The bright side of microbial dark matter: lessons learned from the uncultivated majority

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.

Novel insights on microbiome dynamics during a gill disease outbreak in farmed rainbow trout (Oncorhynchus mykiss)

The generic term "Gill disease" refers to a wide range of disorders that affect the gills and severely impact salmonid aquaculture systems worldwide. In rainbow trout freshwater aquaculture, various etiological agents causing gill diseases have been described, particularly Flavobacterium and Amoeba species, but research studies suggest a more complex and multifactorial aetiology. Here, a cohort of rainbow trout affected by gill disease is monitored both through standard laboratory techniques and 16S rRNA Next-Generation Sequencing (NGS) analysis during a natural disease outbreak and subsequent antibiotic treatment with Oxytetracycline. NGS results show a clear clustering of the samples between pre- and post-treatment based on the microbial community of the gills. Interestingly, the three main pathogenic bacteria species in rainbow trout (Yersinia ruckeri, Flavobacterium psychrophilum, and Flavobacterium branchiophilum) appear to be weak descriptors of the diversity between pre-treatment and post-treatment groups. In this study, the dynamics of the gill microbiome during the outbreak and subsequent treatment are far more complex than previously reported in the literature, and environmental factors seem of the utmost importance in determining gill disease. These findings present a potential novel perspective on the diagnosis and management of gill diseases, showing the limitations of conventional laboratory methodologies in elucidating the complexity of this disease in rainbow trout. To the authors' knowledge, this work is the first to describe the microbiome of rainbow trout gills during a natural outbreak and subsequent antibiotic treatment. The results of this study suggest that NGS can play a critical role in the analysis and comprehension of gill pathology. Using NGS in future research is highly recommended to gain deeper insights into such diseases correlating gill's microbiome with other possible cofactors and establish strong prevention guidelines.

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.

Selective Elucidation of Living Microbial Communities in Fermented Grains of Chinese Baijiu: Development of a Technique Integrating Propidium Monoazide Probe Pretreatment and Amplicon Sequencing

The fermentation process of Chinese Baijiu's fermented grains involves the intricate succession and metabolism of microbial communities, collectively shaping the Baijiu's quality. Understanding the composition and succession of these living microbial communities within fermented grains is crucial for comprehending fermentation and flavor formation mechanisms. However, conducting high-throughput analysis of living microbial communities within the complex microbial system of fermented grains poses significant challenges. Thus, this study addressed this challenge by devising a high-throughput analysis framework using light-flavor Baijiu as a model. This framework combined propidium monoazide (PMA) pretreatment technology with amplicon sequencing techniques. Optimal PMA treatment parameters, including a concentration of 50 μM and incubation in darkness for 5 min followed by an exposure incubation period of 5 min, were identified. Utilizing this protocol, viable microorganism biomass ranging from 8.71 × 106 to 1.47 × 108 copies/μL was successfully detected in fermented grain samples. Subsequent amplicon sequencing analysis revealed distinct microbial community structures between untreated and PMA-treated groups, with notable differences in relative abundance compositions, particularly in dominant species such as Lactobacillus, Bacillus, Pediococcus, Saccharomycopsis, Issatchenkia and Pichia, as identified by LEfSe analysis. The results of this study confirmed the efficacy of PMA-amplicon sequencing technology for analyzing living microbial communities in fermented grains and furnished a methodological framework for investigating living microbial communities in diverse traditional fermented foods. This technical framework holds considerable significance for advancing our understanding of the fermentation mechanisms intrinsic to traditional fermented foods.

Decoding the Arsenal: Protist Effectors and Their Impact on Photosynthetic Hosts

Interactions between various microbial pathogens including viruses, bacteria, fungi, oomycetes, and their plant hosts have traditionally been the focus of phytopathology. In recent years, a significant and growing interest in the study of eukaryotic microorganisms not classified among fungi or oomycetes has emerged. Many of these protists establish complex interactions with photosynthetic hosts, and understanding these interactions is crucial in understanding the dynamics of these parasites within traditional and emerging types of farming, including marine aquaculture. Many phytopathogenic protists are biotrophs with complex polyphasic life cycles, which makes them difficult or impossible to culture, a fact reflected in a wide gap in the availability of comprehensive genomic data when compared to fungal and oomycete plant pathogens. Furthermore, our ability to use available genomic resources for these protists is limited by the broad taxonomic distance that these organisms span, which makes comparisons with other genomic datasets difficult. The current rapid progress in genomics and computational tools for the prediction of protein functions and interactions is revolutionizing the landscape in plant pathology. This is also opening novel possibilities, specifically for a deeper understanding of protist effectors. Tools like AlphaFold2 enable structure-based function prediction of effector candidates with divergent protein sequences. In turn, this allows us to ask better biological questions and, coupled with innovative experimental strategies, will lead into a new era of effector research, especially for protists, to expand our knowledge on these elusive pathogens and their interactions with photosynthetic hosts. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Protist communities of microbial mats from the extreme environments of five saline Andean lagoons at high altitudes in the Atacama Desert

Introduction

Heterotrophic protists colonizing microbial mats have received little attention over the last few years, despite their importance in microbial food webs. A significant challenge originates from the fact that many protists remain uncultivable and their functions remain poorly understood.

Methods

Metabarcoding studies of protists in microbial mats across high-altitude lagoons of different salinities (4.3-34 practical salinity units) were carried out to provide insights into their vertical stratification at the millimeter scale. DNA and cDNA were analyzed for selected stations.

Results

Sequence variants classified as the amoeboid rhizarian Rhogostoma and the ciliate Euplotes were found to be common members of the heterotrophic protist communities. They were accompanied by diatoms and kinetoplastids. Correlation analyses point to the salinity of the water column as a main driver influencing the structure of the protist communities at the five studied microbial mats. The active part of the protist communities was detected to be higher at lower salinities (<20 practical salinity units).

Discussion

We found a restricted overlap of the protist community between the different microbial mats indicating the uniqueness of these different aquatic habitats. On the other hand, the dominating genotypes present in metabarcoding were similar and could be isolated and sequenced in comparative studies (Rhogostoma, Euplotes, Neobodo). Our results provide a snapshot of the unculturable protist diversity thriving the benthic zone of five athalossohaline lagoons across the Andean plateau.

Functional and evolutionary significance of unknown genes from uncultivated taxa

Many of the Earth's microbes remain uncultured and understudied, limiting our understanding of the functional and evolutionary aspects of their genetic material, which remain largely overlooked in most metagenomic studies1. Here we analysed 149,842 environmental genomes from multiple habitats2-6 and compiled a curated catalogue of 404,085 functionally and evolutionarily significant novel (FESNov) gene families exclusive to uncultivated prokaryotic taxa. All FESNov families span multiple species, exhibit strong signals of purifying selection and qualify as new orthologous groups, thus nearly tripling the number of bacterial and archaeal gene families described to date. The FESNov catalogue is enriched in clade-specific traits, including 1,034 novel families that can distinguish entire uncultivated phyla, classes and orders, probably representing synapomorphies that facilitated their evolutionary divergence. Using genomic context analysis and structural alignments we predicted functional associations for 32.4% of FESNov families, including 4,349 high-confidence associations with important biological processes. These predictions provide a valuable hypothesis-driven framework that we used for experimental validatation of a new gene family involved in cell motility and a novel set of antimicrobial peptides. We also demonstrate that the relative abundance profiles of novel families can discriminate between environments and clinical conditions, leading to the discovery of potentially new biomarkers associated with colorectal cancer. We expect this work to enhance future metagenomics studies and expand our knowledge of the genetic repertory of uncultivated organisms.

