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1.
Identification of the select agent Burkholderia pseudomallei in macaques imported into the United States is rare. A purpose-bred, 4.5-y-old pigtail macaque (Macaca nemestrina) imported from Southeast Asia was received from a commercial vendor at our facility in March 2012. After the initial acclimation period of 5 to 7 d, physical examination of the macaque revealed a subcutaneous abscess that surrounded the right stifle joint. The wound was treated and resolved over 3 mo. In August 2012, 2 mo after the stifle joint wound resolved, the macaque exhibited neurologic clinical signs. Postmortem microbiologic analysis revealed that the macaque was infected with B. pseudomallei. This case report describes the clinical evaluation of a B. pseudomallei-infected macaque, management and care of the potentially exposed colony of animals, and protocols established for the animal care staff that worked with the infected macaque and potentially exposed colony. This article also provides relevant information on addressing matters related to regulatory issues and risk management of potentially exposed animals and animal care staff.Abbreviations: CDC, Centers for Disease Control and Prevention; IHA, indirect hemagglutination assay; PEP, postexposure prophylacticBurkholderia pseudomallei, formerly known as Pseudomonas pseudomallei, is a gram-negative, aerobic, bipolar, motile, rod-shaped bacterium. B. pseudomallei infections (melioidosis) can be severe and even fatal in both humans and animals. This environmental saprophyte is endemic to Southeast Asia and northern Australia, but it has also been found in other tropical and subtropical areas of the world.7,22,32,42 The bacterium is usually found in soil and water in endemic areas and is transmitted to humans and animals primarily through percutaneous inoculation, ingestion, or inhalation of a contaminated source.8, 22,28,32,42 Human-to-human, animal-to-animal, and animal-to-human spread are rare.8,32 In December 2012, the National Select Agent Registry designated B. pseudomallei as a Tier 1 overlap select agent.39 Organisms classified as Tier 1 agents present the highest risk of deliberate misuse, with the most significant potential for mass casualties or devastating effects to the economy, critical infrastructure, or public confidence. Select agents with this status have the potential to pose a severe threat to human and animal health or safety or the ability to be used as a biologic weapon.39Melioidosis in humans can be challenging to diagnose and treat because the organism can remain latent for years and is resistant to many antibiotics.12,37,41 B. pseudomallei can survive in phagocytic cells, a phenomenon that may be associated with latent infections.19,38 The incubation period in naturally infected animals ranges from 1 d to many years, but symptoms typically appear 2 to 4 wk after exposure.13,17,35,38 Disease generally presents in 1 of 2 forms: localized infection or septicemia.22 Multiple methods are used to diagnose melioidosis, including immunofluorescence, serology, and PCR analysis, but isolation of the bacteria from blood, urine, sputum, throat swabs, abscesses, skin, or tissue lesions remains the ‘gold standard.’9,22,40,42 The prognosis varies based on presentation, time to diagnosis, initiation of appropriate antimicrobial treatment, and underlying comorbidities.7,28,42 Currently, there is no licensed vaccine to prevent melioidosis.There are several published reports of naturally occurring melioidosis in a variety of nonhuman primates (NHP; 2,10,13,17,25,30,31,35 The first reported case of melioidosis in monkeys was recorded in 1932, and the first published case in a macaque species was in 1966.30 In the United States, there have only been 7 documented cases of NHP with B. pseudomallei infection.2,13,17 All of these cases occurred prior to the classification of B. pseudomallei as a select agent. Clinical signs in NHP range from subclinical or subacute illness to acute septicemia, localized infection, and chronic infection. NHP with melioidosis can be asymptomatic or exhibit clinical signs such as anorexia, wasting, purulent drainage, subcutaneous abscesses, and other soft tissue lesions. Lymphadenitis, lameness, osteomyelitis, paralysis and other CNS signs have also been reported.2,7,10,22,28,32 In comparison, human''s clinical signs range from abscesses, skin ulceration, fever, headache, joint pain, and muscle tenderness to abdominal pain, anorexia, respiratory distress, seizures, and septicemia.7,9,21,22

Table 1.

Summary of reported cases of naturally occurring Burkholderia pseudomalleiinfections in nonhuman primates
CountryaImported fromDate reportedSpeciesReference
AustraliaBorneo1963Pongo sp.36
BruneiUnknown1982Orangutan (Pongo pygmaeus)33
France1976Hamlyn monkey (Cercopithecus hamlyni) Patas monkey (Erythrocebus patas)11
Great BritainPhilippines and Indonesia1992Cynomolgus monkey (Macaca fascicularis)10
38
MalaysiaUnknown1966Macaca spp.30
Unknown1968Spider monkey (Brachytelis arachnoides) Lar gibbon (Hylobates lar)20
Unknown1969Pig-tailed macaque (Macaca nemestrina)35
Unknown1984Banded leaf monkey (Presbytis melalophos)25
SingaporeUnknown1995Gorillas, gibbon, mandrill, chimpanzee43
ThailandUnknown2012Monkey19
United StatesThailand1970Stump-tailed macaque (Macaca arctoides)17
IndiaPig-tailed macaque (Macaca nemestrina)
AfricaRhesus macaque (Macaca mulatta) Chimpanzee (Pan troglodytes)
Unknown1971Chimpanzee (Pan troglodytes)3
Malaysia1981Pig-tailed macaque (Macaca nemestrina)2
Wild-caught, unknown1986Rhesus macaque (Macaca mulatta)13
Indonesia2013Pig-tailed macaque (Macaca nemestrina)Current article
Open in a separate windowaCountry reflects the location where the animal was housed at the time of diagosis.Here we describe a case of melioidosis diagnosed in a pigtail macaque (Macaca nemestrina) imported into the United States from Indonesia and the implications of the detection of a select agent identified in a laboratory research colony. We also discuss the management and care of the exposed colony, zoonotic concerns regarding the animal care staff that worked with the shipment of macaques, effects on research studies, and the procedures involved in reporting a select agent incident.  相似文献   

2.
Mesenchymal stem cells (MSC) are adult-derived multipotent stem cells that have been derived from almost every tissue. They are classically defined as spindle-shaped, plastic-adherent cells capable of adipogenic, chondrogenic, and osteogenic differentiation. This capacity for trilineage differentiation has been the foundation for research into the use of MSC to regenerate damaged tissues. Recent studies have shown that MSC interact with cells of the immune system and modulate their function. Although many of the details underlying the mechanisms by which MSC modulate the immune system have been defined for human and rodent (mouse and rat) MSC, much less is known about MSC from other veterinary species. This knowledge gap is particularly important because the clinical use of MSC in veterinary medicine is increasing and far exceeds the use of MSC in human medicine. It is crucial to determine how MSC modulate the immune system for each animal species as well as for MSC derived from any given tissue source. A comparative approach provides a unique translational opportunity to bring novel cell-based therapies to the veterinary market as well as enhance the utility of animal models for human disorders. The current review covers what is currently known about MSC and their immunomodulatory functions in veterinary species, excluding laboratory rodents.Abbreviations: AT, adipose tissue; BM, Bone marrow; CB, umbilical cord blood; CT, umbilical cord tissue; DC, dendritic cell; IDO, indoleamine 2;3-dioxygenase; MSC, mesenchymal stem cells; PGE2, prostaglandin E2; VEGF, vascular endothelial growth factorMesenchymal stem cells (MSC, alternatively known as mesenchymal stromal cells) were first reported in the literature in 1968.39 MSC are thought to be of pericyte origin (cells that line the vasculature)21,22 and typically are isolated from highly vascular tissues. In humans and mice, MSC have been isolated from fat, placental tissues (placenta, Wharton jelly, umbilical cord, umbilical cord blood), hair follicles, tendon, synovial membrane, periodontal ligament, and every major organ (brain, spleen, liver, kidney, lung, bone marrow, muscle, thymus, pancreas, skin).23,121 For most current clinical applications, MSC are isolated from adipose tissue (AT), bone marrow (BM), umbilical cord blood (CB), and umbilical cord tissue (CT; 11,87,99 Clinical trials in human medicine focus on the use of MSC both for their antiinflammatory properties (graft-versus-host disease, irritable bowel syndrome) and their ability to aid in tissue and bone regeneration in combination with growth factors and bone scaffolds (clinicaltrials.gov).131 For tissue regeneration, the abilities of MSC to differentiate and to secrete mediators and interact with cells of the immune system likely contribute to tissue healing (Figure 1). The current review will not address the specific use of MSC for orthopedic applications and tissue regeneration, although the topic is covered widely in current literature for both human and veterinary medicine.57,62,90

Table 1.

Tissues from which MSC have been isolated
Tissue source (reference no.)
SpeciesFatBone marrowCord bloodCord tissueOther
Cat1348356
Chicken63
Cow13812108
Dog973, 5978, 119139Periodontal ligament65
Goat66964
Horse26, 13037, 40, 12367130Periodontal ligament and gingiva88
Nonhuman primate28, 545
Pig1351147014, 20, 91
Rabbit1288032Fetal liver93
Sheep849542, 55
Open in a separate windowOpen in a separate windowFigure 1.The dual roles of MSC: differentiation and modulation of inflammation.Long-term studies in veterinary species have shown no adverse effects with the administration of MSC in a large number of animals.9,10,53 Smaller, controlled studies on veterinary species have shown few adverse effects, such as minor localized inflammation after MSC administration in vivo.7,15,17,45,86,92,98 Private companies, educational institutions, and private veterinary clinics (including Tufts University, Cummins School of Veterinary Medicine, University of California Davis School of Veterinary Medicine, VetStem, Celavet, Alamo Pintado Equine Medical Center, and Rood and Riddle Equine Hospital) offer MSC as a clinical treatment for veterinary species. Clinical uses include tendon and cartilage injuries, tendonitis, and osteoarthritis and, to a lesser extent, bone regeneration, spinal cord injuries, and liver disease in both large and small animals.38,41,113 Even with this broad clinical use, there have been no reports of severe adverse effects secondary to MSC administration in veterinary patients.  相似文献   

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Time-lapse fluorescence microscopy is one of the main tools used to image subcellular structures in living cells. Yet for decades it has been applied primarily to in vitro model systems. Thanks to the most recent advancements in intravital microscopy, this approach has finally been extended to live rodents. This represents a major breakthrough that will provide unprecedented new opportunities to study mammalian cell biology in vivo and has already provided new insight in the fields of neurobiology, immunology, and cancer biology.The discovery of GFP combined with the ability to engineer its expression in living cells has revolutionized mammalian cell biology (Chalfie et al., 1994). Since its introduction, several light microscopy–based techniques have become invaluable tools to investigate intracellular events (Lippincott-Schwartz, 2011). Among them are: time-lapse confocal microscopy, which has been instrumental in studying the dynamics of cellular and subcellular processes (Hirschberg et al., 1998; Jakobs, 2006; Cardarelli and Gratton, 2010); FRAP, which has enabled determining various biophysical properties of proteins in living cells (Berkovich et al., 2011); and fluorescence resonance energy transfer (FRET), which has been used to probe for protein–protein interactions and the local activation of specific signaling pathways (Balla, 2009). The continuous search for improvements in temporal and spatial resolution has led to the development of more sophisticated technologies, such as spinning disk microscopy, which allows the resolution of fast cellular events that occur on the order of milliseconds (Nakano, 2002); total internal reflection microscopy (TIRF), which enables imaging events in close proximity (100 nm) to the plasma membrane (Cocucci et al., 2012); and super-resolution microscopy (SIM, PALM, and STORM), which captures images with resolution higher than the diffraction limit of light (Lippincott-Schwartz, 2011).Most of these techniques have been primarily applied to in vitro model systems, such as cells grown on solid substrates or in 3D matrices, explanted embryos, and organ cultures. These systems, which are relatively easy to maintain and to manipulate either pharmacologically or genetically, have been instrumental in providing fundamental information about cellular events down to the molecular level. However, they often fail to reconstitute the complex architecture and physiology of multicellular tissues in vivo. Indeed, in a live organism, cells exhibit a 3D organization, interact with different cell types, and are constantly exposed to a multitude of signals originated from the vasculature, the central nervous system, and the extracellular environment. For this reason, scientists have been attracted by the possibility of imaging biological processes in live multicellular organisms (i.e., intravital microscopy [IVM]). The first attempt in this direction was in 1839, when Rudolph Wagner described the interaction of leukocytes with the walls of blood vessels in the webbed feet of a live frog by using bright-field transillumination (Wagner, 1839). Since then, this approach has been used for over a century to study vascular biology in thin areas of surgically exposed organs (Irwin and MacDonald, 1953; Zweifach, 1954) or by implanting optical windows in the skin or the ears (Clark and Clark, 1932). In addition, cell migration has also been investigated using transparent tissues, such as the fin of the teleost (Wood and Thorogood, 1984; Thorogood and Wood, 1987). The introduction of epifluorescence microscopy has enabled following in more detail the dynamics of individual cells in circulation (Nuttall, 1987), in tumors (MacDonald et al., 1992), or in the immune system (von Andrian, 1996), and the spatial resolution has been significantly improved by the use of confocal microscopy, which has made it possible to collect serial optical sections from a given specimen (Villringer et al., 1989; O’Rourke and Fraser, 1990; Jester et al., 1991). However, these techniques can resolve structures only within a few micrometers from the surface of optically opaque tissues (Masedunskas et al., 2012a). It was only in the early nineteen nineties, with the development of multiphoton microscopy, that deep tissue imaging has become possible (Denk et al., 1990; Zipfel et al., 2003b), significantly contributing to several fields, including neurobiology, immunology, and cancer biology (Fig. 1; Svoboda and Yasuda, 2006; Amornphimoltham et al., 2011; Beerling et al., 2011). In the last few years, the development of strategies to minimize the motion artifacts caused by the heartbeat and respiration has made it possible to successfully image subcellular structures with spatial and temporal resolutions comparable to those achieved in in vitro model systems, thus providing the opportunity to study cell biology in live mammalian tissues (Fig. 1; Weigert et al., 2010; Pittet and Weissleder, 2011).Open in a separate windowFigure 1.Spatial resolution and current applications of intravital microscopy. IVM provides the opportunity to image several biological processes in live animals at different levels of resolution. Low-magnification objectives (5–10×) enable visualizing tissues and their components under physiological conditions and measuring their response under pathological conditions. Particularly, the dynamics of the vasculature have been one of topic most extensively studied by IVM. Objectives with higher magnification (20–30×) have enabled imaging the behavior of individual cell over long periods of time. This has led to major breakthroughs in fields such as neurobiology, immunology, cancer biology, and stem cell research. Finally, the recent developments of strategies to minimize the motion artifacts caused by the heartbeat and respiration combined with high power lenses (60–100×) have opened the door to image subcellular structures and to study cell biology in live animals.The aim of this review is to highlight the power of IVM in addressing cell biological questions that cannot be otherwise answered in vitro, due to the intrinsic limitations of reductionist models, or by other more classical approaches. Furthermore, we discuss limitations and areas for improvement of this imaging technique, hoping to provide cell biologists with the basis to assess whether IVM is the appropriate choice to address their scientific questions.

Imaging techniques currently used to perform intravital microscopy

Confocal and two-photon microscopy are the most widely used techniques to perform IVM. Confocal microscopy, which is based on single photon excitation, is a well-established technique (Fig. 2 A) that has been extensively discussed elsewhere (Wilson, 2002); hence we will only briefly describe some of the main features of two-photon microscopy and other nonlinear optical techniques.Open in a separate windowFigure 2.Fluorescent light microscopy imaging techniques used for intravital microscopy. (A) Confocal microscopy. (top) In confocal microscopy, a fluorophore absorbs a single photon with a wavelength in the UV-visible range of the spectrum (blue arrow). After a vibrational relaxation (orange curved arrow), a photon with a wavelength shifted toward the red is emitted (green arrow). (center) In thick tissue, excitation and emission occur in a relative large volume around the focal plane (F.P.). The off-focus emissions are eliminated through a pinhole, and the signal from the focal plane is detected via a photomultiplier (PMT). Confocal microscopy enables imaging at a maximal depth to 80–100 µm. (bottom) Confocal z stack of the tongue of a mouse expressing the membrane marker m-GFP (green) in the K14-positive basal epithelial layer, and the membrane marker mTomato in the endothelium (red). The xy view shows a maximal projection of 40 z slices acquired every 2.5 µm, whereas the xz view shows a lateral view of the stack. In blue are the nuclei labeled by a systemic injection of Hoechst. Excitation wavelengths: 450 nm, 488 nm, and 562 nm. (B) Two- and three-photon microscopy. (top) In this process a fluorophore absorbs almost simultaneously two or three photons that have half (red arrow) or a third (dark red arrow) of the energy required for its excitation with a single photon. Two- or three-photon excitations typically require near-IR or IR light (from 690 to 1,600 nm). (center) Emission and excitation occur only at the focal plane in a restricted volume (1.5 fl), and for this reason a pinhole is not required. Two- and three-photon microscopy enable imaging routinely at a maximal depth of 300–500 µm. (bottom) Two-photon z stack of an area adjacent to that imaged in A. xy view shows a maximal projection of 70 slices acquired every 5 µm. xz view shows a lateral view of the stack. Excitation wavelength: 840 nm. (C) SHG and THG. (top) In SHG and THG, photons interact with the specimen and combine to form new photons that are emitted with twice or three times their initial energy without any energy loss. (center) These processes have similar features to those described for two- and three-photon microscopy and enable imaging at a maximal depth of 200–400 µm. (bottom) z stack of a rat heart excited by two-photon microscopy (740 nm) to reveal the parenchyma (green), and SHG (930 nm) to reveal collagen fibers (red). xy shows a maximal projection of 20 slices acquired every 5 µm. xz view shows a lateral view of the stack. Bars: (xy views) 40 µm; (xz views) 50 µm.The first two-photon microscope (Denk et al., 1990) was based on the principle of two-photon excitation postulated by Maria Göppert-Mayer in her PhD thesis (Göppert-Mayer, 1931). In this process a fluorophore is excited by the simultaneous absorption of two photons with wavelengths in the near-infrared (IR) or IR spectrum (from 690 to 1,600 nm; Fig. 2 B). Two-photon excitation requires high-intensity light that is provided by lasers generating very short pulses (in the femtosecond range) and is focused on the excitation spot by high numerical aperture lenses (Zipfel et al., 2003b). There are three main advantages in using two-photon excitation for IVM. First, IR light has a deeper tissue penetration than UV or visible light (Theer and Denk, 2006). Indeed, two-photon microscopy can resolve structures up to a depth of 300–500 µm in most of the tissues (Fig. 2 B), and up to 1.5 mm in the brain (Theer et al., 2003; Masedunskas et al., 2012a), whereas confocal microscopy is limited to 80–100 µm (Fig. 2 A). Second, the excitation is restricted to a very small volume (1.5 fl; Fig. 2 B). This implies that in two-photon microscopy there is no need to eliminate off-focus signals, and that under the appropriate conditions photobleaching and phototoxicity are negligible (Zipfel et al., 2003b). However, confocal microscopy induces out-of-focus photodamage, and thus is less suited for long-term imaging. Third, selected endogenous molecules can be excited, thus providing the contrast to visualize specific biological structures without the need for exogenous labeling (Zipfel et al., 2003a). Some of these molecules can also be excited by confocal microscopy using UV light, although with the risk of inducing photodamage.More recently, other nonlinear optical techniques have been used for IVM, and among them are three-photon excitation, and second and third harmonic generation (SHG and THG; Campagnola and Loew, 2003; Zipfel et al., 2003b; Oheim et al., 2006). Three-photon excitation follows the same principle as two-photon (Fig. 2 B), and can reveal endogenous molecules such as serotonin and melatonin (Zipfel et al., 2003a; Ritsma et al., 2013). In SHG and THG, photons interact with the specimen and combine to form new photons that are emitted with two or three times their initial energy (Fig. 2 C). SHG reveals collagen (Fig. 2 C) and myosin fibers (Campagnola and Loew, 2003), whereas THG reveals lipid droplets and myelin fibers (Débarre et al., 2006; Weigelin et al., 2012). Recently, two other techniques have been used for IVM: coherent anti-Stokes Raman scattering (CARS) and fluorescence lifetime imaging (FLIM). CARS that is based on two laser beams combined to match the energy gap between two vibrational levels of the molecule of interest, has been used to image lipids and myelin fibers (Müller and Zumbusch, 2007; Fu et al., 2008; Le et al., 2010). FLIM, which measures the lifetime that a molecule spends in the excited state, provides quantitative information on cellular parameters such as pH, oxygen levels, ion concentration, and the metabolic state of various biomolecules (Levitt et al., 2009; Provenzano et al., 2009; Bakker et al., 2012).We want to emphasize that two-photon microscopy and the other nonlinear techniques are the obligatory choice when the imaging area is located deep inside the tissue, endogenous molecules have to be imaged, or long-term imaging with frequent sampling is required. However, confocal microscopy is more suited to resolve structures in the micrometer range, because of the possibility of modulating the optical slice (Masedunskas et al., 2012a).

