Dataset: The global proteome of replete laboratory cultures of Ruergeria pomeroyi DSS-3

Final no updates expectedDOI: 10.26008/1912/bco-dmo.875600.1Version 1 (2022-06-14)Dataset Type:experimental

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

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

Data Manager: Laura Gray (Woods Hole Oceanographic Institution)

BCO-DMO Data Manager: Shannon Rauch (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 represents the global proteome of replete laboratory cultures of Ruergeria pomeroyi DSS-3 (collected in triplicate). This dataset is an initial examination of the proteome allocation of this heterotrophic bacteria and will contribute to C-CoMP's efforts that are focused on understanding the physiology of model marine bacteria. A total of 2341 proteins were identified in DSS-3. The Moran laboratory at University of Georgia grew and prepared the cultures and the Saito laboratory at Wo...

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Cite Dataset

Cultures (50 ml each) of Ruergeria pomeroyi DSS-3 and Alteromonas macleodii MIT1002 were harvested in triplicate, centrifuged at 8000 x g for 10 minutes, flash frozen, stored at -80 degrees C, and shipped to Woods Hole Oceanographic Institution for proteomics analysis. Cultures were filtered and filters were extracted using SDS detergent and a SP3 magnetic bead purification followed by trypsin digestion alkylation and reduction. The methods are described in Saito et al. 2020 and were modified from the methods originally published by Hughes et al. 2014. Analysis was conducted by 2D active modulation Orbitrap mass spectrometry as described in McIlvin and Saito 2021.

This dataset reports results for the Ruergeria pomeroyi DSS-3 samples. See related datasets for the Alteromonas macleodii MIT1002 samples.

Note: the sample ids ending in a1, b1, and c1 differentiate biological triplicates from one another.

Related Datasets

IsRelatedTo
Dataset: https://www.ebi.ac.uk/pride/archive/projects/PXD034365
McIlvin, M., Saito, S. (2022) Model Bacteria Physiological Studies Dataset 1: Triplicate replete proteomes for Ruergeria pomeroyi DSS-3 Dataset 2: Triplicate replete proteomes for Alteromonas macleodii MIT1002. Publication date: 2022-06-10. https://www.ebi.ac.uk/pride/archive/projects/PXD034365
IsRelatedTo
Dataset: Alteromonas macleodii MIT1002 replete proteome
Saito, M. A., Moran, M. A. (2022) The global proteome of replete laboratory cultures of Alteromonas macleodii MIT1002. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-06-14 doi:10.26008/1912/bco-dmo.875612.1

Related Publications

Methods
Hughes, C. S., Foehr, S., Garfield, D. A., Furlong, E. E., Steinmetz, L. M., & Krijgsveld, J. (2014). Ultrasensitive proteome analysis using paramagnetic bead technology. Molecular Systems Biology, 10(10), 757. doi:10.15252/msb.20145625
Methods
McIlvin, M. R., & Saito, M. A. (2021). Online Nanoflow Two-Dimension Comprehensive Active Modulation Reversed Phase–Reversed Phase Liquid Chromatography High-Resolution Mass Spectrometry for Metaproteomics of Environmental and Microbiome Samples. Journal of Proteome Research, 20(9), 4589–4597. doi:10.1021/acs.jproteome.1c00588
Methods
Saito, M. A., McIlvin, M. R., Moran, D. M., Santoro, A. E., Dupont, C. L., Rafter, P. A., … Waterbury, J. B. (2020). Abundant nitrite-oxidizing metalloenzymes in the mesopelagic zone of the tropical Pacific Ocean. Nature Geoscience, 13(5), 355–362. doi:10.1038/s41561-020-0565-6

Saito, M. A., Moran, M. A. (2022) The global proteome of replete laboratory cultures of Ruergeria pomeroyi DSS-3. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-06-14 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.875600.1 [access date]

Terms of Use

This dataset is licensed under Creative Commons Attribution 4.0.


If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.

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Funded by the U.S. National Science Foundation