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Unlabelled: Smoking is associated with several serious diseases, such as lung cancer and chronic obstructive pulmonary disease (COPD). Within our systems toxicology framework, we are assessing whether potential modified risk tobacco products (MRTP) can reduce smoking-related health risks compared to conventional cigarettes. In this article, we evaluated to what extent 2D-PAGE/MALDI MS/MS (2D-PAGE) can complement the iTRAQ LC-MS/MS results from a previously reported mouse inhalation study, in which we assessed a prototypic MRTP (pMRTP). Selected differentially expressed proteins identified by both LC-MS/MS and 2D-PAGE approaches were further verified using reverse-phase protein microarrays. LC-MS/MS captured the effects of cigarette smoke (CS) on the lung proteome more comprehensively than 2D-PAGE. However, an integrated analysis of both proteomics data sets showed that 2D-PAGE data complement the LC-MS/MS results by supporting the overall trend of lower effects of pMRTP aerosol than CS on the lung proteome. Biological effects of CS exposure supported by both methods included increases in immune-related, surfactant metabolism, proteasome, and actin cytoskeleton protein clusters. Overall, while 2D-PAGE has its value, especially as a complementary method for the analysis of effects on intact proteins, LC-MS/MS approaches will likely be the method of choice for proteome analysis in systems toxicology investigations., Significance: Quantitative proteomics is anticipated to play a growing role within systems toxicology assessment frameworks in the future. To further understand how different proteomics technologies can contribute to toxicity assessment, we conducted a quantitative proteomics analysis using 2D-PAGE and isobaric tag-based LC-MS/MS approaches and compared the results produced from the 2 approaches. Using a prototypic modified risk tobacco product (pMRTP) as our test item, we show compared with cigarette smoke, how 2D-PAGE results can complement and support LC-MS/MS data, demonstrating the much lower effects of pMRTP aerosol than cigarette smoke on the mouse lung proteome. The combined analysis of 2D-PAGE and LC-MS/MS data identified an effect of cigarette smoke on the proteasome and actin cytoskeleton in the lung., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Mouse models are useful for studying cigarette smoke (CS)-induced chronic pulmonary pathologies such as lung emphysema. To enhance translation of large-scale omics data from mechanistic studies into pathophysiological changes, we have developed computational tools based on reverse causal reasoning (RCR)., Objective: In the present study we applied a systems biology approach leveraging RCR to identify molecular mechanistic explanations of pathophysiological changes associated with CS-induced lung emphysema in susceptible mice., Methods: The lung transcriptomes of five mouse models (C57BL/6, ApoE (-/-) , A/J, CD1, and Nrf2 (-/-) ) were analyzed following 5-7 months of CS exposure., Results: We predicted 39 molecular changes mostly related to inflammatory processes including known key emphysema drivers such as NF-κB and TLR4 signaling, and increased levels of TNF-α, CSF2, and several interleukins. More importantly, RCR predicted potential molecular mechanisms that are less well-established, including increased transcriptional activity of PU.1, STAT1, C/EBP, FOXM1, YY1, and N-COR, and reduced protein abundance of ITGB6 and CFTR. We corroborated several predictions using targeted proteomic approaches, demonstrating increased abundance of CSF2, C/EBPα, C/EBPβ, PU.1, BRCA1, and STAT1., Conclusion: These systems biology-derived candidate mechanisms common to susceptible mouse models may enhance understanding of CS-induced molecular processes underlying emphysema development in mice and their relevancy for human chronic obstructive pulmonary disease.

Exposure to cigarette smoke (CS) is linked to the development of respiratory diseases, and there is a need to understand the mechanisms whereby CS causes damage. Although animal models have provided valuable insights into smoking-related respiratory tract damage, modern toxicity testing calls for reliable in vitro models as alternatives for animal experimentation. We report on a repeated whole mainstream CS exposure of nasal and bronchial organotypic tissue cultures that mimic the morphological, physiological, and molecular attributes of the human respiratory tract. Despite the similar cellular staining and cytokine secretion in both tissue types, the transcriptomic analyses in the context of biological network models identified similar and diverse biological processes that were impacted by CS-exposed nasal and bronchial cultures. Our results demonstrate that nasal and bronchial tissue cultures are appropriate in vitro models for the assessment of CS-induced adverse effects in the respiratory system and promising alternative to animal experimentation., (© The Author(s) 2014.)

