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2.
Oncogene ; 30(45): 4567-77, 2011 Nov 10.
Article in English | MEDLINE | ID: mdl-21666717

ABSTRACT

To identify regulators of intracellular signaling, we targeted 541 kinases and kinase-related molecules with small interfering RNAs (siRNAs), and determined their effects on signaling with a functional proteomics reverse-phase protein array (RPPA) platform assessing 42 phospho and total proteins. The kinome-wide screen demonstrated a strong inverse correlation between phosphorylation of AKT and mitogen-activated protein kinase (MAPK) with 115 genes that, when targeted by siRNAs, demonstrated opposite effects on MAPK and AKT phosphorylation. Network-based analysis identified the MAPK subnetwork of genes along with p70S6K and FRAP1 as the most prominent targets that increased phosphorylation of AKT, a key regulator of cell survival. The regulatory loops induced by the MAPK pathway are dependent on tuberous sclerosis complex 2 but demonstrate a lesser dependence on p70S6K than the previously identified FRAP1 feedback loop. The siRNA screen also revealed novel bi-directionality in the AKT and GSK3 (Glycogen synthase kinase 3) interaction, whereby genetic ablation of GSK3 significantly blocks AKT phosphorylation, an unexpected observation as GSK3 has only been predicted to be downstream of AKT. This method uncovered novel modulators of AKT phosphorylation and facilitated the mapping of regulatory loops.


Subject(s)
Metabolic Networks and Pathways/physiology , Phosphoproteins/metabolism , Proto-Oncogene Proteins c-akt/metabolism , Cell Line, Tumor , Cell Survival/genetics , Humans , Metabolic Networks and Pathways/genetics , Phosphoproteins/genetics , Phosphorylation , Proteomics , Proto-Oncogene Proteins c-akt/genetics , RNA, Small Interfering/metabolism , Signal Transduction/genetics , Signal Transduction/physiology , Tuberous Sclerosis Complex 2 Protein , Tumor Suppressor Proteins/genetics , Tumor Suppressor Proteins/metabolism
3.
Bioinformatics ; 24(13): i123-31, 2008 Jul 01.
Article in English | MEDLINE | ID: mdl-18586704

ABSTRACT

MOTIVATION: In bacterial evolution, inferring a strain tree, which is the evolutionary history of different strains of the same bacterium, plays a major role in analyzing and understanding the evolution of strongly isolated populations, population divergence and various evolutionary events, such as horizontal gene transfer and homologous recombination. Inferring a strain tree from multilocus data of these strains is exceptionally hard since, at this scale of evolution, processes such as homologous recombination result in a very high degree of gene tree incongruence. RESULTS: In this article we present a novel computational method for inferring the strain tree despite massive gene tree incongruence caused by homologous recombination. Our method operates in three phases, where in phase I a set of candidate strain-tree topologies is computed using the maximal cliques concept, in phase II divergence times for each of the topologies are estimated using mixed integer linear programming (MILP) and in phase III the optimal tree (or trees) is selected based on an optimality criterion. We have analyzed 1898 genes from nine strains of the Staphylococcus aureus bacteria, and identified a fully resolved (binary) strain tree with estimated divergence times, despite the high degrees of sequence identity at the nucleotide level and gene tree incongruence. Our method's efficiency makes it particularly suitable for analysis of genome-scale datasets, including those of strongly isolated populations which are usually very challenging to analyze. AVAILABILITY: We have implemented the algorithms in the PhyloNet software package, which is available publicly at http://bioinfo.cs.rice.edu/phylonet/.


Subject(s)
Algorithms , Biological Evolution , Chromosome Mapping/methods , DNA Mutational Analysis/methods , Databases, Genetic , Evolution, Molecular , Genome, Bacterial/genetics , Sequence Analysis, DNA/methods , Base Sequence , Molecular Sequence Data , Species Specificity
4.
J Mol Evol ; 63(6): 815-25, 2006 Dec.
Article in English | MEDLINE | ID: mdl-17086450

ABSTRACT

Ca(2+)/cation antiporter (CaCA) proteins are integral membrane proteins that transport Ca(2+) or other cations using the H(+) or Na(+) gradient generated by primary transporters. The CAX (for CAtion eXchanger) family is one of the five families that make up the CaCA superfamily. CAX genes have been found in bacteria, Dictyostelium, fungi, plants, and lower vertebrates, but only a small number of CAXs have been functionally characterized. In this study, we explored the diversity of CAXs and their phylogenetic relationships. The results demonstrate that there are three major types of CAXs: type I (CAXs similar to Arabidopsis thaliana CAX1, found in plants, fungi, and bacteria), type II (CAXs with a long N-terminus hydrophilic region, found in fungi, Dictyostelium, and lower vertebrates), and type III (CAXs similar to Escherichia coli ChaA, found in bacteria). Some CAXs were found to have secondary structures that are different from the canonical six transmembrane (TM) domains-acidic motif-five TM domain structure. Our phylogenetic tree indicated no evidence to support the cyanobacterial origin of plant CAXs or the classification of Arabidopsis exchangers CAX7 to CAX11. For the first time, these results clearly define the CAX exchanger family and its subtypes in phylogenetic terms. The surprising diversity of CAXs demonstrates their potential range of biochemical properties and physiologic relevance.


Subject(s)
Antiporters/genetics , Cation Transport Proteins/genetics , Phylogeny , Amino Acid Sequence , Antiporters/classification , Arabidopsis Proteins/classification , Arabidopsis Proteins/genetics , Bacterial Proteins/genetics , Cation Transport Proteins/classification , Fungal Proteins/genetics , Molecular Sequence Data , Protozoan Proteins/genetics , Sequence Homology, Amino Acid
5.
Bioinformatics ; 17 Suppl 1: S190-8, 2001.
Article in English | MEDLINE | ID: mdl-11473009

ABSTRACT

Absolute fast converging phylogenetic reconstruction methods are provably guaranteed to recover the true tree with high probability from sequences that grow only polynomially in the number of leaves, once the edge lengths are bounded arbitrarily from above and below. Only a few methods have been determined to be absolute fast converging; these have all been developed in just the last few years, and most are polynomial time. In this paper, we compare pre-existing fast converging methods as well as some new polynomial time methods that we have developed. Our study, based upon simulating evolution under a wide range of model conditions, establishes that our new methods outperform both neighbor joining and the previous fast converging methods, returning very accurate large trees, when these other methods do poorly.


Subject(s)
Computational Biology , Genetic Techniques/statistics & numerical data , Phylogeny , Computer Simulation , Databases, Genetic , Models, Genetic , Models, Statistical , Software
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