Can super-resolution microscopy become a standard characterization technique for materials chemistry?

Supramolecular Guest Exchange in Cucurbit[7]uril for Bioorthogonal Fluorogenic Imaging across the Visible Spectrum

Fluorogenic probes that unmask fluorescence signals in response to bioorthogonal reactions are a powerful new addition to biological imaging. They can significantly reduce background fluorescence and minimize nonspecific signals, potentially enabling real-time, high-contrast imaging without the need to wash out excess fluorophores. While diverse classes of highly refined synthetic fluorophores are now readily available, integrating them into a bioorthogonal fluorogenic scheme still requires extensive design efforts and customized structural alterations to optimize quenching mechanisms for each specific fluorophore scaffold. Herein, we present a highly generalizable strategy that can produce an efficient bioorthogonal fluorogenic response from essentially any readily available fluorophore without further structural alterations. We designed this strategy based on the macrocyclic cucurbit[7]uril (CB7) host, where a fluorogenic response is achieved by programming a guest exchange reaction within the macrocyclic cavity. We employed this strategy to rapidly create fluorogenic probes across the visible spectrum from diverse fluorophore scaffolds, which enabled no-wash imaging in live cells and tissues with minimal background signal. Finally, we demonstrated that this strategy can be combined with metabolic labeling for fluorogenic detection of metabolically tagged mycobacteria under no-wash conditions and paired with covalently clickable probes for high-contrast super-resolution and multiplexed imaging in cells and tissues.

Visualizing the Heterogeneity in Homogeneous Supramolecular Polymers

The dynamic properties of supramolecular polymers enable new functionality beyond the limitations of conventional polymers. The mechanism of the monomer exchange between different supramolecular polymers is proposed to be closely associated with local disordered domains within the supramolecular polymers. However, a direct detection of such heterogeneity has never been experimentally probed. Here, we present the direct visualization of the local disordered domains in the backbone of supramolecular polymers by a super-resolution microscopy technique: Nile Red-based spectrally resolved point accumulation for imaging in nanoscale topography (NR-sPAINT). We investigate the local disordered domains in trisamide-based supramolecular polymers comprising a (co)assembly of benzene-1,3,5-tricarboxamide (BTA) and a variant with one of the amide bonds inverted (iBTA). The NR-sPAINT allows us to simultaneously map the spatial distribution and polarity of the local disordered domains along the polymers with a spatial precision down to ∼20 nm. Quantitative autocorrelation and cross-correlation analysis show subtle differences in the spatial distribution of the disordered domains between polymers composed of different variants of BTA monomers. Further, statistical analysis unraveled high heterogeneity in monomer packing at both intra- and interpolymer levels. The results reported here demonstrate the necessity of investigating the structures in soft materials at nanoscale to fully understand their intricacy.

Direct Imaging of Protein Clusters in Metal-Organic Frameworks

Protein@metal-organic frameworks (P@MOFs) prepared by coprecipitation of protein, metal ions, and organic ligands represent an effective method for protein stabilization with a wide spectrum of applications. However, the formation mechanism of P@MOFs via the coprecipitation process and the reason why proteins can retain their biological activity in the frameworks with highly concentrated metal ions remain unsettled. Here, by a combined methodology of single molecule localization microscopy and clustering analysis, we discovered that in this process enzyme molecules form clusters with metal ions and organic ligands, contributing to both the nucleation and subsequent crystal growth. We proposed that the clusters played an important role in the retention of overall enzymatic activity by sacrificing protein molecules on the cluster surface. This work offers fresh perspectives on protein behaviors in the formation of P@MOFs, inspiring future endeavors in the design and development of artificial bionanocomposites with high biological activities.

Automated Generation and Analysis of Molecular Images Using Generative Artificial Intelligence Models

The development of scanning probe microscopy (SPM) has enabled unprecedented scientific discoveries through high-resolution imaging. Simulations and theoretical analysis of SPM images are equally important as obtaining experimental images since their comparisons provide fruitful understandings of the structures and physical properties of the investigated systems. So far, SPM image simulations are conventionally based on quantum mechanical theories, which can take several days in tasks of large-scale systems. Here, we have developed a scanning tunneling microscopy (STM) molecular image simulation and analysis framework based on a generative adversarial model, CycleGAN. It allows efficient translations between STM data and molecular models. Our CycleGAN-based framework introduces an approach for high-fidelity STM image simulation, outperforming traditional quantum mechanical methods in efficiency and accuracy. We envision that the integration of generative networks and high-resolution molecular imaging opens avenues in materials discovery relying on SPM technologies.

