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Bacteria respond to changing environmental conditions by switching the global pattern of expressed genes. In response to specific environmental stresses the cell activates several stress-specific molecules such as sigma factors. They reversibly bind the RNA polymerase to form the so-called holoenzyme and direct it towards the appropriate stress response genes. In exponentially growing E. coli cells, the majority of the transcriptional activity is carried out by the housekeeping sigma factor, while stress responses are often under the control of alternative sigma factors. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross talk between genes or gene classes via the sharing of expression machinery. To quantitatively analyze the contribution of sigma factor competition to global changes in gene expression, we develop a thermodynamic model that describes binding between sigma factors and core RNAP at equilibrium, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components.
Association of housekeeping sigma factor to RNAP is generally favored by its abundance and higher binding affinity to the core. In order to promote transcription by alternative sigma subunits, the bacterial cell modulates the transcriptional efficiency in a reversible manner through several strategies such as anti-sigma factors, 6S RNA and generally any kind of transcriptional regulators (e.g. activators or inhibitors). By shifting the outcome of sigma factor competition for the core, these modulators bias the transcriptional program of the cell. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. We observe that transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected.
Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross talk effects and raising the question of how their in vitro measure is relevant in the cell. We also estimate that sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors, and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program and gives new insights into RNAP partitioning in the cell.
An important goal in biotechnology and (bio-) medical research is the isolation of single cells from a heterogeneous cell population. These specialised cells are of great interest for bioproduction, diagnostics, drug development, (cancer) therapy and research. To tackle emerging questions, an ever finer differentiation between target cells and non-target cells is required. This precise differentiation is a challenge for a growing number of available methods.
Since the physiological properties of the cells are closely linked to their morphology, it is beneficial to include their appearance in the sorting decision. For established methods, this represents a non addressable parameter, requiring new methods for the identification and isolation of target cells. Consequently, a variety of new flow-based methods have been developed and presented in recent years utilising 2D imaging data to identify target cells within a sample. As these methods aim for high throughput, the devices developed typically require highly complex fluid handling techniques, making them expensive while offering limited image quality.
In this work, a new continuous flow system for image-based cell sorting was developed that uses dielectrophoresis to precisely handle cells in a microchannel. Dielectrophoretic forces are exerted by inhomogeneous alternating electric fields on polarisable particles (here: cells). In the present system, the electric fields can be switched on and off precisely and quickly by a signal generator. In addition to the resulting simple and effective cell handling, the system is characterised by the outstanding quality of the image data generated and its compatibility with standard microscopes. These aspects result in low complexity, making it both affordable and user-friendly.
With the developed cell sorting system, cells could be sorted reliably and efficiently according to their cytosolic staining as well as morphological properties at different optical magnifications. The achieved purity of the target cell population was up to 95% and about 85% of the sorted cells could be recovered from the system. Good agreement was achieved between the results obtained and theoretical considerations. The achieved throughput of the system was up to 12,000 cells per hour. Cell viability studies indicated a high biocompatibility of the system.
The results presented demonstrate the potential of image-based cell sorting using dielectrophoresis. The outstanding image quality and highly precise yet gentle handling of the cells set the system apart from other technologies. This results in enormous potential for processing valuable and sensitive cell samples.
