One of the most important early developments in the field of proteomics was the advent of automated data acquisition routines that allowed high-throughput unattended data acquisition during HPLC introduction of peptide mixtures to a tandem mass spectrometer. Prior to this, data acquisition was orders of magnitude less efficient being based entirely on lists of predetermined ions generated in a prior HPLC-MS experiment. This process, known generically as data-dependent analysis, empowered the development of shotgun proteomics where hundreds to thousands of peptide sequences are matched per experiment. In their most popular implementation, the most abundant ionized species from every precursor ion scan at each moment in chromatographic time are successively selected for isolation, activation and tandem mass analysis. While extremely powerful, this strategy has one primary limitation in that detectable dynamic range is restricted (in a top-down manner) to the peptides that ionize the best. To circumvent the serial nature of the data-dependent process and increase detectable dynamic range, the concepts of multiplexed and data-independent acquisition (DIA) have emerged. Multiplexed-data acquisition is based on more efficient co-selection and co-dissociation of multiple precursor ions in parallel, the data from which is subsequently de-convoluted to provide polypeptide sequences for each individual precursor ion. DIA has similar goals, but there is no real-time ion selection based on prior precursor ion scans. Instead, predefined m/z ranges are interrogated either by fragmenting all ions entering the mass spectrometer at every single point in chromatographic time; or by dividing the m/z range into smaller m/z ranges for isolation and fragmentation. These approaches aim to fully utilize the capabilities of mass spectrometers to maximize tandem MS acquisition time and to address the need to expand the detectable dynamic range, lower the limit of detection, and improve the overall confidence of peptide identifications and relative protein quantification measurements. This review covers all aspects of multiplexed- and data-independent tandem mass spectrometry in proteomics, from experimental implementations to advances in software for data interpretation.
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