Microbial Network Analysis Research Articles

Methanol promotes the biodegradation of 2,2′,3,4,4′,5,5′-heptachlorobiphenyl (PCB 180) by the microbial consortium QY2: Metabolic pathways, toxicity evaluation and community response

As one of the most frequently detected PCB congeners in human adipose tissue, 2,2′,3,4,4′,5,5′-heptachlorobiphenyl (PCB 180) has attracted much attention. However, PCB 180 is difficult to be directly utilized by microorganisms due to its hydrophobicity and obstinacy. Herein, methanol (5 mM) as a co-metabolic carbon source significantly stimulated the degradation performance of microbial consortium QY2 for PCB 180 (51.9% higher than that without methanol addition). Six metabolic products including low-chlorinated PCBs and chlorobenzoic acid were identified during co-metabolic degradation, denoting that PCB 180 was metabolized via dechlorination, hydroxylation and ring-opening pathways. The oxidative stress and apoptosis induced by PCB 180 were dose-dependent, but the addition of methanol effectively promoted the tolerance of consortium QY2 to resist unfavorable environmental stress. Additionally, the significant reduction of intracellular reactive oxygen species (ROS) and enhancement of cell viability during methanol co-metabolic degradation proved that the degradation was a detoxification process. The microbial community and network analyses suggested that the potential PCB 180 degrading bacteria in the community (e.g., Achromobacter, Cupriavidus, Methylobacterium and Sphingomonas) and functional abundance of metabolic pathways were selectively enriched by methanol, and the synergies among species whose richness increased after methanol addition might dominate the degradation process. These findings provide new insights into the biodegradation of PCB 180 by microbial consortium.

Abundant bacterial subcommunity is structured by a stochastic process in an agricultural system with P fertilizer inputs

Soil microorganisms play an important role in agroecosystems and are related to ecosystem functioning. Nevertheless, little is understood about their community assembly and the major factors regulating stochastic and deterministic processes, particularly with respect to the comparison of abundant and rare bacterial subcommunities in agricultural systems. Here, we investigated the assembly of abundant and rare bacterial subcommunities in fields with different crops (maize and wheat) and phosphorus (P) fertilizer input at three different growth stages on the Loess Plateau. The high-throughput sequencing dataset was assessed using null and neutral community models. We found that abundant bacteria was governed by the stochastic process of homogenizing dispersal, but rare bacterial subcommunity was predominant by deterministic processes in maize and wheat fields due to broader niche breadths of abundant species. Soil nitrogen (N) and P also determined the assembly of abundant and rare soil subcommunities. The relative abundance and composition of the abundant and rare bacterial subcommunities were also influenced by soil nutrients (soil available P (AP) and NO3−-N) and agricultural practices (P fertilization and crop cultivation). In addition, the abundant bacterial community was more susceptible to P fertilizer input than that of the rare bacteria, and a higher relative abundance of abundant bacteria was observed in the P70 treatment both in maize and wheat soils. The microbial co-occurrence network analysis indicated that the maize field and low nutrient treatment exhibited stronger associations and that the abundant bacteria showed fewer interconnections. This study provides new insights toward understanding the mechanisms for the assembly of abundant and rare bacterial taxa in dryland cropping systems, enhancing our understanding of ecosystem diversity theory in microbial ecology.

Obese dogs exhibit different fecal microbiome and specific microbial networks compared with normal weight dogs

