March 2021 Virtual Meeting

Speaker: Michael Marty, University of Arizona

Topic: Using native mass spectrometry and nanodiscs to study assembly of membrane protein and antimicrobial peptide complexes

Date: Monday, March 15th, 2021

Time: 1:00 PM Presentation

Location: Webinar – see emails on March 4 and 11 for invite link. Join the mailing list

Abstract: Native mass spectrometry (MS) has emerged as a powerful technique for studying the oligomeric state and interactions of membrane proteins. However, native MS can be challenging for smaller and more fragile membrane protein and transmembrane peptide complexes. To address this challenge, we have used native MS to study small viral membrane protein complexes in both detergent micelles and lipid nanodiscs. Using charge reduction reagents for stabilization and advanced data analysis techniques to unravel complex spectra, we discovered that viroporin complexes can be highly sensitive to their environment, showing different oligomeric states in different lipids/detergents, with different pH conditions, and with addition of antiviral drugs. Unexpected oligomeric states have been observed that do not match existing structural models, highlighting previously unseen behavior of these complexes. We have also studied assembly of antimicrobial peptide complexes in lipid nanodiscs. Antimicrobial peptides are also highly sensitive to the lipid environment, showing unique assembly pathways that are controlled by the thickness of the lipid bilayer. Ultimately, we expect these applications of native MS will reveal new insights into the biology of infectious disease and provide new directions for antiviral and antibacterial drug discovery.

February 2021 Virtual Meeting

Speaker: Allen Everett, Johns Hopkins University

Topic: Proteomics Discovery of Circulating Pulmonary Hypertension Biomarkers: IGF binding proteins are associated with disease severity

Date: Monday, February 15th, 2021

Time: 1:00 PM Presentation

Location: Webinar – see emails on Feb. 4 and 11 for invite link. Join the mailing list

Abstract:
Background: Pulmonary arterial hypertension is a progressive and fatal disease characterized by sustained elevations of pulmonary artery pressure. We lack circulating, diagnostic and prognostic markers to improve outcomes and develop new therapies.
Methods and Results: We performed proteomics discovery using high resolution mass spectrometry to identify new circulating biomarkers of pulmonary arterial hypertension. Plasma samples from patients with idiopathic pulmonary arterial hypertension (N=9, age 35.2 ± 11.2 years, 89% female) and normal controls (N=9, age 34.8 ± 10.6 years, 100% female) were processed by liquid chromatography/tandem mass spectrometry. A total of 826 (0.047 False Discovery Rate) idiopathic pulmonary arterial hypertension and 461 (0.087 False Discovery Rate) control proteins were identified. By Volcano plot, 153 proteins showed > 2 fold change, P<0.05. Carbonic anhydrase 2 (CA2) and Insulin like growth factor binding protein (IGFBP2) were top molecules by spectral counts. When all IGF axis molecules were examined, spectral counts for IGF1, IGF2, IGFBP1, IGFBP4, and IGFBP7 were also different between PAH and control. ELISA verification (N=41 PAH and N=39 controls) demonstrated that IGF1 and 2 were decreased and IGFBP1, 2, 4, 5, 7 and CA2 were increased in PAH. In association with disease severity, IGFBP2, 4 and 7 were associated with decreased 6MWD and IGFBP1, 2, 5 associated with PVR. IGFBP2, 4, and 7 were associated with survival (Kaplan Meier). CA2 was not associated with clinical severity.
Conclusions: We identified candidate plasma proteins that can distinguish PAH from control and verified CA2 and multiple members of the IGF axis associated with PAH and PAH severity. Suggesting that the IGF axis may play an important role in PAH pathogenesis and may be an important diagnostic for PAH, response to therapy and play a role in the pathogenesis of PAH.

January 2021 Virtual Meeting

Speaker: Shao-En Ong, University of Washington

Topic: Kinome analyses for pharmacoproteomics

Date: Tuesday, January 19th, 2021

Time: 2:00 PM Presentation

Location: Webinar – see emails on Jan. 8 and 15 for invite link. Join the mailing list

Abstract: With few targeted therapies for genetic alterations in cancer, pharmacogenomics has been used to link genetic features with drug response. Because proteomics allows sensitive and direct measurements of cellular signaling pathways, we developed a novel pharmacoproteomics platform to identify kinase pathways correlating with drug response by combining kinobead-based activity profiling of 346 kinases and high-throughput screening of 299 kinase inhibitors in 17 hepatocellular carcinoma (HCC) cell lines. We identified novel kinases involved in drug resistance, that upon small molecule inhibition or genetic knockdown, rewired cellular signaling and restored chemosensitivity. We applied kinobead-MS in clinical HCC samples to identify signatures of drug sensitivity common to cell lines and patient tumors. Our broadly applicable approach identifies kinome features responsible for the activity of individual drugs and provides a resource for biomarker discovery and target deconvolution.

December 2020 Virtual Meeting

Speaker: Perry Wang, US Food and Drug Administration

Topic: Advanced Application of LC-MS and Challenges

Date: Monday, December 14th, 2020

Time: 2:00 pm Presentation

Location: Webinar – see emails on Dec. 3 and 10 for invite link. Join the mailing list

Abstract: Liquid chromatography-mass spectrometry (LC-MS) is the most sensitive analytical technique by far. It combines the physical separation power of liquid chromatography with the mass analysis capabilities of mass spectrometry. Because the individual capabilities of each technique are synergistically enhanced, the combination of liquid chromatography with mass spectrometry could be called a “perfect marriage” -liquid chromatography separates components in mixtures by affinity and mass spectrometry differentiates the components by mass. Therefore, LC-MS is applied in a broad field including biotechnology, environment monitoring, food safety, and pharmaceutical, agrochemical, and cosmetic industries. However, the technique often faces a great challenge -matrix effect, which can be observed as either a loss (ion suppression), or an increase (ion enhancement) in responses. The matrix effects affect the detection capability, precision and/or accuracy for the analytes of interest. Thus, the matrix effects should be evaluated during method development by comparing the response of a standard solution prepared in a sample matrix over the response in neat solutions or comparing the calibration-curve slope of standard solutions prepared in sample matrix over the slope of standards prepared in neat solutions. Unfortunately, a representative matrix is not always available for some studies, and how to evaluate and minimize the matrix effects are challenging. Different techniques to minimize matrix effects will be presented and the concept of matrix effect factor (MEF) will be introduced and discussed.

November 2020 Virtual Meeting

Speaker: Yansheng Liu, Yale University School of Medicine

Topic: DIA-MS and Its Application to Profiling Cellular Proteome and Proteoform Dynamics

Date: Monday, November 16th, 2020

Time: 2:00 pm Presentation

Location: Webinar – see emails on Nov. 5 and 12 for invite link. Join the mailing list

Abstract: The term ‘proteoform’ is now used to designate different molecular forms in which the protein product of a single gene can be found, including changes due to genetic variations, alternatively spliced RNA transcripts, and post-translational modifications. Although proteoform is normally studied by the top-down approach, we will discuss a new bottom-up strategy to investigate the site-specific modiforms. We will first review the data-independent acquisition mass spectrometry (DIA-MS) and its development in our group. We will then present how we use DIA-MS, pulse stable isotope-labeled amino acids in cells (pSILAC) approach, and genome-wide correlation analysis for quantifying both abundance and turnover rate of proteins in cancer cell models.