Adaptive Evolution Experiments Research Articles

Case Studies in the Assessment of Microbial Fitness: Seemingly Subtle Changes Can Have Major Effects on Phenotypic Outcomes

Following the completion of an adaptive evolution experiment, fitness evaluations are routinely conducted to assess the magnitude of adaptation. In doing so, proper consideration should be given when determining the appropriate methods as trade-offs may exist between accuracy and throughput. Here, we present three instances in which small changes in the framework or execution of fitness evaluations significantly impacted the outcomes. The first case illustrates that discrepancies in fitness conclusions can arise depending on the approach to evaluating fitness, the culture vessel used, and the sampling method. The second case reveals that variations in environmental conditions can occur associated with culture vessel material. Specifically, these subtle changes can greatly affect microbial physiology leading to changes in the culture pH and distorting fitness measurements. Finally, the last case reports that heterogeneity in CFU formation time can result in inaccurate fitness conclusions. Based on each case, considerations and recommendations are presented for future adaptive evolution experiments.

Web alert: Adaptive evolution of microbes

This review focuses on the adaptive strategies of microbes in the oceans. This study investigated how microbial composition changed spatially and temporally along a climate gradient. This study used two closely related Bacillus strains and observed how positive and negative selective pressures led to gene transfers and adaption. This study used a co-culture of Saccharomyces cerevisiae and Lactobacillus plantarum to show that coevolution prevents the destabilization of community interactions. This study used modelling and empirical experiments to examine the time of adaption as a function of different inoculum sizes in the transfer regime. Findings from this study suggest that changing the order of environmental changes leads to differences in adaptive and genomic changes. This study emphasized setting up conditions specific to a particular microorganism in adaptive evolution experiments. Specifically, they used a semi-continuous bioreactor with a layout that prevented biofilm formation. In natural environments, growth substrates are constantly changing. This study used Escherichia coli and alternated supplying glucose, xylose, glycerol or acetate in the growth medium. This paper describes a model for designing and optimizing adaptive laboratory evolution experiments. This interesting blog post discusses the role of tRNAs in regulating protein expression and hence the ability of microbes to adapt to changing conditions in the environment. This paper posits that microbial communities evolve more rapidly in extreme environments. The extreme environments examined were acid mine drainage, saline lake and hot spring and that was compared to surface ocean, freshwater, and soil. This article focuses on non-microbial systems, but it contains a wonderful description of the first documented laboratory evolution experiment with single-celled organisms, specifically on protist adaption to increasing temperature that was conducted in the 1880's. The take home message of this study is that growth rate and substrate utilization is more influenced by evolutionary history than by climate. Wild type Pseudomonas putida KT2440 cannot grow exclusively on ethylene glycol but that substrate can generate reducing equivalents. Laboratory evolution developed a strain able to grow on ethylene glycol and the study revealed the nature of the mutations required for this new phenotype. While Acidovorax sp. strain JS42 would oxygenate 4-nitrotoluene it would not grow on that substrate. Adaptive evolution experiments generated variants that grew on this new substrate. This review article focuses on using adaptive evolution for strain construction for biotechnological applications.

Screening and Growth Characterization of Non-conventional Yeasts in a Hemicellulosic Hydrolysate.

