Simultaneous detection of mRNA and protein stem cell markers in live cells

<p>Abstract</p> <p>Background</p> <p>Biological studies and medical application of stem cells often require the isolation of stem cells from a mixed cell population, including the detection of cancer stem cells in tumor tissue, and isolation of induced pluripotent stem cells after eliciting the expression of specific genes in adult cells. Here we report the detection of Oct-4 mRNA and SSEA-1 protein in live carcinoma stem cells using respectively molecular beacon and dye-labeled antibody, aiming to establish a new method for stem cells detection and isolation.</p> <p>Results</p> <p>Quantification of Oct-4 mRNA and protein in P19 mouse carcinoma stem cells using respectively RT-PCR and immunocytochemistry confirmed that their levels drastically decreased after differentiation. To visualize Oct-4 mRNA in live stem cells, molecular beacons were designed, synthesized and validated, and the detection specificity was confirmed using control studies. We found that the fluorescence signal from Oct-4-targeting molecular beacons provides a clear discrimination between undifferentiated and retinoic acid-induced differentiated cells. Using deconvolution fluorescence microscopy, Oct-4 mRNAs were found to reside on one side of the cytosol. We demonstrated that, using a combination of Oct-4 mRNA-targeting molecular beacon with SSEA-1 antibody in flow cytometric analysis, undifferentiated stem cells can be clearly distinguished from differentiated cells. We revealed that Oct-4 targeting molecular beacons do not seem to affect stem cell biology.</p> <p>Conclusion</p> <p>Molecular beacons have the potential to provide a powerful tool for highly specific detection and isolation of stem cells, including cancer stem cells and induced pluripotent stem (iPS) cells without disturbing cell physiology. It is advantageous to perform simultaneous detection of intracellular (mRNA) and cell-surface (protein) stem cell markers in flow cytometric analysis, which may lead to high detection sensitivity and efficiency.</p

Translation inhibition reveals interaction of 2′-deoxy and 2′-O-methyl molecular beacons with mRNA targets in living cells

Understanding the interaction between oligonucleotide probes and RNA targets in living cells is important for biological and clinical studies of gene expression in vivo. Here, we demonstrate that starvation of cells and translation inhibition by blocking the mTOR or PI-3 kinase pathway could significantly reduce the fluorescence signal from 2′-deoxy molecular beacons (MBs) targeting K-ras and GAPDH mRNAs in living cells. However, the intensity and localization of fluorescence signal from MBs targeting nontranslated 28S rRNA remained the same in normal and translation-inhibited cells. We also found that, in targeting K-ras and GAPDH mRNAs, the signal level from MBs with 2′-O-methyl backbone did not change when translation was repressed. Taken together, our findings suggest that MBs with DNA backbone hybridize preferentially with mRNAs in their translational state in living cells, whereas those with 2′-O-methyl chemistry tend to hybridize to mRNA targets in both translational and nontranslational states. This work may thus provide a significant insight into probe design for detection of RNA molecules in living cells and RNA biology

Target accessibility and signal specificity in live-cell detection of BMP-4 mRNA using molecular beacons

The ability to visualize mRNA in single living cells and monitor in real-time the changes of mRNA level and localization can provide unprecedented opportunities for biological and disease studies. However, the mRNA detection specificity and sensitivity are critically dependent on the selection of target sequences and their accessibility. We carried out an extensive study of the target accessibility of BMP-4 mRNA using 10 different designs of molecular beacons (MBs), and identified the optimal beacon design. Specifically, for MB design 1 and 8 (MB1 and MB8), the fluorescent intensities from BMP-4 mRNA correlated well with the GFP signal after upregulating BMP-4 and co-expressing GFP using adenovirus, and the knockdown of BMP-4 mRNA using siRNA significantly reduced the beacon signals, demonstrating detection specificity. The beacon specificity was further confirmed using blocking RNA and in situ hybridization. We found that fluorescence signal from MBs depends critically on target sequences; the target sequences corresponding to siRNA sites may not be good sites for beacon-based mRNA detection, and vice versa. Possible beacon design rules are identified and approaches for enhancing target accessibility are discussed. This has significant implications to MB design for live cell mRNA detection

Antepartum Pituitary Necrosis Occurring In Pregnancy with Uncontrolled Gestational Diabetes Mellitus: A Case Report

Antepartum pituitary necrosis is a rare medical condition that has only been reported in pregnant women with type I diabetes attributable to diabetes-related vasculopathy and hypercoagulability. We present for the first time a case of antepartum pituitary necrosis occurring in an uncontrolled gestational diabetes mellitus (GDM) patient. The patient was a 32-yr-old woman at 33 weeks and 2 days of gestation. She suffered from severe headache, blurred vision, dizziness, and vomiting. Her baby was delivered by Cesarean section. The brain magnetic resonance images revealed pituitary necrosis. This suggests that pituitary gland necrosis may also complicate GDM pregnancy when glucose levels are uncontrolled

Crystal structure of hyperthermophilic esterase EstE1 and the relationship between its dimerization and thermostability properties

