The study of longevity and its determinants has been revitalized with the rise of microbiome scholarship. The gut microbiota have been established to play essential protective, metabolic, and physiological roles in human health and disease. The gut dysbiosis has been identified as an important factor contributing to the development of multiple diseases. Accordingly, it is reasonable to hypothesize that the gut microbiota of long-living individuals have healthy antiaging-associated gut microbes, which, by extension, might provide specific molecular targets for antiaging treatments and interventions. In the present study, we compared the gut microbiota of Chinese individuals in two different age groups, long-living adults (aged over 90 years) and elderly adults (aged 65-74 years) who were free of major diseases. We found significantly lower relative abundances of bacteria in the genera Sutterella and Megamonas in the long-living individuals. Furthermore, we established that while biological processes such as autophagy (GO:0006914) and telomere maintenance through semiconservative replication (GO:0032201) were enhanced in the long-living group, response to lipopolysaccharide (GO:0032496), nicotinamide adenine dinucleotide oxidation (GO:0006116), and S-adenosyl methionine metabolism (GO:0046500) were weakened. Moreover, the two groups were found to differ with respect to amino acid metabolism. We suggest that these compositional and functional differences in the gut microbiota may potentially be associated with mechanisms that contribute to determining longevity or aging.

UNASSIGNED: This study aimed to investigate the effect of selenium on gut microbiota in mice with breast cancer under a high-fat diet.
UNASSIGNED: A total of 12 female BALB/c mice were randomly divided into two groups: 4 T1 + selenium+ high-fat diet group and 4 T1 + high-fat diet group. Mice were injected with 4 T1 cells on the right 4th mammary fat pad and kept on a high-fat diet. Fecal samples were collected, and DNA was extracted for metagenomic sequencing and bioinformatics analysis. Relevant target genes and pathways were annotated and metabolically analyzed to explore the intervention effect of selenium on breast cancer in the high-fat diet state.
UNASSIGNED: Selenium supplementation in the high-fat diet altered the composition and diversity of gut microbiota in mice with breast cancer. The gut microbial composition was significantly different in the selenium intervention group, with an increased abundance of Proteobacteria, Actinobacteria, and Verrucomicrobia phyla and species such as Helicobacter ganmani, Helicobacter japonicus, and Akkermansia muciniphila, while phyla, such as Bacteroidetes, Firmicutes, Deferribacteres, and Spirochaetes, and species, such as Prevotella sp. MGM2, Muribaculum intestinale, Lactobacillus murinus, and Prevotella sp. MGM1, were decreased. Functional analysis revealed differential expression of genes related to carbohydrate-active enzymes, pathogen-host interactions, cell communication, cell auto-induction, membrane transporters, and virulence factors. Furthermore, 37 COGs and 48 metabolites with rising metabolic potential in the selenium intervention group were predicted.
UNASSIGNED: Selenium alters the homeostasis of gut microbiota in mice with breast cancer on a high-fat diet, affecting their composition, abundance, and associated metabolism. These findings suggest that the mechanism involves interfering with gut microbiota homeostasis, leading to altered synthesis of tumor-associated proteins and fatty acids and inducing tumor cell apoptosis and pyroptosis.

BACKGROUND: Mobilization typing (MOB) is a classification scheme for plasmid genomes based on their relaxase gene. The host ranges of plasmids of different MOB categories are diverse, and MOB is crucial for investigating plasmid mobilization, especially the transmission of resistance genes and virulence factors. However, MOB typing of plasmid metagenomic data is challenging due to the highly fragmented characteristics of metagenomic contigs.
RESULTS: We developed MOBFinder, an 11-class classifier, for categorizing plasmid fragments into 10 MOB types and a nonmobilizable category. We first performed MOB typing to classify complete plasmid genomes according to relaxase information and then constructed an artificial benchmark dataset of plasmid metagenomic fragments (PMFs) from those complete plasmid genomes whose MOB types are well annotated. Next, based on natural language models, we used word vectors to characterize the PMFs. Several random forest classification models were trained and integrated to predict fragments of different lengths. Evaluating the tool using the benchmark dataset, we found that MOBFinder outperforms previous tools such as MOBscan and MOB-suite, with an overall accuracy approximately 59% higher than that of MOB-suite. Moreover, the balanced accuracy, harmonic mean, and F1-score reached up to 99% for some MOB types. When applied to a cohort of patients with type 2 diabetes (T2D), MOBFinder offered insights suggesting that the MOBF type plasmid, which is widely present in Escherichia and Klebsiella, and the MOBQ type plasmid might accelerate antibiotic resistance transmission in patients with T2D.
CONCLUSIONS: To the best of our knowledge, MOBFinder is the first tool for MOB typing of PMFs. The tool is freely available at https://github.com/FengTaoSMU/MOBFinder.

