Biology subjects

Meszaros, J.

Publications and source records attributed to Meszaros, J..

2 recordsLinked to original sources

bioRxiv2019

Detecting GPCR Complexes in Postmortem Human Brain with Proximity Ligation Assay and a Bayesian Classifier

Despite the general controversy regarding the existence and physiological relevance of Class A GPCR dimerization, there is substantial evidence for functional interactions between dopamine D2 receptor (D2R) and adenosine A2A receptor (A2AR). A2AR-D2R complexes have been detected in rodent brains by proximity ligation assay (PLA), but their existence in the human brain is yet to be demonstrated. In this study, we used brightfield PLA, combined with a systematic sampling and a parameter-free naive Bayesian classifier, and demonstrated proximity between D2R and A2AR in the adult human ventral striatum, consistent with their colocalization within complexes and the possible existence of D2R-A2AR heteromers. These methods are applicable to the quantitative analysis of proximity of two proteins and the expression of individual proteins.\n\nMethod SummaryBrightfield proximity ligation assay (PLA) was used to assess the expression of G protein-coupled receptors and their proximity in postmortem adult human brains. A novel automated machine learning method (Bayesian Optimized PLA Signal Sorting) was developed to automatically quantify brightfield PLA data.

neuroscience↗

bioRxiv2019

Localized semi-nonnegative matrix factorization (LocaNMF) of widefield calcium imaging data

Widefield calcium imaging enables recording of large-scale neural activity across the mouse dorsal cortex. In order to examine the relationship of these neural signals to the resulting behavior, it is critical to demix the recordings into meaningful spatial and temporal components that can be mapped onto well-defined brain regions. However, no current tools satisfactorily extract the activity of the different brain regions in individual mice in a data-driven manner, while taking into account mouse-specific and preparation-specific differences. Here, we introduce Localized semi-Nonnegative Matrix Factorization (LocaNMF), a method that efficiently decomposes widefield video data and allows us to directly compare activity across multiple mice by outputting mouse-specific localized functional regions that are significantly more interpretable than more traditional decomposition techniques. Moreover, it provides a natural subspace to directly compare correlation maps and neural dynamics across different behaviors, mice, and experimental conditions, and enables identification of task- and movement-related brain regions.

neuroscience↗