This article has Open Peer Review reports available.
Alterations in lung gene expression in streptozotocin-induced diabetic rats
© van Lunteren et al.; licensee BioMed Central Ltd. 2014
Received: 7 October 2013
Accepted: 8 January 2014
Published: 15 January 2014
Diabetes profoundly affects gene expression in organs such as heart, skeletal muscle, kidney and liver, with areas of perturbation including carbohydrate and lipid metabolism, oxidative stress, and protein ubiquitination. Type 1 diabetes impairs lung function, but whether gene expression alterations in the lung parallel those of other tissue types is largely unexplored.
Lung from a rat model of diabetes mellitus induced by streptozotocin was subjected to gene expression microarray analysis.
Glucose levels were 67 and 260 mg/dl (p < 0.001) in control and diabetic rats, respectively. There were 46 genes with at least ± 1.5-fold significantly altered expression (19 increases, 27 decreases). Gene ontology groups with significant over-representation among genes with altered expression included apoptosis, response to stress (p = 0.03), regulation of protein kinase activity (p = 0.04), ion transporter activity (p = 0.01) and collagen (p = 0.01). All genes assigned to the apoptosis and response to stress groups had increased expression whereas all genes assigned to the collagen group had decreased expression. In contrast, the protein kinase activity and ion transporter activity groups had genes with both increased and decreased expression.
Gene expression in the lung is affected by type 1 diabetes in several specific areas, including apoptosis. However, the lung is resistant to changes in gene expression related to lipid and carbohydrate metabolism and oxidative stress that occur in other tissue types such as heart, skeletal muscle and kidney.
Type 1 diabetes mellitus has widespread adverse effects on many tissues, including heart, kidney, retina, liver, vasculature, peripheral nerve and skeletal muscle. These perturbations contribute importantly to the heightened morbidity and mortality of subjects with diabetes. The lung is also affected by type 1 diabetes, manifested by declines in diffusion capacity, total lung capacity and forced vital capacity [1–5]. This may contribute to the reduced exercise capacity of humans with type 1 diabetes  and account for a portion of the increased sensation of dyspnea in diabetics when ventilation or respiratory efforts are increased [7, 8]. Nonetheless, severe lung disease is rarely produced by diabetes, suggesting that the lung is more resistant than other organs to this disorder.
Alveolar microangiopathy is postulated to play a prominent role in the genesis of diabetes-induced lung impairment . However, the cellular events leading to lung impairment, and the reasons for the relative sparing of the lung compared with other organs such as the kidney and the eye, are not fully understood. One area with a particular paucity of information is the manner in which diabetes affects expression of genes in the lung. This contrasts with the extensive information gleaned from gene expression array studies of other tissue types, including pancreas , kidney [11–13], liver , spleen , adipose tissue , eye , corpus cavernosum , heart [18–20] and skeletal muscle [14, 21–23]. Perturbations of gene expression by diabetes in these organs are large in number and magnitude, and cover many cellular processes such as carbohydrate and lipid metabolism, oxidative stress, and protein ubiquitination. The purposes of the present study were to a) determine the changes in gene expression in the lung due to streptozotocin-induced diabetes, including alterations in expression of genes in common gene ontology groups and b) examine the extent to which affected processes are similar to those reported for other tissue types or are unique to the lung.
Studies were performed on twelve male Wistar rats obtained from Charles River Laboratories (Wilmington, MA). All studies were approved by the institutional animal care and use committee of the Department of Veterans Affairs (Veterans Health Administration) and conformed with NIH guidelines for animal care. The streptozotocin-induced model was similar to that of Hida et al. . At an age of eight weeks, seven animals were injected intraperitoneally with streptozotocin 60 mg/kg dissolved in sodium citrate buffer, and five with buffer alone. Four weeks later they were well-anesthetized with a mixture of intraperitoneal ketamine, xylazine and acepromazine following an all-night fast. Blood obtained from the tail was analyzed for glucose using a glucometer (Lifescan, Milpitas, CA). Fasting blood glucose values were 67 ± 4 mg/dl (range 59 to 76) for the normal animals, and 260 ± 13 mg/dl (range 222 to 313) for the diabetic animals (P < 0.001 by unpaired t test). Both lungs from each animal were removed surgically, placed in RNAlater, and stored at -80°C.
