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Original Article
56 (
1
); 1-10

Hypoxic Signature of High Altitude Acclimatization: A Gene Expression Study

Scientist ‘F’, Defence Institute of Physiology and Allied Sciences, Defence Research and Development Organization, Lucknow Road, Delhi 110054

Abstract

Indian Air Force and Army Aviation Corps routinely undertake flight to high altitude region which presents an environment of hypoxia and cold. On arrival at altitude, a number of physiological changes occur which ultimately enables the body to function optimally in low oxygen environment through process of acclimatization. An integral part of the human cellular response to hypoxia is changes in gene expression. Profiles of gene expression patterns define the complex biological processes associated with both health and disease in vivo. Microarrays can identify changes in gene expression that can be used as biomarkers of environmental and/or any other stress related exposure and can provide information on mechanisms of various biological processes. In the present investigation, gene expression c2hanges were analysed in sea level residents who were air inducted to high altitude to identify gene transcripts of altitude exposure and thereby understand the mechanism of acclimatization. Gene expression profiling was done by Atlas Powerscript labelling system, California, on Atlas Glass Microarrays. About 89 gene transcripts showed a change in gene expression after acute induction to altitude and the transcripts were protein coding type. Seventy three gene transcripts had a decreased expression and about fifteen transcripts were upregulated under the high altitude hypoxic stress. The pathways found to be affected were antigen processing and presentation (hsa04612), h_ctlPathway: CTL mediated immune response against target cells, GnRH signaling pathway (hsa04912), vascular smooth muscle contraction (hsa04270), ubiquitin mediated proteolysis (hsa04120), regulation of actin cytoskeleton (hsa04810), calcium signaling pathway (hsa04020), neuroactive ligand-receptor interaction (hsa04080) and cytokine-cytokine receptor interaction (hsa04060). Findings of the study indicate high altitude hypoxia has more down regulatory effect on transcript expression in peripheral blood cells and the hypoxic signature of high altitude exposure is evidenced.

Keywords

high altitude hypoxia
acclimatization
gene expression

Introduction

High altitude region presents an environment of hypoxia and cold. Indian Air Force and Army Aviation Corps routinely undertake flight to high altitude and engage in different operations wherein exposure to the harsh environment is inescapable. On arrival at altitude, a number of physiological changes occur through process of acclimatization which ultimately enables the body to function optimally in low oxygen environment. These physiological responses are complex and involve a range of mechanisms occurring within minutes of oxygen sensing resetting a cascade of biosynthetic and physiological events within the cellular milieu [1].

During the initial phase of ascent to HA, most sojourners experience symptoms of acute mountain sickness (AMS) characterized by headache, nausea, vomiting, giddiness, anorexia leading to hypophagia, sleep disturbance and adverse psychological effects (secondary), muscular weakness and depression [2].

High altitude pulmonary edema (HAPE) is a severe form of altitude sickness that generally occurs within 6 to 48 hours of ascent beyond a height of 2500 to 4000 m. Genetic predisposition and individual susceptibility in cases of HAPE has been postulated [3]. Mechanism of high altitude acclimatization and/or maladaptation still remains unclear. Gene expression responses of circulating leukocytes can potentially provide an early warning of threat they discover and have the potential to be used diagnostically for direct sampling of sites of infection or other disease processes. The present investigation aimed at studying the gene expression profile in individuals who were inducted to high altitude to identify changes related to high altitude exposure and understand the mechanism of acclimatization.

Material and Methods

24 male low landers (weight-63.7±6 kg, age-27.7±6 years) were included in the study who were studied at sea level (Chandigarh at 0700h before breakfast) and thereafter at high altitude (Leh, Jammu and Kashmir, AMSL 3650 m). Samples were also collected from HAPE patients (n=6) admitted in the hospital at Leh and age matched control subjects who did not develop HAPE (n=4). Verbal information on the experimental protocol and procedures were given to the subjects after which the subjects gave their informed, written consent to participate. The study conformed to Institute Ethical guidelines. Lake Luoise score was determined for each subject for assessment of AMS and seven volunteers who developed AMS were excluded. Samples were treated anonymously throughout the analysis. Blood samples were directly collected through a scalp vein set (Beckton Dickinson) in PAXgene Blood RNA tubes containing a stabilizing fluid (PreAnalytix, Qiagen).

