Protein profile of well-differentiated versus un-differentiated human bronchial/tracheal epithelial cells

Severe pneumonia and pathogenic damage in human airway epithelium caused by Coxsackievirus B4

Coxsackievirus B4 (CVB4) has one of the highest proportions of fatal outcomes of other enterovirus serotypes. However, the pathogenesis of severe respiratory disease caused by CVB4 infection remains unclear. In this study, 3 of 42 (7.2%, GZ-R6, GZ-R7 and GZ-R8) patients with severe pneumonia tested positive for CVB4 infection in southern China. Three full-length genomes of pneumonia-derived CVB4 were sequenced and annotated for the first time, showing their high nucleotide similarity and clustering within genotype V. To analyze the pathogenic damage caused by CVB4 in the lungs, a well-differentiated human airway epithelium (HAE) was established and infected with the pneumonia-derived CVB4 isolate GZ-R6. The outcome was compared with that of a severe hand-foot-mouth disease (HFMD)-derived CVB4 strain GZ-HFM01. Compared with HFMD-derived CVB4, pneumonia-derived CVB4 caused more intense and rapid disruption of HAE polarity, leading to tight-junction barrier disruption, loss of cilia, and airway epithelial cell hypertrophy. More pneumonia-derived CVB4 were released from the basolateral side of the HAE than HFMD-derived CVB4. Of the 18 cytokines tested, only IL-6 and IL-1b secretion significantly increased on bilateral sides of HAE during the early stage of pneumonia-derived CVB4 infection, while multiple cytokine secretions significantly increased in HFMD-derived CVB4-infected HAE. HFMD-derived CVB4 exhibited stronger neurovirulence in the human neuroblastoma cells SH-SY5Y than pneumonia-derived CVB4, which is consistent with the clinical manifestations of patients infected with these two viruses. This study has increased the depth of our knowledge of severe pneumonia infection caused by CVB4 and will benefit its prevention and treatment.

Development of a novel air-liquid interface airway tissue equivalent model for in vitro respiratory modeling studies

The human airways are complex structures with important interactions between cells, extracellular matrix (ECM) proteins and the biomechanical microenvironment. A robust, well-differentiated in vitro culture system that accurately models these interactions would provide a useful tool for studying normal and pathological airway biology. Here, we report the development and characterization of a physiologically relevant air-liquid interface (ALI) 3D airway 'organ tissue equivalent' (OTE) model with three novel features: native pulmonary fibroblasts, solubilized lung ECM, and hydrogel substrate with tunable stiffness and porosity. We demonstrate the versatility of the OTE model by evaluating the impact of these features on human bronchial epithelial (HBE) cell phenotype. Variations of this model were analyzed during 28 days of ALI culture by evaluating epithelial confluence, trans-epithelial electrical resistance, and epithelial phenotype via multispectral immuno-histochemistry and next-generation sequencing. Cultures that included both solubilized lung ECM and native pulmonary fibroblasts within the hydrogel substrate formed well-differentiated ALI cultures that maintained a barrier function and expressed mature epithelial markers relating to goblet, club, and ciliated cells. Modulation of hydrogel stiffness did not negatively impact HBE differentiation and could be a valuable variable to alter epithelial phenotype. This study highlights the feasibility and versatility of a 3D airway OTE model to model the multiple components of the human airway 3D microenvironment.

In vitro differentiation of ciliated cells in ALI-cultured human airway epithelium - The framework for functional studies on airway differentiation in ciliopathies

Primary cultures of the human airway epithelium (AE) cells are an indispensable tool in studies of pathophysiology of genetic and environmental pulmonary diseases, including cystic fibrosis (CF), primary ciliary dyskinesia (PCD) and chronic obstructive pulmonary disease (COPD). Air-liquid interface (ALI) culture is the best method to follow the differentiation of ciliated cells, whose dysfunction forms the basis of PCD. Here, we used custom-designed Taqman Low Density Array (TLDA), qRT-PCR-based assay, to analyze expression of 14 AE genes in cells from healthy donors, cultured in ALI settings using Pneumacult medium, with the focus on genes involved in cilia differentiation and in PCD pathogenesis. The results of TLDA assay were compared with the bulk RNAseq analysis, and placed in the cellular context using immunofluorescent staining (IF) of ALI cultured cells. Expression analysis revealed culture time-related upregulation of the majority of cilia-related genes, followed by the appearance of respective protein signals visualized by IF. Strong correlation of TLDA with RNAseq results indicated that TLDA assay is a reliable and scalable approach to analyze expression of selected genes specific for different AE cell types. Characterization of temporal and inter-donor changes in the expression of these genes, performed in healthy donors and in well-defined ALI/Pnemacult culture conditions, provides a useful reference relevant for a broad spectrum of functional studies where the in vitro AE differentiation is in focus.

