Metagenomic perspectives on antibiotic resistance genes in tap water: The environmental characteristic, potential mobility and health threat.

As an emerging environmental contaminant, antibiotic resistance genes (ARGs) in tap water have attracted great attention. Although studies have provided ARG profiles in tap water, research on their abundance levels, composition characteristics, and potential threat is still insufficient. Here, 9 household tap water samples were collected from the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. Additionally, 75 sets of environmental sample data (9 types) were downloaded from the public database. Metagenomics was then performed to explore the differences in the abundance and composition of ARGs. 221 ARG subtypes consisting of 17 types were detected in tap water. Although the ARG abundance in tap water was not significantly different from that found in drinking water plants and reservoirs, their composition varied. In tap water samples, the three most abundant classes of resistance genes were multidrug, fosfomycin and MLS (macrolide-lincosamide-streptogramin) ARGs, and their corresponding subtypes ompR, fosX and macB were also the most abundant ARG subtypes. Regarding the potential mobility, vanS had the highest abundance on plasmids and viruses, but the absence of key genes rendered resistance to vancomycin ineffective. Generally, the majority of ARGs present in tap water were those that have not been assessed and are currently not listed as high-threat level ARG families based on the World Health Organization Guideline. Although the current potential threat to human health posed by ARGs in tap water is limited, with persistent transfer and accumulation, especially in pathogens, the potential danger to human health posed by ARGs should not be ignored.

Metagenomic Analysis of Rhizospheric Bacterial Community of Citrus Trees Expressing Phloem-Directed Antimicrobials.

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

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

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

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

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

Application of metagenomic next-generation sequencing for rapid molecular identification in spinal infection diagnosis.

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

Metagenomic analysis reveals altered gut virome and diagnostic potential in pancreatic cancer.

Pancreatic cancer (PC) is a highly aggressive malignancy with a poor prognosis, making early diagnosis crucial for improving patient outcomes. While the gut microbiome, including bacteria and viruses, is believed to be essential in cancer pathogenicity, the potential contribution of the gut virome to PC remains largely unexplored. In this study, we conducted a comparative analysis of the gut viral compositional and functional profiles between PC patients and healthy controls, based on fecal metagenomes from two publicly available data sets comprising a total of 101 patients and 82 healthy controls. Our results revealed a decreasing trend in the gut virome diversity of PC patients with disease severity. We identified significant alterations in the overall viral structure of PC patients, with a meta-analysis revealing 219 viral operational taxonomic units (vOTUs) showing significant differences in relative abundance between patients and healthy controls. Among these, 65 vOTUs were enriched in PC patients, and 154 were reduced. Host prediction revealed that PC-enriched vOTUs preferentially infected bacterial members of Veillonellaceae, Enterobacteriaceae, Fusobacteriaceae, and Streptococcaceae, while PC-reduced vOTUs were more likely to infect Ruminococcaceae, Lachnospiraceae, Clostridiaceae, Oscillospiraceae, and Peptostreptococcaceae. Furthermore, we constructed random forest models based on the PC-associated vOTUs, achieving an optimal average area under the curve (AUC) of up to 0.879 for distinguishing patients from controls. Through additional 10 public cohorts, we demonstrated the reproducibility and high specificity of these viral signatures. Our study suggests that the gut virome may play a role in PC development and could serve as a promising target for PC diagnosis and therapeutic intervention. Future studies should further explore the underlying mechanisms of gut virus-bacteria interactions and validate the diagnostic models in larger and more diverse populations.

Investigations of microbiota composition and neuroactive pathways in association with symptoms of stress and depression in a cohort of healthy women.

