Quantifying the Evolutionary Constraints and Potential of Hepatitis C Virus NS5A Protein.

RNA viruses, such as hepatitis C virus (HCV), influenza virus, and SARS-CoV-2, are notorious for their ability to evolve rapidly under selection in novel environments. It is known that the high mutation rate of RNA viruses can generate huge genetic diversity to facilitate viral adaptation. However, less attention has been paid to the underlying fitness landscape that represents the selection forces on viral genomes, especially under different selection conditions. Here, we systematically quantified the distribution of fitness effects of about 1,600 single amino acid substitutions in the drug-targeted region of NS5A protein of HCV. We found that the majority of nonsynonymous substitutions incur large fitness costs, suggesting that NS5A protein is highly optimized. The replication fitness of viruses is correlated with the pattern of sequence conservation in nature, and viral evolution is constrained by the need to maintain protein stability. We characterized the adaptive potential of HCV by subjecting the mutant viruses to selection by the antiviral drug daclatasvir at multiple concentrations. Both the relative fitness values and the number of beneficial mutations were found to increase with the increasing concentrations of daclatasvir. The changes in the spectrum of beneficial mutations in NS5A protein can be explained by a pharmacodynamics model describing viral fitness as a function of drug concentration. Overall, our results show that the distribution of fitness effects of mutations is modulated by both the constraints on the biophysical properties of proteins (i.e., selection pressure for protein stability) and the level of environmental stress (i.e., selection pressure for drug resistance).IMPORTANCE Many viruses adapt rapidly to novel selection pressures, such as antiviral drugs. Understanding how pathogens evolve under drug selection is critical for the success of antiviral therapy against human pathogens. By combining deep sequencing with selection experiments in cell culture, we have quantified the distribution of fitness effects of mutations in hepatitis C virus (HCV) NS5A protein. Our results indicate that the majority of single amino acid substitutions in NS5A protein incur large fitness costs. Simulation of protein stability suggests viral evolution is constrained by the need to maintain protein stability. By subjecting the mutant viruses to selection under an antiviral drug, we find that the adaptive potential of viral proteins in a novel environment is modulated by the level of environmental stress, which can be explained by a pharmacodynamics model. Our comprehensive characterization of the fitness landscapes of NS5A can potentially guide the design of effective strategies to limit viral evolution.

Application of Deep Mutational Scanning in Hepatitis C Virus.

Mutagenesis is one of the key techniques in virus research. The recent development of deep mutational scanning allows the assessment of replication fitness effects of a large number of viral mutants in a high-throughput manner. Here, we describe a protocol for studying hepatitis C virus (HCV) using deep mutational scanning, which includes the methodologies for mutant library construction, passaging, sequencing, and data analysis.

Correction: Functional Constraint Profiling of a Viral Protein Reveals Discordance of Evolutionary Conservation and Functionality.

[This corrects the article DOI: 10.1371/journal.pgen.1005310.].

Systematic identification of anti-interferon function on hepatitis C virus genome reveals p7 as an immune evasion protein.

Hepatitis C virus (HCV) encodes mechanisms to evade the multilayered antiviral actions of the host immune system. Great progress has been made in elucidating the strategies HCV employs to down-regulate interferon (IFN) production, impede IFN signaling transduction, and impair IFN-stimulated gene (ISG) expression. However, there is a limited understanding of the mechanisms governing how viral proteins counteract the antiviral functions of downstream IFN effectors due to the lack of an efficient approach to identify such interactions systematically. To study the mechanisms by which HCV antagonizes the IFN responses, we have developed a high-throughput profiling platform that enables mapping of HCV sequences critical for anti-IFN function at high resolution. Genome-wide profiling performed with a 15-nt insertion mutant library of HCV showed that mutations in the p7 region conferred high levels of IFN sensitivity, which could be alleviated by the expression of WT p7 protein. This finding suggests that p7 protein of HCV has an immune evasion function. By screening a liver-specific ISG library, we identified that IFI6-16 significantly inhibits the replication of p7 mutant viruses without affecting WT virus replication. In contrast, knockout of IFI6-16 reversed the IFN hypersensitivity of p7 mutant virus. In addition, p7 was found to be coimmunoprecipitated with IFI6-16 and to counteract the function of IFI6-16 by depolarizing the mitochondria potential. Our data suggest that p7 is a critical immune evasion protein that suppresses the antiviral IFN function by counteracting the function of IFI6-16.

