CEN-Display: Construction and optimization of a surface display system in Saccharomyces cerevisiae CEN.PK2-1C
Abstract
Over the past decades, yeast surface display (YSD) technology has emerged as a powerful biotechnological tool with broad applications in biomedicine, industrial catalysis, and environmental science. However, its efficiency, stability and applicability are often limited by proteolytic degradation during secretion in commonly used strains and steric hindrance associated with anchoring architectures. In this study, we developed a high-performance platform, "CEN-Display," using a systematic engineering strategy on the Saccharomyces cerevisiae CEN.PK2-1C strain to expand the YSD toolbox for new chassis. The host chassis was engineered by deleting key vacuolar proteases PEP4/PRB1 to suppress degradation and CAN1 to modulate membrane permeability. And the redesigned display vector incorporated a de novo designed rigid linker (>600 aa) to minimize steric hindrance. Moreover, we conducted a systematic evaluation of eight candidate GPI-anchored proteins and refined cultivation process, specifically optimizing initial inoculation density and induction timing. Eventually, we identified 28_YI as a highly efficient and stable anchor, achieving a sixfold increase in α-galactosidase display efficiency and a 63.5% enhancement in enzymatic activity relative to the conventional Aga1-Aga2 system. Furthermore, the CEN-Display platform exhibited robust compatibility and stability for displaying both the complex enzyme (β-glucosidase, BGL1) and the degradation-prone nanobody (VHH 7D12). Collectively, this work establishes a high-performance yeast surface display platform based on the CEN.PK chassis and provides a foundation for the construction and application of high-performance display systems with broad utility in protein engineering and functional screening.
Fields of Study & Subjects
Plant and Biological Electrophysiology Studies
Interactive and Immersive Displays
Greenhouse Technology and Climate Control
Publication details
- Journal / source
- Bioresource Technology
- Publisher
- Elsevier BV
- Volume
- 458
- Pages
- 135113–135113
- Publication date
- 8 June 2026
- Language
- EN