Neuroprotective Potential of L-Glutamate Transporters in Human Induced Pluripotent Stem Cell-Derived Neural Cells against Excitotoxicity.

Human induced pluripotent stem cell (hiPSC)-derived neural cells have started to be used in safety/toxicity tests at the preclinical stage of drug development. As previously reported, hiPSC-derived neurons exhibit greater tolerance to excitotoxicity than those of primary cultures of rodent neurons; however, the underlying mechanisms remain unknown. We here investigated the functions of L-glutamate (L-Glu) transporters, the most important machinery to maintain low extracellular L-Glu concentrations, in hiPSC-derived neural cells. We also clarified the contribution of respective L-Glu transporter subtypes. At 63 days in vitro (DIV), we detected neuronal circuit functions in hiPSC-derived neural cells by a microelectrode array system (MEA). At 63 DIV, exposure to 100 µM L-Glu for 24 h did not affect the viability of neural cells. 100 µM L-Glu in the medium decreased to almost 0 µM in 60 min. Pharmacological inhibition of excitatory amino acid transporter 1 (EAAT1) and EAAT2 suppressed almost 100% of L-Glu decrease. In the presence of this inhibitor, 100 µM L-Glu dramatically decreased cell viability. These results suggest that in hiPSC-derived neural cells, EAAT1 and EAAT2 are the predominant L-Glu transporters, and their uptake potentials are the reasons for the tolerance of hiPSC-derived neurons to excitotoxicity.

Synchronous spike patterns in differently mixed cultures of human iPSC-derived glutamatergic and GABAergic neurons.

Human induced-pluripotent stem cell (hiPSC)-derived neurons develop organized neuronal networks under in vitro cultivation conditions. Here, using a multielectrode array system, we examined whether the spike patterns of hiPSC-derived neuronal populations differed in a manner that depended on the proportions of glutamatergic and gamma-aminobutyric acid (GABA)ergic neurons in the cultures. Synchronous burst firing events spanning multiple electrodes became more frequent as the number of days in culture increased. However, at all developmental stages, the event rates of synchronous burst firing, the repertoires of synchronous burst firing, and the frequencies of sporadic spikes did not differ in cultures with different glutamatergic-to-GABAergic ratios. Pharmacological blockade of GABAergic synaptic transmission increased the frequencies of spike patterns specifically in cultures with lower glutamatergic-to-GABAergic ratios. These results demonstrate that a robust homeostatic property of developing hiPSC-derived neuronal networks in culture counteracts chronically imbalanced glutamatergic and GABAergic signaling.

Temporally coordinated spiking activity of human induced pluripotent stem cell-derived neurons co-cultured with astrocytes.

In culture conditions, human induced-pluripotent stem cells (hiPSC)-derived neurons form synaptic connections with other cells and establish neuronal networks, which are expected to be an in vitro model system for drug discovery screening and toxicity testing. While early studies demonstrated effects of co-culture of hiPSC-derived neurons with astroglial cells on survival and maturation of hiPSC-derived neurons, the population spiking patterns of such hiPSC-derived neurons have not been fully characterized. In this study, we analyzed temporal spiking patterns of hiPSC-derived neurons recorded by a multi-electrode array system. We discovered that specific sets of hiPSC-derived neurons co-cultured with astrocytes showed more frequent and highly coherent non-random synchronized spike trains and more dynamic changes in overall spike patterns over time. These temporally coordinated spiking patterns are physiological signs of organized circuits of hiPSC-derived neurons and suggest benefits of co-culture of hiPSC-derived neurons with astrocytes.

Evaluation of neurotoxicity for pesticide-related compounds in human iPS cell-derived neurons using microelectrode array.

