Maternal Di-(2-ethylhexyl)-Phthalate exposure during pregnancy altered energy metabolism in immature offspring and caused hyperglycemia.

Di-(2-ethylhexyl)-phthalate (DEHP), as distinctive endocrine disrupting chemicals, has become a global environmental pollutant harmful to human and animal health. However, the impacts on offspring and mothers with maternal DEHP exposure are largely unknown and the mechanism remains elusive. We established DEHP-exposed maternal mice to investigate the impacts on mother and offspring and illustrate the mechanism from multiple perspectives. Pregnant mice were administered with different doses of DEHP, respectively. Metagenomic sequencing used fecal and transcriptome sequencing using placentas and livers from offspring have been performed, respectively. The results of the histopathology perspective demonstrated that DEHP exposure could disrupt the function of islets impact placentas and fetus development for maternal mice, and cause the disorder of glucose and lipid metabolism for immature offspring mice, resulting in hyperglycemia. The results of the metagenome of gut microbial communities indicated that the dysbiosis of gut microbiota in mother and offspring mice and the dominant phyla transformed through vertical transmission. Transcriptome analysis found DEHP exposure induced mutations of Ahcy and Gstp3, which can damage liver cells and affect the metabolism of the host. DEHP exposure harms pregnant mice and offspring by affecting gene expression and altering metabolism. Our results suggested that exposure of pregnant mice to DEHP during pregnancy and lactation increased the risk of metabolic disorders by altering key genes in liver and gut microbiota, and these results provided new insights into the potential long-term harms of DEHP.

TLR4 TIR domain and nucleolin GAR domain synergistically mediate RSV infection and induce neuronal inflammatory damage in SH-SY5Y cells.

Previous research results of our group showed that Toll-like receptor 4 (TLR4) and nucleolin synergistically mediate respiratory syncytial virus (RSV) infection in human central neuron cells, but the specific mechanism remains unclear. Here we designed and synthesized lentiviruses with TIR (674-815 aa), TLR4 (del 674-815 aa), GAR (645-707 aa), and NCL (del 645-707 aa) domains, and obtained stable overexpression cell lines by drug screening, and subsequently infected RSV at different time points. Laser confocal microscopy and coimmunoprecipitation were used for the observation of co-localization and interaction of TIR/GAR domains. Western blot analysis was used for the detection of p-NF-κB and LC3 protein expression. Real-time PCR was used for the detection of TLR4/NCL mRNA expression. ELISA assay was used to measure IL-6, IL-1ß, and TNF-α concentrations and flow cytometric analysis was used for the study of apoptosis. Our results suggest that overexpression of TIR and GAR domains can exacerbate apoptosis and autophagy, and that TIR and GAR domains can synergistically mediate RSV infection and activate the NF-κB signaling pathway, which regulates the secretion of downstream inflammatory factors, such as IL-6, IL-1ß, and TNF-α, and ultimately leads to neuronal inflammatory injury.

Melatonin suppresses TLR4-mediated RSV infection in the central nervous cells by inhibiting NLRP3 inflammasome formation and autophagy.

Respiratory syncytial virus (RSV) infects neuronal cells in the central nervous system (CNS), resulting in neurological symptoms. In the present study, we intended to explore the mechanism of RSV infection-induced neuroinflammatory injury from the perspective of the immune response and sought to identify effective protective measures against the injury. The findings showed that toll-like receptor 4 (TLR4) was activated after RSV infection in human neuronal SY5Y cells. Furthermore, TLR4 activation induced autophagy and apoptosis in neuronal cells, promoted the formation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, and increased the secretion of downstream inflammatory cytokines such as interleukin-1ß (IL-1ß), interleukin-18 (IL-18) and tumour necrosis factor-α (TNF-α). Interestingly, blockade of TLR4 or treatment with exogenous melatonin significantly suppressed TLR4 activation as well as TLR4-mediated apoptosis, autophagy and immune responses. Therefore, we infer that melatonin may act on the TLR4 to ameliorate RSV-induced neuronal injury, which provides a new therapeutic target for RSV infection.

