Genome-scale analysis of anti-metabolite directed strain engineering

Classic strain engineering methods have previously been limited by the low-throughput of conventional sequencing technology. Here, we applied a new genomics technology, scalar analysis of library enrichments (SCALEs), to measure >3 million Escherichia coli genomic library clone enrichment patterns resulting from growth selections employing three aspartic-acid anti-metabolites. Our objective was to assess the extent to which access to genome-scale enrichment patterns would provide strain-engineering insights not reasonably accessible through the use of conventional sequencing. We determined that the SCALEs method identified a surprisingly large range of anti-metabolite tolerance regions (423, 865, or 909 regions for each of the three anti-metabolites) when compared to the number of regions (1-3 regions) indicated by conventional sequencing. Genome-scale methods uniquely enable the calculation of clone fitness values by providing concentration data for all clones within a genomic library before and after a period of selection. We observed that clone fitness values differ substantially from clone concentration values and that this is due to differences in overall clone fitness distributions for each selection. Finally, we show that many of the clones of highest fitness overlapped across all selections, suggesting that inhibition of aspartate metabolism, as opposed to specific inhibited enzymes, dominated each selection. Our follow up studies confirmed our observed growth phenotypes and showed that intracellular amino-acid levels were also altered in several of the identified clones. These results demonstrate that genome-scale methods, such as SCALEs, can be used to dramatically improve understanding of classic strain engineering approaches.     

A genomics approach to improve the analysis and design of strain selections

Strain engineering has been traditionally centered on the use of mutation, selection, and screening to develop improved strains. Although mutational and screening methods are well-characterized, selection remains poorly understood. We hypothesized that we could use a genome-wide method for assessing laboratory selections to design selections with enhanced sensitivity (true positives) and specificity (true negatives) towards a single desired phenotype. To test this hypothesis, we first applied multi-SCale Analysis of Library Enrichments (SCALEs) to identify genes conferring increased fitness in continuous flow selections with increasing levels of 3-hydroxypropionic acid (3-HP). We found that this selection not only enriched for 3-HP tolerance phenotypes but also for wall adherence phenotypes (41% false positives). Using this genome-wide data, we designed a serial-batch selection with a decreasing 3-HP gradient. Further examination by ROC analysis confirmed that the serial-batch approach resulted in significantly increased sensitivity (46%) and specificity (10%) for our desired phenotype (3-HP tolerance).     

Rapid dissection of a complex phenotype through genomic-scale mapping of fitness altering genes

The understanding and engineering of complex phenotypes is a critical issue in biotechnology. Conventional approaches for engineering such phenotypes are often resource intensive, marginally effective, and unable to generate the level of biological understanding desired. Here, we report a new approach for rapidly dissecting a complex phenotype that is based upon the combination of genome-scale growth phenotype data, precisely targeted growth selections, and informatic strategies for abstracting and summarizing data onto coherent biological processes. We measured at high resolution (125 NT) and for the entire genome the effect of increased gene copy number on overall biological fitness corresponding to the expression of a complex phenotype (tolerance to 3-hydroxypropionic acid (3-HP) in Escherichia coli). Genetic level fitness data were then mapped according to various definitions of gene–gene interaction in order to generate network-level fitness data. When metabolic pathways were used to define interactions, we observed that genes within the chorismate and threonine super-pathways were disproportionately enriched throughout selections for 3-HP tolerance. Biochemical and genetic studies demonstrated that alleviation of inhibition of either of these super-pathways was sufficient to mitigate 3-HP toxicity. These data enabled the design of combinatorial modifications that almost completely offset 3-HP toxicity in minimal medium resulting in a 20 g/L and 25-fold increase in tolerance and specific growth, respectively.     

