The best practice for microbiome analysis using R

Warming exacerbates the effects of pesticides on the soil collembolan gut microbiome and antibiotic resistome

In the context of global climate warming, studies have yet to fully clarify how pollutants affect the gut microbiome and antibiotic resistance genes (ARGs) in nontarget soil fauna. This study investigates the interactive effects of pesticide exposure (imidacloprid) and elevated temperature on the gut bacterial community and ARGs in the model soil collembolan Folsomia candida. Our results demonstrate warming exacerbates the toxicity of imidacloprid in collembolans. While exposure to both warming and pesticide significantly altered the gut microbial composition of F. candida, impairing microbial metabolic diversity and potential host defense mechanisms, it also increased collembolan mortality. This combined exposure significantly enhanced the abundance and diversity of ARGs in the collembolan gut. A notable correlation between ARGs and mobile genetic elements (MGEs) underscores the potential risk of ARG transmission. Co-occurrence network analysis identified 52 bacterial genera as potential ARG hosts. Additionally, pure-culture exposure experiments with the isolated bacterium Serratia liquefaciens revealed the adaptability of ARG hosts to pesticide and warming stress plays an important role in driving the observed increase in ARGs. In conclusion, this study highlights the synergistic effects of climate warming and pesticide contamination on nontarget soil organisms, emphasizing the potential long-term risks to soil ecosystem health and stability.

Diagnostic biomarkers and immune infiltration profiles common to COVID-19, acute myocardial infarction and acute ischaemic stroke using bioinformatics methods and machine learning

BACKGROUND

COVID-19 is a disease that affects people globally. Beyond affecting the respiratory system, COVID-19 patients are at an elevated risk for both venous and arterial thrombosis. This heightened risk contributes to an increased probability of acute complications, including acute myocardial infarction (AMI) and acute ischemic stroke (AIS). Given the unclear relationship between COVID-19, AMI, and AIS, it is crucial to gain a deeper understanding of their associations and potential molecular mechanisms. This study aims to utilize bioinformatics to analyze gene expression data, identify potential therapeutic targets and biomarkers, and explore the role of immune cells in the disease.

METHODS

This study employed three Gene Expression Omnibus (GEO) datasets for analysis, which included data on COVID-19, AMI and AIS. We performed enrichment analysis on the co-DEGs for these three diseases to clarify gene pathways and functions, and also examined the relationship between co-DEGs and immune infiltration. Machine learning techniques and protein-protein interaction networks (PPI) were used to identify hub genes within the co-DEGs. Finally, we employed a dual validation strategy integrating independent GEO datasets and in vitro experiments with human blood samples to comprehensively assess the reliability of our experimental findings.

RESULTS

We identified 88 co-DEGs associated with COVID-19, AMI and AIS. Enrichment analysis results indicated that co-DEGs were significantly enriched in immune inflammatory responses related to leukocytes and neutrophils. Immune infiltration analysis revealed significant differences in immune cell populations between the disease group and the normal group. Finally, genes selected through machine learning methods included: CLEC4E, S100A12, and IL1R2. Based on the PPI network, the top ten most influential DEGs were identified as MMP9, TLR2, TLR4, ITGAM, S100A12, FCGR1A, CD163, FCER1G, FPR2, and CLEC4D. The integration of the protein-protein interaction (PPI) network with machine learning techniques facilitated the identification of S100A12 as a potential common biomarker for early diagnosis and a therapeutic target for all three diseases. Ultimately, validation of S100A12 showed that it was consistent with our experimental results, confirming its reliability as a biomarker. Moreover, it demonstrated good diagnostic performance for the three diseases.

CONCLUSION

We employed bioinformatics methods and machine learning to investigate common diagnostic biomarkers and immune infiltration characteristics of COVID-19, AMI and AIS. Functional and pathway analyses indicated that the co-DEGs were primarily enriched in immune inflammatory responses related to leukocytes and neutrophils. Through two machine learning approaches and the PPI network, and subsequent validation and evaluation, we identified S100A12 as a potential common therapeutic target and biomarker related to immune response that may influence these three diseases.

Arbuscular mycorrhizal fungi build a bridge for soybeans to recruit Pseudomonas putida

The assembly of the rhizosphere microbiome determines its functionality for plant fitness. Although the interactions between arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) play important roles in plant growth and disease resistance, research on the division of labor among the members of the symbionts formed among plants, AMF, and PGPR, as well as the flow of carbon sources, is still insufficient. To address the above questions, we used soybean (Glycine max), Funneliformis mosseae, and Pseudomonas putida KT2440 as research subjects to establish rhizobiont interactions and to elucidate the signal exchange and division of labor among these components. Funneliformis mosseae can attract P. putida KT2440 by secreting cysteine as a signaling molecule and can promote the colonization of P. putida KT2440 in the soybean rhizosphere. Colonized P. putida KT2440 can stimulate the l-tryptophan secretion of the host plant and can lead to the upregulation of genes involved in converting methyl-indole-3-acetic acid (Me-IAA) into IAA in response to l-tryptophan stimulation. Collectively, we decipher the tripartite mechanism of rhizosphere microbial community assembly via cross-kingdom interactions.

From air to insight: the evolution of airborne DNA sequencing technologies

Historically, the analysis of airborne biological organisms relied on microscopy and culture-based techniques. However, technological advances such as PCR and next-generation sequencing now provide researchers with the ability to gather vast amounts of data on airborne environmental DNA (eDNA). Studies typically involve capturing airborne biological material, followed by nucleic acid extraction, library preparation, sequencing and taxonomic identification to characterize the eDNA at a given location. These methods have diverse applications, including pathogen detection in agriculture and human health, air quality monitoring, bioterrorism detection and biodiversity monitoring. A variety of methods are used for airborne eDNA analysis, as no single pipeline meets all needs. This review outlines current methods for sampling, extraction, sequencing and bioinformatic analysis, highlighting how different approaches can influence the resulting data and their suitability for specific use cases. It also explores current applications of airborne eDNA sampling and identifies research gaps in the field.

Ocular surface microbiome: Influences of physiological, environmental, and lifestyle factors

PURPOSE

The ocular surface (OS) microbiome is influenced by various factors and impacts on ocular health. Understanding its composition and dynamics is crucial for developing targeted interventions for ocular diseases. This study aims to identify host variables, including physiological, environmental, and lifestyle (PEL) factors, that influence the ocular microbiome composition and establish valid associations between the ocular microbiome and health outcomes.

METHODS

The 16S rRNA gene sequencing was performed on OS samples collected from 135 healthy individuals using eSwab. DNA was extracted, libraries prepared, and PCR products purified and analyzed. PEL confounding factors were identified, and a cross-validation strategy using various bioinformatics methods including Machine learning was used to identify features that classify microbial profiles.

RESULTS

Nationality, allergy, sport practice, and eyeglasses usage are significant PEL confounding factors influencing the eye microbiome. Alpha-diversity analysis revealed significant differences between Spanish and Italian subjects (p-value < 0.001), with a median Shannon index of 1.05 for Spanish subjects and 0.59 for Italian subjects. Additionally, 8 microbial genera were significantly associated with eyeglass usage. Beta-diversity analysis indicated significant differences in microbial community composition based on nationality, age, sport, and eyeglasses usage. Differential abundance analysis identified several microbial genera associated with these PEL factors. The Support Vector Machine (SVM) model for Nationality achieved an accuracy of 100%, with an AUC-ROC score of 1.0, indicating excellent performance in classifying microbial profiles.

