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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2023

Adenovirus protein VII binds the A-box of HMGB1 to repress interferon responses.

Viruses hijack host proteins to promote infection and dampen host defenses. Adenovirus encodes the multifunctional protein VII that serves both to compact viral genomes inside the virion and disrupt host chromatin. Protein VII binds the abundant nuclear protein high mobility group box 1 (HMGB1) and sequesters HMGB1 in chromatin. HMGB1 is an abundant host nuclear protein that can also be released from infected cells as an alarmin to amplify inflammatory responses. By sequestering HMGB1, protein VII prevents its release, thus inhibiting downstream inflammatory signaling. However, the consequences of this chromatin sequestration on host transcription are unknown. Here, we employ bacterial two-hybrid interaction assays and human cell biological systems to interrogate the mechanism of the protein VII-HMGB1 interaction. HMGB1 contains two DNA binding domains, the A- and B-boxes, that bend DNA to promote transcription factor binding while the C-terminal tail regulates this interaction. We demonstrate that protein VII interacts directly with the A-box of HMGB1, an interaction that is inhibited by the HMGB1 C-terminal tail. By cellular fractionation, we show that protein VII renders A-box containing constructs insoluble, thereby acting to prevent their release from cells. This sequestration is not dependent on HMGB1s ability to bind DNA but does require post-translational modifications on protein VII. Importantly, we demonstrate that protein VII inhibits expression of interferon {beta}, in an HMGB1- dependent manner, but does not affect transcription of downstream interferon- stimulated genes. Together, our results demonstrate that protein VII specifically harnesses HMGB1 through its A-box domain to depress the innate immune response and promote infection.

microbiology↗
bioRxiv2020

Label-free single-instance protein detection in vitrified cells

A general method to map molecular interactions and conformational states in structurally intact cells would find wide application in biochemistry and cell biology. We used a library of images-- calculated on the basis of known structural data--as search templates to detect targets as small as the "head" domain (350 kDa) of the ribosomes small subunit in single-tilt electron cryo-micrographs by cellular high resolution template matching (cHRTM). Atomically precise position and orientation estimates reveal the conformation of individual ribosomes and enable the detection of specifically bound ligands down to 24 kDa. We show that highly head-swivelled states are likely to play a role in mRNA translocation in living cells. cHRTM outperforms cryo-electron tomography three-fold in sensitivity and completely avoids the vicissitudes of exogenous labelling.

biophysics↗
bioRxiv2025

Optical tissue clearing and 3D imaging of intact primate testicular tissue: a novel technology development

Classical histology struggles to preserve three-dimensional spatial context, prompting the emergence of optical tissue clearing techniques that enable imaging of intact specimens at cellular or subcellular resolution. These techniques have revolutionised fields like cell biology, developmental biology, and neuroscience. However, their application in reproductive biology remains unexplored - particularly in studying the complexities of testicular development. We developed a novel, efficient and affordable toolbox for studying intact testicular tissues, PT-CLEAR3D, that stands for primate testis - whole mount staining, tissue clearing and three-dimensional imaging. Intact testicular tissues from humans (transgender model), common marmosets and macaques underwent antibody labelling, clearing with organic solvents, and three-dimensional imaging using light sheet fluorescence microscopy. Marker specificity was confirmed by immunofluorescence staining of 3 and 25 {micro}m testicular sections, followed by imaging with confocal. The testicular structure was evaluated using several markers: spermatogonia (melanoma-associated antigen 4), least differentiated spermatogonia (Piwi-like protein 4), Sertoli cells (vimentin and SRY-Box transcription Factor 9), peritubular myoid cells and vasculature (alpha-smooth muscle actin), and NucSpot as a nuclear dye. PT-CLEAR3D efficiently achieved optical transparency while a commercial kit that was ran in parallel was inefficient. This study presents a pioneering three-dimensional visualization of intact testicular samples of up to 50 mm3 in size and imaging depth of up to 4.5 mm across three primate species. Remarkably, PT-CLEAR3D revealed critical details at both tissue and cellular levels such as the spatial distribution of germ and somatic cells, cellular bridges, and vasculature. Furthermore, PT-CLEAR3D enabled three-dimensional reconstructions that effectively reduce confirmation bias enhancing our observation of spermatogonial clones organized as single cells, pairs, and quartets. Importantly, it adeptly identified testicular pathology and the persistence of germ cell clones in select tubules within the transgender testis following hormonal suppression of spermatogenesis. This technological development offers a versatile toolbox with benefits such as applicability across multiple species, fluorophore multiplexing, compatibility with different fixatives and deep tissue volumetric imaging with cellular resolution. Overall, PT-CLEAR3D establishes a foundation for spatial evaluation of testicular development, presenting substantial potential for advancing our understanding of the intricate kinetics of spermatogenesis in health and disease.

