Nicholas R. Sandoval

Cellulosic hydrolysate toxicity and tolerance mechanisms in Escherichia coli.

The sustainable production of biofuels will require the efficient utilization of lignocellulosic biomass. A key barrier involves the creation of growth-inhibitory compounds by chemical pretreatment steps, which ultimately reduce the efficiency of fermentative microbial biocatalysts. The primary toxins include organic acids, furan derivatives, and phenolic compounds. Weak acids enter the cell and dissociate, resulting in a drop in intracellular pH as well as various anion-specific effects on metabolism. Furan derivatives, dehydration products of hexose and pentose sugars, have been shown to hinder fermentative enzyme function. Phenolic compounds, formed from lignin, can disrupt membranes and are hypothesized to interfere with the function of intracellular hydrophobic targets. This review covers mechanisms of toxicity and tolerance for these compounds with a specific focus on the important industrial organism Escherichia coli. Recent efforts to engineer E. coli for improved tolerance to these toxins are also discussed.

Strategy for directing combinatorial genome engineering in Escherichia coli

We describe a directed genome-engineering approach that combines genome-wide methods for mapping genes to traits [Warner JR, Reeder PJ, Karimpour-Fard A, Woodruff LBA, Gill RT (2010) Nat Biotechnol 28:856–862] with strategies for rapidly creating combinatorial ribosomal binding site (RBS) mutation libraries containing billions of targeted modifications [Wang HH, et al. (2009) Nature 460:894–898]. This approach should prove broadly applicable to various efforts focused on improving production of fuels, chemicals, and pharmaceuticals, among other products. We used barcoded promoter mutation libraries to map the effect of increased or decreased expression of nearly every gene in Escherichia coli onto growth in several model environments (cellulosic hydrolysate, low pH, and high acetate). Based on these data, we created and evaluated RBS mutant libraries (containing greater than 100,000,000 targeted mutations), targeting the genes identified to most affect growth. On laboratory timescales, we successfully identified a broad range of mutations (>25 growth-enhancing mutations confirmed), which improved growth rate 10–200% for several different conditions. Although successful, our efforts to identify superior combinations of growth-enhancing genes emphasized the importance of epistatic interactions among the targeted genes (synergistic, antagonistic) for taking full advantage of this approach to directed genome engineering.

Synthetic methylotrophy: engineering the production of biofuels and chemicals based on the biology of aerobic methanol utilization.

Synthetic methylotrophy is the development of non-native methylotrophs that can utilize methane and methanol as sole carbon and energy sources or as co-substrates with carbohydrates to produce metabolites as biofuels and chemicals. The availability of methane (from natural gas) and its oxidation product, methanol, has been increasing, while prices have been decreasing, thus rendering them as attractive fermentation substrates. As they are more reduced than most carbohydrates, methane and methanol, as co-substrates, can enhance the yields of biologically produced metabolites. Here we discuss synthetic biology and metabolic engineering strategies based on the native biology of aerobic methylotrophs for developing synthetic strains grown on methanol, with Escherichia coli as the prototype.

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).

Elucidating acetate tolerance in E. coli using a genome-wide approach

Engineering organisms for improved performance using lignocellulose feedstocks is an important step towards a sustainable fuel and chemical industry. Cellulosic feedstocks contain carbon and energy in the form of cellulosic and hemicellulosic sugars that are not metabolized by most industrial microorganisms. Pretreatment processes that hydrolyze these polysaccharides often also result in the accumulation of growth inhibitory compounds, such as acetate and furfural among others. Here, we have applied a recently reported strategy for engineering tolerance towards the goal of increasing Escherichia coli growth in the presence of elevated acetate concentrations (Lynch et al., 2007). We performed growth selections upon an E. coli genome library developed using a moderate selection pressure to identify genomic regions implicated in acetate toxicity and tolerance. These studies identified a range of high-fitness genes that are normally involved in membrane and extracellular processes, are key regulated steps in pathways, and are involved in pathways that yield specific amino acids and nucleotides. Supplementation of the products and metabolically related metabolites of these pathways significantly increased growth rate (a 130% increase in specific growth) at inhibitory acetate concentrations. Our results suggest that acetate tolerance will not involve engineering of a single pathway; rather we observe a range of potential mechanisms for overcoming acetate based inhibition.

Expression of heterologous sigma factors enables functional screening of metagenomic and heterologous genomic libraries

A key limitation in using heterologous genomic or metagenomic libraries in functional genomics and genome engineering is the low expression of heterologous genes in screening hosts, such as Escherichia coli. To overcome this limitation, here we generate E. coli strains capable of recognizing heterologous promoters by expressing heterologous sigma factors. Among seven sigma factors tested, RpoD from Lactobacillus plantarum (Lpl) appears to be able of initiating transcription from all sources of DNA. Using the promoter GFP-trap concept, we successfully screen several heterologous and metagenomic DNA libraries, thus enlarging the genomic space that can be functionally sampled in E. coli. For an application, we show that screening fosmid-based Lpl genomic libraries in an E. coli strain with a chromosomally integrated Lpl rpoD enables the identification of Lpl genetic determinants imparting strong ethanol tolerance in E. coli. Transcriptome analysis confirms increased expression of heterologous genes in the engineered strain.

