Best of the Week: Mass Spectrometry Innovations and Next-Gen HPLC Insights

This past week, LCGC International continued their series of roundtable discussions on women in chromatography. In addition, we featured an interview with Kevin Jooß of the Vrije Universiteit Amsterdam about using capillary zone electrophoresis combined with mass spectrometry (CZE-MS) to sort and study important protein variations. We also presented work conducted which used untargeted reverse-phase liquid chromatography-mass spectrometry (RPLC-MS) to analyze serum metabolite profiles under normal and sleep-restricted conditions, as well as a study where headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry (GC-MS) was used to analyze human scent traces left on clothing. We also caught up with Gert Desmet at analytica 2026 to get his thoughts on next generation HPLC columns.

This is the Best of the Week.

Standing on Shoulders: Senior Leadership and Early Careers

Our roundtable discussion focused on the experiences, challenges, and contributions of women in chromatography continues,¹with Amandaa Brewer, Paola Tiedemann, Chelsea Plummer, and Jennifer Field about the role that senior leadership can play in the path of early-career professionals.

Advancements in Capillary Zone Electrophoresis for Top-Down Proteomics

A worldwide study involving 12 research groups has confirmed that capillary zone electrophoresis combined with mass spectrometry (CZE-MS) is a highly reproducible and sensitive alternative to traditional methods for analyzing proteoforms, offering a way to separate these critical protein variations based on their charge-to-size ratio. LCGC International spoke to Kevin Jooß of the Vrije Universiteit Amsterdam, one of the authors of a paper outlining the study, about this work.²

RPLC-MS Profiling Reveals How Sleep Loss Disrupts Circulating Microbial Metabolites

Researchers utilized untargeted reverse-phase liquid chromatography-mass spectrometry (RPLC-MS) to analyze serum metabolite profiles under normal and sleep-restricted conditions. The RPLC-MS analysis successfully identified 90 circulating metabolites—including 14 of microbial origin—and demonstrated that sleep deprivation significantly disrupts the natural rhythmic cycles of these host and microbial compounds. These findings indicate that microbial metabolites detected via RPLC-MS could potentially serve as clinical biomarkers for the various health and metabolic risks associated with sleep loss.³

Optimizing HSSE-GC-MS and Machine Learning for Forensic Gender Classification from Human Scent

Researchers have optimized a headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry (GC-MS) to analyze human scent traces left on clothing. This combination of optimized extraction, GC-MS analysis, and machine learning provides a rapid and automated forensic screening technique to help narrow down suspect or victim profiles based on trace evidence.⁴

Why Perfect Order Matters: Gert Desmet on Next-Gen HPLC Columns

At analytica 2026, Gert Desmet of Vrije Universiteit Brussel sat down with LCGC International’s Kate Jones to discuss the drive toward perfectly ordered column structures in high-performance liquid chromatography (HPLC), and the fundamental theoretical gains in chromatographic performance that make this pursuit worthwhile.⁵

References

1. Brewer, A. K.; Tiedemann, P.; Plummer, C.; Field, J. K. Standing on Shoulders: Senior Leadership and Early Careers. ChromatographyOnline website. https://www.chromatographyonline.com/view/standing-on-shoulders-senior-leadership-and-early-careers (accessed 2026-03-27)
2. Jooß, K.; Chasse, J. Advancements in Capillary Zone Electrophoresis for Top-Down Proteomics. ChromatographyOnline website. https://www.chromatographyonline.com/view/advancements-in-capillary-zone-electrophoresis-for-top-down-proteomics (accessed 2026-03-27)
3. Chasse, J. RPLC-MS Profiling Reveals How Sleep Loss Disrupts Circulating Microbial Metabolites. ChromatographyOnline website. https://www.chromatographyonline.com/view/rplc-ms-profiling-reveals-how-sleep-loss-disrupts-circulating-microbial-metabolites (accessed 2026-03-27)
4. Chasse, J. Optimizing HSSE-GC-MS and Machine Learning for Forensic Gender Classification from Human Scent. ChromatographyOnline website.https://www.chromatographyonline.com/view/optimizing-hsse-gc-ms-and-machine-learning-for-forensic-gender-classification-from-human-scent (accessed 2026-03-27)
5. Desmet, G.; Jones, K. Why Perfect Order Matters: Gert Desmet on Next-Gen HPLC Columns. ChromatographyOnline website. https://www.chromatographyonline.com/view/why-perfect-order-matters-gert-desmet-on-next-gen-hplc-columns (accessed 2026-03-27)