MetagenoNets: comprehensive inference and meta-insights for microbial correlation networks

The MTIST platform: a microbiome time series inference standardized test

The human gut microbiome is a promising therapeutic target, but interventions are hampered by our limited understanding of microbial ecosystems. Here, we present a platform to develop, evaluate, and score approaches to learn ecological interactions from microbiome time series data. The microbiome time series inference standardized test (MTIST) comprises: a simulation framework for the in silico generation of microbiome study data akin to what is obtained with quantitative next-generation sequencing approaches, a compilation of a large curated data set generated by the simulation framework representing 648 simulated microbiome studies containing 18,360 time series, with a total of 2,182,800 species abundance measurements, and a scoring method to rank ecological inference algorithms. We use the MTIST platform to rank five implementations of microbiome inference approaches, revealing that while all algorithms performed well on ecosystems with few species (3 and 10), all algorithms failed to infer most interaction in a large ecosystem with 100 member species. However, we do find that the strongest interactions within a large ecosystem are inferred with higher success by all algorithms. Finally, we use the MTIST platform to compare different microbiome study designs, characterizing tradeoffs between samples per subject and number of subjects. Interestingly, we find that when only few samples can be collected per subject, ecological inference is most successful when these samples are collected with highest feasible temporal frequency. Taken together, we provide a computational tool to aid the development of better microbiome ecosystem inference approaches, which will be crucial towards the development of reliable and predictable therapeutic approaches that target the microbiome ecosystem.

Organic farming promotes the abundance of fungi keystone taxa in bacteria-fungi interkingdom networks

Soil bacteria-fungi interactions are essential in the biogeochemical cycles of several nutrients, making these microbes major players in agroecosystems. While the impact of the farming system on microbial community composition has been extensively reported in the literature, whether sustainable farming approaches can promote associations between bacteria and fungi is still unclear. To study this, we employed 16S, ITS, and 18S DNA sequencing to uncover how microbial interactions were affected by conventional and organic farming systems on maize crops. The Bray-Curtis index revealed that bacterial, fungal, and arbuscular mycorrhizal fungi communities were significantly different between the two farming systems. Several taxa known to thrive in healthy soils, such as Nitrosophaerales, Orbiliales, and Glomus were more abundant in the organic farming system. Constrained ordination revealed that the organic farming system microbial community was significantly correlated with the β-glucosidase activity, whereas the conventional farming system microbial community significantly correlated with soil pH. Both conventional and organic co-occurrence interkingdom networks exhibited a parallel node count, however, the former had a higher number of edges, thus being denser than the latter. Despite the similar amount of fungal nodes in the co-occurrence networks, the organic farming system co-occurrence network exhibited more than 3-fold the proportion of fungal taxa as keystone nodes than the conventional co-occurrence network. The genera Bionectria, Cercophora, Geastrum, Penicillium, Preussia, Metarhizium, Myceliophthora, and Rhizophlyctis were among the fungal keystone nodes of the organic farming system network. Altogether, our results uncover that beyond differences in microbial community composition between the two farming systems, fungal keystone nodes are far more relevant in the organic farming system, thus suggesting that bacteria-fungi interactions are more frequent in organic farming systems, promoting a more functional microbial community.

Core microbiota of wheat rhizosphere under Upper Indo-Gangetic plains and their response to soil physicochemical properties

Wheat is widely cultivated in the Indo-Gangetic plains of India and forms the major staple food in the region. Understanding microbial community structure in wheat rhizosphere along the Indo-Gangetic plain and their association with soil properties can be an important base for developing strategies for microbial formulations. In the present study, an attempt was made to identify the core microbiota of wheat rhizosphere through a culture-independent approach. Rhizospheric soil samples were collected from 20 different sites along the upper Indo-Gangetic plains and their bacterial community composition was analyzed based on sequencing of the V3-V4 region of the 16S rRNA gene. Diversity analysis has shown significant variation in bacterial diversity among the sites. The taxonomic profile identified Proteobacteria, Chloroflexi, Actinobacteria, Bacteroidetes, Acidobacteria, Gemmatimonadetes, Planctomycetes, Verrucomicrobia, Firmicutes, and Cyanobacteria as the most dominant phyla in the wheat rhizosphere in the region. Core microbiota analysis revealed 188 taxa as core microbiota of wheat rhizosphere with eight genera recording more than 0.5% relative abundance. The order of most abundant genera in the core microbiota is Roseiflexus> Flavobacterium> Gemmatimonas> Haliangium> Iamia> Flavisolibacter> Ohtaekwangia> Herpetosiphon. Flavobacterium, Thermomonas, Massilia, Unclassified Rhizobiaceae, and Unclassified Crenarchaeota were identified as keystone taxa of the wheat rhizosphere. Correlation studies revealed, pH, organic carbon content, and contents of available nitrogen, phosphorus, and iron as the major factors driving bacterial diversity in the wheat rhizosphere. Redundancy analysis has shown the impact of different soil properties on the relative abundance of different genera of the core microbiota. The results of the present study can be used as a prelude to be developing microbial formulations based on core microbiota.

Translational informatics for human microbiota: data resources, models and applications

With the rapid development of human intestinal microbiology and diverse microbiome-related studies and investigations, a large amount of data have been generated and accumulated. Meanwhile, different computational and bioinformatics models have been developed for pattern recognition and knowledge discovery using these data. Given the heterogeneity of these resources and models, we aimed to provide a landscape of the data resources, a comparison of the computational models and a summary of the translational informatics applied to microbiota data. We first review the existing databases, knowledge bases, knowledge graphs and standardizations of microbiome data. Then, the high-throughput sequencing techniques for the microbiome and the informatics tools for their analyses are compared. Finally, translational informatics for the microbiome, including biomarker discovery, personalized treatment and smart healthcare for complex diseases, are discussed.

