The LIN-3 gene of the nematode C. elegans is the vulval-inducing signal

The development of the vulva of the nematode Caenorhabditis elegans is induced by a signal from the anchor cell of the somatic gonad. Activity of the gene lin-3 is required for the Vulval Precursor Cells (VPCs) to assume vulval fates. It is shown here that lin-3 encodes the vulval-inducing signal.

lin-3 was molecularly cloned by transposon-tagging and shown to encode a nematode member ofthe Epidermal Growth Factor (EGF) family. Genetic epistasis experiments indicate that lin-3 acts upstream of let-23, which encodes a homologue of the EGF-Receptor.

lin-3 transgenes that contain multiple copies of wild-type lin-3 genomic DNA clones confer a dominant multivulva phenotype in which up to all six of the VPCs assume vulval fates. The properties of these trans genes suggest that lin-3 can act in the anchor cell to induce vulval fates. Ablation of the gonadal precursors, which prevents the development of the AC, strongly reduces the ability of lin-3 transgenes to stimulate vulval development. A lin-3 recorder transgene that retains the ability to stimulate vulval development is expressed specifically in the anchor cell at the time of vulval induction.

Expression of an obligate secreted form of the EGF domain of Lin-S from a heterologous promoter is sufficient to induce vulval fates in the absence of the normal source of the inductive signal. This result suggests that Lin-S may act as a secreted factor, and that Lin-S may be the sole vulval-inducing signal made by the anchor cell.

lin-3 transgenes can cause adjacent VPCs to assume the 1° vulval fate and thus can override the action of the lateral signal mediated by lin-12 that normally prevents adjacent 1° fates. This indicates that the production of Lin-3 by the anchor cell must be limited to allow the VPCs to assume the proper pattern of fates of so 3° 3° 2° 1° 2° 3°.

Exploration of new drug delivery pathways: I. Mechanism of folate uptake in cultured human cells. II. Role of nuclear localization signal peptides in the delivery of oligonucleotide into reconstituted nuclei

The roles of the folate receptor and an anion carrier in the uptake of 5- methyltetrahydrofolate (5-MeH_4folate) were studied in cultured human (KB) cells using radioactive 5-MeH_4folate. Binding of the 5-MeH_4folate was inhibited by folic acid, but not by probenecid, an anion carrier inhibitor. The internalization of 5-MeH_4folate was inhibited by low temperature, folic acid, probenecid and methotrexate. Prolonged incubation of cells in the presence of high concentrations of probenecid appeared to inhibit endocytosis of folatereceptors as well as the anion carrier. The V_(max) and K_M values for the carrier were 8.65 ± 0.55 pmol/min/mg cell protein and 3.74 ± 0.54µM, respectively. The transport of 5-MeH4folate was competitively inhibited by folic acid, probenecid and methotrexate. The carrier dissociation constants for folic acid, probenecid and methotreate were 641 µM, 2.23 mM and 13.8 µM, respectively. Kinetic analysis suggests that 5-MeH_4folate at physiological concentration is transported through an anion carrier with the characteristics of the reduced-folate carrier after 5-MeH_4folate is endocytosed by folate receptors in KB cells. Our data with KB cells suggest that folate receptors and probenecid-sensitive carriers work in tandem to transport 5-MeH_4folate to the cytoplasm of cells, based upon the assumption that 1 mM probenecid does not interfere with the acidification of the vesicle where the folate receptors are endocytosed.

Oligodeoxynucleotides designed to hybridize to specific mRNA sequences (antisense oligonucleotides) or double stranded DNA sequences have been used to inhibit the synthesis of a number of cellular and viral proteins (Crooke, S. T. (1993) FASEB J. 7, 533-539; Carter, G. and Lemoine, N. R. (1993) Br. J. Cacer 67, 869-876; Stein, C. A. and cohen, J. S. (1988) Cancer Res. 48, 2659-2668). However, the distribution of the delivered oligonucleotides in the cell, i.e., in the cytoplasm or in the nucleus has not been clearly defined. We studied the kinetics of oligonucleotide transport into the cell nucleus using reconstituted cell nuclei as a model system. We present evidences here that oligonucleotides can freely diffuse into reconstituted nuclei. Our results are consistent with the reports by Leonetti et al. (Proc. Natl. Acad. Sci. USA, Vol. 88, pp. 2702-2706, April 1991), which were published while we were carrying this research independently. We also investigated whether a synthetic nuclear localization signal (NLS) peptide of SV40 T antigen could be used for the nuclear targeting of oligonucleotides. We synthesized a nuclear localization signal peptide-conjugated oligonucleotide to see if a nuclear localization signal peptide can enhance the uptake of oligonucleotides into reconstituted nuclei of Xenopus. Uptake of the NLS peptide-conjugated oligonucleotide was comparable to the control oligonucleotide at similar concentrations, suggesting that the NLS signal peptide does not significantly enhance the nuclear accumulation of oligonucleotides. This result is probably due to the small size of the oligonucleotide.