Performance and mechanism of SMX removal by an electrolysis-integrated ecological floating bed at low temperatures: A new perspective of plant activity, iron plaque, and microbial functions.

Improvements in plant activity and functional microbial communities are important to ensure the stability and efficiency of pollutant removal measures in cold regions. Although electrochemistry is known to accelerate pollutant degradation, cold stress acclimation of plants and the stability and activity of plant-microbial synergism remain poorly understood. The sulfamethoxazole (SMX) removal, iron plaque morphology, plant activity, microbial community, and function responses were investigated in an electrolysis-integrated ecological floating bed (EFB) at 6 ± 2 â„ƒ. Electrochemistry significantly improved SMX removal and plant activity. Dense and uniform iron plaque was found on root surfaces in L-E-Fe which improved the plant adaptability at low temperatures and provided more adsorption sites for bacteria. The microbial community structure was optimized and the key functional bacteria for SMX degradation (e.g., Actinobacteriota, Pseudomonas) were enriched. Electrochemistry improves the relative abundance of enzymes related to energy metabolism, thereby increasing energy responses to SMX and low temperatures. Notably, electrochemistry improved the expression of target genes (sadB and sadC, especially sadC) involved in SMX degradation. Electrochemistry enhances hydrogen bonding and electrostatic interactions between SMX and sadC, thereby enhancing SMX degradation and transformation. This study provides a deeper understanding of the electrochemical stability of antibiotic degradation at low temperatures.

NCRD: A non-redundant comprehensive database for detecting antibiotic resistance genes.

Antibiotic resistance genes (ARGs) are emerging pollutants present in various environments. Identifying ARGs has become a growing concern in recent years. Several databases, including the Antibiotic Resistance Genes Database (ARDB), Comprehensive Antibiotic Resistance Database (CARD), and Structured Antibiotic Resistance Genes (SARG), have been applied to detect ARGs. However, these databases have limitations, which hinder the comprehensive profiling of ARGs in environmental samples. To address these issues, we constructed a non-redundant antibiotic resistance genes database (NRD) by consolidating sequences from ARDB, CARD, and SARG. We identified the homologous proteins of NRD from Non-redundant Protein Database (NR) and the Protein DataBank Database (PDB) and clustered them to establish a non-redundant comprehensive antibiotic resistance genes database (NCRD) with similarities of 100% (NCRD100) and 95% (NCRD95). To demonstrate the advantages of NCRD, we compared it with other databases by using metagenome datasets. Results revealed its strong ability in detecting potential ARGs.

Roles of osteoprotegerin in endocrine and metabolic disorders through receptor activator of nuclear factor kappa-B ligand/receptor activator of nuclear factor kappa-B signaling.

Endocrine and metabolic diseases show increasing incidence and high treatment costs worldwide. Due to the complexity of their etiology and mechanism, therapeutic strategies are still lacking. Osteoprotegerin (OPG), a member of the tumor necrosis factor receptor superfamily, appears to be a potential candidate for the treatment of these diseases. Studies based on clinical analysis and rodent animal models reveal the roles of OPG in various endocrine and metabolic processes or disorders, such as bone remodeling, vascular calcification, and ß-cell proliferation, through the receptor activator of nuclear factor kappa-B ligand (RANKL) and the receptor activator of NF-κB (RANK). Thus, in this review, we mainly focus on relevant diseases, including osteoporosis, cardiovascular disease (CVD), diabetes, and gestational diabetes mellitus (GDM), to summarize the effects of the RANKL/RANK/OPG system in endocrine and metabolic tissues and diseases, thereby providing a comprehensive insight into OPG as a potential drug for endocrine and metabolic diseases.

Metabolomics-based investigation of SARS-CoV-2 vaccination (Sinovac) reveals an immune-dependent metabolite biomarker.

