Microbial Interaction Networks Research Articles

Long-term cultivation reduces soil carbon storage by altering microbial network complexity and metabolism activity in macroaggregates

Cultivation alters soil aggregation, microbial compositions and the potential for carbon sequestration in cropland soils. However, the specific effects of long-term cultivation and the underlying mechanisms on soil organic carbon (SOC) storage at different aggregate sizes remain poorly understood. We characterized the dynamics of SOC storage in macroaggregates (>0.25 mm) and microaggregates (<0.25 mm) across four paddy soils successively cultivated for 60, 100, 125, and 150 years. Microbial community compositions, network patterns, enzyme activities and carbon use efficiency (CUE) were examined to elucidate the underlying microbial pathways governing SOC storage. The results showed that prolonged cultivation led to an average reduction of 45 % in SOC storage, particularly in macroaggregates. Partial least squares path modeling revealed that shifts in microorganisms in macroaggregates explained almost 80 % of the variation in SOC storage. Specifically, variations in fungal composition and decreased complexity of microbial interaction networks were strongly correlated with SOC storage. Fungal community and microbial interactions also indirectly affected SOC storage by positively correlating with extracellular enzyme activity. Moreover, bacterial composition indirectly regulated SOC storage by positively correlating with carbon use efficiency. Our findings indicated that the macroaggregate-associated microbial interactions and the metabolism activities had significant implications for SOC sequestration in paddy fields. We suggest that implementation of management practices targeted at improvement of these microbial attributes could enhance agroecosystems sustainability.

Metagenomic evidence for antibiotic-associated actinomycetes in the Karamay Gobi region.

Due to the misuse of antibiotics, there is an increasing emergence and spread of multidrug-resistant (MDR) bacteria, leading to a human health crisis. To address clinical antibiotic resistance and prevent/control pathogenic microorganisms, the development of novel antibiotics is essential. This also offers a new approach to discovering valuable actinobacterial flora capable of producing natural bioactive products. In this study, we employed bioinformatics and macro-genome sequencing to collect 15 soil samples from three different locations in the Karamay Gobi region. First, we assessed the diversity of microorganisms in soil samples from different locations, analyzing the content of bacteria, archaea, actinomycetes, and fungi. The biodiversity of soil samples from outside the Gobi was found to be higher than that of soil samples from within and in the center of the Gobi. Second, through microbial interaction network analysis, we identified actinomycetes as the dominant group in the system. We have identified the top four antibiotic genes, such as Ecol_fabG_TRC, Efac_liaR_DAP, tetA (58), and macB, by CARD. These genes are associated with peptide antibiotics, disinfecting agents and antiseptics, tetracycline antibiotics, and macrolide antibiotics. In addition, we also obtained 40 other antibiotic-related genes through CARD alignment. Through in-depth analysis of desert soil samples, we identified several unstudied microbial species belonging to different families, including Erythrobacteriaceae, Solirubrobacterales, Thermoleophilaceae, Gaiellaceae, Nocardioidaceae, Actinomycetia, Egibacteraceae, and Acidimicrobiales. These species have the capability to produce peptide antibiotics, macrolide antibiotics, and tetracycline antibiotics, as well as disinfectants and preservatives. This study provides valuable theoretical support for future in-depth research.

Microbiome abundance patterns as attractors and the implications for the inference of microbial interaction networks

Inferring microbial interaction networks from abundance patterns is an important approach to advance our understanding of microbial communities in general and the human microbiome in particular. Here we suggest discriminating two levels of information contained in microbial abundance data: (1) the quantitative abundance values and (2) the pattern of presences and absences of microbial organisms. The latter allows for a binary view on microbiome data and a novel interpretation of microbial data as attractors, or more precisely as fixed points, of a Boolean network.Starting from these attractors, our aim is to infer an interaction network between the species present in the microbiome samples. To accomplish this task, we introduce a novel inference method that combines the previously published ESABO (Entropy Shifts of Abundance vectors under Boolean Operations) method with an evolutionary algorithm. The key idea of our approach is that the inferred network should reproduce the original set of (observed) binary abundance patterns as attractors.We study the accuracy and runtime properties of this evolutionary method, as well as its behavior under incomplete knowledge of the attractor sets. Based on this theoretical understanding of the method we then show an application to empirical data.

