Biomedical subjects

Naama Brenner

Publications and source records attributed to Naama Brenner.

6 recordsLinked to original sources

PubMed2006

Dynamics of protein distributions in cell populations.

A population of cells exhibits wide phenotypic variation even if it is genetically homogeneous. In particular, individual cells differ from one another in the amount of protein they express under a given regulatory system under fixed conditions. Here we study how protein distributions in a population of the yeast S. cerevisiae are shaped by a balance of processes: protein production--an intracellular process--and protein dilution due to cell division--a population process. We measure protein distributions by employing reporter green fluorescence protein (gfp) under the regulation of the yeast GAL system under conditions where it is metabolically essential. Cell populations are grown in chemostats, thus allowing control of the environment and stable measurements of distribution dynamics over many generations. Despite the essential functional role of the GAL system in a pure galactose medium, steady-state distributions are found to be universally broad, with exponential tails and a large standard-deviation-to-mean ratio. Under several different perturbations the dynamics of the distribution is observed to be asymmetric, with a much longer time to build a wide expression distribution from below compared with a fast relaxation of the distribution toward steady state from above. These results show that the main features of the protein distributions are largely determined by population effects and are less sensitive to the intracellular biochemical noise.

Actins↗

PubMed2006

Synthetic gene recruitment reveals adaptive reprogramming of gene regulation in yeast.

The recruitment of a gene to a foreign regulatory system is a major evolutionary event that can lead to novel phenotypes. However, the evolvability potential of cells depends on their ability to cope with challenges presented by gene recruitment. To study this ability, we combined synthetic gene recruitment with continuous culture and online measurements of the metabolic and regulatory dynamics over long timescales. The gene HIS3 from the histidine synthesis pathway was recruited to the GAL system, responsible for galactose utilization in the yeast S. cerevisiae. Following a switch from galactose to glucose--from induced to repressed conditions of the GAL system--in histidine-lacking chemostats (where the recruited HIS3 is essential), the regulatory system reprogrammed to adaptively tune HIS3 expression, allowing the cells to grow competitively in pure glucose. The adapted state was maintained for hundreds of generations in various environments. The timescales involved and the reproducibility of separate experiments render spontaneous mutations an unlikely underlying mechanism. Essentially all cells could adapt, excluding selection over a genetically variable population. The results reveal heritable adaptation induced by the exposure to glucose. They demonstrate that genetic regulatory networks have the potential to support highly demanding events of gene recruitment.

Adaptation, Biological↗

PubMed2005

History-dependent multiple-time-scale dynamics in a single-neuron model.

History-dependent characteristic time scales in dynamics have been observed at several levels of organization in neural systems. Such dynamics can provide powerful means for computation and memory. At the level of the single neuron, several microscopic mechanisms, including ion channel kinetics, can support multiple-time-scale dynamics. How the temporally complex channel kinetics gives rise to dynamical properties of the neuron is not well understood. Here, we construct a model that captures some features of the connection between these two levels of organization. The model neuron exhibits history-dependent multiple-time-scale dynamics in several effects: first, after stimulation, the recovery time scale is related to the stimulation duration by a power-law scaling; second, temporal patterns of neural activity in response to ongoing stimulation are modulated over time; finally, the characteristic time scale for adaptation after a step change in stimulus depends on the duration of the preceding stimulus. All these effects have been observed experimentally and are not explained by current single-neuron models. The model neuron here presented is composed of an ensemble of ion channels that can wander in a large pool of degenerate inactive states and thus exhibits multiple-time-scale dynamics at the molecular level. Channel inactivation rate depends on recent neural activity, which in turn depends through modulations of the neural response function on the fraction of active channels. This construction produces a model that robustly exhibits nonexponential history-dependent dynamics, in qualitative agreement with experimental results.

Algorithms↗

PubMed2004

Transient responses and adaptation to steady state in a eukaryotic gene regulation system.

Understanding the structure and functionality of eukaryotic gene regulation systems is of fundamental importance in many areas of biology. While most recent studies focus on static or short-term properties, measuring the long-term dynamics of these networks under controlled conditions is necessary for their complete characterization. We demonstrate adaptive dynamics in a well-known system of metabolic regulation, the GAL system in the yeast S. cerevisiae. This is a classic model for a eukaryotic genetic switch, induced by galactose and repressed by glucose. We followed the expression of a reporter gfp under a GAL promoter at single-cell resolution in large population of yeast cells. Experiments were conducted for long time scales, several generations, while controlling the environment in continuous culture. This combination enabled us, for the first time, to distinguish between transient responses and steady state. We find that both galactose induction and glucose repression are only transient responses. Over several generations, the system converges to a single robust steady state, independent of external conditions. Thus, at steady state the GAL network loses its hallmark functionality as a sensitive carbon source rheostat. This result suggests that, while short-term dynamics are determined by specific modular responses, over long time scales inter-modular interactions take over and shape a robust steady state response of the regulatory system.

Biophysical Phenomena↗

PubMed2003

Selective adaptation in networks of cortical neurons.

A key property of neural systems is their ability to adapt selectively to stimuli with different features. Using multisite electrical recordings from networks of cortical neurons developing ex vivo, we show that neurons adapt selectively to different stimuli invading the network. We focus on selective adaptation to frequent and rare stimuli; networks were stimulated at two sites with two different stimulus frequencies. When both stimuli were presented within the same period, neurons in the network attenuated their responsiveness to the more frequent input, whereas their responsiveness to the rarely delivered stimuli showed a marked average increase. The amplification of the response to rare stimuli required the presence of the other, more frequent stimulation source. By contrast, the decreased response to the frequent stimuli occurred regardless of the presence of the rare stimuli. Analysis of the response of single units suggests that both of these effects are caused by changes in synaptic transmission. By using synaptic blockers, we find that the increased responsiveness to the rarely stimulated site depends specifically on fast GABAergic transmission. Thus, excitatory synaptic depression, the inhibitory sub-network, and their balance play an active role in generating selective gain control. The observation that selective adaptation arises naturally in a network of cortical neurons developing ex vivo indicates that this is an inherent feature of spontaneously organizing cortical networks.

Action Potentials↗

PubMed2002

Statistical properties of spike trains: universal and stimulus-dependent aspects.

Statistical properties of spike trains measured from a sensory neuron in vivo are studied experimentally and theoretically. Experiments are performed on an identified neuron in the visual system of the blowfly. It is shown that the spike trains exhibit universal behavior over a short time, modulated by a stimulus-dependent envelope over a long time. A model of the neuron as a nonlinear oscillator driven by noise and by an external stimulus is suggested to account for these results. In the short-time universal regime, the main biophysical effect is refractoriness, which can be described as a repulsive ( 1/x) interaction law among spikes. A universal distribution function for intervals is found, defining a point process with special symmetry properties. The long-time modulations in the spike train are related in a simple way to the properties of the input stimulus as seen through the neuronal nonlinearity. Thus our model enables a separation of the effects of internal neuronal properties from the effect of external stimulus properties. Explicit formulas are derived for different statistical properties, which are in very good agreement with the data in both the universal and the stimulus-dependent regimes.

Animals↗