RNA isolation, preparation of labeled cDNA and microarray hybridization

Total cellular RNA was isolated using PAXgene Blood RNA kit (PreAnalytix, Qiagen) along with on-column DNase digestion as per manufacturer’s recommendation. Samples were quantified by absorbance measurement at 260 nm and integrity was analysed by native gel electrophoresis. Total RNA (~5-7 pg) was used as templates in reverse transcription reactions for first strand complimentary DNA synthesis in presence of oligo (dT)15-18 primer and 2-aminoallyl-dUTP (Atlas Powerscript labelly system; BD Biosciences Clontech, Palo Alto,California) following which they were labeled by N-hydroxysuccinimide-derivatized Cy3 (Amersham Pharmaci Ltd., Piscataway, N.J.) (Samples of sea level) and N-hydroxysuccinimide- derivatized Cy5 dyes (same samples at high altitude) respectively following the protocol of manufacturer (BD Biosciences Clontech). Samples of HAPE and controls were labeled with Cy3 and Universal Refererence RNA (URR, Statagene) was labeled with Cy5). 650 pg of synthetic lambda Q gene RNA containing an engineered poly(A) tail was spiked into each cDNA synthesis reaction mixture (Atlas Powerscript labeling system; BD Biosciences Clontech, Palo Alto, California) to provide a control for cDNA synthesis, labeling efficiency and cDNA microarray hybridization. Labeled cDNAs were purified through FluorTrap matrix (Atlas Powerscript labeling system; BD Biosciences Clontech, Palo Alto, California) and eluted through 0.22mm spin filters. Microarray hybridization was performed on BD Atlas Glass Microarrays (Human 3.8 I K, Clontech catalogue no. 634638). Hybridization was conducted for 18 hours at 50°C. Following hybridization, cDNA microarrays were washed as per the manufacturer’s protocol and air dried by centrifugation in a cushioned 50-mi conical centrifuge tube at 3000 x g for 1 minute.

Image processing and Data Analysis

Hybridization signals were collected by Axon microarray scanner (GenePix Pro 3.0) and raw spot intensity report was created by Gene Pix analyzer software. Average pixel intensity within each circle was determined and local background was computed for each spot. Net signal was determined by subtracting local background from the average intensity. Genespring GX V 7.3 software (Agilent Technologies) was used for data analysis. ALowess curve was fit to the log-intensity versus log-ratio plot. 10% of the data was used to adjust the control value for each measurement. Gene Annotation sources included Unigene, Entrez Gene, Genbank, and KEGG Database. Hierarchical clustering was done using Cluster 3.0 program and visualized using Java Tree View. Genes that showed a minimum of 0.7 fold change (to capture even the weak signals on the array) was considered as differentially regulated. Functional Annotation clustering was done by Database for Annotation, Visualization and Integrated Discovery (DAVID v 6.7 available at http://david.abcc.ncifcrf.gov) [4, 5].

Results

Of the 3800 sequences in the gene array, about 297 transcripts showed expression on the 3.8 K array (expressed in at least one condition), 64 transcripts expressed in all three conditions, 49 transcripts expressed in at least 2 conditions and 184 transcripts expressed in only condition. About 89 transcripts showed a change in gene expression after acute induction to altitude and were protein coding type. The differentially regulated genes belonged to both biological functions and cellular component. Seventy three gene transcripts had a decreased expression and about fifteen transcripts were upregulated under the high altitude hypoxic stress (Table 1). Genes of G-protein coupled receptor protein signaling pathway were down regulated on altitude induction: these included guanine nucleotide binding protein (GNA11) and regulator of G-protein signaling 11 (RS11).

