Microbial Dark Matter Investigations: How Microbial Studies Transform Biological Knowledge and Empirically Sketch a Logic of Scientific Discovery

Frequent nonhomologous replacement of replicative helicase loaders by viruses in Vibrionaceae

Several microbial genomes lack textbook-defined essential genes. If an essential gene is absent from a genome, then an evolutionarily independent gene of unknown function complements its function. Here, we identified frequent nonhomologous replacement of an essential component of DNA replication initiation, a replicative helicase loader gene, in Vibrionaceae. Our analysis of Vibrionaceae genomes revealed two genes with unknown function, named vdhL1 and vdhL2, that were substantially enriched in genomes without the known helicase-loader genes. These genes showed no sequence similarities to genes with known function but encoded proteins structurally similar with a viral helicase loader. Analyses of genomic syntenies and coevolution with helicase genes suggested that vdhL1/2 encodes a helicase loader. The in vitro assay showed that Vibrio harveyi VdhL1 and Vibrio ezurae VdhL2 promote the helicase activity of DnaB. Furthermore, molecular phylogenetics suggested that vdhL1/2 were derived from phages and replaced an intrinsic helicase loader gene of Vibrionaceae over 20 times. This high replacement frequency implies the host's advantage in acquiring a viral helicase loader gene.

Epistemic misalignments in microbiome research

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

Accessing the specialized metabolome of actinobacteria from the bulk soil of Paullinia cupana Mart. on the Brazilian Amazon: a promising source of bioactive compounds against soybean phytopathogens

The Amazon rainforest, an incredibly biodiverse ecosystem, has been increasingly vulnerable to deforestation. Despite its undeniable importance and potential, the Amazonian microbiome has historically received limited study, particularly in relation to its unique arsenal of specialized metabolites. Therefore, in this study our aim was to assess the metabolic diversity and the antifungal activity of actinobacterial strains isolated from the bulk soil of Paullinia cupana, a native crop, in the Brazilian Amazon Rainforest. Extracts from 24 strains were subjected to UPLC-MS/MS analysis using an integrative approach that relied on the Chemical Structural and Compositional Similarity (CSCS) metric, GNPS molecular networking, and in silico dereplication tools. This procedure allowed the comprehensive understanding of the chemical space encompassed by these actinobacteria, which consists of features belonging to known bioactive metabolite classes and several unannotated molecular families. Among the evaluated strains, five isolates exhibited bioactivity against a panel of soybean fungal phytopathogens (Rhizoctonia solani, Macrophomina phaseolina, and Sclerotinia sclerotiorum). A focused inspection led to the annotation of pepstatins, oligomycins, hydroxamate siderophores and dorrigocins as metabolites produced by these bioactive strains, with potentially unknown compounds also comprising their metabolomes. This study introduces a pragmatic protocol grounded in established and readily available tools for the annotation of metabolites and the prioritization of strains to optimize further isolation of specialized metabolites. Conclusively, we demonstrate the relevance of the Amazonian actinobacteria as sources for bioactive metabolites useful for agriculture. We also emphasize the importance of preserving this biome and conducting more in-depth studies on its microbiota.

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.

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.

Microbiome-functionality in anaerobic digesters: A critical review

Microbially driven anaerobic digestion (AD) processes are of immense interest due to their role in the biovalorization of biowastes into renewable energy resources. The function-versatile microbiome, interspecies syntrophic interactions, and trophic-level metabolic pathways are important microbial components of AD. However, the lack of a comprehensive understanding of the process hampers efforts to improve AD efficiency. This study presents a holistic review of research on the microbial and metabolic "black box" of AD processes. Recent research on microbiology, functional traits, and metabolic pathways in AD, as well as the responses of functional microbiota and metabolic capabilities to optimization strategies are reviewed. The diverse ecophysiological traits and cooperation/competition interactions of the functional guilds and the biomanipulation of microbial ecology to generate valuable products other than methane during AD are outlined. The results show that AD communities prioritize cooperation to improve functional redundancy, and the dominance of specific microbes can be explained by thermodynamics, resource allocation models, and metabolic division of labor during cross-feeding. In addition, the multi-omics approaches used to decipher the ecological principles of AD consortia are summarized in detail. Lastly, future microbial research and engineering applications of AD are proposed. This review presents an in-depth understanding of microbiome-functionality mechanisms of AD and provides critical guidance for the directional and efficient bioconversion of biowastes into methane and other valuable products.

Metagenomic assembly is the main bottleneck in the identification of mobile genetic elements

Antimicrobial resistance genes (ARG) are commonly found on acquired mobile genetic elements (MGEs) such as plasmids or transposons. Understanding the spread of resistance genes associated with mobile elements (mARGs) across different hosts and environments requires linking ARGs to the existing mobile reservoir within bacterial communities. However, reconstructing mARGs in metagenomic data from diverse ecosystems poses computational challenges, including genome fragment reconstruction (assembly), high-throughput annotation of MGEs, and identification of their association with ARGs. Recently, several bioinformatics tools have been developed to identify assembled fragments of plasmids, phages, and insertion sequence (IS) elements in metagenomic data. These methods can help in understanding the dissemination of mARGs. To streamline the process of identifying mARGs in multiple samples, we combined these tools in an automated high-throughput open-source pipeline, MetaMobilePicker, that identifies ARGs associated with plasmids, IS elements and phages, starting from short metagenomic sequencing reads. This pipeline was used to identify these three elements on a simplified simulated metagenome dataset, comprising whole genome sequences from seven clinically relevant bacterial species containing 55 ARGs, nine plasmids and five phages. The results demonstrated moderate precision for the identification of plasmids (0.57) and phages (0.71), and moderate sensitivity of identification of IS elements (0.58) and ARGs (0.70). In this study, we aim to assess the main causes of this moderate performance of the MGE prediction tools in a comprehensive manner. We conducted a systematic benchmark, considering metagenomic read coverage, contig length cutoffs and investigating the performance of the classification algorithms. Our analysis revealed that the metagenomic assembly process is the primary bottleneck when linking ARGs to identified MGEs in short-read metagenomics sequencing experiments rather than ARGs and MGEs identification by the different tools.

