Methods and platforms for the quantification of splice variants' expression

Translation of human tissue factor pathway inhibitor-β mRNA is controlled by alternative splicing within the 5' untranslated region

OBJECTIVE

Tissue factor pathway inhibitor (TFPI) blocks the initiation of coagulation by inhibiting TF-activated factor VII, activated factor X, and early prothrombinase. Humans produce two 3' splice variants, TFPIα and TFPIβ, which are differentially expressed in endothelial cells and platelets and possess distinct structural features affecting their inhibitory function. TFPI also undergoes alternative splicing of exon 2 within its 5' untranslated region. The role of exon 2 splicing in translational regulation of human TFPI isoform expression is investigated.

APPROACH AND RESULTS

Exon 2 splicing occurs in TFPIα and TFPIβ transcripts. Human tissue mRNA analysis uncovered a wide variability of exon 2 expression. Polysome analysis revealed a repressive effect of exon 2 on TFPIβ translation but not on TFPIα. Luciferase reporter assays further exposed strong translational repression of TFPIβ (90%) but not TFPIα. Use of a Morpholino to remove exon 2 from TFPI mRNA increased cell surface expression of endogenous TFPIβ. Exon 2 also repressed luciferase production (80% to 90%) when paired with the β-actin 3' untranslated region, suggesting that it is a general translational negative element whose effects are overcome by the TFPIα 3' untranslated region.

CONCLUSIONS

Exon 2 is a molecular switch that prevents translation of TFPIβ. This is the first demonstration of a 5' untranslated region alternative splicing event that alters translation of isoforms produced via independent 3' splicing events within the same gene. Therefore, it represents a previously unrecognized mechanism for translational control of protein expression. Differential expression of exon 2 denotes a mechanism to provide temporal and tissue-specific regulation of TFPIβ-mediated anticoagulant activity.

Analysis of protein isoforms: can we do it better?

Protein isoforms/splice variants can play important roles in various biological processes and can potentially be used as biomarkers or therapeutic targets/mediators. Thus, there is a need for efficient and, importantly, accurate methods to distinguish and quantify specific protein isoforms. Since protein isoforms can share a high percentage of amino acid sequence homology and dramatically differ in their cellular concentration, the task for accuracy and efficiency in methodology and instrumentation is challenging. The analysis of intact proteins has been perceived to provide a more accurate and complete result for isoform identification/quantification in comparison to analysis of the corresponding peptides that arise from protein enzymatic digestion. Recently, novel approaches have been explored and developed that can possess the accuracy and reliability important for protein isoform differentiation and isoform-specific peptide targeting. In this review, we discuss the recent development in methodology and instrumentation for enhanced detection of protein isoforms as well as the examples of their biological importance.

Myocardial alternative RNA splicing and gene expression profiling in early stage hypoplastic left heart syndrome

Hypoplastic Left Heart Syndrome (HLHS) is a congenital defect characterized by underdevelopment of the left ventricle and pathological compensation of the right ventricle. If untreated, HLHS is invariably lethal due to the extensive increase in right ventricular workload and eventual failure. Despite the clinical significance, little is known about the molecular pathobiological state of HLHS. Splicing of mRNA transcripts is an important regulatory mechanism of gene expression. Tissue specific alterations of this process have been associated with several cardiac diseases, however, transcriptional signature profiles related to HLHS are unknown. In this study, we performed genome-wide exon array analysis to determine differentially expressed genes and alternatively spliced transcripts in the right ventricle (RV) of six neonates with HLHS, compared to the RV and left ventricle (LV) from non-diseased control subjects. In HLHS, over 180 genes were differentially expressed and 1800 were differentially spliced, leading to changes in a variety of biological processes involving cell metabolism, cytoskeleton, and cell adherence. Additional hierarchical clustering analysis revealed that differential gene expression and mRNA splicing patterns identified in HLHS are unique compared to non-diseased tissue. Our findings suggest that gene expression and mRNA splicing are broadly dysregulated in the RV myocardium of HLHS neonates. In addition, our analysis identified transcriptome profiles representative of molecular biomarkers of HLHS that could be used in the future for diagnostic and prognostic stratification to improve patient outcome.

High-throughput quantification of splicing isoforms

Most human messenger RNAs (mRNAs) are alternatively spliced and many exhibit disease-specific splicing patterns. However, the contribution of most splicing events to the development and maintenance of human diseases remains unclear. As the contribution of alternative splicing events to diagnosis and prognosis is becoming increasingly recognized, it becomes important to develop precise methods to quantify the abundance of these isoforms in clinical samples. Here we present a pipeline for real-time PCR annotation of splicing events (RASE) that allows accurate identification of a large number of splicing isoforms in human tissues. The RASE automatically designed specific primer pairs for 81% of all alternative splicing events in the NCBI build 36 database. Experimentally, the majority of the RASE designed primers resulted in isoform-specific amplification suitable for quantification in human cell lines or in formalin-fixed, paraffin-embedded (FFPE) RNA extract. Using this pipeline it is now possible to rapidly identify splicing isoform signatures in different types of human tissues or to validate complete sets of data generated by microarray expression profiling and deep sequencing techniques.

Genomics, transcriptional profiling, and heart failure

Associated with technological progress in deoxyribonucleic acid and messenger ribonucleic acid profiling, advances in basic biology have led to a more complete and sophisticated understanding of interactions among genes, environment, and affected tissues in the setting of complex and heterogeneous conditions such as heart failure (HF). Ongoing identification of mutations causing hereditary hypertrophic and dilated cardiomyopathies has provided both pathophysiological insights and clinically applicable diagnostics for these relatively rare conditions. Genotyping clinical trial participants and genome-wide association studies have accelerated the identification of much more common disease- and treatment-modifying genes that explain patient-to-patient differences that have long been recognized by practicing clinicians. At the same time, increasingly detailed characterization of gene expression within diseased tissues and circulating cells from animal models and patients are providing new insights into the pathophysiology of HF that permit identification of novel diagnostic and therapeutic targets. In this rapidly evolving field, there is already ample support for the concept that genetic and expression profiling can enhance diagnostic sensitivity and specificity while providing a rational basis for prioritizing alternative therapeutic options for patients with cardiomyopathies and HF. Although the extensive characterizations provided by genomic and transcriptional profiling will increasingly challenge clinicians' abilities to utilize complex and diverse information, advances in clinical information technology and user interfaces will permit greater individualization of prevention and treatment strategies to address the HF epidemic.

Novel strategies to identify biomarkers in tuberculosis

The more we learn about the immune response against tuberculosis (TB) and particularly about the features which distinguish protective immunity, disease susceptibility and pathology, the better we can define biomarkers which correlate with these different stages of infection. The most widely used biomarker in TB, which without a doubt is an important component of protective immunity, is IFNγ secreted by antigen-specific CD4 T-cells. However, the complexity of the immune response against TB makes it more than likely that additional biomarkers are required for a reliable correlate of protection. As a corollary, we assume that a set of biomarkers will be required, termed a biosignature.