A general method for nested RT-PCR amplification and sequencing the complete HCV genotype 1 open reading frame

BACKGROUND: Hepatitis C virus (HCV) is a pathogenic hepatic flavivirus with a single stranded RNA genome. It has a high genetic variability and is classified into six major genotypes. Genotype 1a and 1b cause the majority of infections in the USA. Viral genomic sequence information is needed to correlate viral variation with pathology or response to therapy. However, reverse transcription-polymerase chain reaction (RT-PCR) of the HCV genome must overcome low template concentration and high target sequence diversity. Amplification conditions must hence have both high sensitivity and specificity yet recognize a heterogeneous target population to permit general amplification with minimal bias. This places divergent demands of the amplification conditions that can be very difficult to reconcile. RESULTS: RT and nested PCR conditions were optimized independently and systematically for amplifying the complete open reading frame (ORF) from HCV genotype 1a and 1b using several overlapping amplicons. For each amplicon, multiple pairs of nested PCR primers were optimized. Using these primers, the success rate (defined as the rate of production of sufficient DNA for sequencing with any one of the primer pairs for a given amplicon) for amplification of 72 genotype 1a and 1b patient plasma samples averaged over 95% for all amplicons. In addition, two sets of sequencing primers were optimized for each genotype 1a and 1b. Viral consensus sequences were determined by directly sequencing the amplicons. HCV ORFs from 72 patients have been sequenced using these primers. Sequencing errors were negligible because sequencing depth was over 4-fold and both strands were sequenced. Primer bias was controlled and monitored through careful primer design and control experiments. CONCLUSION: Optimized RT-PCR and sequencing conditions are useful for rapid and reliable amplification and sequencing of HCV genotype 1a and 1b ORFs

Rapid Policy Network Mapping: A New Method for Understanding Governance Structures for Implementation of Marine Environmental Policy

Understanding the relationships and dependencies in the development and implementation of environmental policy is essential to the effective management of the marine environment. A new method of policy network analysis called ‘Rapid Policy Network Mapping’ was developed that delivers an insight for both technical and non-technical users into the lifecycle, relationships and dependencies of policy development. The method was applied to the Marine Strategy Framework Directive and the Water Framework Directive in the UK. These case studies highlight the environmental policy challenges to protect the UK's marine coastal environment and they identify differences in the styles of policy implementation between the devolved authorities of the UK. Rapid Policy Network Mapping provides an opportunity to create a collaborative policy data environment with a relatively small investment. As a tool for civil society it should assist in their ability to understand and influence policy making and implementation

Just Transition for Workers and Communities in Aberdeen and Aberdeenshire : Rapid Evidence Review

Publisher PD

Measuring Just Transition : Indicators and scenarios for a Just Transition in Aberdeen and Aberdeenshire

Publisher PD

Synthesis and evaluation of troponoids as a new class of antibiotics

Novel antibiotics are urgently needed. The troponoids [tropones, tropolones, and α-hydroxytropolones (α-HT)] can have anti-bacterial activity. We synthesized or purchased 92 troponoids and evaluated their antibacterial activities against Staphylococcus aureus, Escherichia coli, Acinetobacter baumannii, and Pseudomonas aeruginosa. Preliminary hits were assessed for minimum inhibitory concentrations (MIC80) and cytotoxicity (CC50) against human hepatoma cells. Sixteen troponoids inhibited S. aureus/E. coli/A. baumannii growth by ≥80% growth at 50 values >50 μM. Two selected tropolones (63 and 285) inhibited 18 methicillin-resistant S. aureus (MRSA) strains with similar MIC80 values as against a reference strain. Two selected thiotropolones (284 and 363) inhibited multidrug-resistant (MDR) E. coli with MIC80 ≤30 μM. One α-HT (261) inhibited MDR-A. baumannii with MIC80 ≤30 μM. This study opens new avenues for development of novel troponoid antibiotics to address the critical need to combat MDR bacterial infections

Prospects for personalizing antiviral therapy for hepatitis C virus with pharmacogenetics

