Biology subjects

Bitzer, M.

Publications and source records attributed to Bitzer, M..

8 recordsLinked to original sources

bioRxiv2025

The landscape of allele-specific expression in human kidneys

Allele-specific expression (ASE), the preferential expression of one gene copy, is a key mechanism of genomic regulation. However, its role in human kidney disease remains poorly understood. In this study, we generated a high-quality, genome-wide ASE map using paired whole-genome sequencing and RNA-seq from microdissected glomerular (GLOM) and tubulointerstitial (TUBE) compartments of patients with proteinuric kidney disease. We showed that the majority of common ASE events were deterministic and sequence-mediated. We also found that diseased kidneys exhibited significantly more ASE in GLOM than TUBE, compared to controls. Unexpectedly, higher ASE in GLOM than TUBE was significantly associated with improved kidney disease outcomes in the disease cohort. Differential gene expression analysis suggested this was the result of an active, protective transcriptional response, including ribosome and ATP synthesis upregulation, rather than pathogenic dysregulation. Our work reveals glomerular ASE as a marker of adaptive transcriptional activity in proteinuric kidney disease.

genomics↗

bioRxiv2025

Cellular and Spatial Drivers of Unresolved Injury and Functional Decline in the Human Kidney

Building upon a foundational Human Kidney resource, we present a comprehensive multi-modal atlas that defines spatially resolved versus unresolved repair states and mechanisms in human kidney disease. Homeostatic interactions between injured kidney epithelium and its surrounding milieu determine successful repair outcomes, while pathogenic signaling promotes unresolved inflammation and fibrosis leading to chronic disease. We integrated multiple single-cell and spatial modalities across [~]700 samples from >350 patients ([~]250 research biopsies), analyzing [~]1.7 million cells alongside complementary mouse multi-omic profiles spanning acute-to-chronic injury and aging (>300,000 cells) and spatial transcriptomic analysis of >150 human biopsies. This cross-species atlas delineates functional pathways and druggable targets across the nephron and defines gene regulatory networks and chromatin landscapes governing tubular, fibroblast, and immune cell transitions from injury to either recovery or failed repair states. We identified distinct cellular states associated with specific pathological features that show dynamic distributions between acute kidney injury (AKI) and chronic kidney disease (CKD), organized within unique spatial niches that reveal progression mechanisms from early injury to unresolved disease. Gene regulatory analyses prioritized key transcription factor activities (SOX4, SOX9, NFKB1, REL, KLFs) and their target networks establishing disease states and tissue microenvironments. These regulatory programs were directly linked to clinical outcomes, identifying molecular signatures of recovery and secreted biomarkers predictive of AKI-to-CKD progression, providing a key resource for therapeutic development and precision medicine approaches in kidney disease.

molecular biology↗

bioRxiv2025

Systematic evaluation of single-cell multimodal data integration for comprehensive human reference atlas.

The integration of multimodal single-cell data enables comprehensive organ reference atlases, yet its impact remains largely unexplored, particularly in complex tissues. We generated a benchmarking dataset for the renal cortex by integrating 3 and 5 scRNA-seq with joint snRNA-seq and snATAC-seq, profiling 119,744 high-quality nuclei/cells from 19 donors. To align cell identities and enable consistent comparisons, we developed the interpretable machine learning tool scOMM (single-cell Omics Multimodal Mapping) and systematically assessed integration strategies. "Horizontal" integration of scRNA and snRNA-seq improved cell-type identification, while "vertical" integration of snRNA-seq and snATAC-seq had an additive effect, enhancing resolution in homogeneous populations and difficult-to-identify states. Global integration was especially effective in identifying adaptive states and rare cell types, including WFDC2-expressing Thick Ascending Limb and Norn cells, previously undetected in kidney atlases. Our work establishes a robust framework for multimodal reference atlas generation, advancing single-cell analysis and extending its applicability to diverse tissues.

genomics↗

bioRxiv2024

A Novel Role of Hyaluronan and its Membrane Receptors, CD44 and RHAMM in Obesity-Related Glomerulopathy

