Sukhvir Kaur Bhangu

Hybridization of common motifs from known antimicrobial peptides (AMPs) is a promising strategy for designing a new class of antimicrobial agents with improved activity. Herein, the machine learning-generated peptide sequence IIKLLGVLAKFVLGQ-NH₂ was utilized for sequence optimization using an alanine scan and alignment with known AMPs to identify the motifs with the highest occurrences. Motifs were then assembled to obtain positively charged peptides with 12 to 18 amino acid lengths and hydrophobicity >60%. The designed peptides exhibit broad-spectrum antimicrobial activity against multiple Gram-negative and Gram-positive bacterial strains, along with excellent pH and plasma stability. The peptides demonstrate high efficiency in eradicating bacterial biofilms with no resistance development over 300 generations against a "superbug" clinical strain of Acinetobacter baumannii. Additionally, AMPs were biocompatible and promoted fibroblast migration, which accelerated artificial wound closure. This study highlights an innovative strategy for engineering highly effective AMPs with significant potential in combating multidrug-resistant pathogens.

Targeted delivery of therapeutics to lymph nodes (LNs) via minimally invasive subcutaneous injection offers promise to treat B and T cell malignancies, latent HIV-1 reservoirs, and cancer metastasis. However, achieving therapeutic drug levels in subcutaneous tissues and LNs is challenging because of the poor retention and accumulation of soluble drugs. Engineered nanoparticles (NPs) provide a platform for prolonging drug stability and retention in the subcutaneous space and LNs, acting as reservoirs for the sustained release of drugs through the lymphatic system. Yet, their clinical translation for LN drug delivery faces limitations owing to the potential immunogenicity and toxicity of NP material components. Herein, we show that glycogen, a natural and biodegradable polysaccharide NP can be tailored by controlling its size, surface charge, and functional groups to enable the delivery of small and large bioactive molecules in LNs. Upon subcutaneous injection, positively charged glycogen NPs primarily accumulate in the liver and kidneys, whereas negatively charged glycogen NPs accumulate in the liver and lungs, irrespective of their size. Small and positively charged (19 ± 2 nm in diameter; 53 ± 4 mV) glycogen NPs accumulate more efficiently in LNs than the large and positively charged (57 ± 2 nm in diameter; 54 ± 9 mV) or small and negatively charged (13 ± 4 nm in diameter; -27 ± 1 mV) glycogen NPs. Moreover, smaller and slightly positively charged glycogen NPs (16 ± 4 nm in diameter; 10 ± 6 mV) enable the loading and delivery of Cre-recombinase mRNA, small organic molecules and antibodies at the site of injection and LNs. The glycogen NPs are associated with macrophages lining the subcapsular sinus and medullary regions of the LNs but are also detected within the paracortex at the T cell zone. This suggests that the glycogen NPs can overcome the phagocytic cell barrier by saturating the phagocytic capacity of the macrophages at the subcapsular sinus and spread to deeper parts of the paracortex region, providing an avenue for their application in the treatment of lymphatic diseases.

Antimicrobial peptides (AMPs) offer a highly potent alternative solution due to their broad‐spectrum activity and minimum resistance development against the rapidly evolving antibiotic‐resistant pathogens. Herein, to accelerate the discovery process of new AMPs, a predictive and generative algorithm is build, which constructs new peptide sequences, scores their antimicrobial activity using a machine learning (ML) model, identifies amino acid motifs, and assembles high‐ranking motifs into new peptide sequences. The eXtreme Gradient Boosting model achieves an accuracy of ≈87% in distinguishing between AMPs and non‐AMPs. The generated peptide sequences are experimentally validated against the bacterial pathogens, and an accuracy of ≈60% is achieved. To refine the algorithm, the physicochemical features are analyzed, particularly charge and hydrophobicity of experimentally validated peptides. The peptides with specific range of charge and hydrophobicity are then removed, which lead to a substantial increase in an experimental accuracy, from ≈60% to ≈80%. Furthermore, generated peptides are active against different fungal strains with minimal off‐target toxicity. In summary, in silico predictive and generative models for functional motif and AMP discovery are powerful tools for engineering highly effective AMPs to combat multidrug resistant pathogens.

Nanoparticle‐mediated intracellular delivery of oligonucleotides is a complex phenomenon that depends on the architecture and the intracellular trafficking of the engineered nanoparticles. Unravelling the molecular arrangements of oligonucleotides within the nanoparticles as well as their intracellular behavior are essential for designing effective nucleic acid delivery systems. Herein, a simple and general strategy for probing the endosomal escape of nanoparticles carrying oligonucleotides in live cells is reported. A triplex‐forming oligonucleotide probe is designed to target the transcription factor, kappa‐light‐chain‐enhancer of activated B cells (NF‐κB), in the cytosol of cells and to transduce the binding into a fluorescent Förster resonance energy transfer (FRET) signal. The combined use of the triplex‐forming oligonucleotide probe and super‐resolution microscopy enables the elucidation of the morphology, intracellular localization, and endosomal escape of the oligonucleotide‐loaded nanoparticles on a molecular level and with nanoscale resolution. The co‐delivery of the FRET probe and mRNA in cells via lipid‐ and polymer‐ based nanoparticles allow simultaneous correlation of the endosomal escape properties of nanoparticles and gene expression efficiency.

