Microbial Association Networks Research Articles

Diversified crop rotations improve soil microbial communities and functions in a six-year field experiment

Diversified crop rotations can help mitigate the negative impacts of increased agricultural intensity on the sustainability of agroecosystems. However, the impact of crop rotation diversity on the complexity of soil microbial association networks and ecological functions is still not well understood. In this study, a 6-year field experiment was conducted to evaluate how six different crop rotations change the composition and network complexity of soil microbial communities, as well as their related ecological functions. Microbial traits were measured in six crop rotations with different crop diversity index (CDI) during 2016–2022, including winter wheat–summer maize (CDI 1, WM) as the control, sweet potato→winter wheat–summer maize (CDI 1.5, SpWM), peanut→winter wheat–summer maize (CDI 1.5, PWM), soybean→winter wheat–summer maize (CDI 1.5, SWM), spring maize→winter wheat–summer maize (CDI 1.5, SmWM), and ryegrass–sweet sorghum→winter wheat–summer maize (CDI 2, RSWM). The study findings indicated that diversified crop rotations significantly increased ASV richness of both bacterial and fungal communities after 6-year treatments, and the β-diversity profiles of bacterial and fungal communities significantly distinguished at the year of 2022 from 2016. The relative abundance of Acidobacteria and Chloroflexi was significantly enriched in SpWM rotation at 2022, while Basidiomycota significantly declined in five diversified rotations compared to WM. Diversified crop rotations at 2022 increased the complexity and density of bacterial and fungal networks than 2016. SpWM and PWM rotations had the highest functional groups involved in chemoheterotrophy and saprotroph, respectively. Structural equation modelling (SEM) also revealed that diversified crop rotations increased soil nutrients through improving the composition of bacterial communities and the augmented intricacy of the interconnections within both bacterial and fungal communities. This research underscores the importance of preserving the diversity and ecological functions of soil microorganisms in the nutrient-recycling processes for efficient agricultural practices.

Mulching drive changes in soil microbial community assembly processes and networks across aggregate fractions

Soil microbial community assembly processes and networks in croplands have been widely explored; however, their dynamics and how they regulate winter wheat yield across distinct soil aggregate fractions under the combined effects of mulching and soil horizons have not been comprehensively understood. Therefore, based on a 9-y field experiment, the responses of soil bacterial and fungal community assembly processes and interkingdom association networks to mulching were specifically investigated at the soil aggregation level. Soil properties and microbial biomass were separated into distinct mulching in the topsoil (0–10 cm), and soil water content was considered the most critical factor. The soil bacterial community was affected mainly by mulching and soil horizon compared with the fungal community in microaggregates (<0.25 mm). Notably, the bacterial community displayed more robust stochastic processes than the fungal one, and microbial interkingdom association networks were more complex and stable in micro-than macroaggregates. Soil potential carbon mineralization, pH, and total nitrogen were the dominant properties regulating winter wheat grain yield in combination with microbial community composition, assembly processes, and networks in each soil aggregate class. Wheat yield decreased under straw mulching and was mainly regulated by bacterial community composition and assembly processes. Thus, this study enhanced our understanding of the regulations for wheat yield, which could facilitate soil microbial community management at the aggregation level for sustainable crop production in mulching conservation agroecosystems.

Integration of metataxonomic data sets into microbial association networks highlights shared bacterial community dynamics in fermented vegetables.

Within the growing body of research on the bacterial communities involved in the fermentation of vegetables, there is particular interest in discovering the species or consortia that drive different fermentation steps. This integrative analysis demonstrates that the reuse and integration of public microbiome data sets can provide new insights into a little-known biotope. Our most important finding is the recurrent but transient appearance, at the beginning of vegetable fermentation, of amplicon sequence variants (ASVs) belonging to Enterobacterales and their associations with ASVs belonging to Lactobacillales. These findings could be applied to the design of new fermented products.

