PlasForest: a homology-based random forest classifier for plasmid detection in genomic datasets

The interplay between mobilome and resistome in Staphylococcus aureus

Antibiotic resistance genes (ARGs) in Staphylococcus aureus can disseminate vertically through successful clones, but also horizontally through the transfer of genes conveyed by mobile genetic elements (MGEs). Even though underexplored, MGE/ARG associations in S. aureus favor the emergence of multidrug-resistant clones, which are challenging therapeutic success in both human and animal health. This study investigated the interplay between the mobilome and the resistome of more than 10,000 S. aureus genomes from human and animal origin. The analysis revealed a remarkable diversity of MGEs and ARGs, with plasmids and transposons being the main carriers of ARGs. Numerous MGE/ARG associations were identified, suggesting that MGEs play a critical role in the dissemination of resistance. A high degree of similarity was observed in MGE/ARG associations between human and animal isolates, highlighting the potential for unrestricted spread of ARGs between hosts. Our results showed that in parallel to clonal expansion, MGEs and their associated ARGs can spread across different strain types sequence types (STs), favoring the evolution of these clones and their adaptation in selective environments. The high variability of MGE/ARG associations within individual STs and their spread across several STs highlight the crucial role of MGEs in shaping the S. aureus resistome. Overall, this study provides valuable insights into the complex interplay between MGEs and ARGs in S. aureus, emphasizing the need to elucidate the mechanisms governing the epidemic success of MGEs, particularly those implicated in ARG transfer.IMPORTANCEThe research presented in this article highlights the importance of understanding the interactions between mobile genetic elements (MGEs) and antibiotic resistance genes (ARGs) carried by Staphylococcus aureus, a versatile bacterium that can be both a harmless commensal and a dangerous pathogen for humans and animals. S. aureus has a great capacity to acquire and disseminate ARGs, enabling efficient adaption to various environmental or clinical conditions. By analyzing a large data set of S. aureus genomes, we highlighted the substantial role of MGEs, particularly plasmids and transposons, in disseminating ARGs within and between S. aureus populations, bypassing host barriers. Given that multidrug-resistant S. aureus strains are classified as a high-priority pathogen by global health organizations, this knowledge is crucial for understanding the complex dynamics of transmission of antibiotic resistance in this species.

Genome Analysis of Potential Probiotic Levilactobacillus brevis AcCh91 Isolated from Indian Home-Made Fermented Milk Product (Chhurpi)

Consumption of naturally fermented milk (NFM) products is the dietary culture in India. The mountainous people of Arunachal Pradesh in India prepare the assorted artisanal home-made NFM products from cow and yak milk. Previously, we isolated and identified 76 strains of lactic acid bacteria (LAB) from NFM products of Arunachal Pradesh, viz. mar, chhurpi and churkam. We hypothesized that some of these LAB strains may possess probiotic potentials; hence, we investigated the probiotic potentials of these strains. On the basis of in vitro and genetic screening for probiotic attributes including haemolytic ability, 20 LAB strains were selected out of 76 strains, for further analysis. Using in silico analysis, viz. multivariate heatmap and PCA (principal component analysis) biplot, Levilactobacillus brevis AcCh91 was selected as the most promising probiotic strain, which was further characterized by the whole-genome analysis. Lev. brevis AcCh91 showed the highest survival rate of 93.38% in low pH and 86.68 ± 2.69% in low bile and the highest hydrophobicity average of 86.34 ± 5.53%. This strain also showed auto-aggregation and co-aggregation with antimicrobial properties against the pathogens, showed ability to produce beta-galactosidase and cholesterol reduction property and, most importantly, produced GABA, an important psychobiotic element. Genomic analysis of Lev. brevis AcCh91 showed the presence of genes corresponding to GABA, vitamins, amino acids, cholesterol reduction, immunomodulation, bioactive peptides and antioxidant activity. The absence of antimicrobial-resistant genes and virulence factors was observed. Hence, genome analysis supports the probiotic potentials of Lev. brevis AcCh91, which may be further investigated to understand its health-promoting properties.

