A metabolomics approach to understand mechanism of heat stress response in rat

CHAPTER INTRODUCTION 1.1 General Introduction The normal core body temperature of a healthy, resting adult human being is stated to be at 98.6°F or 37.0°C. Though the body temperature measured on an individual can vary, a healthy human body can maintain a fairly consistent body temperature that is around the mark of 37.0°C. In high temperature environments, as the body loses water, its ability to regulate temperature is greatly affected. Prolonged dehydration can lead to heat exhaustion (paleness, dizziness, nausea, vomiting, fainting, and a moderately increased temperature (101-102°F) or even heatstroke (very high temeperature (106°F or higher), and delirium, unconsciousness, or seizures). Heat stroke is a multisystem disorder that can progress to shock, circulatory collapse and death. Heat stress can aggravate the effect of other toxins. Dehydration and loss of minerals through sweat decreases the body's ability to detoxify chemicals. Because the circulatory system is under strain other hazards increase. Carbon monoxide, which reduces oxygen supply to the tissues, is of particular concern. Heat stress is one of the leading cause for concern amongst defense personnel in the tropics since the performance of soldiers on the battlefield is greatly influenced by environmental factors such as ambient temperature. Fatigue, resulting from prolonged heat exposure, causes a decline in coordination, alertness, and performance. Understanding the physiology of heat stress, mechanisms of heat tolerance and methods to alleviate damage due to heat stress, is the main motivation for our studies. All organisms respond to a hyperthermic stress by synthesizing a highly conserved set of proteins known as heat-shock proteins (HSPs). An important feature of HSPs is their role in cryoprotection and repair of cells and tissues against the harmful effects of stress and trauma. Extensive studies have been done on HSPs and their role in heat stress tolerance in diverse species from bacteria to humans. Study of HSP’s as biomarkers of heat stress has been the traditional approach to investigate heat related illnesses so far. A biomarker is a cellular or molecular entity found in increased amounts in blood, urine or tissues that can be used as an indicator of disease, susceptibility to disease or exposure to any externally applied perturbation. Biomarkers are measurements thought to be directly related to clinical outcomes. Depending on the specific characteristic, biomarkers can be used to identify the risk of developing an illness (antecedent biomarkers), aid in identifying disease (diagnostic biomarkers), or predict future disease course, including response to therapy (prognostic biomarkers). Biomarkers are nowadays routinely identified using RNA- (microarray) or protein(proteomics) based platforms. Both these types of markers provide possibilities that the cell may behave in a specified manner, but they are not the endpoints of the cellular biochemical responses. In contrast, metabolites provide several advantages. Firstly, metabolite markers are most closely related to the cell’s final endpoint -- its biochemical phenotype. Secondly, they provide more stable and longer term markers than RNA or proteins. Thirdly, metabolome is extremely sensitive to exogenous stimulation, hence it responds quickly and in a stable manner. Fourthly, metabolome changes reflect the cumulative responses of cells, from signaling and transportation to regulation; hence they show an amplification effect in the response, leading to easier detection of changes. Since these changes also arise from convergence of multiple signals to common metabolic pathways, they make the metabolite markers more robust and representative of broader range of signalling responses. Lastly, having a small mass, instrumentation needs for metabolite detection are more established and less expensive than for protein-based (proteomics) methods. These reasons make metabolite-based approaches highly desirable for monitoring purposes. In spite of these advantages, only specific metabolite markers (those detectable by biochemical assays) of heat stress have been extensively studied. This is mainly due to lack of standardized or commercially available reagents or kits as compared to expression profiling approaches. The general aim of metabolomics is to identify, measure and interpret the complex time-related concentration, activity and flux of endogenous metabolites in cells, tissues, and other biosamples such as blood, urine, and saliva without any bias for the class of molecules. Metabolic responses of cells provide the final steps of cellular adaptation to stresses or other perturbations to the tissues or individuals. Multiparallel