IVM to investigate biological processes at the tissue and the single cell level

The main strength of IVM is to provide information on the dynamics of biological processes that otherwise cannot be reconstituted in vitro or ex vivo. Indeed, IVM has been instrumental in studying several aspects of tissue physiopathology (Fig. 3, A and B). Although other approaches such as classical immunohistochemistry, electron microscopy, and indirect immunofluorescence may provide detailed structural and quantitative information on blood vessels, IVM enables measuring events such as variations of blood flow at the level of the capillaries or local changes in blood vessel permeability. These data have been instrumental in understanding the mechanisms of ischemic diseases and tumor progression, and in designing effective anticancer treatments.

Table 1.

IVM to study tissue physiopathology
EventOrganProbesReference
Measurements of local blood flow and glial cell functionBrainDextranHelmchen and Kleinfeld, 2008
Ischemia and reperfusionBrainSulphorhodamine 101, DextranZhang and Murphy, 2007; Masamoto et al., 2012;
Glomerular filtration and tubular reabsorptionKidneyDextran, AlbuminKang et al., 2006; Yu et al., 2007; Camirand et al., 2011
Blood flow patternsPancreatic isletsDextranNyman et al., 2008
Capillary response and synaptic activationOlfactory bulbDextranChaigneau et al., 2003
Imaging angiogenesis during wound healingSkullcapDextranHolstein et al., 2011
Pulmonary microvasculature and endothelial activationLungDextranPresson et al., 2011
Morphology of blood vessels and permeability in tumorsXenograftsDextran, RGD quantum dotsTozer et al., 2005; Smith et al., 2008; Vakoc et al., 2009; Fukumura et al., 2010
Hepatic transport into the bile canaliculiLiverCarboxyfluorescein diacetate Rhodamine 123Babbey et al., 2012; Liu et al., 2012
Progression of amyloid plaques in Alzheimer’s diseaseBrainCurcumin and metoxy-04Spires et al., 2005; Garcia-Alloza et al., 2007
Mitochondrial membrane potentialLiverTetramethylrhodamine methyl ester Rhodamine 123Theruvath et al., 2008; Zhong et al., 2008
Oxygen consumptionLiverRu(phen3)2+Paxian et al., 2004
Sarcomere contraction in humansSkeletal muscleEndogenous fluorescenceLlewellyn et al., 2008
Open in a separate windowOpen in a separate windowFigure 3.Imaging tissues and individual cells in live animals. (A) The vasculature of an immunocompromised mouse was highlighted by the systemic injection of 2 MD dextran (red) before (left) and after (right) the implant of breast cancer cells in the back (green). Note the change in shape of the blood vessels and their increased permeability (arrow). Images were acquired by two-photon microscopy (excitation wavelength: 930 nm). (B) The microvasculature in the liver of a mouse expressing the membrane marker mTomato (red) was highlighted by the injection of cascade blue dextran (blue) and imaged by confocal microscopy (excitation wavelengths: 405 nm and 561 nm). Note the red blood cells that do not uptake the dye and appear as dark objects in the blood stream (arrow). (C) Metastatic and nonmetastatic human adenocarcinoma cells were injected in the tongue of an immunocompromised mouse and imaged for four consecutive days by using two-photon microscopy (excitation wavelength: 930 nm). The metastatic cells, which express the fluorescent protein mCherry (red), migrate away from the edge of the tumor (arrows), whereas the nonmetastatic cells, which express the fluorescent protein Venus (green), do not. (D) A granulocyte moving inside a blood vessel in the mammary gland of a mouse expressing GFP-tagged myosin IIb (green) and labeled with the mitochondrial vital dye MitoTracker (red) was imaged in time lapse by using confocal microscopy (excitation wavelengths: 488 nm and 561 nm). Figure corresponds to Video 1. Time is expressed as minutes:seconds. Bars: (A) 100 µm; (B) 10 µm; (C) 30 µm; (D) 10 µm.IVM has also been used successfully to study the dynamics and the morphological changes of individual cells within a tissue (
EventOrganProbeReference
Neuronal morphology of hippocampal neuronsBrainThy1-GFP mice, dextranBarretto et al., 2011
Neuronal circuitryBrainBrainbow miceLivet et al., 2007
Dendritic spine development in the cortexBrainYFP H-line micePan and Gan, 2008
Calcium imaging in the brainBrainGCAMPZariwala et al., 2012
Natural killer cell and cytotoxic T cell interactions with tumorsXenograftmCFP , mYFPDeguine et al., 2010
Neutrophil recruitment in beating heartHeartDextran, CX3CR1-GFP miceLi et al., 2012
Immune cells in the central nervous systemBrainDextran, CX3CR1-GFP, LysM-GFP and CD11c-YFP miceNayak et al., 2012
Dendritic cells migrationSkinYFP, VE-caherin RFP mice, dextranNitschké et al., 2012
CD8+ T cells interaction with dendritic cells during viral infectionLymph nodesEGFP, Dextran, SHGHickman et al., 2008
B cells and dendritic cells interactions outside lymph nodesLymph nodesEGFPQi et al., 2006
Change in gene expression during metastasisXenograftPinner et al., 2009
Invasion and metastasis in head and neck cancerXenograftYFP, RFP-lifeact, dextranAmornphimoltham et al., 2013
Fibrosarcoma cell migration along collagen fibersDorsal skin chamberSHG, EGFP, DsRed, DextranAlexander et al., 2008
Long term imaging mammary tumors and photo-switchable probesMammary windowDendra-2Kedrin et al., 2008; Gligorijevic et al., 2009
Long term imaging liver metastasis through abdominal windowLiverSHG, Dendra2, EGFPRitsma et al., 2012b
Macrophages during intravasation in mammary tumorsXenograftEGFP, SHG, dextransWang et al., 2007; Wyckoff et al., 2007
Melanoma collective migrationDorsal skin ChamberSHG, THG, EGFP, DextranWeigelin et al., 2012
Hematopoietic stem cells and blood vesselSkullcupDextranLo Celso et al., 2009
Epithelial stem cells during hair regenerationSkinH2B-GFP miceRompolas et al., 2012
Open in a separate windowIn neurobiology, for example, the development of approaches to perform long-term in vivo imaging has permitted the correlation of changes in neuronal morphology and neuronal circuitry to pathological conditions such as stroke (Zhang and Murphy, 2007), tumors (Barretto et al., 2011), neurodegenerative diseases (Merlini et al., 2012), and infections (McGavern and Kang, 2011). This has been accomplished by the establishment of surgical procedures to expose the brain cortex, and the implantation of chronic ports of observations such as cranial windows and imaging guide tubes for micro-optical probes (Svoboda and Yasuda, 2006; Xu et al., 2007; Barretto et al., 2011). In addition, this field has thrived thanks to the development of several transgenic mouse models harboring specific neuronal populations expressing either one or multiple fluorescent molecules (Svoboda and Yasuda, 2006; Livet et al., 2007).In tumor biology, the ability to visualize the motility of cancer cells within a tumor in vivo has provided tremendous information on the mechanisms regulating invasion and metastasis (Fig. 3 C; Beerling et al., 2011). Tumor cells metastasize to distal sites by using a combination of processes, which include tumor outgrowth, vascular intravasation, lymphatic invasion, or migration along components of the extracellular matrix and nerve fibers. Although classical histological analysis and indirect immunofluorescence have been routinely used to study these processes, the ability to perform long-term IVM through the optimization of optical windows (Alexander et al., 2008; Kedrin et al., 2008; Gligorijevic et al., 2009; Ritsma et al., 2012b) has provided unique insights. For example, a longitudinal study performed by using a combination of two-photon microscopy, SHG, and THG has highlighted the fact that various tissue components associated with melanomas may play either a migration-enhancing or migration-impeding role during collective cell invasion (Weigelin et al., 2012). In mammary tumors, the intravasation of metastatic cells has been shown to require macrophages (Wang et al., 2007; Wyckoff et al., 2007). In head and neck cancer, cells have been shown to migrate from specific sites at the edge of the tumor, and to colonize the cervical lymph nodes by migrating though the lymphatic vessels (Fig. 3 C; Amornphimoltham et al., 2013). In highly invasive melanomas, the migratory ability of cells has been correlated with their differentiation state, as determined by the expression of a reporter for melanin expression (Pinner et al., 2009).Imaging the cells of the immune system in a live animal has revealed novel qualitative and quantitative aspects of the dynamics of cellular immunity (Fig. 2 C and Video 1; Germain et al., 2005; Cahalan and Parker, 2008; Nitschke et al., 2008). Indeed, the very complex nature of the immune response, the involvement of a multitude of tissue components, and its tight spatial and temporal coordination clearly indicate that IVM is the most suited approach to study cellular immunity. This is highlighted in studies either in lymphoid tissues, where the exquisite coordination between cell–cell interactions and cell signaling has been studied during the interactions of B lymphocytes and T cell lymphoid tissues (Qi et al., 2006), T cell activation (Hickman et al., 2008; Friedman et al., 2010), and migration of dendritic cells (Nitschké et al., 2012), or outside lymphoid tissues, such as, for example, brain during pathogen infections (Nayak et al., 2012), heart during inflammation (Li et al., 2012), and solid tumors (Deguine et al., 2010).

Imaging subcellular structures in vivo and its application to cell biology

The examples described so far convey that IVM has contributed to unraveling how the unique properties of the tissue environment in vivo significantly regulate the dynamics of individual cells and ultimately tissue physiology. Is IVM suitable to determine (1) how subcellular events occur in vivo, (2) whether they differ in in vitro settings, and (3), finally, the nature of their contribution to tissue physiology?IVM has been extensively used to image subcellular structures in smaller organisms (i.e., zebrafish, Caenorhabditis elegans) that are transparent and can be easily immobilized (Rohde and Yanik, 2011; Tserevelakis et al., 2011; Hove and Craig, 2012). In addition, the ability to easily perform genetic manipulations has made these systems extremely attractive to study several aspects of developmental and cell biology. However, their differences in term of organ physiology with respect to rodents do not make them suitable models for human diseases. For a long time, subcellular imaging in live rodents has been hampered by the motion artifacts derived from the heartbeat and respiration. Indeed, small shifts along the three axes make it practically impossible to visualize structures whose sizes are in the micrometer or submicrometer range, whereas it marginally affects larger structures. This issue has been only recently addressed by using a combination of strategies, which include: (1) the development of specific surgical procedures that allow the exposure and proper positioning of the organ of interest (Masedunskas et al., 2013), (2) the improvement of specific organ holders (Cao et al., 2012; Masedunskas et al., 2012a), and (3) the synchronization of the imaging acquisition with the heartbeat and respiration (Presson et al., 2011; Li et al., 2012). Very importantly, these approaches have been successfully implemented without compromising the integrity and the physiology of the tissue, thus opening the door to study cell biology in a live animal.For example, large subcellular structures such as the nuclei have been easily imaged, making it possible to study processes such as cell division and apoptosis (Fig. 4 A; Goetz et al., 2011; Orth et al., 2011; Rompolas et al., 2012). Interestingly, these studies have highlighted the fact that the in vivo microenvironment substantially affects nuclear dynamics. Indeed, mitosis and the structure of the mitotic spindle were followed over time in a xenograft model of human cancer expressing the histone marker mCherry-H2B and GFP-tubulin (Orth et al., 2011). Specifically, the effects of the anticancer drug Paclitaxel were studied, revealing that the tumor cells in vivo have a higher mitotic index and lower pro-apoptotic propensity than in vitro (Orth et al., 2011). FRET has been used in subcutaneous tumors to image cytotoxic T lymphocyte–induced apoptosis and highlighted that the kinetics of this process are much slower than those reported for nontumor cells in vivo that are exposed to a different microenvironment (Breart et al., 2008). Cell division has also been followed in the hair-follicle stem cells of transgenic mice expressing GFP-H2B. This study determined that epithelial–mesenchymal interactions are essential for stem cell activation and regeneration, and that nuclear divisions occur in a specific area of the hair follicles and are oriented toward the axis of growth (Rompolas et al., 2012). These processes show an extremely high level of temporal and spatial organization that can only be appreciated in vivo and by using time-lapse imaging.Open in a separate windowFigure 4.Imaging subcellular events in live animals. (A) Human squamous carcinoma cells were engineered to stably express the Fucci cell cycle reporter into the nucleus and injected in the back of an immunocompromised mouse. After 1 wk, the tumor was imaged by two-photon microscopy and SHG (excitation wavelength: 930 nm). (top) Maximal projection of a z stack (xy view). Cells in G2/M are in green, cells in G1 are in red, and collagen fibers are in cyan. (bottom) Lateral view (xz) of a z stack. (B) Clusters of GLUT4-containing vesicles (green) in the soleus muscle of a transgenic mouse expressing GFP-GLUT4 and injected with 70 kD Texas red–dextran to visualize the vasculature and imaged by two-photon microscopy (excitation wavelength: 930 nm). (C) Confocal microscopy (excitation wavelength: 488 nm) of hepatocytes in the liver of a transgenic mouse expressing the autophagy marker GFP-LC3. The inset shows small GFP-LC3 autophagic vesicles. (D–G) Dynamics of intracellular compartments imaged by time-lapse two-photon (E) or confocal microscopy (D, F, and G). (D) Endocytosis of systemically injected 10 kD Texas red–dextran into the kidney of a transgenic mouse expressing the membrane marker m-GFP. The dextran (red) is transported from the microvasculature into the proximal tubuli, and then internalized in small endocytic vesicles (arrows; Video 2). (E) Endocytosis of a systemically injected 10 kD of Alexa Fluor 488 dextran into the salivary glands of a live rat. The dextran (green) diffuses from the vasculature into the stroma, and it is internalized by stromal cells (insets). Collagen fibers (red) are highlighted by SHG. (F) Regulated exocytosis of large secretory granules in the salivary glands of a live transgenic mouse expressing cytoplasmic GFP. The GFP is excluded from the secretory granules and accumulates on their limiting membranes (arrows) after fusion with the plasma membrane (broken lines). The gradual collapse of an individual granule is highlighted in the insets. (G) Dynamics of mitochondria labeled with the membrane potential dye TMRM in the salivary glands of a live mouse. Time is expressed as minutes:seconds. Bars: (A) 40 µm; (B) 15 µm; (C, D, E, and G) 10 µm; (F) 5 µm.Imaging membrane trafficking has been more challenging because of its dynamic nature and the size of the structures to image. The first successful attempt to visualize membrane traffic events was achieved in the kidney of live rats by using two-photon microscopy where the endocytosis of fluid-phase markers, such as dextrans, or the receptor-mediated uptake of folate, albumin, and the aminoglycoside gentamicin were followed in the proximal tubuli (Fig. 4 D and Video 2; Dunn et al., 2002; Sandoval et al., 2004; Russo et al., 2007). These pioneering studies showed for the first time that apical uptake is involved in the filtration of large molecules in the kidney, whereas previously it was believed to be exclusively due to a barrier in the glomerular capillary wall. However, in the kidney the residual motion artifacts limited the imaging to short periods of time. Recently, the salivary glands have proven to be a suitable organ to study the dynamics of membrane trafficking by using either two-photon or confocal microscopy. Systemically injected dextrans, BSA, and transferrin were observed to rapidly internalize in the stromal cells surrounding the salivary gland epithelium in a process dependent on the actin cytoskeleton (Masedunskas and Weigert, 2008; Masedunskas et al., 2012b). Moreover, the trafficking of these molecules through the endo-lysosomal system was documented, providing interesting insights on early endosomal fusion (Fig. 4 E; Masedunskas and Weigert, 2008; Masedunskas et al., 2012b). Notably, significant differences were observed in the kinetics of internalization of transferrin and dextran. In vivo, dextran was rapidly internalized by stromal cells, whereas transferrin appeared in endosomal structures after 10–15 min. However, in freshly explanted stromal cells adherent on glass, transferrin was internalized within 1 min, whereas dextran appeared in endosomal structures after 10–15 min. Although the reasons for this difference were not addressed, it is clear that the environment in vivo has profound effects on the regulation of intracellular processes (Masedunskas et al., 2012b). Similar differences have been reported for the caveolae that in vivo are more dynamic than in cell cultures (Thomsen et al., 2002; Oh et al., 2007). Endocytosis has also been investigated in the epithelium of the salivary glands (Sramkova et al., 2009). Specifically, plasmid DNA was shown to be internalized by a clathrin-independent pathway from the apical plasma membrane of acinar and ductal cells, and to subsequently escape from the endo-lysosomal system, thus providing useful information on the mechanisms of nonviral gene delivery in vivo (Sramkova et al., 2012). Receptor-mediated endocytosis has also been studied in cancer models. Indeed, the uptake of a fluorescent EGF conjugated to carbon nanotubes has been followed in xenografts of head and neck cancer cells revealing that the internalization occurs primarily in cells that express high levels of EGFR (Bhirde et al., 2009). The role of endosomal recycling has also been investigated during tumor progression. Indeed, the small GTPase Rab25 was found to regulate the ability of head neck cancer cells to migrate to lymph nodes by controlling the dynamic assembly of plasma membrane actin reach protrusion in vivo (Amornphimoltham et al., 2013). Interestingly, this activity of Rab25 was reconstituted in cells migrating through a 3D collagen matrix but not in cells grown adherent to a solid substrate.IVM has been a powerful tool in investigating the molecular machinery controlling regulated exocytosis in various organs. In salivary glands, the use of selected transgenic mice expressing either soluble GFP or a membrane-targeted peptide has permitted the characterization of the dynamics of exocytosis of the secretory granules after fusion with the plasma membrane (Fig. 4 E; Masedunskas et al., 2011a, 2012d). These studies revealed that the regulation and the modality of exocytosis differ between in vivo and in vitro systems. Indeed, in vivo, regulated exocytosis is controlled by stimulation of the β-adrenergic receptor, and secretory granules undergo a gradual collapse after fusion with the apical plasma membrane, whereas, in vitro, regulated exocytosis is also controlled by the muscarinic receptor and the secretory granules fuse to each other, forming strings of interconnected vesicles at the plasma membrane (compound exocytosis; Masedunskas et al., 2011a, 2012d). Moreover, the transient expression of reporter molecules for F-actin has revealed the requirement for the assembly of an actomyosin complex to facilitate the completion of the exocytic process (Masedunskas et al., 2011a, 2012d). This result underscores the fact that the dynamics of the assembly of the actin cytoskeleton can be studied both qualitatively and quantitatively in live animals at the level of individual secretory granules. In addition, this approach has highlighted some of the mechanisms that contribute to regulate the apical plasma membrane homeostasis in vivo that cannot be recapitulated in an in vitro model systems (Masedunskas et al., 2011b, 2012c; Porat-Shliom et al., 2013). Indeed, the hydrostatic pressure that is built inside the ductal system by the secretion of fluids that accompanies exocytosis plays a significant role in controlling the dynamics of secretory granules at the apical plasma membrane. This aspect has never been appreciated in organ explants where the integrity of the ductal system is compromised. Finally, a very promising model has been developed in the skeletal muscle, where the transient transfection of a GFP-tagged version of the glucose transporter type 4 (GLUT4) has made possible to characterize the kinetics of the GLUT4-containing vesicles in resting conditions and their insulin-dependent translocation to the plasma membrane (Fig. 4 B; Lauritzen et al., 2008, 2010). This represents a very powerful experimental model that bridges together physiology and cell biology and has the potential to provide fundamental information on metabolic diseases.These examples underscore the merits of subcellular IVM to investigate specific areas of cell biology such as membrane trafficking, the cell cycle, apoptosis, and cytoskeletal organization. However, IVM is rapidly extending to other areas, such as cell signaling (Stockholm et al., 2005; Rudolf et al., 2006; Ritsma et al., 2012a), metabolism (Fig. 4 C; Débarre et al., 2006; Cao et al., 2012), mitochondrial dynamics (Fig. 4 F; Sun et al., 2005; Hall et al., 2013), or gene and protein expression (Pinner et al., 2009) that have just begun to be explored.