Insights into the ecology of the infant gut plasmidome

Plasmids are small DNA molecules that enable bacteria to share beneficial traits, influencing microbial communities. However, their role within the human gut microbiome remains largely unknown. In this study, we investigate the gut microbiomes of 34 mother-child cohorts, employing a plasmid analysis workflow to understand the impact of plasmids on the gut microbiome. We create a plasmid phylogenetic tree, devise a method for assigning plasmid hosts, and examine potential plasmid transfer networks. Our research discovers a wide variety of previously unidentified plasmid sequences, indicating that current databases do not fully represent the gut plasmidome. Interestingly, infants display greater plasmid diversity compared to mothers and other healthy adults. We find that Bacteroidota, a major bacterial phylum, serves as the primary host for gut plasmids and plays a dominant role in gut plasmid transfer events. Additionally, plasmids broaden the genetic capabilities of bacteria, with their influence on bacterial function becoming more apparent as children's gut microbiomes develop. This study sheds light on the role of plasmids in the infant gut microbiome, making a significant contribution to our understanding of plasmid biology.

PlasmidHunter: accurate and fast prediction of plasmid sequences using gene content profile and machine learning

Plasmids are extrachromosomal DNA found in microorganisms. They often carry beneficial genes that help bacteria adapt to harsh conditions. Plasmids are also important tools in genetic engineering, gene therapy, and drug production. However, it can be difficult to identify plasmid sequences from chromosomal sequences in genomic and metagenomic data. Here, we have developed a new tool called PlasmidHunter, which uses machine learning to predict plasmid sequences based on gene content profile. PlasmidHunter can achieve high accuracies (up to 97.6%) and high speeds in benchmark tests including both simulated contigs and real metagenomic plasmidome data, outperforming other existing tools.

Plasmids in the human gut reveal neutral dispersal and recombination that is overpowered by inflammatory diseases

Plasmids are pivotal in driving bacterial evolution through horizontal gene transfer. Here, we investigated 3467 human gut microbiome samples across continents and disease states, analyzing 11,086 plasmids. Our analyses reveal that plasmid dispersal is predominantly stochastic, indicating neutral processes as the primary driver of their wide distribution. We find that only 20-25% of plasmid DNA is being selected in various disease states, constraining its distribution across hosts. Selective pressures shape specific plasmid segments with distinct ecological functions, influenced by plasmid mobilization lifestyle, antibiotic usage, and inflammatory gut diseases. Notably, these elements are more commonly shared within groups of individuals with similar health conditions, such as Inflammatory Bowel Disease (IBD), regardless of geographic location across continents. These segments contain essential genes such as iron transport mechanisms- a distinctive gut signature of IBD that impacts the severity of inflammation. Our findings shed light on mechanisms driving plasmid dispersal and selection in the human gut, highlighting their role as carriers of vital gene pools impacting bacterial hosts and ecosystem dynamics.

Adverse Environmental Perturbations May Threaten Kelp Farming Sustainability by Exacerbating Enterobacterales Diseases

Globally kelp farming is gaining attention to mitigate land-use pressures and achieve carbon neutrality. However, the influence of environmental perturbations on kelp farming remains largely unknown. Recently, a severe disease outbreak caused extensive kelp mortality in Sanggou Bay, China, one of the world's largest high-density kelp farming areas. Here, through in situ investigations and simulation experiments, we find indications that an anomalously dramatic increase in elevated coastal seawater light penetration may have contributed to dysbiosis in the kelp Saccharina japonica's microbiome. This dysbiosis promoted the proliferation of opportunistic pathogenic Enterobacterales, mainly including the genera Colwellia and Pseudoalteromonas. Using transcriptomic analyses, we revealed that high-light conditions likely induced oxidative stress in kelp, potentially facilitating opportunistic bacterial Enterobacterales attack that activates a terrestrial plant-like pattern recognition receptor system in kelp. Furthermore, we uncover crucial genotypic determinants of Enterobacterales dominance and pathogenicity within kelp tissue, including pathogen-associated molecular patterns, potential membrane-damaging toxins, and alginate and mannitol lysis capability. Finally, through analysis of kelp-associated microbiome data sets under the influence of ocean warming and acidification, we conclude that such Enterobacterales favoring microbiome shifts are likely to become more prevalent in future environmental conditions. Our study highlights the need for understanding complex environmental influences on kelp health and associated microbiomes for the sustainable development of seaweed farming.

