Complex Microbial Communities Research Articles

Bacteriophage-mediated approaches for biofilm control

Biofilms are complex microbial communities in which planktonic and dormant bacteria are enveloped in extracellular polymeric substances (EPS) such as exopolysaccharides, proteins, lipids, and DNA. These multicellular structures present resistance to conventional antimicrobial treatments, including antibiotics. The formation of biofilms raises considerable concern in healthcare settings, biofilms can exacerbate infections in patients and compromise the integrity of medical devices employed during treatment. Similarly, certain bacterial species contribute to bulking, foaming, and biofilm development in water environments such as wastewater treatment plants, water reservoirs, and aquaculture facilities. Additionally, food production facilities provide ideal conditions for establishing bacterial biofilms, which can serve as reservoirs for foodborne pathogens. Efforts to combat antibiotic resistance involve exploring various strategies, including bacteriophage therapy. Research has been conducted on the effects of phages and their individual proteins to assess their potential for biofilm removal. However, challenges persist, prompting the examination of refined approaches such as drug-phage combination therapies, phage cocktails, and genetically modified phages for clinical applications. This review aims to highlight the progress regarding bacteriophage-based approaches for biofilm eradication in different settings.

One-Step Soft Agar Enrichment and Isolation of Human Lung Bacteria Inhibiting the Germination of Aspergillus fumigatus Conidia

Fungi of the genus Aspergillus are widespread in the environment, where they produce large quantities of airborne conidia. Inhalation of Aspergillus spp. conidia in immunocompromised individuals can cause a wide spectrum of diseases, ranging from hypersensitivity responses to lethal invasive infections. Upon deposition in the lung epithelial surface, conidia encounter and interact with complex microbial communities that constitute the lung microbiota. The lung microbiota has been suggested to influence the establishment and growth of Aspergillus spp. in the human airways. However, the mechanisms underlying this interaction have not yet been sufficiently investigated. In this study, we aimed to enrich and isolate bacterial strains capable of inhibiting the germination and growth of A. fumigatus conidia from bronchoalveolar lavage fluid (BALF) samples of lung transplant recipients using a novel enrichment method. This method is based on a soft agar overlay plate assay in which bacteria are directly in contact with conidia, allowing inhibition to be readily observed during enrichment. We isolated a total of five clonal bacterial strains with identical genotypic fingerprints, as shown by random amplified polymorphic DNA PCR (RAPD–PCR). All strains were identified as Pseudomonas aeruginosa (strains b1–b5). The strains were able to inhibit the germination and growth of Aspergillus fumigatus in a soft agar confrontation assay, as well as in a germination multiplate assay. Moreover, when compared with ten P. aeruginosa strains isolated from expectoration through standard methods, no significant differences in inhibitory potential were observed. Additionally, we showed inhibition of A. fumigatus growth on Calu-3 cell culture monolayers. However, the isolated P. aeruginosa strains were shown to cause significant damage to the cell monolayers. Overall, although P. aeruginosa is a known opportunistic lung pathogen and antagonist of A. fumigatus, we validated this novel one-step enrichment approach for the isolation of bacterial strains antagonistic to A. fumigatus from BALF samples as a proof-of-concept. This opens up a new venue for the targeted enrichment of antagonistic bacterial strains against specific fungal pathogens.

Sophorolipid: An Effective Biomolecule for Targeting Microbial Biofilms.

Biofilms are microbial aggregates encased in a matrix that is attached to biological or nonbiological surfaces and constitute serious problems in food, medical, and marine industries and can have major negative effects on both health and the economy. Biofilm's complex microbial community provides a resistant environment that is difficult to eradicate and is extremely resilient to antibiotics and sanitizers. There are various conventional techniques for combating biofilms, including, chemical removal, physical or mechanical removal, use of antibiotics and disinfectants to destroy biofilm producing organisms. In contrast to free living planktonic cells, biofilms are very resistant to these methods. Hence, new strategies that differ from traditional approaches are urgently required. Microbial world offers a wide range of effective "green" compounds such as biosurfactants. They outperform synthetic surfactants in terms of biodegradability, superior stabilization, and reduced toxicity concerns. They also have better antiadhesive and anti-biofilm capabilities which can be used to treat biofilm-related problems. Sophorolipids (SLs) are a major type of biosurfactants that have gained immense interest in the healthcare industries because of their antiadhesive and anti-biofilm properties. Sophorolipids may therefore prove to be attractive substances that can be used in biomedical applications as adjuvant to other antibiotics against some infections through growth inhibition and/or biofilm disruption.