Future perspectives

IVM has become a powerful tool to study biological processes in live animals that is destined to have an enormous impact on cell biology. The examples described here give a clear picture of the broad applicability of this approach. In essence, we foresee that IVM is going to be the obligatory choice to study highly dynamic subcellular processes that cannot be reconstituted in vitro or ex vivo, or when a link between cellular events and tissue physiopathology is being pursued. In addition, IVM will provide the opportunity to complement and confirm data generated from in vitro studies. Importantly, the fact that in several instances confocal microscopy can be effectively used for subcellular IVM makes this approach immediately accessible to several investigators.In terms of future directions, we envision that other light microscopy techniques will soon become standard tools for in vivo studies, as shown by the recent application of FRET to study signaling (Stockholm et al., 2005; Rudolf et al., 2006; Breart et al., 2008; Ritsma et al., 2012a), and FRAP, which has been used in the live brain to measure the diffusion of α synuclein, thus opening the door to studying the biophysical properties of proteins in vivo (Unni et al., 2010). Moreover, super-resolution microscopy may be applied for imaging live animals, although this task may pose some challenges. Indeed, these techniques require: (1) the complete stability of the specimen, (2) extended periods of time for light collection, (3) substantial modifications to the existing microscopes, and (4) the generation of transgenic mice expressing photoactivatable probes.To reach its full potential, IVM has to further develop two main aspects: animal models and instrumentations. Indeed, a significant effort has to be invested in developing novel transgenic mouse models, which express fluorescently labeled reporter molecules. One example is the recently developed mouse that expresses fluorescently tagged lifeact. This model will provide the unique opportunity to study F-actin dynamics in vivo in the context of processes such as cell migration and membrane trafficking (Riedl et al., 2010). Moreover, the possibility of crossing these reporter mice with knockout animals will provide the means to further study cellular processes at a molecular level. Alternatively, reporter molecules or other transgenes that may perturb a specific cellular pathway can be transiently transfected into live animals in several ways. Indeed, the remarkable advancements in gene therapy have contributed to the development of several nonviral- and viral-mediated strategies for gene delivery to selected target organs. In this respect, the salivary glands and the skeletal muscle are two formidable model systems because either transgenes or siRNAs can be successfully delivered without any adverse reaction and expressed in a few hours. In terms of the current technical limitations of IVM, the main areas of improvement are the temporal resolution, the ability to access the organ of interest with minimal invasion, and the ability to perform long-term imaging. As for the temporal resolution, the issue has begun to be addressed by using two different approaches: (1) the use of spinning disk microscopy, as shown by its recent application to image platelet dynamics in live mice (Jenne et al., 2011); and (2) the development of confocal and two-photon microscopes equipped with resonant scanners that permit increasing the scanning speed to 30 frames per second (Kirkpatrick et al., 2012). As for accessing the organs, recently several microlenses (350 µm in diameter) have been inserted or permanently implanted into live animals, minimizing the exposure of the organs and the risk of affecting their physiology (Llewellyn et al., 2008). Finally, although some approaches for the long-term imaging of the brain, the mammary glands, and the liver have been developed, additional effort has to be devoted to establish chronic ports of observations in other organs.In conclusion, these are truly exciting times, and a new era full of novel discoveries is just around the corner. The ability to see processes inside the cells of a live animal is no longer a dream.

Online supplemental material

Video 1 shows time-lapse confocal microscopy of a granulocyte moving inside a blood vessel in the mammary gland of a mouse expressing GFP-tagged myosin IIb (green) and labeled with MitoTracker (red). Video 2 shows time-lapse confocal microscopy of the endocytosis of systemically injected 10 kD Texas red–dextran (red) into the kidney-proximal tubuli of a transgenic mouse expressing the membrane marker m-GFP (green). Online supplemental material is available at http://www.jcb.org/cgi/content/full/jcb.201212130/DC1.  相似文献   

7.
Peaks cloaked in the mist: The landscape of mammalian replication origins     
Olivier Hyrien 《The Journal of cell biology》2015,208(2):147-160
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8.
Tethering Factors Required for Cytokinesis in Arabidopsis     
Martha Thellmann  Katarzyna Rybak  Knut Thiele  Gerhard Wanner  Farhah F. Assaad 《Plant physiology》2010,154(2):720-732
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9.
Tissue-Specific Expression Patterns of Arabidopsis NF-Y Transcription Factors Suggest Potential for Extensive Combinatorial Complexity          下载免费PDF全文
Nicholas Siefers  Kristen K. Dang  Roderick W. Kumimoto  William Edwards Bynum  IV  Gregory Tayrose  Ben F. Holt  III 《Plant physiology》2009,149(2):625-641
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10.
Monkey B Virus (Cercopithecine herpesvirus 1)     
David Elmore  Richard Eberle 《Comparative medicine》2008,58(1):11-21
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11.
Root System Markup Language: Toward a Unified Root Architecture Description Language   总被引:1,自引:0,他引:1  
Guillaume Lobet  Michael P. Pound  Julien Diener  Christophe Pradal  Xavier Draye  Christophe Godin  Mathieu Javaux  Daniel Leitner  Félicien Meunier  Philippe Nacry  Tony P. Pridmore  Andrea Schnepf 《Plant physiology》2015,167(3):617-627
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12.
Uniform nomenclature for the mitochondrial contact site and cristae organizing system     
Nikolaus Pfanner  Martin van der Laan  Paolo Amati  Roderick A. Capaldi  Amy A. Caudy  Agnieszka Chacinska  Manjula Darshi  Markus Deckers  Suzanne Hoppins  Tateo Icho  Stefan Jakobs  Jianguo Ji  Vera Kozjak-Pavlovic  Chris Meisinger  Paul R. Odgren  Sang Ki Park  Peter Rehling  Andreas S. Reichert  M. Saeed Sheikh  Susan S. Taylor  Nobuo Tsuchida  Alexander M. van der Bliek  Ida J. van der Klei  Jonathan S. Weissman  Benedikt Westermann  Jiping Zha  Walter Neupert  Jodi Nunnari 《The Journal of cell biology》2014,204(7):1083-1086
The mitochondrial inner membrane contains a large protein complex that functions in inner membrane organization and formation of membrane contact sites. The complex was variably named the mitochondrial contact site complex, mitochondrial inner membrane organizing system, mitochondrial organizing structure, or Mitofilin/Fcj1 complex. To facilitate future studies, we propose to unify the nomenclature and term the complex “mitochondrial contact site and cristae organizing system” and its subunits Mic10 to Mic60.Mitochondria possess two membranes of different architecture and function (Palade, 1952; Hackenbrock, 1968). Both membranes work together for essential shared functions, such as protein import (Schatz, 1996; Neupert and Herrmann, 2007; Chacinska et al., 2009). The outer membrane harbors machinery that controls the shape of the organelle and is crucial for the communication of mitochondria with the rest of the cell. The inner membrane harbors the complexes of the respiratory chain, the F1Fo-ATP synthase, numerous metabolite carriers, and enzymes of mitochondrial metabolism. It consists of two domains: the inner boundary membrane, which is adjacent to the outer membrane, and invaginations of different shape, termed cristae (Werner and Neupert, 1972; Frey and Mannella, 2000; Hoppins et al., 2007; Pellegrini and Scorrano, 2007; Zick et al., 2009; Davies et al., 2011). Tubular openings, termed crista junctions (Perkins et al., 1997), connect inner boundary membrane and cristae membranes (Fig. 1, A and B). Respiratory chain complexes and the F1Fo-ATP synthase are preferentially located in the cristae membranes, whereas preprotein translocases are enriched in the inner boundary membrane (Vogel et al., 2006; Wurm and Jakobs, 2006; Davies et al., 2011). Contact sites between outer membrane and inner boundary membrane promote import of preproteins, metabolite channeling, lipid transport, and membrane dynamics (Frey and Mannella, 2000; Sesaki and Jensen, 2004; Hoppins et al., 2007, 2011; Neupert and Herrmann, 2007; Chacinska et al., 2009; Connerth et al., 2012; van der Laan et al., 2012).Open in a separate windowFigure 1.MICOS complex. (A) The MICOS complex (hypothetical model), previously also termed MINOS, MitOS, or Mitofilin/Fcj1 complex, is required for maintenance of the characteristic architecture of the mitochondrial inner membrane (IM) and forms contact sites with the outer membrane (OM). In budding yeast, six subunits of MICOS have been identified. All subunits are exposed to the intermembrane space (IMS), five are integral inner membrane proteins (Mic10, Mic12, Mic26, Mic27, and Mic60), and one is a peripheral inner membrane protein (Mic19). Mic26 is related to Mic27; however, mic26Δ yeast cells show considerably less severe defects of mitochondrial inner membrane architecture than mic27Δ cells (Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011). The MICOS complex of metazoa additionally contains Mic25, which is related to Mic19, yet subunits corresponding to Mic12 and Mic26 have not been identified so far. MICOS subunits that have been conserved in most organisms analyzed are indicated by bold boundary lines. (B, top) Wild-type architecture of the mitochondrial inner membrane with crista junctions and cristae. (bottom) This architecture is considerably altered in micos mutant mitochondria: most cristae membranes are detached from the inner boundary membrane and form internal membrane stacks. In some micos mutants (deficiency of mammalian Mic19 or Mic25), a loss of cristae membranes was observed (Darshi et al., 2011; An et al., 2012). Figure by M. Bohnert (Institute of Biochemistry and Molecular Biology, University of Freiburg, Freiburg, Germany).To understand the complex architecture of mitochondria, it will be crucial to identify the molecular machineries that control the interaction between mitochondrial outer and inner membranes and the characteristic organization of the inner membrane. A convergence of independent studies led to the identification of a large heterooligomeric protein complex of the mitochondrial inner membrane conserved from yeast to humans that plays crucial roles in the maintenance of crista junctions, inner membrane architecture, and formation of contact sites to the outer membrane (Fig. 1 A). Several names were used by different research groups to describe the complex, including mitochondrial contact site (MICOS) complex, mitochondrial inner membrane organizing system (MINOS), mitochondrial organizing structure (MitOS), Mitofilin complex, or Fcj1 (formation of crista junction protein 1) complex (Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012). Mitofilin, also termed Fcj1, was the first component identified (Icho et al., 1994; Odgren et al., 1996; Gieffers et al., 1997; John et al., 2005) and was observed enriched at crista junctions (Rabl et al., 2009). Mutants of Mitofilin/Fcj1 as well as of other MICOS/MINOS/MitOS subunits show a strikingly altered inner membrane architecture. They lose crista junctions and contain large internal membrane stacks, the respiratory activity is reduced, and mitochondrial DNA nucleoids are altered (Fig. 1 B; John et al., 2005; Hess et al., 2009; Rabl et al., 2009; Mun et al., 2010; Harner et al., 2011; Head et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012; Itoh et al., 2013). It has been reported that the complex interacts with a variety of outer membrane proteins, such as channel proteins and components of the protein translocases and mitochondrial fusion machines, and defects impair the biogenesis of mitochondrial proteins (Xie et al., 2007; Darshi et al., 2011; Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012; An et al., 2012; Bohnert et al., 2012; Körner et al., 2012; Ott et al., 2012; Zerbes et al., 2012; Jans et al., 2013; Weber et al., 2013). The MICOS/MINOS/MitOS/Mitofilin/Fcj1 complex thus plays crucial roles in mitochondrial architecture, dynamics, and biogenesis. However, communication of results in this rapidly developing field has been complicated by several different nomenclatures used for the complex as well as for its subunits (Standard nameFormer namesYeast ORFReferencesComplexMICOSMINOS, MitOS, MIB, Mitofilin complex, and Fcj1 complexXie et al., 2007; Rabl et al., 2009; Darshi et al., 2011; Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012; An et al., 2012; Bohnert et al., 2012; Ott et al., 2012; Jans et al., 2013; Weber et al., 2013SubunitsMic10Mcs10, Mio10, Mos1, and MINOS1YCL057C-AHarner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012; Itoh et al., 2013; Jans et al., 2013; Varabyova et al., 2013Mic12Aim5, Fmp51, and Mcs12YBR262CHess et al., 2009; Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Varabyova et al., 2013Mic19Aim13, Mcs19, CHCH-3, CHCHD3, and MINOS3YFR011CXie et al., 2007; Hess et al., 2009; Darshi et al., 2011; Head et al., 2011; Alkhaja et al., 2012; Ott et al., 2012; Jans et al., 2013; Varabyova et al., 2013Mic25 (metazoan Mic19 homologue)CHCHD6 and CHCM1Xie et al., 2007; An et al., 2012Mic26Mcs29, Mio27, and Mos2YGR235CHarner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011Mic27Aim37, Mcs27, APOOL, and MOMA-1YNL100WHess et al., 2009; Harner et al., 2011; Head et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Weber et al., 2013Mic60Fcj1, Aim28, Fmp13, Mitofilin, HMP, IMMT, and MINOS2YKR016WIcho et al., 1994; Odgren et al., 1996; Gieffers et al., 1997; John et al., 2005; Wang et al., 2008; Rabl et al., 2009; Rossi et al., 2009; Mun et al., 2010; Park et al., 2010; Körner et al., 2012; Zerbes et al., 2012; Itoh et al., 2013; Varabyova et al., 2013Open in a separate windowAPOOL, apolipoprotein O–like; HMP, heart muscle protein; IMMT, inner mitochondrial membrane protein; MIB, mitochondrial intermembrane space bridging.To rectify this situation, all authors of this article have agreed on a new uniform nomenclature with the following guidelines. (a) The complex will be called “mitochondrial contact site and cristae organizing system” (MICOS). The protein subunits of MICOS are named Mic10 to Mic60 as listed in Gabriel et al., 2007; Vögtle et al., 2012) will be changed to Mix14, Mix17, and Mix23 (mitochondrial intermembrane space CXnC motif proteins) in the Saccharomyces Genome Database, and the new nomenclature will be used for orthologues identified in other organisms.The MICOS complex is of central importance for the maintenance of mitochondrial inner membrane architecture and the formation of contact sites between outer and inner membranes and thus is involved in the regulation of mitochondrial dynamics, biogenesis, and inheritance. We expect that the uniform nomenclature will facilitate future studies on mitochondrial membrane architecture and dynamics.  相似文献   

