Biology subjects

Kramer, D.

Publications and source records attributed to Kramer, D..

12 recordsLinked to original sources

bioRxiv2026

Histone Variant H2A.J Links Epigenetic Reprogramming to Mitochondrial-dependent Kidney Regeneration under Radiation Stress

The histone variant H2A.J is implicated in radiation-induced senescence by promoting the transcription of inflammatory genes. While H2A.J expression increases in renal tubular epithelial cells (TECs) following ionizing radiation (IR), its functional role remains poorly understood. To investigate this, constitutive H2A.J knock-out (KO) mice and wild-type (WT) controls were subjected to CT-guided IR (fractionated whole-body or localized kidney IR). Kidneys were analyzed at acute, intermediate, and chronic stages using immunofluorescence, histochemistry, automated image analysis, and electron microscopy. In WT TECs, IR induced rapid chromatin incorporation and C-terminal serine phosphorylation of H2A.J. Conversely, KO kidneys exhibited significantly more severe histopathological damage, including tubular dilation, flattened epithelium, associated with increased apoptosis, and premature senescence, characterized by persistent DNA damage with lamin B1 loss. Notably, KO TECs displayed disrupted mitochondrial networks and reduced brush borders even at baseline, which were further exacerbated by IR. Unlike WT controls, KO kidneys developed progressive tubular atrophy and incipient fibrosis, indicating a failure in regenerative capacity. Our findings suggest that H2A.J loss impairs tubular regeneration due to defective mitochondrial activation, resulting in insufficient energy supply for coordinated repair. Collectively, these results identify H2A.J as a critical stress-adaptive histone variant essential for the epigenetic regulation of tissue repair following radiation-induced damage. One Sentence SummaryIn irradiated kidney, the loss of histone variant H2A.J impairs the chromatin-mediated adaptation of mitochondrial function in tubular epithelial cells, thereby exacerbating cellular stress - characterized by increased induction of apoptosis and senescence - and ultimately leading to tubular atrophy. Translational RelevanceAcute and chronic kidney injury are frequent complications of genotoxic cancer therapies. Chemo- and radiotherapy induce DNA lesions that trigger cell death and senescence, often leading to irreversible renal damage. However, renal regeneration can occur through the dedifferentiation, proliferation, and redifferentiation of surviving tubular epithelial cells (TECs). This repair process is governed by epigenetic mechanisms that regulate the DNA damage response (DDR) and adapt gene expression programs. Following ionizing radiation (IR), epigenetic remodeling involves the incorporation of histone variants that modulate chromatin accessibility for stress-responsive transcription factors. We identify the histone variant H2A.J as a constitutive component of renal TECs, significantly upregulated after exposure to ionizing radiation (IR). Using H2A.J knock-out (KO) mice, we demonstrate that its absence disrupts acute damage responses and prevents coordinated repair, severely impairing regeneration. Mechanistically, H2A.J deficiency compromises mitochondrial function under postirradiation metabolic stress, driving the transition from acute injury to chronic kidney disease via persistent inflammation and maladaptive tubulointerstitial repair. Targeting these epigenetic drivers offers a promising strategy for regenerating damaged kidney tissue in oncology.

molecular biology↗

bioRxiv2026

Treg-derived IκBζ promotes their conversion into Th2-like effectors and drives type 2 inflammation via BATF