The Interaction between Intratumoral Microbiome and Immunity Is Related to the Prognosis of Ovarian Cancer

Microbiota can influence the occurrence, development, and therapeutic response of a wide variety of cancer types by modulating immune responses to tumors. Recent studies have demonstrated the existence of intratumor bacteria inside ovarian cancer (OV). However, whether intratumor microbes are associated with tumor microenvironment (TME) and prognosis of OV still remains unknown. The RNA-sequencing data and clinical and survival data of 373 patients with OV in The Cancer Genome Atlas (TCGA) were collected and downloaded. According to the knowledge-based functional gene expression signatures (Fges), OV was classified into two subtypes, termed immune-enriched and immune-deficient subtypes. The immune-enriched subtype, which had higher immune infiltration enriched with CD8+ T cells and the M1 type of macrophages (M1) and higher tumor mutational burden, exhibited a better prognosis. Based on the Kraken2 pipeline, the microbiome profiles were explored and found to be significantly different between the two subtypes. A prediction model consisting of 32 microbial signatures was constructed using the Cox proportional-hazard model and showed great prognostic value for OV patients. The prognostic microbial signatures were strongly associated with the hosts' immune factors. Especially, M1 was strongly associated with five species (Achromobacter deleyi and Microcella alkaliphila, Devosia sp. strain LEGU1, Ancylobacter pratisalsi, and Acinetobacter seifertii). Cell experiments demonstrated that Acinetobacter seifertii can inhibit macrophage migration. Our study demonstrated that OV could be classified into immune-enriched and immune-deficient subtypes and that the intratumoral microbiota profiles were different between the two subtypes. Furthermore, the intratumoral microbiome was closely associated with the tumor immune microenvironment and OV prognosis. IMPORTANCE Recent studies have demonstrated the existence of intratumoral microorganisms. However, the role of intratumoral microbes in the development of ovarian cancer and their interaction with the tumor microenvironment are largely unknown. Our study demonstrated that OV could be classified into immune-enriched and -deficient subtypes and that the immune enrichment subtype had a better prognosis. Microbiome analysis showed that intratumor microbiota profiles were different between the two subtypes. Furthermore, the intratumor microbiome was an independent predictor of OV prognosis that could interact with immune gene expression. Especially, M1 was closely associated with intratumoral microbes, and Acinetobacter seifertii could inhibit macrophage migration. Together, the findings of our study highlight the important roles of intratumoral microbes in the TME and prognosis of OV, paving the way for further investigation into its underlying mechanisms.

Ecological insights into the resilience of marine plastisphere throughout a storm disturbance

Among numerous research about marine plastisphere, the community living on the surface of plastic debris, little attention was given to the ecological mechanisms governing prokaryotes compared to eukaryotes, and even less focused on their resilience in a changing climate with more storm prevalence. Our current research recruited an integrated approach involving community succession across temporal dimension, ecological mechanisms that govern the assembly, and resilience to environmental perturbations to highlight the ecology of different kingdoms in the plastisphere. Towards this goal, we examined the succession of the prokaryotic and eukaryotic communities on artificial plastic nets in a sidestream of seawater from the Gulf of Aqaba over 35 days. A robust local storm enabled investigation of the alterations before, during, and after this disturbance, aiming at the community's potential to recover. Data from 16S and 18S rRNA sequencing and microscopic analyses decrypted the plastisphere diversity, community assembly, and stochasticity, followed by further analyses of functional and co-occurrence networks for the prokaryotic group. Prokaryotic and eukaryotic communities underwent exact opposite ecological mechanisms. While determinism driven by a robust environmental selection dictated the prokaryotic community assembly, stochasticity prevailed when this condition was relaxed. Interestingly, resilience against disturbance was observed in prokaryotes but not in eukaryotes. The decrease in compositional, functional diversity and network complexity in the prokaryotic community was reversed, presumably due to the niche specification process and high dispersal. Niche specification following perturbation was evident in some bacteria by selected functions associated with plastic degradation, stress response, and antibiotic resistance. On the contrary, eukaryotes decreased in diversity and were dominated by the commonly found Chlorophyta towards the later successional period. Novel findings on the ecology of marine plastisphere during perturbation encourage the integration of this aspect into prediction research.

A guide for comparing microbial co-occurrence networks

The article provides a pipeline for comparing microbial co-occurrence networks based on the R microeco package and meconetcomp package. It has high flexibility and expansibility and can help users efficiently compare networks built from different groups of samples or different construction approaches.

Inferring Bacterial Community Interactions and Functionalities Associated with Osteopenia and Osteoporosis in Taiwanese Postmenopausal Women

Growing evidence suggests that the gut microbiota and their metabolites are associated with bone homeostasis and fragility. However, this association is limited to microbial taxonomic differences. This study aimed to explore whether gut bacterial community associations, composition, and functions are associated with osteopenia and osteoporosis. We compared the gut bacterial community composition and interactions of healthy postmenopausal women with normal bone density (n = 8) with those of postmenopausal women with osteopenia (n = 18) and osteoporosis (n = 21) through 16S rRNA sequencing coupled with network biology and statistical analyses. The results of this study showed reduced alpha diversity in patients with osteoporosis, followed by that in patients with osteopenia, then in healthy controls. Taxonomic analysis revealed that significantly enriched bacterial genera with higher abundance was observed in patients with osteoporosis and osteopenia than in healthy subjects. Additionally, a co-occurrence network revealed that, compared to healthy controls, bacterial interactions were higher in patients with osteoporosis, followed by those with osteopenia. Further, NetShift analysis showed that a higher number of bacteria drove changes in the microbial community structure of patients with osteoporosis than osteopenia. Correlation analysis revealed that most of these driver bacteria had a significant positive relationship with several significant metabolic pathways. Further, ordination analysis revealed that height and T-score were the primary variables influencing the gut microbial community structure. Taken together, this study evaluated that microbial community interaction is more important than the taxonomic differences in knowing the critical role of gut microbiota in postmenopausal women associated with osteopenia and osteoporosis. Additionally, the significantly enriched bacteria and functional pathways might be potential biomarkers for the prognosis and treatment of postmenopausal women with osteopenia and osteoporosis.