Canine obesity is a major health concern that predisposes dogs to various disorders. The fecal microbiome has been attracting attention because of their impact on energy efficiency and metabolic disorders of host. However, little is known about specific microbial interactions, and how these may be affected by obesity in dogs. The objective of this study was to investigate the differences in fecal microbiome and specific microbial networks between obese and normal dogs. A total of 20 beagle dogs (males = 12, body weight [BW]: 10.5 ± 1.08 kg; females = 8, BW: 11.3 ± 1.71 kg; all 2-year-old) were fed to meet the maintenance energy requirements for 18 weeks. Then, 12 beagle dogs were selected based on body condition score (BCS) and divided into two groups: high BCS group (HBCS; BCS range: 7–9, males = 4, females = 2) and normal BCS group (NBCS; BCS range: 4–6, males = 4, females = 2). In the final week of the experiment, fecal samples were collected directly from the rectum, before breakfast, for analyzing the fecal microbiome using 16S rRNA gene amplicon sequencing. The HBCS group had a significantly higher final BW than the NBCS group (P < 0.01). The relative abundances of Faecalibacterium, Phascolarctobacterium, Megamonas, Bacteroides, Mucispirillum, and an unclassified genus within Ruminococcaceae were significantly higher in the HBCS group than those in the NBCS group (P < 0.05). Furthermore, some Kyoto Encyclopedia of Genes and Genomes (KEGG) modules related to amino acid biosynthesis and B vitamins biosynthesis were enriched in the HBCS group (P < 0.10), whereas those related to carbohydrate metabolism were enriched in the NBCS group (P < 0.10). Microbial network analysis revealed distinct co-occurrence and mutually exclusive interactions between the HBCS and NBCS groups. In conclusion, several genera related to short-chain fatty acid production were enriched in the HBCS group. The enriched KEGG modules in the HBCS group enhanced energy efficiency through cross-feeding between auxotrophs and prototrophs. However, further studies are needed to investigate how specific networks can be interpreted in the context of fermentation characteristics in the lower gut and obesity in dogs.

Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering.

In recent years, unsupervised analysis of microbiome data, such as microbial network analysis and clustering, has increased in popularity. Many new statistical and computational methods have been proposed for these tasks. This multiplicity of analysis strategies poses a challenge for researchers, who are often unsure which method(s) to use and might be tempted to try different methods on their dataset to look for the "best" ones. However, if only the best results are selectively reported, this may cause over-optimism: the "best" method is overly fitted to the specific dataset, and the results might be non-replicable on validation data. Such effects will ultimately hinder research progress. Yet so far, these topics have been given little attention in the context of unsupervised microbiome analysis. In our illustrative study, we aim to quantify over-optimism effects in this context. We model the approach of a hypothetical microbiome researcher who undertakes four unsupervised research tasks: clustering of bacterial genera, hub detection in microbial networks, differential microbial network analysis, and clustering of samples. While these tasks are unsupervised, the researcher might still have certain expectations as to what constitutes interesting results. We translate these expectations into concrete evaluation criteria that the hypothetical researcher might want to optimize. We then randomly split an exemplary dataset from the American Gut Project into discovery and validation sets multiple times. For each research task, multiple method combinations (e.g., methods for data normalization, network generation, and/or clustering) are tried on the discovery data, and the combination that yields the best result according to the evaluation criterion is chosen. While the hypothetical researcher might only report this result, we also apply the "best" method combination to the validation dataset. The results are then compared between discovery and validation data. In all four research tasks, there are notable over-optimism effects; the results on the validation data set are worse compared to the discovery data, averaged over multiple random splits into discovery/validation data. Our study thus highlights the importance of validation and replication in microbiome analysis to obtain reliable results and demonstrates that the issue of over-optimism goes beyond the context of statistical testing and fishing for significance.

Altered gut microbiome composition by appendectomy contributes to colorectal cancer

