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Abstract The cytoskeleton has a central role in eukaryotic biology, enabling cells to organize internally, polarize, and translocate. Studying cytoskeletal machinery across the tree of life can identify common elements, illuminate fundamental mechanisms, and provide insight into processes specific to less‐characterized organisms. Red algae represent an ancient lineage that is diverse, ecologically significant, and biomedically relevant. Recent genomic analysis shows that red algae have a surprising paucity of cytoskeletal elements, particularly molecular motors. Here, we review the genomic and cell biological evidence and propose testable models of how red algal cells might perform processes including cell motility, cytokinesis, intracellular transport, and secretion, given their reduced cytoskeletons. In addition to enhancing understanding of red algae and lineages that evolved from red algal endosymbioses (e.g., apicomplexan parasites), these ideas may also provide insight into cytoskeletal processes in animal cells. 

Abstract Behaviors of dynamic polymers such as microtubules and actin are frequently assessed at one or both of the following scales: (a) net assembly or disassembly of bulk polymer, (b) growth and shortening of individual filaments. Previous work has derived various forms of an equation to relate the rate of change in bulk polymer mass (i.e., flux of subunits into and out of polymer, often abbreviated as “J”) to individual filament behaviors. However, these versions of the “Jequation” differ in the variables used to quantify individual filament behavior, which correspond to different experimental approaches. For example, some variants of theJequation use dynamic instability parameters, obtained by following particular individual filaments for long periods of time. Another form of the equation uses measurements from many individuals followed over short time steps. We use a combination of derivations and computer simulations that mimic experiments to (a) relate the various forms of theJequation to each other, (b) determine conditions under which theseJequation forms are and are not equivalent, and (c) identify aspects of the measurements that can affect the accuracy of each form of theJequation. Improved understanding of theJequation and its connections to experimentally measurable quantities will contribute to efforts to build a multiscale understanding of steady‐state polymer behavior. 

ABSTRACT: Case studies are helpful teaching tools that can bring scientific concepts to life. Here, we present a case study related to protein−ligand interactions, amino acids, protein structure, and protein modification. While protein−ligand interaction is a foundational concept within Biochemistry, there are few available case studies that focus on this topic. This case study guides students through the scientific thought process and experimental order that could be used to answer questions regarding the role of tau in the etiology of Alzheimer’s disease, based on realistic interactions of tau and microtubules. This case study was trialed in multiple contexts: in a single class period in a one-semester Biochemistry class for nonmajors and as an at-home assignment in a two semester Biochemistry sequence for Biochemistry majors. A survey of student responses indicate that this case study was helpful in improving student creative problem solving and student understanding of real-world applications related to protein−ligand interactions. 

Microtubules (MTs) are cytoskeletal fibers that undergo dynamic instability (DI), a remarkable process involving phases of growth and shortening separated by stochastic transitions called catastrophe and rescue. Dissecting DI mechanism(s) requires first characterizing and quantifying these dynamics, a subjective process that often ignores complexity in MT behavior. We present a Statistical Tool for Automated Dynamic Instability Analysis (STADIA) that identifies and quantifies not only growth and shortening, but also a category of intermediate behaviors that we term “stutters.” During stutters, the rate of MT length change tends to be smaller in magnitude than during typical growth or shortening phases. Quantifying stutters and other behaviors with STADIA demonstrates that stutters precede most catastrophes in our in vitro experiments and dimer-scale MT simulations, suggesting that stutters are mechanistically involved in catastrophes. Related to this idea, we show that the anticatastrophe factor CLASP2γ works by promoting the return of stuttering MTs to growth. STADIA enables more comprehensive and data-driven analysis of MT dynamics compared with previous methods. The treatment of stutters as distinct and quantifiable DI behaviors provides new opportunities for analyzing mechanisms of MT dynamics and their regulation by binding proteins. 

Proper regulation of microtubule (MT) dynamics is critical for cellular processes including cell division and intracellular transport. Plus-end tracking proteins (+TIPs) dynamically track growing MTs and play a key role in MT regulation. +TIPs participate in a complex web of intra- and inter- molecular interactions known as the +TIP network. Hypotheses addressing the purpose of +TIP:+TIP interactions include relieving +TIP autoinhibition and localizing MT regulators to growing MT ends. In addition, we have proposed that the web of +TIP:+TIP interactions has a physical purpose: creating a dynamic scaffold that constrains the structural fluctuations of the fragile MT tip and thus acts as a polymerization chaperone. Here we examine the possibility that this proposed scaffold is a biomolecular condensate (i.e., liquid droplet). Many animal +TIP network proteins are multivalent and have intrinsically disordered regions, features commonly found in biomolecular condensates. Moreover, previous studies have shown that overexpression of the +TIP CLIP-170 induces large “patch” structures containing CLIP-170 and other +TIPs; we hypothesized that these structures might be biomolecular condensates. To test this hypothesis, we used video microscopy, immunofluorescence staining, and Fluorescence Recovery After Photobleaching (FRAP). Our data show that the CLIP-170-induced patches have hallmarks indicative of a biomolecular condensate, one that contains +TIP proteins and excludes other known condensate markers. Moreover, bioinformatic studies demonstrate that the presence of intrinsically disordered regions is conserved in key +TIPs, implying that these regions are functionally significant. Together, these results indicate that the CLIP-170 induced patches in cells are phase-separated liquid condensates and raise the possibility that the endogenous +TIP network might form a liquid droplet at MT ends or other +TIP locations. 

Quantification of microtubule (MT) dynamic instability (DI) is essential to mechanistic dissection of MT assembly and the activities of MT binding proteins. Typical methods for quantifying MT dynamics assume that MT behavior consists of growth and shortening phases, with instantaneous transitions (rescues and catastrophes) in between. However, examination of DI data at high temporal and spatial resolution reveals the presence of ambiguous behaviors that cannot easily fit into these categories. Failure to objectively recognize and quantify these behaviors could reduce the reproducibility of DI data and impact attempts to dissect mechanisms. To address these problems, we recently developed STADIA (Statistical Tool for Automated Dynamic Instability Analysis), a MT analysis software package that uses length-history data as input and is (presently) implemented in MATLAB. STADIA uses machine learning methods to objectively analyze and quantify macro-level DI behaviors exhibited by MTs, including variable rates of growth and shortening and a newly quantified DI phase: stutter. Here we overview the process of using STADIA to quantify MT dynamics and provide a set of concrete protocols for using STADIA to process and analyze MT length history data. 

The concept of critical concentration (CC) is central to understanding the behavior of microtubules (MTs) and other cytoskeletal polymers. Traditionally, these polymers are understood to have one CC, measured in multiple ways and assumed to be the subunit concentration necessary for polymer assembly. However, this framework does not incorporate dynamic instability (DI), and there is work indicating that MTs have two CCs. We use our previously established simulations to confirm that MTs have (at least) two experimentally relevant CCs and to clarify the behavior of individuals and populations relative to the CCs. At free subunit concentrations above the lower CC (CC Elongation ), growth phases of individual filaments can occur transiently; above the higher CC (CC NetAssembly ), the population’s polymer mass will increase persistently. Our results demonstrate that most experimental CC measurements correspond to CC NetAssembly , meaning that “typical” DI occurs below the concentration traditionally considered necessary for polymer assembly. We report that [free tubulin] at steady state does not equal CC NetAssembly , but instead approaches CC NetAssembly asymptotically as [total tubulin] increases, and depends on the number of stable MT nucleation sites. We show that the degree of separation between CC Elongation and CC NetAssembly depends on the rate of nucleotide hydrolysis. This clarified framework helps explain and unify many experimental observations.