Yes / A major barrier to the systematic improvement of biomimetic peptide-mediated strategies for the controlled growth of inorganic nanomaterials in environmentally benign conditions lies in the lack of clear conceptual connections between the sequence of the peptide and its surface binding affinity, with binding being facilitated by noncovalent interactions. Peptide conformation, both in the adsorbed and in the nonadsorbed state, is the key relationship that connects peptide-materials binding with peptide sequence. Here, we combine experimental peptide–titania binding characterization with state-of-the-art conformational sampling via molecular simulations to elucidate these structure/binding relationships for two very different titania-binding peptide sequences. The two sequences (Ti-1, QPYLFATDSLIK; Ti-2, GHTHYHAVRTQT) differ in their overall hydropathy, yet via quartz-crystal microbalance measurements and predictions from molecular simulations, we show these sequences both support very similar, strong titania-binding affinities. Our molecular simulations reveal that the two sequences exhibit profoundly different modes of surface binding, with Ti-1 acting as an entropically driven binder while Ti-2 behaves as an enthalpically driven binder. The integrated approach presented here provides a rational basis for peptide sequence engineering to achieve the in situ growth and organization of titania nanostructures in aqueous media and for the design of sequences suitable for a range of technological applications that involve the interface between titania and biomolecules. / AFOSR grant FA9550-12-1-0226; AFOSR for funding via FA9550-13-1-0040

D’après les données de l’agence International de Prévention de la Cécité, 253 millions de personnes souffrent de pathologies visuelles dans le monde. Il existe des pathologies affectant les photorécepteurs de la rétine causant des millions de déficients visuels sans traitement efficace disponible. Les implants rétiniens ont déjà montré sa capacité pour stimuler de façon électrique les cellules rémanentes de la rétine grâce à un réseau de micro-électrodes de façon à obtenir une réponse neuronale puis une perception visuelle. Ces travaux de thèse en lien avec les implants rétiniens porteront sur deux aspects principaux concernant de nouvelles configurations de micro-électrodes et une analyse comparative des matériaux constitutifs des électrodes avec des tests en vieillissement long terme. Pour le premier aspect, de nouvelles géométries d’électrodes ont été développées en différentes phases : en commencent par une modélisation par éléments finis de la micro-électrode, suivi par la micro fabrication des prototypes et les expériences in-vivo. Pour l’étude du vieillissement des matériaux constitutifs des micro-électrodes, un banc de caractérisation a été développé pour reproduire les conditions de pH, T et stimulation électrique d’un implant réel. Le banc nous permet aussi d’étudier l’évolution de façon comparative des caractéristiques des différents matériaux grâce à la mesure de son impédance électrochimique / Regarding to data provided by the International Agency for Prevention of Blindness, 253 million people suffer some kind of visual impairment around the world. There is a group of diseases that affect the photoreceptors causing millions of impairment cases around the world that do not have an efficacious treatment. Retinal prostheses have proved to electrically stimulate the remaining cells of the retina by means of implantable microelectrode arrays to elicit their response and therefore visual perception. This PhD work tries to study two aspects of these devices: first, new electrode geometries that stimulate the cells in a more efficient manner; and second, the ageing of the different material used for the fabrication of the microelectrodes. For the first aspect new electrode geometries have been developed based on the state of the art. This development has been divided in different phases beginning with a FEM modeling of the electrode, followed by the microfabrication of the structures and their test in-vivo. In order to study the ageing of the microelectrode materials, a characterization bench that reproduces the conditions that an implant has to face during its implantation has been developed. This bench allows us to study in a comparative manner the evolution of the characteristics of the different materials thanks to the measurement of their electrochemical impedance

A fundamental understanding of bio-interfaces will facilitate improvement in the design and application of biomaterials that can beneficially interact with biological objects such as nucleic acids, molecules, bacteria, and mammalian cells. Currently, there exist analytical instruments to investigate material properties and report information on electrical, chemical, physical, and mechanical natures of biomaterials and biological samples. The overall goal of this research was to utilize advanced spectroscopy techniques coupled with data mining to elucidate specific characteristic properties for biological objects and how these properties imply interaction with environmental biomaterials. My studies of interfacial electron transfer (ET) of DNA-modified gold electrodes aided in understanding that DNA surface density is related to the step-wise order of which a self-assembled monolayer is created on a gold substrate. Further surface modification plays a role in surface conductivity, and I found that electro-oxidation of the DNA involved the oxidation of guanine and adenine nucleotides. Scanning tunneling microscopy (STM) was used to create topography and current images of the SAM surfaces. I also used Raman microspectroscopy (RM) to obtain spectra and spectral maps of DNA-modified gold surfaces. For studies of bacteria, atomic force microscopy (AFM) and scanning electron microscopy (SEM) images showed similar morphological features of Gram-positive and Gram-negative bacteria. Direct classical least squares (DCLS) analysis aided to distinguish co-cultured strains. Fourier transform infrared (FTIR) spectroscopy proved insightful for characteristic bands for Gram-positive bacteria and a combined AFM/RM image revealed a relationship between culture height/density and peak Raman intensity. In our mammalian cell studies we focused on human lung adenocarcinoma epithelial cells (A549), metastatic human breast carcinoma cells MDA-MB-435 (435), and non-metastatic MDA-MB-435/BRMS1 (435/BRMS1). RM revealed similarities between metastatic 435 and non-metastatic 435/BRMS1 cells compared to epithelial A549 cells. AFM showed increases in biomechanical properties for 435/BRMS1 in the areas of cell adhesion, cell spring constant, and Young’s modulus. Fluorescent staining illustrates F-actin rearrangement for 435 and 435/BRMS1. Electric cell-substrate impedance sensing (ECIS) revealed that 435 cells adhere tightly to substrata and migrate rapidly compared with 435/BRMS1. For ECIS, ≤10-fold diesel exhaust particles (DEP) concentration exposure caused clastogenic DNA degradation whereas ≥25-fold DEP exposure caused cytotoxic results. Resveratrol (RES) at 10 μM showed minimal to mild protection against DEP before and after exposure and aided in improving injury recovery.