Role of TM7 in the Oral Microbiome and its Implications for Periodontal Disease: A Systematic Review

ABSTRACT Periodontal disease, a prevalent oral health condition, involves a complex microbial community. Advanced sequencing technologies have enabled in-depth studies of the oral microbiome, focusing on specific bacterial taxa like TM7. This systematic review analyzes the role of TM7 in the oral microbiome and its implications for periodontal disease. This review underscores TM7’s importance in the oral microbiome and its potential as a target for future research on periodontal disease pathogenesis.

Classifying compounds as prebiotics - scientific perspectives and recommendations.

Microbiomes provide key contributions to health and potentially important therapeutic targets. Conceived nearly 30 years ago, the prebiotic concept posits that targeted modulation of host microbial communities through the provision of selectively utilized growth substrates provides an effective approach to improving health. Although the basic tenets of this concept remain the same, it is timely to address certain challenges pertaining to prebiotics, including establishing that prebiotic-induced microbiota modulation causes the health outcome, determining which members within a complex microbial community directly utilize specific substrates in vivo and when those microbial effects sufficiently satisfy selectivity requirements, and clarification of the scientific principles on which the term 'prebiotic' is predicated to inspire proper use. In this Expert Recommendation, we provide a framework for the classification of compounds as prebiotics. We discuss ecological principles by which substrates modulate microbiomes and methodologies useful for characterizing such changes. We then propose statistical approaches that can be used to establish causal links between selective effects on the microbiome and health effects on the host, which can help address existing challenges. We use this information to provide the minimum criteria needed to classify compounds as prebiotics. Furthermore, communications to consumers and regulatory approaches to prebiotics worldwide are discussed.

Mechanism of carbonized humic acid and magnesium aluminum-layered double hydroxide promoting biohydrogen generation

Dark fermentation (DF) is prone to low hydrogen (H2) yield. In this work, magnesium aluminum-layered double hydroxide and carbonized humic acid (MgAl-LDH/CHA) was synthesized by co-precipitation to reveal the mechanism in rising bioH2 generation. The results indicated that MgAl-LDH released Mg and Al ions slowly in DF system, improving the activity of H2-producing microbes (HPM) for more H2. The H2 yield increased from 169.3 mL/g glucose to 244.9 mL/g glucose, which was 44.7 % higher than that for the control yield. MgAl-LDH/CHA increased Proteobacteria content from 30.9 % to 43.7 %, making it form a complex microbial community and participate in DF metabolism with Firmicutes and other microbes together. Besides, MgAl-LDH/CHA could serve as an electron shuttle that likely effectively promotes electron transfer in DF, significantly reduced the energy requirements of HPM, thus raising metabolic activity. It provides direction for the multi-element composite applied in DF system.

Exploring microbial diversity in the rhizosphere: a comprehensive review of metagenomic approaches and their applications.

The rhizosphere, the soil region influenced by plant roots, represents a dynamic microenvironment where intricate interactions between plants and microorganisms shape soil health, nutrient cycling, and plant growth. Soil microorganisms are integral players in the transformation of materials, the dynamics of energy flows, and the intricate cycles of biogeochemistry. Considerable research has been dedicated to investigating the abundance, diversity, and intricacies of interactions among different microbes, as well as the relationships between plants and microbes present in the rhizosphere. Metagenomics, a powerful suite of techniques, has emerged as a transformative tool for dissecting the genetic repertoire of complex microbial communities inhabiting the rhizosphere. The review systematically navigates through various metagenomic approaches, ranging from shotgun metagenomics, enabling unbiased analysis of entire microbial genomes, to targeted sequencing of the 16S rRNA gene for taxonomic profiling. Each approach's strengths and limitations are critically evaluated, providing researchers with a nuanced understanding of their applicability in different research contexts. A central focus of the review lies in the practical applications of rhizosphere metagenomics in various fields including agriculture. By decoding the genomic content of rhizospheric microbes, researchers gain insights into their functional roles in nutrient acquisition, disease suppression, and overall plant health. The review also addresses the broader implications of metagenomic studies in advancing our understanding of microbial diversity and community dynamics in the rhizosphere. It serves as a comprehensive guide for researchers, agronomists, and policymakers, offering a roadmap for harnessing metagenomic approaches to unlock the full potential of the rhizosphere microbiome in promoting sustainable agriculture.

