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Background: Scavenging indigenous village chickens play a vital role in sub-Saharan Africa, sustaining the livelihood of millions of farmers. These chickens are exposed to vastly different environments and feeds compared to commercial chickens. In this study, we analysed the caecal microbiota of 243 Ethiopian village chickens living in different altitude-dependent agro-ecologies. Results: Differences in bacterial diversity were significantly correlated with differences in specific climate factors, topsoil characteristics, and supplemental diets provided by farmers. Microbiota clustered into three enterotypes, with one particularly enriched at high altitudes. We assembled 9977 taxonomically and functionally diverse metagenome-assembled genomes. The vast majority of these were not found in a dataset of previously published chicken microbes or in the Genome Taxonomy Database. Conclusions: The wide functional and taxonomic diversity of these microbes highlights their importance in the local adaptation of indigenous poultry, and the significant impacts of environmental factors on the microbiota argue for further discoveries in other agro-ecologies. EEwR8PKafK2-LVnkA2-YG- Video Abstract [ABSTRACT FROM AUTHOR]

The nitrogen (N) cycle is the foundation of the biogeochemistry on Earth and plays a crucial role in global climate stability. It is one of the most important nutrient cycles in high-altitude lakes. The biogeochemistry of nitrogen is almost entirely dependent on redox reactions mediated by microorganisms. However, the nitrogen cycling of microbial communities in the high-altitude saline lakes of the Qinghai-Tibet Plateau (QTP), the world's "third pole" has not been investigated extensively. In this study, we used a metagenomic approach to investigate the microbial communities in four high-altitude pristine saline lakes in the Altun mountain on the QTP. We observed that Proteobacteria, Bacteroidota, and Actinobacteriota were dominant in these lakes. We reconstructed 1,593 bacterial MAGs and 8 archaeal MAGs, 1,060 of which were found to contain nitrogen cycle related genes. Our analysis revealed that nitrite reduction, nitrogen fixation, and assimilatory nitrate reduction processes might be active in the lakes. Denitrification might be a major mechanism driving the potential nitrogen loss, while nitrification might be inactive. A wide variety of microorganisms in the lake, dominated by Proteobacteria, participate together in the nitrogen cycle. The prevalence of the dominant taxon Yoonia in these lakes may be attributed to its well-established nitrogen functions and the coupled proton dynamics. This study is the first to systematically investigate the structure and nitrogen function of the microbial community in the high-altitude pristine saline lakes in the Altun mountain on the QTP. As such, it contributes to a better comprehension of biogeochemistry of high-altitude saline lakes. [ABSTRACT FROM AUTHOR]

Introduction: The dysbiosis of vaginal microbiota is recognized as a potential underlying factor contributing to infertility in women. This study aimed to compare the vaginal microbiomes of infertile and fertile women to investigate their relationship with infertility. Methods: Metagenomic analysis was conducted on samples from 5 infertile and 5 fertile individuals using both amplicon 16S and metagenomics shotgun sequencing methods. Results and discussion: In the infertile group, the bacterial community was primarily represented by three major bacterial genera: Lactobacillus (79.42%), Gardnerella (12.56%) and Prevotella (3.33%), whereas, the fertile group exhibited a more diverse composition with over 8 major bacterial genera, accompanied by significantly reduced abundance of Lactobacillus (48.79%) and Gardnerella (6.98%). At the species level, higher abundances of L. iners, L. gasseri and G. vaginalis were observed in the infertile group. Regarding the microbiome composition, only one fertile and two infertile subjects exhibited the healthiest Community State Types, CST-1, while CST-3 was observed among two infertile and one fertile subject, and CST-4 in three other fertile and one infertile subject. Overall, alpha diversity metrics indicated greater diversity and lower species richness in the control (fertile) group, while the infertile group displayed the opposite trend. However, beta-diversity analysis did not show distinct clustering of samples associated with any specific group; instead, it demonstrated CST-type specific clustering. Shotgun metagenomics further confirmed the dominance of Firmicutes, with a greater abundance of Lactobacillus species in the infertile group. Specifically, L. iners and G. vaginalis were identified as the most dominant and highly abundant in the infertile group. Fungi were only identified in the control group, dominated by Penicillium citrinum (62.5%). Metagenomeassembled genomes (MAGs) corroborated read-based taxonomic profiling, with the taxon L. johnsonii identified exclusively in disease samples. MAG identities shared by both groups include Shamonda orthobunyavirus, L. crispatus, Human endogenous retrovirus K113, L. iners, and G. vaginalis. Interestingly, the healthy microbiomes sequenced in this study contained two clusters, Penicillium and Staphylococcus haemolyticus, not found in the public dataset. In conclusion, this study suggests that lower species diversity with a higher abundance of L. iners, L. gasseri and G. vaginalis, may contribute to female infertility in our study datasets. However, larger sample sizes are necessary to further evaluate such association. [ABSTRACT FROM AUTHOR]

Background: Protists, single-celled eukaryotic organisms, are critical to food web ecology, contributing to primary productivity and connecting small bacteria and archaea to higher trophic levels. Lake Mendota is a large, eutrophic natural lake that is a Long-Term Ecological Research site and among the world's best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last 20 years. Here, we analyze this comprehensive time series to infer changes to the structure and function of the protistan community and to hypothesize about their interactions with bacteria. Results: Based on small subunit rRNA genes extracted from the metagenomes and metagenome-assembled genomes of microeukaryotes, we identify shifts in the eukaryotic phytoplankton community over time, which we predict to be a consequence of reduced zooplankton grazing pressures after the invasion of a invasive predator (the spiny water flea) to the lake. The metagenomic data also reveal the presence of the spiny water flea and the zebra mussel, a second invasive species to Lake Mendota, prior to their visual identification during routine monitoring. Furthermore, we use species co-occurrence and co-abundance analysis to connect the protistan community with bacterial taxa. Correlation analysis suggests that protists and bacteria may interact or respond similarly to environmental conditions. Cryptophytes declined in the second decade of the timeseries, while many alveolate groups (e.g., ciliates and dinoflagellates) and diatoms increased in abundance, changes that have implications for food web efficiency in Lake Mendota. Conclusions: We demonstrate that metagenomic sequence-based community analysis can complement existing efforts to monitor protists in Lake Mendota based on microscopy-based count surveys. We observed patterns of seasonal abundance in microeukaryotes in Lake Mendota that corroborated expectations from other systems, including high abundance of cryptophytes in winter and diatoms in fall and spring, but with much higher resolution than previous surveys. Our study identified long-term changes in the abundance of eukaryotic microbes and provided context for the known establishment of an invasive species that catalyzes a trophic cascade involving protists. Our findings are important for decoding potential long-term consequences of human interventions, including invasive species introduction. BaNPxYigHXA7H5uqkH8sry Video Abstract [ABSTRACT FROM AUTHOR]

Invasive pulmonary aspergillosis (IPA) in patients with diabetes mellitus has high incidence, especially in Type 2 diabetes mellitus (T2DM). The aim of this study was to evaluate the diagnostic efficacy of metagenomic next-generation sequencing (mNGS) for IPA in patients with T2DM. A total of 66 patients with T2DM were included, including 21 IPA and 45 non-IPA patients, from January 2022 to December 2022. The demographic characteristics, comorbidities, laboratory test results, antibiotic treatment response, and 30-day mortality rate of patients were analyzed. The diagnostic accuracy of mNGS and conventional methods was compared, including sensitivity, specificity, positive predictive value and negative predictive value. The sensitivity and specificity of mNGS were 66.7% and 100.0%, respectively, which were significantly higher than those of fluorescence staining (42.1% and 100%), serum 1,3-β-D-glucan detection (38.1% and 90.9%), serum galactomannan detection (14.3% and 94.9%) and BALF galactomannan detection (47.3% and 70.7%). Although the sensitivity of BALF culture (75.0%) was higher than that of mNGS (66.7%), the turnover time of mNGS was significantly shorter than that of traditional culture (1.6 days vs. 5.0 days). The sensitivity of mNGS combined with BALF culture reached 100.0%. In addition, mNGS has a stronger ability to detect co-pathogens with IPA. 47.6% of T2DM patients with IPA were adjusted the initial antimicrobial therapy according to the mNGS results. This is the first study to focus on the diagnostic performance of mNGS in IPA infection in T2DM patients. MNGS can be used as a supplement to conventional methods for the diagnosis of IPA in patients with T2DM. [ABSTRACT FROM AUTHOR]

