Microbial Genomes Research Articles

Iron-sulfur cluster-dependent enzymes and molybdenum-dependent reductases in the anaerobic metabolism of human gut microbes.

Metalloenzymes play central roles in the anaerobic metabolism of human gut microbes. They facilitate redox and radical-based chemistry that enables microbial degradation and modification of various endogenous, dietary, and xenobiotic nutrients in the anoxic gut environment. In this review, we highlight major families of iron-sulfur (Fe-S) cluster-dependent enzymes and molybdenum cofactor-containing enzymes used by human gut microbes. We describe the metabolic functions of 2-hydroxyacyl-CoA dehydratases, glycyl radical enzyme activating enzymes, Fe-S cluster-dependent flavoenzymes, U32 oxidases, and molybdenum-dependent reductases and catechol dehydroxylases in the human gut microbiota. We demonstrate widespread distribution and prevalence of these metalloenzyme families across 5000 human gut microbial genomes. Lastly, we discuss opportunities for metalloenzyme discovery in the human gut microbiota to reveal new chemistry and biology in this important community.

Removal of sequencing adapter contamination improves microbial genome databases

Advances in assembling microbial genomes have led to growth of reference genome databases, which have been transformative for applied and basic microbiome research. Here we show that published microbial genome databases from humans, mice, cows, pigs, fish, honeybees, and marine environments contain significant sequencing-adapter contamination that systematically reduces assembly accuracy and contiguousness. By removing the adapter-contaminated ends of contiguous sequences and reassembling MGnify reference genomes, we improve the quality of assemblies in these databases.

Genomic diversity of phages infecting the globally widespread genus Sulfurimonas

The widespread bacterial genus Sulfurimonas is metabolically versatile and occupies a key ecological niche in different habitats, but its interaction with bacteriophages remains unexplored. Here we systematically investigated the genetic diversity, taxonomy and interaction patterns of Sulfurimonas-associated phages based on sequenced microbial genomes and metagenomes. High-confidence phage contigs related to Sulfurimonas were retrieved from various ecosystems, clustered into 61 viral operational taxonomic units across three viral realms, including Duplodnaviria, Monodnaviria and Varidnaviria. Head-tail phages of Caudoviricetes were assigned to 19 genus-level viral clusters, the majority of which were distantly related to known viruses. Notably, diverse double jelly-roll viruses and inoviruses were also linked to Sulfurimonas, representing two commonly overlooked phage groups. Historical and current phage infections were revealed, implying viral impact on the evolution of host adaptive immunity. Additionally, phages carrying auxiliary metabolic genes might benefit hosts by compensating or augmenting sulfur metabolism. This study highlights the diversity and novelty of Sulfurimonas-associated phages with divergent tailless lineages, providing basis for further investigation of phage-host interactions within this genus.

Gut heavy metal and antibiotic resistome of humans living in the high Arctic

Contaminants, such as heavy metals (HMs), accumulate in the Arctic environment and the food web. The diet of the Indigenous Peoples of North Greenland includes locally sourced foods that are central to their nutritional, cultural, and societal health but these foods also contain high concentrations of heavy metals. While bacteria play an essential role in the metabolism of xenobiotics, there are limited studies on the impact of heavy metals on the human gut microbiome, and it is so far unknown if and how Arctic environmental contaminants impact the gut microbes of humans living in and off the Arctic environment. Using a multiomics approach including amplicon, metagenome, and metatranscriptome sequencing, we identified and assembled a near-complete (NC) genome of a mercury-resistant bacterial strain from the human gut microbiome, which expressed genes known to reduce mercury toxicity. At the overall ecological level studied through α- and β-diversity, there was no significant effect of heavy metals on the gut microbiota. Through the assembly of a high number of NC metagenome-assembled genomes (MAGs) of human gut microbes, we observed an almost complete overlap between heavy metal-resistant strains and antibiotic-resistant strains in which resistance genes were all located on the same genetic elements.

GutMGene v2.0: an updated comprehensive database for target genes of gut microbes and microbial metabolites.

