Biology subjects

Taniguchi, D.

Publications and source records attributed to Taniguchi, D..

4 recordsLinked to original sources

bioRxiv2026

Dimerisation and twist reversal of the Lewy fold in α-synuclein mutants with Parkinson's disease and dementia

Dominantly inherited missense and gene dosage mutations in SNCA, the -synuclein gene, cause familial forms of Parkinsons disease and dementia. Here we report the structures of -synuclein filaments from the brains of such individuals. Pathogenic mutations A53T and G51D in SNCA give rise to singlets and doublets of the Lewy fold with a left-handed helical twist in the absence of a peptide-like density for island A. By contrast, filaments from the non-pathogenic variant H50Q consist of singlets of the right-handed Lewy fold with a density for island A, like filaments of wild-type -synuclein. The structures of filaments from homozygous mice transgenic for human mutant A53T -synuclein (line M83) are unlike those from human brains. They are more similar to the multiple system atrophy folds than to the Lewy fold of Parkinsons disease, Parkinsons disease dementia and dementia with Lewy bodies

biophysics↗

bioRxiv2025

Enhanced axonal transport in large vertebrates: KIF5A adaptations in giraffes and pythons

Efficient axonal transport is essential for neuronal function, particularly in species with exceptionally long axons. The Kinesin-1 motor protein KIF5A plays a key role in this process, but whether and how it adapts to the transport demands of large vertebrates remains unclear. Here, we show that KIF5A from giraffes (GcKIF5A) and pythons (PbKIF5A), moves 25% faster than its mouse counterpart (MmKIF5A) on neuronal microtubules in vitro and within axons of cultured mouse hippocampal neurons. This enhanced velocity, driven by three unique amino acid substitutions (R114Q, S155A and Y309F), facilitates long-distance transport in these species and represents a case of convergent evolution. Our structural analysis reveals that accelerated ADP release underlies the increased speed of GcKIF5A. Despite exhibiting a reduced force generation, GcKIF5A maintains efficient cargo transport under load. Furthermore, GcKIF5A exerts less drag in mixed-motor environments, an adaptation particularly beneficial for multiple motor-driven long-distance axonal transport. These findings reveal that KIF5A has evolved specific adaptations to facilitate efficient axonal transport in large vertebrates, highlighting the evolutionary plasticity of kinesin motors.

biophysics↗

bioRxiv2021

Investigating the growth of an engineered strain of Cyanobacteria with an Agent-Based Model and a Recurrent Neural Network

A computational framework combining Agent-Based Models (ABMs) and Deep Learning techniques was developed to help design microbial communities that convert light and CO2 into useful bioproducts. An ABM that accounts for CO2, light, sucrose export rate and cell-to-cell mechanical interactions was used to investigate the growth of an engineered sucrose-exporting strain of Synechococcus elongatus PCC 7942. The ABM simulations produced population curves and synthetic images of colony growth. The curves and the images were analyzed, and growth was correlated to nutrients availability and colonies initial spatial distribution. To speed up the ABM simulations, a metamodel based on a Recurrent Neural Network, RNN, was trained on the synthetic images of growth. This metamodel successfully reproduced the population curves and the images of growth at a lower computational cost. The computational framework presented here paves the road towards designing microbial communities containing sucrose-exporting Synechococcus elongatus PCC 7942 by exploring the solution space in silico first.

microbiology↗

bioRxiv2019

NUFEB: A Massively Parallel Simulator for Individual-based Modelling of Microbial Communities

We present NUFEB, a flexible, efficient, and open source software for simulating the 3D dynamics of microbial communities. The tool is based on the Individual-based Modelling (IbM) approach, where microbes are represented as discrete units and their behaviour changes over time due to a variety of processes. This approach allows us to study population behaviours that emerge from the interaction between individuals and their environment. NUFEB is built on top of the classical molecular dynamics simulator LAMMPS, which we extended with IbM features. A wide range of biological, physical and chemical processes are implemented to explicitly model microbial systems. NUFEB is fully parallelised and allows for the simulation of large numbers of microbes (107 individuals and beyond). The parallelisation is based on a domain decomposition scheme that divides the domain into multiple sub-domains which are distributed to different processors. NUFEB also offers a collection of post-processing routines for the visualisation and analysis of simulation output. In this article, we give an overview of NUFEBs functionalities and implementation details. We provide examples that illustrate the type of microbial systems NUFEB can be used to model and simulate.\n\nAuthor summaryIndividual-based Models (IbM) are one of the most promising frameworks to study microbial communities, as they can explicitly describe the behaviour of each cell. The development of a general-purpose IbM solver should focus on efficiency and flexibility due to the unique characteristics of microbial systems. However, available tools for these purposes present significant limitations. Most of them only facilitate serial computing for single simulation, or only focus on biological processes, but do not model mechanical and chemical processes in detail. In this work, we introduce the IbM solver NUFEB that addresses these shortcoming. The tool facilitates the modelling of much needed biological, chemical, physical and individual microbes in detail, and offers the flexibility of model extension and customisation. NUFEB is also fully parallelised and allows for the simulation of large complex microbial system. In this paper, we first give an overview of NUFEBs functionalities and implementation details. Then, we use NUFEB to model and simulate a biofilm system with fluid dynamics, and a large and complex biofilm system with multiple microbial functional groups and multiple nutrients.\n\nThis is a PLOS Computational Biology Software paper.

microbiology↗