developmental biology↗
bioRxiv2024

FLIPs: Novel Genetically Encoded Probes for Functional Imaging of Cell Signaling by Polarization Microscopy

Genetically encoded fluorescent biosensors convert specific biomolecular events into optically detectable signals. By revealing biochemical processes in situ, they have revolutionized cell biology. However, imaging molecular processes often requires modifying the proteins involved, and many molecular processes are still to be imaged. Here we present a novel, widely applicable design of genetically encoded biosensors that notably expand the observation possibilities, by taking advantage of a hitherto overlooked detection principle: directionality of optical properties of fluorescent proteins. The probes, which we term FLIPs, offer an extremely simple design, high sensitivity, multiplexing capability, ratiometric readout and resilience to bleaching artifacts, without requiring any modifications to the probe targets. We demonstrate their performance on real-time single-cell imaging of activation of G protein-coupled receptors (GPCRs), G proteins, arrestins, small GTPases, as well as receptor tyrosine kinases, even at endogenous expression levels. We also identify a new, pronounced, endocytosis-associated conformational change in a GPCR-{beta}-arrestin complex. By demonstrating a novel detection principle and allowing many more cellular processes to be visualized, FLIPs are likely to inspire numerous future developments and insights.

physiology↗
bioRxiv2021

Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0 identifies proteins enriched within inflammatory lesions in tissue sections and human clinical biopsies.

Tissue microenvironment properties like blood flow, extracellular matrix or proximity to immune infiltrate are important regulators of cell biology. However, methods to study regional protein expression in context of the native tissue environment are limited. To address this need we have developed a novel approach to visualize, purify and measure proteins in situ using Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0. We previously implemented AutoSTOMP to identify proteins localized to the vacuoles of obligate intracellular microbes at the 1-2 m scale within infected host cells1. Here we report custom codes in SikuliX to specify regions of heterogeneity in a tissue section and then biotin tag and identify proteins belonging to specific cell types or structures within those regions. To enrich biotinylated targets from fixed tissue samples we developed a biochemical protocol compatible with LC-MS. These tools were applied to a) identify inflammatory proteins expressed by CD68+ macrophages in rat cardiac infarcts and b) characterize inflammatory proteins enriched in IgG4+ lesions in esophageal tissue. These data indicate that AutoSTOMP is a flexible approach to determine regional protein expression in situ on a range of primary tissues and clinical biopsies where current tools are limited.

immunology↗
bioRxiv2025

Description of a new Telonemia genus and species with novel observations providing insights into its hidden diversity

