Influence of Nutrient Availability and Quorum Sensing on the Formation of Metabolically Inactive Microcolonies Within Structurally Heterogeneous Bacterial Biofilms: An Individual-Based 3D Cellular Automata Model

Machineni, Lakshmi; Rajapantul, Anil; Nandamuri, Vandana; Pawar, Parag D.

doi:10.1007/s11538-017-0246-9

Cited by 17 publications

(16 citation statements)

References 82 publications

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“…A full mathematical description of the various components and processes incorporated in the model has been presented elsewhere . Here, we briefly present the governing equations, behaviors of the particulate and soluble entities, and the numerical scheme used.…”

Section: Methodsmentioning

confidence: 99%

“…We have previously formulated and analyzed a 3‐dimensional, individual‐based computational model to simulate biofilm growth dynamics and to quantify spatial heterogeneity in the bacterial population as a function of nutrient availability and QS . The model treats bacterial cells as individual entities with their own states, thereby allowing for variability between individual behaviors with respect to their growth rates, antibiotic and nutrient uptake rates, autoinducer production, upregulation and downregulation states, and EPS secretion.…”

Section: Introductionmentioning

confidence: 99%

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A 3D individual‐based model to investigate the spatially heterogeneous response of bacterial biofilms to antimicrobial agents

Machineni

Reddy

Nandamuri

et al. 2018

Math Methods in App Sciences

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The response of bacterial biofilms to treatment with antimicrobial agents is often characterized by the emergence of recalcitrant cellular microcolonies. We present an individual-based model to investigate the biophysical mechanisms of the selective resistance that arises within the biofilm and leads to a spatially heterogeneous response upon treatment with antibiotics. The response occurs in 3 distinct phases. In the first phase, the subpopulation of metabolically active cells diminishes due to antibiotic-induced cell death. Subsequently, in the second phase, increased nutrient availability allows dormant cells in the lower layers of the biofilm to transform into metabolically active cells. In the third phase, survival of the biofilm is governed by the interplay between 2 contrasting factors: (1) rate of antibiotic-induced cell death and (2) rate of transformation of dormant cells into active ones. Metabolically active cells at the distal edge of the biofilm sacrifice themselves to protect the dormant cells in the interior by (1) reducing local antibiotic concentrations and (2) increasing nutrient availability. In the presence of quorum sensing, biofilms exhibit increased tolerance compared with the quorum sensing-negative strains. Extracellular polymeric substance (EPS) forms a protective layer at the top of the biofilm, thereby limiting antibiotic penetration. The surviving cells, in turn, produce EPS resulting in a feedback-like mechanism of resistance. Whereas resistance in QS − biofilms occurs because of transformation of dormant cells into metabolically active cells, this transformation is less pronounced in QS + biofilms, and resistance is a consequence of the sequestration of the antibiotic by EPS.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A 3D individual‐based model to investigate the spatially heterogeneous response of bacterial biofilms to antimicrobial agents

Machineni

Reddy

Nandamuri

et al. 2018

Math Methods in App Sciences

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“…The Java programming language is used since it provides a convenient object-oriented framework well-suited for the individual-based model described here. Nutrient: 0.84 x 10 -2 m 2 h -1 HQNO: 0.84 x 10 -6 m 2 h -1 Autoinducer (S. aureus): 1.5 x 10 -6 m 2 h -1 Autoinducer (P. aeruginosa): 1 x 10 -6 m 2 h -1 (Machineni et al 2017)…”

Section: Model Simulation and Numerical Schemementioning

confidence: 99%

“…Previously, we have used our model to investigate the roles of nutrient availability and QS on the growth dynamics of a monomicrobial biofilm (Machineni et al 2017(Machineni et al , 2018. In the present work, we extend the model to a two-species biofilm comprising of P. aeruginosa and S. aureus, competing for nutrients.…”

Section: Biofilm Growth Dynamics Of a Two-species Biofilm: Influence mentioning

confidence: 99%

Quorum sensing-induced phenotypic switching as a regulatory nutritional stress response in a competitive two-species biofilm: An individual-based cellular automata model

