Biology subjects

Hiramatsu, K.

Publications and source records attributed to Hiramatsu, K..

7 recordsLinked to original sources

bioRxiv2026

Data-driven spectroscopic dictionaries and detector-calibrated inference for photon-limited Raman hyperspectral imaging of living cells

Label-free Raman imaging of living cells is photon limited: at exposures compatible with cellular dynamics, single-pixel spectra carry about one count per channel on a dominant smooth background. We present an unmixing framework in which the decoder of a physics-constrained autoencoder is restricted to a data-driven spectroscopic dictionary: band centers,widths, and pseudo-Voigt shapes are measured from the dataset and fixed, and the network learns only nonnegative band amplitudes, a smooth B-spline background, and a per-pixel gain.First, on slit-scanning images of HeLa cells (532 nm) the dictionary yields spike-free component spectra that read as band tables, including a resonance-enhanced cytochrome-c-associated component matching literature spectra, and the most stable decomposition against the component number. Second, the dictionary and initialization calibrated at 1 s exposure perline transfer to 100 ms per line (12 s sweeps): cytochrome-c spectral identity survives a single sweep (correlation 0.92) while its map remains photon limited; the dictionary provides spectral physicality, and the transferred initialization prevents a structural collapse that global map correlations miss; in a measurement-derived phantom the dictionary estimator holds thecytochrome-c spectrum to 17-19{degrees} spectral angle at 100 ms, where classical factorizations and free decoders lose it (55-64{degrees}). Estimation on the count-equivalent detector output uses a calibrated shifted-Poisson quasi-likelihood. Third, evaluation must be time matched:correlation against a separately acquired reference saturates through slow specimen drift and acquisition mismatch rather than photon noise, and the self-consistency of learned denoisers is inflated by shared bias; time-matched self-consistency and independent cross-checks areproposed.

cell biology↗

bioRxiv2026

Long-term single-particle tracking by NIR imaging using Au42 (gold) quantum needles

Single-particle tracking (SPT) over time enables direct observation of molecular transport and interactions in living cells. Fluorescence-based SPT has provided insights into intracellular processes such as endocytosis, receptor signaling, and drug delivery. Extending the observation window to several hours and beyond is critical for capturing slow intracellular dynamics, including the full course of endosomal trafficking, the long-term accumulation of particles within subcellular compartments, and transitions between transport modes that occur on hour-scale timescales. However, long-term intracellular SPT under visible-wavelength excitation remains challenging because fluorescence probes generally suffer from photobleaching and phototoxicity. While near-infrared (NIR) excitation can simultaneously mitigate these issues, generally weak emission of NIR-emitting dyes has hindered its wide application in long-term SPT. Here, we demonstrate long-term NIR SPT using atomically precise gold quantum needles, Au42(PET)32 (PET = 2-phenylethanethiolate). Continuous tracking of intracellular particles in living HEK293 cells was achieved for up to 12 h. Trajectory analysis revealed temporal transitions between directional and diffusive transport, as well as the accumulation of multiple particles within localized intracellular domains over several-hour timescales. The high photostability of Au42, combined with low phototoxicity of NIR excitation, enables visualization of intracellular transport dynamics over timescales difficult to access using conventional visible fluorescent probes. These results establish Au42-based NIR imaging as a platform for long-term, low-phototoxicity intracellular SPT and provide a framework for investigating slow intracellular dynamics in living systems.

biophysics↗

bioRxiv2025

Broadband electronic resonance coherent anti-Stokes/Stokes Raman scattering microscopy

Coherent Raman imaging (CRI) enables label-free chemical imaging based on intrinsic molecular vibrations, but its applicability is often limited by low sensitivity, hindering the detection of low-abundance biomolecules. While electronic resonance significantly enhances sensitivity, most resonance CRI implementations rely on narrowband excitation and/or detection, which limits spectral coverage and makes it difficult to distinguish target molecules from backgrounds. Here we address these challenges by developing broadband electronic-resonance coherent anti-Stokes/Stokes Raman scattering (BER-CARS/CSRS) microscopy. We show that BER-CARS/CSRS enables highly sensitive, label-free imaging of endogenous chromophores with broad spectral coverage of the entire fingerprint region. Specifically, we captured time-lapse images across the fingerprint region, visualizing low-abundance cytochromes alongside abundant biomolecules (lipids, proteins, nucleic acids) in living HEK293 cells. Furthermore, we applied the method to complex biological tissues, mapping distinct distributions of cytochromes in mouse brain slices, highlighting their characteristic localizations in the cortex and the cerebral ventricle wall. Our results demonstrate that BER-CARS/CSRS is a powerful platform for highly sensitive chemical imaging, from large-area tissue mapping to organelle-level dynamics. By coupling resonance enhancement with broadband fingerprinting, BER-CARS/CSRS enables dynamic, label-free phenotyping of mitochondrial and physiological states from single cells to tissues, opening a path to quantitative, slide-scale chemical histopathology and intraoperative margin assessment.

