Posts Tagged ‘Drosophila’

Only accessible information is useful: insights from gradient-mediated patterning

Mikhail Tikhonov, Shawn C. Little, and Thomas Gregor. Roy. Soc. Open Sci. 2: 150486 (2015). (more…)

Enhancer additivity and non-additivity are determined by enhancer strength in the Drosophila embryo

Jacques Bothma, Hernan Garcia, Samuel Ng, Michael W. Perry, Thomas Gregor, and Michael S. Levine. eLife 2015; 4:e07956 (2015). (more…)

Positional information, positional error, and read-out precision in morphogenesis: a mathematical framework

Gasper Tkačik, Julien O. Dubuis, Mariela D. Petkova, and Thomas Gregor. Genetics 199 (1): 39–59 (2015).  (more…)

The embryo as a laboratory: quantifying transcription in Drosophila

Thomas Gregor, Hernan G. Garcia, Shawn C. Little. Trends in Genetics 30 (8): 364–375 (2014).
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Dynamic Regulation of Eve Stripe 2 Expression Reveals Transcriptional Bursts in Living Drosophila Embryos

Jacques P. Bothma, Hernan G. Garcia, Emilia Esposito, Gavin Schlissel, Thomas Gregor, Michael S. Levine. PNAS 111 (29): 10598–10603 (2014).
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Fly wing vein patterns have spatial reproducibility of a single cell

Laurent Abouchar, Mariela D. Petkova, Cynthia R. Steinhardt, and Thomas Gregor.  J. Roy. Soc. Interface 11 (97): 20140443 (2014).
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Lots of November Press for TGLab

“Seeing the Pattern”
Nature Reviews Genetics (PDF)

“Measuring Transcription to Follow Embryo Development”
BioTechniques News Highlight

“Scientist to watch: Thomas Gregor – Biological Quantifier”
The Scientist

“Development: Lights, Camera, Action — The Drosophila Embryo Goes Live!”
Current Biology Dispatch by Bothma and Levine (PDF)

“Nature – the IT wizard”
Nautilus Magazine

Maternal origins of developmental reproducibility

Mariela D. Petkova, Shawn C. Little, Feng Liu, and Thomas Gregor. Current Biology 24 (11): 1283–1288 (2014).
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Morphogenesis at criticality

Dmitry Krotov, Julien O. Dubuis, Thomas Gregor, and William Bialek. PNAS 111 (10): 3683–3688 (2014).
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Quantitative imaging of transcription in living Drosophila embryos links polymerase activity to patterning

Hernan G. Garcia, Mikhail Tikhonov, Albert Lin and Thomas Gregor. Current Biology 23, 2140–2145 (2013).
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Precision and reproducibility of macroscopic developmental patterns

Laurent Abouchar, Mariela D. Petkova, Cynthia R. Steinhardt, and Thomas Gregor (2013).  arXiv.org:1309.6273 [q-bio.TO].
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Positional information, in bits

Julien O. Dubuis, Gasper Tkacik, Eric F. Wieschaus, Thomas Gregor and William Bialek, PNAS 110, 16301-16308 (2013).
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Precise developmental gene expression arises from globally stochastic transcriptional activity

Shawn C. Little, Mikhail Tikhonov and Thomas Gregor, Cell 154, 789–800 (2013).
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Dynamic interpretation of maternal inputs by the Drosophila segmentation gene network

Feng Liu, Alexander H. Morrison and Thomas Gregor, PNAS 110: 6724–6729 (2013).
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Accurate measurements of dynamics and reproducibility in small genetic networks

Julien O. Dubuis, Reba Samanta and Thomas Gregor, Molecular Systems Biology 9: 639 (2013).
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2. Biological pattern formation

Currently, the most advanced topic in the lab is our work on biological pattern formation in developing fruit fly embryos; partly because this project evolves in an environment that has a long tradition at Princeton. How does an organism form a body axis, and how are the different body parts along this axis patterned and established is one of the most fundamental questions in developmental biology, and with current access to quantitative data the prospect of exposing general theoretical principles in the biological context, similar to our understanding of physical pattern formation, are conspicuous. My laboratory has chosen the earliest patterning events of the fly embryo for the conceptual reason that the blueprint for the future adult structure is determined entirely during this time, and for the practical reasons of ease of experimental access, and of the powerful scientific environment at Princeton in this field. Pattering at these early stages consists mainly in the differential expression of genes, where Princeton has been developing tools to quantify protein levels in living and fixed embryos since the early 2000s, both experimental and theoretical.

In the past 2.5 years my laboratory has focussed mainly on widening our tool chest to quantify patterning in the early embryo. The goal of these technical improvements is to obtain eventually a fully quantitative (absolute numbers) dynamic picture of the entire patterning process, and address issues such as reproducibility, precision or scaling of the patterning events. We have developed a method to count individual molecules of mRNA in whole fixed embryos, which gives us besides proteins an independent access into the transcriptional regulatory machinery and will hopefully allow us to quantify the ??central dogma?? at the molecular level in a natural multicellular context. We have made progress on expanding our investigation of patterning dynamics in living embryos (originally restricted to the maternal input gradient of Bicoid protein concentration) to other members of the regulatory network, which is formed by a cascade of interconnected genes that together with the input gradients determine the final body pattern within the first three hours of the embryo??s development. Using genetic engineering, we are in the process of labeling the gene products of this network with multicolored fluorescent proteins, for both mRNA and protein. In parallel we are developing microscopes that can track the concentrations of these differently colored molecules in living embryos, where we are facing challenges at the level of spectral unmixing, light exposure of the living specimen, and size constraints of our specimen that affect both spatial and temporal resolution of our data.