Succession of the oral microbiome with the increasing severity of periodontitis

AbstractPeriodontitis development is strongly associated with the succession of the oral microbiome. However, the knowledge about the succession of the oral microbiome in the development of periodontitis remains insufficient. In the present study, an analysis was conducted on the succession of tongue back, the saliva (Sal) microbiome, and gingival crevicular fluid (GCF) from healthy individuals and patients with mild (CPL), moderate (CPM), severe chronic (CPH), and generalized aggressive periodontitis (GAgP). The composition and structure of the oral microbiome gradually changed with the increasing severity of periodontitis, among which GCF showed the highest correlation with periodontitis. With an ecological preference, pathogens in the mouth varied with the development of periodontitis. In healthy and CPL patients, Sal‐derived microorganisms accounted for a large proportion of GCF but exhibited a decrease in patients with CPM, CPH, and GAgP. Permutation and time course sequencing analysis revealed that a variety of microorganisms changed with the severity of periodontitis. A majority of these microorganisms are closely related to clinical periodontal indices. Ecological analysis suggested that the composition of oral microbial communities at different stages of periodontitis is controlled by random processes. The comparison of microbial interaction networks demonstrated that a series of key microorganisms drive oral health to severe periodontitis. In this study, the relationship between the succession process of the oral microbiota and the development of periodontitis was revealed.

Changes in microbial composition and interaction patterns of female urogenital tract and rectum in response to HPV infection

BackgroundPrevious studies have shown that changes in the microbial community of the female urogenital tract are associated with Human papillomavirus (HPV) infection. However, research on this association was mostly focused on a single site, and there are currently few joint studies on HPV infection and multiple sites in the female urogenital tract.MethodsWe selected 102 healthy women from Yunnan Province as the research object, collected cervical exfoliation fluid, vaginal, urethral, and rectal swabs for microbial community analysis, and measured bacterial load, and related cytokine content. The link between HPV, microbiota, and inflammation was comprehensively evaluated using bioinformatics methods.FindingsThe impact of HPV infection on the microbial composition of different parts varies. We have identified several signature bacterial genera that respond to HPV infection in several detection sites, such as Corynebacterium, Lactobacillus, Campylobacter, and Cutibacterium have been detected in multiple sites, reflecting their potential significance in cross body sites HPV infection responses. There was a solid microbial interaction network between the cervix, vagina, and urethra. The interrelationships between inflammatory factors and different bacterial genera might also affect the immune system's response to HPV infection.InterpretationIt might be an effective strategy to prevent and treat HPV infection by simultaneously understanding the correlation between the microbial changes in multiple parts of the female urogenital tract and rectum and HPV infection, and controlling the microbial network related to HPV infection in different parts.

Evolutionary radiation and microbial community dynamics shape the thermal tolerance of Fungiidae in the southern South China Sea.

Fungiidae have shown increased thermal adaptability in coral reef ecosystems under global warming. This study analyzes the evolutionary divergence and microbial communities of Fungiidae in the Sanjiao Reef of the southern South China Sea and explores the impact of coral evolution radiation and microbial dynamics on the heat tolerance of Fungiidae. The results found that Cycloseris was an ancient branch of Fungiidae, dating back approximately 147.8953 Mya, and Fungiidae differentiated into two ancestral clades (clades I and II) before 107.0312 Ma. Fungiidae exhibited specific symbioses with the Cladocopium C27 sub-clade. Notably, the Cladocopium C1 sub-clade has a high relative abundance in clade I, whereas the heat-tolerant Cladocopium C40 and C3u sub-clades subdominante in clade II. Regarding bacterial communities, Cycloseris costulata, the earliest divergent species, had higher bacterial β-diversity, while the latest divergent species, Lithophyllon scabra, displayed lower bacterial α-diversity and higher community stability. Beneficial bacteria dominante Fungiidae's bacterial community (54%). The co-occurrence network revealed that microbial networks in clade II exhibited lower complexity and greater resilience than those in clade I. Our study highlights that host evolutionary radiation and microbial communities shaped Fungiidae's thermal tolerance. The variability in subdominant Symbiodiniaceae populations may contribute to interspecific differences in thermal tolerance along the evolutionary branches of Fungiidae. The presence of abundant beneficial bacteria may further enhance the thermal ability of the Fungiidae. Furthermore, the later divergent species of Fungiidae have stronger heat tolerance, possibly driven by the increased regulation ability of the host on the bacterial community, greater microbial community stability, and interaction network resistance.IMPORTANCECoral reefs are facing significant threats due to global warming. The heat tolerance of coral holobionts depends on both the coral host and its microbiome. However, the association between coral evolutionary radiation and interspecific differences in microbial communities remains unclear. In this study, we investigated the role of evolutionary radiation and microbial community dynamics in shaping the thermal acclimation potential of Fungiidae in the Sanjiao Reef of the southern South China Sea. The study's results suggest that evolutionary radiation enhances the thermal tolerance of Fungiidae. Fungiidae species that have diverged more recently have exhibited a higher presence of heat-tolerant Symbiodiniaceae taxa, more stable bacterial communities, and a robust and resilient microbial interaction network, improving the thermal adaptability of Fungiidae. In summary, this study provides new insights into the thermal adaptation patterns of corals under global warming conditions.

