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Genome-scale identification of cellular pathways required for cell surface recognition.

ABSTRACT: Interactions mediated by cell surface receptors initiate important instructive signaling cues but can be difficult to detect in biochemical assays because they are often highly transient and membrane-embedded receptors are difficult to solubilize in their native conformation. Here, we address these biochemical challenges by using a genome-scale, cell-based genetic screening approach using CRISPR gene knockout technology to identify cellular pathways required for specific cell surface recognition events. By using high-affinity monoclonal antibodies and low-affinity ligands, we determined the necessary screening parameters, including the importance of establishing binding contributions from the glycocalyx, that permitted the unequivocal identification of genes encoding directly interacting membrane-embedded receptors with high statistical confidence. Importantly, we show that this genome-wide screening approach additionally identified receptor-specific pathways that are required for functional display of receptors on the cell surface that included chaperones, enzymes that add post-translational modifications, trafficking proteins, and transcription factors. Finally, we demonstrate the utility of the approach by identifying IGF2R (insulin like growth factor 2 receptor) as a binding partner for the R2 subunit of GABAB receptors. We show that this interaction is direct and is critically dependent on mannose-6-phosphate, providing a mechanism for the internalization and regulation of GABAB receptor signaling. We conclude that this single approach can reveal both the molecular nature and the genetic pathways required for functional cell surface display of receptors recognized by antibodies, secreted proteins, and membrane-embedded ligands without the need to make any prior assumptions regarding their biochemical properties.

SUBMITTER: Sharma S

PROVIDER: S-EPMC6120632 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Genome-scale identification of cellular pathways required for cell surface recognition.

Sharma Sumana S Bartholdson S Josefin SJ Couch Amalie C M ACM Yusa Kosuke K Wright Gavin J GJ

Genome research 20180618 9

Interactions mediated by cell surface receptors initiate important instructive signaling cues but can be difficult to detect in biochemical assays because they are often highly transient and membrane-embedded receptors are difficult to solubilize in their native conformation. Here, we address these biochemical challenges by using a genome-scale, cell-based genetic screening approach using CRISPR gene knockout technology to identify cellular pathways required for specific cell surface recognition ...[more]

PMID: 29914970

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Project description:Virus binding to the cell surface triggers an array of host responses, including activation of specific signaling pathways that facilitate steps in virus entry. Using mouse polyomavirus (MuPyV), we identified host signaling pathways activated upon virus binding to mouse embryonic fibroblasts (MEFs). Pathways activated by MuPyV included the phosphatidylinositol 3-kinase (PI3K), FAK/SRC, and mitogen-activated protein kinase (MAPK) pathways. Gangliosides and α4-integrin are required receptors for MuPyV infection. MuPyV binding to both gangliosides and the α4-integrin receptors was required for activation of the PI3K pathway; however, either receptor interaction alone was sufficient for activation of the MAPK pathway. Using small-molecule inhibitors, we confirmed that the PI3K and FAK/SRC pathways were required for MuPyV infection, while the MAPK pathway was dispensable. Mechanistically, the PI3K pathway was required for MuPyV endocytosis, while the FAK/SRC pathway enabled trafficking of MuPyV along microtubules. Thus, MuPyV interactions with specific cell surface receptors facilitate activation of signaling pathways required for virus entry and trafficking. Understanding how different viruses manipulate cell signaling pathways through interactions with host receptors could lead to the identification of new therapeutic targets for viral infection. Virus binding to cell surface receptors initiates outside-in signaling that leads to virus endocytosis and subsequent virus trafficking. How different viruses manipulate cell signaling through interactions with host receptors remains unclear, and elucidation of the specific receptors and signaling pathways required for virus infection may lead to new therapeutic targets. In this study, we determined that gangliosides and α4-integrin mediate mouse polyomavirus (MuPyV) activation of host signaling pathways. Of these pathways, the PI3K and FAK/SRC pathways were required for MuPyV infection. Both the PI3K and FAK/SRC pathways have been implicated in human diseases, such as heart disease and cancer, and inhibitors directed against these pathways are currently being investigated as therapies. It is possible that these pathways play a role in human PyV infections and could be targeted to inhibit PyV infection in immunosuppressed patients.

Project description:BackgroundA central problem in computational metabolic modelling is how to find biochemically plausible pathways between metabolites in a metabolic network. Two general, complementary frameworks have been utilized to find metabolic pathways: constraint-based modelling and graph-theoretical path finding approaches. In constraint-based modelling, one aims to find pathways where metabolites are balanced in a pseudo steady-state. Constraint-based methods, such as elementary flux mode analysis, have typically a high computational cost stemming from a large number of steady-state pathways in a typical metabolic network. On the other hand, graph-theoretical approaches avoid the computational complexity of constraint-based methods by solving a simpler problem of finding shortest paths. However, while scaling well with network size, graph-theoretic methods generally tend to return more false positive pathways than constraint-based methods.ResultsIn this paper, we introduce a computational method, ReTrace, for finding biochemically relevant, branching metabolic pathways in an atom-level representation of metabolic networks. The method finds compact pathways which transfer a high fraction of atoms from source to target metabolites by considering combinations of linear shortest paths. In contrast to current steady-state pathway analysis methods, our method scales up well and is able to operate on genome-scale models. Further, we show that the pathways produced are biochemically meaningful by an example involving the biosynthesis of inosine 5'-monophosphate (IMP). In particular, the method is able to avoid typical problems associated with graph-theoretic approaches such as the need to define side metabolites or pathways not carrying any net carbon flux appearing in results. Finally, we discuss an application involving reconstruction of amino acid pathways of a recently sequenced organism demonstrating how measurement data can be easily incorporated into ReTrace analysis. ReTrace is licensed under GPL and is freely available for academic use at http://www.cs.helsinki.fi/group/sysfys/software/retrace/.ConclusionReTrace is a useful method in metabolic path finding tasks, combining some of the best aspects in constraint-based and graph-theoretic methods. It finds use in a multitude of tasks ranging from metabolic engineering to metabolic reconstruction of recently sequenced organisms.

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Genome-scale identification of cellular pathways required for cell surface recognition.

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Genome-scale identification of cellular pathways required for cell surface recognition.

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