Biology subjects

Pesole, G.

Publications and source records attributed to Pesole, G..

11 recordsLinked to original sources

bioRxiv2026

Intercellular Transfer of PTBP1 Drives Human Neural Stem Cell Fate

During fetal brain development, temporally defined alternative splicing (AS) programs control human neural stem cell (hNSC) self-renewal and differentiation, thereby regulating neurogenesis and gliogenesis. Polypyrimidine tract-binding protein 1 (PTBP1) is a master regulator of AS during neurogenesis; however, its functional role and dynamics in hNSCs remain largely unexplored. Here, we investigate the cellular and molecular functions, nucleocytoplasmic distribution, and intercellular trafficking of PTBP1 in primary hNSCs. We found that PTBP1 knockdown (KD) alters self-renewal capacity, mitochondrial dynamics and membrane potential, lipid droplet abundance, and PTBP2 expression. RNA sequencing analysis revealed that PTBP1 depletion affects the expression profiling of hundreds of coding and non-coding genes, collectively orchestrating a neuronal differentiation program. Super-resolution {tau}-STED microscopy and live-cell imaging demonstrated that PTBP1 localizes not only to the nucleus but also to the cytoplasm, tunneling nanotubes (TNTs), migrasomes, and extracellular vesicles (EVs). Co-culture experiments and EV uptake assays showed that cytosolic PTBP1 can be transferred between hNSCs and delivered to the nuclei of recipient cells via TNTs and EVs. Moreover, EVs were found to contain specific and previously uncharacterized PTBP1 isoforms and were efficiently transferred to PTBP1-KD cells, rescuing their proliferative capacity. Analysis of the mouse brain reveals the presence of PTBP1 in the V-SVZ and within TNT-like structures connecting NSCs, suggesting a role for TNT-mediated PTBP1 trafficking in vivo. Together, these findings uncover previously unrecognized roles for PTBP1 in hNSCs and provide the first evidence that PTBP1 can be transferred between hNSCs via TNTs and EVs, revealing a novel mechanism by which hNSCs may regulate fetal neurogenesis. Graphical AbstractA: PTBP1 regulates hNSC fate by controlling cell proliferation, lipid droplet dynamics, mitochondrial function, and post-transcriptional programs involved in neuronal commitment. B: Cytosolic PTBP1 is transferred between hNSCs via tunneling nanotubes (TNTs) and extracellular vesicles (EVs). Abbreviations: LV, lateral ventricle; aRG, apical radial glial cells; bRG, basal radial glial cells; V-SVZ, ventricular-subventricular zone; EVs, extracellular vesicles; TNTs, tunneling nanotubes.

neuroscience↗

bioRxiv2022

Dealing with the promise of metabarcoding in mega-event biomonitoring: EXPO2015 unedited data

As human activities on our planet persist, causing widespread and irreversible environmental degradation, the need to biomonitor ecosystems has never been more pressing. These circumstances have required a renewal in monitoring techniques, encouraged by necessity to develop more rapid and accurate tools which will support timely observations of ecosystem structure and function. The World Exposition (from now EXPO2015) hosted in Milan from May to October 2015 was a global event that could be categorized as a mega-event, which can be defined as an acute environmental stressor, possibly generating biodiversity alteration and disturbance. During the six months of EXPO2015, exhibitors from more than 135 countries and 22 million visitors insisted on a 1.1 million square meters area. Faced with such a massive event, we explore the potential of DNA metabarcoding using three molecular markers to improve the understanding of anthropogenic impacts in the area, both considering air and water monitoring. Furthermore, we explore the effectiveness of the taxonomy assignment phase considering different taxonomic levels of analysis and the use of data mining approaches to predict sample origin. Unless the degree of taxa identification still remains open, our results showed that DNA metabarcoding is a powerful genomic-based tool to monitor biodiversity at the microscale, allowing us to capture exact fingerprints of specific event sites and to explore in a comprehensive manner the eukaryotic community alteration. With this work, we aim to disentangle and overcome the crucial issues related to the generalization of DNA metabarcoding in order to support future applications.

molecular biology↗

bioRxiv2021

Natural and after colon washing fecal samples: the two sides of the coin for investigating the human gut microbiome

