Strategies and approaches in plasmidome studies-uncovering plasmid diversity disregarding of linear elements?

Analysis of Antimicrobial Resistance in Bacterial Pathogens Recovered from Food and Human Sources: Insights from 639,087 Bacterial Whole-Genome Sequences in the NCBI Pathogen Detection Database

Understanding the role of foods in the emergence and spread of antimicrobial resistance necessitates the initial documentation of antibiotic resistance genes within bacterial species found in foods. Here, the NCBI Pathogen Detection database was used to query antimicrobial resistance gene prevalence in foodborne and human clinical bacterial isolates. Of the 1,843,630 sequence entries, 639,087 (34.7%) were assigned to foodborne or human clinical sources with 147,788 (23.14%) from food and 427,614 (76.88%) from humans. The majority of foodborne isolates were either Salmonella (47.88%), Campylobacter (23.03%), Escherichia (11.79%), or Listeria (11.3%), and the remaining 6% belonged to 20 other genera. Most foodborne isolates were from meat/poultry (95,251 or 64.45%), followed by multi-product mixed food sources (29,892 or 20.23%) and fish/seafood (6503 or 4.4%); however, the most prominent isolation source varied depending on the genus/species. Resistance gene carriage also varied depending on isolation source and genus/species. Of note, Klebsiella pneumoniae and Enterobacter spp. carried larger proportions of the quinolone resistance gene qnrS and some clinically relevant beta-lactam resistance genes in comparison to Salmonella and Escherichia coli. The prevalence of mec in S. aureus did not significantly differ between meat/poultry and multi-product sources relative to clinical sources, whereas this resistance was rare in isolates from dairy sources. The proportion of biocide resistance in Bacillus and Escherichia was significantly higher in clinical isolates compared to many foodborne sources but significantly lower in clinical Listeria compared to foodborne Listeria. This work exposes the gaps in current publicly available sequence data repositories, which are largely composed of clinical isolates and are biased towards specific highly abundant pathogenic species. We also highlight the importance of requiring and curating metadata on sequence submission to not only ensure correct information and data interpretation but also foster efficient analysis, sharing, and collaboration. To effectively monitor resistance carriage in food production, additional work on sequencing and characterizing AMR carriage in common commensal foodborne bacteria is critical.

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.

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.

An overview of plasmid transfer in the plant microbiome

Plant microbiomes are pivotal for healthy plant physiological development. Microbes live in complex co-association with plant hosts, and interactions within these microbial communities vary with plant genotype, plant compartment, phenological stage, and soil properties, among others. Plant microbiomes also harbor a substantial and diverse pool of mobile genes encoded on plasmids. Several plasmid functions attributed to plant-associated bacteria are relatively poorly understood. Additionally, the role of plasmids in disseminating genetic traits within plant compartments is not well known. Here, we present the current knowledge on the occurrence, diversity, function, and transfer of plasmids in plant microbiomes, emphasizing the factors that could modulate gene transfer in-planta. We also describe the role of the plant microbiome as a plasmid reservoir and the dissemination of its genetic material. We include a brief discussion on the current methodological limitations in studying plasmid transfer within plant microbiomes. This information could be useful to elucidate the dynamics of the bacterial gene pools, the adaptations different organisms have made, and variations in bacterial populations that might have never been described before, particularly in complex microbial communities associated with plants in natural and anthropogenic impacted environments.

Metagenomic analysis reveals gut plasmids as diagnosis markers for colorectal cancer

Background

Colorectal cancer (CRC) is linked to distinct gut microbiome patterns. The efficacy of gut bacteria as diagnostic biomarkers for CRC has been confirmed. Despite the potential to influence microbiome physiology and evolution, the set of plasmids in the gut microbiome remains understudied.

Methods

We investigated the essential features of gut plasmid using metagenomic data of 1,242 samples from eight distinct geographic cohorts. We identified 198 plasmid-related sequences that differed in abundance between CRC patients and controls and screened 21 markers for the CRC diagnosis model. We utilize these plasmid markers combined with bacteria to construct a random forest classifier model to diagnose CRC.

Results

The plasmid markers were able to distinguish between the CRC patients and controls [mean area under the receiver operating characteristic curve (AUC = 0.70)] and maintained accuracy in two independent cohorts. In comparison to the bacteria-only model, the performance of the composite panel created by combining plasmid and bacteria features was significantly improved in all training cohorts (mean AUC_composite = 0.804 and mean AUC_bacteria = 0.787) and maintained high accuracy in all independent cohorts (mean AUC_composite = 0.839 and mean AUC_bacteria = 0.821). In comparison to controls, we found that the bacteria-plasmid correlation strength was weaker in CRC patients. Additionally, the KEGG orthology (KO) genes in plasmids that are independent of bacteria or plasmids significantly correlated with CRC.

