Chromosome segregation during female meiosis in C. elegans: A tale of pushing and pulling

The role of the kinetochore during meiotic chromosome segregation in C. elegans oocytes has been a matter of controversy. Danlasky et al. (2020. J. Cell. Biol. https://doi.org/10.1083/jcb.202005179) show that kinetochore proteins KNL-1 and KNL-3 are required for early stages of anaphase during female meiosis, suggesting a new kinetochore-based model of chromosome segregation.

Meiosis consists of two consecutive chromosome segregation events preceded by a single round of DNA replication. Homologous chromosomes are separated in meiosis I, which is followed by sister chromatid separation in meiosis II to produce haploid gametes. Both of these stages require chromosomes/chromatids to align during metaphase before separating to opposite poles during anaphase. During mitosis, microtubules emanating from centrosomes at opposite poles of the cell bind chromosomes through a multiprotein complex called the kinetochore, allowing chromosomes to be pulled apart (1, 2). This segregation event takes place in two stages: anaphase A, where chromosomes are pulled toward spindle poles due to microtubule depolymerization, and anaphase B, where spindle poles themselves move farther apart, taking the attached chromosomes with them (3, 4). In many organisms, including mammals, oocytes lack centrosomes, and it has been of great interest to clarify the mechanisms used to ensure chromosomes are properly segregated during female meiosis (5, 6). Caenorhabditis elegans has served as a model for studying both mitosis and meiosis, but the mechanisms operating during female meiosis have been a matter of debate and controversy.In 2010, Dumont et al. showed that the kinetochore is required for chromosome alignment and congression during metaphase (7). However, they suggested that chromosome segregation was the result of microtubule polymerization between the segregating chromosomes (Fig. 1), resulting in a pushing force exerted onto chromosomes toward the spindle poles in a largely kinetochore-independent manner (7). This mechanism was also supported by the finding that CLIP-associated protein (CLASP)–dependent microtubule polymerization between the segregating chromosomes is essential for chromosome separation (8). An alternative model suggested that chromosomes are transported through microtubule-free channels toward the spindle poles by the action of dynein (9). Later evidence put in doubt a role for dynein and favored a model in which chromosomes initially separate when the spindle shortens and the poles overlap with chromosomes in an anaphase A–like mechanism. This is then followed by separation of chromosome-bound poles by outward microtubule sliding in an anaphase B–like fashion (10). However, because microtubules emanating from the spindle poles are not required to separate the homologous chromosomes but microtubules between the separating chromosomes are (8), this model is unlikely, at least as an explanation for mid-/late-anaphase movement. Furthermore, although lateral microtubule interactions with chromosomes predominate during metaphase of C. elegans oocyte meiosis, cryo-electron tomography data described end-on attachments between the separating chromosomes as anaphase progresses (11). This led to the suggestion that lateral microtubule interactions with chromosomes are responsible for the initial separation, but microtubule polymerization between the separating chromosomes is required for the later stages of segregation (11). The mechanisms involved in this initial separation have remained obscure. In this issue, Danlasky et al. show that the kinetochore is in fact required for the initial stages of chromosome segregation during female meiosis—an important step forward in our understanding of the mechanisms governing acentrosomal chromosome segregation (12).Open in a separate windowFigure 1.Some of the key findings in Danlasky et al. Kinetochore proteins surround the outer surface of the chromosomes, resulting in a characteristic cup shape. As anaphase progresses, chromosomes come into close contact to the spindle poles (anaphase A). Chromosome stretching is provided by KNL-1, MIS-12 (KNL-3), and NDC-80 (KMN)–dependent forces. Once the spindle starts elongating (anaphase B), central spindle microtubules provide the pushing forces for chromosome segregation. At this stage, kinetochore proteins also occupy the inward face of separating chromosomes. Upon KMN network depletion, bivalents flatten, and chromosome congression and alignment are defective. Anaphase A chromosome movement is almost absent, which leads to error-prone anaphase B.By simultaneously depleting kinetochore proteins KNL-1 and KNL-3 in C. elegans, Danlasky et al. observed the meiotic chromosome congression and alignment defects described in previous studies (7). However, this double-depletion phenotype displayed three key characteristics that suggested a role for kinetochores in chromosome segregation, which are discussed below.The kinetochore is required for bivalent stretching. It was previously shown that the bivalent chromosomes stretch before the initiation of segregation (10). Danlasky et. al found that this stretching of the chromosomes did not occur when KNL-1,3 were depleted, indicating that the kinetochore is required for this process (Fig. 1). Together with the observation that kinetochore proteins appear to extend toward the spindle poles, this finding suggested that pulling forces resulting from the interaction between the kinetochore and spindle microtubules are occurring during metaphase/preanaphase (Fig. 1).The kinetochore is required for anaphase A. In C. elegans female meiosis, anaphase A occurs when homologous chromosomes begin to separate during spindle shortening, and anaphase B when the chromosomes separate alongside the spindle poles (10). Danlasky et al. observed that KNL-1,3 depletion drastically reduced the velocity of anaphase A, as chromosomes only separated when spindle poles began to move apart. This indicated that pulling forces caused by the interaction between the kinetochore and spindle microtubules are also important for the initial separation of homologous chromosomes in anaphase A.The kinetochore is required for proper separation of homologous chromosomes. In KNL-1,3 depletion strains, 60% of bivalents failed to separate before segregation began, resulting in intact bivalents being pulled to the same spindle pole (Fig. 1). This failure of homologous chromosomes to separate was not thought to be a result of KNL-1,3 depletion interfering with the cleavage of cohesin that holds the two homologous chromosomes together because (a) separase and AIR-2^AuroraB, both of which are required for cohesin cleavage, localized normally during metaphase and anaphase, and (b) bivalents separated by metaphase II. This leaves the possibility open that the failure of bivalents to separate was due to the disrupted pulling forces thought to be important in bivalent stretching and anaphase A.Altogether, these data strongly indicate that the kinetochore is required not only for chromosome congression and alignment but also for the early stages of homologue separation. Anaphase B occurred successfully in the absence of KNL-1,3 but was more error prone, likely as a result of the earlier congression and anaphase A defects. While it is clear that chromosome masses do segregate in the absence of the kinetochore, this segregation is highly erroneous as a result of defects during the earlier stages of segregation in anaphase A (Fig. 1).The findings of Danlasky et al. raise testable hypotheses that could significantly enhance our understanding of acentrosomal chromosome segregation. Further investigation of the proposed pulling forces required during metaphase and early anaphase will be of great interest. Additionally, a more detailed analysis of the dynamic localization of separase and Securin, as well as assessing successful cohesin cleavage when KNL-1,3 are depleted, would back up the assertion that the failure of homologous chromosomes to separate was not due to the kinetochore impacting cohesin cleavage. It has previously been shown that the CLASP orthologue CLS-2 in C. elegans localizes to the kinetochore surrounding the bivalent chromosomes during metaphase before relocalizing to the central spindle during anaphase (7, 8, 13). It will be interesting to examine whether this key microtubule-stabilizing protein contributes to anaphase A pulling forces alongside its essential role in microtubule polymerization between chromosomes in anaphase B (8).While the regulation of proper chromosome segregation during acentrosomal meiosis in C. elegans is not yet fully understood, Danlasky et al.’s results represent a significant step forward in this endeavor by showing that the kinetochore is in fact required for the early stages of chromosome segregation.     

The role of molecular diffusion within dendritic spines in synaptic function

Spines are tiny nanoscale protrusions from dendrites of neurons. In the cortex and hippocampus, most of the excitatory postsynaptic sites reside in spines. The bulbous spine head is connected to the dendritic shaft by a thin membranous neck. Because the neck is narrow, spine heads are thought to function as biochemically independent signaling compartments. Thus, dynamic changes in the composition, distribution, mobility, conformations, and signaling properties of molecules contained within spines can account for much of the molecular basis of postsynaptic function and regulation. A major factor in controlling these changes is the diffusional properties of proteins within this small compartment. Advances in measurement techniques using fluorescence microscopy now make it possible to measure molecular diffusion within single dendritic spines directly. Here, we review the regulatory mechanisms of diffusion in spines by local intra-spine architecture and discuss their implications for neuronal signaling and synaptic plasticity.

IntroductionNeurons communicate with each other through synapses that organize to create functional circuits. Most excitatory synapses in the central nervous system are formed on dendritic spines, tiny protrusions that extend from dendrites (Bourne and Harris, 2008; Fig. 1 a). The spine typically has a head of 200–1,000-nm diameter, which is connected to the dendritic shaft via a neck of 100–200-nm width (Arellano et al., 2007; Fig. 1 b). The head contains postsynaptic density (PSD) proteins, the actin cytoskeleton, membrane structures, and organelles (Sheng and Hoogenraad, 2007; Fig. 1 c). The molecular composition of spine heads is different from that of the shaft. Because of its characteristic morphology, spines are thought to function as biochemically independent compartments by limiting molecular movement between the spine head and the rest of the dendrite (Adrian et al., 2014; Tønnesen and Nägerl, 2016). Clarifying this regulation is key to understanding how this unitary site of synaptic transmission is controlled. This is particularly crucial to our understanding about how changes in the postsynaptic site lead to synaptic plasticity.Open in a separate windowFigure 1.The shape and internal architecture of dendritic spines. (a) A super-resolution SIM image of a hippocampal neuron dendrite expressing GFP. (b) A surface image of a spine (arrow in a) reconstructed from a SIM image. (c) Schematic representation of a spine containing the PSD, actin cytoskeleton, recycling endosome, and SER.The control of spine architecture is critical at excitatory synapses in the brain (Alvarez and Sabatini, 2007; Forrest et al., 2018). Excitatory synapses exhibit synaptic plasticity, which changes the strength of synaptic transmission through mechanisms at both pre- and postsynaptic sides (Citri and Malenka, 2008). This process is generally thought to be a basis for changes in neural circuits controlled by experiences—i.e., learning and memory (Humeau and Choquet, 2019; Magee and Grienberger, 2020). Here, the size and shape of spines are strongly correlated with the strength of synaptic transmission (Kasai et al., 2010). Spine volume is proportional to PSD area (Harris and Stevens, 1989) and the number of α-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate–type glutamate receptors (AMPARs; Nusser et al., 1998; Matsuzaki et al., 2001). Recently, combinational analysis of electrophysiology and correlative light and EM (CLEM) revealed the linear relationship between PSD area and synaptic strength (Holler et al., 2021). Also, longer spine necks attenuate somatic potentials to a greater degree (Araya et al., 2006). Thus, structural and functional plasticity of spines is tightly regulated. Specifically, when synaptic transmission is strengthened (e.g., long-term potentiation [LTP]), spines grow (Matsuzaki et al., 2004). In turn, when synaptic transmission weakens (e.g., long-term depression), spines shrink (Zhou et al., 2004; Oh et al., 2013).While many molecules involved in the plasticity of spine synapses have been identified (Sala and Segal, 2014), their mechanisms and regulations can only be discovered by monitoring the regulated changes in the composition and signaling properties of these factors within the confined space of the spine’s cytoplasm. To this end, the development of local photolysis of caged-glutamate played an important role (Matsuzaki et al., 2001). This method made it possible to induce structural plasticity locally at a single spine. Spine enlargement is induced by uncaging of caged-glutamate in the absence of Mg²⁺ or with postsynaptic depolarization in the presence of Mg²⁺ to activate N-methyl-D-aspartate–type glutamate receptors (NMDARs; Matsuzaki et al., 2004). Conversely, spine shrinkage is induced by low-frequency uncaging of caged-glutamate in the absence of Mg²⁺ or with postsynaptic depolarization (Oh et al., 2013). Shrinkage can also be induced by glutamate uncaging temporally coupled with back propagation action potential and uncaging of caged–γ-aminobutyric acid (GABA; Hayama et al., 2013). Glutamate uncaging–induced structural plasticity has also been seen to occur in vivo (Noguchi et al., 2019).These methods have vastly improved our understanding of the molecular mechanisms of structural plasticity (Nishiyama and Yasuda, 2015). In particular, stimulus-dependent increases in spine size (structural LTP [sLTP]), which are thought to be associated with functional LTP, have been studied extensively as a model of LTP (Nakahata and Yasuda, 2018; Fig. 2). Strong synaptic input causes an influx of Ca²⁺ through NMDARs that activates Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) and the downstream signaling cascades. This modification of signaling cascades can affect cytoskeletal organization and membrane trafficking, which are responsible for two subsequent cellular events. First, spine morphology is modulated through cytoskeletal changes (Borovac et al., 2018). Second, synaptic transmission is enhanced by increased AMPAR insertion into the plasma membrane and movement to the PSD (Huganir and Nicoll, 2013). However, the molecular mechanisms that link these two phenomena are not fully understood (Herring and Nicoll, 2016). As sLTP progresses, the molecular composition within spines changes (Bosch et al., 2014; Meyer et al., 2014). Specifically, immediately after sLTP induction, actin-related molecules such as cofilin and actin-related protein 2/3 (Arp2/3) complex accumulate within a stimulated spine. On the other hand, scaffold proteins such as PSD-95 slowly accumulate over tens of minutes. SynGAP, which is localized at the PSD through interaction with PSD-95, escapes from spines immediately after stimulation and contributes to the expression of sLTP (Araki et al., 2015). These changes in molecular compositions immediately after stimulation may be due not only to molecule-specific binding but also to the physical regulation of diffusion (Obashi et al., 2019).Open in a separate windowFigure 2.Molecular motion important in sLTP. Strong synaptic input causes an influx of Ca²⁺ through NMDARs that activates CaMKII and the downstream signaling cascades. This modification of signaling cascades can affect cytoskeletal organization and membrane trafficking, which regulate spine morphology. Spine morphology affects the molecular exchange between the spine head and the dendritic shaft and lateral diffusion of membrane proteins including AMPARs. Regulation of molecular movements through the spine neck affects the molecular composition within spines. This change affects signal propagation into nearby spines. For example, cofilin and Arp2/3 complex accumulate within spines. SynGAP and activated RhoA escape from spines. Reorganization of the actin cytoskeleton affects movement of large molecules and the formation of a large signaling complex containing CaMKII and Tiam1. Also, the structure of the PSD affects membrane protein diffusion and alters the synaptic trafficking of AMPARs.In addition to molecular localization, fluorescence lifetime imaging of FRET-based biosensors has made it possible to measure spatiotemporal changes in the activity of signaling molecules involved in sLTP (Yasuda, 2012). These studies have demonstrated a critical relationship between the time that a molecule spends within a spine and the rate of signal inactivation. This relationship determines whether an activated signaling molecule is confined within a single spine or escapes from the spine and interacts with effectors present in the adjacent dendritic shaft or nearby spines (Yasuda, 2017). The signal propagation into nearby spines is most likely related to heterosynaptic plasticity, where activated synapses influence neighbor synapses within the same dendritic segments (Oh et al., 2015; Colgan et al., 2018; Chater and Goda, 2021). Thus, diffusion is a central feature of the regulation of spine structural plasticity. However, because the size of spines is small relative to the spatial resolution of diffraction-limited fluorescence microscopy and measuring methods are limited, elucidation of the mechanism regulating diffusion within spines has been challenging.To address this gap in understanding, researchers advanced fluorescence microscopy techniques, which enabled us to measure changes in the nanoscale localization, diffusion, and signal activities inside spines. These studies allow us to directly understand how spine structures physically limit molecular diffusion and reveal fundamental mechanisms that control the localization and biochemical signal transduction pathways in neurons. Here, we summarize recent findings that have revealed physical barriers within spines using super-resolution microscopy (Sigal et al., 2018; Table 1) and molecular dynamics measurements (Fig. 3 and Table 2), and we discuss how these barriers serve as a fundamental feature controlling neuronal signaling and synaptic plasticity.Table 1.List of super-resolution microscopy techniques

