Biomaterials in nature form hierarchical structures and functions across various length scales through binding and assembly processes. Inspired by nature, we developed hierarchically organized tissue engineering materials through evolutionary screening and self-templating assembly. Leveraging the M13 bacteriophage (phage), we employed an evolutionary selection process against hydroxyapatite (HA) to isolate HA-binding phage (HAPh). The newly discovered phage exhibits a bimodal length, comprising 950 nm and 240 nm, where the synergistic effect of these dual lengths promotes the formation of supramolecular fibrils with periodic banded structures. The assembled HAPh fibrils show the capability of HA mineralization and the directional growth of osteoblast cells. When applied to a dentin surface, it induces the regeneration of dentin-like tissue structures, showcasing its potential applications as a scaffold in tissue engineering. The integration of evolutionary screening and self-templating assembly holds promise for the future development of hierarchically organized tissue engineering materials.

The use of naturally sourced organic materials with chirality, such as the M13 bacteriophage, holds intriguing implications, especially in the field of nanotechnology. The chirality properties of bacteriophages have been demonstrated through numerous studies, particularly in the analysis of liquid crystal phase transitions, developing specific applications. However, exploring the utilization of the M13 bacteriophage as a template for creating chiral nanostructures for optics and sensor applications comes with significant challenges. In this study, the chirality of the M13 bacteriophage was leveraged as a valuable tool for generating helical hybrid structures by combining it with nanoparticles through an evaporation-induced three-dimensional (3D) printing process. Utilizing on the self-assembly property of the M13 bacteriophage, metal nanoparticles were organized into a helical chain under the influence of the M13 bacteriophage at the meniscus interface. External parameters, including nanoparticle shape, the ratio between the bacteriophage and nanoparticles, and pulling speed, were demonstrated as crucial factors affecting the fabrication of helical nanostructures. This study aimed to explore the potential of chiral nanostructure fabrication by utilizing the chirality of the M13 bacteriophage and manipulating external parameters to control the properties of the resulting hybrid structures.

The colorimetric sensor-based electronic nose has been demonstrated to discriminate specific gaseous molecules for various applications, including health or environmental monitoring. However, conventional colorimetric sensor systems rely on RGB sensors, which cannot capture the complete spectral response of the system. This limitation can degrade the performance of machine learning analysis, leading to inaccurate identification of chemicals with similar functional groups. Here, we propose a novel time-resolved hyperspectral (TRH) data set from colorimetric array sensors consisting of 1D spatial, 1D spectral, and 1D temporal axes, which enables hierarchical analysis of multichannel 2D spectrograms via a convolution neural network (CNN). We assessed the outstanding classification performance of the TRH data set compared to an RGB data set by conducting a relative humidity (RH) concentration classification. The time-dependent spectral response of the colorimetric sensor was measured and trained as a CNN model using TRH and RGB sensor systems at different RH levels. While the TRH model shows a high classification accuracy of 97.5% for the RH concentration, the RGB model yields 72.5% under identical conditions. Furthermore, we demonstrated the detection of various functional volatile gases with the TRH system by using experimental and simulation approaches. The results reveal distinct spectral features from the TRH system, corresponding to changes in the concentration of each substance.

Phage-assisted evolution has emerged as a powerful technique for improving a protein\'s function by using mutagenesis and selective pressure. However, mutations typically occur throughout the host\'s genome and are not limited to the gene-of-interest (GOI): these undesirable genomic mutations can yield host cells that circumvent the system\'s selective pressure. Our system targets mutations specifically toward the GOI by combining T7 targeted mutagenesis and phage-assisted evolution. This system improves the structure and function of proteins by accumulating favorable mutations that can change its binding affinity, specificity, and activity.

This study investigates a real-time handheld bioaerosol monitoring system for the detection of biological particles using UV-LED and light-induced fluorescence technology. Biological particles produce both scattering and fluorescence signals simultaneously, which can help distinguish them from general particles. The detected scattering, fluorescence, and simultaneous signals are then converted into photon signals and categorized based on predetermined criteria. A reliable biological particle generator was required to validate the performance of the system. This study explores the use of an M13 bacteriophage as a virus simulant of biological agents and employs a customized inkjet aerosol generator to produce M13 bacteriophage aerosols of a specific size by controlling the concentration of M13. We confirmed that micro-sized, narrowly dispersed M13 aerosols were efficiently generated. Additionally, we confirmed the performance of this real-time handheld bioaerosol monitoring system by detecting viruses.