Table 1:: List of differentially expressed gene transcripts during high altitude acclimatization
Gene symbol Ref Seq Accession no Gene Fold change Gene symbol Ref Seq < Accession no Gene Fold
HBA1 NM_000558 hemoglobin, alpha 1 2.411 LALBA NM_002289 lactalbumin, alpha- 0.695
AQP5 NM_001651 aquaporin 5 2.24 HLA-C NM_002117 major histocompatibility complex, class I, C 0.695
ARL4A NM_001037164 ADP-ribosylation factor-like 4A 1.744 AURKC NM_001015878 aurora kinase C 0.695
RPL3L NMJD05061 ribosomal protein L3-like 1.667 ARCN1 NMJI01655 archain 1 0.694
STX1A NMJD04603 syntaxin 1A (brain) 1.609 PSMC5 NM_002805 proteasome (prosome, macropain) 0.694
PITX1 NM_002653 paired-like homeodomain 26S subunit, ATPase, 5
transcription factor 1 1.604 SSNA1 NM_003731 Sjogren’s syndrome nuclear autoantigen 1 0.693
ST8SIA1 NM_003034 ST8 alpha-N-acetyl-neuraminide 1.59 PLAGL2 NMJ102657 pleiomorphic adenoma gene-like 2 0.692
alpha-2, 8-sialyltransferase 1 CNGA1 NMJ100087 cyclic nucleotide gated channel alpha 1 0.692
HBA1 NM_000517 hemoglobin, alpha 2 1.519 RGS11 NM_003834 regulator of G-protein signalling 11 0.69
PTMS NM_002824 parathymosin 1.504 PABPC4 NM_003819 poly(A) binding protein, cytoplasmic 4 0.688
ClOorfl 16 NM_006829 chromosome 10 open reading frame 116 1.501 (inducible form)
SEPT5 NM_001009939 septin 5 1.499 APRT NML000485 adenine phosphoribosyltransferase 0.688
COX6A2 NM_005205 cytochrome c oxidase subunit 1.431 DYRK2 NML003583 dual-specificity tyrosine-(Y) 0.687
Via polypeptide 2 -phosphorylation regulated kinase 2
ARSE NM_000047 arylsulfatase E (chondrodysplasia 1.423 CASK NM_003688 calcium/calmodulin-dependent serine 0.687
punctata 1) protein kinase (MAGUK family)
PTPRS NM_002850 protein tyrosine phosphatase, 1.409 CALM2 NM_001743 calmodulin 2 (phosphorylase kinase, delta) 0.682
receptor type, S DYRK3 NM_001004023 dual-specificity tyrosine-(Y)- 0.681
ARPC4 NM_001024959 actin related protein 2/3 complex, 1.407 phosphorylation regulated kinase 3
subunit 4, 20kDa SSR1 NM_003144 signal sequence receptor, alpha (translocon- 0.68
PLA2G4C NM_003706 phospholipase A2, group IVC 0.7 associated protein alpha)
(cytosolic, calcium-independent) ' UBE2D3 NM_003340 ubiquitin-conjugating enzyme E2D 3 0.677
TNFSF12 NM_003809 tumor necrosis factor (ligand) 0.699 (UBC4/5 homolog, yeast)
superfamily, member 12 TMEFF1 NM 003692 transmembrane protein with EGF-like and 0.677
GNA11 NM_002067 guanine nucleotide binding protein 0.699 two follistatin-like domains 1
(G protein), alpha 11 (Gq class) IFNA14 NM 002172 interferon, alpha 14 0.676
KRT31 NM 002277 keratin, hair, acidic, 1 0.699
DOC2A NM 003586 double C2-like domains, alpha 0.673
RFXANK NM_003721 regulatory factor X-associated ankyrin- 0.698 ATXN2L NM 007245 ataxin 2-like 0.672
containing protein
GPA33 NM_005814 glycoprotein A33 (transmembrane) 0.697 ZNF124 NM__003431 zinc finger protein 124 (HZF-16) 0.672
TNFRSF6B NM_003823 tumor necrosis factor receptor superfamily, 0.67 member 6b, decoy RDH16 NM_003708 retinol dehydrogenase 16 (all-trans and 13-cis) 0.625
SCARF1 NM_003693 scavenger receptor class F, member 1 0.666 DYRK1A NM_001396 dual-specificity tyrosine-(Y)-
SLC25A12 NM_003705 solute carrier family 25 0.665 phosphorylation regulated kinase 1A 0.622
(mitochondrial carrier, Aralar), member 12 GP5 NM_004488 glycoprotein V (platelet) 0.621
RNMT NM_003799 RNA (guanine-7-) methyltransferase 0.663 BCL7B NM_001707 B-cell CLL/lymphoma 7B 0.62
STC1 NM_003155 stanniocalcin 1 0.662 APCL NM 005883 adenomatosis polyposis coli 2 0.62
HIST2H2BE NM_003528 histone 2, H2be 0.662 FBLN2 NM 001004019 fibulin 2 0.613
CUL3 NM_003590 cullin 3 0.66 MRPL49 NM 004927 mitochondrial ribosomal protein L49 0.609
BTG1 NM_001731 B-cell translocation gene 1, anti-proliferative 0.66 TPST1 NM_003596 tyrosylprotein sulfotransferase 1 0.607
MZF1 NM_003422 zinc finger protein 42 (myeloid-specific retinoic acid-responsive) 0.658 FABP5 NM 001444 fatty acid binding protein 5 (psoriasis-associated) 0.607
MADD NM_003682 MAP-kinase activating death domain 0.657 PRKRA NM 003690 protein kinase, interferon-inducible double stranded RNA dependent activator 0.605
SRPK2 synonym: SFRSK2; isoform b is encoded bv transcript variant 2; H RG152G17. la; WUGSC:H_RG152G17.1a; serine kinase SRPK2; H_RG152G17.1b; go_component: nucleus [goid 0005634] [evidence IDA] [pmid 9472028]; go component: cytoplasm [goid 0005737] [evidence IDA 0.651 APOH NM_000042 apolipoprotein H (beta-2-glycoprotein I) 0.595
FOXN1 NM_003593 forkhead box N1 0.594
AQP2 NM_000486 aquaporin 2 (collecting duct) 0.583
BAG6 NM 004639 HLA-B associated transcript 3 0.577
AGTR2 NM_000686 angiotensin II receptor, type 2 0.573
PPAP2B NM_003713 phosphatidic acid phosphatase type 2B 0.569
RARA NM_000964 retinoic acid receptor, alpha 0.65 PRKX NM_005044 protein kinase, X-linked 0.566
CUL2 NM_003591 cullin 2 0.646 FKBP1A NM-000801 FK506 binding protein 1A, 12kDa 0.56
HSD17B10 NM 003725 hydroxysteroid (17-beta) 0.646 DHX16 NM-003587 DEAH (Asp-Glu-Ala-His) 0.547
dehydrogenase 6 box polypeptide 16
RUVBL1 NM_003707 RuvB-like 1 (E. coli) 0.645 UBE2L3 NM„003347 ubiquitin-conjugating enzyme E2L 3 0.542
OFD1 NM_003611 oral-facial-digital syndrome 1 0.642 RNASE4 NM_002937 ribonuclease, RNase A family, 4 0.54
TRP1 NM_002769 protease, serine, 1 (trypsin 1) 0.641 PPAP2A NM_003711 phosphatidic acid phosphatase type 2A 0.539
SCGB2A2 NM 002411 secretoglobin, family 2A, member 2 0.641 OR6A2 NM-003696 olfactory receptor, family 6, 0.538
CALCA NM 001033952 calcitonin/calcitonin-related 0.641 subfamily A, member 2
polypeptide, alpha GNRHR NM_000406 gonadotropin-releasing hormone receptor 0.537
SYN2 NM_003178 synapsin II 0.631 STK16 NM_001008910 serine/threonine kinase 16 0.514

