Reversion to an embryonic alternative splicing program enhances leukemia stem cell self-renewal.

Formative research suggests that a human embryonic stem cell-specific alternative splicing gene regulatory network, which is repressed by Muscleblind-like (MBNL) RNA binding proteins, is involved in cell reprogramming. In this study, RNA sequencing, splice isoform-specific quantitative RT-PCR, lentiviral transduction, and in vivo humanized mouse model studies demonstrated that malignant reprogramming of progenitors into self-renewing blast crisis chronic myeloid leukemia stem cells (BC LSCs) was partially driven by decreased MBNL3. Lentiviral knockdown of MBNL3 resulted in reversion to an embryonic alternative splice isoform program typified by overexpression of CD44 transcript variant 3, containing variant exons 8-10, and BC LSC proliferation. Although isoform-specific lentiviral CD44v3 overexpression enhanced chronic phase chronic myeloid leukemia (CML) progenitor replating capacity, lentiviral shRNA knockdown abrogated these effects. Combined treatment with a humanized pan-CD44 monoclonal antibody and a breakpoint cluster region - ABL proto-oncogene 1, nonreceptor tyrosine kinase (BCR-ABL1) antagonist inhibited LSC maintenance in a niche-dependent manner. In summary, MBNL3 down-regulation-related reversion to an embryonic alternative splicing program, typified by CD44v3 overexpression, represents a previously unidentified mechanism governing malignant progenitor reprogramming in malignant microenvironments and provides a pivotal opportunity for selective BC LSC detection and therapeutic elimination.

Systematic transcriptome analysis reveals tumor-specific isoforms for ovarian cancer diagnosis and therapy.

Tumor-specific molecules are needed across diverse areas of oncology for use in early detection, diagnosis, prognosis and therapy. Large and growing public databases of transcriptome sequencing data (RNA-seq) derived from tumors and normal tissues hold the potential of yielding tumor-specific molecules, but because the data are new they have not been fully explored for this purpose. We have developed custom bioinformatic algorithms and used them with 296 high-grade serous ovarian (HGS-OvCa) tumor and 1,839 normal RNA-seq datasets to identify mRNA isoforms with tumor-specific expression. We rank prioritized isoforms by likelihood of being expressed in HGS-OvCa tumors and not in normal tissues and analyzed 671 top-ranked isoforms by high-throughput RT-qPCR. Six of these isoforms were expressed in a majority of the 12 tumors examined but not in 18 normal tissues. An additional 11 were expressed in most tumors and only one normal tissue, which in most cases was fallopian or colon. Of the 671 isoforms, the topmost 5% (n = 33) ranked based on having tumor-specific or highly restricted normal tissue expression by RT-qPCR analysis are enriched for oncogenic, stem cell/cancer stem cell, and early development loci--including ETV4, FOXM1, LSR, CD9, RAB11FIP4, and FGFRL1. Many of the 33 isoforms are predicted to encode proteins with unique amino acid sequences, which would allow them to be specifically targeted for one or more therapeutic strategies--including monoclonal antibodies and T-cell-based vaccines. The systematic process described herein is readily and rapidly applicable to the more than 30 additional tumor types for which sufficient amounts of RNA-seq already exist.

An RNA editing fingerprint of cancer stem cell reprogramming.

BACKGROUND: Deregulation of RNA editing by adenosine deaminases acting on dsRNA (ADARs) has been implicated in the progression of diverse human cancers including hematopoietic malignancies such as chronic myeloid leukemia (CML). Inflammation-associated activation of ADAR1 occurs in leukemia stem cells specifically in the advanced, often drug-resistant stage of CML known as blast crisis. However, detection of cancer stem cell-associated RNA editing by RNA sequencing in these rare cell populations can be technically challenging, costly and requires PCR validation. The objectives of this study were to validate RNA editing of a subset of cancer stem cell-associated transcripts, and to develop a quantitative RNA editing fingerprint assay for rapid detection of aberrant RNA editing in human malignancies. METHODS: To facilitate quantification of cancer stem cell-associated RNA editing in exons and intronic or 3'UTR primate-specific Alu sequences using a sensitive, cost-effective method, we established an in vitro RNA editing model and developed a sensitive RNA editing fingerprint assay that employs a site-specific quantitative PCR (RESSq-PCR) strategy. This assay was validated in a stably-transduced human leukemia cell line, lentiviral-ADAR1 transduced primary hematopoietic stem and progenitor cells, and in primary human chronic myeloid leukemia stem cells. RESULTS: In lentiviral ADAR1-expressing cells, increased RNA editing of MDM2, APOBEC3D, GLI1 and AZIN1 transcripts was detected by RESSq-PCR with improved sensitivity over sequencing chromatogram analysis. This method accurately detected cancer stem cell-associated RNA editing in primary chronic myeloid leukemia samples, establishing a cancer stem cell-specific RNA editing fingerprint of leukemic transformation that will support clinical development of novel diagnostic tools to predict and prevent cancer progression. CONCLUSIONS: RNA editing quantification enables rapid detection of malignant progenitors signifying cancer progression and therapeutic resistance, and will aid future RNA editing inhibitor development efforts.

