Role of Intracellular Stochasticity in Biofilm Growth. Insights from Population Balance Modeling
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{"title"=>"Role of intracellular stochasticity in biofilm growth. insights from population balance modeling", "type"=>"journal", "authors"=>[{"first_name"=>"Che Chi", "last_name"=>"Shu", "scopus_author_id"=>"42662508800"}, {"first_name"=>"Anushree", "last_name"=>"Chatterjee", "scopus_author_id"=>"56405003000"}, {"first_name"=>"Wei Shou", "last_name"=>"Hu", "scopus_author_id"=>"36064794400"}, {"first_name"=>"Doraiswami", "last_name"=>"Ramkrishna", "scopus_author_id"=>"35566975200"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84893372431", "pui"=>"372245171", "doi"=>"10.1371/journal.pone.0079196", "isbn"=>"1932-6203", "sgr"=>"84893372431", "pmid"=>"24232571"}, "id"=>"36bceb49-57d2-39c9-98fd-41a6782bd2d5", "abstract"=>"There is increasing recognition that stochasticity involved in gene regulatory processes may help cells enhance the signal or synchronize expression for a group of genes. Thus the validity of the traditional deterministic approach to modeling the foregoing processes cannot be without exception. In this study, we identify a frequently encountered situation, i.e., the biofilm, which has in the past been persistently investigated with intracellular deterministic models in the literature. We show in this paper circumstances in which use of the intracellular deterministic model appears distinctly inappropriate. In Enterococcus faecalis, the horizontal gene transfer of plasmid spreads drug resistance. The induction of conjugation in planktonic and biofilm circumstances is examined here with stochastic as well as deterministic models. The stochastic model is formulated with the Chemical Master Equation (CME) for planktonic cells and Reaction-Diffusion Master Equation (RDME) for biofilm. The results show that although the deterministic model works well for the perfectly-mixed planktonic circumstance, it fails to predict the averaged behavior in the biofilm, a behavior that has come to be known as stochastic focusing. A notable finding from this work is that the interception of antagonistic feedback loops to signaling, accentuates stochastic focusing. Moreover, interestingly, increasing particle number of a control variable could lead to an even larger deviation. Intracellular stochasticity plays an important role in biofilm and we surmise by implications from the model, that cell populations may use it to minimize the influence from environmental fluctuation.", "link"=>"http://www.mendeley.com/research/role-intracellular-stochasticity-biofilm-growth-insights-population-balance-modeling", "reader_count"=>30, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>1, "Student > Master"=>5, "Other"=>2, "Student > Bachelor"=>2, "Professor"=>4}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>1, "Student > Master"=>5, "Other"=>2, "Student > Bachelor"=>2, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Engineering"=>4, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>9, "Medicine and Dentistry"=>1, "Veterinary Science and Veterinary Medicine"=>1, "Chemical Engineering"=>3, "Chemistry"=>1, "Social Sciences"=>1, "Computer Science"=>4}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Chemistry"=>{"Chemistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>9}, "Computer Science"=>{"Computer Science"=>4}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>1}, "Chemical Engineering"=>{"Chemical Engineering"=>3}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Iran"=>1, "United States"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1279943"], "description"=>"<p>Nomenclature of pCF10 system.</p>", "links"=>[], "tags"=>["pcf10"], "article_id"=>850048, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.t001", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Nomenclature_of_pCF10_system_/850048", "title"=>"Nomenclature of pCF10 system.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279941"], "description"=>"<p>When iCF10 concentration in liquid phase is subject to small environmental fluctuation, stochastic model are less sensitive to it. A) The Gaussian white noise with standard deviation of 10 nM. Only positive concentration is taken from the noise (the negative concentrations have been set to zero) and exactly the same noise is imposed to both models. B) and C) the response from stochastic and deterministic models, respectively, after exposing to different magnitude of Gaussian white noise, blue 10 nM, green 20 nM, red 40 nM and cyan 80 nM. Cell population may probably use this feature against unwanted environmental fluctuation.</p>", "links"=>[], "tags"=>["intracellular", "stochasticity"], "article_id"=>850046, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.g005", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cells_with_intracellular_stochasticity_are_less_sensitive_to_small_environmental_fluctuation_/850046", "title"=>"Cells with intracellular stochasticity are less sensitive to small environmental fluctuation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279937"], "description"=>"<p>The width of biofilm is considered to be much larger than its thickness (L). For vertical direction, one end of biofilm attaches to wall (z = 0) and the other end is exposed to liquid phase (z = L). The biofilm is discretized into many subdomains, denoted by the boxed regions. The length of subdomain is considered to be small enough for applying well-stirred assumption.</p>", "links"=>[], "tags"=>["schematic", "biofilm"], "article_id"=>850042, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.g002", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_schematic_representation_of_the_biofilm_model_/850042", "title"=>"The schematic representation of the biofilm model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279946", "https://ndownloader.figshare.com/files/1279947"], "description"=>"<div><p>There is increasing recognition that stochasticity involved in gene regulatory processes may help cells enhance the signal or synchronize expression for a group of genes. Thus the validity of the traditional deterministic approach to modeling the foregoing processes cannot be without exception. In this study, we identify a frequently encountered situation, i.e., the biofilm, which has in the past been persistently investigated with intracellular deterministic models in the literature. We show in this paper circumstances in which use of the intracellular deterministic model appears distinctly inappropriate. In <i>Enterococcus faecalis,</i> the horizontal gene transfer of plasmid spreads drug resistance. The induction of conjugation in planktonic and biofilm circumstances is examined here with stochastic as well as deterministic models. The stochastic model is formulated with the Chemical Master Equation (CME) for planktonic cells and Reaction-Diffusion Master Equation (RDME) for biofilm. The results show that although the deterministic model works well for the perfectly-mixed planktonic circumstance, it fails to predict the averaged behavior in the biofilm, a behavior that has come to be known as <i>stochastic focusing.