Evidence map›Paper›PMID 41532502›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

A Mini-Spidroin Forms High-Performance Artificial Spider Silk via Edge-Cysteine-Locked β-Sheet Assembly.

Min Li, Huan Chen, Qi Zhang, Xiaoyun Xu, Yini Zheng, Chunyu Lyu, Weibin Jia, Jun Fan, Fu-Rong Chen, Wei Liu and 1 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Liquid-liquid phase separation enables chromatography-free purification and high-performance spidroin-amyloid hybrid silk fibers.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Min LiDepartment of Biomedical Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0001-9388-8835
Huan ChenDepartment of Materials Science and Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0009-0003-0076-2718
Qi ZhangDepartment of Biomedical Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0003-3418-1121
Xiaoyun XuDepartment of Biomedical Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0001-5122-0431
Yini ZhengDepartment of Materials Science and Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0002-4220-9449
Chunyu LyuShenzhen Key Laboratory For Neuronal Structural Biology, Biomedical Research Institute, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen, P. R. China.ORCID https://orcid.org/0000-0002-9234-5107
Weibin JiaDepartment of Biomedical Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0001-5532-7199
Jun FanDepartment of Materials Science and Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0001-8227-9671
Fu-Rong ChenDepartment of Materials Science and Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0003-4707-6590
Wei LiuShenzhen Key Laboratory For Neuronal Structural Biology, Biomedical Research Institute, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen, P. R. China.ORCID https://orcid.org/0000-0001-8250-2562
Jinlian HuDepartment of Biomedical Engineering, the City University of Hong Kong, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0001-8914-5473

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2021A1515010796Basic and Applied Basic Research Foundation of Guangdong Province 2022A1515010666Basic and Applied Basic Research Foundation of Guangdong Province 2025A1515010736National Natural Science Foundation of China 15201719National Natural Science Foundation of China 31870746National Natural Science Foundation of China 51673162National Natural Science Foundation of China 52073241Research Grants Council of the Hong Kong Special Administrative Region, China CityU C1017-22GShenzhen Basic Research Grants JCYJ20200109140414636Shenzhen Basic Research Grants JCYJ20230807145103007
6 · The paper itself

Abstract

Spider silk's remarkable mechanical properties arise from its hierarchical organization, where β-sheet nanocrystals confer strength and amorphous chains impart extensibility. However, replicating this performance in synthetic fibers has been hindered by the challenges of expressing high-molecular-weight spidroins and processing them into fibers. Here, we overcome these limitations by engineering a mini-spidroin (∼33 kDa) that is both easily expressible and spinnable, yet yields fibers with exceptional strength and toughness. Our strategy introduces cysteine residues at the termini of polyalanine (polyA) segments, enabling inter-strand disulfide bonds that enhance molecular cohesion during liquid-liquid phase separation (LLPS). This "edge-cysteine locking" promotes directional β-sheet assembly under extensional flow, resulting in fibers with an ultimate tensile strength of 531 ± 33 MPa and toughness of 182 ± 6 MJ/m

Indexed as

CysteineFibroinsSilkSpidersAnimalsPeptidesProtein Conformation, beta-StrandTensile StrengthCysteineFibroinsPeptidespolyalanineSilkdisulfide crosslinkingliquid–liquid phase separationmolecular alignmentrecombinant spider silkβ‐sheet assembly

Identifiers

PMID41532502
PMCPMC12915095

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.