NanoDeep: a deep learning framework for nanopore adaptive sampling on microbial sequencing.

Nanopore sequencers can enrich or deplete the targeted DNA molecules in a library by reversing the voltage across individual nanopores. However, it requires substantial computational resources to achieve rapid operations in parallel at read-time sequencing. We present a deep learning framework, NanoDeep, to overcome these limitations by incorporating convolutional neural network and squeeze and excitation. We first showed that the raw squiggle derived from native DNA sequences determines the origin of microbial and human genomes. Then, we demonstrated that NanoDeep successfully classified bacterial reads from the pooled library with human sequence and showed enrichment for bacterial sequence compared with routine nanopore sequencing setting. Further, we showed that NanoDeep improves the sequencing efficiency and preserves the fidelity of bacterial genomes in the mock sample. In addition, NanoDeep performs well in the enrichment of metagenome sequences of gut samples, showing its potential applications in the enrichment of unknown microbiota. Our toolkit is available at https://github.com/lysovosyl/NanoDeep.

Rapid turnover and short-term blooms of Escherichia coli in the human gut.

Escherichia coli (E. coli) is a common microorganism that is widely present in the environment and closely related to human health. The extent of E. coli presence in the human gut has been a subject of ongoing debate. Through whole-genome shotgun metagenomic sequencing, our study revealed that E. coli exists in the human body at a low abundance (average abundance 1.21%), with occasional short-term bursts leading to temporary increases in abundance, with the highest recorded at 50.91%. Further investigations into the factors contributing to these short-term blooms of E. coli showed significant variations in strain types and genomes within fecal samples collected from the same individuals at different time points. Evolutionary tree analysis indicated that samples from different individuals crossed, suggesting a change in the dominant E. coli strains within the human gut. Therefore, it can be inferred that E. coli in the human body are more likely to be transient bacteria rather than permanent residents in the gut. The rapid rate of turnover among months (87.5% within a month) and short-term blooms of E. coli in the human body can establish "latent infections" of nonpathogenic strains in healthy individuals while also posing a potential risk of introducing pathogenic strains, thereby impacting human health. In summary, our study revealed the variation in E. coli abundance and strains within the human gut, influenced by geographic area and temporal factors. These findings contribute to a better understanding of the relationship between E. coli, the gut microbiota, and human health. IMPORTANCE Escherichia coli (E. coli) is a microorganism closely linked to human health, and its presence in the human gut has been a topic of debate. Our study, using whole-genome shotgun metagenomic sequencing, revealed that E. coli exists at a low abundance in the human body, with occasional short-term bursts leading to temporary increases. Strain and genome variations were observed within fecal samples from the same individuals at different time points, suggesting transient rather than permanent residence of E. coli in the gut. The rapid turnover rate and short-term blooms of E. coli can establish latent infections while also posing a risk of introducing pathogenic strains. These findings enhance our understanding of the relationship between E. coli, the gut microbiota, and human health.

Chronic and Neurotropic: A Paradigm-Challenging Case of Dengue Virus Encephalitis in a Patient With Advanced HIV Infection.

A 32-year-old female with advanced human immunodeficiency virus infection presented to an Australian hospital with subacute, worsening symptoms of encephalitis. Metagenomic sequencing and Dengue NS3 antigen staining of brain tissue confirmed active dengue virus (DENV) encephalitis. The most recent possible DENV exposure was months prior in West Africa, indicating chronicity.

Gut microbiome in association with chemotherapy-induced toxicities among patients with breast cancer.

