1
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Yueqi L, Jie X, Ya S, Huan F, Jiaqi L, Siyao L, Yuen Yee C, Yi N, Wenfang L, Bo P, Kedong S. A biocompatible double-crosslinked gelatin/ sodium alginate/dopamine/quaterniazed chitosan hydrogel for wound dressings based on 3D bioprinting technology. Int J Bioprint 2023; 9:689. [PMID: 37125261 PMCID: PMC10132973 DOI: 10.18063/ijb.v9i1.689] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 12/15/2022] [Indexed: 05/02/2023] Open
Abstract
438Severe skin injuries can cause serious problems, which could affect the patient's normal life, if not dealt properly in a timely and effective manner. It is an urgent requirement to develop personalized wound dressings with excellent antibacterial activity and biocompatibility to match the shape of the wound to facilitate clinical application. In this study, a bioink (GAQ) based on gelatin (Gel)/sodium alginate (SA)/ quaternized chitosan (QCS) was prepared, and GAQ hydrogel dressing grafting with dopamine (GADQ) was fabricated by an extrusion three-dimensional (3D) printing technology. QCS was synthesized by modifying quaternary ammonium group on chitosan, and its structure was successfully characterized by nuclear magnetic resonance (1H NMR) and Fourier-transform infrared spectroscopy (FT-IR). Our results showed that the GADQ hydrogel dressing that was double-crosslinked by EDC/ NHS and Ca2+ had good tensile strength, considerable swelling ratio, and effective antioxidation properties. It also showed that GADQ1.5% had 93.17% and 91.06% antibacterial activity against Staphylococcus aureus and Escherichia coli, respectively. Furthermore, the relative survival ratios of fibroblast cells seeded on these hydrogels exceeded 350% after cultured for 7 days, which proved the biocompatibility of these hydrogels. Overall, this advanced 3D-printed GADQ1.5% hydrogels with effective antioxidation, excellent antibacterial activity and good biocompatibility had a considerable application potential for wound healing.
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Affiliation(s)
- Lu Yueqi
- State Key Laboratory of Fine Chemicals, Dalian R&D Center for Stem Cell and Tissue Engineering, Dalian University of Technology, Dalian 116024, China
- Zhengzhou Institute of Emerging Industrial Technology, Zhengzhou 450000, China
| | - Xu Jie
- State Key Laboratory of Fine Chemicals, Dalian R&D Center for Stem Cell and Tissue Engineering, Dalian University of Technology, Dalian 116024, China
- Zhengzhou Institute of Emerging Industrial Technology, Zhengzhou 450000, China
| | - Su Ya
- State Key Laboratory of Fine Chemicals, Dalian R&D Center for Stem Cell and Tissue Engineering, Dalian University of Technology, Dalian 116024, China
| | - Fang Huan
- State Key Laboratory of Fine Chemicals, Dalian R&D Center for Stem Cell and Tissue Engineering, Dalian University of Technology, Dalian 116024, China
- Zhengzhou Institute of Emerging Industrial Technology, Zhengzhou 450000, China
| | - Liu Jiaqi
- State Key Laboratory of Fine Chemicals, Dalian R&D Center for Stem Cell and Tissue Engineering, Dalian University of Technology, Dalian 116024, China
| | - Lv Siyao
- State Key Laboratory of Fine Chemicals, Dalian R&D Center for Stem Cell and Tissue Engineering, Dalian University of Technology, Dalian 116024, China
| | - Cheng Yuen Yee
- State Key Laboratory of Fine Chemicals, Dalian R&D Center for Stem Cell and Tissue Engineering, Dalian University of Technology, Dalian 116024, China
| | - Nie Yi
- Zhengzhou Institute of Emerging Industrial Technology, Zhengzhou 450000, China
- Corresponding authors: Kedong Song ()
| | - Li Wenfang
- School of Life Science and Technology, Weifang Medical University, Weifang, 261053, China
- Corresponding authors: Kedong Song ()
| | - Pan Bo
- School of Life Science and Technology, Weifang Medical University, Weifang, 261053, China
- Corresponding authors: Kedong Song ()
| | - Song Kedong
- State Key Laboratory of Fine Chemicals, Dalian R&D Center for Stem Cell and Tissue Engineering, Dalian University of Technology, Dalian 116024, China
- Corresponding authors: Kedong Song ()
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2