Lignocellulosic biomass is an attractive raw material for the sustainable production of chemicals and materials using microbial cell factories. Most of the existing bioprocesses focus on second-generation ethanol production using genetically modified Saccharomyces cerevisiae, however, this microorganism is naturally unable to consume xylose. Moreover, extensive metabolic engineering has to be carried out to achieve high production levels of industrially relevant building blocks. Hence, the use of non-Saccharomyces species, or non-conventional yeasts, bearing native metabolic routes, allows conversion of a wide range of substrates into different products, and higher tolerance to inhibitors improves the efficiency of biorefineries. In this study, nine non-conventional yeast strains were selected and screened on a diluted hemicellulosic hydrolysate from Birch. Kluyveromyces marxianus CBS 6556, Scheffersomyces stipitis CBS 5773, Lipomyces starkeyi DSM 70295, and Rhodotorula toruloides CCT 7815 were selected for further characterization, where their growth and substrate consumption patterns were analyzed under industrially relevant substrate concentrations and controlled environmental conditions in bioreactors. K. marxianus CBS 6556 performed poorly under higher hydrolysate concentrations, although this yeast was determined among the fastest-growing yeasts on diluted hydrolysate. S. stipitis CBS 5773 demonstrated a low growth and biomass production while consuming glucose, while during the xylose-phase, the specific growth and sugar co-consumption rates were among the highest of this study (0.17 h–1 and 0.37 g/gdw*h, respectively). L. starkeyi DSM 70295 and R. toruloides CCT 7815 were the fastest to consume the provided sugars at high hydrolysate conditions, finishing them within 54 and 30 h, respectively. R. toruloides CCT 7815 performed the best of all four studied strains and tested conditions, showing the highest specific growth (0.23 h–1), substrate co-consumption (0.73 ± 0.02 g/gdw*h), and xylose consumption (0.22 g/gdw*h) rates. Furthermore, R. toruloides CCT 7815 was able to produce 10.95 ± 1.37 gL–1 and 1.72 ± 0.04 mgL–1 of lipids and carotenoids, respectively, under non-optimized cultivation conditions. The study provides novel information on selecting suitable host strains for biorefinery processes, provides detailed information on substrate consumption patterns, and pinpoints to bottlenecks possible to address using metabolic engineering or adaptive evolution experiments.

Empowering a Methanol-Dependent Escherichia coli via Adaptive Evolution Using a High-Throughput Microbial Microdroplet Culture System.

Recently, a methanol-essential Escherichia coli was constructed; this strain is highly dependent on a supply of gluconate as a co-substrate for growth. Adaptive laboratory evolution is commonly applied to obtain mutants with specific phenotypes under certain selected pressure. However, conventional adaptive evolution approaches are not only laborious and time consuming, but they also come with lower throughput and inefficiency. In order to empower the aforementioned E. coli with reduced gluconate usage and enhanced growth rate, an irrational strategy based on a microbial microdroplet culture (MMC) platform was developed in this study. Given the automatic high-throughput selection of the MMC, a three-stage regime of an adaptive evolution experiment via gradually decreasing the availability of gluconate during the cultivation was performed for 50 days continuously in order to obtain the mutations. Finally, a candidate mutant was obtained with a 3-fold faster growth rate, a 43% shorter lag phase, and 40% less gluconate usage compared with the starting strain. Moreover, the gene mutations of gntU, idnT, edd, and pckA were identified by analyzing the whole-genome sequencing of mutants, which are strongly associated with the efficiency of gluconate uptake and cell growth. In conclusion, we have successfully demonstrated the feasibility of using MMC platform to empower the target strain with specific requirements in a manner of labor, time efficiency, and directed evolution.

Build Your Bioprocess on a Solid Strain-β-Carotene Production in Recombinant Saccharomyces cerevisiae.

Robust fermentation performance of microbial cell factories is critical for successful scaling of a biotechnological process. From shake flask cultivations to industrial-scale bioreactors, consistent strain behavior is fundamental to achieve the production targets. To assert the importance of this feature, we evaluated the impact of the yeast strain design and construction method on process scalability -from shake flasks to bench-scale fed-batch fermentations- using two recombinant Saccharomyces cerevisiae strains capable of producing β-carotene; SM14 and βcar1.2 strains. SM14 strain, obtained previously from adaptive evolution experiments, was capable to accumulate up to 21 mg/gDCW of β-carotene in 72 h shake flask cultures; while the βcar1.2, constructed by overexpression of carotenogenic genes, only accumulated 5.8 mg/gDCW of carotene. Surprisingly, fed-batch cultivation of these strains in 1L bioreactors resulted in opposite performances. βcar1.2 strain reached much higher biomass and β-carotene productivities (1.57 g/L/h and 10.9 mg/L/h, respectively) than SM14 strain (0.48 g/L/h and 3.1 mg/L/h, respectively). Final β-carotene titers were 210 and 750 mg/L after 80 h cultivation for SM14 and βcar1.2 strains, respectively. Our results indicate that these substantial differences in fermentation parameters are mainly a consequence of the exacerbated Crabtree effect of the SM14 strain. We also found that the strategy used to integrate the carotenogenic genes into the chromosomes affected the genetic stability of strains, although the impact was significantly minor. Overall, our results indicate that shake flasks fermentation parameters are poor predictors of the fermentation performance under industrial-like conditions, and that appropriate construction designs and performance tests must be conducted to properly assess the scalability of the strain and the bioprocess.

