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CD8 Effector and Memory T Cells Differentiation

What controls CD8 effector and memory T cells differentiation?
Introduction:
The capability of initiating and cultivating a population of memory T cells is the key component of an effective adaptive immune response and the fundamental foundation for a productive vaccine since memory cells can trigger an aggressive response upon reinfection. Throughout an infection, T cells can differentiate into a multitude of effector and memory cells, which help resolve pathogenic invasion and promote protective immunity. Effector and memory CD8 T cells are one group of T cells that help cells maintain homeostasis by maintaining the proper proportion of heterogeneous cells in the immune system. Technical advances and progressive research has made it possible to unravel some of the mechanisms necessary in generating effector and memory CD8 T cells. Here, we discuss some regulatory molecules, transcriptional factors, and signaling pathways that contribute to current models of how heterogeneous populations of CD8 T cell arise after infection.
Separate-Precursor and Decreasing-potential model:
There are currently several models put forth to explain the rise of different differentiated states of CD8 T cells. Historically, one of the earliest models put forth is the separate-precursor model. In this model, naïve T cells are primed and pre-programmed in the thymus to evolve into the specific effector states. Thus, when the cells reach their peripheral locations, they can readily differentiate into their predetermined states. But, research revolving around cellular barcoding has shown that naïve T cells are actually multi-potent – thus this model seems unlikely,
The decreasing-potential model, on the other hand, suggests that the degree of differentiation is dependent on the duration of exposure to signaling molecules that the T cell encounters. Cumulative signaling will drive the naïve T cell into a differentiated state. This is seen when repetitive exposure of IL-2 drives T cells to proliferate and become terminally differentiated. However, once a cell becomes terminally differentiated, the cell looses other functional aspects – such as longevity and proliferative capabilities – an integral component of becoming a memory cell. However, the exact mechanism of how this process occurs is unclear.
Signaling strength model:
The signaling strength model states that formation of heterogeneous CD8 T cells is contingent on the overall strength of three signals (signal 1, 2, and 3) that are stimulated during early T cell priming. The strength and duration of signal 1 is mediated by antigens, signal 2 by co-stimulatory molecules, and signal 3 by inflammatory cytokines – each influencing later T cell development and differentiation. The aggregation of these signals results in clonal expansion and development into memory CD8 T cells, while superfluous signaling results in differentiation into effector CD8 T cells. Thus, CD8 T cell populations are delicately modulated by homeostatic mechanisms that are tightly coordinated with environmental cues and concentration gradients of signaling molecules.
But, how does CD8 T cells sense the intensity and duration of signals 1, 2, and 3 and then properly respond to these signals and differentiate into distinctive states? This model suggests that the stromal microenvironment that the T cell migrates to early in their development influences later cell commitments. The delicate balance between cytokines and signaling molecules directs the degree of differentiation – resulting in a continuum of cells that are essential for mediating a proper immune response. On one end of the continuum are naïve T cells that are highly proliferative, young, and can become memory cells while on the other end are cells that are terminally differentiated. In the middle are an array of cells with variability in these three characteristics.
To try and differentiate between this heterogeneous populations of CD8 T cells, scientists are trying to determine which phenotypic surface markers, individually or in combination, severe as an indicator of a particular cell lineage and differentiate those markers from markers that arise simply due to response from an infection. Simply put, can we determine which diverse set of expression surface molecules are necessary for cell lineages from markers due to environmental cues? In some ways, this seems like a likely avenue. In an acute infection, it has been shown that CD8 T cells with KLRG1lowIL-7Rhigh are more likely to survive after an infection than KLRG1highIL-7Rlow cells. This indicates that IL-7Rhigh cell induces T cells into a memory states, while KLRG1high populations stimulates the cells to become terminally differentiated. While these markers are useful, they have yet to capture the degree of heterogeneity seen in these CD8 T cells since other phenotypic or functional characteristics have been seen in these cells.
