College of Medicine Research Core Facilities
The UC College of Medicine houses a number of research core facilities designated as core service centers. These facilities exist within multiple departments but are collectively supported by the College of Medicine, Office of Research through the Associate Dean for Research Core Facilities: Ken Greis, PhD. (email@example.com; Tel: 515-558-7012).
The service center designation signifies that the rates charged by each of these facilities have been reviewed and approved by the UC government cost compliance office, thus the service fees can be cross-charged to federal grants and contracts. Details related to the services offered and the internal rates for each of the cores are provided below. Since these rates are substantially subsidized by the University, external investigators should contact individual core directors to get a rate quote.
Resources to offset some of the cost of the core services may be available through a variety of centers and institutes across UC depending on an investigator’s affiliation. Information related to some of those opportunities and the website links are provided below:
- Center for Clinical and Translational Science and Training (CCTST) Just-in-Time Core Support
- Cincinnati Cancer Center (CCC) Just-in-Time Shared Facilities Award
- Center for Environmental Genetics (CEG) Integrative Technologies Support
UC Proteomics Laboratory (UCPL)
- Comparative protein profiling:
- Comparative MS-based profiling using Label-Free and Isotope Tagging methods (SILAC, TMTs)
- Protein identification by Mass Spectrometry
- Characterization of Protein Complexes
- Confirming and Mapping Protein Modification sites
Advanced Services/Collaborative Projects
- Global Profiling of Protein Modifications (e.g. phospho, ubiquitin)
- Complex MRM quantitation of targeted proteins
- Enzyme assays and inhibitor screening by MS
Location & Hours:
The UCPL is located in the Vontz Center for Molecular Studies 1208-1216. Staff are typically available M-F, 9A-6P to accept samples, but please call 513 558-4057 to confirm. First time customers should include a discussion with the director or associate director prior to preparing samples.
For manuscripts, please include the following statements as appropriate or consult with the director regarding authorship:
- Mass spectrometry data were collected and analyzed in the UC Proteomics Laboratory under the direction of KD Greis, PhD.
- Funding for the Sciex 5600 nanoLC-MS/MS system was obtained in part through an NIH shared instrumentation grant (S10 RR027015-01)
- Funding for the Thermo Orbitrap Eclipse nanoLC-MS/MS system was obtained in part through an NIH high end instrumentation grant (S10OD026717-01)
Specific instrumentation and facilities information for your grant submission will be supplied by the core director. Please contact the core director at least two weeks before the grant is due to ensure proper alignment of the core infromation with in your grant needs.
Protein Concentration by Pierce 660 assay per sample
Protease digestion and peptide recovery per sample
Mini 1D gel protein separation per gel
Mini 2D gel protein separation per gel
Gel Stain (Silver Coomassie) per gel
Sample preparation by buffer exchange per sample
Preparative High pH RP separation of peptides with fraction collection per sample
MALDI-TOF of protein or peptides
Orbitrap ECLIPSE LC-MS instrument time per hr
Orbitrap FUSION-LUMOS LC-MS instrument time per hr
5600 Triple-TOF instrument time per hr
Data Processing and Report Generation per hour
Research Staff hourly rate
Materials and reagents pass through cost
Affinity capture for protein interaction
Protein interactions can be determine by capturing protein complexes followed by digestion and mass spectrometry
Mapping protein modifications
MS/MS fragmentation can be used to confirm peptides sequences and sites of modification. Shown here is an example of mapping phosphorylation (left) and a covalent-enzyme inhibitor (right).
2D gel profiling and protein ID by MS
Proteins can be separated by 2D gels and visualized by silver-stain (left). Coupled with image analysis, protein changes among sample groups can be determined. Protein digestion and mass spectrometry-based sequencing (middle) coupled with database searching (right) can be used to identify the proteins.
Accurate protein mass and glycoform distribution
Electrospray-Tof MS can be used to get accurate masses of intact proteins or mixtures of proteins. In this example, accurate mass measurements confirm the various standard fragments of a monoclonal antibody as well as the distribution of the glycoforms on the Fc/2 fragment for QA of a therapeutic antibody.