bioengineering↗

bioRxiv2024

Label-free visualization of ciliary rootlets in mouse brain

Neuronal primary cilia are important role in brain development, sensory perception and neurogenesis. Rootletin, a fibrous protein composed of coiled-coil motifs, is a major structural component of ciliary rootlets and is essential for understanding ciliary functions. However, the precise mechanisms by which Rootletin influences ciliary dynamics and impacts neuronal function remain largely unknown, primarily due to the challenges in visualizing these structures. Here, we describe a label-free, rapid, and highly sensitive method to visualize Rootletin molecules in brain tissue. This platform integrates a second harmonic generation (SHG) microscope and background reduction by a one-step chemical pretreatment. Additionally, we employ coherent anti-Stokes Raman scattering imaging to simultaneously determine the cellular regions and intracellular locations of SHG signals. By applying this multimodal multiphoton imaging to mouse hippocampus, we found that neuronal ciliary rootlets were found to exhibit highly organized specific intracellular distributions. Moreover, the formation of ciliary rootlets precedes that of primary cilia. These findings highlight the utility of our label-free imaging platform in developmental and neuroscience research, providing a new tool to characterize ciliary dynamics and neuronal function.

biophysics↗

bioRxiv2024

Flow zoometry of Drosophila

Drosophila serves as a highly valuable model organism across numerous fields including genetics, immunology, neuroscience, cancer biology, and developmental biology. Central to Drosophila-based biological research is the ability to perform comprehensive genetic or chemical screens. However, this research is often limited by its dependence on laborious manual handling and analysis, making it prone to human error and difficult to discern statistically significant or rare events amid the noise of individual variations resulting from genetic and environmental factors. In this article we present flow zoometry, a whole-animal equivalent of flow cytometry for large-scale, individual-level, high-content screening of Drosophila. Our flow zoometer automatically clears the tissues of Drosophila melanogaster, captures three-dimensional (3D) multi-color fluorescence tomograms of single flies with single-cell volumetric resolution at an unprecedented throughput of over 1,000 animals within 48 hours (24 hr for clearing; 24 hr for imaging), and performs AI-enhanced data-driven analysis - a task that would traditionally take months or years with manual techniques. To demonstrate its broad applications, we employed the flow zoometer in various laborious screening assays, including those in toxicology, genotyping, and tumor screening. Flow zoometry represents a pivotal evolution in high-throughput screening technology: previously from molecules to cells, now from cells to whole animals. This advancement serves as a foundational platform for "statistical spatial biology", to improve empirical precision and enable serendipitous discoveries across various fields of biology.

bioengineering↗

bioRxiv2021

High-throughput Raman-activated cell sorting in the fingerprint region

Cell sorting is the workhorse of biological research and medicine. Cell sorters are commonly used to sort heterogeneous cell populations based on their intrinsic features. Raman-activated cell sorting (RACS) has recently received considerable interest by virtue of its ability to discriminate cells by their intracellular chemical content, in a label-free manner. However, broad deployment of RACS beyond lab-based demonstrations is hindered by a fundamental trade-off between throughput and measurement bandwidth (i.e., cellular information content). Here we overcome this trade-off and demonstrate broadband RACS in the fingerprint region (300 - 1,600 cm-1) with a record high throughput of ~50 cells per second. This represents a 100x throughput increase compared to previous demonstrations of broadband fingerprint-region RACS. To show the utility of our RACS, we demonstrate real-time label-free sorting of microalgal cells based on their accumulation of carotenoids and polysaccharide granules. These results hold promise for medical, biofuel, and bioplastic applications.

bioengineering↗

bioRxiv2019

A non-mosaic humanized mouse model of Down syndrome, trisomy of the long arm of human chromosome 21 in mouse chromosome background

Down syndrome (DS) is a complex human condition, and animal models trisomic for human chromosome 21 (HSA21) genes or orthologs provide insights into better understanding and treating DS. However, HSA21 orthologs are distributed into three mouse chromosomes, preventing us from generating mouse models trisomy of a complete set of HSA21 orthologs. The only existing humanized mouse DS model, Tc1, carries a HSA21 with over 20% of protein coding genes (PCGs) disrupted. More importantly, due to the human centromere, Tc1 is mosaic (a mix of euploid and trisomic cells), which makes every mouse unique and compromises interpretation of results. Here, we used mouse artificial chromosome (MAC) technology to "clone" the 34 MB long arm of HSA21 (HSA21q). Through multiple steps of microcell-mediated chromosome transfer we created a new humanized DS mouse model, Tc(HSA21q;MAC)1Yakaz ("TcMAC21"). Constitutive EGFP expression from the transchromosome and fluorescent in situ hybridization validate that TcMAC21, containing a hybrid chromosome of HSA21q and mouse centromere, is not mosaic. Whole genome sequencing shows that TcMAC21 contains a nearly complete copy of HSA21q with 93% of intact PCGs, while RNA-seq and additional mRNA/protein expression analyses confirm that PCGs are transcribed and regulated. A battery of tests show that TcMAC21 recapitulates many DS phenotypes including morphological anomalies in heart, craniofacial skeleton and brain, pathologies at molecular and cellular level, and impairments in learning, memory and synaptic plasticity. TcMAC21 is the most complete mouse model of DS extant and has potential for supporting a wide range of basic and preclinical research. Significance StatementIn the last 25 years, mouse models of trisomy 21 have supported research into Down syndrome, from defining the basis for developmental effects up to support for clinical trials. However, existing models have significant shortfalls, especially for preclinical studies. These deficiencies include incomplete or inappropriate representation of trisomic genes, absence of an extra chromosome, and mosaicism. Using cutting edge technologies we produced a mouse artificial chromosome containing the entire 34Mb long arm of human chromosome 21 and, with assisted reproductive technologies, established it in the germ line of mice. This trisomic mouse manifests developmental and functional features of Down syndrome, including hippocampal-based learning and memory deficits. This is the most complete model of Down syndrome produced to date.

genetics↗