# Plasmid Conjugation & Antibiotic Resistance

Watch resistance plasmids spread through a bacterial colony via conjugation, and how antibiotic selection decides who survives

> Canonical page: https://elysiatools.com/en/visualizations/plasmid-conjugation-resistance

- **Category:** Biology

## Overview

Interactive grid-based simulation of horizontal gene transfer (HGT) and antibiotic-resistance spread in a 2D bacterial colony — distinct from existing biology cases (quorum-sensing = cooperative gene activation via autoinducers, dna-replication = intracellular replication mechanics, crispr-gene-editing-sandbox = targeted genome editing); this is the only case on horizontal plasmid transfer and population-level AMR dynamics. Models three cell types per lattice site: S (susceptible/plasmid-free recipient), D (donor carrying the resistance plasmid), and T (transconjugant — a former S that received the plasmid and, after a short lag, becomes a donor too). Based on the Stewart & Levin (1977) / Levin-Stewart-Rice (1979) mass-action conjugation framework: the continuum transfer rate γ·D·R becomes, on the grid, a per-contact conversion probability 1−exp(−γ·Δt) applied to each (donor, recipient) Moore-neighbour pair. Five coupled processes per tick: (1) CONJUGATION (mass-action, both D and lag-expired T donate); (2) SEGREGATION/plasmid loss (rate τ, D or T revert to S); (3) FITNESS COST (c, plasmid-bearing cells reproduce at ψ·(1−c)); (4) ANTIBIOTIC (dose a kills only S cells, applied after a configurable start tick); (5) LOGISTIC GROWTH (rate ψ, empty sites colonised by a fitness-weighted random neighbour, capped at carrying capacity); plus (6) SPATIAL MIXING (fraction of cells swapped per tick, modelling motility). Toroidal Moore neighbourhood with randomised update order to avoid directional bias. Also includes a deterministic well-mixed D/R/T ODE reference (RK4 integration of the Levin/Stewart system) for comparison and rate estimation. Real-time visualisation: (1) the colony as a colour-coded grid showing the expanding resistance wavefront (green S, red D, gold T); (2) a stacked population time-series (S/D/T areas) with a live prevalence line and an antibiotic-start marker. Adjustable parameters: conjugation rate γ (0–2), plasmid loss τ (0–0.2), fitness cost c (0–0.8), antibiotic dose (0–1), antibiotic start tick (0–200), initial density (0.1–0.9), growth rate ψ (0–0.4), spatial mixing (0–0.8). Five scenario presets: free spread, antibiotic rescue (plasmid rescues colony when drug added), cost dominates (plasmid lost without selection), well-mixed (high motility), static biofilm (no mixing). Live metrics: tick, prevalence, susceptible/resistant/total counts, with phase indicator (spreading/dominant/fading/antibiotic-active). Educational content covers conjugation as horizontal gene transfer, mass-action kinetics and the D/R/T ODE model, the fitness-cost-vs-selection trade-off, why spatial structure matters (wavefronts vs well-mixed), and real-world AMR stakes (hospitals, agriculture, wastewater, stewardship, plasmid-curing, One-Health). Verified by 51 model tests (grid dynamics, gamma/tau/cost/antibiotic scaling, transconjugant lag, ODE reference for conjugation/cost/antibiotic). Multi-language support (zh, en, es, fr, de, ru, pt).

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