Monitoring of population dynamics of <i><scp>C</scp>orynebacterium glutamicum</i> by multiparameter flow cytometry

Neumeyer, Andrea; Hübschmann, Thomas; Müller, Susann; Frunzke, Julia

doi:10.1111/1751-7915.12018

Cited by 38 publications

(36 citation statements)

References 41 publications

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“…4) showing a high MP in all samples. It has been implied previously for that MP decreases in a cell population during the stationary phase (Neumeyer et al, 2013), but glucose availability was not clearly identified as source for the MP shift. 4A).…”

Section: Impact Of Compartment Specific Glucose Availability On Cell mentioning

confidence: 79%

“…The DiOC 2 (3) staining was performed as previously described (Neumeyer et al, 2013). The DiOC 2 (3) staining was performed as previously described (Neumeyer et al, 2013).…”

Section: Flow Cytometrymentioning

confidence: 99%

“…In a first experiment, the membrane potential (MP) was used to analyze the compartment specific metabolic state of the microbial population (Neumeyer et al, 2013). The used carbocyanine dye (3,3 0 -diethyloxacarbocyanine iodide; DiOC 2 ) exhibits green fluorescence shifting toward red emission due to self-association correlating with the amount of up-taken DiOC 2 in dependency of the MP.…”

Section: Impact Of Compartment Specific Glucose Availability On Cell mentioning

confidence: 99%

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Metabolic profile of 1,5‐diaminopentane producing Corynebacterium glutamicum under scale‐down conditions: Blueprint for robustness to bioreactor inhomogeneities

Limberg

Schulte

Aryani

et al. 2016

Biotech & Bioengineering

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Performance losses during scale-up are described since decades, but are still one of the major obstacles for industrial bioprocess development. Consequently, robustness to inhomogeneous cultivation environments is an important quality of industrial production organisms. Especially, Corynebacterium glutamicum was proven to have an outstanding resistance against rapid changes of oxygen and substrate availability as occurring in industrial scale bioreactors. This study focuses on the identification of metabolic key mechanisms for this robustness to get a deeper insight and provide future targets for process orientated strain development. A 1,5-diaminopentane producing C. glutamicum strain was cultivated in a two compartment scale-down device to create short-term environmental changes simulating industrial scale cultivation conditions. Using multi omics based methods, it is shown, that central metabolism is flexibly rearranged under short-term oxygen depletion and carbon source excess to overcome shortage in NAD recycling. In order to balance the redox state, key enzymes for the non-oxygen dependent fermentative NAD regeneration were significantly up-regulated while parts of non-essential pathways were down-regulated. The transfer of the cells back into the well aerated zones with low substrate concentration triggers an additional upregulation of genes for the re-assimilation of previously formed side products, showing L-lactate forming and utilizing reactions being active at the same time. Especially L-lactate as reversible and flexible external buffer for carbon and redox equivalents puts C. glutamicum in a robust position to deal with inhomogeneity in large scale processes. Biotechnol. Bioeng. 2017;114: 560-575. © 2016 Wiley Periodicals, Inc.

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Section: Impact Of Compartment Specific Glucose Availability On Cell mentioning

confidence: 79%

“…The DiOC 2 (3) staining was performed as previously described (Neumeyer et al, 2013). The DiOC 2 (3) staining was performed as previously described (Neumeyer et al, 2013).…”

Section: Flow Cytometrymentioning

confidence: 99%

Section: Impact Of Compartment Specific Glucose Availability On Cell mentioning

confidence: 99%

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Metabolic profile of 1,5‐diaminopentane producing Corynebacterium glutamicum under scale‐down conditions: Blueprint for robustness to bioreactor inhomogeneities

Limberg

Schulte

Aryani

et al. 2016

Biotech & Bioengineering

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“…Besides the use of fluorescence proteins, the use of the fluorescing dyes Syto 9, propidium iodide, and 3,3=-diethyloxacarbocyanine iodide [DiOC2(3)] proved to be useful for the identification of subpopulations with reduced viability and membrane potential within C. glutamicum populations (84). Other studies employed in situ reverse transcription-PCRs at a single-cell level in combination with a single-cell beta-galactosidase assay to monitor heterogeneous expression of the lac operon in Salmonella enterica serovar Typhimurium (85).…”

Section: Measuring Phenotypic Heterogeneity At a Single-cell Levelmentioning

confidence: 99%

Phenotypic Heterogeneity, a Phenomenon That May Explain Why Quorum Sensing Does Not Always Result in Truly Homogenous Cell Behavior

