Biology subjects

Kinjo, T.

Publications and source records attributed to Kinjo, T..

8 recordsLinked to original sources

bioRxiv2026

Tractometry reproducibility and generalizability across scanners, scanner models, and acquisition protocols

Diffusion-weighted magnetic resonance imaging (dMRI)-based tractometry enables the quantification of white matter tissue properties in living humans while preserving anatomical specificity. Although tractometry is highly reproducible when the same scanner and acquisition protocol are used, its generalizability across scanners and protocols remains unclear. To address this gap, we performed a traveling-head experiment involving five subjects to evaluate tractometry across progressively different acquisition conditions, including multiple scanners, different scanner models, and two distinct protocols. Tractometry was performed for 20 major white matter tracts using diffusion tensor imaging metrics, neurite orientation dispersion and density imaging (NODDI) metrics, and a semi-quantitative ratio metric (T1w/b0). Generalizability across dataset pairs was quantified using the intraclass correlation coefficient (ICC). Tractometry showed consistently high ICCs when the scanner and protocol were identical; however, ICCs declined as differences in scanner model and acquisition protocol increased. Fractional anisotropy and orientation dispersion index retained relatively high ICCs across these comparisons, whereas other metrics showed marked declines when scanners or protocols differed. ComBat harmonization partially mitigated these declines, but ICCs did not reach the levels observed for datasets acquired using identical scanners and protocols. Finally, the minimum detectable change (MDC) for tractometry in datasets pooled across scanners and protocols varied by tract; for example, the optic radiation showed a lower MDC than the cingulum hippocampus. These findings highlight both the strengths and limitations of tractometry in multisite studies and highlight the importance of quantifying scanner- and protocol-dependent effects for specific metrics and tracts when interpreting measurements from heterogeneous datasets.

neuroscience↗

bioRxiv2026

Enhancing ML-based binder design with high-throughput screening: a comparison of mRNA and yeast display technologies

Recent advances in machine learning (ML)-based protein design methods have enabled the rapid in silico generation of large libraries of miniprotein binders with minimal manual input. While computational design capacity has scaled rapidly, experimental validation methods have lagged, creating a bottleneck in binder discovery pipelines. Here, we apply mRNA display to screen an ML-designed miniprotein binder library and directly compare its performance with the more widely used yeast surface display platform using a single shared DNA library. We screened 2,009 designs targeting the platelet receptor TLT-1 and 3,159 designs targeting the immune receptor B7-H3 across both platforms. While both selection methods reliably identified functional binders, we found that mRNA display preferentially enriched binders with slower dissociation rates. In addition, mRNA display achieved higher library coverage than yeast display, likely rescuing functional designs that are penalized in a cell-based expression system. Biophysical characterization of selected binders from both platforms revealed strong binding affinities and high thermal stabilities. These results showcase the power of integrating ML-based computational design tools with rapid in vitro selection technologies, providing a scalable framework for therapeutic miniprotein discovery. IMPORTANCEMiniprotein binders offer major advantages as next-generation therapeutics, including small size, high stability, and efficient production. In this work, we conduct a side-by-side comparison of mRNA and yeast display as platforms for high-throughput evaluation of de novo miniprotein binders. The binders generated here serve as starting points for therapeutics targeting TLT-1 or B7-H3, two clinically relevant molecules.