Another area of research of great interest is the role of transcriptional factors that are potentially linked to CD8 T cell differentiation and evolution into memory cells. From these researches, an important theme has emerged – the idea that pairs of transcriptional factors operate in an antagonistic fashion to mediate effector vs. memory cell fates. For example, high concentrations of T-bet foment CD8 T cells to become terminally differentiated, while high concentration of Eomes foster the development of memory cells. Thus, concentration gradients of these transcriptional pairs are key regulators in the differentiation of terminal effector cells and memory cells. Other transcriptional factor pairs include Bcl-6 and BLIMP1, ID3 and ID2, and STAT3 and STAT4.
The asymmetric cell fate model:
One of the last models mentioned is the asymmetric cell fate model. This model states different T cell populations arise from a single T cell precursor due to asymmetric cell division. During APC-T cell interaction, the proximal side of the T cell will adopt an effector cell fate, while the distal side of the T cell will adopt a memory cell fate. Evidence for this type of cell division and differentiation has been shown, however it does not explain all mechanisms associated with CD8 T cell differentiation. Overall, these models show the progression in our understanding of potential pathways that could explain how CD8 T cells can either become an effector or memory cell.
Signaling pathways:
As mentioned above, consolidated signaling via TCR, co-stimulatory receptors, and inflammatory cytokine receptors can shift the expression level of paired transcriptional factors, thus changing the differentiation states of CD8 T cells. Thus, it would be apparent to assume that this structural organization is also influenced by other signals such as signals from the PI3K/AKT signal transduction pathway. In particular, researchers have shown that molecules within this pathway can influence and regulate cell growth and protein synthesis thus directing CD8 differentiation. For example, mTOR stimulation results in terminal differentiation of effector T cells but lack differentiation of memory T cells. It has been suggested that mTOR regulates differentiation by regulating the concentration gradients of T-bet:Eomes since mTOR promotes T-bet expression while suppressing Eomes. Thus, increases in T-bet promotes effector T cell differentiation. Additionally, PI3K/AKT has been suggested to regulate T cell metabolism via FOXO1 by stimulating crosstalking with other signaling pathways such as Wnt/?-catenin. However, many specific roles and key players in these interactions are still unclear; but, understanding these players might lead to drug delivery system that could modulate the T cell repertoire.
Conclusion:
Concentration gradients of signaling molecules and transcriptional factors control the differentiation and functional maturation of T cells into effector or memory CD8 T cells. Though many advances have been made in understanding these mechanisms, there are still many unanswered questions about the physiological characteristics of these cells. By uncovering how T cells are able to diversify from a naïve T cell to its heterogenous population have important implications for future vaccines, drug therapies, and the fight against cancer and autoimmune diseases.

Glycogen Storage Disease Types

Abstract
Glycogen storage diseases (GSD) are inherited metabolic disorders of glycogen metabolism. Different hormones, including insulin, glucagon, and cortisol regulate the relationship of glycolysis, gluconeogenesis and glycogen synthesis. The overall GSD incidence is estimated 1 case per 20 000-43 000 live births. There are over 12 types and they are classified based on the enzyme deficiency and the affected tissue. Disorders of glycogen degradation may affect primarily the liver, the muscle, or both. Type Ia involves the liver, kidney and intestine (and Ib also leukocytes), and the clinical manifestations are hepatomegaly, failure to thrive, hypoglycemia, hyperlactatemia, hyperuricemia and hyperlipidemia. Type IIIa involves both the liver and muscle, and IIIb solely the liver. The liver symptoms generally improve with age. Type II is a prototype of inborn lysosomal storage diseases and involves many organs but primarily the muscle. In this review glycogen storage disease types in which recent advances in diagnosis, pathogenesis or treatment have been highlighted
Introduction