Mock community taxonomic classification performance of publicly available shotgun metagenomics pipelines

Shotgun metagenomic sequencing comprehensively samples the DNA of a microbial sample. Choosing the best bioinformatics processing package can be daunting due to the wide variety of tools available. Here, we assessed publicly available shotgun metagenomics processing packages/pipelines including bioBakery, Just a Microbiology System (JAMS), Whole metaGenome Sequence Assembly V2 (WGSA2), and Woltka using 19 publicly available mock community samples and a set of five constructed pathogenic gut microbiome samples. Also included is a workflow for labelling bacterial scientific names with NCBI taxonomy identifiers for better resolution in assessing results. The Aitchison distance, a sensitivity metric, and total False Positive Relative Abundance were used for accuracy assessments for all pipelines and mock samples. Overall, bioBakery4 performed the best with most of the accuracy metrics, while JAMS and WGSA2, had the highest sensitivities. Furthermore, bioBakery is commonly used and only requires a basic knowledge of command line usage. This work provides an unbiased assessment of shotgun metagenomics packages and presents results assessing the performance of the packages using mock community sequence data.

MiST 4.0: a new release of the microbial signal transduction database, now with a metagenomic component

Signal transduction systems in bacteria and archaea link environmental stimuli to specific adaptive cellular responses. They control gene expression, motility, biofilm formation, development and other processes that are vital to survival. The microbial signal transduction (MiST) database is an online resource that stores tens of thousands of genomes and allows users to explore their signal transduction profiles, analyze genomes in bulk using the database application programming interface (API) and make testable hypotheses about the functions of newly identified signaling systems. However, signal transduction in metagenomes remained completely unexplored. To lay the foundation for research in metagenomic signal transduction, we have prepared a new release of the MiST database, MiST 4.0, which features over 10 000 metagenome-assembled genomes (MAGs), a scaled representation of proteins and detailed BioSample information. In addition, several thousands of new genomes have been processed and stored in the database. A new interface has been developed that allows users to seamlessly switch between genomes and MAGs. MiST 4.0 is freely available at https://mistdb.com; metagenomes and MAGs can also be explored using the API available on the same page.

Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

Different microbial assemblage colonized on microplastics and clay particles in aerobic sludge treatment

In this study, a combination of property analysis and high-throughput sequencing was used to investigate the microbial colonization ability and their community structures and functions in polypropylene microplastics (PPMPs), polystyrene microplastics (PSMPs) and montmorillonite (MMT), respectively as the representatives of artificial and natural substrates in aerobic sludge treatment. After 45 d of incubation, the surface properties of substrates were altered with the increased oxygen functional groups and surface roughness, indicating microbial settlement. Moreover, MPs had different microbial structures from that of MMT, and PSMPs exhibited higher microbial diversity and abundance than PPMPs and MMT. Also, these substrates changed the inherent ecological niche in sludge. Especially, the abundance of some pathogens (e.g., Pseudomonas, Klebsiella and Flavobacterium) was increased in MPs, and the disease risk of Kyoto Encyclopedia of Genes and Genomes metabolic pathway (e.g., Infectious diseases: Bacterial, Infectious diseases: Parasitic and Immune diseases) was higher. Also, the presence of MPs inhibited the decomposition of organic matter including soluble chemical oxygen demand and protein compared to natural substrates. The findings revealed the crucial vector role of MPs for microbes and the effect on aerobic sludge treatment, highlighting the necessity of MP removal in sludge.

Taxonomic and environmental distribution of bacterial amino acid auxotrophies

Many microorganisms are auxotrophic-unable to synthesize the compounds they require for growth. With this work, we quantify the prevalence of amino acid auxotrophies across a broad diversity of bacteria and habitats. We predicted the amino acid biosynthetic capabilities of 26,277 unique bacterial genomes spanning 12 phyla using a metabolic pathway model validated with empirical data. Amino acid auxotrophy is widespread across bacterial phyla, but we conservatively estimate that the majority of taxa (78.4%) are able to synthesize all amino acids. Our estimates indicate that amino acid auxotrophies are more prevalent among obligate intracellular parasites and in free-living taxa with genomic attributes characteristic of 'streamlined' life history strategies. We predicted the amino acid biosynthetic capabilities of bacterial communities found in 12 unique habitats to investigate environmental associations with auxotrophy, using data compiled from 3813 samples spanning major aquatic, terrestrial, and engineered environments. Auxotrophic taxa were more abundant in host-associated environments (including the human oral cavity and gut) and in fermented food products, with auxotrophic taxa being relatively rare in soil and aquatic systems. Overall, this work contributes to a more complete understanding of amino acid auxotrophy across the bacterial tree of life and the ecological contexts in which auxotrophy can be a successful strategy.

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.

Bioinformatic approaches for studying the microbiome of fermented food

High-throughput DNA sequencing-based approaches continue to revolutionise our understanding of microbial ecosystems, including those associated with fermented foods. Metagenomic and metatranscriptomic approaches are state-of-the-art biological profiling methods and are employed to investigate a wide variety of characteristics of microbial communities, such as taxonomic membership, gene content and the range and level at which these genes are expressed. Individual groups and consortia of researchers are utilising these approaches to produce increasingly large and complex datasets, representing vast populations of microorganisms. There is a corresponding requirement for the development and application of appropriate bioinformatic tools and pipelines to interpret this data. This review critically analyses the tools and pipelines that have been used or that could be applied to the analysis of metagenomic and metatranscriptomic data from fermented foods. In addition, we critically analyse a number of studies of fermented foods in which these tools have previously been applied, to highlight the insights that these approaches can provide.

Capturing the microbial dark matter in desert soils using culturomics-based metagenomics and high-resolution analysis

Deserts occupy one-third of the Earth's terrestrial surface and represent a potentially significant reservoir of microbial biodiversity, yet the majority of desert microorganisms remain uncharacterized and are seen as "microbial dark matter". Here, we introduce a multi-omics strategy, culturomics-based metagenomics (CBM) that integrates large-scale cultivation, full-length 16S rRNA gene amplicon, and shotgun metagenomic sequencing. The results showed that CBM captured a significant amount of taxonomic and functional diversity missed in direct sequencing by increasing the recovery of amplicon sequence variants (ASVs) and high/medium-quality metagenome-assembled genomes (MAGs). Importantly, CBM allowed the post hoc recovery of microbes of interest (e.g., novel or specific taxa), even those with extremely low abundance in the culture. Furthermore, strain-level analyses based on CBM and direct sequencing revealed that the desert soils harbored a considerable number of novel bacterial candidates (1941, 51.4%), of which 1095 (from CBM) were culturable. However, CBM would not exactly reflect the relative abundance of true microbial composition and functional pathways in the in situ environment, and its use coupled with direct metagenomic sequencing could provide greater insight into desert microbiomes. Overall, this study exemplifies the CBM strategy with high-resolution is an ideal way to deeply explore the untapped novel bacterial resources in desert soils, and substantially expands our knowledge on the microbial dark matter hidden in the vast expanse of deserts.

