ATP synthase: from single molecule to human bioenergetics

ATP synthase (FoF1) consists of an ATP-driven motor (F1) and a H+-driven motor (Fo), which rotate in opposite directions. FoF1 reconstituted into a lipid membrane is capable of ATP synthesis driven by H+ flux. As the basic structures of F1 (α3β3γδε) and Fo (ab2c10) are ubiquitous, stable thermophilic FoF1 (TFoF1) has been used to elucidate molecular mechanisms, while human F1Fo (HF1Fo) has been used to study biomedical significance. Among F1s, only thermophilic F1 (TF1) can be analyzed simultaneously by reconstitution, crystallography, mutagenesis and nanotechnology for torque-driven ATP synthesis using elastic coupling mechanisms. In contrast to the single operon of TFoF1, HFoF1 is encoded by both nuclear DNA with introns and mitochondrial DNA. The regulatory mechanism, tissue specificity and physiopathology of HFoF1 were elucidated by proteomics, RNA interference, cytoplasts and transgenic mice. The ATP synthesized daily by HFoF1 is in the order of tens of kilograms, and is primarily controlled by the brain in response to fluctuations in activity

Tumor-promoting functions of transforming growth factor-β in progression of cancer

Transforming growth factor-β (TGF-β) elicits both tumor-suppressive and tumor-promoting functions during cancer progression. Here, we describe the tumor-promoting functions of TGF-β and how these functions play a role in cancer progression. Normal epithelial cells undergo epithelial-mesenchymal transition (EMT) through the action of TGF-β, while treatment with TGF-β and fibroblast growth factor (FGF)-2 results in transdifferentiation into activated fibroblastic cells that are highly migratory, thereby facilitating cancer invasion and metastasis. TGF-β also induces EMT in tumor cells, which can be regulated by oncogenic and anti-oncogenic signals. In addition to EMT promotion, invasion and metastasis of cancer are facilitated by TGF-β through other mechanisms, such as regulation of cell survival, angiogenesis, and vascular integrity, and interaction with the tumor microenvironment. TGF-β also plays a critical role in regulating the cancer-initiating properties of certain types of cells, including glioma-initiating cells. These findings thus may be useful for establishing treatment strategies for advanced cancer by inhibiting TGF-β signaling

Selective Activation of p120ctn-Kaiso Signaling to Unlock Contact Inhibition of ARPE-19 Cells without Epithelial-Mesenchymal Transition

Contact-inhibition ubiquitously exists in non-transformed cells and explains the poor regenerative capacity of in vivo human retinal pigment epithelial cells (RPE) during aging, injury and diseases. RPE injury or degeneration may unlock mitotic block mediated by contact inhibition but may also promote epithelial-mesenchymal transition (EMT) contributing to retinal blindness. Herein, we confirmed that EMT ensued in post-confluent ARPE-19 cells when contact inhibition was disrupted with EGTA followed by addition of EGF and FGF-2 because of activation of canonical Wnt and Smad/ZEB signaling. In contrast, knockdown of p120-catenin (p120) unlocked such mitotic block by activating p120/Kaiso, but not activating canonical Wnt and Smad/ZEB signaling, thus avoiding EMT. Nuclear BrdU labeling was correlated with nuclear release of Kaiso through p120 nuclear translocation, which was associated with activation of RhoA-ROCK signaling, destabilization of microtubules. Prolonged p120 siRNA knockdown followed by withdrawal further expanded RPE into more compact monolayers with a normal phenotype and a higher density. This new strategy based on selective activation of p120/Kaiso but not Wnt/β-catenin signaling obviates the need of using single cells and the risk of EMT, and may be deployed to engineer surgical grafts containing RPE and other tissues

Structure of the ATP synthase catalytic complex (F(1)) from Escherichia coli in an autoinhibited conformation.

ATP synthase is a membrane-bound rotary motor enzyme that is critical for cellular energy metabolism in all kingdoms of life. Despite conservation of its basic structure and function, autoinhibition by one of its rotary stalk subunits occurs in bacteria and chloroplasts but not in mitochondria. The crystal structure of the ATP synthase catalytic complex (F(1)) from Escherichia coli described here reveals the structural basis for this inhibition. The C-terminal domain of subunit ɛ adopts a heretofore unknown, highly extended conformation that inserts deeply into the central cavity of the enzyme and engages both rotor and stator subunits in extensive contacts that are incompatible with functional rotation. As a result, the three catalytic subunits are stabilized in a set of conformations and rotational positions distinct from previous F(1) structures

Inferring microRNA and transcription factor regulatory networks in heterogeneous data

Background: Transcription factors (TFs) and microRNAs (miRNAs) are primary metazoan gene regulators. Regulatory mechanisms of the two main regulators are of great interest to biologists and may provide insights into the causes of diseases. However, the interplay between miRNAs and TFs in a regulatory network still remains unearthed. Currently, it is very difficult to study the regulatory mechanisms that involve both miRNAs and TFs in a biological lab. Even at data level, a network involving miRNAs, TFs and genes will be too complicated to achieve. Previous research has been mostly directed at inferring either miRNA or TF regulatory networks from data. However, networks involving a single type of regulator may not fully reveal the complex gene regulatory mechanisms, for instance, the way in which a TF indirectly regulates a gene via a miRNA. Results: We propose a framework to learn from heterogeneous data the three-component regulatory networks, with the presence of miRNAs, TFs, and mRNAs. This method firstly utilises Bayesian network structure learning to construct a regulatory network from multiple sources of data: gene expression profiles of miRNAs, TFs and mRNAs, target information based on sequence data, and sample categories. Then, in order to produce more meaningful results for further biological experimentation and research, the method searches the learnt network to identify the interplay between miRNAs and TFs and applies a network motif finding algorithm to further infer the network. We apply the proposed framework to the data sets of epithelial-to-mesenchymal transition (EMT). The results elucidate the complex gene regulatory mechanism for EMT which involves both TFs and miRNAs. Several discovered interactions and molecular functions have been confirmed by literature. In addition, many other discovered interactions and bio-markers are of high statistical significance and thus can be good candidates for validation by experiments. Moreover, the results generated by our method are compact, involving a small number of interactions which have been proved highly relevant to EMT. Conclusions: We have designed a framework to infer gene regulatory networks involving both TFs and miRNAs from multiple sources of data, including gene expression data, target information, and sample categories. Results on the EMT data sets have shown that the proposed approach is able to produce compact and meaningful gene regulatory networks that are highly relevant to the biological conditions of the data sets. This framework has the potential for application to other heterogeneous datasets to reveal the complex gene regulatory relationships.Thuc D Le, Lin Liu, Bing Liu, Anna Tsykin, Gregory J Goodall, Kenji Satou and Jiuyong L