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Biology subjects

Horvath, P.

Publications and source records attributed to Horvath, P..

At least 19 recordsLinked to original sources

Spheroid surgery: a first-generation micromanipulation platform for extracting viable cell clusters from the outer layers of hydrogel-embedded spheroids

Three-dimensional (3D) cell culture systems have gained attention as in vitro models capable of reproducing the tissue-like architecture, spatial organization, and physiological morphology of in vivo tumors. Their ability to mimic native cell-cell and cell-matrix interactions has positioned 3D cell cultures as powerful models for studying tumor biology and drug responses. However, methods for the localized extraction of viable cells remain limited, as existing approaches often disrupt the original 3D structure, limit access to defined regions, or compromise cell viability, restricting the biological insight that can be achieved. We present a manual, micropipette-based manipulation system designed to extract viable multicellular clusters from the outer layers of compact 3D tumor spheroids, embedded in biocompatible hydrogels. The extracted clusters remained fully functional, demonstrating that the procedure is sufficiently gentle to remove small multicellular units. This technology enables the localized extraction of viable multicellular clusters from 3D in vitro models without complete dissociation of the parent spheroid. The method opens new opportunities for longitudinal studies, spatially targeted sampling and controlled manipulation of living 3D cultures. This capability marks a step toward a new era of 3D model manipulation, where researchers can add, remove, or replace specific regions of living multicellular systems with precision.

bioengineering↗

Uncovering novel phage defense systems through genomic island analysis in Streptococcus thermophilus

Bacteria encode diverse antiviral defense systems, yet the evolutionary reservoirs that generate this immune innovation remain poorly defined. Although genomic context has been instrumental in discovering defense systems, genomic islands (GIs), variable chromosomal regions enriched in defense genes and proteins of unknown function, have not been systematically explored as sources of new bacterial immunity. Here, using comparative genomics of Streptococcus thermophilus, we identified 30 defense-associated GIs displaying extensive accessory gene diversity. Investigation of candidate loci from three GIs uncovered 15 previously uncharacterized antiviral systems, including 10 with novel architectures or features, revealing the potential within even a small subset of GIs. Several systems were not located near known defense genes, highlighting that GI-based discovery complements the traditional guilt-by-association approach, revealing systems that would otherwise remain undetected. Together, our findings establish GIs as reservoirs of antiviral innovation and provide a framework for uncovering the diversity of bacterial immune systems.

microbiology↗

Intrahepatic reporter assay reveals leaky somatic blockade of L1 retrotransposition in mice

Long interspersed element-1 (LINE-1, L1) retrotransposition has long been proposed to occur in somatic tissues, yet direct experimental evidence distinguishing adult somatic events from early embryonic insertions has remained limited. Here we establish an intrahepatic L1 reporter assay that enables immunohistochemical detection and quantitative analysis of L1 retrotransposition in vivo. Using autonomous and non-autonomous L1 reporter variants, we demonstrate clearly detectable somatic L1 activity in the mouse liver. Comparative analysis of L1 activity in liver tissue and tumor-derived cell culture reveals that tumor cells preferentially restrict L1 at early regulatory stages, consistent with epigenetic control, whereas downstream defence mechanisms are comparatively permissive. In contrast, normal liver tissue shows stronger restriction at later stages of the L1 life cycle. Together, our results provide direct experimental evidence for somatic L1 retrotransposition in vivo in adult liver and reveal distinct regulatory strategies that shape L1 activity in tumor versus normal somatic cells. TeaserGenome destabilizing L1 retrotransposon activity is present in somatic tissues, where it likely contributes to cancer development.

genetics↗

Prevalent Gut Phages Encode Modular Adhesins Mediating Epithelial Binding and Endoplasmic Reticulum Trafficking

