Development of an Ocean Protein Portal for Interactive Discovery and Education

Proteins are critical in catalyzing chemical reactions, forming key cellular structures, and in regulating cellular processes. Investigation of marine microbial proteins by metaproteomics methods enables the discovery of numerous aspects of microbial biogeochemistry processes. However, these datasets present big-data challenges as they often involve many samples collected across broad geospatial and temporal scales, resulting in thousands of protein identifications, abundances, and corresponding annotation information. The Ocean Protein Portal (OPP) was created to enable data sharing and discovery among multiple scientific domains and serve both research and education functions. The portal focuses on three use case questions: “Where is my protein of interest?”, “Who makes it?”, and “How much is there?”, and provides profile and section visualizations, real-time taxonomic analysis, and links to metadata, sequence analysis, and other external resources to enabling connections to be made between biogeochemical and proteomics datasets.

[1]  Cheryl A Kerfeld,et al.  Identification and structural analysis of a novel carboxysome shell protein with implications for metabolite transport. , 2009, Journal of molecular biology.

[2]  Rong Wang,et al.  The APEX Quantitative Proteomics Tool: Generating protein quantitation estimates from LC-MS/MS proteomics results , 2008, BMC Bioinformatics.

[3]  Patrick G. A. Pedrioli Trans-Proteomic Pipeline: A Pipeline for Proteomic Analysis , 2010, Proteome Bioinformatics.

[4]  Ramunas Stepanauskas,et al.  Organic matter processing by microbial communities throughout the Atlantic water column as revealed by metaproteomics , 2017, Proceedings of the National Academy of Sciences.

[5]  A. Halpern,et al.  The Sorcerer II Global Ocean Sampling Expedition: Northwest Atlantic through Eastern Tropical Pacific , 2007, PLoS biology.

[6]  Mak A. Saito,et al.  Abundant nitrite-oxidizing metalloenzymes in the mesopelagic zone of the tropical Pacific Ocean , 2020, Nature Geoscience.

[7]  Joe Futrelle,et al.  Harnessing the Power of Scientific Python to Investigate Biogeochemistry and Metaproteomes of the Central Pacific Ocean , 2018 .

[8]  David R. Goodlett,et al.  Protein recycling in Bering Sea algal incubations , 2014 .

[9]  William Stafford Noble,et al.  An Alignment-Free "Metapeptide" Strategy for Metaproteomic Characterization of Microbiome Samples Using Shotgun Metagenomic Sequencing. , 2016, Journal of proteome research.

[10]  Michael J MacCoss,et al.  Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry , 2018, Nature Communications.

[11]  Ludovic C. Gillet,et al.  Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis* , 2012, Molecular & Cellular Proteomics.

[12]  Anitra E. Ingalls,et al.  Suspended marine particulate proteins in coastal and oligotrophic waters , 2015 .

[13]  P. Bork,et al.  A global ocean atlas of eukaryotic genes , 2018, Nature Communications.

[14]  David R Goodlett,et al.  Identifying and tracking proteins through the marine water column: insights into the inputs and preservation mechanisms of protein in sediments. , 2012, Geochimica et cosmochimica acta.

[15]  B. Searle Scaffold: A bioinformatic tool for validating MS/MS‐based proteomic studies , 2010, Proteomics.

[16]  Michael J MacCoss,et al.  Multiplexed peptide analysis using data-independent acquisition and Skyline , 2015, Nature Protocols.

[17]  Richard D. Smith,et al.  Transport functions dominate the SAR11 metaproteome at low-nutrient extremes in the Sargasso Sea , 2009, The ISME Journal.

[18]  Ljiljana Paša-Tolić,et al.  Metaproteomics reveals differential modes of metabolic coupling among ubiquitous oxygen minimum zone microbes , 2014, Proceedings of the National Academy of Sciences.

[19]  E. Delong,et al.  The Microbial Engines That Drive Earth's Biogeochemical Cycles , 2008, Science.

[20]  R. Azencott,et al.  Improvement of OMSSA for High Accuracy MS/MS Data. , 2014 .

[21]  Giacomo R. DiTullio,et al.  Colony formation in Phaeocystis antarctica: connecting molecular mechanisms with iron biogeochemistry , 2018, Biogeosciences.

[22]  I-Min A. Chen,et al.  IMG/M: a data management and analysis system for metagenomes , 2007, Nucleic Acids Res..

[23]  Peer Bork,et al.  Open science resources for the discovery and analysis of Tara Oceans data , 2015, Scientific Data.

[24]  S. Kravitz,et al.  CAMERA: A Community Resource for Metagenomics , 2007, PLoS biology.

[25]  Alexander Dorsk,et al.  Needles in the blue sea: Sub‐species specificity in targeted protein biomarker analyses within the vast oceanic microbial metaproteome , 2015, Proteomics.

