Mixtures of phosphatidylcholine (PC) and phosphatidic acid (PA) are particularly effective at stabilizing a functional nicotinic acetylcholine receptor (nAChR). To test whether the ability of PA to adopt both monoanionic and dianionic states plays a role in lipid-nAChR interactions, we monitored the ionization state of PA in nAChR-reconstituted membranes. In the presence of the nAChR, PA head groups in PC/PA 3:2 membranes are stabilized in the monoanionic state. Stabilization of monoanionic PA in nAChR-reconstituted membranes accounts for some of the observed increase in membrane gel-to-liquid crystal phase transition temperature (Tm) upon nAChR incorporation, possibly by nAChR-induced pH reduction at the membrane surface. Increasing concentrations of cations at the bilayer surface and diacylglycerol within the bilayer account for the remaining shift in membrane Tm observed upon nAChR incorporation. We conclude that the nAChR, which is a cation-selective ion channel, alters its environment through both cation concentration and enzymatic activity.

The nucleus is an organelle of central importance to the mammalian cell. However, our understanding of the organizations and dynamics of many nuclear structures and processes remains inadequate, largely due to the difficulty in probing them in situ, with single-molecule sensitivity as well as ultra-high resolutions in space and time. In this dissertation, we develop approaches to interrogate, through imaging and modeling, the spatio-temporal organizations and dynamics of two key nuclear processes: gene expression and DNA replication. We first describe a novel fluorescence imaging technique, named reflected light-sheet (RLS) microscopy, that is capable of detecting single molecules with superior signal-to-background ratio inside the mammalian nucleus. By selectively illuminating only a thin section of the nucleus using a light-sheet reflected off a miniature mirror, RLS microscopy combines the capabilities of 3D optical sectioning, fast imaging speed, and applicability to single, normal-sized adherent cells. As demonstration, we apply RLS microscopy to directly monitor the DNA binding dynamics and spatio-temporal colocalization of single mammalian transcription factor molecules in live cells. By measuring their diffusion constants, DNA-bound fraction, as well as in vivo residence times, we resolve three distinct modes of their interaction with genomic DNA. Furthermore, we take advantage of the prowess of RLS illumination for super-resolution microscopy (SRM), attaining resolution improvements critical for resolving nuclear structures with high molecular density. Using RLS-SRM, we map the distribution of RNA polymerase II (RNAP II), the main workhorse of mammalian transcription, which has been proposed to heterogeneously cluster into spatially discrete foci termed “transcription factories”. Leveraging on the photophysics of rhodamine-based dyes, we also develop an image analysis algorithm capable of accurately counting the copy number of RNAP II molecules in these foci. We found that majority of the foci originate from single RNAP II molecules, which exhibit no significant clustering within the length scale of the reported diameters of “transcription factories”, arguing against the prevalent existence of such “factories” as previously believed. We also super-resolve in the mammalian nucleus individual DNA replication domains (RDs), and quantitatively characterize their physical morphology and propagation on a global scale. Our results support a spatio-temporal model for RD dynamics across different stages of S-phase, in which the progression of replicons along chromosomes as well as the nuclear lamina constrains the distribution of DNA synthesis sites and drives the spreading of RDs in specific spatial patterns. Lastly, to better understand the catalytic mechanism of DNA replication at the molecular level, we simulate the dynamics of DNA polymerase, whose catalytic action is accompanied by a large nucleotide-induced movement of its finger domain, using a Langevin-type Gaussian Network Model. Our model captures the induced conformational dynamics of the polymerase upon substrate binding, and reveals its close coupling to the advancement towards transition-state along the reaction coordinate. These results demonstrate the precise role of conformational dynamics in achieving catalysis of the polymerization reaction, and indicate that the mechanism for lowering the reaction barrier through conformational motion is encoded in the structural topology of DNA polymerase. Overall, the strategies developed in this dissertation pave the way for quantitative mapping and characterization of nuclear processes at unprecedented levels of detail, both in space and in time. / Biophysics