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Korkmazhan E, Dunn AR. High-order correlations in species interactions lead to complex diversity-stability relationships for ecosystems. Phys Rev E 2022; 105:014406. [PMID: 35193273 DOI: 10.1103/physreve.105.014406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 12/22/2021] [Indexed: 11/07/2022]
Abstract
How ecosystems maintain stability is an active area of research. Inspired by applications of random matrix theory in nuclear physics, May showed decades ago that in an ecosystem model with many randomly interacting species, increasing species diversity decreases the stability of the ecosystem. There have since been many additions to May's efforts, one being an improved understanding the effect of mutualistic, competitive, or predator-prey-like correlations between pairs of species. Here we extend a random matrix technique developed in the context of spin-glass theory to study the effect of high-order correlations among species interactions. The resulting analytically solvable models include next-to-nearest-neighbor correlations in the species interaction network, such as the enemy of my enemy is my friend, as well as higher-order correlations. We find qualitative differences from May and others' models, including nonmonotonic diversity-stability relationships. Furthermore, inclusion of particular next-to-nearest-neighbor correlations in predator-prey as opposed to mutualist-competitive networks causes the former to transition to being more stable at higher species diversity. We discuss potential applicability of our results to microbiota engineering and to the ecology of interpredator interactions, such as cub predation between lions and hyenas as well as companionship between humans and dogs.
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Affiliation(s)
- Elgin Korkmazhan
- Biophysics Program, Stanford University, Stanford, California 94305, USA and Department of Chemical Engineering, Stanford University, Stanford, California 94305, USA
| | - Alexander R Dunn
- Biophysics Program, Stanford University, Stanford, California 94305, USA and Department of Chemical Engineering, Stanford University, Stanford, California 94305, USA
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3
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Sheykhloo H, Milani M, Najafi F, Bani F, Zarebkohan A. Conjugation of Gentamicin to Polyamidoamine Dendrimers Improved Anti-bacterial Properties against Pseudomonas aeruginosa. Adv Pharm Bull 2021; 11:675-683. [PMID: 34888214 PMCID: PMC8642794 DOI: 10.34172/apb.2021.076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 09/29/2020] [Accepted: 10/13/2020] [Indexed: 11/15/2022] Open
Abstract
Purpose: This study aimed to design gentamicin-conjugated poly (amidoamine) (PAMAM) dendrimers to increase the therapeutic efficiency of gentamicin against Pseudomonas aeruginosa. Methods: Gentamicin-presenting dendrimers were synthesized using MAL-PEG3400-NHS as a redox-sensitive linker to attach gentamicin to the surface of G4 PAMAM dendrimers. The gentamicin molecules were thiolated by using Traut reagent. Then, the functionalized gentamicin molecules were attached to PEGylated PAMAM dendrimers through simple and high selectively maleimide (MAL)-thiol reaction. The structure of gentamicin-conjugated PAMAM dendrimers was characterized and confirmed using nuclear magnetic resonance (NMR), dynamic light scattering (DLS), zeta potential analysis, and transmission electron microscopy (TEM) imaging. The antibacterial properties of the synthesized complex were examined on P. aeruginosa and compared to gentamycin alone. Results: NMR, DLS, zeta potential analysis, and TEM imaging revealed the successful conjugation of gentamicin to PAMAM dendrimers. Data showed the appropriate physicochemical properties of the synthesized nanoparticles. We found a 3-fold increase in the antibacterial properties of gentamicin conjugated to the surface of PAMAM dendrimers compared to non-conjugated gentamicin. Based on data, the anti-biofilm effects of PAMAM-Gentamicin dendrimers increased at least 13 times more than the gentamicin in normal conditions. Conclusion: Data confirmed that PAMAM dendrimer harboring gentamicin could be touted as a novel smart drug delivery system in infectious conditions.