The gut microbiota is essential for various physiological functions in the host, primarily through the metabolites it produces. To support researchers in uncovering how gut microbiota contributes to host homeostasis, we launched the gutMGene database in 2022. In this updated version, we conducted an extensive review of previous papers and incorporated new papers to extract associations among gut microbes, their metabolites, and host genes, carefully classifying these as causal or correlational. Additionally, we performed metabolic reconstructions for representative gut microbial genomes from both human and mouse. gutMGene v2.0 features an upgraded web interface, providing users with improved accessibility and functionality. This upgraded version is freely available at http://bio-computing.hrbmu.edu.cn/gutmgene. We believe that this new version will greatly advance research in the gut microbiota field by offering a comprehensive resource.

Deciphering Toxic Pollutants Breakdown Potential in Microbial Community of Chumathang Hot Spring, Ladakh, India via Shotgun Metagenome Sequencing.

Persistent Organic Pollutants (POPs) have been in focus of research due to their massive contamination ofenvironment and bio-accumulation. Bioremediation and high-throughput research have gained momentum to curb the harmful effects of POPs. The present research has explored the microbial diversity of Chumathang Hot Spring, Ladakh, India, through Illumina metagenomic HiSeq 4000 sequencing platform and their potential to degrade persistent pollutants, especially xenobiotics. Taxonomic characterization based on raw metagenomic data illuminated the abundance of members of Pseudomonadota and Actinomyceota. The re-construction of the microbial genomes from assembled contigs and scaffolds using de novo assembler metaSPAdes and their further annotation through contig alignment with available reference genomes elucidated the landscape of the hot spring's microbes. The predominantly occupied key genera reported were Pannonibacter and Novosphingobium. Comparative genomic analysis established evolutionary relationships and functional diversities among hot spring microbial communities. The function annotation through MG-RAST has revealed their metabolic versatility of degrading a wide array of xenobiotic compounds, including caprolactam, dioxin, chlorobenzene, benzoate, and. Further, the hydroxylating dioxygenase (Saro_3901) was identified as a pivotal component in the aromatic degradation pathways, showcasing extensive metabolic interconnectivity. Interestingly, protein interaction network analysis identified hub genes like Saro_1233 (protocatechuate 4,5-dioxygenase alpha subunit), while Saro_3057 (amidase) was noted for its critical role in network communication and control. The resilience of thermal ecosystems, evidenced by robust enzymatic activity and degradation capability among organisms with < 95% genetic similarity, underscores their potential for industrial and bioremediation exploration, emphasizing the importance of preserving and studying biodiverse habitats.

A new selective force driving metabolic gene clustering.

The formation of clusters of functionally related genes in microbial genomes has puzzled microbiologists since their discovery. Here, we suggest that replication, and the copy number variations due to the replisome passage, might play a role in the process through a perturbation in metabolite homeostasis. We provide theoretical support to this hypothesis, and we found that both simulations and genomic analysis support our hypothesis.

Evaluating Sequence Alignment Tools for Antimicrobial Resistance Gene Detection in Assembly Graphs

Antimicrobial resistance (AMR) is an escalating global health threat, often driven by the horizontal gene transfer (HGT) of resistance genes. Detecting AMR genes and understanding their genomic context within bacterial populations is crucial for mitigating the spread of resistance. In this study, we evaluate the performance of three sequence alignment tools—Bandage, SPAligner, and GraphAligner—in identifying AMR gene sequences from assembly and de Bruijn graphs, which are commonly used in microbial genome assembly. Efficiently identifying these genes allows for the detection of neighboring genetic elements and possible HGT events, contributing to a deeper understanding of AMR dissemination. We compare the performance of the tools both qualitatively and quantitatively, analyzing the precision, computational efficiency, and accuracy in detecting AMR-related sequences. Our analysis reveals that Bandage offers the most precise and efficient identification of AMR gene sequences, followed by GraphAligner and SPAligner. The comparison includes evaluating the similarity of paths returned by each tool and measuring output accuracy using a modified edit distance metric. These results highlight Bandage’s potential for contributing to the accurate identification and study of AMR genes in bacterial populations, offering important insights into resistance mechanisms and potential targets for mitigating AMR spread.

Editorial: Microbial comparative genomics and pangenomics: new tools, approaches and insights into gene and genome evolution

Editorial: Microbial comparative genomics and pangenomics: new tools, approaches and insights into gene and genome evolution

Systematic discovery of antibacterial and antifungal bacterial toxins.