Unraveling the interplay between root exudates, microbiota, and rhizosheath formation in pearl millet

BackgroundThe rhizosheath, a cohesive soil layer firmly adhering to plant roots, plays a vital role in facilitating water and mineral uptake. In pearl millet, rhizosheath formation is genetically controlled and influenced by root exudates. Here, we investigated the impact of root exudates on the microbiota composition, interactions, and assembly processes, and rhizosheath structure in pearl millet using four distinct lines with contrasting soil aggregation abilities.ResultsUtilizing 16S rRNA gene and ITS metabarcoding for microbiota profiling, coupled with FTICR-MS metabonomic analysis of metabolite composition in distinct plant compartments and root exudates, we revealed substantial disparities in microbial diversity and interaction networks. The ß-NTI analysis highlighted bacterial rhizosphere turnover driven primarily by deterministic processes, showcasing prevalent homogeneous selection in root tissue (RT) and root-adhering soil (RAS). Conversely, fungal communities were more influenced by stochastic processes. In bulk soil assembly, a combination of deterministic and stochastic mechanisms shapes composition, with deterministic factors exerting a more pronounced role. Metabolic profiles across shoots, RT, and RAS in different pearl millet lines mirrored their soil aggregation levels, emphasizing the impact of inherent plant traits on microbiota composition and unique metabolic profiles in RT and exudates. Notably, exclusive presence of antimicrobial compounds, including DIMBOA and H-DIMBOA, emerged in root exudates and RT of low aggregation lines.ConclusionsThis research underscores the pivotal influence of root exudates in shaping the root-associated microbiota composition across pearl millet lines, entwined with their soil aggregation capacities. These findings underscore the interconnectedness of root exudates and microbiota, which jointly shape rhizosheath structure, deepening insights into soil–plant-microbe interactions and ecological processes shaping rhizosphere microbial communities. Deciphering plant–microbe interactions and their contribution to soil aggregation and microbiota dynamics holds promise for the advancement of sustainable agricultural strategies.46mkfZGLAk7WD-UFCK_cLiVideo

Rhizosphere microbial ecological characteristics of strawberry root rot.

Strawberry (Fragaria × ananassa Duch.) holds a preeminent position among small fruits globally due to its delectable fruits and significant economic value. However, strawberry cultivation is hampered by various plant diseases, hindering the sustainable development of the strawberry industry. The occurrence of plant diseases is closely linked to imbalance in rhizosphere microbial community structure. In the present study, a systematic analysis of the differences and correlations among non-culturable microorganisms, cultivable microbial communities, and soil nutrients in rhizosphere soil, root surface soil, and non-rhizosphere soil of healthy and diseased strawberry plants affected by root rot was conducted. The goal was to explore the relationship between strawberry root rot occurrence and rhizosphere microbial community structure. According to the results, strawberry root rot altered microbial community diversity, influenced fungal community composition in strawberry roots, reduced microbial interaction network stability, and enriched more endophytic-phytopathogenic bacteria and saprophytic bacteria. In addition, the number of bacteria isolated from the root surface soil of diseased plants was significantly higher than that of healthy plants. In summary, the diseased strawberry plants changed microbial community diversity, fungal species composition, and enriched functional microorganisms significantly, in addition to reshaping the microbial co-occurrence network. The results provide a theoretical basis for revealing the microecological mechanism of strawberry root rot and the ecological prevention and control of strawberry root rot from a microbial ecology perspective.

