CRISPR single base-editing: in silico predictions to variant clonal cell lines.

Engineering single base edits using CRISPR technology including specific deaminases and single-guide RNA (sgRNA) is a rapidly evolving field. Different types of base edits can be constructed, with cytidine base editors (CBEs) facilitating transition of C-to-T variants, adenine base editors (ABEs) enabling transition of A-to-G variants, C-to-G transversion base editors (CGBEs) and recently adenine transversion editors (AYBE) that create A-to-C and A-to-T variants. The base-editing machine learning algorithm BE-Hive predicts which sgRNA and base editor combinations have the strongest likelihood of achieving desired base edits. We have used BE-Hive and TP53 mutation data from The Cancer Genome Atlas (TCGA) ovarian cancer cohort to predict which mutations can be engineered, or reverted to wild-type (WT) sequence, using CBEs, ABEs or CGBEs. We have developed and automated a ranking system to assist in selecting optimally designed sgRNA that considers the presence of a suitable protospacer adjacent motif (PAM), the frequency of predicted bystander edits, editing efficiency and target base change. We have generated single constructs containing ABE or CBE editing machinery, an sgRNA cloning backbone and an enhanced green fluorescent protein tag (EGFP), removing the need for co-transfection of multiple plasmids. We have tested our ranking system and new plasmid constructs to engineer the p53 mutants Y220C, R282W and R248Q into WT p53 cells and shown that these mutants cannot activate four p53 target genes, mimicking the behaviour of endogenous p53 mutations. This field will continue to rapidly progress, requiring new strategies such as we propose to ensure desired base-editing outcomes.

Smoking induces shifts in cellular composition and transcriptome within the bronchial mucus barrier.

BACKGROUND AND OBJECTIVE: Smoking disturbs the bronchial-mucus-barrier. This study assesses the cellular composition and gene expression shifts of the bronchial-mucus-barrier with smoking to understand the mechanism of mucosal damage by cigarette smoke exposure. We explore whether single-cell-RNA-sequencing (scRNA-seq) based cellular deconvolution (CD) can predict cell-type composition in RNA-seq data. METHODS: RNA-seq data of bronchial biopsies from three cohorts were analysed using CD. The cohorts included 56 participants with chronic obstructive pulmonary disease [COPD] (38 smokers; 18 ex-smokers), 77 participants without COPD (40 never-smokers; 37 smokers) and 16 participants who stopped smoking for 1 year (11 COPD and 5 non-COPD-smokers). Differential gene expression was used to investigate gene expression shifts. The CD-derived goblet cell ratios were validated by correlating with staining-derived goblet cell ratios from the COPD cohort. Statistics were done in the R software (false discovery rate p-value < 0.05). RESULTS: Both CD methods indicate a shift in bronchial-mucus-barrier cell composition towards goblet cells in COPD and non-COPD-smokers compared to ex- and never-smokers. It shows that the effect was reversible within a year of smoking cessation. A reduction of ciliated and basal cells was observed with current smoking, which resolved following smoking cessation. The expression of mucin and sodium channel (ENaC) genes, but not chloride channel genes, were altered in COPD and current smokers compared to never smokers or ex-smokers. The goblet cell-derived staining scores correlate with CD-derived goblet cell ratios. CONCLUSION: Smoking alters bronchial-mucus-barrier cell composition, transcriptome and increases mucus production. This effect is partly reversible within a year of smoking cessation. CD methodology can predict goblet-cell percentages from RNA-seq.

Early transcriptional responses of bronchial epithelial cells to whole cigarette smoke mirror those of in-vivo exposed human bronchial mucosa.

