Microbial Genes Research Articles

Molecular mechanism of boosted hydrogen production by Thermoanaerobacterium thermosaccharolyticum with biochar revealed by transcriptome analysis

Although numerous studies have reported the enhancement of hydrogen production by biochar in dark fermentation, the molecular mechanisms underlying this enhancement remain poorly understood. This study investigated the role of biochar in boosting hydrogen production by Thermoanaerobacterium thermosaccharolyticum MJ2. The results showed that BC600 addition led to a 290.7% increase in hydrogen production and a 67.1% improvement in hydrogen yield, with a significant increase in cell biomass, 74% of which was immobilized on biochar. Transcriptome analysis revealed the upregulation of genes coding for hydrogen-producing ech hydrogenases and the downregulation of hnd hydrogenase genes involved in hydrogen consumption. Additionally, gene expression related to cell immobilization, nitrogen fixation for hydrogen production were also enhanced, while genes associated with glycolysis showed an overall downregulation. For the key genes of interest, BC600 had a more profound effect on their expression levels in immobilized cells compared to suspended cells within the same system. This study provides valuable insights into how biochar regulates microbial metabolism and gene expression to enhance hydrogen production, aiding in the development of more effective biochar application strategies for biohydrogen production.

Cow Dung Liquid Mulch Improves Maize Yields: Beneficial Microorganisms Are Enriched and Environmental Risks Are Reduced and Nutrient Cycling Is Promoted

Cow dung liquid mulch (CDLM), which uses cow dung as a raw material, has a good degradability and is a potential alternative to traditional plastic agricultural mulch, but there is a lack of research on the effects of CDLM on rhizosphere soil physicochemical properties, rhizosphere soil microbial functions, and crop yields. In this study, the link between maize yield, environmental factors, and functional genes as well as the responses of microbial community functions to CDLM and polyethylene mulch (PE) were studied using metagenomic sequencing. Functional annotation was also performed on clusters of orthologous groups of proteins, the Kyoto Encyclopedia of Genes and Genomes, and carbohydrate-active enzyme sequencing data. The results showed that CDLM significantly increased maize yield by 30.9% compared to CK while maintaining lower soil microplastic levels. CDLM promotes the enrichment of beneficial microorganisms such as Mycolicibacterium and Pseudomonas. The relative abundance of functional genes related to microbial metabolism, soil element cycling pathways, and organic matter degradation was significantly higher in CDLM than in CK. Microbial functional genes were positively correlated with maize yield and environmental factors such as soil nutrients. These results suggested that CDLM can improve maize yield by enriching beneficial microorganisms, reducing rhizosphere soil environmental risks, and enhancing rhizosphere soil microbial function. Rhizosphere soil nutrients and microbial functional genes together mediated the positive response of maize yield to CDLM. This study can provide a scientific basis and data support for the safe use of mulch in the future.

Metagenomic analysis during capecitabine therapy reveals microbial chemoprotective mechanisms and predicts drug toxicity in colorectal cancer patients.

Unpredictable chemotherapy side effects are a major barrier to successful treatment. Cell culture and mouse experiments indicate that the gut microbiota is influenced by and influences anti-cancer drugs. However, metagenomic data from patients paired to careful side effect monitoring remains limited. Herein, we focus on the oral fluoropyrimidine capecitabine (CAP). We investigate CAP-microbiome interactions through metagenomic sequencing of longitudinal stool sampling from a cohort of advanced colorectal cancer (CRC) patients. We established a prospective cohort study including 56 patients with advanced CRC treated with CAP monotherapy across 4 centers in the Netherlands. Stool samples and clinical questionnaires were collected at baseline, during cycle 3, and post-treatment. Metagenomic sequencing to assess microbial community structure and gene abundance was paired with transposon mutagenesis, targeted gene deletion, and media supplementation experiments. An independent US cohort was used for model validation. CAP treatment significantly altered gut microbial composition and pathway abundance, enriching for menaquinol (vitamin K2) biosynthesis genes. Transposon library screens, targeted gene deletions, and media supplementation confirmed that menaquinol biosynthesis protects Escherichia coli from drug toxicity. Microbial menaquinol biosynthesis genes were associated with decreased peripheral sensory neuropathy. Machine learning models trained in this cohort predicted hand-foot syndrome and dose reductions in an independent cohort. These results suggest treatment-associated increases in microbial vitamin biosynthesis serve a chemoprotective role for bacterial and host cells, with implications for toxicities outside the gastrointestinal tract. We provide a proof-of-concept for the use of microbiome profiling and machine learning to predict drug toxicities across independent cohorts. These observations provide a foundation for future human intervention studies, more in-depth mechanistic dissection in preclinical models, and extension to other cancer treatments.