A metagenomic library cloning strategy that promotes high-level expression of captured genes to enable efficient functional screening

Functional screening of environmental DNA (eDNA) libraries is a potentially powerful approach to discover enzymatic "unknown unknowns", but is usually heavily biased toward the tiny subset of genes preferentially transcribed and translated by the screening strain. We have overcome this by preparing an eDNA library via partial digest with restriction enzyme FatI (cuts CATG), causing a substantial proportion of ATG start codons to be precisely aligned with strong plasmid-encoded promoter and ribosome-binding sequences. Whereas we were unable to select nitroreductases from standard metagenome libraries, our FatI strategy yielded 21 nitroreductases spanning eight different enzyme families, each conferring resistance to the nitro-antibiotic niclosamide and sensitivity to the nitro-prodrug metronidazole. We showed expression could be improved by co-expressing rare tRNAs and encoded proteins purified directly using an embedded His6-tag. In a transgenic zebrafish model of metronidazole-mediated targeted cell ablation, our lead MhqN-family nitroreductase proved ∼5-fold more effective than the canonical nitroreductase NfsB.

Comparative analysis of HiSeq3000 and BGISEQ-500 sequencing platform over whole genome sequencing metagenomics data

Recent advances in sequencing technologies and platforms have enabled to generate metagenomics sequences using different sequencing platforms. In this study, we analyzed and compared shotgun metagenomic sequences generated by HiSeq3000 and BGISEQ-500 platforms from 12 sediment samples collected across the Norwegian coast. Metagenomics DNA sequences were normalized to an equal number of bases for both platforms and further evaluated by using different taxonomic classifiers, reference databases, and assemblers. Normalized BGISEQ-500 sequences retained more reads and base counts after preprocessing, while a slightly higher fraction of HiSeq3000 sequences were taxonomically classified. Kaiju classified a higher percentage of reads relative to Kraken2 for both platforms, and comparison of reference database for taxonomic classification showed that MAR database outperformed RefSeq. Assembly using MEGAHIT produced longer assemblies and higher total contigs count in majority of HiSeq3000 samples than using metaSPAdes, but the assembly statistics notably improved with unprocessed or normalized reads. Our results indicate that both platforms perform comparably in terms of the percentage of taxonomically classified reads and assembled contig statistics for metagenomics samples. This study provides valuable insights for researchers in selecting an appropriate sequencing platform and bioinformatics pipeline for their metagenomics studies.

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.

A metagenomic library cloning strategy that promotes high-level expression of captured genes to enable efficient functional screening

Functional screening of environmental DNA (eDNA) libraries is a potentially powerful approach to discover enzymatic "unknown unknowns", but is usually heavily biased toward the tiny subset of genes preferentially transcribed and translated by the screening strain. We have overcome this by preparing an eDNA library via partial digest with restriction enzyme FatI (cuts CATG), causing a substantial proportion of ATG start codons to be precisely aligned with strong plasmid-encoded promoter and ribosome-binding sequences. Whereas we were unable to select nitroreductases from standard metagenome libraries, our FatI strategy yielded 21 nitroreductases spanning eight different enzyme families, each conferring resistance to the nitro-antibiotic niclosamide and sensitivity to the nitro-prodrug metronidazole. We showed expression could be improved by co-expressing rare tRNAs and encoded proteins purified directly using an embedded His6-tag. In a transgenic zebrafish model of metronidazole-mediated targeted cell ablation, our lead MhqN-family nitroreductase proved ~5-fold more effective than the canonical nitroreductase NfsB.

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.

Red Sea Atlas of Coral-Associated Bacteria Highlights Common Microbiome Members and Their Distribution across Environmental Gradients-A Systematic Review

The Red Sea is a suitable model for studying coral reefs under climate change due to its strong environmental gradient that provides a window into future global warming scenarios. For instance, corals in the southern Red Sea thrive at temperatures predicted to occur at the end of the century in other biogeographic regions. Corals in the Red Sea thrive under contrasting thermal and environmental regimes along their latitudinal gradient. Because microbial communities associated with corals contribute to host physiology, we conducted a systematic review of the known diversity of Red Sea coral-associated bacteria, considering geographic location and host species. Our assessment comprises 54 studies of 67 coral host species employing cultivation-dependent and cultivation-independent techniques. Most studies have been conducted in the central and northern Red Sea, while the southern and western regions remain largely unexplored. Our data also show that, despite the high diversity of corals in the Red Sea, the most studied corals were Pocillopora verrucosa, Dipsastraea spp., Pleuractis granulosa, and Stylophora pistillata. Microbial diversity was dominated by bacteria from the class Gammaproteobacteria, while the most frequently occurring bacterial families included Rhodobacteraceae and Vibrionaceae. We also identified bacterial families exclusively associated with each of the studied coral orders: Scleractinia (n = 125), Alcyonacea (n = 7), and Capitata (n = 2). This review encompasses 20 years of research in the Red Sea, providing a baseline compendium for coral-associated bacterial diversity.

Seasonal microbial dynamics in the ocean inferred from assembled and unassembled data: a view on the unknown biosphere

In environmental metagenomic experiments, a very high proportion of the microbial sequencing data (> 70%) remains largely unexploited because rare and closely related genomes are missed in short-read assemblies. The identity and the potential metabolisms of a large fraction of natural microbial communities thus remain inaccessible to researchers. The purpose of this study was to explore the genomic content of unassembled metagenomic data and test their level of novelty. We used data from a three-year microbial metagenomic time series of the NW Mediterranean Sea, and conducted reference-free and database-guided analysis. The results revealed a significant genomic difference between the assembled and unassembled reads. The unassembled reads had a lower mean identity against public databases, and fewer metabolic pathways could be reconstructed. In addition, the unassembled fraction presented a clear temporal pattern, unlike the assembled ones, and a specific community composition that was similar to the rare communities defined by metabarcoding using the 16S rRNA gene. The rare gene pool was characterised by keystone bacterial taxa, and the presence of viruses, suggesting that viral lysis could maintain some taxa in a state of rarity. Our study demonstrates that unassembled metagenomic data can provide important information on the structure and functioning of microbial communities.

