Evolutionary adaptation to environmental pH in experimental lineages of Escherichia coli

This study uses the enteric bacterium Escherichia coli as an experimental system to examine evolutionary responses of bacteria to an environmental acidic-alkaline range between pH 5.3 and 7.8 (15-5000 nM [H(+)]). Our goal was both to test general hypotheses about adaptation to abiotic variables and to provide insights into how coliform organisms might respond to changing conditions inside and outside of hosts. Six replicate lines of E. coli evolved for 2000 generations at one of four different constant pH conditions: pH 5.3, 6.3, 7.0, or 7.8. Direct adaptation to the evolutionary environment, as well as correlated changes in other environments, was measured as a change in fitness relative to the ancestor in direct competition experiments. The pH 5.3 group had the highest fitness gains, with a highly significant increase of 20%. The pH 7.8 group had far less significant gains and much higher variance among its lines. Analysis of individual lines within these two groups revealed complex patterns of adaptation: all of the pH 5.3 lines exhibited trade-offs (reduced fitness in another environment), but only 33% of the pH 7.8 lines showed such trade-offs and one of the pH 7.8 lines demonstrated exaptation by improving fitness in the pH 5.3 environment. Although there was also prevalent exaptation in other groups to the acidic environment, there were no such cases of exaptation to alkalinity. Comparison across the entire experimental pH range revealed that the most acidic lines, the pH 5.3 group, were all specialists, in contrast to the pH 6.3 lines, which were almost all generalists. That is, although none of the pH 5.3 lines showed any correlated fitness gains, all of the pH 6.3 lines did.     

Long-term experimental evolution in Escherichia coli. V. Effects of recombination with immigrant genotypes on the rate of bacterial evolution

This study builds upon an earlier experiment that examined the dynamics of mean fitness in evolving populations of Escherichia coli in which mutations were the sole source of genetic variation. During thousands of generations in a constant environment, the rate of improvement in mean fitness of these asexual populations slowed considerably from an initially rapid pace. In this study, we sought to determine whether sexual recombination with novel genotypes would reaccelerate the rate of adaption in these populations. To that end, treatment populations were propagated for an additional 1000 generations in the same environment as their ancestors, but they were periodically allowed to mate with an immigrant pool of genetically distinct Hfr (high frequency recombination) donors. These donors could transfer genes to the resident populations by conjugation, but the donors themselves could not grow in the experimental environment. Control populations were propagated under identical conditions, but in the absence of sexual recombination with the donors. All twelve control populations retained the ancestral alleles at every locus that was scored. In contrast, the sexual recombination treatment yielded dramatic increases in genetic variation. Thus, there was a profound effect of recombination on the rate of genetic change. However, the increased genetic variation in the treatment populations had no significant effect on the rate of adaptive evolution, as measured by changes in mean fitness relative to a common competitor. We then considered three hypotheses that might reconcile these two outcomes: recombination pressure, hitchhiking of recombinant genotypes in association with beneficial mutations, and complex selection dynamics whereby certain genotypes may have a selective advantage only within a particular milieu of competitors. The estimated recombination rate was too low to explain the observed rate of genetic change, either alone or in combination with hitchhiking effects. However, we documented comple x ecological interactions among some recombinant genotypes, suggesting that our method for estimating fitness relative to a common competitor might have underestimated the rate of adaptive evolution in the treatment populations.     

Platform development for expression and purification of stable isotope labeled monoclonal antibodies in Escherichia coli

The widespread use of monoclonal antibodies (mAbs) as a platform for therapeutic drug development in the pharmaceutical industry has led to an increased interest in robust experimental approaches for assessment of mAb structure, stability and dynamics. The ability to enrich proteins with stable isotopes is a prerequisite for the in-depth application of many structural and biophysical methods, including nuclear magnetic resonance (NMR), small angle neutron scattering, neutron reflectometry, and quantitative mass spectrometry. While mAbs can typically be produced with very high yields using mammalian cell expression, stable isotope labeling using cell culture is expensive and often impractical. The most common and cost-efficient approach to label proteins is to express proteins in Escherichia coli grown in minimal media; however, such methods for mAbs have not been reported to date. Here we present, for the first time, the expression and purification of a stable isotope labeled mAb from a genetically engineered E. coli strain capable of forming disulfide bonds in its cytoplasm. It is shown using two-dimensional NMR spectral fingerprinting that the unlabeled mAb and the mAb singly or triply labeled with ¹³C, ¹⁵N, ²H are well folded, with only minor structural differences relative to the mammalian cell-produced mAb that are attributed to the lack of glycosylation in the Fc domain. This advancement of an E. coli-based mAb expression platform will facilitate the production of mAbs for in-depth structural characterization, including the high resolution investigation of mechanisms of action.     

