scholarly journals Emergent Subpopulation Behavior Uncovered with a Community Dynamic Metabolic Model ofEscherichia coliDiauxic Growth

mSystems ◽  
2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Antonella Succurro ◽  
Daniel Segrè ◽  
Oliver Ebenhöh
Keyword(s):  
Metabolic Modeling ◽  
Metabolic Model ◽  
Published Data ◽  
Diauxic Shift ◽  
Source Modeling ◽  
Cell Level ◽  
Modeling Framework ◽  
Content Type ◽  
E Coli ◽  
New Perspective

ABSTRACTMicrobes have adapted to greatly variable environments in order to survive both short-term perturbations and permanent changes. A classical and yet still actively studied example of adaptation to dynamic environments is the diauxic shift ofEscherichia coli, in which cells grow on glucose until its exhaustion and then transition to using previously secreted acetate. Here we tested different hypotheses concerning the nature of this transition by using dynamic metabolic modeling. To reach this goal, we developed an open source modeling framework integrating dynamic models (ordinary differential equation systems) with structural models (metabolic networks) which can take into account the behavior of multiple subpopulations and smooth flux transitions between time points. We used this framework to model the diauxic shift, first with a singleE. colimodel whose metabolic state represents the overall population average and then with a community of two subpopulations, each growing exclusively on one carbon source (glucose or acetate). After introduction of an environment-dependent transition function that determined the balance between subpopulations, our model generated predictions that are in strong agreement with published data. Our results thus support recent experimental evidence that diauxie, rather than a coordinated metabolic shift, would be the emergent pattern of individual cells differentiating for optimal growth on different substrates. This work offers a new perspective on the use of dynamic metabolic modeling to investigate population heterogeneity dynamics. The proposed approach can easily be applied to other biological systems composed of metabolically distinct, interconverting subpopulations and could be extended to include single-cell-level stochasticity.IMPORTANCEEscherichia colidiauxie is a fundamental example of metabolic adaptation, a phenomenon that is not yet completely understood. Further insight into this process can be achieved by integrating experimental and computational modeling methods. We present a dynamic metabolic modeling approach that captures diauxie as an emergent property of subpopulation dynamics inE. colimonocultures. Without fine-tuning the parameters of theE. colicore metabolic model, we achieved good agreement with published data. Our results suggest that single-organism metabolic models can only approximate the average metabolic state of a population, therefore offering a new perspective on the use of such modeling approaches. The open source modeling framework that we provide can be applied to model general subpopulation systems in more-complex environments and can be extended to include single-cell-level stochasticity.

scholarly journals Emergent sub-population behavior uncovered with a community dynamic metabolic model ofEscherichia colidiauxic growth

2018 ◽  
Author(s):  
Antonella Succurro ◽  
Daniel Segrè ◽  
Oliver Ebenhöh
Keyword(s):  
Metabolic Modeling ◽  
Metabolic Model ◽  
Published Data ◽  
Diauxic Shift ◽  
Single Cell Level ◽  
Source Modeling ◽  
Cell Level ◽  
Modeling Framework ◽  
E Coli ◽  
New Perspective

AbstractMicrobes have adapted to greatly variable environments in order to survive both short-term perturbations and permanent changes. A classical, yet still actively studied example of adaptation to dynamic environments is the diauxic shift ofEscherichia coli, in which cells grow on glucose until its exhaustion, and then transition to using previously secreted acetate. Here we tested different hypotheses concerning the nature of this transition by using dynamic metabolic modeling. Towards this goal, we developed an open source modeling framework integrating dynamic models (ordinary differential equation systems) with structural models (metabolic networks), which can take into account the behavior of multiple sub-populations, and smooth ux transitions between different time points. We used this framework to model the diauxic shift, first with a singleE. colimodel whose metabolic state represents the overall population average, and then with a community of two sub-populations each growing exclusively on one carbon source (glucose or acetate). After introducing an environment-dependent transition function that determines the balance between different sub-populations, our model generates predictions that are in strong agreement with published data. We thus support recent experimental evidence that, rather than a coordinated metabolic shift, diauxie would be the emergent pattern of individual cells differentiating for optimal growth on different sub-strates. This work offers a new perspective on the use of dynamic metabolic modeling to investigate population heterogeneity dynamics. The proposed approach can easily be applied to other biological systems composed of metabolically distinct, interconverting sub-populations, and could be extended to include single-cell level stochasticity.ImportanceEscherichia colidiauxie is a fundamental example of metabolic adaptation that is not yet completely understood. Further insight into this process can be achieved by integrating experimental and computational modeling methods. We present a dynamic metabolic modeling approach that captures diauxie as an emergent property of sub-population dynamics inE. colimonocultures. Without fine tuning the parameters of theE. colicore metabolic model, we achieve good agreement with published data. Our results suggest that single-organism metabolic models can only approximate the average metabolic state of a population, therefore offering a new perspective on the use of such modeling approaches. The open source modeling framework we provide can be applied to model general sub-population systems in more complex environments, and can be extended to include single-cell level stochasticity.

