proGenomes2: an improved database for accurate and consistent habitat, taxonomic and functional annotations of prokaryotic genomes

Genomic analysis of three medieval parchments from German monasteries

In the last two decades there has been growing interest in the analysis of ancient DNA obtained from the parchment used in historic documents. The genetic insight that this data provides makes collections of historic documents an invaluable source for studying the development and spread of historical livestock populations. Additionally, the biological data may provide new information for the historical analysis that could be used to determine the provenance as well as the authenticity of these documents. In this study, we extracted DNA from three medieval parchments that were written in German monasteries in the twelfth century. The source animal of the parchments could be identified as cattle and we compared their genome sequences with those of modern populations that are part of the 1000 Bull Genomes Project. The three animals were found to carry mtDNA haplogroup T3 and show a closer genetic relationship to other historic animals than to modern breeds. We further identified 39 haplotypes and 132 SNPs variants, which are rare ( < 0.1 ) or even non-existent in modern breeds. Finally, the genetic distances between the parchment samples show a putative association with the dates when the documents were written, indicating the usefulness of genetic analysis for provenance research.

A catalog of small proteins from the global microbiome

Small open reading frames (smORFs) shorter than 100 codons are widespread and perform essential roles in microorganisms, where they encode proteins active in several cell functions, including signal pathways, stress response, and antibacterial activities. However, the ecology, distribution and role of small proteins in the global microbiome remain unknown. Here, we construct a global microbial smORFs catalog (GMSC) derived from 63,410 publicly available metagenomes across 75 distinct habitats and 87,920 high-quality isolate genomes. GMSC contains 965 million non-redundant smORFs with comprehensive annotations. We find that archaea harbor more smORFs proportionally than bacteria. We moreover provide a tool called GMSC-mapper to identify and annotate small proteins from microbial (meta)genomes. Overall, this publicly-available resource demonstrates the immense and underexplored diversity of small proteins.

Microbiome Dynamics and Functional Composition in Coelopa frigida (Diptera, Coelopidae): Insights into Trophic Specialization of Kelp Flies

Coelopidae (Diptera), known as kelp flies, exhibit an ecological association with beached kelp and other rotting seaweeds. This unique trophic specialization necessitates significant adaptations to overcome the limitations of an algal diet. We aimed to investigate whether the flies' microbiome could be one of these adaptive mechanisms. Our analysis focused on assessing composition and diversity of adult and larval microbiota of the kelp fly Coelopa frigida. Feeding habits of the larvae of this species have been subject of numerous studies, with debates whether they directly consume kelp or primarily feed on associated bacteria. By using a 16S rRNA metabarcoding approach, we found that the larval microbiota displayed considerably less diversity than adults, heavily dominated by only four operational taxonomic units (OTUs). Phylogenetic placement recovered the most dominant OTU of the larval microbiome, which is the source of more than half of all metabarcoding sequence reads, as an undescribed genus of Orbaceae (Gammaproteobacteria). Interestingly, this OTU is barely found among the 15 most abundant taxa of the adult microbiome, where it is responsible for less than 2% of the metabarcoding sequence reads. The other three OTUs dominating the larval microbiome have been assigned as Psychrobacter (Gammaproteobacteria), Wohlfahrtiimonas (Gammaproteobacteria), and Cetobacterium (Fusobacteriota). Moreover, we also uncovered a distinct shift in the functional composition between the larval and adult stages, where our taxonomic profiling suggests a significant decrease in functional diversity in larval samples. Our study offers insights into the microbiome dynamics and functional composition of Coelopa frigida.

Strain dynamics of contaminating bacteria modulate the yield of ethanol biorefineries

Bioethanol is a sustainable energy alternative and can contribute to global greenhouse-gas emission reductions by over 60%. Its industrial production faces various bottlenecks, including sub-optimal efficiency resulting from bacteria. Broad-spectrum removal of these contaminants results in negligible gains, suggesting that the process is shaped by ecological interactions within the microbial community. Here, we survey the microbiome across all process steps at two biorefineries, over three timepoints in a production season. Leveraging shotgun metagenomics and cultivation-based approaches, we identify beneficial bacteria and find improved outcome when yeast-to-bacteria ratios increase during fermentation. We provide a microbial gene catalogue which reveals bacteria-specific pathways associated with performance. We also show that Limosilactobacillus fermentum overgrowth lowers production, with one strain reducing yield by ~5% in laboratory fermentations, potentially due to its metabolite profile. Temperature is found to be a major driver for strain-level dynamics. Improved microbial management strategies could unlock environmental and economic gains in this US $ 60 billion industry enabling its wider adoption.

Airway microbiome signature accurately discriminates Mycobacterium tuberculosis infection status

Mycobacterium tuberculosis remains one of the deadliest infectious agents globally. Amidst efforts to control TB, long treatment duration, drug toxicity, and resistance underscore the need for novel therapeutic strategies. Despite advances in understanding the interplay between microbiome and disease in humans, the specific role of the microbiome in predicting disease susceptibility and discriminating infection status in tuberculosis still needs to be fully investigated. We investigated the impact of M.tb infection and M.tb-specific IFNγ immune responses on airway microbiome diversity by performing TB GeneXpert and QuantiFERON-GOLD assays during the follow-up phase of a longitudinal HIV-Lung Microbiome cohort of individuals recruited from two large independent cohorts in rural Uganda. M.tb rather than IFNγ immune response mainly drove a significant reduction in airway microbiome diversity. A microbiome signature comprising Streptococcus, Neisseria, Fusobacterium, Prevotella, Schaalia, Actinomyces, Cutibacterium, Brevibacillus, Microbacterium, and Beijerinckiacea accurately discriminated active TB from Latent TB and M.tb-uninfected individuals.