Phyto-microbiome to mitigate abiotic stress in crop plants

Plant-associated microbes include taxonomically diverse communities of bacteria, archaebacteria, fungi, and viruses, which establish integral ecological relationships with the host plant and constitute the phyto-microbiome. The phyto-microbiome not only contributes in normal growth and development of plants but also plays a vital role in the maintenance of plant homeostasis during abiotic stress conditions. Owing to its immense metabolic potential, the phyto-microbiome provides the host plant with the capability to mitigate the abiotic stress through various mechanisms like production of antioxidants, plant growth hormones, bioactive compounds, detoxification of harmful chemicals and toxins, sequestration of reactive oxygen species and other free radicals. A deeper understanding of the structure and functions of the phyto-microbiome and the complex mechanisms of phyto-microbiome mediated abiotic stress mitigation would enable its utilization for abiotic stress alleviation of crop plants and development of stress-resistant crops. This review aims at exploring the potential of phyto-microbiome to alleviate drought, heat, salinity and heavy metal stress in crop plants and finding sustainable solutions to enhance the agricultural productivity. The mechanistic insights into the role of phytomicrobiome in imparting abiotic stress tolerance to plants have been summarized, that would be helpful in the development of novel bioinoculants. The high-throughput modern approaches involving candidate gene identification and target gene modification such as genomics, metagenomics, transcriptomics, metabolomics, and phyto-microbiome based genetic engineering have been discussed in wake of the ever-increasing demand of climate resilient crop plants.

Uncultured Microorganisms and Their Functions in the Fermentation Systems of Traditional Chinese Fermented Foods

Traditional Chinese fermented foods are diverse and loved by people for their rich nutrition and unique flavors. In the fermentation processes of these foods, the microorganisms in the fermentation systems play a crucial role in determining the flavor and quality. Currently, some microorganisms in the fermentation systems of traditional Chinese fermented foods are in a state of being unculturable or difficult to culture, which hinders the comprehensive analysis and resource development of the microbial communities in the fermentation systems. This article provides an overview of the uncultured microorganisms in the natural environment, in the fermentation systems of traditional Chinese fermented foods, and the research methods for studying such microorganisms. It also discusses the prospects of utilizing the uncultured microorganisms in the fermentation systems of traditional Chinese fermented foods. The aim is to gain a comprehensive understanding of the microbial diversity and uncultured microorganisms in the fermentation systems of traditional Chinese fermented foods in order to better exploit and utilize these microorganisms and promote the development of traditional Chinese fermented foods.

Inter-kingdom interactions and stability of methanogens revealed by machine-learning guided multi-omics analysis of industrial-scale biogas plants

Multi-omics analysis is a powerful tool for the detection and study of inter-kingdom interactions, such as those between bacterial and archaeal members of complex biogas-producing microbial communities. In the present study, the microbiomes of three industrial-scale biogas digesters, each fed with different substrates, were analysed using a machine-learning guided genome-centric metagenomics framework complemented with metatranscriptome data. This data permitted us to elucidate the relationship between abundant core methanogenic communities and their syntrophic bacterial partners. In total, we detected 297 high-quality, non-redundant metagenome-assembled genomes (nrMAGs). Moreover, the assembled 16 S rRNA gene profiles of these nrMAGs showed that the phylum Firmicutes possessed the highest copy number, while the representatives of the archaeal domain had the lowest. Further investigation of the three anaerobic microbial communities showed characteristic alterations over time but remained specific to each industrial-scale biogas plant. The relative abundance of various microorganisms as revealed by metagenome data was independent from corresponding metatranscriptome activity data. Archaea showed considerably higher activity than was expected from their abundance. We detected 51 nrMAGs that were present in all three biogas plant microbiomes with different abundances. The core microbiome correlated with the main chemical fermentation parameters, and no individual parameter emerged as a predominant shaper of community composition. Various interspecies H₂/electron transfer mechanisms were assigned to hydrogenotrophic methanogens in the biogas plants that ran on agricultural biomass and wastewater. Analysis of metatranscriptome data revealed that methanogenesis pathways were the most active of all main metabolic pathways.

Metavirome Profiling and Dynamics of the DNA Viral Community in Seawater in Chuuk State, Federated States of Micronesia

Despite their abundance and ecological importance, little is known about the diversity of marine viruses, in part because most cannot be cultured in the laboratory. Here, we used high-throughput viral metagenomics of uncultivated viruses to investigate the dynamics of DNA viruses in tropical seawater sampled from Chuuk State, Federated States of Micronesia, in March, June, and December 2014. Among the identified viruses, 71-79% were bacteriophages belonging to the families Myoviridae, Siphoviridae, and Podoviridae (Caudoviriales), listed in order of abundance at all sampling times. Although the measured environmental factors (temperature, salinity, and pH) remained unchanged in the seawater over time, viral dynamics changed. The proportion of cyanophages (34.7%) was highest in June, whereas the proportion of mimiviruses, phycodnaviruses, and other nucleo-cytoplasmic large DNA viruses (NCLDVs) was higher in March and December. Although host species were not analysed, the dramatic viral community change observed in June was likely due to changes in the abundance of cyanophage-infected cyanobacteria, whereas that in NCLDVs was likely due to the abundance of potential eukaryote-infected hosts. These results serve as a basis for comparative analyses of other marine viral communities, and guide policy-making when considering marine life care in Chuuk State.

Single-cell transcriptomics and data analyses for prokaryotes-Past, present and future concepts

Transcriptomics, or more specifically mRNA sequencing, is a powerful tool to study gene expression at the single-cell level (scRNA-seq) which enables new insights into a plethora of biological processes. While methods for single-cell RNA-seq in eukaryotes are well established, application to prokaryotes is still challenging. Reasons for that are rigid and diverse cell wall structures hampering lysis, the lack of polyadenylated transcripts impeding mRNA enrichment, and minute amounts of RNA requiring amplification steps before sequencing. Despite those obstacles, several promising scRNA-seq approaches for bacteria have been published recently, albeit difficulties in the experimental workflow and data processing and analysis remain. In particular, bias is often introduced by amplification which makes it difficult to distinguish between technical noise and biological variation. Future optimization of experimental procedures and data analysis algorithms are needed for the improvement of scRNA-seq but also to aid in the emergence of prokaryotic single-cell multi-omics. to help address 21st century challenges in the biotechnology and health sector.

