Despite the success of antiretroviral therapy in controlling HIV replication, latent viral reservoirs persist, presenting a major barrier to a cure. Current treatment approaches that aim to reactivate latent virus and eliminate infected cells, termed "shock and kill," hold promise but have yet to demonstrate meaningful reservoir reduction in vivo. In this study, we explored combining ciapavir, a Smac mimetic latency-reversing agent, with adeno-associated virus-delivered (AAV-delivered) eCD4-Ig to treat antiretroviral therapy-suppressed, SHIV-infected rhesus macaques. We could demonstrate that a Smac mimetic can induce modest reactivation of the latent SHIV reservoir, as evidenced by transient increases in plasma viremia. However, while AAV-expressed eCD4-Ig conferred partial protection against intrarectal SHIV challenge in uninfected animals, neither eCD4-Ig nor ciapavir reduced the viral reservoir in SHIV-infected rhesus macaques, as determined by total SHIV DNA and a 5-target intact provirus detection assay. Animals treated with the combination showed no significant differences in viral rebound kinetics post-analytical treatment interruption compared with controls. Additionally, repeated ciapavir dosing resulted in adverse effects in some animals, suggesting potential toxicity with repeat administration. These findings highlight the challenges in reducing viral reservoirs using this shock-and-kill approach, particularly in SHIV-infected models, and suggest that further optimization of both latency-reversing agent and immune-mediated clearance strategies is required.

Coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can cause severe disease in humans, whereas reservoir hosts such as horseshoe bats remain asymptomatic. To investigate how host-specific protein-protein interactions (PPIs) influence infection, we generated comparative PPI maps for SARS-CoV-2 and its bat progenitor RaTG13, using affinity purification mass spectrometry (AP-MS) in human and greater horseshoe bat cells. We identify both conserved and virus- and host-specific interactions that regulate infection dynamics. Notably, SARS-CoV-2 requires a nonsynonymous mutation in the nucleocapsid to replicate in bat cells expressing human ACE2 and TMPRSS2. Strikingly, a single amino acid difference in Orf9b between viruses acts as a molecular switch that reprograms mitochondrial targeting: in human cells, enhanced translocase of outer mitochondrial membrane 70 (Tom70) binding promotes immune evasion, whereas in bat cells, strengthened interaction with the bat-enriched restriction factor mitochondrial amidoxime reducing component 2 (MTARC2) limits infection. These findings establish a general principle by which minimal sequence variation can reshape virus-host interactions and contribute to immune antagonism, host adaptation, and species barriers.

Influenza A virus (IAV) infection remodels cellular processes to support viral replication. The modulation of host factors by the virus drives pathogenesis during infection, and these factors may serve as therapeutic targets. Here, we infect mice with two IAV strains, H1N1 and H5N1, and analyze lung tissue with multi-omics. Using network propagation analysis, we identify twenty-four distinct host modules altered by infection, encompassing 2920 genes/proteins. Independently, we develop a computational pipeline, MidTOD, which integrates metabolomic data with other OMICs data-types, linking metabolites to gene/protein alterations. Combining datasets from both approaches reveals alterations in mitochondrial and peroxisomal metabolism in IAV-infected cells and identifies arginine:glycine amidinotransferase (GATM) as a host dependency factor in both human cells and mice. Knockdown of this enzyme reduces IAV-mediated pathology and host inflammatory responses after infection. Collectively, this work provides an integrated systems-level view of host changes during infection and identifies an abundance of IAV-host factors.

Coronaviruses, including SARS-CoV-2, can cause severe disease in humans, whereas reservoir hosts like Rhinolophus bats remain asymptomatic. To investigate how host-specific protein-protein interactions (PPIs) influence infection, we generated comparative PPI maps for SARS-CoV-2 and its bat-origin relative RaTG13 using affinity purification-mass spectrometry (AP-MS) in human and Rhinolophus ferrumequinum (RFe) bat cells. This approach identified both conserved and virus- and host-specific interactions that regulate infection dynamics. Notably, SARS-CoV-2 required a non-synonymous mutation in nucleocapsid to replicate in bat cells expressing human ACE2 and TMPRSS2. Analysis of the viral protein Orf9b revealed differential interactions with mitochondrial proteins Tom70 and MTARC2. A single residue difference in Orf9b between SARS-CoV-2 and RaTG13 functions as a molecular switch, weakening Tom70 binding and immune evasion in human cells while enhancing interaction with the bat-specific restriction factor MTARC2. These findings demonstrate how a single-residue substitution can reshape virus-host interactions and contribute to immune evasion and host adaptation.

Defining the subset of cellular factors governing SARS-CoV-2 replication can provide critical insights into viral pathogenesis and identify targets for host-directed antiviral therapies. While a number of genetic screens have previously reported SARS-CoV-2 host dependency factors, most of these approaches relied on utilizing pooled genome-scale CRISPR libraries, which are biased toward the discovery of host proteins impacting early stages of viral replication. To identify host factors involved throughout the SARS-CoV-2 infectious cycle, we conducted an arrayed genome-scale siRNA screen. Resulting data were integrated with published functional screens and proteomics data to reveal (i) common pathways that were identified in all OMICs datasets-including regulation of Wnt signaling and gap junctions, (ii) pathways uniquely identified in this screen-including NADH oxidation, or (iii) pathways supported by this screen and proteomics data but not published functional screens-including arachionate production and MAPK signaling. The identified proviral host factors were mapped into the SARS-CoV-2 infectious cycle, including 32 proteins that were determined to impact viral replication and 27 impacting late stages of infection, respectively. Additionally, a subset of proteins was tested across other coronaviruses revealing a subset of proviral factors that were conserved across pandemic SARS-CoV-2, epidemic SARS-CoV-1 and MERS-CoV, and the seasonal coronavirus OC43-CoV. Further studies illuminated a role for the heparan sulfate proteoglycan perlecan in SARS-CoV-2 viral entry and found that inhibition of the non-canonical NF-kB pathway through targeting of BIRC2 restricts SARS-CoV-2 replication both in vitro and in vivo. These studies provide critical insight into the landscape of virus-host interactions driving SARS-CoV-2 replication as well as valuable targets for host-directed antivirals.

Hybrid immunity (vaccination + natural infection) to SARS-CoV-2 provides superior protection to re-infection. We performed immune profiling studies during breakthrough infections in mRNA-vaccinated hamsters to evaluate hybrid immunity induction. The mRNA vaccine, BNT162b2, was dosed to induce binding antibody titers against ancestral spike, but inefficient serum virus neutralization of ancestral SARS-CoV-2 or variants of concern (VoCs). Vaccination reduced morbidity and controlled lung virus titers for ancestral virus and Alpha but allowed breakthrough infections in Beta, Delta and Mu-challenged hamsters. Vaccination primed for T cell responses that were boosted by infection. Infection back-boosted neutralizing antibody responses against ancestral virus and VoCs. Hybrid immunity resulted in more cross-reactive sera, reflected by smaller antigenic cartography distances. Transcriptomics post-infection reflects both vaccination status and disease course and suggests a role for interstitial macrophages in vaccine-mediated protection. Therefore, protection by vaccination, even in the absence of high titers of neutralizing antibodies in the serum, correlates with recall of broadly reactive B- and T-cell responses.

Many machine learning applications in bioinformatics currently rely on matching gene identities when analyzing input gene signatures and fail to take advantage of preexisting knowledge about gene functions. To further enable comparative analysis of OMICS datasets, including target deconvolution and mechanism of action studies, we develop an approach that represents gene signatures projected onto their biological functions, instead of their identities, similar to how the word2vec technique works in natural language processing. We develop the Functional Representation of Gene Signatures (FRoGS) approach by training a deep learning model and demonstrate that its application to the Broad Institute’s L1000 datasets results in more effective compound-target predictions than models based on gene identities alone. By integrating additional pharmacological activity data sources, FRoGS significantly increases the number of high-quality compound-target predictions relative to existing approaches, many of which are supported by in silico and/or experimental evidence. These results underscore the general utility of FRoGS in machine learning-based bioinformatics applications. Prediction networks pre-equipped with the knowledge of gene functions may help uncover new relationships among gene signatures acquired by large-scale OMICs studies on compounds, cell types, disease models, and patient cohorts.