Microbial single-cell applications under anoxic conditions.

The field of microbiology traditionally focuses on studying microorganisms at the population level. Nevertheless, the application of single-cell level methods, including microfluidics and imaging techniques, has revealed heterogeneity within populations, making these methods essential to understand cellular activities and interactions at a higher resolution. Moreover, single-cell sorting has opened new avenues for isolating cells of interest from microbial populations or complex microbial communities. These isolated cells can be further interrogated in downstream single-cell "omics" analyses, providing physiological and functional information. However, applying these methods to study anaerobic microorganisms under in situ conditions remains challenging due to their sensitivity to oxygen. Here, we review the existing methodologies for the analysis of viable anaerobic microorganisms at the single-cell level, including live-imaging, cell sorting, and microfluidics (lab-on-chip) applications, and we address the challenges involved in their anoxic operation. Additionally, we discuss the development of non-destructive imaging techniques tailored for anaerobes, such as oxygen-independent fluorescent probes and alternative approaches.

Unveiling the Brazilian kefir microbiome: discovery of a novel Lactobacillus kefiranofaciens (LkefirU) genome and in silico prospection of bioactive peptides with potential anti-Alzheimer properties

BackgroundKefir is a complex microbial community that plays a critical role in the fermentation and production of bioactive peptides, and has health-improving properties. The composition of kefir can vary by geographic localization and weather, and this paper focuses on a Brazilian sample and continues previous work that has successful anti-Alzheimer properties. In this study, we employed shotgun metagenomics and peptidomics approaches to characterize Brazilian kefir further.ResultsWe successfully assembled the novel genome of Lactobacillus kefiranofaciens (LkefirU) and conducted a comprehensive pangenome analysis to compare it with other strains. Furthermore, we performed a peptidome analysis, revealing the presence of bioactive peptides encrypted by L. kefiranofaciens in the Brazilian kefir sample, and utilized in silico prospecting and molecular docking techniques to identify potential anti-Alzheimer peptides, targeting β-amyloid (fibril and plaque), BACE, and acetylcholinesterase. Through this analysis, we identified two peptides that show promise as compounds with anti-Alzheimer properties.ConclusionsThese findings not only provide insights into the genome of L. kefiranofaciens but also serve as a promising prototype for the development of novel anti-Alzheimer compounds derived from Brazilian kefir.

Transcriptional profiling elucidates biofilm functionality in the dynamic environment of an enhanced biological phosphorus removal reactor

ABSTRACT Recently, biofilms, complex and dynamic structures of microorganisms, have been applied to enhanced biological phosphorus removal (EBPR), a wastewater treatment configuration dependent on cyclic shifts between anaerobic and aerobic conditions. In this study, comparative metagenomics and metatranscriptomics were performed on biofilms collected from seven sites of a moving-bed-biofilm-reactor-based EBPR process. The aim was to examine the functional ecology of phosphorus-accumulating biofilms throughout a single EBPR cycle. Taxonomic profiling revealed high microbial diversity, stable throughout the EBPR cycle. The dominant phosphorus-accumulating organisms (PAOs) were identified as Candidatus accumulibacter, Candidatus phosphoribacter, and Candidatus lutibacillus. However, these did not show the highest transcriptional activities. Propionivibrio, a potential glycogen-accumulating organism, was the most transcriptionally active. Comparative analysis of biofilms from different EBPR stages showed a progressive change in metatranscriptome composition, correlating with nutrient removal. Analysis of differentially expressed genes in abundant PAOs revealed key genes associated with the uptake of phosphorus, degradation of glycogen, biosynthesis of polyhydroxyalkanoates, and acetate production. In conclusion, this study reveals that biofilms possess the capability to adapt to environmental fluctuations primarily through alterations in microbial gene expression activity and subsequent metabolic modulation, and dominant taxa may not necessarily exhibit the highest transcriptional activity in complex microbial communities.

Exploring the vitamin biosynthesis landscape of the human gut microbiota.

