Isaac Klapper

Challenges in microbial ecology: building predictive understanding of community function and dynamics

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth’s soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.

Mighty small: Observing and modeling individual microbes becomes big science

Progress in microbiology has always been driven by technological advances, ever since Antonie van Leeuwenhoek discovered bacteria by making an improved compound microscope. However, until very recently we have not been able to identify microbes and record their mostly invisible activities, such as nutrient consumption or toxin production on the level of the single cell, not even in the laboratory. This is now changing with the rapid rise of exciting new technologies for single-cell microbiology (1, 2), which enable microbiologists to do what plant and animal ecologists have been doing for a long time: observe who does what, when, where, and next to whom. Single cells taken from the environment can be identified and even their genomes sequenced. Ex situ, their size, elemental, and biochemical composition, as well as other characteristics can be measured with high-throughput and cells sorted accordingly. Even better, individual microbes can be observed in situ with a range of novel microscopic and spectroscopic methods, enabling localization, identification, or functional characterization of cells in a natural sample, combined with detecting uptake of labeled compounds. Alternatively, they can be placed into fabricated microfluidic environments, where they can be positioned, exposed to stimuli, monitored, and their interactions controlled “in microfluido.” By introducing genetically engineered reporter cells into a fabricated landscape or a microcosm taken from nature, their reproductive success or activity can be followed, or their sensing of their local environment recorded.

Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms

Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptive and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabit this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms, and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g., glycolate) and fermentation (e.g., acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gasses (e.g., H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: (1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; (2) photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; (3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and (4) fluctuations in many metabolite pools (e.g., wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their niches.

The molecular dimension of microbial species: 2. Synechococcus strains representative of putative ecotypes inhabiting different depths in the Mushroom Spring microbial mat exhibit different adaptive and acclimative responses to light

Closely related strains of thermophilic Synechococcus were cultivated from the microbial mats found in the effluent channels of Mushroom Spring, Yellowstone National Park (YNP). These strains have identical or nearly identical 16S rRNA sequences but are representative of separate, predicted putative ecotype (PE) populations, which were identified by using the more highly resolving psaA locus and which predominate at different vertical positions within the 1-mm-thick upper-green layer of the mat. Pyrosequencing confirmed that each strain contained a single, predominant psaA genotype. Strains differed in growth rate as a function of irradiance. A strain with a psaA genotype corresponding to a predicted PE that predominates near the mat surface grew fastest at high irradiances, whereas strains with psaA genotypes representative of predominant subsurface populations grew faster at low irradiance and exhibited greater sensitivity to abrupt shifts to high light. The high-light-adapted and low-light-adapted strains also exhibited differences in pigment content and the composition of the photosynthetic apparatus (photosystem ratio) when grown under different light intensities. Cells representative of the different strains had similar morphologies under low-light conditions, but under high-light conditions, cells of low-light-adapted strains became elongated and formed short chains of cells. Collectively, the results presented here are consistent with the hypothesis that closely related, but distinct, ecological species of Synechococcus occupy different light niches in the Mushroom Spring microbial mat and acclimate differently to changing light environments.

Productivity and Equilibrium in Simple Biofilm Models

Biofilms are dense, sessile collections of microorganisms with complicated internal structures. However, in many applications internal details are less important, rather basic, averaged information such as overall community productivity are of most interest. This paper studies averaged community functions in the context of one dimensional, single species, single limiting substrate biofilm models. In particular, using a derived formula for flux of substrate into the biofilm as a function of biofilm height and substrate loading, overall community production can be calculated and system equilibria can be characterized. Consequences for equilibria dependence on a number of mechanisms for balancing growth are considered.