BACKGROUND: Little research has focused on the relationship between gut microbiome and chemotherapy-induced toxicity. METHODS: This prospective study involves 301 patients with breast cancer who had prechemotherapy stool samples collected. Gut microbiome was sequenced by shotgun metagenomics; associations with chemotherapy-induced toxicities during first-line treatment by gut microbial diversity, composition, and metabolic pathways with severe (i.e., grade ≥3) hematological and gastrointestinal toxicities were evaluated via multivariable logistic regression. RESULTS: High prechemotherapy α-diversity was associated with a significantly reduced risk of both severe hematological toxicity (odds ratio [OR] = 0.94; 95% CI, 0.89-0.99; p = .048) and neutropenia (OR = 0.94; 95% CI, 0.89-0.99; p = .016). A high abundance of phylum Synergistota, class Synergistia, and order Synergistales were significantly associated with a reduced risk of severe neutropenia; conversely, enrichment of phylum Firmicutes C, class Negativicutes, phylum Firmicutes I, and class Bacilli A, order Paenibacillales were significantly associated with an increased risk of severe neutropenia (p range: 0.012-2.32 × 10-3; false discovery rate <0.1). Significant positive associations were also observed between severe nausea/vomiting and high Chao1 indexes, ß-diversity (p < .05), 20 species belonging to the family Lachnospiraceae, Oscillospiraceae, and Ruminococcaceae (p value range: 6.14 × 10-3 to 1.33 × 10-5; false discovery rate <0.1), and three metabolic pathways involved in reductive tricarboxylic acid cycle I and cycle II, and an incomplete reductive tricarboxylic acid cycle (p < .01). Conversely, a high abundance of species Odoribacter laneus and the pathway related to the L-proline biosynthesis II were inversely associated with severe nausea/vomiting. CONCLUSIONS: Our study suggests that gut microbiota may be a potential preventive target to reduce chemotherapy-induced toxicity.

Landscapes of gut bacterial and fecal metabolic signatures and their relationship in severe preeclampsia.

BACKGROUND: Preeclampsia is a pregnancy-specific disease leading to maternal and perinatal morbidity. Hypertension and inflammation are the main characteristics of preeclampsia. Many factors can lead to hypertension and inflammation, including gut microbiota which plays an important role in hypertension and inflammation in humans. However, alterations to the gut microbiome and fecal metabolome, and their relationships in severe preeclampsia are not well known. This study aims to identify biomarkers significantly associated with severe preeclampsia and provide a knowledge base for treatments regulating the gut microbiome. METHODS: In this study, fecal samples were collected from individuals with severe preeclampsia and healthy controls for shotgun metagenomic sequencing to evaluate changes in gut microbiota composition. Quantitative polymerase chain reaction analysis was used to validate the reliability of our shotgun metagenomic sequencing results. Additionally, untargeted metabolomics analysis was performed to measure fecal metabolome concentrations. RESULTS: We identified several Lactobacillaceae that were significantly enriched in the gut of healthy controls, including Limosilactobacillus fermentum, the key biomarker distinguishing severe preeclampsia from healthy controls. Limosilactobacillus fermentum was significantly associated with shifts in KEGG Orthology (KO) genes and KEGG pathways of the gut microbiome in severe preeclampsia, such as flagellar assembly. Untargeted fecal metabolome analysis found that severe preeclampsia had higher concentrations of Phenylpropanoate and Agmatine. Increased concentrations of Phenylpropanoate and Agmatine were associated with the abundance of Limosilactobacillus fermentum. Furthermore, all metabolites with higher abundances in healthy controls were enriched in the arginine and proline metabolism pathway. CONCLUSION: Our research indicates that changes in metabolites, possibly due to the gut microbe Limosilactobacillus fermentum, can contribute to the development of severe preeclampsia. This study provides insights into the interaction between gut microbiome and fecal metabolites and offers a basis for improving severe preeclampsia by modulating the gut microbiome.

Multi-omic profiling reveals associations between the gut microbiome, host genome and transcriptome in patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the leading cancer worldwide. Microbial agents have been considered to contribute to the pathogenesis of different disease. But the underlying relevance between CRC and microbiota remain unclear. METHODS: We dissected the fecal microbiome structure and genomic and transcriptomic profiles of matched tumor and normal mucosa tissues from 41 CRC patients. Of which, the relationship between CRC-associated bacterial taxa and their significantly correlated somatic mutated gene was investigated by exome sequencing technology. Differentially expressed functional genes in CRC were clustered according to their correlation with differentially abundant species, following by annotation with DAVID. The composition of immune and stromal cell types was identified by XCELL. RESULTS: We identified a set of 22 microbial gut species associated with CRC and estimate the relative abundance of KEGG ontology categories. Next, the interactions between CRC-related gut microbes and clinical phenotypes were evaluated. 4 significantly mutated gene: TP53, APC, KRAS, SMAD4 were pointed out and the associations with cancer related microbes were identified. Among them, Fusobacterium nucleatum positively corelated with different host metabolic pathways. Finally, we revealed that Fusobacterium nucleatum modified the tumor immune environment by TNFSF9 gene expression. CONCLUSION: Collectively, our multi-omics data could help identify novel biomarkers to inform clinical decision-making in the detection and diagnosis of CRC.

