In-one-pot-at-a-time Ligation for High-throughput Construction of a Protein Expression Vector Library

Nakazawa, Hikaru; Todokoro, Rui; Ishigaki, Yuri; Kumagai, Izumi; Umetsu, Mitsuo

doi:10.1246/cl.130014

Cited by 5 publications

(9 citation statements)

References 13 publications

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“…To maximize the speed of this screening process, we developed a method for high-throughput preparation of recombinant proteins by refining the steps of expression vector construction, protein expression, and protein purification. For instance, to simultaneously construct a number of expression vectors, we applied the in-one-pot-at-a-time (iPaT) ligation approach 40 . Gene fragments encoding a VH and VL domain were prepared from scFv expression vectors, and a mixture of them were introduced into linearized expression vectors by iPaT ligation to simultaneously generate each diabody expression vector (Fig.…”

Section: Discussionmentioning

confidence: 99%

“…DNA encoding VH domains and a part of linker sequence (2 × GGGGS) was removed from the 13 pRA vectors for anti-EGFR family members by digestion with Nco I and Bsp EI to produce linearized vectors. Finally, the four digested fragments containing anti-CD3 or -CD28 VH domains were simultaneously ligated into the 13 VH-minus and linearized pRA vectors to replace the original VH domain 40 . E. coli bacteria were transformed with the resultant vectors to clone and separate each vector containing a hetero scFv gene with an anti-CD3 or -CD28 VH domain followed by an anti-EGFR-family VL domain.…”

Section: Methodsmentioning

confidence: 99%

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A semi high-throughput method for screening small bispecific antibodies with high cytotoxicity

Sugiyama

Umetsu

Nakazawa

et al. 2017

Sci Rep

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Small bispecific antibodies that induce T-cell–mediated cytotoxicity have the potential to damage late-stage tumor masses to a clinically relevant degree, but their cytotoxicity is critically dependent on their structural and functional properties. Here, we constructed an optimized procedure for identifying highly cytotoxic antibodies from a variety of the T-cell–recruiting antibodies engineered from a series of antibodies against cancer antigens of epidermal growth factor receptor family and T-cell receptors. By developing and applying a set of rapid operations for expression vector construction and protein preparation, we screened the cytotoxicity of 104 small antibodies with diabody format and identified some with 103-times higher cytotoxicity than that of previously reported active diabody. The results demonstrate that cytotoxicity is enhanced by synergistic effects between the target, epitope, binding affinity, and the order of heavy-chain and light-chain variable domains. We demonstrate the importance of screening to determine the critical rules for highly cytotoxic antibodies.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

A semi high-throughput method for screening small bispecific antibodies with high cytotoxicity

Sugiyama

Umetsu

Nakazawa

et al. 2017

Sci Rep

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“…Here, saturation mutagenesis by means of 22-c trick method (15) was independently applied to each residue, to make saturated groups of GFP variants where only one of the four residues is mutated (i.e., 19 × 4 = 76 variants). The gene fragments of GFP variants with saturated mutagenesis at one residue were amplified by PCR with a pair of designed 22-c trick primer (Table S2), and the mixed gene fragments were ligated in expression vectors in one pot (16). Escherichia (E.) coli bacteria were transformed with the mixture of the ligated vectors and they were spread on agar culture plates to form colonies, each of which should contain a vector bearing a gene fragment.…”

Section: Preparation Of the Initial Data Of Gfp Variants For Machine Learningmentioning

confidence: 99%

Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins

et al. 2018

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Molecular evolution based on mutagenesis is widely used in protein engineering. However, optimal proteins are often difficult to obtain due to a large sequence space. Here, we propose a novel approach that combines molecular evolution with machine learning. In this approach, we conduct two rounds of mutagenesis where an initial library of protein variants is used to train a machine-learning model to guide mutagenesis for the second-round library. This enables us to prepare a small library suited for screening experiments with high enrichment of functional proteins. We demonstrated a proof-of-concept of our approach by altering the reference green fluorescent protein (GFP) so that its fluorescence is changed into yellow. We successfully obtained a number of proteins showing yellow fluorescence, 12 of which had longer wavelengths than the reference yellow fluorescent protein (YFP). These results show the potential of our approach as a powerful method for directed evolution of fluorescent proteins.

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Section: Science Advancesmentioning

confidence: 99%

“…The amplified gene fragments of GFP variants were digested with NotI and NdeI, then were ligated into the linear (NotI-and NdeI-digested) pET22b vectors. E. coli bacteria were transformed with the resultant vectors and spread on an agar media plate containing 100 g/mL ampicillin to form colonies (16). The colonies grown on the agar media plates were randomly After washing with 0.005% Tween 20 in PBS, 50 L of 3,3',5,5'-tetramethylbenzidine solution (1step Ultra TMB-ELISA, Thermo scientific, MA, USA) was added and incubated for 2-10 min at 37 °C, and then absorbance at 450 nm was measured after the addition of 50 L of 2 M H2SO4.…”

Section: Preparation Of Gfp Variantsmentioning

confidence: 99%

A machine-learning-guided mutagenesis platform for accelerated discovery of novel functional proteins

Saitô

Oikawa

Nakazawa

et al. 2018

Preprint

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Molecular evolution based on mutagenesis is widely used in protein engineering. However, optimal proteins are often difficult to obtain due to a large sequence space that requires high costs for screening experiments. Here, we propose a novel approach that combines molecular evolution with machine learning. In this approach, we conduct two rounds of mutagenesis where an initial library of protein variants is used to train a machine-learning model to guide mutagenesis for the second-round library. This enables to prepare a small library suited for screening experiments with high enrichment of functional proteins. We demonstrated a proof-of-concept of our approach by altering the reference green fluorescent protein (GFP) so that its fluorescence is changed to yellow while improving its fluorescence intensity. Using 155 and 78 variants for the initial and the second-round libraries, respectively, we successfully obtained a number of proteins showing yellow fluorescence, 12 of which had better fluorescence performance than the reference yellow fluorescent protein (YFP). These results show the potential of our approach as a powerful platform for accelerated discovery of functional proteins. Science AdvancesManuscript Template

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In-one-pot-at-a-time Ligation for High-throughput Construction of a Protein Expression Vector Library

Cited by 5 publications

References 13 publications

A semi high-throughput method for screening small bispecific antibodies with high cytotoxicity

A semi high-throughput method for screening small bispecific antibodies with high cytotoxicity

Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins

A machine-learning-guided mutagenesis platform for accelerated discovery of novel functional proteins

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