Putative genome contamination has minimal impact on the GTDB taxonomy

The Genome Taxonomy Database (GTDB) provides a species to domain classification of publicly available genomes based on average nucleotide identity (ANI) (for species) and a concatenated gene phylogeny normalized by evolutionary rates (for genus to phylum), which has been widely adopted by the scientific community. Here, we use the Genome UNClutterer (GUNC) software to identify putatively contaminated genomes in GTDB release 07-RS207. We found that GUNC reported 35,723 genomes as putatively contaminated, comprising 11.25 % of the 317,542 genomes in GTDB release 07-RS207. To assess the impact of this high level of inferred contamination on the delineation of taxa, we created 'clean' versions of the 34,846 putatively contaminated bacterial genomes by removing the most contaminated half. For each clean half, we re-calculated the ANI and concatenated gene phylogeny and found that only 77 (0.22 %) of the genomes were not consistent with their original classification. We conclude that the delineation of taxa in GTDB is robust to the putative contamination detected by GUNC.

A global survey of prokaryotic genomes reveals the eco-evolutionary pressures driving horizontal gene transfer

Horizontal gene transfer, the exchange of genetic material through means other than reproduction, is a fundamental force in prokaryotic genome evolution. Genomic persistence of horizontally transferred genes has been shown to be influenced by both ecological and evolutionary factors. However, there is limited availability of ecological information about species other than the habitats from which they were isolated, which has prevented a deeper exploration of ecological contributions to horizontal gene transfer. Here we focus on transfers detected through comparison of individual gene trees to the species tree, assessing the distribution of gene-exchanging prokaryotes across over a million environmental sequencing samples. By analysing detected horizontal gene transfer events, we show distinct functional profiles for recent versus old events. Although most genes transferred are part of the accessory genome, genes transferred earlier in evolution tend to be more ubiquitous within present-day species. We find that co-occurring, interacting and high-abundance species tend to exchange more genes. Finally, we show that host-associated specialist species are most likely to exchange genes with other host-associated specialist species, whereas species found across different habitats have similar gene exchange rates irrespective of their preferred habitat. Our study covers an unprecedented scale of integrated horizontal gene transfer and environmental information, highlighting broad eco-evolutionary trends.

Toxicological Characteristics of Bacterial Nanocellulose in an In Vivo Experiment-Part 1: The Systemic Effects

Bacterial nanocellulose (BNC) is being considered as a potential replacement for microcrystalline cellulose as a food additive and a source of dietary fiber due to its unique properties. However, studies on the risks of consuming BNC in food are limited, and it is not yet approved for use in food in the US, EU, and Russia.

AIM

This study aims to perform a toxicological and hygienic assessment of the safety of BNC in a subacute 8-week administration in rats.

METHODS

BNC was administered to male Wistar rats in doses of 0, 1.0, 10.0, and 100 mg/kg body weight for 8 weeks. Various parameters such as anxiety levels, cognitive function, organ masses, blood serum and liver biochemistry, oxidative stress markers, vitamin levels, antioxidant gene expression, and liver and kidney histology were evaluated.

RESULTS

Low and medium doses of BNC increased anxiety levels and liver glutathione, while high doses led to elevated LDL cholesterol, creatinine, and uric acid levels. Liver tissue showed signs of degeneration at high doses. BNC did not significantly affect vitamin levels.

CONCLUSION

The adverse effects of BNC are either not dose-dependent or fall within normal physiological ranges. Any effects on rats are likely due to micronutrient deficiencies or impacts on intestinal microbiota.

Clinically used broad-spectrum antibiotics compromise inflammatory monocyte-dependent antibacterial defense in the lung

Hospital-acquired pneumonia (HAP) is associated with high mortality and costs, and frequently caused by multidrug-resistant (MDR) bacteria. Although prior antimicrobial therapy is a major risk factor for HAP, the underlying mechanism remains incompletely understood. Here, we demonstrate that antibiotic therapy in hospitalized patients is associated with decreased diversity of the gut microbiome and depletion of short-chain fatty acid (SCFA) producers. Infection experiments with mice transplanted with patient fecal material reveal that these antibiotic-induced microbiota perturbations impair pulmonary defense against MDR Klebsiella pneumoniae. This is dependent on inflammatory monocytes (IMs), whose fatty acid receptor (FFAR)2/3-controlled and phagolysosome-dependent antibacterial activity is compromized in mice transplanted with antibiotic-associated patient microbiota. Collectively, we characterize how clinically relevant antibiotics affect antimicrobial defense in the context of human microbiota, and reveal a critical impairment of IM´s antimicrobial activity. Our study provides additional arguments for the rational use of antibiotics and offers mechanistic insights for the development of novel prophylactic strategies to protect high-risk patients from HAP.

Enhancing coevolutionary signals in protein-protein interaction prediction through clade-wise alignment integration

Protein-protein interactions (PPIs) play essential roles in most biological processes. The binding interfaces between interacting proteins impose evolutionary constraints that have successfully been employed to predict PPIs from multiple sequence alignments (MSAs). To construct MSAs, critical choices have to be made: how to ensure the reliable identification of orthologs, and how to optimally balance the need for large alignments versus sufficient alignment quality. Here, we propose a divide-and-conquer strategy for MSA generation: instead of building a single, large alignment for each protein, multiple distinct alignments are constructed under distinct clades in the tree of life. Coevolutionary signals are searched separately within these clades, and are only subsequently integrated using machine learning techniques. We find that this strategy markedly improves overall prediction performance, concomitant with better alignment quality. Using the popular DCA algorithm to systematically search pairs of such alignments, a genome-wide all-against-all interaction scan in a bacterial genome is demonstrated. Given the recent successes of AlphaFold in predicting direct PPIs at atomic detail, a discover-and-refine approach is proposed: our method could provide a fast and accurate strategy for pre-screening the entire genome, submitting to AlphaFold only promising interaction candidates-thus reducing false positives as well as computation time.

