Analysis of antibodies from HCV elite neutralizers identifies genetic determinants of broad neutralization.

The high genetic diversity of hepatitis C virus (HCV) complicates effective vaccine development. We screened a cohort of 435 HCV-infected individuals and found that 2%-5% demonstrated outstanding HCV-neutralizing activity. From four of these patients, we isolated 310 HCV antibodies, including neutralizing antibodies with exceptional breadth and potency. High neutralizing activity was enabled by the use of the VH1-69 heavy-chain gene segment, somatic mutations within CDRH1, and CDRH2 hydrophobicity. Structural and mutational analyses revealed an important role for mutations replacing the serines at positions 30 and 31, as well as the presence of neutral and hydrophobic residues at the tip of the CDRH3. Based on these characteristics, we computationally created a de novo antibody with a fully synthetic VH1-69 heavy chain that efficiently neutralized multiple HCV genotypes. Our findings provide a deep understanding of the generation of broadly HCV-neutralizing antibodies that can guide the design of effective vaccine candidates.

Incorporating temporal dynamics of mutations to enhance the prediction capability of antiretroviral therapy's outcome for HIV-1.

MOTIVATION: In predicting HIV therapy outcomes, a critical clinical question is whether using historical information can enhance predictive capabilities compared with current or latest available data analysis. This study analyses whether historical knowledge, which includes viral mutations detected in all genotypic tests before therapy, their temporal occurrence, and concomitant viral load measurements, can bring improvements. We introduce a method to weigh mutations, considering the previously enumerated factors and the reference mutation-drug Stanford resistance tables. We compare a model encompassing history (H) with one not using this information (NH). RESULTS: The H-model demonstrates superior discriminative ability, with a higher ROC-AUC score (76.34%) than the NH-model (74.98%). Wilcoxon test results confirm significant improvement of predictive accuracy for treatment outcomes through incorporating historical information. The increased performance of the H-model might be attributed to its consideration of latent HIV reservoirs, probably obtained when leveraging historical information. The findings emphasize the importance of temporal dynamics in acquiring mutations. However, our result also shows that prediction accuracy remains relatively high even when no historical information is available. AVAILABILITY AND IMPLEMENTATION: This analysis was conducted using the Euresist Integrated DataBase (EIDB). For further validation, we encourage reproducing this study with the latest release of the EIDB, which can be accessed upon request through the Euresist Network.

Torque Teno Virus load is associated with CDC stage and CD4+ cell count in people living with HIV but unrelated to AIDS-defining events and Human Pegivirus load.

BACKGROUND: Torque Teno Virus (TTV) is a non-enveloped, circular single-strand DNA virus and part of the human virome. The replication of TTV was related to the immune status in patients treated with immunosuppressive drugs after organ transplantation. We hypothesize that TTV load could be an additional marker for immune function in people living with HIV (PLWH). METHODS: In this analysis serum samples of PLWH from the RESINA multicenter cohort were reanalysed for TTV. Investigated clinical and epidemiological parameters included Pegivirus (HPgV) load, age, sex, HIV load, CD4+ cell count (CDC 1, 2, 3) and CDC clinical stages (1993 CDC classification system, A, B, C) before initiation of antiretroviral treatment. Regression analysis was used to detect possible associations among parameters. RESULTS: Our analysis confirmed TTV as a strong predictor of CD4+ cell count and CDC class 3. This relationship was used to propose a first classification of TTV load in regard to clinical stage. We found no association with clinical CDC stages A, B and C. HPgV load was inversely correlated with HIV load but not TTV load. CONCLUSIONS: TTV load was associated with immunodeficiency in PLWH. Neither TTV- nor HIV load were predictive for the clinical categories of HIV infection.

Five-year single-center analysis of cytomegalovirus viremia in kidney transplant recipients and possible implication for novel prophylactic therapy approaches.

