Individual-Based Model of Microbial Life on Hydrated Rough Soil Surfaces

Fluid flow drives phenotypic heterogeneity in bacterial growth and adhesion on surfaces

Bacteria often thrive in surface-attached communities, where they can form biofilms affording them multiple advantages. In this sessile form, fluid flow is a key component of their environments, renewing nutrients and transporting metabolic products and signaling molecules. It also controls colonization patterns and growth rates on surfaces, through bacteria transport, attachment and detachment. However, the current understanding of bacterial growth on surfaces neglects the possibility that bacteria may modulate their division behavior as a response to flow. Here, we employed single-cell imaging in microfluidic experiments to demonstrate that attached Escherichia coli cells can enter a growth arrest state while simultaneously enhancing their adhesion underflow. Despite utilizing clonal populations, we observed a non-uniform response characterized by bistable dynamics, with co-existing subpopulations of non-dividing and actively dividing bacteria. As the proportion of non-dividing bacteria increased with the applied flow rate, it resulted in a reduction in the average growth rate of bacterial populations on flow-exposed surfaces. Dividing bacteria exhibited asymmetric attachment, whereas non-dividing counterparts adhered to the surface via both cell poles. Hence, this phenotypic diversity allows bacterial colonies to combine enhanced attachment with sustained growth, although at a reduced rate, which may be a significant advantage in fluctuating flow conditions.

The chosen few-variations in common and rare soil bacteria across biomes

Soil bacterial communities are dominated by a few abundant species, while their richness is associated with rare species with largely unknown ecological roles and biogeography. Analyses of previously published soil bacterial community data using a novel classification of common and rare bacteria indicate that only 0.4% of bacterial species can be considered common and are prevalent across biomes. The remaining bacterial species designated as rare are endemic with low relative abundances. Observations coupled with mechanistic models highlight the central role of soil wetness in shaping bacterial rarity. An individual-based model reveals systematic shifts in community composition induced by low carbon inputs in drier soils that deprive common species of exhibiting physiological advantages relative to other species. We find that only a "chosen few" common species shape bacterial communities across biomes; however, their contributions are curtailed in resource-limited environments where a larger number of rare species constitutes the soil microbiome.

Collecting eco-evolutionary data in the dark: Impediments to subterranean research and how to overcome them

Caves and other subterranean habitats fulfill the requirements of experimental model systems to address general questions in ecology and evolution. Yet, the harsh working conditions of these environments and the uniqueness of the subterranean organisms have challenged most attempts to pursuit standardized research.Two main obstacles have synergistically hampered previous attempts. First, there is a habitat impediment related to the objective difficulties of exploring subterranean habitats and our inability to access the network of fissures that represents the elective habitat for the so-called "cave species." Second, there is a biological impediment illustrated by the rarity of most subterranean species and their low physiological tolerance, often limiting sample size and complicating laboratory experiments.We explore the advantages and disadvantages of four general experimental setups (in situ, quasi in situ, ex situ, and in silico) in the light of habitat and biological impediments. We also discuss the potential of indirect approaches to research. Furthermore, using bibliometric data, we provide a quantitative overview of the model organisms that scientists have exploited in the study of subterranean life.Our over-arching goal is to promote caves as model systems where one can perform standardized scientific research. This is important not only to achieve an in-depth understanding of the functioning of subterranean ecosystems but also to fully exploit their long-discussed potential in addressing general scientific questions with implications beyond the boundaries of this discipline.

Life in a Droplet: Microbial Ecology in Microscopic Surface Wetness

While many natural and artificial surfaces may appear dry, they are in fact covered by thin liquid films and microdroplets invisible to the naked eye known as microscopic surface wetness (MSW). Central to the formation and the retention of MSW are the deliquescent properties of hygroscopic salts that prevent complete drying of wet surfaces or that drive the absorption of water until dissolution when the relative humidity is above a salt-specific level. As salts are ubiquitous, MSW occurs in many microbial habitats, such as soil, rocks, plant leaf, and root surfaces, the built environment, and human and animal skin. While key properties of MSW, including very high salinity and segregation into droplets, greatly affect microbial life therein, it has been scarcely studied, and systematic studies are only in their beginnings. Based on recent findings, we propose that the harsh micro-environment that MSW imposes, which is very different from bulk liquid, affects key aspects of bacterial ecology including survival traits, antibiotic response, competition, motility, communication, and exchange of genetic material. Further research is required to uncover the fundamental principles that govern microbial life and ecology in MSW. Such research will require multidisciplinary science cutting across biology, physics, and chemistry, while incorporating approaches from microbiology, genomics, microscopy, and computational modeling. The results of such research will be critical to understand microbial ecology in vast terrestrial habitats, affecting global biogeochemical cycles, as well as plant, animal, and human health.

