Biology subjects

Ma, S.

Publications and source records attributed to Ma, S..

260 records · Page 15Linked to original sources

bioRxiv2018

Planar cell polarity pathway and development of the human visual cortex

The radial unit hypothesis provides a framework for global (proliferation) and regional (distribution) expansion of the primate cerebral cortex. Using principal component analysis (PCA), we have identified cortical regions with shared variance in their surface area and cortical thickness, respectively, segmented from magnetic resonance images obtained in 23,800 participants. We then carried out meta-analyses of genome-wide association studies of the first two principal components for each phenotype. For surface area (but not cortical thickness), we have detected strong associations between each of the components and single nucleotide polymorphisms in a number of gene loci. The first (global) component was associated mainly with loci on chromosome 17 (9.5e-32 [≤] p [≤] 2.8e-10), including those detected previously as linked with intracranial volume and/or general cognitive function. The second (regional) component captured shared variation in the surface area of the primary and adjacent secondary visual cortices and showed a robust association with polymorphisms in a locus on chromosome 14 containing Disheveled Associated Activator of Morphogenesis 1 (DAAM1; p=2.4e-34). DAAM1 is a key component in the planar-cell-polarity signaling pathway. In follow-up studies, we have focused on the latter finding and established that: (1) DAAM1 is highly expressed between 12th and 22nd post-conception weeks in the human cerebral cortex; (2) genes co-expressed with DAAM1 in the primary visual cortex are enriched in mitochondria-related pathways; and (3) volume of the lateral geniculate nucleus, which projects to regions of the visual cortex staining for cytochrome oxidase (a mitochondrial enzyme), correlates with the surface area of the visual cortex in major-allele homozygotes but not in carriers of the minor allele. Altogether, we speculate that, in concert with thalamocortical input to cortical subplate, DAAM1 enables migration of neurons to cytochrome-oxidase rich regions of the visual cortex, and, in turn, facilitates regional expansion of this set of cortical regions during development.

neuroscience↗

bioRxiv2018

Icariin induces MC3T3-E1 cell proliferation and differentiation via the BMP-2/Smads/Runx2 signal pathway

Icariin, the main active ingredient of Epimedium, has played an important role in bone anabolism. However, the molecular mechanism for this effect was not convincingly reported yet. In this paper, the role of icariin on cell morphology, viability, cell cycling and the activity of alkaline phosphatase (ALP) were studied, and the molecular mechanism of icariin induced osteogenic effect was also investigated. Icariin with different concentrations (10, 20 and 40 ng/ml) was used to modify the pre-osteoblastic MC3T3-E1 cells for 48, 72 and 96 h, and the proliferation, morphology, and the cell cycle of the cells were evaluated by Cell Counting Kit-8 (CCK-8), microscopy and flow cytometry, respectively. Bone morphogenic protein-2 (BMP-2), bone morphogenic protein receptor-2 (BMPR-2), Smad4, Smadl/5/8 proteins expression levels were obtained by Western blotting and the expression levels of runt-related transcription factor 2 (Runx2) mRNA was examined by reverse transcription-polymerase chain reaction (RT-PCR). In this study, we found that icariin could promote the proliferation and differentiation of MC3T3-E1 cells in a dose - and time-dependent manner. Icariin could stimulate the expression of the BMP-2, BMPR-2, Smad4 and Smadl/5/8 proteins. Furthermore, icariin could upregulate the expression of Runx2 mRNA. These results showed that icariin played an important role in upregulating BMP-2 expression to activate the BMP-2/Smads/Runx2 signal pathway for increasing both the proliferation and differentiation of the MC3T3-E1 cells. However, the osteogenic effects of icariin can be suppressed by the BMP-2 antagonist (Noggin). In conclusion, we demonstrate that icariin is an osteoinductive factor that exerts its osteogenic effect by regulating the BMP-2/Smads/Runx2 signal pathway in MC3T3-E1 cells.

cell biology↗

bioRxiv2018

Black swimming dots in cell culture: the identity, detection method and judging criteria

Black swimming dots (BSDs) -- the biological UFO in cell culture -- have perplexed biologists for decades. BSDs are extremely tiny dots found in dishes of cultured cells. It is still controversial on their origin and identity. BSDs are very hard to be removed and bring adverse impact to cell experiments (Supplementary Table 1). Here we wish to answer three urgent questions about BSDs. First, is the identity of BSDs nonliving matter or living organism? Second, is there any reliable method to tell whether the donor cattle for FBS production or the animals for primary cells isolation carry BSDs? Third, what are the judging criteria for BSDs when \"tiny black dots\" were observed? In 2015, we happened to observe BSDs in the perivitelline space of mouse oocytes and embryos; and the cells derived from these mice exhibited typical properties of BSDs infected cells (described in Supplementary Information). With these BSDs infected (BSD+) mice, we demonstrate that BSDs per se are ...