CONCLUSION

This study underscores the importance of considering PEL factors when studying the ocular microbiome. Our findings highlight the complex interplay between environmental, lifestyle, and demographic factors in shaping the OS microbiome. Future research should further explore these interactions to develop personalized approaches for managing ocular health.

Endozoicomonas dominance and Vibrionaceae stability underpin resilience in urban coral Madracis auretenra

Coral resilience varies across species, with some exhibiting remarkable stability and adaptability, often mediated by their associated microbiomes. Given the species-specific nature of coral-microbiome interactions, investigating the microbiomes of urban-adapted corals provides critical insights into the health, dynamics, and functioning of coral holobionts. In this study, we examined the microbiome of Madracis auretenra, a Caribbean coral from Santa Marta, Colombia, across contrasting environmental conditions. Over two years, we compared the microbiomes of healthy and stressed coral colonies from two distinct reef habitats-urban and protected-using 16S rRNA gene sequencing (V4 region) to assess microbial diversity. Our findings revealed microbial richness and diversity were primarily influenced by seasonal and local factors rather than host-specific traits such as interaction with algae, health status, or microhabitat. These variations were not substantial enough to disrupt the overall microbial community structure, which remained stable across temporal and spatial scales. Dominant taxa included Endozoicomonas, along with Vibrionaceae and Rhodobacteraceae, which form dense ecological interaction networks. Notably, nutrient and oxygen levels emerged as key drivers of microbiome fluctuations, yet Vibrionaceae populations exhibited exceptional temporal stability. These findings highlight the presence of a well-structured and resilient coral microbiome with minimal seasonal variability, even in urban-influenced environments. We propose that the dominance of Endozoicomonas and the stability of Vibrionaceae populations play a pivotal role in maintaining microbiome balance, ultimately contributing to the ecological resilience of M. auretenra in dynamic reef habitats.

Bioclimatic zonation and spatial-scale dependence of lacustrine microbial assemblages

Bioclimatic zonation is critical for understanding how climate shapes biodiversity and biogeographic patterns. However, existing studies have primarily focused on macroorganisms, leaving microbial communities largely underexplored. This study seeks to address this gap through extensive sampling of bacterial communities from 931 sediment samples across 199 lakes in China. Based on the obtained data, we identified five distinct lacustrine microbial bioclimatic zones, each showing significant differences in multiple facets of bacterial diversity (i.e., alpha, beta, and gamma diversity) and clear bioclimatic zone-dependent microbial biogeographic patterns. Notably, the alpha and beta diversity of the bacterial communities showed opposing patterns across bioclimatic zones. Dominant environmental variables-specifically mean annual temperature, elevation, lake hydrological variables, and sediment pH-exerted contrasting effects on the alpha and beta diversity and played critical roles in shaping microbial community distribution at different spatial scales. At continental scales, predominant geographic and climatic variables dictated the patterns of bioclimatic zonation of lacustrine microbial communities. At regional scales, hydrological variables influenced the dispersal capacity of lake microbes, whereas sediment physicochemical variables were the most important selection factors shaping local microbial communities. Furthermore, our findings indicated that bioclimatic boundaries substantially enhanced the contribution of variable selection on bacterial community assembly and led to marked changes in distance-decay relationships in community dissimilarities. Overall, this study established a continental bioclimatic framework for lacustrine microbial communities, clarifying how environmental variables control microbial distributions across spatial scales, providing new insights into microbial biogeography, and advancing our knowledge about biodiversity under future climate change scenarios.

Evaluation of extended-spectrum β-lactamase producing bacteria in feces of shelter dogs as a biomarker for altered gut microbial taxa and functional profiles

Background

The USA is home to 83-88 million dogs, with 3-7 million living in shelters. Shelter dogs move through the supply chain from their geographical origin to adoptive homes, with possible exposure to pathogens and shift in their gut microbiota. However, research in this area is limited. This study examined the effects of intestinal colonization by ESBL bacteria on gut taxa abundance, diversity, and functions in 52 shelter dogs of various ages, sexes, and fertility statuses.

Methodology

We isolated fecal DNA, sequenced their 16S, processed the sequences using DADA2, identified taxa profiles in each dog by Phyloseq, and analyzed Chao1, Shannon, and Simpson alpha diversity by ggplot2 and Wilcoxon test. We analyzed beta diversity using Bray-Curtis dissimilarity matrix from the vegan package. Differential abundance of taxa, gut microbiome functions, and differential abundance of microbiome functions were analyzed using DESeq2, PICRUSt2, and ALDEx2, respectively, with Wilcoxon rank and Kruskal-Wallis tests for comparisons between dog groups.

Results

Firmicutes (69.3%), Bacteroidota (13.5%), Actinobacteriota (6.77%), Proteobacteria (5.54%), and Fusobacteriota (4.75%) were the major phyla in the gut of shelter dogs. ESBL bacteria colonized dogs had reduced gut microbiota alpha diversity than non-colonized dogs. The abundance levels of the following phyla (Proteobacteria, Deferribacterota, Bacteroidota, Fusobacteriota, and Spirochaetota), class (Gammaproteobacteria, Bacteroidia, Deferribacteres, Brachyspirae, and Fusobacteria), and families (Enterobacteriaceae, Peptostreptococcaceae, Lactobacillaceae, Lachnospiraceae, Prevotellaceae, and Peptostreptococcaceae) were significantly (p < 0.05) varied between the two dog groups. Further stratified analysis by age, sex, and spaying/neutering status influenced the abundance of taxa in ESBL bacteria colonized dogs, indicating these covariates act as effect modifiers. Most gut metabolic and biosynthetic pathways were downregulated in ESBL bacteria colonized dogs compared to non-colonized dogs. However, alpha-linolenic acid metabolism and shigellosis, fluorobenzoate degradation, allantoin degradation, toluene degradation, glycol degradation, fatty acid and beta-oxidation, and glyoxylate metabolism bypass pathways were increased in dogs colonized by ESBL bacteria.

Conclusion

Colonization by ESBL bacteria marks altered gut microbiota. Dog's demography and fertility status modify the alterations, indicating host factors and ESBL bacteria interplay to shape gut microbiota. ESBL bacteria or other factors reprogram gut microbiome functions through down and upregulating multiple metabolic and biosynthesis pathways to promote ESBL bacteria colonization.

Symbiotic bacteria play crucial roles in a herbivorous mite host suitability

BACKGROUND

The tomato russet mite (TRM), Aculops lycopersici, is a strictly herbivorous and economically significant pest that infests Solanaceae plants, but its host suitability varies, showing high performance on tomatoes. Although symbiotic bacteria have been suggested to play crucial roles in the host adaptation of herbivores, their effects on TRM remain unclear.

RESULTS

In this study, using next generation high-throughput sequencing of the bacterial 16S rRNA data, we identified the bacterial diversity and community composition of TRM feeding on tomato, eggplant, and chili. Our results show no significant difference in the bacterial community composition of TRM across three host plants. However, the relative density of Escherichia coli (TRM_Escherichia) showed 9.36-fold higher on tomato than on eggplant and chili. These results align with the observed TRM performance among three host plants. When TRM_Escherichia was reduced using antibiotics, the treated TRM decreased the population density on tomato. However, when we transferred TRM from eggplant to tomato, the population density of TRM increased, coinciding with an increase of the TRM_Escherichia density. These results indicate that TRM_Escherichia may affect the host suitability of TRM. Our fluorescence in situ hybridization (FISH) results further showed that TRM_Escherichia is primarily distributed in the salivary glands. Metagenomic data results suggest that TRM_Escherichia functions in food digestion and energy metabolism.

