Paper spray mass spectrometry for high-throughput quantification of nicotine and cotinine

The rapid release of new tobacco products requires high-throughput quantitative methods to support tobacco research. Sample preparation for LC-MS and GC-MS is time consuming and limits throughput. Paper spray tandem mass spectrometry (PS-MS/MS) is proposed and validated as a simple and rapid method for quantification of nicotine and cotinine in complex matrices to support tobacco-related research. Air liquid interface (ALI) human tracheobronchial epithelial cell (HTBEC) cultures were exposed to tobacco smoke using a Vitrocell VC-10 smoking machine. Apical culture washes (phosphate buffered saline, PBS) and basolateral media were analyzed with the PS-MS/MS method. GC-MS/MS was used as a comparative quantitative technique. The PS-MS/MS approach allowed for direct spotting of samples on the paper substrate, whereas the GC-MS/MS method required additional sample preparation in the form of solvent-solvent extraction. Limits of quantitation (LOQs) were higher with the PS-MS/MS approach than GC-MS/MS, but still below the relevant concentrations found in HTBEC smoke exposure experiments as well as most clinical applications. PS-MS/MS is readily achieved on mass spectrometers that include atmospheric pressure inlets, and allows for convenient quantification from complex matrices that would otherwise require additional sample preparation and chromatographic separation. © 2017 The Royal Society of Chemistry

Intercellular communication between airway epithelial cells is mediated by exosome-like vesicles

Airway epithelium structure/function can be altered by local inflammatory/immune signals, and this process is called epithelial remodeling. The mechanism by which this innate response is regulated, which causes mucin/mucus overproduction, is largely unknown. Exosomes are nanovesicles that can be secreted and internalized by cells to transport cellular cargo, such as proteins, lipids, and miRNA. The objective of this study was to understand the role exosomes play in airway remodeling through cell–cell communication. We used two different human airway cell cultures: primary human tracheobronchial (HTBE) cells, and a cultured airway epithelial cell line (Calu-3). After intercellular exosomal transfer, comprehensive proteomic and genomic characterization of cell secretions and exosomes was performed. Quantitative proteomics and exosomal miRNA analysis profiles indicated that the two cell types are fundamentally distinct. HTBE cell secretions were typically dominated by fundamental innate/protective proteins, including mucin MUC5B, and Calu-3 cell secretions were dominated by pathology-associated proteins, including mucin MUC5AC. After exosomal transfer/intake, approximately 20% of proteins, including MUC5AC and MUC5B, were significantly altered in HTBE secretions. After exosome transfer, approximately 90 miRNAs (z4%) were upregulated in HTBE exosomes, whereas Calu-3 exosomes exhibited a preserved miRNA profile. Together, our data suggest that the transfer of exosomal cargo between airway epithelial cells significantly alters the qualitative and quantitative profiles of airway secretions, including mucin hypersecretion, and the miRNA cargo of exosomes in target cells. This finding indicates that cellular information can be carried between airway epithelial cells via exosomes, which may play an important role in airway biology and epithelial remodeling

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease