High-throughput metagenomic technologies for complex microbial community analysis: open and closed formats

Revealing the hidden world of soil microbes: Metagenomic insights into plant, bacteria, and fungi interactions for sustainable agriculture and ecosystem restoration

The future of agriculture is questionable under the current climate change scenario. Climate change and climate-related calamities directly influence biotic and abiotic factors that control agroecosystems, endangering the safety of the world's food supply. The intricate interactions between soil microorganisms, including plants, bacteria, and fungi, play a pivotal role in promoting sustainable agriculture and ecosystem restoration. Soil microbes play a major part in nutrient cycling, including soil organic carbon (SOC), and play a pivotal function in the emission and depletion of greenhouse gases, including CH4, CO2, and N2O, which can impact the climate. At this juncture, developing a triumphant metagenomics approach has greatly increased our knowledge of the makeup, functionality, and dynamics of the soil microbiome. Currently, the involvement of plants in climate change indicates that they can interact with the microbial communities in their environment to relieve various stresses through the innate microbiome assortment of focused strains, a phenomenon dubbed "Cry for Help." The metagenomics method has lately appeared as a new platform to adjust and encourage beneficial communications between plants and microbes and improve plant fitness. The metagenomics of soil microbes can provide a powerful tool for designing and evaluating ecosystem restoration strategies that promote sustainable agriculture under a changing climate. By identifying the specific functions and activities of soil microbes, we can develop restoration programs that support these critical components of healthy ecosystems while providing economic benefits through ecosystem services. In the current review, we highlight the innate functions of microbiomes to maintain the sustainability of agriculture and ecosystem restoration. Through this insight study of soil microbe metagenomics, we pave the way for innovative strategies to address the pressing challenges of food security and environmental conservation. The present article elucidates the mechanisms through which plants and microbes communicate to enhance plant resilience and ecosystem restoration and to leverage metagenomics to identify and promote beneficial plant-microbe interactions. Key findings reveal that soil microbes are pivotal in nutrient cycling, greenhouse gas modulation, and overall ecosystem health, offering novel insights into designing ecosystem restoration strategies that bolster sustainable agriculture. As this is a topic many are grappling with, hope these musings will provide people alike with some food for thought.

Reproducible responses of geochemical and microbial successional patterns in the subsurface to carbon source amendment

Carbon amendments designed to remediate environmental contamination lead to substantial perturbations when injected into the subsurface. For the remediation of uranium contamination, carbon amendments promote reducing conditions to allow microorganisms to reduce uranium to an insoluble, less mobile state. However, the reproducibility of these amendments and underlying microbial community assembly mechanisms have rarely been investigated in the field. In this study, two injections of emulsified vegetable oil were performed in 2009 and 2017 to immobilize uranium in the groundwater at Oak Ridge, TN, USA. Our objectives were to determine whether and how the injections resulted in similar abiotic and biotic responses and their underlying community assembly mechanisms. Both injections caused similar geochemical and microbial succession. Uranium, nitrate, and sulfate concentrations in the groundwater dropped following the injection, and specific microbial taxa responded at roughly the same time points in both injections, including Geobacter, Desulfovibrio, and members of the phylum Comamonadaceae, all of which are well established in uranium, nitrate, and sulfate reduction. Both injections induced a transition from relatively stochastic to more deterministic assembly of microbial taxonomic and phylogenetic community structures based on 16S rRNA gene analysis. We conclude that geochemical and microbial successions after biostimulation are reproducible, likely owing to the selection of similar phylogenetic groups in response to EVO injection.

A novel method for multi-pollutant monitoring in water supply systems using chemical machine vision

Drinking water is vital for human health and life, but detecting multiple contaminants in it is challenging. Traditional testing methods are both time-consuming and labor-intensive, lacking the ability to capture abrupt changes in water quality over brief intervals. This paper proposes a direct analysis and rapid detection method of three indicators of arsenic, cadmium, and selenium in complex drinking water systems by combining a novel long-path spectral imager with machine learning models. Our technique can obtain multiple parameters in about 1 s. The experiment involved setting up samples from various drinking water backgrounds and mixed groups, totaling 9360 injections. A raw visible light source ranging from 380 to 780 nm was utilized, uniformly dispersing light into the sample cell through a filter. The residual beam was captured by a high-definition camera, forming a distinctive spectrum. Three deep learning models-ResNet-50, SqueezeNet V1.1, and GoogLeNet Inception V1-were employed. Datasets were divided into training, validation, and test sets in a 6:2:2 ratio, and prediction performance across different datasets was assessed using the coefficient of determination and root mean square error. The experimental results show that a well-trained machine learning model can extract a lot of feature image information and quickly predict multi-dimensional drinking water indicators with almost no preprocessing. The model's prediction performance is stable under different background drinking water systems. The method is accurate, efficient, and real-time and can be widely used in actual water supply systems. This study can improve the efficiency of water quality monitoring and treatment in water supply systems, and the method's potential for environmental monitoring, food safety, industrial testing, and other fields can be further explored in the future.

CyanoStrainChip: A Novel DNA Microarray Tool for High-Throughput Detection of Environmental Cyanobacteria at the Strain Level

Detecting cyanobacteria in environments is an important concern due to their crucial roles in ecosystems, and they can form blooms with the potential to harm humans and nonhuman entities. However, the most widely used methods for high-throughput detection of environmental cyanobacteria, such as 16S rRNA sequencing, typically provide above-species-level resolution, thereby disregarding intraspecific variation. To address this, we developed a novel DNA microarray tool, termed the CyanoStrainChip, that enables strain-level comprehensive profiling of environmental cyanobacteria. The CyanoStrainChip was designed to target 1277 strains; nearly all major groups of cyanobacteria are included by implementing 43,666 genome-wide, strain-specific probes. It demonstrated strong specificity by in vitro mock community experiments. The high correlation (Pearson's R > 0.97) between probe fluorescence intensities and the corresponding DNA amounts (ranging from 1-100 ng) indicated excellent quantitative capability. Consistent cyanobacterial profiles of field samples were observed by both the CyanoStrainChip and next-generation sequencing methods. Furthermore, CyanoStrainChip analysis of surface water samples in Lake Chaohu uncovered a high intraspecific variation of abundance change within the genus Microcystis between different severity levels of cyanobacterial blooms, highlighting two toxic Microcystis strains that are of critical concern for Lake Chaohu harmful blooms suppression. Overall, these results suggest a potential for CyanoStrainChip as a valuable tool for cyanobacterial ecological research and harmful bloom monitoring to supplement existing techniques.

Metagenomics analysis of water samples collected from the Yamuna River of Agra city, India

Yamuna River water in Agra city of India is contaminated with toxic pollutants, including heavy metals that cause damage to the environment and human health. At present, the direct use of river water for drinking purposes and household activities lead to the direct exposure of society to the contaminants. In this study, Yamuna River water samples were collected from three different sites in Agra city during the monsoon, summer, and winter seasons. The physico-chemical parameters were estimated along with heavy metals. In physico-chemical parameter, the values found were mostly above the permissible limits. The results water samples contain high levels of cadmium, chromium, lead, and nickel above the desirable levels in most cases. The metagenomic analysis revealed that Proteobacteria, Bacteroidetes, Verrucomicrobia, Actinobacteria, and Planctobacteria were the most abundant phyla with a relative abundance of 61%, 9.34%, 5.23%, 4.64%, and 4.3%, respectively. The Comamonadaceae, the most abundant family consists of the genera involved in hydrogen oxidation, iron reduction, degraders of polycyclic aromatic hydrocarbons, and fermentation. The presence of Pseudomonas, Nitrosomonas sp., Thauera humireducens and Dechloromonas denitrificans (decomposition of sewage and organic matter) and Pseudomonas aeruginosa indicates the presence of heavy metal degrading bacteria in water sample. Functional prediction showed the presence of genes responsible for different metabolic pathways that could help developing new bioremediation strategies. The study concludes the status of water contamination, the presence of complex microbial community and suggests the futuristic use and their role in bioremediation.

