Bacteroidales species in the human gut are a reservoir of antibiotic resistance genes regulated by invertible promoters

Antibiotic-resistance genes (ARGs) regulated by invertible promoters can mitigate the fitness cost of maintaining ARGs in the absence of antibiotics and could potentially prolong the persistence of ARGs in bacterial populations. However, the origin, prevalence, and distribution of these ARGs regulated by invertible promoters remains poorly understood. Here, we sought to assess the threat posed by ARGs regulated by invertible promoters by systematically searching for ARGs regulated by invertible promoters in the human gut microbiome and examining their origin, prevalence, and distribution. Through metagenomic assembly of 2227 human gut metagenomes and genomic analysis of the Unified Human Gastrointestinal Genome (UHGG) collection, we identified ARGs regulated by invertible promoters and categorized them into three classes based on the invertase-regulating phase variation. In the human gut microbiome, ARGs regulated by invertible promoters are exclusively found in Bacteroidales species. Through genomic analysis, we observed that ARGs regulated by invertible promoters have convergently originated from ARG insertions into glycan-synthesis loci that were regulated by invertible promoters at least three times. Moreover, all three classes of invertible promoters regulating ARGs are located within integrative conjugative elements (ICEs). Therefore, horizontal transfer via ICEs could explain the wide taxonomic distribution of ARGs regulated by invertible promoters. Overall, these findings reveal that glycan-synthesis loci regulated by invertible promoters in Bacteroidales species are an important hotspot for the emergence of clinically-relevant ARGs regulated by invertible promoters.

Full Genome Sequence of a Methanomassiliicoccales Representative Enriched from Peat Soil

The full genome of a Methanomassiliicoccales strain, U3.2.1, was obtained from enrichment cultures of percolation fen peat soil under methanogenic conditions, with methanol and hydrogen as the electron acceptor and donor, respectively. Metagenomic assembly of combined long-read and short-read sequences resulted in a 1.51-Mbp circular genome.

Characterization and simulation of metagenomic nanopore sequencing data with Meta-NanoSim

Nanopore sequencing is crucial to metagenomic studies as its kilobase-long reads can contribute to resolving genomic structural differences among microbes. However, platform-specific challenges, including high base-call error rate, non-uniform read lengths, and the presence of chimeric artifacts, necessitate specifically designed analytical tools. Here, we present Meta-NanoSim, a fast and versatile utility that characterizes and simulates the unique properties of nanopore metagenomic reads. Further, Meta-NanoSim improves upon state-of-the-art methods on microbial abundance estimation through a base-level quantification algorithm. We demonstrate that Meta-NanoSim simulated data can facilitate the development of metagenomic algorithms and guide experimental design through a metagenomic assembly benchmarking task.

Metagenomic Assembly Reveals the Fate of the Core Antibiotic Resistome, its Hosts and Mobility in Animal Manure and After Compost

