PDF(4852 KB)
PDF(4852 KB)
PDF(4852 KB)
秀丽隐杆线虫的线粒体形态和功能研究方法及应用实例
Approaches and Application Examples for Studying Mitochondrial Morphology and Function in Caenorhabditis elegans
线粒体作为细胞的能量代谢中枢,其动态形态和氧化磷酸化功能异常与衰老及多种疾病直接相关。秀丽隐杆线虫(Caenorhabditis elegans,C. elegans,以下简称线虫)是被广泛使用的模式动物。本文系统总结了作者实验室以线虫为模型,多尺度分析了线粒体形态与功能的实验方法,主要包括:(1)形态定性分析,即采用单盲法人工分类(如点状、棒状、网状),该法虽然依赖主观经验,但操作简便,适用于初步表型的筛选;(2)形态定量分析,即依托Fiji/ImageJ平台,对特定组织(如表皮及体壁肌)中线粒体进行自动化参数提取,通过骨架化算法量化网络连通性(分支点数量、网络长度),结合二值化分析计算碎片化指数(如面积/周长比、碎片计数),实现客观表型比对;(3)高通量图像处理,即通过宏命令批量处理,整合形态学滤波、阈值分割及参数导出流程,显著提升大样本量的研究效率;(4)代谢功能监测,即应用Seahorse XF分析仪开展活体线虫呼吸代谢检测,通过序贯注入ATP合酶抑制剂N,N′-二环己基碳二亚胺(dicyclohexylcarbodiimide,DCCD)、解偶联剂羰基氰化物 4-(三氟甲氧基)苯腙[carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone,FCCP]及呼吸链抑制剂叠氮钠(sodium azide,NaN?),精准解析基础耗氧率(oxygen consumption rate,OCR)、ATP耦合呼吸效率及最大呼吸容量(呼吸潜力),进而揭示能量代谢规律。本文整合了形态-功能双维度方法,不仅为关于线虫的线粒体研究提供经验技术,其框架亦可拓展至哺乳动物细胞与类器官模型,以推动靶向线粒体的基础研究和药物开发。
Mitochondria, as the energy metabolism center of cells, have abnormal dynamic morphology and oxidative phosphorylation function, which are directly related to aging and various diseases. Caenorhabditis elegans (C. elegans) is a widely used model animal. This article systematically summarizes the experimental methods for analyzing mitochondrial morphology and function at multiple scales in the laboratory using C. elegans as a model, mainly including: (1) morphological qualitative analysis, which uses a single-blind manual classification method (such as point, rod, and mesh), although it relies on subjective experience, it is easy to operate and suitable for preliminary phenotype screening; (2) morphological quantitative analysis, which relies on the Fiji/ImageJ platform for automated parameter extraction of mitochondria in specific tissues (such as epidermis and body wall muscles), quantifies network connectivity (number of branch points, network length) through skeletonization algorithm, and calculates fragmentation indices (such as area/perimeter ratio, fragment count) with binarization analysis, achieving objective phenotype comparison; (3) high-throughput image processing, which performs batch processing through macro commands, integrates morphological filtering, threshold segmentation, and parameter export workflow, significantly improving research efficiency for large sample sizes; (4) metabolic function monitoring, which uses the Seahorse XF analyzer to measure in vivo respiratory metabolism in C. elegans. By sequential injection of ATP synthase inhibitor N, N'-dicyclohexylcarbodiimide (DCCD), uncoupling agent carbonyl cyanide-4-(trifluoromethoxy) phenylhydrazone (FCCP) and respiratory chain inhibitor sodium azide (NaN3), the basal oxygen consumption rate (OCR), ATP coupled respiratory efficiency, and maximum respiratory capacity (respiratory potential) are accurately analyzed to reveal energy metabolism patterns. This article integrates a dual dimensional approach of morphology and function, which not only provides empirical techniques for mitochondrial research on C. elegans, but also extends its framework to mammalian cell and organoid models, promoting the basic research and drug development targeting mitochondria.
