Biology subjects

Itang, E. C. M.

Publications and source records attributed to Itang, E. C. M..

3 recordsLinked to original sources

bioRxiv2026

Preimplantation factor (PIF) is an endogenous inhibitor of potassium channel KV1.3 regulating neutrophil function during pregnancy

Pregnancy is a unique period regarding immune cell regulation. Within the placenta, maternal immune cells play a central role in immune surveillance and tissue remodeling. However, regulatory mechanisms of systemic immunity during pregnancy are less clear. Here, we show that neutrophil function is altered in pregnant mice (E13.5), indicated by increased slow rolling velocity and reduced adhesion. Mechanistically, PreImplantation factor (PIF), a 15 amino acid peptide which is produced by human and murine trophoblast cells of the placenta, is continuously secreted into the maternal circulation and plays a key role in modulating neutrophil function via blocking the voltage-gated potassium channel KV1.3. This resulted in impaired intracellular Ca2+ signaling and subsequently disturbance of neutrophil post-arrest modifications and a higher susceptibility to physiological shear forces in vivo and in vitro. Furthermore, PIF-mediated KV1.3 blockade impaired E-selectin-mediated release of S100A8/A9 and phagocytosis. Taken together, we have identified PIF as an important modulator of neutrophil function during pregnancy suggesting a critical role in regulating innate immune responses throughout gestation.

immunology↗

bioRxiv2025

Exploring chromatographic dimensions for state-of-the-art proteomics applications

The evolution of mass spectrometry (MS)-based proteomics has been driven by continuous technological advances in sample preparation, instrumentation, and data acquisition. While chromatographic separation has historically been considered a critical bottleneck in achieving comprehensive proteome coverage, recent developments in ultra-fast data acquisition fundamentally challenge this paradigm. We investigated whether the traditional paradigm that chromatographic performance directly correlates with proteome depth still holds true. Spanning a matrix of experiments with five distinct stationary phases, including C18 chemistries, C8, and Phenyl-Hexyl, across eight column lengths (40-140 mm), we evaluate protein identification performance using data-independent acquisition (DIA) on the Orbitrap Astral mass spectrometer. Despite substantial chromatographic differences, we observed remarkably convergent proteome coverage metrics. All C18 and C8 phases consistently achieved over 150,000 precursor- and approximately 9,000 protein group identifications, regardless of column length variations. While distinct selectivity fingerprints persisted across chemistries, these chromatographic differences did not translate into meaningful variations in proteome coverage under high-speed acquisition conditions at 200 Hz. We conclude that the analytical bottleneck has fundamentally shifted from chromatographic resolution to mass spectrometric sampling efficiency, where comprehensive peptide identification is now gained through advanced spectral deconvolution rather than physical separation alone. This paradigmatic shift is reflected in modern proteomics by method development priorities being directed beyond traditional separation optimization, with greater emphasis placed on operational robustness, analytical throughput, and reproducibility.

biochemistry↗

bioRxiv2025

Pre-Analytical Drivers of Bias in Bead-Enriched Plasma Proteomics

Bead-based enrichment has emerged as a promising strategy to improve depth in plasma proteomics by overcoming the dynamic range barrier. However, its robustness against pre-analytical variation has not been sufficiently characterized. Here, we systematically evaluate five plasma proteomics workflows--including three bead-based methods and two conventional protocols--using controlled spike-ins of low-abundance proteins and defined cellular contaminants. We find that bead-based approaches enhance detection of low-abundance proteins but can be highly susceptible to systematic bias from platelet and PBMC contamination, even at low levels. This can easily inflate results by thousands of proteins, likely accounting for some of the very high literature-reported numbers. In contrast, a perchloric acid-based workflow shows notable resistance to erythrocyte and platelet-derived contamination. We further investigate how centrifugation conditions, anticoagulant choice, and buffer-bead combinations modulate contamination profiles and demonstrate that bias can partially be mitigated by optimized sample handling. In total, we identify more than 13,000 different protein groups from various conditions, including cellular components from the circulating proteome. Our results provide a quantitative framework for assessing workflow performance under variable sample quality and offer guidance for both biomarker discovery and quality control in clinical proteomics studies.

biochemistry↗