Microbial evolution in laboratory environments

Metabolic cooperation between conspecific genotypic groups contributes to bacterial fitness

Microbial interactions are important for the survival of species and the stability of the microbial ecosystem. Although bacteria have diverse conspecific genotypes in the natural microbial ecosystem, little is known about whether wild-type strains within species would interact with each other and how the intraspecific interaction influences the growth of the species. In this work, using Lactobacillus acetotolerans, a dominant species with diverse conspecific genotypes in natural food fermentation ecosystems as a case, we studied the interactions between different genotypic groups of this species. In interspecific and intraspecific pairwise cocultures, the growth of L. acetotolerans decreased, but the increase of the phylogenetic similarity would reduce this negative effect, indicating a potential intraspecific interaction of this species. Meanwhile, the strain classification method affected the analysis of intraspecific interactions, which can be efficiently demonstrated using 99.5% average nucleotide identity (ANI) as the strain-level classification method. Using this ANI classification method, we revealed the population fitness significantly increased in cocultures of different genotypic groups. Facilitation involving 11 amino acids was identified between different ANI genotypic groups, which was beneficial for increasing population fitness. This work revealed that wild-type conspecific strains could interact with each other via cooperative metabolic changes and benefit each other to increase fitness. It shed new light on the survival and stability of species in natural microbial ecosystems.

Experimental Evolution Reveals Favored Adaptive Routes to Cell Aggregation in Yeast

Yeast flocculation is a community-building cell aggregation trait that is an important mechanism of stress resistance and a useful phenotype for brewers; however, it is also a nuisance in many industrial processes, in clinical settings, and in the laboratory. Chemostat-based evolution experiments are impaired by inadvertent selection for aggregation, which we observe in 35% of populations. These populations provide a testing ground for understanding the breadth of genetic mechanisms Saccharomyces cerevisiae uses to flocculate, and which of those mechanisms provide the biggest adaptive advantages. In this study, we employed experimental evolution as a tool to ask whether one or many routes to flocculation are favored, and to engineer a strain with reduced flocculation potential. Using a combination of whole genome sequencing and bulk segregant analysis, we identified causal mutations in 23 independent clones that had evolved cell aggregation during hundreds of generations of chemostat growth. In 12 of those clones, we identified a transposable element insertion in the promoter region of known flocculation gene FLO1, and, in an additional five clones, we recovered loss-of-function mutations in transcriptional repressor TUP1, which regulates FLO1 and other related genes. Other causal mutations were found in genes that have not been previously connected to flocculation. Evolving a flo1 deletion strain revealed that this single deletion reduces flocculation occurrences to 3%, and demonstrated the efficacy of using experimental evolution as a tool to identify and eliminate the primary adaptive routes for undesirable traits.

Spatially-resolved metabolic cooperativity within dense bacterial colonies

Background

The exchange of metabolites and the reprogramming of metabolism in response to shifting microenvironmental conditions can drive subpopulations of cells within colonies toward divergent behaviors. Understanding the interactions of these subpopulations—their potential for competition as well as cooperation—requires both a metabolic model capable of accounting for a wide range of environmental conditions, and a detailed dynamic description of the cells’ shared extracellular space.

Results

Here we show that a cell’s position within an in silicoEscherichia coli colony grown on glucose minimal agar can drastically affect its metabolism: “pioneer” cells at the outer edge engage in rapid growth that expands the colony, while dormant cells in the interior separate two spatially distinct subpopulations linked by a cooperative form of acetate crossfeeding that has so far gone unnoticed. Our hybrid simulation technique integrates 3D reaction-diffusion modeling with genome-scale flux balance analysis (FBA) to describe the position-dependent metabolism and growth of cells within a colony. Our results are supported by imaging experiments involving strains of fluorescently-labeled E. coli. The spatial patterns of fluorescence within these experimental colonies identify cells with upregulated genes associated with acetate crossfeeding and are in excellent agreement with the predictions. Furthermore, the height-to-width ratios of both the experimental and simulated colonies are in good agreement over a growth period of 48 hours.

Conclusions

Our modeling paradigm can accurately reproduce a number of known features of E. coli colony growth, as well as predict a novel one that had until now gone unrecognized. The acetate crossfeeding we see has a direct analogue in a form of lactate crossfeeding observed in certain forms of cancer, and we anticipate future application of our methodology to models of tissues and tumors.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0155-1) contains supplementary material, which is available to authorized users.

