Rationally designed protein A surface molecularly imprinted magnetic nanoparticles for the capture and detection of Staphylococcus aureus.

Staphylococcus aureus (S. aureus), a commensal organism found on the human skin, is commonly associated with nosocomial infections and exhibits virulence mediated by toxins and resistance to antibiotics. The global threat of antibiotic resistance has necessitated antimicrobial stewardship to improve the safe and appropriate use of antimicrobials; hence, there is an urgent demand for the advanced, cost-effective, and rapid detection of specific bacteria. In this regard, we aimed to selectively detect S. aureus using surface molecularly imprinted magnetic nanoparticles templated with a well-known biomarker protein A, specific to S. aureus. Herein, a highly selective surface molecularly imprinted polymeric thin layer was created on ∼250 nm magnetic nanoparticles (MNPs) through the immobilization of protein A to aldehyde functionalized MNPs, followed by monomer polymerization and template washing. This study employs the rational selection of monomers based on their computationally predicted binding affinity to protein A at multiple surface residues. The resulting MIPs from rationally selected monomer combinations demonstrated an imprinting factor as high as ∼5. Selectivity studies revealed MIPs with four-fold higher binding capacity (BC) to protein A than other non-target proteins, such as lysozyme and serum albumin. In addition, it showed significant binding to S. aureus, whereas negligible binding to other non-specific Gram-negative, i.e. Escherichia coli (E. coli), Pseudomonas aeruginosa (P. aeruginosa), and Gram-positive, i.e. Bacillus subtilis (B. subtilis), bacteria. This MIP was employed for the capture and specific detection of fluorescently labeled S. aureus. Quantitative detection was performed using a conventional plate counting technique in a linear detection range of 101-107 bacterial cells. Remarkably, the MIPs also exhibited approximately 100% cell recovery from milk samples spiked with S. aureus (106 CFU mL-1), underscoring its potential as a robust tool for sensitive and accurate bacterial detection in dairy products. The developed MIP exhibiting high affinity and selective binding to protein A finds its potential applications in the magnetic capture and selective detection of protein A as well as S. aureus infections and contaminations.

Rational design of MIPs for the detection of Myxovirus resistance protein A (MxA), a biomarker for viral infection.

Accurate diagnosis is crucial for effective patient care and the containment of antimicrobial resistance outbreaks. The intricate challenge of distinguishing bacterial from viral infections, coupled with limited diagnostic tools and overlapping symptoms has driven the utilization of molecular imprinting techniques. This study focuses on developing cost-effective, chemically stable antibody analogs for the interferon-induced protein myxovirus resistance protein A (MxA). MxA is an intracellular, cytoplasmic GTPase having activity against a wide range of viruses and serves as a distinctive biomarker for viral infections. We utilized computational design to guide the polymer assembly, centering on epitope imprinting to target MxA-specific regions crucial for interaction. Molecular docking calculations, alongside a pioneering multi-monomer simultaneous docking (MMSD) protocol, efficiently elucidate cooperativity during pre-polymerization. Monomer binding affinity scores, such as for APTMS, exhibited notable increase, ranging from -3.11 to -13.03 kcal/mol across various MMSD combinations compared to a maximum of -2.78 kcal/mol in single monomer docking, highlighting the capacity of MMSD in elucidating crucial monomer-monomer interactions. This computational approach provides a theoretical alternative to labor-intensive experimental optimization, streamlining the development process for synthetic receptors. Simulations reveal unique interactions enhancing MIP-peptide complementarity, yielding optimized receptors selectively binding to MxA epitopes. The obtained MIPs demonstrated a maximum adsorption capacity of approximately 12 mg/g and captured 1.6 times more epitope and 2.6 times more epitope containing MxA protein than corresponding NIPs. A proof-of-concept study demonstrates MxA protein binding to synthetic receptors, highlighting the potential of MIPs, analogous to antibodies, in overcoming current diagnostic challenges for precise detection of viral infection.

Guided mode resonance immunosensor for label-free detection of pathogenic bacteria Pseudomonas aeruginosa.

