Proteome-Scale Screening to Identify High-Expression Signal Peptides with Minimal N‑Terminus Biases via Yeast Display

Signal
peptides are critical for the efficient expression and routing
of extracellular and secreted proteins. Most protein production and
screening technologies rely upon a relatively small set of signal
peptides. Despite their central role in biotechnology, there are limited
studies comprehensively examining the interplay between signal peptides
and expressed protein sequences. Here, we describe a high-throughput
method to screen novel signal peptides that maintain a high degree
of surface expression across a range of protein scaffolds with highly
variable N-termini. We find that the canonical signal peptide used
in yeast surface display, derived from Aga2p, fails to achieve high
surface expression for 42.5% of constructs containing diverse N-termini.
To circumvent this, we have identified two novel signal peptides derived
from endogenous yeast proteins, SRL1 and KISH, which are highly tolerant
to diverse N-terminal sequences. This pipeline can be used to expand
our understanding of signal peptide function, identify improved signal
peptides for protein expression, and refine the computational tools
used for signal peptide prediction.

信号肽（Signal peptides）对于胞外蛋白与分泌蛋白的高效表达及转运至关重要。当前多数蛋白质生产与筛选技术仅依赖于数量相对有限的信号肽品类。尽管信号肽在生物技术领域占据核心地位，但目前针对信号肽与目标蛋白序列之间相互作用的系统性研究仍较为匮乏。本研究报道一种高通量筛选方法，可用于筛选能够在多种N端序列高度可变的蛋白质支架中维持高效表面表达的新型信号肽。我们发现，酵母表面展示体系中常用的源自Aga2p的经典信号肽，在42.5%携带多样化N端序列的重组构建体中无法实现高效表面表达。为解决这一局限，我们从酵母内源蛋白中筛选得到两种新型信号肽SRL1与KISH，二者对多样化的N端序列均具备极佳的耐受性。该筛选流程可用于深化我们对信号肽功能的认知，筛选获得更适配蛋白质表达的优质信号肽，并优化用于信号肽预测的计算工具。