Dynamic regulation of RNA editing in human brain development and disease

RNA editing is increasingly recognized as a molecular mechanism regulating RNA activity and recoding proteins. Here, I surveyed the global landscape of RNA editing in human brain tissues and identify three unique patterns of A-to-I RNA editing during cortical development: stable high, stable low and increasing. RNA secondary structure and the temporal expression of adenosine deaminase acting on RNA (ADAR) contribute to cis- and trans- regulatory mechanisms of these RNA editing patterns, respectively. Interestingly, the increasing pattern in development is most apparent in brain and conserved in mouse brain development. The increasing pattern associates with the growth of cortical layers and neuronal maturation, correlates with mRNA abundance, and influences miRNA binding energy. Gene ontology analyses implicate the increasing pattern in vesicle or organelle membrane-related genes and glutamate signaling pathways. We also show that the increasing pattern is selectively perturbed in spinal cord injury and glioblastoma. Our findings reveal dynamic and functional aspects of RNA editing in brain, providing new insight into epigenetic regulation of sequence diversity

Tunable colors of chiral liquid crystal displays

Abstract We report a method of the color variation in the reflective CLC displays depending on thermodynamically and the electric field switching. The reflective wavelength can be thermodynamically switched to reflect green from a cell initially reflecting a red color. Afterwards, the reflective wavelength can be electrically switched to reflect blue color. It is found that continuous decrease of the pitch is mainly originated from the dopant solubility below the critical temperature and stepwise decrease of the pitch is dominantly affected by the thermodynamic property above the critical temperature. The blue color change is a result of the compression to the helical pitches in planar layers in response to the applied voltage

Identification of differentially expressed subnetworks based on multivariate ANOVA

<p>Abstract</p> <p>Background</p> <p>Since high-throughput protein-protein interaction (PPI) data has recently become available for humans, there has been a growing interest in combining PPI data with other genome-wide data. In particular, the identification of phenotype-related PPI subnetworks using gene expression data has been of great concern. Successful integration for the identification of significant subnetworks requires the use of a search algorithm with a proper scoring method. Here we propose a multivariate analysis of variance (MANOVA)-based scoring method with a greedy search for identifying differentially expressed PPI subnetworks.</p> <p>Results</p> <p>Given the MANOVA-based scoring method, we performed a greedy search to identify the subnetworks with the maximum scores in the PPI network. Our approach was successfully applied to human microarray datasets. Each identified subnetwork was annotated with the Gene Ontology (GO) term, resulting in the phenotype-related functional pathway or complex. We also compared these results with those of other scoring methods such as <it>t </it>statistic- and mutual information-based scoring methods. The MANOVA-based method produced subnetworks with a larger number of proteins than the other methods. Furthermore, the subnetworks identified by the MANOVA-based method tended to consist of highly correlated proteins.</p> <p>Conclusion</p> <p>This article proposes a MANOVA-based scoring method to combine PPI data with expression data using a greedy search. This method is recommended for the highly sensitive detection of large subnetworks.</p

Integrative analysis of DNA methylation suggests down-regulation of oncogenic pathways and reduced somatic mutation rates in survival outliers of glioblastoma

The study of survival outliers of glioblastoma can provide important clues on gliomagenesis as well as on the ways to alter clinical course of this almost uniformly lethal cancer type. However, there has been little consensus on genetic and epigenetic signatures of the long-term survival outliers of glioblastoma. Although the two classical molecular markers of glioblastoma including isocitrate dehydrogenase 1 or 2 (IDH1/2) mutation and O6-methylguanine DNA methyltransferase (MGMT) promoter methylation are associated with overall survival rate of glioblastoma patients, they are not specific to the survival outliers. In this study, we compared the two groups of survival outliers of glioblastoma with IDH wild-type, consisting of the glioblastoma patients who lived longer than 3 years (n = 17) and the patients who lived less than 1 year (n = 12) in terms of genome-wide DNA methylation profile. Statistical analyses were performed to identify differentially methylated sites between the two groups. Functional implication of DNA methylation patterns specific to long-term survivors of glioblastoma were investigated by comprehensive enrichment analyses with genomic and epigenomic features. We found that the genome of long-term survivors of glioblastoma is differentially methylated relative to short-term survivor patients depending on CpG density: hypermethylation near CpG islands (CGIs) and hypomethylation far from CGIs. Interestingly, these two patterns are associated with distinct oncogenic aspects in gliomagenesis. In the long-term survival glioblastoma-specific sites distant from CGI, somatic mutations of glioblastoma are enriched with higher DNA methylation, suggesting that the hypomethylation in long-term survival glioblastoma can contribute to reduce the rate of somatic mutation. On the other hand, the hypermethylation near CGIs associates with transcriptional downregulation of genes involved in cancer progression pathways. Using independent cohorts of IDH1/2- wild type glioblastoma, we also showed that these two patterns of DNA methylation can be used as molecular markers of long-term survival glioblastoma. Our results provide extended understanding of DNA methylation, especially of DNA hypomethylation, in cancer genome and reveal clinical importance of DNA methylation pattern as prognostic markers of glioblastoma.This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Ministry of Science & ICT (NRF-2018M3A9H3021707). in Korea, and the Seoul National University Hospital Research Fund (3020180010)