Chronic hepatitis C virus (HCV) infection is a major cause of liver disease worldwide. HCV infection is currently treated with IFNα plus ribavirin for 24 to 48 weeks. This demanding therapy fails in up to 50% of patients, so the use of pharmacogenetic biomarkers to predict the outcome of treatment would reduce futile treatment of non-responders and help identify patients in whom therapy would be justified. Both IFNα and ribavirin primarily act by modulating the immune system of the patient, and HCV uses multiple mechanisms to counteract the antiviral effects stimulated by therapy. Therefore, response to therapy is influenced by variations in human genes governing the immune system and by differences in HCV genes that blunt antiviral immune responses. This article summarizes recent advances in understanding how host and viral genetic variation affect outcome of therapy. The most notable human associations are polymorphisms within the IL28B gene, but variations in human leukocyte antigen and cytokine genes have also been associated with treatment outcome. The most prominent viral genetic association with outcome of therapy is that HCV genotype 1 is much less sensitive to treatment than genotypes 2 and 3, but genetic differences below the genotype level also influence outcome of therapy, presumably by modulating the ability of viral genes to blunt antiviral immune responses. Pharmacogenetic prediction of the outcome of IFN-based therapy for HCV will require integrating the efficacies of the immunosuppressive mechanisms of a viral isolate, and then interpreting the viral resistance potential in context of the genetic profile of the patient at loci associated with outcome of therapy. Direct-acting inhibitors of HCV that will be used in combination with IFNα are nearing approval, so genetic prediction for anti-HCV therapy will soon need to incorporate viral genetic markers of viral resistance to the new drugs

Mechanistic Characterization and Molecular Modeling of Hepatitis B Virus Polymerase Resistance to Entecavir

BACKGROUND: Entecavir (ETV) is a deoxyguanosine analog competitive inhibitor of hepatitis B virus (HBV) polymerase that exhibits delayed chain termination of HBV DNA. A high barrier to entecavir-resistance (ETVr) is observed clinically, likely due to its potency and a requirement for multiple resistance changes to overcome suppression. Changes in the HBV polymerase reverse-transcriptase (RT) domain involve lamivudine-resistance (LVDr) substitutions in the conserved YMDD motif (M204V/I +/- L180M), plus an additional ETV-specific change at residues T184, S202 or M250. These substitutions surround the putative dNTP binding site or primer grip regions of the HBV RT. METHODS/PRINCIPAL FINDINGS: To determine the mechanistic basis for ETVr, wildtype, lamivudine-resistant (M204V, L180M) and ETVr HBVs were studied using in vitro RT enzyme and cell culture assays, as well as molecular modeling. Resistance substitutions significantly reduced ETV incorporation and chain termination in HBV DNA and increased the ETV-TP inhibition constant (K(i)) for HBV RT. Resistant HBVs exhibited impaired replication in culture and reduced enzyme activity (k(cat)) in vitro. Molecular modeling of the HBV RT suggested that ETVr residue T184 was adjacent to and stabilized S202 within the LVDr YMDD loop. ETVr arose through steric changes at T184 or S202 or by disruption of hydrogen-bonding between the two, both of which repositioned the loop and reduced the ETV-triphosphate (ETV-TP) binding pocket. In contrast to T184 and S202 changes, ETVr at primer grip residue M250 was observed during RNA-directed DNA synthesis only. Experimentally, M250 changes also impacted the dNTP-binding site. Modeling suggested a novel mechanism for M250 resistance, whereby repositioning of the primer-template component of the dNTP-binding site shifted the ETV-TP binding pocket. No structural data are available to confirm the HBV RT modeling, however, results were consistent with phenotypic analysis of comprehensive substitutions of each ETVr position. CONCLUSIONS: Altogether, ETVr occurred through exclusion of ETV-TP from the dNTP-binding site, through different, novel mechanisms that involved lamivudine-resistance, ETV-specific substitutions, and the primer-template

Factors Influencing Nutritional Intake and Interests in Educational Content of Athletes and Sport Professionals Toward the Development of a Clinician-Supported Mobile App to Combat Relative Energy Deficiency in Sport: Formative Research and a Description of App Functions

Background: Relative energy deficiency in sport (RED-S) as a consequence of athlete malnutrition remains a prominent issue. However, it remains underrecognized, in part due to the perceived outward health of athletes. The Eat2Win app was designed to combat RED-S and athlete malnutrition by providing education, behavior modification, and direct communication with expert sports dietitians to athletes and sport professionals (professionals who work with athletes, eg, sport coaches and athletic trainers). Objective: The purpose of this formative research was to gain critical insight on motivators and barriers to optimal nutritional intake from both the athletes’ and sport professionals’ perspectives. Additionally, since these 2 groups represent the primary end users of an app aimed at improving athlete nutrition and reducing the risk of RED-S, a secondary objective was to gain insight on the preferences and perceptions of app-based educational content and functionality. Methods: An electronic survey was developed by an interdisciplinary team of experts. Survey questions were established based upon prevailing literature, professional dietetic field experience, and app design considerations to obtain respondent knowledge on key sports nutrition topics along with motivations and barriers to meal choices. Additionally, the survey included questions about the development of an integrative, clinician-support app aimed at addressing RED-S. These questions included preferences for educational content, modes of in-app information, and communication delivery for the target population (app end users: athletes and sport professionals). The survey was distributed through Research Electronic Data Capture (REDCap) to athletes and sport professionals using targeted email, social media, and community engagement campaigns. The electronic survey was available from May 4 to August 2, 2022. Results: Survey respondents (n=1352) included athletes and professionals who work with athletes from a variety of settings, like high school, collegiate, professional, and club sports. Respondents reported high interest in 8 core sports nutrition topics. The preferred modes of information and communication delivery were visual formats (eg, videos and infographics) and in-app alerts (eg, direct messaging and meal reminders). Only athlete respondents were asked about motivators and barriers that influence meal choices. “Health” and “sports performance” were the highest scoring motivators, while the highest scoring barriers were “cost of food,” “easy access to unhealthy food,” and “time to cook or prepare food.” Notably, survey respondents provided positive feedback and interest using a novel function of the app: real-time meal feedback through food photography. Conclusions: The Eat2Win app is designed to combat RED-S and athlete malnutrition. Results from this study provide critical information on end-user opinions and preferences and will be used to further develop the Eat2Win app. Future research will aim to determine whether the Eat2Win app can prevent RED-S and the risk of athlete malnutrition to improve both health and performance