Monotonic trends of soil microbiomes, metagenomic and metabolomic functioning across ecosystems along water gradients in the Altai region, northwestern China

To investigate microbial communities and their contributions to carbon and nutrient cycling along water gradients can enhance our comprehension of climate change impacts on ecosystem services. Thus, we conducted an assessment of microbial communities, metagenomic functions, and metabolomic profiles within four ecosystems, i.e., desert grassland (DG), shrub-steppe (SS), forest (FO), and marsh (MA) in the Altai region of Xinjiang, China. Our results showed that soil total carbon (TC), total nitrogen, NH4+, and NO3- increased, but pH decreased with soil water gradients. Microbial abundances and richness also increased with soil moisture except the abundances of fungi and protists being lowest in MA. A shift in microbial community composition is evident along the soil moisture gradient, with Proteobacteria, Basidiomycota, and Evosea proliferating but a decline in Actinobacteria and Cercozoa. The β-diversity of microbiomes, metagenomic, and metabolomic functioning were correlated with soil moisture gradients and have significant associations with specific soil factors of TC, NH4+, and pH. Metagenomic functions associated with carbohydrate and DNA metabolisms, as well as phages, prophages, TE, plasmids functions diminished with moisture, whereas the genes involved in nitrogen and potassium metabolism, along with certain biological interactions and environmental information processing functions, demonstrated an augmentation. Additionally, MA harbored the most abundant metabolomics dominated by lipids and lipid-like molecules and organic oxygen compounds, except certain metabolites showing decline trends along water gradients, such as N'-Hydroxymethylnorcotinine and 5-Hydroxyenterolactone. Thus, our study suggests that future ecosystem succession facilitated by changes in rainfall patterns will significantly alter soil microbial taxa, functional potential, and metabolite fractions.

Effects of Land Use Type Transformation on the Structure and Diversity of Soil Bacterial Communities

Soil microbiota are significantly influenced by their microenvironments. Therefore, to understand the impacts of various land use patterns on the diversity and composition of soil bacterial communities, this study focused on three typical land use types-NF (natural forest), AF (artificial forests), and FL (farmland)-in the Heilongjiang Central Station Black-billed Capercaillie National Nature Reserve, located in the southwestern part of Heihe City, Heilongjiang Province, China. Using high-throughput sequencing of the 16S rRNA gene, we examined the soil bacterial community structures in these different land use types and explored their correlation with soil environmental factors. The following were our main observations: (1) Significant variations in soil chemical properties among different land use patterns were observed. In artificial forests, total nitrogen (TN), alkali hydrolyzed nitrogen (AN), total phosphorus (TP), and available phosphorus (AP) were higher compared to farmland and significantly higher than those in natural forests. Furthermore, the organic carbon content (SOC) in natural forests was higher than in artificial forests and significantly higher than in farmland. (2) Comparative analysis using the Shannon and Simpson indices revealed that bacterial community diversity was higher in artificial forests than in natural forests, which was significantly higher than in farmland. (3) The effect of different land use types on soil bacterial community structure was not significant. The three land types were dominated by Proteobacteria, Acidobacteria, and Actinobacteria. Proteobacteria exhibited a higher relative abundance in farmland and artificial forests compared to natural forests, whereas Actinobacteria exhibited the lowest relative abundance in natural forests. (4) Redundancy analysis (RDA) revealed that SOC, TN, AN, and AP were key environmental factors influencing the microbial communities of soil. Collectively, our findings demonstrated that land use practices can significantly alter soil nutrient levels, thereby influencing the structure of bacterial communities.

Community assembly of organisms regulates soil microbial functional potential through dual mechanisms

Unraveling the influence of community assembly processes on soil ecosystem functioning presents a major challenge in the field of theoretical ecology, as it has received limited attention. Here, we used a series of long-term experiments spanning over 25 years to explore the assembly processes of bacterial, fungal, protist, and nematode communities using high-throughput sequencing. We characterized the soil microbial functional potential by the abundance of microbial genes associated with carbon, nitrogen, phosphorus, and sulfur cycling using GeoChip-based functional gene profiling, and determined how the assembly processes of organism groups regulate soil microbial functional potential through community diversity and network stability. Our results indicated that balanced fertilization (NPK) treatment improved the stochastic assembly of bacterial, fungal, and protist communities compared to phosphorus-deficient fertilization (NK) treatment. However, there was a nonsignificant increase in the normalized stochasticity ratio of the nematode community in response to fertilization across sites. Our findings emphasized that soil environmental factors influenced the assembly processes of the biotic community, which regulated soil microbial functional potential through dual mechanisms. One mechanism indicated that the high phosphorus levels and low soil nutrient stoichiometry may increase the stochasticity of bacterial, fungal, and protist communities and the determinism of the nematode community under NPK treatment, ultimately enhancing soil microbial functional potential by reinforcing the network stability of the biotic community. The other mechanism indicated that the low phosphorus levels and high soil nutrient stoichiometry may increase the stochastic process of the bacterial community and the determinism of the fungal, protist, and nematode communities under NK treatment, thereby enhancing soil microbial functional potential by improving the β-diversity of the biotic community. Taken together, these results provide valuable insights into the mechanisms underlying the assembly processes of the biotic community that regulate ecosystem functioning.

Environmental stress mediates groundwater microbial community assembly

Community assembly describes how different ecological processes shape microbial community composition and structure. How environmental factors impact community assembly remains elusive. Here we sampled microbial communities and >200 biogeochemical variables in groundwater at the Oak Ridge Field Research Center, a former nuclear waste disposal site, and developed a theoretical framework to conceptualize the relationships between community assembly processes and environmental stresses. We found that stochastic assembly processes were critical (>60% on average) in shaping community structure, but their relative importance decreased as stress increased. Dispersal limitation and 'drift' related to random birth and death had negative correlations with stresses, whereas the selection processes leading to dissimilar communities increased with stresses, primarily related to pH, cobalt and molybdenum. Assembly mechanisms also varied greatly among different phylogenetic groups. Our findings highlight the importance of microbial dispersal limitation and environmental heterogeneity in ecosystem restoration and management.

Effects of Different Heat Treatments on Yak Milk Proteins on Intestinal Microbiota and Metabolism

Dairy products are susceptible to modifications in protein oxidation during heat processing, which can lead to changes in protein function, subsequently affecting intestinal health. Despite being a unique nutritional source, yak milk has not been thoroughly examined for the effects of its oxidized proteins on intestinal microbiota and metabolism. Hence, this study employed different heat treatment methods (low-temperature pasteurization, high-temperature pasteurization, and high-temperature sterilization) to induce oxidation in yak milk proteins. The study then assessed the degree of oxidation in these proteins and utilized mice as research subjects. Using metagenomics and metabolomics methods, this study examined the structure of intestinal microbial communities and metabolic products in mice consuming oxidized yak milk. The results showed a decrease in carbonyl and total thiol contents of yak milk proteins after different heat treatments, indicating that heat treatment causes oxidation in yak milk proteins. Metagenomic analysis of mouse intestinal microbiota revealed significant changes in 66 genera. In the high-temperature sterilization group (H), key differential genera included Verrucomicrobiales, Verrucomicrobiae, Akkermansiaceae, and 28 others. The high-temperature pasteurization group (M) mainly consisted of Latilactobacillus, Bacillus, and Romboutsia. The low-temperature pasteurization group (L) primarily comprised of Faecalibacterium, Chaetomium, Paenibacillaceae, Eggerthella, Sordariales, and 33 others. Functionally, compared to the control group (C), the H group upregulated translation and energy metabolism functions, the L group the M group significantly upregulated metabolism of other amino acids, translation, and cell replication and repair functions. Based on metabolomic analysis, differential changes in mouse metabolites could affect multiple metabolic pathways in the body. The most significantly affected metabolic pathways were phenylalanine metabolism, vitamin B6 metabolism, steroid hormone biosynthesis, and pantothenate and CoA biosynthesis. The changes were similar to the functional pathway analysis of mouse metagenomics, affecting amino acid and energy metabolism in mice. In summary, moderate oxidation of yak milk proteins exhibits a positive effect on mouse intestinal microbiota and metabolism. In conclusion, yak milk has a positive effect on mouse intestinal microflora and metabolism, and this study provides a scientific basis for optimizing dairy processing technology and further developing and applying yak milk.

