Integrated Respirometry and Metabolomics Unveil Circadian Metabolic Dynamics in Drosophila

Reviewer #1 (Public review):

Summary:

This study by Akhtar et al. aims to investigate the link between systemic metabolism and respiratory demands, and how sleep and the circadian clock regulate metabolic states and respiratory dynamics. The authors leverage genetic mutants that are defective in sleep and circadian behavior in combination with indirect respirometry and steady-state LC-MS-based metabolomics to address this question in the Drosophila model.

First, the authors performed respirometry (on groups of 25 flies) to measure oxygen consumption (VO2) and carbon dioxide production (VCO2) to calculate the respiratory quotient (RQ) across the 24-hour day (12h:12h light-dark cycle) and assess metabolic fuel utilization. They observed that among all the genotypes tested, wild type (WT) flies and per0 flies in LD and WT flies in DD exhibit RQ >1. They concluded the >1 RQ is consistent with active lipogenesis. In contrast, the short-sleep mutants fumin (fmn) and sleepless (sss) showed significantly different RQ; the fmn exhibits a slight reduction in RQ values, suggesting increased reliance on carbohydrate metabolism, while sss exhibits even lower RQ (0.94), consistent with a shift toward lipid and protein catabolism.

The authors then proceeded to bin these measurements in 12-hour partitions, ZT0-12 and ZT12-24, to assess diurnal differences in average values of VO2, VCO2, and RQ. They observed significant day-night differences in metabolic rates in WT-LD flies, with higher rates during the day. The diurnal differences remain in the short-sleep mutants, but the overall metabolic rates are higher. WT-DD flies exhibit the lowest respiratory activity, although the day-night differences remain in free-running conditions. Finally, per01 mutants exhibit no significant change in day-night respiratory rates, suggesting that a functional circadian clock is necessary for diurnal differences in metabolic rates.

They then performed finer-resolution 24-hour rhythmic analysis (RAIN and JTK) to determine if VO2, VCO2, and RQ exhibit 24-hour rhythmic and if there are genotype-specific differences. Based on their criteria, VCO2 is rhythmic in all conditions tested, while VO2 is rhythmic in all conditions except in fmn-LD. Finally, RQ is rhythmic in all 3 mutants but not in WT-LD and WT-DD. Peak phases for the rhythms were deduced using JTK lag values.

The authors proceeded to leverage a previously published steady-state metabolite dataset to investigate the potential association of RQ with metabolite profiles. Spearman correlation was performed to identify metabolites that exhibit coupling to respiratory output. Positive and negative lag analysis were subsequently performed to further characterize these associations based on the timing of the metabolite peak changes relative to RQ fluctuations. The authors suggest that a positive lag indicates that metabolite changes occur after shifts in RQ, and a negative lag signifies that metabolite changes precede RQ changes. To visualize metabolic pathways that exhibit these temporal relationships, a clustered heatmap and enrichment analysis were performed. Through these analyses, they concluded that both sleep and circadian systems are essential for aligning metabolic substrate selection with energy demands, and different metabolic pathways are misregulated in the different mutants with sleep and circadian defects.

Strength:

The research questions this study explores are significant, given that metabolism and respiratory demand are central to animal biology. The experimental methods used, including the well-characterized fly genetic mutants, the newly developed method for indirect calorimetry measurements, and LC-MS-based metabolomics, are all appropriate. This study provides insights into the impact of sleep and circadian rhythm disruption on metabolism and respiratory demand and serves as a foundation for future mechanistic investigations.

Weaknesses:

There are some conceptual flaws that the authors need to address regarding circadian biology, and some of the conclusions can be better supported by additional analysis to provide a stronger foundation for future functional investigation. At times, the methods, especially the statistical analysis, are not well articulated; they need to be better explained.

Reviewer #2 (Public review):

This is an innovative and technically strong study that integrates dual-gas respirometry with LC-MS metabolomics to examine how sleep and circadian disruption shape metabolism in Drosophila. The combination of continuous O₂/CO₂ measurements with high-temporal-resolution metabolite profiling is novel and provides fresh insight into how wild-type flies maintain anticipatory fuel alignment, while mutants shift to reactive or misaligned metabolism. The use of lag-shift correlation analysis is particularly clever, as it highlights temporal coordination rather than static associations. Together, the findings advance our understanding of how circadian clocks and sleep contribute to metabolic efficiency and redox balance.

However, there are several areas where the manuscript could be strengthened. The authors should acknowledge that their findings may be gene-specific. Because sleep deprivation was not performed, it remains uncertain whether the observed metabolic shifts generalize to sleep loss broadly or are restricted to the fmn and sss mutants. This concern also connects to the finding of metabolic misalignment under constant darkness despite an intact clock. The conclusion that external entrainment is essential for maintaining energy homeostasis in flies may not translate to mammals. It would help to reference supporting data for the finding and discuss differences across species. Ideally, complementary circadian (light-dark cycle disruption) or sleep deprivation (for several hours) experiments, or citation of comparable studies, would strengthen the generality of the findings. Figures 1-4 are straightforward and clear, but when the manuscript transitions to the metabolite-respiration correlations, there is little description of the metabolomics methods or datasets, which should be clarified. The Discussion is at times repetitive and could be tightened, with the main message (i.e., wild-type flies align metabolism in advance, while mutants do not) kept front and center. Terms such as "anticipatory" and "reactive" should be defined early and used consistently throughout.

