BackgroundMosquito-borne diseases threaten over half the world’s human population, making the need for environmentally-safe mosquito population control tools critical. The sterile insect technique (SIT) is a biological control method that can reduce pest insect populations by releasing a large number of sterile males to compete with wild males for female mates to reduce the number of progeny produced. Typically, males are sterilized using radiation, but such methods can reduce their mating competitiveness. The method is also most effective if only males are produced, but this requires the development of effective sex-sorting methods. Recent efforts to use transgenic methods to produce sterile male mosquitoes have increased interest in using SIT to control some of our most serious disease vectors, but the release of genetically modified mosquitoes will undoubtedly encounter considerable delays as regulatory agencies deal with safety issues and public concerns.MethodsTestis genes in the dengue vector Aedes aegypti were identified using a suppression subtractive hybridization technique. Mosquito larvae were fed double-stranded RNAs (dsRNAs) that targeted both the testis genes and a female sex determination gene (doublesex) to induce RNA interference (RNAi) -mediated sterility and inhibition of female development. Fertility and mating competiveness of the treated males were assessed in small-scale mating competition experiments.ResultsFeeding mosquito larvae dsRNAs targeting testis genes produced adult males with greatly reduced fertility; several dsRNAs produced males that were highly effective in competing for mates. RNAi-mediated knockdown of the female-specific isoform of doublesex was also effective in producing a highly male-biased population of mosquitoes, thereby overcoming the need to sex-sort insects before release.ConclusionsThe sequence-specific gene-silencing mechanism of this RNAi technology renders it adaptable for species-specific application across numerous insect species. We envisage its use for traditional large-scale reared releases of mosquitoes and other pest insects, although the technology might also have potential for field-based control of mosquitoes where eggs deposited into a spiked larval site lead to the release of new sterile males.

IntroductionNext‐generation sequencing (NGS) has several advantages over conventional Sanger sequencing for HIV drug resistance (HIVDR) genotyping, including detection and quantitation of low‐abundance variants bearing drug resistance mutations (DRMs). However, the high HIV genomic diversity, unprecedented large volume of data, complexity of analysis and potential for error pose significant challenges for data processing. Several NGS analysis pipelines have been developed and used in HIVDR research; however, the absence of uniformity in data processing strategies results in lack of consistency and comparability of outputs from different pipelines. To fill this gap, an international symposium on bioinformatic strategies for NGS‐based HIVDR testing was held in February 2018 in Winnipeg, Canada, convening laboratory scientists, bioinformaticians and clinicians involved in four recently developed, publicly available NGS HIVDR pipelines. The goal of this symposium was to establish a consensus on effective bioinformatic strategies for NGS data management and its use for HIVDR reporting.DiscussionEssential functionalities of an NGS HIVDR pipeline were divided into five analytic blocks: (1) NGS read quality control (QC)/quality assurance (QA); (2) NGS read alignment and reference mapping; (3) HIV variant calling and variant QC; (4) NGS HIVDR reporting; and (5) extended data applications and additional considerations for data management. The consensuses reached among the participants on all major aspects of these blocks are summarized here. They encompass not only recommended data management and analysis strategies, but also detailed bioinformatic approaches that help ensure accuracy of the derived HIVDR analysis outputs for both research and potential clinical use.ConclusionsWhile NGS is being adopted more broadly in HIVDR testing laboratories, data processing is often a bottleneck hindering its generalized application. The proposed standardization of NGS read QC/QA, read alignment and reference mapping, variant calling and QC, HIVDR reporting and relevant data management strategies in this “Winnipeg Consensus” may serve as a starting guideline for NGS HIVDR data processing that informs the refinement of existing pipelines and those yet to be developed. Moreover, the bioinformatic strategies presented here may apply more broadly to NGS data analysis of microbes harbouring significant genomic diversity.