To date there are several studies focusing on the importance of gut microbiome for human health, however the selection of a universal sampling matrix representative of the microbial biodiversity associated to the gastrointestinal (GI) tract, still represents a challenge. Here we present a study in which, through a deep metabarcoding analysis of the 16S rRNA gene, we compared two sampling matrices, feces (F) and colonic lavage liquid (LL), in order to evaluate their accuracy to represent the complexity of the human gut microbiome. A training set of 37 volunteers was attained and paired F and LL samples were collected from each subject. A preliminary absolute quantification of total 16S rDNA, performed by droplet digital PCR (ddPCR), confirmed that sequencing and taxonomic analysis were performed on same total bacterial abundance obtained from the two sampling methods. The taxonomic analysis of paired samples revealed that, although specific taxa were predominantly or exclusively observed in LL samples, as well as other taxa were detectable only or were predominant in stool, the microbiomes of the paired samples F and LL in the same subject hold overlapping taxonomic composition. Moreover, LL samples revealed a higher biodiversity than stool at all taxonomic ranks, as demonstrated by the Shannon Index and the Inverse Simpsons Index. We also found greater inter-individual variability than intra-individual variability in both sample matrices. Finally, functional differences were unveiled in the gut microbiome detected in the F and LL samples. A significant overrepresentation of 22 and 13 metabolic pathways, mainly occurring in Firmicutes and Proteobacteria, was observed in gut microbiota detected in feces and LL samples, respectively. This suggests that LL samples may allow for the detection of microbes adhering to the intestinal mucosal surface as members of the resident flora that are not easily detectable in stool, most likely representative of a diet-influenced transient microbiota. This first comparative study on feces and LL samples for the study of the human gut microbiome demonstrates that the use of both types of sample matrices may represent a possible choice to obtain a more complete view of the human gut microbiota in response to different biological and clinical questions.

molecular biology↗

bioRxiv2021

Unsupervised classification of SARS-CoV-2 genomic sequences uncovers hidden genetic diversity and suggests an efficient strategy for genomic surveillance

Accurate and timely monitoring of emerging genomic diversity is crucial for limiting the spread of potentially more transmissible/pathogenic strains of SARS-CoV-2. At the time of writing, over 1.8M distinct viral genome sequences have been made publicly available, and a sophisticated nomenclature system based on phylogenetic evidence and expert manual curation has allowed the relatively rapid classification of emerging lineages of potential concern. Here, we propose a complementary approach that integrates fine-grained spatiotemporal estimates of allele frequency with unsupervised clustering of viral haplotypes, and demonstrate that multiple highly frequent genetic variants, arising within large and/or rapidly expanding SARS-CoV-2 lineages, have highly biased geographic distributions and are not adequately captured by current SARS-CoV-2 nomenclature standards. Our results advocate a partial revision of current methods used to track SARS-CoV-2 genomic diversity and highlight the importance of the application of strategies based on the systematic analysis and integration of regional data. Here we provide a complementary, completely automated and reproducible framework for the mapping of genetic diversity in time and across different geographic regions, and for the prioritization of virus variants of potential concern. We believe that the approach outlined in this study will contribute to relevant advances to current genomic surveillance methods.

genomics↗

bioRxiv2021

Loss of C3aR induces immune infiltration and inflammatory microbiota in a novel spontaneous model of colon cancer

Several lines of evidence suggest that inflammation plays a pivotal role in the development and progression of colorectal cancer (CRC) and can be unleashed by the loss of innate immunosurveillance. The complement system is a well characterized first line of defense against pathogens and a central component of the immune response. Emerging evidence suggests that complement anaphylatoxin C3a produced upon complement activation and acting via its receptor (C3aR) may play a role in intestinal homeostasis. However, to date, it is unknown whether and how the C3a/C3aR axis can affect CRC. By mining publicly available datasets, we found that CpG island methylation of c3ar1 occurs in CRC patients and is associated with significant downregulation of C3aR. By reverse-translating this finding we were able to shift in APCMin/+ mice the tumorigenesis from the small intestine to the colon therefore generating a novel mouse model, which more closely mirrors the CRC in humans. Transcriptomic analysis on colorectal polyps from our newly developed genetic mouse model revealed a significant increase in innate and adaptive immune signatures in absence of C3aR. Furthermore, loss of C3aR significantly impacted the fecal and tumor-associated microbiota and supported the blooming of pro-inflammatory bacterial species as confirmed by experiments of fecal microbiota transplantation. Future studies will elucidate whether loss of C3aR can be exploited as a biomarker for sub-groups of CRC and whether the C3a/C3aR axis may be exploited for the generation of more effective therapeutic interventions.