Background : Endometriosis, defined as the presence of endometrial-like tissue outside of the uterus, is one of the most prevalent gynecological disorders. Although different theories have been proposed, its pathogenesis is not clear. Novel studies indicate that the gut microbiome may be involved in the etiology of endometriosis; nevertheless, the connection between microbes, their dysbiosis, and the development of endometriosis is understudied. This case–control study analyzed the gut microbiome in women with and without endometriosis to identify microbial targets involved in the disease. Methods: A subsample of 1000 women from the Estonian Microbiome cohort, including 136 women with endometriosis and 864 control women, was analyzed. Microbial composition was determined by shotgun metagenomics and microbial functional pathways were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Partitioning Around Medoids (PAM) algorithm was performed to cluster the microbial profile of the Estonian population. The alpha- and beta-diversity and differential abundance analyses were performed to assess the gut microbiome (species and KEGG orthologies (KO)) in both groups. Metagenomic reads were mapped to estrobolome-related enzymes' sequences to study potential microbiome-estrogen metabolism axis alterations in endometriosis. Results: Diversity analyses did not detect significant differences between women with and without endometriosis (alpha-diversity: all p-values > 0.05; beta-diversity: PERMANOVA, both R2 < 0.0007, p-values > 0.05). No differential species or pathways were detected after multiple testing adjustment (all FDR p-values > 0.05). Sensitivity analysis excluding women at menopause (> 50 years) confirmed our results. Estrobolome-associated enzymes' sequence reads were not significantly different between groups (all FDR p-values > 0.05). Conclusions: Our findings do not provide enough evidence to support the existence of a gut microbiome-dependent mechanism directly implicated in the pathogenesis of endometriosis. To the best of our knowledge, this is the largest metagenome study on endometriosis conducted to date. [ABSTRACT FROM AUTHOR]

Background: The average daily gain (ADG) of preweaning calves significantly influences their adult productivity and reproductive performance. Gastrointestinal microbes are known to exert an impact on host phenotypes, including ADG. The aim of this study was to investigate the mechanisms by which gastrointestinal microbiome regulate ADG in preweaning calves and to further validate them by isolating ADG-associated rumen microbes in vitro. Results: Sixteen Holstein heifer calves were selected from a cohort with 106 calves and divided into higher ADG (HADG; n = 8) and lower ADG (LADG; n = 8) groups. On the day of weaning, samples of rumen contents, hindgut contents, and plasma were collected for rumen metagenomics, rumen metabolomics, hindgut metagenomics, hindgut metabolomics, and plasma metabolomics analyses. Subsequently, rumen contents of preweaning Holstein heifer calves from the same dairy farm were collected to isolate ADG-associated rumen microbes. The results showed that the rumen microbes, including Pyramidobacter sp. C12-8, Pyramidobacter sp. CG50-2, Pyramidobacter porci, unclassified_g_Pyramidobacter, Pyramidobacter piscolens, and Acidaminococcus fermentans, were enriched in the rumen of HADG calves (LDA > 2, P < 0.05). Enrichment of these microbes in HADG calves' rumen promoted carbohydrate degradation and volatile fatty acid production, increasing proportion of butyrate in the rumen and ultimately contributing to higher preweaning ADG in calves (P < 0.05). The presence of active carbohydrate degradation in the rumen was further suggested by the negative correlation of the rumen microbes P. piscolens, P. sp. C12-8 and unclassified_g_Pyramidobacter with the rumen metabolites D-fructose (R < − 0.50, P < 0.05). Widespread positive correlations were observed between rumen microbes (such as P. piscolens, P. porci, and A. fermentans) and beneficial plasma metabolites (such as 1-pyrroline-5-carboxylic acid and 4-fluoro-L-phenylalanine), which were subsequently positively associated with the growth rate of HADG calves (R > 0.50, P < 0.05). We succeeded in isolating a strain of A. fermentans from the rumen contents of preweaning calves and named it Acidaminococcus fermentans P41. The in vitro cultivation revealed its capability to produce butyrate. In vitro fermentation experiments demonstrated that the addition of A. fermentans P41 significantly increased the proportion of butyrate in the rumen fluid (P < 0.05). These results further validated our findings. The relative abundance of Bifidobacterium pseudolongum in the hindgut of HADG calves was negatively correlated with hindgut 4-hydroxyglucobrassicin levels, which were positively correlated with plasma 4-hydroxyglucobrassicin levels, and plasma 4-hydroxyglucobrassicin levels were positively correlated with ADG (P < 0.05). Conclusions: This study's findings unveil that rumen and hindgut microbes play distinctive roles in regulating the preweaning ADG of Holstein heifer calves. Additionally, the successful isolation of A. fermentans P41 not only validated our findings but also provided a valuable strain resource for modulating rumen microbes in preweaning calves. 22vFWxsoqrtVsfZ2TEiGhk Video Abstract [ABSTRACT FROM AUTHOR]

Acute coronary syndrome (ACS) is a predominant cause of mortality, and the prompt and precise identification of this condition is crucial to minimize its impact. Recent research indicates that gut microbiota is associated with the onset, progression, and treatment of ACS. To investigate its role, we sequenced the gut microbiota of 38 ACS patients before and after percutaneous coronary intervention and statin therapy at three time points, examining differential species and metabolic pathways. We observed a decrease in the abundance of Parabacteroides, Escherichia, and Blautia in patients after treatment and an increase in the abundance of Gemalla, Klebsiella variicola, Klebsiella pneumoniae, and others. Two pathways related to sugar degradation were more abundant in patients before treatment, possibly correlated with disorders of sugar metabolism and risk factors, such as hyperglycemia, insulin resistance, and insufficient insulin secretion. Additionally, seven pathways related to the biosynthesis of vitamin K2 and its homolog were reduced after treatment, suggesting that ACS patients may gradually recover after therapy. The gut microbiota of patients treated with different statins exhibited notable differences after treatment. Rosuvastatin appeared to promote the growth of anti-inflammatory bacteria while reducing pro-inflammatory bacteria, whereas atorvastatin may have mixed effects on pro-inflammatory and anti-inflammatory bacteria while increasing the abundance of Bacteroides. Our research will provide valuable insights and enhance comprehension of ACS, leading to better patient diagnosis and therapy. [ABSTRACT FROM AUTHOR]

Background: Using next-generation sequencing technologies, scientists can sequence complex microbial communities directly from the environment. Significant insights into the structure, diversity, and ecology of microbial communities have resulted from the study of metagenomics. The assembly of reads into longer contigs, which are then binned into groups of contigs that correspond to different species in the metagenomic sample, is a crucial step in the analysis of metagenomics. It is necessary to organize these contigs into operational taxonomic units (OTUs) for further taxonomic profiling and functional analysis. For binning, which is synonymous with the clustering of OTUs, the tetra-nucleotide frequency (TNF) is typically utilized as a compositional feature for each OTU. Results: In this paper, we present AFIT, a new l-mer statistic vector for each contig, and AFITBin, a novel method for metagenomic binning based on AFIT and a matrix factorization method. To evaluate the performance of the AFIT vector, the t-SNE algorithm is used to compare species clustering based on AFIT and TNF information. In addition, the efficacy of AFITBin is demonstrated on both simulated and real datasets in comparison to state-of-the-art binning methods such as MetaBAT 2, MaxBin 2.0, CONCOT, MetaCon, SolidBin, BusyBee Web, and MetaBinner. To further analyze the performance of the purposed AFIT vector, we compare the barcodes of the AFIT vector and the TNF vector. Conclusion: The results demonstrate that AFITBin shows superior performance in taxonomic identification compared to existing methods, leveraging the AFIT vector for improved results in metagenomic binning. This approach holds promise for advancing the analysis of metagenomic data, providing more reliable insights into microbial community composition and function. Availability: A python package is available at: https://github.com/SayehSobhani/AFITBin. [ABSTRACT FROM AUTHOR]

The knowledge of the different population‐level processes operating within a species, and the genetic variability of the individual prokaryotic genomes, is key to understanding the adaptability of microbial populations. Here, we characterized the flexible genome of ammonia‐oxidizing archaeal (AOA) populations using a metagenomic recruitment approach and long‐read (PacBio HiFi) metagenomic sequencing. In the lower photic zone of the western Mediterranean Sea (75 m deep), the genomes Nitrosopelagicus brevis CN25 and Nitrosopumilus catalinensis SPOT1 had the highest recruitment values among available complete AOA genomes. They were used to analyse the diversity of flexible genes (variable from strain to strain) by examining the long‐reads located within the flexible genomic islands (fGIs) identified by their under‐recruitment. Both AOA genomes had a large fGI involved in the glycosylation of exposed structures, highly variable, and rich in glycosyltransferases. N. brevis had two fGIs related to the transport of phosphorus and ammonium respectively. N. catalinensis had fGIs involved in phosphorus transportation and metal uptake. A fGI5 previously reported as 'unassigned function' in N. brevis could be associated with defense. These findings demonstrate that the microdiversity of marine microbe populations, including AOA, can be effectively characterized using an approach that incorporates third‐generation sequencing metagenomics. [ABSTRACT FROM AUTHOR]

