A network approach to elucidate and prioritize microbial dark matter in microbial communities

Plastic debris mediates bacterial community coalescence by breaking dispersal limitation in the sediments of a large river

Plastic debris has recently been proposed as a novel habitat for bacterial colonization, which can raise perturbations in bacterial ecology after burial in riverine sediments. However, community coalescence, as a prevalent process involving the interrelationships of multiple communities and their surrounding environments, has been rarely discussed to reveal the impact of the plastisphere on sedimentary bacterial community. This study analyzed the bacterial community in plastic debris and sediment along the Nujiang River, elucidating the role of the plastisphere in mediating community coalescence in sediments. Our results demonstrated that the plastisphere and sedimentary bacterial communities exhibited distinct biogeography along the river (r = 0.694, p < 0.01). Based on overlapped taxa and SourceTracker, the extent of coalescence between adjacent communities was in following orders: plastic-plastic (0.589) > plastic-sediment (0.561) > sediment-sediment (0.496), indicating the plastisphere promoted bacterial community coalescence along the river. Flow velocity and geographic distance were the major factors driving the plastisphere changes, suggesting that the plastisphere were vulnerable to dispersal. The null model and the neutral model provided additional support for the higher immigration ability of the plastisphere to overcome dispersal limitation, highlighting the potential importance of the plastisphere in community coalescence. Network analysis indicated the critical role of keystone species (Proteobacteria, Bacteroidetes, and Gemmatimonadetes) in mediating the coalescence between sedimentary bacterial community and the plastisphere. In summary, the plastisphere could mediate the coalescence of bacterial communities by overcoming dispersal limitation, which provides new perspectives on the plastisphere altering bacterial ecology in riverine sediments.

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.

Colon or semicolon: gut sampling microdevices for omics insights

Ingestible microdevices represent a breakthrough in non-invasive sampling of the human gastrointestinal (GI) tract. By capturing the native spatiotemporal microbiome and intricate biochemical gradients, these devices allow a non-invasive multi-omic access to the unperturbed host-microbiota crosstalk, immune/nutritional landscapes and gut-organ connections. We present the current progress of GI sampling microdevices towards personalized metabolism and fostering collaboration among clinicians, engineers, and data scientists.

Bacterial specialists playing crucial roles in maintaining system stability and governing microbial diversity in bioremediation of oil-polluted sediments under typical deep-sea condition

Ecologically, interactions and contributions of microbiota generalists and specialists remain largely unexplored in remediation of deep-sea oil pollution. Herein, ecological and evolutionary characteristics of the two taxa were comprehensively investigated in restoration of oil-polluted sediment at deep-sea microcosm. Niche-specialized taxa exhibited rapid speciation rate, more complex network structure and highly interspecific mutualism. In contrast, generalists possessed higher richness but with poor local performance, as evidenced by higher extinction rate, lower stability, and more interspecific antagonism. Generalists were the primary oil degraders, while specialists acted as auxiliaries promoting degradation via production of biofilm and biosurfactant. Evolutionarily, the continuous transition from specialists to generalists insured the exclusion of generalist at a relatively constant level for ecological trade-offs. Collectively, the findings emphasize the importance of specialists in facilitating oil degradation by elucidating their vital roles in maintaining system stability and regulating microbial diversity during process, and offer valuable guidance for designing remediation plans.

Assembling bacterial puzzles: piecing together functions into microbial pathways

Functional metagenomics enables the study of unexplored bacterial diversity, gene families, and pathways essential to microbial communities. However, discovering biological insights with these data is impeded by the scarcity of quality annotations. Here, we use a co-occurrence-based analysis of predicted microbial protein functions to uncover pathways in genomic and metagenomic biological systems. Our approach, based on phylogenetic profiles, improves the identification of functional relationships, or participation in the same biochemical pathway, between enzymes over a comparable homology-based approach. We optimized the design of our profiles to identify potential pathways using minimal data, clustered functionally related enzyme pairs into multi-enzymatic pathways, and evaluated our predictions against reference pathways in the KEGG database. We then demonstrated a novel extension of this approach to predict inter-bacterial protein interactions amongst members of a marine microbiome. Most significantly, we show our method predicts emergent biochemical pathways between known and unknown functions. Thus, our work establishes a basis for identifying the potential functional capacities of the entire metagenome, capturing previously unknown and abstract functions into discrete putative pathways.

Diversity and ecological assembly process of aerobic anoxygenic phototrophic bacteria in a low irradiation area, Three Gorges Reservoir

Aerobic anoxygenic phototrophic bacteria (AAPB) are significant bacterial groups in aquatic ecosystems, known for their rapid growth and photoheterotrophic characteristics. However, the distribution and ecological assembly process of AAPB in low irradiation freshwater basins remain unclear, warranting further investigation. In this study, we present the diversity, abundance, spatial variations, ecological process, and community interaction of AAPB in sediment of Three Gorges Reservoir (TGR) under low irradiation. Our findings demonstrate the dominant genera of AAPB community that exist in the TGR area also are appeared in different waters, with some regional preference. Moreover, the concentration of pufM gene, an indicator for AAPB, maintains a consistently high numerical level ranging from (2.21 ± 0.44) × 104 to (9.98 ± 0.30) × 107 gene copies/g. Although solar irradiation is suggested as the major factor affecting AAPB, it remains unclear whether and how AAPB differ between regions due to varying solar irradiation levels. Our results show spatial differences between total bacteria and AAPB communities, with significant differences observed only in AAPB. Geographical and environmental factor contributed less than 10% to the spatial difference of community, with sediment type and environmental factors being the key factors influencing microbial community structure. The stochastic process plays a dominant role in the aggregation and replacement of AAPB communities, among which the most contribution is dispersal limitation. For AAPB network, Yoonia and Gemmobacter are the hubs for modules. Those results valuable insights into the AAPB communities in TGR with low irradiation.

Soil keystone viruses are regulators of ecosystem multifunctionality

Ecosystem multifunctionality reflects the capacity of ecosystems to simultaneously maintain multiple functions which are essential bases for human sustainable development. Whereas viruses are a major component of the soil microbiome that drive ecosystem functions across biomes, the relationships between soil viral diversity and ecosystem multifunctionality remain under-studied. To address this critical knowledge gap, we employed a combination of amplicon and metagenomic sequencing to assess prokaryotic, fungal and viral diversity, and to link viruses to putative hosts. We described the features of viruses and their potential hosts in 154 soil samples from 29 farmlands and 25 forests distributed across China. Although 4,460 and 5,207 viral populations (vOTUs) were found in the farmlands and forests respectively, the diversity of specific vOTUs rather than overall soil viral diversity was positively correlated with ecosystem multifunctionality in both ecosystem types. Furthermore, the diversity of these keystone vOTUs, despite being 10-100 times lower than prokaryotic or fungal diversity, was a better predictor of ecosystem multifunctionality and more strongly associated with the relative abundances of prokaryotic genes related to soil nutrient cycling. Gemmatimonadota and Actinobacteria dominated the host community of soil keystone viruses in the farmlands and forests respectively, but were either absent or showed a significantly lower relative abundance in that of soil non-keystone viruses. These findings provide novel insights into the regulators of ecosystem multifunctionality and have important implications for the management of ecosystem functioning.

Difference in microbial community structure along a gradient of crater altitude: insights from the Nushan volcano

The variation in the soil microbial community along the altitude gradient has been widely documented. However, the structure and function of the microbial communities distributed along the altitude gradient in the crater still need to be determined. We gathered soil specimens from different elevations within the Nushan volcano crater to bridge this knowledge gap. We investigated the microbial communities of bacteria and fungi in the soil. It is noteworthy that the microbial alpha diversity peaks in the middle of the crater. However, network analysis shows that bacterial (nodes 760 vs 613 vs 601) and fungal (nodes 328 vs 224 vs 400) communities are most stable at the bottom and top of the crater, respectively. Furthermore, the soil microbial network exhibited a decline, followed by an increase across varying altitudes. The core microorganisms displayed the highest correlation with pH and alkaline phosphatase (AP, as determined through redundancy analysis (RDA) and Mantel tests for correlation analysis. The fungal community has a higher number of core microorganisms, while the bacterial core microorganisms demonstrate greater susceptibility to environmental factors. In conclusion, we utilized Illumina sequencing techniques to assess the disparities in the structure and function of bacteria and fungi in the soil.IMPORTANCEThese findings serve as a foundation for future investigations on microbial communities present in volcanic soil.

