NIST is developing a portal to enable researchers to mine high-quality proteomic data from phylogenetically diverse species, to identify advantageous biological adaptations and drive human biomedical breakthroughs.
NIST is seeking partners to contribute samples, provide biological expertise, improve bioinformatic capabilities in non-model species, and inform new areas of biomedical research.
Comparative proteomics strives to gain insight into key underlying molecular changes that result in unique phenotypes across related taxa. Proteomic analysis complements comparative genomics by providing evidence of protein abundance, orthogonal to gene copy number and amount of transcript. In order to realize the potential of comparative proteomics in accelerating human biomedical discoveries, data across a swath of mammals must be acquired in a standardized fashion, though this has unique challenges at every step. NIST and its partners are uniquely situated to accomplish this by having access to unique and diverse samples, developing and defining standard protocols, acquiring data on state of the art instrumentation and providing a platform to disseminate the resulting data. This resource will be foundational to advances related to the bioeconomy and one health initiatives, and will provide an invaluable resource to biomedical researchers, governmental agencies, and software developers, accelerating development and discoveries.
Comparative proteomics is akin to how comparative medicine uses different animals as models of human disease, but in this case the goal of comparative proteomics (and biomimetic studies) is to study diverse species to better understand traits that may help mitigate injury that results in chronic human disease (e.g., acute kidney injury, stroke, myocardial infarction). Evolution of millions of species over billions of years has allowed a diversity of molecular solutions to exist to allow for adaptation and speciation. For instance, diving mammals are able to deal with ischemia/reperfusion stress and hibernating mammals avoid cardiac stress and avoid uremia. Due to the high degree of protein homology between mammalian species, humans often possess similar molecular machinery, and therefore insights are likely translatable to humans. The CoMPARe Program will generate data sets in a standardized fashion and develop a web portal for stakeholders to access and explore results in order to facilitate biomimetic discoveries and accelerate biomedical advances.
If you would like to learn more or assist with the project, please email benjamin.neely [at] nist.gov.
Neely BA, Prager KC, Bland AM, Fontaine C, Gulland FM, Janech MG. "Proteomic analysis of urine from California sea lions (Zalophus californianus): a resource for urinary biomarker discovery." J. Prot. Res. 17(9):3281-3291; bioRxiv doi: 10.1101/336867 (2018).
Neely BA, Ellisor DL, Davis WL. "Proteomics as a metrological tool to evaluate genome annotation accuracy following de novo genome assembly: a case study using the Atlantic bottlenose dolphin (Tursiops truncatus)". bioRxiv doi:10.1101/254250 (2018). [link]
Sobolesky P, Parry C, Boxall B, Wells R, Venn-Watson S, Janech MG. "Proteomic Analysis of Non-depleted Serum Proteins from Bottlenose Dolphins Uncovers a High Vanin-1 Phenotype." Scientific Reports 6:33879 (2016). [link]
Neely BA, Soper JL, Gulland FMD, Bell PD, Kindy M, Arthur JM, Janech MG. "Proteomic analysis of cerebrospinal fluid in California sea lions (Zalophus californianus) with domoic acid toxicosis identifies proteins associated with neurodegeneration." Proteomics 15(23-24):4051-63 (2015). [link]
Neely BA, Ferrante JA, Chaves JM, Soper JL, Almeida JS, Arthur JM, Gulland FMD, Janech MG. "Proteomic analysis of plasma from California sea lions (Zalophus californianus) reveals apolipoprotein E as a candidate biomarker of chronic domoic acid toxicosis." PLoS One 10(4):e0123295 (2015). [link]
Neely BA, Carlin KP, Arthur JM, McFee WE, Janech MG. "Ratiometric measurements of adiponectin by mass spectrometry in bottlenose dolphins (Tursiops truncatus) with iron overload reveal an association with insulin resistance and glucagon." Front Endocrinol 4:132 (2013). [link]