Overall, this is a strong and novel contribution. With clarification of scope, refinement of presentation, and a more focused Discussion, the paper will make a significant impact.

Reviewer #3 (Public review):

Summary:

The authors investigate how sleep loss and circadian disruption affect whole-organism metabolism in Drosophila melanogaster. They used chamber-based flow-through respirometry to measure oxygen consumption and carbon dioxide production in wild-type flies and in mutants with impaired sleep or circadian function. These measurements were then integrated with a previously published metabolomics dataset to explore how respiratory dynamics align with metabolic pathways. The central claim is that wild-type flies display anticipatory coordination of metabolic processes with circadian time, while mutants exhibit reactive shifts in substrate use, redox imbalance, and signs of mitochondrial stress.

Strengths:

The study has several strengths. Continuous high-resolution respirometry in flies is challenging, and its application across multiple genotypes provides good comparative insight. The conceptual framework distinguishing anticipatory from reactive metabolic regulation is interesting. The translational framing helps place the work in a broader context of sleep, circadian biology, and metabolic health.

Weaknesses:

At the same time, the evidence supporting the conclusions is somewhat limited. The metabolomics data were not newly generated but repurposed from prior work, reducing novelty. The biological replication in the respirometry assays is low, with only a small number of chambers per genotype. Importantly, respiratory parameters in flies are strongly influenced by locomotor activity, yet no direct measurements of activity were included, making it difficult to separate intrinsic metabolic changes from behavioral differences in mutants. In addition, repeated claims of "mitochondrial stress" are not directly substantiated by assays of mitochondrial function. The study also excluded female flies entirely, despite well-documented sex differences in metabolism, which narrows the generality of the findings.

Author response:

We thank the reviewers for their thoughtful public feedback. Our revision will clarify scope and methods/statistics, as well as streamline the narrative so the central message is clear: wild-type flies exhibit anticipatory alignment of fuel selection with circadian time, whereas short-sleep and clock mutants show reactive or misaligned metabolism under our conditions.

Major conceptual and experimental revisions:

(1) We will define “anticipatory” (clock-aligned, pre-emptive substrate choice) and “reactive” (post-hoc substrate shifts) up front and use these terms consistently. We will clearly distinguish diurnal (LD) from circadian (DD) regulation and avoid implying that DD abolishes rhythmicity. Claims will be limited to the tested genotypes (fmn, sss, and per⁰¹) without generalizing to all forms of sleep loss or to mammals (although we will speculate in the discussion about translation and generalizability). We will temper language around external entrainment in DD to “contributes strongly under our conditions in flies.”

(2) We will expand the respirometry and rhythmicity sections (RAIN/JTK parameters, period/phase outputs, multiple-testing control). We will clarify that each measurement is an average of 300 flies per genotype (25 flies/chamber, 4 chambers/experiment, 3 experimental days) and specify the chamber as the experimental unit with n and error structure in each figure legend. For metabolomics–respirometry correlations, we will briefly describe dataset parameters, time-matching across ZT, normalization, Spearman correlations, and lag interpretation.

(3) We are performing additional experimental measurements through tissue respirometry of gut tissues and ROS staining to support our claims of “mitochondrial stress” in the short sleeping mutants. We note that this has already been shown for fmn in Vaccaro et al (Cell, 2020) and we will extend this to the other mutants studied in our work.

Reviewer-specific points

Reviewer #1.

We will clarify the circadian/diurnal framing, fully report rhythmicity analyses (parameters, n, q-values, phases), and better explain the metabolomics-respiration coupling with a concise workflow figure and supplementary table. The conclusion that sleep and clock systems align substrate selection with energy demand will be presented as supported under our tested conditions and positioned as groundwork for future mechanistic studies.

Reviewer #2.

We will state explicitly that findings may be gene-specific and avoid inferring generality to all sleep loss. We will soften cross-species language about external entrainment and add a brief note on species differences. For behavioral context (activity/feeding/sleep in fmn andsss), we will cite our related manuscript in revision (Malik et al, https://www.biorxiv.org/content/10.1101/2023.10.30.564837v2) in which we have measured both activity and feeding for fmn, sss, and wt flies. We will add a concise description of LC-MS processing and pathway analysis and define “anticipatory”/“reactive” early, using them consistently.

Reviewer #3.

We acknowledge that metabolomics were repurposed and emphasize the novelty of integrating continuous VCO2 and VO2 respirometry with temporal lag analysis. We will report replication clearly (chambers as the unit, n per genotype) and acknowledge locomotor activity as a potential confound, pointing to the related manuscript (Malik et al) for independent activity/feeding measurements and experimental measures of mitochondrial stress as outlined above. We will also further note that only males were studied, outlining this as a limitation and a future direction.