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Hypoxic Signature of High Altitude Acclimatization: A Gene Expression Study
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).
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).
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 |
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).
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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