Sperm Associated Antigen 9 Plays an Important Role in Bladder Transitional Cell Carcinoma

Background

Majority of bladder cancer deaths are caused due to transitional cell carcinoma (TCC) which is the most prevalent and chemoresistant malignancy of urinary bladder. Therefore, we analyzed the role of Sperm associated antigen 9 (SPAG9) in bladder TCC.

Methodology and Findings

We examined SPAG9 expression and humoral response in 125 bladder TCC patients. Four bladder cancer cell lines were assessed for SPAG9 expression. In addition, we investigated the effect of SPAG9 ablation on cellular proliferation, cell cycle, migration and invasion in UM-UC-3 bladder cancer cells by employing gene silencing approach. Our SPAG9 gene and protein expression analysis revealed SPAG9 expression in 81% of bladder TCC tissue specimens. High SPAG9 expression (>60% SPAG9 positive cells) was found to be significantly associated with superficial non-muscle invasive stage (P = 0.042) and low grade tumors (P = 0.002) suggesting SPAG9 putative role in early spread and tumorigenesis. Humoral response against SPAG9 was observed in 95% of patients found positive for SPAG9 expression. All four bladder cancer cell lines revealed SPAG9 expression. In addition, SPAG9 gene silencing in UM-UC-3 cells resulted in induction of G₀–G₁ arrest characterized by up-regulation of p16 and p21 and consequent down-regulation of cyclin E, cyclin D and cyclin B, CDK4 and CDK1. Further, SPAG9 gene silencing also resulted in reduction in cellular growth, and migration and invasion ability of cancer cells in vitro.

Conclusions

Collectively, our data in clinical specimens indicated that SPAG9 is potential biomarker and therapeutic target for bladder TCC.     

Ligand binding to cytochrome P450 3A4 in phospholipid bilayer nanodiscs: the effect of model membranes

The membrane-bound protein cytochrome P450 3A4 (CYP3A4) is a major drug-metabolizing enzyme. Most studies of ligand binding by CYP3A4 are currently carried out in solution, in the absence of a model membrane. Therefore, there is little information concerning the membrane effects on CYP3A4 ligand binding behavior. Phospholipid bilayer Nanodiscs are a novel model membrane system derived from high density lipoprotein particles, whose stability, monodispersity, and consistency are ensured by their self-assembly. We explore the energetics of four ligands (6-(p-toluidino)-2-naphthalenesulfonic acid (TNS), alpha-naphthoflavone (ANF), miconazole, and bromocriptine) binding to CYP3A4 incorporated into Nanodiscs. Ligand binding to Nanodiscs was monitored by a combination of environment-sensitive ligand fluorescence and ligand-induced shifts in the fluorescence of tryptophan residues present in the scaffold proteins of Nanodiscs; binding to the CYP3A4 active site was monitored by ligand-induced shifts in the heme Soret band absorbance. The dissociation constants for binding to the active site in CYP3A4-Nanodiscs were 4.0 microm for TNS, 5.8 microm for ANF, 0.45 microm for miconazole, and 0.45 microm for bromocriptine. These values are for CYP3A4 incorporated into a lipid bilayer and are therefore presumably more biologically relevant that those measured using CYP3A4 in solution. In some cases, affinity measurements using CYP3A4 in Nanodiscs differ significantly from solution values. We also studied the equilibrium between ligand binding to CYP3A4 and to the membrane. TNS showed no marked preference for either environment; ANF preferentially bound to the membrane, and miconazole and bromocriptine preferentially bound to the CYP3A4 active site.     

