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Towlson EK, Barabási AL. Synthetic ablations in the C. elegans nervous system. Netw Neurosci 2020; 4:200-216. [PMID: 32166208 PMCID: PMC7055645 DOI: 10.1162/netn_a_00115] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Accepted: 11/12/2019] [Indexed: 01/03/2023] Open
Abstract
Synthetic lethality, the finding that the simultaneous knockout of two or more individually nonessential genes leads to cell or organism death, has offered a systematic framework to explore cellular function, and also offered therapeutic applications. Yet the concept lacks its parallel in neuroscience—a systematic knowledge base on the role of double or higher order ablations in the functioning of a neural system. Here, we use the framework of network control to systematically predict the effects of ablating neuron pairs and triplets on the gentle touch response. We find that surprisingly small sets of 58 pairs and 46 triplets can reduce muscle controllability in this context, and that these sets are localized in the nervous system in distinct groups. Further, they lead to highly specific experimentally testable predictions about mechanisms of loss of control, and which muscle cells are expected to experience this loss. “Synthetic lethality” in cell biology is an extreme example of the effects of higher order genetic interactions: The simultaneous knockout of two or more individually nonessential genes leads to cell death. We define a neural analog to this concept in relation to the locomotor response to gentle touch in C. elegans. Two or more neurons are synthetic essential if individually they are not required for this behavior, yet their combination is. We employ a network control approach to systematically assess all pairs and triplets of neurons by their effect on body wall muscle controllability, and find that only surprisingly small sets of neurons are synthetic essential. They are highly localized in the nervous system and predicted to affect control over specific sets of muscles.
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Affiliation(s)
- Emma K Towlson
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA, USA
| | - Albert-László Barabási
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA, USA
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Towlson EK, Vértes PE, Yan G, Chew YL, Walker DS, Schafer WR, Barabási AL. Caenorhabditis elegans and the network control framework-FAQs. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170372. [PMID: 30201837 PMCID: PMC6158218 DOI: 10.1098/rstb.2017.0372] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/10/2018] [Indexed: 12/31/2022] Open
Abstract
Control is essential to the functioning of any neural system. Indeed, under healthy conditions the brain must be able to continuously maintain a tight functional control between the system's inputs and outputs. One may therefore hypothesize that the brain's wiring is predetermined by the need to maintain control across multiple scales, maintaining the stability of key internal variables, and producing behaviour in response to environmental cues. Recent advances in network control have offered a powerful mathematical framework to explore the structure-function relationship in complex biological, social and technological networks, and are beginning to yield important and precise insights on neuronal systems. The network control paradigm promises a predictive, quantitative framework to unite the distinct datasets necessary to fully describe a nervous system, and provide mechanistic explanations for the observed structure and function relationships. Here, we provide a thorough review of the network control framework as applied to Caenorhabditis elegans (Yan et al. 2017 Nature550, 519-523. (doi:10.1038/nature24056)), in the style of Frequently Asked Questions. We present the theoretical, computational and experimental aspects of network control, and discuss its current capabilities and limitations, together with the next likely advances and improvements. We further present the Python code to enable exploration of control principles in a manner specific to this prototypical organism.This article is part of a discussion meeting issue 'Connectome to behaviour: modelling C. elegans at cellular resolution'.
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Affiliation(s)
- Emma K Towlson
- Center for Complex Network Research and Department of Physics, Northeastern University, Boston, MA 02115, USA
| | - Petra E Vértes
- Department of Psychiatry, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Gang Yan
- Center for Complex Network Research and Department of Physics, Northeastern University, Boston, MA 02115, USA
- School of Physics Science and Engineering, Tongji University, Shanghai 200092, People's Republic of China
| | - Yee Lian Chew
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Denise S Walker
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - William R Schafer
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Albert-László Barabási
- Center for Complex Network Research and Department of Physics, Northeastern University, Boston, MA 02115, USA
- Center for Cancer Systems Biology, Dana Farber Cancer Institute, Boston, MA 02115, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Center for Network Science, Central European University, Budapest 1051, Hungary
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Liu H, Kim J, Shlizerman E. Functional connectomics from neural dynamics: probabilistic graphical models for neuronal network of Caenorhabditis elegans. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170377. [PMID: 30201841 PMCID: PMC6158227 DOI: 10.1098/rstb.2017.0377] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/16/2018] [Indexed: 12/26/2022] Open
Abstract
We propose an approach to represent neuronal network dynamics as a probabilistic graphical model (PGM). To construct the PGM, we collect time series of neuronal responses produced by the neuronal network and use singular value decomposition to obtain a low-dimensional projection of the time-series data. We then extract dominant patterns from the projections to get pairwise dependency information and create a graphical model for the full network. The outcome model is a functional connectome that captures how stimuli propagate through the network and thus represents causal dependencies between neurons and stimuli. We apply our methodology to a model of the Caenorhabditis elegans somatic nervous system to validate and show an example of our approach. The structure and dynamics of the C. elegans nervous system are well studied and a model that generates neuronal responses is available. The resulting PGM enables us to obtain and verify underlying neuronal pathways for known behavioural scenarios and detect possible pathways for novel scenarios.This article is part of a discussion meeting issue 'Connectome to behaviour: modelling C. elegans at cellular resolution'.