In vivo evaluations of chemicals in neurotoxicity have certain limitations due to the considerable time and cost required, necessity of extrapolation from rodents to humans, and limited information on toxicity mechanisms. To address this issue, the development of in vitro test methods using new approach methodologies (NAMs) is important to evaluate the chemicals in neurotoxicity. Microelectrode array (MEA) allows the assessment of changes in neural network activity caused by compound administration. However, studies on compound evaluation criteria are scarce. In this study, we evaluated the impact of pesticides on neural activity using MEA measurements of human iPSC-derived neurons. A principal component analysis was performed on the electrical physiological parameters obtained by MEA measurements, and the influence of excessive neural activity due to compound addition was defined using the standard deviation of neural activity with solvent addition as the reference. By using known seizurogenic compounds as positive controls for neurotoxicity in MEA and evaluating pesticides with insufficient verification of their neurotoxicity in humans, we demonstrated that these pesticides exhibit neurotoxicity in humans. In conclusion, our data suggest that the neurotoxicity evaluation method in human iPSC neurons using MEA measurements could be one of the in vitro neurotoxicity test methods that could replace animal experiments.

Development of an In Vitro Assessment Method for Chemotherapy-Induced Peripheral Neuropathy (CIPN) by Integrating a Microphysiological System (MPS) with Morphological Deep Learning of Soma and Axonal Images.

Several anticancer drugs used in cancer therapy induce chemotherapy-induced peripheral neuropathy (CIPN), leading to dose reduction or therapy cessation. Consequently, there is a demand for an in vitro assessment method to predict CIPN and mechanisms of action (MoA) in drug candidate compounds. In this study, a method assessing the toxic effects of anticancer drugs on soma and axons using deep learning image analysis is developed, culturing primary rat dorsal root ganglion neurons with a microphysiological system (MPS) that separates soma from neural processes and training two artificial intelligence (AI) models on soma and axonal area images. Exposing the control compound DMSO, negative compound sucrose, and known CIPN-causing drugs (paclitaxel, vincristine, oxaliplatin, suramin, bortezomib) for 24 h, results show the somatic area-learning AI detected significant cytotoxicity for paclitaxel (* p < 0.05) and oxaliplatin (* p < 0.05). In addition, axonal area-learning AI detected significant axonopathy with paclitaxel (* p < 0.05) and vincristine (* p < 0.05). Combining these models, we detected significant toxicity in all CIPN-causing drugs (** p < 0.01) and could classify anticancer drugs based on their different MoA on neurons, suggesting that the combination of MPS-based culture segregating soma and axonal areas and AI image analysis of each area provides an effective evaluation method to predict CIPN from low concentrations and infer the MoA.

An In Vitro Assessment Method for Chemotherapy-Induced Peripheral Neurotoxicity Caused by Anti-Cancer Drugs Based on Electrical Measurement of Impedance Value and Spontaneous Activity.

Chemotherapy-induced peripheral neurotoxicity (CIPN) is a major adverse event of anti-cancer drugs, which still lack standardized measurement and treatment methods. In the present study, we attempted to evaluate neuronal dysfunctions in cultured rodent primary peripheral neurons using a microelectrode array system. After exposure to typical anti-cancer drugs (i.e., paclitaxel, vincristine, oxaliplatin, and bortezomib), we successfully detected neurotoxicity in dorsal root ganglia neurons by measuring electrical activities, including impedance value and spontaneous activity. The impedance value decreased significantly for all compounds, even at low concentrations, which indicated cell loss and/or neurite degeneration. The spontaneous activity was also suppressed after exposure, which suggested neurotoxicity again. However, an acute response was observed for paclitaxel and bortezomib before toxicity, which showed different mechanisms based on compounds. Therefore, MEA measurement of impedance value could provide a simple assessment method for CIPN, combined with neuronal morphological changes.

Large-Area Field Potential Imaging Having Single Neuron Resolution Using 236 880 Electrodes CMOS-MEA Technology.

