Memory shapes microbial populations

Correct decision making is fundamental for all living organisms to thrive under environmental changes. The patterns of environmental variation and the quality of available information define the most favourable strategy among multiple options, from randomly adopting a phenotypic state to sensing and reacting to environmental cues. Cellular memory—the ability to track and condition the time to switch to a different phenotypic state—can help withstand environmental fluctuations. How does memory manifest itself in unicellular organisms? We describe the population-wide consequences of phenotypic memory in microbes through a combination of deterministic modelling and stochastic simulations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that memory in individual cells generates patterns at the population level coherent with overshoots and non-exponential lag times distributions experimentally observed in phenotypically heterogeneous populations. We emphasise the implications of our work in understanding antibiotic tolerance and, in general, bacterial survival under fluctuating environments.     

Transient responses of budding yeast populations

The unequal-division model for budding yeast is used to formulate a population-balance model for the transient behavior of populations of these organisms. The model consists of linear partial differential equations coupled through algebraic equations. It is shown how the solution of this system of equations can be obtained in a systematic stepwise fashion. The special case of a population subjected to a step change in growth rate is described in some detail, and solutions for two special cases are determined for transients following an age-distribution perturbation. It is shown how experimental data on transient behavior of a cell population can yield information on single-cell mass-synthesis kinetics and on the manner in which individual cells control certain critical parameters in the cell cycle.     

Soil microbial populations after wildfire

Abstract Population fluctuations were increased by burning, which also modified the incubation patterns and the densities of several microbial groups, although without changing the order of their population sizes. In the short term, fire produced a sharp increase in microbes but affected the groups studied differently. Aerobic heterotrophic bacteria, including the acidophilic and sporulating ones, were stimulated by fire while cyanobacteria, algae and fungi (propagules as well as hyphae length) were clearly depressed. In the long term, the positive effect of fire on bacteria was nullified except on the sporulating ones; fungal propagules, but not mycelium, reached the unburned soil values, cyanobacteria and algae also increased. Soil incubation both improved the beneficial and diminished the negative fire effect on the microbiota.     

Evolution of cross-feeding in microbial populations

Although limited by a single resource, microbial populations that grow for long periods in continuous culture (chemostat) frequently evolve stable polymorphisms. These polymorphisms may be maintained by cross-feeding, where one strain partially degrades the primary energy resource and excretes an intermediate that is used as an energy resource by a second strain. It is unclear what selective advantage cross-feeding strains have over a single competitor that completely degrades the primary resource. Here we show that cross-feeding may evolve in microbial populations as a consequence of the following optimization principles: the rate of ATP production is maximized, the concentration of enzymes of the pathway is minimized, and the concentration of intermediates of the pathway is minimized.     

Forward-time simulations of non-random mating populations using simuPOP

Computer simulations play an important role in studies of non-random mating populations. Because of implementation difficulties, only very limited types of non-random mating schemes are provided in the currently available simulation programs. Starting with version 0.8.5, simuPOP provides a few mating schemes that can be used to simulate arbitrary non-random mating models. This article describes the concepts and methods behind these mating schemes and demonstrates their uses in a few examples, including partial self-mating, positive assortative mating, non-random outbreeding, and simulation of overlapping generations in age-structured populations. AVAILABILITY: simuPOP is freely available at http://simupop.sourceforge.net, distributed under a GPL license. Cited examples are in the doc/cookbook directory of a simuPOP distribution.     

Forward-time simulations of human populations with complex diseases

Due to the increasing power of personal computers, as well as the availability of flexible forward-time simulation programs like simuPOP, it is now possible to simulate the evolution of complex human diseases using a forward-time approach. This approach is potentially more powerful than the coalescent approach since it allows simulations of more than one disease susceptibility locus using almost arbitrary genetic and demographic models. However, the application of such simulations has been deterred by the lack of a suitable simulation framework. For example, it is not clear when and how to introduce disease mutants—especially those under purifying selection—to an evolving population, and how to control the disease allele frequencies at the last generation. In this paper, we introduce a forward-time simulation framework that allows us to generate large multi-generation populations with complex diseases caused by unlinked disease susceptibility loci, according to specified demographic and evolutionary properties. Unrelated individuals, small or large pedigrees can be drawn from the resulting population and provide samples for a wide range of study designs and ascertainment methods. We demonstrate our simulation framework using three examples that map genes associated with affection status, a quantitative trait, and the age of onset of a hypothetical cancer, respectively. Nonadditive fitness models, population structure, and gene–gene interactions are simulated. Case-control, sibpair, and large pedigree samples are drawn from the simulated populations and are examined by a variety of gene-mapping methods.     