Evaluation of phoxim toxicity on aquatic and zebrafish intestinal microbiota by metagenomics and 16S rRNA gene sequencing analysis

Phoxim is one of the main organophosphorus pesticides used in agricultural production. However, little information is known about how it affects the aquatic microbial community and the intestinal microbiota of fish. Herein, we utilized shotgun metagenomics and 16S rRNA gene sequencing to reveal the aquatic eco-risk of phoxim. Seven days of phoxim exposure significantly changed the composition of aquatic microbial community, obliterated the interactions between microorganisms, and thus reduced the complexity and stability of the microbial community. During long-time exposure (i.e., 14 days), most of the ecological functions were restored due to the redundancy of the microbial community. However, phoxim exposure promoted the dissemination of elfamycin resistance gene. The zebrafish gut microbial community also recovered from a temporary ecological disorder of aquatic microbiota, but phoxim continually affected zebrafish growth and swimming behavior. Overall, our results demonstrated that phoxim exposure significantly changed the structure and function of the microbial community and displayed a negative impact on freshwater ecosystems in a short exposure time.

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.

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.

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’.

Industrial Biotechnology Based on Enzymes From Extreme Environments

Biocatalysis is crucial for a green, sustainable, biobased economy, and this has driven major advances in biotechnology and biocatalysis over the past 2 decades. There are numerous benefits to biocatalysis, including increased selectivity and specificity, reduced operating costs and lower toxicity, all of which result in lower environmental impact of industrial processes. Most enzymes available commercially are active and stable under a narrow range of conditions, and quickly lose activity at extremes of ion concentration, temperature, pH, pressure, and solvent concentrations. Extremophilic microorganisms thrive under extreme conditions and produce robust enzymes with higher activity and stability under unconventional circumstances. The number of extremophilic enzymes, or extremozymes, currently available are insufficient to meet growing industrial demand. This is in part due to difficulty in cultivation of extremophiles in a laboratory setting. This review will present an overview of extremozymes and their biotechnological applications. Culture-independent and genomic-based methods for study of extremozymes will be presented.

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.

Unifying the known and unknown microbial coding sequence space

Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40–60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we present a conceptual framework, its translation into the computational workflow AGNOSTOS and a demonstration on how we can bridge the known-unknown gap in genomes and metagenomes. By analyzing 415,971,742 genes predicted from 1749 metagenomes and 28,941 bacterial and archaeal genomes, we quantify the extent of the unknown fraction, its diversity, and its relevance across multiple organisms and environments. The unknown sequence space is exceptionally diverse, phylogenetically more conserved than the known fraction and predominantly taxonomically restricted at the species level. From the 71 M genes identified to be of unknown function, we compiled a collection of 283,874 lineage-specific genes of unknown function for Cand. Patescibacteria (also known as Candidate Phyla Radiation, CPR), which provides a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.

It is estimated that scientists do not know what half of microbial genes actually do. When these genes are discovered in microorganisms grown in the lab or found in environmental samples, it is not possible to identify what their roles are. Many of these genes are excluded from further analyses for these reasons, meaning that the study of microbial genes tends to be limited to genes that have already been described.

These limitations hinder research into microbiology, because information from newly discovered genes cannot be integrated to better understand how these organisms work. Experiments to understand what role these genes have in the microorganisms are labor-intensive, so new analytical strategies are needed.

To do this, Vanni et al. developed a new framework to categorize genes with unknown roles, and a computational workflow to integrate them into traditional analyses. When this approach was applied to over 400 million microbial genes (both with known and unknown roles), it showed that the share of genes with unknown functions is only about 30 per cent, smaller than previously thought. The analysis also showed that these genes are very diverse, revealing a huge space for future research and potential applications. Combining their approach with experimental data, Vanni et al. were able to identify a gene with a previously unknown purpose that could be involved in antibiotic resistance.

This system could be useful for other scientists studying microorganisms to get a more complete view of microbial systems. In future, it may also be used to analyze the genetics of other organisms, such as plants and animals.

A breath of fresh air in microbiome science: shallow shotgun metagenomics for a reliable disentangling of microbial ecosystems

Next-generation sequencing technologies allow accomplishing massive DNA sequencing, uncovering the microbial composition of many different ecological niches. However, the various strategies developed to profile microbiomes make it challenging to retrieve a reliable classification that is able to compare metagenomic data of different studies. Many limitations have been overcome thanks to shotgun sequencing, allowing a reliable taxonomic classification of microbial communities at the species level. Since numerous bioinformatic tools and databases have been implemented, the sequencing methodology is only the first of many choices to make for classifying metagenomic data. Here, we discuss the importance of choosing a reliable methodology to achieve consistent information in uncovering microbiomes.

Construction of Aerobic/Anaerobic-Substrate-Induced Gene Expression Procedure for Exploration of Metagenomes From Subseafloor Sediments

Substrate-induced gene expression (SIGEX) is a high-throughput promoter-trap method. It is a function-based metagenomic screening tool that relies on transcriptional activation of a reporter gene green fluorescence protein (gfp) by a metagenomic DNA library upon induction with a substrate. However, its use is limited because of the relatively small size of metagenomic DNA libraries and incompatibility with screening metagenomes from anaerobic environments. In this study, these limitations of SIGEX were addressed by fine-tuning metagenome DNA library construction protocol and by using Evoglow, a green fluorescent protein that forms a chromophore even under anaerobic conditions. Two metagenomic libraries were constructed for subseafloor sediments offshore Shimokita Peninsula (Pacific Ocean) and offshore Joetsu (Japan Sea). The library construction protocol was improved by (a) eliminating short DNA fragments, (b) applying topoisomerase-based high-efficiency ligation, (c) optimizing insert DNA concentration, and (d) column-based DNA enrichment. This led to a successful construction of metagenome DNA libraries of approximately 6 Gbp for both samples. SIGEX screening using five aromatic compounds (benzoate, 3-chlorobenzoate, 3-hydroxybenzoate, phenol, and 2,4-dichlorophenol) under aerobic and anaerobic conditions revealed significant differences in the inducible clone ratios under these conditions. 3-Chlorobenzoate and 2,4-dichlorophenol led to a higher induction ratio than that for the other non-chlorinated aromatic compounds under both aerobic and anaerobic conditions. After the further screening of induced clones, a clone induced by 3-chlorobenzoate only under anaerobic conditions was isolated and characterized. The clone harbors a DNA insert that encodes putative open reading frames of unknown function. Previous aerobic SIGEX attempts succeeded in the isolation of gene fragments from anaerobes. This study demonstrated that some gene fragments require a strict in vivo reducing environment to function and may be potentially missed when screened by aerobic induction. The newly developed anaerobic SIGEX scheme will facilitate functional exploration of metagenomes from the anaerobic biosphere.