Granular detail of β cell structures for insulin secretion

Pancreatic β cells secrete insulin in response to increased glucose concentrations. Müller et al. (2021. J. Cell Biol. https://doi.org/10.1083/jcb.202010039) use 3D FIB-SEM to study the architecture of these cells and to elucidate how glucose stimulation remodels microtubules to control insulin secretory granule exocytosis.

The pancreatic islet β cell is a prototypical model for regulated protein secretion, which has been studied extensively because of its importance for diabetes in humans. Upon stimulation by increased glucose concentrations, β cells mobilize insulin-containing secretory vesicles to the cell surface. These “insulin secretory granules” fuse at the plasma membrane to release insulin into the circulation. Insulin then acts on the liver to inhibit glucose production and on muscle and fat cells to stimulate glucose uptake, thus returning blood glucose concentrations to a narrow physiological range. During the development of diabetes, this negative feedback system fails. In type 1 diabetes, β cells are destroyed by an autoimmune process; in type 2 diabetes, attenuated insulin action (“insulin resistance”) occurs together with impaired β cell function. In both cases, blood glucose concentrations rise above the normal range. Overall, glucose homeostasis requires a delicate balance between glucose-stimulated insulin secretion from β cells and insulin-stimulated effects on glucose metabolism in liver, muscle, fat, and other cell types.Each β cell contains 5,000 to ≥10,000 insulin secretory granules, and acute glucose stimulation causes exocytosis of only 1–2% of this pool (1, 2). Both readily releasable and reserve pools of granules contribute to insulin secretion. Classically, the readily releasable pool has been considered as vesicles that are docked at the plasma membrane; the reserve pool, which is larger and more important, resides deeper within the cell and relies on microtubule-based transport to reach the cell surface. Yet, other data show that newly synthesized insulin is preferentially released, and aged insulin granules are targeted for degradation in lysosomes, implying that microtubules play a more complicated role in granule trafficking (3). In the setting of insulin resistance, the flux of insulin through the secretory pathway is increased. Demands are placed upon the machinery for folding of the insulin precursor, proinsulin, for its proteolytic conversion to produce insulin, and for insulin secretory granule maturation. As well, in type 2 diabetes, lipids and other metabolites act directly on β cells to impair glucose-stimulated insulin secretion. What steps are affected by this critical pathophysiologic insult is not well understood, in part because basic mechanisms by which glucose stimulation remodels microtubules to promote insulin release remain undefined.To better understand these processes, Müller et al. used focused ion beam scanning electron microscopy (FIB-SEM) to image microtubules, insulin secretory granules, and other organelles in whole primary mouse β cells and to study the effects of glucose stimulation on these structures (4). Together with advances in sample preparation, image segmentation, and analysis, FIB-SEM is uniquely suited to this task. The resulting 3D images have a voxel size of 4 × 4 × 4 nm and encompass volumes of 20–30 µm in x, y, and z dimensions. This is sufficient to image microtubules, which have an outer diameter of ~25 nm, in whole β cells, which are 10–20 µm in diameter. Moreover, the imaging was performed on intact islets, rather than on dissociated cells, which may better preserve insulin secretory granule dynamics. The images captured seven β cells in all, three in a low-glucose (unstimulated) condition and four in the glucose-stimulated state. Finally, the images were quantified in a way that controlled for the overall geometry of the cells.The data show that the β cell microtubule network is nonradial, dense, tortuous, and mostly not connected to either centrioles or the Golgi complex, so that microtubules appear to be freely positioned in the cytosol (Fig. 1). This is similar to other differentiated cells (5) but in contrast to previous data suggesting that in β cells most microtubules originate at the Golgi (6). The microtubule cytoskeleton negatively regulates insulin granule exocytosis in unstimulated cells (7). Yet, the FIB-SEM data suggest that the effect of glucose is not simply to disinhibit this effect. Glucose stimulated an approximately threefold increase in the number of microtubules and an approximately threefold decrease in the average length of each microtubule, so that total tubulin polymer density remained unchanged (4). The images also show that microtubule ends and insulin secretory granules are enriched near the plasma membrane and indicate an important role for microtubules in positioning the granules for exocytosis. Intriguingly, glucose stimulation did not cause any marked change in the association of secretory granules with microtubules, suggesting that it may act by other mechanisms to increase microtubule-based transport (3). The data also demonstrate an increase in the number of secretory granules near the Golgi in glucose-stimulated cells, raising the possibility that glucose may promote budding of nascent secretory vesicles at the trans-Golgi network. If so, it is not yet clear whether this is a direct effect or if it is secondary to increased flux through the secretory pathway.Open in a separate windowFigure 1.Regulation of β cell architecture by glucose. In low-glucose conditions (left panel), microtubules form a dense, nonradial network. The tubules are mostly not anchored to the Golgi complex or to centrosomes but are associated with insulin secretory granules near the plasma membrane (PM). After stimulation with high-glucose concentrations (right panel), the microtubules are shorter and more numerous, and an increased density of vesicles near the Golgi was observed.The observation that glucose stimulation results in shorter, more numerous microtubules, without changing tubulin polymer density, suggests a possible role for severing enzymes such as katanin, spastin, or fidgetin (8). Whether and how such enzymes may be stimulated by glucose is not known. Glucose stimulates insulin secretion by increasing the ATP/ADP ratio, in part due to local ATP generation by pyruvate kinase, as well as by oxidative phosphorylation (9). Although these microtubule-severing enzymes are AAA ATPases, it is not clear that ATP availability acts physiologically to regulate their activities. Other data show that in β cells, glucose-responsive kinases phosphorylate tau, causing it to dissociate from microtubule plus ends to destabilize microtubules and to promote remodeling (10). Could such kinases regulate severing enzymes as well?The technological achievements of Müller et al. are impressive, and the work will serve as a model for the analysis of cellular architecture in other cell types. In β cells, the results may be extended by using FIB-SEM to study effects of various genetic manipulations, by using EM-visible tags, and by examining diabetes models. It may be informative to image granules of different ages or to use drugs to manipulate microtubules or membrane lipids, or that act on β cells to enhance insulin secretion (3). In this study, Müller and colleagues used a 1-h high-glucose stimulation, but it may be interesting to test other time points to determine the effects of more acute versus chronic glucose exposure. Although FIB-SEM can image only fixed, static cells, the work will complement other studies using super-resolution imaging and live cell microscopy. Aside from these future directions, it is worthwhile to pause and celebrate the present work, which is the first to reconstruct the entire 3D architecture of the microtubule network in a primary mammalian cell during interphase. The movies in the supplement are gorgeous. The work bodes well for the future of FIB-SEM and will stimulate new directions to understand both diabetes physiology and regulated protein secretion.     

Comparison of Insulins Glargine and Degludec in Diabetic Rhesus Macaques (Macaca mulatta) with CGM Devices

Treating and monitoring type 2 diabetes mellitus (T2DM) in NHP can be challenging. Multiple insulin and hypoglycemic therapies and management tools exist, but few studies demonstrate their benefits in a NHP clinical setting. The insulins glargine and degludec are long-acting insulins; their duration of action in humans exceeds 24 and 42 h, respectively. In the first of this study''s 2 components, we evaluated whether insulin degludec could be dosed daily at equivalent units to glargine to achieve comparable blood glucose (BG) reduction in diabetic rhesus macaques (Macaca mulatta) with continuous glucose monitoring (CGM) devices. The second component assessed the accuracy of CGM devices in rhesus macaques by comparing time-stamped CGM interstitial glucose values, glucometer BG readings, and BG levels measured by using an automated clinical chemistry analyzer from samples that were collected at the beginning and end of each CGM device placement. The CGM devices collected a total of 21,637 glucose data points from 6 diabetic rhesus macaques that received glargine followed by degludec every 24 h for 1 wk each. Ultimately, glucose values averaged 29 mg/dL higher with degludec than with glargine. Glucose values were comparable between the CGM device, glucometer, and chemistry analyzer, thus validating that CGM devices as reliable for measuring BG levels in rhesus macaques. Although glargine was superior to degludec when given at the same dose (units/day), both are safe and effective treatment options. Glucose values from CGM, glucometers, and chemistry analyzers provided results that were analogous to BG values in rhesus macaques. Our report further highlights critical clinical aspects of using glargine as compared with degludec in NHP and the benefits of using CGM devices in macaques.

