Engineering serendipity: High-throughput discovery of materials that resist bacterial attachment

AI energized hydrogel design, optimization and application in biomedicine

Traditional hydrogel design and optimization methods usually rely on repeated experiments, which is time-consuming and expensive, resulting in a slow-moving of advanced hydrogel development. With the rapid development of artificial intelligence (AI) technology and increasing material data, AI-energized design and optimization of hydrogels for biomedical applications has emerged as a revolutionary breakthrough in materials science. This review begins by outlining the history of AI and the potential advantages of using AI in the design and optimization of hydrogels, such as prediction and optimization of properties, multi-attribute optimization, high-throughput screening, automated material discovery, optimizing experimental design, and etc. Then, we focus on the various applications of hydrogels supported by AI technology in biomedicine, including drug delivery, bio-inks for advanced manufacturing, tissue repair, and biosensors, so as to provide a clear and comprehensive understanding of researchers in this field. Finally, we discuss the future directions and prospects, and provide a new perspective for the research and development of novel hydrogel materials for biomedical applications.

Beyond Encapsulation: Exploring Macrophage-Fibroblast Cross Talk in Implant-Induced Fibrosis

The foreign body response (FBR) and organ fibrosis are complex biological processes involving the interaction between macrophages and fibroblasts. Understanding the molecular mechanisms underlying macrophage-fibroblast cross talk is crucial for developing strategies to mitigate implant encapsulation, a major cause of implant failure. This article reviews the current knowledge on the role of macrophages and fibroblasts in the FBR and organ fibrosis, highlighting the similarities between these processes. The FBR is characterized by the formation of a fibrotic tissue capsule around the implant, leading to functional impairment. Various factors, including material properties such as surface chemistry, stiffness, and topography, influence the degree of encapsulation. Cross talk between macrophages and fibroblasts plays a critical role in both the FBR and organ fibrosis. However, the precise molecular mechanisms remain poorly understood. Macrophages secrete a wide range of cytokines that modulate fibroblast behavior such as abundant collagen deposition and myofibroblast differentiation. However, the heterogeneity of macrophages and fibroblasts and their dynamic behavior in different tissue environments add complexity to this cross talk. Experimental evidence from in vitro studies demonstrates the impact of material properties on macrophage cytokine secretion and fibroblast physiology. However, the correlation between in vitro response and in vivo encapsulation outcomes is not robust. Adverse outcome pathways (AOPs) offer a potential framework to understand and predict process complexity. AOPs describe causal relationships between measurable events leading to adverse outcomes, providing mechanistic insights for in vitro testing and predictive modeling. However, the development of an AOP for the FBR does require a comprehensive understanding of the molecular initiating events and key event relationships to identify which events are essential. In this article, we describe the current knowledge on macrophage-fibroblast cross talk in the FBR and discuss how targeted research can help build an AOP for implant-related fibrosis.

A potential alternative to fungicides using actives-free (meth)acrylate polymers for protection of wheat crops from fungal attachment and infection

Fungicidal compounds are actives widely used for crop protection from fungal infection, but they can also kill beneficial organisms, enter the food chain and promote resistant pathogen strains from overuse. Here we report the first field crop trial of homopolymer materials that prevent fungal attachment, showing successful crop protection via an actives-free approach. In the trial, formulations containing two candidate polymers were applied to young wheat plants that were subject to natural infection with the wheat pathogen Zymoseptoria tritici. A formulation containing one of the candidate polymers, poly(di(ethylene glycol) ethyl ether acrylate) (abbreviated DEGEEA), produced a significant reduction (26%) in infection of the crop by Z. tritici, delivering protection against fungal infection that compared favourably with three different commercially established fungicide programmes tested in parallel. Furthermore, the sprayed polymers did not negatively affect wheat growth. The two lead polymer candidates were initially identified by bio-performance testing using in vitro microplate- and leaf-based assays and were taken forward successfully into a programme to optimize and scale-up their synthesis and compound them into a spray formulation. Therefore, the positive field trial outcome has also established the validity of the smaller-scale, laboratory-based bioassay data and scale-up methodologies used. Because fungal attachment to plant surfaces is a first step in many crop infections, this non-eluting polymer: (i) now offers significant potential to deliver protection against fungal attack, while (ii) addressing the fourth and aligning with the eleventh principles of green chemistry by using chemical products designed to preserve efficacy of function while reducing toxicity. A future focus should be to develop the material properties for this and other applications including other fungal pathogens.