BACKGROUND: Cytomegalovirus (CMV) infections are a common complication after kidney transplantation (KTx) and negatively affecting patient outcome. Valganciclovir (VGC) prophylaxis is often limited by drug-induced side effects and dose reduction due to decline in kidney function. METHOD: In the present study, episodes of CMV viremia in the first year after KTx in a cohort of 316 recipients were analyzed retrospectively to identify risk factors linked to persistent infections. RESULTS: In the studied cohort, 18.7% of patients showed a high-risk (HR) constellation (D+/R-) for CMV infections. CMV viremia affected 22% of our cohort, with HR patients being the most affected cohort (44.1%). Within this group, most viremic events (65.3%) occurred while patients were still on prophylactic therapy, showing significantly higher viral loads and a longer duration compared to seropositive recipients. CONCLUSION: The analysis at hand revealed that detection of viremia under ongoing antiviral prophylaxis bears an increased risk for sustained viral replication and antiviral drug resistance in HR patients. We identified low estimated glomerular filtration rate (eGFR) and lower dose VGC prophylaxis post-KTx as a risk factor for breakthrough infections in HR patients in our single center cohort. These patients might benefit from a closer CMV monitoring or novel prophylactic agents as letermovir.

HAMdetector: a Bayesian regression model that integrates information to detect HLA-associated mutations.

MOTIVATION: A key process in anti-viral adaptive immunity is that the human leukocyte antigen (HLA) system presents epitopes as major histocompatibility complex I (MHC I) protein-peptide complexes on cell surfaces and in this way alerts CD8+ cytotoxic T-lymphocytes (CTLs). This pathway exerts strong selection pressure on viruses, favoring viral mutants that escape recognition by the HLA/CTL system. Naturally, such immune escape mutations often emerge in highly variable viruses, e.g. HIV or HBV, as HLA-associated mutations (HAMs), specific to the hosts MHC I proteins. The reliable identification of HAMs is not only important for understanding viral genomes and their evolution, but it also impacts the development of broadly effective anti-viral treatments and vaccines against variable viruses. By their very nature, HAMs are amenable to detection by statistical methods in paired sequence/HLA data. However, HLA alleles are very polymorphic in the human host population which makes the available data relatively sparse and noisy. Under these circumstances, one way to optimize HAM detection is to integrate all relevant information in a coherent model. Bayesian inference offers a principled approach to achieve this. RESULTS: We present a new Bayesian regression model for the detection of HAMs that integrates a sparsity-inducing prior, epitope predictions and phylogenetic bias assessment, and that yields easily interpretable quantitative information on HAM candidates. The model predicts experimentally confirmed HAMs as having high posterior probabilities, and it performs well in comparison to state-of-the-art models for several datasets from individuals infected with HBV, HDV and HIV. AVAILABILITY AND IMPLEMENTATION: The source code of this software is available at https://github.com/HAMdetector/Escape.jl under a permissive MIT license. The data underlying this article were provided by permission. Data will be shared on request to the corresponding author with permission of the respective co-authors. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Acute orchitis deciphered: Coxsackievirus B strains are the main etiology and their presence in semen is associated with acute inflammation and risk of persistent oligozoospermia.

Although various viruses are considered to be the clinical cause for acute orchitis, it is completely unclear to what extent and which viruses are etiologically involved in acute orchitis and what the clinic and course of these patients are like. Therefore, a prospective study was set up to decipher acute isolated orchitis. Between July 2007 and February 2023, a total of 26 patients with isolated orchitis were recruited and compared with 530 patients with acute epididymitis. We were able to show for isolated orchitis, that (1) orchitis is usually of viral origin (20/26, 77%) and enteroviruses with coxsackievirus B strains (16/26, 62%) are predominant, (2) virus isolates could be received from semen indicating the presence of replication-competent virus particles, (3) a polymerase chain reaction (PCR) for enteroviruses should be conducted using semen provided at the onset of disease, because the virus is not detectable in serum/urine, (4) there is a circannual occurrence with the maximum in summer, (5) orchitis is associated with a characteristic inflammatory cytokine panel in the semen and systemic inflammation, (6) orchitis is usually rapidly self-limiting, and (7) about 30% of patients (6/20) suffer ongoing oligozoospermia. These seven emerging aspects are likely to fundamentally change thinking and clinical practice regarding acute isolated orchitis.

Analysis of mutational history of multidrug-resistant genotypes with a mutagenetic tree model.