The study of chromosome, and genome, organization is a both an ongoing challenge, and one with a long history. Following the advent of high-throughput sequencing and genomic technologies, much research has focused on the one-dimensional, or sequence-level, organization of genomes, with many successes. Nonetheless, genomes are physically organized as chromosomes in the three-dimensional confines of the cell nucleus, with implications for processes including gene regulation, DNA replication, and cell division. Recently, chromosome conformation capture (3C) based methods have enabled new high-resolution and genome-wide views (Hi-C) of chromosome organization in three-dimensions. 3C methods convert direct spatial contacts between pairs of genomic loci into molecular products that can be assayed using high-throughput sequencing. The new views of chromosomal organization enabled by 3C techniques have been the principal motivation for my graduate research. In particular, 3C technologies now pose multiple important computational and theoretical challenges, including how to: (1) process and filter large quantities of experimental data; (2) develop computational models of chromosomes that agree with and help the understanding of experimental data; and (3) integrate views from 3C technologies with other genomic datasets, including complementary characterizations of the chromatin fiber. This thesis presents a series of projects addressing these challenges in chronological order of their publication. The first project relates to the integration of views from Hi-C with other genomic datasets to understand the functional implications of chromosome organization. This project examined the connection between Hi-C chromosome contact maps and the distribution and positions of somatic copy number alterations observed across a variety of cancers. Since the observed alterations are the consequence of both mutational processes and evolutionary pressures on the cancers, we used a population genetics framework to consider how a mutational process governed by polymer physics might manifest in the patterns of alterations observed in cancer genomes. The second project relates to the processing and filtering of Hi-C data. This project investigated how to correct for various biases that could be introduced at different stages of the experimental protocol, and then how to decompose the resulting contact maps into dominant features of chromosomal organization. We found that we could dramatically compress the complexity of chromosome interaction patterns, and that these compressed patterns are surprisingly conserved between humans and mice. These methods have been used by our lab and others to investigate 3C data across a broad range of organisms. The third project involved the analysis of Hi-C data through the cell cycle, and the development of polymer models of chromosome organization in metaphase, when cells are prepared for division. Before cell division, chromosomes undergo extensive compaction; after division, they decondense and resume their cell-type-specific gene expression in interphase. We found that while interphase chromosome organization reflects cell-type-specific programs of gene expression, all traces of this organization are wiped clear in metaphase chromosomes. Our models of metaphase chromosomes allowed us to discriminate between two classic biological hypotheses of metaphase chromosome organization. We found that metaphase chromosomes are inconsistent with classic hierarchical models of folding, yet can be described by a two-stage process of compaction. The fourth project used polymer models to understand how local interactions, or loops, between genomic elements might in turn alter local chromosome organization. This has implications for gene regulation, as the classic model of eukaryotic gene expression requires direct spatial contact between a distal enhancer and a proximal promoter. We found that a chromatin loop can either suppress or facilitate enhancer-promoter interactions, depending on the location of the loop relative to the enhancer-promoter pair, and that looping interactions that do not directly involve an enhancer-promoter pair can nevertheless significantly modulate their interactions / Biophysics

