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Fiorentino J, Armaos A, Colantoni A, Tartaglia G. Prediction of protein-RNA interactions from single-cell transcriptomic data. Nucleic Acids Res 2024; 52:e31. [PMID: 38364867 PMCID: PMC11014251 DOI: 10.1093/nar/gkae076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 01/12/2024] [Accepted: 01/26/2024] [Indexed: 02/18/2024] Open
Abstract
Proteins are crucial in regulating every aspect of RNA life, yet understanding their interactions with coding and noncoding RNAs remains limited. Experimental studies are typically restricted to a small number of cell lines and a limited set of RNA-binding proteins (RBPs). Although computational methods based on physico-chemical principles can predict protein-RNA interactions accurately, they often lack the ability to consider cell-type-specific gene expression and the broader context of gene regulatory networks (GRNs). Here, we assess the performance of several GRN inference algorithms in predicting protein-RNA interactions from single-cell transcriptomic data, and propose a pipeline, called scRAPID (single-cell transcriptomic-based RnA Protein Interaction Detection), that integrates these methods with the catRAPID algorithm, which can identify direct physical interactions between RBPs and RNA molecules. Our approach demonstrates that RBP-RNA interactions can be predicted from single-cell transcriptomic data, with performances comparable or superior to those achieved for the well-established task of inferring transcription factor-target interactions. The incorporation of catRAPID significantly enhances the accuracy of identifying interactions, particularly with long noncoding RNAs, and enables the identification of hub RBPs and RNAs. Additionally, we show that interactions between RBPs can be detected based on their inferred RNA targets. The software is freely available at https://github.com/tartaglialabIIT/scRAPID.
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Affiliation(s)
- Jonathan Fiorentino
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
| | - Alexandros Armaos
- Centre for Human Technologies (CHT), RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 16152 Genova, Italy
| | - Alessio Colantoni
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, 00185 Rome, Italy
| | - Gian Gaetano Tartaglia
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- Centre for Human Technologies (CHT), RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 16152 Genova, Italy
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Vandelli A, Arnal Segura M, Monti M, Fiorentino J, Broglia L, Colantoni A, Sanchez de Groot N, Torrent Burgas M, Armaos A, Tartaglia GG. The PRALINE database: protein and Rna humAn singLe nucleotIde variaNts in condEnsates. Bioinformatics 2023; 39:6967034. [PMID: 36592044 PMCID: PMC9825767 DOI: 10.1093/bioinformatics/btac847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 11/16/2022] [Accepted: 12/30/2022] [Indexed: 01/03/2023] Open
Abstract
SUMMARY Biological condensates are membraneless organelles with different material properties. Proteins and RNAs are the main components, but most of their interactions are still unknown. Here, we introduce PRALINE, a database for the interrogation of proteins and RNAs contained in stress granules, processing bodies and other assemblies including droplets and amyloids. PRALINE provides information about the predicted and experimentally validated protein-protein, protein-RNA and RNA-RNA interactions. For proteins, it reports the liquid-liquid phase separation and liquid-solid phase separation propensities. For RNAs, it provides information on predicted secondary structure content. PRALINE shows detailed information on human single-nucleotide variants, their clinical significance and presence in protein and RNA binding sites, and how they can affect condensates' physical properties. AVAILABILITY AND IMPLEMENTATION PRALINE is freely accessible on the web at http://praline.tartaglialab.com.
