Fruit flies (Drosophila melanogaster) have been used as a promising model for understanding cellular and molecular mechanisms of diverse human genetic diseases including neuronal degeneration. The vast array of transgenic techniques in Drosophila enables in-depth analyses of disease gene functions. This can be done not only through conventional loss-of-function approaches, but also through gain-of-function approaches which drive constructs of exogenous genes, such as human disease genes, in a targeted set of neurons in the fly brain at diverse and controlled developmental stages. However, for the analysis of biological mechanisms relevant to mental disorders, genetic studies using fruit flies involve a number of empirical and theoretical complications. The major challenge lies in the strategies to dissect psychiatric symptoms that are considered to be specific to human patients. Thus, animal models would not be directly applicable for phenocopying many psychological conditions such as hallucination, delusion, thought distortion and other complex mental representations. The lack of objective biological markers sets another challenge in modeling mental diseases using animals in general. Nevertheless, mechanistic and etiological approaches focusing on endophenotypes, biological alterations underlying or often preceding the psychiatric symptoms, have been conducted for diverse mental disorders although major efforts have been limited to rodent models so far. On the other hand, recent advancements in human genetics have paved the way for systematic genome-wide studies leading to the identification of a large number of gene loci that are either associated with specific mental conditions or are familiarly transmitted with diverse psychiatric abnormalities. Fortunately, the majorities of the genes identified in such studies are evolutionarily conserved and can be found in the fruit fly genome. We thus envisage an emerging opportunity for rapid advancement of molecular psychiatry via convergence of human psychiatric genetics and Drosophila neurogenetics. Such cross-phylum efforts will certainly facilitate the identification of novel risk factors and molecular cellular processes that underlie the pathophysiology of mental illnesses, ultimately translating into novel mechanism-based treatments. In this topic, we aim to overview the emerging field of Drosophila psychogenetics with cutting-edge applications of fruit flies to molecular genetic studies of mental disorders including autism spectrum disorder, bipolar disorder and schizophrenia.
Fruit flies (Drosophila melanogaster) have been used as a promising model for understanding cellular and molecular mechanisms of diverse human genetic diseases including neuronal degeneration. The vast array of transgenic techniques in Drosophila enables in-depth analyses of disease gene functions. This can be done not only through conventional loss-of-function approaches, but also through gain-of-function approaches which drive constructs of exogenous genes, such as human disease genes, in a targeted set of neurons in the fly brain at diverse and controlled developmental stages. However, for the analysis of biological mechanisms relevant to mental disorders, genetic studies using fruit flies involve a number of empirical and theoretical complications. The major challenge lies in the strategies to dissect psychiatric symptoms that are considered to be specific to human patients. Thus, animal models would not be directly applicable for phenocopying many psychological conditions such as hallucination, delusion, thought distortion and other complex mental representations. The lack of objective biological markers sets another challenge in modeling mental diseases using animals in general. Nevertheless, mechanistic and etiological approaches focusing on endophenotypes, biological alterations underlying or often preceding the psychiatric symptoms, have been conducted for diverse mental disorders although major efforts have been limited to rodent models so far. On the other hand, recent advancements in human genetics have paved the way for systematic genome-wide studies leading to the identification of a large number of gene loci that are either associated with specific mental conditions or are familiarly transmitted with diverse psychiatric abnormalities. Fortunately, the majorities of the genes identified in such studies are evolutionarily conserved and can be found in the fruit fly genome. We thus envisage an emerging opportunity for rapid advancement of molecular psychiatry via convergence of human psychiatric genetics and Drosophila neurogenetics. Such cross-phylum efforts will certainly facilitate the identification of novel risk factors and molecular cellular processes that underlie the pathophysiology of mental illnesses, ultimately translating into novel mechanism-based treatments. In this topic, we aim to overview the emerging field of Drosophila psychogenetics with cutting-edge applications of fruit flies to molecular genetic studies of mental disorders including autism spectrum disorder, bipolar disorder and schizophrenia.