Diabetes is a group of metabolic diseases that cause hyperglycemia secondary to deficient insulin response, secretion, or both.⁴ Diabetes is categorized by the American Diabetes Association into 4 types: 1) type 1 diabetes mellitus, in which the pancreas is unable to produce insulin for glucose absorption; 2) type 2 diabetes mellitus (T2DM), when the body does not use insulin correctly; 3) gestational diabetes, in which the body is insulin-intolerant during pregnancy (or is first discovered then); and 4) other specific forms of diabetes in which the patient is particularly predisposed to becoming diabetic due to various comorbidities or to inadvertent induction caused by some medications.⁴ In 2018, 34.2 million (10.5%) Americans of all ages were diagnosed with diabetes.^22,23,30 Approximately 90% to 95% of Americans with diabetes have T2DM,²⁴ making T2DM the most common form of diabetes diagnosed in humans.T2DM is a multifactorial disease primarily determined by genetics, behavioral and environmental factors (for example, age, diet, sedentary lifestyle, obesity).^4,46,50,74 As a consequence of these factors, the pancreas increases insulin secretion to maintain normal glucose tolerance.⁷⁴ Over time, the high insulin demand causes pancreatic β-cell destruction, resulting in reduced production of insulin.^39,50,74 As β-cell destruction increases, hyperglycemia and T2DM develop. Insulin resistance and hyperglycemia are tolerated for a period of time^19,82,83 before clinical signs associated with T2DM develop (e.g., polydipsia, polyuria, polyphagia with concurrent weight loss).⁴ Once clinical signs develop, T2DM is most commonly diagnosed as a fasting blood glucose level (FBG) of 126 mg/dL or greater,^2,4 2-h plasma glucose value of 200 mg/d or greater during a 75-g oral glucose tolerance test,^2,4 and/or glycosylated hemoglobin (HbA1c) of 6.5% or greater.^2,4 Depending on the FBG, oral glucose tolerance test, and HbA1c results, various treatment options are recommended by the American Diabetes Association. Most importantly, lifestyle changes, including diet and exercise, are recommended as the first line of treatment, along with oral antihyperglycemic drugs such as metformin.^5,25,46 Treatment efficacy is evaluated with self-monitoring blood glucose or continuous glucose monitoring (CGM) devices.³ Human patients using CGM devices have achieved considerable reductions in HbA1c compared with patients not using them.³ As CGM devices have become more readily available, user friendly, and affordable, they have become an essential tool in managing T2DM.Similar to humans, most NHP affected by diabetes are diagnosed with T2DM.^80,83 NHP are predisposed to similar genetic, behavioral and environmental factors (e.g., age, diet, sedentary lifestyle, obesity);^{6,18,19,37,44,52,82,83} have similar pathophysiology;^38,81-83 are diagnosed via FBG,^39,83 HbA1c,^21,31,49,56 fructosamine,^20,83,87 and weight loss;^49,80,83,86 and are treated with exercise and diet modifications as a first line of treatment.^{11,19,39,53,79} Although the human and NHP conditions are similar, the treatment and management of T2DM is somewhat different, especially when NHP have restricted physical activity due to housing constraints.Previous studies indicate that daily dosing with insulin glargine achieves appropriate glycemic control in NHP.⁴⁸ Therefore, we implemented glargine, along with some diet modification, to improve glycemic control in our diabetic colony. Other noninsulin therapies, such as metformin, had been used, but compliance was low (for example, due to large pill size, unpleasant taste, etc.). However, achieving glycemic control using diet modification, insulin glargine treatment, monthly scheduled FBG, quarterly HbA1c, and regular weight monitoring was challenging in a large colony. Monthly FBG and fructosamine testing were performed due to affordability and practicality for NHP in a research setting. Given that fructosamine levels correlate with BG concentrations for the preceding 2 to 3 wk and HbA1c percentages relate to BG concentration over 1.5 to 3 mo,^49,87 HbA1C was selected over fructosamine for T2DM management in our colony. Determining which T2DM treatment and diagnostics are most effective can be difficult in large colonies of NHP. Therefore, improved treatment and management strategies would help to manage T2DM in NHP more efficiently.Insulin glargine is a long-acting insulin, with a half-life of 12 h and duration of action of 12 to 24 h in humans^40,55 and 12 h in dogs.^34,43,60 Once injected subcutaneously, insulin glargine forms a microprecipitate in the neutral pH environment, which delays and prolongs absorption in subcutaneous tissues.¹² Insulin degludec is a newer form of long-acting insulin, with a half-life of 25 h^41,63,62,77 and duration of action that exceeds 42 h in humans.^40,41,68,77 Insulin degludec forms a soluble and stable dihexamer in the pharmaceutical formulation, which includes phenol and zinc.^63,78 The phenol diffuses away, leading to the formation of a soluble depot in the form of long multihexamer chains in which zinc slowly diffuses from the end of the multihexamers, causing a gradual, continuous, and extended-release of monomers from the depot of the injection site.^63,78 Pharmacodynamic studies in humans, demonstrate that the “glucose-lowering effect” of insulin degluc⁴⁰ is evenly distributed over 24 h, allowing a more stable steady-state and improved wellbeing.⁷⁸ This approach could potentially reduce the number of hypoglycemic events and provide a less rigid daily injection schedule,⁵⁸ thus potentially making insulin degludec—compared with insulin glargine—a safer, alternative diabetes therapy.In addition to medical intervention, glycemic control is achieved through regular management and monitoring of BG. Self-monitoring blood glucose checks in humans^3,5 and glucose curves in animals¹⁰ are some of the management tools used to determine or evaluate therapy for T2DM patients. Telemetry systems like CGM devices are used to monitor interstitial glucose and have been used extensively in humans^3,17,33 and animals^{16,27,36,42,47,84,85} to monitor BG in real-time. Using CGM devices 1) reduces or eliminates the number of blood draws needed to collect FBG,⁶¹ 2) accurately assesses insulin therapy via a real-time glucose curve,^72,84,85 3) allows patients and clinicians to titrate treatment^61,73 as indicated, and 4) obtains continuous glucose data with reduced manipulation and subsequent decreased stress.^72,84,85 Therefore, CGM devices can be a safe and informative tool in monitoring spontaneous T2DM in NHP.Between 2015 and 2030, the prevalence of diabetes is predicted to increase by 54% to more than 54 million Americans affected by diabetes (i.e., diabetes mellitus types 1 and 2).⁷⁰ NHP are an essential model for human T2DM because of their similar pathophysiology, diagnostics, treatment, and management. As more people develop diabetes, novel therapies will continue to be developed. Studying new treatments and management tools in NHP can further human and NHP T2DM research to prevent the progression of T2DM and hopefully diminish projections for the number of future diabetes cases. Human medical literature, American Diabetes Association, and drug manufacturers all recommend giving equal doses (i.e., number of units/day) of long-acting insulins when changing from one long-acting insulin to degludec.^26,63,67 Therefore, we hypothesized that insulin degludec would provide effective glycemic control for rhesus macaques with T2DM when dosed at equivalent doses (that is, the same number of units/day) as insulin glargine. In addition, we hypothesized that CGM devices would provide accurate BG readings as compared with chemistry analyzer and glucometer BG readings, making it a more efficient and effective tool for measurement of BG levels in rhesus macaques with T2DM.     

The dynamic instability of actin filament barbed ends

The turnover of actin filament networks in cells has long been considered to reflect the treadmilling behavior of pure actin filaments in vitro, where only the pointed ends depolymerize. Newly discovered molecular mechanisms challenge this notion, as they provide evidence of situations in which growing and depolymerizing barbed ends coexist.

IntroductionIn cells, actin assembles into filament networks with diverse architectures and lifetimes, playing key roles in functions such as endocytosis, cell motility, and cell division. These filament networks are maintained and renewed by actin turnover, which implies that assembly and disassembly must take place simultaneously and in a controlled manner within the networks. Each actin filament end has the ability to either grow or shrink, depending on the concentration of actin and regulatory proteins, but pure actin treadmills at steady state: ATP-actin is added at the barbed end at a rate matching the departure of ADP-actin from the pointed end, and ATP hydrolysis takes place within the filament. This hallmark feature of actin dynamics has been known for decades (Wegner, 1976) and has been generalized to the cell context, in which it is commonly assumed that actin polymerization takes place at the barbed end, while depolymerization takes place only at the pointed end (whether it be the ends of filaments within the network or the ends of fragments that have detached from it). This notion is reinforced by the fact that the cytoplasm contains high concentrations of monomeric actin (G-actin) in complex with profilin (Funk et al., 2019), which is unable to bind to pointed ends and should drive the elongation of all noncapped barbed ends.Recently, however, in vitro studies have identified two seemingly independent mechanisms in which, in the presence of profilin-actin, filament barbed ends alternate between phases of growth and depolymerization. This behavior, referred to as “dynamic instability,” is widely observed for microtubules but was unexpected for actin filaments. It suggests that cells could use barbed ends for both elongation and disassembly.Driving the depolymerization of barbed ends with cofilin side-decorationProteins of the actin depolymerizing factor (ADF)/cofilin family (henceforth cofilin) are composed of a single ADF-homology (ADF-H) domain and are mostly known for their actin filament–severing activity (De La Cruz, 2009). Cofilin binds cooperatively to the sides of actin filaments, forming clusters where the conformation of the filament is locally altered, leading to its severing at cofilin cluster boundaries. In addition, the barbed ends of cofilin-decorated filaments steadily depolymerize, despite the presence of G-actin and profilin-actin (Fig. 1 A) and even capping protein (CP) in solution (Wioland et al., 2017, 2019). This unexpected result likely originates from the conformational change of actin subunits at the barbed end, induced by cofilin side-binding. As a consequence, filaments exposed to G-actin (with or without profilin), CP, and cofilin alternate between phases of barbed-end elongation and barbed-end depolymerization. In these conditions, actin filament barbed ends thus exhibit a form of dynamic instability.Open in a separate windowFigure 1.Two mechanisms that give rise to barbed-end depolymerization in elongation-promoting conditions. (A) When a cofilin side-decorated region reaches the barbed end, adding a new actin or profilin-actin becomes very difficult, and the barbed end depolymerizes. Not represented: Capping by CP can lead to depolymerization, as it allows the cofilin cluster to reach the barbed end, which then has a much weaker affinity for CP and steadily depolymerizes. Also, severing events occur at cofilin cluster boundaries, creating new barbed ends, either bare or cofilin-decorated. (B) Twinfilin binds to the barbed end, preventing its elongation and causing its depolymerization. Whether twinfilin remains processively attached to the depolymerizing barbed end or departs with the actin subunits is still unknown. Twinfilin has no impact on the elongation of mDia1-bearing barbed ends.Driving the depolymerization of barbed ends with twinfilin end-targetingTwinfilin has two ADF-H domains, but unlike cofilin, it binds poorly to the sides of actin filaments. Rather, twinfilin appears to mainly sequester ADP-actin monomers and target the barbed end to modulate its elongation and capping. Recent in vitro studies have shown that the interaction of twinfilin with actin filament barbed ends could drive their depolymerization, even in the presence of G-actin and profilin-actin (Johnston et al., 2015; Hakala et al., 2021; Shekhar et al., 2021). Very interestingly, the processive barbed-end elongator formin mDia1 is able to protect barbed ends from twinfilin, allowing them to sustain elongation (Shekhar et al., 2021). This leads to a situation in which, as filaments are exposed to profilin-actin and twinfilin, mDia1-bearing barbed ends elongate while bare barbed ends depolymerize (Fig. 1 B). It is safe to assume that, if filaments were continuously exposed to this protein mix including formin in solution, they would alternate between phases of growth and shrinkage over time, as formins come on and fall off the barbed end. This mix of proteins would therefore constitute another situation causing actin filament dynamic instability.From actin treadmilling to dynamic instability, in cells?This newly identified versatile behavior of actin filaments is reminiscent of microtubules. While dynamic instability is the hallmark behavior of microtubules, they can also be made to treadmill steadily by adding 4 microtubule-associated proteins (Arpağ et al., 2020). In cells, both microtubule dynamic instability and treadmilling have been clearly observed (Wittmann et al., 2003). In contrast, the disassembly of single actin filaments, either embedded in a network or severed from it, has not yet been directly observed in cells. Despite insights from techniques such as single-molecule speckle microscopy, it is still unclear from which end actin filaments depolymerize, even in networks that appear to globally treadmill, such as the lamellipodium. Pointed end depolymerization alone cannot account for what is observed in cells (Miyoshi et al., 2006) and alternative mechanisms have been proposed, including brutal filament-to-monomer transitions occurring in bursts, driven by cofilin, coronin, and Aip1 (Brieher, 2013; Tang et al., 2020).In cells, the high amounts of available G-actin (tens of micromolars; Funk et al., 2019) should limit barbed-end depolymerization. Based on the reported on-rate for ATP–G-actin at the barbed ends of cofilin-decorated filaments (Wioland et al., 2017, 2019), we can estimate that these barbed ends, under such conditions, would depolymerize for tens of seconds before being “rescued,” which is enough to remove tens of subunits from each filament. In contrast, twinfilin concentrations similar to those of G-actin appear necessary to drive barbed-end depolymerization (Hakala et al., 2021; Shekhar et al., 2021). As proteomics studies in HeLa cells report that twinfilin is 50-fold less abundant than actin, this may be difficult to achieve in cells (Bekker-Jensen et al., 2017). However, future studies may uncover proteins, or posttranslational modifications of actin, that enhance the ability of twinfilin to drive barbed-end depolymerization in the presence of high concentrations of profilin-actin.Molecular insights and possible synergiesWhile cofilin and twinfilin both interact with actin via ADF-H domains, they appear to drive barbed-end depolymerization through different mechanisms: twinfilin by directly targeting the barbed end, and cofilin by decorating the filament sides, thereby changing the conformation of the filament and putting its barbed end in a depolymerization-prone state.The two mechanisms, nonetheless, share clear similarities. For instance, cofilin side-binding and twinfilin end-targeting both slow down ADP-actin barbed-end depolymerization, compared with bare ADP-actin filaments (Wioland et al., 2017; Hakala et al., 2021; Shekhar et al., 2021). Strikingly, a crystal structure of the actin/twinfilin/CP complex indicates that the actin conformational change induced by twinfilin binding at the barbed end is similar to that induced by cofilin decorating the sides (Mwangangi et al., 2021). It is thus possible that the dynamic instability of actin filament barbed ends reflects the same conformation changes, triggered either by cofilin side-decoration or twinfilin end-targeting.In addition to decorating the filament sides, cofilin targets ADP-actin barbed ends. Unlike twinfilin, the direct interaction of cofilin with the barbed end cannot cause its depolymerization in the presence of ATP-actin monomers. Indeed, cofilin end-targeting accelerates the depolymerization of ADP-actin barbed ends in the absence of G-actin, but cofilin does not appear to interact with growing ATP-actin barbed ends (Wioland et al., 2017). This is in stark contrast with twinfilin end-targeting, which slows down ADP-actin depolymerization and accelerates ADP–Pi-actin depolymerization (Shekhar et al., 2021). These different behaviors regarding the nucleotide state of actin are intriguing and should be investigated further.Cofilin thus needs to decorate the filament sides in order to have an impact on barbed-end dynamics in elongation-promoting conditions. However, it is unknown whether cofilin side-decoration extends all the way to the terminal subunits and occupies sites that twinfilin would target. Thus, it is unclear whether cofilin and twinfilin would compete or synergize to drive barbed-end depolymerization.Synergies with other proteins are also worth further investigation, CP being an interesting candidate. Cofilin side-decoration drastically decreases the barbed-end affinity for CP, and capped filaments are thereby an efficient intermediate to turn growing barbed ends into depolymerizing barbed ends (Wioland et al., 2017). Twinfilin interacts with CP and the barbed end to enhance uncapping (Hakala et al., 2021; Mwangangi et al., 2021). Since CP can bind mDia1-bearing barbed ends and displace mDia1 (Bombardier et al., 2015; Shekhar et al., 2015), perhaps CP can also contribute to turn growing, mDia1-bearing barbed ends into depolymerizing barbed ends, by removing mDia1 from barbed ends and subsequently getting displaced from the barbed end by twinfilin.Finally, it is worth noting that profilin, which does not contain an ADF-H domain, also interacts with the barbed face of G-actin and with the barbed end of the filament. When profilin is in sufficient excess, it is able to promote barbed-end depolymerization in the presence of ATP–G-actin (Pernier et al., 2016). Unlike twinfilin, its depolymerization-promoting activity is not prevented by formin mDia1, and it thus does not lead to dynamic instability (bare and mDia1-bearing barbed ends all either grow or depolymerize). The coexistence of growing, mDia1-bearing barbed ends and depolymerizing, twinfilin-targeted barbed ends (Fig. 1 B) was observed in the presence of profilin (Shekhar et al., 2021), but profilin actually may not be required. Future studies should determine the exact role of profilin in this mechanism.ConclusionThe extent to which barbed-end dynamic instability contributes to actin turnover in cells is not known, but possible molecular mechanisms have now been identified. They should change the way we envision actin network dynamics, as we must now consider the possibility that cells also exploit the barbed end for disassembly. More work is needed to further document these mechanisms, but the idea of a “generalized treadmilling” has now been contradicted at its source: in vitro experiments.     

