VLA-5-mediated Adhesion to Fibronectin Accelerates Hemin-stimulated Erythroid Differentiation of K562 Cells through Induction of VLA-4 Expression

Fibronectin plays important roles in erythropoiesis through the fibronectin receptors VLA-4 and VLA-5. However, the substantial role of these fibronectin receptors and their functional assignment in erythroid differentiation are not yet fully understood. Here, we investigated the effects of cell adhesion to fibronectin on erythroid differentiation using K562 human erythroid progenitor cells. Erythroid differentiation could be induced in K562 cells in suspension by stimulating with hemin. This hemin-stimulated erythroid differentiation was highly accelerated when cells were induced to adhere to fibronectin by treatment with TNIIIA2, a peptide derived from tenascin-C, which has recently been found to induce β1-integrin activation. Another integrin activator, Mn²⁺, also accelerated hemin-stimulated erythroid differentiation. Adhesive interaction with fibronectin via VLA-4 as well as VLA-5 was responsible for acceleration of the hemin-stimulated erythroid differentiation in response to TNIIIA2, although K562 cells should have been lacking in VLA-4. Adhesion to fibronectin forced by TNIIIA2 causally induced VLA-4 expression in K562 cells, and this was blocked by the RGD peptide, an antagonist for VLA-5. The resulting adhesive interaction with fibronectin via VLA-4 strongly enhanced the hemin-stimulated activation of p38 mitogen-activated protein kinase, which was shown to serve as a signaling molecule crucial for erythroid differentiation. Suppression of VLA-4 expression by RNA interference abrogated acceleration of hemin-stimulated erythroid differentiation in response to TNIIIA2. Thus, VLA-4 and VLA-5 may contribute to erythropoiesis at different stages of erythroid differentiation.Hematopoietic stem and progenitor cells proliferate and differentiate in the bone marrow and fetal liver (1–6). Stromal cells of the bone marrow and fetal liver form a hematopoietic microenvironment called a “niche.” This microenvironment niche plays a crucial role in the regulation of the proliferation and differentiation of hematopoietic stem and progenitor cells. Besides humoral factors that include hematopoietic growth factors, adhesive interaction of hematopoietic stem and progenitor cells with stromal cells and/or the extracellular matrix (ECM)² in the hematopoietic microenvironment is indispensable for hematopoietic development (1–6). The ECM in the hematopoietic microenvironment is composed of various macromolecules, such as fibronectin (FN), collagens, laminins, and proteoglycans. Among them, FN is one of the most important parts of the microenvironment niche (7–11). Also, in erythropoiesis, the importance of the adhesion of erythroid progenitors to FN via the FN receptors VLA-4 and VLA-5 has been reported (11–16). However, the substantial role of these FN receptors and their functional assignment in erythroid differentiation are not yet fully understood.We previously found that FN, which provides scaffolding for the adhesion of various cell types, has an alternative functional site opposing cell adhesion (17). A 22-mer peptide derived from the 14th FN type III-like (FNIII) repeat of the FN molecule, termed FNIII14, strongly suppresses cell adhesion to FN by inhibiting the activation of β1-integrins including VLA-4 and VLA-5 (18, 19). Conversely, we have recently found that tenascin (TN)-C, which is an anti-adhesive ECM protein (20, 21), has a functional site for stimulating cell adhesion to FN (22). A 22-mer peptide derived from the FNIII repeat A2 in the TN-C molecule, termed TNIIIA2, can induce the conformational change necessary for functional activation of FN receptors through binding with syndecan-4 (22, 23). The active sites of FNIII14 and TNIIIA2 appear to be cryptic in the molecular structures of FN and TN-C but are exposed by conformational change through interaction with other ECM molecules or by processing with matrix metalloproteinase-2 (22, 24). Thus, these functional sites found in FN and TN-C molecules, which act in opposition to their parental ECM proteins, may act as a negative feedback loop for preventing excessive cellular responses to these ECM proteins in biological processes with ECM rearrangement. In any case, FNIII14 and TNIIIA2 enable us to control, either negatively or positively, the adhesion of various cell types to FN.Various hematopoietic progenitor cell lines have been used in in vitro studies of hematopoietic differentiation. However, most hematopoietic progenitor cell lines are nonadherent, because their cell surface β1-integrins, including FN receptors, have impaired ligand-binding activity (25, 26). Therefore, in order to investigate the role of cell adhesion to FN in hematopoietic differentiation, their FN receptors must be activated. Since TNIIIA2 can induce activation of FN receptors in various hematopoietic progenitor cell lines (22), this peptide factor may be useful for investigating the substantial role of cell adhesion to FN in hematopoietic differentiation. Here, we investigate the effects of cell adhesion to FN on erythroid differentiation using TNIIIA2 and Mn²⁺ as the integrin activator and the human erythroid progenitor cell line K562, which only expresses VLA-5, as the FN receptor (27). As a result, we show that hemin-stimulated erythroid differentiation of K562 cells is strongly enhanced when K562 cells are forced to adhere to FN. Sustained adhesion to FN via VLA-5, which is induced by TNIIIA2 or Mn²⁺, causes induction of VLA-4 expression. The resulting adhesive interaction with FN via newly expressed VLA-4 then generates a conspicuous increase in the hemin-stimulated phosphorylation/activation of p38 MAP kinase, which is shown to serve as a signaling molecule crucial for erythroid differentiation of K562 cells.     

The Wavelet-Based Cluster Analysis for Temporal Gene Expression Data

A variety of high-throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Common methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy can be applied in the analysis of data sets of thousands of genes under different conditions.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]