Dataset: Normalized protein abundance data and protein annotations for proteomic data from laboratory cultures of Ruegeria pomeroyi DSS-3 and Alteromonas macleodii MIT1002 in 2022

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.927507.1Version 1 (2024-05-14)Dataset Type:experimental

Principal Investigator: Mak A. Saito (Woods Hole Oceanographic Institution)

Co-Principal Investigator: Mary Ann Moran (University of Georgia)

Scientist: Zachary Shane Cooper (University of Georgia)

Technician: Matthew R. McIlvin (Woods Hole Oceanographic Institution)

Data Manager: Laura Gray (Woods Hole Oceanographic Institution)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)


Program: Center for Chemical Currencies of a Microbial Planet (C-CoMP)

Project: C-CoMP Model Bacteria Physiological Studies (C-CoMP Model Bacteria)


Abstract

This dataset includes normalized protein abundance data and protein annotations for proteomic data from cultures of Ruegeria pomeroyi DSS-3 and Alteromonas macleodii MIT1002. These model marine bacteria were grown in defined culture media with either glucose, acetate, or a mix of both as carbon substrates. The data are sampled so as to capture the metabolic differences the bacteria employ when catabolizing these different substrates and when switching between them. The raw proteomics files are a...

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Under well-defined laboratory conditions, we grew R. pomeroyi DSS-3 and A. macleodii MIT1002 in batch cultures on a monosaccharide (glucose) and organic acid (acetate), provided either individually or in combination, and all at the same carbon equivalent. This batch culturing approach mimicked bacterial DOC assimilation in short-lived substrate ‘hot spots’, such as those formed by high phytoplankton extracellular release at peak photon availability. Measurements were made of bacterial metabolite uptake, respiration, and biomass accumulation through a growth cycle. Insights into bacterial core metabolism came from gene and protein expression measured at intervals during growth. Curated genome-scale models (flux balance analysis; FBA) were used to explore the metabolic foundation of CO2 production for insights into determinants of BGE and bCUE.

Samples were collected for proteomic analysis during the exponential growth phase from liquid cultures. Proteomic samples were pelleted by centrifugation, frozen at –80 ̊C, and analyzed at the Bioinorganic Chemistry Laboratory at the Woods Hole Oceanographic Institution (WHOI).

Protein extracts from the biological triplicates were analyzed by liquid chromatography-mass spectrometry (LC-MS) (Michrom Advance HPLC coupled to a Thermo Scientific Fusion Orbitrap mass spectrometer with a Thermo Flex source). Each sample was concentrated onto a trap column (0.2 x 10 mm ID, 5 µm particle size, 120 Å pore size, C18 Reprosil-Gold, Dr. Maisch GmbH) and rinsed with 100 µL 0.1% formic acid, 2% acetonitrile (ACN), 97.9% water before gradient elution through a reverse phase C18 column (0.1 x 500 mm ID, 3 µm particle size, 120 Å pore size, C18 Reprosil-Gold, Dr. Maisch GmbH) at a flow rate of 250 nL/min. The chromatography consisted of a nonlinear 190 min gradient from 5% to 95% buffer B, where A was 0.1% formic acid in water and B was 0.1% formic acid in ACN (all solvents were Fisher Optima grade). The mass spectrometer was set to perform MS scans on the orbitrap (240000 resolution at 200 m/z) with a scan range of 380 m/z to 1580 m/z. MS/MS was performed on the ion trap using data-dependent settings (top speed, dynamic exclusion 15 seconds, excluding unassigned and singly charged ions, precursor mass tolerance of ±3ppm, with a maximum injection time of 50 ms).

Curated genome-scale models (flux balance analysis; FBA) were used to explore the metabolic foundation of CO2 production for insights into determinants of bacterial growth efficiency (BGE) and bacterial carbon use efficiency (bCUE).


Related Datasets

IsRelatedTo

Dataset: Substrate-specific metabolic responses of model marine bacteria
Relationship Description: These proteomic data accompany the transcriptomic expression data "Substrate-specific metabolic responses of model marine bacteria" (https://www.bco-dmo.org/dataset/916134).
Moran, M. A., Cooper, Z. S. (2023) Metadata for transcriptomic expression data from cultures of Ruegeria pomeroyi DSS-3 and Alteromonas macleodii MIT1002 grown in defined culture media with either glucose, acetate, or a mix of both as carbon substrates. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2023-12-06 doi:10.26008/1912/bco-dmo.916134.1
IsRelatedTo

Dataset: https://www.ebi.ac.uk/pride/archive/projects/PXD045824
Saito, M. A., McIlvin, M. R. (2023) Dynamic metabolic efficiency of substrate utilization by copiotrophic marine bacteria. Proteomics Identifications Database (PRIDE). URL: https://www.ebi.ac.uk/pride/archive/projects/PXD045824

Related Publications

Methods

Saunders, J. K., McIlvin, M. R., Dupont, C. L., Kaul, D., Moran, D. M., Horner, T., Laperriere, S. M., Webb, E. A., Bosak, T., Santoro, A. E., & Saito, M. A. (2022). Microbial functional diversity across biogeochemical provinces in the central Pacific Ocean. Proceedings of the National Academy of Sciences, 119(37). https://doi.org/10.1073/pnas.2200014119
Software

Proteome Software Inc. (n.d.) Scaffold 5. [Software]. Available from https://www.proteomesoftware.com/products/scaffold-5
Software

Thermo Fisher Scientific Inc. (n.d.) Proteome Discoverer (catalog number: OPTON-31105) [Software]. Available from https://www.thermofisher.com/order/catalog/product/OPTON-31105