Functional Metabolomics Describes the Yeast Biosynthetic Regulome.

Genome-metabolism interactions enable cell growth. To probe the extent of these interactions and delineate their functional contributions, we quantified the Saccharomyces amino acid metabolome and its response to systematic gene deletion. Over one-third of coding genes, in particular those important for chromatin dynamics, translation, and transport, contribute to biosynthetic metabolism. Specific amino acid signatures characterize genes of similar function. This enabled us to exploit functional metabolomics to connect metabolic regulators to their effectors, as exemplified by TORC1, whose inhibition in exponentially growing cells is shown to match an interruption in endomembrane transport. Providing orthogonal information compared to physical and genetic interaction networks, metabolomic signatures cluster more than half of the so far uncharacterized yeast genes and provide functional annotation for them. A major part of coding genes is therefore participating in gene-metabolism interactions that expose the metabolism regulatory network and enable access to an underexplored space in gene function.

Exploring functional genes' correlation with (S)-equol concentration and new daidzein racemase identification.

With its estrogenic activity, (S)-equol plays an important role in maintaining host health and preventing estrogen-related diseases. Exclusive production occurs through the transformation of soy isoflavones by intestinal bacteria, but the reasons for variations in (S)-equol production among different individuals and species remain unclear. Here, fecal samples from humans, pigs, chickens, mice, and rats were used as research objects. The concentrations of (S)-equol, along with the genetic homology and evolutionary relationships of (S)-equol production-related genes [daidzein reductase (DZNR), daidzein racemase (DDRC), dihydrodaidzein reductase (DHDR), tetrahydrodaidzein reductase (THDR)], were analyzed. Additionally, in vitro functional verification of the newly identified DDRC gene was conducted. It was found that approximately 40% of human samples contained (S)-equol, whereas 100% of samples from other species contained (S)-equol. However, there were significant variations in (S)-equol content among the different species: rats > pigs > chickens > mice > humans. The distributions of the four genes displayed species-specific patterns. High detection rates across various species were exhibited by DHDR, THDR, and DDRC. In contrast, substantial variations in detection rates among different species and individuals were observed with respect to DZNR. It appears that various types of DZNR may be associated with different concentrations of (S)-equol, which potentially correspond to the regulatory role during (S)-equol synthesis. This enhances our understanding of individual variations in (S)-equol production and their connection with functional genes in vitro. Moreover, the newly identified DDRC exhibits higher potential for (S)-equol synthesis compared to the known DDRC, providing valuable resources for advancing in vitro (S)-equol production. IMPORTANCE: (S)-equol ((S)-EQ) plays a crucial role in maintaining human health, along with its known capacity to prevent and treat various diseases, including cardiovascular diseases, metabolic syndromes, osteoporosis, diabetes, brain-related diseases, high blood pressure, hyperlipidemia, obesity, and inflammation. However, factors affecting individual variations in (S)-EQ production and the underlying regulatory mechanisms remain elusive. This study examines the association between functional genes and (S)-EQ production, highlighting a potential correlation between the DZNR gene and (S)-EQ content. Various types of DZNR may be linked to the regulation of (S)-EQ synthesis. Furthermore, the identification of a new DDRC gene offers promising prospects for enhancing in vitro (S)-EQ production.

Simultaneous removal of nitrogen, phosphorus, and organic matter from oligotrophic water in a system containing biochar and construction waste iron: Performances and biotic community analysis.

The issue of combined pollution in oligotrophic water has garnered increasing attention in recent years. To enhance the pollutant removal efficiency in oligotrophic water, the system containing Zoogloea sp. FY6 was constructed using polyester fiber wrapped sugarcane biochar and construction waste iron (PWSI), and the denitrification test of simulated water and actual oligotrophic water was carried out for 35 days. The experimental findings from the systems indicated that the removal efficiencies of nitrate (NO3--N), total nitrogen (TN), chemical oxygen demand (COD), and total phosphorus (TP) in simulated water were 88.61%, 85.23%, 94.28%, and 98.90%, respectively. The removal efficiencies of actual oligotrophic water were 83.06%, 81.39%, 81.66%, and 97.82%, respectively. Furthermore, the high-throughput sequencing data demonstrated that strain FY6 was successfully loaded onto the biological carrier. According to functional gene predictions derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, the introduction of PWSI enhanced intracellular iron cycling and nitrogen metabolism.

