Research
Shaevitz's work focuses on precision measurements in a variety of biological systems, focusing on topics related to cell shape in bacteria, active matter and pattern formation in groups of moving cells, and the quantification of animal behavior.
His group pioneered the use of 3D live-cell imaging to study the shape of bacteria during growth. In a series of papers, Shaevitz and colleagues unraveled how a cell-wall insertion mechanism with helical coordination can produce cells with the correct shape in both rod and helical cells. [9] [10] [11] [12] His group also studies bacterial cell mechanics, including bending rigidity, [13] turgor pressure and cell wall stiffness, [14] and pressure regulation. [15] [16]
Shaevitz also has worked on the mechanisms of gliding motility and collective behavior in the social bacterium Myxococcus xanthus. This work includes measurement of the mechanochemistry of individual gliding motors inside live bacteria [17] [18] and the connection between active matter phase transitions and evolutionarily advantageous fruiting body formation. [19] [20]
A third thread to Shaevitz's research involves the quantification of animal behavior using supervised and unsupervised machine learning algorithms. Shaevitz and Princeton Neuroscience professor Mala Murthy published an automated system (LEAP) for measuring animal pose from large movie data sets. [21] This has recently been extended to multi-animal data in a package called SLEAP. [22] His work has extended to understanding the dynamics of animal behavior through unsupervised clustering methods in collaboration with Princeton Physics colleague William Bialek and others. [23] [24] [25] [26]
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