immunology↗

bioRxiv2020

A-to-I RNA editing in SARS-COV-2: real or artifact?

ADAR1-mediated deamination of adenosines in long double stranded RNAs plays an important role in modulating the innate immune response. However, recent investigations based on metatranscriptomic samples of COVID-19 patients and SARS-COV-2 infected Vero cells have recovered contrasting findings. Using RNAseq data from time course experiments of infected human cell lines and transcriptome data from Vero cells and clinical samples, we prove that A-to-G changes observed in SARS-COV-2 genomes represent genuine RNA editing events, likely mediated by ADAR1. While the A-to-I editing rate is generally low, changes are distributed along the entire viral genome, are overrepresented in exonic regions and are, in the majority of cases, nonsynonymous. The impact of RNA editing on virus-host interactions could be relevant to identify potential targets for therapeutic interventions.

genomics↗

bioRxiv2020

Comparative genomic provides an operational classification system and reveals early emergence and spatio-temporal

Effective systems for the analysis of molecular data are of fundamental importance for real-time monitoring of the spread of infectious diseases and the study of pathogen evolution. While the Nextstrain and GISAID portals offer widely used systems for the classification of SARS-CoV-2 genomes, both present relevant limitations. Here we propose a highly reproducible method for the systematic classification of SARS-CoV-2 viral types. To demonstrate the validity of our approach, we conduct an extensive comparative genomic analysis of more than 20,000 SARS-CoV-2 genomes. Our classification system delineates 12 clusters and 4 super-clusters in SARS-CoV-2, with a highly biased spatio-temporal distribution worldwide, and provides important observations concerning the evolutionary processes associated with the emergence of novel viral types. Based on the estimates of SARS-CoV-2 evolutionary rate and genetic distances of genomes of the early pandemic phase, we infer that SARS-CoV-2 could have been circulating in humans since August-November 2019. The observed pattern of genomic variability is remarkably similar between all clusters and super-clusters, being UTRs and the s2m element, a highly conserved secondary structure element, the most variable genomic regions. While several polymorphic sites that are specific to one or more clusters were predicted to be under positive or negative selection, overall, our analyses also suggest that the emergence of novel genome types is unlikely to be driven by widespread convergent evolution and independent fixation of advantageous substitutions. While, in the absence of rigorous experimental validation, several questions concerning the evolutionary processes and the phenotypic characteristics (increased/decreased virulence) remain open, we believe that the approach outlined in this study can be of relevance for the tracking and functional characterization of different types of SARS-CoV-2 genomes.

genomics↗

bioRxiv2020

HPC-REDItools: a Novel HPC-aware Tool for Improved Large Scale RNA-editing Analysis

BackgroundRNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. ResultsIn this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2. ConclusionsHPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores.

bioinformatics↗

bioRxiv2020

Comparative genomics suggests limited variability and similar evolutionary patterns between major clades of SARS-Cov-2