Real-time application of ITS and D1-D3 nanopore amplicon metagenomic sequencing in fungal infections: Enhancing fungal infection diagnostics.

While fungal infections cause considerable morbidity and mortality, the performance of the current diagnostic tests for fungal infection is low. Even though fungal metagenomics or targeted next-generation sequencing have been investigated for various clinical samples, the real-time clinical utility of these methods still needs to be elucidated. In this study, we used internal transcribed spacer (ITS) and D1-D3 ribosomal DNA nanopore amplicon metagenomic sequencing to assess its utility in patients with fungal infections. Eighty-four samples from seventy-three patients were included and categorized into 'Fungal infection,' 'Fungal colonization,' and 'Fungal contamination' groups based on the judgement of infectious disease specialists. In the 'Fungal infection' group, forty-seven initial samples were obtained from forty-seven patients. Three fungal cases detected not by the sequencing but by conventional fungal assays were excluded from the analysis. In the remaining cases, the conventional fungal assay-negative/sequencing-positive group (n=11) and conventional fungal assay-positive/sequencing-positive group (n=33) were compared. Non-Candida and non-Aspergillus fungi infections were more frequent in the conventional-negative/sequencing-positive group (p-value = 0.031). We demonstrated the presence of rare human pathogens, such as Trichosporon asahii and Phycomyces blakesleeanus. In the 'Fungal infection' group and 'Fungal colonization' group, sequencing was faster than culturing (mean difference = 4.92 days, p-value < 0.001/ mean difference = 4.67, p-value <0.001). Compared to the conventional diagnostic methods including culture, nanopore amplicon sequencing showed a shorter turnaround time and a higher detection rate for uncommon fungal pathogens.

Gut microbes on the risk of advanced adenomas.

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 ß diversity. α diversity included box diagram, and ß 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. CONCLUSION: 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.

Metagenomic gut microbiome analysis of Japanese patients with multiple chemical sensitivity/idiopathic environmental intolerance.

BACKGROUND: Although the pathology of multiple chemical sensitivity (MCS) is unknown, the central nervous system is reportedly involved. The gut microbiota is important in modifying central nervous system diseases. However, the relationship　between the gut microbiota and MCS remains unclear. This study aimed to identify gut microbiota variations associated with MCS using shotgun metagenomic sequencing of fecal samples. METHODS: We prospectively recruited 30 consecutive Japanese female patients with MCS and analyzed their gut microbiomes using shotgun metagenomic sequencing. The data were compared with metagenomic data obtained from 24 age- and sex-matched Japanese healthy controls (HC). RESULTS: We observed no significant difference in alpha and beta diversity of the gut microbiota between the MCS patients and HC. Focusing on the important changes in the literatures, at the genus level, Streptococcus, Veillonella, and Akkermansia were significantly more abundant in MCS patients than in HC (p < 0.01, p < 0.01, p = 0.01, respectively, fold change = 4.03, 1.53, 2.86, respectively). At the species level, Akkermansia muciniphila was significantly more abundant (p = 0.02, fold change = 3.3) and Faecalibacterium prausnitzii significantly less abundant in MCS patients than in HC (p = 0.03, fold change = 0.53). Functional analysis revealed that xylene and dioxin degradation pathways were significantly enriched (p < 0.01, p = 0.01, respectively, fold change = 1.54, 1.46, respectively), whereas pathways involved in amino acid metabolism and synthesis were significantly depleted in MCS (p < 0.01, fold change = 0.96). Pathways related to antimicrobial resistance, including the two-component system and cationic antimicrobial peptide resistance, were also significantly enriched in MCS (p < 0.01, p < 0.01, respectively, fold change = 1.1, 1.2, respectively). CONCLUSIONS: The gut microbiota of patients with MCS shows dysbiosis and alterations in bacterial functions related to exogenous chemicals and amino acid metabolism and synthesis. These findings may contribute to the further development of treatment for MCS. TRIAL REGISTRATION: This study was registered with the University Hospital Medical Information Clinical Trials Registry as UMIN000031031. The date of first trial registration: 28/01/2018.