scholarly journals d-Serine induces distinct transcriptomes in diverse Escherichia coli pathotypes

Microbiology ◽  
2021 ◽  
Vol 167 (10) ◽  
Author(s):  
James P. R. Connolly ◽  
Natasha C. A. Turner ◽  
Jennifer C. Hallam ◽  
Patricia T. Rimbi ◽  
Tom Flett ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Type Species ◽  
Pathogenic Bacteria ◽  
Neonatal Meningitis ◽  
Published Data ◽  
Toxic Metabolite ◽  
Transcriptional Responses ◽  
Content Type ◽  
E Coli ◽  
Link Type

Appropriate interpretation of environmental signals facilitates niche specificity in pathogenic bacteria. However, the responses of niche-specific pathogens to common host signals are poorly understood. d-Serine (d-ser) is a toxic metabolite present in highly variable concentrations at different colonization sites within the human host that we previously found is capable of inducing changes in gene expression. In this study, we made the striking observation that the global transcriptional response of three Escherichia coli pathotypes – enterohaemorrhagic E. coli (EHEC), uropathogenic E. coli (UPEC) and neonatal meningitis-associated E. coli (NMEC) – to d-ser was highly distinct. In fact, we identified no single differentially expressed gene common to all three strains. We observed the induction of ribosome-associated genes in extraintestinal pathogens UPEC and NMEC only, and the induction of purine metabolism genes in gut-restricted EHEC, and UPEC indicating distinct transcriptional responses to a common signal. UPEC and NMEC encode dsdCXA – a genetic locus required for detoxification and hence normal growth in the presence of d-ser. Specific transcriptional responses were induced in strains accumulating d-ser (WT EHEC and UPEC/NMEC mutants lacking the d-ser-responsive transcriptional activator DsdC), corroborating the notion that d-ser is an unfavourable metabolite if not metabolized. Importantly, many of the UPEC-associated transcriptome alterations correlate with published data on the urinary transcriptome, supporting the hypothesis that d-ser sensing forms a key part of urinary niche adaptation in this pathotype. Collectively, our results demonstrate distinct pleiotropic responses to a common metabolite in diverse E. coli pathotypes, with important implications for niche selectivity.

scholarly journals Minicells as a Damage Disposal Mechanism inEscherichia coli

mSphere ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Camilla U. Rang ◽  
Audrey Proenca ◽  
Christen Buetz ◽  
Chao Shi ◽  
Lin Chao
Keyword(s):  
Wild Type ◽  
Chromosomal Dna ◽  
Cell Level ◽  
Content Type ◽  
E Coli ◽  
Survival And Growth ◽  
First Time ◽  
Antibiotic Level ◽  
Type Strains ◽  
Sister Cells

