Scanning ion conductance microscopy reveals differences in the ionic environments of gram-positive and negative bacteria

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 and the Gram-positive . SICM results find heterogeneities across the bacterial surface and significant differences among the Gram-positive and Gram-negative bacteria. The bioelectrical environment of the was found to be considerably more negatively charged compared to . SICM measurements, fitted to a simplified finite element method (FEM) model, revealed surface charge values of -80 to -140 mC m for the Gram-negative . The Gram-positive show a much higher conductivity around the cell wall, and surface charge values between -350 and -450 mC m were found using the same simplified model. SICM was also able to detect regions of high negative charge near , not detected in the topographical SICM response and attributed to the extracellular polymeric substance. To further explore how the 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

Bioelectrical understanding and engineering of cell biology

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

Groundwater metabolome responds to recharge in fractured sedimentary strata

Understanding the sources, structure and fate of dissolved organic matter (DOM) in groundwater is paramount for the protection and sustainable use of this vital resource. On its passage through the Critical Zone, DOM is subject to biogeochemical conversions. Therefore, it carries valuable cross-habitat information for monitoring and predicting the stability of groundwater ecosystem services and assessing these ecosystems' response to fluctuations caused by external impacts such as climatic extremes. Challenges arise from insufficient knowledge on groundwater metabolite composition and dynamics due to a lack of consistent analytical approaches for long-term monitoring. Our study establishes groundwater metabolomics to decipher the complex biogeochemical transport and conversion of DOM. We explore fractured sedimentary bedrock along a hillslope recharge area by a 5-year untargeted metabolomics monitoring of oxic perched and anoxic phreatic groundwater. A summer with extremely high temperatures and low precipitation was included in the monitoring. Water was accessed by a monitoring well-transect and regularly collected for liquid chromatography-mass spectrometry (LC-MS) investigation. Dimension reduction of the resulting complex data set by principal component analysis revealed that metabolome dissimilarities between distant wells coincide with transient cross-stratal flow indicated by groundwater levels. Time series of the groundwater metabolome data provides detailed insights into subsurface responses to recharge dynamics. We demonstrate that dissimilarity variability between groundwater bodies with contrasting aquifer properties coincides with recharge dynamics. This includes groundwater high- and lowstands as well as recharge and recession phases. Our monitoring approach allows to survey groundwater ecosystems even under extreme conditions. Notably, the metabolome was highly variable lacking seasonal patterns and did not segregate by geographical location of sampling wells, thus ruling out vegetation or (agricultural) land use as a primary driving factor. Patterns that emerge from metabolomics monitoring give insight into subsurface ecosystem functioning and water quality evolution, essential for sustainable groundwater use and climate change-adapted management