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Fluorescence labelling in re-coded E. coli with non-canonical chemical entities: Single-codon labelling for single-molecule tracking
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology. (Magnus Johansson Lab)ORCID iD: 0000-0003-0968-9011
2026 (English)Doctoral thesis, comprehensive summary (Other academic)
Description
Abstract [en]

Single-molecule tracking (SMT) enables direct observation of molecular dynamics in living cells, revealing heterogeneity hidden by in vitro ensemble measurements. However, current protein labeling strategies using self-labeling tags such as HaloTag (~33 kDa) or SNAPtag (~20 kDa) can interfere with the function of proteins that undergo large conformational changes or participate in tightly orchestrated multi-factor complexes. This thesis develops and applies FLORENCE (Fluorescence Labelling in Re-coded E. coli with Non-canonical Chemical Entities), a genetic code expansion (GCE) technology that enables site-specific protein labeling with single-codon resolution for SMT of bacterial elongation factors.

Conventional labeling with bulky tags can prevent functional ribosome binding of translation factors. To address this, in Paper I, we systematically optimized a complete GCE system in genomically re-coded E. coli (GRE) strains where all 321 UAG stop codons have been converted to UAA and release factor 1 deleted. We evaluated pyrrolysyl-tRNA synthetase variants (PylRS1–3), characterized six GRE strains for growth rate and morphology, and optimized a single-plasmid vector architecture combining the orthogonal translation system with the target gene. Using strain-promoted azide-alkyne cycloaddition (SPAAC) between BCNcontaining non-canonical amino acids and JF646-azide dye, we achieved complete labeling within 30 minutes in live cells. Validation with dual-labeled HaloTag and LacY reporters demonstrated that FLORENCE yields SMT results comparable to conventional HaloTag labeling.

In Paper II we applied FLORENCE to study elongation factor G (EF-G), an essential for ribosomal translocation. HaloTag fusions at both termini showed that bulky tags abolish EF-G function in vivo. In contrast, FLORENCE labeling at position 301 (301UAG) revealed 30–45% slow-state occupancy consistent with ribosome binding, as confirmed by tracking the catalytically inactive H92A mutant.

To improve GRE fitness for physiological studies, Paper III reports a novel GRE*, with superior growth compared to the parental GRE6. Single-cell microfluidic analysis confirmed wild-type-like phenotype, and whole genome sequencing revealed deletion of the ratA translation initiation toxin. FLORENCE-labelled EF-G and EF-Tu were tracked at 1 ms temporal resolution, with catalytically inactive mutants showing an increase in ribosome-bound states. Still, as in Paper III, optimization of the expression level of these factors remains critical.

In summary, this thesis establishes FLORENCE as a user-friendly experimental platform for SMT investigation of translation factors and other challenging targets in living bacterial cells.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2026. , p. 77
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 2631
Keywords [en]
Translation elongation, genetic code expansion, single-molecule tracking, protein synthesis, FLORENCE
National Category
Molecular Biology
Research subject
Molecular Life Sciences; Biology; Microbiology
Identifiers
URN: urn:nbn:se:uu:diva-577811ISBN: 978-91-513-2727-3 (print)OAI: oai:DiVA.org:uu-577811DiVA, id: diva2:2033027
Public defence
2026-03-17, Sal XI, Universitetshuset, Biskopsgatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2026-02-11 Created: 2026-01-28 Last updated: 2026-02-11
List of papers
1. Optimization of the genetic code expansion technology for intracellular labelling and single-molecule tracking of proteins in genomically re-coded E. coli
Open this publication in new window or tab >>Optimization of the genetic code expansion technology for intracellular labelling and single-molecule tracking of proteins in genomically re-coded E. coli
Show others...
2026 (English)In: RSC Chemical Biology, E-ISSN 2633-0679Article in journal (Refereed) Published
National Category
Natural Sciences
Research subject
Biochemistry
Identifiers
urn:nbn:se:uu:diva-573024 (URN)10.1039/d5cb00221d (DOI)
Funder
EU, European Research Council, 947747-SMACKSwedish Research Council, 2019-03714Swedish Research Council, 2023-03383
Available from: 2025-12-09 Created: 2025-12-09 Last updated: 2026-01-28
2. Single-molecule tracking of Elongation factor G in re-coded E. coli
Open this publication in new window or tab >>Single-molecule tracking of Elongation factor G in re-coded E. coli
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Protein synthesis is one of the central processes of life. With recent single-molecule tracking techniques, detailed information about protein synthesis dynamics has been extracted from living cells. Still, there are conflicting results and very little knowledge about the dynamic behaviour of elongation factors because of the lack of fluorescent labels that preserve their native function. In the present study, we combine single-molecule tracking with the genetic code expansion (GCE) technology to directly observe ribosome binding dynamics of translation elongation factor EF-G in growing E. coli cells. We show that EF-G cannot be functionally labelled with the commonly used HaloTag. Instead, we utilize bio-orthogonal click-chemistry to fluorescently label EF-G in an optimized re-coded E. coli. This system reports the first estimation of the ribosome-binding time of EF-G in vivo, contributing to measuring the kinetics of elongation under physiological conditions. These findings open a technological avenue for difficult-to-label molecules inside living cells.

Keywords
Translation elongation, genetic code expansion, single-molecule tracking, protein synthesis
National Category
Biophysics
Research subject
Biology with specialization in Microbiology
Identifiers
urn:nbn:se:uu:diva-577767 (URN)
Projects
European Research Council (947747-SMACK)Swedish Research Council (2019-03714, 2023-03383)
Funder
EU, European Research Council, 947747-SMACK
Available from: 2026-01-28 Created: 2026-01-28 Last updated: 2026-01-30
3. Adaptive lab evolution of a fully re-coded E.coli for single-molecule tracking
Open this publication in new window or tab >>Adaptive lab evolution of a fully re-coded E.coli for single-molecule tracking
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Genomically recoded Escherichia coli (GRE) strains represent a valuable tool as model organisms for single-molecule tracking via click-labelling. These strains are constantly being engineered to incorporate non-canonical amino acids, enabling expanded chemical functionality. However, extensive genome-scale recoding frequently reduces their fitness and imposes metabolic re-wiring limiting the utility of GREs as practical model organisms for live-cell imaging in vivo. This study reports that previously optimized GRE6 was subjected to adaptive laboratory evolution (ALE) in an imaging-rich defined media (RDM) to recover fitness. The evolved strain displayed improved growth relative to the ancestral GRE6, and a wild-type-like growth was confirmed by single-cell analysis. Whole-genome sequencing revealed deletion of the initiation inhibitor ratA. ncAA incorporation was comparable or slightly improved relative to the common MG1655 strain. These results point out the importance of applying ALE in parallel to rational genome engineering in expanding the benefits of genomically re-coded organisms. Moreover, they point out the necessity for the development of improved vectors for essential translation factors for SMT.

Keywords
Adaptive lab evolution, single-molecule tracking, genomically re-coded organisms
National Category
Cell Biology
Research subject
Molecular Life Sciences
Identifiers
urn:nbn:se:uu:diva-577809 (URN)
Available from: 2026-01-28 Created: 2026-01-28 Last updated: 2026-01-28

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12345674 of 22
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