D. Benjamin Gordon

Transcriptional regulatory code of a eukaryotic genome

DNA-binding transcriptional regulators interpret the genomes regulatory code by binding to specific sequences to induce or repress gene expression. Comparative genomics has recently been used to identify potential cis-regulatory sequences within the yeast genome on the basis of phylogenetic conservation, but this information alone does not reveal if or when transcriptional regulators occupy these binding sites. We have constructed an initial map of yeasts transcriptional regulatory code by identifying the sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species. The organization of regulatory elements in promoters and the environment-dependent use of these elements by regulators are discussed. We find that environment-specific use of regulatory elements predicts mechanistic models for the function of a large population of yeasts transcriptional regulators.

Histone H4K20/H3K9 demethylase PHF8 regulates zebrafish brain and craniofacial development

X-linked mental retardation (XLMR) is a complex human disease that causes intellectual disability. Causal mutations have been found in approximately 90 X-linked genes; however, molecular and biological functions of many of these genetically defined XLMR genes remain unknown. PHF8 (PHD (plant homeo domain) finger protein 8) is a JmjC domain-containing protein and its mutations have been found in patients with XLMR and craniofacial deformities. Here we provide multiple lines of evidence establishing PHF8 as the first mono-methyl histone H4 lysine 20 (H4K20me1) demethylase, with additional activities towards histone H3K9me1 and me2. PHF8 is located around the transcription start sites (TSS) of ∼7,000 RefSeq genes and in gene bodies and intergenic regions (non-TSS). PHF8 depletion resulted in upregulation of H4K20me1 and H3K9me1 at the TSS and H3K9me2 in the non-TSS sites, respectively, demonstrating differential substrate specificities at different target locations. PHF8 positively regulates gene expression, which is dependent on its H3K4me3-binding PHD and catalytic domains. Importantly, patient mutations significantly compromised PHF8 catalytic function. PHF8 regulates cell survival in the zebrafish brain and jaw development, thus providing a potentially relevant biological context for understanding the clinical symptoms associated with PHF8 patients. Lastly, genetic and molecular evidence supports a model whereby PHF8 regulates zebrafish neuronal cell survival and jaw development in part by directly regulating the expression of the homeodomain transcription factor MSX1/MSXB, which functions downstream of multiple signalling and developmental pathways. Our findings indicate that an imbalance of histone methylation dynamics has a critical role in XLMR.

Functional optimization of gene clusters by combinatorial design and assembly

Large microbial gene clusters encode useful functions, including energy utilization and natural product biosynthesis, but genetic manipulation of such systems is slow, difficult and complicated by complex regulation. We exploit the modularity of a refactored Klebsiella oxytoca nitrogen fixation (nif) gene cluster (16 genes, 103 parts) to build genetic permutations that could not be achieved by starting from the wild-type cluster. Constraint-based combinatorial design and DNA assembly are used to build libraries of radically different cluster architectures by varying part choice, gene order, gene orientation and operon occupancy. We construct 84 variants of the nifUSVWZM operon, 145 variants of the nifHDKY operon, 155 variants of the nifHDKYENJ operon and 122 variants of the complete 16-gene pathway. The performance and behavior of these variants are characterized by nitrogenase assay and strand-specific RNA sequencing (RNA-seq), and the results are incorporated into subsequent design cycles. We have produced a fully synthetic cluster that recovers 57% of wild-type activity. Our approach allows the performance of genetic parts to be quantified simultaneously in hundreds of genetic contexts. This parallelized design-build-test-learn cycle, which can access previously unattainable regions of genetic space, should provide a useful, fast tool for genetic optimization and hypothesis testing.

Exact rotamer optimization for protein design.