Human immunodeficiency virus (HIV) can develop resistance to all antiretroviral drugs. Multidrug resistance, however, is a rare event in modern HIV treatment, but can be life-threatening, particular in patients with very long therapy histories and in areas with limited access to novel drugs. To understand the evolution of multidrug resistance, we analyzed the EuResist database to uncover the accumulation of mutations over time. We hypothesize that the accumulation of resistance mutations is not acquired simultaneously and randomly across viral genotypes but rather tends to follow a predetermined order. The knowledge of this order might help to elucidate potential mechanisms of multidrug resistance. Our evolutionary model shows an almost monotonic increase of resistance with each acquired mutation, including less well-known nucleoside reverse transcriptase (RT) inhibitor-related mutations like K223Q, L228H, and Q242H. Mutations within the integrase (IN) (T97A, E138A/K G140S, Q148H, N155H) indicate high probability of multidrug resistance. Hence, these IN mutations also tend to be observed together with mutations in the protease (PR) and RT. We followed up with an analysis of the mutation-specific error rates of our model given the data. We identified several mutations with unusual rates (PR: M41L, L33F, IN: G140S). This could imply the existence of previously unknown virus variants in the viral quasispecies. In conclusion, our bioinformatics model supports the analysis and understanding of multidrug resistance.

Torque teno virus-DNA load as individual cytomegalovirus risk assessment parameter upon allogeneic hematopoietic stem cell transplantation.

BACKGROUND: Immune recovery following allogeneic hematopoietic stem cell transplantation (allo-HSCT) decisively influences the occurrence of opportunistic infections, one of the leading causes of death among this group of patients. Yet, today, there are no laboratory parameters mirroring immune function sufficiently. Torque teno virus (TTV) has already proven itself as a functional immune marker in other settings. AIMS: In this analysis, we investigated whether monitoring of TTV-DNA load in whole blood is able to provide additional information on the capacity of the immune system to control cytomegalovirus (CMV) replication in allo-HSCT recipients. METHODS: Whole blood samples from 59 patients were collected upon allo-HSCT (between Day -7 and +10), on Day +14, +21, +28, +56, +90, and +365 post-transplant. TTV-DNA loads and other relevant clinical information were correlated with the risk of CMV infections or reactivations, defined by evidence of viral replication in blood. RESULTS: CMV serostatus of the recipient and a TTV load below 1000 copies/mL upon allo-HSCT were significantly associated with an increased incidence of CMV infection or reactivation. CONCLUSIONS: Quantification of TTV load in the early phase of allo-HSCT procedure could provide additional information in order to identify patients at risk for CMV infection or reactivation.

Implementing the Lolli-Method and pooled RT-qPCR testing for SARS-CoV-2 surveillance in schools: a pilot project.

PURPOSE: School closures have been used as part of lockdown strategies to contain the spread of SARS-CoV-2, adversely affecting children's health and education. To ensure the accessibility of educational institutions without exposing society to the risk of increased transmissions, it is essential to establish SARS-CoV-2 testing strategies that are child-friendly, scalable and implementable in a daily school routine. Self-sampling using non-invasive saliva swabs combined with pooled RT-qPCR testing (Lolli-Method) has been proven to be a sensitive method for the detection of SARS-CoV-2. METHODS: We conducted a pilot project in Cologne, Germany, designed to determine the feasibility of a large-scale rollout of the Lolli-Method for testing without any additional on-site medical staff in schools. Over a period of three weeks, students from 22 schools were sampled using the Lolli-Method. At the end of the project, teachers were asked to evaluate the overall acceptance of the project. RESULTS: We analyzed a total of 757 pooled RT-qPCRs obtained from 8,287 individual swabs and detected 7 SARS-CoV-2 infected individuals. The Lolli-Method was shown to be a feasible and accepted testing strategy whose application is only slightly disruptive to the daily school routine. CONCLUSION: Our observations suggest that the Lolli-Method in combination with pooled RT-qPCR can be implemented for SARS-CoV-2 surveillance in daily school routine, applicable on a large scale.

European Cohorts of patients and schools to Advance Response to Epidemics (EuCARE): a cluster randomised interventional and observational study protocol to investigate the relationship between schools and SARS-CoV-2 infection.

