Biology subjects

Saraiva, L.

Publications and source records attributed to Saraiva, L..

2 recordsLinked to original sources

bioRxiv2022

Commonality of Odorant Receptor Choice Mechanism Revealed by Analysis of a Highly Represented Odorant Receptor Transgene

In the mouse, more than 1,100 odorant receptors (ORs) are expressed in a monogenic and monoallelic fashion, referred to as singular gene expression. Using a 21bp singular-choice enhancer (x21), we radically increase representation of olfactory sensory neurons (OSNs) choosing a 5x21 enhanced OR transgene, but not overexpression of its mRNA on a per cell basis. RNA-sequencing and differential expression analysis identified 425 differentially expressed genes (DEGs). ORs make up 86% of all DEGs, of which 325 have decreased representation and 40 have increased representation. Underrepresented ORs include Class I, Class II and TAAR genes and within each of their respective olfactory bulb domains: DI, DII, and DIII (TAAR) we committedly observe multiple homogeneous glomeruli with an OR1A1-identity. The underrepresentation of endogenous, class-specific ORs across evolutionarily distinct cell types in favor of the expression of the 5x21-OR1A1 transgene argues that a common mechanism of singular gene choice is present for all OR-expressing OSNs.

neuroscience↗

bioRxiv2019

A simple linearization method unveils hidden enzymatic assay interferences

Enzymes are among the most important drug targets in the pharmaceutical industry. The bioassays used to screen enzyme modulators can be affected by unaccounted interferences such as time-dependent inactivation and inhibition effects. Using procaspase-3, caspase-3, and -thrombin as model enzymes, we show that some of these effects are not eliminated by merely ignoring the reaction phases that follow initial-rate measurements. We thus propose a linearization method (LM) for detecting spurious changes of enzymatic activity based on the representation of progress curves in modified coordinates. This method is highly sensitive to signal readout distortions, thereby allowing rigorous selection of valid kinetic data. The method allows the detection of assay interferences even when their occurrence is not suspected a priori. By knowing the assets and liabilities of the bioassay, enzymology results can be reported with enhanced reproducibility and accuracy. Critical analysis of full progress curves is expected to help discriminating experimental artifacts from true mechanisms of enzymatic inhibition.

biophysics↗