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Background: The expansion of sequencing technologies as a result of the response to the COVID-19 pandemic enabled pathogen (meta)genomics to be deployed as a routine component of surveillance in many countries. Scaling genomic surveillance, however, comes with associated costs in both equipment and sequencing reagents, which should be optimized. Here, we evaluate the cost efficiency and performance of different read lengths in identifying pathogens in metagenomic samples. We carefully evaluated performance metrics, costs, and time requirements relative to choices of 75, 150 and 300 base pairs (bp) read lengths in pathogen identification. Results: Our findings revealed that moving from 75 bp to 150 bp read length approximately doubles both the cost and sequencing time. Opting for 300 bp reads leads to approximately two- and three-fold increases, respectively, in cost and sequencing time compared to 75 bp reads. For viral pathogen detection, the sensitivity median ranged from 99% with 75 bp reads to 100% with 150–300 bp reads. However, bacterial pathogens detection was less effective with shorter reads: 87% with 75 bp, 95% with 150 bp, and 97% with 300 bp reads. These findings were consistent across different levels of taxa abundance. The precision of pathogen detection using shorter reads was comparable to that of longer reads across most viral and bacterial taxa. Conclusions: During disease outbreak situations, when swift responses are required for pathogen identification, we suggest prioritizing 75 bp read lengths, especially if detection of viral pathogens is aimed. This practical approach allows better use of resources, enabling the sequencing of more samples using streamlined workflows, while maintaining a reliable response capability. [ABSTRACT FROM AUTHOR]

Background: Laccases can oxidize a broad spectrum of substrates, offering promising applications in various sectors, such as bioremediation, biomass fractionation in future biorefineries, and synthesis of biochemicals and biopolymers. However, laccase discovery and optimization with a desirable pH optimum remains a challenge due to the labor-intensive and time-consuming nature of the traditional laboratory methods. Results: This study presents a machine learning (ML)-integrated approach for predicting pH optima of basidiomycete fungal laccases, utilizing a small, curated dataset against a vast metagenomic data. Comparative computational analyses unveiled the structural and pH-dependent solubility differences between acidic and neutral-alkaline laccases, helping us understand the molecular bases of enzyme pH optimum. The pH profiling of the two ML-predicted alkaline laccase candidates from the basidiomycete fungus Lepista nuda further validated our computational approach, showing the accuracy of this comprehensive method. Conclusions: This study uncovers the efficacy of ML in the prediction of enzyme pH optimum from minimal datasets, marking a significant step towards harnessing computational tools for systematic screening of enzymes for biotechnology applications. [ABSTRACT FROM AUTHOR]

Background: Cutaneous infectious granulomas (CIG) are localized and chronic skin infection caused by a variety of pathogens such as protozoans, bacteria, worms, viruses and fungi. The diagnosis of CIG is difficult because microbiological examination shows low sensitivity and the histomorphological findings of CIG caused by different pathogens are commonly difficult to be distinguished. Objective: The objective of this study is to explore the application of mNGS in tissue sample testing for CIG cases, and to compare mNGS with traditional microbiological methods by evaluating sensitivity and specificity. Methods: We conducted a retrospective study at the Department of Dermatology of Sun Yat-sen Memorial Hospital, Sun Yat-sen University from January 1st, 2020, to May 31st, 2024. Specimens from CIG patients with a clinical presentation of cutaneous infection that was supported by histological examination were retrospectively enrolled. Specimens were delivered to be tested for microbiological examinations and mNGS. Results: Our data show that mNGS detected Non-tuberculosis mycobacteria, Mycobacterium tuberculosis, fungi and bacteria in CIG. Compared to culture, mNGS showed a higher positive rate (80.77% vs. 57.7%) with high sensitivity rate (100%) and negative predictive value (100%). In addition, mNGS can detect more pathogens in one sample and can be used to detect variable samples including the samples of paraffin-embedded tissue with shorter detective time. Of the 21 patients who showed clinical improvement within a 30-day follow-up, eighteen had their treatments adjusted, including fifteen who continued treatment based on the results of mNGS. Conclusions: mNGS could provide a potentially rapid and effective alternative detection method for diagnosis of cutaneous infectious granulomas and mNGS results may affect the clinical prognosis resulting from enabling the patients to initiate timely treatment. [ABSTRACT FROM AUTHOR]

Background: Clean energy hydrogen (H2) produced from abundant lignocellulose is an alternative to fossil energy. As an essential influencing factor, there is a lack of comparison between constant temperatures (35, 55 and 65 °C) and gradient heating temperature (35 to 65 °C) on the H2 production regulation potential from lignocellulose-rich straw via high-solid anaerobic digestion (HS-AD). More importantly, the microbial mechanism of temperature regulating H2 accumulation needs to be investigated. Results: Constant 65 °C led to the lowest lignin residue (1.93%) and the maximum release of cellulose and hemicellulose, and the highest H2 production (26.01 mL/g VS). H2 production at 35 and 55 °C was only 14.56 and 24.13 mL/g VS, respectively. In order to further explore the potential of ultra-high temperature (65 °C), HS-AD was performed by gradient heating conditions (35 to 65 °C). However, compared to constant 65 °C, gradient heating conditions led to higher lignin residue (2.49%) and lower H2 production (13.53 mL/g VS) than gradient heating conditions (47.98%). In addition, metagenomic analysis showed the cellulose/hemicellulose hydrolyzing bacteria and genes (mainly Thermoclostridium, and xynA, xynB, abfA, bglB and xynD), H2-producing bacteria and related genes (mainly Thermoclostridium, and nifD, nifH and nifK), and microbial movement and metabolic functions were enriched at 65 °C. However, the enrichment of two-component systems under gradient heating conditions resulted in a lack of highly-enriched ultra-high-temperature cellulose/hemicellulose hydrolyzing genera and related genes but rather enriched H2 consumption genera and genes (mainly Acetivibrio, and hyaB and hyaA) resulting in a weaker H2 production. Conclusions: The lignin degradation process does not directly determine H2 accumulation, which was actually regulated by bacteria/genes contributing to H2 production/consumption. In addition, it is temperature that enhances the hydrolysis process of lignin rather than lignin-degrading enzymes, bacteria and genes by promoting microbial material transfer and metabolism. In terms of temperature, one of the key parameters of HS-AD for H2 production, we developed an important regulatory strategy, enriched the theoretical basis of temperature regulation for H2 production to further expanded the research horizon in this field. ABqfqNejHM5MQBNj5XnjcN Video Abstract [ABSTRACT FROM AUTHOR]

Background: Antibiotic resistance is a critical global concern, posing significant challenges to human health and medical treatments. Studying antibiotic resistance genes (ARGs) is essential not only in clinical settings but also in diverse environmental contexts. However, ARGs in unique environments such as anchialine caves, which connect both fresh and marine water, remain largely unexplored despite their intriguing ecological characteristics. Results: We present the first study that comprehensively explores the occurrence and distribution of ARGs and mobile genetic elements (MGEs) within an anchialine cave. Utilizing metagenomic sequencing we uncovered a wide array of ARGs with the bacitracin resistance gene, bacA and multidrug resistance genes, being the most dominant. The cave's microbial community and associated resistome were significantly influenced by the salinity gradient. The discovery of novel β-lactamase variants revealed the cave's potential as a reservoir for previously undetected resistance genes. ARGs in the cave demonstrated horizontal transfer potential via plasmids, unveiling ecological implications. Conclusions: These findings highlight the need for further exploration of the resistome in unique environments like anchialine caves. The interconnected dynamics of ARGs and MGEs within anchialine caves offer valuable insights into potential reservoirs and mechanisms of antibiotic resistance in natural ecosystems. This study not only advances our fundamental understanding but also highlights the need for a comprehensive approach to address antibiotic resistance in diverse ecological settings. [ABSTRACT FROM AUTHOR]

