Super-resolution microscopies, such as single molecule localization microscopy (SMLM), allow the visualization of biomolecules at the nanoscale. The requirement to observe molecules multiple times during an acquisition has pushed the field to explore methods that allow the binding of a fluorophore to a target. This binding is then used to build an image via points accumulation for imaging nanoscale topography (PAINT), which relies on the stochastic binding of a fluorescent ligand instead of the stochastic photo-activation of a permanently bound fluorophore. Recently, systems that use DNA to achieve repeated, transient binding for PAINT imaging have become the cutting edge in SMLM. Here, we review the history of PAINT imaging, with a particular focus on the development of DNA-PAINT. We outline the different variations of DNA-PAINT and their applications for imaging of both DNA origamis and cellular proteins via SMLM. Finally, we reflect on the current challenges for DNA-PAINT imaging going forward.

Intracellular compartments are functional units that support the metabolism within living cells, through spatiotemporal regulation of chemical reactions and biological processes. Consequently, as a step forward in the bottom-up creation of artificial cells, building analogous intracellular architectures is essential for the expansion of cell-mimicking functionality. Herein, we report the development of a droplet laboratory platform to engineer complex emulsion-based, multicompartment artificial cells, using microfluidics and acoustic levitation. Such levitated models provide free-standing, dynamic, definable droplet networks for the compartmentalisation of chemical species. Equally, they can be remotely operated with pneumatic, heating, and magnetic elements for post-processing, including the incorporation of membrane proteins; alpha-hemolysin; and mechanosensitive channel of large-conductance. The assembly of droplet networks is three-dimensionally patterned with fluidic input configurations determining droplet contents and connectivity, whilst acoustic manipulation can be harnessed to reconfigure the droplet network in situ. The mechanosensitive channel can be repeatedly activated and deactivated in the levitated artificial cell by the application of acoustic and magnetic fields to modulate membrane tension on demand. This offers possibilities beyond one-time chemically mediated activation to provide repeated, non-contact, control of membrane protein function. Collectively, this expands our growing capability to program and operate increasingly sophisticated artificial cells as life-like materials.

Conventional 19th century thermodynamics has limited our understanding of statistical physics to systems in the thermodynamic limit, and at or near-equilibrium. However, in the last decade two new theorems, collectively referred to as Fluctuation Theorems or FTs, were introduced that quantify the energy distributions of small systems that are driven out of equilibrium, possibly far-from-equilibrium, by an external field. As such the FTs represent a much needed extension of nonequilibrium thermodynamics that can potentially address systems of interest in the 21st century, including nano/micro-machines and single biomolecular function. Optical trapping has served as an ideal experimental technique for demonstrating these theorems. Measurement of picoNewton range forces over nanometre-sized displacements of a trapped micron-sized particle allows us to measure the energies to a fraction of thermal energy along the particle's trajectory - precisely what is needed to demonstrate the predictions of the FTs. Here we review the Fluctuation Theorems, as originally cast by Evans et al. (1, 2) and Crooks (3), and provide a discussion of their importance and a comparison of their arguments. We further demonstrate an optical trap experiment that confirms the FTs. We've chosen to review an optical trapping experiment that is identical to a previously published experiment (10), but where the solvent is viscoelastic rather than purely viscous. This represents the first experimental demonstration where dynamics of the colloidal particle are complex and not known apriori.

Protein structure is more conserved than protein sequence, and therefore may be useful for phylogenetic inference beyond the “twilight zone” where sequence similarity is highly decayed. Until recently, structural phylogenetics was constrained by the lack of solved structures for most proteins, and the reliance on phylogenetic distance methods which made it difficult to treat inference and uncertainty statistically. AlphaFold has mostly overcome the first problem by making structural predictions readily available. We address the second problem by redeploying a structural alphabet recently developed for Foldseek, a highly-efficient deep homology search program. For each residue in a structure, Foldseek identifies a tertiary interaction closest-neighbor residue in the structure, and classifies it into one of twenty “3Di” states. We test the hypothesis that 3Dis can be used as standard phylogenetic characters using a dataset of 53 structures from the ferritin-like superfamily. We performed 60 IQtree Maximum Likelihood runs to compare structure-free, PDB, and AlphaFold analyses, and default versus custom model sets that include a 3DI-specific rate matrix. Analyses that combine amino acids, 3Di characters, partitioning, and custom models produce the closest match to the structural distances tree of Malik et al. (2020), avoiding the long-branch attraction errors of structure-free analyses. Analyses include standard ultrafast bootstrapping confidence measures, and take minutes instead of weeks to run on desktop computers. These results suggest that structural phylogenetics could soon be routine practice in protein phylogenetics, allowing the re-exploration of many fundamental phylogenetic problems.