Recording of elapsed time and temporal information about biological events using Cas9

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Structures of HCMV Trimer reveal the basis for receptor recognition and cell entry

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Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing

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Tracing the invasion characteristics of the yellow-legged hornet,Vespa velutina nigrithorax (Hymenoptera: Vespidae), in Korea using newly detected variable mitochondrial DNA sequences

The yellow-legged hornet, Vespa velutina nigrithorax (Hymenoptera: Vespidae), invaded South Korea in 2003 through Busan metropolitan city, which is located in the southeast region of the country. Previous studies aiming to trace the origin of V. velutina in Korea used a portion of mitochondrial (mt) COI and detected a single haplotype common to the site of origin. However, no subsequent study on invasive dynamics such as additional entry and/or another site of entry has been performed. In this study, segments of mt COI, CytB, and lrRNA were sequenced from 238 individuals collected in 11 Korean and two Japanese localities, but no variation in each gene was observed. Thus, we developed two intergenic spacer (IGS) sequences from the publicly available mt genome of V. velutina, which provided substantially increased variability (i.e., 19 haplotypes with 1.74% maximum sequence divergence in 1,129–1,146-bp-long concatenated sequences). Population genetic analyses using the concatenated sequences unexpectedly provided higher genetic diversity estimates in the northwest and southwest regions, both of which also harbor international cargo ports, than in the southeast region, in which Busan is located. Furthermore, this genetic result was roughly concordant with our questionnaire survey demonstrating that V. velutina was observed in apiaries located in the northwest and southwest regions up to 2012, when there was no reported prevalent distribution of the hornet beyond the southeast region. These results collectively suggest that the northwest and southwest regions of Korea are additional sites of V. velutina entry to the country, independent from the southeast region origin.     

Profiling of Volatile Organic Compounds in Exhaled Breath As a Strategy to Find Early Predictive Signatures of Asthma in Children

Wheezing is one of the most common respiratory symptoms in preschool children under six years old. Currently, no tests are available that predict at early stage who will develop asthma and who will be a transient wheezer. Diagnostic tests of asthma are reliable in adults but the same tests are difficult to use in children, because they are invasive and require active cooperation of the patient. A non-invasive alternative is needed for children. Volatile Organic Compounds (VOCs) excreted in breath could yield such non-invasive and patient-friendly diagnostic. The aim of this study was to identify VOCs in the breath of preschool children (inclusion at age 2–4 years) that indicate preclinical asthma. For that purpose we analyzed the total array of exhaled VOCs with Gas Chromatography time of flight Mass Spectrometry of 252 children between 2 and 6 years of age. Breath samples were collected at multiple time points of each child. Each breath-o-gram contained between 300 and 500 VOCs; in total 3256 different compounds were identified across all samples. Using two multivariate methods, Random Forests and dissimilarity Partial Least Squares Discriminant Analysis, we were able to select a set of 17 VOCs which discriminated preschool asthmatic children from transient wheezing children. The correct prediction rate was equal to 80% in an independent test set. These VOCs are related to oxidative stress caused by inflammation in the lungs and consequently lipid peroxidation. In conclusion, we showed that VOCs in the exhaled breath predict the subsequent development of asthma which might guide early treatment.     

The C-Terminal Amino Acid of the MHC-I Heavy Chain Is Critical for Binding to Derlin-1 in Human Cytomegalovirus US11-Induced MHC-I Degradation

Derlin-1 plays a critical role in endoplasmic reticulum-associated protein degradation (ERAD) of a particular subset of proteins. Although it is generally accepted that Derlin-1 mediates the export of ERAD substrates from the ER to the cytosol, little is known about how Derlin-1 interacts with these substrates. Human cytomegalovirus (HCMV) US11 exploits Derlin-1-dependent ERAD to degrade major histocompatibility complex class I (MHC-I) molecules and evade immune surveillance. US11 requires the cytosolic tail of the MHC-I heavy chain to divert MHC-I molecules into the ERAD pathway for degradation; however, the underlying mechanisms remain unknown. Here, we show that the cytosolic tail of the MHC-I heavy chain, although not required for interaction with US11, is required for tight binding to Derlin-1 and thus for US11-induced dislocation of the MHC-I heavy chain to the cytosol for proteasomal degradation. Surprisingly, deletion of a single C-terminal amino acid from the cytosolic tail disrupted the interaction between MHC-I molecules and Derlin-1, rendering mutant MHC-I molecules resistant to US11-induced degradation. Consistently, deleting the C-terminal cytosolic region of Derlin-1 prevented it from binding to MHC-I molecules. Taken together, these results suggest that the cytosolic region of Derlin-1 is involved in ERAD substrate binding and that this interaction is critical for the Derlin-1-mediated dislocation of the MHC-I heavy chain to the cytosol during US11-induced MHC-I degradation.     