Computational methods play a central role in the rational design of novel proteins. The present work describes a new hybrid exact rotamer optimization (HERO) method that builds on previous dead‐end elimination algorithms to yield dramatic performance enhancements. Measured on experimentally validated physical models, these improvements make it possible to perform previously intractable designs of entire protein core, surface, or boundary regions. Computational demonstrations include a full core design of the variable domains of the light and heavy chains of catalytic antibody 48G7 FAB with 74 residues and 10128 conformations, a full core/boundary design of the β1 domain of protein G with 25 residues and 1053 conformations, and a full surface design of the β1 domain of protein G with 27 residues and 1060 conformations. In addition, a full sequence design of the β1 domain of protein G is used to demonstrate the strong dependence of algorithm performance on the exact form of the potential function and the fidelity of the rotamer library. These results emphasize that search algorithm performance for protein design can only be meaningfully evaluated on physical models that have been subjected to experimental scrutiny. The new algorithm greatly facilitates ongoing efforts to engineer increasingly complex protein features.

Radical performance enhancements for combinatorial optimization algorithms based on the dead-end elimination theorem

Recent advances in protein design have demonstrated the effectiveness of optimization algorithms based on the dead‐end elimination theorem. The algorithms solve the combinatorial problem of finding the optimal placement of side chains for a set of backbone coordinates. Although they are powerful tools, these algorithms have severe limitations when the number of side chain rotamers is large. This is due to the high‐order time dependence of the aspect of the calculation that deals with rotamer doubles. We present three independent algorithmic enhancements that significantly increase the speed of the doubles computation. These methods work by using quantities that are inexpensive to compute as a basis for forecasting which expensive calculations are worthwhile. One of the methods, the comparison of extrema, is derived from analytical considerations, and the remaining two, the “magic‐bullet” and the “qrs” and “quv” metrics, are based on empirical observation of the distribution of energies in the system. When used together, these methods effect an overall speed improvement of as much as a factor of 47, and for the doubles aspect of the calculation, a factor of 95. Together, these enhancements extend the envelope of inverse folding to larger proteins by making formerly intractable calculations attainable in reasonable computer time. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 1505–1514, 1998

A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data

MOTIVATION Genome-wide chromatin-immunoprecipitation (ChIP-chip) detects binding of transcriptional regulators to DNA in vivo at low resolution. Motif discovery algorithms can be used to discover sequence patterns in the bound regions that may be recognized by the immunoprecipitated protein. However, the discovered motifs often do not agree with the binding specificity of the protein, when it is known. RESULTS We present a powerful approach to analyzing ChIP-chip data, called THEME, that tests hypotheses concerning the sequence specificity of a protein. Hypotheses are refined using constrained local optimization. Cross-validation provides a principled standard for selecting the optimal weighting of the hypothesis and the ChIP-chip data and for choosing the best refined hypothesis. We demonstrate how to derive hypotheses for proteins from 36 domain families. Using THEME together with these hypotheses, we analyze ChIP-chip datasets for 14 human and mouse proteins. In all the cases the identified motifs are consistent with the published data with regard to the binding specificity of the proteins.

Global Mass Spectrometry Based Metabolomics Profiling of Erythrocytes Infected with Plasmodium falciparum

Malaria is a global infectious disease that threatens the lives of millions of people. Transcriptomics, proteomics and functional genomics studies, as well as sequencing of the Plasmodium falciparum and Homo sapiens genomes, have shed new light on this host-parasite relationship. Recent advances in accurate mass measurement mass spectrometry, sophisticated data analysis software, and availability of biological pathway databases, have converged to facilitate our global, untargeted biochemical profiling study of in vitro P. falciparum-infected (IRBC) and uninfected (NRBC) erythrocytes. In order to expand the number of detectable metabolites, several key analytical steps in our workflows were optimized. Untargeted and targeted data mining resulted in detection of over one thousand features or chemical entities. Untargeted features were annotated via matching to the METLIN metabolite database. For targeted data mining, we queried the data using a compound database derived from a metabolic reconstruction of the P. falciparum genome. In total, over one hundred and fifty differential annotated metabolites were observed. To corroborate the representation of known biochemical pathways from our data, an inferential pathway analysis strategy was used to map annotated metabolites onto the BioCyc pathway collection. This hypothesis-generating approach resulted in over-representation of many metabolites onto several IRBC pathways, most prominently glycolysis. In addition, components of the “branched” TCA cycle, partial urea cycle, and nucleotide, amino acid, chorismate, sphingolipid and fatty acid metabolism were found to be altered in IRBCs. Interestingly, we detected and confirmed elevated levels for cyclic ADP ribose and phosphoribosyl AMP in IRBCs, a novel observation. These metabolites may play a role in regulating the release of intracellular Ca2+ during P. falciparum infection. Our results support a strategy of global metabolite profiling by untargeted data acquisition. Untargeted and targeted data mining workflows, when used together to perform pathway-inferred metabolomics, have the benefit of obviating MS/MS confirmation for every detected compound.