Microorganisms use toxins to kill competing microorganisms or eukaryotic cells. Polymorphic toxins are proteins that encode carboxy-terminal toxin domains. Here we developed a computational approach to identify previously undiscovered, conserved toxin domains of polymorphic toxins within 105,438 microbial genomes. We validated nine short toxins, showing that they cause cell death upon heterologous expression in either Escherichia coli or Saccharomyces cerevisiae. Five cognate immunity genes that neutralize the toxins were also discovered. The toxins are encoded by 2.2% of sequenced bacteria. A subset of the toxins exhibited potent antifungal activity against various pathogenic fungi but not against two invertebrate model organisms or macrophages. Experimental validation suggested that these toxins probably target the cell membrane or DNA or inhibit cell division. Further characterization and structural analysis of two toxin-immunity protein complexes confirmed DNase activity. These findings expand our knowledge of microbial toxins involved in inter-microbial competition that may have the potential for clinical and biotechnological applications.

Genomic and functional characterization of the Atlantic salmon gut microbiome in relation to nutrition and health.

To ensure sustainable aquaculture, it is essential to understand the path 'from feed to fish', whereby the gut microbiome plays an important role in digestion and metabolism, ultimately influencing host health and growth. Previous work has reported the taxonomic composition of the Atlantic salmon (Salmo salar) gut microbiome; however, functional insights are lacking. Here we present the Salmon Microbial Genome Atlas consisting of 211 high-quality bacterial genomes, recovered by cultivation (n = 131) and gut metagenomics (n = 80) from wild and farmed fish both in freshwater and seawater. Bacterial genomes were taxonomically assigned to 14 different orders, including 35 distinctive genera and 29 previously undescribed species. Using metatranscriptomics, we functionally characterized key bacterial populations, across five phyla, in the salmon gut. This included the ability to degrade diet-derived fibres and release vitamins and other exometabolites with known beneficial effects, which was supported by genome-scale metabolic modelling and in vitro cultivation of selected bacterial species coupled with untargeted metabolomic studies. Together, the Salmon Microbial Genome Atlas provides a genomic and functional resource to enable future studies on salmon nutrition and health.

Discovery of a New Class of Aminoacyl Radical Enzymes Expands Nature's Known Radical Chemistry.

Radical enzymes, including the evolutionarily ancient glycyl radical enzyme (GRE) family, catalyze chemically challenging reactions that are involved in a myriad of important biological processes. All GREs possess an essential, conserved backbone glycine that forms a stable catalytically essential α-carbon radical. Through close examination of the GRE family, we unexpectedly identified hundreds of noncanonical GRE homologues that encode either an alanine, serine, or threonine in place of the catalytic glycine residue. Contrary to a long-standing belief, we experimentally demonstrate that these aminoacyl radical enzymes (AAREs) form stable α-carbon radicals on the three cognate residues when activated by partner activating enzymes. The previously unrecognized AAREs are widespread in microbial genomes, highlighting their biological importance and potential for exhibiting new reactivity. Collectively, these studies expand the known radical chemistry of living systems while raising questions about the evolutionary emergence of the AAREs.

Compression rates of microbial genomes are associated with genome size and base composition

