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Blinco, J.

Publications and source records attributed to Blinco, J..

2 recordsLinked to original sources

Make it so: Rapid and affordable plasmid sequencing on ONT platforms with PICARD-seq

Plasmid construction underpins molecular biology and synthetic biology, yet validation is often limited to the inserted fragment rather than the whole plasmid, and around a third of laboratory-made plasmids carry sequence errors that can affect function. Sanger sequencing scales poorly across whole plasmids, while short-read approaches cannot resolve the repeated DNA parts, such as promoters, that are common in synthetic constructs. We present PICARD-seq, a rapid nanopore-based protocol that uses off-the-shelf Tn5 rapid barcoding reagents and a MinION to sequence pools of whole plasmids in under a day, and we systematically benchmark the computational pipelines available for analysing the resulting data. Using a curated set of 25 plasmids of known sequence spanning 3.0-20.6 kbp, including various dilution series and repetitive multi-part constructs, we ran five independent replicates of each pipeline. The ONT EPI2ME Clone Validation workflow was fast (13-18 min) but stochastic, varying between replicates for both plasmids assembled and what sequence was returned; Canu outperformed the default Flye assembler, and reducing the minimum coverage parameter from 60x to 20x substantially improved assembly of large, repetitive, and dilute samples. The ensemble assembler Autocycler was slower (81-111 min) but gave the highest and most consistent rate of recovering the expected sequence. Complementary read mapping with minimap2 distinguished genuine sequence differences from assembly artefacts. Applying PICARD-seq to problematic plasmids revealed backbone concatemers, a misincorporated promoter part, and a mixed population of rearranged molecules in a repetitive construct. PICARD-seq makes routine whole-plasmid validation practical and affordable for individual laboratories.

bioinformatics↗

Robotic Antimicrobial Susceptibility Platform (RASP): A Next Generation Approach to One-Health Surveillance of Antimicrobial Resistance.

BackgroundSurveillance of antimicrobial resistance (AMR) is critical to reducing its wide-reaching impact. Its reliance on sample size invites solutions to longstanding constraints regarding scalability. A robotic platform (RASP) was developed for high-throughput AMR surveillance in accordance with internationally recognised standards (CLSI and ISO 20776-1:2019) and validated through a series of experiments. MethodsExperiment A compared RASPs ability to achieve consistent MICs to that of a human technician across eight replicates for four E. coli isolates. Experiment B assessed RASPs agreement with human performed MICs across 91 E. coli isolates with a diverse range of AMR profiles. Additionally, to demonstrate its real-world applicability, the RASP workflow was then applied to five faecal samples where a minimum of 47 E. coli per animal (239 total) were evaluated using an AMR indexing framework. ResultsFor each drug-rater-isolate combination in experiment A, there was a clear consensus of the MIC and deviation from the consensus remained within one doubling-dilution (the exception being gentamicin at two dilutions). Experiment B revealed a concordance correlation coefficient of 0.9670 (95%CI: 0.9670 - 0.9670) between the robot and human performed MICs. RASPs application to the five faecal samples highlighted the intra-animal diversity of gut commensal E. coli, identifying between five and nine unique isolate AMR phenotypes per sample. ConclusionsWhile adhering to internationally accepted guidelines, RASP was superior in throughput, cost and data resolution when compared to an experienced human technician. Integration of robotics platforms in the microbiology laboratory is a necessary advancement for future One-Health AMR endeavours.

microbiology↗