Composition, function, and timing: exploring the early-life gut microbiota in piglets for probiotic interventions

BackgroundThe establishment of a robust gut microbiota in piglets during their early developmental stage holds the potential for long-term advantageous effects. However, the optimal timeframe for introducing probiotics to achieve this outcome remains uncertain.ResultsIn the context of this investigation, we conducted a longitudinal assessment of the fecal microbiota of 63 piglets at three distinct pre-weaning time points. Simultaneously, we gathered vaginal and fecal samples from 23 sows. Employing 16S rRNA gene and metagenomic sequencing methodologies, we conducted a comprehensive analysis of the fluctuation patterns in microbial composition, functional capacity, interaction networks, and colonization resistance within the gut microbiota of piglets. As the piglets progressed in age, discernible modifications in intestinal microbial diversity, composition, and function were observed. A source-tracking analysis unveiled the pivotal role of fecal and vaginal microbiota derived from sows in populating the gut microbiota of neonatal piglets. By D21, the microbial interaction network displayed a more concise and efficient configuration, accompanied by enhanced colonization resistance relative to the other two time points. Moreover, we identified three strains of Ruminococcus sp. at D10 as potential candidates for improving piglets' weight gain during the weaning phase.ConclusionsThe findings of this study propose that D10 represents the most opportune juncture for the introduction of external probiotic interventions during the early stages of piglet development. This investigation augments our comprehension of the microbiota dynamics in early-life of piglets and offers valuable insights for guiding forthcoming probiotic interventions.

Comparative Analysis of Rumen Microbiota Composition in Dairy Cows with Simple Indigestion and Healthy Cows.

Simple indigestion in cows leads to substantial economic losses in the dairy industry. Despite ongoing efforts, an effective treatment for this issue remains elusive. Previous studies have emphasized the vital role of rumen microbes in maintaining ruminant health. To deepen our comprehension of the intricate interplay between rumen microbiota and simple indigestion, we undertook a study involving the analysis of rumen fluid from eight cows with simple indigestion and ten healthy cows. Additionally, we collected data pertaining to milk production, rumination behavior, and rumen characteristics. The results showed that cows with simple indigestion displayed significantly lower milk yield, reduced rumination duration, and weakened rumen contraction when contrasted with the healthy cows (p < 0.05). However, no significant difference in microbiota α-diversity emerged (p > 0.05). Principal coordinate analysis (PCoA) illuminated substantial variations in rumen microbial structure among the two groups (p < 0.05). Further analysis spotlighted distinctive bacteria in the rumen of the cows with indigestion, including Allisonella, Synergistes, Megasphaera, Clostridium_XIVb, Campylobacter, and Acidaminococcus. In contrast, Coraliomargarita, Syntrophococcus, and Coprococcus are the dominant bacterial genera in the rumen of healthy dairy cows. Importantly, these key bacterial genera also dominated the overarching microbial interaction network. The observation suggests that changes in the abundance of these dominant bacterial genera potentially underlie the principal etiology of cows with simple indigestion. The present findings can provide insights into simple indigestion prevention and treatment in dairy cows.

Regulation of potential denitrification rates in sediments by microbial-driven elemental coupled metabolisms

Microbial driven coupled processes between denitrification and methane/sulfur metabolism play a very substantial role in accelerating nitrogen removal in river sediments. Until now, little is known about how element coupling processes alter nitrogen metabolism by the microbial functional communities. The primary objective of this research was to clarify the contributory role of microbial-mediated coupled processes in controlling denitrification. Specifically, the study sought to identify the key bioindicators (or metabolic pathway) for preferably regulating and predicting potential denitrification rate (PDR). Here, a total of 40 sediment samples were collected from the inflow rivers of Chaohu Lake under nitrogen stress. The results revealed the ecological importance of methanogens and sulfate reducing bacteria in the microbial interaction network. Correlations between quantitative or predicted genes showed that the methanogenic gene (mcrA) was synergistic with denitrifying genes, further unraveling that the key role of methanogenesis in denitrification process for facilitating nitrogen removal. The PDR of sediments ranged from 0.03 to 133.21 μg N·g−1·h−1. The study uncovered specific environmental factors (NH4+ and OM) and microbial indicators (nosZ, mcrA, Paracoccus, Thauera, Methanobrevibacter and Desulfomicrobium) as potential contributors to the variations in PDR. Structural Equation Model (SEM) analysis revealed a significant direct effect of NH4+ on PDR, evidenced by a standardized coefficient (λ) of 0.77 (P < 0.001). Additionally, the findings also emphasized the salient role of methanogens (Methanobrevibacter) and methanogenic gene (mcrA) in indicating PDR. The research's aforementioned findings shed light on the substantial consequences of methanogenesis on nitrogen metabolism in coupled processes, enabling improved control of nitrogen pollution in river sediments. This study provided fresh perspectives on the effects of multiple functional taxa on denitrification, and reinforces the significance of coupling processes for nitrogen removal.