BackgroundTo what degree a string of symbols can be compressed reveals important details about its complexity. For instance, strings that are not compressible are random and carry a low information potential while the opposite is true for highly compressible strings. We explore to what extent microbial genomes are amenable to compression as they vary considerably both with respect to size and base composition. For instance, microbial genome sizes vary from less than 100,000 base pairs in symbionts to more than 10 million in soil-dwellers. Genomic base composition, often summarized as genomic AT or GC content due to the similar frequencies of adenine and thymine on one hand and cytosine and guanine on the other, also vary substantially; the most extreme microbes can have genomes with AT content below 25% or above 85% AT. Base composition determines the frequency of DNA words, consisting of multiple nucleotides or oligonucleotides, and may therefore also influence compressibility. Using 4,713 RefSeq genomes, we examined the association between compressibility, using both a DNA based- (MBGC) and a general purpose (ZPAQ) compression algorithm, and genome size, AT content as well as genomic oligonucleotide usage variance (OUV) using generalized additive models.ResultsWe find that genome size (p < 0.001) and OUV (p < 0.001) are both strongly associated with genome redundancy for both type of file compressors. The DNA-based MBGC compressor managed to improve compression with approximately 3% on average with respect to ZPAQ. Moreover, MBGC detected a significant (p < 0.001) compression ratio difference between AT poor and AT rich genomes which was not detected with ZPAQ.ConclusionAs lack of compressibility is equivalent to randomness, our findings suggest that smaller and AT rich genomes may have accumulated more random mutations on average than larger and AT poor genomes which, in turn, were significantly more redundant. Moreover, we find that OUV is a strong proxy for genome compressibility in microbial genomes. The ZPAQ compressor was found to agree with the MBGC compressor, albeit with a poorer performance, except for the compressibility of AT-rich and AT-poor/GC-rich genomes.

The Catalog of Microbial Genes and Metagenome-Assembled Genomes from the Gut Microbiomes of Five Typical Crow Species on the Qinghai-Tibetan Plateau.

While considerable progress has been made in understanding the complex relationships between gut microbiomes and their hosts, especially in mammals and humans, the functions of these microbial communities in avian species remain largely unexplored. This gap in knowledge is particularly notable, given the critical roles gut microbiomes are known to play in facilitating crucial physiological functions, such as digestion, nutrient absorption, and immune system development. Corvidae birds are omnivorous and widely distributed across various habitats, exhibiting strong adaptability and often displaying the traits of accompanying humans. However, to date, information on species composition, sequenced genomes, and functional characteristics of crow gut microbes is lacking. Herein, we constructed the first relatively comprehensive crows gut microbial gene catalog (2.74 million genes) and 195 high-quality and medium-quality metagenome-assembled genomes using 53 metagenomic samples from five typical crow species (Pyrrhocorax pyrrhocorax, Corvus dauuricus, Corvus frugilegus, Corvus macrorhynchos, and Corvus corax) on the Qinghai-Tibetan Plateau. The species composition of gut microbiota at the phylum and genus levels was revealed for these five crow species. Simultaneously, numerous types of prevalent pathogenic bacteria were identified, indicating the potential of these crows to transmit diseases within the local community. At the functional level, we annotated a total of 356 KEGG functional pathways, six CAZyme categories, and 3607 virulence factor genes in the gut microbiomes of the crows. The gut microbiota of five distinct crow species underwent a comparative analysis, which uncovered significant differences in their composition, diversity, and functional structures. Over 36% of MAGs showed no overlap with existing databases, suggesting they might represent new species. Consequently, these findings enriched the dataset of microbial genomes associated with crows' digestive systems. Overall, this study offers crucial baseline information regarding the gut microbial gene catalog and genomes in crows, potentially aiding microbiome-based research, as well as an evaluation of the health risks to humans from the bacterial pathogens transmitted by wild birds.

A-264 Validation of a Novel Real-Time PCR Assay for Identification of Mycobacterium species Isolates Recovered from Clinical Culture