Telonemia is a fascinating and understudied group of microbial eukaryotes known to have a vast diversity that is still uncharacterized. In fact, although they are thought to be the closest relatives of the eukaryotic supergroup SAR (Stramenopiles, Alveolata and Rhizaria), their diversity and biology are largely unexplored: to date, there are only seven described species in three genera, although there are estimated to be hundreds more unknown lineages. Here, we describe the isolation and characterization of two new strains, including a new genus (Hyaliora molinica gen. et sp. nov.) and a new species (Telonema blandense sp. nov.), and the re-isolation of a previously characterized telonemid, Telonema subtile, accompanied by new behavioral observations. We present morphological measurements highlighting differences among the isolates and a phylogenetic tree incorporating their 18S rRNA gene sequences. Furthermore, key aspects of their cell biology and structure are highlighted to provide insights into the evolution of TSAR. Since they are relevant not only phylogenetically, but also play a crucial role in food webs with some very abundant representatives in aquatic ecosystems, the findings of this study provide a further sampling and culturing of Telonemia to increase the knowledge of the hidden diversity and evolution of this mysterious group.

evolutionary biology↗
bioRxiv2025

Cytotoxic Vδ2+T cell subsets expand in response to malaria in human tonsil and spleen organoids

Vaccine effectiveness against malaria is dramatically reduced in malaria-exposed compared to malaria-naive populations, potentially due to altered immune responses in secondary lymphoid organs following repeated infection. Newly developed human tonsil and spleen organoids, which replicate key features of B and T cell immunity, provide an exciting opportunity to overcome challenges of other models and to improve our understanding of innate-adaptive interactions in lymphoid tissue. The objectives of this study were to use these organoids to investigate the impact of malaria parasites on 1) cells within lymphoid tissues and 2) responses to a heterologous antigen. When we exposed organoids from malaria-naive donors to Plasmodium falciparum-infected red blood cells (iRBC), we observed that iRBC exposure did not disrupt organoid formation and significantly increased V{delta}2+ {gamma}{delta} T cell frequencies in both tonsil and spleen organoids at multiple timepoints. Single-cell RNA/TCR sequencing revealed that iRBC-responsive V{delta}2+ T cells in organoids were clonally expanded and exhibited activated, cytotoxic phenotypes with upregulated expression of granzymes, interferon-stimulated genes, and antigen presentation machinery. TCR repertoire analysis demonstrated that malaria exposure drove clonal expansion of cytotoxic V{delta}2+ T cells, contrasting with the diverse, smaller clones observed in control conditions. To validate these findings, we analyzed tonsils from Ugandan children with asymptomatic malaria infection and found expanded V{delta}2+ T cells with enhanced cytotoxic potential compared to uninfected controls. When we tested whether malaria pre-exposure affected subsequent recall responses to influenza vaccine, malaria pre-exposure or {gamma}{delta} T cell depletion did not significantly alter cellular frequencies or influenza-specific antibody responses in most donors, though modest reductions were observed in some individuals. This work demonstrates the utility of human lymphoid organoids for studying malaria-host interactions and provides novel insights into V{delta}2+ T cell biology, including evidence for antigen-specific clonal expansion and cytotoxic differentiation in response to malaria parasites within secondary lymphoid tissues. Author SummaryMalaria vaccines are significantly less effective in populations with endemic malaria exposure compared to malaria-naive individuals. We used human tonsil and spleen organoids to investigate whether repeated malaria infections alter immune responses in secondary lymphoid organs, potentially contributing to this reduced vaccine efficacy. These organoids create a controlled system that preserves the architecture and cellular interactions of secondary lymphoid tissues. When we exposed organoids to Plasmodium falciparum-infected red blood cells, we observed dramatic expansion of the V{delta}2+ subset of {gamma}{delta} T cells. This finding was particularly noteworthy because V{delta}2+ T cells are not typically considered major participants in immune responses within secondary lymphoid organs. Single-cell analysis revealed that these expanded V{delta}2+ T cells underwent clonal expansion and acquired cytotoxic phenotypes, suggesting antigen-specific responses. Tonsil tissue from Ugandan children with asymptomatic malaria infections showed similar patterns of V{delta}2+ T cell expansion and enhanced cytotoxic potential. Surprisingly, malaria pre-exposure did not affect subsequent recall responses to influenza vaccine in most donors, although this does not discount a possible impact on immune responses to primary vaccination. Our work reveals unexpected roles for {gamma}{delta} T cells in lymphoid tissues during malaria infection and establishes organoids as valuable models for studying host-pathogen interactions.

