A Multiscale Agent-Based Model for the Investigation of <Emphasis Type="Italic">E. coli</Emphasis> K12 Metabolic Response During Biofilm Formation

Bacterial biofilm formation is an organized collective response to biochemical cues that enables bacterial colonies to persist and withstand environmental insults. We developed a multiscale agent-based model that characterizes the intracellular, extracellular, and cellular scale interactions that modulate Escherichia coli MG1655 biofilm formation. Each bacterium’s intracellular response and cellular state were represented as an outcome of interactions with the environment and neighboring bacteria. In the intracellular model, environment-driven gene expression and metabolism were captured using statistical regression and Michaelis–Menten kinetics, respectively. In the cellular model, growth, death, and type IV pili- and flagella-dependent movement were based on the bacteria’s intracellular state. We implemented the extracellular model as a three-dimensional diffusion model used to describe glucose, oxygen, and autoinducer 2 gradients within the biofilm and bulk fluid. We validated the model by comparing simulation results to empirical quantitative biofilm profiles, gene expression, and metabolic concentrations. Using the model, we characterized and compared the temporal metabolic and gene expression profiles of sessile versus planktonic bacterial populations during biofilm formation and investigated correlations between gene expression and biofilm-associated metabolites and cellular scale phenotypes. Based on our in silico studies, planktonic bacteria had higher metabolite concentrations in the glycolysis and citric acid cycle pathways, with higher gene expression levels in flagella and lipopolysaccharide-associated genes. Conversely, sessile bacteria had higher metabolite concentrations in the autoinducer 2 pathway, with type IV pili, autoinducer 2 export, and cellular respiration genes upregulated in comparison with planktonic bacteria. Having demonstrated results consistent with in vitro static culture biofilm systems, our model enables examination of molecular phenomena within biofilms that are experimentally inaccessible and provides a framework for future exploration of how hypothesized molecular mechanisms impact bulk community behavior.     

Multiscale Modeling of Metabolism and Macromolecular Synthesis in E. coli and Its Application to the Evolution of Codon Usage

Biological systems are inherently hierarchal and multiscale in time and space. A major challenge of systems biology is to describe biological systems as a computational model, which can be used to derive novel hypothesis and drive experiments leading to new knowledge. The constraint-based reconstruction and analysis approach has been successfully applied to metabolism and to the macromolecular synthesis machinery assembly. Here, we present the first integrated stoichiometric multiscale model of metabolism and macromolecular synthesis for Escherichia coli K12 MG1655, which describes the sequence-specific synthesis and function of almost 2000 gene products at molecular detail. We added linear constraints, which couple enzyme synthesis and catalysis reactions. Comparison with experimental data showed improvement of growth phenotype prediction with the multiscale model over E. coli’s metabolic model alone. Many of the genes covered by this integrated model are well conserved across enterobacters and other, less related bacteria. We addressed the question of whether the bias in synonymous codon usage could affect the growth phenotype and environmental niches that an organism can occupy. We created two classes of in silico strains, one with more biased codon usage and one with more equilibrated codon usage than the wildtype. The reduced growth phenotype in biased strains was caused by tRNA supply shortage, indicating that expansion of tRNA gene content or tRNA codon recognition allow E. coli to respond to changes in codon usage bias. Our analysis suggests that in order to maximize growth and to adapt to new environmental niches, codon usage and tRNA content must co-evolve. These results provide further evidence for the mutation-selection-drift balance theory of codon usage bias. This integrated multiscale reconstruction successfully demonstrates that the constraint-based modeling approach is well suited to whole-cell modeling endeavors.     

Multirate method for co-simulation of electrical-chemical systems in multiscale modeling

Multiscale modeling by means of co-simulation is a powerful tool to address many vital questions in neuroscience. It can for example be applied in the study of the process of learning and memory formation in the brain. At the same time the co-simulation technique makes it possible to take advantage of interoperability between existing tools and multi-physics models as well as distributed computing. However, the theoretical basis for multiscale modeling is not sufficiently understood. There is, for example, a need of efficient and accurate numerical methods for time integration. When time constants of model components are different by several orders of magnitude, individual dynamics and mathematical definitions of each component all together impose stability, accuracy and efficiency challenges for the time integrator. Following our numerical investigations in Brocke et al. (Frontiers in Computational Neuroscience, 10, 97, 2016), we present a new multirate algorithm that allows us to handle each component of a large system with a step size appropriate to its time scale. We take care of error estimates in a recursive manner allowing individual components to follow their discretization time course while keeping numerical error within acceptable bounds. The method is developed with an ultimate goal of minimizing the communication between the components. Thus it is especially suitable for co-simulations. Our preliminary results support our confidence that the multirate approach can be used in the class of problems we are interested in. We show that the dynamics ofa communication signal as well as an appropriate choice of the discretization order between system components may have a significant impact on the accuracy of the coupled simulation. Although, the ideas presented in the paper have only been tested on a single model, it is likely that they can be applied to other problems without loss of generality. We believe that this work may significantly contribute to the establishment of a firm theoretical basis and to the development of an efficient computational framework for multiscale modeling and simulations.     