Biogeography and diversity patterns of functional genes associated with C, N, P, S cycling processes across China classical sea sediments

Microbial activities influence the ecological functions of marine ecosystems and play an essential role in biogeochemical cycling. However, there are more studies on microbial diversity and community structure, and few reports have explored nutrient cycling processes by microbial functional gene abundance and diversity. Given these limitations, in order to investigate the variability of nutrient cycling among different sea areas and its influencing factors, the sediments of the Bohai Sea, Yellow Sea, East China Sea and South China Sea were used in this study. The number of average copies of each functional gene was obtained by the quantitative microbial element cycling (QMEC) smart chip. A total of 65 functional genes related to C, N, P and S cycling were identified, and the results showed that all functional genes decreased in the order of magnitude from the Bohai Sea to the East China Sea, Yellow Sea and South China Sea, and the abundance of functional genes was significantly higher at the sampling sites near the land side, which related to human activities. Additionally, NH4+, organic carbon, total carbon and geographical factor were the main driving factors of functional gene composition changes (p < 0.05), and all functional genes were significantly correlated with total carbon and geographical distance (p < 0.01). These findings further expand the understanding of marine ecosystems and provide robust support for global biogeochemical cycles.

Characterizing alterations in the gut microbiota following postpartum weight change

IMPORTANCE

Previous research has reported differences in the gut microbiome associated with varying body compositions. More specifically, within populations of mothers, the focus has been on the impact of gestational weight gain. This is the first study to examine postpartum weight change and its association with changes in the gut microbiome, similarly, it is the first to use a Latina cohort to do so. The results support the idea that weight gain may be an important factor in reducing gut microbiome network connectivity, diversity, and changing abundances of specific microbial taxa, all measures thought to impact host health. These results suggest that weight gain dynamically alters mothers' gut microbial communities in the first 6 months postpartum, with comparatively little change in mothers who lost weight; further research is needed to examine the health consequences of such changes.

A sequential one-pot approach for rapid and convenient characterization of putative restriction-modification systems

IMPORTANCE

The elucidation of the molecular basis of virus-host coevolutionary interactions is boosted with state-of-the-art sequencing technologies. However, the sequence-only information is often insufficient to output a conclusive argument without biochemical characterizations. We proposed a 1-day and one-pot approach to confirm the exact function of putative restriction-modification (R-M) genes that presumably mediate microbial coevolution. The experiments mainly focused on a series of putative R-M enzymes from a deep-sea virus and its host bacterium. The results quickly unveiled unambiguous substrate specificities, superior catalytic performance, and unique sequence preferences for two new restriction enzymes (capable of cleaving DNA) and two new methyltransferases (capable of modifying DNA with methyl groups). The reality of the functional R-M system reinforced a model of mutually beneficial interactions with the virus in the deep-sea microbial ecosystem. The cell culture-independent approach also holds great potential for exploring novel and biotechnologically significant R-M enzymes from microbial dark matter.

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing

IMPORTANCE

Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

Land use conversion increases network complexity and stability of soil microbial communities in a temperate grassland

Soils harbor highly diverse microbial communities that are critical to soil health, but agriculture has caused extensive land use conversion resulting in negative effects on critical ecosystem processes. However, the responses and adaptations of microbial communities to land use conversion have not yet been understood. Here, we examined the effects of land conversion for long-term crop use on the network complexity and stability of soil microbial communities over 19 months. Despite reduced microbial biodiversity in comparison with native tallgrass prairie, conventionally tilled (CT) cropland significantly increased network complexity such as connectivity, connectance, average clustering coefficient, relative modularity, and the number of species acting at network hubs and connectors as well as resulted in greater temporal variation of complexity indices. Molecular ecological networks under CT cropland became significantly more robust and less vulnerable, overall increasing network stability. The relationship between network complexity and stability was also substantially strengthened due to land use conversion. Lastly, CT cropland decreased the number of relationships between network structure and environmental properties instead being strongly correlated to management disturbances. These results indicate that agricultural disturbance generally increases the complexity and stability of species "interactions", possibly as a trade-off for biodiversity loss to support ecosystem function when faced with frequent agricultural disturbance.

Plant Growth-Promoting Bacteria of Soil: Designing of Consortia Beneficial for Crop Production

Plant growth-promoting bacteria are commonly used in agriculture, particularly for seed inoculation. Multispecies consortia are believed to be the most promising form of these bacteria. However, designing and modeling bacterial consortia to achieve desired phenotypic outcomes in plants is challenging. This review aims to address this challenge by exploring key antimicrobial interactions. Special attention is given to approaches for developing soil plant growth-promoting bacteria consortia. Additionally, advanced omics-based methods are analyzed that allow soil microbiomes to be characterized, providing an understanding of the molecular and functional aspects of these microbial communities. A comprehensive discussion explores the utilization of bacterial preparations in biofertilizers for agricultural applications, focusing on the intricate design of synthetic bacterial consortia with these preparations. Overall, the review provides valuable insights and strategies for intentionally designing bacterial consortia to enhance plant growth and development.

Depth-Dependent Distribution of Prokaryotes in Sediments of the Manganese Crust on Nazimov Guyots of the Magellan Seamounts

Deep ocean polymetallic nodules, rich in cobalt, nickel, and titanium which are commonly used in high-technology and biotechnology applications, are being eyed for green energy transition through deep-sea mining operations. Prokaryotic communities underneath polymetallic nodules could participate in deep-sea biogeochemical cycling, however, are not fully described. To address this gap, we collected sediment cores from Nazimov guyots, where polymetallic nodules exist, to explore the diversity and vertical distribution of prokaryotic communities. Our 16S rRNA amplicon sequencing data, quantitative PCR results, and phylogenetic beta diversity indices showed that prokaryotic diversity in the surficial layers (0-8 cm) was > 4-fold higher compared to deeper horizons (8-26 cm), while heterotrophs dominated in all sediment horizons. Proteobacteria was the most abundant taxon (32-82%) across all sediment depths, followed by Thaumarchaeota (4-37%), Firmicutes (2-18%), and Planctomycetes (1-6%). Depth was the key factor controlling prokaryotic distribution, while heavy metals (e.g., iron, copper, nickel, cobalt, zinc) can also influence significantly the downcore distribution of prokaryotic communities. Analyses of phylogenetic diversity showed that deterministic processes governing prokaryotic assembly in surficial layers, contrasting with stochastic influences in deep layers. This was further supported from the detection of a more complex prokaryotic co-occurrence network in the surficial layer which suggested more diverse prokaryotic communities existed in the surface vs. deeper sediments. This study expands current knowledge on the vertical distribution of benthic prokaryotic diversity in deep sea settings underneath polymetallic nodules, and the results reported might set a baseline for future mining decisions.

Species' functional traits and interactions drive nitrate-mediated sulfur-oxidizing community structure and functioning

IMPORTANCE

Understanding the processes and mechanisms governing microbial community assembly and their linkages to ecosystem functioning has long been a core issue in microbial ecology. An in-depth insight still requires combining with analyses of species' functional traits and microbial interactions. Our study showed how species' functional traits and interactions determined microbial community structure and functions by a well-controlled laboratory experiment with nitrate-mediated sulfur oxidation systems using high-throughput sequencing and culture-dependent technologies. The results provided solid evidences that species' functional traits and interactions were the intrinsic factors determining community structure and function. More importantly, our study established quantitative links between community structure and function based on species' functional traits and interactions, which would have important implications for the design and synthesis of microbiomes with expected functions.