Conclusion

We identified plasmid features associated with CRC and showed how plasmid and bacterial markers could be combined to further enhance CRC diagnosis accuracy.

Multilayer networks of plasmid genetic similarity reveal potential pathways of gene transmission

Antimicrobial resistance (AMR) is a significant threat to public health. Plasmids are principal vectors of AMR genes, significantly contributing to their spread and mobility across hosts. Nevertheless, little is known about the dynamics of plasmid genetic exchange across animal hosts. Here, we use theory and methodology from network and disease ecology to investigate the potential of gene transmission between plasmids using a data set of 21 plasmidomes from a single dairy cow population. We constructed a multilayer network based on pairwise plasmid genetic similarity. Genetic similarity is a signature of past genetic exchange that can aid in identifying potential routes and mechanisms of gene transmission within and between cows. Links between cows dominated the transmission network, and plasmids containing mobility genes were more connected. Modularity analysis revealed a network cluster where all plasmids contained a mobM gene, and one where all plasmids contained a beta-lactamase gene. Cows that contain both clusters also share transmission pathways with many other cows, making them candidates for super-spreading. In support, we found signatures of gene super-spreading in which a few plasmids and cows are responsible for most gene exchange. An agent-based transmission model showed that a new gene invading the cow population will likely reach all cows. Finally, we showed that edge weights contain a non-random signature for the mechanisms of gene transmission, allowing us to differentiate between dispersal and genetic exchange. These results provide insights into how genes, including those providing AMR, spread across animal hosts.

Insights into the fates of plasmids and antimicrobial resistance genes during swine manure treatment and related factors based on plasmidome and metagenome analyses

Swine manure treatment plants are important reservoirs of plasmid-harboring antibiotic resistance genes (ARGs) and physicochemical contaminants, but the changes in the abundances of plasmids and ARGs, and their interactions with the physicochemical properties of manure, are still unclear. Thus, in the present study, plasmidome and metagenome analyses were conducted for samples collected at different stages in the swine manure treatment process. The results indicated that anaerobic digestion and aerobic digestion were the most efficient stages for reducing the abundances of ARGs in swine manure. However, the plasmids associated with ARGs were not effectively removed in these stages. Through the whole treatment process, the IncL/M, IncQ1, IncHI2A, IncA/C, and IncN plasmid groups had strong correlations (r > 0.8, P < 0.01) with most ARG types, thereby indicating that these plasmids play important roles in the persistence of ARGs in this environment. Furthermore, the pH, total nitrogen, total phosphorus, and four heavy metals (Cu, Zn, As, and Fe) significantly affected the abundances of seven ARG subtypes (tetB(P), ant(6)-Ia, tet44, aph(3'')-Ib, mefB, tet(L), and tet(39)). In particular, florfenicol had the most positive correlations with ARGs. Our results indicated that nutrients, heavy metals, and antibiotics all contributed to the presence and persistence of plasmid-harboring ARGs. This study provides insights into the fate of plasmids and ARGs, and related factors during the swine manure treatment process, thereby facilitating the development of a new treatment technique for removing ARGs and reducing the public health risk associated with livestock production.

Plasmid-Mediated Transfer of Antibiotic Resistance Genes in Soil

Due to selective pressure from the widespread use of antibiotics, antibiotic resistance genes (ARGs) are found in human hosts, plants, and animals and virtually all natural environments. Their migration and transmission in different environmental media are often more harmful than antibiotics themselves. ARGs mainly move between different microorganisms through a variety of mobile genetic elements (MGEs), such as plasmids and phages. The soil environment is regarded as the most microbially active biosphere on the Earth’s surface and is closely related to human activities. With the increase in human activity, soils are becoming increasingly contaminated with antibiotics and ARGs. Soil plasmids play an important role in this process. This paper reviews the current scenario of plasmid-mediated migration and transmission of ARGs in natural environments and under different antibiotic selection pressures, summarizes the current methods of plasmid extraction and analysis, and briefly introduces the mechanism of plasmid splice transfer using the F factor as an example. However, as the global spread of drug-resistant bacteria has increased and the knowledge of MGEs improves, the contribution of soil plasmids to resistance gene transmission needs to be further investigated. The prevalence of multidrug-resistant bacteria has also made the effective prevention of the transmission of resistance genes through the plasmid-bacteria pathway a major research priority.