Impact of Combined Pollution of Ciprofloxacin and Copper on the Diversity of Archaeal Communities and Antibiotic-Resistance Genes

This study aimed to explore the response of archaeal communities and antibiotic-resistance genes (ARGs) to ciprofloxacin (CIP, 0.05-40 mg/L) and copper (Cu, 3 mg/L) combined pollution during stress- and post-effect periods in an activated sludge system. With the increase in the CIP concentration, the diversity of archaea decreased, but the richness increased under the stress of 10 mg/L CIP. Under stress and post effects, the change in unknown archaeal community structure was more significant than that of the known archaea. The relative abundance of unknown archaea was significantly reduced with the increase in CIP concentration. Meanwhile, there were certain archaea that belonged to abundant and rare taxa with different resistance and recovery characteristics. Among them, Methanosaeta (49.15-83.66%), Methanoculleus (0.11-0.45%), and Nitrososphaera (0.03-0.36%) were the typical resistant archaea to combined pollution. And the resistance of the abundant taxa to combined pollution was significantly higher than that of the rare taxa. Symbiotic and competitive relationships were observed between the known and the unknown archaea. The interactions of abundant known taxa were mainly symbiotic relationships. While the rare unknown taxa were mainly competitive relationships in the post-effect period. Rare archaea showed an important ecological niche under the stress-effect. Some archaea displayed positive correlation with ARGs and played important roles as potential hosts of ARGs during stress- and post-periods. Methanospirillum, Methanosphaerula, Nitrososphaera and some rare unknown archaea also significantly co-occurred with a large number of ARGs. Overall, this study points out the importance of interactions among known and unknown archaeal communities and ARGs in a wastewater treatment system under the stress of antibiotics and heavy metal combined pollution.

The Y-ome Conundrum: Insights into Uncharacterized Genes and Approaches for Functional Annotation

The ever-increasing availability of genome sequencing data has revealed a substantial number of uncharacterized genes without known functions across various organisms. The first comprehensive genome sequencing of E. coli K12 revealed that more than 50% of its open reading frames corresponded to transcripts with no known functions. The group of protein-coding genes without a functional description and/or a recognized pathway, beginning with the letter "Y", is classified as the "y-ome". Several efforts have been made to elucidate the functions of these genes and to recognize their role in biological processes. This review provides a brief update on various strategies employed when studying the y-ome, such as high-throughput experimental approaches, comparative omics, metabolic engineering, gene expression analysis, and data integration techniques. Additionally, we highlight recent advancements in functional annotation methods, including the use of machine learning, network analysis, and functional genomics approaches. Novel approaches are required to produce more precise functional annotations across the genome to reduce the number of genes with unknown functions.

Global WWTP Microbiome-based Integrative Information Platform: From experience to intelligence

Domestic and industrial wastewater treatment plants (WWTPs) are facing formidable challenges in effectively eliminating emerging pollutants and conventional nutrients. In microbiome engineering, two approaches have been developed: a top-down method focusing on domesticating seed microbiomes into engineered ones, and a bottom-up strategy that synthesizes engineered microbiomes from microbial isolates. However, these approaches face substantial hurdles that limit their real-world applicability in wastewater treatment engineering. Addressing this gap, we propose the creation of a Global WWTP Microbiome-based Integrative Information Platform, inspired by the untapped microbiome and engineering data from WWTPs and advancements in artificial intelligence (AI). This open platform integrates microbiome and engineering information globally and utilizes AI-driven tools for identifying seed microbiomes for new plants, providing technical upgrades for existing facilities, and deploying microbiomes for accidental pollution remediation. Beyond its practical applications, this platform has significant scientific and social value, supporting multidisciplinary research, documenting microbial evolution, advancing Wastewater-Based Epidemiology, and enhancing global resource sharing. Overall, the platform is expected to enhance WWTPs' performance in pollution control, safeguarding a harmonious and healthy future for human society and the natural environment.

Microbial co-occurrence network demonstrates spatial and climatic trends for global soil diversity

Despite recent research efforts to explore the co-occurrence patterns of diverse microbes within soil microbial communities, a substantial knowledge-gap persists regarding global climate influences on soil microbiota behaviour. Comprehending co-occurrence patterns within distinct geoclimatic groups is pivotal for unravelling the ecological structure of microbial communities, that are crucial for preserving ecosystem functions and services. Our study addresses this gap by examining global climatic patterns of microbial diversity. Using data from the Earth Microbiome Project, we analyse a meta-community co-occurrence network for bacterial communities. This method unveils substantial shifts in topological features, highlighting regional and climatic trends. Arid, Polar, and Tropical zones show lower diversity but maintain denser networks, whereas Temperate and Cold zones display higher diversity alongside more modular networks. Furthermore, it identifies significant co-occurrence patterns across diverse climatic regions. Central taxa associated with different climates are pinpointed, highlighting climate's pivotal role in community structure. In conclusion, our study identifies significant correlations between microbial interactions in diverse climatic regions, contributing valuable insights into the intricate dynamics of soil microbiota.

Uncovering the microbial community structure and physiological profiles of terrestrial mud volcanoes: A comprehensive metagenomic insight towards their trichloroethylene biodegradation potentiality

Mud volcanoes are dynamic geological features releasing methane (CH4), carbon dioxide (CO2), and hydrocarbons, harboring diverse methane and hydrocarbon-degrading microbes. However, the potential application of these microbial communities in chlorinated hydrocarbons bioremediation purposes such as trichloroethylene (TCE) has not yet been explored. Hence, this study investigated the mud volcano's microbial diversity functional potentiality in TCE degradation as well as their eco-physiological profiling using metabolic activity. Geochemical analysis of the mud volcano samples revealed variations in pH, temperature, and oxidation-reduction potential, indicating diverse environmental conditions. The Biolog Ecoplate™ carbon substrates utilization pattern showed that the Tween 80 was highly consumed by mud volcanic microbial community. Similarly, MicroResp® analysis results demonstrated that presence of additive C-substrates condition might enhanced the cellular respiration process within mud-volcanic microbial community. Full-length 16 S rRNA sequencing identified Proteobacteria as the dominant phylum, with genera like Pseudomonas and Hydrogenophaga associated with chloroalkane degradation, and methanotrophic bacteria such as Methylomicrobium and Methylophaga linked to methane oxidation. Functional analysis uncovered diverse metabolic functions, including sulfur and methane metabolism and hydrocarbon degradation, with specific genes involved in methane oxidation and sulfur metabolism. These findings provide insights into the microbial diversity and metabolic capabilities of mud volcano ecosystems, which could facilitate their effective application in the bioremediation of chlorinated compounds.