Exogenous compound bacteria enhance the nutrient removal efficiency of integrated bioremediation systems: Functional genes and microorganisms play key roles.

With the continuous development of intensive mariculture, the application of the integrated bioremediation system of aquaculture wastewater (IBSAW) is increasingly promoted. However, the process and nutrients removal performance of the IBSAW need to be further optimized due to its immature technologies. In this study, exogenous compound bacteria (ECB) were added to IBSAW to investigate its pollutants removal efficiency and the relevant mechanisms. High-throughput sequencing and Geochip gene array were used to analyze the correlation between nutrients and bacteria, and the abundance of N and P cycling genes were quantified. Multivariable statistics, dimensionality reduction analysis, and network analysis were applied to explore the mechanisms of IBSAW operation. The results showed that the nutrients decreased significantly after adding ECB, with the brush treatment group significantly outperforming the ceramsite in removing NO3- and PO43-. Ceramsite has an advantage in removing NO2--N. The addition of ECB and different substrates significantly affected the composition of bacterial communities. The contents of nosZ and nirKS related to denitrification in the treatment groups were significantly higher than those in the control group, and the contents in the brush treatment group were significantly higher than that of ceramsite. The biomarkers Psychroserpens and Ruegeria on the biofilm of the brush treatment group were positively correlated with nirKS, while Mycobacterium, Erythrobacter and Paracoccus, Pseudohaliea in the ceramsite group were positively correlated with nirS and nirK, respectively. Therefore, it is speculated that the ECB significantly promoted the increase of denitrification bacteria by affecting the composition of bacterial communities, and the ECB combined with functional genera improved the efficiency of nutrients removal in the system. This study provided a reference for understanding the process and mechanism of nutrients removal, optimizing the wastewater purification technology of the IBSAW and improving the performance of the system.

Effects of citric acid on arsenic transformation and microbial communities in different paddy soils.

Root exudate is a major source of soil organic matter and can significantly affect arsenic (As) migration and transformation in paddy soils. Citric acid is the main component of rice root exudate, however, the impacts and rules of citric acid on As bioavailability and rhizobacteria in different soils remains unclear. This study investigated the effects of citric acid on As transformation and microbial community in ten different paddy soils by flooded soil culture experiments. The results showed that citric acid addition increased total As and arsenate (As(V)) in the soil porewater by up to 41-fold and 65-fold, respectively, after 2-h incubation. As(V) was the main As species in soil porewater within 10 days with the addition of citric acid. Non-specifically sorbed As of soils, total Fe and total As were the main environmental factors affecting the soil microbial communities. High-throughput sequencing analysis demonstrated that citric acid addition significantly altered the soil microbial community structure, shifting the Proteobacteria-related reducing bacteria to Firmicutes-related reducing bacteria in different paddy soils. The relative abundance of Firmicutes was promoted by 174-196%. Clostridium-related bacteria belonging to Firmicutes became the dominant genera, which is believed to regulate As release through the reductive dissolution of iron oxides or the direct reduction of As(V) to arsenite (As(III)). However, citric acid addition significantly decreased the relative abundance of Geobacter and Anaeromyxobacter, which are also typical active As(V)- and ferric-reducing bacteria. Real-time quantitative polymerase chain reaction (qPCR) also revealed that the addition of citric acid significantly decreased the relative abundances of Geobacter in the different soils by 8-28 times while the relative abundances of Clostridium increased by 2-5 times. These results provide significant insight on As transformation in different types of rice rhizospheric soils and guidance for the application of rice varieties with low citric acid exuding to restrict As accumulation.

