Altering transcription factor binding reveals comprehensive transcriptional kinetics of a basic gene.

Transcription is a vital process activated by transcription factor (TF) binding. The active gene releases a burst of transcripts before turning inactive again. While the basic course of transcription is well understood, it is unclear how binding of a TF affects the frequency, duration and size of a transcriptional burst. We systematically varied the residence time and concentration of a synthetic TF and characterized the transcription of a synthetic reporter gene by combining single molecule imaging, single molecule RNA-FISH, live transcript visualisation and analysis with a novel algorithm, Burst Inference from mRNA Distributions (BIRD). For this well-defined system, we found that TF binding solely affected burst frequency and variations in TF residence time had a stronger influence than variations in concentration. This enabled us to device a model of gene transcription, in which TF binding triggers multiple successive steps before the gene transits to the active state and actual mRNA synthesis is decoupled from TF presence. We quantified all transition times of the TF and the gene, including the TF search time and the delay between TF binding and the onset of transcription. Our quantitative measurements and analysis revealed detailed kinetic insight, which may serve as basis for a bottom-up understanding of gene regulation.

Requirements of Health Data Management Systems for Biomedical Care and Research: Scoping Review.

BACKGROUND: Over the last century, disruptive incidents in the fields of clinical and biomedical research have yielded a tremendous change in health data management systems. This is due to a number of breakthroughs in the medical field and the need for big data analytics and the Internet of Things (IoT) to be incorporated in a real-time smart health information management system. In addition, the requirements of patient care have evolved over time, allowing for more accurate prognoses and diagnoses. In this paper, we discuss the temporal evolution of health data management systems and capture the requirements that led to the development of a given system over a certain period of time. Consequently, we provide insights into those systems and give suggestions and research directions on how they can be improved for a better health care system. OBJECTIVE: This study aimed to show that there is a need for a secure and efficient health data management system that will allow physicians and patients to update decentralized medical records and to analyze the medical data for supporting more precise diagnoses, prognoses, and public insights. Limitations of existing health data management systems were analyzed. METHODS: To study the evolution and requirements of health data management systems over the years, a search was conducted to obtain research articles and information on medical lawsuits, health regulations, and acts. These materials were obtained from the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery, Elsevier, MEDLINE, PubMed, Scopus, and Web of Science databases. RESULTS: Health data management systems have undergone a disruptive transformation over the years from paper to computer, web, cloud, IoT, big data analytics, and finally to blockchain. The requirements of a health data management system revealed from the evolving definitions of medical records and their management are (1) medical record data, (2) real-time data access, (3) patient participation, (4) data sharing, (5) data security, (6) patient identity privacy, and (7) public insights. This paper reviewed health data management systems based on these 7 requirements across studies conducted over the years. To our knowledge, this is the first analysis of the temporal evolution of health data management systems giving insights into the system requirements for better health care. CONCLUSIONS: There is a need for a comprehensive real-time health data management system that allows physicians, patients, and external users to input their medical and lifestyle data into the system. The incorporation of big data analytics will aid in better prognosis or diagnosis of the diseases and the prediction of diseases. The prediction results will help in the development of an effective prevention plan.

Inferring quantity and qualities of superimposed reaction rates from single molecule survival time distributions.

Actions of molecular species, for example binding of transcription factors to chromatin, may comprise several superimposed reaction pathways. The number and the rate constants of such superimposed reactions can in principle be resolved by inverse Laplace transformation of the corresponding distribution of reaction lifetimes. However, current approaches to solve this transformation are challenged by photobleaching-prone fluorescence measurements of lifetime distributions. Here, we present a genuine rate identification method (GRID), which infers the quantity, rates and amplitudes of dissociation processes from fluorescence lifetime distributions using a dense grid of possible decay rates. In contrast to common multi-exponential analysis of lifetime distributions, GRID is able to distinguish between broad and narrow clusters of decay rates. We validate GRID by simulations and apply it to CDX2-chromatin interactions measured by live cell single molecule fluorescence microscopy. GRID reveals well-separated narrow decay rate clusters of CDX2, in part overlooked by multi-exponential analysis. We discuss the amplitudes of the decay rate spectrum in terms of frequency of observed events and occupation probability of reaction states. We further demonstrate that a narrow decay rate cluster is compatible with a common model of TF sliding on DNA.

Single-molecule imaging correlates decreasing nuclear volume with increasing TF-chromatin associations during zebrafish development.

