Proteomics in the genome engineering era
Genome engineering experiments used to be lengthy, inefficient, and often expensive, preventing a widespread adoption of such experiments for the full assessment of endogenous protein functions. With the revolutionary clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 technology, genome engineering became accessible to the broad life sciences community and is now implemented in several research areas. One particular field that can benefit significantly from this evolution is proteomics where a substantial impact on experimental design and general proteome biology can be expected. In this review, we describe the main applications of genome engineering in proteomics, including the use of engineered disease models and endogenous epitope tagging. In addition, we provide an overview on current literature and highlight important considerations when launching genome engineering technologies in proteomics workflows.

Proteomics in the genome engineering era. Vandemoortele, Giel; Gevaert, Kris; Eyckerman, Sven. PROTEOMICS, 16 (2):177-187; SI 10.1002/pmic.201500262 JAN 2016.

Exploring the potential of public proteomics data
In a global effort for scientific transparency, it has become feasible and good practice to share experimental data supporting novel findings. Consequently, the amount of publicly available MS-based proteomics data has grown substantially in recent years. With some notable exceptions, this extensive material has however largely been left untouched. The time has now come for the proteomics community to utilize this potential gold mine for new discoveries, and uncover its untapped potential. In this review, we provide a brief history of the sharing of proteomics data, showing ways in which publicly available proteomics data are already being (re-)used, and outline potential future opportunities based on four different usage types: use, reuse, reprocess, and repurpose. We thus aim to assist the proteomics community in stepping up to the challenge, and to make the most of the rapidly increasing amount of public proteomics data.

Exploring the potential of public proteomics data. Vaudel, Marc; Verheggen, Kenneth; Csordas, Attila; Rder, Helge; Berven, Frode S.; Martens, Lennart; Vizcaino, Juan A.; Barsnes, Harald. PROTEOMICS, 16 (2):214-225; SI 10.1002/pmic.201500295 JAN 2016