Biology subjects

Wang, J. P.

Publications and source records attributed to Wang, J. P..

8 recordsLinked to original sources

bioRxiv2024

CRISPR editing of candidate host factors that impact influenza A virus infection

Influenza A virus (IAV) is a respiratory pathogen with a segmented negative-sense RNA genome that can cause epidemics and pandemics. The host factors required for the complete IAV infectious cycle have not been fully identified. Here, we examined select host factors that were identified by independent CRISPR screens as candidate contributors to IAV infectivity. We performed CRISPR-mediated knockout of cytidine monophosphate N-acetylneuraminic acid synthetase (CMAS) as well as CRISPR-mediated overexpression of beta-1,4 N-acetylgalactosaminyltransferase 2 (B4GALNT2) and adenosine deaminase acting on RNA 1 (ADAR1) in the human bronchial epithelial A549 cell line and evaluated IAV infectivity. We confirmed that the knockout of CMAS or overexpression of B4GALNT2 restricts IAV infection by diminishing binding to the cell surface but has no effect on vesicular stomatitis virus infection. While ADAR1 overexpression does not significantly inhibit IAV replication, it has a pro-viral effect with coxsackie B virus (CVB) infection. This pro-viral effect is not likely secondary to reduced type I interferon (IFN) production, as the induction of the IFN-stimulated genes ISG15 and CXCL10 is negligible in both parent and ADAR1-overexpressing A549 cells following CVB challenge. In contrast, ISG15 and CXCL10 production is robust and equal for parent and ADAR1-overexpressing A549 cells challenged with IAV. Taken together, these data provide insight into how host factors identified in CRISPR screens can be further explored to understand the dynamics of pro- and anti-viral factors. ImportanceInfluenza A virus (IAV) remains a global threat due to its ability to cause pandemics, making the identification of host factors essential for developing new antiviral strategies. In this study, we utilized CRISPR-based techniques to investigate host factors identified in screens as reducing IAV infectivity. Knockout of CMAS, a key enzyme in sialic acid biosynthesis, significantly reduced IAV binding and infection by disrupting sialic acid production on the cell surface. Overexpression of B4GALNT2 had similar effects, conferring resistance to IAV infection through diminished cell-surface binding. While overexpression of ADAR1, known for its role in RNA editing and immune regulation, slightly reduced IAV replication, it increased coxsackie B virus replication. Such findings reveal the diverse roles of host factors in viral infection, offering insights for targeted therapeutic development against IAV and other pathogens.

immunology↗

bioRxiv2023

Dysregulated Pulmonary Inflammatory Responses Exacerbate the Outcome of Secondary Aspergillosis Following Influenza

Inhalation of airborne conidia of the ubiquitous fungus Aspergillus fumigatus commonly occurs but invasive aspergillosis is rare except in profoundly immunocompromised persons. Severe influenza predisposes patients to invasive pulmonary aspergillosis by mechanisms that are poorly defined. Using a post-influenza aspergillosis model, we found that superinfected mice had 100% mortality when challenged with A. fumigatus conidia on days 2 and 5 (early stages) of influenza A virus infection but 100% survival when challenged on days 8 and 14 (late stages). Influenza-infected mice superinfected with A. fumigatus had increased levels of the pro-inflammatory cytokines and chemokines IL-6, TNF, IFN{beta}, IL-12p70, IL-1, IL-1{beta}, CXCL1, G-CSF, MIP-1, MIP-1{beta}, RANTES and MCP-1. Surprisingly, on histopathological analysis, superinfected mice did not have greater lung inflammation compared with mice infected with influenza alone. Mice infected with influenza had dampened neutrophil recruitment to the lungs following subsequent challenge with A. fumigatus, but only if the fungal challenge was executed during the early stages of influenza infection. However, influenza infection did not have a major effect on neutrophil phagocytosis and killing of A. fumigatus conidia. Moreover, minimal germination of conidia was seen on histopathology even in the superinfected mice. Taken together, our data suggest that the high mortality rate seen in mice during the early stages of influenza-associated pulmonary aspergillosis is multifactorial, with a greater contribution from dysregulated inflammation than microbial growth. ImportanceSevere influenza is a risk factor for fatal invasive pulmonary aspergillosis; however, the mechanistic basis for the lethality is unclear. Utilizing an influenza-associated pulmonary aspergillosis (IAPA) model, we found that mice infected with influenza A virus followed by A. fumigatus had 100% mortality when superinfected during the early stages of influenza but survived at later stages. While superinfected mice had dysregulated pulmonary inflammatory responses compared to controls, they had neither increased inflammation nor extensive fungal growth. Although influenza-infected mice had dampened neutrophil recruitment to the lungs following subsequent challenge with A. fumigatus, influenza did not affect the ability of neutrophils to clear the fungi. Our data suggest that the lethality seen in our model IAPA is multifactorial with dysregulated inflammation being a greater contributor than uncontrollable microbial growth. If confirmed in humans, our findings provide a rationale for clinical studies of adjuvant anti-inflammatory agents in the treatment of IAPA.

