White blood cells such as neutrophils and macrophages are made competent for chemotaxis and phagocytosis — the dynamic cellular behaviors that are hallmarks of their innate immune functions — by the reorganization of complex biological circuits during differentiation. Conventional loss-of-function approaches have revealed that more than 100 genes participate in these cellular functions, and we have begun to understand the intricate signaling circuits that are built up from these gene products. We now appreciate: (1) that these circuits come in a variety of flavors — so that we can make a distinction between genetic circuits, metabolic circuits and signaling circuits; and (2) that they are usually so complex that the assumption of multiple feedback loops, as well as that of crosstalk between seemingly independent pathways, is now routine. It has not escaped our notice, however, that just as physicists and electrical engineers have long been able to disentangle complex electric circuits simply by repetitive cycles of probing and measuring electric currents using a voltmeter, we might similarly be able to dissect these intricate biological circuits by incorporating equivalent approaches in the fields of cell biology and bioengineering. Existing techniques in biology for probing individual circuit components are unfortunately lacking, so that the overarching goal of drawing an exact circuit diagram for the whole cell — complete with kinetic parameters for connections between individual circuit components — is not yet in near sight. My laboratory and others have thus begun the development of a new series of molecular tools that can measurably investigate the circuit connectivity inside living cells, as if we were doing so on a silicon board. In these proceedings, I will introduce some of these techniques, provide examples of their implementation, and offer a perspective on directions moving forward.

Date Published: 19 May 2016
PDF: 12 pages
Proc. SPIE 9871, Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016, 987102 (19 May 2016); doi: 10.1117/12.2225185

Published in SPIE Proceedings Vol. 9871:
Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016
Liyi Dai; Yufeng Zheng; Henry Chu; Anke D. Meyer-Bäse, Editor(s)