High-resolution genetic profile of viral genomes: why it matters.

The approval of novel antiviral treatments for hepatitis C virus (HCV) infection provides a great example of research driven medicine in action. However, the emergence of resistant viral strains to existing treatments reminds us of the ongoing challenge that we still face in HCV therapy. What can be done to minimize the health risk posed by viral variants that develop resistance and cause failure of therapy? Here we propose that a high-resolution genetic profiling approach that can assess the function at a single nucleotide/amino acid resolution, may provide a solution. We further discuss the potential application of this methodology in resolving viral resistance through the following three aspects: (1) high-resolution mapping of inflexible regions on the viral genome to identify better drug targets; (2) exhaustive drug resistance profiles to facilitate next-generation drug design; (3) coupled with closely monitoring within-host virus quasi-species, drug resistance profiles can aid in optimized drug combination and personalized medicine in HCV treatments.

Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection.

Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design.

Functional Constraint Profiling of a Viral Protein Reveals Discordance of Evolutionary Conservation and Functionality.

Viruses often encode proteins with multiple functions due to their compact genomes. Existing approaches to identify functional residues largely rely on sequence conservation analysis. Inferring functional residues from sequence conservation can produce false positives, in which the conserved residues are functionally silent, or false negatives, where functional residues are not identified since they are species-specific and therefore non-conserved. Furthermore, the tedious process of constructing and analyzing individual mutations limits the number of residues that can be examined in a single study. Here, we developed a systematic approach to identify the functional residues of a viral protein by coupling experimental fitness profiling with protein stability prediction using the influenza virus polymerase PA subunit as the target protein. We identified a significant number of functional residues that were influenza type-specific and were evolutionarily non-conserved among different influenza types. Our results indicate that type-specific functional residues are prevalent and may not otherwise be identified by sequence conservation analysis alone. More importantly, this technique can be adapted to any viral (and potentially non-viral) protein where structural information is available.

High-throughput profiling of point mutations across the HIV-1 genome.

BACKGROUND: The HIV-1 pandemic is not the result of a static pathogen but a large genetically diverse and dynamic viral population. The virus is characterized by a highly mutable genome rendering efforts to design a universal vaccine a significant challenge and drives the emergence of drug resistant variants upon antiviral pressure. Gaining a comprehensive understanding of the mutational tolerance of each HIV-1 genomic position is therefore of critical importance. RESULTS: Here we combine high-density mutagenesis with the power of next-generation sequencing to gauge the replication capacity and therefore mutational tolerability of single point mutations across the entire HIV-1 genome. We were able to achieve the evaluation of point mutational effects on viral replicative capacity for 5,553 individual HIV-1 nucleotide positions - representing 57% of the viral genome. Replicative capacity was assessed at 3,943 nucleotide positions for a single alternate base change, 1,459 nucleotide positions for two alternate base changes, and 151 nucleotide positions for all three possible alternate base changes. This resulted in the study of how a total of 7,314 individual point mutations impact HIV-1 replication on a single experimental platform. We further utilize the dataset for a focused structural analysis on a capsid inhibitor binding pocket. CONCLUSION: The approach presented here can be applied to any pathogen that can be genetically manipulated in a laboratory setting. Furthermore, the methodology can be utilized under externally applied selection conditions, such as drug or immune pressure, to identify genetic elements that contribute to drug or host interactions, and therefore mutational routes of pathogen resistance and escape.

Imaging and sizing of single DNA molecules on a mobile phone.

DNA imaging techniques using optical microscopy have found numerous applications in biology, chemistry and physics and are based on relatively expensive, bulky and complicated set-ups that limit their use to advanced laboratory settings. Here we demonstrate imaging and length quantification of single molecule DNA strands using a compact, lightweight and cost-effective fluorescence microscope installed on a mobile phone. In addition to an optomechanical attachment that creates a high contrast dark-field imaging setup using an external lens, thin-film interference filters, a miniature dovetail stage and a laser-diode for oblique-angle excitation, we also created a computational framework and a mobile phone application connected to a server back-end for measurement of the lengths of individual DNA molecules that are labeled and stretched using disposable chips. Using this mobile phone platform, we imaged single DNA molecules of various lengths to demonstrate a sizing accuracy of <1 kilobase-pairs (kbp) for 10 kbp and longer DNA samples imaged over a field-of-view of ∼2 mm2.

