated with SML genomes, and two active prophages of new viral genera from the Arctic SML strain Leeuwenhoekiella aequorea Arc30 were induced. We found evidence that vOTU abundance in the SML compared to that of ~60 cm depth was more positively correlated with the distribution of a vOTU across five different Arctic stations. Conclusions: The results indicate that viruses employ elaborate strategies to endure in extreme, host-limited environments. Moreover, our observations suggest that the immediate air-sea interface serves as a platform for viral distribution in the Central Arctic. Dvb_jZZ1H7pg55rxrDSVb2 Video Abstract [ABSTRACT FROM AUTHOR]

Background: Alterations in upper respiratory microbiomes have been implicated in shaping host health trajectories, including by limiting mucosal pathogen colonization. However, limited comparative studies of respiratory microbiome development and functioning across age groups have been performed. Herein, we perform shotgun metagenomic sequencing paired with pathogen inhibition assays to elucidate differences in nasal and oral microbiome composition and intermicrobial interactions across healthy 24-month-old infant (n = 229) and adult (n = 100) populations. Results: We find that beta diversity of nasal and oral microbiomes varies with age, with nasal microbiomes showing greater population-level variation compared to oral microbiomes. Infant microbiome alpha diversity was significantly lower across nasal samples and higher in oral samples, relative to adults. Accordingly, we demonstrate significant differences in genus- and species-level composition of microbiomes between sites and age groups. Antimicrobial resistome patterns likewise varied across body sites, with oral microbiomes showing higher resistance gene abundance compared to nasal microbiomes. Biosynthetic gene clusters encoding specialized metabolite production were found in higher abundance across infant oral microbiomes, relative to adults. Investigation of pathogen inhibition revealed greater inhibition of gram-negative and gram-positive bacteria by oral commensals, while nasal isolates had higher antifungal activity. Conclusions: In summary, we identify significant differences in the microbial communities inhabiting nasal and oral cavities of healthy infants relative to adults. These findings inform our understanding of the interactions impacting respiratory microbiome composition and functions related to colonization resistance, with important implications for host health across the lifespan. 5XcHcd9N21H4_6hqSTf5-o Video Abstract [ABSTRACT FROM AUTHOR]

Background: Processing environments can be an important source of pathogenic and spoilage microorganisms that cross contaminate meat and meat products. The aim of this study was to characterize the microbiome of raw materials, processing environments and end products from 19 facilities producing different meat products. Results: The taxonomic profiles of the microbial communities evolved along processing, from raw materials to end products, suggesting that food contact (FC) surfaces play an important role in modulating the microbiome of final products. Some species persisted with the highest relative abundance in raw materials, food processing environments and/or in the final product, including species from the genera Pseudomonas, Staphylococcus, Brochothrix, Acinetobacter and Psychrobacter. Processing environments showed a very diverse core microbiota, partially shared with the products. Pseudomonas fragi and Pseudomonas sp. Lz4W (in all sample and facility types) and Brochothrix thermosphacta, Psychrobacter sp. and Psychrobacter sp. P11F6 (in raw materials, FC surfaces and end products) were prominent members of the core microbiota for all facilities, while Latilactobacillus sakei was found as a dominant species exclusively in end products from the facilities producing fermented sausages. Processing environments showed a higher amount of antimicrobial resistance genes and virulence factors than raw materials and end products. One thousand four hundred twenty-one medium/high-quality metagenome-assembled genomes (MAGs) were reconstructed. Of these, 274 high-quality MAGs (completeness > 90%) corresponded to 210 putative new species, mostly found in processing environments. For two relevant taxa in meat curing and fermentation processes (S. equorum and L. sakei, respectively), phylogenetic variation was observed associated with the specific processing facility under study, which suggests that specific strains of these taxa may be selected in different meat processing plants, likely contributing to the peculiar sensorial traits of the end products produced in them. Conclusions: Overall, our findings provide the most detailed metagenomics-based perspective up to now of the microbes that thrive in meat, meat products and associated environments and open avenues for future research activities to better understand the microbiome functionality and potential contribution to meat quality and safety. BW5-yJYgBWXLb4-yN7W47n Video Abstract [ABSTRACT FROM AUTHOR]