For the elucidation of the dynamics of signal transduction processes that are induced by cellular interactions, defined events along the signal transduction cascade and subsequent activation steps have to be analyzed and then also correlated with each other. This cannot be achieved by ensemble measurements because averaging biological data ignores the variability in timing and response patterns of individual cells and leads to highly blurred results. Instead, only a multi-parameter analysis at a single-cell level is able to exploit the information that is crucially needed for deducing the signaling pathways involved. The aim of this work was to develop a process line that allows the initiation of cell-cell or cell-particle interactions while at the same time the induced cellular reactions can be analyzed at various stages along the signal transduction cascade and correlated with each other. As this approach requires the gentle management of individually addressable cells, a dielectrophoresis (DEP)-based microfluidic system was employed that provides the manipulation of microscale objects with very high spatiotemporal precision and without the need of contacting the cell membrane. The system offers a high potential for automation and parallelization. This is essential for achieving a high level of robustness and reproducibility, which are key requirements in order to qualify this approach for a biomedical application. As an example process for intercellular communication, T cell activation has been chosen. The activation of the single T cells was triggered by contacting them individually with microbeads that were coated with antibodies directed against specific cell surface proteins, like the T cell receptor-associated kinase CD3 and the costimulatory molecule CD28 (CD; cluster of differentiation). The stimulation of the cells with the functionalized beads led to a rapid rise of their cytosolic Ca2+ concentration which was analyzed by a dual-wavelength ratiometric fluorescence measurement of the Ca2+-sensitive dye Fura-2. After Ca2+ imaging, the cells were isolated individually from the microfluidic system and cultivated further. Cell division and expression of the marker molecule CD69 as a late activation event of great significance were analyzed the following day and correlated with the previously recorded Ca2+ traces for each individual cell. It turned out such that the temporal profile of the Ca2+ traces between both activated and non-activated cells as well as dividing and non-dividing cells differed significantly. This shows that the pattern of Ca2+ signals in T cells can provide early information about a later reaction of the cell. As isolated cells are highly delicate objects, a precondition for these experiments was the successful adaptation of the system to maintain the vitality of single cells during and after manipulation. In this context, the influences of the microfluidic environment as well as the applied electric fields on the vitality of the cells and the cytosolic Ca2+ concentration as crucially important physiological parameters were thoroughly investigated. While a short-term DEP manipulation did not affect the vitality of the cells, they showed irregular Ca2+ transients upon exposure to the DEP field only. The rate and the strength of these Ca2+ signals depended on exposure time, electric field strength and field frequency. By minimizing their occurrence rate, experimental conditions were identified that caused the least interference with the physiology of the cell. The possibility to precisely control the exact time point of stimulus application, to simultaneously analyze short-term reactions and to correlate them with later events of the signal transduction cascade on the level of individual cells makes this approach unique among previously described applications and offers new possibilities to unravel the mechanisms underlying intercellular communication.
With the downscaling of CMOS technologies, the radiation-induced Single Event Transient (SET) effects in combinational logic have become a critical reliability issue for modern integrated circuits (ICs) intended for operation under harsh radiation conditions. The SET pulses generated in combinational logic may propagate through the circuit and eventually result in soft errors. It has thus become an imperative to address the SET effects in the early phases of the radiation-hard IC design. In general, the soft error mitigation solutions should accommodate both static and dynamic measures to ensure the optimal utilization of available resources. An efficient soft-error-aware design should address synergistically three main aspects: (i) characterization and modeling of soft errors, (ii) multi-level soft error mitigation, and (iii) online soft error monitoring. Although significant results have been achieved, the effectiveness of SET characterization methods, accuracy of predictive SET models, and efficiency of SET mitigation measures are still critical issues. Therefore, this work addresses the following topics: (i) Characterization and modeling of SET effects in standard combinational cells, (ii) Static mitigation of SET effects in standard combinational cells, and (iii) Online particle detection, as a support for dynamic soft error mitigation.
Since the standard digital libraries are widely used in the design of radiation-hard ICs, the characterization of SET effects in standard cells and the availability of accurate SET models for the Soft Error Rate (SER) evaluation are the main prerequisites for efficient radiation-hard design. This work introduces an approach for the SPICE-based standard cell characterization with the reduced number of simulations, improved SET models and optimized SET sensitivity database. It has been shown that the inherent similarities in the SET response of logic cells for different input levels can be utilized to reduce the number of required simulations. Based on characterization results, the fitting models for the SET sensitivity metrics (critical charge, generated SET pulse width and propagated SET pulse width) have been developed. The proposed models are based on the principle of superposition, and they express explicitly the dependence of the SET sensitivity of individual combinational cells on design, operating and irradiation parameters. In contrast to the state-of-the-art characterization methodologies which employ extensive look-up tables (LUTs) for storing the simulation results, this work proposes the use of LUTs for storing the fitting coefficients of the SET sensitivity models derived from the characterization results. In that way the amount of characterization data in the SET sensitivity database is reduced significantly.
The initial step in enhancing the robustness of combinational logic is the application of gate-level mitigation techniques. As a result, significant improvement of the overall SER can be achieved with minimum area, delay and power overheads. For the SET mitigation in standard cells, it is essential to employ the techniques that do not require modifying the cell structure. This work introduces the use of decoupling cells for improving the robustness of standard combinational cells. By insertion of two decoupling cells at the output of a target cell, the critical charge of the cell’s output node is increased and the attenuation of short SETs is enhanced. In comparison to the most common gate-level techniques (gate upsizing and gate duplication), the proposed approach provides better SET filtering. However, as there is no single gate-level mitigation technique with optimal performance, a combination of multiple techniques is required. This work introduces a comprehensive characterization of gate-level mitigation techniques aimed to quantify their impact on the SET robustness improvement, as well as introduced area, delay and power overhead per gate. By characterizing the gate-level mitigation techniques together with the standard cells, the required effort in subsequent SER analysis of a target design can be reduced. The characterization database of the hardened standard cells can be utilized as a guideline for selection of the most appropriate mitigation solution for a given design.