Microbial carbohydrate active enzyme (CAZyme) genes and diversity from Menagesha Suba natural forest soils of Ethiopia as revealed by shotgun metagenomic sequencing.

BACKGROUND: The global over-reliance on non-renewable fossil fuels has led to the emission of greenhouse gases, creating a critical global environmental challenge. There is an urgent need for alternative solutions like biofuels. Advanced biofuel is a renewable sustainable energy generated from lignocellulosic plant materials, which can significantly contribute to mitigating CO2 emissions. Microbial Carbohydrate Active Enzymes (CAZymes) are the most crucial enzymes for the generation of sustainable biofuel energy. The present study designed shotgun metagenomics approaches to assemble, predict, and annotate, aiming to gain an insight into the taxonomic diversity, annotate CAZymes, and identify carbohydrate hydrolyzing CAZymes from microbiomes in Menagesha suba forest soil for the first time. RESULTS: The microbial diversity based on small subunit (SSU) rRNA analysis revealed the dominance of the bacterial domain representing 81.82% and 92.31% in the studied samples. Furthermore, the phylum composition result indicated the dominance of the phyla Proteobacteria (23.08%, 27.27%), Actinobacteria (11.36%, 20.51%), and Acidobacteria (10.26%, 15.91%). The study also identified unassigned bacteria which might have a unique potential for biopolymer hydrolysis. The metagenomic study revealed that 100,244 and 65,356 genes were predicted from the two distinct samples. A total number of 1806 CAZyme genes were identified, among annotated CAZymes, 758 had a known enzyme assigned to CAZymes. Glycoside hydrolases (GHs) CAZyme family contained most of the CAZyme genes with known enzymes such as ß-glucosidase, endo-ß-1,4-mannanase, exo-ß-1,4-glucanase, α-L-arabinofuranosidase and oligoxyloglucan reducing end-specific cellobiohydrolase. On the other hand, 1048 of the identified CAZyme genes were putative CAZyme genes with unknown enzymatical activity and the majority of which belong to the GHs family. CONCLUSIONS: In general, the identified putative CAZymes genes open up an opportunity for the discovery of new enzymes responsible for hydrolyzing biopolymers utilized for biofuel energy generation. This finding is used as a first-hand piece of evidence to serve as a benchmark for further and comprehensive studies to unveil novel classes of bio-economically valuable genes and their encoded products.

Simultaneous identification of DNA and RNA pathogens using metagenomic sequencing in cases of severe acute respiratory infection.

Metagenomic next-generation sequencing (mNGS) is a valuable technique for identifying pathogens. However, conventional mNGS requires the separate processing of DNA and RNA genomes, which can be resource- and time-intensive. To mitigate these impediments, we propose a novel method called DNA/RNA cosequencing that aims to enhance the efficiency of pathogen detection. DNA/RNA cosequencing uses reverse transcription of total nucleic acids extracted from samples by using random primers, without removing DNA, and then employs mNGS. We applied this method to 85 cases of severe acute respiratory infections (SARI). Influenza virus was identified in 13 cases (H1N1: seven cases, H3N2: three cases, unclassified influenza type: three cases) and was not detected in the remaining 72 samples. Bacteria were present in all samples. Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii were detected in four influenza-positive samples, suggesting coinfections. The sensitivity and specificity for detecting influenza A virus were 73.33% and 95.92%, respectively. A κ value of 0.726 indicated a high level of concordance between the results of DNA/RNA cosequencing and SARI influenza virus monitoring. DNA/RNA cosequencing enhanced the efficiency of pathogen detection, providing a novel capability to strengthen surveillance and thereby prevent and control infectious disease outbreaks.

Treatment response in rheumatoid arthritis is predicted by the microbiome: a large observational study in UK DMARD-naïve patients.