Perturbed gut microbiome and fecal and serum metabolomes are associated with chronic kidney disease severity

BACKGROUND

Chronic kidney disease (CKD) is a severe public health problem associated with a disordered gut microbiome. However, the functional alterations of microbiota and their cross talk with metabolism pathways based on disease severity remain unclear.

RESULTS

We performed metagenomics and untargeted metabolomics in a cohort of 68 patients with CKD of differing severities and 20 healthy controls to characterize the complex interplay between the gut microbiome and fecal and serum metabolites during CKD progression. We identified 26 microbial species that significantly changed in patients with CKD; 18 species changed as the disease progressed, and eight species changed only in a specific CKD group. These distinct changes in gut microbiota were accompanied by functional alterations in arginine and proline, arachidonic acid, and glutathione metabolism and ubiquinone and other terpenoid-quinone biosynthesis pathways during CKD progression. Further metabolomic analyses revealed that the distributions of toxic and pro-oxidant metabolites from these four essential metabolic pathways varied in the feces and serum as CKD progressed. Furthermore, we observed a complex co-occurrence between CKD severity-related bacteria and the characterized metabolites from the four essential metabolic pathways. Notably, Ruminococcus bromii, fecal hydroquinone, and serum creatinine were identified as the main contributors to the integrated network, indicating their key roles in CKD progression. Moreover, a noninvasive model including R. bromii and fecal hydroquinone, L-cystine, and 12-keto-tetrahydro-LTB4 levels classified the CKD severity (area under the curve [AUC]: > 0.9) and had better performance than the serum creatinine level for mild CKD (AUC: 0.972 vs. 0.896).

CONCLUSIONS

Perturbed CKD severity-related gut microbiota may contribute to unbalanced toxic and pro-oxidant metabolism in the gut and host, accelerating CKD progression, which may be an early diagnostic and therapeutic target for CKD. Video Abstract.

Influence of host genotype in establishing root associated microbiome of indica rice cultivars for plant growth promotion

Rice plants display a unique root ecosystem comprising oxic-anoxic zones, harboring a plethora of metabolic interactions mediated by its root microbiome. Since agricultural land is limited, an increase in rice production will rely on novel methods of yield enhancement. The nascent concept of tailoring plant phenotype through the intervention of synthetic microbial communities (SynComs) is inspired by the genetics and ecology of core rhizobiome. In this direction, we have studied structural and functional variations in the root microbiome of 10 indica rice varieties. The studies on α and β-diversity indices of rhizospheric root microbiome with the host genotypes revealed variations in the structuring of root microbiome as well as a strong association with the host genotypes. Biomarker discovery, using machine learning, highlighted members of class Anaerolineae, α-Proteobacteria, and bacterial genera like Desulfobacteria, Ca. Entotheonella, Algoriphagus, etc. as the most important features of indica rice microbiota having a role in improving the plant's fitness. Metabolically, rice rhizobiomes showed an abundance of genes related to sulfur oxidation and reduction, biofilm production, nitrogen fixation, denitrification, and phosphorus metabolism. This comparative study of rhizobiomes has outlined the taxonomic composition and functional diversification of rice rhizobiome, laying the foundation for the development of next-generation microbiome-based technologies for yield enhancement in rice and other crops.

Modulation of gut microbiota: The effects of a fruits and vegetables supplement

The consumption of an optimal amount of fruits and vegetables is known to improve physical fitness and physiological body functions. Healthy eating habits, including intake of fruits and vegetables, can modify gut microbiota. This study aimed to demonstrate the effectiveness of a formulated fruit and vegetable supplement (FVS) in modulating the antioxidant capacity and the gut microbiota composition. We enrolled 30 healthy volunteer subjects, matched for age, gender, BMI, and smoking habits, and randomized them into the FVS and the placebo (PLA) groups. Among the serum vitamins, the folic acid level was significantly higher (p = 0.001) in the FVS group than in the PLA group, whereas the vitamin B2 level was significantly higher in the PLA group than in the FVS group (p = 0.028). The antioxidant capacity, measured by using the oxygen radical absorbance capacity (ORAC) method, was also slightly higher in the FVS group than in the PLA group but did not reach statistical significance. The dietary intake, assessed by 24-h recalls, did not show any significant changes after the supplementation in both the groups. The gut microbiome composition, measured by 16S rDNA sequencing, showed no difference in both alpha and beta diversities, whereas the LEfse analysis revealed a microbial shift after the treatment, with a decreased abundance of the genus Ruminococcus from the Lachnospiraceae family (p = 0.009), and the unclassified genus from the family Erysipelotrichaceae (UC36, p = 0.003) in the FVS group compared with the PLA group (confirmed by SIAMCAT analysis, AUC = 74.1%). With a minor effect, the genus Faecalibacterium and unclassified genus and family from the order Lactobacillales (UC31) were also increased in the FVS group compared with the PLA group (p = 0.0474, p = 0.0352, respectively). SCFA measurement by gas chromatography–mass spectrometry showed an increased level of 2-methylbutyrate in the FVS group compared with the PLA group (p = 0.0385). Finally, the Spearman correlation analysis showed that in the FVS group, the genus Faecalibacterium positively correlated with 2-methyl butyrate (p = 0.040). In the PLA group, none of the significant bacteria correlated with either SCFA or serum biomarkers. The network analysis confirmed the positive correlation between genus Faecalibacterium and 2-methyl butyrate. We can conclude that the FVS in healthy individuals modified the gut microbiota composition and metabolites, and it can potentially contribute to reduce the pro-inflammatory response along with the antioxidant capacity.

