Search bioRxiv⌕ Search

Biology subjects

Comte, J.

Publications and source records attributed to Comte, J..

3 recordsLinked to original sources

Novel DNA methylation changes in mouse lungs associated with heavy smoking

Smoking is a potent cause of asthma, chronic obstructive pulmonary disease (COPD) and many other health defects, and changes in DNA methylation (DNAm) have been identified as a potential link between smoking and these health outcomes. However, most links between smoking and DNAm have been made using blood and other easily accessible tissues in humans, while evidence from more directly affected tissues such as the lungs is greatly lacking. Here, we identified DNAm patterns which are altered by smoking directly in the lungs. We used a well-established mouse model to measure the effects of heavy smoking first on lung phenotype immediately after smoking and then after a period of smoking cessation. Next, we determined whether our mouse model could recapitulate previous DNAm patterns observed in smoking humans by measuring DNAm at a candidate gene responsive to cigarette smoke (CS), Cyp1a1. Finally we carried out epigenome-wide DNAm analyses using the newly released Illumina mouse methylation microarrays. Our results recapitulate some of the phenotypes and DNAm patterns observed in human studies but reveal 32 differentially methylated genes specific to the lungs which have not been previously associated with smoking. The affected genes are known to be involved in nicotine dependency, tumorigenesis and metastasis, immune cell dysfunction, lung function decline, and COPD. This research emphasizes the need to study CS-mediated DNAm signatures in directly affected tissues like the lungs, as that may be essential in understanding mechanisms underlying CS-mediated health outcomes.

molecular biology↗

Early life exposure to cigarette smoke is associated with lung function changes and primes gene expression and DNA methylation changes at Cyp1a1 upon exposure later in life

Prenatal and early life exposure to cigarette smoke (CS) have repeatedly been shown to induce stable, long-term changes in DNA methylation (DNAm) in offspring. It has been hypothesized that these changes might be functionally related to the known outcomes of prenatal and early life CS exposure, which include impaired lung development, altered lung function and increased risk of asthma and wheeze. However, to date, few studies have examined DNAm changes induced by prenatal CS in tissues of the lung, and even fewer have attempted to examine the specific influences of prenatal versus early postnatal exposures. Here, we have established a mouse model of CS exposure which isolates the effects of prenatal and early postnatal CS exposures in early life. We have used this model to measure the effects of prenatal and/or postnatal CS exposures on lung function and immune cell infiltration as well as DNAm and expression of Cyp1a1, a candidate gene previously observed to demonstrate DNAm differences upon CS exposure in humans. Our study revealed that exposure to CS prenatally and in the early postnatal period cause long-lasting differences in offspring lung function, gene expression and lung Cyp1a1 DNAm, which wane over time but are reestablished upon re-exposure to CS in adulthood. This study creates a testable mouse model which can be used to investigate the effects of prenatal and early postnatal CS exposures and will contribute to the design of intervention strategies to mediate these detrimental effects.

genetics↗

Rapid assessment of phytoplankton assemblages using Next Generation Sequencing - Barcode of Life database: a widely applicable toolkit to monitor biodiversity and harmful algal blooms (HABs)

Harmful algal blooms have important implications for the health, functioning and services of aquatic ecosystems. Our ability to detect and monitor these events is often challenged by the lack of rapid and cost-effective methods to identify bloom-forming organisms and their potential for toxin production, Here, we developed and applied a combination of DNA barcoding and Next Generation Sequencing (NGS) for the rapid assessment of phytoplankton community composition with focus on two important indicators of ecosystem health: toxigenic bloom-forming cyanobacteria and impaired planktonic biodiversity. To develop this molecular toolset for identification of cyanobacterial and algal species present in HABs (Harmful Algal Blooms), hereafter called HAB-ID, we optimized NGS protocols, applied a newly developed bioinformatics pipeline and constructed a BOLD (Barcode of Life Data System) 16S reference database from cultures of 203 cyanobacterial and algal strains representing 101 species with particular focus on bloom and toxin producing taxa. Using the new reference database of 16S rDNA sequences and constructed mock communities of mixed strains for protocol validation we developed new NGS primer set which can recover 16S from both cyanobacteria and eukaryotic algal chloroplasts. We also developed DNA extraction protocols for cultured algal strains and environmental samples, which match commercial kit performance and offer a cost-efficient solution for large scale ecological assessments of harmful blooms while giving benefits of reproducibility and increased accessibility. Our bioinformatics pipeline was designed to handle low taxonomic resolution for problematic genera of cyanobacteria such as the Anabaena-Aphanizomenon-Dolichospermum species complex, two clusters of Anabaena (I and II), Planktothrix and Microcystis. This newly developed HAB-ID toolset was further validated by applying it to assess cyanobacterial and algal composition in field samples from waterbodies with recurrent HABs events.

molecular biology↗