Construction and Characterization of a Magnaporthe grisea Bacterial Artificial Chromosome Library

Diaz-Perez, S. V., Crouch, V. W., and Orbach, M. J. 1996. Construction and characterization of a Magnaporthe grisea bacterial artificial chromosome library. Fungal Genet. Biol. 20, 280-288. A bacterial artificial chromosome (BAC) library of Magnaporthe grisea containing 4128 clones with an average insert size of 66-kb has been constructed. This library represents seven genome equivalents of M. grisea and has been demonstrated to be representative of the genome by screening for the presence of several single-copy genes and DNA markers. The utility of the library for use in map-based cloning projects was shown by the spanning of a nine-cosmid, 207-kb DNA contig with only 3 BAC clones. In addition, using a lys1-3 auxotroph, we have shown that BAC clones at least 113 kb can be transformed into M. grisea to screen for complementation of mutations. Thus, BACs isolated in chromosome walks can be rapidly screened for the presence of the sought after gene. The ease of construction of BAC libraries and of isolation and manipulation of BAC clones makes the BAC system an ideal one for physical analyses of fungal genomes.     

Biomarker Development for the Clinical Activity of the mTOR Inhibitor Everolimus (RAD001): Processes,Limitations, and Further Proposals

The mTOR inhibitor everolimus (RAD001, Afinitor) is an orally active anticancer agent. Everolimus demonstrates growth-inhibitory activity against a broad range of tumor cell histotypes in vitro and has the capacity to retard tumor growth in preclinical tumor models in vivo through mechanisms directed against both the tumor cell and the solid tumor stroma components. These properties have rendered it to be a clinically active drug, with subsequent registration in renal cell carcinoma (Motzer et al. [2008]. Lancet 372, 449–456) as well as showing strong potential as a combination partner (André F et al. [2008]. J Clin Oncol 26. Abstract 1003). Although everolimus has a high specificity for its molecular target, the ubiquitous nature of mTOR and the multifactorial influence that mTOR signaling has on cell physiology have made studies difficult on the identification and validation of a biomarker set to predict and monitor drug sensitivity for clinical use. In this review, a summary of the preclinical and clinical data relevant to biomarker development for everolimus is presented, and the advantages and problems of current biomarkers are reviewed. In addition, alternative approaches to biomarker development are proposed on the basis of examples of a combination of markers and functional noninvasive imaging. In particular, we show how basal levels of pAKT and pS6 together could, in principle, be used to stratify patients for likely response to an mTOR inhibitor.     

Uric acid is a strong independent predictor of renal dysfunction in patients with rheumatoid arthritis

Introduction  

Recent evidence suggests that uric acid (UA), regardless of crystal deposition, may play a direct pathogenic role in renal disease. We have shown that UA is an independent predictor of hypertension and cardiovascular disease (CVD), and that CVD risk factors associate with renal dysfunction, in patients with rheumatoid arthritis (RA). In this study we investigated whether UA associates with renal dysfunction in patients with RA and whether such an association is independent or mediated through other comorbidities or risk factors for renal impairment.     

Physiological responses to folate overproduction in <Emphasis Type="Italic">Lactobacillus plantarum</Emphasis> WCFS1

Background  

Using a functional genomics approach we addressed the impact of folate overproduction on metabolite formation and gene expression in Lactobacillus plantarum WCFS1. We focused specifically on the mechanism that reduces growth rates in folate-overproducing cells.     

Hypercholesterolemia boosts joint destruction in chronic arthritis. An experimental model aggravated by foam macrophage infiltration

Objective

The aim of this study was to determine whether hypercholesterolemia increases articular damage in a rabbit model of chronic arthritis.

Methods

Hypercholesterolemia was induced in 18 rabbits by administrating a high-fat diet (HFD). Fifteen rabbits were fed normal chow as controls. Chronic antigen-induced arthritis (AIA) was induced in half of the HFD and control rabbits, previously immunized, by intra-articular injections of ovalbumin. After sacrifice, lipid and systemic inflammation markers were analyzed in blood serum. Synovium was analyzed by Krenn score, multinucleated cell counting, immunohistochemistry of RAM11 and CD31, and TNF-α and macrophage chemoattractant protein-1 (MCP-1) gene expression. Active bone resorption was assessed by protein expression of receptor activator of nuclear factor kappa-B ligand (RANKL), osteoprotegerin (OPG) and quantification of cathepsin K, contact surface and the invasive area of pannus into bone.

Results

Rabbits receiving the HFD showed higher total serum cholesterol, HDL, triglycerides and CRP levels than rabbits fed a normal diet. Synovitis score was increased in HFD, and particularly in AIA and AIA + HFD groups. AIA + HFD synovium was characterized by a massive infiltration of RAM11+ cells, higher presence of multinucleated foam cells and bigger vascularization than AIA. Cathepsin K+ osteoclasts and the contact surface of bone resorbing pannus were also increased in rabbits with AIA + HFD compared with AIA alone. Synovial TNF-α and MCP-1 gene expression was increased in AIA and HFD rabbits compared with healthy animals. RANKL protein expression in AIA and AIA + HFD groups was higher compared with either HFD or normal groups.

Conclusions

This experimental model demonstrates that hypercholesterolemia increments joint tissue damage in chronic arthritis, with foam macrophages being key players in this process.     

High-resolution amplified fragment length polymorphism typing of Lactococcus lactis strains enables identification of genetic markers for subspecies-related phenotypes

A high-resolution amplified fragment length polymorphism (AFLP) methodology was developed to achieve the delineation of closely related Lactococcus lactis strains. The differentiation depth of 24 enzyme-primer-nucleotide combinations was experimentally evaluated to maximize the number of polymorphisms. The resolution depth was confirmed by performing diversity analysis on 82 L. lactis strains, including both closely and distantly related strains with dairy and nondairy origins. Strains clustered into two main genomic lineages of L. lactis subsp. lactis and L. lactis subsp. cremoris type-strain-like genotypes and a third novel genomic lineage rooted from the L. lactis subsp. lactis genomic lineage. Cluster differentiation was highly correlated with small-subunit rRNA homology and multilocus sequence analysis (MLSA) studies. Additionally, the selected enzyme-primer combination generated L. lactis subsp. cremoris phenotype-specific fragments irrespective of the genotype. These phenotype-specific markers allowed the differentiation of L. lactis subsp. lactis phenotype from L. lactis subsp. cremoris phenotype strains within the same L. lactis subsp. cremoris type-strain-like genomic lineage, illustrating the potential of AFLP for the generation of phenotype-linked genetic markers.     

Impacts of yeast metabolic network structure on enzyme evolution

A comment on D Vitkup, P Kharchenko and A Wagner: Influence of metabolic network structure and function on enzyme evolution. Genome Biol 2006, 7:R39.     

The Deuterator: software for the determination of backbone amide deuterium levels from H/D exchange MS data

Background  

The combination of mass spectrometry and solution phase amide hydrogen/deuterium exchange (H/D exchange) experiments is an effective method for characterizing protein dynamics, and protein-protein or protein-ligand interactions. Despite methodological advancements and improvements in instrumentation and automation, data analysis and display remains a tedious process. The factors that contribute to this bottleneck are the large number of data points produced in a typical experiment, each requiring manual curation and validation, and then calculation of the level of backbone amide exchange. Tools have become available that address some of these issues, but lack sufficient integration, functionality, and accessibility required to address the needs of the H/D exchange community. To date there is no software for the analysis of H/D exchange data that comprehensively addresses these issues.