Skip to content

Efficient production of recombinant human serum albumin in Escherichia coli via oxidative folding mediated by the a domain of protein disulfide isomerase.

Oct 2026 · Journal of Bioscience and Bioengineering · 0 citations · 59 references
Medicine

TL;DR

It is demonstrated that PDI(a)-mediated cis-fusion enables high-yield production of structurally native-like and functionally competent HSA in the bacterial cytosol and provides a practical platform for producing complex disulfide-rich proteins in E. coli.

Abstract

Efficient production of properly folded, disulfide-rich proteins in the cytosol of Escherichia coli remains challenging because the cytosol is highly reducing. Here, we developed an expression system for recombinant human serum albumin (rHSA) by fusing the a domain of human protein disulfide isomerase (PDI) to the N-terminus of HSA. PDI(a)-mediated cis-fusion enabled high-level production of soluble rHSA in oxidizing E. coli strains under low-temperature conditions. Purified E. coli-rHSA was predominantly monomeric and had the molecular mass expected for HSA containing 17 intramolecular disulfide bonds. E. coli-rHSA retained esterase-like activity comparable to that of rHSA produced in Pichia pastoris (P. pastoris-rHSA) and serum-derived HSA, confirming preservation of this activity. Circular dichroism analyses and small-angle X-ray scattering showed that E. coli-rHSA adopted a solution structure nearly identical to that of P. pastoris-rHSA. Disulfide-bond mapping identified 13 of the 17 native disulfide bonds, although alternative pairings were also detected. E. coli-rHSA showed slightly lower thermal stability than P. pastoris-rHSA under nonreducing conditions. These results demonstrate that PDI(a)-mediated cis-fusion enables high-yield production of structurally native-like and functionally competent HSA in the bacterial cytosol and provides a practical platform for producing complex disulfide-rich proteins in E. coli.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.