Bacterial diversity patterns of desert dunes in the northeastern Qinghai-Tibet Plateau, China

Limited knowledge about the variation patterns of bacterial community composition in the sand and vegetative ecosystems confines our understanding regarding the contribution of the sand dune to desert areas. In this study, 454 pyrosequencing platforms were adopted to determine the community structure of bacteria and diversity of sand dunes in northeastern Qinghai-Tibet Plateau, China: 50 cm deep, rhizosphere, physical crusts, and biological crusts representing sand and vegetative ecosystems, respectively. The findings revealed significant variation in bacterial diversities and the structure of communities in the sand and vegetative ecosystems. The dominant bacterial phyla of sand and vegetative ecosystems were Firmicutes (47%), Actinobacteria (21%), Proteobacteria (16%), and Bacteroidetes (13%), while Lactococcus (50%) was found to be the dominant genus. Furthermore, samples with high alpha-diversity indices (Chao 1 and Shannon) for the vegetative ecosystem have the lowest modularity index and the largest number of biomarkers, with some exceptions. Redundancy analysis exhibited that environmental factors could explain 72% (phyla) and 67% (genera) of the bacterial communities, with EC, TC, and TOC being the major driving factors. This study expands our understanding of bacterial community composition in the desert ecosystem. The findings suggest that variations in the sand and vegetative ecosystems, such as those predicted by environmental factors, may reduce the abundance and diversity of bacteria, a response that likely affects the provision of key ecosystem processes by desert regions.

Spatial organization in microbial range expansion emerges from trophic dependencies and successful lineages

Evidence suggests that bacterial community spatial organization affects their ecological function, yet details of the mechanisms that promote spatial patterns remain difficult to resolve experimentally. In contrast to bacterial communities in liquid cultures, surface-attached range expansion fosters genetic segregation of the growing population with preferential access to nutrients and reduced mechanical restrictions for cells at the expanding periphery. Here we elucidate how localized conditions in cross-feeding bacterial communities shape community spatial organization. We combine experiments with an individual based mathematical model to resolve how trophic dependencies affect localized growth rates and nucleate successful cell lineages. The model tracks individual cell lineages and attributes these with trophic dependencies that promote counterintuitive reproductive advantages and result in lasting influences on the community structure, and potentially, on its functioning. We examine persistence of lucky lineages in structured habitats where expansion is interrupted by physical obstacles to gain insights into patterns in porous domains.

Deep learning predicts microbial interactions from self-organized spatiotemporal patterns

Microbial communities organize into spatial patterns that are largely governed by interspecies interactions. This phenomenon is an important metric for understanding community functional dynamics, yet the use of spatial patterns for predicting microbial interactions is currently lacking. Here we propose supervised deep learning as a new tool for network inference. An agent-based model was used to simulate the spatiotemporal evolution of two interacting organisms under diverse growth and interaction scenarios, the data of which was subsequently used to train deep neural networks. For small-size domains (100 µm × 100 µm) over which interaction coefficients are assumed to be invariant, we obtained fairly accurate predictions, as indicated by an average R2 value of 0.84. In application to relatively larger domains (450 µm × 450 µm) where interaction coefficients are varying in space, deep learning models correctly predicted spatial distributions of interaction coefficients without any additional training. Lastly, we evaluated our model against real biological data obtained using Pseudomonas fluorescens and Escherichia coli co-cultures treated with polymeric chitin or N-acetylglucosamine, the hydrolysis product of chitin. While P. fluorescens can utilize both substrates for growth, E. coli lacked the ability to degrade chitin. Consistent with our expectations, our model predicted context-dependent interactions across two substrates, i.e., degrader-cheater relationship on chitin polymers and competition on monomers. The combined use of the agent-based model and machine learning algorithm successfully demonstrates how to infer microbial interactions from spatially distributed data, presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Soil bacterial diversity mediated by microscale aqueous-phase processes across biomes