Bacteriophages are crucial components of the human microbiome and hold promise as therapeutic agents. Yet, their physical interactions with mammalian cells remain poorly understood. Here, we developed a high-throughput platform to identify phages that adhere to epithelial layers and the proteins that mediate this interaction. The identified phages encode immunoglobulin (Ig)-like domain-containing proteins that, when displayed on a non-adherent phage, confer epithelial binding and internalization in vitro, and increased phage retention in the mouse gut in vivo. Phages encoding these adhesins are among the most abundant and prevalent human gut phages, including crAss-like phages and a distinct cluster of uncharacterized myophages. Domain sequence variation alters epithelial interaction profiles, and internalized phages traffic to the endoplasmic reticulum through the Golgi apparatus, suggesting access to non-degradative internalization pathways. These findings reveal widespread phage-human interactions in the human virome, with potential impacts on health and implications for next-generation phage therapeutics.

microbiology↗

Circulating Lipids are Associated with PTSD Severity and Predict Symptomatic PTSD in a Cohort of Veterans and Service Members

Post-traumatic stress disorder (PTSD) is characterized by chronic stress, alterations in mood, and avoidance after a traumatic event has occurred. While recovery can occur, many PTSD patients suffer life-long impairments. In combat veterans, high rates of PTSD contribute to increased rates of depression and anxiety and a higher likelihood of suicidal ideation. The lack of biological markers for psychiatric conditions such as PTSD highlights the need for omics-based approaches to diagnosis. Discovery of novel blood-based biomarkers could aid in the development of treatments or therapies, quantify groups for those at the highest risk of adverse events, and provide insight into the molecular underpinnings of PTSD. This study used untargeted lipidomics to analyze 602 circulating lipid species in blood from a cohort of 133 veterans and combat members with varying severities of PTSD. We discovered five circulating lipids, including serum total cholesterol, cholesterol ether (ChE(18:2)), and lipids associated with metabolic dysfunction (cardiolipin : CL(87:7), monolysocardiolipin : MLCL(50:4), and phosphatidylethanolamine plasmalogen/ether lipid : PE(18:1e_20:3)) that correlated significantly with increasing PTSD severity after adjustment for multiple comparisons. Additionally, we showed that symptomatic PTSD patients could be separated from asymptomatic controls using these lipid species. This study contributes to the limited research surrounding the role of circulating lipids in PTSD.

neuroscience↗

Concerted actions of distinct serotonin neurons orchestrate female pup care behavior

In many mammalian species, female behavior towards infant conspecifics changes across reproductive stages. Sexually naive females interact minimally or aggressively with infants, whereas the same animals exhibit extensive care behavior, even towards unrelated infants, after parturition1-6. Here, we discovered that two distinct sets of serotonin neurons collectively mediate this dramatic transition in maternal behavior--serotonin neurons projecting to the medial preoptic area (mPOA) promote pup care in mothers, whereas those projecting to the bed nucleus of the stria terminalis (BNST) suppress pup interaction in virgin female mice. Disrupting serotonin synthesis in either of these subpopulations or stimulating either subpopulation is sufficient to toggle pup-directed behavior between that displayed by virgin females and that of lactating mothers. In virgin female mice, the first pup interaction triggers an increase in serotonin release in BNST but a decrease in mPOA. In mothers, serotonin activity becomes greatly elevated in mPOA during pup interactions. Acute interruption of serotonin signaling locally in either mPOA or BNST disrupts the stage-dependent switch in pup care. Together, these results highlight how functionally distinct serotonin subpopulations orchestrate social behaviors appropriate for a given reproductive state, and suggest a circuit logic for how a neuromodulator coordinates adaptive behavioral changes across life stages.

