Biomedical subjects

Ling-Yun Wu

Publications and source records attributed to Ling-Yun Wu.

10 recordsLinked to original sources

PubMed2026

Deficiency of Setd2 in mesenchymal stem cells facilitates the progression of myelodysplastic syndrome to leukemia.

While previous studies have indicated that H3K36me3, which is mediated by Setd2, may regulate the cell fate of mesenchymal stem cells (MSCs) both in vitro and in vivo, the specific role of MSCs in the onset and progression of MDS remains unclear. Thus, the histone methyltransferase Setd2 is implicated in MDS-associated leukemia. This study utilized NUP98-HOXD13 (NHD13) mice with targeted deletion of Setd2 in MSCs. Here, we found that Setd2-deficient mice undergo faster leukemia transformation than control mice do, as evidenced by the abnormal differentiation of hematopoietic stem progenitor cells in the bone marrow, abnormal hematopoiesis, and increased number of blast cells. Compared with that of control mice, the morphology of NHD13 mouse MSCs with Setd2 deficiency was irregular, and the support function of hematopoietic cells was compromised. This study demonstrated that targeted deletion of Setd2 in MSCs facilitates the advancement of MDS. Furthermore, we identified increased expression of coagulation factor XII as a key leukemic transformation mediator in Setd2-deficient MSCs. Moreover, we found that SETD2 expression is significantly lower in high-risk MDS patients than in low-risk MDS patients, further suggesting that the targeted deletion of Setd2 in MSCs is associated with MDS progression. Collectively, our results suggest that Setd2 in MSCs suppresses MDS progression to leukemia through coagulation factor XII-mediated suppression of the stem cell support capacity of MSCs. Overall, this study sheds light on the pathogenesis of MDS and provides a therapeutic strategy for regulating the microenvironment in patients with MDS who cannot be cured by haematopoietic stem cell transplantation.

Animals↗

PubMed2006

Revealing divergent evolution, identifying circular permutations and detecting active-sites by protein structure comparison.

BACKGROUND: Protein structure comparison is one of the most important problems in computational biology and plays a key role in protein structure prediction, fold family classification, motif finding, phylogenetic tree reconstruction and protein docking. RESULTS: We propose a novel method to compare the protein structures in an accurate and efficient manner. Such a method can be used to not only reveal divergent evolution, but also identify circular permutations and further detect active-sites. Specifically, we define the structure alignment as a multi-objective optimization problem, i.e., maximizing the number of aligned atoms and minimizing their root mean square distance. By controlling a single distance-related parameter, theoretically we can obtain a variety of optimal alignments corresponding to different optimal matching patterns, i.e., from a large matching portion to a small matching portion. The number of variables in our algorithm increases with the number of atoms of protein pairs in almost a linear manner. In addition to solid theoretical background, numerical experiments demonstrated significant improvement of our approach over the existing methods in terms of quality and efficiency. In particular, we show that divergent evolution, circular permutations and active-sites (or structural motifs) can be identified by our method. The software SAMO is available upon request from the authors, or from http://zhangroup.aporc.org/bioinfo/samo/ and http://intelligent.eic.osaka-sandai.ac.jp/chenen/samo.htm. CONCLUSION: A novel formulation is proposed to accurately align protein structures in the framework of multi-objective optimization, based on a sequence order-independent strategy. A fast and accurate algorithm based on the bipartite matching algorithm is developed by exploiting the special features. Convergence of computation is shown in experiments and is also theoretically proven.

Algorithms↗

PubMed2006

Gene profile for differentiation of vascular adventitial myofibroblasts.

