Disentangling Interactions in the Microbiome: A Network Perspective

Vadose-zone characteristic pollutants distribution, microbial community structure and functionality changes in response to long-term leachate pollution of an informal landfill site

The study embarked on a comprehensive examination of the evolution and diversity of microorganisms within long-term leachate pollution environments, with a focus on varying depths and levels of contamination, and its linkage to soil characteristics and the presence of heavy metals. It was observed that microbial diversity presented distinct cross-depth trend, where archaeal communities were found to be particularly sensitive to alterations in soil depth. Noteworthily, Euryarchaeota increased by 4.82 %, 7.64 % and 9.87 % compared with topsoil. The abundance of Tahumarchaeota was successively reduced by 5.79 %, 9.58 %, and 12.66 %. The bacterial community became more sensitive to leachate pollution, and the abundance of Protebacteria in contaminated soil decreased by 10.27 %, while the abundance of Firmicutes increased by 7.46 %. The bacterial genus Gemmobacter, Chitinophaga and Rheinheimera; the archaeal genus Methanomassiliicoccus and Nitrosopumilus; along with the fungal genus Goffeauzyma, Gibberella, and Setophaeosphaeria emerged as pivotal biological markers for their respective domains, underpinning the biogeochemical dynamics of these environments. Furthermore, the study highlighted that geochemical factors, specifically nitrate (NO₃--N) levels and humic acid (HA) fractions, played crucial roles in modulating the composition and metabolic potential of these communities. Predictive analyses of functional potentials suggested that the N functional change of archaea was more pronounced, with anaerobic ammonia oxidation and nitrification decreased by 15.78 % and 14.62 %, respectively. Overall, soil characteristics alone explained 57.9 % of the total variation in the bacterial community structure. For fungal communities within contaminated soil, HMs were the primary contributors, explaining 46.9 % of the variability, while soil depth accounting for 6.4 % of the archaeal variation. This research enriches the understanding of the complex interrelations between heavy metal pollution, soil attributes, and microbial communities, paving the way for informed strategies in managing informal landfill sites effectively.

Long-Term Photochemical and Microbial Alterations Lead to the Compositional Convergence of Algal and Terrestrial Dissolved Organic Matter

Lakes are expected to become more active in processing dissolved organic matter (DOM), but the fate of DOM with different origins remains poorly constrained. We conducted long-term incubation experiments (∼1 year) with sole light, sole microbial, and combined light and microbial treatments using DOM from algal and terrestrial sources (DOMa and DOMt, respectively). Fourier transform ion cyclotron resonance mass spectrometry and 16s rRNA were used to analyze the DOM molecular composition and bacterial community, respectively. We observed that DOMa and DOMt converged toward a similar composition under the combined light and microbial treatment, driven by the removal of source-specific compositions along with the production of refractory, carboxylic-rich alicyclic molecules (CRAM). For CRAM enrichment, microbial processes played a greater role for DOMa, while phototransformation was more important for DOMt. The co-occurrence patterns between DOM molecules and bacteria showed that DOM molecular composition influenced the bacterial community. More complex DOM-bacteria interactions were observed for DOMt compared to DOMa, suggesting that greater bacterial cooperation was necessary for transforming DOMt. Collectively, these findings offer new insights into the mechanisms underlying the uniformity of DOM from various sources through prolonged environmental transformations in lakes.

Integrated large-scale metagenome assembly and multi-kingdom network analyses identify sex differences in the human nasal microbiome

BACKGROUND

Respiratory diseases impose an immense health burden worldwide. Epidemiological studies have revealed extensive disparities in the incidence and severity of respiratory tract infections between men and women. It has been hypothesized that there might also be a nasal microbiome axis contributing to the observed sex disparities.

RESULTS

Here, we study the nasal microbiome of healthy young adults in the largest cohort to date with 1593 individuals, using shotgun metagenomic sequencing. We compile the most comprehensive reference catalog for the nasal bacterial community containing 4197 metagenome-assembled genomes and integrate the mycobiome, to provide a valuable resource and a more holistic perspective for the understudied human nasal microbiome. We systematically evaluate sex differences and reveal extensive sex-specific features in both taxonomic and functional levels in the nasal microbiome. Through network analyses, we capture markedly higher ecological stability and antagonistic potentials in the female nasal microbiome compared to the male's. The analysis of the keystone bacteria reveals that the sex-dependent evolutionary characteristics might have contributed to these differences.

CONCLUSIONS

In summary, we construct the most comprehensive catalog of metagenome-assembled-genomes for the nasal bacterial community to provide a valuable resource for the understudied human nasal microbiome. On top of that, comparative analysis in relative abundance and microbial co-occurrence networks identify extensive sex differences in the respiratory tract community, which may help to further our understanding of the observed sex disparities in the respiratory diseases.

The microbial communities of the rust layer were influenced by seawater microbial communities

To reveal the responsible microorganisms of microbiologically-influenced-corrosion (MIC), using 16S rRNA and ITS sequencing techniques, we investigated the bacterial and fungal communities in rust layer and seawater. Results show that the corrosion-related genera of Erythrobacter, norank_f__Rhodothermaceae, and Acinetobacter bacteria, as well as Aspergillus fungi, were overrepresented in the rust layer, along with the Pseudoalteromonas and Marinobacterium bacteria in seawater, and Ramlibacter, Aquimarina, and Williamsia bacteria were first detected in the rust layer. SourceTracker analysis revealed that approximately 23.08% of bacteria and 21.48% of fungi originated from seawater. Stochastic processes governed the rust layer and seawater microbial communities, and network analysis showed coexistence and interaction among bacterial and fungal communities. These results indicate that the composition of microbial communities in the rust layer was influenced by the marine environmental microbial communities, which can provide basic data support for the control of MIC in marine-related projects.

Enhanced salt tolerance in Glycyrrhiza uralensis Fisch. via Bacillus subtilis inoculation alters microbial community

The widespread prevalence of saline environments poses a significant global environmental challenge. Salt stress, induced by saline soils, disrupts soil microecology and affects the plant-microbe-soil cycling process. Utilizing microbial fungicides stands as a primary strategy to mitigate salt stress-induced damage to plants and soils. This study investigated the influence of Bacillus subtilis (Bs) inoculation on the microbial community, assembly processes, and functional changes in bacteria and fungi in Glycyrrhiza uralensis Fisch. (licorice) seedlings under varying salt stress levels, primarily employing microbiomics techniques. Soil enzyme activities displayed a declining trend with increasing salt stress, which was mitigated by Bs inoculation. Microbiome analysis revealed a significant increase in bacterial and fungal operational taxonomic units, particularly in Ascomycetes and Nitrogen-fixing Bacteria, thereby enhancing soil denitrification. The abundance of Proteobacteria, Actinobacteriota, Bacteroidota, and Firmicutes in bacteria, as well as Ascomycota in fungi, increased with higher salt stress levels, a process facilitated by Bs inoculation. However, functional predictions indicated a reduction in the relative abundance of Dung Saprotrophs with Bs inoculation. Salt stress disrupted soil assembly processes, showcasing a continuous decline in diffusion limitation with increased salt concentration, where Bs inoculation reached a peak under moderate stress. In summary, this research elucidates the communication mechanism of Bs in enhancing salt tolerance in licorice from a microbiome perspective, contributing to a comprehensive understanding of abiotic and biotic factors.IMPORTANCELicorice is a herb that grows in deserts or saline soils. Enhancing the salt tolerance of licorice is necessary to maintain the quality of cultivated licorice and to ensure the supply of medicinal herbs. In the past, we have demonstrated the effectiveness of inoculation with Bacillus subtilis (Bs) to enhance the salt tolerance of licorice and revealed the key metabolic pathways for the development of salt tolerance through multi-omics. In this study, we used the microbiomics approach to reveal the plant-microbe-soil interactions at the level of inoculation of Bs affecting the dynamics of soil microbial communities from bacterial and fungal perspectives, thus bridging the interactions between biotic and abiotic factors.

Networks as tools for defining emergent properties of microbiomes and their stability

The potential promise of the microbiome to ameliorate a wide range of societal and ecological challenges, from disease prevention and treatment to the restoration of entire ecosystems, hinges not only on microbiome engineering but also on the stability of beneficial microbiomes. Yet the properties of microbiome stability remain elusive and challenging to discern due to the complexity of interactions and often intractable diversity within these communities of bacteria, archaea, fungi, and other microeukaryotes. Networks are powerful tools for the study of complex microbiomes, with the potential to elucidate structural patterns of stable communities and generate testable hypotheses for experimental validation. However, the implementation of these analyses introduces a cascade of dichotomies and decision trees due to the lack of consensus on best practices. Here, we provide a road map for network-based microbiome studies with an emphasis on discerning properties of stability. We identify important considerations for data preparation, network construction, and interpretation of network properties. We also highlight remaining limitations and outstanding needs for this field. This review also serves to clarify the varying schools of thought on the application of network theory for microbiome studies and to identify practices that enhance the reproducibility and validity of future work. Video Abstract.