As a support for dynamic soft error mitigation techniques, it is important to enable the online detection of energetic particles causing the soft errors. This allows activating the power-greedy fault-tolerant configurations based on N-modular redundancy only at the high radiation levels. To enable such a functionality, it is necessary to monitor both the particle flux and the variation of particle LET, as these two parameters contribute significantly to the system SER. In this work, a particle detection approach based on custom-sized pulse stretching inverters is proposed. Employing the pulse stretching inverters connected in parallel enables to measure the particle flux in terms of the number of detected SETs, while the particle LET variations can be estimated from the distribution of SET pulse widths. This approach requires a purely digital processing logic, in contrast to the standard detectors which require complex mixed-signal processing. Besides the possibility of LET monitoring, additional advantages of the proposed particle detector are low detection latency and power consumption, and immunity to error accumulation.
The results achieved in this thesis can serve as a basis for establishment of an overall soft-error-aware database for a given digital library, and a comprehensive multi-level radiation-hard design flow that can be implemented with the standard IC design tools. The following step will be to evaluate the achieved results with the irradiation experiments.
Recognizing, understanding, and responding to quantities are considerable skills for human beings. We can easily communicate quantities, and we are extremely efficient in adapting our behavior to numerical related tasks. One usual task is to compare quantities. We also use symbols like digits in numerical-related tasks. To solve tasks including digits, we must to rely on our previously learned internal number representations.
This thesis elaborates on the process of number comparison with the use of noisy mental representations of numbers, the interaction of number and size representations and how we use mental number representations strategically. For this, three studies were carried out.
In the first study, participants had to decide which of two presented digits was numerically larger. They had to respond with a saccade in the direction of the anticipated answer. Using only a small set of meaningfully interpretable parameters, a variant of random walk models is described that accounts for response time, error rate, and variance of response time for the full matrix of 72 digit pairs. In addition, the used random walk model predicts a numerical distance effect even for error response times and this effect clearly occurs in the observed data. In relation to corresponding correct answers error responses were systematically faster. However, different from standard assumptions often made in random walk models, this account required that the distributions of step sizes of the induced random walks be asymmetric to account for this asymmetry between correct and incorrect responses.
Furthermore, the presented model provides a well-defined framework to investigate the nature and scale (e.g., linear vs. logarithmic) of the mapping of numerical magnitude onto its internal representation. In comparison of the fits of proposed models with linear and logarithmic mapping, the logarithmic mapping is suggested to be prioritized.
Finally, we discuss how our findings can help interpret complex findings (e.g., conflicting speed vs. accuracy trends) in applied studies that use number comparison as a well-established diagnostic tool. Furthermore, a novel oculomotoric effect is reported, namely the saccadic overschoot effect. The participants responded by saccadic eye movements and the amplitude of these saccadic responses decreases with numerical distance.
For the second study, an experimental design was developed that allows us to apply the signal detection theory to a task where participants had to decide whether a presented digit was physically smaller or larger. A remaining question is, whether the benefit in (numerical magnitude – physical size) congruent conditions is related to a better perception than in incongruent conditions. Alternatively, the number-size congruency effect is mediated by response biases due to numbers magnitude. The signal detection theory is a perfect tool to distinguish between these two alternatives. It describes two parameters, namely sensitivity and response bias. Changes in the sensitivity are related to the actual task performance due to real differences in perception processes whereas changes in the response bias simply reflect strategic implications as a stronger preparation (activation) of an anticipated answer. Our results clearly demonstrate that the number-size congruency effect cannot be reduced to mere response bias effects, and that genuine sensitivity gains for congruent number-size pairings contribute to the number-size congruency effect.
Third, participants had to perform a SNARC task – deciding whether a presented digit was odd or even. Local transition probability of irrelevant attributes (magnitude) was varied while local transition probability of relevant attributes (parity) and global probability occurrence of each stimulus were kept constantly. Participants were quite sensitive in recognizing the underlying local transition probability of irrelevant attributes. A gain in performance was observed for actual repetitions of the irrelevant attribute in relation to changes of the irrelevant attribute in high repetition conditions compared to low repetition conditions. One interpretation of these findings is that information about the irrelevant attribute (magnitude) in the previous trial is used as an informative precue, so that participants can prepare early processing stages in the current trial, with the corresponding benefits and costs typical of standard cueing studies.
Finally, the results reported in this thesis are discussed in relation to recent studies in numerical cognition.