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Definition of a consensus integrin adhesome and its dynamics during adhesion complex assembly and disassembly

Nature Cell Biology volume 17, pages 1577–1587 (2015)Cite this article

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Abstract

Integrin receptor activation initiates the formation of integrin adhesion complexes (IACs) at the cell membrane that transduce adhesion-dependent signals to control a multitude of cellular functions. Proteomic analyses of isolated IACs have revealed an unanticipated molecular complexity; however, a global view of the consensus composition and dynamics of IACs is lacking. Here, we have integrated several IAC proteomes and generated a 2,412-protein integrin adhesome. Analysis of this data set reveals the functional diversity of proteins in IACs and establishes a consensus adhesome of 60 proteins. The consensus adhesome is likely to represent a core cell adhesion machinery, centred around four axes comprising ILK–PINCH–kindlin, FAK–paxillin, talin–vinculin and α-actinin–zyxin–VASP, and includes underappreciated IAC components such as Rsu-1 and caldesmon. Proteomic quantification of IAC assembly and disassembly detailed the compositional dynamics of the core cell adhesion machinery. The definition of this consensus view of integrin adhesome components provides a resource for the research community.

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Figure 1: Overlap and comparison of IAC proteomes in the meta-adhesome.
Figure 2: Meta-adhesome coverage of the literature-curated adhesome.
Figure 3: Functional enrichment map of the consensus integrin adhesome.
Figure 4: Curated network model of the consensus integrin adhesome.
Figure 5: Caldesmon and Rsu-1 localization in IACs.
Figure 6: Temporal profiling of the consensus adhesome during IAC assembly.
Figure 7: Temporal profiling of the consensus adhesome during IAC disassembly.
Figure 8: Changes in consensus adhesome components during IAC disassembly.

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Acknowledgements

We thank S. E. Craig for technical assistance, J. N. Selley for bioinformatic support, M. Manca for preliminary data analysis, P. March, S. Marsden and E. Zindy for assistance with microscopy, the PRIDE team for assistance with MS data deposition and G. Jacquemet, M. C. Jones and A. P. Mould for discussions. We are grateful to K. Clark, M. L. Cutler, I. J. Fidler, M. E. Hemler, D. Vestweber, J. A. Wilkins and K. M. Yamada for reagents. This work was supported by the Wellcome Trust (grant 092015 to M.J.H.), a Wellcome Trust Institutional Strategic Support Fund award (grant 097820 to the University of Manchester) and a Biotechnology and Biological Sciences Research Council studentship from the Systems Biology Doctoral Training Centre (to E.R.H.). The mass spectrometers and microscopes used in this study were purchased with grants from the Biotechnology and Biological Sciences Research Council, Wellcome Trust and the University of Manchester Strategic Fund. Data are available from ProteomeXchange with identifiers PXD000018, PXD002159 and PXD002129.

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Author notes

  1. Edward R. Horton and Adam Byron: These authors contributed equally to this work.

Authors and Affiliations

  1. Wellcome Trust Centre for Cell-Matrix Research, Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, UK

    Edward R. Horton, Adam Byron, Janet A. Askari, Daniel H. J. Ng, Angélique Millon-Frémillon, Joseph Robertson, Ewa J. Koper, Nikki R. Paul, Jonathan D. Humphries & Martin J. Humphries

  2. Edinburgh Cancer Research UK Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XR, UK

    Adam Byron

  3. Biological Mass Spectrometry Core Facility, Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, UK

    Stacey Warwood & David Knight

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Contributions

A.B. and M.J.H. conceived the project; E.R.H., A.B., J.A.A., D.H.J.N., A.M.-F., J.D.H. and M.J.H. designed the experiments and interpreted the results; E.R.H., A.B., J.A.A., D.H.J.N., A.M.-F., J.R., E.J.K., N.R.P. and J.D.H. performed the experiments and analysed the data; A.B., S.W. and D.K. carried out mass spectrometry; E.R.H., A.B., J.D.H. and M.J.H. wrote the paper; all authors commented on the manuscript and approved the final version. E.R.H. and A.B. contributed equally to this work.