Obesity-related glomerulopathy (ORG) contributes to diabetic nephropathy and kidney cancer, leading to chronic/end-stage kidney disease. To date, treatments for ORG are limited because of incomplete understanding of the disease pathogenesis. Here, we identified a novel role for hyaluronan (HA) and its membrane receptors, CD44 and RHAMM in obesity-associated renal inflammation, fibrosis, tubular injury, and kidney dysfunction. Pharmacological and genetic ablation of HA, CD44 or RHAMM reversed these renal disorders induced by high fat diet feeding in mice in vivo. Increased HA content, and CD44 and RHAMM expression damaged the kidney via activation of TGF-{beta}1/Smad2/3, P38/JNK MAPK and ROCK/ERK pathways. We further established a link between renal insulin resistance and ECM remodelling using human kidney cells in vitro, shedding mechanistic insight into the role of HA, CD44 and RHAMM in the pathogenesis of ORG. Furthermore, in human kidney biopsies gene expression of CD44 and RHAMM was increased in chronic kidney disease and diabetic nephropathy, and their levels were correlated with markers of kidney (dys)function (GFR, serum creatinine, proteinuria). Our findings provide evidence for HA-CD44/RHAMM as a potential therapeutic target in ORG and consequent prevention of chronic kidney disease.

physiology↗

bioRxiv2023

Maintained imbalance of triglycerides, apolipoproteins, energy metabolites and cytokines in long-term COVID-19 syndrome (LTCS) patients

Deep metabolomic, proteomic and immunologic phenotyping of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients have matched a wide diversity of clinical symptoms with potential biomarkers for coronavirus disease 2019 (COVID-19). Within here, several studies described the role of metabolites, lipoproteins and inflammation markers during infection and in recovered patients. In fact, after SARS-CoV-2 viral infection almost 20-30% of patients experience persistent symptoms even after 12 weeks of recovery which has been defined as long-term COVID-19 syndrome (LTCS). Emerging evidence revealed that a dysregulated immune system and persisting inflammation could be one of the key drivers of LTCS. However, how these small biomolecules such as metabolites, lipoprotein, cytokines and chemokines altogether govern pathophysiology is largely underexplored. Thus, a clear understanding how these parameters into an integrated fashion could predict the disease course may help to stratify LTCS patients from acute COVID-19 or recovered specimen and would help to elucidate a potential mechanistic role of these biomolecules during the disease course. Here, we report an integrated analysis of blood serum and plasma by in vitro diagnostics research NMR spectroscopy and flow cytometry-based cytokine quantification in a total of 125 individuals (healthy controls (HC; n=73), recovered (n=12), acute (n=7) and LTCS (n=33)). We identified that in LTCS patients lactate and pyruvate were significantly different from either healthy controls or acute COVID-19 patients. Further correlational analysis of cytokines and metabolites indicated that creatine, glutamine, and high-density lipoprotein (HDL) phospholipids were distributed differentially amongst patients or individuals. Of note, triglycerides and several lipoproteins (apolipoproteins Apo-A1 and A2) in LTCS patients demonstrate COVID-19-like alterations compared to HC. Interestingly, LTCS and acute COVID-19 samples were distinguished mostly by their creatinine, phenylalanine, succinate, 3-hydroxybutyrate (3-HB) and glucose concentrations, illustrating an imbalanced energy metabolism. Most of the cytokines and chemokines were present at low levels in LTCS patients compared with HC except IL-18 chemokine, which tended to be higher in LTCS patients and correlated positively with several amino acids (creatine, histidine, leucine, and valine), metabolites (lactate and 3-HB) and lipoproteins. The identification of these persisting plasma metabolites, lipoprotein and inflammation alterations will help to better stratify LTCS patients from other diseases and could help to predict ongoing severity of LTCS patients. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/523998v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@ecdeacorg.highwire.dtl.DTLVardef@10f0f80org.highwire.dtl.DTLVardef@1c2ddaborg.highwire.dtl.DTLVardef@672120_HPS_FORMAT_FIGEXP M_FIG C_FIG Layman summary & significance of the researchAlmost 20-30% of individuals infected with the SARS-CoV-2 virus regardless of hospitalization status experience long-term COVID-19 syndrome (LTCS). It is devasting for millions of individuals worldwide and hardly anything is known about why some people experience these symptoms even after 3 to 12 months after the acute phase. In this, we attempted to understand whether dysregulated metabolism and inflammation could be contributing factors to the ongoing symptoms in LTCS patients. Total blood triglycerides and the Cory cycle metabolites (lactate and pyruvate) were significantly higher, lipoproteins (Apo-A1 and A2) were drastically lower in LTCS patients compared to healthy controls. Correlation analysis revealed that either age or gender are positively correlated with several metabolites (citrate, glutamate, 3-hydroxybutyrate, glucose) and lipoproteins (Apo-A1, HDL Apo-A1, LDL triglycerides) in LTCS patients. Several cytokines and chemokines were also positively correlated with metabolites and lipoproteins thus, dysregulation in metabolism and inflammation could be a potential contributory factor for LTCS symptoms.

