COPLA, a taxonomic classifier of plasmids.

BACKGROUND: Plasmids are mobile genetic elements, key in the dissemination of antibiotic resistance, virulence determinants and other adaptive traits in bacteria. Obtaining a robust method for plasmid classification is necessary to better understand the genetics and epidemiology of many pathogens. Until now, plasmid classification systems focused on specific traits, which limited their precision and universality. The definition of plasmid taxonomic units (PTUs), based on average nucleotide identity metrics, allows the generation of a universal plasmid classification scheme, applicable to all bacterial taxa. Here we present COPLA, a software able to assign plasmids to known and novel PTUs, based on their genomic sequence. RESULTS: We implemented an automated pipeline able to assign a given plasmid DNA sequence to its cognate PTU, and assessed its performance using a sample of 1000 unclassified plasmids. Overall, 41% of the samples could be assigned to a previously defined PTU, a number that reached 63% in well-known taxa such as the Enterobacterales order. The remaining plasmids represent novel PTUs, indicating that a large fraction of plasmid backbones is still uncharacterized. CONCLUSIONS: COPLA is a bioinformatic tool for universal, species-independent, plasmid classification. Offered both as an automatable pipeline and an open web service, COPLA will help bacterial geneticists and clinical microbiologists to quickly classify plasmids.

PLACNETw: a web-based tool for plasmid reconstruction from bacterial genomes.

SUMMARY: PLACNET is a graph-based tool for reconstruction of plasmids from next generation sequence pair-end datasets. PLACNET graphs contain two types of nodes (assembled contigs and reference genomes) and two types of edges (scaffold links and homology to references). Manual pruning of the graphs is a necessary requirement in PLACNET, but this is difficult for users without solid bioinformatic background. PLACNETw, a webtool based on PLACNET, provides an interactive graphic interface, automates BLAST searches, and extracts the relevant information for decision making. It allows a user with domain expertise to visualize the scaffold graphs and related information of contigs as well as reference sequences, so that the pruning operations can be done interactively from a personal computer without the need for additional tools. After successful pruning, each plasmid becomes a separate connected component subgraph. The resulting data are automatically downloaded by the user. AVAILABILITY AND IMPLEMENTATION: PLACNETw is freely available at https://castillo.dicom.unican.es/upload/. CONTACT: delacruz@unican.es. SUPPLEMENTARY INFORMATION: A tutorial video and several solved examples are available at https://castillo.dicom.unican.es/placnetw_video/ and https://castillo.dicom.unican.es/examples/.

Mobile genetic elements define the non-random structure of the Salmonella enterica serovar Typhi pangenome.

Bacterial relatedness measured using select chromosomal loci forms the basis of public health genomic surveillance. While approximating vertical evolution through this approach has proven exceptionally valuable for understanding pathogen dynamics, it excludes a fundamental dimension of bacterial evolution-horizontal gene transfer. Incorporating the accessory genome is the logical remediation and has recently shown promise in expanding epidemiological resolution for enteric pathogens. Employing k-mer-based Jaccard index analysis, and a novel genome length distance metric, we computed pangenome (i.e., core and accessory) relatedness for the globally important pathogen Salmonella enterica serotype Typhi (Typhi), and graphically express both vertical (homology-by-descent) and horizontal (homology-by-admixture) evolutionary relationships in a reticulate network of over 2,200 U.S. Typhi genomes. This analysis revealed non-random structure in the Typhi pangenome that is driven predominantly by the gain and loss of mobile genetic elements, confirming and expanding upon known epidemiological patterns, revealing novel plasmid dynamics, and identifying avenues for further genomic epidemiological exploration. With an eye to public health application, this work adds important biological context to the rapidly improving ways of analyzing bacterial genetic data and demonstrates the value of the accessory genome to infer pathogen epidemiology and evolution.IMPORTANCEGiven bacterial evolution occurs in both vertical and horizontal dimensions, inclusion of both core and accessory genetic material (i.e., the pangenome) is a logical step toward a more thorough understanding of pathogen dynamics. With an eye to public, and indeed, global health relevance, we couple contemporary tools for genomic analysis with decades of research on mobile genetic elements to demonstrate the value of the pangenome, known and unknown, annotated, and hypothetical, for stratification of Salmonella enterica serovar Typhi (Typhi) populations. We confirm and expand upon what is known about Typhi epidemiology, plasmids, and antimicrobial resistance dynamics, and offer new avenues of exploration to further deduce Typhi ecology and evolution, and ultimately to reduce the incidence of human disease.

Determination of conjugation rates on solid surfaces.

A cytometric method for the estimation of end-point conjugation rates is developed and adapted to surface conjugation. This method improves the through-put of conjugation assays based on replica-plating and results in less noisy experimental data. Although conjugation on solid surfaces deviates from ideal conditions in which cells are continuously mixed, results show that, within the limits of high initial population densities and short mating times, end-point estimates of the conjugation rates are robust measurements. They are independent of the donor/recipient ratios and, to some extent, of the sampling time. Remixing the mating population in the course of a conjugation experiment results in a boost in the frequency of transconjugants.

