Host genetic variation guides hepacivirus clearance, chronicity, and liver fibrosis in mice.

BACKGROUND AIMS: Human genetic variation is thought to guide the outcome of HCV infection, but model systems within which to dissect these host genetic mechanisms are limited. Norway rat hepacivirus, closely related to HCV, causes chronic liver infection in rats but causes acute self-limiting hepatitis in typical strains of laboratory mice, which resolves in 2 weeks. The Collaborative Cross (CC) is a robust mouse genetics resource comprised of a panel of recombinant inbred strains, which model the complexity of the human genome and provide a system within which to understand diseases driven by complex allelic variation. APPROACH RESULTS: We infected a panel of CC strains with Norway rat hepacivirus and identified several that failed to clear the virus after 4 weeks. Strains displayed an array of virologic phenotypes ranging from delayed clearance (CC046) to chronicity (CC071, CC080) with viremia for at least 10 months. Body weight loss, hepatocyte infection frequency, viral evolution, T-cell recruitment to the liver, liver inflammation, and the capacity to develop liver fibrosis varied among infected CC strains. CONCLUSIONS: These models recapitulate many aspects of HCV infection in humans and demonstrate that host genetic variation affects a multitude of viruses and host phenotypes. These models can be used to better understand the molecular mechanisms that drive hepacivirus clearance and chronicity, the virus and host interactions that promote chronic disease manifestations like liver fibrosis, therapeutic and vaccine performance, and how these factors are affected by host genetic variation.

Charting the impact of maternal antibodies and repeat exposures on sapovirus immunity in early childhood from a Nicaraguan birth cohort.

BACKGROUND: Sapovirus is an important cause of acute gastroenteritis in childhood. While vaccines against sapovirus may reduce gastroenteritis burden, a major challenge to their development is a lack of information about natural immunity. METHODS: We measured sapovirus-specific IgG in serum collected, between 2017 and 2020, of mothers soon after delivery and at 6 time points in Nicaraguan children until 3 years of age (n=112 dyads) using virus-like particles representing three sapovirus genotypes (GI.1, GI.2, GV.1). RESULTS: Sixteen (14.3%) of the 112 children experienced at least one sapovirus gastroenteritis episode, of which GI.1 was the most common genotype. Seroconversion to GI.1 and GI.2 was most common between 5 and 12 months of age, while seroconversion to GV.1 peaked at 18 to 24 months of age. All children who experienced sapovirus GI.1 gastroenteritis seroconverted and developed genotype-specific IgG. The impact of sapovirus exposure on population immunity was determined using antigenic cartography: newborns share their mothers' broadly binding IgG responses, which declined at 5 months of age and then increased as infants experienced natural sapovirus infections. CONCLUSION: By tracking humoral immunity to sapovirus over the first 3 years of life, this study provides important insights for the design and timing of future pediatric sapovirus vaccines.

Ancient fish lineages illuminate toll-like receptor diversification in early vertebrate evolution.

Since its initial discovery over 50 years ago, understanding the evolution of the vertebrate RAG- mediated adaptive immune response has been a major area of research focus for comparative geneticists. However, how the evolutionary novelty of an adaptive immune response impacted the diversity of receptors associated with the innate immune response has received considerably less attention until recently. Here, we investigate the diversification of vertebrate toll-like receptors (TLRs), one of the most ancient and well conserved innate immune receptor families found across the Tree of Life, integrating genomic data that represent all major vertebrate lineages with new transcriptomic data from Polypteriformes, the earliest diverging ray-finned fish lineage. Our analyses reveal TLR sequences that reflect the 6 major TLR subfamilies, TLR1, TLR3, TLR4, TLR5, TLR7, and TLR11, and also currently unnamed, yet phylogenetically distinct TLR clades. We additionally recover evidence for a pulse of gene gain coincident with the rise of the RAG-mediated adaptive immune response in jawed vertebrates, followed by a period of rapid gene loss during the Cretaceous. These gene losses are primarily concentrated in marine teleost fish and synchronous with the mid Cretaceous anoxic event, a period of rapid extinction for marine species. Finally, we reveal a mismatch between phylogenetic placement and gene nomenclature for up to 50% of TLRs found in clades such as ray-finned fishes, cyclostomes, amphibians, and elasmobranchs. Collectively, these results provide an unparalleled perspective of TLR diversity and offer a ready framework for testing gene annotations in non-model species.

Ex vivo discovery of synergistic drug combinations for hematologic malignancies.