DNASimCLR: a contrastive learning-based deep learning approach for gene sequence data classification

BackgroundThe rapid advancements in deep neural network models have significantly enhanced the ability to extract features from microbial sequence data, which is critical for addressing biological challenges. However, the scarcity and complexity of labeled microbial data pose substantial difficulties for supervised learning approaches. To address these issues, we propose DNASimCLR, an unsupervised framework designed for efficient gene sequence data feature extraction.ResultsDNASimCLR leverages convolutional neural networks and the SimCLR framework, based on contrastive learning, to extract intricate features from diverse microbial gene sequences. Pre-training was conducted on two classic large scale unlabelled datasets encompassing metagenomes and viral gene sequences. Subsequent classification tasks were performed by fine-tuning the pretrained model using the previously acquired model. Our experiments demonstrate that DNASimCLR is at least comparable to state-of-the-art techniques for gene sequence classification. For convolutional neural network-based approaches, DNASimCLR surpasses the latest existing methods, clearly establishing its superiority over the state-of-the-art CNN-based feature extraction techniques. Furthermore, the model exhibits superior performance across diverse tasks in analyzing biological sequence data, showcasing its robust adaptability.ConclusionsDNASimCLR represents a robust and database-agnostic solution for gene sequence classification. Its versatility allows it to perform well in scenarios involving novel or previously unseen gene sequences, making it a valuable tool for diverse applications in genomics.

Small amounts of misassembly can have disproportionate effects on pangenome-based metagenomic analyses.

Individual genes from microbiomes can drive host-level phenotypes. To help identify such candidate genes, several recent tools estimate microbial gene copy numbers directly from metagenomes. These tools rely on alignments to pangenomes, which in turn are derived from the set of all individual genomes from one species. While large-scale metagenomic assembly efforts have made pangenome estimates more complete, mixed communities can also introduce contamination into assemblies, and it is unknown how robust pangenome-based metagenomic analyses are to these errors. To gain insight into this problem, we re-analyzed a case-control study of the gut microbiome in cirrhosis, focusing on commensal Clostridia previously implicated in this disease. We tested for differentially prevalent genes in the Lachnospiraceae , then investigated which were likely to be contaminants using sequence similarity searches. Out of 86 differentially prevalent genes, we found that 33 (38%) were probably contaminants originating in taxa such as Veillonella and Haemophilus , unrelated genera that were independently correlated with disease status. Our results demonstrate that even small amounts of contamination in metagenome assemblies, below typical quality thresholds, can threaten to overwhelm gene-level metagenomic analyses. However, we also show that such contaminants can be accurately identified using a method based on gene-to-species correlation. After removing these contaminants, we observe that several flagellar motility gene clusters in the Lachnospira eligens pangenome are associated with cirrhosis status. We have integrated our analyses into an analysis and visualization pipeline, PanSweep, that can automatically identify cases where pangenome contamination may bias the results of gene-resolved analyses.