Exploring nature's filters: Peat-mineral mix for low and high-strength oilfield produced water reclamation

Nature-based solutions are encouraged for treating oilfield produced water from oil and gas extraction, a crucial undertaking that aligns with the Canadian oil sands industry's ambitious goal of zero waste, and the globally recognized Sustainable Development Goals (SDGs) pertaining to water conservation and ecosystem preservation. This study explored the use of peat-mineral mix (PMM), a leftover of inevitable oil sands mining, for treating low and high-strength wastewaters during biofiltration, which contained large molecular weight (44.3 kDa), which include alcohols, aliphatics, aromatics, and ketones, and can impart high toxicity to both fauna and flora (MicroTox: 99 %). The breakthrough curve indicated an effective initial adsorption phase driven by advection within the column dynamics. For complete organics removal and mechanistic insights, the wastewater was re-circulated in a continuous mode for up to 42 days. Here, we found that chemical oxygen demand was reduced from ∼85,000 mg/L to ∼965 mg/L). Kinetics investigations along with physicochemical characterization of PMM and wastewater suggested that chemisorption and anaerobic digestion contributed to the overall removal of contaminants. Chemisorption, led by hydrogen bonding and hydrophobic interactions, was the dominant mechanism, with a limited contribution from physical adsorption (surface area: 2.85 m2/g). The microbial community within the PMM bed was rich/diverse (Shannon > 6.0; Chao1 > 600), with ∼ 50 % unclassified phylotypes representing 'microbial dark matter'. High electric conductivity (332.1 μS cm-1) of PMM and the presence of Geobacter, syntrophs, and Methanosaeta suggest that direct interspecies electron transfer was likely occurring during anaerobic digestion. Both low and high-strength wastewaters showed effective removal of dissolved organics (e.g., naphthenic acids, acid extractable fraction, oil and grease content), nutrients, and potentially toxic metals. The successful use of PMM in treating oilfield produced water offers promising avenues for embracing nature-based remediation solutions at oil refining sites.

Meta-omics assisted microbial gene and strain resources mining in contaminant environment

Human activities have led to the release of various environmental pollutants, triggering ecological challenges. In situ, microbial communities in these contaminated environments are usually assumed to possess the potential capacity of pollutant degradation. However, the majority of genes and microorganisms in these environments remain uncharacterized and uncultured. The advent of meta-omics provided culture-independent solutions for exploring the functional genes and microorganisms within complex microbial communities. In this review, we highlight the applications and methodologies of meta-omics in uncovering of genes and microbes from contaminated environments. These findings may assist in future bioremediation research.

Regulation of wheat growth by soil multifunctionality and metagenomic-based microbial functional profiles under mulching treatments

Soil microbial functional genes play key roles in biogeochemical processes that are closely related to crop development. However, the regulation of crop growth by the composition and potential interactions of metagenomic-based functional genes is poorly understood. Therefore, in a long-term mulching experiment, the regulation of wheat growth by soil multifunctionality, microbial functional profiles driven by soil properties and microbial activity was studied. Soil properties and microbial activity were significantly separated into distinct mulching treatments, and were significantly declined by plastic film mulching treatment, similar to soil multifunctionality. Only carbon (C) and phosphorus (P) cycling gene compositions were divided significantly into distinct mulching treatments to varying degrees. Similarly, intra- and inter-connected sub-networks associated with C and P cycling genes were more complex and stable than the sub-networks containing nitrogen cycling genes. Despite core functional genes being located in the middle of each network, they were rarely observed in the metagenomic assembly genomes. Subsequently, the dominant soil properties and microbial activity had greater effects on C cycling gene composition and network, which played essential roles in wheat growth regulation. Overall, wheat yield and biomass were affected differently by straw and plastic film mulching treatments, and were mainly regulated by C cycling gene network and soil multifunctionality, respectively. The results of the present study provide novel insights into wheat growth regulation by soil microbial functional profiles, with potential implications for sustainable crop production in mulching conservation agroecosystems.

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.

Bisphenol A exposure affects specific gut taxa and drives microbiota dynamics in childhood obesity

Cumulative xenobiotic exposure has an environmental and human health impact which is currently assessed under the One Health approach. Bisphenol A (BPA) exposure and its potential link with childhood obesity that has parallelly increased during the last decades deserve special attention. It stands during prenatal or early life and could trigger comorbidities and non-communicable diseases along life. Accumulation in the nature of synthetic chemicals supports the "environmental obesogen" hypothesis, such as BPA. This estrogen-mimicking xenobiotic has shown endocrine disruptive and obesogenic effects accompanied by gut microbiota misbalance that is not yet well elucidated. This study aimed to investigate specific microbiota taxa isolated and selected by direct BPA exposure and reveal its role on the overall children microbiota community and dynamics, driving toward specific obesity dysbiosis. A total of 333 BPA-resistant isolated species obtained through culturing after several exposure conditions were evaluated for their role and interplay with the global microbial community. The selected BPA-cultured taxa biomarkers showed a significant impact on alpha diversity. Specifically, Clostridium and Romboutsia were positively associated promoting the richness of microbiota communities, while Intestinibacter, Escherichia-Shigella, Bifidobacterium, and Lactobacillus were negatively associated. Microbial community dynamics and networks analyses showed differences according to the study groups. The normal-weight children group exhibited a more enriched, structured, and connected taxa network compared to overweight and obese groups, which could represent a more resilient community to xenobiotic substances. In this sense, subnetwork analysis generated with the BPA-cultured genera showed a correlation between taxa connectivity and more diverse potential enzymatic BPA degradation capacities.IMPORTANCEOur findings indicate how gut microbiota taxa with the capacity to grow in BPA were differentially represented within differential body mass index children study groups and how these taxa affected the overall dynamics toward patterns of diversity generally recognized in dysbiosis. Community network and subnetwork analyses corroborated the better connectedness and stability profiles for normal-weight group compared to the overweight and obese groups.

Effects of operational parameters on bacterial communities in Hong Kong and global wastewater treatment plants

Wastewater treatment plants (WWTPs) are indispensable biotechnology facilities for modern cities and play an essential role in modern urban infrastructure by employing microorganisms to remove pollutants in wastewater, thus protecting public health and the environment. This study conducted a 13-month bacterial community survey of six full-scale WWTPs in Hong Kong with samples of influent, activated sludge (AS), and effluent to explore their synchronism and asynchronism of bacterial community. Besides, we compared AS results of six Hong Kong WWTPs with data from 1,186 AS amplicon data in 269 global WWTPs and a 9-year metagenomic sequencing survey of a Hong Kong WWTP. Our results showed the compositions of bacterial communities varied and the bacterial community structure of AS had obvious differences across Hong Kong WWTPs. The co-occurrence analysis identified 40 pairs of relationships that existed among Hong Kong WWTPs to show solid associations between two species and stochastic processes took large proportions for the bacterial community assembly of six WWTPs. The abundance and distribution of the functional bacteria in worldwide and Hong Kong WWTPs were examined and compared, and we found that ammonia-oxidizing bacteria had more diversity than nitrite-oxidizing bacteria. Besides, Hong Kong WWTPs could make great contributions to the genome mining of microbial dark matter in the global "wanted list." Operational parameters had important effects on OTUs' abundance, such as the temperature to the genera of Tetrasphaera, Gordonia and Nitrospira. All these results obtained from this study can deepen our understanding of the microbial ecology in WWTPs and provide foundations for further studies.

IMPORTANCE

Wastewater treatment plants (WWTPs) are an indispensable component of modern cities, as they can remove pollutants in wastewater to prevent anthropogenic activities. Activated sludge (AS) is a fundamental wastewater treatment process and it harbors a highly complex microbial community that forms the main components and contains functional groups. Unveiling "who is there" is a long-term goal of the research on AS microbiology. High-throughput sequencing provides insights into the inventory diversity of microbial communities to an unprecedented level of detail. At present, the analysis of communities in WWTPs usually comes from a specific WWTP and lacks comparisons and verification among different WWTPs. The wide-scale and long-term sampling project and research in this study could help us evaluate the AS community more accurately to find the similarities and different results for different WWTPs in Hong Kong and other regions of the world.

