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Microorganisms perform multiple metabolic functions that shape the global cycling of elements, health and disease of their host organisms, and biotechnological processes. The rates, at which different metabolic activities are performed by individual cells, can vary between genetically identical cells within clonal populations. While the molecular mechanisms that result in such metabolic heterogeneity have attracted considerable interest, the environmental conditions that shape heterogeneity and its consequences have received attention only in recent years. Here, we review the environmental drivers that lead to metabolic heterogeneity with a focus on nutrient limitation, temporal fluctuations and spatial structure, and the functional consequences of such heterogeneity. We highlight studies using single-cell methods that allow direct investigation of metabolic heterogeneity and discuss the relevance of metabolic heterogeneity in complex microbial communities.
A fundamental question in ecology is how biodiversity affects ecosystem function. Biodiversity is commonly estimated based on genetic variation. We investigated a new approach that defines and measures biodiversity in complex microbial communities. We used the variation in multiple functionally-relevant, phenotypic traits measured in parallel in single cells as a metric for microbial phenotypic diversity. We studied phenotypic diversity and ecosystem functioning throughout different photosynthetic layers dominated by divergent microbial communities in the gradient of Lago di Cadagno. We determined genetic diversity by 16S and 18S amplicon sequencing and bulk ecosystem functioning (photosynthesis). In addition, we determined phenotypic diversity using single-cell technologies such as nanometer-scale secondary ion mass spectrometry (NanoSIMS) correlated with confocal laser scanning microscopy (CLSM) and scanning flow-cytometry. We measured functional trait variation between individuals in 13CO2 fixation, 15NH4+ uptake, and variation in physio-morphological cell traits, such as cell size, shape, and auto-fluorescence for various pigments related to photosynthesis. We used the distances between individuals in a multidimensional trait space to derive phenotypic trait-based diversity indices, such as trait richness, trait evenness, and trait divergence. We find that phenotypic trait divergence associates with ecosystem functioning, whereas genetic diversity does not. Including activity-based, single-cell phenotypic measurements with NanoSIMS provided an additional accuracy to the trait-based diversity assessment and allowed us to formulate hypotheses on the mechanisms that shape the correlation between phenotypic diversity and eco-system function. Together, our results show that phenotypic diversity is a meaningful concept to measure microbial biodiversity and associate it with ecosystem functioning.
A fundamental question in ecology is how biodiversity affects ecosystem function. Biodiversity is commonly estimated based on genetic variation. We investigated a new approach that defines and measures biodiversity in complex microbial communities. We used the variation in multiple functionally-relevant, phenotypic traits measured in parallel in single cells as a metric for microbial phenotypic diversity. We studied phenotypic diversity and ecosystem functioning throughout different photosynthetic layers dominated by divergent microbial communities in the gradient of Lago di Cadagno. We determined genetic diversity by 16S and 18S amplicon sequencing and bulk ecosystem functioning (photosynthesis). In addition, we determined phenotypic diversity using single-cell technologies such as nanometer-scale secondary ion mass spectrometry (NanoSIMS) correlated with confocal laser scanning microscopy (CLSM) and scanning flow-cytometry. We measured functional trait variation between individuals in 13CO2 fixation, 15NH4+ uptake, and variation in physio-morphological cell traits, such as cell size, shape, and auto-fluorescence for various pigments related to photosynthesis. We used the distances between individuals in a multidimensional trait space to derive phenotypic trait-based diversity indices, such as trait richness, trait evenness, and trait divergence. We find that phenotypic trait divergence associates with ecosystem functioning, whereas genetic diversity does not. Including activity-based, single-cell phenotypic measurements with NanoSIMS provided an additional accuracy to the trait-based diversity assessment and allowed us to formulate hypotheses on the mechanisms that shape the correlation between phenotypic diversity and eco-system function. Together, our results show that phenotypic diversity is a meaningful concept to measure microbial biodiversity and associate it with ecosystem functioning.
Porous materials play an important role in several fields of technology, especially for energy applications like photovoltaics, electrolysis or batteries. The activity of porous films is affected by properties like porosity, film thickness, chemical composition of the material as well as the crystallinity of the framework. The complex morphology of such porous films constitutes a challenge even for modern analytical techniques and requires new approaches employing the combination/complementation of data of different analytical methods. In this contribution we characterize thin mesoporous iridium-titanium mixed oxide film properties by Electron Probe Microanalysis (EPMA) with energy dispersive X-ray spectroscopy (EDS) at an SEM.
Porous materials play an important role in several fields of technology, especially for energy applications like photovoltaics, electrolysis or batteries. The activity of porous films is affected by properties like porosity, film thickness, chemical composition of the material as well as the crystallinity of the framework. The complex morphology of such porous films constitutes a challenge even for modern analytical techniques and requires new approaches employing the combination/complementation of data of different analytical methods. In this contribution we characterize thin mesoporous iridium-titanium mixed oxide film properties by Electron Probe Microanalysis (EPMA) with energy dispersive X-ray spectroscopy (EDS) at an SEM.