13.
Cell biology in neuroscience: RNA-based mechanisms underlying axon guidance     
Toshiaki Shigeoka  Bo Lu  Christine E. Holt 《The Journal of cell biology》2013,202(7):991-999
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14.
Poly(ADP-ribose): An organizer of cellular architecture     
Anthony K.L. Leung 《The Journal of cell biology》2014,205(5):613-619
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15.
Variation in Adult Plant Phenotypes and Partitioning among Seed and Stem-Borne Roots across Brachypodium distachyon Accessions to Exploit in Breeding Cereals for Well-Watered and Drought Environments     
Vincent Chochois  John P. Vogel  Gregory J. Rebetzke  Michelle Watt 《Plant physiology》2015,168(3):953-967
Seedling roots enable plant establishment. Their small phenotypes are measured routinely. Adult root systems are relevant to yield and efficiency, but phenotyping is challenging. Root length exceeds the volume of most pots. Field studies measure partial adult root systems through coring or use seedling roots as adult surrogates. Here, we phenotyped 79 diverse lines of the small grass model Brachypodium distachyon to adults in 50-cm-long tubes of soil with irrigation; a subset of 16 lines was droughted. Variation was large (total biomass, ×8; total root length [TRL], ×10; and root mass ratio, ×6), repeatable, and attributable to genetic factors (heritabilities ranged from approximately 50% for root growth to 82% for partitioning phenotypes). Lines were dissected into seed-borne tissues (stem and primary seminal axile roots) and stem-borne tissues (tillers and coleoptile and leaf node axile roots) plus branch roots. All lines developed one seminal root that varied, with branch roots, from 31% to 90% of TRL in the well-watered condition. With drought, 100% of TRL was seminal, regardless of line because nodal roots were almost always inhibited in drying topsoil. Irrigation stimulated nodal roots depending on genotype. Shoot size and tillers correlated positively with roots with irrigation, but partitioning depended on genotype and was plastic with drought. Adult root systems of B. distachyon have genetic variation to exploit to increase cereal yields through genes associated with partitioning among roots and their responsiveness to irrigation. Whole-plant phenotypes could enhance gain for droughted environments because root and shoot traits are coselected.Adult plant root systems are relevant to the size and efficiency of seed yield. They supply water and nutrients for the plant to acquire biomass, which is positively correlated to the harvest index (allocation to seed grain), and the stages of flowering and grain development. Modeling in wheat (Triticum aestivum) suggested that an extra 10 mm of water absorbed by such adult root systems during grain filling resulted in an increase of approximately 500 kg grain ha−1 (Manschadi et al., 2006). This was 25% above the average annual yield of wheat in rain-fed environments of Australia. This number was remarkably close to experimental data obtained in the field in Australia (Kirkegaard et al., 2007). Together, these modeling and field experiments have shown that adult root systems are critical for water absorption and grain yield in cereals, such as wheat, emphasizing the importance of characterizing adult root systems to identify phenotypes for productivity improvements.Most root phenotypes, however, have been described for seedling roots. Seedling roots are essential for plant establishment, and hence, the plant’s potential to set seed. For technical reasons, seedlings are more often screened than adult plants because of the ease of handling smaller plants and the high throughput. Seedling-stage phenotyping may also improve overall reproducibility of results because often, growth media are soil free. Seedling soil-free root phenotyping conditions are well suited to dissecting fine and sensitive mechanisms, such as lateral root initiation (Casimiro et al., 2003; Péret et al., 2009a, 2009b). A number of genes underlying root processes have been identified or characterized using seedlings, notably with the dicotyledonous models Arabidopsis (Arabidopsis thaliana; Mouchel et al., 2004; Fitz Gerald et al., 2006; Yokawa et al., 2013) and Medicago truncatula (Laffont et al., 2010) and the cereals maize (Zea mays; Hochholdinger et al., 2001) and rice (Oryza sativa; Inukai et al., 2005; Kitomi et al., 2008).Extrapolation from seedling to adult root systems presents major questions (Hochholdinger and Zimmermann, 2008; Chochois et al., 2012; Rich and Watt, 2013). Are phenotypes in seedling roots present in adult roots given developmental events associated with aging? Is expression of phenotypes correlated in seedling and adult roots if time compounds effects of growth rates and growth conditions on roots? Watt et al. (2013) showed in wheat seedlings that root traits in the laboratory and field correlated positively but that neither correlated with adult root traits in the field. Factors between seedling and adult roots seemed to be differences in developmental stage and the time that growing roots experience the environment.Seedling and adult root differences may be larger in grasses than dicotyledons. Grass root systems have two developmental components: seed-borne (seminal) roots, of which a number emerge at germination and continue to grow and branch throughout the plant life, and stem-borne (nodal or adventitious) roots, which emerge from around the three-leaf stage and continue to emerge, grow, and branch throughout the plant life. Phenotypes and traits of adult root systems of grasses, which include the major cereal crops wheat, rice, and maize, are difficult to predict in seedling screens and ideally identified from adult root systems first (Gamuyao et al., 2012).Phenotyping of adult roots is possible in the field using trenches (Maeght et al., 2013) or coring (Wasson et al., 2014). A portion of the root system is captured with these methods. Alternatively, entire adult root systems can be contained within pots dug into the ground before sowing. These need to be large; field wheat roots, for example, can reach depths greater than 1.5 m depending on genotype and environment. This method prevents root-root interactions that occur under normal field sowing of a plant canopy and is also a compromise.A solution to the problem of phenotyping adult cereal root systems is a model for monocotyledon grasses: Brachypodium distachyon. B. distachyon is a small-stature grass with a small genome that is fully sequenced (Vogel et al., 2010). It has molecular tools equivalent to those available in Arabidopsis (Draper et al., 2001; Brkljacic et al., 2011; Mur et al., 2011). The root system of B. distachyon reference line Bd21 is more similar to wheat than other model and crop grasses (Watt et al., 2009). It has a seed-borne primary seminal root (PSR) that emerges from the embryo at seed germination and multiple stem-borne coleoptile node axile roots (CNRs) and leaf node axile roots (LNRs), also known as crown roots or adventitious roots, that emerge at about three leaves through to grain development. Branch roots emerge from all root types. There are no known anatomical differences between root types of wheat and B. distachyon (Watt et al., 2009). In a recent study, we report postflowering root growth in B. distachyon line Bd21-3, showing that this model can be used to answer questions relevant to the adult root systems of grasses (Chochois et al., 2012).In this study, we used B. distachyon to identify adult plant phenotypes related to the partitioning among seed-borne and stem-borne shoots and roots for the genetic improvement of well-watered and droughted cereals (Fig. 1; Krassovsky, 1926; Navara et al., 1994), nitrogen, phosphorus (Tennant, 1976; Brady et al., 1995), oxygen (Wiengweera and Greenway, 2004), soil hardness (Acuna et al., 2007), and microorganisms (Sivasithamparam et al., 1978). Of note is the study by Krassovsky (1926), which was the first, to our knowledge, to show differences in function related to water. Krassovsky (1926) showed that seminal roots of wheat absorbed almost 2 times the water as nodal roots per unit dry weight but that nodal roots absorbed a more diluted nutrient solution than seminal roots. Krassovsky (1926) also showed by removing seminal or nodal roots as they emerged that “seminal roots serve the main stem, while nodal roots serve the tillers” (Krassovsky, 1926). Volkmar (1997) showed, more recently, in wheat that nodal and seminal roots may sense and respond to drought differently. In millet (Pennisetum glaucum) and sorghum (Sorghum bicolor), Rostamza et al. (2013) found that millet was able to grow nodal roots in a dryer soil than sorghum, possibly because of shoot and root vigor.Open in a separate windowFigure 1.B. distachyon plant scanned at the fourth leaf stage, with the root and shoot phenotypes studied indicated. Supplemental Table S1.
PhenotypeAbbreviationUnitRange of Variation
All Experiments (79 Lines and 582 Plants)Experiment 6 (36 Lines)
Whole plant
TDWTDWMilligrams88.6–773.8 (×8.7)285.6–438 (×1.5)
Shoot
SDWSDWMilligrams56.4–442.5 (×7.8)78.2–442.5 (×5.7)
 No. of tillersTillerNCount2.8–20.3 (×7.4)10–20.3 (×2)
Total root system
TRLTRLCentimeters1,050–10,770 (×10.3)2,090–5,140 (×2.5)
RDWRDWMilligrams28.9–312.17 (×10.8)62.2–179.1 (×2.9)
RootpcRootpcPercentage (of TDW)20.5–60.6 (×3)20.5–44.3 (×2.2)
R/SR/SUnitless ratio0.26–1.54 (×6)0.26–0.80 (×3.1)
PSRs
 Length (including branch roots)PSRLCentimeters549.1–4,024.6 (×7.3)716–2,984 (×4.2)
PSRpcPSRpcPercentage (of TRL)14.9–94.1 (×6.3)31.3–72.3 (×2.3)
 No. of axile rootsPSRcountCount11
 Length of axile rootPSRsumCentimeters17.45–52 (×3)17.45–30.3 (×1.7)
 Branch rootsPSRbranchCentimeters · (centimeters of axile root)−119.9–109.3 (×5.5)29.3–104.3 (×3.6)
CNRs
 Length (including branch roots)CNRLCentimeters0–3,856.70–2,266.5
CNRpcCNRpcPercentage (of TRL)0–57.10–49.8
 No. of axile rootsCNRcountCount0–20–2
 Cumulated length of axile rootsCNRsumCentimeters0–113.90–47.87
 Branch rootsCNRbranchCentimeters · (centimeters of axile root)−10–77.80–77.8
LNRs
 Length (including branch roots)LNRLCentimeters99.5–5,806.5 (×58.5)216.1–2,532.4 (×11.7)
LNRpcLNRpcPercentage (of TRL)4.2–72.7 (×17.5)6–64.8 (×10.9)
LNRcountLNRcountCount2–22.2 (×11.1)3.3–15.3 (×4.6)
LNRsumLNRsumCentimeters25.9–485.548–232 (×4.8)
 Branch rootsLNRbranchCentimeters · (centimeters of axile root)−12.1–25.4 (×12.1)3.2–15.9 (×5)
Open in a separate windowThe third reason for dissecting the different root types in this study was that they seem to have independent genetic regulation through major genes. Genes affecting specifically nodal root growth have been identified in maize (Hetz et al., 1996; Hochholdinger and Feix, 1998) and rice (Inukai et al., 2001, 2005; Liu et al., 2005, 2009; Zhao et al., 2009; Coudert et al., 2010; Gamuyao et al., 2012). Here, we also dissect branch (lateral) development on the seminal or nodal roots. Genes specific to branch roots have been identified in Arabidopsis (Casimiro et al., 2003; Péret et al., 2009a), rice (Hao and Ichii, 1999; Wang et al., 2006; Zheng et al., 2013), and maize (Hochholdinger and Feix, 1998; Hochholdinger et al., 2001; Woll et al., 2005).This study explored the hypothesis that adult root systems of B. distachyon contain genotypic variation that can be exploited through phenotyping and genotyping to increase cereal yields. A selection of 79 wild lines of B. distachyon from various parts of the Middle East (Fig. 2 shows the geographic origins of the lines) was phenotyped. They were selected for maximum genotypic diversity from 187 diploid lines analyzed with 43 simple sequence repeat markers (Vogel et al., 2009). We phenotyped shoots and mature root systems concurrently because B. distachyon is small enough to complete its life cycle in relatively small pots of soil with minimal influence of pot size compared with crops, such as wheat. We further phenotyped a subset of this population under irrigation (well watered) and drought to assess genotype response to water supply. By conducting whole-plant studies, we aimed to identify phenotypes that described partitioning among shoot and root components and within seed-borne and stem-borne roots. Phenotypes that have the potential to be beneficial to shoot and root components may speed up genetic gain in future.Open in a separate windowFigure 2.B. distachyon lines phenotyped in this study and their geographical origin. Capital letters in parentheses indicate the country of origin: Turkey (T), Spain (S), and Iraq (I; Vogel et al., 2009). a, Adi3, Adi7, Adi10, Adi12, Adi13, and Adi15; b, Bd21 and Bd21-3 are the reference lines of this study. Bd21 was the first sequenced line (Vogel et al., 2010) and root system (described in detail in Watt et al., 2009), and Bd21-3 is the most easily transformed line (Vogel and Hill, 2008) and parent of a T-DNA mutant population (Bragg et al., 2012); c, Gaz1, Gaz4, and Gaz7; d, Kah1, Kah2, and Kah3. e, Koz1, Koz3, and Koz5; f, Tek1 and Tek6; g, exact GPS coordinates are unknown for lines Men2 (S), Mur2 (S), Bd2.3 (I), Bd3-1 (I), and Abr1 (T).  相似文献   

16.
Mitotic spindle (DIS)orientation and DISease: Cause or consequence?     
Anna Noatynska  Monica Gotta  Patrick Meraldi 《The Journal of cell biology》2012,199(7):1025-1035
  相似文献   

17.
Arabidopsis LON2 Is Necessary for Peroxisomal Function and Sustained Matrix Protein Import     
Matthew J. Lingard  Bonnie Bartel 《Plant physiology》2009,151(3):1354-1365
Relatively little is known about the small subset of peroxisomal proteins with predicted protease activity. Here, we report that the peroxisomal LON2 (At5g47040) protease facilitates matrix protein import into Arabidopsis (Arabidopsis thaliana) peroxisomes. We identified T-DNA insertion alleles disrupted in five of the nine confirmed or predicted peroxisomal proteases and found only two—lon2 and deg15, a mutant defective in the previously described PTS2-processing protease (DEG15/At1g28320)—with phenotypes suggestive of peroxisome metabolism defects. Both lon2 and deg15 mutants were mildly resistant to the inhibitory effects of indole-3-butyric acid (IBA) on root elongation, but only lon2 mutants were resistant to the stimulatory effects of IBA on lateral root production or displayed Suc dependence during seedling growth. lon2 mutants displayed defects in removing the type 2 peroxisome targeting signal (PTS2) from peroxisomal malate dehydrogenase and reduced accumulation of 3-ketoacyl-CoA thiolase, another PTS2-containing protein; both defects were not apparent upon germination but appeared in 5- to 8-d-old seedlings. In lon2 cotyledon cells, matrix proteins were localized to peroxisomes in 4-d-old seedlings but mislocalized to the cytosol in 8-d-old seedlings. Moreover, a PTS2-GFP reporter sorted to peroxisomes in lon2 root tip cells but was largely cytosolic in more mature root cells. Our results indicate that LON2 is needed for sustained matrix protein import into peroxisomes. The delayed onset of matrix protein sorting defects may account for the relatively weak Suc dependence following germination, moderate IBA-resistant primary root elongation, and severe defects in IBA-induced lateral root formation observed in lon2 mutants.Peroxisomes are single-membrane-bound organelles found in most eukaryotes. Peroxin (PEX) proteins are necessary for various aspects of peroxisome biogenesis, including matrix protein import (for review, see Distel et al., 1996; Schrader and Fahimi, 2008). Most matrix proteins are imported into peroxisomes from the cytosol using one of two targeting signals, a C-terminal type 1 peroxisome-targeting signal (PTS1) or a cleavable N-terminal type 2 peroxisome-targeting signal (PTS2) (Reumann, 2004). PTS1- and PTS2-containing proteins are bound in the cytosol by soluble matrix protein receptors, escorted to the peroxisome membrane docking complex, and translocated into the peroxisome matrix (for review, see Platta and Erdmann, 2007). Once in the peroxisome, many matrix proteins participate in metabolic pathways, such as β-oxidation, hydrogen peroxide decomposition, and photorespiration (for review, see Gabaldon et al., 2006; Poirier et al., 2006).In addition to metabolic enzymes, several proteases are found in the peroxisome matrix. Only one protease, DEG15/Tysnd1, has a well-defined role in peroxisome biology. The rat Tysnd1 protease removes the targeting signal after PTS2-containing proteins enter the peroxisome and also processes certain PTS1-containing β-oxidation enzymes (Kurochkin et al., 2007). Similarly, the Arabidopsis (Arabidopsis thaliana) Tysnd1 homolog DEG15 (At1g28320) is a peroxisomal Ser protease that removes PTS2 targeting signals (Helm et al., 2007; Schuhmann et al., 2008).In contrast with DEG15, little is known about the other eight Arabidopsis proteins that are annotated as proteases in the AraPerox database of putative peroxisomal proteins (Reumann et al., 2004; Carter et al., 2004; Shimaoka et al., 2004), which, in combination with the minor PTS found in both of these predicted proteases (Reumann, 2004), suggests that these enzymes may not be peroxisomal. Along with DEG15, only two of the predicted peroxisomal proteases, an M16 metalloprotease (At2g41790), which we have named PXM16 for peroxisomal M16 protease, and a Lon-related protease (At5g47040/LON2; Ostersetzer et al., 2007), are found in the proteome of peroxisomes purified from Arabidopsis suspension cells (Eubel et al., 2008). DEG15 and LON2 also have been validated as peroxisomally targeted using GFP fusions (Ostersetzer et al., 2007; Schuhmann et al., 2008).

Table I.

