Showing papers by "James J. Collins published in 2012"

Wisdom of crowds for robust gene network inference

Abstract: Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus, each comprising ~1,700 transcriptional interactions at a precision of ~50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli, of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.

Wisdom of crowds for robust gene network inference

Abstract: Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus, each comprising ∼1,700 transcriptional interactions at a precision of ∼50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli, of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.

Oxidation of the Guanine Nucleotide Pool Underlies Cell Death by Bactericidal Antibiotics

Abstract: A detailed understanding of the mechanisms that underlie antibiotic killing is important for the derivation of new classes of antibiotics and clinically useful adjuvants for current antimicrobial therapies Our efforts to understand why DinB (DNA polymerase IV) overproduction is cytotoxic to Escherichia coli led to the unexpected insight that oxidation of guanine to 8-oxo-guanine in the nucleotide pool underlies much of the cell death caused by both DinB overproduction and bactericidal antibiotics We propose a model in which the cytotoxicity of beta-lactams and quinolones predominantly results from lethal double-strand DNA breaks caused by incomplete repair of closely spaced 8-oxo-deoxyguanosine lesions, whereas the cytotoxicity of aminoglycosides might additionally result from mistranslation due to the incorporation of 8-oxo-guanine into newly synthesized RNAs

Signaling-mediated bacterial persister formation

Abstract: Here we show that bacterial communication through indole signaling induces persistence, a phenomenon in which a subset of an isogenic bacterial population tolerates antibiotic treatment. We monitor indole-induced persister formation using microfluidics and identify the role of oxidative-stress and phage-shock pathways in this phenomenon. We propose a model in which indole signaling 'inoculates' a bacterial subpopulation against antibiotics by activating stress responses, leading to persister formation.

Oxidation of the Guanine Nucleotide Pool Underlies Cell Death by Bactericidal Antibiotics

Abstract: A Specific Oxidative Catastrophe Three different classes of antibiotics induce bacterial cell death by the production of hydroxyl radicals. Hydroxyl radicals are powerful oxidizing agents in living cells and will oxidize the nucleic acid base, guanine, to form 8-oxoguanine, which is potentially mutagenic because it can pair with both cytosine and adenine and form lethal double-strand DNA breaks. Foti et al. (p. 315) discovered that overproduction of the nucleotide sanitizer MutT, which hydrolyzes 8-oxo-dGTP to 8-oxo-dGMP, gives striking protection against cell death. Several antibiotics kill bacteria by causing oxidative damage to guanine nucleotides, which then damage nucleic acids. A detailed understanding of the mechanisms that underlie antibiotic killing is important for the derivation of new classes of antibiotics and clinically useful adjuvants for current antimicrobial therapies. Our efforts to understand why DinB (DNA polymerase IV) overproduction is cytotoxic to Escherichia coli led to the unexpected insight that oxidation of guanine to 8-oxo-guanine in the nucleotide pool underlies much of the cell death caused by both DinB overproduction and bactericidal antibiotics. We propose a model in which the cytotoxicity of beta-lactams and quinolones predominantly results from lethal double-strand DNA breaks caused by incomplete repair of closely spaced 8-oxo-deoxyguanosine lesions, whereas the cytotoxicity of aminoglycosides might additionally result from mistranslation due to the incorporation of 8-oxo-guanine into newly synthesized RNAs.

Oncogenic NRAS signaling differentially regulates survival and proliferation in melanoma

Abstract: NRAS-driven melanomas have limited therapeutic options. Combining genetically engineered models and oncogenic signaling inhibitors with rational systems-biology approaches, the authors compare the effects of genetic extinction of NRAS to that of chemical pathway inhibition targeting downstream MEK. The differences provide actionable targets by revealing that NRAS signaling operates as a gated output and that MEK inhibition, although inducing apoptosis, is not able to achieve further inhibition of NRAS-induced outputs such as cell-cycle progression. A combination of MEK and CDK4 inhibitors provides a more complete inhibition of NRAS signaling and a more effective antitumor effect in vivo.

A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells.

