Printing Microbial Dark Matter: Using Single Cell Dispensing and Genomics to Investigate the Patescibacteria/Candidate Phyla Radiation

First shotgun metagenomics study of Juan de Fuca deep-sea sediments reveals distinct microbial communities above, within, between, and below sulfate methane transition zones

The marine deep subsurface is home to a vast microbial ecosystem, affecting biogeochemical cycles on a global scale. One of the better-studied deep biospheres is the Juan de Fuca (JdF) Ridge, where hydrothermal fluid introduces oxidants into the sediment from below, resulting in two sulfate methane transition zones (SMTZs). In this study, we present the first shotgun metagenomics study of unamplified DNA from sediment samples from different depths in this stratified environment. Bioinformatic analyses showed a shift from a heterotrophic, Chloroflexota-dominated community above the upper SMTZ to a chemolithoautotrophic Proteobacteria-dominated community below the secondary SMTZ. The reintroduction of sulfate likely enables respiration and boosts active cells that oxidize acetate, iron, and complex carbohydrates to degrade dead biomass in this low-abundance, low-diversity environment. In addition, analyses showed many proteins of unknown function as well as novel metagenome-assembled genomes (MAGs). The study provides new insights into microbial communities in this habitat, enabled by an improved DNA extraction protocol that allows a less biased view of taxonomic composition and metabolic activities, as well as uncovering novel taxa. Our approach presents the first successful attempt at unamplified shotgun sequencing samples from beyond 50 meters below the seafloor and opens new ways for capturing the true diversity and functional potential of deep-sea sediments.

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.

Taxonomic Re-Classification and Expansion of the Phylum Chloroflexota Based on over 5000 Genomes and Metagenome-Assembled Genomes

The phylum Chloroflexota (formerly Chloroflexi) encompasses metabolically diverse bacteria that often have high prevalence in terrestrial and aquatic habitats, some even with biotechnological application. However, there is substantial disagreement in public databases which lineage should be considered a member of the phylum and at what taxonomic level. Here, we addressed these issues through extensive phylogenomic analyses. The analyses were based on a collection of >5000 Chloroflexota genomes and metagenome-assembled genomes (MAGs) from public databases, novel environmental sites, as well as newly generated MAGs from publicly available sequence reads via an improved binning approach incorporating covariance information. Based on calculated relative evolutionary divergence, we propose that Candidatus Dormibacterota should be listed as a class (i.e., Ca. Dormibacteria) within Chloroflexota together with the classes Anaerolineae, Chloroflexia, Dehalococcoidia, Ktedonobacteria, Ca. Limnocylindria, Thermomicrobia, and two other classes containing only uncultured members. All other Chloroflexota lineages previously listed at the class rank appear to be rather orders or families in the Anaerolineae and Dehalococcoidia, which contain the vast majority of genomes and exhibited the strongest phylogenetic radiation within the phylum. Furthermore, the study suggests that a common ecophysiological capability of members of the phylum is to successfully cope with low energy fluxes.

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.

Using Genomics to Decipher the Enigmatic Properties and Survival Adaptation of Candidate Phyla Radiation

Microbial ecology is a critical field for understanding the composition, diversity, and functions of microorganisms in various environmental and health-related processes. The discovery of Candidate Phyla Radiation (CPR) through culture-independent methods has introduced a new division of microbes characterized by a symbiotic/parasitic lifestyle, small cell size, and small genome. Despite being poorly understood, CPRs have garnered significant attention in recent years due to their widespread detection in a variety of environmental and clinical samples. These microorganisms have been found to exhibit a high degree of genetic diversity compared to other microbes. Several studies have shed light on their potential importance in global biogeochemical cycles and their impact on various human activities. In this review, we provide a systematic overview of the discovery of CPRs. We then focus on describing how the genomic characteristics of CPRs have helped them interact with and adapt to other microbes in different ecological niches. Future works should focus on discovering the metabolic capacities of CPRs and, if possible, isolating them to obtain a better understanding of these microorganisms.