The functional basis of adaptive evolution in chemostats

Two of the central problems in biology are determining the molecular basis of adaptive evolution and understanding how cells regulate their growth. The chemostat is a device for culturing cells that provides great utility in tackling both of these problems: it enables precise control of the selective pressure under which organisms evolve and it facilitates experimental control of cell growth rate. The aim of this review is to synthesize results from studies of the functional basis of adaptive evolution in long-term chemostat selections using Escherichia coli and Saccharomyces cerevisiae. We describe the principle of the chemostat, provide a summary of studies of experimental evolution in chemostats, and use these studies to assess our current understanding of selection in the chemostat. Functional studies of adaptive evolution in chemostats provide a unique means of interrogating the genetic networks that control cell growth, which complements functional genomic approaches and quantitative trait loci (QTL) mapping in natural populations. An integrated approach to the study of adaptive evolution that accounts for both molecular function and evolutionary processes is critical to advancing our understanding of evolution. By renewing efforts to integrate these two research programs, experimental evolution in chemostats is ideally suited to extending the functional synthesis to the study of genetic networks.

Experimental microbial evolution: history and conceptual underpinnings

We chronicle and dissect the history of the field of Experimental Microbial Evolution, beginning with work by Monod. Early research was largely carried out by microbiologists and biochemists, who used experimental evolutionary change as a tool to understand structure-function relationships. These studies attracted the interest of evolutionary biologists who recognized the power of the approach to address issues such as the tempo of adaptive change, the costs and benefits of sex, parallelism, and the role which contingency plays in the evolutionary process. In the 1980s and 1990s, an ever-expanding body of microbial, physiological and biochemical data, together with new technologies for manipulating microbial genomes, allowed such questions to be addressed in ever-increasing detail. Since then, technological advances leading to low-cost, high-throughput DNA sequencing have made it possible for these and other fundamental questions in evolutionary biology to be addressed at the molecular level.

Potential impact of antimicrobial resistance in wildlife, environment and human health

Given the significant spatial and temporal heterogeneity in antimicrobial resistance distribution and the factors that affect its evolution, dissemination, and persistence, it is important to highlight that antimicrobial resistance must be viewed as an ecological problem. Monitoring the resistance prevalence of indicator bacteria such as Escherichia coli and enterococci in wild animals makes it possible to show that wildlife has the potential to serve as an environmental reservoir and melting pot of bacterial resistance. These researchers address the issue of antimicrobial-resistant microorganism proliferation in the environment and the related potential human health and environmental impact.

A mechanistic explanation linking adaptive mutation, niche change, and fitness advantage for the wrinkly spreader

Experimental evolution studies have investigated adaptive radiation in static liquid microcosms using the environmental bacterium Pseudomonas fluorescens SBW25. In evolving populations a novel adaptive mutant known as the Wrinkly Spreader arises within days having significant fitness advantage over the ancestral strain. A molecular investigation of the Wrinkly Spreader has provided a mechanistic explanation linking mutation with fitness improvement through the production of a cellulose-based biofilm at the air-liquid interface. Colonisation of this niche provides greater access to oxygen, allowing faster growth than that possible for non-biofilm-forming competitors located in the lower anoxic region of the microcosm. Cellulose is probably normally used for attachment to plant and soil aggregate surfaces and to provide protection in dehydrating conditions. However, the evolutionary innovation of the Wrinkly Spreader in static microcosms is the use of cellulose as the matrix of a robust biofilm, and is achieved through mutations that deregulate multiple diguanylate cyclases leading to the over-production of cyclic-di-GMP and the stimulation of cellulose expression. The mechanistic explanation of the Wrinkly Spreader success is an exemplar of the modern evolutionary synthesis, linking molecular biology with evolutionary ecology, and provides an insight into the phenomenal ability of bacteria to adapt to novel environments.