Effect of a probiotic and an antibiotic on the mobilome of the porcine microbiota

Introduction: To consider the growing health issues caused by antibiotic resistance from a "one health" perspective, the contribution of meat production needs to be addressed. While antibiotic resistance is naturally present in microbial communities, the treatment of farm animals with antibiotics causes an increase in antibiotic resistance genes (ARG) in the gut microbiome. Pigs are among the most prevalent animals in agriculture; therefore, reducing the prevalence of antibiotic-resistant bacteria in the pig gut microbiome could reduce the spread of antibiotic resistance. Probiotics are often studied as a way to modulate the microbiome and are, therefore, an interesting way to potentially decrease antibiotic resistance. Methods: To assess the efficacy of a probiotic to reduce the prevalence of ARGs in the pig microbiome, six pigs received either treatment with antibiotics (tylvalosin), probiotics (Pediococcus acidilactici MA18/5M; Biopower® PA), or a combination of both. Their faeces and ileal digesta were collected and DNA was extracted for whole genome shotgun sequencing. The reads were compared with taxonomy and ARG databases to identify the taxa and resistance genes in the samples. Results: The results showed that the ARG profiles in the faeces of the antibiotic and combination treatments were similar, and both were different from the profiles of the probiotic treatment (p < 0.05). The effects of the treatments were different in the digesta and faeces. Many macrolide resistance genes were detected in a higher proportion in the microbiome of the pigs treated with antibiotics or the combination of probiotics and antibiotics. Resistance-carrying conjugative plasmids and horizontal transfer genes were also amplified in faeces samples for the antibiotic and combined treatments. There was no effect of treatment on the short chain fatty acid content in the digesta or the faeces. Conclusion: There is no positive effect of adding probiotics to an antibiotic treatment when these treatments are administered simultaneously.

MOBFinder: a tool for mobilization typing of plasmid metagenomic fragments based on a language model

BACKGROUND

Mobilization typing (MOB) is a classification scheme for plasmid genomes based on their relaxase gene. The host ranges of plasmids of different MOB categories are diverse, and MOB is crucial for investigating plasmid mobilization, especially the transmission of resistance genes and virulence factors. However, MOB typing of plasmid metagenomic data is challenging due to the highly fragmented characteristics of metagenomic contigs.

RESULTS

We developed MOBFinder, an 11-class classifier, for categorizing plasmid fragments into 10 MOB types and a nonmobilizable category. We first performed MOB typing to classify complete plasmid genomes according to relaxase information and then constructed an artificial benchmark dataset of plasmid metagenomic fragments (PMFs) from those complete plasmid genomes whose MOB types are well annotated. Next, based on natural language models, we used word vectors to characterize the PMFs. Several random forest classification models were trained and integrated to predict fragments of different lengths. Evaluating the tool using the benchmark dataset, we found that MOBFinder outperforms previous tools such as MOBscan and MOB-suite, with an overall accuracy approximately 59% higher than that of MOB-suite. Moreover, the balanced accuracy, harmonic mean, and F1-score reached up to 99% for some MOB types. When applied to a cohort of patients with type 2 diabetes (T2D), MOBFinder offered insights suggesting that the MOBF type plasmid, which is widely present in Escherichia and Klebsiella, and the MOBQ type plasmid might accelerate antibiotic resistance transmission in patients with T2D.

CONCLUSIONS

To the best of our knowledge, MOBFinder is the first tool for MOB typing of PMFs. The tool is freely available at https://github.com/FengTaoSMU/MOBFinder.

Plasmid genomic epidemiology of blaKPC carbapenemase-producing Enterobacterales in Canada, 2010-2021

Carbapenems are considered last-resort antibiotics for the treatment of infections caused by multidrug-resistant Enterobacterales, but carbapenem resistance due to acquisition of carbapenemase genes is a growing threat that has been reported worldwide. Klebsiella pneumoniae carbapenemase (blaKPC) is the most common type of carbapenemase in Canada and elsewhere; it can hydrolyze penicillins, cephalosporins, aztreonam, and carbapenems and is frequently found on mobile plasmids in the Tn4401 transposon. This means that alongside clonal expansion, blaKPC can disseminate through plasmid- and transposon-mediated horizontal gene transfer. We applied whole genome sequencing to characterize the molecular epidemiology of 829 blaKPC carbapenemase-producing isolates collected by the Canadian Nosocomial Infection Surveillance Program from 2010 to 2021. Using a combination of short-read and long-read sequencing, we obtained 202 complete and circular blaKPC-encoding plasmids. Using MOB-suite, 10 major plasmid clusters were identified from this data set which represented 87% (175/202) of the Canadian blaKPC-encoding plasmids. We further estimated the genomic location of incomplete blaKPC-encoding contigs and predicted a plasmid cluster for 95% (603/635) of these. We identified different patterns of carbapenemase mobilization across Canada related to different plasmid clusters, including clonal transmission of IncF-type plasmids (108/829, 13%) in K. pneumoniae clonal complex 258 and novel repE(pEh60-7) plasmids (44/829, 5%) in Enterobacter hormaechei ST316, and horizontal transmission of IncL/M (142/829, 17%) and IncN-type plasmids (149/829, 18%) across multiple genera. Our findings highlight the diversity of blaKPC genomic loci and indicate that multiple, distinct plasmid clusters have contributed to blaKPC spread and persistence in Canada.