Insights into gut microbiomes in stem cell transplantation by comprehensive shotgun long-read sequencing

The gut microbiome is a diverse ecosystem, dominated by bacteria; however, fungi, phages/viruses, archaea, and protozoa are also important members of the gut microbiota. Exploration of taxonomic compositions beyond bacteria as well as an understanding of the interaction between the bacteriome with the other members is limited using 16S rDNA sequencing. Here, we developed a pipeline enabling the simultaneous interrogation of the gut microbiome (bacteriome, mycobiome, archaeome, eukaryome, DNA virome) and of antibiotic resistance genes based on optimized long-read shotgun metagenomics protocols and custom bioinformatics. Using our pipeline we investigated the longitudinal composition of the gut microbiome in an exploratory clinical study in patients undergoing allogeneic hematopoietic stem cell transplantation (alloHSCT; n = 31). Pre-transplantation microbiomes exhibited a 3-cluster structure, characterized by Bacteroides spp. /Phocaeicola spp., mixed composition and Enterococcus abundances. We revealed substantial inter-individual and temporal variabilities of microbial domain compositions, human DNA, and antibiotic resistance genes during the course of alloHSCT. Interestingly, viruses and fungi accounted for substantial proportions of microbiome content in individual samples. In the course of HSCT, bacterial strains were stable or newly acquired. Our results demonstrate the disruptive potential of alloHSCTon the gut microbiome and pave the way for future comprehensive microbiome studies based on long-read metagenomics.

Duplicated antibiotic resistance genes reveal ongoing selection and horizontal gene transfer in bacteria

Horizontal gene transfer (HGT) and gene duplication are often considered as separate mechanisms driving the evolution of new functions. However, the mobile genetic elements (MGEs) implicated in HGT can copy themselves, so positive selection on MGEs could drive gene duplications. Here, we use a combination of modeling and experimental evolution to examine this hypothesis and use long-read genome sequences of tens of thousands of bacterial isolates to examine its generality in nature. Modeling and experiments show that antibiotic selection can drive the evolution of duplicated antibiotic resistance genes (ARGs) through MGE transposition. A key implication is that duplicated ARGs should be enriched in environments associated with antibiotic use. To test this, we examined the distribution of duplicated ARGs in 18,938 complete bacterial genomes with ecological metadata. Duplicated ARGs are highly enriched in bacteria isolated from humans and livestock. Duplicated ARGs are further enriched in an independent set of 321 antibiotic-resistant clinical isolates. Our findings indicate that duplicated genes often encode functions undergoing positive selection and horizontal gene transfer in microbial communities.

Genomic attributes of airway commensal bacteria and mucosa

Microbial communities at the airway mucosal barrier are conserved and highly ordered, in likelihood reflecting co-evolution with human host factors. Freed of selection to digest nutrients, the airway microbiome underpins cognate management of mucosal immunity and pathogen resistance. We show here the initial results of systematic culture and whole-genome sequencing of the thoracic airway bacteria, identifying 52 novel species amongst 126 organisms that constitute 75% of commensals typically present in heathy individuals. Clinically relevant genes encode antimicrobial synthesis, adhesion and biofilm formation, immune modulation, iron utilisation, nitrous oxide (NO) metabolism and sphingolipid signalling. Using whole-genome content we identify dysbiotic features that may influence asthma and chronic obstructive pulmonary disease. We match isolate gene content to transcripts and metabolites expressed late in airway epithelial differentiation, identifying pathways to sustain host interactions with microbiota. Our results provide a systematic basis for decrypting interactions between commensals, pathogens, and mucosa in lung diseases of global significance.

Essential gene complement of Planctopirus limnophila from the bacterial phylum Planctomycetes

Planctopirus limnophila belongs to the bacterial phylum Planctomycetes, a relatively understudied lineage with remarkable cell biology features. Here, we report a genome-wide analysis of essential gene content in P. limnophila. We show that certain genes involved in peptidoglycan synthesis or cell division, which are essential in most other studied bacteria, are not essential for growth under laboratory conditions in this species. We identify essential genes likely involved in lipopolysaccharide biosynthesis, consistent with the view of Planctomycetes as diderm bacteria, and highlight other essential genes of unknown functions. Furthermore, we explore potential stages of evolution of the essential gene repertoire in Planctomycetes and the related phyla Verrucomicrobia and Chlamydiae. Our results provide insights into the divergent molecular and cellular biology of Planctomycetes.

Genome content predicts the carbon catabolic preferences of heterotrophic bacteria

Heterotrophic bacteria-bacteria that utilize organic carbon sources-are taxonomically and functionally diverse across environments. It is challenging to map metabolic interactions and niches within microbial communities due to the large number of metabolites that could serve as potential carbon and energy sources for heterotrophs. Whether their metabolic niches can be understood using general principles, such as a small number of simplified metabolic categories, is unclear. Here we perform high-throughput metabolic profiling of 186 marine heterotrophic bacterial strains cultured in media containing one of 135 carbon substrates to determine growth rates, lag times and yields. We show that, despite high variability at all levels of taxonomy, the catabolic niches of heterotrophic bacteria can be understood in terms of their preference for either glycolytic (sugars) or gluconeogenic (amino and organic acids) carbon sources. This preference is encoded by the total number of genes found in pathways that feed into the two modes of carbon utilization and can be predicted using a simple linear model based on gene counts. This allows for coarse-grained descriptions of microbial communities in terms of prevalent modes of carbon catabolism. The sugar-acid preference is also associated with genomic GC content and thus with the carbon-nitrogen requirements of their encoded proteome. Our work reveals how the evolution of bacterial genomes is structured by fundamental constraints rooted in metabolism.