Rapid quantitative profiling of complex microbial populations

Diverse and complex microbial ecosystems are found in virtually every environment on earth, yet we know very little about their composition and ecology. Comprehensive identification and quantification of the constituents of these microbial communities—a ‘census’—is an essential foundation for understanding their biology. To address this problem, we developed, tested and optimized a DNA oligonucleotide microarray composed of 10 462 small subunit (SSU) ribosomal DNA (rDNA) probes (7167 unique sequences) selected to provide quantitative information on the taxonomic composition of diverse microbial populations. Using our optimized experimental approach, this microarray enabled detection and quantification of individual bacterial species present at fractional abundances of <0.1% in complex synthetic mixtures. The estimates of bacterial species abundance obtained using this microarray are similar to those obtained by phylogenetic analysis of SSU rDNA sequences from the same samples—the current ‘gold standard’ method for profiling microbial communities. Furthermore, probes designed to represent higher order taxonomic groups of bacterial species reliably detected microbes for which there were no species-specific probes. This simple, rapid microarray procedure can be used to explore and systematically characterize complex microbial communities, such as those found within the human body.     

Failure of antibiotic treatment in microbial populations

The tolerance of bacterial populations to biocidal or antibiotic treatment has been well documented in both biofilm and planktonic settings. However, there is still very little known about the mechanisms that produce this tolerance. Evidence that small, non-mutant subpopulations of bacteria are not affected by an antibiotic challenge has been accumulating and provides an attractive explanation for the failure of typical dosing protocols. Although a dosing challenge can kill the susceptible bacteria, the remaining persister cells can serve as a source of population regrowth. We give a condition for the failure of a periodic dosing protocol for a general chemostat model, which supports the simulations of an earlier, more specialized batch model. Our condition implies that the treatment protocol fails globally, in the sense that a mixed bacterial population will ultimately persist above a level that is independent of the initial composition of the population. We also give a sufficient condition for treatment success, at least for initial population compositions near the steady state of interest, corresponding to bacterial washout. Finally, we investigate how the speed at which the bacteria are wiped out depends on the duration of administration of the antibiotic. We find that this dependence is not necessarily monotone, implying that optimal dosing does not necessarily correspond to continuous administration of the antibiotic. Thus, genuine periodic protocols can be more advantageous in treating a wide variety of bacterial infections.      

Retention of cryptic genes in microbial populations

Cryptic genes are silenced genes that can still be reactivated by mutation. Since they can make no positive contribution to the fitness of their carriers, it is not clear why many cryptic genes in microbial populations have not degenerated into useless DNA sequences. Hall et al. (1983) have suggested that cryptic genes have persisted because of occasional strong environmental selection for reactivated genes. The present mathematical study supports their suggestion. It shows that a cryptic gene can be retained without having any selective advantage over a useless DNA sequence, if selection for the reactivated gene occasionally occurs for a substantially long time.      

Toward a self-similar theory of microbial populations

A fresh quest is made of segregated cell models of microbial populations with a view to determine whether the multivarite distribution of physiological states, during transient growth, can attain self-similar forms (i.e., become time invariant) when each physiological state variable is scaled with respect to its population average. Such self-similar growth situations are believed to be more general than those of balanced growth. The conditions under which self-similarity is possible are investigated. Thus conditions are stipulated on the synthesis rates of different physiological entities, cell division rate, and the partitioning of the parent cell's components among the daughter cells (assuming binary division) in order for self-similar growth to be attained. Subject to the attainment of self-similar growth, it is shown that cytometric data can be analyzed systematically to determine how the rates of syntheses of various biochemical entities and cell division rates vary with the physiological entities that are measured. Inverse problems, represented by algebraic systems, are identified which will potentially allow flow cytometric data to be inverted to yield quantitative information on the absolute rates of cellular growth and reproductory processes as a function of the cell states chosen for measurement. It is suggested that the methods become more effective when cytometry can be used to make direct observations on dividing cells so that the number of unknowns in the inverse problem can be reduced, thus facilitating its more complete solution. Preliminary analysis of cytometric data obtained in the literature show promise of self-similarity and thus the possibility of application of the methods discussed here. (c) 1994 John Wiley & Sons, Inc.     

