Xeroderma pigmentosum group A protein loads as a separate factor onto DNA lesions

Nucleotide excision repair (NER) is the main DNA repair pathway in mammals for removal of UV-induced lesions. NER involves the concerted action of more than 25 polypeptides in a coordinated fashion. The xeroderma pigmentosum group A protein (XPA) has been suggested to function as a central organizer and damage verifier in NER. How XPA reaches DNA lesions and how the protein is distributed in time and space in living cells are unknown. Here we studied XPA in vivo by using a cell line stably expressing physiological levels of functional XPA fused to green fluorescent protein and by applying quantitative fluorescence microscopy. The majority of XPA moves rapidly through the nucleoplasm with a diffusion rate different from those of other NER factors tested, arguing against a preassembled XPA-containing NER complex. DNA damage induced a transient ( approximately 5-min) immobilization of maximally 30% of XPA. Immobilization depends on XPC, indicating that XPA is not the initial lesion recognition protein in vivo. Moreover, loading of replication protein A on NER lesions was not dependent on XPA. Thus, XPA participates in NER by incorporation of free diffusing molecules in XPC-dependent NER-DNA complexes. This study supports a model for a rapid consecutive assembly of free NER factors, and a relatively slow simultaneous disassembly, after repair

Population-level transcription cycles derive from stochastic timing of single-cell transcription

Eukaryotic transcription is a dynamic process relying on a large number of proteins. By measuring the cycling expression of the pyruvate dehydrogenase kinase 4 gene in human cells, we constructed a detailed stochastic model for single-gene transcription at the molecular level using realistic kinetics for diffusion and protein complex dynamics. We observed that gene induction caused an approximate 60 min periodicity of several transcription related processes: first, the covalent histone modifications and presence of many regulatory proteins at the transcription start site; second, RNA polymerase II activity; third, chromatin loop formation; and fourth, mRNA accumulation. Our model can predict the precise timing of single-gene activity leading to transcriptional cycling on the cell population level when we take into account the sequential and irreversible multistep nature of transcriptional initiation. We propose that the cyclic nature of population gene expression is primarily based on the intrinsic periodicity of the transcription process itself. © 2009 Elsevier Inc. All rights reserved

Systems Biology towards life in silico: mathematics of the control of living cells.

Systems Biology is the science that aims to understand how biological function absent from macromolecules in isolation, arises when they are components of their system. Dedicated to the memory of Reinhart Heinrich, this paper discusses the origin and evolution of the new part of systems biology that relates to metabolic and signal-transduction pathways and extends mathematical biology so as to address postgenomic experimental reality. Various approaches to modeling the dynamics generated by metabolic and signal-transduction pathways are compared. The silicon cell approach aims to describe the intracellular network of interest precisely, by numerically integrating the precise rate equations that characterize the ways macromolecules' interact with each other. The non-equilibrium thermodynamic or 'lin-log' approach approximates the enzyme rate equations in terms of linear functions of the logarithms of the concentrations. Biochemical Systems Analysis approximates in terms of power laws. Importantly all these approaches link system behavior to molecular interaction properties. The latter two do this less precisely but enable analytical solutions. By limiting the questions asked, to optimal flux patterns, or to control of fluxes and concentrations around the (patho)physiological state, Flux Balance Analysis and Metabolic/Hierarchical Control Analysis again enable analytical solutions. Both the silicon cell approach and Metabolic/Hierarchical Control Analysis are able to highlight where and how system function derives from molecular interactions. The latter approach has also discovered a set of fundamental principles underlying the control of biological systems. The new law that relates concentration control to control by time is illustrated for an important signal transduction pathway, i.e. nuclear hormone receptor signaling such as relevant to bone formation. It is envisaged that there ismuch more Mathematical Biology to be discovered in the area between molecules and Life. © Springer-Verlag 2008

Impact on perinatal health and cost-effectiveness of risk-based care in obstetrics: a before-after study

BACKGROUND: Obstetric health care relies on an adequate antepartum risk selection. Most guidelines used for risk stratification, however, do not assess absolute risks. In 2017, a prediction tool was implemented in a Dutch region. This tool combines first trimester prediction models with obstetric care paths tailored to the individual risk profile, enabling risk-based care. OBJECTIVE: To assess impact and cost-effectiveness of risk-based care compared to care-as-usual in a general population. METHODS: A before-after study was conducted using 2 multicenter prospective cohorts. The first cohort (2013-2015) received care-as-usual; the second cohort (2017-2018) received risk-based care. Health outcomes were (1) a composite of adverse perinatal outcomes and (2) maternal quality-adjusted life-years. Costs were estimated using a health care perspective from conception to 6 weeks after the due date. Mean costs per woman, cost differences between the 2 groups, and incremental cost effectiveness ratios were calculated. Sensitivity analyses were performed to evaluate the robustness of the findings. RESULTS: In total 3425 women were included. In nulliparous women there was a significant reduction of perinatal adverse outcomes among the risk-based care group (adjusted odds ratio, 0.56; 95% confidence interval, 0.32-0.94), but not in multiparous women. Mean costs per pregnant woman were significantly lower for risk-based care (mean difference, -(sic)2766; 95% confidence interval, -(sic)3700 to -(sic)1825). No differences in maternal quality of life, adjusted for baseline health, were observed. CONCLUSION: In the Netherlands, risk-based care in nulliparous women was associated with improved perinatal outcomes as compared to care-as-usual. Furthermore, risk-based care was cost-effective compared to care-as-usual and resulted in lower health care costs