Find research datasets worth reusing

opencc-by-4.0Apr 2024View details →

Supporting dataset for manuscript "Role of metabolism, resistance, and/or antagonism as drivers of endomicrobiomes assemblage in Origanum heracleoticum L." by Giulia Semenzato et al. 2024

Raw data used for the analysis presented in the manuscript "Role of metabolism, resistance, and/or antagonism as drivers of endomicrobiomes assemblage in Origanum heracleoticum L." by authors Giulia Semenzato, Francesco Vitali, Arcangela Frascella, Ludovica Lollini, Stefano Mocali, Alessio Papini, Renato Fania, and Giovanni Emiliani  <ul> <li>phenome_combined_normalized_R.csv = activity values (AV) obtained after DuctApe elaboration of phenotype microarray data for carbon sources analysis. Control well signal was substracted.</li> <li>phenome_combined_nonNormalized_R.csv = activity values (AV) obtained after DuctApe elaboration of phenotype microarray data for resistance/sensibility sources analysis. Control well were signal not substracted.</li> <li>Rawdata_cross_streaking.csv = raw data obtained from cross-streaking experiment.</li> <li>Rawdata_MIC.csv = raw data obtained from MIC experiment.</li> <li>Raw_data_BIOLOG.zip = raw data from phenotype microarray readings.</li> </ul>

Data for "Diel Variability and Decoupled pH-Oxygen Dynamics Drive Metabolic Plasticity in Kelp Crabs from an Upwelling Seascape".

Data for “Diel Variability and Decoupled pH-Oxygen Dynamics Drive Metabolic Plasticity in Kelp Crabs from an Upwelling Seascape”. By Vargas, C.A. et al.   Two files: Readme.txt Diel cycle Taliepus upwelling dataset.xlsx   -Sheet “Upwelling index” Time-series of “u” and “v” component of the wind, and calculated upwelling index (UI) for two coastal sites in Arauco Gulf, an upwelling shadow (US) area, and an active upwelling (AU) area. Dataset used in Figure 1A. -Sheet “Time series”. Time-series data of seawater temperature (T), dissolved oxygen (DO), and pH for an upwelling shadow (US) area, and an active upwelling (AU) area. T in ºC, DO in mg L-1, and pH units. Dataset used in Figure 1D, E, Figure 2A, B, C, and Figure 3A, B, C, D. -Sheet “O2 consumption and C production”. Results data for oxygen consumption (umol O2 g-1 h-1), carbon production (umol C g-1 h-1), and respiratory quotient (RQ) during incubations. Datast used in Figure 5A, B, C, D, E, F. -Sheet “Glucose and lactate content”. Results data for hemolymph pH, glucose and lactate content (mg mg-tissue-1) in Taliepus dentatus muscle during incubations. Datast used in Figure 6A, B, C, D, E, F. All date and time (Date_Time) data format (mm/dd/yyyy hh:mm:ss)

Dataset Mayen et al_Temporal variations of water carbon and atmospheric carbon dioxide fluxes in a temperate salt marsh and influence of aquatic metabolism

Open the record for dataset details and reuse information.

Optimized Analytical Workflow for Single-Nucleus Transcriptomics in Main Metabolic Tissues

Single-nucleus RNA sequencing (snRNA-seq) has emerged as a powerful approach for studying cellular heterogeneity in metabolic tissues. However, snRNA-seq analysis remains challenging due to low gene expression and data complexity. Here, we introduce an optimized analytical workflow for snRNA-seq data from 67 samples across four main metabolic tissues white adipose tissue, hypothalamus, muscle and liver. We emphasized the importance of key steps including ambient RNA removal, doublet identification, normalization and data integration to ensure accurate downstream analysis. This workflow offers a valuable resource for researchers in metabolism, facilitating deeper insights into cellular diversity and metabolic function through rigorous snRNA-seq analysis.

Data and code to reproduce analyses in Heinken et al, "A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites"

This datasets archives the GitHub version found at https://github.com/ThieleLab/CodeBase to reproduce simulations for the article Heinken et al, "A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites", Cell Systems, in press.