Laboratory evolution reveals a two-dimensional rate-yield tradeoff in microbial metabolism.

Growth rate and yield are fundamental features of microbial growth. However, we lack a mechanistic and quantitative understanding of the rate-yield relationship. Studies pairing computational predictions with experiments have shown the importance of maintenance energy and proteome allocation in explaining rate-yield tradeoffs and overflow metabolism. Recently, adaptive evolution experiments of Escherichia coli reveal a phenotypic diversity beyond what has been explained using simple models of growth rate versus yield. Here, we identify a two-dimensional rate-yield tradeoff in adapted E. coli strains where the dimensions are (A) a tradeoff between growth rate and yield and (B) a tradeoff between substrate (glucose) uptake rate and growth yield. We employ a multi-scale modeling approach, combining a previously reported coarse-grained small-scale proteome allocation model with a fine-grained genome-scale model of metabolism and gene expression (ME-model), to develop a quantitative description of the full rate-yield relationship for E. coli K-12 MG1655. The multi-scale analysis resolves the complexity of ME-model which hindered its practical use in proteome complexity analysis, and provides a mechanistic explanation of the two-dimensional tradeoff. Further, the analysis identifies modifications to the P/O ratio and the flux allocation between glycolysis and pentose phosphate pathway (PPP) as potential mechanisms that enable the tradeoff between glucose uptake rate and growth yield. Thus, the rate-yield tradeoffs that govern microbial adaptation to new environments are more complex than previously reported, and they can be understood in mechanistic detail using a multi-scale modeling approach.

Evolution of a novel chimeric maltotriose transporter in Saccharomyces eubayanus from parent proteins unable to perform this function.

At the molecular level, the evolution of new traits can be broadly divided between changes in gene expression and changes in protein-coding sequence. For proteins, the evolution of novel functions is generally thought to proceed through sequential point mutations or recombination of whole functional units. In Saccharomyces, the uptake of the sugar maltotriose into the cell is the primary limiting factor in its utilization, but maltotriose transporters are relatively rare, except in brewing strains. No known wild strains of Saccharomyces eubayanus, the cold-tolerant parent of hybrid lager-brewing yeasts (Saccharomyces cerevisiae x S. eubayanus), are able to consume maltotriose, which limits their ability to fully ferment malt extract. In one strain of S. eubayanus, we found a gene closely related to a known maltotriose transporter and were able to confer maltotriose consumption by overexpressing this gene or by passaging the strain on maltose. Even so, most wild strains of S. eubayanus lack native maltotriose transporters. To determine how this rare trait could evolve in naive genetic backgrounds, we performed an adaptive evolution experiment for maltotriose consumption, which yielded a single strain of S. eubayanus able to grow on maltotriose. We mapped the causative locus to a gene encoding a novel chimeric transporter that was formed by an ectopic recombination event between two genes encoding transporters that are unable to import maltotriose. In contrast to classic models of the evolution of novel protein functions, the recombination breakpoints occurred within a single functional domain. Thus, the ability of the new protein to carry maltotriose was likely acquired through epistatic interactions between independently evolved substitutions. By acquiring multiple mutations at once, the transporter rapidly gained a novel function, while bypassing potentially deleterious intermediate steps. This study provides an illuminating example of how recombination between paralogs can establish novel interactions among substitutions to create adaptive functions.

