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Integrative Profiling of Amyotrophic Lateral Sclerosis Lymphoblasts Identifies Unique Metabolic and Mitochondrial Disease Fingerprints

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Abstract

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease with a rapid progression and no effective treatment. Metabolic and mitochondrial alterations in peripheral tissues of ALS patients may present diagnostic and therapeutic interest. We aimed to identify mitochondrial fingerprints in lymphoblast from ALS patients harboring SOD1 mutations (mutSOD1) or with unidentified mutations (undSOD1), compared with age-/sex-matched controls. Three groups of lymphoblasts, from mutSOD1 or undSOD1 ALS patients and age-/sex-matched controls, were obtained from Coriell Biobank and divided into 3 age-/sex-matched cohorts. Mitochondria-associated metabolic pathways were analyzed using Seahorse MitoStress and ATP Rate assays, complemented with metabolic phenotype microarrays, metabolite levels, gene expression, and protein expression and activity. Pooled (all cohorts) and paired (intra-cohort) analyses were performed by using bioinformatic tools, and the features with higher information gain values were selected and used for principal component analysis and Naïve Bayes classification. Considering the group as a target, the features that contributed to better segregation of control, undSOD1, and mutSOD1 were found to be the protein levels of Tfam and glycolytic ATP production rate. Metabolic phenotypic profiles in lymphoblasts from ALS patients with mutSOD1 and undSOD1 revealed unique age-dependent different substrate oxidation profiles. For most parameters, different patterns of variation in experimental endpoints in lymphoblasts were found between cohorts, which may be due to the age or sex of the donor. In the present work, we investigated several metabolic and mitochondrial hallmarks in lymphoblasts from each donor, and although a high heterogeneity of results was found, we identified specific metabolic and mitochondrial fingerprints, especially protein levels of Tfam and glycolytic ATP production rate, that may have a diagnostic and therapeutic interest.

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Data Availability

The data generated and analyzed in this work are available at: https://figshare.com/projects/Integrative_Profiling_of_Amyotrophic_Lateral_Sclerosis_Lymphoblasts_Identifies_Unique_Metabolic_and_Mitochondrial_Disease_Fingerprints/133428

Abbreviations

2-DG:

2-Deoxyglucose

ΔΨm:

Mitochondrial membrane potential

Ala-Gln:

Alanine-glutamine

ALS:

Amyotrophic lateral sclerosis

BCA:

Bicinchoninic acid method

Bcl-2:

B cell lymphoma 2

BHI:

Bioenergetic health index

CNS:

Central nervous system

COX4i1:

Cytochrome c oxidase subunit IV isoform 1

CYCS:

Cytochrome c, somatic

CYCs_mRNA:

Transcripts coding for cytochrome c, somatic

DTT:

Dithiothreitol

ECAR:

Extracellular acidification rate

EDTA:

Ethylenediaminetetraacetic acid

EGTA:

Ethyleneglycol-bis (2-aminoethylether) N, N,′N, ′N-tetraacetic acid

ETC:

Mitochondrial electron transport chain

fALS:

Familial ALS

FN:

False negatives

FP:

False positives

G6PD_mRNA:

Transcripts coding for glucose-6-phosphate dehydrogenase

HRP:

Horseradish peroxidase

IMS:

Mitochondrial intermembrane space

LDH:

Lactate dehydrogenase

MAS:

Biolog mitochondrial assay solution

mutSOD1:

Mutant SOD1

NAM:

Nicotinamide

NDUFA9:

NADH:ubiquinone oxidoreductase subunit A9

OCR:

Oxygen consumption rate

OMM:

Outer mitochondrial membrane

PBMCs:

Peripheral blood mononuclear cells

PBS:

Phosphate-buffered saline

PCA:

Principal component analysis

PDHA1_mRNA:

Transcripts coding for pyruvate dehydrogenase A1

PMSF:

Phenylmethanesulfonylfluoride

sALS:

Sporadic ALS

SDS:

Sodium dodecyl sulfate

SOD1:

Cu/Zn superoxide dismutase 1

Ta:

Annealing temperature

TBS-T:

Tris-buffered saline Tween

Tfam_p:

Protein levels of Tfam

TMRM:

Tetramethylrhodamine methyl ester perchlorate

TN:

True negatives

TP:

True positives

undSOD1:

Unknown (or undetermined) SOD1 mutation

VDAC:

Voltage-dependent anion-selective channel

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Acknowledgements

We are thankful to Barry Bochner and Enrico Tatti from Biolog, Inc. for making the Omnilog device available for this study and for insightful comments on our data.

