Characterization of the metabolic burden on <i>Escherichia coli</i> DH1 cells imposed by the presence of a plasmid containing a gene therapy sequence

Rozkov, Aleksei; Avignone-Rossa, CA; Ertl, PF; Jones, Peter; O'Kennedy, RD; Smith, J. J.; Dale, JW; Bushell, ME

doi:10.1002/bit.20327

Cited by 106 publications

(85 citation statements)

References 24 publications

(24 reference statements)

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“…Similar observations were reported for pWW100, inferring biphenyl metabolism (BPH ϩ ) (18), and pWWO-1, inferring toluene degradation (TOL ϩ ) (19) in P. putida. Metabolic burden related to extra DNA/plasmid replication (20,21) is suggested as a major reason for the growth retardation of plasmid-bearing cells compared to the growth of cured cells (17).…”

Section: Discussionmentioning

confidence: 99%

Genetic (In)stability of 2,6-Dichlorobenzamide Catabolism in Aminobacter sp. Strain MSH1 Biofilms under Carbon Starvation Conditions

Horemans

Raes

Brocatus

et al. 2017

Appl Environ Microbiol

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Aminobacter sp. strain MSH1 grows on and mineralizes the groundwater micropollutant 2,6-dichlorobenzamide (BAM) and is of interest for BAM removal in drinking water treatment plants (DWTPs). The BAM-catabolic genes in MSH1 are located on plasmid pBAM1, carrying bbdA, which encodes the conversion of BAM to 2,6-dichlorobenzoic acid (2,6-DCBA) (BbdA ϩ phenotype), and plasmid pBAM2, carrying gene clusters encoding the conversion of 2,6-DCBA to tricarboxylic acid (TCA) cycle intermediates (Dcba ϩ phenotype). There are indications that MSH1 easily loses its BAM-catabolic phenotype. We obtained evidence that MSH1 rapidly develops a population that lacks the ability to mineralize BAM when grown on nonselective (R2B medium) and semiselective (R2B medium with BAM) media. Lack of mineralization was explained by loss of the Dcba ϩ phenotype and corresponding genes. The ecological significance of this instability for the use of MSH1 for BAM removal in the oligotrophic environment of DWTPs was explored in lab and pilot systems. A higher incidence of BbdA ϩ Dcba Ϫ MSH1 cells was also observed when MSH1 was grown as a biofilm in flow chambers under C and N starvation conditions due to growth on nonselective residual assimilable organic carbon. Similar observations were made in experiments with a pilot sand filter reactor bioaugmented with MSH1. BAM conversion to 2,6-DCBA was not affected by loss of the DCBA-catabolic genes. Our results show that MSH1 is prone to BAM-catabolic instability under the conditions occurring in a DWTP. While conversion of BAM to 2,6-DCBA remains unaffected, BAM mineralization activity is at risk, and monitoring of metabolites is warranted.IMPORTANCE Bioaugmentation of dedicated biofiltration units with bacterial strains that grow on and mineralize micropollutants was suggested as an alternative for treating micropollutant-contaminated water in drinking water treatment plants (DWTPs). Organic-pollutant-catabolic genes in bacteria are often easily lost, especially under nonselective conditions, which affects the bioaugmentation success. In this study, we provide evidence that Aminobacter sp. strain MSH1, which uses the common groundwater micropollutant 2,6-dichlorobenzamide (BAM) as a C source, shows a high frequency of loss of its BAM-mineralizing phenotype due to the loss of genes that convert 2,6-DCBA to Krebs cycle intermediates when nonselective conditions occur. Moreover, we show that catabolic-gene loss also occurs in the oligotrophic environment of DWTPs, where growth of MSH1 depends mainly on the high fluxes of low concentrations of assimilable organic carbon, and hence show the ecological relevance of catabolic instability for using strain MSH1 for BAM removal in DWTPs.

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Section: Discussionmentioning

confidence: 99%

Genetic (In)stability of 2,6-Dichlorobenzamide Catabolism in Aminobacter sp. Strain MSH1 Biofilms under Carbon Starvation Conditions

Horemans

Raes

Brocatus

et al. 2017

Appl Environ Microbiol

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“…The conjugative proficiency requires the expression of set of transmembrane proteins which are known collectively as type IV secretion systems (T4SS; Lawley, Klimke, Gubbins, & Frost, 2003). The presence of conjugative plasmids and the expression of conjugative machinery are detrimental for the host cell fitness (Rozkov et al., 2004), but there is no consensus on the valid ranges of metabolic costs imposed by the conjugative process. Therefore, in this model the short‐term dynamics of two plasmid system P1 and P2 is simulated.…”

Section: Example 3: T4ss Common Poolmentioning

confidence: 99%

Sensitivity analysis of Repast computational ecology models with R/Repast

García

Rodríguez‐Patón

2016

Ecology and Evolution

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Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual‐based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom‐up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in‐silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results.

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“…Besides the above mentioned regulatory aspect, Rozkov et al (2004) note another one that should be taken into consideration when selecting the plasmid stabilizing system. According to these authors, the presence of an antibiotic selection marker imposes a huge metabolic burden on an expression system.…”

Section: Microbial Expression Systems Andmentioning

confidence: 99%

Microbial Expression Systems and Manufacturing from a Market and Economic Perspective

Meyer¹,

Schmidhalter²

2012

Innovations in Biotechnology

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Characterization of the metabolic burden on Escherichia coli DH1 cells imposed by the presence of a plasmid containing a gene therapy sequence

Cited by 106 publications

References 24 publications

Genetic (In)stability of 2,6-Dichlorobenzamide Catabolism in Aminobacter sp. Strain MSH1 Biofilms under Carbon Starvation Conditions

Genetic (In)stability of 2,6-Dichlorobenzamide Catabolism in Aminobacter sp. Strain MSH1 Biofilms under Carbon Starvation Conditions

Sensitivity analysis of Repast computational ecology models with R/Repast

Microbial Expression Systems and Manufacturing from a Market and Economic Perspective

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