CONCLUSION

We provided the first comprehensive analysis of TRM bacterial communities. Our findings demonstrate that the symbiotic bacterium TRM_Escherichia may play crucial roles in the suitability of TRM feeding on different Solanaceae hosts. © 2024 Society of Chemical Industry.

Phages Affect Soil Dissolved Organic Matter Mineralization by Shaping Bacterial Communities

Viruses are considered to regulate bacterial communities and terrestrial nutrient cycling, yet their effects on bacterial metabolism and the mechanisms of carbon (C) dynamics during dissolved organic matter (DOM) mineralization remain unknown. Here, we added active and inactive bacteriophages (phages) to soil DOM with original bacterial communities and incubated them at 18 or 23 °C for 35 days. Phages initially (1-4 days) reduced CO2 efflux rate by 13-21% at 18 °C and 3-30% at 23 °C but significantly (p < 0.05) increased by 4-29% at 18 °C and 9-41% at 23 °C after 6 days, raising cumulative CO2 emissions by 14% at 18 °C and 21% at 23 °C. Phages decreased dominant bacterial taxa and increased bacterial community diversity (consistent with a "cull-the-winner" dynamic), thus altering the predicted microbiome functions. Specifically, phages enriched some taxa (such as Pseudomonas, Anaerocolumna, and Caulobacter) involved in degrading complex compounds and consequently promoted functions related to C cycling. Higher temperature facilitated phage-bacteria interactions, increased bacterial diversity, and enzyme activities, boosting DOM mineralization by 16%. Collectively, phages impact soil DOM mineralization by shifting microbial communities and functions, with moderate temperature changes modulating the magnitude of these processes but not qualitatively altering their behavior.

The responses of root exudates and microbiome in the rhizosphere of main plant and aromatic intercrops to soil Cr stress

Soil chromium (Cr) stress has a well-recognized negative impact on plant growth, and intercropping is a commonly used method to mitigate heavy metal toxicity to main plants. However, the responses of root exudates-microbial and their interactions among soil zones to soil Cr stress are always in need of clarification in intercropping system. In this study, three intercropping patterns (CT, Malus only; TM, Malus × Mentha and TA, Malus × Ageratum) with different soil Cr addition levels (NCR, LCR, HCR) were applied, and the rhizosphere ecological traits in the main plant (FRS) and intercrop (ARS) were investigated. The results indicate that intercropping with either Mentha or Ageratum has a positive effect on main plants response to soil Cr stress, and intercropping with Ageratum showing a more significant effect. Importantly, we found that the rhizosphere of main plant tends to alleviate stress by accumulating organic acids and amino acids, while aromatic plants exhibit a broader accumulation of metabolites. Additionally, we identified five core differential microbial genera. Our findings provide novel insights into intercrop Cr detoxification in the main plant.

Non-Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints and Machine Learning

Moyamoya disease (MMD) is a progressive cerebrovascular disorder that increases the risk of intracranial ischemia and hemorrhage. Timely diagnosis and intervention can significantly reduce the risk of new-onset stroke in patients with MMD. However, the current diagnostic methods are invasive and expensive, and non-invasive diagnosis using biomarkers of MMD is rarely reported. To address this issue, nanoparticle-enhanced laser desorption/ionization mass spectrometry (LDI MS) was employed to record serum metabolic fingerprints (SMFs) with the aim of establishing a non-invasive diagnosis method for MMD. Subsequently, a diagnostic model was developed based on deep learning algorithms, which exhibited high accuracy in differentiating the MMD group from the HC group (AUC = 0.958, 95% CI of 0.911 to 1.000). Additionally, hierarchical clustering analysis revealed a significant association between SMFs across different groups and vascular cognitive impairment in MMD. This approach holds promise as a novel and intuitive diagnostic method for MMD. Furthermore, the study may have broader implications for the diagnosis of other neurological disorders.

MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics

The rapid growth of microbiome research has generated an unprecedented amount of multi-omics data, presenting challenges in data analysis and visualization. To address these issues, we present MicrobiomeStatPlots, a comprehensive platform offering streamlined, reproducible tools for microbiome data analysis and visualization. This platform integrates essential bioinformatics workflows with multi-omics pipelines and provides 82 distinct visualization cases for interpreting microbiome datasets. By incorporating basic tutorials and advanced R-based visualization strategies, MicrobiomeStatPlots enhances accessibility and usability for researchers. Users can customize plots, contribute to the platform's expansion, and access a wealth of bioinformatics knowledge freely on GitHub (https://github.com/YongxinLiu/MicrobiomeStatPlot). Future plans include extending support for metabolomics, viromics, and metatranscriptomics, along with seamless integration of visualization tools into omics workflows. MicrobiomeStatPlots bridges gaps in microbiome data analysis and visualization, paving the way for more efficient, impactful microbiome research.

EasyMetagenome: A user-friendly and flexible pipeline for shotgun metagenomic analysis in microbiome research

Shotgun metagenomics has become a pivotal technology in microbiome research, enabling in-depth analysis of microbial communities at both the high-resolution taxonomic and functional levels. This approach provides valuable insights of microbial diversity, interactions, and their roles in health and disease. However, the complexity of data processing and the need for reproducibility pose significant challenges to researchers. To address these challenges, we developed EasyMetagenome, a user-friendly pipeline that supports multiple analysis methods, including quality control and host removal, read-based, assembly-based, and binning, along with advanced genome analysis. The pipeline also features customizable settings, comprehensive data visualizations, and detailed parameter explanations, ensuring its adaptability across a wide range of data scenarios. Looking forward, we aim to refine the pipeline by addressing host contamination issues, optimizing workflows for third-generation sequencing data, and integrating emerging technologies like deep learning and network analysis, to further enhance microbiome insights and data accuracy. EasyMetageonome is freely available at https://github.com/YongxinLiu/EasyMetagenome.

A comparative study on the antipyretic effect and underlying mechanisms of different bile-fermented Arisaemas

ETHNOPHARMACOLOGICAL RELEVANCE

Cattle bile Arisaema (CBA) and Pig bile Arisaema (PBA) are both processed products fermented from Arisaema erubescens (Wall.) Schott and animal bile, which are recorded in China Pharmacopoeia. Traditionally, bile Arisaema was often used for clearing heat and eliminating phlegm, calming wind and calming panic. Modern pharmacological researches suggest that both two drugs exert an antipyretic effect, while there is lack of the systematical and comparative evidence on underlying mechanism.

AIM OF THE STUDY

To comprehensively clarify the differences and underlying mechanisms of antipyretic effect of the two drugs.

METHODS

In this study, an accurate and reliable detection method based on ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-TQ MS) for comparing the content difference of bile acids from the two drugs was successfully established and applied. Besides, a dry yeast-induced fever rat model was established, and rectal temperature and content of pyrogenic cytokines were conducted to evaluate the antipyretic effect of CBA and PBA. Serum and hypothalamus untargeted metabolomics analysis based on ultra-performance liquid chromatography coupled with quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF-MS/MS) technology were performed for elucidating the changes of metabolic profile.

RESULTS

The results indicated that CBA and PBA both exerted a significantly antipyretic effect, but CBA showed the characteristic of quicker onset and longer duration than that of PBA. The ELISA and western blotting analysis exhibited that the underlying antipyretic mechanism of the two drugs was closely associated with inhibiting inflammation through regulating TLR4/NF-κB signaling pathway. Moreover, the metabolism pathway analysis revealed that lipid metabolism and amino acid metabolism were greatly disturbed, which showed a certain correlation with antipyretic effect of two drugs.