Abstract: The transcription factor Foxp3 participates dominantly in the specification and function of Foxp3(+)CD4(+) regulatory T cells (T(reg) cells) but is neither strictly necessary nor sufficient to determine the characteristic T(reg) cell signature. Here we used computational network inference and experimental testing to assess the contribution of other transcription factors to this. Enforced expression of Helios or Xbp1 elicited distinct signatures, but Eos, IRF4, Satb1, Lef1 and GATA-1 elicited exactly the same outcome, acting in synergy with Foxp3 to activate expression of most of the T(reg) cell signature, including key transcription factors, and enhancing occupancy by Foxp3 at its genomic targets. Conversely, the T(reg) cell signature was robust after inactivation of any single cofactor. A redundant genetic switch thus 'locked in' the T(reg) cell phenotype, a model that would account for several aspects of T(reg) cell physiology, differentiation and stability.

Genetic switchboard for synthetic biology applications

Abstract: A key next step in synthetic biology is to combine simple circuits into higher-order systems. In this work, we expanded our synthetic riboregulation platform into a genetic switchboard that independently controls the expression of multiple genes in parallel. First, we designed and characterized riboregulator variants to complete the foundation of the genetic switchboard; then we constructed the switchboard sensor, a testing platform that reported on quorum-signaling molecules, DNA damage, iron starvation, and extracellular magnesium concentration in single cells. As a demonstration of the biotechnological potential of our synthetic device, we built a metabolism switchboard that regulated four metabolic genes, pgi, zwf, edd, and gnd, to control carbon flow through three Escherichia coli glucose-utilization pathways: the Embden–Meyerhof, Entner–Doudoroff, and pentose phosphate pathways. We provide direct evidence for switchboard-mediated shunting of metabolic flux by measuring mRNA levels of the riboregulated genes, shifts in the activities of the relevant enzymes and pathways, and targeted changes to the E. coli metabolome. The design, testing, and implementation of the genetic switchboard illustrate the successful construction of a higher-order system that can be used for a broad range of practical applications in synthetic biology and biotechnology.

Microbial environments confound antibiotic efficacy

Abstract: Despite our continued efforts to assert control over pathogens, more and more bacteria are saying “no” to drugs. It is becoming increasingly apparent that microbial environments, influenced by intracellular and extracellular metabolic processes, modulate antibiotic susceptibility in bacteria. A deeper understanding of these environmental processes may prove crucial for the development of new antibacterial therapies.

Iterative plug-and-play methodology for constructing and modifying synthetic gene networks

Abstract: We present a methodology for the design, construction and modification of synthetic gene networks. This method emphasizes post-assembly modification of constructs based on network behavior, thus facilitating iterative design strategies and rapid tuning and repurposing of gene networks. The ease of post-construction modification afforded by this approach and the ever-increasing repository of components within the framework will help accelerate the development of functional genetic circuits for synthetic biology.

microRNA Regulatory Network Inference Identifies miR-34a as a Novel Regulator of TGF-β Signaling in Glioblastoma

Abstract: Leveraging The Cancer Genome Atlas (TCGA) multidimensional data in glioblastoma, we inferred the putative regulatory network between microRNA and mRNA using the Context Likelihood of Relatedness modeling algorithm. Interrogation of the network in context of defined molecular subtypes identified 8 microRNAs with a strong discriminatory potential between proneural and mesenchymal subtypes. Integrative in silico analyses, a functional genetic screen, and experimental validation identified miR-34a as a tumor suppressor in proneural subtype glioblastoma. Mechanistically, in addition to its direct regulation of platelet-derived growth factor receptor-alpha ( PDGFRA ), promoter enrichment analysis of context likelihood of relatedness–inferred mRNA nodes established miR-34a as a novel regulator of a SMAD4 transcriptional network. Clinically, miR-34a expression level is shown to be prognostic, where miR-34a low-expressing glioblastomas exhibited better overall survival. This work illustrates the potential of comprehensive multidimensional cancer genomic data combined with computational and experimental models in enabling mechanistic exploration of relationships among different genetic elements across the genome space in cancer. Significance: We illustrate here that network modeling of complex multidimensional cancer genomic data can generate a framework in which to explore the biology of cancers, leading to discovery of new pathogenetic insights as well as potential prognostic biomarkers. Specifically in glioblastoma, within the context of the global network, promoter enrichment analysis of network edges uncovered a novel regulation of TGF-β signaling via a Smad4 transcriptomic network by miR-34a. Cancer Discov; 2(8); 736–49. ©2012 AACR. Read the Commentary on this article by Babic et al., [p. 676][1]. This article is highlighted in the In This Issue feature, [p. 653][2]. [1]: /lookup/volpage/2/676?iss=8 [2]: /lookup/volpage/2/653?iss=8

