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. 2025 Aug 5;16(1):7215.
doi: 10.1038/s41467-025-60526-6.

Characterizing and engineering post-translational modifications with high-throughput cell-free expression

Affiliations

Characterizing and engineering post-translational modifications with high-throughput cell-free expression

Derek A Wong et al. Nat Commun. .

Abstract

Post-translational modifications (PTMs) are important for the stability and function of many therapeutic proteins and peptides. Current methods for studying and engineering PTMs are often limited by low-throughput experimental techniques. Here we describe a generalizable, in vitro workflow coupling cell-free gene expression (CFE) with AlphaLISA for the rapid expression and testing of PTM installing proteins. We apply our workflow to two representative classes of peptide and protein therapeutics: ribosomally synthesized and post-translationally modified peptides (RiPPs) and glycoproteins. First, we demonstrate how our workflow can be used to characterize the binding activity of RiPP recognition elements, an important first step in RiPP biosynthesis, and be integrated into a biodiscovery pipeline for computationally predicted RiPP products. Then, we adapt our workflow to study and engineer oligosaccharyltransferases (OSTs) involved in protein glycan coupling technology, leading to the identification of mutant OSTs and sites within a model vaccine carrier protein that enable high efficiency production of glycosylated proteins. We expect that our workflow will accelerate design-build-test-learn cycles for engineering PTMs.

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Conflict of interest statement

Competing interests: M.C.J. and M.P.D. have a financial interest in National Resilience and Gauntlet Bio. M.C.J. also has a financial interest in Stemloop Inc. and Synolo Therapeutics. M.C.J.’s interests are reviewed and managed by Northwestern University and Stanford University in accordance with their competing interest policies. M.P.D.s interests are reviewed and managed by Cornell University. All other authors declare no competing interests.

Figures

Fig. 1
Fig. 1. A cell-free plate-based assay for detecting RRE-peptide interactions.
a Schematic of the cell-free workflow. sFLAG-tagged peptides and MBP-tagged RREs are expressed in individual PUREfrex reactions, mixed in a 384 well plate, and incubated to enable binding interactions. Addition of anti-FLAG AlphaLISA donor beads and anti-MBP AlphaLISA acceptor beads enables detection of interactions between the RRE and peptide of interest. PUREfrex reactions of precursor peptide and RRE for (b) pyrroloquinoline quinone (PQQ), (c) a putative lasso peptide from Thermobacculum terrenum ATCC BAA−798, (d) a heterocycloanthracin from Bacillus sp. Al Hakam, and (e) thiomuracin, a thiopeptide from Thermobispora bispora were cross-titrated across different dilutions (with 0 indicating no PUREfrex reaction added) and assessed for binding interactions via AlphaLISA. Data are representative of three (n = 3) biological replicates. RLU relative luminescence units. Source data are provided in the Source Data 1 file.
Fig. 2
Fig. 2. Cell-free workflow identifies peptide residues important for binding by TbtF.
a An alanine scan library of the leader sequence of TbtA was expressed in individual PUREfrex reactions and assessed for binding interactions in the presence of MBP-TbtF RRE domain using AlphaLISA. b A synthetic peptide library was constructed using the first 40 amino acids of sfGFP. Variants of the sfGFP were then constructed by replacing residues in the peptide identified in the alanine scan as important for binding by TbtF with the corresponding residue in the wild-type TbtA leader sequence. Each peptide variant was expressed in an individual PUREfrex reaction and then assessed for binding interactions in the presence and absence of TbtF using AlphaLISA. Peptide variant 2 contains 9% identity to TbtA wild-type peptide due to sharing residues G(-2), G(-7) and G(−9). For simplicity, only amino acids between the −34 and −17 position are depicted, however each peptide was composed of 40 amino acids reflecting the length of the TbtA leader sequence with an additional 5 amino acid linker. Sequences for each of the peptide variants assayed in panel b are provided in Supplementary Table 1. All data are presented as the mean of technical replicates (n = 3). RLU relative luminescence units. Source data are provided in the Source Data 1 file.
Fig. 3
Fig. 3. Computationally guided screen of lasso peptide RREs.
a Overall prediction and screening workflow for lasso peptide BGCs. b For predicted BGCs with a single RRE and precursor peptide, individual PUREfrex reactions expressing RREs and the respective peptide were cross-titrated and assessed for binding activity via AlphaLISA. c For predicted biosynthetic gene clusters with multiple RREs and precursor peptides, all possible combinations of RRE and precursor peptide were assessed for binding activity via AlphaLISA (select combinations shown, see Supplementary Fig. 6 for additional pairwise combinations). All data shown are single replicate, with confirmation reactions performed in biological triplicate provided in Supplementary Fig. 7 to show reproducibility. RLU relative luminescence units. Source data are provided in the Source Data 1 file.
Fig. 4
Fig. 4. CFE and AlphaLISA can be combined to prototype in vitro glycosylation reactions.
a Schematic of the cell-free workflow. Nanodisc supplemented CFE reactions were first used to express CjPglB variants and then mixed with an acceptor protein containing a 6xHis tag and sequon and crude membrane fraction enriched with a bacterial glycan of interest. Samples were then analyzed using Protein A AlphaLISA donor beads and anti-6xHis AlphaLISA acceptor beads. b An IVG reaction using CjPglB, crude membrane fraction enriched with CPS from S. pneumoniae serotype 4, and sfGFP with a 6xHis tag and either (b) a DQNAT sequon or (c) an AQNAT sequon was serially diluted, mixed with varying concentrations of S. pneumoniae CPS4 antiserum, and analyzed via AlphaLISA. All data are representative of three independent experiments (n = 3). RLU relative luminescence units. Source data are provided in the Source Data 1 file.
Fig. 5
Fig. 5. Cell-free workflow identifies high-efficiency CjPglB mutants.
a Homology model of CjPglB. Sites chosen for site saturation mutagenesis are highlighted in colors denoted in (b). b Rationale of sites chosen for mutagenesis. c AlphaLISA results for IVG reactions containing crude membrane fraction enriched with CPS from S. pneumoniae serotype 4, sfGFP with a 6xHis tag and DQNAT sequon, and a unique CjPglB mutant. Data are a mean of AlphaLISA signals produced by duplicate IVG reactions (n = 2). RLU relative luminescence units. Source data are provided in the Source Data 1 file.
Fig. 6
Fig. 6. Sequon scanning of H. influenzae protein D.
a Schematic of the cell-free workflow. A library of PD constructs was designed with a glycosylation sequon inserted between every two amino acids. Each sequon variant was expressed in an individual CFE reaction. Following expression, sequon variants were combined with extract enriched with S. pneumoniae CPS4 glycan and CjPglBQ287K to form IVG reactions. IVG products were assessed for glycosylation with AlphaLISA. b AlphaLISA results for sequon scanning from N-terminus (site 1) through C-terminus (site 328). Data are presented as the mean of n = 3 biological replicates. “DQLAT” sequons, due to the lack of an asparagine residue, are unable to be N-glycosylated by CjPglB. Blue bars denote sequon positions resulting in significantly higher AlphaLISA signal than the negative control, as determined using one-way ANOVA with Bonferroni correction. Error bars show SEM. c AlphaLISA results from (b) mapped onto the crystal structure of PD. RLU relative luminescence units. Source data are provided in the Source Data 1 file.

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