Clinically relevant antibiotic resistance genes are linked to a limited set of taxa within gut microbiome worldwide

The acquisition of antimicrobial resistance (AR) genes has rendered important pathogens nearly or fully unresponsive to antibiotics. It has been suggested that pathogens acquire AR traits from the gut microbiota, which collectively serve as a global reservoir for AR genes conferring resistance to all classes of antibiotics. However, only a subset of AR genes confers resistance to clinically relevant antibiotics, and, although these AR gene profiles are well-characterized for common pathogens, less is known about their taxonomic associations and transfer potential within diverse members of the gut microbiota. We examined a collection of 14,850 human metagenomes and 1666 environmental metagenomes from 33 countries, in addition to nearly 600,000 isolate genomes, to gain insight into the global prevalence and taxonomic range of clinically relevant AR genes. We find that several of the most concerning AR genes, such as those encoding the cephalosporinase CTX-M and carbapenemases KPC, IMP, NDM, and VIM, remain taxonomically restricted to Proteobacteria. Even cfiA, the most common carbapenemase gene within the human gut microbiome, remains tightly restricted to Bacteroides, despite being found on a mobilizable plasmid. We confirmed these findings in gut microbiome samples from India, Honduras, Pakistan, and Vietnam, using a high-sensitivity single-cell fusion PCR approach. Focusing on a set of genes encoding carbapenemases and cephalosporinases, thus far restricted to Bacteroides species, we find that few mutations are required for efficacy in a different phylum, raising the question of why these genes have not spread more widely. Overall, these data suggest that globally prevalent, clinically relevant AR genes have not yet established themselves across diverse commensal gut microbiota.

plASgraph2: using graph neural networks to detect plasmid contigs from an assembly graph

Identification of plasmids from sequencing data is an important and challenging problem related to antimicrobial resistance spread and other One-Health issues. We provide a new architecture for identifying plasmid contigs in fragmented genome assemblies built from short-read data. We employ graph neural networks (GNNs) and the assembly graph to propagate the information from nearby nodes, which leads to more accurate classification, especially for short contigs that are difficult to classify based on sequence features or database searches alone. We trained plASgraph2 on a data set of samples from the ESKAPEE group of pathogens. plASgraph2 either outperforms or performs on par with a wide range of state-of-the-art methods on testing sets of independent ESKAPEE samples and samples from related pathogens. On one hand, our study provides a new accurate and easy to use tool for contig classification in bacterial isolates; on the other hand, it serves as a proof-of-concept for the use of GNNs in genomics. Our software is available at https://github.com/cchauve/plasgraph2 and the training and testing data sets are available at https://github.com/fmfi-compbio/plasgraph2-datasets.

Systematic bioprospection for cellulolytic actinomycetes in the Chihuahuan Desert: isolation and enzymatic profiling

The quest for microbial cellulases has intensified as a response to global challenges in biofuel production. The efficient deconstruction of lignocellulosic biomass holds promise for generating valuable products in various industries such as food, textile, and detergents. This article presents a systematic bioprospection aimed at isolating actinomycetes with exceptional cellulose deconstruction capabilities. Our methodology explored the biodiverse oligotrophic region of Cuatro Cienegas, Coahuila, within the Chihuahuan Desert. Among the evaluated actinomycetes collection, 78% exhibited cellulolytic activity. Through a meticulous screening process based on enzymatic index evaluation, we identified a highly cellulolytic Streptomyces strain for further investigation. Submerged fermentation of this strain revealed an endoglucanase enzymatic activity of 149 U/mg. Genomic analysis of strain Streptomyces sp. STCH565-A revealed unique configurations of carbohydrate-active enzyme (CAZyme) genes, underscoring its potential for lignocellulosic bioconversion applications. These findings not only highlight the significance of the Chihuahuan Desert as a rich source of cellulolytic microorganisms but also offer insights into the systematic exploration and selection of high-performing cellulolytic microorganisms for application in diverse environmental contexts. In conclusion, our bioprospecting study lays a foundation for harnessing the cellulolytic potential of actinomycetes from the Chihuahuan Desert, with implications for advancing cellulose deconstruction processes in various industries. The findings can serve as a blueprint for future bioprospecting efforts in different regions, facilitating the targeted discovery of microorganisms with exceptional cellulosic deconstruction capabilities.

