3D mapping reveals a complex and transient interstitial matrix during murine renal development

Abstract

Background: The extracellular matrix (ECM) is a network of proteins and glycosaminoglycans that provides structural and biochemical cues to cells. In the kidney, the ECM is critical for nephrogenesis; however, the dynamics of ECM composition and how it relates to 3D structure during development is unknown. Methods: Using embryonic day (E)14.5, E18.5, postnatal day (P)3, and adult kidneys, we fractionated proteins based on differential solubilities, performed liquid chromatography tandem-mass spectrometry, and identified changes in ECM protein content (matrisome). Decellularized kidneys were stained for ECM proteins and imaged in 3D using confocal microscopy. Results: We observed an increase in interstitial ECM that connect the stromal mesenchyme to the basement membrane (TNXB, COL6A1, COL6A2, COL6A3) between the embryo and adult, and a transient elevation of interstitial matrix proteins (COL5A2, COL12A1, COL26A1, ELN, EMID1, FBN1, LTBP4, THSD4) at perinatal timepoints. Basement membrane proteins critical for metanephric induction (FRAS1, FREM2) were highest in the embryo, whereas proteins necessary for glomerular basement membrane integrity (COL4A3, COL4A4, COL4A5, LAMB2) were more abundant in the adult. 3D visualization revealed a complex interstitial matrix that dramatically changed over development, including the perinatal formation of fibrillar structures that appear to support the medullary rays. Conclusion: By correlating 3D ECM spatiotemporal organization with global protein abundance, we identified novel changes in the interstitial matrix during kidney development. This new information regarding the ECM in developing kidneys offers the potential to inform the design of regenerative scaffolds that can guide nephrogenesis in vitro.

Kidney organoids recapitulate human basement membrane assembly in health and disease

“…These included 83 BM proteins and the most abundant were those seen early (COL4A1, COL4A2, COL18A1, LAMB1, LAMC1) and later (LAMA5) in BM assembly (Figure 5-figure supplement 1C). We compared these findings to a proteomic dataset from the E18.5 mouse kidney (Lipp et al, 2021), and found considerable overlap, with a further 130 matrix protein identifications (Figure 5C), including key GBM components COL4A3, COL4A4, COL4A5 and COL4A6. We then compared the BM proteins from each organoid timepoint with E19 mouse kidneys (Figure 5D) and found the highest overlap (58.4%) between E19 and day 25 kidney organoids.…”

“…Most understanding about vertebrate BMs comes from immunolocalization and genetic knock-out studies (Abrahamson et al, 2013) and for composition, mass spectrometry (MS)-based proteomics has enabled global analysis (Naba et al, 2016;Randles et al, 2015). Proteomics also allows time course studies, which have provided insight into matrix dynamics during development and in disease progression (Hebert et al, 2020;Lipp et al, 2021;Naba et al, 2017). However, proteomics lacks the spatial context that is captured by localization studies including fluorescent tagging of endogenous proteins.…”

Kidney organoids: A system to study human basement membrane assembly in health and disease

“…These included 83 BM proteins and the most abundant were those seen early (COL4A1, COL4A2, COL18A1, LAMB1, LAMC1) and later (LAMA5) in BM assembly (Figure S5C). We compared these findings to a proteomic dataset from the E18.5 mouse kidney (Lipp et al, 2021), and found considerable overlap, with a further 130 matrix protein identifications (Figure 5C), including key GBM components COL4A3, COL4A4, COL4A5 and COL4A6. We then compared the BM proteins from each organoid timepoint with E19 mouse kidneys (Figure 5D) and found the highest overlap (58.4%) between E19 and day 25 kidney organoids.…”

“…Most understanding about vertebrate BMs comes from immunolocalization and knock-out studies (Abrahamson et al, 2013) and for composition, mass spectrometry (MS)-based proteomics has enabled global analysis (Naba et al, 2016;Randles et al, 2015). Proteomics also allows time course studies, which have provided insight into matrix dynamics during development and in disease progression (Hebert et al, 2020;Lipp et al, 2021;Naba et al, 2017). However, proteomics lacks the spatial context that is captured by localization studies including fluorescent tagging of endogenous proteins.…”

“…Pooled data are presented as median, error bars indicate the 95% confidence interval for the median. (C) Expanded fetal mouse kidney matrisome represented as a proteininteraction network (nodes represent proteins identified in this and in a previous study(Lipp et al, 2021), and connecting lines indicate protein-protein interaction). (D) Comparison of BM proteins identified in the E19 mouse fetal kidney* (MFK) and human kidney organoids(HKO)…”