Large-scale software development companies delivering market-driven products have introduced agile methodologies as the way of working to a big extent. Even though there are many benefits with an agile way of working, problems occur when scaling agile because of the increased complexity. One explicit problem area is to evolve deep product knowledge, which is a domain specific knowledge that cannot be developed anywhere else but at the specific workplace. This research aims to identify impediments for developing domain specific knowledge and provide solutions to overcome these challenges in order to optimize knowledge growth and throughput. The result of the research shows that impediments occur in four different categories, based on a framework for knowledge sharing drivers. These are people-related, task-related, structure-related and technology-related. The challenging element with knowledge growth is to integrate the training into the feature development process, without affecting the feature throughput negatively. The research also shows that by increasing the knowledge sharing, the competence level of the whole organization can be increased, and thereby be beneficial from many perspectives, such as feature-throughput and code quality.

Surgery of axons in C. elegans using ultrafast laser pulses, and observing their subsequent regrowth opens a new frontier in neuroscience, since such research holds a great potential for the development of novel therapies and cures to neurodegenerative diseases. In order to make the required large-scale genetic screenings in C. elegans possible and thus obtain statistically significant biological data, an automated laser axotomy system needs to be developed. Microfluidic devices hold the promise of improved throughput by integrating different functional modules into a single chip. The first step to developing a microfluidic device for laser axotomy is to devise an on-chip worm trapping method, which maintains a high degree of immobilization to sever axons without using anesthetics. In this thesis, we present a novel method that uses a thin, deflectable PDMS membrane that individually traps worms in a microfluidic device. Axons can successfully be severed with the same accuracy as those using conventional paralyzing techniques. This device also incorporates recovery chambers for housing worms after surgery and for time-lapse imaging of axonal regrowth without the repeated use of anesthetics. Towards accomplishing an automated, high-throughput laser axotomy system, we developed an improved microfluidic design based on the same mechanical immobilization technique. This second generation device allows for serially processing of a large quantity of worms rapidly using a semi-automated system. Integrated to the opto-mechanical platform, a software program utilizing image processing techniques is developed. This semi-automated program can automatically identify the location of worms, their neuronal cell bodies, focus on the axons of interest, and align the laser beam with the axon via a PID based viso-servo feedback algorithm. Statistic data demonstrate that there is no significant difference in axonal reconnection rates between surgeries performed on-chip and using anesthetics. To improve flow control, a three-dimensional novel microfluidic valve structure is designed and fabricated. This novel valve structure allows for a complete sealing of the flow channel, without degrading optical conditions for imaging and laser ablation in the trapping area. Finally, we developed a prototypical microfluidic assembly that will eventually be able to interface a well-plate to automatically deliver population of worms from individual wells to the automated chip for axotomy. This interface consists of a microfluidic multiplexer to significantly reduce the number of solenoid valves needed to individually address each well. / text

Ricin and Shiga toxin type 1 are potent cytotoxins known as ribosome inhibition proteins, abbreviated RIPs. Proteins of this family shut down protein synthesis by removing a critical adenine in the conserved stem-loop structure of 28S rRNA. Due to its exquisite cytotoxicity, the plant toxin ricin has been used as a biological warfare agent. Although great achievement has been made on ricin research, including catalytic mechanism and structure analysis, there is still no specific treatment available for ricin exposure. In addition, ricin A chain inhibitors may also be useful against the homologous bacterial proteins shiga toxins, which are responsible for dysentery, and diseases related to food poisoning, including hemolytic uremic syndrome. Previous study on RTA inhibitor search has provided a number of substrate analog inhibitors, all of which, however, are weaker inhibitors. Therefore, the goal of this work is to improve the binding affinity of known inhibitors and to discovery new scaffolds for inhibitor discovery and development. In this work, multiple approaches were employed for this purpose, including optimizing known inhibitors and searching new inhibitors by Virtual Drug Screening (VDS) and High Throughput Screening (HTS). A number of new RTA inhibitors were discovered by these strategies, which provide a variety of pharmacophores for RTA inhibitor design, and also added a new line of evidence for VDS as an advanced technology for drug discovery and development. / text