immunology↗
bioRxiv2021

MultiMAP: Dimensionality Reduction and Integration of Multimodal Data

Multimodal data is rapidly growing in many fields of science and engineering, including single-cell biology. We introduce MultiMAP, an approach for dimensionality reduction and integration of multiple datasets. MultiMAP recovers a single manifold on which all of the data resides and then projects the data into a single low-dimensional space so as to preserve the structure of the manifold. It is based on a framework of Riemannian geometry and algebraic topology, and generalizes the popular UMAP algorithm1 to the multimodal setting. MultiMAP can be used for visualization of multimodal data, and as an integration approach that enables joint analyses. MultiMAP has several advantages over existing integration strategies for single-cell data, including that MultiMAP can integrate any number of datasets, leverages features that are not present in all datasets (i.e. datasets can be of different dimensionalities), is not restricted to a linear mapping, can control the influence of each dataset on the embedding, and is extremely scalable to large datasets. We apply MultiMAP to the integration of a variety of single-cell transcriptomics, chromatin accessibility, methylation, and spatial data, and show that it outperforms current approaches in preservation of high-dimensional structure, alignment of datasets, visual separation of clusters, transfer learning, and runtime. On a newly generated single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) and single-cell RNA-seq (scRNA-seq) dataset of the human thymus, we use MultiMAP to integrate cells along a temporal trajectory. This enables the quantitative comparison of transcription factor expression and binding site accessibility over the course of T cell differentiation, revealing patterns of transcription factor kinetics.

bioinformatics↗
bioRxiv2022

Learning orientation-invariant representations enables accurate and robust morphologic profiling of cells and organelles

Cell and organelle morphology are driven by diverse genetic and environmental factors and thus accurate quantification of cellular phenotypes is essential to experimental cell biology. Representation learning methods for phenotypic profiling map images to feature vectors that form an embedding space of morphological variation useful for clustering, dimensionality reduction, outlier detection, and supervised learning problems. Morphology properties do not change with orientation, and thus we argue that representation learning methods should encode this orientation invariance. We show that prior methods are sensitive to orientation, which can lead to suboptimal clustering. To address this issue, we develop O2-VAE, an unsupervised learning method that learns robust, orientation-invariant representations. We use O2-VAE to discover novel morphology subgroups in segmented cells and mitochondria, detect outlier cells, and rapidly characterise cellular shape and texture in large datasets, including in a newly generated synthetic benchmark.

bioinformatics↗
bioRxiv2026

Hierarchical bounds on RNA chromatin statistical dependence across cellular states in paired single-cell multiome data

Understanding how transcriptional output and chromatin accessibility coordinate across cellular states remains a central challenge in multimodal single-cell biology. Here, we establish explicit hierarchical empirical bounds on RNA-chromatin statistical dependence using a strictly falsification-driven, information-theoretic analysis of paired RNA-seq and ATAC-seq data. Our contribution is not to assert universal coupling, but to quantify the maximum intra-state coupling that survives adversarial nulls, thereby converting qualitative intuition into empirical bounds. Leveraging unimodal latent representations and adversarial null models, we quantify both the existence and the limits of cross-modal dependence across organizational scales. At the population level, global RNA-ATAC mutual information is strong and reproducible across donors, but is shown to be overwhelmingly dominated by cell-type composition rather than fine-grained regulatory coordination. When cellular state is explicitly controlled, intra-state RNA-ATAC coupling collapses to null expectations in the majority of populations, directly falsifying the hypothesis of a universal within-state regulatory channel. Despite this collapse, a weak but statistically robust residual coupling persists in a restricted subset of highly dynamic states, including erythroid differentiation compartments, activated T cells, and NK cells. This residual signal survives stringent local permutation tests and conditional mutual information analysis, demonstrating that it cannot be reduced to compositional mixing alone. Quantitatively, residual within-state dependence is consistently an order of magnitude smaller than global dependence, placing an empirical upper bound on within-state RNA-ATAC coordination in this dataset. Donor-resolved ratios {rho} = I(R;A|S)/I(R;A) indicate that most of the global dependence is removed by conditioning on state; operationally, we refer to the removed fraction (1-{rho}) as composition-dominated dependence. Throughout, "state-contingent statistical dependence" is used strictly as an operational descriptor rather than a causal claim: mutual information and conditional mutual information quantify statistical dependence only, not directionality or mechanism. This framing constrains downstream mechanistic interpretation and future multimodal modeling.