Next generation sequencing (NGS) is a trending new standard for genotypic HIV-1 drug resistance (HIVDR) testing. Many NGS HIVDR data analysis pipelines have been independently developed, each with variable outputs and data management protocols. Standardization of such analytical methods and comparison of available pipelines are lacking, yet may impact subsequent HIVDR interpretation and other downstream applications. Here we compared the performance of five NGS HIVDR pipelines using proficiency panel samples from NIAID Virology Quality Assurance (VQA) program. Ten VQA panel specimens were genotyped by each of six international laboratories using their own in-house NGS assays. Raw NGS data were then processed using each of the five different pipelines including HyDRA, MiCall, PASeq, Hivmmer and DEEPGEN. All pipelines detected amino acid variants (AAVs) at full range of frequencies (1~100%) and demonstrated good linearity as compared to the reference frequency values. While the sensitivity in detecting low abundance AAVs, with frequencies between 1~20%, is less a concern for all pipelines, their specificity dramatically decreased at AAV frequencies <2%, suggesting that 2% threshold may be a more reliable reporting threshold for ensured specificity in AAV calling and reporting. More variations were observed among the pipelines when low abundance AAVs are concerned, likely due to differences in their NGS read quality control strategies. Findings from this study highlight the need for standardized strategies for NGS HIVDR data analysis, especially for the detection of minority HiVDR variants.Genotypic HIV drug resistance (HIVDR) testing not only guides effective clinical care of HIV-infected patients but also serves to provide surveillance of transmitted HIVDR in the population. Treatment guidelines in resource-permitted settings advocate the use of HIVDR monitoring both prior to ART initiation and when treatment failure is suspected 1,2 . There is increasing evidence showing that the presence of minority resistance variants open Scientific RepoRtS | (2020) 10:1634 | https://doi.org/10.1038/s41598-020-58544-z www.nature.com/scientificreports www.nature.com/scientificreports/ (MRV) in the HIV quasispecies (i.e., a swarm of highly-related but genotypically different viral variants) may be clinically significant and increase the risk of virological failure, impair immune recovery, lead to accumulation of drug resistance, increase risk of treatment switches and death [3][4][5][6][7][8] . A nationwide study in Mexico focusing on pretreatment drug resistance (PDR) found that lowering the detection threshold for PDR to 5% versus the conventional 20% improved the ability to identify patients with virological failure 6 . In addition, a European wide study found that pre-existing minority drug-resistant HIV-1 variants more than doubled the risk of virological failure to first-line NNRTI-based ART 9 . A more recent African study also reported similar findings, suggesting lowering the threshold below 20% improved the ability to i...

Conventional HIV drug resistance (HIVDR) genotyping utilizes Sanger sequencing (SS) methods, which are limited by low data throughput and the inability of detecting low abundant drug resistant variants (LADRVs). Here we present a next generation sequencing (NGS)-based HIVDR typing platform that leverages the advantages of Illumina MiSeq and HyDRA Web. The platform consists of a fully validated sample processing protocol and HyDRA web, an open web portal that allows automated customizable NGS-based HIVDR data processing. This platform was characterized and validated using a panel of HIV-spiked plasma representing all major HIV-1 subtypes, pedigreed plasmids, HIVDR proficiency specimens and clinical specimens. All examined major HIV-1 subtypes were consistently amplified at viral loads of ≥1,000 copies/ml. The gross error rate of this platform was determined at 0.21%, and minor variations were reliably detected down to 0.50% in plasmid mixtures. All HIVDR mutations identifiable by SS were detected by the MiSeq-HyDRA protocol, while LADRVs at frequencies of 1~15% were detected by MiSeq-HyDRA only. As compared to SS approaches, the MiSeq-HyDRA platform has several notable advantages including reduced cost and labour, and increased sensitivity for LADRVs, making it suitable for routine HIVDR monitoring for both patient care and surveillance purposes.

Human immunodeficiency virus type 1 (HIV-1) is able to evade the host cytotoxic T-lymphocyte (CTL)response through a variety of escape avenues. Epitopes that are presented to CTLs are first processed in the presenting cell in several steps, including proteasomal cleavage, transport to the endoplasmic reticulum, binding by the HLA molecule, and finally presentation to the T-cell receptor. An understanding of the potential of the virus to escape CTL responses can aid in designing an effective vaccine. To investigate such a potential, we analyzed HIV-1 gag from 468 HIV-1-positive Kenyan women by using several bioinformatic approaches that allowed the identification of positively selected amino acids in the HIV-1 gag region and study of the effects that these mutations could have on the various stages of antigen processing. Correlations between positively selected residues and mean CD4 counts also allowed study of the effect of mutation on HIV disease progression. A number of mutations that could create or destroy proteasomal cleavage sites or reduce binding affinity of the transport antigen processing protein, effectively hindering epitope presentation, were identified. Many mutations correlated with the presence of specific HLA alleles and with lower or higher CD4 counts. For instance, the mutation V190I in subtype A1-infected individuals is associated with HLA-B*5802 (P ‫؍‬ 4.73 ؋ 10 ؊4 ), a rapid-progression allele according to other studies, and also to a decreased mean CD4 count (P ‫؍‬ 0.019). Thus, V190I is a possible HLA escape mutant. This method classifies many positively selected mutations across the entire gag region according to their potential for immune escape and their effect on disease progression.