A comprehensive functional map of the hepatitis C virus genome provides a resource for probing viral proteins.

UNLABELLED: Pairing high-throughput sequencing technologies with high-throughput mutagenesis enables genome-wide investigations of pathogenic organisms. Knowledge of the specific functions of protein domains encoded by the genome of the hepatitis C virus (HCV), a major human pathogen that contributes to liver disease worldwide, remains limited to insight from small-scale studies. To enhance the capabilities of HCV researchers, we have obtained a high-resolution functional map of the entire viral genome by combining transposon-based insertional mutagenesis with next-generation sequencing. We generated a library of 8,398 mutagenized HCV clones, each containing one 15-nucleotide sequence inserted at a unique genomic position. We passaged this library in hepatic cells, recovered virus pools, and simultaneously assayed the abundance of mutant viruses in each pool by next-generation sequencing. To illustrate the validity of the functional profile, we compared the genetic footprints of viral proteins with previously solved protein structures. Moreover, we show the utility of these genetic footprints in the identification of candidate regions for epitope tag insertion. In a second application, we screened the genetic footprints for phenotypes that reflected defects in later steps of the viral life cycle. We confirmed that viruses with insertions in a region of the nonstructural protein NS4B had a defect in infectivity while maintaining genome replication. Overall, our genome-wide HCV mutant library and the genetic footprints obtained by high-resolution profiling represent valuable new resources for the research community that can direct the attention of investigators toward unidentified roles of individual protein domains. IMPORTANCE: Our insertional mutagenesis library provides a resource that illustrates the effects of relatively small insertions on local protein structure and HCV viability. We have also generated complementary resources, including a website (http://hangfei.bol.ucla.edu) and a panel of epitope-tagged mutant viruses that should enhance the research capabilities of investigators studying HCV. Researchers can now detect epitope-tagged viral proteins by established antibodies, which will allow biochemical studies of HCV proteins for which antibodies are not readily available. Furthermore, researchers can now quickly look up genotype-phenotype relationships and base further mechanistic studies on the residue-by-residue information from the functional profile. More broadly, this approach offers a general strategy for the systematic functional characterization of viruses on the genome scale.

Aging and age-related diseases--from endocrine therapy to target therapy.

Aging represents an important health issue not only for the individual, but also for society in general. Burdens associated with aging are expanding as longevity increases. This has led to an enhanced focus on issues related to aging and age-related diseases. Until recently, anti-aging endocrine-therapy has been largely limited to hormone-replacement therapy (HRT) that is associated with multiple side effects, including an increased risk of cancer. This has greatly limited the application of HRT in anti-aging therapy. Recently, the focus of anti-aging research has expanded from endocrine signaling pathways to effects on regulatory gene networks. In this regard, the GHRH-GH-IGF-1/Insulin, TOR-S6K1,NAD(+)-Sirtuin, P53, Klotho and APOE pathways have been linked to processes associated with age-related diseases, including cancer, cardiovascular disease, diabetes, osteoporosis, and neurodegenerative diseases, all of which directly influence health in aging, and represent key targets in anti-aging therapy.

High-throughput identification of loss-of-function mutations for anti-interferon activity in the influenza A virus NS segment.