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Affiliation(s)
- Andrea Vandelli
- Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain,Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
| | - Magdalena Arnal Segura
- Center for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova 16152, Italy,Department of Biology and Biotechnologies, University Sapienza Rome, Roma 00185, Italy
| | - Michele Monti
- Center for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova 16152, Italy
| | - Jonathan Fiorentino
- Center for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova 16152, Italy
| | - Laura Broglia
- Center for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova 16152, Italy
| | - Alessio Colantoni
- Department of Biology and Biotechnologies, University Sapienza Rome, Roma 00185, Italy
| | - Natalia Sanchez de Groot
- Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
| | - Marc Torrent Burgas
- Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
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Nakatani T, Lin J, Ji F, Ettinger A, Pontabry J, Tokoro M, Altamirano-Pacheco L, Fiorentino J, Mahammadov E, Hatano Y, Van Rechem C, Chakraborty D, Ruiz-Morales ER, Arguello Pascualli PY, Scialdone A, Yamagata K, Whetstine JR, Sadreyev RI, Torres-Padilla ME. DNA replication fork speed underlies cell fate changes and promotes reprogramming. Nat Genet 2022; 54:318-327. [PMID: 35256805 PMCID: PMC8920892 DOI: 10.1038/s41588-022-01023-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 01/27/2022] [Indexed: 01/29/2023]
Abstract
Totipotency emerges in early embryogenesis, but its molecular underpinnings remain poorly characterized. In the present study, we employed DNA fiber analysis to investigate how pluripotent stem cells are reprogrammed into totipotent-like 2-cell-like cells (2CLCs). We show that totipotent cells of the early mouse embryo have slow DNA replication fork speed and that 2CLCs recapitulate this feature, suggesting that fork speed underlies the transition to a totipotent-like state. 2CLCs emerge concomitant with DNA replication and display changes in replication timing (RT), particularly during the early S-phase. RT changes occur prior to 2CLC emergence, suggesting that RT may predispose to gene expression changes and consequent reprogramming of cell fate. Slowing down replication fork speed experimentally induces 2CLCs. In vivo, slowing fork speed improves the reprogramming efficiency of somatic cell nuclear transfer. Our data suggest that fork speed regulates cellular plasticity and that remodeling of replication features leads to changes in cell fate and reprogramming. Totipotent cells in mouse embryos and 2-cell-like cells have slow DNA replication fork speed. Perturbations that slow replication fork speed promote 2-cell-like cell emergence and improve somatic cell nuclear transfer reprogramming and formation of induced pluripotent stem cell colonies.
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Abstract
Cellular heterogeneity is a property of any living system; however, its relationship with cellular fate decision remains an open question. Recent technological advances have enabled valuable insights, especially in complex systems such as the mouse embryo. In this review, we discuss recent studies that characterize cellular heterogeneity at different levels during mouse development, from the two-cell stage up to gastrulation. In addition to key experimental findings, we review mathematical modeling approaches that help researchers interpret these findings. Disentangling the role of heterogeneity in cell fate decision will likely rely on the refined integration of experiments, large-scale omics data, and mathematical modeling, complemented by the use of synthetic embryos and gastruloids as promising in vitro models.
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Affiliation(s)
- Jonathan Fiorentino
- Institute of Epigenetics and Stem Cells (IES), Helmholtz Zentrum München, D-81377 München, Germany; .,Institute of Functional Epigenetics (IFE) and Institute of Computational Biology (ICB), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
| | - Maria-Elena Torres-Padilla
- Institute of Epigenetics and Stem Cells (IES), Helmholtz Zentrum München, D-81377 München, Germany; .,Faculty of Biology, Ludwig-Maximilians Universität, D-82152 Planegg-Martinsried, Germany
| | - Antonio Scialdone
- Institute of Epigenetics and Stem Cells (IES), Helmholtz Zentrum München, D-81377 München, Germany; .,Institute of Functional Epigenetics (IFE) and Institute of Computational Biology (ICB), Helmholtz Zentrum München, D-85764 Neuherberg, Germany
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Abstract
Genetic regulatory circuits universally cope with different sources of noise that limit their ability to coordinate input and output signals. In many cases, optimal regulatory performance can be thought to correspond to configurations of variables and parameters that maximize the mutual information between inputs and outputs. Since the mid-2000s, such optima have been well characterized in several biologically relevant cases. Here we use methods of statistical field theory to calculate the statistics of the maximal mutual information (the "capacity") achievable by tuning the input variable only in an ensemble of regulatory motifs, such that a single controller regulates N targets. Assuming (i) sufficiently large N, (ii) quenched random kinetic parameters, and (iii) small noise affecting the input-output channels, we can accurately reproduce numerical simulations both for the mean capacity and for the whole distribution. Our results provide insight into the inherent variability in effectiveness occurring in regulatory systems with heterogeneous kinetic parameters.