MALDI MS-based enzyme assays and inhibitor screening
MALDI-MS can be used to measure the conversion of a substrate to a product. In this case a peptide converted to a phosphorylated peptide by a kinase (left). With increasing concentrations of an inhibitor, the degree of inhibition and ultimately the IC50 value for the inhibitor can be measured (right). HTS applications are possible as these measurements can be made in a few seconds per sample.
iTRAQ-labeling for quantitative profiling
Relative levels of proteins from multiple sample groups can be evaluated as a single sample after digestion of the proteins and tagging with MS/MS reporter reagents (iTRAQ) followed by nanoLC-MS/MS for protein identification (left). The relative amount of each peptide is determined by the ratio of the reporter tags (114, 115, 116, 117). A table of the significant up- and down-regulated urine proteins in steroid resistant nephronic syndrome (right).
Label-Free Quantitation by SWATH-MS.
Performance of the SWATH-MS workflow to compare urinary extracellular vesicles. (a). Quantitative data of 888 proteins in ELVs, MVs and UP samples (3 replicates for each sample) were demonstrated in a heat map manner. The scale of SWATH-estimated protein intensity showed the relative amount of original data after Total Area Sum (TAS) normalization. The missing values (6 out of 7,992 data across all replicates) were labeled in black color. (b). Numbers of unique peptide per protein. (c). Pearson correlation of nine sample replicates based on 888 expression data. Each number in the sample matrix was the correlation coefficient (r), in which r=1 was a perfect positive relationship, and r=0 showed no association between a sample pair. (d). The coefficient of variation (CV) of 888 protein quantitation in urinary ELVs, in which the median-CV was 7.7%.
Two Sciex 5600+ Quadrapole-Tof Mass Spectrometer w/Eksigent nanoLC-Ultra 2D System
One system is configured with an Eksigent nanoflow LC system and a nanospray interface primarily for proteomics application. It offers the hybrid capabilities for high resolution and high sensitivity profiling, characterization of compounds in complex mixtures, and also high selectivity and sensitivity for quantitation of compounds in complex mixtures by monitoring fragmentations transitions either in selected reaction monitoring (SRM) or multiple reaction monitoring (MRM) modes. With attomole sensitivity, this system is optimized for quantitative proteomics profiling using label free (e.g. DIA, SWATH), isotope tagging methods (e.g. SILAC, iTRAQ) and quantitation of specific proteins (as peptide surrogates) from complex mixtures using SRM/MRM workflows. The second system in coupled with the Dionex 3000 UHPLC units running at more conventional microflow rates for targeted quantitation analyses using SRM/MRM workflows for peptides and small molecule quantitation.
Sciex 4800 MALDI-TOF/TOF MS
The 4800 instrument is the primary instrument in the proteomics laboratory used for core services that require protein identification from single bands or spot from gels. The attomole sensitivity and high repetition laser for fast data collection make it the ideal option for protein identification including protein complexes captured by affinity methods. This instrument is also the primary system used for the rapid readout of enzyme assays and inhibitor screening studies.
Beckman Coulter NX Liquid Handling Workstation
Beckman Coulter NX Liquid Handling Workstation
This system is use for samples preparation of enzyme reactions for MS-bases screening activities.
Computational Systems and Software for Data Analysis include:
- 10 terrabyte general file server for automatic backup and archival of all proteomics data and reports.
- 8-processor MASCOT server for high throughput identification and quantification of proteins.
- 12-processor system running Sciex ProteinPilot software for relative quantitation of label-free or isotope tagged peptides
- 8-processor system running the Thermo Proteome Discoverer suite of data analysis software.
Thermo Oribitrap Eclipse Tribrid mass spectrometer
This newest system acquired via an NIH S10 instrumentation grant in October of 2019 is configured with a Dionex Ultimate 3000 RSLCnano LC and a FAIMS Pro High Field Asymmetric Waveform Ion Mobility Spectrometry Interface to allow for maximum separation and detection of peptides in complex mixtures. This system is ideally suited for high throughput and high sensitivity comparative quantitative studies using Tandem Mass Tag (TMT) reagents or label-free quantitation methods. With up to 5X better sensitivity compared to the Quadrupole-Tof systems in the lab, this system is used for global profiling of protein modifications (e.g. phosphorylation, ubiquitination) and for multiplex profiling studies of large number of samples.