FI: The Fecobiome Initiative

Animal husbandry has been key to the sustainability of human societies for millennia. Livestock animals, such as cattle, convert plants to protein biomass due to a compartmentalized gastrointestinal tract (GIT) and the complementary contributions of a diverse GIT microbiota, thereby providing humans with meat and dairy products. Research on cattle gut microbial symbionts has mainly focused on the rumen (which is the primary fermentation compartment) and there is a paucity of functional insight on the intestinal (distal end) microbiota, where most foodborne zoonotic bacteria reside. Here, we present the Fecobiome Initiative (or FI), an international effort that aims at facilitating collaboration on research projects related to the intestinal microbiota, disseminating research results, and increasing public availability of resources. By doing so, the FI can help mitigate foodborne and animal pathogens that threaten livestock and human health, reduce the emergence and spread of antimicrobial resistance in cattle and their proximate environment, and potentially improve the welfare and nutrition of animals. We invite all researchers interested in this type of research to join the FI through our website: www.fecobiome.com

The Dark mAtteR iNvestigator (DARN) tool: getting to know the known unknowns in COI amplicon data

The mitochondrial cytochrome C oxidase subunit I gene (COI) is commonly used in environmental DNA (eDNA) metabarcoding studies, especially for assessing metazoan diversity. Yet, a great number of COI operational taxonomic units (OTUs) or/and amplicon sequence variants (ASVs) retrieved from such studies do not get a taxonomic assignment with a reference sequence. To assess and investigate such sequences, we have developed the Dark mAtteR iNvestigator (DARN) software tool. For this purpose, a reference COI-oriented phylogenetic tree was built from 1,593 consensus sequences covering all the three domains of life. With respect to eukaryotes, consensus sequences at the family level were constructed from 183,330 sequences retrieved from the Midori reference 2 database, which represented 70% of the initial number of reference sequences. Similarly, sequences from 431 bacterial and 15 archaeal taxa at the family level (29% and 1% of the initial number of reference sequences respectively) were retrieved from the BOLD and the PFam databases. DARN makes use of this phylogenetic tree to investigate COI pre-processed sequences of amplicon samples to provide both a tabular and a graphical overview of their phylogenetic assignments. To evaluate DARN, both environmental and bulk metabarcoding samples from different aquatic environments using various primer sets were analysed. We demonstrate that a large proportion of non-target prokaryotic organisms, such as bacteria and archaea, are also amplified in eDNA samples and we suggest prokaryotic COI sequences to be included in the reference databases used for the taxonomy assignment to allow for further analyses of dark matter. DARN source code is available on GitHub at https://github.com/hariszaf/darn and as a Docker image at https://hub.docker.com/r/hariszaf/darn.

Phenogenomic Characterization of a Newly Domesticated and Novel Species from the Genus Verrucosispora

The concept of bacterial dark matter stems from our inability to culture most microbes and represents a fundamental gap in our knowledge of microbial diversity. Here, we present the domestication of such an organism: a previously uncultured, novel species from the rare Actinomycetes genus Verrucosispora. Although initial recovery took >4 months, isolation of phenotypically distinct, domesticated generations occurred within weeks. Two isolates were subjected to phenogenomic analyses, revealing domestication correlated with enhanced growth rates in nutrient-rich media but diminished capacity to metabolize diverse amino acids. This is seemingly mediated by genomic atrophy through a mixed approach of pseudogenization and reversion of pseudogenization of amino acid metabolism genes. Conversely, later generational strains had enhanced spore germination rates, potentially through the reversion of a sporulation-associated kinase from pseudogene to true gene status. We observed that our most wild-type isolate had the greatest potential for antibacterial activity, which correlated with extensive mutational attrition of biosynthetic gene clusters in domesticated strains. Comparative analyses revealed wholesale genomic reordering in strains, with widespread single nucleotide polymorphism, indel, and pseudogene-impactful mutations observed. We hypothesize that domestication of this previously unculturable organism resulted from the shedding of genomic flexibility required for life in a dynamic marine environment, parsing out genetic redundancy to allow for a newfound cultivable amenability. IMPORTANCE The majority of environmental bacteria cannot be cultured within the laboratory. Understanding why only certain environmental isolates can be recovered is key to unlocking the abundant microbial dark matter that is widespread on our planet. In this study, we present not only the culturing but domestication of just such an organism. Although initial recovery took >4 months, we were able to isolate distinct, subpassaged offspring from the originating colony within mere weeks. A phenotypic and genotypic analysis of our generational strains revealed that adaptation to life in the lab occurred as a result of wholesale mutational changes. These permitted an enhanced ability for growth in nutrient rich media but came at the expense of reduced genomic flexibility. We suggest that without dynamic natural environmental stressors our domesticated strains effectively underwent genomic atrophy as they adapted to static conditions experienced in the laboratory.

Functional Characterisation of Bile Metagenome: Study of Metagenomic Dark Matter

Gallbladder metagenome involves a wide range of unidentified sequences comprising the so-called metagenomic dark matter. Therefore, this study aimed to characterise three gallbladder metagenomes and a fosmid library with an emphasis on metagenomic dark matter fraction. For this purpose, a novel data analysis strategy based on the combination of remote homology and molecular modelling has been proposed. According to the results obtained, several protein functional domains were annotated in the metagenomic dark matter fraction including acetyltransferases, outer membrane transporter proteins, membrane assembly factors, DNA repair and recombination proteins and response regulator phosphatases. In addition, one deacetylase involved in mycothiol biosynthesis was found in the metagenomic dark matter fraction of the fosmid library. This enzyme may exert a protective effect in Actinobacteria against bile components exposure, in agreement with the presence of multiple antibiotic and multidrug resistance genes. Potential mechanisms of action of this novel deacetylase were elucidated by molecular simulations, highlighting the role of histidine and aspartic acid residues. Computational pipelines presented in this work may be of special interest to discover novel microbial enzymes which had not been previously characterised.

Contribution of single-cell omics to microbial ecology

Micro-organisms play key roles in various ecosystems, but many of their functions and interactions remain undefined. To investigate the ecological relevance of microbial communities, new molecular tools are being developed. Among them, single-cell omics assessing genetic diversity at the population and community levels and linking each individual cell to its functions is gaining interest in microbial ecology. By giving access to a wider range of ecological scales (from individual to community) than culture-based approaches and meta-omics, single-cell omics can contribute not only to micro-organisms' genomic and functional identification but also to the testing of concepts in ecology. Here, we discuss the contribution of single-cell omics to possible breakthroughs in concepts and knowledge on microbial ecosystems and ecoevolutionary processes.

