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Regulation of autophagy in neurons remains unclear. In this issue, Kulkarni et al. (2021. J. Cell Biol. https://doi.org/10.1083/jcb.202002084) show with elegant live imaging that in dendrites, but not in axons, autophagosome motility and function is regulated by synaptic activity.

Macroautophagy is a type of autophagy that refers to the capacity to form double membrane compartments called autophagosomes that engulf large protein aggregates and defective organelles. Autophagosomes fuse with lysosomes, forming degradative autolysosomes (1). Autophagosome formation depends on the conjugation of LC3-I (cytosolic) to phosphatidylethanolamine, generating LC3-II, which remains bound to autolysosomes (1). In neurons, inactivation of autophagy genes impacts neurodevelopment, axon growth and guidance, synapse formation and pruning, ultimately leading to neurodegeneration. Particularly, in motor neurons and cerebellum Purkinje cells, autophagy gene knockout leads to the accumulation of intracellular protein aggregates and degeneration, impacting movement coordination (1). Interestingly, stimulation of memory up-regulates autophagy, and while reducing autophagy reduces memory, activating it has the opposite effect on memory (2). What triggers macroautophagy in neurons remains unclear. In this issue, Kulkarni et al. test whether synaptic activity regulates autophagy and detail the impact of synaptic activity on autophagosome motility (3).Kulkarni et al. used multiple strategies to manipulate synaptic activity. They stimulated synaptic activity by depolarizing neurons with high potassium, treating them with a cocktail of antagonists of voltage-gated potassium channels and inhibitory gamma-aminobutyric A receptors, and using uncaging of the excitatory neurotransmitter glutamate. To inhibit synaptic activity, the researchers treated neurons with antagonists of excitatory α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid and N-methyl-D-aspartate receptors (4). To image autophagosomes and autolysosomes (here globally termed autophagic vacuoles [AVs]) in live neurons, the authors expressed LC3 tagged with fluorescent proteins. They elegantly imaged the same neuronal compartment before and after depolarization, or under basal, increased, or reduced synaptic activity, and used kymograph analysis (via Kymoanalyser; 5) to quantify the mean speeds of AVs in both dendrites and axons. An increase in intracellular calcium measured with a genetically encoded calcium sensor, GCAMP3, indicated synaptic activity. Kulkarni et al. observed that, in dendrites, AVs stop with synaptic activity and move with synaptic inhibition (Fig. 1). This AV movement change was swift and unaltered by co-culture with astrocytes, and reversible. One key finding is that this change in AV movement occurred in dendrites, but not in axons. Interestingly, AVs stopped at or near synapses, which were identified with PSD-95-GFP.Open in a separate windowFigure 1.In dendrites, AVs stop at synapses upon synaptic activity.The authors further characterized the AVs in terms of acidity (lysotracker labelling of acidic organelles) and of degradative capacity (DQ-BSA fluorescence accumulation upon lysosomal degradation). Lysotracker motility changed similarly with synaptic activity. Interestingly, the lysotracker density increased with synaptic stimulation. The higher number of acidic organelles (likely autolysosomes) indicated increased autophagy or acidification with synaptic activity, which could underlie increased degradative activity. Indeed, about half of the LC3-positive AVs were degradative in dendrites, while in axons there was virtually no degradative AV, supporting the requirement for transport to the soma for degradation of autophagic cargo (6). Finally, Kulkarni et al. show that degradative AVs increase with synaptic activity, correlating with the reduced motility of LC3-positive AVs.An intriguing observation is that the autophagic vacuoles identified by LC3-mCherry were virtually all positive for LAMP1, a marker of late endosomes and lysosomes, indicating that dendrites mainly contain autolysosomes and no or very few autophagosomes (LC3-positive and LAMP1-negative) and late endosomes/lysosomes (LC3-negative and LAMP1-positive). One is left wondering if it results from LC3 overexpression and overflooding to interconnected organelles. An alternative possibility is that LC3 may not always label autophagosomes, in which case complementary electron microscopy is necessary for confirmation. Where are dendritic autolysosomes formed? In axons, a fraction of the LC3 autophagic vacuoles was LAMP1 negative, and the formation of autophagosomes at axon terminals has been well documented (7). Thus, do autophagosomes form in axons, fuse with LAMP1-positive late endosomes/lysosomes, and only after are they transported to dendrites? Alternatively, autophagosomes may form in dendrites and fuse with late endosomes/lysosomes, preventing their detection unless fusion is inhibited (8).Another interesting observation concerns the similar change in the motility of early endosomes, identified by Rab5, an early endosome GTPase, with synaptic activity. Other organelles, post-ER vesicles (4), and proteasomes (9) similarly display a change in motility in dendrites upon synaptic activity. In contrast, mitochondria stop moving in axons with synaptic activity (10). The significance of this arrest of several dendritic organelles with synaptic activity is an attractive area for research.Neuronal autophagy dysfunction is implicated in many neurodegenerative diseases (1). At least early in the disease, increasing autophagy improves neuronal function and synapse activity (1). Genetic risk factors include lysosomal proteins, whose defective function leads to the accumulation of nondegraded autophagic vacuoles and recapitulate neurodegenerative phenotypes (11). Lysosomal dysfunction is a mechanism of cellular aging. Moreover, synapses become dysfunctional with aging and lost in neurodegenerative diseases (12). Based on this study, synapse dysfunction and thus reduced synaptic activity could increase AV motility and reduce acidification and the degradative capacity of autolysosomes. Similarly, neuronal overexcitability, as in early Alzheimer''s disease patients with seizures, could cause excessive AV motility and degradative activity.What is the mechanism that stops AV movement? Do early endosomes, secretory vesicles, or proteasomes change motility using similar mechanisms? For post-ER vesicles, the CAMKII dependent phosphorylation of the microtubule motor Kif17 was sufficient to arrest movement (4). Alternatively, could it be the actin cytoskeleton that forms patches in the dendritic shaft at the base of postsynaptic glutamatergic synapses to halt microtubule-dependent transport of organelles (13)? More work is needed to tackle these questions and define the cell biological mechanisms by which synaptic activity controls AV function and dynamics in different neuronal compartments. Understanding the mechanisms underlying the regulation of autophagy and autophagosome maturation and degradation provides an exciting opportunity for therapeutic development in neurodegenerative diseases.  相似文献   

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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 time19,82,83 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 humans40,55 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 h41,63,62,77 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 humans3,5 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 humans3,17,33 and animals16,27,36,42,47,84,85 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 treatment61,73 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.  相似文献   

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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.140,205,216,274,575,782This 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”.  相似文献   

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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 myocardium1,9,12,14,17,18,20,21 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 infarction5,13,16 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.  相似文献   

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Systemic buprenorphine and topical antiseptics such as chlorhexidine are frequently used in research animals to aid in pain control and to reduce infection, respectively. These therapeutics are controversial, especially when used in wound healing studies, due to conflicting data suggesting that they delay wound healing. Low-level laser therapy (LLLT) has been used to aid in wound healing without exerting the systemic effects of therapies such as buprenorphine. We conducted 2 studies to investigate the effects of these common treatment modalities on the rate of wound healing in mice. The first study used models of punch biopsy and dermal abrasion to assess whether buprenorphine HCl or 0.12% chlorhexidine delayed wound healing. The second study investigated the effects of sustained-released buprenorphine, 0.05% chlorhexidine, and LLLT on excisional wound healing. The rate of wound healing was assessed by obtaining photographs on days 0, 2, 4, 7, and 9 for the punch biopsy model in study 1, days 0, 1, 2, 4, 6, 8, 11, and 13 for the dermal abrasion model in study 1, and days 0, 3, 6, and 10 for the mice in study 2. Image J software was used to analyze the photographed wounds to determine the wound area. When comparing the wound area on the above days to the original wound area, no significant differences in healing were observed for any of the treatment groups at any time period for either study. Given the results of these studies, we believe that systemic buprenorphine, topical chlorhexidine, and LLLT can be used without impairing or delaying wound healing in mice.