Feeding strategy and feed protein level affect the gut microbiota of common carp (Cyprinus carpio).

Common carp (Cyprinus carpio) were fed food with different protein concentrations following different feeding regimes, which were previously shown to affect growth, nitrogen excretion and amino acid catabolism. 16S rRNA gene amplicon sequencing was performed to investigate the gut microbiota of these fish. Lower dietary protein content increased microbial richness, while the combination of demand feeding and dietary protein content affected the composition of the gut microbiota. Hepatic glutamate dehydrogenase (GDH) activity was correlated to the composition of the gut microbiota in all dietary treatments. We found that demand-fed carp fed a diet containing 39% protein had a significantly higher abundance of Beijerinckiaceae compared to other dietary groups. Network analysis identified this family and two Rhizobiales families as hubs in the microbial association network. In demand-fed carp, the microbial association network had significantly fewer connections than in batch-fed carp. In contrast to the large effects of the feeding regime and protein content of the food on growth and nitrogen metabolism, it had only limited effects on gut microbiota composition. However, correlations between gut microbiota composition and liver GDH activity showed that host physiology and gut microbiota are connected, which warrants functional studies into the role of the gut microbiota in fish physiology.

Gut microbial interactions based on network construction and bacterial pairwise cultivation.

Association networks are widely applied for the prediction of bacterial interactions in studies of human gut microbiomes. However, the experimental validation of the predicted interactions is challenging due to the complexity of gut microbiomes and the limited number of cultivated bacteria. In this study, we addressed this challenge by integrating in vitro time series network (TSN) associations and co-cultivation of TSN taxon pairs. Fecal samples were collected and used for cultivation and enrichment of gut microbiome on YCFA agar plates for 13 days. Enriched cells were harvested for DNA extraction and metagenomic sequencing. A total of 198 metagenome-assembled genomes (MAGs) were recovered. Temporal dynamics of bacteria growing on the YCFA agar were used to infer microbial association networks. To experimentally validate the interactions of taxon pairs in networks, we selected 24 and 19 bacterial strains from this study and from the previously established human gut microbial biobank, respectively, for pairwise co-cultures. The co-culture experiments revealed that most of the interactions between taxa in networks were identified as neutralism (51.67%), followed by commensalism (21.67%), amensalism (18.33%), competition (5%) and exploitation (3.33%). Genome-centric analysis further revealed that the commensal gut bacteria (helpers and beneficiaries) might interact with each other via the exchanges of amino acids with high biosynthetic costs, short-chain fatty acids, and/or vitamins. We also validated 12 beneficiaries by adding 16 additives into the basic YCFA medium and found that the growth of 66.7% of these strains was significantly promoted. This approach provides new insights into the gut microbiome complexity and microbial interactions in association networks. Our work highlights that the positive relationships in gut microbial communities tend to be overestimated, and that amino acids, short-chain fatty acids, and vitamins are contributed to the positive relationships.