Experimental and Computational Investigation of Biofilm Formation by Rhodopseudomonas palustris Growth under Two Metabolic Modes

We examined biofilms formed by the metabolically versatile bacterium Rhodopseudomonas palustris grown via different metabolic modes. R. palustris was grown in flow cell chambers with identical medium conditions either in the presence or absence of light and oxygen. In the absence of oxygen and the presence of light, R. palustris grew and formed biofilms photoheterotrophically, and in the presence of oxygen and the absence of light, R. palustris grew and formed biofilms heterotrophically. We used confocal laser scanning microscopy and image analysis software to quantitatively analyze and compare R. palustris biofilm formation over time in these two metabolic modes. We describe quantifiable differences in structure between the biofilms formed by the bacterium grown heterotrophically and those grown photoheterotrophically. We developed a computational model to explore ways in which biotic and abiotic parameters could drive the observed biofilm architectures, as well as a random-forest machine-learning algorithm based on structural differences that was able to identify growth conditions from the confocal imaging of the biofilms with 87% accuracy. Insight into the structure of phototrophic biofilms and conditions that influence biofilm formation is relevant for understanding the generation of biofilm structures with different properties, and for optimizing applications with phototrophic bacteria growing in the biofilm state.     

Cryptococcus neoformans Biofilm Formation Depends on Surface Support and Carbon Source and Reduces Fungal Cell Susceptibility to Heat, Cold, and UV Light

The fungus Cryptococcus neoformans possesses a polysaccharide capsule and can form biofilms on medical devices. We describe the characteristics of C. neoformans biofilm development using a microtiter plate model, microscopic examinations, and a colorimetric 2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-5-[(phenylamino) carbonyl]-2H-tetrazolium-hydroxide (XTT) reduction assay to observe the metabolic activity of cryptococci within a biofilm. A strong correlation between XTT and CFU assays was demonstrated. Chemical analysis of the exopolymeric material revealed sugar composition consisting predominantly of xylose, mannose, and glucose, indicating the presence of other polysaccharides in addition to glucurunoxylomannan. Biofilm formation was affected by surface support differences, conditioning films on the surface, characteristics of the medium, and properties of the microbial cell. A specific antibody to the capsular polysaccharide of this fungus was used to stain the extracellular polysaccharide matrix of the fungal biofilms using light and confocal microscopy. Additionally, the susceptibility of C. neoformans biofilms and planktonic cells to environmental stress was investigated using XTT reduction and CFU assays. Biofilms were less susceptible to heat, cold, and UV light exposition than their planktonic counterparts. Our findings demonstrate that fungal biofilm formation is dependent on support surface characteristics and that growth in the biofilm state makes fungal cells less susceptible to potential environmental stresses.     

A paired-quadrat method for use in multiscale ordination

Multiscale ordination is a technique for examining spatial patterns of several species at several scales. We present a paired-quadrat method (paired quadrat covariance; PQC) to be used in multiscale ordination and test it with artificial data. Multiscale ordination with PQC successfully extracted the salient features of the data set. The method appears to be more sensitive than blocked-quadrat techniques for extracting small-scale patterns. We suggest that PQC will be useful as a complement to existing procedures or as a tool for analysing data from scattered quadrat arrangements.Abbreviations PQC = Paired Quadrat Covariance - PQV = Paired Quadrat Variance - TTLC = Two-Term Local Covariance - TTLQV = Two-Term Local Quadrat Variance     

First Principles Modeling of Dissociative Adsorption at Crystal Surfaces: Hydrogen on Pt(111)

Multiscale simulation has the potential of becoming the new modeling paradigm in chemical sciences. An important class of multiscale models involves the mapping of a finer scale model into an approximate surface that is used by a coarser scale model. As a specific example of this class we present the case of the adsorption dynamics of diatomic molecules on single crystal catalyst surfaces. The prototype system studied is the dissociative adsorption of H₂ on Pt(111). The finer scale model consists of density functional theory (DFT) periodic slab calculations that provide a small dataset for training an atomistic scale potential energy surface. The coarser scale model uses a semi-classical molecular dynamics (MD) algorithm to obtain the sticking coefficient as a function of the incident energy. Comparison to experimental data and published simulation work is presented. Finally, major challenges in multiscale modeling of chemical reactivity in coupled DFT/MD simulations are discussed, specifically the need for a systematic method of assessing the accuracy of the coarse graining process.     

