Review papers with raw data transparency

Paper summary (what they did and claim)

• Determined two cryo-EM RdCas12n-sgRNA-dsDNA ternary complex structures (PDB 9J09 and 9UDI; maps EMD-61051 and EMD-64070) and built an atomic model for the core REC/WED interactions while the NUC lobe showed flexibility/unresolved density Cryo-EM reconstructions and flexible NUC lobe
• Described a unique A-rich PAM recognition (primary 5'-AAC-3') via specific residues in WED and REC and upstream phosphate backbone contacts mediated by an expanded R/K-rich extra-WED region; alanine mutagenesis (e.g., R140A, P189A, E190A abolished cleavage; P187A/K102A reduced activity) validated key contacts PAM recognition and mutagenesis
• Characterized sgRNA architecture (214 nt initial sgRNA; resolved stems and pseudoknot) and performed guided sgRNA engineering: selected sgRNA_T19 (truncated/optimized scaffold) that increased editing in HEK293T and bacterial assays; sgRNA_T19 reached ~40% indel at HEXA-4 and improved activity across many loci relative to WT sgRNA sgRNA engineering and T19 performance
• Placed Cas12n evolutionarily between TnpB and other Cas12 effectors, noting shared bilobed REC/NUC architecture with lineage-specific expansions (notably REC and WED expansions) that correlate with nucleic-acid interactions Evolutionary comparisons to TnpB

Major strengths

1. High-resolution structural data (2.95–3.01 A) with deposited PDB/EMDB entries and associated sequence/NGS data (PRJNA1261697) enabling reuse and reanalysis Data deposition and accessibility
2. Comprehensive multi-modal validation: biochemical cleavage assays, EMSA, alanine scanning, bacterial targeting, mammalian editing, and CRISPRa assays all contribute to a convergent mechanistic interpretation Experimental validation breadth
3. Structure-guided engineering produced tangible performance gains in cells (sgRNA_T19), demonstrating actionable engineering routes for compact editors and translational potential for delivery-limited applications (AAV compatibility discussion) Engineering and delivery relevance

Limitations and blindspots (critical)

• NUC lobe unresolved: active site architecture (RuvC/TNB) is inferred partly from AlphaFold predictions rather than experimental density, leaving catalytic geometry and conformational transitions uncertain Unresolved NUC lobe and reliance on AlphaFold
• Limited mammalian editing breadth and modest efficiency: only 20 loci tested; the highest reported ~40% indel at one site (HEXA-4) but typical performance across other sites was much lower (often ~10% at three loci), substantially underperforming benchmark nucleases (SpCas9, AsCas12a) in their dataset Editing efficiencies in HEK293T
• PAM restriction and context-dependence: primary 5'-AAC-3' PAM (A-rich) is rarer across genomes than common NGG or TTTV PAMs, limiting targetable loci without PAM engineering or PAM-relaxed orthologs; authors note clade-specific PAM differences that complicate generalization PAM specificity and clade variation
• Potential publication and engineering bias: extensive sgRNA optimization was performed and several constructs tested; the paper emphasizes the best-performing sgRNA_T19 — necessary but raises risk of overfitting to chosen loci, cell line, and constructs (authors note some sgRNA variants that worked in bacteria performed worse in mammalian cells) sgRNA optimization and context dependence

Technical critique and suggestions

• Strive for experimental capture of NUC lobe dynamics: additional cryo-EM with alternative sample conditions (different sgRNA variants, dsDNA PAMs, Mg2+/Ca2+ substitution, crosslinking, or liganded inhibitors) could stabilize the NUC lobe and reveal the active site architecture rather than relying on AlphaFold models NUC lobe flexibility noted
• Broaden and blind-test editing in diverse mammalian cell types and primary cells and include unbiased off-target profiling (GUIDE-seq/CIRCLE-seq) to assess specificity and safety for translational claims — the current paper focuses on HEK293T with amplicon-seq analyses but lacks genome-wide off-target data
• Map PAM frequency across human therapeutically relevant loci and quantify how many clinically relevant targets become accessible with RdCas12n versus SpCas9/AsCas12a to better evaluate real-world delivery tradeoffs (AAV size vs PAM constraint)
• Functional tests of RuvC catalytic mutants and kinetics: measure single-turnover and multiple-turnover kinetics, nicking vs DSB patterns, and collateral ssDNA cleavage (if present) to clarify RdCas12n nuclease behavior

Data visualizations (interactive)

Conclusions and confidence

Overall, this is a high-quality structural and engineering study that meaningfully advances mechanistic understanding of miniature type V-N nucleases and demonstrates an actionable engineering path (sgRNA optimization) to substantially improve activity in human cells. Key mechanistic claims about PAM recognition and sgRNA architecture are well supported by cryo-EM, mutagenesis, and biochemical assays. However, the functional performance in mammalian cells remains modest and locus/PAM-limited; resolving the NUC lobe experimentally and expanding specificity/off-target characterization are important next steps before robust translational claims can be made Overall study claims and caveats

Next actions and tools

Author reviews