cell biology↗

bioRxiv2018

Programmable single and multiplex base-editing in Bombyx mori using RNA-guided cytidine deaminases

Standard genome editing tools (ZFN, TALEN and CRISPR/Cas9) edited genome depending on DNA double strand breaks (DSBs). A series of new CRISPR tools that convert cytidine to thymine (C to T) without the requirement for DNA double-strand breaks were developed recently, which have changed this status and have been quickly applied in a variety of organisms. Here, we demonstrate that CRISPR/Cas9-dependent base editor (BE3) converts C to T with a high frequency in the invertebrate Bombyx mori silkworm. Using BE3 as a knock-out tool, we inactivated exogenous and endogenous genes through base-editing-induced nonsense mutations with an efficiency of up to 66.2%. Furthermore, genome-scale analysis showed that 96.5% of B. mori genes have one or more targetable sites being knocked out by BE3 with a median of 11 sites per gene. The editing window of BE3 reached up to 13 bases (from C1 to C13 in the range of gRNA) in B. mori. Notably, up to 14 bases were substituted simultaneously in a single DNA molecule, with a low indel frequency of 0.6%, when 32 gRNAs were co-transfected. Collectively, our data show for the first time that RNA-guided cytidine deaminases are capable of programmable single and multiplex base-editing in an invertebrate model.

genetics↗

bioRxiv2017

A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy

We introduce the Interaction Factor (IF), a measure for quantifying the interaction of molecular clusters in super-resolution microscopy images. The IF is robust in the sense that it is independent of cluster density, and it only depends on the extent of the pair-wise interaction between different types of molecular clusters in the image. The IF for a single or a collection of images is estimated by first using stochastic modelling where the locations of clusters in the images are repeatedly randomized to estimate the distribution of the overlaps between the clusters in the absence of interaction (IF=0). Second, an analytical form of the relationship between IF and the overlap (which has the random overlap as its only parameter) is used to estimate the IF for the experimentally observed overlap. The advantage of IF compared to conventional methods to quantify interaction in microscopy images is that it is insensitive to changing cluster density and is an absolute measure of interaction, making the interpretation of experiments easier. We validate the IF method by using both simulated and experimental data and provide an ImageJ plugin for determining the IF of an image.

bioinformatics↗

bioRxiv2017

Pathway-Level Integration of Proteogenomic data in Breast Cancer Using Independent Component Analysis

Recent advances in the multi-omics characterization necessitate pathway-level abstraction and knowledge integration across different data types. In this study, we apply independent component analysis (ICA) to human breast cancer proteogenomics data to retrieve mechanistic information. We show that as an unsupervised feature extraction method, ICA was able to construct signatures with known biological relevance on both transcriptome and proteome levels. Moreover, proteome and transcriptome signatures can be associated by their respective correlation with patient clinical features, providing an integrated description of phenotype-related biological processes. Our results demonstrate that the application of ICA to proteogenomics data could lead to pathway-level knowledge discovery. Potential extension of this approach to other data and cancer types may contribute to pan-cancer integration of multi-omics information.

cancer biology↗

bioRxiv2017

Common Piezo1 allele in African populations causes xerocytosis and attenuates Plasmodium infection

Hereditary xerocytosis (HX) is thought to be a rare genetic condition characterized by red blood cell (RBC) dehydration with mild hemolysis. Gain-of-function (GOF) mutations in mechanosensitive Piezo1 ion channels are identified in HX patients. RBC dehydration is linked to reduced Plasmodium infection rates in vitro. We engineered a Piezo1 mouse model of HX and show that Plasmodium infection fails to cause experimental cerebral malaria in these mice. Furthermore, we identified a novel GOF human Piezo1 variant, E756del, present in a third of African population. Remarkably, RBCs from individuals carrying this allele are dehydrated and protected against Plasmodium infection in vitro. The presence of an HX-causing Piezo1 mutation at such high frequencies in African population is surprising, and suggests an association with malaria resistance.

physiology↗

bioRxiv2016

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced REgulation And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAMs enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.\n\nAuthor SummaryThe integration of gene regulatory and metabolic network models is an important goal in computational biology, in order to develop methods that can identify the underlying mechanistic links in biological networks and advance metabolic engineering techniques. In this paper, we develop a framework called Integrated Deduced REgulation And Metabolism (IDREAM) that can improve our ability to predict phenotypes of microorganisms, and particularly it can address the challenges in evaluating phenotypic consequence of perturbing transcriptional regulation of metabolism in a eukaryotic cell. We compare the predictive performance of an IDREAM S. cerevisiae model with a PROM model using a TRN available from the YEASTRACT database. IDREAM outperforms PROM using any of three popular yeast metabolic models and across three experimental growth conditions, making it possible to identify subtle synthetic growth defects, and a new role for Oaf1 in the regulation of acetyl-CoA biosynthesis.

systems biology↗