techniques, allowing analyses of the levels of low molecular weight compounds, have only just begun to be established during the past decade. This is especially true in mammalian systems. There are a few examples of metabolic profiling applications in medical field such as in drug metabolism in animal systems, but reports investigating effects of heat stress with a metabolomics approach are almost absent. Recent advances have made it possible to carry out an unbiased, simultaneous, and rapid determination of metabolites in various organisms based on metabolic profiling. Thus, metabolic profiling appears to be one of key additional tools in multiparallel system analysis and plays an important role in functional genomics. The focus of my research is to develop a metabolomics platform for understanding heat stress response in a model animal, rat, and identify marker metabolites (intermediates and end-points of metabolic pathways) responsible for this response. This will ultimately help in monitoring performance and recovery of military personnel under heat stress. 1.2 Objectives The overall aim of this project was to understand cellular responses to hyperthermia in multiple organs using a metabolomics approach. The specific objectives of this study were as follows: 1) Establish a metabolomics platform for application in animal model 2) Identify metabolites from plasma and organs using a statistical approach. 3) Identify metabolic pathways affected by heat stress and their regulation. 4) Identify a comprehensive set of biomarkers from biochemical entities, specific to heat stress. In this thesis, the first chapter gives a brief introduction and the major objectives of this research work. Chapter is the literature review section, which provides background information and previous as well as current research carried in the field of heat stress effects and acclimation in mammalian systems and metabolomics. Chapter provides details of the materials and methods that were used during the entire study. Chapter focuses on the extensive optimization studies of metabolomics methods, performed using organ tissue of Rattus norvegicus (model animal, rat). It establishes a metabolomics platform for ideal sample preparation and data processing techniques using a data driven approach. This involved the use of various homogenization buffers, ionization methods and solid phase extraction methods and their combinations. In Chapter 5, a non-targeted approach to identify perturbational effects is focused upon. Metabolic profiling results of the heat stressed animals after different times of recovery, in plasma were reported and differential metabolites were identified. Chapter compares the differential expression of metabolites in various organs at different time-points during heat stress and after times of recovery. This chapter explores the effects of heat stress on a systems level and identifies the target pathways. Statistical methods like t-test, ANOVA, and log base2 ratio and database searches were used for identification of early as well as late responding markers of heat stress and the pathways involved. Lastly, in Chapter 7, a summary of this whole research work and scope for future research potential from the current study are described. CHAPTER REVIEW OF LITERATURE The literature reviewed here has been categorized under three parts. The first part of the review includes heat stress metabolism, the effects of heat stress in animals, heat acclimation, markers of heat stress and other common stressors. The second part of this review deals with metabolomic overview, metabolomics technology platforms, its applications and metabolomic data handling and knowledge extraction. In the third part, metabolic pathways and networks and the applications of pathway analysis have been highlighted. 2.1 Heat Stress Metabolism 2.1.1 Heat stress and homeostasis Homeothermic animals must keep their body temperature within narrow limits for optimal function. While heat is constantly generated in the body due to metabolism and due to external factors like the air, radiant temperature, as well as humidity, the body is equipped with adaptive mechanisms that enable a person to preserve a constant core temperature (Tc). The hypothalamus plays a vital role in controlling body temperature by coordinating thermal information from all body areas and directing the efferent signals to the appropriate heat production and heat conservation systems. Because both thermal and several non-thermal factors will be present at all times, it may not be appropriate to dismiss the contribution of either when discussing the regulation of body temperature in mammals. The sources of heat gain and heat loss to and from the body are, principally: (1) Bodily heat production, or