Saunders-Pullman, R. | Search bioRxiv

bioRxiv2021

BATL: Bayesian annotations for targeted lipidomics

MotivationBioinformatic tools capable of annotating, rapidly and reproducibly, large, targeted lipidomic datasets are limited. Specifically, few programs enable high-throughput peak assessment of liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) data acquired in either selected or multiple reaction monitoring (SRM and MRM) modes. ResultsWe present here Bayesian Annotations for Targeted Lipidomics (BATL), a Gaussian naive Bayes classifier for targeted lipidomics that annotates peak identities according to eight features related to retention time, intensity, and peak shape. Lipid identification is achieved by modelling distributions of these eight input features across biological conditions and maximizing the joint posterior probabilities of all peak identities at a given transition. When applied to sphingolipid and glycerophosphocholine SRM datasets, we demonstrate over 95% of all peaks are rapidly and correctly identified. Availability and implementationBATL software is freely accessible online at https://complimet.ca/batl/ and is compatible with Safari, Firefox, Chrome and Edge. Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

Discordant transcriptional signatures of mitochondrial genes in Parkinson's disease human myeloid cells

An increasing number of identified Parkinsons disease (PD) risk loci contain genes highly expressed in innate immune cells, yet their potential role in pathological mechanisms is not obvious. We have generated transcriptomic profiles of CD14+ monocytes from 230 individuals with sporadic PD and age-matched healthy subjects. We identified dysregulation of genes involved in mitochondrial and proteasomal function. We also generated transcriptomic profiles of primary microglia from autopsied brains of 55 PD and control subjects and observed discordant transcriptomic signatures of mitochondrial genes in PD monocytes and microglia. We further identified PD susceptibility genes, whose expression, relative to each risk allele, is altered in monocytes. These findings reveal that transcriptomic mitochondrial alterations are detectable in PD monocytes and are distinct from brain microglia, and facilitates efforts to understand the roles of myeloid cells in PD.

neuroscience↗