Detecting Disruption of HER2 Membrane Protein Organization in Cell Membranes with Nanoscale Precision

The spatiotemporal organization of proteins within the cell membrane can affect numerous biological functions, including cell signaling, communication, and transportation. Deviations from normal spatial arrangements have been observed in various diseases, and a better understanding of this process is a key stepping stone to advancing development of clinical interventions. However, given the nanometer length scales involved, detecting these subtle changes has primarily relied on complex super-resolution and single-molecule imaging methods. In this work, we demonstrate an alternative fluorescent imaging strategy for detecting protein organization based on a material that exhibits a unique photophysical behavior known as aggregation-induced emission (AIE). Organic AIE molecules have an increase in emission signal when they are in close proximity, and the molecular motion is restricted. This property simultaneously addresses the high background noise and low detection signal that limit conventional widefield fluorescent imaging. To demonstrate the potential of this approach, the fluorescent molecule sensor is conjugated to a human epidermal growth factor receptor 2 (HER2)-specific antibody and used to investigate the spatiotemporal behavior of HER2 clustering in the membrane of HER2-overexpressing breast cancer cells. Notably, the disruption of HER2 clusters in response to an FDA-approved monoclonal antibody therapeutic (Trastuzumab) is successfully detected using a simple widefield fluorescent microscope. While the sensor demonstrated here is optimized for sensing HER2 clustering, it is an easily adaptable platform. Moreover, given the compatibility with widefield imaging, the system has the potential to be used with high-throughput imaging techniques, accelerating investigations into membrane protein spatiotemporal organization.

Advanced optical imaging for the rational design of nanomedicines

Despite the enormous potential of nanomedicines to shape the future of medicine, their clinical translation remains suboptimal. Translational challenges are present in every step of the development pipeline, from a lack of understanding of patient heterogeneity to insufficient insights on nanoparticle properties and their impact on material-cell interactions. Here, we discuss how the adoption of advanced optical microscopy techniques, such as super-resolution optical microscopies, correlative techniques, and high-content modalities, could aid the rational design of nanocarriers, by characterizing the cell, the nanomaterial, and their interaction with unprecedented spatial and/or temporal detail. In this nanomedicine arena, we will discuss how the implementation of these techniques, with their versatility and specificity, can yield high volumes of multi-parametric data; and how machine learning can aid the rapid advances in microscopy: from image acquisition to data interpretation.

Impact of subtle intermolecular interactions on the structure and dynamics of multicomponent supramolecular polymers

Multicomponent supramolecular polymers offer versatile dynamic and functional properties; however, the influence of the monomer chemical structures on their structure-dynamics-function relationship remains unclear. In this study, we investigated the subtle variations in monomer interactions using one monomer and its two dopant derivatives, with functionalization away from the self-assembling core. We systematically investigated their multicomponent supramolecular polymers using a combination of spectroscopy and super-resolution microscopy. Our results highlight the significant impact of the supplementary intermolecular interactions, resulting from the functional motifs located away from the core and present in small quantities, on the microstructure and dynamics. Thus, a comprehensive approach, combining spectroscopy, microscopy, and well-designed experiments, is essential for assessing multicomponent supramolecular polymers. These findings have implications for the rational design of functional multicomponent supramolecular materials.

Super-resolution imaging of antibody-conjugated biodegradable periodic mesoporous organosilica nanoparticles for targeted chemotherapy of prostate cancer

Biodegradable periodic mesoporous organosilica nanoparticles (nanoPMOs) are widely used as responsive drug delivery platforms for targeted chemotherapy of cancer. However, the evaluation of their properties such as surface functionality and biodegradability is still challenging, which has a significant impact on the efficiency of chemotherapy. In this study, we have applied direct stochastic optical reconstruction microscopy (dSTORM), a single-molecule super-resolution microscopy technique, to quantify the degradation of nanoPMOs triggered by glutathione and the multivalency of antibody-conjugated nanoPMOs. Subsequently, the effect of these properties on cancer cell targeting, drug loading and release capability, and anticancer activity is also studied. Due to the higher spatial resolution at the nanoscale, dSTORM imaging is able to reveal the structural properties (i.e., size and shape) of fluorescent and biodegradable nanoPMOs. The quantification of nanoPMOs' biodegradation using dSTORM imaging demonstrates their excellent structure-dependent degradation behavior at a higher glutathione concentration. The surface functionality of anti-M6PR antibody-conjugated nanoPMOs as quantified by dSTORM imaging plays a key role in prostate cancer cell labeling: oriented antibody is more effective than random ones, while high multivalency is also effective. The higher biodegradability and cancer cell-targeting properties of nanorods conjugated with oriented antibody (EAB4H) effectively deliver the anticancer drug doxorubicin to cancer cells, exhibiting potent anticancer effects.