Appendectomy impacts the homeostasis of gut microbiome in patients. We aimed to study the role of appendectomy in colorectal cancer (CRC) risk through causing gut microbial dysbiosis. Population-based longitudinal study (cohort 1, n = 129,155) showed a 73.0% increase in CRC risk among appendectomy cases throughout 20 years follow-up (Adjusted sub-distribution hazard ratio (SHR) 1.73, 95% CI 1.49–2.01, P < 0.001). Shotgun metagenomic sequencing was performed on fecal samples from cohort 2 (n = 314). Gut microbial dysbiosis in appendectomy subjects was observed with significant enrichment of 7 CRC-promoting bacteria (Bacteroides vulgatus, Bacteroides fragilis, Veillonella dispar, Prevotella ruminicola, Prevotella fucsa, Prevotella dentalis, Prevotella denticola) and depletion of 5 beneficial commensals (Blautia sp YL58, Enterococcus hirae, Lachnospiraceae bacterium Choco86, Collinsella aerofaciens, Blautia sp SC05B48). Microbial network analysis showed increased correlation strengths among enriched bacteria and their enriched oncogenic pathways in appendectomy subjects compared to controls. Of which, B. fragilis was the centrality in the network of the enriched bacteria. We further confirmed that appendectomy promoted colorectal tumorigenesis in mice by causing gut microbial dysbiosis and impaired intestinal barrier function. Collectively, this study revealed appendectomy-induced microbial dysbiosis characterized by enriched CRC-promoting bacteria and depleted beneficial commensals, signifying that the gut microbiome may play a crucial role in CRC development induced by appendectomy.

Investigation of the nitrogen removal performance and microbial community structure in a full-scale A/O1/H/O2 coking wastewater treatment system.

Biological treatment processes are an effective method for removing the nitrogen-containing contaminants that exist in coking wastewater. However, little is known about microbial composition and keystone taxa involved in biological nitrogen removal processes. In order to improve the removal efficiency of nitrogen-containing contaminants in anaerobic-aerobic-hydrolytic-aerobic (A/O1/H/O2) system, the microbial composition and interactions of keystone taxa should be clarified. The present work clarifies the removal performance of nitrogen-containing contaminants in the A/O1/H/O2 system, identifies the microbial community involved in various bioreactors, and reveals the keystone taxa within the microbial communities. Combined the processes of ammoniation, denitrification, and nitrification, total nitrogen decreased from 248 to 31 mg L-1 and achieved a removal efficiency of 87.5% in the full-scale A/O1/H/O2 system. High-throughput MiSeq sequencing revealed that Proteobacteria was the most abundant phylum in the A/O1/H/O2 system with relative abundances of 24%-50%. Thiobacillus dominated in bioreactors A and O1 with relative abundances of 2.90% and 4.44%, respectively, while Nitrospira was identified as the most dominant genus in bioreactors H and O2, accounting for 13.33% and 18.38%, respectively. The microbial community composition and co-occurrence network analysis showed that the keystone taxa belonged to Thiobacillus, Nitrospira, Bdellovibrio, Planctomyces, Desulfotomaculum, and Sphingobium, which are related to nitrogen degradation.

Metagenomic insights into role of red mud in regulating fate of compost antibiotic resistance genes mediated by both direct and indirect ways

In this study, the amendment of red mud (RM) in dairy manure composting on the fate of antibiotic resistance genes (ARGs) by both direct (bacteria community, mobile genetic elements and quorum sensing) and indirect ways (environmental factors and antibiotics) was analyzed. The results showed that RM reduced the total relative abundances of 10 ARGs and 4 mobile genetic elements (MGEs). And the relative abundances of total ARGs and MGEs decreased by 53.48% and 22.30% in T (with RM added) on day 47 compared with day 0. Meanwhile, the modification of RM significantly increased the abundance of lsrK, pvdQ and ahlD in quorum quenching (QQ) and decreased the abundance of luxS in quorum sensing (QS) (P < 0.05), thereby attenuating the intercellular genes frequency of communication. The microbial community and network analysis showed that 25 potential hosts of ARGs were mainly related to Firmicutes, Proteobacteria and Actinobacteria. Redundancy analysis (RDA) and structural equation model (SEM) further indicated that RM altered microbial community structure by regulating antibiotic content and environmental factors (temperature, pH, moisture content and organic matter content), which then affected horizontal gene transfer (HGT) in ARGs mediated by QS and MGEs. These results provide new insights into the dissemination mechanism and removal of ARGs in composting process.