The combined nitrogen and phosphorus fertilizer application reduced soil multifunctionality in Qinghai-Tibet plateau grasslands, China

The impact of nitrogen (N) and phosphorus (P) fertilizer inputs on soil nutrient cycling and ecological function processes has garnered significant attention. Soil multifunctionality primarily refers to the soil's ability to perform multiple functions simultaneously, particularly the functions related to the genes involved in carbon (C), nitrogen (N), and phosphorus (P) cycles, which are critical for ecosystem sustainability. Despite this, the effects of N and P fertilizers on the expression of genes involved in soil carbon (C), nitrogen (N), and phosphorus (P) cycles, and their consequent influence on soil multifunctionality, remain unclear. To investigate this, we conducted a long-term nine-year experiment. The experimental site was fenced to prevent grazing and included four treatments: Control (no fertilizer), N (10 g N m−2 y−1, urea), P (5 g P m−2 y−1, Ca(H2PO4)2), and NP (10 g N and 5 g P m−2 y−1, urea and Ca(H2PO4)2). We examined the effects of these treatments on soil microbial functional gene abundance and multifunctionality. Our findings revealed that N addition altered the composition of soil microbial functional genes but did not affect functional diversity. Both N and P inputs, as well as their combination, negatively impacted soil carbon fixation and the genes encoding enzymes for the degradation of starch, hemicellulose, cellulose, and chitin. N input also disrupted soil nitrogen and phosphorus cycling by inhibiting the expression of soil denitrification genes (nirS and nosZ), phytate hydrolase gene (cphy), and a phosphatase gene (phoD). Additionally, P input significantly inhibited functional genes involved in soil nitrification, denitrification, ammonification, nitrogen fixation, and ammonia oxidation processes. It also adversely affected phytate synthesis and degradation. The combined N and P inputs had a substantial negative impact on soil nitrification (hao), denitrification (narG, nirK, nirS, and norZ), ammonification (gdh), nitrogen fixation, annamox, and nitrogen reduction, and inhibited the expression of soil phosphorus cycle genes. Long-term phosphorus application was found to have a more detrimental effect on soil multifunctionality compared to nitrogen application. Furthermore, our study showed that vegetation diversity and abundance are crucial drivers of soil carbon, nitrogen, and phosphorus cycling functional genes and multifunctionality. We concluded that N and P inputs alter soil multifunctionality by influencing vegetation diversity; therefore, maintaining vegetation diversity is essential for sustaining soil multifunctionality.

Impact of metallic nanoparticles on gut microbiota modulation in colorectal cancer: A review.

Colorectal cancer (CRC) is the third most prevalent cancer. Ongoing research aims to uncover the causes of CRC, with a growing focus on the role of gut microbiota (GM) in carcinogenesis. The GM influences CRC development, progression, treatment efficacy, and therapeutic toxicities. For example, Fusobacterium nucleatum and Escherichia coli can regulate microbial gene expression through the incorporation of human small noncode RNA and potentially contribute to cancer progression. Metallic nanoparticles (MNPs) have both negative and positive impacts on GM, depending on their type. Several studies state that titanium dioxide may increase the diversity, richness, and abundance of probiotics bacteria, whereas other studies demonstrate dose-dependent GM dysbiosis. The MNPs offer cytotoxicity through the modulation of MAPK signaling pathways, NF-kB signaling pathways, PI3K/Akt signaling pathways, extrinsic signaling pathways, intrinsic apoptosis, and cell cycle arrest at G1, G2, or M phase. MNPs enhance drug delivery, enable targeted therapy, and may restore GM. However, there is a need to conduct well-designed clinical trials to assess the toxicity, safety, and effectiveness of MNPs-based CRC therapies.

Removal of sulfamethoxazole in an algal-bacterial membrane aerated biofilm reactor: Microbial responses and antibiotic resistance genes

