Person:

Church, George

In the past decade, computational methods have been shown to be well suited to unraveling the complex web of metabolic reactions in biological systems. Methods based on flux–balance analysis (FBA) and bi-level optimization have been used to great effect in aiding metabolic engineering. These methods predict the result of genetic manipulations and allow for the best set of manipulations to be found computationally. Bi-level FBA is, however, limited in applicability because the required computational time and resources scale poorly as the size of the metabolic system and the number of genetic manipulations increase. To overcome these limitations, we have developed Genetic Design through Local Search (GDLS), a scalable, heuristic, algorithmic method that employs an approach based on local search with multiple search paths, which results in effective, low-complexity search of the space of genetic manipulations. Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing.

Fermentation of plant biomass by microbes like Clostridium phytofermentans recycles carbon globally and can make biofuels from inedible feedstocks. We analyzed C. phytofermentans fermenting cellulosic substrates by integrating quantitative mass spectrometry of more than 2500 proteins with measurements of growth, enzyme activities, fermentation products, and electron microscopy. Absolute protein concentrations were estimated using Absolute Protein EXpression (APEX); relative changes between treatments were quantified with chemical stable isotope labeling by reductive dimethylation (ReDi). We identified the different combinations of carbohydratases used to degrade cellulose and hemicellulose, many of which were secreted based on quantification of supernatant proteins, as well as the repertoires of glycolytic enzymes and alcohol dehydrogenases (ADHs) enabling ethanol production at near maximal yields. Growth on cellulose also resulted in diverse changes such as increased expression of tryptophan synthesis proteins and repression of proteins for fatty acid metabolism and cell motility. This study gives a systems-level understanding of how this microbe ferments biomass and provides a rational, empirical basis to identify engineering targets for industrial cellulosic fermentation.

Background: Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process requires a detailed molecular description of the networks involved. Results: We have developed a computational approach for generating static models of signal transduction networks which utilizes protein-interaction maps generated from large-scale two-hybrid screens and expression profiles from DNA microarrays. Networks are determined entirely by integrating protein-protein interaction data with microarray expression data, without prior knowledge of any pathway intermediates. In effect, this is equivalent to extracting subnetworks of the protein interaction dataset whose members have the most correlated expression profiles. Conclusion: We show that our technique accurately reconstructs MAP Kinase signaling networks in Saccharomyces cerevisiae. This approach should enhance our ability to model signaling networks and to discover new components of known networks. More generally, it provides a method for synthesizing molecular data, either individual transcript abundance measurements or pairwise protein interactions, into higher level structures, such as pathways and networks.

Several emerging technologies are aiming to meet renewable fuel standards, mitigate greenhouse gas emissions, and provide viable alternatives to fossil fuels. Direct conversion of solar energy into fungible liquid fuel is a particularly attractive option, though conversion of that energy on an industrial scale depends on the efficiency of its capture and conversion. Large-scale programs have been undertaken in the recent past that used solar energy to grow innately oil-producing algae for biomass processing to biodiesel fuel. These efforts were ultimately deemed to be uneconomical because the costs of culturing, harvesting, and processing of algal biomass were not balanced by the process efficiencies for solar photon capture and conversion. This analysis addresses solar capture and conversion efficiencies and introduces a unique systems approach, enabled by advances in strain engineering, photobioreactor design, and a process that contradicts prejudicial opinions about the viability of industrial photosynthesis. We calculate efficiencies for this direct, continuous solar process based on common boundary conditions, empirical measurements and validated assumptions wherein genetically engineered cyanobacteria convert industrially sourced, high-concentration CO(_2) into secreted, fungible hydrocarbon products in a continuous process. These innovations are projected to operate at areal productivities far exceeding those based on accumulation and refining of plant or algal biomass or on prior assumptions of photosynthetic productivity. This concept, currently enabled for production of ethanol and alkane diesel fuel molecules, and operating at pilot scale, establishes a new paradigm for high productivity manufacturing of nonfossil-derived fuels and chemicals.

Recent advances allow multiplexed genome engineering in E. coli, employing easily designed oligonucleotides to edit multiple loci simultaneously. A similar technology in human cells would greatly expedite functional genomics, both by enhancing our ability to test how individual variants such as single nucleotide polymorphisms (SNPs) are related to specific phenotypes, and potentially allowing simultaneous mutation of multiple loci. However, oligo-mediated targeting of human cells is currently limited by low targeting efficiencies and low survival of modified cells. Using a HeLa-based EGFP-rescue reporter system we show that use of modified base analogs can increase targeting efficiency, in part by avoiding the mismatch repair machinery. We investigate the effects of oligonucleotide toxicity and find a strong correlation between the number of phosphorothioate bonds and toxicity. Stably EGFP-corrected cells were generated at a frequency of (\sim)0.05% with an optimized oligonucleotide design combining modified bases and reduced number of phosphorothioate bonds. We provide evidence from comparative RNA-seq analysis suggesting cellular immunity induced by the oligonucleotides might contribute to the low viability of oligo-corrected cells. Further optimization of this method should allow rapid and scalable genome engineering in human cells.