On reconstruction theorems in noncommutative Riemannian geometry

We present a novel account of the theory of commutative spectral triples and their two closest noncommutative generalisations, almost-commutative spectral triples and toric noncommutative manifolds, with a focus on reconstruction theorems, viz, abstract, functional-analytic characterisations of global-analytically defined classes of spectral triples. We begin by reinterpreting Connes's reconstruction theorem for commutative spectral triples as a complete noncommutative-geometric characterisation of Dirac-type operators on compact oriented Riemannian manifolds, and in the process clarify folklore concerning stability of properties of spectral triples under suitable perturbation of the Dirac operator. Next, we apply this reinterpretation of the commutative reconstruction theorem to obtain a reconstruction theorem for almost-commutative spectral triples. In particular, we propose a revised, manifestly global-analytic definition of almost-commutative spectral triple, and, as an application of this global-analytic perspective, obtain a general result relating the spectral action on the total space of a finite normal compact oriented Riemannian cover to that on the base space. Throughout, we discuss the relevant refinements of these definitions and results to the case of real commutative and almost-commutative spectral triples. Finally, we outline progess towards a reconstruction theorem for toric noncommutative manifolds.

New directions in sparse sampling and estimation for underdetermined systems

A central objective in signal processing is to infer meaningful information from a set of measurements or data. While most signal models have an overdetermined structure (the number of unknowns less than the number of equations), traditionally very few statistical estimation problems have considered a data model which is underdetermined (number of unknowns more than the number of equations). However, in recent times, an explosion of theoretical and computational methods have been developed primarily to study underdetermined systems by imposing sparsity on the unknown variables. This is motivated by the observation that inspite of the huge volume of data that arises in sensor networks, genomics, imaging, particle physics, web search etc., their information content is often much smaller compared to the number of raw measurements. This has given rise to the possibility of reducing the number of measurements by down sampling the data, which automatically gives rise to underdetermined systems.

In this thesis, we provide new directions for estimation in an underdetermined system, both for a class of parameter estimation problems and also for the problem of sparse recovery in compressive sensing. There are two main contributions of the thesis: design of new sampling and statistical estimation algorithms for array processing, and development of improved guarantees for sparse reconstruction by introducing a statistical framework to the recovery problem.

We consider underdetermined observation models in array processing where the number of unknown sources simultaneously received by the array can be considerably larger than the number of physical sensors. We study new sparse spatial sampling schemes (array geometries) as well as propose new recovery algorithms that can exploit priors on the unknown signals and unambiguously identify all the sources. The proposed sampling structure is generic enough to be extended to multiple dimensions as well as to exploit different kinds of priors in the model such as correlation, higher order moments, etc.

Recognizing the role of correlation priors and suitable sampling schemes for underdetermined estimation in array processing, we introduce a correlation aware framework for recovering sparse support in compressive sensing. We show that it is possible to strictly increase the size of the recoverable sparse support using this framework provided the measurement matrix is suitably designed. The proposed nested and coprime arrays are shown to be appropriate candidates in this regard. We also provide new guarantees for convex and greedy formulations of the support recovery problem and demonstrate that it is possible to strictly improve upon existing guarantees.

This new paradigm of underdetermined estimation that explicitly establishes the fundamental interplay between sampling, statistical priors and the underlying sparsity, leads to exciting future research directions in a variety of application areas, and also gives rise to new questions that can lead to stand-alone theoretical results in their own right.

Signal transduction with hybridization chain reactions

Some of the most exciting developments in the field of nucleic acid engineering include the utilization of synthetic nucleic acid molecular devices as gene regulators, as disease marker detectors, and most recently, as therapeutic agents. The common thread between these technologies is their reliance on the detection of specific nucleic acid input markers to generate some desirable output, such as a change in the copy number of an mRNA (for gene regulation), a change in the emitted light intensity (for some diagnostics), and a change in cell state within an organism (for therapeutics). The research presented in this thesis likewise focuses on engineering molecular tools that detect specific nucleic acid inputs, and respond with useful outputs.