Recent progress in high-throughput droplet screening and sorting for bioanalysis

Owing to its ability to isolate single cells and perform high-throughput sorting, droplet sorting has been widely applied in several research fields. Compared with flow cytometry, droplet allows the encapsulation of single cells for cell secretion or lysate analysis. With the rapid development of this technology in the past decade, various droplet sorting devices with high throughput and accuracy have been developed. A droplet sorter with the highest sorting throughput of 30,000 droplets per second was developed in 2015. Since then, increased attention has been paid to expanding the possibilities of droplet sorting technology and strengthening its advantages over flow cytometry. This review aimed to summarize the recent progress in droplet sorting technology from the perspectives of device design, detection signal, actuating force, and applications. Technical details for improving droplet sorting through various approaches are introduced and discussed. Finally, we discuss the current limitations of droplet sorting for single-cell studies along with the existing gap between the laboratory and industry and provide our insights for future development of droplet sorters.

Macroporous Silicone Chips for Decoding Microbial Dark Matter in Environmental Microbiomes

Natural evolution has produced an almost infinite variety of microorganisms that can colonize almost any conceivable habitat. Since the vast majority of these microbial consortia are still unknown, there is a great need to elucidate this "microbial dark matter" (MDM) to enable exploitation in biotechnology. We report the fabrication and application of a novel device that integrates a matrix of macroporous elastomeric silicone foam (MESIF) into an easily fabricated and scalable chip design that can be used for decoding MDM in environmental microbiomes. Technical validation, performed with the model organism Escherichia coli expressing a fluorescent protein, showed that this low-cost, bioinert, and widely modifiable chip is rapidly colonized by microorganisms. The biological potential of the chip was then illustrated through targeted sampling and enrichment of microbiomes in a variety of habitats ranging from wet, turbulent moving bed biofilters and wastewater treatment plants to dry air-based environments. Sequencing analyses consistently showed that MESIF chips are not only suitable for sampling with high robustness but also that the material can be used to detect a broad cross section of microorganisms present in the habitat in a short time span of a few days. For example, results from the biofilter habitat showed efficient enrichment of microorganisms belonging to the enigmatic Candidate Phyla Radiation, which comprise ∼70% of the MDM. From dry air, the MESIF chip was able to enrich a variety of members of Actinobacteriota, which is known to produce specific secondary metabolites. Targeted sampling from a wastewater treatment plant where the herbicide glyphosate was added to the chip's reservoir resulted in enrichment of Cyanobacteria and Desulfobacteria, previously associated with glyphosate degradation. These initial case studies suggest that this chip is very well suited for the systematic study of MDM and opens opportunities for the cultivation of previously unculturable microorganisms.

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.

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’.

Anaerobic single-cell dispensing facilitates the cultivation of human gut bacteria

Cultivation via classical agar plate (CAP) approaches is widely used to study microbial communities, but they are time-consuming. An alternative approach is the application of single-cell dispensing (SCD), which allows high-throughput, label-free sorting of microscopic particles. We aimed to develop a new anaerobic SCD workflow to cultivate human gut bacteria and compared it with CAP using faecal communities on three rich culture media. We found that the SCD approach significantly decreased the experimental time to obtain pure cultures from 17 ± 4 to 5 ± 0 days, while the isolate diversity and relative abundance coverage were comparable for both approaches. We further tested the total captured fraction by sequencing the sorted bacteria directly after growth as bulk biomass from 2400 dispensed single cells without downstream identification of individual strains. In this approach, the cultured fraction increased from 35.2% to 52.2% for SCD, highlighting the potential for deeper cultivation projects from single samples. SCD-based cultivation also captured species not detected by sequencing (16 ± 5 per sample, including seven novel taxa). From this work, 82 human gut bacterial species across five phyla (Actinobacteriota, Bacteroidota, Desulfobacterota, Firmicutes and Proteobacteria) and 24 families were obtained, including the first cultured member of 11 novel genera and 10 novel species that were fully characterized taxonomically.

Dual-layered hydrogels allow complete genome recovery with nucleic acid cytometry

Targeting specific cells for sequencing is important for applications in cancer, microbiology, and infectious disease. Nucleic acid cytometry is a powerful approach for accomplishing this because it allows specific cells to be isolated based on sequence biomarkers that are otherwise impossible to detect. However, existing methods require specialized microfluidic devices, limiting adoption. Here, we describe a modified workflow that uses particle-templated emulsification and flow cytometry to conduct the essential steps of cell detection and sorting normally accomplished by microfluidics. Our microfluidic-free workflow allows facile isolation and sequencing of cells, viruses, and nucleic acids and thus provides a powerful enrichment approach for targeted sequencing applications. This article is protected by copyright. All rights reserved.