Exploring microbial diversity responses in agricultural fields: a comparative analysis under pesticide stress and non-stress conditions

Exposure to pesticides changes the microbial community structure in contaminated agricultural fields. To analyze the changes in the native microbial composition qRT-PCR, a metagenomic study was conducted. The qRT-PCR results exhibited that the uncontaminated soil has a higher copy number of 16S rDNA relative to the soil contaminated with pesticide. Metagenome analysis interprets that uncontaminated soil is enriched with proteobacteria in comparison with pesticide-contaminated soil. However, the presence of Actinobacteria, Firmicutes, and Bacteroides was found to be dominant in the pesticide-spiked soil. Additionally, the presence of new phyla such as Chloroflexi, Planctomycetes, and Verrucomicrobia was noted in the pesticide-spiked soil, while Acidobacteria and Crenarchaeota were observed to be extinct. These findings highlight that exposure to pesticides on soil significantly impacts the biological composition of the soil. The abundance of microbial composition under pesticide stress could be of better use for the treatment of biodegradation and bioremediation of pesticides in contaminated environments.

Assessing mechanisms for microbial taxa and community dynamics using process models

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer-resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer-resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

MV-CVIB: microbiome-based multi-view convolutional variational information bottleneck for predicting metastatic colorectal cancer

Introduction

Imbalances in gut microbes have been implied in many human diseases, including colorectal cancer (CRC), inflammatory bowel disease, type 2 diabetes, obesity, autism, and Alzheimer's disease. Compared with other human diseases, CRC is a gastrointestinal malignancy with high mortality and a high probability of metastasis. However, current studies mainly focus on the prediction of colorectal cancer while neglecting the more serious malignancy of metastatic colorectal cancer (mCRC). In addition, high dimensionality and small samples lead to the complexity of gut microbial data, which increases the difficulty of traditional machine learning models.

Methods

To address these challenges, we collected and processed 16S rRNA data and calculated abundance data from patients with non-metastatic colorectal cancer (non-mCRC) and mCRC. Different from the traditional health-disease classification strategy, we adopted a novel disease-disease classification strategy and proposed a microbiome-based multi-view convolutional variational information bottleneck (MV-CVIB).

Results

The experimental results show that MV-CVIB can effectively predict mCRC. This model can achieve AUC values above 0.9 compared to other state-of-the-art models. Not only that, MV-CVIB also achieved satisfactory predictive performance on multiple published CRC gut microbiome datasets.

Discussion

Finally, multiple gut microbiota analyses were used to elucidate communities and differences between mCRC and non-mCRC, and the metastatic properties of CRC were assessed by patient age and microbiota expression.

High resolution micro-confocal Raman spectrometer-based photo-affinity microarray technology for the investigation of active ingredients - Target protein recognition strategy

Natural products has been used for the prevention and treatment of diseases for a long history. Research on the bioactive components from natural products and their interaction with target proteins are essential for drug discovery. However, studying the binding ability of natural products' active ingredients to target proteins is usually time-consuming and laborious due to their complex and diverse chemical structures. In this study, we have developed a high resolution micro-confocal Raman spectrometer-based photo-affinity microarray (HRMR-PM) technology for the investigation of active ingredients-target protein recognition strategy. The novel photo-affinity microarray was constructed by photo-cross-linking the small molecule with the photo-affinity group (4-[3-(Trifluoromethyl)-3H-diazirin-3-yl]benzoic acid, TAD) on the photo-affinity linker coated (PALC) slides under 365 nm ultraviolet irradiation. The small molecules on the microarrays with specific binding ability might immobilize target protein, which were characterized by high resolution micro-confocal Raman spectrometer. Using this method, more than a dozen components of Shenqi Jiangtang granules (SJG) were made into small molecule probe (SMP) microarrays. As a result, 8 of them had been identified to have α-glucosidase binding ability according to characteristic Raman shift at about 3060 cm^-1. These compounds were further verified by different small molecule-protein interaction analysis methods, including contact angle D-value, surface plasmon resonance (SPR) and molecular docking. The results showed that Ginsenosides Mb, Formononetin and Gomisin D exhibited the strongest binding ability. In conclusion, the HRMR-PM strategy for investigating the interaction between target proteins and small molecules has the advantages such as high throughput, low sample consumption and fast qualitative characterization. This strategy is universal which can be applied in the study of in vitro binding activity of various types of small molecules to target proteins.

Uncovering the virome and its interaction with antibiotic resistome during compost fertilization

Antibiotic resistance is a pressing global health issue, leading to increased illnesses and fatalities. The contribution of viruses to the acquisition, preservation, and dissemination of antibiotic resistance genes (ARGs) is not yet fully understood. By using a high-throughput functional gene-based microarray (GeoChip 5.0), this study examines the prevalence and relative abundance of bacteriophage and eukaryotic viral genes in swine manure, compost, compost-amended agricultural soil, and unamended soil from suburban regions of Beijing, China. Our findings reveal a significantly elevated presence of biomarker viral genes in compost-amended soils compared to unamended soils, suggesting potential health risks associated with compost fertilization. We also observed stronger ecological interactions between ARGs and viral genes in manure and compost than in soils. Network analysis identified arabinose efflux permeases and EmrB/QacA resistance genes, linked to CRISPR encoding sequences, as keystone nodes, indicating possible ARG acquisition via virus infections. Moreover, positive correlations were found between viral genes, antibiotic concentrations, and ARG diversity in manure, compost, and compost-amended soils, highlighting a likely pathway for virus-mediated ARG transfer. In summary, our results indicate that use of compost as a fertilizer in agricultural settings could facilitate the spread of ARGs through viral mechanisms, allowing for time-delayed genetic exchanges over broader temporal and spatial scales than ARGs within bacterial genomes.

Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States

Phytoplankton is the essential primary producer in fresh surface water ecosystems. However, excessive phytoplankton growth due to eutrophication significantly threatens ecologic, economic, and public health. Therefore, phytoplankton identification and quantification are essential to understanding the productivity and health of freshwater ecosystems as well as the impacts of phytoplankton overgrowth (such as Cyanobacterial blooms) on public health. Microscopy is the gold standard for phytoplankton assessment but is time-consuming, has low throughput, and requires rich experience in phytoplankton morphology. Quantitative polymerase chain reaction (qPCR) is accurate and straightforward with high throughput. In addition, qPCR does not require expertise in phytoplankton morphology. Therefore, qPCR can be a useful alternative for molecular identification and enumeration of phytoplankton. Nonetheless, a comprehensive study is missing which evaluates and compares the feasibility of using qPCR and microscopy to assess phytoplankton in fresh water. This study 1) compared the performance of qPCR and microscopy in identifying and quantifying phytoplankton and 2) evaluated qPCR as a molecular tool to assess phytoplankton and indicate eutrophication. We assessed phytoplankton using both qPCR and microscopy in twelve large freshwater rivers across the United States from early summer to late fall in 2017, 2018, and 2019. qPCR- and microscope-based phytoplankton abundance had a significant positive linear correlation (adjusted R2 = 0.836, p-value < 0.001). Phytoplankton abundance had limited temporal variation within each sampling season and over the three years studied. The sampling sites in the midcontinent rivers had higher phytoplankton abundance than those in the eastern and western rivers. For instance, the concentration (geometric mean) of Bacillariophyta, Cyanobacteria, Chlorophyta, and Dinoflagellates at the sampling sites in the midcontinent rivers was approximately three times that at the sampling sites in the western rivers and approximately 18 times that at the sampling sites in the eastern rivers. Welch's analysis of variance indicates that phytoplankton abundance at the sampling sites in the midcontinent rivers was significantly higher than that at the sampling sites in the eastern rivers (p-value = 0.013) but was comparable to that at the sampling sites in the western rivers (p-value = 0.095). The higher phytoplankton abundance at the sampling sites in the midcontinent rivers was presumably because these rivers were more eutrophic. Indeed, low phytoplankton abundance occurred in oligotrophic or low trophic sites, whereas eutrophic sites had greater phytoplankton abundance. This study demonstrates that qPCR-based phytoplankton abundance can be a useful numerical indicator of the trophic conditions and water quality in freshwater rivers.