the heat of metabolism, which can vary depending on the amount of physical activity undertaken, (2) convection and (3) radiation, either of which may result in heat gain or heat loss depending on whether the skin temperature is respectively below or above the ambient temperature, and (4) evaporation of sweat from the surface of the skin, which can only result in the loss of heat from the body. Non-thermal factors influencing heat loss and heat production responses are exercise (Kenny et al., 1997, Thoden et al., 1994), blood glucose (Passias et al., 1993), hydration/plasma osmolality (Ekbolm et al., 1970; Turlejska et al., 1986), sleep (Aschoff et al., 1974), motion sickness (Mekjavic et al., 2001; Nobel et al., 2005), fever (Bligh J., 1998), inert gas narcosis (Meklavic et al., 1992; Passias et al., 1992; Washington et al., 1993). Fig. 2.1 is a representation of the pathology of heat stress leading to heat stroke in mammals (Leithead, 1978). 2.1.2 Heat stress in animals All living creatures suffer from excessive heat and the effects of heat stress on various species of bacteria, plants and animals have been extensively studied in the past few decades. Metabolic adaptation of E. coli to a higher temperature via production of heat stress proteins was reported (Weber et al., 2002). Eukaryotes like yeasts have been known to produce heat stress proteins (Chen et al., 2003), though sphingolipids too seem to be relevant for heat stress adaptation (Dickson et al., 1997; Jenkins et al., 1997). Figure 2.1: Schematic representation of the factors leading to heat stress and heat stroke (Redrawn based on Leithead, 1978) Effects of heat stress on plants has been widely investigated in a variety of plant species (Hong et al., 2001; Locato et al., 2009; Meiri et al., 2009), including commercially important species like rice (Wang et al., 2009), lettuce (Oh et al., 2009) and tomato (Qu et al., 2009). Chronic exposure to environmental heat is known to improve tolerance via heat acclimation even in lower animals like Caenorhabditis elegans (Treinin et al., 2003). Cell lines have also been subjected to heat stress and their effects been studied (Zimmerman et al., 1991; Gibbs et al., 2009). Effects of heat stress on mammalian cell cultures (CHOK1, P19 and NIH 3T3) include changes in the cellular architecture, and the synthesis and degradation rates, of specific proteins and during recovery from hyperthermic shock (Roobol et al., 2009). To define better the subcellular mechanism of heat shock induced cardioprotection, the selective expression of individual heat stress proteins (HSPs) has been investigated (Wei et al., 2006). Heat tolerance in higher animals is mediated by activation of the hypothalamopituitary-adrenocortical (HPA) axis (Michel et al., 2007). Some studies have shown that marked accumulation of either dopamine, serotonin or IL-1 in brain occurs in heatstroke-induced cerebral ischemia and neuronal damage in rats. The survival of such animals can be increased by inhibition of IL-1 receptors or monoamine system in brain as well as by induction of heat shock proteins (Lin et al., 1997). 2.1.3 Factors affecting the outcome of heat stress Other than environmental conditions of temperature, humidity, air movement, insulation and clothing that may affect heat tolerance, there are several physiological conditions that make certain individuals more vulnerable to heat stress. These personal factors include, age, sex, obesity, sleep deprivation and diabetes. Ageing has been shown to increase protein nitration, causing a decline in HSP induction (Oberley et al., 2008). Studies have also shown that mitochondria in old rats are more vulnerable to and less able to repair oxidative damage that occurs in response to physiologically relevant heat stress (Zhang et al., 2002). Aging alters stress-induced expression of heme oxygenase-1 in a cell-specific manner, which may contribute to the diminished stress tolerance observed in older organisms (Bloomer et al., 2009). Mitochondria in old animals are more vulnerable to incurring and less able to repair oxidative damage that occurs in response to a physiologically relevant heat stress (Haak et al.,2009). The thermoregulatory capacities of men and women are mostly dependent on the number and activity of sweat glands, sex hormones and the distribution of subcutaneous fat. A variety of chronic pain conditions are more prevalent for females, and psychological stress is implicated in development and maintenance of these conditions (Kawahata, A. 1960). Understanding relationships between gender differences in stress and pain sensitivity and sympathetic activation could shed light on mechanisms for some varieties of chronic stress (Vierck et al., 2008). Diabetes impairs the ability to activate the