Alternative Splicing Events Are a Late Feature of Pathology in a Mouse Model of Spinal Muscular Atrophy

Spinal muscular atrophy is a severe motor neuron disease caused by inactivating mutations in the SMN1 gene leading to reduced levels of full-length functional SMN protein. SMN is a critical mediator of spliceosomal protein assembly, and complete loss or drastic reduction in protein leads to loss of cell viability. However, the reason for selective motor neuron degeneration when SMN is reduced to levels which are tolerated by all other cell types is not currently understood. Widespread splicing abnormalities have recently been reported at end-stage in a mouse model of SMA, leading to the proposition that disruption of efficient splicing is the primary mechanism of motor neuron death. However, it remains unclear whether splicing abnormalities are present during early stages of the disease, which would be a requirement for a direct role in disease pathogenesis. We performed exon-array analysis of RNA from SMN deficient mouse spinal cord at 3 time points, pre-symptomatic (P1), early symptomatic (P7), and late-symptomatic (P13). Compared to littermate control mice, SMA mice showed a time-dependent increase in the number of exons showing differential expression, with minimal differences between genotypes at P1 and P7, but substantial variation in late-symptomatic (P13) mice. Gene ontology analysis revealed differences in pathways associated with neuronal development as well as cellular injury. Validation of selected targets by RT–PCR confirmed the array findings and was in keeping with a shift between physiologically occurring mRNA isoforms. We conclude that the majority of splicing changes occur late in SMA and may represent a secondary effect of cell injury, though we cannot rule out significant early changes in a small number of transcripts crucial to motor neuron survival

Detection of HPV and co-infecting pathogens in healthy Italian women by multiplex real-time PCR

Several pathogens can be transmitted sexually and are an important cause of morbidity among sexually active women. The aim of the study was to detect the presence of human papillomavirus (HPV), Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), Trichomonas vaginalis (TV), Mycoplasma hominis (MH), Mycoplasma genitalium (MG), Ureaplasma urealyticum (UU), and Ureaplasma parvum (UP) in a group of 309 healthy women enrolled at the San Camillo - Forlanini hospital of Rome by using two multiplex real-time PCR assays based on TOCE® technology. The women's ages ranged from 34 to 60 years, median 49 [IQR 45-54]. Of the 309 women tested, HPV DNA was detected in 77/309 (24.9%) patients. Of these, 44 (14.2%) harboured a single infection while 33 (10.7%) were infected by multiple genotypes. Prevalence of HPV infection was highest among females aged 40-50 years (15.2%). Of the other pathogens sought, CT, MG and NG were not detected while positive results were found for MH (12/309, 3.9%), TV (4/309, 1.3%), UP (89/309, 28.8%) and UU (14/309, 4.5%). Co-infections were as follows: 5 MH/HPV, 4 TV/HPV, 34 UP/HPV and 9 UU/HPV. In HPV-positive women, the probability of being infected by UP and UU was 2.5 (p=0.00045) and 6 fold higher (p=0.0016) than in HPV-negative women. The study supports the use of multiplex real-time PCR assays in a routine diagnostic setting. The high sensitivity and specificity of these assays along with the simultaneous detection of the most common sexually transmitted pathogens confers an advantage with respect to more obsolete methods reducing costs and time to diagnosis

Detection of HPV and co-infecting pathogens in healthy Italian women by multiplex real-time PCR

Several pathogens can be transmitted sexually and are an important cause of morbidity among sexually active women. The aim of the study was to detect the presence of human papillomavirus (HPV), Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), Trichomonas vaginalis (TV), Mycoplasma hominis (MH), Mycoplasma genitalium (MG), Ureaplasma urealyticum (UU), and Ureaplasma parvum (UP) in a group of 309 healthy women enrolled at the San Camillo - Forlanini hospital of Rome by using two multiplex real-time PCR assays based on TOCE® technology. The women's ages ranged from 34 to 60 years, median 49 [IQR 45-54]. Of the 309 women tested, HPV DNA was detected in 77/309 (24.9%) patients. Of these, 44 (14.2%) harboured a single infection while 33 (10.7%) were infected by multiple genotypes. Prevalence of HPV infection was highest among females aged 40-50 years (15.2%). Of the other pathogens sought, CT, MG and NG were not detected while positive results were found for MH (12/309, 3.9%), TV (4/309, 1.3%), UP (89/309, 28.8%) and UU (14/309, 4.5%). Co-infections were as follows: 5 MH/HPV, 4 TV/HPV, 34 UP/HPV and 9 UU/HPV. In HPV-positive women, the probability of being infected by UP and UU was 2.5 (p=0.00045) and 6 fold higher (p=0.0016) than in HPV-negative women. The study supports the use of multiplex real-time PCR assays in a routine diagnostic setting. The high sensitivity and specificity of these assays along with the simultaneous detection of the most common sexually transmitted pathogens confers an advantage with respect to more obsolete methods reducing costs and time to diagnosis

DEGAS: de novo discovery of dysregulated pathways in human diseases

Background Molecular studies of the human disease transcriptome typically involve a search for genes whose expression is significantly dysregulated in sick individuals compared to healthy controls. Recent studies have found that only a small number of the genes in human disease-related pathways show consistent dysregulation in sick individuals. However, those studies found that some pathway genes are affected in most sick individuals, but genes can differ among individuals. While a pathway is usually defined as a set of genes known to share a specific function, pathway boundaries are frequently difficult to assign, and methods that rely on such definition cannot discover novel pathways. Protein interaction networks can potentially be used to overcome these problems. Methodology/Principal Findings We present DEGAS (DysrEgulated Gene set Analysis via Subnetworks), a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. We applied DEGAS to seven human diseases and obtained statistically significant results that appear to home in on compact pathways enriched with hallmarks of the diseases. In Parkinson's disease, we provide novel evidence for involvement of mRNA splicing, cell proliferation, and the 14-3-3 complex in the disease progression. DEGAS is available as part of the MATISSE software package (http://acgt.cs.tau.ac.il/matisse). Conclusions/Significance The subnetworks identified by DEGAS can provide a signature of the disease potentially useful for diagnosis, pinpoint possible pathways affected by the disease, and suggest targets for drug intervention.Sixth Framework Programme (European Commission) (“GENEPARK: GENomic Biomarkers for PARKinson's disease” project, contract number EU-LSHB-CT-2006-037544)Israeli Science Foundation (grant no. 802/08)Sixth Framework Programme (European Commission) (“GENEPARK: GENomic Biomarkers for PARKinson's disease” project, contract EU-LSHB-CT-2006- 0375)Seventh Framework Programme (European Commission) (grant HEALTH-F4-2009-223575 for the TRIREME project