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  1. Article ; Online: Spatial transition tensor of single cells.

    Zhou, Peijie / Bocci, Federico / Li, Tiejun / Nie, Qing

    Nature methods

    2024  

    Abstract: Spatial transcriptomics and messenger RNA splicing encode extensive spatiotemporal information for cell states and transitions. The current lineage-inference methods either lack spatial dynamics for state transition or cannot capture different dynamics ... ...

    Abstract Spatial transcriptomics and messenger RNA splicing encode extensive spatiotemporal information for cell states and transitions. The current lineage-inference methods either lack spatial dynamics for state transition or cannot capture different dynamics associated with multiple cell states and transition paths. Here we present spatial transition tensor (STT), a method that uses messenger RNA splicing and spatial transcriptomes through a multiscale dynamical model to characterize multistability in space. By learning a four-dimensional transition tensor and spatial-constrained random walk, STT reconstructs cell-state-specific dynamics and spatial state transitions via both short-time local tensor streamlines between cells and long-time transition paths among attractors. Benchmarking and applications of STT on several transcriptome datasets via multiple technologies on epithelial-mesenchymal transitions, blood development, spatially resolved mouse brain and chicken heart development, indicate STT's capability in recovering cell-state-specific dynamics and their associated genes not seen using existing methods. Overall, STT provides a consistent multiscale description of single-cell transcriptome data across multiple spatiotemporal scales.
    Language English
    Publishing date 2024-05-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2169522-2
    ISSN 1548-7105 ; 1548-7091
    ISSN (online) 1548-7105
    ISSN 1548-7091
    DOI 10.1038/s41592-024-02266-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6022: Show issues Location:
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  2. Article ; Online: Tipping points in epithelial-mesenchymal lineages from single-cell transcriptomics data.

    Barcenas, Manuel / Bocci, Federico / Nie, Qing

    Biophysical journal

    2024  

    Abstract: Understanding cell fate decision-making during complex biological processes is an open challenge that is now aided by high-resolution single-cell sequencing technologies. Specifically, it remains challenging to identify and characterize transition states ...

    Abstract Understanding cell fate decision-making during complex biological processes is an open challenge that is now aided by high-resolution single-cell sequencing technologies. Specifically, it remains challenging to identify and characterize transition states corresponding to "tipping points" whereby cells commit to new cell states. Here, we present a computational method that takes advantage of single-cell transcriptomics data to infer the stability and gene regulatory networks (GRNs) along cell lineages. Our method uses the unspliced and spliced counts from single-cell RNA sequencing data and cell ordering along lineage trajectories to train an RNA splicing multivariate model, from which cell-state stability along the lineage is inferred based on spectral analysis of the model's Jacobian matrix. Moreover, the model infers the RNA cross-species interactions resulting in GRNs and their variation along the cell lineage. When applied to epithelial-mesenchymal transition in ovarian and lung cancer-derived cell lines, our model predicts a saddle-node transition between the epithelial and mesenchymal states passing through an unstable, intermediate cell state. Furthermore, we show that the underlying GRN controlling epithelial-mesenchymal transition rearranges during the transition, resulting in denser and less modular networks in the intermediate state. Overall, our method represents a flexible tool to study cell lineages with a combination of theory-driven modeling and single-cell transcriptomics data.
    Language English
    Publishing date 2024-03-19
    Publishing country United States
    Document type Journal Article
    ZDB-ID 218078-9
    ISSN 1542-0086 ; 0006-3495
    ISSN (online) 1542-0086
    ISSN 0006-3495
    DOI 10.1016/j.bpj.2024.03.021
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 235: Show issues Location:
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  3. Article: Editorial: Epithelial to Mesenchymal Plasticity in Colorectal Cancer.

    Bocci, Federico / Schneider-Stock, Regine / Banerjee, Sreeparna

    Frontiers in cell and developmental biology

    2022  Volume 10, Page(s) 950980

    Language English
    Publishing date 2022-06-23
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2737824-X
    ISSN 2296-634X
    ISSN 2296-634X
    DOI 10.3389/fcell.2022.950980
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  4. Article ; Online: Spatial-temporal order-disorder transition in angiogenic NOTCH signaling controls cell fate specification.

    Kang, Tae-Yun / Bocci, Federico / Nie, Qing / Onuchic, José N / Levchenko, Andre

    eLife

    2024  Volume 12

    Abstract: Angiogenesis is a morphogenic process resulting in the formation of new blood vessels from pre-existing ones, usually in hypoxic micro-environments. The initial steps of angiogenesis depend on robust differentiation of oligopotent endothelial cells into ... ...

