Sampling strategies for characterization of neuropeptides using mass spectrometry and functional implications into cell-cell signaling

In this dissertation, there are developed different analytical strategies to discover and characterize mammalian brain peptides using small amount of tissues. The magnocellular neurons of rat supraoptic nucleus in tissue and cell culture served as the main model to study neuropeptides, in addition to hippocampal neurons and mouse embryonic pituitaries. The neuropeptidomcis studies described here use different extraction methods on tissue or cell culture combined with mass spectrometry (MS) techniques, matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI). These strategies lead to the identification of multiple peptides from the rat/mouse brain in tissue and cell cultures, including novel compounds One of the goals in this dissertation was to optimize sample preparations on samples isolated from well-defined brain regions for mass spectrometric analysis. Here, the neuropeptidomics study of the SON resulted in the identification of 85 peptides, including 20 unique peptides from known prohormones. This study includes mass spectrometric analysis even from individually isolated magnocellular neuroendocrine cells, where vasopressin and several other peptides are detected. At the same time, it was shown that the same approach could be applied to analyze peptides isolated from a similar hypothalamic region, the suprachiasmatic nucleus (SCN). Although there were some overlaps regarding the detection of the peptides in the two brain nuclei, different peptides were detected specific to each nucleus. Among other peptides, provasopressin fragments were specifically detected in the SON while angiotensin I, somatostatin-14, neurokinin B, galanin, and vasoactive-intestinal peptide (VIP) were detected in the SCN only. Lists of peptides were generated from both brain regions for comparison of the peptidome of SON and SCN nuclei. Moving from analysis of magnocellular neurons in tissue to cell culture, the direct peptidomics of the magnocellular and hippocampal neurons led to the detection of 10 peaks that were assigned to previously characterized peptides and 17 peaks that remain unassigned. Peptides from the vasopressin prohormone and secretogranin-2 are attributed to magnocellular neurons, whereas neurokinin A, peptide J, and neurokinin B are attributed to cultured hippocampal neurons. This approach enabled the elucidation of cell-specific prohormone processing and the discovery of cell-cell signaling peptides. The peptides with roles in the development of the pituitary were analyzed using transgenic mice. Hes1 KO is a genetically modified mouse that lives only e18.5 (embryonic days). Anterior pituitaries of Hes1 null mice exhibit hypoplasia due to increased cell death and reduced proliferation and in the intermediate lobe, the cells differentiate abnormally into somatotropes instead of melanotropes. These previous findings demonstrate that Hes1 has multiple roles in pituitary development, cell differentiation, and cell fate. AVP was detected in all samples. Interestingly, somatostatin [92-100] and provasopressin [151-168] were detected in the mutant but not in the wild type or heterozygous pituitaries while somatostatin-14 was detected only in the heterozygous pituitary. In addition, the putative peptide corresponding to m/z 1330.2 and POMC [205-222] are detected in the mutant and heterozygous pituitaries, but not in the wild type. These results indicate that Hes1 influences the processing of different prohormones having possible roles during development and opens new directions for further developmental studies. This research demonstrates the robust capabilities of MS, which ensures the unbiased direct analysis of peptides extracted from complex biological systems and allows addressing important questions to understand cell-cell signaling in the brain.