neuroscience↗

Subphase-Labeled Mitotic Dataset for AI-powered Cell Division Analysis

Mitosis detection represents a critical task in the field of digital pathology, as determination of the mitotic index (MI) plays an important role in the tumor grading and prognostic assessment of patients. Manual determination of MI is a labor-intensive and time-consuming task for practitioners with rather high interobserver variability, thus, automation has become a priority. There has been substantial progress towards creating robust mitosis detection algorithms in recent years, primarily driven by the Mitosis Domain Generalization (MIDOG) challenges. In parallel, there has been growing interest in the molecular characterization of mitosis with the goal of achieving a more comprehensive understanding of its underlying mechanisms in a subphase-specific manner. Here, we introduce a new mitotic figure dataset annotated with subphase information based on the MIDOG++ dataset as well as a previously unrepresented tumor domain to enhance the diversity and applicability of the dataset. We envision a new perspective for domain generalization by improving the performance of models with subtyping mitotic cells into the 5 main stages of normal mitosis, complemented with an atypical mitotic class. We believe that our work broadens the horizon in digital pathology: subtyping information could provide useful help for mitosis detection, while also providing promising new directions in answering biological questions, such as molecular analysis of the subphases on a single cell level.

bioinformatics↗

Microenvironmental information significantly improves the recognition of cell types in human lung cancer patients

Accurate single-cell phenotypic classification in histopathological tissue sections is essential for understanding tumor behavior, identifying potential therapeutic targets, and improving prognostic assessments in cancer research. In this study, we applied deep learning to classify lung cancer cell phenotypes in hematoxylin and eosin-stained tissue sections. Using 11 whole slide images from 11 patients, we annotated nearly 20,000 cells into seven distinct phenotypes for training and validation. We used a fisheye transformation technique, which modifies images to mimic fisheye camera effects in order to incorporate cellular microenvironment information to enhance deep learning models. We evaluated its effectiveness on lung cancer tissue sections, optimizing transformation parameters and assessing classification performance through multiple cross-validation strategies. Our results demonstrate that the transformation significantly improves classification accuracy, approaching human level performance, particularly for phenotypes that rely on subtle morphological differences. The approach enhances model generalizability across patient samples, highlighting the importance of integrating spatial context in computational pathology. These findings suggest that incorporating adaptive image transformations can significantly improve automated histopathological analysis, with potential implications for more robust and clinically applicable AI-driven diagnostics.

bioinformatics↗

Very long chain fatty acids drive 1-deoxy-Sphingolipid toxicity

1-deoxy-sphingolipids (1-deoxySLs) are atypical sphingolipids synthesized by the serine palmitoyltransferase (SPT) when L-alanine is used instead of its canonical substrate L-serine. Increased 1-deoxySLs are associated with sensory neuropathies such as Hereditary Sensory and Autonomic Neuropathy type 1 (HSAN1) and diabetic polyneuropathy (DPN). Despite their known cellular, mitochondrial, and neurotoxic effects, the mechanisms underlying their toxicity remain poorly understood. Using a CRISPR interference (CRISPRi) screening approach, we identified CERS2, ELOVL1, ACACA, HSD17B12, and PTPLB as key mediators of 1-deoxySL-induced toxicity. All genes are integral to the biosynthesis of very long-chain (VLC) fatty acids and VLC-ceramides. We validated these findings through genetic knockdown experiments, cytotoxicity assays, and stable isotope-resolved lipidomics via LC-MS/MS. Pharmacological inhibition of ELOVL1 using a preclinical tested compound alleviated the cellular, mitochondrial, and neuronal toxicity induced by 1-deoxySLs. Supplementation experiments combining 1-deoxySLs with various VLC fatty acids revealed that 1-deoxyDHceramide conjugated to nervonic acid (m18:0/24:1) is the principal toxic specie. Further mechanistic studies showed that m18:0/24:1 induces apoptosis through the mitochondrial permeability transition pore (mPTP) formation. Inhibition of BAX or blocking mPTP formation with cyclosporin A effectively prevented toxicity. In conclusion, our findings demonstrate that 1-deoxyDHCeramides conjugated to nervonic acid are the primary mediators of 1-deoxySL toxicity, acting through mitochondrial dysfunction and BAX-dependent apoptosis.

biochemistry↗

Multiplexed Deep Visual Proteomics Unveils Spatial Heterogeneity and Rare Endocrine States in Human Adult Pancreatic Islets

