Study of in vitro transcriptional binding effects and noise using constitutive promoters combined with UP element sequences in Escherichia coli

Background UP elements (upstream element) are DNA sequences upstream of a promoter that interact with the α-subunit of RNA polymerase (RNAP) and can affect transcription by altering the binding RNAP to DNA. However, details of UP element and binding affinity effects on transcriptional strength are unclear. Results Here, we investigated the effects of UP element sequences on gene transcription, binding affinity, and gene expression noise. Addition of UP elements resulted in increased gene expression (maximum 95.7-fold increase) and reduced gene expression noise (8.51-fold reduction). Half UP element sequences at the proximal subsite has little effect on transcriptional strength despite increasing binding affinity by 2.28-fold. In vitro binding assays were used to determine dissociation constants (Kd) and in the in vitro system, the full range of gene expression occurs in a small range of dissociation constants (25 nM \u3c Kd \u3c 45 nM) indicating that transcriptional strength is highly sensitive to small changes in binding affinity. Conclusions These results demonstrate the utility of UP elements and provide mechanistic insight into the functional relationship between binding affinity and transcription. Given the centrality of gene expression via transcription to biology, additional insight into transcriptional mechanisms can foster both fundamental and applied research. In particular, knowledge of the DNA sequence-specific effects on expression strength can aid in promoter engineering for different organisms and for metabolic engineering to balance pathway fluxes

Bound states of the Klein-Gordon equation for vector and scalar general Hulthen-type potentials in D-dimension

We solve the Klein-Gordon equation in any $D$-dimension for the scalar and vector general Hulth\'{e}n-type potentials with any $l$ by using an approximation scheme for the centrifugal potential. Nikiforov-Uvarov method is used in the calculations. We obtain the bound state energy eigenvalues and the corresponding eigenfunctions of spin-zero particles in terms of Jacobi polynomials. The eigenfunctions are physical and the energy eigenvalues are in good agreement with those results obtained by other methods for D=1 and 3 dimensions. Our results are valid for $q=1$ value when $l\neq 0$ and for any $q$ value when $l=0$ and D=1 or 3. The $s$% -wave ($l=0$) binding energies for a particle of rest mass $m_{0}=1$ are calculated for the three lower-lying states $(n=0,1,2)$ using pure vector and pure scalar potentials.Comment: 25 page

Proton spin in a light-cone chiral quark model

We discuss the spin structure of the proton in a light-cone treatment of the chiral quark model. Based on the fact that the quark helicity ($\Delta q$) measured in polarized deep inelastic scattering experiments is actually the quark spin defined in the light-cone formalism, rather than the quark spin ($\Delta q_{QM}$) defined in the conventionally quark model (or in the rest frame of the nucleon), we calculate the $x$-dependence of the polarized quark distribution functions $\Delta q(x)$, and the polarized structure functions $g_1 (x)$. Special attention is focused on the Melosh-Wigner rotation due to the transversal motions of quarks inside the nucleon and its effects on the bare quark input. It is shown that our results match the experimental data well.Comment: 11 latex pages, 8 figures, final version published in PR

Modeling Collaboration in Academia: A Game Theoretic Approach

In this work, we aim to understand the mechanisms driving academic collaboration. We begin by building a model for how researchers split their effort between multiple papers, and how collaboration affects the number of citations a paper receives, supported by observations from a large real-world publication and citation dataset, which we call the h-Reinvestment model. Using tools from the field of Game Theory, we study researchers' collaborative behavior over time under this model, with the premise that each researcher wants to maximize his or her academic success. We find analytically that there is a strong incentive to collaborate rather than work in isolation, and that studying collaborative behavior through a game-theoretic lens is a promising approach to help us better understand the nature and dynamics of academic collaboration.Comment: Presented at the 1st WWW Workshop on Big Scholarly Data (2014). 6 pages, 5 figure