The idea that interactions between individual members drive a collective output is fundamental to biology. It is how fish, birds, and migrating cells only interact with their proximal neighbors yet create an emergent behavior for the school, flock, or sheet of cells (Friederici, 2009, Friedl and Gilmour, 2009). There is a tremendous amount of excitement that similar principles may apply to molecules within the cytoplasm – groups of molecules work together within the cytoplasm to form functionally significant molecular aggregates or condensates. However, how condensates give rise to cellular behaviors remains to be determined. It is generally acknowledged that the field "desperately needs" new tools (Leslie, 2021). Proposals have been made suggesting using single-molecule (SM) super-resolution microscopy and single-particle tracking, but it is unclear how they should be applied (Lyon et al., 2021). Here, we explore how these tools can be used to identify and quantify the heterogeneous molecular behaviors indicative of condensate formation.

Condensates frequently arise from liquid-liquid phase separations (LLPS), transforming a single, uniform liquid phase into two compositionally distinct liquid phases (Lafontaine et al., 2021). The concept of LLPSs rose to prominence with the discovery of the liquid-like behavior of Caenorhabditis elegans P granules, a class of perinuclear RNA granules specific to the germline (Brangwynne et al., 2009). P granules are separated from the rest of the cytoplasm, but they are not confined by a membrane, giving rise to the term “membrane-less” organelle. Since an LLPS can merge with another LLPS and coalesce, similar to the everyday example of oil droplets separating from water when a bottle of salad dressing is shaken, this visual imagery has led to the observational properties of droplet roundness and merging becoming de facto standard metrics for describing LLPSs (McSwiggen et al., 2019b). Using descriptors such as fusion and dispersion as indicators of LLPSs has resulted in the current qualitative state of the field, which has been documented by an in-depth review of 33 papers reporting on the properties of LLPSs (McSwiggen et al., 2019). Adding to the challenges of quantifying condensates by describing them simply as droplets is the production of unwanted puncta when tools like 1,6-hexanediol are used to disrupt the hydrophobic interactions within LLPSs (Leslie, 2021).

The term condensate has recently been extended to include functional molecular aggregates or heterogeneities, such as synaptic densities, nucleoli, and membrane clusters, which are not LLPSs (Banani et al., 2017). As the number of identified condensates expands, so does the recognition of their importance in normal physiology and pathologies ranging from cancer to Alzheimer's (Lyon et al., 2021). Condensates now appear almost everywhere and are involved in nearly everything. However, there is still no consensus on how they should be quantified. The discord arises from the experimental difficulties in measuring the behaviors of molecules that move with instantaneous velocities of ~10 m/s in the cytoplasm (Bray, 2000). Molecules rotate around and change axes so fast that a single molecule will meet with every other molecule inside a bacterium cell every second (Milo and Phillips, 2015). While this environment facilitates the formation of the transient molecular aggregations that underlie many condensates, it also makes it more challenging to quantify them.