Host genotype-specific rhizosphere fungus enhances drought resistance in wheat

BackgroundThe severity and frequency of drought are expected to increase substantially in the coming century and dramatically reduce crop yields. Manipulation of rhizosphere microbiomes is an emerging strategy for mitigating drought stress in agroecosystems. However, little is known about the mechanisms underlying how drought-resistant plant recruitment of specific rhizosphere fungi enhances drought adaptation of drought-sensitive wheats. Here, we investigated microbial community assembly features and functional profiles of rhizosphere microbiomes related to drought-resistant and drought-sensitive wheats by amplicon and shotgun metagenome sequencing techniques. We then established evident linkages between root morphology traits and putative keystone taxa based on microbial inoculation experiments. Furthermore, root RNA sequencing and RT-qPCR were employed to explore the mechanisms how rhizosphere microbes modify plant response traits to drought stresses.ResultsOur results indicated that host plant signature, plant niche compartment, and planting site jointly contribute to the variation of soil microbiome assembly and functional adaptation, with a relatively greater effect of host plant signature observed for the rhizosphere fungi community. Importantly, drought-resistant wheat (Yunhan 618) possessed more diverse bacterial and fungal taxa than that of the drought-sensitive wheat (Chinese Spring), particularly for specific fungal species. In terms of microbial interkingdom association networks, the drought-resistant variety possessed more complex microbial networks. Metagenomics analyses further suggested that the enriched rhizosphere microbiomes belonging to the drought-resistant cultivar had a higher investment in energy metabolism, particularly in carbon cycling, that shaped their distinctive drought tolerance via the mediation of drought-induced feedback functional pathways. Furthermore, we observed that host plant signature drives the differentiation in the ecological role of the cultivable fungal species Mortierella alpine (M. alpina) and Epicoccum nigrum (E. nigrum). The successful colonization of M. alpina on the root surface enhanced the resistance of wheats in response to drought stresses via activation of drought-responsive genes (e.g., CIPK9 and PP2C30). Notably, we found that lateral roots and root hairs were significantly suppressed by co-colonization of a drought-enriched fungus (M. alpina) and a drought-depleted fungus (E. nigrum).ConclusionsCollectively, our findings revealed host genotypes profoundly influence rhizosphere microbiome assembly and functional adaptation, as well as it provides evidence that drought-resistant plant recruitment of specific rhizosphere fungi enhances drought tolerance of drought-sensitive wheats. These findings significantly underpin our understanding of the complex feedbacks between plants and microbes during drought, and lay a foundation for steering “beneficial keystone biome” to develop more resilient and productive crops under climate change.FGv_ocsEwwAXXw4e-N4VhrVideo

Streptomyces-triggered coordination between rhizosphere microbiomes and plant transcriptome enables watermelon Fusarium wilt resistance.

The use of microbial inoculant is a promising strategy to improve plant health, but their efficiency often faces challenges due to difficulties in successful microbial colonization in soil environments. To this end, the application of biostimulation products derived from microbes is expected to resolve these barriers via direct interactions with plants or soil pathogens. However, their effectiveness and mechanisms for promoting plant growth and disease resistance remain elusive. In this study, we showed that root irrigation with the extracts of Streptomyces ahygroscopicus strain 769 (S769) solid fermentation products significantly reduced watermelon Fusarium wilt disease incidence by 30% and increased the plant biomass by 150% at a fruiting stage in a continuous cropping field. S769 treatment led to substantial changes in both bacterial and fungal community compositions, and induced a highly interconnected microbial association network in the rhizosphere. The root transcriptome analysis further suggested that S769 treatment significantly improved the expression of the MAPK signalling pathway, plant hormone signal transduction and plant-pathogen interactions, particular those genes related to PR-1 and ethylene, as well as genes associated with auxin production and reception. Together, our study provides mechanistic and empirical evidences for the biostimulation products benefiting plant health through coordinating plant and rhizosphere microbiome interaction.

Strong succession in prokaryotic association networks and community assembly mechanisms in an acid mine drainage-impacted riverine ecosystem.

Acid mine drainage (AMD) serves as an ideal model system for investigating microbial ecology, interaction, and assembly mechanism in natural environments. While previous studies have explored the structure and function of microbial communities in AMD, the succession patterns of microbial association networks and underlying assembly mechanisms during natural attenuation processes remain elusive. Here, we investigated prokaryotic microbial diversity and community assembly along an AMD-impacted river, from the extremely acidic, heavily polluted headwaters to the nearly neutral downstream sites. Microbial diversity was increased along the river, and microbial community composition shifted from acidophile-dominated to freshwater taxa-dominated communities. The complexity and relative modularity of the microbial networks were also increased, indicating greater network stability during succession. Deterministic processes, including abiotic selection of pH and high contents of sulfur and iron, governed community assembly in the headwaters. Although the stochasticity ratio was increased downstream, manganese content, microbial negative cohesion, and relative modularity played important roles in shaping microbial community structure. Overall, this study provides valuable insights into the ecological processes that govern microbial community succession in AMD-impacted riverine ecosystems. These findings have important implications for in-situ remediation of AMD contamination.

