Journal: bioRxiv

Article Title: Quantitative profiling of millions of nucleotides reveals sequence-encoded interactions that govern plasmid propagation

doi: 10.64898/2025.12.15.694402

Figure Lengend Snippet: A) Plasmids support cloning, library propagation, and gene expression, but unintended interactions with host transcriptional and replication machinery can drive recombination, plasmid instability, low plasmid DNA (pDNA) yields, and reduced expression. B) Overview of the pooled plasmid fitness assay. A diverse library of mammalian expression plasmid parts is assembled using Golden Gate cloning and transformed into E. coli . The pooled culture is grown over time, and changes in plasmid abundance are measured via long read nanopore sequencing and alignment. Log fold change (LFC) in relative plasmid abundance is used as a fitness metric and ranked across the library. Machine learning models predict sequence-dependent fitness effects. C) A set of Mammalian Toolkit (MTK) plasmids was transformed into E. coli DH5α, DH10B, and Stbl3 and the pooled assay performed in triplicate. Violin plots show plasmid fitness with three distinct categories of poor plasmid propagation including reduced fitness (light grey), low fitness (grey) and severe plasmid loss. This was compared to plasmid size (left) and GC content (right).

Article Snippet: Single-part plasmid libraries were assembled using the Mammalian Tool Kit (MTK) modular cloning framework, sourced from Addgene. ( ) Individual regulatory elements (promoters, UTRs, coding sequences, localization tags, and polyadenylation sequences) were cloned into a common bacterial backbone containing a chloramphenicol resistance marker and a pMB1-derived origin of replication.

Techniques: Cloning, Gene Expression, Plasmid Preparation, Expressing, Transformation Assay, Nanopore Sequencing, Sequencing

Journal: bioRxiv

Article Title: Quantitative profiling of millions of nucleotides reveals sequence-encoded interactions that govern plasmid propagation

doi: 10.64898/2025.12.15.694402

Figure Lengend Snippet: A) Four-part expression cassette assembly from the MTK library, comprising a promoter, coding sequence (CDS), localisation tag, and terminator, combined by one-pot Golden Gate cloning and propagated in E. coli DH5α. Pooled fitness was measured by quantifying plasmid abundance over a 16-hour batch culture. B) Plasmid log fold change (LFC) plotted against plasmid size (top) and GC content (bottom) for 1,847 assembled constructs. Each point represents one plasmid. C) Overview of the random forest regression workflow used to predict plasmid fitness from one-hot-encoded part identities. D) Predicted versus measured plasmid LFC for the random forest model. Each point represents one plasmid. E) Comparison of mean part fitness (LFC) with contextual effect estimated by mean SHAP value for each part. Points are coloured by cassette position (promoter, CDS, tag, terminator). F) SHAP value distributions showing part contributions to predicted plasmid fitness across all assemblies. Each ridge represents one part. G) Pairwise SHAP interaction values between selected parts. Points represent individual assemblies; distributions summarise interaction variability across the library.

Article Snippet: Single-part plasmid libraries were assembled using the Mammalian Tool Kit (MTK) modular cloning framework, sourced from Addgene. ( ) Individual regulatory elements (promoters, UTRs, coding sequences, localization tags, and polyadenylation sequences) were cloned into a common bacterial backbone containing a chloramphenicol resistance marker and a pMB1-derived origin of replication.

Techniques: Expressing, Sequencing, Cloning, Plasmid Preparation, Construct, Comparison