Combinatorial high throughput methodologies are central for both screening and discovery in synthetic biochemistry and biomedical sciences. They are, however, often reliant on large scale analyses and thus limited by long running time and excessive materials cost. We herein present Single PARticle Combinatorial multiplexed Liposome fusion mediated by DNA (SPARCLD), for the parallelized, multi-step and nondeterministic fusion of individual zeptoliter nanocontainers. We observed directly the efficient (>93%), and leakage free stochastic fusion sequences for arrays of surface tethered target liposomes with six freely diffusing populations of cargo liposomes, each functionalized with individual lipidated ssDNA (LiNA) and fluorescent barcoded by distinct ratio of chromophores. The stochastic fusion results in distinct permutation of fusion sequences for each autonomous nanocontainer. Real-time TIRF imaging allowed the direct observation of >16000 fusions and 566 distinct fusion sequences accurately classified using machine learning.The high-density arrays of surface tethered target nanocontainers ~42,000 containers per mm 2 offers entire combinatorial multiplex screens using only picograms of material.

Protein misfolding in the form of fibrils or spherulites is involved in a spectrum of pathological abnormalities. Our current understanding of protein aggregation mechanisms has primarily relied on the use of spectrometric methods to determine the average growth rates and diffraction-limited microscopes with low temporal resolution to observe the large-scale morphologies of intermediates. We developed a REal-time kinetics via binding and Photobleaching LOcalization Microscopy (REPLOM) super-resolution method to directly observe and quantify the existence and abundance of diverse aggregate morphologies of human insulin, below the diffraction limit and extract their heterogeneous growth kinetics. Our results revealed that even the growth of microscopically identical aggregates, e.g., amyloid spherulites, may follow distinct pathways. Specifically, spherulites do not exclusively grow isotropically but, surprisingly, may also grow anisotropically, following similar pathways as reported for minerals and polymers. Combining our technique with machine learning approaches, we associated growth rates to specific morphological transitions and provided energy barriers and the energy landscape at the level of single aggregate morphology. Our unifying framework for the detection and analysis of spherulite growth can be extended to other self-assembled systems characterized by a high degree of heterogeneity, disentangling the broad spectrum of diverse morphologies at the single-molecule level.

Carbohydrates are involved in various physiological and pathological activities including cell adhesion, signal transduction and tumor invasion. The distribution of carbohydrates is the molecular basis of their multiple functions, but remains poorly understood. Here, we employed direct stochastic optical reconstruction microscopy (dSTORM) to visualize the pattern of N-acetylglucosamine (N-GlcNAc) on Vero cell membranes at the nanometer level of resolution. We found that N-GlcNAcs exist in irregular clusters on the apical membrane with an average cluster area of about 0.37 μm(2). Most of these N-GlcNAc clusters are co-localized with lipid rafts by dual-color dSTORM imaging, suggesting that carbohydrates are closely associated with lipid rafts as the functional domains. Our results demonstrate that super-resolution imaging is capable of characterizing the distribution of carbohydrates on the cellular surface at the molecular level.