Skip to main content

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

Cite this dataset

Villegas Mendoza, Josue Rodolfo; Gomez Ocampo, Eliana; Velasquez Aristizabal, Jorge Armando; Rodriguez Escobar, Diana (2022). Data from: Microbial metabolic activity in two basins of the Gulf of Mexico influenced by mesoscale structures [Dataset]. Dryad.


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.


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


* 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.

* 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.

* Del Giorgio, P., Williams, P., 2007. Respiration in Aquatic Ecosystems, Respiration in Aquatic Ecosystems. Oxford University Press, New York.

* 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

* 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.

Usage notes

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 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) (CIGoM;


Secretariat of Public Education, Award: 511-6/2019.-11768

Consejo Nacional de Ciencia y Tecnología – Secretaría de Energía, Award: 201441