Putative Arabidopsis proteases predicted or demonstrated to be peroxisomal
AGI IdentifierAliasProtein ClassT-DNA Insertion AllelesPTSLocalization EvidenceLocalization References
At1g28320DEG15PTS2-processing proteaseSALK_007184 (deg15-1)SKL>aGFPReumann et al., 2004; Helm et al., 2007; Eubel et al., 2008; Schuhmann et al., 2008)
Proteomics
Bioinformatics
At2g41790PXM16Peptidase M16 family proteinSALK_019128 (pxm16-1)PKL>bProteomicsReumann et al., 2004, 2009; Eubel et al., 2008)
SALK_023917 (pxm16-2)Bioinformatics
At5g47040LON2Lon protease homologSALK_128438 (lon2-1)SKL>aGFPReumann et al., 2004, 2009; Ostersetzer et al., 2007; Eubel et al., 2008)
SALK_043857 (lon2-2)Proteomics
Bioinformatics
At2g18080Ser-type peptidaseSALK_020628SSI>cBioinformatics(Reumann et al., 2004)
SALK_102239
At2g35615Aspartyl proteaseSALK_090795ANL>bBioinformatics(Reumann et al., 2004)
SALK_036333
At3g57810Ovarian tumor-like Cys proteaseSKL>aBioinformatics(Reumann et al., 2004)
At4g14570Acylaminoacyl-peptidase proteinCKL>bBioinformatics (peroxisome)(Reumann et al., 2004; Shimaoka et al., 2004)
Proteomics (vacuole)
At4g20310Peptidase M50 family proteinRMx5HLdBioinformatics(Reumann et al., 2004)
At4g36195Ser carboxypeptidase S28 familySSM>bBioinformatics (peroxisome)(Carter et al., 2004; Reumann et al., 2004)





Proteomics (vacuole)

Open in a separate windowaMajor PTS1 (Reumann, 2004).bMinor PTS1 (Reumann, 2004).cValidated PTS1 (Reumann et al., 2007).dMinor PTS2 (Reumann, 2004).PXM16 is the only one of the nine Arabidopsis M16 (pitrilysin family) metalloproteases (García-Lorenzo et al., 2006; Rawlings et al., 2008) containing a predicted PTS. M16 subfamilies B and C contain the plastid and mitochondrial processing peptidases (for review, see Schaller, 2004), whereas PXM16 belongs to M16 subfamily A, which includes insulin-degrading peptidases (Schaller, 2004). A tomato (Solanum lycopersicum) M16 subfamily A protease similar to insulin-degrading enzymes with a putative PTS1 was identified in a screen for proteases that cleave the wound response peptide hormone systemin (Strassner et al., 2002), but the role of Arabidopsis PXM16 is unknown.Arabidopsis LON2 is a typical Lon protease with three conserved domains: an N-terminal domain, a central ATPase domain in the AAA family, and a C-terminal protease domain with a Ser-Lys catalytic dyad (Fig. 1A; Lee and Suzuki, 2008). Lon proteases are found in prokaryotes and in some eukaryotic organelles (Fig. 1C) and participate in protein quality control by cleaving unfolded proteins and can regulate metabolism by controlling levels of enzymes from many pathways, including cell cycle, metabolism, and stress responses (for review, see Tsilibaris et al., 2006). Four Lon homologs are encoded in the Arabidopsis genome; isoforms have been identified in mitochondria, plastids, and peroxisomes (Ostersetzer et al., 2007; Eubel et al., 2008; Rawlings et al., 2008). Mitochondrial Lon protesases are found in a variety of eukaryotes (Fig. 1A) and function both as ATP-dependent proteases and as chaperones promoting protein complex assemblies (Lee and Suzuki, 2008). LON2 is the only Arabidopsis Lon isoform with a canonical C-terminal PTS1 (SKL-COOH; Ostersetzer et al., 2007) or found in the peroxisome proteome (Eubel et al., 2008; Reumann et al., 2009). Functional studies have been conducted with peroxisomal Lon isoforms found in the proteome of peroxisomes purified from rat hepatic cells (pLon; Kikuchi et al., 2004) and the methylotrophic yeast Hansenula polymorpha (Pln; Aksam et al., 2007). Rat pLon interacts with β-oxidation enzymes, and a cell line expressing a dominant negative pLon variant has decreased β-oxidation activity, displays defects in the activation processing of PTS1-containing acyl-CoA oxidase, and missorts catalase to the cytosol (Omi et al., 2008). H. polymorpha Pln is necessary for degradation of a misfolded, peroxisome-targeted version of dihydrofolate reductase and for degradation of in vitro-synthesized alcohol oxidase in peroxisomal matrix extracts, but does not contribute to degradation of peroxisomally targeted GFP (Aksam et al., 2007).Open in a separate windowFigure 1.Diagram of LON2 protein domains, gene models for LON2, PXM16, DEG15, PED1, PEX5, and PEX6, and phylogenetic relationships of LON family members. A, Organization of the 888-amino acid LON2 protein. Locations of the N-terminal domain conserved among Lon proteins, predicted ATP-binding Walker A and B domains (black circles), active site Ser (S) and Lys (K) residues (asterisks), and the C-terminal Ser-Lys-Leu (SKL) peroxisomal targeting signal (PTS1) are shown (Lee and Suzuki, 2008). B, Gene models for LON2, PXM16, DEG15, PED1, PEX5, and PEX6 and locations of T-DNA insertions (triangles) or missense alleles (arrows) used in this study. Exons are depicted by black boxes, introns by black lines, and untranslated regions by gray lines. C, Phylogenetic relationships among LON homologs. Sequences were aligned using MegAlign (DNAStar) and the ClustalW method. The PAUP 4.0b10 program (Swofford, 2001) was used to generate an unrooted phylogram from a trimmed alignment corresponding to Arabidopsis LON2 residues 400 to 888 (from the beginning of the ATPase domain to the end of the protein). The bootstrap method was performed for 500 replicates with distance as the optimality criterion. Bootstrap values are indicated at the nodes. Predicted peroxisomal proteins have C-terminal PTS1 signals in parentheses and are in light-gray ovals. Proteins in the darker gray oval have N-terminal extensions and include mitochondrial and chloroplastic proteins. Sequence identifiers are listed in Supplemental Table S2.In this work, we examined the roles of several putative peroxisomal proteases in Arabidopsis. We found that lon2 mutants displayed peroxisome-deficient phenotypes, including resistance to the protoauxin indole-3-butyric acid (IBA) and age-dependent defects in peroxisomal import of PTS1- and PTS2-targeted matrix proteins. Our results indicate that LON2 contributes to matrix protein import into Arabidopsis peroxisomes.  相似文献   

18.
SOS2-LIKE PROTEIN KINASE5, an SNF1-RELATED PROTEIN KINASE3-Type Protein Kinase,Is Important for Abscisic Acid Responses in Arabidopsis through Phosphorylation of ABSCISIC ACID-INSENSITIVE5   总被引:1,自引:0,他引:1  
Xiaona Zhou  Hongmei Hao  Yuguo Zhang  Yili Bai  Wenbo Zhu  Yunxia Qin  Feifei Yuan  Feiyi Zhao  Mengyao Wang  Jingjiang Hu  Hong Xu  Aiguang Guo  Huixian Zhao  Yang Zhao  Cuiling Cao  Yongqing Yang  Karen S. Schumaker  Yan Guo  Chang Gen Xie 《Plant physiology》2015,168(2):659-676
  相似文献   

19.
Ion channel regulation by protein S-acylation     
Michael J. Shipston 《The Journal of general physiology》2014,143(6):659-678
Protein S-acylation, the reversible covalent fatty-acid modification of cysteine residues, has emerged as a dynamic posttranslational modification (PTM) that controls the diversity, life cycle, and physiological function of numerous ligand- and voltage-gated ion channels. S-acylation is enzymatically mediated by a diverse family of acyltransferases (zDHHCs) and is reversed by acylthioesterases. However, for most ion channels, the dynamics and subcellular localization at which S-acylation and deacylation cycles occur are not known. S-acylation can control the two fundamental determinants of ion channel function: (1) the number of channels resident in a membrane and (2) the activity of the channel at the membrane. It controls the former by regulating channel trafficking and the latter by controlling channel kinetics and modulation by other PTMs. Ion channel function may be modulated by S-acylation of both pore-forming and regulatory subunits as well as through control of adapter, signaling, and scaffolding proteins in ion channel complexes. Importantly, cross-talk of S-acylation with other PTMs of both cysteine residues by themselves and neighboring sites of phosphorylation is an emerging concept in the control of ion channel physiology. In this review, I discuss the fundamentals of protein S-acylation and the tools available to investigate ion channel S-acylation. The mechanisms and role of S-acylation in controlling diverse stages of the ion channel life cycle and its effect on ion channel function are highlighted. Finally, I discuss future goals and challenges for the field to understand both the mechanistic basis for S-acylation control of ion channels and the functional consequence and implications for understanding the physiological function of ion channel S-acylation in health and disease.Ion channels are modified by the attachment to the channel protein of a wide array of small signaling molecules. These include phosphate groups (phosphorylation), ubiquitin (ubiquitination), small ubiquitin-like modifier (SUMO) proteins (SUMOylation), and various lipids (lipidation). Such PTMs are critical for controlling the physiological function of ion channels through regulation of the number of ion channels resident in the (plasma) membrane; their activity, kinetics, and modulation by other PTMs; or their interaction with other proteins. S-acylation is one of a group of covalent lipid modifications (Resh, 2013). However, unlike N-myristoylation and prenylation (which includes farnesylation and geranylgeranylation), S-acylation is reversible (Fig. 1). Because of the labile thioester bond, S-acylation thus represents a dynamic lipid modification to spatiotemporally control protein function. The most common form of S-acylation, the attachment of the C16 lipid palmitate to proteins (referred to as S-palmitoylation), was first described more than 30 years ago in the transmembrane glycoprotein of the vesicular stomatitis virus and various mammalian membrane proteins (Schmidt and Schlesinger, 1979; Schlesinger et al., 1980). A decade later, S-acylated ion channels—rodent voltage-gated sodium channels (Schmidt and Catterall, 1987) and the M2 ion channel from the influenza virus (Sugrue et al., 1990)—were first characterized. Since then, more than 50 distinct ion channel subunits have been experimentally demonstrated to be S-acylated (El-Husseini and Bredt, 2002; Linder and Deschenes, 2007; Fukata and Fukata, 2010; Greaves and Chamberlain, 2011; Resh, 2012). In the last few years, with the cloning of enzymes controlling S-acylation and development of various proteomic tools, we have begun to gain substantial mechanistic and physiological insight into how S-acylation may control multiple facets of the life cycle of ion channels: from their assembly, through their trafficking and regulation at the plasma membrane, to their final degradation (Fig. 2).Open in a separate windowFigure 1.Protein S-acylation: a reversible lipid posttranslational modification of proteins. (A) Major lipid modifications of proteins. S-acylation is reversible due to the labile thioester bond between the lipid (typically, but not exclusively, palmitate) and the cysteine amino acid of is target protein. Other lipid modifications result from stable bond formation between either the N-terminal amino acid (amide) or the amino acid side chain in the protein (thioether and oxyester). The zDHHC family of palmitoyl acyltransferases mediates S-acylation with other enzyme families controlling other lipid modifications: N-methyltransferase (NMT) controls myristoylation of many proteins such as the src family kinase, Fyn kinase; and amide-linked palmitoylation of the secreted sonic hedgehog protein is mediated by Hedgehog acyltransferase (Hhat), a membrane-bound O-acyl transferase (MBOAT) family. Prenyl transferases catalyze farnesyl (farnesyltransferase, FTase) or geranylgeranyl (geranylgeranyl transferase I [GGTase I] and geranylgeranyl transferase II [GGTase II]) in small GTPase proteins such as RAS and the Rab proteins, respectively. Porcupine (Porcn) is a member of the MBOAT family acylates secreted proteins such as Wnt. (B) zDHHC enzymes typically use coenzyme A (CoA)-palmitate; however, other long chain fatty acids (either saturated or desaturated) can also be used. Deacylation is mediated by several acylthioesterases of the serine hydrolase family. (C) zDHHC acyltransferases (23 in humans) are predicted transmembrane proteins (typically with 4 or 6 transmembrane domains) with the catalytic DHHC domain located in a cytosolic loop.

Table 1.

Pore-forming subunits of ion channels experimentally determined to be S-acylated
ChannelSubunitGeneCandidate S-acylation sitesUniProt IDReferences
Ligand-gated
AMPAGluA1Gria1593FSLGAFMQQGCDISPRSLSGRIP23818Hayashi et al., 2005
819LAMLVALIEFCYKSRSESKRMKP23818Hayashi et al., 2005
GluA2Gria2600FSLGAFMRQGCDISPRSLSGRIP23819Hayashi et al., 2005
826LAMLVALIEFCYKSRAEAKRMKP23819Hayashi et al., 2005
GluA3Gria3605FSLGAFMQQGCDISPRSLSGRIQ9Z2W9Hayashi et al., 2005
831LAMMVALIEFCYKSRAESKRMKQ9Z2W9Hayashi et al., 2005
GluA4Gria4601FSLGAFMQQGCDISPRSLSGRIQ9Z2W8Hayashi et al., 2005
827LAMLVALIEFCYKSRAEAKRMKQ9Z2W8Hayashi et al., 2005
GABAAγ2Gabrg2405QERDEEYGYECLDGKDCASFFCCFEDCRTGAWRHGRIP22723Rathenberg et al., 2004; Fang et al., 2006
KainateGluK2Grik2848KNAQLEKRSFCSAMVEELRMSLKCQRRLKHKPQAPVP39087Pickering et al., 1995
nAChRα4Chrna4263TVLVFYLPSECGEKVTLCISVO70174Alexander et al., 2010; Amici et al., 2012
α7Chrna7NDAlexander et al., 2010; Drisdel et al., 2004
β2Chrnb2NDAlexander et al., 2010
NMDAGluN2AGrin2a838EHLFYWKLRFCFTGVCSDRPGLLFSISRGIYSCIHGVHIEEKKP35436Hayashi et al., 2009
1204SDRYRQNSTHCRSCLSNLPTYSGHFTMRSPFKCDACLRMGNLYDIDP35436Hayashi et al., 2009
GluN2BGrin2b839EHLFYWQFRHCFMGVCSGKPGMVFSISRGIYSCIHGVAIEERQQ01097Hayashi et al., 2009
1205DWEDRSGGNFCRSCPSKLHNYSSTVAGQNSGRQACIRCEACKKAGNLYDISQ01097Hayashi et al., 2009
P2X7P2X7P2rx7361AFCRSGVYPYCKCCEPCTVNEYYYRKKQ9Z1M0Gonnord et al., 2009
469APKSGDSPSWCQCGNCLPSRLPEQRRQ9Z1M0Gonnord et al., 2009
488PEQRRALEELCCRRKPGRCITTQ9Z1M0Gonnord et al., 2009
562DMADFAILPSCCRWRIRKEFPKQ9Z1M0Gonnord et al., 2009
Voltage gated
Potassium
BK, maxiKKCa1.1Kcnma143WRTLKYLWTVCCHCGGKTKEAQKIQ08460Jeffries et al., 2010
635MSIYKRMRRACCFDCGRSERDCSCMQ08460Tian et al., 2008; 2010
Kv1.1Kcna1233SFELVVRFFACPSKTDFFKNIP16388Gubitosi-Klug et al., 2005
Kv1.5Kcna516LRGGGEAGASCVQSPRGECGCQ61762Jindal et al., 2008
583VDLRRSLYALCLDTSRETDL-stopQ61762Zhang et al., 2007; Jindal et al., 2008
SodiumNaV1.2Scn2a1NDSchmidt and Catterall, 1987
640MNGKMHSAVDCNGVVSLVGGPP04775Bosmans et al., 2011
1042LEDLNNKKDSCISNHTTIEIGP04775Bosmans et al., 2011
1172TEDCVRKFKCCQISIEEGKGKP04775Bosmans et al., 2011
Other channels
AquaporinAQP4Aqp43DRAAARRWGKCGHSCSRESIMVAFKP55088Crane and Verkman, 2009; Suzuki et al., 2008
CFTRCFTRCFTR514EYRYRSVIKACQLEEDISKFAEKDP13569McClure et al., 2012
1385RRTLKQAFADCTVILCEHRIEAP13569McClure et al., 2012
ConnexinCx32Gjb1270GAGLAEKSDRCSAC-stopP28230Locke et al., 2006
ENaCENaC βScnn1b33TNTHGPKRIICEGPKKKAMWFLQ9WU38Mueller et al., 2010
547WITIIKLVASCKGLRRRRPQAPYQ9WU38Mueller et al., 2010
ENaC γScnn1g23PTIKDLMHWYCLNTNTHGCRRIVVSRGRLQ9WU39Mukherjee et al., 2014
Influenza M2M240LWILDRLFFKCIYRFFEHGLKQ20MD5Sugrue et al., 1990; Holsinger et al., 1995; Veit et al., 1991
RyR1RYR1Ryr114LRTDDEVVLQCSATVLKEQLKLCLAAEGFGNRLP11716Chaube et al., 2014
110RHAHSRMYLSCLTTSRSMTDKP11716Chaube et al., 2014
243RLVYYEGGAVCTHARSLWRLEP11716Chaube et al., 2014
295EDQGLVVVDACKAHTKATSFCP11716Chaube et al., 2014
527ASLIRGNRANCALFSTNLDWVP11716Chaube et al., 2014
1030ATKRSNRDSLCQAVRTLLGYGP11716Chaube et al., 2014
1664SHTLRLYRAVCALGNNRVAHAP11716Chaube et al., 2014
2011HFKDEADEEDCPLPEDIRQDLP11716Chaube et al., 2014
2227KMVTSCCRFLCYFCRISRQNQP11716Chaube et al., 2014
2316KGYPDIGWNPCGGERYLDFLRP11716Chaube et al., 2014
2353VVRLLIRKPECFGPALRGEGGP11716Chaube et al., 2014
2545EMALALNRYLCLAVLPLITKCAPLFAGTEHRP11716Chaube et al., 2014
3160DVQVSCYRTLCSIYSLGTTKNTYVEKLRPALGECLARLAAAMPVP11716Chaube et al., 2014
3392LLVRDEFSVLCRDLYALYPLLP11716Chaube et al., 2014
3625SKQRRRAVVACFRMTPLYNLPP11716Chaube et al., 2014
Open in a separate windowCommon channel abbreviation and subunit as well as gene names are given. Candidate S-acylation sites: experimentally determined cysteine residues (bold) with flanking 10 amino acids. Underlines indicate predicted transmembrane domains. Amino acid numbering corresponds to the UniProt ID. References: selected original supporting citations.Open in a separate windowFigure 2.Protein S-acylation and regulation of the ion channel lifecycle zDHHCs are found in multiple membrane compartments and regulate multiple steps in the ion channel lifecycle including: (1) assembly and (2) ER exit; (3) maturation and Golgi exit; (4) sorting and trafficking; (5) trafficking and insertion into target membrane; (6) clustering and localization in membrane microdomains; control of properties, activity (7), and regulation by other signaling pathways; and (8) internalization, recycling, and final degradation.

Table 3.

Other channels identified in mammalian palmitoylome screens
ChannelGene
Anion
Chloride channel 6Clcn6
Chloride intracellular channel 1Clic1
Chloride intracellular channel 4Clic4
Tweety homologue 1Ttyh1
Tweety homologue 3Ttyh3
Voltage-dependent anion channel 1Vdac1
Voltage-dependent anion channel 2Vdac2
Voltage-dependent anion channel 3Vdac3
Calcium
Voltage-dependent, L-type subunit α 1SCacna1s
Voltage-dependent, gamma subunit 8Cacng8
Cation
Amiloride-sensitive cation channel 2Accn2
Glutamate
Ionotropic, Δ1Grid1
Perforin
Perforin 1Prf1
Potassium
Voltage-gated channel, subfamily Q, member 2Kcnq2
Sodium
Voltage-gated, type I, αScn1a
Voltage-gated, type III, αScn3a
Voltage-gated, type IX, αScn9a
Transient receptor potential
Cation channel, subfamily V, member 2Trpv2
Cation channel, subfamily M, member 7Trpm7
Open in a separate windowChannels identified in global S-acylation screens (Wan et al., 2007, 2013; Kang et al., 2008; Martin and Cravatt, 2009; Yang et al., 2010; Yount et al., 2010; Merrick et al., 2011; Wilson et al., 2011; Jones et al., 2012; Ren et al., 2013; Chaube et al., 2014) and not independently characterized as in and2.2. Common channel abbreviation and gene names are given.Here, I provide a primer on the fundamentals of S-acylation, in the context of ion channel regulation, along with a brief overview of tools available to interrogate ion channel S-acylation. I will discuss key examples of how S-acylation controls distinct stages of the ion channel life cycle before highlighting some of the key challenges for the field in the future.