BACKGROUND: Despite the well-known detrimental effects of cigarette smoke (CS), little is known about the complex gene expression dynamics in the early stages after exposure. This study aims to investigate early transcriptomic responses following CS exposure of airway epithelial cells in culture and compare these to those found in human CS exposure studies. METHODS: Primary bronchial epithelial cells (PBEC) were differentiated at the air-liquid interface (ALI) and exposed to whole CS. Bulk RNA-sequencing was performed at 1 h, 4 h, and 24 h hereafter, followed by differential gene expression analysis. Results were additionally compared to data retrieved from human CS studies. RESULTS: ALI-PBEC gene expression in response to CS was most significantly changed at 4 h after exposure. Early transcriptomic changes (1 h, 4 h post CS exposure) were related to oxidative stress, xenobiotic metabolism, higher expression of immediate early genes and pro-inflammatory pathways (i.e., Nrf2, AP-1, AhR). At 24 h, ferroptosis-associated genes were significantly increased, whereas PRKN, involved in removing dysfunctional mitochondria, was downregulated. Importantly, the transcriptome dynamics of the current study mirrored in-vivo human studies of acute CS exposure, chronic smokers, and inversely mirrored smoking cessation. CONCLUSION: These findings show that early after CS exposure xenobiotic metabolism and pro-inflammatory pathways were activated, followed by activation of the ferroptosis-related cell death pathway. Moreover, significant overlap between these transcriptomic responses in the in-vitro model and human in-vivo studies was found, with an early response of ciliated cells. These results provide validation for the use of ALI-PBEC cultures to study the human lung epithelial response to inhaled toxicants.

Single-nucleotide polymorphism rs2070600 regulates AGER splicing and the sputum levels of the COPD biomarker soluble receptor for advanced glycation end-products.

The COPD susceptibility SNP rs2070600 affects the levels of the COPD biomarker sRAGE in sputum as well as splicing of AGER. Moreover, @PouwelsScience et al. demonstrate large differences in sRAGE levels between serum and sputum. https://bit.ly/3t0pJtK.

Current Smoking Alters Gene Expression and DNA Methylation in the Nasal Epithelium of Patients with Asthma.

Current smoking contributes to worsened asthma prognosis and more severe symptoms and limits the beneficial effects of corticosteroids. As the nasal epithelium can reflect smoking-induced changes in the lower airways, it is a relevant source to investigate changes in gene expression and DNA methylation. This study explores gene expression and DNA methylation changes in current and ex-smokers with asthma. Matched gene expression and epigenome-wide DNA methylation samples collected from nasal brushings of 55 patients enrolled in a clinical trial investigation of current and ex-smoker patients with asthma were analyzed. Differential gene expression and DNA methylation analyses were conducted comparing current smokers with ex-smokers. Expression quantitative trait methylation (eQTM) analysis was completed to explore smoking-relevant genes by CpG sites that differ between current and ex-smokers. To investigate the relevance of the smoking-associated DNA methylation changes for the lower airways, significant CpG sites were explored in bronchial biopsies from patients who had stopped smoking. A total of 809 genes and 18,814 CpG sites were differentially associated with current smoking in the nose. The cis-eQTM analysis uncovered 171 CpG sites with a methylation status associated with smoking-related gene expression, including AHRR, ALDH3A1, CYP1A1, and CYP1B1. The methylation status of CpG sites altered by current smoking reversed with 1 year of smoking cessation. We confirm that current smoking alters epigenetic patterns and affects gene expression in the nasal epithelium of patients with asthma, which is partially reversible in bronchial biopsies after smoking cessation. We demonstrate the ability to discern molecular changes in the nasal epithelium, presenting this as a tool in future investigations into disease-relevant effects of tobacco smoke.

RAGE and TLR4 differentially regulate airway hyperresponsiveness: Implications for COPD.