Chromosomal barcoding as a tool for multiplexed phenotypic characterization of laboratory evolved lineages

Adaptive laboratory evolution is an important tool to evolve organisms to increased tolerance towards different physical and chemical stress. It is applied to study the evolution of antibiotic resistance as well as genetic mechanisms underlying improvements in production strains. Adaptive evolution experiments can be automated in a high-throughput fashion. However, the characterization of the resulting lineages can become a time consuming task, when the performance of each lineage is evaluated individually. Here, we present a novel method for the markerless insertion of randomized genetic barcodes into the genome of Escherichia coli using a novel dual-auxotrophic selection approach. The barcoded E. coli library allows multiplexed phenotyping of evolved strains in pooled competition experiments. We use the barcoded library in an adaptive evolution experiment; evolving resistance towards three common antibiotics. Comparing this multiplexed phenotyping with conventional susceptibility testing and growth-rate measurements we can show a significant positive correlation between the two approaches. Use of barcoded bacterial strain libraries for individual adaptive evolution experiments drastically reduces the workload of characterizing the resulting phenotypes and enables prioritization of lineages for in-depth characterization. In addition, barcoded clones open up new ways to profile community dynamics or to track lineages in vivo or situ.

Time-Resolved Tracking of Mutations Reveals Diverse Allele Dynamics during Escherichia coli Antimicrobial Adaptive Evolution to Single Drugs and Drug Pairs.

Understanding the evolutionary processes that lead to antibiotic resistance can help to achieve better treatment strategies. Yet, little is known about the dynamics of the resistance alleles during adaptation. Here, we use population sequencing to monitor genetic changes in putative resistance loci at several time-points during adaptive evolution experiments involving five different antibiotic conditions. We monitor the mutational spectra in lineages evolved to be resistant to single antibiotics [amikacin (AMK), chloramphenicol (CHL), and ciprofloxacin (CIP)], as well as antibiotic combinations (AMK + CHL and CHL + CIP). We find that lineages evolved to antibiotic combinations exhibit different resistance allele dynamics compared with those of single-drug evolved lineages, especially for a drug pair with reciprocal collateral sensitivity. During adaptation, we observed interfering, superimposing and fixation allele dynamics. To further understand the selective forces driving specific allele dynamics, a subset of mutations were introduced into the ancestral wild type enabling differentiation between clonal interference and negative epistasis.

Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments.

The costs and benefits of protein expression are balanced through evolution. Expression of un-utilized protein (that have no benefits in the current environment) incurs a quantifiable fitness costs on cellular growth rates; however, the magnitude and variability of un-utilized protein expression in natural settings is unknown, largely due to the challenge in determining environment-specific proteome utilization. We address this challenge using absolute and global proteomics data combined with a recently developed genome-scale model of Escherichia coli that computes the environment-specific cost and utility of the proteome on a per gene basis. We show that nearly half of the proteome mass is unused in certain environments and accounting for the cost of this unused protein expression explains >95% of the variance in growth rates of Escherichia coli across 16 distinct environments. Furthermore, reduction in unused protein expression is shown to be a common mechanism to increase cellular growth rates in adaptive evolution experiments. Classification of the unused protein reveals that the unused protein encodes several nutrient- and stress- preparedness functions, which may convey fitness benefits in varying environments. Thus, unused protein expression is the source of large and pervasive fitness costs that may provide the benefit of hedging against environmental change.

Vibrio anguillarum Is Genetically and Phenotypically Unaffected by Long-Term Continuous Exposure to the Antibacterial Compound Tropodithietic Acid.