Thermo Oribitrap Fusion Lumos Tribrid mass spectrometer
This high resolution mass spectrometer coupled with a Thermo Vanquish UHPLC system. This system is primarily dedicated to the development of new metabolomics profiling capabilities include steady state and metabolic flux analysis, as well as lipids, nucleosides, fatty acids and other metabolites. With its high resolution accurate mass (HRAM), it is ideally suited for structural elucidate of small molecule via intact mass and fragmentation spectra for metabolomics needs. With its rapid duty cycle and attomole sensitivity, it is dedicated for use to evaluate and quantify very complex sample mixtures for Metabolomics capabilities
1. How do I submit a sample for analysis.
In order to ensure the best chance of success for all samples submitted to proteomics lab for analysis, all new customers should contact the proteomics director for a consultation prior to submitting samples. Please read the other FAQ's below since these are intended to address many of the common issues. During the consultation, the director will ask a number of question to be sure that the analyses requested are both appropriate to meet the investigators needs and available within the proteomics research community. If the request is outside the scope of the laboratory capability, the director will recommend other options for the investigator. The goal of this consultation is provide the investigator with realistic expectation of what can be done, the time it will take, and the cost of the analyses
2. How much protein do I need to identify it my mass spectrometer?
We can identify a protein by trypsin digestion and mass spectrometry from as little as a few fmoles of a purified protein. From a 1D gel, considering the losses that one takes in the digestion and recovery of peptides from the gel, we can often identify most proteins that are distinctly visible with a MS-compatible silver stain. For 2D gels this is a bit trickier since the protein gets concentrated into such a small spot that sometimes we get a nicely detected protein spot that just does not liberate sufficient peptides after digestions for identification. The truth is that it is very dependent on the structure and sequence of the protein.
3. I have heard that protein ID from a silver stained gel is not feasible, is this true?
The answer is NO. As indicated above, we routinely identify protein from silver-stained gels; however, there are a couple precautions that need to be followed. First, one must use an MS-compatible silver-stain. There are a number of commercial staining kits marketed as MS-compatible and to our knowledge they all work. You can still make your own reagents; you just have to eliminate steps that include glutaraldehyde fixation because glutaraldehyde crosslinks the proteins and makes it very difficult to recover peptides from the gel. A second concern is that one must take extreme care to avoid handling the gels, reagents and/or stains without gloves for fear of introducing keratin contamination (see FAQ 7) which can mask the detection of low level proteins.
4. I have a protein that gives a nice band by western blot; can I identify it my MS?
Like many questions, the answer here depends on a number of factors. First, one must keep in mind that detection with antibodies and chemiluminescence reagents only require a few hundred molecules (of course depending on the quality and specificity of your antibody). To detect proteins at the low femtomole range by MS requires about 1 billion molecules. Thus a protein readily detected by Western blot may not be in sufficient quantities to identify by MS. Furthermore, antibody detection is typically used on complex protein mixtures because there is no need to purify the protein of interest prior to Western blot to get good signals. Unfortunately if the target protein is buried under a number of more abundant proteins at the same mobility position on the gel, then these more abundant proteins may mask the MS-detection and identification of the protein of interest. Having said all this, we and others have been most successful at identifying proteins that interact with antibodies by using immobilized antibodies to enrich for your protein of interest (see FAQ 5 for details). When done correctly this has two advantages; first, one selectively enriches for the protein(s) of interest, and secondly, the protein(s) can be eluted from the immobilized antibody without releasing the Ig heavy and light chains thus minimizing interference on the gel and mass spectrometer.
5. What about protein identification from immunoprecipitations?
IPs, like western blots, can be a bit tricky, but can be effectively coupled with mass spectrometry to identify the target protein and other proteins that interact with the target protein. The key here is that you must remember that the most abundant protein in an IP will be your antibody, thus when you run the resulting pull-down on a gel, you will get huge bands for the Ig heavy and light chains that often mask the protein(s) of interest. This is a more difficult challenge for polyclonal antiserum since you not only have your antibody of interest, but also all other antibodies in the serum. In all cases, the best success is achieved by immuno-enriching your Ig of interest then immobilizing it on a resin. That way you can capture and elute your protein(s) of interest without liberating the interfering heavy and light chains. We have identified interacting protein in a number of biological systems for several investigators using these methods. One final note here; Ig purification, generation of the immobilized column and collection of the enriched fractions are all functions carried out in the investigators laboratory. The proteomics lab personnel generally take over just before or after running the 1D gel. Consult the Proteomics Director for additional details.