DNA built from modular repeats presents a challenge for gene synthesis. We present a solid surface-based sequential ligation approach, which we refer to as iterative capped assembly (ICA), that adds DNA repeat monomers individually to a growing chain while using hairpin ‘capping’ oligonucleotides to block incompletely extended chains, greatly increasing the frequency of full-length final products. Applying ICA to a model problem, construction of custom transcription activator-like effector nucleases (TALENs) for genome engineering, we demonstrate efficient synthesis of TALE DNA-binding domains up to 21 monomers long and their ligation into a nuclease-carrying backbone vector all within 3 h. We used ICA to synthesize 20 TALENs of varying DNA target site length and tested their ability to stimulate gene editing by a donor oligonucleotide in human cells. All the TALENS show activity, with the ones >15 monomers long tending to work best. Since ICA builds full-length constructs from individual monomers rather than large exhaustive libraries of pre-fabricated oligomers, it will be trivial to incorporate future modified TALE monomers with improved or expanded function or to synthesize other types of repeat-modular DNA where the diversity of possible monomers makes exhaustive oligomer libraries impractical.

High-throughput recording of signals embedded within inaccessible micro-environments is a technological challenge. The ideal recording device would be a nanoscale machine capable of quantitatively transducing a wide range of variables into a molecular recording medium suitable for long-term storage and facile readout in the form of digital data. We have recently proposed such a device, in which cation concentrations modulate the misincorporation rate of a DNA polymerase (DNAP) on a known template, allowing DNA sequences to encode information about the local cation concentration. In this work we quantify the cation sensitivity of DNAP misincorporation rates, making possible the indirect readout of cation concentration by DNA sequencing. Using multiplexed deep sequencing, we quantify the misincorporation properties of two DNA polymerases – Dpo4 and Klenow exo− – obtaining the probability and base selectivity of misincorporation at all positions within the template. We find that Dpo4 acts as a DNA recording device for Mn2+ with a misincorporation rate gain of ∼2%/mM. This modulation of misincorporation rate is selective to the template base: the probability of misincorporation on template T by Dpo4 increases >50-fold over the range tested, while the other template bases are affected less strongly. Furthermore, cation concentrations act as scaling factors for misincorporation: on a given template base, Mn2+ and Mg2+ change the overall misincorporation rate but do not alter the relative frequencies of incoming misincorporated nucleotides. Characterization of the ion dependence of DNAP misincorporation serves as the first step towards repurposing it as a molecular recording device.

Multiplex Automated Genome Engineering (MAGE) employs short oligonucleotides to scarlessly modify genomes. However, insertions of >10 bases are still inefficient, but can be improved substantially by selection of highly modified chromosomes. Here, we describe Co-Selection MAGE (CoS-MAGE) to optimize biosynthesis of aromatic amino acid derivatives by combinatorially inserting multiple T7 promoters simultaneously into 12 genomic operons. Promoter libraries can be quickly generated to study gain-of-function epistatic interactions in gene networks.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated (Cas) systems in bacteria and archaea use RNA-guided nuclease activity to provide adaptive immunity against invading foreign nucleic acids. Here, we report the use of type II bacterial CRISPR-Cas system in Saccharomyces cerevisiae for genome engineering. The CRISPR-Cas components, Cas9 gene and a designer genome targeting CRISPR guide RNA (gRNA), show robust and specific RNA-guided endonuclease activity at targeted endogenous genomic loci in yeast. Using constitutive Cas9 expression and a transient gRNA cassette, we show that targeted double-strand breaks can increase homologous recombination rates of single- and double-stranded oligonucleotide donors by 5-fold and 130-fold, respectively. In addition, co-transformation of a gRNA plasmid and a donor DNA in cells constitutively expressing Cas9 resulted in near 100% donor DNA recombination frequency. Our approach provides foundations for a simple and powerful genome engineering tool for site-specific mutagenesis and allelic replacement in yeast.

Adenosine-to-inosine (A-to-I) RNA editing alters the original genomic content of the human transcriptome and is essential for maintenance of normal life in mammals. A-to-I editing in Alu repeats is abundant in the human genome, with many thousands of expressed Alu sequences undergoing editing. Little is known so far about the contribution of Alu editing to transcriptome complexity. Transcripts derived from a single edited Alu sequence can be edited in multiple sites, and thus could theoretically generate a large number of different transcripts. Here we explored whether the combinatorial potential nature of edited Alu sequences is actually fulfilled in the human transcriptome. We analyzed datasets of editing sites and performed an analysis of a detailed transcript set of one edited Alu sequence. We found that editing appears at many more sites than detected by earlier genomic screens. To a large extent, editing of different sites within the same transcript is only weakly correlated. Thus, rather than finding a few versions of each transcript, a large number of edited variants arise, resulting in immense transcript diversity that eclipses alternative splicing as mechanism of transcriptome diversity, although with less impact on the proteome.