Comparative Genomics Reveals Novel Species and Insights into the Biotechnological Potential, Virulence, and Resistance of Alcaligenes

Alcaligenes is a cosmopolitan bacterial genus that exhibits diverse properties which are beneficial to plants. However, the genomic versatility of Alcaligenes has also been associated with the ability to cause opportunistic infections in humans, raising concerns about the safety of these microorganisms in biotechnological applications. Here, we report an in-depth comparative analysis of Alcaligenes species using all publicly available genomes to investigate genes associated with species, biotechnological potential, virulence, and resistance to multiple antibiotics. Phylogenomic analysis revealed that Alcaligenes consists of at least seven species, including three novel species. Pan-GWAS analysis uncovered 389 species-associated genes, including cold shock proteins (e.g., cspA) and aquaporins (e.g., aqpZ) found exclusively in the water-isolated species, Alcaligenes aquatilis. Functional annotation of plant-growth-promoting traits revealed enrichment of genes for auxin biosynthesis, siderophores, and organic acids. Genes involved in xenobiotic degradation and toxic metal tolerance were also identified. Virulome and resistome profiles provide insights into selective pressures exerted in clinical settings. Taken together, the results presented here provide the grounds for more detailed clinical and ecological studies of the genus Alcaligenes.

PLASMe: a tool to identify PLASMid contigs from short-read assemblies using transformer

Plasmids are mobile genetic elements that carry important accessory genes. Cataloging plasmids is a fundamental step to elucidate their roles in promoting horizontal gene transfer between bacteria. Next generation sequencing (NGS) is the main source for discovering new plasmids today. However, NGS assembly programs tend to return contigs, making plasmid detection difficult. This problem is particularly grave for metagenomic assemblies, which contain short contigs of heterogeneous origins. Available tools for plasmid contig detection still suffer from some limitations. In particular, alignment-based tools tend to miss diverged plasmids while learning-based tools often have lower precision. In this work, we develop a plasmid detection tool PLASMe that capitalizes on the strength of alignment and learning-based methods. Closely related plasmids can be easily identified using the alignment component in PLASMe while diverged plasmids can be predicted using order-specific Transformer models. By encoding plasmid sequences as a language defined on the protein cluster-based token set, Transformer can learn the importance of proteins and their correlation through positionally token embedding and the attention mechanism. We compared PLASMe and other tools on detecting complete plasmids, plasmid contigs, and contigs assembled from CAMI2 simulated data. PLASMe achieved the highest F1-score. After validating PLASMe on data with known labels, we also tested it on real metagenomic and plasmidome data. The examination of some commonly used marker genes shows that PLASMe exhibits more reliable performance than other tools.

Global transmission of broad-host-range plasmids derived from the human gut microbiome

Broad-host-range (BHR) plasmids in human gut bacteria are of considerable interest for their ability to mediate horizontal gene transfer (HGT) across large phylogenetic distance. However, the human gut plasmids, especially the BHR plasmids, remain largely unknown. Here, we identified the plasmids in the draft genomes of gut bacterial isolates from Chinese and American donors, resulting in 5372 plasmid-like clusters (PLCs), of which, 820 PLCs (comPLCs) were estimated with > 60% completeness genomes and only 155 (18.9%) were classified to known replicon types (n = 37). We observed that 175 comPLCs had a broad host range across distinct bacterial genera, of which, 71 were detected in at least two human populations of Chinese, American, Spanish, and Danish, and 13 were highly prevalent (>10%) in at least one human population. Haplotype analyses of two widespread PLCs demonstrated their spreading and evolutionary trajectory, suggesting frequent and recent exchanges of the BHR plasmids in environments. In conclusion, we obtained a large collection of plasmid sequences in human gut bacteria and demonstrated that a subset of the BHR plasmids can be transmitted globally, thus facilitating extensive HGT (e.g. antibiotic resistance genes) events. This study highlights the potential implications of the plasmids for global human health.