Uncultured prokaryotic genomes in the spotlight: An examination of publicly available data from metagenomics and single-cell genomics

Owing to the ineffectiveness of traditional culture techniques for the vast majority of microbial species, culture-independent analyses utilizing next-generation sequencing and bioinformatics have become essential for gaining insight into microbial ecology and function. This mini-review focuses on two essential methods for obtaining genetic information from uncultured prokaryotes, metagenomics and single-cell genomics. We analyzed the registration status of uncultured prokaryotic genome data from major public databases and assessed the advantages and limitations of both the methods. Metagenomics generates a significant quantity of sequence data and multiple prokaryotic genomes using straightforward experimental procedures. However, in ecosystems with high microbial diversity, such as soil, most genes are presented as brief, disconnected contigs, and lack association of highly conserved genes and mobile genetic elements with individual species genomes. Although technically more challenging, single-cell genomics offers valuable insights into complex ecosystems by providing strain-resolved genomes, addressing issues in metagenomics. Recent technological advancements, such as long-read sequencing, machine learning algorithms, and in silico protein structure prediction, in combination with vast genomic data, have the potential to overcome the current technical challenges and facilitate a deeper understanding of uncultured microbial ecosystems and microbial dark matter genes and proteins. In light of this, it is imperative that continued innovation in both methods and technologies take place to create high-quality reference genome databases that will support future microbial research and industrial applications.

Computational exploration of the global microbiome for antibiotic discovery

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine learning-based approach to predict prokaryotic antimicrobial peptides (AMPs) by leveraging a vast dataset of 63,410 metagenomes and 87,920 microbial genomes. This led to the creation of AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, the majority of which were previously unknown. We observed that AMP production varies by habitat, with animal-associated samples displaying the highest proportion of AMPs compared to other habitats. Furthermore, within different human-associated microbiota, strain-level differences were evident. To validate our predictions, we synthesized and experimentally tested 50 AMPs, demonstrating their efficacy against clinically relevant drug-resistant pathogens both in vitro and in vivo. These AMPs exhibited antibacterial activity by targeting the bacterial membrane. Additionally, AMPSphere provides valuable insights into the evolutionary origins of peptides. In conclusion, our approach identified AMP sequences within prokaryotic microbiomes, opening up new avenues for the discovery of antibiotics.

PyHMMER: a Python library binding to HMMER for efficient sequence analysis

SUMMARY

PyHMMER provides Python integration of the popular profile Hidden Markov Model software HMMER via Cython bindings. This allows the annotation of protein sequences with profile HMMs and building new ones directly with Python. PyHMMER increases flexibility of use, allowing creating queries directly from Python code, launching searches, and obtaining results without I/O, or accessing previously unavailable statistics like uncorrected P-values. A new parallelization model greatly improves performance when running multithreaded searches, while producing the exact same results as HMMER.

AVAILABILITY AND IMPLEMENTATION

PyHMMER supports all modern Python versions (Python 3.6+) and similar platforms as HMMER (x86 or PowerPC UNIX systems). Pre-compiled packages are released via PyPI (https://pypi.org/project/pyhmmer/) and Bioconda (https://anaconda.org/bioconda/pyhmmer). The PyHMMER source code is available under the terms of the open-source MIT licence and hosted on GitHub (https://github.com/althonos/pyhmmer); its documentation is available on ReadTheDocs (https://pyhmmer.readthedocs.io).

Marginal specificity in protein interactions constrains evolution of a paralogous family

The evolution of novel functions in biology relies heavily on gene duplication and divergence, creating large paralogous protein families. Selective pressure to avoid detrimental cross-talk often results in paralogs that exhibit exquisite specificity for their interaction partners. But how robust or sensitive is this specificity to mutation? Here, using deep mutational scanning, we demonstrate that a paralogous family of bacterial signaling proteins exhibits marginal specificity, such that many individual substitutions give rise to substantial cross-talk between normally insulated pathways. Our results indicate that sequence space is locally crowded despite overall sparseness, and we provide evidence that this crowding has constrained the evolution of bacterial signaling proteins. These findings underscore how evolution selects for "good enough" rather than optimized phenotypes, leading to restrictions on the subsequent evolution of paralogs.

Fortuitously compatible protein surfaces primed allosteric control in cyanobacterial photoprotection

Highly specific interactions between proteins are a fundamental prerequisite for life, but how they evolve remains an unsolved problem. In particular, interactions between initially unrelated proteins require that they evolve matching surfaces. It is unclear whether such surface compatibilities can only be built by selection in small incremental steps, or whether they can also emerge fortuitously. Here, we used molecular phylogenetics, ancestral sequence reconstruction and biophysical characterization of resurrected proteins to retrace the evolution of an allosteric interaction between two proteins that act in the cyanobacterial photoprotection system. We show that this interaction between the orange carotenoid protein (OCP) and its unrelated regulator, the fluorescence recovery protein (FRP), evolved when a precursor of FRP was horizontally acquired by cyanobacteria. FRP's precursors could already interact with and regulate OCP even before these proteins first encountered each other in an ancestral cyanobacterium. The OCP-FRP interaction exploits an ancient dimer interface in OCP, which also predates the recruitment of FRP into the photoprotection system. Together, our work shows how evolution can fashion complex regulatory systems easily out of pre-existing components.

Cultivation-independent genomes greatly expand taxonomic-profiling capabilities of mOTUs across various environments

BACKGROUND

Taxonomic profiling is a fundamental task in microbiome research that aims to detect and quantify the relative abundance of microorganisms in biological samples. Available methods using shotgun metagenomic data generally depend on the deposition of sequenced and taxonomically annotated genomes, usually from cultures of isolated strains, in reference databases (reference genomes). However, the majority of microorganisms have not been cultured yet. Thus, a substantial fraction of microbial community members remains unaccounted for during taxonomic profiling, particularly in samples from underexplored environments. To address this issue, we developed the mOTU profiler, a tool that enables reference genome-independent species-level profiling of metagenomes. As such, it supports the identification and quantification of both "known" and "unknown" species based on a set of select marker genes.