Micro-aeration assisted with electrogenic respiration enhanced the microbial catabolism and ammonification of aromatic amines in industrial wastewater

Improvement of refractory nitrogen-containing organics biodegradation is crucial to meet discharged nitrogen standards and guarantee aquatic ecology safety. Although electrostimulation accelerates organic nitrogen pollutants amination, it remains uncertain how to strengthen ammonification of the amination products. This study demonstrated that ammonification was remarkably facilitated under micro-aerobic conditions through the degradation of aniline, an amination product of nitrobenzene, using an electrogenic respiration system. The microbial catabolism and ammonification were significantly enhanced by exposing the bioanode to air. Based on 16S rRNA gene sequencing and GeoChip analysis, our results indicated that aerobic aniline degraders and electroactive bacteria were enriched in suspension and inner electrode biofilm, respectively. The suspension community had a significantly higher relative abundance of catechol dioxygenase genes contributing to aerobic aniline biodegradation and reactive oxygen species (ROS) scavenger genes to protect from oxygen toxicity. The inner biofilm community contained obviously higher cytochrome c genes responsible for extracellular electron transfer. Additionally, network analysis indicated the aniline degraders were positively associated with electroactive bacteria and could be the potential hosts for genes encoding for dioxygenase and cytochrome, respectively. This study provides a feasible strategy to enhance nitrogen-containing organics ammonification and offers new insights into the microbial interaction mechanisms of micro-aeration assisted with electrogenic respiration.

Chemical Pretreatments and Anaerobic Digestion Shape the Virome and Functional Microbiome in Fecal Sludge

The decomposition and pathogen inactivation of fecal sludge (FS) are vitally important for safely managing onsite sanitation and protecting public and environmental health. However, the microbiome and virome assemblages in FS after chemical and biological treatments remain unclear. Here, we reported the differences in the solid reduction and microbiomes of FS subjected to potassium ferrate (PF), alkali (ALK), and sodium hypochlorite (NaClO) pretreatments and anaerobic digestion (AD). The PF and NaClO pretreatments enhanced FS hydrolysis and pathogen suppression, respectively; AD suppressed Gram-positive bacteria. Most of the viromes were those of bacteriophages, which were also shaped by chemical pretreatments and AD. Metatranscriptome analysis revealed distinct gene expression patterns between the PF- and ALK-pretreated FS and the subsequent AD. Differentially expressed gene profiles indicated that genes related to biological processes, molecular functions, and transcriptional regulators were upregulated in ALK-AD and PF-AD samples. These findings suggested that the effect of different treatment technologies on the viral diversity, pathogen abundance, and metabolic function of the core microbiome extends beyond FS decomposition and that the use of combined processes would provide possible alternatives for FS management in pandemic emergencies.

Tundra Soil Viruses Mediate Responses of Microbial Communities to Climate Warming

The rise of global temperature causes the degradation of the substantial reserves of carbon (C) stored in tundra soils, in which microbial processes play critical roles. Viruses are known to influence the soil C cycle by encoding auxiliary metabolic genes and infecting key microorganisms, but their regulation of microbial communities under climate warming remains unexplored. In this study, we evaluated the responses of viral communities for about 5 years of experimental warming at two depths (15 to 25 cm and 45 to 55 cm) in the Alaskan permafrost region. Our results showed that the viral community and functional gene composition and abundances (including viral functional genes related to replication, structure, infection, and lysis) were significantly influenced by environmental conditions such as total nitrogen (N), total C, and soil thawing duration. Although long-term warming did not impact the viral community composition at the two depths, some glycoside hydrolases encoded by viruses were more abundant at both depths of the warmed plots. With the continuous reduction of total C, viruses may alleviate methane release by altering infection strategies on methanogens. Importantly, viruses can adopt lysogenic and lytic lifestyles to manipulate microbial communities at different soil depths, respectively, which could be one of the major factors causing the differences in microbial responses to warming. This study provides a new ecological perspective on how viruses regulate the responses of microbes to warming at community and functional scales. IMPORTANCE Permafrost thawing causes microbial release of greenhouse gases, exacerbating climate warming. Some previous studies examined the responses of the microbial communities and functions to warming in permafrost region, but the roles of viruses in mediating the responses of microbial communities to warming are poorly understood. This study revealed that warming induced changes in some viral functional classes and in the virus/microbe ratios for specific lineages, which might influence the entire microbial community. Furthermore, differences in viral communities and functions, along with soil depths, are important factors influencing microbial responses to warming. Collectively, our study revealed the regulation of microbial communities by viruses and demonstrated the importance of viruses in the microbial ecology research.

To assemble or not to assemble: metagenomic profiling of microbially mediated biogeochemical pathways in complex communities

High-throughput profiling of microbial functional traits involved in various biogeochemical cycling pathways using shotgun metagenomic sequencing has been routinely applied in microbial ecology and environmental science. Multiple bioinformatics data processing approaches are available, including assembly-based (single-sample assembly and multi-sample assembly) and read-based (merged reads and raw data). However, it remains not clear how these different approaches may differ in data analyses and affect result interpretation. In this study, using two typical shotgun metagenome datasets recovered from geographically distant coastal sediments, the performance of different data processing approaches was comparatively investigated from both technical and biological/ecological perspectives. Microbially mediated biogeochemical cycling pathways, including nitrogen cycling, sulfur cycling and B12 biosynthesis, were analyzed. As a result, multi-sample assembly provided the most amount of usable information for targeted functional traits, at a high cost of computational resources and running time. Single-sample assembly and read-based analysis were comparable in obtaining usable information, but the former was much more time- and resource-consuming. Critically, different approaches introduced much stronger variations in microbial profiles than biological differences. However, community-level differences between the two sampling sites could be consistently observed despite the approaches being used. In choosing an appropriate approach, researchers shall balance the trade-offs between multiple factors, including the scientific question, the amount of usable information, computational resources and time cost. This study is expected to provide valuable technical insights and guidelines for the various approaches used for metagenomic data analysis.

Metagenomics revealing molecular profiles of microbial community structure and metabolic capacity in Bamucuo lake, Tibet

Microorganisms play critical ecological roles in the global biogeochemical cycles. However, extensive information on the microbial communities in Qinghai-Tibet Plateau (QTP), which is the highest plateau in the world, is still lacking, particularly in high elevation locations above 4500 m. Here, we performed a survey of th e soil and water microbial communities in Bamucuo Lake, Tibet, by using shotgun metagenomic methods. In the soil and water samples, we reconstructed 75 almost complete metagenomic assembly genomes, and 74 of the metagenomic assembly genomes from the water sample represented novel species. Proteobacteria and Actinobacteria were found to be the dominant bacterial phyla, while Euryarchaeota was the dominant archaeal phylum. The largest virus, Pandoravirus salinus, was found in the soil microbial community. We concluded that the microorganisms in Bamucuo Lake are most likely to fix carbon mainly through the 3-hydroxypropionic bi-cycle pathway. This study, for the first time, characterized the microbial community composition and metabolic capacity in QTP high-elevation locations with 4555 m, confirming that QTP is a vast and valuable resource pool, in which many microorganisms can be used to develop new bioactive substances and new antibiotics to which pathogenic microorganisms have not yet developed resistance.

Microbial and phage communities as well as their interaction in PO saponification wastewater treatment systems

Viruses or phages were considered affecting microbial community composition, metabolic process, and biogeochemical cycles. However, phage communities and their potential associations with microbial community are not well understood in the activated sludge (AS) of wastewater treatment plants (WWTPs). In this study, we explored the interactions between phages and microbial community by using propylene oxide (PO) saponification WWTPs as an example. Bacterial, eukaryal and archaeal communities were investigated and 34 phage contigs (>10 kb) were recovered from PO saponification WWTPs. At least 3 complete phage genomes were assembled. In all 34 phages, 21 of them have been predicted to their host. The association network analysis showed that abundant phages were associated with abundant microorganisms. This result conformed to Kill-the-Winner model. Notably, 45 auxiliary metabolic genes (AMGs) were identified from phage genomes (including small contig fragments). They influenced bacterial metabolism through facilitating phages replication and avoiding host death. Collectively, our results suggested that phage community affect microbial community and metabolic pathways by killing their hosts and AMGs transfer in AS of PO saponification WWTPs.

