| Literature DB >> 23409001 |
Bing Li1, Yuguan Ze, Qingqing Sun, Ting Zhang, Xuezi Sang, Yaling Cui, Xiaochun Wang, Suxin Gui, Danlin Tan, Min Zhu, Xiaoyang Zhao, Lei Sheng, Ling Wang, Fashui Hong, Meng Tang.
Abstract
The pulmonary damage induced by nanosized titanium dioxide (nano-TiO2) is of great concern, but the mechanism of how this damage may be incurred has yet to be elucidated. Here, we examined how multiple genes may be affected by nano-TiO2 exposure to contribute to the observed damage. The results suggest that long-term exposure to nano-TiO2 led to significant increases in inflammatory cells, and levels of lactate dehydrogenase, alkaline phosphate, and total protein, and promoted production of reactive oxygen species and peroxidation of lipid, protein and DNA in mouse lung tissue. We also observed nano-TiO2 deposition in lung tissue via light and confocal Raman microscopy, which in turn led to severe pulmonary inflammation and pneumonocytic apoptosis in mice. Specifically, microarray analysis showed significant alterations in the expression of 847 genes in the nano-TiO2-exposed lung tissues. Of 521 genes with known functions, 361 were up-regulated and 160 down-regulated, which were associated with the immune/inflammatory responses, apoptosis, oxidative stress, the cell cycle, stress responses, cell proliferation, the cytoskeleton, signal transduction, and metabolic processes. Therefore, the application of nano-TiO2 should be carried out cautiously, especially in humans.Entities:
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Year: 2013 PMID: 23409001 PMCID: PMC3567101 DOI: 10.1371/journal.pone.0055563
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Body weight, relative weight of lung and titanium accumulation in the mouse lung after nasal administration with nano-TiO2 for 90 consecutive days.
| Index | Nano-TiO2 (mg/kg BW) | |||
| 0 | 2.5 | 5 | 10 | |
|
| 20±1a | 16±0.8b | 11±0.55c | 5±0.25d |
|
| 9.27±0.47a | 9.67±0.48a | 11.31±0.57b | 14.28±0.71c |
|
| Not detected | 65±3.25a | 113±5.65b | 207±10.35c |
Letters indicate significant differences between groups (p<0.05). Values represent means ± SE(N = 10).
Figure 1Histopathology of the lung tissue in ICR mice caused by nasal administration of nano-TiO2 for 90 consecutive days.
(a) Control group; (b) 2.5 mg/kg BW nano-TiO2 group indicates inflammatory cell infiltration (green cycles) and thickening of pulmonary interstitium (green arrows); (c) 5 mg/kg BW nano-TiO2 group indicates severs inflammatory cell infiltration (green circles), and great thickening of pulmonary interstitium (green arrows) and pulmonary edema (yellow arrows); (d) 10 mg/kg BW nano-TiO2 group indicates severe inflammatory cell infiltration (green arrows) and great thickening of pulmonary interstitium (green arrows), yellow circles show black deposition in the lung. Arrow A spot is a representative cell that not engulfed the nano-TiO2, while arrow B spot denotes a representative cell that loaded with nano-TiO2. The right panels show the corresponding Raman spectra identifying the specific peak at about 148 cm-1.
Figure 2Ultrastructure of pneumonocyte in female mice lung caused by nasal administration of nano-TiO2 for 90 consecutive days.
(a) Control: chromatin is well distributed, normal lamellar bodies; (b) 2.5 mg/kg BW nano-TiO2 indicates a significant shrinkage and chromatin marginalization of the nucleus (yellow arrows), mitochondria swelling(red arrows); (c) 5 mg/kg BW nano-TiO2 indicates a significant nucleus pyknosis (green arrows); (d) 10 mg/kg BW nano-TiO2 indicate a significant nucleus pyknosis (yellow arrows), mitochondria swelling(red arrows) as well as evacuation of lamellar bodies (green arrows), circles show black deposition. Arrow A spot is a representative cell that not engulfed the nano-TiO2, while arrow B spot denotes a representative cell that loaded with nano-TiO2. (c) The right panels show the corresponding Raman spectra identifying the specific peak at about 148 cm−1.