Fundamentals of S-acylation: The what, when, where, and how

S-acylation: A fatty modification that controls multiple aspects of protein function.

Protein S-acylation results from the attachment of a fatty acid to intracellular cysteine residues of proteins via a labile, thioester linkage (Fig. 1, A and B). Because the thioester bond is subject to nucleophilic attack, S-acylation, unlike other lipid modifications such as N-myristoylation and prenylation, is reversible. However, for most ion channels, as for other S-acylated proteins, the dynamics of S-acylation are poorly understood. Distinct classes of proteins can undergo cycles of acylation and deacylation that are very rapid (e.g., on the timescale of seconds, as exemplified by rat sarcoma [RAS] proteins), much longer (hours), or essentially irreversible during the lifespan of the protein (El-Husseini and Bredt, 2002; Linder and Deschenes, 2007; Zeidman et al., 2009; Fukata and Fukata, 2010; Greaves and Chamberlain, 2011; Resh, 2012). For most ion channels, in fact most S-acylated proteins, the identity of the native lipid species attached to specific cysteine residues is also largely unknown. However, the saturated C16:0 lipid palmitate is commonly thought to be the major lipid species in many S-acylated proteins (Fig. 1). Indeed, much of the earliest work on S-acylation involved the metabolic labeling of proteins in cells with tritiated [3H]palmitate, an approach that still remains useful and important. However, lipids with different chain lengths and degrees of unsaturation (such as oleic and stearic acids) can also be added to cysteines via a thioester linkage, potentially allowing differential control of protein properties through the attachment of distinct fatty acids (El-Husseini and Bredt, 2002; Linder and Deschenes, 2007; Zeidman et al., 2009; Fukata and Fukata, 2010; Greaves and Chamberlain, 2011; Resh, 2012).S-acylation increases protein hydrophobicity and has thus been implicated in controlling protein function in many different ways. Most commonly, as with membrane-associated proteins like RAS and postsynaptic density protein 95 (PSD-95), S-acylation controls membrane attachment and intracellular trafficking. However, S-acylation can also control protein–protein interactions, protein targeting to membrane subdomains, protein stability, and regulation by other PTMs such as phosphorylation (El-Husseini and Bredt, 2002; Fukata and Fukata, 2010; Linder and Deschenes, 2007; Greaves and Chamberlain, 2011; Shipston, 2011; Resh, 2012). Evidence for all these mechanisms in controlling ion channel function is beginning to emerge.

Enzymatic control of S-acylation by zinc finger–containing acyltransferase (zDHHC) transmembrane acyltransferases.

Although autoacylation of some proteins has been reported in the presence of acyl coenzyme A (acyl-CoA; Linder and Deschenes, 2007), most cellular S-acylation, in organisms from yeast to humans, is thought to be enzymatically driven by a family of protein acyltransferases (gene family: zDHHC, with ∼23 members in mammals). These acyltransferases are predicted to be transmembrane zinc finger containing proteins (Fig. 1 C) that include a conserved Asp-His-His-Cys (DHHC) signature sequence within a cysteine-rich stretch of ∼50 amino acids critical for catalytic activity (Fukata et al., 2004). Although the enzymatic activity and lipid specificity of all of the zDHHC family proteins has not been elucidated, S-acylation is thought to proceed through a common, two step “ping pong” process (Mitchell et al., 2010; Jennings and Linder, 2012). However, different zDHHC enzymes may show different acyl-CoA substrate specificities. For example, zDHHC3 activity is reduced by acyl chains of >16 carbons (e.g., stearoyl CoA), whereas zDHHC2 efficiently transfers acyl chains of 14 carbons or longer (Jennings and Linder, 2012). The local availability of different acyl-CoA species may thus play an important role in differentially controlling protein S-acylation.We know very little about how zDHHC activity and function are regulated. Dimerization of zDHHCs 2 and 3 reduces their zDHHC activity compared with the monomeric form (Lai and Linder, 2013). Moreover, zDHHCs undergo autoacylation and contain predicted sites for other posttranslational modifications. Almost half of all mammalian zDHHCs contain a C-terminal PSD-95, Discs large, and ZO-1 (PDZ) domain binding motif, allowing them to assemble with various PDZ domain proteins that regulate ion channels (such as GRIP1b and PSD-95; Thomas and Hayashi, 2013). Other protein interaction domains are also observed in zDHHCs, such as ankyrin repeats in zDHHC17 and zDHHC13 (Greaves and Chamberlain, 2011). Indeed, increasing evidence suggests that various ion channels—including the ligand-gated γ-aminobutyric (GABAA), α-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate (AMPA), and NMDA receptors and the large conductance calcium- and voltage-activated (BK) potassium channels—can assemble in complexes with their cognate zDHHCs.The expansion of the number of zDHHCs in mammals (23 vs. 7 in yeast), together with increased prevalence of PDZ interaction motifs, likely represents evolutionary gain-of-function mechanisms to diversify zDHHC function (Thomas and Hayashi, 2013). Evolutionary gain of function is also seen in ion channel subunit orthologues through acquisition of S-acylated cysteine residues absent in orthologues lower in the phylogenetic tree (such as the transmembrane domain 4 [TM4] sites in GluA1–4 subunits of AMPA receptors [Thomas and Hayashi, 2013] and the sites in the alternatively spliced stress-regulated exon [STREX] insert in the C terminus of the BK channel [Tian et al., 2008]). Importantly, some zDHHCs may have additional roles beyond their acyltransferase function. For example, the Drosophila melanogaster zDHHC23 orthologue lacks the catalytic DHHC sequence, and thus protein acyltransferase activity, and is a chaperone involved in protein trafficking (Johswich et al., 2009), whereas mammalian zDHHC 23 has a functional zDHHC motif and, in addition to S-acylating BK channels (Tian et al., 2012), can bind and regulate, but does not S-acylate, neuronal nitric oxide synthase (nNOS; Saitoh et al., 2004).However, as with most S-acylated proteins, the identity of the zDHHCs that modify specific cysteine residues on individual ion channels is not known. Indeed, relatively few studies have tried to systematically identify the zDHHCs controlling ion channel function (Tian et al., 2010, 2012). Thus we are largely ignorant of the extent to which different zDHHCs may have specific ion channel targets or may display specificity. Some details are beginning to emerge: for example, zDHHC3 appears to be a rather promiscuous acyltransferase reported to S-acylate several ion channels (Keller et al., 2004; Hayashi et al., 2005, 2009; Tian et al., 2010), whereas distinct sites on the same ion channel subunit can be modified by distinct subsets of zDHHCs (Tian et al., 2010, 2012). Although we are still in the foothills of understanding the substrates and physiological roles of different zDHHCs, mutation or loss of function in zDHHCs is associated with an increasing number of human disorders, including cancers, various neurological disorders (such as Huntington’s disease and X-linked mental retardations), and disruption of endocrine function in diabetes (Linder and Deschenes, 2007; Fukata and Fukata, 2010; Greaves and Chamberlain, 2011; Resh, 2012).

Deacylation is controlled by acylthioesterases.

Protein deacylation is enzymatically driven by a family of acylthioesterases that belong to the serine hydrolase superfamily (Zeidman et al., 2009; Bachovchin et al., 2010). Indeed, using a broad spectrum serine lipase inhibitor, global proteomic S-acylation profiling identified a subset of serine hydrolases responsible for depalmitoylation (Martin et al., 2012). This study identified both the previously known acylthioesterases as well as potential novel candidate acylthioesterases. The acylthioesterases responsible for deacylating ion channels, as for most other acylated membrane proteins, have not been clearly defined. Furthermore, the extent to which different members of the serine hydrolase superfamily display acylthioesterase activity toward ion channels is not known. Moreover, whether additional mechanisms of nucleophilic attack of the labile thioester bond may also mediate deacylation is not known.Homeostatic control of deacylation of many signaling proteins is likely affected by a family of cytosolic acyl protein thioesterases including lysophospholipase 1 (LYPLA1; Yeh et al., 1999; Devedjiev et al., 2000) and lysophospholipase 2 (LYPLA2; Tomatis et al., 2010). These enzymes show some selectivity for different S-acylated peptides (Tomatis et al., 2010). Indeed, LYPLA1, but not LYPLA2, deacylates the S0-S1 loop of BK channels, leading to Golgi retention of the channel (Tian et al., 2012). A splice variant of the related LYPLAL1 acylthioesterases can also deacylate the BK channel S0-S1 loop, although the crystal structure of LYPLAL1 suggests it is likely to have a preference for lipids with shorter chains than palmitate (Bürger et al., 2012). Thus, whether lipid preference depends on protein interactions or if BK channels have multiple lipid species at the multicysteine S0-S1 site remain unknown. Relatively little is known about the regulation of these acylthioesterases; however, both LYPLA1 and LYPLA2 are themselves S-acylated. This controls their trafficking and association with membranes (Kong et al., 2013; Vartak et al., 2014) and may be important for accessing the thioesterase bond at the membrane interface. Additional mechanisms may promote accessibility of thioesterases to target cysteines. For example, the prolyl isomerase protein FKBP12 binds to palmitoylated RAS, and promotes RAS deacylation via a proline residue near the S-acylated cysteine (Ahearn et al., 2011).Upon lysosomal degradation, many proteins are deacylated by the lysosomal palmitoyl protein thioesterase (PPT1; Verkruyse and Hofmann, 1996), and mutations in PPT1 lead to the devastating condition of infantile neuronal ceroid lipofuscinosis (Vesa et al., 1995; Sarkar et al., 2013). However, PPT1 can also be found in synaptic and other transport vesicles, and genetic deletion of PPT1 in mice may have different effects on similar proteins, which suggests roles beyond just lysosomal mediated degradation. For example, in PPT1 knockout mice the total expression and surface membrane abundance of the GluA4 AMPA receptor subunit was decreased, whereas PPT1 knockout had no effect on GluA1 or GluA2 AMPA subunits nor on NMDA receptor subunit expression or surface abundance (Finn et al., 2012).However, for most ion channels, the questions of which enzymes control deacylation, where this occurs in cells, and how the time course of acylation–deacylation cycles are regulated are largely unknown. Thus, whether deacylation plays an active role in channel regulation remains poorly understood.

S-acylation occurs at membrane interfaces.

Because the zDHHCs are transmembrane proteins and the catalytic DHHC domain is located at the cytosolic interface with membranes (Fig. 1 C), S-acylation of ion channels occurs at membrane interfaces. Although overexpression studies of recombinant mammalian zDHHCs in heterologous expression systems have indicated that most zDHHCs are localized to either the endoplasmic reticular or Golgi apparatus membranes (or both; Ohno et al., 2006), some zDHHCs are also found in other compartments, including the plasma membrane and trafficking endosomes (Thomas et al., 2012; Fukata et al., 2013). We know very little about the regulation and subcellular localization of most native zDHHC enzymes in different cell types, in large part because of the lack of high-quality antibodies that recognize native zDHHCs. However, some enzymes, including zDHHC2, can dynamically shuttle between different membrane compartments. Activity-dependent redistribution of zDHHC2 in neurons (Noritake et al., 2009) controls S-acylation of the postsynaptic scaffolding protein PSD-95, thereby regulating NMDA receptor function. Intriguingly, as ion channels themselves determine cellular excitability, this may provide a local feedback mechanism to regulate S-acylation status. Thus, although different zDHHCs may reside in multiple membrane compartments through which ion channels traffic, the subcellular location at which most ion channels are S-acylated, as well as the temporal dynamics, is largely unknown. As discussed below (see the “Tools to analyze ion channel S-acylation” section), we are starting to unravel some of the details, with ER exit, Golgi retention, recycling endosomes, and local plasma membrane compartments being key sites in the control of ion channel S-acylation (Fig. 2).

Local membrane and protein environment determines cysteine S-acylation.

The efficiency of S-acylation of cysteine residues is likely enhanced by its localization at membranes because the local concentration of fatty acyl CoA is increased near hydrophobic environments (Bélanger et al., 2001). Furthermore, S-acylation of polytopic transmembrane proteins such as ion channels would be facilitated when S-acylated cysteines are bought into close proximity of membranes by membrane targeting mechanisms such as transmembrane helices (Figs. 3 and and4).4). However, the S-acylated cysteine is located within 10 amino acids of a transmembrane domain in only ∼20% of identified S-acylated ion channel subunits, such as the TM4 site of GluA1–4 (and2).2). Most S-acylated cysteines are located either within intracellular loops (∼40%: Fig. 3, A and B) or the N- or C-terminal cytosolic domains (∼5% and 35%, respectively; Fig. 3, A and B). Furthermore, the majority of S-acylated cysteines located in intracellular loops or intracellular N- or C-terminal domains of ion channel subunits are within predicted regions of protein disorder (Fig. 3 B). This suggests that S-acylation may provide a signal to promote conformational restraints on such domains, in particular by providing a membrane anchor. For these sites, additional initiating membrane association signals are likely required adjacent to the site of S-acylation. Likely candidates include other hydrophobic domains (as for the TM2 site in GluA1–4 subunits; Fig. 4 A) and other lipid anchors (e.g., myristoylation in src family kinases, such as Fyn kinase). However, in >30% of S-acylated ion channels, the S-acylated cysteine is juxtaposed to a (poly) basic region of amino acids that likely allows electrostatic interaction with negative membrane phospholipids. The BK channel pore-forming α subunit, encoded by the KCNMA1 gene, provides a clear example of this latter mechanism. This channel is S-acylated within an alternatively spliced domain (STREX) in its large intracellular C terminus (Fig. 4 C). Immediately upstream of the S-acylated dicysteine motif is a polybasic region enriched with arginine and lysine. Site-directed mutation of these basic amino acids disrupts S-acylation of the downstream cysteine residues (Jeffries et al., 2012). Furthermore, phosphorylation of a consensus PKA site (i.e., introduction of negatively charged phosphate) into the polybasic domain prevents STREX S-acylation. Thus, at the STREX domain, an electrostatic switch, controlled by phosphorylation, is an important determinant of BK channel S-acylation. In other proteins, cysteine reactivity is also enhanced by proximity to basic (or hydrophobic) residues (Bélanger et al., 2001; Britto et al., 2002; Kümmel et al., 2010). Furthermore, cysteine residues are subject to a range of modifications including nitrosylation, sulphydration, reduction-oxidation (REDOX) modification, and formation of disulphide bonds (Sen and Snyder, 2010). Evidence is beginning to emerge that these reversible modifications are mutually competitive for S-acylation of target cysteines (see the “S-acylation and posttranslational cross-talk controls channel trafficking and activity” section; Ho et al., 2011; Burgoyne et al., 2012).Open in a separate windowFigure 3.S-acylation sites in ion channel pore-forming subunits. (A) Schematic illustrating different locations of cysteine S-acylation in transmembrane ion channels subunits. (B) Relative proportion of identified S-acylated cysteine residues: in each location indicated in A (top); in -C-, -CC-, or -Cx(2–3)C- motifs (middle); or in cytosolic regions of predicted protein disorder (bottom; determined using multiple algorithms on the DisProt server, http://www.disprot.org/metapredictor.php; Sickmeier et al., 2007) for transmembrane ion channel pore-forming subunits.Open in a separate windowFigure 4.Multisite S-acylation in ion channels controls distinct functions. (A–C) Schematic illustrating location of multiple S-acylated domains in AMPA receptor GluA1–4 subunits (A), NMDA receptor GluN2A subunits (B), and BK channel pore-forming α subunits (C), encoded by the Kcnma1 gene. Each domain confers distinct functions/properties on the respective ion channel and is regulated by distinct zDHHCs (see the “Control of ion channel cell surface expression and spatial organization in membranes” section for further details).

Table 2.