Beyond DNA: new probes for PAINT super-resolution microscopy

In the last decade, point accumulation for imaging in nanoscale topography (PAINT) has emerged as a versatile tool for single-molecule localization microscopy (SMLM). Currently, DNA-PAINT is the most widely used, in which a transient stochastically binding DNA docking-imaging pair is used to reconstruct specific characteristics of biological or synthetic materials on a single-molecule level. Slowly, the need for PAINT probes that are not dependent on DNA has emerged. These probes can be based on (i) endogenous interactions, (ii) engineered binders, (iii) fusion proteins, or (iv) synthetic molecules and provide complementary applications for SMLM. Therefore, researchers have been expanding the PAINT toolbox with new probes. In this review, we provide an overview of the currently existing probes that go beyond DNA and their applications and challenges.

Unsupervised Data-Driven Reconstruction of Molecular Motifs in Simple to Complex Dynamic Micelles

The reshuffling mobility of molecular building blocks in self-assembled micelles is a key determinant of many their interesting properties, from emerging morphologies and surface compartmentalization, to dynamic reconfigurability and stimuli-responsiveness. However, the microscopic details of such complex structural dynamics are typically nontrivial to elucidate, especially in multicomponent assemblies. Here we show a machine-learning approach that allows us to reconstruct the structural and dynamic complexity of mono- and bicomponent surfactant micelles from high-dimensional data extracted from equilibrium molecular dynamics simulations. Unsupervised clustering of smooth overlap of atomic position (SOAP) data enables us to identify, in a set of multicomponent surfactant micelles, the dominant local molecular environments that emerge within them and to retrace their dynamics, in terms of exchange probabilities and transition pathways of the constituent building blocks. Tested on a variety of micelles differing in size and in the chemical nature of the constitutive self-assembling units, this approach effectively recognizes the molecular motifs populating them in an exquisitely agnostic and unsupervised way, and allows correlating them to their composition in terms of constitutive surfactant species.

The power of super-resolution microscopy in modern biomedical science

Super-resolution microscopy (SRM) technology that breaks the diffraction limit has revolutionized the field of cell biology since its appearance, which enables researchers to visualize cellular structures with nanometric resolution, multiple colors and single-molecule sensitivity. With the flourishing development of hardware and the availability of novel fluorescent probes, the impact of SRM has already gone beyond cell biology and extended to nanomedicine, material science and nanotechnology, and remarkably boosted important breakthroughs in these fields. In this review, we will mainly highlight the power of SRM in modern biomedical science, discussing how these SRM techniques revolutionize the way we understand cell structures, biomaterials assembly and how assembled biomaterials interact with cellular organelles, and finally their promotion to the clinical pre-diagnosis. Moreover, we also provide an outlook on the current technical challenges and future improvement direction of SRM. We hope this review can provide useful information, inspire new ideas and propel the development both from the perspective of SRM techniques and from the perspective of SRM's applications.

Nanoparticles for super-resolution microscopy: intracellular delivery and molecular targeting

Following an overview of the approaches and techniques used to acheive super-resolution microscopy, this review presents the advantages supplied by nanoparticle based probes for these applications. The various clases of nanoparticles that have been developed toward these goals are then critically described and these discussions are illustrated with a variety of examples from the recent literature.

Calcite-Assisted Localization and Kinetics (CLocK) Microscopy

Localization-based super-resolution imaging techniques have improved the spatial resolution of optical microscopy well below the diffraction limit, yet encoding additional information into super-resolved images, such as anisotropy and orientation, remains a challenge. Here we introduce calcite-assisted localization and kinetics (CLocK) microscopy, a multiparameter super-resolution imaging technique easily integrated into any existing optical microscope setup at low cost and with straightforward analysis. By placing a rotating calcite crystal in the infinity space of an optical microscope, CLocK microscopy provides immediate polarization and orientation information while maintaining the ability to localize an emitter/scatterer with <10 nm resolution. Further, kinetic information an order of magnitude shorter than the integration time of the camera is encoded in the unique point spread function of a CLocK image, allowing for new mechanistic insight into dynamic processes such as single-nanoparticle dissolution and single-molecule surface-enhanced Raman scattering.

Personal Perspective on Understanding Low Molecular Weight Gels

Low molecular weight gels are formed by the self-assembly of small molecules into anisotropic structures that form a network capable of immobilizing the solvent. Such gels are common, with a huge number of different examples existing, and they have many applications. However, there are still significant gaps in our understanding of these systems and challenges that need to be addressed if we are to be able to fully design such systems. Here, a number of these challenges are discussed.