Procedures of Mitochondria Purification and Gene Expression to Study Alternative Respiratory and Uncoupling Pathways in Fruits

  • Jurandi Gonçalves de OliveiraEmail author
  • Luis Miguel Mazorra Morales
  • Gláucia Michelle Cosme Silva
  • Kátia Daniella da Cruz Saraiva
  • Diederson Bortolino Santana
  • Clesivan Pereira dos Santos
  • Marcos Goes Oliveira
  • José Hélio Costa
Part of the Methods in Molecular Biology book series (MIMB, volume 1670)


We describe detailed procedures to get intact and well-coupled mitochondria from a variety of fruit species such as papaya (Carica papaya), guava (Psidium guajava), tomato (Solanum lycopersicum), and strawberry (Fragaria x ananassa) as well as the protocols to assess the capacities of AOX and UCP pathways in intact fruit mitochondria. The procedures presented here were tested for the species mentioned above; their use with other types of fruits must be tested for yield of intact and active mitochondria. This is possible from individual adjustments. Strict care during extraction, including the use of osmotic protectants (i.e., mannitol/sucrose) and antioxidants (i.e., cysteine, ascorbate) at defined concentrations, are critical factors to ensure mitochondrial integrity and to obtain higher yields. The mitochondria purified using the discontinuous Percoll gradients described here can be used for the analysis of the capacity of alternative respiration and uncoupling pathways in fruits. In addition, protocols for quantitative and semiquantitative PCR applicable for the analysis of AOX and UCP gene expression in fruits are shown. Microarray and RNA-seq data from public databases are also valuable for the analysis of AOX and UCP genes. In both cases having the sequences of genes or cDNAs to be used in primer design or probe identification is necessary.

Key words

Gene identification Mitochondria isolation Respiratory control ratio RNA extraction Semiquantitative RT-PCR 


  1. 1.
    Oliveira MG, Mazorra LM, Souza AF et al (2015) Involvement of AOX and UCP pathways in the post-harvest ripening of papaya fruits. J Plant Physiol 189:42–50CrossRefPubMedGoogle Scholar
  2. 2.
    Considine MJ, Goodman M, Echtay KS et al (2003) Superoxide stimulates a proton leak in potato mitochondria that is related to the activity of uncoupling protein. J Biol Chem 278:22298–22302CrossRefPubMedGoogle Scholar
  3. 3.
    Bradford MM (1976) Microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72:248–259CrossRefPubMedGoogle Scholar
  4. 4.
    Altschul SF, Madden TL, Schäffer AA et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Costa JH, McDonald AE, Arnholdt-Schmitt B et al (2014) A classification scheme for alternative oxidases reveals the taxonomic distribution and evolutionary history of the enzyme in angiosperms. Mitochondrion 19:172–183CrossRefPubMedGoogle Scholar
  6. 6.
    Marshall OJ (2004) Perlprimer: cross-platform, graphical primer design for standard, bisulphite and real-time PCR. Bioinformatics 20:2471–2472CrossRefPubMedGoogle Scholar
  7. 7.
    Costa JH, Mota EF, Cambursano MV et al (2010) Stress-induced co-expression of two alternative oxidase (VuAox1 and 2b) genes in Vigna unguiculata. J Plant Physiol 167:561–570CrossRefPubMedGoogle Scholar
  8. 8.
    Cavalcanti JH, Oliveira GM, Saraiva KD et al (2013) Identification of duplicated and stress-inducible Aox2b gene co-expressed with Aox1 in species of the Medicago genus reveals a regulation linked to gene rearrangement in leguminous genomes. J Plant Physiol 170:1609–1619CrossRefPubMedGoogle Scholar
  9. 9.
    Livak KJ, Schmitten TD (2001) Analysis of gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 25:402–408CrossRefPubMedGoogle Scholar
  10. 10.
    Hellemans J, Mortier G, De Paepe A et al (2007) qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol 8:R19CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Saraiva KDC, Fernandes de Melo D, Morais VD et al (2014) Selection of suitable soybean EF1a genes as internal controls for real-time PCR analyses of tissues during plant development and under stress conditions. Plant Cell Rep 33:1453–1465CrossRefPubMedGoogle Scholar
  12. 12.
    Saraiva KDC, Oliveira AER, dos Santos CP et al (2016) Phylogenetic analysis and differential expression of EF1α genesin soybean during development, stress and phytohormone treatments. Mol Gen Genomics 291(4):1505–1522. doi: 10.1007/s00438-016-1198-8 CrossRefGoogle Scholar
  13. 13.
    Navarro E, Serrano-Heras G, Castaño MJ et al (2015) Real-time PCR detection chemistry. Clin Chim Acta 439:231–250CrossRefPubMedGoogle Scholar
  14. 14.
    Rutledge RG, Stewart D (2008) Critical evaluation of methods used to determine amplification efficiency refutes the exponential character of real-time PCR. BMC Mol Biol 9:96CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Vandesompele J, De Preter K, Pattyn F et al (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3:1–11CrossRefGoogle Scholar
  16. 16.
    Verk MCV, Hichman R, Pieterse CMJ et al (2013) RNA-Seq: revelation of the messengers. Trends Plant Sci 18:175–179CrossRefPubMedGoogle Scholar
  17. 17.
    Schena M, Shalon D, Davis RW et al (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarrays. Science 270:467–470CrossRefPubMedGoogle Scholar
  18. 18.
    Nagalakshmi U, Wang Z, Waern K et al (2008) The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320:1344–1349CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Mortazavi A, Williams BA, Mccue K et al (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5:621–628CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  • Jurandi Gonçalves de Oliveira
    • 1
    Email author
  • Luis Miguel Mazorra Morales
    • 1
  • Gláucia Michelle Cosme Silva
    • 1
  • Kátia Daniella da Cruz Saraiva
    • 2
  • Diederson Bortolino Santana
    • 1
  • Clesivan Pereira dos Santos
    • 2
  • Marcos Goes Oliveira
    • 3
  • José Hélio Costa
    • 2
  1. 1.Universidade Estadual do Norte Fluminense Darcy RibeiroCampos dos GoytacazesBrazil
  2. 2.Functional Genomics and Bioinformatics, Department of Biochemistry and Molecular BiologyFederal University of CearaFortalezaBrazil
  3. 3.Universidade Federal do Espirito SantoSão MateusBrazil

Personalised recommendations