Abstract Background Historically, clinical mycobacteriology laboratories used the nucleic acid hybridization-based AccuProbe assay manufactured by Hologic, Inc., to rapidly rule in or rule out Mycobacterium tuberculosis (MTB) and members of the M. avium-intracellulare complex (MAC). The clinical value of this test was in its ability to rapidly rule in/out MTB from positive broth cultures and allow the initiation of appropriate antimicrobial therapy and infection prevention practices. Recent discontinuation of this commercial assay left a gap in testing available for the rapid identification of these organisms, which allowed us to develop an in-house real-time PCR test. Methods A replacement assay was developed by Labcorp R &amp; D based on real-time PCR amplification of extracted nucleic acids from positive culture growth. Aliquots from positive AFB VersaTREK broth cultures were heat inactivated, and nucleic acids were extracted using the MagNA Pure 24 (MP24) instrument (Roche). Real-time PCR using published primer probe sets (Rocchetti, et al 2016) was performed on the QuantStudio™ 7 (QS7) instrument (Applied Biosystems®). The assay was designed with three independent primer/probe sequence targets: one for MTB Complex (IS6110), one for MAC (ITS), and one pan-target for the Mycobacterium genus (16s rRNA). Results Procedural verification was performed using 100 residual clinical specimens previously identified using the Hologic AccuProbe® assay. Categorical concordance was 97% (97/100). The three discrepant results were identified as MAC positive by PCR; however, these were not identified as MAC on the predicate assay. Analytical sensitivity for the PCR assay was established to be 1,000 CFU/mL for each target. Analytical specificity was assessed in vitro for nine Mycobacterium species, with no cross-reactivity observed. In vitro analysis of target detection in the presence of yeast (Candida glabrata) was also performed, and we saw no inhibition. Analysis of the primer/probe sets for all targets was performed in silico using XploreDB database of microbial genomes, with confirmed 100% matches for both MAC and MTB genomes compared to hundreds of species. By comparison, the PAN-Myco primer set showed decreased performance, having three mismatches (two on forward primer and one on the probe). As this target sequence is used as an Internal Control (IC) this was not problematic for overall assay performance. The assay demonstrated excellent precision (%CV) for each target: MTB = 0.74%, MAC = 1.10%, PAN-Myco = 3.19%. Conclusions Utilizing the depth of molecular methodologies available in our laboratories, we developed a rapid method for identification of MAC and MTB from positive broth cultures, which had excellent performance compared to the predicate assay. The PCR ID LDT test is now available and allows testing to continue with no interruption in patient care.

Metagenome sequencing and 982 microbial genomes from Kermadec and Diamantina Trenches sediments

Deep-sea trenches representing an intriguing ecosystem for exploring the survival and evolutionary strategies of microbial communities in the highly specialized deep-sea environments. Here, 29 metagenomes were obtained from sediment samples collected from Kermadec and Diamantina trenches. Notably, those samples covered a varying sampling depths (from 5321 m to 9415 m) and distinct layers within the sediment itself (from 0~40 cm in Kermadec trench and 0~24 cm in Diamantina trench). Through metagenomic binning process, we reconstructed 982 metagenome assembled genomes (MAGs) with completeness >60% and contamination <5%. Within them, completeness of 351 MAGs were >90%, while an additional 331 were >80%. Phylogenomic analysis for the MAGs revealed nearly all of them were distantly related to known cultivated isolates. The abundant bacterial MAGs affiliated to phyla of Proteobacteria, Planctomycetota, Nitrospirota, Acidobacteriota, Actinobacteriota, and Chlorofexota, while the abundant archaeal phyla affiliated with Nanoarchaeota and Thermoproteota. These results provide a dataset available for further interrogation of diversity, distribution and ecological function of deep-sea microbes existed in the trenches.

Seminal plasma microbiomes, sperm parameters, and cryopreservation in a healthy fertile population.

Recent advances in microbiome research have revealed the presence of diverse microbial communities in human tissues previously thought to be sterile. The present study delves into the emerging field of seminal plasma microbiomics, examining the relationship between semen microbes and semen parameters and post-freezing tolerance. The study involved a cohort of healthy fertility males and microbial genome analysis using 16S rRNA to characterize the microbial diversity of seminal plasma. Microbial diversity analysis identified unique amplicon sequence variants (ASVs) and genera dominant in seminal plasma. Spearman's correlation coefficient was used to assess the relationship between flora and semen parameters. A paired t-test was used to compare the changes in microbiome expression in seminal plasma before and after cryo-resuscitation. The relevant results show that the top five phyla in terms of abundance of seminal plasma microbiome were Firmicutes, Bacteroidota, Proteobacteria, Actinobacteriota, and Campylobacterota. Spearman correlation analysis highlighted the association between specific microbial species and semen parameters, between Porphyromonas_asaccharolytica and sperm concentration. Microbial changed significantly after cryo-resuscitation, affecting taxonomic units such as Campylobacter and Muribaculaceae, and KEGG enrichment analyses, suggesting that metabolic pathways are associated with sperm freezing. Eubacterium_coprostanoligenes and Eptoniphilus_duerdenii exhibited a potential impact, while Orynebacterium_tuberculostearicum demonstrated a positive correlation with the recovery rate of progressive motile sperm. The semen of normal fertile individuals contains a microflora component that is closely related to semen quality, including the sperm's ability to withstand freezing.