Comparative Evaluation of Pseudomonas aeruginosa Adhesion to a Poly-(2-Methacryloyloxyethyl Phosphorylcholine)-Modified Silicone Hydrogel Contact Lens

Pseudomonas aeruginosa is the most common causative agent associated with microbial keratitis. During contact lens wear, pathogens may be introduced into the ocular environment, which might cause adverse events. Lehfilcon A is a recently developed contact lens with a water gradient surface composed of polymeric 2-methacryloyloxyethyl phosphorylcholine (MPC). MPC is re-ported to impart anti-biofouling properties onto modified substrates. Therefore, in this in vitro experimental study, we tested the capability of lehfilcon A to resist adhesion by P. aeruginosa. Quantitative bacterial adhesion assays using five strains of P. aeruginosa were conducted to compare the adherence properties of lehfilcon A to five currently marketed silicone hydrogel (SiHy) contact lenses (comfilcon A, fanfilcon A, senofilcon A, senofilcon C, and samfilcon A). Compared to lehfilcon A, we observed 26.7 ± 8.8 times (p = 0.0028) more P. aeruginosa binding to comfilcon A, 30.0 ± 10.8 times (p = 0.0038) more binding to fanfilcon A, 18.2 ± 6.2 times (p = 0.0034) more binding to senofilcon A, 13.6 ± 3.9 times (p = 0.0019) more binding to senofilcon C, and 29.5 ± 11.8 times (p = 0.0057) more binding to samfilcon A. These results demonstrate that, for various strains of P. aeruginosa, lehfilcon A reduces bacterial adhesion compared to other contact lens materials.

Biomaterialomics: Data science-driven pathways to develop fourth-generation biomaterials

Conventional approaches to developing biomaterials and implants require intuitive tailoring of manufacturing protocols and biocompatibility assessment. This leads to longer development cycles, and high costs. To meet existing and unmet clinical needs, it is critical to accelerate the production of implantable biomaterials, implants and biomedical devices. Building on the Materials Genome Initiative, we define the concept 'biomaterialomics' as the integration of multi-omics data and high-dimensional analysis with artificial intelligence (AI) tools throughout the entire pipeline of biomaterials development. The Data Science-driven approach is envisioned to bring together on a single platform, the computational tools, databases, experimental methods, machine learning, and advanced manufacturing (e.g., 3D printing) to develop the fourth-generation biomaterials and implants, whose clinical performance will be predicted using 'digital twins'. While analysing the key elements of the concept of 'biomaterialomics', significant emphasis has been put forward to effectively utilize high-throughput biocompatibility data together with multiscale physics-based models, E-platform/online databases of clinical studies, data science approaches, including metadata management, AI/ Machine Learning (ML) algorithms and uncertainty predictions. Such integrated formulation will allow one to adopt cross-disciplinary approaches to establish processing-structure-property (PSP) linkages. A few published studies from the lead author's research group serve as representative examples to illustrate the formulation and relevance of the 'Biomaterialomics' approaches for three emerging research themes, i.e. patient-specific implants, additive manufacturing, and bioelectronic medicine. The increased adaptability of AI/ML tools in biomaterials science along with the training of the next generation researchers in data science are strongly recommended. STATEMENT OF SIGNIFICANCE: This leading opinion review paper emphasizes the need to integrate the concepts and algorithms of the data science with biomaterials science. Also, this paper emphasizes the need to establish a mathematically rigorous cross-disciplinary framework that will allow a systematic quantitative exploration and curation of critical biomaterials knowledge needed to drive objectively the innovation efforts within a suitable uncertainty quantification framework, as embodied in 'biomaterialomics' concept, which integrates multi-omics data and high-dimensional analysis with artificial intelligence (AI) tools, like machine learning. The formulation of this approach has been demonstrated for patient-specific implants, additive manufacturing, and bioelectronic medicine.

Machine Learning-Driven Biomaterials Evolution

Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been hampered by the relatively long development period required. In recent years, driven by the need to accelerate materials development, the applications of machine learning in materials science has progressed in leaps and bounds. The combination of machine learning with high-throughput theoretical predictions and high-throughput experiments (HTE) has shifted the traditional Edisonian (trial and error) paradigm to a data-driven paradigm. In this review, each type of biomaterial and their key properties and use cases are systematically discussed, followed by how machine learning can be applied in the development and design process. The discussions are classified according to various types of materials used including polymers, metals, ceramics, and nanomaterials, and implants using additive manufacturing. Last, the current gaps and potential of machine learning to further aid biomaterials discovery and application are also discussed.