JC Virus Mediates Invasion and Migration in Colorectal Metastasis

INTRODUCTION:JC Virus (JCV), a human polyomavirus, is frequently present in colorectal cancers (CRCs). JCV large T-Ag (T-Ag) expressed in approximately half of all CRC's, however, its functional role in CRC is poorly understood. We hypothesized that JCV T-Ag may mediate metastasis in CRC cells through increased migration and invasion. MATERIAL AND METHODS:CRC cell lines (HCT116 and SW837) were stably transfected with JCV early transcript sequences cloned into pCR3 or empty vectors. Migration and invasion assays were performed using Boyden chambers. Global gene expression analysis was performed to identify genetic targets and pathways altered by T-Ag expression. Microarray results were validated by qRT-PCR, protein expression analyses and immunohistochemistry. Matching primary CRCs and liver metastases from 33 patients were analyzed for T-Ag expression by immunohistochemistry. RESULTS:T-Ag expressing cell lines showed 2 to 3-fold increase in migration and invasion compared to controls. JCV T-Ag expression resulted in differential expression of several genetic targets, including genes that mediate cell migration and invasion. Pathway analysis suggested a significant involvement of these genes with AKT and MAPK signaling. Treatment with selective PI3K/AKT and MAPK pathway inhibitors resulted in reduced migration and invasion. In support of our in-vitro results, immunohistochemical staining of the advanced stage tumors revealed frequent JCV T-Ag expression in metastatic primary tumors (92%) as well as in their matching liver metastasis (73%). CONCLUSION:These data suggest that JCV T-Ag expression in CRC associates with a metastatic phenotype, which may partly be mediated through the AKT/MAPK signaling pathway. Frequent expression of JCV T-Ag in CRC liver metastasis provides further clues supporting a mechanistic role for JCV as a possible mediator of cellular motility and invasion in CRC

Baseline Prediction of Combination Therapy Outcome in Hepatitis C Virus 1b Infected Patients by Discriminant Analysis Using Viral and Host Factors

Current treatment of chronic hepatitis C virus (HCV) infection has limited efficacy -especially among genotype 1 infected patients-, is costly, and involves severe side effects. Thus, predicting non-response is of major interest for both patient wellbeing and health care expense. At present, treatment cannot be individualized on the basis of any baseline predictor of response. We aimed to identify pre-treatment clinical and virological parameters associated with treatment failure, as well as to assess whether therapy outcome could be predicted at baseline.Forty-three HCV subtype 1b (HCV-1b) chronically infected patients treated with pegylated-interferon alpha plus ribavirin were retrospectively studied (21 responders and 22 non-responders). Host (gender, age, weight, transaminase levels, fibrosis stage, and source of infection) and viral-related factors (viral load, and genetic variability in the E1-E2 and Core regions) were assessed. Logistic regression and discriminant analyses were used to develop predictive models. A "leave-one-out" cross-validation method was used to assess the reliability of the discriminant models.Lower alanine transaminase levels (ALT, p=0.009), a higher number of quasispecies variants in the E1-E2 region (number of haplotypes, nHap_E1-E2) (p=0.003), and the absence of both amino acid arginine at position 70 and leucine at position 91 in the Core region (p=0.039) were significantly associated with treatment failure. Therapy outcome was most accurately predicted by discriminant analysis (90.5% sensitivity and 95.5% specificity, 85.7% sensitivity and 81.8% specificity after cross-validation); the most significant variables included in the predictive model were the Core amino acid pattern, the nHap_E1-E2, and gamma-glutamyl transferase and ALT levels.Discriminant analysis has been shown as a useful tool to predict treatment outcome using baseline HCV genetic variability and host characteristics. The discriminant models obtained in this study led to accurate predictions in our population of Spanish HCV-1b treatment naïve patients