Ofloxacin weakened treatment performance of rural domestic sewage in an aerobic biofilm system by affecting biofilm resistance, bacterial community, and functional genes.

Ofloxacin (OFL) is a typical fluoroquinolone antibiotic widely detected in rural domestic sewage, however, its effects on the performance of aerobic biofilm systems during sewage treatment process remain poorly understood. We carried out an aerobic biofilm experiment to explore how the OFL with different concentrations affects the pollutant removal efficiency of rural domestic sewage. Results demonstrated that the OFL negatively affected pollutant removal in aerobic biofilm systems. High OFL levels resulted in a decrease in removal efficiency: 9.33% for chemical oxygen demand (COD), 18.57% for ammonium (NH4+-N), and 8.49% for total phosphorus (TP) after 35 days. The findings related to the chemical and biological properties of the biofilm revealed that the OFL exposure triggered oxidative stress and SOS responses, decreased the live cell number and extracellular polymeric substance content of biofilm, and altered bacterial community composition. More specifically, the relative abundance of key genera linked to COD (e.g., Rhodobacter), NH4+-N (e.g., Nitrosomonas), and TP (e.g., Dechlorimonas) removal was decreased. Such the OFL-induced decrease of these genera might result in the down-regulation of carbon degradation (amyA), ammonia oxidation (hao), and phosphorus adsorption (ppx) functional genes. The conventional pollutants (COD, NH4+-N, and TP) removal was directly affected by biofilm resistance, functional genes, and bacterial community under OFL exposure, and the bacterial community played a more dominant role based on partial least-squares path model analysis. These findings will provide valuable insights into understanding how antibiotics impact the performance of aerobic biofilm systems during rural domestic sewage treatment.

Rainfall-induced changes in aquatic microbial communities and stability of dissolved organic matter: Insight from a Fen river analysis.

Microbial communities are pivotal in aquatic ecosystems, as they affect water quality, energy dynamics, nutrient cycling, and hydrological stability. This study explored the effects of rainfall on hydrological and photosynthetic parameters, microbial composition, and functional gene profiles in the Fen River. Our results demonstrated that rainfall-induced decreases in stream temperature, dissolved oxygen, pH, total phosphorus, chemical oxygen demand, and dissolved organic carbon concentrations. In contrast, rainfall increased total dissolved solids, salinity, and ammonia-nitrogen concentrations. A detailed microbial community structure analysis revealed that Cyanobacteria was the dominant microbial taxon in the Fen River, accounting for approximately 75% and 25% of the microalgal and bacterial communities, respectively. The abundance of Chlorophyta and Bacillariophyta increased by 47.66% and 29.92%, respectively, whereas the relative abundance of Bacteroidetes decreased by 37.55% under rainfall conditions. Stochastic processes predominantly affected the assembly of the bacterial community on rainy days. Functional gene analysis revealed variations in bacterial functions between sunny (Sun) and rainy (Rain) conditions, particularly in genes associated with the carbon cycle. The 3-oxoacyl-[acyl-carrier-protein] reductase gene was more abundant in the Fen River bacterial community. Particular genes involved in metabolism and environmental information processing, including the acetyl-CoA C-acetyltransferase (atoB), enoyl-CoA hydratase (paaF), and branched-chain amino acid transport system gene (livK), which are integral to environmental information processing, were more abundant in Sun than the Rain conditions. In contrast, the phosphate transport system gene, the galactose metabolic gene, and the pyruvate metabolic gene were more abundant in Rain. The excitation-emission matrix analysis with parallel factor analysis identified four fluorescence components (C1-C4) in the river, which were predominantly protein- (C1) and humic-like (C2-C4) substances. Rainfall affected organic matter production and transport, leading to changes in the degradation and stability of dissolved organic matter. Overall, this study offers insight into how rainfall affects aquatic ecosystems.

Metagenomic analysis revealed N-metabolizing microbial response of Iris tectorum to Cr stress after colonization by arbuscular mycorrhizal fungi.

Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting bacteria enhance plant tolerance to abiotic stress and promote plant growth in contaminated soil. However, the interaction mechanism between rhizosphere microbial communities under chromium (Cr) stress remains unclear. This study conducted a greenhouse pot experiment and metagenomics analysis to reveal the comprehensive effects of the interaction between AMF (Rhizophagus intraradices) and nitrogen-N metabolizing plant growth promoters on the growth of Iris tectorum. The results showed that AMF significantly increased the biomass and nutrient levels of I. tectorum in contaminated soil and decreased the content of Cr in the soil. Metagenomics analysis revealed that the structure and composition of the rhizosphere microbial community involved in nitrogen metabolism changed significantly after inoculation with AMF under Cr stress. Functional genes related to soil nitrogen mineralization (gltB, gltD, gdhA, ureC, and glnA), nitrate reduction to ammonium (nirB, nrfA, and nasA), and soil nitrogen assimilation (NRT, nrtA, and nrtC) were up-regulated in the N-metabolizing microbial community. In contrast, the abundance of functional genes involved in denitrification (nirK and narI) was down-regulated. In addition, the inoculation of AMF regulates the synergies between the N-metabolic rhizosphere microbial communities and enhances the complexity and stability of the rhizosphere ecological network. This study provides a basis for improving plant tolerance to heavy metal stress by regulating the functional abundance of N-metabolizing plant growth-promoting bacteria through AMF inoculation. It helps to understand the potential mechanism of wetland plant remediation of Cr-contaminated soil.

Discovery and Characterization of the ddx41 Gene in Atlantic Salmon: Evolutionary Implications, Structural Functions, and Innate Immune Responses to Piscirickettsia salmonis and Renibacterium salmoninarum Infections.

The innate immune response in Salmo salar, mediated by pattern recognition receptors (PRRs), is crucial for defending against pathogens. This study examined DDX41 protein functions as a cytosolic/nuclear sensor for cyclic dinucleotides, RNA, and DNA from invasive intracellular bacteria. The investigation determined the existence, conservation, and functional expression of the ddx41 gene in S. salar. In silico predictions and experimental validations identified a single ddx41 gene on chromosome 5 in S. salar, showing 83.92% homology with its human counterpart. Transcriptomic analysis in salmon head kidney confirmed gene transcriptional integrity. Proteomic identification through mass spectrometry characterized three unique peptides with 99.99% statistical confidence. Phylogenetic analysis demonstrated significant evolutionary conservation across species. Functional gene expression analysis in SHK-1 cells infected by Piscirickettsia salmonis and Renibacterium salmoninarum indicated significant upregulation of DDX41, correlated with increased proinflammatory cytokine levels and activation of irf3 and interferon signaling pathways. In vivo studies corroborated DDX41 activation in immune responses, particularly when S. salar was challenged with P. salmonis, underscoring its potential in enhancing disease resistance. This is the first study to identify the DDX41 pathway as a key component in S. salar innate immune response to invading pathogens, establishing a basis for future research in salmonid disease resistance.

Iron-mediated DAMO-anammox process: Revealing the mechanism of electron transfer.

The nitrate denitrifying anaerobic methane oxidation-anaerobic ammonia oxidation (DAMO-anammox) can accomplish nitrogen removal and methane (CH4) reduction. This process greatly contributes to carbon emission mitigation and carbon neutrality. In this study, we investigated the electron transfer process of functional microorganisms in the iron-mediated DAMO-anammox system. Fe3+ could be bound to several functional groups (-CH3, COO-, -CH) in extracellular polymeric substance (EPS), and the functional groups bound were different at different iron concentration. Fe3+ underwent reduction reactions to produce Fe2+. Most Fe3+ and Fe2+ react with microorganisms and formed chelates with EPS. Three-dimensional fluorescence spectra showed that Fe3+ affected the secretion of tyrosine and tryptophan, which were essential for cytochrome synthesis. The presence of Fe3+ accelerated c-type cytochrome-mediated extracellular electron transfer (EET), and when more Fe3+ existed, the more cytochrome C expressed. DAMO archaea (M. nitroreducens) in the system exhibited a high positive correlation with the functional genes (resa and ccda) for cytochrome c synthesis. Some denitrifying microorganisms showed positive correlations with the abundance of riboflavin. This finding showed that riboflavin secreted by functional microorganisms acted as an electron shuttle. In addition, DAMO archaea were positively correlated with the hair synthesis gene pily1, which indicated that direct interspecies electron transfer (DIET) may exist in the iron-mediated DAMO-anammox system.