The electrophysiological technology having a high spatiotemporal resolution at the single-cell level and noninvasive measurements of large areas provide insights on underlying neuronal function. Here, a complementary metal-oxide semiconductor (CMOS)-microelectrode array (MEA) is used that uses 236 880 electrodes each with an electrode size of 11.22 × 11.22 µm and 236 880 covering a wide area of 5.5 × 5.9 mm in presenting a detailed and single-cell-level neural activity analysis platform for brain slices, human iPS cell-derived cortical networks, peripheral neurons, and human brain organoids. Propagation pattern characteristics between brain regions changes the synaptic propagation into compounds based on single-cell time-series patterns, classification based on single DRG neuron firing patterns and compound responses, axonal conduction characteristics and changes to anticancer drugs, and network activities and transition to compounds in brain organoids are extracted. This detailed analysis of neural activity at the single-cell level using the CMOS-MEA provides a new understanding of the basic mechanisms of brain circuits in vitro and ex vivo, on human neurological diseases for drug discovery, and compound toxicity assessment.

Responses to antibiotics in human iPSC-derived neurons based on the clinical antibiotic-associated encephalopathy classification.

Antibiotic-associated encephalopathy (AAE) is a central nervous system disorder caused by antibiotics administration and classified into three types based on clinical symptoms. Type 1 AAE causes seizures and myoclonus, type 2 causes psychiatric symptoms, and type 3 is characterized by cerebellar ataxia. In this study, we investigated whether the electrical activity of in vitro human iPSC-derived neurons to antibiotics could be classified based on the 3 types of AAEs classified by clinical symptoms. Glutamatergic, GABAergic neurons and astrocytes differentiated from human iPS cells were seeded on micro-electrode array (MEA). The cumulative administration of 13 different antimicrobials detected changes in neural activity that differed according to AAE type. Next, we classified the antimicrobials by principal component analysis (PCA) and confirmed the AAE type of each agent. We found that Types 1-3 AAE agents were distributed separately. The classification of antibiotics depending on electrophysiological response characteristics was consistent with the clinical practice classification of AAEs. In conclusion, the combination of electrophysiological responses of human iPS cell-derived neural networks measured by MEA plus multivariate analysis methods will effectively detect and classify antibiotics developmental risks.

Detection of astrocytic slow oscillatory activity and response to seizurogenic compounds using planar microelectrode array.

Since the development of the planar microelectrode array (MEA), it has become popular to evaluate compounds based on the electrical activity of rodent and human induced pluripotent stem cell (iPSC)-derived neurons. However, there are no reports recording spontaneous human astrocyte activity from astrocyte-only culture sample by MEA. It is becoming clear that astrocytes play an important role in various neurological diseases, and astrocytes are expected to be excellent candidates for targeted therapeutics for the treatment of neurological diseases. Therefore, measuring astrocyte activity is very important for drug development for astrocytes. Recently, astrocyte activity has been found to be reflected in the low-frequency band < 1 Hz, which is much lower than the frequency band for recording neural activity. Here, we separated the signals obtained from human primary astrocytes cultured on MEA into seven frequency bands and successfully recorded the extracellular electrical activity of human astrocytes. The slow waveforms of spontaneous astrocyte activity were observed most clearly in direct current potentials < 1 Hz. We established nine parameters to assess astrocyte activity and evaluated five seizurogenic drug responses in human primary astrocytes and human iPSC-derived astrocytes. Astrocytes demonstrated the most significant dose-dependent changes in pilocarpine. Furthermore, in a principal component analysis using those parameter sets, the drug responses to each seizurogenic compound were separated. In this paper, we report the spontaneous electrical activity measurement of astrocytes alone using MEA for the first time and propose that the MEA measurement focusing on the low-frequency band could be useful as one of the methods to assess drug response in vitro.

In Vitro Pain Assay Using Human iPSC-Derived Sensory Neurons and Microelectrode Array.