Cadmium contamination decreased bacterial network complexity and stability in coastal reclamation areas

Cadmium(Cd) contamination can exert significantly adverse effects on soil microbiota in reclaimed areas, however, its effects on bacterial network structure are still limitedly understood. Here we collected soil samples from typical reclaimed wetlands (RW) and ditch wetlands (DW) in coastal reclamation areas and examined the effects of Cd contamination on the bacterial network complexity and stability. The results showed that the bacterial networks were destabilized by the Cd contamination, while bacteria in DW soils showed robust invulnerability characterized by higher node constancy and compositional stability compared with RW soils. Soil bacteria resisted Cd stress by forming a network with intensive connections in the module but sparser connections among the modules. Especially, network modularity was higher in DW soils than in RW soils, but made it more vulnerable to nodes removal. In addition, Cd contamination promoted bacterial positive cohesion but decreased negative cohesion in RW soils. Flavobacteriaceae, Xanthomonadaceae, and Alcaligenaceae were identified as core phylotypes, which played pivotal roles in regulating interspecies interactions due to higher contributions to cohesion and significant correlations with soil nutrients. The findings of this work indicate the changes of bacterial network structure and the indispensable role of core phylotypes in regulating interactions and maintaining network sustainability under Cd contamination.

Exploring optimal incubation conditions and characteristics of methane oxidizing organisms in deep-sea environments

Anaerobic methanotrophic archaea (ANME) play key roles in buffering the methane budget in the deep-sea environment. This study aimed to explore the optimal environmental conditions for ANME enrichment. The result showed that the sample at 10.5 MPa contained the largest copy numbers of methyl-coenzyme M reductase alpha subunit (mcrA) gene (1.1 × 106 copies/g) compared to any other pressures and the sample at 4 °C contained higher mcrA gene (1.6 × 106 copies/g) than other temperatures. The optimal enrichment pressure for ANME-2c is 10.5 MPa at 4 °C, with an optimal subsequent incubation for ANME-2c less than 211days. Moreover, the beta nearest taxon index was significantly correlated with the incubation time (P<0.05). Total inorganic carbon and sulfate ion were key environmental factors driving community construction. This study offers insights into how ANME-2c was enriched and how species coexist in shared habitats during enrichment.

Enhancing total nitrogen removal in constructed wetlands: A Comparative study of iron ore and biochar amendments

Efficient nitrogen removal in constructed wetlands (CWs) remains challenging when treating agricultural runoff with a low carbon-to-nitrogen ratio (C/N). However, using biochar, iron ore, and FeCl3-modified biochar (Fe-BC) as amendments could potentially improve total nitrogen (TN) removal efficiency in CWs, but the underlying mechanisms associated with adding these substrates are unclear. In this study, five CWs: quartz sand constructed wetland (Control), biochar constructed wetland, Fe-BC constructed wetland, iron ore constructed wetland, and iron ore + biochar constructed wetland, were built to compare their treatment performance. The rhizosphere microbial community compositions and their co-occurrence networks were analyzed to reveal the underlying mechanisms driving their treatment performance. The results showed that iron ore was the most efficient amendment, although all treatments increased TN removal efficiency in the CWs. Ammonia-oxidizing, heterotrophic denitrifying, nitrate-dependent anaerobic ferrous oxidizing (NAFO), and Feammox bacteria abundance was higher in the iron ore system and led to the simultaneous removal of NH4+-N, NO3--N, and NO2--N. Visual representations of the co-occurrence networks further revealed that there was an increase in cooperative mutualism (the high proportion of positive links) and more complex interactions among genera related to the nitrogen and iron cycle (especially ammonia-oxidizing bacteria, heterotrophic denitrifying bacteria, NAFO bacteria, and Feammox bacteria) in the iron ore system, which ultimately contributed to the highest TN removal efficiency. This study provides critical insights into how different iron ore or biochar substrates could be used to treat agricultural runoff in CWs.

Functional redundancy and niche specialization in honeybee and Varroa microbiomes

The honeybee (Apis mellifera) is a key pollinator critical to global agriculture, facing threats from various stressors, including the ectoparasitic Varroa mite (Varroa destructor). Previous studies have identified shared bacteria between Varroa mites and honeybees, yet it remains unclear if these bacteria assemble similarly in both species. This study builds on existing knowledge by investigating co-occurrence patterns in the microbiomes of both Varroa mites and honeybees, shedding light on potential interactions. Leveraging 16S rRNA datasets, we conducted co-occurrence network analyses, explored Core Association Networks (CAN) and assess network robustness. Comparative network analyses revealed structural differences between honeybee and mite microbiomes, along with shared core features and microbial motifs. The mite network exhibited lower robustness, suggesting less resistance to taxa extension compared to honeybees. Furthermore, analyses of predicted functional profiling and taxa contribution revealed that common central pathways in the metabolic networks have different taxa contributing to Varroa mites and honeybee microbiomes. The results show that while both microbial systems exhibit functional redundancy, in which different taxa contribute to the functional stability and resilience of the ecosystem, there is evidence for niche specialization resulting in unique contributions to specific pathways in each part of this host-parasite system. The specificity of taxa contribution to key pathways offers targeted approaches to Varroa microbiome management and preserving honeybee microbiome. Our findings provide valuable insights into microbial interactions, aiding farmers and beekeepers in maintaining healthy and resilient bee colonies amid increasing Varroa mite infestations.

Exploring the potential of biochar for the remediation of microbial communities and element cycling in microplastic-contaminated soil

The detrimental effects of microplastics (MPs) on soil microbial and elemental raise significant environmental concerns. The potential of remediation with biochar to mitigate these negative impacts remains an open question. The remediation effects of biochar derived from corn and cotton straw on MPs concerning soil microorganisms and element cycling were investigated. Specifically, biochar induced substantial remediations in microbial community structure following MP exposure, restoring and fortifying the symbiotic network while exerting dominance over microbial community changes. A combined treatment of biochar and MPs exhibited a noteworthy increase in the abundance of NH4+, NO3-, and available phosphorous by 0.46-2.1 times, reversing the declining trend of dissolved organic carbon, showing a remarkable increase by 0.36 times. This combined treatment also led to a reduction in the abundance of the nitrogen fixation gene nifH by 0.46 times, while significantly increasing the expression of nitrification genes (amoA and amoB) and denitrification genes (nirS and nirK) by 22.5 times and 1.7 times, respectively. Additionally, the carbon cycle cbbLG gene showed a 2.3-fold increase, and the phosphorus cycle gene phoD increased by 0.1-fold. The mixed treatment enriched element-cycling microorganisms by 4.8-9.6 times. In summary, the addition of biochar repaired the negative effects of MPs in terms of microbial community dynamics, element content, gene expression, and functional microbiota. These findings underscore the crucial role of biochar in alleviating the adverse effects of MPs on microbial communities and elemental cycling, providing valuable insights into sustainable environmental remediation strategies.

Harnessing technology for infectious disease response in conflict zones: Challenges, innovations, and policy implications

Epidemic outbreaks of infectious diseases in conflict zones are complex threats to public health and humanitarian activities that require creativity approaches of reducing their damage. This narrative review focuses on the technology intersection with infectious disease response in conflict zones, and complexity of healthcare infrastructure, population displacement, and security risks. This narrative review explores how conflict-related destruction is harmful towards healthcare systems and the impediments to disease surveillance and response activities. In this regards, the review also considered the contributions of technological innovations, such as the improvement of epidemiological surveillance, mobile health (mHealth) technologies, genomic sequencing, and surveillance technologies, in strengthening infectious disease management in conflict settings. Ethical issues related to data privacy, security and fairness are also covered. By advisement on policy that focuses on investment in surveillance systems, diagnostic capacity, capacity building, collaboration, and even ethical governance, stakeholders can leverage technology to enhance the response to infectious disease in conflict settings and, thus, protect the global health security. This review is full of information for researchers, policymakers, and practitioners who are dealing with the issues of infectious disease outbreaks in conflicts worn areas.

Systematic Evaluation of Biotic and Abiotic Factors in Antifungal Microorganism Screening

Microorganisms have significant potential to control fungal contamination in various foods. However, the identification of strains that exhibit robust antifungal activity poses challenges due to highly context-dependent responses. Therefore, to fully exploit the potential of isolates as antifungal agents, it is crucial to systematically evaluate them in a variety of biotic and abiotic contexts. Here, we present an adaptable and scalable method using a robotic platform to study the properties of 1022 isolates obtained from maple sap. We tested the antifungal activity of isolates alone or in pairs on M17 + lactose (LM17), plate count agar (PCA), and sucrose-allantoin (SALN) culture media against Kluyveromyces lactis, Candida boidinii, and Saccharomyces cerevisiae. Microorganisms exhibited less often antifungal activity on SALN and PCA than LM17, suggesting that the latter is a better screening medium. We also analyzed the results of ecological interactions between pairs. Isolates that showed consistent competitive behaviors were more likely to show antifungal activity than expected by chance. However, co-culture rarely improved antifungal activity. In fact, an interaction-mediated suppression of activity was more prevalent in our dataset. These findings highlight the importance of incorporating both biotic and abiotic factors into systematic screening designs for the bioprospection of microorganisms with environmentally robust antifungal activity.

