Sample multiplexed quantitative proteomics assays have
proved to
be a highly versatile means to assay molecular phenotypes. Yet, stochastic
precursor selection and precursor coisolation can dramatically reduce
the efficiency of data acquisition and quantitative accuracy. To address
this, intelligent data acquisition (IDA) strategies have recently
been developed to improve instrument efficiency and quantitative accuracy
for both discovery and targeted methods. Toward this end, we sought
to develop and implement a new real-time spectral library searching
(RTLS) workflow that could enable intelligent scan triggering and
peak selection within milliseconds of scan acquisition. To ensure
ease of use and general applicability, we built an application to
read in diverse spectral libraries and file types from both empirical
and predicted spectral libraries. We demonstrate that RTLS methods
enable improved quantitation of multiplexed samples, particularly
with consideration for quantitation from chimeric fragment spectra.
We used RTLS to profile proteome responses to small molecule perturbations
and were able to quantify up to 15% more significantly regulated proteins
in half the gradient time compared to traditional methods. Taken together,
the development of RTLS expands the IDA toolbox to improve instrument
efficiency and quantitative accuracy for sample multiplexed analyses.