DisCVR: Rapid viral diagnosis from high-throughput sequencing data

Application of next-generation sequencing to identify different pathogens

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing the prevalence of clinical infectious diseases. Traditional pathogen detection techniques, which include mass spectrometry, biochemical tests, molecular testing, and culture-based methods, are limited in application and are time-consuming. Next generation sequencing (NGS) has emerged as an essential technology for identifying pathogens. NGS is a cutting-edge sequencing method with high throughput that can create massive volumes of sequences with a broad application prospects in the field of pathogen identification and diagnosis. In this review, we introduce NGS technology in detail, summarizes the application of NGS in that identification of different pathogens, including bacteria, fungi, and viruses, and analyze the challenges and outlook for using NGS to identify clinical pathogens. Thus, this work provides a theoretical basis for NGS studies and provides evidence to support the application of NGS in distinguishing various clinical pathogens.

Next Generation Sequencing Approaches to Characterize the Respiratory Tract Virome

The COVID-19 pandemic and heightened perception of the risk of emerging viral infections have boosted the efforts to better understand the virome or complete repertoire of viruses in health and disease, with a focus on infectious respiratory diseases. Next-generation sequencing (NGS) is widely used to study microorganisms, allowing the elucidation of bacteria and viruses inhabiting different body systems and identifying new pathogens. However, NGS studies suffer from a lack of standardization, in particular, due to various methodological approaches and no single format for processing the results. Here, we review the main methodological approaches and key stages for studies of the human virome, with an emphasis on virome changes during acute respiratory viral infection, with applications for clinical diagnostics and epidemiologic analyses.

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Deep Profiling Identifies Selection of Nonsynonymous Amino Acid Substitutions in HIV-1 Envelope During Early Infection

Understanding the evolutionary dynamics of the viruses within an individual at or near the moment of transmission can provide critical inputs for the design of an effective vaccine for HIV infection. In this study, high-throughput sequencing technology was employed to analyze the evolutionary rate in viruses obtained at a single time point from drug-naive recently infected infants and adults in the chronic stage of disease. Gene-wise nonsynonymous (pN) and synonymous (pS) mutation rates were estimated and compared between the two groups. Significant differences were observed in the evolutionary rates between viruses in the early and late stages of infection. Higher rates of adaptive mutations in the HIV-1 envelope gene (env) were found in the chronic viruses as compared with those in the early stages of HIV infection. Conversely, percentage of nonsynonymous substitutions in env was found to be higher in recently transmitted viruses. In addition, a positive correlation was found between mutation and the evolutionary rate, and infectivity titer in recent infection. Despite the small sample size, the study identified useful information about viral evolution on transmission-associated bottlenecks. The effect of intraindividual HIV-1 evolution at the population level was highly contemporary, and the higher percentage of nonsynonymous substitutions seen in env during recent HIV-1 infection has suggested a pattern of convergent evolution leading to a positive selection for survival fitness and disease progression.