Environmental Perturbations during the Rehabilitation of Wild Migratory Birds Induce Gut Microbiome Alteration and Antibiotic Resistance Acquisition

Wild migratory birds are essential for sustaining healthy ecosystems, but the effects of a rehabilitation period on their gut microbiomes are still unclear. Here, we performed longitudinal sampling, 16S rRNA sequencing, and antibiotic resistance monitoring of the gut microbiome of six species of wild migratory birds protected as natural monuments in South Korea that are subject to short- or long-term rehabilitation periods. Overall, gut microbiome diversity was significantly decreased in the early stages of rehabilitation, and it did not recover to a level comparable to that of wild birds. Moreover, while the abundance of short-chain fatty acid-producing bacteria decreased, that of zoonotic pathogens increased, indicating rehabilitation-induced dysbiosis. The metabolic pathways involved in the degradation of aromatic pollutants were significantly downregulated, suggesting the depletion of pollutant-degrading microorganisms. Antibiotic resistance of Escherichia coli significantly increased during rehabilitation, particularly ciprofloxacin and tetracycline resistance, and seven of the rehabilitated wild birds acquired multidrug resistance. The diet and habitat changes experienced by wild migratory birds during rehabilitation may have induced the observed gut microbiome dysbiosis and acquisition of antibiotic resistance. These rehabilitation-induced alterations might affect the adaptability of wild birds to their natural environments and contribute to the spread of antibiotic resistance after their release. IMPORTANCE Wild migratory birds are key for ecosystem health but highly sensitive to anthropogenic activities. Therefore, wild migratory birds often undergo rehabilitation to prevent species extinction or biodiversity monitoring. However, the impact of rehabilitation on the gut microbiome of wild migratory birds, which is closely associated with host fitness, remains unclear. For the migratory bird species considered natural monuments in South Korea evaluated here, such impacts could include rehabilitation-induced gut microbiome dysbiosis and acquisition of antibiotic resistance, with possible repercussions on the adaptability of wild birds and spread of antibiotic resistance in the environment after their release. Therefore, the dynamics of the gut microbiome and antibiotic resistance should be considered for implementing sustainable rehabilitation strategies.

Lactobacillus salivarius SNK-6 Activates Intestinal Mucosal Immune System by Regulating Cecal Microbial Community Structure in Laying Hens

The production performance and disease resistance of laying hens decrease obviously with age. This study aimed to investigate the effects of supplementary Lactobacillus salivarius (L. salivarius) SNK-6 on laying performance, the immune-related gene expression in cecal tonsil, and the cecal microbial composition of laying hens. Here, 384 Xinyang black commercial hens (55 weeks old) were randomly allocated to three groups under the same husbandry and dietary regimes: basal diet (Con), the low L. salivarius SNK-6 group (T1: 1.0 × 106 CFU/g), and the high L. salivarius SNK-6 group (T2: 1.0 × 107 CFU/g). The results showed that the feed intake and broken-egg rate in the T1 group were significantly higher than the Con group (p < 0.05). Meanwhile, expressions of intestinal mucosal immune-related genes were significantly upregulated. The 16S rRNA gene sequencing indicated that supplementary L. salivarius SNK-6 had no significant difference in α -diversity and only displayed a trend difference in the β-diversity of cecal microbiota (p = 0.07). LEfSe and random forest were further used to identify bacteria family Enterobacteriaceae, order RF39, genera Ochrobactrum, and Eubacterium as biomarkers between the Con and T1 groups. Genera Ochrobactrum, which had high relative abundance and nodal degree in the T1 and T2 groups, showed a significant positive correlation with the expression of TLR-6, IL-10, MHC-II, and CD40 in cecal tonsils and might play a critical role in activating the host intestinal mucosal immune responses. Overall, dietary supplementary L. salivarius SNK-6 can display an immunomodulatory function, possibly by regulating cecal microbial composition. However, the changes in immune responses may be at the expenditure of corresponding production performance, which needs to be weighed up in practical application.

Metagenomic Characterization of Resistance Genes in Deception Island and Their Association with Mobile Genetic Elements

Antibiotic resistance genes (ARGs) are undergoing a remarkably rapid geographic expansion in various ecosystems, including pristine environments such as Antarctica. The study of ARGs and environmental resistance genes (ERGs) mechanisms could provide a better understanding of their origin, evolution, and dissemination in these pristine environments. Here, we describe the diversity of ARGs and ERGs and the importance of mobile genetic elements as a possible mechanism for the dissemination of resistance genes in Antarctica. We analyzed five soil metagenomes from Deception Island in Antarctica. Results showed that detected ARGs are associated with mechanisms such as antibiotic efflux, antibiotic inactivation, and target alteration. On the other hand, resistance to metals, surfactants, and aromatic hydrocarbons were the dominant ERGs. The taxonomy of ARGs showed that Pseudomonas, Psychrobacter, and Staphylococcus could be key taxa for studying antibiotic resistance and environmental resistance to stress in Deception Island. In addition, results showed that ARGs are mainly associated with phage-type mobile elements suggesting a potential role in their dissemination and prevalence. Finally, these results provide valuable information regarding the ARGs and ERGs in Deception Island including the potential contribution of mobile genetic elements to the spread of ARGs and ERGs in one of the least studied Antarctic ecosystems to date.

