Development of a Biosensor Platform for Phenolic Compounds Using a Transition Ligand Strategy

Abstract

The time-consuming and laborious characterization of protein or microbial strain designs limits the development of high-performance biocatalysts for biotechnological applications. Here, transcriptional biosensors emerged as valuable tools as they allow for rapid characterization of several thousand variants within a very short time. However, for many molecules of interest, no specific transcriptional regulator determining a biosensor’s specificity is available. We present an approach for rapidly engineering biosensor specificities using a semirational transition ligand approach combined with fluorescence-activated cell sorting. In this two-step approach, a biosensor is first evolved toward a more relaxed-ligand specificity before using the resulting variant as the starting point in a second round of directed evolution toward high specificity for several chemically different ligands. By following this strategy, highly specific biosensors for 4-hydroxybenzoic acid, p-coumaric acid, 5-bromoferulic acid, and 6-methyl salicylic acid were developed, starting from a biosensor for the intracellular detection of trans-cinnamic acid.

Metabolic engineering of Corynebacterium glutamicum for the production of anthranilate from glucose and xylose

“…The pSenCA biosensor for the intracellular detection of cinnamic acid and phenylpropionic acid in E. coli was previously engineered to also detect other small aromatic molecules of biotechnological interest (Flachbart et al, 2019(Flachbart et al, , 2021. One of these customized biosensor variants is pSen6MSA, engineered for the detection of 6-methylsalicylic acid (6MSA).…”

Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology

“…At the end of each cycle, improved mutants are propagated for further rounds of mutation until functional improvements reach a plateau. Through these strategies, many facets of sensor function can be modified including target specificity [ 47 , 49 , 285 , 286 ], sensitivity [ 41 , 43 , 112 , 287 ], dynamic range [ 42 , 52 , 288 ], cooperativity [ 112 ], DNA interaction type [ 38 , 262 , 264 , 289 ], and stability [ 290 , 291 ].…”

“…Mutations can have a broad range of effects on phenotype, and modifications in specific functional domains can alter sensitivities or even target recognition entirely. For example, mutations have been introduced in ligand binding pockets to both improve target specificity [ 111 , 292 ] or even change the target molecule entirely [ 47 , 49 , 285 ]. Similarly, mutations can be introduced to DNA binding domains to tune operator binding kinetics, as well as create orthogonal operator sequences to increase the multiplexing potential of a limited repertoire of parts [ 49 , 262 ].…”

“…In addition to functional domains, distal mutations can alter protein stability and conformation, and play a major role in sensor function, affecting sensitivity to the target molecule [ 42 , 52 , 288 , 293 ], specificity to the ligand [ 47 , 285 , 286 ], and dynamic range [ 42 , 52 , 288 ]. Interestingly, distal mutations in inhibitory transcription factors have even been shown to invert a sensor's response [ 38 , 112 , 289 ].…”

The Growth Dependent Design Constraints of Transcription-Factor-Based Metabolite Biosensors

“…Metabolite-responsive transcription factor (MRTF)-based biosensors have broad applications in synthetic biology and metabolic engineering, ranging from metabolic detection, − screening and selecting for high-metabolite-producing strains, − dynamic metabolic control, − to strain functional evolution. , Nature has evolved various MRTFs that can be harnessed to create biosensors for a wide range of metabolites. − Protein engineering and directed evolution of MRTF have further expanded the range of compounds that can be detected. − Additionally, promoters regulated by MRTFs can be engineered to tune sensitivity and dynamic range, , enabling precise control of biosensor performance. , These biosensors can be further layered to create complex circuits, , which require a well-defined performance for correct operation …”