Huanglongbing, also known as citrus greening, is currently the most devastating citrus disease with limited success in prevention and mitigation. A promising strategy for Huanglongbing control is the use of antimicrobials fused to a carrier protein (phloem protein of 16 kDa or PP16) that targets vascular tissues. This study investigated the effects of genetically modified citrus trees expressing Citrus sinensis PP16 (CsPP16) fused to human lysozyme and β-defensin-2 on the soil microbiome diversity using 16S amplicon analysis. The results indicated that there were no significant alterations in alpha diversity, beta diversity, phylogenetic diversity, differential abundance, or functional prediction between the antimicrobial phloem-overexpressing plants and the control group, suggesting minimal impact on microbial community structure. However, microbiota diversity analysis revealed distinct bacterial assemblages between the rhizosphere soil and root environments. This study helps to understand the ecological implications of crops expressing phloem-targeted antimicrobials for vascular disease management, with minimal impact on soil microbiota. [ABSTRACT FROM AUTHOR]

Simple Summary: Scale drop disease virus (SDDV) has been identified as a significant pathogen causing scale drop syndrome (SDS), leading to significant economic losses in Asian seabass production in Southeast Asia. This study utilized a metagenomic approach to investigate the bacterial and viral communities associated with SDS, with a particular focus on SDDV, and evaluated the potential of metagenomics for retrieving complete SDDV genomes. By characterizing the complete genomes of SDDV strains, we aimed to gain a deeper understanding of the virus. The insights gained from this study are expected to inform the development of comprehensive disease prevention and control strategies for SDDV, mitigating its impact on the aquaculture industry. Scale drop disease virus (SDDV), a double-stranded DNA virus in the family Iridoviridae, has been reported widely in southeast Asian countries as a causative agent of scale drop syndrome (SDS) in Asian seabass. SDS has resulted in high mortality and significant economic losses to the aquaculture industry. This study demonstrated the use of metagenomic methods to investigate bacterial and viral communities present in infected fish tissues and recover a complete genome of the causative agent named SDDV TH7_2019. Characterization of the TH7_2019 genome revealed a genome size of 131 kb with 134 putative ORFs encoding viral proteins potentially associated with host apoptosis manipulation. A comparative genome analysis showed a high degree of amino acid identity across SDDV strains, with variations in number of repeat sequences and mutations within core genes. Phylogenetic analyses indicate a close relationship among SDDV genomes. This research enhances our understanding of the genetic diversity and evolutionary relationship of SDDV, contributing valuable insights for further development of effective control strategies of SDDV. [ABSTRACT FROM AUTHOR]

Polychlorinated biphenyls (PCBs) are a class of synthetic organic compounds that are widely distributed in the environment and have significant adverse effects on humans as well as the ecosystem. Many microorganisms that can degrade PCBs have been reported, including monocultures of bacteria and fungi, as well as natural and artificial microbial consortia. Generally, anaerobic dechlorination can degrade highly chlorinated PCBs to reduce their toxicity, while aerobic oxidation degrades lowly chlorinated PCBs (four or fewer chlorine atoms) and realizes their complete mineralization into CO2 by disrupting the benzene ring structure. Due to the need for the metabolism of a wide range of PCB congeners in the environment, microbial consortia have become a research hotspot, and their species diversity facilitates metabolic cooperation, enabling them to undertake more complex tasks. In this review, we will discuss the metabolic mechanisms of PCB degradation by monocultures as well as microbial consortia, and focus on the recent progress in the development and optimization of PCB-degrading microbial consortia, the community composition analysis methods, the prevailing optimization strategies such as biostimulation, bioaugmentation, metagenomics, and the combination of other methods for a better remediation effect, which will provide theoretical and practical bases for the rational design, construction and further optimization of efficient microbial consortia for the high-efficiency degradation of PCBs. [ABSTRACT FROM AUTHOR]

Background: With the emergence of Oxford Nanopore technology, now the on-site sequencing of 16S rRNA from environments is available. Due to the error level and structure, the analysis of such data demands some database of reference sequences. However, many taxa from complex and diverse environments, have poor representation in publicly available databases. In this paper, we propose the METASEED pipeline for the reconstruction of full-length 16S sequences from such environments, in order to improve the reference for the subsequent use of on-site sequencing. Results: We show that combining high-precision short-read sequencing of both 16S and full metagenome from the same samples allow us to reconstruct high-quality 16S sequences from the more abundant taxa. A significant novelty is the carefully designed collection of metagenome reads that matches the 16S amplicons, based on a combination of uniqueness and abundance. Compared to alternative approaches this produces superior results. Conclusion: Our pipeline will facilitate numerous studies associated with various unknown microorganisms, thus allowing the comprehension of the diverse environments. The pipeline is a potential tool in generating a full length 16S rRNA gene database for any environment. [ABSTRACT FROM AUTHOR]

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

Background: The incidence of early-stage lung adenocarcinoma (ES-LUAD) is steadily increasing among non-smokers. Previous research has identified dysbiosis in the gut microbiota of patients with lung cancer. However, the local microbial profile of non-smokers with ES-LUAD remains largely unknown. In this study, we systematically characterized the local microbial community and its associated features to enable early intervention. Methods: A prospective collection of ES-LUAD samples (46 cases) and their corresponding normal tissues adjacent to the tumor (41 cases), along with normal lung tissue samples adjacent to pulmonary bullae in patients with spontaneous pneumothorax (42 cases), were subjected to ultra-deep metagenomic sequencing, host transcriptomic sequencing, and proteomic sequencing. The obtained omics data were subjected to both individual and integrated analysis using Spearman correlation coefficients. Results: We concurrently detected the presence of bacteria, fungi, and viruses in the lung tissues. The microbial profile of ES-LUAD exhibited similarities to NAT but demonstrated significant differences from the healthy controls (HCs), characterized by an overall reduction in species diversity. Patients with ES-LUAD exhibited local microbial dysbiosis, suggesting the potential pathogenicity of certain microbial species. Through multi-omics correlations, intricate local crosstalk between the host and local microbial communities was observed. Additionally, we identified a significant positive correlation (rho > 0.6) between Methyloversatilis discipulorum and GOLM1 at both the transcriptional and protein levels using multi-omics data. This correlated axis may be associated with prognosis. Finally, a diagnostic model composed of six bacterial markers successfully achieved precise differentiation between patients with ES-LUAD and HCs. Conclusions: Our study depicts the microbial spectrum in patients with ES-LUAD and provides evidence of alterations in lung microbiota and their interplay with the host, enhancing comprehension of the pathogenic mechanisms that underlie ES-LUAD. The specific model incorporating lung microbiota can serve as a potential diagnostic tool for distinguishing between ES-LUAD and HCs. [ABSTRACT FROM AUTHOR]

This review article offers a comprehensive overview of the current understanding of using metagenomic tools in food microbiome research. It covers the scientific foundation and practical application of genetic analysis techniques for microbial material from food, including bioinformatic analysis and data interpretation. The method discussed in the article for analyzing microorganisms in food without traditional culture methods is known as food metagenomics. This approach, along with other omics technologies such as nutrigenomics, proteomics, metabolomics, and transcriptomics, collectively forms the field of foodomics. Food metagenomics allows swift and thorough examination of bacteria and potential metabolic pathways by utilizing foodomic databases. Despite its established scientific basis and available bioinformatics resources, the research approach of food metagenomics outlined in the article is not yet widely implemented in industry. The authors believe that the integration of next-generation sequencing (NGS) with rapidly advancing digital technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data will facilitate the widespread adoption of this research strategy in microbial analysis for the food industry. This adoption is expected to enhance food safety and product quality in the near future. [ABSTRACT FROM AUTHOR]