Soil bacterial diversity varies across biomes with potential impacts on soil ecological functioning. Here, we incorporate key factors that affect soil bacterial abundance and diversity across spatial scales into a mechanistic modeling framework considering soil type, carbon inputs and climate towards predicting soil bacterial diversity. The soil aqueous-phase content and connectivity exert strong influence on bacterial diversity for each soil type and rainfall pattern. Biome-specific carbon inputs deduced from net primary productivity provide constraints on soil bacterial abundance independent from diversity. The proposed heuristic model captures observed global trends of bacterial diversity in good agreement with predictions by an individual-based mechanistic model. Bacterial diversity is highest at intermediate water contents where the aqueous phase forms numerous disconnected habitats and soil carrying capacity determines level of occupancy. The framework delineates global soil bacterial diversity hotspots; located mainly in climatic transition zones that are sensitive to potential climate and land use changes.

Microscale pH variations during drying of soils and desert biocrusts affect HONO and NH3 emissions

Microscale interactions in soil may give rise to highly localised conditions that disproportionally affect soil nitrogen transformations. We report mechanistic modelling of coupled biotic and abiotic processes during drying of soil surfaces and biocrusts. The model links localised microbial activity with pH variations within thin aqueous films that jointly enhance emissions of nitrous acid (HONO) and ammonia (NH₃) during soil drying well above what would be predicted from mean hydration conditions and bulk soil pH. We compared model predictions with case studies in which reactive nitrogen gaseous fluxes from drying biocrusts were measured. Soil and biocrust drying rates affect HONO and NH₃ emission dynamics. Additionally, we predict strong effects of atmospheric NH₃ levels on reactive nitrogen gas losses. Laboratory measurements confirm the onset of microscale pH localisation and highlight the critical role of micro-environments in the resulting biogeochemical fluxes from terrestrial ecosystems.

The mechanisms that determine the composition of nitrogen gas emissions from soil remain unclear. A biocrust mechanistic model was developed to resolve puzzling dynamics of nitrous acid and ammonia emissions from drying soil pointing to previously unknown microscale pH zonation in thinning water films that affect soil biogeochemical fluxes.

Modeling metabolic networks of individual bacterial agents in heterogeneous and dynamic soil habitats (IndiMeSH)

Natural soil is characterized as a complex habitat with patchy hydrated islands and spatially variable nutrients that is in a constant state of change due to wetting-drying dynamics. Soil microbial activity is often concentrated in sparsely distributed hotspots that contribute disproportionally to macroscopic biogeochemical nutrient cycling and greenhouse gas emissions. The mechanistic representation of such dynamic hotspots requires new modeling approaches capable of representing the interplay between dynamic local conditions and the versatile microbial metabolic adaptations. We have developed IndiMeSH (Individual-based Metabolic network model for Soil Habitats) as a spatially explicit model for the physical and chemical microenvironments of soil, combined with an individual-based representation of bacterial motility and growth using adaptive metabolic networks. The model uses angular pore networks and a physically based description of the aqueous phase as a backbone for nutrient diffusion and bacterial dispersal combined with dynamic flux balance analysis to calculate growth rates depending on local nutrient conditions. To maximize computational efficiency, reduced scale metabolic networks are used for the simulation scenarios and evaluated strategically to the genome scale model. IndiMeSH was compared to a well-established population-based spatiotemporal metabolic network model (COMETS) and to experimental data of bacterial spatial organization in pore networks mimicking soil aggregates. IndiMeSH was then used to strategically study dynamic response of a bacterial community to abrupt environmental perturbations and the influence of habitat geometry and hydration conditions. Results illustrate that IndiMeSH is capable of representing trophic interactions among bacterial species, predicting the spatial organization and segregation of bacterial populations due to oxygen and carbon gradients, and provides insights into dynamic community responses as a consequence of environmental changes. The modular design of IndiMeSH and its implementation are adaptable, allowing it to represent a wide variety of experimental and in silico microbial systems.

Soil bacterial communities are key players in global biogeochemical cycles and drive other soil regulatory and provisional ecosystem functions. Despite the relatively high bacterial abundance found in fertile soil, bacteria occupy only a small fraction of the soil surfaces and often form hotspots with disproportionate contributions to observed biogenic fluxes. As soil opacity and complexity limit detailed observations of such hotspots in situ, we have developed a modeling platform, IndiMeSH (Individual-based Metabolic network model for Soil Habitats), to enable systematic study of dense multispecies bacterial communities within a structured habitat resembling (but not limited) to soil. The model is capable of representing multispecies trophic interactions and spatial self-organization in response to nutrient gradients, as confirmed in comparison with published results. IndiMeSH offers new opportunities for quantifying bacterial hotspot formation and dynamics and observe their resilience and response to perturbations in hydration and nutrient conditions.

