Genetics and genomics of alcohol responses in Drosophila

Abstract

Drosophila melanogaster has become a significant model organism for alcohol research. In flies, a rich variety of behaviors can be leveraged for identifying genes affecting alcohol responses and adaptations. Furthermore, almost all genes can be easily genetically manipulated. Despite the great evolutionary distance between flies and mammals, many of the same genes have been implicated in strikingly similar alcohol-induced behaviors. A major problem in medical research today is that it is difficult to extrapolate from any single model system to humans. Strong evolutionary conservation of a mechanistic response between distantly related organisms, such as flies and mammals, is a powerful predictor that conservation will continue all the way to humans. This review describes the state of the Drosophila alcohol research field. It describes common alcohol behavioral assays, the independent origins of resistance and tolerance, the results of classical genetic screens and candidate gene analysis, and the outcomes of recent genomics studies employing GWAS, transcriptome, miRNA, and genome-wide histone acetylation surveys. This article is part of the Special Issue entitled "Alcoholism".

Keywords: Alcoholism; Behavior; Drosophila; Genetics; Genomics; Level of response; Preference; Tolerance.

Figure 1. Two common assays

A) The Inebriometer. The illustration depicts the inebriometer: a large vertical glass tube with scoop-like ledges on which flies can walk or stand. While ethanol vapor is pumped through the apparatus, flies are introduced through a small opening at the top and allowed to breath the vapor. As flies succumb to the ethanol effects and lose postural control, they elute from the bottom of the column. B) Visually monitoring ethanol sedation in vials is an extremely common assay. Figure not drawn to scale.

Figure 2. The 50% knockdown time (K50) is a behavioral endpoint that occurs at a fixed ethanol concentration even when environmental conditions produce extreme differences in K50 time

The internal ethanol concentration of 39 groups of 10 flies quantified at the time when half of the flies in each group succumbed to ethanol sedation. While the K50 time differed greatly, the internal ethanol remains fixed within a narrow range around 111 mM +/− 2.3 (Pohl et al, 2013 used with permission).

Figure 3. The ethanol-conditioned odor preference assay

The illustration depicts the training (left) and the test (right) stages of the assay. During training, groups of flies are exposed to two odorants separately. One of the odors is paired with an intoxicating ethanol exposure, while the other odor is unpaired (as shown in the timeline). Flies are later tested (30 mins or 24 hours post training) in a Y-maze where the odors alone are pumped in through either arm of the Y. Flies choose which arm to approach. Figure not to scale.

Figure 4. Ethanol resistance, tolerance, and preference genes identified by one-gene-at-a-time genetics organize into GO-like gene categories

The Venn diagram shows how overrepresented gene categories/functions become apparent once sufficient numbers of genes are identified. The evidence for each gene is as follows: ple (Bainton et al, 2005), cher, klg, kra, pum (Berger et al, 2008), mys, scb (Bhandari et al, 2009), Clic (Bhandari et al, 2012), KCNQ (Cavaliere et al, 2012), Fas2 (Cheng et al, 2001), chico, Ilp2, InR (Corl et al, 2005), Egfr, hppy, rl (Erk), S, spi (Corl et al, 2009), slo (Cowmeadow et al, 2005), unc-13 (Das et al, 2013), GABA-B-R1 (Dzitoyeva et al, 2003), Akt1, aru, Pi3K92E (Eddison et al, 2011), Syn (Godenschwege et al, 2004), Nmdar1, sca (Kaun et al, 2011), htl (King et al, 2014), Dop1R1 (Kong et al, 2010b), shi, Syx1A (Krishnan et al, 2012), Bx (dLmo) (Lasek et al, 2011a), Jwa (Li et al, 2008), CASK, dlg1 (Maiya et al, 2012), amn, Pka-C1, rut (Moore et al, 1998), ics (Rsu1) (Ojelade et al, 2013), Pka-R2 (Park et al, 2000), Arf51F (Peru Y Colon de Portugal et al, 2012), DopEcR (Petruccelli et al, 2016), cyc, per, tim (Pohl et al, 2013), Rac1, Rho1, RhoGAP18B (Rothenfluh et al, 2006), hang (Scholz et al, 2005), iav, Tbh (Scholz, 2005), cact, Dif, Myd88, pll, Rel, Tl, tub (Troutwine et al, 2016), CrebB (Wang et al, 2007), NPF (Wen et al, 2005). The learning and memory category contains many more genes that have been only cursorily characterized (see text).

Figure 5. The Aru protein is regulated by both EGFR and PI3K signaling pathways to alter ethanol level of response by different mechanisms

The ethanol-relevant activity of these pathways appears to occur in different developmental stages. The genetic evidence does not necessarily indicate that all steps occur in the same cell (Eddison et al, 2011). Gray arrows indicate activation, and inverted T indicates inhibition.

Figure 6. RhoGAP18B regulates Rho GTPases, cell shape, and ethanol resistance

Adapted from Ojelade et al, (2015a).