Second compartment widens plasmid invasion conditions: Two-compartment pair-formation model of conjugation in the gut

Understanding under which conditions conjugative plasmids encoding antibiotic resistance can invade bacterial communities in the gut is of particular interest to combat the spread of antibiotic resistance within and between animals and humans. We extended a one-compartment model of conjugation to a two-compartment model, to analyse how differences in plasmid dynamics in the gut lumen and at the gut wall affect the invasion of plasmids. We compared scenarios with one and two compartments, different migration rates between the lumen and wall compartments, and different population dynamics. We focused on the effect of attachment and detachment rates on plasmid dynamics, explicitly describing pair formation followed by plasmid transfer in the pairs. The parameter space allowing plasmid invasion in the one-compartment model is affected by plasmid costs and intrinsic conjugation rates of the transconjugant, but not by these characteristics of the donor. The parameter space allowing plasmid invasion in the two-compartment model is affected by attachment and detachment rates in the lumen and wall compartment, and by the bacterial density at the wall. The one- and two-compartment models predict the same parameter space for plasmid invasion if the conditions in both compartments are equal to the conditions in the one-compartment model. In contrast, the addition of the wall compartment widens the parameter space allowing invasion compared with the one-compartment model, if the density at the wall is higher than in the lumen, or if the attachment rate at the wall is high and the detachment rate at the wall is low. We also compared the pair-formation models with bulk-conjugation models that describe conjugation by instantaneous transfer of the plasmid at contact between cells, without explicitly describing pair formation. Our results show that pair-formation and bulk-conjugation models predict the same parameter space for plasmid invasion. From our simulations, we conclude that conditions at the gut wall should be taken into account to describe plasmid dynamics in the gut and that transconjugant characteristics rather than donor characteristics should be used to parameterize the models.

RFPlasmid: predicting plasmid sequences from short-read assembly data using machine learning

Antimicrobial-resistance (AMR) genes in bacteria are often carried on plasmids and these plasmids can transfer AMR genes between bacteria. For molecular epidemiology purposes and risk assessment, it is important to know whether the genes are located on highly transferable plasmids or in the more stable chromosomes. However, draft whole-genome sequences are fragmented, making it difficult to discriminate plasmid and chromosomal contigs. Current methods that predict plasmid sequences from draft genome sequences rely on single features, like k-mer composition, circularity of the DNA molecule, copy number or sequence identity to plasmid replication genes, all of which have their drawbacks, especially when faced with large single-copy plasmids, which often carry resistance genes. With our newly developed prediction tool RFPlasmid, we use a combination of multiple features, including k-mer composition and databases with plasmid and chromosomal marker proteins, to predict whether the likely source of a contig is plasmid or chromosomal. The tool RFPlasmid supports models for 17 different bacterial taxa, including Campylobacter, Escherichia coli and Salmonella, and has a taxon agnostic model for metagenomic assemblies or unsupported organisms. RFPlasmid is available both as a standalone tool and via a web interface.

Genomics and transcriptomics insights into luteolin effects on the beta-rhizobial strain Cupriavidus necator UYPR2.512

Cupriavidus necator UYPR2.512 is a rhizobial strain that belongs to the Beta-subclass of proteobacteria, able to establish successful symbiosis with Mimosoid legumes. The initial steps of rhizobium-legumes symbioses involve the reciprocal recognition by chemical signals, being luteolin one of the molecules involved. However, there is a lack of information on the effect of luteolin in beta-rhizobia. In this work, we used long-read sequencing to complete the genome of UYPR2.512 providing evidence for the existence of four closed circular replicons. We used an RNA-Seq approach to analyse the response of UYPR2.512 to luteolin. One hundred and forty-five genes were differentially expressed, with similar numbers of downregulated and upregulated genes. Most repressed genes were mapped to the main chromosome, while the upregulated genes were overrepresented among pCne512e, containing the symbiotic genes. Induced genes included the nod operon and genes implicated in exopolysaccharides and flagellar biosynthesis. We identified many genes involved in iron, copper and other heavy metals metabolism. Among repressed genes, we identified genes involved in basal carbon and nitrogen metabolism. Our results suggest that in response to luteolin, C. necator strain UYPR2.512 reshapes its metabolism in order to be prepared for the forthcoming symbiotic interaction.