Dynamic response of bacterial communities to Microcystis blooms: A three-year study

Although nutrient availability is widely recognized as the driving force behind Microcystis blooms, identifying the microorganisms that play a pivotal role in their formation is a challenging task. Our understanding of the contribution of bacterial communities to the development of Microcystis blooms remains incomplete, despite the fact that the relationship between Microcystis and bacterial communities has been extensively investigated. Most studies have focused on their interaction for a single year rather than for multiple years. To determine key bacteria crucial for the formation of Microcystis blooms, we collected samples from three sites in the Daechung Reservoir (Chuso, Hoenam, and Janggye) over three years (2017, 2019, and 2020). Our results indicated that Microcystis bloom-associated bacterial communities were more conserved across stations than across years. Bacterial communities could be separated into modules corresponding to the different phases of Microcystis blooms. Dolichospermum and Aphanizomenon belonged to the same module, whereas the module of Microcystis was distinct. The microbial recurrent association network (MRAN) showed that amplicon sequence variants (ASVs) directly linked to Microcystis belonged to Pseudanabaena, Microscillaceae, Sutterellaceae, Flavobacterium, Candidatus Aquiluna, Bryobacter, and DSSD61. These ASVs were also identified as key indicators of the bloom stage, indicating that they were fundamental biological elements in the development of Microcystis blooms. Overall, our study highlights that, although bacterial communities change annually, they continue to share core ASVs that may be crucial for the formation and maintenance of Microcystis blooms.

Plant domestication shapes rhizosphere microbiome assembly and metabolic functions

BackgroundThe rhizosphere microbiome, which is shaped by host genotypes, root exudates, and plant domestication, is crucial for sustaining agricultural plant growth. Despite its importance, how plant domestication builds up specific rhizosphere microbiomes and metabolic functions, as well as the importance of these affected rhizobiomes and relevant root exudates in maintaining plant growth, is not well understood. Here, we firstly investigated the rhizosphere bacterial and fungal communities of domestication and wild accessions of tetraploid wheat using amplicon sequencing (16S and ITS) after 9 years of domestication process at the main production sites in China. We then explored the ecological roles of root exudation in shaping rhizosphere microbiome functions by integrating metagenomics and metabolic genomics approaches. Furthermore, we established evident linkages between root morphology traits and keystone taxa based on microbial culture and plant inoculation experiments.ResultsOur results suggested that plant rhizosphere microbiomes were co-shaped by both host genotypes and domestication status. The wheat genomes contributed more variation in the microbial diversity and composition of rhizosphere bacterial communities than fungal communities, whereas plant domestication status exerted much stronger influences on the fungal communities. In terms of microbial interkingdom association networks, domestication destabilized microbial network and depleted the abundance of keystone fungal taxa. Moreover, we found that domestication shifted the rhizosphere microbiome from slow growing and fungi dominated to fast growing and bacteria dominated, thereby resulting in a shift from fungi-dominated membership with enrichment of carbon fixation genes to bacteria-dominated membership with enrichment of carbon degradation genes. Metagenomics analyses further indicated that wild cultivars of wheat possess higher microbial function diversity than domesticated cultivars. Notably, we found that wild cultivar is able to harness rhizosphere microorganism carrying N transformation (i.e., nitrification, denitrification) and P mineralization pathway, whereas rhizobiomes carrying inorganic N fixation, organic N ammonification, and inorganic P solubilization genes are recruited by the releasing of root exudates from domesticated wheat. More importantly, our metabolite-wide association study indicated that the contrasting functional roles of root exudates and the harnessed keystone microbial taxa with different nutrient acquisition strategies jointly determined the aboveground plant phenotypes. Furthermore, we observed that although domesticated and wild wheats recruited distinct microbial taxa and relevant functions, domestication-induced recruitment of keystone taxa led to a consistent growth regulation of root regardless of wheat domestication status.ConclusionsOur results indicate that plant domestication profoundly influences rhizosphere microbiome assembly and metabolic functions and provide evidence that host plants are able to harness a differentiated ecological role of root-associated keystone microbiomes through the release of root exudates to sustain belowground multi-nutrient cycles and plant growth. These findings provide valuable insights into the mechanisms underlying plant-microbiome interactions and how to harness the rhizosphere microbiome for crop improvement in sustainable agriculture.CBzZNC2FEDswGcHctbDosaVideo