A recent retrospective analysis using a medical insurance dataset estimated that approximately 8.2 million people experienced wounds ranging from acute to chronic conditions within the particular year analyzed, and estimated that the cost of acute and chronic wound treatments ranged from $28.1 to $96.8 billion dollars.52 The projected rise in the number of people experiencing wounds and the cost of wound care products52 have made wound healing a growing area of interest in both clinical medicine and research. Wound healing is a complex process that involves many overlapping, intricate physiologic processes. Each step can have associated deviations that may lead to enhanced, altered, impaired, or delayed healing. Animal research has been used to develop a better understanding of the basic, physiologic mechanisms of wound healing. Mice are the most commonly used animal in biomedical research, and they are used to model a host of conditions, including wound healing. Despite known anatomic and physiologic differences between murine and human skin,17,53 this species is commonly used due to their small size, ease of handling, and relatively low cost. In addition, the overlapping phases of the wound healing process are similar in mice and humans, making mice a valuable model.65Pain is inherent to the development of wound models. Pain receptors in the skin are sensitized during the actual wounding process and during the inflammatory response that occurs immediately after wounding.19 Pain can also occur during the cleansing and treatment of wounds.19 Just as managing wound pain is critical in human patients, The Guide for the Care and Use of Laboratory Animals (the Guide)30 and other federal guidelines and regulations governing the care and use of laboratory animals strongly encourages the use of analgesics for animals that experience pain and/or distress.30 Pain, which can also cause stress, may evoke a persistent catabolic state and may ultimately delay wound healing.19,28,31,43 Therefore, adequate pain control is necessary to avoid negatively affecting or altering the wound healing process.As in human medicine, opioids are commonly used to provide analgesia to research rodents. Buprenorphine, a mixed agonist-antagonist opioid,26,54 is a common analgesic that acts as a very weak partial agonist of the mu opioid receptor and an antagonist of the κ opioid receptor.26 Buprenorphine is frequently used in animals as both a pre- and post-operative analgesic. It works by binding to the opioid receptors in the skin and other tissues. This ligand-receptor binding regulates the physiologic responses of nociception and inflammation,7 which are key factors in the process of healing and regeneration. Buprenorphine is often used instead of full mu-opioid receptor agonist drugs, such as morphine or hydromorphone, because it has fewer systemic side effects.28 Despite their common use as analgesics, reports are mixed in terms of whether opioids, as a class, delay or impair wound healing.11,28,35,40In addition to controlling pain, minimizing wound contamination and preventing infection is critical to wound healing. The use of antiseptics is often favored over the use of antibiotics as the former presents less chance for developing antibiotic resistance.6 As an antiseptic, chlorhexidine is commonly used to irrigate, cleanse, and treat cutaneous wounds. Chlorhexidine has high antimicrobial activity against gram-positive and gram-negative bacteria and some fungi and viruses.4 Although considered to be relatively safe, reports are conflicting with regard to whether chlorhexidine delays or impairs wound healing.4,9,50,57Laser techniques have been used medically for many years, and their powerful, but precise capabilities have rendered them a unique surgical and therapeutic modality. In brief, when the electrons of atoms move to higher energy levels, these electrons absorb energy. This excited energy state is unstable and temporary. The natural return of electrons to their more stable ground state releases energy in the form of photons or light. Light Amplification by Stimulated Emission of Radiation (LASERS) are characterized by the photon stimulation of an already excited electron. This stimulation causes the emitted light to be amplified, as demonstrated by the intense, bright light that is emitted from lasers.63 The concept of low-level laser therapy (LLLT) has garnered interest as a therapeutic modality in both human and veterinary medicine. Specifically characterized as laser therapy using a low power output and a low power range, LLLT is distinguished from other forms of laser therapies by certain parameters such as wavelength, pulse rate and duration, total irradiation time, and dose.44 Although the mechanism of action for LLLT is not completely understood,46,64 the absorption of red and near infrared light energy may reduce detrimental, inflammatory substances13,15,24,56 while simultaneously stimulating restorative processes.15,24,46,64 The reduced photothermal impact of LLLT44 is reported to produce beneficial physiologic and biologic effects including analgesia, reduction in inflammation, and acceleration of healing.48 The initial report of LLLT as a therapeutic modality found accelerated wound healing and fur regrowth in mice exposed to LLLT.13,44,46,64 LLLT has since been used as a sole or adjunct therapy for a variety of conditions including tooth root resorption,55 traumatic brain injuries,58 and tendon, muscle, and bone injuries.2,3,25,38Studies conducted to assess the effects of LLLT on healing often use parameters of normal wound healing to analyze how LLLT influences those parameters in comparison to healthy, undamaged tissue and damaged tissue not receiving laser therapy. Despite the numerous studies designed to investigate the effects of LLLT on wound healing, conflicting reports exist regarding its efficacy.15,17,46,22,23,24,29,34,38,39,55,56,60,64 A recent study in dogs reported accelerated healing and improved cosmetic appearance of a hemilaminectomy surgical site after LLLT,60 while other canine studies reported no significant differences in the healing of surgically induced skin wounds between dogs that did and did not receive LLLT.22,34 Similarly, in an attempt to study the effects of LLLT in pigs, an animal with skin very similar to that of humans, no significant differences were reported in the healing of surgically created skin wounds between swine that did and did not receive LLLT.29 Studies using diabetic rats with excisional cutaneous wounds reported accelerated wound healing,17,46 and beneficial results were reported in a similar study using diabetic mice.56,64 While fewer studies have been conducted on the use of LLLT in rodents without concomitant comorbidities, LLLT has been reported to accelerate wound healing in healthy rodents.15,24 Conversely, some studies found that LLLT does not accelerate or significantly improve wound healing in rodents.24,39We performed 2 separate studies to investigate the effects of a commonly used opioid, a topical antiseptic solution, and LLLT on excisional wound healing in mice. At the time the initial study (study 1) was conducted, some of our investigators were reluctant to use the recommended analgesic, buprenorphine, due to concern about interference with their study outcomes. Therefore, we conducted study 1 to determine if a single dose of peri-operative buprenorphine would delay healing of a full-thickness excisional wound or a partial-thickness felt wheel dermal abrasion. We also examined the effects of topical chlorhexidine solution on wound healing. The chlorhexidine concentrations used in study 1 were prepared using our standard operating procedure at that time. Study 2 was conducted after study 1, with the design expanded to evaluate a sustained release buprenorphine formulation and LLLT. Study 2 used a full-thickness excisional biopsy to determine the effect of LLLT on excisional wound healing. Commonly used doses of systemic Buprenorphine Sustained Release (SR) and topical chlorhexidine were also included to evaluate their effect on excisional wound healing. The concentration of chlorhexidine in the revised, approved standard operating procedure had been decreased due to literature suggesting that higher concentrations may inhibit healing.4,49,61 For both studies, we hypothesized that the use of buprenorphine and chlorhexidine would have no effect on the rate of wound healing, and that LLLT would accelerate wound healing in a full-thickness excision as compared with a control.  相似文献   

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The gray mouse lemur (Microcebus murinus, GML) is a nocturnal, arboreal, prosimian primate that is native to Madagascar. Captive breeding colonies of GMLs have been established primarily for noninvasive studies on questions related to circadian rhythms and metabolism. GMLs are increasingly considered to be a strong translational model for neurocognitive aging due to overlapping histopathologic features shared with aged humans. However, little information is available describing the clinical presentations, naturally occurring diseases, and histopathology of aged GMLs. In our colony, a 9 y-old, male, GML was euthanized after sudden onset of weakness, lethargy, and tibial fracture. Evaluation of this animal revealed widespread fibrous osteodystrophy (FOD) of the mandible, maxilla, cranium, appendicular, and vertebral bones. FOD and systemic metastatic mineralization were attributed to underlying chronic renal disease. Findings in this GML prompted periodic colony-wide serum biochemical screenings for azotemia and electrolyte abnormalities. Subsequently, 3 additional GMLs (2 females and 1 male) were euthanized due to varying clinical and serum biochemical presentations. Common to all 4 animals were FOD, chronic renal disease, uterine adenocarcinoma (females only), cataracts, and osteoarthritis. This case study highlights the concurrent clinical and histopathologic abnormalities that are relevant to use of GMLs in the expanding field of aging research.