Micro-positive pressure significantly decreases greenhouse gas emissions by regulating archaeal community during industrial-scale dairy manure composting.

In this study, the effects of micro-positive pressure formed by covering with a semipermeable membrane in the heating phase of dairy manure composting on greenhouse gas emissions and the mechanism of reducing methane emissions by the archaeal community were investigated. A large-scale experiment was conducted with semipermeable membrane-covered composting (SMC), forced aeration composting (FAC), and traditional static composting (TSC) groups. The results showed that the oxygen concentration and methanogen abundance were key factors in regulating methane emissions. In the heating phase of SMC, the micro-positive pressure could enhance the O2 utilization rate and heating rate, resulting in Methanobrevibacter and Methanobacterium greatly decreasing, and the abundance of mcrA decreased by 90.03%, while that of pmoA did not increase. Compared with FAC and TSC, the cumulative methane emissions in SMC decreased by 51.75% and 96.04%, respectively. Therefore, the micro-positive pressure could effectively reduce greenhouse gas emissions by inhibiting the growth of methanogens.

Arbuscular mycorrhizal fungi offset NH3 emissions in temperate meadow soil under simulated warming and nitrogen deposition.

Most soil ammonia (NH3) emissions originate from soil nitrogen (N) that has been in the form of exchangeable ammonium. Emitted NH3 not only induces nutrient loss but also has adverse effects on the cycling of N and accelerates global warming. There is evidence that arbuscular mycorrhizal (AM) fungi can alleviate N loss by reducing N2O emissions in N-limited ecosystems, however, some studies have also found that global changes, such as warming and N deposition, can affect the growth and development of AM fungi and alter their functionality. Up to now, the impact of AM fungi on NH3 emissions, and whether global changes reduce the AM fungi's contribution to NH3 emissions reduction, has remained unclear. In this study, we examined how warming, N addition, and AM fungi alter NH3 emissions from high pH saline soils typical of a temperate meadow through a controlled microscopic experiment. The results showed that warming significantly increased soil NH3 emissions, but N addition and combined warming plus N addition had no impact. Inoculations with AM fungi strongly reduced NH3 emissions both under warming and N addition, but AM fungi effects were more pronounced under warming than following N addition. Inoculation with AM fungi reduced soil NH4+-N content and soil pH, and increased plant N content and soil net N mineralization rate while increasing the abundance of ammonia-oxidizing bacterial (AOB) gene. Structural equation modeling (SEM) shows that the regulation of NH3 emissions by AM fungi may be related to soil NH4+-N content and soil pH. These findings highlight that AM fungi can reduce N loss in the form of NH3 by increasing N turnover and uptake under global changes; thus, AM fungi play a vital role in alleviating the aggravation of N loss caused by global changes and in mitigating environmental pollution in the future.

Enhanced nitrogen removal of the anaerobic ammonia oxidation process by coupling with an efficient nitrate reducing bacterium (Bacillus velezensis M3-1).