Background Antibiotics and antibiotic resistance genes (ARGs) used in intensive animal husbandry threaten human health worldwide; however, the core resistome, mobility of ARGs, and the composition of ARG hosts in animal manure and the following composts remain unclear. In the present study, metagenomic assembly was used to comprehensively decipher the core resistome and its potential mobility and hosts in animal manure and compost. Results In total, 201 ARGs were shared among different animal (layer, broiler, swine, beef cow, and dairy cow) manures and accounted for 86–99% of total relative abundance of ARGs, which mainly comprised multidrug, macrolide-lincosamide-streptogramin (M-L-S), tetracycline, beta-lactam, aminoglycoside, and sulfonamide resistance genes. Moreover, efficient composting reduced the total relative abundance of ARGs in manure from 0.938 to 0.405 copies per 16S rRNA gene; however, it did not have any remarkable effect on the multidrug, sulfonamide, and trimethoprim resistance genes. Procrustes analysis indicated that composting can reduce antibiotic residues and decrease the correlation between antibiotics and resistance genes. Furthermore, the ARG hosts included Proteobacteria (50.08%), Firmicutes (37.77%), Bacteroidetes (6.49%), and Actinobacteria (5.24%). In manure, aminoglycoside resistance genes were majorly found in Enterococcus, Streptococcus, and Enterobacter; tetracycline resistance genes (TRGs) were found in Pseudomonas, Lactobacillus, and Streptococcus; and multidrug resistance genes were mainly found in Escherichia coli. In our samples, ARGs were more prevalent in plasmids than in chromosomes. The broad host range and diverse mobile genetic elements may be two key factors for ARGs, such as sul1 and aadA, which could survive during composting. The multidrug resistance genes represented the dominant ARGs in pathogenic antibiotic-resistant bacteria (PARB) in manure, and composting could effectively control PARB. Conclusions Our experiments revealed the core resistome in animal manure, classified and relative quantified the ARG hosts, and assessed the mobility of ARGs. Composting can mitigate ARGs in animal manure by altering the bacterial hosts; however, some ARGs can escape from the removal with the survivor heat-tolerant hosts or transfer to these hosts. These findings will help optimize composting strategies for the effective treatment of ARGs and their hosts in farms.

Metagenomic Analysis Reveals Neisseria bacilliformis Variation in the Early Childhood Caries Plaque Microbiome

The progression of early childhood caries (ECC) is caused by microbial colonized in dental plaque. However, the association framework both from 16s genus down to high resolution metagenomic strain level and from composition to genome function analysis on caries lacks. 16S rRNA sequence revealed the composition of 3–6 years dental caries (ECC, n = 29), and severe dental caries (SECC, n = 36) children are significantly different from caries-free controls (CF, n = 31). Especially, genus Neisseria is enriched in caries ( P < 0.05 ). Metagenomics sequence of 3 ECCs, 3 SECCs, and 3 CFs reveals Neisseria bacilliformis ATCC BAA-1200 in genus Neisseria is also significantly enriched in caries ( P < 0.05 ). Then, we recovered high-quality metagenomic assembly genomes (MAG), named bin 86, which have 99% identity with Neisseria bacilliformis ATCC BAA-1200 genome. Function analysis of Neisseria bacilliformis ATCC BAA-1200 genome shows its metabolism power of sugar and adhesion, colonization, acid production, and acid tolerance ability, which suggested Neisseria bacilliformis ATCC BAA-1200 may serve as a biomarker for childhood caries.

Cryptosporidium hominis Phylogenomic Analysis Reveals Separate Lineages With Continental Segregation

Cryptosporidium is a leading cause of waterborne outbreaks globally, and Cryptosporidium hominis and C. parvum are the principal cause of human cryptosporidiosis on the planet. Thanks to the advances in Next-Generation Sequencing (NGS) sequencing and bioinformatic software development, more than 100 genomes have been generated in the last decade using a metagenomic-like strategy. This procedure involves the parasite oocyst enrichment from stool samples of infected individuals, NGS sequencing, metagenomic assembly, parasite genome computational filtering, and comparative genomic analysis. Following this approach, genomes of infected individuals of all continents have been generated, although with striking different quality results. In this study, we performed a thorough comparison, in terms of assembly quality and purity, of 100+ de novo assembled genomes of C. hominis. Remarkably, after quality genome filtering, a comprehensive phylogenomic analysis allowed us to discover that C. hominis encompasses two lineages with continental segregation. These lineages were named based on the observed continental distribution bias as C. hominis Euro-American (EA) and the C. hominis Afro-Asian (AA) lineages.

