Comparative genomics and transcriptomics analysis of experimentally evolved Escherichia coli MC1000 in complex environments

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis ( M. tb ), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Importance

Understanding mechanisms of resistance and tolerance in Mycobacterium tuberculosis ( M. tb ) can help us develop new treatments that capitalize on M. tb 's vulnerabilities. Here we used transcriptomics to study both the regulation of biofilm formation in clinical isolates as well as how those regulatory systems adapt to new environments. We find that closely related clinical populations have diverse strategies for growth under biofilm conditions, and that genetic background plays a large role in determining the trajectory of evolution. These results have implications for future treatment strategies that may be informed by our knowledge of the evolutionary constraints on strain(s) from an individual infection. This work provides new information about the mechanisms of biofilm formation in M. tb and outlines a framework for population level approaches for studying bacterial adaptation.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

CRISPR Perturbation of Gene Expression Alters Bacterial Fitness under Stress and Reveals Underlying Epistatic Constraints

The evolution of antibiotic resistance has engendered an impending global health crisis that necessitates a greater understanding of how resistance emerges. The impact of nongenetic factors and how they influence the evolution of resistance is a largely unexplored area of research. Here we present a novel application of CRISPR-Cas9 technology for investigating how gene expression governs the adaptive pathways available to bacteria during the evolution of resistance. We examine the impact of gene expression changes on bacterial adaptation by constructing a library of deactivated CRISPR-Cas9 synthetic devices to tune the expression of a set of stress-response genes in Escherichia coli. We show that artificially inducing perturbations in gene expression imparts significant synthetic control over fitness and growth during stress exposure. We present evidence that these impacts are reversible; strains with synthetically perturbed gene expression regained wild-type growth phenotypes upon stress removal, while maintaining divergent growth characteristics under stress. Furthermore, we demonstrate a prevailing trend toward negative epistatic interactions when multiple gene perturbations are combined simultaneously, thereby posing an intrinsic constraint on gene expression underlying adaptive trajectories. Together, these results emphasize how CRISPR-Cas9 can be employed to engineer gene expression changes that shape bacterial adaptation, and present a novel approach to synthetically control the evolution of antimicrobial resistance.

Gene Expression Variability Underlies Adaptive Resistance in Phenotypically Heterogeneous Bacterial Populations

The root cause of the antibiotic resistance crisis is the ability of bacteria to evolve resistance to a multitude of antibiotics and other environmental toxins. The regulation of adaptation is difficult to pinpoint due to extensive phenotypic heterogeneity arising during evolution. Here, we investigate the mechanisms underlying general bacterial adaptation by evolving wild-type Escherichia coli populations to dissimilar chemical toxins. We demonstrate the presence of extensive inter- and intrapopulation phenotypic heterogeneity across adapted populations in multiple traits, including minimum inhibitory concentration, growth rate, and lag time. To search for a common response across the heterogeneous adapted populations, we measured gene expression in three stress-response networks: the mar regulon, the general stress response, and the SOS response. While few genes were differentially expressed, clustering revealed that interpopulation gene expression variability in adapted populations was distinct from that of unadapted populations. Notably, we observed both increases and decreases in gene expression variability upon adaptation. Sequencing select genes revealed that the observed gene expression trends are not necessarily attributable to genetic changes. To further explore the connection between gene expression variability and adaptation, we propagated single-gene knockout and CRISPR (clustered regularly interspaced short palindromic repeats) interference strains and quantified impact on adaptation to antibiotics. We identified significant correlations that suggest genes with low expression variability have greater impact on adaptation. This study provides evidence that gene expression variability can be used as an indicator of bacterial adaptive resistance, even in the face of the pervasive phenotypic heterogeneity underlying adaptation.

Bacterial transcriptome reorganization in thermal adaptive evolution

Background

Evolution optimizes a living system at both the genome and transcriptome levels. Few studies have investigated transcriptome evolution, whereas many studies have explored genome evolution in experimentally evolved cells. However, a comprehensive understanding of evolutionary mechanisms requires knowledge of how evolution shapes gene expression. Here, we analyzed Escherichia coli strains acquired during long-term thermal adaptive evolution.

