Molecular Clock on a Neutral Network

The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating the topological structure of a neutral network from empirical measurements of the substitution process.Comment: 10 page

Analysis of multiple incidence angle SIR-B data for determining forest stand characteristics

For the first time in the U.S. space program, digital synthetic aperture radar (SR) data were obtained from different incidence angles during Space Shuttle Mission 41-G. Shuttle Imaging Radar-B (SIR-B) data were obtained at incidence angles of 58 deg., 45 deg., and 28 deg., on October 9, 10, and 11, 1984, respectively, for a predominantly forested study area in northern Florida. Cloud-free LANDSAT Thematic Mapper (T.M.) data were obtained over the same area on October 12. The SIR-B data were processed and then digitally registered to the LANDSAT T.M. data by scientists at the Jet Propulsion Laboratory. This is the only known digitally registered SIR-B and T.M. data set for which the data were obtained nearly simultaneously. The data analysis of this information is discussed

Analytical study of non Gaussian fluctuations in a stochastic scheme of autocatalytic reactions

A stochastic model of autocatalytic chemical reactions is studied both numerically and analytically. The van Kampen perturbative scheme is implemented, beyond the second order approximation, so to capture the non Gaussianity traits as displayed by the simulations. The method is targeted to the characterization of the third moments of the distribution of fluctuations, originating from a system of four populations in mutual interaction. The theory predictions agree well with the simulations, pointing to the validity of the van Kampen expansion beyond the conventional Gaussian solution.Comment: 15 pages, 8 figures, submitted to Phys. Rev.

Error threshold in finite populations

A simple analytical framework to study the molecular quasispecies evolution of finite populations is proposed, in which the population is assumed to be a random combination of the constiyuent molecules in each generation,i.e., linkage disequilibrium at the population level is neglected. In particular, for the single-sharp-peak replication landscape we investigate the dependence of the error threshold on the population size and find that the replication accuracy at threshold increases linearly with the reciprocal of the population size for sufficiently large populations. Furthermore, in the deterministic limit our formulation yields the exact steady-state of the quasispecies model, indicating then the population composition is a random combination of the molecules.Comment: 14 pages and 4 figure

The transcriptional cofactor MIER1-beta negatively regulates histone acetyltransferase activity of the CREB-binding protein

Background: Mier1 encodes a novel transcriptional regulator and was originally isolated as a fibroblast growth factor early response gene. Two major protein isoforms have been identified, MIER1 and, which differ in their C-terminal sequence. Previously, we demonstrated that both isoforms recruit histone deacetylase 1 (HDAC1) to repress transcription. To further explore the role of MIER1 in chromatin remodeling, we investigated the functional interaction of MIER1 with the histone acetyltransferase (HAT), Creb-binding protein (CBP). Findings: Using GST pull-down assays, we demonstrate that MIER1 interacts with CBP and that this interaction involves the N-terminal half (amino acids 1-283) of MIER1, which includes the acidic activation and ELM2 domains and the C-terminal half (amino acids 1094-2441) of CBP, which includes the bromo-, HAT, C/H3 and glutamine-rich domains. Functional analysis, using HEK293 cells, shows that the CBP bound to MIER1 in vivo has no detectable HAT activity. Histone 4 peptide binding assays demonstrate that this inhibition of HAT activity is not the result of interference with histone binding. Conclusion: Our data indicate that an additional mechanism by which MIER1 could repress transcription involves the inhibition of histone acetyltransferase activity

Stability of adhesion clusters under constant force

We solve the stochastic equations for a cluster of parallel bonds with shared constant loading, rebinding and the completely dissociated state as an absorbing boundary. In the small force regime, cluster lifetime grows only logarithmically with bond number for weak rebinding, but exponentially for strong rebinding. Therefore rebinding is essential to ensure physiological lifetimes. The number of bonds decays exponentially with time for most cases, but in the intermediate force regime, a small increase in loading can lead to much faster decay. This effect might be used by cell-matrix adhesions to induce signaling events through cytoskeletal loading.Comment: Revtex, 4 pages, 4 Postscript files include

On-the-fly Uniformization of Time-Inhomogeneous Infinite Markov Population Models

This paper presents an on-the-fly uniformization technique for the analysis of time-inhomogeneous Markov population models. This technique is applicable to models with infinite state spaces and unbounded rates, which are, for instance, encountered in the realm of biochemical reaction networks. To deal with the infinite state space, we dynamically maintain a finite subset of the states where most of the probability mass is located. This approach yields an underapproximation of the original, infinite system. We present experimental results to show the applicability of our technique

Differential Splicing Alters Subcellular Localization of the Alpha but not Beta Isoform of the MIER1 Transcriptional Regulator in Breast Cancer Cells

MIER1 was originally identified in a screen for novel fibroblast growth factor activated early response genes. The mier1 gene gives rise to multiple transcripts encoding protein isoforms that differ in their amino (N-) and carboxy (C-) termini. Much of the work to date has focused on the two C-terminal variants, MIER1α and β, both of which have been shown to function as transcriptional repressors. Our previous work revealed a dramatic shift in MIER1α subcellular localization from nuclear in normal breast tissue to cytoplasmic in invasive breast carcinoma, suggesting that loss of nuclear MIER1α may play a role in breast cancer development. In the present study, we investigated whether alternative splicing to include a cassette exon and produce an N–terminal variant of MIER1α affects its subcellular localization in MCF7 breast carcinoma cells. We demonstrate that this cassette exon, exon 3A, encodes a consensus leucine-rich nuclear export signal (NES). Inclusion of this exon in MIER1α to produce the MIER1-3Aα isoform altered its subcellular distribution in MCF7 cells from 81% nuclear to 2% nuclear and this change in localization was abrogated by mutation of critical leucines within the NES. Treatment with leptomycin B (LMB), an inhibitor of the nuclear export receptor CRM1, resulted in a significant increase in the percentage of cells with nuclear MIER1-3Aα, from 4% to 53%, demonstrating that cytoplasmic localization of this isoform was due to CRM1-dependent nuclear export. Inclusion of exon 3A in MIER1β to produce the N-terminal variant MIER1-3Aβ however had little effect on the nuclear targeting of this isoform. Our results demonstrate that alternative splicing to include exon 3A specifically affects the localization pattern of the α isoform

Programmable models of growth and mutation of cancer-cell populations

In this paper we propose a systematic approach to construct mathematical models describing populations of cancer-cells at different stages of disease development. The methodology we propose is based on stochastic Concurrent Constraint Programming, a flexible stochastic modelling language. The methodology is tested on (and partially motivated by) the study of prostate cancer. In particular, we prove how our method is suitable to systematically reconstruct different mathematical models of prostate cancer growth - together with interactions with different kinds of hormone therapy - at different levels of refinement.Comment: In Proceedings CompMod 2011, arXiv:1109.104