Assigning the unassigned: A signature-based classification of rDNA metabarcodes reveals new deep-sea diversity

Environmental DNA metabarcoding reveals a vast genetic diversity of marine eukaryotes. Yet, most of the metabarcoding data remain unassigned due to the paucity of reference databases. This is particularly true for the deep-sea meiofauna and eukaryotic microbiota, whose hidden diversity is largely unexplored. Here, we tackle this issue by using unique DNA signatures to classify unknown metabarcodes assigned to deep-sea foraminifera. We analyzed metabarcoding data obtained from 311 deep-sea sediment samples collected in the Clarion-Clipperton Fracture Zone, an area of potential polymetallic nodule exploitation in the Eastern Pacific Ocean. Using the signatures designed in the 37F hypervariable region of the 18S rRNA gene, we were able to classify 802 unassigned metabarcodes into 61 novel lineages, which have been placed in 27 phylogenetic clades. The comparison of new lineages with other foraminiferal datasets shows that most novel lineages are widely distributed in the deep sea. Five lineages are also present in the shallow-water datasets; however, phylogenetic analysis of these lineages separates deep-sea and shallow-water metabarcodes except in one case. While the signature-based classification does not solve the problem of gaps in reference databases, this taxonomy-free approach provides insight into the distribution and ecology of deep-sea species represented by unassigned metabarcodes, which could be useful in future applications of metabarcoding for environmental monitoring.

Peeling off the layers from microbial dark matter (MDM): recent advances, future challenges, and opportunities

Microbes represent the most common organisms on Earth; however, less than 2% of microbial species in the environment can undergo cultivation for study under laboratory conditions, and the rest of the enigmatic, microbial world remains mysterious, constituting a kind of "microbial dark matter" (MDM). In the last two decades, remarkable progress has been made in culture-dependent and culture-independent techniques. More recently, studies of MDM have relied on culture-independent techniques to recover genetic material through either unicellular genomics or shotgun metagenomics to construct single-amplified genomes (SAGs) and metagenome-assembled genomes (MAGs), respectively, which provide information about evolution and metabolism. Despite the remarkable progress made in the past decades, the functional diversity of MDM still remains uncharacterized. This review comprehensively summarizes the recently developed culture-dependent and culture-independent techniques for characterizing MDM, discussing major challenges, opportunities, and potential applications. These activities contribute to expanding our knowledge of the microbial world and have implications for various fields including Biotechnology, Bioprospecting, Functional genomics, Medicine, Evolutionary and Planetary biology. Overall, this review aims to peel off the layers from MDM, shed light on recent advancements, identify future challenges, and illuminate the exciting opportunities that lie ahead in unraveling the secrets of this intriguing microbial realm.

Microbiome Dynamics: A Paradigm Shift in Combatting Infectious Diseases

Infectious diseases have long posed a significant threat to global health and require constant innovation in treatment approaches. However, recent groundbreaking research has shed light on a previously overlooked player in the pathogenesis of disease-the human microbiome. This review article addresses the intricate relationship between the microbiome and infectious diseases and unravels its role as a crucial mediator of host-pathogen interactions. We explore the remarkable potential of harnessing this dynamic ecosystem to develop innovative treatment strategies that could revolutionize the management of infectious diseases. By exploring the latest advances and emerging trends, this review aims to provide a new perspective on combating infectious diseases by targeting the microbiome.

Searching for microbial contribution to micritization of shallow marine sediments

Micritization is an early diagenetic process that gradually alters primary carbonate sediment grains through cycles of dissolution and reprecipitation of microcrystalline calcite (micrite). Typically observed in modern shallow marine environments, micritic textures have been recognized as a vital component of storage and flow in hydrocarbon reservoirs, attracting scientific and economic interests. Due to their endolithic activity and the ability to promote nucleation and reprecipitation of carbonate crystals, microorganisms have progressively been shown to be key players in micritization, placing this process at the boundary between the geological and biological realms. However, published research is mainly based on geological and geochemical perspectives, overlooking the biological and ecological complexity of microbial communities of micritized sediments. In this paper, we summarize the state-of-the-art and research gaps in micritization from a microbial ecology perspective. Since a growing body of literature successfully applies in vitro and in situ 'fishing' strategies to unveil elusive microorganisms and expand our knowledge of microbial diversity, we encourage their application to the study of micritization. By employing these strategies in micritization research, we advocate promoting an interdisciplinary approach/perspective to identify and understand the overlooked/neglected microbial players and key pathways governing this phenomenon and their ecology/dynamics, reshaping our comprehension of this process.

Graphene oxide stimulated low-temperature denitrification activity of microbial communities in lake sediments by enhancing anabolism and inhibiting cellular respiration

Nitrate pollution in fresh water is becoming increasingly serious. In this study, the effects of temperature and graphene oxide materials on the potential functions of denitrification communities in lake sediments were investigated by metagenome. The addition of graphene oxide significantly affected the abundance of denitrification genes such as Nap, Nos, and enhanced the contribution of Pseudomonas, making low temperature and material addition conducive to the denitrification process. Module network implied that low temperature increased the centrality of denitrification in community functions. At low temperatures, graphene oxide enhanced community anabolism by stimulation organic carbon consumption and regulating the gene abundance in the citric acid cycle and the semi-phosphorylation Entner-Doudoroff, thus possibly stimulating extracellular polymeric substances (EPS) synthesis and secretion. In addition, graphene oxide may also regulate the transfer of reducing electrons from NADH to denitrifying enzymes by affecting the gene abundances of complex I and complex IV.

Bacterially enhanced plant-growing media for controlled environment agriculture

Microbe-plant interactions in the root zone not only shape crop performance in soil but also in hydroponic cultivation systems. The biological and physicochemical properties of the plant-growing medium determine the root-associated microbial community and influence bacterial inoculation effectiveness, which affects plant growth. This study investigated the combined impact of plant-growing media composition and bacterial community inoculation on the root-associated bacterial community of hydroponically grown lettuce (Lactuca sativa L.). Ten plant-growing media were composed of varying raw materials, including black peat, white peat, coir pith, wood fibre, composted bark, green waste compost, perlite and sand. In addition, five different bacterial community inocula (BCI S1-5) were collected from the roots of lettuce obtained at different farms. After inoculation and cultivation inside a vertical farm, lettuce root-associated bacterial community structures, diversity and compositions were determined by evaluating 16S rRNA gene sequences. The study revealed distinct bacterial community structures among experimental replicates, highlighting the influence of raw material variations on root-associated bacterial communities, even at the batch level. However, bacterial community inoculation allowed modulation of the root-associated bacterial communities independently from the plant-growing medium composition. Bacterial diversity was identified as a key determinant of plant growth performance with green waste compost introducing Bacilli and Actinobacteria, and bacterial community inoculum S3 introducing Pseudomonas, which positively correlated with plant growth. These findings challenge the prevailing notion of hydroponic cultivation systems as sterile environments and highlight the significance of proper plant-growing media raw material selection and bacterial community inoculation in shaping root-associated microbiomes that provide stability through microbial diversity. This study supports the concept of creating bacterially enhanced plant-growing media to promote plant growth in controlled environment agriculture.

Dynamics of rhizosphere microbial structure and function associated with the biennial bearing of moso bamboo

Moso bamboo (Phyllostachys edulis) is a valuable nontimber forestry product with a biennial cycle, producing abundant bamboo shoots within one year (on-year) and few shoots within the following year (off-year). Moso bamboo plants undergo clonal reproduction, resulting in similar genetic backgrounds. However, the number of moso bamboo shoots produced each year varies. Despite this variation, the impact of soil nutrients and the root microbiome on the biennial bearing of moso bamboo is poorly understood. We collected 139 soil samples and determined 14 major physicochemical properties of the rhizosphere, rhizoplane, and bulk soil in different seasons (i.e., the growing and deciduous seasons) and different years (i.e., on- and off-years). Based on 16S rRNA and metagenomic sequencing, major variations were found in the rhizospheric microbial composition during different seasons and years in the moso bamboo forest. Environmental driver analysis revealed that essential nutrients (i.e., SOC, TOC, TN, P, and NH4+) were the main drivers of the soil microbial community composition and were correlated with the on- and off-year cycles. Moreover, 19 MAGs were identified as important biomarkers that could distinguish on- and off-years. We found that both season and year influenced both the microbial community structure and functional pathways through the biosynthesis of nutrients that potentially interact with the moso bamboo growth rhythm, especially the on-year root-associated microbiome, which had a greater abundance of specific nutrients such as gibberellins and vitamin B6. This work provides a dynamic perspective of the differential responses of various on- and off-year microbial communities and enhances our understanding of bamboo soil microbiome biodiversity and stability.