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Affiliation(s)
- Hamed Sheykhloo
- Biotechnology Department, Rabe Rashidi University, Tabriz, Iran
| | - Morteza Milani
- Department of Medical Nanotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Farhood Najafi
- Department of Resin and Additives, Institute for Color Science and Technology, Tehran, Iran
| | - Farhad Bani
- Department of Medical Nanotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.,Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Amir Zarebkohan
- Department of Medical Nanotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.,Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
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4
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Activity of β-Lactam Antibiotics against Metallo-β-Lactamase-Producing Enterobacterales in Animal Infection Models: a Current State of Affairs. Antimicrob Agents Chemother 2021; 65:AAC.02271-20. [PMID: 33782001 DOI: 10.1128/aac.02271-20] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Metallo-β-lactamases (MBLs) result in resistance to nearly all β-lactam antimicrobial agents, as determined by currently employed susceptibility testing methods. However, recently reported data demonstrate that variable and supraphysiologic zinc concentrations in conventional susceptibility testing media compared with physiologic (bioactive) zinc concentrations may be mediating discordant in vitro-in vivo MBL resistance. While treatment outcomes in patients appear suggestive of this discordance, these limited data are confounded by comorbidities and combination therapy. To that end, the goal of this review is to evaluate the extent of β-lactam activity against MBL-harboring Enterobacterales in published animal infection model studies and provide contemporary considerations to facilitate the optimization of current antimicrobials and development of novel therapeutics.
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5
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Abstract
Bacteria use intercellular signaling, or quorum sensing (QS), to share information and respond collectively to aspects of their surroundings. The autoinducers that carry this information are exposed to the external environment; consequently, they are affected by factors such as removal through fluid flow, a ubiquitous feature of bacterial habitats ranging from the gut and lungs to lakes and oceans. To understand how QS genetic architectures in cells promote appropriate population-level phenotypes throughout the bacterial life cycle requires knowledge of how these architectures determine the QS response in realistic spatiotemporally varying flow conditions. Here we develop and apply a general theory that identifies and quantifies the conditions required for QS activation in fluid flow by systematically linking cell- and population-level genetic and physical processes. We predict that when a subset of the population meets these conditions, cell-level positive feedback promotes a robust collective response by overcoming flow-induced autoinducer concentration gradients. By accounting for a dynamic flow in our theory, we predict that positive feedback in cells acts as a low-pass filter at the population level in oscillatory flow, allowing a population to respond only to changes in flow that occur over slow enough timescales. Our theory is readily extendable and provides a framework for assessing the functional roles of diverse QS network architectures in realistic flow conditions.
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Affiliation(s)
- Mohit P Dalwadi
- Mathematical Institute, University of Oxford, Oxford OX2 6GG, United Kingdom;
| | - Philip Pearce
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115
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6
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Oriano M, Zorzetto L, Guagliano G, Bertoglio F, van Uden S, Visai L, Petrini P. The Open Challenge of in vitro Modeling Complex and Multi-Microbial Communities in Three-Dimensional Niches. Front Bioeng Biotechnol 2020; 8:539319. [PMID: 33195112 PMCID: PMC7606986 DOI: 10.3389/fbioe.2020.539319] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 09/28/2020] [Indexed: 12/03/2022] Open
Abstract
The comprehension of the underlying mechanisms of the interactions within microbial communities represents a major challenge to be faced to control their outcome. Joint efforts of in vitro, in vivo and ecological models are crucial to controlling human health, including chronic infections. In a broader perspective, considering that polymicrobial communities are ubiquitous in nature, the understanding of these mechanisms is the groundwork to control and modulate bacterial response to any environmental condition. The reduction of the complex nature of communities of microorganisms to a single bacterial strain could not suffice to recapitulate the in vivo situation observed in mammals. Furthermore, some bacteria can adapt to various physiological or arduous environments embedding themselves in three-dimensional matrices, secluding from the external environment. Considering the increasing awareness that dynamic complex and dynamic population of microorganisms (microbiota), inhabiting different apparatuses, regulate different health states and protect against pathogen infections in a fragile and dynamic equilibrium, we underline the need to produce models to mimic the three-dimensional niches in which bacteria, and microorganisms in general, self-organize within a microbial consortium, strive and compete. This review mainly focuses, as a case study, to lung pathology-related dysbiosis and life-threatening diseases such as cystic fibrosis and bronchiectasis, where the co-presence of different bacteria and the altered 3D-environment, can be considered as worst-cases for chronic polymicrobial infections. We illustrate the state-of-art strategies used to study biofilms and bacterial niches in chronic infections, and multispecies ecological competition. Although far from the rendering of the 3D-environments and the polymicrobial nature of the infections, they represent the starting point to face their complexity. The increase of knowledge respect to the above aspects could positively affect the actual healthcare scenario. Indeed, infections are becoming a serious threat, due to the increasing bacterial resistance and the slow release of novel antibiotics on the market.