Regulatory T cells (Treg cells) maintain peripheral immune tolerance but display considerable plasticity in peripheral tissues. The molecular mechanisms governing their function and plasticity, particularly under inflammatory conditions, remain poorly defined. Here, we identify the NF-{kappa}B-associated transcriptional cofactor I{kappa}B{zeta} as a critical regulator of Treg cell plasticity and function. Enforced expression of I{kappa}B{zeta} in Treg cells triggered the excessive expansion of functionally impaired Treg cells, resulting in lymphadenopathy, splenomegaly, and systemic type 2 inflammation, most prominently in the lung. Mechanistically, I{kappa}B{zeta} modified BATF expression and function, thereby driving the cell-intrinsic production of Th2-associated cytokines by Treg cells. Conversely, Treg-specific deletion of I{kappa}B{zeta} constrained IL-33-mediated expansion of tissue Treg cells and surprisingly attenuated type 2 inflammation. Thus, I{kappa}B{zeta} functions as a molecular switch that reprograms regulatory T cells into Th2-like Treg cells, thereby perturbing peripheral immune tolerance. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/707402v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1ef0b17org.highwire.dtl.DTLVardef@c12eaaorg.highwire.dtl.DTLVardef@decc86org.highwire.dtl.DTLVardef@1458767_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

3D multi-omic mapping of whole nondiseased human fallopian tubes at cellular resolution reveals a large incidence of ovarian cancer precursors

Uncovering the spatial and molecular landscape of precancerous lesions is essential for developing meaningful cancer prevention and early detection strategies. High-Grade Serous Carcinoma (HGSC), the most lethal gynecologic malignancy, often originates from Serous Tubal Intraepithelial Carcinomas (STICs) in the fallopian tubes, yet their minute size and our historical reliance on standard 2D histology contribute to their underreporting. Here, we present a spatially resolved, multi-omics framework that integrates whole-organ 3D imaging at cellular resolution with targeted proteomic, metabolomic, and transcriptomic profiling to detect and characterize microscopic tubal lesions. Using this platform, we identified a total of 99 STICs and their presumed precursors that harbor TP53 mutations in morphologically unremarkable tubal epithelium in all five specimens obtained from cancer-free organ donors with average-risk of developing ovarian cancer. Although these lesions comprised only 0.2% of the epithelial compartment, they displayed geographic diversity, immune exclusion, metabolic rewiring, and DNA copy number changes among lesions and normal fallopian tube epithelium discovered alterations in STIC-associated genes and the pathways they control. In sum, this platform provides a comprehensive 3D atlas of early neoplastic transformation, yielding mechanistic insights into tumor initiation and informing clinical screening strategies for detecting cancer precursors in whole organs at cellular resolution.

bioinformatics↗

bioRxiv2025

PIVOT: an open-source tool for multi-omic spatial data registration

Advances in spatial profiling have resulted in the generation of multi-omic atlases that span biological scales. In general, multiple workflows are required for image registration, coordinate registration, and spot deconvolution to integrate modalities. To improve the throughput of registration of multi-omic cohorts, we introduce PIVOT, a user-friendly and open-source interface for streamlined nonlinear registration. We demonstrate PIVOTs strengths through registration of three multi-omic datasets, and show comparison of its performance to existing workflows.

bioinformatics↗

bioRxiv2025

Integration of nuclear morphology and 3D imaging to profile cellular neighborhoods

Nuclear morphology is an indicator of cellular function and disease states, as changes in nuclear size, shape, and texture often reflect underlying disease-related genetic, epigenetic, and microenvironmental alterations. For disease diagnosis, nuclear segmentation performed in 2D hematoxylin and eosin (H&E)-stained tissue sections has long represented the gold standard. However, recent advances in three-dimensional (3D) histology, which provide a more biologically accurate representation of the spatial heterogeneity of human microanatomy, has led to improved understandings of disease pathology. Yet challenges remain in the development of scalable and computationally efficient pipelines for extracting and interpreting nuclear features in 3D space. 2D histology neglects crucial spatial information, such as 3D connectivity, morphology, and rare events missed by sparser sampling. Here, through extension of the CODA platform, we integrate 3D imaging with nuclear segmentation to analyze nuclear morphological features in human tissue. Analysis of 3D tissue microenvironments uncovered critical changes in 3D morphometric heterogeneity. Additionally, it enables the spatial characterization of immune cell distribution in relation to tissue structures, such as variations in leukocyte density near pancreatic ducts and blood vessels of different sizes. This approach provides a more comprehensive understanding of tissue and nuclear structures, revealing spatial patterns and interactions that are critical for disease progression.