![Sleep behavior in wild-type (Canton-S) male flies was assessed between 3 and 5 days after eclosion (n = 15 flies as control). Canton-S flies fed with 1.6 × 10−3 g/mL of Kamikihito (n = 16 flies), Unkei-to (n = 16), Saiko (n = 15), and AC-Negia (n = 15), as well as 2.0 × 10−4 g/mL of myo-inositol (n = 15), d-pinitol (n = 15), l-alpha-glycerophosphatidylcholine (α-GPC) (n = 16), and PC-DHA (n = 16) in standard cornmeal yeast medium after eclosion. Sleep amount/day (A,B), number (C,D), and duration (E,F) of sleep bouts. Results are expressed as mean ± SEM. Data were statistically analyzed by one-way ANOVA, followed by Dunnett’s post hoc test. Obtained F values are as follows: (A) [day: F(8,130) = 1.13; p = 0.34, night: F(8,130) = 0.69; p = 0.69], (B) [day: F(8,130) = 2.18; p = 0.03, night: F(8,130) = 2.95; p = 0.0045], (C) [F(8,130) = 2.60; p = 0.011], (D) [F(8,130) = 1.77; p = 0.088], (E) [F(8,130) = 1.63; p = 0.11], (F) [F(8,130) = 2.29; p = 0.024]. * represents significant differences (p < 0.05).](https://www.frontiersin.org/_rtmag/_next/image?url=https%3A%2F%2Fwww.frontiersin.org%2Ffiles%2FArticles%2F260591%2Ffpsyt-08-00132-HTML%2Fimage_m%2Ffpsyt-08-00132-g002.jpg&w=3840&q=75)
![Auditory function, courtship songs, and chaining. (A) Relative compound action potential (CAP) amplitude of tone-evoked auditory nerve responses plotted against the intensity of the tone. Tone frequencies were matched to the individual best frequencies of the antennal sound receiver. No distinct shift in the response threshold could be detected when comparing wild-type (N = 5), Dnlg4-deficient (N = 5), and Dnl2g-deficient (N = 3) flies. The insect shows a general schematic with which the antennal movements and sounds were recorded as references during the electrophysiological recordings. (B) Dominant frequency component of sine songs. Significance was calculated using Fisher’s permutation test for differences of medians, corrected with Benjamini–Hochberg false detection rate procedure [dnlg2KO17 vs dnlg4LL01874/Def p-value = 0.0195; N(wt) = 17; N(dnlg2KO17) = 10; N(dnlg4LL01874/Def) = 17]. (C) Period durations (=inter-pulse intervals) of pulse songs [identical test for significance; wt vs dnlg2KO17 p = 2 × 10−4; dnlg2KO17 vs dnlg4LL01874/Def p = 8 × 10−5; N(wt) = 16, N(dnlg2KO17) = 10, N(dnlg4LL01874/Def) = 17] (D) Probability of male–male chaining (a chain consists of two or more flies that chase each other with one extended wing) behavior per animal in dependence to the number of animals being present in the arena. In wt, the chance for male–male chaining behavior increases slightly with increasing numbers of present animals but never exceeds 4%. While dnlg2KO17-mutants never engaged in courtship chains, dnlg4LL01874/Def-mutants showed increased chaining behavior, reaching maximum probabilities of over 60% [N(wt) = 104, N(dnlg2KO17) = 94, N(dnlg4LL01874/Def) = 119]. (E) Boxplots depicting the individual probability to be part of male courtship chain. Dnlg4 shows a significantly increased chance, while dnlg4LL01874/Def shows a significant decrease [Kolmogorov–Smirnov test; wt vs dnlg2KO17 p = 7.3279 × 10−5; wt vs dnlg4LL01874/Def p = 6.0598 × 10−9; dnlg2KO17 vs dnlg4LL01874/Def p = 1.7207 × 10−9; N(wt) = 104, N(dnlg2KO17) = 94, N(dnlg4LL01874/Def) = 119].](https://www.frontiersin.org/_rtmag/_next/image?url=https%3A%2F%2Fwww.frontiersin.org%2Ffiles%2FArticles%2F261419%2Ffpsyt-08-00113-HTML%2Fimage_m%2Ffpsyt-08-00113-g006.jpg&w=3840&q=75)
