Moseley, Hunter

Owned by UKY CCS RCD
Jun 09, 2024
7 min read

Introduction to the Moseley Bioinformatics and Metabolomics Laboratory


Automated Analysis Tools for Magic Angle Spinning Solid State NMR Protein Resonance Data


Membrane proteins are essential for many biological functions. They comprise roughly one third of all sequenced genomes, and represent 70% of all current drug targets. However, fewer than 500 of the ~58,000 protein structure entries in the worldwide Protein Data Bank (PDB) involve integral membrane proteins as of June 2009. This is because they are difficult to crystallize for x-ray crystallographic studies and difficult to solubilize for solution nuclear magnetic resonance (NMR) studies. Magic-angle spinning solid-state NMR (MAS SSNMR) represents a fast developing experimental method that has great potential to provide structural and dynamics information of membrane proteins without the sample limitations of other techniques. We are developing automated analysis tools that will aid in the analysis of SSNMR data and specifically tailored for SSNMR data from membrane protein samples. Specifically our lab is focusing on developing and testing algorithms that will automate all analysis steps from raw SSNMR spectral data to protein resonance assignments for uniformly 13C/15N-labeled membrane proteins. This development will provide necessary analysis tools for expansion of MAS SSNMR and its application to membrane proteins into the broader biological community.

Automated Analysis and Prediction of Metal-Ion Coordination in Metalloproteins


Zinc ions bound to proteins serve a wide variety of catalytic, structural, and signal transduction purposes in biological systems. Zinc is the only metal ion seen in all six classes of enzymes. Iron and zinc are the most abundant trace elements in the human body. Roughly 2800 human proteins are predicted to be zinc-binding which equates to 10% of the human genome. Change in zinc trafficking is now associated with a variety of diseases, including Alzheimer’s, Parkinson’s, type 2 diabetes, and pathological conditions related to neural and myocardial ischemia. Recently, great strides were made in predicting zinc-binding from 3D structure and from sequence across many genomes. However, verification, classification, and sequence annotation of zinc-binding lags behind. Using nuclear magnetic resonance (NMR) chemical shift data, we have developed an analysis for identifying Zn-ligated cysteine residues and verifying zinc-binding.

Systems Biochemistry Approach to Metabolomics Data Analysis


With the improvements in mass spectrometry and nuclear magnetic resonance, there is an explosion of metabolomics data being collected on a variety of cells and tissue associated with human diseases, especially cancer. The weight of the data requires the development of automated analysis methods that are truly robust. We are developing ways to combine analyses of NMR and mass spectrometry metabolomics data that can lead to robust metabolite analysis. Such new methods will allow a wealth of metabolomics data to be brought into the analysis and deconvolution of metabolic pathways. For example, we are developing a combined simulated annealing and genetic algorithms method called GAIMS to analyze NMR and FT-ICR-MS isotopomer data of uridine diphospho-N-acetylglucosamine (UDP-GlcNAc) and uridine diphospho-N-acetylgalactosamine (UDP-GalNAc) extracted from tissue culture grown on 13-C enriched media. Both metabolites are used in O-glycosylation of proteins which serves cellular regulatory roles in nutrient sensing, protein degradation, and gene expression. We are applying these analyses to cancer tissue cultures treated with potential cancer chemoprevention agents to better understand how these agents change cancer cell metabolism.

Prototyping raw metabolomics data analysis tools


Computational Method:


Software:

Moseley Lab Publicly Available Software

SSNMR Assignment Software Suite (SASS)
High-throughput natural abundance correction software for stable isotope resolved metabolomics (SIRM) experiments

Personnel involved in project:

Dr. Hunter Moseley, PI, Molecular and Cellular Biochemistry
Dr. Robert Flight, Postdoc, Markey Medical Center
Jim Carreer, Staff, Markey Medical Center
Joshua Mitchell, Graduate, Biochemistry
http://bioinformatics.cesb.uky.edu/(external link)

Christian D Powell, Graduate, Cancer Center Core

Huan Jin, Graduate, Dept of Toxicology & Cancer Biology, 03/05/2021

Sean R Meredith, B & E Economics, Added 08/20/2021

Erik D Huckvale, Added on MCC cluster, 03/06/2023

Moiety modeling of FTMS metabolomics data

Computational Method:


Software:

Moseley Lab Publicly Available Software

SSNMR Assignment Software Suite (SASS)
High-throughput natural abundance correction software for stable isotope resolved metabolomics (SIRM) experiments

Personnel involved in project:

Dr. Hunter Moseley, PI, Molecular and Cellular Biochemistry
David Henderson, Grad Student
http://bioinformatics.cesb.uky.edu/(external link)

Lab Publications:

2022 

Huan Jin and Hunter N.B. Moseley. "md_harmonize: a Python package for atom-level harmonization of public metabolic data-bases" bioRxiv 2022.12.08.519680 (2022).

