Analytical ultracentrifugation (AUC) is a powerful and versatile tool for studying biomolecular interactions. The purpose of this commentary is to provide foundational knowledge of the technique and its uses through the presentation of two case studies in which AUC provides key data to answer research questions. The first case study concerns a practical formulation problem associated with mRNA-based vaccines. The second case study showcases how we tackle the problem of defining the properties of a protein-DNA interaction that regulates gene expression. We place AUC in the context of other biophysical techniques that we use in the Biomolecular Interaction Centre, based at the University of Canterbury in Ōtautahi Christchurch. We hope this work may prove helpful for protein biochemists and biophysicists in Aotearoa New Zealand in selecting appropriate approaches for investigating biomolecular interactions and encourage them to contact us if any of the resources presented herein may be useful to them. We also use a portion of this commentary to acknowledge and document the foundational contributions of the early innovators in AUC in Aotearoa New Zealand.
Biomolecular condensates are dynamic, membrane-free compartments that continuously exchange molecules with their surroundings. The dwell time, defined as the time a molecule remains inside a condensate between entry and exit, determines how extensively the molecule can explore the dense phase and encounter potential binding partners or reaction sites, thereby modulating condensate function. Motivated by our single-molecule measurements of RNA dwell times, we developed an analytical theory to understand dwell-time distributions in biomolecular condensates. Our theory predicts that the dwell-time distributions generally exhibit an early-time power-law regime followed by a late-time exponential tail. The form of the distribution encodes the rate-limiting mechanism of molecular escape: dense-phase diffusion-limited transport feature a -1.5 power law with an exponential tail set by a diffusion timescale, whereas interfacial barrier-crossing-limited transport feature a - 0.5 power law with a decay governed by a barrier-crossing timescale. These distinct signatures provide a direct readout of the physical processes that control molecular retention in condensates, with implications for both natural and synthetic condensates.
The escalating global prevalence of Alzheimer's disease (AD) requires the development of sensitive, non-invasive diagnostic strategies capable of detecting pathological changes previous the clinical onset. By exploiting the spontaneous formation of the biomolecular corona (BC) around nanoparticles (NPs), it's possible to capture a rich, disease-specific fingerprint from the plasma that reflects systemic alterations often invisible to traditional diagnostic assays. In the present study, we demonstrate the efficacy of an innovative nanotechnological platform utilizing a synergistic dual-silica NPs system (comprising amino- and sulfonate-functionalized surfaces) integrated with proteomic and lipidomic profiling of the NP-associated BC. Our results revealed a significant enrichment of ribosomal machinery in the BC of AD patients, contrasted by a simultaneous decrease of glycolytic enzymes and mitochondrial respiratory components. This metabolic impairment is further corroborated by the lipidomic profile, which shows a reduction in short-chain acyl-carnitines (C2, C3, C5) and essential membrane phospholipids. Additionally, the observed loss of structural proteins, such as Cofilin-1 and Vinculin, contributes to a comprehensive molecular fingerprint unique to the AD phenotype.
Plant cell walls are dynamic composite structures whose biogenesis, remodelling, and integrity maintenance require coordinated regulation across biosynthetic, trafficking, sensing, and signalling pathways. Plasma membrane-localised receptor kinases and mechanosensitive channels monitor wall status and transduce perturbations into intracellular responses, whilst biomolecular condensates, membrane-less or membrane-associated assemblies formed through liquid-liquid phase separation and related processes, have emerged as candidate organisational features of several of these pathways. Direct experimental evidence linking condensates to cell wall function nonetheless remains sparse, and for many systems it is unclear whether observed puncta represent bona fide phase-separated assemblies. In this review we survey cell wall biogenesis and integrity pathways during development and under stress and critically evaluate where condensates plausibly participate. To keep claims proportionate to the evidence, we apply an explicit hierarchy, classifying each system as direct, indirect, contextual, or speculative. On this basis, the RALF-pectin system, in which extracellular phase separation generates signalling platforms that recruit the receptor kinase FERONIA and its co-receptor LLG1 as client proteins, remains the only directly validated example; most other associations, including P-bodies, stress granules, and nuclear transcriptional condensates, appear to respond to osmotic stress or molecular crowding arising as secondary consequences of wall perturbations. We further assess how computational and artificial intelligence approaches might complement experimental work, alongside their present limitations for plant systems.