Enumeration of denitrifying microbial populations in turf

Summary Denitrifer populations of a silt and silt loam soil under a Kentucky bluegrass turf were enumerated using the most probable number (MPN) procedure. The influence of soil texture, soil depth, soil moisture, and additions of nitrate fertilizer on denitrifier populations were determined. Saturated soil conditions increased denitrifier populations 87-fold in the silt soil and 121-fold in the silt loam soil. Denitrifier populations did not differ significantly between soil depths and additions of fertilizer nitrate did not influence populations.     

Response of microbial populations to environmental disturbance

Taxonomic and genetic diversities of microbial communities disturbed by chemical pollutants were lower than in undisturbed reference communities. The dominant populations within the disturbed communities had enhanced physiological tolerances and substrate utilization capabilities, indicating that generalized physiological versatility is an adaptive characteristic of populations that successfully compete within disturbed communities.     

Transient response of bienzyme electrodes

A mathematical model of the transient response of amperometric bienzyme electrodes with a consecutive cyclic and parallel substrate conversion is developed. At high catalytic activity the kinetic behavior of consecutive and parallel conversion is close to the substance diffusion through the inert membrane, and the kinetics of cyclic conversion are 3.54 times slower. At low substrate conversion rates the electrodes' response is markedly retarded. Mathematical modeling results are compared with the experimental data on the kinetic behavior of amperometric enzyme electrodes in the membranes of which the consecutive and cyclic conversions of glucose and nicotinamide adenine dinucleotide, respectively, take place.     

Transient dominant selection of recombinant vaccinia viruses.

A general method for constructing and selecting recombinant vaccinia viruses with insertions, deletions, or mutations in any gene that is similar in principle to one originally devised for Saccharomyces cerevisiae (S. Scherer and R. W. Davis, Proc. Natl. Acad. Sci. USA 76:4951-4955, 1979) is described. The selectable marker used, Escherichia coli guanine phosphoribosyltransferase, is not retained within the final recombinant virus, and hence, this procedure may be used serially to introduce several foreign genes or to make multiple site-directed mutations.     

Use of computer simulations in microbial and molecular genetics

The development of five computer programs in microbial and molecular genetics is described. Four of these are simulations of genetic and physical mapping experiments, designed to give students experience in generating and analysing meaningful data, and to help in the consolidation of the concepts underlying the simulation. They should be used after the experiment proper has been performed, rather than as a substitute for it. The fifth is an interactive learning program on the genetic coding mechanism.     

Adaptive response of microbial communities to soluble microbial products

We carried out two experiments to study the influence of soluble microbial products (SMP) on biomass concentration [defined as mixed liquor suspended solids (MLSS)] and removal of soluble biological and chemical oxygen demands (sBOD₅ and sCOD): (1) SMP were allowed to accumulate, and (2) SMP content was artificially reduced by washing the biomass. The daily initial sCOD in both experiments was kept constant at 859±6 mg/l for 16 days. In experiment 1, the highest sCOD removal (80%) occurred during the first day. Thereafter, it decreased successively to 40% [sludge retention time (SRT), 12 days], after which it increased steadily to 50±4%. Variations in residual sCOD were accompanied by variations in sBOD₅, showing that the biodegradability of the accumulated SMP components was changing. MLSS fluctuated within the range 1,200±25–1,993±58 mg/l. We attributed the irregular accumulation of the biomass to variations in the biodegradability of SMP components. The initial sBOD₅/MLSS ratio varied according to variations in initial sBOD₅ and MLSS, whereas the residual ratio was constant at 0.025±0.008. This indicated a direct relationship between the concentrations of biomass and SMP produced. In experiment 2, MLSS increased from 1,200±25 to a constant value (2,810±16 mg/l; SRT, 12 days). After this time, no decrease or increase in MLSS was observed. Correspondingly, sCOD and sBOD₅ removal increased from 80–97 to 84–99%. A stable microbial community that could consume organic matter efficiently was developed under these conditions.     

Competition for mixed substrates by microbial populations

A model for the growth of an organism on multiple substrates was developed, assuming that each substrate has a competitive inhibition effect on the uptake of other substrates. The model was extended to examine mixed substrates, showing that the coexistence of several species at steady state in continuous cultures is possible, even when all the organisms all strongly prefer the one substrate. The diversity of nutrient sources in a real system may be a key factor in supporting a heterogeneous microbial population.