The Role of Mobile Genetic Elements in Virulence Factor Carriage from Symptomatic and Asymptomatic Cases of Escherichia coli Bacteriuria

Uropathogenic Escherichia coli (UPEC) is extremely diverse genotypically and phenotypically. Individual strains can variably carry diverse virulence factors, making it challenging to define a molecular signature for this pathotype. For many bacterial pathogens, mobile genetic elements (MGEs) constitute a major mechanism of virulence factor acquisition. For urinary E. coli, the total distribution of MGEs and their role in the acquisition of virulence factors is not well defined, including in the context of symptomatic infection versus asymptomatic bacteriuria (ASB). In this work, we characterized 151 isolates of E. coli, derived from patients with either urinary tract infection (UTI) or ASB. For both sets of E. coli, we catalogued the presence of plasmids, prophage, and transposons. We analyzed MGE sequences for the presence of virulence factors and antimicrobial resistance genes. These MGEs were associated with only ~4% of total virulence associated genes, while plasmids contributed to ~15% of antimicrobial resistance genes under consideration. Our analyses suggests that, across strains of E. coli, MGEs are not a prominent driver of urinary tract pathogenesis and symptomatic infection. IMPORTANCE Escherichia coli is the most common etiological agent of urinary tract infections (UTIs), with UTI-associated strains designated "uropathogenic" E. coli or UPEC. Across urinary strains of E. coli, the global landscape of MGEs and its relationship to virulence factor carriage and clinical symptomatology require greater clarity. Here, we demonstrate that many of the putative virulence factors of UPEC are not associated with acquisition due to MGEs. The current work enhances our understanding of the strain-to-strain variability and pathogenic potential of urine-associated E. coli and points toward more subtle genomic differences distinguishing ASB from UTI isolates.

The structure of biodegradable surfactants shaped the microbial community, antimicrobial resistance, and potential for horizontal gene transfer

While most household surfactants are biodegradable in aerobic conditions, their biodegradability may obscure their environmental risks. The presence of surfactants in a biological treatment process can lead to the proliferation of antimicrobial-resistance genes (ARG) in the biomass. Surfactants can be cationic, anionic, or zwitterionic, and these different classes may have different effects on the proliferation ARG. Cationic hexadecyltrimethyl-ammonium (CTAB), anionic sodium dodecyl sulfate (SDS), and zwitterionic 3-(decyldimethylammonio)-propanesulfonate inner salt (DAPS) were used to represent the three classes of surfactants in domestic household clean-up products. This study focused on the removal of these surfactants by the O₂-based Membrane Biofilm Reactor (O_2-MBfR) for hotspot scenarios (∼1 mM) and how the three classes of surfactants affected the microbial community's structure and ARG. Given sufficient O₂ delivery, the MBfR provided at least 98% surfactant removal. The presence and biodegradation for each surfactant uniquely shaped the biofilms' microbial communities and the presence of ARG. CTAB had by far the strongest impact and the higher ARG abundance. In particular, Pseudomonas and Stenotrophomonas, the two main genera in the biofilm treating CTAB, were highly correlated to the abundance of ARG for efflux pumps and antibiotic inactivation. CTAB also led to more functional genes relevant to the Type-IV secretion system and protection against oxidative stress, which also could encourage horizontal gene transfer. Our findings highlight that the biodegradation of quaternary ammonium surfactants, while beneficial, can pose public health concerns from its ability to promote the proliferation of ARG.

Ecology, more than antibiotics consumption, is the major predictor for the global distribution of aminoglycoside-modifying enzymes

Antibiotic consumption and its abuses have been historically and repeatedly pointed out as the major driver of antibiotic resistance emergence and propagation. However, several examples show that resistance may persist despite substantial reductions in antibiotic use, and that other factors are at stake. Here, we study the temporal, spatial, and ecological distribution patterns of aminoglycoside resistance, by screening more than 160,000 publicly available genomes for 27 clusters of genes encoding aminoglycoside-modifying enzymes (AME genes). We find that AME genes display a very ubiquitous pattern: about 25% of sequenced bacteria carry AME genes. These bacteria were sequenced from all the continents (except Antarctica) and terrestrial biomes, and belong to a wide number of phyla. By focusing on European countries between 1997 and 2018, we show that aminoglycoside consumption has little impact on the prevalence of AME-gene-carrying bacteria, whereas most variation in prevalence is observed among biomes. We further analyze the resemblance of resistome compositions across biomes: soil, wildlife, and human samples appear to be central to understand the exchanges of AME genes between different ecological contexts. Together, these results support the idea that interventional strategies based on reducing antibiotic use should be complemented by a stronger control of exchanges, especially between ecosystems.