Minimizing the use of antibiotics in the food production chain is essential for limiting the development and spread of antibiotic-resistant bacteria. One alternative intervention strategy is the use of probiotic bacteria, and bacteria of the marine Roseobacter clade are capable of antagonizing fish-pathogenic vibrios in fish larvae and live feed cultures for fish larvae. The antibacterial compound tropodithietic acid (TDA), an antiporter that disrupts the proton motive force, is key in the antibacterial activity of several roseobacters. Introducing probiotics on a larger scale requires understanding of any potential side effects of long-term exposure of the pathogen to the probionts or any compounds they produce. Here we exposed the fish pathogen Vibrio anguillarum to TDA for several hundred generations in an adaptive evolution experiment. No tolerance or resistance arose during the 90 days of exposure, and whole-genome sequencing of TDA-exposed lineages and clones revealed few mutational changes, compared to lineages grown without TDA. Amino acid-changing mutations were found in two to six different genes per clone; however, no mutations appeared unique to the TDA-exposed lineages or clones. None of the virulence genes of V. anguillarum was affected, and infectivity assays using fish cell lines indicated that the TDA-exposed lineages and clones were less invasive than the wild-type strain. Thus, long-term TDA exposure does not appear to result in TDA resistance and the physiology of V. anguillarum appears unaffected, supporting the application of TDA-producing roseobacters as probiotics in aquaculture. It is important to limit the use of antibiotics in our food production, to reduce the risk of bacteria developing antibiotic resistance. We showed previously that marine bacteria of the Roseobacter clade can prevent or reduce bacterial diseases in fish larvae, acting as probiotics. Roseobacters produce the antimicrobial compound tropodithietic acid (TDA), and we were concerned regarding whether long-term exposure to this compound could induce resistance or affect the disease-causing ability of the fish pathogen. Therefore, we exposed the fish pathogen Vibrio anguillarum to increasing TDA concentrations over 3 months. We did not see the development of any resistance to TDA, and subsequent infection assays revealed that none of the TDA-exposed clones had increased virulence toward fish cells. Hence, this study supports the use of roseobacters as a non-risk-based disease control measure in aquaculture.

Compensating the Fitness Costs of Synonymous Mutations.

Synonymous mutations do not change the sequence of the polypeptide but they may still influence fitness. We investigated in Salmonella enterica how four synonymous mutations in the rpsT gene (encoding ribosomal protein S20) reduce fitness (i.e., growth rate) and the mechanisms by which this cost can be genetically compensated. The reduced growth rates of the synonymous mutants were correlated with reduced levels of the rpsT transcript and S20 protein. In an adaptive evolution experiment, these fitness impairments could be compensated by mutations that either caused up-regulation of S20 through increased gene dosage (due to duplications), increased transcription of the rpsT gene (due to an rpoD mutation or mutations in rpsT), or increased translation from the rpsT transcript (due to rpsT mutations). We suggest that the reduced levels of S20 in the synonymous mutants result in production of a defective subpopulation of 30S subunits lacking S20 that reduce protein synthesis and bacterial growth and that the compensatory mutations restore S20 levels and the number of functional ribosomes. Our results demonstrate how specific synonymous mutations can cause substantial fitness reductions and that many different types of intra- and extragenic compensatory mutations can efficiently restore fitness. Furthermore, this study highlights that also synonymous sites can be under strong selection, which may have implications for the use of dN/dS ratios as signature for selection.

Rapid evolution of recombinant Saccharomyces cerevisiae for Xylose fermentation through formation of extra-chromosomal circular DNA.

Circular DNA elements are involved in genome plasticity, particularly of tandem repeats. However, amplifications of DNA segments in Saccharomyces cerevisiae reported so far involve pre-existing repetitive sequences such as ribosomal DNA, Ty elements and Long Terminal Repeats (LTRs). Here, we report the generation of an eccDNA, (extrachromosomal circular DNA element) in a region without any repetitive sequences during an adaptive evolution experiment. We performed whole genome sequence comparison between an efficient D-xylose fermenting yeast strain developed by metabolic and evolutionary engineering, and its parent industrial strain. We found that the heterologous gene XylA that had been inserted close to an ARS sequence in the parent strain has been amplified about 9 fold in both alleles of the chromosomal locus of the evolved strain compared to its parent. Analysis of the amplification process during the adaptive evolution revealed formation of a XylA-carrying eccDNA, pXI2-6, followed by chromosomal integration in tandem arrays over the course of the evolutionary adaptation. Formation of the eccDNA occurred in the absence of any repetitive DNA elements, probably using a micro-homology sequence of 8 nucleotides flanking the amplified sequence. We isolated the pXI2-6 eccDNA from an intermediate strain of the evolutionary adaptation process, sequenced it completely and showed that it confers high xylose fermentation capacity when it is transferred to a new strain. In this way, we have provided clear evidence that gene amplification can occur through generation of eccDNA without the presence of flanking repetitive sequences and can serve as a rapid means of adaptation to selection pressure.

