Bulletin of the American Physical Society
APS March Meeting 2013
Volume 58, Number 1
Monday–Friday, March 18–22, 2013; Baltimore, Maryland
Session U44: Focus Session: Physics of Single-Cell Heterogeneity |
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Sponsoring Units: DBIO Chair: Wolfgang Losert, University of Maryland College Park Room: Hilton Baltimore Holiday Ballroom 1 |
Thursday, March 21, 2013 11:15AM - 11:27AM |
U44.00001: Single-molecule RNA observation in vivo reveals dynamics of co-transcriptional splicing M.L. Ferguson, A. Coulon, V. de Turris, M. Palangat, C.C. Chow, R.H. Singer, D.R. Larson The synthesis of pre-mRNA and the splicing of that pre-mRNA to form completed transcripts requires coordination between two large multi-subunit complexes (the transcription elongation complex and the spliceosome). How this coordination occurs in vivo is unknown. Here we report the first experimental observation of transcription and splicing occurring at the same gene in living cells. By utilizing the PP7/MS2 fluorescent RNA reporter system, we can directly observe two distinct regions of the nascent RNA, allowing us to measure the rise and fall time of the intron and exon of a reporter gene stably integrated into a human cell line. The reporter gene consists of a beta globin gene where we have inserted a 24 RNA hairpin cassette into the intron/exon. Upon synthesis, the RNA hairpins are tightly bound by fluorescently-labeled PP7/MS2 bacteriophage coat proteins. After gene induction, a single locus of active transcription in the nucleus shows fluorescence intensity changes characteristic of the synthesis and excision of the intron/exon. Using fluctuation analysis, we determine the elongation rate to be 1.5 kb/min. From the temporal cross correlation function, we determine that splicing of this gene must be co-transcriptional with a splicing time of $\sim$100 seconds before termination and a $\sim$200 second pause at termination. We propose that dual-color RNA imaging may be extended to investigate other mechanisms of transcription, gene regulation, and RNA processing. [Preview Abstract] |
Thursday, March 21, 2013 11:27AM - 11:39AM |
U44.00002: Cellular volume is a global controller of mRNA abundance Olivia Padovan-Merhar, Arjun Raj Many researchers have observed large variability in the numbers of RNA and protein molecules from cell to cell, a phenomenon thought to result from random bursts of transcription. These findings hold even for genes involved in core cellular processes, raising questions as to how cells can function in the presence of such molecular noise. However, biochemical processes typically depend on concentrations of cellular constituents rather than absolute numbers, so we use RNA fluorescence in situ hybridization to measure mRNA counts and cellular volume in single cells. We find that while both mRNA numbers and volume vary widely between cells, mRNA density does not. Thus, for many genes, mRNA abundance is precisely controlled to match the volume of the cell, as though the genes know how big the cell is. We measure transcription on a global and single-gene scale, and find that transcriptional activity scales with volume, suggesting that density is regulated at a transcriptional level. We present a mathematical model explaining which transcriptional bursting parameters account for the presence or lack of density conservation. Our findings suggest that global properties of RNA dynamics require a reassessment of our understanding of cellular heterogeneity and stochastic gene expression. [Preview Abstract] |
Thursday, March 21, 2013 11:39AM - 11:51AM |
U44.00003: Protocols for discriminating sources of intrinsic noise in gene expression Niraj Kumar, Rahul Kulkarni The intrinsic stochasticity of gene expression leads to heterogeneity of protein levels across a population of cells. Different molecular mechanisms have been proposed that contribute to this variability in protein levels. Among these are Poissonian fluctuations of mRNAs, promoter fluctuations based on a random telegraph process, and general waiting-time distributions (``gestation'') for the arrival of mRNAs. Given these different sources, an important problem in the field is the development of protocols for discriminating the dominant molecular mechanisms giving rise to the observed noise. Considering the ``burst'' limit (for which mRNA lifetimes are much shorter than protein lifetimes) we develop protocols for discriminating the sources of intrinsic noise based on accessible experimental measurements. Computational validation of these protocols indicates that they could lead to promising experimental approaches for discriminating the sources of intrinsic noise in gene expression. [Preview Abstract] |
Thursday, March 21, 2013 11:51AM - 12:27PM |