Experimental evolution reveals genome-wide spectrum and dynamics of mutations in the rice blast fungus, Magnaporthe oryzae

Knowledge on mutation processes is central to interpreting genetic analysis data as well as understanding the underlying nature of almost all evolutionary phenomena. However, studies on genome-wide mutational spectrum and dynamics in fungal pathogens are scarce, hindering our understanding of their evolution and biology. Here, we explored changes in the phenotypes and genome sequences of the rice blast fungus Magnaporthe oryzae during the forced in vitro evolution by weekly transfer of cultures on artificial media. Through combination of experimental evolution with high throughput sequencing technology, we found that mutations accumulate rapidly prior to visible phenotypic changes and that both genetic drift and selection seem to contribute to shaping mutational landscape, suggesting the buffering capacity of fungal genome against mutations. Inference of mutational effects on phenotypes through the use of T-DNA insertion mutants suggested that at least some of the DNA sequence mutations are likely associated with the observed phenotypic changes. Furthermore, our data suggest oxidative damages and UV as major sources of mutation during subcultures. Taken together, our work revealed important properties of original source of variation in the genome of the rice blast fungus. We believe that these results provide not only insights into stability of pathogenicity and genome evolution in plant pathogenic fungi but also a model in which evolution of fungal pathogens in natura can be comparatively investigated.

Natural genetic variation in yeast longevity

The genetics of aging in the yeast Saccharomyces cerevisiae has involved the manipulation of individual genes in laboratory strains. We have instituted a quantitative genetic analysis of the yeast replicative lifespan by sampling the natural genetic variation in a wild yeast isolate. Haploid segregants from a cross between a common laboratory strain (S288c) and a clinically derived strain (YJM145) were subjected to quantitative trait locus (QTL) analysis, using 3048 molecular markers across the genome. Five significant, replicative lifespan QTL were identified. Among them, QTL 1 on chromosome IV has the largest effect and contains SIR2, whose product differs by five amino acids in the parental strains. Reciprocal gene swap experiments showed that this gene is responsible for the majority of the effect of this QTL on lifespan. The QTL with the second-largest effect on longevity was QTL 5 on chromosome XII, and the bulk of the underlying genomic sequence contains multiple copies (100–150) of the rDNA. Substitution of the rDNA clusters of the parental strains indicated that they play a predominant role in the effect of this QTL on longevity. This effect does not appear to simply be a function of extrachromosomal ribosomal DNA circle production. The results support an interaction between SIR2 and the rDNA locus, which does not completely explain the effect of these loci on longevity. This study provides a glimpse of the complex genetic architecture of replicative lifespan in yeast and of the potential role of genetic variation hitherto unsampled in the laboratory.

Stock culture heterogeneity rather than new mutational variation complicates short-term cell physiology studies of Escherichia coli K-12 MG1655 in continuous culture

Nutrient-limited continuous cultures in chemostats have been used to study microbial cell physiology for over 60 years. Genome instability and genetic heterogeneity are possible uncontrolled factors in continuous cultivation experiments. We investigated these issues by using high-throughput (HT) DNA sequencing to characterize samples from different phases of a glucose-limited accelerostat (A-stat) experiment with Escherichia coli K-12 MG1655 and a duration regularly used in cell physiology studies (20 generations of continuous cultivation). Seven consensus mutations from the reference sequence and five subpopulations characterized by different mutations were detected in the HT-sequenced samples. This genetic heterogeneity was confirmed to result from the stock culture by Sanger sequencing. All the subpopulations in which allele frequencies increased (betA, cspG/cspH, glyA) during the experiment were also present at the end of replicate A-stats, indicating that no new subpopulations emerged during our experiments. The fact that ~31 % of the cells in our initial cultures obtained directly from a culture stock centre were mutants raises concerns that even if cultivations are started from single colonies, there is a significant chance of picking a mutant clone with an altered phenotype. Our results show that current HT DNA sequencing technology allows accurate subpopulation analysis and demonstrates that a glucose-limited E. coli K-12 MG1655 A-stat experiment with a duration of tens of generations is suitable for studying cell physiology and collecting quantitative data for metabolic modelling without interference from new mutations.

Optimality models in the age of experimental evolution and genomics

Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimental context with a well-researched organism allows dissection of the evolutionary process to identify causes of model failure--whether the model is wrong about genetics or selection. Second, optimality models provide a meaningful context for the process and mechanics of evolution, and thus may be used to elicit realistic genetic bases of adaptation--an especially useful augmentation to well-researched genetic systems. A few studies of microbes have begun to pioneer this new direction. Incompatibility between the assumed and actual genetics has been demonstrated to be the cause of model failure in some cases. More interestingly, evolution at the phenotypic level has sometimes matched prediction even though the adaptive mutations defy mechanisms established by decades of classic genetic studies. Integration of experimental evolutionary tests with genetics heralds a new wave for optimality models and their extensions that does not merely emphasize the forces driving evolution.