秀丽隐杆线虫 / 线粒体 / 氧化呼吸能力 / Fiji数据处理 / Seahorse检测 / 衰老模型
Caenorhabditis elegans / Mitochondria / Oxidative respiration / Fiji data processing / Seahorse assay / Aging model
| [1] | MUKHERJEE I, GHOSH M, MEINECKE M. MICOS and the mitochondrial inner membrane morphology–when things get out of shape[J]. FEBS Lett, 2021, 595(8):1159-1183. DOI:10.1002/1873-3468.14089 . |
| [2] | OKAMOTO K, SHAW J M. Mitochondrial morphology and dynamics in yeast and multicellular eukaryotes[J]. Annu Rev Genet, 2005, 39:503-536. DOI:10.1146/annurev.genet.38. 072902.093019 . |
| [3] | LóPEZ-OTíN C, BLASCO M A, PARTRIDGE L, et al. Hallmarks of aging: an expanding universe[J]. Cell, 2023, 186(2):243-278. DOI:10.1016/j.cell.2022.11.001 . |
| [4] | YAN C J, DUANMU X Y, ZENG L, et al. Mitochondrial DNA: distribution, mutations, and elimination[J]. Cells, 2019, 8(4):379. DOI:10.3390/cells8040379 . |
| [5] | KLIONSKY D J, ABDELMOHSEN K, ABE A, et al. Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)[J]. Autophagy, 2016, 12(1):1-222. DOI:10.1080/15548627.2015.1100356 . |
| [6] | MACK H I D, HEIMBUCHER T, MURPHY C T. The nematode Caenorhabditis elegans as a model for aging research[J]. Drug Discov Today Dis Models, 2018, 27:3-13. DOI:10.1016/j.ddmod.2018.11.001 . |
| [7] | JI T, ZHANG X L, XIN Z L, et al. Does perturbation in the mitochondrial protein folding pave the way for neurodegeneration diseases?[J]. Ageing Res Rev, 2020, 57:100997. DOI:10.1016/j.arr.2019.100997 . |
| [8] | SOHRABI S, MOR D E, KALETSKY R, et al. High-throughput behavioral screen in C. elegans reveals Parkinson's disease drug candidates[J]. Commun Biol, 2021, 4(1):203. DOI:10.1038/s42003-021-01731-z . |
| [9] | YE S W, SONG S D, LIU X J, et al. A small-molecule screen identifies novel aging modulators by targeting 5-HT/DA signaling pathway[J]. Aging Cell, 2025, 24(3): 1-13. DOI:10.1111/acel.14411 . |
| [10] | PANDA M, FAKITSA M, MARKAKI M, et al. Caenorhabditis elegans as an emerging high throughput chronotherapeutic drug screening platform for human neurodegenerative disorders[J]. Adv Drug Deliv Rev, 2025, 224:115655. DOI:10.1016/j.addr.2025.115655 . |
| [11] | YOO I, AHN I, LEE J, et al. Extracellular flux assay (Seahorse assay): Diverse applications in metabolic research across biological disciplines[J]. Mol Cells, 2024, 47(8):100095. DOI:10.1016/j.mocell.2024.100095 . |
| [12] | STIERNAGLE T. Maintenance of C. elegans [J]. WormBook, 2006:1-11. DOI:10.1895/wormbook.1.101.1 . |
| [13] | MALLICK A, RANAWADE A, VAN DEN BERG W, et al. Axin-mediated regulation of lifespan and muscle health in C. elegans requires AMPK-FOXO signaling[J]. iScience, 2020, 23(12):101843. DOI:10.1016/j.isci.2020.101843 . |
| [14] | REGMI S G, ROLLAND S G, CONRADT B. Age-dependent changes in mitochondrial morphology and volume are not predictors of lifespan[J]. Aging (Albany NY), 2014, 6(2):118-30. DOI: 10.18632/aging.100639 . |
| [15] | XIA Q, LI P L, CASAS-MARTINEZ J C, et al. Peroxiredoxin 2 regulates DAF-16/FOXO mediated mitochondrial remodelling in response to exercise that is disrupted in ageing[J]. Mol Metab, 2024, 88:102003. DOI: 10.1016/j.molmet.2024.102003 . |
