Associated Faculty, Physics and the Lewis-Sigler Institute for Integrative Genomics

Contact

tg2@princeton.edu
609-258-4335
Jadwin Hall, 120
Gregor Lab

Research Area

Cell Biology, Development & Cancer

Research Focus

Quantitative approaches to systems and developmental biology



Research
Selected Publications

Interest and Focus

Traditionally, biological questions have been investigated with qualitative techniques that allow for interpretation classically in the context of evolution. This qualitative approach, however, struggles to adequately describe the dynamic nature of most of the essential biological processes upon which evolution is acting. Recent advances in molecular biology, optical microscopy, nanoscopic physics and computer science have opened up new avenues for interpreting biological phenomena, combining high-precision measurement of biological processes with theoretical predictions and models that are bound by physical principles and formulated in mathematical language. This allows for models to be numerically tested and validated by experiments and, conversely, for experiments to be designed and guided by theoretical models. My laboratory uses such an approach to understand a biological system holistically, within a framework of fundamental physical principles that dictate and constrain biological phenomena.

Methods and Models

Research in the lab is highly interdisciplinary. The interests and expertise of the lab's members range from physics to biology to computer science to engineering; we use a combination of computational and experimental approaches. We build microscopes and microfluidic devices to measure the concentrations dynamics of proteins and signaling molecules; we use tools from molecular biology and genetics to manipulate the organisms we study; and we use image analysis and modeling to analyze our data. Researchers are encouraged to move freely between the different disciplines and to learn a variety of techniques according to their specific needs and interests. We primarily address questions concerning the development of fruit fly embryos and emergent collective behavior via cell signaling in amoeba populations, but we are open to new ideas and collaborations addressing questions in other model systems.

Specific example research projects

Signaling and emergent collective behavior in cell populations

Cells often communicate via concentration oscillations of small molecules, such as ions in neurons or cAMP in stressed (starved) cells of the social amoeba Dictyostelium. However, the "code'' or the language that these cells use to change their behavior is largely unknown. Optical concentration measurements of the relevant oscillating constituents will be used to measure the spatiotemporal communication dynamics among a few Dictyostelium cells. Simultaneously, a combination of electro-physiological and optical measurements will be used to measure similar dynamics in a developing network of cultured neurons. In both cases, communication among cells via oscillations affects the resulting behavior, i.e., aggregation for amoebae, network rewiring for neurons. The goal is to seek common strategies and mechanisms these cells use to change their behavior to form an organism, ultimately revealing unifying principles of communication in different systems.

Spatio-temporal patterning and differentiation during early development

In many multicellular organisms, cells differentiate in a hierarchical cascade of gene expression in order to determine a well defined spatio-temporal pattern. Although the qualitative picture of this process is well laid out, quantitatively we know very little about the underlying mechanisms that account for a precise readout of small transcription factor concentration differences or for the exact positioning of gene expression boundaries. Using organisms that express fluorescently labeled proteins or mRNA molecules, the spatiotemporal dynamics of an entire branch of the differentiation cascade will be measured and analyzed. Particular focus will be given to generation and transmission of positional information in the organism, as well as to the precision of the readout mechanisms that ensures a proper handling of the intrinsic sources of noise associated with transcriptional processes. The main focus of this research will be to analyze the gene expression pattern of the segmentation network in early Drosophila embryos and the differentiation processes in starved, aggregating cells of the cellular slime mold Dictyostelium.

In utero imaging of early mammalian development

In a crucial moment of mammalian development, the maturing blastocyst implants itself in the uterus. The mother starts to transmit vital information to the embryo, with the formation of the body axes happening very soon thereafter. To date, this stage has only been visualized using fixation methods; it has never been observed dynamically. We are currently developing novel techniques to image, in utero, the embryos of anesthetized mice. As a first step, we will use fluorescent proteins to label the embryo ubiquitously. We will then label specific proteins to observe and eventually quantify patterning processes, such as axis formation.




