Biology subjects

Papadopoulos, C.

Publications and source records attributed to Papadopoulos, C..

10 recordsLinked to original sources

bioRxiv2026

Identification of a large class of cancer-germline microproteins as a source of immunotherapeutic targets

Classical cancer germline-antigens (CGAs) are proteins that are expressed in the male germinal line but not in somatic tissues, and that can also become expressed in tumors. However, the vast majority of testis-specific transcripts are long non-coding RNAs (lncRNAs) rather than protein-coding genes. Since recent studies have shown that many lncRNAs contain non-canonical open reading frames (ncORFs) that are translated into small proteins, or microproteins, there could be a large class of non-canonical cancer-germline antigens (ncCGAs) that remains to be discovered. Here, we integrate ribosome profiling from human testis and cancer cell lines with paired tumor/normal transcriptomes from 917 patients across eight common cancer types to define a comprehensive catalog of ncCGAs. This set comprises 235 ncCGAs encoded by lncRNAs or mRNA untranslated regions (5UTRs and 3UTRs), compared to 192 canonical CGAs (cCGAs) with similar expression patterns. We show that ncCGAs are evolutionary young, consistent with recent de novo emergence in the rapidly evolving male germline. Moreover, a large fraction is expressed across multiple patients and cancer types, indicating recurrent reactivation mechanisms in tumors. We further find that ncCGAs are frequently located in cancer-amplified regions or associated with MYC or E2F-regulated pathways, which may explain their expression in cancer. Finally, we provide strong evidence that a subset of ncCGAs give rise to potentially immunogenic HLA class I bound peptides. Together, our results describe a previously unexplored class of tumor-restricted antigens with potential applications in cancer immunotherapy.

cancer biology↗

bioRxiv2026

Evolutionary emergence and preservation of microproteins encoded by upstream ORFs

The analysis of ribosome profiling (Ribo-Seq) data has provided evidence that many eukaryotic mRNAs contain translated upstream or downstream ORFs (uORFs/dORFs), but the biological significance of this translation activity remains, for the most part, unknown. One of the principal limitations has been the lack of Ribo-Seq data from several closely related species, precluding the identification of cases in which translation is phylogenetically conserved. Here, by combining Ribo-Seq data from 100 different experiments, we identify 2,332 translated uORFs and 1,008 translated dORFs in S. cerevisiae, which result in microproteins that tend to be highly hydrophobic or positively charged. To study their phylogenetic conservation, we have generated Nanopore direct RNA sequencing data, together with Ribo-Seq data, from six additional Saccharomyces species, spanning an evolutionary period of around 16 million years. We have identified 195 translated S. cerevisiae uORFs that are also translated in other Saccharomyces species; these uORFs are translated at levels comparable to the main coding sequence and display signatures of purifying selection at the level of the encoded microproteins. In contrast, dORFs are translated at very low levels and they are rarely conserved, suggesting much more limited microprotein functionalization. We have also discovered that uORF translation is associated with the formation of alternative transcript isoforms encompassing the region containing the uORFs but not the main protein coding sequence, implying that some microproteins can be produced independently of the main protein product. This work significantly advances our understanding of how initially pervasive uORF translation can result in new microproteins, providing many new candidates for further functional studies.

genomics↗

bioRxiv2024

Erythrocyte TLR9 is upregulated in metabolic associated fatty liver disease, and is linked to an inflammatory immunometabolic signature.

Metabolic associated fatty liver disease (MAFLD) consists of lipid accumulation in the liver. Lipotoxicity, supported by aberrant amino acid metabolism, induces TLR9 upregulation, and activation, driving inflammation. Relatively, erythrocyte TLR9 activation leads to membrane rearrangement, surface CD47 loss, and pro-inflammatory erythrophagocytosis. Erythrocyte surface protein loss is accompanied by chemokine release. In addition, CD47 binds circulating TSP-1, a molecule controlling arginine and glutamine metabolism, along with metabolic inflammation. Based on these, we speculated that in MAFLD, lipotoxicity would drive erythrocyte TLR9 upregulation and activation, leading to immunometabolic remodeling. Twenty-four patients (15 men and 9 women) with MAFLD and 9 healthy controls (4 men and 5 women) were enrolled. Erythrocytes were isolated from EDTA-containing blood. Protein levels were measured in erythrocyte lysates (triton X-100 0.01% v/v) or plasma with enzyme-linked immunosorbent assays, whereas lipids and enzyme activities were measured in erythrocyte hemoglobin-free membranes by a semi-quantitative thin layer chromatography and assay kits, respectively. The levels of TLR9 were increased (p=0.002) and positively correlated with sphingosine levels, albeit not statistically significantly (p=0.060). The erythrocyte membrane PC/PE ratio was decreased (p=0.002) and inversely correlated to TLR9 levels. Erythrocyte TLR9 levels correlated inversely with CD47, and positively with MCP-1 release. TSP-1 was decreased in MAFLD erythrocytes (p=0.0017) and correlated positively with CD47 and negatively with TLR9 levels. In vitro, erythrocytes of MAFLD patients bound less TSP-1 molecules. Erythrocytes of MAFLD patients also exhibit decreased arginase-1 protein (p=0.009) and activity (p=0.042). Glutaminase activity was increased, albeit to not statistically significantly different levels (p=0.25). The levels of CD35 were not different (p=0.65), excluding the role of erythrocyte aging for explaining these events. In MAFLD patients, erythrocyte TLR9 is upregulated and is associated with erythrocyte sphingolipid and glycerophospholipid perturbation, CD47 loss, MCP1 release, reduced TSP-1 scavenging, decreased arginase and increased glutaminase.