Robert M Flight, Praneeth S Bhatt, and Hunter N.B. Moseley. "Information-Content-Informed Kendall-tau Correlation: Utilizing Missing Values" bioRxiv 2022.02.24.481854 (2022).

2014

Abdallah M. Eteleeb, Hunter N.B. Moseley, and Eric C. Rouchka. “A Comparison of Combined P-value Methods for Gene Differential Expression Using RNA-Seq Data” Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology and Health Informatics, accepted.

Joshua M. Mitchell, Teresa, W-M. Fan, Andrew N. Lane, Hunter N.B. Moseley. "Development and In silico Evaluation of Large-Scale Metabolite Identification Methods using Functional Group Detection for Metabolomics" Frontiers in Genetics - Systems Biology 5, 237 (2014).

Richard M. Higashi, Teresa W-M. Fan, Pawel K. Lorkiewicz, Hunter N.B. Moseley, Andrew N. Lane. “Stable Isotope Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS” Mass Spectrometry Methods in Metabolomics, D. Raftery Editor, Humana Press. accepted.


2013

http://www.mdpi.com/2218-1989/3/4/853(external link)
29) William J. Carreer, Robert M. Flight, and Hunter N.B. Moseley. “A computational framework for high-throughput isotopic natural abundance correction of omics-level ultra-high resolution FT-MS datasets” Metabolites, 3, 853-866 (2013).

http://journals.sfu.ca/rncsb/index.php/csbj/article/view/csbj.201301006(external link)
28) Hunter N.B. Moseley. “Error Analysis and Propagation in Metabolomics Data Analysis” Comp Struct Biotech J, 4, e201301006 (2013).

2012

http://www.biomedcentral.com/1471-2105/13/S12/A1(external link)
27) Eric C. Rouchka, Robert M. Flight, and Hunter N.B. Moseley. “Proceedings of the Eleventh Annual UT-ORNL-KBRIN Bioinformatics Summit 2012” BMC Bioinformatics, 13, A1 (2012).

http://www.sciencedirect.com/science/article/pii/S0163725811002300(external link)
26) Teresa W-M. Fan, Pawel Lorkiewicz, Katherine Sellers, Hunter N.B. Moseley, Richard M. Higashi, and Andrew N. Lane. “Stable isotope-resolved metabolomics and applications to drug development” Pharmacology & Therapeutics, 133, 366 (2012).

2011

http://www.biomedcentral.com/content/pdf/1741-7007-9-37.pdf(external link)
25) Hunter N.B. Moseley, Andrew N. Lane, Alex C. Belshoff, Richard M. Higashi, and Teresa W-M. Fan. “A novel method for deconvoluting metabolic subunits from mass isotopologues in stable isotope resolved metabolomic experiments under non steady-state conditions: application to the biosynthesis of UDP-GlcNAc” BMC Biology, 9, 37 (2011).

http://bioinformatics.cesb.uky.edu/pub/Main/LabPublications/BIOINFORMATICS_2011_Proceedings_1082011.pdf(external link)
24) Hunter N.B. Moseley, Richard M. Higashi, Teresa W-M. Fan, and Andrew N. Lane. “Metabolic Modeling of Converging Metabolic Pathways: Analysis of Non-Steady State Stable Isotope-Resolve Metabolism of UDP-GlcNAc and UDP-GalNAc” BIOINFORMATICS 2011 – Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. Ed. Marco Pellegrini, Ana Fred, Joaquim Filipe, and Hugo Gamboa. SciTePress, Portugal, 108-115 (2011).

2010

http://www.springerlink.com/content/93t752457716k252/(external link)
23) Hunter N.B. Moseley, Lindsay J. Sperling, and Chad M. Rienstra. “Automated Protein Resonance Assignments of Magic Angle Spinning Solid-State NMR Spectra of β1 Immunoglobulin Binding Domain of Protein G (GB1)” J Biomol NMR 48, 123-128 (2010).

http://bioinformatics.cesb.uky.edu/pub/Main/LabPublications/BMC_Bioinformatics_11_1392010.pdf(external link)
22) Hunter N.B. Moseley. “Correcting for the Effects of Natural Abundance in Stable Isotope Resolved Metabolomics Experiments Involving Ultra-High Resolution Mass Spectrometry.” BMC Bioinformatics 11, 139-144 (2010).