Glycogen storage diseases (GSD) are a part of inherited disorders in the metabolism of glycogen. Postprandial periods show individuals to have a rise in blood glucose and suppression of endogenous glucose production. This exogenous glucose production is metabolized to pyruvate or stored as glycogen in the liver and skeletal muscle. Under aerobic conditions pyruvate is either converted to acetyl coenzyme A (acetyl-CoA), which then is metabolized under the mechanism of the citric acid cycle, producing water, carbon dioxide and ATP, or is used in the synthesis of fatty acids. Anaerobic metabolism of pyruvate results in its conversion into lactate, which is highly significant in periods of hypoglycaemia in acting as an alternative fuel. This process is regulated by various hormones including, insulin, glucagon, and cortisol. Regulation of the relationship between glycolysis, gluconeogenesis and glycogen synthesis is also hormonally controlled. The overall synthesis of glycogen is summarised in Figure. 1. There are currently over 12 types of GSD and they are classified on the basis of the enzyme deficiency and the type of tissue involved. Although the disorder primarily affects the liver and skeletal muscles, interactions between kidney and the CNS resulting in characteristic symptoms of this disease have been recently observed. (Roach PJ 2002)
Glycogen Storage Disease type I
Glycogen storage disease type 1 is believed to be caused by a deficiency in the glucose-6- phospatase-α (G6Pase-α) complex. This is made up of a glucose-6-phosphate transporter (G6PT) which is able to translocate glucose-6-phosphate (G6P) into the lumen of the endoplasmic reticulum from the cytoplasm, and a G6Pase-α catalytic subunit (G6PC) which is responsible for the hydrolysis of endoluminal G6P to glucose and phosphate. It is the combined action of these two subunits which maintain blood glucose homeostasis between meals.
A deficiency of G6Pase-α results in type 1a and a deficiency in G6PT results in the presentation of GSD type 1b. Expression of G6Pase-α predominantly occurs in the liver, kidney and intestine Applegarth DA (2000), while expression of G6PT is unbound and ubiquitous. Detrimental mutations in either protein results in functional efficacy of the other protein to reduce leading to the same metabolic phenotype, characterised by fasting hypoglycaemia, hepatomegaly, nephromegaly, hyperlipidaemia, hyperuricaemia, lacticacidaemia, and growth retardation. The hypoglycaemia seen in GSD type 1 patients is predominantly due to the lack of hepatic and/or renal gluconeogenesis and glycogenolysis. However in vivo kinetic studies have shown that extrahepatic and extrarenal tissue have an involvement in glucose homeostasis. Huidekoper HH et al. (2010) Current diagnostic methods include rapid qualitative enzyme chromatographic test for glucose-6-phosphate dehydrogenase deficiency, this rapid test for G6PD deficiency is a sensitive method for screening of G6PD deficiency requiring minimal training and equipment and enables rapid identification of G6PD-deficient persons. Tests are highly sensitive and give definitive diagnostic results. Tinley KE et al. (2010).
Currently therapy for GSD I patients consists primarily of nutritional support including frequent carbohydrate-rich meals. Janice YC and Brian CM (2007) However recent studies in murine GSD 1a models using adeno -associated virus expressing human G6Pase-α directed by G6Pase-α promoter/enhancer has shown promise as a suitable treatment of GSD1a patients, whereby complete normalization of hepatic glucose homeostasis can be achieved. (GHOSH A et al 2006) Hypoketotic hypoglycaemia and hypertriglyceridaemia are biochemical hallmarks of glycogen storage disease (GSD) 1. Increased malonyl coenzyme A production which compromises oxidation of long-chain fatty acids via carnitine palmitoyltransferase (CPT) 1 inhibition plays a crucial role in the pathogenesis of these complications, as medium chain triglycerides can be metabolised independent of CPT 1 a study carried out using a medium chain triglyceride diet showed a reduction in the amount of carbohydrate and caloric intake required to maintain euglycaemia and led to improvement in growth and metabolic control in two prepubertal patients. DAS AM et al (2010)
Glycogen storage disease type II
GSD II, or Pompe disease, is primarily classified by the age of onset, rate of progression severity, and the organ involvement. Onset is generally apparent in the first month of life with symptoms of hypotonia, systemic muscle weakness, cardiomegaly and hypertrophic cardiomyopathy, feeding difficulties, respiratory distress, hearing loss, and general failure to thrive. Mellies, U et al (2009). The clinical presentation of GSD type 2 is heterogeneous, largely due to the varied residual enzyme activity, associated with mutations in chromosome 17q25.2-q25.3. It occurs due to the absence of the human lysosomal enzyme GAA and the metabolic processes in both normal (a) and Pompe’s (b) is shown in a diagram below.