immunology↗

bioRxiv2022

Cell culture model system utilizing engineered A549 cells to express high levels of ACE2 and TMPRSS2 for investigating SARS-CoV-2 infection and antivirals

Novel pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to pose an imminent global threat since its initial outbreak in December 2019. A simple in vitro model system using cell lines highly susceptible to SARS-CoV-2 infection are critical to facilitate the study of the virus cycle and to discover effective antivirals against the virus. Human lung alveolar A549 cells are regarded as a useful and valuable model for respiratory virus infection. However, SARS-CoV-2 uses the ACE2 as receptor for viral entry and the TMPRSS2 to prime the Spike protein, both of which are negligibly expressed in A549 cells. Here, we report the generation of a robust human lung epithelial cell-based model by transducing ACE2 and TMPRSS2 into A549 cells and show that the ACE2 enriched A549ACE2/TMPRSS2 cells (ACE2plus) and its single-cell-derived subclone (ACE2plusC3) are highly susceptible to SARS-CoV-2 infection. These engineered ACE2plus showed higher ACE2 and TMPRSS2 mRNA expression levels than currently used Calu3 and commercial A549ACE2/TMPRSS2 cells. ACE2 and TMPRSS2 proteins were also highly and ubiquitously expressed in ACE2plusC3 cells. Additionally, antiviral drugs like Camostat mesylate, EIDD-1931, and Remdesivir strongly inhibited SARS-CoV-2 replication. Notably, multinucleated syncytia, a clinical feature commonly observed in severe COVID-19 patients was induced in ACE2plusC3 cells either by virus infection or by overexpressing the Spike proteins of different variants of SARS-CoV-2. Syncytial process was effectively blocked by the furin protease inhibitor, Decanoyl-RVKR-CMK. Taken together, we have developed a robust human A549 lung epithelial cell-based model that can be applied to probe SARS-CoV-2 replication and to facilitate the discovery of SARS-CoV-2 inhibitors.

cell biology↗

bioRxiv2021

Quantitative Structural Analysis of Influenza Virus by Cryo-electron Tomography and Convolutional Neural Networks

Influenza viruses pose severe public health threats; they cause millions of infections and tens of thousands of deaths annually in the US. Influenza viruses are extensively pleomorphic, in both shape and size as well as organization of viral structural proteins. Analysis of influenza morphology and ultrastructure can help elucidate viral structure-function relationships as well as aid in therapeutics and vaccine development. While cryo-electron tomography (cryoET) can depict the 3D organization of pleomorphic influenza, the low signal-to-noise ratio inherent to cryoET and extensive viral heterogeneity have precluded detailed characterization of influenza viruses. In this report, we developed a cryoET processing pipeline leveraging convolutional neural networks (CNNs) to characterize the morphological architecture of the A/Puerto Rico/8/34 (H1N1) influenza strain. Our pipeline improved the throughput of cryoET analysis and accurately identified viral components within tomograms. Using this approach, we successfully characterized influenza viral morphology, glycoprotein density, and conduct subtomogram averaging of HA glycoproteins. Application of this processing pipeline can aid in the structural characterization of not only influenza viruses, but other pleomorphic viruses and infected cells. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/472010v1_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@983f56org.highwire.dtl.DTLVardef@1664734org.highwire.dtl.DTLVardef@1cce73dorg.highwire.dtl.DTLVardef@1617998_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2020

