A perfect day for zebrafish : neuromodulation of sleep in a diurnal vertebrate

Every day, we shift among various states of sleep and arousal to meet the many demands of our bodies and environment. A central puzzle in neurobiology is how the brain controls these behavioral states, which are essential to an animal's well-being and survival. Mammalian models have predominated sleep and arousal research, although in the past decade, invertebrate models have made significant contributions to our understanding of the genetic underpinnings of behavioral states. More recently, the zebrafish (Danio rerio), a diurnal vertebrate, has emerged as a promising model system for sleep and arousal research.

In this thesis, I describe two studies on sleep/arousal pathways that I conducted using zebrafish, and I discuss how the findings can be combined in future projects to advance our understanding of vertebrate sleep/arousal pathways. In the first study, I discovered a neuropeptide that regulates zebrafish sleep and arousal as a result of a large-scale effort to identify molecules that regulate behavioral states. Taking advantage of facile zebrafish genetics, I constructed mutants for the three known receptors of this peptide and identified the one receptor that exclusively mediates the observed behavioral effects. I further show that the peptide exerts its behavioral effects independently of signaling at a key module of a neuroendocrine signaling pathway. This finding contradicts the hypothesis put forth in mammalian systems that the peptide acts through the classical neuroendocrine pathway; our data further generate new testable hypotheses for determining the central nervous system or alternative neuroendocrine pathways involved.

Second, I will present the development of a chemigenetic method to non-invasively manipulate neurons in the behaving zebrafish. I validated this technique by expressing and inducing the chemigenetic tool in a restricted population of sleep-regulating neurons in the zebrafish. As predicted by established models of this vertebrate sleep regulator, chemigenetic activation of these neurons induced hyperactivity, whereas chemigenetic ablation of these neurons induced increased sleep behavior. Given that light is a potent modulator of behavior in zebrafish, our proof-of-principle data provide a springboard for future studies of sleep/arousal and other light-dependent behaviors to interrogate genetically-defined populations of neurons independently of optogenetic tools.

Microfluidics-based single-cell functional proteomics microchip for portraying protein signal transduction networks within the framework of physicochemical principles, with applications in fundamental and translational cancer research

Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.

Ferrous iron sensing and responding in Pseudomonas aeruginosa

Controlling iron distribution is important for all organisms, and is key in bacterial pathogenesis. It has long been understood that cystic fibrosis (CF) patient sputum contains elevated iron concentrations. However, anaerobic bacteria have been isolated from CF sputum and hypoxic zones in sputum have been measured. Because ferrous iron [Fe(II)] is stable in reducing, acidic conditions, it could exist in the CF lung. I show that a two-component system, BqsRS, specifically responds to Fe(II) in the CF pathogen, Pseudomonas aeruginosa. Concurrently, a clinical study found that Fe(II) is present in CF sputum at all stages of lung function decline. Fe(II), not Fe(III) correlates with patients in the most severe disease state. Furthermore, transcripts of the newly identified BqsRS were detected in sputum. Two component systems are the main method bacteria interact with their extracellular environment. A typical two-component system contains a sensor histidine kinase, which upon activation phosphorylates a response regulator that then acts as a transcription factor to elicit a cellular response to stimuli. To explore the mechanism of BqsRS, I describe the Fe(II)-sensing RExxE motif in the sensor BqsS and determine the consensus DNA sequence BqsR binds. With the BqsR binding sequence, I identify novel regulon members through bioinformatic and molecular biology techniques. From the predicted function of new BqsR regulon members, I find that Fe(II) elicits a response that globally protects the cells against cationic stressors, including clinically relevant antibiotics. Subsequently, I use BqsR as a case study to determine if promoter outputs can accurately be predicted based only on a deep understanding of a transcriptional activator’s operator or if a broader regulatory context is required for accurate predictions at all genomic loci. This work highlights the importance of Fe(II) as a (micro)environmental factor, even in conditions typically thought of as aerobic. Since the presence of Fe(II) can alter P. aeruginosa’s antibiotic susceptibility, combining the current strategy of targeting Fe(III) with a new approach targeting Fe(II) may help eradicate infections in the CF lung in the future.