[26]  Paul Bachelerie,et al.  The Ocean Gene Atlas: exploring the biogeography of plankton genes online , 2018, bioRxiv.

[27]  David R Goodlett,et al.  Comparative metaproteomics reveals ocean-scale shifts in microbial nutrient utilization and energy transduction , 2010, The ISME Journal.

[28]  Jing Chen,et al.  Community cyberinfrastructure for Advanced Microbial Ecology Research and Analysis: the CAMERA resource , 2010, Nucleic Acids Res..

[29]  Nicholas R. Bates,et al.  Overview of the US JGOFS Bermuda Atlantic Time-series Study (BATS): a decade-scale look at ocean biology and biogeochemistry , 2001 .

[30]  Alexey I Nesvizhskii,et al.  MSFragger: ultrafast and comprehensive peptide identification in shotgun proteomics , 2017, Nature Methods.

[31]  J. Yates,et al.  An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database , 1994, Journal of the American Society for Mass Spectrometry.

[32]  William Stafford Noble,et al.  Estimating relative abundances of proteins from shotgun proteomics data , 2012, BMC Bioinformatics.

[33]  Adam Shepherd,et al.  METATRYP v 2.0: Metaproteomic Least Common Ancestor Analysis for Taxonomic Inference Using Specialized Sequence Assemblies—Standalone Software and Web Servers for Marine Microorganisms and Coronaviruses , 2020, Journal of proteome research.

[34]  D. Hasselquist,et al.  No evidence that carotenoid pigments boost either immune or antioxidant defenses in a songbird , 2018, Nature Communications.

[35]  Lindsay K. Pino,et al.  The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. , 2020, Mass spectrometry reviews.

[36]  Luis Mendoza,et al.  Trans‐Proteomic Pipeline, a standardized data processing pipeline for large‐scale reproducible proteomics informatics , 2015, Proteomics. Clinical applications.

[37]  E. Marcotte,et al.  Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation , 2007, Nature Biotechnology.

[38]  Adam Shepherd,et al.  METATRYP v 2.0: Metaproteomic Least Common Ancestor Analysis for Taxonomic Inference Using Specialized Sequence Assemblies - Standalone Software and Web Servers for Marine Microorganisms and Coronaviruses , 2020, bioRxiv.

[39]  J. Eng,et al.  Comet: An open‐source MS/MS sequence database search tool , 2013, Proteomics.

[40]  D. N. Perkins,et al.  Probability‐based protein identification by searching sequence databases using mass spectrometry data , 1999, Electrophoresis.

[41]  R. Beavis,et al.  A method for reducing the time required to match protein sequences with tandem mass spectra. , 2003, Rapid communications in mass spectrometry : RCM.

[42]  Michael W. Lomas,et al.  Sea Change: Charting the Course for Biogeochemical Ocean Time-Series Research in a New Millennium , 2013 .

[43]  P. Huybers,et al.  The Little Ice Age and 20th-century deep Pacific cooling , 2019, Science.

[44]  Mak A. Saito,et al.  Methionine synthase interreplacement in diatom cultures and communities: Implications for the persistence of B12 use by eukaryotic phytoplankton , 2013 .

[45]  Etienne Yergeau,et al.  Metaproteomics of aquatic microbial communities in a deep and stratified estuary , 2015, Proteomics.

[46]  D. Shultis,et al.  Outer Membrane Active Transport: Structure of the BtuB:TonB Complex , 2006, Science.

[47]  Mak A Saito,et al.  Characterization of the Fe metalloproteome of a ubiquitous marine heterotroph, Pseudoalteromonas (BB2-AT2): multiple bacterioferritin copies enable significant Fe storage. , 2020, Metallomics : integrated biometal science.

[48]  Ken Youens-Clark,et al.  iMicrobe: Tools and data-driven discovery platform for the microbiome sciences , 2019, GigaScience.

[49]  Giacomo R. DiTullio,et al.  Multiple nutrient stresses at intersecting Pacific Ocean biomes detected by protein biomarkers , 2014, Science.

[50]  Matthew L. Baker,et al.  Structural Changes in a Marine Podovirus Associated with Release of its Genome into Prochlorococcus , 2010, Nature Structural &Molecular Biology.

[51]  Elizabeth B. Kujawinski,et al.  Environmental metabolomics: Analytical strategies , 2015 .

[52]  Benjamin A. Neely,et al.  Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing. , 2019, Journal of proteome research.

[53]  William Stafford Noble,et al.  Metaproteomics reveal that rapid perturbations in organic matter prioritize functional restructuring over taxonomy in western Arctic Ocean microbiomes , 2019, The ISME Journal.