Background: Assembly of metagenomic samples can provide essential information about the mobility potential and taxonomic origin of antibiotic resistance genes (ARGs) and inform interventions to prevent further spread of resistant bacteria. However, similar to other conserved regions, such as ribosomal RNA genes and mobile genetic elements, almost identical ARGs typically occur in multiple genomic contexts across different species, representing a considerable challenge for the assembly process. Usually, this results in many fragmented contigs of unclear origin, complicating the risk assessment of ARG detections. To systematically investigate the impact of this issue on detection, quantification and contextualization of ARGs, we evaluated the performance of different assembly approaches, including genomic-, metagenomic- and transcriptomic-specialized assemblers. We quantified recovery and accuracy rates of each tool for ARGs both from in silico spiked metagenomic samples as well as real samples sequenced using both long- and short-read sequencing technologies. Results: The results revealed that none of the investigated tools can accurately capture genomic contexts present in samples of high complexity. The transcriptomic assembler Trinity showed a better performance in terms of reconstructing longer and fewer contigs matching unique genomic contexts, which can be beneficial for deciphering the taxonomic origin of ARGs. The currently commonly used metagenomic assembly tools metaSPAdes and MEGAHIT were able to identify the ARG repertoire but failed to fully recover the diversity of genomic contexts present in a sample. On top of that, in a complex scenario MEGAHIT produced very short contigs, which can lead to considerable underestimation of the resistome in a given sample. Conclusions: Our study shows that metaSPAdes and Trinity would be the preferable tools in terms of accuracy to recover correct genomic contexts around ARGs in metagenomic samples characterized by uneven coverages. Overall, the inability of assemblers to reconstruct long ARG-containing contigs has impacts on ARG quantification, suggesting that directly mapping reads to an ARG database should be performed as a complementary strategy to get accurate ARG abundance and diversity measures. [ABSTRACT FROM AUTHOR]

Background: Foodborne pathogens such as Campylobacter jejuni are responsible for a large proportion of the gastrointestinal infections worldwide associated with poultry meat. Campylobacter spp. can be found in the chicken fecal microbiome and can contaminate poultry meat during the slaughter process. Commonly used sampling methods to detect Campylobacter spp. at poultry farms use fecal droppings or boot swabs in combination with conventional culture techniques or PCR. In this pilot study, we have used air filtering and filters spiked with mock communities in combination with shotgun metagenomics to detect Campylobacter and test the applicability of this approach for the detection and characterization of foodborne pathogens. To the best of our knowledge is this the first study that combines air filtering with shotgun metagenomic sequencing for detection and characterization of Campylobacter. Results: Analysis of air filters spiked with different levels of Campylobacter, into a background of mock or poultry house communities, indicated that we could detect as little as 200 colony forming units (CFU) Campylobacter per sample using our protocols. The results indicate that even with limited sequencing effort we could detect Campylobacter in the samples analysed in this study. We observed significant amounts of Campylobacter in real-life samples from poultry houses using both real-time PCR as well as shotgun metagenomics, suggesting that the flocks in both houses were infected with Campylobacter spp. Interestingly, in both houses we find diverse microbial communities present in the indoor air which reflect the fecal microbiome of poultry. Some of the identified genera such as Staphylococcus, Escherichia and Pseudomonas are known to contain opportunistic pathogenic species. Conclusions: These results show that air sampling of poultry houses in combination with shotgun metagenomics can detect and identify Campylobacter spp. present at low levels. This is important since early detection of Campylobacter enables measures to be put in place to ensure the safety of broiler products, animal health and public health. This approach has the potential to detect any pathogen present in poultry house air. [ABSTRACT FROM AUTHOR]

Background: Termitarium is an intricate biological home with exceptional physicochemical soil properties and numerous beneficial microbiomes. The termitarium microbiome plays a role in several bionetwork processes. It contributes significantly to sustainable agriculture, forestry, and horticulture. In contrast to the immense number of research works focusing on termitarium bacteria and archaea, the amount of study about termitarium fungal communities is limited. This is despite the fact that fungi significantly contribute to the cycling of energy and matter on Earth. Thus, this study investigates the metagenomic datasets from termitarium soil collected from agricultural soils, to obtain a depiction of their mycobiome of ecological importance. Results: Our dataset showed that Ascomycota was the most rank phylum, while Basidiomycota was the next in rank. Specifically, we identified numerous fungi of commercially importance, for example, producers of cellulases and cellulosomes. This was strengthened with the presence of functional genes/enzymes capable of promoting plant growth traits and defence system. Analysis further shown that soil properties influenced the distribution of fungal communities. Magnesium, nitrogen, and potassium, for example, were observed to be among the best predictor of fungal distribution and explained 87.40% of the total variation. Conclusion: This study epitomize further insights into the mycobiome of termitarium soils that are of ecological interest. Again, with some of our sequences assembled as uncategorized fungi, further studies are recommended for the evaluation of the metabolic potentials of these fungi as there is a possibility of the discovery of new fungi or genes of industrial or environmental applications. [ABSTRACT FROM AUTHOR]

