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Biomedical subjects

J J Collins

Publications and source records attributed to J J Collins.

At least 19 recordsLinked to original sources
PubMed2006

A bottom-up approach to gene regulation.

The ability to construct synthetic gene networks enables experimental investigations of deliberately simplified systems that can be compared to qualitative and quantitative models. If simple, well-characterized modules can be coupled together into more complex networks with behaviour that can be predicted from that of the individual components, we may begin to build an understanding of cellular regulatory processes from the 'bottom up'. Here we have engineered a promoter to allow simultaneous repression and activation of gene expression in Escherichia coli. We studied its behaviour in synthetic gene networks under increasingly complex conditions: unregulated, repressed, activated, and simultaneously repressed and activated. We develop a stochastic model that quantitatively captures the means and distributions of the expression from the engineered promoter of this modular system, and show that the model can be extended and used to accurately predict the in vivo behaviour of the network when it is expanded to include positive feedback. The model also reveals the counterintuitive prediction that noise in protein expression levels can increase upon arrest of cell growth and division, which we confirm experimentally. This work shows that the properties of regulatory subsystems can be used to predict the behaviour of larger, more complex regulatory networks, and that this bottom-up approach can provide insights into gene regulation.

Arabinose↗
PubMed2005

Cancer dose--response assessment for acrylonitrile based upon rodent brain tumor incidence: use of epidemiologic, mechanistic, and pharmacokinetic support for nonlinearity.

A cancer dose-response assessment was conducted for acrylonitrile (AN) using updated information on mechanism of action, epidemiology, toxicity, and pharmacokinetics. Although more than 10 chronic bioassays indicate that AN produces multiple tumors in rats and mice, a number of large, well-conducted epidemiology studies provide no evidence of a causal association between AN exposure and cancer mortality of any type. The epidemiological data include early industry exposures that are far higher than occur today and that approach or exceed levels found to be tumorigenic in animals. Despite the absence of positive findings in the epidemiology data, a dose-response assessment was conducted for AN based on brain tumors in rats. Mechanistic studies implicate the involvement of oxidative stress in rat brain due to a metabolite (2-cyanoethylene oxide or CEO, cyanide), but do not conclusively rule out a potential role for the direct genotoxicity of CEO. A PBPK model was used to predict internal doses (peak CEO in brain) for 12 data sets, which were pooled together to provide a consistent characterization of the dose-response relationship for brain tumor incidence in the rat. The internal dose corresponding to a 5% increase in extra risk (ED 05=0.017 mg/L brain) and its lower confidence limit (LED 05=0.014 mg/L brain) was used as the point of departure. The weight-of-evidence supports the use of a nonlinear extrapolation for the cancer dose-response assessment. A quantitative comparison of the epidemiology exposure-response data (lung and brain cancer mortality) to the rat brain tumor data in terms of internal dose adds to the confidence in the nonlinear extrapolation. Uncertainty factors of 200 and 220 (for the oral and inhalation routes, respectively) were applied to the LED 05 to account for interspecies variation, intraspecies variation, and the severity of the response measure. Accordingly, oral doses below 0.009 mg/kg-day and air concentrations below 0.1mg/m(3) are not expected to pose an appreciable risk to human populations exposed to AN.

Acrylonitrile↗
PubMed2004

Evolving complex dynamics in electronic models of genetic networks.

Ordinary differential equations are often used to model the dynamics and interactions in genetic networks. In one particularly simple class of models, the model genes control the production rates of products of other genes by a logical function, resulting in piecewise linear differential equations. In this article, we construct and analyze an electronic circuit that models this class of piecewise linear equations. This circuit combines CMOS logic and RC circuits to model the logical control of the increase and decay of protein concentrations in genetic networks. We use these electronic networks to study the evolution of limit cycle dynamics. By mutating the truth tables giving the logical functions for these networks, we evolve the networks to obtain limit cycle oscillations of desired period. We also investigate the fitness landscapes of our networks to determine the optimal mutation rate for evolution.

Biological Evolution↗
PubMed2004

Robust identification of large genetic networks.