Dynamics of the sedimentary bacterial communities in a plain river network: similar coalescence patterns with bacterioplankton communities driven by distinct assembly processes

IMPORTANCE

Microorganisms play important roles in driving the biogeochemical cycles within river ecosystems. It has been suggested that hydrologic conditions could influence microbial communities in rivers, but their specific effects on the behaviours of microbial coalescence have not been thoroughly investigated. In this study, the dynamics of sedimentary bacterial communities within a plain river network were analyzed by amplicon sequencing followed by several ecological models to uncover the underlying assembly processes. Additionally, a comparative analysis between bacterioplankton communities and sedimentary bacterial communities was performed to unveil their coalescence patterns. The results suggested that similar coalescence patterns between sedimentary bacterial and bacterioplankton communities were driven by distinct assembly processes under dynamic hydrological conditions. These findings enhanced our understanding of microbial diversity features within river ecosystems.

In situ devices can culture the microbial dark matter of corals

Most microorganisms found in environmental samples have never been cultured and can often only be explored through molecular or microscopic approaches. Here, we adapt the use of in situ diffusion-based devices to culture "yet-to-be-cultured" microorganisms associated with coral mucus and compare this with a traditional culturing method. The culturability of microorganisms associated with mucus of the coral Pocillopora damicornis increased by 420% and 570% with diffusion growth chambers and microwell chip devices, respectively, compared with the traditional method tested. The obtained cultures represent up to 64.4% of the total diversity of amplicon sequence variants (ASVs) found in the mucus of the coral P. damicornis. In addition, some previously uncultured microorganisms, such as members of the family Nitrosopumilaceae and halophilic/halotolerant bacteria were cultured. Our results validate alternative microbial culturing strategies to culture coral-associated microorganisms, while significantly increasing the culturability of previous microbial dark matter.

Effect of castration timing and weaning strategy on the taxonomic and functional profile of ruminal bacteria and archaea of beef calves

BACKGROUND

Beef cattle experience several management challenges across their lifecycle. Castration and weaning, two major interventions in the early life of beef cattle, can have a substantial impact on animal performance. Despite the key role of the rumen microbiome on productive traits of beef cattle, the effect of castration timing and weaning strategy on this microbial community has not been formally described. We assessed the effect of four castration time windows (at birth, turnout, pre-weaning and weaning) and two weaning strategies (fence-line and truck transportation) on the rumen microbiome in a randomized controlled study with 32 male calves across 3 collection days (i.e., time points). Ruminal fluid samples were submitted to shotgun metagenomic sequencing and changes in the taxonomic (microbiota) and functional profile (metagenome) of the rumen microbiome were described.

RESULTS

Using a comprehensive yet stringent taxonomic classification approach, we identified 10,238 unique taxa classified under 40 bacterial and 7 archaeal phyla across all samples. Castration timing had a limited long-term impact on the rumen microbiota and was not associated with changes in alpha and beta diversity. The interaction of collection day and weaning strategy was associated with changes in the rumen microbiota, which experienced a significant decrease in alpha diversity and shifts in beta diversity within 48 h post-weaning, especially in calves abruptly weaned by truck transportation. Calves weaned using a fence-line weaning strategy had lower relative abundance of Bacteroides, Lachnospira, Fibrobacter and Ruminococcus genera compared to calves weaned by truck transportation. Some genes involved in the hydrogenotrophic methanogenesis pathway (fwdB and fwdF) had higher relative abundance in fence-line-weaned calves post-weaning. The antimicrobial resistance gene tetW consistently represented more than 50% of the resistome across time, weaning and castration groups, without significant changes in relative abundance.

CONCLUSIONS

Within the context of this study, castration timing had limited long-term effects on the rumen microbiota, while weaning strategy had short-term effects on the rumen microbiota and methane-associated metagenome, but not on the rumen resistome.

Association between host nitrogen absorption and root-associated microbial community in field-grown wheat

Plant roots and rhizosphere soils assemble diverse microbial communities, and these root-associated microbiomes profoundly influence host development. Modern wheat has given rise to numerous cultivars for its wide range of ecological adaptations and commercial uses. Variations in nitrogen uptake by different wheat cultivars are widely observed in production practices. However, little is known about the composition and structure of the root-associated microbiota in different wheat cultivars, and it is not sure whether root-associated microbial communities are relevant in host nitrogen absorption. Therefore, there is an urgent need for systematic assessment of root-associated microbial communities and their association with host nitrogen absorption in field-grown wheat. Here, we investigated the root-associated microbial community composition, structure, and keystone taxa in wheat cultivars with different nitrogen absorption characteristics at different stages and their relationships with edaphic variables and host nitrogen uptake. Our results indicated that cultivar nitrogen absorption characteristics strongly interacted with bacterial and archaeal communities in the roots and edaphic physicochemical factors. The impact of host cultivar identity, developmental stage, and spatial niche on bacterial and archaeal community structure and network complexity increased progressively from rhizosphere soils to roots. The root microbial community had a significant direct effect on plant nitrogen absorption, while plant nitrogen absorption and soil temperature also significantly influenced root microbial community structure. The cultivar with higher nitrogen absorption at the jointing stage tended to cooperate with root microbial community to facilitate their own nitrogen absorption. Our work provides important information for further wheat microbiome manipulation to influence host nitrogen absorption. KEY POINTS: • Wheat cultivar and developmental stage affected microbiome structure and network. • The root microbial community strongly interacted with plant nitrogen absorption. • High nitrogen absorption cultivar tended to cooperate with root microbiome.

Responses of soil and collembolan (Folsomia candida) gut microbiomes to 6PPD-Q pollution

The potential risk of N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-Q) to soil organisms remains poorly understood. Here we showed that 6PPD-Q pollution inhibited the survival of collembolans (Folsomia candida) with the chronic median lethal concentration (LC50) of 16.31 μg kg-1 in a 28-day soil culture. The microbe-microbe interactions between abundant taxa in soil and collembolan gut helped alleviate the negative impact of 6PPD-Q on soil microbial community, while rare taxa contributed to maintaining microbial network complexity and stability under 6PPD-Q stresses. Gammaproteobacteria, Alphaproteobacteria and Actinobacteria in the gut of both adult and juvenile collembolans were identified as potential indicators for 6PPD-Q exposure. Such responses were accompanied by increases in the relative abundances of genes involved in nutrient cycles and their interactions between soil and collembolan gut microbiomes, which enhanced nitrogen and carbon turnover in 6PPD-Q polluted soil, potentially alleviating the stresses caused by 6PPD-Q. Overall, this study sheds new light on the toxicity of 6PPD-Q to soil organisms and links 6PPD-Q stresses to microbial responses and soil functions, thus highlighting the urgency of assessing its potential risk to the terrestrial ecosystem.

Unravelling the dynamics of soil microbial communities under the environmental selection and range shift process in afforestation ecosystems

The process of forest range shift not only affects the vegetation aboveground but also influences the dynamics of belowground microbial communities. To investigate the changes in soil under forest range shift, we examined the natural forest soil microbiome along with its corresponding physicochemical properties, as well as the afforestation of natural forest by seedlings and sowing. By utilizing natural forests and employing different afforestation methods, we simulated the three stages of forest range shift: the staging stage, regeneration, and colonization. We employed network analysis and phylogenetic assemblages to examine the structure of soil microbial communities during these three stages in a macro-environmental change context. Ordination and regression analyses were also used to explore the correlation between microorganisms, environmental factors, and changes in their niches. The findings revealed that different afforestation (range shift) types led to distinct microbial compositions. Seedling afforestation exhibited similarities to mature forests, suggesting a significant influence on below-ground microorganisms. In contrast, sowing-based afforestation resulted in small changes in soil microbes, indicating a legacy effect on grassland soils. The impact of the rhizosphere on microbial composition remained consistent across the three forest types. Overall, this study underscores the significance of forest range shift in shaping soil microbial communities and emphasizes the need to consider these dynamics in forest management and restoration endeavours.