Collateral Resistance and Sensitivity Modulate Evolution of High-Level Resistance to Drug Combination Treatment in Staphylococcus aureus.

As drug-resistant pathogens continue to emerge, combination therapy will increasingly be relied upon to treat infections and to help combat further development of multidrug resistance. At present a dichotomy exists between clinical practice, which favors therapeutically synergistic combinations, and the scientific model emerging from in vitro experimental work, which maintains that this interaction provides greater selective pressure toward resistance development than other interaction types. We sought to extend the current paradigm, based on work below or near minimum inhibitory concentration levels, to reflect drug concentrations more likely to be encountered during treatment. We performed a series of adaptive evolution experiments using Staphylococcus aureus. Interestingly, no relationship between drug interaction type and resistance evolution was found as resistance increased significantly beyond wild-type levels. All drug combinations, irrespective of interaction types, effectively limited resistance evolution compared with monotreatment. Cross-resistance and collateral sensitivity were found to be important factors in the extent of resistance evolution toward a combination. Comparative genomic analyses revealed that resistance to drug combinations was mediated largely by mutations in the same genes as single-drug-evolved lineages highlighting the importance of the component drugs in determining the rate of resistance evolution. Results of this work suggest that the mechanisms of resistance to constituent drugs should be the focus of future resistance evolution work.

Biotechnological production of value-added carotenoids from microalgae

We recently evaluated the relationship between abiotic environmental stresses and lutein biosynthesis in the green microalga Dunaliella salina and suggested a rational design of stress-driven adaptive evolution experiments for carotenoids production in microalgae. Here, we summarize our recent findings regarding the biotechnological production of carotenoids from microalgae and outline emerging technology in this field. Carotenoid metabolic pathways are characterized in several representative algal species as they pave the way for biotechnology development. The adaptive evolution strategy is highlighted in connection with enhanced growth rate and carotenoid metabolism. In addition, available genetic modification tools are described, with emphasis on model species. A brief discussion on the role of lights as limiting factors in carotenoid production in microalgae is also included. Overall, our analysis suggests that light-driven metabolism and the photosynthetic efficiency of microalgae in photobioreactors are the main bottlenecks in enhancing biotechnological potential of carotenoid production from microalgae.

Computational identification of adaptive mutants using the VERT system

BackgroundEvolutionary dynamics of microbial organisms can now be visualized using the Visualizing Evolution in Real Time (VERT) system, in which several isogenic strains expressing different fluorescent proteins compete during adaptive evolution and are tracked using fluorescent cell sorting to construct a population history over time. Mutations conferring enhanced growth rates can be detected by observing changes in the fluorescent population proportions.ResultsUsing data obtained from several VERT experiments, we construct a hidden Markov-derived model to detect these adaptive events in VERT experiments without external intervention beyond initial training. Analysis of annotated data revealed that the model achieves consensus with human annotation for 85-93% of the data points when detecting adaptive events. A method to determine the optimal time point to isolate adaptive mutants is also introduced.ConclusionsThe developed model offers a new way to monitor adaptive evolution experiments without the need for external intervention, thereby simplifying adaptive evolution efforts relying on population tracking. Future efforts to construct a fully automated system to isolate adaptive mutants may find the algorithm a useful tool.