PTBGRP: predicting phage-bacteria interactions with graph representation learning on microbial heterogeneous information network.

Identifying the potential bacteriophages (phage) candidate to treat bacterial infections plays an essential role in the research of human pathogens. Computational approaches are recognized as a valid way to predict bacteria and target phages. However, most of the current methods only utilize lower-order biological information without considering the higher-order connectivity patterns, which helps to improve the predictive accuracy. Therefore, we developed a novel microbial heterogeneous interaction network (MHIN)-based model called PTBGRP to predict new phages for bacterial hosts. Specifically, PTBGRP first constructs an MHIN by integrating phage-bacteria interaction (PBI) and six bacteria-bacteria interaction networks with their biological attributes. Then, different representation learning methods are deployed to extract higher-level biological features and lower-level topological features from MHIN. Finally, PTBGRP employs a deep neural network as the classifier to predict unknown PBI pairs based on the fused biological information. Experiment results demonstrated that PTBGRP achieves the best performance on the corresponding ESKAPE pathogens and PBI dataset when compared with state-of-art methods. In addition, case studies of Klebsiella pneumoniae and Staphylococcus aureus further indicate that the consideration of rich heterogeneous information enables PTBGRP to accurately predict PBI from a more comprehensive perspective. The webserver of the PTBGRP predictor is freely available at http://120.77.11.78/PTBGRP/.

Ecology of the respiratory tract microbiome.

A thriving multi-kingdom microbial ecosystem inhabits the respiratory tract: the respiratory tract microbiome (RTM). In recent years, the contribution of the RTM to human health has become a crucial research aspect. However, research into the key ecological processes, such as robustness, resilience, and microbial interaction networks, has only recently started. This review leans on an ecological framework to interpret the human RTM and determine how the ecosystem functions and assembles. Specifically, the review illustrates the ecological RTM models and discusses microbiome establishment, community structure, diversity stability, and critical microbial interactions. Lastly, the review outlines the RTM responses to ecological disturbances, as well as the promising approaches for restoring ecological balance.

Carbon source shaped microbial ecology, metabolism and performance in denitrification systems.

The limited information on microbial interactions and metabolic patterns in denitrification systems, especially those fed with different carbon sources, has hindered the establishment of ecological linkages between microscale connections and macroscopic reactor performance. In this work, denitrification performance, metabolic patterns, and ecological structure were investigated in parallel well-controlled bioreactors with four representative carbon sources, i.e., methanol, glycerol, acetate, and glucose. After long-term acclimation, significant differences were observed among the four bioreactors in terms of denitrification rates, organic utilization, and heterotrophic bacterial yields. Different carbon sources induced the succession of denitrifying microbiota toward different ecological structures and exhibited distinct metabolic patterns. Methanol-fed reactors showed distinctive microbial carbon utilization pathways and a more intricate microbial interaction network, leading to significant variations in organic utilization and metabolite production compared to other carbon sources. Three keystone taxa belonging to the Verrucomicrobiota phylum, SJA-15 order and the Kineosphaera genus appeared as network hubs in the methanol, glycerol, and acetate-fed systems, playing essential roles in their ecological functions. Several highly connected species were also identified within the glucose-fed system. The close relationship between microbial metabolites, ecological structures, and system performances suggests that this complex network relationship may greatly contribute to the efficient operation of bioreactors.

Nutritional and host environments determine community ecology and keystone species in a synthetic gut bacterial community

A challenging task to understand health and disease-related microbiome signatures is to move beyond descriptive community-level profiling towards disentangling microbial interaction networks. Using a synthetic gut bacterial community, we aimed to study the role of individual members in community assembly, identify putative keystone species and test their influence across different environments. Single-species dropout experiments reveal that bacterial strain relationships strongly vary not only in different regions of the murine gut, but also across several standard culture media. Mechanisms involved in environment-dependent keystone functions in vitro include exclusive access to polysaccharides as well as bacteriocin production. Further, Bacteroides caecimuris and Blautia coccoides are found to play keystone roles in gnotobiotic mice by impacting community composition, the metabolic landscape and inflammatory responses. In summary, the presented study highlights the strong interdependency between bacterial community ecology and the biotic and abiotic environment. These results question the concept of universally valid keystone species in the gastrointestinal ecosystem and underline the context-dependency of both, keystone functions and bacterial interaction networks.