A One Health Perspective for Defining and Deciphering Escherichia coli Pathogenic Potential in Multiple Hosts

E. coli is one of the most common species of bacteria colonizing humans and animals. The singularity of E. coli’s genus and species underestimates its multifaceted nature, which is represented by different strains, each with different combinations of distinct virulence factors. In fact, several E. coli pathotypes, or hybrid strains, may be associated with both subclinical infection and a range of clinical conditions, including enteric, urinary, and systemic infections. E. coli may also express DNA-damaging toxins that could impact cancer development. This review summarizes the different E. coli pathotypes in the context of their history, hosts, clinical signs, epidemiology, and control. The pathotypic characterization of E. coli in the context of disease in different animals, including humans, provides comparative and One Health perspectives that will guide future clinical and research investigations of E. coli infections.

Escherichia coli (E. coli) is the most common bacterial model used in research and biotechnology. It is an important cause of morbidity and mortality in humans and animals worldwide, and animal hosts can be involved in the epidemiology of infections.^{240,367,373,452,727} The adaptive and versatile nature of E. coli argues that ongoing studies should receive a high priority in the context of One Health involving humans, animals, and the environment.^{240,315,343,727} Two of the 3 E. coli pathogens associated with death in children with moderate-to-severe diarrhea in Asia and Africa are classified into 2 E. coli pathogenic groups (also known as pathotypes or pathovars): enterotoxigenic E. coli (ETEC) and enteropathogenic E. coli (EPEC).³⁶⁷ In global epidemiologic studies, ETEC and EPEC rank among the deadliest causes of foodborne diarrheal illness and are important pathogens for increasing disability adjusted life years.^355,382,570 Furthermore, in humans, E. coli is one of the top-ten organisms involved in coinfections, which generally have deleterious effects on health.²⁷⁰ETEC is also an important etiologic agent of diarrhea in the agricultural setting.¹⁸³ E. coli-associated extraintestinal infections, some of which may be antibiotic-resistant, have a tremendous impact on human and animal health. These infections have a major economic impact on the poultry, swine, and dairy industries.^{70,151,168,681,694,781,797} The pervasive nature of E. coli, and its capacity to induce disease have driven global research efforts to understand, prevent, and treat these devastating diseases. Animal models for the study of E. coli infections have been useful for pathogenesis elucidation and development of intervention strategies; these include zebrafish, rats, mice, Syrian hamsters, guinea pigs, rabbits, pigs, and nonhuman primates.^{27,72,101,232,238,347,476,489,493,566,693,713,744,754} Experiments involving human volunteers have also been important for the study of infectious doses associated with E. coli-induced disease and of the role of virulence determinants in disease causation.^{129,176,365,400,497,702,703} E. coli strains (or their lipopolysaccharide) have also been used for experimental induction of sepsis in animals; the strains used for these studies, considered EPEC, are not typically involved in systemic disease.^{140,205,216,274,575,782}This article provides an overview of selected topics related to E. coli, a common aerobic/facultative anaerobic gastrointestinal organism of humans and animals.^{14,277,432,477,716} In addition, we briefly review: history, definition, pathogenesis, prototype (archetype or reference) strains, and features of the epidemiology and control of specific pathotypes. Furthermore, we describe cases attributed to different E. coli pathotypes in a range of animal hosts. The review of scientific and historical events regarding the discovery and characterization of the different E. coli pathotypes will increase clinical awareness of E. coli, which is too often regarded merely as a commensal organism, as a possible primary or co- etiologic agent during clinical investigations. As Will and Ariel Durant write in The Lessons of History: “The present is the past rolled up for action, and the past is the present unrolled for understanding”.     

The tubulin code: Molecular components,readout mechanisms,and functions

Microtubules are cytoskeletal filaments that are dynamically assembled from α/β-tubulin heterodimers. The primary sequence and structure of the tubulin proteins and, consequently, the properties and architecture of microtubules are highly conserved in eukaryotes. Despite this conservation, tubulin is subject to heterogeneity that is generated in two ways: by the expression of different tubulin isotypes and by posttranslational modifications (PTMs). Identifying the mechanisms that generate and control tubulin heterogeneity and how this heterogeneity affects microtubule function are long-standing goals in the field. Recent work on tubulin PTMs has shed light on how these modifications could contribute to a “tubulin code” that coordinates the complex functions of microtubules in cells.

Introduction

Microtubules are key elements of the eukaryotic cytoskeleton that dynamically assemble from heterodimers of α- and β-tubulin. The structure of microtubules, as well as the protein sequences of α- and β-tubulin, is highly conserved in evolution, and consequently, microtubules look alike in almost all species. Despite the high level of conservation, microtubules adapt to a large variety of cellular functions. This adaptation can be mediated by a large panel of microtubule-associated proteins (MAPs), including molecular motors, as well as by mechanisms that directly modify the microtubules, thus either changing their biophysical properties or attracting subsets of MAPs that convey specific functions to the modified microtubules. Two different mechanism can generate microtubule diversity: the expression of different α- and β-tubulin genes, referred to as tubulin isotypes, and the generation of posttranslational modifications (PTMs) on α- and β-tubulin (Figs. 1 and ​and2).2). Although known for several decades, deciphering how tubulin heterogeneity controls microtubule functions is still largely unchartered. This review summarizes the current advances in the field and discusses new concepts arising.Open in a separate windowFigure 1.Tubulin heterogeneity generated by PTMs. (A) Schematic representation of the distribution of different PTMs of tubulin on the α/β-tubulin dimer with respect to their position in the microtubule lattice. Acetylation (Ac), phosphorylation (P), and polyamination (Am) are found within the tubulin bodies that assemble into the microtubule lattice, whereas polyglutamylation, polyglycylation, detyrosination, and C-terminal deglutamylation take place within the C-terminal tubulin tails that project away from the lattice surface. The tubulin dimer represents TubA1A and TubB2B (Fig. 2), and modification sites for polyglutamylation and polyglycylation have been randomly chosen. (B) Chemical structure of the branched peptide formed by polyglutamylation and polyglycylation, using the γ-carboxyl groups of the modified glutamate residues as acceptor sites for the isopeptide bonds. Note that in the case of polyglutamylation, the elongation of the side chains generates classical peptide bonds (Redeker et al., 1991).Open in a separate windowFigure 2.Heterogeneity of C-terminal tails of tubulin isotypes and their PTMs. The amino acid sequences of all tubulin genes found in the human genome are indicated, starting at the last amino acid of the folded tubulin bodies. Amino acids are represented in single-letter codes and color coded according to their biochemical properties. Known sites for polyglutamylation are indicated (Eddé et al., 1990; Alexander et al., 1991; Rüdiger et al., 1992). Potential modification sites (all glutamate residues) are indicated. Known C-terminal truncation reactions of α/β-tubulin (tub) are indicated. The C-terminal tails of the yeast Saccharomyces cerevisiae are shown to illustrate the phylogenetic diversity of these domains.

Tubulin isotypes

The cloning of the first tubulin genes in the late 1970’s (Cleveland et al., 1978) revealed the existence of multiple genes coding for α- or β-tubulin (Ludueña and Banerjee, 2008) that generate subtle differences in their amino acid sequences, particularly in the C-terminal tails (Fig. 2). It was assumed that tubulin isotypes, as they were named, assemble into discrete microtubule species that carry out unique functions. This conclusion was reinforced by the observation that some isotypes are specifically expressed in specialized cells and tissues and that isotype expression changes during development (Lewis et al., 1985; Denoulet et al., 1986). These high expectations were mitigated by a subsequent study showing that all tubulin isotypes freely copolymerize into heterogeneous microtubules (Lewis et al., 1987). To date, only highly specialized microtubules, such as ciliary axonemes (Renthal et al., 1993; Raff et al., 2008), neuronal microtubules (Denoulet et al., 1986; Joshi and Cleveland, 1989), and microtubules of the marginal band of platelets (Wang et al., 1986; Schwer et al., 2001) are known to depend on some specific (β) tubulin isotypes, whereas the function of most other microtubules appears to be independent of their isotype composition.More recently, a large number of mutations in single tubulin isotypes have been linked to deleterious neurodevelopmental disorders (Keays et al., 2007; Fallet-Bianco et al., 2008; Tischfield et al., 2010; Cederquist et al., 2012; Niwa et al., 2013). Mutations of a single tubulin isotype could lead to an imbalance in the levels of tubulins as a result of a lack of incorporation of mutant isoforms into the microtubule lattice or to incorporation that perturbs the architecture or dynamics of the microtubules. The analysis of tubulin disease mutations is starting to reveal how subtle alterations of the microtubule cytoskeleton can lead to functional aberrations in cells and organisms and might provide novel insights into the roles of tubulin isotypes that have so far been considered redundant.