Flexible metal‐organic materials are of growing interest owing to their ability to undergo reversible structural transformations under external stimuli. Here, we report flexible metal‐phenolic networks (MPNs) featuring stimuli‐responsive behavior to diverse solute guests. The competitive coordination of metal ions to phenolic ligands of multiple coordination sites and solute guests (e.g., glucose) primarily determines the responsive behavior of the MPNs, as revealed experimentally and computationally. Glucose molecules can be embedded into the dynamic MPNs upon mixing, leading to the reconfiguration of the metal‐organic networks and thus changes in their physicochemical properties for targeting applications. This study expands the library of stimuli‐responsive flexible metal‐organic materials and the understanding of intermolecular interactions between metal‐organic materials and solute guests, which is essential for the rational design of responsive materials for various applications.

Flexible metal‐organic materials are of growing interest owing to their ability to undergo reversible structural transformations under external stimuli. Here, we report flexible metal‐phenolic networks (MPNs) featuring stimuli‐responsive behavior to diverse solute guests. The competitive coordination of metal ions to phenolic ligands of multiple coordination sites and solute guests (e.g., glucose) primarily determines the responsive behavior of the MPNs, as revealed experimentally and computationally. Glucose molecules can be embedded into the dynamic MPNs upon mixing, leading to the reconfiguration of the metal‐organic networks and thus changes in their physicochemical properties for targeting applications. This study expands the library of stimuli‐responsive flexible metal‐organic materials and the understanding of intermolecular interactions between metal‐organic materials and solute guests, which is essential for the rational design of responsive materials for various applications.

DNA‐based materials have attracted interest due to the tunable structure and encoded biological functionality of nucleic acids. A simple and general approach to synthesize DNA‐based materials with fine control over morphology and bioactivity is important to expand their applications. Here, we report the synthesis of DNA‐based particles via the supramolecular assembly of tannic acid (TA) and DNA. Uniform particles with different morphologies are obtained using a variety of DNA building blocks. The particles enable the co‐delivery of cytosine‐guanine adjuvant sequences and the antigen ovalbumin in model cells. Intramuscular injection of the particles in mice induces antigen‐specific antibody production and T cell responses with no apparent toxicity. Protein expression in cells is shown using capsules assembled from TA and plasmid DNA. This work highlights the potential of TA as a universal material for directing the supramolecular assembly of DNA into gene and vaccine delivery platforms.

DNA‐based materials have attracted interest due to the tunable structure and encoded biological functionality of nucleic acids. A simple and general approach to synthesize DNA‐based materials with fine control over morphology and bioactivity is important to expand their applications. Here, we report the synthesis of DNA‐based particles via the supramolecular assembly of tannic acid (TA) and DNA. Uniform particles with different morphologies are obtained using a variety of DNA building blocks. The particles enable the co‐delivery of cytosine‐guanine adjuvant sequences and the antigen ovalbumin in model cells. Intramuscular injection of the particles in mice induces antigen‐specific antibody production and T cell responses with no apparent toxicity. Protein expression in cells is shown using capsules assembled from TA and plasmid DNA. This work highlights the potential of TA as a universal material for directing the supramolecular assembly of DNA into gene and vaccine delivery platforms.

Amyloid crystals, a form of ordered protein aggregates documented relatively recently, have not been studied as extensively as amyloid fibres. This study investigates the formation of amyloid crystals with low frequency ultrasound (20 kHz) using β-lactoglobulin, as a model protein for amyloid synthesis. Acoustic cavitation generates localised zones of intense shear, with extreme heat and pressure that could potentially drive the formation of amyloid structures at ambient bulk fluid temperatures (20 ± 1 °C). Thioflavin T fluorescence and electron microscopy showed that low-frequency ultrasound at 20 W/cm³ input power induced β-stacking to produce amyloid crystals in the mesoscopic size range, with a mean length of approximately 22 µm. FTIR spectroscopy indicated a shift towards increased intermolecular antiparallel β-sheet content. An increase in sonication time (0–60 min) and input power (4–24 W/cm³) increased the mean crystal length, but this increase was not linearly proportional to sonication time and input power due to the delayed onset of crystal growth. We propose that acoustic cavitation causes protein unfolding and aggregation and imparts energy to aggregates to cross the torsion barrier, to achieve their lowest energy state as amyloid crystals. The study contributes to a further understanding of protein chemistry relating to the energy landscape of folding and aggregation. Ultrasound presents opportunities for practical applications of amyloid structures, presenting a more adaptable and scalable approach for synthesis. Graphical abstract