Temporal and spatial gene expression, together with the concentration of proteins and metabolites, is tightly controlled in the cell. This is possible thanks to complex regulatory networks between these different elements. The identification of these networks would be extremely valuable. We developed a novel algorithm to identify a large genetic network, as a set of linear differential equations, starting from measurements of gene expression at steady state following transcriptional perturbations. Experimentally, it is possible to overexpress each of the genes in the network using an episomal expression plasmid and measure the change in mRNA concentration of all the genes, following the perturbation. Computationally, we reduced the identification problem to a multiple linear regression, assuming that the network is sparse. We implemented a heuristic search method in order to apply the algorithm to large networks. The algorithm can correctly identify the network, even in the presence of large noise in the data, and can be used to predict the genes that directly mediate the action of a compound. Our novel approach is experimentally feasible and it is readily applicable to large genetic networks.

Algorithms↗
PubMed2003

Prediction and measurement of an autoregulatory genetic module.

The deduction of phenotypic cellular responses from the structure and behavior of complex gene regulatory networks is one of the defining challenges of systems biology. This goal will require a quantitative understanding of the modular components that constitute such networks. We pursued an integrated approach, combining theory and experiment, to analyze and describe the dynamics of an isolated genetic module, an in vivo autoregulatory gene network. As predicted by the model, temperature-induced protein destabilization led to the existence of two expression states, thus elucidating the trademark bistability of the positive feedback-network architecture. After sweeping the temperature, observed population distributions and coefficients of variation were in quantitative agreement with those predicted by a stochastic version of the model. Because model fluctuations originated from small molecule-number effects, the experimental validation underscores the importance of internal noise in gene expression. This work demonstrates that isolated gene networks, coupled with proper quantitative descriptions, can elucidate key properties of functional genetic modules. Such an approach could lead to the modular dissection of naturally occurring gene regulatory networks, the deduction of cellular processes such as differentiation, and the development of engineered cellular control.

Cell Differentiation↗
PubMed2003

Noise in eukaryotic gene expression.

Transcription in eukaryotic cells has been described as quantal, with pulses of messenger RNA produced in a probabilistic manner. This description reflects the inherently stochastic nature of gene expression, known to be a major factor in the heterogeneous response of individual cells within a clonal population to an inducing stimulus. Here we show in Saccharomyces cerevisiae that stochasticity (noise) arising from transcription contributes significantly to the level of heterogeneity within a eukaryotic clonal population, in contrast to observations in prokaryotes, and that such noise can be modulated at the translational level. We use a stochastic model of transcription initiation specific to eukaryotes to show that pulsatile mRNA production, through reinitiation, is crucial for the dependence of noise on transcriptional efficiency, highlighting a key difference between eukaryotic and prokaryotic sources of noise. Furthermore, we explore the propagation of noise in a gene cascade network and demonstrate experimentally that increased noise in the transcription of a regulatory protein leads to increased cell-cell variability in the target gene output, resulting in prolonged bistable expression states. This result has implications for the role of noise in phenotypic variation and cellular differentiation.

Cell Differentiation↗
PubMed2003

Cancer risk for chemical workers exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin.

AIMS: To describe the long term mortality experience of a cohort of 2187 male chemical production workers previously exposed to substantial levels of dioxin. METHODS: Vital status for a previously identified cohort was determined for an additional 10 years, to 1995. Dioxin exposures took place before 1983 and were sufficient to result in chloracne in 245 individuals. Mortality rates were compared with national figures and with a large pool of co-workers in unrelated production jobs. RESULTS: All cancers combined (standardised mortality ratio (SMR) = 1.0, 95% CI 0.8 to 1.1) and lung cancer (SMR = 0.8, 95% CI 0.6 to 1.1) were at or below expected levels. Rates for soft tissue sarcoma (SMR = 2.4, 95% CI 0.3 to 8.6) and non-Hodgkin's lymphoma (SMR = 1.4, 95% CI 0.6 to 2.7) were greater than expected overall, but below expectation in the update period. No trend of increasing risk with increasing exposure was observed for these cancers. Workers who developed chloracne had very low all-cancer rates (SMR = 0.5, 95% CI 0.3 to 1.0), and lung cancer rates (SMR = 0.3, 95% CI 0.0 to 1.1). CONCLUSIONS: We found no coherent evidence of increased cancer risk from dioxin exposure in this cohort. Our study highlights the wide range of cancer rates and the lack of consistency across dioxin studies.

Cause of Death↗
PubMed2003

Lymphohaematopoeitic cancer mortality among workers with benzene exposure.