Photonic biosensors are promising platforms for the rapid detection of pathogens with the potential to replace conventional diagnostics based on microbiological culturing methods. Intricately designed sensing elements with robust architectures can offer highly sensitive detection at minimal development cost enabling rapid adoption in low-resource settings. In this work, an optical detection scheme is developed by structuring guided mode resonance (GMR) on a highly stable, transparent silicon nitride (SiN) substrate and further biofunctionalized to identify a specific bacteria Pseudomonas aeruginosa. The resonance condition of the GMR chip is optimized to have relatively high bulk sensitivity with a good quality factor. The biofunctionalization aims at oriented immobilization of specific antibodies to allow maximum bacteria attachment and improved specificity. The sensitivity of the assays is evaluated for clinically relevant concentrations ranging from 102 to 108 CFU/mL. From the calibration curves, the sensitivity of the chip is extracted as 0.134nm/Log10 [concentration], and the detection modality possesses a favorably good limit of detection (LOD) 89 CFU/mL. The use of antibodies as a biorecognition element complemented with a good figure of merit of GMR sensing element allows selective bacteria identification compared to other non-specific pathogenic bacteria that are relevant for testing physiological samples. Our developed GMR biosensor is low-cost, easy to handle, and readily transformable into a portable handheld detection modality for remote usage.

Rational In Silico Design of Molecularly Imprinted Polymers: Current Challenges and Future Potential.

The rational design of molecularly imprinted polymers has evolved along with state-of-the-art experimental imprinting strategies taking advantage of sophisticated computational tools. In silico methods enable the screening and simulation of innovative polymerization components and conditions superseding conventional formulations. The combined use of quantum mechanics, molecular mechanics, and molecular dynamics strategies allows for macromolecular modelling to study the systematic translation from the pre- to the post-polymerization stage. However, predictive design and high-performance computing to advance MIP development are neither fully explored nor practiced comprehensively on a routine basis to date. In this review, we focus on different steps along the molecular imprinting process and discuss appropriate computational methods that may assist in optimizing the associated experimental strategies. We discuss the potential, challenges, and limitations of computational approaches including ML/AI and present perspectives that may guide next-generation rational MIP design for accelerating the discovery of innovative molecularly templated materials.

An in silico predictive method to select multi-monomer combinations for peptide imprinting.

In silico methods enable optimizing artificial receptors such that constructive mimics of natural antibodies can be envisaged. The introduction of combinatorial synthesis strategies via multi-monomer combinations has improved the performance of molecularly imprinted polymers (MIP) significantly. However, it remains experimentally challenging to screen thousands of combinations resulting from a large library of monomers. The present study introduces a molecular mechanics based multi-monomer simultaneous docking approach (MMSD) to computationally screen monomer combinations according to their potential, facilitating selective molecular imprints. Thereby, the diversity of multipoint interactions realizable with a peptide surface is efficiently explored yielding how individual monomer binding capacities constructively or adversely add up when docked together. Additionally, spatially distributed molecular models were mapped for analyzing intermolecular H-bonding and hydrophobic interactions resulting from single monomer docking, as well as bi- and tri-monomer simultaneous docking. A direct impact of complex formation on the binding capacity of the resulting MIPs has been observed. In a first small-scale study, the predictive potential of the MMSD approach was validated via experimentally applied polymer combinations for peptide imprinting via the scoring functions established during the screening process. MMSD clearly enables rational design of MIPs for synthesizing more sensitive and selective artificial receptor materials especially for peptide and protein-epitope templates.

Plastic Antibodies Mimicking the ACE2 Receptor for Selective Binding of SARS-CoV-2 Spike.

Molecular imprinting has proven to be a versatile and simple strategy to obtain selective materials also termed "plastic antibodies" for a wide variety of species, i.e., from ions to macromolecules and viruses. However, to the best of the authors' knowledge, the development of epitope-imprinted polymers for selective binding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is not reported to date. An epitope from the SARS-CoV-2 spike protein comprising 17 amino acids is used as a template during the imprinting process. The interactions between the epitope template and organosilane monomers used for the polymer synthesis are predicted via molecular docking simulations. The molecularly imprinted polymer presents a 1.8-fold higher selectivity against the target epitope compared to non-imprinted control polymers. Rebinding studies with pseudoviruses containing SARS-CoV-2 spike protein demonstrate the superior selectivity of the molecularly imprinted matrices, which mimic the interactions of angiotensin-converting enzyme 2 receptors from human cells. The obtained results highlight the potential of SARS-CoV-2 molecularly imprinted polymers for a variety of applications including chem/biosensing and antiviral delivery.