OBJECTIVES: Disease-modifying antirheumatic drugs (DMARDs) are first line treatment in rheumatoid arthritis (RA). Treatment response to DMARDs is patient-specific, dose efficacy is difficult to predict and long-term results variable. The gut microbiota are known to play a pivotal role in prodromal and early-disease RA, manifested by Prevotella spp. enrichment. The clinical response to therapy may be mediated by microbiota, and large-scale studies assessing the microbiome are few. This study assessed whether microbiome signals were associated with, and predictive of, patient response to DMARD-treatment. Accurate early identification of those who will respond poorly to DMARD therapy would allow selection of alternative treatment (e.g. biologic therapy), and potentially improve patient outcome. METHODS: A multicentre, longitudinal, observational study of stool- and saliva microbiome was performed in DMARD-naïve, newly diagnosed RA patients during introduction of DMARD treatment. Clinical data and samples were collected at baseline (n = 144) in DMARD-naïve patients and at six weeks (n = 117) and 12 weeks (n = 95) into DMARD-therapy. Samples collected (n = 365 stool, n = 365 saliva) underwent shotgun sequencing. Disease activity measures were collected at each timepoint and minimal clinically important improvement determined. RESULTS: In total, 26 stool microbes were found to decrease in those manifesting a minimal clinically important improvement. Prevotella spp. and Streptococcus spp. were the predominant taxa to decline following six weeks and 12 weeks of DMARDs, respectively. Furthermore, baseline microbiota of DMARD-naïve patients were indicative of future response. CONCLUSION: DMARDs appear to restore a perturbed microbiome to a eubiotic state. Moreover, microbiome status can be used to predict likelihood of patient response to DMARD.

One Health Threat of Treated Wastewater Discharge in Urban Ohio Rivers: Implications for Surface Water and Fish Gut Microbiome and Resistome.

Wastewater treatment plants (WWTPs) are thought to be a major disseminating source of antibiotic resistance (AR) to the environment, establishing a crucial connection between human and environmental resistome. The objectives of this study were to determine how wastewater effluents impact microbiome and resistome of freshwater and fish, and identify potential AR-carrying clinically relevant pathogens in these matrices. We analyzed wastewater influent and effluent from four WWTPs in three metropolitan areas of Ohio, USA via shotgun metagenomic sequencing. We also sequenced river water and fish guts from three reaches (upstream, at the WWTP outfall, and downstream). Notably, we observed a decline in microbiome diversity and AR gene abundance from wastewater to the receiving river. We also found significant differences by reach and trophic level (diet) in beta-diversity of the fish gut microbiomes. SourceTracker revealed that 0.443 and 0.248 more of the of the fish gut microbiome was sourced from wastewater effluent in fish from the outfall and downstream locations, respectively, compared to upstream fish. Additionally, AR bacteria of public health concern were annotated in effluent and river water samples, indicating potential concern for human exposure. In summary, our findings show the continued role of wastewater as a significant AR reservoir and underscores the considerable impact of wastewater discharge on aquatic wildlife, which highlights the One Health nature of this issue.

Metagenomics and Stable Isotopes Uncover the Augmented Sulfide-Driven Autotrophic Denitrification in a Seasonally Hypoxic, Sulfate-Abundant Reservoir.

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.

Metagenomics uncovers microbiome and resistome in soil and reindeer faeces from Ny-Ålesund (Svalbard, High Arctic).

