Dataset Information

Novel applications for a noninvasive sampling method of the nasal mucosa.

ABSTRACT: Reliable methods for sampling the nasal mucosa provide clinical researchers with key information regarding respiratory biomarkers of exposure and disease. For quick and noninvasive sampling of the nasal mucosa, nasal lavage (NL) collection has been widely used as a clinical tool; however, limitations including volume variability, sample dilution, and storage prevent NL collection from being used in nonlaboratory settings and analysis of low abundance biomarkers. In this study, we optimize and validate a novel methodology using absorbent Leukosorb paper cut to fit the nasal passage to extract epithelial lining fluid (ELF) from the nasal mucosa. The ELF sampling method limits the dilution of soluble mediators, allowing quantification of both high- and low-abundance soluble biomarkers such as IL-1β, IL-8, IL-6, interferon gamma-induced protein 10 (IP-10), and neutrophil elastase. Additionally, we demonstrate that this method can successfully detect the presence of respiratory pathogens such as influenza virus and markers of antibiotic-resistant bacteria in the nasal mucosa. Efficacy of ELF collection by this method is not diminished in consecutive-day sampling, and percent recovery of both recombinant IL-8 and soluble mediators are not changed despite freezing or room temperature storage for 24 h. Our results indicate that ELF collection using Leukosorb paper sampling of ELF provides a sensitive, easy-to-use, and reproducible methodology to collect concentrated amounts of soluble biomarkers from the nasal mucosa. Moreover, the methodology described herein improves upon the standard NL collection method and provides researchers with a novel tool to assess changes in nasal mucosal host defense status.

SUBMITTER: Rebuli ME

PROVIDER: S-EPMC5336583 | biostudies-other | 2017 Feb

REPOSITORIES: biostudies-other

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Novel applications for a noninvasive sampling method of the nasal mucosa.

Rebuli Meghan E ME Speen Adam M AM Clapp Phillip W PW Jaspers Ilona I

American journal of physiology. Lung cellular and molecular physiology 20161223 2

Reliable methods for sampling the nasal mucosa provide clinical researchers with key information regarding respiratory biomarkers of exposure and disease. For quick and noninvasive sampling of the nasal mucosa, nasal lavage (NL) collection has been widely used as a clinical tool; however, limitations including volume variability, sample dilution, and storage prevent NL collection from being used in nonlaboratory settings and analysis of low abundance biomarkers. In this study, we optimize and va ...[more]

PMID: 28011618

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Project description:Outbreaks of infectious viruses resulting from spillover events from bats have brought much attention to bat-borne zoonoses, which has motivated increased ecological and epidemiological studies on bat populations. Field sampling methods often collect pooled samples of bat excreta from plastic sheets placed under-roosts. However, positive bias is introduced because multiple individuals may contribute to pooled samples, making studies of viral dynamics difficult. Here, we explore the general issue of bias in spatial sample pooling using Hendra virus in Australian bats as a case study. We assessed the accuracy of different under-roost sampling designs using generalized additive models and field data from individually captured bats and pooled urine samples. We then used theoretical simulation models of bat density and under-roost sampling to understand the mechanistic drivers of bias. The most commonly used sampling design estimated viral prevalence 3.2 times higher than individual-level data, with positive bias 5-7 times higher than other designs due to spatial autocorrelation among sampling sheets and clustering of bats in roosts. Simulation results indicate using a stratified random design to collect 30-40 pooled urine samples from 80 to 100 sheets, each with an area of 0.75-1 m2, and would allow estimation of true prevalence with minimum sampling bias and false negatives. These results show that widely used under-roost sampling techniques are highly sensitive to viral presence, but lack specificity, providing limited information regarding viral dynamics. Improved estimation of true prevalence can be attained with minor changes to existing designs such as reducing sheet size, increasing sheet number, and spreading sheets out within the roost area. Our findings provide insight into how spatial sample pooling is vulnerable to bias for a wide range of systems in disease ecology, where optimal sampling design is influenced by pathogen prevalence, host population density, and patterns of aggregation.

Dataset Information

Novel applications for a noninvasive sampling method of the nasal mucosa.

Publications

Novel applications for a noninvasive sampling method of the nasal mucosa.

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