Defining the subset of cellular factors governing SARS-CoV-2 replication can provide critical insights into viral pathogenesis and identify targets for host-directed antiviral therapies. While a number of genetic screens have previously reported SARS-CoV-2 host dependency factors, these approaches relied on utilizing pooled genome-scale CRISPR libraries, which are biased towards the discovery of host proteins impacting early stages of viral replication. To identify host factors involved throughout the SARS-CoV-2 infectious cycle, we conducted an arrayed genome-scale siRNA screen. Resulting data were integrated with published datasets to reveal pathways supported by orthogonal datasets, including transcriptional regulation, epigenetic modifications, and MAPK signalling. The identified proviral host factors were mapped into the SARS-CoV-2 infectious cycle, including 27 proteins that were determined to impact assembly and release. Additionally, a subset of proteins were tested across other coronaviruses revealing 17 potential pan-coronavirus targets. Further studies illuminated a role for the heparan sulfate proteoglycan perlecan in SARS-CoV-2 viral entry, and found that inhibition of the non-canonical NF-kB pathway through targeting of BIRC2 restricts SARS-CoV-2 replication both in vitro and in vivo. These studies provide critical insight into the landscape of virus-host interactions driving SARS-CoV-2 replication as well as valuable targets for host-directed antivirals.

Antigenically distinct SARS-CoV-2 variants increase the reinfection risk for vaccinated and previously exposed population due to antibody neutralization escape. COVID-19 severity depends on many variables, including host immune responses, which differ depending on genetic predisposition. To address this, we perform immune profiling of female mice with different genetic backgrounds -transgenic K18-hACE2 and wild-type 129S1- infected with the severe B.1.351, 30 days after exposure to the milder BA.1 or severe H1N1. Prior BA.1 infection protects against B.1.351-induced morbidity in K18-hACE2 but aggravates disease in 129S1. H1N1 protects against B.1.351-induced morbidity only in 129S1. Enhanced severity in B.1.351 re-infected 129S1 is characterized by an increase of IL-10, IL-1β, IL-18 and IFN-γ, while in K18-hACE2 the cytokine profile resembles naïve mice undergoing their first viral infection. Enhanced pathology during 129S1 reinfection cannot be attributed to weaker adaptive immune responses to BA.1. Infection with BA.1 causes long-term differential remodeling and transcriptional changes in the bronchioalveolar CD11c+ compartment. K18-hACE2 CD11c+ cells show a strong antiviral defense expression profile whereas 129S1 CD11c+ cells present a more pro-inflammatory response upon restimulation. In conclusion, BA.1 induces cross-reactive adaptive immune responses in K18-hACE2 and 129S1, but reinfection outcome correlates with differential CD11c+ cells responses in the alveolar space.