Our previous study demonstrated that TGF-beta1 could induce the differentiation of vascular adventitial fibroblasts (AFs) to myofibroblasts (MFs). The aim of this study was to identify the genes which might be responsible for the cell phenotypic change using genechips. Cultured rat AFs were treated with TGF-beta1 (10 ng/ml) for 0 min, 5 min, 15 min, 2 h, 12 h and 24 h, respectively. Then the cells were gathered to prepare total RNA. We examined TGF-beta1-induced gene expression profiling using Affymetrix oligonucleotide microarrays and analyzed data by GCOS1.2 software. Moreover, expressional similarity was measured by hierarchical clustering. Some of genechip results were confirmed by real-time quantitative RT-PCR. Microarray analysis identified 2121 genes with a 2-fold change or above after TGF-beta1 stimulation. 1318 genes showed a greater than 2-fold increase and 761 genes were reduced 2 folds or more at mRNA levels, whereas a small portion of the total regulated genes (42 genes) displayed dynamically up- and down-regulated pattern. Genes were further segregated for early (peak at 5 min, 15 min and/or 2 h), late (peak at 12 h and/or 24 h), and sustained (2-fold change or above at five time points) temporal response groups according to the time of their peak expression level. Among 1318 up-regulated genes, 333 genes (25.3%) responded rapidly to TGF-beta1 and 159 genes (12.1%) responded in a sustained manner. Most genes (826, 62.6%) were regulated at 12 h or later. For the 761 down-regulated genes, numbers of early and late responsive genes were 335 (44%) and 267 (36.1%), respectively. There were also 159 genes, 19.9% of total down-regulated genes, decreased at five time points treated by TGF-beta1. The results suggested that the gene expressions of secreted phosphoprotein 1 (APP1) and Rho-associated coiled-coil forming kinase 2 (ROCK2) had the same trends as alpha-smooth muscle-actin, a marker of MF differentiation. In addition, the gene expression of potassium voltage-gated channel, Shal-related family and member 2 (KCND2) was up-regulated. Furthermore, it was found that endothelin 1 (EDN1), some complement components, NADPH oxidase 4 (NOX4) and NAD(P)H dehydrogenase, quinone 1 (NQO1) might be involved in MF differentiation. Using microarrary technique, we confirmed some genes that have been identified by other techniques were implicated in MF differentiation and observed new genes involved in this process. Our results suggest that gene expression profiling study is helpful in identifying genes and pathways potentially involved in cell differentiation.

Adventitia↗

PubMed2006

Inferring protein interactions from experimental data by association probabilistic method.

To elucidate protein interaction networks is one of the major goals of functional genomics for whole organisms. So far, various computational methods have been proposed for inference of protein-protein interactions. Based on the association method by Sprinzak et al., we propose an association probabilistic method in this short communication to infer protein interactions directly from the experimental data, which outperformed other existing methods in terms of both accuracy and efficiency despite its simple form. Specifically, we show that the association probabilistic method achieves the highest accuracy among the existing approaches for the measures of root-mean-square error and the Pearson correlation coefficient, and also runs much faster than the LP-based method, by experimental dataset in Yeast. Software is available from the authors upon request.

Databases, Protein↗

PubMed2005

Haplotype reconstruction from SNP fragments by minimum error correction.

MOTIVATION: Haplotype reconstruction based on aligned single nucleotide polymorphism (SNP) fragments is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. An important computational model of this problem is the minimum error correction (MEC) model, which has been mentioned in several literatures. The model retrieves a pair of haplotypes by correcting minimum number of SNPs in given genome fragments coming from an individual's DNA. RESULTS: In the first part of this paper, an exact algorithm for the MEC model is presented. Owing to the NP-hardness of the MEC model, we also design a genetic algorithm (GA). The designed GA is intended to solve large size problems and has very good performance. The strength and weakness of the MEC model are shown using experimental results on real data and simulation data. In the second part of this paper, to improve the MEC model for haplotype reconstruction, a new computational model is proposed, which simultaneously employs genotype information of an individual in the process of SNP correction, and is called MEC with genotype information (shortly, MEC/GI). Computational results on extensive datasets show that the new model has much higher accuracy in haplotype reconstruction than the pure MEC model.

Algorithms↗

PubMed2005

Haplotype assembly from aligned weighted SNP fragments.

Given an assembled genome of a diploid organism the haplotype assembly problem can be formulated as retrieval of a pair of haplotypes from a set of aligned weighted SNP fragments. Known computational formulations (models) of this problem are minimum letter flips (MLF) and the weighted minimum letter flips (WMLF; Greenberg et al. (INFORMS J. Comput. 2004, 14, 211-213)). In this paper we show that the general WMLF model is NP-hard even for the gapless case. However the algorithmic solutions for selected variants of WMFL can exist and we propose a heuristic algorithm based on a dynamic clustering technique. We also introduce a new formulation of the haplotype assembly problem that we call COMPLETE WMLF (CWMLF). This model and algorithms for its implementation take into account a simultaneous presence of multiple kinds of data errors. Extensive computational experiments indicate that the algorithmic implementations of the CWMLF model achieve higher accuracy of haplotype reconstruction than the WMLF-based algorithms, which in turn appear to be more accurate than those based on MLF.