SARS-CoV-2 and its mutant strains continue to rapidly spread with high infection and fatality. Large-scale SARS-CoV-2 vaccination provides an important guarantee for effective resistance to existing or mutated SARS-CoV-2 virus infection. However, whether the host metabolite levels respond to SARS-CoV-2 vaccine-influenced host immunity remains unclear. To help delineate the serum metabolome profile of SARS-CoV-2 vaccinated volunteers and determine that the metabolites tightly respond to host immune antibodies and cytokines, in this study, a total of 59 sera samples were collected from 30 individuals before SARS-CoV-2 vaccination and from 29 COVID-19 vaccines 2 weeks after the two-dose vaccination. Next, untargeted metabolomics was performed and a distinct metabolic composition was revealed between the pre-vaccination (VB) group and two-dose vaccination (SV) group by partial least squares-discriminant and principal component analyses. Based on the criteria: FDR < 0.05, absolute log2 fold change greater than 0.25, and VIP >1, we found that L-glutamic acid, gamma-aminobutyric acid (GABA), succinic acid, and taurine showed increasing trends from SV to VB. Furthermore, SV-associated metabolites were mainly annotated to butanoate metabolism and glutamate metabolism pathways. Moreover, two metabolite biomarkers classified SV from VB individuals with an area under the curve (AUC) of 0.96. Correlation analysis identified a positive association between four metabolites enriched in glutamate metabolism and serum antibodies in relation to IgG, IgM, and IgA. These results suggest that the contents of gamma-aminobutyric acid and indole in serum could be applied as biomarkers in distinguishing vaccinated volunteers from the unvaccinated. What's more, metabolites such as GABA and taurine may serve as a metabolic target for adjuvant vaccines to boost the ability of the individuals to improve immunity.

The Potential of Gut Microbiota Metabolic Capability to Detect Drug Response in Rheumatoid Arthritis Patients.

Gut microbiota plays an essential role in the development of rheumatoid arthritis (RA) and affects drug responses. However, the underlying mechanism remains elusive and urgent to elucidate to explore the pathology and clinical treatment of RA. Therefore, we selected methotrexate (MTX) as an example of RA drugs to explore the interactions between the gut microbiota and drug responses and obtain an in-depth understanding of their correlation from the perspective of the metabolic capability of gut microbiota on drug metabolism. We identified 2,654 proteins and the corresponding genes involved in MTX metabolism and then profiled their abundances in the gut microbiome datasets of four cohorts. We found that the gut microbiota harbored various genes involved in MTX metabolism in healthy individuals and RA patients. Interestingly, the number of genes involved in MTX metabolism was not significantly different between response (R) and non-response (NR) groups to MTX, but the gene composition in the microbial communities significantly differed between these two groups. Particularly, several models were built based on clinical information, as well as data on the gene, taxonomical, and functional biomarkers by using the random forest algorithm and then validated. Our findings provide bases for clinical management not only of RA but also other gut microbiome-related diseases. First, it suggests that the potential metabolic capability of gut microbiota on drug metabolism is important because they affect drug efficiency; as such, clinical treatment strategies should incorporate the gene compositions of gut microbial communities, in particular genes involved in drug metabolism. Second, a suitable model can be developed to determine hosts' responses to drugs before clinical treatment.

Characterization of Altered Oropharyngeal Microbiota in Hospitalized Patients With Mild SARS-CoV-2 Infection.