ABSTRACTMany bacteria produce small, spherical minicells that lack chromosomal DNA and therefore are unable to proliferate. Although minicells have been used extensively by researchers as a molecular tool, nothing is known about why bacteria produce them. Here, we show that minicells helpEscherichia colicells to rid themselves of damaged proteins induced by antibiotic stress. By comparing the survival and growth rates of wild-type strains with theE. coliΔminCmutant, which produces excess minicells, we found that the mutant was more resistant to streptomycin. To determine the effects of producing minicells at the single-cell level, we also tracked the growth ofΔminClineages by microscopy. We were able to show that the mutant increased the production of minicells in response to a higher level of the antibiotic. When we compared two sister cells, in which one produced minicells and the other did not, the daughters of the former had a shorter doubling time at this higher antibiotic level. Additionally, we found that minicells were more likely produced at the mother’s old pole, which is known to accumulate more aggregates. More importantly, by using a fluorescent IbpA chaperone to tag damage aggregates, we found that polar aggregates were contained by and ejected with the minicells produced by the mother bacterium. These results demonstrate for the first time the benefit to bacteria for producing minicells.IMPORTANCEBacteria have the ability to produce minicells, or small spherical versions of themselves that lack chromosomal DNA and are unable to replicate. A minicell can constitute as much as 20% of the cell’s volume. Although molecular biology and biotechnology have used minicells as laboratory tools for several decades, it is still puzzling that bacteria should produce such costly but potentially nonfunctional structures. Here, we show that bacteria gain a benefit by producing minicells and using them as a mechanism to eliminate damaged or oxidated proteins. The elimination allows the bacteria to tolerate higher levels of stress, such as increasing levels of streptomycin. If this mechanism extends from streptomycin to other antibiotics, minicell production could be an overlooked pathway that bacteria are using to resist antimicrobials.

scholarly journals Dynamics of Solitary Predation by Myxococcus xanthus on Escherichia coli Observed at the Single-Cell Level

2019 ◽  
Vol 86 (3) ◽  
Author(s):  
Wenchao Zhang ◽  
Yan Wang ◽  
Huining Lu ◽  
Qin Liu ◽  
Chuandong Wang ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Single Cell ◽  
Myxococcus Xanthus ◽  
Predatory Behavior ◽  
Single Cell Level ◽  
Cell Level ◽  
Prey Cell ◽  
Content Type ◽  
E Coli ◽  
Tracking Technique

ABSTRACT The predatory behavior of Myxococcus xanthus has attracted extensive attention due to its unique social traits and inherent biological activities. In addition to group hunting, individual M. xanthus cells are able to kill and lyse prey cells; however, there is little understanding of the dynamics of solitary predation. In this study, by employing a bacterial tracking technique, we investigated M. xanthus predatory dynamics on Escherichia coli at the single-cell level. The killing and lysis of E. coli by a single M. xanthus cell was monitored in real time by microscopic observation, and the plasmolysis of prey cells was identified at a relatively early stage of solitary predation. After quantitative characterization of their solitary predatory behavior, M. xanthus cells were found to respond more dramatically to direct contact with live E. coli cells than heat-killed or UV-killed cells, showing slower predator motion and faster lysing of prey. Among the three contact-dependent killing modes classified according to the major subareas of M. xanthus cells in contact with prey, leading pole contact was observed most. After killing the prey, approximately 72% of M. xanthus cells were found to leave without thorough degradation of the lysed prey, and this postresidence behavior is described as a lysis-leave pattern, indicating that solitary predation has low efficiency in terms of prey-cell consumption. Our results provide a detailed description of the single-cell level dynamics of M. xanthus solitary predation from both prey and predator perspectives. IMPORTANCE Bacterial predation plays multiple essential roles in bacterial selection and mortality within microbial ecosystems. In addition to its ecological and evolutionary importance, many potential applications of bacterial predation have been proposed. The myxobacterium Myxococcus xanthus is a well-known predatory member of the soil microbial community. Its predation is commonly considered a collective behavior comparable to a wolf pack attack; however, individual M. xanthus cells are also able to competently lead to the lysis of a prey cell. Using a bacterial tracking technique, we are able to observe and analyze solitary predation by M. xanthus on Escherichia coli at the single-cell level and reveal the dynamics of both predator and prey during the process. The present study will not only provide a comprehensive understanding of M. xanthus solitary predation but also help to explain why M. xanthus often displays multicellular characteristic predatory behaviors in nature, while a single cell is capable of predation.

scholarly journals Metabolic Responses to Polymyxin Treatment in Acinetobacter baumannii ATCC 19606: Integrating Transcriptomics and Metabolomics with Genome-Scale Metabolic Modeling

mSystems ◽  
2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Yan Zhu ◽  
Jinxin Zhao ◽  
Mohd Hafidz Mahamad Maifiah ◽  
Tony Velkov ◽  
Falk Schreiber ◽  
...  
Keyword(s):  
Acinetobacter Baumannii ◽  
Metabolic Modeling ◽  
Metabolic Model ◽  
Metabolic Responses ◽  
Metabolomics Data ◽  
Gram Negative ◽  
Content Type ◽  
Integrative Modeling ◽  
Line Therapy ◽  
Genome Scale

