Biology subjects

Kazama, H.

Publications and source records attributed to Kazama, H..

7 recordsLinked to original sources

bioRxiv2025

Divergent evolution of insecticidal protein families across bacteria and ferns

Insecticidal Cry proteins produced by the bacterial insect pathogen Bacillus thuringiensis possess conserved three domains (3D). Two other families of insecticidal proteins--Prb proteins from bacterial symbionts of entomopathogenic nematodes and a marine bacterial pathogen, and IPD113 proteins from ferns--are two-domain (2D) proteins structurally resembling domains I and II of Cry proteins. Despite the structural resemblance, the amino acid sequence identity among these families is only [~]10%, supporting the prevailing view that they evolved independently through convergent evolution. However, the possibility of remote homology and ancient horizontal gene transfer (HGT) has remained largely unexplored. Here, we present evidence supporting divergent evolution of these protein families. We found that proteins containing Cry-like two domains are distributed far more broadly across bacteria, eukaryotes, and archaea than previously recognized. Phylogenetic analyses separated the structurally similar proteins into five clades including Cry, IPD113, Prb, and 2D/3D-mixed clades. Domain-level trees revealed intermixing within domain II, with nematocidal Cry proteins frequently clustering with IPD113 and 2D/3D-mixed clades, suggesting domain swapping events across these clades. Conserved amino acid motifs and domain core structures across clades further support a shared evolutionary origin. Phylogenetic and structural analyses suggest a bacterial origin of the fern IPD113 gene and its horizontal transfer via fungal symbionts, as well as multiple HGT events into diverse terrestrial and marine eukaryotes and archaea. This work redefines the evolutionary landscape of the insecticidal protein families, revealing their unexpectedly wide taxonomic distribution, possibly shaped through bacterial ecological networks and close biological interactions such as symbiosis.

molecular biology↗

bioRxiv2025

Synaptic and potential fluctuations drive representational drift with differential effects on discrimination learning

Large-scale neuronal measurements have revealed continual drift of neural representations without explicit learning, raising fundamental questions about how the brain maintains reliable perception. While representational drift has been studied both experimentally and theoretically, the underlying mechanisms and computational consequences remain unclear. Here, we systematically compare two drift mechanisms--fluctuations in synaptic weights versus membrane potential--using an analytically tractable neural network model with aligned drift magnitude and timescale. We found that both mechanisms preserve representational structure across time regardless of the drift magnitude. However, only synaptic fluctuations maintain discriminability between representations under large drift magnitude. We use a selectivity space to explain how these similar and differential effects on representational drift emerge from the dynamics of individual neuronal tuning. We further examine functional consequences of drift using reversal learning tasks where stimulus-reward associations switch. Both mechanisms enhance single stimulus learning by gradually removing the old associations, but only synaptic fluctuations substantially improved learning of multiple stimuli by preserving the representational structure during drift. Our results reveal distinct computations performed by specific fluctuation mechanisms and explain how representational drift can support both stable and adaptive behavior.

neuroscience↗

bioRxiv2025

Sleep promotes aversive value coding in Drosophila

Sleep is a state of reduced behavioural responsiveness to the external world. Lowered arousal is thought to arise from sensory gating in the brain, yet there is compelling evidence that stimuli can still be processed to some degree. Which aspects of sensory information are processed during sleep remains largely unknown. Here, we perform comprehensive recordings of activity from multiple neuron types during sleep and wakefulness in the Drosophila olfactory association center. We find that baseline activity of dopamine neurons (DANs) is distinct between active, rest and sleep states, enabling a decoder to predict when the fly is asleep. Optogenetic inhibition of DANs acutely induces sleep and lowers odor-evoked arousal, suggesting causality between DAN activity and behavior. We then examine odor processing during sleep, and find that whereas coding of odor identity in Kenyon cells (KCs) remains intact, coding of odor value in DANs is altered. Specifically, DANs encoding positive (attractive) and negative (aversive) values change their odor responses in an opposing manner, producing more aversive odor representations during sleep. Consistent with these changes in neural activity, sleeping flies awoken by odors show reduced approach and increased avoidance behaviour. Taken together, our data reveal that the brain does not simply suppress the propagation of sensory signals during sleep; rather, it utilizes different cell types to retain or modify specific aspects of sensory information. The aversive odor evaluation in DANs may have ethological benefits as it suppresses the motivation to pursue attractive odors during sleep and primes defensive action when aroused by the scent of potential dangers.