The human body is composed of hundreds of specialized cell types, each fulfilling distinct functions that are together essential for normal tissue homeostasis. This thesis is aimed at identifying genes that contribute to to cell type-specific functions, with major projects focused on (1) a specialized epithelial transport pathway called transcytosis and (2) the challenge of measuring cell type-specific gene expression. In both projects, we applied high-throughput methods to narrow down from the ~25,000 protein coding genes to distinguish the subset that contribute to specialized cellular functions. Common themes include the development of enabling technology and the value of integrating diverse genomic datasets. The results described here implicate new genes in cell type-specific processes and provide a starting place for subsequent investigation into the individual genes and pathways. In the first project, we performed an RNA interference (RNAi) screen to identify genes necessary for receptor-mediated transcytosis, a specialized endosomal pathway in epithelial cells. We developed high-throughput assays to measure the transcytosis of immunoglobulin G (IgG) across cultured epithelial cells in conjunction with gene knockdown. Then we selected a set of 582 candidate genes to screen using a combination of literature review and integrated high-throughput evidence, including expression data, proteomics, and domain annotation. We knocked-down each of these candidates in parallel and identified many reagents that interfered with transcytosis. In small-scale validation assays, we confirmed a reproducible decrease in transcytosis after knocking down 7 genes with multiple independent reagents (7 confirmed out of 8 genes tested). The validated hits included genes with an established role in related pathways, such as EXOC2 and PARD6B, and genes that have not been implicated in epithelial trafficking before, such as LEPROT, VPS13C, and ARMT. In the second project, we developed an approach to identify genes expressed selectively in specific cell types, using a computational algorithm that searches thousands of microarrays for genes with a similar expression profile to known cell type-specific markers. Our method, CellMapper, is accurate without the need for cell isolation and can be applied to any cell type where at least one cell-specific marker gene is known. We demonstrated the approach for 30 diverse cell types, many of which have not been isolated for expression analysis in humans before. Furthermore, we explored the applicability of our method to infer causal relationships in genome-wide association studies (GWAS) and to investigate the transcriptional identity of a poorly understood cell type, enteric glia. We provided a user-friendly R implementation that will enable researchers from systems biology, molecular biology of disease, and population genetics to identify cellular localization of genes of interest or to expand the catalog of known marker genes for difficult-to-isolate cell types. / Biophysics

Understanding biomolecular information at the single-molecule level requires tools for manipulating and observing individual biomolecules at the nanoscale. Programmable DNA nanotechnology provides an ideal interface to bridge engineering principles with biomolecular compatibility, especially with high-information-content, programmable molecular interactions. In my dissertation research, I have focused on two specific topics that both harness the programmable and high-information-content nature of complementary DNA interactions, to arrange and observe biomolecules at the single-molecule level, and with high spatial precision. First, I studied the capability of using self-assembled DNA nanostructure to pattern biomolecules with high precision and tunable spatial arrangement. Previous efforts in DNA nanostructure synthesis with complex patterning have mostly focused on rigid tile-based or DNA origami approaches, which did not provide a modular and scalable method. With my colleagues, I have designed and assembled complex and programmable two-dimensional nano-patterns with a simple and robust synthesis method, based on flexible single-stranded DNA tiles (SST). This method allowed for a modular, scalable, and synthetically economic way of synthesis and biomolecule patterning at the nanoscale, for potential use of studying molecular interactions and construction of novel biomolecular devices. Next, I investigated the capability of using programmable transient DNA hybridisation for optical super-resolution imaging of single biomolecular targets. Recent advances in fluorescence super-resolution microscopy have circumvented the conventional diffraction limit and shown images of sub-cellular features and synthetic nanostructures down to ~15 nm in size, but observation of individual molecular targets remains difficult, and has only been shown with multiple labelling and tens of nanometres target separation. In particular, direct optical observation of individual molecular targets in a densely packed (~5 nm spacing) biomolecular cluster has not been demonstrated. I called this concept "discrete molecular imaging (DMI) and tackled this challenge as part of my dissertation work by adopting the DNA-PAINT method, which utilised programmable transient DNA hybridisation for localisation-based super-resolution microscopy. I proposed systematic characterisation and optimisation of four technical requirements to achieve DMI with DNA-PAINT. I examined the effects of high photon count, high blinking statistics and appropriate blinking duty cycle on imaging quality, and reported a novel software-based drift correction method that achieves <1 nm residual drift (r.m.s.) over hours. With this method, I reported fluorescence imaging of a densely packed triangular lattice pattern with ~5 nm point-to-point distance, and analysed DNA origami structural offset with angstrom-level precision (<2 A) from single-molecule studies. Combined with multiplexed exchange-PAINT imaging, I further demonstrated an optical nano-display with 5x5 nm pixel size and three distinct colours, and with <1 nm cross-channel registration accuracy. After this study, I further extended the capability of single-molecule observation from nanostructures to cellular environments. Super-resolution imaging of single molecular targets have been difficult in cellular context, due to high levels of fluorescence background and potential crosstalk between multiple fluorophores. In my dissertation work, I proposed a data analysis framework that exploits the repetitive blinking that is typical of DNA-PAINT, and performs temporal analysis on single-target blinking time traces to detect single targets in noisy environment. With my colleagues, I first studied the possibility of kinetic trace profiling and accurate blinking on-time for kinetic multiplexing, then applied the method to detect single-copy mRNA targets in situ. As a proof of principle, I demonstrated specific and sensitive single-target detection with this method in fixed cells. Taken together, the two branches of nanotechnology that have tried to develop during my dissertation, a modular and versatile synthesis method for nanoscale molecular organisation and templating, as well as an imaging method capable of visualising and interrogating singly-labelled molecular targets, from a complementary package of nanoscale research tools towards enabling a thorough molecular characterisation of biology. / Biophysics