Pathogen Profile of Klebsiella variicola, the Causative Agent of Banana Sheath Rot.

Banana (Musa spp.) is an important fruit and food crop worldwide. In recent years, banana sheath rot has become a major problem in banana cultivation, causing plant death and substantial economic losses. Nevertheless, the pathogen profile of this disease has not been fully characterized. Klebsiella variicola is a versatile bacterium capable of colonizing different hosts, such as plants, humans, insects, and animals, and is recognized as an emerging pathogen in various hosts. In this study, we obtained 12 bacterial isolates from 12 different banana samples showing banana sheath rot in Guangdong and Guangxi Provinces, China. Phylogenetic analysis based on 16S rRNA sequences confirmed that all 12 isolates were K. variicola strains. We sequenced the genomes of these strains, performed comparative genomic analysis with other sequenced K. variicola strains, and found a lack of consistency in accessory gene content among these K. variicola strains. However, prediction based on the pan-genome of K. variicola revealed 22 unique virulence factors carried by the 12 pathogenic K. variicola isolates. Microbiome and microbial interaction network analysis of endophytes between the healthy tissues of diseased plants and healthy plants of two cultivars showed that Methanobacterium negatively interacts with Klebsiella in banana plants and that Herbaspirillum might indirectly inhibit Methanobacterium to promote Klebsiella growth. These results suggest that banana sheath rot is caused by the imbalance of plant endophytes and opportunistic pathogenic bacteria, providing an important basis for research and control of this disease.[Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

P-672 Vaginal microbiome changes in women with polycystic ovary syndrome: a large cross-sectional study

Abstract Study question How the vaginal microbiome changes in women with polycystic ovary syndrome? Summary answer The PCOS women had a higher diversity in the vaginal microbiome and showed an enhanced level of heterogeneity. What is known already PCOS is a common reproductive endocrine disorder with a highly heterogeneous clinical presentation. Recently, few studies with limited sample size have reported that the inconsistent vaginal microbiota composition changes in PCOS. Study design, size, duration The cross-sectional study conducted at a single academic university-affiliated center. A total of 1,446 subjects, including 713 PCOS cases and 733 controls, were recruited. Participants/materials, setting, methods Vaginal swabs were collected for subsequent 16S rRNA gene sequencing. The microbiome diversities, community distances, vaginal bacterial relative abundances, and microbial interactions network were compared between the PCOS group and control group. Main results and the role of chance The PCOS group had a higher alpha diversity in the vaginal microbiome than the control (P &amp;lt; 0.05), while higher intra-group variability was observed in PCOS (P &amp;lt; 0.05). At the genus level, the abundance of Lactobacillus in the PCOS group decreased, while the abundance of Gardnerella and Ureaplasma increased (FDR&amp;lt;0.2). Gardnerella vaginalis, Prevotella buccalis, and Prevotella timonensis were identified as differential species and were significantly associated with clinical parameters of PCOS, like AMH. The microbial interaction network analysis revealed that Prevotella and Lactobacillus could be key drivers for network rewiring in PCOS. Notable alterations of predicted pathways, which significantly differed between PCOS and control women, mainly enriched in amino acid metabolism. Limitations, reasons for caution The study only included Chinese Han population data. Due to the structure of the vaginal flora may vary between ethnic groups, generalizing the results of this study to other populations should be taken caution. Wider implications of the findings This study with large samples could enhance our understanding of the PCOS vaginal microbiome, and provide a basis for future research on the potential mechanism by which pathogenic bacteria are involved in PCOS vaginal microbial imbalances. Trial registration number Not applicable

Response characteristics of indigenous microbial community in polycyclic aromatic hydrocarbons (PAHs) contaminated aquifers under polyethylene microplastics stress: A microcosmic experimental study

