Upstream stimulatory factor‐2 mediates quercetin‐induced suppression of PAI‐1 gene expression in human endothelial cells

The polyphenol quercetin (Quer) represses expression of the cardiovascular disease risk factor plasminogen activator inhibitor‐1 (PAI‐1) in cultured endothelial cells (ECs). Transfection of PAI‐1 promoter‐luciferase reporter deletion constructs identified a 251‐bp fragment (nucleotides ?800 to ?549) responsive to Quer. Two E‐box motifs (CACGTG), at map positions ?691 (E‐box1) and ?575 (E‐box2), are platforms for occupancy by several members of the c‐MYC family of basic helix‐loop‐helix leucine zipper (bHLH‐LZ) proteins. Promoter truncation and electrophoretic mobility shift/supershift analyses identified upstream stimulatory factor (USF)‐1 and USF‐2 as E‐box1/E‐box2 binding factors. ECs co‐transfected with a 251 bp PAI‐1 promoter fragment containing the two E‐box motifs (p251/luc) and a USF‐2 expression vector (pUSF‐2/pcDNA) exhibited reduced luciferase activity versus p251/luc alone. Overexpression of USF‐2 decreased, while transfection of a dominant‐negative USF construct increased, EC growth consistent with the known anti‐proliferative properties of USF proteins. Quer‐induced decreases in PAI‐1 expression and reduced cell proliferation may contribute, at least in part, to the cardioprotective benefit associated with daily intake of polyphenols. J. Cell. Biochem. 111: 720–726, 2010. © 2010 Wiley‐Liss, Inc.     

Molecular dynamics simulation on the allosteric analysis of the c‐di‐GMP class I riboswitch induced by ligand binding

Riboswitches are RNA molecules that regulate gene expression using conformation change, affected by binding of small molecule ligands. Although a number of ligand‐bound aptamer complex structures have been solved, it is important to know ligand‐free conformations of the aptamers in order to understand the mechanism of specific binding by ligands. In this paper, we use dynamics simulations on a series of models to characterize the ligand‐free and ligand‐bound aptamer domain of the c‐di‐GMP class I (GEMM‐I) riboswitch. The results revealed that the ligand‐free aptamer has a stable state with a folded P2 and P3 helix, an unfolded P1 helix and open binding pocket. The first Mg ions binding to the aptamer is structurally favorable for the successive c‐di‐GMP binding. The P1 helix forms when c‐di‐GMP is successive bound. Three key junctions J1/2, J2/3 and J1/3 in the GEMM‐I riboswitch contributing to the formation of P1 helix have been found. The binding of the c‐di‐GMP ligand to the GEMM‐I riboswitch induces the riboswitch's regulation through the direct allosteric communication network in GEMM‐I riboswitch from the c‐di‐GMP binding sites in the J1/2 and J1/3 junctions to the P1 helix, the indirect ones from those in the J2/3 and P2 communicating to P1 helix via the J1/2 and J1/3 media.     

Bet‐hedging as a complex interaction among developmental instability,environmental heterogeneity,dispersal, and life‐history strategy

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet‐hedging. I used an individual‐based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life‐history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life‐history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet‐hedging, but not in a simple linear fashion. I found higher‐order interactions between life‐history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.     

Comparative genomics in the Amoebozoa clade

Amoeboid life forms can be found throughout the evolutionary tree. The greatest proportion of these life forms is found in the Amoebozoa clade, one of the six major eukaryote evolutionary branches. Despite its common origin this clade exhibits a wide diversity of lifestyles including free‐living and parasitic species and species with multicellular and multinucleate life stages. In this group, development, cooperation, and social behaviour can be studied in addition to traits common to unicellular organisms. To date, only a few Amoebozoa genomes have been sequenced completely, however a number of expressed sequence tags (ESTs) and complete and draft genomes have become available recently for several species that represent some of the major evolutionary lineages in this clade. This resource allows us to compare and analyse the evolutionary history and fate of branch‐specific genes if properly exploited. Despite the large evolutionary time scale since the emergence of the major groups the genomic organization in Amoebozoa has retained common features. The number of Amoebozoa‐specific genetic inventions seems to be rather small. The emergence of subgroups is accompanied by gene and domain losses and acquisitions of bacterial gene material. The sophisticated developmental cycles of Myxogastria and Dictyosteliida likely have a common origin and are deeply rooted in amoebozoan evolution. In this review we describe initial approaches to comparative genomics in Amoebozoa, summarize recent findings, and identify goals for further studies.