CONCLUSION

Collectively, our results delineate a potential mechanism of two different bile Arisaemas against febrile via regulating metabolic disorders and targeting inhibition of inflammation for the improvement of fever symptom of the body. Notably, our current study suggested that CBA might be a better choice for suppressing fever clinically.

Microplastics mediates the spread of antimicrobial resistance plasmids via modulating conjugal gene expression

Antimicrobial resistance (AMR) and environmental degradation are existential global public health threats. Linking microplastics (MPs) and AMR is particularly concerning as MPs pollution would have significant ramifications on controlling of AMR; however, the effects of MPs on the spread and genetic mechanisms of AMR bacteria remain unclear. Herein, we performed Simonsen end-point conjugation to investigate the impact of four commonly used MPs on transfer of clinically relevant plasmids. The transfer breadth of a representative pA/C_MCR-8 plasmid across bacterial communities was confirmed by the cell sorting and 16S rRNA gene amplicon sequencing. Our study shows that exposure to four commonly found MPs promotes the conjugation rates of four clinically relevant AMR plasmids by up to 200-fold, when compared to the non-exposed group and that the transfer rates are MP concentrations demonstrate a positive correlation with higher transfer rates. Furthermore, we show that MPs induce the expression of plasmid-borne conjugal genes and SOS-linked genes such as recA, lexA, dinB and dinD. High-throughput sequencing of the broad transmission of plasmid pA/C_MCR-8, shows distribution over two main phyla, Pseudomonadota (50.0 %-95.0 %) and Bacillota (0.4 %-2.0 %). These findings definitively link two global health emergencies - AMR and environmental degradation via MPs, and to tackle global AMR, we must also now consider plastic utilisation and waste management.

Altitudinal decline of vegetation restoration effects on soil microbial communities on high-altitude roadside slops: Environmental drivers and management implications

Construction activities in high-altitude regions have left many bare roadside slopes vulnerable to degradation, complicating restoration efforts. Soil microorganisms are vital for plant growth and nutrient cycling, yet their responses to restoration efforts at various altitudes remains uncertain. This study investigates soil microbial composition, network properties, ecological functions, keystone taxa, and environmental drivers across three restored vegetation types: herbaceous plants (H), shrubs + herbaceous plants (SH), and trees + shrubs + herbaceous plants (TSH) at elevations from 3100 to 3800 m. Our structural equation model identifies elevation and vegetation type as key factors influencing microbial communities, directly or indirectly, through their effects on plant and soil properties. We also found that bacterial α-diversity decreased with elevation, while fungal α-diversity increased, resulting in more complex but less stable microbial networks. R-strategists predominated in the herbaceous type (H) and at lower altitudes, whereas K-strategists dominated in the SH and TSH types, and at higher altitudes. Keystone species of type H, associated with pathotrophs and plant pathogens, showed a negative correlation with plant properties, which weakened at higher altitudes. Both bacterial and fungal communities were driven more by abiotic factors, especially ammonium (NH4+-N) and dissolved organic nitrogen (DON) for bacteria and soil water content (SWC) for fungi. This study proposes managing restoration-sensitive microbes and keystone taxa associated with specific vegetation types for effective restoration at appropriate altitudes, especially those shared by SH and TSH. Furthermore, integrating suitable legume or nitrogen-fixing woody vegetation into restoration efforts at lower altitudes and herbaceous vegetation into higher altitudes has the potential to significantly enhance plant growth and health at high altitudes. This study offers valuable guidance for optimizing restoration strategies by effectively addressing key environmental factors and nurturing essential microbial species crucial for successful restoration efforts and global warming mitigation.

Genomic and Gut Microbiome Evaluations of Growth and Feed Efficiency Traits in Broilers

In this study, we combined genomic and gut microbiome data to evaluate 13 economically important growth and feed efficiency traits in 407 Dahen broilers, including body weight (BW) at four, six, nine, and ten weeks of age (BW4, BW6, BW9, and BW10), as well as the average daily gain (ADG6, ADG9, and ADG10), feed conversion ratio (FCR6, FCR9, and FCR10), and residual feed intake (RFI6, RFI9, and RFI10) for the three growing ages. The highest ADG and lowest FCR were observed at nine and six weeks of age, respectively. We obtained 47,872 high-quality genomic single-nucleotide polymorphisms (SNPs) by sequencing the genomes and 702 amplicon sequence variants (ASVs) of the gut microbiome by sequencing the 16S rRNA gene, both of which were used for analyses of linear mixed models. The heritability estimates (± standard error, SE) ranged from 0.103 ± 0.072 to 0.156 ± 0.079 for BW, 0.154 ± 0.074 to 0.276 ± 0.079 for the ADG, 0.311 ± 0.076 to 0.454 ± 0.076 for the FCR, and 0.413 ± 0.077 to 0.609 ± 0.076 for the RFI traits. We consistently observed moderate and low negative genetic correlations between the BW traits and the FCR and RFI traits (r = -0.562 to -0.038), whereas strong positive correlations were observed between the FCR and RFI traits (r = 0.564 to 0.979). For the FCR and RFI traits, strong positive correlations were found between the measures at the three ages. In contrast to the genomic contribution, we did not detect a gut microbial contribution to all of these traits, as the estimated microbiabilities did not confidently deviate from zero. We systematically evaluated the contributions of host genetics and gut microbes to several growth and feed efficiency traits in Dahen broilers, and the results show that only the host genetics had significant effects on the phenotypic variations in a flock. The parameters obtained in this study, based on the combined use of genomic and gut microbiota data, may facilitate the implementation of efficient breeding schemes in Dahen broilers.

Effects of artemisinin sustained-release algaecides on in-situ cyanobacterial inhibition and microbes-floating plants dominated ecosystem functions in artificial landscape lake

The artemisinin sustained-release algaecides (ASAs) have been proven to be a safe and effective mean of inhibiting cyanobacteria in laboratory experiments. However, their effectiveness and impacts on ecosystem functions (EF) in natural waters are still unclear. In this study, the in-situ inhibitory effect of ASAs on cyanobacteria in natural waters was investigated over a period of 110 days to assess EF impacts dominated by microbes and floating plants. The results indicated that ASAs had a long-term inhibitory effect on cyanobacteria. ASAs did not affect sediment but increased TOC and TP in the water column in 2-10 days. Microbial diversity and network analyses indicated that ASAs enhanced bacterial diversity, network complexity, and hub-bacteria in networks. Metabolic pathway predictions and CCA analysis showed that ASAs maintained the stability of EF by enhancing the metabolic capacities of bacteria, and the relationships between metabolic microorganisms and environmental factors. PLS-PM revealed that ASAs primarily drove bacterial resistance to cyanobacteria, which was the key mechanism for its long-term inhibition of cyanobacteria. However, the early outbreak of floating plants was not conducive to the long-term inhibition of cyanobacteria by ASAs. This study provides new insights into the mechanisms and ecological impacts of cyanobacterial inhibition by ASAs in complex aquatic environments.

Sex-Dependent Gut Microbiota Features and Functional Signatures in Metabolic Disfunction-Associated Steatotic Liver Disease

Background/Objectives: This study investigates the gut microbiota's role in metabolic dysfunction-associated steatotic liver disease (MASLD), focusing on microbial and functional signatures and sex-based differences. Methods: Using baseline data from 98 MASLD patients and 45 controls from the Fatty Liver in Obesity (FLiO) study, the gut microbiota was profiled with 16S gene sequencing, followed by statistical and machine learning analyses to identify disease-associated microbial signatures. Results: Notable alpha and beta diversity differences were observed between MASLD patients and the controls, varying by sex. Machine learning models highlighted specific microbial signatures for each sex, achieving high accuracy (area under the receiver operating characteristic curves of 0.91 for women and 0.72 for men). The key microbial taxa linked to MASLD included Christensenella and Limosilactobacillus in women and Beduinibacterium and Anaerotruncus in men. Functional profiling showed that MASLD patients had increased pathways for amine biosynthesis and amino acid degradation, while the controls exhibited enhanced fermentation pathways. These microbial features were associated with systemic inflammation, insulin resistance, and metabolite production linked to gut dysbiosis. Conclusions: The findings support the potential of gut microbiota signatures to be used as non-invasive indicators of MASLD and highlight sex-specific variations that could inform personalized diagnostic and therapeutic approaches.