Smoking has been associated with diseases of the lung, pulmonary airways and oral cavity. Cytologic, genomic and transcriptomic changes in oral mucosa correlate with oral pre-neoplasia, cancer and inflammation (e.g. periodontitis). Alteration of smoking-related gene expression changes in oral epithelial cells is similar to that in bronchial and nasal epithelial cells. Using a systems toxicology approach, we have previously assessed the impact of cigarette smoke (CS) seen as perturbations of biological processes in human nasal and bronchial organotypic epithelial culture models. Here, we report our further assessment using in vitro human oral organotypic epithelium models. We exposed the buccal and gingival organotypic epithelial tissue cultures to CS at the air-liquid interface. CS exposure was associated with increased secretion of inflammatory mediators, induction of cytochrome P450s activity and overall weak toxicity in both tissues. Using microarray technology, gene-set analysis and a novel computational modeling approach leveraging causal biological network models, we identified CS impact on xenobiotic metabolism-related pathways accompanied by a more subtle alteration in inflammatory processes. Gene-set analysis further indicated that the CS-induced pathways in the in vitro buccal tissue models resembled those in the in vivo buccal biopsies of smokers from a published dataset. These findings support the translatability of systems responses from in vitro to in vivo and demonstrate the applicability of oral organotypical tissue models for an impact assessment of CS on various tissues exposed during smoking, as well as for impact assessment of reduced-risk products.

In yeast, ribosome production is controlled transcriptionally by tight coregulation of the 138 ribosomal protein genes (RPGs). RPG promoters display limited sequence homology, and the molecular basis for their coregulation remains largely unknown. Here we identify two prevalent RPG promoter types, both characterized by upstream binding of the general transcription factor (TF) Rap1 followed by the RPG-specific Fhl1/Ifh1 pair, with one type also binding the HMG-B protein Hmo1. We show that the regulatory properties of the two promoter types are remarkably similar, suggesting that they are determined to a large extent by Rap1 and the Fhl1/Ifh1 pair. Rapid depletion experiments allowed us to define a hierarchy of TF binding in which Rap1 acts as a pioneer factor required for binding of all other TFs. We also uncovered unexpected features underlying recruitment of Fhl1, whose forkhead DNA-binding domain is not required for binding at most promoters, and Hmo1, whose binding is supported by repeated motifs. Finally, we describe unusually micrococcal nuclease (MNase)-sensitive nucleosomes at all RPG promoters, located between the canonical +1 and -1 nucleosomes, which coincide with sites of Fhl1/Ifh1 and Hmo1 binding. We speculate that these "fragile" nucleosomes play an important role in regulating RPG transcriptional output., (© 2014 Knight et al.; Published by Cold Spring Harbor Laboratory Press.)

Mapping gene regulatory networks is a significant challenge in systems biology, yet only a few methods are currently capable of systems-level identification of transcription factors (TFs) that bind a specific regulatory element. We developed a microfluidic method for integrated systems-level interaction mapping of TF-DNA interactions, generating and interrogating an array of 423 full-length Drosophila TFs. With integrated systems-level interaction mapping, it is now possible to rapidly and quantitatively map gene regulatory networks of higher eukaryotes.

Quantitative biology requires quantitative data. No high-throughput technologies exist capable of obtaining several hundred independent kinetic binding measurements in a single experiment. We present an integrated microfluidic device (k-MITOMI) for the simultaneous kinetic characterization of 768 biomolecular interactions. We applied k-MITOMI to the kinetic analysis of transcription factor (TF)-DNA interactions, measuring the detailed kinetic landscapes of the mouse TF Zif268, and the yeast TFs Tye7p, Yox1p, and Tbf1p. We demonstrated the integrated nature of k-MITOMI by expressing, purifying, and characterizing 27 additional yeast transcription factors in parallel on a single device. Overall, we obtained 2,388 association and dissociation curves of 223 unique molecular interactions with equilibrium dissociation constants ranging from 2 × 10(-6) M to 2 × 10(-9) M, and dissociation rate constants of approximately 6 s(-1) to 8.5 × 10(-3) s(-1). Association rate constants were uniform across 3 TF families, ranging from 3.7 × 10(6) M(-1) s(-1) to 9.6 × 10(7) M(-1) s(-1), and are well below the diffusion limit. We expect that k-MITOMI will contribute to our quantitative understanding of biological systems and accelerate the development and characterization of engineered systems.