Calcitonin/calcitonin-related polypeptide (CGRP), angiotensin II receptor type 2 (ATGR2), olfactory receptor family 6 (OR6A2P) and gonadotropin releasing hormone receptor (GRHR) were also downregulated. Among the other downregulated genes were present genes for cyclic nucleotide gated channel (CNG1) and mitochondrial solute carrier family 25 (ARALAR1). Genes involved in RNA processing, regulation of transcription, RNA processing/catabolism (PLAGL2), (APP1), zinc finger proteins (ZNF124, MZF1), retinoic acid receptor (FAR), genes involved in mRNA cleavage (RNS4), RNA splicing gene [DEAH (Asp-Glu- Ala_His) box polypeptide 16] (DBP2), mRNA capping RNA (guanine-7-methyltransferase) were also downregulated. Also downregulated was dualspecificity tyrosine (Y) phosphorylated kinases (DYRK5, DYRK2). Genes involved in defence response like interferon alpha 14 (MGC125756), apolipoproein H (APOB) andforkhead box N1 (FKHL20) were downregulated on exposure to high altitude. Transcripts involved in cell adhesion like calcium/calmodulin dependent serine protein kinase (LIN2) and scavenger receptor class F (SREC) were downregulated. Antigen presenting major histocompatibility complex class 1 (HLA-JY3 or D6S204), blood coagulation factor glycoprotein V (CD42d) and neurotransmitter synapsin II (SYNII) were also downregulatedon high altitude induction.