stress response partly due to, the selective atrophy of certain muscles or muscle fiber types (Najemnikova et al., 2007). It is also known to cause aortic stiffness and this may contribute to the increase in mortality and morbidity associated with diabetes in rats (Ugurlucan et al., 2009). Neural differentiation is associated with a decreased induction of the heat shock response and an increased vulnerability to stress induced pathologies and death (Yang et al., 2008). The activation of the hypothalamus-pituitary-adrenal axis by stress depends mainly on the characteristics of the stressor. Moreover, the response of this axis to stress also depends on the time of day in which the stressor is applied (Retana-Márquez et al., 2003). 2.1.4 Heat stress response and heat acclimation Among the variety of predisposing factors that affect thermal tolerance, only two adaptations are directly invoked to combat heat stress: 1) the rapid heat shock response (HSR); and 2) heat acclimation (Moseley P.L., 1997; Sawka et al., 1985). 10 323.2 323.3 324.3 323.05954 323.098389 323.098389 323.028595 323.028748 323.028595 323.178284 323.178284 323.199249 323.12085 323.178314 323.193604 323.156525 323.193604 323.124847 323.128235 323.178314 323.178314 323.141876 323.124878 323.199249 323.214722 323.199249 323.178284 323.224152 323.222778 Sedoheptulose Methylsuccinic acid Ethylmalonic acid Pseudouridine 5'-phosphate Orotidine Uridine 5'-monophosphate 9-cis-Retinol 11-cis-Retinol Retinoic acid L-Asparagine Androstanedione D-Ornithine Citalopram Ornithine Trigonelline Pantetheine Testosterone Dehydroepiandrosterone Androstenedione Alpha-N-Phenylacetyl-L-glutamine Retinyl ester All-trans-13,14-dihydroretinol Retinoic acid Vitamin A Anabasine Gamma-Linolenic acid 324.387756 Liothyronine Index Purine and Pyrimidine metabolism Androgen and Estrogen metabolism Galactose metabolism Retinol metabolism 6.2.3 Some metabolites changing in organs are secreted in plasma Principal component analysis was performed to compare patterns of ions from different organs/plasma over time (Fig. 6.5). No distinct pattern was observed up to the zero hour mark. However, after the 30 minute time-point, a clear separation of markers 105 was observed. The plasma ions, detected at 40˚C (P1), just after heat stress (P2) and after recovery (P3) were seen clustered together with each other, away from the ions from the organs. In fact, in the later time-points, heart and lung ions were clustered together and away from the liver and kidney ions. In spite of this peculiar grouping, there were a few ions that were common to plasma and organs at a particular timepoint. 106 Figure 6.5: PCA showing behavior of metabolites in organs and plasma over time. Different symbols indicate different animals and different instances of the same symbol and color indicate biological replicates of the same organ/plasma sample. PCA performed in MATLAB software. From the entire set of differentially expressed metabolites across time-points, those which are common between plasma and organs were compared. Ions changing more than fold at p < 0.01 were taken into consideration. Similarities between differentially expressed metabolites were seen only after the 30 minute time point. Lists of possible metabolites at hour, hour and hour time-point were prepared for positive as well as negative ions. At the 1hour time-point, 91 ions in the positive mode (Table 6.3) and 56 ions in the negative mode (Table 6.4) were distinguished. Androgen and estrogen metabolism seemed to be most affected along with fatty acid synthesis, arginine and proline metabolism, glutathione pathway, lysine degradation and nucleotide representatives. metabolism. The arachidonic acid pathway showed few In the negative ions list, the most distinct were the metabolites involved in synthesis of bile acids along with carbohydrate metabolism intermediates. 107 Table 6.3: List of differentially expressed metabolites common between organs and plasma, hour after heat stress. List of ions analyzed in the positive mode during Q1 analysis. m/Z 150.6 150.7 150.7 185.5 211.9 323 323.1 323.2 Theoretical masses 150.537598 150.563141 150.545776 150.574371 150.594574 150.581329 150.648499 150.677734 150.677734 150.648499 185.529785 185.529785 185.519302 185.529785 185.571503 211.973541 211.97197 211.954437 323.061462 323.094879 323.038849 323.182617 323.094879 323.084229 323.073761 323.094879 323.094879 323.022095 323.02478 323.177185 323.094879 323.027466 323.161774 323.161774 323.258057 323.258057 323.156097 323.23468 323.19574 323.182617 Possible Metabolites 7,8-Dihydroneopterin Ascorbic acid D-4'-Phosphopantothenate Allantoic acid Serotonin 2-Isopropylmalic acid Sphingosine ADP dGDP 3-Dehydrosphinganine Adenosine monophosphate 3'-AMP Deoxyadenosine