Algorithms↗

PubMed2005

Exploring protein's optimal HP configurations by self-organizing mapping.

Self-organizing map (SOM) has been used in protein folding prediction when the HP model is employed. The existing work uses a square-like shape lattice with l = m x n points to represent the optimal compact structure of a sequence of l amino acids. In this paper, a general l'-size sequence of amino acids is self-organized in a two dimensional lattice with l (> l') points. The obtained minimum configuration then has a flexible shape, in contrast to the compact structure limited in the lattice. To fulfil this extension, a new self-organizing map (SOM) technique is proposed to deal with the difficulty of the unsymmetric input and output spaces. New competition rules in the training phase are introduced and a local search method is applied to overcome the multi-mapping phenomena. Several HP benchmark examples with up to 36 amino acids are tested to verify the effectiveness of the proposed approach in this paper.

Algorithms↗

PubMed2005

Comparison of protein structures by multi-objective optimization.

We propose a novel method for solving the structure comparison problem for proteins, based on a decomposition technique. We define the structure alignment as a multi-objective optimization problem with both discrete and continuous variables, i.e., maximizing the number of aligned atoms and minimizing their root mean square distance. By controlling a single distance-related parameter, theoretically we can obtain a variety of optimal alignments corresponding to different optimal matching patterns, i.e., from a large matching portion to a small portion. The number of variables in our algorithm increases with the number of atoms of protein pairs in almost a linear manner. The software is available upon request, or from http://zhangroup.aporc.org/bioinfo/samo/.

Algorithms↗

PubMed2004

Angiogenic synergistic effect of basic fibroblast growth factor and vascular endothelial growth factor in an in vitro quantitative microcarrier-based three-dimensional fibrin angiogenesis system.

AIM: To develop an in vitro three-dimensional (3-D) angiogenesis system to analyse the capillary sprouts induced in response to the concentration ranges of basic fibroblast growth factor (bFGF) and vascular endothelial growth factor (VEGF) and to quantify their synergistic activity. METHODS: Microcarriers (MCs) coated with human microvascular endothelial cells (HMVECs) were embedded in fibrin gel and cultured in 24-well plates with assay media. The growth factors bFGF, or VEGF, or both were added to the system. The wells (n = 8/group) were digitally photographed and the average length of capillary-like sprouts (ALS) from each microcarrier was quantitated. RESULTS: In aprotinin-stabilized fibrin matrix, human microvascular endothelial cells on the MCs invaded fibrin, forming sprouts and capillary networks with lumina. The angiogenic effects of bFGF or VEGF were dose-dependent in the range from 10 to 40 ng/mL. At d 1, 10 ng/mL of bFGF and VEGF induced angiogenesis with an ALS of 32.13 +/- 16.6 microm and 43.75 +/- 27.92 microm, respectively, which were significantly higher than that of the control (5.88 +/- 4.45 microm, P<0.01), and the differences became more significant as the time increased. In addition, the combination of 10 ng/mL of bFGF and VEGF each induced a more significant effect than the summed effects of bFGF (10 ng/mL) alone and VEGF (10 ng/mL) alone when analyzed using SPSS system for general linear model (GLM) (P = 0.011), and that also exceeded the effects by 20 ng/mL of either bFGF or VEGF. CONCLUSION: A microcarrier-based in vitro three-dimensional angiogenesis model can be developed in fibrin. It offers a unique system for quantitative analysis of angiogenesis. Both bFGF and VEGF exert their angiogenic effects on HMVECs synergistically and in a dose-dependent manner.

Capillaries↗

PubMed2003

Reconstruction of DNA sequencing by hybridization.

MOTIVATION: It is widely recognized that the hybridization process is prone to errors and that the future of DNA sequencing by hybridization is predicated on the ability to successfully cope with such errors. However, the occurrence of hybridization errors results in the computational difficulty of the reconstruction of DNA sequencing by hybridization. The reconstruction problem of DNA sequencing by hybridization with errors is a strongly NP-hard problem. So far the problem has not been solved well. RESULTS: In this paper, a new approach is presented to solve the reconstruction problem of DNA sequencing by hybridization, which realizes the computational part of the SBH experiment. The proposed algorithm accepts both the negative and positive errors. The computational experiments show that the algorithm behaves satisfactorily, especially for the case with k-tuple repetitions and positive errors.

Algorithms↗