Sex-specific fear acquisition following early life stress is linked to amygdala and hippocampal purine and glutamate metabolism

Motion tracking dataset used for the paper "Sex-specific fear acquisition following early life stress is linked to amygdala and hippocampal purine and glutamate metabolism", by Joeri Bordes et al. Abstract Early life stress (ELS) can negatively impact health, increasing the risk of stress-related disorders, such as post-traumatic stress disorder (PTSD). Importantly, PTSD disproportionately affects women, emphasizing the critical need to explore how sex differences influence the genetic and metabolic neurobiological pathways underlying trauma-related behaviors. This study uses the limited bedding and nesting (LBN) paradigm to model ELS and investigate its sex-specific effects on fear memory formation. Employing innovative unsupervised behavioral classification, the current study reveals distinct behavioral patterns associated with fear acquisition and retrieval in male and female mice following ELS. Females exposed to LBN display heightened active fear responses, contrasting with males. Furthermore, the study examined the crucial link between behavioral regulation and cellular metabolism in key brain regions involved in fear and stress processing. Sex-specific and stress-dependent alterations were observed in purine, pyrimidine, and glutamate metabolism within the basolateral amygdala, the dorsal hippocampus, and the ventral hippocampus. These findings provide crucial insights into the complex interplay between metabolic pathways, the neurobiological underpinnings of fear memory, and stress responses. Importantly, they emphasize the significance of considering sex-specific metabolic alterations when investigating stress-related disorders, opening potential avenues for the development of targeted interventions.

Additions to AGORA2 made for Shaaban et al, "Personalized modeling of gut microbiome metabolism throughout the first year of life"

This dataset contains expansions made to AGORA2 (https://www.nature.com/articles/s41587-022-01628-0) and published in Shaaban et al, "Personalized modeling of gut microbiome metabolism throughout the first year of life", in press. Included are: <ul> <li>289 additional genome-scale reconstructions built for genomes not included in AGORA2</li> <li>250 genome-scale reconstructions from AGORA2 endapnded with human milk oligosaccharide degradation pathways</li> </ul> In this version, slight updates have been made to the 289 additional genome-scale reconstructions based on additional experimental data.

Optimized Analytical Workflow for Single-Nucleus Transcriptomics in Main Metabolic Tissues

Single-nucleus RNA sequencing (snRNA-seq) has emerged as a powerful approach for studying cellular heterogeneity in metabolic tissues. However, snRNA-seq analysis remains challenging due to low gene expression and data complexity. Here, we introduce an optimized analytical workflow for snRNA-seq data from 67 samples across four main metabolic tissues white adipose tissue, hypothalamus, muscle and liver. We emphasized the importance of key steps including ambient RNA removal, doublet identification, normalization and data integration to ensure accurate downstream analysis. This workflow offers a valuable resource for researchers in metabolism, facilitating deeper insights into cellular diversity and metabolic function through rigorous snRNA-seq analysis.

Characterizing Metabolic Alterations in Early-stage chronic kidney disease (CKD) patients: A Pathway for Improved Diagnosis and Personalized Treatment.

The raw NMR data that I have uploaded contains the final concentration results that have been used for this study.

opencc-by-4.0Aug 2024View details →

Emerging Clostridioides difficile ribotypes have divergent metabolic phenotypes

Dataset of multi-well plate reader files related to the analysis of the growth of C. difficile isolates on differnet carbon substrates.  Data Collection. This dataset accompanies an mSystems article which is available at <a href="https://doi.org/10.1128/msystems.01075-24">https://doi.org/10.1128/msystems.01075-24</a>. The "Materials and Methods" section in this article fully describes the biological nature of these samples and how the samples were processed and analyzed.   Repository Content. The amiga folders contains both the raw data (see data and mapping sub-folders), intermediate outpus (see dervied sub-folders), and final outputs (see figures and summary sub-folders). Each amiga folder corresponds to a single working directory analyzed by the <a href="https://github.com/firasmidani/amiga">AMiGA</a> software. For the amiga-biolog directory, the notes sub-folder also includes text files related to flagging plates and wells for quality issues. Data Organization. Growth plate data are organized by the following experiments.  <ul> <li>biolog</li> <li>validation</li> <li>ribotype-255</li> <li>clade-5</li> <li>yeast-extract-biolog</li> <li>yeast-extract-validation</li> </ul> Data Analysis. Code used for manipulating and analyzing these samples is also publicly available on GitHub (<a href="https://github.com/firasmidani/cdiff-biolog-growth">https://github.com/firasmidani/cdiff-biolog-growth</a>) under the GNU GPL-3.0 license. The scripts in "analyze-code" can be used to analyze all data and the scripts in the "generate-figures" folder can be used to reproduce all figures included in the manuscript. See the GitHub repository for instructions on how to do so.

opencc-by-4.0Sep 2024View details →

Data: Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD

This archive contains all scripts, resource data and results, including intermediate results to reproduce the results for "Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD".