Model-based analysis of an adaptive evolution experiment with Escherichia coli in a pyruvate limited continuous culture with glycerol

Bacterial strains that were genetically blocked in important metabolic pathways and grown under selective conditions underwent a process of adaptive evolution: certain pathways may have been deregulated and therefore allowed for the circumvention of the given block. A block of endogenous pyruvate synthesis from glycerol was realized by a knockout of pyruvate kinase and phosphoenolpyruvate carboxylase in E. coli. The resulting mutant strain was able to grow on a medium containing glycerol and lactate, which served as an exogenous pyruvate source. Heterologous expression of a pyruvate carboxylase gene from Corynebacterium glutamicum was used for anaplerosis of the TCA cycle. Selective conditions were controlled in a continuous culture with limited lactate feed and an excess of glycerol feed. After 200–300 generations pyruvate-prototrophic mutants were isolated. The genomic analysis of an evolved strain revealed that the genotypic basis for the regained pyruvate-prototrophy was not obvious. A constraint-based model of the metabolism was employed to compute all possible detours around the given metabolic block by solving a hierarchy of linear programming problems. The regulatory network was expected to be responsible for the adaptation process. Hence, a Boolean model of the transcription factor network was connected to the metabolic model. Our model analysis only showed a marginal impact of transcriptional control on the biomass yield on substrate which is a key variable in the selection process. In our experiment, microarray analysis confirmed that transcriptional control probably played a minor role in the deregulation of the alternative pathways for the circumvention of the block.

Metabolic networks evolve towards states of maximum entropy production

A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles.

Functional and Metabolic Effects of Adaptive Glycerol Kinase (GLPK) Mutants in Escherichia coli

Herein we measure the effect of four adaptive non-synonymous mutations to the glycerol kinase (glpK) gene on catalytic function and regulation, to identify changes that correlate to increased fitness in glycerol media. The mutations significantly reduce affinity for the allosteric inhibitor fructose-1,6-bisphosphate (FBP) and formation of the tetramer, which are structurally related, in a manner that correlates inversely with imparted fitness during growth on glycerol, which strongly suggests that these enzymatic parameters drive growth improvement. Counterintuitively, the glpK mutations also increase glycerol-induced auto-catabolite repression that reduces glpK transcription in a manner that correlates to fitness. This suggests that increased specific GlpK activity is attenuated by negative feedback on glpK expression via catabolite repression, possibly to prevent methylglyoxal toxicity. We additionally report that glpK mutations were fixed in 47 of 50 independent glycerol-adapted lineages. By far the most frequently mutated locus (nucleotide 218) was mutated in 20 lineages, strongly suggesting this position has an elevated mutation rate. This study demonstrates that fitness correlations can be used to interrogate adaptive processes at the protein level and to identify the regulatory constraints underlying selection and improved growth.

Modification and Evolution of Gluconobacter oxydans for Enhanced Growth and Biotransformation Capabilities at Low Glucose Concentration

Gluconobacter oxydans is widely used in several biotechnological applications, where sorbitol or mannitol is commonly used as carbon source at high concentration. In this study, a membrane-bound glucose dehydrogenase-deficient strain (GDHK) was constructed to eliminate growth problems on glucose caused by direct oxidation of glucose in the medium. To achieve improved growth properties for the GDHK strain on glucose, a laboratory adaptive evolution experiment was performed with glucose as the sole carbon source. Results indicated evident, albeit modest, improvements in cell growth after a 50-day (about 430generations) experimental evolution on glucose. The maximum specific growth rate and biomass yield of the resulting GDHE50 strain were increased around 1.35- to 1.4-fold compared with those of the GDHK strain. Meanwhile, two types of biotransformation reactions using resting cells of G. oxydans were investigated. Significant elevations in biotransformation performance of the GHDE50 strain were observed in comparison with that of the wild-type strain. In addition, resting cells of the GDHE50 strain grown on a relatively low concentration of glucose (10g/l) could catalyze the biotransformation of glycerol to dihydroxyacetone and ethylene glycol to glycolic acid as efficient as the wild-type G. oxydans cultured on higher concentration of sorbitol or other carbon sources. These results suggest very favorable prospects of using glucose to lower production cost in many important industrial biocatalysis and biotransformation processes.