Results

Evolved and ancestor Escherichia coli cells were exponentially grown under normal and high temperatures for subsequent transcriptome analysis. We found that both the ancestor and evolved cells had comparable magnitudes of transcriptional change in response to heat shock, although the evolutionary progression of their expression patterns during exponential growth was different at either normal or high temperatures. We also identified inverse transcriptional changes that were mediated by differences in growth temperatures and genotypes, as well as negative epistasis between genotype—and heat shock-induced transcriptional changes. Principal component analysis revealed that transcriptome evolution neither approached the responsive state at the high temperature nor returned to the steady state at the regular temperature. We propose that the molecular mechanisms of thermal adaptive evolution involve the optimization of steady-state transcriptomes at high temperatures without disturbing the heat shock response.

Conclusions

Our results suggest that transcriptome evolution works to maintain steady-state gene expression during constrained differentiation at various evolutionary stages, while also maintaining responsiveness to environmental stimuli and transcriptome homeostasis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1999-x) contains supplementary material, which is available to authorized users.

Metabolism at evolutionary optimal States

Metabolism is generally required for cellular maintenance and for the generation of offspring under conditions that support growth. The rates, yields (efficiencies), adaptation time and robustness of metabolism are therefore key determinants of cellular fitness. For biotechnological applications and our understanding of the evolution of metabolism, it is necessary to figure out how the functional system properties of metabolism can be optimized, via adjustments of the kinetics and expression of enzymes, and by rewiring metabolism. The trade-offs that can occur during such optimizations then indicate fundamental limits to evolutionary innovations and bioengineering. In this paper, we review several theoretical and experimental findings about mechanisms for metabolic optimization.

Mutations in global regulators lead to metabolic selection during adaptation to complex environments

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes if many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased genetic and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that subtle modulations of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order metabolic selection that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism, and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a “one-step” mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.

Changing environmental conditions are the norm in biology. However, understanding adaptation to complex environments presents many challenges. For example, adaptation to resource-rich environments can potentially have many successful evolutionary trajectories to increased fitness. Even in conditions of plenty, the utilization of numerous but novel resources can require multiple mutations before a benefit is accrued. We evolved two bacterial species isolated from the gut of healthy humans in two different, resource-rich media commonly used in the laboratory. We anticipated that under weak selection the population would evolve tremendous genetic diversity. Despite such a complex genetic background we were able to identify a strong degree of parallel evolution and using a combination of population proteomic and population genomic approaches we show that two global regulators, arcA and rpoS, are the principle targets of selection. Up-regulation of the different metabolic pathways that are controlled by these global regulators in combination with up-regulation of transporters that transport nutrients into the cell revealed increased use of the novel resources. Thus global regulators can provide a one-step model to shift metabolism efficiently and provide rapid a one-step reprogramming of the cell metabolic profile.

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.

Differential stress resistance and metabolic traits underlie coexistence in a sympatrically evolved bacterial population

Following intermittent batch growth in Luria-Bertani (LB) broth for about 1000 generations, differentially evolved forms were found in a population of Escherichia coli cells. Studies on this population revealed the emergence of key polymorphisms, as evidenced by analysis of both whole genome sequences and transcription analysis. Here, we investigated the phenotypic nature of several key forms and found a remarkable (interactive) coexistence of forms which highlights the presence of different ecological roles pointing at a dichotomy in: (i) tolerance to environmental stresses and (ii) the capacity to utilize particular carbon sources such as galactose. Both forms differed from their common ancestor by different criteria. This apparent coexistence of two diverged forms points at the occurrence of niche partitioning as a consequence of dichotomous adaptive evolution. Remarkably, the two forms were shown to continue to coexist - in varying ratio's - in an experiment that cycled them through periods of nutrient feast (plentiful growth substrates) and famine (growth-restrictive - stress conditions). The results further indicated that the equilibrium of the coexistence was destroyed when one of the parameters was high tuned, jeopardizing the stability of the coexisting pair.