An integrated linkage map reveals candidate genes underlying adaptive variation in Chinook salmon (Oncorhynchus tshawytscha)

Salmonids are an important cultural and ecological resource exhibiting near worldwide distribution between their native and introduced range. Previous research has generated linkage maps and genomic resources for several species as well as genome assemblies for two species. We first leveraged improvements in mapping and genotyping methods to create a dense linkage map for Chinook salmon Oncorhynchus tshawytscha by assembling family data from different sources. We successfully mapped 14 620 SNP loci including 2336 paralogs in subtelomeric regions. This improved map was then used as a foundation to integrate genomic resources for gene annotation and population genomic analyses. We anchored a total of 286 scaffolds from the Atlantic salmon genome to the linkage map to provide a framework for the placement 11 728 Chinook salmon ESTs. Previously identified thermotolerance QTL were found to colocalize with several candidate genes including HSP70, a gene known to be involved in thermal response, as well as its inhibitor. Multiple regions of the genome with elevated divergence between populations were also identified, and annotation of ESTs in these regions identified candidate genes for fitness related traits such as stress response, growth and behaviour. Collectively, these results demonstrate the utility of combining genomic resources with linkage maps to enhance evolutionary inferences.     

Engineering improved ethanol production in Escherichia coli with a genome-wide approach

A key challenge to the commercial production of commodity chemical and fuels is the toxicity of such molecules to the microbial host. While a number of studies have attempted to engineer improved tolerance for such compounds, the majority of these studies have been performed in wild-type strains and culturing conditions that differ considerably from production conditions. Here we applied the multiscalar analysis of library enrichments (SCALEs) method and performed a growth selection in an ethanol production system to quantitatively map in parallel all genes in the genome onto ethanol tolerance and production. In order to perform the selection in an ethanol-producing system, we used a previously engineered Escherichia coli ethanol production strain (LW06; ATCC BAA-2466) (Woodruff et al., in press), as the host strain for the multiscalar genomic library analysis (>10⁶ clones for each library of 1, 2, or 4 kb overlapping genomic fragments). By testing individually selected clones, we confirmed that growth selections enriched for clones with both improved ethanol tolerance and production phenotypes. We performed combinatorial testing of the top genes identified (uspC, otsA, otsB) to investigate their ability to confer improved ethanol tolerance or ethanol production. We determined that overexpression of otsA was required for improved tolerance and productivity phenotypes, with the best performing strains showing up to 75% improvement relative to the parent production strain.     

Mapping salinity tolerance during Arabidopsis thaliana germination and seedling growth

To characterize and dissect genetic variation for salinity tolerance, we assessed variation in salinity tolerance during germination and seedling growth for a worldwide sample of Arabidopsis thaliana accessions. By combining QTL mapping, association mapping and expression data, we identified genomic regions involved in salinity response. Among the worldwide sample, we found germination ability within a moderately saline environment (150 mM NaCl) varied considerable, from >90% among the most tolerant lines to complete inability to germinate among the most susceptible. Our results also demonstrated wide variation in salinity tolerance within A. thaliana RIL populations and identified multiple genomic regions that contribute to this variation. These regions contain known candidate genes, but at least four of the regions contain loci not yet associated with salinity tolerance response phenotypes. Our observations suggest A. thaliana natural variation may be an underutilized resource for investigating salinity stress response.     

Epistasis and frequency dependence influence the fitness of an adaptive mutation in a diversifying lineage

The opportunity for a mutation to invade a population can dramatically vary depending on the context in which this mutation occurs. Such context dependence is difficult to document as it requires the ability to measure how a mutation affects phenotypes and fitness and to manipulate the context in which the mutation occurs. We identified a mutation in a gene encoding a global regulator in one of two ecotypes that diverged from a common ancestor during 1200 generations of experimental evolution. We replaced the ancestral allele by the mutant allele, and vice versa, in several clones isolated during the time course of the evolution experiment, and compared the phenotype and fitness of clones isogenic except for the focal mutation. We show that the fitness and phenotype of the mutation are strongly affected by epistatic interactions between genes in the same genome, as well as by frequency dependent selection resulting from biotic interactions between individuals in the same population. We conclude that amongst the replicate population in which it spread, the mutation we identified is only adaptive when occurring in specific genomes and competing with specific individuals. This study thus demonstrates that the opportunity for an adaptive mutation to spread in an evolutionary lineage can only be understood in the light of its genomic and competitive environments.     