Here, there and everywhere: Ecology and biology of the Dependentiae phylum

Our view of bacterial diversity has been dramatically impacted by cultivation-independent approaches such as metagenomics and 16S rRNA gene sequencing. Consequently, most bacterial phyla known to date are only documented by the presence of DNA sequences in databases and lack cultivated representatives. This bacterial majority that is yet-to-be cultivated, is forming the 'Microbial Dark Matter', (MDM) a consortium, whose ecology and biology remain largely unexplored. The Candidatus Dependentiae stands as one of many phyla within this MDM, found worldwide in various environments. Genomic evidence suggests ancestral, unusual adaptations of all Ca. Dependentiae to a host dependent lifestyle. In line with this, protists appear to be important for Ca. Dependentiae biology, as revealed by few recent studies, which enabled their growth in laboratory through host cultivation. However, the Ca. Dependentiae still remain to this day a poorly documented phylum. The present review aims to summarize the current knowledge accumulated on this often found, but rarely highlighted, bacterial phylum.

Back to Basics: A Simplified Improvement to Multiple Displacement Amplification for Microbial Single-Cell Genomics

Microbial single-cell genomics (SCG) provides access to the genomes of rare and uncultured microorganisms and is a complementary method to metagenomics. Due to the femtogram-levels of DNA in a single microbial cell, sequencing the genome requires whole genome amplification (WGA) as a preliminary step. However, the most common WGA method, multiple displacement amplification (MDA), is known to be costly and biased against specific genomic regions, preventing high-throughput applications and resulting in uneven genome coverage. Thus, obtaining high-quality genomes from many taxa, especially minority members of microbial communities, becomes difficult. Here, we present a volume reduction approach that significantly reduces costs while improving genome coverage and uniformity of DNA amplification products in standard 384-well plates. Our results demonstrate that further volume reduction in specialized and complex setups (e.g., microfluidic chips) is likely unnecessary to obtain higher-quality microbial genomes. This volume reduction method makes SCG more feasible for future studies, thus helping to broaden our knowledge on the diversity and function of understudied and uncharacterized microorganisms in the environment.

Altered microbial P cycling genes drive P availability in soil after afforestation

Soil Phosphorous (P) availability is a limiting factor for plant growth and regulates biological metabolism in plantation ecosystems. The effect of variations in soil microbial P cycling potential on the availability of soil P during succession in plantation ecosystems is unclear. In this study, a metagenomics approach was used to explore variations in the composition and diversity of microbial P genes along a 45-year recovery sequence of Robinia pseudoacacia on the Loess Plateau, as well soil properties were measured. Our results showed that the diversity of P cycling genes (inorganic P solubilization and organic P mineralization genes) increased significantly after afforestation, and the community composition showed clear differences. The gcd and ppx genes were dominant in inorganic P transformation, whereas phnM gene dominated the transformation of organic P. The abundance of genes involved in inorganic P solubilization and organic P mineralization was significantly positively correlated with P availability, particularly for phnM, gcd, ppx, and phnI genes, corresponding to the phyla Gemmatimonadetes, Acidobacteria, Bacteroidetes, and Planctomycetes. The critical drivers of the microbial main genes of soil P cycling were available P (AP) and total N (TN) in soil. Overall, these findings highlight afforestation-induced increases in microbial P cycling genes enhanced soil P availability. and help to better understand how microbial growth metabolism caused by vegetation restoration in ecologically fragile areas affects the soil P cycling.

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.

The identification of the new species Nitratireductor thuwali sp. nov. reveals the untapped diversity of hydrocarbon-degrading culturable bacteria from the arid mangrove sediments of the Red Sea

Introduction

The geological isolation, lack of freshwater inputs and specific internal water circulations make the Red Sea one of the most extreme-and unique-oceans on the planet. Its high temperature, salinity and oligotrophy, along with the consistent input of hydrocarbons due to its geology (e.g., deep-sea vents) and high oil tankers traffic, create the conditions that can drive and influence the assembly of unique marine (micro)biomes that evolved to cope with these multiple stressors. We hypothesize that mangrove sediments, as a model-specific marine environment of the Red Sea, act as microbial hotspots/reservoirs of such diversity not yet explored and described.

Methods

To test our hypothesis, we combined oligotrophic media to mimic the Red Sea conditions and hydrocarbons as C-source (i.e., crude oil) with long incubation time to allow the cultivation of slow-growing environmentally (rare or uncommon) relevant bacteria.

Results and discussion

This approach reveals the vast diversity of taxonomically novel microbial hydrocarbon degraders within a collection of a few hundred isolates. Among these isolates, we characterized a novel species, Nitratireductor thuwali sp. nov., namely, Nit1536^T. It is an aerobic, heterotrophic, Gram-stain-negative bacterium with optimum growth at 37°C, 8 pH and 4% NaCl, whose genome and physiological analysis confirmed the adaptation to extreme and oligotrophic conditions of the Red Sea mangrove sediments. For instance, Nit1536^T metabolizes different carbon substrates, including straight-chain alkanes and organic acids, and synthesizes compatible solutes to survive in salty mangrove sediments. Our results showed that the Red Sea represent a source of yet unknown novel hydrocarbon degraders adapted to extreme marine conditions, and their discovery and characterization deserve further effort to unlock their biotechnological potential.

Cross Cultivation on Homologous/Heterologous Plant-Based Culture Media Empowers Host-Specific and Real Time In Vitro Signature of Plant Microbiota

Alliances of microbiota with plants are masked by the inability of in vitro cultivation of their bulk. Pure cultures piled in international centers originated from dissimilar environments/hosts. Reporting that plant root/leaf-based culture media support the organ-specific growth of microbiota, it was of interest to further investigate if a plant-based medium prepared from homologous (maize) supports specific/adapted microbiota compared to another prepared from heterologous plants (sunflower). The culture-independent community of maize phyllosphere was compared to communities cross-cultivated on plant broth-based media: CFU counts and taxa prevalence (PCR-DGGE; Illumina MiSeq amplicon sequencing). Similar to total maize phyllospheric microbiota, culture-dependent communities were overwhelmed by Proteobacteria (>94.3–98.3%); followed by Firmicutes (>1.3–3.7%), Bacteroidetes (>0.01–1.58%) and Actinobacteria (>0.06–0.34%). Differential in vitro growth on homologous versus heterologous plant-media enriched/restricted various taxa. In contrast, homologous cultivation over represented members of Proteobacteria (ca. > 98.0%), mainly Pseudomonadaceae and Moraxellaceae; heterologous cultivation and R2A enriched Firmicutes (ca. > 3.0%). The present strategy simulates/fingerprints the chemical composition of host plants to expand the culturomics of plant microbiota, advance real-time in vitro cultivation and lab-keeping of compatible plant microbiota, and identify preferential pairing of plant-microbe partners toward future synthetic community (SynComs) research and use in agriculture.