Metagenomic analysis reveals unexplored diversity of archaeal virome in the human gut

The human gut microbiome has been extensively explored, while the archaeal viruses remain largely unknown. Here, we present a comprehensive analysis of the archaeal viruses from the human gut metagenomes and the existing virus collections using the CRISPR spacer and viral signature-based approach. This results in 1279 viral species, of which, 95.2% infect Methanobrevibacteria_A, 56.5% shared high identity (>95%) with the archaeal proviruses, 37.2% have a host range across archaeal species, and 55.7% are highly prevalent in the human population (>1%). A methanogenic archaeal virus-specific gene for pseudomurein endoisopeptidase (PeiW) frequently occurs in the viral sequences (n = 150). Analysis of 33 Caudoviricetes viruses with a complete genome often discovers the genes (integrase, n = 29; mazE, n = 10) regulating the viral lysogenic-lytic cycle, implying the dominance of temperate viruses in the archaeal virome. Together, our work uncovers the unexplored diversity of archaeal viruses, revealing the novel facet of the human gut microbiome.

Discovery of Highly Trimethoprim-Resistant DfrB Dihydrofolate Reductases in Diverse Environmental Settings Suggests an Evolutionary Advantage Unrelated to Antibiotic Resistance

Type B dihydrofolate reductases (DfrB) are intrinsically highly resistant to the widely used antibiotic trimethoprim, posing a threat to global public health. The ten known DfrB family members have been strongly associated with genetic material related to the application of antibiotics. Several dfrB genes were associated with multidrug resistance contexts and mobile genetic elements, integrated both in chromosomes and plasmids. However, little is known regarding their presence in other environments. Here, we investigated the presence of dfrB beyond the traditional areas of enquiry by conducting metagenomic database searches from environmental settings where antibiotics are not prevalent. Thirty putative DfrB homologues that share 62 to 95% identity with characterized DfrB were identified. Expression of ten representative homologues verified trimethoprim resistance in all and dihydrofolate reductase activity in most. Contrary to samples associated with the use of antibiotics, the newly identified dfrB were rarely associated with mobile genetic elements or antibiotic resistance genes. Instead, association with metabolic enzymes was observed, suggesting an evolutionary advantage unrelated to antibiotic resistance. Our results are consistent with the hypothesis that multiple dfrB exist in diverse environments from which dfrB were mobilized into the clinically relevant resistome. Our observations reinforce the need to closely monitor their progression.

Exploring strain diversity of dominant human skin bacterial species using single-cell genome sequencing

To understand the role of the skin commensal bacterial community in skin health and the spread of pathogens, it is crucial to identify genetic differences in the bacterial strains corresponding to human individuals. A culture-independent genomics approach is an effective tool for obtaining massive high-quality bacterial genomes. Here we present a single-cell genome sequencing to obtain comprehensive whole-genome sequences of uncultured skin bacteria from skin swabs. We recovered 281 high-quality (HQ) and 244 medium-quality single-amplified genomes (SAGs) of multiple skin bacterial species from eight individuals, including cohabiting group. Single-cell sequencing outperformed in the genome recovery from the same skin swabs, showing 10-fold non-redundant strain genomes compared to the shotgun metagenomic sequencing and binning approach. We then focused on the abundant skin bacteria and identified intra-species diversity, especially in 47 Moraxella osloensis derived HQ SAGs, characterizing the strain-level heterogeneity at mobile genetic element profiles, including plasmids and prophages. Even between the cohabiting individual hosts, they have unique skin bacterial strains in the same species, which shows microdiversity in each host. Genetic and functional differences between skin bacterial strains are predictive of in vivo competition to adapt bacterial genome to utilize the sparse nutrients available on the skin or produce molecules that inhibit the colonization of other microbes or alter their behavior. Thus, single-cell sequencing provides a large number of genomes of higher resolution and quality than conventional metagenomic analysis and helps explore the skin commensal bacteria at the strain level, linking taxonomic and functional information.

