10Microorganisms efficiently coordinate phenotype expressions through a decision-making 11 process known as quorum sensing (QS). We investigated QS amongst heterogeneously 12 distributed microbial aggregates under various flow conditions using a process-driven numerical 13 model. Model simulations assess the conditions suitable for QS induction and quantify the 14 importance of advective transport of signaling molecules. In addition, advection dilutes signaling 15 molecules so that faster flow conditions require higher microbial densities, faster signal 16 production rates, or higher sensitivities to signaling molecules to induce QS. However, 17 autoinduction of signal production can substantially increase the transport distance of signaling 18 molecules in both upstream and downstream directions. We present approximate analytical 19 solutions of the advection-diffusion-reaction equation that describe the concentration profiles of 20 signaling molecules for a wide range of flow and reaction rates. These empirical relationships, 21 which predict the distribution of dissolved solutes following zero-order production kinetics along 22 pore channels, allow to quantitatively estimate the effective communication distances amongst 23 multiple microbial aggregates without further numerical simulations. 24 25 Author Summary
26Microbes can interact with their surrounding environments by producing and sensing small 27 signaling molecules. When the microbes experience a high enough concentration of the signaling 28 molecules, they express certain phenotypes which is often energetically expensive. This 29 microbial decision-making process known as quorum sensing (QS) has been understood to 30 confer evolutionary benefits. However, it is still not completely understood how transport of the 31 produced signaling molecules affects QS. Using a mathematical approach investigating QS 32 across a range of environmentally relevant flow conditions, we find that advective transport 33 promotes QS downstream yet also dilutes the concentration of signaling molecules. We quantify 34 the importance of microbial cell location with respect to both other microbes and flow direction. 35 By analyzing complex numerical simulation results, we provide analytical approximations to 36 assess the distribution of signaling molecules in pore channels across a range of flow and 37 reaction conditions. 38 39 Introduction
40Microorganisms preferentially reside on solid surfaces, which often leads to a closer 41 proximity of neighboring cells than when in a planktonic form [1]. At elevated cell densities, 42 microorganisms need to efficiently coordinate the expression of energetically expensive 43 phenotypes, such as biofilm development, exoenzyme production, and microbial dispersal. 44 Efficiency is achieved by producing and detecting relatively cheap signaling molecules which 45 regulate the phenotype expression only when a sufficient signal concentration has been reached 46 [2]. This microbial decision-making process called "quorum sensing (QS)" was orig...