Zygotic genome activation (ZGA), the onset of transcription after initial quiescence, is a major developmental step in many species, which occurs after ten cell divisions in zebrafish embryos. How transcription factor (TF)-chromatin interactions evolve during early development to support ZGA is largely unknown. We establish single molecule tracking in live developing zebrafish embryos using reflected light-sheet microscopy to visualize two fluorescently labeled TF species, mEos2-TBP and mEos2-Sox19b. We further develop a data acquisition and analysis scheme to extract quantitative information on binding kinetics and bound fractions during fast cell cycles. The chromatin-bound fraction of both TFs increases during early development, as expected from a physical model of TF-chromatin interactions including a decreasing nuclear volume and increasing DNA accessibility. For Sox19b, data suggests the increase is mainly due to the shrinking nucleus. Our single molecule approach provides quantitative insight into changes of TF-chromatin associations during the developmental period embracing ZGA.

DNA residence time is a regulatory factor of transcription repression.

Transcription comprises a highly regulated sequence of intrinsically stochastic processes, resulting in bursts of transcription intermitted by quiescence. In transcription activation or repression, a transcription factor binds dynamically to DNA, with a residence time unique to each factor. Whether the DNA residence time is important in the transcription process is unclear. Here, we designed a series of transcription repressors differing in their DNA residence time by utilizing the modular DNA binding domain of transcription activator-like effectors (TALEs) and varying the number of nucleotide-recognizing repeat domains. We characterized the DNA residence times of our repressors in living cells using single molecule tracking. The residence times depended non-linearly on the number of repeat domains and differed by more than a factor of six. The factors provoked a residence time-dependent decrease in transcript level of the glucocorticoid receptor-activated gene SGK1. Down regulation of transcription was due to a lower burst frequency in the presence of long binding repressors and is in accordance with a model of competitive inhibition of endogenous activator binding. Our single molecule experiments reveal transcription factor DNA residence time as a regulatory factor controlling transcription repression and establish TALE-DNA binding domains as tools for the temporal dissection of transcription regulation.

Tactile Toe Agnosia and Percept of a "Missing Toe" in Healthy Humans.

A disturbance of body representation is central to many neurological and psychiatric conditions, but the mechanisms by which body representations are constructed by the brain are not fully understood. We demonstrate a directional disturbance in tactile identification of the toes in healthy humans. Nineteen young adult participants underwent tactile stimulation of the digits with the eyes closed and verbally reported the identity of the stimulated digit. In the majority of individuals, responses to the second and third toes were significantly biased toward the laterally neighboring digit. The directional bias was greater for the nondominant foot and was affected by the identity of the immediately preceding stimulated toe. Unexpectedly, 9/19 participants reported the subjective experience of a "missing toe" or "missing space" during the protocol. These findings challenge current models of somatosensory localization, as they cannot be explained simply by a lack of distinct representations for toes compared with fingers, or by overt toe-finger correspondences. We present a novel theory of equal spatial representations of digit width combined with a "preceding neighbor" effect to explain the observed phenomena. The diagnostic implications for neurological disorders that involve "digit agnosia" are discussed.

Innovative concept for a major breakthrough in atmospheric radioactive xenon detection for nuclear explosion monitoring.

The verification regime of the comprehensive test ban treaty (CTBT) is based on a network of three different waveform technologies together with global monitoring of aerosols and noble gas in order to detect, locate and identify a nuclear weapon explosion down to 1 kt TNT equivalent. In case of a low intensity underground or underwater nuclear explosion, it appears that only radioactive gases, especially the noble gas which are difficult to contain, will allow identification of weak yield nuclear tests. Four radioactive xenon isotopes, 131mXe, 133mXe, 133Xe and 135Xe, are sufficiently produced in fission reactions and exhibit suitable half-lives and radiation emissions to be detected in atmosphere at low level far away from the release site. Four different monitoring CTBT systems, ARIX, ARSA, SAUNA, and SPALAX™ have been developed in order to sample and to measure them with high sensitivity. The latest developed by the French Atomic Energy Commission (CEA) is likely to be drastically improved in detection sensitivity (especially for the metastable isotopes) through a higher sampling rate, when equipped with a new conversion electron (CE)/X-ray coincidence spectrometer. This new spectrometer is based on two combined detectors, both exhibiting very low radioactive background: a well-type NaI(Tl) detector for photon detection surrounding a gas cell equipped with two large passivated implanted planar silicon chips for electron detection. It is characterized by a low electron energy threshold and a much better energy resolution for the CE than those usually measured with the existing CTBT equipments. Furthermore, the compact geometry of the spectrometer provides high efficiency for X-ray and for CE associated to the decay modes of the four relevant radioxenons. The paper focus on the design of this new spectrometer and presents spectroscopic performances of a prototype based on recent results achieved from both radioactive xenon standards and air sample measurements. Major improvements in detection sensitivity have been reached and quantified, especially for metastable radioactive isotopes 131mXe and 133mXe with a gain in minimum detectable activity (about 2 × 10-3 Bq) relative to current CTBT SPALAX™ system (air sampling frequency normalized to 8 h) of about 70 and 30 respectively.