Growth enhancement of soybean (Glycine max) upon exclusion of UV-B and UV-B/A components of solar radiation: characterization of photosynthetic parameters in leaves

Exclusion of UV (280–380 nm) radiation from the solar spectrum can be an important tool to assess the impact of ambient UV radiation on plant growth and performance of crop plants. The effect of exclusion of UV-B and UV-A from solar radiation on the growth and photosynthetic components in soybean (Glycine max) leaves were investigated. Exclusion of solar UV-B and UV-B/A radiation, enhanced the fresh weight, dry weight, leaf area as well as induced a dramatic increase in plant height, which reflected a net increase in biomass. Dry weight increase per unit leaf area was quite significant upon both UV-B and UV-B/A exclusion from the solar spectrum. However, no changes in chlorophyll a and b contents were observed by exclusion of solar UV radiation but the content of carotenoids was significantly (34–46%) lowered. Analysis of chlorophyll (Chl) fluorescence transient parameters of leaf segments suggested no change in the F _v/F _m value due to UV-B or UV-B/A exclusion. Only a small reduction in photo-oxidized signal I (P700⁺)/unit Chl was noted. Interestingly the total soluble protein content per unit leaf area increased by 18% in UV-B/A and 40% in UV-B excluded samples, suggesting a unique upregulation of biosynthesis and accumulation of biomass. Solar UV radiation thus seems to primarily affect the photomorphogenic regulatory system that leads to an enhanced growth of leaves and an enhanced rate of net photosynthesis in soybean, a crop plant of economic importance. The presence of ultra-violet components in sunlight seems to arrest carbon sequestration in plants. An erratum to this article can be found at     

Identification and structural characterization of heme binding in a novel dye-decolorizing peroxidase, TyrA

TyrA is a member of the dye-decolorizing peroxidase (DyP) family, a new family of heme-dependent peroxidase recently identified in fungi and bacteria. Here, we report the crystal structure of TyrA in complex with iron protoporphyrin (IX) at 2.3 A. TyrA is a dimer, with each monomer exhibiting a two-domain, alpha/beta ferredoxin-like fold. Both domains contribute to the heme-binding site. Co-crystallization in the presence of an excess of iron protoporphyrin (IX) chloride allowed for the unambiguous location of the active site and the specific residues involved in heme binding. The structure reveals a Fe-His-Asp triad essential for heme positioning, as well as a novel conformation of one of the heme propionate moieties compared to plant peroxidases. Structural comparison to the canonical DyP family member, DyP from Thanatephorus cucumeris (Dec 1), demonstrates conservation of this novel heme conformation, as well as residues important for heme binding. Structural comparisons with representative members from all classes of the plant, bacterial, and fungal peroxidase superfamily demonstrate that TyrA, and by extension the DyP family, adopts a fold different from all other structurally characterized heme peroxidases. We propose that a new superfamily be added to the peroxidase classification scheme to encompass the DyP family of heme peroxidases.     

Applications of phospholipid bilayer nanodiscs in the study of membranes and membrane proteins

Phospholipid bilayer Nanodiscs are novel model membranes derived from high-density lipoprotein particles and have proven to be useful in studies of membrane proteins. Membrane protein enzymology has been hampered by the inherent insolubility of membrane proteins in aqueous environments and has necessitated the use of model membranes such as liposomes and detergent-stabilized micelles. Current model membranes display a polydisperse particle size distribution and can suffer from problems of inconsistency and instability. It is also unclear how well they mimic biological lipid bilayers. In contrast, Nanodiscs, the particle size of which is constrained by a coat of scaffold proteins, are relatively monodisperse, stable model membranes with a "nativelike" lipid bilayer. Nanodiscs have already been used to study a variety of membrane proteins, including cytochrome P450s, seven-transmembrane proteins, and bacterial chemoreceptors. These proteins are simultaneously monomerized, solubilized, and incorporated into the well-defined membrane environment provided by Nanodiscs. Nanodiscs may also provide useful insights into the thermodynamics and biophysics of biological membranes and binding of small molecules to membranes.     