Metabolic picture of microbial interaction: chemical crosstalk during co-cultivation between three dominant genera of bacteria and fungi in medicinal plants rhizosphere

INTRODUCTION

Microbial communities affect several aspects of the earth's ecosystem through their metabolic interaction. The dynamics of this interaction emerge from complex multilevel networks of crosstalk. Elucidation of this interaction could help us to maintain the balance for a sustainable future.

OBJECTIVES

To investigate the chemical language among highly abundant microbial genera in the rhizospheres of medicinal plants based on the metabolomic analysis at the interaction level.

METHODS

Coculturing experiments involving three microbial species: Aspergillus (A), Trichoderma (T), and Bacillus (B), representing fungi (A, T) and bacteria (B), respectively. These experiments encompassed various interaction levels, including dual cultures (AB, AT, TB) and triple cultures (ATB). Metabolic profiling by LC-QTOFMS revealed the effect of interaction level on the productivity and diversity of microbial specialized metabolites.

RESULTS

The ATB interaction had the richest profile, while the bacterial profile in the monoculture condition had the lowest. Two native compounds of the Aspergillus genus, aspergillic acid and the dipeptide asperopiperazine B, exhibited decreased levels in the presence of the AT interaction and were undetectable in the presence of bacteria during the interaction. Trichodermarin N and Trichodermatide D isolated from Trichoderma species exclusively detected during coexistence with bacteria (TB and ATB). These findings indicate that the presence of Bacillus activates cryptic biosynthetic gene clusters in Trichoderma. The antibacterial activity of mixed culture extracts was stronger than that of the monoculture extracts. The TB extract exhibited strong antifungal activity compared to the monoculture extract and other mixed culture treatments.

CONCLUSION

The elucidation of medicinal plant microbiome interaction chemistry and its effect on the environment will also be of great interest in the context of medicinal plant health Additionally, it sheds light on the content of bioactive constituents, and facilitating the discovery of novel antimicrobials.

Impact of captivity and natural habitats on gut microbiome in Epinephelus akaara across seasons

BACKGROUND

The gut microbiota significantly influences the health and growth of red-spotted grouper (Epinephelus akaara), a well-known commercial marine fish from Fujian Province in southern China. However, variations in survival strategies and seasons can impact the stability of gut microbiota data, rendering it inaccurate in reflecting the state of gut microbiota. Which impedes the effective enhancement of aquaculture health through a nuanced understanding of gut microbiota. Inspired by this, we conducted a comprehensive analysis of the gut microbiota of wild and captive E. akaara in four seasons.

RESULTS

Seventy-two E. akaara samples were collected from wild and captive populations in Dongshan city, during four different seasons. Four sections of the gut were collected to obtain comprehensive information on the gut microbial composition and sequenced using 16S rRNA next-generation Illumina MiSeq. We observed the highest gut microbial diversity in both captive and wild E. akaara during the winter season, and identified strong correlations with water temperature using Mantel analysis. Compared to wild E. akaara, we found a more complex microbial network in captive E. akaara, as evidenced by increased abundance of Bacillaceae, Moraxellaceae and Enterobacteriaceae. In contrast, Vibrionaceae, Clostridiaceae, Flavobacteriaceae and Rhodobacteraceae were found to be more active in wild E. akaara. However, some core microorganisms, such as Firmicutes and Photobacterium, showed similar distribution patterns in both wild and captive groups. Moreover, we found the common community composition and distribution characteristics of top 10 core microbes from foregut to hindgut in E. akaara.

CONCLUSIONS

Collectively, the study provides relatively more comprehensive description of the gut microbiota in E. akaara, taking into account survival strategies and temporal dimensions, which yields valuable insights into the gut microbiota of E. akaara and provides a valuable reference to its aquaculture.

Microbiome analysis reveals alteration in water microbial communities due to livestock activities

The Baihe River, a tributary of the Yellow River located in the Ngawa Tibetan and Qiang Autonomous Prefecture in Northern Sichuan, is surrounded by natural resources suitable for animal development. However, the impact of livestock activities water microbiome in this area remains unexplored. This study collected water samples from areas with captive yaks and sheep (NS and YS) and compared them with water samples from Hongyuan Baihe River. Through amplicon sequencing, we investigated the impact of livestock activities on aquatic microorganisms. Diversity analysis, significance analysis, and microbial phenotype prediction indicated a significant decrease in microbial community diversity and function in the NS and YS groups. Pathogenic microorganisms such as Bacteroidales and Thelebolaceae and antibiotic-resistant bacteria genes such as Flavobacteriales and Burkholderiaceae were significantly higher in livestock breeding areas. Additionally, bacteria adapted to acidification, hypoxia, and eutrophication (e.g., Acidobacteria, Flavobacteriales, Deltaproteobacteria, Rhodobacterales) were more abundant in these areas. Our results demonstrate that livestock activities significantly alter the structure and function of microbial communities in surrounding water bodies, deteriorating water quality.

Integrative analysis of systemic lupus erythematosus biomarkers: Role of fecal hsa-mir-223-3p and gut microbiota in transkingdom dynamics

Systemic lupus erythematosus (SLE) involves a florid set of clinical manifestations whose autoreactive origin is characterized by an overactivation of the immune system and the production of a large number of autoantibodies. Because it is a complex pathology with an inflammatory component, its pathogenesis is not yet fully understood, assuming both genetic and environmental predisposing factors. Currently, it is known that the role of the human microbiome is crucial in maintaining the transkingdom balance between commensal microorganisms and the immune system. In the present work we study the intestinal microbiota of Argentine patients with different stages of SLE receiving or not different treatments. Microbiota composition and fecal miRNAs were assessed by 16 S sequencing and qPCR. hsa-miR-223-3p, a miRNA involved in several inflammation regulation pathways, was found underexpressed in SLE patients without immunosuppressive treatment. In terms of microbiota there were clear differences in population structure (Weighted and Unweighted Unifrac distances, p-value <0.05) and core microbiome between cases and controls. In addition, Collinsella, Bifidobacterium, Streptococcus genera and aromatics degradation metabolisms were overrepresented in the SLE group. Medical treatment was also determinant as several microbial metabolic pathways were influenced by immunosuppressive therapy. Particularly, allantoin degradation metabolism was differentially expressed in the group of patients receiving immunosuppressants. Finally, we performed a logistic regression model (LASSO: least absolute shrinkage and selection operator) considering the expression levels of the fecal hsa-miR223-3p; the core microbiota; the differentially abundant bacterial taxa and the differentially abundant metabolic pathways (p<0.05). The model predicted that SLE patients could be associated with greater relative abundance of the formaldehyde oxidation pathway (RUMP_PWY). On the contrary, the preponderance of the ketodeoxyoctonate (Kdo) biosynthesis and activation route (PWY_1269) and the genera Lachnospiraceae_UCG_004, Lachnospira, Victivallis and UCG_003 (genus belonging to the family Oscillospiraceae of the class Clostridia) were associated with a control phenotype. Overall, the present work could contribute to the development of integral diagnostic tools for the comprehensive phenotyping of patients with SLE. In this sense, studying the commensal microbial profile and possible pathobionts associated with SLE in our population proposes more effective and precise strategies to explore possible treatments based on the microbiota of SLE patients.

Infection and the microbiome in bronchiectasis

Bronchiectasis is marked by bronchial dilatation, recurrent infections and significant morbidity, underpinned by a complex interplay between microbial dysbiosis and immune dysregulation. The identification of distinct endophenotypes have refined our understanding of its pathogenesis, including its heterogeneous disease mechanisms that influence treatment and prognosis responses. Next-generation sequencing (NGS) has revolutionised the way we view airway microbiology, allowing insights into the "unculturable". Understanding the bronchiectasis microbiome through targeted amplicon sequencing and/or shotgun metagenomics has provided key information on the interplay of the microbiome and host immunity, a central feature of disease progression. The rapid increase in translational and clinical studies in bronchiectasis now provides scope for the application of precision medicine and a better understanding of the efficacy of interventions aimed at restoring microbial balance and/or modulating immune responses. Holistic integration of these insights is driving an evolving paradigm shift in our understanding of bronchiectasis, which includes the critical role of the microbiome and its unique interplay with clinical, inflammatory, immunological and metabolic factors. Here, we review the current state of infection and the microbiome in bronchiectasis and provide views on the future directions in this field.

Deciphering the core microbes and their interactions in spontaneous Baijiu fermentation: A comprehensive review

The spontaneous Baijiu fermentation system harbors a complex microbiome that is highly dynamic in time and space and varies depending on the Jiuqu starters and environmental factors. The intricate microbiota presents in the fermentation environment is responsible for carrying out various reactions. These reactions necessitate the interaction among the core microbes to influence the community function, ultimately shaping the distinct Baijiu styles through the process of spontaneous fermentation. Numerous studies have been conducted to enhance our understanding of the diversity, succession, and function of microbial communities with the aim of improving fermentation manipulation. However, a comprehensive and critical assessment of the core microbes and their interaction remains one of the significant challenges in the Baijiu fermentation industry. This paper focuses on the fermentation properties of core microbes. We discuss the state of the art of microbial traceability, highlighting the crucial role of environmental and starter microbiota in the Baijiu brewing microbiome. Also, we discuss the various interactions between microbes in the Baijiu production system and propose a potential conceptual framework that involves constructing predictive network models to simplify and quantify microbial interactions using co-culture models. This approach offers effective strategies for understanding the core microbes and their interactions, thus beneficial for the management of microbiota and the regulation of interactions in Baijiu fermentation processes.