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Affiliation(s)
- Martina Oriano
- Molecular Medicine Department (DMM), Center for Health Technologies (CHT), UdR INSTM, University of Pavia, Pavia, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Internal Medicine Department, Respiratory Unit and Adult Cystic Fibrosis Center, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Laura Zorzetto
- Department of Biomaterials, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
| | - Giuseppe Guagliano
- Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” and UdR INSTM Politecnico di Milano, Milan, Italy
| | - Federico Bertoglio
- Molecular Medicine Department (DMM), Center for Health Technologies (CHT), UdR INSTM, University of Pavia, Pavia, Italy
- Technische Universität Braunschweig, Institute of Biochemistry, Biotechnology and Bioinformatic, Department of Biotechnology, Braunschweig, Germany
| | - Sebastião van Uden
- Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” and UdR INSTM Politecnico di Milano, Milan, Italy
| | - Livia Visai
- Molecular Medicine Department (DMM), Center for Health Technologies (CHT), UdR INSTM, University of Pavia, Pavia, Italy
- Department of Occupational Medicine, Toxicology and Environmental Risks, Istituti Clinici Scientifici (ICS) Maugeri, IRCCS, Pavia, Italy
| | - Paola Petrini
- Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” and UdR INSTM Politecnico di Milano, Milan, Italy
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7
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Teimouri H, Kolomeisky AB. Theoretical investigation of stochastic clearance of bacteria: first-passage analysis. J R Soc Interface 2020; 16:20180765. [PMID: 30890051 DOI: 10.1098/rsif.2018.0765] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Understanding mechanisms of bacterial eradication is critically important for overcoming failures of antibiotic treatments. Current studies suggest that the clearance of large bacterial populations proceeds deterministically, while for smaller populations, the stochastic effects become more relevant. Here, we develop a theoretical approach to investigate the bacterial population dynamics under the effect of antibiotic drugs using a method of first-passage processes. It allows us to explicitly evaluate the most important characteristics of bacterial clearance dynamics such as extinction probabilities and extinction times. The new meaning of minimal inhibitory concentrations for stochastic clearance of bacterial populations is also discussed. In addition, we investigate the effect of fluctuations in population growth rates on the dynamics of bacterial eradication. It is found that extinction probabilities and extinction times generally do not correlate with each other when random fluctuations in the growth rates are taking place. Unexpectedly, for a significant range of parameters, the extinction times increase due to these fluctuations, indicating a slowing in the bacterial clearance dynamics. It is argued that this might be one of the initial steps in the pathway for the development of antibiotic resistance. Furthermore, it is suggested that extinction times is a convenient measure of bacterial tolerance.
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Affiliation(s)
- Hamid Teimouri
- 1 Department of Chemistry, Rice University , Houston, TX , USA.,3 Center for Theoretical Biological Physics, Rice University , Houston, TX , USA
| | - Anatoly B Kolomeisky
- 1 Department of Chemistry, Rice University , Houston, TX , USA.,2 Department of Chemical and Biomolecular Engineering, Rice University , Houston, TX , USA.,3 Center for Theoretical Biological Physics, Rice University , Houston, TX , USA
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8
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Carballo-Pacheco M, Nicholson MD, Lilja EE, Allen RJ, Waclaw B. Phenotypic delay in the evolution of bacterial antibiotic resistance: Mechanistic models and their implications. PLoS Comput Biol 2020; 16:e1007930. [PMID: 32469859 PMCID: PMC7307788 DOI: 10.1371/journal.pcbi.1007930] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 06/22/2020] [Accepted: 05/06/2020] [Indexed: 11/19/2022] Open
Abstract
Phenotypic delay-the time delay between genetic mutation and expression of the corresponding phenotype-is generally neglected in evolutionary models, yet recent work suggests that it may be more common than previously assumed. Here, we use computer simulations and theory to investigate the significance of phenotypic delay for the evolution of bacterial resistance to antibiotics. We consider three mechanisms which could potentially cause phenotypic delay: effective polyploidy, dilution of antibiotic-sensitive molecules and accumulation of resistance-enhancing molecules. We find that the accumulation of resistant molecules is relevant only within a narrow parameter range, but both the dilution of sensitive molecules and effective polyploidy can cause phenotypic delay over a wide range of parameters. We further investigate whether these mechanisms could affect population survival under drug treatment and thereby explain observed discrepancies in mutation rates estimated by Luria-Delbrück fluctuation tests. While the effective polyploidy mechanism does not affect population survival, the dilution of sensitive molecules leads both to decreased probability of survival under drug treatment and underestimation of mutation rates in fluctuation tests. The dilution mechanism also changes the shape of the Luria-Delbrück distribution of mutant numbers, and we show that this modified distribution provides an improved fit to previously published experimental data.