Pyrazinamide drug resistance in RpsA mutant (∆438A) of Mycobacterium tuberculosis: Dynamics of essential motions and free-energy landscape analysis

Pyrazinamide is an essential first-line antitubercular drug which plays pivotal role in tuberculosis treatment. It is a prodrug that requires amide hydrolysis by mycobacterial pyrazinamidase enzyme for conversion into pyrazinoic acid (POA). POA is known to target ribosomal protein S1 (RpsA), aspartate decarboxylase (PanD), and some other mycobacterial proteins. Spontaneous chromosomal mutations in RpsA have been reported for phenotypic resistance against pyrazinamide. We have constructed and validated 3D models of the native and Δ438A mutant form of RpsA protein. RpsA protein variants were then docked to POA and long range molecular dynamics simulations were carried out. Per residue binding free-energy calculations, free-energy landscape analysis, and essential dynamics analysis were performed to outline the mechanism underlying the high-level PZA resistance conferred by the most frequently occurring deletion mutant of RpsA. Our study revealed the conformational modulation of POA binding site due to the disruptive collective modes of motions and increased conformational flexibility in the mutant than the native form. Residue wise MMPBSA decomposition and protein-drug interaction pattern revealed the difference of energetically favorable binding site in the wild-type (WT) protein in comparison with the mutant. Analysis of size and shape of minimal energy landscape area delineated higher stability of the WT complex than the mutant form. Our study provides mechanistic insights into pyrazinamide resistance in Δ438A RpsA mutant, and the results arising out of this study will pave way for design of novel and effective inhibitors targeting the resistant strains of Mycobacterium tuberculosis.     

Unraveling the regulatory connections between two controllers of breast cancer cell fate

Estrogen receptor alpha (ERα) expression is critical for breast cancer classification, high ERα expression being associated with better prognosis. ERα levels strongly correlate with that of GATA binding protein 3 (GATA3), a major regulator of ERα expression. However, the mechanistic details of ERα–GATA3 regulation remain incompletely understood. Here we combine mathematical modeling with perturbation experiments to unravel the nature of regulatory connections in the ERα–GATA3 network. Through cell population-average, single-cell and single-nucleus measurements, we show that the cross-regulation between ERα and GATA3 amounts to overall negative feedback. Further, mathematical modeling reveals that GATA3 positively regulates its own expression and that ERα autoregulation is most likely absent. Lastly, we show that the two cross-regulatory connections in the ERα–GATA3 negative feedback network decrease the noise in ERα or GATA3 expression. This may ensure robust cell fate maintenance in the face of intracellular and environmental fluctuations, contributing to tissue homeostasis in normal conditions, but also to the maintenance of pathogenic states during cancer progression.     

A fast NMR method for resonance assignments: application to metabolomics

We present a new method for rapid NMR data acquisition and assignments applicable to unlabeled (¹²C) or ¹³C-labeled biomolecules/organic molecules in general and metabolomics in particular. The method involves the acquisition of three two dimensional (2D) NMR spectra simultaneously using a dual receiver system. The three spectra, namely: (1) G-matrix Fourier transform (GFT) (3,2)D [¹³C, ¹H] HSQC–TOCSY, (2) 2D ¹H–¹H TOCSY and (3) 2D ¹³C–¹H HETCOR are acquired in a single experiment and provide mutually complementary information to completely assign individual metabolites in a mixture. The GFT (3,2)D [¹³C, ¹H] HSQC–TOCSY provides 3D correlations in a reduced dimensionality manner facilitating high resolution and unambiguous assignments. The experiments were applied for complete ¹H and ¹³C assignments of a mixture of 21 unlabeled metabolites corresponding to a medium used in assisted reproductive technology. Taken together, the experiments provide time gain of order of magnitudes compared to the conventional data acquisition methods and can be combined with other fast NMR techniques such as non-uniform sampling and covariance spectroscopy. This provides new avenues for using multiple receivers and projection NMR techniques for high-throughput approaches in metabolomics.     

Content-based histopathology image retrieval using CometCloud

Background

The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance.

Results

The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers.

Conclusions

In this paper, we present a set of newly developed CBIR algorithms and validate them using two different pathology applications, which are regularly evaluated in the practice of pathology. Comparative experimental results demonstrate excellent performance throughout the course of a set of systematic studies. Additionally, we present and evaluate a framework to enable the execution of these algorithms across distributed resources. We show how parallel searching of content-wise similar images in the dataset significantly reduces the overall computational time to ensure the practical utility of the proposed CBIR algorithms.