pam library plasmids  (GenScript corporation)

Journal: bioRxiv

Article Title: Engineering of CRISPR-Cas PAM recognition using deep learning of vast evolutionary data

doi: 10.1101/2025.01.06.631536

Figure Lengend Snippet: (a) A bioinformatics pipeline was employed to identify PAMs across diverse CRISPR-Cas systems. The pipeline aligned CRISPR spacers to a large database of viral and plasmid sequences to detect conserved flanking motifs. The Cas proteins responsible for PAM recognition during target inference are shown: Cas9 and Cas12 function as single-protein effectors, while Cas8 operates as part of the multi-subunit Cascade complex. In total, 45,816 distinct PAM predictions were made (Type I: n = 28, 410, Type II: n = 15, 731, Type V: n = 1, 675). (b) Fraction of CRISPR-Cas operons associated with a PAM prediction. (c) Accumulation curves of PAM diversity with increasing data volume. Discovery of new PAMs has largely plateaued for Type I and II systems. (d) PAM similarity was compared between Cas proteins with different levels of relatedness. PAM similarity rapidly diverges for Type II systems but is highly conserved for Types I and V. (e) A phylogenetic tree of Cas9 proteins clustered at 70% identity using MMseqs2 . Outer rings indicate the information content at each of the first 9 PAM positions. Phylogenetic tree built using FastTree and visualized using iToL .

Article Snippet: Briefly, the PAM library plasmids were linearized with PvuI-HF (NEB).

Techniques: CRISPR, Plasmid Preparation

Journal: bioRxiv

Article Title: Engineering of CRISPR-Cas PAM recognition using deep learning of vast evolutionary data

doi: 10.1101/2025.01.06.631536

Figure Lengend Snippet: (a) Phylogenetic trees were built for Cas8, Cas9, and Cas12 proteins. Proteins were first clustered using MMseqs2 at 70% identity for Cas8 and Cas9 and at 95% identity for Cas12. Phylogenetic trees were built using FastTree and visualized using iToL . Colored strips indicate the information content at PAM positions. (b) Distribution of high-information content positions across PAMs from Type I, II, and V systems. In Type I systems, the PAM is predominantly restricted to positions −1 to −3 relative to the protospacer, while in Type II systems, the distribution of high information content PAM positions is more variable. (c) Distribution of the number of spacers aligned to virus and plasmid genomes for PAMs predictions from the CRISPR-Cas Atlas. (d) Signal-to-noise ratio comparing nucleotide conservation upstream and downstream of the protospacer for PAMs predictions from the CRISPR-Cas Atlas. In Type II systems, a downstream motif is expected, while in Type I and V systems, the motif is upstream. Bioinformatic PAM predictions are based on a high number of aligned CRISPR spacers, resulting in strong signal-to-noise ratios and providing a robust training dataset for Protein2PAM.

Article Snippet: Briefly, the PAM library plasmids were linearized with PvuI-HF (NEB).

Techniques: Virus, Plasmid Preparation, CRISPR

Journal: bioRxiv

Article Title: Engineering of CRISPR-Cas PAM recognition using deep learning of vast evolutionary data

doi: 10.1101/2025.01.06.631536

Figure Lengend Snippet: (a) Proteins were characterized using the high-throughput PAM determination assay (HT-PAMDA) in human cell lysate, measuring Cas9 cleavage rates on substrates with all possible PAMs. Cleavage rates were quantified at positions 5 to 8 of the PAM library after deep sequencing at four time points. (b) Activity landscape across Nme1Cas9 enzyme variants. The cleavage rate of each PAM is derived by tracking depletion over four time points (Fast: rate > 1e-3, Medium: rate > 1e-4, Slow: rate > 5e-5). (c) Top: PAM logos predicted using Protein2PAM. Bottom: PAM logos generated from HT-PAMDA data. For HT-PAMDA logos, each four-nucleotide PAM was weighted by its corresponding rate constant, nucleotide counts were normalized to frequencies summing to 1.0 per position, and frequencies were converted to information content. (d) HT-PAMDA heatmaps which display rate constants for different enzyme variants at PAM positions 5-8.

Article Snippet: Briefly, the PAM library plasmids were linearized with PvuI-HF (NEB).

Techniques: High Throughput Screening Assay, Sequencing, Activity Assay, Derivative Assay, Generated