U44.00004: Relating Single Cell Heterogeneity To Genotype During Cancer Progression Invited Speaker: Satwik Rajaram Progression of normal cells towards cancer is driven by a series of genetic changes. Traditional population-averaged measurements have found that cell signalling activities are increasingly altered during this progression. Despite the fact that cancer cells are known to be highly heterogeneous, the response of individual pathways to specific genetic changes remains poorly characterized at a single cell level. Do signalling alterations in a pathway reflect a shift of the whole population, or changes to specific subpopulations? Are alterations to pathways independent, or are cells with alterations in one pathway more likely to be abnormal in another due to crosstalk? We are building a computational framework that analyzes immunofluorescence microscopy images of cells to identify alterations in individual pathways at a single-cell level. A primary novelty of our approach is a ``change of basis'' that allows us to understand signalling in cancer cells in terms of the much better understood patterns of signalling in normal cells. This allows us to model heterogeneous populations of cancer cells as a mixture of distinct subpopulations, each with a specific combination of signalling pathways altered beyond the normal baseline. We used this framework to analyze human bronchial epithelial cell lines containing a series of genetic modifications commonly seen in lung cancer. We confirmed expected trends (such as a population-wide epithelial mesenchymal transition following the last of our series of modifications) and are presently studying the relation between the mutational profiles of cancer cells and pathway crosstalk. Our framework will help establish a more natural basis for future investigations into the phenotype-genotype relationship in heterogeneous populations. [Preview Abstract] |
Thursday, March 21, 2013 12:27PM - 12:39PM |
U44.00005: Mapping chromatin modifications in nanochannels Shuang Fang Lim, Alena Karpusenko, Robert Riehn DNA and chromatin are elongated to a fixed fraction of their contour length when introduced into quasi-1d nanochannels. Because single molecules are analyzed, their hold great potential for the analysis for the genetic analysis of material from single cells. In this study, we have reconstituted chromatin with histones from a variety of sources, and mapped the modification profile of the chromatin. We monitored methylation and acetylation patterns of the histone tail protein residues using fluorescently labelled antibodies. Using those, we distinguished chromatin reconstituted from chicken erythrocytes, calf thymus, and HeLa cells. We discuss prospects for profiling histone modifications for whole chromosomes from single cells. [Preview Abstract] |
Thursday, March 21, 2013 12:39PM - 12:51PM |
U44.00006: What is Growth? Concurrent determination of a bacterial population's many shades of growth Guillaume Lambert, Edo Kussell One of the most exciting developments in the study of the physics of microbial life is the ability to precisely monitor stochastic variations of gene expression in individual cells. A fundamental question is whether these variations improve the long-term ability of a population to adapt to new environments. While variations in gene expression in bacteria are easily measured through the use of reporter systems such as green fluorescent proteins and its variants, precise determination of a cell's growth rate, and how it is influenced by its immediate environment, remains challenging. Here, we show that many conflicting and ambiguous definitions of bacterial growth can actually be used interchangeably in E. coli. Indeed, by monitoring small populations of E. coli bacteria inside a microfluidic device, we show that seemingly independent measurements of growth (elongation rate and the average division time, for instance) agree very precisely with one another. We combine these definitions with the population's length and age distribution to very precisely quantify the influence of temperature variations on a population's growth rate. We conclude by using coalescence theory to describe the evolution of a population's genetic structure over time. [Preview Abstract] |
Thursday, March 21, 2013 12:51PM - 1:03PM |
U44.00007: Noise in Exponential Growth Srividya Iyer-Biswas, Charles Wright, Jon Henry, Stas Burov, Yihan Lin, Sean Crosson, Aaron Dinner, Norbert Scherer The interplay between growth and division of cells is has been studied in the context of exponential growth of bacterial cells (in suitable conditions) for decades. However, bulk culture studies obscure phenomena that manifest in single cells over many generations. We introduce a unique technology combining microfluidics, single-cell imaging, and quantitative analysis. This enables us to track the growth of single Caulobacter crescentus stalked cells over hundreds of generations. The statistics that we extract indicate a size thresholding mechanism for cell division and a non-trivial scaling collapse of division time distributions at different temperatures. In this talk I shall discuss these observations and a stochastic model of growth and division that captures all our observations with no free parameters. [Preview Abstract] |
