Rapid Eco-AI CE–MS Enables Sub‑7 Min Low-Input Proteome Profiling with Quantitative Validation

Implemented on a legacy Orbitrap platform (Q Exactive Plus), Rapid Eco–AI cumulatively identified 1,634 and 1,347 proteins from 300 pg of single-cell-equivalent HeLa digest across technical triplicates using 7 and 5 min effective separations, corresponding to <15 and <11 min injection-to-injection runtimes, respectively. Using the 7 min separation, 835 proteins were cumulatively identified from 75 pg of HeLa digest. Hybrid HeLa–yeast proteome mixtures validated quantitative performance, with median coefficients of variation <5% and measured mean B/A ratios of 0.57 and 1.60 for expected values of 0.60 and 1.80, respectively.

As a proof-of-principle application, we analyzed fractional digest loads from 13 freshly isolated single human neutrophils, corresponding to ∼2 pg of digest per run on a manual CE–MS platform, and identified 135 proteins after conservative background filtering. Collectively, these results establish Rapid Eco–AI as a fast CE–MS workflow for low-input proteome profiling with quantitative validation and proof-of-principle transfer to neutrophil-derived digest analysis.