Phylogenomic analysis of SARS-CoV-2 as available from publicly available repositories suggests the presence of 3 prevalent groups of viral episomes (super-clades), which are mostly associated with outbreaks in distinct geographic locations (China, USA and Europe). While levels of genomic variability between SARS-CoV-2 isolates are limited, to our knowledge, it is not clear whether the observed patterns of variability in viral super-clades reflect ongoing adaptation of SARS-CoV-2, or merely genetic drift and founder effects. Here, we analyze more than 1100 complete, high quality SARS-CoV-2 genome sequences, and provide evidence for the absence of distinct evolutionary patterns/signatures in the genomes of the currently known major clades of SARS-CoV-2. Our analyses suggest that the presence of distinct viral episomes at different geographic locations are consistent with founder effects, coupled with the rapid spread of this novel virus. We observe that while cross species adaptation of the virus is associated with hypervariability of specific protein coding regions (including the RDB domain of the spike protein), the more variable genomic regions between extant SARS-CoV-2 episomes correspond with the 3 and 5 UTRs, suggesting that at present viral protein coding genes should not be subjected to different adaptive evolutionary pressures in different viral strains. Although this study can not be conclusive, we believe that the evidence presented here is strongly consistent with the notion that the biased geographic distribution of SARS-CoV-2 isolates should not be associated with adaptive evolution of this novel pathogen.

genomics↗

bioRxiv2020

VINYL: Variant prIoritizatioN bY survivaL analysis

MotivationClinical applications of genome re-sequencing technologies typically generate large amounts of data that need to be carefully annotated and interpreted to identify genetic variants associated with pathological conditions. In this context, accurate and reproducible methods for the functional annotation and prioritization of genetic variants are of fundamental importance, especially when large volumes of data - like those produced by modern sequencing technologies - are involved. ResultsIn this paper, we present VINYL, a highly accurate and fully automated system for the functional annotation and prioritization of genetic variants in large scale clinical studies. Extensive analyses of both real and simulated datasets suggest that VINYL show higher accuracy and sensitivity when compared to equivalent state of the art methods, allowing the rapid and systematic identification of potentially pathogenic variants in different experimental settings.

bioinformatics↗

bioRxiv2018

Laniakea: an open solution to provide Galaxy \"on-demand\" instances over heterogeneous cloud infrastructures.

BackgroundGalaxy is rapidly becoming the de facto standard among workflow managers for bioinformatics. A rich feature set, its overall flexibility, and a thriving community of enthusiastic users are among the main factors contributing to the popularity of Galaxy and Galaxy based applications. One of the main advantages of Galaxy consists in providing access to sophisticated analysis pipelines, e.g., involving numerous steps and large data sets, even to users lacking computer proficiency, while at the same time improving reproducibility and facilitating teamwork and data sharing among researchers. Although several Galaxy public services are currently available, these resources are often overloaded with a large number of jobs and offer little or no customization options to end users. Moreover, there are scenarios where a private Galaxy instance still constitutes a more viable alternative, including, but not limited to, heavy workloads, data privacy concerns or particular needs of customization. In such cases, a cloud-based virtual Galaxy instance can represent a solution that overcomes the typical burdens of managing the local hardware and software infrastructure needed to run and maintain a production-grade Galaxy service.\n\nResultsHere we present Laniakea, a robust and feature-rich software suite which can be deployed on any scientific or commercial Cloud infrastructure in order to provide a \"Galaxy on demand\" Platform as a Service (PaaS). Laying its foundations on the INDIGO-DataCloud middleware, which has been developed to accommodate the needs of a large number of scientific communities, Laniakea can be deployed and provisioned over multiple architectures by private or public e-infrastructures. The end user interacts with Laniakea through a front-end that allows a general setup of the Galaxy instance, then Laniakea takes charge of the deployment both of the virtual hardware and all the software components. At the end of the process the user has access to a private, production-grade, yet fully customizable, Galaxy virtual instance. Laniakeas supports the deployment of plain or cluster backed Galaxy instances, shared reference data volumes, encrypted data volumes and rapid development of novel Galaxy flavours, that is Galaxy configurations tailored for specific tasks. As a proof of concept, we provide a demo Laniakea instance hosted at an ELIXIR-IT Cloud facility.\n\nConclusionsThe migration of scientific computational services towards virtualization and e-infrastructures is one of the most visible trends of our times. Laniakea provides Cloud administrators with a ready-to-use software suite that enables them to offer Galaxy, a popular workflow manager for bioinformatics, as an on-demand PaaS to their users. We believe that Laniakea can concur in making the many advantages of using Galaxy more accessible to a broader user base by removing most of the burdens involved in running a private instance. Finally, Laniakeas design is sufficiently general and modular that could be easily adapted to support different services and platforms beyond Galaxy.

bioinformatics↗