Emergent Properties of Microbial Activity in Heterogeneous Soil Microenvironments: Different Research Approaches Are Slowly Converging, Yet Major Challenges Remain

Over the last 60 years, soil microbiologists have accumulated a wealth of experimental data showing that the bulk, macroscopic parameters (e.g., granulometry, pH, soil organic matter, and biomass contents) commonly used to characterize soils provide insufficient information to describe quantitatively the activity of soil microorganisms and some of its outcomes, like the emission of greenhouse gasses. Clearly, new, more appropriate macroscopic parameters are needed, which reflect better the spatial heterogeneity of soils at the microscale (i.e., the pore scale) that is commensurate with the habitat of many microorganisms. For a long time, spectroscopic and microscopic tools were lacking to quantify processes at that scale, but major technological advances over the last 15 years have made suitable equipment available to researchers. In this context, the objective of the present article is to review progress achieved to date in the significant research program that has ensued. This program can be rationalized as a sequence of steps, namely the quantification and modeling of the physical-, (bio)chemical-, and microbiological properties of soils, the integration of these different perspectives into a unified theory, its upscaling to the macroscopic scale, and, eventually, the development of new approaches to measure macroscopic soil characteristics. At this stage, significant progress has been achieved on the physical front, and to a lesser extent on the (bio)chemical one as well, both in terms of experiments and modeling. With regard to the microbial aspects, although a lot of work has been devoted to the modeling of bacterial and fungal activity in soils at the pore scale, the appropriateness of model assumptions cannot be readily assessed because of the scarcity of relevant experimental data. For significant progress to be made, it is crucial to make sure that research on the microbial components of soil systems does not keep lagging behind the work on the physical and (bio)chemical characteristics. Concerning the subsequent steps in the program, very little integration of the various disciplinary perspectives has occurred so far, and, as a result, researchers have not yet been able to tackle the scaling up to the macroscopic level. Many challenges, some of them daunting, remain on the path ahead. Fortunately, a number of these challenges may be resolved by brand new measuring equipment that will become commercially available in the very near future.

Listening to earthworms burrowing and roots growing - acoustic signatures of soil biological activity

We report observations of acoustic emissions (AE) from growing plant roots and burrowing earthworms in soil, as a noninvasive method for monitoring biophysical processes that modify soil structure. AE emanating from earthworm and plants root activity were linked with time-lapse imaging in glass cells. Acoustic waveguides where installed in soil columns to monitor root growth in real time (mimicking field application). The cumulative AE events were in correlation with earthworm burrow lengths and with root growth. The number of AE events recorded from the soil columns with growing maize roots were several orders of magnitude larger than AE emanating from bare soil under similar conditions. The results suggest that AE monitoring may offer a window into largely unobservable dynamics of soil biomechanical processes such as root growth or patterns of earthworm activity - both important soil structure forming processes.

Spatial organization of bacterial populations in response to oxygen and carbon counter-gradients in pore networks

Microbial activity in soil is spatially heterogeneous often forming spatial hotspots that contribute disproportionally to biogeochemical processes. Evidence suggests that bacterial spatial organization contributes to the persistence of anoxic hotspots even in unsaturated soils. Such processes are difficult to observe in situ at the microscale, hence mechanisms and time scales relevant for bacterial spatial organization remain largely qualitative. Here we develop an experimental platform based on glass-etched micrometric pore networks that mimics resource gradients postulated in soil aggregates to observe spatial organization of fluorescently tagged aerobic and facultative anaerobic bacteria. Two initially intermixed bacterial species, Pseudomonas putida and Pseudomonas veronii, segregate into preferential regions promoted by opposing gradients of carbon and oxygen (such persistent coexistence is not possible in well-mixed cultures). The study provides quantitative visualization and modeling of bacterial spatial organization within aggregate-like hotspots, a key step towards developing a mechanistic representation of bacterial community organization in soil pores.

