Biology subjects

Hiramatsu, F.

Publications and source records attributed to Hiramatsu, F..

6 recordsLinked to original sources

bioRxiv2026

Contact-based kin discrimination is associated with specific surface lipids in the cannibalistic nematode Pristionchus pacificus

Kin-recognition is widespread, yet its molecular basis remains poorly understood. In the predatory nematode Pristionchus pacificus, kin-recognition prevents cannibalism of close relatives and depends on the peptide SELF-1. Here, we show this behavior is robust to environmental stress but disrupted by a surfactant wash, implicating lipids or other amphiphilic molecules as necessary components for this mechanism. Using 3D-OrbiSIMS, we profiled the outer cuticle of kin-recognition defective self-1 mutants and found these animals exhibit distinct surface lipids. Furthermore, analysis of surface chemistry defective daf-22 mutants alongside self-1;daf-22 double mutants revealed additional, non-overlapping surface lipid profiles, indicating that multiple pathways contribute to shaping surface lipid composition. Importantly, by combining automated behavioral tracking with state-based analysis, we show daf-22 mutants are also kin-recognition defective. Together, these findings demonstrate that the composition of the nematode surface is required to maintain kin identity, with the cuticle acting as a signaling interface that regulates contact-dependent behaviors. Teaser (125 characters)Surface lipid composition correlates with nematode kin-recognition signaling abilities.

animal behavior and cognition↗

bioRxiv2024

Predatory aggression evolved through adaptations to noradrenergic circuits

Behaviors are adaptive traits evolving through natural selection. Crucially, the genetic, molecular, and neural modifications that shape behavioral innovations are poorly understood. Here, we identify specialized adaptations linked to the evolution of aggression in the predatory nematode Pristionchus pacificus. Using machine learning, we identified robust behavioral states associated with aggressive episodes. These depend on modifications to the invertebrate noradrenergic pathway, with octopamine promoting predatory bouts, and tyramine antagonistically suppressing predation. Strikingly, aggression coincides with rewiring of key circuits across nematode evolution. We find additional octopaminergic neurons with morphological adaptations, including neurites extending to teeth-like structures, and expanded receptor expression throughout head sensory neurons gating prey detection. Thus, evolutionary adaptations in noradrenergic circuits facilitated the emergence of aggressive behavioral states associated with complex predatory traits.

animal behavior and cognition↗

bioRxiv2024

Molecular surface chemistry defines nematode development, identity and behaviour

ABSTRACT/SUMMARYChemical signalling facilitates organismal communication and coordinates physiological and behavioural processes. In nematodes, signalling has predominantly focused on secreted molecules leaving the surfaces communicative potential unexplored. By utilising 3D-OrbiSIMS, an advanced surface-sensitive mass spectrometry method, we directly characterised the molecular composition of the outermost regions (50 nm in depth) of Caenorhabditis elegans and Pristionchus pacificus to improve the understanding of surface-mediated chemical communication. We found that nematode surfaces consist of a lipid-dominated landscape (> 81 % C. elegans and > 69 % P. pacificus of all surveyed chemistries) with distinct compositions, which enrich in granularity and complexity through development. The surface-anchored lipids are also species-specific, reflecting evolutionary and ecological adaptations to their environmental niches. By exploring the effect of mutations on lipid production we found the peroxisomal fatty acid {beta}-oxidation component daf-22 is essential for defining the surface molecular fingerprint. This pathway is conserved across species in producing distinct chemical profiles, indicating its fundamental role in lipid metabolism and for maintaining surface integrity and function. Furthermore, we discovered that variations in surface-anchored lipids of C. elegans daf-22 larvae contribute to significantly increased susceptibility to predation by P. pacificus. Therefore, our findings reveal that the nematode surface is not just a passive boundary but a dynamic signalling platform with evolved, species-specific signatures. These molecular mechanisms are pivotal in shaping identity and communication strategies, providing new insights into the evolutionary and ecological dynamics of chemical signalling across organisms. HIGHLIGHTSO_LINematode surfaces are lipid-rich, changing with development. C_LIO_LISurface lipids are species-specific, reflecting adaptations. C_LIO_LIThe daf-22 gene is key in shaping the surface lipid profile. C_LIO_LISurface lipids mediate predator-prey interactions in nematodes. C_LI

systems biology↗

bioRxiv2023

Kin-recognition shapes collective behaviors in the cannibalistic nematode Pristionchus pacificus