A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19)

BACKGROUND

The Coronavirus Disease 2019 (COVID-19) global pandemic has had a profound, lasting impact on the world's population. A key aspect to providing care for those with COVID-19 and checking its further spread is early and accurate diagnosis of infection, which has been generally done via methods for amplifying and detecting viral RNA molecules. Detection and quantitation of peptides using targeted mass spectrometry-based strategies has been proposed as an alternative diagnostic tool due to direct detection of molecular indicators from non-invasively collected samples as well as the potential for high-throughput analysis in a clinical setting; many studies have revealed the presence of viral peptides within easily accessed patient samples. However, evidence suggests that some viral peptides could serve as better indicators of COVID-19 infection status than others, due to potential misidentification of peptides derived from human host proteins, poor spectral quality, high limits of detection etc. METHODS: In this study we have compiled a list of 636 peptides identified from Sudden Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples, including from in vitro and clinical sources. These datasets were rigorously analyzed using automated, Galaxy-based workflows containing tools such as PepQuery, BLAST-P, and the Multi-omic Visualization Platform as well as the open-source tools MetaTryp and Proteomics Data Viewer (PDV).

RESULTS

Using PepQuery for confirming peptide spectrum matches, we were able to narrow down the 639-peptide possibilities to 87 peptides that were most robustly detected and specific to the SARS-CoV-2 virus. The specificity of these sequences to coronavirus taxa was confirmed using Unipept and BLAST-P. Through stringent p-value cutoff combined with manual verification of peptide spectrum match quality, 4 peptides derived from the nucleocapsid phosphoprotein and membrane protein were found to be most robustly detected across all cell culture and clinical samples, including those collected non-invasively.

CONCLUSION

We propose that these peptides would be of the most value for clinical proteomics applications seeking to detect COVID-19 from patient samples. We also contend that samples harvested from the upper respiratory tract and oral cavity have the highest potential for diagnosis of SARS-CoV-2 infection from easily collected patient samples using mass spectrometry-based proteomics assays.

A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19)

The Coronavirus Disease 2019 (COVID-19) global pandemic has had a profound, lasting impact on the world's population. A key aspect to providing care for those with COVID-19 and checking its further spread is early and accurate diagnosis of infection, which has been generally done via methods for amplifying and detecting viral RNA molecules. Detection and quantitation of peptides using targeted mass spectrometry-based strategies has been proposed as an alternative diagnostic tool due to direct detection of molecular indicators from non-invasively collected samples as well as the potential for high-throughput analysis in a clinical setting; many studies have revealed the presence of viral peptides within easily accessed patient samples. However, evidence suggests that some viral peptides could serve as better indicators of COVID-19 infection status than others, due to potential misidentification of peptides derived from human host proteins, poor spectral quality, high limits of detection etc. In this study we have compiled a list of 639 peptides identified from Sudden Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples, including from in vitro and clinical sources. These datasets were rigorously analyzed using automated, Galaxy-based workflows containing tools such as PepQuery, BLAST-P, and the Multi-omic Visualization Platform as well as the open-source tools MetaTryp and Proteomics Data Viewer (PDV). Using PepQuery for confirming peptide spectrum matches, we were able to narrow down the 639 peptide possibilities to 87 peptides which were most robustly detected and specific to the SARS-CoV-2 virus. The specificity of these sequences to coronavirus taxa was confirmed using Unipept and BLAST-P. Applying stringent statistical scoring thresholds, combined with manual verification of peptide spectrum match quality, 4 peptides derived from the nucleocapsid phosphoprotein and membrane protein were found to be most robustly detected across all cell culture and clinical samples, including those collected non-invasively. We propose that these peptides would be of the most value for clinical proteomics applications seeking to detect COVID-19 from a variety of sample types. We also contend that samples taken from the upper respiratory tract and oral cavity have the highest potential for diagnosis of SARS-CoV-2 infection from easily collected patient samples using mass spectrometry-based proteomics assays.