bioinformatics↗

bioRxiv2024

Constitutive expression of IκBζ promotes tumor growth and immunotherapy resistance in melanoma

BackgroundI{kappa}B{zeta}, a rather unknown co-regulator of NF-{kappa}B, is mostly inducibly expressed and can either activate or repress a specific subset of NF-{kappa}B target genes. While its role as a transcriptional regulator of various cytokines and chemokines in immune cells has been revealed, I{kappa}B{zeta}s function in solid cancer remains unclear. MethodsWe investigated I{kappa}B{zeta} expression in melanoma, and assessed its impact on target gene expression, tumor growth, and response to immunotherapy in melanoma cell lines, mouse models, and patient samples. ResultsUnlike in other cell types, I{kappa}B{zeta} protein was found to be constitutively expressed in a subfraction of melanoma cell lines, and around 35% of melanoma cases. This atypical expression pattern of I{kappa}B{zeta} did not correlate with its mRNA levels or known driver mutations, but instead seemed to result from changes in its post-transcriptional or post-translational regulation. Deleting constitutively expressed I{kappa}B{zeta} abrogated the activity and chromatin association of STAT3 and p65, leading to reduced expression of the pro-proliferative cytokines IL-1{beta} and IL-6 in melanoma cells. Consequently, loss of tumor-derived I{kappa}B{zeta} suppressed self-sustained melanoma cell growth both in vitro and in vivo. Additionally, constitutive I{kappa}B{zeta} expression suppressed the induction of the chemokines CXCL9, CXCL10, and CCL5, which impaired the recruitment of NK and CD8+ T-cells to the tumor, causing resistance to -PD-1 immunotherapy in mice. Furthermore, the expression of tumor-derived I{kappa}B{zeta} also correlated with the absence of CD8+ T-cells in human melanoma samples and progressive disease during immunotherapy. ConclusionWe propose that tumor-derived I{kappa}B{zeta} could serve as a new therapeutic target and prognostic marker that characterizes melanoma with high tumor cell proliferation, cytotoxic T- and NK-cell exclusion, and unfavorable immunotherapy responses. Targeting I{kappa}B{zeta} expression might open up a new therapy option to re-establish the recruitment of cytotoxic cells, thereby resensitizing for immunotherapy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/613946v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@76389aorg.highwire.dtl.DTLVardef@17e3f1eorg.highwire.dtl.DTLVardef@161d491org.highwire.dtl.DTLVardef@1ca9f2d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

Precision-engineered biomimetics: the human fallopian tube

The fallopian tube has an essential role in several physiological and pathological processes from pregnancy to ovarian cancer. However, there are no biologically relevant models to study its pathophysiology. The state-of-the-art organoid model has been compared to two-dimensional tissue sections and molecularly assessed providing only cursory analyses of the models accuracy. We developed a novel multi-compartment organoid model of the human fallopian tube that was meticulously tuned to reflect the compartmentalization and heterogeneity of the tissues composition. We validated this organoids molecular expression patterns, cilia-driven transport function, and structural accuracy through a highly iterative platform wherein organoids are compared to a three-dimensional, single-cell resolution reference map of a healthy, transplantation-quality human fallopian tube. This organoid model was precision-engineered to match the human microanatomy. One sentence summaryTunable organoid modeling and CODA architectural quantification in tandem help design a tissue-validated organoid model.

bioengineering↗

bioRxiv2021

Selection-Enriched Genomic Loci (SEGL) Reveals Genetic Loci for Environmental Adaptation and Photosynthetic Productivity in Chlamydomonas reinhardtii.