Metal single-atom catalysts (MSACs) possess multiple advantages in chemical synthesis; their efficient fabrication routes, however, remain a challenge to date. Here, an interdisciplinary design using M13 bacteriophage virus as a biotemplate to carry Fe nanoclusters, which we figuratively call \"Fe-nanonests\", is proposed to enable facile and versatile synthesis of MSACs. The feasibility and generality of this self-assembly method was demonstrated by the observation of six different metal single atoms (MSAs) including Ag, Pt, Pd, Zn, Cu, and Ni. With Pd as a representative, key factors dominating the fabrication were determined. The Pd single atoms exhibited excellent horseradish peroxidase (HRP)-like activity, which was further improved by 50% via genetic editing of the M13 pVIII protein terminals. Excellent stability was also observed in the quantification of acid phosphatase, a cancer predictor. X-ray absorption near-edge structure spectroscopy has been applied to the analysis of Pd single atoms as well, and the Pd-N4 coordination explained the mechanism of high HRP-like catalytic activity. The MSAs synthesized by the M13 phage and Fe-nanonest self-assembly method show promising prospects in non-cold-chain medical detection applications.

Stem cell technology holds immense potential for revolutionizing medicine, particularly in regenerative treatment for heart disease. The unique capacity of stem cells to differentiate into diverse cell types offers promise in repairing damaged tissues and implanting organs. Ensuring the quality of differentiated cells, essential for specific functions, demands in-depth analysis. However, this process consumes time and incurs substantial costs while invasive methods may alter stem cell features during differentiation and deplete cell numbers. To address these challenges, we propose a non-invasive strategy, using cellular respiration, to assess the quality of differentiation-induced stem cells, notably cardiovascular stem cells. This evaluation employs an electronic nose (E-Nose) and neural pattern separation (NPS). Our goal is to assess differentiation-induced cardiac stem cells (DICs) quality through E-Nose data analysis and compare it with standard commercial human cells (SCHCs). Sensitivity and specificity were evaluated by interacting SCHCs and DICs with the E-Nose, achieving over 90% classification accuracy. Employing selective combinations optimized by NPS, E-Nose successfully classified all six cell types. Consequently, the relative similarity among DICs like cardiomyocytes, endothelial cells with SCHCs was established relied on comparing response data from the E-Nose sensor without resorting to complex evaluations.

OBJECTIVE: In this study, we confirmed the binding of M13KO7 to Potato virus Y (PVY) using enzyme-linked immunosorbent assay. M13KO7 is a \"bald\" bacteriophage in which no recombinant antibody is displayed. M13KO7 is easy to propagate by using Escherichia coli, making this method more reasonable in economic perspective. Based on this study, we suggest that M13KO7 detection system has applicability as a novel biological tool for the detection of PVY.

Sensors for detecting infinitesimal amounts of chemicals in air have been widely developed because they can identify the origin of chemicals. These sensing technologies are also used to determine the variety and freshness of fresh food and detect explosives, hazardous chemicals, environmental hormones, and diseases using exhaled gases. However, there is still a need to rapidly develop portable and highly sensitive sensors that respond to complex environments. Here, we show an efficient method for optimising an M13 bacteriophage-based multi-array colourimetric sensor for multiple simultaneous classifications. Apples, which are difficult to classify due to many varieties in distribution, were selected for classifying targets. M13 was adopted to fabricate a multi-array colourimetric sensor using the self-templating process since a chemical property of major coat protein p8 consisting of the M13 body can be manipulated by genetic engineering to respond to various target substances. The twenty sensor units, which consisted of different types of manipulated M13, exhibited colour changes because of the change of photonic crystal-like nanostructure when they were exposed to target substances associated with apples. The classification success rate of the optimal sensor combinations was achieved with high accuracy for the apple variety (100%), four standard fragrances (100%), and aging (84.5%) simultaneously. We expect that this optimisation technique can be used for rapid sensor development capable of multiple simultaneous classifications in various fields, such as medical diagnosis, hazardous environment monitoring, and the food industry, where sensors need to be developed in response to complex environments consisting of various targets.

The demand for the ultrasensitive and rapid quantitative analysis of trace target analytes has become increasingly urgent. However, the sensitivity of traditional immunoassay-based detection methods is limited due to the contradiction between molecular recognition and signal amplification caused by the size effect of nanoprobes. To address this dilemma, we describe versatile M13 phage-assisted immunorecognition and signal transduction spatiotemporal separation that enable ultrasensitive light-scattering immunoassay systems for the quantitative detection of low-abundance target analytes. The newly developed immunoassay strategy combines the M13 phage-assisted light scattering signal fluctuations of gold nanoparticles (AuNPs) with gold in situ growth (GISG) technology. Given the synergy of M13 phage-mediated leverage effect and GISG-amplified light scattering signal modulation, the practical detection capability of this strategy can achieve the ultrasensitive and rapid quantification of ochratoxin A and alpha-fetoprotein in real samples at the subfemtomolar level within 50 min, displaying about 4 orders of magnitude enhancement in sensitivity compared with traditional phage-based ELISA. To further improve the sensitivity of our immunoassay, the biotin-streptavidin amplification scheme is implemented to detect severe acute respiratory syndrome coronavirus 2 spike protein down to the attomolar range. Overall, this study offers a direction for ultrasensitive quantitative detection of target analytes by the synergistic combination of M13 phage-mediated leverage effect and GISG-amplified light scattering signal modulation.