UNLABELLED: Viral proteins often display several functions which require multiple assays to dissect their genetic basis. Here, we describe a systematic approach to screen for loss-of-function mutations that confer a fitness disadvantage under a specified growth condition. Our methodology was achieved by genetically monitoring a mutant library under two growth conditions, with and without interferon, by deep sequencing. We employed a molecular tagging technique to distinguish true mutations from sequencing error. This approach enabled us to identify mutations that were negatively selected against, in addition to those that were positively selected for. Using this technique, we identified loss-of-function mutations in the influenza A virus NS segment that were sensitive to type I interferon in a high-throughput fashion. Mechanistic characterization further showed that a single substitution, D92Y, resulted in the inability of NS to inhibit RIG-I ubiquitination. The approach described in this study can be applied under any specified condition for any virus that can be genetically manipulated. IMPORTANCE: Traditional genetics focuses on a single genotype-phenotype relationship, whereas high-throughput genetics permits phenotypic characterization of numerous mutants in parallel. High-throughput genetics often involves monitoring of a mutant library with deep sequencing. However, deep sequencing suffers from a high error rate (∼0.1 to 1%), which is usually higher than the occurrence frequency for individual point mutations within a mutant library. Therefore, only mutations that confer a fitness advantage can be identified with confidence due to an enrichment in the occurrence frequency. In contrast, it is impossible to identify deleterious mutations using most next-generation sequencing techniques. In this study, we have applied a molecular tagging technique to distinguish true mutations from sequencing errors. It enabled us to identify mutations that underwent negative selection, in addition to mutations that experienced positive selection. This study provides a proof of concept by screening for loss-of-function mutations on the influenza A virus NS segment that are involved in its anti-interferon activity.

High-throughput profiling of influenza A virus hemagglutinin gene at single-nucleotide resolution.

Genetic research on influenza virus biology has been informed in large part by nucleotide variants present in seasonal or pandemic samples, or individual mutants generated in the laboratory, leaving a substantial part of the genome uncharacterized. Here, we have developed a single-nucleotide resolution genetic approach to interrogate the fitness effect of point mutations in 98% of the amino acid positions in the influenza A virus hemagglutinin (HA) gene. Our HA fitness map provides a reference to identify indispensable regions to aid in drug and vaccine design as targeting these regions will increase the genetic barrier for the emergence of escape mutations. This study offers a new platform for studying genome dynamics, structure-function relationships, virus-host interactions, and can further rational drug and vaccine design. Our approach can also be applied to any virus that can be genetically manipulated.

HIV-1 quasispecies delineation by tag linkage deep sequencing.

Trade-offs between throughput, read length, and error rates in high-throughput sequencing limit certain applications such as monitoring viral quasispecies. Here, we describe a molecular-based tag linkage method that allows assemblage of short sequence reads into long DNA fragments. It enables haplotype phasing with high accuracy and sensitivity to interrogate individual viral sequences in a quasispecies. This approach is demonstrated to deduce ∼ 2000 unique 1.3 kb viral sequences from HIV-1 quasispecies in vivo and after passaging ex vivo with a detection limit of ∼ 0.005% to ∼ 0.001%. Reproducibility of the method is validated quantitatively and qualitatively by a technical replicate. This approach can improve monitoring of the genetic architecture and evolution dynamics in any quasispecies population.

A quantitative high-resolution genetic profile rapidly identifies sequence determinants of hepatitis C viral fitness and drug sensitivity.

Widely used chemical genetic screens have greatly facilitated the identification of many antiviral agents. However, the regions of interaction and inhibitory mechanisms of many therapeutic candidates have yet to be elucidated. Previous chemical screens identified Daclatasvir (BMS-790052) as a potent nonstructural protein 5A (NS5A) inhibitor for Hepatitis C virus (HCV) infection with an unclear inhibitory mechanism. Here we have developed a quantitative high-resolution genetic (qHRG) approach to systematically map the drug-protein interactions between Daclatasvir and NS5A and profile genetic barriers to Daclatasvir resistance. We implemented saturation mutagenesis in combination with next-generation sequencing technology to systematically quantify the effect of every possible amino acid substitution in the drug-targeted region (domain IA of NS5A) on replication fitness and sensitivity to Daclatasvir. This enabled determination of the residues governing drug-protein interactions. The relative fitness and drug sensitivity profiles also provide a comprehensive reference of the genetic barriers for all possible single amino acid changes during viral evolution, which we utilized to predict clinical outcomes using mathematical models. We envision that this high-resolution profiling methodology will be useful for next-generation drug development to select drugs with higher fitness costs to resistance, and also for informing the rational use of drugs based on viral variant spectra from patients.

Modelling clinical data shows active tissue concentration of daclatasvir is 10-fold lower than its plasma concentration.