High-Throughput Human Primary Cell-Based Airway Model for Evaluating Influenza, Coronavirus, or other Respiratory Viruses in vitro

Influenza and other respiratory viruses represent a significant threat to public health, national security, and the world economy, and can lead to the emergence of global pandemics such as the current COVID-19 crisis. One of the greatest barriers to the development of effective therapeutic agents to treat influenza, coronaviruses, and many other infections of the respiratory tract is the absence of a robust preclinical model. Preclinical studies currently rely on high-throughput, low-fidelity in vitro screening with cell lines and/or low-throughput animal models that often provide a poor correlation to human clinical responses. Here, we introduce a human primary airway epithelial cell-based model integrated into a high-throughput platform where tissues are cultured at an air-liquid interface (PREDICT96-ALI). We present results on the application of this platform to influenza and coronavirus infections, providing multiple readouts capable of evaluating viral infection kinetics and potentially the efficacy of therapeutic agents in an in vitro system. Several strains of influenza A virus are shown to successfully infect the human primary cell-based airway tissue cultured at an air-liquid interface (ALI), and as a proof-of-concept, the effect of the antiviral oseltamivir on one strain of Influenza A is evaluated. Human coronaviruses NL63 (HCoV-NL63) and SARS-CoV-2 enter host cells via ACE2 and utilize the protease TMPRSS2 for protein priming, and we confirm expression of both in our ALI model. We also demonstrate coronavirus infection in this system with HCoV-NL63, observing sufficient viral propagation over 96 hours post-infection to indicate successful infection of the primary cell-based model. This new capability has the potential to address a gap in the rapid assessment of therapeutic efficacy of various small molecules and antiviral agents against influenza and other respiratory viruses including coronaviruses.

microbiology↗

bioRxiv2020

Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults

Influenza virus infections are major causes of morbidity and mortality. Research using cultured cells, bulk tissue, and animal models cannot fully capture human disease dynamics. Many aspects of virus-host interactions in a natural setting remain unclear, including the specific cell types that are infected and how they and neighboring bystander cells contribute to the overall antiviral response. To address these questions, we performed single-cell RNA sequencing (scRNA-Seq) on cells from freshly collected nasal washes from healthy human donors and donors diagnosed with acute influenza during the 2017-18 season. We describe a previously uncharacterized goblet cell population, specific to infected individuals, with high expression of MHC class II genes. Furthermore, leveraging scRNA-Seq reads, we obtained deep viral genome coverage and developed a model to rigorously identify infected cells that detected influenza infection in all epithelial cell types and even some immune cells. Our data revealed that each donor was infected by a unique influenza variant and that each variant was separated by at least one unique non-synonymous difference. Our results demonstrate the power of massively-parallel scRNA-Seq to study viral variation, as well as host and viral transcriptional activity during human infection.

genomics↗

bioRxiv2019

Modeling cross-regulatory influences on monolignol transcripts and proteins under single and combinatorial gene knockdowns in Populus trichocarpa

