Sannino, D. R. | bioRxiv Science

bioRxiv2026

Barcoding biology: Chemotype predicts variation in genotype, physiology, and stress response

Predicting biological responses to perturbations such as stress, nutrition, or pharmaceuticals could transform healthcare and biosciences. The task is challenging because complex interactions among many factors interactively drive biological variation, and thereby alter responses. However, metabolism integrates these drivers of variation, suggesting that emergent biological states may be reflected in aggregate chemical states. We define such states as chemotypes and test their predictive utility. Using Fourier-transform infrared (FTIR) spectroscopy coupled with machine learning in Drosophila melanogaster, we show that chemotypes serve as proxies for biological variation driven by sex, genotype, nutrition and age, and - critically - predict among-population variation in stress response. These findings indicate that chemotypes provide a computable and integrative representation of organismal biology, predicting genotype, phenotype, and response to perturbation.

systems biology↗

bioRxiv2025

Microbiota reduce Drosophila triacylglyceride density by providing pantothenate

Metabolism follows ground-rules that evolved in ancient bacteria: as a legacy, animal gut microbiota have abundant opportunity to modulate host metabolism, via conserved mechanisms. When these effects are beneficial, natural selection should favour hosts that reciprocally support bacterial growth. Whether microbes simply nourish hosts or more profoundly reprogram host metabolism remains to be established. Here we show that Acetobacter promote Drosophila coenzyme A, an ancient signalling metabolite, reprogramming host metabolism and generating a state that reciprocally supports bacterial growth. Impairing pathways from bacterial pantothenate to host coenzyme A increases host lipid storage, reduces nitrogen excretion, and diminishes bacterial load. These processes correspond to reprogrammed host carbohydrate handling and tissue-specific acyl-CoA pools, but live bacteria and short-chain fatty acids are dispensable. These results outline a simple microbial basis for complex host metabolic effects, via mechanisms that precede the origins of metazoa, facilitating metabolic and symbiotic homeostasis.

physiology↗

bioRxiv2023

Outcome of Drosophila microbiota manipulation depends on dietary preservative formula and batch variation in dietary yeast

Gut microbiota are fundamentally important for healthy function in their animal hosts. The fly Drosophila melanogaster is a powerful system for understanding the underlying host/microbe interactions, with modulation of the microbiota inducing phenotypic changes that are conserved across animal taxa. The context-dependence of these responses has not been explored systematically, which may confound repeatability. Here we show that the microbiotas impact on fly triacylglyceride (TAG) levels - a commonly-measured metabolic index - depends on factors in fly media that are rarely considered or controlled, and are not standardized among laboratories: media preservative formula, yeast batch, and the interactive effect of their combinatorial variation. In studies of conventional, axenic and gnotobiotic flies, we found that microbial impacts were apparent only on specific yeast-by-preservative conditions, with TAG levels determined by a tripartite interaction of the three experimental factors. When comparing axenic and conventional flies, we found that preservatives rather than microbiota status was the main driver of variance in host TAG, and certain yeast-preservative combinations reversed microbiota effects on TAG levels. Further, comparisons between TAG levels of axenic flies and those associated with Acetobacter pomorum or Levilactobacillus brevis determined that preservatives, microbiota status, and their interaction were the major drivers of TAG variation. Our results suggest that the microbiota shapes the host TAG response in a manner dependent on the combination of the dietary factors of preservative formulation and yeast batch, with implications for repeatability, interpretation, and optimal experimental standards. ImportanceDrosophila melanogaster is a premier model for microbiome science, which has greatly enhanced our understanding of the basic biology of host-microbe biology. However, often overlooked factors such as dietary composition, including yeast batch variability and preservative formulation used, may cofound data interpretation of experiments within the same lab and lead to different findings when comparing between labs. Our study supports this concept; we find that host TAG levels are not solely dependent on the presence or absence of microbiota members, but rather the combinatorial effects of microbiota members, yeast batch, and preservative formulation used, with preservatives being the largest driver. It serves as a cautionary tale that underappreciated components of fly rearing can mask or drive phenotypes that are believed to be impacted by microbiota members.

microbiology↗