Transcriptome sequencing reveals potential mechanism of cryptic 3' splice site selection in SF3B1-mutated cancers.

Mutations in the splicing factor SF3B1 are found in several cancer types and have been associated with various splicing defects. Using transcriptome sequencing data from chronic lymphocytic leukemia, breast cancer and uveal melanoma tumor samples, we show that hundreds of cryptic 3' splice sites (3'SSs) are used in cancers with SF3B1 mutations. We define the necessary sequence context for the observed cryptic 3' SSs and propose that cryptic 3'SS selection is a result of SF3B1 mutations causing a shift in the sterically protected region downstream of the branch point. While most cryptic 3'SSs are present at low frequency (<10%) relative to nearby canonical 3'SSs, we identified ten genes that preferred out-of-frame cryptic 3'SSs. We show that cancers with mutations in the SF3B1 HEAT 5-9 repeats use cryptic 3'SSs downstream of the branch point and provide both a mechanistic model consistent with published experimental data and affected targets that will guide further research into the oncogenic effects of SF3B1 mutation.

Characterizing the interplay between multiple levels of organization within bacterial sigma factor regulatory networks.

Bacteria contain multiple sigma factors, each targeting diverse, but often overlapping sets of promoters, thereby forming a complex network. The layout and deployment of such a sigma factor network directly impacts global transcriptional regulation and ultimately dictates the phenotype. Here we integrate multi-omic data sets to determine the topology, the operational, and functional states of the sigma factor network in Geobacter sulfurreducens, revealing a unique network topology of interacting sigma factors. Analysis of the operational state of the sigma factor network shows a highly modular structure with σ(N) being the major regulator of energy metabolism. Surprisingly, the functional state of the network during the two most divergent growth conditions is nearly static, with sigma factor binding profiles almost invariant to environmental stimuli. This first comprehensive elucidation of the interplay between different levels of the sigma factor network organization is fundamental to characterize transcriptional regulatory mechanisms in bacteria.

Transcriptome sequencing of tumor subpopulations reveals a spectrum of therapeutic options for squamous cell lung cancer.

BACKGROUND: The only therapeutic options that exist for squamous cell lung carcinoma (SCC) are standard radiation and cytotoxic chemotherapy. Cancer stem cells (CSCs) are hypothesized to account for therapeutic resistance, suggesting that CSCs must be specifically targeted. Here, we analyze the transcriptome of CSC and non-CSC subpopulations by RNA-seq to identify new potential therapeutic strategies for SCC. METHODS: We sorted a SCC into CD133- and CD133+ subpopulations and then examined both by copy number analysis (CNA) and whole genome and transcriptome sequencing. We analyzed The Cancer Genome Atlas (TCGA) transcriptome data of 221 SCCs to determine the generality of our observations. RESULTS: Both subpopulations highly expressed numerous mRNA isoforms whose protein products are active drug targets for other cancers; 31 (25%) correspond to 18 genes under active investigation as mAb targets and an additional 4 (3%) are of therapeutic interest. Moreover, we found evidence that both subpopulations were proliferatively driven by very high levels of c-Myc and the TRAIL long isoform (TRAILL) and that normal apoptotic responses to high expression of these genes was prevented through high levels of Mcl-1L and Bcl-xL and c-FlipL-isoforms for which drugs are now in clinical development. SCC RNA-seq data (n = 221) from TCGA supported our findings. Our analysis is inconsistent with the CSC concept that most cells in a cancer have lost their proliferative potential. Furthermore, our study suggests how to target both the CSC and non-CSC subpopulations with one treatment strategy. CONCLUSIONS: Our study is relevant to SCC in particular for it presents numerous potential options to standard therapy that target the entire tumor. In so doing, it demonstrates how transcriptome sequencing provides insights into the molecular underpinnings of cancer propagating cells that, importantly, can be leveraged to identify new potential therapeutic options for cancers beyond what is possible with DNA sequencing.

