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Next-generation sequencing enables the discovery of more diverse positive clones from a phage-displayed antibody library

View Article: PubMed Central - PubMed

ABSTRACT

Phage display technology provides a powerful tool to screen a library for a binding molecule via an enrichment process. It has been adopted as a critical technology in the development of therapeutic antibodies. However, a major drawback of phage display technology is that because the degree of the enrichment cannot be controlled during the bio-panning process, it frequently results in a limited number of clones. In this study, we applied next-generation sequencing (NGS) to screen clones from a library and determine whether a greater number of clones can be identified using NGS than using conventional methods. Three chicken immune single-chain variable fragment (scFv) libraries were subjected to bio-panning on prostate-specific antigen (PSA). Phagemid DNA prepared from the original libraries as well as from the Escherichia coli pool after each round of bio-panning was analyzed using NGS, and the heavy chain complementarity-determining region 3 (HCDR3) sequences of the scFv clones were determined. Subsequently, through two-step linker PCR and cloning, the entire scFv gene was retrieved and analyzed for its reactivity to PSA in a phage enzyme immunoassay. After four rounds of bio-panning, the conventional colony screening method was performed for comparison. The scFv clones retrieved from NGS analysis included all clones identified by the conventional colony screening method as well as many additional clones. The enrichment of the HCDR3 sequence throughout the bio-panning process was a positive predictive factor for the selection of PSA-reactive scFv clones.

No MeSH data available.


Related in: MedlinePlus

Heat map representing the population of heavy chain complementarity-determining region 3 (HCDR3) sequences in each cluster through bio-panning rounds. Red and blue denote high and low proportions of the HCDR3 sequence, respectively. (a) scFv library 1, (b) scFv library 2 and (c) scFv library 3.
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fig1: Heat map representing the population of heavy chain complementarity-determining region 3 (HCDR3) sequences in each cluster through bio-panning rounds. Red and blue denote high and low proportions of the HCDR3 sequence, respectively. (a) scFv library 1, (b) scFv library 2 and (c) scFv library 3.

Mentions: A total of 15 sets of phagemid DNA (three chicken libraries from bio-panning rounds 0, 1, 2, 3, and 4) were used for NGS analysis. After the NGS experiment, we obtained 60,000–180,000 VH sequences. Raw paired-end nucleotide sequences were merged, filtered, aligned and trimmed by uniformly applying pre-specified criteria to remove low-quality and meaningless short sequences. The numbers of nucleotide sequences remaining after each preprocess are summarized in Table 2; 44–53% of the original sequences were retained after aligning with OmpSeq primer sequence14 by Needle, and were used in subsequent analyses. From the NGS results, the total population of VH fragment nucleotides decreased as the bio-panning rounds proceeded. To analyze HCDR3 diversity and frequency, we used HCDR3 sequences existing only in the fourth bio-panning round. clValid predicted that 2–6 clusters would be the most dependable in the HCDR3 sequence count profile data (Table 3). The sequence reads in chicken library 1 showed the maximum Dunn index (0.1048) with 4–6 clusters, and chicken libraries 2 and 3 had maximum Dunn indices with 2–3 clusters. We clustered HCDR3 sequences into 2–6 clusters using hierarchical clustering, and generated heat maps for each cluster to examine the patterns of HCDR3 sequence enrichment and population shift throughout the bio-panning rounds. The pattern of HCDR3 sequence enrichment and population shift in chicken library 1 showed four clear clusters, and the patterns in chicken libraries 2 and 3 showed three clear clusters (Figure 1).


Next-generation sequencing enables the discovery of more diverse positive clones from a phage-displayed antibody library
Heat map representing the population of heavy chain complementarity-determining region 3 (HCDR3) sequences in each cluster through bio-panning rounds. Red and blue denote high and low proportions of the HCDR3 sequence, respectively. (a) scFv library 1, (b) scFv library 2 and (c) scFv library 3.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5382563&req=5

fig1: Heat map representing the population of heavy chain complementarity-determining region 3 (HCDR3) sequences in each cluster through bio-panning rounds. Red and blue denote high and low proportions of the HCDR3 sequence, respectively. (a) scFv library 1, (b) scFv library 2 and (c) scFv library 3.
Mentions: A total of 15 sets of phagemid DNA (three chicken libraries from bio-panning rounds 0, 1, 2, 3, and 4) were used for NGS analysis. After the NGS experiment, we obtained 60,000–180,000 VH sequences. Raw paired-end nucleotide sequences were merged, filtered, aligned and trimmed by uniformly applying pre-specified criteria to remove low-quality and meaningless short sequences. The numbers of nucleotide sequences remaining after each preprocess are summarized in Table 2; 44–53% of the original sequences were retained after aligning with OmpSeq primer sequence14 by Needle, and were used in subsequent analyses. From the NGS results, the total population of VH fragment nucleotides decreased as the bio-panning rounds proceeded. To analyze HCDR3 diversity and frequency, we used HCDR3 sequences existing only in the fourth bio-panning round. clValid predicted that 2–6 clusters would be the most dependable in the HCDR3 sequence count profile data (Table 3). The sequence reads in chicken library 1 showed the maximum Dunn index (0.1048) with 4–6 clusters, and chicken libraries 2 and 3 had maximum Dunn indices with 2–3 clusters. We clustered HCDR3 sequences into 2–6 clusters using hierarchical clustering, and generated heat maps for each cluster to examine the patterns of HCDR3 sequence enrichment and population shift throughout the bio-panning rounds. The pattern of HCDR3 sequence enrichment and population shift in chicken library 1 showed four clear clusters, and the patterns in chicken libraries 2 and 3 showed three clear clusters (Figure 1).

View Article: PubMed Central - PubMed

ABSTRACT

Phage display technology provides a powerful tool to screen a library for a binding molecule via an enrichment process. It has been adopted as a critical technology in the development of therapeutic antibodies. However, a major drawback of phage display technology is that because the degree of the enrichment cannot be controlled during the bio-panning process, it frequently results in a limited number of clones. In this study, we applied next-generation sequencing (NGS) to screen clones from a library and determine whether a greater number of clones can be identified using NGS than using conventional methods. Three chicken immune single-chain variable fragment (scFv) libraries were subjected to bio-panning on prostate-specific antigen (PSA). Phagemid DNA prepared from the original libraries as well as from the Escherichia coli pool after each round of bio-panning was analyzed using NGS, and the heavy chain complementarity-determining region 3 (HCDR3) sequences of the scFv clones were determined. Subsequently, through two-step linker PCR and cloning, the entire scFv gene was retrieved and analyzed for its reactivity to PSA in a phage enzyme immunoassay. After four rounds of bio-panning, the conventional colony screening method was performed for comparison. The scFv clones retrieved from NGS analysis included all clones identified by the conventional colony screening method as well as many additional clones. The enrichment of the HCDR3 sequence throughout the bio-panning process was a positive predictive factor for the selection of PSA-reactive scFv clones.

No MeSH data available.


Related in: MedlinePlus