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Kiviet, D. J.

Publications and source records attributed to Kiviet, D. J..

2 recordsLinked to original sources

Short-range interactions govern cellular dynamics in microbial multi-genotype systems

Ecosystem processes result from interaction between organisms. When interactions are local, the spatial organization of organisms defines their network of interactions, and thus influences the systems functioning. This can be especially relevant for microbial systems, which often consist of spatially structured communities of cells connected by a dense interaction network. Here we measured the spatial interaction network between cells in microbial systems and identify the factors that determine it. Combining quantitative single-cell analysis of synthetic bacterial communities with mathematical modeling, we find that cells only interact with other cells in their immediate neighbourhood. This short interaction range impacts the functioning of the whole system by reducing its ability to perform metabolic processes collectively. Our experiments and models demonstrate that the spatial scale of cell-to-cell interaction plays a fundamental role in understanding and controlling natural communities, and in engineering microbial systems for specific purposes. Significance StatementCommunities of interacting microbes perform fundamental processes on earth. We do not understand well how these processes emerge from the interactions between individual microbial cells. Our work investigates how strongly individual cells interact and how the strength of the interaction depends on the distance between cells. The discovery that individual cells live in a small world, i.e. they only interact with a small number of cells around them, changes our understanding of how cells in natural microbial communities are metabolically coupled and how their spatial arrangement determines emergent properties at the community level. Our quantitative single-cell approach allows to address central questions on systems composed of interacting genotypes and to increase our understanding and ability to control microbial communities.

systems biology↗

Effective polyploidy causes phenotypic delay and influences bacterial evolvability

Whether mutations in bacteria exhibit a noticeable delay before expressing their corresponding mutant phenotype was discussed intensively in the 1940s-50s, but the discussion eventually waned for lack of supportive evidence and perceived incompatibility with observed mutant distributions in fluctuation tests. Phenotypic delay in bacteria is widely assumed to be negligible, despite lack of direct evidence. Here we revisited the question using recombineering to introduce antibiotic resistance mutations into E. coli at defined time points and then tracking expression of the corresponding mutant phenotype over time. Contrary to previous assumptions, we found a substantial median phenotypic delay of 3-4 generations. We provided evidence that the primary source of this delay is multifork replication causing cells to be effectively polyploid, whereby wild-type gene copies transiently mask the phenotype of recessive mutant gene copies in the same cell. Using modeling and simulation methods, we explored the consequences of effective polyploidy for mutation rate estimation by fluctuation tests and sequencing-based methods. For recessive mutations, despite the substantial phenotypic delay, the per-copyor per-genome mutation rate is accurately estimated. However, the per-cell rate cannot be estimated by existing methods. Finally, with a mathematical model, we showed that effective polyploidy increases the frequency of costly recessive mutations in the standing genetic variation, and thus their potential contribution to evolutionary adaptation, while drastically reducing the chance that de novo recessive mutations can rescue populations facing a harsh environmental change such as antibiotic treatment. Overall, we have identified phenotypic delay and effective polyploidy as previously overlooked but essential components in bacterial evolvability, including antibiotic resistance evolution.\n\nAuthor summaryWhat is the time delay between the occurrence of a genetic mutation in a bacterial cell and manifestation of its phenotypic effect? We show that antibiotic resistance mutations in E.coli show a remarkably long phenotypic delay of 3-4 bacterial generations. The primary underlying mechanism of this delay is effective polyploidy. In a polyploid cell with multiple chromosomes, once a mutation arises on one of the chromosomes, the presence of non-mutated, wild-type gene copies on other chromosomes may mask the phenotype of the mutation. One implication of this finding is that conventional methods to determine the mutation rates of bacteria do not detect polyploidy and thus underestimate their potential for adaptation. More generally, the effect that a new mutation may become useful only in the \"grand-children of the grand-children\" suggests that pre-existing mutations are more important for surviving sudden environmental catastrophe.

evolutionary biology↗