A network approach to decipher the dynamics of Lysobacteraceae plasmid gene sharing

Plasmids provide an efficient vehicle for gene sharing among bacterial populations, playing a key role in bacterial evolution. Network approaches are particularly suitable to represent multipartite relationships and are useful tools to characterize plasmid-mediated gene sharing events. The Lysobacteraceae bacterial family gathers plant commensal, plant pathogenic and opportunistic human pathogens for which plasmid mediated adaptation was reported. We searched for homologues of plasmid gene sequences from this family in all the diversity of available bacterial genome sequences and built a network of plasmid gene sharing from the results. While plasmid genes are openly shared between the bacteria of the Lysobacteraceae family, taxonomy strongly defined the boundaries of these exchanges, that only barely reached other families. Most inferred plasmid gene sharing events involved a few genes only, and evidence of full plasmid transfers were restricted to taxonomically close taxon. We detected multiple plasmid-chromosome gene transfers, among which the otherwise known sharing of a heavy metal resistance transposon. In the network, bacterial lifestyles shaped sub-structures of isolates colonizing specific ecological niches and harboring specific types of resistance genes. Genes associated to pathogenicity or antibiotic and metal resistance were among those that most importantly structured the network, highlighting the imprints of human-mediated selective pressure on pathogenic populations. A massive sequencing effort on environmental Lysobacteraceae is therefore required to refine our understanding on how this reservoir fuels the emergence and the spread of genes amongst this family and its potential impact on plant, animal and human health.

Intelligent Identification and Features Attribution of Saline–Alkali-Tolerant Rice Varieties Based on Raman Spectroscopy

Planting rice in saline–alkali land can effectively improve saline–alkali soil and increase grain yield, but traditional identification methods for saline–alkali-tolerant rice varieties require tedious and time-consuming field investigations based on growth indicators by rice breeders. In this study, the Python machine deep learning method was used to analyze the Raman molecular spectroscopy of rice and assist in feature attribution, in order to study a fast and efficient identification method of saline–alkali-tolerant rice varieties. A total of 156 Raman spectra of four rice varieties (two saline–alkali-tolerant rice varieties and two saline–alkali-sensitive rice varieties) were analyzed, and the wave crests were extracted by an improved signal filtering difference method and the feature information of the wave crest was automatically extracted by scipy.signal.find_peaks. Select K Best (SKB), Recursive Feature Elimination (RFE) and Select F Model (SFM) were used to select useful molecular features. Based on these feature selection methods, a Logistic Regression Model (LRM) and Random Forests Model (RFM) were established for discriminant analysis. The experimental results showed that the RFM identification model based on the RFE method reached a higher recognition rate of 89.36%. According to the identification results of RFM and the identification of feature attribution materials, amylum was the most significant substance in the identification of saline–alkali-tolerant rice varieties. Therefore, an intelligent method for the identification of saline–alkali-tolerant rice varieties based on Raman molecular spectroscopy is proposed.

OUP accepted manuscript

Despite recent methodology and reference database improvements for taxonomic profiling tools, metagenomic assembly and genomic binning remain important pillars of metagenomic analysis workflows. In case reference information is lacking, genomic binning is considered to be a state-of-the-art method in mixed culture metagenomic data analysis. In this light, our previously published tool BusyBee Web implements a composition-based binning method efficient enough to function as a rapid online utility. Handling assembled contigs and long nanopore generated reads alike, the webserver provides a wide range of supplementary annotations and visualizations. Half a decade after the initial publication, we revisited existing functionality, added comprehensive visualizations, and increased the number of data analysis customization options for further experimentation. The webserver now allows for visualization-supported differential analysis of samples, which is computationally expensive and typically only performed in coverage-based binning methods. Further, users may now optionally check their uploaded samples for plasmid sequences using PLSDB as a reference database. Lastly, a new application programming interface with a supporting python package was implemented, to allow power users fully automated access to the resource and integration into existing workflows. The webserver is freely available under: https://www.ccb.uni-saarland.de/busybee.

PLSDB: advancing a comprehensive database of bacterial plasmids

Plasmids are known to contain genes encoding for virulence factors and antibiotic resistance mechanisms. Their relevance in metagenomic data processing is steadily growing. However, with the increasing popularity and scale of metagenomics experiments, the number of reported plasmids is rapidly growing as well, amassing a considerable number of false positives due to undetected misassembles. Here, our previously published database PLSDB provides a reliable resource for researchers to quickly compare their sequences against selected and annotated previous findings. Within two years, the size of this resource has more than doubled from the initial 13,789 to now 34,513 entries over the course of eight regular data updates. For this update, we aggregated community feedback for major changes to the database featuring new analysis functionality as well as performance, quality, and accessibility improvements. New filtering steps, annotations, and preprocessing of existing records improve the quality of the provided data. Additionally, new features implemented in the web-server ease user interaction and allow for a deeper understanding of custom uploaded sequences, by visualizing similarity information. Lastly, an application programming interface was implemented along with a python library, to allow remote database queries in automated workflows. The latest release of PLSDB is freely accessible under https://www.ccb.uni-saarland.de/plsdb.