Upregulated transcripts on altitude induction were for various binding molecules viz., heme binding (hemoglobin alpha 1), hemoglobin alpha 2 (HBA1), GTP binding (ADP-ribosylation factor like 4A, ARIA), GTP binding septin 5 (H5), RNA binding ribosomal protein L3 type (RPL3L), protein binding (syntaxinlA, STX1A), parathymosin (PTMS) which is known to be involved in cellular defense response, transporter activity related to excretion (aquaporin 5, AQP5), gene involved in carbohydrate metabolism (ST8 alpha-n-acetyl-neuraminide alpha 2,8 sialytransferase, GD3S), cytochrome c oxidase subunit Via polypeptide involved in electron transport (COX6AH), cell adhesion molecule protein tyrosine phosphatase receptor (PTPSIGMA), actin related protein 2/3 complex involved in actin related polymerization (ARC20) as well as chromosome 10 open reading frame 116 of unknown biological function. The prominent functional clusters were regulation of apoptosis, T cell activation, oxygen transport, neurotransmitter secretion, regulation of blood pressure, regulation of body fluid levels, cell-cell signaling, transcripts of calcium ion binding etc (Table 2). The pathways which were found to be affected were antigen processing and presentation (hsa04612), h_ctlPathway: CTL mediated immune response against target cells, GnRH signaling pathway (hsa04912), vascular smooth muscle contraction (hsa04270), ubiquitin mediated proteolysis (hsa04120), regulation of actin cytoskeleton (hsa04810), calcium signaling pathway (hsa04020), neuroactive ligand-receptor interaction (hsa04080) and cytokine-cytokine receptor interaction (hsa04060) (Table 3).