Resistance to extinction of low fitness virus subjected to plaque-to-plaque transfers: diversification by mutation clustering.

Plaque-to-plaque transfers of RNA viruses lead to accumulation of mutations and fitness decrease. To test whether continuing plaque-to-plaque transfers would lead to viral extinction, we have subjected several low fitness foot-and-mouth disease virus (FMDV) clones to up to 130 successive plaque transfers, and have analyzed the evolution of plaque titers and genomic nucleotide sequences. No case of viral extinction could be documented. Some low fitness clones that posses an internal poly(A) tract evaded extinction by modifying the length or base composition of the poly(A) tract. The comparison of entire genomic sequences of FMDV clones at increasing plaque transfer number revealed that mutations accumulated at a uniform rate, and that they were distributed unevenly along the genome. Clusters of mutations were identified at different genomic sites in two plaque transfer lineages. Mutation clustering appears to occur stochastically and could not be related to fixation of compensatory mutations. The results document resistance of viral clones to extinction, and suggest that mutation clustering may be a mechanism of genetic diversification of low fitness virus.     

When to wake up? The optimal waking-up strategies for starvation-induced persistence

Prolonged lag time can be induced by starvation contributing to the antibiotic tolerance of bacteria. We analyze the optimal lag time to survive and grow the iterative and stochastic application of antibiotics. A simple model shows that the optimal lag time can exhibit a discontinuous transition when the severeness of the antibiotic application, such as the probability to be exposed the antibiotic, the death rate under the exposure, and the duration of the exposure, is increased. This suggests the possibility of reducing tolerant bacteria by controlled usage of antibiotics application. When the bacterial populations are able to have two phenotypes with different lag times, the fraction of the second phenotype that has different lag time shows a continuous transition. We then present a generic framework to investigate the optimal lag time distribution for total population fitness for a given distribution of the antibiotic application duration. The obtained optimal distributions have multiple peaks for a wide range of the antibiotic application duration distributions, including the case where the latter is monotonically decreasing. The analysis supports the advantage in evolving multiple, possibly discrete phenotypes in lag time for bacterial long-term fitness.     

Quantitative trait loci for thermotolerance phenotypes in Drosophila melanogaster

For insects, temperature is a major environmental variable that can influence an individual's behavioral activities and fitness. Drosophila melanogaster is a cosmopolitan species that has had great success in adapting to and colonizing diverse thermal niches. This adaptation and colonization has resulted in complex patterns of genetic variation in thermotolerance phenotypes in nature. Although extensive work has been conducted documenting patterns of genetic variation, substantially less is known about the genomic regions or genes that underlie this ecologically and evolutionarily important genetic variation. To begin to understand and identify the genes controlling thermotolerance phenotypes, we have used a mapping population of recombinant inbred (RI) lines to map quantitative trait loci (QTL) that affect variation in both heat- and cold-stress resistance. The mapping population was derived from a cross between two lines of D. melanogaster (Oregon-R and 2b) that were not selected for thermotolerance phenotypes, but exhibit significant genetic divergence for both phenotypes. Using a design in which each RI line was backcrossed to both parental lines, we mapped seven QTL affecting thermotolerance on the second and third chromosomes. Three of the QTL influence cold-stress resistance and four affect heat-stress resistance. Most of the QTL were trait or sex specific, suggesting that overlapping but generally unique genetic architectures underlie resistance to low- and high-temperature extremes. Each QTL explained between 5 and 14% of the genetic variance among lines, and degrees of dominance ranged from completely additive to partial dominance. Potential thermotolerance candidate loci contained within our QTL regions are identified and discussed.     