 

Current projects

The following paragraphs summarize the projects that are currently progressing in the lab to contribute to the execution of the program outlined above:

  1. Originally instigated in the summer of 2009 by an undergraduate project, we developed a novel mRNA quantification method in fly embryos, the core concept of which was published last year as a proof of principle. We essentially tag individual mRNA particles with fluorescent probes in fixed tissue and use diffraction-limited confocal microscopy to image and count. The real challenge of this method, however, was to convince ourselves that we are indeed looking at individual molecules (and not spots or aggregates of molecules) and that we can indeed count all of them. A further challenge was to go beyond simple spot identification, and to quantify the actual intensities that we obtain per spot. Intensities at the DNA location of active native transcription reveal the actual transcriptional state of that site at the moment of specimen fixation. Using multiple colors on the same site we will be able to even extract dynamic parameters such as binding rates and lifetimes from our data. We have resolved most of these challenges over the last year in a very talented team composed of a postdoc, a graduate student and an undergraduate. Using this powerful method and some of the other tools currently developed in the laboratory I am convinced that we will be able to reveal many of the molecular underpinnings of transcriptional regulation in the early fly embryo over the next few years.
  2. The wealth of approaches developed in molecular biology over the past decades gives us the luxury in this field to do the same experiment twice, but with a completely different set of systematic errors. Consequently, over the past two years we have developed an independent way to measure the mean number of mRNA molecules in single embryos. Our method exploits a combination of polymerase-chain-reactions (PCR) with techniques typically used by biochemists, and by making sure at each step we understand what we do to our absolute numbers of initial mRNA molecules. The key is then to compare the numbers we get from single embryos with a precisely quantified molecular standard. The means of the two methods match within less than either of the two standard deviations.
  3. Again in the spirit of an alternative approach to the same problem, we are also developing a direct handle on transcriptional dynamics by directly labeling mRNA strands with fluorescent proteins. This technique has been pioneered in bacteria to trace individual mRNA molecules and in fly embryos to trace mRNA aggregates. We are extending this application to reveal the dynamics of nascent mRNA molecules as they are assembled at the DNA transcription site in living fly embryos. By simultaneously measuring fluorescently labeled input transcription factors (as we have done in the past) and mRNA output dynamics we will be able to extract dynamic input-output relations of transcription in a natural, which has never been done in any biological system. We thus will have a fine tool at hand to put models of transcriptional regulation to a real quantitative test.
  4. We are collaborating with Bill Bialek (Princeton/Physics) and Eric Wieschaus (Princeton/Molecular Biology) to measure the amount of information transmitted through the gene network, testing the idea whether optimization principles govern and apply during early fly patterning, i.e. is there an optimal matching between the distribution of transcription factor concentrations and the noise levels in the control mechanism? What would be the structure of of genetic regulatory networks that maximize information transmission, if they optimize their regulatory power and precision while using a limited number of molecules? We are currently measuring information that is transmitted through the gene network that controls the early patterning events in the fly embryo, and initial results are about to be disclosed in full.
  5. Perturbation experiments have a long tradition in both the physical and biological sciences to understand complex processes and networks. In biology, however, it is customary to perform such perturbations in terms of a mutation analyses which result in the partial or complete disruption of the function of a particular protein. In reality, such a mutation is much more than a simple perturbation, as it leads to a transformation of the original network to a new and completely different network that has one less node. To avoid such a disruptive perturbation, my laboratory has developed a system in which we have a dial knob for the network??s input concentration. We genetically generated a set of fly lines that express the input protein Bicoid at dosages that differ from its wild type expression level in increments of 10-20% up to factors of 2.5-3 in either direction. We are currently in the process to carefully measure the response of the network to these subtle absolute input concentration changes. Our preliminary results indicate that the traditional picture of a local concentration readout may no longer be in agreement with our observations.

Quantifying the Bicoid morphogen gradient in living fly embryos

Alexander H. Morrison, Martin Scheeler Julien O. Dubuis and Thomas GregorCold Spring Harb Protoc. 2012(4): 398-406 (2012).
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Researchers Develop Improved Method to Visualize Biologic Molecules

PLoS Press Release for our first paper on mRNA quantification in whole embryos.

“How are biologic molecules arranged inside the embryo so that embryonic development occurs reliably every time? Princeton researchers, led by Thomas Gregor, an assistant professor of physics and the Lewis-Sigler Institute for Integrative Genomics, and Shawn Little, a postdoctoral fellow in the laboratory of Professor Eric Wieschaus in the Department of Molecular Biology, have developed a new method to better understand how an embryo’s basic molecular makeup helps ensure that the embryo’s development occurs reliably every time. The results of this research into the fruit fly Drosophila introduce a method for making precise measurements of biologic units (so-called mRNA molecules) that play a key role in development. The findings are published in the March 1st issue of  in the online, open access journal PLoS Biology.”

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The formation of the Bicoid morphogen gradient requires protein movement from anteriorly localized mRNA.

Shawn Little, Gašper Tkačik, Thomas Kneeland, Eric Wieschaus and Thomas Gregor, PLoS Biology 9(3): e1000596 (2011).
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