Adaptive laboratory evolution of microbial co‐cultures for improved metabolite secretion

Adaptive laboratory evolution has proven highly effective for obtaining microorganisms with enhanced capabilities. Yet, this method is inherently restricted to the traits that are positively linked to cell fitness, such as nutrient utilization. Here, we introduce coevolution of obligatory mutualistic communities for improving secretion of fitness‐costly metabolites through natural selection. In this strategy, metabolic cross‐feeding connects secretion of the target metabolite, despite its cost to the secretor, to the survival and proliferation of the entire community. We thus co‐evolved wild‐type lactic acid bacteria and engineered auxotrophic Saccharomyces cerevisiae in a synthetic growth medium leading to bacterial isolates with enhanced secretion of two B‐group vitamins, viz., riboflavin and folate. The increased production was specific to the targeted vitamin, and evident also in milk, a more complex nutrient environment that naturally contains vitamins. Genomic, proteomic and metabolomic analyses of the evolved lactic acid bacteria, in combination with flux balance analysis, showed altered metabolic regulation towards increased supply of the vitamin precursors. Together, our findings demonstrate how microbial metabolism adapts to mutualistic lifestyle through enhanced metabolite exchange.     

Acetate formation during recombinant protein production in Escherichia coli K‐12 with an elevated NAD(H) pool

Acetate formation is a disadvantage in the use of Escherichia coli for recombinant protein production, and many studies have focused on optimizing fermentation processes or altering metabolism to eliminate acetate accumulation. In this study, E. coli MEC697 (MG1655 nadR nudC mazG) maintained a larger pool of NAD(H) compared to the wild‐type control, and also accumulated lower concentrations of acetate when grown in batch culture on glucose. In steady‐state cultures, the elevated total NAD(H) found in MEC697 delayed the threshold dilution rate for acetate formation to a growth rate of 0.27 h^?1. Batch and fed‐batch processes using MEC697 were examined for the production of β‐galactosidase as a model recombinant protein. Fed‐batch culture of MEC697/pTrc99A‐lacZ compared to MG1655/pTrc99A‐lacZ at a growth rate of 0.22 h^?1 showed only a modest increase of protein formation. However, 1 L batch growth of MEC697/pTrc99A‐lacZ resulted in 50% lower acetate formation compared to MG1655/pTrc99A‐lacZ and a two‐fold increase in recombinant protein production.     

The impact of rapid evolution on population dynamics in the wild: experimental test of eco-evolutionary dynamics

Rapid evolution challenges the assumption that evolution is too slow to impact short-term ecological dynamics. This insight motivates the study of 'Eco-Evolutionary Dynamics' or how evolution and ecological processes reciprocally interact on short time scales. We tested how rapid evolution impacts concurrent population dynamics using an aphid (Myzus persicae) and an undomesticated host (Hirschfeldia incana) in replicated wild populations. We manipulated evolvability by creating non-evolving (single clone) and potentially evolving (two-clone) aphid populations that contained genetic variation in intrinsic growth rate. We observed significant evolution in two-clone populations whether or not they were exposed to predators and competitors. Evolving populations grew up to 42% faster and attained up to 67% higher density, compared with non-evolving control populations but only in treatments exposed to competitors and predators. Increased density also correlates with relative fitness of competing clones suggesting a full eco-evolutionary dynamic cycle defined as reciprocal interactions between evolution and density.     

Mass spectrometry‐based protein–protein interaction networks for the study of human diseases

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein–protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)‐based approaches have allowed unbiased mapping of these disease‐mediated changes in protein–protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein–protein interactions at a system‐level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS‐based protein–protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.     

进化代谢选育高渗透压耐受型产琥珀酸大肠杆菌

在以碳酸钠为酸中和剂的大肠杆菌两阶段发酵产琥珀酸的过程中,由于Na+的积累造成发酵体系中渗透压的提高,严重抑制了琥珀酸的产物浓度。为了增强大肠杆菌对渗透压的耐受性,考察了利用进化代谢方法筛选高渗透压耐受型高产琥珀酸大肠杆菌菌株的可行性。进化代谢系统作为一种菌株突变装置,可以使菌体在连续培养条件下以最大的生长速率生长。以NaCl为渗透压调节剂,通过在连续培养装置中逐步提高NaCl浓度使菌体在高渗透压条件下快速生长,最终得到了一株高渗透压耐受型琥珀酸生产菌株Escherichia coli XB4。以碳酸钠为酸中和剂,在7 L发酵罐中利用Escherichia coli XB4进行两阶段发酵,厌氧培养60 h后,琥珀酸产量达到了69.5 g/L,琥珀酸生产速率达到了1.81 g/(L.h),分别比出发菌株提高了18.6%和20%。     

