Brinton Lindsey T, Bauknight Dustin K, Dasa Siva Sai Krishna, Kelly Kimberly A
Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, 22908, United States of America.
Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, 22908, United States of America.
PLoS One. 2016 May 17;11(5):e0155244. doi: 10.1371/journal.pone.0155244. eCollection 2016.
Next-generation sequencing has enhanced the phage display process, allowing for the quantification of millions of sequences resulting from the biopanning process. In response, many valuable analysis programs focused on specificity and finding targeted motifs or consensus sequences were developed. For targeted drug delivery and molecular imaging, it is also necessary to find peptides that are selective-targeting only the cell type or tissue of interest. We present a new analysis strategy and accompanying software, PHage Analysis for Selective Targeted PEPtides (PHASTpep), which identifies highly specific and selective peptides. Using this process, we discovered and validated, both in vitro and in vivo in mice, two sequences (HTTIPKV and APPIMSV) targeted to pancreatic cancer-associated fibroblasts that escaped identification using previously existing software. Our selectivity analysis makes it possible to discover peptides that target a specific cell type and avoid other cell types, enhancing clinical translatability by circumventing complications with systemic use.
下一代测序技术改进了噬菌体展示过程，能够对数百万个淘选过程产生的序列进行定量分析。相应地，人们开发了许多专注于特异性以及寻找靶向基序或共有序列的有价值的分析程序。对于靶向给药和分子成像而言，找到仅选择性靶向目标细胞类型或组织的肽也很有必要。我们提出了一种新的分析策略及配套软件——选择性靶向肽的噬菌体分析软件（PHASTpep），该软件可识别高度特异性和选择性的肽。通过这个过程，我们在小鼠体内外发现并验证了两个靶向胰腺癌相关成纤维细胞的序列（HTTIPKV和APPIMSV），而使用现有软件则无法识别这些序列。我们的选择性分析能够发现靶向特定细胞类型且避开其他细胞类型的肽，通过避免全身使用带来的并发症，提高了临床可转化性。