Generation and Characterization of a Library of Novel Biologically Active Functional Surfactants (Surfmers) Using Combined High-Throughput Methods

We report the first successful combination of three distinct high-throughput techniques to deliver the accelerated design, synthesis, and property screening of a library of novel, bio-instructive, polymeric, comb-graft surfactants. These three-dimensional, surface-active materials were successfully used to control the surface properties of particles by forming a unimolecular deep layer on the surface of the particles via microfluidic processing. This strategy deliberately utilizes the surfactant to both create the stable particles and deliver a desired cell-instructive behavior. Therefore, these specifically designed, highly functional surfactants are critical to promoting a desired cell response. This library contained surfactants constructed from 20 molecularly distinct (meth)acrylic monomers, which had been pre-identified by HT screening to exhibit specific, varied, and desirable bacterial biofilm inhibitory responses. The surfactant's self-assembly properties in water were assessed by developing a novel, fully automated, HT method to determine the critical aggregation concentration. These values were used as the input data to a computational-based evaluation of the key molecular descriptors that dictated aggregation behavior. Thus, this combination of HT techniques facilitated the rapid design, generation, and evaluation of further novel, highly functional, cell-instructive surfaces by application of designed surfactants possessing complex molecular architectures.

Droplet Microfluidic Optimisation Using Micropipette Characterisation of Bio-Instructive Polymeric Surfactants

Droplet microfluidics can produce highly tailored microparticles whilst retaining monodispersity. However, these systems often require lengthy optimisation, commonly based on a trial-and-error approach, particularly when using bio-instructive, polymeric surfactants. Here, micropipette manipulation methods were used to optimise the concentration of bespoke polymeric surfactants to produce biodegradable (poly(d,l-lactic acid) (PDLLA)) microparticles with unique, bio-instructive surface chemistries. The effect of these three-dimensional surfactants on the interfacial tension of the system was analysed. It was determined that to provide adequate stabilisation, a low level (0.1% (w/v)) of poly(vinyl acetate-co-alcohol) (PVA) was required. Optimisation of the PVA concentration was informed by micropipette manipulation. As a result, successful, monodisperse particles were produced that maintained the desired bio-instructive surface chemistry.

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology

The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.

Controlling Experimental Parameters to Improve Characterization of Biomaterial Fouling

Uncontrolled protein adsorption and cell binding to biomaterial surfaces may lead to degradation, implant failure, infection, and deleterious inflammatory and immune responses. The accurate characterization of biofouling is therefore crucial for the optimization of biomaterials and devices that interface with complex biological environments composed of macromolecules, fluids, and cells. Currently, a diverse array of experimental conditions and characterization techniques are utilized, making it difficult to compare reported fouling values between similar or different biomaterials. This review aims to help scientists and engineers appreciate current limitations and conduct fouling experiments to facilitate the comparison of reported values and expedite the development of low-fouling materials. Recent advancements in the understanding of protein-interface interactions and fouling variability due to experiment conditions will be highlighted to discuss protein adsorption and cell adhesion and activation on biomaterial surfaces.

Natural Architectures for Tissue Engineering and Regenerative Medicine

The ability to control the interactions between functional biomaterials and biological systems is of great importance for tissue engineering and regenerative medicine. However, the underlying mechanisms defining the interplay between biomaterial properties and the human body are complex. Therefore, a key challenge is to design biomaterials that mimic the in vivo microenvironment. Over millions of years, nature has produced a wide variety of biological materials optimised for distinct functions, ranging from the extracellular matrix (ECM) for structural and biochemical support of cells to the holy lotus with special wettability for self-cleaning effects. Many of these systems found in biology possess unique surface properties recognised to regulate cell behaviour. Integration of such natural surface properties in biomaterials can bring about novel cell responses in vitro and provide greater insights into the processes occurring at the cell-biomaterial interface. Using natural surfaces as templates for bioinspired design can stimulate progress in the field of regenerative medicine, tissue engineering and biomaterials science. This literature review aims to combine the state-of-the-art knowledge in natural and nature-inspired surfaces, with an emphasis on material properties known to affect cell behaviour.