Coronavirus disease 2019 (COVID-19) remains a serious emerging global health problem, and little is known about the role of oropharynx commensal microbes in infection susceptibility and severity. Here, we present the oropharyngeal microbiota characteristics identified by full-length 16S rRNA gene sequencing through the NANOPORE platform of oropharynx swab specimens from 10 mild COVID-19 patients and 10 healthy controls. Our results revealed a distinct oropharyngeal microbiota composition in mild COVID-19 patients, characterized by enrichment of opportunistic pathogens such as Peptostreptococcus anaerobius and Pseudomonas stutzeri and depletion of Sphingomonas yabuuchiae, Agrobacterium sullae, and Pseudomonas veronii. Based on the relative abundance of the oropharyngeal microbiota at the species level, we built a microbial classifier to distinguish COVID-19 patients from healthy controls, in which P. veronii, Pseudomonas fragi, and S. yabuuchiae were identified as the most prominent signatures for their depletion in the COVID-19 group. Several members of the genus Campylobacter, especially Campylobacter fetus and Campylobacter rectus, which were highly enriched in COVID-19 patients with higher severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and showed a significant correlation with disease status and several routine clinical blood indicators, indicate that several bacteria may transform into opportunistic pathogen in COVID-19 patients when facing the challenges of viral infection. We also found the diver taxa Streptococcus anginosus and Streptococcus alactolyticus in the network of disease patients, suggesting that these oropharynx microbiota alterations may impact COVID-19 severity by influencing the microbial association patterns. In conclusion, the low sample size of SARS-CoV-2 infection patients (n = 10) here makes these results tentative; however, we have provided the overall characterization that oropharyngeal microbiota alterations and microbial correlation patterns were associated with COVID-19 severity in Anhui Province.

Decoding herbal materials of TCM preparations with the multi-barcode sequencing approach.

With the rapid development of high-throughput sequencing technology, approaches for assessing biological ingredients in Traditional Chinese Medicine (TCM) preparations have also advanced. Using a multi-barcode sequencing approach, all biological ingredients could be identified from TCM preparations in theory, as long as their DNA is present. The biological ingredients of several classical TCM preparations were analyzed successfully based on this approach in previous studies. However, the universality, sensitivity and reliability of this approach on a diverse set of TCM preparations remain unclear. In this study, we selected four representative TCM preparations, namely Bazhen Yimu Wan, Da Huoluo Wan, Niuhuang Jiangya Wan, and You Gui Wan, for concrete assessment of the multi-barcode sequencing approach. Based on ITS2 and trnL biomarkers, we have successfully detected the prescribed herbal materials (PHMs) in these representative TCM preparations (minimum sensitivity: 77.8%, maximum sensitivity: 100%). The results based on ITS2 have also shown higher reliability than trnL at species level, while their combination could provide higher sensitivity and reliability. The multi-barcode sequencing approach has shown good universality, sensitivity and reliability in decoding these four representative TCM preparations. In the omics big-data era, this work has undoubtedly made one step forward for applying multi-barcode sequencing approach in PHMs analysis of TCM preparation, towards better digitization and modernization of drug quality control.

Microbiome Resilience and Health Implications for People in Half-Year Travel.

Travel entail change in geography and diet, both of which are known as determinant factors in shaping the human gut microbiome. Additionally, altered gut microbiome modulates immunity, bringing about health implications in humans. To explore the effects of the mid-term travel on the gut microbiome, we generated 16S rRNA gene and metagenomic sequencing data from longitudinal samples collected over six months. We monitored dynamic trajectories of the gut microbiome variation of a Chinese volunteer team (VT) in their whole journey to Trinidad and Tobago (TAT). We found gut microbiome resilience that VT's gut microbial compositions gradually transformed to the local TAT's enterotypes during their six-month stay in TAT, and then reverted to their original enterotypes after VT's return to Beijing in one month. Moreover, we identified driven species in this bi-directional plasticity that could play a role in immunity modulation, as exemplified by Bacteroides dorei that attenuated atherosclerotic lesion formation and effectively suppressed proinflammatory immune response. Another driven species P. copri could play a crucial role in rheumatoid arthritis pathogenesis, a chronic autoimmune disease. Carbohydrate-active enzymes are often implicated in immune and host-pathogen interactions, of which glycoside hydrolases were found decreased but glycosyltransferases and carbohydrate esterases increased during the travel; these functions were then restored after VT' returning to Beijing. Furthermore, we discovered these microbial changes and restoration were mediated by VT people's dietary changes. These findings indicate that half-year travel leads to change in enterotype and functional patterns, exerting effects on human health. Microbial intervention by dietary guidance in half-year travel would be conducive to immunity modulation for maintaining health.

Analysis of antibiotic resistance genes reveals their important roles in influencing the community structure of ocean microbiome.