Asymmetric synthesis has become an important tool to prepare enantiomerically pure compounds because it avoids the wasteful discarding of the undesired enantiomer. Combinatorial libraries allow for much faster screening for new and better asymmetric catalysts/auxiliaries, but they generate a large number of samples whose enantiomeric excess (ee) cannot be determined rapidly. This bottleneck currently limits the applicability of such approaches. We propose here the use of faster optical techniques for the determination of ee using common instrumentation, such as UV-vis spectrophotometers, and circular dichroism (CD) spectrophotometers. Our methods are easily transitioned to the microwell format commonly used in parallel/combinatorial chemistry endeavors, just by using common microplate readers: this allows for an even more rapid analysis of samples and a seamless integration in a high-throughput workflow. We have shown that enantioselective indicator displacement assays can be developed to determine ee in a high-throughput fashion utilizing either a UV-vis spectrophotometer or a 96-well plate reader. Two chiral receptors and a commercial pH indicator were used to enantioselectively discriminate α-amino acids by monitoring the degree of indicator displacement. The two receptors were able to enantioselectively discriminate 13 of the 17 analyzed α-amino acids and accurately determine ee values of independent test samples with the use of ee calibration curves. Moreover, a sample of valine was synthesized through an asymmetric reaction, whose ee was then determined with our assay and compared to chiral HPLC and 1H NMR chiral shift reagent analysis, with excellent correlation. An artificial neural network was also successfully employed in the analyses, as an alternative to ee calibration curves. Both techniques consistently produced results accurate enough for preliminary determination of ee in a rapid manner, allowing for high throughput screening (HTS) of asymmetric reactions. The use of circular dichroism spectroscopy with chiral BINAP was also explored to enantioselectively discriminate α-chiral ketones. The ketones were derivatized with pyridyl hydrazines to produce hydrazones, which were then bound to enantiomerically pure [Cu(I)(BINAP)]+, forming diastereomeric complexes with differential steric interactions leading to different degrees of twist in the BINAP moiety and characteristic signatures in the CD spectrum, as a function of sample ee. / text

eEF-2K, also known as CaM kinase-III, is an atypical protein kinase which negatively regulates the global rate of protein synthesis through the phosphorylation and inactivation of its substrate eEF-2. Recently eEF-2K has been validated as a novel target for anti-cancer therapy. However, a detailed understanding of the role of eEF-2K in cancer biology is unavailable. Mechanistic studies can often provide an understanding of enzyme function. Therefore, we determined the kinetic mechanism of eEF-2K using a peptide substrate (Acetyl-RKKYKFNEDTERRRFL-amide). We found that eEF-2K adopts a ternary-complex, steady state ordered mechanism, with ATP binding required before the peptide substrate. A good cellular inhibitor is required for elucidating the role of eEF-2K in cancer biology. To date, NH125 is the only inhibitor used to investigate the activity of eEF-2K in cells. Although it is reported as a specific inhibitor of eEF-2K, its exact mode of action has not been reported. Through in-vitro assays and cellular studies, we found that NH125 is a non-specific inhibitor of eEF-2K that blocks eEF-2 phosphorylation in cells. There is a great demand for specific inhibitors of eEF-2K. We developed a fluorescence high throughput assay system for eEF-2K. The assay utilizes the peptide substrate labeled with a Sox moiety whose phosphorylation can be monitored at 485 nm in the presence of magnesium. We also validated the assay in a screen of 30,000 compounds in 384 well plates. We found the assay to be robust and identified a relatively specific inhibitor of eEF-2K and determined its mechanism of action. We found it behaved as a slowly reversible inhibitor of eEF-2K with a two step inhibition mechanism - fast initial binding at the enzyme active site, followed by a slower inactivation step. We propose that the nitrile group on the compound binds to the active site thiol in the enzyme covalently forming a reversible thioimidate adduct to inactivate the enzyme. / text