Gene expression array studies were performed similar to previous investigations from our laboratory [20, 25, 26]. Total RNA was extracted using Trizol (GibcoBRL, Rockville, MD), and the RNA pellets were resuspended at 1 μg RNA/μl DEPC-treated water. This was followed by a cleanup protocol with a Qiagen (Valencia, CA) RNeasy Total RNA mini kit. Total RNA was prepared for use on Affymetrix (Santa Clara, CA) microarrays, according to the directions from the manufacturer. Briefly, 8 μg of RNA was used in a reverse transcription reaction (SuperScript II; Life Technologies, Rockville, MD) to generate first strand cDNA. After second strand synthesis, double strand cDNA was used in an in vitro transcription reaction to generate biotinylated cRNA. This was purified and fragmented, following which 15 μg of biotin-labeled cRNA was used in a 300 μl hybridization cocktail which included spiked transcript controls. 200 μl of cocktail was loaded onto Affymetrix RAE 230A microarrays (Santa Clara, CA) and hybridized for 16 hr at 45°C with agitation. Standard post-hybridization washes and double-stain protocols used an Affymetrix GeneChip Fluidics Station 400. Arrays were scanned using a Hewlett Packard Gene Array scanner, and analyzed with Affymetrix MAS 5.0 software. The data have been deposited in the NCBI Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO Series accession number GSE15900.
Statistical analysis of the microarray data utilized Bayesian analysis of variance for microarrays (BAM), using BAMarray software (http://www.bamarray.com) . Genes identified by BAM as having significantly changed expression were then further selected based on consistent and appropriate present and absent calls per Affymetrix software. Subsequently signals were averaged for tissue from the non-diabetic and from diabetic animals, and fold changes were calculated based on average values from each group. Analysis focused on genes whose expression changed at least ±1.5 fold in diabetic compared with control lung tissue, unless indicated otherwise. To assign biological meaning to the group of genes with changed expression, the subset of genes which met the above criteria was analyzed with the Gene Ontology (GO) classification system, using DAVID 2.1 software (http://david.abcc.ncifcrf.gov/) [28, 29]. Over-representation of genes with altered expression within specific GO categories was determined using the one-tailed Fisher exact probability modified by the addition of a jackknifing procedure, which penalizes the significance of categories with very few genes and favors more robust categories with larger numbers of genes.
Real-time PCR (RT-PCR) was used to confirm changes in gene expression as described previously [20, 25, 26]. Testing was done using the same lung tissue that had been used for gene expression arrays. An Applied Biosystems ABI 7900HT unit with automation attachment (Foster City, CA) was used for RT-PCR. This unit is capable of collecting spectral data at multiple points during a PCR run. To execute the first step and make archive cDNA, 3 μg of total RNA was reverse transcribed in a 100 μl reaction using Applied Biosystems enzymes and reagents in accordance with the manufacturer’s protocols. RNA samples were accurately quantitated using a Nanodrop Technologies ND-1000 spectrophotometer (Wilmington, DE). Equal amounts of total RNA were reverse transcribed and then used in PCR amplifications. β-Actin had very little variation in expression across the sample set and therefore was chosen as the endogenous control. Since many of the target genes of interest were signaling molecules and likely to be expressed at low levels, we opted for a low dilution factor so as to create an environment more conducive to obtaining reliable results. The cDNA reaction from above was diluted by a factor of 10. For the PCR step, 9 μl of this diluted cDNA was used for each of three replicate 15 μl-reactions carried out in a 384 well plate. Standard PCR conditions were used for the Applied Biosystems assays: 50°C for 2 min, followed by 95°C for 10 min, followed by 40 cycles of 95°C for 15 sec alternating with 60°C for 1 min each. Values for RNA abundance were normalized for each gene with respect to the endogenous control in that sample, mean values for fold changes were calculated for each gene, and statistical testing was performed with the unpaired t-test.