Antibiotics are frequently detected in wastewater, but often are poorly removed in conventional wastewater treatment processes. Combining microalgal and nitrifying bacterial processes may provide synergistic removal of antibiotics and ammonium. In this research, we studied the removal of the antibiotic sulfamethoxazole (SMX) in two different reactors: a conventional nitrifying bacterial membrane aerated biofilm reactor (bMABR) and algal-bacterial membrane aerated biofilm reactor (abMABR) systems. We investigated the synergistic removal of antibiotics and ammonium, antioxidant activity, microbial communities, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and their potential hosts. Our findings show that the abMABR maintained a high sulfamethoxazole (SMX) removal efficiency, with a minimum of 44.6 % and a maximum of 75.8 %, despite SMX inhibition, it maintained a consistent 25.0 % ammonium removal efficiency compared to the bMABR. Through a production of extracellular polymeric substances (EPS) with increased proteins/polysaccharides (PN/PS), the abMABR possibly allowed the microalgae-bacteria consortium to protect the bacteria from SMX inactivation. The activity of antioxidant enzymes caused by SMX was reduced by 62.1–98.5 % in the abMABR compared to the bMABR. Metagenomic analysis revealed that the relative abundance of Methylophilus, Pseudoxanthomonas, and Acidovorax in the abMABR exhibited a significant positive correlation with SMX exposure and reduced nitrate concentrations and SMX removal. Sulfonamide ARGs (sul1 and sul2) appeared to be primarily responsible for defense against SMX stress, and Hyphomicrobium and Nitrosomonas were the key carriers of ARGs. This study demonstrated that the abMABR system has great potential for removing SMX and reducing the environmental risks of ARGs.

Decoupled fungal and bacterial functional responses to biochar amendment drive rhizosphere priming effect on soil organic carbon mineralization

The application of biochar to soil is widely recognized as a promising strategy for enhancing the accumulation and stability of soil organic carbon (SOC), which is crucial in mitigating climate change. However, the influence of interactions between plants and biochar on soil microbial communities and their involvement in SOC mineralization and stability remains unclear. This understanding is essential for optimizing carbon (C) sequestration in systems involving plants, soil, and biochar. In this study, employing a 13C natural abundance approach, we investigated the effect of biochar on the maize rhizosphere priming effect (RPE) in paddy soil. We also examined alterations in microbial communities and functional genes related to C degradation and fixation. Over the 99 days of maize growth, biochar application increased RPE and total SOC while decreasing dissolved organic C. It also elevated soil pH, resulting in shifts in fungal and bacterial community structure, favoring oligotrophic species. Fungal and bacterial assemblies were dominated by deterministic and stochastic processes, respectively. While the abundance of fungal guilds varied irregularly, bacterial guilds were uniformly enriched under biochar-plant interactions. Functional traits such as ecoenzymatic activities, bacterial guilds, and functional genes predominantly affected RPE under biochar application. Bacterial functional genes associated with C degradation and fixation were concurrently enhanced with biochar application. Our results indicate that interactions between plants and biochar can enhance native SOC mineralization and accumulation in a short timeframe by modulating functional traits of soil microorganisms, particularly the bacterial community involved in C degradation and fixation.Graphical

Unveiling the Hidden Responses: Metagenomic Insights into Dwarf Bamboo (Fargesia denudata) Rhizosphere under Drought and Nitrogen Challenges.

Dwarf bamboo (Fargesia denudata) is a crucial food source for the giant pandas. With its shallow root system and rapid growth, dwarf bamboo is highly sensitive to drought stress and nitrogen deposition, both major concerns of global climate change affecting plant growth and rhizosphere environments. However, few reports address the response mechanisms of the dwarf bamboo rhizosphere environment to these two factors. Therefore, this study investigated the effects of drought stress and nitrogen deposition on the physicochemical properties and microbial community composition of the arrow bamboo rhizosphere soil, using metagenomic sequencing to analyze functional genes involved in carbon and nitrogen cycles. Both drought stress and nitrogen deposition significantly altered the soil nutrient content, but their combination had no significant impact on these indicators. Nitrogen deposition increased the relative abundance of the microbial functional gene nrfA, while decreasing the abundances of nirK, nosZ, norB, and nifH. Drought stress inhibited the functional genes of key microbial enzymes involved in starch and sucrose metabolism, but promoted those involved in galactose metabolism, inositol phosphate metabolism, and hemicellulose degradation. NO3--N showed the highest correlation with N-cycling functional genes (p < 0.01). Total C and total N had the greatest impact on the relative abundance of key enzyme functional genes involved in carbon degradation. This research provides theoretical and technical references for the sustainable management and conservation of dwarf bamboo forests in giant panda habitats under global climate change.