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

Milk is a biological fluid with a dynamic composition of micronutrients and bioactive molecules that serves as a vital nutrient source for infants. Milk composition is affected by multiple factors, including genetics, geographical location, environmental conditions, lactation phase, and maternal nutrition, and plays a key role in dictating its microbiome. This study addresses a less-explored aspect, comparing the microbial communities in human breast milk with those in mature milk from species that are used for milk consumption. Since mature animal milk is used as a supplement for both the infant (formula) and the child/adolescent, our main aim was to identify shared microbial communities in colostrum and mature human milk. Using 16S rRNA metagenomic sequencing, we focused on characterizing the milk microbiota in the Northern Greek population by identifying shared microbial communities across samples and comparing the relative abundance of prevalent genera. We analyzed ten human milk samples (from five mothers), with five collected three days postpartum (colostrum) and five collected thirty to forty days postpartum (mature milk) from corresponding mothers. To perform an interspecies comparison of human milk microbiota, we analyzed five goat and five bovine milk samples from a local dairy industry, collected fifty to seventy days after birth. Alpha diversity analysis indicated moderate diversity and stability in bovine milk, high richness in goat milk, and constrained diversity in breast milk. Beta diversity analysis revealed significant distinctions among mammalian species, emphasizing both presence/absence and abundance-based clustering. Despite noticeable differences, shared microbial components underscore fundamental aspects across all mammalian species, highlighting the presence of a core microbiota predominantly comprising the Proteobacteria, Firmicutes, and Actinobacteriota phyla. At the genus level, Acinetobacter, Gemella, and Sphingobium exhibit significant higher abundance in human milk compared to bovine and goat milk, while Pseudomonas and Atopostipes are more prevalent in animal milk. Our comparative analysis revealed differences and commonalities in the microbial communities of various mammalian milks and unraveled the existence of a common fundamental milk core microbiome. We thus revealed both species-specific and conserved microbial communities in human, bovine, and goat milk. The existence of a common core microbiome with conserved differences between colostrum and mature human milk underscores fundamental similarities in the microbiota of milk across mammalian species, which could offer valuable implications for optimizing the nutritional quality and safety of dairy products as well as supplements for infant health. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to determine the sensitivity and specificity of metagenomic next-generation sequencing (mNGS) for detecting pathogens in spinal infections and to identify the differences in the diagnostic performance between mNGS and targeted next-generation sequencing (tNGS). Methods: A total of 76 consecutive patients with suspected spinal infections who underwent mNGS, culture, and histopathological examinations were retrospectively studied. The final diagnosis of the patient was determined by combining the clinical treatment results, pathological examinations, imaging changes and laboratory indicators. The sensitivity and specificity of mNGS and culture were determined. Results: The difference between the two detection rates was statistically significant (p < 0.001), with mNGS exhibiting a significantly higher detection rate (77.6% versus 18.4%). The average diagnosis time of mNGS was significantly shorter than that of bacterial culture (p < 0.001, 1.65 versus 3.07 days). The sensitivity and accuracy of mNGS were significantly higher than that of the culture group (p < 0.001, 82.3% versus 17.5%; 75% versus 27.6%), whereas the specificity of mNGS (42.9%) was lower than that of the culture group (p > 0.05, 42.9% versus 76.9%). The sensitivity, specificity, accuracy, and positive predictive value (PPV) of pus were higher than those of tissue samples for mNGS, whereas for culture, the sensitivity, specificity, accuracy, and PPV of tissue samples were higher than those of pus. tNGS demonstrated higher sensitivity and accuracy in diagnosing tuberculosis (TB) than mNGS (80% versus 50%; 87.5% versus 68.8%). Conclusion: mNGS for spinal infection demonstrated better diagnostic value in developing an antibiotic regimen earlier, and it is recommended to prioritize pus samples for testing through mNGS. Moreover, tNGS outperformed othermethods for diagnosing spinal TB and identifying antibiotic-resistance genes in drug-resistant TB. [ABSTRACT FROM AUTHOR]

Elucidating the impact of rhizosphere microbial communities in the Caragana intermedia forest on soil polyfunctionality can significantly enhance our understanding of the microbial mechanisms underpinning soil multi-functionality, which is crucial for sustainable land management. The rhizosphere soils under Caragana intermedia forests in different regions with variable precipitation gradients (MAP500 (precipitation ≥ 500 mm), MAP450 (400~500 mm), MAP300 (300~400 mm), MAP250 (200~300 mm)) were investigated in the research object. The interrelationships among soil properties, particularly the soil bacterial taxa and soil multi-functionality, were examined using metagenomic analysis, sequencing techniques, redundancy analysis, and partial least squares path modeling. The results show that (1) concurrent with escalating precipitation, Rhizosphere Soil Multi-functionality Index (SMI) exhibited a significant increase (p < 0.05); (2) the community structures of the Always Abundant Taxa (AAT), Always Rare Taxa (ART), Moderate Taxa (MT), Conditionally Abundant Taxa (CAT), Conditionally Rare group (CRT), and Conditionally Abundant Taxa (CRAT) varied significantly across precipitation gradients. Mean annual precipitation (MAP), soil moisture content (SMC), and pH were identified as the most critical environmental factors influencing the overall bacterial community and various taxa; (3) precipitation predominantly exerts indirect effects on AAT, MT, CAT, and CRAT by modulating soil moisture. Bacterial taxa that are conditionally rare or abundant in arid and semi-arid regions are the principal drivers of soil multi-functionality alterations within the rhizosphere of the Caragana intermedia forest. In the stewardship of Caragana intermedia plantations, microbial community composition can be optimized through the regulation of soil moisture and pH, as well as the strategic introduction of conditional microbial taxa, thereby enhancing the plantation's resilience to climate change. This research contributes to sustainable land use practices by providing insights into microbial management strategies that enhance soil health and ecosystem resilience. [ABSTRACT FROM AUTHOR]

The estuarine plastisphere, a novel ecological habitat in the Anthropocene, has garnered global concerns. Recent geochemical evidence has pointed out its potential role in influencing nitrogen biogeochemistry. However, the biogeochemical significance of the plastisphere and its mechanisms regulating nitrogen cycling remain elusive. Using 15N- and 13C-labelling coupled with metagenomics and metatranscriptomics, here we unveil that the plastisphere likely acts as an underappreciated nitrifying niche in estuarine ecosystems, exhibiting a 0.9 ~ 12-fold higher activity of bacteria-mediated nitrification compared to surrounding seawater and other biofilms (stone, wood and glass biofilms). The shift of active nitrifiers from O2-sensitive nitrifiers in the seawater to nitrifiers with versatile metabolisms in the plastisphere, combined with the potential interspecific cooperation of nitrifying substrate exchange observed among the plastisphere nitrifiers, collectively results in the unique nitrifying niche. Our findings highlight the plastisphere as an emerging nitrifying niche in estuarine environment, and deepen the mechanistic understanding of its contribution to marine biogeochemistry. The biogeochemical roles of the plastisphere regulating N cycling are elusive. This study reveals the plastisphere as an emerging nitrifying niche, featured by distinct shifts in nitrifiers and potential substrate exchanges compared to seawater. [ABSTRACT FROM AUTHOR]

Background: Metagenomic next-generation sequencing (mNGS) excels in diagnosis of infection pathogens. We aimed to evaluate the performance of mNGS for the diagnosis of Pneumocystis jirovecii pneumonia (PJP) in non-HIV infected children. Methods: Totally 36 PJP children and 61 non-PJP children admitted to the pediatric intensive care unit from March 2018 to December 2021 were retrospectively enrolled. Clinical features of PJP children were summarized. 1,3-β-D glucan (BDG) test and bronchoalveolar lavage fluid (BALF) mNGS were used for evaluation of PJP diagnostic performance. Antimicrobial management modifications for PJP children after the mNGS results were also reviewed. Results: Pneumocystis jirovecii was detected in all PJP children by mNGS (36/36), and the sensitivity of mNGS was 100% (95% confidence interval [CI]: 90.26–100%). The sensitivity of BDG was 57.58% (95% CI: 39.22–74.52%). Of the 26 (72.2%) PJP patients with mixed infection, twenty-four (66.7%) were detected by BALF-mNGS. Thirteen patients (36.1%) had their antimicrobial management adjusted according to the mNGS results. Thirty-six PJP children included 17 (47.2%) primary immunodeficiency and 19 (52.8%) secondary immunodeficiency, of whom 19 (52.8%) survived and 17 (47.2%) died. Compared to survival subgroup, non-survival subgroup had a higher rate of primary immunodeficiency (64.7% vs. 31.6%, P = 0.047), younger age (7 months vs. 39 months, P = 0.011), lower body weight (8.0 kg vs. 12.0 kg, P = 0.022), and lower T lymphocyte counts. Conclusions: The mortality rate of PJP in immunosuppressed children without HIV infection is high and early diagnosis is challenging. BALF-mNGS could help identify PJP and guide clinical management. [ABSTRACT FROM AUTHOR]