Influence of phosphorus on biofilm formation in model drinking water distribution systems

Aims:  This study investigated the effects of phosphorus on biofilm formation via annular reactor systems in terms of biofilm cell growth, exopolysaccharide (EPS) production, biofilm structure and cell metabolic potential.
Methods and Results:  Drinking water biofilms were developed in annular reactors with supplement of carbon and different levels of phosphorus. The biofilm formation was monitored over a period of 30 days. Biofilm related parameters were examined by various methods, which included heterotrophic plate count, total carbohydrate content, confocal laser scanning microscopy and GN2 microplate assay. Our results showed that phosphorus addition can promote the biofilm cell growth (cell count increased about 1 log with addition of 30 and 300 μg l⁻¹ of phosphorus). However, the addition of 30 and 300 μg l⁻¹ of phosphorus caused 81% and 77% decrease in EPS production, respectively. The results of biofilm structure analysis showed that the addition of 30 and 300 μg l⁻¹ of phosphorus can induce thicker and less homogeneous biofilms with more biomass. Furthermore, the addition of 30 and 300 μg l⁻¹ of phosphorus dramatically increased the biofilm cell metabolic potential. The addition of 3 μg l⁻¹ of phosphorus was found to have minor effects on the parameters examined.
Conclusions:  The results indicate phosphorus addition to drinking water distribution system (DWDS) has a complicated effect on the biofilm formation.
Significance and Impact of the Study:  As the addition of phosphorus at certain levels can affect the biofilm growth in DWDS, care should be taken when phosphate-based corrosion inhibitors are used in the DWDS.     

Microtiter Dish Biofilm Formation Assay

Biofilms are communities of microbes attached to surfaces, which can be found in medical, industrial and natural settings. In fact, life in a biofilm probably represents the predominate mode of growth for microbes in most environments. Mature biofilms have a few distinct characteristics. Biofilm microbes are typically surrounded by an extracellular matrix that provides structure and protection to the community. Microbes growing in a biofilm also have a characteristic architecture generally comprised of macrocolonies (containing thousands of cells) surrounded by fluid-filled channels. Biofilm-grown microbes are also notorious for their resistance to a range of antimicrobial agents including clinically relevant antibiotics.The microtiter dish assay is an important tool for the study of the early stages in biofilm formation, and has been applied primarily for the study of bacterial biofilms, although this assay has also been used to study fungal biofilm formation. Because this assay uses static, batch-growth conditions, it does not allow for the formation of the mature biofilms typically associated with flow cell systems. However, the assay has been effective at identifying many factors required for initiation of biofilm formation (i.e, flagella, pili, adhesins, enzymes involved in cyclic-di-GMP binding and metabolism) and well as genes involved in extracellular polysaccharide production. Furthermore, published work indicates that biofilms grown in microtiter dishes do develop some properties of mature biofilms, such a antibiotic tolerance and resistance to immune system effectors.This simple microtiter dish assay allows for the formation of a biofilm on the wall and/or bottom of a microtiter dish. The high throughput nature of the assay makes it useful for genetic screens, as well as testing biofilm formation by multiple strains under various growth conditions. Variants of this assay have been used to assess early biofilm formation for a wide variety of microbes, including but not limited to, pseudomonads, Vibrio cholerae, Escherichia coli, staphylocci, enterococci, mycobacteria and fungi.In the protocol described here, we will focus on the use of this assay to study biofilm formation by the model organism Pseudomonas aeruginosa. In this assay, the extent of biofilm formation is measured using the dye crystal violet (CV). However, a number of other colorimetric and metabolic stains have been reported for the quantification of biofilm formation using the microtiter plate assay. The ease, low cost and flexibility of the microtiter plate assay has made it a critical tool for the study of biofilms.Download video file.^{(24M, mov)}     

Involvement of NADH Oxidase in Biofilm Formation in Streptococcus sanguinis

Biofilms play important roles in microbial communities and are related to infectious diseases. Here, we report direct evidence that a bacterial nox gene encoding NADH oxidase is involved in biofilm formation. A dramatic reduction in biofilm formation was observed in a Streptococcus sanguinis nox mutant under anaerobic conditions without any decrease in growth. The membrane fluidity of the mutant bacterial cells was found to be decreased and the fatty acid composition altered, with increased palmitic acid and decreased stearic acid and vaccenic acid. Extracellular DNA of the mutant was reduced in abundance and bacterial competence was suppressed. Gene expression analysis in the mutant identified two genes with altered expression, gtfP and Idh, which were found to be related to biofilm formation through examination of their deletion mutants. NADH oxidase-related metabolic pathways were analyzed, further clarifying the function of this enzyme in biofilm formation.     