Biosensor-assisted evolution for high-level production of 4-hydroxyphenylacetic acid in Escherichia coli

4-Hydroxyphenylacetic acid (4HPAA) is an important building block for synthesizing drugs, agrochemicals, and biochemicals, and requires sustainable production to meet increasing demand. Here, we use a 4HPAA biosensor to overcome the difficulty of conventional library screening in identification of preferred mutants. Strains with higher 4HPAA production and tolerance are successfully obtained by atmospheric and room temperature plasma (ARTP) mutagenesis coupled with adaptive laboratory evolution using this biosensor. Genome shuffling integrates preferred properties in the strain GS-2-4, which produces 25.42 g/L 4HPAA. Chromosomal mutations of the strain GS-2-4 are identified by whole genome sequencing. Through comprehensive analysis and experimental validation, important genes, pathways and regulations are revealed. The best gene combination in inverse engineering, acrD-aroG, increases 4HPAA production of strain GS-2-4 by 37% further. These results emphasize precursor supply and stress resistance are keys to efficient 4HPAA biosynthesis. Our work shows the power of biosensor-assisted screening of mutants from libraries. The methods developed here can be easily adapted to construct cell factories for the production of other aromatic chemicals. Our work also provides many valuable target genes to build cell factories for efficient 4HPAA production in the future.     

Parasite diversity drives rapid host dynamics and evolution of resistance in a bacteria‐phage system

Host–parasite evolutionary interactions are typically considered in a pairwise species framework. However, natural infections frequently involve multiple parasites. Altering parasite diversity alters ecological and evolutionary dynamics as parasites compete and hosts resist multiple infection. We investigated the effects of parasite diversity on host–parasite population dynamics and evolution using the pathogen Pseudomonas aeruginosa and five lytic bacteriophage parasites. To manipulate parasite diversity, bacterial populations were exposed for 24 hours to either phage monocultures or diverse communities containing up to five phages. Phage communities suppressed host populations more rapidly but also showed reduced phage density, likely due to interphage competition. The evolution of resistance allowed rapid bacterial recovery that was greater in magnitude with increases in phage diversity. We observed no difference in the extent of resistance with increased parasite diversity, but there was a profound impact on the specificity of resistance; specialized resistance evolved to monocultures through mutations in a diverse set of genes. In summary, we demonstrate that parasite diversity has rapid effects on host–parasite population dynamics and evolution by selecting for different resistance mutations and affecting the magnitude of bacterial suppression and recovery. Finally, we discuss the implications of phage diversity for their use as biological control agents.     

Extent of adaptation is not limited by unpredictability of the environment in laboratory populations of Escherichia coli

Environmental variability is on the rise in different parts of the earth, and the survival of many species depends on how well they cope with these fluctuations. Our current understanding of how organisms adapt to unpredictably fluctuating environments is almost entirely based on studies that investigate fluctuations among different values of a single environmental stressor such as temperature or pH . How would unpredictability affect adaptation when the environment fluctuates between qualitatively very different kinds of stresses? To answer this question, we subjected laboratory populations of Escherichia coli to selection over ~ 260 generations. The populations faced predictable and unpredictable environmental fluctuations across qualitatively different selection environments, namely, salt and acidic pH . We show that predictability of environmental fluctuations does not play a role in determining the extent of adaptation, although the extent of ancestral adaptation to the chosen selection environments is of key importance.     

Reducing the cost of resistance; experimental evolution in the filamentous fungus Aspergillus nidulans

We have studied compensatory evolution in a fludioxonil resistant mutant of the filamentous fungus Aspergillus nidulans. In an evolution experiment lasting for 27 weeks (about 3000 cell cycles) 35 parallel strains of this mutant evolved in three different environmental conditions. Our results show a severe cost of resistance (56%) in the absence of fludioxonil and in all conditions the mutant strain was able to restore fitness without loss of the resistance. In several cases, the evolved strain reached a higher fitness than the original sensitive ancestor. Fitness compensation occurred in one, two or three discrete steps. Genetic analysis of crosses between different evolved strains and between evolved and ancestral strains revealed interaction between compensatory mutations and provided information on the number of loci involved in fitness compensation. In addition, we discuss the opportunities for the experimental study of evolutionary processes provided by the filamentous fungus A. nidulans.     