The mechanism governing sulfur cycling in nitrate reduction within sulfate-rich reservoirs during seasonal hypoxic conditions remains poorly understood. This study employs nitrogen and oxygen isotope fractionation in nitrate, along with metagenomic sequencing to elucidate the intricacies of the coupled sulfur oxidation and nitrate reduction process in the water column. In the Aha reservoir, a typical seasonally stratified water body, we observed the coexistence of denitrification, bacterial sulfide oxidation, and bacterial sulfate reduction in hypoxic conditions. This is substantiated by the presence of abundant N/S-related genes (nosZ and aprAB/dsrAB) and fluctuations in N/S species. The lower 15εNO3/18εNO3 ratio (0.60) observed in this study, compared to heterotrophic denitrification, strongly supports the occurrence of sulfur-driven denitrification. Furthermore, we found a robust positive correlation between the metabolic potential of bacterial sulfide oxidation and denitrification (p < 0.05), emphasizing the role of sulfide produced via sulfate reduction in enhancing denitrification. Sulfide-driven denitrification relied on ∑S2- as the primary electron donor preferentially oxidized by denitrification. The pivotal genus, Sulfuritalea, emerged as a central player in both denitrification and sulfide oxidation processes in hypoxic water bodies. Our study provides compelling evidence that sulfides assume a critical role in regulating denitrification in hypoxic water within an ecosystem where their contribution to the overall nitrogen cycle was previously underestimated.

UNASSIGNED: Transforming coniferous plantation into broadleaved or mixed broadleaved-coniferous plantations is the tendency of forest management strategies in subtropical China. However, the effects of this conversion on soil phosphorus (P) cycling microbial functional genes are still unknown.
UNASSIGNED: Soil samples were collected from 0-20, 20-40, and 40-60 cm (topsoil, middle layer, and subsoil, respectively) under coniferous Pinus massoniana (PM), broadleaved Erythrophleum fordii (EF), and their mixed (PM/EF) plantation in subtropical China. Used metagenomic sequencing to examine the alterations of relative abundances and molecular ecological network structure of soil P-cycling functional genes after the conversion of plantations.
UNASSIGNED: The composition of P-cycling genes in the topsoil of PM stand was significantly different from that of PM/EF and EF stands (p < 0.05), and total phosphorus (TP) was the main factor causing this difference. After transforming PM plantation into EF plantation, the relative abundances of P solubilization and mineralization genes significantly increased in the topsoil and middle layer with the decrease of soil TP content. The abundances of P-starvation response regulation genes also significantly increased in the subsoil (p < 0.05), which may have been influenced by soil organic carbon (SOC). The dominant genes in all soil layers under three plantations were phoR, glpP, gcd, ppk, and ppx. Transforming PM into EF plantation apparently increased gcd abundance in the topsoil (p < 0.05), with TP and NO3 --N being the main influencing factors. After transforming PM into PM/EF plantations, the molecular ecological network structure of P-cycling genes was more complex; moreover, the key genes in the network were modified with the transformation of PM plantation.
UNASSIGNED: Transforming PM into EF plantation mainly improved the phosphate solubilizing potential of microorganisms at topsoil, while transforming PM into PM/EF plantation may have enhanced structural stability of microbial P-cycling genes react to environmental changes.