Antibiotic resistance gene (ARG) content is a well-established driver of microbial abundance and diversity in an environment. By reanalyzing 132 metagenomic datasets from the Tara Oceans project, we aim to unveil the associations between environmental factors, the ocean microbial community structure and ARG contents. We first investigated the structural patterns of microbial communities including both prokaryotes such as bacteria and eukaryotes such as protists. Additionally, several ARG-dominant horizontal gene transfer events between Protist and Prokaryote have been identified, indicating the potential roles of ARG in shaping the ocean microbial communities. For a deeper insight into the role of ARGs in ocean microbial communities on a global scale, we identified 1926 unique types of ARGs and discovered that the ARGs are more abundant and diverse in the mesopelagic zone than other water layers, potentially caused by limited resources. Finally, we found that ARG-enriched genera were often more abundant compared to their ARG-less neighbors in the same environment (e.g. coastal oceans). A deeper understanding of the ARG-microbiome relationships could help in the conservation of the oceanic ecosystem.

Is rice-crayfish co-culture a better aquaculture model: From the perspective of antibiotic resistome profiles.

Aquaculture ecosystem is a hot-spot for antibiotic resistance genes (ARGs). Rice-crayfish co-culture was considered an eco-friendly aquaculture model and has been widely adopted in China. However, it is unclear whether rice-crayfish co-culture is one of the most eco-friendly models from the perspective of antibiotic resistance profiles. In this study, we evaluated the eco-friendliness of rice-crayfish co-culture, and compared this model with other aquaculture models, from the perspectives of antibiotics and ARG patterns, based on multi-omics and antibiotic profiles. Results showed that the nutrient levels, antibiotic concentrations, dominant microbial genera and ARG patterns in the rice-crayfish co-culture model were profoundly different from the other three aquaculture models (crab only aquaculture model, crayfish only aquaculture model, and crab-crayfish co-culture models). Specifically, the rice-crayfish co-culture model has significantly lower diversity of ARGs and lower potential risks of ARGs when compared to the other aquaculture models. Nutrient and antibiotic concentrations were the important environmental factors for shaping ARG patterns, but compared with environmental factors, the effects of mobile genes and bacteria community on the proliferation and transmission of ARGs were stronger. This study has deepened our understanding of ARGs in freshwater aquaculture ecosystem, and suggested that rice-crayfish co-culture model is a relatively eco-friendly aquaculture model when compared with the other aquaculture models.

Antibiotic resistome in a large urban-lake drinking water source in middle China: Dissemination mechanisms and risk assessment.

The increasing pollution of urban drinking water sources by antibiotic resistance genes (ARGs) threatens human health worldwide. However, the distribution and influencing factors of ARGs, especially how to reveal the risks of ARGs in this environment remains unclear. Hence, Chaohu Lake was selected as an example to investigate the characteristics of ARGs and explore the interactions among physicochemical factors, microorganisms, and ARGs by metagenomic approach. In this work, 75 ARG subtypes with an average of 30.4 × /Gb (ranging from 15.2 ×/Gb to 57.9 ×/Gb) were identified, and multidrug and bacA were most frequent in Chaohu Lake. Non-random co-occurrence patterns and potential host bacteria of ARGs were revealed through co-occurrence networks. Microbial community and mobile genetic elements (MGEs) were the major direct factors in ARG profiles. The dissemination of ARGs was mainly driven by plasmids. Considering the interactions among MGEs, human bacterial pathogens, and ARGs, antibiotic resistome risk index (ARRI) was proposed to manifest the risks of ARGs. Overall, our work systemically investigated the composition and associated factors of ARGs and built ARRI to estimate the potential risks of ARGs in a typical urban drinking water source, providing an intuitive indicator for managing similar lakes.

Comprehensive analysis of 84 Faecalibacterium prausnitzii strains uncovers their genetic diversity, functional characteristics, and potential risks.