A Pan-BCL2 inhibitor renders bone-marrow-resident human leukemia stem cells sensitive to tyrosine kinase inhibition.

Leukemia stem cells (LSCs) play a pivotal role in the resistance of chronic myeloid leukemia (CML) to tyrosine kinase inhibitors (TKIs) and its progression to blast crisis (BC), in part, through the alternative splicing of self-renewal and survival genes. To elucidate splice-isoform regulators of human BC LSC maintenance, we performed whole-transcriptome RNA sequencing, splice-isoform-specific quantitative RT-PCR (qRT-PCR), nanoproteomics, stromal coculture, and BC LSC xenotransplantation analyses. Cumulatively, these studies show that the alternative splicing of multiple prosurvival BCL2 family genes promotes malignant transformation of myeloid progenitors into BC LSCS that are quiescent in the marrow niche and that contribute to therapeutic resistance. Notably, sabutoclax, a pan-BCL2 inhibitor, renders marrow-niche-resident BC LSCs sensitive to TKIs at doses that spare normal progenitors. These findings underscore the importance of alternative BCL2 family splice-isoform expression in BC LSC maintenance and suggest that the combinatorial inhibition of prosurvival BCL2 family proteins and BCR-ABL may eliminate dormant LSCs and obviate resistance.

ADAR1 promotes malignant progenitor reprogramming in chronic myeloid leukemia.

The molecular etiology of human progenitor reprogramming into self-renewing leukemia stem cells (LSC) has remained elusive. Although DNA sequencing has uncovered spliceosome gene mutations that promote alternative splicing and portend leukemic transformation, isoform diversity also may be generated by RNA editing mediated by adenosine deaminase acting on RNA (ADAR) enzymes that regulate stem cell maintenance. In this study, whole-transcriptome sequencing of normal, chronic phase, and serially transplantable blast crisis chronic myeloid leukemia (CML) progenitors revealed increased IFN-γ pathway gene expression in concert with BCR-ABL amplification, enhanced expression of the IFN-responsive ADAR1 p150 isoform, and a propensity for increased adenosine-to-inosine RNA editing during CML progression. Lentiviral overexpression experiments demonstrate that ADAR1 p150 promotes expression of the myeloid transcription factor PU.1 and induces malignant reprogramming of myeloid progenitors. Moreover, enforced ADAR1 p150 expression was associated with production of a misspliced form of GSK3ß implicated in LSC self-renewal. Finally, functional serial transplantation and shRNA studies demonstrate that ADAR1 knockdown impaired in vivo self-renewal capacity of blast crisis CML progenitors. Together these data provide a compelling rationale for developing ADAR1-based LSC detection and eradication strategies.

Cumulative number of cell divisions as a meaningful timescale for adaptive laboratory evolution of Escherichia coli.

Adaptive laboratory evolution (ALE) under controlled conditions has become a valuable approach for the study of the genetic and biochemical basis for microbial adaptation under a given selection pressure. Conventionally, the timescale in ALE experiments has been set in terms of number of generations. As mutations are believed to occur primarily during cell division in growing cultures, the cumulative number of cell divisions (CCD) would be an alternative way to set the timescale for ALE. Here we show that in short-term ALE (up to 40-50 days), Escherichia coli, under growth rate selection pressure, was found to undergo approximately 10(11.2) total cumulative cell divisions in the population to produce a new stable growth phenotype that results from 2 to 8 mutations. Continuous exposure to a low level of the mutagen N-methyl-N'-nitro-N-nitrosoguanidine was found to accelerate this timescale and led to a superior growth rate phenotype with a much larger number of mutations as determined with whole-genome sequencing. These results would be useful for the fundamental kinetics of the ALE process in designing ALE experiments and provide a basis for its quantitative description.

Sensitive and accurate identification of protein-DNA binding events in ChIP-chip assays using higher order derivative analysis.