Optimized detection of sequence variation in heterozygous genomes using DNA microarrays with isothermal-melting probes

The use of DNA microarrays to identify nucleotide variation is almost 20 years old. A variety of improvements in probe design and experimental conditions have brought this technology to the point that single-nucleotide differences can be efficiently detected in unmixed samples, although developing reliable methods for detection of mixed sequences (e.g., heterozygotes) remains challenging. Surprisingly, a comprehensive study of the probe design parameters and experimental conditions that optimize discrimination of single-nucleotide polymorphisms (SNPs) has yet to be reported, so the limits of this technology remain uncertain. By targeting 24,549 SNPs that differ between two Saccharomyces cerevisiae strains, we studied the effect of SNPs on hybridization efficiency to DNA microarray probes of different lengths under different hybridization conditions. We found that the critical parameter for optimization of sequence discrimination is the relationship between probe melting temperature (Tm) and the temperature at which the hybridization reaction is performed. This relationship can be exploited through the design of microarrays containing probes of equal Tm by varying the length of probes. We demonstrate using such a microarray that we detect >90% homozygous SNPs and >80% heterozygous SNPs using the SNPScanner algorithm. The optimized design and experimental parameters determined in this study should guide DNA microarray designs for applications that require sequence discrimination such as mutation detection, genotyping of unmixed and mixed samples, and allele-specific gene expression. Moreover, designing microarray probes with optimized sensitivity to mismatches should increase the accuracy of standard microarray applications such as copy-number variation detection and gene expression analysis.

Double Dutch: A Tool for Designing Combinatorial Libraries of Biological Systems

Recently, semirational approaches that rely on combinatorial assembly of characterized DNA components have been used to engineer biosynthetic pathways. In practice, however, it is not practical to assemble and test millions of pathway variants in order to elucidate how different DNA components affect the behavior of a pathway. To address this challenge, we apply a rigorous mathematical approach known as design of experiments (DOE) that can be used to construct empirical models of system behavior without testing all variants. To support this approach, we have developed a tool named Double Dutch, which uses a formal grammar and heuristic algorithms to automate the process of DOE library design. Compared to designing by hand, Double Dutch enables users to more efficiently and scalably design libraries of pathway variants that can be used in a DOE framework and uniquely provides a means to flexibly balance design considerations of statistical analysis, construction cost, and risk of homologous recombination, thereby demonstrating the utility of automating decision making when faced with complex design trade-offs.

Registry in a tube: multiplexed pools of retrievable parts for genetic design space exploration

Abstract Genetic designs can consist of dozens of genes and hundreds of genetic parts. After evaluating a design, it is desirable to implement changes without the cost and burden of starting the construction process from scratch. Here, we report a two-step process where a large design space is divided into deep pools of composite parts, from which individuals are retrieved and assembled to build a final construct. The pools are built via multiplexed assembly and sequenced using next-generation sequencing. Each pool consists of ∼20 Mb of up to 5000 unique and sequence-verified composite parts that are barcoded for retrieval by PCR. This approach is applied to a 16-gene nitrogen fixation pathway, which is broken into pools containing a total of 55 848 composite parts (71.0 Mb). The pools encompass an enormous design space (1043 possible 23 kb constructs), from which an algorithm-guided 192-member 4.5 Mb library is built. Next, all 1030 possible genetic circuits based on 10 repressors (NOR/NOT gates) are encoded in pools where each repressor is fused to all permutations of input promoters. These demonstrate that multiplexing can be applied to encompass entire design spaces from which individuals can be accessed and evaluated.