Within the past 5 y, recognition of the translational utility of the gray mouse lemur (Microcebus murinus, GML) has greatly expanded, in part due to the sequencing of its genome.27 GMLs have been proposed as an animal model in the context of aging research,14,35 most notably within the fields of Alzheimer disease and dementia33,39 and circadian rhythms.15,20 GMLs are nocturnal, arboreal, prosimian primates (family Cheirogaleidae) that are endemic to Madagascar. They are among the smallest primates, with a body weight of 49 to 80 g in the wild37 (60 to 110 g in captivity) and have a life expectancy of approximately 8 to 10 y in captivity.14 A small number of captive breeding colonies have been established throughout Europe and the United States, many of which have arisen from a closed captive breeding colony at the Muséum National d''Histoire Naturelle (MNHN) in Brunoy, France.Despite an ever-growing interest in the GML as a model organism, clinical and pathologic case reports focusing on naturally occurring disease are rare for this species.1,4,10,16,17,20,28,31,34,38 Reports of spontaneous disease often focus on neoplasia28,31,34 or on ocular abnormalities, which are accessible without invasive interventions.1,4,12 Apart from age-related neurodegenerative disease and cognitive impairment,5,23,25,26,32,36 little is known about the natural disease predilection and histologic aging phenotypes of GMLs.In June 2017, a 9 y-old male GML was euthanized after the sudden onset of weakness, lethargy, and tibial fracture. Necropsy and histopathology revealed chronic renal disease, widespread fibrous osteodystrophy (FOD), and systemic metastatic mineralization. These findings prompted colony-wide serum biochemical screenings for potential underlying renal disease and subsequent metabolic bone disease within the population.Herein, we report the clinical, gross, and histologic multisystemic pathology of 4 aged GMLs. This is the first documentation of FOD secondary to chronic renal disease in GMLs in a captive research colony. In addition, we corroborate previous reports31,34 of uterine adenocarcinoma in aged female GMLs. Together, these findings aid in providing appropriate clinical care to GMLs as their use in the field of aging research continues to expand.  相似文献   

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PSI is an essential component of the photosynthetic apparatus of oxygenic photosynthesis. While most of its subunits are conserved, recent data have shown that the arrangement of the light-harvesting complexes I (LHCIs) differs substantially in different organisms. Here we studied the PSI-LHCI supercomplex of Botryococccus braunii, a colonial green alga with potential for lipid and sugar production, using functional analysis and single-particle electron microscopy of the isolated PSI-LHCI supercomplexes complemented by time-resolved fluorescence spectroscopy in vivo. We established that the largest purified PSI-LHCI supercomplex contains 10 LHCIs (∼240 chlorophylls). However, electron microscopy showed heterogeneity in the particles and a total of 13 unique binding sites for the LHCIs around the PSI core. Time-resolved fluorescence spectroscopy indicated that the PSI antenna size in vivo is even larger than that of the purified complex. Based on the comparison of the known PSI structures, we propose that PSI in B. braunii can bind LHCIs at all known positions surrounding the core. This organization maximizes the antenna size while maintaining fast excitation energy transfer, and thus high trapping efficiency, within the complex.

The multisubunit-pigment-protein complex PSI is an essential component of the electron transport chain in oxygenic photosynthetic organisms. It utilizes solar energy in the form of visible light to transfer electrons from plastocyanin to ferredoxin.PSI consists of a core complex composed of 12 to 14 proteins, which contains the reaction center (RC) and ∼100 chlorophylls (Chls), and a peripheral antenna system, which enlarges the absorption cross section of the core and differs in different organisms (Mazor et al., 2017; Iwai et al., 2018; Pi et al., 2018; Suga et al., 2019; for reviews, see Croce and van Amerongen, 2020; Suga and Shen, 2020). For the antenna system, cyanobacteria use water-soluble phycobilisomes; green algae, mosses, and plants use membrane-embedded light-harvesting complexes (LHCs); and red algae contain both phycobilisomes and LHCs (Busch and Hippler, 2011). In the core complex, PsaA and PsaB, the subunits that bind the RC Chls, are highly conserved, while the small subunits PsaK, PsaL, PsaM, PsaN, and PsaF have undergone substantial changes in their amino acid sequences during the evolution from cyanobacteria to vascular plants (Grotjohann and Fromme, 2013). The appearance of the core subunits PsaH and PsaG and the change of the PSI supramolecular organization from trimer/tetramer to monomer are associated with the evolution of LHCs in green algae and land plants (Busch and Hippler, 2011; Watanabe et al., 2014).A characteristic of the PSI complexes conserved through evolution is the presence of “red” forms, i.e. Chls that are lower in energy than the RC (Croce and van Amerongen, 2013). These forms extend the spectral range of PSI beyond that of PSII and contribute significantly to light harvesting in a dense canopy or algae mat, which is enriched in far-red light (Rivadossi et al., 1999). The red forms slow down the energy migration to the RC by introducing uphill transfer steps, but they have little effect on the PSI quantum efficiency, which remains ∼1 (Gobets et al., 2001; Jennings et al., 2003; Engelmann et al., 2006; Wientjes et al., 2011). In addition to their role in light-harvesting, the red forms were suggested to be important for photoprotection (Carbonera et al., 2005).Two types of LHCs can act as PSI antennae in green algae, mosses, and plants: (1) PSI-specific (e.g. LHCI; Croce et al., 2002; Mozzo et al., 2010), Lhcb9 in Physcomitrella patens (Iwai et al., 2018), and Tidi in Dunaliela salina (Varsano et al., 2006); and (2) promiscuous antennae (i.e. complexes that can serve both PSI and PSII; Kyle et al., 1983; Wientjes et al., 2013a; Drop et al., 2014; Pietrzykowska et al., 2014).PSI-specific antenna proteins vary in type and number between algae, mosses, and plants. For example, the genomes of several green algae contain a larger number of lhca genes than those of vascular plants (Neilson and Durnford, 2010). The PSI-LHCI complex of plants includes only four Lhcas (Lhca1–Lhc4), which are present in all conditions analyzed so far (Ballottari et al., 2007; Wientjes et al., 2009; Mazor et al., 2017), while in algae and mosses, 8 to 10 Lhcas bind to the PSI core (Drop et al., 2011; Iwai et al., 2018; Pinnola et al., 2018; Kubota-Kawai et al., 2019; Suga et al., 2019). Moreover, some PSI-specific antennae are either only expressed, or differently expressed, under certain environmental conditions (Moseley et al., 2002; Varsano et al., 2006; Swingley et al., 2010; Iwai and Yokono, 2017), contributing to the variability of the PSI antenna size in algae and mosses.The colonial green alga Botryococcus braunii (Trebouxiophyceae) is found worldwide throughout different climate zones and has been targeted for the production of hydrocarbons and sugars (Metzger and Largeau, 2005; Eroglu et al., 2011; Tasić et al., 2016). Here, we have purified and characterized PSI from an industrially relevant strain isolated from a mountain lake in Portugal (Gouveia et al., 2017). This B. braunii strain forms colonies, and since the light intensity inside the colony is low, it is expected that PSI in this strain has a large antenna size (van den Berg et al., 2019). We provide evidence that B. braunii PSI differs from that of closely related organisms through the particular organization of its antenna. The structural and functional characterization of B. braunii PSI highlights a large flexibility of PSI and its antennae throughout the green lineage.  相似文献   

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Despite the use of Syrian hamsters (Mesocricetus auratus) in research, little is known about the evaluation of pain in this species. This study investigated whether the frequency of certain behaviors, a grimace scale, the treat-take-test proxy indicator, body weight, water consumption, and coat appearance could be monitored as signs of postoperative pain in hamsters in a research setting. Animals underwent no manipulation, anesthesia only or laparotomy under anesthesia. An ethogram was constructed and used to determine the frequencies of pain, active and passive behaviors by in-person and remote videorecording observation methods. The Syrian Hamster Grimace Scale (SHGS) was developed for evaluation of facial expressions before and after the surgery. The treat-take-test assessed whether surgery would affect the animals’ motivation to take a high-value food item from a handler. The hypothesis was that behavior frequency, grimace scale, treat-take-test score, body weight, water consumption, and coat appearance would change from baseline in the surgery group but not in the no-intervention and anesthesia-only groups. At several time points, pain and passive behaviors were higher than during baseline in the surgery group but not the anesthesia-only and no-intervention groups. The SHGS score increased from baseline scores in 3 of the 9 animals studied after surgery. The frequency of pain behaviors and SHGS scores were highly specific but poorly sensitive tools to identify animals with pain. Behaviors in the pain category were exhibited by chiefly, but not solely, animals that underwent the laparotomy. Also, many animals that underwent laparotomy did not show behaviors in the pain category. Treat-take-test scores, body weight, water consumption, and coat appearance did not change from baseline in any of the 3 groups. Overall, the methods we tested for identifying Syrian hamsters experiencing postoperative pain were not effective. More research is needed regarding clinically relevant strategies to assess pain in Syrian hamsters.

