The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Structural Biology and Evolution of the TGF-β Family
Open accessAbstract
We review the evolution and structure of members of the transforming growth factor β (TGF-β) family, antagonistic or agonistic modulators, and receptors that regulate TGF-β signaling in extracellular environments. The growth factor (GF) domain common to all family members and many of their antagonists evolved from a common cystine knot growth factor (CKGF) domain. The CKGF superfamily comprises six distinct families in primitive metazoans, including the TGF-β and Dan families. Compared with Wnt/Frizzled and Notch/Delta families that also specify body axes, cell fate, tissues, and other families that contain CKGF domains that evolved in parallel, the TGF-β family was the most fruitful in evolution. Complexes between the prodomains and GFs of the TGF-β family suggest a new paradigm for regulating GF release by conversion from closed- to open-arm procomplex conformations. Ternary complexes of the final step in extracellular signaling show how TGF-β GF dimers bind type I and type II receptors on the cell surface, and enable understanding of much of the specificity and promiscuity in extracellular signaling. However, structures suggest that when GFs bind repulsive guidance molecule (RGM) family coreceptors, type I receptors do not bind until reaching an intracellular, membrane-enveloped compartment, blurring the line between extra- and intracellular signaling. Modulator protein structures show how structurally diverse antagonists including follistatins, noggin, and members of the chordin family bind GFs to regulate signaling; complexes with the Dan family remain elusive. Much work is needed to understand how these molecular components assemble to form signaling hubs in extracellular environments in vivo.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
Katoh, K., & Standley, D. M. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst010 · Cited by 46,209
Broad phylogenomic sampling improves resolution of the animal tree of life
Dunn, C. W., Hejnol, A., Matus, D. Q., Pang, K., Browne, W. E., Smith, S. A., Seaver, E., Rouse, G. W., Obst, M., Edgecombe, G. D., et al. (2008) · Nature · doi:10.1038/nature06614 · Cited by 1,921 · cited 1×
“Bilaterian phyla are grouped by nucleotide and protein sequence into three branches that extend previous embryological classification (Blair and Hedges 2005; Dunn et al. 2008; Hejnol et al. 2009).”
Myofibroblast contraction activates latent TGF-β1 from the extracellular matrix
Wipff, P.-J., Rifkin, D. B., Meister, J.-J., & Hinz, B. (2007) · The Journal of Cell Biology · doi:10.1083/jcb.200704042 · Cited by 1,346
Latent TGF-β structure and activation
Shi, M., Zhu, J., Wang, R., Chen, X., Mi, L., Walz, T., & Springer, T. A. (2011) · Nature · doi:10.1038/nature10152 · Cited by 1,013
Self-citationAssessing the root of bilaterian animals with scalable phylogenomic methods
Hejnol, A., Obst, M., Stamatakis, A., Ott, M., Rouse, G. W., Edgecombe, G. D., Martinez, P., Baguñà, J., Bailly, X., Jondelius, U., et al. (2009) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2009.0896 · Cited by 747 · cited 1×
“Bilaterian phyla are grouped by nucleotide and protein sequence into three branches that extend previous embryological classification (Blair and Hedges 2005; Dunn et al. 2008; Hejnol et al. 2009).”
The establishment of spemann's organizer and patterning of the vertebrate embryo
De Robertis, E. M., Larraín, J., Oelgeschläger, M., & Wessely, O. (2000) · Nature Reviews Genetics · doi:10.1038/35042039 · Cited by 429
Follistatin complexes Myostatin and antagonises Myostatin-mediated inhibition of myogenesis
Amthor, H., Nicholas, G., McKinnell, I., Kemp, C. F., Sharma, M., Kambadur, R., & Patel, K. (2004) · Developmental Biology · doi:10.1016/j.ydbio.2004.01.046 · Cited by 401
Wise, a context-dependent activator and inhibitor of Wnt signalling
Itasaki, N., Jones, C. M., Mercurio, S., Rowe, A., Domingos, P. M., Smith, J. C., & Krumlauf, R. (2003) · Development · doi:10.1242/dev.00674 · Cited by 321
Francois, V, Solloway, M., O'Neill, J. W., Emery, J., & Bier, E. (1994) · Genes & Development · doi:10.1101/gad.8.21.2602 · Cited by 308
Sidis, Y., Mukherjee, A., Keutmann, H., Delbaere, A., Sadatsuki, M., & Schneyer, A. (2006) · Endocrinology · doi:10.1210/en.2006-0089 · Cited by 211
Structural determinants of integrin β-subunit specificity for latent TGF-β
Dong, X., Hudson, N. E., Lu, C., & Springer, T. A. (2014) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2905 · Cited by 141
Self-citationRepulsive guidance molecule is a structural bridge between neogenin and bone morphogenetic protein
Healey, E. G., Bishop, B., Elegheert, J., Bell, C. H., Padilla-Parra, S., & Siebold, C. (2015) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.3016 · Cited by 112
Evolution of the TGF-β Signaling Pathway and Its Potential Role in the Ctenophore, Mnemiopsis leidyi
Pang, K., Ryan, J. F., Baxevanis, A. D., & Martindale, M. Q. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024152 · Cited by 93
Cited by
TGF-β signaling in health and disease
Massagué, J., & Sheppard, D. (2023) · Cell · doi:10.1016/j.cell.2023.07.036 · Cited by 890
Contextual determinants of TGFβ action in development, immunity and cancer
David, C. J., & Massagué, J. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0007-0 · Cited by 851
TGF-β1 Signaling and Tissue Fibrosis
Kim, K. K., Sheppard, D., & Chapman, H. A. (2018) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a022293 · Cited by 800
Specificity, versatility, and control of TGF-β family signaling
Derynck, R., & Budi, E. H. (2019) · Science Signaling · doi:10.1126/scisignal.aav5183 · Cited by 785
Regulation of the Bioavailability of TGF-β and TGF-β-Related Proteins
Robertson, I. B., & Rifkin, D. B. (2016) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a021907 · Cited by 403
Metadata
- Authors
- Hinck, A. P., Mueller, T. D., & Springer, T. A.
- Venue
- Cold Spring Harbor Perspectives in Biology
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2016-09-16
- Volume
- 8
- Issue
- 12
- Pages
- a022103
- ISSN
- 1943-0264 (ISSN-L)
- OpenAlex
- W2518755163
- Cited by
- 368
- References
- 13
- Type
- posted content
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