Pancreatic islets are highly specialized tissue compartments that regulate metabolism, and their dysfunction contributes to diseases such as prediabetes and diabetes. Characterizing islet morphology and cell plasticity is essential for understanding these pathophysiological states, yet high-resolution spatial proteomics remains challenging due to the islets small size and cellular complexity. Here, we present multiplexed deep visual proteomics (mxDVP), an approach that integrates high-plex imaging with ultra-sensitive mass spectrometry to achieve deep spatial proteome profiling of defined cell types in tissue sections. Enhanced segmentation, semi- automated annotation, and optimized laser microdissection enable the enrichment of rare endocrine populations that are often overlooked in single-cell analyses. mxDVP achieves deep proteome coverage of >6,000 proteins from as few as 100 cells, including low-abundance transcription factors critical for endocrine cell fate determination. By profiling over 864,000 human pancreatic cells, we identify 12 endocrine subtypes, including polyhormonal hybrids, revealing previously unrecognized islet heterogeneity, metabolic regulation, and cellular adaptability.

molecular biology↗

A Morpho-Proteomic Atlas of Mitosis at Sub-Minute Resolution

Precise spatiotemporal protein organization is critical for fundamental biological processes including cell division1,2. Indeed, aberrant mitosis and mitotic factors are involved in diverse diseases, including various cancers3,4, Alzheimers disease5, and rare diseases6. During mitosis, complex spatial rearrangements and regulation ensure the accurate separation of replicated sister chromatids to produce genetically identical daughter cells7-9. Previous studies employed high-throughput methodologies to follow specific proteins during mitosis10-15. Still a temporally refined systems-level approach capable of monitoring morphological and proteomic changes throughout mitosis has been lacking. Here, we achieved unprecedented resolution by phenotypically decomposing mitosis into 40 subsections of a regression plane for proteomic analysis using deep learning and regression techniques. Our deep visual proteomics (DVP) workflow16, revealed rapid, dynamic proteomic changes throughout mitosis. We quantified 4,350 proteins with high confidence, demonstrating that 147 show significant dynamic abundance changes during mitotic progression. Clustering revealed coordinated patterns of protein regulation, while network analysis uncovered tight regulation of core cell cycle proteins and a link between cell cycle and cancer-linked mutations. Immunofluorescence validated abundance changes and linked previously uncharacterised proteins, like C19orf53, to mitosis. To facilitate data navigation, we developed Mito-Omix, a user-friendly online platform that integrates intricate morphological and molecular data. Our morphological and proteomic dataset spans mitosis at high resolution, providing a rich resource for understanding healthy and aberrant cell division.

cell biology↗

Deep visual multi-omics profiling reveals mechanisms that underly cancer cell differentiation and aggressiveness in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) exhibits significant intra-tumoral heterogeneity (ITH) at both morphological and genetic levels, complicating treatment and contributing to disease progression. Among these, ccRCCs with focal rhabdoid differentiation stand out as highly aggressive tumors distinguished by cells with unique morphological features. However, the correlation between distinct morphological phenotypes, specific molecular alterations, and their influence on tumor behavior remains poorly understood. In this study, we integrated advanced AI-based image analysis with single-cell isolation and multi-omics profiling to dissect the link between clinically relevant morphological and molecular features of ccRCC cells. Using a novel digital pathology workflow, we quantified low-grade, high-grade, and rhabdoid morphologies in ccRCC diagnostic images with unprecedented precision. Subsequently, isolation of two sets of 1,000 morphologically distinct cells for detailed mRNA and protein expression analyses, revealed significant increasing dysregulation associating with higher histopathological grades. Rhabdoid ccRCC cells (grade 4) demonstrated unique molecular profiles, including upregulated FOXM1-driven proliferation, disrupted cell-matrix interactions, and enhanced immune evasion pathways. Despite high T-cell infiltration in rhabdoid areas, we identified a rhabdoid-specific immunosuppressive network driven by cytokines, IFN-beta, and integrin signaling, likely contributing to T-cell exhaustion. Rhabdoid ccRCC cells develop a distinct immunosuppressive signaling network, involving PD-L1 and novel immunomodulatory factors such as CD38 and ITGB2. These findings provide a basis for novel therapeutic strategies targeting these pathways in combination with immunotherapy to improve outcomes for patients with aggressive rhabdoid ccRCC. Key PointsO_LIccRCC is characterized by well-established morphological heterogeneity but the correlation with the underlying molecular aberrations remained elusive. C_LIO_LIBy integrating AI-based image analysis with single cell isolation and deep multi-omics profiling, we dissect the molecular intricacies of ccRCC, from targeted collection of 1,000 morphologically distinct cells. C_LIO_LIOur results demonstrate significant dysregulation of gene and protein expression correlating with higher histopathological grades in ccRCC. C_LIO_LIAggressive ccRCC cells with rhabdoid differentiation (grade 4) display distinct molecular profiles, as they upregulate FOXM1-mediated proliferation, ECM remodeling and the immune evasion responses, suggesting new therapeutic avenues enhancing ICI efficacy in these patients. C_LI