Heavy metals in a typical industrial area-groundwater system: Spatial distribution, microbial response and ecological risk

The environmental burden due to industrial activities has been quite observable in the last few years, with heavy metals (HMs) like lead, cadmium, and arsenic inducing serious perturbations to the microbial ecosystem of groundwater. Studies carried out in North China, a region known for interconnection of industrial and groundwater systems, sought to explore the natural mechanisms of adaptation of microbes to groundwater contamination. The results showed that heavy metals permeate from surface increased the diversity and abundance of microbial communities in groundwater, producing an average decrease of 40.84% and 34.62% in the relative abundance of Bacteroidetes and Proteobacteria in groundwater, respectively. Meanwhile, the key environmental factors driving the evolution of microbial communities shift from groundwater nutrients to heavy metals, which explained 50.80% of the change in the microbial community composition. Microbial indicators are more sensitive to HMs pollution and could accurately identify industrial area where HMs permeation occurred and other extraneous pollutants. The phylum Bacteroidetes could act as appropriate indicators for the identification. Significant genera that were identified, being Mesorhizobium, Clostridium, Bacillus and Mucilaginibacter, were found to play important roles in the microbial network in terms of the potential to assist in groundwater clean-up. Notably, pollution from heavy metals has diminished the effectiveness and resilience of microbial communities in groundwater, thereby heightening the susceptibility of these normally stable microbial ecosystems. These findings offer new perspectives on how to monitor and detect groundwater pollution, and provide scientific guidance for developing suitable remediation methods for groundwater contaminated with heavy metals. Future research is essential explore the application of metal-tolerant or resistant bacteria in bioremediation strategies to rehabilitate groundwater systems contaminated by HMs.

Shifts in Microbial Community Structure and Co-occurrence Network along a Wide Soil Salinity Gradient

The response of microbiomes to salinity has been clarified in different geographic scales or ecosystems. However, how soil microbial community structure and interaction respond to salinity across wide salinity range and climatic region is still unclearly resolved. To address this issue, we examined the microbial community's composition in saline soils from two climatic regions (coastal wetland and arid desert). Our research confirms that soil salinity had a negative effect on soil nutrient content. Salinity decreased the relative abundance of bacteria, but increased archaea abundance, leading to the shifts from bacteria dominant community to archaea dominant community. Low-water medium-salinity soil (LWMS) had the most complex archaeal community network, whereas for bacteria, the most complex bacterial community network was observed in low-water high-salinity soils (LWHS). Key microbial taxa differed in three salinity gradients. Salinity, soil water content, pH, total nitrogen (TN), and soil organic carbon (SOC) were the main driving factors for the composition of archaeal and bacterial community. Salinity directly affected archaeal community, but indirectly influenced bacteria community through SOC; pH affected archaeal community indirectly through TN, but directly affected bacterial community. Our study suggests that soil salinity dramatically influences diversity, composition, and interactions within the microbial community.

Microbiome modeling: a beginner's guide

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding between microbiologists and modelers/bioinformaticians, stemming from a lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored for microbiologists, researchers new to microbiome modeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metaomics methods, common modeling formalisms, and how models facilitate microbiome control. It concludes with guidelines and repositories for modeling. Each section provides entry-level information, example applications, and important references, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling.

Prebiotic galactooligosaccharide improves piglet growth performance and intestinal health associated with alterations of the hindgut microbiota during the peri-weaning period

BACKGROUND

Weaning stress reduces growth performance and health of young pigs due in part to an abrupt change in diets from highly digestible milk to fibrous plant-based feedstuffs. This study investigated whether dietary galactooligosaccharide (GOS), supplemented both pre- and post-weaning, could improve growth performance and intestinal health via alterations in the hindgut microbial community.

METHODS

Using a 3 × 2 factorial design, during farrowing 288 piglets from 24 litters received either no creep feed (FC), creep without GOS (FG-) or creep with 5% GOS (FG+) followed by a phase 1 nursery diet without (NG-) or with 3.8% GOS (NG+). Pigs were sampled pre- (D22) and post-weaning (D31) to assess intestinal measures.

RESULTS

Creep fed pigs grew 19% faster than controls (P < 0.01) prior to weaning, and by the end of the nursery phase (D58), pigs fed GOS pre-farrowing (FG+) were 1.85 kg heavier than controls (P < 0.05). Furthermore, pigs fed GOS in phase 1 of the nursery grew 34% faster (P < 0.04), with greater feed intake and efficiency. Cecal microbial communities clustered distinctly in pre- vs. post-weaned pigs, based on principal coordinate analysis (P < 0.01). No effects of GOS were detected pre-weaning, but gruel creep feeding increased Chao1 α-diversity and altered several genera in the cecal microbiota (P < 0.05). Post-weaning, GOS supplementation increased some genera such as Fusicatenibacter and Collinsella, whereas others decreased such as Campylobacter and Frisingicoccus (P < 0.05). Changes were accompanied by higher molar proportions of butyrate in the cecum of GOS-fed pigs (P < 0.05).

CONCLUSIONS

Gruel creep feeding effectively improves suckling pig growth regardless of GOS treatment. When supplemented post-weaning, prebiotic GOS improves piglet growth performance associated with changes in hindgut microbial composition.

Lung microbiome: new insights into bronchiectasis' outcome

The present treatments for bronchiectasis, which is defined by pathological dilatation of the airways, are confined to symptom relief and minimizing exacerbations. The condition is becoming more common worldwide. Since the disease's pathophysiology is not entirely well understood, developing novel treatments is critically important. The interplay of chronic infection, inflammation, and compromised mucociliary clearance, which results in structural alterations and the emergence of new infection, is most likely responsible for the progression of bronchiectasis. Other than treating bronchiectasis caused by cystic fibrosis, there are no approved treatments. Understanding the involvement of the microbiome in this disease is crucial, the microbiome is defined as the collective genetic material of all bacteria in an environment. In clinical practice, bacteria in the lungs have been studied using cultures; however, in recent years, researchers use next-generation sequencing methods, such as 16S rRNA sequencing. Although the microbiome in bronchiectasis has not been entirely investigated, what is known about it suggests that Haemophilus, Pseudomonas and Streptococcus dominate the lung bacterial ecosystems, they present significant intraindividual stability and interindividual heterogeneity. Pseudomonas and Haemophilus-dominated microbiomes have been linked to more severe diseases and frequent exacerbations, however additional research is required to fully comprehend the role of microbiome in the evolution of bronchiectasis. This review discusses recent findings on the lung microbiota and its association with bronchiectasis.

Mechanisms of microbial coexistence in a patchy ecosystem: Differences in ecological niche overlap and species fitness between rhythmic and non-rhythmic species

Resource patchiness caused by external events breaks the continuity and homogeneity of resource distribution in the original ecosystem. For local organisms, this leads to drastic changes in the availability of resources, breaks down the co-existence of species, and reshuffles the local ecosystem. West Lake is a freshwater lake with resource patchiness caused by multiple exogenous disturbances that has strong environmental heterogeneity that prevents clear observation of seasonal changes in the microbial communities. Despite this, the emergence of rhythmic species in response to irregular changes in the environment has been helpful for observing microbial communities dynamics in patchy ecosystems. We investigated the ecological mechanisms of seasonal changes in microbial communities in West Lake by screening rhythmic species based on the ecological niche and modern coexistence theories. The results showed that rhythmic species were the dominant factors in microbial community changes and the effects of most environmental factors on the microbial community were indirectly realised through the rhythmic species. Random forest analyses showed that seasonal changes in the microbial community were similarly predicted by the rhythmic species. In addition, we incorporated species interactions and community phylogenetic patterns into stepwise multiple regression analyses, the results of which indicate that ecological niches and species fitness may drive the coexistence of these subcommunities. Thus, this study extends our understanding of seasonal changes in microbial communities and provides new ways for observing seasonal changes in microbial communities, especially in ecosystems with resource patches. Our study also show that combining community phylogenies with co-occurrence networks based on ecological niches and modern coexistence theory can further help us understand the ecological mechanisms of interspecies coexistence.

Arbuscular mycorrhizal fungal interactions bridge the support of root-associated microbiota for slope multifunctionality in an erosion-prone ecosystem

The role of diverse soil microbiota in restoring erosion-induced degraded lands is well recognized. Yet, the facilitative interactions among symbiotic arbuscular mycorrhizal (AM) fungi, rhizobia, and heterotrophic bacteria, which underpin multiple functions in eroded ecosystems, remain unclear. Here, we utilized quantitative microbiota profiling and ecological network analyses to explore the interplay between the diversity and biotic associations of root-associated microbiota and multifunctionality across an eroded slope of a Robinia pseudoacacia plantation on the Loess Plateau. We found explicit variations in slope multifunctionality across different slope positions, associated with shifts in limiting resources, including soil phosphorus (P) and moisture. To cope with P limitation, AM fungi were recruited by R. pseudoacacia, assuming pivotal roles as keystones and connectors within cross-kingdom networks. Furthermore, AM fungi facilitated the assembly and composition of bacterial and rhizobial communities, collectively driving slope multifunctionality. The symbiotic association among R. pseudoacacia, AM fungi, and rhizobia promoted slope multifunctionality through enhanced decomposition of recalcitrant compounds, improved P mineralization potential, and optimized microbial metabolism. Overall, our findings highlight the crucial role of AM fungal-centered microbiota associated with R. pseudoacacia in functional delivery within eroded landscapes, providing valuable insights for the sustainable restoration of degraded ecosystems in erosion-prone regions.