ABSTRACT Multidrug-resistant (MDR) Acinetobacter baumannii has emerged as a very problematic pathogen over the past decades, with a high incidence in nosocomial infections. Discovered in the late 1940s but abandoned in the 1970s, polymyxins (i.e., polymyxin B and colistin) have been revived as the last-line therapy against Gram-negative “superbugs,” including MDR A. baumannii. Worryingly, resistance to polymyxins in A. baumannii has been increasingly reported, urging the development of novel antimicrobial therapies to rescue this last-line class of antibiotics. In the present study, we integrated genome-scale metabolic modeling with multiomics data to elucidate the mechanisms of cellular responses to colistin treatment in A. baumannii. A genome-scale metabolic model, iATCC19606, was constructed for strain ATCC 19606 based on the literature and genome annotation, containing 897 genes, 1,270 reactions, and 1,180 metabolites. After extensive curation, prediction of growth on 190 carbon sources using iATCC19606 achieved an overall accuracy of 84.3% compared to Biolog experimental results. Prediction of gene essentiality reached a high accuracy of 86.1% and 82.7% compared to two transposon mutant libraries of AB5075 and ATCC 17978, respectively. Further integrative modeling with our correlative transcriptomics and metabolomics data deciphered the complex regulation on metabolic responses to colistin treatment, including (i) upregulated fluxes through gluconeogenesis, the pentose phosphate pathway, and amino acid and nucleotide biosynthesis; (ii) downregulated TCA cycle and peptidoglycan and lipopolysaccharide biogenesis; and (iii) altered fluxes over respiratory chain. Our results elucidated the interplay of multiple metabolic pathways under colistin treatment in A. baumannii and provide key mechanistic insights into optimizing polymyxin combination therapy. IMPORTANCE Combating antimicrobial resistance has been highlighted as a critical global health priority. Due to the drying drug discovery pipeline, polymyxins have been employed as the last-line therapy against Gram-negative “superbugs”; however, the detailed mechanisms of antibacterial killing remain largely unclear, hampering the improvement of polymyxin therapy. Our integrative modeling using the constructed genome-scale metabolic model iATCC19606 and the correlative multiomics data provide the fundamental understanding of the complex metabolic responses to polymyxin treatment in A. baumannii at the systems level. The model iATCC19606 may have a significant potential in antimicrobial systems pharmacology research in A. baumannii.

scholarly journals The Polyamine Spermidine Modulates the Production of the Bacterial Genotoxin Colibactin

mSphere ◽  
2019 ◽  
Vol 4 (5) ◽  
Author(s):  
Camille V. Chagneau ◽  
Christophe Garcie ◽  
Nadège Bossuet-Greif ◽  
Sophie Tronnet ◽  
Alexander O. Brachmann ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Escherichia Coli ◽  
Colorectal Carcinogenesis ◽  
Eukaryotic Cells ◽  
Cancer Tissue ◽  
Dna Double Strand Breaks ◽  
Content Type ◽  
E Coli ◽  
Genotoxic Activity ◽  
New Perspective

ABSTRACT Colibactin is a polyketide/nonribosomal peptide produced by Escherichia coli strains that harbor the pks island. This toxin induces DNA double-strand breaks and DNA interstrand cross-links in infected eukaryotic cells. Colibactin-producing strains are found associated with colorectal cancer biopsy specimens and promote intestinal tumor progression in various murine models. Polyamines are small polycationic molecules produced by both microorganisms and eukaryotic cells. Their levels are increased in malignancies, where they contribute to disease progression and metastasis. In this study, we demonstrated that the endogenous spermidine synthase SpeE is required for full genotoxic activity of colibactin-producing E. coli. Supplying spermidine in a ΔspeE pks+ E. coli strain restored genotoxic activity. Spermidine is involved in the autotoxicity linked to colibactin and is required for direct damaging activity on DNA. The production of the colibactin prodrug motif is impaired in ΔspeE mutants. Therefore, we demonstrated that spermidine has a direct impact on colibactin synthesis. IMPORTANCE Colibactin-producing Escherichia coli strains are associated with cancerous and precancerous colorectal tissues and are suspected of promoting colorectal carcinogenesis. In this study, we describe a new interplay between the synthesis of the genotoxin colibactin and the polyamine spermidine. Polyamines are highly abundant in cancer tissue and are associated with cell proliferation. The need for spermidine in genotoxic activity provides a new perspective on the role of these metabolites in the pathogenicity of colibactin-producing E. coli strains in colorectal cancer.