BACKGROUND: Contradictory results were reported on the role of school closure/reopening on the overall SARS-CoV-2 transmission rate, as well as on which kind and level of mitigation measures implemented in schools may be effective in limiting its diffusion. Some recent studies were reassuring, showing that opening did not increase the community spread, although teachers and families are worried about the high class density. On the other hand, distance learning was associated with a negative impact on learning, sociability and psychological health, especially in vulnerable children. As it becomes clear that the SARS-CoV-2 pandemic will last for a long time, there is a high need for studies and solutions to support safe schools opening based on scientific evidence of harms and benefits. The Lolli-Methode (LM) is a strategy for epidemiological surveillance and early intervention aiming at SARS-CoV-2 outbreaks' reduction in schools, relying on polymerase chain reaction analysis of saliva samples. METHODS: In this cluster randomised trial protocol, we aim to determine whether the LM is useful to support schools opening and to reduce clusters and attack rates in schools, compared with the standard of care (SoC) surveillance by public health departments. This multicenter study will enrol 440 classes (around 8800 students, teachers and other personnel) from two countries, cluster randomised to LM or SoC. The samples from the pools will be collected and tested using PCR-based techniques. Test results will be combined with questionnaires filled in by children, parents, schoolteachers, and principals, concerning ongoing mitigation measures, their perceived psychological impact and other health and socio-economic information. An ancillary observational study will be carried out to study the prevalence of SARS-CoV-2 in schools, frequencies and size of clusters and attack rates, to compare the effectiveness of the different preventive measures adopted and to evaluate psychological issues in students and teachers in relation to the pandemic's containment measures. DISCUSSION: By the end of this study, we will have defined and characterised the applicability of the LM for SARS-CoV-2 surveillance, as well as the impact of pandemic preventive measures on children and teachers. Trial registration International Standard Randomised Controlled Trial Number: NCT05396040, 27.05.2022.

Generating synthetic clinical data that capture class imbalanced distributions with generative adversarial networks: Example using antiretroviral therapy for HIV.

OBJECTIVE: Clinical data's confidential nature often limits the development of machine learning models in healthcare. Generative adversarial networks (GANs) can synthesise realistic datasets, but suffer from mode collapse, resulting in low diversity and bias towards majority demographics and common clinical practices. This work proposes an extension to the classic GAN framework that includes a variational autoencoder (VAE) and an external memory mechanism to overcome these limitations and generate synthetic data accurately describing imbalanced class distributions commonly found in clinical variables. METHODS: The proposed method generated a synthetic dataset related to antiretroviral therapy for human immunodeficiency virus (ART for HIV). We evaluated it based on five metrics: (1) accurately representing imbalanced class distribution; (2) the realism of the individual variables; (3) the realism among variables; (4) patient disclosure risk; and (5) the utility of the generated dataset for developing downstream machine learning models. RESULTS: The proposed method overcomes the issue of mode collapse and generates a synthetic dataset that accurately describes imbalanced class distributions commonly found in clinical variables. The generated data has a patient disclosure risk of 0.095%, lower than the 9% threshold stated by Health Canada and the European Medicines Agency, making it suitable for distribution to the research community with high security. The generated data also has high utility, indicating the potential of the proposed method to enable the development of downstream machine learning algorithms for healthcare applications using synthetic data. CONCLUSION: Our proposed extension to the classic GAN framework, which includes a VAE and an external memory mechanism, represents a promising approach towards generating synthetic data that accurately describe imbalanced class distributions commonly found in clinical variables. This method overcomes the limitations of GANs and creates more realistic datasets with higher patient cohort diversity, facilitating the development of downstream machine learning algorithms for healthcare applications.

Effectiveness of integrase strand transfer inhibitors in HIV-infected treatment-experienced individuals across Europe.

OBJECTIVES: To explore the effectiveness and durability of integrase strand transfer inhibitor (INSTI)-based regimens in pre-treated subjects. METHODS: Treatment-experienced individuals starting an INSTI-based regimen during 2012-2019 were selected from the INTEGRATE collaborative study. The time to virological failure [VF: one measurement of viral load (VL) ≥ 1000 copies/mL or two ≥ 50 copies/ml or one VL measurement ≥ 50 copies/mL followed by treatment change] and to INSTI discontinuation were evaluated. RESULTS: Of 13 560 treatments analysed, 4284 were from INSTI-naïve, non-viraemic (IN-NV) individuals, 1465 were from INSTI-naïve, viraemic (IN-V) individuals, 6016 were from INSTI-experienced, non-viraemic (IE-NV) individuals and 1795 were from INSTI-experienced, viraemic (IE-V) individuals. Major INSTI drug resistance mutations (DRMs) were previously detected in 4/519 (0.8%) IN-NV, 3/394 (0.8%) IN-V, 7/1510 (0.5%) IE-NV and 25/935 (2.7%) IE-V individuals. The 1-year estimated probabilities of VF were 3.1% [95% confidence interval (CI): 2.5-3.8] in IN-NV, 18.4% (95% CI: 15.8-21.2) in IN-V, 4.2% (95% CI: 3.6-4.9) in IE-NV and 23.9% (95% CI: 20.9-26.9) in IE-V subjects. The 1-year estimated probabilities of INSTI discontinuation were 12.1% (95% CI: 11.1-13.0) in IN-NV, 19.6% (95% CI: 17.5-21.6) in IN-V, 10.8% (95% CI: 10.0-11.6) in IE-NV and 21.7% (95% CI: 19.7-23.5) in IE-V subjects. CONCLUSIONS: Both VF and INSTI discontinuation occur at substantial rates in viraemic subjects. Detection of DRMs in a proportion of INSTI-experienced individuals makes INSTI resistance testing mandatory after failure.