Rapid emergence of antigenic distinct SARS-CoV-2 variants implies a greater risk of reinfection as viruses can escape neutralizing antibodies induced by vaccination or previous viral exposure. Disease severity during COVID-19 depends on many variables such as age-related comorbidities, host immune status and genetic variation. The host immune response during infection with SARS-CoV-2 may contribute to disease severity, which can range from asymptomatic to severe with fatal outcome. Furthermore, the extent of host immune response activation may rely on underlying genetic predisposition for disease or protection. To address these questions, we performed immune profiling studies in mice with different genetic backgrounds - transgenic K18-hACE2 and wild-type 129S1 mice – subjected to reinfection with the severe disease-causing SARS-CoV-2 B.1.351 variant, 30 days after experimental milder BA.1 infection. BA.1 preinfection conferred protection against B.1.351-induced morbidity in K18-hACE2 mice but aggravated disease in 129S1 mice. We found that he cytokine/chemokine profile in B.1.351 re-infected 129S1mice is similar to that during severe SARS-CoV-2 infection in humans and is characterized by a much higher level of IL-10, IL-1β, IL-18 and IFN-γ, whereas in B.1.351 re-infected K18-hACE2 mice, the cytokine profile echoes the signature of naïve mice undergoing viral infection for the first time. Interestingly, the enhanced pathology observed in 129S1 mice upon reinfection cannot be attributed to a less efficient induction of adaptive immune responses to the initial BA.1 infection, as both K18-hACE2 and 129S1 mice exhibited similar B and T cell responses at 30 DPI against BA.1, with similar anti-BA.1 or B.1.351 spike-specific ELISA binding titers, levels of germinal center B-cells, and SARS-CoV-2-Spike specific tissue-resident T-cells. Long-term effects of BA.1 infection are associated with differential transcriptional changes in bronchoalveolar lavage-derived CD11c + immune cells from K18-hACE2 and 129S1, with K18-hACE2 CD11c + cells showing a strong antiviral defense gene expression profile whereas 129S1 CD11c + cells showed a more pro-inflammatory response. In conclusion, initial infection with BA.1 induces cross-reactive adaptive immune responses in both K18-hACE2 and 129S1 mice, however the different disease outcome of reinfection seems to be driven by differential responses of CD11c + cells in the alveolar space.

Antiretroviral therapy (ART) has brought the HIV/AIDS epidemic under control, but a curative strategy for viral eradication is still needed. The cessation of ART results in rapid viral rebound from latently infected CD4+ T cells, showing that control of viral replication alone does not fully restore immune function, nor does it eradicate viral reservoirs. With a better understanding of factors and mechanisms that promote viral latency, current approaches are primarily focused on the permanent silencing of latently infected cells (“block and lock”) or reactivating HIV-1 gene expression in latently infected cells, in combination with immune restoration strategies to eliminate HIV infected cells from the host (“shock and kill”). In this review, we provide a summary of the current, most promising approaches for HIV-1 cure strategies, including an analysis of both latency-promoting agents (LPA) and latency-reversing agents (LRA) that have shown promise in vitro, ex vivo, and in human clinical trials to reduce the HIV-1 reservoir.

Biomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability, reusability). As a Consortium of infectious disease researchers from 15 Centers, we aim to adopt open science practices to promote transparency, encourage reproducibility, and accelerate research advances through data reuse. To improve FAIRness of our datasets and computational tools, we evaluated metadata standards across established biomedical data repositories. The vast majority do not adhere to a single standard, such as Schema.org, which is widely-adopted by generalist repositories. Consequently, datasets in these repositories are not findable in aggregation projects like Google Dataset Search. We alleviated this gap by creating a reusable metadata schema based on Schema.org and catalogued nearly 400 datasets and computational tools we collected. The approach is easily reusable to create schemas interoperable with community standards, but customized to a particular context. Our approach enabled data discovery, increased the reusability of datasets from a large research consortium, and accelerated research. Lastly, we discuss ongoing challenges with FAIRness beyond discoverability.