Abundance and Compositions of B-Vitamin-Producing Microbes in the Mammalian Gut Vary Based on Feeding Strategies

Mammals maintain close associations with gut microbes that provide numerous nutritional benefits, including vitamin synthesis. While most mammals obtain sufficient vitamins from their diets, deficiencies in various B vitamins (biotin, cobalamin, riboflavin, thiamine, etc.) are reported in captive animals. Biomedical and agricultural research has shown that gut microbes are capable of synthesizing B vitamins and assisting with host vitamin homeostasis. However, we have a poor understanding of distribution and abundance of B-vitamin synthesis across mammalian hosts. Here, we leveraged a publicly available metagenomic data set from 39 mammalian species and used MG-RAST to compare the abundance and composition of B-vitamin-synthesizing microbes across mammalian feeding strategies. We predicted that herbivores would have the highest abundance of genes associated with vitamin synthesis, as plant material is often low in B vitamins. However, this hypothesis was not supported. Instead, we found that relative abundances of genes associated with cobalamin and thiamine synthesis were significantly enriched in carnivorous mammals. The taxonomic community structure of microbes predicted to be involved in B-vitamin synthesis also varied significantly based on host feeding strategy. For example, the genus Acinetobacter primarily contributed to predicted biotin synthesis in carnivores but was not predicted to contribute to biotin synthesis in herbivores or omnivores. Given that B vitamins cannot be stored within the body, we hypothesize that microbial synthesis of B vitamins could be important for wild carnivores that regularly experience periods of fasting. Overall, these results shed light on the distribution and abundance of microbial B-vitamin synthesis across mammalian groups, with potential implications for captive animals. IMPORTANCE Microbial communities offer numerous physiological services to their hosts, but we still have a poor understanding of how these functions are structured across mammalian species. Specifically, our understanding of processes of vitamin synthesis across animals is severely limited. Here, we compared the abundance of genes associated with the synthesis of B vitamins and the taxonomic composition of the microbes containing these genes. We found that herbivores, omnivores, and carnivores harbor distinct communities of microbes that putatively conduct vitamin synthesis. Additionally, carnivores exhibited the highest abundance of genes associated with synthesis of specific B vitamins, cobalamin and thiamine. These data uncover the potential importance of microbes in the vitamin homeostasis of various mammals, especially carnivorous mammals. These findings have implications for understanding the microbial interactions that contribute to the nutritional requirements of animals held in captivity.

Towards omics-based predictions of planktonic functional composition from environmental data

Marine microbes play a crucial role in climate regulation, biogeochemical cycles, and trophic networks. Unprecedented amounts of data on planktonic communities were recently collected, sparking a need for innovative data-driven methodologies to quantify and predict their ecosystemic functions. We reanalyze 885 marine metagenome-assembled genomes through a network-based approach and detect 233,756 protein functional clusters, from which 15% are functionally unannotated. We investigate all clusters' distributions across the global ocean through machine learning, identifying biogeographical provinces as the best predictors of protein functional clusters' abundance. The abundances of 14,585 clusters are predictable from the environmental context, including 1347 functionally unannotated clusters. We analyze the biogeography of these 14,585 clusters, identifying the Mediterranean Sea as an outlier in terms of protein functional clusters composition. Applicable to any set of sequences, our approach constitutes a step towards quantitative predictions of functional composition from the environmental context.

Anna Karenina and the subgingival microbiome associated with periodontitis

BACKGROUND

Although localized aggressive periodontitis (LAP), generalized aggressive periodontitis (GAP), and chronic periodontitis (CP) are microbially driven diseases, our inability to separate disease-specific associations from those common to all three forms of periodontitis has hampered biomarker discovery. Therefore, we aimed to map the genomic content of, and the biological pathways encoded by, the microbiomes associated with these clinical phenotypes. We also estimated the extent to which these biomes are governed by the Anna Karenina principle (AKP), which states that eubiotic communities are similar between individuals while disease-associated communities are highly individualized.

METHODS

We collected subgingival plaque from 25 periodontally healthy individuals and diseased sites of 59 subjects with stage 3 periodontitis and used shotgun metagenomics to characterize the aggregate of bacterial genes.

RESULTS

Beta-dispersion metrics demonstrated that AKP was most evident in CP, followed by GAP and LAP. We discovered broad dysbiotic signatures spanning the three phenotypes, with over-representation of pathways that facilitate life in an oxygen-poor, protein- and heme-rich, pro-oxidant environment and enhance capacity for attachment and biofilm formation. Phenotype-specific indicators were more readily evident in LAP microbiome than GAP or CP. Genes that enable acetate-scavenging lifestyle, utilization of alternative nutritional sources, oxidative and nitrosative stress responses, and siderophore production were unique to LAP. An attenuation of virulence-related functionalities and stress response from LAP to GAP to CP was apparent. We also discovered that clinical phenotypes of disease resolved variance in the microbiome with greater clarity than the newly established grading system. Importantly, we observed that one third of the metagenome of LAP is unique to this phenotype while GAP shares significant functional and taxonomic features with both LAP and CP, suggesting either attenuation of an aggressive disease or an early-onset chronic disease.

CONCLUSION

Within the limitations of a small sample size and a cross-sectional study design, the distinctive features of the microbiomes associated with LAP and CP strongly persuade us that these are discrete disease entities, while calling into question whether GAP is a separate disease, or an artifact induced by cross-sectional study designs. Further studies on phenotype-specific microbial genes are warranted to explicate their role in disease etiology. Video Abstract.

Microbiome-immune interactions in tuberculosis

Tuberculosis (TB) remains an infectious disease of global significance and a leading cause of death in low- and middle-income countries. Significant effort has been directed towards understanding Mycobacterium tuberculosis genomics, virulence, and pathophysiology within the framework of Koch postulates. More recently, the advent of “-omics” approaches has broadened our appreciation of how “commensal” microbes have coevolved with their host and have a central role in shaping health and susceptibility to disease. It is now clear that there is a diverse repertoire of interactions between the microbiota and host immune responses that can either sustain or disrupt homeostasis. In the context of the global efforts to combatting TB, such findings and knowledge have raised important questions: Does microbiome composition indicate or determine susceptibility or resistance to M. tuberculosis infection? Is the development of active disease or latent infection upon M. tuberculosis exposure influenced by the microbiome? Does microbiome composition influence TB therapy outcome and risk of reinfection with M. tuberculosis? Can the microbiome be actively managed to reduce risk of M. tuberculosis infection or recurrence of TB? Here, we explore these questions with a particular focus on microbiome-immune interactions that may affect TB susceptibility, manifestation and progression, the long-term implications of anti-TB therapy, as well as the potential of the host microbiome as target for clinical manipulation.

