Biology subjects

Lee, D. F.

Publications and source records attributed to Lee, D. F..

4 recordsLinked to original sources

bioRxiv2022

The open field assay is influenced by room temperature and by drugs that affect core body temperature

The open field assay is used to study anxiety-related traits and anxiolytic drugs in rodents. This assay entails measuring locomotor activity and time spent in the center of a chamber that is maintained at ambient room temperature. However, the ambient temperature in most laboratories varies daily and seasonally and can differ substantially between buildings. Here, we sought to evaluate how varying ambient temperature and core body temperature (CBT) affected open field locomotor activity and center time of wild-type (WT) and Trpm8 knock-out (Trpm8-/-) mice. TRPM8 is an ion channel that detects cool temperatures and is activated by cooling agents, including icilin and menthol. We found that the cooling agent icilin increased CBT and profoundly reduced distance traveled and center time of WT mice relative to vehicle controls. Likewise, cooling the ambient temperature to 4{degrees}C reduced distance traveled and center time of WT mice relative to Trpm8-/- mice. Conversely, the TRPM8 antagonist (M8-B) reduced CBT and increased distance traveled and center time of WT mice when tested at 4{degrees}C. Predictably, the TRPM8 antagonist (M8-B) had no effect on CBT or open field behavior of Trpm8-/- mice. The anxiolytic diazepam reduced CBT in both WT and Trpm8-/- mice. When tested at 4{degrees}C, diazepam increased distance traveled and center time in WT mice but did not alter open field behavior of Trpm8-/- mice. Our study shows that environmental temperature and drugs that affect CBT can influence locomotor behavior and center time in the open field assay, highlighting temperature (ambient and core) as sources of environmental and physiologic variability in this commonly used behavioral assay.

neuroscience↗

bioRxiv2021

Cocaine-induced locomotor activation differs across six sets of inbred mouse substrains

Cocaine use disorders (CUD) are devastating for affected individuals and impose a significant burden on society, but there are currently no FDA-approved therapies. The development of novel and effective treatments has been hindered by substantial gaps in our knowledge about the etiology of these disorders. The risk for developing a CUD is influenced by genetics, the environment and complex interactions between the two. Identifying specific genes and environmental risk factors that increase CUD risk would provide an avenue for the development of novel treatments. Rodent models of addiction-relevant behaviors have been a valuable tool for studying the genetics of response to drugs of abuse. Traditional genetic mapping using genetically and phenotypically divergent inbred mice has been successful in identifying numerous chromosomal regions that influence addiction-relevant behaviors, but these strategies rarely result in identification of the causal gene or genetic variant. To overcome this challenge, reduced complexity crosses (RCC) between closely related inbred mouse substrains have been proposed as a method for rapidly identifying and validating functional variants. The RCC approach is dependent on identifying phenotypic differences between substrains. To date, however, the study of addiction-relevant behaviors has been limited to very few sets of substrains, mostly comprising the C57BL/6 lineage. The present study expands upon the current literature to assess cocaine-induced locomotor activation in 20 inbred mouse substrains representing six inbred strain lineages (A/J, BALB/c, FVB/N, C3H/He, DBA/2 and NOD) that were either bred in-house or supplied directly by a commercial vendor. To our knowledge, we are the first to identify significant differences in cocaine-induced locomotor response in several of these inbred substrains. The identification of substrain differences allows for the initiation of RCC populations to more rapidly identify specific genetic variants associated with acute cocaine response. The observation of behavioral profiles that differ between mice generated in-house and those that are vendor-supplied also presents an opportunity to investigate the influence of environmental factors on cocaine-induced locomotor activity.

genetics↗

bioRxiv2020

Genomic Architecture of Cells in Tissues (GeACT): Study of Human Mid-gestation Fetus

By circumventing cellular heterogeneity, single cell omics have now been widely utilized for cell typing in human tissues, culminating with the undertaking of human cell atlas aimed at characterizing all human cell types. However, more important are the probing of gene regulatory networks, underlying chromatin architecture and critical transcription factors for each cell type. Here we report the Genomic Architecture of Cells in Tissues (GeACT), a comprehensive genomic data base that collectively address the above needs with the goal of understanding the functional genome in action. GeACT was made possible by our novel single-cell RNA-seq (MALBAC-DT) and ATAC-seq (METATAC) methods of high detectability and precision. We exemplified GeACT by first studying representative organs in human mid-gestation fetus. In particular, correlated gene modules (CGMs) are observed and found to be cell-type-dependent. We linked gene expression profiles to the underlying chromatin states, and found the key transcription factors for representative CGMs. HighlightsO_LIGenomic Architecture of Cells in Tissues (GeACT) data for human mid-gestation fetus C_LIO_LIDetermining correlated gene modules (CGMs) in different cell types by MALBAC-DT C_LIO_LIMeasuring chromatin open regions in single cells with high detectability by METATAC C_LIO_LIIntegrating transcriptomics and chromatin accessibility to reveal key TFs for a CGM C_LI

genomics↗

bioRxiv2020

Correlated Gene Modules Uncovered by Single-Cell Transcriptomics with High Detectability and Accuracy

Single cell transcriptome sequencing has become extremely useful for cell typing. However, such differential expression data has shed little light on regulatory relationships among genes. Here, by examining pairwise correlations between mRNA levels of any two genes under steady-state conditions, we uncovered correlated gene modules (CGMs), clusters of intercorrelated genes that carry out certain biological functions together. We report a novel single-cell RNA-seq method called MALBAC-DT with higher detectability and accuracy, allowing determination of the covariance matrix of the expressed mRNAs for a homogenous cell population. We observed a prevalence of positive correlations between pairs of genes, with higher correlations corresponding to higher likelihoods of protein-protein interactions. Some CGMs, such as the p53 module in a cancer cell line, are cell type specific, while others, such as the protein synthesis CGM, are shared by different cell types. CGMs distinguished direct targets of p53 and exposed different modes of regulation of these genes in different cell types. Our covariance analyses of steady-state fluctuations provides a powerful way to advance our functional understanding of gene-to-gene interactions.

genomics↗