Pain experienced by laboratory animals can affect both animal welfare and research results. Little is known about the evaluation of pain in Syrian hamsters (Mesocricetus auratus) in the laboratory setting. However, various research models using Syrian hamsters involve surgery and are presumed to cause pain.16,47,49 In 2018 alone, the USDA reported that 35,695 hamsters were used for research studies involving painful procedures.48 Previously published behaviors exhibited by hamsters in response to pain include hunched posture with head down, reluctance to move, increased depression or aggression, extended sleep periods, and weight loss.7,8,10,16,21 How these behaviors are affected by factors such as the type of painful stimulus, anesthetic protocol, handling procedures, and environmental conditions is unclear. The practicality of observing these signs in the research environment is uncertain and likely complicated by the nocturnal nature of Syrian hamsters and an assumed propensity of this species to mask pain, much like other prey species.8,14,16A significant need exists for published data investigating whether behavioral observations or other clinical indicators can help recognize, quantify, or monitor pain in hamsters in a research setting. Detailed behavioral observations and well-controlled studies are needed to develop a system to assess postoperative pain in laboratory animals.8,33 Moreover, little information is available on the efficacy of analgesic agents in hamsters.1 The few studies of analgesics in hamsters rely on the mitigation of evoked pain responses (such as using a hot plate), which has limited relevance to clinical situations such as postoperative pain.8,32,36,51 To date, no published literature has evaluated the efficacy or safety of analgesics to treat postoperative pain in hamsters. Validated real-time and practical methods for evaluating pain in Syrian hamsters would support the evaluation of analgesic efficacy in this species.Various assessments have been developed to identify signs of pain in other species. Behavioral ethograms have been used to evaluate pain and analgesic efficacy in mice, rats, rabbits, and guinea pigs in the research environment.5,6,20,23,25,34,35,39-41,53 Another tool used to evaluate pain in animals is the grimace scale, which has been developed for mice, rats, rabbits, ferrets, cats, sheep, pigs, horses, and even harbor seals.3,4,9,11,13,15,19,22,26,30,37,45,50 The use of a proxy indicator, such as burrowing and time-to-integrate-to-nest in mice and time-to-consume in guinea pigs, can be used as an additional tool for the evaluation of pain.5,17,18,35,38Because none of the previously mentioned assessment techniques were specific to hamsters, we here explored using these approaches to detect pain in Syrian hamsters that underwent laparotomy in a laboratory setting. We developed a species-specific ethogram and the Syrian Hamster Grimace Scale (SHGS). We also devised a novel proxy indicator of pain for use in Syrian hamsters, the treat-take-test (TTT), which is based on hamsters’ natural behavior to hoard food.16,46,49,52 Although water intake, body weight, and coat appearance are non-specific indicators of pain, we also measured these parameters.5,19,23,33 Furthermore, we analyzed the effects of the presence of an observer and time of day. We hypothesized that behavior frequency, grimace scale, treat-take-test score, body weight, water consumption, and coat appearance would change from baseline in the surgery group but not in the no-intervention and anesthesia-only groups.  相似文献   

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The rapid and responsive growth of a pollen tube requires delicate coordination of membrane receptor signaling, Rho-of-Plants (ROP) GTPase activity switching, and actin cytoskeleton assembly. The tomato (Solanum lycopersicum) kinase partner protein (KPP), is a ROP guanine nucleotide exchange factor (GEF) that activates ROP GTPases and interacts with the tomato pollen receptor kinases LePRK1 and LePRK2. It remains unclear how KPP relays signals from plasma membrane-localized LePRKs to ROP switches and other cellular machineries to modulate pollen tube growth. Here, we biochemically verified KPP’s activity on ROP4 and showed that KPP RNA interference transgenic pollen tubes grew slower while KPP-overexpressing pollen tubes grew faster, suggesting that KPP functions as a rheostat for speed control in LePRK2-mediated pollen tube growth. The N terminus of KPP is required for self-inhibition of its ROPGEF activity, and expression of truncated KPP lacking the N terminus caused pollen tube tip enlargement. The C-terminus of KPP is required for its interaction with LePRK1 and LePRK2, and the expression of a truncated KPP lacking the C-terminus triggered pollen tube bifurcation. Furthermore, coexpression assays showed that self-associated KPP recruited actin-nucleating Actin-Related Protein2/3 (ARP2/3) complexes to the tip membrane. Interfering with ARP2/3 activity reduced the pollen tube abnormalities caused by overexpressing KPP fragments. In conclusion, KPP plays a key role in pollen tube speed and shape control by recruiting the branched actin nucleator ARP2/3 complex and an actin bundler to the membrane-localized receptors LePRK1 and LePRK2.

The delivery of nonmotile sperm to the embryo sac via a pollen tube is a key innovation that allowed flowering plants to carry out sexual reproduction without the need for water (Friedman, 1993; Lord and Russell, 2002). Both the speed and signal responsiveness of pollen tube growth are critical for successful fertilization (Johnson et al., 2019). The typical shape of a growing pollen tube cell protruding from a pollen grain is a cylinder with a dome-shaped tip (Geitmann, 2010). Maintaining such a typical tube shape during pollen tube growth is fundamental to support its ability for fast growth (Michard et al., 2017), and a plasticity range of tubular growth rates allows a pollen tube to optimize directional growth along its journey from the stigma to the ovule (Luo et al., 2017). The pollen tube cell extends mainly by tip growth, requiring huge amounts of secretion/exocytosis at the tip (McKenna et al., 2009; Grebnev et al., 2017). The newly secreted cell wall at the tip is mainly composed of esterified pectin, which is expandable, whereas cell wall remodeling at the lateral region (including pectin deesterification and callose deposition) limits expansion (Grebnev et al., 2017). The tip width of a growing pollen tube actually reflects the size of the secretion zone capped by an expandable membrane and cell wall, as a collective result of multiple pollen tube growth machineries (Luo et al., 2017).The tip-localized exocytosis of a growing pollen tube is supported by a spatiotemporal tightly controlled actin cytoskeleton network (Hepler, 2016). The actin cytoskeleton configuration in a pollen tube includes highly dynamic fine actin filaments in the apical and subapical regions and parallel longitudinal actin bundles in the shank region (Qu et al., 2017). Various actin-binding proteins, such as actin nucleation factors, actin-severing proteins, and actin-bundling factors, are responsible for organizing the dynamic actin cytoskeleton network (Ren and Xiang, 2007). For example, the actin-bundling proteins fimbrin and LIM (Lin-1, isl1, Mec3) domain-containing proteins function in shank-localized actin bundles in pollen tubes (Zhang et al., 2019). For another example, the actin nucleator formin (formin3 in Arabidopsis [Arabidopsis thaliana] and formin1 in lily [Lilium longiflorum]) functions in actin polymerization in the pollen tube tip (Li et al., 2017; Lan et al., 2018). The branched actin nucleator Actin-Related Protein2/3 (ARP2/3) complex is an evolutionarily conserved, seven-subunit complex consisting of the actin-related proteins ARP2 and ARP3 (Machesky et al., 1994). The ARP2/3 complex initiates the formation of branches on the side of preexisting actin filaments, locally creating a force-generating branched actin network that underlies cellular protrusion and movement (Blanchoin et al., 2000; Amann and Pollard, 2001; Molinie and Gautreau, 2018). The phenotypes of mutants in ARP2/3 in the moss Physcomitrella patens (Harries et al., 2005; Perroud and Quatrano, 2006), in Arabidopsis (Le et al., 2003; Li et al., 2003; Mathur et al., 2003; Brembu et al., 2004; Deeks et al., 2004), in maize (Zea mays; Frank and Smith, 2002), and in tomato (Solanum lycopersicum; Chang et al., 2019) demonstrated the broad importance of the ARP2/3 complex and its activation during cellular morphogenesis, including tip-growing cells. Perhaps surprisingly, in Arabidopsis, null ARP2/3 alleles are transmitted normally through pollen and there is no obvious root hair phenotype (Le et al., 2003; Djakovic et al., 2006).These cell growth machineries are tightly coordinated by multiple signaling pathways, including membrane-localized receptor kinases and Rho-of-Plants (ROP) GTPases (Li et al., 2018). The tomato pollen-specific and membrane-localized receptor kinases LePRK1 and LePRK2 mediate signaling during pollen tube growth (Muschietti et al., 1998). LePRK2 perceives several extracellular growth-stimulating factors, including a Cys-rich extracellular protein (Late-Anther-Specific52 [LAT52]), a Leu-rich repeat protein from pollen, and two pistil/stigma molecules, Style Interactor for LePRKs and Stigma-Specific Protein1 (Tang et al., 2002, 2004; Wengier et al., 2003, 2010), which increase the speed of pollen tube growth (Zhang et al., 2008b; Huang et al., 2014). LePRK2 antisense and RNA interference (RNAi) pollen tubes grow slower (Zhang et al., 2008b), consistent with a positive role for LePRK2 in regulating the speed of pollen tube growth. LePRK1 binds LePRK2 (Wengier et al., 2003), but LePRK1 plays a negative role in pollen tube growth by controlling a switch from a fast tubular mode to a slow blebbing mode (Gui et al., 2014). LePRK1 RNAi pollen tubes burst more often than wild-type pollen tubes, implicating a role for LePRK1 in maintaining plasma membrane integrity (Gui et al., 2014). An Arabidopsis paralog of these LePRKs, PRK6, also localized on the tip membrane, perceives Arabidopsis attraction cues from the female, AtLURE1s, to guide pollen tube growth (Takeuchi and Higashiyama, 2016; Zhang et al., 2017).Rho family small guanine nucleotide-binding proteins called ROPs or RACs, which can switch between a GDP-bound inactive form and a GTP-bound active form, are regulators of polar growth in pollen tubes (Cheung and Wu, 2008; Yang, 2008). In Arabidopsis, ROP1-dependent signaling controls tip growth. Active ROP1 defines a cap region in the apical plasma membrane as an exocytosis zone (Luo et al., 2017). Overexpression of ROP1 or of a constitutively active version resulted in pollen tube tip swelling (i.e. increased tip width) and slower growth (i.e. reduced tube length), while overexpressing a dominant negative version of ROP1 inhibited pollen tube growth (i.e. shorter but normal width tubes). The size of the pollen tube tip reflects the aggregate activity of membrane-associated ROP at the tip (McKenna et al., 2009; Luo et al., 2017). Tomato ROPs have been reported to be associated with the LePRK1-LePRK2 complex (Wengier et al., 2003) and therefore presumably play similar roles as the Arabidopsis homologs in pollen tube growth, yet their biological roles have not been directly investigated.Guanine nucleotide exchange factors (GEFs) activate ROPs by promoting the conversion of ROP/RAC GTPases from a GDP-bound inactive form to a GTP-bound active form. Plants possess a plant-specific ROPGEF family whose members contain a highly conserved GEF catalytic domain, the PRONE (plant-specific ROP nucleotide exchanger) domain (Berken et al., 2005; Gu et al., 2006). The intracellular portions of LePRK1 and LePRK2 interact with Kinase Partner Protein (KPP; Kaothien et al., 2005), whose Arabidopsis homologs were later shown to belong to the PRONE-type ROPGEF family (Berken et al., 2005; Gu et al., 2006). Pollen tubes overexpressing nearly full-length KPP (missing eight amino acids at the N terminus) developed swollen tips with abnormal cytoplasmic streaming and F-actin arrangements (Kaothien et al., 2005). An Arabidopsis homolog of receptor kinase, AtPRK2a (also named AtPRK2), interacts with AtROPGEF12 (Zhang and McCormick, 2007) and with AtROPGEF1 (Chang et al., 2013) to affect ROP activity. Based on the in vitro catalytic activity of full-length and truncated AtROPGEF1, an autoinhibition conferred by the C-terminal variable region was proposed (Gu et al., 2006). AtROPGEF12 was also shown to interact with the guidance receptor kinase PRK6 (Takeuchi and Higashiyama, 2016).Increased expression of full-length KPP increased the speed of pollen tube growth without significantly affecting pollen tube shape. We show biochemically that the PRONE domain of KPP does have ROPGEF activity on several class I ROPs, with highest activity on ROP4. The N-terminal domain of KPP inhibits its own GEF activity, while its C-terminal domain enhances its own GEF activity. The C-terminal domain of KPP is also required for its interactions with LePRK1, LePRK2, and an actin-bundling protein, Pollen-expressed LIM2a (PLIM2a), while the C-terminal domain alone is sufficient to bind LePRK1 but insufficient to bind LePRK2. Furthermore, self-associated KPP colocalized with the actin nucleation proteins ARP2/3 complex during pollen tube growth and enriched the membrane localization of ARP2/3 in the pollen tube. Interfering with ARP2/3 activation by coexpressing a dominant negative version of ARP2 reduced the speed of pollen tube growth and alleviated the defects caused by the overexpression of truncated KPP. CK-666, a specific small molecule inhibitor of ARP2/3 activation, canceled the promotive effect of full-length KPP on the speed of pollen tube growth. These results indicate that during pollen germination and tube growth, KPP not only links pollen receptor kinase and ROP signaling but also links the actin network to the pollen tube plasma membrane, thereby directly affecting the cellular morphology and efficiency of pollen tube growth.  相似文献   