The development of the biological soil crust regulates the fungal distribution and the stability of fungal networks

The heterogeneous composition of fungi plays an indispensable role in the foundation of the multifunctionalities of ecosystems within drylands. The precise mechanisms that govern fluctuations in soil fungal assemblages in dryland ecosystems remain incompletely elucidated. In this study, biological soil crusts (biocrusts) at different successional stages in the Gurbantunggut Desert were used as substrates to examine the characteristics and driving factors that influence fungal abundance and community dynamics during biocrust development using qPCR and high-throughput sequencing of the ITS2 region. The findings showed that the physicochemical properties changed significantly with the development of biocrusts. In particular, total nitrogen increased 4.8 times, along with notable increases in ammonium, total phosphorus (2.1 times) and soil organic carbon (6.5 times). Initially, there was a rise in fungal abundance, which was subsequently followed by a decline as the biocrust developed, with the highest abundance detected in lichen crust (2.66 × 107 copies/g soil) and the lowest in bare sand (7.98 × 106 copies/g soil). Ascomycetes and Basidiomycetes emerged as dominant phyla, collectively forming 85% of the fungal community. As the biocrust developed, noticeable alterations occurred in fungal community compositions, resulting from changes in the relative proportions of Dothideomycetes, Lecanoromycetes and unclassified ascomycetes. Nitrogen, phosphorus, organic carbon content, and pH of biocrusts were identified as direct or indirect regulators of fungal abundance and community structure. The complexity of fungal networks increased as biocrusts developed as revealed by network analysis, but reduced in the stability of fungal communities within algal and lichen crusts. Keystone species within the fungal community also underwent changes as biocrust developed. These results suggested that shifts in interspecies relationships among fungi could further contribute to the variation in fungal communities during the development of biocrusts.

MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data

Multivariate analysis is becoming central in studies investigating high-throughput molecular data, yet, some important features of these data are seldom explored. Here, we present MANOCCA (Multivariate Analysis of Conditional CovAriance), a powerful method to test for the effect of a predictor on the covariance matrix of a multivariate outcome. The proposed test is by construction orthogonal to tests based on the mean and variance and is able to capture effects that are missed by both approaches. We first compare the performances of MANOCCA with existing correlation-based methods and show that MANOCCA is the only test correctly calibrated in simulation mimicking omics data. We then investigate the impact of reducing the dimensionality of the data using principal component analysis when the sample size is smaller than the number of pairwise covariance terms analysed. We show that, in many realistic scenarios, the maximum power can be achieved with a limited number of components. Finally, we apply MANOCCA to 1000 healthy individuals from the Milieu Interieur cohort, to assess the effect of health, lifestyle and genetic factors on the covariance of two sets of phenotypes, blood biomarkers and flow cytometry-based immune phenotypes. Our analyses identify significant associations between multiple factors and the covariance of both omics data.

Post-stroke cognitive impairment: exploring molecular mechanisms and omics biomarkers for early identification and intervention

Post-stroke cognitive impairment (PSCI) is a major stroke consequence that has a severe impact on patients' quality of life and survival rate. For this reason, it is especially crucial to identify and intervene early in high-risk groups during the acute phase of stroke. Currently, there are no reliable and efficient techniques for the early diagnosis, appropriate evaluation, or prognostication of PSCI. Instead, plenty of biomarkers in stroke patients have progressively been linked to cognitive impairment in recent years. High-throughput omics techniques that generate large amounts of data and process it to a high quality have been used to screen and identify biomarkers of PSCI in order to investigate the molecular mechanisms of the disease. These techniques include metabolomics, which explores dynamic changes in the organism, gut microbiomics, which studies host-microbe interactions, genomics, which elucidates deeper disease mechanisms, transcriptomics and proteomics, which describe gene expression and regulation. We looked through electronic databases like PubMed, the Cochrane Library, Embase, Web of Science, and common databases for each omics to find biomarkers that might be connected to the pathophysiology of PSCI. As all, we found 34 studies: 14 in the field of metabolomics, 5 in the field of gut microbiomics, 5 in the field of genomics, 4 in the field of transcriptomics, and 7 in the field of proteomics. We discovered that neuroinflammation, oxidative stress, and atherosclerosis may be the primary causes of PSCI development, and that metabolomics may play a role in the molecular mechanisms of PSCI. In this study, we summarized the existing issues across omics technologies and discuss the latest discoveries of PSCI biomarkers in the context of omics, with the goal of investigating the molecular causes of post-stroke cognitive impairment. We also discuss the potential therapeutic utility of omics platforms for PSCI mechanisms, diagnosis, and intervention in order to promote the area's advancement towards precision PSCI treatment.

Short-term exposure to antibiotics begets long-term disturbance in gut microbial metabolism and molecular ecological networks

BACKGROUND

Antibiotic exposure can occur in medical settings and from environmental sources. Long-term effects of brief antibiotic exposure in early life are largely unknown.

RESULTS

Post a short-term treatment by ceftriaxone to C57BL/6 mice in early life, a 14-month observation was performed using 16S rRNA gene-sequencing technique, metabolomics analysis, and metagenomics analysis on the effects of ceftriaxone exposure. Firstly, the results showed that antibiotic pre-treatment significantly disturbed gut microbial α and β diversities (P < 0.05). Both Chao1 indices and Shannon indices manifested recovery trends over time, but they didn't entirely recover to the baseline of control throughout the experiment. Secondly, antibiotic pre-treatment reduced the complexity of gut molecular ecological networks (MENs). Various network parameters were affected and manifested recovery trends over time with different degrees, such as nodes (P < 0.001, R2 = 0.6563), links (P < 0.01, R2 = 0.4543), number of modules (P = 0.0672, R2 = 0.2523), relative modularity (P = 0.6714, R2 = 0.0155), number of keystones (P = 0.1003, R2 = 0.2090), robustness_random (P = 0.79, R2 = 0.0063), and vulnerability (P = 0.0528, R2 = 0.28). The network parameters didn't entirely recover. Antibiotic exposure obviously reduced the number of key species in gut MENs. Interestingly, new keystones appeared during the recovery process of network complexity. Changes in network stability might be caused by variations in network complexity, which supports the ecological theory that complexity begets stability. Besides, the metabolism profiles of the antibiotic group and control were significantly different. Correlation analysis showed that antibiotic-induced differences in gut microbial metabolism were related to MEN changes. Antibiotic exposure also caused long-term effects on gut microbial functional networks in mice.

CONCLUSIONS

These results suggest that short-term antibiotic exposure in early life will cause long-term negative impacts on gut microbial diversity, MENs, and microbial metabolism. Therefore, great concern should be raised about children's brief exposure to antibiotics if the results observed in mice are applicable to humans. Video Abstract.

Response of microbial communities to exogenous nitrate nitrogen input in black and odorous sediment

Since nitrate nitrogen (NO3--N) input has proved an effective approach for the treatment of black and odorous river waterbody, it was controversial whether the total nitrogen concentration standard should be raised when the effluent from the sewage treatment plant is discharged into the polluted river. To reveal the effect of exogenous nitrate (NO3--N) on black odorous waterbody, sediments with different features from contaminated rivers were collected, and the changes of physical and chemical characteristics and microbial community structure in sediments before and after the addition of exogenous NO3--N were investigated. The results showed that after the input of NO3--N, reducing substances such as acid volatile sulfide (AVS) in the sediment decreased by 80 % on average, ferrous (Fe2+) decreased by 50 %, yet the changing trend of ammonia nitrogen (NH4+-N) in some sediment samples increased while others decreased. High-throughput sequencing results showed that the abundance of Thiobacillus at most sites increased significantly, becoming the dominant genus in the sediment, and the abundance of functional genes in the metabolome increased, such as soxA, soxX, soxY, soxZ. Network analysis showed that sediment microorganisms evolved from a single sulfur oxidation ecological function to diverse ecological functions, such as nitrogen cycle nirB, nirD, nirK, nosZ, and aerobic decomposition. In summary, inputting an appropriate amount of exogenous NO3--N is beneficial for restoring and maintaining the oxidation states of river sediment ecosystems.