Introduction: Alveolar echinococcosis (AE), caused by the larval forms of Echinococcus multilocularis, is a zoonotic disease affecting the liver, lungs, lymph nodes, kidneys, brain, bones, thyroid, and other organs. Diagnosing AE in a non-endemic area is usually challenging. With the rapid development and increasing application of sequencing techniques in recent years, metagenomic next-generation sequencing (mNGS) has become a powerful tool for diagnosing rare infectious diseases. Case Presentation: A 45-year-old woman was admitted to the hospital for the presence of pulmonary shadows for more than 3 months. The lung computed tomography (CT) at a local hospital revealed scattered solid and quasi-circular nodules in the left upper lobe, left lower lobe, right middle lobe, and right lower lobe. The largest nodule was located in the dorsal part of the right lung, measuring 2.0 × 1.7 × 1.5 cm. Moreover, abdominal CT revealed one space-occupying lesion each in the left and right lobes. The pathological analysis of the lung biopsy specimen revealed infiltration of lymphocytes, plasma cells, and eosinophils in the alveolar wall and interstitial area. No pathogenic bacteria were observed in the sputum smear and culture tests. There were no parasite eggs in the stool. The mNGS of the lung puncture tissue revealed 6156 sequence reads matching E. multilocularis; thus, the condition was diagnosed as AE. Albendazole 400 mg was administered twice daily, and the patient was stable during follow-up. Conclusion: This case emphasizes the role of mNGS in diagnosing AE. As a novel, sensitive, and accurate diagnostic method, mNGS could be an attractive approach for facilitating early diagnosis and prompt treatment of infectious diseases, especially when the infection was caused by rare pathogens. [ABSTRACT FROM AUTHOR]

Metagenomic sequencing has provided great advantages in the characterisation of microbiomes, but currently available analysis tools lack the ability to combine subspecies-level taxonomic resolution and accurate abundance estimation with functional profiling of assembled genomes. To define the microbiome and its associations with human health, improved tools are needed to enable comprehensive understanding of the microbial composition and elucidation of the phylogenetic and functional relationships between the microbes. Here, we present MAGinator, a freely available tool, tailored for profiling of shotgun metagenomics datasets. MAGinator provides de novo identification of subspecies-level microbes and accurate abundance estimates of metagenome-assembled genomes (MAGs). MAGinator utilises the information from both gene- and contig-based methods yielding insight into both taxonomic profiles and the origin of genes and genetic content, used for inference of functional content of each sample by host organism. Additionally, MAGinator facilitates the reconstruction of phylogenetic relationships between the MAGs, providing a framework to identify clade-level differences. Metagenomic sequencing enhances microbiome analysis and understanding of microbial relationships but lacks tools for subspecies-level resolution. Here, authors present MAGinator, a tool that enables accurate profiling of microbiomes with strain-level information. [ABSTRACT FROM AUTHOR]

Phosphorous (P) is essential for mediating plant and microbial growth and thus could impact carbon (C) cycle in permafrost ecosystem. However, little is known about soil P availability and its biological acquisition strategies in permafrost environment. Based on a large‐scale survey along a ~1000 km transect, combining with shotgun metagenomics, we provided the first attempt to explore soil microbial P acquisition strategies across the Tibetan alpine permafrost region. Our results showed the widespread existence of microbial functional genes associated with inorganic P solubilization, organic P mineralization and transportation, reflecting divergent microbial P acquisition strategies in permafrost regions. Moreover, the higher gene abundance related to solubilization and mineralization as well as an increased ration of metagenomic assembled genomes (MAGs) carrying these genes were detected in the active layer, while the greater abundance of low‐affinity transporter gene (pit) and proportions of MAGs harbouring pit gene were observed in permafrost deposits, illustrating a stronger potential for P activation in active layer but an enhanced P transportation potential in permafrost deposits. Our results highlight multiple P‐related acquisition strategies and their differences among various soil layers should be considered simultaneously to improve model prediction for the responses of biogeochemical cycles in permafrost ecosystems to climate change. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Background: Despite rapid advances in genomic-resolved metagenomics and remarkable explosion of metagenome-assembled genomes (MAGs), the function of uncultivated anaerobic lineages and their interactions in carbon mineralization remain largely uncertain, which has profound implications in biotechnology and biogeochemistry. Results: In this study, we combined long-read sequencing and metatranscriptomics-guided metabolic reconstruction to provide a genome-wide perspective of carbon mineralization flow from polymers to methane in an anaerobic bioreactor. Our results showed that incorporating long reads resulted in a substantial improvement in the quality of metagenomic assemblies, enabling the effective recovery of 132 high-quality genomes meeting stringent criteria of minimum information about a metagenome-assembled genome (MIMAG). In addition, hybrid assembly obtained 51% more prokaryotic genes in comparison to the short-read-only assembly. Metatranscriptomics-guided metabolic reconstruction unveiled the remarkable metabolic flexibility of several novel Bacteroidales-affiliated bacteria and populations from Mesotoga sp. in scavenging amino acids and sugars. In addition to recovering two circular genomes of previously known but fragmented syntrophic bacteria, two newly identified bacteria within Syntrophales were found to be highly engaged in fatty acid oxidation through syntrophic relationships with dominant methanogens Methanoregulaceae bin.74 and Methanothrix sp. bin.206. The activity of bin.206 preferring acetate as substrate exceeded that of bin.74 with increasing loading, reinforcing the substrate determinantal role. Conclusion: Overall, our study uncovered some key active anaerobic lineages and their metabolic functions in this complex anaerobic ecosystem, offering a framework for understanding carbon transformations in anaerobic digestion. These findings advance the understanding of metabolic activities and trophic interactions between anaerobic guilds, providing foundational insights into carbon flux within both engineered and natural ecosystems. 38JKnB3DNsQtzzVWuKzfx4 Video Abstract [ABSTRACT FROM AUTHOR]

Objective •Metagenomic sequencing (mNGS) is a promising technique for pathogen detection. However, the use of mNGS in pediatric lung infections is still rarely reported. Methods • A total of 59 cases were included between January 2019 and December 2021. To compare the performance of mNGS and routine detection in diagnosing pulmonary infection and identifying pathogenic bacteria. Results • 59 children (33.90%) were infected with Mycoplasma pneumoniae, 15 were infected with adenovirus type 7 (25.42%), 11 were infected with Streptococcus pneumoniae (18.64%), 6 were infected with Staphylococcus aureus (10.17%), 5 were infected with Klebsiella pneumoniae, Acinetobacter baumannii, pertussis, and oral streptococcus (8.47%), 3 were infected with Haemophilus influenzae (5.08%), and 3 were infected with Pseudomonas aeruginosa (5.08%). Among 59 patients, 41 were co-infected with multiple pathogens and 18 were infected with independent pathogens. Mycoplasma pneumoniae infection was most common in 6 out of 18 independent pathogen patients (33%). Among them were 3 cases of type 7 adenovirus, 53 cases of human herpesvirus (16.7%), and 2 cases of pertussis bacillus (11.1%). One case (5.6%) was infected with Streptococcus pneumoniae, Proteus albicans, Mycobacterium tuberculosis, Staphylococcus aureus, and Klebsiella pneumoniae. In cases where routine testing results are negative, mNGS improves the diagnostic efficiency of mixed pulmonary infections. 17 cases (17/59=28.81%) were diagnosed as single infection through routine testing, and the mNGS results of 4 cases were consistent with routine testing, all of which were Mycoplasma pneumoniae infections. Three cases were tested for partial mNGS matching, of which one case tested positive for Mycoplasma pneumoniae antibody and tested positive for Mycoplasma pneumoniae infection and human infection γ Herpes virus type 4, one case tested positive for antibodies and tested for infection with Mycoplasma pneumoniae and Streptococcus pneumoniae. The routine examination results of the remaining 11 patients were inconsistent with the mNGS examination results. Two patients tested positive for Mycoplasma antibodies. Patient 17 presented with mNGS infection of Haemophilus, Neisseria, and adenovirus type 7, while another patient 18 presented with herpes virus type 5 infection. Conclusion • mNGS is a promising technique for detecting co-pathogens in mixed pediatric lung infections, with potential benefits in terms of speed and sensitivity. [ABSTRACT FROM AUTHOR]

The intricate consortium of microorganisms in the human gut plays a crucial role in different physiological functions. The complex known‐unknown elements of the gut microbiome are perplexing and the absence of standardized procedures for collecting and preserving samples has hindered continuous research in comprehending it. The technological bias produced because of lack of standard protocols has affected the reproducibility of results. The complex nature of diseases like colorectal cancer, gastric cancer, hepatocellular carcinoma and breast cancer require a thorough understanding of its etiology for an efficient and timely diagnosis. The designated protocols for collection and preservation of stool specimens have great variance, hence generate inconsistencies in OMICS studies. Due to the complications associated to the nature of sample, it is important to preserve the sample to be studied later in a laboratory or to be used in the future research purpose. Stool preservation is gaining importance due to the increased use of treatment options like fecal microbiota transplantation to cure conditions like recurrent Clostridium difficile infections and for OMICS studies including metagenomics, metabolomics and culturomics. This review provides an insight into the importance of omics studies for the identification and development of novel biomarkers for quick and noninvasive diagnosis of various diseases. Significance statement: Fecal specimen is a slightly intrusive test for disease diagnosis.Biomarker analysis for diseases in stool specimen detects disease at early stage.Stool specimen is a determinant of gut health. [ABSTRACT FROM AUTHOR]