RESULTS

We present mOTUs3, a command line tool that enables the profiling of metagenomes for >33,000 species-level operational taxonomic units. To achieve this, we leveraged the reconstruction of >600,000 draft genomes, most of which are metagenome-assembled genomes (MAGs), from diverse microbiomes, including soil, freshwater systems, and the gastrointestinal tract of ruminants and other animals, which we found to be underrepresented by reference genomes. Overall, two thirds of all species-level taxa lacked a reference genome. The cumulative relative abundance of these newly included taxa was low in well-studied microbiomes, such as the human body sites (6-11%). By contrast, they accounted for substantial proportions (ocean, freshwater, soil: 43-63%) or even the majority (pig, fish, cattle: 60-80%) of the relative abundance across diverse non-human-associated microbiomes. Using community-developed benchmarks and datasets, we found mOTUs3 to be more accurate than other methods and to be more congruent with 16S rRNA gene-based methods for taxonomic profiling. Furthermore, we demonstrate that mOTUs3 increases the resolution of well-known microbial groups into species-level taxa and helps identify new differentially abundant taxa in comparative metagenomic studies.

CONCLUSIONS

We developed mOTUs3 to enable accurate species-level profiling of metagenomes. Compared to other methods, it provides a more comprehensive view of prokaryotic community diversity, in particular for currently underexplored microbiomes. To facilitate comparative analyses by the research community, it is released with >11,000 precomputed profiles for publicly available metagenomes and is freely available at: https://github.com/motu-tool/mOTUs . Video Abstract.

Growth temperature and chromatinization in archaea

DNA in cells is associated with proteins that constrain its structure and affect DNA-templated processes including transcription and replication. HU and histones are the main constituents of chromatin in bacteria and eukaryotes, respectively, with few exceptions. Archaea, in contrast, have diverse repertoires of nucleoid-associated proteins (NAPs). To analyse the evolutionary and ecological drivers of this diversity, we combined a phylogenomic survey of known and predicted NAPs with quantitative proteomic data. We identify the Diaforarchaea as a hotbed of NAP gain and loss, and experimentally validate candidate NAPs in two members of this clade, Thermoplasma volcanium and Methanomassiliicoccus luminyensis. Proteomic analysis across a diverse sample of 19 archaea revealed that NAP investment varies from <0.03% to >5% of total protein. This variation is predicted by growth temperature. We propose that high levels of chromatinization have evolved as a mechanism to prevent uncontrolled helix denaturation at higher temperatures, with implications for the origin of chromatin in both archaea and eukaryotes.

Comparative genome analysis of mycobacteria focusing on tRNA and non-coding RNA

BACKGROUND

The Mycobacterium genus encompasses at least 192 named species, many of which cause severe diseases such as tuberculosis. Non-tuberculosis mycobacteria (NTM) can also infect humans and animals. Some are of emerging concern because they show high resistance to commonly used antibiotics while others are used and evaluated in bioremediation or included in anticancer vaccines.

RESULTS

We provide the genome sequences for 114 mycobacterial type strains and together with 130 available mycobacterial genomes we generated a phylogenetic tree based on 387 core genes and supported by average nucleotide identity (ANI) data. The 244 genome sequences cover most of the species constituting the Mycobacterium genus. The genome sizes ranged from 3.2 to 8.1 Mb with an average of 5.7 Mb, and we identified 14 new plasmids. Moreover, mycobacterial genomes consisted of phage-like sequences ranging between 0 and 4.64% dependent on mycobacteria while the number of IS elements varied between 1 and 290. Our data also revealed that, depending on the mycobacteria, the number of tRNA and non-coding (nc) RNA genes differ and that their positions on the chromosome varied. We identified a conserved core set of 12 ncRNAs, 43 tRNAs and 18 aminoacyl-tRNA synthetases among mycobacteria.

CONCLUSIONS

Phages, IS elements, tRNA and ncRNAs appear to have contributed to the evolution of the Mycobacterium genus where several tRNA and ncRNA genes have been horizontally transferred. On the basis of our phylogenetic analysis, we identified several isolates of unnamed species as new mycobacterial species or strains of known mycobacteria. The predicted number of coding sequences correlates with genome size while the number of tRNA, rRNA and ncRNA genes does not. Together these findings expand our insight into the evolution of the Mycobacterium genus and as such they establish a platform to understand mycobacterial pathogenicity, their evolution, antibiotic resistance/tolerance as well as the function and evolution of ncRNA among mycobacteria.

A faecal microbiota signature with high specificity for pancreatic cancer

BACKGROUND

Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression.

OBJECTIVE

To explore the faecal and salivary microbiota as potential diagnostic biomarkers.

METHODS

We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case-control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case-control study (n=76), in the validation phase.

RESULTS

Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19-9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation.

CONCLUSION

Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

Ancestral reconstruction of duplicated signaling proteins reveals the evolution of signaling specificity

Gene duplication is crucial to generating novel signaling pathways during evolution. However, it remains unclear how the redundant proteins produced by gene duplication ultimately acquire new interaction specificities to establish insulated paralogous signaling pathways. Here, we used ancestral sequence reconstruction to resurrect and characterize a bacterial two-component signaling system that duplicated in α-proteobacteria. We determined the interaction specificities of the signaling proteins that existed before and immediately after this duplication event and then identified key mutations responsible for establishing specificity in the two systems. Just three mutations, in only two of the four interacting proteins, were sufficient to establish specificity of the extant systems. Some of these mutations weakened interactions between paralogous systems to limit crosstalk. However, others strengthened interactions within a system, indicating that the ancestral interaction, although functional, had the potential to be strengthened. Our work suggests that protein-protein interactions with such latent potential may be highly amenable to duplication and divergence.