Characterization of HIV-1 drug resistance among patients with failure of second-line combined antiretroviral therapy in central Ethiopia.

BACKGROUND: As a consequence of the improved availability of combined antiretroviral therapy (cART) in resource-limited countries, an emergence of HIV drug resistance (HIVDR) has been observed. We assessed the prevalence and spectrum of HIVDR in patients with failure of second-line cART at two HIV clinics in central Ethiopia. METHODS: HIV drug resistance was analysed in HIV-1-infected patients with virological failure of second-line cART using the geno2pheno application. RESULTS: Among 714 patients receiving second-line cART, 44 (6.2%) fulfilled the criteria for treatment failure and 37 were eligible for study inclusion. Median age was 42 years [interquartile range (IQR): 20-45] and 62.2% were male. At initiation of first-line cART, 23 (62.2%) were WHO stage III, mean CD4 cell count was 170.6 (range: 16-496) cells/µL and median (IQR) HIV-1 viral load was 30 220 (7963-82 598) copies/mL. Most common second-line cART regimens at the time of failure were tenofovir disoproxil fumarate (TDF)-lamivudine (3TC)-ritonavir-boosted atazanavir (ATV/r) (19/37, 51.4%) and zidovudine (ZDV)-3TC-ATV/r (9/37, 24.3%). Genotypic HIV-1 resistance testing was successful in 35 (94.6%) participants. We found at least one resistance mutation in 80% of patients and 40% carried a protease inhibitor (PI)-associated mutation. Most common mutations were M184V (57.1%), Y188C (25.7%), M46I/L (25.7%) and V82A/M (25.7%). High-level resistance against the PI ATV (10/35, 28.6%) and lopinavir (LPV) (5/35, 14.3%) was reported. As expected, no resistance mutations conferring integrase inhibitor resistance were detected. CONCLUSIONS: We found a high prevalence of resistance mutations, also against PIs (40%), as the national standard second-line cART components. Resistance testing before switching to second- or third-line cART is warranted.

Respiratory viruses dynamics and interactions: ten years of surveillance in central Europe.

BACKGROUND: Lower respiratory tract infections are among the main causes of death. Although there are many respiratory viruses, diagnostic efforts are focused mainly on influenza. The Respiratory Viruses Network (RespVir) collects infection data, primarily from German university hospitals, for a high diversity of infections by respiratory pathogens. In this study, we computationally analysed a subset of the RespVir database, covering 217,150 samples tested for 17 different viral pathogens in the time span from 2010 to 2019. METHODS: We calculated the prevalence of 17 respiratory viruses, analysed their seasonality patterns using information-theoretic measures and agglomerative clustering, and analysed their propensity for dual infection using a new metric dubbed average coinfection exclusion score (ACES). RESULTS: After initial data pre-processing, we retained 206,814 samples, corresponding to 1,408,657 performed tests. We found that Influenza viruses were reported for almost the half of all infections and that they exhibited the highest degree of seasonality. Coinfections of viruses are frequent; the most prevalent coinfection was rhinovirus/bocavirus and most of the virus pairs had a positive ACES indicating a tendency to exclude each other regarding infection. CONCLUSIONS: The analysis of respiratory viruses dynamics in monoinfection and coinfection contributes to the prevention, diagnostic, treatment, and development of new therapeutics. Data obtained from multiplex testing is fundamental for this analysis and should be prioritized over single pathogen testing.

Human Immunodeficiency Virus-2 (HIV-2): A Summary of the Present Standard of Care and Treatment Options for Individuals Living with HIV-2 in Western Europe.