Microarray technology has revolutionized the field of molecular biology by offering an efficient and cost effective platform for the simultaneous quantification of thousands of genes or even entire genomes in a single experiment. Unlike southern blotting, which is restricted to the measurement of one gene at-a-time, microarrays offer biologists with the opportunity to carry out genome-wide experiments in order to help them gain a systems level understanding of cell regulation and control. The application of bioinformatics in the milieu of gene expression analysis has attracted a great deal of attention in the recent past due to specific algorithms and software solutions that attempt to illustrate complex multidimensional microarray data in a biologically coherent fashion so that it can be understood by the biologist. This has given rise to some exciting prospects for deciphering microarray data, by helping us refine our comprehension pertinent to the underlying physiological dynamics of disease. Although much progress is being made in the development of specialized bioinformatics software pipelines with the purpose of decoding large volumes of gene expression data in the context of systems biology, several loopholes exist. Perhaps most notable of these loopholes is the fact that there is an increasing demand for software solutions that specialize in automating the comparison of multiple gene expression profiles, derived from microarray experiments sharing a common biological theme. This is no doubt an important challenge, since common genes across different biological conditions having similar expression patterns are likely to be involved in the same biological process and hence, may share the same regulatory signatures. The potential benefits of this in refining our understanding of the physiology of disease are undeniable. The research presented in this thesis provides a systematic walkthrough of a series of software pipelines developed for the purpose of streamlining gene expression analysis in a systems biology context. Firstly, we present BiSAn, a software tool that deciphers expression data from the perspective of transcriptional regulation. Following this, we present Genome Interaction Analyzer (GIA), which analyzes microarray data in the integrative framework of transcription factor binding sites, protein-protein interactions and molecular pathways. The final contribution is a software pipeline called MicroPath, which analyzes multiple sets of gene expression profiles and attempts to extract common regulatory signatures that may be implicating the biological question.

The rise of high-throughput scientific experimentation and data collection has introduced new classes of statistical and computational challenges. The technologies driving this data explosion are subject to complex new forms of measurement error, requiring sophisticated statistical approaches. Simultaneously, statistical computing must adapt to larger volumes of data and new computational environments, particularly parallel and distributed settings. This dissertation presents several computational and theoretical contributions to these challenges. In chapter 1, we consider the problem of estimating the genome-wide distribution of nucleosome positions from paired-end sequencing data. We develop a modeling approach based on nonparametric templates that controls for variability due to enzymatic digestion. We use this to construct a calibrated Bayesian method to detect local concentrations of nucleosome positions. Inference is carried out via a distributed HMC algorithm that scales linearly in complexity with the length of the genome being analyzed. We provide MPI-based implementations of the proposed methods, stand-alone and on Amazon EC2, which can provide inferences on an entire S. cerevisiae genome in less than 1 hour on EC2. We then present a method for absolute quantitation from LC-MS/MS proteomics experiments in chapter 2. We present a Bayesian model for the non-ignorable missing data mechanism induced by this technology, which includes an unusual combination of censoring and truncation. We provide a scalable MCMC sampler for inference in this setting, enabling full-proteome analyses using cluster computing environments. A set of simulation studies and actual experiments demonstrate this approach's validity and utility. We close in chapter 3 by proposing a theoretical framework for the analysis of preprocessing under the banner of multiphase inference. Preprocessing forms an oft-neglected foundation for a wide range of statistical and scientific analyses. We provide some initial theoretical foundations for this area, including distributed preprocessing, building upon previous work in multiple imputation. We demonstrate that multiphase inferences can, in some cases, even surpass standard single-phase estimators in efficiency and robustness. Our work suggests several paths for further research into the statistical principles underlying preprocessing. / Statistics

The zebrafish larva is an ideal candidate for in vivo high-throughput screening: it is a small vertebrate, it is optically transparent, possesses complex organs, and is easy to culture. In addition, genetic mutants and models of human diseases are widely available. Despite these attractive features there are no tools capable of screening at sufficient throughput and resolution to fully exploit the zebrafish. Here, I present a collection of technologies that enable high-throughput studies on zebrafish larvae at cellular resolution. / Engineering and Applied Sciences