The human gut microbiota possesses the capacity to synthesize vitamins, especially B group vitamins, which are recognized as indispensable for various biological processes both among members of these bacterial communities and host cells. Accordingly, vitamin production by intestinal commensals has attracted significant interest. Nevertheless, our current understanding of bacterial vitamin synthesis is primarily based on individual genomic and monoculture investigations, therefore not providing an overall view of the biosynthetic potential of complex microbial communities. In the current study, we utilized over 100 bacterial genes known to be involved in the biosynthesis of B group and K vitamins to assess the corresponding vitamin biosynthetic potential of approximately 8,000 human gut microbiomes. Our analyses reveal that host-associated factors, such as age and geographical origin, appear to influence the diversity and abundance of vitamin biosynthetic pathways. Furthermore, we identify gut microbiota members that substantially contribute to these biosynthetic functions at each stage of human life. Interestingly, inference of microbial co-associations and network relationships uncovered the apparent key role played by folate and cobalamin in equilibrium establishment of the infant and adult gut microbial communities, respectively.IMPORTANCEOverall, this study expands our understanding of microbe-mediated vitamin biosynthesis in the human gut and may provide potential novel targets to improve availability of these essential micronutrients in the host.

CAMP: A modular metagenomics analysis system for integrated multi-step data exploration.

Computational analysis of large-scale metagenomics sequencing datasets have proven to be both incredibly valuable for extracting isolate-level taxonomic, and functional insights from complex microbial communities. However, due to an ever-expanding ecosystem of metagenomics-specific methods and file-formats, designing studies which implement seamless and scalable end-to-end workflows, and exploring the massive amounts of output data have become studies unto themselves. One-click bioinformatics pipelines have helped to organize these tools into targeted workflows, but they suffer from general compatibility and maintainability issues. To address the gap in easily extensible yet robustly distributable metagenomics workflows, we have developed a module-based metagenomics analysis system "Core Analysis Metagenomics Pipeline" (CAMP), written in Snakemake, a popular workflow management system, along with a standardized module and working directory architecture. Each module can be run independently or conjointly with a series of others to produce the target data format (ex. short-read preprocessing alone, or short-read preprocessing followed by \textit{de novo} assembly), and outputs aggregated summary statistics reports and semi-guided Jupyter notebook-based visualizations. We have applied CAMP to a set of ten metagenomics samples to demonstrate how a modular analysis system with built-in data visualization at intermediate steps facilitates rich and seamless inter-communication between output data from different analytic purposes. The module template as well as the modules described below can be found at https://github.com/MetaSUB-CAMP.

Selection for amoxicillin-, doxycycline-, and enrofloxacin-resistant Escherichia coli at concentrations lower than the ECOFF in broiler-derived cecal fermentations.

Antimicrobial resistance (AMR) is an emerging worldwide problem and a health threat for humans and animals. Antimicrobial usage in human and animal medicine or in agriculture results in selection for AMR. The selective concentration of antimicrobial compounds can be lower than the minimum inhibitory concentration and differs between environments, which can be a reason for bacterial resistance. Therefore, knowledge of the minimal selective concentration (MSC), under natural conditions, is essential to understand the selective window of bacteria when exposed to residual antimicrobials. In this study, we estimated the MSCs of three antimicrobials, amoxicillin, doxycycline, and enrofloxacin in a complex microbial community by conducting fermentation assays with cecal material derived from broilers. We examined the phenotypic resistance of Escherichia coli, resistome, and microbiome after 6 and 30 hours of fermenting in the presence of the antimicrobials of interest. The concentrations were estimated to be 10-100 times lower than the epidemiological cut-off values in E. coli for the respective antimicrobials as determined by EUCAST, resulting in an MSC between 0.08 and 0.8 mg/L for amoxicillin, 0.4 and 4 mg/L for doxycycline, and 0.0125 and 0.125 mg/L for enrofloxacin. Additionally, resistome analysis provided an MSC for doxycycline between 0.4 and 4 mg/L, but amoxicillin and enrofloxacin exposure did not induce a significant difference. Our findings indicate at which concentrations there is still selection for antimicrobial-resistant bacteria. This knowledge can be used to manage the risk of the emergence of antimicrobial-resistant bacteria.IMPORTANCEAntimicrobial resistance possibly affects human and animal health, as well as economic prosperity in the future. The rise of antimicrobial-resistant bacteria is a consequence of using antimicrobial compounds in humans and animals selecting for antimicrobial-resistant bacteria. Concentrations reached during treatment are known to be selective for resistant bacteria. However, at which concentrations residues are still selective is important, especially for antimicrobial compounds that remain in the environment at low concentrations. The data in this paper might inform decisions regarding guidelines and regulations for the use of specific antimicrobials. In this study, we are providing these minimal selective concentrations for amoxicillin, doxycycline, and enrofloxacin in complex environments.

