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{\bf [[TAG] OBJECT OF THE DOCUMENT]} In this work we introduce an individual-based model for bacterial conjugation constructed using a modular design which has been used to evaluate the better alternative for modeling and understand the conjugation systemically. Thereby, using this modular design we have plugged different approaches to model the conjugation with respect the time within cell cycle which produces the best and most natural fit to a complete and diverse experimental data.   \section*{Materials and Methods}  \subsection*{Theoretical Framework}  The wave speed of plasmid spread in a bacterial population is a complex and non-lineal process and as such is hard to grasp some intuitive idea about the main factors controlling the global behavior of the system as a whole. In order to understand the spatiotemporal behavior and visualize the processes some simplifications are required to be made. Hence we have used a network analogy, comparing bacterial cells to network nodes which store and forward messages, being the conjugative plasmids the message transmitted from cell to cell.  It is known the most cellular processes follows a tight time schedule and is natural to think that the bacterial conjugation must be subject to the same constraints. Nonetheless until now, no works have studied how conjugative events are distributed across the cell cycle duration. With respect to time and ignoring other constraints, such as the availability of reachable susceptible individuals, we may state the following biologically relevant hypotheses:  \begin{itemize}  \item The time of conjugative transfer event is completely independent of bacterial cell cycle and grown conditions being merely a function of plasmid endogenous factors.  \item On the other hand, plasmids could behave as all other cellular processes being linked to the host metabolic level and growth rate.  \end{itemize}  The main implication of first hypothesis, as should became clear in the next paragraphs, is that the larger is the bacterial generation time more efficient becomes the conjugative process because the infection rate surpasses the host growth rate allowing the complete plasmid invasion.  In the second hypothesis, the efficiency of a conjugative plasmid depends on the host growth regime and also on the plasmid intrinsic factors. Hence the time where conjugation will occur can be expressed as a percentage of bacterial doubling time indicating the fact that conjugative activity depends and is coordinated by the host dynamics.   It has already been pointed out recently that timing and delays are the most important parameters governing the global observed dynamics of plasmid spread in bacterial populations\cite{citeulike:10283930}. This work has shown using sensitivity analysis, that the lag time from the initial infection until the new formed transconjugant cell becomes a proficient donor is the most significant parameter of the model.  The bacterial cellular dynamics controlling the growth and division process has a theoretical framework which has been pointed out as the central dogma bacterial cell division cycle or simply of Cooper-Helmstetter model\cite{citeulike:13777623}. The model describes the bacterial cell process relating a set of events such as the chromosome replication and division to the changes in the cell mass.  Therefore, taking into account the bacterial cell cycle, three basic cases for the temporal properties of bacterial conjugation which are enumerated bellow:  \begin{itemize}  \item Conjugation is independent of host dynamics and conjugation may take place as soon a suitable recipient is found on the neighborhood of plasmid bearing cell.  \item The frequency of conjugative events is evenly distributed across the cell cycle.  \item Finally, conjugation is linked and coordinated to the host dynamics being the frequency of conjugative events concentrated in some specific point late in the cell cycle.  \end{itemize}  The time related parameters of a conjugation model can be grouped, for the sake of simplicity, as a plasmid infection forwarding delay which stands for the lag time required for some plasmid being forewarned to any adjacent cell. Thereby we can study the forwarding delay effect on the slope of flooding speed.   In the most elemental level, the rate at which the infection progresses depends on how many times every single cell can spread the plasmid, which hereafter we call intrinsic conjugation rate, it also depends on how fast the transmissions from donor cells to recipient cells and further retransmission from transconjugants cells can be accomplished. Thus the intrinsic conjugation rate, ignoring other aspects, depends almost exclusively on the bacterial growth regime and on the time required for a complete plasmid transfer. Just to put forward a simple example to clarify that idea: Using a generation time $\mathcal{G}=20^\prime$, the average transfer speed, which is approximately 45kb/m and the archetypical F plasmid which has a size of 100 kb, the minimal amount of time required for conjugation to complete would be roughly two minutes and the maximum intrinsic transfer rate would be 10 conjugations per cell cycle.   Let us assume a simple and yet idealized bacterial population of $N$ individuals with a growth rate $\mu = 0$. The population will be sessile, which implies that the topology of network will be static and individuals cells will be distributed side by side conforming an interaction structure which could be abstracted by a linear graph as can be seen in Fig. ~\ref{fig:conjugation-delays}.