Substrate and electron donor limitation induce phenotypic heterogeneity in different metabolic activities in a green sulphur bacterium

Zimmermann, M.; Escrig, Stéphane; Lavik, Gaute; Kuypers, Marcel M. M.; Meibom, Anders; Ackermann, Martin; Schreiber, Frank

doi:10.1111/1758-2229.12616

Cited by 19 publications

(19 citation statements)

References 33 publications

(50 reference statements)

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“…Individual-level variation in traits is a feature common to all species, including clonal and microbial populations (Ackermann 2015). Limitation and fluctuations in resources are important drivers of intraspecific phenotypic heterogeneity, which favours population fitness (Ackermann 2015;Schreiber et al 2016;Zimmermann et al 2018). For example, NH 4 + limitation can trigger an increase in phenotypic heterogeneity in the N 2 -fixing bacterium Klebsiella oxytoca, which proves beneficial under resource fluctuations (Schreiber et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Light limitation increases multidimensional trait evenness in phytoplankton populations

et al. 2019

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Individual-level variation arising from responses to environmental gradients influences population and community dynamics. How such responses empirically relate to the mechanisms that govern species coexistence is, however, poorly understood. Previous results from lake phytoplankton communities suggested that the evenness of organismal traits in multiple dimensions increases with resource limitation, possibly due to resource partitioning at the individual level. Here we experimentally tested the emergence of this pattern by growing two phytoplankton species (Pseudokirchneriella subcapitata and Microcystis aeruginosa) under a gradient of light intensity, in monoculture and jointly. Under low light (resource) conditions, the populations diversified into a wide range of phenotypes, which were evenly distributed in multidimensional trait space (defined by four pigment-related trait dimensions), consistent with the observed field pattern. Our interpretation is that under conditions of light limitation, individual phytoplankton cells alter photosynthetic traits to reduce overlap in light acquisition, acquiring unexploited resources and thereby likely maximizing individual success. Our results provide prime experimental evidence that resource limitation increases the evenness of conspecific and heterospecific microbial phenotypes along trait axes, advancing our understanding of trait-based coexistence.

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Section: Introductionmentioning

confidence: 99%

Light limitation increases multidimensional trait evenness in phytoplankton populations

et al. 2019

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“…erefore, it tends to converge to the true modality as the number of samples increase. It is also reliable and stable and thus widely used for the assessment of unimodality or multimodality [11,12,14,26].…”

Section: Hartigan's Dip Statistic With Bimodality Coefficientmentioning

confidence: 99%

“…However, HDS also has some limitations in estimating modality according to significance level; hence, an advanced HDS method must be developed. e modality assessment method have been recently applied into various research fields; the BC has been employed in the psychiatry science, public opinion, chemistry, and physics [11,13,[20][21][22], and HDS has been implemented in the brain science, biological science, microbiology, and ecology [23][24][25][26]. Even though there are many applications with multimodality in the engineering fields, the methods of evaluating the multimodality have been rarely applied, and graphical methods such as histograms have been simply employed [3][4][5][6][7][8][9][27][28][29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Development of Hartigan’s Dip Statistic with Bimodality Coefficient to Assess Multimodality of Distributions

Kang

Noh

2019

Mathematical Problems in Engineering

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In general, although some random variables such as wind speed, temperature, and load are known to have multimodal distributions, input or output random variables are considered to follow unimodal distributions without assessing the unimodality or multimodality of distributions from samples. In uncertainty analysis, estimating unimodal distribution as multimodal distribution or vice versa can lead to erroneous analysis results. Thus, whether a distribution is unimodal or multimodal must be assessed before the estimation of distributions. In this paper, the bimodality coefficient (BC) and Hartigan’s dip statistic (HDS), which are representative methods for assessing multimodality, are introduced and compared. Then, a combined HDS with BC method is proposed. The proposed method has the advantages of both BC and HDS by using the skewness and kurtosis of samples as well as the dip statistic through a link function between the BC values in BC and significance level in HDS. To verify the performance of the proposed method, statistical simulation tests were conducted to evaluate the multimodality for various unimodal, bimodal, and trimodal models. The implementation of the proposed method to real engineering data is shown through case studies. The results demonstrate that the proposed method is more accurate, robust, and reliable than the BC and original HDS alone.

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“…Studies applying SIP-nanoSIMS have been focused on assimilation activity in the frame of specific metabolic functions, considering exclusively the heterogeneity in terms of isotopic enrichment at the singlecell level. Metabolic heterogeneity in monoclonal population has been shown to increase under limitation of nutrients and/or electron donors (Zimmermann et al, 2015(Zimmermann et al, , 2018Schreiber et al, 2016); nutritional and temperature upshifts as well as carbon-source competition enhance metabolic specialization among monoclonal cells (Sheik et al, 2015;Nikolic et al, 2017;Simşek and Kim, 2018). The above-mentioned studies have quantified the uptake of isotope-labeled substrates normalizing it with output from bulk measurements and applying empirical assimilation expressions.…”

Section: Introductionmentioning

confidence: 99%

Quantitation and Comparison of Phenotypic Heterogeneity Among Single Cells of Monoclonal Microbial Populations

Calabrese

Voloshynovska²,

Musat

et al. 2019

Front. Microbiol.

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Phenotypic heterogeneity within microbial populations arises even when the cells are exposed to putatively constant and homogeneous conditions. The outcome of this phenomenon can affect the whole function of the population, resulting in, for example, new "adapted" metabolic strategies and impacting its fitness at given environmental conditions. Accounting for phenotypic heterogeneity becomes thus necessary, due to its relevance in medical and applied microbiology as well as in environmental processes. Still, a comprehensive evaluation of this phenomenon requires a common and unique method of quantitation, which allows for the comparison between different studies carried out with different approaches. Consequently, in this study, two widely applicable indices for quantitation of heterogeneity were developed. The heterogeneity coefficient (HC) is valid when the population follows unimodal activity, while the differentiation tendency index (DTI) accounts for heterogeneity implying outbreak of subpopulations and multimodal activity. We demonstrated the applicability of HC and DTI for heterogeneity quantitation on stable isotope probing with nanoscale secondary ion mass spectrometry (SIP-nanoSIMS), flow cytometry, and optical microscopy datasets. The HC was found to provide a more accurate and precise measure of heterogeneity, being at the same time consistent with the coefficient of variation (CV) applied so far. The DTI is able to describe the differentiation in single-cell activity within monoclonal populations resolving subpopulations with low cell abundance, individual cells with similar phenotypic features (e.g., isotopic content close to natural abundance, as detected with nanoSIMS). The developed quantitation approach allows for a better understanding on the impact and the implications of phenotypic heterogeneity in environmental, medical and applied microbiology, microbial ecology, cell biology, and biotechnology.

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Substrate and electron donor limitation induce phenotypic heterogeneity in different metabolic activities in a green sulphur bacterium

Cited by 19 publications

References 33 publications

Light limitation increases multidimensional trait evenness in phytoplankton populations

Light limitation increases multidimensional trait evenness in phytoplankton populations

Development of Hartigan’s Dip Statistic with Bimodality Coefficient to Assess Multimodality of Distributions

Quantitation and Comparison of Phenotypic Heterogeneity Among Single Cells of Monoclonal Microbial Populations

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