Numbers on the edges: a simplified and scalable method for quantifying the gene regulation function.

The gene regulation function (GRF) provides an operational description of a promoter behavior as a function of the concentration of one of its transcriptional regulators. Behind this apparently trivial definition lies a central concept in biological control: the GRF provides the input/output relationship of each edge in a transcriptional network, independently from the molecular interactions involved. Here we discuss how existing methods allow direct measurement of the GRF, and how several trade-offs between scalability and accuracy have hindered its application to relatively large networks. We discuss the theoretical and technical requirements for obtaining the GRF. Based on these requirements, we introduce a simplified and easily scalable method that is able to capture the significant parameters of the GRF. The GRF is able to predict the behavior of a simple genetic circuit, illustrating how addressing the quantitative nature of gene regulation substantially increases our comprehension on the mechanisms of gene control.

MOBscan: Automated Annotation of MOB Relaxases.

Relaxase-based plasmid classification has become popular in the past 10 years. Nevertheless, it is not obvious how to assign a query protein to a relaxase MOB family. Automated protein annotation is commonly used to classify them into families, gathering evolutionarily related proteins that likely perform the same function, while circumventing the problem of different naming conventions. Here, we implement an automated method, MOBscan, to identify relaxases and classify them into any of the nine MOB families. MOBscan is a web tool that carries out a HMMER search against a curated database of MOB profile Hidden Markov models. It is freely available at https://castillo.dicom.unican.es/mobscan/ .

Plasmid Reconstruction from Next-Gen Data: A Detailed Protocol for the Use of PLACNETw for the Reconstruction of Plasmids from WGS Datasets.

Mobile Genetic Elements (MGE) play essential roles in adaptive bacterial evolution, facilitating genetic exchange for extrachromosomal DNA, especially antibiotic resistance genes and virulence factors. For this reason, high-throughput next-generation sequencing of bacteria is of great relevance, especially for clinical pathogenic bacteria. Accurate identification of MGE from whole-genome sequencing (WGS) datasets is one of the major challenges, still hindered by methodological limitations and high sequencing costs.This chapter encompasses the protocol used for plasmid reconstruction by applying the PLACNETw methodology, from raw reads to assembled plasmids and chromosome. PLACNETw is a graphical user-friendly interface to visualize and reconstruct MGE from short-read WGS datasets. No bioinformatic background or sophisticated computational resources are required and high precision and sensitivity are achieved.

Pathways for horizontal gene transfer in bacteria revealed by a global map of their plasmids.

Plasmids can mediate horizontal gene transfer of antibiotic resistance, virulence genes, and other adaptive factors across bacterial populations. Here, we analyze genomic composition and pairwise sequence identity for over 10,000 reference plasmids to obtain a global map of the prokaryotic plasmidome. Plasmids in this map organize into discrete clusters, which we call plasmid taxonomic units (PTUs), with high average nucleotide identity between its members. We identify 83 PTUs in the order Enterobacterales, 28 of them corresponding to previously described archetypes. Furthermore, we develop an automated algorithm for PTU identification, and validate its performance using stochastic blockmodeling. The algorithm reveals a total of 276 PTUs in the bacterial domain. Each PTU exhibits a characteristic host distribution, organized into a six-grade scale (I-VI), ranging from plasmids restricted to a single host species (grade I) to plasmids able to colonize species from different phyla (grade VI). More than 60% of the plasmids in the global map are in groups with host ranges beyond the species barrier.

Dynamics of the IncW genetic backbone imply general trends in conjugative plasmid evolution.

Plasmids cannot be understood as mere tools for genetic exchange: they are themselves subject to the forces of evolution. Their genomic and phylogenetic features have been less studied in this respect. Focusing on the IncW incompatibility group, which includes the smallest known conjugative plasmids, we attempt to unveil some common trends in plasmid evolution. The functional modules of IncW genetic backbone are described, with emphasis on their architecture and relationships to other plasmid groups. Some plasmid regions exhibit strong phylogenetic mosaicism, in striking contrast to others of unusual synteny conservation. The presence of genes of unknown function that are widely distributed in plasmid genomes is also emphasized, exposing the existence of ill-defined yet conserved plasmid functions. Conjugation is an essential hallmark of IncW plasmid biology and special attention is given to the organization and evolution of its transfer modules. Genetic exchange between plasmids and their hosts is analysed by following the evolution of the type IV secretion system. Adaptation of the trw conjugative machinery to pathogenicity functions in Bartonella is discussed as an example of how plasmids can change their host modus vivendi. Starting from the phage paradigm, our analysis articulates novel concepts that apply to plasmid evolution.