Assessment of the plasmidome of an extremophilic microbial community from the Diamante Lake, Argentina

Diamante Lake located at 4589 m.a.s.l. in the Andean Puna constitutes an extreme environment. It is exposed to multiple extreme conditions such as an unusually high concentration of arsenic (over 300 mg L^-1) and low oxygen pressure. Microorganisms thriving in the lake display specific genotypes that facilitate survival, which include at least a multitude of plasmid-encoded resistance traits. Hence, the genetic information provided by the plasmids essentially contributes to understand adaptation to different stressors. Though plasmids from cultivable organisms have already been analyzed to the sequence level, the impact of the entire plasmid-borne genetic information on such microbial ecosystem is not known. This study aims at assessing the plasmidome from Diamante Lake, which facilitates the identification of potential hosts and prediction of gene functions as well as the ecological impact of mobile genetic elements. The deep-sequencing analysis revealed a large fraction of previously unknown DNA sequences of which the majority encoded putative proteins of unknown function. Remarkably, functions related to the oxidative stress response, DNA repair, as well as arsenic- and antibiotic resistances were annotated. Additionally, all necessary capacities related to plasmid replication, mobilization and maintenance were detected. Sequences characteristic for megaplasmids and other already known plasmid-associated genes were identified as well. The study highlights the potential of the deep-sequencing approach specifically targeting plasmid populations as it allows to evaluate the ecological impact of plasmids from (cultivable and non-cultivable) microorganisms, thereby contributing to the understanding of the distribution of resistance factors within an extremophilic microbial community.

A highly effective and self-transmissible CRISPR antimicrobial for elimination of target plasmids without antibiotic selection

The use of CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated protein) for sequence-specific elimination of bacteria or resistance genes is a powerful tool for combating antibiotic resistance. However, this approach requires efficient delivery of CRISPR/Cas DNA cassette(s) into the targeted bacterial population. Compared to phage transduction, plasmid conjugation can deliver DNA to a broader host range but often suffers from low delivery efficiency. Here, we developed multi-plasmid conjugation systems for efficient CRISPR/Cas delivery, target DNA elimination and plasmid replacement. The CRISPR/Cas system, delivered via a broad-host-range R1162 mobilizable plasmid, specifically eliminated the targeted plasmid in recipient cells. A self-transmissible RK2 helper plasmid facilitated the spread of mobilizable CRISPR/Cas. The replacement of the target plasmid with another plasmid from the same compatibility group helped speed up target plasmid elimination especially when the target plasmid was also mobilizable. Together, we showed that up to 100% of target plasmid from the entire recipient population could be replaced even at a low (1:180) donor-to-recipient ratio and in the absence of transconjugant selection. Such an ability to modify genetic content of microbiota efficiently in the absence of selection will be critical for future development of CRISPR antimicrobials as well as genetic tools for in situ microbiome engineering.

Exploring Phytochemicals for Combating Antibiotic Resistance in Microbial Pathogens

Antibiotic resistance or microbial drug resistance is emerging as a serious threat to human healthcare globally, and the multidrug-resistant (MDR) strains are imposing major hurdles to the progression of drug discovery programs. Newer antibiotic-resistance mechanisms in microbes contribute to the inefficacy of the existing drugs along with the prolonged illness and escalating expenditures. The injudicious usage of the conventional and commonly available antibiotics in human health, hygiene, veterinary and agricultural practices is proving to be a major driver for evolution, persistence and spread of antibiotic-resistance at a frightening rate. The drying pipeline of new and potent antibiotics is adding to the severity. Therefore, novel and effective new drugs and innovative therapies to treat MDR infections are urgently needed. Apart from the different natural and synthetic drugs being tested, plant secondary metabolites or phytochemicals are proving efficient in combating the drug-resistant strains. Various phytochemicals from classes including alkaloids, phenols, coumarins, terpenes have been successfully demonstrated their inhibitory potential against the drug-resistant pathogens. Several phytochemicals have proved effective against the molecular determinants responsible for attaining the drug resistance in pathogens like membrane proteins, biofilms, efflux pumps and bacterial cell communications. However, translational success rate needs to be improved, but the trends are encouraging. This review highlights current knowledge and developments associated challenges and future prospects for the successful application of phytochemicals in combating antibiotic resistance and the resistant microbial pathogens.