bioengineering↗

bioRxiv2026

Computational design of orthogonal TCR α/β interfaces for dual-TCR therapeutics

T-cell receptors (TCRs) recognize peptides presented by MHC, enabling access to intracellular targets that are largely inaccessible to antibodies and difficult to target with small molecules. Despite this potential, their inherent cross-reactivity limits tumor specificity, while single-antigen targeting provides limited coverage of intratumoral heterogeneity. Dual-TCR therapeutics comprising two distinct TCRs could enhance tumor specificity via combinatorial recognition while broadening coverage across heterogeneous antigens. However, practical development of dual-TCR therapeutics has been limited by /{beta} subunit mispairing that prevents efficient production and creates undesired binding properties. Here, we develop orthogonal TCR /{beta} interfaces that prevent subunit mispairing. Using computational multistate design and second-site suppressor strategies implemented in Rosetta, we identified over 250 TCR variants for experimental screening to assess protein stability and pairing fidelity. The top-performing designs achieved approximately 95% correct pairing, as validated by mass spectrometry and X-ray crystallography. Focusing mutations on constant domains and conserved framework regions of variable domains enabled broad applicability across diverse TCRs while preserving antigen recognition. Using these orthogonal interfaces, we developed trispecific T-cell engagers (TriTEs) that target two cancer-testis antigens and CD3 on T cells, demonstrating enhanced potency under dual-antigen engagement (EC50 of 380 fM) while maintaining high activity when targeting cells displaying a single antigen (EC50s of 48 pM and 20 pM). This orthogonal TCR interface technology establishes a generalizable platform for engineering multi-specific immune therapeutics targeting diverse cancer antigens.

bioengineering↗

bioRxiv2025

Intensity Modulation of Trichromatic Split Fluorescent Proteins for Live Cell Mapping

Multiplexed live cell-labeling technologies are essential tools for investigating complex biological systems, yet existing approaches face limitations in achieving reliable discrimination of multiple cell populations. Here, we present color and intensity modulation with split fluorescent proteins for cell labeling (Caterpie), a live cell labeling system that enables high-fidelity identification of multiple cell populations through rational design of split fluorescent proteins. Drawing inspiration from human trichromatic vision, we engineered optimized split fluorescent protein variants--split CFP2, split mNG3A, and split sfCherry3C--and developed a comprehensive library of the 11th {beta}-strand (FP11) tags comprising variable numbers of tandem repeats. Structure-guided protein engineering enhanced the performance of split mNG3A and split sfCherry3C through targeted modifications of their C-terminal sequences and binding interfaces, respectively. By systematically varying the composition and arrangement of FP11 repeats, we selected 20 distinct FP11 tags that enable robust cell population discrimination with 97% accuracy using conventional fluorescence microscopy. In these FP11 tag-expressing cells, we expressed multiple EGF ligands and their receptors and cultured them in bulk to examine the effects of EGF signaling on chemotaxis within the cell population. The results showed that chemotaxis changes according to the intensity of EGFR signaling. The Caterpie system holds significant potential for applications requiring precise identification and tracking of multiple cell populations in complex biological systems.

cell biology↗

bioRxiv2025

PRAME Epitopes are T-Cell Immunovulnerabilities in BRD4::NUTM1 Initiated NUT Carcinoma

