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Characterization of the within-host genetic diversity of viral pathogens is required for selection of effective treatment of some important viral infections, e.g. HIV, HBV and HCV. Despite the technical ability of detection, there are conflicting data regarding the clinical significance of low-frequency variants, partially because of the difficulty of their distinguishing from experimental artifacts. The issue of cross-contamination is relevant for all highly sensitive techniques, including deep sequencing: even trace contamination leads to a significant increase of false positives in identified SNVs. Determination of infections by multiple genotypes of some viruses, the incidence of which can be considerable, especially in risk groups, is also clinically significant in some cases. We developed a new viral reference-guided assembler, VirGenA, that can separate mixtures of strains of different intraspecies genetic groups (genotypes, subtypes, clades, etc.) and assemble a separate consensus sequence for each group in a mixture. It produced long assemblies for mixture components of extremely low frequencies (<1%) allowing detection of cross-contamination of samples by divergent genotypes. We tested VirGenA on both clinical and simulated data. On both types of data, VirGenA shows better or similar results than the existing de novo assemblers. Cross-platform implementation (including source code) is freely available at https://github.com/gFedonin/VirGenA/releases.

The accuracy and sensitivity of deep sequencing were assessed using viral standards (pNL4-3 and pLAI.2) of both DNA and RNA. The sequencing accuracy did not depend on the type of nucleic acid, but critically depended on the number of reads and threshold of sensitivity to minor viral populations. With coverage of more than 236 reads, the accuracy of viral RNA sequencing was equal to or exceeded 99.9%, with a sensitivity threshold to minor nucleotides of 20%. When the sensitivity threshold was below 1%, reduced accuracy dynamics were clearly visible even when the coverage was massive (more than 9.000 reads). It was found that the floating sensitivity threshold allowed the sequencing accuracy to be maintained at an acceptable level in cases of low coverage (less than 1.500-2.000) of reads. These results indicate the quality that can be expected with a specific number of reads and sensitivity threshold. Deep sequencing is a very powerful tool that can significantly improve the value of study results, but despite its superior performance, it should be used with caution regarding its sensitivity to minor populations below 1%., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Sanger sequencing is a common method of reading DNA sequences. It is less expensive than high-throughput methods, and it is appropriate for numerous applications including molecular diagnostics. However, sequencing mixtures of similar DNA of pathogens with this method is challenging. This is important because most clinical samples contain such mixtures, rather than pure single strains. The traditional solution is to sequence selected clones of PCR products, a complicated, time-consuming, and expensive procedure. Here, we propose the base-calling with vocabulary (BCV) method that computationally deciphers Sanger chromatograms obtained from mixed DNA samples. The inputs to the BCV algorithm are a chromatogram and a dictionary of sequences that are similar to those we expect to obtain. We apply the base-calling function on a test dataset of chromatograms without ambiguous positions, as well as one with 3-14% sequence degeneracy. Furthermore, we use BCV to assemble a consensus sequence for an HIV genome fragment in a sample containing a mixture of viral DNA variants and to determine the positions of the indels. Finally, we detect drug-resistant Mycobacterium tuberculosis strains carrying frameshift mutations mixed with wild-type bacteria in the pncA gene, and roughly characterize bacterial communities in clinical samples by direct 16S rRNA sequencing.

The charged quaternary ammonium compounds--methyl, ethyl and benzyl viologens--generate reactive oxygen species in photosynthetic cells. Three independent methyl viologen-resistant spontaneous mutants of Synechocystis sp. PCC 6803 were identified, in which the conserved R115 residue of the Slr1174 protein was replaced with G115, L115 and C115. The Slr1174 protein of the DUF990 family is related to the permease subunit of an ABC-2-type transporter and its R115 mutation was found to be solely responsible for the observed methyl viologen resistance. Bioinformatic analysis showed that in various bacterial genomes, two genes encoding another permease subunit and the ATPase component of an ATP-binding cassette transporter form putative operons with slr1174 orthologs, suggesting that the protein products of these genes may form functional transporters. The corresponding genes in Synechocystis sp. PCC 6803, i.e. slr0610 for the permease and slr1901 for the ATPase, did not form such an operon. However, insertional inactivation of any slr1174, slr0610 or slr1901 genes in both the wild-type and the R115-resistant mutant resulted in increased sensitivity to methyl, ethyl and benzyl viologens; moreover, single- and double-insertion mutants did not differ in their viologen sensitivity. Our data suggest that Slr1901, Slr1174 and Slr0610 form a heteromeric ATP-binding cassette-type viologen exporter, in which each component is critical for viologen extrusion. Because the greatest increase in mutant sensitivity was observed in the case of ethyl viologen, the three proteins have been named EvrA (Slr1901), EvrB (Slr1174) and EvrC (Slr0610). This is the first report of a function for a DUF990 family protein.