Bacillus velezensis M3-1 strain isolated from the sediment of Myriophyllum aquatium constructed wetlands was found to efficiently convert NO3--N to NO2--N, and the requirements for carbon source addition were not very rigorous. This work demonstrates, for the first time, the feasibility of using the synergy of anammox and Bacillus velezensis M3-1 microorganisms for nitrogen removal. In this study, the possibility of M3-1 that converted NO3--N produced by anammox to NO2--N was verified in an anaerobic reactor. The NO3--N reduction ability of M3-1 and denitrifying bacteria in coupling system was investigated under different C/N conditions, and it was found that M3-1 used carbon sources preferentially over denitrifying bacteria. By adjusting the ratio of NH4+-N to NO2--N, it was found that the NO2--N converted from NO3--N by M3-1 participated in the original anammox.The nitrogen removal efficacy (NRE) of the coupled system was increased by 12.1%, compared to the control group anammox system at C/N = 2:1. Functional gene indicated that it might be a nitrate reducing bacterium.This study shows that the nitrate reduction rate achieved by the Bacillus velezensis M3-1 can be high enough for removing nitrate produced by anammox process, which would enable improve nitrogen removal from wastewater.

Roles of nanoparticles in arsenic mobility and microbial community composition in arsenic-enriched soils.

Environmental effects of nano remediation engineering of arsenic (As) pollution need to be considered. In this study, the roles of Fe2O3 and TiO2 nanoparticles (NPs) on the microbial mediated As mobilization from As contaminated soil were investigated. The addition of Fe2O3 and TiO2 NPs restrained As(V) release, and stimulated As(III) release. As(V) concentration decreased by 94% and 93% after Fe2O3 addition, and decreased by 89% and 45% after TiO2 addition compared to the Biotic and Biotic+Acetate (amended with sodium acetate) controls, respectively. The maximum values of As(III) were 20.5 and 27.1 µg/L at 48 d after Fe2O3 and TiO2 NPs addition, respectively, and were higher than that in Biotic+Acetate control (12.9 µg/L). The released As co-precipitated with Fe in soils in the presence of Fe2O3 NPs, but adsorbed on TiO2 NPs in the presence of TiO2 NPs. Moreover, the addition of NPs amended with sodium acetate as the electron donor clearly promoted As(V) reduction induced by microbes. The NPs addition changed the relative abundance of soil bacterial community, while Proteobacteria (42.8%-70.4%), Planctomycetes (2.6%-14.3%), and Firmicutes (3.5%-25.4%) were the dominant microorganisms in soils. Several potential As/Fe reducing bacteria were related to Pseudomonas, Geobacter, Desulfuromonas, and Thiobacillus. The addition of Fe2O3 and TiO2 NPs induced to the decrease of arrA gene. The results indicated that the addition of NPs had a negative impact on soil microbial population in a long term. The findings offer a relatively comprehensive assessment of Fe2O3 and TiO2 NPs effects on As mobilization and soil bacterial communities.

A multimodal deep learning model to infer cell-type-specific functional gene networks.

BACKGROUND: Functional gene networks (FGNs) capture functional relationships among genes that vary across tissues and cell types. Construction of cell-type-specific FGNs enables the understanding of cell-type-specific functional gene relationships and insights into genetic mechanisms of human diseases in disease-relevant cell types. However, most existing FGNs were developed without consideration of specific cell types within tissues. RESULTS: In this study, we created a multimodal deep learning model (MDLCN) to predict cell-type-specific FGNs in the human brain by integrating single-nuclei gene expression data with global protein interaction networks. We systematically evaluated the prediction performance of the MDLCN and showed its superior performance compared to two baseline models (boosting tree and convolutional neural network). Based on the predicted cell-type-specific FGNs, we observed that cell-type marker genes had a higher level of hubness than non-marker genes in their corresponding cell type. Furthermore, we showed that risk genes underlying autism and Alzheimer's disease were more strongly connected in disease-relevant cell types, supporting the cellular context of predicted cell-type-specific FGNs. CONCLUSIONS: Our study proposes a powerful deep learning approach (MDLCN) to predict FGNs underlying a diverse set of cell types in human brain. The MDLCN model enhances prediction accuracy of cell-type-specific FGNs compared to single modality convolutional neural network (CNN) and boosting tree models, as shown by higher areas under both receiver operating characteristic (ROC) and precision-recall curves for different levels of independent test datasets. The predicted FGNs also show evidence for the cellular context and distinct topological features (i.e. higher hubness and topological score) of cell-type marker genes. Moreover, we observed stronger modularity among disease-associated risk genes in FGNs of disease-relevant cell types. For example, the strength of connectivity among autism risk genes was stronger in neurons, but risk genes underlying Alzheimer's disease were more connected in microglia.