Nanopore sequencing: flourishing in its teenage years

Over the past decade, nanopore sequencing has experienced significant advancements and changes, transitioning from an initially emerging technology to a significant instrument in the field of genomic sequencing. However, as advancements in next-generation sequencing technology persist, nanopore sequencing also improves. This paper reviews the developments, applications, and outlook on nanopore sequencing technology. Currently, nanopore sequencing supports both DNA and RNA sequencing, making it widely applicable in areas such as telomere-to-telomere (T2T) genome assembly, direct RNA sequencing (DRS), and metagenomics. The openness and versatility of nanopore sequencing have established it as a preferred option for an increasing number of research teams, signaling a transformative influence on life science research. As the nanopore sequencing technology advances, it provides a faster, more cost-effective approach with extended read lengths, demonstrating the significant potential for complex genome assembly, pathogen detection, environmental monitoring, and human disease research, offering a fresh perspective in sequencing technologies.

Multi-omics approach in gut and environmental microbiota research under the One Health concept

The One Health concept, although formulated two decades ago, remains challenging to implement. It necessitates the integration of numerous scientific disciplines, diverse techniques and various professional expertise. Furthermore, it often requires the collaboration of different institutions, encompassing both scientific and administrative entities. This concept posits that human health is intrinsically linked to and dependent on the well-being of animals, plants and the broader environment, while the environment not only sustains life but can also serve as a source of xenobiotics that affect the health-disease balance. In this context, all components of the potential exposome, encompassing the entirety of factors of various natures that influence health throughout life, must be considered comprehensively. Achieving this holistic understanding typically demands the application of multiple research techniques, known as the multi-omics approach and the adoption of an integrated method for data analysis. This project endeavoured to utilise such an integrated approach, examining data from diverse origins: human (children stool for gut microbiota analysis) and environmental (groundwater for hyporheic zone microbial analysis), as well as implementing comprehensive informatic tools for data processing. Analysis of stool samples revealed significant differences in gut microbiota composition across various taxonomic levels between normal weight, overweight and obese children. Additionally, a potential link between certain xenobiotics and gut microbiota composition, body weight and overall health status was identified. Analysis of groundwater samples revealed significant differences in hyporheic zone microbial composition at various taxonomic levels based on the sampling location and depth. Key geochemical factors influencing sample diversity were also identified. The promising results obtained not only demonstrate the viability of this methodology but also pave the way for future research initiatives.

Neutrophil-centric analysis of gastric cancer: prognostic modeling and molecular insights

Gastric cancer remains a significant global health concern with poor prognosis. This study investigates the role of neutrophils in gastric cancer progression and their potential as prognostic indicators. Using multi-omics approaches, including Weighted Gene Co-expression Network Analysis (WGCNA), machine learning, and single-cell analysis, we identified neutrophil-associated gene signatures and developed a robust prognostic model. Our findings reveal distinct gastric cancer subtypes based on neutrophil-associated genes, with one subtype showing increased neutrophil infiltration and poorer prognosis. Single-cell analysis uncovered neutrophil-associated alterations in cell composition, gene expression profiles, and intercellular communication within the tumor microenvironment. Additionally, we explored the relationship between neutrophil-associated genes, microbiota composition, and alternative splicing events in gastric cancer. Furthermore, we identified QKI as a key regulator of alternative splicing and demonstrated its role in promoting malignant phenotypes and enhancing TGF-beta signaling and epithelial-mesenchymal transition in gastric cancer cells by wet experiment. Lastly, the role of QKI in the association with drug resistance and the identification of specific agents for treating QKI-associated drug resistance were also explored. This comprehensive study provides novel insights into the complex interplay between neutrophils, the tumor microenvironment, microbiota, alternative splicing and gastric cancer progression, offering potential new targets for therapeutic intervention.

Single-cell sequencing to multi-omics: technologies and applications

Cells, as the fundamental units of life, contain multidimensional spatiotemporal information. Single-cell RNA sequencing (scRNA-seq) is revolutionizing biomedical science by analyzing cellular state and intercellular heterogeneity. Undoubtedly, single-cell transcriptomics has emerged as one of the most vibrant research fields today. With the optimization and innovation of single-cell sequencing technologies, the intricate multidimensional details concealed within cells are gradually unveiled. The combination of scRNA-seq and other multi-omics is at the forefront of the single-cell field. This involves simultaneously measuring various omics data within individual cells, expanding our understanding across a broader spectrum of dimensions. Single-cell multi-omics precisely captures the multidimensional aspects of single-cell transcriptomes, immune repertoire, spatial information, temporal information, epitopes, and other omics in diverse spatiotemporal contexts. In addition to depicting the cell atlas of normal or diseased tissues, it also provides a cornerstone for studying cell differentiation and development patterns, disease heterogeneity, drug resistance mechanisms, and treatment strategies. Herein, we review traditional single-cell sequencing technologies and outline the latest advancements in single-cell multi-omics. We summarize the current status and challenges of applying single-cell multi-omics technologies to biological research and clinical applications. Finally, we discuss the limitations and challenges of single-cell multi-omics and potential strategies to address them.

Looking at the full picture, using topic modeling to observe microbiome communities associated with disease

The microbiome, a complex micro-ecosystem, helps the host with various vital physiological processes. Alterations of the microbiome (dysbiosis) have been linked with several diseases, and generally, differential abundance testing between the healthy and patient groups is performed to identify important bacteria. However, providing a singular species of bacteria to an individual as treatment has not been as successful as fecal microbiota transplant therapy, where the entire microbiome of a healthy individual is transferred. These observations suggest that a combination of bacteria might be crucial for the beneficial effects. Here we provide the framework to utilize topic modeling, an unsupervised machine learning approach, to identify a community of bacteria related to health or disease. Specifically, we used our previously published gut microbiome data of patients with multiple sclerosis (MS), a neurodegenerative disease linked to a dysbiotic gut microbiome. We identified communities of bacteria associated with MS, including genera previously discovered, but also others that would have been overlooked by differential abundance testing. This method can be a useful tool for analyzing the microbiome, and it should be considered along with the commonly utilized differential abundance tests to better understand the role of the gut microbiome in health and disease.

Native and Alien Antarctic Grasses as a Habitat for Fungi

Biological invasions are now seen as one of the main threats to the Antarctic ecosystem. An example of such an invasion is the recent colonization of the H. Arctowski Polish Antarctic Station area by the non-native grass Poa annua. This site was previously occupied only by native plants like the Antarctic hair grass Deschampsia antarctica. To adapt successfully to new conditions, plants interact with soil microorganisms, including fungi. The aim of this study was to determine how the newly introduced grass P. annua established an interaction with fungi compared to resident grass D. antarctica. We found that fungal diversity in D. antarctica roots was significantly higher compared with P. annua roots. D. antarctica managed a biodiverse microbiome because of its ability to recruit fungal biocontrol agents from the soil, thus maintaining a beneficial nature of the endophyte community. P. annua relied on a set of specific fungal taxa, which likely modulated its cold response, increasing its competitiveness in Antarctic conditions. Cultivated endophytic fungi displayed strong chitinolysis, pointing towards their role as phytopathogenic fungi, nematode, and insect antagonists. This is the first study to compare the root mycobiomes of both grass species by direct culture-independent techniques as well as culture-based methods.