The Catalog of Microbial Genes and Metagenome-Assembled Genomes from the Gut Microbiomes of Five Typical Crow Species on the Qinghai-Tibetan Plateau.

While considerable progress has been made in understanding the complex relationships between gut microbiomes and their hosts, especially in mammals and humans, the functions of these microbial communities in avian species remain largely unexplored. This gap in knowledge is particularly notable, given the critical roles gut microbiomes are known to play in facilitating crucial physiological functions, such as digestion, nutrient absorption, and immune system development. Corvidae birds are omnivorous and widely distributed across various habitats, exhibiting strong adaptability and often displaying the traits of accompanying humans. However, to date, information on species composition, sequenced genomes, and functional characteristics of crow gut microbes is lacking. Herein, we constructed the first relatively comprehensive crows gut microbial gene catalog (2.74 million genes) and 195 high-quality and medium-quality metagenome-assembled genomes using 53 metagenomic samples from five typical crow species (Pyrrhocorax pyrrhocorax, Corvus dauuricus, Corvus frugilegus, Corvus macrorhynchos, and Corvus corax) on the Qinghai-Tibetan Plateau. The species composition of gut microbiota at the phylum and genus levels was revealed for these five crow species. Simultaneously, numerous types of prevalent pathogenic bacteria were identified, indicating the potential of these crows to transmit diseases within the local community. At the functional level, we annotated a total of 356 KEGG functional pathways, six CAZyme categories, and 3607 virulence factor genes in the gut microbiomes of the crows. The gut microbiota of five distinct crow species underwent a comparative analysis, which uncovered significant differences in their composition, diversity, and functional structures. Over 36% of MAGs showed no overlap with existing databases, suggesting they might represent new species. Consequently, these findings enriched the dataset of microbial genomes associated with crows' digestive systems. Overall, this study offers crucial baseline information regarding the gut microbial gene catalog and genomes in crows, potentially aiding microbiome-based research, as well as an evaluation of the health risks to humans from the bacterial pathogens transmitted by wild birds.

Multi-Omics Analysis Reveals Molecular Responses of Alkaloid Content Variations in Lycoris aurea Across Different Locations.

Lycoris aurea, celebrated for its visually striking flowers and significant medicinal value due to the presence of alkaloids such as lycorine and galanthamine, has intricate yet poorly understood regulatory mechanisms. This study provides a detailed examination of the transcriptomic, metabolomic and ecological dynamics of L. aurea, aiming to elucidate the underlying molecular mechanisms of alkaloid biosynthesis. Our comparative analysis across different ecological settings highlighted key genes involved in alkaloid biosynthesis, such as genes encoding aldehyde dehydrogenase and norbelladine 4'-O-methyltransferase, which were distinctively increased in the high alkaloids-producing group. We identified a total of 6871 differentially expressed genes and 915 metabolites involved in pathways like terpenoid backbone biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis. Protein interaction network analysis revealed significant upregulation of photosynthesis, photosystem and photosynthetic membrane pathways in the alkaloids-producing region. Furthermore, our research delineated the interactions among soil microbial communities, genes and plant and soil biochemical properties, noting that bacterial populations correlate with soil properties that favour the activation of metabolic pathways essential for alkaloid production. Collectively, this study advances our understanding of the genetic and metabolic alkaloid biosynthesis pathways in L. aurea, shedding light on the complex interactions that govern alkaloid production.

