Rapid Temporal Dynamics of Transcription, Protein Synthesis, and Secretion during Macrophage Activation

Macrophages provide the first line of host defense with their capacity to react to an array of cytokines and bacterial components requiring tight regulation of protein expression and secretion to invoke a properly tuned innate immune response. To capture the dynamics of this system, we introduce a novel method combining pulsed stable isotope labeling with amino acids in cell culture (SILAC) with pulse labeling using the methionine analog azidohomoalanine that allows the enrichment of newly synthesized proteins via click-chemistry followed by their identification and quantification by mass spectrometry. We show that this permits the analysis of proteome changes on a rapid time scale, as evidenced by the detection of 4852 newly synthesized proteins after only a 20-min SILAC pulse. We have applied this methodology to study proteome response during macrophage activation in a time-course manner. We have combined this with full proteome, transcriptome, and secretome analyses, producing an integrative analysis of the first 3 h of lipopolysaccharide-induced macrophage activation. We observed the rapid induction of multiple processes well known to TLR4 signaling, as well as anti-inflammatory proteins and proteins not previously associated with immune response. By correlating transcriptional, translational, and secretory events, we derived novel mechanistic principles of processes specifically induced by lipopolysaccharides, including ectodomain shedding and proteolytic processing of transmembrane and extracellular proteins and protein secretion independent of transcription. In conclusion, we demonstrate that the combination of pulsed azidohomoalanine and pulsed SILAC permits the detailed characterization of proteomic events on a rapid time scale. We anticipate that this approach will be very useful in probing the immediate effects of cellular stimuli and will provide mechanistic insight into cellular perturbation in multiple biological systems. The data have been deposited in ProteomeXchange with the identifier PXD000600.