faculty

Michael MacCoss

maccoss@uw.edu

University of Washington, 

Computational Biology

Developmental Biology, Stem Cells & Aging

Genetics, Genomics & Evolution

Development and application of proteomics technologies

Faculty Contact Information

Building: Foege Room: S113 Box: 355065 Phone: 206-616-7451 http://maccosslab.org/

Lab Information

Location: University of Washington Building: Foege Room: S111 Phone: 206-616-9023 http://maccosslab.org/

Accepting Students For:

Rotation, Autumn
Rotation, Spring
Rotation, Summer
Rotation, Winter
Permanent

Publications

The following publications were retrieved from PubMed:

Autophagy accounts for approximately one-third of mitochondrial protein turnover and is protein selective.

Vincow ES, Thomas RE, Merrihew G, Shulman NJ, Bammler TK, MacDonald JW, MacCoss MJ, Pallanck LJ.

Autophagy. 2019 Mar 13;

Improving Precursor Selectivity in Data-Independent Acquisition Using Overlapping Windows.

Amodei D, Egertson J, MacLean BX, Johnson R, Merrihew GE, Keller A, Marsh D, Vitek O, Mallick P, MacCoss MJ.

J Am Soc Mass Spectrom. 2019 Jan 22;

Initial Guidelines for Manuscripts Employing Data-independent Acquisition Mass Spectrometry for Proteomic Analysis.

Chalkley RJ, MacCoss MJ, Jaffe JD, Röst HL.

Mol Cell Proteomics. 2019 Jan; 1(18)1-2

Improving mitochondrial function with SS-31 reverses age-related redox stress and improves exercise tolerance in aged mice.

Campbell MD, Duan J, Samuelson AT, Gaffrey MJ, Merrihew GE, Egertson JD, Wang L, Bammler TK, Moore RJ, White CC, Kavanagh TJ, Voss JG, Szeto HH, Rabinovitch PS, MacCoss MJ, Qian WJ, Marcinek DJ.

Free Radic Biol Med. 2018 Dec 28; (134)268-281

Time-resolved interaction proteomics of the GIGANTEA protein under diurnal cycles in Arabidopsis.

Krahmer J, Goralogia GS, Kubota A, Zardilis A, Johnson RS, Song YH, MacCoss MJ, Le Bihan T, Halliday KJ, Imaizumi T, Millar AJ.

FEBS Lett. 2019 Feb; 3(593)319-338

Research Summary

The focus of our research is in the development of stable isotope and mass spectrometry based approaches to improve our understanding of biology on a molecular, cellular, and whole organism level. Presently, individuals in the laboratory are working on technology for 1) automating biochemical sample preparation methods for the analysis of protein mixtures; 2) increasing the dynamic range of liquid chromatography-mass spectrometry for the analysis of peptides; and 3) developing computational tools for the automated conversion of mass spectrometry data into biologically meaningful results.