Michael Elowitz | |
|---|---|
| Alma mater | University of California, Berkeley (BA) Princeton University (PhD) |
| Awards | MacArthur Fellows Program |
| Scientific career | |
| Fields | Biology |
| Institutions | California Institute of Technology; Howard Hughes Medical Institute |
| External videos | |
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Michael B. Elowitz is a biologist and professor of Biology, Bioengineering, and Applied Physics at the California Institute of Technology, [1] [2] [3] and investigator at the Howard Hughes Medical Institute. [4] In 2007 he was the recipient of the Genius grant, better known as the MacArthur Fellows Program for the design of a synthetic gene regulatory network, the Repressilator, which helped initiate the field of synthetic biology. [5] He was the first to show how inherently random effects, or 'noise', in gene expression could be detected and quantified in living cells, [6] leading to a growing recognition of the many roles that noise plays in living cells. His work in Synthetic Biology and Noise represent two foundations of the field of Systems Biology. Since then, his laboratory has contributed to the development of synthetic biological circuits that perform a range of functions inside cells, and revealed biological circuit design principles underlying epigenetic memory, cell fate control, cell-cell communication, and multicellular behaviors. [7]
Elowitz was born in Los Angeles, California, [8] where he attended the Portola Highly Gifted Magnet School and the Hamilton Humanities Magnet High Schools. In 1992, he received his B.A. in physics from the University of California, Berkeley. In 1999, he completed his Ph.D. in physics at Princeton University. [9]
As a graduate student under the mentorship of Stanislas Leibler, he began designing synthetic genetic circuits. During his graduate studies, he spent a year at the European Molecular Biology Laboratory (EMBL) in Heidelberg, where he engineered parts of the Repressilator. Upon returning to Princeton, Elowitz showed that the circuit could successfully generate dynamic oscillations in gene expression, causing individual cells to "blink" on and off, and demonstrating that new dynamic behaviors could be programmed in living cells. [10]
His laboratory studies the dynamics of genetic circuits in individual living cells using synthetic biology, time-lapse microscopy, and mathematical modeling, with a particular focus on the way in which cells make use of noise to implement behaviors that would be difficult or impossible without it. Recently, his lab has expanded their approaches beyond bacteria to include eukaryotic and mammalian cells. [11]
Elowitz's research seeks to learn how to program new behaviors in living cells through a "build to understand" approach. [12] His laboratory integrates synthetic biology, quantitative systems biology, and single-cell analysis techniques. Lab research has focused on biological circuits that process and store information, allow cell-cell communication, generate differentiation and other dynamic cell behaviors, as well as circuits that can provide therapeutic capabilities. [13] [14] [15]
As a graduate student, Elowitz designed and constructed the repressilator, a synthetic genetic oscillator composed of three transcriptional repressors arranged in a cyclic inhibitory loop. This fully synthetic circuit, rationally designed using mathematical modeling, generated periodic fluorescence oscillations in individual cells, demonstrating that engineered gene networks can produce predictable dynamic behaviors. [16] Together with a simultaneous demonstration of synthetic toggle switches, this work sparked the development of synthetic biology. [17]
A major theme of Elowitz’s work has been quantifying how stochastic biochemical events lead to both useful and deleterious biological variation. In 2002, his group introduced two fluorescent reporters into the same cells, enabling them to quantify intrinsic stochastic noise in gene expression from other, extrinsic, sources of variation, such as fluctuations in upstream components. [18] Subsequent time-lapse studies showed that intrinsic and extrinsic noise operate on distinct timescales, [19] and showed that correlations in stochastic fluctuations can be used to infer molecular interactions in synthetic and natural circuits. [20]
Elowitz's lab also revealed functional roles for noise. For example, they showed how excitable gene-circuit architectures generate probabilistic, rather than deterministic, differentiation behaviors to enable bet-hedging in prokaryotes. [21] [22] [23] In a different study, Elowitz and his team showed how noise in bacterial sporulation could facilitate developmental evolution by enabling partially penetrant mutant phenotypes. [24] [25]
Extending this approach to mammalian cells, he worked with Ellen Rothenberg to show that stochastic epigenetic events at a single gene could control T cell lineage commitment. [26] Collectively, this and other work established that stochastic interactions can control cellular decision-making.
Building on these discoveries, Elowitz's group went on to discover an inherently dynamic mode of gene regulation, in which transcription factors regulate genes through dynamic pulsing rather than through steady activation levels. In these systems, cells control the frequency and relative timing of activity pulses rather than tune steady-state factor activities. In yeast, they showed that the Crz1 transcription factor undergoes frequency-modulated nuclear localization bursts whose rate encodes upstream input signals, enabling cells to coordinate the responses of many genes. [27] [28] They then demonstrated that cells use the relative timing of pulses to integrate information from multiple signaling pathways. [29] [30] Interestingly, pulsatile regulation was not limited to eukaryotes. Elowitz's team showed that bacteria generate dynamic pulses of the sigma factors regulating the general stress response. [31] Collectively, this work revealed a pervasive, inherently dynamic mode of gene regulation, its mechanistic basis, and its functional roles.
Moving from gene regulation to cell-cell communication, Elowitz's laboratory uncovered principles of important signaling pathways. His group discovered that interactions between Notch receptors and ligands in the same cell (cis interactions) can generate mutually exclusive “sender” and “receiver” states [32] or allow autocrine signaling. [33] They further discovered that different Notch ligands can activate distinct transcriptional programs through a single receptor by activating it with different dynamics, showing how signaling pathways use dynamics to encode and decode informatio.n [34]
Extending this work to spatial patterning, Elowitz's team reconstituted and re-wired morphogen signaling pathways in spatial systems to understand what features of signaling pathways enable precise spatial patterning. This work revealed specific circuit design principles underlying patterning in the Sonic Hedgehog [35] and Bone Morphogenetic Protein (BMP) pathways. [36]
Elowitz's laboratory also uncovered principles of combinatorial encoding. A ubiquitous feature of cell signaling systems is their use of many-to-many interactions among sets of ligand and receptor variants. The Elowitz team showed this feature allows information to be encoded in ligand combinations and contextually decoded in different ways by different cell types. [37] They also worked out functional implications of this scheme in subsequent papers. [38] The laboratory has extended this principle to systems of interacting transcription factors, showing that they could similarly provide contextual responses to combinatorial inputs. [39]
Elowitz and his team also applied synthetic biology and rewiring approaches to understand and engineer epigenetic memory, showing how cells write and maintain stable memory states at individual loci through a dynamic, stochastic system. [40]
A major challenge in biology is to recover the dynamic histories of individual cells. With Long Cai and others, the Elowitz lab developed MEMOIR, a system for recording lineage and cellular event histories within cellular genomes. [41] [42] [43] A distinguishing feature of these systems is their ability to recover lineage information from images, preserving spatial organization. [44]
Together with Jay Shendure and Alex Schier, Elowitz co-directed the Allen Discovery Center for Cell Lineage Tracing to enable the engineering of synthetic recording systems. [45] Alongside this work, they also created and demonstrated methods for inferring cell fate programs from lineage histories. [46] [47]
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