Polyhydroxyalkanoates from extremophiles: A review

Polyhydroxyalkanoates (PHAs) are group monomers/heteropolymers that are biodegradable and widely used in biomedical applications. They are considered as alternatives to fossil derived polymers and accumulated by microbes including extremophilic archaea as energy storage inclusions under nutrient limitations. The use of extremophilic archaea for PHA production is an economically viable option for conventional aerobic processes, but less is known about their pathways and PHA accumulation capacities. This review summarized: (a) specific adaptive mechanisms towards extreme environments by extremophiles and specific role of PHAs; (b) understanding of PHA synthesis/metabolism in archaea and specific functional genes; (c) genetic engineering and process engineering approaches required for high-rate PHA production using extremophilic archaea. To conclude, the future studies are suggested to understand the membrane lipids and PHAs accumulation to explain the adaptation mechanism of extremophiles and exploiting it for commercial production of PHAs.

Information Theoretic Metagenome Assembly Allows the Discovery of Disease Biomarkers in Human Microbiome

Quantitative metagenomics is an important field that has delivered successful microbiome biomarkers associated with host phenotypes. The current convention mainly depends on unsupervised assembly of metagenomic contigs with a possibility of leaving interesting genetic material unassembled. Additionally, biomarkers are commonly defined on the differential relative abundance of compositional or functional units. Accumulating evidence supports that microbial genetic variations are as important as the differential abundance content, implying the need for novel methods accounting for the genetic variations in metagenomics studies. We propose an information theoretic metagenome assembly algorithm, discovering genomic fragments with maximal self-information, defined by the empirical distributions of nucleotides across the phenotypes and quantified with the help of statistical tests. Our algorithm infers fragments populating the most informative genetic variants in a single contig, named supervariant fragments. Experiments on simulated metagenomes, as well as on a colorectal cancer and an atherosclerotic cardiovascular disease dataset consistently discovered sequences strongly associated with the disease phenotypes. Moreover, the discriminatory power of these putative biomarkers was mainly attributed to the genetic variations rather than relative abundance. Our results support that a focus on metagenomics methods considering microbiome population genetics might be useful in discovering disease biomarkers with a great potential of translating to molecular diagnostics and biotherapeutics applications.

High Culturable Bacterial Diversity From a European Desert: The Tabernas Desert

One of the most diverse ecological niches for microbial bioprospecting is soil, including that of drylands. Drylands are one of the most abundant biomes on Earth, but extreme cases, such as deserts, are considered very rare in Europe. The so-called Tabernas Desert is one of the few examples of a desert area in continental Europe, and although some microbial studies have been performed on this region, a comprehensive strategy to maximize the isolation of environmental bacteria has not been conducted to date. We report here a culturomics approach to study the bacterial diversity of this dryland by using a simple strategy consisting of combining different media, using serial dilutions of the nutrients, and using extended incubation times. With this strategy, we were able to set a large (254 strains) collection of bacteria, the majority of which (93%) were identified through 16S ribosomal RNA (rRNA) gene amplification and sequencing. A significant fraction of the collection consisted of Actinobacteria and Proteobacteria, as well as Firmicutes strains. Among the 254 isolates, 37 different genera were represented, and a high number of possible new taxa were identified (31%), of which, three new Kineococcus species. Moreover, 5 out of the 13 genera represented by one isolate were also possible new species. Specifically, the sequences of 80 isolates held a percentage of identity below the 98.7% threshold considered for potentially new species. These strains belonged to 20 genera. Our results reveal a clear link between medium dilution and isolation of new species, highlight the unexploited bacterial biodiversity of the Tabernas Desert, and evidence the potential of simple strategies to yield surprisingly large numbers of diverse, previously unreported, bacterial strains and species.

Macrel: antimicrobial peptide screening in genomes and metagenomes

Motivation

Antimicrobial peptides (AMPs) have the potential to tackle multidrug-resistant pathogens in both clinical and non-clinical contexts. The recent growth in the availability of genomes and metagenomes provides an opportunity for in silico prediction of novel AMP molecules. However, due to the small size of these peptides, standard gene prospection methods cannot be applied in this domain and alternative approaches are necessary. In particular, standard gene prediction methods have low precision for short peptides, and functional classification by homology results in low recall.

Results

Here, we present Macrel (for metagenomic AMP classification and retrieval), which is an end-to-end pipeline for the prospection of high-quality AMP candidates from (meta)genomes. For this, we introduce a novel set of 22 peptide features. These were used to build classifiers which perform similarly to the state-of-the-art in the prediction of both antimicrobial and hemolytic activity of peptides, but with enhanced precision (using standard benchmarks as well as a stricter testing regime). We demonstrate that Macrel recovers high-quality AMP candidates using realistic simulations and real data.

Availability

Macrel is implemented in Python 3. It is available as open source at https://github.com/BigDataBiology/macrel and through bioconda. Classification of peptides or prediction of AMPs in contigs can also be performed on the webserver: https://big-data-biology.org/software/macrel.

Anomalous Phylogenetic Behavior of Ribosomal Proteins in Metagenome-Assembled Asgard Archaea

Metagenomic studies permit the exploration of microbial diversity in a defined habitat, and binning procedures enable phylogenomic analyses, taxon description, and even phenotypic characterizations in the absence of morphological evidence. Such lineages include asgard archaea, which were initially reported to represent archaea with eukaryotic cell complexity, although the first images of such an archaeon show simple cells with prokaryotic characteristics. However, these metagenome-assembled genomes (MAGs) might suffer from data quality problems not encountered in sequences from cultured organisms due to two common analytical procedures of bioinformatics: assembly of metagenomic sequences and binning of assembled sequences on the basis of innate sequence properties and abundance across samples. Consequently, genomic sequences of distantly related taxa, or domains, can in principle be assigned to the same MAG and result in chimeric sequences. The impacts of low-quality or chimeric MAGs on phylogenomic and metabolic prediction remain unknown. Debates that asgard archaeal data are contaminated with eukaryotic sequences are overshadowed by the lack of evidence indicating that individual asgard MAGs stem from the same chromosome. Here, we show that universal proteins including ribosomal proteins of asgard archaeal MAGs fail to meet the basic phylogenetic criterion fulfilled by genome sequences of cultured archaea investigated to date: These proteins do not share common evolutionary histories to the same extent as pure culture genomes do, pointing to a chimeric nature of asgard archaeal MAGs. Our analysis suggests that some asgard archaeal MAGs represent unnatural constructs, genome-like patchworks of genes resulting from assembly and/or the binning process.