Comparative Analysis of Gut Microbiota between Captive and Wild Long-Tailed Gorals for Ex Situ Conservation

The long-tailed goral is close to extinction, and ex situ conservation is essential to prevent this phenomenon. Studies on the gut microbiome of the long-tailed goral are important for understanding the ecology of this species. We amplified DNA from the 16S rRNA regions and compared the microbiomes of wild long-tailed gorals and two types of captive long-tailed gorals. Our findings revealed that the gut microbiome diversity of wild long-tailed gorals is greatly reduced when they are reared in captivity. A comparison of the two types of captive long-tailed gorals confirmed that animals with a more diverse diet exhibit greater gut microbiome diversity. Redundancy analysis confirmed that wild long-tailed gorals are distributed throughout the highlands, midlands, and lowlands. For the first time, it was revealed that the long-tailed goral are divided into three groups depending on the height of their habitat, and that the gut bacterial community changes significantly when long-tailed gorals are raised through ex situ conservation. This provides for the first time a perspective on the diversity of food plants associated with mountain height that will be available to long-tailed goral in the future.

The microgeo: an R package rapidly displays the biogeography of soil microbial community traits on maps

Many R packages provide statistical approaches for elucidating the diversity of soil microbes, yet they still struggle to visualize microbial traits on a geographical map. This creates challenges in interpreting microbial biogeography on a regional scale, especially when the spatial scale is large or the distribution of sampling sites is uneven. Here, we developed a lightweight, flexible, and user-friendly R package called microgeo. This package integrates many functions involved in reading, manipulating, and visualizing geographical boundary data; downloading spatial datasets; and calculating microbial traits and rendering them onto a geographical map using grid-based visualization, spatial interpolation, or machine learning. Using this R package, users can visualize any trait calculated by microgeo or other tools on a map and can analyze microbiome data in conjunction with metadata derived from a geographical map. In contrast to other R packages that statistically analyze microbiome data, microgeo provides more-intuitive approaches in illustrating the biogeography of soil microbes on a large geographical scale, serving as an important supplement to statistically driven comparisons and facilitating the biogeographic analysis of publicly accessible microbiome data at a large spatial scale in a more convenient and efficient manner. The microgeo R package can be installed from the Gitee (https://gitee.com/bioape/microgeo) and GitHub (https://github.com/ChaonanLi/microgeo) repositories. Detailed tutorials for the microgeo R package are available at https://chaonanli.github.io/microgeo.

Degradation of Complex Carbon Sources in Organic Fertilizers Facilitates Nitrogen Fixation

Biological nitrogen fixation is crucial for agriculture and improving fertilizer efficiency, but organic fertilizers in enhancing this process remain debated. Here, we investigate the impact of organic fertilizers on biological nitrogen fixation through experiments and propose a new model where bacterial interactions with complex carbon sources enhance nitrogen fixation. Field experiments showed that adding organic fertilizers increased the nitrogenase activity by 57.85%. Subculture experiments revealed that organic fertilizer addition enriched genes corresponding to complex carbon and energy metabolism, as well as nifJ involved in electron transfer for nitrogenase. It also enhanced bacterial interactions and enhanced connectors associated with complex carbon degradation. Validation experiments demonstrated that combinations increased nitrogenase activity by 2.98 times compared to the single. Our findings suggest that organic fertilizers promoted nitrogen fixation by enhancing microbial cooperation, improved the degradation of complex carbon sources, and thereby provided utilizable carbon sources, energy, and electrons to N-fixers, thus increasing nitrogenase activity and nitrogen fixation.

Visualizing set relationships: EVenn's comprehensive approach to Venn diagrams

Venn diagrams serve as invaluable tools for visualizing set relationships due to their ease of interpretation. Widely applied across diverse disciplines such as metabolomics, genomics, transcriptomics, and proteomics, their utility is undeniable. However, the operational complexity has been compounded by the absence of standardized data formats and the need to switch between various platforms for generating different Venn diagrams. To address these challenges, we introduce the EVenn platform, a versatile tool offering a unified interface for efficient data exploration and visualization of diverse Venn diagrams. EVenn (http://www.ehbio.com/test/venn) streamlines the data upload process with a standardized format, enhancing the capabilities for multimodule analysis. This comprehensive protocol outlines various applications of EVenn, featuring representative results of multiple Venn diagrams, data uploads in the centralized data center, and step-by-step case demonstrations. Through these functionalities, EVenn emerges as a valuable and user-friendly tool for the in-depth exploration of multiomics data.

Vaginal microbiota are associated with in vitro fertilization during female infertility

The vaginal microbiome plays an essential role in the reproductive health of human females. As infertility increases worldwide, understanding the roles that the vaginal microbiome may have in infertility and in vitro fertilization (IVF) treatment outcomes is critical. To determine the vaginal microbiome composition of 1411 individuals (1255 undergoing embryo transplantation) and their associations with reproductive outcomes, clinical and biochemical features are measured, and vaginal samples are 16S rRNA sequenced. Our results suggest that both too high and too low abundance of Lactobacillus is not beneficial for pregnancy; a moderate abundance is more beneficial. A moderate abundance of Lactobacillus crispatus and Lactobacillus iners (~80%) (with a pregnancy rate of I-B: 54.35% and III-B: 57.73%) is found beneficial for pregnancy outcomes compared with a higher abundance (>90%) of Lactobacillus (I-A: 44.81% and III-A: 51.06%, respectively). The community state type (CST) IV-B (contains a high to moderate relative abundance of Gardnerella vaginalis) shows a similar pregnant ratio (48.09%) with I-A and III-A, and the pregnant women in this CST have a higher abundance of Lactobacillus species. Metagenome analysis of 71 samples shows that nonpregnant women are detected with more antibiotic-resistance genes, and Proteobacteria and Firmicutes are the main hosts. The inherent differences within and between women in different infertility groups suggest that vaginal microbes might be used to detect infertility and potentially improve IVF outcomes.

Tools and methodology to in silico phage discovery in freshwater environments

Freshwater availability is essential, and its maintenance has become an enormous challenge. Due to population growth and climate changes, freshwater sources are becoming scarce, imposing the need for strategies for its reuse. Currently, the constant discharge of waste into water bodies from human activities leads to the dissemination of pathogenic bacteria, negatively impacting water quality from the source to the infrastructure required for treatment, such as the accumulation of biofilms. Current water treatment methods cannot keep pace with bacterial evolution, which increasingly exhibits a profile of multidrug resistance to antibiotics. Furthermore, using more powerful disinfectants may affect the balance of aquatic ecosystems. Therefore, there is a need to explore sustainable ways to control the spreading of pathogenic bacteria. Bacteriophages can infect bacteria and archaea, hijacking their host machinery to favor their replication. They are widely abundant globally and provide a biological alternative to bacterial treatment with antibiotics. In contrast to common disinfectants and antibiotics, bacteriophages are highly specific, minimizing adverse effects on aquatic microbial communities and offering a lower cost-benefit ratio in production compared to antibiotics. However, due to the difficulty involving cultivating and identifying environmental bacteriophages, alternative approaches using NGS metagenomics in combination with some bioinformatic tools can help identify new bacteriophages that can be useful as an alternative treatment against resistant bacteria. In this review, we discuss advances in exploring the virome of freshwater, as well as current applications of bacteriophages in freshwater treatment, along with current challenges and future perspectives.