Rhizosphere microbial community assembly and association networks strongly differ based on vegetation type at a local environment scale.

Rhizosphere microbes perform critical functions for their hosts, and their structure is strongly influenced by vegetation type. Although studies on the effects of vegetation on rhizosphere microbial community structure have been conducted at large and global environment scales, studies at local environment scales would eliminate numerous external factors such as climate and soil type, while highlighting the potential influence of local vegetation type. Here, we compared rhizosphere microbial communities using 54 samples under three vegetation types (herb, shrubs, and arbors, with bulk soil as the control) at the campus of Henan University. 16S rRNA and ITS amplicons were sequenced using Illumina high throughput sequencing. Rhizosphere bacterial and fungal community structures were influenced considerably by vegetation type. Bacterial alpha diversity under herbs was significantly different from that under arbors and shrubs. The abundance of phyla such as Actinobacteria was extremely higher in bulk soil than in the rhizosphere soils. Herb rhizosphere harbored more unique species than other vegetation type soils. Furthermore, bacterial community assembly in bulk soil was more dominated by deterministic process, whereas the rhizosphere bacterial community assembly was dominated by stochasticity and the construction of fungal communities was all dominated by deterministic processes. In addition, rhizosphere microbial networks were less complex than bulk soil networks, and their keystone species differed based on vegetation type. Notably, bacterial community dissimilarities were strongly correlated with plant phylogenetic distance. Exploring rhizosphere microbial community patterns under different vegetation types could enhance our understanding of the role of rhizosphere microbes in ecosystem function and service provision, as well as basic information that could facilitate plant and microbial diversity conservation at the local environment scale.

Microbiome and metabolic features of tissues and feces reveal diagnostic biomarkers for colorectal cancer.

Microbiome and their metabolites are increasingly being recognized for their role in colorectal cancer (CRC) carcinogenesis. Towards revealing new CRC biomarkers, we compared 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) metabolite analyses in 10 CRC (TCRC) and normal paired tissues (THC) along with 10 matched fecal samples (FCRC) and 10 healthy controls (FHC). The highest microbial phyla abundance from THC and TCRC were Firmicutes, while the dominant phyla from FHC and FCRC were Bacteroidetes, with 72 different microbial genera identified among four groups. No changes in Chao1 indices were detected between tissues or between fecal samples whereas non-metric multidimensional scaling (NMDS) analysis showed distinctive clusters among fecal samples but not tissues. LEfSe analyses indicated Caulobacterales and Brevundimonas were higher in THC than in TCRC, while Burkholderialese, Sutterellaceaed, Tannerellaceaea, and Bacteroidaceae were higher in FHC than in FCRC. Microbial association networks indicated some genera had substantially different correlations. Tissue and fecal analyses indicated lipids and lipid-like molecules were the most abundant metabolites detected in fecal samples. Moreover, partial least squares discriminant analysis (PLS-DA) based on metabolic profiles showed distinct clusters for CRC and normal samples with a total of 102 differential metabolites between THC and TCRC groups and 700 metabolites different between FHC and FCRC groups. However, only Myristic acid was detected amongst all four groups. Highly significant positive correlations were recorded between genus-level microbiome and metabolomics data in tissue and feces. And several metabolites were associated with paired microbes, suggesting a strong microbiota-metabolome coupling, indicating also that part of the CRC metabolomic signature was attributable to microbes. Suggesting utility as potential biomarkers, most such microbiome and metabolites showed directionally consistent changes in CRC patients. Nevertheless, further studies are needed to increase sample sizes towards verifying these findings.