Occurrence, Diversity, and Genomes of "Candidatus Patescibacteria" along the Early Diagenesis of Marine Sediments

The phylum "Candidatus Patescibacteria" (or Candidate Phyla Radiation [CPR]) accounts for roughly one-quarter of microbial diversity on Earth, but the presence and diversity of these bacteria in marine sediments have been rarely charted. Here, we investigate the abundance, diversity, and metabolic capacities of CPR bacteria in three sediment sites (Mohns Ridge, North Pond, and Costa Rica Margin) with samples covering a wide range of redox zones formed during the early diagenesis of organic matter. Through metagenome sequencing, we found that all investigated sediment horizons contain "Ca. Patescibacteria" (0.4 to 28% of the total communities), which are affiliated with the classes "Ca. Paceibacteria," "Ca. Gracilibacteria," "Ca. Microgenomatia," "Ca. Saccharimonadia," "Ca. ABY1," and "Ca. WWE3." However, only a subset of the diversity of marine sediment "Ca. Patescibacteria," especially the classes "Ca. Paceibacteria" and "Ca. Gracilibacteria," can be captured by 16S rRNA gene amplicon sequencing with commonly used universal primers. We recovered 11 metagenome-assembled genomes (MAGs) of CPR from these sediments, most of which are novel at the family or genus level in the "Ca. Paceibacteria" class and are missed by the amplicon sequencing. While individual MAGs are confined to specific anoxic niches, the lack of capacities to utilize the prevailing terminal electron acceptors indicates that they may not be directly selected by the local redox conditions. These CPR bacteria lack essential biosynthesis pathways and may use a truncated glycolysis pathway to conserve energy as fermentative organotrophs. Our findings suggest that marine sediments harbor some novel yet widespread CPR bacteria during the early diagenesis of organic matter, which needs to be considered in population dynamics assessments in this vast environment. IMPORTANCE Ultrasmall-celled "Ca. Patescibacteria" have been estimated to account for one-quarter of the total microbial diversity on Earth, the parasitic lifestyle of which may exert a profound control on the overall microbial population size of the local ecosystems. However, their diversity and metabolic functions in marine sediments, one of the largest yet understudied ecosystems on Earth, remain virtually uncharacterized. By applying cultivation-independent approaches to a range of sediment redox zones, we reveal that "Ca. Patescibacteria" members are rare but widespread regardless of the prevailing geochemical conditions. These bacteria are affiliated with novel branches of "Ca. Patescibacteria" and have been largely missed in marker gene-based surveys. They do not have respiration capacity but may conserve energy by fermenting organic compounds from their episymbiotic hosts. Our findings suggest that these novel "Ca. Patescibacteria" are among the previously overlooked microbes in diverse marine sediments.

Direct Detection of Antibacterial-Producing Soil Isolates Utilizing a Novel High-Throughput Screening Assay

The ever-increasing global threat of common infections developing resistance to current therapeutics is rapidly accelerating the onset of a primitive post-antibiotic era in medicine. The prevention of further antimicrobial resistance development is unlikely due to the continued misuse of antibiotics, augmented by the lack of discovery of novel antibiotics. Screening large libraries of synthetic compounds have yet to offer effective replacements for current antibiotics. Due to historical successes, discovery from large and diverse natural sources and, more specifically, environmental bacteria, may still yield novel alternative antibiotics. However, the process of antibiotic discovery from natural sources is laborious and time-consuming as a result of outdated methodologies. Therefore, we have developed a simple and rapid preliminary screening assay to identify antibacterial-producing bacteria from natural sources. In brief, the assay utilizes the presence or absence of luminescence in bioluminescent reporter bacteria and test bacterium co-cultures in a 96-well plate format to determine the absence or presence of antibacterial compound production. Our assay, called the bioluminescent simultaneous antagonism (BSLA) assay, can accurately distinguish between known antibacterial-producing and non-producing test bacteria. The BSLA assay was validated by screening 264 unknown soil isolates which resulted in the identification of 10 antibacterial-producing isolates, effectively decreasing the pool of isolates for downstream analysis by 96%. By design, the assay is simple and requires only general laboratory equipment; however, we have shown that the assay can be scaled to automated high-throughput screening systems. Taken together, the BSLA assay allows for the rapid pre-screening of unknown bacterial isolates which, when coupled with innovative downstream dereplication and identification technologies, can effectively fast-track antimicrobial discovery.

The novel oligopeptide utilizing species Anaeropeptidivorans aminofermentans M3/9T, its role in anaerobic digestion and occurrence as deduced from large-scale fragment recruitment analyses

Research on biogas-producing microbial communities aims at elucidation of correlations and dependencies between the anaerobic digestion (AD) process and the corresponding microbiome composition in order to optimize the performance of the process and the biogas output. Previously, Lachnospiraceae species were frequently detected in mesophilic to moderately thermophilic biogas reactors. To analyze adaptive genome features of a representative Lachnospiraceae strain, Anaeropeptidivorans aminofermentans M3/9T was isolated from a mesophilic laboratory-scale biogas plant and its genome was sequenced and analyzed in detail. Strain M3/9T possesses a number of genes encoding enzymes for degradation of proteins, oligo- and dipeptides. Moreover, genes encoding enzymes participating in fermentation of amino acids released from peptide hydrolysis were also identified. Based on further findings obtained from metabolic pathway reconstruction, M3/9T was predicted to participate in acidogenesis within the AD process. To understand the genomic diversity between the biogas isolate M3/9T and closely related Anaerotignum type strains, genome sequence comparisons were performed. M3/9T harbors 1,693 strain-specific genes among others encoding different peptidases, a phosphotransferase system (PTS) for sugar uptake, but also proteins involved in extracellular solute binding and import, sporulation and flagellar biosynthesis. In order to determine the occurrence of M3/9T in other environments, large-scale fragment recruitments with the M3/9T genome as a template and publicly available metagenomes representing different environments was performed. The strain was detected in the intestine of mammals, being most abundant in goat feces, occasionally used as a substrate for biogas production.

Marine Bioprospecting, Biocatalysis and Process Development

Oceans possess tremendous diversity in microbial life. The enzymatic machinery that marine bacteria present is the result of extensive evolution to assist cell survival under the harsh and continuously changing conditions found in the marine environment. Several bacterial cells and enzymes are already used at an industrial scale, but novel biocatalysts are still needed for sustainable industrial applications, with benefits for both public health and the environment. Metagenomic techniques have enabled the discovery of novel biocatalysts, biosynthetic pathways, and microbial identification without their cultivation. However, a key stage for application of novel biocatalysts is the need for rapid evaluation of the feasibility of the bioprocess. Cultivation of not-yet-cultured bacteria is challenging and requires new methodologies to enable growth of the bacteria present in collected environmental samples, but, once a bacterium is isolated, its enzyme activities are easily measured. High-throughput screening techniques have also been used successfully, and innovative in vitro screening platforms to rapidly identify relevant enzymatic activities continue to improve. Small-scale approaches and process integration could improve the study and development of new bioprocesses to produce commercially interesting products. In this work, the latest studies related to (i) the growth of marine bacteria under laboratorial conditions, (ii) screening techniques for bioprospecting, and (iii) bioprocess development using microreactors and miniaturized systems are reviewed and discussed.

Biphenyl-degrading Bacteria Isolation with Laser Induced Visualized Ejection Separation Technology and Traditional Colony Sorting

In this work, biphenyl was used as carbon source to enrich microorganisms from polychlorinated biphenyls (PCBs)-contaminated paddy soil samples, and the taxonomic structures in both of the soil samples and the fourth-generation enrichments were examined with high-throughput sequencing. Single cells were isolated from the enrichments via single cell sorting technology named Laser Induced Visualized Ejection Separation Technology (LIVEST) and also traditional single colony sorting, and the genera of the isolates were identified using 16S rRNA sequencing. The results from high-throughput sequencing present that enrichment from generation to generation can considerably change the microbial community. Comparing the two sorting methods, the LIVEST is more time-saving and cell-targeted for microbial resource exploration. Based on the further verification of biphenyl degradation, it was found that some strains belonging to genera Macrococcus, Aerococcus and Metabacillus are capable in degrading biphenyl, which have not been reported yet.