This work demonstrates an approach to produce and select hybrid algal strains exhibiting increased photosynthetic productivity under multiple environmental conditions. This simultaneously addresses two major impediments to improving algal bioenergy production: 1) generating new genetic variants with improved performance; and 2) disentangling complex interactions between genetic and physiological factors contributing to these improvements. We pooled progeny generated from mating two environmental isolates of the green alga Chlamydomonas reinhardtii and cultured the pools under multiple environmental conditions. Strains from the outcompeting populations showed substantial (in some cases over 3 fold) increases in productivity over the parental lines under certain environments related to biomass production, including laboratory conditions as well as hyperoxia, fluctuating light, high salinity and high temperature. The results indicate that C. reinhardtii has remarkable, untapped, directed evolution capacity that may be harnessed using breeding and competition approaches. The populations were deep sequenced at multiple time points to identify "Selection-Enriched Genomic Loci" (SEGL) that accumulated in the populations, and thus likely confer increased fitness under the respective environmental conditions. With improved resolution, SEGL mapping can identify allelic combinations used for targeted breeding approaches, generating elite algal lines with multiple desirable traits, as well as to further understand the genetic and mechanistic bases of photosynthetic productivity. Significance StatementIncreasing the photosynthetic efficiency of algae during biomass production is perhaps the most critical hurdle for economically sustainable algal based biofuels. This presents unique challenges because modifications designed to increase photosynthesis often result in decreased fitness, due to production of toxic reactive oxygen species when photosynthesis is not adequately regulated. These problems are exacerbated under natural and outdoor production environments because of the complex nature of photosynthesis and the multifaceted interactions between genetic, environmental and physiological factors. Here, we demonstrate a high throughput biotechnological screening approach that simultaneously produces algal strains with highly increased autotrophic productivity and identifies genomic loci contributing to these improvements. Our results demonstrate that Chlamydomonas reinhardtii exhibits high directed evolutionary capacity readily accessed through breeding and selection.

evolutionary biology↗

bioRxiv2020

Dynamic Loading of Human Engineered Heart Tissue Enhances Contractile Function and Drives Desmosome-linked Disease Phenotype

The role mechanical forces play in shaping the structure and function of the heart is critical to understanding heart formation and the etiology of disease but is challenging to study in patients. Engineered heart tissues (EHTs) incorporating human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes have the potential to provide insight into these adaptive and maladaptive changes in the heart. However, most EHT systems are unable to model both preload (stretch during chamber filling) and afterload (pressure the heart must work against to eject blood). Here, we have developed a new dynamic EHT (dyn-EHT) model that enables us to tune preload and have unconstrained fractional shortening of >10%. To do this, 3D EHTs are integrated with an elastic polydimethylsiloxane (PDMS) strip that provides mechanical pre- and afterload to the tissue in addition to enabling contractile force measurements based on strip bending. Our results demonstrate in wild-type EHTs that dynamic loading is beneficial based on the magnitude of the forces, leading to improved alignment, conduction velocity, and contractility. For disease modeling, we use hiPSC-derived cardiomyocytes from a patient with arrhythmogenic cardiomyopathy (ACM) due to mutations in desmoplakin. We demonstrate that manifestation of this desmosome-linked disease state requires the dyn-EHT conditioning and that it cannot be induced using 2D or standard 3D EHT approaches. Thus, dynamic loading strategy is necessary to provoke a disease phenotype (diastolic lengthening, reduction of desmosome counts, and reduced contractility), which are akin to primary endpoints of clinical disease, such as chamber thinning and reduced cardiac output. Single Sentence SummaryDevelopment of a dynamic mechanical loading platform to improve contractile function of engineered heart tissues and study cardiac disease progression.