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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
TechniquePrincipleResolutionCommentsApplications in spines and synapses
Lateral (XY)Axial (Z)
CLSM250 nm500 nm
TPLSMTwo-photon excitation350 nm700 nmDeeper tissue penetration; adaptive optics further improveHelmchen and Denk, 2005; Ji, 2017
STEDStimulated emission (Vicidomini et al., 2018)20–70 nm500 nm3-D STED increases axial resolution; chronic in vivo imaging is possibleNägerl et al., 2008; Berning et al., 2012; Pfeiffer et al., 2018
SIMMoiré effect with structured illumination (Wu and Shroff, 2018)100 nm250 nmNo need for special fluorophores; limited resolution improvementKashiwagi et al., 2019; Li et al., 2020
SMLM (PALM, STORM)Photoactivation, photoconversion (Baddeley and Bewersdorf, 2018)10–30 nm30–60 nmHigh spatial resolution; temporal resolution is relatively worseDani et al., 2010; Tang et al., 2016
ExMPhysical expansion of sample (Wassie et al., 2019)4–20-fold improvement4–20-fold improvementCapable of combining with other imaging techniques, only for fixed samplesGao et al., 2019; Sarkar et al., 2020 Preprint
Open in a separate windowCLSM, confocal laser scanning microscopy; SMLM, single-molecule localization microscopy; STORM, stochastic optical reconstruction microscopy; TPLSM, two-photon laser scanning microscopy.Open in a separate windowFigure 3.Imaging techniques to measure diffusion inside dendritic spines. (a) FRAP. Fluorescence intensity change is measured after photobleaching fluorescent molecules in a spine head. Fluorescence recovery rate is mostly determined by the exchange rate between spine and dendrite. (b) FCS. The fluctuation of fluorescence intensity from the detection volume fixed inside a spine head (blue region in left panel) is recorded as a function of time (center panel). Since the fluorescence intensity fluctuates as the molecules enter and leave the fixed detection volume, the characteristics of intensity fluctuation essentially contain information about local diffusion speed. To estimate the diffusion coefficient, the autocorrelation function of fluorescence intensity fluctuation is calculated (right panel). (c) SPT. In SPT, molecular trajectory is directly measured with video microscopy. To analyze the speed and pattern of molecular motion, mean squared displacement (MSD) is calculated. For diffusion without barrier, MSD increases linearly against time. On the other hand, for diffusion within the compartment, MSD converges to a certain value, which corresponds to compartment size. (d) Comparison of three measurement techniques.Table 2.List of fluorescence molecular dynamic measurement techniques
TechniquePrincipleApplications in spines and synapses
FRAPFluorescent molecules in a small region are photobleached, and subsequent movement of surrounding nonbleached fluorescent molecules into the photobleached area is monitored (Lippincott-Schwartz et al., 2018).Svoboda et al., 1996; Bloodgood and Sabatini, 2005
FCSFluctuation of fluorescence intensity from the detection volume fixed at a specific position is recorded, and a temporal correlation is analyzed (Elson, 2011).Chen et al., 2015; Obashi et al., 2019
RICSSpatial correlation is analyzed from raster-scanned images (Digman and Gratton, 2011).Obashi et al., 2019
SPTThe movement of a single particle is tracked using time-lapse imaging, and a trajectory is made and analyzed. To detect single particles, the density of fluorescence particles should be kept low (Shen et al., 2017).Borgdorff and Choquet, 2002; Varela et al., 2016
SPT-PALMOnly a small number of photoactivatable fluorescent proteins in the field of view are activated and tracked until they are bleached (Manley et al., 2010).Frost et al., 2010b; Nair et al., 2013
Open in a separate windowSpine structures and diffusionThe complex physical structures of spines can impact the diffusion of molecules inside the spine cytoplasm and between spines and their parental dendritic shafts (Fig. 1 c and Fig. 2). For example, consider the diffusional translocation of molecules between the PSD and dendritic shaft. For cytoplasmic proteins, because a spine is connected to the dendritic shaft through a narrow neck, proteins must pass through the neck by diffusion or slow active transport. A spine neck functions as a diffusion barrier because of its narrow width (Svoboda et al., 1996). Molecular complexes with actin filaments and related proteins, such as synaptopodin and ankyrin-G, that maintain this characteristic neck morphology may also affect diffusion. Furthermore, the cytoplasm within spines is likely to be not homogeneous but organized with multiple nanoscale domains with different biophysical properties (Frost et al., 2010a; MacGillavry and Hoogenraad, 2015). Thus, these locally dense cytoskeletal and membranous structures can limit the molecular path of diffusion within a spine by specific binding interactions or nonspecific local steric effects. These factors will change the residence time of proteins within spines.Besides cytosolic proteins, membrane protein diffusion can be regulated by structures on and near the plasma membrane. For example, the cortical cytoskeleton affects the movement of membrane proteins (Kusumi et al., 2012). Furthermore, specialized membrane domains with a high density of membrane-associated structures, such as synaptic contact sites, accumulate many relatively immobile molecules and limit membrane protein diffusion (Trimble and Grinstein, 2015). Lastly, spines are not simply spherical. Boundaries between the spine shaft and neck—and also the spine head and neck—can contain high curvatures. Also, large spine heads contain a concave surface (Kashiwagi et al., 2019). Thus, local concavities, undulations, and convexities may affect the possible path a molecule can take (Simon et al., 2014; Klaus et al., 2016). From all these factors, the shape and internal architecture of spines can have strong effects on diffusion for both cytosolic and membranous proteins.Influences of spine morphology on diffusional coupling between spines and dendritesAlthough the cytoplasm of spines is directly connected to the cytoplasm of dendritic shafts, a narrow neck is thought to limit diffusion of both cytosolic and membrane molecules between two compartments (Holcman and Schuss, 2011; Kusters et al., 2013; Ramirez et al., 2015). FRAP is a method that can be used to measure the diffusional speeds from an exchange rate between nonbleached and bleached molecules after bleaching fluorescent molecules in a small region (Lippincott-Schwartz et al., 2018; Fig. 3, a and d). Local photoactivation or photoconversion and subsequent measurements of fluorescence intensity is another technique comparable to FRAP (Bancaud et al., 2010). When fluorescence bleaching is performed in a spine head, the speed of fluorescence recovery mostly reflects the rate of molecular exchange between the head and the connected dendrite. Because the diffusion of small molecules in a head is faster than the rate of molecular exchange between spines and dendrites, the fast component of intra-spine diffusion is more difficult to detect in FRAP recovery curves (Svoboda et al., 1996). FRAP or photoactivation experiments of cytoplasmic and membrane-anchored fluorescent proteins showed that diffusional coupling between spines and dendrites varies between spines (Bloodgood and Sabatini, 2005; Ashby et al., 2006). Since the shape of spines is diverse, it has been proposed that this diversity underlies variability in spine–dendrite coupling. However, because the details of spine morphology cannot be analyzed with the spatial resolution of diffraction-limited fluorescence microscopy, a relationship between the shape of spines and diffusional coupling had not been directly demonstrated.Recently, however, super-resolution microscopy has made it possible to analyze spine shape in living neurons with a spatial resolution of ∼50 nm (Nägerl et al., 2008). Influences of spine morphology on diffusional coupling were verified experimentally for the first time by directly comparing the morphological features of spines and diffusional coupling. This comparison was achieved by stimulated emission depletion (STED) microscopy of spines combined with FRAP of YFP or Alexa dyes applied to the same spine (Takasaki and Sabatini, 2014; Tønnesen et al., 2014). These direct comparisons indicated that the diversity in diffusional couplings could be explained solely by the diversity of spine shapes for more than half of the measured spines. In other words, it was shown that for many spines, the exchange rate (τ) of small molecules within spines could be explained by a single-compartment model (Svoboda et al., 1996) described by the shape of the spine:τ=V×LA×D ,where V is the head volume, L is the length of the neck, A is the cross-sectional area of the neck, and D is the diffusion coefficient of molecules. Also, sLTP induction made a spine neck thicker and shorter (Tønnesen et al., 2014). This change in the