Faecalibacterium prausnitzii is a beneficial human gut microbe and a candidate for next-generation probiotics. With probiotics now being used in clinical treatments, concerns about their safety and side effects need to be considered. Therefore, it is essential to obtain a comprehensive understanding of the genetic diversity, functional characteristics, and potential risks of different F. prausnitzii strains. In this study, we collected the genetic information of 84 F . prausnitzii strains to conduct a pan-genome analysis with multiple perspectives. Based on single-copy genes and the sequences of 16S rRNA and the compositions of the pan-genome, different phylogenetic analyses of F. prausnitzii strains were performed, which showed the genetic diversity among them. Among the proteins of the pan-genome, we found that the accessory clusters made a greater contribution to the primary genetic functions of F. prausnitzii strains than the core and specific clusters. The functional annotations of F. prausnitzii showed that only a very small number of proteins were related to human diseases and there were no secondary metabolic gene clusters encoding harmful products. At the same time, complete fatty acid metabolism was detected in F. prausnitzii. In addition, we detected harmful elements, including antibiotic resistance genes, virulence factors, and pathogenic genes, and proposed the probiotic potential risk index (PPRI) and probiotic potential risk score (PPRS) to classify these 84 strains into low-, medium-, and high-risk groups. Finally, 15 strains were identified as low-risk strains and prioritized for clinical application. Undoubtedly, our results provide a comprehensive understanding and insight into F. prausnitzii, and PPRI and PPRS can be applied to evaluate the potential risks of probiotics in general and to guide the application of probiotics in clinical application.

Profiles of antibiotic resistance genes in an inland salt-lake Ebinur Lake, Xinjiang, China: The relationship with antibiotics, environmental factors, and microbial communities.

Lakes in arid northwestern China, as the main pollutant-holding water bodies in the typical ecologically fragile areas, are facing the unknown risk of exposure to antibiotics and antibiotic resistance genes (ARGs). In this study, five ARGs and one mobile genetic element (intI1) and their relation with antibiotics, microbial communities and water quality were investigated in Ebinur Lake Basin, a typical salt-lake of China. Quantitative PCR analysis indicated that ARGs decreasing order in both surface water and sediment was sul1 >sul2 >tetW>ermB>qnrS, which means sulfonamide resistance genes were the main pollution ARGs. Macrolide antibiotics were the predominant antibiotics in the surface water and sediment in winter, while sulfonamides and quinolones accounted for a high proportion in summer. There was a non-corresponding relationship between ARGs and antibiotics. Moreover, the relationship between ARGs and microbial communities were defined. Sulfonamide resistance genes were carried by a greater diversity of potential host bacteria (76 genera) than other ARGs (9 genera). And their positive correlation with intI1 (p < 0.05) which promotes their migration and provides possibility of their co-occurrence in bacterial populations (e.g., Nitrospira). Bacterial genera were the main driver of ARGs distribution pattern in highly saline lake sediment. Environmental factors like salinity, total nitrogen and organic matter could have a certain influence on the occurrence of ARGs by affecting microorganisms. The results systematically show the distribution and propagation characteristics of ARGs in typical inland salt-lakes in China, and preliminarily explored the relationship between ARGs and antibiotics, resistance genes and microorganisms in lakes in ecologically fragile areas.

Association of Gut Microbiota during Early Pregnancy with Risk of Incident Gestational Diabetes Mellitus.