Voortman L, Anderson C, Urban E, Yuan L, Tran S, Neuhaus-Follini A, et al. Temporally dynamic antagonism between transcription and chromatin compaction controls stochastic photoreceptor specification in flies. Dev Cell. 2022 ;57(15):1817-1832.e5. PubMed
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Seyboldt R, Lavoie J, Henry A, Vanaret J, Petkova MD, Gregor T, et al. Latent space of a small genetic network: Geometry of dynamics and information. Proc Natl Acad Sci U S A. 2022 ;119(26):e2113651119. PubMed
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Nollmann M, Bennabi I, G?tz M, Gregor T. The Impact of Space and Time on the Functional Output of the Genome. Cold Spring Harb Perspect Biol. 2022 ;14(4). PubMed
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Levo M, Raimundo J, Bing XYang, Sisco Z, Batut PJ, Ryabichko S, et al. Transcriptional coupling of distant regulatory genes in living embryos. Nature. 2022 ;605(7911):754-760. PubMed
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Singh AP, Wu P, Ryabichko S, Raimundo J, Swan M, Wieschaus E, et al. Optogenetic control of the Bicoid morphogen reveals fast and slow modes of gap gene regulation. Cell Rep. 2022 ;38(12):110543. PubMed
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Wang MD, Nicodemi M, Dekker NH, Gregor T, Holcman D, van Oijen AM, et al. Physics meets biology: The joining of two forces to further our understanding of cellular function. Mol Cell. 2021 ;81(15):3033-3037. PubMed
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Bauer M, Petkova MD, Gregor T, Wieschaus EF, Bialek W. Trading bits in the readout from a genetic network. Proc Natl Acad Sci U S A. 2021 ;118(46). PubMed
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Tka?ik G, Gregor T. The many bits of positional information. Development. 2021 ;148(2). PubMed
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Rossine FW, Martinez-Garcia R, Sgro AE, Gregor T, Tarnita CE. Eco-evolutionary significance of "loners". PLoS Biol. 2020 ;18(3):e3000642. PubMed
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Chen H, Gregor T. Using RNA Tags for Multicolor Live Imaging of Chromatin Loci and Transcription in Drosophila Embryos. Methods Mol Biol. 2020 ;2166:373-384. PubMed
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Petkova MD, Tka?ik G, Bialek W, Wieschaus EF, Gregor T. Optimal Decoding of Cellular Identities in a Genetic Network. Cell. 2019 ;176(4):844-855.e15. PubMed
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Zoller B, Little SC, Gregor T. Diverse Spatial Expression Patterns Emerge from Unified Kinetics of Transcriptional Bursting. Cell. 2018 ;175(3):835-847.e25. PubMed
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Chen H, Levo M, Barinov L, Fujioka M, Jaynes JB, Gregor T. Dynamic interplay between enhancer-promoter topology and gene activity. Nat Genet. 2018 ;50(9):1296-1303. PubMed
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Garcia HG, Gregor T. Live Imaging of mRNA Synthesis in Drosophila. Methods Mol Biol. 2018 ;1649:349-357. PubMed
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Little SC, Gregor T. Single mRNA Molecule Detection in Drosophila. Methods Mol Biol. 2018 ;1649:127-142. PubMed
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Gregor T. Beyond D'Arcy Thompson: Future challenges for quantitative biology. Mech Dev. 2017 ;145:10-12. PubMed
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Tikhonov M, Little SC, Gregor T. Only accessible information is useful: insights from gradient-mediated patterning. R Soc Open Sci. 2015 ;2(11):150486. PubMed
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Noorbakhsh J, Schwab DJ, Sgro AE, Gregor T, Mehta P. Modeling oscillations and spiral waves in Dictyostelium populations. Phys Rev E Stat Nonlin Soft Matter Phys. 2015 ;91(6):062711. PubMed
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Sgro AE, Schwab DJ, Noorbakhsh J, Mestler T, Mehta P, Gregor T. From intracellular signaling to population oscillations: bridging size- and time-scales in collective behavior. Mol Syst Biol. 2015 ;11(1):779. PubMed
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Tka?ik G, Dubuis JO, Petkova MD, Gregor T. Positional information, positional error, and readout precision in morphogenesis: a mathematical framework. Genetics. 2015 ;199(1):39-59. PubMed
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Bothma JP, Garcia HG, Ng S, Perry MW, Gregor T, Levine M. Enhancer additivity and non-additivity are determined by enhancer strength in the Drosophila embryo. Elife. 2015 ;4. PubMed
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Bothma JP, Garcia HG, Esposito E, Schlissel G, Gregor T, Levine M. Dynamic regulation of eve stripe 2 expression reveals transcriptional bursts in living Drosophila embryos. Proc Natl Acad Sci U S A. 2014 ;111(29):10598-603. PubMed
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