Single-cell trait diversity explains niche and fitness differences in aquatic microbial communities
Fontana, S.; Schmitz, D. A.; Daniels, M.; Danza, F.; Röösli, T.; Bruderer, H.; Walser, J.-C.; Dekaezemacker, J.; Escrig, S.; Meibom, A.; Pomati, F.; Schreiber, F.
Show abstract
Two fundamental questions in ecology are how biodiversity is maintained and how it affects ecosystem functioning. Until now, it has been difficult to study the above mechanisms in natural microbial communities, yet they are important drivers of biogeochemical ecosystem functions. Here, we use a new approach to define and measure biodiversity in complex lake microbial communities (Lake Cadagno, Switzerland) based on the cell-to-cell variation in multiple functionally relevant phenotypic traits. We use stable isotope probing coupled to correlative imaging using confocal laser scanning microscopy (CLSM) and nanometer-scale secondary ion mass spectrometry (NanoSIMS) to obtain morphological (size), physiological (pigments) and metabolic (carbon and nitrogen isotope uptake and sulfur content) traits for a large number of individual cells along the environmental gradient found across lake depth. We show that cell-to-cell trait variation is significantly correlated with cell densities as a proxy for ecosystem functioning, whereas genetic diversity measured at the level of 16S and 18S is not. Our single-cell analysis provides evidence for a simultaneous increase in niche partitioning (measured as increased evenness in pigment composition) and decrease in fitness differences (measured as decreased variability in sulfur content) due to light limitation and competition for nutrients in deep layers of the lake. This leads to a negative relationship between niche and fitness differences. Our results suggest that niche and fitness differences in natural microbial communities can be understood at the level of single-cell traits, providing a mechanistic understanding of the relationship between microbial diversity and ecosystem functioning.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Quantification of archaea-driven freshwater nitrification: from single cell to ecosystem level 97%
- Depth-discrete metagenomics reveals the roles of microbes in biogeochemical cycling in the tropical freshwater Lake Tanganyika 97%
- Frequency of change determines effectiveness of microbial response strategies in sulfidic stream microbiomes 96%
Similar papers in this journal
Similar papers in this journal
- Unexpected diversity and ecological significance of uncultivable large virus-like particles in aquatic environments 96%
- B12-dependent virioplankton demonstrate interseasonal dynamics and associate with a diversity of pelagic bacterioplankton 96%
- Upwelling periodically disturbs the ecological assembly of microbial communities in Lake Ontario 96%
Similar papers in this journal
- Single-colony sequencing reveals phylosymbiosis, co-phylogeny, and horizontal gene transfer between the cyanobacterium Microcystis and its microbiome 97%
- Reductive dehalogenation by diverse microbes is central to biogeochemical cycles in deep-sea cold seeps 94%
- Variable impact of geochemical gradients on the functional potential of bacteria, archaea, and phages from the permanently stratified Lac Pavin 94%
Similar papers in this journal
- Bacterial ecology and evolution converge on seasonal and decadal scales 96%
- Large Freshwater Phages with the Potential to Augment Aerobic Methane Oxidation 95%
- A 20-year time-series of a freshwater lake reveals seasonal dynamics and environmental drivers of viral diversity, ecology, and evolution 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.