Skip to main content
2024 BMES Annual Meeting Main banner
Icon Legend
This session is not in your schedule.
This session is in your schedule. Click again to remove it.
Back

Bioinformatics, Computational and Systems Biology

Bioinformatics, Computational and Systems Biology - Poster Session D

Poster A5 - Microbiome-modulated behavioral changes in D. melanogaster

Friday, October 25, 2024
3:30 PM – 4:30 PM EST
Location: Exhibit Hall E, F & G

Introduction:  The gut microbiome plays a significant role in health, not only regulating metabolic activity and promoting immune-system function, but also modulating neurological signaling through the bi-deirectional pathway known as the gut-brain axis [1]. In humans, the features of the gut-brain axis are known to impact mental well-being and cognitive function, with recent studies highlighting the correlation between microbiome dysbiosis (a disruption or disturbance in commensal microbiota composition [2]) and anxiety and depression [3,4]. A deeper understanding of this neurological connection will lay the foundation for novel treatments for these disorders, such as the prescription of prebiotics and probiotics, as well as the use of fecal matter transplant [5]. However, since clinical study of the human gut-brain axis is challenging from both a practical and ethical standpoint, direct analysis of its behavioral effects is difficult.

Materials and

Methods:  Alternatively, model organisms, such as rats, mice, and hamsters are an effective tool when studying the gut microbiome. D. melanogaster has previously been identified as a relevant model organism due to the physiological similarities between its intestinal tract and the human intestinal tract [6]. Furthermore, the D. melanogaster gut microbiome is composed of merely 5-20 bacterial species (compared to thousands of species in humans and mice [7]), allowing for specific and directed microbiome manipulation [8]. Prior to manipulating the D. melanogaster gut microbiome, one must first be able to effectively and efficiently remove all bacteria from the gut.

Results, Conclusions, and Discussions: Here, we examine the efficacy of two existing microbiome-elimination methods in D. melanogaster: egg dechorionation and a low-dose streptomycin diet [9]. We also propose a new method of microbiome removal: Holidic Media treatment. We quantify the effectiveness of each treatment in removing the gut microbiome through whole-fly homogenization and plating, and determine that egg dechorionation, streptomycin diet, and Holidic Media treatment are effective methods for removing the D. melanogaster gut microbiome. We then use SLEAP, a deep learning-based software, to obtain robust tracking data across treatment groups, and compare behavioral trends across groups [10]. We did not find a statistically significant difference between treatment groups among male D. melanogaster; however, we found that both antibiotic treatment and dechorionation decreased female activity levels compared to the control group, with dechorionation decreasing activity levels to a greater extent. We plan to use the MotionMapper pipeline to produce a behavioral space that can identify specific behavioral differences between groups, such as grooming behaviors [11].

Acknowledgements (Optional):  1. Hou, K., Wu, ZX., Chen, XY. et al. Microbiota in health and diseases. Sig Transduct Target Ther 7, 135 (2022). https://doi.org/10.1038/s41392-022-00974-4
2. Petersen, C., & Round, J. L. (2014). Defining dysbiosis and its influence on host immunity and disease. Cellular microbiology, 16(7), 1024–1033. https://doi.org/10.1111/cmi.12308
3. Kumar, A., Pramanik, J., Goyal, N., Chauhan, D., Sivamaruthi, B. S., Prajapati, B. G., & Chaiyasut, C. (2023). Gut Microbiota in Anxiety and Depression: Unveiling the Relationships and Management Options. Pharmaceuticals (Basel, Switzerland), 16(4), 565. https://doi.org/10.3390/ph16040565
4. Liu, L., Wang, H., Chen, X., Zhang, Y., Zhang, H., & Xie, P. (2023) Gut microbiota and its metabolites in depression: from pathogenesis to treatment. eBioMedicine 90 104527. https://doi.org/10.1016/j.ebiom.2023.104527
5. Karrouri, R., Hammani, Z., Benjelloun, R., & Otheman, Y. (2021). Major depressive disorder: Validated treatments and future challenges. World journal of clinical cases, 9(31), 9350–9367. https://doi.org/10.12998/wjcc.v9.i31.9350
6. Sadaqat, Z., Kaushik, S., Kain, P., Gut Feeding the Brain: Drosophila Gut an Animal Model for Medicine to Understand Mechanisms Mediating Food Preferences. Preclinical Animal Modeling in Medicine. 10.5772/intechopen.96503
7. Kieser, S., Zdobnov, E. M., & Trajkovski, M. (2022). Comprehensive mouse microbiota genome catalog reveals major difference to its human counterpart. PLoS computational biology, 18(3), e1009947. https://doi.org/10.1371/journal.pcbi.1009947
8. Ludington, W. B., & Ja, W. W. (2020). Drosophila as a model for the gut microbiome. PLoS pathogens, 16(4), e1008398. https://doi.org/10.1371/journal.ppat.1008398
9. Heys, C., Lizé, A., Blow, F., White, L., Darby, A., & Lewis, Z. J. (2018). The effect of gut microbiota elimination in Drosophila melanogaster: A how-to guide for host-microbiota studies. Ecology and evolution, 8(8), 4150–4161. https://doi.org/10.1002/ece3.3991
10. Pereira, T.D., Tabris, N., Matsliah, A. et al. SLEAP: A deep learning system for multi-animal pose tracking. Nat Methods 19, 486–495 (2022). https://doi.org/10.1038/s41592-022-01426-1
11. Berman GJ, Choi DM, BialekW, Shaevitz JW. 2014 Mapping the stereotyped behaviour of freely moving fruit flies. J. R. Soc.Interface 11: 20140672.http://dx.doi.org/10.1098/rsif.2014.0672