Summary Shotgun metagenomics allows for direct analysis of microbial community genetics, but scalable computational methods for the recovery of bacterial strain genomes from microbiomes remains a key challenge. We introduce Floria, a novel method designed for rapid and accurate recovery of strain haplotypes from short and long-read metagenome sequencing data, based on minimum error correction (MEC) read clustering and a strain-preserving network flow model. Floria can function as a standalone haplotyping method, outputting alleles and reads that co-occur on the same strain, as well as an end-to-end read-to-assembly pipeline (Floria-PL) for strain-level assembly. Benchmarking evaluations on synthetic metagenomes show that Floria is   >   3 × faster and recovers 21% more strain content than base-level assembly methods (Strainberry) while being over an order of magnitude faster when only phasing is required. Applying Floria to a set of 109 deeply sequenced nanopore metagenomes took <20 min on average per sample and identified several species that have consistent strain heterogeneity. Applying Floria's short-read haplotyping to a longitudinal gut metagenomics dataset revealed a dynamic multi-strain Anaerostipes hadrus community with frequent strain loss and emergence events over 636 days. With Floria, accurate haplotyping of metagenomic datasets takes mere minutes on standard workstations, paving the way for extensive strain-level metagenomic analyses. Availability and implementation Floria is available at https://github.com/bluenote-1577/floria , and the Floria-PL pipeline is available at https://github.com/jsgounot/Floria%5fanalysis%5fworkflow along with code for reproducing the benchmarks. [ABSTRACT FROM AUTHOR]

Premise: The genomes of polyploid plants archive the evolutionary events leading to their present forms. However, plant polyploid genomes present numerous hurdles to the genome comparison algorithms for classification of polyploid types and exploring genome dynamics. Methods: Here, the problem of intra‐ and inter‐genome comparison for examining polyploid genomes is reframed as a metagenomic problem, enabling the use of the rapid and scalable MinHashing approach. To determine how types of polyploidy are described by this metagenomic approach, plant genomes were examined from across the polyploid spectrum for both k‐mer composition and frequency with a range of k‐mer sizes. In this approach, no subgenome‐specific k‐mers are identified; rather, whole‐chromosome k‐mer subspaces were utilized. Results: Given chromosome‐scale genome assemblies with sufficient subgenome‐specific repetitive element content, literature‐verified subgenomic and genomic evolutionary relationships were revealed, including distinguishing auto‐ from allopolyploidy and putative progenitor genome assignment. The sequences responsible were the rapidly evolving landscape of transposable elements. An investigation into the MinHashing parameters revealed that the downsampled k‐mer space (genomic signatures) produced excellent approximations of sequence similarity. Furthermore, the clustering approach used for comparison of the genomic signatures is scrutinized to ensure applicability of the metagenomics‐based method. Discussion: The easily implementable and highly computationally efficient MinHashing‐based sequence comparison strategy enables comparative subgenomics and genomics for large and complex polyploid plant genomes. Such comparisons provide evidence for polyploidy‐type subgenomic assignments. In cases where subgenome‐specific repeat signal may not be adequate given a chromosomes' global k‐mer profile, alternative methods that are more specific but more computationally complex outperform this approach. [ABSTRACT FROM AUTHOR]

With the increasing prevalence of age-related chronic diseases burdening healthcare systems, there is a pressing need for innovative management strategies. Our study focuses on the gut microbiota, essential for metabolic, nutritional, and immune functions, which undergoes significant changes with aging. These changes can impair intestinal function, leading to altered microbial diversity and composition that potentially influence health outcomes and disease progression. Using advanced metagenomic sequencing, we explore the potential of personalized probiotic supplements in 297 older adults by analyzing their gut microbiota. We identified distinctive Lactobacillus and Bifidobacterium signatures in the gut microbiota of older adults, revealing probiotic patterns associated with various population characteristics, microbial compositions, cognitive functions, and neuroimaging results. These insights suggest that tailored probiotic supplements, designed to match individual probiotic profile, could offer an innovative method for addressing age-related diseases and functional declines. Our findings enhance the existing evidence base for probiotic use among older adults, highlighting the opportunity to create more targeted and effective probiotic strategies. However, additional research is required to validate our results and further assess the impact of precision probiotics on aging populations. Future studies should employ longitudinal designs and larger cohorts to conclusively demonstrate the benefits of tailored probiotic treatments. [ABSTRACT FROM AUTHOR]

Plasmids are extrachromosomal DNA found in microorganisms. They often carry beneficial genes that help bacteria adapt to harsh conditions. Plasmids are also important tools in genetic engineering, gene therapy, and drug production. However, it can be difficult to identify plasmid sequences from chromosomal sequences in genomic and metagenomic data. Here, we have developed a new tool called PlasmidHunter, which uses machine learning to predict plasmid sequences based on gene content profile. PlasmidHunter can achieve high accuracies (up to 97.6%) and high speeds in benchmark tests including both simulated contigs and real metagenomic plasmidome data, outperforming other existing tools. [ABSTRACT FROM AUTHOR]

Profile hidden Markov models (pHMMs) are able to achieve high sensitivity in remote homology search, making them popular choices for detecting novel or highly diverged viruses in metagenomic data. However, many existing pHMM databases have different design focuses, making it difficult for users to decide the proper one to use. In this review, we provide a thorough evaluation and comparison for multiple commonly used profile HMM databases for viral sequence discovery in metagenomic data. We characterized the databases by comparing their sizes, their taxonomic coverage, and the properties of their models using quantitative metrics. Subsequently, we assessed their performance in virus identification across multiple application scenarios, utilizing both simulated and real metagenomic data. We aim to offer researchers a thorough and critical assessment of the strengths and limitations of different databases. Furthermore, based on the experimental results obtained from the simulated and real metagenomic data, we provided practical suggestions for users to optimize their use of pHMM databases, thus enhancing the quality and reliability of their findings in the field of viral metagenomics. [ABSTRACT FROM AUTHOR]

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

In Cameroon, Aedes mosquitoes transmit various arboviruses, posing significant health risks. We aimed to characterize the Aedes virome in southwestern Cameroon and identify potential core viruses which might be associated with vector competence. A total of 398 Aedes mosquitoes were collected from four locations (Bafoussam, Buea, Edea, and Yaounde). Aedes albopictus dominated all sites except for Bafoussam, where Aedes africanus prevailed. Metagenomic analyses of the mosquitoes grouped per species into 54 pools revealed notable differences in the eukaryotic viromes between Ae. africanus and Ae. albopictus, with the former exhibiting greater richness and diversity. Thirty-seven eukaryotic virus species from 16 families were identified, including six novel viruses with near complete genome sequences. Seven viruses were further quantified in individual mosquitoes via qRT-PCR. Although none of them could be identified as core viruses, Guangzhou sobemo-like virus and Bafoussam mosquito solemovirus, were highly prevalent regionally in Ae. albopictus and Ae. africanus, respectively. This study highlights the diverse eukaryotic virome of Aedes species in southwestern Cameroon. Despite their shared genus, Aedes species exhibit limited viral sharing, with varying viral abundance and prevalence across locations. Ae. africanus, an understudied vector, harbors a rich and diverse virome, suggesting potential implications for arbovirus vector competence. [ABSTRACT FROM AUTHOR]

Biting midges (Culicoides) are vectors of many pathogens of medical and veterinary importance, but their viromes are poorly characterized compared to certain other hematophagous arthropods, e.g., mosquitoes and ticks. The goal of this study was to use metagenomics to identify viruses in Culicoides from Mexico. A total of 457 adult midges were collected in Chihuahua, northern Mexico, in 2020 and 2021, and all were identified as female Culicoides reevesi. The midges were sorted into five pools and homogenized. An aliquot of each homogenate was subjected to polyethylene glycol precipitation to enrich for virions, then total RNA was extracted and analyzed by unbiased high-throughput sequencing. We identified six novel viruses that are characteristic of viruses from five families (Nodaviridae, Partitiviridae, Solemoviridae, Tombusviridae, and Totiviridae) and one novel virus that is too divergent from all classified viruses to be assigned to an established family. The newly discovered viruses are phylogenetically distinct from their closest known relatives, and their minimal infection rates in female C. reevesi range from 0.22 to 1.09. No previously known viruses were detected, presumably because viral metagenomics had never before been used to study Culicoides from the Western Hemisphere. To conclude, we discovered multiple novel viruses in C. reevesi from Mexico, expanding our knowledge of arthropod viral diversity and evolution. [ABSTRACT FROM AUTHOR]