Background: Next-generation sequencing (NGS) approaches have revolutionized gut microbiome research and can provide strain-level resolution, but these techniques have limitations in that they are only semi-quantitative, suffer from high detection limits, and generate data that is compositional. The present study aimed to systematically compare quantitative PCR (qPCR) and droplet digital PCR (ddPCR) for the absolute quantification of Limosilactobacillus reuteri strains in human fecal samples and to develop an optimized protocol for the absolute quantification of bacterial strains in fecal samples. Results: Using strain-specific PCR primers for L. reuteri 17938, ddPCR showed slightly better reproducibility, but qPCR was almost as reproducible and showed comparable sensitivity (limit of detection [LOD] around 104 cells/g feces) and linearity (R2 > 0.98) when kit-based DNA isolation methods were used. qPCR further had a wider dynamic range and is cheaper and faster. Based on these findings, we conclude that qPCR has advantages over ddPCR for the absolute quantification of bacterial strains in fecal samples. We provide an optimized and easy-to-follow step-by-step protocol for the design of strain-specific qPCR assays, starting from primer design from genome sequences to the calibration of the PCR system. Validation of this protocol to design PCR assays for two L. reuteri strains, PB-W1 and DSM 20016 T, resulted in a highly accurate qPCR with a detection limit in spiked fecal samples of around 103 cells/g feces. Applying our strain-specific qPCR assays to fecal samples collected from human subjects who received live L. reuteri PB-W1 or DSM 20016 T during a human trial demonstrated a highly accurate quantification and sensitive detection of these two strains, with a much lower LOD and a broader dynamic range compared to NGS approaches (16S rRNA gene sequencing and whole metagenome sequencing). Conclusions: Based on our analyses, we consider qPCR with kit-based DNA extraction approaches the best approach to accurately quantify gut bacteria at the strain level in fecal samples. The provided step-by-step protocol will allow scientists to design highly sensitive strain-specific PCR systems for the accurate quantification of bacterial strains of not only L. reuteri but also other bacterial taxa in a broad range of applications and sample types. -oGjUmj5e8MXZDxyDjzcm- Video Abstract [ABSTRACT FROM AUTHOR]

Background: Environmental reservoirs of antibiotic resistance pose a threat to human and animal health. Aquatic biofilms impacted by wastewater effluent (WW) are known environmental reservoirs for antibiotic resistance; however, the relative importance of biotic factors and abiotic factors from WW on the abundance of antibiotic resistance genes (ARGs) within aquatic biofilms remains unclear. Additionally, experimental evidence is limited within complex aquatic microbial communities as to whether genes bearing low sequence similarity to validated reference ARGs are functional as ARGs. Results: To disentangle the effects of abiotic and biotic factors on ARG abundances, natural biofilms were previously grown in flume systems with different proportions of stream water and either ultrafiltered or non-ultrafiltered WW. In this study, we conducted deep shotgun metagenomic sequencing of 75 biofilm, stream, and WW samples from these flume systems and compared the taxonomic and functional microbiome and resistome composition. Statistical analysis revealed an alignment of the resistome and microbiome composition and a significant association with experimental treatment. Several ARG classes exhibited an increase in normalized metagenomic abundances in biofilms grown with increasing percentages of non-ultrafiltered WW. In contrast, sulfonamide and extended-spectrum beta-lactamase ARGs showed greater abundances in biofilms grown in ultrafiltered WW compared to non-ultrafiltered WW. Overall, our results pointed toward the dominance of biotic factors over abiotic factors in determining ARG abundances in WW-impacted stream biofilms and suggested gene family-specific mechanisms for ARGs that exhibited divergent abundance patterns. To investigate one of these specific ARG families experimentally, we biochemically characterized a new beta-lactamase from the Planctomycetota (Phycisphaeraceae). This beta-lactamase displayed activity in the cleavage of cephalosporin analog despite sharing a low sequence identity with known ARGs. Conclusions: This discovery of a functional planctomycete beta-lactamase ARG is noteworthy, not only because it was the first beta-lactamase to be biochemically characterized from this phylum, but also because it was not detected by standard homology-based ARG tools. In summary, this study conducted a metagenomic analysis of the relative importance of biotic and abiotic factors in the context of WW discharge and their impact on both known and new ARGs in aquatic biofilms. DkJa1T-YWptaXXeH_hsDtB Video Abstract [ABSTRACT FROM AUTHOR]

Kinema, a sticky-textured fermented soybean food with umami flavour, is originated in the historical Limbuwan region, now situated in the eastern districts of Nepal. It has since expanded to different areas in Darjeeling Hills and Sikkim in India and Bhutan. The Limboo community, one of the oldest indigenous groups in the Himalayas, has developed a method for fermenting soybeans to produce kinema. Bacillus is the main bacterial genus responsible for fermenting kinema, along with lactic acid bacteria, yeasts, and fungi. Kinema is full of nutrients like protein, fats, carbohydrates, amino acids, vitamins, and minerals and offers health benefits through its antioxidant, anti-inflammatory, antiobesity, and antidiabetic properties. A novel strain of Bacillus subtilis Tamang has been identified in kinema samples from Darjeeling Hills, India, exhibiting elevated levels of γ-PGA and various biomarker genes for health benefits and biological functionalities. Kinema contains secondary metabolites including several bioactive compounds, immunomodulators, vitamin B-complexes, and others that help promote good health. The transcriptome of the B. subtilis Tamang strain reveals genes associated with GABA production, Vitamin B12 synthesis, and fibrinolytic activity. Safety evaluations have demonstrated that the strain and the production of kinema do not pose any toxicity risks based on animal studies. Despite facing challenges in terms of its strong taste and slimy consistency for broader acceptance, the bioactive elements and safe starter cultures found in kinema hold promise for the development of functional food. [ABSTRACT FROM AUTHOR]

Background: Haemaphysalis qinghaiensis is a tick species distributed only in China. Due to its ability to transmit a variety of pathogens, including species of the genera Anaplasma, Rickettsia, Babesia, and Theileria, it seriously endangers livestock husbandry. However, the microbial community of the midgut of H. qinghaiensis females collected from yaks and Tibetan sheep has not yet been characterized using metagenomic sequencing technology. Methods: Haemaphysalis qinghaiensis were collected from the skins of yaks and Tibetan sheep in Gansu Province, China. Genomic DNA was extracted from the midguts and midgut contents of fully engorged H. qinghaiensis females collected from the two hosts. Metagenomic sequencing technology was used to analyze the microbial community of the two groups. Results: Fifty-seven phyla, 483 genera, and 755 species were identified in the two groups of samples. The ticks from the two hosts harbored common and unique microorganisms. At the phylum level, the dominant common phyla were Proteobacteria, Firmicutes, and Mucoromycota. At the genus level, the dominant common genera were Anaplasma, Ehrlichia, and Pseudomonas. At the species level, bacteria including Anaplasma phagocytophilum, Ehrlichia minasensis, and Pseudomonas aeruginosa along with eukaryotes such as Synchytrium endobioticum and Rhizophagus irregularis, and viruses such as the orf virus, Alphadintovirus mayetiola, and Parasteatoda house spider adintovirus were detected in both groups. In addition, the midgut of H. qinghaiensis collected from yaks had unique microbial taxa including two phyla, eight genera, and 23 species. Unique microorganisms in the midgut of H. qinghaiensis collected from Tibetan sheep included two phyla, 14 genera, and 32 species. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that the functional genes of the microbiome of H. qinghaiensis were annotated to six pathways, and the metabolic pathways included 11 metabolic processes, in which the genes involved in carbohydrate metabolism were the most abundant, followed by the genes involved in lipid metabolism. Conclusions: These findings indicate that most of the microbial species in the collected H. qinghaiensis ticks were the same in both hosts, but there were also slight differences. The analytical data from this study have enhanced our understanding of the midgut microbial composition of H. qinghaiensis collected from different hosts. The database of H. qinghaiensis microbe constructed from this study will lay the foundation for predicting tick-borne diseases. Furthermore, a comprehensive understanding of tick microbiomes will be useful for understanding vector competency and interactions with ticks and midgut microorganisms. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has underscored the critical role of sequencing technology in disease control and outbreak response. However, resource limitations and challenging environments often impede such efforts in low and middle-income countries. This study aimed to investigate the spectrum of viral co-infections, particularly with human viral pathogens, in SARS-CoV-2 positive individuals in Sierra Leone using metagenomic sequencing, evaluating the feasibility of utilizing this technology for epidemiological and evolutionary surveillance of pathogens related to public health in low-income environments. Methods: We retrospectively collected and analyzed 98 nasopharyngeal swab specimens from SARS-CoV-2 positive individuals in Sierra Leone. Samples were pre-processed locally and transferred to China via FTA cards for metagenomic sequencing, which was performed using the Novaseq platform. The study focused on the identification of nasopharyngeal viruses co-infecting with SARS-CoV-2, with a deeper analysis of significant human viral pathogens such as HPV. Results: The study identified 22 viral taxa from 20 families, including 4 human viruses. Notably, 19.4% of samples showed HPV co-infection with 34 distinct types, predominantly beta and gamma HPVs. Multiple HPV types were found in individual samples, indicating a high complexity of viral co-infections. Conclusions: The identification of a wide range of co-infecting viruses, particularly multiple HPV genotypes, highlights the complexity of viral interactions and their potential implications for public health. These findings enhance our understanding of viral co-infections and provide valuable insights for public health interventions in Sierra Leone. Further research is needed to explore the clinical significance of these findings and their impact on disease outcomes. [ABSTRACT FROM AUTHOR]