molecular biology↗
bioRxiv2021

The C. albicans virulence factor Candidalysin polymerizes in solution to form membrane pores and damage epithelial cells.

The pathogenic fungus Candida albicans causes severe invasive candidiasis. C. albicans infection requires the action of the virulence factor Candidalysin (CL), which damages the plasma membrane of the target human cells. However, the molecular mechanism that CL uses to permeabilize membranes is poorly understood. We employed complementary biophysical, modeling, microscopy, and cell biology methods to reveal that CL forms membrane pores using a unique molecular mechanism. Unexpectedly, it was observed that CL readily assembles into linear polymers in solution. The basic structural unit in polymer formation is a CL 8-mer, which is sequentially added into a string configuration. Finally, the linear polymers can close into a loop. Our data indicate that CL loops spontaneously insert into the membrane to become membrane pores. We identified a CL mutation (G4W) that inhibited the formation of polymers in solution and prevented formation of pores in different synthetic lipid membranes systems. Studies in epithelial cells showed that G4W CL failed to activate the danger response signaling pathway, a hallmark of the pathogenic effect of CL. These results indicate that CL polymerization in solution is a necessary step for the damage of cellular membranes. Analysis of thousands of CL pores by atomic force microscopy revealed the co-existence of simple depressions and complex pores decorated with protrusions. Imaging and modeling indicate that the two types of pores are formed by CL molecules assembled into alternate orientations. We propose that this structural rearrangement represents a maturation mechanism that might stabilize pore formation to achieve more robust cellular damage. Taken together, the data show that CL uses a previously unknown mechanism to damage membranes, whereby pre-assembly of CL loops in solution directly leads to formation of membrane pores. Our investigation not only unravels a new paradigm for the formation of membrane pores, but additionally identifies CL polymerization as a novel therapeutic target to treat candidiasis.

biophysics↗
bioRxiv2016

P2Y2 purinergic receptor is induced following human cytomegalovirus infection and its activity is required for efficient viral replication

Human cytomegalovirus (HCMV) manipulates many aspects of host cell biology to create an intracellular milieu optimally supportive of its replication and spread. The current study reveals a role for purinergic signaling in HCMV infection. The levels of several components of the purinergic signaling system, including the P2Y2 receptor, were altered in HCMV-infected fibroblasts. P2Y2 receptor RNA and protein are strongly induced following infection. Pharmacological inhibition of receptor activity or knockdown of receptor expression markedly reduced the production of infectious HCMV progeny. When P2Y2 activity was inhibited, the accumulation of most viral RNAs tested and viral DNA was reduced. In addition, the level of cytosolic calcium within infected cells was reduced when P2Y2 signaling was blocked. The HCMV-coded UL37x1 protein was previously shown to induce calcium flux from the smooth endoplasmic reticulum to the cytosol, and the present study demonstrates that P2Y2 function is required for this mobilization. We conclude that P2Y2 supports the production of HCMV progeny, possibly at multiple points within the viral replication cycle that interface with signaling pathways induced by the purinergic receptor.\n\nImportanceHCMV infection is ubiquitous and can cause life-threatening disease in immunocompromised patients, debilitating birth defects in newborns, and has been increasingly associated with a wide range of chronic conditions. Such broad clinical implications result from the modulation of multiple host cell processes. This study documents that cellular purinergic signaling is usurped in HCMV-infected cells and that the function of this signaling axis is critical for efficient HCMV infection. Therefore, we speculate that blocking P2Y2 receptor activity has the potential to become an attractive novel treatment option for HCMV infection.