immunology↗

bioRxiv2021

Upregulated PD-1 Signaling is an Important Antagonist to Glomerular Health in Aged Kidneys

Kidney aging and its contribution to disease and its underlying mechanisms are not well understood. With an aging population, kidney health becomes an important medical and socioeconomic factor. We previously showed that podocytes isolated from aged mice exhibit increased expression of Programed Cell Death Protein 1 (PD-1) surface receptor and its two ligands (PD-L1, PD-L2). PDCD1 transcript increases with age in micro-dissected human glomeruli, which correlates with lower eGFR, and higher segmental glomerulosclerosis and vascular arterial intima to lumen ratio. In vitro studies in podocytes demonstrate a critical role for PD-1 signaling in cell survival and induction of a Senescence-Associated Secretory Phenotype (SASP). To prove PD-1 signaling is critical to podocyte aging, aged mice were injected with anti-PD-1 antibody (aPD-1ab). Treatment significantly improved the aging phenotype in both kidney and liver. In the glomerulus, it increased the life-span of podocytes, but not parietal epithelial, mesangial or endothelial cells. Transcriptomic and immunohistochemistry studies demonstrate that anti-PD-1 treatment improved the health-span of podocytes. It restored the expression of canonical podocyte genes, transcription factors and gene regulatory networks, increased cellular metabolism signatures and lessened SASPs. These results suggest a critical contribution for increased PD-1 signaling towards both kidney and liver aging.

cell biology↗

bioRxiv2021

Micro-dissection and integration of long and short reads to create a robust catalog of kidney compartment-specific isoforms

Studying isoform expression at the microscopic level has always been a challenging task. A classical example is kidney, where glomerular and tubulo-insterstitial compartments carry out drastically different physiological functions and thus presumably their isoform expression also differs. We aim at developing an experimental and computational pipeline for identifying isoforms at microscopic structure-level. We microdissed glomerular and tubulo-interstitial compartments from healthy human kidney tissues from two cohorts. The two compartments were separately sequenced with the PacBio RS II platform. These transcripts were then validated using transcripts of the same samples by the traditional Illumina RNA-Seq protocol, distinct Illumina RNA-Seq short reads from European Renal cDNA Bank (ERCB) samples, and annotated GENCODE transcript list, thus identifying novel transcripts. We identified 14,739 and 14,259 annotated transcripts, and 17,268 and 13,118 potentially novel transcripts in the glomerular and tubulo-interstitial compartments, respectively. Of note, relying solely on either short or long reads would have resulted in many erroneous identifications. We identified distinct pathways involved in glomerular and tubulointerstitial compartments at the isoform level.We demonstrated the possibility of micro-dissecting a tissue, incorporating both long- and short-read sequencing to identify isoforms for each compartment.

bioinformatics↗

bioRxiv2019

Efficient data management infrastructure for the integration of imaging and omics data in life science research

As technical developments in omics and biomedical imaging drive the increase in quality, modality, and throughput of data generation in life sciences, the need for information systems capable of integrative, long-term storage and management of these heterogeneous digital assets is also increasing. Here, we propose an approach based on principles of Service Oriented Architecture design, to allow the integrated management and analysis of multi-omics and biomedical imaging data. The proposed architecture introduces an interoperable image management system, the OMERO server, into the backend of qPortal, a FAIR-compliant web-based platform for omics data management. The implementation of an integrated metadata model, the development of software components to enable the communication with the OMERO server, and an extension to the data management operations of established software, allows for FAIR management of heterogeneous omics and biomedical imaging data within an integrated system, which facilitates metadata queries from web-based scientific applications. The applicability of the proposed architecture is demonstrated in two prototypical use cases, a plant biology study using confocal scanning microscopy, and a clinical study on hepatocellular carcinoma, with data from a variety of medical imaging and omics modalities. We anticipate that FAIR data management systems for multi-modal data repositories will play a pivotal role in data-driven research, as the joint analysis of omics and imaging data becomes not only desirable but necessary to derive novel insights into biological processes. In particular for powerful machine learning applications where the availability of large datasets with high quality phenotypic annotations is a requirement.

bioinformatics↗