BACKGROUND: The receptor for advanced glycation end products (RAGE) and Toll-like receptor 4 (TLR4) is implicated in COPD. Although these receptors share common ligands and signalling pathways, it is not known whether they act in concert to drive pathological processes in COPD. We examined the impact of RAGE and/or TLR4 gene deficiency in a mouse model of COPD and also determined whether expression of these receptors correlates with airway neutrophilia and airway hyperresponsiveness (AHR) in COPD patients. METHODS: We measured airway inflammation and AHR in wild-type, RAGE-/- , TLR4-/- and TLR4-/- RAGE-/- mice following acute exposure to cigarette smoke (CS). We also examined the impact of smoking status on AGER (encodes RAGE) and TLR4 bronchial gene expression in patients with and without COPD. Finally, we determined whether expression of these receptors correlates with airway neutrophilia and AHR in COPD patients. RESULTS: RAGE-/- mice were protected against CS-induced neutrophilia and AHR. In contrast, TLR4-/- mice were not protected against CS-induced neutrophilia and had more severe CS-induced AHR. TLR4-/- RAGE-/- mice were not protected against CS-induced neutrophilia but were partially protected against CS-induced mediator release and AHR. Current smoking was associated with significantly lower AGER and TLR4 expression irrespective of COPD status, possibly reflecting negative feedback regulation. However, consistent with preclinical findings, AGER expression correlated with higher sputum neutrophil counts and more severe AHR in COPD patients. TLR4 expression did not correlate with neutrophilic inflammation or AHR. CONCLUSIONS: Inhibition of RAGE but not TLR4 signalling may protect against airway neutrophilia and AHR in COPD.

Gene expression profiling of bronchial brushes is associated with the level of emphysema measured by computed tomography-based parametric response mapping.

Parametric response mapping (PRM) is a computed tomography (CT)-based method to phenotype patients with chronic obstructive pulmonary disease (COPD). It is capable of differentiating emphysema-related air trapping with nonemphysematous air trapping (small airway disease), which helps to identify the extent and localization of the disease. Most studies evaluating the gene expression in smokers and COPD patients related this to spirometric measurements, but none have investigated the relationship with CT-based measurements of lung structure. The current study aimed to examine gene expression profiles of brushed bronchial epithelial cells in association with the PRM-defined CT-based measurements of emphysema (PRMEmph) and small airway disease (PRMfSAD). Using the Top Institute Pharma (TIP) study cohort (COPD = 12 and asymptomatic smokers = 32), we identified a gene expression signature of bronchial brushings, which was associated with PRMEmph in the lungs. One hundred thirty-three genes were identified to be associated with PRMEmph. Among the most significantly associated genes, CXCL11 is a potent chemokine involved with CD8+ T cell activation during inflammation in COPD, indicating that it may play an essential role in the development of emphysema. The PRMEmph signature was then replicated in two independent data sets. Pathway analysis showed that the PRMEmph signature is associated with proinflammatory and notch signaling pathways. Together these findings indicate that airway epithelium may play a role in the development of emphysema and/or may act as a biomarker for the presence of emphysema. In contrast, its role in relation to functional small airways disease is less clear.

Genetic profiling for disease stratification in chronic obstructive pulmonary disease and asthma.

PURPOSE OF REVIEW: In asthma and chronic obstructive pulmonary disease (COPD), the movement towards genetic profiling with a push towards 'personalized medicine' has been hindered by complex environment--gene interactions and lack of tools to identify clear causal genetic traits. In this review, we will discuss the need for genetic profiling in asthma and COPD, what methods are currently used in the clinics and the recent finding using new sequencing methods. RECENT FINDINGS: Over the past 10-15 years, genome-wide association studies analysis of common variants has provide little in the way of new genetic profiling markers for asthma and COPD. Whole exome/genome sequencing has provided a new method to identify lowly abundant alleles, which might have a much higher impact. Although, low population numbers due to high costs has hindered early studies, recent studies have reached genome wide significance. SUMMARY: The use of genetic profiling of COPD in the clinic is current limited to the identification of Alpha-1 antitrypsin deficiency, while being absent in asthma. Advances in sequencing technology provide new avenues to identify disease causes or therapy response altering variants that in the short-term will allow for the development of screening procedures for disease to identify patients at risk of developing asthma or COPD.