Recovery of platinum nanoparticles by the anaerobic mixed consortium: Platinum (IV) ion reduction, microbial community dynamics and functional genes identification

Removal and recovery of platinum (Pt) from platinum-contaminated wastestreams is beneficial to tackle the increasing supply risk and prevent adverse environmental impacts. Reduction soluble Pt (IV) to Pt nanoparticles using biological method is a plausible approach. However, current studies mainly focus on pure bacterial cultures to reduce Pt (IV). This study evaluates Pt (IV) removal via bioreduction by anaerobic granular sludge with the addition of exogenous electron donors and elucidates underlying mechanisms. Results show that formate and ethanol exhibited significant effects of Pt (IV) reduction, while acetate, lactate and pyruvate showed limited effects. The reduced products Pt nanoparticles were deposited on bacterial cell surface and periplasm. Moreover, Bacteroidetes, Patescibacteria and Proteobacteria were dominant bacteria during the Pt (IV) reduction process. Pt (IV) reduction was mainly mediated by enzymatic processes. Overall, these findings deepen understanding of Pt (IV) bioreduction by anaerobic mixed consortium.

Long-term organic fertilization increases phosphorus content but reduces its release in soil aggregates

There is currently limited published information on the coupling correlation between phosphorus (P) redistribution and release in soil aggregates. To fulfill this gap, we conducted a 10-year field experiment of soil amended with organic fertilizer to investigate phosphorus transformation and immobilization during the organic fertilization process. Microbial communities, functional genes and enzymes were analyzed to elucidate the multi-mechanisms of the conversion among phosphorus fractions. Phosphorus content in soil aggregates was determined as follows: FeP (34 % ~ 45 %) > Ca-P (16 % ~ 27 %) > Oc-P (15 % ~ 17 %) > Or-P (13 % ~ 19 %) > Al-P (4 % ~ 5 %) ≈ Ex-P (2 % ~ 4 %). Compared to a control with only chemical fertilizer, a 13 % ~ 38 % increase in P availability of experimental treatments mixed with chemical and organic fertilizers was attributed to the mineralization of Or-P, but not to the dissolution of inorganic P. Following organic fertilization, the phnF gene was dominant factor to promote the mineralization of Or-P, because it encodes CP lyases that pyrolyzes the CP bounds in organophosphate esters. Overall, organic fertilization decreased P release risk in soil aggregates, especially for the micro-aggregates that showed a higher capacity to activate non-available P and immobilize endogenous P in farmland soil. These results provide a theoretical guidance for the source control of P pollution in agro-ecosystems.

Effects of manure and nitrogen fertilization on soil microbial carbon fixation genes and associated communities in the Loess Plateau of China

The effects of long-term fertilization on soil carbon (C) cycling have been a key focus of agricultural sustainable development research. However, the influences of different fertilization treatments on soil microbial C fixation profiles are still unclear. Metagenomics technology and multivariate analysis were employed to inquire changes in soil properties, soil microbial C fixation genes and associated bacterial communities, and the influence of dominant soil properties on C fixation genes. The contents of soil C and nitrogen fractions were signicficantly higher in manure or combined with nitrogen fertilization (NM) than other treatments. The composition of soil microbial C fixation genes and associated bacterial communities varied among different fertilization treatments. Compared with other treatments, the total abundance of microbial C fixation genes and the abundance of Proteobacteria were significantly higher in NM than in other treatments, as well as the abundances of C fixation genes involved in dicarboxylate/4-hydroxybutyrate cycle and reductive citrate cycle. Key functional genes and main bacterial communities presented in the middle of the co-occurrence network. Soil organic carbon, total nitrogen, and microbial biomass nitrogen were the dominant soil properties influencing microbial C fixation genes and associated bacterial communitis. Fertilization increased the abundance of C fixation genes by affecting the changes in bacterial communities abundance mediated by soil properties. Overall, elucidating the responses of soil microbial C fixation genes and associated communities to different fertilization will enhance our understanding of the processes of soil C fixation in farmland.