Occurrence and plasmid profiles of multidrug-resistant Enterobacteriaceae isolated from hawked soymilk samples in the Polytechnic of Ibadan Community, Nigeria

This study was conducted to determine the occurrence, antibiotic susceptibility pattern, and plasmid profile of multidrug-resistant (MDR) Enterobacteriaceae isolated from soymilk hawked in the Ibadan Polytechnic Community, Nigeria. Bacterial isolation and identification were performed using a culture-dependent method and biochemical characterization, respectively, while antibiotic susceptibility was tested using the disk diffusion method. Plasmid analysis and curing were performed using standard procedures. The results revealed the following occurrence rate of bacterial species in soymilk samples collected from all axes (South, North, East, West, and Central) of Ibadan Polytechnic: Citrobacter spp., 64%; Klebsiella spp., 7%; Enterobacter spp., Escherichia coli, and Serratia spp., 6% each; Proteus spp., 5%; and Salmonella spp. and Shigella spp., 3% each. The highest heterotrophic bacterial count of 9.3 × 10³ CFU/ml was recorded at Ibadan Polytechnic North and South, while the least count (3.2 × 10⁷ CFU/ml) was recorded at Ibadan Polytechnic Central. The highest enteric bacterial count of 1.3 × 10³ CFU/ml was recorded in soymilk samples from Ibadan Polytechnic Central, while the least count of 1.7 × 10⁷ CFU/ml was recorded in soymilk samples from Ibadan Polytechnic North. A total of 26% of the isolates showed resistance to cefpodoxime, while 88% of the isolates were susceptible to trimethoprim-sulfamethoxazole. Four of the MDR isolates possessed plasmid bands ranging from 6 to 1 with molecular weights from 2.7 to 17.2 kbp. Enterobacteriaceae such as isolates O14 (Klebsiella spp.) and B10 (E. coli ) retained their resistance to antibiotics even after removal of plasmids, while isolates S13 (Citrobacter spp.) and O4 (Shigella spp.) were susceptible to some antibiotics after curing. Conclusively, soymilk sold in the sampled areas was highly contaminated with Enterobacteriaceae, thereby indicating poor hygiene standards of soymilk production.

Characterization of putative circular plasmids in sponge-associated bacterial communities using a selective multiply-primed rolling circle amplification

Plasmid transfers among bacterial populations can directly influence the ecological adaptation of these populations and their interactions with host species and environment. In this study, we developed a selective multiply-primed rolling circle amplification (smRCA) approach to enrich and characterize circular plasmid DNA from sponge microbial symbionts via high-throughput sequencing (HTS). DNA (plasmid and total community DNA) obtained from sponge (Cinachyrella sp.) samples and a bacterial symbiont (Vibrio sp. CyArs1) isolated from the same sponge species (carrying unknown plasmids) were used to develop and validate our methodology. The smRCA was performed during 16 hr with 141 plasmid-specific primers covering all known circular plasmid groups. The amplified products were purified and subjected to a reamplification with random hexamer primers (2 hr) and then sequenced using Illumina MiSeq. The developed method resulted in the successful amplification and characterization of the sponge plasmidome and allowed us to detect plasmids associated with the bacterial symbiont Vibrio sp. CyArs1 in the sponge host. In addition to this, a large number of small (<2 kbp) and cryptic plasmids were also amplified in sponge samples. Functional analysis identified proteins involved in the control of plasmid partitioning, maintenance and replication. However, most plasmids contained unknown genes, which could potentially serve as a resource of unknown genetic information and novel replication systems. Overall, our results indicate that the smRCA-HTS approach developed here was able to selectively enrich and characterize plasmids from bacterial isolates and sponge host microbial communities, including plasmids larger than 20 kbp.

Experimental approaches to tracking mobile genetic elements in microbial communities

Horizontal gene transfer is an important mechanism of microbial evolution and is often driven by the movement of mobile genetic elements between cells. Due to the fact that microbes live within communities, various mechanisms of horizontal gene transfer and types of mobile elements can co-occur. However, the ways in which horizontal gene transfer impacts and is impacted by communities containing diverse mobile elements has been challenging to address. Thus, the field would benefit from incorporating community-level information and novel approaches alongside existing methods. Emerging technologies for tracking mobile elements and assigning them to host organisms provide promise for understanding the web of potential DNA transfers in diverse microbial communities more comprehensively. Compared to existing experimental approaches, chromosome conformation capture and methylome analyses have the potential to simultaneously study various types of mobile elements and their associated hosts. We also briefly discuss how fermented food microbiomes, given their experimental tractability and moderate species complexity, make ideal models to which to apply the techniques discussed herein and how they can be used to address outstanding questions in the field of horizontal gene transfer in microbial communities.

Reconstruction of plasmids by shotgun sequencing from environmental DNA: which bioinformatic workflow?