Solid-liquid interactions in microscale structures and devices

Liquid-solid interactions become important as dimensions approach mciro/nano-scale. This dissertation focuses on liquid-solid interactions in two distinct applications: capillary driven self-assembly of thin foils into 3D structures, and droplet wetting of hydrophobic micropatterned surfaces. The phenomenon of self-assembly of complex structures is common in biological systems. Examples include self-assembly of proteins into macromolecular structures and self-assembly of lipid bilayer membranes. The principles governing this phenomenon have been applied to induce self-assembly of millimeter scale Si thin films into spherical and other 3D structures, which are then integrated into light-trapping photovoltaic (PV) devices. Motivated by this application, we present a generalized analytical study of the self-folding of thin plates into deterministic 3D shapes, through fluid-solid interactions, to be used as PV devices. This study consists of developing a model using beam theory, which incorporates the two competing components — a capillary force that promotes folding and the bending rigidity of the foil that resists folding into a 3D structure. Through an equivalence argument of thin foils of different geometry, an effective folding parameter, which uniquely characterizes the driving force for folding, has been identified. A criterion for spontaneous folding of an arbitrarily shaped 2D foil, based on the effective folding parameter, is thus established. Measurements from experiments using different materials and predictions from the model match well, validating the assumptions used in the analysis. As an alternative to the mechanics model approach, the minimization of the total free energy is employed to investigate the interactions between a fluid droplet and a flexible thin film. A 2D energy functional is proposed, comprising the surface energy of the fluid, bending energy of the thin film and gravitational energy of the fluid. Through simulations with Surface Evolver, the shapes of the droplet and the thin film at equilibrium are obtained. A critical thin film length necessary for complete enclosure of the fluid droplet, and hence successful self-assembly into a PV device, is determined and compared with the experimental results and mechanics model predictions. The results from the modeling and energy approaches and the experiments are all consistent. Superhydrophobic surfaces, which have unique properties including self-cleaning and water repelling are desired in many applications. One excellent example in nature is the lotus leaf. To fabricate these surfaces, well designed micro/nano- surface structures are often employed. In this research, we fabricate superhydrophobic micropatterned Polydimethylsiloxane (PDMS) surfaces composed of micropillars of various sizes and arrangements by means of soft lithography. Both anisotropic surfaces, consisting of parallel grooves and cylindrical pillars in rectangular lattices, and isotropic surfaces, consisting of cylindrical pillars in square and hexagonal lattices, are considered. A novel technique is proposed to image the contact line (CL) of the droplet on the hydrophobic surface. This technique provides a new approach to distinguish between partial and complete wetting. The contact area between droplet and microtextured surface is then measured for a droplet in the Cassie state, which is a state of partial wetting. The results show that although the droplet is in the Cassie state, the contact area does not necessarily follow Cassie model predictions. Moreover, the CL is not circular, and is affected by the micropatterns, in both isotropic and anisotropic cases. Thus, it is suggested that along with the contact angle — the typical parameter reported in literature quantifying wetting, the size and shape of the contact area should also be presented. This technique is employed to investigate the evolution of the CL on a hydrophobic micropatterned surface in the cases of: a single droplet impacting the micropatterned surface, two droplets coalescing on micropillars, and a receding droplet resting on the micropatterned surface. Another parameter which quantifies hydrophobicity is the contact angle hysteresis (CAH), which indicates the resistance of the surface to the sliding of a droplet with a given volume. The conventional methods of using advancing and receding angles or tilting stage to measure the resistance of the micropatterned surface are indirect, without mentioning the inaccuracy due to the discrete and stepwise motion of the CL on micropillars. A micronewton force sensor is utilized to directly measure the resisting force by dragging a droplet on a microtextured surface. Together with the proposed imaging technique, the evolution of the CL during sliding is also explored. It is found that, at the onset of sliding, the CL behaves as a linear elastic solid with a constant stiffness. Afterwards, the force first increases and then decreases and reaches a steady state, accompanied with periodic oscillations due to regular pinning and depinning of the CL. Both the maximum and steady state forces are primarily dependent on area fractions of the micropatterned surfaces in our experiment. The resisting force is found to be proportional to the number of pillars which pin the CL at the trailing edge, validating the assumption that the resistance mainly arises from the CL pinning at the trailing edge. In each pinning-and-depinning cycle during the steady state, the CL also shows linear elastic behavior but with a lower stiffness. The force variation and energy dissipation involved can also be determined. This novel method of measuring the resistance of the micropatterned surface elucidates the dependence on CL pinning and provides more insight into the mechanisms of CAH.

Analysis of the role of the transcription factor C/EBPβ in controlling uterine functions during early pregnancy

Embryo implantation into the endometrium is a complex biological process involving the integration of steroid hormone signaling, endometrial tissue remodeling and maternal- fetal communications. A successful pregnancy is the outcome of the timely integration of these events during the early stages of implantation. The involvement of ovarian steroid hormones, estrogen (E) and progesterone (P), acting through their cognate receptors, is essential for uterine functions during pregnancy. The molecular mechanisms that control the process of implantation are undergoing active exploration. Through our recent efforts, we identified the transcription factor, CCAAT Enhancer Binding Protein Beta (C/EBPb) as a prominent target of estrogen and progesterone signaling in the uterus. The development of a C/EBPb-null mouse model, which is infertile, presented us with an opportunity to analyze the role of this molecule in uterine function. We discovered that C/EBPb functions in two distinct manners: (i) by acting as a mediator of E-induced proliferation of the uterine epithelium and (ii) by controlling uterine stromal cell differentiation, a process known as decidualization, during pregnancy. My studies have delineated important mechanisms by which E regulates C/EBPb expression to induce DNA replication and prevent apoptosis of uterine epithelial cells during E-induced epithelial growth. In subsequent studies, I analyzed the role of C/EBPb in decidualization and uncovered a unique mechanism by which C/EBPb regulates the synthesis of a unique laminin-containing extracellular matrix (ECM) that supports stromal cell differentiation and embryo invasion. In order to better define the role of laminin in implantation, we developed a laminin gamma 1-conditional knockout mouse model. This is currently an area of ongoing investigation. The information gained from our analysis of C/EBPb function in the uterus provides new insights into the mechanisms of steroid hormone action during early pregnancy. Ultimately, our findings may aid in the understanding of dysregulation of hormone-controlled pathways that underlie early pregnancy loss and infertility in women.

Information and the evolution of codon bias

The informational properties of biological systems are the subject of much debate and research. I present a general argument in favor of the existence and central importance of information in organisms, followed by a case study of the genetic code (specifically, codon bias) and the translation system from the perspective of information. The codon biases of 831 Bacteria and Archeae are analyzed and modeled as points in a 64-dimensional statistical space. The major results are that (1) codon bias evolution does not follow canonical patterns, and (2) the use of coding space in organsims is a subset of the total possible coding space. These findings imply that codon bias is a unique adaptive mechanism that owes its existence to organisms' use of information in representing genes, and that there is a particularly biological character to the resulting biased coding and information use.