Four contributions to the field of nucleic acid engineering are presented: (1) the construction of a single nucleotide polymorphism (SNP) detector based on the mechanism of hybridization chain reaction (HCR); (2) the utilization of a single-stranded oligonucleotide molecular Scavenger as a means of enhancing HCR selectivity; (3) the implementation of Quenched HCR, a technique that facilitates transduction of a nucleic acid chemical input into an optical (light) output, and (4) the engineering of conditional probes that function as sequence transducers, receiving target signal as input and providing a sequence of choice as output. These programmable molecular systems are conceptually well-suited for performing wash-free, highly selective rapid genotyping and expression profiling in vitro, in situ, and potentially in living cells.

Signal transduction, regulation, and developmental logic of EGFR signalling in C. elegans

RTKs-mediated signaling systems and the pathways with which they interact (e.g., those initiated by G protein-mediated signaling) involve a highly cooperative network that sense a large number of cellular inputs and then integrate, amplify, and process this information to orchestrate an appropriate set of cellular responses. The responses include virtually all aspects of cell function, from the most fundamental (proliferation, differentiation) to the most specialized (movement, metabolism, chemosensation). The basic tenets of RTK signaling system seem rather well established. Yet, new pathways and even new molecular players continue to be discovered. Although we believe that many of the essential modules of RTK signaling system are rather well understood, we have relatively little knowledge of the extent of interaction among these modules and their overall quantitative importance.

My research has encompassed the study of both positive and negative signaling by RTKs in C. elegans. I identified the C. elegans S0S-1 gene and showed that it is necessary for multiple RAS-mediated developmental signals. In addition, I demonstrated that there is a SOS-1-independent signaling during RAS-mediated vulval differentiation. By assessing signal outputs from various triple mutants, I have concluded that this SOS-1-independent signaling is not mediated by PTP-2/SHP-2 or the removal of inhibition by GAP-1/ RasGAP and it is not under regulation by SLI-1/Cb1. I speculate that there is either another exchange factor for RASor an as yet unidentified signaling pathway operating during RAS-mediated vulval induction in C. elegans.

In an attempt to uncover the molecular mechanisms of negative regulation of EGFR signaling by SLI-1/Cb1, I and two other colleagues codiscovered that RING finger domain of SLI-1 is partially dispensable for activity. This structure-function analysis shows that there is an ubiquitin protein ligase-independent activity for SLI-1 in regulating EGFR signaling. Further, we identified an inhibitory tyrosine of LET-23/ EGFR requiring sli-1(+)for its effects: removal of this tyrosine closely mimics loss of sli-1 but not loss of other negative regulator function.

By comparative analysis of two RTK pathways with similar signaling mechanisms, I have found that clr-1, a previously identified negative regulator of egl-15 mediated FGFR signaling, is also involved in let-23 EGFR signaling. The success of this approach promises a similar reciprocal test and could potentially extend to the study of other signaling pathways with similar signaling logic.

Finally, by correlating the developmental expression of lin-3 EGF to let-23 EGFR signaling activity, I demonstrated the existence of reciprocal EGF signaling in coordinating the morphogenesis of epithelia. This developmental logic of EGF signaling could provide a basis to understand a universal mechanism for organogenesis.

Mechanisms of substrate selection by the signal recognition particle

The signal recognition particle (SRP) targets membrane and secretory proteins to their correct cellular destination with remarkably high fidelity. Previous studies have shown that multiple checkpoints exist within this targeting pathway that allows ‘correct cargo’ to be quickly and efficiently targeted and for ‘incorrect cargo’ to be promptly rejected. In this work, we delved further into understanding the mechanisms of how substrates are selected or discarded by the SRP. First, we discovered the role of the SRP fingerloop and how it activates the SRP and SRP receptor (SR) GTPases to target and unload cargo in response to signal sequence binding. Second, we learned how an ‘avoidance signal’ found in the bacterial autotransporter, EspP, allows this protein to escape the SRP pathway by causing the SRP and SR to form a ‘distorted’ complex that is inefficient in delivering the cargo to the membrane. Lastly, we determined how Trigger Factor, a co-translational chaperone, helps SRP discriminate against ‘incorrect cargo’ at three distinct stages: SRP binding to RNC; targeting of RNC to the membrane via SRP-FtsY assembly; and stronger antagonism of SRP targeting of ribosomes bearing nascent polypeptides that exceed a critical length. Overall, results delineate the rich underlying mechanisms by which SRP recognizes its substrates, which in turn activates the targeting pathway and provides a conceptual foundation to understand how timely and accurate selection of substrates is achieved by this protein targeting machinery.

