Beyond the bulk: disclosing the life of single microbial cells

Rosenthal, Katrin; Oehling, Verena; Dusny, Christian; Schmid, Andreas

doi:10.1093/femsre/fux044

Cited by 43 publications

(32 citation statements)

References 327 publications

(504 reference statements)

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“…The heterogeneity among budding cells was reduced during the growth phase, while it was higher in the lag phase. As recent studies have shown, bet-hedging mechanisms may be the reason for prolonged growth delay periods due to the formation of subpopulations with different phenotypes when cells cope with environmental stress, as it occurs after inoculation [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

Real-time monitoring of the budding index in Saccharomyces cerevisiae batch cultivations with in situ microscopy

Marbà-Ardébol

Emmerich²,

Muthig³

et al. 2018

Microb Cell Fact

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BackgroundThe morphology of yeast cells changes during budding, depending on the growth rate and cultivation conditions. A photo-optical microscope was adapted and used to observe such morphological changes of individual cells directly in the cell suspension. In order to obtain statistically representative samples of the population without the influence of sampling, in situ microscopy (ISM) was applied in the different phases of a Saccharomyces cerevisiae batch cultivation. The real-time measurement was performed by coupling a photo-optical probe to an automated image analysis based on a neural network approach.ResultsAutomatic cell recognition and classification of budding and non-budding cells was conducted successfully. Deviations between automated and manual counting were considerably low. A differentiation of growth activity across all process stages of a batch cultivation in complex media became feasible. An increased homogeneity among the population during the growth phase was well observable. At growth retardation, the portion of smaller cells increased due to a reduced bud formation. The maturation state of the cells was monitored by determining the budding index as a ratio between the number of cells, which were detected with buds and the total number of cells. A linear correlation between the budding index as monitored with ISM and the growth rate was found.ConclusionIt is shown that ISM is a meaningful analytical tool, as the budding index can provide valuable information about the growth activity of a yeast cell, e.g. in seed breeding or during any other cultivation process. The determination of the single-cell size and shape distributions provided information on the morphological heterogeneity among the populations. The ability to track changes in cell morphology directly on line enables new perspectives for monitoring and control, both in process development and on a production scale.Electronic supplementary materialThe online version of this article (10.1186/s12934-018-0922-y) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Real-time monitoring of the budding index in Saccharomyces cerevisiae batch cultivations with in situ microscopy

Marbà-Ardébol

Emmerich²,

Muthig³

et al. 2018

Microb Cell Fact

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“…The value of single-cell analysis has long been appreciated for different biological systems, ranging from microorganisms [ 48 ] to human cells [ 49 , 50 , 51 , 52 ]. There have been excellent reviews on the clinical implications of tumor heterogeneity and methodologies for its study at the single cell level (e.g., [ 50 ]).…”

Section: Discussionmentioning

confidence: 99%

Viability Assessment Following Anticancer Treatment Requires Single-Cell Visualization

Mirzayans

Andrais

Murray

2018

Cancers

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A subset of cells within solid tumors become highly enlarged and enter a state of dormancy (sustained proliferation arrest) in response to anticancer treatment. Although dormant cancer cells might be scored as “dead” in conventional preclinical assays, they remain viable, secrete growth-promoting factors, and can give rise to progeny with stem cell-like properties. Furthermore, cancer cells exhibiting features of apoptosis (e.g., caspase-3 activation) following genotoxic stress can undergo a reversal process called anastasis and survive. Consistent with these observations, single-cell analysis of adherent cultures (solid tumor-derived cell lines with differing p53 status) has demonstrated that virtually all cells—irrespective of their size and morphology—that remain adherent to the culture dish for a long time (weeks) after treatment with anticancer agents exhibit the ability to metabolize 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl- tetrazolium bromide (MTT). The purpose of this commentary is to briefly review these findings and discuss the significance of single-cell (versus population averaged) observation methods for assessment of cancer cell viability and metabolic activity.

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“…Microfluidic parallelization and single-cell monitoring allows the measurement and averaging of parameters on hundreds of individual cells, compared to measuring parameters of a whole cell population. New insights can be obtained by observing single cells, such as the monitoring of certain classes of proteins, using fluorescently tagged proteins [102,103] and give information about the cell-to-cell variation in a heterogeneous microbial population [104][105][106]. Automation of microfluidic cell culture systems also leads to standardized manipulation and monitoring, which allows the perfect timing of protocols to characterize dynamic processes at high temporal resolution to be performed [94].…”

Section: Microfluidic High-throughput Antifungal Drug Discoverymentioning

confidence: 99%

Micro- and Nanoscale Approaches in Antifungal Drug Discovery

Willaert

2018

Fermentation

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Clinical needs for novel antifungal agents have increased due to the increase of people with a compromised immune system, the appearance of resistant fungi, and infections by unusual yeasts. The search for new molecular targets for antifungals has generated considerable research, especially using modern omics methods (genomics, genome-wide collections of mutants, and proteomics) and bioinformatics approaches. Recently, micro-and nanoscale approaches have been introduced in antifungal drug discovery. Microfluidic platforms have been developed, since they have a number of advantages compared to traditional multiwell-plate screening, such as low reagent consumption, the manipulation of a large number of cells simultaneously and independently, and ease of integrating numerous analytical standard operations and large-scale integration. Automated high-throughput antifungal drug screening is achievable by massive parallel processing. Various microfluidic antimicrobial susceptibility testing (AST) methods have been developed, since they can provide the result in a short time-frame, which is necessary for personalized medicine in the clinic. New nanosensors, based on detecting the nanomotions of cells, have been developed to further decrease the time to test antifungal susceptibility to a few minutes. Finally, nanoparticles (especially, silver nanoparticles) that demonstrated antifungal activity are reviewed.Fermentation 2018, 4, 43 2 of 23 antifungal classes have been reported since 2006 [7]. Current antifungal drugs show some limitations: Amphothericin B (a polyene antibiotic) displays a considerable toxicity and undesirable side effects [8,9], issues with pharmacokinetic properties (such as a short half-life of echinocandins) and activity spectrum, a small number of targets [10,11], and they can interact with other drugs, such as chemotherapy agents and immunosuppressants [12,13]. The last approved antifungal (i.e., anidulafungin) by the European Medicines Agency and the Food and Drug Administration (FDA) dates back to 2006 [14]. There is an urgent need for safer and more effective antifungal drugs. Multiple types of antifungal compounds are in clinical development and these new agents have been recently reviewed [15][16][17].Over the last 20 years, several approaches to antifungal discovery have been explored. The traditional approach seeks, first, to identify active compounds from large compound libraries using a panel of fungal pathogens in standardised assays when possible. In the genetic, genomic, or bioinformatics approach, the objective is, initially, to identify broadly represented targets in fungal pathogens and non-pathogens [18]. In this "target-centric" genomic approach, up-front genetic, bioinformatics, and biochemical target prioritisation is performed and, subsequently, an in vitro-based screening of individual targets is achieved. However, an exceedingly high rate of failure has been observed when applying this approach [19]. Additionally, not all bioactive compounds act through a target-specific mechan...

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Beyond the bulk: disclosing the life of single microbial cells

Cited by 43 publications

References 327 publications

Real-time monitoring of the budding index in Saccharomyces cerevisiae batch cultivations with in situ microscopy

Real-time monitoring of the budding index in Saccharomyces cerevisiae batch cultivations with in situ microscopy

Viability Assessment Following Anticancer Treatment Requires Single-Cell Visualization

Micro- and Nanoscale Approaches in Antifungal Drug Discovery

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