PPNet: Identifying Functional Association Networks by Phylogenetic Profiling of Prokaryotic Genomes.

Identification of microbial functional association networks allows interpretation of biological phenomena and a greater understanding of the molecular basis of pathogenicity and also underpins the formulation of control measures. Here, we describe PPNet, a tool that uses genome information and analysis of phylogenetic profiles with binary similarity and distance measures to derive large-scale bacterial gene association networks of a single species. As an exemplar, we have derived a functional association network in the pig pathogen Streptococcus suis using 81 binary similarity and dissimilarity measures which demonstrates excellent performance based on the area under the receiver operating characteristic (AUROC), the area under the precision-recall (AUPR), and a derived overall scoring method. Selected network associations were validated experimentally by using bacterial two-hybrid experiments. We conclude that PPNet, a publicly available (https://github.com/liyangjie/PPNet), can be used to construct microbial association networks from easily acquired genome-scale data. IMPORTANCE This study developed PPNet, the first tool that can be used to infer large-scale bacterial functional association networks of a single species. PPNet includes a method for assigning the uniqueness of a bacterial strain using the average nucleotide identity and the average nucleotide coverage. PPNet collected 81 binary similarity and distance measures for phylogenetic profiling and then evaluated and divided them into four groups. PPNet can effectively capture gene networks that are functionally related to phenotype from publicly prokaryotic genomes, as well as provide valuable results for downstream analysis and experiment testing.

Foliar herbivory affects the rhizosphere microbial assembly processes and association networks

Insect herbivores are prevalent in terrestrial ecosystems, and plants inevitably and continuously suffer damage by insect herbivores. Numerous studies have reported the effect of insect herbivory on plants; however, its effect on the belowground soil microbial community remains understudied. In the present study, using high-throughput sequencing, we investigated the effect of foliar insect herbivory on rhizosphere soil bacterial community. Our results showed that both herbivory intensity and duration after herbivory had no significant effect on the rhizosphere microbial community structure, but microbial assembly processes and association networks were strongly affected by the above two factors. Under moderate and high herbivory and at 6 weeks after herbivory, variable selection explained 55.56% and 51.52% of the community variation indicating that deterministic processes played a dominant role. Network complexity decreased from no herbivory (1.07) to high herbivory (0.97), and network complexity at 2 weeks after herbivory (0.92) was higher than that at 4 and 6 weeks after herbivory (0.79 and 0.84, respectively). The proportion of negative correlations decreased with increasing herbivory intensity and duration after herbivory. The number of keystone species decreased with increasing duration after herbivory but showed no change with increasing herbivory intensity. To our knowledge, this is among the first studies to illustrate the response mechanisms of rhizosphere microbial assembly processes and association networks to foliar herbivory. Our findings suggest that the assembly process and association network patterns of microbes are closely associated with herbivory intensity and duration after herbivory and enhance the understanding of insect-plant-soil microbe interactions.

Seasonal Changes in the Microbial Communities on Lettuce (Lactuca sativa L.) in Chungcheong-do, South Korea.