Quantifying Trade-Offs in the Choice of Ribosomal Barcoding Markers for Fungal Amplicon Sequencing: a Case Study on the Grapevine Trunk Mycobiome

The evolution of sequencing technology and multiplexing has rapidly expanded our ability to characterize fungal diversity in the environment. However, obtaining an unbiased assessment of the fungal community using ribosomal markers remains challenging. Longer amplicons were shown to improve taxonomic resolution and resolve ambiguities by reducing the risk of spurious operational taxonomic units. We examined the implications of barcoding strategies by amplifying and sequencing two ribosomal DNA fragments. We analyzed the performance of the full internal transcribed spacer (ITS) and a longer fragment including also a part of the 28S ribosomal subunit replicated on 60 grapevine trunk core samples. Grapevine trunks harbor highly diverse fungal communities with implications for disease development. Using identical handling, amplification, and sequencing procedures, we obtained higher sequencing depths for the shorter ITS amplicon. Despite the more limited access to polymorphism, the overall diversity in amplified sequence variants was higher for the shorter ITS amplicon. We detected no meaningful bias in the phylogenetic composition due to the amplicon choice across analyzed samples. Despite the increased resolution of the longer ITS-28S amplicon, the higher and more consistent yields of the shorter amplicons produced a clearer resolution of the fungal community of grapevine stem samples. Our study highlights that the choice of ribosomal amplicons should be carefully evaluated and adjusted according to specific goals. IMPORTANCE Surveying fungal communities is key to our understanding of ecological functions of diverse habitats. Fungal communities can inform about the resilience of agricultural ecosystems, risks to human health, and impacts of pathogens. Community compositions are typically analyzed using ribosomal DNA sequences. Due to technical limitations, most fungal community surveys were based on amplifying a short but highly variable fragment. Advances in sequencing technology enabled the use of longer fragments that can address some limitations of species identification. In this study, we examined the implications of choosing either a short or long ribosomal sequence fragment by replicating the analyses on 60 grapevine wood core samples. Using highly accurate long-read sequencing, we found that the shorter fragment produced substantially higher yields. The shorter fragment also revealed more sequence and species diversity. Our study highlights that the choice of ribosomal amplicons should be carefully evaluated and adjusted according to specific goals.

Research on the Gut Microbiota of Hainan Black Goat

The intestine of animals is a complex micro-ecosystem containing a large number of microbiomes, which is essential for the host's health development. The Hainan black goat with good resistance and adaptability is a unique species in Hainan, China. These unique physiological characteristics are inseparable from their intestinal microbiota. In this study, high-throughput sequencing was used to investigate bacterial communities in different segments of the intestinal tract of Hainan black goat. The results showed that the indices of Chao1 and ACE in the cecum and colon were significantly greater than those in the ileum (p = 0.007, 0.018). According to PCoA, the intestinal flora composition of the cecum and colon is almost equivalent. In contexts of the phylum, Firmicutes, Bacteroidota, and Pseudomonadota were the dominant phyla in the gut of the Hainan black goat. While in context of the genus, the dominant groups in the gut of black goats mainly include Ruminococcaceae_UCG-005, Bacteroides, Paeniclostridium, Christensenellaceae_R-7_group, Rikenellaceae_RC9_gut_group, and Eubacterium coprostanoligenes _group, Prevotella_1, they have different proportions in different intestinal segments. The gut microbiota of Hainan black goat is mainly Firmicutes, Bacteroidota, and Pseudomonadota. Influenced by the intestinal location where they colonize, the large intestine has a more complex intestinal flora than the small intestine. In contrast, there are only minor differences between the caecum and the colon in the large intestine.

Therapeutic and Metagenomic Potential of the Biomolecular Therapies against Periodontitis and the Oral Microbiome: Current Evidence and Future Perspectives

The principles of periodontal therapy are based on the control of microbial pathogens and host factors that contribute to biofilm dysbiosis, with the aim of modulating the progression of periodontitis and periodontal tissue destruction. It is currently known how differently each individual responds to periodontal treatment, depending on both the bacterial subtypes that make up the dysbiotic biofilm and interindividual variations in the host inflammatory response. This has allowed the current variety of approaches for the management of periodontitis to be updated by defining the goals of target strategies, which consist of reducing the periodontopathogenic microbial flora and/or modulating the host-mediated response. Therefore, this review aims to update the current variety of approaches for the management of periodontitis based on recent target therapies. Recently, encouraging results have been obtained from several studies exploring the effects of some targeted therapies in the medium- and long-term. Among the most promising target therapies analyzed and explored in this review include: cell-based periodontal regeneration, mediators against bone resorption, emdogain (EMD), platelet-rich plasma, and growth factors. The reviewed evidence supports the hypothesis that the therapeutic combination of epigenetic modifications of periodontal tissues, interacting with the dysbiotic biofilm, is a key step in significantly reducing the development and progression of disease in periodontal patients and improving the therapeutic response of periodontal patients. However, although studies indicate promising results, these need to be further expanded and studied to truly realize the benefits that targeted therapies could bring in the treatment of periodontitis.

Exploration of pristine plate-tectonic plains and mining exposure areas for indigenous microbial communities and its impact on the mineral-microbial geochemical weathering process in ultramafic setting

Heavy metal release from harsh ultramafic settings influences microbial diversity and function in soil ecology. This study aimed to determine how serpentine mineralosphere bacterial assemblies and their functions differed in two different plate-tectonic plains and mining exposure sites under heavy metal release conditions. The results showed that the Proteobacteria, Actinobacteria, Cyanobacteria, Planctomycetes, and Chloroflexi were the most abundant bacterial groups among all the sites. The log10-based LDA scores highlighted that some specific groups of bacterial assemblies were enriched in plate-tectonic plains and mining activity areas of the serpentine mineralosphere. Functional prediction revealed that the abundance of heavy metal (Cr and Ni) resistance and biogeochemical cycles involving functional KEGG orthology varied in samples from plate-tectonic plains and mining activity sites. The bipartite plot showed that the enrichment of the biogeochemical cycle and heavy metal resistance functional genes correlated with the abundance of serpentine mineralosphere bacterial groups at a 0.005% confidence level. The co-occurrence network plot revealed that the interconnection pattern of the indigenous bacterial assemblies changed in different plate-tectonic plains and mining exposure areas. Finally, this study concluded that due to heavy metal release, the variation in bacterial assemblies, their functioning, and intercommunity co-occurrence patterns were clarified the synergetic effect of mineral-microbial geochemical weathering process in serpentine mining areas.

Potential and limitations for monitoring of pesticide biodegradation at trace concentrations in water and soil

Pesticides application on agricultural fields results in pesticides being released into the environment, reaching soil, surface water and groundwater. Pesticides fate and transformation in the environment depend on environmental conditions as well as physical, chemical and biological degradation processes. Monitoring pesticides biodegradation in the environment is challenging, considering that traditional indicators, such as changes in pesticides concentration or identification of pesticide metabolites, are not suitable for many pesticides in anaerobic environments. Furthermore, those indicators cannot distinguish between biotic and abiotic pesticide degradation processes. For that reason, the use of molecular tools is important to monitor pesticide biodegradation-related genes or microorganisms in the environment. The development of targeted molecular (e.g., qPCR) tools, although laborious, allowed biodegradation monitoring by targeting the presence and expression of known catabolic genes of popular pesticides. Explorative molecular tools (i.e., metagenomics & metatranscriptomics), while requiring extensive data analysis, proved to have potential for screening the biodegradation potential and activity of more than one compound at the time. The application of molecular tools developed in laboratory and validated under controlled environments, face challenges when applied in the field due to the heterogeneity in pesticides distribution as well as natural environmental differences. However, for monitoring pesticides biodegradation in the field, the use of molecular tools combined with metadata is an important tool for understanding fate and transformation of the different pesticides present in the environment.