To understand the response characteristics of indigenous microbial community in PAH-contaminated aquifers to the coexistence of microplastics. In this paper, we constructed a groundwater microecosystem using lithologic media collected from the field and subjected it to the stress of a polyethylene microplastics (PE-MPs) concentration gradient. By conducting adsorption experiments and 16S rRNA sequencing, we revealed the growth, structure, metabolism, and resistance mechanisms of the indigenous microbial community in the aquifer lithologic media exposed to varying levels of co-stress from PE-MPs and phenanthrene. Our findings suggest that the adsorption capacity of aquifer lithologic media for phenanthrene is significantly weaker than that of PE-MPs. Additionally, our observations indicated that small particle lithologic media had a greater adsorption capacity for phenanthrene than large particle lithologic media. The presence of PE-MPs was found to increase both the abundance and diversity of microbial communities, although the relationship was not linear with the content of PE-MPs. When exposed to the combined stress of PE-MPs and phenanthrene, the relative abundance of Proteobacteria decreased while that of Bacteroidetes increased. Several genera belonging to Proteobacteria (Aeromonas, Desulfovibrio, Klebsiella, Pantoea, and Microvirgula) and Bacteroidetes (Macellibacteroides and Bacteroides) occupied a central position in the microbial community interaction network and showed significant correlations with other genera. Furthermore, an increase in the proportion of genera capable of degrading various refractory organics was observed. The presence of PE-MPs increased the phenanthrene content in the aquifer lithologic media, thereby intensifying the inhibitory effect on indigenous microbial community in this environment. Despite an increase in the phenanthrene content of aquifer lithologic media due to the presence of PE-MPs, indigenous microbial community in this environment exhibited resistance to the combined inhibition of PE-MPs and phenanthrene through a series of resistance mechanisms. These mechanisms included strengthening the N-cycle process, enhancing metabolic capacity for phenanthrene, improving perception, response, and adaptation to changes in the external environment or intracellular state, modifying the transmembrane transport of the cell membrane to the substrate, and regulating life processes.

Edge and modular significance assessment in individual-specific networks

Individual-specific networks, defined as networks of nodes and connecting edges that are specific to an individual, are promising tools for precision medicine. When such networks are biological, interpretation of functional modules at an individual level becomes possible. An under-investigated problem is relevance or ”significance” assessment of each individual-specific network. This paper proposes novel edge and module significance assessment procedures for weighted and unweighted individual-specific networks. Specifically, we propose a modular Cook’s distance using a method that involves iterative modeling of one edge versus all the others within a module. Two procedures assessing changes between using all individuals and using all individuals but leaving one individual out (LOO) are proposed as well (LOO-ISN, MultiLOO-ISN), relying on empirically derived edges. We compare our proposals to competitors, including adaptions of OPTICS, kNN, and Spoutlier methods, by an extensive simulation study, templated on real-life scenarios for gene co-expression and microbial interaction networks. Results show the advantages of performing modular versus edge-wise significance assessments for individual-specific networks. Furthermore, modular Cook’s distance is among the top performers across all considered simulation settings. Finally, the identification of outlying individuals regarding their individual-specific networks, is meaningful for precision medicine purposes, as confirmed by network analysis of microbiome abundance profiles.

Canker Disease Intensifies Cross-Kingdom Microbial Interactions in the Endophytic Microbiota of Citrus Phyllosphere

Plant disease is an important factor that affects the plant microbiome. However, for many plant–pathogen–microbiome interactions, the influences are unknown. Citrus, comprising abundant varieties of mandarin, sweet orange, pomelo, and lemon, is widely cultivated in different production areas in China. Most of these varieties are vulnerable to citrus canker, which is caused by Xanthomonas spp. In this study, asymptomatic and cankered leaves from asymptomatic and canker-infected trees, respectively, were collected from 17 orchards in six citrus production areas and their endophytic microbiomes were compared. The effects of canker on the microbial community richness and diversity were dependent on whether the interaction type was intrakingdom (for bacteria, positive) and interkingdom (for fungi, negative), respectively. The negative effects of canker on the fungal communities might be affected by the strong correlation between Xanthomonas and Fusarium/ Gibberella species. The occurrence of canker significantly affected the composition and structure of both the endophytic fungal and bacterial communities, and altered the dominant genera of each community. In addition, canker occurrence intensified the cross-kingdom microbial interaction network, in which species of Enterobacter, Xanthomonas, Pseudomonas, and Pantoea were detected with increased roles in the network and responsible for the predominant functional genes involved in nutritional metabolism, the bacterial secretion system, and biotin metabolism. The results provide insights into the responses of the endophytic microbiome to citrus canker disease.