Non-invasive and continuous spatiotemporal pathogen monitoring at biological interfaces (e.g., human tissue) holds promise for transformative applications in personalized healthcare (e.g., wound infection monitoring) and environmental surveillance (e.g., airborne virus surveillance). Despite notable progress, current receptor-based biosensors encounter inherent limitations, including inadequate long-term performance, restricted spatial resolutions and length scales, and challenges in obtaining multianalyte information. Surface-enhanced Raman spectroscopy (SERS) has emerged as a robust analytical method, merging the molecular specificity of Raman spectroscopy's vibrational fingerprinting with the enhanced detection sensitivity from strong light-matter interaction in plasmonic nanostructures. As a receptor-free and noninvasive detection tool capable of capturing multianalyte chemical information, SERS holds the potential to actualize bio-interfaced spatiotemporal pathogen monitoring. Nonetheless, several challenges must be addressed before practical adoption, including the development of plasmonic bio-interfaces, sensitive capture of multianalyte information from pathogens, regeneration of nanogap hotspots for long-term sensing, and extraction of meaningful information from spatiotemporal SERS datasets. This dissertation tackles these fundamental challenges. Plasmonic bio-interfaces were created using innovative nanoimprint lithography-based scalable nanofabrication methods for reliable bio-interfaced spatiotemporal measurements. These plasmonic bio-interfaces feature sensitive, dense, and uniformly distributed plasmonic transducers (e.g., plasmonic nano dome arrays, optically-coupled plasmonic nanodome and nanohole arrays, self-assembled nanoparticle micro patches) on ultra-flexible and porous platforms (e.g., biomimetic polymeric meshes, textiles). Using these plasmonic bio-interfaces, advancements were made in SERS signal transduction, machine-learning-enabled data analysis, and sensor regeneration. Large-area multianalyte spatiotemporal monitoring of bacterial biofilm components and pH was demonstrated in in-vitro biofilm models, crucial for wound biofilm diagnostics. Additionally, novel approaches for sensitive virus detection were introduced, including monitoring spectral changes during viral infection in living biofilms and direct detection of decomposed viral components. Spatiotemporal SERS datasets were analyzed using unsupervised machine-learning methods to extract biologically relevant spatiotemporal information and supervised machine-learning tools to classify and predict biological outcomes. Finally, a sensor regeneration method based on plasmon-induced nanocavitation was developed to enable long-term continuous detection in protein-rich backgrounds. Through continuous implementation of spatiotemporal SERS signal transduction, machine-learning-enabled data analysis, and sensor regeneration in a closed loop, our solution has the potential to enable spatiotemporal pathogen monitoring at the bio-interface. / Doctor of Philosophy / Continuous monitoring of pathogens within our bodies and surrounding environments is indispensable for various applications in personalized healthcare (e.g., monitoring wound infections) and environmental surveillance (e.g., airborne virus tracking). To accomplish this, we require sensors capable of seamlessly interfacing with biological systems, such as human tissue, and consistently providing pathogen-related information (e.g., spatial location and pathogen type) over prolonged periods. Our research relies on Surface-enhanced Raman spectroscopy (SERS) to address this challenge. SERS enables noninvasive sensing by providing unique fingerprints of molecules near the sensor's surface. SERS holds the potential to enable bio-interfaced spatiotemporal pathogen monitoring, but several challenges must be tackled before practical adoption. In this dissertation, we address various fundamental challenges in SERS, including constructing SERS devices that can seamlessly interface with biological systems while maintaining performance, sensitively capturing pathogen-related information, extracting meaningful insights from SERS datasets, and continuously regenerating the sensor surface to ensure long-term performance. We developed SERS devices capable of seamlessly interfacing with biological systems using innovative scalable nanofabrication methods. These devices contain sensitive, dense, and uniformly distributed SERS sensors on flexible and porous platforms, such as polymeric scaffolds and textiles. Leveraging these SERS devices, we made advancements in pathogen sensing, data analysis, and sensor regeneration. We demonstrated large-area spatiotemporal monitoring of biofilm components and pH in lab-grown biofilm models, critical for wound biofilm diagnostics. Additionally, we introduced novel approaches for sensitive virus detection, including monitoring changes in SERS signals during viral infection in living biofilms and directly detecting decomposed viral components. The SERS datasets were analyzed using machine learning models to extract biologically relevant spatial and temporal information, such as the spatial location of pathogen components and the temporal stage of pathogen growth, and to predict biological outcomes. Finally, we developed a sensor regeneration method to enable long-term continuous detection in complex backgrounds, such as blood. By continuously performing spatiotemporal pathogen sensing, data analysis, and sensor regeneration in a closed loop, our solution has the potential to realize bio-interfaced spatiotemporal pathogen monitoring.