Experimental evolution in yeast: a practical guide

Experimental evolution refers to a broad range of studies in which selection pressures are applied to populations. In some applications, particular traits are desired, while in others the subject of study is the mechanisms of evolution or the different modes of behavior between systems. This chapter will explore the range of studies falling under the experimental evolution umbrella, and their relative merits for different types of applications. Practical aspects of experimental evolution will also be discussed, including commercial suppliers, analysis methods, and best laboratory practices.

Adaptive evolution of a lactose-consuming Saccharomyces cerevisiae recombinant

The construction of Saccharomyces cerevisiae strains that ferment lactose has biotechnological interest, particularly for cheese whey fermentation. A flocculent lactose-consuming S. cerevisiae recombinant expressing the LAC12 (lactose permease) and LAC4 (beta-galactosidase) genes of Kluyveromyces lactis was constructed previously but showed poor efficiency in lactose fermentation. This strain was therefore subjected to an evolutionary engineering process (serial transfer and dilution in lactose medium), which yielded an evolved recombinant strain that consumed lactose twofold faster, producing 30% more ethanol than the original recombinant. We identified two molecular events that targeted the LAC construct in the evolved strain: a 1,593-bp deletion in the intergenic region (promoter) between LAC4 and LAC12 and a decrease of the plasmid copy number by about 10-fold compared to that in the original recombinant. The results suggest that the intact promoter was unable to mediate the induction of the transcription of LAC4 and LAC12 by lactose in the original recombinant and that the deletion established the transcriptional induction of both genes in the evolved strain. We propose that the tuning of the expression of the heterologous LAC genes in the evolved recombinant was accomplished by the interplay between the decreased copy number of both genes and the different levels of transcriptional induction for LAC4 and LAC12 resulting from the changed promoter structure. Nevertheless, our results do not exclude other possible mutations that may have contributed to the improved lactose fermentation phenotype. This study illustrates the usefulness of simple evolutionary engineering approaches in strain improvement. The evolved strain efficiently fermented threefold-concentrated cheese whey, providing an attractive alternative for the fermentation of lactose-based media.

The spread of a beneficial mutation in experimental bacterial populations: the influence of the environment and genotype on the fixation of rpoS mutations

The spread of beneficial mutations through populations is at the core of evolutionary change. A long-standing hindrance to understanding mutational sweeps was that beneficial mutations have been slow to be identified, even in commonly studied experimental populations. The lack of information on what constitutes a beneficial mutation has led to many uncertainties about the frequency, fitness benefit and fixation of beneficial mutations. A more complete picture is currently emerging for a limited set of identified mutations in bacterial populations. In turn, this will allow quantitation of several features of mutational sweeps. Most importantly, the 'benefit' of beneficial mutations can now be explained in terms of physiological function and how variations in the environment change the selectability of mutations. Here, the sweep of rpoS mutations in Escherichia coli, in both experimental and natural populations, is described in detail. These studies reveal the subtleties of physiology and regulation that strongly influence the benefit of a mutation and explain differences in sweeps between strains and between various environments.

Bacterial physiology, regulation and mutational adaptation in a chemostat environment

The chemostat was devised over 50 years ago and rapidly adopted for studies of bacterial physiology and mutation. Despite the long history and earlier analyses, the complexity of events in continuous cultures is only now beginning to be resolved. The application of techniques for following regulatory and mutational changes and the identification of mutated genes in chemostat populations has provided new insights into bacterial behaviour. Inoculation of bacteria into a chemostat culture results in a population competing for a limiting amount of a particular resource. Any utilizable carbon source or ion can be a limiting nutrient and bacteria respond to limitation through a regulated nutrient-specific hunger response. In addition to transcriptional responses to nutrient limitation, a second regulatory influence in a chemostat culture is the reduced growth rate fixed by the dilution rate in individual experiments. Sub-maximal growth rates and hunger result in regulation involving sigma factors and alarmones like cAMP and ppGpp. Reduced growth rate also results in increased mutation frequencies. The combination of a strongly selective environment (where mutants able to compete for limiting nutrient have a major fitness advantage) and elevated mutation rates (both endogenous and through the secondary enrichment of mutators) results in a population that changes rapidly and persistently over many generations. Contrary to common belief, the chemostat environment is never in "steady state" with fixed bacterial characteristics usable for clean comparisons of physiological or regulatory states. Adding to the complexity, chemostat populations do not simply exhibit a succession of mutational sweeps leading to a dominant winner clone. Instead, within 100 generations large populations become heterogeneous and evolving bacteria adopt alternative, parallel fitness strategies. Transport physiology, metabolism and respiration, as well as growth yields, are highly diverse in chemostat-evolved bacteria. The rich assortment of changes in an evolving chemostat provides an excellent experimental system for understanding bacterial evolution. The adaptive radiation or divergence of populations into a collection of individuals with alternative solutions to the challenge of chemostat existence provides an ideal model system for testing evolutionary and ecological theories on adaptive radiations and the generation of bacterial diversity.