Characterization of physiological responses to 22 gene knockouts in Escherichia coli central carbon metabolism

Understanding the impact of gene knockouts on cellular physiology, and metabolism in particular, is centrally important to quantitative systems biology and metabolic engineering. Here, we present a comprehensive physiological characterization of wild-type Escherichia coli and 22 knockouts of enzymes in the upper part of central carbon metabolism, including the PTS system, glycolysis, pentose phosphate pathway and Entner-Doudoroff pathway. Our results reveal significant metabolic changes that are affected by specific gene knockouts. Analysis of collective trends and correlations in the data using principal component analysis (PCA) provide new, and sometimes surprising, insights into E. coli physiology. Additionally, by comparing the data-to-model predictions from constraint-based approaches such as FBA, MOMA and RELATCH we demonstrate the important role of less well-understood kinetic and regulatory effects in central carbon metabolism.

Parallel mapping of genotypes to phenotypes contributing to overall biological fitness.

Laboratory selection is a powerful approach for engineering new traits in metabolic engineering applications. This approach is limited because determining the genetic basis of improved strains can be difficult using conventional methods. We have recently reported a new method that enables the measurement of fitness for all clones contained within comprehensive genomic libraries, thus enabling the genome-scale mapping of fitness altering genes. Here, we demonstrate a strategy for relating these measurements to the individual phenotypes selected for in a particular environment. We first provide a mathematical framework for decomposing fitness into selectable phenotypes. We then employed this framework to predict that single-batch selections would enrich primarily for library clones with increased growth rate, serial-batch would enrich for a broad collection of clones enhanced via a combination of increased growth rate and/or reduced lag times, and that overlap among selected clones would be minimal. We used the SCalar Analysis of Library Enrichments (SCALEs) method to test these predictions. We mapped all genomic regions for which increased copy number conferred a selective advantage to Escherichia coli when cultured via single- or serial-batch in the presence of 1-naphthol. We identified a surprisingly large collection (163 total) of tolerance regions, including all previously identified solvent tolerance genes in E. coli. We show that the majority of the identified regions were unique to the different selection strategies examined and that such differences were indeed due to differences among enriched clones in growth rate and lag times over the solvent concentrations examined. The combination of a framework for decomposing overall fitness into selectable phenotypes along with a genome-scale method for mapping genes to such phenotypes lays the groundwork for improving the rational design of laboratory selections.

Genome-wide mapping of furfural tolerance genes in Escherichia coli.

Advances in genomics have improved the ability to map complex genotype-to-phenotype relationships, like those required for engineering chemical tolerance. Here, we have applied the multiSCale Analysis of Library Enrichments (SCALEs; Lynch et al. (2007) Nat. Method.) approach to map, in parallel, the effect of increased dosage for >105 different fragments of the Escherichia coli genome onto furfural tolerance (furfural is a key toxin of lignocellulosic hydrolysate). Only 268 of >4,000 E. coli genes (∼6%) were enriched after growth selections in the presence of furfural. Several of the enriched genes were cloned and tested individually for their effect on furfural tolerance. Overexpression of thyA, lpcA, or groESL individually increased growth in the presence of furfural. Overexpression of lpcA, but not groESL or thyA, resulted in increased furfural reduction rate, a previously identified mechanism underlying furfural tolerance. We additionally show that plasmid-based expression of functional LpcA or GroESL is required to confer furfural tolerance. This study identifies new furfural tolerant genes, which can be applied in future strain design efforts focused on the production of fuels and chemicals from lignocellulosic hydrolysate.

Co-utilization of glucose and xylose by evolved Thermus thermophilus LC113 strain elucidated by (13)C metabolic flux analysis and whole genome sequencing.

We evolved Thermus thermophilus to efficiently co-utilize glucose and xylose, the two most abundant sugars in lignocellulosic biomass, at high temperatures without carbon catabolite repression. To generate the strain, T. thermophilus HB8 was first evolved on glucose to improve its growth characteristics, followed by evolution on xylose. The resulting strain, T. thermophilus LC113, was characterized in growth studies, by whole genome sequencing, and (13)C-metabolic flux analysis ((13)C-MFA) with [1,6-(13)C]glucose, [5-(13)C]xylose, and [1,6-(13)C]glucose+[5-(13)C]xylose as isotopic tracers. Compared to the starting strain, the evolved strain had an increased growth rate (~2-fold), increased biomass yield, increased tolerance to high temperatures up to 90°C, and gained the ability to grow on xylose in minimal medium. At the optimal growth temperature of 81°C, the maximum growth rate on glucose and xylose was 0.44 and 0.46h(-1), respectively. In medium containing glucose and xylose the strain efficiently co-utilized the two sugars. (13)C-MFA results provided insights into the metabolism of T. thermophilus LC113 that allows efficient co-utilization of glucose and xylose. Specifically, (13)C-MFA revealed that metabolic fluxes in the upper part of metabolism adjust flexibly to sugar availability, while fluxes in the lower part of metabolism remain relatively constant. Whole genome sequence analysis revealed two large structural changes that can help explain the physiology of the evolved strain: a duplication of a chromosome region that contains many sugar transporters, and a 5x multiplication of a region on the pVV8 plasmid that contains xylose isomerase and xylulokinase genes, the first two enzymes of xylose catabolism. Taken together, (13)C-MFA and genome sequence analysis provided complementary insights into the physiology of the evolved strain.