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Correspondence to Adam Byron or Martin J. Humphries.

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Integrated supplementary information

Supplementary Figure 1 Comparison of FN-enriched IAC proteomes.

(a) Seven proteomic datasets of FN-enriched IACs were analysed by unsupervised hierarchical clustering. The binary heat map shows proteins at least two-fold enriched to FN over the negative control (red). Dataset occurrence is plotted for each protein (rainbow), and literature-curated adhesome4 components are indicated by purple bars. Details of the proteomic datasets are provided in Supplementary Table 1. (b) Dendogram illustrating the clustering of the FN-enriched IAC proteomes shown in a. Dataset dissimilarity is measured by Jaccard distance. (c) Pairwise overlaps of FN-enriched proteins identified in the seven proteomic datasets and the literature-curated adhesome were measured by Jaccard coefficient and are displayed as a hierarchically clustered heatmap (lower diagonal matrix; blue). Numbers of proteins in each overlap set are indicated (upper diagonal matrix). (d) FN-enriched proteins identified in the seven proteomic datasets were analysed by principal component analysis. A plot of the first two principal components is shown. K562, human chronic myelogenous leukaemia cells11; MEF, mouse embryonic fibroblast cells (this study); A375, human malignant melanoma cells14; HFF, human foreskin fibroblast cells13; MKF1, mouse kidney fibroblast cells15; MKF2 and MKF3, mouse kidney fibroblast cells16.

Supplementary Figure 2 Topological analysis of the meta-adhesome interaction network.

(a) Clustered protein–protein interaction network model of the meta-adhesome. The largest connected graph component is displayed, comprising 11,430 interactions (black lines; edges) between 2,035 proteins (circles; nodes). Node size is proportional to degree and node colour is proportional to betweenness centrality. Black node borders indicate literature-curated adhesome4 components, which are labelled with gene names. (b) Betweenness centrality (a measure of the control a node exerts over the interactions of other nodes in the network) for each protein is plotted according to the number of datasets in which it was identified. Box-and-whisker plot shows the median (line), mean (plus sign), 25th and 75th percentiles (box) and 5th and 95th percentiles (whiskers) (n = 1,117, 518, 238, 102, 33, 25 and 10 mapped proteins identified in 1–7 datasets, respectively, with degree ≥1). ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001; Kruskal–Wallis test with Dunn’s post hoc correction (see Supplementary Table 15 for statistics source data).

Supplementary Figure 3 Functional enrichment map of the meta-adhesome.

(a) Overrepresented biological process terms from proteins identified in the meta-adhesome were hierarchically clustered according to proteomic dataset occurrence. This identified clusters of similarly detected proteins associated with a similar set of functional terms. (b) The two clusters containing proteins detected in the most datasets (grey boxes in a; 1, 2) are shown in detail. Proteins are labelled with gene names for clarity (see Supplementary Table 3 for details).

Supplementary Figure 4 Comparison of IAC proteomes in the consensus adhesome.

Proteins identified in the consensus adhesome were analysed by unsupervised hierarchical clustering. The binary heat map shows proteins at least two-fold enriched to FN over the negative control (red). Dataset occurrence is plotted for each protein (rainbow), literature-curated adhesome4 components are indicated by purple bars, and the presence of a LIM domain is indicated by grey bars. Dataset dissimilarity is measured by Pearson correlation. The numbers of consensus adhesome proteins identified in each IAC proteome are displayed below the heat map. Details of the proteomic datasets are provided in Supplementary Table 1, and details of proteins identified in the consensus adhesome are provided in Supplementary Table 4. K562, human chronic myelogenous leukaemia cells11; MEF, mouse embryonic fibroblast cells (this study); A375, human malignant melanoma cells14; HFF, human foreskin fibroblast cells13; MKF1, mouse kidney fibroblast cells15; MKF2 and MKF3, mouse kidney fibroblast cells16.

Supplementary Figure 5 Hierarchical clustering analysis of meta-adhesome proteins identified during IAC assembly.