Lettuce is one of the most consumed vegetables worldwide. However, it has potential risks associated with pathogenic bacterial contamination because it is usually consumed raw. In this study, we investigated the changes in the bacterial community on lettuce (Lactuca sativa L.) in Chungcheong-do, South Korea, and the prevalence of foodborne pathogens on lettuce in different seasons using 16S rRNA gene-based sequencing. Our data revealed that the Shannon diversity index showed the same tendency in term of the number of OTUs, with the index being greatest for summer samples in comparison to other seasons. Moreover, the microbial communities were significantly different between the four seasons. The relative abundance of Actinobacteriota varied according to the season. Family Micrococcaceae was most dominant in all samples except summer, and Rhizobiaceae was predominant in the microbiome of the summer sample. At the genus level, the relative abundance of Bacillus was greatest in spring samples, whereas Pseudomonas was greatest in winter samples. Potential pathogens, such as Staphylococcus and Clostridium, were detected with low relative abundance in all lettuce samples. We also performed metagenome shotgun sequencing analysis on the selected summer and winter samples, which were expected to be contaminated with foodborne pathogens, to support 16S rRNA gene-based sequencing dataset. Moreover, we could detect seasonal biomarkers and microbial association networks of microbiota on lettuce samples. Our results suggest that seasonal characteristics of lettuce microbial communities, which include diverse potential pathogens, can be used as basic data for food safety management to predict and prevent future outbreaks.

Phylogenetically informed Bayesian truncated copula graphical models for microbial association networks

Microorganisms play critical roles in host health. The advancement of high-throughput sequencing technology provides opportunities for a deeper understanding of microbial interactions. However, due to the technological limitations of 16S ribosomal RNA sequencing, microbiome data are zero-inflated, and a quantitative comparison of microbial abundances cannot be made across subjects. By leveraging a recent microbiome profiling technique that quantifies 16S ribosomal RNA microbial counts, we propose a novel Bayesian graphical model that incorporates microorganisms’ evolutionary history through a phylogenetic tree prior and explicitly accounts for zero inflation using the truncated Gaussian copula. Our simulation study reveals that the evolutionary information substantially improves the network estimation accuracy. We apply the proposed model to the quantitative gut microbiome data of 106 healthy subjects and identify three distinct microbial communities that are not found by existing microbial network estimation models. We further find that these communities are discriminated based on microorganisms’ ability to utilize oxygen as an energy source.

Dynamic Changes of Bacterial Communities and Microbial Association Networks in Ready-to-Eat Chicken Meat during Storage.

Ready-to-eat (RTE) chicken is a popular food in China, but its lack of food safety due to bacterial contamination remains a concern, and the dynamic changes of microbial association networks during storage are not fully understood. This study investigated the impact of storage time and temperature on bacterial compositions and microbial association networks in RTE chicken using 16S rDNA high-throughput sequencing. The results show that the predominant phyla present in all samples were Proteobacteria and Firmicutes, and the most abundant genera were Weissella, Pseudomonas and Proteus. Increased storage time and temperature decreased the richness and diversity of the microorganisms of the bacterial communities. Higher storage temperatures impacted the bacterial community composition more significantly. Microbial interaction analyses showed 22 positive and 6 negative interactions at 4 °C, 30 positive and 12 negative interactions at 8 °C and 44 positive and 45 negative interactions at 22 °C, indicating an increase in the complexity of interaction networks with an increase in the storage temperature. Enterobacter dominated the interactions during storage at 4 and 22 °C, and Pseudomonas did so at 22 °C. Moreover, interactions between pathogenic and/or spoilage bacteria, such as those between Pseudomonas fragi and Weissella viridescens, Enterobacter unclassified and Proteus unclassified, or those between Enterobacteriaceae unclassified and W.viridescens, were observed. This study provides insight into the process involved in RTE meat spoilage and can aid in improving the quality and safety of RTE meat products to reduce outbreaks of foodborne illness.

Niche differentiation of denitrifying anaerobic methane oxidation microbes in Taihu Lake of China