Background: Despite mounting evidence of gut-brain involvement in psychiatric conditions, functional data remain limited, and analyses of other microbial niches, such as the vaginal microbiota, are lacking in relation to mental health. This aim of this study was to investigate if the connections between the gut microbiome and mental health observed in populations with a clinical diagnosis of mental illness extend to healthy women experiencing stress and depressive symptoms. Additionally, this study examined the functional pathways of the gut microbiota according to the levels of psychological symptoms. Furthermore, the study aimed to explore potential correlations between the vaginal microbiome and mental health parameters in young women without psychiatric diagnoses. Methods: In this cross-sectional study, 160 healthy Danish women (aged 18-40 years) filled out questionnaires with validated scales measuring symptoms of stress and depression and frequency of dietary intake. Fecal and vaginal microbiota samples were collected at the beginning of the menstrual cycle and vaginal samples were also collected at cycle day 8-12 and 18-22. Shotgun metagenomic profiling of the gut and vaginal microbiome was performed. The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for functional profiling and 56 Gut Brain Modules were analyzed in the fecal samples. Results: The relative abundance in the gut of the genera Escherichia, Parabacteroides, and Shigella was higher in women with elevated depressive symptoms. Women with high perceived stress showed a tendency of increased abundance of Escherichia, Shigella, and Blautia. Amongst others, the potentially pathogenic genera, Escherichia and Shigella correlate with alterations in the neuroactive pathways such as the glutamatergic, GABAeric, dopaminergic, and Kynurenine pathways. Vaginosis symptoms were more prevalent in women reporting high levels of stress and depressive symptoms. Conclusions: The findings of this study support the concept of a microbiota-associated effect on the neuroactive pathways even in healthy young women. This suggest, that targeting the gut microbiome could be a promising approach for future psychiatric interventions.

Clinical diagnostic value of targeted next­generation sequencing for infectious diseases (Review).

As sequencing technology transitions from research to clinical settings, due to technological maturity and cost reductions, metagenomic next­generation sequencing (mNGS) is increasingly used. This shift underscores the growing need for more cost­effective and universally accessible sequencing assays to improve patient care and public health. Therefore, targeted NGS (tNGS) is gaining prominence. tNGS involves enrichment of target pathogens in patient samples based on multiplex PCR amplification or probe capture with excellent sensitivity. It is increasingly used in clinical diagnostics due to its practicality and efficiency. The present review compares the principles of different enrichment methods. The high positivity rate of tNGS in the detection of pathogens was found in respiratory samples with specific instances. tNGS maintains high sensitivity (70.8­95.0%) in samples with low pathogen loads, including blood and cerebrospinal fluid. Furthermore, tNGS is effective in detecting drug­resistant strains of Mycobacterium tuberculosis, allowing identification of resistance genes and guiding clinical treatment decisions, which is difficult to achieve with mNGS. In the present review, the application of tNGS in clinical settings and its current limitations are assessed. The continued development of tNGS has the potential to refine diagnostic accuracy and treatment efficacy and improving infectious disease management. However, further research to overcome technical challenges such as workflow time and cost is required.

VirRep: a hybrid language representation learning framework for identifying viruses from human gut metagenomes.

Identifying viruses from metagenomes is a common step to explore the virus composition in the human gut. Here, we introduce VirRep, a hybrid language representation learning framework, for identifying viruses from human gut metagenomes. VirRep combines a context-aware encoder and an evolution-aware encoder to improve sequence representation by incorporating k-mer patterns and sequence homologies. Benchmarking on both simulated and real datasets with varying viral proportions demonstrates that VirRep outperforms state-of-the-art methods. When applied to fecal metagenomes from a colorectal cancer cohort, VirRep identifies 39 high-quality viral species associated with the disease, many of which cannot be detected by existing methods.

A powerful machine learning approach to identify interactions of differentially abundant gut microbial subsets in patients with metastatic and non-metastatic pancreatic cancer.

Pancreatic cancer has a dismal prognosis, as it is often diagnosed at stage IV of the disease and is characterized by metastatic spread. Gut microbiota and its metabolites have been suggested to influence the metastatic spread by modulating the host immune system or by promoting angiogenesis. To date, the gut microbial profiles of metastatic and non-metastatic patients need to be explored. Taking advantage of the 16S metagenomic sequencing and the PEnalized LOgistic Regression Analysis (PELORA) we identified clusters of bacteria with differential abundances between metastatic and non-metastatic patients. An overall increase in Gram-negative bacteria in metastatic patients compared to non-metastatic ones was identified using this method. Furthermore, to gain more insight into how gut microbes can predict metastases, a machine learning approach (iterative Random Forest) was performed. Iterative Random Forest analysis revealed which microorganisms were characterized by a different level of relative abundance between metastatic and non-metastatic patients and established a functional relationship between the relative abundance and the probability of having metastases. At the species level, the following bacteria were found to have the highest discriminatory power: Anaerostipes hadrus, Coprobacter secundus, Clostridium sp. 619, Roseburia inulinivorans, Porphyromonas and Odoribacter at the genus level, and Rhodospirillaceae, Clostridiaceae and Peptococcaceae at the family level. Finally, these data were intertwined with those from a metabolomics analysis on fecal samples of patients with or without metastasis to better understand the role of gut microbiota in the metastatic process. Artificial intelligence has been applied in different areas of the medical field. Translating its application in the field of gut microbiota analysis may help fully exploit the potential information contained in such a large amount of data aiming to open up new supportive areas of intervention in the management of cancer.

gNOMO2: a comprehensive and modular pipeline for integrated multi-omics analyses of microbiomes.