Research on the microbiome and resistome in polar environments, such as the Arctic, is crucial for understanding the emergence and spread of antibiotic resistance genes (ARGs) in the environment. In this study, soil and reindeer faeces samples collected from Ny-Ålesund (Svalbard, High Arctic) were examined to analyze the microbiome, ARGs, and biocide/metal resistance genes (BMRGs). The dominant phyla in both soil and faeces were Pseudomonadota, Actinomycetota, and Bacteroidota. A total of 2,618 predicted Open Reading Frames (ORFs) containing antibiotic resistance genes (ARGs) were detected. These ARGs belong to 162 different genes across 17 antibiotic classes, with rifamycin and multidrug resistance genes being the most prevalent. We focused on investigating antibiotic resistance mechanisms in the Ny-Ålesund environment by analyzing the resistance genes and their biological pathways. Procrustes analysis demonstrated a significant correlation between bacterial communities and ARG/BMRG profiles in soil and faeces samples. Correlation analysis revealed that Pseudomonadota contributed most to multidrug and triclosan resistance, while Actinomycetota were predominant contributors to rifamycin and aminoglycoside resistance. The geochemical factors, SiO42- and NH4+, were found to significantly influence the microbial composition and ARG distribution in the soil samples. Analysis of ARGs, BMRGs, virulence factors (VFs), and pathogens identified potential health risks associated with certain bacteria, such as Cryobacterium and Pseudomonas, due to the presence of different genetic elements. This study provided valuable insights into the molecular mechanisms and geochemical factors contributing to antibiotic resistance and enhanced our understanding of the evolution of antibiotic resistance genes in the environment.

Residue quality drives SOC sequestration by altering microbial taxonomic composition and ecophysiological function in desert ecosystem.

Plant residues are important sources of soil organic carbon in terrestrial ecosystems. The degradation of plant residue by microbes can influence the soil carbon cycle and sequestration. However, little is known about the microbial composition and function, as well as the accumulation of soil organic carbon (SOC) in response to the inputs of different quality plant residues in the desert environment. The present study evaluated the effects of plant residue addition from Pinus sylvestris var. mongolica (Pi), Artemisia desertorum (Ar) and Amorpha fruticosa (Am) on desert soil microbial community composition and function in a field experiment in the Mu Us Desert. The results showed that the addition of the three plant residues with different C/N ratios induced significant variation in soil microbial communities. The Am treatment (low C/N ratio) improved microbial diversity compared with the Ar and Pi treatments (medium and high C/N ratios). The variations in the taxonomic and functional compositions of the dominant phyla Actinobacteria and Proteobacteria were higher than those of the other phyla among the different treatments. Moreover, the network links between Proteobacteria and other phyla and the CAZyme genes abundances from Proteobacteria increased with increasing residue C/N, whereas those decreased for Actinobacteria. The SOC content of the Am, Ar and Pi treatments increased by 45.73%, 66.54% and 107.99%, respectively, as compared to the original soil. The net SOC accumulation was positively correlated with Proteobacteria abundance and negatively correlated with Actinobacteria abundance. These findings showed that changing the initial quality of plant residue from low C/N to high C/N can result in shifts in taxonomic and functional composition from Actinobacteria to Proteobacteria, which favors SOC accumulation. This study elucidates the ecophysiological roles of Actinobacteria and Proteobacteria in the desert carbon cycle, expands our understanding of the potential microbial-mediated mechanisms by which plant residue inputs affect SOC sequestration in desert soils, and provides valuable guidance for species selection in desert vegetation reconstruction.

Phosphate solubilization and plant growth properties are promoted by a lactic acid bacterium in calcareous soil.

On the basis of good phosphate solubilization ability of a lactic acid bacteria (LAB) strain Limosilactobacillus sp. LF-17, bacterial agent was prepared and applied to calcareous soil to solubilize phosphate and promote the growth of maize seedlings in this study. A pot experiment showed that the plant growth indicators, phosphorus content, and related enzyme activity of the maize rhizospheric soils in the LF treatment (treated with LAB) were the highest compared with those of the JP treatment (treated with phosphate solubilizing bacteria, PSB) and the blank control (CK). The types of organic acids in maize rhizospheric soil were determined through LC-MS, and 12 acids were detected in all the treatments. The abundant microbes belonged to the genera of Lysobacter, Massilia, Methylbacillus, Brevundimonas, and Limosilactobacillus, and they were beneficial to dissolving phosphate or secreting growth-promoting phytohormones, which were obviously higher in the LF and JP treatments than in CK as analyzed by high-throughput metagenomic sequencing methods. In addition, the abundance values of several enzymes, Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology, and Carbohydrate-Active Enzymes (CAZys), which were related to substrate assimilation and metabolism, were the highest in the LF treatment. Therefore, aside from phosphate-solubilizing microorganisms, LAB can be used as environmentally friendly crop growth promoters in agriculture and provide another viable option for microbial fertilizers. KEY POINTS: • The inoculation of LAB strain effectively promoted the growth and chlorophyll synthesis of maize seedlings. • The inoculation of LAB strain significantly increased the TP content of maize seedlings and the AP concentration of the rhizosphere soil. • The inoculation of LAB strain increased the abundances of the dominant beneficial functional microbes in the rhizosphere soil.