BackgroundNUT carcinoma is a rare but highly lethal solid tumor without an effective standard of care. NUT carcinoma is caused by bromodomain-containing NUTM1 fusion oncogenes, most commonly BRD4::NUTM1. BRD4::NUTM1 recruits p300 to acetylate H3K27 forming expansive stretches of hyperacetylated chromatin called "megadomains" with the overexpression of corresponding oncogenes, including MYC. We hypothesized that transcriptional dysregulation caused by BRD4::NUTM1 would lead to the generation of cancer-specific antigens that could be therapeutically actionable. MethodsWe integrated genomics, computational antigen prediction software, targeted immunopeptidomics using single- and double-labeled peptide standards, and gain/loss-of-function genetic experiments on a panel of cell lines (N=5), a patient derived xenograft, a tissue microarray (N=77), and patient samples from the Tempus AI Sequencing Database harboring evidence of NUTM1 fusions (N=165). We created an PRAME425 T-cell receptor x SP34 CD3 bispecific molecule modeled after brenetafusp, an PRAME425 T-cell receptor bispecific T-cell engager, as well as PRAME425 TCR T-cells based on anzutresgene autoleucel and we applied these products to NUT carcinoma cells in vitro. ResultsWe identified PRAME as the most commonly expressed cancer/testis antigen in patient samples harboring the three canonical NUT carcinoma fusions (BRD4::NUTM1, BRD3::NUTM1, and NSD3::NUTM1). Additionally, 56% (43/77) of NUT carcinoma tissue microarray samples stained positive for PRAME. BRD4::NUTM1 expression in HEK 293T cells enhanced PRAME levels and BRD4::NUTM1 knockout in NUT carcinoma cells reduced PRAME levels. Immunopeptidomics detected more PRAME-derived HLA ligands (N=9) than all other cancer/testis antigens combined (N=5). Targeted mass spectrometry detected the HLA-A*02:01/SLLQHLIGL (PRAME425) epitope in 100% (4/4) of HLA-A*02+, PRAME+ NUT carcinoma samples at higher levels (>0.01 fM) than HLA-A*02:01/RLDQLLRHV (PRAME312) or HLA-A*02:01/YLHARLREL (PRAME462). The PRAME425 T-cell receptor x SP34 CD3 bispecific molecule and PRAME425 TCR T-cells each exhibited potent, T-cell mediated cytotoxicity against PRAME+ NUT carcinoma cells. ConclusionsPRAME is highly and frequently expressed in NUT carcinoma and the most common oncoprotein causing NUT carcinoma, BRD4::NUTM1, contributes to these high PRAME levels. PRAME epitopes presented by HLA Class I are a previously unrecognized therapeutic vulnerability for NUT carcinoma that warrant clinical trials testing PRAME targeted immunotherapies in this neglected patient population. What is already known on this topicNUT carcinoma is a devastating malignancy that is recalcitrant to cytotoxic chemotherapy, T-cell checkpoint blockade, and targeted therapies in the form of bromodomain inhibitors. What this study addsNUT carcinoma tumors are high in the cancer/testis gene PRAME. The oncogene most commonly causing NUT carcinoma, BRD4::NUTM1, contributes to these high levels. NUT carcinoma cells present PRAME epitopes on HLA Class I molecules and are susceptible to PRAME-directed, T-cell mediated cytotoxicity. How this study might affect research, practice or policyOur results argue for phase I/II clinical trials testing PRAME immunotherapies like brenetafusp or anzutresgene autoleucel in PRAME+ NUT carcinoma patients. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=149 SRC="FIGDIR/small/642090v3_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@495654org.highwire.dtl.DTLVardef@c2b975org.highwire.dtl.DTLVardef@1de507org.highwire.dtl.DTLVardef@a76d33_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

In silico evolution of protein binders with deep learning models for structure prediction and sequence design

There has been considerable progress in the development of computational methods for designing protein-protein interactions, but engineering high-affinity binders without extensive screening and maturation remains challenging. Here, we test a protein design pipeline that uses iterative rounds of deep learning (DL)-based structure prediction (AlphaFold2) and sequence optimization (ProteinMPNN) to design autoinhibitory domains (AiDs) for a PD-L1 antagonist. Inspired by recent advances in therapeutic design, we sought to create autoinhibited (or masked) forms of the antagonist that can be conditionally activated by proteases. Twenty-three de novo designed AiDs, varying in length and topology, were fused to the antagonist with a protease sensitive linker, and binding to PD-L1 was tested with and without protease treatment. Nine of the fusion proteins demonstrated conditional binding to PD-L1 and the top performing AiDs were selected for further characterization as single domain proteins. Without any experimental affinity maturation, four of the AiDs bind to the PD-L1 antagonist with equilibrium dissociation constants (KDs) below 150 nM, with the lowest KD equal to 0.9 nM. Our study demonstrates that DL-based protein modeling can be used to rapidly generate high affinity protein binders. Significance statementProtein-protein interactions are critical to most processes in biology, and improved methods for designing protein binders will enable the creation of new research reagents, diagnostics, and therapeutics. In this study, we show that a deep learning-based method for protein design can create high-affinity protein binders without the need for extensive screening or affinity maturation.

biophysics↗

bioRxiv2020

Hypoxia-tolerant vascular endothelial growth factor-A (VEGF-A) and the genetic variations of VEGFA in Sherpa highlanders

