This README_Villegas-Mendoza_et_al_2021.txt file was generated on 2021-03-09 by Josué Villegas-Mendoza (JVM), Eliana Gómez-Ocampo (EGO), Diana Rodríguez-Escobar (DRE) and Jorge Velásquez-Aristizábal (JVA) GENERAL INFORMATION 1. Title of Dataset: Microbial Metabolic Activity in Two Basins of the Gulf of Mexico Influenced by Mesoscale Structures 2. Author Information A. Principal Investigator Contact Information Name: Josué Villegas-Mendoza (ORCID: https://orcid.org/0000-0001-5614-3375) Institution: Universidad Autónoma de Baja California Address: Carretera Tijuana-Ensenada km 106, Ensenada, Baja California 22860, Mexico Email: jvillegas18@uabc.edu.mx B. Alternate Contact Information Name: Eliana Gómez-Ocampo (ORCID: https://orcid.org/0000-0001-5593-7595) Institution: Universidad Autónoma de Baja California Address: Carretera Tijuana-Ensenada km 106, Ensenada, Baja California 22860, Mexico Email: eliana.gomez.ocampo@uabc.edu.mx C. Alternate Contact Information Name: Jorge Velásquez-Aristizábal (ORCID: https://orcid.org/0000-0003-2842-0931) Institution: Universidad Autónoma de Baja California Address: Carretera Tijuana-Ensenada km 106, Ensenada, Baja California 22860, Mexico Email: velasquez.jorge@uabc.edu.mx D. Alternate Contact Information Name: Diana Rodríguez-Escobar (ORCID: https://orcid.org/0000-0002-1590-8746) Institution: Universidad Autónoma de Baja California Address: Carretera Tijuana-Ensenada km 106, Ensenada, Baja California 22860, Mexico Email: drodriguez41@uabc.edu.mx 3. Date of data collection: First oceanographic campaign ("Malla fina 1": MMF-01; March sampling) from 2016-03-04 to 2016-03-23. Second oceanographic campaign ("Malla fina 2": MMF-02; September sampling) from 2016-09-19 to 2016-09-29. 4. Geographic location of data collection: Two Gulf of Mexico basin's, Perdido (~25–26 °N, 95–96 °W) and Coatzacoalcos (~19–21 °N, 94–95 °W) 5. Information about funding sources that supported the collection of the data: This is a contribution of the Consorcio de Investigación del Golfo de México (CIGOM). We thankfully acknowledge the specific request placed by PEMEX to the Hydrocarbon Fund to address the environmental effects of oil spills in the Gulf of Mexico. This study was funded by the Hydrocarbon Fund of Consejo Nacional de Ciencia y Tecnología – Secretaría de Energía, through grants No. 201441 and by Secretaría de Educación Pública through grants SEP UABC‐PTC‐702: 511‐6/17‐8051 (to Josué Villegas-Mendoza) and grant PRODEP 511-6/2019.-11768 (to Eliana Gómez-Ocampo). SHARING/ACCESS INFORMATION Recommended citation for this dataset: Villegas-Mendoza, J., Gomez-Ocampo, E., Velasquez-Aristizabal, J., and Rodriguez-Escobar, D. (2021) Microbial Metabolic Activity in Two Basins of the Gulf of Mexico Influenced by Mesoscale Structures. Manuscript submitted for publication DATA & FILE OVERVIEW 1. File List: One EXCEL file: continuos data (CTD) and discrete data (bottle samples): Villegas-Mendoza_et_al_2022_Dataset.xlsx 2. Relationship between files, if important: Both files are related since they correspond to the continuous hydrographic (CTD) and discrete metabolic variables collected for all stations during both cruises. 3. Additional related data collected that was not included in the current data package: no 4. Are there multiple versions of the dataset? no METHODOLOGICAL INFORMATION Water samples were collected with Niskin oceanographic bottles at five depth levels (0.1% and 30% light, maximum fluorescence, minimum oxygen, and 500 m) at three stations in each of the study basins, Perdido and Coatzacoalcos. CTD data Dissolved oxygen, practical salinity, and in-situ temperature data were acquired with a CTD instrument from surface to 500 m. Community and Bacterial Respiration Rates Water samples from different depth levels were incubated in triplicate in 100 mL BOD bottles previously rinsed with 3% hydrogen peroxide (H2O2) and fitted with oxygen-sensitive patches (SP-PSt3-NAU-YOP). Samples for assessing community respiration were collected directly from BOD bottles; samples for bacterial respiration were filtered through 1-µm pore