Microbial perspective on restoration of degraded urban soil using ornamental plants

The urban soil where abandoned buildings are demolished is barren and structurally poor, and this degraded soil requires restoration. Ornamental plants enhance the urban environment, increase biodiversity, and affect soil physicochemical properties, microbial diversity; however, their effects remain unclear. Thus, in this study, a mixed-planting meadow consisting of 14 perennial ornamental flower species, including Iris tectorum, Iris lacteal, and Patrinia scabiosaefolia, etc. Was planted at a demolition site with sewage-contaminated soil in Beijing. Simultaneously, a single-planting lawn of I. tectorum was established in a nearby park. We aimed to examine soil physicochemical properties, sequence soil bacterial 16S rRNA and fungal ITS amplicons, and analyze soil microbial diversity and community structure at both sites at five time points in the year after planting, To explore the effect of herbaceous ornamental plants on degraded urban soil, we used FAPROTAX and FUNGuild to predict bacterial and fungal functions, the bin-based null model to evaluate the soil microbial community, and random matrix theory to construct soil microbial molecular networks. The mixed-planting meadow produced a visually appealing landscape and dynamic seasonal enrichment, significantly increasing soil total nitrogen (TN) and organic matter (SOM) contents by 1.99 and 1.21 times, respectively. TN had a positive correlation with soil microbial α diversity and community structure. Dominant phyla at both sites included Proteobacteria, Actinobacteria, and Ascomycota. Although soil microorganisms were primarily influenced by stochastic processes, stochasticity was notably higher in the mixed-planting meadow than in the single-planting lawn. The mixed-planting meadow significantly increased the relative abundance of beneficial microorganisms, improving nitrification and aerobic ammonium oxidation of soil bacteria, as well as symbiotroph of fungi. No significant changes were observed in the single-planting lawn. The mixed-planting meadow established a complex soil microbial molecular network, enhancing the correlation between bacteria and fungi and increasing the number of key microorganisms. Our findings suggest the potential of mixed-planting meadow in restoring degraded urban soils by influencing the soil microbial community and enhancing the ecological service function. Our study provides theoretical support for applying mixed-planting meadow communities to improve the soil environment of urban green spaces.

AM, Doster E, Fernandes L, Calles VF, Bauman C, Godden S, Heins B, Pinedo P, Machado VS, Caixeta LS, Noyes NR. Exploring associations between the teat apex metagenome and Staphylococcus aureus intramammary infections in primiparous cows under organic directives

The primary objective of this study was to identify associations between the prepartum teat apex microbiome and the presence of Staphylococcus aureus intramammary infections (IMI) in primiparous cows during the first 5 weeks after calving. We performed a case-control study using shotgun metagenomics of the teat apex and culture-based milk data collected longitudinally from 710 primiparous cows on five organic dairy farms. Cases had higher odds of having S. aureus metagenomic DNA on the teat apex prior to parturition compared to controls (OR = 38.9, 95% CI: 14.84-102.21). Differential abundance analysis confirmed this association, with cases having a 23.8 higher log fold change (LFC) in the abundance of S. aureus in their samples compared to controls. Of the most prevalent microorganisms in controls, those associated with a lower risk of post-calving S. aureus IMI included Microbacterium phage Min 1 (OR = 0.37, 95% CI: 0.25-0.53), Corynebacterium efficiens (OR = 0.53, 95% CI: 0.30-0.94), Kocuria polaris (OR = 0.54, 95% CI: 0.35-0.82), Micrococcus terreus (OR = 0.64, 95% CI: 0.44-0.93), and Dietzia alimentaria (OR = 0.45, 95% CI: 0.26-0.75). Genes encoding for Microcin B17 AMPs were the most prevalent on the teat apex of cases and controls (99.7% in both groups). The predicted abundance of genes encoding for Microcin B17 was also higher in cases compared to controls (LFC 0.26).

IMPORTANCE

Intramammary infections (IMI) caused by Staphylococcus aureus remain an important problem for the dairy industry. The microbiome on the external skin of the teat apex may play a role in mitigating S. aureus IMI risk, in particular the production of antimicrobial peptides (AMPs) by commensal microbes. However, current studies of the teat apex microbiome utilize a 16S approach, which precludes the detection of genomic features such as genes that encode for AMPs. Therefore, further research using a shotgun metagenomic approach is needed to understand what role prepartum teat apex microbiome dynamics play in IMI risk.

Artificial light at night causes community instability of bacterial community in urban soils

Urban soils host diverse bacteria crucial for ecosystem functions and urban health. As urbanization rises, artificial light at night (ALAN) imposes disturbances on soil ecosystems, yet how ALAN affects the structure and stability of soil bacterial community remains unclear. Here we coupled a short-term incubation experiment, community profiling, network analysis, and in situ field survey to assess the ecological impacts of ALAN. We showed that ALAN influenced bacterial compositions and shifted the bacterial network to a less stable phase, altering denitrification potential. Such transition in community stability probably resulted from an ALAN-induced decrease in competition and/or an increase in facilitation, in line with the Stress Gradient Hypothesis. Similar destabilizing effects were also detected in bacterial networks in multiple urban soils subjected to different levels of ALAN stress, supporting the action of ALAN on naturally-occurring soil bacterial communities. Overall, our findings highlight ALAN as a new form of anthropogenic stress that jeopardizes the stability of soil bacterial community, which would facilitate ecological projection of expanding ALAN exposure.

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

Epistemic misalignments in microbiome research

We argue that microbiome research should be more reflective on the methods that it relies on to build its datasets due to the danger of facing a methodological problem which we call "epistemic misalignment." An epistemic misalignment occurs when the method used to answer specific scientific questions does not track justified answers, due to the material constraints imposed by the very method. For example, relying on 16S rRNA to answer questions about the function of the microbiome generates epistemic misalignments, due to the different temporal scales that 16S rRNA provides information about and the temporal scales that are required to know about the functionality of some microorganisms. We show how some of these exist in contemporary microbiome science and urge microbiome scientists to take some measures to avoid them, as they may question the credibility of the field as a whole.

Biological interactions control bacterial but not fungal β diversity during vegetation degradation in saline-alkaline soil

The patterns and mechanisms by which soil bacterial and fungal community β-diversity respond to vegetation degradation in saline-alkaline soils are currently not clear, and in particular, the role of biotic interactions is relatively unknown. To investigate the assembly of bacterial and fungal communities in topsoil (0-10 cm) in saline-alkaline soils at different stages of vegetation degradation, the β-Mean Nearest Classification Unit Distance, the β-Nearest Taxon Index, and the Raup-Crick index were calculated. The relative importance of biotic and environmental factors in controlling β diversity under deterministic processes was also quantified by using relative importance analyses. The β diversity of soil bacterial and fungal communities responded differently in different stages of vegetation degradation in saline-alkaline soils, with bacterial β diversity increasing with increasing vegetation degradation but fungal β diversity showing few differences. Deterministic processes regulated soil bacterial community assembly, and biotic factors were important in driving changes in β diversity, whereas both deterministic and stochastic processes were essential in soil fungal community assembly, and environmental factors were important in affecting fungal β diversity. Furthermore, fungal β diversity is far more affected by interactions between fungus and bacteria than bacteria. Our study demonstrates the different effects of vegetation degradation on bacterial and fungal communities in saline soils to provide the overall implications for saline soils microorganisms in deteriorating ecosystems.

phylaGAN: data augmentation through conditional GANs and autoencoders for improving disease prediction accuracy using microbiome data

MOTIVATION

Research is improving our understanding of how the microbiome interacts with the human body and its impact on human health. Existing machine learning methods have shown great potential in discriminating healthy from diseased microbiome states. However, Machine Learning based prediction using microbiome data has challenges such as, small sample size, imbalance between cases and controls and high cost of collecting large number of samples. To address these challenges, we propose a deep learning framework phylaGAN to augment the existing datasets with generated microbiome data using a combination of conditional generative adversarial network (C-GAN) and autoencoder. Conditional generative adversarial networks train two models against each other to compute larger simulated datasets that are representative of the original dataset. Autoencoder maps the original and the generated samples onto a common subspace to make the prediction more accurate.

RESULTS

Extensive evaluation and predictive analysis was conducted on two datasets, T2D study and Cirrhosis study showing an improvement in mean AUC using data augmentation by 11% and 5% respectively. External validation on a cohort classifying between obese and lean subjects, with a smaller sample size provided an improvement in mean AUC close to 32% when augmented through phylaGAN as compared to using the original cohort. Our findings not only indicate that the generative adversarial networks can create samples that mimic the original data across various diversity metrics, but also highlight the potential of enhancing disease prediction through machine learning models trained on synthetic data.

AVAILABILITY AND IMPLEMENTATION

https://github.com/divya031090/phylaGAN.

Investigating the relationship between microbial network features of giant kelp "seedbank" cultures and subsequent farm performance

Microbial inoculants can increase the yield of cultivated crops and are successful in independent trials; however, efficacy drops in large-scale applications due to insufficient consideration of microbial community dynamics. The structure of microbiomes, in addition to the impact of individual taxa, is an important factor to consider when designing growth-promoting inoculants. Here, we investigate the microbial network and community assembly patterns of Macrocystis pyrifera gametophyte germplasm cultures (collectively referred to as a "seedbank") used to cultivate an offshore farm in Santa Barbara, California, and identify network features associated with increased biomass of mature sporophytes. We found that [1] several network features, such as clustering coefficient and edge ratios, significantly vary with biomass outcomes; [2] gametophytes that become low- or high-biomass sporophytes have different hub taxa; and [3] microbial community assembly of gametophyte germplasm cultures is niche-driven. Overall, this study describes microbial community dynamics in M. pyrifera germplasm cultures and ultimately supports the development of early life stage inoculants that can be used on seaweed cultivars to increase biomass yield.

