In this episode of Concentrating on Chromatography, host David Oliva is joined for the first time by co-host Candice (Candi) Gokey — PhD candidate at UC San Diego / San Diego State University and expert in LC-MS/MS method development for untargeted metabolomics to interview Jacob Russell, a third-year PhD student in the Riley Research Group at the University of Washington (Seattle).Jacob's research sits at the frontier of mass spectrometry based intact glycoproteomics, where the goal is to keep glycans attached to peptides during analysis — preserving the biological information that is lost when glycans are enzymatically removed. His lab, led by Prof. Nick Riley, develops new methods to tackle every stage of glycoproteomic analysis, from sample preparation and enrichment through data acquisition and bioinformatics.🔬 WHAT WE COVER:• What is the glycocalyx, and why does glycoproteomics matter for cancer, immunity, and protein biology?• N-linked vs. O-linked glycosylation: why they require completely different fragmentation strategies (HCD vs. ETD/EThcD)• Autonomous Dissociation-type Selection (ADS): how real-time library searching (RTLS) of oxonium ion ratios (m/z 138 vs. 144) enables on-the-fly selection of the right fragmentation method for N- vs. O-glycopeptides — published in J. Proteome Research (Sutherland, Veth, Russell et al., 2024)• How XGBoost machine learning outperforms RTLS by classifying ~50 oxonium ions simultaneously, recovering Core 2 O-glycopeptides that the simpler ratio-based method misses• Casanovo Foundation: a transformer-based foundation model for tandem mass spectra and how deep learning is reshaping glycopeptide classification (Sanders et al., arXiv 2025)• LacNAc-ase enabled glycoproteomics: using endo-β-galactosidase (EBG) to ”trim” poly-LacNAc chains on N-glycans — uncovering previously undetectable glycoforms (ASMS 2026 presentation)• Cutaneous vs. uveal melanoma: comparing poly-LacNAcylated glycoproteins (including galectin-3 binding partners like CD63, LAMP-2, and basigin) between cell lines — and why uveal melanoma has a ~50% distant metastasis rate vs. ~5% for cutaneous • The future of intelligent data acquisition and real-time mass spectrometry• Candi's parallel world of untargeted metabolomics, coral-algae chemical communication, and GNPS/MassQL — and the surprising overlap with glycoproteomics🔗 RESOURCES MENTIONED:• Riley Research Group at UW: https://www.riley-research.com/• ADS Paper: Sutherland, Veth, Russell et al., J. Proteome Res. 2024, 23, 5606–5614• Casanovo Foundation: Sanders et al., arXiv 2025• GlyCounter software (Riley Lab, UW)• XGBoost (Chen & Guestrin, UW)• GNPS / MassQL (Dorrestein Lab, UCSD)👥 GUESTS:Jacob H. Russell — PhD Student, Dept. of Chemistry, University of Washington | Riley Research Group | Glycoproteomics | Mass Spectrometry | Machine LearningCo-host: Candice Gokey — PhD Candidate, UC San Diego / San Diego State University | LC-MS/MS Method Development | Untargeted Metabolomics | Coral Reef Holobiont Research🎙️ HOST: David Oliva |  @ChromatographyTalk  |  @Organomation  |  @SeparationScience  collaborator━━━━━━━━━━━━━━━━━━━━━━━━━━━━━🔔 Subscribe for more interviews with researchers and industry leaders in analytical chemistry, chromatography, and mass spectrometry.#Glycoproteomics #MassSpectrometry #Chromatography #AnalyticalChemistry #MachineLearning #Glycans #Proteomics #Cancer #UVealMelanoma #LCMS #OxoniumIons #ETD #XGBoost #RileyLab #UniversityOfWashington #PodcastScience #Metabolomics“`