Comparison of permeable cell culture inserts for use in culture of a human in vitro air-liquid interface model system.

In this study, we compared 12 mm cell culture inserts with permeable polyester membranes (0.4 µm pores) from two different manufacturers: CELLTREAT® and Corning®. Physical dimensions and masses of the inserts were found to be very similar between the two brands, with CELLTREAT® inserts having a slightly smaller diameter and growth area (11.91 mm; 1.11 cm2 ) compared to Corning® Transwells® (12 mm; 1.13 cm2 ). We compared cell differentiation outcomes of human nasal epithelial cells (HNECs) at air-liquid interface grown on inserts from the two different manufacturers, including trans-epithelial electrical resistance, ciliary beat frequency, ciliated area, and gene expression. HNECs from three male donors were used for all endpoints. No statistically significant differences were observed between paired cultures grown on different brands of insert. In conclusion, these inserts are comparable for use with airway epithelial cell model systems and likely do not impact cellular differentiation or cell culture quality.

Woodsmoke particle exposure prior to SARS-CoV-2 infection alters antiviral response gene expression in human nasal epithelial cells in a sex-dependent manner.

Inhalational exposure to particulate matter (PM) derived from natural or anthropogenic sources alters gene expression in the airways and increases susceptibility to respiratory viral infection. Woodsmoke-derived ambient PM from wildfire events during 2020 was associated with higher COVID-19 case rates in the western United States. We hypothesized that exposure to suspensions of woodsmoke particles (WSPs) or diesel exhaust particles (DEPs) prior to SARS-CoV-2 infection would alter host immune gene expression at the transcript level. Primary human nasal epithelial cells (hNECs) from both sexes were exposed to WSPs or DEPs (22 µg/cm2) for 2 h, followed by infection with SARS-CoV-2 at a multiplicity of infection of 0.5. Forty-six genes related to SARS-CoV-2 entry and host response were assessed. Particle exposure alone minimally affected gene expression, whereas SARS-CoV-2 infection alone induced a robust transcriptional response in hNECs, upregulating type I and III interferons, interferon-stimulated genes, and chemokines by 72 h postinfection (p.i.). This upregulation was higher overall in cells from male donors. However, exposure to WSPs prior to infection dampened expression of antiviral, interferon, and chemokine mRNAs. Sex stratification of these results revealed that WSP exposure downregulated gene expression in cells from females more so than males. We next hypothesized that hNECs exposed to particles would have increased apical viral loads compared with unexposed cells. Although apical viral load was correlated to expression of host response genes, viral titer did not differ between groups. These data indicate that WSPs alter epithelial immune responses in a sex-dependent manner, potentially suppressing host defense to SARS-CoV-2 infection.

Woodsmoke particulates alter expression of antiviral host response genes in human nasal epithelial cells infected with SARS-CoV-2 in a sex-dependent manner.

We have previously shown that exposure to particulate air pollution, both from natural and anthropogenic sources, alters gene expression in the airways and increases susceptibility to respiratory viral infection. Additionally, we have shown that woodsmoke particulates (WSP) affect responses to influenza in a sex-dependent manner. In the present study, we used human nasal epithelial cells (hNECs) from both sexes to investigate how particulate exposure could modulate gene expression in the context of SARS-CoV-2 infection. We used diesel exhaust particulate (DEP) as well as WSP derived from eucalyptus or red oak wood. HNECs were exposed to particulates at a concentration of 22 µg/cm 2 for 2 h then immediately infected with SARS-CoV-2 at a MOI (multiplicity of infection) of 0.5. Exposure to particulates had no significant effects on viral load recovered from infected cells. Without particulate exposure, hNECs from both sexes displayed a robust upregulation of antiviral host response genes, though the response was greater in males. However, WSP exposure before infection dampened expression of genes related to the antiviral host response by 72 h post infection. Specifically, red oak WSP downregulated IFIT1, IFITM3, IFNB1, MX1, CCL3, CCL5, CXCL11, CXCL10 , and DDX58 , among others. After sex stratification of these results, we found that exposure to WSP prior to SARS-CoV-2 infection downregulated anti-viral gene expression in hNECs from females more so than males. These data indicate that WSP, specifically from red oak, alter virus-induced gene expression in a sex-dependent manner and potentially suppress antiviral host defense responses following SARS-CoV-2 infection.

Impact of inhaled pollutants on response to viral infection in controlled exposures.

Air pollutants are a major source of increased risk of disease, hospitalization, morbidity, and mortality worldwide. The respiratory tract is a primary target of potential concurrent exposure to both inhaled pollutants and pathogens, including viruses. Although there are various associative studies linking adverse outcomes to co- or subsequent exposures to inhaled pollutants and viruses, knowledge about causal linkages and mechanisms by which pollutant exposure may alter human respiratory responses to viral infection is more limited. In this article, we review what is known about the impact of pollutant exposure on antiviral host defense responses and describe potential mechanisms by which pollutants can alter the viral infection cycle. This review focuses on evidence from human observational and controlled exposure, ex vivo, and in vitro studies. Overall, there are a myriad of points throughout the viral infection cycle that inhaled pollutants can alter to modulate appropriate host defense responses. These alterations may contribute to observed increases in rates of viral infection and associated morbidity and mortality in areas of the world with high ambient pollution levels or in people using tobacco products. Although the understanding of mechanisms of interaction is advancing through controlled in vivo and in vitro exposure models, more studies are needed because emerging infectious pathogens, such as severe acute respiratory syndrome coronavirus 2, present a significant threat to public health.

Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning.

Lipid membrane permeation of drug molecules was investigated with Heterogeneous Dielectric Generalized Born (HDGB)-based models using solubility-diffusion theory and machine learning. Free energy profiles were obtained for neutral molecules by the standard HDGB and Dynamic HDGB (DHDGB) to account for the membrane deformation upon insertion of drugs. We also obtained hybrid free energy profiles where the neutralization of charged molecules was taken into account upon membrane insertion. The evaluation of the predictions was done against experimental permeability coefficients from Parallel Artificial Membrane Permeability Assays (PAMPA), and effects of partial charge sets, CGenFF, AM1-BCC, and OPLS, on the performance of the predictions were discussed. (D)HDGB-based models improved the predictions over the two-state implicit membrane models, and partial charge sets seemed to have a strong impact on the predictions. Machine learning increased the accuracy of the predictions, although it could not outperform the physics-based approach in terms of correlations.