General Theory for Integrated Analysis of Growth, Gene, and Protein Expression in Biofilms

A theory for analysis and prediction of spatial and temporal patterns of gene and protein expression within microbial biofilms is derived. The theory integrates phenomena of solute reaction and diffusion, microbial growth, mRNA or protein synthesis, biomass advection, and gene transcript or protein turnover. Case studies illustrate the capacity of the theory to simulate heterogeneous spatial patterns and predict microbial activities in biofilms that are qualitatively different from those of planktonic cells. Specific scenarios analyzed include an inducible GFP or fluorescent protein reporter, a denitrification gene repressed by oxygen, an acid stress response gene, and a quorum sensing circuit. It is shown that the patterns of activity revealed by inducible stable fluorescent proteins or reporter unstable proteins overestimate the region of activity. This is due to advective spreading and finite protein turnover rates. In the cases of a gene induced by either limitation for a metabolic substrate or accumulation of a metabolic product, maximal expression is predicted in an internal stratum of the biofilm. A quorum sensing system that includes an oxygen-responsive negative regulator exhibits behavior that is distinct from any stage of a batch planktonic culture. Though here the analyses have been limited to simultaneous interactions of up to two substrates and two genes, the framework applies to arbitrarily large networks of genes and metabolites. Extension of reaction-diffusion modeling in biofilms to the analysis of individual genes and gene networks is an important advance that dovetails with the growing toolkit of molecular and genetic experimental techniques.

Critical occlusion via biofilm induced calcite precipitation in porous media

A model for biofilm induced calcite precipitation with pressure driven flow is presented at the scale of a single pore within a porous medium. The system, an extension of previous work (Zhang and Klapper 2010 Water Sci. Technol. 61 2957–64, Zhang and Klapper 2011 Int. J. Non-Linear Mech. 46 657–66), is based on a mixture model including biomaterial, mineral, and water with dissolved components. Computational results suggest the possibility of critical occlusion in the sense that there is a distinguished trans-pore pressure head such that for pressure drops below this level, pore clogging occurs relatively quickly while for pressure drops above, clogging occurs after much longer times if at all. Beyond its relevance to engineered biofilm applications, this phenomenon is suggestive of the subtleties of embedding simple biofilm models in larger media.

Hypoxia arising from concerted oxygen consumption by neutrophils and microorganisms in biofilms

Abstract Infections associated with microbial biofilms are often found to involve hypoxic or anoxic conditions within the biofilm or its vicinity. To shed light on the phenomenon of local oxygen depletion, mathematical reaction‐diffusion models were derived that integrated the two principal oxygen sinks, microbial respiration and neutrophil consumption. Three simple one‐dimensional problems were analyzed approximating biofilm near an air interface as in a dermal wound or mucus layer, biofilm on an implanted medical device, or biofilm aggregates dispersed in mucus or tissue. In all three geometries considered, hypoxia at the biofilm‐neutrophil interface or within the biofilm was predicted for a subset of plausible parameter values. The finding that oxygen concentration at the biofilm‐neutrophil juncture can be diminished to hypoxic levels is biologically relevant because oxygen depletion will reduce neutrophil killing ability. The finding that hypoxia can readily establish in the interior of the biofilm is biologically relevant because this change will alter microbial metabolism and persistence.

Niche Partitioning Along an Environmental Gradient

Biological systematics studies suggest that species are discretized in niche space. That is, rather than seeing a continuum of organism types with respect to continuous environmental variations, observers instead find discrete species or clumps of species, with one clump separated from another in niche space by a gap. Here, using a simple one dimensional model with a smoothly varying environmental condition, we investigate conditions for a discrete niche partitioning instability of a continuously varying species structure in the context of asexually reproducing microbes. We find that significant perturbation of translational invariance is required for instability, but that conditions for such perturbations might reasonably occur, for example, through influence of boundary conditions.

Flux-Balance Based Modeling of Biofilm Communities

Models of microbial community dynamics generally rely on a sub-scale model for microbial metabolisms. In systems such as distributed multispecies communities like biofilms, where it is not reasonable to simplify to a small number of limiting substrates, tracking the large number of active metabolites likely requires measurement or estimation of large numbers of kinetic and regulatory parameters. Alternatively, a largely kinetics-free methodology is proposed combining cellular level constrained, steady state metabolic flux analysis with macro scale microbial community models. The methodology easily allows coupling of macroscale information, including measurement data, with cell-scale metabolism. Illustrative examples are included.