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Subunit vaccines are considered the safest immunization platforms but typically require adjuvants to elicit robust immune responses. Although nanoparticles have emerged as promising adjuvants, biogenic silver nanoparticles (AgNPs) produced by mycosynthesis remain largely unexplored. Herein, nine different AgNPs were mycosynthesized using local strains of Phanerochaete chrysosporium, Penicillium expansum and Punctularia atropurpurascens grown in three different culture media (PDB, MEB, MGYP). Mycosynthesized AgNPs were all shown to be spherical, negatively charged and containing fungal proteins within the biomolecular capping. Additionally, although in vitro biocompatibility assessments showed AgNPs-specific differences in haemolytic and cytotoxic activities, no signs of acute toxicity were observed in mice. The adjuvant potential of AgNPs was further evaluated in ovalbumin-immunized mice, showing that four AgNPs displayed significant immunoenhancement activity with an outstanding IgG2a-polarizaing effect. Adjuvant and IgG subclass polarizing activities were both shown to be dose dependent. Finally, distal effects induced by selected AgNPs were assessed through faecal microbiota analyses. Remarkably, while Firmicutes and Bacteroidota remained the dominant phyla, AgNPs-treated groups showed compositional shifts consistent with mild immunomodulation. Summing up, our results on biocompatibility, adjuvant capacity, strong and dose-dependent IgG2a-polarizing activity, as well as limited impact on gut microbiota, support mycosynthesized AgNPs as versatile next-generation platforms for developing novel vaccine adjuvants.
Cellular organization in the form of biomolecular condensates is a fundamental regulatory mechanism across all forms of life. Formation of condensates relies on multivalent interactions that are often weak and transient, making them challenging to study experimentally. We have developed Condensate Partitioning by mRNA-Display (CPmD) to measure these interactions from the partition free energies of peptides and nucleic acids into reconstituted condensates. CPmD increases experimental throughput by several orders of magnitude, and we apply it to reveal the interactions driving condensate formation of intrinsically disordered proteins. We show that the partition free energies of about one hundred thousand peptides derived from the disordered proteome into a model condensate directly reflect their intrinsic propensity to form condensates. We reveal that amino acid content, linked to hydrophobicity, is the primary determinant of phase behavior. Additionally, CPmD uniquely resolves subtle sequence-dependent contributions that can encode specificity. CPmD thus provides a powerful tool to decipher how weak interactions between protein and RNA regulate biological function through condensate formation.
Engineering the free-energy surfaces (FES) of proteins and peptides is central to controlling conformational ensembles and their responses to perturbations. However, predicting how chemical modifications such as point mutations reshape the FES and shift conformational equilibria remains challenging, particularly in data-scarce settings. Building on the Collective Variables for Free-Energy Surface Tailoring (CV-FEST) framework, we develop a computational approach that leverages short, unbiased molecular dynamics trajectories to guide mutation analysis. Using the ten-residue β-hairpin CLN025 and a systematic library of its single-point mutants, we apply Harmonic Linear Discriminant Analysis (HLDA) to extract collective variables from the conformational data. We find that the HLDA eigenvector learned solely from short wild-type trajectories provides residue-level insights into the propensity of mutations at specific positions to thermodynamically stabilize or destabilize the folded state. Extending this analysis, we show that shifts in the leading HLDA eigenvalue across mutants, a measure of changes in separability between the conformational ensembles along the HLDA coordinate, correlate strongly with mutation-induced changes in the free-energy difference between states, as reflected in melting temperatures. Benchmarked against Replica-Exchange Molecular Dynamics simulations, these findings suggest a promising and computationally affordable route toward guiding the engineering of biomolecular free-energy landscapes.
Intracellular chromophores {e.g., NADH [reduced form of nicotinamide adenine dinucleotide (oxidized form)] and FAD (flavin adenine dinucleotide)} play a central role in regulation of cellular metabolism. Although autofluorescence has been extensively used for label-free mapping of chromophores inside a cell, its sensitivity and molecular specificity are constrained by the low quantum yield and the fluorescence spectral overlap. Here, we address these challenges by using a photothermal approach to measure the optical absorption of chromophores rather than its autofluorescence. Our two-photon photothermal (2PPT) microscope exploits localized thermal transients generated through two-photon absorption, enabling detection of chromophore-specific signatures beyond the reach of autofluorescence. We demonstrate submicromolar limits of detection for the metabolic coenzymes NADH and FAD of 0.87 and 0.99 μM, respectively. Such high sensitivity enables differentiating the influence of mitochondrial shapes on metabolism. 2PPT can identify the biomolecular source of contrast from cellular mitochondria in a label-free manner on the basis of spectroscopy. 2PPT microscopy is used to study metabolic alterations of mitochondria in cancer under chemotherapy at the single-organelle level.