Microbiology↗
bioRxiv2019

Widespread diversity in the transcriptomes of functionally divergent limb tendons

Tendon is a functionally important connective tissue that transmits force between skeletal muscle and bone. Previous studies have evaluated the architectural designs and mechanical properties of different tendons throughout the body. However, less is known about the underlying transcriptional differences between tendons which may dictate their designs and properties. Therefore, our objective was to develop a comprehensive atlas of the transcriptome of limb tendons in adult mice and rats using systems biology techniques. We selected the Achilles, forepaw digit flexor, patellar, and supraspinatus tendons due to their divergent functions and high rates of injury and tendinopathies in patients. Using RNA sequencing data, we generated the Comparative Tendon Transcriptional Database (CTTDb) that identified substantial diversity in the transcriptomes of tendons both within and across species. Approximately 30% of transcripts were differentially regulated between tendons of a given species, and nearly 60% of the transcripts present in anatomically similar tendons were different between species. Many of the genes that differed between tendons and across species are important in tissue specification and limb morphogenesis, tendon cell biology and tenogenesis, growth factor signaling, and production and maintenance of the extracellular matrix. This study indicates that tendon is a surprisingly heterogenous tissue with substantial genetic variation based on anatomical location and species. Key PointsO_LITendon is a hypocellular, matrix-rich tissue that has been excluded from comparative transcriptional atlases. These atlases have provided important knowledge about biological heterogeneity between tissues, and our manuscript addresses this important gap. C_LIO_LIWe performed measures on four of the most studied tendons, the Achilles, forepaw flexor, patellar, and supraspinatus tendons of both mice and rats. These tendons are functionally distinct and are also among the most commonly injured, and therefore of important translational interest. C_LIO_LIApproximately one-third of the transcriptome was differentially regulated between Achilles, forepaw flexor, patellar, and supraspinatus tendons within either mice or rats. Nearly two thirds of the transcripts that are expressed in anatomically similar tendons were different between mice and rats. C_LIO_LIThe overall findings from this study identified that although tendons across the body share a common anatomical definition based on their physical location between skeletal muscle and bone, tendon is a surprisingly genetically heterogeneous tissue. C_LI