Kin-recognition is observed across diverse species forming an important behavioral adaptation influencing organismal interactions. In most species, proximate level mechanisms are poorly characterized, but in the nematode Pristionchus pacificus molecular components regulating its kin-recognition system have been identified which determine its predatory behaviors. This ability prevents the killing of kin however, its impact on other interactions including collective behaviors is unknown. Utilizing pairwise aggregation assays between distinct strains of P. pacificus, we observed aggregation between kin but not distantly related con-specifics. In these assays, only one strain aggregates with solitary behavior induced in the rival. Abolishing predation through Ppa-nhr-40 mutations results in rival strains successfully aggregating together. Additionally, interactions between P. pacificus populations and Caenorhabditis elegans are dominated by P. pacificus which also disrupts C. elegans aggregation dynamics. Thus, aggregating strains of P. pacificus preferentially group with kin, revealing competition and nepotism as previously unknown components influencing collective behaviors in nematodes.

animal behavior and cognition↗

bioRxiv2021

Neural mechanism of experience-dependent sensory gain control in C. elegans

Animals sensory systems adjust their responsiveness to environmental stimuli that vary greatly in their intensity. Here we report the neural mechanism of experience-dependent sensory adjustment, especially gain control, in the ASH nociceptive neurons in Caenorhabditis elegans. Using calcium imaging under gradual changes in stimulus intensity, we find that the ASH neurons of naive animals respond to concentration increases in a repulsive odor 2-nonanone regardless of the magnitude of the concentration increase. However, after preexposure to the odor, the ASH neurons exhibit significantly weak responses to a small gradual increase in odor concentration while their responses to a large gradual increase remain strong. Thus, preexposure changes the slope of stimulus-response relationships (i.e., gain control). Behavioral analysis suggests that this gain control contributes to the preexposure-dependent enhancement of odor avoidance behavior. Mathematical analysis reveals that the ASH response consists of fast and slow components, and that the fast component is specifically suppressed by preexposure. In addition, genetic analysis suggests that G protein signaling is required for the fast component. Thus, our integrative study demonstrates how prior experience dynamically modulates stimulus-response relationships in sensory neurons, eventually leading to adaptive modulation of behavior.

neuroscience↗

bioRxiv2017

Experience-dependent modulation of behavioral features in sensory navigation of nematodes and bats revealed by machine learning

Animal behavior is the final and integrated output of the brain activity. Thus, recording and analyzing behavior is critical to understand the underlying brain function. While recording animal behavior has become easier than ever with the development of compact and inexpensive devices, detailed behavioral data analysis requires sufficient previous knowledge and/or high content data such as video images of animal postures, which makes it difficult for most of the animal behavioral data to be efficiently analyzed to understand brain function. Here, we report a versatile method using a hybrid supervised/unsupervised machine learning approach to efficiently estimate behavioral states and to extract important behavioral features only from low-content animal trajectory data. As proof of principle experiments, we analyzed trajectory data of worms, fruit flies, rats, and bats in the laboratories, and penguins and flying seabirds in the wild, which were recorded with various methods and span a wide range of spatiotemporal scales--from mm to 1000 km in space and from sub-seconds to days in time. We estimated several states during behavior and comprehensively extracted characteristic features from a behavioral state and/or a specific experimental condition. Physiological and genetic experiments in worms revealed that the extracted behavioral features reflected specific neural or gene activities. Thus, our method provides a versatile and unbiased way to extract behavioral features from simple trajectory data to understand brain function.

neuroscience↗