Abstract
Bacteria are an enormous and largely untapped reservoir of biosensing proteins. We describe an approach to identify and isolate bacterial allosteric transcription factors (aTFs) that recognize a target analyte and to develop these TFs into biosensor devices. Our approach utilizes a combination of genomic screens and functional assays to identify and isolate biosensing TFs, and a quantum-dot Förster Resonance Energy Transfer (FRET) strategy for transducing analyte recognition into real-time quantitative measurements. We use this approach to identify a progesterone-sensing bacterial aTF and to develop this TF into an optical sensor for progesterone. The sensor detects progesterone in artificial urine with sufficient sensitivity and specificity for clinical use, while being compatible with an inexpensive and portable electronic reader for point-of-care applications. Our results provide proof-of-concept for a paradigm of microbially-derived biosensors adaptable to inexpensive, real-time sensor devices.
Highlights
Bacteria are an enormous and largely untapped reservoir of biosensing proteins
We show the application of our approach to develop an optical progesterone sensor based on a previously uncharacterized microbial allosteric transcription factors (aTFs) identified with our screening approach
Our approach (Supplementary Fig. 1) is based on three observations: bacterial TFs commonly bind upstream of their genes to regulate their own promoters or those of adjacent genes[17,18,19,20,21], genes for the metabolism of analytes are often found in genome clusters[22], and these clusters are often induced by their substrates via TFs in genomic proximity[23,24,25,26]
Summary
Experiments with varying concentrations of progesterone demonstrated that progesterone-induced dissociation was dose-dependent (Fig. 2b, c) Together, these data confirm that SRTF1 is an aTF that binds its cognate DNA site in the absence of sterol hormones and allosterically rapidly unbinds in the presence of progesterone. We observed a clear and reproducible dose-dependent decrease in sensor response with increasing progesterone (Fig. 3c), corresponding to progressive unbinding of SRTF1 from the oligonucleotide and decreased FRET. Published reports have demonstrated the ability to dramatically alter the specificity profile of aTFs with a combination of random mutagenesis, directed evolution, and targeted protein modifications[41] These methods can be used to further increase the specificity of SRTF1-based sensors to progesterone. Our results provide a paradigm for the targeted development of a diverse range of sensor devices
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