BACKGROUND: In recent years, omics technologies have offered an exceptional chance to gain a deeper insight into the structural and functional characteristics of microbial communities. As a result, there is a growing demand for user-friendly, reproducible, and versatile bioinformatic tools that can effectively harness multi-omics data to provide a holistic understanding of microbiomes. Previously, we introduced gNOMO, a bioinformatic pipeline tailored to analyze microbiome multi-omics data in an integrative manner. In response to the evolving demands within the microbiome field and the growing necessity for integrated multi-omics data analysis, we have implemented substantial enhancements to the gNOMO pipeline. RESULTS: Here, we present gNOMO2, a comprehensive and modular pipeline that can seamlessly manage various omics combinations, ranging from 2 to 4 distinct omics data types, including 16S ribosomal RNA (rRNA) gene amplicon sequencing, metagenomics, metatranscriptomics, and metaproteomics. Furthermore, gNOMO2 features a specialized module for processing 16S rRNA gene amplicon sequencing data to create a protein database suitable for metaproteomics investigations. Moreover, it incorporates new differential abundance, integration, and visualization approaches, enhancing the toolkit for a more insightful analysis of microbiomes. The functionality of these new features is showcased through the use of 4 microbiome multi-omics datasets encompassing various ecosystems and omics combinations. gNOMO2 not only replicated most of the primary findings from these studies but also offered further valuable perspectives. CONCLUSIONS: gNOMO2 enables the thorough integration of taxonomic and functional analyses in microbiome multi-omics data, offering novel insights in both host-associated and free-living microbiome research. gNOMO2 is available freely at https://github.com/muzafferarikan/gNOMO2.

Nitrifying niche in estuaries is expanded by the plastisphere.

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

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

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

Metagenomic next-generation sequencing promotes diagnosis and treatment of Pneumocystis jirovecii pneumonia in non-HIV infected children: a retrospective study.

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-ß-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.

Integrative metagenomic, transcriptomic, and proteomic analysis reveal the microbiota-host interplay in early-stage lung adenocarcinoma among non-smokers.

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.

Comprehensive analysis of key host gene-microbe networks in the cecum tissues of the obese rabbits induced by a high-fat diet.

The Cecum is a key site for cellulose digestion in nutrient metabolism of intestine, but its mechanisms of microbial and gene interactions has not been fully elucidated during pathogenesis of obesity. Therefore, the cecum tissues of the New Zealand rabbits and their contents between the high-fat diet-induced group (Ob) and control group (Co) were collected and analyzed using multi-omics. The metagenomic analysis indicated that the relative abundances of Corallococcus_sp._CAG:1435 and Flavobacteriales bacterium species were significantly lower, while those of Akkermansia glycaniphila, Clostridium_sp._CAG:793, Mycoplasma_sp._CAG:776, Mycoplasma_sp._CAG:472, Clostridium_sp._CAG:609, Akkermansia_sp._KLE1605, Clostridium_sp._CAG:508, and Firmicutes_bacterium_CAG:460 species were significantly higher in the Ob as compared to those in Co. Transcriptomic sequencing results showed that the differentially upregulated genes were mainly enriched in pathways, including calcium signaling pathway, PI3K-Akt signaling pathway, and Wnt signaling pathway, while the differentially downregulated genes were mainly enriched in pathways of NF-kappaB signaling pathway and T cell receptor signaling pathway. The comparative analysis of metabolites showed that the glycine, serine, and threonine metabolism and cysteine and methionine metabolism were the important metabolic pathways between the two groups. The combined analysis showed that CAMK1, IGFBP6, and IGFBP4 genes were highly correlated with Clostridium_sp._CAG:793, and Akkermansia_glycaniphila species. Thus, the preliminary study elucidated the microbial and gene interactions in cecum of obese rabbit and provided a basis for further studies in intestinal intervention for human obesity.