Diabetes altered the expression of a relatively small number of genes in the lung
Fold change threshold
Total number of genes
Genes with increased expression
Genes with decreased expression
Five major specific gene ontology (GO) groupings with statistically significant over-representation among genes with at least 1.5-fold changed expression in diabetic compared with normal lung
Number of genes
Specific GO term
Terms Related to collagen
Terms Related to Ion Transport
Ion Transporter Activity
Cation Transporter Activity
Terms Related to Apoptosis and Cell Death
Programmed Cell Death
Terms Related to Response to Stress
Response to Stress
Terms Related to Regulation of Kinase Activity
Regulation of Protein Kinase Activity
Regulation of Kinase Activity
Positive Regulation of Protein Kinase Activity
Specific genes assigned to the gene ontology groups for which the direction of the expression changes were uniform
Apoptosis and Cell Death
growth arrest and DNA-damage-inducible 45 beta
Kruppel-like factor 10
estrogen receptor-binding fragment-associated gene 9
protein kinase, AMP-activated, alpha 1 catalytic subunit
Response to Stress
connective tissue growth factor
growth arrest and DNA-damage-inducible 45 beta
protein kinase, AMP-activated, alpha 1 catalytic subunit
lipopolysaccharide binding protein
procollagen, type XV
procollagen, type 1, alpha 1
procollagen, type III, alpha 1
The present study used a genome-wide expression approach to characterize alterations in lung gene expression by streptozotocin-induced diabetes in rats. Several specific areas were noted with altered gene expression, three of which had uniform directional changes (apoptosis/cell death, response to stress and collagen) and two of which had heterogeneous directional changes (protein kinase activity and ion transport). Nonetheless, the number of genes with altered expression, and the magnitude of the changed expression, were modest compared with findings in most other (albeit not all) tissue types reported previously [13, 15–21, 31].
Several GO groups of genes with streptozotocin-induced diabetes altered expression found in the present lung study have previously been identified in gene expression array studies of other organ systems. Diabetes-induced changed gene expression related to apoptosis and/or cell death has been found in spleen , skeletal muscle , and lens . Gene expression changes related to response to stress have been found in skeletal muscle  and lens . Collagen gene expression changes have been found in skeletal muscle [21, 31], corpus cavernosum , and heart . Thus lung and other tissue types share at least some of the effects of type 1 diabetes on gene expression.
A previous study found differences among tissue types (kidney, heart, skeletal muscle and retina) in the effects of diabetes on gene expression . In the present study, two gene groups identified as having changed expression with diabetes in the lung were not identified as having changed expression in a number of gene expression array studies examining other tissues, namely protein kinase activity and ion transport [13, 15–21, 31]. Conversely, many GO groups of genes with changed expression in other tissues were not found to have changed expression in the lung. One notable area is that of energy production, including lipid and carbohydrate metabolism, which has been identified as having changed expression with type 1 diabetes in skeletal muscle [19, 21], heart [18–20], and kidney . Another area is that of oxidative stress, for which gene expression changes have been described with type 1 diabetes in corpus cavernosum  and heart [18, 20]. One limitation of such direct comparisons of tissue types is the methodological heterogeneity among studies with regards to the specific model of type 1 diabetes studied, the type of gene expression array, and the data analysis and statistical approaches. However, a previous study of the heart from our laboratory  used the same methodological strategies as the present study, and identified cardiac changes related to lipid metabolism, oxidoreductase activity and calcium ion binding which were not found in the lung in the present study. This suggests that lung has tissue-specific gene expression responses to type 1 diabetes in addition to the shared responses already mentioned.
Among the five GO terms or groups of GO terms identified as having changed gene expression in the lung with type 1 diabetes, apotosis/cell death is an attractive candidate process that may contribute importantly to the genesis of functional impairment of the lung. Interestingly, insulin inhibits apoptosis  and furthermore tight glycemic control accomplished with exogenous insulin or pancreatic transplantation attenuates and/or reverses type 1 diabetes-induced pulmonary function abnormalities [2, 33]. Furthermore, osteopontin-deficient mice with streptozotocin-induced diabetes have milder cardiomyopathy and reduced apoptosis compared with wild-type mice with streptozotocin-induced diabetes , supporting the involvement of apotosis in diabetes-induced organ dysfunction (albeit that of cardiac muscle). However, genes belonging to the other four GO terms or groups of GO terms, or even single genes not assigned to specific GO terms, may very well also play important roles in the genesis of pulmonary dysfunction with diabetes.
