Expression of the CD44v2-10 isoform confers a metastatic phenotype: Importance of the heparan sulfate attachment site CD44v3

We expressed the full-length CD44v2-10 isoform in SKHep1 cells, a nonmetastatic human hepatocellular carcinoma cell line that does not express any endogenous CD44v isoforms. In SCID mice, expression of CD44v2-10 by SKHep1 cells had no effect on s.c. primary tumor development but caused pulmonary metastases in 41% (7 of 17) of animals compared with control SKHep1 cells (0 of 16; P < 0.01). CD44v2-10 expression by SKHep1 cells resulted in enhanced heparan sulfate (HS) attachment and an enhanced capacity to bind heparin-binding growth factors. Mutation of the v3 domain to prevent HS attachment and growth factor binding abolished the metastatic phenotype, demonstrating that HS modification of CD44v2-10 plays a critical role in the development of metastases in this model. However, in vitro proliferation, motility, and invasion were not altered by CD44v2-10 expression.

Targeting a complex transcriptome: The construction of the mouse full-length cDNA encyclopedia

We report the construction of the mouse full-length cDNA encyclopedia, the most extensive view of a complex transcriptome, on the basis of preparing and sequencing 246 libraries. Before cloning, cDNAs were enriched in full-length by Cap-Trapper, and in most cases, aggressively subtracted/normalized. We have produced 1,442,236 successful 3'-end sequences clustered into 171,144 groups, from which 60,770 clones were fully sequenced cDNAs annotated in the FANTOM-2 annotation. We have also produced 547,149 5' end reads, which clustered into 124,258 groups. Altogether, these cDNAs were further grouped in 70,000 transcriptional units (TU), which represent the best coverage of a transcriptome so far. By monitoring the extent of normalization/subtraction, we define the tentative equivalent coverage (TEC), which was estimated to be equivalent to >12,000,000 ESTs derived from standard libraries. High coverage explains discrepancies between the very large. numbers of clusters (and TUs) of this project, which also include non-protein-coding RNAs, and the lower gene number estimation of genome annotations. Altogether, S'-end clusters identify regions that are potential promoters for 8637 known genes and S'-end clusters suggest the presence of almost 63,000 transcriptional starting points. An estimate of the frequency of polyadenylation signals suggests that at least half of the singletons in the EST set represent real mRNAs. Clones accounting for about half of the predicted TUs await further sequencing. The continued high-discovery rate suggests that the task of transcriptome discovery is not yet complete.

Identification of putative noncoding RNAs among the RIKEN mouse full-length cDNA collection

With the sequencing and annotation of genomes and transcriptomes of several eukaryotes, the importance of noncoding RNA (ncRNA)-RNA molecules that are not translated to protein products-has become more evident. A subclass of ncRNA transcripts are encoded by highly regulated, multi-exon, transcriptional units, are processed like typical protein-coding mRNAs and are increasingly implicated in regulation of many cellular functions in eukaryotes. This study describes the identification of candidate functional ncRNAs from among the RIKEN mouse full-length cDNA collection, which contains 60,770 sequences, by using a systematic computational filtering approach. We initially searched for previously reported ncRNAs and found nine murine ncRNAs and homologs of several previously described nonmouse ncRNAs. Through our computational approach to filter artifact-free clones that lack protein coding potential, we extracted 4280 transcripts as the largest-candidate set. Many clones in the set had EST hits, potential CpG islands surrounding the transcription start sites, and homologies with the human genome. This implies that many candidates are indeed transcribed in a regulated manner. Our results demonstrate that ncRNAs are a major functional subclass of processed transcripts in mammals.

Functional expression and characterization of Eehinococcus granulosus thioredoxin peroxidase suggests a role in protection against oxidative damage

A full-length cDNA sequence coding for Echinococcus granulosus thioredoxin peroxidase (EgTPx) was isolated from a sheep strain protoscolex cDNA library by immunoscreening using a pool of sera from mice infected with oncospheres. EgTPx expressed as a fusion protein with glutathione S-transferase (GST) exhibited significant thiol-dependent peroxidase activity that protected plasmid DNA from damage by metal-catalyzed oxidation (MCO) in vitro. Furthermore, the suggested antioxidant role for EgTPx was reinforced in an in vivo assay, whereby its expression in BL21 bacterial cells markedly increased the tolerance and survival of the cells to high concentrations of H2O2 compared with controls. Immunolocalization studies revealed that EgTPx was specifically expressed in all tissues of the protoscolex and brood capsules. Higher intensity of labelling was detected in many, but not all, calcareous corpuscle cells in protoscoleces. The purified recombinant EgTPx protein was used to screen sera from heavily infected mice and patients with confirmed hydatid infection. Only a portion of the sera reacted positively with the EgTPx-GST fusion protein in Western blots, suggesting that EgTPx may form antibody-antigen complexes or that responses to the EgTPx antigen may be immunologically regulated. Recombinant EgTPx may prove useful for the screening of specific inhibitors that could serve as new drugs for treatment of hydatid disease. Moreover, given that TPx from different parasitic phyla were phylogenetically distant from host TPx molecules, the development of antiparasite TPx inhibitors that do not react with host TPx might be feasible. (C) 2003 Elsevier B.V. All rights reserved.