Lymphohaematopoeitic cancer mortality was examined among 4417 workers at a chemical plant by cumulative and peak benzene exposure. There was little evidence of increasing risk with increasing cumulative exposure for all leukaemias or acute non-lymphocytic leukaemias (ANL), or the other lymphohaematopoeitic cancers with the exception of multiple myeloma. For multiple myeloma, the SMRs were 1.1 (95% CI 0.3 to 2.5) in the non-exposed group, 1.4 (95% CI 0.2 to 5.1) in the <1 ppm-years, 1.5 (95% CI 0.2 to 5.4) in the 1-6 ppm-years, and 2.6 (95% CI 0.7 to 6.7) in the >6 ppm-years group. We found no trends by peak exposures for any of the cancers. However, when peak exposures over 100 ppm for 40 or more days were considered, the observed number of all leukaemias (SMR = 2.7, 95% CI 0.8 to 6.4), ANL (SMR = 4.1, 95% CI 0.5 to 14.9), and multiple myeloma (SMR = 4.0, 95% CI 0.8 to 11.7) were greater than expected. While the observed number of deaths is small in this study, the number of peak exposures greater than 100 ppm to benzene is a better predictor of risk than cumulative exposure. The dose rate of benzene and a threshold for exposure response may be important factors for evaluating lymphohaematopoietic risk.

Benzene↗
PubMed2003

The engineering of gene regulatory networks.

The rapid accumulation of genetic information and advancement of experimental techniques have opened a new frontier in biomedical engineering. With the availability of well-characterized components from natural gene networks, the stage has been set for the engineering of artificial gene regulatory networks with sophisticated computational and functional capabilities. In these efforts, the ability to construct, analyze, and interpret qualitative and quantitative models is becoming increasingly important. In this review, we consider the current state of gene network engineering from a combined experimental and modeling perspective. We discuss how networks with increased complexity are being constructed from simple modular components and how quantitative deterministic and stochastic modeling of these modules may provide the foundation for accurate in silico representations of gene regulatory network function in vivo.

Animals↗
PubMed2002

Engineered gene circuits.

A central focus of postgenomic research will be to understand how cellular phenomena arise from the connectivity of genes and proteins. This connectivity generates molecular network diagrams that resemble complex electrical circuits, and a systematic understanding will require the development of a mathematical framework for describing the circuitry. From an engineering perspective, the natural path towards such a framework is the construction and analysis of the underlying submodules that constitute the network. Recent experimental advances in both sequencing and genetic engineering have made this approach feasible through the design and implementation of synthetic gene networks amenable to mathematical modelling and quantitative analysis. These developments have signalled the emergence of a gene circuit discipline, which provides a framework for predicting and evaluating the dynamics of cellular processes. Synthetic gene networks will also lead to new logical forms of cellular control, which could have important applications in functional genomics, nanotechnology, and gene and cell therapy.

Animals↗
PubMed2002

Noise-enhanced human balance control.

Noise can enhance the detection and transmission of weak signals in certain nonlinear systems, via a mechanism known as stochastic resonance. Here we show that input noise can be used to improve motor control in humans. Specifically, we show that the postural sway of both young and elderly individuals during quiet standing can be significantly reduced by applying subsensory mechanical noise to the feet. We further demonstrate with input noise a trend towards the reduction of postural sway in elderly subjects to the level of young subjects. These results suggest that noise-based devices, such as randomly vibrating shoe inserts, may enable people to overcome functional difficulties due to age-related sensory loss.

Adult↗
PubMed2002

Synchronizing genetic relaxation oscillators by intercell signaling.

The ability to design and construct synthetic gene regulatory networks offers the prospect of studying issues related to cellular function in a simplified context; such networks also have many potential applications in biotechnology. A synthetic network exhibiting oscillatory behavior has recently been constructed [Elowitz, M. B. & Leibler, S. (2000) Nature (London) 403, 335-338]. It has also been shown that a natural bacterial quorum-sensing mechanism can be used in a synthetic system to communicate a signal between two populations of cells, such that receipt of the signal causes expression of a target gene [Weiss, R. & Knight, T. F. (2000) in DNA6: Sixth International Meeting on DNA-Based Computers, June 13-17, 2000, Leiden, The Netherlands]. We propose a synthetic gene network in Escherichia coli which combines these two features: the system acts as a relaxation oscillator and uses an intercell signaling mechanism to couple the oscillators and induce synchronous oscillations. We model the system and show that the proposed coupling scheme does lead to synchronous behavior across a population of cells. We provide an analytical treatment of the synchronization process, the dominant mechanism of which is "fast threshold modulation."