A longitudinal census of the bacterial community in raw milk correlated with Staphylococcus aureus clinical mastitis infections in dairy cattle

BackgroundStaphylococcus aureus is a common cause of clinical mastitis (CM) in dairy cattle. Optimizing the bovine mammary gland microbiota to resist S. aureus colonization is a growing area of research. However, the details of the interbacterial interactions between S. aureus and commensal bacteria, which would be required to manipulate the microbiome to resist infection, are still unknown. This study aims to characterize changes in the bovine milk bacterial community before, during, and after S. aureus CM and to compare bacterial communities present in milk between infected and healthy quarters.MethodsWe collected quarter-level milk samples from 698 Holstein dairy cows over an entire lactation. A total of 11 quarters from 10 cows were affected by S. aureus CM and milk samples from these 10 cows (n = 583) regardless of health status were analyzed by performing 16S rRNA gene amplicon sequencing.ResultsThe milk microbiota of healthy quarters was distinguishable from that of S. aureus CM quarters two weeks before CM diagnosis via visual inspection. Microbial network analysis showed that 11 OTUs had negative associations with OTU0001 (Staphylococcus). A low diversity or dysbiotic milk microbiome did not necessarily correlate with increased inflammation. Specifically, Staphylococcus xylosus, Staphylococcus epidermidis, and Aerococcus urinaeequi were each abundant in milk from the quarters with low levels of inflammation.ConclusionOur results show that the udder microbiome is highly dynamic, yet a change in the abundance in certain bacteria can be a potential indicator of future S. aureus CM. This study has identified potential prophylactic bacterial species that could act as a barrier against S. aureus colonization and prevent future instances of S. aureus CM.

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.

Experimental temperatures shape host microbiome diversity and composition.

Global climate change has led to more extreme thermal events. Plants and animals harbour diverse microbial communities, which may be vital for their physiological performance and help them survive stressful climatic conditions. The extent to which microbiome communities change in response to warming or cooling may be important for predicting host performance under global change. Using a meta-analysis of 1377 microbiomes from 43 terrestrial and aquatic species, we found a decrease in the amplicon sequence variant-level microbiome phylogenetic diversity and alteration of microbiome composition under both experimental warming and cooling. Microbiome beta dispersion was not affected by temperature changes. We showed that the host habitat and experimental factors affected microbiome diversity and composition more than host biological traits. In particular, aquatic organisms-especially in marine habitats-experienced a greater depletion in microbiome diversity under cold conditions, compared to terrestrial hosts. Exposure involving a sudden long and static temperature shift was associated with microbiome diversity loss, but this reduction was attenuated by prior-experimental lab acclimation or when a ramped regime (i.e., warming) was used. Microbial differential abundance and co-occurrence network analyses revealed several potential indicator bacterial classes for hosts in heated environments and on different biome levels. Overall, our findings improve our understanding on the impact of global temperature changes on animal and plant microbiome structures across a diverse range of habitats. The next step is to link these changes to measures of host fitness, as well as microbial community functions, to determine whether microbiomes can buffer some species against a more thermally variable and extreme world.

Effect of different carbon sources on sulfate reduction and microbial community structure in bioelectrochemical systems.

Microbial electrolysis cells (MECs) have rapidly developed into a promising technology to treat sulfate-rich wastewater that lacks electron donors. Hence, a better understanding of the effect on the microbial community structure caused by different sources in bioelectrochemical systems is required. This study sought to investigate the effect of different carbon sources (NaHCO3, ethanol, and acetate were employed as sole carbon source respectively) on the performance of sulfate-reducing biocathodes. The sulfate reduction efficiency enhanced by the bioelectrochemical systems was 8.09 - 11.57% higher than that of open-circuit reference experiments. Furthermore, the optimum carbon source was ethanol with a maximum sulfate reduction rate of 170mg L-1 d-1 in the bioelectrochemical systems. The different carbon sources induced significant differences in sulfate reduction efficiency as demonstrated by the application of a micro-electrical field. Microbial community structure and network analysis revealed that all three kinds of carbon source systems enriched large proportions of sulfate-reducing bacteria and electroactive bacteria but were significantly distinct in composition. The dominant sulfate-reducing bacteria that use NaHCO3 and acetate as carbon sources were Desulfobacter and Desulfobulbus, whereas those that use ethanol as carbon source were Desulfomicrobium and Desulfovibrio. Our results suggest that ethanol is a more suitable carbon source for sulfate reduction in bioelectrochemical systems.