A Comprehensive View of Food Microbiota: Introducing FoodMicrobionet v5

Amplicon-targeted metagenomics is now the standard approach for the study of the composition and dynamics of food microbial communities. Hundreds of papers on this subject have been published in scientific journals and the information is dispersed in a variety of sources, while raw sequences and their metadata are available in public repositories for some, but not all, of the published studies. A limited number of web resources and databases allow scientists to access this wealth of information but their level of annotation on studies and samples varies. Here, we report on the release of FoodMicrobionet v5, a comprehensive database of metataxonomic studies on bacterial and fungal communities of foods. The current version of the database includes 251 published studies (11 focusing on fungal microbiota, 230 on bacterial microbiota, and 10 providing data for both bacterial and fungal microbiota) and 14,035 samples with data on bacteria and 1114 samples with data on fungi. The new structure of the database is compatible with interactive apps and scripts developed for previous versions and allows scientists, R&D personnel in industries and regulators to access a wealth of information on food microbial communities.

Fermentation broth from fruit and vegetable waste works: Reducing the risk of human bacterial pathogens in soil by inhibiting quorum sensing

Fermentation broth from fruit and vegetable waste (FFVW) has demonstrated remarkable ability as a soil amendment and in reducing antibiotic resistance genes (ARGs) pollution. However, the potential of FFVW to mitigate other microbial contamination such as human bacterial pathogens (HBPs) and virulence factor genes (VFGs), which are closely associated with human health, remains unknown. In this study, metagenomic analysis revealed that FFVW reduced the HBPs with high-risk of ARGs and VFGs including Klebsiella pneumoniae (reduced by 40.4 %), Mycobacterium tuberculosis (reduced by 21.4 %) and Streptococcus pneumoniae (reduced by 38.7 %). Correspondingly, VFG abundance in soil decreased from 3.40 copies/cell to 2.99 copies/cell. Further analysis illustrated that these was mainly attributed to the inhibition of quorum sensing (QS). FFVW reduced the abundance of QS signals, QS synthesis genes such as rpaI and luxS, as well as receptor genes such as rpfC and fusK, resulting in a decreased in risk of ARGs and VFGs. The pure culture experiment revealed that the expression of genes related to QS, VFGs, ARGs and mobile genetic elements (MGEs) were downregulated in Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli and K. pneumoniae treated by FFVW, consistent with the result of metagenomic analysis. This study suggested an environmentally friendly approach for controlling soil VFGs/ARGs-carrying HBPs, which is crucial for both soil and human health under the framework of "One Health".

Standard rodent diets differentially impact alcohol consumption, preference, and gut microbiome diversity

Alcohol use disorder (AUD) is a complex and widespread disease with limited pharmacotherapies. Preclinical animal models of AUD use a variety of voluntary alcohol consumption procedures to recapitulate different phases of AUD, including binge alcohol consumption and dependence. However, voluntary alcohol consumption in mice is widely variable, making it difficult to reproduce results across labs. Accumulating evidence indicates that different brands of commercially available rodent chow can profoundly influence alcohol intake. In this study, we investigated the effects of three commercially available and widely used rodent diet formulations on alcohol consumption and preference in C57BL/6 J mice using the 24 h intermittent access procedure. The three brands of chow tested were LabDiet 5,001 (LD5001), LabDiet 5,053 (LD5053), and Teklad 2019S (TL2019S) from two companies (Research Diets and Envigo, respectively). Mice fed LD5001 and LD5053 displayed higher levels of alcohol consumption and preference compared to mice fed TL2019S. We also found that alcohol consumption and preference could be rapidly switched by changing the diet 48 h prior to alcohol administration. Sucrose, saccharin, and quinine preferences were not altered, suggesting that the diets did not alter sweet and bitter taste perception. We also found that mice fed LD5001 displayed increased quinine-resistant alcohol intake compared to mice fed TL2019S, suggesting that diets could influence the development of compulsive behaviors such as alcohol consumption. We profiled the gut microbiome of water- and alcohol-drinking mice that were maintained on different diets and found significant differences in bacterial alpha- and beta-diversities, which could impact the gut-brain axis signaling and alcohol consumption.

Fungal, but not bacterial, diversity and network complexity promote network stability during roadside slope restoration

To restore degraded roadside ecosystems, conventional methods such as revegetation and soil amendment are frequently employed. However, our understanding of the long-term effects of these restoration approaches on soil microbial diversity and network complexity across different vegetation types remains poor, which contributes to poor restoration outcomes. In this study, we explored the effects of roadside slope restoration on microbial communities across different vegetation types at varying stages of restoration. We found that restoration time had a more pronounced impact on microbial diversity than specific vegetation type. As restoration progressed, microbial network complexity and fungal diversity increased, but bacterial diversity declined, suggesting that keystone taxa may contribute to network complexity. Interestingly, bacterial network complexity increased concomitant with decreasing network modularity and robustness, which may compromise system stability. Distinct vegetation types were associated with restoration-sensitive microbial communities at different restoration stages. Leguminouse and nitrogen-fixing plants, such as Albiziak alkora, Ginkgo biloba, Rhus chinensis, Rhapis excels, and Rubia cordifolia exhibited such associations after five years of restoration. These keystone taxa included Proteobacteria, Actinobacteria, Chloroflexi, Gemmatimonadota, and Myxococcota. We also found that bacterial alpha diversity was significantly correlated with restoration time, soil pH, moisture, available phosphate, nitrate nitrogen, and plant height, while fungal diversity was primarily shaped by restoration time. Together, our findings suggest that soil properties, environmental factors, vegetation type, and dominant species can be manipulated to guide the trajectory of ecological recovery by regulating the abundance of certain microbial taxa.

Microplastics affect soil-plant system: Implications for rhizosphere biology and fitness of sage (Salvia officinalis L.)

A mesocosm experiment was set-up to investigate the effects of low-density polyethylene (LDPE) fragments deriving from plastic film on soil ecology, rhizosphere and plant (Salvia officinalis L.) fitness. The internal transcribed spacer (ITS) and 16S metagenomic analysis was adopted to evaluate taxonomic and functional shifts of both soil and rhizosphere under the influence of microplastics (MPs). Photosynthetic parameters and enzymes involved in oxidative stress were assessed to unveil the plant physiological state. MP fragments were analysed by scanning electron microscope (SEM) and metagenomics to investigate the plastisphere. Microbial biomarkers of MPs pollution were identified in soil and rhizosphere, reinforcing the concept of molecular biomonitoring. Overall, Bacillus, Nocardioides and Streptomyces genera are bacterial biomarkers of MPs pollution in soil whereas Aspergillus, Fusarium and Trichoderma genera, and Nectriaceae family are fungal biomarkers of MPs polluted soil. The data show that the presence of MPs promotes the abundance of taxa involved in the soil N cycle, but simultaneously reduces the endophytic interaction capability and enhances pathogen related functions at the rhizosphere level. A significant decrease in chlorophyll levels and increase of oxidative stress enzymes was observed in plants grown in MPs-polluted soil. The SEM observations of MPs fragments revealed a complex colonisation, where bacteria (Bacillus in MPSo and Microvirga in MPRz) and fungi (Aspergillus in MPSo and Trichoderma in MPRz) represent the main colonisers. The results demonstrate that the presence of MPs causes changes in the soil and rhizosphere microbial community and functions leading to negative effects on plant fitness.