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2757635/(external link)
21) Andrew N. Lane, Teresa W-M. Fan, Zhengzhi Xie, Hunter N.B. Moseley, and Richard M. Higashi. “Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR.” Anal. Chim. Acta. 651, 201-208 (2009).

http://link.springer.com/article/10.1007%2Fs10858-006-0027-5(external link)
20) Gregory J. Kornhaber, David Snyder, Hunter N.B. Moseley, and Gaetano T. Montelione. “Identification of Zinc-Ligated Cysteine Residues Based on 13Ca and 13Cb Chemical Shift Data.” J Biomol NMR 34, 259-269 (2006).

http://onlinelibrary.wiley.com/doi/10.1002/prot.20840/abstract(external link)
19) Michael Baran, Hunter N.B. Moseley, James M. Aramini, Marvin J. Bayro, Daniel Monleon, Jessica Lau, and Gaetano T. Montelione. “SPINS: A Laboratory Information Management System for Organizing and Archiving Intermediate and Final Results from NMR Protein Structure Determinations.” Proteins: Struct Funct Bioinformatics, 62,843-851 (2006).

http://www.sciencedirect.com/science/article/pii/S0076687905940056(external link)
18) Yuanpeng J. Huang, Hunter N.B. Moseley, Michael C. Baran, Cheryl Arrowsmith, Robert Powers, Roberto Tejero, Thomas Szyperski, and Gaetano T. Montelione. “An integrated platform for automated analysis of protein NMR structures.” Meth Enzymology 394, 111-141 (2005).


http://bioinformatics.cesb.uky.edu/pub/Main/LabPublications/Chemical_Reviews_104_35412004.pdf(external link)
17) Michael C. Baran, Janet Y. Huang, Hunter N.B. Moseley, and Gaetano T. Montelione. “Automated Analysis of Protein NMR Assignments and Structures.” Chemical Reviews 104, 3541-3556 (2004).

http://www.sciencedirect.com/science/article/pii/S1090780704001855(external link)
16) Hunter N.B. Moseley, Nadeem Riaz, James M. Aramini, Thomas Szyperski, and Gaetano T. Montelione. “A Generalized Approach to Automated NMR Peak List Editing: Application to Reduced Dimensionality Triple Resonance Spectra.” J Magn Reson 170, 263-277 (2004).

http://link.springer.com/article/10.1023/B%3AJNMR.0000015420.44364.06(external link)
15) Hunter N.B. Moseley, Gurmukh Sahota, and Gaetano T. Montelione, “Assignment Validation Software Suite for the Evaluation and Presentation of Protein Resonance Assignment Data.” J Biomol NMR 28, 341-355 (2004).

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2323888/(external link)
14) Deyou Zheng, Yuanpeng J. Huang, Hunter N.B. Moseley, Rong Xiao, James Aramini, G.V.T. Swapna, and Gaetano T. Montelione, “Automated protein fold determination using a minimal NMR constraint strategy.” Protein Science 12, 1232-1246 (2003).

http://link.springer.com/article/10.1023/A%3A1020940806745(external link)
13) Michael Baran, Hunter N.B. Moseley, Gurmukh Sahota, and Gaetano T. Montelione, “SPINS: Standardized ProteIn NMR Storage. A data dictionary and object-oriented relational database for archiving protein NMR spectra.” J Biomol NMR 24, 113-121 (2002).

http://link.springer.com/article/10.1023/A%3A1020499629298(external link)
12) Daniel Monleon, Kimberly Colson, Hunter N.B. Moseley, Clemens Anklin, Robert Oswald, Thomas A. Szyperski, and Gaetano T. Montelione, "Rapid Analysis of Protein Backbone Resonance Assignments Using Cryogenic Probes, Distributed Linux-based Computing, and Automated Spectral Analysis." J Struct Func Genomics 2, 93-101 (2002).

http://www.pnas.org/content/99/12/8009.full(external link)
11) Thomas Szyperski, Deok C. Yeh, Dinesh K. Sukumaran, Hunter N.B. Moseley, and Gaetano T. Montelione. “Reduced-dimensionality NMR Spectroscopy for High-Throughput Protein Resonance Assignment: Implementation and Automated Analysis.” Proc Natl Acad Sci USA 99, 8009-8014 (2002).

