Evidence map›Paper›PMID 35243528›Full record

ArticleApplied microbiology and biotechnology2022

A novel silk fibroin protein-based fusion system for enhancing the expression of nanobodies in Escherichia coli.

Jianli Yu, Yang Guo, Yi Gu, Xiying Fan, Fei Li, Haipeng Song, Rui Nian, Wenshuai Liu

Open access · bronzeAbstract read
In one paragraph

Article in Applied microbiology and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

6 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
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  5. Large-Scale Production of Anti-RNase A VHH Expressed inCurrent issues in molecular biology · 2023
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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

8 authors at 1 institution in 1 country.

Jianli Yu *CAS Key Laboratory of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, No. 189 Songling Road, Qingdao, 266101, China.
Yang Guo *CAS Key Laboratory of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, No. 189 Songling Road, Qingdao, 266101, China.
Yi GuCAS Key Laboratory of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, No. 189 Songling Road, Qingdao, 266101, China.
Xiying FanCAS Key Laboratory of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, No. 189 Songling Road, Qingdao, 266101, China.
Fei LiShenzhen Innova Nanobodi Co., Ltd, No. 7018 Caitian Road, Shenzhen, 518000, China.
Haipeng SongShenzhen Innova Nanobodi Co., Ltd, No. 7018 Caitian Road, Shenzhen, 518000, China.
Rui NianCAS Key Laboratory of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, No. 189 Songling Road, Qingdao, 266101, China.
Wenshuai LiuCAS Key Laboratory of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, No. 189 Songling Road, Qingdao, 266101, China. liuws@qibebt.ac.cn.ORCID http://orcid.org/0000-0002-6628-9690
Chinese Academy of Sciences · CN

Funding

Shandong Energy Institute SEI I202128
6 · The paper itself

Abstract

Nanobodies show a great potential in biomedical and biotechnology applications. Bacterial expression is the most widely used expression system for nanobody production. However, the yield of nanobodies is relatively low compared to that of eukaryotic systems. In this study, the repetitive amino acid sequence motifs (GAGAGS) found in silk fibroin protein (SFP) were developed as a novel fusion tag (SF-tag) to enhance the expression of nanobodies in Escherichia coli. SF-tags of 1 to 5 hexapeptide units were fused to the C-terminus of 4G8, a nanobody against human epididymis protein 4 (HE4). The protein yield of 4G8 variants was increased by the extension of hexapeptide units and achieved a 2.5 ~ 7.1-fold increase compared with that of untagged 4G8 (protein yield of 4G8-5C = 0.307 mg/g vs that of untagged 4G8 = 0.043 mg/g). Moreover, the fusion of SF-tags not only had no significant effect on the affinity of 4G8, but also showed a slight increase in the thermal stability of SF-tag-fused 4G8 variants. The fusion of SF-tags increased the transcription of 4G8 by 2.3 ~ 7.0-fold, indicating SF-tags enhanced the protein expression at the transcriptional level. To verify the applicability of the SF-tags for other nanobody expression, we further investigated the protein expression of two other anti-HE4 nanobodies 1G8 and 3A3 upon fusion with the SF-tags. Results indicated that the SF-tags enhanced the protein expression up to 5.2-fold and 5.7-fold for 1G8 and 3A3, respectively. For the first time, this study reported a novel and versatile fusion tag system based on the SFP for improving nanobody expression in Escherichia coli, which may enhance its potential for wider applications.Key points• A silk fibroin protein-based fusion tag (SF-tag) was developed to enhance the expression of nanobodies in Escherichia coli.• The SF-tag enhanced the nanobody expression at the transcriptional level.• The fusion of SF-tag had no significant effect on the affinity of nanobodies and could slightly increase the thermal stability of nanobodies.

Indexed as

FibroinsSingle-Domain AntibodiesBiotechnologyEscherichia coliHumansProtein Processing, Post-TranslationalRecombinant Fusion ProteinsFibroinsRecombinant Fusion ProteinsSingle-Domain AntibodiesEscherichia coliExpression-enhancing tagHexapeptideNanobodySilk fibroin protein

Identifiers

PMID35243528
PMCPMC8894094
OpenAlexW4214858070

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.