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The life cycle of eukaryotic microorganisms involves complex transitions between states such as dormancy, mating, meiosis, and cell division, which are often studied independently from each other. Therefore, most microbial life cycles are theoretical reconstructions from partial observations of cellular states. Here we show that complete microbial life cycles can be directly and continuously studied by combining microfluidic culturing, life cycle stage-specific segmentation of micrographs, and a novel cell tracking algorithm, FIEST, based on deep learning video frame interpolation. As proof of principle, we quantitatively imaged and compared cell growth and the activity state of the cell division kinase, Cdk1, across the life cycle of Saccharomyces cerevisiae for up to three sexually reproducing generations. Our analysis of S. cerevisiae's life cycle provided the following new insights: 1) the accumulation of cell cycle regulators, such as Whi5, is tailored to each life cycle stage; 2) cell growth always preceded exit from nonproliferative states in our conditions; 3) the temporal coordination of meiotic events is the same across sexually reproducing populations when each generation is exposed to same conditions; 4) information such as cell size and morphology resets after each sexual reproduction cycle. Image processing and tracking algorithms are available as the Python package Yeastvision, which could be used study pathogens such as Candida glabrata, Cryptococcus neoformans, Colletotrichum acutatum, and other unicellular systems. 

Condensates have emerged as a new way to understand how cells are orga- nized, and have been invoked to play crucial roles in essentially all cellular processes. In this view, the cell is occupied by numerous assemblies, each composed of member proteins and nucleic acids that preferentially interact with each other. However, available visual represen- tations of condensates fail to communicate the growing body of knowledge about how con- densates form and function. The resulting focus on only a subset of the potential implications of condensates can skew interpretations of results and hinder the generation of new hypoth- eses. Here we summarize the discussion from a workshop that brought together cell biolo- gists, visualization and computation specialists, and other experts who specialize in thinking about space and ways to represent it. We place the recent advances in condensate research in a historical perspective that describes evolving views of the cell; highlight different attri- butes of condensates that are not well-served by current visual conventions; and survey po- tential approaches to overcome these challenges. An important theme of these discussions is that the new understanding on the roles of condensates exposes broader challenges in visual representations that apply to cell biological research more generally.