cancer biology↗

LBR and LAP2 mediate heterochromatin tethering to the nuclear periphery to preserve genome homeostasis

In most eukaryotic cells, euchromatin is localized in the nuclear interior, whereas heterochromatin is enriched at the nuclear envelope (NE). This conventional chromatin organization is established by heterochromatin tethering to the NE, however its importance for cellular homeostasis is largely unexplored. Peripheral heterochromatin localization relies on redundant NE-tethering systems. One tether is constituted by the lamin B receptor (LBR) in mammals, but the enigmatic nature of the other tethers has hampered functional analyses. Here we demonstrate that the downregulation of abundant, ubiquitous NE proteins can induce the global detachment of heterochromatin from the NE. Among these factors, we identify LBR and LAP2 as major players in bulk heterochromatin attachment to the NE in pluripotent and differentiated mammalian cells. Their loss leads to repositioning of heterochromatin to the nuclear interior, changes in chromatin accessibility, deregulation of gene expression including activation of antiviral innate immunity, and defects in cell fate determination.

cell biology↗

Strengthening Phage Resistance of Streptococcus thermophilus by Leveraging Complementary Defense Systems

CRISPR-Cas and restriction-modification systems represent the core defense arsenal in Streptococcus thermophilus to block lytic phages, but their effectiveness is compromised by phages encoding anti-CRISPR proteins (ACRs) and other counter-defense strategies. Here, we explored the resistome of 263 S. thermophilus strains to uncover other anti-phage systems. The defense landscape of S. thermophilus was enriched by 21 accessory defense systems, 13 of which had not been previously investigated in this species. Experimental validation of 17 systems with 14 phages showed varying anti-phage levels, uncovering intra-genus specificities among the five viral genera infecting S. thermophilus. Interestingly, the resistance levels were even higher when some defense systems (Dodola and PD-Lambda-1) were expressed from a low-copy plasmid or when integrated into the chromosome. We also observed a synergistic effect when combining Gabija with CRISPR-Cas, underscoring the potential of these additional defense systems for developing more robust industrial S. thermophilus strains, particularly against ACR-encoding phages.

microbiology↗

HCS-3DX, a next-generation AI-driven automated 3D high-content screening system

Self-organized three-dimensional (3D) cell cultures, collectively called 3D-oids, include spheroids, organoids and other co-culture models. Systematic evaluation of these models forms a critical new generation of high-content screening (HCS) systems for patient-specific drug analysis and cancer research. However, the standardisation of working with 3D-oids remains challenging and lacks convincing implementation. This study develops and tests HCS-3DX, a next-generation system revolutionising HCS analysis in 3D imaging and image evaluation. HCS-3DX is based on three main components: an automated Artificial Intelligence (AI)-driven micromanipulator for 3D-oid selection, an HCS foil multiwell plate for optimised imaging, and image-based AI software for single-cell data analysis. We validated HCS-3DX directly on 3D tumour models, including tumour-stroma co-cultures. Our data demonstrate that HCS-3DX achieves a resolution that overcomes the limitations of current systems and reliably and effectively performs 3D HCS at the single-cell level. Its application will enhance the accuracy and efficiency of drug screening processes, support personalised medicine approaches, and facilitate more detailed investigations into cellular behaviour within 3D structures.