Microbial dark matter sequences verification in amplicon sequencing and environmental metagenomics data

Although microorganisms constitute the most diverse and abundant life form on Earth, in many environments, the vast majority of them remain uncultured. As it is based on information gleaned mainly from cultivated microorganisms, our current body of knowledge regarding microbial life is partial and does not reflect actual microbial diversity. That diversity is hidden in the uncultured microbial majority, termed by microbiologists as "microbial dark matter" (MDM), a term borrowed from astrophysics. Metagenomic sequencing analysis techniques (both 16S rRNA gene and shotgun sequencing) compare gene sequences to reference databases, each of which represents only a small fraction of the existing microorganisms. Unaligned sequences lead to groups of "unknown microorganisms" that are usually ignored and rarefied from diversity analysis. To address this knowledge gap, we analyzed the 16S rRNA gene sequences of microbial communities from four different environments-a living organism, a desert environment, a natural aquatic environment, and a membrane bioreactor for wastewater treatment. From those datasets, we chose representative sequences of potentially unknown bacteria for additional examination as "microbial dark matter sequences" (MDMS). Sequence existence was validated by specific amplification and re-sequencing. These sequences were screened against databases and aligned to the Genome Taxonomy Database to build a comprehensive phylogenetic tree for additional sequence classification, revealing potentially new candidate phyla and other lineages. These putative MDMS were also screened against metagenome-assembled genomes from the explored environments for additional validation and for taxonomic and metabolic characterizations. This study shows the immense importance of MDMS in environmental metataxonomic analyses of 16S rRNA gene sequences and provides a simple and readily available methodology for the examination of MDM hidden behind amplicon sequencing results.

Insights into the prokaryotic communities of the abyssal-hadal benthic-boundary layer of the Kuril Kamchatka Trench

BACKGROUND

The Kuril-Kamchatka Trench (maximum depth 9604 m), located in the NW Pacific Ocean, is among the top seven deepest hadal trenches. The work aimed to investigate the unexplored abyssal-hadal prokaryotic communities of this fascinating, but underrated environment.

RESULTS

As for the bacterial communities, we found that Proteobacteria (56.1-74.5%), Bacteroidetes (6.5-19.1%), and Actinobacteria (0.9-16.1%) were the most represented bacterial phyla over all samples. Thaumarchaeota (52.9-91.1%) was the most abundant phylum in the archaeal communities. The archaeal diversity was highly represented by the ammonia-oxidizing Nitrosopumilus, and the potential hydrocarbon-degrading bacteria Acinetobacter, Zhongshania, and Colwellia were the main bacterial genera. The α-diversity analysis evidenced that both prokaryotic communities were characterized by low evenness, as indicated by the high Gini index values (> 0.9). The β-diversity analysis (Redundancy Analysis) indicated that, as expected, the depth significantly affected the structure of the prokaryotic communities. The co-occurrence network revealed seven prokaryotic groups that covaried across the abyssal-hadal zone of the Kuril-Kamchatka Trench. Among them, the main group included the most abundant archaeal and bacterial OTUs (Nitrosopumilus OTU A2 and OTU A1; Acinetobacter OTU B1), which were ubiquitous across the trench.

CONCLUSIONS

This manuscript represents the first attempt to characterize the prokaryotic communities of the KKT abyssal-hadal zone. Our results reveal that the most abundant prokaryotes harbored by the abyssal-hadal zone of Kuril-Kamchatka Trench were chemolithotrophic archaea and heterotrophic bacteria, which did not show a distinctive pattern distribution according to depth. In particular, Acinetobacter, Zhongshania, and Colwellia (potential hydrocarbon degraders) were the main bacterial genera, and Nitrosopumilus (ammonia oxidizer) was the dominant representative of the archaeal diversity.

Cultivation strategies for prokaryotes from extreme environments

The great majority of microorganisms are as-yet-uncultivated, mostly found in extreme environments. High-throughput sequencing provides data-rich genomes from single-cell and metagenomic techniques, which has enabled researchers to obtain a glimpse of the unexpected genetic diversity of "microbial dark matter." However, cultivating microorganisms from extreme environments remains essential for dissecting and utilizing the functions of extremophiles. Here, we provide a straightforward protocol for efficiently isolating prokaryotic microorganisms from different extreme habitats (thermal, xeric, saline, alkaline, acidic, and cryogenic environments), which was established through previous successful work and our long-term experience in extremophile resource mining. We propose common processes for extremophile isolation at first and then summarize multiple cultivation strategies for recovering prokaryotic microorganisms from extreme environments and meanwhile provide specific isolation tips that are always overlooked but important. Furthermore, we propose the use of multi-omics-guided microbial cultivation approaches for culturing these as-yet-uncultivated microorganisms and two examples are provided to introduce how these approaches work. In summary, the protocol allows researchers to significantly improve the isolation efficiency of pure cultures and novel taxa, which therefore paves the way for the protection and utilization of microbial resources from extreme environments.

Integration of multi-omics data to elucidate keystone unknown taxa within microbialite-forming ecosystems

Microbes continually shape Earth's biochemical and physical landscapes by inhabiting diverse metabolic niches. Despite the important role microbes play in ecosystem functioning, most microbial species remain unknown highlighting a gap in our understanding of structured complex ecosystems. To elucidate the relevance of these unknown taxa, often referred to as "microbial dark matter," the integration of multiple high throughput sequencing technologies was used to evaluate the co-occurrence and connectivity of all microbes within the community. Since there are no standard methodologies for multi-omics integration of microbiome data, we evaluated the abundance of "microbial dark matter" in microbialite-forming communities using different types meta-omic datasets: amplicon, metagenomic, and metatranscriptomic sequencing previously generated for this ecosystem. Our goal was to compare the community structure and abundances of unknown taxa within the different data types rather than to perform a functional characterization of the data. Metagenomic and metatranscriptomic data were input into SortMeRNA to extract 16S rRNA gene reads. The output, as well as amplicon sequences, were processed through QIIME2 for taxonomy analysis. The R package mdmnets was utilized to build co-occurrence networks. Most hubs presented unknown classifications, even at the phyla level. Comparisons of the highest scoring hubs of each data type using sequence similarity networks allowed the identification of the most relevant hubs within the microbialite-forming communities. This work highlights the importance of unknown taxa in community structure and proposes that ecosystem network construction can be used on several types of data to identify keystone taxa and their potential function within microbial ecosystems.

Comparison of the Strengths and Weaknesses of Machine Learning Algorithms and Feature Selection on KEGG Database Microbial Gene Pathway Annotation and Its Effects on Reconstructed Network Topology

The development of tools for the annotation of genes from newly sequenced species has not evolved much from homologous alignment to prior annotated species. While the quality of gene annotations continues to decline as we sequence and assemble more evolutionary distant gut microbiome species, machine learning presents a high quality alternative to traditional techniques. In this study, we investigate the relative performance of common classical and nonclassical machine learning algorithms in the problem of gene annotation using human microbiome-associated species genes from the KEGG database. The majority of the ensemble, clustering, and deep learning algorithms that we investigated showed higher prediction accuracy than CD-Hit in predicting partial KEGG function. Motif-based, machine-learning methods of annotation in new species were faster and had higher precision-recall than methods of homologous alignment or orthologous gene clustering. Gradient boosted ensemble methods and neural networks also predicted higher connectivity in reconstructed KEGG pathways, finding twice as many new pathway interactions than blast alignment. The use of motif-based, machine-learning algorithms in annotation software will allow researchers to develop powerful tools to interact with bacterial microbiomes in ways previously unachievable through homologous sequence alignment alone.