Background: Oral microbiota comprises polymicrobial communities shaped by mutualistic coevolution with the host, contributing to homeostasis and regulating immune function. Nevertheless, dysbiosis of oral bacterial communities is associated with a number of clinical symptoms that ranges from infections to oral cancer. Peri-implant diseases are biofilm-associated inflammatory conditions affecting the soft and hard tissues around dental implants. Characterization and identification of the biofilm community are essential for the understanding of the pathophysiology of such diseases. For that sampling methods should be representative of the biofilm communities Therefore, there is a need to know the effect of different sampling strategies on the biofilm characterization by next generation sequencing. Methods: With the aim of selecting an appropriate microbiome sampling procedure for periimplant biofilms, next generation sequencing was used for characterizing the bacterial communities obtained by three different sampling strategies two months after transepithelial abutment placement: adjacent periodontal crevicular fluid (ToCF), crevicular fluid from transepithelial abutment (TACF) and transepithelial abutment (TA). Results: Significant differences in multiple alpha diversity indices were detected at both the OTU and the genus level between different sampling procedures. Differentially abundant taxa were detected between sample collection strategies, including peri-implant health and disease related taxa. At the community level significant differences were also detected between TACF and TA and also between TA and ToCF. Moreover, differential network properties and association patterns were identified. Conclusions: The selection of sample collection strategy can significantly affect the community composition and structure. Trial registration: This research is part of a randomized clinical trial that was designed to assess the effect of transepithelial abutment surface on the biofilm formation. The trial was registered at Trial Registration ClinicalTrials.gov under the number NCT03554876. [ABSTRACT FROM AUTHOR]

Bats (order: Chiroptera) are known to host a diverse range of viruses, some of which present a human public health risk. Thorough viral surveillance is therefore essential to predict and potentially mitigate zoonotic spillover. Astroviruses (family: Astroviridae) are an understudied group of viruses with a growing amount of indirect evidence for zoonotic transfer. Astroviruses have been detected in bats with significant prevalence and diversity, suggesting that bats may act as important astrovirus hosts. Most astrovirus surveillance in wild bat hosts has, to date, been restricted to single-gene PCR detection and concomitant Sanger sequencing; additionally, many bat species and many geographic regions have not yet been surveyed for astroviruses at all. Here, we use metagenomic Next Generation Sequencing (mNGS) to detect astroviruses in three species of Madagascar fruit bats, Eidolon dupreanum, Pteropus rufus, and Rousettus madagascariensis. We detect numerous partial sequences from all three species and one near-full length astrovirus sequence from Rousettus madagascariensis, which we use to characterize the evolutionary history of astroviruses both within bats and the broader mammalian clade, Mamastrovirus. Taken together, applications of mNGS implicate bats as important astrovirus hosts and demonstrate novel patterns of bat astrovirus evolutionary history, particularly in the Southwest Indian Ocean region. [ABSTRACT FROM AUTHOR]

Background: Lake Bonney, which is divided into a west lobe (WLB) and an east lobe (ELB), is a perennially ice-covered lake located in the McMurdo Dry Valleys of Antarctica. Despite previous reports on the microbial community dynamics of ice-covered lakes in this region, there is a paucity of information on the relationship between microbial genomic diversity and associated nutrient cycling. Here, we applied gene- and genome-centric approaches to investigate the microbial ecology and reconstruct microbial metabolic potential along the depth gradient in Lake Bonney. Results: Lake Bonney is strongly chemically stratified with three distinct redox zones, yielding different microbial niches. Our genome enabled approach revealed that in the sunlit and relatively freshwater epilimnion, oxygenic photosynthetic production by the cyanobacterium Pseudanabaena and a diversity of protists and microalgae may provide new organic carbon to the environment. CO-oxidizing bacteria, such as Acidimicrobiales, Nanopelagicales, and Burkholderiaceae were also prominent in the epilimnion and their ability to oxidize carbon monoxide to carbon dioxide may serve as a supplementary energy conservation strategy. In the more saline metalimnion of ELB, an accumulation of inorganic nitrogen and phosphorus supports photosynthesis despite relatively low light levels. Conversely, in WLB the release of organic rich subglacial discharge from Taylor Glacier into WLB would be implicated in the possible high abundance of heterotrophs supported by increased potential for glycolysis, beta-oxidation, and glycoside hydrolase and may contribute to the growth of iron reducers in the dark and extremely saline hypolimnion of WLB. The suboxic and subzero temperature zones beneath the metalimnia in both lobes supported microorganisms capable of utilizing reduced nitrogens and sulfurs as electron donors. Heterotrophs, including nitrate reducing sulfur oxidizing bacteria, such as Acidimicrobiales (MAG72) and Salinisphaeraceae (MAG109), and denitrifying bacteria, such as Gracilimonas (MAG7), Acidimicrobiales (MAG72) and Salinisphaeraceae (MAG109), dominated the hypolimnion of WLB, whereas the environmental harshness of the hypolimnion of ELB was supported by the relatively low in metabolic potential, as well as the abundance of halophile Halomonas and endospore-forming Virgibacillus. Conclusions: The vertical distribution of microbially driven C, N and S cycling genes/pathways in Lake Bonney reveals the importance of geochemical gradients to microbial diversity and biogeochemical cycles with the vertical water column. [ABSTRACT FROM AUTHOR]

Background: Construction of co-occurrence networks in metagenomic data often employs correlation to infer pairwise relationships between microbes. However, biological systems are complex and often display qualities non-linear in nature. Therefore, the reliance on correlation alone may overlook important relationships and fail to capture the full breadth of intricacies presented in underlying interaction networks. It is of interest to incorporate metrics that are not only robust in detecting linear relationships, but non-linear ones as well. Results: In this paper, we explore the use of various mutual information (MI) estimation approaches for quantifying pairwise relationships in biological data and compare their performances against two traditional measures–Pearson's correlation coefficient, r, and Spearman's rank correlation coefficient, ρ. Metrics are tested on both simulated data designed to mimic pairwise relationships that may be found in ecological systems and real data from a previous study on C. diff infection. The results demonstrate that, in the case of asymmetric relationships, mutual information estimators can provide better detection ability than Pearson's or Spearman's correlation coefficients. Specifically, we find that these estimators have elevated performances in the detection of exploitative relationships, demonstrating the potential benefit of including them in future metagenomic studies. Conclusions: Mutual information (MI) can uncover complex pairwise relationships in biological data that may be missed by traditional measures of association. The inclusion of such relationships when constructing co-occurrence networks can result in a more comprehensive analysis than the use of correlation alone. [ABSTRACT FROM AUTHOR]

Background: Metagenomic binning, the clustering of assembled contigs that belong to the same genome, is a crucial step for recovering metagenome-assembled genomes (MAGs). Contigs are linked by exploiting consistent signatures along a genome, such as read coverage patterns. Using coverage from multiple samples leads to higher-quality MAGs; however, standard pipelines require all-to-all read alignments for multiple samples to compute coverage, becoming a key computational bottleneck. Results: We present fairy (https://github.com/bluenote-1577/fairy), an approximate coverage calculation method for metagenomic binning. Fairy is a fast k-mer-based alignment-free method. For multi-sample binning, fairy can be > 250 × faster than read alignment and accurate enough for binning. Fairy is compatible with several existing binners on host and non-host-associated datasets. Using MetaBAT2, fairy recovers 98.5 % of MAGs with > 50 % completeness and < 5 % contamination relative to alignment with BWA. Notably, multi-sample binning with fairy is always better than single-sample binning using BWA ( > 1.5 × more > 50 % complete MAGs on average) while still being faster. For a public sediment metagenome project, we demonstrate that multi-sample binning recovers higher quality Asgard archaea MAGs than single-sample binning and that fairy's results are indistinguishable from read alignment. Conclusions: Fairy is a new tool for approximately and quickly calculating multi-sample coverage for binning, resolving a computational bottleneck for metagenomics. FUg-6r-bD5B9L5eToLSA3E Video Abstract [ABSTRACT FROM AUTHOR]