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Affiliation(s)
- Hexuan Liu
- Department of Applied Mathematics, University of Washington, Seattle, WA 98195, USA
| | - Jimin Kim
- Department of Electrical Engineering, University of Washington, Seattle, WA 98195, USA
| | - Eli Shlizerman
- Department of Applied Mathematics, University of Washington, Seattle, WA 98195, USA
- Department of Electrical Engineering, University of Washington, Seattle, WA 98195, USA
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The role of gap junctions in the C. elegans connectome. Neurosci Lett 2017; 695:12-18. [PMID: 28886984 DOI: 10.1016/j.neulet.2017.09.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 07/12/2017] [Accepted: 09/01/2017] [Indexed: 10/18/2022]
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Zhen M, Samuel ADT. C. elegans locomotion: small circuits, complex functions. Curr Opin Neurobiol 2015; 33:117-26. [PMID: 25845627 DOI: 10.1016/j.conb.2015.03.009] [Citation(s) in RCA: 113] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2015] [Revised: 03/18/2015] [Accepted: 03/18/2015] [Indexed: 12/20/2022]
Abstract
With 302 neurons in the adult Caenorhabditis elegans nervous system, it should be possible to build models of complex behaviors spanning sensory input to motor output. The logic of the motor circuit is an essential component of such models. Advances in physiological, anatomical, and neurogenetic analysis are revealing a surprisingly complex signaling network in the worm's small motor circuit. We are progressing towards a systems level dissection of the network of premotor interneurons, motor neurons, and muscle cells that move the animal forward and backward in its environment.
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Affiliation(s)
- Mei Zhen
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada M5G 1X5; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada M5S 1A8; Department of Physiology, University of Toronto, Toronto, ON, Canada M5S 1A8.
| | - Aravinthan D T Samuel
- Center for Brain Science, Department of Physics, Harvard University, Cambridge, MA 02138, United States.
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Gjorgjieva J, Biron D, Haspel G. Neurobiology of Caenorhabditis elegans Locomotion: Where Do We Stand? Bioscience 2014; 64:476-486. [PMID: 26955070 PMCID: PMC4776678 DOI: 10.1093/biosci/biu058] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Animals use a nervous system for locomotion in some stage of their life cycle. The nematode Caenorhabditis elegans, a major animal model for almost all fields of experimental biology, has long been used for detailed studies of genetic and physiological locomotion mechanisms. Of its 959 somatic cells, 302 are neurons that are identifiable by lineage, location, morphology, and neurochemistry in every adult hermaphrodite. Of those, 75 motoneurons innervate body wall muscles that provide the thrust during locomotion. In this Overview, we concentrate on the generation of either forward- or backward-directed motion during crawling and swimming. We describe locomotion behavior, the parts constituting the locomotion system, and the relevant neuronal connectivity. Because it is not yet fully understood how these components combine to generate locomotion, we discuss competing hypotheses and models.
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Affiliation(s)
- Julijana Gjorgjieva
- Julijana Gjorgjieva is a postdoctoral research fellow at the Center for Brain Science of Harvard University, in Cambridge, Massachusetts. She uses theoretical and numerical tools to understand how developing neural circuits wire to perform a particular function, from the mammalian visual system to the motor system of small invertebrates. David Biron is a physicist at the University of Chicago, Illinois. He studies the sleep of the roundworm Caenorhabditis elegans and related problems in biological physics. Gal Haspel ( ) is a neuroethologist at the New Jersey Institute of Technology, in Newark. He studies the activity, connectivity and recovery from injury of the neuronal network that underlie locomotion in the nematode Caenorhabditis elegans
| | - David Biron
- Julijana Gjorgjieva is a postdoctoral research fellow at the Center for Brain Science of Harvard University, in Cambridge, Massachusetts. She uses theoretical and numerical tools to understand how developing neural circuits wire to perform a particular function, from the mammalian visual system to the motor system of small invertebrates. David Biron is a physicist at the University of Chicago, Illinois. He studies the sleep of the roundworm Caenorhabditis elegans and related problems in biological physics. Gal Haspel ( ) is a neuroethologist at the New Jersey Institute of Technology, in Newark. He studies the activity, connectivity and recovery from injury of the neuronal network that underlie locomotion in the nematode Caenorhabditis elegans
| | - Gal Haspel
- Julijana Gjorgjieva is a postdoctoral research fellow at the Center for Brain Science of Harvard University, in Cambridge, Massachusetts. She uses theoretical and numerical tools to understand how developing neural circuits wire to perform a particular function, from the mammalian visual system to the motor system of small invertebrates. David Biron is a physicist at the University of Chicago, Illinois. He studies the sleep of the roundworm Caenorhabditis elegans and related problems in biological physics. Gal Haspel ( ) is a neuroethologist at the New Jersey Institute of Technology, in Newark. He studies the activity, connectivity and recovery from injury of the neuronal network that underlie locomotion in the nematode Caenorhabditis elegans
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Cohen N, Sanders T. Nematode locomotion: dissecting the neuronal-environmental loop. Curr Opin Neurobiol 2014; 25:99-106. [PMID: 24709607 DOI: 10.1016/j.conb.2013.12.003] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2013] [Revised: 11/01/2013] [Accepted: 12/05/2013] [Indexed: 10/25/2022]
Abstract
With a fully reconstructed and extensively characterized neural circuit, the nematode Caenorhabditis elegans is a promising model system for integrating our understanding of neuronal, circuit and whole-animal dynamics. Fundamental to addressing this challenge is the need to consider the tight neuronal-environmental coupling that allows the animal to survive and adapt to changing conditions. Locomotion behaviors are affected by environmental variables both at the biomechanical level and via adaptive sensory responses that drive and modulate premotor and motor circuits. Here we review significant advances in our understanding of proprioceptive control of locomotion, and more abstract models of spatial orientation and navigation. The growing evidence of the complexity of the underlying circuits suggests that the intuition gained is but the first step in elucidating the secrets of neural computation in this relatively simple system.
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Affiliation(s)
- Netta Cohen
- School of Computing, University of Leeds, Leeds LS2 9JT, United Kingdom.
| | - Tom Sanders
- School of Computing, University of Leeds, Leeds LS2 9JT, United Kingdom
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