The use of natural milk culture (NMC) represents a key factor in Protected Designation of Origin (PDO) Montasio cheese, contributing to its distinctive sensory profile. The complex microbial ecosystem of NMC is the result of heat treatment and incubation conditions, which can vary considerably among different production plants. In this study, the microbiota of NMC collected from 10 PDO Montasio cheese dairies was investigated by employing colony counts and metagenomic analysis. Furthermore, residual sugars, organic acids, and volatile profiles were quantitatively investigated. Results showed that Streptococcus thermophilus was the dominant species in all NMC, and a subdominant population made of other streptococci and Ligilactobacillus salivarius was also present. The incubation temperature appeared to be the main driver of biodiversity in NMC. Metagenomics allowed us to evidence the presence of minor species involving safety (e.g., Staphylococcus aureus) as well as possible functional aspects (Next Generation Probiotics). Statistical analysis based on residual sugars, organic acids, and volatiles' content allowed to correlate the presence of specific microbial groups with metabolites of great technological and sensory relevance, which can contribute to giving value to the artisanal production procedures of NMC and clarify their role in the creation of the characteristics of PDO Montasio cheese. [ABSTRACT FROM AUTHOR]

Four dairy foods processing by-products (acid whey permeate [AWP], buttermilk [BM], sweet whey permeate [SWP], and sweet whey permeate with added milk fat globule ingredient [SWP+MFGM]) were fermented for 4 wk and compared with traditional kefir milks for production of novel kefir-like dairy products. Sweet whey permeates and SWP supplemented with 1.5% milk fat globule membrane (MFGM) proved to be the most viable by-products for kefir grain fermentation, exhibiting diverse abundance of traditional kefir microorganisms and positive indicators of bioactive properties. Grain viability was assessed with shotgun metagenomics, texture profile analysis, live cell counts, and scanning electron microscopy. Assessed bioactivities of the kefir-like products included antibacterial, antioxidant, potential anticancerogenic properties, and membrane barrier effects on human colorectal adenocarcinoma Caco-2 cells. All kefir grains were most abundant in Lactobacillus kefiranofaciens when analyzed with shotgun metagenomics. When analyzed with live cell counts on selective media, AWP kefir-like product had no countable Lactococcus spp., indicating suboptimal conditions for kefir grain microbiota survival and application for fermented dairy starter culture bacterium. Live cell counts were affirmed with kefir grain surface scanning electron microscopy images. The SWP treatment had the most adhesive kefir grain surface, and SWP+MFGM had the largest exopolysaccharide yield from grain extraction. All kefir and kefir-like products were able to achieve a 6-log reduction against Listeria innocua and Escherichia coli. Traditional milk kefirs had the highest antioxidant capacity for 2,2-diphenyl-1-picrylhydrazyl (DPPH) and the 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid; ABTS) assay. The AWP formulation had a significantly higher DPPH antioxidant activity compared with the other kefir and kefir-like products, and SWP had the lowest Trolox equivalence concentration in the ABTS assay. Sweet whey and supplemented milk fat sweet whey had upregulation of Cldn-1 and Ocln-1 gene expression, which correspond with a significant increase in transepithelial electrical resistance. [ABSTRACT FROM AUTHOR]

In the field of metagenomic research, the choice of DNA extraction methods plays a pivotal yet often underestimated role in shaping the reliability and interpretability of microbial community data. This study delves into the impact of five commercially available DNA extraction kits on the analysis of bovine fecal microbiota. Recognizing the importance of accurate DNA extraction in elucidating microbial community dynamics, we systematically assessed DNA yield, quality, and microbial composition across these kits using 16S rRNA gene sequencing. Notably, the FastDNA spin soil kit yielded the highest DNA concentration, while significant variations in quality were observed across kits. Furthermore, differential abundance analysis revealed kit-specific biases that impacted taxa representation. Microbial richness and diversity were significantly influenced by the choice of extraction kit, with QIAamp DNA stool minikit, QIAamp Power Pro, and DNeasy PowerSoil outperforming the Stool DNA Kit. Principal-coordinate analysis revealed distinct clustering based on DNA isolation procedures, particularly highlighting the unique microbial community composition derived from the Stool DNA Kit. This study also addressed practical implications, demonstrating how kit selection influences the concentration of Gram-positive and Gram-negative bacterial taxa in samples. This research highlights the need for consideration of DNA extraction kits in metagenomic studies, offering valuable insights for researchers striving to advance the precision and depth of microbiota analyses in ruminants. [ABSTRACT FROM AUTHOR]

The dynamics of the physiological adaptability of plants and the rhizosphere soil environment after waterlogging remain unclear. Here we investigated the mechanisms regulating plant condition and shaping of the rhizosphere microbiome in a pot experiment. In the experiment, we added melatonin to waterlogged plants, which promoted waterlogging relief. The treatment significantly enhanced photosynthesis and the antioxidant capacity of apple plants, and significantly promoted nitrogen (N) utilization efficiency by upregulating genes related to N transport and metabolism. Multiperiod soil microbiome analysis showed the dynamic effects of melatonin on the diversity of the microbial community during waterlogging recovery. Random forest and linear regression analyses were used to screen for potential beneficial bacteria (e.g., Azoarcus, Pseudomonas and Nocardioides) specifically regulated by melatonin and revealed a positive correlation with soil nutrient levels and plant growth. Furthermore, metagenomic analyses revealed the regulatory effects of melatonin on genes involved in N cycling in soil. Melatonin positively contributed to the accumulation of plant dry weight by upregulating the expression of nifD and nifK (N fixation). In summary, melatonin positively regulates physiological functions in plants and the structure and function of the microbial community; it promoted the recovery of apple plants after waterlogging stress. Summary Statement: The application of melatonin to waterlogged plants significantly enhanced photosynthesis and antioxidant capacity, promoted nitrogen utilization efficiency and regulated the diversity and function of the rhizosphere microbial community, ultimately facilitating the recovery of apple plants after waterlogging stress. [ABSTRACT FROM AUTHOR]

Aims This study aimed to compare the effects of linear and branched fructooligosaccharides (FOS) extracted from chicory and grass (Lolium perenne), respectively on human microbiota composition, diversity, and metabolism. Methods and results To test the effects of linear and branched FOS on human microbiota we used the artificial in vitro human colon model (TIM-2). Microbiota composition and diversity were assessed by V3–V4 16S rRNA metagenomic sequencing, followed by differential taxa abundance and alpha/beta diversity analyses. SCFA/BCFA production was evaluated by gas chromatography–mass spectrometry. As a result, branched FOS had the most beneficial effects on microbial diversity and metabolite production. Also, branched FOS significantly increased the abundance of commensal bacteria associated with maintaining healthy gut functions and controlling inflammation, such as Butyricicoccus, Erysipelotrichaceae, Phascolarctobacterium , and Sutterella. Linear FOS also significantly increased the abundance of some other commensal gut bacteria (Anaerobutyricum, Lachnospiraceae, Faecalibacterium), but there were no differences in diversity metrics compared to the control. Conclusions The study revealed that branched FOS had the most beneficial effects compared to the linear FOS in vitro , concerning microbiota modulation, and metabolite production, making this a good candidate for further studies in food biotechnology. [ABSTRACT FROM AUTHOR]

Biliary dysbiosis is associated with gallbladder cancer (GBC). We aimed to look for biliary bacteria specifically detected in GBC patients. We used 16S rRNA-based metagenomic analysis to elucidate biliary microbiota in 30 GBC and 30 gallstones-associated chronic cholecystitis patients. Relative abundance of five genera, Streptococcus, Enterococcus, Halomonas, Escherichia and Caulobacter was significantly associated with GBC. Of 15-species, 7 were detected significantly higher in GBC, Streptococcus anginosus, Streptococcus constellatus, Streptococcus intermedius, Actinomyces bowdenii, Actinomyces israelii, Actinomyces gerencseriae, and Escherichia fergusonii were biosafety level-2 infectious bacteria; other 8 species were biosafety level-1 bacteria. These bacterial species may be involved in pathogenesis of GBC. [ABSTRACT FROM AUTHOR]

