A pH‐Based High‐Throughput Screening of Sucrose‐Utilizing Transglucosidases for the Development of Enzymatic Glucosylation Tools

Champion, Elise; Moulis, Claire; Morel, Sandrine; Mulard, Laurence A.; Monsan, Pierre; Remaud‐Siméon, Magali; André, Isabelle

doi:10.1002/cctc.201000111

Cited by 8 publications

(20 citation statements)

References 19 publications

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“…Champion et al (2), for example, report screening about 8,000 variants when randomizing two NNN positions. When screening 8,000 variants, the probability of discovering the best variant in variant space, P(T 1 ), is 0.997; to make this probability "only" 0.99, about 5,500 variants are needed.…”

Section: Discussionmentioning

confidence: 99%

When Second Best Is Good Enough: Another Probabilistic Look at Saturation Mutagenesis

Nov

2012

Appl Environ Microbiol

107

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We developed new criteria for determining the library size in a saturation mutagenesis experiment. When the number of all possible distinct variants is large, any of the top-performing variants (e.g., any of the top three) is likely to meet the design requirements, so the probability that the library contains at least one of them is a sensible criterion for determining the library size. By using a criterion of this type, one may significantly reduce the library size and thus save costs and labor while minimally compromising the quality of the best variant discovered. We present the probabilistic tools underlying these criteria and use them to compare the efficiencies of four randomization schemes: NNN, which uses all 64 codons; NNB, which uses 48 codons; NNK, which uses 32 codons; and MAX, which assigns equal probabilities to each of the 20 amino acids. MAX was found to be the most efficient randomization scheme and NNN the least efficient. TopLib, a computer program for carrying out the related calculations, is available through a user-friendly Web server. Saturation mutagenesis (also called oligonucleotide-directed randomization) is a protein-engineering technique that has been used widely and successfully to improve protein properties such as catalytic activity, enantioselectivity, thermostability, and binding affinity (3,12,14,16). We use the term "activity" for the protein's property under optimization, but the methodology developed below is aimed at any desirable protein feature that may be influenced by mutation.In saturation mutagenesis, one or more positions along the protein sequence are identified as likely to accommodate beneficial mutations and are then randomized, i.e., the amino acids at these positions are replaced by random ones. The randomization originates at the DNA level, typically via degenerate primers containing a mixture of sequences at the chosen codons. To decrease the chances of introducing a premature stop codon, reduced codon sets are often used: NNB, NNS, and NNK codons (where N ϭ A/C/G/T, B ϭ C/G/T, S ϭ C/G, and K ϭ G/T) are popular choices that still encode all 20 amino acids, but the use of codon sets encoding fewer amino acids has been also advocated (9, 15). More sophisticated randomization schemes, such as MAX (6, 7), result in equal probabilities for all 20 amino acids (or for some predetermined subset thereof) without encoding stop codons. Either way, a large number of random variants, which together constitute a library, are produced and then screened in an attempt to discover a highly active variant among them. Clearly, the larger the library, the higher the probability of exploring more distinct variants. We shall use the term "variant space" to denote the set of all possible distinct variants in a given experiment; this space is determined by the number of positions randomized and the randomization scheme.The probabilistic literature on saturation mutagenesis (1, 5, 8, 11) focuses mainly on two mathematical quantities: the first is the expected percentage of variant spa...

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Section: Discussionmentioning

confidence: 99%

When Second Best Is Good Enough: Another Probabilistic Look at Saturation Mutagenesis

Nov

2012

Appl Environ Microbiol

107

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“…In two unrelated experiments, each involving randomization of a single NNS position, Boersma et al [42] screened 1,250 variants and Maeda et al [43] screened 360 variants, where ∼80 variants seem to suffice. Similarly, Champion et al [44] screened ∼8,000 variants when randomizing two NNN positions, where ∼2,000 seem to suffice.…”

Section: Discussionmentioning

confidence: 99%

Fitness Loss and Library Size Determination in Saturation Mutagenesis

Nov

2013

PLoS ONE

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Saturation mutagenesis is a widely used directed evolution technique, in which a large number of protein variants, each having random amino acids in certain predetermined positions, are screened in order to discover high-fitness variants among them. Several metrics for determining the library size (the number of variants screened) have been suggested in the literature, but none of them incorporates the actual fitness of the variants discovered in the experiment. We present the results of an extensive simulation study, which is based on probabilistic models for protein fitness landscape, and which investigates how the result of a saturation mutagenesis experiment – the fitness of the best variant discovered – varies as a function of the library size. In particular, we study the loss of fitness in the experiment: the difference between the fitness of the best variant discovered, and the fitness of the best variant in variant space. Our results are that the existing criteria for determining the library size are conservative, so smaller libraries are often satisfactory. Reducing the library size can save labor, time, and expenses in the laboratory.

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“…The screening protocol was inspired from Champion et al . 34 and is detailed in Supplementary Fig. S1 available.…”

Section: Methodsmentioning

confidence: 99%

Engineering a branching sucrase for flavonoid glucoside diversification

Malbert

Moulis

Brison

et al. 2018

Sci Rep

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Enzymatic glycosylation of flavonoids is an efficient mean to protect aglycons against degradation while enhancing their solubility, life time and, by extension, their bioavailability which is critical for most of their applications in health care. To generate a valuable enzymatic platform for flavonoid glucosylation, an α-1,2 branching sucrase belonging to the family 70 of glycoside-hydrolases was selected as template and subsequently engineered. Two libraries of variants targeting pair-wise mutations inferred by molecular docking simulations were generated and screened for quercetin glucosylation using sucrose as a glucosyl donor. Only a limited number of variants (22) were retained on the basis of quercetin conversion and product profile. Their acceptor promiscuity towards five other flavonoids was subsequently assessed, and the automated screening effort revealed variants showing remarkable ability for luteolin, morin and naringenin glucosylation with conversion ranging from 30% to 90%. Notably, naringenin and morin, a priori considered as recalcitrant compounds to glucosylation using this α-transglucosylases, could also be modified. The approach reveals the potential of small platforms of engineered GH70 α-transglucosylases and opens up the diversity of flavonoid glucosides to molecular structures inaccessible yet.

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A pH‐Based High‐Throughput Screening of Sucrose‐Utilizing Transglucosidases for the Development of Enzymatic Glucosylation Tools

Cited by 8 publications

References 19 publications

When Second Best Is Good Enough: Another Probabilistic Look at Saturation Mutagenesis

When Second Best Is Good Enough: Another Probabilistic Look at Saturation Mutagenesis

Fitness Loss and Library Size Determination in Saturation Mutagenesis

Engineering a branching sucrase for flavonoid glucoside diversification

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