Plasmids play important roles in microbial evolution and also in the spread of antibiotic resistance. Plasmid sequences are extensively studied from clinical isolates but rarely from the environment with a metagenomic approach focused on the plasmid fraction referred to as the plasmidome. A clear challenge in this context is to define a workflow for discriminating plasmids from chromosomal contaminants existing in the plasmidome. For this purpose, we benchmarked existing tools from assembly to detection of the plasmids by reference-free methods (cBar and PlasFlow) and database-guided approaches. Our simulations took into account short-reads alone or combined with moderate long-reads like those actually generated in environmental genomics experiments. This benchmark allowed us to select the best tools for limiting false-positives associated to plasmid prediction tools and a combination of reference-guided methods based on plasmid and bacterial databases.

Probing the Mobilome: Discoveries in the Dynamic Microbiome

There has been an explosion of metagenomic data representing human, animal, and environmental microbiomes. This provides an unprecedented opportunity for comparative and longitudinal studies of many functional aspects of the microbiome that go beyond taxonomic classification, such as profiling genetic determinants of antimicrobial resistance, interactions with the host, potentially clinically relevant functions, and the role of mobile genetic elements (MGEs). One of the most important but least studied of these aspects are the MGEs, collectively referred to as the 'mobilome'. Here we elaborate on the benefits and limitations of using different metagenomic protocols, discuss the relative merits of various sequencing technologies, and highlight relevant bioinformatics tools and pipelines to predict the presence of MGEs and their microbial hosts.

Novel Multidrug-Resistant Enterococcal Mobile Linear Plasmid pELF1 Encoding vanA and vanM Gene Clusters From a Japanese Vancomycin-Resistant Enterococci Isolate

Vancomycin-resistant enterococci are troublesome pathogens in clinical settings because of few treatment options. A VanA/VanM-type vancomycin-resistant Enterococcus faecium clinical isolate was identified in Japan. This strain, named AA708, harbored five plasmids, one of which migrated during agarose gel electrophoresis without S1 nuclease treatment, which is indicative of a linear topology. We named this plasmid pELF1. Whole genome sequencing (WGS) analysis of the AA708 strain revealed that the complete sequence of pELF1 was 143,316 bp long and harbored both the vanA and vanM gene clusters. Furthermore, mfold analysis and WGS data show that the left end of pELF1 presumably forms a hairpin structure, unlike its right end. The pELF1 plasmid was not digested by lambda exonuclease, indicating that terminal proteins were bound to the 5′ end of the plasmid, similar to the Streptomyces linear plasmids. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis results were also consistent with the exonuclease assay results. In retardation assays, DNAs containing the right end of proteinase K-untreated pELF1 did not appear to move as well as the proteinase K-treated pELF1, suggesting that terminal proteins might be attached to the right end of pELF1. Palindromic sequences formed hairpin structures at the right terminal sequence of pELF1; however, sequence similarity with the well-known linear plasmids of Streptomyces spp. was not high. pELF1 was unique as it possessed two different terminal structures. Conjugation experiments revealed that pELF1 could be transferred to E. faecalis, E. faecium, E. casseliflavus, and E. hirae. These transconjugants exhibited not only high resistance levels to vancomycin, but also resistance to streptomycin, kanamycin, and erythromycin. These results indicate that pELF1 has the ability to confer multidrug resistance to Enterococcus spp. simultaneously, which might lead to clinical hazards.

Resolution of dynamic MDR structures among the plasmidome of Salmonella using MinION single-molecule, long-read sequencing

Background

ISCR1 is an important mobile genetic element mediating the transfer of antibiotic resistance genes. Genetic diversity regarding distribution and copy numbers of ISCR1 within a bacterial population derived from an ancestral strain, which may reflect the degree of genetic plasticity conferred by such an element, has not been studied.

Objectives

To investigate the plasmid heterogeneity in Salmonella conferred by ISCR1.

Methods

Nanopore long-read and other sequencing technologies were used to resolve the structures harbouring different copies of ISCR1-qnrB6 from the perspective of single molecules.

Results

Salmonella London Sa128 was positive for ISCR1-qnrB6 and harboured an MDR-encoding conjugative IncF plasmid, pSa128, containing a complex class 1 integron. The plasmid pSa128T from the transconjugant was larger compared with the original plasmid pSa128, presumably due to amplification of ISCR1-qnrB6. Single-molecule, long-read analysis indicated that both plasmids in the donor and transconjugant strains were in a heterogeneous state that contains variable numbers of ISCR1-qnrB6, with four and eight copies in single plasmids being the dominant types. This type of plasmid heterogeneity in populations of one strain can be regarded as an atypical plasmidome.

Conclusions

This study highlights the importance of investigation of a single plasmid structure based on long-read sequencing technologies, with a focus on analysing the complex structures of the MDR region, which is expected to exhibit genetic polymorphism or plasmid heterogeneity in various MDR-encoding elements even among members of the same strain. The availability of a single-molecule sequencing technique represents a paradigm shift in the capability of performing population genetic analysis of antibiotic-resistant organisms.