monophosphate 2'-Deoxyguanosine 5'-monophosphate 7-Hydroxy-6-methyl-8-ribityl lumazine Adenine Dihydrogen phosphate Homocysteine Glucosamine 6-phosphate L-Arabinose Xanthosine Homocarnosine L-Ribulose L-Cystine D-Sedoheptulose 7-phosphate D-Xylulose D-Ribose Tartaric acid Xanthine Retinal D-Ribulose Cinnavalininate 2-Methoxyestrone Adrenosterone Epiandrosterone Androsterone Argininosuccinic acid Stearic acid Gamma-Linolenic acid Anserine 108 323.3 323.4 324.2 324.3 324.5 324.6 324.7 383.1 383.2 383.3 323.144897 323.127136 323.101196 323.125397 323.177185 323.102631 323.258057 323.305695 323.418243 323.418243 323.37323 324.237 324.177856 324.214233 324.141724 324.147766 324.118988 324.166138 324.25946 324.289703 324.262146 324.287292 324.498199 324.649902 324.762024 324.776764 383.174927 383.095032 383.115997 383.115997 383.115997 383.115997 383.115997 383.073761 383.115997 383.033905 383.168976 383.073761 383.269287 383.23291 383.279175 383.161926 383.115997 383.166016 383.115997 383.182892 383.216858 383.255829 Aminoadipic acid D-Pantothenoyl-L-cysteine Pantetheine Hydrocinnamic acid 9-cis-Retinal 4,6-Dihydroxyquinoline Dihydrotestosterone Palmitaldehyde cis,cis-3,6-Dodecadienoyl-CoA trans,cis-Lauro-2,6-dienoyl-CoA 4-Hydroxyphenylacetyl-CoA N-Acetylputrescine Tetrahydrobiopterin L-Histidinol 3-Oxohexanoic acid Aerobactin 3-Hydroxyanthranilic acid S-(3-Methylbutanoyl)-dihydrolipoamide-E Agmatine Oleic acid 4-Trimethylammoniobutanal Sphinganine Phosphatidylinositol-3,4,5-trisphosphate Leukotriene C4 Lauroyl-CoA Retinyl palmitate 8,11,14-Eicosatrienoic acid Melibiitol D-Mannose D-Galactose D-Fructose D-Glucose Beta-D-Glucose 3,4-Dihydroxy-trans-cinnamate L-Sorbose AICAR 5-Hydroxykynurenamine Rosmarinic acid 9-cis-Retinoic acid 19-Oxoandrost-4-ene-3,17-dione Tetrahydrocorticosterone 11-Dehydrocorticosterone D-Tagatose Lactosamine Alpha-D-Glucose Cortisone 5,6-DHET Capric acid 109 383.4 383.8 383.330841 383.889587 7-Dehydrodesmosterol Iodotyrosine Index Androgen and Estrogen metabolism Steroid metabolism Fatty Acid metabolism Galactose metabolism Purine metabolism Sugar metabolism Arginine and Proline metabolism Lysine degradation Histidine metabolism Glutathione metabolism Table 6.4: List of differentially expressed metabolites common between organs and plasma, hour after heat stress. List of ions analyzed in the negative mode during Q1 analysis. m/Z Theoretical masses Possible Metabolites 323 323.097809 323.052094 323.098389 323.025604 323.097809 323.097809 323.097809 323.052094 323.124847 323.128235 323.098389 323.098389 323.028595 323.028595 323.199249 323.178284 323.105499 323.162872 323.162872 323.193604 323.193604 323.12085 323.124878 Alpha-Lactose 6-Hydroxynicotinic acid (S)-2-Acetolactate Oxalacetic acid Epimelibiose Galactinol Melibiose 4-Nitrophenol Trigonelline Pantetheine Methylsuccinic acid Ethylmalonic acid Pseudouridine 5'-phosphate Uridine 5'-monophosphate Retinyl ester Vitamin A 2-Hydroxyestrone 2-Methoxyestradiol 19-Hydroxyandrost-4-ene-3,17-dione D-Ornithine Ornithine Ureidopropionic acid Alpha-N-Phenylacetyl-L-glutamine 323.1 323.2 110 324.4 383.1 383.2 383.3 383.4 323.178284 323.178284 323.199249 324.12616 324.387756 383.046722 383.163025 383.046722 383.046722 383.060944 383.007172 383.163025 383.18399 383.18399 383.168457 383.114319 383.18399 383.168457 383.145966 383.145966 383.243896 383.33139 383.33139 383.33139 383.33197 383.33197 383.33197 11-cis-Retinol 9-cis-Retinol Retinoic acid Thiamine Liothyronine 2,3-Diketo-L-gulonate Corticosterone Citric acid Isocitric acid AICAR Cysteic acid 21-Deoxycortisol 18-Hydroxycorticosterone Aldosterone 1-Methylhistidine S-Adenosylhomocysteine Cortisol Dihydrothymine Norepinephrine Pyridoxine 5,6-DHET 24-Hydroxycholesterol 25-Hydroxycholesterol 27-Hydroxycholesterol Cholestenone 7-Dehydrocholesterol Vitamin D3 383.33197 Desmosterol Index Androgen and Estrogen metabolism Steroid metabolism Galactose metabolism Purine and Pyrimidine metabolism Carbohydrate metabolism Retinol metabolism At the hour time-point, a substantial increase in arachidonic acid intermediates was observed in the positive mode. About 250 differentially expressed ions are listed in Table 111 6.5 (Appendix III), out of which metabolites from steroid hormone metabolism, tryptophan, tyrosine, glutathione, fatty acids, ascorbate and arginine metabolism deserve a special mention. 