Aptamer Profiling of A549 Cells Infected with Low-Pathogenicity and High-Pathogenicity Influenza Viruses

Combination of IL-17A/F and TNF-α uniquely alters the bronchial epithelial cell proteome to enhance proteins that augment neutrophil migration

Background

The heterodimer interleukin (IL)-17A/F is elevated in the lungs in chronic respiratory disease such as severe asthma, along with the pro-inflammatory cytokine tumor necrosis factor-α (TNF-α). Although IL-17A/F and TNF-α are known to functionally cooperate to exacerbate airway inflammation, proteins altered by their interaction in the lungs are not fully elucidated.

Results

We used Slow Off-rate Modified Aptamer-based proteomic array to identify proteins that are uniquely and/or synergistically enhanced by concurrent stimulation with IL-17A/F and TNF-α in human bronchial epithelial cells (HBEC). The abundance of 38 proteins was significantly enhanced by the combination of IL-17A/F and TNF-α, compared to either cytokine alone. Four out of seven proteins that were increased > 2-fold were those that promote neutrophil migration; host defence peptides (HDP; Lipocalin-2 (LCN-2) and Elafin) and chemokines (IL-8, GROα). We independently confirmed the synergistic increase of these four proteins by western blots and ELISA. We also functionally confirmed that factors secreted by HBEC stimulated with the combination of IL-17A/F and TNF-α uniquely enhances neutrophil migration. We further showed that PI3K and PKC pathways selectively control IL-17A/F + TNF-α-mediated synergistic production of HDPs LCN-2 and Elafin, but not chemokines IL-8 and GROα. Using a murine model of airway inflammation, we demonstrated enhancement of IL-17A/F, TNF-α, LCN-2 and neutrophil chemokine KC in the lungs, thus corroborating our findings in-vivo.

Conclusion

This study identifies proteins and signaling mediated by concurrent IL-17A/F and TNF-α exposure in the lungs, relevant to respiratory diseases characterized by chronic inflammation, especially neutrophilic airway inflammation such as severe asthma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12950-022-00323-w.

Defining the effects of traffic-related air pollution on the human plasma proteome using an aptamer proteomic array: A dose-dependent increase in atherosclerosis-related proteins

BACKGROUND

Traffic-related air pollution (TRAP) is a critical risk factor and major contributor to respiratory and cardiovascular disease (CVD). The effects of TRAP beyond the lungs can be related to changes in circulatory proteins. However, such TRAP-mediated changes have not been defined in an unbiased manner using a controlled human model.

OBJECTIVE

To detail global protein changes (the proteome) in plasma following exposure to inhaled diesel exhaust (DE), a paradigm of TRAP, using controlled human exposures.

METHODS

In one protocol, ex-smokers and never-smokers were exposed to filtered air (FA) and DE (300 μg PM_2.5/m³), on order-randomized days, for 2 h. In a second protocol, independent never-smoking participants were exposed to lower concentrations of DE (20, 50 or 150 μg PM_2.5/m³) and FA, for 4 h, on order-randomized days. Each exposure was separated by 4 weeks of washout. Plasma samples obtained 24 h post-exposure from ex-smokers (n = 6) were first probed using Slow off-rate modified aptamer proteomic array. Plasma from never-smokers (n = 11) was used for independent assessment of proteins selected from the proteomics study by immunoblotting.

RESULTS

Proteomics analyses revealed that DE significantly altered 342 proteins in plasma of ex-smokers (n = 6). The top 20 proteins therein were primarily associated with inflammation and CVD. Plasma from never-smokers (n = 11) was used for independent assessment of 6 proteins, amongst the top 10 proteins increased by DE in the proteomics study, for immunoblotting. The abundance of all six proteins (fractalkine, apolipoproteins (APOB and APOM), IL18R1, MIP-3 and MMP-12) was significantly increased by DE in plasma of these never-smokers. DE-mediated increase was shown to be concentration-dependent for fractalkine, APOB and MMP-12, all biomarkers of atherosclerosis, which correlated with plasma levels of IL-6, a subclinical marker of CVD, in independent participants.

CONCLUSION

This investigation details changes in the human plasma proteome due to TRAP. We identify specific atherosclerosis-related proteins that increase concentration-dependently across a range of TRAP levels applicable worldwide.

Evaluation of the Sensitivity of Proteomics Methods Using the Absolute Copy Number of Proteins in a Single Cell as a Metric

Proteomic technology has improved at a staggering pace in recent years, with even practitioners challenged to keep up with new methods and hardware. The most common metric used for method performance is the number of peptides and proteins identified. While this metric may be helpful for proteomics researchers shopping for new hardware, this is often not the most biologically relevant metric. Biologists often utilize proteomics in the search for protein regulators that are of a lower relative copy number in the cell. In this review, I re-evaluate untargeted proteomics data using a simple graphical representation of the absolute copy number of proteins present in a single cancer cell as a metric. By comparing single-shot proteomics data to the coverage of the most in-depth proteomic analysis of that cell line acquired to date, we can obtain a rapid metric of method performance. Using a simple copy number metric allows visualization of how proteomics has developed in both sensitivity and overall dynamic range when using both relatively long and short acquisition times. To enable reanalysis beyond what is presented here, two available web applications have been developed for single- and multi-experiment comparisons with reference protein copy number data for multiple cell lines and organisms.

TMBIM6, a potential virus target protein identified by integrated multiomics data analysis in SARS-CoV-2-infected host cells

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we collected open access data to analyze the mechanisms associated with SARS-CoV-2 infection. Gene set enrichment analysis (GSEA) revealed that apoptosis-related pathways were enriched in the cells after SARS-CoV-2 infection, and the results of differential expression analysis showed that biological functions related to endoplasmic reticulum stress (ERS) and lipid metabolism were disordered. TMBIM6 was identified as a potential target for SARS-CoV-2 in host cells through weighted gene coexpression network analysis (WGCNA) of the time course of expression of host and viral proteins. The expression and related functions of TMBIM6 were subsequently analyzed to illuminate how viral proteins interfere with the physiological function of host cells. The potential function of viral proteins was further analyzed by GEne Network Inference with Ensemble of trees (GENIE3). This study identified TMBIM6 as a target protein associated with the pathogenesis of SARS-CoV-2, which might provide a novel therapeutic approach for COVID-19 in the future.

Update on Proteomic approaches to uncovering virus-induced protein alterations and virus -host protein interactions during the progression of viral infection

INTRODUCTION

Viruses induce profound changes in the cells they infect. Understanding these perturbations will assist in designing better therapeutics to combat viral infection. System-based proteomic assays now provide unprecedented opportunity to monitor large numbers of cellular proteins.

AREAS COVERED

This review will describe various quantitative and functional mass spectrometry-based methods, and complementary non-mass spectrometry-based methods, such as aptamer profiling and proximity extension assays, and examples of how each are used to delineate how viruses affect host cells, identify which viral proteins interact with which cellular proteins, and how these change during the course of a viral infection. PubMed was searched multiple times prior to manuscript submissions and revisions, using virus, viral, proteomics; in combination with each keyword. The most recent examples of published works from each search were then analyzed.

EXPERT OPINION

There has been exponential growth in numbers and types of proteomic analyses in recent years. Continued development of reagents that allow increased multiplexing and deeper proteomic probing of the cell, at quantitative and functional levels, enhancements that target more important protein modifications, and improved bioinformatics software tools and pathway prediction algorithms will accelerate this growth and usher in a new era of host proteome understanding.