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Affiliation(s)
| | - Michael D. Nicholson
- School of Physics and Astronomy, The University of Edinburgh, Edinburgh, United Kingdom
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Elin E. Lilja
- School of Physics and Astronomy, The University of Edinburgh, Edinburgh, United Kingdom
| | - Rosalind J. Allen
- School of Physics and Astronomy, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Synthetic and Systems Biology, The University of Edinburgh, Edinburgh, United Kingdom
| | - Bartlomiej Waclaw
- School of Physics and Astronomy, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Synthetic and Systems Biology, The University of Edinburgh, Edinburgh, United Kingdom
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9
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Power-law tail in lag time distribution underlies bacterial persistence. Proc Natl Acad Sci U S A 2019; 116:17635-17640. [PMID: 31427535 DOI: 10.1073/pnas.1903836116] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Genetically identical microbial cells respond to stress heterogeneously, and this phenotypic heterogeneity contributes to population survival. Quantitative analysis of phenotypic heterogeneity can reveal dynamic features of stochastic mechanisms that generate heterogeneity. Additionally, it can enable a priori prediction of population dynamics, elucidating microbial survival strategies. Here, we quantitatively analyzed the persistence of an Escherichia coli population. When a population is confronted with antibiotics, a majority of cells is killed but a subpopulation called persisters survives the treatment. Previous studies have found that persisters survive antibiotic treatment by maintaining a long period of lag phase. When we quantified the lag time distribution of E. coli cells in a large dynamic range, we found that normal cells rejuvenated with a lag time distribution that is well captured by an exponential decay [exp(-kt)], agreeing with previous studies. This exponential decay indicates that their rejuvenation is governed by a single rate constant kinetics (i.e., k is constant). Interestingly, the lag time distribution of persisters exhibited a long tail captured by a power-law decay. Using a simple quantitative argument, we demonstrated that this power-law decay can be explained by a wide variation of the rate constant k Additionally, by developing a mathematical model based on this biphasic lag time distribution, we quantitatively explained the complex population dynamics of persistence without any ad hoc parameters. The quantitative features of persistence demonstrated in our work shed insights into molecular mechanisms of persistence and advance our knowledge of how a microbial population evades antibiotic treatment.
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10
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Levin-Reisman I, Brauner A, Ronin I, Balaban NQ. Epistasis between antibiotic tolerance, persistence, and resistance mutations. Proc Natl Acad Sci U S A 2019; 116:14734-14739. [PMID: 31262806 PMCID: PMC6642377 DOI: 10.1073/pnas.1906169116] [Citation(s) in RCA: 114] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Understanding the evolution of microorganisms under antibiotic treatments is a burning issue. Typically, several resistance mutations can accumulate under antibiotic treatment, and the way in which resistance mutations interact, i.e., epistasis, has been extensively studied. We recently showed that the evolution of antibiotic resistance in Escherichia coli is facilitated by the early appearance of tolerance mutations. In contrast to resistance, which reduces the effectiveness of the drug concentration, tolerance increases resilience to antibiotic treatment duration in a nonspecific way, for example when bacteria transiently arrest their growth. Both result in increased survival under antibiotics, but the interaction between resistance and tolerance mutations has not been studied. Here, we extend our analysis to include the evolution of a different type of tolerance and a different antibiotic class and measure experimentally the epistasis between tolerance and resistance mutations. We derive the expected model for the effect of tolerance and resistance mutations on the dynamics of survival under antibiotic treatment. We find that the interaction between resistance and tolerance mutations is synergistic in strains evolved under intermittent antibiotic treatment. We extend our analysis to mutations that result in antibiotic persistence, i.e., to tolerance that is conferred only on a subpopulation of cells. We show that even when this population heterogeneity is included in our analysis, a synergistic interaction between antibiotic persistence and resistance mutations remains. We expect our general framework for the epistasis in killing conditions to be relevant for other systems as well, such as bacteria exposed to phages or cancer cells under treatment.