Microfluidics for Biotechnology: Bridging Gaps to Foster Microfluidic Applications

Microfluidics and novel lab-on-a-chip applications have the potential to boost biotechnological research in ways that are not possible using traditional methods. Although microfluidic tools were increasingly used for different applications within biotechnology in recent years, a systematic and routine use in academic and industrial labs is still not established. For many years, absent innovative, ground-breaking and “out-of-the-box” applications have been made responsible for the missing drive to integrate microfluidic technologies into fundamental and applied biotechnological research. In this review, we highlight microfluidics’ offers and compare them to the most important demands of the biotechnologists. Furthermore, a detailed analysis in the state-of-the-art use of microfluidics within biotechnology was conducted exemplarily for four emerging biotechnological fields that can substantially benefit from the application of microfluidic systems, namely the phenotypic screening of cells, the analysis of microbial population heterogeneity, organ-on-a-chip approaches and the characterisation of synthetic co-cultures. The analysis resulted in a discussion of potential “gaps” that can be responsible for the rare integration of microfluidics into biotechnological studies. Our analysis revealed six major gaps, concerning the lack of interdisciplinary communication, mutual knowledge and motivation, methodological compatibility, technological readiness and missing commercialisation, which need to be bridged in the future. We conclude that connecting microfluidics and biotechnology is not an impossible challenge and made seven suggestions to bridge the gaps between those disciplines. This lays the foundation for routine integration of microfluidic systems into biotechnology research procedures.

Proteotyping Environmental Microorganisms by Phylopeptidomics: Case Study Screening Water from a Radioactive Material Storage Pool

The microbial diversity encompassed by the environmental biosphere is largely unexplored, although it represents an extensive source of new knowledge and potentially of novel enzymatic catalysts for biotechnological applications. To determine the taxonomy of microorganisms, proteotyping by tandem mass spectrometry has proved its efficiency. Its latest extension, phylopeptidomics, adds a biomass quantitation perspective for mixtures of microorganisms. Here, we present an application of phylopeptidomics to rapidly and sensitively screen microorganisms sampled from an industrial environment, i.e., a pool where radioactive material is stored. The power of this methodology is demonstrated through the identification of both prokaryotes and eukaryotes, whether as pure isolates or present as mixtures or consortia. In this study, we established accurate taxonomical identification of environmental prokaryotes belonging to the Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria phyla, as well as eukaryotes from the Ascomycota phylum. The results presented illustrate the potential of tandem mass spectrometry proteotyping, in particular phylopeptidomics, to screen for and rapidly identify microorganisms.

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

Microbes compose most of the biomass on the planet, yet the majority of taxa remain uncharacterized. These unknown microbes, often referred to as “microbial dark matter,” represent a major challenge for biology. To understand the ecological contributions of these Unknown taxa, it is essential to first understand the relationship between unknown species, neighboring microbes, and their respective environment. Here, we establish a method to study the ecological significance of “microbial dark matter” by building microbial co-occurrence networks from publicly available 16S rRNA gene sequencing data of four extreme aquatic habitats. For each environment, we constructed networks including and excluding unknown organisms at multiple taxonomic levels and used network centrality measures to quantitatively compare networks. When the Unknown taxa were excluded from the networks, a significant reduction in degree and betweenness was observed for all environments. Strikingly, Unknown taxa occurred as top hubs in all environments, suggesting that “microbial dark matter” play necessary ecological roles within their respective communities. In addition, novel adaptation-related genes were detected after using 16S rRNA gene sequences from top-scoring hub taxa as probes to blast metagenome databases. This work demonstrates the broad applicability of network metrics to identify and prioritize key Unknown taxa and improve understanding of ecosystem structure across diverse habitats.

Microbial dark matter filling the niche in hypersaline microbial mats

BACKGROUND

Shark Bay, Australia, harbours one of the most extensive and diverse systems of living microbial mats that are proposed to be analogs of some of the earliest ecosystems on Earth. These ecosystems have been shown to possess a substantial abundance of uncultivable microorganisms. These enigmatic microbes, jointly coined as 'microbial dark matter' (MDM), are hypothesised to play key roles in modern microbial mats.

RESULTS

We reconstructed 115 metagenome-assembled genomes (MAGs) affiliated to MDM, spanning 42 phyla. This study reports for the first time novel microorganisms (Zixibacterial order GN15) putatively taking part in dissimilatory sulfate reduction in surface hypersaline settings, as well as novel eukaryote signature proteins in the Asgard archaea. Despite possessing reduced-size genomes, the MDM MAGs are capable of fermenting and degrading organic carbon, suggesting a role in recycling organic carbon. Several forms of RuBisCo were identified, allowing putative CO₂ incorporation into nucleotide salvaging pathways, which may act as an alternative carbon and phosphorus source. High capacity of hydrogen production was found among Shark Bay MDM. Putative schizorhodopsins were also identified in Parcubacteria, Asgard archaea, DPANN archaea, and Bathyarchaeota, allowing these members to potentially capture light energy. Diversity-generating retroelements were prominent in DPANN archaea that likely facilitate the adaptation to a dynamic, host-dependent lifestyle.

CONCLUSIONS

This is the first study to reconstruct and describe in detail metagenome-assembled genomes (MAGs) affiliated with microbial dark matter in hypersaline microbial mats. Our data suggests that these microbial groups are major players in these systems. In light of our findings, we propose H₂, ribose and CO/CO₂ as the main energy currencies of the MDM community in these mat systems. Video Abstract.

