Cissus sicyoides C. Linnaeus (Vitaceae), a Potential Exotic Pest in the Lower Rio Grande Valley, Texas

English:Cissus sicyoides C. Linnaeus, a perennial vine native to tropical Mexico, Central America, and the Caribbean, has recently been rediscovered in the Lower Rio Grande Valley,Texas. A dense population of this exotic species has been located in a brushy area along a canal network and in two adjacent citrus groves near Weslaco. This species produces a dense mantle that covers other vegetation, appears to be invasive, and may pose a potential weed problem in citrus in the Lower Rio Grande Valley. Spanish: Cissus sicyoides C. Linnaeus, una enredadera perene nativa de los trópicos de México, América Central y el Caribe, se ha redescubierto recientemente en el Bajo Valle del Río Grande,Texas. Una población densa de esta especie exótica ha sido localizada en una área de matorral a lo largo de una red de canales y en dos huertas adyacentes de cítricos cercanas a Weslaco. Esta especie produce un manto denso que cubre otra vegetación, es invasiva y puede tener el potencial de convertirse en una maleza problemática para el cultivo de cítricos en el Bajo Valle del Río Grande en Texas

Sequentiality and processivity of nuclear receptor coregulators in regulation of target gene expression

A series of data has accumulated over the past five years that raises questions about our current understanding of the transcriptional process and its regulation. Following the discovery of coactivators for nuclear receptors (NRs), a large number of these molecules have been reported in the literature. This perspective will summarize some opinions on the significance of this large number of factors

Recovering Protein-Protein and Domain-Domain Interactions from Aggregation of IP-MS Proteomics of Coregulator Complexes

Coregulator proteins (CoRegs) are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP) followed by mass spectrometry (MS) applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/

miRNA Regulatory Circuits in ES Cells Differentiation: A Chemical Kinetics Modeling Approach

MicroRNAs (miRNAs) play an important role in gene regulation for Embryonic Stem cells (ES cells), where they either down-regulate target mRNA genes by degradation or repress protein expression of these mRNA genes by inhibiting translation. Well known tables TargetScan and miRanda may predict quite long lists of potential miRNAs inhibitors for each mRNA gene, and one of our goals was to strongly narrow down the list of mRNA targets potentially repressed by a known large list of 400 miRNAs. Our paper focuses on algorithmic analysis of ES cells microarray data to reliably detect repressive interactions between miRNAs and mRNAs. We model, by chemical kinetics equations, the interaction architectures implementing the two basic silencing processes of miRNAs, namely “direct degradation” or “translation inhibition” of targeted mRNAs. For each pair (M,G) of potentially interacting miRMA gene M and mRNA gene G, we parameterize our associated kinetic equations by optimizing their fit with microarray data. When this fit is high enough, we validate the pair (M,G) as a highly probable repressive interaction. This approach leads to the computation of a highly selective and drastically reduced list of repressive pairs (M,G) involved in ES cells differentiation

The effects of luteinizing hormone ablation/replacement versus steroid ablation/replacement on gene expression in the primate corpus luteum

This study was designed to provide a genome-wide analysis of the effects of luteinizing hormone (LH) versus steroid ablation/replacement on gene expression in the developed corpus luteum (CL) in primates during the menstrual cycle. On Days 9–11 of the luteal phase, female rhesus monkeys were left untreated (control) or received a GnRH antagonist Antide (A), A + LH, A + LH + the 3β-hydroxysteroid dehydrogenase inhibitor Trilostane (TRL) or A + LH + TRL + a progestin R5020. On Day 12 of the luteal phase, CL were removed and samples of RNA from individual CL were hybridized to Affymetrix™ rhesus macaque total genome microarrays. The greatest number of altered transcripts was associated with the ablation/replacement of LH, while steroid ablation/progestin replacement affected fewer transcripts. Replacement of LH during Antide treatment restored the expression of most transcripts to control levels. Validation of a subset of transcripts revealed that the expression patterns were similar between microarray and real-time PCR. Analyses of protein levels were subsequently determined for two transcripts. This is the first genome-wide analysis of LH and steroid regulation of gene transcription in the developed primate CL. Further analysis of novel transcripts identified in this data set can clarify the relative role for LH and steroids in CL maintenance and luteolysis