systems biology↗
bioRxiv2018

AmyCo: the Amyloidoses Collection

AmyCo: the Amyloidoses CollectionAmyloid fibrils are formed when soluble proteins misfold into highly ordered insoluble fibrillar aggregates and affect various organs and tissues. The deposition of amyloid fibrils is the main hallmark of a group of disorders, called amyloidoses. Curiously, fibril deposition has been also recorded as a complication in a number of other pathological conditions, including well-known neurodegenerative or endocrine diseases. To date, amyloidoses are roughly classified, owing to their tremendous heterogeneity. In this work, we introduce AmyCo, a freely available collection of amyloidoses and clinical disorders related to amyloid deposition. AmyCo classifies 74 diseases associated with amyloid deposition into two distinct categories, namely 1) amyloidosis and 2) clinical conditions associated with amyloidosis. Each database entry is annotated with the major protein component (causative protein), other components of amyloid deposits and affected tissues or organs. Database entries are also supplemented with appropriate detailed annotation and are referenced to ICD-10, MeSH, OMIM, PubMed, AmyPro and UniProtKB databases. To our knowledge, AmyCo is the largest repository containing information about amyloidoses and diseases related to amyloid deposition. The AmyCo web interface is available at http://bioinformatics.biol.uoa.gr/amyco.\n\nKaterina C. Nastou is a Ph.D. student in Bioinformatics, at the Department of Biology of the National and Kapodistrian University of Athens. She is currently working on computational analysis of membrane and amyloidogenic proteins as part of her Ph.D. thesis. Her research focuses on the study of protein-protein interactions and the visualization and analysis of biological networks for these protein families, on the computational prediction of protein structure and function and the design and development of biological databases.\n\nGeorgia I. Nasi is a Ph.D. student in Biophysics, at the Department of Biology of the National and Kapodistrian University of Athens and a second year student in the Bioinformatics Masters Program, at the same department. She is currently conducting her Masters thesis on the computational analysis and visualization of the interaction network of amyloidoses and proteins associated with these disorders. Her research for her Ph.D. focuses on biophysical and computational analysis of amyloidogenic proteins and peptide-analogues associated with amyloidoses.\n\nDr. Paraskevi L. Tsiolaki is a Biologist with an MSc in Bioinformatics and a PhD in Molecular Biophysics. She is currently working as a postdoctoral fellow in Dr V. Iconomidous group, Assist. Prof. at the National and Kapodistrian University of Athens and her research interests focus on Molecular Biophysics and Structural Biology. Her current research efforts have been directed towards identifying the structural characteristics that underlie the self-assembly mechanisms,governing amyloidogenicity. More specifically she works on the structure and self-assembly of different amyloidogenic proteins or amyloidogenic peptide-analogues, implicated with amyloidoses, utilizing biophysical and biochemical techniques. She is also working on the computational and structural analysis of the anomalous type of protein-protein interactions in protein aggregation, with particular focus on the development of novel therapeutic intervention strategies.\n\nDr.Zoi Litou works as a Special Laboratory Teaching Staff in \"Bioinformatics-Biophysics\" at the Section of Cell Biology and Biophysics, Department of Biology, National &Kapodistrian University of Athens. She has a PhD in Bioinformatics. She is currently working on computational analysis of membrane proteins focusing on the automated recognition and classification of single-spanning membrane proteins, CWPs, GPCRs and Ion channels. Biological Network Analysis, Prediction algorithms, Algorithm Visualization techniques in Bioinformatics, High throughput sequencing analysis and visualization, Clustering Analysis, Knowledge discovery, management and representation, Data integration, Chemoinformatics, Pharmacogenomics, Text Mining in Bioinformatics, Personalized Medicine, Parallel programming.\n\nDr. Vassiliki A. Iconomidou is an Assistant Professor of Structural Biology/Molecular Biophysics and a group leader of Biophysics and Bioinformatics Lab at the Department of Biology of the National and Kapodistrian University of Athens. Her research interests include: 1) Structural and self-assembly studies of fibrous proteins, which form extracellular, proteinaceous structures of physiological importance like lepidopteran, dipteran and fish chorions and arthropod cuticle, 2) Structural and self-assembly studies of silkmoth chorion peptide-analogues as novel self-assembled polymers with amyloid properties, aiming at the construction of novel biomaterials with extraordinary physical properties, 3) Experimental studiesof the role of a great variety of amyloidogenic ( aggregation-prone) peptides, predicted by our AMYLPRED prediction algorithm, in several widespread and also rare pathological amyloidoses. She had been visiting European Molecular Biology Laboratory (EMBL Heidelberg) for more than ten years, conducting research on molecular self-assembly focusing especially on functional, protective and pathological amyloids and amyloidoses, and she was there when she published the first article on natural protective amyloids. She is the author of 41 publications and 6 book chapters which focus mostly on functional and pathological amyloid studies.

bioinformatics↗
bioRxiv2023

An amortized approach to non-linear mixed-effects modeling based on neural posterior estimation

Non-linear mixed-effects models are a powerful tool for studying heterogeneous populations in various fields, including biology, medicine, economics, and engineering. Here, the aim is to find a distribution over the parameters that describe the whole population using a model that can generate simulations for an individual of that population. However, fitting these distributions to data is computationally challenging if the description of individuals is complex and the population is large. To address this issue, we propose a novel machine learning-based approach: We exploit neural density estimation based on conditional normalizing flows to approximate individual-specific posterior distributions in an amortized fashion, thereby allowing for efficient inference of population parameters. Applying this approach to problems from cell biology and pharmacology, we demonstrate its unseen flexibility and scalability to large data sets compared to established methods.