RNA Graph Partitioning for the Discovery of RNA Modularity: A Novel Application of Graph Partition Algorithm to Biology

Graph representations have been widely used to analyze and design various economic, social, military, political, and biological networks. In systems biology, networks of cells and organs are useful for understanding disease and medical treatments and, in structural biology, structures of molecules can be described, including RNA structures. In our RNA-As-Graphs (RAG) framework, we represent RNA structures as tree graphs by translating unpaired regions into vertices and helices into edges. Here we explore the modularity of RNA structures by applying graph partitioning known in graph theory to divide an RNA graph into subgraphs. To our knowledge, this is the first application of graph partitioning to biology, and the results suggest a systematic approach for modular design in general. The graph partitioning algorithms utilize mathematical properties of the Laplacian eigenvector (µ2) corresponding to the second eigenvalues (λ2) associated with the topology matrix defining the graph: λ2 describes the overall topology, and the sum of µ2′s components is zero. The three types of algorithms, termed median, sign, and gap cuts, divide a graph by determining nodes of cut by median, zero, and largest gap of µ2′s components, respectively. We apply these algorithms to 45 graphs corresponding to all solved RNA structures up through 11 vertices (∼220 nucleotides). While we observe that the median cut divides a graph into two similar-sized subgraphs, the sign and gap cuts partition a graph into two topologically-distinct subgraphs. We find that the gap cut produces the best biologically-relevant partitioning for RNA because it divides RNAs at less stable connections while maintaining junctions intact. The iterative gap cuts suggest basic modules and assembly protocols to design large RNA structures. Our graph substructuring thus suggests a systematic approach to explore the modularity of biological networks. In our applications to RNA structures, subgraphs also suggest design strategies for novel RNA motifs.     

Animal models of diabetic retinopathy: doors to investigate pathogenesis and potential therapeutics

Effective and validated animal models are valuable to investigate the pathogenesis and potential therapeutics for human diseases. There is much concern for diabetic retinopathy (DR) in that it affects substantial number of working population all around the world, resulting in visual deterioration and social deprivation. In this review, we discuss animal models of DR based on different species of animals from zebrafish to monkeys and prerequisites for animal models. Despite criticisms on imprudent use of laboratory animals, we hope that animal models of DR will be appropriately utilized to deepen our understanding on the pathogenesis of DR and to support our struggle to find novel therapeutics against catastrophic visual loss from DR.     

Connexin32 inhibits gastric carcinogenesis through cell cycle arrest and altered expression of p21Cip1 and p27Kip1

Gap junctions and their structural proteins, connexins (Cxs), have been implicated in carcinogenesis. To explore the involvement of Cx32 in gastric carcinogenesis, immunochemical analysis of Cx32 and proliferation marker Ki67 using tissue-microarrayed human gastric cancer and normal tissues was performed. In addition, after Cx32 overexpression in the human gastric cancer cell line AGS, cell proliferation, cell cycle analyses, and p21^Cip1 and p27^Kip1 expression levels were examined by bromodeoxyuridine assay, flow cytometry, real-time RT-PCR, and western blotting. Immunohistochemical study noted a strong inverse correlation between Cx32 and Ki67 expression pattern as well as their location. In vitro, overexpression of Cx32 in AGS cells inhibited cell proliferation significantly. G₁ arrest, up-regulation of cell cycle-regulatory proteins p21^Cip1 and p27^Kip1 was also found at both mRNA and protein levels. Taken together, Cx32 plays some roles in gastric cancer development by inhibiting gastric cancer cell proliferation through cell cycle arrest and cell cycle regulatory proteins. [BMB Reports 2013; 46(1): 25-30]