The Firre locus produces a trans -acting RNA molecule that functions in hematopoiesis

Abstract: RNA has been classically known to play central roles in biology, including maintaining telomeres, protein synthesis, and in sex chromosome compensation. While thousands of long noncoding RNAs (lncRNAs) have been identified, attributing RNA-based roles to lncRNA loci requires assessing whether phenotype(s) could be due to DNA regulatory elements, transcription, or the lncRNA. Here, we use the conserved X chromosome lncRNA locus Firre, as a model to discriminate between DNA- and RNA-mediated effects in vivo. We demonstrate that (i) Firre mutant mice have cell-specific hematopoietic phenotypes, and (ii) upon exposure to lipopolysaccharide, mice overexpressing Firre exhibit increased levels of pro-inflammatory cytokines and impaired survival. (iii) Deletion of Firre does not result in changes in local gene expression, but rather in changes on autosomes that can be rescued by expression of transgenic Firre RNA. Together, our results provide genetic evidence that the Firre locus produces a trans-acting lncRNA that has physiological roles in hematopoiesis

Combination therapy of vitamin C and thiamine for septic shock in a multicentre, double-blind, randomized, controlled study (ATESS): study protocol for a randomized controlled trial

Background Septic shock is a life-threatening condition with underlying circulatory and cellular/metabolic abnormalities. Vitamin C and thiamine are potential candidates for adjunctive therapy; they are expected to improve outcomes based on recent experimental and clinical research. The aim of the Ascorbic Acid and Thiamine Effect in Septic Shock (ATESS) trial is to evaluate the effects of early combination therapy with intravenous vitamin C and thiamine on recovery from organ failure in patients with septic shock. Methods This study is a randomized, double-blind, placebo-controlled, multicentre trial in adult patients with septic shock recruited from six emergency departments in South Korea. Patients will be randomly allocated into the treatment or control group (1:1 ratio), and we will recruit 116 septic shock patients (58 per group). For the treatment group, vitamin C (50 mg/kg) and thiamine (200 mg) will be mixed in 50 ml of 0.9% saline and administered intravenously every 12 h for a total of 48 h. For the placebo group, an identical volume of 0.9% saline will be administered in the same manner. The primary outcome is the delta Sequential Organ Failure Assessment (SOFA) score (ΔSOFA = initial SOFA at enrolment – follow-up SOFA after 72 h). Discussion This trial will provide valuable evidence about the effectiveness of vitamin C and thiamine therapy for septic shock. If effective, this therapy might improve survival and become one of the main therapeutic adjuncts for patients with septic shock. Trial registration ClinicalTrials.gov, NCT03756220. Registered on 5 December 2018.This work was supported by a National Research Foundation of Korea grant funded by the Korean government (No. 2018R1C1B6006821). The government did not have any role in the study design; collection, management, analysis, and interpretation of data; writing of the report; and the decision to submit the report for publication

Gene-Chip Diagnostics for Personalized Global Medicine

Single nucleotide polymorphisms (SNP) in a gene sequence are markers for variety of human diseases. Their detection with high specificity and sensitivity is essential for effective practical implementation of personalized medicine. Current DNA sequencing, including SNP detection, primarily uses enzyme based methods or fluorophore-labeled assays that are time consuming, need lab-scale settings, and are expensive. Electrical detection of DNA has been advancing rapidly, with to achieve high specificity, sensitivity and portability. However, existing electrical charge-based SNP detectors have insufficient specificity and accuracy limiting their effectiveness. Its actual implementation is still in infancy because of the low specificity, especially for analytically optimal and practically useful length of target DNA strands. Most of the research so far has focused on the enhancement of the sensitivity of DNA biosensors while the specificity problem has remained unresolved. The low specificity is primarily due to the non-specific binding during hybridization of probe and the target DNA. Here, we have addressed these limitations by designing a functional prototype of electrical biosensors for SNP detection. We demonstrate the use of DNA strand displacement-based probes on a graphene field effect transistor (FET) for high specificity single nucleotide mismatch detection. The single mismatch was detected by measuring strand displacement-induced resistance (and hence current) change and Dirac point shift in a graphene FET. SNP detection in large double helix DNA strands (e.g., 47 nucleotides) minimize false positive. We describe the first integrated dynamic DNA nanotechnology and 2-D material electronics, to overcome current limitations for the detection of DNA single nucleotide polymorphism (SNP). Existing SNP detection systems have poor sensitivity and specificity and lack portability and real-time wireless transmission of detected molecular signals. We have integrated two different kinds of dynamic DNA nano-devices as nucleic acid-sensing probes with electrical biosensors using graphene FET and analytical wireless communication platform. The signal was transmitted remotely using a microcontroller board and Bluetooth standard to personal electronics, including smart phones, tablets and computers. Our electrical sensor-based SNP detection technology without labeling and without apparent cross-hybridization artifacts would allow fast, sensitive and portable SNP detection with single-nucleotide resolution. Practical implementation of this enabling technology will provide cheaper, faster and portable point-of-care molecular diagnostic devices for personalized global health management. It will have wide applications in digital and implantable biosensors and high-throughput DNA genotyping with transformative implications for personalized medicine