Immuno-precipitation of protein-DNA complexes followed by microarray hybridization is a powerful and cost-effective technology for discovering protein-DNA binding events at the genome scale. It is still an unresolved challenge to comprehensively, accurately and sensitively extract binding event information from the produced data. We have developed a novel strategy composed of an information-preserving signal-smoothing procedure, higher order derivative analysis and application of the principle of maximum entropy to address this challenge. Importantly, our method does not require any input parameters to be specified by the user. Using genome-scale binding data of two Escherichia coli global transcription regulators for which a relatively large number of experimentally supported sites are known, we show that ∼90% of known sites were resolved to within four probes, or ∼88 bp. Over half of the sites were resolved to within two probes, or ∼38 bp. Furthermore, we demonstrate that our strategy delivers significant quantitative and qualitative performance gains over available methods. Such accurate and sensitive binding site resolution has important consequences for accurately reconstructing transcriptional regulatory networks, for motif discovery, for furthering our understanding of local and non-local factors in protein-DNA interactions and for extending the usefulness horizon of the ChIP-chip platform.

A c-type cytochrome and a transcriptional regulator responsible for enhanced extracellular electron transfer in Geobacter sulfurreducens revealed by adaptive evolution.

The stimulation of subsurface microbial metabolism often associated with engineered bioremediation of groundwater contaminants presents subsurface microorganisms, which are adapted for slow growth and metabolism in the subsurface, with new selective pressures. In order to better understand how Geobacter species might adapt to selective pressure for faster metal reduction in the subsurface, Geobacter sulfurreducens was put under selective pressure for rapid Fe(III) oxide reduction. The genomes of two resultant strains with rates of Fe(III) oxide reduction that were 10-fold higher than those of the parent strain were resequenced. Both strains contain either a single base-pair change or a 1 nucleotide insertion in a GEMM riboswitch upstream of GSU1761, a gene coding for the periplasmic c-type cytochrome designated PgcA. GSU1771, a gene coding for a SARP regulator, was also mutated in both strains. Introduction of either of the GEMM riboswitch mutations upstream of pgcA in the wild-type increased the abundance of pgcA transcripts, consistent with increased expression of pgcA in the adapted strains. One of the mutations doubled the rate of Fe(III) oxide reduction. Interruption of GSU1771 doubled the Fe(III) oxide reduction rate. This was associated with an increased in expression of pilA, the gene encoding the structural protein for the pili thought to function as microbial nanowires. The combination of the GSU1771 interruption with either of the pgcA mutations resulted in a strain that reduced Fe(III) as fast as the comparable adapted strain. These results suggest that the accumulation of a small number of beneficial mutations under selective pressure, similar to that potentially present during bioremediation, can greatly enhance the capacity for Fe(III) oxide reduction in G. sulfurreducens. Furthermore, the results emphasize the importance of the c-type cytochrome PgcA and pili in Fe(III) oxide reduction and demonstrate how adaptive evolution studies can aid in the elucidation of complex mechanisms, such as extracellular electron transfer.

Production of pilus-like filaments in Geobacter sulfurreducens in the absence of the type IV pilin protein PilA.

The pili of Geobacter sulfurreducens are of interest because of the apparent importance of the type IV pili in extracellular electron transfer. A strain of G. sulfurreducens, designated strain MA, produced many more pili than the previously studied DL-1 strain even though genome resequencing indicated that the MA and DL-1 genome sequences were identical. Filaments that looked similar to type IV pili in transmission electron micrographs were abundant even after the gene encoding PilA, the structural pilin protein, was deleted. The results of proteinase K treatment indicated that the filaments were proteinaceous. The simultaneous deletion of several genes encoding homologues of type II pseudopilins was required before the filaments were significantly depleted. The pilA-deficient MA strain attached to glass as well as the wild-type MA did, but strains in which three or four pseudopilin genes were deleted in addition to pilA had impaired attachment capabilities. These results demonstrate that there are several proteins that can yield pilin-like filaments in G. sulfurreducens and that some means other than microscopic observation is required before the composition of filaments can be unambiguously specified.

De Novo assembly of the complete genome of an enhanced electricity-producing variant of Geobacter sulfurreducens using only short reads.

State-of-the-art DNA sequencing technologies are transforming the life sciences due to their ability to generate nucleotide sequence information with a speed and quantity that is unapproachable with traditional Sanger sequencing. Genome sequencing is a principal application of this technology, where the ultimate goal is the full and complete sequence of the organism of interest. Due to the nature of the raw data produced by these technologies, a full genomic sequence attained without the aid of Sanger sequencing has yet to be demonstrated.We have successfully developed a four-phase strategy for using only next-generation sequencing technologies (Illumina and 454) to assemble a complete microbial genome de novo. We applied this approach to completely assemble the 3.7 Mb genome of a rare Geobacter variant (KN400) that is capable of unprecedented current production at an electrode. Two key components of our strategy enabled us to achieve this result. First, we integrated the two data types early in the process to maximally leverage their complementary characteristics. And second, we used the output of different short read assembly programs in such a way so as to leverage the complementary nature of their different underlying algorithms or of their different implementations of the same underlying algorithm.The significance of our result is that it demonstrates a general approach for maximizing the efficiency and success of genome assembly projects as new sequencing technologies and new assembly algorithms are introduced. The general approach is a meta strategy, wherein sequencing data are integrated as early as possible and in particular ways and wherein multiple assembly algorithms are judiciously applied such that the deficiencies in one are complemented by another.