| [16] | CHAUDHRY A, SHI R, LUCIANI D S. A pipeline for multidimensional confocal analysis of mitochondrial morphology, function, and dynamics in pancreatic β-cells[J]. Am J Physiol Endocrinol Metab, 2020, 318(2):E87-E101. DOI:10.1152/ajpendo.00457.2019 . |
| [17] | Mitochondria Analyzer[Z/OL]. [2025-07-16]. . |
| [18] | VALENTE A J, MADDALENA L A, ROBB E L, et al. A simple ImageJ macro tool for analyzing mitochondrial network morphology in mammalian cell culture[J]. Acta Histochem, 2017, 119(3):315-326. DOI:10.1016/j.acthis.2017.03.001 . |
| [19] | MiNA - Mitochondrial Network Analysis[Z/OL]. [2025-07-16]. . |
| [20] | NG L F, GRUBER J. Measurement of respiration rate in live Caenorhabditis elegans [J]. Bio Protoc, 2019, 9(10):1-12. DOI:10.21769/BioProtoc.3243 . |
| [21] | HAROON S, VERMULST M. Oxygen consumption measurements in Caenorhabditis elegans using the seahorse XF24[J]. Bio Protoc, 2019, 9(13):e3288. DOI:10.21769/BioProtoc.3288 . |
| [22] | SONG M J, DONG S M, ZHANG X F, et al. A moderate static magnetic field promotes C. elegans longevity through cytochrome P450s[J]. Sci Rep, 2022, 12:16108. DOI:10.1038/s41598-022-20647-0 . |
| [23] | DILLIN A, HSU A L, ARANTES-OLIVEIRA N, et al. Rates of behavior and aging specified by mitochondrial function during development[J]. Science, 2002, 298(5602):2398-2401. DOI: 10.1126/science/1077780 . |
| [24] | AMORIM J A, COPPOTELLI G, ROLO A P, et al. Mitochondrial and metabolic dysfunction in ageing and age-related diseases[J]. Nat Rev Endocrinol, 2022, 18(4):243-258. DOI:10.1038/s41574-021-00626-7 . |
| [25] | SUN N, YOULE R J, FINKEL T. The mitochondrial basis of aging[J]. Mol Cell, 2016, 61(5):654-666. DOI:10.1016/j.molcel.2016.01.028 . |
| [26] | BAR-ZIV R, BOLAS T, DILLIN A. Systemic effects of mitochondrial stress[J]. EMBO Rep, 2020, 21(6):e50094. DOI:10.15252/embr.202050094 . |
| [27] | REGMI S G, ROLLAND S G, CONRADT B. Age-dependent changes in mitochondrial morphology and volume are not predictors of lifespan[J]. Aging, 2014, 6(2):118-130. DOI:10.18632/aging.100639 . |
| [28] | SON H G, ALTINTAS O, KIM E J E, et al. Age-dependent changes and biomarkers of aging in Caenorhabditis elegans [J]. Aging Cell, 2019, 18(2):e12853. DOI:10.1111/acel.12853 . |
| [29] | MAGLIONI S, MELLO D F, SCHIAVI A, et al. Mitochondrial bioenergetic changes during development as an indicator of C. elegans health-span[J]. Aging, 2019, 11(16):6535-6554. DOI:10.18632/aging.102208 . |
| [30] | MITRA K, WUNDER C, ROYSAM B, et al. A hyperfused mitochondrial state achieved at G1–S regulates cyclin E buildup and entry into S phase[J]. Proc Natl Acad Sci U S A, 2009, 106(29):11960-11965. DOI:10.1073/pnas.0904875106 . |
| [31] | DAGDA R K, CHERRA S J, KULICH S M, et al. Loss of PINK1 function promotes mitophagy through effects on oxidative stress and mitochondrial fission[J]. J Biol Chem, 2009, 284(20):13843-13855. DOI:10.1074/jbc.M808515200 . |
/
| 〈 |
|
〉 |