Proteome profiling of formalin-fixed paraffin-embedded (FFPE) specimens has gained traction for the analysis of cancer tissue for the discovery of molecular biomarkers. However, reports so far focused on single cancer entities, comprised relatively few cases and did not assess the long-term performa …

Mass spectrometry instrumentation continues to evolve rapidly, yet quantifying these advances beyond conventional peptide and protein detections remains challenging. Here, we evaluate a modified Orbitrap Astral Zoom mass spectrometer (MS) prototype and compare its performance to the standard Orbitrap Astral MS. Across a range of acquisition methods and sample inputs, the prototype instrument outperformed the standard Orbitrap Astral MS in precursor and protein identifications, ion beam utilization, and quantitative precision. To enable meaningful cross-platform comparisons, we implemented an ion calibration framework that converts signal intensity from arbitrary units to ions per second. This benchmarking strategy showed that the prototype sampled 23.1% more ions per peptide than the original Orbitrap Astral MS. This increase in the ion beam utilization resulted in improved sensitivity and quantitative precision. To make these metrics broadly accessible, we added new metrics to the Skyline document grid to report the number of ions measured in a spectrum at the apex of the elution peak or the sum of ions between the peak integration boundaries. Taken together, our results demonstrate the Orbitrap Astral Zoom prototype as a high-performance platform for data-independent acquisition proteomics and establish a generalizable framework for evaluation of MS performance based on the number of ions detected for each analyte. Data are available on Panorama Public and ProteomeXchange under the identifier PXD064536.

Mass-spectrometry-based phosphoproteomics enables the analysis of thousands of protein phosphorylation events across the human proteome. However, there is a lack of scalable, hypothesis-free, and stat...

Abstract. Proteomic and phenotypic cell sensitivity datasets are increasingly important for understanding chemoproteomics and the underlying drug mechanism

Koina is an open-source, online platform that simplifies access to machine learning models in proteomics, enabling easier integration into analysis tools and helping researchers adopt and reuse ML mod...

A theoretical foundation for entrapment methods is presented, along with a method that enables more accurate evaluation of false discovery rate (FDR) control in proteomics mass spectrometry analysis p...

Zero-distance photo-crosslinking reveals direct protein-DNA interactions in living cells, enabling quantitative analysis of the DNA-interacting proteome on a timescale of minutes with single-amino-aci...

CHIMERYS is a spectrum-centric and data acquisition method-agnostic algorithm for the analysis of MS2 spectra. It is capable of deconvoluting any MS2 spectrum, regardless of whether it was acquired by...

Mass spectrometry-based sample multiplexing with isobaric tags permits the development of high-throughput and precise quantitative biological assays with proteome-wide coverage and minimal missing val...

imageimagePhosphoproteomics unveils the mode of action of clinical ATR inhibitors and explains their synergy with Gemcitabine in pancreatic cancer cells. Viability screening of 146 targeted drugs ide...