Strontium-releasing mesoporous bioactive glasses with anti-adhesive zwitterionic surface as advanced biomaterials for bone tissue regeneration

HYPOTHESIS

The treatment of bone fractures still represents a challenging clinical issue when complications due to impaired bone remodelling (i.e. osteoporosis) or infections occur. These clinical needs still require a radical improvement of the existing therapeutic approach through the design of advanced biomaterials combining the ability to promote bone regeneration with anti-adhesive properties able to minimise unspecific biomolecules adsorption and bacterial adhesion. Strontium-containing mesoporous bioactive glasses (Sr-MBG), which are able to exert a pro-osteogenic effect by releasing Sr²⁺ ions, have been successfully functionalised to provide mixed-charge (NH₃^⊕/COO^⊝) surface groups with anti-adhesive abilities.

EXPERIMENTS

Sr-MBG have been post-synthesis modified by co-grafting hydrolysable short chain silanes containing amino (aminopropylsilanetriol) and carboxylate (carboxyethylsilanetriol) moieties to achieve a zwitterionic zero-charge surface. The final system was then characterised in terms of textural-structural properties, bioactivity, cytotoxicity, pro-osteogenic and anti-adhesive capabilities.

FINDINGS

After zwitterionization the in vitro bioactivity was maintained, as well as the ability to release Sr²⁺ ions which are capable of inducing a mineralization process. Irrespective of their size, Sr-MBG particles did not exhibit any cytotoxicity in pre-osteoblastic MC3T3-E1 up to the concentration of 75 µg/mL. Finally, the zwitterionic Sr-MBGs showed a significant reduction of serum protein adhesion with respect to the pristine ones. These results open promising future expectations in the design of nanosystems which combine pro-osteogenic and anti-adhesive properties.

Host-guest self-assembly toward reversible visible-light-responsive switching for bacterial adhesion

Here we report a facile method to construct reversible visible-light-responsive switching from antibacterial to bioadhesion by host-guest self-assembly of β-cyclodextrin (β-CD) and azobenzene functionalized polycation/polyanion. The visible-light-responsible azobenzene functionalized polycation, poly{6-[(2,6-dimethoxyphenyl)azo-4-(2',6'-dimethoxy)phenoxy]propyl dimethylaminoethyl methacrylate-random-poly(2-(N,N-dimethylaminoethyl) methacrylate) (Azo-PDMAEMA), was synthesized via quaternization reaction between 2,6,2',6'-tetramethoxy-4-(3-bromopropoxy)azobenzene (AzoOMeBr) and poly(2-(N,N-dimethylaminoethyl) methacrylate) (PDMAEMA), and the polyanion, poly{6-[(2,6-dimethoxyphenyl)azo-4-(2',6'-dimethoxy) phenoxy]hexyl acrylate-random-acrylic acid} (Azo-PAA), was synthesized via esterification reaction between 2,6,2',6'-tetramethoxy-4-(6-hydroxyhexyloxy) azobenzene (AzoOMeOH) and poly(acryloyl chloride) (PAC) and subsequent hydrolysis reactions. The switch surface could be achieved via the alternate host-guest assembly of Azo-PDMAEMA and Azo-PAA onto a β-CD-terminated substratum (Sub-CD) through visible light irradiation. The positively charged Azo-PDMAEMA with quaternary ammonium groups exhibited antimicrobial properties and few bacteria were adhered on the surface, while the negatively charged Azo-PAA with carboxyl acid groups exhibited excellent bioadhesive properties and a large number of bacteria were adhered. Interestingly, the switch between antibacterial and bioadhesive could be realized upon visible light irradiation via alternate assembly of Azo-PDMAEMA and Azo-PAA. The proposed approach to manufacturing visible-light-responsive surface with reversible and alterable biofunctionality switching between antibacterial and bioadhesive is simple and efficient, which is promising for preparation of multifunctional polymeric surfaces to encounter multifarious demands for the biomedical and biotechnological applications.

STATEMENT OF SIGNIFICANCE

Light has attracted great attention in building biointerfaces for its precise spatiotemporal control and convenient operation. However, UV light may damage to biological samples and living tissues, which will limit its applications. This study demonstrates a novel visible-light-responsive surface fabricated through reversible assembly of azobenzene functionalized polycations/polyanions on cyclodextrin (CD)-terminated substrate by host-guest interactions between the visible-light-responsive azobenzene mAzo and CD, which has not been examined previously. It is noted that the azobenzene functionalized polycations show strong antibacterial activities, while the polyanions show excellent bioadhesive properties, as can be switched through the alternate assembly upon visible-light irradiation. This facile and versatile approach to visible-light-responsive surfaces holds great potential for switching of bioadhesion.