Co-occurrence network of microbial communities affected by application of anaerobic fermentation residues during phytoremediation of ionic rare earth tailings area

The long-term exploitation of ionic rare earth elements (REEs) in southern China has produced a large-scale of abandoned tailings area. While the application of anaerobic fermentation residues to cultivate economically valuable remediation plants (e.g. energy plant) has become a hotspot due to their merits in low-cost and sustainability in recent years, the succession and co-occurrence patterns of these microbial communities remain unclear. In this study, soil samples were collected from the sustainable restoration area, natural restoration area and tailings area. The composition and diversity of bacterial and fungal communities on five soil samples were evaluated using high-throughput sequencing technology. The results shown that the phytoremediation with anaerobic fermentation residues could significantly improve the physicochemical properties (especially for soil nutrients) and microbial diversity of soil within 3 years, while these parameters in natural restoration area were lower. The nonmetric multidimensional scaling (NMDS) ordinations revealed the shifts of microbial communities depending on soil physicochemical properties and plant species, and soil nutrients were the main factors affecting the microbial variation explained by the variation partition analysis (VPA). The soil nutrient accumulation obviously changed the proportion of oligotrophic and copiotrophic groups, among which the copiotrophic groups were significantly increased, such as Proteobacteria, Bacteroidetes, Gemmatimonadetes and Glomeromycota. The microbial co-occurrence network analysis indicated that application of anaerobic fermentation residues could significantly improve the topological properties and the stability of microbial network. The copiotrophic groups (e.g. Proteobacteria, Ascomycota) became the key to assemble stable network structure. Moreover, herbaceous plants could increase the proportion of fungi (e.g. Ascomycota) in microbial network, which improved the topological properties with bacteria synergistically. Therefore, the soil environment of REEs tailings area was effectively optimized by anaerobic fermentation residues and herbaceous plants, which furthered understanding of co-occurrence pattern and mutualistic relationships of microbial communities during sustainable restoration.

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.

Storm promotes the dissemination of antibiotic resistome in an urban lagoon through enhancing bio-interactions.

Antibiotic-resistance genes (ARGs) and resistant bacteria (ARB) are abundant in stormwater that could cause serious infections, posing a potential threat to public health. However, there is no inference about how stormwater contributes to ARG profiles as well as the dynamic interplay between ARGs and bacteria via vertical gene transfer (VGT) or horizontal gene transfer (HGT) in urban water ecosystems. In this study, the distribution of ARGs, their host communities, and the source and community assembly process of ARGs were investigated in Yundang Lagoon (China) via high-throughput quantitative PCR, 16S rRNA gene amplicon sequencing, and application of SourceTracker before, after and recovering from an extreme precipitation event (132.1mm). The abundance of ARGs and mobile genetic elements (MGEs) was the highest one day after precipitation and then decreased 2days after precipitation and so on. Based on SourceTracker and NMDS analysis, the ARG and bacterial communities in lagoon surface water from one day after precipitation were mainly contributed by the wastewater treatment plant (WWTP) influent and effluent. However, the contribution of WWTP to ARG communities was minor 11days after the precipitation, suggesting that the storm promoted the ARG levels by introducing the input of ARGs, MGEs, and ARB from point and non-point sources, such as sewer overflow and land-applied manure. Based on a novel microbial network analysis framework, the contribution of positive biological interactions between ARGs and MGEs or bacteria was the highest one day after precipitation, indicating a promoted VGT and HGT for ARG dissemination. The microbial networks deconstructed 11days after precipitation, suggesting the stormwater practices (e.g., tide gate opening, diversion channels, and pumping) alleviated the spread of ARGs. These results advanced our understanding of the distribution and transport of ARGs associated with their source in urban stormwater runoff.