Migration, Sociolinguistic Scale, and Educational Reproduction

Abstract: Migration-based language pluralism and globalized identity conflicts pose challenges for educational research and linguistic anthropology, in particular, how we think about education and social inequality. This article proposes new conceptual tools, drawn from linguistic anthropology as well as world systems theory, for analyzing the role of schooling in social reproduction and for investigating the dynamics of globalized social polarization. It grounds the argument in an ethnographic study of Latino migrant schoolchildren in upstate New York. [scale, migration, globalization, social reproduction, linguistic anthropology]

Regulation of Physiologic Actions of LRRK2: Focus on Autophagy

Abstract: Background: Mutations in LRRK2 are associated with familial and sporadic Parkinson’s disease (PD). Subjects with PD caused by LRRK2 mutations show pleiotropic pathology that can involve inclusions containing α-synuclein, tau or neither protein. The mechanisms by which mutations in LRRK2 lead to this pleiotropic pathology remain unknown. Objectives: To investigate mechanisms by which LRRK2 might cause PD. Methods: We used systems biology to investigate the transcriptomes from human brains, human blood cells and Caenorhabditis elegans expressing wild-type LRRK2. The role of autophagy was tested in lines of C. elegans expressing LRRK2, V337M tau or both proteins. Neuronal function was measured by quantifying thrashing. Results: Genes regulating autophagy were coordinately regulated with LRRK2. C. elegans expressing V337M tau showed reduced thrashing, as has been noted previously. Coexpressing mutant LRRK2 (R1441C or G2019S) with V337M tau increased the motor deficits. Treating the lines of C. elegans with an mTOR inhibitor that enhances autophagic flux, ridaforolimus, increased the thrashing behavior to the same level as nontransgenic nematodes. Conclusion: These data support a role for LRRK2 in autophagy, raise the possibility that deficits in autophagy contribute to the pathophysiology of LRRK2, and point to a potential therapeutic approach addressing the pathophysiology of LRRK2 in PD.

Fibrinogen-binding and platelet-aggregation activities of a Lactobacillus salivarius septicaemia isolate are mediated by a novel fibrinogen-binding protein

Abstract: The marketplace for probiotic foods is burgeoning, measured in billions of euro per annum. It is imperative, however, that all bacterial strains are fully assessed for human safety. The ability to bind fibrinogen is considered a potential pathogenicity trait that can lead to platelet aggregation, serious medical complications, and in some instances, death. Here we examined strains from species frequently used as probiotics for their ability to bind human fibrinogen. Only one strain (CCUG 47825), a Lactobacillus salivarius isolate from a case of septicaemia, was found to strongly adhere to fibrinogen. Furthermore, this strain was found to aggregate human platelets at a level comparable to the human pathogen Staphylococcus aureus. By sequencing the genome of CCUG 47825, we were able to identify candidate genes responsible for fibrinogen binding. Complementing the genetic analysis with traditional molecular microbiological techniques enabled the identification of the novel fibrinogen receptor, CCUG_2371. Although only strain CCUG 47825 bound fibrinogen under laboratory conditions, homologues of the novel fibrinogen binding gene CCUG_2371 are widespread among L. salivarius strains, maintaining their potential to bind fibrinogen if expressed. We highlight the fact that without a full genetic analysis of strains for human consumption, potential pathogenicity traits may go undetected. © 2012 Blackwell Publishing Ltd. (Less)

A Synthetic Biology Framework for Programming Eukaryotic Transcription Functions

Abstract: Eukaryotic transcription factors (TFs) perform complex and combinatorial functions within transcriptional networks. Here, we present a synthetic framework for systematically constructing eukaryotic transcription functions using artificial zinc fingers, modular DNA-binding domains found within many eukaryotic TFs. Utilizing this platform, we construct a library of orthogonal synthetic transcription factors (sTFs) and use these to wire synthetic transcriptional circuits in yeast. We engineer complex functions, such as tunable output strength and transcriptional cooperativity, by rationally adjusting a decomposed set of key component properties, e.g., DNA specificity, affinity, promoter design, protein-protein interactions. We show that subtle perturbations to these properties can transform an individual sTF between distinct roles (activator, cooperative factor, inhibitory factor) within a transcriptional complex, thus drastically altering the signal processing behavior of multi-input systems. This platform provides new genetic components for synthetic biology and enables bottom-up approaches to understanding the design principles of eukaryotic transcriptional complexes and networks.

