Biology subjects

Ohkawa, Y.

Publications and source records attributed to Ohkawa, Y..

39 records · Page 3Linked to original sources

bioRxiv2019

Modeling latent flows on single-cell data using the Hodge decomposition

Single-cell analysis is a powerful technique used to identify a specific cell population of interest during differentiation, aging, or oncogenesis. Individual cells occupy a particular transient state in the cell cycle, circadian rhythm, or during cell death. An appealing concept of pseudo-time trajectory analysis of single-cell RNA sequencing data was proposed in the software Monocle, and several methods of trajectory analysis have since been published to date. These aim to infer the ordering of cells and enable the tracing of gene expression profile trajectories in cell differentiation and reprogramming. However, the methods are restricted in terms of time structure because of the pre-specified structure of trajectories (linear, branched, tree or cyclic) which contrasts with the mixed state of single cells.\n\nHere, we propose a technique to extract underlying flows in single-cell data based on the Hodge decomposition (HD). HD is a theorem of vector fields on a manifold which guarantees that any given flow can decompose into three types of orthogonal component: gradient-flow (acyclic), curl-, and harmonic-flow (cyclic). HD is generalized on a simplicial complex (graph) and the discretized HD has only a weak assumption that the graph is directed. Therefore, in principle, HD can extract flows from any mixture of tree and cyclic time flows of observed cells. The decomposed flows provide intuitive interpretations about complex flow because of their linearity and orthogonality. Thus, each extracted flow can be focused on separately with no need to consider crosstalk.\n\nWe developed ddhodge software, which aims to model the underlying flow structure that implies unobserved time or causal relations in the hodge-podge collection of data points. We demonstrated that the mathematical framework of HD is suitable to reconstruct a sparse graph representation of diffusion process as a candidate model of differentiation while preserving the divergence of the original fully-connected graph. The preserved divergence can be used as an indicator of the source and sink cells in the observed population. A sparse graph representation of the diffusion process transforms data analysis of the non-linear structure embedded in the high-dimensional space of single-cell data into inspection of the visible flow using graph algorithms. Hence, ddhodge is a suitable toolkit to visualize, inspect, and subsequently interpret large data sets including, but not limited to, high-throughput measurements of biological data.\n\nThe beta version of ddhodge R package is available at: https://github.com/kazumits/ddhodge

bioinformatics↗

bioRxiv2018

Anti-tumor effects of antimicrobial peptides, targets of the innate immune system, against hematopoietic tumors in Drosophila mxc mutants

The innate immune response is the first line of defense against microbial infections. In Drosophila, three immune pathways induce the synthesis of antimicrobial peptides (AMPs) in the fat body. Recently, it has been reported that certain cationic AMPs exhibit selective cytotoxicity against human cancer cells. However, little is known about their anti-tumor effects. Drosophila mxcmbn1 mutants exhibit malignant hyperplasia in a larval hematopoietic organ called the lymph gland (LG). Here, using RNA-Seq analysis, we found that many immunoresponsive genes, including AMP genes, were up-regulated in the mutants. Down-regulation of these pathways by either a Toll or an imd mutation enhanced the tumor phenotype of the mxc mutants. Conversely, ectopic expression of each of five different AMPs in the fat body significantly suppressed the LG hyperplasia phenotype in the mutants. Thus, we propose that the Drosophila innate immune system can suppress progression of hematopoietic tumors by inducing AMP gene expression. Overexpression of any one of these five AMPs resulted in enhanced apoptosis in the mutant LGs, while no apoptosis signals were detected in controls. We observed that two AMPs, Drosomycin and Defensin, were taken up by circulating hemocyte-like cells, which were associated with LG regions showing reduced cell-to-cell adhesion in the mutants; another AMP, diptericin, was directly localized on the tumors without intermediating hemocytes. These results lead us to conclude that the AMPs have a specific cytotoxic effect that enhance apoptosis exclusively in the tumor cells.\n\nSummary statementAntimicrobial peptides can be associated with tumor cells generated in a hematopoietic tissue in Drosophila mxc mutants and have an anti-tumor effect in suppressing their growth.

developmental biology↗

bioRxiv2018

Cell competition corrects noisy Wnt morphogen gradients to achieve robust patterning

Morphogen signaling forms an activity gradient and instructs cell identities in a signaling strength-dependent manner to pattern developing tissues. However, developing tissues also undergo dynamic morphogenesis, which may produce cells with unfit morphogen signaling and consequent noisy morphogen gradient. Here we show that a cell competition-related system corrects such noisy morphogen gradients. Zebrafish imaging analyses of the Wnt/{beta}-catenin signaling-gradient, which acts as a morphogen to establish embryonic anterior-posterior patterning, revealed that unfit cells with abnormal Wnt/{beta}-catenin activity spontaneously appear and produce noise in the Wnt/{beta}-catenin-gradient. Communication between the unfit and neighboring fit cells via cadherin proteins stimulates the apoptosis of the unfit cells by activating Smad signaling and reactive oxygen species production. This unfit cell elimination is required for proper Wnt/{beta}-catenin-gradient formation and consequent anterior-posterior patterning. Because this gradient controls patterning not only in the embryo but also in adult tissues, this system may support tissue robustness and disease prevention.

cell biology↗