opencc-by-4.0Nov 2021View details →

Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies

The pcYeast7.6 model and files, required to reproduce the figures, provided in the publication "Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies", accepted in Nat Commun. The Zenodo upload was created by Pranas Grigaitis, p.grigaitis [at] vu.nl. Abstract When conditions change, unicellular organisms rewire their metabolism to sustain cell maintenance and cellular growth. Such rewiring may be understood as resource re-allocation under cellular constraints. Eukaryal cells contain metabolically active organelles such as mitochondria, competing for cytosolic space and resources, and the nature of the relevant cellular constraints remain to be determined for such cells. Here we present a comprehensive metabolic model of the yeast cell, based on its full metabolic reaction network extended with protein synthesis and degradation reactions. The model predicts metabolic fluxes and corresponding protein expression by constraining compartment-specific protein pools and maximising growth rate. Comparing model predictions with quantitative experimental data suggests that under glucose limitation, a mitochondrial constraint limits growth at the onset of ethanol formation - known as the Crabtree effect. Under sugar excess, however, a constraint on total cytosolic volume dictates overflow metabolism. Our comprehensive model thus identifies condition-dependent and compartment-specific constraints that can explain metabolic strategies and protein expression profiles from growth rate optimization, providing a framework to understand metabolic adaptation in eukaryal cells.

Thermal-metabolic phenotypes of the lizard Podarcis muralis differ across elevation, but converge in high elevation hypoxia

In response to a warming climate, many montane species are shifting upslope to track the emergence of preferred temperatures. Characterizing patterns of variation in metabolic, physiological and thermal traits along an elevational gradient, and the plastic potential of these traits, is necessary to understand current and future responses to abiotic constraints at high elevations, including limited oxygen availability. We performed a transplant experiment with the upslope-colonizing common wall lizard (Podarcis muralis) in which we measured nine aspects of thermal physiology and aerobic capacity in lizards from replicate low- (400 m above sea level, ASL) and high-elevation (1700 m ASL) populations. We first measured traits at their elevation of origin and then transplanted half of each group to extreme high elevation (2900 m ASL; above the current elevational range limit of this species), where oxygen availability is reduced by ∼25% relative to sea level. After 3 weeks of acclimation, we again measured these traits in both the transplanted and control groups. The multivariate thermal–metabolic phenotypes of lizards originating from different elevations differed clearly when measured at the elevation of origin. For example, high-elevation lizards are more heat tolerant than their low-elevation counterparts (counter-gradient variation). Yet, these phenotypes converged after exposure to reduced oxygen availability at extreme high elevation, suggesting limited plastic responses under this novel constraint. Our results suggest that high-elevation populations are well suited to their oxygen environments, but that plasticity in the thermal–metabolic phenotype does not pre-adapt these populations to colonize more hypoxic environments at higher elevations.

Large and exaggerated sexually selected weapons comprise high proportions of metabolically inexpensive exoskeleton

The cost-minimization hypothesis proposes that positive allometry in sexually selected traits can be explained if the proportional energetic maintenance costs of weapons decrease as traits increase in size. Energetic maintenance costs are the costs of maintaining homeostasis. They are slow, persistent energy sinks that are distinct from ephemeral costs of growth. Because some tissues expend more energy on maintenance than others, energetic maintenance costs can be inferred from proportional tissue composition. For example, soft tissues require more energy for maintenance than exoskeleton, so an arthropod claw that is 50% soft tissue and 50% exoskeleton would have higher energetic maintenance costs than one that is 30% soft tissue and 70% exoskeleton. I tested the cost-minimization hypothesis using proportional tissue composition as a proxy for energetic maintenance costs in snapping shrimp ( Alpheus heterochaelis and Alpheus estuariensis ) and fiddler crabs ( Uca pugilator ). As predicted, larger weapons comprised proportionally less soft tissue mass and more exoskeleton mass than smaller weapons. Furthermore, I extended cost-minimization to explain trait exaggeration: individuals might exaggerate traits by investing more mass in exoskeleton. As predicted, exoskeleton mass proportional to weapon mass increased as exaggeration increased. These results support and extend the cost-minimization hypothesis to explain positive allometry and weapon exaggeration.

opencc-by-4.0Dec 2021View details →

Mediobasal hypothalamic FKBP51 acts as a molecular switch linking autophagy to whole-body metabolism - Dataset IC

Raw data associated to the following publication: “Mediobasal hypothalamic FKBP51 acts as a molecular switch linking autophagy to whole-body metabolism". The stress-responsive FKBP51 controls body weight gain by regulating the balance between autophagy and mTOR signaling. We identified FKBP51 as a central nexus for the recruitment of the LKB1/AMPK complex to WIPI4 and TSC2 to WIPI3, thereby regulating the balance between autophagy and mTOR signaling in response to metabolic challenges. MBH FKBP51 dose-dependently regulates autophagy both in the brain as well as in peripheral metabolic tissues. Consequently, deletion of MBH FKBP51 strongly induces obesity, while its overexpression protects against high-fat diet (HFD) induced obesity. IC data in Thermo RAW data format; 2nd of 2 datasets.