Bacterial Proteins↗
PubMed2002

Sensory nerves and neuropeptides in uterine cervical ripening.

At the time of parturition (fetal delivery) the uterine cervix must "ripen," becoming soft, pliable, and dilated to accommodate the fetus' delivery. The fundamental processes underlying cervical ripening remain poorly understood. Knowledge that abundant autonomic and sensory nerves supply the uterine cervix, that transection of afferent nerves supplying the cervix blocks parturition, and that some of the changes in the cervix resemble those seen in inflammatory reactions suggests nerves may have a role in the cervical ripening changes. The present study utilized immunohistochemistry, plasma extravasation, and solution hybridization-nuclease protection assay to elucidate the complement of primary afferent nerves and some receptors in the rat cervix during pregnancy, and to determine if they may have roles in the ripening process at term. This study revealed an abundance of nerves associated with the cervical vasculature and myometrial smooth muscle containing immunoreactivity for substance P, calcitonin gene-related peptide, secretoneurin, and nitric oxide synthase throughout pregnancy. Many of these are small unmyelinated capsaicin-sensitive C-fibers. Substance P- (NK1-) and calcitonin gene-related peptide receptors were apparent on uterine cervix vasculature from pregnant, parturient, and postpartum rats. NK1 receptor mRNA was maximal at 20 days of pregnancy. Plasma extravasation of i.v. administered Evans Blue or Monastral Blue was most pronounced at parturition (shortly after NK1 mRNA is maximal); this was similar to plasma extravasation evoked by i.v. administration of substance P or capsaicin-treatment. This study revealed new data about the nervous system of the rat uterine cervix and that these nerves and their transmitters could very well be part of a neurogenic inflammatory process involved in cervical ripening.

Animals↗
PubMed2002

Molecular epidemiology of cystic fibrosis-linked Burkholderia cepacia complex isolates from three national referral centres in Ireland.

AIMS: Burkholderia cepacia is a Gram-negative bacterium associated with increasing morbidity and mortality and is readily transmitted among infected cystic fibrosis (CF) patients. The B. cepacia complex consists of five distinct subgroups, termed genomovars. A collection of 17 presumptive B. cepacia isolates, obtained from three national CF referral centres located in different geographical regions in Ireland, was studied. The aim of this study was to investigate these isolates using molecular subtyping protocols for evidence of genetic relationships and for the presence of antibiotic resistance-encoding class 1 integron structures. METHODS AND RESULTS: Genomovar classifications were assigned to each isolate based on HaeIII enzyme profiles of their recA locus. Genetic relationships among this collection were also assessed after restriction fragment length polymorphism (RFLP)-mediated analysis of the 16S rDNA locus and DNA amplification fingerprinting (DAF). The surface expression of the cable pilus gene (cblA) may facilitate an early step in the infection process. All isolates were tested by amplification strategies for this marker. Burkholderia cepacia is known to be resistant to several antimicrobial agents. Resistance typing showed that the majority were resistant to three or more common antimicrobial agents. Five of the 17 isolates were resistant to sulphonamide, a characteristic linked with the presence of class 1 integrons. Gene cassettes containing beta-lactamase (oxa) and aminoglycoside acetyltransferase (aac(6')-1a) encoding genes were identified by polymerase chain reaction amplification. CONCLUSIONS: Most of the isolates in this study were classified as genomovar III and were indistinguishable based on their corresponding 16S rDNA-RFLP profiles, whilst DAF further subtyped the collection. The cblA marker was identified in 47% of the isolates, many of which clustered in the genomovar III group. Class 1 integrons with recombined gene cassettes containing bla-OXA and aac(6')-1a genes were identified. SIGNIFICANCE AND IMPACT OF THE STUDY: This study demonstrates the application of molecular methods to investigate B. cepacia, a well-recognized human pathogen, cultured from Irish CF patients. Genomovar III was the most common genomic type identified. DNA fingerprinting further subtyped the latter isolates, facilitating a more detailed description of the molecular epidemiology. Drug resistance in these organisms can be explained, at least in part, by the presence of class 1 integrons. Development of targeted infection control strategies could be facilitated using these applied methods.

Amino Acid Sequence↗