A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology.

Since genes do not function individually, the gene module is considered an important tool for interpreting gene expression profiles. In order to consider both functional similarity and expression similarity in module identification, GMIGAGO, a functional Gene Module Identification algorithm based on Genetic Algorithm and Gene Ontology, was proposed in this work. GMIGAGO is an overlapping gene module identification algorithm, which mainly includes two stages: In the first stage (initial identification of gene modules), Improved Partitioning Around Medoids Based on Genetic Algorithm (PAM-GA) is used for the initial clustering on gene expression profiling, and traditional gene co-expression modules can be obtained. Only similarity of expression levels is considered at this stage. In the second stage (optimization of functional similarity within gene modules), Genetic Algorithm for Functional Similarity Optimization (FSO-GA) is used to optimize gene modules based on gene ontology, and functional similarity within gene modules can be improved. Without loss of generality, we compared GMIGAGO with state-of-the-art gene module identification methods on six gene expression datasets, and GMIGAGO identified the gene modules with the highest functional similarity (much higher than state-of-the-art algorithms). GMIGAGO was applied in BRCA, THCA, HNSC, COVID-19, Stem, and Radiation datasets, and it identified some interesting modules which performed important biological functions. The hub genes in these modules could be used as potential targets for diseases or radiation protection. In summary, GMIGAGO has excellent performance in mining molecular mechanisms, and it can also identify potential biomarkers for individual precision therapy.

Differential priority effects impact taxonomy and functionality of host-associated microbiomes.

Most multicellular eukaryotes host complex communities of microorganisms, but the factors that govern their assembly are poorly understood. The settlement of specific microorganisms may have a lasting impact on community composition, a phenomenon known as the priority effect. Priority effects of individual bacterial strains on a host's microbiome are, however, rarely studied and their impact on microbiome functionality remains unknown. We experimentally tested the effect of two bacterial strains (Pseudoalteromonas tunicata D2 and Pseudovibrio sp. D323) on the assembly and succession of the microbial communities associated with the green macroalga Ulva australis. Using 16S rRNA gene sequencing and qPCR, we found that both strains exert a priority effect, with strain D2 causing initially strong but temporary taxonomic changes and strain D323 causing weaker but consistent changes. Consistent changes were predominately facilitatory and included taxa that may benefit the algal host. Metagenome analyses revealed that the strains elicited both shared (e.g., depletion of type III secretion system genes) and unique (e.g., enrichment of antibiotic resistance genes) effects on the predicted microbiome functionality. These findings indicate strong idiosyncratic effects of colonizing bacteria on the structure and function of host-associated microbial communities. Understanding the idiosyncrasies in priority effects is key for the development of novel probiotics to improve host condition.

Climate warming has direct and indirect effects on microbes associated with carbon cycling in northern lakes.

Northern lakes disproportionately influence the global carbon cycle, and may do so more in the future depending on how their microbial communities respond to climate warming. Microbial communities can change because of the direct effects of climate warming on their metabolism and the indirect effects of climate warming on groundwater connectivity from thawing of surrounding permafrost, especially at lower landscape positions. Here we used shotgun metagenomics to compare the taxonomic and functional gene composition of sediment microbes in 19 peatland lakes across a 1600-km permafrost transect in boreal western Canada. We found microbes responded differently to the loss of regional permafrost cover than to increases in local groundwater connectivity. These results suggest that both the direct and indirect effects of climate warming, which were respectively associated with loss of permafrost and subsequent changes in groundwater connectivity interact to change microbial composition and function. Archaeal methanogens and genes involved in all major methanogenesis pathways were more abundant in warmer regions with less permafrost, but higher groundwater connectivity partly offset these effects. Bacterial community composition and methanotrophy genes did not vary with regional permafrost cover, and the latter changed similarly to methanogenesis with groundwater connectivity. Finally, we found an increase in sugar utilization genes in regions with less permafrost, which may further fuel methanogenesis. These results provide the microbial mechanism for observed increases in methane emissions associated with loss of permafrost cover in this region and suggest that future emissions will primarily be controlled by archaeal methanogens over methanotrophic bacteria as northern lakes warm. Our study more generally suggests that future predictions of aquatic carbon cycling will be improved by considering how climate warming exerts both direct effects associated with regional-scale permafrost thaw and indirect effects associated with local hydrology.