Efficient biodegradation of acetoacetanilide in hypersaline wastewater with a synthetic halotolerant bacterial consortium

The high concentrations of salt and refractory toxic organics in industrial wastewater seriously restrict biological treatment efficiency and functional stability. However, how to construct a salt-tolerant biocatalytic community and realize the decarbonization coupled with detoxification toward green bio-enhanced treatment, has yet to be well elucidated. Here, acetoacetanilide (AAA), an important intermediate for many dyes and medicine synthesis, was used as the model amide pollutant to elucidate the directional enrichment of halotolerant degradative communities and the corresponding bacterial interaction mechanism. Combining microbial community composition and molecular ecological network analyses as well as the biodegradation efficiencies of AAA and its hydrolysis product aniline (AN) of pure strains, the core degradative bacteria were identified during the hypersaline AAA degradation process. A synthetic bacterial consortium composed of Paenarthrobacter, Rhizobium, Rhodococcus, Delftia and Nitratireductor was constructed based on the top-down strategy to treat AAA wastewater with different water quality characteristics. The synthetic halotolerant consortium showed promising treatment ability toward the simulated AAA wastewater (AAA 100–500 mg/L, 1–5% salinity) and actual AAA mother liquor. Additionally, the comprehensive toxicity of AAA mother liquor significantly reduced after biological treatment. This study provides a green biological approach for the treatment of hypersaline and high concentration of organics wastewater.

Rapid evolution of a novel protective symbiont into keystone taxon in Caenorhabditis elegans microbiota

Protective microbes have a major role in shaping host–pathogen interactions, but their relative importance in the structure of the host microbiota remains unclear. Here, we used a network approach to characterize the impact of a novel, experimentally evolved ‘protective microbial symbiont’ (Enterococcus faecalis) on the structure and predicted function of the natural microbiota of the model organism Caenorhabditis elegans. We used microbial network analysis to identify keystone taxa and describe the hierarchical placement of protective and non-protective symbionts in the microbiota. We found that early colonization with symbionts produce statistically significant changes in the structure of the community. Notably, only the protective E. faecalis became a keystone taxon in the nematode microbiota. Non-protective lineages of the same bacterial species remained comparatively unimportant to the community. Prediction of functional profiles in bacterial communities using PICRUSt2 showed that the presence of highly protective E. faecalis decreased the abundance of ergothioneine (EGT) biosynthesis pathway involved in the synthesis of the antioxidant molecule EGT, a potential public good. These data show that in addition to direct antagonism with virulent pathogens, keystone protective symbionts are linked to modified bacterial community structure and possible reductions in public goods, potentially driving decreased antioxidant defense. We suggest that this response could suppress infection via wholesale microbial community changes to further benefit the host. These findings extend the concept of protective symbionts beyond bodyguards to ecosystem engineers.

Namco: a microbiome explorer.

16S rRNA gene profiling is currently the most widely used technique in microbiome research and allows the study of microbial diversity, taxonomic profiling, phylogenetics, functional and network analysis. While a plethora of tools have been developed for the analysis of 16S rRNA gene data, only a few platforms offer a user-friendly interface and none comprehensively covers the whole analysis pipeline from raw data processing down to complex analysis. We introduce Namco, an R shiny application that offers a streamlined interface and serves as a one-stop solution for microbiome analysis. We demonstrate Namco’s capabilities by studying the association between a rich fibre diet and the gut microbiota composition. Namco helped to prove the hypothesis that butyrate-producing bacteria are prompted by fibre-enriched intervention. Namco provides a broad range of features from raw data processing and basic statistics down to machine learning and network analysis, thus covering complex data analysis tasks that are not comprehensively covered elsewhere. Namco is freely available at https://exbio.wzw.tum.de/namco/.