Human immunodeficiency virus-2 (HIV-2) is endemic in some countries in West Africa. Due to the lower prevalence in industrialized countries, there is limited experience and knowledge on the management of individuals living with HIV-2 in Europe. Compared to HIV-1, there are differential characteristics of HIV-2 regarding diagnostic procedures, the clinical course, and, most importantly, antiretroviral therapy. We integrated the published literature on HIV-2 (studies and reports on epidemiology, diagnostics, the clinical course, and treatment), as well as expert experience in diagnosing and clinical care, to provide recommendations for a present standard of medical care of those living with HIV-2 in Western European countries, including an overview of strategies for diagnosis, monitoring, and treatment, with suggestions for effective drug combinations for first- and second-line treatments, post-exposure prophylaxis, and the prevention of mother-to-child transmission, as well as listings of mutations related to HIV-2 drug resistance and C-C motif chemokine receptor type 5 and C-X-C motif chemokine receptor type 4 coreceptor tropism.

Effectiveness of integrase strand transfer inhibitor-based regimens in HIV-infected treatment-naive individuals: results from a European multi-cohort study.

BACKGROUND: INSTIs have become a pillar of first-line ART. Real-world data are needed to assess their effectiveness in routine care. OBJECTIVES: We analysed ART-naive patients who started INSTI-based regimens in 2012-19 whose data were collected by INTEGRATE, a European collaborative study including seven national cohorts. METHODS: Kaplan-Meier analyses assessed time to virological failure (VF), defined as one viral load (VL) ≥1000 copies/mL, two consecutive VLs ≥50 copies/mL, or one VL ≥50 copies/mL followed by treatment change after ≥24 weeks of follow-up, and time to INSTIs discontinuation (INSTI-DC) for any reason. Factors associated with VF and INSTI-DC were explored by logistic regression analysis. RESULTS: Of 2976 regimens started, 1901 (63.9%) contained dolutegravir, 631 (21.2%) elvitegravir and 444 (14.9%) raltegravir. The 1 year estimated probabilities of VF and INSTI-DC were 5.6% (95% CI 4.5-6.7) and 16.2% (95% CI 14.9-17.6), respectively, and were higher for raltegravir versus both elvitegravir and dolutegravir. A baseline VL ≥100 000 copies/mL [adjusted HR (aHR) 2.17, 95% CI 1.55-3.04, P < 0.001] increased the risk of VF, while a pre-treatment CD4 count ≥200 cells/mm3 reduced the risk (aHR 0.52, 95% CI 0.37-0.74, P < 0.001). Predictors of INSTI-DC included use of raltegravir versus dolutegravir (aHR 3.03, 95% CI 2.34-3.92, P < 0.001), use of >3 drugs versus 3 drugs (aHR 2.73, 95% CI 1.55-4.79, P < 0.001) and starting ART following availability of dolutegravir (aHR 0.64, 95% CI 0.48-0.83, P = 0.001). Major INSTI mutations indicative of transmitted drug resistance occurred in 2/1114 (0.2%) individuals. CONCLUSIONS: This large multi-cohort study indicates high effectiveness of elvitegravir- or dolutegravir-based first-line ART in routine practice across Europe.

Sensitivity of anti-SARS-CoV-2 serological assays in a high-prevalence setting.

Evaluation and power of seroprevalence studies depend on the performed serological assays. The aim of this study was to assess four commercial serological tests from EUROIMMUN, DiaSorin, Abbott, and Roche as well as an in-house immunofluorescence and neutralization test for their capability to identify SARS-CoV-2 seropositive individuals in a high-prevalence setting. Therefore, 42 social and working contacts of a German super-spreader were tested. Consistent with a high-prevalence setting, 26 of 42 were SARS-CoV-2 seropositive by neutralization test (NT), and immunofluorescence test (IFT) confirmed 23 of these 26 positive test results (NT 61.9% and IFT 54.8% seroprevalence). Four commercial assays detected anti-SARS-CoV-2 antibodies in 33.3-40.5% individuals. Besides an overall discrepancy between the NT and the commercial assays regarding their sensitivity, this study revealed that commercial SARS-CoV-2 spike-based assays are better to predict the neutralization titer than nucleoprotein-based assays are.

Rhinovirus prevalence as indicator for efficacy of measures against SARS-CoV-2.