IACs were isolated from K562 cells in biological duplicate after 3, 9 and 32 min incubation with FN-coated beads and analysed by MS (data are from 2 independent experiments; see Supplementary Table 11). Throughout IAC maturation, 1,266 of the 2,412 meta-adhesome proteins were identified and were analysed by unsupervised hierarchical clustering, revealing distinct temporal profiles of protein recruitment to IACs. Quantitative heat map displays mean spectral counts as a proportion of the maximum spectral count for each given protein. Twelve clusters were chosen on the basis of a Pearson correlation threshold greater than 0.8, labelled SA1–12, and are indicated by blue and green bars. Literature-curated adhesome4 and consensus adhesome proteins identified in each cluster are indicated by gene name (italic, literature-curated adhesome; regular, consensus adhesome; bold, literature-curated adhesome and consensus adhesome). Literature-curated adhesome proteins that interact with consensus adhesome molecules in interaction network analyses are indicated by an asterisk (see Supplementary Table 7 for details). Clusters are shown alongside corresponding profile plots, with the mean temporal profile for each cluster indicated by a red line. The most significantly overrepresented functional annotations for selected clusters are listed. Full details of enriched functional terms are provided in Supplementary Table 13.

Supplementary Figure 6 Hierarchical clustering analysis of meta-adhesome proteins identified during IAC disassembly.

(a) IACs were isolated from adherent U2OS cells in biological triplicate on nocodazole removal and 5, 10 and 15 min after nocodazole washout to examine changes in IAC composition throughout IAC disruption32. Isolated IACs at each time point were analysed by MS (data are from 3 independent experiments; see Supplementary Table 12). Throughout IAC disassembly, 455 of the 2,412 meta-adhesome proteins were identified and were analysed by unsupervised hierarchical clustering, revealing distinct temporal profiles of protein dissociation from IACs. Quantitative heat map displays mean spectral counts as a proportion of the maximum spectral count for each given protein. Seventeen clusters were chosen on the basis of a Pearson correlation threshold greater than 0.8, labelled SD1–17, and are indicated by blue and green bars. Literature-curated adhesome4 and consensus adhesome proteins identified in each cluster are indicated by gene name (italic, literature-curated adhesome; regular, consensus adhesome; bold, literature-curated adhesome and consensus adhesome). Literature-curated adhesome proteins that interact with consensus adhesome molecules in interaction network analyses are indicated by an asterisk (see Supplementary Table 7 for details). Clusters are shown alongside corresponding profile plots, with the mean temporal profile for each cluster indicated by a red line. The most significantly overrepresented functional annotations for selected clusters are listed. Full details of enriched functional terms are provided in Supplementary Table 14. (b,c) Area-proportional Venn diagrams showing the overlap between the meta-adhesome and proteins identified by MS during IAC assembly (b) or IAC disassembly (c). For each set, the total number of proteins (black text) and the number of proteins identified in the consensus adhesome (bold red text) is indicated.

Supplementary Figure 7 Changes in additional consensus adhesome components during IAC disassembly.

(a) To examine IAC dynamics during microtubule-induced IAC disassembly32, HFF cells treated with DMSO, 10 μM nocodazole or after nocodazole removal at different times were stained for phospho-paxillinY 118, paxillin, phospho-FAKY 397 andβ1 integrin. Representative images are shown. Scale bars, 20 μm. (b–e) Quantification of images in a. Phospho-paxillinY 118 (b), paxillin (c), phospho-FAKY 397 (d) and β1 integrin (e) levels were quantified as a proportion of total cell area. Box-and-whisker plots show median (line), mean (plus sign), 25th and 75th percentiles (box) and 5th and 95th percentiles (whiskers) (n = 10 cells per condition from one independent experiment). ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001; Kruskal–Wallis test with Dunn’s post hoc correction (see Supplementary Table 15 for statistics source data). Noc, nocodazole.

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Horton, E., Byron, A., Askari, J. et al. Definition of a consensus integrin adhesome and its dynamics during adhesion complex assembly and disassembly. Nat Cell Biol 17, 1577–1587 (2015). https://doi.org/10.1038/ncb3257

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