Vegetation recovery reshapes the composition and enhances the network connectivity of phoD-harboring microorganisms to promote P availability in a karst ecosystem

Soil phoD-harboring microorganisms can facilitate phosphorus (P) transformation and increase the available P (AP) in P-limited soils; however, the mechanism by which these microorganisms enhance AP throughout the vegetation recovery process of karst ecosystems is poorly understood. Accordingly, this study investigates the effect of vegetation recovery on soil AP and the community composition and network connectivity of phoD-harboring microorganisms to elucidate the mechanism by which phoD-harboring microorganisms enhance soil AP in the four vegetation recovery stages (i.e., grassland, shrubland, shrub-arbor forest, and arbor forest) in a karst ecosystem. Results show that soil total P, AP, and microbial biomass P concentrations, as well as alkaline phosphatase activities, litter and soil nutrients, and plant diversity indices (Shannon-Wiener and Pielou) increase with advancing vegetation recovery. Moreover, the diversity indices (Shannon-Wiener and Simpson) and network complexity of the phoD-harboring microorganisms also increase with advancing vegetation recovery, leading to distinct communities among the four recovery stages. Rhizobiales, Pseudomonadales, and Burkholderiales comprise the dominant phoD-harboring microorganism orders. The relative abundances of Pseudomonadales and Burkholderiales increase with advancing vegetation recovery; Rhizobiales is the highest in shrubland and the lowest in grassland. The structural equation model results show that advanced vegetation recovery is associated with increased plant diversity, litter nutrients, and soil nutrients. The network connectivity is enhanced with advancing vegetation recovery accompanied by increasing soil phosphatase activity and P availability. These results suggest that regulating the phoD-harboring microorganism composition and network connectivity is essential to alleviate plant P limitation in karst ecosystems.

Progress on network modeling and analysis of gut microecology: a review

The gut microecological network is a complex microbial community within the human body that plays a key role in linking dietary nutrition and host physiology. To understand the complex relationships among microbes and their functions within this community, network analysis has emerged as a powerful tool. By representing the interactions between microbes and their associated omics data as a network, we can gain a comprehensive understanding of the ecological mechanisms that drive the human gut microbiota. In addition, the network-based approach provides a more intuitive analysis of the gut microbiota, simplifying the study of its complex dynamics and interdependencies. This review provides a comprehensive overview of the methods used to construct and analyze networks in the context of gut microecological background. We discuss various types of network modeling approaches, including co-occurrence networks, causal networks, dynamic networks, and multi-omics networks, and describe the analytical techniques used to identify important network properties. We also highlight the challenges and limitations of network modeling in this area, such as data scarcity and heterogeneity, and provide future research directions to overcome these limitations. By exploring these network-based methods, researchers can gain valuable insights into the intricate relationships and functional roles of microbial communities within the gut, ultimately advancing our understanding of the gut microbiota's impact on human health.

The effects of food provisioning on the gut microbiota community and antibiotic resistance genes of Yunnan snub-nosed monkey

Yunnan snub-nosed monkeys (Rhinopithecus bieti) are the highest elevation lived non-human primate, and their survival has been threatened for decades. To promote their population growth, a reserve provides a typical monkey population with supplemental food. However, the influences of this food provisioning on their gut microbiota and antibiotic resistance genes (ARGs) were unknown. Therefore, we investigated the gut microbiota and ARGs of the food-provisioned monkey population compared with another wild foraging population. We found that food provisioning significantly increased the gut microbiota diversity and changed the community composition, particularly increased both the Firmicutes abundance and Firmicutes/Bacteroidetes ratio. Meanwhile, the food provisioning decreased the complex and stable gut microbiota network. KEGG functions were also influenced by food provisioning, with wild foraging monkeys showing higher functions of metabolism and genetic information processing, especially the carbohydrate metabolism, while food-provisioned monkeys exhibited increased environmental information processing, cellular processes, and organismal systems, including valine, leucine, and isoleucine degradation. In addition, food provisioning increased the abundance of ARGs in the gut microbiota, with most increasing the abundance of bacA gene and changing the correlations between specific ARGs and bacterial phyla in each population. Our study highlights that even food provisioning could promote wildlife nutrient intake, and it is necessary to pay attention to the increased ARGs and potential effects on gut microbiota stability and functions for this human conservation measure.

Differential network connectivity analysis for microbiome data adjusted for clinical covariates using jackknife pseudo-values

BACKGROUND

A recent breakthrough in differential network (DN) analysis of microbiome data has been realized with the advent of next-generation sequencing technologies. The DN analysis disentangles the microbial co-abundance among taxa by comparing the network properties between two or more graphs under different biological conditions. However, the existing methods to the DN analysis for microbiome data do not adjust for other clinical differences between subjects.

RESULTS

We propose a Statistical Approach via Pseudo-value Information and Estimation for Differential Network Analysis (SOHPIE-DNA) that incorporates additional covariates such as continuous age and categorical BMI. SOHPIE-DNA is a regression technique adopting jackknife pseudo-values that can be implemented readily for the analysis. We demonstrate through simulations that SOHPIE-DNA consistently reaches higher recall and F1-score, while maintaining similar precision and accuracy to existing methods (NetCoMi and MDiNE). Lastly, we apply SOHPIE-DNA on two real datasets from the American Gut Project and the Diet Exchange Study to showcase the utility. The analysis of the Diet Exchange Study is to showcase that SOHPIE-DNA can also be used to incorporate the temporal change of connectivity of taxa with the inclusion of additional covariates. As a result, our method has found taxa that are related to the prevention of intestinal inflammation and severity of fatigue in advanced metastatic cancer patients.

CONCLUSION

SOHPIE-DNA is the first attempt of introducing the regression framework for the DN analysis in microbiome data. This enables the prediction of characteristics of a connectivity of a network with the presence of additional covariate information in the regression. The R package with a vignette of our methodology is available through the CRAN repository ( https://CRAN.R-project.org/package=SOHPIE ), named SOHPIE (pronounced as Sofie). The source code and user manual can be found at https://github.com/sjahnn/SOHPIE-DNA .

Bioaerosols in the coastal region of Qingdao: Community diversity, impact factors and synergistic effect

Atmospheric bioaerosols are influenced by multiple factors, including physical, chemical, and biotic interactions, and pose a significant threat to the public health and the environment. The nonnegligible truth however is that the primary driver of the changes in bioaerosol community diversity remains unknown. In this study, putative biological association (PBA) was obtained by constructing an ecological network. The relationship between meteorological conditions, atmospheric pollutants, water-soluble inorganic ions, PBA and bioaerosol community diversity was analyzed using random forest regression (RFR)-An ensemble learning algorithm based on a decision tree that performs regression tasks by constructing multiple decision trees and integrating the predicted results, and the contribution of different rich species to PBA was predicted. The species richness, evenness and diversity varied significantly in different seasons, with the highest in summer, followed by autumn and spring, and was lowest in winter. The RFR suggested that the explanation rate of alpha diversity increased significantly from 73.74 % to 85.21 % after accounting for the response of the PBA to diversity. The PBA, temperature, air pollution, and marine source air masses were the most crucial factors driving community diversity. PBA, particularly putative positive association (PPA), had the highest significance in diversity. We found that under changing external conditions, abundant taxa tend to cooperate to resist external pressure, thereby promoting PPA. In contrast, rare taxa were more responsive to the putative negative association because of their sensitivity to environmental changes. The results of this research provided scientific advance in the understanding of the dynamic and temporal changes in bioaerosols, as well as support for the prevention and control of microbial contamination of the atmosphere.

Gut microbial network signatures of early colonizers in preterm neonates with extrauterine growth restriction

BACKGROUND

Extrauterine growth restriction (EUGR) represents a prevalent condition observed in preterm neonates, which poses potential adverse implications for both neonatal development and long-term health outcomes. The manifestation of EUGR has been intricately associated with perturbations in microbial and metabolic profiles. This study aimed to investigate the characteristics of the gut microbial network in early colonizers among preterm neonates with EUGR.

METHODS

Twenty-nine preterm infants participated in this study, comprising 14 subjects in the EUGR group and 15 in the normal growth (AGA) group. Meconium (D1) and fecal samples were collected at postnatal day 28 (D28) and 1 month after discharge (M1). Subsequently, total bacterial DNA was extracted and sequenced using the Illumina MiSeq system, targeting the V3-V4 hyper-variable regions of the 16S rRNA gene.

RESULTS

The outcomes of principal coordinates analysis (PCoA) and examination of the microbial network structure revealed distinctive developmental trajectories in the gut microbiome during the initial three months of life among preterm neonates with and without EUGR. Significant differences in microbial community were observed at the D1 (P = 0.039) and M1 phases (P = 0.036) between the EUGR and AGA groups, while a comparable microbial community was noted at the D28 phase (P = 0.414). Moreover, relative to the AGA group, the EUGR group exhibited significantly lower relative abundances of bacteria associated with secretion of short-chain fatty acids, including Lactobacillus (P = 0.041) and Parabacteroides (P = 0.033) at the D1 phase, Bifidobacterium at the D28 phase, and genera Dysgonomonas (P = 0.042), Dialister (P = 0.02), Dorea (P = 0.042), and Fusobacterium (P = 0.017) at the M1 phase.