immunology↗

bioRxiv2023

The Ribosome Profiling landscape of yeast reveals a high diversity in pervasive translation

Pervasive translation is a widespread phenomenon that plays an important role in de novo gene birth; however, its underlying mechanisms remain unclear. Based on multiple Ribosome Profiling (Ribo-Seq) datasets, we investigated the RiboSeq landscape of coding and noncoding regions of yeast. Therefore, we developed a representation framework which allows the visual representation and rational classification of the entire diversity of Ribo-Seq signals that could be observed in yeast. We show that if coding regions are restricted to specific areas of the Ribo-Seq landscape, noncoding regions are associated with a wide diversity of translation signals and, conversely, populate the entire yeast Ribo-Seq landscape. Specifically, we reveal that noncoding regions are associated with canonical translation signals, but also with non-canonical ones absent from coding regions, and which appear to be a hallmark of pervasive translation. Notably, we report thousands of translated noncoding ORFs among which, 251 led to detectable products with Mass Spectrometry while being characterized by a wide range of translation specificities. Overall, we show that pervasive translation is not random with noncoding ORF translation signals being consistent across Ribo-Seq experiments. Finally, we show that the translation signal of noncoding ORFs is not explained by features related to the emergence of function, but rather determined by the translation start codon and the codon distribution in their two alternative frames. Overall, our results enable us to propose a topology of the pervasive Ribo-Seq landscape of a species, and open the way to future comparative analyses of this translation landscape under different conditions.

evolutionary biology↗

bioRxiv2023

NEURD: A mesh decomposition framework forautomated proofreading and morphologicalanalysis of neuronal EM reconstructions

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons in these volumes contain detailed morphological information at multiple scales, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes meshed neurons into compact and extensively-annotated graph representations. With these feature-rich graphs, we automate a variety of tasks such as state of the art automated proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other annotations. These features enable many downstream analyses of neural morphology and connectivity, making these massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

neuroscience↗

bioRxiv2023

Functional connectomics reveals general wiring rule in mouse visual cortex

Understanding the relationship between circuit connectivity and function is crucial for uncovering how the brain implements computation. In the mouse primary visual cortex (V1), excitatory neurons with similar response properties are more likely to be synaptically connected, but previous studies have been limited to within V1, leaving much unknown about broader connectivity rules. In this study, we leverage the millimeter-scale MICrONS dataset to analyze synaptic connectivity and functional properties of individual neurons across cortical layers and areas. Our results reveal that neurons with similar responses are preferentially connected both within and across layers and areas -- including feedback connections -- suggesting the universality of the like-to-like connectivity across the visual hierarchy. Using a validated digital twin model, we separated neuronal tuning into feature (what neurons respond to) and spatial (receptive field location) components. We found that only the feature component predicts fine-scale synaptic connections, beyond what could be explained by the physical proximity of axons and dendrites. We also found a higher-order rule where postsynaptic neuron cohorts downstream of individual presynaptic cells show greater functional similarity than predicted by a pairwise like-to-like rule. Notably, recurrent neural networks (RNNs) trained on a simple classification task develop connectivity patterns mirroring both pairwise and higher-order rules, with magnitude similar to those in the MICrONS data. Lesion studies in these RNNs reveal that disrupting like-to-like connections has a significantly greater impact on performance compared to lesions of random connections. These findings suggest that these connectivity principles may play a functional role in sensory processing and learning, highlighting shared principles between biological and artificial systems.

neuroscience↗

bioRxiv2023

The effect of in vitro starch digestibility on glycemic/insulinemic index of biscuits and bread made from non-conventional wholemeal/wholegrain flour mixtures.

BACKGROUNDCarbohydrates as starch are a staple part of the Mediterranean diet. Starch is digested in the small intestine and the resulting glucose is absorbed into the blood, eliciting an insulin response. The digestion and absorption kinetics (rapid or slow) depends on starch structure. OBJECTIVETo study the relationship between the in vivo glycemic and insulinemic index and the in vitro digestibility characteristics of six bakery products, made from non-conventional wholemeal/wholegrain flours. METHODSWe analyzed in vitro the rapidly- and slowly- available glucose (RAG and SAG), the rapidly- and slowly- digestible starch (RDS and SDS), and the resistant starch (RS) fraction of the six wholemeal/wholegrain products and one white type of bread. The glycemic and the insulinemic index (GI and II respectively) were estimated by in vivo testing in a group of eleven healthy individuals. RESULTSThe GI of the wholemeal/wholegrain flour biscuits and breads were low, (range 28{+/-}3.2 to 41{+/-}3.9, Mean{+/-}SEM) correlating with the II. RAG positively correlated with both GI and II, with fiber having a marginal correlation. CONCLUSIONSOur findings indicate that both conventional and non-conventional wholemeal/wholegrain bakery products have low GI and moderate II, correlating to in vitro starch digestibility and the type of processing.