Natural mating ability is associated with gut microbiota composition and function in captive male giant pandas

The issue of poor sexual performance of some male giant pandas seriously impairs the growth and the genetic diversity of the captive population, yet there is still no clear understanding of the cause of the loss of this ability and its underlying mechanism. In this study, we analyzed the gut microbiota and its function in 72 fecal samples obtained from 20 captive male giant pandas, with an equal allocation between individuals capable and incapable of natural mating. Additionally, we investigated fecal hormone levels and behavioral differences between the two groups. A correlation analysis was then conducted among these factors to explore the influencing factors of their natural mating ability. The results showed significant differences in the composition of gut microbiota between the two groups of male pandas. The capable group had significantly higher abundance of Clostridium sensu stricto 1 (p adjusted = .0021, GLMM), which was positively correlated with fatty acid degradation and two-component system functions (Spearman, p adjusted < .05). Additionally, the capable group showed higher gene abundance in gut microbiota function including purine and pyrimidine metabolism and galactose metabolism, as well as pathways related to biological processes such as ribosome and homologous recombination (DEseq2, p adjusted < .05). We found no significant differences in fecal cortisol and testosterone levels between the two groups, and no difference was found in their behavior either. Our study provides a theoretical and practical basis for further studying the behavioral degradation mechanisms of giant pandas and other endangered mammal species.

The gut microbiota-aromatic hydrocarbon receptor (AhR) axis mediates the anticolitic effect of polyphenol-rich extracts from Sanghuangporus

Inflammatory bowel disease (IBD) is a significant global health concern. The gut microbiota plays an essential role in the onset and development of IBD. Sanghuangporus (SH), a traditional Chinese medicinal mushroom, has excellent anti-inflammatory effects and is effective at modulating the gut microbiota. Despite these attributes, the specific anticolitic effects of SH and the mechanisms through which the gut microbiota mediates its benefits remain unclear. Herein, we demonstrated that polyphenol-rich extract from SH effectively alleviated the pathological symptoms of dextran sodium sulfate (DSS)-induced colitis in mice by modulating the gut microbiota. Treatment with SH distinctly enriched Alistipes, especially Alistipes onderdonkii, and its metabolite 5-hydroxyindole-3-acetic acid (5HIAA). Oral gavage of live A. onderdonkii or 5HIAA potently mitigated DSS-induced colitis in mice. Moreover, both 5HIAA and SH significantly activated the aromatic hydrocarbon receptor (AhR), and the administration of an AhR antagonist abrogated their protective effects against colitis. These results underscore the potent efficacy of SH in diminishing DSS-induced colitis through the promotion of A. onderdonkii and 5HIAA, ultimately activating AhR signaling. This study unveils potential avenues for developing therapeutic strategies for colitis based on the interplay between SH and the gut microbiota.

Wekemo Bioincloud: A user-friendly platform for meta-omics data analyses

The increasing application of meta-omics approaches to investigate the structure, function, and intercellular interactions of microbial communities has led to a surge in available data. However, this abundance of human and environmental microbiome data has exposed new scalability challenges for existing bioinformatics tools. In response, we introduce Wekemo Bioincloud-a specialized platform for -omics studies. This platform offers a comprehensive analysis solution, specifically designed to alleviate the challenges of tool selection for users in the face of expanding data sets. As of now, Wekemo Bioincloud has been regularly equipped with 22 workflows and 65 visualization tools, establishing itself as a user-friendly and widely embraced platform for studying diverse data sets. Additionally, the platform enables the online modification of vector outputs, and the registration-independent personalized dashboard system ensures privacy and traceability. Wekemo Bioincloud is freely available at https://www.bioincloud.tech/.

Long-term application of organic fertilizer prompting the dispersal of antibiotic resistance genes and their health risks in the soil plastisphere

Microplastic (MP) pollution is a rapidly growing global environmental concern that has led to the emergence of a new environmental compartment, the plastisphere, which is a hotspot for the accumulation of antibiotic resistance genes (ARGs) and human bacterial pathogens (HBPs). However, studies on the effects of long-term organic fertilizer application on the dispersal of ARGs and virulence factor genes (VFGs) in the plastisphere of farmland soil have been limited. Here, we performed a field culture experiment by burying nylon bags filled with MPs in paddy soil that had been treated with different fertilizers for over 30 years to explore the changes of ARGs and VFGs in soil plastisphere. Our results show that the soil plastisphere amplified the ARG and VFG pollution caused by organic fertilization by 1.5 and 1.4 times, respectively. And it also led to a 2.7-fold increase in the risk of horizontal gene transfer. Meanwhile, the plastisphere tended to promote deterministic process in the community assembly of HBPs, with an increase of 1.4 times. Network analysis found a significant correlation between ARGs, VFGs, and bacteria in plastisphere. Correlation analysis highlight the important role of mobile genetic elements (MGEs) and bacterial communities in shaping the abundance of ARGs and VFGs, respectively. Our findings provide new insights into the health risk associated with the soil plastisphere due ARGs and VFGs derived from organic fertilizers.

Changes in Gut Microbiota Associated with Parity in Large White Sows

As one of the most critical economic traits, the litter performance of sows is influenced by their parity. Some studies have indicated a connection between the gut microbiota and the litter performance of animals. In this study, we examined litter performance in 1363 records of different parities of Large White sows. We observed a marked decline in TNB (Total Number Born) and NBH (Number of Healthy Born) We observed a marked decline in TNB (Total Number Born) and NBH (Number of Healthy Born) among sows with parity 7 or higher. To gain a deeper understanding of the potential role of gut microbiota in this phenomenon, we conducted 16S rRNA amplicon sequencing of fecal DNA from 263 Large White sows at different parities and compared the changes in their gut microbiota with increasing parity. The results revealed that in comparison to sows with a parity from one to six, sows with a parity of seven or higher exhibited decreased alpha diversity in their gut microbiota. There was an increased proportion of pathogenic bacteria (such as Enterobacteriaceae, Streptococcus, and Escherichia-Shigella) and a reduced proportion of SCFA-producing families (such as Ruminococcaceae), indicating signs of inflammatory aging. The decline in sow function may be one of the primary reasons for the reduction in their litter performance.

Exploring the Microbiome in Human Reproductive Tract: High-Throughput Methods for the Taxonomic Characterization of Microorganisms

Microorganisms are important due to their widespread presence and multifaceted roles across various domains of life, ecology, and industries. In humans, they underlie the proper functioning of multiple systems crucial to well-being, including immunological and metabolic functions. Emerging research addressing the presence and roles of microorganisms within human reproduction is increasingly relevant. Studies implementing new methodologies (e.g., to investigate vaginal, uterine, and semen microenvironments) can now provide relevant insights into fertility, reproductive health, or pregnancy outcomes. In that sense, cutting-edge sequencing techniques, as well as others such as meta-metabolomics, culturomics, and meta-proteomics, are becoming more popular and accessible worldwide, allowing the characterization of microbiomes at unprecedented resolution. However, they frequently involve rather complex laboratory protocols and bioinformatics analyses, for which researchers may lack the required expertise. A suitable pipeline would successfully enable both taxonomic classification and functional profiling of the microbiome, providing easy-to-understand biological interpretations. However, the selection of an appropriate methodology would be crucial, as it directly impacts the reproducibility, accuracy, and quality of the results and observations. This review focuses on the different current microbiome-related techniques in the context of human reproduction, encompassing niches like vagina, endometrium, and seminal fluid. The most standard and reliable methods are 16S rRNA gene sequencing, metagenomics, and meta-transcriptomics, together with complementary approaches including meta-proteomics, meta-metabolomics, and culturomics. Finally, we also offer case examples and general recommendations about the most appropriate methods and workflows and discuss strengths and shortcomings for each technique.