BACKGROUND: Non-pharmaceutical measures to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) should be carefully tuned as they can impose a heavy social and economic burden. To quantify and possibly tune the efficacy of these anti-SARS-CoV-2 measures, we have devised indicators based on the abundant historic and current prevalence data from other respiratory viruses. METHODS: We obtained incidence data of 17 respiratory viruses from hospitalized patients and outpatients collected by 37 clinics and laboratories between 2010-2020 in Germany. With a probabilistic model for Bayes inference we quantified prevalence changes of the different viruses between months in the pre-pandemic period 2010-2019 and the corresponding months in 2020, the year of the pandemic with noninvasive measures of various degrees of stringency. RESULTS: We discovered remarkable reductions δ in rhinovirus (RV) prevalence by about 25% (95% highest density interval (HDI) [-0.35,-0.15]) in the months after the measures against SARS-CoV-2 were introduced in Germany. In the months after the measures began to ease, RV prevalence increased to low pre-pandemic levels, e.g. in August 2020 δ=-0.14 (95% HDI [-0.28,0.12]). CONCLUSIONS: RV prevalence is negatively correlated with the stringency of anti-SARS-CoV-2 measures with only a short time delay. This result suggests that RV prevalence could possibly be an indicator for the efficiency for these measures. As RV is ubiquitous at higher prevalence than SARS-CoV-2 or other emerging respiratory viruses, it could reflect the efficacy of noninvasive measures better than such emerging viruses themselves with their unevenly spreading clusters.

Non-active site mutants of HIV-1 protease influence resistance and sensitisation towards protease inhibitors.

BACKGROUND: HIV-1 can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs. In HIV-1 protease, a majority of resistance-associated mutations that develop in response to therapy with protease inhibitors are found in the protease's active site that serves also as a binding pocket for the protease inhibitors, thus directly impacting the protease-inhibitor interactions. Some resistance-associated mutations, however, are found in more distant regions, and the exact mechanisms how these mutations affect protease-inhibitor interactions are unclear. Furthermore, some of these mutations, e.g. N88S and L76V, do not only induce resistance to the currently administered drugs, but contrarily induce sensitivity towards other drugs. In this study, mutations N88S and L76V, along with three other resistance-associated mutations, M46I, I50L, and I84V, are analysed by means of molecular dynamics simulations to investigate their role in complexes of the protease with different inhibitors and in different background sequence contexts. RESULTS: Using these simulations for alchemical calculations to estimate the effects of mutations M46I, I50L, I84V, N88S, and L76V on binding free energies shows they are in general in line with the mutations' effect on [Formula: see text] values. For the primary mutation L76V, however, the presence of a background mutation M46I in our analysis influences whether the unfavourable effect of L76V on inhibitor binding is sufficient to outweigh the accompanying reduction in catalytic activity of the protease. Finally, we show that L76V and N88S changes the hydrogen bond stability of these residues with residues D30/K45 and D30/T31/T74, respectively. CONCLUSIONS: We demonstrate that estimating the effect of both binding pocket and distant mutations on inhibitor binding free energy using alchemical calculations can reproduce their effect on the experimentally measured [Formula: see text] values. We show that distant site mutations L76V and N88S affect the hydrogen bond network in the protease's active site, which offers an explanation for the indirect effect of these mutations on inhibitor binding. This work thus provides valuable insights on interplay between primary and background mutations and mechanisms how they affect inhibitor binding.

geno2pheno[ngs-freq]: a genotypic interpretation system for identifying viral drug resistance using next-generation sequencing data.

Identifying resistance to antiretroviral drugs is crucial for ensuring the successful treatment of patients infected with viruses such as human immunodeficiency virus (HIV) or hepatitis C virus (HCV). In contrast to Sanger sequencing, next-generation sequencing (NGS) can detect resistance mutations in minority populations. Thus, genotypic resistance testing based on NGS data can offer novel, treatment-relevant insights. Since existing web services for analyzing resistance in NGS samples are subject to long processing times and follow strictly rules-based approaches, we developed geno2pheno[ngs-freq], a web service for rapidly identifying drug resistance in HIV-1 and HCV samples. By relying on frequency files that provide the read counts of nucleotides or codons along a viral genome, the time-intensive step of processing raw NGS data is eliminated. Once a frequency file has been uploaded, consensus sequences are generated for a set of user-defined prevalence cutoffs, such that the constructed sequences contain only those nucleotides whose codon prevalence exceeds a given cutoff. After locally aligning the sequences to a set of references, resistance is predicted using the well-established approaches of geno2pheno[resistance] and geno2pheno[hcv]. geno2pheno[ngs-freq] can assist clinical decision making by enabling users to explore resistance in viral populations with different abundances and is freely available at http://ngs.geno2pheno.org.