A recent paper posted to bioRxiv, from Boston University and Boston Medical Center, highlights that collagen post-translational modifications can be quantified alongside matrisome proteins in archived human kidney biopsies, offering a new angle on how fibrosis becomes irreversible.

Langston, Zaia et al. focused on interstitial fibrosis and tubular atrophy (IFTA), the common final pathway to end-stage kidney disease. Using laser microdissection (LMD) of FFPE diagnostic biopsies, they compared healthy and chronically damaged tubulointerstitium from a diabetic nephropathy case with healthy tissue from a kidney transplant case. Signature tubulointerstitial proteins such as UMOD and SLC12A1 were abundant, with few glomerular proteins captured, confirming compartment-specific sampling. Collagens COL1A1 and COL6A3, along with tenascin-C, were more abundant in regions of IFTA. Hydroxyproline was the most abundant modification, followed by hydroxylysine. All confidently localized hydroxyproline sites were 4-hydroxyproline, and levels were highest in healthy transplant tissue.

PEAKS Studio 13.1 was used for protein identifications and PTM profiling with label-free quantification across all LC-MS/MS runs, using the de novo-assisted proteomic workflow. PEAKS PTM search was crucial in identifying hydroxyproline, hydroxylysine, and hydroxylysine-hexose modifications on collagen chains. Only sites with a high site localisation score, AScore, ≥ 20 (p < 0.01) were retained, allowing confident peptide-level localization despite the identical mass shift of hydroxyproline and hydroxylysine. In total, 852 protein groups, 817 unique proteins, and 6,516 peptides were identified, and 671 proteins and 2,821 peptides were quantified after reproducibility filtering. Of these, 54 hydroxyproline peptides and five hydroxylysine peptides met the confidence criteria, with COL1A2 and COL4A2 carrying the most.

By pairing protein-level and site-level PTM data from minimal archived tissue, this work lays the groundwork for identifying early molecular markers of chronic kidney disease progression and new therapeutic targets for fibrosis. BSI is proud to support research that connects spatial proteomics to the molecular drivers of kidney disease.

Read the full paper here: Langston, J.C., Candib, A., Sethi, M., Henderson, J., Zaia, J. (2026) Proteomics of highly post-translationally modified proteins in kidney tubulointerstitium. bioRxiv. doi:10.64898/2026.09.30.755814