Coupling cell growth to protein secretion enables pooled screening at single-cell resolution in bioreactors
Galez, H., Franja Da Silva, A., Capela, C., Napolitano, S., Batt, G.
synthetic biology
Quick verdict
A growth-secretion coupling biosensor enables bioreactor pooled screening; proof-of-concept convincing, but readout is periplasmic POI, not secreted amount.
Summary
This paper presents AutoGrowth, a yeast screening strategy that preserves the genotype–phenotype linkage for secreted recombinant proteins by converting secretion into growth rate. The authors fuse a 13-residue α-factor peptide to the C-terminus of a protein of interest (POI) in an engineered S. cerevisiae chassis, so secreted POI activates the Ste2 pheromone receptor in an autocrine-only manner, driving an mScarletI.2A.HIS3 reporter; in histidine-free medium, HIS3 expression turns downstream activation into growth rate, with stringency tunable by 3-aminotriazole. Co-cultures with reporter-only strains show no paracrine activation, activation scales monotonically with secretion or display for mNG and five further POIs (two xylanases, α-amylase, a nanobody, scFv), and activation is stable over days in eVOLVER turbidostats with automated cytometry. As proof of concept, a 13-member signal peptide library screened for scFv secretion in bioreactors enriched top variants such as OsMF2; spike-ins enriched a vps5Δ strain from 1:10^6 within two days (~1500-fold) and from roughly ten cells at 1:10^8 within three days (>2500-fold). Key limitations: the readout reflects periplasmic/cell-surface POI concentration rather than true secreted amount (dTA antagonist data), cheater cells emerge after about two days under strong stringency, the vps5Δ strain carries a fitness burden from its hygromycin cassette, and statistical testing is minimal.
Review complete
Assessment at a glance
6
risk flags identified
● high 0
● medium 4
● low 2
5 strengths · 5 weaknesses · 5 author questions
AI text signal = Binoculars zero-shot detector score over 20 sampled passages (Fast-DetectGPT co-reported) — absence does not prove human authorship, and a flag does not imply misconduct.
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Key claims under review
- A 13-residue C-terminal α-factor fusion renders the secretion biosensor strictly autocrine, preserving genotype–phenotype linkage despite protein diffusion into the medium.
- Downstream activation scales monotonically and stably with secretion or display for mNG and five additional POIs spanning different secretion challenges.
- HIS3-dependent growth under tunable histidine/3AT stringency converts downstream activation into graded growth rates, enabling selection for secretion, fitness, or their balance.
- AutoGrowth screening in eVOLVER bioreactors enriches the best signal peptides for scFv secretion and detects favorable variants diluted 1:10^6 (~1500-fold in 2 days) and ~1:10^8 (>2500-fold in 3 days).
- Selection must be limited to a few days because cheater cells with decoupled reporter expression emerge under strong stringency.
Strengths
Autocrine-only design rigorously mechanistically validated
Four autocrine×paracrine co-cultures show zero paracrine activation (Fig 2A); the activation site is pinned down with the dTA antagonist, a Golgi-cleavable protection, and an N-terminal α-factor fusion that abolishes paracrine signaling (Supplementary Note 3).
Modular, multi-scale validation chain
Each module is characterized separately (POI secretion/display Fig 1C; sensing range spanning four orders of magnitude for pPOP6-Ste2id Fig 1D; HIS3-tunable growth Fig 1E), then integrated through batch (Fig 3B) and turbidostat (Fig 3C) growth coupling before any screening claim.
Rare-variant enrichment tested against proper controls
Transparent reporting of failure modes
Strong reproducibility infrastructure for a wet-lab paper
Weaknesses
Readout measures periplasmic POI, not secreted protein
Minimal statistical treatment
Fitness confound in the headline spike-ins
Selection window capped by cheater emergence
Partial concordance in the SP screen and exclusivity overclaims
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Scope & Claims
AutoGrowth (bioRxiv preprint; patent application pending by Galez, Napolitano, Batt) is a growth-based screening platform for recombinant protein secretion in *S. cerevisiae*. The central claims are threefold: (1) a 13-residue C-terminal α-factor fusion makes a secretion biosensor strictly single-cell (autocrine-only) despite protein diffusion; (2) downstream activation of a Ste2/Ste2id → LexA-PRD-Ste12 → mScarletI.2A.HIS3 cascade scales monotonically and stably with secretion or display across mNeonGreen (mNG) and five biotechnologically relevant POIs (XylC, Xyl2, α-amylase Amy, nanobody Nb21, scFv); (3) in histidine-free medium with 3AT-tunable stringency, HIS3 prototrophy converts activation into graded growth rate, so pooled bioreactor culture enriches high-secretor variants detectable by deep sequencing — including variants diluted 1:10^6 to 1:10^8.
The remaining sections cover Methodology Assessment, Statistical Evidence, Results & Reproducibility, Limitations & Risks, and Verdict & Recommendations.
- All 5 strengths & 5 weaknesses, analyzed in detail
- 6 risk flags with severity, section & reviewer questions
- Methods & statistical evidence assessment
- 5 questions a peer reviewer would ask
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Frequently asked questions
What is AutoGrowth and how does it work?
AutoGrowth is a yeast (S. cerevisiae) screening method that couples recombinant protein secretion to cell growth rate. A 13-residue α-factor peptide is fused to the C-terminus of the protein of interest; secretion activates the cell's own Ste2 pheromone receptor (autocrine signaling), which drives a HIS3 reporter. In histidine-free medium, cells that secrete more grow faster, so pooled cultures enrich high-secretor variants that are then identified by deep sequencing.
How large a library can AutoGrowth screen?
The authors demonstrate enrichment of a favorable variant diluted 1:10^6 (about 1500-fold in 2 days) and at roughly 1:10^8 (average >2500-fold in 3 days from about 10 starting cells). Throughput is limited mainly by sequencing depth and by the need to stop selection before cheater cells emerge, after roughly 2 days under strong selection pressure.
Does AutoGrowth measure true secreted protein levels?
Not exactly. Using the dTA α-factor antagonist, the authors show downstream activation tracks the concentration of the protein at the cell surface/periplasm rather than the amount released into the medium. Variants that improve secretion specifically at the cell-wall diffusion step could therefore be missed by this biosensor.
Are the data and code for this paper available?
Yes. Raw data (flow cytometry, microscopy images, OD curves, digital PCR, deep sequencing, colony counts, bioreactor logs) are deposited on Zenodo (doi:10.5281/zenodo.21282497), and processing notebooks, scripts, and plasmid sequences are in the public AutoGrowth GitLab repository at INRIA.
About this review
This is an AI-generated preliminary review by Evolve.Pub, produced from the openly available text of the paper. It is not peer review and does not represent the authors' views. The canonical record of the paper is at the publisher link above.
- Figures could not be analyzed from the extracted text; quantitative relationships are judged from captions and in-text statements only.
- All 12 supplementary notes carry key evidence (autocrine mechanism, vps5Δ quantification, cheaters, dPCR) but were not included in the provided text.
- The DOI prefix 10.64898 and the 2026 posting date are unusual for bioRxiv and are treated as given metadata; the preprint could not be verified offline.
- License/watermark boilerplate interleaves with body text, indicating imperfect extraction; some numeric statements may be mis-associated.
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