110 metabolites were identified in the negative mode (Table 6.6, Appendix III). Several metabolites from the Vitamin B6 metabolism showed an increase in expression along with those from nucleotide metabolism and synthesis of bile acids. At the hour time-point, 192 ions in the positive mode and 90 ions in the negative mode showed differential expression. Table 6.7 (Appendix III) lists the positive ions in which the arachidonic acid pathway metabolites still showed substantial up-regulation along with androgen, glutathione, ascorbate and nucleotide metabolism. Several amino acid metabolic pathways, like those of arginine, glycine, serine, threonine, histidine and tyrosine were likely to be active. The negative ions list (Table 6.8, Appendix III), showed presence of androgen and estrogen metabolites, citric acid cycle intermediates, steroids hormone metabolites, glutathione metabolism intermediates, vitamin B6 intermediates and components of bile salts. 6.2.4 System attempts to return to basal level after heat stress is removed Once heat stress is removed, the core temperature of the rats tends to come to normal levels (34°C) (Fig. 6.6). But after hours and hours, core temperature went as low as 31°C and 28°C respectively. 112 Heat Stress Zero hours 44 Temp (Deg C) 42 Rat 40 Rat 38 Rat 36 Rat 34 Rat 32 30 00 15 30 45 60 75 90 105 120 135 150 165 180 195 210 225 240 Time (min) Heat Stress 30 44 Temp (Deg C) 42 Rat 40 Rat 38 Rat 36 Rat 34 Rat 32 30 00 15 30 45 60 75 90 105 120 135 150 165 180 195 210 225 240 255 270 Time (min) Heat Stress One hour 44 Temp (Deg C) 42 Rat 40 Rat 38 Rat 36 Rat 34 Rat 32 30 00 15 30 45 60 75 90 105 120 135 150 165 180 195 210 225 240 255 270 285 300 Time (min) 113 Heat Stress Two hours 44 Temp (Deg C) 42 Rat 40 Rat 38 Rat 36 Rat 34 Rat 32 30 00 15 30 45 60 75 90 105 120 135 150 165 180 195 210 225 240 255 270 285 300 315 330 345 360 Time (min) 44 42 40 38 36 34 32 30 28 26 24 Rat Rat Rat Rat 45 42 39 36 33 30 27 24 21 18 15 12 90 60 Rat 30 00 Temp (Deg C) Heat Stress Four hours Time (min) Figure 6.6: Variation in core temperature (Tc °C) of all experimental animals at all time-points. It was then decided to assess the status of the whole body (plasma and organs) with respect to the differential metabolites. Fig. 6.7 shows a heat map indicating the number of differentially expressed metabolites across all tissues, over the period of heat stress and recovery. It was observed that changes in metabolic profiles start appearing only 30 minutes after heat stress, reach maximum values at the hour time-point and start turning to basal levels by the time the hour mark is reached. 114 Figure 6.7: A system wide response to heat stress. All differentially expressed ions at all time-points, in all organs and plasma samples are shown. The panel on the bottom right side shows number of ions. 6.3 DISCUSSION 6.3.1 Altered metabolic profiles of heat stressed animals It was observed that lung was the earliest to respond to heat stress in terms of differentially expressed metabolites. This is due to the immediate increase in blood pressure, heart rate and panting seen in the animal early during heat stress. Kidney on the other hand showed the most vigorous response. This suggests a high rate of catabolism and therefore increased need for excretion of those breakdown products in the early stages after heat stress. Studying groups of metabolites as opposed to individual metabolites can be useful once the identities of those metabolites is known. This can be 115 useful to understand why certain metabolites show a certain pattern of expression at specific time-points. Unsupervised clustering methods like PCA were not very conclusive in identifying groups of metabolites with distinguishing characteristics in any of the four organs. 6.3.2 Some metabolites respond in all organs at the same time One of the groups of metabolites studied was a bunch of 59 metabolites, that were expressed in all organs, at practically the same levels, throughout all time-points of recovery. After a database search, the possible metabolites were found to belong to the androgen-estrogen pathway, the ascorbate pathway, fatty acid metabolism, nicotinamide pathway and metabolism of amino acids like tyrosine, arginine, histidine, phenylalanine and tryptophan. This suggests that these pathways remain active throughout the heat stress and recovery phase and may play a vital role in the achievement and maintainence of homeostasis after heat stress. Members of the above mentioned pathways are involved mostly in pathways leading to signaling molecules like hormones, secondary messengers and neurotransmitters. These results are indicative of a highly active communication system between organs. 6.3.3 Signaling pathways and anti-oxidants are active in organs and plasma Amongst the possible metabolites that show a steady increase in expression from 1hour to hours is the arachidonic acid pathway. Responsible for producing inflammatory response, its steady up-regulation implies that inflammatory response is still very active even hours after heat stress. Pathways involved in steroid hormone synthesis and phsphatidyl inositol are also highly active indicating increased metabolism of signal molecules. Metabolites involved in anti-oxidation like ascorbate and glutathione are 116 present at all time-points in organs and plasma, indicating continuous functioning antioxidation mechanisms and the body’s need for repairing damaged tissue. The presence of bile acids in both plasma and organs is indicative of the ongoing catabolism, conjugation and excretion of the various breakdown products of different pathways. 