Sediment microbial community structure, enzymatic activities and functional gene abundance in the coastal hypersaline habitats.

Salt marsh vegetation, mudflat and salt production are common features in worldwide coastal areas; however, their influence on microbial community composition and structure has been poorly studied and rarely compared. In the present study, microbial community composition (phospholipid fatty acid (PLFA) profiling and 16S rRNA gene sequencing (bacterial and archaeal)) and structure, enzymatic activities and abundance of functional genes in the sediments of salt ponds (crystallizer, condenser and reservoir), mudflat and vegetated mudflat were determined. Enzyme activities (ß-glucosidase, urease and alkaline phosphatase) were considerably decreased in saltpan sediments because of elevated salinity while sediment of vegetated mudflat sediments showed the highest enzyme activities. Concentrations of total microbial biomarker PLFAs (total bacterial, Gram-positive, Gram-negative, fungal and actinomycetes) were the highest in vegetated mudflat sediments and the lowest in crystallizer sediments. Nonmetric-multidimensional scaling (NMDS) analysis of PLFA data revealed that the microbial community of crystallizer, mudflat and vegetated mudflat was significantly different from each other as well as different from condenser and reservoir. The most predominant phyla within the classified bacterial fractions were Proteobacteria followed by Firmicutes, Bacteroidetes and Planctomycetes, while Euryarchaeota and Crenarchaeota phyla dominated the classified archaeal fraction. Cyanobacterial genotypes were the most dominant in the condenser. Mudflat and vegetated mudflat supported a greater abundance of Bacteroidetes and Actinobacteria, respectively. The results of the present study suggest that salt ponds had significantly decreased the microbial and enzyme activities in comparison to mudflat and vegetated mudflat sediments due to very high salinity, ionic concentrations and devoid of vegetation. The present study expands our understanding of microbial resource utilization and adaptations of microorganisms in a hypersaline environment.

Mediative Mechanism of Freezing/Thawing on Greenhouse Gas Emissions in an Inland Saline-Alkaline Wetland: a Metagenomic Analysis.

Inland saline-alkaline wetlands distributed in the mid-high latitude have repeatedly experienced freezing and thawing. However, the response of greenhouse gas (GHG) emission and microbially-mediated carbon and nitrogen cycle to freezing and thawing remains unclear. We monitored the GHG flux in an inland saline-alkaline wetland and found that, compared with the growth period, the average CO2 flux decreased from 171.99 to 76.61-80.71 mg/(m2‧h), the average CH4 flux decreased from 10.72 to 1.96-3.94 mg/(m2‧h), and the average N2O flux decreased from 56.17 to - 27.14 to - 20.70 µg/(m2‧h). Freezing and thawing significantly decreased the relative abundance of functional genes involved in carbon and nitrogen cycles. The aceticlastic methanogenic pathway was the main methanogenic pathway, whereas the Candidatus Methylomirabilis oxyfera was the most abundant methane oxidizer in the wetland. Ammonia-oxidizing archaea and denitrifier belonging to proteobacteria was the major microbial N2O source, while bacteria within clade II nosZ was the major microbial N2O sink. Freezing and thawing reduced the relative abundance of these genes, leading to a decrease in GHG flux.