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Affiliation(s)
- Irit Levin-Reisman
- Racah Institute of Physics, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
- The Harvey M. Kruger Family Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
| | - Asher Brauner
- Racah Institute of Physics, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
- The Harvey M. Kruger Family Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
| | - Irine Ronin
- Racah Institute of Physics, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
- The Harvey M. Kruger Family Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
| | - Nathalie Q Balaban
- Racah Institute of Physics, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel;
- The Harvey M. Kruger Family Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
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11
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Hornung R, Grünberger A, Westerwalbesloh C, Kohlheyer D, Gompper G, Elgeti J. Quantitative modelling of nutrient-limited growth of bacterial colonies in microfluidic cultivation. J R Soc Interface 2019; 15:rsif.2017.0713. [PMID: 29445038 DOI: 10.1098/rsif.2017.0713] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Accepted: 01/22/2018] [Indexed: 11/12/2022] Open
Abstract
Nutrient gradients and limitations play a pivotal role in the life of all microbes, both in their natural habitat as well as in artificial, microfluidic systems. Spatial concentration gradients of nutrients in densely packed cell configurations may locally affect the bacterial growth leading to heterogeneous micropopulations. A detailed understanding and quantitative modelling of cellular behaviour under nutrient limitations is thus highly desirable. We use microfluidic cultivations to investigate growth and microbial behaviour of the model organism Corynebacterium glutamicum under well-controlled conditions. With a reaction-diffusion-type model, parameters are extracted from steady-state experiments with a one-dimensional nutrient gradient. Subsequently, we employ particle-based simulations with these parameters to predict the dynamical growth of a colony in two dimensions. Comparing the results of those simulations with microfluidic experiments yields excellent agreement. Our modelling approach lays the foundation for a better understanding of dynamic microbial growth processes, both in nature and in applied biotechnology.
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Affiliation(s)
- Raphael Hornung
- Theoretical Soft Matter and Biophysics, Institute of Complex Systems and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany
| | - Alexander Grünberger
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, 52425 Jülich, Germany.,Multiscale Bioengineering, Bielefeld University, Universitätsstrasse 25, Bielefeld 33615, Germany
| | - Christoph Westerwalbesloh
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Dietrich Kohlheyer
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, 52425 Jülich, Germany.,Aachener Verfahrenstechnik (AVT.MSB), RWTH Aachen University, 52056 Aachen, Germany
| | - Gerhard Gompper
- Theoretical Soft Matter and Biophysics, Institute of Complex Systems and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany
| | - Jens Elgeti
- Theoretical Soft Matter and Biophysics, Institute of Complex Systems and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany
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12
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Allen RJ, Waclaw B. Bacterial growth: a statistical physicist's guide. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2019; 82:016601. [PMID: 30270850 PMCID: PMC6330087 DOI: 10.1088/1361-6633/aae546] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Bacterial growth presents many beautiful phenomena that pose new theoretical challenges to statistical physicists, and are also amenable to laboratory experimentation. This review provides some of the essential biological background, discusses recent applications of statistical physics in this field, and highlights the potential for future research.
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Affiliation(s)
- Rosalind J Allen
- School of Physics and Astronomy, The University of Edinburgh, James Clerk Maxwell Building, Peter Guthrie Tait Road, Edinburgh EH9 3FD, United Kingdom
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13
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De Martino D. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Phys Rev E 2018; 96:060401. [PMID: 29347381 DOI: 10.1103/physreve.96.060401] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Indexed: 11/07/2022]
Abstract
In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region.
