Ranomics
Flow cytometry cell sorting equipment used for FACS-based selection of yeast surface display libraries
Case study

pH-dependent antibody engineering via yeast surface display

A worked technical case study from a real client campaign. Six rounds of FACS selection across a 640-clone library converged on a small set of hotspot substitutions that switch antibody binding between physiological and endosomal pH.

640-clone targeted mutagenesis library, NGS-quantified pre-selection
Six-cycle FACS sort series with paired pH-7.4 and pH-5.5 selection arms
Convergent hotspot residues (designated H-1 and H-2) emerging across independent lineages
Per-cycle enrichment-score methodology for quantitative variant ranking
Top candidate panel selected by cumulative enrichment across the full sort series

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What's inside

A complete walkthrough of the campaign, from library design to ranked candidates

Library design and quality control

640 targeted variants, NGS-confirmed coverage and uniformity before selection begins. Diversity rationale and the trade-offs that informed library size.

FACS panel and gating strategy

Two-color labeling for surface expression and antigen binding, paired pH-7.4 and pH-5.5 sort arms, gating thresholds tuned per cycle to maintain enrichment without losing diversity.

Enrichment-score methodology

How per-cycle read counts are converted into a quantitative enrichment metric. Why enrichment scores rank variants more reliably than raw read counts at any single cycle.

Convergent hotspot analysis

Two residues (H-1 and H-2) recurred across independent enriched lineages. Convergence is the strongest signal that a position genuinely controls pH-dependent binding rather than reflecting library bias.

Cumulative enrichment ranking

Top candidates ranked by cumulative enrichment across all six cycles. Why a multi-cycle composite outperforms picking winners from any single sort.

Decision framework for pH-dependent campaigns

When pH-dependent binding is worth engineering for (FcRn-mediated recycling, tumor-microenvironment selectivity, ADC linker stability) and how to scope library size and sort cycle count for your target.

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