The pioneer factor hypothesis is not necessary to explain ectopic liver gene activation

The Pioneer Factor Hypothesis (PFH) states that pioneer factors (PFs) are a subclass of transcription factors (TFs) that bind to and open inaccessible sites and then recruit non-pioneer factors (nonPFs) that activate batteries of silent genes. The PFH predicts that ectopic gene activation requires the sequential activity of qualitatively different TFs. We tested the PFH by expressing the endodermal PF FOXA1 and nonPF HNF4A in K562 lymphoblast cells. While co-expression of FOXA1 and HNF4A activated a burst of endoderm-specific gene expression, we found no evidence for a functional distinction between these two TFs. When expressed independently, both TFs bound and opened inaccessible sites, activated endodermal genes, and 'pioneered' for each other, although FOXA1 required fewer copies of its motif for binding. A subset of targets required both TFs, but the predominant mode of action at these targets did not conform to the sequential activity predicted by the PFH. From these results we hypothesize an alternative to the PFH where 'pioneer activity' depends not on categorically different TFs but rather on the affinity of interaction between TF and DNA.

Cyclic Peptide-Gadolinium Nanocomplexes as siRNA Delivery Tools

We have recently reported that a cyclic peptide containing five tryptophan, five arginine, and one cysteine amino acids [(WR)5C], was able to produce peptide-capped gadolinium nanoparticles, [(WR)5C]-GdNPs, in the range of 240 to 260 nm upon mixing with an aqueous solution of GdCl3. Herein, we report [(WR)5C]-GdNPs as an efficient siRNA delivery system. The peptide-based gadolinium nanoparticles (50 µM) did not exhibit significant cytotoxicity (~93% cell viability at 50 µM) in human leukemia T lymphoblast cells (CCRF-CEM) and triple-negative breast cancer cells (MDA-MB-231) after 48 h. Fluorescence-activated cell sorting (FACS) analysis indicated that the cellular uptakes of Alexa-488-labeled siRNA were found to be enhanced by more than 10 folds in the presence of [(WR)5C]-GdNPs compared with siRNA alone in CCRF-CEM and MDA-MB-231 cells after 6 h of incubation at 37 °C. The gene silencing efficacy of the nanoparticles was determined via the western blot technique using an over-expressed gene, STAT-3 protein, in MDA-MB-231 cells. The results showed ~62% reduction of STAT-3 was observed in MDA-MB-231 with [(WR)5C]-GdNPs at N/P 40. The integrity of the cellular membrane of CCRF-CEM cells was found to be intact when incubated with [(WR)5C]-Gd nanoparticles (50 µM) for 2 h. Confocal microscopy reveals higher internalization of siRNA in MDA-MB-231 cells using [(WR)5C]-GdNPs at N/P 40. These results provided insight about the use of the [(WR)5C]-GdNPs complex as a potent intracellular siRNA transporter that could be a nontoxic choice to be used as a transfection agent for nucleic-acid-based therapeutics.

A Test of the Pioneer Factor Hypothesis

The Pioneer Factor Hypothesis (PFH) states that pioneer factors (PFs) are a subclass of transcription factors (TFs) that bind to and open inaccessible sites and then recruit non-pioneer factors (nonPFs) that activate batteries of silent genes. We tested the PFH by expressing the endodermal PF FoxA1 and nonPF Hnf4a in K562 lymphoblast cells. While co-expression of FoxA1 and Hnf4a activated a burst of endoderm-specific gene expression, we found no evidence for functional distinction between these two TFs. When expressed independently, both TFs bound and opened inaccessible sites, activated endodermal genes, and “pioneered” for each other, although FoxA1 required fewer copies of its motif to bind at inaccessible sites. A subset of targets required both TFs, but the mode of action at these targets did not conform to the sequential activity predicted by the PFH. From these results we propose an alternative to the PFH where “pioneer activity” depends not on the existence of discrete TF subclasses, but on TF binding affinity and genomic context.

