Exploring Barmah Forest virus pathogenesis: molecular tools to investigate non-structural protein 3 nuclear localization and viral genomic determinants of replication.

Barmah Forest virus (BFV) is a mosquito-borne virus that causes arthralgia with accompanying rash, fever, and myalgia in humans. The virus is mainly found in Australia and has caused outbreaks associated with significant health concerns. As the sole representative of the Barmah Forest complex within the genus Alphavirus, BFV is not closely related genetically to other alphaviruses. Notably, basic knowledge of BFV molecular virology has not been well studied due to a lack of critical investigative tools such as an infectious clone. Here we describe the construction of an infectious BFV cDNA clone based on Genbank sequence and demonstrate that the clone-derived virus has in vitro and in vivo properties similar to naturally occurring virus, BFV field isolate 2193 (BFV2193-FI). A substitution in nsP4, V1911D, which was identified in the Genbank reference sequence, was found to inhibit virus rescue and replication. T1325P substitution in nsP2 selected during virus passaging was shown to be an adaptive mutation, compensating for the inhibitory effect of nsP4-V1911D. The two mutations were associated with changes in viral non-structural polyprotein processing and type I interferon (IFN) induction. Interestingly, a nuclear localization signal, active in mammalian but not mosquito cells, was identified in nsP3. A point mutation abolishing nsP3 nuclear localization attenuated BFV replication. This effect was more prominent in the presence of type I interferon signaling, suggesting nsP3 nuclear localization might be associated with IFN antagonism. Furthermore, abolishing nsP3 nuclear localization reduced virus replication in mice but did not significantly affect disease.IMPORTANCEBarmah Forest virus (BFV) is Australia's second most prevalent arbovirus, with approximately 1,000 cases reported annually. The clinical symptoms of BFV infection include rash, polyarthritis, arthralgia, and myalgia. As BFV is not closely related to other pathogenic alphaviruses or well-studied model viruses, our understanding of its molecular virology and mechanisms of pathogenesis is limited. There is also a lack of molecular tools essential for corresponding studies. Here we describe the construction of an infectious clone of BFV, variants harboring point mutations, and sequences encoding marker protein. In infected mammalian cells, nsP3 of BFV was located in the nuclei. This finding extends our understanding of the diverse mechanisms used by alphavirus replicase proteins to interact with host cells. Our novel observations highlight the complex synergy through which the viral replication machinery evolves to correct mutation errors within the viral genome.

PlasmidSeeker: identification of known plasmids from bacterial whole genome sequencing reads.

BACKGROUND: Plasmids play an important role in the dissemination of antibiotic resistance, making their detection an important task. Using whole genome sequencing (WGS), it is possible to capture both bacterial and plasmid sequence data, but short read lengths make plasmid detection a complex problem. RESULTS: We developed a tool named PlasmidSeeker that enables the detection of plasmids from bacterial WGS data without read assembly. The PlasmidSeeker algorithm is based on k-mers and uses k-mer abundance to distinguish between plasmid and bacterial sequences. We tested the performance of PlasmidSeeker on a set of simulated and real bacterial WGS samples, resulting in 100% sensitivity and 99.98% specificity. CONCLUSION: PlasmidSeeker enables quick detection of known plasmids and complements existing tools that assemble plasmids de novo. The PlasmidSeeker source code is stored on GitHub: https://github.com/bioinfo-ut/PlasmidSeeker.

StrainSeeker: fast identification of bacterial strains from raw sequencing reads using user-provided guide trees.

BACKGROUND: Fast, accurate and high-throughput identification of bacterial isolates is in great demand. The present work was conducted to investigate the possibility of identifying isolates from unassembled next-generation sequencing reads using custom-made guide trees. RESULTS: A tool named StrainSeeker was developed that constructs a list of specific k-mers for each node of any given Newick-format tree and enables the identification of bacterial isolates in 1-2 min. It uses a novel algorithm, which analyses the observed and expected fractions of node-specific k-mers to test the presence of each node in the sample. This allows StrainSeeker to determine where the isolate branches off the guide tree and assign it to a clade whereas other tools assign each read to a reference genome. Using a dataset of 100 Escherichia coli isolates, we demonstrate that StrainSeeker can predict the clades of E. coli with 92% accuracy and correct tree branch assignment with 98% accuracy. Twenty-five thousand Illumina HiSeq reads are sufficient for identification of the strain. CONCLUSION: StrainSeeker is a software program that identifies bacterial isolates by assigning them to nodes or leaves of a custom-made guide tree. StrainSeeker's web interface and pre-computed guide trees are available at http://bioinfo.ut.ee/strainseeker. Source code is stored at GitHub: https://github.com/bioinfo-ut/StrainSeeker.