Functional Guilds, Community Assembly, and Co-occurrence Patterns of Fungi in Metalliferous Mine Tailings Ponds in Mainland China

Metalliferous mine tailings ponds are generally characterized by low levels of nutrient elements, sustained acidic conditions, and high contents of toxic metals. They represent one kind of extreme environments that are believed to resemble the Earth's early environmental conditions. There is increasing evidence that the diversity of fungi inhabiting mine tailings ponds is much higher than previously thought. However, little is known about functional guilds, community assembly, and co-occurrence patterns of fungi in such habitats. As a first attempt to address this critical knowledge gap, we employed high-throughput sequencing to characterize fungal communities in 33 mine tailings ponds distributed across 18 provinces of mainland China. A total of 5842 fungal phylotypes were identified, with saprotrophic fungi being the major functional guild. The predictors of fungal diversity in whole community and sub-communities differed considerably. Community assembly of the whole fungal community and individual functional guilds were primarily governed by stochastic processes. Total soil nitrogen and total phosphorus mediated the balance between stochastic and deterministic processes of the fungal community assembly. Co-occurrence network analysis uncovered a high modularity of the whole fungal community. The observed main modules largely consisted of saprotrophic fungi as well as various phylotypes that could not be assigned to known functional guilds. The richness of core fungal phylotypes, occupying vital positions in co-occurrence network, was positively correlated with edaphic properties such as soil enzyme activity. This indicates the important roles of core fungal phylotypes in soil organic matter decomposition and nutrient cycling. These findings improve our understanding of fungal ecology of extreme environments.

Prospects of advanced metagenomics and meta-omics in the investigation of phytomicrobiome to forecast beneficial and pathogenic response

Microorganisms dwell in diverse plant niches as non-axenic biotic components that are beneficial as well pathogenic for the host. They improve nutrients-uptake, stress tolerance, phytohormone synthesis, and strengthening the defense system through phyllosphere, rhizosphere, and endosphere. The negative consequences of the microbial communities are largely in the form of diseases characterized by certain symptoms such as gall, cankers, rots etc. Uncultivable and unspecified nature of different phytomicrobiomes communities is a challenge in the management of plant disease, a leading cause for the loss of the plant products. Metagenomics has opened a new gateway for the exploration of microorganisms that are hitherto unknown, enables investigation of the functional aspect of microbial gene products through metatranscriptomics and metabolomics. Metagenomics offers advantages of characterizing previously unknown microorganisms from extreme environments like hot springs, glaciers, deep seas, animal gut etc. besides bioprospecting gene products such as Taq polymerase, bor encoded indolotryptoline, hydrolases, and polyketides. This review provides a detailed account of the phytomicrobiome networks and highlights the importance and limitations of metagenomics and other meta-omics approaches for the understanding of plant microbial diversity with special focus on the disease control and its management.

Fungal dynamics and potential functions during anaerobic digestion of food waste

Fungi could play an important role during anaerobic digestion (AD), but have received less attention than prokaryotes. Here, AD bioreactors of food waste were performed to explore fungal succession and their potential ecological and engineering value. We found that similar patterns in fungal biomass and diversity, decreasing from the initial time point (Day 0) to the lowest value within 3-6 days and then started to rise and stabilized between 9 and 42 days. Throughout the entire AD process, variations in fungal community composition were observed and dominant fungal taxa have the potential ability to degrade complex organic matter and alleviate fatty acid and ammonia accumulation. Furthermore, we found that deterministic processes gradually dominated fungal assembly succession (up to 84.85% at the final stage), suggesting changing environmental status responsible for fungal community dynamics and specifically, fungal community structure, diversity and biomass were regulated by different environmental variables or the same variables with opposite effects. AD bioreactors could directionally select specific fungal taxa over time, but some highly abundant fungi could not be mapped to any fungal species with defined function in the reference database, so function prediction relying on PICRUSt2 may underestimate fungal function in AD systems. Collectively, our study confirmed fungi have important ecological and engineering values in AD systems.

Single-cell metagenomics and metagenomics approaches reveal extracellular electron transfer of psychrophilic electroactive biofilms

Revealing the metabolic functions and the extracellular electron transfer (EET) process of psychrophilic electroactive biofilms (PEB) is important for understanding the functional adaptability of electroactive bacteria (EAB) to low temperatures. In this study, single cell sorting (SCS)-based metagenomics sequencing was used to characterize the composition and function of the PEB. Biofilm microbiome analysis showed that Geobacter, with a relative abundance of 62.64%, dominated the PEB enriched in the bioelectrochemical system (BES) at 4 °C. Both the metagenome (MAG) and single-cell metagenome (SCM) revealed that there were no obvious metabolic differences between the original biofilm and the sorted single cells. The presence of genes associated with type IV pilus, c-type cytochromes, and riboflavin indicated that the EET potential was maintained in the PEB at low temperatures. These results suggested that SCM provides an alternative approach to reconstruct the metabolic functions of uncultured and slow-growing EAB.

MRG Chip: A High-Throughput qPCR-Based Tool for Assessment of the Heavy Metal(loid) Resistome

Bacterial metal detoxification mechanisms have been well studied for centuries in pure culture systems. However, profiling metal resistance determinants at the community level is still a challenge due to the lack of comprehensive and reliable quantification tools. Here, a novel high-throughput quantitative polymerase chain reaction (HT-qPCR) chip, termed the metal resistance gene (MRG) chip, has been developed for the quantification of genes involved in the homeostasis of 9 metals. The MRG chip contains 77 newly designed degenerate primer sets and 9 published primer sets covering 56 metal resistance genes. Computational evaluation of the taxonomic coverage indicated that the MRG chip had a broad coverage matching 2 kingdoms, 29 phyla, 64 classes, 130 orders, 226 families, and 382 genera. Temperature gradient PCR and HT-qPCR verified that 57 °C was the optimal annealing temperature, with amplification efficiencies of over 94% primer sets achieving 80-110%, with R² > 0.993. Both computational evaluation and the melting curve analysis of HT-qPCR validated a high specificity. The MRG chip has been successfully applied to characterize the distribution of diverse metal resistance determinants in natural and human-related environments, confirming its wide scope of application. Collectively, the MRG chip is a powerful and efficient high-throughput quantification tool for exploring the microbial metal resistome.

Comparison of bacterial diversity, root exudates and soil enzymatic activities in the rhizosphere of AVP1-transgenic and non-transgenic wheat (Triticum aestivum L.)

AIMS

Soil microbial communities are among the most diverse communities that might be affected due to transgenic crops. Therefore, risk assessment studies on transgenes are essentially required as any adverse effects may depend not only on the specific gene and crop involved but also on soil conditions.

METHODS AND RESULTS

The present study deals with the comparison of bacterial populations, root exudates, and activities of soil enzymes in non-transgenic and AVP1-transgenic wheat rhizosphere, overexpressing vacuolar H+pyrophosphatase for salinity and drought stress tolerance. Amounts of organic acids and sugars produced as root exudates and activities of dehydrogenase, phosphatase, and protease enzymes in soil solution showed no significant differences in AVP1-transgenic and non-transgenic wheat rhizosphere, except for urease and phenol oxidase activities. The higher copy number of nifH gene showed the abundance of nitrogen-fixing bacteria in the rhizosphere of AVP1-transgenic wheat compared with non-transgenic wheat. nifH gene sequence analysis indicated the common diazotrophic genera Azospirillum, Bradyrhizobium, Rhizobium, and Pseudomonas in AVP1-transgenic and non-transgenic wheat except for Zoogloea detected only in non-transgenic wheat. Using 454-pyrosequencing of 16S rRNA gene from soil DNA, a total of 156, 282 sequences of 18 phyla were obtained, which represented bacterial (128,006), Archeal (7,928), and unclassified (21,568) sequences. Proteobacteria, Crenarchaeota, and Firmicutes were the most abundant phyla in transgenic and non-transgenic wheat rhizosphere. Further comparison of different taxonomic units at the genus level showed similar distribution in transgenic and non-transgenic wheat rhizosphere.

CONCLUSION

We conclude that AVP1 gene in transgenic wheat has no apparent adverse effects on the soil environment and different bacterial communities. However, bacterial community depends on several other factors not only genetic composition of the host plants.

SIGNIFICANCE OF THE STUDY

The present research supports introduction and cultivation of transgenic plants in agricultural systems without any adverse effects on indigenous bacterial communities and soil ecosystem.

