General Theory for Integrated Analysis of Growth, Gene, and Protein Expression in Biofilms

Abstract

A theory for analysis and prediction of spatial and temporal patterns of gene and protein expression within microbial biofilms is derived. The theory integrates phenomena of solute reaction and diffusion, microbial growth, mRNA or protein synthesis, biomass advection, and gene transcript or protein turnover. Case studies illustrate the capacity of the theory to simulate heterogeneous spatial patterns and predict microbial activities in biofilms that are qualitatively different from those of planktonic cells. Specific scenarios analyzed include an inducible GFP or fluorescent protein reporter, a denitrification gene repressed by oxygen, an acid stress response gene, and a quorum sensing circuit. It is shown that the patterns of activity revealed by inducible stable fluorescent proteins or reporter unstable proteins overestimate the region of activity. This is due to advective spreading and finite protein turnover rates. In the cases of a gene induced by either limitation for a metabolic substrate or accumulation of a metabolic product, maximal expression is predicted in an internal stratum of the biofilm. A quorum sensing system that includes an oxygen-responsive negative regulator exhibits behavior that is distinct from any stage of a batch planktonic culture. Though here the analyses have been limited to simultaneous interactions of up to two substrates and two genes, the framework applies to arbitrarily large networks of genes and metabolites. Extension of reaction-diffusion modeling in biofilms to the analysis of individual genes and gene networks is an important advance that dovetails with the growing toolkit of molecular and genetic experimental techniques.

Gel-Entrapped Staphylococcus aureus Bacteria as Models of Biofilm Infection Exhibit Growth in Dense Aggregates, Oxygen Limitation, Antibiotic Tolerance, and Heterogeneous Gene Expression

“…These signatures for local hypoxia and anaerobiosis agree with those from previous transcriptomic, proteomic, and metabolomics comparisons of planktonic and biofilm staphylococcal cells, which collectively revealed decreased aerobic energy metabolism and increased fermentative activity in biofilms (34)(35)(36)(37)(38)(39). More specifically, the spatial pattern of ldh expression conforms to the qualitative pattern predicted for a gene whose expression is induced under conditions of diminished oxygen (40). The modeled pattern predicts maximal expression at an intermediate depth from the oxygenated interface of the biofilm.…”

Vertical stratification of matrix production is essential for physical integrity and architecture of macrocolony biofilms of Escherichia coli

“…Thus, Pseudomonas aeruginosa – another well‐studied Gram‐negative biofilm model bacterium – depends on oxygen for metabolic activity and growth (if not provided with an electron acceptor for anaerobic respiration). As a consequence, metabolically active cells, which are in a state of post‐exponential growth, populate the upper layer of a macrocolony, where they find sufficient oxygen as well as nutrients, which can diffuse upwards through the lower layer of metabolically inert cells (Lenz et al ., ; Williamson et al ., ; Zhang et al ., ). What does this mean for the regulation of synthesis of the biofilm matrix, which in the case of P. aeruginosa contains the EPSs Psl and Pel as well as eDNA?…”

Modeling Biofilms: From Genes to Communities

“…There are several advantages of this model: most of its parameters are either directly measurable (µ j , K s ) or easily obtained by calculation (F T ); numerical solutions from the model give gene abundances and chemical concentrations that allow direct comparisons between model predictions and experimental results; and the metabolic plasticity could be important for understanding the complex microbial community dynamics. Zhang et al [50] developed a theory for the analysis and prediction of the spatial and temporal patterns of gene and protein expression within microbial biofilms based on similar ideas. The theory integrates the phenomena of solute reaction and diffusion, microbial growth, mRNA or protein synthesis, biomass advection and gene transcript or protein turnover.…”

“…Under the very low nutrient condition, (3) can be approximated by the first order kinetics, where µ is proportional to S (µ = µ max · S). These two approximations provide convenient mathematical bounds on the Monod kinetic forms and have the advantages of allowing analytic solutions [50] to the model equations for simple scenarios (ODE model or 1D in space). The success of the kinetic models depends crucially both on their particular formula and parameter values.…”