Tubulin PTMs

Tubulin is subject to a large range of PTMs (Fig. 1), from well-known ones, such as acetylation or phosphorylation, to others that have so far mostly been found on tubulin. Detyrosination/tyrosination, polyglutamylation, and polyglycylation, for instance, might have evolved to specifically regulate tubulin and microtubule functions, in particular in cilia and flagella, as their evolution is closely linked to these organelles. The strong link between those modifications and tubulin evolution has led to the perception that they are tubulin PTMs; however, apart from detyrosination/tyrosination, most of them have other substrates (Regnard et al., 2000; Xie et al., 2007; van Dijk et al., 2008; Rogowski et al., 2009).

Tubulin acetylation.

Tubulin acetylation was discovered on lysine 40 (K40; Fig. 1 A) of flagellar α-tubulin in Chlamydomonas reinhardtii (L’Hernault and Rosenbaum, 1985) and is generally enriched on stable microtubules in cells. Considering that K40 acetylation per se has no effect on the ultrastructure of microtubules (Howes et al., 2014), it is rather unlikely that it directly stabilizes microtubules. As a result of its localization at the inner face of microtubules (Soppina et al., 2012), K40 acetylation might rather affect the binding of microtubule inner proteins, a poorly characterized family of proteins (Nicastro et al., 2011; Linck et al., 2014). Functional experiments in cells have further suggested that K40 acetylation regulates intracellular transport by regulating the traffic of kinesin motors (Reed et al., 2006; Dompierre et al., 2007). These observations could so far not be confirmed by biophysical measurements in vitro (Walter et al., 2012; Kaul et al., 2014), suggesting that in cells, K40 acetylation might affect intracellular traffic by indirect mechanisms.Enzymes involved in K40 acetylation are HDAC6 (histone deacetylase family member 6; Hubbert et al., 2002) and Sirt2 (sirtuin type 2; North et al., 2003). Initial functional studies used overexpression, depletion, or chemical inhibition of these enzymes. These studies should be discussed with care, as both HDAC6 and Sirt2 deacetylate other substrates and have deacetylase-independent functions and chemical inhibition of HDAC6 is not entirely selective for this enzyme (Valenzuela-Fernández et al., 2008). In contrast, acetyl transferase α-Tat1 (or Mec-17; Akella et al., 2010; Shida et al., 2010) specifically acetylates α-tubulin K40 (Fig. 3), thus providing a more specific tool to investigate the functions of K40 acetylation. Knockout mice of α-Tat1 are completely void of K40-acetylated tubulin; however, they show only slight phenotypic aberrations, for instance, in their sperm flagellum (Kalebic et al., 2013). A more detailed analysis of α-Tat1 knockout mice demonstrated that absence of K40 acetylation leads to reduced contact inhibition in proliferating cells (Aguilar et al., 2014). In migrating cells, α-Tat1 is targeted to microtubules at the leading edge by clathrin-coated pits, resulting in locally restricted acetylation of those microtubules (Montagnac et al., 2013). A recent structural study of α-Tat1 demonstrated that the low catalytic rate of this enzyme, together with its localization inside the microtubules, caused acetylation to accumulate selectively in stable, long-lived microtubules (Szyk et al., 2014), thus explaining the link between this PTM and stable microtubules in cells. However, the direct cellular function of K40 acetylation on microtubules is still unclear.Open in a separate windowFigure 3.Enzymes involved in PTM of tubulin. Schematic representation of known enzymes (mammalian enzymes are shown) involved in the generation and removal of PTMs shown in Fig. 1. Note that some enzymes still remain unknown, and some modifications are irreversible. (*CCP5 preferentially removes branching points [Rogowski et al., 2010]; however, the enzyme can also hydrolyze linear glutamate chains [Berezniuk et al., 2013]).Recent discoveries have brought up the possibility that tubulin could be subject to multiple acetylation events. A whole-acetylome study identified >10 novel sites on α- and β-tubulin (Choudhary et al., 2009); however, none of these sites have been confirmed. Another acetylation event has been described at lysine 252 (K252) of β-tubulin. This modification is catalyzed by the acetyltransferase San (Fig. 3) and might regulate the assembly efficiency of microtubules as a result of its localization at the polymerization interface (Chu et al., 2011).

Tubulin detyrosination.

Most α-tubulin genes in different species encode a C-terminal tyrosine residue (Fig. 2; Valenzuela et al., 1981). This tyrosine can be enzymatically removed (Hallak et al., 1977) and religated (Fig. 3; Arce et al., 1975). Mapping of tyrosinated and detyrosinated microtubules in cells using specific antibodies (Gundersen et al., 1984; Geuens et al., 1986; Cambray-Deakin and Burgoyne, 1987a) revealed that subsets of interphase and mitotic spindle microtubules are detyrosinated (Gundersen and Bulinski, 1986). As detyrosination was mostly found on stable and long-lived microtubules, especially in neurons (Cambray-Deakin and Burgoyne, 1987b; Robson and Burgoyne, 1989; Brown et al., 1993), it was assumed that this modification promotes microtubule stability (Gundersen et al., 1987; Sherwin et al., 1987). Although a direct stabilization of the microtubule lattice was considered unlikely (Khawaja et al., 1988), it was found more recently that detyrosination protects cellular microtubules from the depolymerizing activity of kinesin-13–type motor proteins, such as KIF2 or MCAK, thus increasing their longevity (Peris et al., 2009; Sirajuddin et al., 2014).Besides kinesin-13 motors, plus end–tracking proteins with cytoskeleton-associated protein glycine-rich (CAP-Gly) domains, such as CLIP170 or p150/glued, specifically interact with tyrosinated microtubules (Peris et al., 2006; Bieling et al., 2008) via this domain (Honnappa et al., 2006). In contrast, kinesin-1 moves preferentially on detyrosinated microtubules tracks in cells (Liao and Gundersen, 1998; Kreitzer et al., 1999; Konishi and Setou, 2009). The effect of detyrosination on kinesin-1 motor behavior was recently measured in vitro, and a small but significant increase in the landing rate and processivity of the motor has been found (Kaul et al., 2014). Such subtle changes in the motor behavior could, in conjunction with other factors, such as regulatory MAPs associated with cargo transport complexes (Barlan et al., 2013), lead to a preferential use of detyrosinated microtubules by kinesin-1 in cells.Despite the early biochemical characterization of a detyrosinating activity, the carboxypeptidase catalyzing detyrosination of α-tubulin has yet to be identified (Hallak et al., 1977; Argaraña et al., 1978, 1980). In contrast, the reverse enzyme, tubulin tyrosine ligase (TTL; Fig. 3; Raybin and Flavin, 1975; Deanin and Gordon, 1976; Argaraña et al., 1980), has been purified (Schröder et al., 1985) and cloned (Ersfeld et al., 1993). TTL modifies nonpolymerized tubulin dimers exclusively. This selectivity is determined by the binding interface between the TTL and tubulin dimers (Szyk et al., 2011, 2013; Prota et al., 2013). In contrast, the so far unidentified detyrosinase acts preferentially on polymerized microtubules (Kumar and Flavin, 1981; Arce and Barra, 1983), thus modifying a select population of microtubules within cells (Gundersen et al., 1987).In most organisms, only one unique gene for TTL exists. Consequently, TTL knockout mice show a huge accumulation of detyrosinated and particularly Δ2-tubulin (see next section). TTL knockout mice die before birth (Erck et al., 2005) with major developmental defects in the nervous system that might be related to aberrant neuronal differentiation (Marcos et al., 2009). TTL is strictly tubulin specific (Prota et al., 2013), indicating that all observed defects in TTL knockout mice are directly related to the deregulation of the microtubule cytoskeleton.

Δ2-tubulin and further C-terminal modification.

A biochemical study of brain tubulin revealed that ∼35% of α-tubulin cannot be retyrosinated (Paturle et al., 1989) because of the lack of the penultimate C-terminal glutamate residue of the primary protein sequence (Fig. 2; Paturle-Lafanechère et al., 1991). This so-called Δ2-tubulin (for two C-terminal amino acids missing) cannot undergo retyrosination as a result of structural constraints within TTL (Prota et al., 2013) and thus is considered an irreversible PTM.Δ2-tubulin accumulates in long-lived microtubules of differentiated neurons, axonemes of cilia and flagella, and also in cellular microtubules that have been artificially stabilized, for instance, with taxol (Paturle-Lafanechère et al., 1994). The generation of Δ2-tubulin requires previous detyrosination of α-tubulin; thus, the levels of this PTM are indirectly regulated by the detyrosination/retyrosination cycle. This mechanistic link is particularly apparent in the TTL knockout mice, which show massive accumulation of Δ2-tubulin in all tested tissues (Erck et al., 2005). Loss of TTL and the subsequent increase of Δ2-tubulin levels were also linked to tumor growth and might contribute to the aggressiveness of the tumors by an as-yet-unknown mechanism (Lafanechère et al., 1998; Mialhe et al., 2001). To date, no specific biochemical role of Δ2-tubulin has been determined; thus, one possibility is that the modification simply locks tubulin in the detyrosinated state.The enzymes responsible for Δ2-tubulin generation are members of a family of cytosolic carboxypeptidases (CCPs; Fig. 3; Kalinina et al., 2007; Rodriguez de la Vega et al., 2007), and most of them also remove polyglutamylation from tubulin (see next section; Rogowski et al., 2010). These enzymes are also able to generate Δ3-tubulin (Fig. 1 A; Berezniuk et al., 2012), indicating that further degradation of the tubulin C-terminal tails are possible; however, the functional significance of this event is unknown.

Polyglutamylation.