Background: Subsurface microorganisms contribute to important ecosystem services, yet little is known about how the composition of these communities is affected by small scale heterogeneity such as in preferential flow paths including biopores and fractures. This study aimed to provide a more complete characterization of microbial communities from preferential flow paths and matrix sediments of a clayey till to a depth of 400 cm by using 16S rRNA gene and fungal ITS2 amplicon sequencing of environmental DNA. Moreover, shotgun metagenomics was applied to samples from fractures located 150 cm below ground surface (bgs) to investigate the bacterial genomic adaptations resulting from fluctuating exposure to nutrients, oxygen and water. Results: The microbial communities changed significantly with depth. In addition, the bacterial/archaeal communities in preferential flow paths were significantly different from those in the adjacent matrix sediments, which was not the case for fungal communities. Preferential flow paths contained higher abundances of 16S rRNA and ITS gene copies than the corresponding matrix sediments and more aerobic bacterial taxa than adjacent matrix sediments at 75 and 150 cm bgs. These findings were linked to higher organic carbon and the connectivity of the flow paths to the topsoil as demonstrated by previous dye tracer experiments. Moreover, bacteria, which were differentially more abundant in the fractures than in the matrix sediment at 150 cm bgs, had higher abundances of carbohydrate active enzymes, and a greater potential for mixotrophic growth. Conclusions: Our results demonstrate that the preferential flow paths in the subsurface are unique niches that are closely connected to water flow and the fluctuating ground water table. Although no difference in fungal communities were observed between these two niches, hydraulically active flow paths contained a significantly higher abundance in fungal, archaeal and bacterial taxa. Metagenomic analysis suggests that bacteria in tectonic fractures have the genetic potential to respond to fluctuating oxygen levels and can degrade organic carbon, which should result in their increased participation in subsurface carbon cycling. This increased microbial abundance and activity needs to be considered in future research and modelling efforts of the soil subsurface. [ABSTRACT FROM AUTHOR]

Background: Gemmatimonadota bacteria are widely distributed in nature, but their metabolic potential and ecological roles in marine environments are poorly understood. Results: Here, we obtained 495 metagenome-assembled genomes (MAGs), and associated viruses, from coastal to deep-sea sediments around the world. We used this expanded genomic catalog to compare the protein composition and update the phylogeny of these bacteria. The marine Gemmatimonadota are phylogenetically different from those previously reported from terrestrial environments. Functional analyses of these genomes revealed these marine genotypes are capable of degradation of complex organic carbon, denitrification, sulfate reduction, and oxidizing sulfide and sulfite. Interestingly, there is widespread genetic potential for secondary metabolite biosynthesis across Gemmatimonadota, which may represent an unexplored source of novel natural products. Furthermore, viruses associated with Gemmatimonadota have the potential to "hijack" and manipulate host metabolism, including the assembly of the lipopolysaccharide in their hosts. Conclusions: This expanded genomic diversity advances our understanding of these globally distributed bacteria across a variety of ecosystems and reveals genetic distinctions between those in terrestrial and marine communities. -srP_8yBftBuaKffV-GvkT Video Abstract [ABSTRACT FROM AUTHOR]

Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning. [ABSTRACT FROM AUTHOR]

Background: Symbioses between primary producers and bacteria are crucial for nutrient exchange that fosters host growth and niche adaptation. Yet, how viruses that infect bacteria (phages) influence these bacteria-eukaryote interactions is still largely unknown. Here, we investigate the role of viruses on the genomic diversity and functional adaptations of bacteria associated with pelagic sargassum. This brown alga has dramatically increased its distribution range in the Atlantic in the past decade and is predicted to continue expanding, imposing severe impacts on coastal ecosystems, economies, and human health. Results: We reconstructed 73 bacterial and 3963 viral metagenome-assembled genomes (bMAGs and vMAGs, respectively) from coastal Sargassum natans VIII and surrounding seawater. S. natans VIII bMAGs were enriched in prophages compared to seawater (28% and 0.02%, respectively). Rhodobacterales and Synechococcus bMAGs, abundant members of the S. natans VIII microbiome, were shared between the algae and seawater but were associated with distinct phages in each environment. Genes related to biofilm formation and quorum sensing were enriched in S. natans VIII phages, indicating their potential to influence algal association in their bacterial hosts. In-vitro assays with a bacterial community harvested from sargassum surface biofilms and depleted of free viruses demonstrated that these bacteria are protected from lytic infection by seawater viruses but contain intact and inducible prophages. These bacteria form thicker biofilms when growing on sargassum-supplemented seawater compared to seawater controls, and phage induction using mitomycin C was associated with a significant decrease in biofilm formation. The induced metagenomes were enriched in genomic sequences classified as temperate viruses compared to uninduced controls. Conclusions: Our data shows that prophages contribute to the flexible genomes of S. natans VIII-associated bacteria. These prophages encode genes with symbiotic functions, and their induction decreases biofilm formation, an essential capacity for flexible symbioses between bacteria and the alga. These results indicate that prophage acquisition and induction contribute to genomic and functional diversification during sargassum-bacteria symbioses, with potential implications for algae growth. 1vVC6YGWLCm_DZc419o4RC Video Abstract [ABSTRACT FROM AUTHOR]

Metagenomic data plays a crucial role in analyzing the relationship between microbes and diseases. However, the limited number of samples, high dimensionality, and sparsity of metagenomic data pose significant challenges for the application of deep learning in data classification and prediction. Previous studies have shown that utilizing the phylogenetic tree structure to transform metagenomic abundance data into a 2D matrix input for convolutional neural networks (CNNs) improves classification performance. Inspired by the success of a Permutable MLP-like architecture in visual recognition, we propose Metagenomic Permutator (MetaP), which applied the Permutable MLP-like network structure to capture the phylogenetic information of microbes within the 2D matrix formed by phylogenetic tree. Our experiments demonstrate that our model achieved competitive performance compared to other deep neural networks and traditional machine learning, and has good prospects for multi-classification and large sample sizes. Furthermore, we utilize the SHAP (SHapley Additive exPlanations) method to interpret our model predictions, identifying the microbial features that are associated with diseases. [ABSTRACT FROM AUTHOR]

Background: The causative agents of Acute Encephalitis Syndrome remain unknown in 68–75% of the cases. In Nepal, the cases are tested only for Japanese encephalitis, which constitutes only about 15% of the cases. However, there could be several organisms, including vaccine-preventable etiologies that cause acute encephalitis, when identified could direct public health efforts for prevention, including addressing gaps in vaccine coverage. Objectives: This study employs metagenomic next-generation-sequencing in the investigation of underlying causative etiologies contributing to acute encephalitis syndrome in Nepal. Methods: In this study, we investigated 90, Japanese-encephalitis-negative, banked cerebrospinal fluid samples that were collected as part of a national surveillance network in 2016 and 2017. Randomization was done to include three age groups (< 5-years; 5-14-years; >15-years). Only some metadata (age and gender) were available. The investigation was performed in two batches which included total nucleic-acid extraction, followed by individual library preparation (DNA and RNA) and sequencing on Illumina iSeq100. The genomic data were interpreted using Chan Zuckerberg-ID and confirmed with polymerase-chain-reaction. Results: Human-alphaherpes-virus 2 and Enterovirus-B were seen in two samples. These hits were confirmed by qPCR and semi-nested PCR respectively. Most of the other samples were marred by low abundance of pathogen, possible freeze-thaw cycles, lack of process controls and associated clinical metadata. Conclusion: From this study, two documented causative agents were revealed through metagenomic next-generation-sequencing. Insufficiency of clinical metadata, process controls, low pathogen abundance and absence of standard procedures to collect and store samples in nucleic-acid protectants could have impeded the study and incorporated ambiguity while correlating the identified hits to infection. Therefore, there is need of standardized procedures for sample collection, inclusion of process controls and clinical metadata. Despite challenging conditions, this study highlights the usefulness of mNGS to investigate diseases with unknown etiologies and guide development of adequate clinical-management-algorithms and outbreak investigations in Nepal. [ABSTRACT FROM AUTHOR]

Background: Rivers and streams are important components of the global carbon cycle and methane budget. However, our understanding of the microbial diversity and the metabolic pathways underpinning methylotrophic methane production in river sediments is limited. Dimethylsulfide is an important methylated compound, found in freshwater sediments. Yet, the magnitude of DMS-dependent methanogenesis nor the methanogens carrying out this process in river sediments have been explored before. This study addressed this knowledge gap in DMS-dependent methanogenesis in gravel and sandy river sediments. Results: Significant methane production via DMS degradation was found in all sediment microcosms. Sandy, less permeable river sediments had higher methane yields (83 and 92%) than gravel, permeable sediments (40 and 48%). There was no significant difference between the methanogen diversity in DMS-amended gravel and sandy sediment microcosms, which Methanomethylovorans dominated. Metagenomics data analysis also showed the dominance of Methanomethylovorans and Methanosarcina. DMS-specific methyltransferase genes (mts) were found in very low relative abundances whilst the methanol-, trimethylamine- and dimethylamine-specific methyltransferase genes (mtaA, mttB and mtbB) had the highest relative abundances, suggesting their involvement in DMS-dependent methanogenesis. Conclusions: This is the first study demonstrating a significant potential for DMS-dependent methanogenesis in river sediments with contrasting geologies. Methanomethylovorans were the dominant methylotrophic methanogen in all river sediment microcosms. Methyltransferases specific to methylotrophic substrates other than DMS are likely key enzymes in DMS-dependent methanogenesis, highlighting their versatility and importance in the methane cycle in freshwater sediments, which would warrant further study. [ABSTRACT FROM AUTHOR]