AIR data sharing is integral to spur research reproducibility, promote data reuse, and accelerate research.However, the first step in using these data assets -discovering that they exist -is compounded by problems in incentives, standardization, and coordination of efforts.In 2023, the National Institutes of Health (NIH) implemented their updated Data Sharing Policy, which mandates timely data sharing of all NIH-funded data.However, for the policy to shift the data sharing culture, to improve research reproducibility, and to promote data reuse, several changes must happen.In a companion piece 1 , we present a survey of the data sharing landscape for immune-mediated and infectious disease data, combined with our efforts to create a reusable methodology to catalog data we generate.We found that researchers routinely share data, but datasets are still not necessarily findable, accessible, interoperable, or reusable (FAIR) 2 .In the course of these efforts, we identified three interdependent barriers that need to be addressed to maximize the impact of data sharing efforts that are becoming increasingly commonplace: (1) a lack of incentives, (2) little standardization in metadata collection and access, and (3) uncoordinated efforts.Here, we propose solutions to improve the FAIRness of metadata, data, and the experimental conditions used to generate these data.Our solutions include leveraging journals as a key driver of research incentives and consolidating data searching and citation into a centralized platform.While we focus our discussion based on our experience primarily with NIH-funded research, these principles are broadly applicable to other data sharing efforts worldwide.Barrier 1: Without incentives, researchers tend to provide incomplete metadata, which limits data discovery and reuse.Currently, there are few tangible incentives for researchers to share data.There is limited recognition amongst scientists regarding the benefits of data sharing, while the potential for downside effects such as the risk of getting scooped, concerns over protecting participant/patient privacy, a lack of Intellectual Property protection, and the enhanced workload associated with providing good, reusable, and discoverable data are all well recognized.As a result, researchers frequently do the bare minimum to comply with journal and funder mandates.When sharing data, researchers also include metadata which describe the contents of the dataset to aid in searchability, but these metadata are often insufficient to help researchers identify useful datasets.Even if a metadata property is required, researchers can circumvent these requirements by providing short, generic descriptions.Consequently, metadata is often cursory and incomplete, and data is often provided in non-machine readable formats (e.g., .pdf,Microsoft Word, or free text) without associated documentation to support reuse.While there are many projects that attempt to improve the FAIRness of poorly collected metadata 3,4 , it is far easier to collect complete, well-structured metadata from the start (see Solution 2.3).Our proposed solutions tap into the two primary incentive structures for researchers: funding opportunities and recognition via citations.Solution 1.1: Ensure that there are sufficient resources for data sharing activities within funding opportunities.Documenting data to make it reusable takes time and effort, detracting from experimentation, data analysis, and synthesis of insights into publications.If funding agencies (e.g., NIH) mandate data sharing, they should be prepared to increase budgets accordingly to dedicate a portion of the effort to ensuring the resulting CommeNt oPeN

Influenza A Virus (IAV) is a recurring respiratory virus with limited availability of antiviral therapies. Understanding host proteins essential for IAV infection can identify targets for alternative host-directed therapies (HDTs). Using affinity purification-mass spectrometry and global phosphoproteomic and protein abundance analyses using three IAV strains (pH1N1, H3N2, H5N1) in three human cell types (A549, NHBE, THP-1), we map 332 IAV-human protein-protein interactions and identify 13 IAV-modulated kinases. Whole exome sequencing of patients who experienced severe influenza reveals several genes, including scaffold protein AHNAK, with predicted loss-of-function variants that are also identified in our proteomic analyses. Of our identified host factors, 54 significantly alter IAV infection upon siRNA knockdown, and two factors, AHNAK and coatomer subunit COPB1, are also essential for productive infection by SARS-CoV-2. Finally, 16 compounds targeting our identified host factors suppress IAV replication, with two targeting CDK2 and FLT3 showing pan-antiviral activity across influenza and coronavirus families. This study provides a comprehensive network model of IAV infection in human cells, identifying functional host targets for pan-viral HDT.

Molecular responses to influenza A virus (IAV) infections vary between mammalian species. To identify conserved and species-specific molecular responses, we perform a comparative study of transcriptomic data derived from blood cells, primary epithelial cells, and lung tissues collected from IAV-infected humans, ferrets, and mice. The molecular responses in the human host have unique functions such as antigen processing that are not observed in mice or ferrets. Highly conserved gene coexpression modules across the three species are enriched for IAV infection–induced pathways including cell cycle and interferon (IFN) signaling. TDRD7 is predicted as an IFN-inducible host factor that is up-regulated upon IAV infection in the three species. TDRD7 is required for antiviral IFN response, potentially modulating IFN signaling via the JAK/STAT/IRF9 pathway. Identification of the common and species-specific molecular signatures, networks, and regulators of IAV infection provides insights into host-defense mechanisms and will facilitate the development of novel therapeutic interventions against IAV infection.