<p>Abstract</p> <p>Background</p> <p>EstE1 is a hyperthermophilic esterase belonging to the hormone-sensitive lipase family and was originally isolated by functional screening of a metagenomic library constructed from a thermal environmental sample. Dimers and oligomers may have been evolutionally selected in thermophiles because intersubunit interactions can confer thermostability on the proteins. The molecular mechanisms of thermostabilization of this extremely thermostable esterase are not well understood due to the lack of structural information.</p> <p>Results</p> <p>Here we report for the first time the 2.1-Å resolution crystal structure of EstE1. The three-dimensional structure of EstE1 exhibits a classic α/β hydrolase fold with a central parallel-stranded beta sheet surrounded by alpha helices on both sides. The residues Ser154, Asp251, and His281 form the catalytic triad motif commonly found in other α/β hydrolases. EstE1 exists as a dimer that is formed by hydrophobic interactions and salt bridges. Circular dichroism spectroscopy and heat inactivation kinetic analysis of EstE1 mutants, which were generated by structure-based site-directed mutagenesis of amino acid residues participating in EstE1 dimerization, revealed that hydrophobic interactions through Val274 and Phe276 on the β8 strand of each monomer play a major role in the dimerization of EstE1. In contrast, the intermolecular salt bridges contribute less significantly to the dimerization and thermostability of EstE1.</p> <p>Conclusion</p> <p>Our results suggest that intermolecular hydrophobic interactions are essential for the hyperthermostability of EstE1. The molecular mechanism that allows EstE1 to endure high temperature will provide guideline for rational design of a thermostable esterase/lipase using the lipolytic enzymes showing structural similarity to EstE1.</p

Soluble expression and stability enhancement of transcription factors using 30Kc19 cell-penetrating protein

Transcription factors have been studied as an important drug candidate. Ever since the successful generation of induced pluripotent stem cells (iPSCs), there has been tremendous interest in reprogramming transcription factors. Because of the safety risks involved in a virus-based approach, many researchers have been trying to deliver transcription factors using nonintegrating materials. Thus, delivery of transcription factors produced as recombinant proteins in E. coli was proposed as an alternative method. However, the low level of soluble expression and instability of such recombinant proteins are potential barriers. We engineered a Bombyx mori 30Kc19 protein as a fusion partner for transcription factors to overcome those problems. We have previously reported that 30Kc19 protein can be produced as a soluble form in E. coli and has a cell-penetrating property and a protein-stabilizing effect. Transcription factors fused with 30Kc19 (Oct4-30Kc19, Sox2-30Kc19, c-Myc-30Kc19, L-Myc-30Kc19, and Klf4-30Kc19) were produced as recombinant proteins. Interestingly, Oct4 and L-Myc were expressed as a soluble form by conjugating with 30Kc19 protein, whereas Oct4 alone and L-Myc alone aggregated. The 30Kc19 protein also enhanced the stability of transcription factors both in vitro and in cells. In addition, 30Kc19-conjugated transcription factors showed rapid delivery into cells and transcriptional activity significantly increased. Overall, 30Kc19 protein conjugation simultaneously enhanced soluble expression, stability, and transcriptional activity of transcription factors. We propose that the conjugation with 30Kc19 protein is a novel approach to solve the technical bottleneck of gene regulation using transcription factors.OAIID:RECH_ACHV_DSTSH_NO:T201623709RECH_ACHV_FG:RR00200001ADJUST_YN:EMP_ID:A002014CITE_RATE:3.376FILENAME:2. (2016.04) Soluble expression and stability enhancement of.pdfDEPT_NM:화학생물공학부EMAIL:[email protected]_YN:YFILEURL:https://srnd.snu.ac.kr/eXrepEIR/fws/file/0df54ee9-e9f1-4612-9d6e-6deaa8197e3e/linkCONFIRM:

Metabolic Syndrome Prediction Using Machine Learning Models with Genetic and Clinical Information from a Nonobese Healthy Population

The prevalence of metabolic syndrome (MS) in the nonobese population is not low. However, the identification and risk mitigation of MS are not easy in this population. We aimed to develop an MS prediction model using genetic and clinical factors of nonobese Koreans through machine learning methods. A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). The analysis was performed in two stages (training and test sets). Model A was designed with only clinical information (age, sex, body mass index, smoking status, alcohol consumption status, and exercise status), and for model B, genetic information (for 10 polymorphisms) was added to model A. Of the 7,502 nonobese participants, 647 (8.6%) had MS. In the test set analysis, for the maximum sensitivity criterion, NB showed the highest sensitivity: 0.38 for model A and 0.42 for model B. The specificity of NB was 0.79 for model A and 0.80 for model B. In a comparison of the performances of models A and B by NB, model B (area under the receiver operating characteristic curve [AUC] = 0.69, clinical and genetic information input) showed better performance than model A (AUC = 0.65, clinical information only input). We designed a prediction model for MS in a nonobese population using clinical and genetic information. With this model, we might convince nonobese MS individuals to undergo health checks and adopt behaviors associated with a preventive lifestyle