Accessory subunits and selected ion channel adapter proteins
ChannelSubunitGeneCandidate S-acylation sitesUniProt IDReferences
Voltage gated
CalciumCaVβ2aCacnb21MQCCGLVHRRRVRVQ8CC27Chien et al., 1996; Stephens et al., 2000; Heneghan et al., 2009; Mitra-Ganguli et al., 2009
PotassiumKChip2Kcnip234LKQRFLKLLPCCGPQALPSVSEQ9JJ69Takimoto et al., 2002
KChip3Kcnip335PRFTRQALMRCCLIKWILSSAAQ9QXT8Takimoto et al., 2002
BK β4Kcnmb4193VGVLIVVLTICAKSLAVKAEAQ9JIN6Chen et al., 2013
Adapter proteins that interact with ion channelsPICK1Pick1404TGPTDKGGSWCDS-stopQ62083Thomas et al., 2013
Grip1bGrip11MPGWKKNIPICLQAEEQEREQ925T6-2Thomas et al., 2012; Yamazaki et al., 2001
psd-95Dlg41MDCLCIVTTKKYRQ62108Topinka and Bredt, 1998
S-delphilinGrid2ip1MSCLGIFIPKKHQ0QWG9-2Matsuda et al., 2006
Ankyrin-GAnk360YIKNGVDVNICNQNGLNALHLF1LNM3He et al., 2012
Open in a separate windowCommon channel abbreviation and subunit as well as gene names are given. Candidate S-acylation sites: experimentally determined cysteine residues (bold) with flanking 10 amino acids. Underlines indicate predicted transmembrane domains. Amino acid numbering corresponds to the UniProt ID. References: selected original supporting citations.Although these linear amino acid sequence features are likely to be important for efficient S-acylation, there is no canonical “consensus” S-acylation motif analogous to the linear amino acid sequences that predict sites of phosphorylation. Of the experimentally validated ion channel subunits shown to be S-acylated, ∼70% of candidate S-acylated cysteines are predominantly characterized as single cysteine (-C-) motifs, whereas dicysteine motifs (-CC-) and (CX(1–3)C-) motifs comprise ∼10% and 20% of all sites, respectively (Fig. 3 B). However, several freely available online predictive tools have proved successful in characterizing potential new palmitoylation targets. In particular, the latest iteration of the multiplatform CSS-palm 4.0 tool (Ren et al., 2008) exploits a Group-based prediction algorithm by comparing the surrounding amino acid sequence similarity to that of a set of 583 experimentally determined S-acylation sites from 277 distinct proteins. CSS-palm 4.0 predicts >80% of the experimentally identified ion channel S-acylation sites (Location of S-acylated cysteine is important for differential control of channel function.Many proteins are S-acylated at multiple sites. A remarkable example of this, in the ion channel field, is the recent identification of 18 S-acylated cysteine residues in the skeletal muscle ryanodine receptor/Ca2+-release channel (RyR1). The S-acylated cysteine residues are distributed throughout the cytosolic N terminus, including domains important for protein–protein interactions (Chaube et al., 2014). Although deacylation of skeletal muscle RyR1 reduces RyR1 activity, the question of which of these cysteine residues in RyR1 are important for this effect and whether distinct S-acylated cysteines in RyR1 control different functions and/or properties remains to be determined.However, both ligand-gated (NMDA and AMPA) and voltage-gated (BK) channels provide remarkable insights into how S-acylation of different domains within the same polytopic protein can exert fundamentally distinct effects (Fig. 4). For example, S-acylation of the hydrophobic cytosolic TM2 domain located at the membrane interface of the AMPA GluA1 subunit (Fig. 4 A) decreases AMPA receptor surface expression by retaining the subunit at the Golgi apparatus (Hayashi et al., 2005). In contrast, depalmitoylation of the C-terminal cysteine in GluA1 results in enhanced PKC-dependent phosphorylation of neighboring serine residues, which results in increased interaction with the actin-binding protein 4.1N in neurons, leading to enhanced AMPA plasma membrane insertion (Lin et al., 2009). S-acylation of the C-terminal cluster of cysteine residues (Fig. 4 B, Cys II site) in GluN2A and GluN2B controls Golgi retention, whereas palmitoylation of the cysteine cluster (Cys I site) proximal to the M4 transmembrane domain controls channel internalization (Hayashi et al., 2009). Distinct roles of S-acylation on channel trafficking and regulation are also observed in BK channels (Figs. 4 C and and5).5). S-acylation of the N-terminal intracellular S0-S1 linker controls surface expression, in part by controlling ER and Golgi exit of the channel (Jeffries et al., 2010; Tian et al., 2012), whereas S-acylation of the large intracellular C terminus, within the alternatively spliced STREX domain, controls BK channel regulation by AGC family protein kinases (Tian et al., 2008; Zhou et al., 2012).Open in a separate windowFigure 5.S-acylation controls BK channel trafficking and regulation by AGC family protein kinases via distinct sites. The BK channel STREX splice variant pore-forming α subunit is S-acylated at two sites: the S0-S1 loop and the STREX domain in the large intracellular C terminus. S-acylation of the S0-S1 loop promotes high surface membrane expression of the channel; thus, deacylation of this site decreases the number of channels at the cell surface (see the “Control of ion channel cell surface expression and spatial organization in membranes” section for further details). In contrast, S-acylation of the STREX domain allows inhibition of channel activity by PKA-mediated phosphorylation of a PKA serine motif (closed hexagon) immediately upstream of the palmitoylated cysteine residues in STREX. In the S-acylated state, PKC has no effect on channel activity even though a PKC phosphorylation site serine motif is located immediately downstream of the STREX domain (open triangle). Deacylation of STREX dissociates the STREX domain from the plasma membrane, and exposes the PKC serine motif so that it can now be phosphorylated by PKC (closed triangle), resulting in channel inhibition. In the deacylated state, PKA has no effect on channel activity (open hexagon). Thus, deacylation of the STREX domain switches channel regulation from a PKA-inhibited to a PKC-inhibited phenotype (see the “S-acylation and posttranslational cross-talk controls channel trafficking and activity” section for further details).How does S-acylation of distinct domains control such behavior, and are distinct sites on the same protein acylated by distinct zDHHCs? A systematic small interfering RNA (siRNA) screen of zDHHC enzymes mediating BK channel S-acylation indicated that distinct subsets of zDHHCs modify discrete sites. The S0-S1 loop is S-acylated by zDHHCs 22 and 23, whereas the STREX domain is S-acylated by several zDHHCs including 3, 9, and 17 (Tian et al., 2008, 2012). In both cases, each domain has two distinct S-acylated cysteines; however, whether these cysteines are differentially S-acylated by specific zDHHCs is unknown, Furthermore, whether multiple zDHHCs are required because the domains undergo repeated cycles of S-acylation and deacylation, and thus different zDHHCs function at different stages of the protein lifecycle, remains to be determined. Although systematic siRNA screens have, to date, not been performed on other ion channels, data from other multiply S-acylated channels, such as NMDA, AMPA, and BK channel subunits, supports the hypothesis that zDHHCs can show substrate specificity (Hayashi et al., 2005, 2009; Tian et al., 2010).It is generally assumed that S-acylation facilitates the membrane association of protein domains. This is clearly the case for peripheral membrane proteins, such as RAS or PSD-95, but direct experimental evidence for S-acylation controlling membrane association of the cytosolic domains of transmembrane proteins is largely elusive. One of the best examples involves the large C-terminal domain of the BK channel, which comprises more than two-thirds of the pore-forming subunit (Fig. 5). In the absence of S-acylation of the STREX domain, or exclusion of the 59–amino acid STREX insert, the BK channel C terminus is cytosolic (Tian et al., 2008). However, if the STREX domain is S-acylated, the entire C terminus associates with the plasma membrane, a process that can be dynamically regulated by phosphorylation of a serine immediately upstream of the S-acylated cysteines in the STREX domain (Tian et al., 2008). This S-acylation–dependent membrane association markedly affects the properties and regulation of the channel (Jeffries et al., 2012) and has been proposed to confer significant structural rearrangements. In support of such structural rearrangement, S-acylated STREX channels are not inhibited by PKC-dependent phosphorylation even though a PKC phosphorylation site serine motif, conserved in other BK channel variants, is present downstream of the STREX domain. In other BK channel variants lacking the STREX insert, this PKC site is required for channel inhibition by PKC-dependent phosphorylation. However, after deacylation of the STREX domain, PKC can now phosphorylate this PKC phosphorylation serine motif, which suggests that the site has become accessible, consequently resulting in channel inhibition (Fig. 5; Zhou et al., 2012).How might S-acylation of a cysteine residue juxtaposed to another membrane anchoring domain control protein function? The simplest mechanism would involve acting as an additional anchor (Fig. 3 A). In some systems, juxta-transmembrane palmitoylation allows tilting of transmembrane domains, effectively shortening the transmembrane domain to reduce hydrophobic mismatch (Nyholm et al., 2007), particularly at the thinner ER membrane (Abrami et al., 2008; Charollais and Van Der Goot, 2009; Baekkeskov and Kanaani, 2009), and confer conformational restraints on the peptide (Fig. 3 A). Such a mechanism has been proposed to control ER exit of the regulatory β4 subunits of BK channels. In this case, depalmitoylation of a cysteine residue juxtaposed to the second transmembrane domain of the β4 subunits may result in hydrophobic mismatch at the ER, reducing ER exit, and yield a conformation that is unfavorable for interaction with BK channel α subunits, thereby decreasing surface expression of BK channel α subunits (Chen et al., 2013).

Tools to analyze ion channel S-acylation

Before the seminal discovery of the mammalian enzymes that control S-acylation (Fukata et al., 2004) and current advances in proteomic techniques to assay S-acylation, progress in the field was relatively slow, largely because of the lack of pharmacological, proteomic, and genetic tools to investigate the functional role of S-acylation. It is perhaps instructive to consider that protein tyrosine phosphorylation was discovered the same year as S-acylation (Hunter, 2009). However, the subsequent rapid identification and cloning of tyrosine kinases provided a very extensive toolkit to investigate this pathway. Although the S-acylation toolkit remains limited, the last few years have seen rapid progress in our ability to interrogate S-acylation function and its control of ion channel physiology. Furthermore, S-acylation prediction algorithms, such as CSS-palm 4.0 (Ren et al., 2008), provide an in silico platform to inform experimental approaches for candidate targets.

Pharmacological tools.

The S-acylation pharmacological toolkit remains, unfortunately, empty, with limited specific agents with which to explore S-acylation function in vitro or in vivo. Although the palmitate analogue 2-bromopalmitate (2-BP) is widely used for cellular assays and to analyze ion channel regulation by S-acylation, caution must be taken in using this agent, even though it remains our best pharmacological inhibitor of zDHHCs (Resh, 2006; Davda et al., 2013; Zheng et al., 2013). Unfortunately, 2-BP is a nonselective inhibitor of lipid metabolism and many membrane-associated enzymes, and displays widespread promiscuity (e.g., Davda et al., 2013); does not show selectivity toward specific zDHHC proteins (Jennings et al., 2009); has many pleiotropic effects on cells at high concentrations, including cytotoxicity (Resh, 2006); and also inhibits acylthioesterases (Pedro et al., 2013). Other lipid inhibitors include cerulenin and tunicamycin. However, cerulenin affects many aspects of lipid metabolism, and tunicamycin inhibits N-linked glycosylation (Resh, 2006). Although some nonlipid inhibitors have been developed, these are not widely used (Ducker et al., 2006; Jennings et al., 2009), and there are currently no known activators of zDHHCs or compounds that inhibit specific zDHHCs. In the last few years, several inhibitors for the acylthioesterases LYPLA1 and LYPLA2 have been developed (Bachovchin et al., 2010; Dekker et al., 2010; Adibekian et al., 2012). However, several of these compounds, such as palmostatin B, are active against several members of the larger serine hydrolase family. Clearly, the development of novel S-acylation inhibitors and activators that display both specificity and zDHHC selectivity would represent a substantial advance for investigation of channel S-acylation.

Genetic tools.

To date, most studies have used overexpression of candidate zDHHCs in heterologous expression or native systems and analyzed increases in [3H]palmitate incorporation to define zDHHCs that may S-acylate specific ion channels (e.g. Rathenberg et al., 2004; Hayashi et al., 2005, 2009; Tian et al., 2010; Thomas et al., 2012). Although this is a powerful approach, caution is required to determine whether results obtained with overexpression in fact replicate endogenous regulation. For example, overexpression of some zDHHCs normally expressed in the cell type of interest can result in S-acylation of a cysteine residue that is not endogenously palmitoylated in BK channels (Tian et al., 2010). Point mutation of the cysteine of the catalytic DHHC domain abolishes the acyltransferase activity of zDHHCs and is thus an invaluable approach to confirming that the acyltransferase function of overexpressed zDHHC is required by itself. Increasingly, knockdown of endogenous zDHHCs using siRNA, and related approaches, is beginning to reveal the identity of zDHHCs that S-acylate native ion channel subunits. For example, knockdown of zDHHCs 5 or 8 reduces S-acylation of the accessory subunits PICK1 and Grip1, which control AMPA receptor trafficking (Thomas et al., 2012, 2013); and knockdown of zDHHC2 disrupts local nanoclusters of the PDZ domain protein PSD-95 in neuronal dendrites to control AMPA receptor membrane localization (Fukata et al., 2013). However, relatively few studies have taken a systematic knockdown approach to identify zDHHCs important for ion channel S-acylation. One such approach has, however, revealed that multiple, distinct zDHHCs mediate palmitoylation of the BK channel C terminus (zDHHCs 3, 5, 7, 9, and 17) and that a different subset of zDHHCs (22 and 23) mediate S-acylation of the intracellular S0-S1 loop in the same channel (Tian et al., 2010, 2012). Because some zDHHCs are themselves palmitoylated, the functional effect of overexpressing or knocking down individual zDHHCs on the localization and activity of other zDHHCs must also be carefully determined. For example, siRNA-mediated knockdown of zDHHC 5, 7, or 17 in HEK293 cells paradoxically results in an up-regulation of zDHHC23 mRNA expression (Tian et al., 2012). Furthermore, because many signaling and cytoskeletal elements are also controlled by S-acylation, direct effects on channel S-acylation by themselves must be evaluated in parallel (for example using site-directed cysteine mutants of the channel subunit). Fewer studies have used these approaches to examine the role of acylthioesterases, although overexpression of LYPLA1 and a splice variant of LYPLAL1, but not LYPLA2, deacylates the S0-S1 loop of the BK channel, promoting Golgi retention of the channels (Tian et al., 2012). Gene-trap and knockout mouse models for some zDHHCs (such as 5 and 17) are becoming available, although full phenotypic analysis and analysis of ion channel function in these models are largely lacking.

Proteomic and imaging tools. Lipid-centric (metabolic) labeling assays.

Metabolic labeling approaches are most suited to analysis of isolated cells, rather than tissues, but provide information on dynamic palmitoylation of proteins during the relatively short (∼4 h) labeling period as well as insight into the species of lipid bound to cysteine residues. The classical approach using radioactive palmitate (e.g., [3H]palmitate) remains a “gold standard” for validation, in particular for identification that palmitate is the bound lipid. However, metabolic labeling with [3H]palmitate generally requires immunoprecipitation and days to weeks of autoradiography or fluorography, particularly when analyzing low abundance membrane proteins such as ion channels. To overcome some of these issues, and also to provide a platform to allow cellular imaging of S-acylation, a variety of biorthogonal lipid probes have recently been developed (Hannoush and Arenas-Ramirez, 2009; Hannoush, 2012; Martin et al., 2012; for reviews see Charron et al., 2009a; Hannoush and Sun, 2010). These probes are modified fatty acids with reactive groups, such as an azide or alkyne group, allowing labeled proteins to be conjugated to biotin or fluorophores via the reactive group using Staudinger ligation or “click” chemistry. In particular, development of a family of ω-alkynyl fatty acid probes of different chain lengths (such as Alk-C16 and Alk-C18) have been exploited for proteomic profiling as well as single cell imaging (Gao and Hannoush, 2014) and have been used to identify candidate S-acylated channels in several mammalian cell lines (Charron et al., 2009b; Hannoush and Arenas-Ramirez, 2009; Martin and Cravatt, 2009; Yap et al., 2010; Yount et al., 2010; Martin et al., 2012). It is important to note that palmitic acid can also be incorporated into free N-terminal cysteines of proteins via an amide linkage (N-palmitoylation), addition of the monounsaturated palmitoleic acid via an oxyester linkage to a serine residue (O-palmitoylation), and oleic acid (oleoylation) as well as myristate via amide linkages on lysine residues (Stevenson et al., 1992; Linder and Deschenes, 2007; Hannoush and Sun, 2010; Schey et al., 2010). These modifications can be discriminated from S-acylation by their insensitivity to hydroxylamine cleavage (at neutral pH) compared with the S-acylation thioester linkage. Whether N- or O-linked palmitoylation or oleoylation controls ion channel function remains to be determined.

Cysteine centric (cysteine accessibility) assays: Acyl-biotin exchange (ABE) and resin-assisted capture (Acyl-RAC).

The metabolic labeling approach requires treating isolated cells with lipid conjugates and thus largely precludes analysis of native S-acylation in tissues. However, several related approaches have been developed that exploit the exposure of a reactive cysteine after hydroxylamine cleavage (at neutral pH) of the cysteine-acyl thioester linkage. The newly exposed cysteine thiol can then react with cysteine-reactive groups (such as biotin-BMCC or biotin-HPDP used in the ABE approach; Drisdel and Green, 2004; Drisdel et al., 2006; Draper and Smith, 2009; Wan et al., 2007) or thiopropyl sepharose (used in Acyl-RAC; Forrester et al., 2011) to allow purification of S-acylated proteins that can be identified by Western blot analysis or mass spectrometry. Acyl-RAC has been reported to improve detection of higher molecular weight S-acylated proteins and thus may prove valuable for ion channel analysis. These approaches have been exploited to determine the “palmitoylome” in several species and tissues (e.g., Wan et al., 2007, 2013; Kang et al., 2008; Martin and Cravatt, 2009; Yang et al., 2010; Yount et al., 2010; Merrick et al., 2011; Wilson et al., 2011; Jones et al., 2012; Ren et al., 2013). For example, analysis of rat brain homogenates identified both previously characterized as well as novel S-acylated ion channels (Wan et al., 2013), although it must be remembered that these approaches detect S-acylation and do not define S-palmitoylation per se. Cysteine accessibility approaches determine the net amount of preexisting S-acylated proteins; however, caution is required to eliminate false positives. In particular it is necessary to fully block all reactive cysteines before hydroxylamine cleavage; moreover, the identity of the endogenously bound lipid is of course not known.The lipid- and cysteine-centric approaches are thus complementary. In conjunction with site-directed mutagenesis of candidate S-acylated cysteine residues in ion channel subunits, these approaches have provided substantial insight into the role and regulation of ion channel S-acylation (Fukata et al., 2013). However, this approach does not directly confirm that the protein is S-acylated per se. Furthermore, in most ion channels, and in fact most S-acylated proteins, the identity of the native lipid bound to a specific S-acylated cysteine is not known. Although palmitate is considered to be the major lipid species involved in S-acylation, this has not been directly demonstrated in most cases, and other fatty acids, including arachidonic acid, oleate acid, and stearic acid, have also been reported to bind to cysteine via a thioester S-linkage (Linder and Deschenes, 2007; Hannoush and Sun, 2010). A major reason for this discrepancy is that mass spectrometry–based approaches to identify the native lipid specifically bound to S-acylated cysteines remain a significant challenge. This is particularly true for low abundance proteins such as mammalian ion channels, in contrast to the widespread application of mass spectrometry to directly identify native amino acids that are phosphorylated (Kordyukova et al., 2008, 2010; Sorek and Yalovsky, 2010; McClure et al., 2012; Ji et al., 2013). As such, direct biochemical demonstration of native cysteine S-acylation is lacking in most ion channels.

S-acylation and control of the ion channel lifecycle

Ion channel physiology is determined by both the number of channel proteins at the cognate membrane and by their activity and/or kinetics at the membrane. Evidence has begun to emerge that S-acylation of either pore-forming or regulatory subunits of ion channels controls all of these aspects of ion channel function. Although the focus of this review is S-acylation–dependent regulation of ion channel subunits itself, S-acylation also regulates the localization or activity of many adaptor, scaffolding, and cellular signaling proteins (e.g., G protein–coupled receptors [GPCRs], AKAP18, AKAP79/150, G proteins, etc.), as well as other aspects of cell biology that affect ion channel trafficking and the activity and regulation of macromolecular ion channel complexes (El-Husseini and Bredt, 2002; Linder and Deschenes, 2007; Fukata and Fukata, 2010; Greaves and Chamberlain, 2011; Shipston, 2011; Resh, 2012).

Control of ion channel cell surface expression and spatial organization in membranes.