In summary, this study demonstrates that diabetes mellitus induced by streptozotocin alters gene expression in the lung of Wistar rats. Directionally uniform changes were noted for genes involved in three areas, apoptosis/cell death, response to stress and collagen, whereas directionally heterogeneous changes were noted for genes involved in the regulation of protein kinase activity and ion transport. Equally notable was the absence of changes in some processes such as carbohydrate and lipid metabolism that are implicated in diabetes-induced dysfunction in other tissues.
We would like to thank Dr. Patrick Leahy from the Gene Expression Array Core Facility of the Comprehensive Cancer Center of Case Western Reserve University.
These studies were supported by funding from the Department of Veterans Affairs (Veterans Health Administration).
- Boulbou MS, Gourgoulianis KI, Klisiaris VK, Tsikrikas TS, Stathakis NE, Molyvdas PA: Diabetes mellitus and lung function. Med Princ Pract. 2003, 12: 87-91. 10.1159/000069118.View ArticlePubMedGoogle Scholar
- Dieterle CD, Schmauss S, Arbogast H, Domsch C, Huber RM, Landgraf R: Pulmonary function in patients with type 1 diabetes before and after simultaneous pancreas and kidney transplantation. Transplantation. 2007, 83: 566-569. 10.1097/01.tp.0000253882.95177.61.View ArticlePubMedGoogle Scholar
- Kaparianos A, Argyropoulou E, Sampsonas F, Karkoulias K, Tsiamita M, Spiropoulos K: Pulmonary complications in diabetes mellitus. Chron Respir Dis. 2008, 5: 101-108. 10.1177/1479972307086313.View ArticlePubMedGoogle Scholar
- Schnack C, Festa A, Schwarzmaier-D'Assié A, Haber P, Schernthaner G: Pulmonary dysfunction in type 1 diabetes in relation to metabolic long-term control and to incipient diabetic nephropathy. Nephron. 1996, 74: 395-400. 10.1159/000189342.View ArticlePubMedGoogle Scholar
- Villa MP, Montesano M, Barreto M, Pagani J, Stegagno M, Multari G, Ronchetti R: Diffusing capacity for carbon monoxide in children with type 1 diabetes. Diabetologia. 2004, 47: 1931-1935. 10.1007/s00125-004-1548-7.View ArticlePubMedGoogle Scholar
- Wanke T, Formanek D, Auinger M, Zwick H, Irsigler K: Pulmonary gas exchange and oxygen uptake during exercise in patients with type 1 diabetes mellitus. Diabet Med. 1992, 9: 252-257. 10.1111/j.1464-5491.1992.tb01771.x.View ArticlePubMedGoogle Scholar
- Scano G, Filippelli M, Romagnoli I, Mancini M, Misuri G, Duranti R, Rosi E: Hypoxic and hypercapnic breathlessness in patients with type I diabetes mellitus. Chest. 2000, 117: 960-967. 10.1378/chest.117.4.960.View ArticlePubMedGoogle Scholar
- Wanke T, Lahrmann H, Auinger M, Merkle M, Formanek D, Ogris E, Irsigler K, Zwick H: Endogenous opiod system during inspiratory loading in patients with type 1 diabetes. Am Rev Respir Dis. 1993, 148: 1335-1340. 10.1164/ajrccm/148.5.1335.View ArticlePubMedGoogle Scholar
- Hsia CC, Raskin P: The diabetic lung: relevance of alveolar microangiopathy for the use of inhaled insulin. Am J Med. 2006, 118: 205-211.View ArticleGoogle Scholar
- Garnett KE, Chapman P, Chambers JA, Waddell ID, Boam DS: Differential gene expression between Zucker Fatty rats and Zucker Diabetic Fatty rats: a potential role for the immediate-early gene Egr-1 in regulation of beta cell proliferation. J Mol Endocrinol. 2005, 35: 13-25. 10.1677/jme.1.01792.View ArticlePubMedGoogle Scholar