Chirathanamettu

Pawar

2020

Preprint

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Competition for nutrients in a polymicrobial biofilm may lead to susceptible species being subjected to nutritional stress. The influence of bacterial growth rates and interspecies interactions on their susceptibility and response to nutritional stress is not well understood. Pseudomonas aeruginosa and Staphylococcus aureus are two prevalent causative pathogens that coexist in biofilm-associated infections. Despite being the slower-growing species, P. aeruginosa dominates in a two-species biofilm by inducing phenotypic switching of S. aureus to a metabolically-challenged small colony variant (SCV) via the release of 2-heptyl-4-hydroxyquinoline N-oxide (HQNO). We hypothesize that P. aeruginosa experiences nutritional stress in competition with S. aureus, and that the release of HQNO is an adaptive response to nutritional stress. We present an individual-based two-species biofilm model in which interactions between entities induce emergent properties. As the biofilm matured, the difference in growth rates of the two species caused a non-uniform distribution of nutrients leading to nutritional stress for P. aeruginosa and a concurrent increase in the proportion of S. aureus subpopulation. The latter resulted in increased release of autoinducer, and subsequently the upregulation of P. aeruginosa cells via quorum sensing. Upregulated P. aeruginosa cells released HQNO at enhanced rates, thereby inducing phenotypic switching of S. aureus to SCVs which consume nutrient at a reduced rate. This shifted the nutrient distribution back in favor of P. aeruginosa, thereby relieving nutritional stress. Increase in nutritional stress potentiated the transformation of S. aureus into SCVs. HQNO production decreased once nutritional stress was relieved, indicating that phenotypic switching acts as a regulatory stressadaptive response.

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“…1 The antimicrobial resistance of bacteria assuming a biofilm mode of growth poses challenges not only to host immune clearance mechanisms but also to health care settings, in the form of an increased risk of hospital-acquired infections. 2 The high level of antibiotic resistance that characterizes biofilms can be attributed to their structurally heterogeneous microenvironments, some of which contain metabolically inactive cell population, 3,4 as well as to the differential expression of multiple gene networks and extracellular matrix by the resident bacterial species. 4 Over the last decade, increasing attention has been paid to antimicrobial peptides (AMPs) as therapeutic agents, because resistance to them is thus far rare.…”

Section: Introductionmentioning

confidence: 99%

Determination of the spatiotemporal dependence of <em>Pseudomonas aeruginosa</em> biofilm viability after treatment with NLC-colistin

Sans-Serramitjana¹,

Jorba²,

Pedraz³

et al. 2017

IJN

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The emergence of colistin-resistant Pseudomonas aeruginosa in cystic fibrosis (CF) patients, particularly after long-term inhalation treatments, has been recently reported. Nanoen-capsulation may enable preparations to overcome the limitations of conventional pharmaceutical forms. We have determined the time-dependent viability of P. aeruginosa biofilms treated with both free and nanoencapsulated colistin. We also examined the relationship between the optimal anti-biofilm activity of nanostructured lipid carrier (NLC)-colistin and the structural organization of the biofilm itself. The results showed the more rapid killing of P. aeruginosa bacterial biofilms by NLC-colistin than by free colistin. However, the two formulations did not differ in terms of the final percentages of living and dead cells, which were higher in the inner than in the outer layers of the treated biofilms. The effective anti-biofilm activity of NLC-colistin and its faster killing effect recommend further studies of its use over free colistin in the treatment of P. aeruginosa infections in CF patients.

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Influence of Nutrient Availability and Quorum Sensing on the Formation of Metabolically Inactive Microcolonies Within Structurally Heterogeneous Bacterial Biofilms: An Individual-Based 3D Cellular Automata Model

Cited by 17 publications

References 82 publications

A 3D individual‐based model to investigate the spatially heterogeneous response of bacterial biofilms to antimicrobial agents

A 3D individual‐based model to investigate the spatially heterogeneous response of bacterial biofilms to antimicrobial agents

Quorum sensing-induced phenotypic switching as a regulatory nutritional stress response in a competitive two-species biofilm: An individual-based cellular automata model

Determination of the spatiotemporal dependence of <em>Pseudomonas aeruginosa</em> biofilm viability after treatment with NLC-colistin

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