Polyglutamylation is a PTM that occurs when secondary glutamate side chains are formed on γ-carboxyl groups of glutamate residues in a protein (Fig. 1, A and B). The modification was first discovered on α- and β-tubulin from the brain (Eddé et al., 1990; Alexander et al., 1991; Rüdiger et al., 1992; Mary et al., 1994) as well as on axonemal tubulin from different species (Mary et al., 1996, 1997); however, it is not restricted to tubulin (Regnard et al., 2000; van Dijk et al., 2008). Using a glutamylation-specific antibody, GT335 (Wolff et al., 1992), it was observed that tubulin glutamylation increases during neuronal differentiation (Audebert et al., 1993, 1994) and that axonemes of cilia and flagella (Fouquet et al., 1994), as well as centrioles of mammalian centrosomes (Bobinnec et al., 1998), are extensively glutamylated.Enzymes catalyzing polyglutamylation belong to the TTL-like (TTLL) family (Regnard et al., 2003; Janke et al., 2005). In mammals, nine glutamylases exist, each of them showing intrinsic preferences for modifying either α- or β-tubulin as well as for initiating or elongating glutamate chains (Fig. 3; van Dijk et al., 2007). Two of the six well-characterized TTLL glutamylases also modify nontubulin substrates (van Dijk et al., 2008).Knockout or depletion of glutamylating enzymes in different model organisms revealed an evolutionarily conserved role of glutamylation in cilia and flagella. In motile cilia, glutamylation regulates beating behavior (Janke et al., 2005; Pathak et al., 2007; Ikegami et al., 2010) via the regulation of flagellar dynein motors (Kubo et al., 2010; Suryavanshi et al., 2010). Despite the expression of multiple glutamylases in ciliated cells and tissues, depletion or knockout of single enzymes often lead to ciliary defects, particularly in motile cilia (Ikegami et al., 2010; Vogel et al., 2010; Bosch Grau et al., 2013; Lee et al., 2013), suggesting essential and nonredundant regulatory functions of these enzymes in cilia.Despite the enrichment of polyglutamylation in neuronal microtubules (Audebert et al., 1993, 1994), knockout of TTLL1, the major polyglutamylase in brain (Janke et al., 2005), did not show obvious neuronal defects in mice (Ikegami et al., 2010; Vogel et al., 2010). This suggests a tolerance of neuronal microtubules to variations in polyglutamylation.Deglutamylases, the enzymes that reverse polyglutamylation, were identified within a novel family of CCPs (Kimura et al., 2010; Rogowski et al., 2010). So far, three out of six mammalian CCPs have been shown to cleave C-terminal glutamate residues, thus catalyzing both the reversal of polyglutamylation and the removal of gene-encoded glutamates from the C termini of proteins (Fig. 3). The hydrolysis of gene-encoded glutamate residues is not restricted to tubulin, in which it generates Δ2- and Δ3-tubulin, but has also been reported for other proteins such as myosin light chain kinase (Rusconi et al., 1997; Rogowski et al., 2010). One enzyme of the CCP family, CCP5, preferentially removes branching points generated by glutamylation, thus allowing the complete reversal of the polyglutamylation modification (Kimura et al., 2010; Rogowski et al., 2010). However, CCP5 can also hydrolyze C-terminal glutamate residues from linear peptide chains similar to other members of the CCP family (Berezniuk et al., 2013).CCP1 is mutated in a well-established mouse model for neurodegeneration, the pcd (Purkinje cell degeneration) mouse (Mullen et al., 1976; Greer and Shepherd, 1982; Fernandez-Gonzalez et al., 2002). The absence of a key deglutamylase leads to strong hyperglutamylation in brain regions that undergo degeneration, such as the cerebellum and the olfactory bulb (Rogowski et al., 2010). When glutamylation levels were rebalanced by depletion or knockout of the major brain polyglutamylase TTLL1 (Rogowski et al., 2010; Berezniuk et al., 2012), Purkinje cells survived. Although the molecular mechanisms of hyperglutamylation-induced degeneration remain to be elucidated, perturbation of neuronal transport, as well as changes in the dynamics and stability of microtubules, is expected to be induced by hyperglutamylation. Increased polyglutamylation levels have been shown to affect kinesin-1–mediated transport in cultured neurons (Maas et al., 2009), and the turnover of microtubules can also be regulated by polyglutamylation via the activation of microtubule-severing enzymes such as spastin (Lacroix et al., 2010).Subtle differences in polyglutamylation can be seen on diverse microtubules in different cell types. The functions of these modifications remain to be studied; however, its wide distribution strengthens the idea that it could be involved in fine-tuning a range of microtubule functions.

Polyglycylation.

Tubulin polyglycylation or glycylation, like polyglutamylation, generates side chains of glycine residues within the C-terminal tails of α- and β-tubulin (Fig. 1, A and B). The modification sites of glycylation are considered to be principally the same as for glutamylation, and indeed, both PTMs have been shown to be interdependent in cells (Rogowski et al., 2009; Wloga et al., 2009). Initially discovered on Paramecium tetraurelia tubulin (Redeker et al., 1994), glycylation has been extensively studied using two antibodies, TAP952 and AXO49 (Bressac et al., 1995; Levilliers et al., 1995; Bré et al., 1996). In contrast to polyglutamylation, glycylation is restricted to cilia and flagella in most organisms analyzed so far.Glycylating enzymes are also members of the TTLL family, and homologues of these enzymes have so far been found in all organisms with proven glycylation of ciliary axonemes (Rogowski et al., 2009; Wloga et al., 2009). In mammals, initiating (TTLL3 and TTLL8) and elongating (TTLL10) glycylases work together to generate polyglycylation (Fig. 3). In contrast, the two TTLL3 orthologues from Drosophila melanogaster can both initiate and elongate glycine side chains (Rogowski et al., 2009).In mice, motile ependymal cilia in brain ventricles acquire monoglycylation upon maturation, whereas polyglycylation is observed only after several weeks (Bosch Grau et al., 2013). Sperm flagella, in contrast, acquire long glycine chains much faster, suggesting that the extent of polyglycylation could correlate with the length of the axonemes (Rogowski et al., 2009). Depletion of glycylases in mice (ependymal cilia; Bosch Grau et al., 2013), zebrafish (Wloga et al., 2009; Pathak et al., 2011), Tetrahymena thermophila (Wloga et al., 2009), and D. melanogaster (Rogowski et al., 2009) consistently led to ciliary disassembly or severe ciliary defects. How glycylation regulates microtubule functions remains unknown; however, the observation that glycylation-depleted axonemes disassemble after initial assembly (Rogowski et al., 2009; Bosch Grau et al., 2013) suggests a role of this PTM in stabilizing axonemal microtubules. Strikingly, human TTLL10 is enzymatically inactive; thus, humans have lost the ability to elongate glycine side chains (Rogowski et al., 2009). This suggests that the elongation of the glycine side chains is not an essential aspect of the function of this otherwise critical tubulin PTM.

Other tubulin PTMs.

Several other PTMs have been found on tubulin. Early studies identified tubulin phosphorylation (Eipper, 1974; Gard and Kirschner, 1985; Díaz-Nido et al., 1990); however, no specific functions were found. The perhaps best-studied phosphorylation event on tubulin takes place at serine S172 of β-tubulin (Fig. 1 A), is catalyzed by the Cdk1 (Fig. 3), and might regulate microtubule dynamics during cell division (Fourest-Lieuvin et al., 2006; Caudron et al., 2010). Tubulin can be also modified by the spleen tyrosine kinase Syk (Fig. 3; Peters et al., 1996), which might play a role in immune cells (Faruki et al., 2000; Sulimenko et al., 2006) and cell division (Zyss et al., 2005; Sulimenko et al., 2006).Polyamination has recently been discovered on brain tubulin (Song et al., 2013), after having been overlooked for many years as a result of the low solubility of polyaminated tubulin. Among several glutamine residues of α- and β-tubulin that can be polyaminated, Q15 of β-tubulin is considered the primary modification site (Fig. 1 A). Polyamination is catalyzed by transglutaminases (Fig. 3), which modify free tubulin as well as microtubules in an irreversible manner, and most likely contribute to the stabilization of microtubules (Song et al., 2013).Tubulin was also reported to be palmitoylated (Caron, 1997; Ozols and Caron, 1997; Caron et al., 2001), ubiquitinated (Ren et al., 2003; Huang et al., 2009; Xu et al., 2010), glycosylated (Walgren et al., 2003; Ji et al., 2011), arginylated (Wong et al., 2007), methylated (Xiao et al., 2010), and sumoylated (Rosas-Acosta et al., 2005). These PTMs have mostly been reported without follow-up studies, and some of them are only found in specific cell types or organisms and/or under specific metabolic conditions. Further studies will be necessary to gain insights into their potential roles for the regulation of the microtubule cytoskeleton.

Current advances and future perspectives

The molecular heterogeneity of microtubules, generated by the expression of different tubulin isotypes and by the PTM of tubulin has fascinated the scientific community for ∼40 years. Although many important advances have been made in the past decade, the dissection of the molecular mechanisms and a comprehensive understanding of the biological functions of tubulin isotypes and PTMs will be a challenging field of research in the near future.

Direct measurements of the impact of tubulin heterogeneity.

The most direct and reliable type of experiments to determine the impact of tubulin heterogeneity on microtubule behavior are in vitro measurements with purified proteins. However, most biophysical work on microtubules has been performed with tubulin purified from bovine, ovine, or porcine brains, which can be obtained in large quantities and with a high degree of purity and activity (Vallee, 1986; Castoldi and Popov, 2003). Brain tubulin is a mixture of different tubulin isotypes and is heavily posttranslationally modified and thus inept for investigating the functions of tubulin heterogeneity (Denoulet et al., 1986; Cambray-Deakin and Burgoyne, 1987b; Paturle et al., 1989; Eddé et al., 1990). Thus, pure, recombinant tubulin will be essential to dissect the roles of different tubulin isoforms and PTMs.Attempts to produce recombinant, functional α- and β-tubulin in bacteria have failed so far (Yaffe et al., 1988), most likely because of the absence of the extensive tubulin-specific folding machinery (Yaffe et al., 1992; Gao et al., 1993; Tian et al., 1996; Vainberg et al., 1998) in prokaryotes. An alternative source of tubulin with less isotype heterogeneity and with almost no PTMs is endogenous tubulin from cell lines such as HeLa, which in the past has been purified using a range of biochemical procedures (Bulinski and Borisy, 1979; Weatherbee et al., 1980; Farrell, 1982; Newton et al., 2002; Fourest-Lieuvin, 2006). Such tubulin can be further modified with tubulin-modifying enzymes, such as polyglutamylases, either by expressing those enzymes in the cells before tubulin purification (Lacroix and Janke, 2011) or in vitro with purified enzymes (Vemu et al., 2014). Despite some technical limitations of these methods, HeLa tubulin modified in cells has been successfully used in an in vitro study on the role of polyglutamylation in microtubule severing (Lacroix et al., 2010).Naturally occurring variants of tubulin isotypes and PTMs can be purified from different organisms, organs, or cell types, but obviously, only some combinations of tubulin isotypes and PTMs can be obtained by this approach. The recent development of an affinity purification method using the microtubule-binding TOG (tumor overexpressed gene) domain of yeast Stu2p has brought a new twist to this approach, as it allows purifying small amounts of tubulin from any cell type or tissue (Widlund et al., 2012).The absence of tubulin heterogeneity in yeast has made budding and fission yeast potential expression systems for recombinant, PTM-free tubulin (Katsuki et al., 2009; Drummond et al., 2011; Johnson et al., 2011). However, the expression of mammalian tubulin in this system has remained impossible. This problem was then partially circumvented by expressing tubulin chimeras that consist of a yeast tubulin body fused to mammalian C-terminal tubulin tails, thus mimicking different tubulin isotypes (Sirajuddin et al., 2014). Moreover, detyrosination can be generated by deleting the key C-terminal residue from endogenous or chimeric α-tubulin (Badin-Larçon et al., 2004), and polyglutamylation is generated by chemically coupling glutamate side chains to specifically engineered tubulin chimeras (Sirajuddin et al., 2014). These approaches allowed the first direct measurements of the impact of tubulin isotypes and PTMs on the behavior of molecular motors in vitro (Sirajuddin et al., 2014) and the analysis of the effects of tubulin heterogeneity on microtubule behavior and interactions inside the yeast cell (Badin-Larçon et al., 2004; Aiken et al., 2014).Currently, the most promising development has been the successful purification of fully functional recombinant tubulin from the baculovirus expression system (Minoura et al., 2013). Using this system, defined α/β-tubulin dimers can be obtained using two different epitope tags on α- and β-tubulin, respectively. Although these epitope tags are essential for separating recombinant from the endogenous tubulin, they could also affect tubulin assembly or microtubule–MAP interactions. Thus, future developments should focus on eliminating these tags.Current efforts have brought the possibility of producing recombinant tubulin into reach. Further improvement and standardization of these methods will certainly provide a breakthrough in understanding the mechanisms by which tubulin heterogeneity contributes to microtubule functions.

Complexity of tubulin—understanding the regulatory principles.