    Abstract Angiogenesis is a morphogenic process resulting in the formation of new blood vessels from pre-existing ones, usually in hypoxic micro-environments. The initial steps of angiogenesis depend on robust differentiation of oligopotent endothelial cells into the Tip and Stalk phenotypic cell fates, controlled by NOTCH-dependent cell-cell communication. The dynamics of spatial patterning of this cell fate specification are only partially understood. Here, by combining a controlled experimental angiogenesis model with mathematical and computational analyses, we find that the regular spatial Tip-Stalk cell patterning can undergo an order-disorder transition at a relatively high input level of a pro-angiogenic factor VEGF. The resulting differentiation is robust but temporally unstable for most cells, with only a subset of presumptive Tip cells leading sprout extensions. We further find that sprouts form in a manner maximizing their mutual distance, consistent with a Turing-like model that may depend on local enrichment and depletion of fibronectin. Together, our data suggest that NOTCH signaling mediates a robust way of cell differentiation enabling but not instructing subsequent steps in angiogenic morphogenesis, which may require additional cues and self-organization mechanisms. This analysis can assist in further understanding of cell plasticity underlying angiogenesis and other complex morphogenic processes.
    MeSH term(s) Endothelial Cells ; Signal Transduction ; Cell Communication ; Morphogenesis ; Cell Differentiation
    Language English
    Publishing date 2024-02-20
    Publishing country England
    Document type Journal Article
    ZDB-ID 2687154-3
    ISSN 2050-084X ; 2050-084X
    ISSN (online) 2050-084X
    ISSN 2050-084X
    DOI 10.7554/eLife.89262
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  5. Article ; Online: spliceJAC: transition genes and state-specific gene regulation from single-cell transcriptome data.

    Bocci, Federico / Zhou, Peijie / Nie, Qing

    Molecular systems biology

    2022  Volume 18, Issue 11, Page(s) e11176

    Abstract: Extracting dynamical information from single-cell transcriptomics is a novel task with the promise to advance our understanding of cell state transition and interactions between genes. Yet, theory-oriented, bottom-up approaches that consider differences ... ...

    Abstract Extracting dynamical information from single-cell transcriptomics is a novel task with the promise to advance our understanding of cell state transition and interactions between genes. Yet, theory-oriented, bottom-up approaches that consider differences among cell states are largely lacking. Here, we present spliceJAC, a method to quantify the multivariate mRNA splicing from single-cell RNA sequencing (scRNA-seq). spliceJAC utilizes the unspliced and spliced mRNA count matrices to constructs cell state-specific gene-gene regulatory interactions and applies stability analysis to predict putative driver genes critical to the transitions between cell states. By applying spliceJAC to biological systems including pancreas endothelium development and epithelial-mesenchymal transition (EMT) in A549 lung cancer cells, we predict genes that serve specific signaling roles in different cell states, recover important differentially expressed genes in agreement with pre-existing analysis, and predict new transition genes that are either exclusive or shared between different cell state transitions.
    MeSH term(s) Humans ; Transcriptome ; Epithelial-Mesenchymal Transition/genetics ; Gene Expression Regulation ; RNA, Messenger/genetics ; A549 Cells
    Chemical Substances RNA, Messenger
    Language English
    Publishing date 2022-10-28
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
    ZDB-ID 2193510-5
    ISSN 1744-4292 ; 1744-4292
    ISSN (online) 1744-4292
    ISSN 1744-4292
    DOI 10.15252/msb.202211176
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  6. Article ; Online: Stochastic fluctuations promote ordered pattern formation of cells in the Notch-Delta signaling pathway.

    Galbraith, Madeline / Bocci, Federico / Onuchic, José N

    PLoS computational biology

    2022  Volume 18, Issue 7, Page(s) e1010306

    Abstract: The Notch-Delta signaling pathway mediates cell differentiation implicated in many regulatory processes including spatiotemporal patterning in tissues by promoting alternate cell fates between neighboring cells. At the multicellular level, this "lateral ... ...

    Abstract The Notch-Delta signaling pathway mediates cell differentiation implicated in many regulatory processes including spatiotemporal patterning in tissues by promoting alternate cell fates between neighboring cells. At the multicellular level, this "lateral inhibition" principle leads to checkerboard patterns with alternation of Sender and Receiver cells. While it is well known that stochasticity modulates cell fate specification, little is known about how stochastic fluctuations at the cellular level propagate during multicell pattern formation. Here, we model stochastic fluctuations in the Notch-Delta pathway in the presence of two different noise types-shot and white-for a multicell system. Our results show that intermediate fluctuations reduce disorder and guide the multicell lattice toward checkerboard-like patterns. By further analyzing cell fate transition events, we demonstrate that intermediate noise amplitudes provide enough perturbation to facilitate "proofreading" of disordered patterns and cause cells to switch to the correct ordered state (Sender surrounded by Receivers, and vice versa). Conversely, high noise can override environmental signals coming from neighboring cells and lead to switching between ordered and disordered patterns. Therefore, in analogy with spin glass systems, intermediate noise levels allow the multicell Notch system to escape frustrated patterns and relax towards the lower energy checkerboard pattern while at large noise levels the system is unable to find this ordered base of attraction.
    MeSH term(s) Cell Communication ; Cell Differentiation ; Receptors, Notch/metabolism ; Signal Transduction
    Chemical Substances Receptors, Notch
    Language English
    Publishing date 2022-07-21
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1010306
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  7. Article ; Online: Stochastic fluctuations promote ordered pattern formation of cells in the Notch-Delta signaling pathway.