OBJECTIVES: Daclatasvir is a highly potent inhibitor of hepatitis C virus. We estimated the active tissue concentration of daclatasvir in vivo. METHODS: We developed a mathematical model incorporating pharmacokinetic/pharmacodynamic and viral dynamics. By fitting the model to clinical data reported previously, we estimated the ratio between plasma drug concentration and active tissue concentration in vivo. RESULTS: The modelling results show that the active tissue concentration of daclatasvir is ∼9% of the concentration measured in plasma (95% CI 1%-29%). CONCLUSIONS: Using plasma concentrations as surrogates for clinical recommendations may lead to substantial underestimation of the risk of resistance.

Fluorescent imaging of single nanoparticles and viruses on a smart phone.

Optical imaging of nanoscale objects, whether it is based on scattering or fluorescence, is a challenging task due to reduced detection signal-to-noise ratio and contrast at subwavelength dimensions. Here, we report a field-portable fluorescence microscopy platform installed on a smart phone for imaging of individual nanoparticles as well as viruses using a lightweight and compact opto-mechanical attachment to the existing camera module of the cell phone. This hand-held fluorescent imaging device utilizes (i) a compact 450 nm laser diode that creates oblique excitation on the sample plane with an incidence angle of ~75°, (ii) a long-pass thin-film interference filter to reject the scattered excitation light, (iii) an external lens creating 2× optical magnification, and (iv) a translation stage for focus adjustment. We tested the imaging performance of this smart-phone-enabled microscopy platform by detecting isolated 100 nm fluorescent particles as well as individual human cytomegaloviruses that are fluorescently labeled. The size of each detected nano-object on the cell phone platform was validated using scanning electron microscopy images of the same samples. This field-portable fluorescence microscopy attachment to the cell phone, weighing only ~186 g, could be used for specific and sensitive imaging of subwavelength objects including various bacteria and viruses and, therefore, could provide a valuable platform for the practice of nanotechnology in field settings and for conducting viral load measurements and other biomedical tests even in remote and resource-limited environments.

On-chip cytometry using plasmonic nanoparticle enhanced lensfree holography.

Computational microscopy tools, in particular lensfree on-chip imaging, provide a large field-of-view along with a long depth-of-field, which makes it feasible to rapidly analyze large volumes of specimen using a compact and light-weight on-chip imaging architecture. To bring molecular specificity to this high-throughput platform, here we demonstrate the use of plasmon-resonant metallic nanoparticles to automatically recognize different cell types based on their plasmon-enhanced lensfree holograms, detected and reconstructed over a large field-of-view of e.g., ~24 mm².

Visible light powered self-disinfecting coatings for influenza viruses.

Influenza A viruses, the pathogens responsible for the recent swine flu outbreak and many historical pandemics, remain a threat to the public health. We report herein the fabrication of self-disinfecting surfaces from photoactive building nanocrystals, which can inactivate influenza viruses rapidly, spontaneously and continuously under visible light illumination.

Efficient identification of human immunodeficiency virus type 1 mutants resistant to a protease inhibitor by using a random mutant library.

Emergence of drug-resistant mutant viruses during the course of antiretroviral therapy is a major hurdle that limits the success of chemotherapeutic treatment to suppress human immunodeficiency virus type 1 (HIV-1) replication and AIDS progression. Development of new drugs and careful patient management based on resistance genotyping data are important for enhancing therapeutic efficacy. However, identifying changes leading to drug resistance can take years of clinical studies, and conventional in vitro assays are limited in generating reliable drug resistance data. Here we present an efficient in vitro screening assay for selecting drug-resistant variants from a library of randomly mutated HIV-1 strains generated by transposon-directed base-exchange mutagenesis. As a test of principle, we screened a library of mutant HIV-1 strains containing random mutations in the protease gene by using a reporter T-cell line in the presence of the protease inhibitor (PI) nelfinavir (NFV). Analysis of replicating viruses from a single round of infection identified 50 amino acid substitutions at 35 HIV-1 protease residue positions. The selected mutant viruses showed specific resistance to NFV and included most of the known NFV resistance mutations. Therefore, the new assay is efficient for identifying changes leading to drug resistance. The data also provide insights into the molecular mechanisms underlying the development of drug resistance.