Mapping, Distribution, Function, and High-Throughput Methodological Strategies for Soil Microbial Communities in the Agroecosystem in the Last Decades

The intricate interplay between SMCs and agroecosystems has garnered substantial attention in recent decades due to its profound implications for agricultural productivity, ecosystem sustainability, and environmental health. Understanding the distribution of SMCs is complemented by investigations into their functional roles within agroecosystems. Soil microbes play pivotal roles in nutrient cycling, organic matter decomposition, disease suppression, and plant‒microbe interactions, profoundly influencing soil fertility, crop productivity, and ecosystem resilience. Elucidating the functional diversity and metabolic potential of SMCs is crucial for designing sustainable agricultural practices that harness the beneficial functions of soil microbes while minimizing detrimental impacts on ecosystem services. Various molecular techniques, such as next-generation sequencing and high-throughput sequencing, have facilitated the elucidation of microbial community structures and dynamics at different spatial scales. These efforts have revealed the influence of factors such as soil type, land management practices, climate, and land use change on microbial community composition and diversity. Advances in high-throughput methodological strategies have revolutionized our ability to characterize SMCs comprehensively and efficiently. These include amplicon sequencing, metagenomics, metatranscriptomics, and metaproteomics, which provide insights into microbial taxonomic composition, functional potential, gene expression, and protein profiles. The integration of multiomics approaches allows for a more holistic understanding of the complex interactions within SMCs and their responses to environmental perturbations. In conclusion, this review highlights the significant progress made in mapping, understanding the distribution, elucidating the functions, and employing high-throughput methodological strategies to study SMCs in agroecosystems.

Combined metabolomic and microbial community analyses reveal that biochar and organic manure alter soil C-N metabolism and greenhouse gas emissions

The use of biochar to reduce the gas emissions from paddy soils is a promising approach. However, the manner in which biochar and soil microbial communities interact to affect CO2, CH4, and N2O emissions is not clearly understood, particularly when compared with other amendments. In this study, high-throughput sequencing, soil metabolomics, and quantitative real-time PCR were utilized to compare the effects of biochar (BC) and organic manure (OM) on soil microbial community structure, metabolomic profiles and functional genes, and ultimately CO2, CH4, and N2O emissions. Results indicated that BC and OM had opposite effects on soil CO2 and N2O emissions, with BC resulting in lower emissions and OM resulting in higher emissions, whereas BC, OM, and their combined amendments increased cumulative CH4 emissions by 19.5 %, 31.6 %, and 49.1 %, respectively. BC amendment increased the abundance of methanogens (Methanobacterium and Methanocella) and denitrifying bacteria (Anaerolinea and Gemmatimonas), resulting in an increase in the abundance of mcrA, amoA, amoB, and nosZ genes and the secretion of a flavonoid (chrysosplenetin), which caused the generation of CH4 and the reduction of N2O to N2, thereby accelerating CH4 emissions while reducing N2O emissions. Simultaneously, OM amendment increased the abundance of the methanogen Caldicoprobacter and denitrifying Acinetobacter, resulting in increased abundance of mcrA, amoA, amoB, nirK, and nirS genes and the catabolism of carbohydrates [maltotriose, D-(+)-melezitose, D-(+)-cellobiose, and maltotetraose], thereby enhancing CH4 and N2O emissions. Moreover, puerarin produced by Bacillus metabolism may contribute to the reduction in CO2 emissions by BC amendment, but increase in CO2 emissions by OM amendment. These findings reveal how BC and OM affect greenhouse gas emissions by modulating soil microbial communities, functional genes, and metabolomic profiles.

Feature sequence-based genome mining uncovers the hidden diversity of bacterial siderophore pathways.

Microbial secondary metabolites are a rich source for pharmaceutical discoveries and play crucial ecological functions. While tools exist to identify secondary metabolite clusters in genomes, precise sequence-to-function mapping remains challenging because neither function nor substrate specificity of biosynthesis enzymes can accurately be predicted. Here, we developed a knowledge-guided bioinformatic pipeline to solve these issues. We analyzed 1928 genomes of Pseudomonas bacteria and focused on iron-scavenging pyoverdines as model metabolites. Our pipeline predicted 188 chemically different pyoverdines with nearly 100% structural accuracy and the presence of 94 distinct receptor groups required for the uptake of iron-loaded pyoverdines. Our pipeline unveils an enormous yet overlooked diversity of siderophores (151 new structures) and receptors (91 new groups). Our approach, combining feature sequence with phylogenetic approaches, is extendable to other metabolites and microbial genera, and thus emerges as powerful tool to reconstruct bacterial secondary metabolism pathways based on sequence data.