There is a pressing need for host-directed therapeutics that elicit broad-spectrum antiviral activities to potentially address current and future viral pandemics. Apratoxin S4 (Apra S4) is a potent Sec61 inhibitor that prevents cotranslational translocation of secretory proteins into the endoplasmic reticulum (ER), leading to anticancer and antiangiogenic activity both in vitro and in vivo. Since Sec61 has been shown to be an essential host factor for viral proteostasis, we tested Apra S4 in cellular models of viral infection, including SARS-CoV-2, influenza A virus, and flaviviruses (Zika, West Nile, and Dengue virus). Apra S4 inhibited viral replication in a concentration-dependent manner and had high potency particularly against SARS-CoV-2 and influenza A virus, with subnanomolar activity in human cells. Characterization studies focused on SARS-CoV-2 revealed that Apra S4 impacted a post-entry stage of the viral life-cycle. Transmission electron microscopy revealed that Apra S4 blocked formation of stacked double-membrane vesicles, the sites of viral replication. Apra S4 reduced dsRNA formation and prevented viral protein production and trafficking of secretory proteins, especially the spike protein. Given the potent and broad-spectrum activity of Apra S4, further preclinical evaluation of Apra S4 and other Sec61 inhibitors as antivirals is warranted.

Ly6C hi inflammatory monocytes show high IFN responses, and contribute to both protective and pathogenic functions following influenza virus infection. In order to understand the significance of IFN responses in this subset, we examined monocytes during infection with a lethal H5N1 virus that induces high levels of IFN and a low-pathogenicity H1N1 virus that induces low levels of IFN. We show that H5N1 infection results in early recruitment of high numbers of Ly6C hi monocytes and induction of chemokines and Ifnb1 . Using unbiased transcriptomic and proteomic approaches, we also find that monocytes are significantly enriched during H5N1 infection and are associated with chemokine and IFN signatures in mice, and with severity of symptoms after influenza virus infection in humans. Recruited Ly6C hi monocytes subsequently become infected in the lung, produce IFN-β, and mature into FasL + monocyte-derived cells (FasL + MCs) expressing dendritic cell markers. Both Ccr2 -/- and Fasl gld mice are protected from lethal infection, indicating that monocytes contribute to pathogenesis. Global loss of type I and type III IFN signaling in Stat2 -/- mice results in loss of monocyte recruitment, likely reflecting a requirement for IFN-dependent chemokine induction. Here we show that IFN is not directly required for monocyte recruitment on an IFN-sufficient background, but is required for maturation to FasL + MCs. Loss of IFN signaling skews to a Ly6C lo phenotype associated with tissue repair, suggesting that IFN signaling in monocytes is a critical determinant of influenza virus pathogenesis.

A deficient interferon (IFN) response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been implicated as a determinant of severe coronavirus disease 2019 (COVID-19). To identify the molecular effectors that govern IFN control of SARS-CoV-2 infection, we conducted a large-scale gain-of-function analysis that evaluated the impact of human IFN-stimulated genes (ISGs) on viral replication. A limited subset of ISGs were found to control viral infection, including endosomal factors inhibiting viral entry, RNA binding proteins suppressing viral RNA synthesis, and a highly enriched cluster of endoplasmic reticulum (ER)/Golgi-resident ISGs inhibiting viral assembly/egress. These included broad-acting antiviral ISGs and eight ISGs that specifically inhibited SARS-CoV-2 and SARS-CoV-1 replication. Among the broad-acting ISGs was BST2/tetherin, which impeded viral release and is antagonized by SARS-CoV-2 Orf7a protein. Overall, these data illuminate a set of ISGs that underlie innate immune control of SARS-CoV-2/SARS-CoV-1 infection, which will facilitate the understanding of host determinants that impact disease severity and offer potential therapeutic strategies for COVID-19.