bioinformatics↗

Piximi - An Images to Discovery web tool for bioimages and beyond

Deep learning has greatly accelerated research in biological image analysis yet it often requires programming skills and specialized tool installation. Here we present Piximi, a modern, no-programming image analysis tool leveraging deep learning. Implemented as a web application at Piximi.app, Piximi requires no installation and can be accessed by any modern web browser. Its client-only architecture preserves the security of researcher data by running all computation locally. Piximi offers four core modules: a deep learning classifier, an image annotator, measurement modules, and pre-trained deep learning segmentation modules. Piximi is interoperable with existing tools and workflows by supporting import and export of common data and model formats. The intuitive researcher interface and easy access to Piximi allows biological researchers to obtain insights into images within just a few minutes. Piximi aims to bring deep learning-powered image analysis to a broader community by eliminating barriers to entry.

cell biology↗

Unveiling the regulatory network controlling natural transformation in lactococci

Lactococcus lactis is a lactic acid bacterium of major importance for food fermentation and biotechnological applications. The ability to manipulate its genome quickly and easily through competence for DNA transformation would accelerate its general use as a platform for a variety of applications. Natural transformation in this species requires the activation of the master regulator ComX. However, the growth conditions that lead to spontaneous transformation, as well as the regulators that control ComX production, are unknown. Here, we identified the carbon source, nitrogen supply, and pH as key factors controlling competence development in this species. Notably, we showed that these conditions are sensed by three global regulators (i.e., CcpA, CodY, and CovR), which repress comX transcription directly. Furthermore, our systematic inactivation of known signaling systems suggests that classical pheromone-sensing regulators are not involved. Finally, we discovered that the ComX-degrading MecA-ClpCP machinery plays a predominant role based on the identification of a single amino-acid substitution in the adaptor protein MecA of a highly transformable strain. Contrasting with closely-related streptococci, the master competence regulator in L. lactis is regulated both proximally by general sensors and distantly by the Clp degradation machinery. This study not only highlights the diversity of regulatory networks for competence control in Gram-positive bacteria, but it also paves the way for the use of natural transformation as a tool to manipulate this biotechnologically important bacterium. IMPORTANCELactic acid bacteria (LAB) play important roles in our daily lives as members of our microbiota or as starters of dairy products. Understanding the natural horizontal gene transfer mechanisms that shape their genomes will allow us to better control and understand their evolution over time. The DNA transformation machinery is found in all beneficial LAB species. With the exception of streptococci, however, the conditions of its activation remain unknown. In this study, the physiological conditions that activate competence for DNA transformation in Lactococcus lactis, the most important lactococcal species, were identified. We also unveiled the guardians of the master competence regulator ComX. In this species, it is directly repressed by global carbon and nitrogen regulators (CcpA and CodY) as well as the general stress system CovRS. Additionally, it was discovered that the Clp machinery degrading ComX plays a dominant role in the strict control of competence activation. In Gram-positive cocci, the hierarchical organization of these regulators for controlling competence development in L. lactis is unprecedented.

microbiology↗

When the pen is mightier than the sword: semi-automatic 2 and 3D image labelling

Data is the driving engine of learning-based algorithms, the creation of which fundamentally determines the performance, accuracy, generalizability and quality of any model or method trained on it. When only skilled or trained personnel can create reliable annotations, assisted software solutions are desirable to reduce the time and effort the expert must spend on labelling. Herein is proposed an automated annotation helper software package in napari that offers multiple methods to assist the annotator in creating object-based labels on 2D or 3D images.

bioinformatics↗