Quantum mechanical (QM) cluster models provide an effective framework for mechanistic studies of enzymatic reactions but remain computationally demanding. Neural network potentials (NNPs) offer a promising route to reduce this cost, but enzymes present challenges beyond small molecules, including large system sizes, implicit-solvent environments, substantial polarization, and charge transfer. Here, we present an integrated software framework for efficient NNP training for mechanistic studies of enzymes, demonstrated on QM cluster models of S-adenosyl-L-methionine-dependent methyltransferases (MTases). Our Enerzyme code introduces modular electrostatics-aware NNP architectures and combines automated QM-cluster construction with reactive dataset generation. The Enerzymette subpackage automates reaction pathway exploration at both NNP and DFT levels. We show that iterative flexible scans and nudged elastic band calculations impose stricter requirements on NNPs than conventional dataset metrics. Nevertheless, NNPs trained on fewer than 1,000 system-specific datapoints reproduce reaction energetics and transition-state structures for MTase clusters containing up to 545 atoms with near-chemical accuracy. Direct supervision of atomic charges and consistent dielectric screening substantially improve simulation stability and accuracy, while multitask-learned atomic charges capture charge transfer and polarization trends and provide chemically meaningful descriptors of reactivity. Finally, transferability across chemically diverse catechol O-methyltransferase substrates indicates that NNPs learn generalizable reactivity patterns as training data expand across multiple enzymes. Together, these results establish a foundation for accelerating enzyme mechanistic studies and guide future NNP development for biomolecular reactivity.
A significant proportion of global photosynthetic carbon fixation relies on the pyrenoid, a biomolecular condensate found in the chloroplast of most unicellular algae, where the CO2-fixing enzyme Rubisco is exposed to saturating concentrations of the gas. In this review, we highlight recent advances in our understanding of the molecular basis of diverse pyrenoids. Phase separation of phylogenetically distant Rubiscos is mediated by convergently evolved linker proteins, with an emerging theme of pyrenoid condensation being organized via Rubisco-binding motifs. To minimize CO2 leakage out of the pyrenoid, starch sheaths and protein shells have evolved to surround the pyrenoid in various algal lineages. Crucially, the pyrenoid is a biomolecular condensate with an increasingly well-defined function that has evolved multiple times over the past billions of years. The emerging similarities and differences of these various pyrenoids will inform our appreciation of phase separation in biology and empower engineering efforts aimed at enhancing photosynthetic CO2 assimilation.
Liquid-liquid phase separation (LLPS) drives the formation of membraneless biomolecular condensates central to cellular organization, but predictive models bridging molecular interactions and macroscopic phase behaviour remain elusive. Here we present a continuum reaction-diffusion model that captures key multiscale features of LLPS. The framework maps the phase space for condensate nucleation and growth, revealing a threshold in dilute-phase diffusivity above which droplet formation is enhanced. We find that stronger interconversion kinetics between the dilute and dense phases accelerate droplet coarsening and Ostwald ripening, consistent with faster growth of large droplets at the expense of smaller ones. Remarkably, our multi-component framework naturally produces ring-like dilute-phase shells around condensates. This phenomenon, observed experimentally, is inaccessible in classical single-field phase-separation models which lack explicit multi-component interactions. Incorporating stochastic fluctuations further accelerates phase separation, highlighting noise-sensitive regimes. By integrating molecular-level interactions into a continuum framework, the model achieves mechanistic transparency alongside computational efficiency. It offers predictive power to interpret and control LLPS across diverse biological and materials contexts.
This review summarizes the evolution of our research on anticancer agents, from early efforts on hypoxia-selective cytotoxins to more recent developments in chemoprevention, molecular targeting, and radiopharmacy. Initial studies focused on the design of N-oxide-containing heterocycles as bioreductive-prodrugs activated under tumor hypoxia. While early triazine N-oxides and furoxans showed limited selectivity, these studies underscored the importance of redox-properties in biological activities. This led to the identification of phenazine 5,10-dioxides as a more suitable pharmacophore, affording compounds with improved potency- and hypoxia-selectivity, supported by mechanistic-, physicochemical-, and in vivo studies. Parallel efforts explored metal-based complexes and formulation strategies enhancing bioavailability and therapeutic performance. Alongside these efforts, cancer chemopreventive-agents were investigated, particularly chalcone-derived scaffolds and related hybrids capable of modulating phase I/II enzymes through Nrf2 activation. Additionally, attention has shifted toward targeted- and diagnostic-approaches, including radiopharmaceuticals for hypoxia-imaging and the use of biomolecular recognition systems, such as aptamers, polypeptides, and antibodies, to selectively address tumor-associated biomarkers. These strategies include aptamer-based biotherapeutics for drug delivery and imaging, as well as approaches combining tyrosine kinase receptor targeting with BNCT. Furthermore, bioorthogonal-methodologies have been explored enabling selective in situ activation and targeting. Together, these studies illustrate a multidisciplinary approach integrating chemistry, biology, and pharmacology toward more selective anticancer strategies.
