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Record W3088158311 · doi:10.1101/2020.09.27.315929

Sequence-dependent mechanics of collagen reflect its structural and functional organization

2020· preprint· en· W3088158311 on OpenAlexafffund
Alaa Al-Shaer, Aaron Lyons, Yoshihiro Ishikawa, Billy G. Hudson, Sergei P. Boudko, Nancy R. Forde

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsSimon Fraser University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNatural Sciences and Engineering Research Council of Canada
KeywordsFlexibility (engineering)FibrilExtracellular matrixTriple helixBiophysicsSequence (biology)Basement membraneChemistryMatrix (chemical analysis)Collagen fibrilFlexibility methodCollagen helixCrystallographyMaterials scienceBiochemistryStereochemistryCell biologyBiologyStiffnessMathematicsComposite material

Abstract

fetched live from OpenAlex

Abstract Extracellular matrix mechanics influence diverse cellular functions, yet surprisingly little is known about the mechanical properties of their constituent collagen proteins. In particular, network-forming collagen IV, an integral component of basement membranes, has been far less studied than fibril-forming collagens. A key feature of collagen IV is the presence of interruptions in the triple-helix-defining (Gly-X-Y) sequence along its collagenous domain. Here, we used atomic force microscopy (AFM) to determine the impact of sequence heterogeneity on the local flexibility of collagen IV and of the fibril-forming collagen III. Our extracted flexibility profile of collagen IV reveals that it possesses highly heterogeneous mechanics, ranging from semi-flexible regions as found for fibril-forming collagens to a lengthy region of high flexibility towards its N terminus. A simple model in which flexibility is dictated only by the presence of interruptions fit the extracted profile reasonably well, providing insight into the alignment of chains and demonstrating that interruptions – particularly when coinciding in multiple chains – significantly enhance local flexibility. To a lesser extent, sequence variations within the triple helix lead to variable flexibility, as seen along the continuously triple-helical collagen III. We found this fibril-forming collagen to possess a high-flexibility region around its matrix-metalloprotease (MMP) binding site, suggesting a unique mechanical fingerprint of this region that is key for matrix remodeling. Surprisingly, proline content did not correlate with local flexibility in either collagen type. We also found that physiologically relevant changes in pH and chloride concentration did not alter the flexibility of collagen IV, indicating such environmental changes are unlikely to control its compaction during secretion. Although extracellular chloride ions play a role in triggering collagen IV network formation, they do not appear to modulate the structure of its collagenous domain. Significance Statement Collagens are the predominant proteins in vertebrates, forming diverse hierarchical structures to support cells and form connective tissues. Despite their mechanical importance, surprisingly little is established about the molecular encoding of mechanics. Here, we image single collagen proteins and find that they exhibit variable flexibility along their backbones. By comparing collagens with continuous and discontinuous triple-helix-forming sequences, we find that the type of helix interruption correlates with local flexibility, providing the first steps towards a much-needed map between sequence, structure, and mechanics in these large proteins. Our results inform our understanding of collagen’s ability to adopt compact conformations during cellular secretion and suggest a physical mechanism by which higher-order structure may be regulated by the distinct molecular properties of different collagens.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.237
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2020
Admission routes2
Has abstractyes

Explore more

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