Biology subjects

Karakikes, I.

Publications and source records attributed to Karakikes, I..

6 recordsLinked to original sources

bioRxiv2026

Shared and Divergent Features of Cardiac Transcriptome and Glucose Metabolism Markers in Human and Mouse HFpEF

Heart Failure with Preserved Ejection Fraction (HFpEF) is more prevalent in females and is associated with altered cardiac glucose metabolism. However, whether these metabolic alterations are conserved across sexes and between humans and widely used cardiometabolic mouse model of HFpEF remains unclear. We investigated species-, sex-, and ventricle-specific conserved and divergent features of HFpEF. Cardiometabolic HFpEF was induced in mice using the 'two-hit' model (high-fat diet + L-NAME), followed by assessment of cardiac function, RNA sequencing, and protein expression in the right (RV) and left (LV) ventricles. Published human HFpEF RV and LV RNA-seq datasets were reanalyzed and compared with our mouse data. Only male HFpEF mice recapitulated human phenotype of increased RV GLUT1 protein. In contrast, mouse GLUT1 was downregulated in RV of females and in the LV of both sexes, whereas GLUT4 protein remained unchanged. Cardiac PDK4 transcript and protein levels increased in the RV and LV of mice. Conversely, human PDK4 mRNA levels were reduced in the RV with HFpEF and unchanged in LV. Cardiac transcriptome analysis in mice revealed extensive alterations in LV, particularly in females, with enrichment of inflammatory pathways. Cross-species analysis demonstrated greater conservation of HFpEF-associated signatures in the RV than the LV. Furthermore, number of differentially expressed transcripts in human LV increased substantially after excluding patients with atrial fibrillation or diabetes. Overall, the RV of the 'two-hit' model more closely resembles human HFpEF. The cardiac transcriptome reflects sexual dimorphism, and conserved signatures are primarily associated with metabolic alteration, mitochondrial dysfunction, and cellular stress.

physiology↗

bioRxiv2026

The MIRO1-BAX Complex Dictates Life and Death at the Mitochondrial Gate

BAX macropores in the outer mitochondrial membrane (OMM) are canonical mediators of apoptosis, but whether the same pore structure can drive distinct cell death pathways remains unclear. Here, we identify the OMM protein MIRO1 as a context-specific modulator of BAX activity. Mechanistically, MIRO1 binds BAX via MIRO1s N-terminal domain to promote macropore formation and the release of mitochondrial DNA (mtDNA) into the cytoplasm, triggering the STING-pIRF3 signaling axis. In glioma cells, this pathway sustains GPX4 expression via pIRF3-mediated transcriptional activation and confers ferroptosis resistance while bypassing inflammation. By contrast, in Parkinsonian neurons, the MIRO1-BAX complex promotes mitochondrial-stress-induced apoptosis. Using structure-guided drug discovery, we developed first-in-class small molecules that allosterically disrupt the MIRO1-BAX complex by engaging MIRO1s distal GTPase pocket. These compounds sensitize glioma cells to ferroptosis and protect neurons from apoptosis. Our findings reveal a disease-specific mitochondrial switch for life-death decisions and illuminate the molecular logic by which cells exploit and interpret OMM permeabilization.

Cell Biology↗

bioRxiv2025

Artery-on-chip demonstrates smooth muscle function comparable to both healthy and diseased living tissues

Arterial diseases affect the mechanical properties of blood vessels, which then alter their function via complex mechanisms. To develop and test effective treatments, microphysiological systems replicating the function and mechanics of a human artery are needed. Here, we establish an artery-on-chip (ARTOC) using vascular derivatives of human induced pluripotent stem cells (iPSCs) cultured with pulsatile flow on an electrospun fibrin hydrogel. ARTOCs have mature, laminated smooth muscle that expresses robust extracellular matrix and contractile proteins, contracts in response to intraluminal pressure and vasoagonists, and exhibits tissue mechanics comparable to those of human small-diameter arteries. Using real-time monitoring of radial distention and luminal pressure to inform computational fluid dynamics modeling, we show that we can effectively tune biomechanical cues using fibrin scaffold thickness and luminal flow rate. We successfully tune these cues to promote the survival and function of both endothelial and smooth muscle cells simultaneously in the ARTOC. To test the ARTOC as a disease modeling platform, we first use non-isogenic iPSC-derived smooth muscle cells from a polycythemia patient, and we find significantly altered cell phenotype and increased vessel wall stiffness compared to controls. We then test a novel isogenic disease model in ARTOCs from iPSCs CRISPR-edited with the LMNA Hutchinson-Guilford Progeria Syndrome (LMNA G608G; LMNAHGPS) mutation. LMNAHGPS ARTOCs show extracellular matrix accumulation, medial layer loss, premature senescence, and loss of tissue elasticity and ductility. With this work, we establish the ARTOC as a platform for basic and translational studies of arterial diseases, bridging the current gap in linking protein expression and cell phenotype to tissue mechanics and function in small-diameter arteries.

