Proteomic characterization of a temperature-sensitive conditional lethal in Drosophila melanogaster

Abstract

Genetic variation that is expressed only under specific environmental conditions can contribute to additional adverse effects of inbreeding if environmental conditions change. We present a proteomic characterization of a conditional lethal found in an inbred line of Drosophila melanogaster. The lethal effect is apparent as a large increase in early mortality at the restrictive temperature (29 1C) as opposed to normal survival at the permissive temperature (20 1C). The increased mortality in response to the restrictive temperature is probably caused by a single recessive major locus. A quantitative trait locus (QTL) region segregating variation affecting the lethal effect has been identified, allowing for a separation of primary/causal effects and secondary consequences in the proteome expression patterns observed. In this study, the proteomic response to the restrictive temperature in the lethal-line (L-line) was compared with the response in an inbred-control-line (IC-line) and an outbred-control-line (OC-line). Quantitative protein changes were detected using isobaric tags for relative and absolute quantitation (iTRAQ) two-dimensional liquid chromatography-tandem mass spectrometry. In all, 45 proteins were found to be significantly differently regulated in response to the restrictive temperature in the L-line as compared with the IC-line. No proteins were significantly differently regulated between the IC-line and the OC-line, verifying that differential protein regulation was specific to a genetic defect in the L-line. Proteins associated with oxidative phosphorylation and mitochondria were significantly overrepresented within the list of differentially expressed proteins. Proteins related to muscle contraction were also found to be differentially expressed in the L-line in response to the restrictive temperature, supporting phenotypic observations of moribund muscle hypercontraction.

Proteomic data reveals a physiological basis for costs and benefits associated with thermal acclimation

“…Since then, technologies have been developing fast and state of the art methods now enable identification and quantification of sometimes thousands of proteins in organisms such as Escherichia coli (Soufi et al, 2015). In spite of this, studies on thermal acclimation responses in arthropods have rarely identified more than a few hundred proteins (Colinet et al, 2007(Colinet et al, , 2013Pedersen et al, 2010;Wei et al, 2015), making investigation of complex physiological changes in response to thermal acclimation difficult.…”

Proteomic Characterization of Inbreeding-Related Cold Sensitivity in Drosophila melanogaster

“…Pedersen et al [13] performed a proteomic analysis of an inbred strain of D. melanogaster that suffered from extreme heat-sensitivity. They identified 45 proteins that were differentially regulated in response to the restrictive conditions, with an overrepresentation of proteins associated with oxidative phosphorylation and mitochondria.…”

“…This is a great omission, as functional genomic studies of inbreeding are invaluable for dissecting many yet unsolved problems within evolutionary biology, conservation biology, agriculture, and medical sciences [7]–[9]. Proteome analysis is suitable as an approach to link genotypic with phenotypic effects at the organismal level, and some studies have been successful in identifying and characterizing genotypic differences using proteomic methods [10]–[13]. With the increasing use of genome-wide technologies, data are emerging that showcase the complexity of the whole organism responses [13]–[16].…”

“…Proteome analysis is suitable as an approach to link genotypic with phenotypic effects at the organismal level, and some studies have been successful in identifying and characterizing genotypic differences using proteomic methods [10]–[13]. With the increasing use of genome-wide technologies, data are emerging that showcase the complexity of the whole organism responses [13]–[16]. Since the data generated by these methods typically are very complex, a powerful strategy is to focus on genetically simple, large and reproducible effects [13], [17].…”

“…With the increasing use of genome-wide technologies, data are emerging that showcase the complexity of the whole organism responses [13]–[16]. Since the data generated by these methods typically are very complex, a powerful strategy is to focus on genetically simple, large and reproducible effects [13], [17]. Similar strategies have been successfully pursued for the study of other complex phenomena, e.g.…”