A novel barcoded nanopore sequencing workflow of high-quality, full-length bacterial 16S amplicons for taxonomic annotation of bacterial isolates and complex microbial communities.

Due to recent improvements, Nanopore sequencing has become a promising method for experiments relying on amplicon sequencing. We describe a flexible workflow to generate and annotate high-quality, full-length 16S rDNA amplicons. We evaluated it for two applications, namely, (i) identification of bacterial isolates and (ii) species-level profiling of microbial communities. We assessed the identification of single bacterial isolates by sequencing, using a set of barcoded full-length 16S rRNA gene primer pairs (pair A), on 47 isolates encompassing multiple genera and compared those results with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)-based identification. Species-level community profiling was tested with two sets of barcoded full-length 16S primer pairs (A and B) and compared to the results obtained with shotgun Illumina sequencing using 27 stool samples. We developed a Nextflow pipeline to retain high-quality reads and taxonomically annotate them. We found high agreement between our workflow and MALDI-TOF data for isolate identification (positive predictive value = 0.90, Cramér's V = 0.857, and Theil's U = 0.316). For species-level community profiling, we found strong correlations (rs > 0.6) of alpha diversity indices between the two primer sets and Illumina sequencing. At the community level, we found significant but small differences when comparing sequencing techniques. Finally, we found a moderate to strong correlation when comparing the relative abundances of individual species (average rs = 0.6 and 0.533 for primers A and B). Despite identified shortcomings, the proposed workflow enabled accurate identification of single bacterial isolates and prominent features in microbial communities, making it a worthwhile alternative to MALDI-TOF MS and Illumina sequencing.IMPORTANCEA quick, robust, simple, and cost-effective method to identify bacterial isolates and communities in each sample is indispensable in the fields of microbiology and infection biology. Recent technological advances in Oxford Nanopore Technologies sequencing make this technique an attractive option considering the adaptability, portability, and cost-effectiveness of the platform, even with small sequencing batches. Here, we validated a flexible workflow to identify bacterial isolates and characterize bacterial communities using the Oxford Nanopore Technologies sequencing platform combined with the most recent v14 chemistry kits. For bacterial isolates, we compared our nanopore-based approach to matrix-assisted laser desorption ionization-time of flight mass spectrometry-based identification. For species-level profiling of complex bacterial communities, we compared our nanopore-based approach to Illumina shotgun sequencing. For reproducibility purposes, we wrapped the code used to process the sequencing data into a ready-to-use and self-contained Nextflow pipeline.

The predicted secreted proteome of activated sludge microorganisms indicates distinct nutrient niches.