Deep longitudinal lower respiratory tract microbiome profiling reveals genome-resolved functional and evolutionary dynamics in critical illness

The lower respiratory tract (LRT) microbiome impacts human health, especially among critically ill patients. However, comprehensive characterizations of the LRT microbiome remain challenging due to low microbial mass and host contamination. We develop a chelex100-based low-biomass microbial-enrichment method (CMEM) that enables deep metagenomic profiling of LRT samples to recover near-complete microbial genomes. We apply the method to 453 longitudinal LRT samples from 157 intensive care unit (ICU) patients in three geographically distant hospitals. We recover 120 high-quality metagenome-assembled genomes (MAGs) and associated plasmids without culturing. We detect divergent longitudinal microbiome dynamics and hospital-specific dominant opportunistic pathogens and resistomes in pneumonia patients. Diagnosed pneumonia and the ICU stay duration were associated with the abundance of specific antibiotic-resistance genes (ARGs). Moreover, CMEM can serve as a robust tool for genome-resolved analyses. MAG-based analyses reveal strain-specific resistome and virulome among opportunistic pathogen strains. Evolutionary analyses discover increased mobilome in prevailing opportunistic pathogens, highly conserved plasmids, and new recombination hotspots associated with conjugative elements and prophages. Integrative analysis with epidemiological data reveals frequent putative inter-patient strain transmissions in ICUs. In summary, we present a genome-resolved functional, transmission, and evolutionary landscape of the LRT microbiota in critically ill patients.

Multi-omics analysis reveals the mechanisms by which C6-HSL enhances the resistance of typical functional bacteria in activated sludge to low-temperature stress

Signaling molecules, particularly acyl-homoserine lactones (AHLs), can enhance microbial activity under low-temperature stress. However, the specific mechanisms underlying this effect remain unclear. This study identified a typical activated sludge functional bacterium that is sensitive to low temperatures and regulated by hexanoyl-L-homoserine lactone (C6-HSL), a representative of AHLs. It elucidates how C6-HSL modulates the bacterium's resistance to low-temperature stress. Experimental results indicated that C6-HSL significantly increased the levels of adenosine triphosphate (ATP), superoxide dismutase (SOD), peroxidase (POD) and glutathione peroxidase (GSH-Px) in strain LB-001 under low-temperature stress, while also decreasing the levels of reactive oxygen species (ROS). Additionally, C6-HSL markedly repaired the damage to cell membrane structure caused by low-temperature stress. At the genetic level, C6-HSL upregulated the expression of 20 key genes related to energy metabolism, antioxidation, and fatty acid synthesis. At the metabolic level, C6-HSL increased the levels of metabolites related to energy metabolism and antioxidation, boosted the content of unsaturated fatty acids, and reduced the content of saturated fatty acids. This study utilized C6-HSL and low-temperature induction in conjunction with 16S microbial diversity sequencing, genomics, transcriptomics, and metabolomics. These methods were employed to elucidate the molecular mechanisms by which exogenous C6-HSL regulates the resistance of activated sludge microbial communities to low-temperature stress. This research lays the foundation for the application of AHLs and cell communication in wastewater biological treatment, fostering deeper exploration and further innovation in related academic research.

DeepCheck: multitask learning aids in assessing microbial genome quality.

Metagenomic analyses facilitate theexploration of the microbial world, advancing our understanding of microbial roles in ecological and biological processes. A pivotal aspect of metagenomic analysis involves assessing the quality of metagenome-assembled genomes (MAGs), crucial for accurate biological insights. Current machine learning-based methods often treat completeness and contamination prediction as separate tasks, overlooking their inherent relationship and limiting models' generalization. In this study, we present DeepCheck, a multitasking deep learning framework for simultaneous prediction of MAG completeness and contamination. DeepCheck consistently outperforms existing tools in accuracy across various experimental settings and demonstrates comparable speed while maintaining high predictive accuracy even for new lineages. Additionally, we employ interpretable machine learning techniques to identify specific genes and pathways that drive the model's predictions, enabling independent investigation and assessment of these biological elements for deeper insights.