6. I think my protein has modifications; can you identify all of the sites?
Mass spectrometry is an ideal tool for mapping sites of post-translational modifications (PTM); however, the success will depend on the type of modification, the amount of protein available, the purity of the protein, the sequence of the protein, and the stoichiometry of the modification. I'll use phosphorylation as an example since it represents the majority of inquiries. Let's say we have a protein that we know is phosphorylated (e.g. antibody reactivity (+/-) phosphatase treatment) and we would like to know what sites are modified. First, we will need enough protein (generally low µg amounts) of sufficient purity to digest and recover peptides containing potential sites of modification. This is often the most difficult task when working with low level regulatory proteins. Secondly, the phosphorylation at a given site of the protein must be of sufficient abundance to be detected. In other words, if our limit of detection for peptides is 5 fmole and your stoichiometry of phosphorylation at a given site is 10% occupancy, then we would need a minimum of 50 fmoles of total peptide to even have a change to identity the phosphopeptide or site of phosphorylation. Adding to this challenge is the fact the phosphopeptides are generally more difficult to detect and sequence compare to un-modified peptides due to ionization efficiency issues, thus you may need to have 20-50X more material to detect and sequence a phosphopeptide at a 10% occupancy rate compared than its un-modified counterpart. Lastly, this may be obvious, but I get this question all the time, "You found two sites of phosphorylation, so can I report that they are the only sites modified under my conditions?" The answer here is a resounding NO! The mass spectrometer can only positively confirm a modification, it cannot completely rule out other modifications that go undetected. If the sequence of the protein is such that a site of modification is liberated as a tryptic peptide that is outside the mass range of the instrument (generally below 600Da or above about 4000Da) then it will go undetected. Furthermore, an undetected site of modification may just have a stoichiometry that is below our current detection limits. Thus we can only report what is detected in the mass spectrometry. Having said all this, we have successfully identified various sites of modification including phosphorylation. We have a number of methods to enrich for phosphopeptides to increase our chances of success, but we may have to start with µg amounts of a fairly pure protein.
7. My results had lots of keratin contamination; what does this mean?
Human keratin is a ubiquitous contaminant that originates from sloughed off skin (a major component of common dust-kind of gross by true). It can be inadvertently introduced from contaminated reagent, stains, handling gels without gloves or reuse of reagents. One speck of dust when digested with trypsin can release peptides from a whole series of keratin-family proteins that so overwhelm the spectrum that peptides from other proteins may not be detected. In the proteomics lab, we take special precautions to minimize keratin contamination, thus we prefer to have investigators submit their entire gel and we will process the protein spots or bands in our lab. These precautions are particularly important for silver-stained gels since the protein of interest is typically near the lower limit of detection to start with. Even with these precautions in place, keratin contamination still turns up from time-to-time and is reported as such
8. Why did I get multiple proteins identified from one band; can you tell me which is more abundant?
It is not uncommon to get multiple proteins identified from a single band from a 1D gel. Even with the resolving power on 2D gels, we often detect more than one protein in these samples. This occurs both because of the sensitivity of the mass spectrometer and the fact that sometimes more than one protein has the same or very similar migration properties. The good news is that in most cases, we can provide a pretty good idea about which protein is most abundant in the sample based on the signal intensity of the peptides from each of the proteins. While this is far from an exact measurement (since extraction efficiencies of peptides from the gel and ionization efficiencies in the mass spectrometer can confound the issue) in most cases we have sufficient data to inform the investigator which of the proteins identified accounted for the majority of the material detected in the gel by the staining protocol.
Uehara Y, Nikolaidis NM, Pistick LB, Wu H, Yu JJ, Zhang E, Hasegawa Y, Tanake Y, Noel JG, Gradner JC, Kopras EJ, Haffey WD, Greis KD, Guo J, Woods JC, Wikenheiser-Brokamp KA, Zhao S, Xu Y, Kyle KE, Ansong C, Teitelbaum SL, Inoue Y, Altinisik G, McCormack FX. Novel insights into pulmonary phosphate homeostasis and osteoclastogenesis emerge from the study of pulmonary alveolar microlithiasis (2021) bioRXiv https://doi.org/10.1101/2021.07.11.451970
Ge C, Vilfranc CL, Che L, Pandita RK, Hambarde S, Andreassen PR, Niu L, Olowokure O, Shah S, Waltz SE, Zou L, Wang J, Pandita TK, Du C. The BRUCE-ATR Signaling Axis Is Required for Accurate DNA Replication and Suppression of Liver Cancer Development (2019) Hepatology. Jun; 69 (6) :2608-2622
Forster CS, Haffey WD, Bennett M, Greis KD, Devarajan P. Identification of Urinary CD44 and Prosaposin as Specific Biomarkers of Urinary Tract Infections in Children With Neurogenic Bladders (2019) Biomark Insights. 2019 Mar 15;14:1177271919835570. doi: 10.1177/1177271919835570.