Cross-kingdom co-occurrence networks in the plant microbiome: Importance and ecological interpretations.

Microbial co-occurrence network analysis is being widely used for data exploration in plant microbiome research. Still, challenges lie in how well these microbial networks represent natural microbial communities and how well we can interpret and extract eco-evolutionary insights from the networks. Although many technical solutions have been proposed, in this perspective, we touch on the grave problem of kingdom-level bias in network representation and interpretation. We underscore the eco-evolutionary significance of using cross-kingdom (bacterial-fungal) co-occurrence networks to increase the network’s representability of natural communities. To do so, we demonstrate how ecosystem-level interpretation of plant microbiome evolution changes with and without multi-kingdom analysis. Then, to overcome oversimplified interpretation of the networks stemming from the stereotypical dichotomy between bacteria and fungi, we recommend three avenues for ecological interpretation: (1) understanding dynamics and mechanisms of co-occurrence networks through generalized Lotka-Volterra and consumer-resource models, (2) finding alternative ecological explanations for individual negative and positive fungal-bacterial edges, and (3) connecting cross-kingdom networks to abiotic and biotic (host) environments.

Interkingdom Plant–Soil Microbial Ecological Network Analysis under Different Anthropogenic Impacts in a Tropical Rainforest

Plants and their associated soil microorganisms interact with each other and form complex relationships. The effects of slash-and-burn agriculture and logging on aboveground plants and belowground microorganisms have been extensively studied, but research on plant–microbial interkingdom ecological networks is lacking. In this study, using old growth forest as a control, we used metagenomic data (ITS and 16S rRNA gene amplified sequences) and plant data to obtain interdomain species association patterns for three different soil disturbance types (slash-and-burn, clear cutting and selective cutting) in a tropical rainforest based on interdomain ecological network (IDEN) analysis. Results showed that the soil bacterial–fungal and plant–microbe ecological networks had different topological properties among the three forest disturbance types compared to old growth forest. More nodes, links, higher modularity and negative proportion were found in the selective cutting stand, indicating higher stability with increasing antagonistic relationships and niche differentiation. However, the area of slash-and-burn forest yield opposite results. Network module analysis indicated that different keystone species were found in the four forest types, suggesting alternative stable states among them. Different plant species had more preferential associations with specific fungal taxa than bacterial taxa at the genus level and plant–microbe associations lagged behind bacterial–fungal associations. Overall, compared with old growth forests, the bacterial–fungal and plant–microbe ecological networks in the slash-and-burn and clear cutting stands were simpler, while the network in the selective cutting stand was more complex. Understanding the relationships between aboveground plants and belowground microorganisms under differing disturbance patterns in natural ecosystems will help in better understanding the surrounding ecosystem functions of ecological networks.

Effects of iron-based substrate on coupling of nitrification, aerobic denitrification and Fe(II) autotrophic denitrification in tidal flow constructed wetlands

The aerobic properties of nitrification and the anaerobic properties of denitrification in constructed wetlands are difficult to reconcile. In this study, two constructed wetlands were constructed with pyrite and steel slag in combination with zeolite, and their respective nitrification and denitrification capacities were evaluated under different tidal strategies. The steel slag wetland achieved 70.89 % and 46.04 % removal rates of NH4+-N and total nitrogen (TN), and the carbon consumption of denitrification was 1.51 mg BOD/mgN, which was better than pyrite wetland. Microbial analysis showed that Fe(II) autotrophic denitrification and aerobic denitrification occurred in both wetlands, and they were coupled with nitrification to achieve simultaneous removal of NH4+-N and TN. Microbial co-occurrence network and k-core decomposition analysis indicated that the core genus of steel slag wetlands was nitrifying bacteria. This study provides new insights into the application of tidal flow wetlands to treat rural sewage.