Accurate manipulation of metabolites in the monolignol biosynthetic pathway is a key step for controlling lignin content, structure, and other wood properties important to the bioenergy and biomaterial industries. A crucial component of this strategy is predicting how single and combinatorial knockdowns of monolignol specific gene transcripts influence the abundance of monolignol proteins, which are the driving mechanisms of monolignol biosynthesis. Computational models have been developed to estimate protein abundances from transcript perturbations of monolignol specific genes. The accuracy of these models, however, is hindered by the inability to capture indirect regulatory influences on other pathway genes. Here, we examine the manifestation of these indirect influences collectively on transgenic transcript and protein abundances, identifying putative indirect regulatory influences that occur when one or more specific monolignol pathway genes are perturbed. We created a computational model using sparse maximum likelihood to estimate the resulting monolignol transcript and protein abundances in transgenic Populus trichocarpa based on desired single or combinatorial knockdowns of specific monolignol genes. Using in-silico simulations of this model and root mean square error, we show that our model more accurately estimates transcript and protein abundances in differentiating xylem tissue when individual and families of monolignol genes were perturbed. This approach provides a useful computational tool for exploring the cascaded impact of single and combinatorial modifications of monolignol specific genes on lignin and other wood properties. Additionally, these results can be used to guide future experiments to elucidate the mechanisms responsible for the indirect influences.\n\nAuthor summaryEngineering trees to have desirable lignin and wood traits is of significant interest to the bioenergy and biomaterial industries. Genetically modifying the expression of the genes that drive the monolignol biosynthetic pathway is a useful method for obtaining new traits. Modifying the expression of one gene affects not only the abundance of its encoded protein, but can also indirectly impact the amount of other transcripts and proteins. These proteins drive the monolignol biosynthetic pathway. Having an accurate representation of their abundances is key to understanding how lignin and wood traits are altered. We developed a computational model to estimate how the abundance of monolignol transcripts and proteins are changed when one or more monolignol genes are knocked down. Specifying only the abundances of the targeted genes as input, our model estimates how the levels of the other, untargeted, transcripts and proteins are altered. Our model captures indirect regulatory influences at the transcript and protein levels observed in experimental data. The model is an important addition to current models of lignin biosynthesis. By incorporating our approach into the existing models, we expect to improve our ability to explore how new combinations of gene knockdowns impact lignin and many other wood properties.

systems biology↗

bioRxiv2018

Identification of A Disintegrin and Metalloproteinase 9 domain (ADAM9) required in the early stages of encephalomyocarditis virus infection

Encephalomyocarditis virus (EMCV) is a picornavirus that produces lytic infections in murine and human cells. Employing a genome-wide CRISPR-Cas9 knockout screen to find host factors required for EMCV infection, we identified a role for ADAM9 in EMCV infection. CRISPR-mediated deletion of ADAM9 in multiple human cell lines rendered the cells highly resistant to EMCV infection and cell death. Primary fibroblasts from ADAM9 KO mice were also strongly resistant to EMCV infection and cell death. In contrast, ADAM9 KO and WT cells were equally susceptible to infection with other viruses, including the picornavirus Coxsackie virus B. ADAM9 KO cells failed to produce viral progeny when incubated with EMCV. However, bypassing EMCV entry into cells through delivery of viral RNA directly to the cytosol yielded infectious EMCV virions from ADAM9 KO cells, suggesting that ADAM9 is not required for EMCV replication post-entry. These findings establish that ADAM9 is required for the early stage of EMCV infection, likely for virus entry or viral genome delivery to the cytosol.\n\nImportanceViral myocarditis is a leading cause of death in the U.S., contributing to numerous unexplained deaths in people [≤] 35 years old. Enteroviruses contribute to many cases of human myocarditis. Encephalomyocarditis virus (EMCV) infection causes viral myocarditis in rodent models but its receptor requirements have not been fully identified. CRISPR-Cas9 screens can identify host dependency factors essential for EMCV infection and enhance our understanding of key events that follow viral infection, potentially leading to new strategies for preventing viral myocarditis. Using a CRISPR-Cas9 screen, we identified A Disintegrin and Metalloproteinase 9 Domain (ADAM9) as a major factor required for the early stages of EMCV infection in both human and murine infection.

microbiology↗