- Baelde HJ, Eikmans M, Doran PP, Lappin DW, de Heer E, Bruijn JA: Gene expression profiling in glomeruli from human kidneys with diabetic nephropathy. Am J Kidney Dis. 2004, 43: 636-650. 10.1053/j.ajkd.2003.12.028.View ArticlePubMedGoogle Scholar
- Fan Q, Shike T, Shigihara T, Tanimoto M, Gohda T, Makita Y, Wang LN, Horikoshi S, Tomino Y: Gene expression profile in diabetic KK/Ta mice. Kidney Int. 2003, 64: 1978-1985. 10.1046/j.1523-1755.2003.00312.x.View ArticlePubMedGoogle Scholar
- Wilson KH, Eckenrode SE, Li QZ, Ruan QG, Yang P, Shi JD, Davoodi-Semiromi A, McIndoe RA, Croker BP, She JX: Microarray analysis of gene expression in the kidneys of new- and post-onset diabetic NOD mice. Diabetes. 2003, 52: 2151-2159. 10.2337/diabetes.52.8.2151.View ArticlePubMedGoogle Scholar
- Suh YH, Kim Y, Bang JH, Choi KS, Lee JW, Kim WH, Oh TJ, An S, Jung MH: Analysis of gene expression profiles in insulin-sensitive tissues from pre-diabetic and diabetic Zucker diabetic fatty rats. J Mol Endocrinol. 2005, 34: 299-315. 10.1677/jme.1.01679.View ArticlePubMedGoogle Scholar
- Eckenrode SE, Ruan Q, Yang P, Zheng W, McIndoe RA, She JX: Gene expression profiles define a key checkpoint for type 1 diabetes in NOD mice. Diabetes. 2004, 53: 366-375. 10.2337/diabetes.53.2.366.View ArticlePubMedGoogle Scholar
- Kubo E, Singh DP, Akagi Y: Gene expression profiling of diabetic and galactosaemic cataractous rat lens by microarray analysis. Diabetologia. 2005, 48: 790-798. 10.1007/s00125-005-1687-5.View ArticlePubMedGoogle Scholar
- Sullivan CJ, Teal TH, Luttrell IP, Tran KB, Peters MA, Wessells H: Microarray analysis reveals novel gene expression changes associated with erectile dysfunction in diabetic rats. Physiol Genomics. 2005, 23: 192-205. 10.1152/physiolgenomics.00112.2005.View ArticlePubMedPubMed CentralGoogle Scholar
- Gerber LK, Aronow BJ, Matlib MA: Activation of a novel long-chain free fatty acid generation and export system in mitochondria of diabetic rat hearts. Am J Physiol. 2006, 291: C1198-C1207. 10.1152/ajpcell.00246.2006.View ArticleGoogle Scholar
- Knoll KE, Pietrusz JL, Liang M: Tissue-specific transcriptome responses in rats with early streptozotocin-induced diabetes. Physiol Genomics. 2005, 21: 222-229. 10.1152/physiolgenomics.00231.2004.View ArticlePubMedGoogle Scholar
- van Lunteren E, Moyer M: Oxidoreductase, morphogenesis, extracellular matrix and calcium ion binding gene expression in streptozotocin-induced diabetic rat heart. Am J Physiol Endocrinol Metab. 2007, 293: E759-E768. 10.1152/ajpendo.00191.2007.View ArticlePubMedGoogle Scholar
- Lecker SH, Jagoe RT, Gilbert A, Gomes M, Baracos V, Bailey J, Price SR, Mitch WE, Goldberg AL: Multiple types of skeletal muscle atrophy involve a common program of changes in gene expression. FASEB J. 2004, 18: 39-51. 10.1096/fj.03-0610com.View ArticlePubMedGoogle Scholar
- Sreekumar R, Halvatsiotis P, Schimke JC, Nair KS: Gene expression profile in skeletal muscle of type 2 diabetes and the effect of insulin treatment. Diabetes. 2002, 51: 1913-1920. 10.2337/diabetes.51.6.1913.View ArticlePubMedGoogle Scholar