Profound muscle weakness in Pompe patients has for many years thought to be due to rupture of glycogen lysosomes however a current study has given evidence to an alternative pathogenesis. Failure of productive autophagy in muscle tissue is the predominant factor of weakness, in both patients with Pompe disease and GAA-knockout mouse models. The progressive accumulation of autophagic vesicles occurs in Type II-rich muscle fibre, this build up of autophagosomes disrupt contractile apparatus in muscle fibres, and furthermore this accumulation causes interference in enzyme replacement therapy, as it acts as a sink for recombinant enzyme, preventing efficient delivery to target lysosomes. Shea L and Raben N(2009).
Treatment predominantly involves enzyme replacement therapy, this has shown to significantly prolong survival, decrease cardiomegaly, and improve cardiac and skeletal muscle function. Kishnani PS, et al (2007). Recently a study carried out on the restoration of muscle functionality, was able to achieve complete genetic elimination of glycogen synthesis in GSD II mice, GAA and glycogen synthase 1 knockout mice were inter-crossed to generate a new double-KO model. Muscle atrophy observed in 11-month-old GSDII mice was less pronounced in GAA/GYS1-KO mice, resulting in improved exercise capacity. These double-KO mice exhibited profound reduction in the amount of glycogen present in the heart and skeletal muscles, complete correction of cardiomegaly, and a significant decrease in lysosomal swelling which caused autophagic build up. In addition correction of glucose homeostasis and insulin tolerance was also observed in the double-KO mice. Douillard-Guilloux G, et al. (2010)
Without treatment prognosis is death within the first year of life, and generally is a result of left ventricular outflow obstruction and ventilatory failure. Therefore early detection of this disease can prove to be vital in the treatment of this disease and highlights the reason for screening protocols, a study conducted in 2009 found 6 children out of 206088 which were then treated with alglucosidase alpha at 14 months, all infants had uniformly positive improvements to treatment Chien YH et al. (2009)
Glycogen storage disease type III
GSD III results from deficient glycogen debrancher enzyme activity, which has two independent catalytic activities; oligo-1, 4-1, 4- glucantransferase and amylo-1,6-glucosidase. Both catalytic activities are required for normal full debranching enzyme activity. Deficiency in the enzyme results in an excessive accumulation of abnormal glycogen, which is harmful for hepatocytes. Hepatomegaly, hypoglycemia, short stature, dyslipidemia, and in a few cases, slight mental retardation are seen in both subtypes. Muscle symptoms can start together with liver disorders or long after hepatic disorders or after liver symptoms disappeared in childhood. Currently a definitive diagnosis depends on either mutation analysis or liver and muscle glycogen debranching enzyme activity tests. Ozen H, (2007) A recent study aimed to establish an enzymologic diagnostic method for GSD IIIA by detecting muscular glycogen debranching enzyme activity. The study suggested that enzymologic methods for diagnosis had a power similar to that of gene analysis methods in the diagnosis of GSD-IIIA patients. The sensitivity and specificity of enzymologic diagnostic method and mutation detection were 91.7% and 100% respectively. This suggests that the method is suitable for use in clinic as a first line diagnostic tool. Wang W. (2009)
Treatment for GSD III is primarily dietary and is aimed at maintaining normoglycemia. This is achieved by frequent meals high in carbohydrates and cornstarch supplements alone or with gastric tube feedings. For patients with myopathy, in addition to management of hypoglycemia, a high protein diet is recommended. Demo E et al (2007)

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