The mammalian brain uniquely expresses a large repertoire of extra-long genes critical for neuronal development and function, yet these transcripts are particularly vulnerable to dysregulation linked to neurological disorders, such as autism spectrum disorder and amyotrophic lateral sclerosis. The molecular mechanisms that ensure their stable expression remain poorly understood. Here, we show that the RNA-binding protein SFPQ forms meshwork-like biomolecular condensates that scaffold a multidimensional gene regulatory complex essential for long-gene expression. Super-resolution microscopy and functional perturbation assays demonstrate that disruption of SFPQ condensates impairs both extra-long gene expression and splicing. Proximity-dependent biotin labeling combined with mass spectrometry (BioID-MS) reveals that SFPQ condensates recruit transcriptional elongation factors, splicing regulators, and chromatin remodelers. Notably, many of these interactors overlap with autism-associated genes, suggesting direct disease relevance. These findings define a higher-order nuclear architecture organized by SFPQ and provide mechanistic insight into long-gene transcriptopathies underlying neurological disorders.
Naphthyl-functionalized half-sandwich Ir(III) complexes were designed as non‑platinum metal candidates for colorectal cancer cell growth inhibition, the naphthyl group was purposefully introduced in the ligands in order to facilitate DNA intercalation and enhancing biomolecular interactions. In this work, eight naphthyl-functionalized half-sandwich Ir(III) complexes (L-Ir(cp)Cl) [cp = pentamethylcyclopentadienyl] (C1a-C4a, C1b-C4b) were designed and synthesized bearing central pyridine- or pyrimidine-based N, N-chelating ligands. The target complexes were obtained in high yields via simple single step reaction and characterized by 1H NMR, 13C NMR, UV-vis, IR spectroscopy and high-resolution mass spectrometry (HR-MS). The structures of six complexes (C3a-C4a, C1b-C4b) were determined by single-crystal X-ray analysis, showing a typical half-sandwich "three-legged piano-stool" geometry with a chloride ancillary ligand (Ir-Cl), which may be relevant to their biological activity. In vitro antiproliferative activity was assessed in colorectal cancer RPMI 4788 and LOVO cells via MTT assays. In both these series C1b and C2b exhibited potent proliferation-inhibitory effects, with stronger activity in RPMI 4788 cells, and C2b outperforming C1b. Cancer cell imaging, flow cytometry, and clonogenic assays confirmed strong inhibition of cell proliferation. Concentration- and time-dependent migration assays showed significantly reduced cancer cell migration. Cell-cycle analysis suggested S-phase accumulation in RPMI 4788 cells, and C2b treatment decreased the expression of Cyclin D1 and CDK4. Western blot analysis revealed changes in the representative proteins associated with apoptosis and cell growth, including PARP, Caspase-3, Bcl-2, AKT, and mTOR. This study provided experimental evidence supporting these novel Ir(III) complexes, especially C2b as potential in vitro antiproliferative agents in colorectal cancer cells that need to be further explored in other cancers by detailed in vitro and in vivo mechanistic investigations.
Immune checkpoint blockade has achieved remarkable success in cancer treatment; however, enhancing its efficacy remains a challenge. Here we identified an immunoregulatory micropeptide encoded by the long noncoding RNA USP30-AS1 gene, highly expressed in tumor-associated macrophages. The so-designated UEIS (USP30-AS1-encoded immune suppressor) drives macrophages toward a protumorigenic phenotype, thereby inhibiting antitumor T cell immunity. Mechanistically, UEIS is induced in macrophages by cGAS-STING-type I interferon signaling at a relatively late stage following tumoral DNA stimulation, and exerts a negative feedback regulation on the type I interferon signaling by forming biomolecular condensates with TBK1, thereby inhibiting its interaction with STING. Both an intrinsically disordered region and an alpha helix at the extreme N terminus of UEIS were essential for its function. A peptide designed to disrupt UEIS-TBK1 condensation successfully inhibited UEIS function in tumor-associated macrophages, leading to reduced tumor growth and increased response to immune checkpoint blockade. Thus, these findings highlight UEIS as a promising therapeutic target for cancer treatment.