Toxicity and Anti-Oxidation Capacity of The Extracts from Caulerpa lentillifera

Caulerpa lentillifera (sea grape) has been widely used in pharmaceutical industry and health-care products in Thailand. In this study, we attempted to evaluate the toxicity and antioxidant capacity of sea grape extracts in five fractions (ethanol- CLET, hexane- CLHE, ethyl acetate- CLEA, butanol-CLBU, and aqueous-CLAQ). The extracts were evaluated for cytotoxicity by MTT and LDH assays on four cell lines, fibroblast (L929), macrophages (RAW 264.7), hepatocytes (FL83B), and keratinocytes (HaCaT). Genotoxicity was tested by comet assay and micronucleus assay on human lymphoblast cells (TK6). The antioxidant capacity was measured by DPPH and ABTS scavenging assays. Our results demonstrated low cytotoxicity and genotoxicity of CLET, CLBU and CLAQ. When tested by DPPH and ABTS assays, CLET, CLEA, and CLHE showed high antioxidant activity. In conclusion, CLET, CLBU, and CLAQ demonstrated no toxic effects, and CLET, CLEA, and CLHE exhibited high antioxidant capacity. Therefore, our results indicated that CLET, CLEA, and CLHE could be consumed safely at doses lower than 500 and 200 μg/ml for CLHE and CLEA, respectively. Keywords: Anti-oxidation, Caulerpa lentillifera, Cytotoxicity, Genotoxicity

Investigation of white blood cell biomaker model for acute lymphoblastic leukemia detection based on convolutional neural network

Acute Lymphoblastic Leukemia (ALL) is a disease that is defined by uncontrollable growth of malignant and immature White Blood Cells (WBCs) which is called lymphoblast. Traditionally, lymphoblast analysis is done manually and highly dependent on the pathologist’s skill and experience which sometimes yields inaccurate result. For that reason, in this project an algorithm to automatically detect WBC and subsequently examine ALL disease using Convolutional Neural Network (CNN) is proposed. Several pretrained CNN models which are VGG, GoogleNet and Alexnet were analaysed to compare its performance for differentiating lymphoblast and non-lymphoblast cells from IDB database. The tuning is done by experimenting the convolution layer, pooling layer and fully connected layer. Technically, 70% of the images are used for training and another 30% for testing. From the experiments, it is found that the best pretrained models are VGG and GoogleNet compared to AlexNet by achieving 100% accuracy for training. As for testing, VGG obtained the highest performance which is 99.13% accuracy. Apart from that, VGG also proven to have better result based on the training graph which is more stable and contains less error compared to the other two models.

Quantifying the RNA cap epitranscriptome reveals novel caps in cellular and viral RNA

Chemical modification of transcripts with 5′ caps occurs in all organisms. Here, we report a systems-level mass spectrometry-based technique, CapQuant, for quantitative analysis of an organism's cap epitranscriptome. The method was piloted with 21 canonical caps—m7GpppN, m7GpppNm, GpppN, GpppNm, and m2,2,7GpppG—and 5 ‘metabolite’ caps—NAD, FAD, UDP-Glc, UDP-GlcNAc, and dpCoA. Applying CapQuant to RNA from purified dengue virus, Escherichia coli, yeast, mouse tissues, and human cells, we discovered new cap structures in humans and mice (FAD, UDP-Glc, UDP-GlcNAc, and m7Gpppm6A), cell- and tissue-specific variations in cap methylation, and high proportions of caps lacking 2′-O-methylation (m7Gpppm6A in mammals, m7GpppA in dengue virus). While substantial Dimroth-induced loss of m1A and m1Am arose with specific RNA processing conditions, human lymphoblast cells showed no detectable m1A or m1Am in caps. CapQuant accurately captured the preference for purine nucleotides at eukaryotic transcription start sites and the correlation between metabolite levels and metabolite caps.