Solving the structure of Lgl2, a difficult blind test of unsupervised structure determination

LLGL2 Inhibits Ovarian Cancer Metastasis by Regulating Cytoskeleton Remodeling via ACTN1

Epithelial ovarian cancer is the most lethal gynecological malignant tumor. Although debulking surgery, chemotherapy, and PARP inhibitors have greatly improved survival, the prognosis for patients with advanced EOC without HRD is still poor. LLGL2, as a cell polarity factor, is involved in maintaining cell polarity and asymmetric cell division. In the study of zebrafish development, LLGL2 regulated the proliferation and migration of epidermal cells and the formation of cortical F-actin. However, the role of LLGL2 in ovarian cancer has not been described. Our study found, through bioinformatics analysis, that low expression of LLGL2 was significantly associated with a more advanced stage and a higher grade of EOC and a poorer survival of patients. Functional experiments that involved LLGL2 overexpression and knockdown showed that LLGL2 inhibited the migration and invasion abilities of ovarian cancer cells in vitro, without affecting their proliferation. LLGL2-overexpressing mice had fewer metastatic implant foci than the controls in vivo. Mechanistically, immunoprecipitation combined with mass spectrometry analysis suggested that LLGL2 regulated cytoskeletal remodeling by interacting with ACTN1. LLGL2 altered the intracellular localization and function of ACTN1 without changing its protein and mRNA levels. Collectively, we uncovered that LLGL2 impaired actin filament aggregation into bundles by interacting with ACTN1, which led to cytoskeleton remodeling and inhibition of the invasion and metastasis of ovarian cancer cells.

DNA methylation of Hugl-2 is a prognostic biomarker in kidney renal clear cell carcinoma

It has been reported that loss of Hugl-2 contributes to tumour formation and progression in vitro and in vivo. However, whether Hugl-2 levels decrease during kidney renal clear cell carcinoma (KIRC) and the mechanism involved remain unknown. This study aimed to investigate whether DNA methylation of Hugl-2 reduces its expression, leading to the progression and poor prognosis of KIRC. Hugl-2 methylation and mRNA expression and KIRC clinicopathological data were extracted from The Cancer Genome Atlas (TCGA), and relationships among these factors were analyzed using UALCAN, MethHC, Wanderer and LinkedOmics web tools. We found that Hugl-2 mRNA and protein levels were reduced in KIRC tissues. Moreover, Hugl-2 mRNA levels were related to tumour grade and overall survival, and Hugl-2 methylation was increased in KIRC. According to the results of methylation-specific PCR, KIRC cells had higher Hugl-2 DNA methylation levels than HKC cells. Moreover, Hugl-2 DNA methylation correlated negatively with Hugl-2 mRNA and was also related to the pathology and T stage of KIRC patients. KIRC patients with high Hugl-2 DNA methylation also had shorter overall survival. Additionally, methylation of cg08827674, a Hugl-2 probe, was related to pathologic stage, T stage, neoplasm histologic grade, serum calcium level without laterality, M stage, N stage, and ethnicity. Furthermore, treatment with the DNA methylation inhibitor decitabine resulted in upregulation of Hugl-2 mRNA and protein levels in KIRC cell lines. These results indicate that Hugl-2 DNA methylation may be both a prognostic marker and a therapeutic target in KIRC.

Characterization of the heavy metal binding properties of periplasmic metal uptake protein CLas-ZnuA2

Candidatus Liberibacter asiaticus (CLas), a phloem-limited unculturable Gram-negative bacterium, causes citrus greening disease.

Structural insights into the aPKC regulatory switch mechanism of the human cell polarity protein lethal giant larvae 2

Metazoan cell polarity is controlled by a set of highly conserved proteins. Lethal giant larvae (Lgl) functions in apical-basal polarity through phosphorylation-dependent interactions with several other proteins as well as the plasma membrane. Phosphorylation of Lgl by atypical protein kinase C (aPKC), a component of the partitioning-defective (Par) complex in epithelial cells, excludes Lgl from the apical membrane, a crucial step in the establishment of epithelial cell polarity. We present the crystal structures of human Lgl2 in both its unphosphorylated and aPKC-phosphorylated states. Lgl2 adopts a double β-propeller structure that is unchanged by aPKC phosphorylation of an unstructured loop in its second β-propeller, ruling out models of phosphorylation-dependent conformational change. We demonstrate that phosphorylation controls the direct binding of purified Lgl2 to negative phospholipids in vitro. We also show that a coil-helix transition of this region that is promoted by phosphatidylinositol 4,5-bisphosphate (PIP₂) is also phosphorylation-dependent, implying a highly effective phosphorylative switch for membrane association.

Unsupervised determination of protein crystal structures

Solving crystal structures of large biological macromolecules in the absence of experimental phase information, especially at low resolution, is a tedious problem prone to mistakes and overfitting. Due to errors stemming from poorly interpretable parts of the electron density map, human experience and intuition are imperative for building a correct atomistic model. For this reason, tools for automatic structure determination used nowadays require constant human supervision. Here we present a method that can overcome the difficulties; it greatly reduces or even eliminates human involvement in the solution process by working with ensembles of possible solutions. This approach can find solution of a higher quality than can humans and can solve difficult cases not amenable to other methods.

We present a method for automatic solution of protein crystal structures. The method proceeds with a single initial model obtained, for instance, by molecular replacement (MR). If a good-quality search model is not available, as often is the case with MR of distant homologs, our method first can automatically screen a large pool of poorly placed models and single out promising candidates for further processing if there are any. We demonstrate its utility by solving a set of synthetic cases in the 2.9- to 3.45-Å resolution.