Cloning and functional expression of venom prothrombin activator protease from Pseudonaja textilis with whole blood procoagulant activity

The snake venom group C prothrombin activators contain a number of components that enhance the rate of prothrombin activation. The cloning and expression of full-length cDNA for one of these components, an activated factor X (factor Xa)-like protease from Pseudonaja textilis as well as the generation of functional chimeric constructs with procoagulant activity were described. The complete cDNA codes for a propeptide, light chain, activation peptide (AP) and heavy chain related in sequence to mammalian factor X. Efficient expression of the protease was achieved with constructs where the AP was deleted and the cleavage sites between the heavy and light chains modified, or where the AP was replaced with a peptide involved in insulin receptor processing. In human kidney cells (H293F) transfected with these constructs, up to 80% of the pro-form was processed to heavy and light chains. Binding of the protease to barium citrate and use of specific antibodies demonstrated that gamma-carboxylation of glutamic acid residues had occurred on the light chain in both cases, as observed in human factor Xa and the native P. textilis protease. The recombinant protease caused efficient coagulation of whole citrated blood and citrated plasma that was enhanced by the presence of Ca2+. This study identified the complete cDNA sequence of a factor Xa-like protease from P. textilis and demonstrated for the first time the expression of a recombinant form of P. textilis protease capable of blood coagulation.

Compartmentalized expression of kallikrein 4 (KLK4/hK4) isoforms in prostate cancer: nuclear, cytoplasmic and secreted forms

The prostate-specific antigen-related serine protease gene, kallikrein 4 (KLK4), is expressed in the prostate and, more importantly, overexpressed in prostate cancer. Several KLK4 mRNA splice variants have been reported, but it is still not clear which of these is most relevant to prostate cancer. Here we report that, in addition to the full-length KLK4 (KLK4-254) transcript, the exon 1 deleted KLK4 transcripts, in particular, the 5'-truncated KLK4-205 transcript, is expressed in prostate cancer. Using V5/His6 and green fluorescent protein (GFP) carboxy terminal tagged expression constructs and immunocytochemical approaches, we found that hK4-254 is cytoplasmically localized, while the N-terminal truncated hK4-205 is in the nucleus of transfected PC-3 prostate cancer cells. At the protein level, using anti-hK4 peptide antibodies specific to different regions of hK4-254 (N-terminal and C-terminal), we also demonstrated that endogenous hK4-254 (detected with the N-terminal antibody) is more intensely stained in malignant cells than in benign prostate cells, and is secreted into seminal fluid. In contrast, for the endogenous nuclear-localized N-terminal truncated hK4-205 form, there was less difference in staining intensity between benign and cancer glands. Thus, KLK4-254/hK4-254 may have utility as an immunohistochemical marker for prostate cancer. Our studies also indicate that the expression levels of the truncated KLK4 transcripts, but not KLK4-254, are regulated by androgens in LNCaP cells. Thus, these data demonstrate that there are two major isoforms of hK4 (KLK4-254/hK4-254 and KLK4-205/hK4-205) expressed in prostate cancer with different regulatory and expression profiles that imply both secreted and novel nuclear roles.

Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings

The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036). The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within- family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will allow the estimation of genetic variation for disease susceptibility and quantitative traits that is free from confounding with non-genetic factors and will allow partitioning of genetic variation into additive and non-additive components.

Experimental validation of the regulated expression of large numbers of non-coding RNAs from the mouse genome

Recent large-scale analyses of mainly full-length cDNA libraries generated from a variety of mouse tissues indicated that almost half of all representative cloned sequences did flat contain ail apparent protein-coding sequence, and were putatively derived from non-protein-coding RNA (ncRNA) genes. However, many of these clones were singletons and the majority were unspliced, raising the possibility that they may be derived from genomic DNA or unprocessed pre-rnRNA contamination during library construction, or alternatively represent nonspecific transcriptional noise. Here we Show, using reverse transcriptase-dependent PCR, microarray, and Northern blot analyses, that many of these clones were derived from genuine transcripts Of unknown function whose expression appears to be regulated. The ncRNA transcripts have larger exons and fewer introns than protein-coding transcripts. Analysis of the genomic landscape around these sequences indicates that some cDNA clones were produced not from terminal poly(A) tracts but internal priming sites within longer transcripts, only a minority of which is encompassed by known genes. A significant proportion of these transcripts exhibit tissue-specific expression patterns, as well as dynamic changes in their expression in macrophages following lipopolysaccharide Stimulation. Taken together, the data provide strong support for the conclusion that ncRNAs are an important, regulated component of the mammalian transcriptome.

Real-Time Gene-Expression Extraction with Fast Classification (FC) Networks

Fast Classification (FC) networks were inspired by a biologically plausible mechanism for short term memory where learning occurs instantaneously. Both weights and the topology for an FC network are mapped directly from the training samples by using a prescriptive training scheme. Only two presentations of the training data are required to train an FC network. Compared with iterative learning algorithms such as Back-propagation (which may require many hundreds of presentations of the training data), the training of FC networks is extremely fast and learning convergence is always guaranteed. Thus FC networks may be suitable for applications where real-time classification is needed. In this paper, the FC networks are applied for the real-time extraction of gene expressions for Chlamydia microarray data. Both the classification performance and learning time of the FC networks are compared with the Multi-Layer Proceptron (MLP) networks and support-vector-machines (SVM) in the same classification task. The FC networks are shown to have extremely fast learning time and comparable classification accuracy.