In wastewater treatment plants (WWTPs), complex microbial communities process diverse chemical compounds from sewage. Secreted proteins are critical because many are the first to interact with or degrade external (macro)molecules. To better understand microbial functions in WWTPs, we predicted secreted proteomes of WWTP microbiota from more than 1,000 high-quality metagenome-assembled genomes (MAGs) from 23 Danish WWTPs with biological nutrient removal. Focus was placed on examining secreted catabolic exoenzymes that target major classes of macromolecules. We demonstrate that Bacteroidota has a high potential to digest complex polysaccharides, but also proteins and nucleic acids. Poorly understood activated sludge members of Acidobacteriota and Gemmatimonadota also have high capacities for extracellular polysaccharide digestion. Secreted nucleases are encoded by 61% of MAGs indicating an importance for extracellular DNA and/or RNA digestion in WWTPs. Secreted lipases were the least common macromolecule-targeting enzymes predicted, encoded mainly by Gammaproteobacteria and Myxococcota. In contrast, diverse taxa encode extracellular peptidases, indicating that proteins are widely used nutrients. Diverse secreted multi-heme cytochromes suggest capabilities for extracellular electron transfer by various taxa, including some Bacteroidota that encode undescribed cytochromes with >100 heme-binding motifs. Myxococcota have exceptionally large secreted protein complements, probably related to predatory lifestyles and/or complex cell cycles. Many Gammaproteobacteria MAGs (mostly former Betaproteobacteria) encode few or no secreted hydrolases, but many periplasmic substrate-binding proteins and ABC- and TRAP-transporters, suggesting they are mostly sustained by small molecules. Together, this study provides a comprehensive overview of how WWTPs microorganisms interact with the environment, providing new insights into their functioning and niche partitioning.IMPORTANCEWastewater treatment plants (WWTPs) are critical biotechnological systems that clean wastewater, allowing the water to reenter the environment and limit eutrophication and pollution. They are also increasingly important for the recovery of resources. They function primarily by the activity of microorganisms, which act as a "living sponge," taking up and transforming nutrients, organic material, and pollutants. Despite much research, many microorganisms in WWTPs are uncultivated and poorly characterized, limiting our understanding of their functioning. Here, we analyzed a large collection of high-quality metagenome-assembled genomes from WWTPs for encoded secreted enzymes and proteins, with special emphasis on those used to degrade organic material. This analysis showed highly distinct secreted proteome profiles among different major phylogenetic groups of microorganisms, thereby providing new insights into how different groups function and co-exist in activated sludge. This knowledge will contribute to a better understanding of how to efficiently manage and exploit WWTP microbiomes.

Flagellar point mutation causes social aggregation in laboratory-adapted Bacillus subtilis under conditions that promote swimming.

Motility allows microbes to explore and maximize success in their environment; however, many laboratory bacterial strains have a reduced or altered capacity for motility. Swimming motility in Bacillus subtilis depends on peritrichous flagella and is carried out individually as cells move by biased random walks toward attractants. Previously, we adapted Bacillus subtilis strain 3610 to the laboratory for 300 generations in lysogeny broth (LB) batch culture and isolated lab-adapted strains. Strain SH2 is motility-defective and in broth culture forms large, frequently spherical aggregates of cells. A single point mutation in the flagellin gene hag that causes amino acid 259 to switch from A to T is necessary and sufficient to cause these social cell aggregates, and aggregation occurs between flagellated cells bearing this point mutation regardless of the strain background. Cells associate when bearing this mutation, but flagellar rotation is needed to pull associating cells into spherical aggregates. Using electron microscopy, we are able to show that the SH2 flagellar filament has limited polymorphism when compared to other flagellar structures. This limited polymorphism hinders the flagellum's ability to function as a motility apparatus but appears to alter its function to that of cell aggregation/adhesion. We speculate that the genotype-specific aggregation of cells producing HagA259T flagella could have increased representation in a batch-culture experiment by allowing similar cells to go through a transfer together and also that this mutation could serve as an early step to evolve sociality in the natural world.IMPORTANCEThe first life forms on this planet were prokaryotic, and the earliest environments were aquatic, and from these relatively simple starting conditions, complex communities of microbes and ultimately multicellular organisms were able to evolve. Usually, motile cells in aqueous environments swim as individuals but become social by giving up motility and secreting extracellular substances to become a biofilm. Here, we identify a single point mutation in the flagellum that is sufficient to allow cells containing this mutation to specifically form large, suspended groups of cells. The specific change in the flagellar filament protein subunits causes a unique change in the flagellar structure. This could represent a distinct way for closely related cells to associate as an early precursor to sociality.

Imputing Metagenomic Hi-C Contacts Facilitates the Integrative Contig Binning Through Constrained Random Walk with Restart.

Metagenomic Hi-C (metaHi-C) has shown remarkable potential for retrieving high-quality metagenome-assembled genomes from complex microbial communities. Nevertheless, existing metaHi-C-based contig binning methods solely rely on Hi-C interactions between contigs, disregarding crucial biological information such as the presence of single-copy marker genes. To overcome this limitation, we introduce ImputeCC, an integrative contig binning tool optimized for metaHi-C datasets. ImputeCC integrates both Hi-C interactions and the discriminative power of single-copy marker genes to group marker-gene-containing contigs into preliminary bins. It also introduces a novel constrained random walk with restart algorithm to enhance Hi-C connectivity among contigs. Comprehensive assessments using both mock and real metaHi-C datasets from diverse environments demonstrate that ImputeCC consistently outperforms other Hi-C-based contig binning tools. A genus-level analysis of the sheep gut microbiota reconstructed by ImputeCC underlines its capability to recover key species from dominant genera and identify previously unknown genera.