Development and Characterization of Magnetic SARS-CoV-2 Peptide-Imprinted Polymers.

The development of new methods for the rapid, sensitive, and selective detection of SARS-CoV-2 is a key factor in overcoming the global pandemic that we have been facing for over a year. In this work, we focused on the preparation of magnetic molecularly imprinted polymers (MMIPs) based on the self-polymerization of dopamine at the surface of magnetic nanoparticles (MNPs). Instead of using the whole SARS-CoV-2 virion as a template, a peptide of the viral spike protein, which is present at the viral surface, was innovatively used for the imprinting step. Thus, problems associated with the infectious nature of the virus along with its potential instability when used as a template and under the polymerization conditions were avoided. Dopamine was selected as a functional monomer following a rational computational screening approach that revealed not only a high binding energy of the dopamine-peptide complex but also multi-point interactions across the entire peptide template surface as opposed to other monomers with similar binding affinity. Moreover, variables affecting the imprinting efficiency including polymerization time and amount of peptide and dopamine were experimentally evaluated. Finally, the selectivity of the prepared MMIPs vs. other peptide sequences (i.e., from Zika virus) was evaluated, demonstrating that the developed MMIPs were only specific for the target SARS-CoV-2 peptide.

Biomarker imprinted magnetic core-shell nanoparticles for rapid, culture free detection of pathogenic bacteria.

Rapid and selective detection of microorganisms in complex biological systems draws huge attention to address the rising issue of antimicrobial resistance. Diagnostics based on the identification of whole microorganisms are laborious, time-consuming and costly, thus alternative strategies for early clinical diagnosis include biomarker based microbial detection. This paper describes a low-cost, easy-to-use method for the detection of Pseudomonas aeruginosa infections by specifically identifying a biomarker pyocyanin, using surface-molecularly imprinted nanoparticles or "plastibodies". The selective nanopockets are created by templating pyocyanin onto 20 nm allyl-functionalized magnetic nanoparticles coated with a thin layer of the acrylamide-based polymer. This functional material with an impressive imprinting factor (IF) of 5 and a binding capacity of ∼2.5 mg g-1 of polymers can be directly applied for the detection of bacteria in complex biological samples based on the presence of pyocyanin. These MIPs are highly selective and sensitive to pyocyanin and can consistently bind with pyocyanin in repeated use. Finally, the facile and efficient capture of pyocyanin has versatile applications ranging from biomarker based culture free detection of P. aeruginosa to monitoring of the therapeutic regime, in addition to developing a new class of antibiotics.

Phenotyping for Nitrogen Use Efficiency: Rice Genotypes Differ in N-Responsive Germination, Oxygen Consumption, Seed Urease Activities, Root Growth, Crop Duration, and Yield at Low N.

The biological improvement of fertilizer nitrogen use efficiency (NUE) is hampered by the poor characterization of the phenotype and genotype for crop N response and NUE. In an attempt to identify phenotypic traits for N-response and NUE in the earliest stages of plant growth, we analyzed the N-responsive germination, respiration, urease activities, and root/shoot growth of 21 Indica genotypes of rice (Oryza sativa var. indica). We found that N delays germination from 0 to 12 h in a genotype-dependent and source-dependent manner, especially with urea and nitrate. We identified contrasting groups of fast germinating genotypes such as Aditya, Nidhi, and Swarnadhan, which were also least delayed by N and slow germinating genotypes such as Panvel 1, Triguna, and Vikramarya, which were also most delayed by N. Oxygen uptake measurements in the seeds of contrasting genotypes revealed that they were affected by N source in accordance with germination rates, especially with urea. Germinating seeds were found to have endogenous urease activity, indicating the need to explore genotypic differences in the effective urea uptake and metabolism, which remain unexplored so far. Urea was found to significantly inhibit early root growth in all genotypes but not shoot growth. Field evaluation of 15 of the above genotypes clearly showed that germination rates, crop duration, and yield are linked to NUE. Slow germinating genotypes had longer crop duration and higher yield even at lower N, indicating their higher NUE, relative to fast germinating or short duration genotypes. Moreover, longer duration genotypes suffered lesser yield losses at reduced N levels as compared to short duration genotypes, which is also a measure of their NUE. Together, these results indicate the potential of germination rates, crop duration, urea utilization and its effect on root growth in the development of novel phenotypic traits for screening genotypes and crop improvement for NUE, at least in rice.