The transcription unit architecture of the Escherichia coli genome.

Bacterial genomes are organized by structural and functional elements, including promoters, transcription start and termination sites, open reading frames, regulatory noncoding regions, untranslated regions and transcription units. Here, we iteratively integrate high-throughput, genome-wide measurements of RNA polymerase binding locations and mRNA transcript abundance, 5' sequences and translation into proteins to determine the organizational structure of the Escherichia coli K-12 MG1655 genome. Integration of the organizational elements provides an experimentally annotated transcription unit architecture, including alternative transcription start sites, 5' untranslated region, boundaries and open reading frames of each transcription unit. A total of 4,661 transcription units were identified, representing an increase of >530% over current knowledge. This comprehensive transcription unit architecture allows for the elucidation of condition-specific uses of alternative sigma factors at the genome scale. Furthermore, the transcription unit architecture provides a foundation on which to construct genome-scale transcriptional and translational regulatory networks.

Whole-genome resequencing of Escherichia coli K-12 MG1655 undergoing short-term laboratory evolution in lactate minimal media reveals flexible selection of adaptive mutations.

BACKGROUND: Short-term laboratory evolution of bacteria followed by genomic sequencing provides insight into the mechanism of adaptive evolution, such as the number of mutations needed for adaptation, genotype-phenotype relationships, and the reproducibility of adaptive outcomes. RESULTS: In the present study, we describe the genome sequencing of 11 endpoints of Escherichia coli that underwent 60-day laboratory adaptive evolution under growth rate selection pressure in lactate minimal media. Two to eight mutations were identified per endpoint. Generally, each endpoint acquired mutations to different genes. The most notable exception was an 82 base-pair deletion in the rph-pyrE operon that appeared in 7 of the 11 adapted strains. This mutation conferred an approximately 15% increase to the growth rate when experimentally introduced to the wild-type background and resulted in an approximately 30% increase to growth rate when introduced to a background already harboring two adaptive mutations. Additionally, most endpoints had a mutation in a regulatory gene (crp or relA, for example) or the RNA polymerase. CONCLUSIONS: The 82 base-pair deletion found in the rph-pyrE operon of many endpoints may function to relieve a pyrimidine biosynthesis defect present in MG1655. In contrast, a variety of regulators acquire mutations in the different endpoints, suggesting flexibility in overcoming regulatory challenges in the adaptation.

Decomposing complex reaction networks using random sampling, principal component analysis and basis rotation.

BACKGROUND: Metabolism and its regulation constitute a large fraction of the molecular activity within cells. The control of cellular metabolic state is mediated by numerous molecular mechanisms, which in effect position the metabolic network flux state at specific locations within a mathematically-definable steady-state flux space. Post-translational regulation constitutes a large class of these mechanisms, and decades of research indicate that achieving a network flux state through post-translational metabolic regulation is both a complex and complicated regulatory problem. No analysis method for the objective, top-down assessment of such regulation problems in large biochemical networks has been presented and demonstrated. RESULTS: We show that the use of Monte Carlo sampling of the steady-state flux space of a cell-scale metabolic system in conjunction with Principal Component Analysis and eigenvector rotation results in a low-dimensional and biochemically interpretable decomposition of the steady flux states of the system. This decomposition comes in the form of a low number of small reaction sets whose flux variability accounts for nearly all of the flux variability in the entire system. This result indicates an underlying simplicity and implies that the regulation of a relatively low number of reaction sets can essentially determine the flux state of the entire network in the given growth environment. CONCLUSION: We demonstrate how our top-down analysis of networks can be used to determine key regulatory requirements independent of specific parameters and mechanisms. Our approach complements the reductionist approach to elucidation of regulatory mechanisms and facilitates the development of our understanding of global regulatory strategies in biological networks.

Genome-scale reconstruction of the Lrp regulatory network in Escherichia coli.