http://www.sciencedirect.com/science/article/pii/S0076687901393114(external link)
10) Hunter N.B. Moseley, Daniel Monleon, and Gaetano T. Montelione, "Automatic Determination of Protein Backbone Resonance Assignments from Triple Resonance NMR Data." Meth Enzymology 339, 91 (2001).

http://bioinformatics.cesb.uky.edu/pub/Main/LabPublications/Current_Opinion_in_Structural_Biology_9_6351999.pdf(external link)
9) Hunter N.B. Moseley and Gaetano T. Montelione. “Automated analysis of NMR assignments and structures for proteins.” Curr Opin Struct Biol 9, 635-642 (1999).

http://link.springer.com/chapter/10.1007%2F0-306-47084-5_7(external link)
8) N. Rama Krishna and Hunter N.B. Moseley. “Complete Relaxation and Conformational Exchange Matrix Analysis of NOESY Spectra of Reversibly Forming Ligand Receptor Complexes: Application to Transferred NOESY,” in “Structure Computation and Dynamics in Protein NMR.” Biological Mag Resonan Vol 17, editors: N. R. Krishna and L.J. Berliner, Plenum Press, New York (1999).

7) Hunter N.B. Moseley. “Implementation and Application of Complete Relaxation and Conformational Exchange Matrix Analysis of NOESY Spectra.” dissertation (1998).

http://pubs.acs.org/doi/abs/10.1021/bi970242k(external link)
6) Hunter N.B. Moseley, Weontae Lee, Cheryl H. Arrowsmith, and N. Rama Krishna. "Quantitative Determination of Conformational, Dynamic, and Kinetic Parameters of a Ligand Protein/DNA Complex from a CORCEMA Analysis of Intermolecular Transferred NOESY." Biochemistry 36, 5293 (1997).

http://link.springer.com/article/10.1007/BF00124470(external link)
5) Ernest V. Curto, Hunter N.B. Moseley, and N. Rama Krishna. “CORCEMA evaluation of the potential role of intermolecular transferred NOESY in the characterization of ligand receptor complexes.” J Comp Aided Molec Design 10, 361 (1996).

http://www.sciencedirect.com/science/article/pii/S1064186685711296(external link)
4) Hunter N.B. Moseley, Ernest V. Curto, and N. Rama Krishna. “Complete Relaxation and Conformational Exchange Matrix (CORCEMA) Analysis of NOESY Spectra of Interacting Systems: Two dimensional Transferred NOESY.” J Magn Reson B108, 243 (1995).

http://www.sciencedirect.com/science/article/pii/S1064186685710928(external link)
3) Patricia L. Jackson, Hunter N.B. Moseley, and N. Rama Krishna. “Relative Effects of Protein Mediated and Ligand Mediated Spin Diffusion Pathways on Transferred NOESY, and Implications on the Accuracy of the Bound Ligand Conformation.” J Magn Reson B107, 289 (1995).

http://www.sciencedirect.com/science/article/pii/S1058668784710448(external link)
2) Curtis C. Maier, Hunter N.B. Moseley, Shan Ren Zhou, John N. Whitaker, and J. Edwin Blalock. “Identification of Interactive Determinants on Idiotypic Anti idiotypic Antibodies through Comparison of Their Hydropathic Profiles.” Immunomethods 5, 107 (1994).

http://bioinformatics.cesb.uky.edu/pub/Main/LabPublications/Forth_Dimensions_8_4_81987.pdf(external link)
1) Rick L. Davies and Hunter N.B. Moseley. “Student Roots: Square root algorithm in Forth.” Forth Dimensions 8(4), 8-9 (1987).

Grants

Moseley, Hunter 1U24DK097215-01A1 Resource Center for Stable Isotope-Resolved Metabolomics - Informatics Core National Institute Diabetes & Digestive & Kidney 9/11/2013 - 8/31/2018 SCOPE
Moseley, Hunter DBI-1419282 CAREER: Developing Biochemoinformatics Tools for Large-Scale Metabolomics Applications National Science Foundation 11/1/2013 - 6/30/2018 $385,756
Moseley, Hunter 5U24DK097215-02 Resource Center for Stable Isotope-Resolved Metabolomivcs - Informatics Core National Institute Diabetes & Digestive & Kidney 9/11/2013 - 8/31/2018 SCOPE

Center for Computational Sciences