Passive control of quorum sensing: prevention of Pseudomonas aeruginosa biofilm formation by imprinted polymers

Here we present the first molecular imprinted polymer (MIP) that is able to attenuate the biofilm formation of the opportunistic human pathogen Pseudomonas aeruginosa through specific sequestration of its signal molecule N-(3-oxododecanoyl)-L-homoserine lactone (3-oxo-C(12)-AHL). The MIP was rationally designed using computational modeling, and its capacity and specificity and that of a corresponding blank polymer toward signal molecule of P. aeruginosa (3-oxo-C(12)-AHL) and its analogue were tested. The biofilm formation in the presence of polymers and without polymers was studied using scanning confocal laser microscopy. Staining with crystal violet dye was used for the quantification of the biofilm formation. A significant reduction of the biofilm growth was observed in the presence of MIP (>80%), which was superior to that of the resin prepared without template, which showed a reduction of 40% in comparison with biofilm, which was grown without polymer addition. It was shown that 3-oxo-C(12)-AHL-specific MIP prevented the development of quorum-sensing-controlled phenotypes (in this case, biofilm formation) from being up-regulated. The developed MIP could be considered as a new tool for the elimination of life-threatening infections in a multitude of practical applications; it could, for example, be grafted on the surface of medical devices such as catheters and lenses, be a component of paints, or be used as a wound adsorbent.     

The confluence of machine learning and multiscale simulations

Multiscale modeling has a long history of use in structural biology, as computational biologists strive to overcome the time- and length-scale limits of atomistic molecular dynamics. Contemporary machine learning techniques, such as deep learning, have promoted advances in virtually every field of science and engineering and are revitalizing the traditional notions of multiscale modeling. Deep learning has found success in various approaches for distilling information from fine-scale models, such as building surrogate models and guiding the development of coarse-grained potentials. However, perhaps its most powerful use in multiscale modeling is in defining latent spaces that enable efficient exploration of conformational space. This confluence of machine learning and multiscale simulation with modern high-performance computing promises a new era of discovery and innovation in structural biology.     

Biofilm formation on human airway epithelia by encapsulated Neisseria meningitidis serogroup B

Neisseria meningitidis is the etiologic agent of meningococcal meningitis. We compared 48-h biofilm formation by N. meningitidis serogroup B strains NMB, MC58, C311 and isogenic mutants defective in capsule formation on SV-40 transformed human bronchial epithelial (HBE) cells in a flow cell. We demonstrated that strains NMB and NMB siaA-D were defective in biofilm formation over glass, and there was a partial rescue of biofilm growth for strain NMB on collagen-coated coverslips at 48 h. We demonstrated all three serogroup B strains form biofilms of statistically equivalent average height on HBE cells as their isogenic capsular mutants. Strain NMB also formed a biofilm of statistically equivalent biomass as the NMB siaA-D mutant on HBE cells at 6 and 48 h. These biofilms are significantly larger than biofilms formed over glass or collagen. Verification that strain NMB expressed capsule in biofilms on HBE cells was demonstrated by staining with 2.2.B, a monoclonal antibody with specificity for the serogroup B capsule. ELISA analysis demonstrated that strains MC58 and C311 also produced capsules during biofilm growth. These findings suggest that encapsulated meningococci can form biofilms on epithelial cells suggesting that biofilm formation may play a role in nasopharyngeal colonization.     