Numbers of inflammatory cells and biochemical changes in BALF of mice after nasal administration with nano-TiO2 for 90 consecutive days.
| Parameter | Nano-TiO2 (mg/kg BW) | |||
| 0 | 2.5 | 5 | 10 | |
|
| 11±0.55a | 20±1.0b | 36±1.80c | 50±2.95d |
|
| 3±0.15a | 6±0.30b | 11±0.55c | 19±0.95d |
|
| 6±0.31a | 14±0.70b | 22±1.10c | 36±1.80d |
|
| 5±0.25a | 10±0.50b | 17±0.85c | 28±1.40d |
|
| 582±29a | 689±34b | 778±39c | 986±49d |
|
| 100±5a | 136±7b | 188±9c | 225±11d |
|
| 26.68±1.34a | 33.49±1.67b | 41.96±2.10c | 48.21±2.41d |
Letters indicate significant differences between groups (p<0.05). Values represent means ± SE(N = 10).
Oxidative stress in the mouse lung after nasal administration with nano-TiO2 for 90 consecutive days.
| Oxidativestress | TiO2 NPs (mg/kg BW) | |||
| 0 | 2.5 | 5 | 10 | |
|
| 23±1.15a | 30.27±1.51b | 39.18±1.96c | 50±2.50d |
|
| 43±2.15a | 61.22±3.06b | 78.96±3.95c | 110±5.50d |
|
| 1.08±0.05a | 1.59±0.08b | 2.89±0.15c | 5.15±0.26d |
|
| 0.54±0.03a | 0.98±0.05b | 1.85±0.09c | 3.04±0.15d |
|
| 0.42±0.02a | 2.26±0.11b | 4.25±0.21c | 7.12±0.36d |
Letters indicate significant differences between groups (p<0.05). Values represent means ± SE (N = 5).
Figure 3Functional categorization of 521 genes.
Genes were functionally classied based on the ontology-driven clustering approach of PANTHER.
Significant alteration of representative genes after nasal administration of 10 mg/kg BW TiO2 NPs for 90 consecutive days.
| Symbol | Gene ID | Ontology | DiffScore | Pval | |
|
| Defb4 | NM_019728 | defense response to bacterium | 121.33 | 0 |
| H2-Oa | NM_008206 | regulation of T cell differentiation | −26.34 | 0 | |
|
| Chi3l3 | NM_009892 | inflammatory response | 93.12 | 0 |
| Alox5ap | NM_009663 | leukotriene production involved in inflammatory response | 20.37 | 0 | |
| Il1b | NM_008361 | inflammatory response | 14.56 | 0 | |
|
| Pdia2 | NM_001081070 | apoptosis | 73.16 | 0 |
| Niacr1 | NM_030701 | apoptosis | 67.22 | 0 | |
| Ada | NM_007398 | negative regulation of thymocyte apoptosis | 28.04 | 0.18 | |
| Sphk2 | NM_203280 | anti-apoptosis | −13.20 | 0 | |
| Erbb2 | NM_001003817 | negative regulation of apoptosis | −14.43 | 0 | |
|
| Cdkn1a | NM_001111099 | cell cycle arrest | 15.26 | 0 |
| Cdkn1c | NM_001161624 | Cell cycle | −15.89 | 0 | |
|
| Cryab | NM_009964 | oxygen and reactive oxygen species metabolic process | 25.36 | 0 |
| Alkbh7 | NM_025538 | oxidoreductase activity | −19.72 | 0 | |
Comparison of fold-difference between the control and 90 day 10 mg/kg BW dosage.
| Gene | △△Ct | Fold | Microarray |
|
| −1.786201 | 3.4490546778 | 2.458522 |
|
| 1.163294 | 0.44649192843 | 0.523989 |
|
| −1.536868 | 2.9016389168 | 1.98002 |
|
| −0.004397 | 1.0030524173 | 1.562935 |
|
| −2.280629 | 4.8588975045 | 6.867184 |
Figure 4Ada network pathway obtained from network analysis of differentially expressed genes.
Gene Spring software was used to construct and visualize molecular interaction networks.