Shedding light on the composition of extreme microbial dark matter: alternative approaches for culturing extremophiles

More than 20,000 species of prokaryotes (less than 1% of the estimated number of Earth's microbial species) have been described thus far. However, the vast majority of microbes that inhabit extreme environments remain uncultured and this group is termed "microbial dark matter." Little is known regarding the ecological functions and biotechnological potential of these underexplored extremophiles, thus representing a vast untapped and uncharacterized biological resource. Advances in microbial cultivation approaches are key for a detailed and comprehensive characterization of the roles of these microbes in shaping the environment and, ultimately, for their biotechnological exploitation, such as for extremophile-derived bioproducts (extremozymes, secondary metabolites, CRISPR Cas systems, and pigments, among others), astrobiology, and space exploration. Additional efforts to enhance culturable diversity are required due to the challenges imposed by extreme culturing and plating conditions. In this review, we summarize methods and technologies used to recover the microbial diversity of extreme environments, while discussing the advantages and disadvantages associated with each of these approaches. Additionally, this review describes alternative culturing strategies to retrieve novel taxa with their unknown genes, metabolisms, and ecological roles, with the ultimate goal of increasing the yields of more efficient bio-based products. This review thus summarizes the strategies used to unveil the hidden diversity of the microbiome of extreme environments and discusses the directions for future studies of microbial dark matter and its potential applications in biotechnology and astrobiology.

Latent Dirichlet Allocation modeling of environmental microbiomes

Interactions between stressed organisms and their microbiome environments may provide new routes for understanding and controlling biological systems. However, microbiomes are a form of high-dimensional data, with thousands of taxa present in any given sample, which makes untangling the interaction between an organism and its microbial environment a challenge. Here we apply Latent Dirichlet Allocation (LDA), a technique for language modeling, which decomposes the microbial communities into a set of topics (non-mutually-exclusive sub-communities) that compactly represent the distribution of full communities. LDA provides a lens into the microbiome at broad and fine-grained taxonomic levels, which we show on two datasets. In the first dataset, from the literature, we show how LDA topics succinctly recapitulate many results from a previous study on diseased coral species. We then apply LDA to a new dataset of maize soil microbiomes under drought, and find a large number of significant associations between the microbiome topics and plant traits as well as associations between the microbiome and the experimental factors, e.g. watering level. This yields new information on the plant-microbial interactions in maize and shows that LDA technique is useful for studying the coupling between microbiomes and stressed organisms.

The microbial dark matter and "wanted list" in worldwide wastewater treatment plants

BACKGROUND

Wastewater treatment plants (WWTPs) are one of the largest biotechnology applications in the world and are of critical importance to modern urban societies. An accurate evaluation of the microbial dark matter (MDM, microorganisms whose genomes remain uncharacterized) proportions in WWTPs is of great value, while there is no such research yet. This study conducted a global meta-analysis of MDM in WWTPs with 317,542 prokaryotic genomes from the Genome Taxonomy Database and proposed a "wanted list" for priority targets in further investigations of activated sludge.

RESULTS

Compared with the Earth Microbiome Project data, WWTPs had relatively lower genome-sequenced proportions of prokaryotes than other ecosystems, such as the animal related environments. Analysis showed that the median proportions of the genome-sequenced cells and taxa (100% identity and 100% coverage in 16S rRNA gene region) in WWTPs reached 56.3% and 34.5% for activated sludge, 48.6% and 28.5% for aerobic biofilm, and 48.3% and 28.5% for anaerobic digestion sludge, respectively. This result meant MDM had high proportions in WWTPs. Besides, all of the samples were occupied by a few predominant taxa, and the majority of the sequenced genomes were from pure cultures. The global-scale "wanted list" for activated sludge contained four phyla that have few representatives and 71 operational taxonomic units with the majority of them having no genome or isolate yet. Finally, several genome mining methods were verified to successfully recover genomes from activated sludge such as hybrid assembly of the second- and third-generation sequencing.

CONCLUSIONS

This work elucidated the proportion of MDM in WWTPs, defined the "wanted list" of activated sludge for future investigations, and certified potential genome recovery methods. The proposed methodology of this study can be applied to other ecosystems and improve understanding of ecosystem structure across diverse habitats. Video Abstract.

Convergent evolution and horizontal gene transfer in Arctic Ocean microalgae

Microbial communities in the world ocean are affected strongly by oceanic circulation, creating characteristic marine biomes. The high connectivity of most of the ocean makes it difficult to disentangle selective retention of colonizing genotypes (with traits suited to biome specific conditions) from evolutionary selection, which would act on founder genotypes over time. The Arctic Ocean is exceptional with limited exchange with other oceans and ice covered since the last ice age. To test whether Arctic microalgal lineages evolved apart from algae in the global ocean, we sequenced four lineages of microalgae isolated from Arctic waters and sea ice. Here we show convergent evolution and highlight geographically limited HGT as an ecological adaptive force in the form of PFAM complements and horizontal acquisition of key adaptive genes. Notably, ice-binding proteins were acquired and horizontally transferred among Arctic strains. A comparison with Tara Oceans metagenomes and metatranscriptomes confirmed mostly Arctic distributions of these IBPs. The phylogeny of Arctic-specific genes indicated that these events were independent of bacterial-sourced HGTs in Antarctic Southern Ocean microalgae.

Beyond the limits of the unassigned protist microbiome: inferring large-scale spatio-temporal patterns of Syndiniales marine parasites

Marine protists are major components of the oceanic microbiome that remain largely unrepresented in culture collections and genomic reference databases. The exploration of this uncharted protist diversity in oceanic communities relies essentially on studying genetic markers from the environment as taxonomic barcodes. Here we report that across 6 large scale spatio-temporal planktonic surveys, half of the genetic barcodes remain taxonomically unassigned at the genus level, preventing a fine ecological understanding for numerous protist lineages. Among them, parasitic Syndiniales (Dinoflagellata) appear as the least described protist group. We have developed a computational workflow, integrating diverse 18S rDNA gene metabarcoding datasets, in order to infer large-scale ecological patterns at 100% similarity of the genetic marker, overcoming the limitation of taxonomic assignment. From a spatial perspective, we identified 2171 unassigned clusters, i.e., Syndiniales sequences with 100% similarity, exclusively shared between the Tropical/Subtropical Ocean and the Mediterranean Sea among all Syndiniales orders and 25 ubiquitous clusters shared within all the studied marine regions. From a temporal perspective, over 3 time-series, we highlighted 39 unassigned clusters that follow rhythmic patterns of recurrence and are the best indicators of parasite community's variation. These clusters withhold potential as ecosystem change indicators, mirroring their associated host community responses. Our results underline the importance of Syndiniales in structuring planktonic communities through space and time, raising questions regarding host-parasite association specificity and the trophic mode of persistent Syndiniales, while providing an innovative framework for prioritizing unassigned protist taxa for further description.

Dark microbiome and extremely low organics in Atacama fossil delta unveil Mars life detection limits

Identifying unequivocal signs of life on Mars is one of the most important objectives for sending missions to the red planet. Here we report Red Stone, a 163-100 My alluvial fan-fan delta that formed under arid conditions in the Atacama Desert, rich in hematite and mudstones containing clays such as vermiculite and smectites, and therefore geologically analogous to Mars. We show that Red Stone samples display an important number of microorganisms with an unusual high rate of phylogenetic indeterminacy, what we refer to as "dark microbiome", and a mix of biosignatures from extant and ancient microorganisms that can be barely detected with state-of-the-art laboratory equipment. Our analyses by testbed instruments that are on or will be sent to Mars unveil that although the mineralogy of Red Stone matches that detected by ground-based instruments on the red planet, similarly low levels of organics will be hard, if not impossible to detect in Martian rocks depending on the instrument and technique used. Our results stress the importance in returning samples to Earth for conclusively addressing whether life ever existed on Mars.