spine neck complements the decrease in the coupling rate associated with the increase in the spine head volume. This coordinated morphological change appears to maintain molecular concentration in a spine.Besides the work focusing on cytoplasmic proteins, the influence of spine shape on the diffusional coupling of membrane molecules has also been investigated (Adrian et al., 2017). The spine–dendrite diffusional coupling was tested by photoactivated localization microscopy (PALM) and photoconversion experiments using membrane-anchored mEos3.2 as a probe. This study showed that even if spines have the same surface area and neck width, the diffusional coupling varies between different spine shapes. Therefore, a model spine was created based on the experimentally measured spine shape parameters, and a simulation was conducted on the model spine and compared with the experiment. As a result, although experimental results tended to provide slower diffusion kinetics than simulation values, experiments showed a good correlation with simulations based on the spine shape parameters alone.Experiments have confirmed that spine morphology is a major factor determining the diffusional coupling for both cytoplasmic and membrane-bound molecules in dendrites. However, for some spines, the simulated and experimental results diverge. One possibility is that the effects of local intra-spine architectures on molecular diffusion vary for each spine. Another possibility is that there was insufficient spatial resolution for reconstructing the spine morphology. Although the above studies used rotationally symmetric shapes as model spines, actual spines are not rotationally symmetrical structures and generally have a more complicated morphology and surface features (Nägerl et al., 2008; Berning et al., 2012; Kashiwagi et al., 2019; Zaccard et al., 2020; Fig. 1, a and b). Thus, it is possible that estimations of spine shape were insufficient or that the fine structure of spines affects diffusion. In this regard, developing an analysis method for spine morphology from both the experimental and computational sides is key (Okabe, 2020a; Tamada et al., 2020). Recently, Kashiwagi et al. (2019) developed a 3-D structured illumination microscopy (SIM)–based nanoscale analysis of spine morphology. Direct comparison of SIM images and serial-section EM images revealed that the basic morphological features were highly correlated among these images. This indicates the high precision of SIM-based nanoscale spine analysis. To analyze spines computationally, SIM images were converted into a computational geometry, and morphological features were calculated. Then, these features were analyzed by principal component analysis. By mapping the temporal changes of spine morphology obtained by live-cell SIM imaging in the dimension-reduced feature space, the authors revealed that the spine population can be categorized based on different simplified morphological dynamics.Also, expansion microscopy (ExM) is another new and important imaging technique for spine structural analysis (Wassie et al., 2019). However, it can only be applied to fixed samples. Since ExM samples are transparent, 3-D super-resolution imaging is available for thick samples with large volumes (Gao et al., 2019). With recent developments in sample preparation technology, ExM has the potential to investigate spine morphology and localization of multiple biomolecules and organelles within a single sample (Chozinski et al., 2016; Tillberg et al., 2016; Karagiannis et al., 2019 Preprint; Sun et al., 2021). Minimizing the distortion of isotropy during expansion will be important for nanoscale morphological analysis. In the future, combining dynamic fluorescence measurements and structural measurements gained from EM (CLEM) will be a powerful approach to evaluate the effects of spine ultrastructure on molecular diffusion in greater nanoscale detail (Maco et al., 2013; Taraska, 2015; Luckner et al., 2018).Along with biochemical compartmentalization, dendritic spines have been proposed to be important for electrical compartmentalization (Yuste, 2013; Araya, 2014; Tønnesen and Nägerl, 2016). Spine morphology, particularly spine neck morphology, is thought to be critical for this effect (Cartailler et al., 2018). Several studies have sought to measure neck resistance based on morphological analysis using EM (Harris and Stevens, 1989; Tamada et al., 2020), super-resolution microscopy (Tønnesen et al., 2014), FRAP of small molecules (Svoboda et al., 1996; Tønnesen et al., 2014), glutamate uncaging (Araya et al., 2006; Takasaki and Sabatini, 2014), calcium imaging (Grunditz et al., 2008; Harnett et al., 2012), voltage imaging (Popovic et al., 2015; Acker et al., 2016; Kwon et al., 2017), and intracellular recordings directly from spine heads (Jayant et al., 2017). However, results were not completely consistent, and the degree of electrical compartmentalization is still unclear. Thus, the relationship between spine morphology and electrical signaling of the synapse is still an open question. Likewise, how morphological changes in the neck induced by LTP affect dendritic computation will be an important area of future study (Araya et al., 2014; Tazerart et al., 2020).Actin cytoskeletonThe cytoskeleton in spines is primarily composed of actin (Hotulainen and Hoogenraad, 2010; Okabe, 2020b). Actin is present in high densities in both the head and neck regions (Korobova and Svitkina, 2010). Actin polymers are essential in controlling the localization of PSD molecules and in changing and maintaining spine morphology (Frost et al., 2010a; Bertling and Hotulainen, 2017). In addition to these functions, dense actin polymers in spines may regulate synaptic functions by controlling diffusion because the intracellular cytoskeleton and membrane structures influence diffusion (Novak et al., 2009). If this regulation occurs in spines, variations in the distribution of intra-spine structures can be a factor in the large deviations between the measured values of diffusional coupling and the value predicted from models. A ratio of the spine FRAP recovery time of Alexa dyes to that of YFP was comparable to that of hydrodynamic radii (Tønnesen et al., 2014). This suggests that the suppression of diffusion by actin polymers is weak for molecules with the size of GFP. However, suppressive effects on molecular diffusion by the cytoskeleton, such as actin polymers, is dependent on the size of molecules (Baum et al., 2014; Katrukha et al., 2017). Thus, diffusion of larger molecules may be influenced to a greater degree by actin polymers.Because the shape of spines affects the recovery time of FRAP measurement, it is difficult to investigate the effects of intra-spine structure on molecular diffusion using FRAP alone. Therefore, there is a need for a method capable of measuring diffusion directly in confined spaces. Lu et al. (2014) measured the motion of mEOS2-fused CaMKIIα in spines by single-particle tracking (SPT)–PALM. SPT can directly evaluate diffusional speed in spines because it analyzes the molecular movement trajectory of single molecules (Fig. 3, c and d). The SPT measurement showed that CaMKIIα exhibited at least three different diffusion modes within spines: (1) a free diffusion component, (2) a component bound to immobile molecules, and (3) a component moving at an intermediate velocity. Depolymerization of actin polymers by latrunculin A reduced the proportion of molecules with intermediate velocities in spines while concomitantly increasing the free diffusion component. Also, diffusional speeds of CaMKIIα were slower and the ratio of the intermediate component was larger in spines than in dendrites. Because the transition between free and bound states would occur rarely during the measurement period due to the slow unbinding rate of CaMKII from actin polymers, transient binding alone does not explain the mechanism for the intermediate velocity. Although the details are unclear, CaMKII motion is restricted by actin polymers through a mechanism distinct from direct binding, including a molecular sieve effect or transient binding to actin-associated molecules.Obashi et al. (2019) used fluorescence correlation spectroscopy (FCS) and raster image correlation spectroscopy (RICS) to measure the diffusion of biologically inert probes within spines. FCS is a method for estimating diffusion speed from the time taken for fluorescent molecules to pass through the detection volume excited by a high numerical aperture objective and is capable of measuring fast diffusion within a small cellular compartment (Elson, 2011; Fig. 3, b and d). RICS is another method for estimating diffusion speed from the spatial similarity of fluorescence intensity in a scanned image (Digman and Gratton, 2011). Since FCS and RICS are affected by the small size of spines due to the boundary effect, it is not possible to measure the diffusion coefficient accurately (Jiang et al., 2020). Still, by averaging, values proportional