Background: Andersen's lesion (AL) is a rare complication of ankylosing spondylitis (AS), characterized by nonneoplastic bone destruction, typically manifested as bone destruction and sclerosis in the vertebral body and/or intervertebral disc area. At present, there is no consensus on the pathology and etiology of AL. Repeated trauma, inflammation in essence and part of the natural history of Ankylosing spondylitis itself are the most widely recognized theories of the etiology of AL. However, positive bacteria cultured in bone biopsy of Andersen's lesion (AL) in Ankylosing spondylitis patients are extremely rare. Herein, we report a rare case of detecting Ewingella americana from a patient with Andersson lesion in ankylosing spondylitis by Metagenomic Next-Generation Sequencing (mNGS) Test. Case presentation: This case involved a 39-year-old male with a history of AS for 11 years, who developed AL (T11/12) in the thoracic vertebrae. After sufficient preoperative preparation, we successfully performed one-stage posterior approach corrective surgery and collected bone biopsies samples for examination. Cultured bacteria were not found, and pathological histology indicated infiltration of inflammatory cells. However, it is worth noting that we discovered a gram-negative bacterium, the Ewingella americana, through mNGS testing. Further histopathological examination suggests chronic inflammatory cell infiltration. After one-stage posterior approach corrective surgery, the patient's condition significantly improved. At the 6-month follow-up, the pain significantly decreased, and the patient returned to normal life. Conclusion: We detected Ewinia americana in the bone biopsies of Andersson lesion (AL) in ankylosing spondylitis patient by mNGS. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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]

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]

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]

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]

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]

Background: Diagnosis and monitoring of leptomeningeal malignancy remain challenging, and are usually based on neurological, radiological, cerebrospinal fluid (CSF) and pathological findings. This study aimed to investigate the diagnostic performance of CSF metagenomic next-generation sequencing (mNGS) and chromosome copy number variations (CNVs) analysis in the detection of leptomeningeal malignancy. Methods: Of the 51 patients included in the study, 34 patients were diagnosed with leptomeningeal malignancies, and 17 patients were diagnosed with central nervous system (CNS) inflammatory diseases. The Sayk's spontaneous cell sedimentation technique was employed for CSF cytology. And a well-designed approach utilizing the CSF mNGS-CNVs technique was explored for early diagnosis of leptomeningeal malignancy. Results: In the tumor group, 28 patients were positive for CSF cytology, and 24 patients were positive for CSF mNGS-CNVs. Sensitivity and specificity of CSF cytology were 82.35% (95% CI: 66.83-92.61%) and 94.12% (95% CI: 69.24-99.69%). In comparison, sensitivity and specificity of CSF mNGS-CNV were 70.59% (95% CI: 52.33-84.29%) and 100% (95% CI: 77.08-100%). There was no significant difference in diagnostic consistency between CSF cytology and mNGS-CNVs (p = 0.18, kappa = 0.650). Conclusions: CSF mNGS-CNVs tend to have higher specificity compared with traditional cytology and can be used as a complementary diagnostic method for patients with leptomeningeal malignancies. [ABSTRACT FROM AUTHOR]

Background: Mangroves are complex and dynamic coastal ecosystems under frequent fluctuations in physicochemical conditions related to the tidal regime. The frequent variation in organic matter concentration, nutrients, and oxygen availability, among other factors, drives the microbial community composition, favoring syntrophic populations harboring a rich and diverse, stress-driven metabolism. Mangroves are known for their carbon sequestration capability, and their complex and integrated metabolic activity is essential to global biogeochemical cycling. Here, we present a metabolic reconstruction based on the genomic functional capability and flux profile between sympatric MAGs co-assembled from a tropical restored mangrove. Results: Eleven MAGs were assigned to six Bacteria phyla, all distantly related to the available reference genomes. The metabolic reconstruction showed several potential coupling points and shortcuts between complementary routes and predicted syntrophic interactions. Two metabolic scenarios were drawn: a heterotrophic scenario with plenty of carbon sources and an autotrophic scenario with limited carbon sources or under inhibitory conditions. The sulfur cycle was dominant over methane and the major pathways identified were acetate oxidation coupled to sulfate reduction, heterotrophic acetogenesis coupled to carbohydrate catabolism, ethanol production and carbon fixation. Interestingly, several gene sets and metabolic routes similar to those described for wastewater and organic effluent treatment processes were identified. Conclusion: The mangrove microbial community metabolic reconstruction reflected the flexibility required to survive in fluctuating environments as the microhabitats created by the tidal regime in mangrove sediments. The metabolic components related to wastewater and organic effluent treatment processes identified strongly suggest that mangrove microbial communities could represent a resourceful microbial model for biotechnological applications that occur naturally in the environment. [ABSTRACT FROM AUTHOR]

Background: Ketogenic diets are increasingly popular for addressing obesity, but their impacts on the gut microbiota and metabolome remain unclear. This paper aimed to investigate how a ketogenic diet affects intestinal microorganisms and metabolites in obesity. Methods: Male mice were provided with one of the following dietary regimens: normal chow, high-fat diet, ketogenic diet, or high-fat diet converted to ketogenic diet. Body weight and fat mass were measured weekly using high-precision electronic balances and minispec body composition analyzers. Metagenomics and non-targeted metabolomics data were used to analyze differences in intestinal contents. Results: Obese mice on the ketogenic diet exhibited notable improvements in weight and body fat. However, these were accompanied by a significant decrease in intestinal microbial diversity, as well as an increase in Firmicutes abundance and a 247% increase in the Firmicutes/Bacteroidetes ratio. The ketogenic diet also altered multiple metabolic pathways in the gut, including glucose, lipid, energy, carbohydrate, amino acid, ketone body, butanoate, and methane pathways, as well as bacterial secretion and colonization pathways. These changes were associated with increased intestinal inflammation and dysbiosis in obese mice. Furthermore, the ketogenic diet enhanced the secretion of bile and the synthesis of aminoglycoside antibiotics in obese mice, which may impair the gut microbiota and be associated with intestinal inflammation and immunity. Conclusions: The study suggest that the ketogenic diet had an unfavorable risk–benefit trade-off and may compromise metabolic homeostasis in obese mice. [ABSTRACT FROM AUTHOR]

Background: Fenofibrate is a compound with diverse biological properties that can be utilized to lower blood lipids. Understanding the impact of the gut microbiota in hyperlipidemia is vital for controlling systemic inflammation and improving serum lipid control. Nevertheless, the specific effects of fenofibrate on the phenotype and gene expression of resident gut bacteria, as well as its influence on the transformation of microbial metabolism into functional networks, remain unclear. In this study, our aimed to examine the gene and metabolic pathways of the gut microbiota in a hamster fed a high-fat diet (HFD) and administered fenofibrate. Results: In this study, we conducted metagenomic analyses on samples from HFD hamsters treated with fenofibrate. The results indicated that fenofibrate treatments significantly reduce the serum lipid levels in hyperlipidemia hamsters. And the group treated with fenofibrate exhibited higher levels of beneficial bacterial species associated with health, including Bacteroides ovatus, Bifidobacterium animalis, Bacteroides intestinalis, Allobaculum stercoricanis, Lactobacillus reuteri, and Bacteroides acidifaciens, in comparison to the HFD group. Additionally, analysis of metabolic pathways demonstrated that dietary fenofibrate significantly enhanced the biosynthesis of unsaturated fatty acids, glycerophospholipid metabolism, and pyrimidine metabolism, while reducing glyoxylate and dicarboxylate metabolism, tyrosine metabolism, tryptophan metabolism, and nonribosomal peptide structures. Furthermore, these metabolic pathway changes were associated with relative alterations in the abundance of genes from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, namely K01667, K11358, K13953, K04072, K06131, K00655, K04567, K02864, K06409, K05366, K01867, K21071, and K13292. Moreover, significant changes were observed in related to carbohydrate and antibiotic resistance, such as glycosyltransferase family 51 (GT51) as well as adeC, carA, and MexT. Conclusions: Dietary fenofibrate exerted significant effects on intestinal flora and genes related to lipid, energy, and amino acid metabolism, ultimately promoting a healthier colonic environment for the host. And these findings contribute to a better understanding of the mechanism of action of fenofibrate and provide a valuable foundation for future experimental and clinical studies, aiming to explore its practical applications. [ABSTRACT FROM AUTHOR]