bioengineering↗

bioRxiv2024

Personalized transcriptome signatures in a cardiomyopathy stem cell biobank

BACKGROUNDThere is growing evidence that pathogenic mutations do not fully explain hypertrophic (HCM) or dilated (DCM) cardiomyopathy phenotypes. We hypothesized that if a patients genetic background was influencing cardiomyopathy this should be detectable as signatures in gene expression. We built a cardiomyopathy biobank resource for interrogating personalized genotype phenotype relationships in human cell lines. METHODSWe recruited 308 diseased and control patients for our cardiomyopathy stem cell biobank. We successfully reprogrammed PBMCs (peripheral blood mononuclear cells) into induced pluripotent stem cells (iPSCs) for 300 donors. These iPSCs underwent whole genome sequencing and were differentiated into cardiomyocytes for RNA-seq. In addition to annotating pathogenic variants, mutation burden in a panel of cardiomyopathy genes was assessed for correlation with echocardiogram measurements. Line-specific co-expression networks were inferred to evaluate transcriptomic subtypes. Drug treatment targeted the sarcomere, either by activation with omecamtiv mecarbil or inhibition with mavacamten, to alter contractility. RESULTSWe generated an iPSC biobank from 300 donors, which included 101 individuals with HCM and 88 with DCM. Whole genome sequencing of 299 iPSC lines identified 78 unique pathogenic or likely pathogenic mutations in the diseased lines. Notably, only DCM lines lacking a known pathogenic or likely pathogenic mutation replicated a finding in the literature for greater nonsynonymous SNV mutation burden in 102 cardiomyopathy genes to correlate with lower left ventricular ejection fraction in DCM. We analyzed RNA-sequencing data from iPSC-derived cardiomyocytes for 102 donors. Inferred personalized co-expression networks revealed two transcriptional subtypes of HCM. The first subtype exhibited concerted activation of the co-expression network, with the degree of activation reflective of the disease severity of the donor. In contrast, the second HCM subtype and the entire DCM cohort exhibited partial activation of the respective disease network, with the strength of specific gene by gene relationships dependent on the iPSC-derived cardiomyocyte line. ADCY5 was the largest hubnode in both the HCM and DCM networks and partially corrected in response to drug treatment. CONCLUSIONSWe have a established a stem cell biobank for studying cardiomyopathy. Our analysis supports the hypothesis the genetic background influences pathologic gene expression programs and support a role for ADCY5 in cardiomyopathy.

genomics↗

bioRxiv2023

Transcription factor stoichiometry, motif affinity and syntax regulate single-cell chromatin dynamics during fibroblast reprogramming to pluripotency

The concentration and stoichiometry of transcription factors (TFs) determine cellular identity and can be manipulated to drive cell state transitions. Understanding how changes in TF concentration regulate chromatin state and expression across cell state transitions remains a challenge. We investigated this relationship by profiling chromatin accessibility and gene expression at single-cell resolution across a densely sampled time course of reprogramming human fibroblasts to induced pluripotent stem cells via ectopic expression of OCT4, SOX2, KLF4, and MYC (OSKM). Using deep learning sequence models of base-resolution chromatin accessibility profiles across cell states, we deciphered predictive transcription factor (TF) motif syntax in regulatory elements, inferred affinity- and concentration-dependent dynamics of TF footprints, linked peaks to putative target genes, and elucidated rewiring of cis-regulatory networks. Our models reveal that early in reprogramming, OSK, at supraphysiological concentrations, rapidly open transient regulatory elements by occupying non-canonical low-affinity binding sites. As OSK concentration falls, the accessibility of these transient elements decays as a function of motif affinity. We find that these OSK-dependent transient elements sequester the somatic TF AP-1. This redistribution is strongly associated with the silencing of fibroblast-specific genes within individual nuclei. Together, our integrated single-cell resource and models reveal insights into the cis-regulatory code of reprogramming at unprecedented resolution. We establish a quantitative, predictive framework that links TF stoichiometry, motif syntax, and somatic silencing to provide new perspectives on the control of cell identity by TFs during fate transitions.

genetics↗

bioRxiv2022

Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease

Congenital heart defects, the most common birth disorders, are the clinical manifestation of anomalies in fetal heart development - a complex process involving dynamic spatiotemporal coordination among various precursor cell lineages. This complexity underlies the incomplete understanding of the genetic architecture of congenital heart diseases (CHDs). To define the multi-cellular epigenomic and transcriptional landscape of cardiac cellular development, we generated single-cell chromatin accessibility maps of human fetal heart tissues. We identified eight major differentiation trajectories involving primary cardiac cell types, each associated with dynamic transcription factor (TF) activity signatures. We identified similarities and differences of regulatory landscapes of iPSC-derived cardiac cell types and their in vivo counterparts. We interpreted deep learning models that predict cell-type resolved, base-resolution chromatin accessibility profiles from DNA sequence to decipher underlying TF motif lexicons and infer the regulatory impact of non-coding variants. De novo mutations predicted to affect chromatin accessibility in arterial endothelium were enriched in CHD cases versus controls. We used CRISPR-based perturbations to validate an enhancer harboring a nominated regulatory CHD mutation, linking it to effects on the expression of a known CHD gene JARID2. Together, this work defines the cell-type resolved cis-regulatory sequence determinants of heart development and identifies disruption of cell type-specific regulatory elements as a component of the genetic etiology of CHD.

genomics↗