Combination therapies have improved outcomes for patients with acute myeloid leukemia (AML). However, these patients still have poor overall survival. Although many combination therapies are identified with high-throughput screening (HTS), these approaches are constrained to disease models that can be grown in large volumes (e.g., immortalized cell lines), which have limited translational utility. To identify more effective and personalized treatments, we need better strategies for screening and exploring potential combination therapies. Our objective was to develop an HTS platform for identifying effective combination therapies with highly translatable ex vivo disease models that use size-limited, primary samples from patients with leukemia (AML and myelodysplastic syndrome). We developed a system, ComboFlow, that comprises three main components: MiniFlow, ComboPooler, and AutoGater. MiniFlow conducts ex vivo drug screening with a miniaturized flow-cytometry assay that uses minimal amounts of patient sample to maximize throughput. ComboPooler incorporates computational methods to design efficient screens of pooled drug combinations. AutoGater is an automated gating classifier for flow cytometry that uses machine learning to rapidly analyze the large datasets generated by the assay. We used ComboFlow to efficiently screen more than 3000 drug combinations across 20 patient samples using only 6 million cells per patient sample. In this screen, ComboFlow identified the known synergistic combination of bortezomib and panobinostat. ComboFlow also identified a novel drug combination, dactinomycin and fludarabine, that synergistically killed leukemic cells in 35 % of AML samples. This combination also had limited effects in normal, hematopoietic progenitors. In conclusion, ComboFlow enables exploration of massive landscapes of drug combinations that were previously inaccessible in ex vivo models. We envision that ComboFlow can be used to discover more effective and personalized combination therapies for cancers amenable to ex vivo models.

Mapping of susceptibility loci for Ebola virus pathogenesis in mice.

Ebola virus (EBOV), a major global health concern, causes severe, often fatal EBOV disease (EVD) in humans. Host genetic variation plays a critical role, yet the identity of host susceptibility loci in mammals remains unknown. Using genetic reference populations, we generate an F2 mapping cohort to identify host susceptibility loci that regulate EVD. While disease-resistant mice display minimal pathogenesis, susceptible mice display severe liver pathology consistent with EVD-like disease and transcriptional signatures associated with inflammatory and liver metabolic processes. A significant quantitative trait locus (QTL) for virus RNA load in blood is identified in chromosome (chr)8, and a severe clinical disease and mortality QTL is mapped to chr7, which includes the Trim5 locus. Using knockout mice, we validate the Trim5 locus as one potential driver of liver failure and mortality after infection. The identification of susceptibility loci provides insight into molecular genetic mechanisms regulating EVD progression and severity, potentially informing therapeutics and vaccination strategies.

The oral nucleoside prodrug GS-5245 is efficacious against SARS-CoV-2 and other endemic, epidemic, and enzootic coronaviruses.

Despite the wide availability of several safe and effective vaccines that prevent severe COVID-19, the persistent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) that can evade vaccine-elicited immunity remains a global health concern. In addition, the emergence of SARS-CoV-2 VOCs that can evade therapeutic monoclonal antibodies underscores the need for additional, variant-resistant treatment strategies. Here, we characterize the antiviral activity of GS-5245, obeldesivir (ODV), an oral prodrug of the parent nucleoside GS-441524, which targets the highly conserved viral RNA-dependent RNA polymerase (RdRp). We show that GS-5245 is broadly potent in vitro against alphacoronavirus HCoV-NL63, SARS-CoV, SARS-CoV-related bat-CoV RsSHC014, Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV-2 WA/1, and the highly transmissible SARS-CoV-2 BA.1 Omicron variant. Moreover, in mouse models of SARS-CoV, SARS-CoV-2 (WA/1 and Omicron B1.1.529), MERS-CoV, and bat-CoV RsSHC014 pathogenesis, we observed a dose-dependent reduction in viral replication, body weight loss, acute lung injury, and pulmonary function with GS-5245 therapy. Last, we demonstrate that a combination of GS-5245 and main protease (Mpro) inhibitor nirmatrelvir improved outcomes in vivo against SARS-CoV-2 compared with the single agents. Together, our data support the clinical evaluation of GS-5245 against coronaviruses that cause or have the potential to cause human disease.

Seasonality of endemic COVID-19.

Successive waves of infection by SARS-CoV-2 have left little doubt that this virus will transition to an endemic disease. Foreknowledge of when to expect seasonal surges is crucial for healthcare and public health decision-making. However, the future seasonality of COVID-19 remains uncertain. Evaluating its seasonality is complicated due to the limited years of SARS-CoV-2 circulation, pandemic dynamics, and varied interventions. In this study, we project the expected endemic seasonality by employing a phylogenetic ancestral and descendant state approach that leverages long-term data on the incidence of circulating HCoV coronaviruses. Our projections indicate asynchronous surges of SARS-CoV-2 across different locations in the northern hemisphere, occurring between October and January in New York and between January and March in Yamagata, Japan. This knowledge of spatiotemporal surges leads to medical preparedness and enables the implementation of targeted public health interventions to mitigate COVID-19 transmission.IMPORTANCEThe seasonality of COVID-19 is important for effective healthcare and public health decision-making. Previous waves of SARS-CoV-2 infections have indicated that the virus will likely persist as an endemic pathogen with distinct surges. However, the timing and patterns of potentially seasonal surges remain uncertain, rendering effective public health policies uninformed and in danger of poorly anticipating opportunities for intervention, such as well-timed booster vaccination drives. Applying an evolutionary approach to long-term data on closely related circulating coronaviruses, our research provides projections of seasonal surges that should be expected at major temperate population centers. These projections enable local public health efforts that are tailored to expected surges at specific locales or regions. This knowledge is crucial for enhancing medical preparedness and facilitating the implementation of targeted public health interventions.