Unravelling microalgal-bacterial interactions in aquatic ecosystems through 16S rRNA gene-based co-occurrence networks

Interactions between microalgae and bacteria can directly influence the global biogeochemical cycles but the majority of such interactions remain unknown. 16S rRNA gene-based co-occurrence networks have potential to help identify microalgal-bacterial interactions. Here, we used data from 10 Earth microbiome projects to identify potential microalgal-bacterial associations in aquatic ecosystems. A high degree of clustering was observed in microalgal-bacterial modules, indicating densely connected neighbourhoods. Proteobacteria and Bacteroidetes predominantly co-occurred with microalgae and represented hubs of most modules. Our results also indicated that species-specificity may be a global characteristic of microalgal associated microbiomes. Several previously known associations were recovered from our network modules, validating that biologically meaningful results can be inferred using this approach. A range of previously unknown associations were recognised such as co-occurrences of Bacillariophyta with uncultured Planctomycetes OM190 and Deltaproteobacteria order NB1-j. Planctomycetes and Verrucomicrobia were identified as key associates of microalgae due to their frequent co-occurrences with several microalgal taxa. Despite no clear taxonomic pattern, bacterial associates appeared functionally similar across different environments. To summarise, we demonstrated the potential of 16S rRNA gene-based co-occurrence networks as a hypothesis-generating framework to guide more focused research on microalgal-bacterial associations.

Elucidation of microbial interactions, dynamics, and keystone microbes in high pressure anaerobic digestion

High-pressure anaerobic digestion (HPAD) is a promising technology for producing biogas enriched with high methane content in a single-step process. To enhance HPAD performance, a comprehensive understanding of microbial community dynamics and their interactions is essential. For this, mesophilic batch high-pressurized anaerobic reactors were operated under 3 bars (H3) and 6 bars (H6). The experimental results showed that the effect of high-pressure (up to 6 bar) on acidification was negligible while methanogenesis was significantly delayed. Microbial analysis showed the predominance of Defluviitoga affiliated with the phylum Thermotogae and the reduction of Thiopseudomonas under high-pressure conditions. In addition, the microbial cluster pattern in H3 and H6 was significantly different compared to the CR, indicating a clear shift in microbial community structure. Moreover, Methanobacterium, Methanomicrobiaceae, Alkaliphilus, and Petrimonas were strongly correlated in network analysis, and they could be identified as keystone microbes in the HPAD reactor.

Novel insights in seasonal dynamics and co-existence patterns of phytoplankton and micro-eukaryotes in drinking water reservoir, Northwest China: DNA data and ecological model

Although associations between phytoplankton and micro-eukaryotes have been studied in aquatic ecosystems, there are still knowledge gaps in comprehending their dynamics and interactions in drinking water reservoirs. Here, the seasonal dynamics of phytoplankton and micro-eukaryotic diversities and their co-existence patterns were studied in a drinking water reservoir, Northwest China. The highest phytoplankton diversity was observed in summer, and Chlorella sp. that belongs to Chlorophyta was the most abundant genus. The highest eukaryotic diversity was also detected in summer, and Rimostrombidium sp. that belongs to Ciliophora was the most dominant genus. Mantel test showed that the phytoplankton diversity was significantly correlated with ammonia nitrogen (r = 0.561, p = 0.001) and dissolved organic carbon (r = 0.267, p = 0.017), while the eukaryotic diversity was significantly associated with ammonia nitrogen (r = 0.265, p = 0.034) and temperature (r = 0.208, p = 0.046). PLS-PM (Partial Least Squares Path Modeling) further revealed that nutrients (P < 0.01) significantly affected the phytoplankton diversity, while nutrients (P < 0.01) and temperature (P < 0.01) significantly influenced the eukaryotic diversity. Co-occurrence network displayed the primarily positive interactions (77.66% positive and 22.34% negative) between phytoplankton and micro-eukaryotes. These findings could deepen our understanding of interactions between phytoplankton and micro-eukaryotes and their driving factors under changing aquatic environments of drinking water reservoirs.

How nutrient loads influence microbial-derived carbon accumulation in wetlands: A new insight from microbial metabolic investment strategies

Excessive anthropogenic nutrient inputs often lead to the degradation of wetland ecosystems and a decrease in carbon sink capacity. Microbial-derived carbon is increasingly recognized as an important precursor for organic carbon formation, which is controlled by the balance between microbial anabolic and catabolic processes. Shifts in microbial metabolic investment under nutrient load disturbance are key, but understudied, components of microbial-derived carbon turnover. Here, the roles of the distinct life-history traits and cooperation degree of key microbial assemblies in regulating microbial-derived carbon accumulation in a wetland receiving treated wastewater were firstly assessed by combining microbial biomarkers and genomic approaches. It was found that microbial-derived carbon was an important source of organic carbon in wetlands, and strongly associated with several microbial assemblies with specific trait strategies. Further analysis demonstrated that high growth yield strategists were mainly associated with microbial necromass accrual, while microbial biomass was more dominated by resource acquisition strategies in nutrient-imbalanced wetlands. A significant positive relationship between positive cohesion and microbial-derived carbon indicated that cooperative behavior among taxa promoted the production and accumulation of microbial-derived carbon. Moreover, resource stoichiometric balance, including C:N and C:P, was identified as an important driver of shifts in microbial metabolic investment strategies. The decreased C:N ratio led to a shift from resource acquisition strategies to high growth yield strategies for the microbial community, which facilitated microbial necromass accrual along the N-limited wetland, while the increased C:P ratio caused by excessive P deposition in sediments limits microbial cooperative growth to some extent. This study highlighted the importance of stoichiometric balance in mediating microbial growth metabolism and, in turn, enhancing the carbon sink capacity of wetlands.

Dark Matter Enhances Interactions within Both Microbes and Dissolved Organic Matter under Global Change

There are vast but uncharacterized microbial taxa and chemical metabolites (that is, dark matter) across the Earth's ecosystems. A lack of knowledge about dark matter hinders a complete understanding of microbial ecology and biogeochemical cycles. Here, we examine sediment bacteria and dissolved organic matter (DOM) in 300 microcosms along experimental global change gradients in subtropical and subarctic climate zones of China and Norway, respectively. We develop an indicator to quantify the importance of dark matter by comparing co-occurrence network patterns with and without dark matter in bacterial or DOM assemblages. In both climate zones, dark matter constitutes approximately 30-56% of bacterial taxa and DOM metabolites and changes connectivity within bacterial and DOM assemblages by between -15.5 and +61.8%. Dark matter is generally more important for changing network connectivity within DOM assemblages than those of microbes, especially in the subtropical zone. However, the importance of dark matter along global change gradients is strongly correlated between bacteria and DOM and consistently increased toward higher primary productivity because of increasing temperatures and nutrient enrichment. Our findings highlight the importance of microbial and chemical dark matter for changing biogeochemical interactions under global change.

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

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

Unveiling Chemical Interactions Between Plants and Fungi Using Metabolomics Approaches

Metabolomics has been extensively used in clinical studies in the search for new biomarkers of human diseases. However, this approach has also been highlighted in agriculture and biological sciences, once metabolomics studies have been assisting researchers to deduce new chemical mechanisms involved in biological interactions that occur between microorganisms and plants. In this sense, the knowledge of the biological role of each metabolite (virulence factors, signaling compounds, antimicrobial metabolites, among others) and the affected biochemical pathways during the interaction contribute to a better understand of different ecological relationships established in nature. The current chapter addresses five different applications of the metabolomics approach in fungal-plant interactions research: (1) Discovery of biomarkers in pathogen-host interactions, (2) plant diseases diagnosis, (3) chemotaxonomy, (4) plant defense, and (5) plant resistance; using mass spectrometry and/or nuclear magnetic resonance spectroscopy, which are the techniques most used in metabolomics.