to the actual values can be obtained. Diffusion of GFP and GFP tandem pentamer (GFP5) were compared, and only diffusion of GFP5 within spines was enhanced by depolymerizing actin with latrunculin A treatment. Molecular dynamics simulation confirmed that the diffusion of molecules over the size of GFP5 was suppressed by actin polymers with a density (380 µM) estimated from the values in the literature and experiments.Together, these experiments support the idea that a meshwork of dense actin polymers in spines acts as a physical barrier to the diffusion of larger (>100 kD) molecules (Fig. 4 a). Photoactivation experiments of intra-spine photoactivatable GFP (PA-GFP)–actin showed that there are at least three groups of actin polymers with different reorganization rates (Honkura et al., 2008). In addition, experiments with SPT-PALM of PA-GFP–actin showed that a rate of actin filament polymerization increased near PSDs (Frost et al., 2010b). PALM analysis also revealed that actin-related molecules within spines are arranged in a manner specific for each molecule (Chazeau et al., 2014). These results suggest that the diffusional control by actin polymers in spines may differ between each subcompartment.Open in a separate windowFigure 4.Diffusion within network of actin polymers and PSD. (a) Comparison of the size of actin polymer network and diffusion molecules. Average distance between actin polymers is estimated for actin polymers with 380 µM (Obashi et al., 2019). GFP is represented as a diameter of 3 nm and CaMKII is represented as a diameter of 20 nm (Myers et al., 2017). (b) A schematic model of AMPAR diffusion within a crowded PSD. Different localization patterns of molecules cause different diffusion patterns. Such mechanisms will occur within the PSD. Density and size of molecules are based on the literature (Okabe, 2007; Li et al., 2016).It was also shown that reorganization of the actin cytoskeleton immediately after sLTP induction (Chazeau and Giannone, 2016; Mikhaylova et al., 2018) enhanced the diffusion of larger molecules within the spine head (Obashi et al., 2019). Further, FRAP experiments showed that diffusional coupling and synaptic translocation of large synaptic molecules, such as CaMKII and T cell lymphoma invasion and metastasis-inducing protein 1 (Tiam1), were facilitated at the initial phase of sLTP. Thus, the reorganization of actin polymers regulates molecular translocation between dendrites and the PSD in coordination with morphological changes of the spine neck (Tønnesen et al., 2014). The enhancement of molecular diffusion by actin may also be related to the formation of a large signaling complex containing CaMKII and Tiam1 and may be an important physical mechanism responsible for the initiation of sLTP (Saneyoshi et al., 2019).Membranous organellesAlong with the cytoskeleton, dendrites also contain many membranous organelles and compartments, and some are present in spines (Bourne and Harris, 2008). Smooth ER (SER) and recycling endosomes are present in <50% of spines. Spine apparatus, which is composed of stacked SER, is present in 10–20% of spines. Localizations of these organelles change after LTP induction, and spines containing SER are larger than those without SER (Chirillo et al., 2019; Kulik et al., 2019; Perez-Alvarez et al., 2020). While mitochondria are abundant in dendritic shafts but rarely present in spines (Wu et al., 2017), synaptic activation relocates mitochondria into spines (Li et al., 2004). Therefore, variations in the diffusional coupling between spines and dendrites could be due to the heterogeneous localization of these organelles (Cugno et al., 2019). Holbro et al. (2009) compared the diffusional coupling of ER-containing spines and ER-free spines by using an ER-targeted GFP probe. FRAP recovery times of RFP were not different among ER-containing and ER-free spines, indicating that the ER does not block cytoplasmic diffusion between spines and dendritic shafts. Understanding both spine morphology and the volume of ER within spines in the future will clarify the effects of excluded volume by the ER and other organelles in more detail.Structures around spine necksMolecules present in spine necks may physically control diffusion by forming a complex higher-order structure. Platinum replica EM showed the presence of Arp2/3 complex within necks and a longitudinal network of branched and linear actin filaments (Korobova and Svitkina, 2010). SPT-PALM of PA-GFP–actin also showed that actin polymers in necks are dynamically reorganized and that they are arranged in many orientations (Frost et al., 2010b). Thus, actin polymers in spine necks may affect molecular diffusion. Synaptopodin, for example, is an actin-binding protein located predominantly in spine necks. It is colocalized with the spine apparatus (Vlachos, 2012). Wang et al. (2016) used SPT to measure metabotropic glutamate receptor 5 (mGluR5) diffusion around necks. They compared the diffusion of mGluR5 around the necks of spines containing (or not containing) synaptopodin. The diffusion of mGluR5 decreases around spine necks near synaptopodin clusters. Further, latrunculin A treatment specifically enhanced the diffusion around spine necks near synaptopodin clusters. These results suggest that synaptopodin regulates the actin polymer network around spine necks. This actin complex can act as a diffusion barrier for membrane proteins.Another protein that has been implicated in diffusional control of membrane proteins is ankyrin-G. Ankyrin-G forms nanodomain at perisynaptic membranes and in spine necks (Smith et al., 2014). AMPARs accumulated in spines with ankyrin-G clusters and showed slower spine–dendrite coupling. Ankyrin-G is the major cytoskeletal scaffold of the axon initial segment (AIS; Leterrier, 2018). Ankyrin-G and actin scaffolds densely accumulate at the AIS and inhibit diffusion of the membrane and cytoplasmic molecules (Winckler et al., 1999; Nakada et al., 2003; Song et al., 2009). Also, super-resolution microscopy recently revealed the presence of membrane-associated periodic skeleton composed of actin rings, spectrin, and accompanying proteins in the axon including the AIS (Xu et al., 2013; Zhong et al., 2014). At the AIS, the actin rings and associated structures act as a diffusion barrier to membrane proteins (Albrecht et al., 2016). Adding to the axon, membrane-associated periodic skeleton was also observed in the dendrites and spine necks (Bär et al., 2016; Sidenstein et al., 2016). Therefore, it is interesting to postulate that a molecular complex with actin filaments similar to the AIS is also present in spine necks and could regulate molecular diffusion in this small compartment.Another cytoskeletal component, septin 7, localizes to the base of spines and acts as a diffusion barrier for membrane-bound molecules (Ewers et al., 2014). Recently, actin patches were found at the base of spines and were shown to be remodeled by synaptic activity. These structures modulate microtubule entry into spines and the transport of lysosomes (Schätzle et al., 2018; van Bommel et al., 2019). It is interesting to ask whether actin patches at spine bases affect molecular diffusion. There are still many unknown features at the spine neck, and how these structures limit the diffusion of cytoplasmic and membrane molecules to control neuronal functions remains unclarified.Molecular crowding in the PSDThe PSD is a membrane-associated structure containing densely packed postsynaptic molecules (Sheng and Hoogenraad, 2007). It was originally identified as an electron-dense structure in EM (Okabe, 2007). The number and location of receptors and adhesion molecules in PSDs are directly related to synaptic function (Chen et al., 2018). SPT studies indicate that AMPARs diffuse laterally into and out of PSDs and regulate synaptic function by controlling the number and location of AMPARs (Choquet and Hosy, 2020). Because there are many scaffold proteins in PSDs, membrane proteins including AMPARs accumulate in PSDs due to intermolecular binding. Furthermore, because the molecular density in PSDs is high, the accumulation of membrane proteins may be regulated by the suppression of mobility within the PSD and molecular exchange at the boundary of PSDs (Gerrow and Triller, 2010; Kokolaki et al., 2020).To check this possibility, Li et al. (2016) combined FRAP, SPT, and Monte Carlo simulation to investigate the effect of molecular crowding of PSDs on the lateral diffusion of membrane molecules. When the intracellular domain size of membrane proteins was large, diffusion within the PSD and the exchange rate between the inside and outside of the PSD decreased. Super-resolution microscopy showed that the distribution of PSD-95, a major scaffolding protein of the PSD, within PSDs is not uniform (Fukata et al., 2013; MacGillavry et al., 2013; Nair et al., 2013; Broadhead et al., 2016; Gwosch et al., 2020). Interestingly, the simulation showed that the residence time of membrane proteins within PSDs