Activation of the cryptic PhnE permease promotes rapid adaptive evolution in a population of Escherichia coli K-12 starved for phosphate

Escherichia coli K-12 suffers acetic acid stress during prolonged incubation in glucose minimal medium containing a limiting concentration of inorganic phosphate (0.1 mM P(i)), which decreases the number of viable cells from 6 × 10(8) to ≤10 CFU/ml between days 6 and 14 of incubation. Here we show that following two serial transfers into P(i)-limiting medium, evolved mutants survived prolonged incubation (≈10(7) CFU/ml on day 14 of incubation). The evolved strains that overtook the populations were generally PhnE(+), whereas the ancestral K-12 strain carries an inactive phnE allele, which prevents the transport of phosphonates. The switching in phnE occurred with a high frequency as a result of the deletion of an 8-bp repeated sequence. In a mixed culture starved for P(i) that contained the K-12 ancestral strain in majority, evolved strains grew through PhnE-dependent scavenging of probably organic phosphate esters (not phosphonates or P(i)) released by E. coli K-12 between days 1 and 3, before acetic acid excreted by E. coli K-12 reached toxic levels. The growth yield of phnE(+) strains in mixed culture was dramatically enhanced by mutations that affect glucose metabolism, such as an rpoS mutation inactivating the alternative sigma factor RpoS. The long-term viability of evolved populations was generally higher when the ancestral strain carried an inactive rather than an active phnE allele, which indicates that cross-feeding of phosphorylated products as a result of the phnE polymorphism may be essential for the spread of mutants which eventually help populations to survive under P(i) starvation conditions.     

Framework for the rapid optimization of soluble protein expression in Escherichia coli combining microscale experiments and statistical experimental design

A major bottleneck in drug discovery is the production of soluble human recombinant protein in sufficient quantities for analysis. This problem is compounded by the complex relationship between protein yield and the large number of variables which affect it. Here, we describe a generic framework for the rapid identification and optimization of factors affecting soluble protein yield in microwell plate fermentations as a prelude to the predictive and reliable scaleup of optimized culture conditions. Recombinant expression of firefly luciferase in Escherichia coli was used as a model system. Two rounds of statistical design of experiments (DoE) were employed to first screen (D-optimal design) and then optimize (central composite face design) the yield of soluble protein. Biological variables from the initial screening experiments included medium type and growth and induction conditions. To provide insight into the impact of the engineering environment on cell growth and expression, plate geometry, shaking speed, and liquid fill volume were included as factors since these strongly influence oxygen transfer into the wells. Compared to standard reference conditions, both the screening and optimization designs gave up to 3-fold increases in the soluble protein yield, i.e., a 9-fold increase overall. In general the highest protein yields were obtained when cells were induced at a relatively low biomass concentration and then allowed to grow slowly up to a high final biomass concentration, >8 g.L-1. Consideration and analysis of the model results showed 6 of the original 10 variables to be important at the screening stage and 3 after optimization. The latter included the microwell plate shaking speeds pre- and postinduction, indicating the importance of oxygen transfer into the microwells and identifying this as a critical parameter for subsequent scale translation studies. The optimization process, also known as response surface methodology (RSM), predicted there to be a distinct optimum set of conditions for protein expression which could be verified experimentally. This work provides a generic approach to protein expression optimization in which both biological and engineering variables are investigated from the initial screening stage. The application of DoE reduces the total number of experiments needed to be performed, while experimentation at the microwell scale increases experimental throughput and reduces cost.     

Proteomics analysis of a long‐term survival strain of Escherichia coli K‐12 exhibiting a growth advantage in stationary‐phase (GASP) phenotype

The aim of this work was the functional and proteomic analysis of a mutant, W3110 Bgl⁺/10, isolated from a batch culture of an Escherichia coli K‐12 strain maintained at room temperature without addition of nutrients for 10 years. When the mutant was evaluated in competition experiments in co‐culture with the wild‐type, it exhibited the growth advantage in stationary phase (GASP) phenotype. Proteomes of the GASP mutant and its parental strain were compared by using a 2DE coupled with MS approach. Several differentially expressed proteins were detected and many of them were successful identified by mass spectrometry. Identified expression‐changing proteins were grouped into three functional categories: metabolism, protein synthesis, chaperone and stress responsive proteins. Among them, the prevalence was ascribable to the “metabolism” group (72%) for the GASP mutant, and to “chaperones and stress responsive proteins” group for the parental strain (48%).