Objective: We developed an in-house bioinformatics pipeline to improve the detection of respiratory pathogens in metagenomic sequencing data. This pipeline addresses the need for short-time analysis, high accuracy, scalability, and reproducibility in a high-performance computing environment. Results: We evaluated our pipeline using ninety synthetic metagenomes designed to simulate nasopharyngeal swab samples. The pipeline successfully identified 177 out of 204 respiratory pathogens present in the compositions, with an average processing time of approximately 4 min per sample (processing 1 million paired-end reads of 150 base pairs). For the estimation of all the 470 taxa included in the compositions, the pipeline demonstrated high accuracy, identifying 420 and achieving a correlation of 0.9 between their actual and predicted relative abundances. Among the identified taxa, 27 were significantly underestimated or overestimated, including only three clinically relevant pathogens. We also validated the pipeline by applying it to a clinical dataset from a study on metagenomic pathogen characterization in patients with acute respiratory infections and successfully identified all pathogens responsible for the diagnosed infections. These findings underscore the pipeline's effectiveness in pathogen detection and highlight its potential utility in respiratory pathogen surveillance. [ABSTRACT FROM AUTHOR]

Background: Bacteria of the candidate phyla radiation (CPR), constituting about 25% of the bacterial biodiversity, are characterized by small cell size and patchy genomes without complete key metabolic pathways, suggesting a symbiotic lifestyle. Gracilibacteria (BD1-5), which are part of the CPR branch, possess alternate coded genomes and have not yet been cultivated. The lifestyle of Gracilibacteria, their temporal dynamics, and activity in natural ecosystems, particularly in groundwater, has remained largely unexplored. Here, we aimed to investigate Gracilibacteria activity in situ and to discern their lifestyle based on expressed genes, using the metaproteogenome of Gracilibacteria as a function of time in the cold-water geyser Wallender Born in the Volcanic Eifel region in Germany. Results: We coupled genome-resolved metagenomics and metaproteomics to investigate a cold-water geyser microbial community enriched in Gracilibacteria across a 12-day time-series. Groundwater was collected and sequentially filtered to fraction CPR and other bacteria. Based on 725 Gbps of metagenomic data, 1129 different ribosomal protein S3 marker genes, and 751 high-quality genomes (123 population genomes after dereplication), we identified dominant bacteria belonging to Gallionellales and Gracilibacteria along with keystone microbes, which were low in genomic abundance but substantially contributing to proteomic abundance. Seven high-quality Gracilibacteria genomes showed typical limitations, such as limited amino acid or nucleotide synthesis, in their central metabolism but no co-occurrence with potential hosts. The genomes of these Gracilibacteria were encoded for a high number of proteins involved in cell to cell interaction, supporting the previously surmised host-dependent lifestyle, e.g., type IV and type II secretion system subunits, transporters, and features related to cell motility, which were also detected on protein level. Conclusions: We here identified microbial keystone taxa in a high-CO2 aquifer, and revealed microbial dynamics of Gracilibacteria. Although Gracilibacteria in this ecosystem did not appear to target specific organisms in this ecosystem due to lack of co-occurrence despite enrichment on 0.2-µm filter fraction, we provide proteomic evidence for the complex machinery behind the host-dependent lifestyle of groundwater Gracilibacteria. 38kgAxaMce3Yn9ghud_S2p Video Abstract [ABSTRACT FROM AUTHOR]

Background: Metagenomics is a powerful approach to study environmental and human-associated microbial communities and, in particular, the role of viruses in shaping them. Viral genomes are challenging to assemble from metagenomic samples due to their genomic diversity caused by high mutation rates. In the standard de Bruijn graph assemblers, this genomic diversity leads to complex k-mer assembly graphs with a plethora of loops and bulges that are challenging to resolve into strains or haplotypes because variants more than the k-mer size apart cannot be phased. In contrast, overlap assemblers can phase variants as long as they are covered by a single read. Results: Here, we present PenguiN, a software for strain resolved assembly of viral DNA and RNA genomes and bacterial 16S rRNA from shotgun metagenomics. Its exhaustive detection of all read overlaps in linear time combined with a Bayesian model to select strain-resolved extensions allow it to assemble longer viral contigs, less fragmented genomes, and more strains than existing assembly tools, on both real and simulated datasets. We show a 3–40-fold increase in complete viral genomes and a 6-fold increase in bacterial 16S rRNA genes. Conclusion: PenguiN is the first overlap-based assembler for viral genome and 16S rRNA assembly from large and complex metagenomic datasets, which we hope will facilitate studying the key roles of viruses in microbial communities. C22dm7AjjRZTtiuc33W1sn Video Abstract [ABSTRACT FROM AUTHOR]