Purpose: Metagenomic next-generation sequencing (mNGS) has been widely used in the diagnosis of infectious diseases. However, studies on Talaromyces marneffei detection using mNGS remain scarce. Therefore, this study aimed to explore the diagnostic performance of mNGS in T. marneffei. Methods: Between March 2021 and June 2023, patients who were discharged with a final diagnosis of talaromycosis, or confirmed T. marneffei infection by mNGS, culture or pathological examination were included in the study. Culture and mNGS were performed simultaneously for all patients. Clinical data were retrieved for analysis. Results: A total of 78 patients were enrolled, with 40 in the talaromycosis group and 38 in the suspected-talaromycosis group. In the talaromycosis group, mNGS showed a higher positivity rate(40/40, 100.0%) compared to culture(34/40, 85.0%)(P = 0.111). All patients in the suspected-talaromycosis group tested negative via culture, while mNGS yielded positive results. The T. marneffei reads in the talaromycosis group were significantly higher than in the suspected-talaromycosis group (4399 vs. 28, P < 0.001). In the suspected-talaromycosis group, of the four patients with low reads who did not receive antifungal therapy, one died and one lung lesion progressed; most patients(31/34, 91.2%) recovered after receiving appropriate antifungal therapy. Conclusion: mNGS proves to be a rapid and highly sensitive method for detecting T. marneffei. Higher reads of T. marneffei correspond to a higher likelihood of infection. However, cases with low reads necessitate a comprehensive approach, integrating clinical manifestations, laboratory tests, and imaging examinations to confirm T. marneffei infection. [ABSTRACT FROM AUTHOR]

For most animals, the microbiome is key for nutrition and pathogen defence, and is often shaped by diet. Corbiculate bees, including honey bees, bumble bees, and stingless bees, share a core microbiome that has been shaped, at least in part, by the challenges associated with pollen digestion. However, three species of stingless bees deviate from the general rule of bees obtaining their protein exclusively from pollen (obligate pollinivores) and instead consume carrion as their sole protein source (obligate necrophages) or consume both pollen and carrion (facultative necrophages). These three life histories can provide missing insights into microbiome evolution associated with extreme dietary transitions. Here, we investigate, via shotgun metagenomics, the functionality of the microbiome across three bee diet types: obligate pollinivory, obligate necrophagy, and facultative necrophagy. We find distinct differences in microbiome composition and gene functional profiles between the diet types. Obligate necrophages and pollinivores have more specialized microbes, whereas facultative necrophages have a diversity of environmental microbes associated with several dietary niches. Our study suggests that necrophagous bee microbiomes may have evolved to overcome cellular stress and microbial competition associated with carrion. We hypothesize that the microbiome evolved social phenotypes, such as biofilms, that protect the bees from opportunistic pathogens present on carcasses, allowing them to overcome novel nutritional challenges. Whether specific microbes enabled diet shifts or diet shifts occurred first and microbial evolution followed requires further research to disentangle. Nonetheless, we find that necrophagous microbiomes, vertebrate and invertebrate alike, have functional commonalities regardless of their taxonomy. [ABSTRACT FROM AUTHOR]

Microbial metabolites can be viewed as the cytokines of the microbiome, transmitting information about the microbial and metabolic environment of the gut to orchestrate and modulate local and systemic immune responses. Still, many immunology studies focus solely on the taxonomy and community structure of the gut microbiota rather than its functions. Early sequencing‐based microbiota profiling approaches relied on PCR amplification of small regions of bacterial and fungal genomes to facilitate identification of the microbes present. However, recent microbiome analysis methods, particularly shotgun metagenomic sequencing, now enable culture‐independent profiling of microbiome functions and metabolites in addition to taxonomic characterization. In this review, we showcase recent advances in functional metagenomics methods and applications and discuss the current limitations and potential avenues for future development. Importantly, we highlight a few examples of key areas of opportunity in immunology research where integrating functional metagenomic analyses of the microbiome can substantially enhance a mechanistic understanding of microbiome–immune interactions and their contributions to health and disease states. [ABSTRACT FROM AUTHOR]

BACKGROUND: Campylobacter jejuni (C. jejuni), a widely distributed global foodborne pathogen, primarily linked with contaminated chicken meat, poses a significant health risk. Reducing the abundance of this pathogen in poultry meat is challenging but essential. This study assessed the impact of Lactobacillus‐fermented rapeseed meal (LFRM) on broilers exposed to C. jejuni‐contaminated litter, evaluating growth performance, Campylobacter levels, and metagenomic profile. RESULTS: By day 35, the litter contamination successfully colonized broilers with Campylobacter spp., particularly C. jejuni. In the grower phase, LFRM improved (P < 0.05) body weight and daily weight gain, resulting in a 9.2% better feed conversion ratio during the pre‐challenge period (the period before artificial infection; days 13–20). The LFRM also reduced the C. jejuni concentration in the ceca (P < 0.05), without altering alpha and beta diversity. However, metagenomic data analysis revealed LFRM targeted a reduction in the abundance of C. jejuni biosynthetic pathways of l‐tryptophan and l‐histidine and gene families associated with transcription and virulence factors while also possibly leading to selected stress‐induced resistance mechanisms. CONCLUSION: The study demonstrated that LFRM inclusion improved growth and decreased cecal Campylobacter spp. concentration and the relative abundance of pivotal C. jejuni genes. Performance benefits likely resulted from LFRM metabolites. At the molecular level, LFRM may have reduced C. jejuni colonization, likely by decreasing the abundance of energy transduction and l‐histidine and l‐tryptophan biosynthesis genes otherwise required for bacterial survival and increased virulence. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Natural wetlands are mostly nitrogen-limited ecosystems, while reclamation stimulates the loss of nitrogen (N) in soils by shifting the N regime. To investigate the microbial mechanisms of the N regime shift, we first conducted a global meta-analysis to quantify the wetland reclamation impacts on soil mineral N pools and then a field campaign to sample 24 soil cores up to 100 cm depth in a natural wetland and a 23-year cultivated soybean field from the Sanjiang Plain in northeastern China. After wetland reclamation, the N regime was shifted to cause a potential risk of massive N loss in soils; their microbial mechanisms were revealed through metagenomic data. In cropland, the relative abundance of genes involved in nitrification and assimilatory nitrate reduction to ammonia (ANRA) were enriched while those in N fixation, mineralization, denitrification, and dissimilatory nitrate reduction to ammonia (DNRA) were diminished. Wetland reclamation substantially enhanced the relative abundance of genes involved in nitrification (except for genes for ammonia oxidation to NH2OH) and denitrification in surface (0–30 cm) soils but decreased them in subsurface (30–100 cm) soils. After wetland reclamation, the relative abundance of genes involved in denitrification and DNRA significantly reduced in spring and summer, but such patterns were not found in autumn and winter. This change enhanced potential microbial-driven N loss in spring and summer. The metagenomic data serve as surrogate data sources for quantifying soil roles on soil N cycles under land use change. [ABSTRACT FROM AUTHOR]

Microbiome scientists critically need modern tools to explore and analyze microbial evolution. Often this involves studying the evolution of microbial genomes as a whole. However, different genes in a single genome can be subject to different evolutionary pressures, which can result in distinct gene-level evolutionary histories. To address this challenge, we propose to treat estimated gene-level phylogenies as data objects, and present an interactive method for the analysis of a collection of gene phylogenies. We use a local linear approximation of phylogenetic tree space to visualize estimated gene trees as points in low-dimensional Euclidean space, and address important practical limitations of existing related approaches, allowing an intuitive visualization of complex data objects. We demonstrate the utility of our proposed approach through microbial data analyses, including by identifying outlying gene histories in strains of Prevotella , and by contrasting Streptococcus phylogenies estimated using different gene sets. Our method is available as an open-source R package, and assists with estimating, visualizing, and interacting with a collection of bacterial gene phylogenies. [ABSTRACT FROM AUTHOR]

A growing number of studies are incorporating microbiome variation into machine learning-based models for the prediction of disease. The prediction of disease is generally improved by considering microbiome signatures. The most promising improvements in microbiome-augmented disease prediction are seen for liver disease, respiratory diseases, diabetes mellitus, inflammatory bowel disease, and neuropsychiatric conditions. As improved prediction relies on accurate microbial definition, detection, and diversity metrics, important considerations during bioinformatics and experimental design must be taken into consideration to limit the effect of unwanted technical bias. The human microbiome has been increasingly recognized as having potential use for disease prediction. Predicting the risk, progression, and severity of diseases holds promise to transform clinical practice, empower patient decisions, and reduce the burden of various common diseases, as has been demonstrated for cardiovascular disease or breast cancer. Combining multiple modifiable and non-modifiable risk factors, including high-dimensional genomic data, has been traditionally favored, but few studies have incorporated the human microbiome into models for predicting the prospective risk of disease. Here, we review research into the use of the human microbiome for disease prediction with a particular focus on prospective studies as well as the modulation and engineering of the microbiome as a therapeutic strategy. [ABSTRACT FROM AUTHOR]