A key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species–species and species–environment interactions in spatially organized environments requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a defined system to study the metabolic interactions in a spatial context among the plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indica under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant seed treatments and for vertical farming under defined conditions.
This paper reports on the use of scanning ion conductance microscopy (SICM) to locally map the ionic properties and charge environment of two live bacterial strains: the Gram-negative Escherichia coli and the Gram-positive Bacillus subtilis. SICM results find heterogeneities across the bacterial surface and significant differences among the Gram-positive and Gram-negative bacteria. The bioelectrical environment of the B. subtilis was found to be considerably more negatively charged compared to E. coli. SICM measurements, fitted to a simplified finite element method (FEM) model, revealed surface charge values of −80 to −140 mC m −2 for the Gram-negative E. coli. The Gram-positive B. subtilis show a much higher conductivity around the cell wall, and surface charge values between −350 and −450 mC m −2 were found using the same simplified model. SICM was also able to detect regions of high negative charge near B. subtilis, not detected in the topographical SICM response and attributed to the extracellular polymeric substance. To further explore how the B. subtilis cell wall structure can influence the SICM current response, a more comprehensive FEM model, accounting for the physical properties of the Gram-positive cell wall, was developed. The new model provides a more realistic description of the cell wall and allows investigation of the relation between its key properties and SICM currents, building foundations to further investigate and improve understanding of the Gram-positive cellular microenvironment.
The last five decades of molecular and systems biology research have provided unprecedented insights into the molecular and genetic basis of many cellular processes. Despite these insights, however, it is arguable that there is still only limited predictive understanding of cell behaviours. In particular, the basis of heterogeneity in single-cell behaviour and the initiation of many different metabolic, transcriptional or mechanical responses to environmental stimuli remain largely unexplained. To go beyond the status quo , the understanding of cell behaviours emerging from molecular genetics must be complemented with physical and physiological ones, focusing on the intracellular and extracellular conditions within and around cells. Here, we argue that such a combination of genetics, physics and physiology can be grounded on a bioelectrical conceptualization of cells. We motivate the reasoning behind such a proposal and describe examples where a bioelectrical view has been shown to, or can, provide predictive biological understanding. In addition, we discuss how this view opens up novel ways to control cell behaviours by electrical and electrochemical means, setting the stage for the emergence of bioelectrical engineering.
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