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Affiliation(s)
- Andrea Crisanti
- Dipartimento di Fisica, Sapienza Università di Roma, piazzale Aldo Moro 5, 00185 Rome, Italy.,Istituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, P.le Aldo Moro 2, 00185 Rome, Italy
| | - Andrea De Martino
- Soft and Living Matter Lab, Institute of Nanotechnology (CNR-NANOTEC), Consiglio Nazionale delle Ricerche, piazzale Aldo Moro 2, 00185 Rome, Italy.,Italian Institute for Genomic Medicine,Via Nizza 52, 10126 Turin, Italy
| | - Jonathan Fiorentino
- Dipartimento di Fisica, Sapienza Università di Roma, piazzale Aldo Moro 5, 00185 Rome, Italy
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Fiorentino J, De Martino A. Independent channels for miRNA biosynthesis ensure efficient static and dynamic control in the regulation of the early stages of myogenesis. J Theor Biol 2017; 430:53-63. [PMID: 28689889 DOI: 10.1016/j.jtbi.2017.06.038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Revised: 05/30/2017] [Accepted: 06/29/2017] [Indexed: 12/21/2022]
Abstract
Motivated by recent experimental work, we define and study a deterministic model of the complex miRNA-based regulatory circuit that putatively controls the early stage of myogenesis in human. We aim in particular at a quantitative understanding of (i) the roles played by the separate and independent miRNA biosynthesis channels (one involving a miRNA-decoy system regulated by an exogenous controller, the other given by transcription from a distinct genomic locus) that appear to be crucial for the differentiation program, and of (ii) how competition to bind miRNAs can efficiently control molecular levels in such an interconnected architecture. We show that optimal static control via the miRNA-decoy system constrains kinetic parameters in narrow ranges where the channels are tightly cross-linked. On the other hand, the alternative locus for miRNA transcription can ensure that the fast concentration shifts required by the differentiation program are achieved, specifically via non-linear response of the target to even modest surges in the miRNA transcription rate. While static, competition-mediated regulation can be achieved by the miRNA-decoy system alone, both channels are essential for the circuit's overall functionality, suggesting that that this type of joint control may represent a minimal optimal architecture in different contexts.
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Affiliation(s)
| | - Andrea De Martino
- Soft & Living Matter Lab, CNR-NANOTEC, Rome, Italy; Italian Institute for Genomic Medicine, Turin, Italy.
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Ayoubi M, Kantarjian H, Cortes JE, Faderl S, Garcia-Manero G, Wen S, Fiorentino J, Huang X, Luthra R, Ravandi Kashani F. Dynamic of morphologic and molecular remission in patients (pts) with APL treated with frontline ATRA and arsenic trioxide (ATO). J Clin Oncol 2010. [DOI: 10.1200/jco.2010.28.15_suppl.6548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Garcia-Manero G, Kantarjian H, Sanchez-Gonzalez B, Verstovsek S, Ravandi F, Ryttling M, Cortes J, Yang H, Fiorentino J, Rosner G, Issa JP. Results of a phase I/II study of the combination of 5-aza-2’-deoxycytidine and valproic acid in patients with acute myeloid leukemia and myelodysplastic syndrome. J Clin Oncol 2005. [DOI: 10.1200/jco.2005.23.16_suppl.6544] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
- G. Garcia-Manero
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - H. Kantarjian
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - B. Sanchez-Gonzalez
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - S. Verstovsek
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - F. Ravandi
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - M. Ryttling
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - J. Cortes
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - H. Yang
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - J. Fiorentino
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - G. Rosner
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
| | - J.-P. Issa
- Univ of Texas MD Anderson Cancer Ctr, Houston, TX; Univ of Texas M. D. Anderson Cancer Ctr, Houston, TX
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Germain MJ, Lipkowitz GS, Guarnera J, Fiorentino J. A comparison of different methods of estimating glomerular filtration rate in cyclosporine-treated renal transplant patients. Transplantation 1993; 55:203-5. [PMID: 8420049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Affiliation(s)
- M J Germain
- Department of Medicine, Baystate Medical Center, Springfield, Massachusetts 01199
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