Community dynamics and heterogeneities in mixed bacterial communities subjected to nutrient periodicities

Sixteen replicate microcosms were inoculated with a mixed assemblage of heterotrophic bacteria and provided with discrete pulses of protein as carbon and energy source. The dynamics of community structure were monitored by 16S rRNA gene polymerase chain reaction denaturant gradient gel electrophoresis (PCR-DGGE). The results were consistent with a strong role for biological interactions in maintaining diversity. Replicate microcosms developed different microbial communities. For systems exposed to nutrient pulses every 7 days, the number of DGGE bands averaged 13 +/- 4 (mean +/- SD) and the Dice similarity coefficient between pairs ranged from 0.08 to 0.67. In each of 16 systems provided protein once each day, there were dynamic changes over the first 30 days but community composition was stable over the next 20 days. However, most systems differed from each other; two-thirds of the pairwise comparisons had similarity coefficients in the range of 0.35-0.63. These 16 systems contained 10 +/- 2 phylotypes (mean +/- SD) and in aggregate 34 phylotypes were found in the 16 systems. Most phylotypes were found in < 25% of the systems, and there were not strong networks of association among phylotypes.

Engineering cell physiology to enhance recombinant protein production in Escherichia coli

The advent of recombinant DNA technology has revolutionized the strategies for protein production. Due to the well-characterized genome and a variety of mature tools available for genetic manipulation, Escherichia coli is still the most common workhorse for recombinant protein production. However, the culture for industrial applications often presents E. coli cells with a growth condition that is significantly different from their natural inhabiting environment in the gastrointestinal tract, resulting in deterioration in cell physiology and limitation in cell's productivity. It has been recognized that innovative design of genetically engineered strains can highly increase the bioprocess yield with minimum investment on the capital and operating costs. Nevertheless, most of these genetic manipulations, by which traits are implanted into the workhorse through recombinant DNA technology, for enhancing recombinant protein productivity often translate into the challenges that deteriorate cell physiology or even jeopardize cell survival. An in-depth understanding of these challenges and their corresponding cellular response at the molecular level becomes crucial for developing superior strains that are more physiologically adaptive to the production environment to improve culture productivity. With the accumulated knowledge in cell physiology, whose importance to gene overexpression was to some extent undervalued previously, this review is intended to focus on the recent biotechnological advancement in engineering cell physiology to enhance recombinant protein production in E. coli.

Environmental stress and antibiotic resistance in food-related pathogens

This study investigated the possibility that sublethal food preservation stresses (high or low temperature and osmotic and pH stress) can lead to changes in the nature and scale of antibiotic resistance (ABR) expressed by three food-related pathogens (Escherichia coli, Salmonella enterica serovar Typhimurium, and Staphylococcus aureus). The study found that some sublethal stresses significantly altered antibiotic resistance. Incubation at sublethal high temperature (45 degrees C) decreased ABR. Incubation under increased salt (>4.5%) or reduced pH (<5.0) conditions increased ABR. Some of the pathogens continued to express higher levels of ABR after removal of stress, suggesting that in some cases the applied sublethal stress had induced stable increases in ABR. These results indicate that increased use of bacteriostatic (sublethal), rather than bactericidal (lethal), food preservation systems may be contributing to the development and dissemination of ABR among important food-borne pathogens.