Graph-Based Approaches Significantly Improve the Recovery of Antibiotic Resistance Genes From Complex Metagenomic Datasets

The lack of control over the usage of antibiotics leads to propagation of the microbial strains that are resistant to many antimicrobial substances. This situation is an emerging threat to public health and therefore the development of approaches to infer the presence of resistant strains is a topic of high importance. The resistome construction of an isolate microbial species could be considered a solved task with many state-of-the-art tools available. However, when it comes to the analysis of the resistome of a microbial community (metagenome), then there exist many challenges that influence the accuracy and precision of the predictions. For example, the prediction sensitivity of the existing tools suffer from the fragmented metagenomic assemblies due to interspecies repeats: usually it is impossible to recover conservative parts of antibiotic resistance genes that belong to different species that occur due to e.g., horizontal gene transfer or residing on a plasmid. The recent advances in development of new graph-based methods open a way to recover gene sequences of interest directly from the assembly graph without relying on cumbersome and incomplete metagenomic assembly. We present GraphAMR—a novel computational pipeline for recovery and identification of antibiotic resistance genes from fragmented metagenomic assemblies. The pipeline involves the alignment of profile hidden Markov models of target genes directly to the assembly graph of a metagenome with further dereplication and annotation of the results using state-of-the art tools. We show significant improvement of the quality of the results obtained (both in terms of accuracy and completeness) as compared to the analysis of an output of ordinary metagenomic assembly as well as different read mapping approaches. The pipeline is freely available from https://github.com/ablab/graphamr.

Evaluating metagenomic assembly approaches for biome-specific gene catalogues

For many environments, biome-specific microbial gene catalogues are being recovered using shotgun metagenomics followed by assembly and gene-calling on the assembled contigs. The assembly can be conducted either by individually assembling each sample or by co-assembling reads from all the samples. The co-assembly approach can potentially recover genes that display too low abundance to be assembled from individual samples. On the other hand, combining samples increases the risk of mixing data from closely related strains, which can hamper the assembly process. In this respect, assembly on individual samples followed by clustering of (near) identical genes is likely preferable. Thus, both approaches have pros and cons and it remains to be evaluated which assembly strategy is most effective. Here, we have evaluated three assembly strategies for generating gene catalogues from metagenomes using a dataset of 124 samples from the Baltic Sea: 1) assembly on individual samples followed by clustering of the resulting genes, 2) co-assembly on all samples, and 3) mix-assembly, combining individual and co-assembly. The mix-assembly approach resulted in a more extensive non-redundant gene set than the other approaches, and with more genes predicted to be complete and that could be functionally annotated. The mix-assembly consists of 67 million genes (Baltic Sea gene set; BAGS) that have been functionally and taxonomically annotated. The majority of the BAGS genes are dissimilar (<95% amino acid identity) to the Tara Oceans gene dataset, and hence BAGS represents a valuable resource for brackish water research.

Metagenomic analysis of ancient dental calculus reveals unexplored diversity of oral archaeal Methanobrevibacter

Background Dental calculus (mineralised dental plaque) preserves many types of microfossils and biomolecules, including microbial and host DNA, and ancient calculus are thus an important source of information regarding our ancestral human oral microbiome. In this study, we taxonomically characterised the dental calculus microbiome from 20 ancient human skeletal remains originating from Trentino-South Tyrol, Italy, dating from the Neolithic (6000–3500 BCE) to the Early Middle Ages (400–1000 CE). Results We found a high abundance of the archaeal genus Methanobrevibacter in the calculus. However, only a fraction of the sequences showed high similarity to Methanobrevibacter oralis, the only described Methanobrevibacter species in the human oral microbiome so far. To further investigate the diversity of this genus, we used de novo metagenome assembly to reconstruct 11 Methanobrevibacter genomes from the ancient calculus samples. Besides the presence of M. oralis in one of the samples, our phylogenetic analysis revealed two hitherto uncharacterised and unnamed oral Methanobrevibacter species that are prevalent in ancient calculus samples sampled from a broad range of geographical locations and time periods. Conclusions We have shown the potential of using de novo metagenomic assembly on ancient samples to explore microbial diversity and evolution. Our study suggests that there has been a possible shift in the human oral microbiome member Methanobrevibacter over the last millennia.