Long-read metagenomic exploration of extrachromosomal mobile genetic elements in the human gut

BACKGROUND

Elucidating the ecological and biological identity of extrachromosomal mobile genetic elements (eMGEs), such as plasmids and bacteriophages, in the human gut remains challenging due to their high complexity and diversity.

RESULTS

Here, we show efficient identification of eMGEs as complete circular or linear contigs from PacBio long-read metagenomic data. De novo assembly of PacBio long reads from 12 faecal samples generated 82 eMGE contigs (2.5~666.7-kb), which were classified as 71 plasmids and 11 bacteriophages, including 58 novel plasmids and six bacteriophages, and complete genomes of five diverse crAssphages with terminal direct repeats. In a dataset of 413 gut metagenomes from five countries, many of the identified plasmids were highly abundant and prevalent. The ratio of gut plasmids by our plasmid data is more than twice that in the public database. Plasmids outnumbered bacterial chromosomes three to one on average in this metagenomic dataset. Host prediction suggested that Bacteroidetes-associated plasmids predominated, regardless of microbial abundance. The analysis found several plasmid-enriched functions, such as inorganic ion transport, while antibiotic resistance genes were harboured mostly in low-abundance Proteobacteria-associated plasmids.

CONCLUSIONS

Overall, long-read metagenomics provided an efficient approach for unravelling the complete structure of human gut eMGEs, particularly plasmids.

PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures

Plasmids are mobile genetics elements that play an important role in the environmental adaptation of microorganisms. Although plasmids are usually analyzed in cultured microorganisms, there is a need for methods that allow for the analysis of pools of plasmids (plasmidomes) in environmental samples. To that end, several molecular biology and bioinformatics methods have been developed; however, they are limited to environments with low diversity and cannot recover large plasmids. Here, we present PlasFlow, a novel tool based on genomic signatures that employs a neural network approach for identification of bacterial plasmid sequences in environmental samples. PlasFlow can recover plasmid sequences from assembled metagenomes without any prior knowledge of the taxonomical or functional composition of samples with an accuracy up to 96%. It can also recover sequences of both circular and linear plasmids and can perform initial taxonomical classification of sequences. Compared to other currently available tools, PlasFlow demonstrated significantly better performance on test datasets. Analysis of two samples from heavy metal-contaminated microbial mats revealed that plasmids may constitute an important fraction of their metagenomes and carry genes involved in heavy-metal homeostasis, proving the pivotal role of plasmids in microorganism adaptation to environmental conditions.

Large Circular Plasmids from Groundwater Plasmidomes Span Multiple Incompatibility Groups and Are Enriched in Multimetal Resistance Genes

Naturally occurring plasmids constitute a major category of mobile genetic elements responsible for harboring and transferring genes important in survival and fitness. A targeted evaluation of plasmidomes can reveal unique adaptations required by microbial communities. We developed a model system to optimize plasmid DNA isolation procedures targeted to groundwater samples which are typically characterized by low cell density (and likely variations in the plasmid size and copy numbers). The optimized method resulted in successful identification of several hundred circular plasmids, including some large plasmids (11 plasmids more than 50 kb in size, with the largest being 1.7 Mb in size). Several interesting observations were made from the analysis of plasmid DNA isolated in this study. The plasmid pool (plasmidome) was more conserved than the corresponding microbiome distribution (16S rRNA based). The circular plasmids were diverse as represented by the presence of seven plasmid incompatibility groups. The genes carried on these groundwater plasmids were highly enriched in metal resistance. Results from this study confirmed that traits such as metal, antibiotic, and phage resistance along with toxin-antitoxin systems are encoded on abundant circular plasmids, all of which could confer novel and advantageous traits to their hosts. This study confirms the ecological role of the plasmidome in maintaining the latent capacity of a microbiome, enabling rapid adaptation to environmental stresses.IMPORTANCE Plasmidomes have been typically studied in environments abundant in bacteria, and this is the first study to explore plasmids from an environment characterized by low cell density. We specifically target groundwater, a significant source of water for human/agriculture use. We used samples from a well-studied site and identified hundreds of circular plasmids, including one of the largest sizes reported in plasmidome studies. The striking similarity of the plasmid-borne ORFs in terms of taxonomical and functional classifications across several samples suggests a conserved plasmid pool, in contrast to the observed variability in the 16S rRNA-based microbiome distribution. Additionally, the stress response to environmental factors has stronger conservation via plasmid-borne genes as marked by abundance of metal resistance genes. Last, identification of novel and diverse plasmids enriches the existing plasmid database(s) and serves as a paradigm to increase the repertoire of biological parts that are available for modifying novel environmental strains.