- Voss MD, Beha A, Tennagels N, Tschank G, Herling AW, Quint M, Gerl M, Metz-Weidmann C, Haun G, Korn M: Gene expression profiling in skeletal muscle of Zucker diabetic fatty rats: implications for a role of stearoyl-CoA desaturase 1 in insulin resistance. Diabetologia. 2005, 48: 2622-2630. 10.1007/s00125-005-0025-2.View ArticlePubMedGoogle Scholar
- Hida W, Shindob C, Satoh J, Sagara M, Kikuchi Y, Toyota T, Shirato K: N-acetyl inhibits loss of diaphragm function in streptozotocin-treated rats. Am J Crit Care Med. 1996, 153: 1875-1979. 10.1164/ajrccm.153.6.8665049.View ArticleGoogle Scholar
- van Lunteren E, Moyer M, Leahy P: Gene expression profiling of diaphragm muscle in alpha2-laminin (merosin)-deficient dy/dy dystrophic mice. Physiol Genomics. 2006, 25: 85-95. 10.1152/physiolgenomics.00226.2005.View ArticlePubMedGoogle Scholar
- van Lunteren E, Spiegler S, Moyer M: Contrast between cardiac left ventricle and diaphragm muscle in expression of genes involved in carbohydrate and lipid metabolism. Respir Physiol Neurobiol. 2008, 161: 41-53. 10.1016/j.resp.2007.11.005.View ArticlePubMedGoogle Scholar
- Ishwaran H, Rao JS: Detecting differentially expressed genes in microarrays using Bayesian model selection. J Am Stat Assoc. 2003, 98: 438-455. 10.1198/016214503000224.View ArticleGoogle Scholar
- Dennis G, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA: DAVID: data base for annotation, visualization, and integrated discovery. Genome Biol. 2003, 4: R60-10.1186/gb-2003-4-9-r60.View ArticlePubMed CentralGoogle Scholar
- Hosack DA, Dennis G, Sherman BT, Lane HC, Lempicki RA: Identifying biological themes within lists of genes with EASE. Genome Biol. 2003, 4: R70-10.1186/gb-2003-4-10-r70.View ArticlePubMedPubMed CentralGoogle Scholar
- Porter JD, Merriam AP, Leahy P, Gong B, Feuerman J, Cheng G, Khanna S: Temporal gene expression profiling of dystrophin-deficient (mdx) mouse diaphragm identifies conserved and muscle-group specific mechanisms in the pathogenesis of muscular dystrophy. Hum Mol Genet. 2004, 13: 257-269.View ArticlePubMedGoogle Scholar
- Lehti TM, Silvennoinen M, Kiveli R, Kainulainen H, Komulainen J: Effects of streptozotocin-induced diabetes and physical training on gene expression of extracellular matrix proteins in mouse skeletal muscle. Am J Physiol Endocrinol Metab. 2006, 290: E900-E907. 10.1152/ajpendo.00444.2005.View ArticlePubMedGoogle Scholar
- Iida KT, Suzuki H, Sone H, Shimano H, Toyoshima H, Yatoh S, Asano T, Okuda Y, Yamada N: Insulin inhibits apoptosis of macrophage cell line, THP-1 cells, via phosphatidylinositol-3-kinase-dependent pathway. Arterioscler Thromb Vasc Biol. 2002, 22: 380-386. 10.1161/hq0302.105272.View ArticlePubMedGoogle Scholar
- Ramirez LC, Dal Nogare A, Hsia C, Arauz C, Butt I, Strowig SM, Schnurr-Breen L, Raskin P: Relationship between diabetes control and pulmonary function in insulin-dependent diabetes mellitus. Am J Med. 1991, 91: 371-376. 10.1016/0002-9343(91)90154-P.View ArticlePubMedGoogle Scholar
- Subramanian V, Krishnamurthy P, Singh K, Singh M: Lack of osteopontin improves cardiac function in streptozotocin-induced diabetic mice. Am J Physiol Heart Circ Physiol. 2007, 292: H673-H683.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6823/14/5/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.