CONCLUSION

Overall, the present findings offer crucial important insights into the distinctive gut microbial signatures exhibited by earlier colonizers in preterm neonates with EUGR. Further mechanistic studies are needed to establish whether these differences are the cause or a consequence of EUGR.

Revealing the response characteristics of periphyton biomass and community structure to sulfamethoxazole exposure in aquaculture water: The perspective of microbial network relationships

The widespread application of sulfonamide antibiotics in aquaculture has raised concerns about their adverse environmental impacts. Periphyton plays a crucial role in the aquatic ecosystem. In this study, we examined sulfamethoxazole (SMX) effects on the community structure and interactions of periphyton in simulated aquaculture water. Our findings indicated that the total biomass of periphyton decreased, while the biomass of periphytic algae and the secretion of extracellular polymeric substances (EPS) increased at 0.7 × 10-3 mg/L. Under higher SMX concentrations (5 mg/L and 10 mg/L), periphyton growth was severely inhibited, the microbial community structure of periphyton were sharply altered, characterized by the cyanobacteria growth suppression and decrease in the diversity index of community. Furthermore, elevated SMX concentrations (5 mg/L and 10 mg/L) increased the ratio of negative relationships from 45.4% to 49.4%, which suggested that high SMX concentrations promoted potential competition among microbes and disrupted the microbial food webs in periphyton. The absolute abundance of sul1 and sul2 genes in T2 and T3 groups were 2-3 orders of magnitude higher than those in control group after 30 days of SMX exposure, which elevated the risk of resistance gene enrichment and dissemination in the natural environment. The study contributes to our understanding of the detrimental effects of antibiotic pollution, which can induce changes in the structure and interaction relationship of microbial communities in aquaculture water.

Urinary microbiome community types associated with urinary incontinence severity in women

BACKGROUND

Urinary microbiome (urobiome) studies have previously reported on specific taxa and community differences in women with mixed urinary incontinence compared with controls. Therefore, a hypothesis was made that higher urinary and vaginal microbiome diversity would be associated with increased urinary incontinence severity.

OBJECTIVE

This study aimed to test whether specific urinary or vaginal microbiome community types are associated with urinary incontinence severity in a population of women with mixed urinary incontinence.

STUDY DESIGN

This planned secondary, cross-sectional analysis evaluated associations between the urinary and vaginal microbiomes and urinary incontinence severity in a subset of Effects of Surgical Treatment Enhanced With Exercise for Mixed Urinary Incontinence trial participants with urinary incontinence. Incontinence severity was measured using bladder diaries and Urinary Distress Inventory questionnaires collected at baseline. Catheterized urine samples and vaginal swabs were concurrently collected before treatment at baseline to assess the urinary and vaginal microbiomes. Of note, 16S rRNA V4 to V6 variable regions were sequenced, characterizing bacterial taxa to the genus level using the DADA2 pipeline and SILVA database. Using Dirichlet multinomial mixtures methods, samples were clustered into community types based on core taxa. Associations between community types and severity measures (Urinary Distress Inventory total scores, Urinary Distress Inventory subscale scores, and the number of urinary incontinence episodes [total, urgency, and stress] from the bladder diary) were evaluated using linear regression models adjusted for age and body mass index. In addition, alpha diversity measures for richness (total taxa numbers) and evenness (proportional distribution of taxa abundance) were analyzed for associations with urinary incontinence episodes and community type.

RESULTS

Overall, 6 urinary microbiome community types were identified, characterized by varying levels of common genera (Lactobacillus, Gardnerella, Prevotella, Tepidimonas, Acidovorax, Escherichia, and others). The analysis of urinary incontinence severity in 126 participants with mixed urinary incontinence identified a Lactobacillus-dominated reference group with the highest abundance of Lactobacillus (mean relative abundance of 76%). A community characterized by fewer Lactobacilli (mean relative abundance of 19%) and greater alpha diversity was associated with higher total urinary incontinence episodes (2.67 daily leaks; 95% confidence interval, 0.76-4.59; P=.007) and urgency urinary incontinence episodes (1.75 daily leaks; 95% confidence interval, 0.24-3.27; P=.02) than the reference group. No significant association was observed between community type and stress urinary incontinence episodes or Urogenital Distress Inventory total or subscores. The composition of vaginal community types and urinary community types were similar but composed of slightly different bacterial taxa. Vaginal community types were not associated with urinary incontinence severity, as measured by bladder diary or Urogenital Distress Inventory total and subscale scores. Alpha diversity indicated that greater sample richness was associated with more incontinence episodes (observed genera P=.01) in urine. Measures of evenness (Shannon and Pielou) were not associated with incontinence severity in the urinary or vaginal microbiomes.

CONCLUSION

In the urobiome of women with mixed urinary incontinence, a community type with fewer Lactobacilli and more diverse bacteria was associated with more severe urinary incontinence episodes (total and urgency) compared with a community type with high predominance of a single genus, Lactobacillus. Whether mixed urinary incontinence severity is due to lesser predominance of Lactobacillus, greater presence of other non-Lactobacillus genera, or the complement of bacteria consisting of urobiome community types remains to be determined.

Influences of plant organ, genotype, and cultivation site on the endophytic bacteriome of maize (Zea mays L.) in the semi-arid region of Pernambuco, Brazil

Endophytic bacteria play a crucial role in plant development and adaptation, and the knowledge of how endophytic bacteria assemblage is influenced by cultivation site and plant genotype is an important step to achieve microbiome manipulation. This work aimed to study the roots and stems of endophytic bacteriome of four maize genotypes cultivated in two regions of the semi-arid region of Pernambuco - Brazil. Our hypothesis is that the endophytic community assemblage will be influenced by plant genotypes and cultivation region. Metabarcoding sequencing data revealed significant differences in alfa diversity in function of both factors, genotypes, and maize organs. Beta diversity analysis showed that the bacterial communities differ mainly in function of the plant organ. The most abundant genera found in the samples were Leifsonia, Bacillus, Klebsiella, Streptomyces, and Bradyrhizobium. To understand ecological interactions within each compartment, we constructed co-occurrence network for each organ. This analysis revealed important differences in network structure and complexity and suggested that Leifsonia (the main genera found) had distinct ecological roles depending on the plant organ. Our data showed that root endophytic maize bacteria would be influenced by cultivation site, but not by genotype. We believe that, collectively, our data not only characterize the bacteriome associated with this plant and how different factors shape it, but also increase the knowledge to select potential bacteria for bioinoculant production.

Dynamic root microbiome sustains soybean productivity under unbalanced fertilization

Root-associated microbiomes contribute to plant growth and health, and are dynamically affected by plant development and changes in the soil environment. However, how different fertilizer regimes affect quantitative changes in microbial assembly to effect plant growth remains obscure. Here, we explore the temporal dynamics of the root-associated bacteria of soybean using quantitative microbiome profiling (QMP) to examine its response to unbalanced fertilizer treatments (i.e., lacking either N, P or K) and its role in sustaining plant growth after four decades of unbalanced fertilization. We show that the root-associated bacteria exhibit strong succession during plant development, and bacterial loads largely increase at later stages, particularly for Bacteroidetes. Unbalanced fertilization has a significant effect on the assembly of the soybean rhizosphere bacteria, and in the absence of N fertilizer the bacterial community diverges from that of fertilized plants, while lacking P fertilizer impedes the total load and turnover of rhizosphere bacteria. Importantly, a SynCom derived from the low-nitrogen-enriched cluster is capable of stimulating plant growth, corresponding with the stabilized soybean productivity in the absence of N fertilizer. These findings provide new insights in the quantitative dynamics of the root-associated microbiome and highlight a key ecological cluster with prospects for sustainable agricultural management.

Fungal complexity and stability across afforestation areas in changing desert environments

The great achievements in combating desertification are attributed to large-scale afforestation, yet we lack verification of how the stability of the fungal community changes in afforestation areas in desert environments. Here, we present the fungal network structure from different niches (root and bulk soil) of plantations of Mongolian pine, a crucial species for afforestation introduced widely in desertification regions. We assessed changes in community complexity and stability of root-associated fungi (RAF) and soil fungi (SF) among different introduction sites: the Hulunbuir Desert (HB), the Horqin Desert (HQ) and the Mu Us Desert (MU). To illuminate the complexity and stability of the fungal network, the differences in topological properties, fungal function, and vegetation and environmental factors between introduction sites were fully considered. We showed that (1) the SF networks had more nodes and edges than the RAF networks. There was a lower ratio of negative:positive cohesion of RAF networks in HB and MU. For SF but not for RAF, across the three introduction sites, a higher modularity and ratio of negative:positive cohesion indicated higher stability. (2) Ectomycorrhizal (EcM) fungi were the dominant functional group in the RAF network (especially in HQ), and were only significantly correlated with vegetation factor. There was a higher relative abundance and number of OTUs of saprophytic fungi in the SF network and they showed positive correlations with soil nutrients. (3) RAF and SF network complexity and stability showed different responses to environmental and vegetation variables. The key determinant of the complexity and stability of the SF networks in Mongolian pine plantations was soil nutrients, followed by climate conditions. The composition and structure of the RAF community was closely related to host plants. Therefore, clarifying the complexity and stability of fungal communities in afforestation areas in changing desert environments is helpful for understanding the interactions between the environment, plants and fungi.