6.3.4 Coordinated system-wide response to heat stress After the removal of heat stress, the core temperature of the animals immediately starts to decrease and goes up to pre-stress levels (Fig. 6.6). However, if longer periods of recovery are allowed, like hours or hours, then the core temperature goes even lower than 34°C. This is most likely due to the influence of prolonged exposure to anesthesia. In the overall assessment of the animal’s response to heat stress, it was seen that the whole system, represented by the four organs and plasma responded in a coordinated fashion as a single unit (Fig. 6.7). This opens up a new area of research; the elucidation of the coordinated, time-dependant, pathway/network analysis of heat stress response. 6.4 CONCLUSIONS Heat stress elicits a coordinated, system-wide response in rat. Coordinated changes in distant pathways could be due to many reasons. Firstly, some metabolites could provide a link between pathways through common reactions. Secondly, there could be common regulators that control multiple pathways. Changes in the expression of such transcription factors can cause simultaneous changes in one or more pathways. Thirdly, stress signals such as infection, wounding and dehydration cause a holistic response from the system that involves a network of transcriptional regulators affecting more than one pathway at 117 the same time. Fourthly, endogenous signals that co-ordinate multiple pathways might exist within the system. To monitor, or study such a complex machinery, it is vital to employ pattern-recognition tools to extract meaningful data from the mass spectrometer. However, the bioinformatics tools can only predict the response pathways and mechanisms. Biological validation is critical, if one has to derive any reliable information form the data. The next step will be to confirm and quantitate the metabolites predicted by the software. 118 CHAPTER CONCLUSIONS AND FUTURE DIRECTIONS 7.1 CONCLUSIONS AND INFERENCES In this chapter the main conclusions derived from this study are presented, as well as the suggestions for future research which should contribute to elucidation of some of the issues which were not covered here. The major conclusions from this research are summarized as follows. The starting point in metabolomics is the experimental design. This is often neglected, but the high dimensionality of omics data means that it needs special attention. Extensive optimization studies were conducted and a metabolomics platform for the analysis of mammalian tissue was established. (Parab et al., 2009). This metabolomics platform was then applied to study the response of model animal, rat (Rattus norvergicus) to heat stress. It is the first such study on the heat stress response of rat using a metabolomics platform. Many metabolites, in the range of hundreds, were observed to have decreased or increased their expression in response to heat stress. Patterns of response of metabolites in plasma, in organs and at various time-points were studied and comprehensive lists of differentially expressed metabolites were prepared. This study revealed several novel aspects of interrelationships in the metabolic 119 pathways involved in heat stress. 7.2 FUTURE DIRECTIONS Based on the current studies, metabolomics of heat stress response in Rattus norvegicus has opened up a vast area for future investigations. Following, are a few suggestions : MS/MS (fragmentation) experiments of selected ions and confirming their identities after comparison with standards. Multiple reaction monitoring (MRM) studies can be performed on selected metabolites to quantitate them. The wealth of information on pathways responding to heat stress could lead to the study of the regulatory mechanisms underlying these pathways. Gene expression data, combined with metabolomics data and proteomics data can give a holistic systems level understanding of heat stress in rat. Robust biomarkers of heat stress can be discovered in animal models using pattern-recognition tools and validated. Interesting pathways like the glutathione-ascorbate antioxidant pathway, steroid metabolism and arachidonic acid pathways must be investigated with respect to their role in heat stress. This study highlights the possibility of developing a platform technology that could simulate the metabolic fluxes and aid in the development of mathematical models of pathways. This can further lead to extraploation and prediction of animal behavior/response mechanisms. 