Denitrifying anaerobic methane oxidation (DAMO) microbes distribute widely and consume methane/nitrogen in freshwater environments. The survival preference of DAMO microbes directly affects their habitat preference, enabling them playing different roles in different environments. There are few studies regarding the preference and adaptability of DAMO microbes in the environment. In this work, the survival characteristics of DAMO microbes in Taihu Lake were studied. The relative abundance of DAMO archaea was relatively high in samples D7 and D8 of the moderately eutrophic region. The abundance of DAMO bacteria was 1.82 × 10 4 –6.11 × 10 6 copies g − 1 sediment, which was the highest in D1 of the mildly eutrophic region. The microbial association network analysis showed a significant difference in the connector number between the Moderate-NA (54 connectors) and Mild-NA (27 connectors), and DAMO bacteria played the connector role in the Mild-NA. The OTU numbers showing a positive and negative correlation with DAMO bacteria were 7 and 8 in Mild-NA, respectively, while 7 and 10 in Moderate-NA, showing a stronger competition relationship. For DAMO archaea, the corresponding OTUs in Mild-NA were 8 and 5, respectively, while 11 and 2 in Moderate-NA, showing a stronger cooperation association. DAMO microbes were differently affected by the antagonism of Rhodocyclaceae and Anammox bacteria. These results showed that DAMO bacteria and archaea had different survival strategies and displayed niche differentiation in the Taihu Lake. The results expanded our understanding of the ecological functions of DAMO microbes in freshwater and even global environment. • Niche differentiation of DAMO bacteria and archaea in Taihu Lake is evidenced. • DAMO bacteria get suitable niche and become key species in mildly eutrophic region. • DAMO archaea survive more suitably in the moderately eutrophic region. • Rhodocyclaceae and Anammox bacteria cause strong antagonism on DAMO microbes.

Meta-analysis of microbiome association networks reveal patterns of dysbiosis in diseased microbiomes

The human gut microbiome is composed of a diverse and dynamic population of microbial species which play key roles in modulating host health and physiology. While individual microbial species have been found to be associated with certain disease states, increasing evidence suggests that higher-order microbial interactions may have an equal or greater contribution to host fitness. To better understand microbial community dynamics, we utilize networks to study interactions through a meta-analysis of microbial association networks between healthy and disease gut microbiomes. Taking advantage of the large number of metagenomes derived from healthy individuals and patients with various diseases, together with recent advances in network inference that can deal with sparse compositional data, we inferred microbial association networks based on co-occurrence of gut microbial species and made the networks publicly available as a resource (GitHub repository named GutNet). Through our meta-analysis of inferred networks, we were able to identify network-associated features that help stratify between healthy and disease states such as the differentiation of various bacterial phyla and enrichment of Proteobacteria interactions in diseased networks. Additionally, our findings show that the contributions of taxa in microbial associations are disproportionate to their abundances and that rarer taxa of microbial species play an integral part in shaping dynamics of microbial community interactions. Network-based meta-analysis revealed valuable insights into microbial community dynamics between healthy and disease phenotypes. We anticipate that the healthy and diseased microbiome association networks we inferred will become an important resource for human-related microbiome research.

Effective data filtering is prerequisite for robust microbial association network construction.

Microorganisms do not exist as individual population in the environment. Rather, they form complex assemblages that perform essential ecosystem functions and maintain ecosystem stability. Besides the diversity and composition of microbial communities, deciphering their potential interactions in the form of association networks has attracted many microbiologists and ecologists. Much effort has been made toward the methodological development for constructing microbial association networks. However, microbial profiles suffer dramatically from zero values, which hamper accurate association network construction. In this study, we investigated the effects of zero-value issues associated with microbial association network construction. Using the TARA Oceans microbial profile as an example, different zero-value-treatment approaches were comparatively investigated using different correlation methods. The results suggested dramatic variations of correlation coefficient values for differently treated microbial profiles. Most specifically, correlation coefficients among less frequent microbial taxa were more affected, whichever method was used. Negative correlation coefficients were more problematic and sensitive to network construction, as many of them were inferred from low-overlapped microbial taxa. Consequently, microbial association networks were greatly differed. Among various approaches, we recommend sequential calculation of correlation coefficients for microbial taxa pairs by excluding paired zero values. Filling missing values with pseudo-values is not recommended. As microbial association network analyses have become a widely used technique in the field of microbial ecology and environmental science, we urge cautions be made to critically consider the zero-value issues in microbial data.