biochemistry↗

bioRxiv2021

Functional connectomics spanning multiple areas of mouse visual cortex

To understand the brain we must relate neurons functional responses to the circuit architecture that shapes them. Here, we present a large functional connectomics dataset with dense calcium imaging of a millimeter scale volume. We recorded activity from approximately 75,000 neurons in primary visual cortex (VISp) and three higher visual areas (VISrl, VISal and VISlm) in an awake mouse viewing natural movies and synthetic stimuli. The functional data were co-registered with a volumetric electron microscopy (EM) reconstruction containing more than 200,000 cells and 0.5 billion synapses. Subsequent proofreading of a subset of neurons in this volume yielded reconstructions that include complete dendritic trees as well the local and inter-areal axonal projections that map up to thousands of cell-to-cell connections per neuron. Here, we release this dataset as an open-access resource to the scientific community including a set of tools that facilitate data retrieval and downstream analysis. In accompanying papers we describe our findings using the dataset to provide a comprehensive structural characterization of cortical cell types1-3 and the most detailed synaptic level connectivity diagram of a cortical column to date2, uncovering unique cell-type specific inhibitory motifs that can be linked to gene expression data4. Functionally, we identify new computational principles of how information is integrated across visual space5, characterize novel types of neuronal invariances6 and bring structure and function together to decipher a general principle that wires excitatory neurons within and across areas7, 8.

neuroscience↗

bioRxiv2021

Validation and Application of a Protocol for the Extraction and Quantitative Analysis of Sphingomyelin in Erythrocyte Membranes of Patients with NAFLD

A set of constituents of the erythrocyte membrane lipidome has been proposed to serve as biomarkers for liver disease and acute coronary syndrome. In erythrocytes, sphingomyelin hydrolysis provides ceramide, a signaling lipid necessary for phosphatidylserine exposure and eryptosis. Phosphatidylserine exposure further amplifies hepatic inflammation and fibrosis during non-alcoholic fatty liver disease (NAFLD). In this study, we developed and applied a quantitative TLC for erythrocyte membrane sphingomyelin of NAFLD patients. We also compared 10 extraction methods for the isolation of sphingomyelin from erythrocytes. For quantitative TLC, lipids were separated in Silica gel 60 F254 using a mixture of chloroform/methanol/acetic acid/water (60/50/1/4) (v/v/v/v). The separated lipids were stained in a chamber containing iodine, and the intensity of each of the primary colors (red, green, blue) and the sum of the Red plus Green colors (R+G) was analyzed. The method was linear over a wide range of concentrations, presented acceptable precision (inter-day CV(%) 0.34, 0.006 and 0.44 for 2.5, 5.0 and 10 g, respectively), good accuracy (recovery range 85.2-97.1%), and excellent limit of detection (0.137 g/spot) and limit of quantification (0.41 g/spot). Using this quantitation method, we compared various lipid extraction methods and found that lipid extraction with methanol led to higher yield of erythrocyte sphingomyelin (135.35{+/-}1.04% recovery, compared to the Folch method). Application of these methods showed that erythrocytes from NAFLD patients (9 men, 15 women, 57.95{+/-}11.11 years old) contained statistically significantly less sphingomyelin (829.82{+/-}511.60 vs 1892.08{+/-}606.25 g/ml of packed erythrocytes) compared to healthy controls (4 men, 6 women, 39.3{+/-}15.55 years old).

biochemistry↗

bioRxiv2021

Intergenic ORFs as elementary structural modules of de novo gene birth and protein evolution

The noncoding genome plays an important role in de novo gene birth and in the emergence of genetic novelty. Nevertheless, how noncoding sequences properties could promote the birth of novel genes and shape the evolution and the structural diversity of proteins remains unclear. Therefore, by combining different bioinformatic approaches, we characterized the fold potential diversity of the amino acid sequences encoded by all intergenic ORFs (Open Reading Frames) of S. cerevisiae with the aim of (i) exploring whether the large structural diversity observed in proteomes is already present in noncoding sequences, and (ii) estimating the potential of the noncoding genome to produce novel protein bricks that can either give rise to novel genes or be integrated into pre-existing proteins, thus participating in protein structure diversity and evolution. We showed that amino acid sequences encoded by most yeast intergenic ORFs contain the elementary building blocks of protein structures. Moreover, they encompass the large structural diversity of canonical proteins with strikingly the majority predicted as foldable. Then, we investigated the early stages of de novo gene birth by identifying intergenic ORFs with a strong translation signal in ribosome profiling experiments and by reconstructing the ancestral sequences of 70 yeast de novo genes. This enabled us to highlight sequence and structural factors determining de novo gene emergence. Finally, we showed a strong correlation between the fold potential of de novo proteins and the one of their ancestral amino acid sequences, reflecting the relationship between the noncoding genome and the protein structure universe.

evolutionary biology↗