No evidence on infectious DNA-based agents in pediatric acute lymphoblastic leukemia using whole metagenome shotgun sequencing.

The etiology of pediatric acute lymphatic leukemia (ALL) is still unclear. Whole-metagenome shotgun sequencing of bone marrow samples in patients with treatment-naïve ALL (n=6) was performed for untargeted investigation of bacterial and viral DNA. The control group consisted of healthy children (n=4) and children with non-oncologic diseases (n=2) undergoing bone marrow sampling. Peripheral blood of all participants was investigated at the same time. After bioinformatical elimination of potential contaminants by comparison with the employed controls, no significant amounts of microbial or viral DNA were identified.

Helicobacter pylori infection alters gastric microbiota structure and biological functions in patients with gastric ulcer or duodenal ulcer.

BACKGROUND: Helicobacter pylori (H. pylori) infection is closely associated with gastrointestinal diseases. Our preliminary studies have indicated that H. pylori infection had a significant impact on the mucosal microbiome structure in patients with gastric ulcer (GU) or duodenal ulcer (DU). AIM: To investigate the contributions of H. pylori infection and the mucosal microbiome to the pathogenesis and progression of ulcerative diseases. METHODS: Patients with H. pylori infection and either GU or DU, and healthy individuals without H. pylori infection were included. Gastric or duodenal mucosal samples was obtained and subjected to metagenomic sequencing. The compositions of the microbial communities and their metabolic functions in the mucosal tissues were analyzed. RESULTS: Compared with that in the healthy individuals, the gastric mucosal microbiota in the H. pylori-positive patients with GU was dominated by H. pylori, with significantly reduced biodiversity. The intergroup differential functions, which were enriched in the H. pylori-positive GU patients, were all derived from H. pylori, particularly those concerning transfer RNA queuosine-modification and the synthesis of demethylmenaquinones or menaquinones. A significant enrichment of the uibE gene was detected in the synthesis pathway. There was no significant difference in microbial diversity between the H. pylori-positive DU patients and healthy controls. CONCLUSION: H. pylori infection significantly alters the gastric microbiota structure, diversity, and biological functions, which may be important contributing factors for GU.

Metatranscriptomics-guided genome-scale metabolic reconstruction reveals the carbon flux and trophic interaction in methanogenic communities.

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. Video Abstract.

Fecal microbiota transplantation alters gut phage communities in a clinical trial for obesity.

BACKGROUND: Fecal microbiota transplantation (FMT) is a therapeutic intervention used to treat diseases associated with the gut microbiome. In the human gut microbiome, phages have been implicated in influencing human health, with successful engraftment of donor phages correlated with FMT treatment efficacy. The impact that gastrointestinal phages exert on human health has primarily been connected to their ability to modulate the bacterial communities in the gut. Nonetheless, how FMT affects recipients' phage populations, and in turn, how this influences the gut environment, is not yet fully understood. In this study, we investigated the effects of FMT on the phageome composition of participants within the Gut Bugs Trial (GBT), a double-blind, randomized, placebo-controlled trial that investigated the efficacy of FMT in treating obesity and comorbidities in adolescents. Stool samples collected from donors at the time of treatment and recipients at four time points (i.e., baseline and 6 weeks, 12 weeks, and 26 weeks post-intervention), underwent shotgun metagenomic sequencing. Phage sequences were identified and characterized in silico to examine evidence of phage engraftment and to assess the extent of FMT-induced alterations in the recipients' phageome composition. RESULTS: Donor phages engrafted stably in recipients following FMT, composing a significant proportion of their phageome for the entire course of the study (33.8 ± 1.2% in females and 33.9 ± 3.7% in males). Phage engraftment varied between donors and donor engraftment efficacy was positively correlated with their phageome alpha diversity. FMT caused a shift in recipients' phageome toward the donors' composition and increased phageome alpha diversity and variability over time. CONCLUSIONS: FMT significantly altered recipients' phage and, overall, microbial populations. The increase in microbial diversity and variability is consistent with a shift in microbial population dynamics. This proposes that phages play a critical role in modulating the gut environment and suggests novel approaches to understanding the efficacy of FMT in altering the recipient's microbiome. TRIAL REGISTRATION: The Gut Bugs Trial was registered with the Australian New Zealand Clinical Trials Registry (ACTR N12615001351505). Trial protocol: the trial protocol is available at https://bmjopen.bmj.com/content/9/4/e026174 . Video Abstract.