A Comparison of Methods for the Extraction of Plasmids Capable of Conferring Antibiotic Resistance in a Human Pathogen From Complex Broiler Cecal Samples

The direct extraction of plasmid DNA containing antibiotic resistance genes from complex samples is imperative when studying plasmid-mediated antibiotic resistance from a One Health perspective, in order to obtain a wide representation of all the resistance plasmids present in these microbial communities. There are also relatively few bacterial species from natural environments which can be cultured in vitro. Extracting plasmids from the cultivable fraction of these complex microbiomes may only represent a fraction of the total antibiotic resistance plasmids present. We compared different methods of plasmid extraction from broiler cecal samples, whose resistance could be expressed in a human pathogen—Escherichia coli. We found that kits designed for DNA extraction from complex samples such as soil or feces did not extract intact plasmid DNA. Commercial kits specific for plasmid extraction were also generally unsuccessful, most likely due to the complexity of our sample and intended use of the kits with bacterial culture. An alkaline lysis method specific for plasmid extraction was ineffective, even with further optimization. Transposon-aided capture of plasmids (TRACA) allowed for the acquirement of a small range of resistance plasmids. Multiple displacement amplification provided the broadest range of resistance plasmids by amplifying all extracted circular plasmid DNA, but the results were not reproducible across all samples. Exogenous plasmid isolation enabled the extraction of resistance plasmids from the microbial fraction by relying on the mobility of the plasmids in the sample. This was the most consistent method from which we obtained a range of resistance plasmids from our samples. We therefore recommend the use of the exogenous plasmid isolation method in order to reliably obtain the greatest representation of the total antibiotic resistance plasmidome in complex samples. While this method has limitations, it is one which will vastly increase our current knowledge of antibiotic resistance plasmids present in complex environments and which are capable of transferring to a human and animal pathogen and environmental contaminant.

Evolution of Plasmid-Mediated Antibiotic Resistance in the Clinical Context

Antibiotic-resistant infections are an urgent problem in clinical settings because they sharply increase mortality risk in critically ill patients. The horizontal spread of antibiotic resistance genes among bacteria is driven by bacterial plasmids, promoting the evolution of resistance. Crucially, particular associations exist between resistance plasmids and bacterial clones that become especially successful in clinical settings. However, the factors underlying the success of these associations remain unknown. Recent in vitro evidence reveals (i) that plasmids produce fitness costs in bacteria, and (ii) that these costs are alleviated over time through compensatory mutations. I argue that plasmid-imposed costs and subsequent compensatory adaptation may determine the success of associations between plasmids and bacteria in clinical settings, shaping the in vivo evolution of antibiotic resistance.

Plasmid Classification in an Era of Whole-Genome Sequencing: Application in Studies of Antibiotic Resistance Epidemiology

Plasmids are extra-chromosomal genetic elements ubiquitous in bacteria, and commonly transmissible between host cells. Their genomes include variable repertoires of 'accessory genes,' such as antibiotic resistance genes, as well as 'backbone' loci which are largely conserved within plasmid families, and often involved in key plasmid-specific functions (e.g., replication, stable inheritance, mobility). Classifying plasmids into different types according to their phylogenetic relatedness provides insight into the epidemiology of plasmid-mediated antibiotic resistance. Current typing schemes exploit backbone loci associated with replication (replicon typing), or plasmid mobility (MOB typing). Conventional PCR-based methods for plasmid typing remain widely used. With the emergence of whole-genome sequencing (WGS), large datasets can be analyzed using in silico plasmid typing methods. However, short reads from popular high-throughput sequencers can be challenging to assemble, so complete plasmid sequences may not be accurately reconstructed. Therefore, localizing resistance genes to specific plasmids may be difficult, limiting epidemiological insight. Long-read sequencing will become increasingly popular as costs decline, especially when resolving accurate plasmid structures is the primary goal. This review discusses the application of plasmid classification in WGS-based studies of antibiotic resistance epidemiology; novel in silico plasmid analysis tools are highlighted. Due to the diverse and plastic nature of plasmid genomes, current typing schemes do not classify all plasmids, and identifying conserved, phylogenetically concordant genes for subtyping and phylogenetics is challenging. Analyzing plasmids as nodes in a network that represents gene-sharing relationships between plasmids provides a complementary way to assess plasmid diversity, and allows inferences about horizontal gene transfer to be made.

Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond

Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.