Improving viral annotation with artificial intelligence.

Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community structure and function. Additionally, their dependence on hosts for replication positions phages as unique sensors of ecosystem features and environmental pressures. High-throughput sequencing approaches have begun to give us access to the diversity and range of phage populations in complex microbial community samples, and metagenomics is currently the primary tool with which we study phage populations. The study of phages by metagenomic sequencing, however, is fundamentally limited by viral diversity, which results in the vast majority of viral genomes and metagenome-annotated genomes lacking annotation. To harness bacteriophages for applications in human and environmental health and disease, we need new methods to organize and annotate viral sequence diversity. We recently demonstrated that methods that leverage self-supervised representation learning can supplement statistical sequence representations for remote viral protein homology detection in the ocean virome and propose that consideration of the functional content of viral sequences allows for the identification of similarity in otherwise sequence-diverse viruses and viral-like elements for biological discovery. In this review, we describe the potential and pitfalls of large language models for viral annotation. We describe the need for new approaches to annotate viral sequences in metagenomes, the fundamentals of what protein language models are and how one can use them for sequence annotation, the strengths and weaknesses of these models, and future directions toward developing better models for viral annotation more broadly.

Detection, isolation and characterization of phage-host complexes using BONCAT and click chemistry.

Phages are viruses that infect prokaryotes and can shape microbial communities by lysis, thus offering applications in various fields. However, challenges exist in sampling, isolation and accurate prediction of the host specificity of phages as well as in the identification of newly replicated virions in response to environmental challenges. A new workflow using biorthogonal non-canonical amino acid tagging (BONCAT) and click chemistry (CC) allowed the combined analysis of phages and their hosts, the identification of newly replicated virions, and the specific tagging of phages with biotin for affinity chromatography. Replication of phage λ in Escherichia coli was selected as a model for workflow development. Specific labeling of phage λ proteins with the non-canonical amino acid 4-azido-L-homoalanine (AHA) during phage development in E. coli was confirmed by LC-MS/MS. Subsequent tagging of AHA with fluorescent dyes via CC allowed the visualization of phages adsorbed to the cell surface by fluorescence microscopy. Flow cytometry enabled the automated detection of these fluorescent phage-host complexes. Alternatively, AHA-labeled phages were tagged with biotin for purification by affinity chromatography. Despite biotinylation the tagged phages could be purified and were infectious after purification. Applying this approach to environmental samples would enable host screening without cultivation. A flexible and powerful workflow for the detection and enrichment of phages and their hosts in pure cultures has been established. The developed method lays the groundwork for future workflows that could enable the isolation of phage-host complexes from diverse complex microbial communities using fluorescence-activated cell sorting or biotin purification. The ability to expand and customize the workflow through the growing range of compounds for CC offers the potential to develop a versatile toolbox in phage research. This work provides a starting point for these further studies by providing a comprehensive standard operating procedure.

Fluorescently probing anaerobic digester sludge: Measuring single-cell anabolic activity in methanogens (Methanosarcina and Methanothermobacter) with deuterium-labeled Raman analysis

This study addresses the challenge of obtaining in situ information on substrate utilization rates for individual microbial species in complex microbial communities such as anaerobic digester sludge. To overcome this hurdle, a novel approach combining doubly-labelled deuterium, fluorescence in situ hybridization (FISH) and Raman microspectroscopy was developed. The method enables quantitative determination of anabolic heavy hydrogen incorporation into FISH-targeted, exemplified by methanogenic cells from the genera Methanosarcina and Methanothermobacter.The deuterium incorporation rates ascertained by Raman red-shifting of C-Hx vibrational region to C-Dx vibrations, quantified through Raman peak area ratios, were compared for different carbon sources. Methanosarcina exhibited highest kinetic rates with acetate and propionate, while Methanothermobacter demonstrated faster incorporation under acetate and methanol supplementation.This groundbreaking study demonstrates the feasibility of obtaining quantitative metabolic rate information at a single-cell level using deuterium, FISH probes, and Raman microspectroscopy.