Cultivating marine bacteria under laboratory conditions: Overcoming the “unculturable” dogma

Underexplored seawater environments may contain biological resources with potential for new biotechnological applications. Metagenomic techniques revolutionized the study of bacterial communities but culture dependent methods will still be important to help the biodiscovery of new products and enzymes from marine bacteria. In this context, we promoted the growth of bacteria from a marine rock pond by culture dependent techniques and compared the results with culture independent methods. The total number of bacteria and diversity were studied in different agar plate media during 6 weeks. Agar plate counting was of the same order of magnitude of direct microscopy counts. The highest efficiency of cultivation was 45% attained in marine agar medium. Molecular analysis revealed 10 different phyla of which only four were isolated by the culture dependent method. On the other hand, four taxonomic orders were detected by cultivation but not by the molecular technique. These include bacteria from the phyla Bacillota and Actinomycetota. Our study shows that it is possible to grow more than the traditionally considered 1% of bacteria from a seawater sample using standard agar plate techniques and laboratorial conditions. The results also demonstrate the importance of culture methods to grow bacteria not detected by molecular approaches for future biotechnological applications.

MLR-OOD: A Markov Chain Based Likelihood Ratio Method for Out-Of-Distribution Detection of Genomic Sequences

Machine learning or deep learning models have been widely used for taxonomic classification of metagenomic sequences and many studies reported high classification accuracy. Such models are usually trained based on sequences in several training classes in hope of accurately classifying unknown sequences into these classes. However, when deploying the classification models on real testing data sets, sequences that do not belong to any of the training classes may be present and are falsely assigned to one of the training classes with high confidence. Such sequences are referred to as out-of-distribution (OOD) sequences and are ubiquitous in metagenomic studies. To address this problem, we develop a deep generative model-based method, MLR-OOD, that measures the probability of a testing sequencing belonging to OOD by the likelihood ratio of the maximum of the in-distribution (ID) class conditional likelihoods and the Markov chain likelihood of the testing sequence measuring the sequence complexity. We compose three different microbial data sets consisting of bacterial, viral, and plasmid sequences for comprehensively benchmarking OOD detection methods. We show that MLR-OOD achieves the state-of-the-art performance demonstrating the generality of MLR-OOD to various types of microbial data sets. It is also shown that MLR-OOD is robust to the GC content, which is a major confounding effect for OOD detection of genomic sequences. In conclusion, MLR-OOD will greatly reduce false positives caused by OOD sequences in metagenomic sequence classification.

Functional characterization of prokaryotic dark matter: the road so far and what lies ahead

Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the "microbial dark matter" (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.

Genome analysis of the candidate phylum MBNT15 bacterium from a boreal peatland predicted its respiratory versatility and dissimilatory iron metabolism

Uncultured bacteria of the candidate phylum MBNT15, distantly related to Desulfobacterota, have been identified in a broad range of mostly organic-rich aquatic environments. We assembled a near-complete genome of a member of MBNT15 from a boreal peatland metagenome and used genomic data to analyze the metabolic pathways of this bacterium and its ecological role. This bacterium, designated SHF-111, was predicted to be rod shaped, it lacks flagellar machinery but twitching motility is encoded. Genome-based phylogenetic analysis supported the phylum-level classification of the MBNT15 lineage. Genome annotation and metabolic reconstruction revealed the presence of the Embden-Meyerhof, Entner-Doudoroff and pentose phosphate pathways, as well as the complete tricarboxylic acid (TCA) cycle, and suggested a facultatively anaerobic chemoheterotrophic lifestyle with the ability to ferment peptides, amino acids, fatty acids and simple sugars, and completely oxidize these substrates through aerobic and anaerobic respiration. The SHF-111 genome encodes multiple multiheme c-type cytochromes that probably enable dissimilatory iron reduction. Consistently, the relative abundance of MBNT15 in peatlands positively correlated with iron concentration. Apparently, in the wetland ecosystem, MBNT15 representatives play the role of scavengers, carrying out the complete mineralization of low molecular weight organic substances formed as a result of microbial degradation of complex polymeric substrates. Comparative genome analysis of the MBNT15 phylum revealed that vast majority of its members are capable of aerobic respiration and dissimilatory iron reduction and some species also can reduce sulfur and nitrogen compounds, but not sulfate. Based on phylogenetic and genomic analyses, the novel bacterium is proposed to be classified as Candidatus Deferrimicrobium borealis, within a candidate phylum Deferrimicrobiota.

Tracking the diversity and interaction of methanogens in the energy recovery process of a full-scale wastewater treatment plant

Methanogens have been significant for the achievement of carbon neutrality in wastewater treatment plants due to their crucial roles in the anaerobic digestion of sludge. Nevertheless, the phylogenetic diversity of methanogens and their versatile metabolism have been continuously investigated, the current scientific knowledge regarding these microbes appears inadequate and requires more evaluations. This study is considered an endeavor in which functional genes sequencing was used to reveal the diversity of methanogens in the sludge process of the wastewater treatment plant. The information obtained was substantially more than that employing 16s sequencing. The methanogenic microbial resources were appropriate to sustain a self-inoculated energy recovery with a potential ability to boost methane production. A constancy was observed in 16 S rRNA gene and mcrA gene sequencing results, where the bacterial or Methanosaeta concilii dominated community of DS (digest sludge) was distinct from the inoculum sources TS (total sludge), CTS (concentrated total sludge), and HTS (hydrolysis total sludge), indicating the independent development of DS. A quantitative cross-network was constructed by coupling the absolute quantify of 16 S rRNA and mcrA sequences. The Methanobacterium petrolearium actively interacted with bacteria in the DS community rather than the dominant species (Methanosaeta concilii). Moreover, the unclassified methanogens were identified to be significantly prevalent in all communities, suggesting that unknown methanogenic taxa might be imperative in accomplishing community functions. Collectively, the findings of this research study will shed light on the comprehensive knowledge of microbial communities, especially the methanogenic microbiota. This will further enhance the exploration of the phylogenetic diversity of methanogens and their corresponding impacts in energy recovery from wastewater treatment plants.