Bioenergetic Controls on Microbial Ecophysiology in Marine Sediments

Marine sediments constitute one of the most energy-limited habitats on Earth, in which microorganisms persist over extraordinarily long timescales with very slow metabolisms. This habitat provides an ideal environment in which to study the energetic limits of life. However, the bioenergetic factors that can determine whether microorganisms will grow, lie dormant, or die, as well as the selective environmental pressures that determine energetic trade-offs between growth and maintenance activities, are not well understood. Numerical models will be pivotal in addressing these knowledge gaps. However, models rarely account for the variable physiological states of microorganisms and their demand for energy. Here, we review established modeling constructs for microbial growth rate, yield, maintenance, and physiological state, and then provide a new model that incorporates all of these factors. We discuss this new model in context with its future application to the marine subsurface. Understanding the factors that regulate cell death, physiological state changes, and the provenance of maintenance energy (i.e., endogenous versus exogenous metabolism), is crucial to the design of this model. Further, measurements of growth rate, growth yield, and basal metabolic activity will enable bioenergetic parameters to be better constrained. Last, biomass and biogeochemical rate measurements will enable model simulations to be validated. The insight provided from the development and application of new microbial modeling tools for marine sediments will undoubtedly advance the understanding of the minimum power required to support life, and the ecophysiological strategies that organisms utilize to cope under extreme energy limitation for extended periods of time.

Biophysical processes supporting the diversity of microbial life in soil

Soil, the living terrestrial skin of the Earth, plays a central role in supporting life and is home to an unimaginable diversity of microorganisms. This review explores key drivers for microbial life in soils under different climates and land-use practices at scales ranging from soil pores to landscapes. We delineate special features of soil as a microbial habitat (focusing on bacteria) and the consequences for microbial communities. This review covers recent modeling advances that link soil physical processes with microbial life (termed biophysical processes). Readers are introduced to concepts governing water organization in soil pores and associated transport properties and microbial dispersion ranges often determined by the spatial organization of a highly dynamic soil aqueous phase. The narrow hydrological windows of wetting and aqueous phase connectedness are crucial for resource distribution and longer range transport of microorganisms. Feedbacks between microbial activity and their immediate environment are responsible for emergence and stabilization of soil structure-the scaffolding for soil ecological functioning. We synthesize insights from historical and contemporary studies to provide an outlook for the challenges and opportunities for developing a quantitative ecological framework to delineate and predict the microbial component of soil functioning.

Microbial community response to hydration-desiccation cycles in desert soil

Life in desert soil is marked by episodic pulses of water and nutrients followed by long periods of drought. While the desert flora and fauna flourish after rainfall the response of soil microorganisms remains unclear and understudied. We provide the first systematic study of the role of soil aqueous habitat dynamics in shaping microbial community composition and diversity. Detailed monitoring of natural microbial communities after a rainfall event revealed a remarkable decrease in diversity and a significant transition in community composition that were gradually restored to pre-rainfall values during soil desiccation. Modelling results suggest a critical role for the fragmented aqueous habitat in maintaining microbial diversity under dry soil conditions and diversity loss with wetting events that increase connectivity among habitats. This interdisciplinary study provides new insights into wetting and drying processes that promote and restore the unparalleled microbial diversity found in soil.

Microbial community dynamics in soil aggregates shape biogeochemical gas fluxes from soil profiles - upscaling an aggregate biophysical model

Microbial communities inhabiting soil aggregates dynamically adjust their activity and composition in response to variations in hydration and other external conditions. These rapid dynamics shape signatures of biogeochemical activity and gas fluxes emitted from soil profiles. Recent mechanistic models of microbial processes in unsaturated aggregate-like pore networks revealed a highly dynamic interplay between oxic and anoxic microsites jointly shaped by hydration conditions and by aerobic and anaerobic microbial community abundance and self-organization. The spatial extent of anoxic niches (hotspots) flicker in time (hot moments) and support substantial anaerobic microbial activity even in aerated soil profiles. We employed an individual-based model for microbial community life in soil aggregate assemblies represented by 3D angular pore networks. Model aggregates of different sizes were subjected to variable water, carbon and oxygen contents that varied with soil depth as boundary conditions. The study integrates microbial activity within aggregates of different sizes and soil depth to obtain estimates of biogeochemical fluxes from the soil profile. The results quantify impacts of dynamic shifts in microbial community composition on CO2 and N2 O production rates in soil profiles in good agreement with experimental data. Aggregate size distribution and the shape of resource profiles in a soil determine how hydration dynamics shape denitrification and carbon utilization rates. Results from the mechanistic model for microbial activity in aggregates of different sizes were used to derive parameters for analytical representation of soil biogeochemical processes across large scales of practical interest for hydrological and climate models.