This review highlights the quartz crystal microbalance (QCM) as a powerful tool for label-free, real-time analysis of biomolecular interactions, with a specific focus on protein-ligand binding in drug discovery. It underscores the unique sensitivity of QCM to nanogram-level mass changes, comparing it favorably to techniques like SPR and ITC. This article consolidates strategies for overcoming central challenges, including optimizing protein immobilization and interpreting the small signals from low-mass ligand binding. By providing a comprehensive framework of theoretical principles and practical solutions, this review aims to advance the use of QCM not only in rational drug design but also in the development of robust biosensors for diagnostics and environmental monitoring.
Gut microbial metabolites, particularly short-chain fatty acids (SCFAs) like butyrate, play a significant role in modulating non-alcoholic fatty liver disease (NAFLD). While animal studies show that butyrate-producing microbes can improve liver function, full recovery is hindered by unintended side effects from commensal bacteria. These underlying biomolecular mechanisms remain elusive, due to the lack of in vitro coculture models capable of systematically examine both the therapeutic benefits of engineered microbial metabolites and their potential adverse impacts. To address this, we developed a modular microfluidic platform to study the effects of live microbial metabolites on hepatic steatosis and liver function. We created a microfluidic-based hepatic steatosis model integrated with a compartmentalized microbial module, facilitating the study of how metabolites produced by live microbes affected the liver model. We compared the effects of synthetic SCFA supplementation with those of coculturing with a control and butyrate-producing E. coli Nissle 1917 (EcN) strains on hepatic steatosis. Our findings showed that live microbial coculture did not phenocopy exogenous SCFA treatment. While both treatments reduced steatotic lipid accumulation, live microbes induced inflammatory and hepatic metabolic changes, suggesting contributions from additional microbial factors, emphasizing the need to thoroughly assess side effects in liver disease treatment.
Liquid-liquid phase separation (LLPS) plays a fundamental role in orchestrating biomolecular condensation and the formation of membraneless organelles. Inspired by this biological principle, there is growing interest in exploiting LLPS as a strategic pathway to guide the self-assembly of synthetic polymers into well-defined nanostructures. Herein, we investigate the LLPS-guided self-assembly of C18H37-substituted poly(ε-caprolactone)-b-poly(N,N-dimethylacrylamide) (C18PCL-b-PDMA) block copolymers (BCPs), where the core-forming block PCL bears octadecyl side chains at different substitution sites (ε, β/δ, γ). Using εC18PCL52-b-PDMA260 as a primary model, we demonstrate that the self-assembly pathway and final morphology can be strategically manipulated by controlling the phase-separation kinetics. After applying a heating-cooling-aging process, the experimental results show that slow cooling rate leads to a multi-step nucleation-growth process involving various metastable intermediates, whereas accelerated cooling rate directly induces the formation of polymer-rich droplets that act as nucleation precursors, effectively lowering the energy barrier toward stable cylinders. Furthermore, precise control over LLPS can be achieved via a solvent-exchange method, where the solvent quality dictates droplet stability and the subsequent transformation kinetics into cylinders. Comparative studies with β/δ- and γ-substituted analogues reveal that the substitution position critically influences the chain mobility to undergo conformational ordering, thereby affecting the assembly rate and structural outcome. This work underscores LLPS as a versatile and powerful strategy for regulating the self-assembly pathways of BCPs, providing fundamental insights into non-equilibrium assembly processes and offering a robust platform for the design of functional polymeric nanomaterials with tailored hierarchical structures.
Infections arising from a broadening variety of viruses are becoming increasingly widespread due to greater zoonotic transmission, with the COVID-19 pandemic exemplifying a global event that claimed the lives of millions worldwide. While targeted vaccines are being developed to thwart the spread of viral infections, they often become available to the public in response to an (expected) outbreak and must be repeatedly adjusted to account for mutations. An alternative to this strategy instead focuses on infection prevention by inactivating viruses prior to human exposure. In this study, we examine the inactivation kinetics of a broad range of infectious viruses on a self-cleaning polymer that functions by a surface pH-drop mechanism upon hydration. Photo-induced surface microscopy confirms that the sulfonic acid groups responsible for proton transport initially reside on the polymer surface, where protons lower the pH of the aqueous layer in contact with the polymer to below unity. This additive-free mechanism results in pH-driven inactivation of three coronaviruses (including SARS-CoV-2), human adenovirus, Tulane virus (a human norovirus surrogate), and four high-consequence viruses (Sudan virus, Marburg virus, Lassa virus, and Nipah virus), often reaching the limit of detection in 10 min or less.