Dwivedi P, Muench D, Wagner M, Azam M, Grimes HL, Greis KD. Phospho serine and threonine analysis of normal and mutated granulocyte colony stimulating factor receptors. (2019) Sci Data, 6(1):21. doi: 10.1038/s41597-019-0015-8.
Yuan L, Mishra R, Patel H, Abdulsalam S, Greis KD, Kadekaro AL, Merino EJ, Garrett JT. Utilization of Reactive Oxygen Species Targeted Therapy to Prolong the Efficacy of BRAF Inhibitors in Melanoma (2018). J. Cancer. 9(24): 4465-4476. doi: 10.7150/jca.27295
Kirley TL, Greis KD, Norman AB. Domain unfolding of monoclonal antibody fragments revealed by non-reducing SDS-PAGE. (2018) Biochem Biophys Reports, 16, 138-144.
Chutipongtanate S and Greis KD. Multiplex Biomarker Screening Assay for Urinary Extracellular Vesicles Study: A Targeted Label-Free Proteomic Approach (2018) Sci Report,8:15039| DOI:10.1038/s41598-018-33280-7
Turnier JL, Brunner HI, Bennett M, Aleed A, Gulati G, Haffey WD, Thornton S, Wagner M, Devarajan P, Witte D, Greis KD, Aronow B. Discovery of SERPINA3 as a candidate urinary biomarker of lupus nephritis activity. (2019) Rheumatology, 58(2):321-330
Swertfeger DK, Rebholz S, Li H, Shah AS, Davidson WS, Lu LJ. Feasibility of a plasma bioassay to assess oxidative protection of low-density lipoproteins by high-density lipoproteins (2018) Journal of clinical lipidology.12 (6) :1539-1548.
Patel ZH, Lu X, et al. A plausibly causal functional lupus-associated risk variant in the STAT1-STAT5 locus (2018) Human Molecular Genetics, 27(13), 2392-2404.
Dwivedi P, Muench D, Wagner M, Azam M, Grimes HL, Greis KD. Time resolved quantitative phospho-tyrosine analysis reveals Bruton?s Tyrosine kinase mediated signaling downstream of the mutated granulocyte-colony stimulating factor receptors (2019). Leukemia 33(1):75-87. doi: 10.1038/s41375-018-0188-8.
Funk AJ, Labilloy G, Reigle J, Alnafisah R, Heaven MR, Roberts R, Shamsaei B, Greis KD, Meller J, McCullumsmith RE. Region-Specific PSD-95 Interactomes Contribute to Functional Diversity of Excitatory Synapses in Human Brain. (2020) bioRXiv https://doi.org/10.1101/2020.05.04.076844
Huang H, Weng H, Sun W, Qin X, Shi H,Wu,H, Zhao BS, Mesquita A, Liu C, Yuan CL, Hu Y-C, Huttelmaier S, Skibbe JR, Su R, Dong L, Sun M, Ki C, Nachtergaele S, Wang Y, Hu C, Ferchen K, Greis KD, Jiang X, Wei M, Qu L, Guan J-L, Je C, Yang J, Chen J. Recognition of RNA N6-methyladenosine by IGF2BP Proteins Enhances mRNA Stability. (2018). Nature Cell Biology, 20(3):285-295. DOI: 10.1038/s41556-018-0045-z.
Smith EA, Krumpelbeck EF, Jegga AG, Prell M, Matrka MM, Kappes F, Greis KD, Ali AM, Meetei AR, Wells SI. The nuclear DEK interactome supports multifunctionality (2018) Proteins, 86(1): 88-97 DOI 10.1002/prot.25411.
Bennett MR, Pleasant L, Haffner C, Ma Q, Haffey WD, Ying J, Wagner M, Greis KD, Devarajan P. A Novel Biomarker Panel to identify Steroid Resistance in Childhood Idiopathic Nephrotic Syndrome (2017) Biomarker Insights. 12, 1-11.
Fang J, Bolanos L, Choi K-M, Liu X, Christie S, Akunuru S, Kumar R, Figueroa ME, Greis KD, Stoilov P, Filippi M-D, Maciejewski JP, Garcia-Manero G, Weirauch MT, Salamonis N, Geiger H, Zheng Y, Starczynowski DT. Ubiquitination of hnRNPA1 by TRAF6 links chronic innate immune signaling to myelodysplasia (2017) Nat. Immunol. 18(2), 236-245.
Kirley TL, Greis KD, Norman AB. Selective disulfide reduction for labeling and enhancement of Fab antibody fragments. (2016) Biochem Biophys Res Comm. 480(4), 752-757.