Seagrasses and local environment control the bacterial community structure and carbon substrate utilization in brackish sediments

Seagrasses are complex benthic coastal ecosystems that play a crucial role in organic matter cycling and carbon sequestration. However, little is known about how seagrasses influence the structure and carbon utilization potential of benthic bacterial communities. This study examined the bacterial communities in monospecific and mixed meadows of seagrasses and compared with bulk (unvegetated) sediments from Chilika, a brackish water coastal lagoon of India. High-throughput sequencing of 16S rRNA genes revealed a vegetation effect in terms of differences in benthic bacterial community diversity, composition, and abundances in comparison with bulk sediments. Desulfobacterales, Chromatiales, Enterobacteriales, Clostridiales, Vibrionales, and Acidimicrobiales were major taxa that contributed to differences between seagrass and bulk sediments. Seagrasses supported ∼5.94 fold higher bacterial abundances than the bulk due to rich organic carbon stock in their sediments. Co-occurrence network demonstrated much stronger potential interactions and connectedness in seagrass bacterial communities compared to bulk. Chromatiales and Acidimicrobiales were identified as the top two keystone taxa in seagrass bacterial communities, whereas, Dehalococcoidales and Rhizobiales were in bulk communities. Seagrasses and local environmental factors, namely, water depth, water pH, sediment salinity, redox potential, total organic carbon, available nitrogen, sediment texture, sediment pH, and sediment core depth were the major drivers of benthic bacterial community composition. Carbon metabolic profiling revealed that heterotrophic bacteria in seagrass sediments were much more metabolically diverse and active than bulk. The utilization of carbon substrate guilds, namely, amino acids, amines, carboxylic acids, carbohydrates, polymers, and phenolic compounds was enhanced in seagrass sediments. Metabolic mapping predicted higher prevalence of sulfate-reducer and N₂ fixation metabolic functions in seagrass sediments. Overall, this study showed that seagrasses control benthic bacterial community composition and diversity, enhance heterotrophic carbon substrate utilization, and play crucial roles in organic matter cycling including degradation of hydrocarbon and xenobiotics in coastal sediments.

The coral pathogen Vibrio coralliilyticus kills non-pathogenic holobiont competitors by triggering prophage induction

The coral reef microbiome is central to reef health and resilience. Competitive interactions between opportunistic coral pathogens and other commensal microbes affect the health of coral. Despite great advances over the years in sequencing-based microbial profiling of healthy and diseased coral, the molecular mechanism underlying colonization competition has been much less explored. In this study, by examining the culturable bacteria inhabiting the gastric cavity of healthy Galaxea fascicularis, a scleractinian coral, we found that temperate phages played a major role in mediating colonization competition in the coral microbiota. Specifically, the non-toxigenic Vibrio sp. inhabiting the healthy coral had a much higher colonization capacity than the coral pathogen Vibrio coralliilyticus, yet this advantage was diminished by the latter killing the former. Pathogen-encoded LodAB, which produces hydrogen peroxide, triggers the lytic cycle of prophage in the non-toxicogenic Vibrio sp. Importantly, V. coralliilyticus could outcompete other coral symbiotic bacteria (for example, Endozoicomonas sp.) through LodAB-dependent prophage induction. Overall, we reveal that LodAB can be used by pathogens as an important weapon to gain a competitive advantage over lysogenic competitors when colonizing corals.

Altered Salivary Microbiota Following Bifidobacterium animalis Subsp. Lactis BL-11 Supplementation Are Associated with Anthropometric Growth and Social Behavior Severity in Individuals with Prader-Willi Syndrome

To evaluate the influence of oral probiotic Bifidobacterium animalis subsp. lactis (BL-11) supplementation on salivary microbiota composition and the association with growth parameters, and behavioral symptoms in individuals with Prader-Willi syndrome (PWS). In this post hoc analysis, we included a subset of 36 PWS patients with available saliva samples from our original randomized, double-blinded, placebo-controlled trial (Chinese Clinical Trial Registry, ChiCTR1900022646, April 20, 2019). Among the 36 subjects, 17 subjects were allocated to the probiotic group for daily use of the BL-11 probiotic and 19 subjects were allocated to the placebo group. Groupwise and longitudinal differences in salivary microbiota abundances, biodiversity metrics, and height were analyzed. Linear correlations were found between identified differentially abundant salivary microbiota and clinical parameters. Salivary microbiome α-diversity was found to be higher in the probiotic-treated group at week 12 relative to placebo controls (P < 0.05). Leptotrichia, Paracoccus, and Faecalibacterium were found to be more abundant in the probiotic-treated group (P < 0.05). Salivary microbiota abundance and predicted functional profiling abundance correlations were found to be associated with anti-inflammation, anti-obesity, toxin degradation, and anti-oxidative injury effects (Q < 0.1). Several oral taxa also displayed correlations with social behavior severity scores in the probiotic-treated group (Q < 0.1). The findings suggest novel salivary microbiota compositional changes in response to the oral supplementation of BL-11 probiotic in individuals with PWS. The observed differentially abundant taxa between groups post-treatment were highly correlated with interventional effects on growth and social behaviors, although further investigation is warranted. Clinical Trial Registration The original clinical trial was registered under the Chinese Clinical Trial Registry with registration number ChiCTR1900022646 (April 20, 2019).