Sherpa highlanders demonstrate extraordinary tolerance to hypoxia at high altitudes, partly by one of the adaptation mechanisms promoting increases of microcirculatory blood flow and capillary density at high altitude for restoring oxygen supply to tissues. Hypoxia stimulates vascular endothelial growth factor (VEGF), which is an important signaling protein involved in hypoxia-stimulated vasculogenesis and angiogenesis. Our present study included 51 Sherpas dwelling in Namche Bazaar village (3440 m) and 76 non-Sherpa lowlanders residing in Kathmandu (1300 m) in Nepal. In these participants, we measured plasma VEGF-A concentrations and genotyped five single-nucleotide polymorphisms (SNPs) of VEGFA: rs699947, rs8333061, rs1570360, and rs2010963 in the 5'-untranslated region (5'-UTR); and rs3025039 in the 3'-UTR. The average circulating VEGF-A level in Sherpas did not respond to hypoxia at the high altitude in 3440 m, remaining equivalent to the level in non-Sherpa lowlanders at low altitude. Allele discriminations for the analyzed SNPs revealed significant genetic divergences of rs699947, rs8333061, and rs2010963 in Sherpa highlanders compared with non-Sherpa lowlanders, East Asians, South Asians, and the global population; however, consistency with the indigenous Tibetan highlanders from the Tibet Plateau. On the other hand, the SNP rs3025039 in the 3'-UTR presented constant preserved genetic variation among global populations. Our findings indicated that the physiological sea-level VEGF-A concentration in Sherpa highlanders at high altitude was probably linked with the significant variations of VEGFA in Sherpas that regulate the gene expression in a manner of tolerance to hypoxia through production of the optimal biological level of VEGF-A at high altitudes. Precise angiogenesis at high altitude contributes to the adaptive levels of capillary density and microcirculation, providing efficient and effective diffusion of oxygen to tissues and representing human adaptation to high-altitude hypoxia environment. Author summarySherpa highlanders demonstrate extraordinary tolerance to hypoxia at high altitudes, partly by one of the adaptation mechanisms promoting increases of microcirculatory blood flow and capillary density at high altitude for restoring oxygen supply to tissues. Vascular endothelial growth factor (VEGF) is mainly stimulated by hypoxia, and is an important signaling protein involved in hypoxia-stimulated vasculogenesis and angiogenesis. Interestingly, we found that the circulating VEGF-A level in Sherpa highlanders did not respond to hypoxia at high altitude. Furthermore, allele discrimination of the single nucleotide polymorphisms (SNPs) of VEGFA revealed significant divergences of rs699947, rs8333061, and rs2010963 within the VEGFA regulation region in Sherpa highlanders compared to the non-Sherpa lowlanders, East Asians, South Asians, and the global population; however, consistency with Tibetan highlanders from the Tibet Plateau. We propose that the hypoxia-tolerant circulating VEGF-A level in Sherpa highlanders is linked with the genetic variations of VEGFA, contributing to human adaptation to high-altitude hypoxic environments.

genetics↗

bioRxiv2020

Population genetic structure in the insular Ryukyu flying fox, Pteropus dasymallus

Small isolated populations are vulnerable to both stochastic events and the negative consequences of genetic drift. For threatened species, the genetic management of such populations has therefore become a crucial aspect of conservation. Flying foxes (Pteropus spp, Chiroptera) are keystone species with essential roles in pollination and seed dispersal in tropical and subtropical ecosystems. Yet many flying fox species are also of conservation concern, having experienced dramatic population declines driven by habitat loss and hunting. The Ryukyu flying fox (Pteropus dasymallus) ranges from Japan and Taiwan to the northern Philippines, and has undergone precipitous population crashes on several islands in recent decades. To assess population genetic structure and diversity in P. dasymallus, and its likely causes, we analyzed mitochondrial and microsatellite DNA. Both markers showed significant genetic differentiation among most island populations with patterns of isolation-by-distance. However, while mitochondrial haplotypes showed some mixing across the region, likely reflecting historical colonization and/or dispersal events, microsatellites markers showed clear subdivisions corresponding to the position of deep ocean trenches. The current distribution of P. dasymallus and its subspecific diversity therefore appears to have arisen through vicariance coupled with a long history of restricted gene flow across oceanic barriers. We conclude that isolated island subgroups should be managed separately, with efforts directed at reducing further declines.

ecology↗