Gene-Chip Diagnostics for Personalized Global Medicine

Single nucleotide polymorphisms (SNP) in a gene sequence are markers for variety of human diseases. Their detection with high specificity and sensitivity is essential for effective practical implementation of personalized medicine. Current DNA sequencing, including SNP detection, primarily uses enzyme based methods or fluorophore-labeled assays that are time consuming, need lab-scale settings, and are expensive. Electrical detection of DNA has been advancing rapidly, with to achieve high specificity, sensitivity and portability. However, existing electrical charge-based SNP detectors have insufficient specificity and accuracy limiting their effectiveness. Its actual implementation is still in infancy because of the low specificity, especially for analytically optimal and practically useful length of target DNA strands. Most of the research so far has focused on the enhancement of the sensitivity of DNA biosensors while the specificity problem has remained unresolved. The low specificity is primarily due to the non-specific binding during hybridization of probe and the target DNA. Here, we have addressed these limitations by designing a functional prototype of electrical biosensors for SNP detection. We demonstrate the use of DNA strand displacement-based probes on a graphene field effect transistor (FET) for high specificity single nucleotide mismatch detection. The single mismatch was detected by measuring strand displacement-induced resistance (and hence current) change and Dirac point shift in a graphene FET. SNP detection in large double helix DNA strands (e.g., 47 nucleotides) minimize false positive. We describe the first integrated dynamic DNA nanotechnology and 2-D material electronics, to overcome current limitations for the detection of DNA single nucleotide polymorphism (SNP). Existing SNP detection systems have poor sensitivity and specificity and lack portability and real-time wireless transmission of detected molecular signals. We have integrated two different kinds of dynamic DNA nano-devices as nucleic acid-sensing probes with electrical biosensors using graphene FET and analytical wireless communication platform. The signal was transmitted remotely using a microcontroller board and Bluetooth standard to personal electronics, including smart phones, tablets and computers. Our electrical sensor-based SNP detection technology without labeling and without apparent cross-hybridization artifacts would allow fast, sensitive and portable SNP detection with single-nucleotide resolution. Practical implementation of this enabling technology will provide cheaper, faster and portable point-of-care molecular diagnostic devices for personalized global health management. It will have wide applications in digital and implantable biosensors and high-throughput DNA genotyping with transformative implications for personalized medicine

Plasmonic Biosensors Based on Deformed Graphene

Rapid, accurate, and label-free detection of biomolecules and chemical substances remains a challenge in healthcare. Optical biosensors have been considered as biomedical diagnostic tools required in numerous areas including the detection of viruses, food monitoring, diagnosing pollutants in the environment, global personalized medicine, and molecular diagnostics. In particular, the broadly emerging and promising technique of surface plasmon resonance has established to provide real-time and label-free detection when used in biosensing applications in a highly sensitive, specific, and cost-effective manner with small footprint platform. In this study we propose a novel plasmonic biosensor based on biaxially crumpled graphene structures, wherein plasmon resonances in graphene are utilized to detect variations in the refractive index of the sample medium. Shifts in the resonance wavelength of the plasmon modes for a given change in the RI of the surrounding analyte are calculated by investigating the optical response of crumpled graphene structures on different substrates using theoretical computations based on the finite element method combined with the semiclassical Drude model. The results reveal a high sensitivity of 4990 nm/RIU, corresponding to a large figure-of-merit of 20 for biaxially crumpled graphene structures on polystyrene substrates. We demonstrate that biaxially crumpled graphene exhibits superior sensing performance compared with a uniaxial structure. According to the results, crumpled graphene structures on a titanium oxide substrate can improve the sensor sensitivity by avoiding the damping effects of polydimethylsiloxane substrates. The enhanced sensitivity and broadband mechanical tunability of the biaxially crumpled graphene render it a promising platform for biosensing applications