A genetic system for direct selection of gene-positive clones during recombinational cloning in yeast

Transformation-associated recombination (TAR) is a cloning technique that allows specific chromosomal regions or genes to be isolated directly from genomic DNA without prior construction of a genomic library. This technique involves homologous recombination during spheroplast transformation between genomic DNA and a TAR vector that has 5′ and 3′ gene targeting sequences (hooks). Typically, TAR cloning produces positive YAC recombinants at a frequency of ~0.5%; the positive clones are identified by PCR or colony hybridization. This paper describes a novel TAR cloning procedure that selects positive clones by positive and negative genetic selection. This system utilizes a TAR vector with two targeting hooks, HIS3 as a positive selectable marker, URA3 as a negative selectable marker and a gene-specific sequence called a loop sequence. The loop sequence lies distal to a targeting hook sequence in the chromosomal target, but proximal to the targeting hook and URA3 in the TAR vector. When this vector recombines with chromosomal DNA at the gene-specific targeting hook, the recombinant YAC product carries two copies of the loop sequence, therefore, the URA3 negative selectable marker becomes mitotically unstable and is lost at high frequency by direct repeat recombination involving the loop sequence. Positive clones are identified by selecting against URA3. This method produces positive YAC recombinants at a frequency of ~40%. This novel TAR cloning method provides a powerful tool for structural and functional analysis of complex genomes.     

FISH physical mapping with barley BAC clones

Fluorescence in situ hybridization (FISH) is a useful technique for physical mapping of genes, markers, and other single- or low-copy sequences. Since clones containing less than 10 kb of single-copy DNA do not reliably produce detectable signals with current FISH techniques in plants, a bacterial artificial chromosome (BAC) partial library of barley was constructed and a FISH protocol for detecting unique sequences in barley BAC clones was developed. The library has a 95 kb average barley insert, representing about 20% of a barley genome. Two BAC clones containing hordein gene sequences were identified and partially characterized. FISH using these two BAC clones as probes showed specific hybridization signals near the end of the short arm of one pair of chromosomes. Restriction digests of these two BAC clones were compared with restriction patterns of genomic DNA; all fragments contained in the BAC clones corresponded to bands present in the genomic DNA, and the two BAC clones were not identical. The barley inserts contained in these two BAC clones were faithful copies of the genomic DNA. FISH with four BAC clones with inserts varying from 20 to 150 kb, showed distinct signals on paired chromatids. Physical mapping of single- or low-copy sequences in BAC clones by FISH will help to correlate the genetic and physical maps. FISH with BAC clones also provide an additional approach for saturating regions of interest with markers and for constructing contigs spanning those regions.     

Nested chromosomal fragmentation in yeast using the meganuclease I-Sce I: a new method for physical mapping of eukaryotic genomes.

We have developed a new method for the physical mapping of genomes and the rapid sorting of genomic libraries which is based on chromosome fragmentation by the meganuclease I-Sce I, the first available member of a new class of endonucleases with very long recognition sequences. I-Sce I allows complete cleavage at a single artificially inserted site in an entire genome. Sites can be inserted by homologous recombination using specific cassettes containing selectable markers or, at random, using transposons. This method has been applied to the physical mapping of chromosome XI (620 kb) of Saccharomyces cerevisi and to the sorting of a cosmid library. Our strategy has potential applications to various genome mapping projects. A set of transgenic yeast strains carrying the I-Sce I sites at various locations along a chromosome defines physical intervals against which new genes, DNA fragments or clones can be mapped directly by simple hybridizations.     