E. coli microcosms indicate a tight link between predictability of ecosystem dynamics and diversity

The diversity-stability hypothesis proposes that ecosystem diversity is positively correlated with stability. The impact of ecosystem diversity is, however, still debated. In a microcosm experiment using diverged Escherichia coli cells, we show that the fitness of community members depends on the complexity (number of participants) of the system. Interestingly, the spread of a community member with a superior genotype is mostly stochastic in low-complexity systems, but highly deterministic in a more complex environment. We conclude that system complexity provides a buffer against stochastic effects.

The impact of diversity loss on the stability of ecosystems is a central issue in ecology. In today's world the continuous reduction in number of species, subspecies, and locally adapted populations, often with anthropogenic causes, turns it into a matter with increased significance for the scientific community. However, a longstanding debate about the importance of variability of a system for its stability has evoked many theoretical and empirical studies. Here the authors introduce a new approach using experimental bacterial microcosms to address this question. For this study stability is defined as nonstochastic, reproducible population dynamics. The authors started with a low-diversity population and let it diversify until an adaptive event occurred. The superior genotype gradually out-competed all other competitors resulting in a selective sweep. This adaptive event served as reference “state” to test the resilience of the system. The authors investigated the reproducibility of the dynamic with competition experiments by gradual disassembly of the community. Their findings showed an increase in fitness of the superior genotype and less variation among replicate experiments with increasing complexity (number of competitors) of the system. The main implication of this study is that diversity buffers against stochastic effects.

Why is metabolic labour divided in nitrification?

Winogradsky discovered in 1890 that nitrification is carried out in two consecutive steps by two distinct groups of bacteria: ammonia-oxidizing bacteria and nitrite-oxidizing bacteria. An explanation for this division of labour is offered based on the kinetic theory of optimal design of metabolic pathways, which postulates the existence of an optimal length for a pathway that maximizes the rate of ATP production. Shortening long pathways could, therefore, increase growth rate. However, this would reduce growth yield if the shorter pathway has fewer ATP-generating steps. High yields would be advantageous when bacteria grow in clonal clusters, as is typical for biofilms. It is postulated that bacteria that completely oxidize ammonia to nitrate exist in such environments.

Clonal interference and the periodic selection of new beneficial mutations in Escherichia coli

The conventional model of adaptation in asexual populations implies sequential fixation of new beneficial mutations via rare selective sweeps that purge all variation and preserve the clonal genotype. However, in large populations multiple beneficial mutations may co-occur, causing competition among them, a phenomenon called "clonal interference." Clonal interference is thus expected to lead to longer fixation times and larger fitness effects of mutations that ultimately become fixed, as well as to a genetically more diverse population. Here, we study the significance of clonal interference in populations consisting of mixtures of differently marked wild-type and mutator strains of Escherichia coli that adapt to a minimal-glucose environment for 400 generations. We monitored marker frequencies during evolution and measured the competitive fitness of random clones from each marker state after evolution. The results demonstrate the presence of multiple beneficial mutations in these populations and slower and more erratic invasion of mutants than expected by the conventional model, showing the signature of clonal interference. We found that a consequence of clonal interference is that fitness estimates derived from invasion trajectories were less than half the magnitude of direct estimates from competition experiments, thus revealing fundamental problems with this fitness measure. These results force a reevaluation of the conventional model of periodic selection for asexual microbes.

Genetic analysis and attribution of microbial forensics evidence

Because of the availability of pathogenic microorganisms and the relatively low cost of preparing and disseminating bioweapons, there is a continuing threat of biocrime and bioterrorism. Thus, enhanced capabilities are needed that enable the full and robust forensic exploitation and interpretation of microbial evidence from acts of bioterrorism or biocrimes. To respond to the need, greater resources and efforts are being applied to the burgeoning field of microbial forensics. Microbial forensics focuses on the characterization, analysis and interpretation of evidence for attributional purposes from a bioterrorism act, biocrime, hoax or inadvertent agent release. To enhance attribution capabilities, a major component of microbial forensics is the analysis of nucleic acids to associate or eliminate putative samples. The degree that attribution can be addressed depends on the context of the case, the available knowledge of the genetics, phylogeny, and ecology of the target microorganism, and technologies applied. The types of genetic markers and features that can impact statistical inferences of microbial forensic evidence include: single nucleotide polymorphisms, repetitive sequences, insertions and deletions, mobile elements, pathogenicity islands, virulence and resistance genes, house keeping genes, structural genes, whole genome sequences, asexual and sexual reproduction, horizontal gene transfer, conjugation, transduction, lysogeny, gene conversion, recombination, gene duplication, rearrangements, and mutational hotspots. Nucleic acid based typing technologies include: PCR, real-time PCR, MLST, MLVA, whole genome sequencing, and microarrays.