was longer in the condition of experimentally measured PSD-95 distribution, while the residence time decreased with a random distribution of PSD-95 (Li et al., 2016).Recently, the shape of PSDs inside spines induced by sLTP was analyzed by CLEM (Sun et al., 2019 Preprint). It was shown that rearrangements of PSD shape occurred immediately after induction of sLTP (<3 min), and the PSD took more complex morphology. This increased structural complexity persisted in the late phase (120 min). PSD size and the accumulation of PSD-95 increased slowly over several tens of minutes after sLTP induction (Meyer et al., 2014), whereas synaptic transmission efficiency increased immediately (Matsuzaki et al., 2004). This difference in time may be explained by a mechanism in which the acute ultrastructural changes of the PSD without net growth of the molecular assembly alter the mobility of AMPARs by changing the distribution of a physical barrier, leading to alternations in the number and localization of AMPARs (Fig. 4 b). In future studies, it will be necessary to clarify how coordination between intermolecular binding and physical diffusion barriers in PSDs supports both acute accumulation of AMPARs and their subsequent stabilization in stimulated spines. Further, 3-D SIM imaging revealed that the concave surface of the spine head, which interacts with presynaptic membranes, is enlarged and stabilized by sLTP induction (Kashiwagi et al., 2019). In the future, it will be interesting to determine the relationships between concave membrane surfaces, PSD morphologies, and the dynamics of receptors and adhesion molecules at single spines.In addition, although AMPAR has been thought to be present as a tetramer (Greger et al., 2007), recent observations of SPT have shown that the majority of diffusive AMPARs are monomers or dimers (Morise et al., 2019). Molecular diffusion in the monomer form increases an exchange rate between the inside and the outside of PSDs, making it possible to efficiently change the AMPAR composition within synapses. It remains to be seen whether other molecular complexes, such as NMDARs and cell adhesion molecules, also modulate their diffusion within the molecularly dense PSD by changing their oligomeric state.Conclusion and outlookHere, we have highlighted key recent findings on the relationship between molecular diffusion and physical barriers within spines. The regulation of molecular diffusion is important for sLTP expression (Fig. 2). Spine structural changes during sLTP will affect synaptic function in a coordinated manner (Fig. 5). For example, after sLTP induction, the actin network is reorganized and diffusion of large molecules is enhanced (Obashi et al., 2019). This facilitates the formation of large signaling complexes and the rearrangement of protein complexes within spines. At the same time, spine necks become wider and shorter, and spine heads enlarge (Tønnesen et al., 2014). Changes in actin and spine morphology enhance the molecular movement between the PSD and the shaft and are important for the relocation of proteins (Fig. 2). These structural changes occur in the early phase of sLTP. Thus, the cooperative regulation of diffusion might act as a precise temporal switch of sLTP induction. Also, this enhancement of molecular exchange affects the relocation of activated signaling molecules into the shaft or nearby synapses, which leads to heterosynaptic plasticity (Yasuda, 2017). Potentiation of synaptic transmission requires synaptic trafficking of AMPARs (Choquet and Hosy, 2020). Although both spine morphology (Adrian et al., 2017) and PSD structure (Li et al., 2016) affect membrane protein diffusion, how structural changes associated with sLTP induction affect diffusion will be clarified in the future. Furthermore, the effects of transient SER visits (Perez-Alvarez et al., 2020) and structural changes around spine necks are an important area for future work. Although the relationship between structure and diffusion in sLTP is critical, the difficulty of measurements with a small single spine has made a comprehensive view difficult to obtain. Thus, future work will be necessary to clarify how structural changes affect diffusion and how this physical change to dendritic spines cooperatively modulates synaptic functions.Open in a separate windowFigure 5.Changes in the shape and internal architecture of spines after induction of sLTP. At the initial phase of sLTP, a spine head expands. In addition, the spine neck becomes wider and shorter (Tønnesen et al., 2014), and a concave surface area of spine head is increased (Kashiwagi et al., 2019). The actin polymer network is reorganized (Obashi et al., 2019), and the SER visits within a spine transiently (Perez-Alvarez et al., 2020). Also, PSD shape becomes more complex (Sun et al., 2019 Preprint). These physical changes should occur in concert and will affect molecular composition and biochemical signaling through diffusional regulation. These physical changes will act as a precise temporal switch of sLTP induction.Although new imaging techniques have demonstrated the connection between diffusion and physical barriers, little is known about how changes in the movement of molecules alter synaptic functions (Reshetniak et al., 2020b). Because of the small volume of the spine, very small molecules with high diffusivity, such as Ca2+, are expected to spread rapidly (∼1 ms) by diffusion (Chen and Sabatini, 2012). For large molecules such as signaling complexes, it remains to be seen whether spatially uniform diffusion takes place or whether local heterogeneity in the spine cytoplasm results in a more complex pattern of diffusion. It is also necessary to clarify whether such changes affect local biochemical signaling events and molecular localizations. The number of molecules per spine could influence the magnitude of functional changes (Okabe, 2007; Ribrault et al., 2011). Furthermore, the changes in diffusion induced by alterations in spine structure will affect the stability of the structure. This will subsequently change the molecule’s diffusivity. Thus, it will be interesting to investigate whether this type of mutual relationship exists within spines.New imaging techniques will help to answer these questions. By applying fast 3-D SPT to intra-spine measurements, it will be possible to investigate the spatial heterogeneity of diffusion in single spines of living neurons in detail (Hou et al., 2020; Xiang et al., 2020). STED-FCS/fluorescence cross-correlation spectroscopy can also detect changes in intermolecular interactions (Lanzanò et al., 2017). In addition to the development of new measurement techniques, molecular dynamics simulations based on experimental data will become increasingly important in the future (Okabe, 2020a; Reshetniak et al., 2020a; Vasan et al., 2020). Spine morphology and intra-spine structures, which affect diffusion, are closely related. Thus, it is difficult to investigate the effect of one without changing the other experimentally. Molecular dynamics simulation is a useful tool to examine how molecular motion is adjusted by combining elements that are difficult to verify experimentally (Bell et al., 2019). Furthermore, the shape of spines and intra-spine components, such as the actin cytoskeleton, which are the structural basis of spines, differ from spine to spine. Here, a combination of quantitative measurements and simulations based on experimental data will help us to understand molecular events more quantitatively.Although we reviewed work using fluorescence microscopy, details of spine morphology and intra-spine structures have also been revealed by EM at the nanoscale (Bourne and Harris, 2012; Tao et al., 2018). However, it is difficult to observe specific molecular localizations with EM. On the other hand, super-resolution microscopy is suitable for obtaining a nanoscale picture of molecular positions within spines. Yet, it is still difficult to observe dense structures such as actin polymers (Kommaddi et al., 2018). Therefore, in the future, it will be essential to combine the advantages of each technique, observing internal structures at the nanoscale using EM and measuring molecular localization with super-resolution microscopy (CLEM; Taraska, 2019; Hoffman et al., 2020). Of course, dynamic intracellular structures such as lipid rafts and biomolecular condensates are also likely to affect molecular mobility (Sezgin et al., 2017; Chen et al., 2020). Thus, it will be key to overlay molecular mobilities from living cells over the static structural information of CLEM. We believe that combinations of multiple imaging modalities, along with modeling, will allow for a more in-depth understanding of synapses at the molecular level. These data will reveal how the elaborate architecture, density, and compartmentalization of subcellular components influence the highly tuned, dynamic, and changeable actions of synapses in the brain.  相似文献   

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