Pathogenicity of Misfolded and Dimeric HLA-B27 Molecules

The association between HLA-B27 and the group of autoimmune inflammatory arthritic diseases, the spondyloarthropathies (SpAs) which include ankylosing spondylitis (AS) and Reactive Arthritis (ReA), has been well established and remains the strongest association between any HLA molecule and autoimmune disease. The mechanism behind this striking association remains elusive; however animal model and biochemical data suggest that HLA-B27 misfolding may be key to understanding its association with the SpAs. Recent investigations have focused on the unusual biochemical structures of HLA-B27 and their potential role in SpA pathogenesis. Here we discuss how these unusual biochemical structures may participate in cellular events leading to chronic inflammation and thus disease progression

A molecular map of mesenchymal tumors

Background Bone and soft tissue tumors represent a diverse group of neoplasms thought to derive from cells of the mesenchyme or neural crest. Histological diagnosis is challenging due to the poor or heterogenous differentiation of many tumors, resulting in uncertainty over prognosis and appropriate therapy. Results We have undertaken a broad and comprehensive study of the gene expression profile of 96 tumors with representatives of all mesenchymal tissues, including several problem diagnostic groups. Using machine learning methods adapted to this problem we identify molecular fingerprints for most tumors, which are pathognomonic (decisive) and biologically revealing. Conclusion We demonstrate the utility of gene expression profiles and machine learning for a complex clinical problem, and identify putative origins for certain mesenchymal tumor

Measuring Synthesis and Degradation of MHC Class I Molecules

Major histocompatibility complex (MHC) class I molecules function to present pathogen-derived peptides to cytotoxic T cells or act as ligands for Natural Killer cells, thus alerting the immune system to the presence of invading pathogens. Furthermore MHC class I molecules can be strongly associated with autoimmune diseases. Therefore understanding not only the biosynthesis and the degradation pathways of MHC class I molecules has become important in determining their role in pathogen and autoimmune-related diseases. Here we describe how using epitope-tagged MHC class I molecules can aid in the analysis of MHC class I molecule biosynthesis and degradation and also complement studies using conventional conformationally specific antibodies. Coupled together with pharmacological manipulation which can target both biosynthetic and degradative pathways, this offers a powerful tool in analyzing MHC class I molecules

Operon Conservation and the Evolution of trans-Splicing in the Phylum Nematoda

The nematode Caenorhabditis elegans is unique among model animals in that many of its genes are cotranscribed as polycistronic pre-mRNAs from operons. The mechanism by which these operonic transcripts are resolved into mature mRNAs includes trans-splicing to a family of SL2-like spliced leader exons. SL2-like spliced leaders are distinct from SL1, the major spliced leader in C. elegans and other nematode species. We surveyed five additional nematode species, representing three of the five major clades of the phylum Nematoda, for the presence of operons and the use of trans-spliced leaders in resolution of polycistronic pre-mRNAs. Conserved operons were found in Pristionchus pacificus, Nippostrongylus brasiliensis, Strongyloides ratti, Brugia malayi, and Ascaris suum. In nematodes closely related to the rhabditine C. elegans, a related family of SL2-like spliced leaders is used for operonic transcript resolution. However, in the tylenchine S. ratti operonic transcripts are resolved using a family of spliced leaders related to SL1. Non-operonic genes in S. ratti may also receive these SL1 variants. In the spirurine nematodes B. malayi and A. suum operonic transcripts are resolved using SL1. Mapping these phenotypes onto the robust molecular phylogeny for the Nematoda suggests that operons evolved before SL2-like spliced leaders, which are an evolutionary invention of the rhabditine lineage

Making sense of EST sequences by CLOBBing them

Background Expressed sequence tags (ESTs) are single pass reads from randomly selected cDNA clones. They provide a highly cost-effective method to access and identify expressed genes. However, they are often prone to sequencing errors and typically define incomplete transcripts. To increase the amount of information obtainable from ESTs and reduce sequencing errors, it is necessary to cluster ESTs into groups sharing significant sequence similarity. Results As part of our ongoing EST programs investigating 'orphan' genomes, we have developed a clustering algorithm, CLOBB (Cl uster o n the b asis of B LAST similarity) to identify and cluster ESTs. CLOBB may be used incrementally, preserving original cluster designations. It tracks cluster-specific events such as merging, identifies 'superclusters' of related clusters and avoids the expansion of chimeric clusters. Based on the Perl scripting language, CLOBB is highly portable relying only on a local installation of NCBI's freely available BLAST executable and can be usefully applied to > 95 % of the current EST datasets. Analysis of the Danio rerio EST dataset demonstrates that CLOBB compares favourably with two less portable systems, UniGene and TIGR Gene Indices. Conclusions CLOBB provides a highly portable EST clustering solution and is freely downloaded from: http://www.nematodes.org/CLOB

200 000 nematode expressed sequence tags on the Net

Expressed sequence tags (ESTs) are single-pass sequence reads made from randomly selected cDNA clones, which represent the expressed genes of an organism. EST analysis is an efficient and cost-effective method for sampling the genes expressed by an organism or tissue. ESTs have been a focus of eukaryotic parasite genome initiatives for several years 1 (see the Parasite Genome web server at http://www.ebi.ac.uk/parasites/parasite-genome.html), and parasitic organism ESTs make up a significant portion of the dbEST subsection of GenBank 2 , 3 . EST data sets can be mined for useful or interesting content using standard similarity-based search tools such as BLAST. In the field of molecular parasitology, such approaches have led to the discovery of many new potential drug targets and vaccine candidates. However, EST data sets also contain important additional types of information