News Release

Proteomics of bone formation in young-adult and old mice

“We conclude that proteomics is a promising approach to study bone biology and detect protein-specific changes in aging.”

Peer-Reviewed Publication

Impact Journals LLC

A proteomics approach to study mouse long bones: examining baseline differences and mechanical loading-induced bone formation in young-adult and old mice

image: 

Figure 1. RNA-seq and proteomics were used to characterize cortical bone from young-adult and old mice at baseline. (A) Untreated 5-month-old (young-adult) and 22-month-old (old) female C57BL/6N mice were sacrificed. Paired right and left tibial mid-diaphyses were isolated, removed of marrow, and snap frozen. From the right tibias, proteins were extracted using 4% SDS. Proteins from 5 tibias per age were analyzed by proteomics using a tandem mass tag (TMT)-11. From the left tibias, RNA was isolated using TRIzol. RNA from 7 tibias per age was sequenced. (B) MicroCT of the distal right femurs from these mice confirmed the expected age-related differences in the cortical bone. (CD) The distal cortical bone area and cortical thickness were lower with age. (E) MicroCT also confirmed age-related changes in the trabecular bone of the distal femur. (FG) The bone volume per total volume (BV/TV) and trabecular number were lower with age. (H) Proteomics and RNA-seq raw data were analyzed, and differential expression analysis was performed separately. For both methods, a Benjamini-Hochberg-adjusted p-value cutoff of 0.05 was used to identify differentially expressed genes (DEGs) and differentially expressed proteins (DEPs). Downstream analyses included correlations, overlaps, weighted gene co-expression network analysis (WGCNA), gene ontology (GO) analysis, pathway analysis, and COMPBIO analysis. (I) 93% (1773/1904) of proteomics hits (PSM≥3) were detectable by RNA-seq (non-zero CPM for all samples). (J) The abundance of the 1773 targets detected by both proteomics and RNA-seq (after PSM and CPM filtering) were correlated (Spearman). (K) Comparing young-adult and old bone at baseline, 183 proteomics targets and 2290 RNA-seq targets met the p-value cutoff to be DEPs and DEGs, respectively. Abbreviations: SDS: Sodium dodecyl sulfate; BV/TV: Bone Volume/Total Volume; DEG: Differentially Expressed Gene; DEP: Differentially Expressed Protein; CPMs: Counts per million; PSMs: Peptide spectral matches.

view more 

Credit: 2024 Chermside-Scabbo et al.

“We conclude that proteomics is a promising approach to study bone biology and detect protein-specific changes in aging.”

BUFFALO, NY- October 15, 2024 – A new research paper was published on the cover of Aging (listed by MEDLINE/PubMed as "Aging (Albany NY)" and "Aging-US" by Web of Science), Volume 16, Issue 19 on October 12, 2024, entitled, “A proteomics approach to study mouse long bones: examining baseline differences and mechanical loading-induced bone formation in young-adult and old mice.”

As noted in the abstract, bone mass declines with age, and the anabolic effects of skeletal loading decrease. While much research has focused on gene transcription, how bone ages and loses its mechanoresponsiveness at the protein level remains unclear.

In their paper, researchers Christopher J. Chermside-Scabbo, John T. Shuster, Petra Erdmann-Gilmore, Eric Tycksen, Qiang Zhang, R. Reid Townsend, and Matthew J. Silva from Washington University School of Medicine and Washington University in St. Louis, Missouri, describe how they developed a novel proteomics approach and conducted paired mass spectrometry and RNA-seq analyses on tibias from young-adult (5-month) and old (22-month) mice.

The researchers report the first correlation estimate between the bone proteome and transcriptome (Spearman ρ = 0.40). While this is consistent with findings from other tissues, it suggests that only a relatively low amount of variation in protein levels is explained by variation in transcript levels.

Of the 71 shared targets that differed with age, eight were associated with bone mineral density in previous GWAS, including the understudied targets Asrgl1 and Timp2. Using complementary RNA in situ hybridization, the researchers confirmed that Asrgl1 and Timp2 showed reduced expression in osteoblasts/osteocytes in aged bones. Additionally, they found evidence of reduced TGF-beta signaling with aging, particularly Tgfb2. The researchers also identified proteomic changes following mechanical loading, noting that at the protein level, bone differed more with age than with loading, and aged bone exhibited fewer loading-induced changes.

"Overall, our findings underscore the need for complementary protein-level assays in skeletal biology research.”

Continue reading: DOI: https://doi.org/10.18632/aging.206131

Corresponding Author: Christopher J. Chermside-Scabboa - ccherms@wustl.edu

Keywords: aging, bone, mechanical loading, proteomics, RNA-seq/transcriptomics

Click here to sign up for free Altmetric alerts about this article.

About Aging:

The journal Aging aims to promote 1) treatment of age-related diseases by slowing down aging, 2) validation of anti-aging drugs by treating age-related diseases, and 3) prevention of cancer by inhibiting aging. (Cancer and COVID-19 are age-related diseases.)

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed Central, Web of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Please visit our website at www.Aging-US.com​​ and connect with us:

Click here to subscribe to Aging publication updates.

For media inquiries, please contact media@impactjournals.com.

Aging (Aging-US) Journal Office
6666 E. Quaker St, Suite 1
Orchard Park, NY 14127
Phone: 1-800-922-0957, option 1


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.