bioengineering↗

bioRxiv2019

Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces

We present a new deep multi-state Dynamic Recurrent Neural Network (DRNN) architecture for Brain Machine Interface (BMI) applications. Our DRNN is used to predict Cartesian representation of a computer cursor movement kinematics from open-loop neural data recorded from the posterior parietal cortex (PPC) of a human subject in a BMI system. We design the algorithm to achieve a reasonable trade-off between performance and robustness, and we constrain memory usage in favor of future hardware implementation. We feed the predictions of the network back to the input to improve prediction performance and robustness. We apply a scheduled sampling approach to the model in order to solve a statistical distribution mismatch between the ground truth and predictions. Additionally, we configure a small DRNN to operate with a short history of input, reducing the required buffering of input data and number of memory accesses. This configuration lowers the expected power consumption in a neural network accelerator. Operating on wavelet-based neural features, we show that the average performance of DRNN surpasses other state-of-the-art methods in the literature on both single- and multi-day data recorded over 43 days. Results show that multi-state DRNN has the potential to model the nonlinear relationships between the neural data and kinematics for robust BMIs.

neuroscience↗

bioRxiv2018

Identifying Emerging Phenomenon in Plant Long Temporal Phenotyping Experiments

The rapid improvement of phenotyping capability, accuracy, and throughput have greatly increased the volume and diversity of phenomics data. A remaining challenge is an efficient way to identify phenotypic patterns to improve our understanding of the quantitative variation of complex phenotypes, and to attribute gene functions. To address this challenge, we developed a new algorithm to identify emerging phenomena from large-scale temporal plant phenotyping experiments. An emerging phenomenon is defined as a group of genotypes who exhibit a coherent phenotype pattern during a relatively short time. Emerging phenomena are highly transient and diverse, and are dependent in complex ways on both environmental conditions and development. Identifying emerging phenomena may help biologists to examine potential relationships among phenotypes and genotypes in a genetically diverse population and to associate such relationships with the change of environments or development. We present an emerging phenomenon identification tool called Temporal Emerging Phenomenon Finder (TEP-Finder). Using large-scale longitudinal phenomics data as input, TEP-Finder first encodes the complicated phenotypic patterns into a dynamic phenotype network. Then, emerging phenomena in different temporal scales are identified from dynamic phenotype network using a maximal clique based approach. Meanwhile, a directed acyclic network of emerging phenomena is composed to model the relationships among the emerging phenomena. The experiment that compares TEP-Finder with two state-of-art algorithms shows that the emerging phenomena identified by TEP-Finder are more functionally specific, robust, and biologically significant. The source code, manual, and sample data of TEP-Finder are all available at: http://phenomics.uky.edu/TEP-Finder/.

bioinformatics↗

bioRxiv2018

IDH1R132H acts as a tumor suppressor in glioma via epigenetic upregulation of the DNA damage response

One sentence summaryMutant IDH1 acts as a tumor suppressor when co-expressed together with TP53 and ATRX inactivating mutations in glioma, inducing genomic stability, DNA repair and resistance to genotoxic therapies.\n\nAbstractGlioma patients whose tumors carry a mutation in the Isocitrate Dehydrogenase 1 (IDH1R132H) gene are younger at the time of diagnosis and survive longer. The molecular glioma subtype which we modelled, harbors IDH1R132H, tumor protein 53 (TP53) and alpha-thalassemia/mental retardation syndrome X-linked (ATRX) loss. The impact of IDH1R132H on genomic stability, DNA damage response (DDR) and DNA repair in this molecular glioma subtype is unknown. We discovered that IDH1R132H expression in the genetic context of ATRX and TP53 inactivation: (i) increases median survival (MS), (ii) enhances DDR activity via epigenetic upregulation of Ataxia-telangiectasia mutated (ATM) signaling, and (iii) elicits tumor radioresistance. Pharmacological inhibition of ATM or checkpoint kinase 1 and 2 (CHK1/2), two essential kinases in the DDR pathways, restored tumors radiosensitivity. Translation of these findings for mlDH1 glioma patients could significantly improve the therapeutic efficacy of radiotherapy, and thus have a major impact on patient survival.

cancer biology↗