Vanderbilt University School of Medicine

Neuert, Gregor , Ph.D.
Assistant Professor of Molecular Physiology and Biophysics
Assistant Professor of Biomedical Engineering

Lab Url: http://www.mc.vanderbilt.edu/root/vumc.php?site=neuertlab

Phone Number: 615-343-6404

Email Address:gregor.neuert@vanderbilt.edu

Neuert, Gregor's picture

Office Address   Mailing Address

813C Light Hall

813C light Hall 37232-0615


Research Keywords
Biophysics, Flow cytometry, Gene regulation, Live cell time-lapse microscopy, Long non-coding RNA, Computational modeling, Image processing, Molecular biology, Quantitative biology, Quantitative microscopy, Single cells, Single-molecule based modeling, Single molecule RNA-FISH, Systems biology, Signal transduction, Transcription, Yeast genetics.

Research Specialty
To study and predict dynamic spatial-temporal processes in signal transduction and gene regulation by quantifying individual cells with single-molecule resolution.

Research Description
A current molecular medicine topic of interest is how cells respond dynamically to changes in their environment utilizing their cellular gene, RNA and protein networks. We aim to approach this question by investigating endogenous, signal transduction and transcriptional regulatory networks of coding and non-coding RNA in yeast. Yeast is an ideal model organism for studying these questions because it can be easily manipulated genetically and many biological principles are conserved in humans. We aim to investigate the architecture and functioning of these networks by measuring the dynamics of protein and RNA levels in single cells. Our research methods include a combination of single-cell techniques such as flow cytometry, live cell time-lapse microscopy, fluorescent in-situ hybridization with single-molecule resolution at the RNA level (single-molecule RNA-FISH) in cells and tissue samples as well as single-molecule-based modeling. The main advantage to quantify single cells is to distinguish between different regulatory mechanisms, which cannot be observed in population-based experiments. Since our approach is general, it can lead to similar quantitative understanding of many genes, pathways or organisms ranging from yeast to human.

Publications
Neuert, G, Munsky, B, Tan, RZ, Teytelman, L, Khammash, M, van Oudenaarden, A. Systematic Identification of Signal-Activated Stochastic Gene Regulation. Science, 339(6119), 584-587, 2013.

Bumgarner, SL, Neuert, G, Voight, BF, Symbor-Nagrabska, A, Grisafi, P, van Oudenaarden, A, Fink, GR. Single-cell analysis reveals that noncoding RNAs contribute to clonal heterogeneity by modulating transcription factor recruitment. Mol Cell, 45(4), 470-82, 2012.

Munsky, B, Neuert, G, van Oudenaarden, A. Using gene expression noise to understand gene regulation. Science, 336(6078), 183-7, 2012.

van Werven, FJ, Neuert, G, Hendrick, N, Lardenois, A, Buratowski, S, van Oudenaarden, A, Primig, M, Amon, A. Transcription of Two Long Noncoding RNAs Mediates Mating-Type Control of Gametogenesis in Budding Yeast. Cell, 150(6), 1170-1181, 2012.

Zimmermann, JL, Nicolaus, T, Neuert, G, Blank, K. Thiol-based, site-specific and covalent immobilization of biomolecules for single-molecule experiments. Nat Protoc, 5(6), 975-85, 2010.


Postdoctoral Position Available
Yes

Postdoctoral Position Details
The Neuert Laboratory focuses on studying and predicting dynamic spatial-temporal processes in signal transduction and gene regulation of coding and non-coding RNA by quantifying individual cells with single-molecule resolution.

If you are interested in working on important problems at the interface of biology, engineering and physics please contact Gregor for more detail. We will provide you with a variety of expertise ranging from quantitative microscopy, image processing, yeast genetics, molecular biology to computational modeling.

Gregor has successfully trained more than fifteen undergraduate and graduate students with backgrounds in biology, chemistry, engineering and physics.

Motivated candidates with backgrounds in biology, chemistry, computer science, engineering, medicine or physics are welcome to apply.

If your background is in biology or medicine, no quantitative knowledge is required.

If your background is in chemistry, computer science, engineering, or physics, no biology knowledge is required.

Please send an email to Gregor with a CV and a short description why you are interested in joining the lab.

Updated Date
10/17/2013



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