Critical Assessment of Metagenome Interpretation: the second round of challenges

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

This study presents the results of the second round of the Critical Assessment of Metagenome Interpretation challenges (CAMI II), which is a community-driven effort for comprehensively benchmarking tools for metagenomics data analysis.

Bacterial ribosome collision sensing by a MutS DNA repair ATPase paralogue

Ribosome stalling during translation is detrimental to cellular fitness, but how this is sensed and elicits recycling of ribosomal subunits and quality control of associated mRNA and incomplete nascent chains is poorly understood^1,2. Here we uncover Bacillus subtilis MutS2, a member of the conserved MutS family of ATPases that function in DNA mismatch repair³, as an unexpected ribosome-binding protein with an essential function in translational quality control. Cryo-electron microscopy analysis of affinity-purified native complexes shows that MutS2 functions in sensing collisions between stalled and translating ribosomes and suggests how ribosome collisions can serve as platforms to deploy downstream processes: MutS2 has an RNA endonuclease small MutS-related (SMR) domain, as well as an ATPase/clamp domain that is properly positioned to promote ribosomal subunit dissociation, which is a requirement both for ribosome recycling and for initiation of ribosome-associated protein quality control (RQC). Accordingly, MutS2 promotes nascent chain modification with alanine-tail degrons-an early step in RQC-in an ATPase domain-dependent manner. The relevance of these observations is underscored by evidence of strong co-occurrence of MutS2 and RQC genes across bacterial phyla. Overall, the findings demonstrate a deeply conserved role for ribosome collisions in mounting a complex response to the interruption of translation within open reading frames.

Contamination detection in genomic data: more is not enough

The decreasing cost of sequencing and concomitant augmentation of publicly available genomes have created an acute need for automated software to assess genomic contamination. During the last 6 years, 18 programs have been published, each with its own strengths and weaknesses. Deciding which tools to use becomes more and more difficult without an understanding of the underlying algorithms. We review these programs, benchmarking six of them, and present their main operating principles. This article is intended to guide researchers in the selection of appropriate tools for specific applications. Finally, we present future challenges in the developing field of contamination detection.

Assembling a Reference Phylogenomic Tree of Bacteria and Archaea by Summarizing Many Gene Phylogenies

Phylogenomics is the inference of phylogenetic trees based on multiple marker genes sampled in the genomes of interest. An important challenge in phylogenomics is the potential incongruence among the evolutionary histories of individual genes, which can be widespread in microorganisms due to the prevalence of horizontal gene transfer. This protocol introduces the procedures for building a phylogenetic tree of a large number of microbial genomes using a broad sampling of marker genes that are representative of whole-genome evolution. The protocol highlights the use of a gene tree summary method, which can effectively reconstruct the species tree while accounting for the topological conflicts among individual gene trees. The pipeline described in this protocol is scalable to tens of thousands of genomes while retaining high accuracy. We discussed multiple software tools, libraries, and scripts to enable convenient adoption of the protocol. The protocol is suitable for microbiology and microbiome studies based on public genomes and metagenomic data.

Towards the biogeography of prokaryotic genes

Microbial genes encode the majority of the functional repertoire of life on earth. However, despite increasing efforts in metagenomic sequencing of various habitats^1-3, little is known about the distribution of genes across the global biosphere, with implications for human and planetary health. Here we constructed a non-redundant gene catalogue of 303 million species-level genes (clustered at 95% nucleotide identity) from 13,174 publicly available metagenomes across 14 major habitats and use it to show that most genes are specific to a single habitat. The small fraction of genes found in multiple habitats is enriched in antibiotic-resistance genes and markers for mobile genetic elements. By further clustering these species-level genes into 32 million protein families, we observed that a small fraction of these families contain the majority of the genes (0.6% of families account for 50% of the genes). The majority of species-level genes and protein families are rare. Furthermore, species-level genes, and in particular the rare ones, show low rates of positive (adaptive) selection, supporting a model in which most genetic variability observed within each protein family is neutral or nearly neutral.

eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale

Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows for: 1) de novo gene prediction from raw contigs, 2) built-in pairwise orthology prediction, 3) fast protein domain discovery, and 4) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.

eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale

Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows for: 1) de novo gene prediction from raw contigs, 2) built-in pairwise orthology prediction, 3) fast protein domain discovery, and 4) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.

A Previously Undescribed Highly Prevalent Phage Identified in a Danish Enteric Virome Catalog

Gut viruses are important, yet often neglected, players in the complex human gut microbial ecosystem. Recently, the number of human gut virome studies has been increasing; however, we are still only scratching the surface of the immense viral diversity. In this study, 254 virus-enriched fecal metagenomes from 204 Danish subjects were used to generate the Danish Enteric Virome Catalog (DEVoC) containing 12,986 nonredundant viral scaffolds, of which the majority was previously undescribed, encoding 190,029 viral genes. The DEVoC was used to compare 91 healthy DEVoC gut viromes from children, adolescents, and adults that were used to create the DEVoC. Gut viromes of healthy Danish subjects were dominated by phages. While most phage genomes (PGs) only occurred in a single subject, indicating large virome individuality, 39 PGs were present in more than 10 healthy subjects. Among these 39 PGs, the prevalences of three PGs were associated with age. To further study the prevalence of these 39 prevalent PGs, 1,880 gut virome data sets of 27 studies from across the world were screened, revealing several age-, geography-, and disease-related prevalence patterns. Two PGs also showed a remarkably high prevalence worldwide-a crAss-like phage (20.6% prevalence), belonging to the tentative AlphacrAssvirinae subfamily, and a previously undescribed circular temperate phage infecting Bacteroides dorei (14.4% prevalence), called LoVEphage because it encodes lots of viral elements. Due to the LoVEphage's high prevalence and novelty, public data sets in which the LoVEphage was detected were de novo assembled, resulting in an additional 18 circular LoVEphage-like genomes (67.9 to 72.4 kb). IMPORTANCE Through generation of the DEVoC, we added numerous previously uncharacterized viral genomes and genes to the ever-increasing worldwide pool of human gut viromes. The DEVoC, the largest human gut virome catalog generated from consistently processed fecal samples, facilitated the analysis of the 91 healthy Danish gut viromes. Characterizing the biggest cohort of healthy gut viromes from children, adolescents, and adults to date confirmed the previously established high interindividual variation in human gut viromes and demonstrated that the effect of age on the gut virome composition was limited to the prevalence of specific phage (groups). The identification of a previously undescribed prevalent phage illustrates the usefulness of developing virome catalogs, and we foresee that the DEVoC will benefit future analysis of the roles of gut viruses in human health and disease.