scholarly journals Tailoring a Global Iron Regulon to a Uropathogen

mBio ◽  
2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Rajdeep Banerjee ◽  
Erin Weisenhorn ◽  
Kevin J. Schwartz ◽  
Kevin S. Myers ◽  
Jeremy D. Glasner ◽  
...  
Keyword(s):  
Amino Acids ◽  
Urinary Tract ◽  
Amino Acid ◽  
Regulatory Network ◽  
Iron Homeostasis ◽  
Iron Limitation ◽  
Content Type ◽  
E Coli ◽  
General Stress ◽  
K 12

ABSTRACT Pathogenicity islands and plasmids bear genes for pathogenesis of various Escherichia coli pathotypes. Although there is a basic understanding of the contribution of these virulence factors to disease, less is known about variation in regulatory networks in determining disease phenotypes. Here, we dissected a regulatory network directed by the conserved iron homeostasis regulator, ferric uptake regulator (Fur), in uropathogenic E. coli (UPEC) strain CFT073. Comparing anaerobic genome-scale Fur DNA binding with Fur-dependent transcript expression and protein levels of the uropathogen to that of commensal E. coli K-12 strain MG1655 showed that the Fur regulon of the core genome is conserved but also includes genes within the pathogenicity/genetic islands. Unexpectedly, regulons indicative of amino acid limitation and the general stress response were also indirectly activated in the uropathogen fur mutant, suggesting that induction of the Fur regulon increases amino acid demand. Using RpoS levels as a proxy, addition of amino acids mitigated the stress. In addition, iron chelation increased RpoS to the same levels as in the fur mutant. The increased amino acid demand of the fur mutant or iron chelated cells was exacerbated by aerobic conditions, which could be partly explained by the O2-dependent synthesis of the siderophore aerobactin, encoded by an operon within a pathogenicity island. Taken together, these data suggest that in the iron-poor environment of the urinary tract, amino acid availability could play a role in the proliferation of this uropathogen, particularly if there is sufficient O2 to produce aerobactin. IMPORTANCE Host iron restriction is a common mechanism for limiting the growth of pathogens. We compared the regulatory network controlled by Fur in uropathogenic E. coli (UPEC) to that of nonpathogenic E. coli K-12 to uncover strategies that pathogenic bacteria use to overcome iron limitation. Although iron homeostasis functions were regulated by Fur in the uropathogen as expected, a surprising finding was the activation of the stringent and general stress responses in the uropathogen fur mutant, which was rescued by amino acid addition. This coordinated global response could be important in controlling growth and survival under nutrient-limiting conditions and during transitions from the nutrient-rich environment of the lower gastrointestinal (GI) tract to the more restrictive environment of the urinary tract. The coupling of the response of iron limitation to increased demand for amino acids could be a critical attribute that sets UPEC apart from other E. coli pathotypes.

scholarly journals Isolation of a Gene Responsible for the Oxidation oftrans-Anethole topara-Anisaldehyde by Pseudomonas putida JYR-1 and Its Expression in Escherichia coli

2012 ◽  
Vol 78 (15) ◽  
pp. 5238-5246 ◽  
Author(s):  
Dongfei Han ◽  
Ji-Young Ryu ◽  
Robert A. Kanaly ◽  
Hor-Gil Hur
Keyword(s):  
Escherichia Coli ◽  
Pseudomonas Putida ◽  
Hypothetical Protein ◽  
Aldehyde Group ◽  
Agrobacterium Vitis ◽  
T7 Promoter ◽  
Content Type ◽  
E Coli ◽  
Cell Extracts ◽  
Isoeugenol Monooxygenase