Thursday, March 21, 2013 1:03PM - 1:39PM |
U44.00008: From Molecules to Cells to Organisms: Understanding Health and Disease with Multidimensional Single-Cell Methods Invited Speaker: Juli\'an Candia The multidimensional nature of many single-cell measurements (e.g. multiple markers measured simultaneously using Fluorescence-Activated Cell Sorting (FACS) technologies) offers unprecedented opportunities to unravel emergent phenomena that are governed by the cooperative action of multiple elements across different scales, from molecules and proteins to cells and organisms. We will discuss an integrated analysis framework to investigate multicolor FACS data from different perspectives: Singular Value Decomposition to achieve an effective dimensional reduction in the data representation, machine learning techniques to separate different patient classes and improve diagnosis, as well as a novel cell-similarity network analysis method to identify cell subpopulations in an unbiased manner. Besides FACS data, this framework is versatile: in this vein, we will demonstrate an application to the multidimensional single-cell shape analysis of healthy and prematurely aged cells. [Preview Abstract] |
Thursday, March 21, 2013 1:39PM - 1:51PM |
U44.00009: Stochastic Cell Fate Progression in Embryonic Stem Cells Ling-Nan Zou, Adele Doyle, Sumin Jang, Sharad Ramanathan Studies on the directed differentiation of embryonic stem (ES) cells suggest that some early developmental decisions may be stochastic in nature. To identify the sources of this stochasticity, we analyzed the heterogeneous expression of key transcription factors in single ES cells as they adopt distinct germ layer fates. We find that under sufficiently stringent signaling conditions, the choice of lineage is unambiguous. ES cells flow into differentiated fates via diverging paths, defined by sequences of transitional states that exhibit characteristic co-expression of multiple transcription factors. These transitional states have distinct responses to morphogenic stimuli; by sequential exposure to multiple signaling conditions, ES cells are steered towards specific fates. However, the rate at which cells travel down a developmental path is stochastic: cells exposed to the same signaling condition for the same amount of time can populate different states along the same path. The heterogeneity of cell states seen in our experiments therefore does not reflect the stochastic selection of germ layer fates, but the stochastic rate of progression along a chosen developmental path. [Preview Abstract] |
Thursday, March 21, 2013 1:51PM - 2:03PM |
U44.00010: Exact protein distributions for stochastic models of gene expression Rahul Kulkarni, Hodjat Pendar, Thierry Platini Stochasticity in gene expression gives rise to variations in protein levels across a population of genetically identical cells. Such fluctuations can drive phenotypic variation in clonal populations, hence there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. We develop a novel mapping that significantly simplifies the analysis of stochastic models of gene expression. Using this mapping, we derive exact analytical results for steady-state and time-dependent protein distributions for the basic 2-stage model of gene expression. Considering extensions of the basic model, we obtain exact protein steady-state distributions for models that include the effects of post-transcriptional and post-translational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation. [Preview Abstract] |
Thursday, March 21, 2013 2:03PM - 2:15PM |
U44.00011: An Experimental Determination of Static Magnetic Fields Induced Noise in Living Systems Megan Brady, Craig Laramee Living systems are constantly exposed to static magnetic fields (SMFs) from both natural and man-made sources. Exposures vary in dose and duration ranging from geomagnetic ($\sim$50$\mu$T) to residential and industrial ($\sim$10s of mT) fields. Efforts to characterize responses to SMFs have yielded conflicting results, showing a dependence on experimental variables used. Here we argue that low to moderate SMF exposure is a sub-threshold perturbation operating below thermal noise, and assays that evaluate statistical characteristics of a single cell may identify responses not consistently found by population averaging approaches. Recent studies of gene expression show that it is a stochastic process capable of producing bursting dynamics. Moreover, theoretical and experimental methods have also been developed to allow quantitative estimates of the associated biophysical parameters. These developments provide a new way to assess responses of living systems to SMFs. In this work, we report on our efforts to use single molecule fluorescence \textit{in situ} hybridization to assess responses of NIH-3T3 cells to SMF exposure at flux densities ranging from 1 to 440 mT for 48 hours. Results will contribute to determining mechanisms by which SMF exposure influences gene expression. [Preview Abstract] |
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