opencc-by-4.0Dec 2021View details →

Mediobasal hypothalamic FKBP51 acts as a molecular switch linking autophagy to whole-body metabolism - Dataset Bz

Raw data associated to the following publication: “Mediobasal hypothalamic FKBP51 acts as a molecular switch linking autophagy to whole-body metabolism". The stress-responsive FKBP51 controls body weight gain by regulating the balance between autophagy and mTOR signaling. We identified FKBP51 as a central nexus for the recruitment of the LKB1/AMPK complex to WIPI4 and TSC2 to WIPI3, thereby regulating the balance between autophagy and mTOR signaling in response to metabolic challenges. MBH FKBP51 dose-dependently regulates autophagy both in the brain as well as in peripheral metabolic tissues. Consequently, deletion of MBH FKBP51 strongly induces obesity, while its overexpression protects against high-fat diet (HFD) induced obesity. Bz data in Thermo RAW data format; 1 of 2 datasets.

Impacts of male-killing Spiroplasma on the metabolic rate and ectoparasite resistance capacity (endurance) of Drosophila

Ectoparasitic mites are hypothesized to horizontally transmit bacterial endosymbionts, especially male-killing Spiroplasma. In this study we test how Spiroplasma poulsonii MSRO affects fly physiology and behaviour, and potential mite interactions.

Data from: Microbial metabolic activity in two basins of the Gulf of Mexico influenced by mesoscale structures

Information on microbial metabolic activity is essential for quantifying carbon and energy flows through marine food webs. We quantified community (Rcom) and prokaryotic (Rpro) respiration rates, bacterial production (BP), bacterial abundance (BA), and bacterial growth efficiencies (BGE) in the Perdido and Coatzacoalcos basins of the Gulf of Mexico (GOM) during summer and winter conditions in 2016. Our results showed seasonal, regional, and mesoscale eddy influences on those metabolic variables. Rpro accounted for more than 60% of total respiration in both regions, being three times higher in stations influenced by a cyclonic eddy (CE) in September (24.1 μM O2 d-1) than in stations affected by an anticyclonic eddy in March (7.2 μM O2 d-1) within the Coatzacoalcos basin where the eddy-trapping mechanism advected biomass-enriched waters from the Bay of Campeche. The eddy-stirring mechanism produced horizontal and vertical dipole patterns of metabolic variables increasing up to one order of magnitude Rcom and Rpro while decreasing BGE to 25-fold from the southeastern to the northwestern edges in CEs. This finding indicates that dissolved organic matter is more actively taken up to build bacterial biomass on the eastern edge of CEs in the GOM, while respiration rates increase on the western edges. Satellite integrated primary production was coupled with surface respiration rates at CEs and no eddies. Bacterial production was mainly regulated by CEs and was about 50% higher in the Coatzacoalcos basin (~0.03–0.14 µmol C L-1 d-1). BP increased in zones with high respiration rates, suggesting that Rcom is associated with heterotrophic prokaryote activity in both basins. Bacterial growth efficiency was lower than 25% within the upper 500 m during both cruises, but the highest values were quantified in the euphotic zone and during the September cruise. Metabolic variables integrated over the water column showed that 40–80% of the activity occurred between the base of the euphotic zone and 150 m depth. Our findings contribute to a better understanding of the metabolic activity of the microbial communities in two regions of the GOM influenced by mesoscale eddies.

opencc-zeroJan 2022View details →

Deriving population scaling rules from individual-level metabolism and life history traits - Code and Data

Individual metabolism generally scales with body mass with an exponent around 3/4. From dimensional arguments it follows that maximum population growth rate (rmax) scales with a -1/4 exponent. However, the dimensional argument implicitly assumes that offspring size is proportional to adult size. Here we calculate rmax from metabolic scaling at the level of individuals within size-structured populations while explicitly accounting for offspring size. We identify four general patterns of how rmax scales with adult mass based on four empirical life-history patterns employed by groups of species. These life-history patterns are determined by how traits of somatic growth rate and/or offspring mass relate to adult mass. One life-history pattern -- constant adult:offspring mass ratio and somatic growth rate independent of adult mass -- leads to the classic -1/4 scaling of rmax. The other three life-history patterns lead either to non-metabolic population growth scaling with adult mass or do not follow a power-law relationship at all. Using life-history data of five marine taxa and terrestrial mammals, we identify species groups that belong to one of each case. We predict that elasmobranchs, copepods, and mammals follow standard -1/4 power-law scaling, whereas teleost fish and bivalves do not have a pure power-law scaling. Our work highlights how taxa may deviate from the classic -1/4 metabolic scaling pattern of maximum population growth. The approach is generic and can be applied to any taxa.