Drug-induced peripheral neuropathy occurs as an adverse reaction of chemotherapy. However, a highly accurate method for assessing peripheral neuropathy and pain caused by compounds has not been established. The use of human-induced pluripotent stem cell (hiPSC)-derived sensory neurons does not require animal experiments, and it is considered an effective method that can approach extrapolation to humans. In this study, we evaluated the response to pain-related compounds based on neural activities using in vitro microelectrode array (MEA) measurements in hiPSC-derived sensory neurons. Cultured sensory neurons exhibited gene expression of the Nav1.7, TRPV1, TRPA1, and TRPM8 channels, which are typical pain-related channels. Channel-dependent evoked responses were detected using the TRPV1 agonist capsaicin, a TRPA1 agonist, allyl isothiocyanate (AITC), and TRPM8 agonist menthol. In addition, the firing frequency increased with an increase in temperature from 37°C to 46°C, and temperature sensitivity was observed. In addition, the temperature of the peak firing rate differed among individual neurons. Next, we focused on the increase in cold sensitivity, which is a side effect of the anticancer drug oxaliplatin, and evaluated the response to AITC in the presence and absence of oxaliplatin. The response to AITC increased in the presence of oxaliplatin in a concentration-dependent manner, suggesting that the increased cold sensitivity in humans can be reproduced in cultured hiPSC-derived sensory neurons. The in vitro MEA system using hiPSC-derived sensory neurons is an alternative method to animal experiments, and it is anticipated as a method for evaluating peripheral neuropathy and pain induced by compounds.

A functional neuron maturation device provides convenient application on microelectrode array for neural network measurement.

BACKGROUND: Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation. METHODS: In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis. RESULTS: We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons. CONCLUSIONS: Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA.

Histograms of Frequency-Intensity Distribution Deep Learning to Predict the Seizure Liability of Drugs in Electroencephalography.

Detection of seizures as well as that of seizure auras is effective in improving the predictive accuracy of seizure liability of drugs. Whereas electroencephalography has been known to be effective for the detection of seizure liability, no established methods are available for the detection of seizure auras. We developed a method for detecting seizure auras through machine learning using frequency-characteristic images of electroencephalograms. Histograms of frequency-intensity distribution prepared from electroencephalograms of rats analyzed during seizures induced with 4-aminopyridine (6 mg/kg), strychnine (3 mg/kg), and pilocarpine (400 mg/kg), were used to create an artificial intelligence (AI) system that learned the features of frequency-characteristic images during seizures. The AI system detected seizure states learned in advance with 100% accuracy induced even by convulsants acting through different mechanisms, and the risk of seizure before a seizure was detected in general observation. The developed AI system determined that the unlearned convulsant Tramadol (150 mg/kg) was the risk of seizure and the negative compounds aspirin and vehicle were negative. Moreover, the AI system detected seizure liability even in electroencephalography data associated with the use of 4-aminopyridine (3 mg/kg), strychnine (1 mg/kg), and pilocarpine (150 mg/kg), which did not induce seizures detectable in general observation. These results suggest that the AI system developed herein is an effective means for electroencephalographic detection of seizure auras, raising expectations for its practical use as a new analytical method that allows for the sensitive detection of seizure liability of drugs that has been overlooked previously in preclinical studies.

Can We Panelize Seizure?

Seizure liability remains a significant cause of attrition in drug discovery and development, leading to loss of competitiveness, delays, and increased costs. Current detection methods rely on observations made in in vivo studies intended to support clinical trials, such as tremors or other abnormal movements. These signs could be missed or misinterpreted; thus, definitive confirmation of drug-induced seizure requires a follow-up electroencephalogram study. There has been progress in in vivo detection of seizure using automated video systems that record and analyze animal movements. Nonetheless, it would be preferable to have earlier prediction of seizurogenic risk that could be used to eliminate liabilities early in discovery while there are options for medicinal chemists making potential new drugs. Attrition due to cardiac adverse events has benefited from routine early screening; could we reduce attrition due to seizure using a similar approach? Specifically, microelectrode arrays could be used to detect potential seizurogenic signals in stem-cell-derived neurons. In addition, there is clear evidence implicating neuronal voltage-gated and ligand-gated ion channels, GPCRs and transporters in seizure. Interactions with surrounding glial cells during states of stress or inflammation can also modulate ion channel function in neurons, adding to the challenge of seizure prediction. It is timely to evaluate the opportunity to develop an in vitro assessment of seizure linked to a panel of ion channel assays that predict seizure, with the aim of influencing structure-activity relationship at the design stage and eliminating compounds predicted to be associated with pro-seizurogenic state.