Broad-acting transcription factors (TFs) in bacteria form regulons. Here, we present a 4-step method to fully reconstruct the leucine-responsive protein (Lrp) regulon in Escherichia coli K-12 MG 1655 that regulates nitrogen metabolism. Step 1 is composed of obtaining high-resolution ChIP-chip data for Lrp, the RNA polymerase and expression profiles under multiple environmental conditions. We identified 138 unique and reproducible Lrp-binding regions and classified their binding state under different conditions. In the second step, the analysis of these data revealed 6 distinct regulatory modes for individual ORFs. In the third step, we used the functional assignment of the regulated ORFs to reconstruct 4 types of regulatory network motifs around the metabolites that are affected by the corresponding gene products. In the fourth step, we determined how leucine, as a signaling molecule, shifts the regulatory motifs for particular metabolites. The physiological structure that emerges shows the regulatory motifs for different amino acid fall into the traditional classification of amino acid families, thus elucidating the structure and physiological functions of the Lrp-regulon. The same procedure can be applied to other broad-acting TFs, opening the way to full bottom-up reconstruction of the transcriptional regulatory network in bacterial cells.

Genome-wide analysis of Fis binding in Escherichia coli indicates a causative role for A-/AT-tracts.

We determined the genome-wide distribution of the nucleoid-associated protein Fis in Escherichia coli using chromatin immunoprecipitation coupled with high-resolution whole genome-tiling microarrays. We identified 894 Fis-associated regions across the E. coli genome. A significant number of these binding sites were found within open reading frames (33%) and between divergently transcribed transcripts (5%). Analysis indicates that A-tracts and AT-tracts are an important signal for preferred Fis-binding sites, and that A(6)-tracts in particular constitute a high-affinity signal that dictates Fis phasing in stretches of DNA containing multiple and variably spaced A-tracts and AT-tracts. Furthermore, we find evidence for an average of two Fis-binding regions per supercoiling domain in the chromosome of exponentially growing cells. Transcriptome analysis shows that approximately 21% of genes are affected by the deletion of fis; however, the changes in magnitude are small. To address the differential Fis bindings under growth environment perturbation, ChIP-chip analysis was performed using cells grown under aerobic and anaerobic growth conditions. Interestingly, the Fis-binding regions are almost identical in aerobic and anaerobic growth conditions-indicating that the E. coli genome topology mediated by Fis is superficially identical in the two conditions. These novel results provide new insight into how Fis modulates DNA topology at a genome scale and thus advance our understanding of the architectural bases of the E. coli nucleoid.

Systems biology as a foundation for genome-scale synthetic biology.

As the ambitions of synthetic biology approach genome-scale engineering, comprehensive characterization of cellular systems is required, as well as a means to accurately model cell-scale molecular interactions. These requirements are coincident with the goals of systems biology and, thus, systems biology will become the foundation for genome-scale synthetic biology. Systems biology will form this foundation through its efforts to reconstruct and integrate cellular systems, develop the mathematics, theory and software tools for the accurate modeling of these integrated systems, and through evolutionary mechanisms. As genome-scale synthetic biology is so enabled, it will prove to be a positive feedback driver of systems biology by exposing and forcing researchers to confront those aspects of systems biology which are inadequately understood.

Iterative reconstruction of transcriptional regulatory networks: an algorithmic approach.

The number of complete, publicly available genome sequences is now greater than 200, and this number is expected to rapidly grow in the near future as metagenomic and environmental sequencing efforts escalate and the cost of sequencing drops. In order to make use of this data for understanding particular organisms and for discerning general principles about how organisms function, it will be necessary to reconstruct their various biochemical reaction networks. Principal among these will be transcriptional regulatory networks. Given the physical and logical complexity of these networks, the various sources of (often noisy) data that can be utilized for their elucidation, the monetary costs involved, and the huge number of potential experiments approximately 10(12)) that can be performed, experiment design algorithms will be necessary for synthesizing the various computational and experimental data to maximize the efficiency of regulatory network reconstruction. This paper presents an algorithm for experimental design to systematically and efficiently reconstruct transcriptional regulatory networks. It is meant to be applied iteratively in conjunction with an experimental laboratory component. The algorithm is presented here in the context of reconstructing transcriptional regulation for metabolism in Escherichia coli, and, through a retrospective analysis with previously performed experiments, we show that the produced experiment designs conform to how a human would design experiments. The algorithm is able to utilize probability estimates based on a wide range of computational and experimental sources to suggest experiments with the highest potential of discovering the greatest amount of new regulatory knowledge.