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In vivo biosensors: mechanisms, development, and applications

  • Metabolic Engineering and Synthetic Biology - Original Paper
  • Published:
Journal of Industrial Microbiology & Biotechnology

Abstract

In vivo biosensors can recognize and respond to specific cellular stimuli. In recent years, biosensors have been increasingly used in metabolic engineering and synthetic biology, because they can be implemented in synthetic circuits to control the expression of reporter genes in response to specific cellular stimuli, such as a certain metabolite or a change in pH. There are many types of natural sensing devices, which can be generally divided into two main categories: protein-based and nucleic acid-based. Both can be obtained either by directly mining from natural genetic components or by engineering the existing genetic components for novel specificity or improved characteristics. A wide range of new technologies have enabled rapid engineering and discovery of new biosensors, which are paving the way for a new era of biotechnological progress. Here, we review recent advances in the design, optimization, and applications of in vivo biosensors in the field of metabolic engineering and synthetic biology.

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Abbreviations

ADC:

Analog-to-digital converter

ADH:

Alcohol dehydrogenase

1,4-BDO:

1,4-Butanediol

CAD :

Cis-aconitate decarboxylase gene

CCM:

Cis,cis-muconic acid

CDA:

Cytidine deaminase

2′,3′-cGAMP:

(2′-5′,3′-5′) Cyclic guanosine monophosphate-adenosine monophosphate

CE:

Capillary electrophoresis

CFP:

Cyan fluorescent protein

COMPACTER:

Customized optimization of metabolic pathways by combinatorial transcriptional engineering

DFHBI:

3,5-Difluoro-4-hydroxybenzylidene imidazolinone

34DHB:

3,4-Dihydroxy benzoate

l-DOPA:

l-3,4-Dihydroxyphenylalanine

DSRS:

Dynamic sensor-regulator system

epPCR:

Error-prone PCR

FACS:

Fluorescence activated cell sorting

fcy1 :

Cytosine deaminase gene

FFA:

Free fatty acid

FI:

Fluorescence intensity

FP:

Fluorescent proteins

FPP:

Farnesyl pyrophosphate

FREP:

Feedback-regulated evolution of phenotype

FRET:

Förster resonance energy transfer

GEMM:

Genes for the environment, membranes, and motility

GFP:

Green fluorescent protein

GlcN6P:

Glucosamine 6-phosphate

GlcNAc:

N-acetyl glucosamine

gltA :

Citrate synthetase gene

GPCR:

G-protein-coupled receptors

HHR:

Hammerhead ribozyme

Hi-Fi:

High-fidelity

HK:

Histidine kinase

3-HP:

3-Hydroxy propionic acid

IL:

Interleukin

IPTG:

Isopropyl-beta-d-thiogalactopyranoside

α-KGDH:

α-Ketoglutarate dehydrogenase

LAO:

Lysine-binding periplasmic protein

LTTR:

LysR-type transcriptional regulator

MAGE:

Multiplex automated genome engineering

malQ :

Maltase gene

MBP:

Metabolite-binding protein

MetN:

Methionine-binding protein

MT:

Metallothionein

MVA:

Mevalonate

NAGK:

N-acetyl-l-glutamate kinase

NeuAC:

N-acetylneuramine acid

NMM:

N-methyl mesoporphyrin IX

OAH:

O-acetyl homoserine

OAS:

O-acetyl serine

PBP:

Periplasmic-binding proteins

PopQC:

Population quality control

QS:

Quorum sensing

RAGE:

RNAi-assisted genome evolution

RBS:

Ribosome binding site

ROK:

Repressor, open reading frame, kinase

RR:

Response regulator

SAM:

S-adenosylmethionine

SAH:

S-adenosyl-l-homocysteine

SATRE:

Sensor-assisted transcriptional regulator engineering

SBA:

Streptavidin-binding aptamer

SELEX:

Systematic evolution of ligands by exponential enrichment

T6P:

Trehalose-6-phosphate

Tc:

Tetracycline

TCA:

Tricarboxylic acid

TCS:

Two-component system

TF:

Transcriptional factor

TreR:

Trehalose repressor

TRMR:

Trackable multiplex recombineering

YFP:

Yellow fluorescent protein

YOGE:

Yeast oligo-mediated genome engineering

ZF:

Zinc finger

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Acknowledgements

We acknowledge funding supports from the State Key Laboratory of Microbial Technology Open Projects Fund in China (Project no. M2017-02 to S.S.), the National Research Foundation Singapore (NRF2013-THE001-095 to E.L.A.), and the Visiting Investigator Programme of Agency for Science, Technology, and Research, Singapore and US Department of Energy (DE-SC0018260 to H.Z.).

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Authors and Affiliations

  1. Metabolic Engineering Research Laboratory, Science and Engineering Institutes, Agency for Science, Technology and Research, Singapore, Singapore

    Shuobo Shi, Ee Lui Ang & Huimin Zhao

  2. Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, People’s Republic of China

    Shuobo Shi & Huimin Zhao

  3. Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Huimin Zhao

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  1. Shuobo Shi
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  2. Ee Lui Ang
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Correspondence to Ee Lui Ang or Huimin Zhao.

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Shi, S., Ang, E.L. & Zhao, H. In vivo biosensors: mechanisms, development, and applications. J Ind Microbiol Biotechnol 45, 491–516 (2018). https://doi.org/10.1007/s10295-018-2004-x

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