Closing the multichannel gap through computational reconstruction of interaction in super-resolution microscopy

Cellular function is defined by pathways that, in turn, are determined by distance-mediated interactions between and within subcellular organelles, protein complexes, and macromolecular structures. Multichannel super-resolution microscopy (SRM) is uniquely placed to quantify distance-mediated interactions at the nanometer scale with its ability to label individual biological targets with independent markers that fluoresce in different spectra. We review novel computational methods that quantify interaction from multichannel SRM data in both point-cloud and voxel form. We discuss in detail SRM-specific factors that can compromise interaction analysis and decompose different classes of interactions based on distinct representative cell biology use cases, the underappreciated non-linear physics of their scale, and the development of specialized methods for those use cases. An abstract mathematical model is introduced to facilitate the comparison and evaluation of interaction reconstruction methods and to quantify the computational bottlenecks. We discuss the different strategies for validation of interaction analysis results with sparse or incomplete ground-truth data. Finally, evolving trends and future directions are presented, highlighting the "multichannel gap," where interaction analysis is trailing behind the rapid increase in novel modes of multichannel SRM acquisitions.