Populations of genetically identical cells can display marked variation in phenotypic traits; such variation is termed phenotypic heterogeneity. Here, we investigate the effect of substrate and electron donor limitation on phenotypic heterogeneity in N2 and CO2 fixation in the green sulphur bacterium Chlorobium phaeobacteroides. We grew populations in chemostats and batch cultures and used stable isotope labelling combined with nanometer‐scale secondary ion mass spectrometry (NanoSIMS) to quantify phenotypic heterogeneity. Experiments in H2S (i.e. electron donor) limited chemostats show that varying levels of NH4+ limitation induce heterogeneity in N2 fixation. Comparison of phenotypic heterogeneity between chemostats and batch (unlimited for H2S) populations indicates that electron donor limitation drives heterogeneity in N2 and CO2 fixation. Our results demonstrate that phenotypic heterogeneity in a certain metabolic activity can be driven by different modes of limitation and that heterogeneity can emerge in different metabolic processes upon the same mode of limitation. In conclusion, our data suggest that limitation is a general driver of phenotypic heterogeneity in microbial populations.
Question: Most microorganisms live in environments where nutrients are limited and fluctuate over time. Cells respond to nutrient fluctuations by sensing and adapting their physiological state. Recent studies suggest phenotypic heterogeneity in isogenic populations as an alternative strategy in fluctuating environments, where a subpopulation of cells express a function that allows growth under conditions that might arise in the future. It is unknown how environmental factors such as nutrient limitation shape phenotypic heterogeneity in metabolism and whether this allows cells to respond to nutrient fluctuations.
Methods: We subjected the N2-fixing bacterium Klebsiella oxytoca to different levels of substrate limitation and substrate shifts, and obtained time-resolved single-cell measurements of metabolic activities using nanometre-scale secondary ion mass spectrometry (NanoSIMS).
Results: We show that substrate limitation increases phenotypic heterogeneity in metabolism, and this
heterogeneity allows cells to cope with substrate fluctuations [1]. We found that the level of NH4+ limitation shapes phenotypic heterogeneity in N2 fixation. In turn, the N2 fixation rate of single cells during NH4+ limitation correlates positively with their growth rate after a shift to NH4+ depletion, experimentally demonstrating the benefit of heterogeneity.
Conclusion: The results indicate that phenotypic heterogeneity is a general solution to two important ecological challenges—nutrient limitation and fluctuations—that many microorganisms face. Currently, we use NanoSIMS to develop a new approach that defines functionally-relevant, phenotypic biodiversity in microbial systems.
Populations of genetically identical cells that share the same environment can differ markedly in their phenotypes. This phenomenon has been termed phenotypic heterogeneity. While a few molecular mechanisms that lead to heterogeneity in gene expression have been elucidated, it remains unclear how heterogeneity in gene expression is transmitted to heterogeneity in activity; especially in metabolism. Metabolic activity of single bacterial cells can be quantified by labeling the substrate with stable isotopes and by measuring label uptake with nanometer-scale secondary ion mass spectrometry (NanoSIMS). Here we combined NanoSIMS with single-molecule mRNA fluorescence in situ hybridization (smFISH) to link heterogeneity in gene expression and metabolism in nitrogen fixing bacteria. We find that gene expression and metabolic activity are decoupled in single cells. However, heterogeneity in gene expression is correlated with heterogeneity in metabolic activity on the population level. Gene expression kinetics can provide insights into the molecular mechanisms that lead to heterogeneity in metabolism.
Populations of genetically identical cells that share the same environment can differ markedly in their phenotypes. This phenomenon has been termed phenotypic heterogeneity. While a few molecular mechanisms that lead to heterogeneity in gene expression have been elucidated, it remains unclear how heterogeneity in gene expression is transmitted to heterogeneity in activity; especially in metabolism. Metabolic activity of single bacterial cells can be quantified by labeling the substrate with stable isotopes and by measuring label uptake with nanometer-scale secondary ion mass spectrometry (NanoSIMS). Here we combined NanoSIMS with single-molecule mRNA fluorescence in situ hybridization (smFISH) to link heterogeneity in gene expression and metabolism in nitrogen fixing bacteria. We find that gene expression and metabolic activity are decoupled in single cells. However, heterogeneity in gene expression is correlated with heterogeneity in metabolic activity on the population level. Gene expression kinetics can provide insights into the molecular mechanisms that lead to heterogeneity in metabolism.
Most microorganisms live in environments where nutrients are limited and fluctuate over time. Cells respond to nutrient fluctuations by sensing and adapting their physiological state. Recent studies suggest phenotypic heterogeneity in isogenic populations as an alternative strategy in fluctuating environments, where a subpopulation of cells express a function that allows growth under conditions that might arise in the future. It is unknown how environmental factors such as nutrient limitation shape phenotypic heterogeneity in metabolism and whether this allows cells to respond to nutrient fluctuations. Here, we show that substrate limitation increases phenotypic heterogeneity in metabolism, and this heterogeneity allows cells to cope with substrate fluctuations. We subjected the N2-fixing bacterium Klebsiella oxytoca to different levels of substrate limitation and substrate shifts, and obtained time-resolved single-cell measurements of metabolic activities using nanometre-scale secondary ion mass spectrometry (NanoSIMS). We found that the level of NH4+ limitation shapes phenotypic heterogeneity in N2 fixation. In turn, the N2 fixation rate of single cells during NH4+ limitation correlates positively with their growth rate after a shift to NH4+ depletion, experimentally demonstrating the benefit of heterogeneity. The results indicate that phenotypic heterogeneity is a general solution to two important ecological challenges - nutrient limitation and fluctuations - that many microorganisms face. Currently, we use NanoSIMS to develop a new approach that defines functionally-relevant, phenotypic biodiversity in microbial systems.