Interactions between Human Gut Microbiome Dynamics and Sub-Optimal Health Symptoms during Seafaring Expeditions

During long ocean voyages, crew members are subject to complex pressures from their living and working environment, which lead to chronic diseases-like sub-optimal health status. Although the association between dysbiotic gut microbiome and chronic diseases has been broadly reported, the correlation between the sub-optimal health status and gut microbiome remains elusive. Here, the health status of 77 crew members (20-35 years old Chinese, male) during a 135-day sea expedition was evaluated using the shotgun metagenomics of stool samples and health questionnaires taken before and after the voyage. We found five core symptoms (e.g., abnormal defecation frequency, insomnia, poor sleep quality, nausea, and overeating) in 55 out of 77 crew members suffering from sub-optimal health status, and this was termed "seafaring syndrome" (SS) in this study. Significant correlation was found between the gut microbiome and SS rather than any single symptom. For example, SS was proven to be associated with individual perturbation in the gut microbiome, and the microbial dynamics between SS and non-SS samples were different during the voyage. Moreover, the microbial signature for SS was identified using the variation of 19 bacterial species and 26 gene families. Furthermore, using a Random Forest model, SS was predicted with high accuracy (84.4%, area under the concentration-time curve = 0.91) based on 28 biomarkers from pre-voyage samples, and the prediction model was further validated by another 30-day voyage cohort (accuracy = 83.3%). The findings in this study provide insights to help us discover potential predictors or even therapeutic targets for dysbiosis-related diseases. IMPORTANCE Systemic and chronic diseases are important health problems today and have been proven to be strongly associated with dysbiotic gut microbiome. Studying the association between the gut microbiome and sub-optimal health status of humans in extreme environments (such as ocean voyages) will give us a better understanding of the interactions between observable health signs and a stable versus dysbiotic gut microbiome states. In this paper, we illustrated that ocean voyages could trigger different symptoms for different crew member cohorts due to individual differences; however, the co-occurrence of high prevalence symptoms indicated widespread perturbation of the gut microbiome. By investigating the microbial signature and gut microbiome dynamics, we demonstrated that such sub-optimal health status can be predicted even before the voyage. We termed this phenomenon as "seafaring syndrome." This study not only provides the potential strategy for health management in extreme environments but also can assist the prediction of other dysbiosis-related diseases.

3MCor: an integrative web server for metabolome-microbiome-metadata correlation analysis

MOTIVATION

The metabolome and microbiome disorders are highly associated with human health, and there are great demands for dual-omics interaction analysis. Here, we designed and developed an integrative platform, 3MCor, for metabolome and microbiome correlation analysis under the instruction of phenotype and with the consideration of confounders.

RESULTS

Many traditional and novel correlation analysis methods were integrated for intra- and inter-correlation analysis. Three inter-correlation pipelines are provided for global, hierarchical and pairwise analysis. The incorporated network analysis function is conducive to rapid identification of network clusters and key nodes from a complicated correlation network. Complete numerical results (csv files) and rich figures (pdf files) will be generated in minutes. To our knowledge, 3MCor is the first platform developed specifically for the correlation analysis of metabolome and microbiome. Its functions were compared with corresponding modules of existing omics data analysis platforms. A real-world dataset was used to demonstrate its simple and flexible operation, comprehensive outputs and distinctive contribution to dual-omics studies.

AVAILABILITYAND IMPLEMENTATION

3MCor is available at http://3mcor.cn and the backend R script is available at https://github.com/chentianlu/3MCorServer.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Co-occurrence of gut microbiota dysbiosis and bile acid metabolism alteration is associated with psychological disorders in Crohn's disease

This study aims to elucidate the relationships between gut microbiota, bile acid metabolism, and psychological comorbidity in Crohn's disease (CD). We profiled the fecal microbiota composition and quantified the bile acid pool of 39 CD patients and 14 healthy controls using 16S rRNA gene sequencing and liquid chromatography-tandem mass spectrometry, respectively. Significant reductions in the secondary bile acids, LCA and DCA, were found in both the feces and serum samples of CD patients, while the concentration of 7-DHCA was particularly higher in the serum of CD patients with psychological disorders. The fecal levels of HDCA and 12-DHCA of the CD patients were inversely correlated with their Self-Rated Depression Scale (SDS) scores, whereas the serum level of 7-DHCA was positively correlated with the SDS scores. In addition, the fecal levels of TDCA, TLCA, and TβMCA showed a positive correlation with the Self-Rated Anxiety Scale (SAS) scores. The fecal microbiota biodiversity was particularly declined in CD patients with psychological disorders. An enrichment of Ruminococcus gnavus in CD patients may cause psychological disorders by affecting the microbiota-gut-brain axis via its ability to degrade the gut barrier, regulate the tryptophan-kynurenine metabolism, and modulate bile acid metabolism. In addition, the overabundant Enterobacteriaceae and Lachnospiraceae in CD patients may contribute to psychological comorbidity via dysregulating their bile acids metabolism. Taken together, changes in the gut microbiota composition may cooperate with alterations in the bile acid metabolism that are involved in the development of psychological disorders in CD.

Multi-Enzyme Supplementation Modifies the Gut Microbiome and Metabolome in Breeding Hens

Laying and reproductive performance, egg quality, and disease resistance of hens decrease during the late laying period. Exogenous enzymes promote nutrient digestibility and utilization and improve the intestinal environment. However, the specific regulation of the gut microbiome and metabolome by exogenous enzymes remains unelucidated. This study was conducted to evaluate effects of dietary multi-enzyme supplementation on egg and reproductive performance, egg quality, ileum microbiome, and metabolome of breeders. Here, 224 Hy-Line Brown breeding hens (55 weeks old) were randomly allocated to two groups: dietary controls fed basal diet (DC), and test hens fed 0.2 g/kg corn enzyme diet (CE). Serum levels of total protein, globulin, immunoglobulin Y, and antibodies against the Newcastle disease virus and avian influenza H9 strain were significantly increased (p < 0.05). Egg albumen height, Haugh unit, and fertilization and hatching rates were also significantly increased (p < 0.05) in the CE-fed group. 16S rRNA sequence analysis showed that CE strongly affected both α- and β-diversity of the ileal microbiota. LEfSe analysis revealed that the potentially beneficial genera Lactobacillus, Enterococcus, Faecalicoccus, and Streptococcus were enriched as biomarkers in the CE-fed group. Microbial functional analysis revealed that the functional genes associated with harmful-substance biodegradation was significantly increased in the CE-fed group. Additionally, Spearman correlation analysis indicated that changes in microbial genera were correlated with differential metabolites. In summary, dietary multi-enzyme addition can improve egg quality, humoral immunity, and reproductive performance and regulate the intestinal microbiome and metabolome in breeders. Therefore, multi-enzymes could be used as feed additive to extend breeder service life.