systems biology↗
bioRxiv2021

Discovery of lipid-mediated protein-protein interactions in living cells using metabolic labeling with photoactivatable clickable probes

Protein-protein interactions (PPIs) are essential and pervasive regulatory elements in cell biology. Despite development of a range of techniques to probe PPIs in living systems, there is a dearth of approaches to capture interactions driven by specific post-translational modifications (PTMs). Myristoylation is a lipid PTM added to more than 200 human proteins, where it may regulate membrane localization, stability or activity. Here we report design and synthesis of a panel of novel photocrosslinkable and clickable myristic acid analog probes, and their characterization as efficient substrates for human N-myristoyltransferases NMT1 and NMT2, both biochemically and through X-ray co-crystallography. We demonstrate metabolic incorporation of probes to label NMT substrates in cell culture and in situ intracellular photoactivation to form a covalent crosslink between modified proteins and their interactors, capturing a snapshot of interactions driven by the presence of the lipid PTM. Proteomic analyses revealed both known and multiple novel interactors of a series of myristoylated proteins, including ferroptosis suppressor protein FSP1 and spliceosome-associated RNA helicase DDX46. The concept exemplified by these probes offers an efficient approach for exploring the PTM-specific interactome, which may prove broadly applicable to other PTMs.

biochemistry↗
bioRxiv2022

Modular automated microfluidic cell culture platform reduces glycolytic stress in cerebral cortex organoids

Organ-on-a-chip systems combine microfluidics, cell biology, and tissue engineering to culture 3D organ-specific in vitro models that recapitulate the biology and physiology of their in vivo counterparts. Here, we have developed a multiplex platform that automates the culture of individual organoids in isolated microenvironments at user-defined media flow rates. Programmable workflows allow the use of multiple reagent reservoirs that may be applied to direct differentiation, study temporal variables, and grow cultures long term. Novel techniques in polydimethylsiloxane (PDMS) chip fabrication are described here that enable features on the upper and lower planes of a single PDMS substrate. RNA sequencing (RNA-seq) analysis of automated cerebral cortex organoid cultures shows benefits in reducing glycolytic and endoplasmic reticulum stress compared to conventional in vitro cell cultures.

bioengineering↗
bioRxiv2023

The phenotype and genotype of fermentative microbes

Fermentation is a major type of metabolism carried out by many organisms. The study of this metabolism cuts across many fields, including cell biology, animal and human health, and biofuel production. Despite this broad importance, there has been no systematic study of fermentation across many organisms. Here we explore the phenotype and genotype of fermentative prokaryotes in order to gain insight into this metabolism. We assembled a dataset containing phenotypic records of 8,350 organisms (type strains) plus 4,355 genomes and 13.6 million genes. Fermentation was widespread, being found in 30% of all organisms and across the tree of life. Fermentative organisms were more likely than non-fermentative ones to have certain phenotypic traits. Some traits (such as oxygen insensitivity) were expected, but others (such as long cells) were surprising. Fermentative organisms also had a distinct genotype, with 9,450 gene functions and 337 metabolic pathways being more common in them. In a related analysis, we identified end products (metabolites) for 1,455 organisms fermenting 100 substrates. We found 55 products were formed in nearly 300 combinations, showing fermentation is more complex than previously realized. Additionally, we built metabolic models for 406 organisms and predicted which products they form. These models did not predict all products accurately, revealing gaps in our knowledge of metabolic pathways. Our study paints a full picture of fermentation while showing there is still much to learn about this type of metabolism. The microbiology community can explore resources in this work with an interactive tool (https://github.com/thackmann/FermentationExplorer).

microbiology↗