ABSTRACTA plasmid, pTA163, inEscherichia colicontained an approximately 34-kb gene fragment fromPseudomonas putidaJYR-1 that included the genes responsible for the metabolism oftrans-anethole to protocatechuic acid. Three Tn5-disrupted open reading frame 10 (ORF 10) mutants of plasmid pTA163 lost their abilities to catalyzetrans-anethole. Heterologously expressed ORF 10 (1,047 nucleotides [nt]) under a T7 promoter inE. colicatalyzed oxidative cleavage of a propenyl group oftrans-anethole to an aldehyde group, resulting in the production ofpara-anisaldehyde, and this gene was designatedtao(trans-anetholeoxygenase). The deduced amino acid sequence of TAO had the highest identity (34%) to a hypothetical protein ofAgrobacterium vitisS4 and likely contained a flavin-binding site. Preferred incorporation of an oxygen molecule from water intop-anisaldehyde using18O-labeling experiments indicated stereo preference of TAO for hydrolysis of the epoxide group. Interestingly, unlike the narrow substrate range of isoeugenol monooxygenase fromPseudomonas putidaIE27 andPseudomonas nitroreducensJin1, TAO fromP. putidaJYR-1 catalyzed isoeugenol,O-methyl isoeugenol, and isosafrole, all of which contain the 2-propenyl functional group on the aromatic ring structure. Addition of NAD(P)H to the ultrafiltered cell extracts ofE. coli(pTA163) increased the activity of TAO. Due to the relaxed substrate range of TAO, it may be utilized for the production of various fragrance compounds from plant phenylpropanoids in the future.

scholarly journals Evaluation of a Genome-ScaleIn SilicoMetabolic Model for Geobacter metallireducens by Using Proteomic Data from a Field Biostimulation Experiment

2012 ◽  
Vol 78 (24) ◽  
pp. 8735-8742 ◽  
Author(s):  
Yilin Fang ◽  
Michael J. Wilkins ◽  
Steven B. Yabusaki ◽  
Mary S. Lipton ◽  
Philip E. Long
Keyword(s):  
Proteomic Analysis ◽  
In Silico ◽  
Field Experiments ◽  
Metabolic Model ◽  
Geobacter Metallireducens ◽  
Content Type ◽  
Proteomic Data ◽  
Subsurface Environment ◽  
A Genome ◽  
Genome Scale

ABSTRACTAccurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within anin silicomodel using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model ofGeobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-basedin silicomodelof G. metallireducensrelates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637G. metallireducensproteins detected during the 2008 experiment were associated with specific metabolic reactions in thein silicomodel. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through thein silicomodel reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in thein silicomodel that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

scholarly journals Metabolic Modeling of Pectobacterium parmentieri SCC3193 Provides Insights into Metabolic Pathways of Plant Pathogenic Bacteria

2019 ◽  
Vol 7 (4) ◽  
pp. 101 ◽  
Author(s):  
Sabina Zoledowska ◽  
Luana Presta ◽  
Marco Fondi ◽  
Francesca Decorosi ◽  
Luciana Giovannetti ◽  
...  
Keyword(s):  
In Silico ◽  
Pathogenic Bacteria ◽  
Metabolic Modeling ◽  
Metabolic Model ◽  
Metabolic Adaptation ◽  
Ecological Niches ◽  
Plant Colonization ◽  
Phenotypic Data ◽  
Plant Pathogenic Bacteria ◽  
Metabolic Versatility

Understanding plant–microbe interactions is crucial for improving plants’ productivity and protection. Constraint-based metabolic modeling is one of the possible ways to investigate the bacterial adaptation to different ecological niches and may give insights into the metabolic versatility of plant pathogenic bacteria. We reconstructed a raw metabolic model of the emerging plant pathogenic bacterium Pectobacterium parmentieri SCC3193 with the use of KBase. The model was curated by using inParanoind and phenotypic data generated with the use of the OmniLog system. Metabolic modeling was performed through COBRApy Toolbox v. 0.10.1. The curated metabolic model of P. parmentieri SCC3193 is highly reliable, as in silico obtained results overlapped up to 91% with experimental data on carbon utilization phenotypes. By mean of flux balance analysis (FBA), we predicted the metabolic adaptation of P. parmentieri SCC3193 to two different ecological niches, relevant for the persistence and plant colonization by this bacterium: soil and the rhizosphere. We performed in silico gene deletions to predict the set of essential core genes for this bacterium to grow in such environments. We anticipate that our metabolic model will be a valuable element for defining a set of metabolic targets to control infection and spreading of this plant pathogen.

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