The control of ion channel trafficking, from synthesis in the ER through modification in the Golgi apparatus to subsequent delivery to the appropriate cellular membrane compartment, is a major mechanism whereby S-acylation modulates ion channel physiology. S-acylation may influence the number of ion channels resident in a membrane through regulation of distinct steps in the ion channel lifecycle (Fig. 2). Indeed S-acylation has been implicated in ion channel synthesis, as well as in channel trafficking to the membrane and subsequent internalization, recycling, and degradation. S-acylation controls the maturation and correct assembly of ion channels early in the biosynthetic pathway. For example, S-acylation regulates assembly of the ligand gated nicotinic acetylcholine receptor (nAChR) to ensure a functional binding site for acetylcholine (Alexander et al., 2010) as well as controlling its surface expression (Amici et al., 2012). S-acylation is also an important determinant of the maturation of both voltage-gated sodium (Nav1.2) and voltage-gated potassium channels (Kv1.5; Schmidt and Catterall, 1987; Zhang et al., 2007). S-acylation also contributes to the efficient trafficking of channels from the ER to Golgi and to post-Golgi transport. Three examples illustrate the importance and potential complexity of S-acylation in controlling ion channel trafficking:(1) S-acylation of a cysteine residue adjacent to a hydrophobic region (TM2) in a cytosolic loop of the GluA1 pore-forming subunit of AMPA receptors (Fig. 4 A) promotes retention of the channel in the Golgi (Hayashi et al., 2005). However, S-acylated Grip1b, a PDZ protein that binds to AMPA receptors, is targeted to mobile trafficking vesicles in neuronal dendrites and accelerates local recycling of AMPA receptors to the plasma membrane (Thomas et al., 2012). In contrast, S-acylation of another AMPA receptor interacting protein, PICK1, is proposed to stabilize AMPA receptor internalization (Thomas et al., 2013).(2) S-acylation of a cluster of cysteine residues juxtaposed to the transmembrane 4 domain (Cys I site) of the NMDA receptor subunit GluN2A (Fig. 4 B) increases surface expression of NMDA receptors by decreasing their constitutive internalization. In contrast S-acylation at C-terminal cysteine residues (Cys II site) decreases their surface expression by introducing a Golgi retention signal that decreases forward trafficking (Hayashi et al., 2009). Even though both sites affect surface expression, only S-acylation of the TM4 juxtaposed cysteine residues influences synaptic incorporation of NMDA receptors, which suggests that this site is an important determinant of the synaptic versus extrasynaptic localization of these ion channels (Mattison et al., 2012). Together, these data highlight the importance of S-acylation of two distinct sites within the same ion channel as well as that of components of the ion channel multimolecular complex as determinants of channel trafficking.(3) S-acylation of a cluster of cysteine residues in the intracellular S0-S1 loop of the pore-forming subunit (Figs. 4 C and and5)5) is required for efficient exit of BK channels from the ER and the trans-Golgi network. Deacylation at the Golgi apparatus appears to be an important regulatory step (Tian et al., 2012). BK channel surface abundance may also be controlled by S-acylation of regulatory β4 subunits. β4 subunit S-acylation on a cysteine residue juxtaposed to the second transmembrane domain is important for the ability of the β4 subunit itself to exit the ER. Importantly, assembly of β4 subunits with specific splice variants of pore-forming α subunits of the BK channel enhances surface expression of the channel, a mechanism that depends on S-acylation of the β4 subunit (Chen et al., 2013). Thus, in BK channels, S-acylation of the S0-S1 loop of the pore-forming subunit controls global BK channel surface expression, and β4 subunit S-acylation controls surface expression of specific pore-forming subunit splice variants. S-acylation of the Kchip 2 and Kchip 3 accessory subunits also controls surface expression of voltage-gated Kv4.3 channels (Takimoto et al., 2002).Moreover, S-acylation modulates the spatial organization of ion channels within membranes. Perhaps the most striking example involves aquaporin 4 (AQP4), where S-acylation of two N-terminal cysteine residues in an N-terminal splice variant (AQP4M1) inhibits assembly of AQP4 into large orthogonal arrays (Suzuki et al., 2008; Crane and Verkman, 2009), perhaps by disrupting interactions within the AQP4 tetramer. S-acylation can affect the distribution of the many membrane-associated proteins between cholesterol-rich microdomains (lipid rafts) and the rest of the membrane. Such clustering has also been reported for various transmembrane proteins, including the P2x purinoceptor 7 (P2X7) receptor, in which S-acylation of the C terminus promotes clustering into lipid rafts (Gonnord et al., 2009). A similar mechanism may underlie synaptic clustering of GABAA receptors mediated by S-acylation of an intracellular loop of the y2 subunit (Rathenberg et al., 2004). In these examples, S-acylation of the channel itself affects membrane partitioning and organization. However, recent evidence in neurons suggests that establishment of “nano” domains of ion channel complexes in postsynaptic membranes may also be established by local clustering of the cognate acyltransferase itself. For example, clustering of zDHHC2 in the postsynaptic membranes of individual dendritic spines provides a mechanism for local control of S-acylation cycles of the PDZ protein adapter, PSD-95, and thereby for controlling its association with the plasma membrane. PSD-95, in turn, can assemble with various ion channels, including NMDA receptors, and can thus dynamically regulate the localization and clustering of ion channel complexes (Fukata et al., 2013). Indeed, an increasing number of other ion channel scaffolding proteins such as Grip1 (Thomas et al., 2012), PICK1 (Thomas et al., 2013), S-delphilin (Matsuda et al., 2006), and Ankyrin G (He et al., 2012) that influence ion channel trafficking, clustering, and localization are now known to be S-acylated.Relatively few studies have identified effects of S-acylation on the intrinsic gating kinetics or pharmacology of ion channels at the plasma membrane. However, a glycine-to-cysteine mutant (G1079C) in the intracellular loop between domains II and III enhances the sensitivity of the voltage-gated Na channel Nav1.2a to the toxins PaurTx3 and ProTx-II, an effect blocked by inhibition of S-acylation. These toxins control channel activation through the voltage sensor in domain III. In addition, deacylation of another (wild-type) cysteine residue (C1182) in the II–III loop produces a hyperpolarizing shift in both activation and steady-state inactivation as well as slowing the recovery from fast inactivation and increasing sensitivity to PaurTx3 (Bosmans et al., 2011). Effects of S-acylation on gating kinetics have also been reported in other channels. For example, in the voltage-sensitive potassium channel Kv1.1, S-acylation of the intracellular linker between transmembrane domains 2 and 3 increases the intrinsic voltage sensitivity of the channel (Gubitosi-Klug et al., 2005). S-acylation of the β and γ subunits of epithelial sodium channels (ENaC) also affects channel gating (Mueller et al., 2010; Mukherjee et al., 2014), and the S-acylated regulatory β2a subunit of N-type calcium channels controls voltage-dependent inactivation (Qin et al., 1998; Hurley et al., 2000).S-acylation is also an important determinant of retrieving ion channels from the plasma membrane for recycling or degradation. S-acylation of a single cysteine residue juxtaposed to the transmembrane TM4 domain of GluA1 and GluA2 subunits of AMPA receptors controls agonist-induced ion channel internalization. These residues are distinct from those controlling Golgi retention of AMPA receptors (Fig. 4 A), which emphasizes the finding that the location and context of the S-acylated cysteines, even in the same protein, is central for their effects on physiological function (Hayashi et al., 2005; Lin et al., 2009; Yang et al., 2009). The stability of many proteins is also regulated by S-acylation; S-acylation of a single cysteine residue in Kv1.5 promotes both its internalization and its degradation (Zhang et al., 2007; Jindal et al., 2008). Thus, in different ion channels, S-acylation can have opposite effects on insertion, membrane stability, and retrieval.

S-acylation and posttranslational cross-talk control channel trafficking and activity.

An emerging concept is that S-acylation is an important determinant of ion channel regulation by other PTMs. Indeed, nearly 20 years ago it was reported that PKC-dependent phosphorylation of the GluK2 (GluR6) subunit of Kainate receptors was attenuated in channels S-acylated at cysteine residues near the PKC consensus site (Pickering et al., 1995). S-acylation of GluA1 subunits of AMPA receptors also blocks PKC phosphorylation of GluA1 and subsequently prevents its binding to the cytoskeletal adapter protein 4.1N, ultimately disrupting AMPA receptor insertion into the plasma membrane (Lin et al., 2009). Intriguingly, PKC phosphorylation and S-acylation have the opposite effect on 4.1N-mediated regulation of Kainate receptor (GluK2 subunit) membrane insertion: in this, case S-acylation promotes 4.1N interaction with Kainate receptors and thereby receptor insertion, whereas PKC phosphorylation disrupts 4.1N interaction, promoting receptor internalization (Copits and Swanson, 2013). Disruption of phosphorylation by S-acylation of residues near consensus phosphorylation sites likely results from steric hindrance, as proposed for S-acylation–dependent regulation of β2 adrenergic receptor phosphorylation (Mouillac et al., 1992; Moffett et al., 1993).S-acylation has also been reported to promote ion channel phosphorylation. For example, site-directed mutation of a cluster of palmitoylated cysteine residues in the GluN2A subunit of NMDA receptors abrogates Fyn-dependent tyrosine phosphorylation at a site between TM4 and the palmitoylated cysteines (Hayashi et al., 2009). Therefore, S-acylation of GluN2A promotes tyrosine phosphorylation, resulting in reduced internalization of the NMDA receptor (Hayashi et al., 2009). Furthermore, S-acylation of BK channels can act as a gate to switch channel regulation to different AGC family kinase signaling pathways, emphasizing the complex interactions that can occur between signaling pathways (Tian et al., 2008; Zhou et al., 2012; Fig. 5). S-acylation of an alternatively spliced insert (STREX) in the large cytosolic domain of the pore-forming subunit of BK channels promotes association of the STREX domain with the plasma membrane. S-acylation of the STREX insert is essential for the functional inhibition of STREX BK channels by PKA-mediated phosphorylation of a serine residue immediately upstream of the S-acylated cysteines. PKA phosphorylation dissociates the STREX domain from the plasma membrane (Tian et al., 2008), preventing STREX domain S-acylation (Jeffries et al., 2012) and leading to channel inhibition. However, deacylation of the STREX domain exposes a PKC consensus phosphorylation site downstream of the STREX domain, allowing PKC to inhibit STREX BK channels (Zhou et al., 2012). Thus, S-acylation acts as a reversible switch to specify regulation by AGC family kinases through control of the membrane association of a cytosolic domain of the channel: S-acylated STREX BK channels are inhibited by PKA but insensitive to PKC, whereas deacylated channels are inhibited by PKC but not PKA (Fig. 5). The reciprocal control of membrane association of a protein domain by S-acylation and protein phosphorylation likely represents a common mechanism in other signaling proteins as revealed for phosphodiesterase 10A (Charych et al., 2010).Cysteine residues are targets for several other modifications that regulate various ion channels, including nitrosylation, sulphydration, REDOX regulation, and formation of disulphide bonds (Sen and Snyder, 2010). Evidence is beginning to emerge that S-acylation may mutually compete with these mechanisms, providing a dynamic network to control cysteine reactivity. For example, the ion channel scaffolding PDZ domain protein PSD-95 is S-acylated at two N-terminal cysteine residues (C3 and C5) that are required for membrane targeting and clustering of PSD-95 (El-Husseini et al., 2002). nNOS also interacts with PSD-95, and stimulation of nitric oxide production results in nitrosylation of these cysteines, preventing their S-acylation and thereby decreasing PSD-95 clusters at postsynaptic sites (Ho et al., 2011). A recent remarkable example of the potential for such cross-talk in ion channel subunits is the identification of the S-acylation of 18 different cysteine residues in the large cytosolic N terminus of RyR1 in skeletal muscle. Of these 18 S-acylated cysteines, six have previously been identified as targets for S-oxidation, and a further cysteine residue was also subject to S-nitrosylation (Chaube et al., 2014) Although the functional relevance of this potential cross-talk in RyR1 has yet to be defined, interaction between oxidation and S-acylation of the same cysteine residue is physiologically relevant in other proteins. For example, oxidation of the signaling protein HRas at two cysteine residues C181/184 prevents S-acylation of these residues, resulting in a loss of plasma membrane localization of this peripheral membrane signaling protein (Burgoyne et al., 2012). Intriguingly, a conserved cysteine residue in nAChR α3 subunits, which has been shown to be S-acylated (C273) in the nAChR α4 subunit, has been implicated in use-dependent inactivation of nAChRs by reactive oxygen species (Amici et al., 2012). Determining whether these mutually competitive cysteine modifications represent an important mechanism for regulation of a range of ion channels is an exciting challenge for the future.S-acylation is also an important determinant of ion channel regulation by heterotrimeric G proteins. This can involve S-acylation of either G protein targets or of regulators of G proteins. In an example of the former, the palmitoylated N terminus of the regulatory β2a subunit splice variant acts as a steric inhibitor of an arachidonic acid binding domain to stimulate N-type calcium channels (Chien et al., 1996; Heneghan et al., 2009; Mitra-Ganguli et al., 2009). When the regulatory β subunits are not S-acylated, however, Gq-mediated signaling, via arachidonic acid, inhibits calcium channel activity. Closure of G protein regulated inward rectifying potassium (GIRK) channels in neurons after Gi/o deactivation provides an example of the latter (Jia et al., 2014). Signaling by members of the Gi/o family of the Gα subunit of heterotrimeric G proteins is terminated by members of the regulator of G protein signaling 7 (R7 RGS) family of GTPase-activating proteins, which accelerate GTP hydrolysis to speed Gi/o deactivation. Membrane localization of regulator of G protein signaling 7 (R7-RGS) is required for its regulation of Gi/o, and this is determined by interaction with an S-acylated R7 binding protein (R7-BP) that acts as an allosteric activator. Thus, the R7-RGS complex, recruited to the plasma membrane by S-acylated R7-BP, promotes Gi/o deactivation to facilitate GIRK channel closure. Conversely, deacylation of R7-BP removes the R7-GS complex from the plasma membrane, slowing Gi/o deactivation and consequent channel closure (Jia et al., 2014). Clearly, as S-acylation can also control an array of GPCRs, enzymes, and signaling and adapter proteins that indirectly control ion channel function (El-Husseini and Bredt, 2002; Linder and Deschenes, 2007; Fukata and Fukata, 2010; Greaves and Chamberlain, 2011; Shipston, 2011; Resh, 2012), understanding how S-acylation dynamically controls other components of ion channel multimolecular signaling complexes will be an essential future goal.

Summary and perspectives

With an ever-expanding “catalog” of S-acylated ion channel pore-forming and regulatory subunits (∼50 to date), together with an array of S-acylated scaffolding and signaling proteins, the importance and ubiquity of this reversible covalent lipid modification in controlling the lifecycle and physiological function and regulation of ion channels is unquestionable. This has been paralleled by a major resurgence in the wider S-acylation field, a consequence in large part of the discovery of S-acylating and deacylating enzymes together with a growing arsenal of genetic, proteomic, imaging, and pharmacological tools to assay and interrogate S-acylation function.As for most other posttranslational modifications of ion channels, including phosphorylation, major future goals for the field include:(1) Understanding mechanistically how covalent addition of a fatty acid can control such a diverse array of ion channel protein properties and functions, and how this is spatiotemporally regulated.(2) Elucidating the physiological relevance of this posttranslational modification from the level of single ion channels to the functional role of the channel in the whole organism in health and disease.Elucidation of these issues has fundamental implications far beyond ion channel physiology.To address these goals several major challenges and questions must be addressed, including:(1) It is largely assumed that S-acylation of transmembrane proteins results in an additional “membrane anchor” to target domains to the membrane interface. However, understanding the mechanisms, forces, and impact of S-acylation on the orientation of transmembrane helices and the architecture and structure of disordered domains in cytosolic loops and linkers, while remaining a considerable technical challenge, should provide major insight into mechanisms controlling channel trafficking, activity, and regulation.(2) Although S-acylation is widely accepted to be reversible, its spatiotemporal regulation of most ion channels is unknown. Mechanistic insight into zDHHC and acylthioesterase substrate specificity, native subcellular localization, and assembly with ion channel signaling complexes will allow us to dissect and understand how S-acylation of ion channels is controlled. Importantly, this should allow us to take both “channel-centric” (e.g., site-directed mutagenesis of S-acylated cysteines) as well as “S-acylation centric” (e.g., knockout of specific zDHHC activity) approaches to understand how multisite S-acylation on the same ion channel subunit can control distinct functions as well as physiological regulation of trafficking and function at the plasma membrane.(3) The functional role of S-acylation cannot be viewed in isolation from other posttranslational modifications. The cross-talk between S-acylation and adjacent phosphorylation sites as well as other cysteine modifications highlights the importance of understanding the interactions between signaling pathways. Insight into the rules, mechanisms, and cross-talk of S-acylation with these modifications has broad implications for cellular signaling.(4) Although it is clear that disruption of S-acylation homeostasis itself has substantial effects on normal physiology, and we are beginning to understand some of the cellular functions of ion channel S-acylation, we know very little about the functional impact of disrupted ion channel S-acylation at the systems and organismal level. Understanding how this may be dynamically regulated during a lifespan is critical to understanding the role of S-acylation in health and disease.To address these issues, development of improved tools to assay and investigate S-acylation from the single protein to organism is required. For example, tools to allow the real-time analysis of S-acylation status of ion channels in cells and tissues will provide fundamental insights into its dynamics and role in ion channel trafficking and membrane localization. Improved proteomic tools will allow direct assay of fatty acids bound to cysteine residues via thioester linkages. Development of new tools and models are essential if we are to understand the physiological relevance of ionic channel S-acylation at the systems level. These include: specific inhibitors of zDHHCs and thioesterases, conditional knockouts to spatiotemporally control zDHHC expression, and transgenics expressing catalytically inactive zDHHCs and models expressing S-acylation–null ion channel subunits. Furthermore, our understanding of how S-acylation may be dynamically controlled during normal ageing in response to homeostatic challenge and disruption in disease states remains rudimentary. Whether we will start to uncover channel “S-acylationopathies” resulting from dysregulation of ion channel S-acylation, analogous to channel phosphorylopathies, remains to be explored. Addressing these issues, together with development of new tools, will provide a paradigm shift in our understanding of both ion channel and S-acylation physiology, and promises to reveal novel therapeutic strategies for a diverse array of disorders.  相似文献   

20.
Experimentally Increased Codon Bias in the Drosophila Adh Gene Leads to an Increase in Larval,But Not Adult,Alcohol Dehydrogenase Activity     
Winfried Hense  Nathan Anderson  Stephan Hutter  Wolfgang Stephan  John Parsch  David B. Carlini 《Genetics》2010,184(2):547-555
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