Dwivedi P and Greis KD. Granulocyte Colony Stimulating Factor Receptor (G-CSFR) signaling in severe congenital neutropenia, chronic neutrophilic leukemia and related malignancies (2017) Exp. Hematol.46, 9-20.
Kirley TL, Greis KD, Norman AB. Structural characterization of expressed monoclonal antibodies by single sample mass spectral analysis after IDeS proteolysis. (2016) Biochem Biophys Res Comm. 477, 363-368.
Sedlacek CJ, Nielsen S, Greis KD, Haffey WD, Revsbech NP, Ticak T, Laanbroek HJ, Bollmann A. The effect of bacterial community members on the proteome of the ammonia-oxidizing bacterium Nitrosomonas sp. Is79. (2016) Applied and Environmental Microbiology. 82(15), 4776-4788.
Blanco VM, Chu Z, LaSance K, Gray GD, Pak KY, Rider T, Greis KD, Qi X. Optical and nuclear imaging of glioblastoma with phosphatidylserine-targeted nanovesicles. (2016). Oncotarget, 7(22), 32866-32875.
Heaven MR, Funk AJ, Cobbs AL, Haffey WD, Norris JL, McCullumsmith RE, Greis KD. Systematic Evaluation of Data-Independent Acquisition for Sensitive and Reproducible Proteomics - a Prototype Design for a Single Injection Assay. (2016) J Mass Spectrom, 51, 1-11.
Schieber M, Marinaccio C, Bolanos LC, Haffey WD, Greis KD, Starczynowski DT, Crispino JD. FBXO11 is a candidate tumor suppressor in the leukemic transformation of myelodysplastic syndrome. (2020) Blood Cancer Journal 10:98; doi.org/10.1038/s41408-020-00362-7
Thowfeik FS, AbdulSalam SF, Wunderlich M, Wyder M, Greis KD, Kadekaro AL, Mulloy JC, Merino EJ. A ROS-activatable agent elicits homologous recombination DNA repair and synergizes with pathway compounds. (2015) Chembiochem. 16, 2513-2521.
Wijeratne AB, Wijesundera DN, Paulose M, Ahiabu IB, Chu W-K, Varghese OK and Greis KD. Phosphopeptide Separation Using Radially Aligned Titania Nanotubes on Titanium Wire. (2015) ACS Applied Material & Interfaces 7, 11155-11164.
Huang Y, Powers C, Madala SK, Greis KD, Haffey WD, Towbin J, Purevjay E, Javadov S, Strauss AW, Khuchua Z. Cardiac metabolic pathways affected in Barth syndrome: The altered mitochondrial proteome in Barth syndrome. (2015) PlosONE | DOI:10.1371/journal.pone.0128561 June 1, 2015.
Marsh JM, Davis MG, Flagler MJ, Sun Y, Chaudhary T, Mamak M, McComb DV, Williams R, Greis KD, Rubio L, Coderch L. Advanced hair damage model from ultra-violet radiation in the presence of copper. (2015). Int'l. J. Cosmetic Sci. 37(5), 532-541.
Lu X, Zoller EE, Weirauch MT, Wu Z, Namjou B, Williams AH, Ziegler JT, Comeau ME, Marion MC, Glenn SB, Adler A, Shen N, Nath SK, Stevens AM, Freedman BI, Tsao BP, Jacob CO, Kamen DL, Brown EE, Gilkeson GS, Alarcón GS, Reveille JD, Anaya JM, James JA, Sivils KL, Criswell LA, Vilá LM, Alarcón-Riquelme ME, Petri M, Scofield RH, Kimberly RP, Ramsey-Goldman R, Joo YB, Choi J, Bae SC, Boackle SA, Graham DC, Vyse TJ, Guthridge JM, Gaffney PM, Langefeld CD, Kelly JA, Greis KD, Kaufman KM, Harley JB, Kottyan LC. Lupus Risk Variant Increases pSTAT1 Binding and Decreases ETS1 Expression. (2015) Am J Hum Genet. 96, 731-9.
Hasegawa K, Sin H-S, Broering TJ, Kartashov AV, Ichijima Y, Zhang F, Greis KD, Andreassen PR, Barski A, Namekawa SH. Scml2 establishes the germline-specific epigenome through regulation of histone H2A ubiquitination. (2015) Dev Cell. 32(5); 574-88.
Liou B, Haffey WD, Greis KD, Grabowski GA. Characterization of the LIMP-2/SCARB2 Ligand on Acid ?-Glucosidase, the Defective Enzyme in Gaucher Disease. (2014) J. Biol. Chem. 289 (43), 30063-74.