How clear is our current view on microbial dark matter? (Re-)assessing public MAG & SAG datasets with MDMcleaner

As of today, the majority of environmental microorganisms remain uncultured and is therefore referred to as 'microbial dark matter' (MDM). Hence, genomic insights into these organisms are limited to cultivation-independent approaches such as single-cell- and metagenomics. However, without access to cultured representatives for verifying correct taxon-assignments, MDM genomes may cause potentially misleading conclusions based on misclassified or contaminant contigs, thereby obfuscating our view on the uncultured microbial majority. Moreover, gradual database contaminations by past genome submissions can cause error propagations which affect present as well as future comparative genome analyses. Consequently, strict contamination detection and filtering need to be applied, especially in the case of uncultured MDM genomes. Current genome reporting standards, however, emphasize completeness over purity and the de facto gold standard genome assessment tool, checkM, discriminates against uncultured taxa and fragmented genomes. To tackle these issues, we present a novel contig classification, screening, and filtering workflow and corresponding open-source python implementation called MDMcleaner, which was tested and compared to other tools on mock and real datasets. MDMcleaner revealed substantial contaminations overlooked by current screening approaches and sensitively detects misattributed contigs in both novel genomes and the underlying reference databases, thereby greatly improving our view on 'microbial dark matter'.

Recovery of Lutacidiplasmatales archaeal order genomes suggests convergent evolution in Thermoplasmatota

The Terrestrial Miscellaneous Euryarchaeota Group has been identified in various environments, and the single genome investigated thus far suggests that these archaea are anaerobic sulfite reducers. We assemble 35 new genomes from this group that, based on genome analysis, appear to possess aerobic and facultative anaerobic lifestyles and may oxidise rather than reduce sulfite. We propose naming this order (representing 16 genera) "Lutacidiplasmatales" due to their occurrence in various acidic environments and placement within the phylum Thermoplasmatota. Phylum-level analysis reveals that Thermoplasmatota evolution had been punctuated by several periods of high levels of novel gene family acquisition. Several essential metabolisms, such as aerobic respiration and acid tolerance, were likely acquired independently by divergent lineages through convergent evolution rather than inherited from a common ancestor. Ultimately, this study describes the terrestrially prevalent Lutacidiciplasmatales and highlights convergent evolution as an important driving force in the evolution of archaeal lineages.

In situ identification of environmental microorganisms with Raman spectroscopy

Microorganisms in natural environments are crucial in maintaining the material and energy cycle and the ecological balance of the environment. However, it is challenging to delineate environmental microbes' actual metabolic pathways and intraspecific heterogeneity because most microorganisms cannot be cultivated. Raman spectroscopy is a culture-independent technique that can collect molecular vibration profiles from cells. It can reveal the physiological and biochemical information at the single-cell level rapidly and non-destructively in situ. The first part of this review introduces the principles, advantages, progress, and analytical methods of Raman spectroscopy applied in environmental microbiology. The second part summarizes the applications of Raman spectroscopy combined with stable isotope probing (SIP), fluorescence in situ hybridization (FISH), Raman-activated cell sorting and genomic sequencing, and machine learning in microbiological studies. Finally, this review discusses expectations of Raman spectroscopy and future advances to be made in identifying microorganisms, especially for uncultured microorganisms.

It’s a Long Way to the Tap: Microbiome and DNA-Based Omics at the Core of Drinking Water Quality

Microbial communities interact with us and affect our health in ways that are only beginning to be understood. Microorganisms have been detected in every ecosystem on Earth, as well as in any built environment that has been investigated. Drinking water sources, drinking water treatment plants and distribution systems provide peculiar microbial ecological niches, dismantling the belief of the “biological simplicity” of drinking water. Nevertheless, drinking water microbiomes are understudied compared to other microbiomes. Recent DNA sequencing and meta-omics advancements allow a deeper understanding of drinking water microbiota. Thus, moving beyond the limits of day-to-day testing for specific pathogenic microbes, new approaches aim at predicting microbiome changes driven by disturbances at the macro-scale and overtime. This will foster an effective and proactive management of water sources, improving the drinking water supply system and the monitoring activities to lower public health risk. Here, we want to give a new angle on drinking water microbiome research. Starting from a selection of 231 scientific publications on this topic, we emphasize the value of biodiversity in drinking water ecosystems and how it can be related with industrialization. We then discuss how microbiome research can support sustainable drinking water management, encouraging collaborations across sectors and involving the society through responsible research and innovation.

Analysis of Microbial Community Structure and Diversity in Burial Soil of Yangguanzhai Cemetery

As one of the common physical remains in archaeological discoveries, human bones are important bases for studying the history of human development, which is of great significance for exploring the evolution law of ancient human, reconstructing ancient human society, and tracking the development of human civilization. However, in the process of human bone burial, in addition to being affected by physical and chemical factors, it will also be affected by microorganisms in the buried soil, resulting in a variety of diseases. According to the determination and analysis of the microbial community structure and diversity in the burial soil of Yangguanzhai Site in Gaoling District in Xi’an city, Shaanxi Province, this paper attempts to explore the influence of microorganisms in the burial environment on human bones, in order to provide scientific proof for the microbial prevention and control of bone relics in the archaeological excavation site. For the first time, Illumina NovaSeq high-throughput sequencing technology was used to analyze the microbial community structure in the burial soil. At the phylum level, there were 8 dominant bacteria species in the soil samples of tombs, which were Firmicutes, Actinobacteriota, Actinobacteria, Proteobacteria, Acidobacteriota, Methylomirabilota, Chloroflexi, Bacteroidota. At the genus level, there were 12 dominant species in the soil samples of tombs, including MIZ17, MND1, Gaiella, oc32, Kroppenstedtia, Halomonas, Bacteroides, Dongia, Faecalibacterium, Nocardioides, Pseudomonas, Pseudonocardia. The overall microorganisms in the soil of Yangguanzhai Cemetery were relatively well-distributed, and the microbial community structure near human bones is the most abundant and diverse. Therefore, it is necessary to take some measures to control microorganisms and protect human bones.

From the bacterial citrus microbiome to the selection of potentially host-beneficial microbes

Citrus is the most cultivated fruit crop worldwide. The modern citrus industry needs new bioproducts to overcome phytopathological threats, tolerate stresses and increase yield and quality. Mutualistic microbes from roots significantly impact host physiology and health and are a potentially beneficial resource. The bacterial microbiome can be surveyed to select potentially host-beneficial microbes. To achieve this goal, a prevalent "core-citrus" bacterial microbiome was obtained by picking those operational taxonomic units (OTUs) shared among samples within and across two Citrus rootstock genotypes grown in the same soil for more than 20 years. A sub-selection of main OTUs from the defined "core-citrus" microbiome was made based on abundance, host-enriched versus bulk soil, and rhizosphere-indicator species. In parallel, an extensive census of the cultivable microbiota was performed to collect a large number of bacterial citrus isolates. Metataxonomic data were linked to cultured microbes, matching 16S rRNA gene sequences from bacterial isolates with those counterpart OTU reference sequences from the selected bacterial "core-citrus" microbiome. This approach allowed selection of potentially host-beneficial bacteria to mine for agricultural probiotics in future biotechnological applications required for the citrus industry.

