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Quantitative Biology

ISSN 2095-4689

ISSN 2095-4697(Online)

CN 10-1028/TM

邮发代号 80-971

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Quantitative Biology  2023, Vol. 11 Issue (3): 214-230   https://doi.org/10.15302/J-QB-022-0326
  本期目录
From qualitative to quantitative: the state of the art and challenges for plant synthetic biology
Chenfei Tian1,2, Jianhua Li1(), Yong Wang1()
1. CAS-Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
2. University of Chinese Academy of Sciences, Beijing 100039, China
 全文: PDF(4621 KB)   HTML
Abstract：

Backgrounds: As an increasing number of synthetic switches and circuits have been created for plant systems and of synthetic products produced in plant chassis, plant synthetic biology is taking a strong foothold in agriculture and medicine. The ever-exploding data has also promoted the expansion of toolkits in this field. Genetic parts libraries and quantitative characterization approaches have been developed. However, plant synthetic biology is still in its infancy. The considerations for selecting biological parts to design and construct genetic circuits with predictable functions remain desired.

Results: In this article, we review the current biotechnological progresses in field of plant synthetic biology. Assembly standardization and quantitative approaches of genetic parts and genetic circuits are discussed. We also highlight the main challenges in the iterative cycles of design-build-test-learn for introducing novel traits into plants.

Conclusion: Plant synthetic biology promises to provide important solutions to many issues in agricultural production, human health care, and environmental sustainability. However, tremendous challenges exist in this field. For example, the quantitative characterization of genetic parts is limited; the orthogonality and the transfer functions of circuits are unpredictable; and also, the mathematical modeling-assisted circuits design still needs to improve predictability and reliability. These challenges are expected to be resolved in the near future as interests in this field are intensifying.
Key words： plant synthetic biology    quantitative characterization    genetic parts    genetic circuits
收稿日期: 2022-08-01      出版日期: 2023-10-08
Corresponding Author(s): Jianhua Li,Yong Wang   
 引用本文:   
. [J]. Quantitative Biology, 2023, 11(3): 214-230.
Chenfei Tian, Jianhua Li, Yong Wang. From qualitative to quantitative: the state of the art and challenges for plant synthetic biology. Quant. Biol., 2023, 11(3): 214-230.
 链接本文:  
https://academic.hep.com.cn/qb/CN/10.15302/J-QB-022-0326
https://academic.hep.com.cn/qb/CN/Y2023/V11/I3/214
Databases and toolsDescriptionRefs.
Scientific databaseMultiple databases of multi-omics
MPODMulti-omics database for medicinal plants[21]
EPDThe eukaryotic promoter database[22]
TDTHubA web server tool for the analysis of transcription factor binding sited in plants[23]
PPDBA web-based plant promoter database[24]
PlantCAREA database of plant cis-acting regulatory elements, enhancers and repressors[25]
OptoBaseAn online platform for molecular optogenetics[26]
TRANSFACA database on eukaryotic transcription factors[27]
RGPDBA database of root-associated genes and promoters in maize, soybean, and sorghum[28]
TSSFinderA tool for prediction and annotation of different organisms[29]
PlantPromA database of plant promoter sequences[30]
TSSPPrediction of plant promoters[31]
NSITE-PLRecognition of plant regulatory motifs[32]
AGRISThe Arabidopsis gene regulatory information server[33]
AthaMapA genome-wide map of putative transcription factor binding sites in Arabidopsis thaliana[34]
Tab.1  
Fig.1  
Fig.2  
Fig.3  
ProductsPlant chassisThe number of genesUsed promotersUsed terminatorsRefs.
Omega-3 long chain polyunsaturated fatty acidsCamelina sativa seed;Stable transformation 9PUSP, PCNL, PSBP, PNP, PPvArc, PGLY, PCsVMVT35STOCS,TCatpA, TE9, TPvArc, TNOS, THSP, TPhaseolin, TGly[84]
Omega-3 long chain polyunsaturated fatty acidsBrassica napus seed; Brassica juncea seedStable transformation 9PFP1, PFAE1, PCNL1, PCNL2, P35STNOS, TLectin, TCNL1, TCNL2[85,86]
BiomassNicotiana tabacumStable transformation 3PNOS, P35STNOS[87]
CoQ10Solanum lycopersicum fruitStable transformation5PE8, P35STAtHSP, T35S[88]
Casbene-derived diterpenoidsNicotiana benthamiana leafTransient transformation; stable transformation6P35S, PStSTLS, PAtCab1, PAtuNos, PAtuMAS, PSlRbcS1, PSlRbcS2, PAtRbcS1B, PSlRbcS3A, PSIH4, PAtLHB1B1TAtuMAS, TAtug7, TAtuOCS, TAtuNos[89]
Auxin analogsN. benthamiana leafTransient transformation4P35STCaMV, TpolyA[90]
AstaxanthinN. benthamianaStable transformation2P35S; PFMVm 34STNOS, T35S[91]
Iron and zinc concentrations Manihot esculenta storage rootStable transformation2PA14, Ppatatin1T35S, TNOS[92]
Folate Z. mays and Triticum aestivum endospermStable transformation3P35S, PLeg1A, PGluCT35S, TNOS[93]
AstaxanthinZea mays seedStable transformation9P35S, P2BDEN (PR5SGPA/P2R5SGPA)T35S, TNOS[94]
N-formyldemecolcineN. benthamiana leafTransient transformation16P35STNOS[95]
Taxadiene-5α-olN. benthamiana leafTransient transformation4P35STNOS[96]
PheromoneN. benthamianaStable transformation4P35ST35S[97]
ViolaceinN. benthamiana leafTransient transformation5PAtHsp18, PMAS, PAct2, PRbcS, PBch1TAtHsp, TAtRbcS, TAtAct2, TAtUbq3, TNOS[62]
AstaxanthinRice endospermStable transformation4PGlub1, PGlub4, PGlb1, PGluCTmas, Tags, T35S[63]
AnthocyaninsRice endospermStable transformation8P10KDa, P16KDa, Pnpr33, PGlub5, PGlb1, PGlub4, PGlub1, PGluCTrbc, Tmas, TNOS, Tocs, Tags, T35S[64]
Tab.2  
Fig.4  
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