</i> A notable finding from this work is that the interception of antagonistic feedback loops to signaling, accentuates stochastic focusing. Moreover, interestingly, increasing particle number of a control variable could lead to an even larger deviation. Intracellular stochasticity plays an important role in biofilm and we surmise by implications from the model, that cell populations may use it to minimize the influence from environmental fluctuation.</p></div>", "links"=>[], "tags"=>["intracellular", "stochasticity", "biofilm", "insights"], "article_id"=>850051, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0079196.s001", "https://dx.doi.org/10.1371/journal.pone.0079196.s002"], "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Role_of_Intracellular_Stochasticity_in_Biofilm_Growth_Insights_from_Population_Balance_Modeling_/850051", "title"=>"Role of Intracellular Stochasticity in Biofilm Growth. Insights from Population Balance Modeling", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279945"], "description"=>"<p>Parameter values of pCF10 system.</p>", "links"=>[], "tags"=>["pcf10"], "article_id"=>850050, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.t003", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Parameter_values_of_pCF10_system_/850050", "title"=>"Parameter values of pCF10 system.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279940"], "description"=>"<p>The dash represents the prediction from the deterministic model and the solid line from stochastic model. The black color is for the system with given bulk concentration as boundary condition and the blue color is for system with reflection boundary condition. For the deterministic model, the results of two cases are overlapped. For stochastic model, lack of feedback causes higher stochastic focusing.</p>", "links"=>[], "tags"=>["interrupting"], "article_id"=>850045, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.g004", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_influence_of_interrupting_feedback_loop_/850045", "title"=>"The influence of interrupting feedback loop.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279939"], "description"=>"<p>A) For planktonic environment, the probability distribution of PrgB protein from population balance model with intracellular stochastic gene regulation (surface) and the averaged value estimated by the deterministic model (solid curve) are consistent. B) For biofilm cells, the bulk concentrations of both iCF10 and cCF10 are set to zero as in the natural niche of <i>E. faecalis</i>, the bulk fluid continues flowing <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079196#pone.0079196-Chuang1\" target=\"_blank\">[68]</a>. The probability distribution of PrgB protein with time from deterministic model (solid surface) deviates from that of stochastic model (mesh surface) because the former is not able to describe the difference of stochasticity from planktonic to biofilm environment. C) Both stochastic and deterministic models have the same extracellular cCF10 concentration. D) Although the extracellular iCF10 predicted from the deterministic model is slightly lower than that of stochastic model around time equal to one hour, this should not be the reason causing deterministic model predicting lower value of PrgB in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079196#pone-0079196-g003\" target=\"_blank\">figure 3B</a> because lower iCF10 should lead to higher PrgB. E) and F) Increasing particle number of iCF10 results in more deviation of the deterministic model. The bulk concentration of iCF10 is 10 nM for <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079196#pone-0079196-g003\" target=\"_blank\">figure 3E</a> and 30 nM for <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079196#pone-0079196-g003\" target=\"_blank\">figure 3F</a>. The bulk concentration of cCF10 is 0 nM for both. When bulk concentration of iCF10 increases, the particle number of intracellular iCF10 also increases and the fluctuation of intracellular iCF10 is supposed to be less. But a higher deviation of PrgB protein from the deterministic model is observed.</p>", "links"=>[], "tags"=>["behaviors"], "article_id"=>850044, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.g003", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_behaviors_of_cells_/850044", "title"=>"The behaviors of cells.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279936"], "description"=>"<p>The <i>prgQ-prgX</i> gene pair regulates conjugation. The inhibitor iCF10 released by pCF10 carrying donor cells, is encoded by Q<sub>S</sub> and Q<sub>L</sub> RNA, a product of the <i>prgQ</i> gene. The pheromone cCF10 is released by pCF10 deficient recipient cells in the extracellular environment or by added in. Without the presence of cCF10, iCF10-PrgX protein complexes bind to pCF10 DNA and repress the expression of <i>prgQ</i> gene. When cCF10 enters the donor cell, it alters the structure of PrgX protein and restores <i>prgQ</i> gene to active conformation. In the repressed conformation, nearly all Q<sub>PRE</sub> reacts with Anti-Q to become Q<sub>s</sub> RNA which has no effect on downstream conjugation-causing genes. In active conformation, overwhelming amount of Q<sub>PRE</sub> results in the production of Q<sub>L</sub> to stimulate the expression of <i>prgB.</i> The membrane protein PrgB helps pCF10 carrying donor cells transfer pCF10 to recipient cells.</p>", "links"=>[], "tags"=>["pcf10"], "article_id"=>850041, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.g001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_gene_regulation_of_pCF10_conjugation_/850041", "title"=>"The gene regulation of pCF10 conjugation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279944"], "description"=>"<p>Nomenclature of pCF10 system.</p>", "links"=>[], "tags"=>["pcf10"], "article_id"=>850049, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.t002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Nomenclature_of_pCF10_system_/850049", "title"=>"Nomenclature of pCF10 system.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-11-13 04:24:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/1279942"], "description"=>"<p>The reactions and propensities for stochastic simulation.</p>", "links"=>[], "tags"=>["reactions", "propensities", "stochastic"], "article_id"=>850047, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Che-Chi Shu", "Anushree Chatterjee", "Wei-Shou Hu", "Doraiswami Ramkrishna"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079196.t004", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_reactions_and_propensities_for_stochastic_simulation_/850047", "title"=>"The reactions and propensities for stochastic simulation.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-11-13 04:24:41"}

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Relative Metric

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