neuroscience↗

bioRxiv2023

A lightweight data-driven spiking neural network model of Drosophila olfactory nervous system with dedicated hardware support

Data-driven spiking neural network (SNN) models are vital for understanding the brains information processing at the cellular and synaptic level. While extensive research has focused on developing data-driven SNN models for mammalian brains, their complexity poses challenges in achieving precision. Network topology often relies on statistical inference, and the functions of specific brain regions and supporting neuronal activities remain unclear. Additionally, these models demand significant computational resources. Here, we propose a lightweight data-driven SNN model that strikes a balance between simplicity and reproducibility. We target the Drosophila olfactory nervous system, extracting its network topology from connectome data. The model implemented on an entry-level field-programmable gate array successfully reproduced the functions and characteristic spiking activities of different neuron types. Our approach thus provides a foundation for constructing lightweight in silico models that are critical for investigating the brains information processing mechanisms at the cellular and synaptic level through an analysis-by-construction approach and applicable to edge artificial intelligence (AI) systems.

neuroscience↗

bioRxiv2022

Dopaminergic neurons dynamically update sensory values during navigation

Updating the value of sensory cues through experiences is a critical element of adaptive behavior. Although dopaminergic neurons (DANs) achieve this by driving associative learning, whether they contribute to assessment of sensory values outside the context of association remains largely unexplored. Here we show in Drosophila that DANs in the mushroom body encode the innate value of odors and constantly update the current value by inducing plasticity during olfactory navigation. Simulation of neuronal activity in a network based on the connectome data reproduced the characteristics of DAN responses, proposing a concrete circuit mechanism for computation. Notably, odors alone induced value- and dopamine-dependent changes in the activity of mushroom body output neurons, which store the current value of odors, as well as the behavior of flies steering in a virtual environment. Thus, the DAN circuit known for discrete, associative learning also continuously updates odor values during navigation in a non-associative manner.

neuroscience↗

bioRxiv2022

Odors drive feeding through gustatory receptor neurons in Drosophila

Odors are intimately tied to the taste system to aid food selection and determine the sensory experience of food. However, how smell and taste are integrated in the nervous system to drive feeding remains elusive. We show in Drosophila that odors alone activate gustatory receptor neurons (GRNs), trigger proboscis extension reflex (PER), a canonical taste-evoked feeding behavior, and enhance food intake. Odor-evoked PER requires the function of sugar-sensing GRNs but not olfactory organs. Calcium imaging and electrophysiological recording show that GRNs directly respond to odors. Odor-evoked PER is mediated by the Gr5a receptor, and is bidirectionally modulated by olfactory binding proteins. Finally, odors and sucrose co-applied to GRNs synergistically enhance PER and food consumption. These results reveal a cell-intrinsic mechanism for odor-taste multimodal integration that takes place as early as in GRNs, indicating that unified chemosensory experience is a product of layered integration in peripheral neurons and in the brain.

neuroscience↗

bioRxiv2018

Nanopore formation in the cuticle of the insect olfactory sensillum

Insects sense odorants through small (50-200-nm diameter) pores in the cuticle covering the olfactory sensilla. These nanopores serve as a filter, preventing the entry of larger airborne particles and limiting water loss. Here we show that the nanopores in Drosophila originate from a curved ultrathin film formed in the outermost layer of the cuticle, secreted from specialized plasma membrane protrusions. The gore-tex/Osiris23 gene, encoding an endosomal protein, is required for nanopore formation and odor receptivity, and is expressed specifically in developing olfactory shaft cells. The 24-member Osiris gene family is expressed in various cuticle-secreting cells, and is found only in insect genomes. Some Osiris mutants show defective cuticle-associated functions, suggesting that Osiris genes may provide a platform for investigating functional surface nano-fabrication in insects.\n\nOne Sentence SummaryAn insect-specific endosomal protein promotes the formation of nano-scale pore structures of the apical extracellular matrix.

developmental biology↗