Total spectral counts of peptides from the R/V Falkor cruise 160115 in the Central Pacific for the ProteOMZ expedition in 2016
Project
| Contributors | Affiliation | Role |
|---|---|---|
| Saito, Mak A. | Woods Hole Oceanographic Institution (WHOI) | Principal Investigator |
| Ake, Hannah | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
| York, Amber D. | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Abstract
These data are part of the Ocean Protein Portal "ProteOMZ" dataset v3 (https://proteinportal.whoi.edu/; Saito et al., 2019).
The raw mass spectra files were searched against SEQUEST within Proteome Discoverer v2.2 software. Processed files were then loaded into Proteome Software and protein and peptide reports as well as and fasta files were exported. The files were modified slightly to map to the Protein Portal data model for submission to BCO-DMO. The peptide report was too large to work with within Excel and was modified in Pandas/Python to produce a CSV file.
Preprocessing:
-Date, time, filter min, filter max, lat, lon, and cruise columns added based on information from the Falkor 160115 Event log and CTD log.
-Column names reformatted to comply with BCO-DMO standards.
Dataset Version 1: This file version (2022-06-03) replaces a previous revision of dataset version 1 from 2019-02-24.
* Data from source file "ProteOMZ_peptides_for_OPP.csv" was imported into the BCO-DMO data system for this dataset. This file "ProteOMZ_peptides_for_OPP.csv" is from Ocean Protein Portal "ProteOMZ" dataset v3 (file version 2022-06-03)
** In the BCO-DMO data system missing data identifiers are displayed according to the format of data you access. For example, in csv files it will be blank (null) values. In Matlab .mat files it will be NaN values. When viewing data online at BCO-DMO, the missing value will be shown as blank (null) values.
* Column names adjusted to conform to BCO-DMO naming conventions designed to support broad re-use by a variety of research tools and scripting languages. [Only numbers, letters, and underscores. Can not start with a number] e.g. date_y-m-d changed to date_ymd
* ISO DateTime with timezone (UTC) column added in ISO 8601 format from local date and times in HST.
* Data table attached to dataset as Data File:"737596_v1_proteomz-peptides.csv"
| File |
|---|
737596_v1_proteomz-peptides.csv (Comma Separated Values (.csv), 775.75 MB) MD5:2a69f9ed3937e0384f9d9b453108dd63 Primary data file for dataset ID 737596, version 1 |
| Parameter | Description | Units |
| sample_id | Unique sample name for the specific filter collected (station/depth/version if applicable) | unitless |
| MS_MS_sample_name | Unique name for the mass spec sample and run | unitless |
| protein_id | The specific name of the full protein length sequence assembled in the metagenome that was used for peptide identification | unitless |
| protein_molecular_weight_kDa | Molecular weight of the full length protein sequences | kDa |
| best_protein_id_probability | Probability of the protein assignment for the peptide | unitless |
| peptide_sequence | Amino acid sequence of the identified peptide. Unique Peptide sequence; this is the most unique identifier | unitless |
| peptide_start_index | Starting amino acid in the full length protein sequence for the identified peptide | unitless |
| peptide_stop_index | Stopping amino acid in the full length protein sequence for the identified peptide | unitless |
| plus2H_spectra_count | Number of identified spectral counts for a peptide of the +2 charge state | count |
| plus3H_spectra_count | Number of identified spectral counts for a peptide of the +3 charge state | count |
| plus4H_spectra_count | Number of identified spectral counts for a peptide of the +4 charge state | count |
| best_sequest_DCn_score | Delta CN score for peptide spectrum match (PSM). Metric of peptide quality | unitless |
| best_sequest_Xcorr_score | XCorr score for peptide spectrum match (PSM). Metric of peptide quality | unitless |
| median_retention_time | Median amount of time for a peptide in LC before it was identified via MS/MS | minutes |
| total_precursor_intensity | Total precursor intensity. | unitless |
| TIC | Total Ion Chromatogram (TIC). | unitless |
| spectral_count_sum | The sum of spectral counts for all peptide proton ionzation states. Sum of +2 +3 +4 data = total unnormalized spectral counts; Quantitative Value | count |
| other_protein_ids | All other possible proteins in the metagenome that contain the same peptide as the protein assigned. Other protein IDs from the FASTA file (see Related Datasets) | unitless |
| station_id | Station number | unitless |
| depth_m | Depth of sampling | meters |
| latitude_dd | Latitude of station | decimal degrees |
| longitude_dd | Longitude of station | decimal degrees |