Prevalence and Specificity of Chemoreceptor Profiles in Plant-Associated Bacteria

Chemosensory pathways are among the most abundant prokaryotic signal transduction systems, allowing bacteria to sense and respond to environmental stimuli. Signaling is typically initiated by the binding of specific molecules to the ligand binding domain (LBD) of chemoreceptor proteins (CRs). Although CRs play a central role in plant-microbiome interactions such as colonization and infection, little is known about their phylogenetic and ecological specificity. Here, we analyzed 82,277 CR sequences from 11,806 representative microbial species covering the whole prokaryotic phylogeny, and we classified them according to their LBD type using a de novo homology clustering method. Through phylogenomic analysis, we identified hundreds of LBDs that are found predominantly in plant-associated bacteria, including several LBDs specific to phytopathogens and plant symbionts. Functional annotation of our catalogue showed that many of the LBD clusters identified might constitute unknown types of LBDs. Moreover, we found that the taxonomic distribution of most LBD types that are specific to plant-associated bacteria is only partially explained by phylogeny, suggesting that lifestyle and niche adaptation are important factors in their selection. Finally, our results show that the profile of LBD types in a given genome is related to the lifestyle specialization, with plant symbionts and phytopathogens showing the highest number of niche-specific LBDs. The LBD catalogue and information on how to profile novel genomes are available at https://github.com/compgenomicslab/CRs.

IMPORTANCE Considering the enormous variety of LBDs at sensor proteins, an important question resides in establishing the forces that have driven their evolution and selection. We present here the first clear demonstration that environmental factors play an important role in the selection and evolution of LBDs. We were able to demonstrate the existence of LBD families that are highly enriched in plant-associated bacteria but show a wide phylogenetic spread. These findings offer a number of research opportunities in the field of single transduction, such as the exploration of similar relationships in chemoreceptors of bacteria with a different lifestyle, like those inhabiting or infecting the human intestine. Similarly, our results raise the question whether similar LBD types might be shared by members of different sensor protein families. Lastly, we provide a comprehensive catalogue of CRs classified by their LBD region that includes a large number of putative new LBD types.

'Whole Organism', Systems Biology, and Top-Down Criteria for Evaluating Scenarios for the Origin of Life

While most advances in the study of the origin of life on Earth (OoLoE) are piecemeal, tested against the laws of chemistry and physics, ultimately the goal is to develop an overall scenario for life's origin(s). However, the dimensionality of non-equilibrium chemical systems, from the range of possible boundary conditions and chemical interactions, renders the application of chemical and physical laws difficult. Here we outline a set of simple criteria for evaluating OoLoE scenarios. These include the need for containment, steady energy and material flows, and structured spatial heterogeneity from the outset. The Principle of Continuity, the fact that all life today was derived from first life, suggests favoring scenarios with fewer non-analog (not seen in life today) to analog (seen in life today) transitions in the inferred first biochemical pathways. Top-down data also indicate that a complex metabolism predated ribozymes and enzymes, and that full cellular autonomy and motility occurred post-LUCA. Using these criteria, we find the alkaline hydrothermal vent microchamber complex scenario with a late evolving exploitation of the natural occurring pH (or Na⁺ gradient) by ATP synthase the most compelling. However, there are as yet so many unknowns, we also advocate for the continued development of as many plausible scenarios as possible.

GUNC: detection of chimerism and contamination in prokaryotic genomes

Genomes are critical units in microbiology, yet ascertaining quality in prokaryotic genome assemblies remains a formidable challenge. We present GUNC (the Genome UNClutterer), a tool that accurately detects and quantifies genome chimerism based on the lineage homogeneity of individual contigs using a genome's full complement of genes. GUNC complements existing approaches by targeting previously underdetected types of contamination: we conservatively estimate that 5.7% of genomes in GenBank, 5.2% in RefSeq, and 15-30% of pre-filtered "high-quality" metagenome-assembled genomes in recent studies are undetected chimeras. GUNC provides a fast and robust tool to substantially improve prokaryotic genome quality.

Keeping up with the Bacillus cereus group: taxonomy through the genomics era and beyond

The Bacillus cereus group, also known as B. cereus sensu lato (s.l.), is a species complex that contains numerous closely related lineages, which vary in their ability to cause illness in humans and animals. The classification of B. cereus s.l. isolates into species-level taxonomic units is thus essential for informing public health and food safety efforts. However, taxonomic classification of these organisms is challenging. Numerous-often conflicting-taxonomic changes to the group have been proposed over the past two decades, making it difficult to remain up to date. In this review, we discuss the major nomenclatural changes that have accumulated in the B. cereus s.l. taxonomic space prior to 2020, particularly in the genomic sequencing era, and outline the resulting problems. We discuss several contemporary taxonomic frameworks as applied to B. cereus s.l., including (i) phenotypic, (ii) genomic, and (iii) hybrid nomenclatural frameworks, and we discuss the advantages and disadvantages of each. We offer suggestions as to how readers can avoid B. cereus s.l. taxonomic ambiguities, regardless of the nomenclatural framework(s) they choose to employ. Finally, we discuss future directions and open problems in the B. cereus s.l. taxonomic realm, including those that cannot be solved by genomic approaches alone.