Mono-specific algal diets shape microbial networking in the gut of the sea urchin Tripneustes gratilla elatensis

BACKGROUND

Algivorous sea urchins can obtain energy from a diet of a single algal species, which may result in consequent changes in their gut microbe assemblies and association networks.

METHODS

To ascertain whether such changes are led by specific microbes or limited to a specific region in the gut, we compared the microbial assembly in the three major gut regions of the sea urchin Tripneustes gratilla elatensis when fed a mono-specific algal diet of either Ulva fasciata or Gracilaria conferta, or an algal-free diet. DNA extracts from 5 to 7 individuals from each diet treatment were used for Illumina MiSeq based 16S rRNA gene sequencing (V3-V4 region). Niche breadth of each microbe in the assembly was calculated for identification of core, generalist, specialist, or unique microbes. Network analyzers were used to measure the connectivity of the entire assembly and of each of the microbes within it and whether it altered with a given diet or gut region. Lastly, the predicted metabolic functions of key microbes in the gut were analyzed to evaluate their potential contribution to decomposition of dietary algal polysaccharides.

RESULTS

Sea urchins fed with U. fasciata grew faster and their gut microbiome network was rich in bacterial associations (edges) and networking clusters. Bacteroidetes was the keystone microbe phylum in the gut, with core, generalist, and specialist representatives. A few microbes of this phylum were central hub nodes that maintained community connectivity, while others were driver microbes that led the rewiring of the assembly network based on diet type through changes in their associations and centrality. Niche breadth agreed with microbes' richness in genes for carbohydrate active enzymes and correlated Bacteroidetes specialists to decomposition of specific polysaccharides in the algal diets.

CONCLUSIONS

The dense and well-connected microbial network in the gut of Ulva-fed sea urchins, together with animal's rapid growth, may suggest that this alga was most nutritious among the experimental diets. Our findings expand the knowledge on the gut microbial assembly in T. gratilla elatensis and strengthen the correlation between microbes' generalism or specialism in terms of occurrence in different niches and their metabolic arsenal which may aid host nutrition.

Open challenges for microbial network construction and analysis

Microbial network construction is a popular explorative data analysis technique in microbiome research. Although a large number of microbial network construction tools has been developed to date, there are several issues concerning the construction and interpretation of microbial networks that have received less attention. The purpose of this perspective is to draw attention to these underexplored challenges of microbial network construction and analysis.

Application of Deep Learning in Plant-Microbiota Association Analysis

Unraveling the association between microbiome and plant phenotype can illustrate the effect of microbiome on host and then guide the agriculture management. Adequate identification of species and appropriate choice of models are two challenges in microbiome data analysis. Computational models of microbiome data could help in association analysis between the microbiome and plant host. The deep learning methods have been widely used to learn the microbiome data due to their powerful strength of handling the complex, sparse, noisy, and high-dimensional data. Here, we review the analytic strategies in the microbiome data analysis and describe the applications of deep learning models for plant–microbiome correlation studies. We also introduce the application cases of different models in plant–microbiome correlation analysis and discuss how to adapt the models on the critical steps in data processing. From the aspect of data processing manner, model structure, and operating principle, most deep learning models are suitable for the plant microbiome data analysis. The ability of feature representation and pattern recognition is the advantage of deep learning methods in modeling and interpretation for association analysis. Based on published computational experiments, the convolutional neural network and graph neural networks could be recommended for plant microbiome analysis.

Environmental factors shaping bacterial, archaeal and fungal community structure in hydrothermal sediments of Guaymas Basin, Gulf of California

The flanking regions of Guaymas Basin, a young marginal rift basin located in the Gulf of California, are covered with thick sediment layers that are hydrothermally altered due to magmatic intrusions. To explore environmental controls on microbial community structure in this complex environment, we analyzed site- and depth-related patterns of microbial community composition (bacteria, archaea, and fungi) in hydrothermally influenced sediments with different thermal conditions, geochemical regimes, and extent of microbial mats. We compared communities in hot hydrothermal sediments (75-100°C at ~40 cm depth) covered by orange-pigmented Beggiatoaceae mats in the Cathedral Hill area, temperate sediments (25-30°C at ~40 cm depth) covered by yellow sulfur precipitates and filamentous sulfur oxidizers at the Aceto Balsamico location, hot sediments (>115°C at ~40 cm depth) with orange-pigmented mats surrounded by yellow and white mats at the Marker 14 location, and background, non-hydrothermal sediments (3.8°C at ~45 cm depth) overlain with ambient seawater. Whereas bacterial and archaeal communities are clearly structured by site-specific in-situ thermal gradients and geochemical conditions, fungal communities are generally structured by sediment depth. Unexpectedly, chytrid sequence biosignatures are ubiquitous in surficial sediments whereas deeper sediments contain diverse yeasts and filamentous fungi. In correlation analyses across different sites and sediment depths, fungal phylotypes correlate to each other to a much greater degree than Bacteria and Archaea do to each other or to fungi, further substantiating that site-specific in-situ thermal gradients and geochemical conditions that control bacteria and archaea do not extend to fungi.