Table 2:: Functional clusters obtained from the differentially expressed gene transcripts during high altitude acclimatization
Term Count % P Value Genes Fold Enrichment
G0:0043067~regulation of programmed cell death 24 15.4 1.06E-05 TRAF1, LALBA, TNFRSF6B, CEBPB, CD3G, MADD, CD3E, ACTN1, SOX4, TNFSF14, TNFSF12, CUL3, CUL2, PEA15, AGTR2, SSTR3, PSMC5, DYNLL1, BTG1, PRKRA, APOH, TPT1, DYRK2, PLAGL2 2.81
G0:0042110-T cell activation 7 4.48 0.002 CD3Q CD3E, FYN, TNFSF14, SOX4, FKBP1A, LCP1 5.29
G0:0008092~cytoskeletal protein binding 14 8.97 0.002 STX1A, APC2, BA1AP2, ACTN1, ARPC4, AQP2, YWHAH, SYN1, FYN, SORBS2, ARPC2, CALM2, LCP1, BCL7B 2.61
oxygen transport 3 1.92 0.004 HBA2, HBA1, HBE1, HBB 30.82
G0:0046649~lymphocyte activation 8 5.12 0.004 CD3G, CD3E, FYN, TNFSF14, SOX4, FKBP1A, CD79A, LCP1 3.82
G0:0007269~neurotransmitter secretion 4 2.56 0.005 STX1A, DOC2A, SYN1, SYN2 11.2
G0:0005856~cytoskeleton 25 16 0.008 APC2, GNA11, AURKC, CASK, ARPC4, CCT3, OFD1, ACTG2, PEA15, DYNLL1, SPRR2D, SORBS2, ARPC2, TPT1, TUBG1, STX1A, KIF5A, ACTN1, KRT13, KRT17, SGCG, RUVBL1, SSNA1, LCP1, CALM2 1.72
calcium binding 5 3.2 0.009 DOC2A, ACINI, CALM2, CALB2, LCP1 5.98
G0:0007267~cell-cell signaling 14 8.97 0.009 LALBA, INSL3, EGR3, STX1A, GLRA1, KIF5A, SLC6A2, CTF1, CALCA, DOC2A, SSTR3, SYN1, SYN2, STC1 2.22
calcium 14 8.97 0.013 LALBA, ARSE, PRSS1, ACTN1, CALB2, SSR1, ATP2B1, SLC25A12, DOC2A, FBLN2, TPT1, ARSA, LCP1, CALM2 2.14
G0:0060191~regulation of lipase activity 5 3.2 0.012 CALCA, AGTR2, GNA11, APOH, FKBP1A 5.47
GO:0051004-regulation of lipoprotein lipase activity 3 1.92 0.013 AGTR2, APOH, FKBP1A 16.81
G0:0006706~steroid catabolic process 3 1.92 0.019 YWHAH, HSD17B6, SCARF1 13.6
G0:0008217-regulation of blood pressure 5 3.2 0.02 CALCA, ACTG2, AGTR2, HBB, AQP2 4.76
IPR002290:Serine/threonine protein kinase 7 4.48 0.03 DYRK1A, MAP4K2, AURKC, CASK, DYRK3, DYRK2, PRKX 2.96
immune response 6 3.84 0.035 HLA-C, CD79A, TNFSF12, PTMS, HLA-G, B2M 3.3
G0:0002684~positive regulation of immune system process 7 4.48 0.038 CD3E, FYN, TNFSF14, RARA, CD79A, TNFSF12, B2M 2.8
G0:0003073~regulation of systemic arterial blood pressure 3 1.92 0.051 CALCA, AGTR2, AQP2 8.16
G0:0050878~regulation of body fluid levels 5 3.2 0.06 GP5, GP1BB, PABPC4, APOH, AQP2 3.37
ribonucleoprotein 6 3.84 0.075 SRP14, RPL3L, MRPL49, RPL37, RPL38, SNRPF 2.65
G0:0032844~regulation of homeostatic process 4 2.56 0.116 CALCA, FKBP1A, CALM2, AHSG 3.34
G0:0005509~calcium ion binding 14 8.97 0.171 LALBA, ARSE, PRSS1, ACTN1, CALB2, SSR1, ATP2B1, SLC25A12, DOC2A, FBLN2, TPT1, ARSA, LCP1, CALM2 1.43
G00:0051924-regulation of calcium ion transport 3 1.92 0.161 CALCA, FKBP1A, CALM2 4.14
ubl conjugation 8 5.12 0.197 CUL3, CUL2, CEBPB, HIST2H2BE, SORBS2, COX6A2, HLA-C, CALM2 1.67
G0:0007155~cell adhesion 11 7.05 0.194 CALCA, GP5, GP1BB, CASK, PTPRS, ACTN1, ADAM 12, ECM2, CD151, SCARF1, NPHP1 1.49
G0:0019953~sexual reproduction 8 5.12 0.201 INSL3, GLRA1, DYNLL1, ARSA, RUVBL1, PPAP2A, PPAP2B, CNGA1 1.66
palmitate 4 2.56 0.243 STK16, FYN, GPA33, CD151 2.31
G0:0006936~muscle contraction 4 2.56 0.213 ACTG2, GLRA1, GNA11, FKBP1A 2.49
GO:0016887~ATPase activity 6 3.84 0.277 TNFRSF6B, ATP2B1, PSMC5, DHX16, RUVBL1, ABCC6 1.69
G0:0003700~transcription factor activity 12 7.69 0.454 SHOX2, DLX3, TCF21, EGR3, CEBPB, FOXN1, SOX4, RARA, PBX2, RFXANK, PITX1, PLAGL2 1.15
G0:0044057~regulation of system process 5 3.2 0.402 CALCA, STX1A, AGTR2, YWHAH, GLRA1 1.54
G0:0009055~electron carrier activity 3 1.92 0.68 ACOX2, HSD17B6, RDH16 1.27
G0:0055085- transmembrane transport 6 3.84 0.712 SLC25A12, AQP5, SLC30A3, CNGA1, AQP2, ABCC6 1
G0:0055085~transmembrane transport 6 3.84 0.712 SLC25A12, AQP5, SLC30A3, CNGA1, AQP2, ABCC6 1
G0:0050890~cognition 6 3.84 0.964 CALCA, GLRA1, FYN, OR6A2, CNGA1, ABCC6 0.62
Table 3:: Pathway specific transcripts of high altitude acclimatization
Term Count % P Value Genes Fold Enrichment
hsa04612:Antigen processing and presentation 5 3.2 0.01 HLA-C, IFNA14, RFXANK, HLA-G, B2M 4.71
h_ctlPathway: CTL mediated immune response against target cells 3 1.92 0.03 CD3Q CD3E, B2M 9.91
hsa04912:GnRH signaling pathway 4 2.56 0.12 GNA11, GNRHR, CALM2, PRKX 3.19
hsa04270: Vascular smooth muscle contraction 4 2.56 0.16 ACTG2, GNA11, CALM2, PRKX 2.79
hsa04120:Ubiquitin mediated proteolysis 4 2.56 0.24 CUL3, CUL2, UBE2D3, UBE2L3 2.28
hsa04810:Regulation of actin, cytoskeleton 5 3.2 0.28 APC2, ARPC2, BAIAP2, ACTN1, ARPC4 1.81
hsa04020:Calcium signaling pathway 4 2.56 0.38 ATP2B1, GNA11, CALM2, PRKX 1.77
hsa04080:Neuroactive ligand-receptor interaction 5 3.2 0.4 AGTR2, SSTR3, GLRA1, PRSS1, GNRHR 1.52
hsa04060:Cytokine-cytokine receptor interaction 5 3.2 0.42 TNFRSF6B, CTF1, TNFSF14, IFNA14, TNFSF12 1.49'
hsa04080:Neuroactive ligand-receptor interaction 5 3.2 0.4 AGTR2, SSTR3, GLRA1, PRSS1, GNRHR 1.52
hsa04060:Cytokine-cytokine receptor interaction 5 3.2 0.42 TNFRSF6B, CTF1, TNFSF14, IFNA14, TNFSF12 1.49