Insulating gene circuits from context by RNA processing

Abstract: Two studies find that programmable RNA-processing tools counter the problem of context-dependence in the construction of synthetic biology circuits.

Spontaneous keloid formation in patients with Bethlem myopathy

Abstract: A 32-year-old woman and a 50-year-old man with clinically typical Bethlem myopathy developed seemingly spontaneous keloids on their shoulder region (figure). The patients did not recall any significant trauma to the skin of this region.

Abstract 4920: Gene network models identify targets for mammary tumor normalization

Abstract: Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL The majority of breast cancer therapeutics aim at slowing tumor expansion through selective killing of tumor cells. Given the enormous plasticity of cells (highlighted by recent advances in the iPS field), we instead sought to induce a cell state transition from a mammary tumor cell phenotype to a normal mammary epithelial cell state. We have tackled the critical problem of identifying target genes for the normalization or differentiation of mammary tumor cells by employing a systems biology approach that integrates computational modeling with in vivo and in vitro studies. In vivo gene expression data of mammary tumor progression in the FVB C3(1) SV40Tag transgenic mouse model were collected at multiple time points as the disease progressed from normal gland to DCIS-like lesions to invasive carcinoma. Gene regulatory network models predicted novel transcription factor targets that appeared critical to the rise of the tumor phenotype. These putative gene targets were then assessed in a 3D spheroid assay. RNAi inhibition of two computationally predicted transcription factors reverted mammary tumor cells to a normalized mammary epithelial cell phenotype, with appropriate apical/basal polarization, lumen formation and reduced proliferative index. This integrated strategy has pinpointed transcription factors for RNAi therapeutic targeting in vivo but importantly, the method is not limited to breast cancer and may be useful for many different tumor types. In summary, our major advance has been the demonstration that a gene regulatory network reverse engineering approach can identify genes that are causatively involved in cancer progression and that represent viable therapeutic differentiation targets. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4920. doi:1538-7445.AM2012-4920

Methods of treating gram-negative microbial infections

Abstract: Provided herein are methods and compositions for treatment of a microbial infection or a microbial biofilm in a subject or on a surface by administering to the subject or surface determined to have or suspected of having a microbial infection/film an antimicrobial agent in combination with a silver-containing compound (e.g., a silver salt). In some embodiments, a silver-containing compound can increase activity of the antimicrobial agent. In other embodiments, addition of a silver-containing compound to an antimicrobial agent can expand the antimicrobial spectrum of the antimicrobial agent such that the antimicrobial agent originally indicated for treatment of one microbial strain (e.g., Gram-positive microbes) becomes effective for treating additional microbial strains (e.g., Gram-negative microbes). Other aspects relating to methods and compositions for delivering an agent to a microbe by increasing the membrane permeability of the microbe are also provided herein.

Proton-motive force stimulation to potentiate aminoglycoside antibiotics against persistent bacteria

Abstract: Provided herein are compositions and methods to improve treatment of chronic infections, and reduce, delay, or inhibit formation of biofilms, using specific combinations of aminoglycoside antibiotics and high, localized concentrations of one or more PMF stimulating compounds. These novel methods are easily adapted to clinical settings as toxicity and efficacy of the antibiotics and metabolites used have already been studied in vivo, and as dosing for both the antibiotics and metabolites are known. These approaches and therapeutic methods are also useful with non-metabolic chemicals that induce proton-motive force in bacteria.

Erratum: Oncogenic NRAS signaling differentially regulates survival and proliferation in melanoma (Nature Medicine (2012) 18 (1503-1510))

Abstract: Corrigendum: Oncogenic NRAS signaling differentially regulates survival and proliferation in melanoma