Broad-Spectrum Anti-biofilm Peptide That Targets a Cellular Stress Response

Bacteria form multicellular communities known as biofilms that cause two thirds of all infections and demonstrate a 10 to 1000 fold increase in adaptive resistance to conventional antibiotics. Currently, there are no approved drugs that specifically target bacterial biofilms. Here we identified a potent anti-biofilm peptide 1018 that worked by blocking (p)ppGpp, an important signal in biofilm development. At concentrations that did not affect planktonic growth, peptide treatment completely prevented biofilm formation and led to the eradication of mature biofilms in representative strains of both Gram-negative and Gram-positive bacterial pathogens including Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, methicillin resistant Staphylococcus aureus, Salmonella Typhimurium and Burkholderia cenocepacia. Low levels of the peptide led to biofilm dispersal, while higher doses triggered biofilm cell death. We hypothesized that the peptide acted to inhibit a common stress response in target species, and that the stringent response, mediating (p)ppGpp synthesis through the enzymes RelA and SpoT, was targeted. Consistent with this, increasing (p)ppGpp synthesis by addition of serine hydroxamate or over-expression of relA led to reduced susceptibility to the peptide. Furthermore, relA and spoT mutations blocking production of (p)ppGpp replicated the effects of the peptide, leading to a reduction of biofilm formation in the four tested target species. Also, eliminating (p)ppGpp expression after two days of biofilm growth by removal of arabinose from a strain expressing relA behind an arabinose-inducible promoter, reciprocated the effect of peptide added at the same time, leading to loss of biofilm. NMR and chromatography studies showed that the peptide acted on cells to cause degradation of (p)ppGpp within 30 minutes, and in vitro directly interacted with ppGpp. We thus propose that 1018 targets (p)ppGpp and marks it for degradation in cells. Targeting (p)ppGpp represents a new approach against biofilm-related drug resistance.     

The Role of the QseC Quorum-Sensing Sensor Kinase in Epinephrine-Enhanced Motility and Biofilm Formation by Escherichia coli

Biofilms play a pivotal role in infections related to devices. Biofilm formation in Escherichia coli is mediated by the quorum-sensing E. coli regulator C (QseC), the histidine sensor kinase that can sense epinephrine (EPI)/norepinephrine (NE). In this study, we evaluate the role of the QseC quorum-sensing sensor kinase in epinephrine-enhanced motility and biofilm formation by E. coli. An E. coli MC1000 qseC mutant was constructed. We investigated the role of the QseC in the formation of biofilms on the surface of medical-grade polyvinyl chloride using the E. coli K-12 MC1000 strain as well as a corresponding qseC mutant. Addition of EPI/NE increased biofilm formation by wild-type K-12 MC1000 but not by the isogenic qseC mutant. Scanning confocal laser microscopy corroborated these results by showing that EPI/NE addition significantly increased biofilm’s thickness. As expected, the addition of EPI/NE to the qseC mutant, which lacks the ability to sense the hormones, failed to stimulate biofilm formation. Since EPI/NE addition increased bacterial motility, we proposed that their stimulatory effects on biofilm formation occur by enhancing bacterial motility and altering biofilm architecture. We also found that EPI/NE regulate motility and the biofilm phenotype via QseC, as motility was diminished and biofilm formation was significantly decreased in a qseC deletion mutant. These results indicate that EPI/NE induce E. coli biofilm formation on the surface of polyvinyl chloride through QseC. Cross-talk between E. coli (quorum sensing) and host hormones may explain the pathogen-caused opportunistic infections that occur in patients with prosthetic devices used during hormone level fluctuations in the host.     

A Systems-Level Approach for Investigating Pseudomonas aeruginosa Biofilm Formation

Prevention of the initiation of biofilm formation is the most important step for combating biofilm-associated pathogens, as the ability of pathogens to resist antibiotics is enhanced 10 to 1000 times once biofilms are formed. Genes essential to bacterial growth in the planktonic state are potential targets to treat biofilm-associated pathogens. However, the biofilm formation capability of strains with mutations in these essential genes must be evaluated, since the pathogen might form a biofilm before it is eliminated. In order to address this issue, this work proposes a systems-level approach to quantifying the biofilm formation capability of mutants to determine target genes that are essential for bacterial metabolism in the planktonic state but do not induce biofilm formation in their mutants. The changes of fluxes through the reactions associated with the genes positively related to biofilm formation are used as soft sensors in the flux balance analysis to quantify the trend of biofilm formation upon the mutation of an essential gene. The essential genes whose mutants are predicted not to induce biofilm formation are regarded as gene targets. The proposed approach was applied to identify target genes to treat Pseudomonas aeruginosa infections. It is interesting to find that most essential gene mutants exhibit high potential to induce the biofilm formation while most non-essential gene mutants do not. Critically, we identified four essential genes, lysC, cysH, adk, and galU, that constitute gene targets to treat P. aeruginosa. They have been suggested by existing experimental data as potential drug targets for their crucial role in the survival or virulence of P. aeruginosa. It is also interesting to find that P. aeruginosa tends to survive the essential-gene mutation treatment by mainly enhancing fluxes through 8 metabolic reactions that regulate acetate metabolism, arginine metabolism, and glutamate metabolism.