Background: Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, the latter of which then helps retrieve their function based on annotated gene products, mRNA, protein, and metabolites. Within the context of a specific hypothesis, additional modalities are often included, to give host-microbiome interaction. For example, in human-associated microbiome projects, it has become increasingly common to include host immunology through flow cytometry. Whilst there are plenty of software approaches available, some that utilize marker-based and assembly-based approaches, for downstream statistical analyses, there is still a dearth of statistical tools that help consolidate all such information in a single platform. By virtue of stringent computational requirements, the statistical workflow is often passive with limited visual exploration. Results: In this study, we have developed a Java-based statistical framework (https://github.com/KociOrges/cviewer) to explore shotgun metagenomics data, which integrates seamlessly with conventional pipelines and offers exploratory as well as hypothesis-driven analyses. The end product is a highly interactive toolkit with a multiple document interface, which makes it easier for a person without specialized knowledge to perform analysis of multiomics datasets and unravel biologically relevant patterns. We have designed algorithms based on frequently used numerical ecology and machine learning principles, with value-driven from integrated omics tools which not only find correlations amongst different datasets but also provide discrimination based on case–control relationships. Conclusions: CViewer was used to analyse two distinct metagenomic datasets with varying complexities. These include a dietary intervention study to understand Crohn's disease changes during a dietary treatment to include remission, as well as a gut microbiome profile for an obesity dataset comparing subjects who suffer from obesity of different aetiologies and against controls who were lean. Complete analyses of both studies in CViewer then provide very powerful mechanistic insights that corroborate with the published literature and demonstrate its full potential. EDLr-6-tH-9CdVCxoa6z_8 Video Abstract [ABSTRACT FROM AUTHOR]

Background: Population stratification based on interindividual variability in gut microbiota composition has revealed the existence of several ecotypes named enterotypes in humans and various animal species. Enterotypes are often associated with environmental factors including diet, but knowledge of the role of host genetics remains scarce. Moreover, enterotypes harbor functionalities likely associated with varying abilities and susceptibilities of their host. Previously, we showed that under controlled conditions, 60-day-old pig populations consistently split into two enterotypes with either Prevotella and Mitsuokella (PM enterotype) or Ruminococcus and Treponema (RT enterotype) as keystone taxa. Here, our aim was to rely on pig as a model to study the influence of host genetics to assemble enterotypes, and to provide clues on enterotype functional differences and their links with growth traits. Results: We established two pig lines contrasted for abundances of the genera pairs specifying each enterotype at 60 days of age and assessed them for fecal microbiota composition and growth throughout three consecutive generations. Response to selection across three generations revealed, per line, an increase in the prevalence of the selected enterotype and in the average relative abundances of directly and indirectly selected bacterial genera. The PM enterotype was found less diverse than the RT enterotype but more efficient for piglet growth during the post-weaning period. Shotgun metagenomics revealed differentially abundant bacterial species between the two enterotypes. By using the KEGG Orthology database, we show that functions related to starch degradation and polysaccharide metabolism are enriched in the PM enterotype, whereas functions related to general nucleoside transport and peptide/nickel transport are enriched in the RT enterotype. Our results also suggest that the PM and RT enterotypes might differ in the metabolism of valine, leucin, and isoleucine, favoring their biosynthesis and degradation, respectively. Conclusion: We experimentally demonstrated that enterotypes are functional ecosystems that can be selected as a whole by exerting pressure on the host genetics. We also highlight that holobionts should be considered as units of selection in breeding programs. These results pave the way for a holistic use of host genetics, microbiota diversity, and enterotype functionalities to understand holobiont shaping and adaptation. 4B2VhAArUR-Phf8Fa7EFRX Video Abstract [ABSTRACT FROM AUTHOR]

Background: Virome studies on birds, including chickens are relatively scarce, particularly from the African continent. Despite the continuous evolution of RNA viruses and severe losses recorded in poultry from seasonal viral outbreaks, the information on RNA virome composition is even scantier as a result of their highly unstable nature, genetic diversity, and difficulties associated with characterization. Also, information on factors that may modulate the occurrence of some viruses in birds is limited, particularly for domesticated birds. Viral metagenomics through advancements in sequencing technologies, has enabled the characterization of the entire virome of diverse host species using various samples. Methods: The complex RNA viral constituents present in 27 faecal samples of asymptomatic chickens from a South African farm collected at 3-time points from two independent seasons were determined, and the impact of the chicken's age and collection season on viral abundance and diversity was further investigated. The study utilized the non-invasive faecal sampling method, mRNA viral targeted enrichment steps, a whole transcriptome amplification strategy, Illumina sequencing, and bioinformatics tools. Results: The results obtained revealed a total of 48 viral species spanning across 11 orders, 15 families and 21 genera. Viral RNA families such as Coronaviridae, Picornaviridae, Reoviridae, Astroviridae, Caliciviridae, Picorbirnaviridae and Retroviridae were abundant, among which picornaviruses, demonstrated a 100% prevalence across the three age groups (2, 4 and 7 weeks) and two seasons (summer and winter) of the 27 faecal samples investigated. A further probe into the extent of variation between the different chicken groups investigated indicated that viral diversity and abundance were significantly influenced by age (P = 0.01099) and season (P = 0.00099) between chicken groups, while there was no effect on viral shedding within samples in a group (alpha diversity) for age (P = 0.146) and season (P = 0.242). Conclusion: The presence of an exceedingly varied chicken RNA virome, encompassing avian, mammalian, fungal, and dietary-associated viruses, underscores the complexities inherent in comprehending the causation, dynamics, and interspecies transmission of RNA viruses within the investigated chicken population. Hence, chickens, even in the absence of discernible symptoms, can harbour viruses that may exhibit opportunistic, commensal, or pathogenic characteristics. [ABSTRACT FROM AUTHOR]

Background: Malassezia restricta, a lipophilic and lipodependent yeast belonging to the basidiomycetes group, is an opportunistic fungal pathogen associated with various skin diseases, including seborrheic dermatitis and dandruff. Typically, Malassezia infection in neonates manifests as fungemia or hematogenous dissemination to the bone or lungs. However, vertebral osteomyelitis caused by these fungi is rarely reported owing to non-specific clinical presentations and laboratory/imaging findings. The Pathogen Metagenomics Sequencing (PMseq) technique enables direct high-throughput sequencing of infected specimens, facilitating the rapid and accurate detection of all microorganisms in clinical samples through comprehensive reports. Case presentation: A 52-year-old male was admitted to our hospital on July 20, 2022 with a 3-month history of ambulatory difficulties and localized low back pain. Magnetic Resonance Imaging (MRI) examination of the spinal column revealed irregular bone destruction affecting the L2, L3, and L5 vertebral bodies. Additionally, low T1 and high T2 intensity lesions were observed at the intervertebral discs between L3 and L5. The presumptive diagnosis of tuberculous spondylitis was made based on the imaging findings, despite negative results in all mycobacterium tests. However, the patient exhibited no improvement after receiving regular anti-tuberculosis treatment for 3 months. Subsequent MRI revealed an expansive abnormal signal within the vertebral body, leading to progressive bone destruction. The absence of spinal tuberculosis or other infective microorganisms was confirmed through culture from blood and pathological tissue from the L4 vertebral body. Subsequently, PMseq was performed on the specimens, revealing M. restricta as the predominant pathogen with the highest relative abundance value. The pathological examination revealed the presence of fungal mycelium in the L4 vertebral body, with positive findings on periodic Schiff-methenamine and periodic acid-Schiff staining. The anti-tuberculosis treatment was discontinued, and an antifungal combination of fluconazole and voriconazole was administered. All symptoms were resolved after 7 consecutive months of treatment, and the patient was able to ambulate autonomously. Vertebral lesions were reduced on MRI during the 13-month follow-up. Conclusions: M. restricta is not a commonly recognized pathogen associated with infectious vertebral osteomyelitis. However, PMseq can aid in diagnosis, timely treatment, and decision making for some non-specific infectious diseases. [ABSTRACT FROM AUTHOR]