Natural materials, such as bone, integrate living cells composed of organic molecules together with inorganic components. This enables combinations of functionalities, such as mechanical strength and the ability to regenerate and remodel, which are not present in existing synthetic materials. Taking a cue from nature, we propose that engineered ‘living functional materials’ and ‘living materials synthesis platforms’ that incorporate both living systems and inorganic components could transform the performance and the manufacturing of materials1. As a proof-of-concept, we recently demonstrated that synthetic gene circuits in Escherichia coli enabled biofilms to be both a functional material in its own right and a materials-synthesis platform. To demonstrate the former, we engineered E. coli biofilms into a chemical-inducer-responsive electrical switch. To demonstrate the latter, we engineered E. coli biofilms to dynamically organize biotic-abiotic materials across multiple length scales, template gold nanorods, gold nanowires, and metal/semiconductor heterostructures, and synthesize semiconductor nanoparticles1. Thus, tools from synthetic biology, such as those for artificial gene regulation, can be used to engineer the spatiotemporal characteristics of living systems and to interface living systems with inorganic materials. Such hybrids can possess novel properties enabled by living cells while retaining desirable functionalities of inorganic systems. These systems, as living functional materials and as living materials foundries, would provide a radically different paradigm of materials performance and synthesis – materials possessing multifunctional, self-healing, adaptable, and evolvable properties that are created and organized in a distributed, bottom-up, autonomously assembled, and environmentally sustainable manner. / Biophysics

Bistability, in which a system has two stable states, is a common property of many dynamic systems. This thesis explores the properties of such systems across a range of length scales, from gene circuits to ecosystems. Cells often store memories of environmental stimuli using bistable gene circuits. High fidelity memory storage requires that a state has a long lifetime. However, an underappreciated aspect of stable memory is that the distance from a bifurcation could determine how sensitive a state is to perturbations in the extracellular environment. We predict that cell memory should become increasingly sensitive to perturbations near a bifurcation and test this idea in three different gene circuits: a toggle switch, the yeast galactose utilization network, and the E. coli lactose utilization network. In a second study, we explore how the environmental context in which two species interact can influence their mode of interaction. Two species in nature often form reciprocally beneficial partnerships termed mutualisms, but in certain environmental regimes the species might shift to competing with one another for resources. This mutualism-competition transition has been understudied in experimental ecosystems. Using a synthetic yeast cross-feeding mutualism, we modulate the degree to which two partners rely on each other by supplementing the cells with variable amounts of nutrients. Surprisingly, we find that as the amount of supplemented nutrients is increased, the system passes through eight qualitatively distinct dynamic regimes: extinction, obligatory mutualism, obligatory/facultative mutualism, facultative mutualism, parasitism, amensalism, competition, and competitive exclusion. In a third study, we probe how population growth dynamics can influence the probability of evolutionary rescue. Natural populations frequently face harsh environments in which their death rate exceeds their birth rate and population size tends toward zero. In such scenarios, populations can either go extinct, migrate to a better habitat, or adapt to the harsh environment. Natural populations often exhibit an “Allee effect,” in which populations grow slowly at low density due to struggles with such behaviors as finding a mate or collective hunting. We hypothesize that the presence of an Allee effect could impede evolutionary rescue and confirm this hypothesis in a model laboratory yeast ecosystem. / Biophysics