Exploring Gut Microbiota in Patients with Colorectal Disease Based on 16S rRNA Gene Amplicon and Shallow Metagenomic Sequencing

The gastrointestinal tract, the largest human microbial reservoir, is highly dynamic. The gut microbes play essential roles in causing colorectal diseases. In the present study, we explored potential keystone taxa during the development of colorectal diseases in central China. Fecal samples of some patients were collected and were allocated to the adenoma (Group A), colorectal cancer (Group C), and hemorrhoid (Group H) groups. The 16S rRNA amplicon and shallow metagenomic sequencing (SMS) strategies were used to recover the gut microbiota. Microbial diversities obtained from 16S rRNA amplicon and SMS data were similar. Group C had the highest diversity, although no significant difference in diversity was observed among the groups. The most dominant phyla in the gut microbiota of patients with colorectal diseases were Bacteroidetes, Firmicutes, and Proteobacteria, accounting for >95% of microbes in the samples. The most abundant genera in the samples were Bacteroides, Prevotella, and Escherichia/Shigella, and further species-level and network analyses identified certain potential keystone taxa in each group. Some of the dominant species, such as Prevotella copri, Bacteroides dorei, and Bacteroides vulgatus, could be responsible for causing colorectal diseases. The SMS data recovered diverse antibiotic resistance genes of tetracycline, macrolide, and beta-lactam, which could be a result of antibiotic overuse. This study explored the gut microbiota of patients with three different types of colorectal diseases, and the microbial diversity results obtained from 16S rRNA amplicon sequencing and SMS data were found to be similar. However, the findings of this study are based on a limited sample size, which warrants further large-scale studies. The recovery of gut microbiota profiles in patients with colorectal diseases could be beneficial for future diagnosis and treatment with modulation of the gut microbiota. Moreover, SMS data can provide accurate species- and gene-level information, and it is economical. It can therefore be widely applied in future clinical metagenomic studies.

Dysbiotic Gut Microbiota and Dysregulation of Cytokine Profile in Children and Teens With Autism Spectrum Disorder

Inflammation and the gut-brain axis have been implicated in the pathogenesis of autism spectrum disorders (ASDs). To further understand the relationship between aberrant immune responses and dysbiotic features of the gut microbiome in ASD, we enrolled 45 ASD individuals and 41 healthy control subjects with ages ranging from 2 to 19 years. We found that ASD group subjects have significantly higher plasma levels of IL-2, IL-4, IL-5, IL-6, IL-10, TNF-α, TNF-β, and IFN-γ when compared to healthy controls (FDR-adjusted p < 0.05). The plasma levels of pro-inflammatory cytokines IFN-γ and IL-6 are found to be further associated with several largely pathogenic gut microbiota uniquely detected in subjects with ASD. Furthermore, the ASD gut microbiome is characterized by reduced levels of several beneficial microbiota, including Bacteroides (FDR-adjusted p < 0.01) and Lachnospiraceae (FDR-adjusted p < 0.001). Analysis of Lachnospiraceae family and genus level taxa suggested that relative abundances of such taxa are negatively correlated with pro-inflammatory signaling cytokines IFN-γ and IL-6, particularly in subjects with severe ASD as defined by CARS (p < 0.05). Several largely pathogenic genera are determined to be associated with the pro-inflammatory cytokines IFN-γ and IL-6 (FDR-adjusted p < 0.1). Additionally, IL-4 is significantly negatively correlated with CARS total score (p < 0.05). Based on such results, we propose that the association between the disturbances of specific cytokines and alterations in gut microbiota abundance observed in children and adolescents with ASD provides additional evidence on the induction of aberrant pro-inflammatory mechanisms in ASD and its early diagnosis.

The pint- sized powerhouse: Illuminating the mighty role of the gut microbiome in improving the outcome of anti- cancer therapy

Cancer persists as a major health catastrophe and a leading cause of widespread mortality across every nation. Research of several decades has increased our understanding of the pivotal pathways and key players of the host during tumor development and progression, which has enabled generation of precision therapeutics with improved efficacy. Despite such tremendous advancements in our combat against this fatal disease, a majority of the cancer patients suffer from poor tumor- free survival owing to the increased incidence of recurrent tumor. This is primarily due to the development of resistance against contemporary anti- cancer strategies. Recent studies have pointed towards the involvement of the human symbiotic gut microbiota in regulating the outcome of chemotherapy and immunotherapy. It does so primarily by modulating the metabolism of the drugs and host immune response, thereby enhancing the efficacy and ameliorating the toxicity. The interactions between the therapeutic agents, microbial community and host immunity may provide a new avenue for the clinical management of cancer. In addition, consumption of dietary pro-, pre- and synbiotics has been recognized to confer protection against tumor genesis and also promote improved response to traditional tumor suppressive strategies. Naturally, the use of various combinatorial regimes containing dietary supplements that improve the gut microbiome in amalgamation with conventional cancer treatment methods may significantly augment the therapeutic outcome of cancer patients and circumnavigate the resistance mechanisms that confound traditional therapies. In this review, we have summarized the role of the gut microbiome, which is the largest assembly of commensals within the human body, in regulating the efficacy and toxicity of various existing anti- cancer therapies including chemotherapy, immunotherapy and surgery. Furthermore, we have discussed how novel strategies integrating the application of probiotics, prebiotics, synbiotics and antibiotics in combination with the aforementioned anti- cancer modules manipulate the gut microbiota and, therefore, augment their therapeutic outcome. Together, such innovative anti- tumorigenic approaches may prove highly effective in improving the prognosis of cancer patients.