Human ADA3 regulates RARα transcriptional activity through direct contact between LxxLL motifs and the receptor coactivator pocket

The alternation/deficiency in activation-3 (ADA3) is an essential component of the human p300/CBP-associated factor (PCAF) and yeast Spt-Ada-Gcn5-acetyltransferase (SAGA) histone acetyltransferase complexes. These complexes facilitate transactivation of target genes by association with transcription factors and modification of local chromatin structure. It is known that the yeast ADA3 is required for nuclear receptor (NR)-mediated transactivation in yeast cells; however, the role of mammalian ADA3 in NR signaling remains elusive. In this study, we have investigated how the human (h) ADA3 regulates retinoic acid receptor (RAR) α-mediated transactivation. We show that hADA3 interacts directly with RARα in a hormone-dependent manner and this interaction contributes to RARα transactivation. Intriguingly, this interaction involves classical LxxLL motifs in hADA3, as demonstrated by both ‘loss’ and ‘gain’ of function mutations, as well as a functional coactivator pocket of the receptor. Additionally, we show that hADA3 associates with RARα target gene promoter in a hormone-dependent manner and ADA3 knockdown impairs RARβ2 expression. Furthermore, a structural model was established to illustrate an interaction network within the ADA3/RARα complex. These results suggest that hADA3 is a bona fide transcriptional coactivator for RARα, acting through a conserved mechanism involving direct contacts between NR boxes and the receptor’s co-activator pocket

Androgen receptor footprint on the way to prostate cancer progression

The prostate gland is exquisitely sensitive to androgen receptor (AR) signaling. AR signaling is obligatory for prostate development and changes in AR levels, its ligands or shifts in AR mode of action are reflected in the physiology of the prostate. The AR is intimately linked to prostate cancer biology through the regulation of epithelial proliferation, suppression of apoptosis and the development of castration-resistant disease. Thus, AR is the primary therapeutic target in various prostate diseases such as BPH and cancer. Although some tumors lose AR expression, most retain the AR and have elevated levels and/or shifts in activity that are required for tumor progression and metastasis. New AR inhibitors currently in clinical trials with higher receptor affinity and specificity may improve prostate cancer patient outcome. Several events play an important role in initiation, primary tumor development and metastatic spread. Androgen receptor activity and promoter specificity change due to altered coregulator expression. Changes in epigenetic surveillance alter the AR cistrome. Both systemic and local inflammation increases with PCa progression affecting AR levels, activity, and requirement for ligand. Our current understanding of AR biology suggest that global androgen suppression may drive the development of castration-resistant disease and therefore the question remains: Does effective inhibition of AR activity mark the end of the road for PCa or only a sharp turn toward a different type of malignancy

A Linear Framework for Time-Scale Separation in Nonlinear Biochemical Systems

Cellular physiology is implemented by formidably complex biochemical systems with highly nonlinear dynamics, presenting a challenge for both experiment and theory. Time-scale separation has been one of the few theoretical methods for distilling general principles from such complexity. It has provided essential insights in areas such as enzyme kinetics, allosteric enzymes, G-protein coupled receptors, ion channels, gene regulation and post-translational modification. In each case, internal molecular complexity has been eliminated, leading to rational algebraic expressions among the remaining components. This has yielded familiar formulas such as those of Michaelis-Menten in enzyme kinetics, Monod-Wyman-Changeux in allostery and Ackers-Johnson-Shea in gene regulation. Here we show that these calculations are all instances of a single graph-theoretic framework. Despite the biochemical nonlinearity to which it is applied, this framework is entirely linear, yet requires no approximation. We show that elimination of internal complexity is feasible when the relevant graph is strongly connected. The framework provides a new methodology with the potential to subdue combinatorial explosion at the molecular level