Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network

Open Access. Powered by Scholars. Published by Universities.®

Genetics and Genomics

PDF

Dartmouth College

Series

2006

Sequence analysis

Articles 1 - 2 of 2

Full-Text Articles in Entire DC Network

Saccharomyces Cerevisiae-Based Molecular Tool Kit For Manipulation Of Genes From Gram-Negative Bacteria, Robert M. Q. Shanks, Nicky C. Caiazza, Shannon M. Hinsa, Christine M. Toutain, George A. O'Toole Jul 2006

Saccharomyces Cerevisiae-Based Molecular Tool Kit For Manipulation Of Genes From Gram-Negative Bacteria, Robert M. Q. Shanks, Nicky C. Caiazza, Shannon M. Hinsa, Christine M. Toutain, George A. O'Toole

Dartmouth Scholarship

A tool kit of vectors was designed to manipulate and express genes from a wide range of gram-negative species by using in vivo recombination. Saccharomyces cerevisiae can use its native recombination proteins to combine several amplicons in a single transformation step with high efficiency. We show that this technology is particularly useful for vector design. Shuttle, suicide, and expression vectors useful in a diverse group of bacteria are described and utilized. This report describes the use of these vectors to mutate clpX and clpP of the opportunistic pathogen Pseudomonas aeruginosa and to explore their roles in biofilm formation and surface …


Bounded Search For De Novo Identification Of Degenerate Cis-Regulatory Elements, Jonathan M. Carlson, Arijit Chakravarty, Radhika S. Khetani, Robert H. Gross May 2006

Bounded Search For De Novo Identification Of Degenerate Cis-Regulatory Elements, Jonathan M. Carlson, Arijit Chakravarty, Radhika S. Khetani, Robert H. Gross

Dartmouth Scholarship

The identification of statistically overrepresented sequences in the upstream regions of coregulated genes should theoretically permit the identification of potential cis-regulatory elements. However, in practice many cis-regulatory elements are highly degenerate, precluding the use of an exhaustive word-counting strategy for their identification. While numerous methods exist for inferring base distributions using a position weight matrix, recent studies suggest that the independence assumptions inherent in the model, as well as the inability to reach a global optimum, limit this approach.