Wijeratne AB, Manning JR, Schultz JEJ, Greis KD. Quantitative phosphoproteomics using acetone-based peptide labeling: Method evaluation and application to a cardiac ischemia/reperfusion model. (2013) J. Proteom. Res. 12(10):4268-4279.
Marsh JM, Iveson R, Flagler MJ, Davis MG, Newland AB, Greis KD, Sun Y, Chaudhary T, Aistrup ER. Role of Copper in Photochemical Damage to Hair. (2014) Int'l. J. Cosmetic Sci. 36, 32-38.
Green JV, Orsborn KI, Long JL, Zhang M, Queenie K.-G. Tan QK-G, Greis KD, Porollo A, Andes DR, Hostetter MK. Heparin Binding Motifs and Biofilm Formation by Candida albicans (2013) J. Infect. Diseases. 208(10):1695-1704.
Davis HW, Vallabhapurapu SD, Chu Z, Wyder MA, Greis KD, Fannin V, Sun Y, Desai PB, Pak KY, Gray BD and Qi X. Biotherapy of Brain Tumors with Phosphatidylserine-Targeted Radioiodinated SapC-DOPS Nanovesicles. (2020) Cells, 9, 1960; doi:10.3390/cells9091960
Kattamuri C, Luedeke DM, Nolan K, Rankin SA, Greis KD, Zorn AM, Thompson TB. Members of the DAN Family are BMP Antagonists That Form Highly Stable Noncovalent Dimers. (2012) J. Mol. Biol. 424(5):313-327.
Gauthamadasa K, Vaitinadin NS, Greis KD, Macha S, Dressman JL, Silva RAGD. Apolipoprotein A-II mediated conformational changes of Apoliprotein A-I in discoidal high density lipoproteins. (2012) J. Biol. Chem. 287 (10), 7615-7625.
Govindan S, McElligott A, Muthusamy S, Nair N, Barefield, D, Greis KD, Martin JL, Gongora E, Luther PK, Winegrad S, Henderson KK, Sadayappan S. Cardiac myosin binding protein-C is a potential diagnostic biomarker for myocardial infarction. (2011) J. Molec. Cell. Cardiology, 52, 154-164.
Piyaphanee N, Ma Q, Kremen O, Czech K, Greis KD, Mitsnefes M, Devarajan P, Bennett MR. Discovery and initial validation of alpha 1-B glycoprotein fragmentation as a differential urinary biomarker in pediatric steroid resistant nephrotic syndrome (2011). Proteomics-Clinical Applications, 5, 334-342.
Myer DL, Robbins SB, Yin M, Boivin GP, Liu Y, Greis KD, Bahassi EM, Stambrook PJ. Absence of polo-like kinase 3 in mice stabilizes Cdc25A after DNA damage but is not sufficient to produce tumors. (2011) Mutation Research, 714, 1-10.
Linares JF, Amanchy R, Greis K, Diaz-Meco MT, Moscat J. Phosphorylation of p62 by cdk1 Controls the Timely Transit of Cells through Mitosis and Tumor Cell Proliferation (2011). Mol. Cell. Biol. 31(10), 2171. Correction of 31(1), 105-117.
Djung JF, Mears RJ, Montalbetti C, Golebiowski A, Carr AN, Barker O, Greis KD, Zhou S, Dolan E, Davis GF. The Synthesis and Evaluation of Indolylureas as PKC? Inhibitors (2011) Biorg. Med. Chem. 19, 2742-2750.
Greis KD. Can mass spectrometry transform the way we do HTS of isolated enzymes? (2010) SBS News, 44, 4.
Ridsdale R, Na C-L, Xu Y, Greis KD, Weaver TE. Comparative proteomic analysis of lung lamellar bodies and lysosome-related organelles (2011) PLoS ONE, 6, e16482.
Rathore R, Corr JJ, Pribil P, Seibel WL, Evdokimov A, Greis KD. Multiplexed Enzyme assays for Inhibitor Screening via Mass Spectrometry. (2010) J. Biomolec. Screen., 15, 1001-1007.
Manning JR, Wijeratne AB, Oloizia BB, Zhang Y, Greis KD, Schultz JEJ. Phosphoproteomic (and genomic) analysis identifies multiple sarcoplasmic reticulum calcium-handling proteins in low molecular weight isoform of fibroblast growth factor 2-induced protection against post-ischemic cardiac dysfunction. (2020) J. Molec. & Cell. Cardiol, 148, 1-14 https://doi.org/10.1016/j.yjmcc.2020.08.006.