Long-term survival during stationary phase: evolution and the GASP phenotype

The traditional view of the stationary phase of the bacterial life cycle, obtained using standard laboratory culture practices, although useful, might not always provide us with the complete picture. Here, the traditional three phases of the bacterial life cycle are expanded to include two additional phases: death phase and long-term stationary phase. In many natural environments, bacteria probably exist in conditions more akin to those of long-term stationary-phase cultures, in which the expression of a wide variety of stress-response genes and alternative metabolic pathways is essential for survival. Furthermore, stressful environments can result in selection for mutants that express the growth advantage in stationary phase (GASP) phenotype.

Evolutionary Feedback Mediated through Population Density, Illustrated with Viruses in Chemostats

A cornerstone of evolutionary ecology is that population density affects adaptation: r and K selection is the obvious example. The reverse is also appreciated: adaptation impacts population density. Yet, empirically demonstrating a direct connection between population density and adaptation is challenging. Here, we address both evolution and ecology of population density in models of viral (bacteriophage) chemostats. Chemostats supply nutrients for host cell growth, and the hosts are prey for viral reproduction. Two different chemostat designs have profoundly different consequences for viral evolution. If host and virus are confined to the same chamber, as in a predator-prey system, viral regulation of hosts feeds back to maintain low viral density (measured as infections per cell). Viral adaptation impacts host density but has a small effect on equilibrium viral density. More interesting are chemostats that supply the viral population with hosts from a virus-free refuge. Here, a type of evolutionary succession operates: adaptation at low viral density leads to higher density, but high density then favors competitive ability. Experiments support these models with both phenotypic and molecular data. Parallels to these designs exist in many natural systems, so these experimental systems may yield insights to the evolution and regulation of natural populations.

Latent pathway activation and increased pathway capacity enable Escherichia coli adaptation to loss of key metabolic enzymes

The ability of biological systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process at the molecular level. By quantifying metabolic fluxes and global mRNA abundance, we investigated the genetic and metabolic mechanisms that underlie adaptive evolution of four metabolic gene deletion mutants of Escherichia coli (delta pgi, delta ppc, delta pta, and delta tpi) in parallel evolution experiments of each mutant. The initial response to the gene deletions was flux rerouting through local bypass reactions or normally latent pathways. The principal effect of evolution was improved capacity of already active pathways, whereas new flux distributions were not observed. Combinatorial changes in capacity and pathway activation, however, led to different intracellular flux states that enabled evolution in three of the four parallel cases tested. The molecular bases of the evolved phenotypes were then elucidated by global mRNA transcript analyses. Activation of latent pathways and flux changes in the tricarboxylic acid cycle were found to correlate well with molecular changes at the transcriptional level. Flux alterations in other central metabolic pathways, in contrast, were apparently not connected to changes in the transcriptional network. These results give new insight into the dynamics of the evolutionary process by demonstrating the flexibility of the metabolic network of E. coli to compensate for genetic perturbations and the utility of combining multiple high throughput data sets to differentiate between causal and noncausal mechanistic changes.

Adaptive molecular evolution for 13,000 phage generations: a possible arms race

Bacteriophage phiX174 was evolved on a continuous supply of sensitive hosts for 180 days ( approximately 13,000 phage generations). The average rate of nucleotide substitution was nearly 0.2% (11 substitutions)/20 days, and, surprisingly, substitutions accumulated in a clock-like manner throughout the study, except for a low rate during the first 20 days. Rates of silent and missense substitutions varied over time and among genes. Approximately 40% of the 71 missense changes and 25% of the 58 silent changes have been observed in previous adaptations; the rate of parallel substitution was highest in the early phase of the evolution, but 7% of the later changes had evolved in previous studies of much shorter duration. Several lines of evidence suggest that most of the changes were adaptive, even many of the silent substitutions. The sustained, high rate of adaptive evolution for 180 days defies a model of adaptation to a constant environment. We instead suggest that continuing molecular evolution reflects a potentially indefinite arms race, stemming from high levels of co-infection and the resulting conflict among genomes competing within the same cell.