Injury-induced FoxM1 expression in mouse kidney drives epithelial proliferation by a Cyclin F dependent mechanism.

Acute kidney injury strongly upregulates the transcription factor Foxm1 in proximal tubule in vivo and Foxm1 drives epithelial proliferation in vitro. Here we report that deletion of Foxm1 either with a nephron specific Cre driver or by inducible global deletion reduces proximal tubule proliferation after ischemic injury in vivo. Foxm1 deletion led to increased AKI-to-CKD transition with enhanced fibrosis and ongoing tubule injury 6 weeks after injury. We report extracellular signal-regulated kinase (ERK) mediates FOXM1 induction downstream of the epidermal growth factor receptor (EGFR) in primary proximal tubule cells. We defined FOXM1 genomic binding sites by Cleavage Under Targets & Release Using Nuclease (CUT&RUN) and compared the genes located near FOXM1 binding sites with genes downregulated in primary proximal tubule cells after FOXM1 knockdown. The aligned datasets revealed the cell cycle regulator cyclin F (CCNF) as a putative FOXM1 target. We identify two cis regulatory elements that bind FOXM1 and regulate CCNF expression, demonstrate that Ccnf is strongly induced after kidney injury and that Foxm1 deletion abrogates Ccnf expression in vivo and in vitro. Knockdown of CCNF also reduced proximal tubule proliferation in vitro. These studies identify an ERK-FOXM1-CCNF signaling pathway that regulates injury-induced proximal tubule cell proliferation.

Sequencing of Physically Interacting Cells in Human Kidney Allograft Rejection to Infer Contact-dependent Immune Cell Transcription.

BACKGROUND: Rejection requires cell-cell contact involving immune cells. Inferring the transcriptional programs of cell-cell interactions from single-cell RNA-sequencing (scRNA-seq) data is challenging as spatial information is lost. METHODS: We combined a CD45 pos enrichment strategy with Cellular Indexing of Transcriptomes and Epitopes by sequencing based quantification of leukocyte surface proteins to analyze cell-cell interactions in 11 human kidney transplant biopsies encompassing a spectrum of rejection diagnoses. scRNA-seq was performed using the 10X Genomics platform. We applied the sequencing physically interacting cells computational method to deconvolute the transcriptional profiles of heterotypic physically interacting cells. RESULTS: The 11 human allograft biopsies generated 31 203 high-quality single-cell libraries. Clustering was further refined by combining Cellular Indexing of Transcriptomes and Epitopes by sequencing data from 6 different leukocyte-specific surface proteins. Three of 6 doublet clusters were identified as physically interacting cell complexes; macrophages or dendritic cells bound to B cells or plasma cells; natural killer (NK) or T cells bound to macrophages or dendritic cells and NK or T cells bound to endothelial cells. Myeloid-lymphocyte physically interacting cell complexes expressed activated and proinflammatory genes. Lymphocytes physically interacting with endothelial cells were enriched for NK and CD4 T cells. NK cell-endothelial cell contact caused increased expression of endothelial proinflammatory genes CXCL9 and CXCL10 and NK cell proinflammatory genes CCL3 , CCL4 , and GNLY . CONCLUSIONS: The transcriptional profiles of physically interacting cells from human kidney transplant biopsies can be inferred from scRNA-seq data using the sequencing physically interacting cells method. This approach complements previous methods that estimate cell-cell physical contact from scRNA-seq data.