Background: The emergence of metagenomic next-generation sequencing (mNGS) may provide a promising tool for early and comprehensive identification of the causative pathogen in community-acquired pneumonia (CAP). In this study, we aim to further evaluate the etiological diagnostic value of mNGS in suspected CAP. Methods: A total of 555 bronchoalveolar lavage fluid (BALF) samples were collected for pathogen detection by mNGS from 541 patients with suspected CAP. The clinical value was assessed based on infection diagnosis and treatment guidance. The diagnostic performance for pathogen identification by mNGS and sputum culture and for tuberculosis (TB) by mNGS and X-pert MTB/RIF were compared. To evaluate the potential for treatment guidance, we analyzed the treatment regimen of patients with suspected CAP, including imaging changes of lung after empirical antibacterial therapy, intensified regimen, antifungal treatment, and a 1-year follow up for patients with unconfirmed diagnosis and non-improvement imaging after anti-infective treatment and patients with high suspicion of TB or NTM infection who were transferred to the Wuhan Pulmonary Hospital for further diagnosis and even anti-mycobacterium therapy. Results: Of the 516 BALF samples that were analyzed by both mNGS and sputum culture, the positivity rate of mNGS was significantly higher than that of sputum culture (79.1% vs. 11.4%, P = 0.001). A total of 48 samples from patients with confirmed TB were analyzed by both mNGS and X-pert MTB/RIF, and the sensitivity of mNGS for the diagnosis of active TB was significantly lower than that of X-pert MTB/RIF (64.6% vs. 85.4%, P = 0.031). Of the 106 pathogen-negative cases, 48 were ultimately considered non-infectious diseases, with a negative predictive value of 45.3%. Of the 381 pathogen-positive cases, 311 were eventually diagnosed as CAP, with a positive predictive value of 81.6%. A total of 487 patients were included in the evaluation of the therapeutic effect, and 67.1% improved with initial empirical antibiotic treatment. Of the 163 patients in which bacteria were detected, 77.9% improved with antibacterial therapy; of the 85 patients in which fungi were detected, 12.9% achieved remission after antifungal therapy. Conclusions: Overall, mNGS had unique advantages in the detection of suspected CAP pathogens. However, mNGS was not superior to X-pert MTB/RIF for the diagnosis of TB. In addition, mNGS was not necessary as a routine test for all patients admitted with suspected CAP. Furthermore, when fungi are detected by mNGS, antifungal therapy should be cautious. [ABSTRACT FROM AUTHOR]

Heimdallarchaeia is a class of the Asgardarchaeota, are the most probable candidates for the archaeal protoeukaryote ancestor that have been identified to date. However, little is known about their life habits regardless of their ubiquitous distribution in diverse habitats, which is especially true for Heimdallarchaeia from deep-sea environments. In this study, we obtained 13 metagenome-assembled genomes (MAGs) of Heimdallarchaeia from the deep-sea cold seep and hydrothermal vent. These MAGs belonged to orders o_Heimdallarchaeales and o_JABLTI01, and most of them (9 MAGs) come from the family f_Heimdallarchaeaceae according to genome taxonomy database (GTDB). These are enriched for common eukaryote-specific signatures. Our results show that these Heimdallarchaeia have the metabolic potential to reduce sulfate (assimilatory) and nitrate (dissimilatory) to sulfide and ammonia, respectively, suggesting a previously unappreciated role in biogeochemical cycling. Furthermore, we find that they could perform both TCA and rTCA pathways coupled with pyruvate metabolism for energy conservation, fix CO2 and generate organic compounds through an atypical Wood-Ljungdahl pathway. In addition, many genes closely associated with bacteriochlorophyll and carotenoid biosynthesis, and oxygen-dependent metabolic pathways are identified in these Heimdallarchaeia MAGs, suggesting a potential light-utilization by pigments and microoxic lifestyle. Taken together, our results indicate that Heimdallarchaeia possess a mixotrophic lifestyle, which may give them more flexibility to adapt to the harsh deep-sea conditions. [ABSTRACT FROM AUTHOR]

Modern broiler breeds allow for high feed efficiency and rapid growth, which come at a cost of increased susceptibility to pathogens and disease. Broiler growth rate, feed efficiency, and health are affected by the composition of the gut microbiota, which in turn is influenced by diet. In this study, we therefore assessed how diet composition can affect the broiler jejunal gut microbiota. A total of 96 broiler chickens were divided into four diet groups: control, coated butyrate supplementation, medium-chain fatty acid supplementation, or a high-fibre low-protein content. Diet groups were sub-divided into age groups (4, 12 and 33 days of age) resulting in groups of 8 broilers per diet per age. The jejunum content was used for metagenomic shotgun sequencing to determine the microbiota taxonomic composition at species level. The composed diets resulted in a total of 104 differentially abundant bacterial species. Most notably were the butyrate-induced changes in the jejunal microbiota of broilers 4 days post-hatch, resulting in the reduced relative abundance of mainly Enterococcus faecium (-1.8 l2fc, Padj = 9.9E-05) and the opportunistic pathogen Enterococcus hirae (-2.9 l2fc, Padj = 2.7E-08), when compared to the control diet. This effect takes place during early broiler development, which is critical for broiler health, thus exemplifying the importance of how diet can influence the microbiota composition in relation to broiler health. Future studies should therefore elucidate how diet can be used to promote a beneficial microbiota in the early stages of broiler development. [ABSTRACT FROM AUTHOR]

Background: Microbial adaptation to salinity has been a classic inquiry in the field of microbiology. It has been demonstrated that microorganisms can endure salinity stress via either the "salt-in" strategy, involving inorganic ion uptake, or the "salt-out" strategy, relying on compatible solutes. While these insights are mostly based on laboratory-cultured isolates, exploring the adaptive mechanisms of microorganisms within natural salinity gradient is crucial for gaining a deeper understanding of microbial adaptation in the estuarine ecosystem. Results: Here, we conducted metagenomic analyses on filtered surface water samples collected from a typical subtropical short residence-time estuary and categorized them by salinity into low-, intermediate-, and high-salinity metagenomes. Our findings highlighted salinity-driven variations in microbial community composition and function, as revealed through taxonomic and Clusters of Orthologous Group (COG) functional annotations. Through metagenomic binning, 127 bacterial and archaeal metagenome-assembled genomes (MAGs) were reconstructed. These MAGs were categorized as stenohaline—specific to low-, intermediate-, or high-salinity—based on the average relative abundance in one salinity category significantly exceeding those in the other two categories by an order of magnitude. Those that did not meet this criterion were classified as euryhaline, indicating a broader range of salinity tolerance. Applying the Boruta algorithm, a machine learning-based feature selection method, we discerned important genomic features from the stenohaline bacterial MAGs. Of the total 12,162 COGs obtained, 40 were identified as important features, with the "inorganic ion transport and metabolism" COG category emerging as the most prominent. Furthermore, eight COGs were implicated in microbial osmoregulation, of which four were related to the "salt-in" strategy, three to the "salt-out" strategy, and one to the regulation of water channel activity. COG0168, annotated as the Trk-type K+ transporter related to the "salt-in" strategy, was ranked as the most important feature. The relative abundance of COG0168 was observed to increase with rising salinity across metagenomes, the stenohaline strains, and the dominant Actinobacteriota and Proteobacteria phyla. Conclusions: We demonstrated that salinity exerts influences on both the taxonomic and functional profiles of the microbial communities inhabiting the estuarine ecosystem. Our findings shed light on diverse salinity adaptation strategies employed by the estuarine microbial communities, highlighting the crucial role of the "salt-in" strategy mediated by Trk-type K+ transporters for microorganisms thriving under osmotic stress in the short residence-time estuary. 22YT9hkSS5Zn-gk-qyndrE Video Abstract [ABSTRACT FROM AUTHOR]

Background: To better understand the influence of habitat on the genetic content of bacteria, with a focus on members of Candidate Phyla Radiation (CPR) bacteria, we studied the effects of transitioning from soil via seepage waters to groundwater on genomic composition of ultra-small Parcubacteria, the dominating CPR class in seepage waters, using genome resolved metagenomics. Results: Bacterial metagenome-assembled genomes (MAGs), (318 total, 32 of Parcubacteria) were generated from seepage waters and compared directly to groundwater counterparts. The estimated average genome sizes of members of major phyla Proteobacteria, Bacteroidota and Cand. Patescibacteria (Candidate Phyla Radiation – CPR bacteria) were significantly higher in soil-seepage water as compared to their groundwater counterparts. Seepage water Parcubacteria (Paceibacteria) exhibited 1.18-fold greater mean genome size and 2-fold lower mean proportion of pseudogenes than those in groundwater. Bacteroidota and Proteobacteria also showed a similar trend of reduced genomes in groundwater compared to seepage. While exploring gene loss and adaptive gains in closely related CPR lineages in groundwater, we identified a membrane protein, and a lipoglycopeptide resistance gene unique to a seepage Parcubacterium genome. A nitrite reductase gene was also identified and was unique to the groundwater Parcubacteria genomes, likely acquired from other planktonic microbes via horizontal gene transfer. Conclusions: Overall, our data suggest that bacteria in seepage waters, including ultra-small Parcubacteria, have significantly larger genomes and higher metabolic enrichment than their groundwater counterparts, highlighting possible genome streamlining of the latter in response to habitat selection in an oligotrophic environment. [ABSTRACT FROM AUTHOR]

