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Next-generation sequencing (NGS) has raised a growing interest in phage display research. Sequencing depth is a pivotal parameter for using NGS. In the current study, we made a side-by-side comparison of two NGS platforms with different sequencing depths, denoted as lower-throughput (LTP) and higher-throughput (HTP). The capacity of these platforms for characterization of the composition, quality, and diversity of the unselected Ph.D.TM-12 Phage Display Peptide Library was investigated. Our results indicated that HTP sequencing detects a considerably higher number of unique sequences compared to the LTP platform, thus covering a broader diversity of the library. We found a larger percentage of singletons, a smaller percentage of repeated sequences, and a greater percentage of distinct sequences in the LTP datasets. These parameters suggest a higher library quality, resulting in potentially misleading information when using LTP sequencing for such assessment. Our observations showed that HTP reveals a broader distribution of peptide frequencies, thus revealing increased heterogeneity of the library by the HTP approach and offering a comparatively higher capacity for distinguishing peptides from each other. Our analyses suggested that LTP and HTP datasets show discrepancies in their peptide composition and position-specific distribution of amino acids within the library. Taken together, these findings lead us to the conclusion that a higher sequencing depth can yield more in-depth insights into the composition of the library and provide a more complete picture of the quality and diversity of phage display peptide libraries. [ABSTRACT FROM AUTHOR]

Simple Summary: A common issue in glioblastoma stem cells (GSCs) studies is the need to efficiently and precisely target GSCs using reliable biomedical markers. Using single-cell RNA sequencing datasets, we quantitatively evaluated an extensive number of GSCs markers with multiple parameters that dictate the feasibility of various laboratory and therapeutic applications. We present promising marker candidates with their scores on the corresponding parameters and apply sequential selection based on these parameters. Both previously approved and novel markers are proposed according to the evaluation. We demonstrate the possibility of choosing a biomedical marker in a nonarbitrary way and provide quantitative references for potential GSCs markers. Targeting glioblastoma (GBM) stem-like cells (GSCs) is a common interest in both the laboratory investigation and clinical treatment of GBM. Most of the currently applied GBM stem-like markers lack validation and comparison with common standards regarding their efficiency and feasibility in various targeting methods. Using single-cell RNA sequencing datasets from 37 GBM patients, we obtained a large pool of 2173 GBM stem-like marker candidates. To evaluate and select these candidates quantitatively, we characterized the efficiency of the candidate markers in targeting the GBM stem-like cells by their frequencies and significance of being the stem-like cluster markers. This was followed by further selection based on either their differential expression in GBM stem-like cells compared with normal brain cells or their relative expression level compared with other expressed genes. The cellular location of the translated protein was also considered. Different combinations of selection criteria highlight different markers for different application scenarios. By comparing the commonly used GSCs marker CD133 (PROM1) with markers selected by our method regarding their universality, significance, and abundance, we revealed the limitations of CD133 as a GBM stem-like marker. Overall, we propose BCAN, PTPRZ1, SOX4, etc. for laboratory-based assays with samples free of normal cells. For in vivo targeting applications that require high efficiency in targeting the stem-like subtype, the ability to distinguish GSCs from normal brain cells, and a high expression level, we recommend the intracellular marker TUBB3 and the surface markers PTPRS and GPR56. [ABSTRACT FROM AUTHOR]

The principal presumption of phage display biopanning is that the naïve library contains an unbiased repertoire of peptides, and thus, the enriched variants derive from the affinity selection of an entirely random peptide pool. In the current study, we utilized deep sequencing to characterize the widely used Ph.DTM-12 phage display peptide library (New England Biolabs). The next-generation sequencing (NGS) data indicated the presence of stop codons and a high abundance of wild-type clones in the naïve library, which collectively result in a reduced effective size of the library. The analysis of the DNA sequence logo and global and position-specific frequency of amino acids demonstrated significant bias in the nucleotide and amino acid composition of the library inserts. Principal component analysis (PCA) uncovered the existence of four distinct clusters in the naïve library and the investigation of peptide frequency distribution revealed a broad range of unequal abundances for peptides. Taken together, our data provide strong evidence for the notion that the naïve library represents substantial departures from randomness at the nucleotide, amino acid, and peptide levels, though not undergoing any selective pressure for target binding. This non-uniform sequence representation arises from both the M13 phage biology and technical errors of the library construction. Our findings highlight the paramount importance of the qualitative assessment of the naïve phage display libraries prior to biopanning. [ABSTRACT FROM AUTHOR]

The nonspecific enrichment of target-unrelated peptides during biopanning remains a major drawback for phage display technology. The commercial Ph.D.TM-7 phage display library is used extensively for peptide discovery. This library is based on the M13KE vector, which carries the lacZα sequence, leading to the formation of blue plaques on IPTG-X-gal agar plates. In the current study, we report the isolation of a fast-propagating white clone (displaying WSLGYTG peptide) identified through screening against a recombinant protein. Sanger sequencing demonstrated that white plaques are not contamination from environmental M13-like phages, but derive from the library itself. Whole genome sequencing revealed that the white color of the plaques results from a large 827-nucleotide genomic deletion. The phenotypic characterization of propagation capacity through plaque count- and NGS-based competitive propagation assay supported the higher propagation rate of Ph-WSLGYTG clone compared with the library. According to our data, white plaques are likely to arise endogenously in Ph.D. libraries due to mutations in the M13KE genome and should not always be viewed as exogenous contamination. Our findings also led to the conclusion that the deletion observed here might be an ancestral mutation already present in the naïve library, which causes target-unrelated nonspecific enrichment of white clone during biopanning due to propagation advantage. [ABSTRACT FROM AUTHOR]