[Approach to drug efficacy and safety assessment based on functions of a human iPSC-derived neuronal network].

Development of an in vitro drug efficacy and safety assessment based on the function of the neural network is required in preclinical studies. A microelectrode array (MEA), which can simultaneously measure the electrical activity of a human induced pluripotent stem cell-derived neural network at multiple points, is an effective assay system. In this study, we focused on seizure liability and clarified the responsiveness to seizure-positive compounds depending on the excitatory and inhibitory balance (E/I balance) of each evaluation sample. In addition, it has been shown that multivariate analysis and AI analysis methods are effective for detecting toxicity and predicting drug mechanisms of action. The future challenge is to approach in vitro-to-in vivo extrapolation (IVIVE) for in vitro assessment. An assessment using brain organoids and low-frequency component analysis, in which enable comparison with in vivo ECoG are effective approaches to IVIVE. MEA can be applied to the central nervous system and the peripheral nervous system; therefore, MEA is also expected to become a highly useful assessment tool for peripheral neuropathy.

[Evaluation methods for drug-induced seizure by microelectrode array recording using human iPS cell-derived neurons].

In the drug development in pharmaceuticals, development of drugs may be discontinued due to the toxicity and clinical side effect, therefore, safety assessment is one of the important factors in drug development. Consortium for Safety Assessment using Human Cells (CSAHi) has been launched for developing and standardizing a toxicity evaluation system for development of drug using human iPS cell differentiated cells. CSAHi focuses on hepato-, cardio-, and neuro-toxicities as important toxicity organs which are attributed to the causes of discontinuation of drug development. In neurotoxicity, seizure is an important finding because of high frequency expression in nonclinical. Multi-electrode array (MEA) systems have recently attracted attention as useful for evaluating seizure risk because they can non-invasively measure the electrophysiological activities of neural networks. We are evaluating the electrophysiological responses to several seizure compounds using MEA in cultured hiPSC-derived neurons. It is important to establish an analytical method to detecting seizure-like activities. We have focused the establish of the effective analysis parameters for detecting seizure risk. We identify to be separate the responses between seizure-positive and seizure-negative compounds using principal component analysis of 10 analysis parameters. In addition, we could separate the mechanism of action of the seizure-positive compounds by principal component analysis and cluster analysis using 10 parameters. It is considered that principal component analysis or cluster analysis could not only assess the seizure risk but also classify mechanism of action by in vitro MEA system using human iPS cell-derived neurons.

Approach to Neurotoxicity using Human iPSC Neurons: Consortium for Safety Assessment using Human iPS Cells.

Neurotoxicity, as well as cardiotoxicity and hepatotoxicity, resulting from administration of a test article is considered a major adverse effect both pre-clinically and clinically. Among the different types of neurotoxicity occurring during the drug development process, seizure is one of the most serious one. Seizure occurrence is usually assessed using in vivo animal models, the Functional Observational Battery, the Irwin test or electroencephalograms. In in vitro studies, a number of assessments can be performed using animal organs/cells. Interestingly, recent developments in stem cell biology, especially the development of Human-Induced Pluripotent Stem (iPS) cells, are enabling the assessment of neurotoxicity in human iPS cell-derived neurons. Further, a Multi-Electrode Array (MEA) using rodent neurons is a useful tool for identifying seizure-inducing compounds. The Consortium for Safety Assessment using Human iPS Cells (CSAHi; http://csahi.org/en/) was established in 2013 by the Japan Pharmaceutical Manufacturers Association (JPMA) to verify the application of human iPS cell-derived neuronal cells to drug safety evaluation. The Neuro Team of CSAHi has been attempting to evaluate the seizure risk of compounds using the MEA platform. Here, we review the current status of neurotoxicity and recent work, including problems related to the use of the MEA assay with human iPS neuronal cell-derived neurons, and future developments.

Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level.

Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.

Impact of Sleep-Wake-Associated Neuromodulators and Repetitive Low-Frequency Stimulation on Human iPSC-Derived Neurons.

The cross-regional neurons in the brainstem, hypothalamus, and thalamus regulate the central nervous system, including the cerebral cortex, in a sleep-wake cycle-dependent manner. A characteristic brain wave, called slow wave, of about 1 Hz is observed during non-REM sleep, and the sleep homeostasis hypothesis proposes that the synaptic connection of a neural network is weakened during sleep. In the present study, in vitro human induced pluripotent stem cell (iPSC)-derived neurons, we investigated the responses to the neuromodulator known to be involved in sleep-wake regulation. We also determined whether long-term depression (LTD)-like phenomena could be induced by 1 Hz low-frequency stimulation (LFS), which is within the range of the non-REM sleep slow wave. A dose-dependent increase was observed in the number of synchronized burst firings (SBFs) when 0.1-1000 nM of serotonin, acetylcholine, histamine, orexin, or noradrenaline, all with increased extracellular levels during wakefulness, was administered to hiPSC-derived dopaminergic (DA) neurons. The number of SBFs repeatedly increased up to 5 h after 100 nM serotonin administration, inducing a 24-h rhythm cycle. Next, in human iPSC-derived glutamate neurons, 1 Hz LFS was administered four times for 15 min every 90 min. A significant reduction in both the number of firings and SBFs was observed in the 15 min immediately after LFS. Decreased frequency of spontaneous activity and recovery over time were repeatedly observed. Furthermore, we found that LFS attenuates synaptic connections, and particularly attenuates the strong connections in the neuronal network, and does not cause uniform attenuation. These results suggest sleep-wake states can be mimicked by cyclic neuromodulator administration and show that LTD-like phenomena can be induced by LFS in vitro human iPSC-derived neurons. These results could be applied in studies on the mechanism of slow waves during sleep or in an in vitro drug efficacy evaluation depending on sleep-wake state.

Bundle Gel Fibers with a Tunable Microenvironment for in Vitro Neuron Cell Guiding.

As scaffolds for neuron cell guiding in vitro, gel fibers with a bundle structure, comprising multiple microfibrils, were fabricated using a microfluidic device system by casting a phase-separating polymer blend solution comprising hydroxypropyl cellulose (HPC) and sodium alginate (Na-Alg). The topology and stiffness of the obtained bundle gel fibers depended on their microstructure derived by the polymer blend ratio of HPC and Na-Alg. High concentrations of Na-Alg led to the formation of small microfibrils in a one-bundle gel fiber and stiff characteristics. These bundle gel fibers permitted for the elongation of the neuron cells along their axon orientation with the long axis of fibers. In addition, human-induced pluripotent-stem-cell-derived dopaminergic neuron progenitor cells were differentiated into neuronal cells on the bundle gels. The bundle gel fibers demonstrated an enormous potential as cell culture scaffold materials with an optimal microenvironment for guiding neuron cells.

Near-Infrared-Responsive Peptide that Targets Collagen Fibrils to Induce Cytotoxicity.

A novel conjugate, PHG10 dye, was synthesized using a collagen peptide and a near-infrared (NIR)-responsive dye to achieve targeted cytotoxicity. The collagen peptide motif, -(Pro-Hyp-Gly)10 - (PHG10), was incorporated for targeting collagen fibrils that are excessively produced by activated fibroblasts around tumor cells. PHG10 dye was purified by HPLC and identified by MALDI-MS. The phototoxicity and cytotoxicity of PHG10 dye were examined using human glioma cells (HGCs). Fluorescent images indicated that PHG10 dye preferably assembled to collagen-coated HGCs compared with noncoated HGCs. Under irradiation with NIR light, effective cytotoxicity was observed on collagen-coated HGCs within 20 min. Because phototoxicity and cytotoxicity are dependent on the assembled amount of PHG10 dye, the targeting of collagen fibrils by the collagen peptide motif PHG10 is assured.