Rapid phylogenetic analysis of African swine fever virus from metagenomic sequences

African swine fever virus (ASFV) has devastating impacts on swine health and the world economy. Rapid and accurate phylogenetic analysis of ASFV causing outbreaks is important to reveal diversity and evolutionary of ASFV. Because it is time-consuming and needs biosafety laboratories to isolate ASFV, here we present a new way to perform rapid genome-wide phylogenetic analysis of ASFV using an allele calling based on gene by gene approach directly from genome drafts assembled from metagenomic sequences. Using open-accessed chewBBACA software, 41 publicly available ASFV genomes were analyzed to optimize the parameters and find the alleles. Alleles as many as 94 were found for building the phylogenetic trees, which covered more than 56% of the whole genome. Based on the alleles, current ASFV isolates could be divided into two major clades and a few subclades. Then the method is used to analyze two ASFV genome drafts assembled from two metagenomic sequences of a swine whole blood and a swine spleen tissue collected in Wuhan, China. It shows that the two ASFV genomes showed highest similarity to that of Pig/HLJ/2018 strain and DB/LN/2018 strain, which isolated recently in China. This proved that the ASFV in Wuhan originate from the same source causing the earlier outbreaks in Helongjiang and Liaoning province of China. This method makes it possible to analyze phylogenetic analysis of ASFV draft genomes flexibly without the need of ASFV isolation. Furthermore, because it is based on Allele calling, the ASFV-specific genetic markers found could be translated into clinical diagnostics or can be used broadly to identify conserved putative therapeutic candidates.

chewBBACA: A complete suite for gene-by-gene schema creation and strain identification

ABSTRACTGene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. The software can run in a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available athttps://github.com/B-UMMI/chewBBACAor as a docker image athttps://hub.docker.com/r/ummidock/chewbbaca/.DATA SUMMARYAssembled genomes used for the tutorial were downloaded from NCBI in August 2016 by selecting those submitted asStreptococcus agalactiaetaxon or sub-taxa. All the assemblies have been deposited as a zip file in FigShare (https://figshare.com/s/9cbe1d422805db54cd52), where a file with the original ftp link for each NCBI directory is also available.Code for the chewBBACA suite is available athttps://github.com/B-UMMI/chewBBACAwhile the tutorial example is found athttps://github.com/B-UMMI/chewBBACA_tutorial.I/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. ⊠IMPACT STATEMENTThe chewBBACA software offers a computational solution for the creation, evaluation and use of whole genome (wg) and core genome (cg) multilocus sequence typing (MLST) schemas. It allows researchers to develop wg/cgMLST schemes for any bacterial species from a set of genomes of interest. The alleles identified by chewBBACA correspond to potential coding sequences, possibly offering insights into the correspondence between the genetic variability identified and phenotypic variability. The software performs allele calling in a matter of seconds to minutes per strain in a laptop but is easily scalable for the analysis of large datasets of hundreds of thousands of strains using multiprocessing options. The chewBBACA software thus provides an efficient and freely available open source solution for gene-by-gene methods. Moreover, the ability to perform these tasks locally is desirable when the submission of raw data to a central repository or web services is hindered by data protection policies or ethical or legal concerns.

High-Throughput Mycobacterial Interspersed Repetitive-Unit–Variable-Number Tandem-Repeat Genotyping for Mycobacterium tuberculosis Epidemiological Studies

The emergence of drug-resistant forms of tuberculosis (TB) represents a major public health concern. Understanding the transmission routes of the disease is a key factor for its control and for the implementation of efficient interventions. Mycobacterial interspersed repetitive-unit–variable-number tandem-repeat (MIRU-VNTR) marker typing is a well-described method for lineage identification and transmission tracking. However, the conventional manual genotyping technique is cumbersome and time-consuming and entails many risks for errors, thus hindering its implementation and dissemination. We describe here a new approach using the QIAxcel system, an automated high-throughput capillary electrophoresis system that also carries out allele calling. This automated method was assessed on 1,824 amplicons from 82 TB isolates and tested with sets of markers of 15 or 24 loci. Overall allele-calling concordance between the methods from 140 to 1,317 bp was 98.9%. DNA concentrations and repeatability and reproducibility performances showed no biases in allele calling. Furthermore, turnaround time using this automated system was reduced by 81% compared to the conventional manual agarose gel method. In sum, this new automated method facilitates MIRU-VNTR genotyping and provides reliable results. Therefore, it is well suited for field genotyping. The implementation of this method will help to achieve accurate and cost-effective epidemiological studies, especially in countries with a high prevalence of TB, where the high number of strains complicates the surveillance of circulating lineages and requires efficient interventions to be carried out in an urgent manner.