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Affiliation(s)
- Daniele De Martino
- Institute of Science and Technology Austria, Am Campus 1, A-3400 Klosterneuburg, Austria
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14
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Greulich P, Doležal J, Scott M, Evans MR, Allen RJ. Predicting the dynamics of bacterial growth inhibition by ribosome-targeting antibiotics. Phys Biol 2017; 14:065005. [PMID: 28714461 PMCID: PMC5730049 DOI: 10.1088/1478-3975/aa8001] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Understanding how antibiotics inhibit bacteria can help to reduce antibiotic use and hence avoid antimicrobial resistance—yet few theoretical models exist for bacterial growth inhibition by a clinically relevant antibiotic treatment regimen. In particular, in the clinic, antibiotic treatment is time-dependent. Here, we use a theoretical model, previously applied to steady-state bacterial growth, to predict the dynamical response of a bacterial cell to a time-dependent dose of ribosome-targeting antibiotic. Our results depend strongly on whether the antibiotic shows reversible transport and/or low-affinity ribosome binding (‘low-affinity antibiotic’) or, in contrast, irreversible transport and/or high affinity ribosome binding (‘high-affinity antibiotic’). For low-affinity antibiotics, our model predicts that growth inhibition depends on the duration of the antibiotic pulse, and can show a transient period of very fast growth following removal of the antibiotic. For high-affinity antibiotics, growth inhibition depends on peak dosage rather than dose duration, and the model predicts a pronounced post-antibiotic effect, due to hysteresis, in which growth can be suppressed for long times after the antibiotic dose has ended. These predictions are experimentally testable and may be of clinical significance.
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Affiliation(s)
- Philip Greulich
- Mathematical Sciences, University of Southampton, Highfield Campus, SO17 1BJ, United Kingdom. Institute for Life Sciences, University of Southampton, Highfield Campus, SO17 1BJ, United Kingdom
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15
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Gralka M, Fusco D, Martis S, Hallatschek O. Convection shapes the trade-off between antibiotic efficacy and the selection for resistance in spatial gradients. Phys Biol 2017; 14:045011. [PMID: 28649977 PMCID: PMC5728155 DOI: 10.1088/1478-3975/aa7bb3] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Since penicillin was discovered about 90 years ago, we have become used to using drugs to eradicate unwanted pathogenic cells. However, using drugs to kill bacteria, viruses or cancer cells has the serious side effect of selecting for mutant types that survive the drug attack. A crucial question therefore is how one could eradicate as many cells as possible for a given acceptable risk of drug resistance evolution. We address this general question in a model of drug resistance evolution in spatial drug gradients, which recent experiments and theories have suggested as key drivers of drug resistance. Importantly, our model takes into account the influence of convection, resulting for instance from blood flow. Using stochastic simulations, we study the fates of individual resistance mutations and quantify the trade-off between the killing of wild-type cells and the rise of resistance mutations: shallow gradients and convection into the antibiotic region promote wild-type death, at the cost of increasing the establishment probability of resistance mutations. We can explain these observed trends by modeling the adaptation process as a branching random walk. Our analysis reveals that the trade-off between death and adaptation depends on the relative length scales of the spatial drug gradient and random dispersal, and the strength of convection. Our results show that convection can have a momentous effect on the rate of establishment of new mutations, and may heavily impact the efficiency of antibiotic treatment.
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Affiliation(s)
- Matti Gralka
- Department of Physics, University of California, Berkeley, CA 94720, United States of America
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16
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Johnson R, Munsky B. The finite state projection approach to analyze dynamics of heterogeneous populations. Phys Biol 2017; 14:035002. [PMID: 28428446 DOI: 10.1088/1478-3975/aa6e5a] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Population modeling aims to capture and predict the dynamics of cell populations in constant or fluctuating environments. At the elementary level, population growth proceeds through sequential divisions of individual cells. Due to stochastic effects, populations of cells are inherently heterogeneous in phenotype, and some phenotypic variables have an effect on division or survival rates, as can be seen in partial drug resistance. Therefore, when modeling population dynamics where the control of growth and division is phenotype dependent, the corresponding model must take account of the underlying cellular heterogeneity. The finite state projection (FSP) approach has often been used to analyze the statistics of independent cells. Here, we extend the FSP analysis to explore the coupling of cell dynamics and biomolecule dynamics within a population. This extension allows a general framework with which to model the state occupations of a heterogeneous, isogenic population of dividing and expiring cells. The method is demonstrated with a simple model of cell-cycle progression, which we use to explore possible dynamics of drug resistance phenotypes in dividing cells. We use this method to show how stochastic single-cell behaviors affect population level efficacy of drug treatments, and we illustrate how slight modifications to treatment regimens may have dramatic effects on drug efficacy.
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Affiliation(s)
- Rob Johnson
- Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London SW7 2AZ, United Kingdom
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