Evidence map›Paper›PMID 37105971›Full record

ArticleNature communications2023

Automated design of protein-binding riboswitches for sensing human biomarkers in a cell-free expression system.

Grace E Vezeau, Lipika R Gadila, Howard M Salis

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
6.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
  2. Design and discovery of 'tug-of-war' riboswitches.bioRxiv : the preprint server for biology · 2026
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  7. Programming Next-Generation Synthetic Biosensors by Genetic Circuit Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Grace E VezeauDepartment of Agricultural and Biological Engineering, Pennsylvania State University, University Park, PA, 16802, USA.
Lipika R GadilaDepartment of Chemical Engineering, Pennsylvania State University, University Park, PA, 16802, USA.
Howard M SalisDepartment of Agricultural and Biological Engineering, Pennsylvania State University, University Park, PA, 16802, USA. salis@psu.edu.ORCID 0000-0003-0411-4390
Pennsylvania State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-free genetically encoded biosensors have been developed to detect small molecules and nucleic acids, but they have yet to be reliably engineered to detect proteins. Here we develop an automated platform to convert protein-binding RNA aptamers into riboswitch sensors that operate within low-cost cell-free assays. We demonstrate the platform by engineering 35 protein-sensing riboswitches for human monomeric C-reactive protein, human interleukin-32γ, and phage MS2 coat protein. The riboswitch sensors regulate output expression levels by up to 16-fold with input protein concentrations within the human serum range. We identify two distinct mechanisms governing riboswitch-mediated regulation of translation rates and leverage computational analysis to refine the protein-binding aptamer regions, improving design accuracy. Overall, we expand the cell-free sensor toolbox and demonstrate how computational design is used to develop protein-sensing riboswitches with future applications as low-cost medical diagnostics.

Indexed as

Aptamers, NucleotideBiosensing TechniquesRiboswitchBiomarkersHumansProtein EngineeringAptamers, NucleotideBiomarkersRiboswitch

Identifiers

PMID37105971
PMCPMC10140043
OpenAlexW4367181448

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.