Characteristics of intestinal bacteriophages and their relationship with Bacteria and serum metabolites during quail sexual maturity transition.

BACKGROUND: Bacteriophages are prokaryotic viruses that rank among the most abundant microbes in the gut but remain among the least understood, especially in quails. In this study, we surveyed the gut bacteriophage communities in 22 quails at different ages (days 20 and 70) using shotgun metagenomic sequencing. We then systematically evaluated the relationships with gut bacteria and host serum metabolites. RESULTS: We discovered that Myoviridae and Siphoviridae were the dominant bacteriophage families in quails. Through a random forest and LEfSe analysis, we identified 23 differential bacteriophages with overlapping presence. Of these, 21 bacteriophages (e.g., Enterococcus phage IME-EFm5 and Enterococcus phage IME-EFm1) showed higher abundances in the day 20 group, while two bacteriophages (Bacillus phage Silence and Bacillus virus WPh) were enriched in the day 70 group. These key bacteriophages can serve as biomarkers for quail sexual maturity. Additionally, the differential bacteriophages significantly correlated with specific bacterial species and shifts in the functional capacities of the gut microbiome. For example, Enterococcus phages (e.g., Enterococcus phage EFP01, Enterococcus phage IME-EFm5, and Enterococcus phage IME-EFm1) were significantly (P < 0.001, FDR) and positively correlated with Enterococcus faecalis. However, the relationships between the host serum metabolites and either bacteriophages or bacterial species varied. None of the bacteriophages significantly (P > 0.05, FDR) correlated with nicotinamide riboside and triacetate lactone. In contrast, some differential bacterial species (e.g., Christensenella massiliensis and Bacteroides neonati) significantly (P < 0.05, FDR) correlated with nicotinamide riboside and triacetate lactone. Furthermore, characteristic successional alterations in gut bacteriophages, bacteria, and host serum metabolites across different ages highlighted a sexual maturity transition coexpression network. CONCLUSION: This study improves our understanding of the gut bacteriophage characteristics in quails and offers profound insights into the interactions among gut bacteriophages, bacteria, and host serum metabolites during the quail's sexual maturity transition.

Gut microbiota and metabolic changes in children with idiopathic short stature.

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. CONCLUSION: 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.

Characteristics and function of the gut microbiota in patients with IgA nephropathy via metagenomic sequencing technology.

OBJECTIVE: The aim of this study was to investigate the characteristics and related functional pathways of the gut microbiota in patients with IgA nephropathy (IgAN) through metagenomic sequencing technology. METHODS: We enrolled individuals with primary IgAN, including patients with normal and abnormal renal function. Additionally, we recruited healthy volunteers as the healthy control group. Stool samples were collected, and species and functional annotation were performed through fecal metagenome sequencing. We employed linear discriminant analysis effect size (LEfSe) analysis to identify significantly different bacterial microbiota and functional pathways. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to annotate microbiota functions, and redundancy analysis (RDA) was performed to analyze the factors affecting the composition and distribution of the gut microbiota. RESULTS: LEfSe analysis revealed differences in the gut microbiota between IgAN patients and healthy controls. The characteristic microorganisms in the IgAN group were classified as Escherichia coli, with a significantly greater abundance than that in the healthy control group (p < 0.05). The characteristic microorganisms in the IgAN group with abnormal renal function were identified as Enterococcaceae, Moraxella, Moraxella, and Acinetobacter. KEGG functional analysis demonstrated that the functional pathways of the microbiota that differed between IgAN patients and healthy controls were related primarily to bile acid metabolism. CONCLUSIONS: The status of the gut microbiota is closely associated not only with the onset of IgAN but also with the renal function of IgAN patients. The characteristic gut microbiota may serve as a promising diagnostic biomarker and therapeutic target for IgAN.