AIMS: We aimed to assess the association between gut bacterial biomarkers during early pregnancy and subsequent risk of gestational diabetes mellitus (GDM) in Chinese pregnant women. METHODS: Within the Tongji-Shuangliu Birth Cohort study, we conducted a nested case-control study among 201 incident GDM cases and 201 matched controls. Fecal samples were collected during early pregnancy (at 6-15 weeks), and GDM was diagnosed at 24 to 28 weeks of pregnancy. Community DNA isolated from fecal samples and V3-V4 region of 16S rRNA gene amplicon libraries were sequenced. RESULTS: In GDM cases versus controls, Rothia, Actinomyces, Bifidobacterium, Adlercreutzia, and Coriobacteriaceae and Lachnospiraceae spp. were significantly reduced, while Enterobacteriaceae, Ruminococcaceae spp., and Veillonellaceae were overrepresented. In addition, the abundance of Staphylococcus relative to Clostridium, Roseburia, and Coriobacteriaceae as reference microorganisms were positively correlated with fasting blood glucose, 1-hour and 2-hour postprandial glucose levels. Adding microbial taxa to the base GDM prediction model with conventional risk factors increased the C-statistic significantly (P < 0.001) from 0.69 to 0.75. CONCLUSIONS: Gut microbiota during early pregnancy was associated with subsequent risk of GDM. Several beneficial and commensal gut microorganisms showed inverse relations with incident GDM, while opportunistic pathogenic members were related to higher risk of incident GDM and positively correlated with glucose levels on OGTT.

Mechanisms of niche-neutrality balancing can drive the assembling of microbial community.

One hotspot of present community ecology is to uncover the mechanisms of community succession. In this study, two popular concepts, niche-neutrality dynamic balancing and co-occurrence network analysis, were integrated to investigate the dispersal dynamics of microbial communities in a freshwater river continuum in subtropical China. Results showed that when habitat conditions were mild and appropriate, such as in the clean upstream river, free of heavy pollution or long-lasting extreme disturbances, stochastic processes could increase species diversities, and organize communities into relatively loosely linked and stable networks with higher modularity and more modules. However, when conditions became degraded under heavy pollution, the influence of neutrality diminished, and niche-based selection imposed more constraints on communities and guided the assembling processes in certain directions: depleting species richness, strengthening interspecies connections and breaking boundaries of modules. Consequently, communities became more sensitive to fluctuations so as to deal with the harsh conditions efficiently. Another interesting finding was that, both as keystone taxa of communities, module hubs were mostly neutrally distributed generalists with high abundances, and were beneficial to many related operational taxonomic units. In contrast, connectors were less abundant and their distributions were more subjected to the environments. Therefore, connectors were probably responsible for the information transmission between microbial communities and environments, as well as between different modules, and thus could restrict the dispersal of microbes and guide the direction of community assembly.

Comparison and interpretation of characteristics of Rhizosphere microbiomes of three blueberry varieties.

BACKGROUND: Studies on the rhizosphere microbiome of various plants proved that rhizosphere microbiota carries out various vital functions and can regulate the growth and improve the yield of plants. However, the rhizosphere microbiome of commercial blueberry was only reported by a few studies and remains elusive. Comparison and interpretation of the characteristics of the rhizosphere microbiome of blueberry are critical important to maintain its health. RESULTS: In this study, a total of 20 rhizosphere soil samples, including 15 rhizosphere soil samples from three different blueberry varieties and five bulk soil samples, were sequenced with a high-throughput sequencing strategy. Based on these sequencing datasets, we profiled the taxonomical, functional, and phenotypic compositions of rhizosphere microbial communities for three different blueberry varieties and compared our results with a previous study focused on the rhizosphere microbiome of blueberry varieties. Our results demonstrated significant differences in alpha diversity and beta diversity of rhizosphere microbial communities of different blueberry varieties and bulk soil. The distribution patterns of taxonomical, functional, and phenotypic compositions of rhizosphere microbiome differ across the blueberry varieties. The rhizosphere microbial communities of three different blueberry varieties could be distinctly separated, and 28 discriminative biomarkers were selected to distinguish these three blueberry varieties. Core rhizosphere microbiota for blueberry was identified, and it contained 201 OTUs, which were mainly affiliated with Proteobacteria, Actinobacteria, and Acidobacteria. Moreover, the interactions between OTUs of blueberry rhizosphere microbial communities were explored by a co-occurrence network of OTUs from an ecological perspective. CONCLUSIONS: This pilot study explored the characteristics of blueberry's rhizosphere microbial community, such as the beneficial microorganisms and core microbiome, and provided an integrative perspective on blueberry's rhizosphere microbiome, which beneficial to blueberry health and production.