120 [...]... human heat acclimation Better understanding of heat stress mechanism and metabolism in rat can eventually help in better management of heat related disorders Studies have already shown that pretreatment with anti-inflammatory dose of aspirin can provide protection against heat stroke in rats, which may be associated with the inhibition of elevation of plasma IL-1beta levels by aspirin (Song et al.,... Data handling and knowledge extraction As with all functional analyses, a typical metabolomics experiment can generate mountains of data (samples times variables times metabolites) and critical steps must 22 be taken to turn these data (information) into knowledge In particular, we need wellcurated databases, very good data to populate them, and even better algorithms to turn these metabolite data into... very popular linear regression-based method (Martens et al., 1989) The algorithm can be programmed in a quantitative way (PLS1) or categorical (PLS2 or PLS-DA), and as for DA, loadings matrices can give an indication of important metabolites Artificial neural networks (ANN) are very popular based machine learning methods, which in contrast to DA and PLS can learn non-linear as well as linear mappings (Bishop... sodium, potassium, calcium, inorganic phosphorus, triiodothyronine (T3) and thyroxine (T4) and the activities of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), creatine kinase (CK) and lactate dehydrogenase (LD) in heat stressed camels (Gheisari et al., 1999), quails (Yenisey et al., 2004), rats (Lee et al., 2008) 12 Presently, more than 100 genes (including... significantly increases the esophageal temperature triggering thermoregulatory sweating, but that the sensitivity and maximum sweating rate are maintained at normal levels relatively well (Washington et al., 1993) Ischemia followed by reperfusion presents a stress in mammalian tissue, that is very similar to heat stress in its metabolic outcome and like in heat stressed animals, the ischemia-reperfusion tolerance... understanding the function and interactions of all of the involved elements, proteins and others 2.1.6 Heat stress management Simultaneous measurement of heart rate, blood pressure and temperature, has not previously been reported in unrestrained heat- acclimated rats Measurement of these variables without the confounding effects of restraint or handling has increased the validity of the rat as a model... laboratories and datasets from different laboratories can be shared, leading to construction of standard databases However, the limitations as to the size and types of metabolites that can be analyzed and the extensive preparation and derivatization required is a big concern Liquid chromatography mass spectrometry (LC/MS) is ideal for metabolite profiling as biofluids such as urine can be directly injected... generation of spectral profiles of a wide range of low molecular weights (MW) metabolites that reflect the metabolic status of an organism 24 Nowadays a variety of metabolomics technologies are employed to several applications for studying mammalian systems By far the most extensive application of metabolomics is in the medical/clinical field ‘Clinical metabolomics aims at evaluating and predicting... 2004) Also, dietary supplementation of chromium as chromium nanoparticles significantly decreased serum concentrations of insulin and cortisol, increased sera levels of insulin-like growth factor I and immunoglobulin G, and enhanced the lymphoproliferative response and phagocytic activity of peritoneal macrophages in heat- stressed rats (Zha et al., 2008) In a similar study, it was suggested that hyperHAES... can be categorical (diseased vs healthy) or quantitative (severity of disease) Discriminant analysis (DA) is a particularly popular algorithm, which is a cluster analysis-based method and involves projection of test data into cluster space (Manly B.F.J., 1994) This is a categorical method and loadings matrices can give an indication of important inputs (metabolites) Partial least squares (PLS) is a . effects of restraint or handling has increased the validity of the rat as a model for human heat acclimation. Better understanding of heat stress mechanism and metabolism in rat can eventually. prolonged heat exposure, causes a decline in coordination, alertness, and performance. Understanding the physiology of heat stress, mechanisms of heat tolerance and methods to alleviate damage due to. indicates that isoflurane anesthesia significantly increases the esophageal temperature triggering thermoregulatory sweating, but that the sensitivity and maximum sweating rate are maintained at