Prediction of Broad-Spectrum Pathogen Attachment to Coating Materials for Biomedical Devices

Bacterial infections in healthcare settings are a frequent accompaniment to both routine procedures such as catheterization and surgical site interventions. Their impact is becoming even more marked as the numbers of medical devices that are used to manage chronic health conditions and improve quality of life increases. The resistance of pathogens to multiple antibiotics is also increasing, adding an additional layer of complexity to the problems of employing safe and effective medical procedures. One approach to reducing the rate of infections associated with implanted and indwelling medical devices is the use of polymers that resist the formation of bacterial biofilms. To significantly accelerate the discovery of such materials, we show how state of the art machine learning methods can generate quantitative predictions for the attachment of multiple pathogens to a large library of polymers in a single model for the first time. Such models facilitate design of polymers with very low pathogen attachment across different bacterial species that will be candidate materials for implantable or indwelling medical devices such as urinary catheters, cochlear implants, and pacemakers.

Engineering microbial physiology with synthetic polymers: cationic polymers induce biofilm formation in Vibrio cholerae and downregulate the expression of virulence genes

Here we report the first application of non-bactericidal synthetic polymers to modulate the physiology of a bacterial pathogen. Poly(N-[3-(dimethylamino)propyl] methacrylamide) (P1) and poly(N-(3-aminopropyl)methacrylamide) (P2), cationic polymers that bind to the surface of V. cholerae, the infectious agent causing cholera disease, can sequester the pathogen into clusters. Upon clustering, V. cholerae transitions to a sessile lifestyle, characterised by increased biofilm production and the repression of key virulence factors such as the cholera toxin (CTX). Moreover, clustering the pathogen results in the minimisation of adherence and toxicity to intestinal epithelial cells. Our results suggest that the reduction in toxicity is associated with the reduction to the number of free bacteria, but also the downregulation of toxin production. Finally we demonstrate that these polymers can reduce colonisation of zebrafish larvae upon ingestion of water contaminated with V. cholerae. Overall, our results suggest that the physiology of this pathogen can be modulated without the need to genetically manipulate the microorganism and that this modulation is an off-target effect that results from the intrinsic ability of the pathogen to sense and adapt to its environment. We believe these findings pave the way towards a better understanding of the interactions between pathogenic bacteria and polymeric materials and will underpin the development of novel antimicrobial polymers.

Linking the Transcriptional Landscape of Bone Induction to Biomaterial Design Parameters

New engineering possibilities allow biomaterials to serve as active orchestrators of the molecular and cellular events of tissue regeneration. Here, the molecular control of tissue regeneration for calcium phosphate (CaP)-based materials is established by defining the parameters critical for tissue induction and those are linked to the molecular circuitry controlling cell physiology. The material properties (microporosity, ion composition, protein adsorption) of a set of synthesized osteoinductive and noninductive CaP ceramics are parameterized and these properties are correlated to a transcriptomics profile of osteogenic cells grown on the materials in vitro. Using these data, a genetic network controlling biomaterial-induced bone formation is built. By isolating the complex material properties into single-parameter test conditions, it is verified that a subset of these genes is indeed controlled by surface topography and ions released from the ceramics, respectively. The gene network points to a decisive role for extracellular matrix deposition in osteoinduction by genes such as tenascin C and hyaluronic acid synthase 2, which are controlled by calcium and phosphate ions as well as surface topography. This work provides insight into the biomaterial composition and material engineering aspects of bone void filling and can be used as a strategy to explore the interface between biomaterials and tissue regeneration.

Making Silicone Rubber Highly Resistant to Bacterial Attachment Using Thiol-ene Grafting

Biomedical devices are indispensable in modern medicine yet offer surfaces that promote bacterial attachment and biofilm formation, resulting in acute and chronic healthcare-associated infections. We have developed a simple method to graft acrylates to silicone rubber, polydimethylsiloxane (PDMS), a commonly used device material that is often colonized by bacteria. We demonstrate a novel method whereby nontoxic bacteria attachment-resistant polymers can be readily grafted from and grafted to the surface using thiol-ene chemistry, substantially reducing bacterial colonization. With use of this approach, bacterial biofilm coverage can be reduced by 99% compared with standard PDMS in an in vitro assay. This grafting approach offers significant advantages over commonly used physisorbed coatings, especially in areas of high shear or mechanical stress. Furthermore, the approach is versatile such that the grafted material properties can be tailored for the desired final application.