The diversity of tubulin genes (isotypes) and the complexity of tubulin PTMs have led to the proposal of the term “tubulin code” (Verhey and Gaertig, 2007; Wehenkel and Janke, 2014), in analogy to the previously coined histone code (Jenuwein and Allis, 2001). Tubulin molecules consist of a highly structured and thus evolutionarily conserved tubulin body and the unstructured and less conserved C-terminal tails (Nogales et al., 1998). As PTMs and sequence variations within the tubulin body are expected to affect the conserved tubulin fold and therefore the properties of the microtubule lattice, they are not likely to be involved in generating the tubulin code. In contrast, modulations of the C-terminal tails could encode signals on the microtubule surface without perturbing basic microtubule functions and properties (Figs. 1 A and ​and4).4). Indeed, the highest degree of gene-encoded diversity (Fig. 2) and the highest density and complexity of PTMs (Fig. 1) are found within these tail domains.Open in a separate windowFigure 4.Molecular components of the tubulin code. Schematic representation of potential coding elements that could generate specific signals for the tubulin code. (A) The length of the C-terminal tails of different tubulin isotypes differ significantly (Fig. 2) and could have an impact on the interactions between microtubules and MAPs. (B) Tubulin C-terminal tails are rich in charged amino acid residues. The distribution of these residues and local densities of charges could influence the electrostatic interactions with the tails and the readers. (C) Although each glutamate residue within the C-terminal tails could be considered a potential modification site, only some sites have been found highly occupied in tubulin purifications from native sources. This indicates selectivity of the modification reactions, which can participate in the generation of specific modification patterns (see D). Modification sites might be distinguished by their neighboring amino acid residues, which could create specific modification epitopes. (D) As a result of the large number of modification sites and the variability of side chains, a large variety of modification patterns could be generated within a single C-terminal tail of tubulin. (E) Modification patterns as shown in D can be distinct between α- and β-tubulin. These modification patterns could be differentially distributed at the surface of the microtubule lattice, thus generating a higher-order patterning. Tub, tubulin. For color coding, see Fig. 2.Considering the number of tubulin isotypes plus all potential combinations of PTMs (e.g., each glutamate residue within the C-terminal tubulin tail could be modified by either polyglutamylation or polyglycylation, each of them generating side chains of different lengths; Fig. 4), the number of distinct signals generated by the potential tubulin code would be huge. However, as many of these potential signals represent chemical structures that are similar and might not be reliably distinguished by readout mechanisms, it is possible that the tubulin code generates probabilistic signals. In this scenario, biochemically similar modifications would have similar functional readouts, and marginal differences between those signals would only bias biological processes but not determine them. This stands in contrast to the concept of the histone code, in which precise patterns of different PTMs on the histone proteins encode distinct biological signals.The concept of probabilistic signaling is already inscribed in the machinery that generates the tubulin code. Polyglutamylases and polyglycylases from the TTLL family have preferential activities for either α- or β-tubulin and for generating different lengths of the branched glutamate or glycine chains. Although under conditions of low enzyme concentrations, as found in most cells and tissues, the enzymes seem to selectively generate their preferential type of PTM, higher enzyme concentrations induce a more promiscuous behavior, leading, for instance, to a loss of selectivity for α- or β-tubulin (van Dijk et al., 2007). Similarly, the modifying enzymes might prefer certain modification sites within the C-terminal tails of tubulin but might be equally able to modify other sites, which could be locally regulated in cells. For example, β-tubulin isotypes isolated from mammalian brain were initially found to be glutamylated on single residues (Alexander et al., 1991; Rüdiger et al., 1992), which in the light of the comparably low sensitivity of mass spectrometry at the time might rather indicate a preferential than a unique modification of these sites. Nevertheless, the neuron-specific polyglutamylase for β-tubulin TTLL7 (Ikegami et al., 2006) can incorporate glutamate onto many more modification sites of β-tubulin in vitro (Mukai et al., 2009), which clearly indicates that not all of the possible modification events take place under physiological conditions.Several examples supporting a probabilistic signaling mode of the tubulin code are found in the recent literature. In T. thermophila, a ciliate without tubulin isotype diversity (Gaertig et al., 1993) but with a huge repertoire of tubulin PTMs and tubulin-modifying enzymes (Janke et al., 2005), tubulin can be easily mutagenized to experimentally eliminate sites for PTMs. Mutagenesis of the most commonly occupied glutamylation/glycylation sites within the β-tubulin tails did not generate a clear decrease of glycylation levels nor did it cause obvious phenotypic alterations. This indicates that the modifying enzymes can deviate toward alternative modification sites and that similar PTMs on different sites can compensate the functions of the mutated site. However, when all of the key modification sites were mutated, glycylation became prominently decreased, which led to severe phenotypes, including lethality (Xia et al., 2000). Most strikingly, these phenotypes could be recovered by replacing the C-terminal tail of α-tubulin with the nonmutated β-tubulin tail. This α–β-tubulin chimera became overglycylated and functionally compensated for the absence of modification sites on β-tubulin. The conclusion of this study is that PTM- and isotype-generated signals can fulfill a biological function within a certain range of tolerance.But how efficient is such compensation? The answer can be found in a variety of already described deletion mutants for tubulin-modifying enzymes in different model organisms. Most single-gene knockouts for TTLL genes (glutamylases or glycylases) did not result in prominent phenotypic alterations in mice, even for enzymes that are ubiquitously expressed. Only some highly specialized microtubule structures show functional aberrations upon the deletion of a single enzyme. These “tips of the iceberg” are usually the motile cilia and sperm flagella, which carry very high levels of polyglutamylation and polyglycylation (Bré et al., 1996; Kann et al., 1998; Rogowski et al., 2009). It thus appears that some microtubules are essentially dependent on the generation of specific PTM patterns, whereas others can tolerate changes and appear to function normally. How “normal” these functions are remains to be investigated in future studies. It is possible that defects are subtle and thus overlooked but could become functionally important under specific conditions.A tubulin code also requires readout mechanisms. The most likely “readers” of the tubulin code are MAPs and molecular motors. Considering the probabilistic signaling hypothesis, the expected effects of the signals would be in most cases rather gradual changes, for instance, to fine-tune molecular motor traffic and/or to bias motors toward defined microtubule tracks but not to obliterate motor activity or MAP binding to microtubules. An in vitro study using recombinant tubulin chimeras purified from yeast confirmed this notion (Sirajuddin et al., 2014). By analyzing which elements of the tubulin code can regulate the velocity and processivity of the molecular motors kinesin and dynein, these researchers found that the C-terminal tails of α- and β-tubulin differentially influence the kinetic parameters of the tested motors; however, the modulation was rather modest. One of their striking observations was that a single lysine residue, present in the C-terminal tails of two β-tubulin isotypes (Figs. 2 and ​and4),4), significantly affected motor traffic and that this effect can be counterbalanced by polyglutamylation. These observations are the first in vitro evidence for the interdependence of different elements of the tubulin code and provide another indication for its probabilistic mode of signaling.

Future directions.

One of the greatest technological challenges to understanding the function of the tubulin code is to detect and interpret subtle and complex regulatory events generated by this code. It will thus be instrumental to further develop tools to better distinguish graded changes in PTM levels on microtubules in cells and tissues (Magiera and Janke, 2013) and to reliably measure subtle modulations of microtubule behavior in reconstituted systems.The current advances in the field and especially the availability of whole-organism models, as well as first insights into the pathological role of tubulin mutations (Tischfield et al., 2011), are about to transform our way of thinking about the regulation of microtubule cytoskeleton. Tubulin heterogeneity generates complex probabilistic signals that cannot be clearly attributed to single biological functions in most cases and that are not essential for most cellular processes. Nevertheless, it has been conserved throughout evolution of eukaryotes and can hardly be dismissed as not important. To understand the functional implications of these processes, we might be forced to reconsider how we define biologically important events and how we measure events that might encode probabilistic signals. The answers to these questions could provide novel insights into how complex systems, such as cells and organisms, are sustained throughout difficult and challenging life cycles, resist to environmental stress and diseases, and have the flexibility needed to succeed in evolution.     

Inflammatory Responses with Left Ventricular Compromise after Induction of Myocardial Infarcts in Sheep (Ovis aries)

Ischemic myocardial disease is a major cause of death among humans worldwide; it results in scarring and pallor of the myocardium and triggers an inflammatory response that contributes to impaired left ventricular function. This response includes and is evidenced by the production of several inflammatory cytokines including TNFα, IL1β, IL4, IFNγ, IL10 and IL6. In the current study, myocardial infarcts were induced in 6 mo old male castrated sheep by ligation of the left circumflex obtuse marginal arteries (OM 1 and 2). MRI was used to measure parameters of left ventricular function that include EDV, ESV, EF, SVI, dp/dt max and dp/dt min at baseline and at 4 wk and 3 mo after infarct induction. We also measured serum concentrations of an array of cytokines. Postmortem histologic findings corroborate the existence of left ventricular myocardial injury and deterioration. Our data show a correlation between serum cytokine concentrations and the development of myocardial damage and left ventricular functional compromise.

Heart failure is a globally significant problem in both humans and lower animals.^3,18 The medical literature is replete with predisposing causes of heart disease,¹³ yet the prevalence of heart failure remained high.^4,5,16 Regardless of the cause of myocardial damage and subsequent left ventricular compromise, the literature indicated that the proinflammatory response that occurs after myocardial infarction is an important contributor to the deterioration of the myocardium^{1,9,12,14,17,18,20,21} Sheep and pigs are excellent translational models of human cardiology because their hearts bear many physiologic and anatomic similarities to the human heart.^4,8,15 The primary use of these models in cardiology is primarily to study myocardial infarction^5,13,16 and to a lesser extent, physiologic processes that develop after myocardial insult.Our study measured some of the major proinflammatory cytokines that contribute to myocardial damage. Most of these cytokines, including: TNFα, IL6, and IFNγ, are important correlates of myocardial ischemia that contribute to a decline in left ventricular myocardial function.^1,9,14 In our study, we detected left ventricular compromise as early as 4 wk after the infarction, while the proinflammatory response was recorded at 48 h after the infarct and peaked at 4 wk. Cardiac functional parameters began to decline early in the study consistent with the proinflammatory response. The cardiac functional parameters continued to decline until 3 mo, which was the termination of the study. These findings may support antiinflammatory intervention as an important adjunct of any therapeutic regimen.     

Structure versus function: Are new conformations of pannexin 1 yet to be resolved?

Pannexin 1 (Panx1) plays a decisive role in multiple physiological and pathological settings, including oxygen delivery to tissues, mucociliary clearance in airways, sepsis, neuropathic pain, and epilepsy. It is widely accepted that Panx1 exerts its role in the context of purinergic signaling by providing a transmembrane pathway for ATP. However, under certain conditions, Panx1 can also act as a highly selective membrane channel for chloride ions without ATP permeability. A recent flurry of publications has provided structural information about the Panx1 channel. However, while these structures are consistent with a chloride selective channel, none show a conformation with strong support for the ATP release function of Panx1. In this Viewpoint, we critically assess the existing evidence for the function and structure of the Panx1 channel and conclude that the structure corresponding to the ATP permeation pathway is yet to be determined. We also list a set of additional topics needing attention and propose ways to attain the large-pore, ATP-permeable conformation of the Panx1 channel.