Rathore R, Corr JJ, Lebre DT, Seibel WL, Greis KD. Extending MALDI-QqQMS Enzyme Screening Assays to Targets with Small Molecule Substrates. (2009) Rapid Commun. Mass Spectrom. 23, 3293-3300.
Stella CL, Bennett MR, Devarajan P, Greis KD, Wyder M, Macha S, Rao M, Jodicke C, Moussa H, How HY, Myatt L, Webster RP, Sibai BM. Preterm Labor Biomarker Discovery in Serum Using 3 Proteomic Profiling Methodologies. (2009) Am. J. Obstet. & Gynecol., 201,387.e1-13.
Aslan JE, You H, Williamson DM, Endig J, Youker RT, Thomas L, Shu H, Du Y, Milewski RL Brush MH, Possemato A, Sprott K, Fu H, Greis KD, Runckel DK, Vogel A, Thomas G. Akt and 14-3-3 control a PAC-2 homeostatic switch that integrates membrane traffic with TRAIL-induced apoptosis. (2009) Molec. Cell, 34, 497-509.
Suzuki M, Wiers K, Brooks EB, Greis KD, Haines K, Klein-Gitelman MS, Olson J, Onel K, O'Neil KM, Silverman ED, Tucker L, Ying J, Devarajan P, and Brunner HI. Initial Validation of a Novel Protein Biomarker Panel for Active Pediatric Lupus Nephritis. (2009) Pediatric Research, 65, 530-536.
Haffey WD, Mikhaylova O, Meller J, Greis KD, Czyzyk-Krzeska MF. iTRAQ Proteomic identification of pVHL-dependent and -independent targets of Egln1prolyl hydroxylase knockdown in renal carcinoma cells. (2009) Advances in Enzyme Regulation. 49, 121-132
Eismann T, Huber N, Shin T, Kuboki S, Galloway E, Wyder M, Edwards MJ, Greis KD, Shertzer HG, Fisher AB, Lentsch AB. (2008) Peroxiredoxin-6 Protects Against Mitochondrial Dysfunction and Liver Injury During Ischemia/Reperfusion in Mice. Am J Physiol Gastrointest Liver Physiol. 296(2), G266-74.
Rathore R, Corr J, Scott G, Vollmerhaus P, Greis KD. (2008) Development of an inhibitor screening platform via Mass Spectrometry. J. Biomolec. Screen., 13, 1007-1013
Mikhaylova O, Ignacak ML, Barankiewicz TJ, Harbaugh SV, Yi Y, Maxwell PH, Schneider M, Van Geyte K, Carmeliet P, Revelo MP, Wyder M, Greis KD, Meller J, Czyzyk-Krzeska MF (2008) The von Hippel-Lindau tumor suppressor protein and Egl 9-type proline hydroxylases regulate the large subunit of RNA Polymerase II in response to oxidative stress. Mol. Cell. Biol. 28, 2701-2717
Greis KD (2007) Mass Spectrometry for Enzyme Assay and Inhibitor Screening: Emerging Applications in Pharmaceutical Research. Mass Spectrom Rev. 26, 324-339.
Muench DE, Ferchen K, Pham G, Dwivedi P, Chutipongtanate S, Hay S, Chetal K, Mookerjee-Basu J, Zhang K, Myers KC, Nazor KL, Greis KD, Kappes DJ, Way SS, Salomonis N, and Grimes HL. A neutropenia-associated transcription factor mutation differentially impacts target genes in the cell-states traversed during granulocyte specification and commitment. (2020) Nature, in press.
Dwivedi P, Chutipongtanate S, Muench DE, Azam M, Grimes HL, Greis KD. SWATH-proteomics of ibrutinib?s action in myeloid leukemia initiating mutated G-CSFR. (2020) Proteomic Clin. Appl. In press.
He Q, Wang F, Honda T, Greis KD, Redington AN. Ablation of miR-144 increases vimentin expression and atherosclerotic plaque formation (2020) Sci. Reports. 10:6127 | https://doi.org/10.1038/s41598-020-63335-7.
Niederkorn M, Hueneman K, Choi K, Varney ME, Romano L, Pujato MA, Greis KD, Inoue J-I, Meetei R, and Starczynowski DT. TIFAB regulates USP15-mediated p53 signaling during stressed and malignant hematopoiesis (2020) Cell Reports, 30, 2776?2790. https://doi.org/10.1016/j.celrep.2020.01.093