| date_ymd | Date of sampling; (local time zone HST) | unitless |
| time_hms | Time of sampling; (local time zone HST) | unitless |
| minimum_filter_size_microns | Minimum filter size | microns |
| maximum_filter_size_microns | Maximum filter size | microns |
| cruise_id | The unique cruise identifier | unitless |
| ISO_DateTime_UTC | DateTime with timezone (UTC)of sampling in ISO 8601 format | unitless |
| Dataset-specific Instrument Name | Alpkem Autosampler |
| Generic Instrument Name | Alpkem RFA300 |
| Dataset-specific Description | Used in nutrient analysis |
| Generic Instrument Description | A rapid flow analyser (RFA) that may be used to measure nutrient concentrations in seawater. It is an air-segmented, continuous flow instrument comprising a sampler, a peristaltic pump which simultaneously pumps samples, reagents and air bubbles through the system, analytical cartridge, heating bath, colorimeter, data station, and printer. The RFA-300 was a precursor to the smaller Alpkem RFA/2 (also RFA II or RFA-2). |
| Dataset-specific Instrument Name | SeaBird SBE19 CTD |
| Generic Instrument Name | CTD Sea-Bird |
| Dataset-specific Description | Used for water sampling |
| Generic Instrument Description | Conductivity, Temperature, Depth (CTD) sensor package from SeaBird Electronics, no specific unit identified. This instrument designation is used when specific make and model are not known. See also other SeaBird instruments listed under CTD. More information from Sea-Bird Electronics. |
| Dataset-specific Instrument Name | Technicon AutoAnalyzer II |
| Generic Instrument Name | Technicon AutoAnalyzer II |
| Dataset-specific Description | Used to measure phosphate and ammonium |
| Generic Instrument Description | A rapid flow analyzer that may be used to measure nutrient concentrations in seawater. It is a continuous segmented flow instrument consisting of a sampler, peristaltic pump, analytical cartridge, heating bath, and colorimeter. See more information about this instrument from the manufacturer. |
| Dataset-specific Instrument Name | Trace Metal Rosette |
| Generic Instrument Name | Trace Metal Bottle |
| Dataset-specific Description | Used for nutrient sampling |
| Generic Instrument Description | Trace metal (TM) clean rosette bottle used for collecting trace metal clean seawater samples. |
FK160115
| Website | |
| Platform | R/V Falkor |
| Report | |
| Start Date | 2016-01-16 |
| End Date | 2016-02-11 |
| Description | Project: Using Proteomics to Understand Oxygen Minimum Zones (ProteOMZ)
More information is available from the ship operator at https://schmidtocean.org/cruise/investigating-life-without-oxygen-in-the...
Additional cruise information is available from the Rolling Deck to Repository (R2R): https://www.rvdata.us/search/cruise/FK160115 |
The ProteOMZ Expedition: Investigating Life Without Oxygen in the Pacific Ocean (ProteOMZ (Proteomics in an Oxygen Minimum Zone))
From Schmidt Ocean Institute's ProteOMZ Project page:
Rising temperatures, ocean acidification, and overfishing have now gained widespread notoriety as human-caused phenomena that are changing our seas. In recent years, scientists have increasingly recognized that there is yet another ingredient in that deleterious mix: a process called deoxygenation that results in less oxygen available in our seas.
Large-scale ocean circulation naturally results in low-oxygen areas of the ocean called oxygen deficient zones (ODZs). The cycling of carbon and nutrients – the foundation of marine life, called biogeochemistry – is fundamentally different in ODZs than in oxygen-rich areas. Because researchers think deoxygenation will greatly expand the total area of ODZs over the next 100 years, studying how these areas function now is important in predicting and understanding the oceans of the future. This first expedition of 2016 led by Dr. Mak Saito from the Woods Hole Oceanographic Institution (WHOI) along with scientists from University of Maryland Center for Environmental Science, University of California Santa Cruz, and University of Washington aimed to do just that, investigate ODZs.
During the 28 day voyage named “ProteOMZ,” researchers aboard R/V Falkor traveled from Honolulu, Hawaii to Tahiti to describe the biogeochemical processes that occur within this particular swath of the ocean’s ODZs. By doing so, they contributed to our greater understanding of ODZs, gathered a database of baseline measurements to which future measurements can be compared, and established a new methodology that could be used in future research on these expanding ODZs.
| Funding Source | Award |
|---|---|
| Gordon and Betty Moore Foundation: Marine Microbiology Initiative (MMI) | |
| Schmidt Ocean Institute (SOI) |
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