Grote

Krysciak

Streit

2015

Appl Environ Microbiol

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Phenotypic heterogeneity describes the occurrence of "nonconformist" cells within an isogenic population. The nonconformists show an expression profile partially different from that of the remainder of the population. Phenotypic heterogeneity affects many aspects of the different bacterial lifestyles, and it is assumed that it increases bacterial fitness and the chances for survival of the whole population or smaller subpopulations in unfavorable environments. Well-known examples for phenotypic heterogeneity have been associated with antibiotic resistance and frequently occurring persister cells. Other examples include heterogeneous behavior within biofilms, DNA uptake and bacterial competence, motility (i.e., the synthesis of additional flagella), onset of spore formation, lysis of phages within a small subpopulation, and others. Interestingly, phenotypic heterogeneity was recently also observed with respect to quorum-sensing (QS)-dependent processes, and the expression of autoinducer (AI) synthase genes and other QS-dependent genes was found to be highly heterogeneous at a single-cell level. This phenomenon was observed in several Gram-negative bacteria affiliated with the genera Vibrio, Dinoroseobacter, Pseudomonas, Sinorhizobium, and Mesorhizobium. A similar observation was made for the Gram-positive bacterium Listeria monocytogenes. Since AI molecules have historically been thought to be the keys to homogeneous behavior within isogenic populations, the observation of heterogeneous expression is quite intriguing and adds a new level of complexity to the QS-dependent regulatory networks. All together, the many examples of phenotypic heterogeneity imply that we may have to partially revise the concept of homogeneous and coordinated gene expression in isogenic bacterial populations. Bacteria have evolved multiple strategies to cope with rapid and frequent changes in their environment. These survival strategies may include spore formation, increased production of polysaccharides, biofilm formation or escape from biofilms (i.e., switching from a motile into a sessile form and vice versa), altered motility, change of metabolic capabilities, response to antibiotics, and many more. In general, these switches are initiated by environmental or bacterially produced signals that are perceived by a diverse array of regulators and delegated into the corresponding regulatory networks. This presumably results in altered transcription levels of different genes or operons, which eventually causes a change in the phenotype and a response to the environmental stimulus. Within this context, it is generally assumed that the majority of a population will undergo this switch within a short time period and that the population will show a mostly homogeneous expression profile. During the last decade, it became, however, evident that a certain fraction of cells in an isogenic population behaves differently from the others, even though the environment may not have changed significantly. The term "phenotypic heterogeneity" thereby descr...

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“…Recent studies using multiparameter flow cytometry revealed phenotypic heterogeneity in terms of viability, membrane potential and growth activity of C. glutamicum wild type cells grown in shake flasks [17]. However, population heterogeneity during production processes has not been studied in detail for this species, yet.…”

Section: Introductionmentioning

confidence: 99%

Application of a Genetically Encoded Biosensor for Live Cell Imaging of L-Valine Production in Pyruvate Dehydrogenase Complex-Deficient Corynebacterium glutamicum Strains

et al. 2014

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The majority of biotechnologically relevant metabolites do not impart a conspicuous phenotype to the producing cell. Consequently, the analysis of microbial metabolite production is still dominated by bulk techniques, which may obscure significant variation at the single-cell level. In this study, we have applied the recently developed Lrp-biosensor for monitoring of amino acid production in single cells of gradually engineered L-valine producing Corynebacterium glutamicum strains based on the pyruvate dehydrogenase complex-deficient (PDHC) strain C. glutamicum ΔaceE. Online monitoring of the sensor output (eYFP fluorescence) during batch cultivation proved the sensor's suitability for visualizing different production levels. In the following, we conducted live cell imaging studies on C. glutamicum sensor strains using microfluidic chip devices. As expected, the sensor output was higher in microcolonies of high-yield producers in comparison to the basic strain C. glutamicum ΔaceE. Microfluidic cultivation in minimal medium revealed a typical Gaussian distribution of single cell fluorescence during the production phase. Remarkably, low amounts of complex nutrients completely changed the observed phenotypic pattern of all strains, resulting in a phenotypic split of the population. Whereas some cells stopped growing and initiated L-valine production, others continued to grow or showed a delayed transition to production. Depending on the cultivation conditions, a considerable fraction of non-fluorescent cells was observed, suggesting a loss of metabolic activity. These studies demonstrate that genetically encoded biosensors are a valuable tool for monitoring single cell productivity and to study the phenotypic pattern of microbial production strains.

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Monitoring of population dynamics of Corynebacterium glutamicum by multiparameter flow cytometry

Cited by 38 publications

References 41 publications

Metabolic profile of 1,5‐diaminopentane producing Corynebacterium glutamicum under scale‐down conditions: Blueprint for robustness to bioreactor inhomogeneities

Metabolic profile of 1,5‐diaminopentane producing Corynebacterium glutamicum under scale‐down conditions: Blueprint for robustness to bioreactor inhomogeneities

Phenotypic Heterogeneity, a Phenomenon That May Explain Why Quorum Sensing Does Not Always Result in Truly Homogenous Cell Behavior

Application of a Genetically Encoded Biosensor for Live Cell Imaging of L-Valine Production in Pyruvate Dehydrogenase Complex-Deficient Corynebacterium glutamicum Strains

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