In individuals with HAPE, thirty one transcripts were down regulated and fourteen transcripts were upregulated when compared to URR. In resistant control samples, twenty six genes were down regulated and eighteen genes were upregulated compared to URR. Although the pattern of gene expression was distinct in the three groups, there was overlapping also (Fig 1). Genes like alpha 2-HS glycoproein (AHSG), neurotansmiter transporter (SLC6A2), ADAM metallopeptidase domain 12 (ADAM12), UDP- glucose ceramideglycosyltransferase (UGCG) gonadotropin releasing hormone receptor (GNRHR), solute carrier family 6 (SLC6A2), protein coupled receptor CD3 antigen (T3E), aquaporin 2 (AQP2), mitochodrial ribosomal protein L49 (MRPL49), ATP binding cassette sub family C (CFTR/MRP), member 6 (ABCC6), lymphocyte cytosolic protein 1 (LCP1), distal less homeobox 3 (DLX3), keratin 13 (KRT13), a transmembrane glycoprotein A33 (GPA33) major histocompatibility complex class I C (HLA-C) adenine phosphorybosyltransferase (APRT) were more pronounced in HAPE than in resistant controls. Downregulated transcripts in HAPE were lysyl oxidase-like 1 (LOXL1), Wiskott-Aldrich syndrome protein interacting protein (WSPIP), pancreatic popeptide (PPY), hepatic transcription factor 1 (TCF1), actin gama 2 (ACTG2), solute carrier family 30 (zinc transporter) (SLC30A3), protein tyrosine phosphatase receptor type S (PTPRS) and protein tyrosine phosphatase receptor type N (PPRN).