A QTL analysis of female variation contributing to refractoriness and sperm competition in Drosophila melanogaster

Sperm competition is an important fitness component in many animal groups. Drosophila melanogaster males exhibit substantial genetic variation for sperm competitive ability and females show considerable genetic variation for first versus second male sperm use. Currently, the forces responsible for maintaining genetic variation in sperm competition related phenotypes are receiving much attention. While several candidate genes contributing to the variation seen in male competitive ability are known, genes involved in female sperm use remain largely undiscovered. Without knowledge of the underlying genes, it will be difficult to distinguish between different models of sexual selection such as cryptic female choice and sexual conflict. We used quantitative trait locus (QTL) mapping to identify regions of the genome contributing to female propensity to use first or second male sperm, female refractoriness to re-mating, and early-life fertility. The most well supported markers influencing the phenotypes include 33F/34A (P2), 57B (refractoriness) and 23F/24A (fertility). Between 10% and 15% of the phenotypic variance observed in these recombinant inbred lines was explained by these individual QTLs. More detailed investigation of the regions detected in this experiment may lead to the identification of genes responsible for the QTLs identified here.     

A simple method for genome-wide screening for advantageous insertions of mobile DNAs in Escherichia coli

Laboratory evolution in Escherichia coli has revealed that fitness typically increases in experimental populations. These changes are sometimes associated with changes in insertion sequence positions, some of which may themselves cause advantageous phenotypes. We have a novel and general method for identifying genes in Escherichia coli, whose knockout by mobile DNA insertions is beneficial in experimental evolution. Insertion sites in favored clones can be identified by reference to genomic information. We have implemented the method using modified Tn10 transposons bearing kanamycin and chloramphenicol resistance cassettes. Results are consistent across replicated experiments, demonstrating that the insertions are themselves creating selective advantages, rather than hitch-hiking with favorable base substitutions. The successful clones have subsequently been confirmed to have a fitness advantage relative to the progenitor strain. In experiments in shaking culture, we find that advantageous insertions usually fall in operons required in the pathways creating flagella. The method allows a rapid genome-wide screening for advantageous insertions in arbitrary environmental conditions. It allows investigation of the extent to which transient mutations generating environment-dependent selective advantages may help to explain the persistence of mobile DNAs in primarily clonal organisms, such as E. coli.     

Epistatic interaction maps relative to multiple metabolic phenotypes

An epistatic interaction between two genes occurs when the phenotypic impact of one gene depends on another gene, often exposing a functional association between them. Due to experimental scalability and to evolutionary significance, abundant work has been focused on studying how epistasis affects cellular growth rate, most notably in yeast. However, epistasis likely influences many different phenotypes, affecting our capacity to understand cellular functions, biochemical networks adaptation, and genetic diseases. Despite its broad significance, the extent and nature of epistasis relative to different phenotypes remain fundamentally unexplored. Here we use genome-scale metabolic network modeling to investigate the extent and properties of epistatic interactions relative to multiple phenotypes. Specifically, using an experimentally refined stoichiometric model for Saccharomyces cerevisiae, we computed a three-dimensional matrix of epistatic interactions between any two enzyme gene deletions, with respect to all metabolic flux phenotypes. We found that the total number of epistatic interactions between enzymes increases rapidly as phenotypes are added, plateauing at approximately 80 phenotypes, to an overall connectivity that is roughly 8-fold larger than the one observed relative to growth alone. Looking at interactions across all phenotypes, we found that gene pairs interact incoherently relative to different phenotypes, i.e. antagonistically relative to some phenotypes and synergistically relative to others. Specific deletion-deletion-phenotype triplets can be explained metabolically, suggesting a highly informative role of multi-phenotype epistasis in mapping cellular functions. Finally, we found that genes involved in many interactions across multiple phenotypes are more highly expressed, evolve slower, and tend to be associated with diseases, indicating that the importance of genes is hidden in their total phenotypic impact. Our predictions indicate a pervasiveness of nonlinear effects in how genetic perturbations affect multiple metabolic phenotypes. The approaches and results reported could influence future efforts in understanding metabolic diseases and the role of biochemical regulation in the cell.