Substrate degradation pathways, conserved functions and community composition of the hindgut microbiota in the herbivorous marine fish Kyphosus sydneyanus

Symbiotic gut microbiota in the herbivorous marine fish Kyphosus sydneyanus play an important role in digestion by converting refractory algal carbohydrate into short-chain fatty acids. Here we characterised community composition using both 16S rRNA gene amplicon sequencing and shotgun-metagenome sequencing. Sequencing was carried out on lumen and mucosa samples (radial sections) from three axial sections taken from the hindgut of wild-caught fish. Both lumen and mucosa communities displayed distinct distributions along the hindgut, likely an effect of the differing selection pressures within these hindgut locations, as well as considerable variation among individual fish. In contrast, metagenomic sequences displayed a high level of functional similarity between individual fish and gut sections in the relative abundance of genes (based on sequencing depth) that encoded enzymes involved in algal-derived substrate degradation. These results suggest that the host gut environment selects for functional capacity in symbionts rather than taxonomic identity. Functional annotation of the enzymes encoded by the gut microbiota was carried out to infer the metabolic pathways used by the gut microbiota for the degradation of important dietary substrates: mannitol, alginate, laminarin, fucoidan and galactan (e.g. agar and carrageenan). This work provides the first evidence of the genomic potential of K. sydneyanus hindgut microbiota to convert highly refractory algal carbohydrates into metabolically useful short-chain fatty acids.

Ecosystem-specific microbiota and microbiome databases in the era of big data

The rapid development of sequencing methods over the past decades has accelerated both the potential scope and depth of microbiota and microbiome studies. Recent developments in the field have been marked by an expansion away from purely categorical studies towards a greater investigation of community functionality. As in-depth genomic and environmental coverage is often distributed unequally across major taxa and ecosystems, it can be difficult to identify or substantiate relationships within microbial communities. Generic databases containing datasets from diverse ecosystems have opened a new era of data accessibility despite costs in terms of data quality and heterogeneity. This challenge is readily embodied in the integration of meta-omics data alongside habitat-specific standards which help contextualise datasets both in terms of sample processing and background within the ecosystem. A special case of large genomic repositories, ecosystem-specific databases (ES-DB's), have emerged to consolidate and better standardise sample processing and analysis protocols around individual ecosystems under study, allowing independent studies to produce comparable datasets. Here, we provide a comprehensive review of this emerging tool for microbial community analysis in relation to current trends in the field. We focus on the factors leading to the formation of ES-DB's, their comparison to traditional microbial databases, the potential for ES-DB integration with meta-omics platforms, as well as inherent limitations in the applicability of ES-DB's.

Embracing mountain microbiome and ecosystem functions under global change

Mountains are pivotal to maintaining habitat heterogeneity, global biodiversity, ecosystem functions and services to humans. They have provided classic model natural systems for plant and animal diversity gradient studies for over 250 years. In the recent decade, the exploration of microorganisms on mountainsides has also achieved substantial progress. Here, we review the literature on microbial diversity across taxonomic groups and ecosystem types on global mountains. Microbial community shows climatic zonation with orderly successions along elevational gradients, which are largely consistent with traditional climatic hypotheses. However, elevational patterns are complicated for species richness without general rules in terrestrial and aquatic environments and are driven mainly by deterministic processes caused by abiotic and biotic factors. We see a major shift from documenting patterns of biodiversity towards identifying the mechanisms that shape microbial biogeographical patterns and how these patterns vary under global change by the inclusion of novel ecological theories, frameworks and approaches. We thus propose key questions and cutting-edge perspectives to advance future research in mountain microbial biogeography by focusing on biodiversity hypotheses, incorporating meta-ecosystem framework and novel key drivers, adapting recently developed approaches in trait-based ecology and manipulative field experiments, disentangling biodiversity-ecosystem functioning relationships and finally modelling and predicting their global change responses.

Dissecting the Effect of Berberine on the Intestinal Microbiome in the Weaned Piglets by Metagenomic Sequencing

This study aimed to investigate the microbial structure and function in the rectum of weaned piglets with berberine supplementation. Twelve healthy 21-day-old Duorc × (Landrace × Large White) weaned piglets (similar body weight) were evenly divided into control and berberine groups and were fed a basal diet supplemented with 0 and 0.1% berberine, respectively. After 21 days, metagenomic sequencing analysis was performed to detect microbial composition and function in the rectum of weaned piglets. Results showed that there were 10,597,721,931–14,059,392,900 base pairs (bp) and 10,186,558,171–15,859,563,342 bp of clean data in the control and berberine groups, respectively. The Q20s of the control and berberine groups were 97.15 to 97.7% and 96.26 to 97.68%, respectively. The microorganisms in the berberine group had lower (p < 0.05) Chao1, alternating conditional expectation, Shannon, and Simpson indices at the species levels than those in the control group. Analysis of similarity showed that there were significant differences (p < 0.01) between the control and berberine groups at the genus and species levels of the gut microorganisms. Dietary berberine significantly increased (p < 0.05) the abundance of Subdoligranulum variabile, but decreased (p < 0.05) the abundance of Prevotella copri compared with the control group. Carbohydrate-active enzymes analysis revealed that the levels of polysaccharide lyases and carbohydrate esterases were lower (p < 0.05) in the berberine group than that in the control group. Linear discriminant analysis effect size analysis showed that berberine supplementation could induce various significant Kyoto Encyclopedia of Genes and Genomes pathways, including carbohydrate metabolism, environmental information processing, and microbial metabolism in diverse environments. In conclusion, our findings suggest that berberine could improve the composition, abundance, structure, and function of gut microbiome in the weaned piglets, potentially providing a suitable approach for the application of berberine in human and animal health.

Environmental DNA metabarcoding for benthic monitoring: A review of sediment sampling and DNA extraction methods

Environmental DNA (eDNA) metabarcoding (parallel sequencing of DNA/RNA for identification of whole communities within a targeted group) is revolutionizing the field of aquatic biomonitoring. To date, most metabarcoding studies aiming to assess the ecological status of aquatic ecosystems have focused on water eDNA and macroinvertebrate bulk samples. However, the eDNA metabarcoding has also been applied to soft sediment samples, mainly for assessing microbial or meiofaunal biota. Compared to classical methodologies based on manual sorting and morphological identification of benthic taxa, eDNA metabarcoding offers potentially important advantages for assessing the environmental quality of sediments. The methods and protocols utilized for sediment eDNA metabarcoding can vary considerably among studies, and standardization efforts are needed to improve their robustness, comparability and use within regulatory frameworks. Here, we review the available information on eDNA metabarcoding applied to sediment samples, with a focus on sampling, preservation, and DNA extraction steps. We discuss challenges specific to sediment eDNA analysis, including the variety of different sources and states of eDNA and its persistence in the sediment. This paper aims to identify good-practice strategies and facilitate method harmonization for routine use of sediment eDNA in future benthic monitoring.

Antimicrobial Resistance in Rivers: A Review of the Genes Detected and New Challenges

River ecosystems are very important parts of the water cycle and an excellent habitat, food, and drinking water source for many organisms, including humans. Antibiotics are emerging contaminants which can enter rivers from various sources. Several antibiotics and their related antibiotic resistance genes (ARGs) have been detected in these ecosystems by various research programs and could constitute a substantial problem. The presence of antibiotics and other resistance cofactors can boost the development of ARGs in the chromosomes or mobile genetic elements of natural bacteria in rivers. The ARGs in environmental bacteria can also be transferred to clinically important pathogens. However, antibiotics and their resistance genes are both not currently monitored by national or international authorities responsible for controlling the quality of water bodies. For example, they are not included in the contaminant list in the European Water Framework Directive or in the US list of Water-Quality Benchmarks for Contaminants. Although ARGs are naturally present in the environment, very few studies have focused on non-impacted rivers to assess the background ARG levels in rivers, which could provide some useful indications for future environmental regulation and legislation. The present study reviews the antibiotics and associated ARGs most commonly measured and detected in rivers, including the primary analysis tools used for their assessment. In addition, other factors that could enhance antibiotic resistance, such as the effects of chemical mixtures, the effects of climate change, and the potential effects of the coronavirus disease 2019 pandemic, are discussed. Environ Toxicol Chem 2022;41:687-714. © 2022 SETAC.