Fig 1.: Hierarchical clustering of gene expression from individuals who developed HAPE labeled with Cy3 compared to Universal Reference RNA labeled with Cy5 (Group I), matched controls who did not developed HAPE labeled with Cy3 compared to Universal Reference RNA labeled with Cy5 (Group II) and individuals at sea level labeled with Cy3 and at high altitude after acclimatization labeled with Cy5 (Group III).

Discussion

Low cellular oxygen tension (hypoxia) is a feature of high altitude. An integral part of the human cellular response to hypoxia is changes in gene expression [6, 7]. Till date, more than 100 genes have been identified that show a change in expression during hypoxic exposure, including a number of genes that are thought to be part of a nonspecific cellular response to stress. In the present study, about 89 transcripts showed a change in gene expression on the 3.8 K gene array after acute induction to altitude and were protein coding type. High altitude hypoxia appears to have a substantial down regulatory effect on transcript expression in peripheral blood cells. The functional clusters of apoptosis, oxygen transport, neurotransmitter secretion, regulation of blood pressure, regulation of body fluid levels, cell-cell signaling, transcripts of calcium ion binding were evident of an hypoxic signature of altitude acclimatization. The pathways which were found to be affected were antigen processing and presentation (hsa04612), h_ctlPathway: CTL mediated immune response against target cells, GnRH signaling pathway (hsa04912), vascular smooth muscle contraction (hsa04270), ubiquitin mediated proteolysis (hsa04120), regulation of actin cytoskeleton (hsa04810), calcium signaling pathway (hsa04020), neuroactive ligand-receptor interaction (hsa04080) and cytokine-cytokine receptor interaction (hsa04060).

It has been reported that continuous residence at moderate heights (2,000-2,500 m) tends to improve oxygen transport capacity by an erythropoietin-induced increase in the hematocrit [8]. An increase in hemoglobin concentration augments maximal 02 consumption (V02max) and enhances exercise performance [9]. In the present study, increase in expression of hemoglobin alpha 1 and hemoglobin alpha 2 was noted on acute altitude induction. The result of the present study suggests that cellular response to hypoxia at the level of transcript expression is quite broad, although it may also be more specific to hypoxia than generally appreciated. Fink and colleagues [10] by applying DNA array technology and real-time PCRin a variety of human hepatocyte cell lines identified several previously unrecognized hypoxia-responsive genes; it was also seen that hypoxic exposure without reoxygenation led to an overall decrease in the number of transcripts expressed by cells, although increase in expression of heat shock proteins was not observed. In a recent study on effect of hypoxia on gene expression in HepG2 cells, it was shown that gene expression was broad, had a significant component of down regulation, and included a relatively small number of genes whose response was independent of cell and stress type [11].

Profiles of gene expression patterns are helping to define the complex biological processes associated with both health and disease in vivo. Microarrays can identify changes in gene expression that can be used as biomarkers of environmental and any other stress related exposure and their early effect and can provide information on mechanisms of various biological processes. DNA arrays have increased substantially in power and complexity and application of late-generation arrays would enable identification of more hypoxia- responsive genes. Gene expression is often stochastic [12] because most genes exist at single or low copy number in a cell. Some genes are expressed at high levels and others at low levels. It is now possible to track mRNA expression in a single cell with single molecule sensitivity in real time dynamics providing mechanistic insight into macromolecules [13]. Such kind of real time assays together with other emerging single molecule techniques [14] will yield further insight into not only gene expression and but many other fundamental biological processes. Understanding of this biological phenomenon will strategize therapeutic approaches for combating the harsh environment as well as perform better under the circumstances.

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