IntroductionInitially, the pannexin field got off to an inauspicious start. Because the three proteins of the pannexin family (Panx1, Panx2, and Panx3) were discovered on the basis of their limited sequence homology to the invertebrate innexin gap junction proteins, it was assumed that they, too, would form gap junctions (Panchin et al., 2000; Bruzzone et al., 2003). However, notwithstanding some disputed science, it soon became clear that the gap junction function of pannexins is not realized (Dahl and Locovei, 2006; Huang et al., 2007; Sosinsky et al., 2011). Gap junction formation by pannexins is moreover prevented by glycosylation of the Panx1 protein (Boassa et al., 2007; Penuela et al., 2007; Boassa et al., 2008). It is conceivable, however, that the nonglycosylated form of Panx1 could allow the docking of oligomers in apposing membranes to each other. Indeed, such docking was observed in cryo-EM preparations of a mutant Panx1, N255A (Ruan et al., 2020). However, because glycosylation of the protein is required for membrane trafficking (Boassa et al., 2007; Penuela et al., 2007), it is unlikely that this process occurs in vivo. This notion is supported by the observation that a glycosylation mutant of Panx1 failed to lead to junctional conductance between paired oocytes, while expression of wtPanx1 followed by glycosidase F treatment before pairing of the cells resulted in gap junction formation, albeit at a much reduced rate as compared with the rate observed with connexins (Boassa et al., 2008). Furthermore, the gap junction function also is unlikely because of theoretical reasons and experimental findings, including expression in single cells, such as erythrocytes (Locovei et al., 2006a), and exclusive expression in the apical membrane of polarized epithelial cells (Ransford et al., 2009; Hanner et al., 2012; Shum et al., 2019). Of the three pannexins, only Panx1 has been studied in detail, and a clear channel function is well established for it. Therefore, this Viewpoint will exclusively deal with Panx1.It is generally assumed that an important function of Panx1 is to form ATP release channels. For example, as of this writing, a PubMed search with “pannexin” and “ATP release” as search terms yielded 287 publications. However, the biophysical evidence for this function is sparse, and the supporting evidence is largely correlative and/or based on pharmacological or genetic interference with ATP release. The ATP release function of Panx1 channels has been contested based on evidence that the channels are highly selective for Cl⁻ and the lack of detectable ATP release under the experimental conditions, i.e., activation by voltage, used in these studies (Ma et al., 2012; Romanov et al., 2012).It was long held that the oligomeric state of the Panx1 channel is that of a hexamer (Penuela et al., 2013; Dahl, 2015; Chiu et al., 2018). Recently, in a <6-mo period, six research groups independently published similar cryo-EM structures of the Panx1 membrane channel (Deng et al., 2020; Jin et al., 2020; Michalski et al., 2020; Mou et al., 2020; Qu et al., 2020; Ruan et al., 2020). All these papers challenge the view of the oligomeric state of the channel. Instead of the hexameric arrangement of identical Panx1 subunits, the channel appears to be formed by a homomeric heptamer.It is uncontested that the Panx1 channel can operate in a conformation in which the channel exhibits a unitary conductance of <100 pS. However, it has also been reported that, under certain experimental conditions, the channel can exhibit several subconductances with very rare sojourns to a maximal conductance of ∼500 pS (Dahl 2015).Activation of the Panx1 channel can be obtained by various stimuli, some physiological or pathological, others in the form of experimental tools. The majority of the physiological stimuli involve ligands, including ATP, glutamate, α adrenergic agonists, and bradykinin, binding to their cognitive receptors and leading to opening of Panx1 channels and “secondary” ATP release (Dahl 2015, 2018). A nonreversible activation of the channel is induced by cleavage with caspase 3 or 8 (Chekeni et al., 2010), leading to cell death. Experimental stimulation can be obtained in some cells but not in others by increasing the extracellular K⁺ concentration (Silverman et al., 2009; Wang and Dahl 2018; Chiu et al., 2018).Here, we present a point of view on these contested issues in the Panx1 field and attempt to reconcile apparently contradictory data or their interpretations. In addition, we ask to what extent the new structural data support the functional data.The structure of Panx1 channels as revealed by cryo-EMThe excitement for the long-awaited Panx1 structure was rewarded with not one but six publications, all appearing within the first half of 2020 and using cryo-EM to image the channel (Deng et al., 2020; Jin et al., 2020; Michalski et al., 2020; Mou et al., 2020; Qu et al., 2020; Ruan et al., 2020). Five of the six Panx1 publications showed human Panx1 structures (Deng et al., 2020; Jin et al., 2020; Michalski et al., 2020; Mou et al., 2020; Qu et al., 2020; Ruan et al., 2020), and two showed frog Panx1 structures (Deng et al., 2020; Michalski et al., 2020). To stabilize the frog Panx1 structure, thus improving the resolution for cryo-EM, Michalski et al. (2020) truncated the C terminus by 71 amino acids and removed 24 amino acids from the intracellular loop between transmembrane (TM) helices 2 and 3; this truncation was the version reported. The other publications reported full-length Panx1 structures, although one used a truncated Panx1 variant (Ruan et al., 2020) and another used a mutation (Jin et al., 2020) as their principal references. Because the C terminus–truncated structure and the (combined) WT structure had the highest overall quality of the several Panx1 structures presented by Ruan et al. (2020), it was used for de novo model building, as the reference structure for analyses, and for discussion. For the same reason, Jin et al. (2020) used the double mutation D376E/D379E, which eliminated the caspase-cleavage site, for their de novo model building. The overall architecture and dimensions of the human and frog Panx1 structures were similar, and the extracellular domains (ECDs) and transmembrane domains (TMDs) were nearly identical, except that the N-terminal helix (NTH) of the frog Panx1 is positioned on the intracellular side and not within the TMD as reported in human Panx1. These structures are becoming an important and critical tool to guide functional experiments and open a new venue to perform molecular dynamics simulations.The most novel finding shared by all the Panx1 structures is that instead of the hexamer hitherto believed to represent the native state of the Panx1 channel, the cryo-EM data show unequivocally a homo-heptamer arranged around a central symmetry axis that constitutes the principal permeation pathway. Panx1’s structural envelope adopts an inverted pail shape in the view parallel to the membrane. The heptameric channel is ∼110 Å long and ∼100 Å wide, with a flat ECD protruding ∼35 Å above the cell membrane and an intracellular domain (ICD) extending ∼35 Å into the cytoplasm with the TMD in between (Fig. 1). Both the N and C termini reside on the cytoplasmic side of the channel. Each TMD has four membrane-spanning helices per protomer. The TMD pore is predominantly lined by hydrophobic amino acids. The NTH is short and lines the TMD pore (human Panx1) with the NTH of one subunit interacting with the TMD of the adjacent subunit. Thus, it has been proposed that the NTH helps to maintain a rigid TMD pore (Ruan et al., 2020). Both the extracellular and intracellular pore entrances are lined with positively charged amino acids, making them favorable for negatively charged cargos such as Cl⁻ and ATP to enter and leave the pore.Open in a separate windowFigure 1.Structural model of Panx1. (A) Cartoon representation of Panx1 WT (PDB accession no. 6wbk) stabilized with detergent. The approximate position of the membrane is indicated by the bars. One protomer of the heptameric assembly is indicated in orange. The lipids resolved in the structure are colored in magenta. It is notable that many of the resolved lipids are found at the interface between subunits. CTH, C-terminal helix; CLH, cytoplasmic linker helix. (B) Overlay of different Panx1 cryo-EM–based structures from different groups (PDB accession no. 6lto = gold, WT hPanx1; PDB accession no. 6wbk = blue, hPanx1 ΔC terminus, ΔN terminus; PDB accession no. 6v6d = lilac, WT hPanx1). The structures diverge very little in the ECD and the membrane domain. However, the variation is larger in the ICD. The approximate positions of F54 and I58 are indicated. (C) Comparison of the extracellular pore. Key residues are annotated using their one-letter abbreviation. All structures are shown as backbone traces except W74, which is part of the constriction ring of the pore. The narrowest constriction is indicated by the arrow.A cap structure is formed on the extracellular side from seven ECDs, one from each subunit. The ECDs are organized into the pore’s most constricted site, thus defining the maximum size of permeable molecules and establishing the extracellular entrance to the TMD. Each ECD contains one helix cross-linked through a disulfide bond to a three-stranded antiparallel β-sheet. The N-terminal end of each subunit helix protrudes inward toward the central pore axis contributing to the constriction site. The key residues involved in the gating of Panx1 are part of the W74-R75-D81 inter-subunit triplet (Fig. 1) from the N-terminal ends of the ECD helices and are proposed to provide rigidity to the extracellular entrance containing positive charges (Deng et al., 2020). This ring lining the wall of the constriction defines a hydrated pore diameter of ∼9 Å (Fig. 1) and is the crux of the argument that the extracellular constriction site is the effective selectivity filter discriminating cargoes on the basis of their charge and size. By contrast, the narrowest point of the pore in the TMD has a hydrated diameter of ∼13 Å.Other inter-subunit interactions that stabilize the pore arrangement in the TMD are (1) the F67-Y79 aromatic–aromatic and Q266-T252 hydrogen bonding in the ECD, (2) the TM helix TM1-TM1 and TM2-TM4 interfaces between adjacent subunits, (3) the N-terminal loop from the neighboring subunit extending into the TMD pore lining, and (4) the resolvable residues of C-terminal helix 3 association with the cytoplasmic linker helices 1 and 2 from the adjacent subunit (Fig. 1; Deng et al., 2020; Michalski et al., 2020). In addition, membrane lipids occupy the crevice between TM3 and an adjacent TM4 at the edge of the channel. Lipid head groups associate with positively charged residues from the N-terminal end of TM3 (K214) and the C-terminal domain of TM4 (R302 and K303; Deng et al., 2020). It may be that the lipid environment influences the assembly and possibly the activation of the Panx1 channel.The pore substantially widens toward the intracellular side. The ICDs extend away from the pore axis, producing a voluminous intracellular vestibule. Two helices in the ICD connect to two TMD helices to form a compact assembly that provides rigidity to the vestibule. The vestibule is slightly larger in the frog Panx1 structure, but the pore architecture is essentially the same as in the human version. The C-terminal segment consisting of ∼70 amino acids, including the caspase cleavage site located immediately before the C terminus, was not visualized in any of the published cryo-EM structures, suggesting that it is intrinsically flexible. C-terminal cleavage removes its autoinhibitory effect without inducing an overall conformational change to the pore (Jin et al., 2020).A novel feature presented by Ruan et al. (2020) is seven narrow side tunnels in the upper ICD running perpendicular to and ending at the pore, like a T-intersection. This tunnel network was proposed to allow passage of small anions because each tunnel contains several positively charged and other polar residues along its length. The flexible NTH-TM1 linker would function as a gate. They hypothesized that these side tunnels facilitate Cl⁻ flux when the pore is blocked by the C terminus residing in the ICD vestibule. Movement or cleavage of the C terminus then would induce the ATP-permeable large-pore conformation. Further structural work is needed to determine whether the C terminus actually resides in the ICD vestibule. One complication with this tunnel hypothesis is that each tunnel has two constriction sites formed by R29 and A33, with diameters of 5.8 and 4.0 Å, respectively, meaning that partial dehydration of a Cl⁻ ion is likely required for it to pass through the tunnel. The possibility of anion tunnels in the Panx1 structure raises the question: could there be multiple open (active) conformations, and does “open” mean open to ATP and Cl⁻ ion or Cl⁻ ion only? Three of the six papers (Michalski et al., 2020; Qu et al., 2020) assume that the Panx1 structure is in the closed or inactive conformation, whereas the other three report an open or active conformation. These discrepancies should be resolved with further work. Interestingly, the overlay of three of these structures, one presumably open and two closed, shows nearly identical conformations of the extracellular constriction of the pore (Fig. 1 C).The structures of Panx1 truncation and mutant variants, as well as its docked inhibitor, carbenoxolone (CBX), illuminate the roles of distinct structural elements. For example, cryo-EM revealed that CBX sits atop the ECD and plugs the W74-R75-D81 ring (Jin et al., 2020; Ruan et al., 2020), supporting pore blocking as its mechanism of Panx1 inhibition. Second, removal of the NTH did not much change the shape of the TMD. This truncation still generated a CBX-sensitive, voltage-dependent current similar to the full-length Panx1 current (Ruan et al., 2020), suggesting that the NTH may play a role in the assembly of the heptamer from the Panx1 protomers rather than being an essential element in the pore conduction pathway. Third, the Panx1 structures obtained in the presence of Ca²⁺ and K⁺ were indistinguishable from the untreated Panx1 structure, suggesting that neither Ca²⁺ nor K⁺ is likely to directly activate the Panx1 channel (Ruan et al., 2020). Fourth, the glycosylation-deficient mutant (N255A) generated gap junction structures as well as hemichannels as determined by cryo-EM (Ruan et al., 2020). The N255A gap junction is formed by two hemichannels docked by the interaction of the extracellular linker 2 on apposing ECDs. Ruan et al. (2020) noted that this Panx1 gap junction likely is not a normal physiological conformation.Comparing the Panx1 structure with other ATP-permeant pore structures offers a blueprint for dissecting pore properties of Panx1. The oligomeric configuration of the ATP-permeant channels does not appear to correlate with pore diameter, in particular when comparing the narrowest extent of the pore (Table 1). Like Panx1, CALHM1 was originally thought to adopt a hexameric configuration (Siebert et al., 2013) until the cryo-EM structure revealed an octameric configuration (Syrjanen et al., 2020). It should be noted that not all connexin channels transport ATP. For example, Cx26, Cx30, Cx43, and Cx46 transport ATP, but Cx32 does not (Harris, 2001; Hansen et al., 2014). An interesting comparison can be made between Panx1 and human Cx31.3. Cx31.3 has a pore with a constriction site diameter of ∼8 Å, similar to Panx1’s constriction of ∼9 Å, and also selectively transports Cl⁻ and ATP (Lee et al., 2020). One difference between the two structures is that the constriction is in the ICD’s NTH for Cx31.3 and in the ECD for Panx1. Lee et al. (2020) pointed out that because Cx31.3’s pore constriction at the cytoplasmic entrance is smaller than the effective hydrated diameter of ATP (∼12 Å; Sabirov and Okada, 2004), the reported conformation would not allow ATP to pass through the pore without substantial conformational changes of the NTH. The same argument could be applied to Panx1’s ECD.Table 1.Comparison of oligomeric configuration with pore constriction diameter