Discovery proteomics in aging human skeletal muscle finds change in spliceosome, immunity, proteostasis and mitochondria

  1. Ceereena Ubaida-Mohien
  2. Alexey Lyashkov
  3. Marta Gonzalez-Freire
  4. Ravi Tharakan
  5. Michelle Shardell
  6. Ruin Moaddel
  7. Richard D Semba
  8. Chee W Chia
  9. Myriam Gorospe
  10. Ranjan Sen
  11. Luigi Ferrucci  Is a corresponding author
  1. National Institute on Aging, National Institutes of Health, United States
  2. Johns Hopkins Medical Institute, United States
6 figures

Figures

Figure 1 with 5 supplements
Classification of age-associated proteins.

(A) Effect of age on protein expression levels. The x-axis represents the size and sign of the beta coefficient of the specific protein regressed to age (adjusted for covariates) and the y-axis …

https://doi.org/10.7554/eLife.49874.003
Figure 1—source data 1

Baseline characteristics of the GESTALT skeletal muscle participants.

Participants are classified into five different age groups. Gender: M is Male, F is Female; the number of participants is indicated. Age is indicated in years as mean and standard deviation (SD ±) for each age group. Race: number of participants is shown on the left and race is shown in italics; C is Caucasian, AA is African American, and A is Asian. Body Mass Index (BMI) is expressed as mean and SD (±) for each group. p-Value is calculated by one-way ANOVA with Kruskal-Wallis test. Race is analyzed by Chi-square test. *p-Value calculated from linear regression model, gender adjusted. ± Knee Extension Isokinetic Strength (KEIS) (300/sec; Nm). †Physical activity is calculated from self-report involvement in weight circuit, vigorous exercise, brisk walking and casual walking and summed as high-intensity physical activity hours per week. This is further categorized into 0 (not active), 1 (moderately active), 2 (active), and 3 (highly active) and expressed as mean of categorical variables (0,1,2,3) ± SD.

https://doi.org/10.7554/eLife.49874.009
Figure 1—source data 2

Characteristics of participants.

https://doi.org/10.7554/eLife.49874.010
Figure 1—source data 3

Complete protein dataset of skeletal muscle proteome quantified by TMT6plex.

Sheet1: Description of the column headers and information for the sheets. Sheet2: Sample details (age, gender, race) and TMT labeling information. Sheet3: Raw data of all the proteins quantified and analyzed in this manuscript. Sheet4-Sheet15: Lists of proteins quantified for each TMT experiment from Scaffold Q+ analysis.

https://doi.org/10.7554/eLife.49874.011
Figure 1—source data 4

Complete peptide dataset of skeletal muscle proteome quantified by TMT6-plex.

Sheet 1: Description of the column headers and information for the sheets. Sheet 2: Sample details (age, gender, race) and TMT labeling information. Sheet 3: Raw data of all the proteins quantified and analyzed in this manuscript. Sheet 4-Sheet 15: Lists of peptides quantified for each TMT experiment from Scaffold Q+ analysis.

https://doi.org/10.7554/eLife.49874.012
Figure 1—source data 5

Dysregulated proteins with age.

Sheet 1. Age-associated proteins. Proteins which were significantly (p<0.05) dysregulated with age. Sheet 2. Description of the column headers for the sheet1.

https://doi.org/10.7554/eLife.49874.013
Figure 1—figure supplement 1
Quantitative analysis of the skeletal muscle proteome with healthy aging.

(A) Study design, TMT assessment, and bioinformatics platform for protein quantification and age-associated protein analysis. (B) Correlation among all TMTs after using COMBAT experimental bias …

https://doi.org/10.7554/eLife.49874.004
Figure 1—figure supplement 2
Quantitative analysis of muscle proteome.

(A) Normalized relative protein expression from all participants. Bar plot of log2 normalized protein relative expression abundance from all 58 participants. Each circle is a protein. Median levels …

https://doi.org/10.7554/eLife.49874.005
Figure 1—figure supplement 3
Muscle proteins and robustness of age association.

(A1-A5) Protein biomarkers of slow-twitch and fast-twitch fiber types and estimated muscle fiber ratios. Log2-normalized fiber expression intensity from all the 58 donors are shown for fast …

https://doi.org/10.7554/eLife.49874.006
Figure 1—figure supplement 4
Disregulation of proteins involved in genomic maintenance and cellular senesncence.

(A) Dysregulation of proteins involved in genomic maintenance. A large number of proteins involved in genetic maintenance are overrepresented at older ages. (B) Prelamin. Protein levels increase …

https://doi.org/10.7554/eLife.49874.007
Figure 1—figure supplement 5
Age-associated ribosomal biogenesis proteins.

(A) Depletion of ribosomal proteins with age. Age-associated ribosome proteins and interacting partners. Different categories of ribosome proteins are color-coded. (B) Protein-protein interaction of …

https://doi.org/10.7554/eLife.49874.008
Figure 2 with 1 supplement
Functional decline of mitochondrial proteins with age.

(A) Percent coverage within categories of skeletal muscle proteins compared to the Uniprot database. The top section shows various energetics categories, while the z axis indicates the number of …

https://doi.org/10.7554/eLife.49874.014
Figure 2—figure supplement 1
Age-associated bioenergetics pathways.

(A) Age-associated protein abundance of CYB5R3 protein. The abundance of this protein is significantly higher at older age; age groups are color-coded. (B) Respiratory Chain Complex I-V and Aging. …

https://doi.org/10.7554/eLife.49874.015
Figure 3 with 1 supplement
Implications of proteins that modulate transcription and splicing.

(A) Log2 protein abundance of age-associated transcriptional regulation proteins. Simple linear regression was shown for age (x axis) and protein (y axis) correlation, unadjusted p-values were …

https://doi.org/10.7554/eLife.49874.016
Figure 3—figure supplement 1
Spliceosomal proteins and age association.

(A) Spliceosome protein abundance and expression variation across ages. A total of 99 spliceosomal proteins are detected across all five age groups. The abundance of each protein is represented as a …

https://doi.org/10.7554/eLife.49874.017
Age-associated alternative splicing.

(A) The number of participants with detected splicing variants is substantial, with >20% of the participants showing <5% splicing variants for the detected gene. Overall, 3.7% of all identified …

https://doi.org/10.7554/eLife.49874.018
Figure 4—source data 1

Age-associated splicing events.

Sheet 1. Age-associated splicing events (6255 events). Sheet 2. Description of the column headers for the sheet1.

https://doi.org/10.7554/eLife.49874.019
Figure 4—source data 2

Age-associated positive and negative splicing events.

Sheet 1. Age-associated negative splicing events. Sheet 2. Age associated positive splicing events. Sheet 3. Description of the column headers for the sheet1 and sheet2.

https://doi.org/10.7554/eLife.49874.020
Figure 5 with 1 supplement
Age-associated proteostasis proteins.

(A) Log2 protein abundance of all 74 age-associated proteostasis proteins across all 58 donors. Rows represent proteostasis proteins and columns represents donors. The average expression of all …

https://doi.org/10.7554/eLife.49874.021
Figure 5—figure supplement 1
HSPA8 protein and its association with age.
https://doi.org/10.7554/eLife.49874.022
Age-associated immune proteins.

(A) Immune-related proteins are depicted; the x axis shows the genes that code for age-differentially regulated proteins, while the y axis shows the log2 fold expression difference associated with …

https://doi.org/10.7554/eLife.49874.023

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