    Madeline Galbraith / Federico Bocci / José N Onuchic

    PLoS Computational Biology, Vol 18, Iss 7, p e

    2022  Volume 1010306

    Abstract: The Notch-Delta signaling pathway mediates cell differentiation implicated in many regulatory processes including spatiotemporal patterning in tissues by promoting alternate cell fates between neighboring cells. At the multicellular level, this "lateral ... ...

    Abstract The Notch-Delta signaling pathway mediates cell differentiation implicated in many regulatory processes including spatiotemporal patterning in tissues by promoting alternate cell fates between neighboring cells. At the multicellular level, this "lateral inhibition" principle leads to checkerboard patterns with alternation of Sender and Receiver cells. While it is well known that stochasticity modulates cell fate specification, little is known about how stochastic fluctuations at the cellular level propagate during multicell pattern formation. Here, we model stochastic fluctuations in the Notch-Delta pathway in the presence of two different noise types-shot and white-for a multicell system. Our results show that intermediate fluctuations reduce disorder and guide the multicell lattice toward checkerboard-like patterns. By further analyzing cell fate transition events, we demonstrate that intermediate noise amplitudes provide enough perturbation to facilitate "proofreading" of disordered patterns and cause cells to switch to the correct ordered state (Sender surrounded by Receivers, and vice versa). Conversely, high noise can override environmental signals coming from neighboring cells and lead to switching between ordered and disordered patterns. Therefore, in analogy with spin glass systems, intermediate noise levels allow the multicell Notch system to escape frustrated patterns and relax towards the lower energy checkerboard pattern while at large noise levels the system is unable to find this ordered base of attraction.
    Keywords Biology (General) ; QH301-705.5
    Subject code 612
    Language English
    Publishing date 2022-07-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Historical Overview of the "Firing" Liaison between Brain Tumors and Epilepsy.

    Natale, Gianfranco / Cucchiara, Federico / Bocci, Guido

    The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry

    2021  Volume 28, Issue 5, Page(s) 411–419

    Abstract: This review addresses, in a critical historical perspective, the link between seizures and endocranic neoplasms. Folkloric descriptions of epilepsy can be found in writings from ancient cultures. Hippocrates first provided a medical interpretation. In ... ...

    Abstract This review addresses, in a critical historical perspective, the link between seizures and endocranic neoplasms. Folkloric descriptions of epilepsy can be found in writings from ancient cultures. Hippocrates first provided a medical interpretation. In 1770, Tissot published
    MeSH term(s) Humans ; Brain/pathology ; Brain Neoplasms/complications ; Brain Neoplasms/pathology ; Epilepsy/history ; History, 19th Century ; History, 20th Century ; Neurology/history ; Seizures
    Language English
    Publishing date 2021-02-10
    Publishing country United States
    Document type Historical Article ; Journal Article ; Review
    ZDB-ID 1233753-5
    ISSN 1089-4098 ; 1073-8584
    ISSN (online) 1089-4098
    ISSN 1073-8584
    DOI 10.1177/1073858421992316
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4315: Show issues Location:
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  9. Article ; Online: Theoretical and computational tools to model multistable gene regulatory networks.

    Bocci, Federico / Jia, Dongya / Nie, Qing / Jolly, Mohit Kumar / Onuchic, Jose

    ArXiv

    2023  

    Abstract: The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of ... ...

    Abstract The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.
    Language English
    Publishing date 2023-06-26
    Publishing country United States
    Document type Preprint
    ISSN 2331-8422
    ISSN (online) 2331-8422
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  10. Article ; Online: Theoretical and computational tools to model multistable gene regulatory networks.

    Bocci, Federico / Jia, Dongya / Nie, Qing / Jolly, Mohit Kumar / Onuchic, José

    Reports on progress in physics. Physical Society (Great Britain)

    2023  Volume 86, Issue 10

    Abstract: The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of ... ...

    Abstract The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.
    MeSH term(s) Gene Regulatory Networks ; Models, Biological ; Nonlinear Dynamics
    Language English
    Publishing date 2023-08-22
    Publishing country England
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 205657-4
    ISSN 1361-6633 ; 0034-4885
    ISSN (online) 1361-6633
    ISSN 0034-4885
    DOI 10.1088/1361-6633/acec88
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