Clubroot is a major disease and severe threat to Chinese cabbage, and it is caused by the pathogen Plasmodiophora brassicae Woron. This pathogen is an obligate biotrophic protist and can persist in soil in the form of resting spores for more than 18 years, which can easily be transmitted through a number of agents, resulting in significant economic losses to global Chinese cabbage production. Rhizosphere microbiomes play fundamental roles in the occurrence and development of plant diseases. The changes in the rhizosphere microorganisms could reveal the severity of plant diseases and provide the basis for their control. Here, we studied the rhizosphere microbiota after clubroot disease infections with different severities by employing metagenomic sequencing, with the aim of exploring the relationships between plant health, rhizosphere microbial communities, and soil environments; then, we identified potential biomarker microbes of clubroot disease. The results showed that clubroot disease severity significantly affected the microbial community composition and structure of the rhizosphere soil, and microbial functions were also dramatically influenced by it. Four different microbes that had great potential in the biocontrol of clubroot disease were identified from the obtained results; they were the genera Pseudomonas, Gemmatimonas, Sphingomonas, and Nocardioides. Soil pH, organic matter contents, total nitrogen, and cation exchange capacity were the major environmental factors modulating plant microbiome assembly. In addition, microbial environmental information processing was extremely strengthened when the plant was subjected to pathogen invasion, but weakened when the disease became serious. In particular, oxidative phosphorylation and glycerol-1-phosphatase might have critical functions in enhancing Chinese cabbage\'s resistance to clubroot disease. This work revealed the interactions and potential mechanisms among Chinese cabbage, soil environmental factors, clubroot disease, and microbial community structure and functions, which may provide a novel foundation for further studies using microbiological or metabolic methods to develop disease-resistant cultivation technologies.

BACKGROUND: Accurate evaluation of the response to preoperative treatment enables the provision of a more appropriate personalized therapeutic schedule for locally advanced rectal cancer (LARC), which remains an enormous challenge, especially neoadjuvant immunotherapy plus chemoradiotherapy (nICRT).
METHODS: This prospective, multicenter cohort study enrolled patients with LARC from 6 centers who received nICRT. The dynamic variation in the gut microbiome during nICRT was evaluated. A species-level gut microbiome prediction (SPEED) model was developed and validated to predict the pathological complete response (pCR) to nICRT.
RESULTS: A total of 50 patients were enrolled, 75 fecal samples were collected from 33 patients at different time points, and the pCR rate reached 42.4% (14/33). Lactobacillus and Eubacterium were observed to increase after nICRT. Additionally, significant differences in the gut microbiome were observed between responders and non-responders at baseline. Significantly higher abundances of Lachnospiraceaebacterium and Blautiawexlerae were found in responders, while Bacteroides, Prevotella, and Porphyromonas were found in non-responders. The SPEED model showcased a superior predictive performance with areas under the curve of 98.80% (95% confidence interval [CI]: 95.67%-100%) in the training cohort and 77.78% (95% CI: 65.42%-88.29%) in the validation cohort.
CONCLUSIONS: Programmed death 1 (PD-1) blockade plus concurrent long-course CRT showed a favorable pCR rate and is well tolerated in microsatellite-stable (MSS)/mismatch repair-proficient (pMMR) patients with LARC. The SPEED model can be used to predict the pCR to nICRT based on the baseline gut microbiome with high robustness and accuracy, thereby assisting clinical physicians in providing individualized management for patients with LARC.
BACKGROUND: This research was funded by the China National Natural Science Foundation (82202884).

BACKGROUND: Haematological patients exhibit immune system abnormalities that make them susceptible to viral infections. Understanding the relationship between the virome in the blood plasma of haematological patients and their clinical characteristic is crucial for disease management. We aimed to explore the presence of viral pathogens and identify close associations between viral infections and various clinical features.
RESULTS: A total of 21 DNA viruses and 6 RNA viruses from 12 virus families were identified from 1383 patients. Patients with haematological diseases exhibited significantly higher diversity, prevalence, and co-detection rates of viral pathogens. During fever episodes, pathogen detection was notably higher, with Epstein-Barr virus (EBV) and Mucorales infections being the most probable culprits for fever symptoms in non-haematological patients. The detection rate of torque teno virus (TTV) significantly increases in haematological patients after transplantation and during primary lung infections. Additionally, TTV-positive patients demonstrate significantly higher absolute neutrophil counts, while C-reactive protein and procalcitonin levels are notably lower. Furthermore, TTV, cytomegalovirus, and parvovirus B19 (B19V) were found to be more prevalent in non-neutropenic patients, while non-viral pathogenic infections, such as Gram-negative bacteria and Mucorales, were more common in neutropenic patients. Pegivirus C (HPgV-C) infection often occurred post-transplantation, regardless of neutropenia. Additionally, some viruses such as TTV, B19V, EBV, and HPgV-C showed preferences for age and seasonal infections.
CONCLUSIONS: Analysis of the plasma virome revealed the susceptibility of haematological patients to plasma viral infections at specific disease stages, along with the occurrence of mixed infections with non-viral pathogens. Close associations were observed between the plasma virome and various clinical characteristics, as well as clinical detection parameters. Understanding plasma virome aids in auxiliary clinical diagnosis and treatment, enabling early prevention to reduce infection rates in patients and improve their quality of life. Video Abstract.