Metformin Strongly Affects Gut Microbiome Composition in High-Fat Diet-Induced Type 2 Diabetes Mouse Model of Both Sexes

Effects of metformin, the first-line drug for type 2 diabetes therapy, on gut microbiome composition in type 2 diabetes have been described in various studies both in human subjects and animals. However, the details of the molecular mechanisms of metformin action have not been fully understood. Moreover, there is a significant lack of information on how metformin affects gut microbiome composition in female mouse models, depending on sex and metabolic status in well controlled experimental setting. Our study aimed to examine metformin-induced alterations in gut microbiome diversity, composition, and functional implications of high-fat diet-induced type 2 diabetes mouse model, using, for the first time in mice study, the shotgun metagenomic sequencing that allows estimation of microorganisms at species level. We also employed a randomized block, factorial study design, and including 24 experimental units allocated to 8 treatment groups to systematically evaluate the effect of sex and metabolic status on metformin interaction with microbiome. We used DNA obtained from fecal samples representing gut microbiome before and after ten weeks-long metformin treatment. We identified 100 metformin-related differentially abundant species in high-fat diet-fed mice before and after the treatment, with most of the species relative abundances increased. In contrast, no significant changes were observed in control diet-fed mice. Functional analysis targeted to carbohydrate, lipid, and amino acid metabolism pathways revealed 14 significantly altered hierarchies. We also observed sex-specific differences in response to metformin treatment. Males experienced more pronounced changes in metabolic markers, while in females the extent of changes in gut microbiome representatives was more marked, indicated by 53 differentially abundant species with more remarkable Log fold changes compared to the combined-sex analysis. The same pattern manifested regarding the functional analysis, where we discovered 5 significantly affected hierarchies in female groups but not in males. Our results suggest that both sexes of animals should be included in future studies focusing on metformin effects on the gut microbiome.

Metage2Metabo, microbiota-scale metabolic complementarity for the identification of key species

To capture the functional diversity of microbiota, one must identify metabolic functions and species of interest within hundreds or thousands of microorganisms. We present Metage2Metabo (M2M) a resource that meets the need for de novo functional screening of genome-scale metabolic networks (GSMNs) at the scale of a metagenome, and the identification of critical species with respect to metabolic cooperation. M2M comprises a flexible pipeline for the characterisation of individual metabolisms and collective metabolic complementarity. In addition, M2M identifies key species, that are meaningful members of the community for functions of interest. We demonstrate that M2M is applicable to collections of genomes as well as metagenome-assembled genomes, permits an efficient GSMN reconstruction with Pathway Tools, and assesses the cooperation potential between species. M2M identifies key organisms by reducing the complexity of a large-scale microbiota into minimal communities with equivalent properties, suitable for further analyses.

From bag-of-genes to bag-of-genomes: metabolic modelling of communities in the era of metagenome-assembled genomes

Metagenomic sequencing of complete microbial communities has greatly enhanced our understanding of the taxonomic composition of microbiotas. This has led to breakthrough developments in bioinformatic disciplines such as assembly, gene clustering, metagenomic binning of species genomes and the discovery of an incredible, so far undiscovered, taxonomic diversity. However, functional annotations and estimating metabolic processes from single species - or communities - is still challenging. Earlier approaches relied mostly on inferring the presence of key enzymes for metabolic pathways in the whole metagenome, ignoring the genomic context of such enzymes, resulting in the 'bag-of-genes' approach to estimate functional capacities of microbiotas. Here, we review recent developments in metagenomic bioinformatics, with a special focus on emerging technologies to simulate and estimate metabolic information, that can be derived from metagenomic assembled genomes. Genome-scale metabolic models can be used to model the emergent properties of microbial consortia and whole communities, and the progress in this area is reviewed. While this subfield of metagenomics is still in its infancy, it is becoming evident that there is a dire need for further bioinformatic tools to address the complex combinatorial problems in modelling the metabolism of large communities as a 'bag-of-genomes'.

Disentangling the impact of environmental and phylogenetic constraints on prokaryotic within-species diversity

Microbial organisms inhabit virtually all environments and encompass a vast biological diversity. The pangenome concept aims to facilitate an understanding of diversity within defined phylogenetic groups. Hence, pangenomes are increasingly used to characterize the strain diversity of prokaryotic species. To understand the interdependence of pangenome features (such as the number of core and accessory genes) and to study the impact of environmental and phylogenetic constraints on the evolution of conspecific strains, we computed pangenomes for 155 phylogenetically diverse species (from ten phyla) using 7,000 high-quality genomes to each of which the respective habitats were assigned. Species habitat ubiquity was associated with several pangenome features. In particular, core-genome size was more important for ubiquity than accessory genome size. In general, environmental preferences had a stronger impact on pangenome evolution than phylogenetic inertia. Environmental preferences explained up to 49% of the variance for pangenome features, compared with 18% by phylogenetic inertia. This observation was robust when the dataset was extended to 10,100 species (59 phyla). The importance of environmental preferences was further accentuated by convergent evolution of pangenome features in a given habitat type across different phylogenetic clades. For example, the soil environment promotes expansion of pangenome size, while host-associated habitats lead to its reduction. Taken together, we explored the global principles of pangenome evolution, quantified the influence of habitat, and phylogenetic inertia on the evolution of pangenomes and identified criteria governing species ubiquity and habitat specificity.