EZH2 is a SET domain-containing methyltransferase and the catalytic component of the multimeric Polycomb- group (PcG) protein complex, PRC2. When in complex with other PRC2 members (EED, SUZ12, AEBP2, and RBBP4), EZH2 catalyzes methylation of H3K27, a histone modification associated with transcriptional repression and developmental regulation. As several PRC2 components are upregulated or mutated in a variety of human cancers, efforts to discover small-molecule modulators of PRC2 and understand its regulation may yield therapeutic insights. Identification of small-molecule probes with distinct chemotypes, MOAs, and selectivity profiles are not only of great value, but necessary in establishing comprehensive probe sets capable of illuminating the various roles of EZH2 in oncogenesis. Here we describe efforts to identify and characterize small-molecule modulators of PRC2 and further understand its regulation. Chapter II outlines the expression and purification of 5-component PRC2 (EZH2-EED-SUZ12-AEBP2-RBBP4) and the establishment of biochemical and cellular HTS assays. These assays were used to screen a diverse set of small molecules (>120,000), identifying biochemical PRC2 inhibitors and activators (described in Chapter III). One biochemical PRC2 inhibitor, BRD1835, appeared to inhibit PRC2 activity through a novel artifactual mechanism involving interaction with peptide substrate, leading to apparent peptide-competitive behavior and putative cellular activity (described in Chapter IV). The characterization of novel biochemical PRC2 activators, BRD3934 and BRD8284, is discussed in Chapter V. Chapter VI describes the use of an HCS assay to identify known bioactive compounds that alter intracellular levels of H3K27me3 through modulating H3K27me3-connected regulatory nodes or by targeting PRC2 directly. These efforts led to the discovery that an antifungal agent, miconazole, is capable of activating PRC2 activity in vitro, while a mucolytic agent, bromhexine, selectively ablates cellular H3K27me3 levels through targeting an activity distinct from PRC2. Finally, Chapter VII discusses novel PRC2-connected crosstalk mechanisms identified through screening libraries of uniquely modified histone peptides for their ability to bind or support methylation by PRC2. These studies enhance our understanding of PRC2 regulation by revealing the effects of H3R26 and H3K23me1 modifications on enzymatic activity, implicating their respective methyltransferases in PRC2 regulation.

The interactions between protein-protein, protein-nucleic acid, and protein-small molecules are central to biological processes and are key for the design of new therapeutics. Rapid and easy to implement methodologies are needed that enable the interrogation of these interactions in a complex cellular context. Towards this goal, I have utilized the concept of split-protein reassembly, also called protein complementation, for the creation of a variety of sensor architectures that enable the interrogation of protein-nucleic acid, protein-protein, and protein-small molecule interactions. Utilizing the enzymatic split-reporter β-lactamase and existing zinc finger design strategies we applied our recently developed technology termed SEquence-Enabled Reassembly (SEER) towards the creation of a sensor capable of the specific detection of the CryIA transgene. Additionally, the split β-lactamase reporter was utilized for the sitespecific determination of DNA methylation at cytosine residues that is involved in epigenetic regulation. This method, dubbed mCpG-SEER, enabled the direct detection of femtomole levels of dsDNA methylation in sequence specific manner. In a separate endeavor, we have developed and optimized the first cell-free split-reporter systems for GFP, split β-lactamase, and firefly luciferase for the successful dsDNA-dependent reassembly of the various reporters. Our cell free in vitro translation systems eliminates previous bottlenecks encountered in split-reporter technologies such as laborious transfection/cell culture or protein purification. Capitalizing on the ease of use and speed afforded by this new technology we describe the sensitive detection of protein-protein, protein-nucleic acid, and protein-small molecule interactions and inhibitors thereof. In a related area, we have applied this rapid cell-free split-firefly luciferase assay to the specific interrogation of a large class of helix-receptor protein-protein interactions. We have built a panel consisting of the clinically relevant Bcl-2 family of proteins, hDM2, hDM4, and p53 and interrogated the specificity of helix-receptor interactions as well as the specificity of peptide and small-molecule inhibitors of these interactions. Finally, we describe the further applications of our cell-free technology to the development of a large number of general split-firefly luciferase sensors for the detection of ssRNA sequences, the detection of native proteins, the evaluation of protease activity, and interrogation of enzyme-inhibitor interactions. The new methodologies provided in this study provides a general and enabling methodology for the rapid interrogation of a wide variety of biomolecular interactions and their antagonists without the limitations imposed by current in vitro and in vivo approaches.