Candidate Phyla Radiation, an Underappreciated Division of the Human Microbiome, and Its Impact on Health and Disease

Candidate phyla radiation (CPR) is an emerging division of the bacterial domain within the human microbiota. Still poorly known, these microorganisms were first described in the environment in 1981 as "ultramicrobacteria" with a cell volume under 0.1 μm³ and were first associated with the human oral microbiota in 2007. The evolution of technology has been paramount for the study of CPR within the human microbiota. In fact, since these ultramicrobacteria have yet to be axenically cultured despite ongoing efforts, progress in imaging technology has allowed their observation and morphological description. Although their genomic abilities and taxonomy are still being studied, great strides have been made regarding their taxonomic classification, as well as their lifestyle. In addition, advancements in next-generation sequencing and the continued development of bioinformatics tools have allowed their detection as commensals in different human habitats, including the oral cavity and gastrointestinal and genital tracts, thus highlighting CPR as a nonnegligible part of the human microbiota with an impact on physiological settings. Conversely, several pathologies present dysbiosis affecting CPR levels, including inflammatory, mucosal, and infectious diseases. In this exhaustive review of the literature, we provide a historical perspective on the study of CPR, an overview of the methods available to study these organisms and a description of their taxonomy and lifestyle. In addition, their distribution in the human microbiome is presented in both homeostatic and dysbiotic settings. Future efforts should focus on developing cocultures and, if possible, axenic cultures to obtain isolates and therefore genomes that would provide a better understanding of these ultramicrobacteria, the importance of which in the human microbiome is undeniable.

Stool and Ruminal Microbiome Components Associated With Methane Emission and Feed Efficiency in Nelore Beef Cattle

Background: The impact of extreme changes in weather patterns on the economy and human welfare is one of the biggest challenges our civilization faces. From anthropogenic contributions to climate change, reducing the impact of farming activities is a priority since it is responsible for up to 18% of global greenhouse gas emissions. To this end, we tested whether ruminal and stool microbiome components could be used as biomarkers for methane emission and feed efficiency in bovine by studying 52 Brazilian Nelore bulls belonging to two feed intervention treatment groups, that is, conventional and by-product-based diets.

Results: We identified a total of 5,693 amplicon sequence variants (ASVs) in the Nelore bulls’ microbiomes. A Differential abundance analysis with the ANCOM approach identified 30 bacterial and 15 archaeal ASVs as differentially abundant (DA) among treatment groups. An association analysis using Maaslin2 software and a linear mixed model indicated that bacterial ASVs are linked to the host’s residual methane emission (RCH₄) and residual feed intake (RFI) phenotype variation, suggesting their potential as targets for interventions or biomarkers.

Conclusion: The feed composition induced significant differences in both abundance and richness of ruminal and stool microbial populations in ruminants of the Nelore breed. The industrial by-product-based dietary treatment applied to our experimental groups influenced the microbiome diversity of bacteria and archaea but not of protozoa. ASVs were associated with RCH₄ emission and RFI in ruminal and stool microbiomes. While ruminal ASVs were expected to influence CH₄ emission and RFI, the relationship of stool taxa, such as Alistipes and Rikenellaceae (gut group RC9), with these traits was not reported before and might be associated with host health due to their link to anti-inflammatory compounds. Overall, the ASVs associated here have the potential to be used as biomarkers for these complex phenotypes.

Microcystin drives the composition of small-sized bacterioplankton communities from a coastal lagoon

Cyanobacterial blooms affect biotic interactions in aquatic ecosystems, including those involving heterotrophic bacteria. Ultra-small microbial communities are found in both surface water and groundwater and include diverse heterotrophic bacteria. Although the taxonomic composition of these communities has been described in some environments, the involvement of these small cells in the fate of environmentally relevant molecules has not been investigated. Here, we aimed to test if small-sized microbial fractions from a polluted urban lagoon were able to degrade the cyanotoxin microcystin (MC). We obtained cells after filtration through 0.45 as well as 0.22 μm membranes and characterized the morphology and taxonomic composition of bacteria before and after incubation with and without microcystin-LR (MC-LR). Communities from different size fractions (< 0.22 and < 0.45 μm) were able to remove the dissolved MC-LR. The originally small-sized cells grew during incubation, as shown by transmission electron microscopy, and changed in both cell size and morphology. The analysis of 16S rDNA sequences revealed that communities originated from < 0.22 and < 0.45 μm fractions diverged in taxonomic composition although they shared certain bacterial taxa. The presence of MC-LR shifted the structure of < 0.45 μm communities in comparison to those maintained without toxin. Actinobacteria was initially dominant and after incubation with MC-LR Proteobacteria predominated. There was a clear enhancement of taxa already known to degrade MC-LR such as Methylophilaceae. Small-sized bacteria constitute a diverse and underestimated fraction of microbial communities, which participate in the dynamics of MC-LR in natural environments.

Quantifying and Cataloguing Unknown Sequences within Human Microbiomes

Advances in genome sequencing technologies and lower costs have enabled the exploration of a multitude of known and novel environments and microbiomes. This has led to an exponential growth in the raw sequence data that are deposited in online repositories. Metagenomic and metatranscriptomic data sets are typically analysed with regard to a specific biological question. However, it is widely acknowledged that these data sets are comprised of a proportion of sequences that bear no similarity to any currently known biological sequence, and this so-called "dark matter" is often excluded from downstream analyses. In this study, a systematic framework was developed to assemble, identify, and measure the proportion of unknown sequences present in distinct human microbiomes. This framework was applied to 40 distinct studies, comprising 963 samples, and covering 10 different human microbiomes including fecal, oral, lung, skin, and circulatory system microbiomes. We found that while the human microbiome is one of the most extensively studied, on average 2% of assembled sequences have not yet been taxonomically defined. However, this proportion varied extensively among different microbiomes and was as high as 25% for skin and oral microbiomes that have more interactions with the environment. A rate of taxonomic characterization of 1.64% of unknown sequences being characterized per month was calculated from these taxonomically unknown sequences discovered in this study. A cross-study comparison led to the identification of similar unknown sequences in different samples and/or microbiomes. Both our computational framework and the novel unknown sequences produced are publicly available for future cross-referencing. Our approach led to the discovery of several novel viral genomes that bear no similarity to sequences in the public databases. Some of these are widespread as they have been found in different microbiomes and studies. Hence, our study illustrates how the systematic characterization of unknown sequences can help the discovery of novel microbes, and we call on the research community to systematically collate and share the unknown sequences from metagenomic studies to increase the rate at which the unknown sequence space can be classified.

Dataset for Genome Sequencing and De Novo Assembly of the Candidate Phyla Radiation in Supragingival Plaque

The Candidate Phyla Radiation (CPR), as a newly discovered and difficult-to-culture bacterium, accounts for the majority of the bacterial domain, which may be related to various oral diseases, including dental caries. Restricted by laboratory culture conditions, there is limited knowledge about oral CPR. Advances in metagenomics provide a new way to study CPR through molecular biology. Here, we used metagenomic assembly and binning to reconstruct more and higher quality metagenome-assembled genomes (MAGs) of CPR from oral dental plaque. These MAGs represent novel CPR species, which differed from all known CPR organisms. Relative abundance of different CPR MAGs in the caries and caries-free group was estimated by mapping metagenomic reads to newly constructed MAGs. The relative abundance of two CPR MAGs was significantly increased in the caries group, indicating that there might be a relationship with caries activity. The detection of a large number of unclassified CPR MAGs in the dataset implies that the phylogenetic diversity of CPR is enormous. The results provide a reference value for exploring the ecological distribution and function of uncultured or difficult-to-culture microorganisms.