Introduction: Lower respiratory tract infections(LRTIs) in adults are complicated by diverse pathogens that challenge traditional detection methods, which are often slow and insensitive. Metagenomic next-generation sequencing (mNGS) offers a comprehensive, high-throughput, and unbiased approach to pathogen identification. This retrospective study evaluates the diagnostic efficacy of mNGS compared to conventional microbiological testing (CMT) in LRTIs, aiming to enhance detection accuracy and enable early clinical prediction. Methods: In our retrospective single-center analysis, 451 patients with suspected LRTIs underwent mNGS testing from July 2020 to July 2023. We assessed the pathogen spectrum and compared the diagnostic efficacy of mNGS to CMT, with clinical comprehensive diagnosis serving as the reference standard. The study analyzed mNGS performance in lung tissue biopsies and bronchoalveolar lavage fluid (BALF) from cases suspected of lung infection. Patients were stratified into two groups based on clinical outcomes (improvement or mortality), and we compared clinical data and conventional laboratory indices between groups. A predictive model and nomogram for the prognosis of LRTIs were constructed using univariate followed by multivariate logistic regression, with model predictive accuracy evaluated by the area under the ROC curve (AUC). Results: (1) Comparative Analysis of mNGS versus CMT: In a comprehensive analysis of 510 specimens, where 59 cases were concurrently collected from lung tissue biopsies and BALF, the study highlights the diagnostic superiority of mNGS over CMT. Specifically, mNGS demonstrated significantly higher sensitivity and specificity in BALF samples (82.86% vs. 44.42% and 52.00% vs. 21.05%, respectively, p < 0.001) alongside greater positive and negative predictive values (96.71% vs. 79.55% and 15.12% vs. 5.19%, respectively, p < 0.01). Additionally, when comparing simultaneous testing of lung tissue biopsies and BALF, mNGS showed enhanced sensitivity in BALF (84.21% vs. 57.41%), whereas lung tissues offered higher specificity (80.00% vs. 50.00%). (2) Analysis of Infectious Species in Patients from This Study: The study also notes a concerning incidence of lung abscesses and identifies Epstein-Barr virus (EBV), Fusobacterium nucleatum, Mycoplasma pneumoniae, Chlamydia psittaci, and Haemophilus influenzae as the most common pathogens, with Klebsiella pneumoniae emerging as the predominant bacterial culprit. Among herpes viruses, EBV and herpes virus 7 (HHV-7) were most frequently detected, with HHV-7 more prevalent in immunocompromised individuals. (3) Risk Factors for Adverse Prognosis and a Mortality Risk Prediction Model in Patients with LRTIs: We identified key risk factors for poor prognosis in lower respiratory tract infection patients, with significant findings including delayed time to mNGS testing, low lymphocyte percentage, presence of chronic lung disease, multiple comorbidities, false-negative CMT results, and positive herpesvirus affecting patient outcomes. We also developed a nomogram model with good consistency and high accuracy (AUC of 0.825) for predicting mortality risk in these patients, offering a valuable clinical tool for assessing prognosis. Conclusion: The study underscores mNGS as a superior tool for lower respiratory tract infection diagnosis, exhibiting higher sensitivity and specificity than traditional methods. [ABSTRACT FROM AUTHOR]

Background: Aquaculture is an important food source worldwide. The extensive use of antibiotics in intensive large-scale farms has resulted in resistance development. Non-intensive aquaculture is another aquatic feeding model that is conducive to ecological protection and closely related to the natural environment. However, the transmission of resistomes in non-intensive aquaculture has not been well characterized. Moreover, the influence of aquaculture resistomes on human health needs to be further understood. Here, metagenomic approach was employed to identify the mobility of aquaculture resistomes and estimate the potential risks to human health. Results: The results demonstrated that antibiotic resistance genes (ARGs) were widely present in non-intensive aquaculture systems and the multidrug type was most abundant accounting for 34%. ARGs of non-intensive aquaculture environments were mainly shaped by microbial communities accounting for 51%. Seventy-seven genera and 36 mobile genetic elements (MGEs) were significantly associated with 23 ARG types (p < 0.05) according to network analysis. Six ARGs were defined as core ARGs (top 3% most abundant with occurrence frequency > 80%) which occupied 40% of ARG abundance in fish gut samples. Seventy-one ARG-carrying contigs were identified and 75% of them carried MGEs simultaneously. The qacEdelta1 and sul1 formed a stable combination and were detected simultaneously in aquaculture environments and humans. Additionally, 475 high-quality metagenomic-assembled genomes (MAGs) were recovered and 81 MAGs carried ARGs. The multidrug and bacitracin resistance genes were the most abundant ARG types carried by MAGs. Strikingly, Fusobacterium_A (opportunistic human pathogen) carrying ARGs and MGEs were identified in both the aquaculture system and human guts, which indicated the potential risks of ARG transfer. Conclusions: The mobility and pathogenicity of aquaculture resistomes were explored by a metagenomic approach. Given the observed co-occurrence of resistomes between the aquaculture environment and human, more stringent regulation of resistomes in non-intensive aquaculture systems may be required. 4-S8N7kaEyTj6WBvQ6hX9p Video Abstract [ABSTRACT FROM AUTHOR]

Background: Emerging evidence has indicated a link between the gut microbiota and acute lymphoblastic leukaemia (ALL). However, the acute changes in gut microbiota during chemotherapy and the predictive value of baseline gut microbiota in infectious complication remain largely unknown. Methods: Faecal samples (n = 126) from children with ALL (n = 49) undergoing induction chemotherapy were collected at three timepoints, i.e., initiation of chemotherapy (baseline, T0), 7 days (T1) and 33 days (T2) after initiation of chemotherapy. Gut microbiome profile was performed via metagenomic shotgun sequencing. The bioBakery3 pipeline (Kneaddata, Metaphlan 3 and HUMAnN) was performed to assign taxonomy and functional annotations. Gut microbiome at T0 were used to predict infection during chemotherapy. Results: The microbial diversities and composition changed significantly during chemotherapy, with Escherichia coli, Klebsiella pneumoniae and Bifidobacterium longum being the most prominent species. The microbial metabolic pathways were also significantly altered during chemotherapy, including the pathway of pyruvate fermentation to acetate and lactate, and assimilatory sulfate reduction pathway. The receiver operating characteristic (ROC) models based on Bifidobacterium longum at T0 could predict infectious complications during the first month of chemotherapy with the area under the curve (AUC) of 0.720. Conclusions: Our study provides new insights into the acute changes in microbial and functional characteristics in children with ALL during chemotherapy. The baseline gut microbiota could be potential biomarkers for infections during chemotherapy. Trial registration: The study was approved by the Ethics Committee of Zhujiang Hospital, Southern Medical University (2021-KY-171-01) and registered on http://www.chictr.org.cn (ChiCTR2200065406, Registration Date: November 4, 2022). [ABSTRACT FROM AUTHOR]

Background: Legionella pneumonia is one of the most severe types of atypical pneumonia, impairing multiple organ systems, posing a threat to life. Diagnosing Legionella pneumonia is challenging due to difficulties in culturing the bacteria and limitations in immunoassay sensitivity and specificity. Case presentation: This paper reports a rare case of sepsis caused by combined infection with Legionella pneumophila and Fusobacterium necrophorum, leading to respiratory failure, acute kidney injury, acute liver injury, myocardial damage, and electrolyte disorders. In addition, we systematically reviewed literature on patients with combined Legionella infections, analyzing their clinical features, laboratory results and diagnosis. Conclusions: For pathogens that require prolonged incubation periods and are less sensitive to conventional culturing methods, metagenomic next-generation sequencing (mNGS) can be a powerful supplement to pathogen screening and plays a significant role in the auxiliary diagnosis of complex infectious diseases. [ABSTRACT FROM AUTHOR]