DOI: 10.5061/dryad.ncjsxkt4r
title: Data from: Fuel stores and time of day account for variation in serum metabolomes of passerine migrants stopping over

description: Migratory birds excel in phenotypic flexibility, adapting physiologically
 as their life histories and environments require. Discerning the metabolic
 processes underlying migrants’ physiology, an emergent property of
 multiple continuous and dynamic organism-environment interactions, is
 therefore challenging, particularly under natural conditions. Accordingly,
 analyses of snapshot-sampled serum-circulating metabolites, versatile and
 readily applicable for migrating birds, have increasingly become the
 method of choice for such physiologic inference. However, the atemporal
 nature of single sampling might obscure the links between observed
 metabolite concentrations and the processes producing them, necessitating
 an analytical decoupling of focal processes from their broader biochemical
 background. In the present study, we examined how variation in combined
 fat and muscle fuel stores, traits pivotal in migratory context, relates
 to the serum-circulating metabolomes of spring-migrating Eurasian
 Blackcaps stopping-over. Our analyses accounted for potential
 spatiotemporal influences in the form of time past night’s fasting and
 random local conditions across three sites within the Negev Desert. We
 shifted the focus from compound-level analysis of preselected metabolites
 towards the level of inclusive metabolome, quantifying serum-circulating
 lipophilic and polar molecules via UHPLC–MS/MS untargeted metabolomic
 technique. Our results indicated a general relationship between fuel
 stores and the metabolome, comprising 16326 lipophilic and 6923 polar
 compounds, among which 918 and 44 were annotated, respectively. By
 applying Generalized Latent-Variable Linear Modeling (GLLVM) upon
 concentrations of annotated metabolites, we identified several candidate
 biomarkers, some novel in migratory context, notably the fuel-associated
 increase in serum ceramides likely derived from circulating very
 low-density lipoproteins (VLDLs). Relying on estimated metabolite links
 with fuel and foraging time, and on modeled residual covariations among
 metabolites, we demonstrate fuel-metabolite associations generally
 consistent with higher fat- and lower protein mobilization in birds having
 greater stores, and with decreased fuel utilization as ingested nutrients
 accumulate over time, thus introducing a novel approach for the
 physiological study of migrating birds.
description: # Data from: Fuel stores and time of day account for variation in serum
 metabolomes of passerine migrants stopping over
 [https://doi.org/10.5061/dryad.ncjsxkt4r](https://doi.org/10.5061/dryad.ncjsxkt4r) The data used in the analyses is presented in the four "csv" files: "Zimin et al. 2024 Fuel stores metabolomics data - All lipophilic compounds", "Zimin et al. 2024 Fuel stores metabolomics data - All polar compounds", "Zimin et al. 2024 Fuel stores metabolomics data - Annotated lipophilic compounds", and "Zimin et al. 2024 Fuel stores metabolomics data - Annotated polar compounds". The first two files ("all compounds") are organized by analytes and metabolites detected via Compound Discoverer software (ver. 3.3; Thermo Fisher Scientific). The columns signify the library-based annotation of each analyte ("Name"), its Mass-to-Charge ratio ("m/z"), and its retention time in minutes ("RT [min]"). The rest of the columns represent peak areas (analyte or metabolite abundances) of each analyte for individual sampled birds (column per individual; IDs are consistent across all data files). NA in the "Name" column indicate analytes with no matching compound in the searched libraries; NA in sample columns indicate that the analyte was not detected in the corresponding sample. The last two files ("annotated compounds") are organized by sampled individuals (IDs same as above; column "A"), including metadata (columns "B" to "M") and metabolite relative abundances (starting at column "N"; for more details see text). The metadata columns are as follows: "Date": Calendar date; "Location": Name of the stopover locality; "Wing_chord": measurement of wing chord (± 0.5 mm); "Fat_score": score representing the quantity of the observed subcutaneous fat in the tracheal pit and on the abdomen (on a 0-8 scale). "Muscle_score": score representing the size of the pectoralis muscle (on a 0-3 scale). "Body_mass": measurement of body mass (± 0.1 g). "Capture_time": capture time of an individual bird. "Time_past_sunrise": standardized (z-scores) time between capture time and the sunrise time on the capture day. "Fuel_Stores_Index": standardized (z-scores) log-transformed body mass. "Mass_Wing_resid": residuals of body mass-wing chord OLS regression. "Fat_Load_Index" Fat Load Index sensu Ellegren & Fransson (1992). "Sampling_order": order of sampling of individuals captured simultaneously, representing sampling delay (on a 0-6 scale).