New insights into the enteric methane production based on the archaeal genome atlas of ruminant gastrointestinal tract

IntroductionAs one of the important components of ruminant gastrointestinal tract (GIT) microbiome, archaea are involved in many biological processes, especially methanogenesis. In spite of being a well-recognised member of the mammalian gut microbiome, it remains poorly characterized, partly due to the lack of a unified reference genome catalog. ObjectivesThis study aimed to construct a unified genome atlas that captures the wider diversity in archaea and is thus more appropriate for functional and taxonomic exploration of ruminant GIT archaea. MethodsWe collected archaeal genomes from public sources and new data of this study. We performed phylogenetic and functional genomics analysis, prophage identification based on the genomes. Using collected genomes as a reference, we conducted metagenomic and metatranscriptomic analysis on rumen fluid samples from 18 dairy cows, and investigated the correlation between rumen archaeal communities and methane (CH4) production profiles. ResultsWe constructed the ruminant GIT archaeal genomes (RGAG) by compiling 405 strain-level (160 species) non-redundant archaeal genomes from more than 10 ruminant species. Investigating the functional heterogeneity and methanogenic structure within RGAG revealed that it possessed 1,124 (99.5%) unknown microbial biosynthetic gene clusters. A survey of RGAG-borne prophages identified 63 prophages with 122 host-beneficial genes and 18 auxiliary metabolic genes. The pipeline for both metagenomics and metatranscriptomics generated in the study revealed the roles of archaeal genomes under-assessed in general multi-omics analysis. The highly expressed genus Methanosphaera was negatively correlated with CH4 production at the RNA level. ConclusionA unified genome atlas of ruminant GIT archaea is constructed in the study. Our analyses revealed the advantages of metatranscriptomics over metagenomics in studying rumen archaeal communities and further demonstrated that the multifaceted functions of ruminant archaea remain undiscovered. Differences in rumen archaeal community structure among cattle with different CH4 production profiles may reflect the balance between rumen hydrogen production and methanogenesis. Our work provides a new resource for interrogating archaeal functions in the ruminant GIT and potential targets for future CH4 reduction.

Enhanced denitrification by sunlight–hematite: A neglected nitrogen flow pattern in red soil

Mineral-microbe interactions in the Earth's Critical Zone significantly influence elemental biogeochemical cycling and energy flow processes. This study addresses the key scientific question of how semiconducting minerals drive microbial nitrogen cycling. In the red soil environment, the presence of semiconducting minerals enhances the denitrification process mediated by facultative microorganisms (Pseudomonas aeruginosa PAO1) with denitrifying activity. Compared to darkness, light significantly enhanced the synergistic denitrification kinetic process of red soil and Pseudomonas aeruginosa PAO1 (1.87 times). Cyclic voltammetry shows that the P. aeruginosa PAO1-red soil synergistic system exhibits distinct redox peaks under light. The constant potential current curve and electrochemical impedance spectroscopy measurements reveal a high photocurrent density (1.0 μA/cm2) and minimal polarization resistance (102 Ω) under this condition. These findings confirm that the sunlight-red soil-P. aeruginosa PAO1 synergistic process has excellent electron generation and migration capacity, active redox reactions, and good electron compatibility. Additionally, the photoelectrons of semiconductive minerals in red soil profoundly impact the metabolic processes of microbial denitrification functional genes. Using real-time polymerase chain reaction (qPCR) gene array technology, the abundance of nitrogen metabolism functional genes in P. aeruginosa PAO1 increased by 200 % during the light-red soil synergistic process. Notably, denitrification-related genes (ureC, nirS1, gdhA, and nosZ2) were significantly upregulated. This study confirms that semiconducting minerals are involved in the nitrogen cycle pathway of microbial denitrification and supplements the theory of mineral-microbial synergistic element biogeochemical cycling in the natural environment.