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Quantitative Basis: Plasmid Selection Across Transfer Regimes

Effective simultaneous measurement requires plasmids that span multiple orders of magnitude in conjugation frequency. The IncX1 plasmid pMAS2027 transfers at 0.032 per donor when mrk fimbriae are deleted, versus 0.0064 wild-type — a fivefold cost of carrying biofilm adhesins on transfer efficiency pMAS2027 IncX1 conjugation and adhesion dynamics. Clinical IncU plasmids from K. quasipneumoniae ST978-KL103 co-harboring tmexCD2-toprJ2 and blaIMP-4 transfer at only ~2×10⁻⁶ per donor K. quasipneumoniae ST978 clinical IncU plasmid conjugation. This 1,500-fold dynamic range ensures the design captures both rapid-spread and cryptic-transfer dynamics.

Only 4.14% of 142,492 sequenced plasmids are conjugative, with mobilizable plasmids disproportionately carrying ARGs 4.14% conjugative plasmids in 142K dataset. Therefore the donor panel must also include a mobilizable clinical plasmid to capture trans-mobilization events.

Contained Polymicrobial Architecture

System: CDC Biofilm Reactor (BSL-2) with polycarbonate coupons. Donor: K. quasipneumoniae ST978 (KP58) carrying pKP58-1 (IncU, 360 kbp, blaIMP-4 + tmexCD2-toprJ2) and pKP58-3 (IncC, 154 kbp, blaNDM-1). Recipient panel: E. coli MG1655 (GFP), A. baumannii 17978 (mCherry), P. aeruginosa PAO1 (YFP) — three species spanning Gammaproteobacteria phylogenetic distance. Co-colonizer: E. coli CAUTI isolate MS2027 carrying pMAS2027 (IncX1, mrkABCDF) to test cross-species biofilm enhancement Conjugative plasmids drive E. coli biofilm expansion.

Six Parallel Readouts at Each Timepoint (0, 6, 12, 24, 48 h)

• Transfer: Species-selective plating + qPCR for plasmid-specific markers (tmexD2, blaIMP-4, blaNDM-1); flow cytometry to quantify fluorescent transconjugants per species
• Plasmid loss: Long-read Nanopore sequencing of pooled transconjugant colonies; absence of plasmid contigs vs timepoint-0 reference
• Mobile-element replacement: Detect IS insertions into lost-plasmid regions, co-integrate formation, or prophage acquisition via Unicycler hybrid assembly; compare replicon profiles with PlasmidFinder and MOB-suite
• Resistance phenotype: Broth microdilution MIC for tigecycline, meropenem, gentamicin per CLSI; correlate with plasmid copy number (ddPCR)
• Biofilm fitness: Crystal violet biomass (A595); confocal laser scanning microscopy for biofilm depth and spatial distribution; live/dead staining
• Virulence traits: Serum killing assay; A549 epithelial cell LDH cytotoxicity; G. mellonella larvae survival (n=15 per condition) Virulence and resistance phenotype methods

Bioinformatics/Coding Pipeline

Workflow: Snakemake orchestrates: (1) NanoFilt → Flye long-read assembly → contig classification with MOB-suite; (2) Short-read metagenomic profiling with MetaPhlAn + HUMAnN for species/gene abundance; (3) Abricate against ResFinder + VFDB for resistome/virulome; (4) Custom Python scripts using Biopython and NetworkX to build mobile-element co-occurrence networks across timepoints; (5) Bayesian hierarchical model in PyMC3 estimating transfer rate β, loss rate μ, and replacement rate ρ with 95% credible intervals; (6) scikit-bio for biofilm community diversity (Bray-Curtis, PERMANOVA). Statistical design: 3×2 factorial (recipient species × plasmid type), n=3 biological replicates, 6 timepoints = 108 independent samples. Power analysis via Python statsmodels targets detection of transfer frequency differences ≥5×10⁻⁷ with α=0.05, power=0.8.

Three-stage framework (initial transfer → lateral spread → vertical inheritance) structures the model: biofilm spatial structure constrains invasion to growth-active edges, so sampling must capture both edge and depth strata via cryo-sectioning Three-stage plasmid spread framework in biofilms. Plasmid-encoded T6SS repression interactions must be monitored by Western blot for Hcp secretion Plasmid T6SS repression enables dissemination.