BACKGROUND: Idiopathic short stature (ISS) is characterized by short stature with unknown causes. Recent studies showed different gut microbiota flora and reduced fecal short-chain fatty acids in ISS children. However, the roles of the microbiome and metabolites in the pathogenesis of ISS remains largely unknown.
METHODS: We recruited 51 Chinese subjects, comprising 26 ISS children and 25 normal-height control individuals. Untargeted metabolomics was performed to explore the fecal metabolic profiles between groups. A shotgun metagenomic sequencing approach was used to investigate the microbiome at the strains level. Mediation analyses were done to reveal correlations between the height standard deviation (SD) value, the gut microbiome and metabolites.
RESULTS: We detected marked differences in the composition of fecal metabolites in the ISS group, particularly a significant increase in erucic acid and a decrease in spermidine, adenosine and L-5-Hydroxytryptophan, when compared to those of controls. We further identified specific groups of bacterial strains to be associated with the different metabolic profile. Through mediation analysis, 50 linkages were established. KEGG pathway analysis of microbiota and metabolites indicated nutritional disturbances. 13 selected features were able to accurately distinguish the ISS children from the controls (AUC = 0.933 [95%CI, 79.9-100%]) by receiver operating characteristic (ROC) analysis.
CONCLUSIONS: Our study suggests that the microbiome and the microbial-derived metabolites play certain roles in children\'s growth. These findings provide a new research direction for better understanding the mechanism(s) underlying ISS.

BACKGROUND: More than 90% of colorectal cancer (CRC) arises from advanced adenomas (AA) and gut microbes are closely associated with the initiation and progression of both AA and CRC.
OBJECTIVE: To analyze the characteristic microbes in AA.
METHODS: Fecal samples were collected from 92 AA and 184 negative control (NC). Illumina HiSeq X sequencing platform was used for high-throughput sequencing of microbial populations. The sequencing results were annotated and compared with NCBI RefSeq database to find the microbial characteristics of AA. R-vegan package was used to analyze α diversity and β diversity. α diversity included box diagram, and β diversity included Principal Component Analysis (PCA), principal co-ordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS). The AA risk prediction models were constructed based on six kinds of machine learning algorithms. In addition, unsupervised clustering methods were used to classify bacteria and viruses. Finally, the characteristics of bacteria and viruses in different subtypes were analyzed.
RESULTS: The abundance of Prevotella sp900557255, Alistipes putredinis, and Megamonas funiformis were higher in AA, while the abundance of Lilyvirus, Felixounavirus, and Drulisvirus were also higher in AA. The Catboost based model for predicting the risk of AA has the highest accuracy (bacteria test set: 87.27%; virus test set: 83.33%). In addition, 4 subtypes (B1V1, B1V2, B2V1, and B2V2) were distinguished based on the abundance of gut bacteria and enteroviruses (EVs). Escherichia coli D, Prevotella sp900557255, CAG-180 sp000432435, Phocaeicola plebeiuA, Teseptimavirus, Svunavirus, Felixounavirus, and Jiaodavirus are the characteristic bacteria and viruses of 4 subtypes. The results of Catboost model indicated that the accuracy of prediction improved after incorporating subtypes. The accuracy of discovery sets was 100%, 96.34%, 100%, and 98.46% in 4 subtypes, respectively.
CONCLUSIONS: Prevotella sp900557255 and Felixounavirus have high value in early warning of AA. As promising non-invasive biomarkers, gut microbes can become potential diagnostic targets for AA, and the accuracy of predicting AA can be improved by typing.