Important goals of developmental biology include identifying cell types, understanding the sequence of lineage choices made by multipotent cells and unconvering the molecular networks controlling these decisions. Achieving these goals through computational analysis of gene expression data has been difficult. In this dissertation supervised by Sharad Ramanathan, I develop a probabilistic framework to identify cell types, infer lineage relationships and discover core gene networks controlling lineage decisions. Working with Sandeep Choubey and Sumin Jang, we infer the gene expression dynamics of early differentiation of mouse embryonic stem cells, revealing discrete state transitions across nine cell states. Using a probabilistic model of the gene regulatory networks, we predict that these states are further defined by distinct responses to perturbations and experimentally verify three such examples of state-dependent behavior. Working with Vilas Menon and Sam Melton, we infer a lineage tree for early neural development and putative regulatory transcription factors from single-cell transcriptomic profiles. The lineage tree shows a prominent bifurcation between cortical and mid/hindbrain cell types, and the inferred lineage relationships were confirmed by clonal analysis experiments. In summary, this study provides a framework to infer predictive models of the gene regulatory networks that drive cell fate decisions. / Biophysics

Weakly electric fish continuously emit a quasi-sinusoidal electric organ discharge (EOD) to probe their near environment (electrolocation). P-type tuberous receptors located on their skin respond to the periodic EOD by triggering action potentials in a phase locked manner. It is observed that the intervals between firing times are random multiples of the EOD period. This is known as skipping. Weak carrier amplitude modulations caused by relevant stimuli are encoded by P-type receptors through modulation of their output firing rate. We investigate the effect of P---the baseline firing probability per EOD cycle of a receptor---as well as of other parameters on the quality of information transfer in four biophysically plausible numerical receptor models. In particular, we study how internal noise affects the transduction of random EOD modulations, since noise is perhaps essential for good neural computation. Information is quantified using the stimulus reconstruction technique. We discuss the firing characteristics of the four considered models and discuss their relevance as models of P-afferents. Our information measurements indicate that the presence of noise may enhance information transfer in these receptors. And the coding quality is found to not depend on P alone, but also on the actual combination of biophysical parameters that determine P.

Dans le cadre du programme international d'analyse du genome humain, nombres d'efforts sont actuellement deployes pour augmenter le nombre de bandes qui peuvent etre lues par experience d'electrophorese. Ici, nous etudions comment le fait d'ajouter une grosse proteine neutre (la streptavidine) a un des bouts des molecules d'ADN va modifier leur dynamique quand on en fait l'electrophorese dans un gel. Un modele analytique base sur une equation de diffusion a ete developpe et montre des resultats qui sont en accord qualitatif avec les simulations numeriques et avec les experiences. Ce modele est le seul qui permet d'etudier le coefficient de diffusion, ce qui nous permet d'evaluer le facteur de resolution. En plus de ce modele theorique, des simulations ont ete effectuees et nous ont permis de mieux comprendre comment les processus de piegeage et de depiegeage vont influencer la dynamique du systeme en champs constants et en champs pulses. Nous prevoyons ainsi certains effets anomaux qui pourront etre verifies sous peu. De plus, les resultats de nos simulations nous suggerent de nouvelles methodes pour augmenter l'efficacite de l'electrophorese de piegeage.