Funding

This work was financed by the European Regional Development Fund (ERDF), through the COMPETE 2020—Operational Programme for Competitiveness and Internationalization and Portuguese national funds via FCT – Fundação para a Ciência e a Tecnologia, under projects, PTDC/MED-FAR/29391/2017, POCI-01–0145-FEDER-029391, PTDC/BTM-SAL/29297/2017, POCI-01–0145-FEDER-029297, PTDC/BTM-ORG/0055/2021, DL57/2016/CP1448/CT0016 [TCO], CEECIND/00322/2017 [EF], UIDP/04539/2020, UIDB/04539/2020 and UIDB/00081/2020. DM was supported by MSc Contract Mito4ALS—PTDC/MED-FAR/29391/2017.

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Authors and Affiliations

  1. CNC-Center for Neuroscience and Cell Biology, CIBB - Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal

    Teresa Cunha-Oliveira, Marcelo Carvalho, Vilma Sardão, Elisabete Ferreiro, Débora Mena, Paulo J. Oliveira & Filomena S. G. Silva

  2. CISUC-Center for Informatics & Systems, University of Coimbra, Coimbra, Portugal

    Francisco B. Pereira

  3. Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Coimbra, Portugal

    Francisco B. Pereira

  4. CIQUP/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, Porto, Portugal

    Fernanda Borges

  5. Mitotag Lda, Biocant Park, Cantanhede, Portugal

    Filomena S. G. Silva

Authors
  1. Teresa Cunha-Oliveira
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  2. Marcelo Carvalho
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  3. Vilma Sardão
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  4. Elisabete Ferreiro
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  5. Débora Mena
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  7. Fernanda Borges
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  8. Paulo J. Oliveira
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  9. Filomena S. G. Silva
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Contributions

Filomena S.G Silva, Marcelo Carvalho, Elisabete Ferreiro and Débora Mena performed experiments. Filomena S. G. Silva, Teresa Cunha-Oliveira and Paulo J. Oliveira designed research and acquired funding. Filomena S. G. Silva, Teresa Cunha-Oliveira, Vilma Sardão and Francisco B. Pereira analyzed data. Filomena S. G. Silva, Vilma Sardão, Elisabete Ferreiro, Teresa Cunha-Oliveira and Paulo J. Oliveira wrote the paper. Fernanda Borges acquired funding and wrote the paper. Teresa Cunha-Oliveira prepared the figures. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Teresa Cunha-Oliveira or Filomena S. G. Silva.

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Highlights

• Lymphoblasts from ALS patients present altered mitochondrial function

• Metabolic profiles of ALS lymphoblasts with SOD1 mutation differ from those without characterized mutation

• ALS lymphoblasts present hypermetabolic profiles

• Tfam protein expression and glycolytic ATP production rate are promising discriminative markers

• Some metabolic differences in lymphoblasts are sex and age dependent.

Supplementary Information

Below is the link to the electronic supplementary material.

12035_2022_2980_MOESM1_ESM.pdf

Fig. S1 Pooled and paired comparisons of lymphoblasts’ substrate preference, sorted by the average preference of the pooled control samples. The values represent the average dye MC maximal reduction rates obtained in the presence of the 31 different substrates included in the MitoPlate S1 metabolic microarray (Biolog). Substrate names are color-coded for the respective metabolic pathways leading to mitochondrial dye reduction; purple - TCA cycle, red - free fatty acid oxidation, blue - cytosolic pathways and black - other pathways. Data are available at: https://doi.org/10.6084/m9.figshare.19229229 (PDF 609 KB)

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Cunha-Oliveira, T., Carvalho, M., Sardão, V. et al. Integrative Profiling of Amyotrophic Lateral Sclerosis Lymphoblasts Identifies Unique Metabolic and Mitochondrial Disease Fingerprints. Mol Neurobiol 59, 6373–6396 (2022). https://doi.org/10.1007/s12035-022-02980-7

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