Convex Relaxation for Low-Dimensional Representation: Phase Transitions and Limitations

There is a growing interest in taking advantage of possible patterns and structures in data so as to extract the desired information and overcome the curse of dimensionality. In a wide range of applications, including computer vision, machine learning, medical imaging, and social networks, the signal that gives rise to the observations can be modeled to be approximately sparse and exploiting this fact can be very beneficial. This has led to an immense interest in the problem of efficiently reconstructing a sparse signal from limited linear observations. More recently, low-rank approximation techniques have become prominent tools to approach problems arising in machine learning, system identification and quantum tomography.

In sparse and low-rank estimation problems, the challenge is the inherent intractability of the objective function, and one needs efficient methods to capture the low-dimensionality of these models. Convex optimization is often a promising tool to attack such problems. An intractable problem with a combinatorial objective can often be "relaxed" to obtain a tractable but almost as powerful convex optimization problem. This dissertation studies convex optimization techniques that can take advantage of low-dimensional representations of the underlying high-dimensional data. We provide provable guarantees that ensure that the proposed algorithms will succeed under reasonable conditions, and answer questions of the following flavor:

More specifically, i) Focusing on linear inverse problems, we generalize the classical error bounds known for the least-squares technique to the lasso formulation, which incorporates the signal model. ii) We show that intuitive convex approaches do not perform as well as expected when it comes to signals that have multiple low-dimensional structures simultaneously. iii) Finally, we propose convex relaxations for the graph clustering problem and give sharp performance guarantees for a family of graphs arising from the so-called stochastic block model. We pay particular attention to the following aspects. For i) and ii), we aim to provide a general geometric framework, in which the results on sparse and low-rank estimation can be obtained as special cases. For i) and iii), we investigate the precise performance characterization, which yields the right constants in our bounds and the true dependence between the problem parameters.

The conjugate representation of signal envelope

The problem of the representation of signal envelope is treated, motivated by the classical Hilbert representation in which the envelope is represented in terms of the received signal and its Hilbert transform. It is shown that the Hilbert representation is the proper one if the received signal is strictly bandlimited but that some other filter is more appropriate in the bandunlimited case. A specific alternative filter, the conjugate filter, is proposed and the overall envelope estimation error is evaluated to show that for a specific received signal power spectral density the proposed filter yields a lower envelope error than the Hilbert filter.

The oculomotor system: (1) Vertical-horizontal interaction and signal recognition, (2) Time delays and power spectra

In the first section of this thesis, two-dimensional properties of the human eye movement control system were studied. The vertical - horizontal interaction was investigated by using a two-dimensional target motion consisting of a sinusoid in one of the directions vertical or horizontal, and low-pass filtered Gaussian random motion of variable bandwidth (and hence information content) in the orthogonal direction. It was found that the random motion reduced the efficiency of the sinusoidal tracking. However, the sinusoidal tracking was only slightly dependent on the bandwidth of the random motion. Thus the system should be thought of as consisting of two independent channels with a small amount of mutual cross-talk.

These target motions were then rotated to discover whether or not the system is capable of recognizing the two-component nature of the target motion. That is, the sinusoid was presented along an oblique line (neither vertical nor horizontal) with the random motion orthogonal to it. The system did not simply track the vertical and horizontal components of motion, but rotated its frame of reference so that its two tracking channels coincided with the directions of the two target motion components. This recognition occurred even when the two orthogonal motions were both random, but with different bandwidths.

In the second section, time delays, prediction and power spectra were examined. Time delays were calculated in response to various periodic signals, various bandwidths of narrow-band Gaussian random motions and sinusoids. It was demonstrated that prediction occurred only when the target motion was periodic, and only if the harmonic content was such that the signal was sufficiently narrow-band. It appears as if general periodic motions are split into predictive and non-predictive components.

For unpredictable motions, the relationship between the time delay and the average speed of the retinal image was linear. Based on this I proposed a model explaining the time delays for both random and periodic motions. My experiments did not prove that the system is sampled data, or that it is continuous. However, the model can be interpreted as representative of a sample data system whose sample interval is a function of the target motion.

It was shown that increasing the bandwidth of the low-pass filtered Gaussian random motion resulted in an increase of the eye movement bandwidth. Some properties of the eyeball-muscle dynamics and the extraocular muscle "active state tension" were derived.