Discovery of an Abundance of Biosynthetic Gene Clusters in Shark Bay Microbial Mats

Microbial mats are geobiological multilayered ecosystems that have significant evolutionary value in understanding the evolution of early life on Earth. Shark Bay, Australia has some of the best examples of modern microbial mats thriving under harsh conditions of high temperatures, salinity, desiccation, and ultraviolet (UV) radiation. Microorganisms living in extreme ecosystems are thought to potentially encode for secondary metabolites as a survival strategy. Many secondary metabolites are natural products encoded by a grouping of genes known as biosynthetic gene clusters (BGCs). Natural products have diverse chemical structures and functions which provide competitive advantages for microorganisms and can also have biotechnology applications. In the present study, the diversity of BGC were described in detail for the first time from Shark Bay microbial mats. A total of 1477 BGCs were detected in metagenomic data over a 20 mm mat depth horizon, with the surface layer possessing over 200 BGCs and containing the highest relative abundance of BGCs of all mat layers. Terpene and bacteriocin BGCs were highly represented and their natural products are proposed to have important roles in ecosystem function in these mat systems. Interestingly, potentially novel BGCs were detected from Heimdallarchaeota and Lokiarchaeota, two evolutionarily significant archaeal phyla not previously known to possess BGCs. This study provides new insights into how secondary metabolites from BGCs may enable diverse microbial mat communities to adapt to extreme environments.

The origin and evolution of viruses inferred from fold family structure

The canonical frameworks of viral evolution describe viruses as cellular predecessors, reduced forms of cells, or entities that escaped cellular control. The discovery of giant viruses has changed these standard paradigms. Their genetic, proteomic and structural complexities resemble those of cells, prompting a redefinition and reclassification of viruses. In a previous genome-wide analysis of the evolution of structural domains in proteomes, with domains defined at the fold superfamily level, we found the origins of viruses intertwined with those of ancient cells. Here, we extend these data-driven analyses to the study of fold families confirming the co-evolution of viruses and ancient cells and the genetic ability of viruses to foster molecular innovation. The results support our suggestion that viruses arose by genomic reduction from ancient cells and validate a co-evolutionary ‘symbiogenic’ model of viral origins.

Bacterial communities associated with cell phones and shoes

Background

Every human being carries with them a collection of microbes, a collection that is likely both unique to that person, but also dynamic as a result of significant flux with the surrounding environment. The interaction of the human microbiome (i.e., the microbes that are found directly in contact with a person in places such as the gut, mouth, and skin) and the microbiome of accessory objects (e.g., shoes, clothing, phones, jewelry) is of potential interest to both epidemiology and the developing field of microbial forensics. Therefore, the microbiome of personal accessories are of interest because they serve as both a microbial source and sink for an individual, they may provide information about the microbial exposure experienced by an individual, and they can be sampled non-invasively.

Findings

We report here a large-scale study of the microbiome found on cell phones and shoes. Cell phones serve as a potential source and sink for skin and oral microbiome, while shoes can act as sampling devices for microbial environmental experience. Using 16S rRNA gene sequencing, we characterized the microbiome of thousands of paired sets of cell phones and shoes from individuals at sporting events, museums, and other venues around the United States.

Conclusions

We place this data in the context of previous studies and demonstrate that the microbiome of phones and shoes are different. This difference is driven largely by the presence of “environmental” taxa (taxa from groups that tend to be found in places like soil) on shoes and human-associated taxa (taxa from groups that are abundant in the human microbiome) on phones. This large dataset also contains many novel taxa, highlighting the fact that much of microbial diversity remains uncharacterized, even on commonplace objects.

Tools for Analysis of the Microbiome

Over the past decade, it has become exceedingly clear that the microbiome is a critical factor in human health and disease and thus should be investigated to develop innovative treatment strategies. The field of metagenomics has come a long way in leveraging the advances of next-generation sequencing technologies resulting in the capability to identify and quantify all microorganisms present in human specimens. However, the field of metagenomics is still in its infancy, specifically in regard to the limitations in computational analysis, statistical assessments, standardization, and validation due to vast variability in the cohorts themselves, experimental design, and bioinformatic workflows. This review summarizes the methods, technologies, computational tools, and model systems for characterizing and studying the microbiome. We also discuss important considerations investigators must make when interrogating the involvement of the microbiome in health and disease in order to establish robust results and mechanistic insights before moving into therapeutic design and intervention.

A critical analysis of state-of-the-art metagenomics OTU clustering algorithms

Taxonomic profiling, using hyper-variable regions of 16S rRNA, is one of the important goals in metagenomics analysis. Operational taxonomic unit (OTU) clustering algorithms are the important tools to perform taxonomic profiling by grouping 16S rRNA sequence reads into OTU clusters. Presently various OTU clustering algorithms are available within different pipelines, even some pipelines have implemented more than one clustering algorithms, but there is less literature available for the relative performance and features of these algorithms. This makes the choice of using these methods unclear. In this study five current state-of-the-art OTU clustering algorithms (CDHIT, Mothur's Average Neighbour, SUMACLUST, Swarm, and UCLUST) have been comprehensively evaluated on the metagenomics sequencing data. It was found that in all the datasets, Mothur's average neighbour and Swarm created more number of OTU clusters. Based on normalized mutual information (NMI) and normalized information difference (NID), Swarm and Mothur's average neighbour showed better clustering qualities than others. But in terms of time complexity the greedy algorithms (SUMACLUST, CDHIT, and UCLUST) performed well. So there is a trade-off between quality and time, and it is necessary while analysing large size of 16S rRNA gene sequencing data.

Exploration of activated sludge resistome using metagenomics

Antibiotic resistance is a global problem. In India poor waste management and inadequate sanitary are key factors which encourage the dissemination of antimicrobial resistance. Microbial biodiversity serves as an invaluable source for diverse types of bioactive compounds that encompass most of the pharmaceuticals to date. Therefore, in this study, we used the metagenomic approach for the surveillance of antibiotic resistance genes, drug resistant microbes and mobile-genetic elements in two activated sludge metagenome samples collected from Ankleshwar, Gujarat, India. Proteobacteria were found to be the most abundant bacteria among the metagenome analyzed. Twenty-four genes conferring resistance to antibiotics and heavy metals were found. Multidrug resistant "ESKAPE pathogens" were also abundant in the sludge metagenome. Mobile genetic elements like IncP-1 plasmid pKJK5, IncP-1beta multi resistance plasmid and pB8 were also noticed in the higher abundance. These plasmids play an important role in the spread of antibiotic resistance by the horizontal gene transfer. Statistical analysis of both metagenome using STAMP software confirmed presence of mobile genetic elements such as gene transfer agents, phages, Prophages etc. which also play important role in the dissemination of antibiotic resistant genes.