size polycarbonate filters. All the bottles were incubated for 24 hours in the dark under a controlled temperature (18 ± 1 °C) (Bondyale-Juez et al., 2017). Oxygen concentration at different times was recorded with optode sensors using the Fibox 4 system (PreSens, Regensburg, Germany) (Villegas-Mendoza et al., 2019). Oxygen optode sensors provide continuous measurements (at intervals of seconds to minutes) with high accuracy (± 0.14–2.83 µmol and ± 1.4–283.1 µmol; 15 ppb detection limit). Bacterial growth efficiency was calculated as the ratio between bacterial production and (bacterial production plus bacterial respiration). Bacterial Abundance Bacterial abundance was determined in 10 mL samples from each depth; the samples were fixed with 2% formaldehyde solution. A 0.5–1.0 mL aliquot of the sample was incubated with DAPI and filtered immediately through 0.2 µm black polycarbonate filters (Poretics). Cells were counted with an Eclipse Ti-E inverted microscope (Nikon Instruments Inc.) and the image analysis software Nikon NIS-Elements (Kirchman D., 1993). Bacterial Production Bacterial production (BP) is the amount of organic carbon that becomes incorporated into cells per unit of time (Del Giorgio and Williams, 2007). It represents the potential flow of organic carbon from bacteria to the upper trophic levels (Azam, 1998). BP was determined by estimating protein synthesis with the micro-centrifugation technique developed by Smith and Azam (1992). Triplicate 1.5 mL water samples were spiked with 3H-leucine (Perkin Elmer, specific activity 123 Ci mmol-1) and incubated for 5–7 hours in the dark at 18 °C; 100 μL of cold 100% TCA were spiked into the control replicates. Afterward, 1 mL of EcoLume liquid scintillation cocktail (MP Biomedicals) was added and mixed; bacterial 3H emission was measured on a liquid scintillation counter (Beckman LS6500). A constant 0.073 value for the leucine/protein fraction was used, assuming that leucine is not transformed into other amino acids. This value was multiplied by the leucine molecular weight (131.2 g mol-1), by the carbon-protein cell ratio (0.86), and by the isotopic dilution (2) (Smith and Azam, 1992). Bacterial Growth Efficiency Bacterial growth efficiency (BGE) was calculated as was reported for the Gulf of Mexico by Biddanda and Benner (1997). Respiration per Cell Respiration per cell was calculated by dividing the prokaryotic respiration rate by the bacterial abundance References * Biddanda, B., Benner, R., 1997. Major contribution from mesopelagic plankton to heterotrophic metabolism in the upper ocean. Deep Sea Res. Part I Oceanogr. Res. Pap. 44, 2069–2085. https://doi.org/https://doi.org/10.1016/S0967-0637(97)00045-9 * Bondyale-Juez, D. R., Packard, T. T., Viera-Rodríguez, M. A., & Gómez, M. (2017). Respiration: comparison of the Winkler technique, O2 electrodes, O2 optodes and the respiratory electron transport system assay. Marine Biology, 164(12), 1–11. https://doi.org/10.1007/s00227-017-3271-1 * Del Giorgio, P., Williams, P., 2007. Respiration in Aquatic Ecosystems, Respiration in Aquatic Ecosystems. Oxford University Press, New York. https://doi.org/10.1093/acprof:oso/9780198527084.001.0001 * Kirchman D (1993) Statistical analysis of direct counts of microbial abundance. In:Kemp PF, Sherr BF, Sherr EB, Cole JJ (eds) Handbook of methods in aquatic microbial ecology. Lewis Publishers, Boca Raton, FL, p 117−119 * Smith, D. C., & Azam, F. (1992). A simple, economical method for measuring bacterial protein synthesis rates in seawater using 3H-leucine. Marine Microbial Food Webs, 6(2), 107–114. Retrieved from http://scrippsscholars.ucsd.edu/fazam/content/simple-economical-method-measuring-bacterial-protein-synthesis-rates-seawater-using-3h-leucine * Villegas-Mendoza, J., Cajal-Medrano, R., & Maske, H. (2019). The Chemical Transformation of the Cellular Toxin INT (2-(4-Iodophenyl)-3-(4-Nitrophenyl)-5-(Phenyl) Tetrazolium Chloride) as an Indicator of Prior Respiratory Activity in Aquatic Bacteria. International journal of molecular sciences, 20(3), 782. https://doi.org/10.3390/ijms20030782