Characterizing libraries of mutant proteins is a challenging task, but can lead to detailed functional insights on a specific protein, and general insights for families of proteins such as transcription factors. Challenges in mutant protein screening consist in synthesizing the necessary expression-ready DNA constructs and transforming them into a suitable host for protein expression. Protein purification and characterization are also non-trivial tasks that are not easily scalable to hundreds or thousands of protein variants. Here we describe a method based on a high-throughput microfluidic platform to screen and characterize the binding profile of hundreds of transcription factor variants. DNA constructs are synthesized by a rapid two-step PCR approach without the need of cloning or transformation steps. All transcription factor mutants are expressed on-chip followed by characterization of their binding specificities against 64 different DNA target sequences. The current microfluidic platform can synthesize and characterize up to 2,400 protein-DNA pairs in parallel. The platform method is also generally applicable, allowing high-throughput functional studies of proteins.

Gene regulatory networks (GRNs) consist of transcription factors (TFs) that determine the level of gene expression by binding to specific DNA sequences. Mapping all TF-DNA interactions and elucidating their dynamics is a major goal to generate comprehensive models of GRNs. Measuring quantitative binding affinities of large sets of TF-DNA interactions requires the application of novel tools and methods. These tools need to cope with the difficulties related to the facts that TFs tend to be expressed at low levels in vivo, and often form only transient interactions with both DNA and their protein partners. Our approach describes a high-throughput microfluidic platform with a novel detection principle based on the mechanically induced trapping of molecular interactions (MITOMI). MITOMI allows the detection of transient and low-affinity TF-DNA interactions in high-throughput.

In growing bacterial cells, the global reorganization of transcription is associated with alterations of RNA polymerase composition and the superhelical density of the DNA. However, the existence of any regulatory device coordinating these changes remains elusive. Here we show that in an exponentially growing Escherichia coli rpoZ mutant lacking the polymerase ω subunit, the impact of the Eσ(38) holoenzyme on transcription is enhanced in parallel with overall DNA relaxation. Conversely, overproduction of σ(70) in an rpoZ mutant increases both overall DNA supercoiling and the transcription of genes utilizing high negative superhelicity. We further show that transcription driven by the Eσ(38) and Eσ(70) holoenzymes from cognate promoters induces distinct superhelical densities of plasmid DNA in vivo. We thus demonstrate a tight coupling between polymerase holoenzyme composition and the supercoiling regimen of genomic transcription. Accordingly, we identify functional clusters of genes with distinct σ factor and supercoiling preferences arranging alternative transcription programs sustaining bacterial exponential growth. We propose that structural coupling between DNA topology and holoenzyme composition provides a basic regulatory device for coordinating genome-wide transcription during bacterial growth and adaptation. IMPORTANCE Understanding the mechanisms of coordinated gene expression is pivotal for developing knowledge-based approaches to manipulating bacterial physiology, which is a problem of central importance for applications of biotechnology and medicine. This study explores the relationships between variations in the composition of the transcription machinery and chromosomal DNA topology and suggests a tight interdependence of these two variables as the major coordinating principle of gene regulation. The proposed structural coupling between the transcription machinery and DNA topology has evolutionary implications and suggests a new methodology for studying concerted alterations of gene expression during normal and pathogenic growth both in bacteria and in higher organisms.

Background: The 3D structure of the chromosome of the model organism Escherichia coli is one key component of its gene regulatory machinery. This type of regulation mediated by topological transitions of the chromosomal DNA can be thought of as an analog control, complementing the digital control, i.e. the network of regulation mediated by dedicated transcription factors. It is known that alterations in the superhelical density of chromosomal DNA lead to a rich pattern of differential expressed genes. Using a network approach, we analyze these expression changes for wild type E. coli and mutants lacking nucleoid associated proteins (NAPs) from a metabolic and transcriptional regulatory network perspective., Results: We find a significantly higher correspondence between gene expression and metabolism for the wild type expression changes compared to mutants in NAPs, indicating that supercoiling induces meaningful metabolic adjustments. As soon as the underlying regulatory machinery is impeded (as for the NAP mutants), this coherence between expression changes and the metabolic network is substantially reduced. This effect is even more pronounced, when we compute a wild type metabolic flux distribution using flux balance analysis and restrict our analysis to active reactions. Furthermore, we are able to show that the regulatory control exhibited by DNA supercoiling is not mediated by the transcriptional regulatory network (TRN), as the consistency of the expression changes with the TRN logic of activation and suppression is strongly reduced in the wild type in comparison to the mutants., Conclusions: So far, the rich patterns of gene expression changes induced by alterations of the superhelical density of chromosomal DNA have been difficult to interpret. Here we characterize the effective networks formed by supercoiling-induced gene expression changes mapped onto reconstructions of E. coli's metabolic and transcriptional regulatory network. Our results show that DNA supercoiling coordinates gene expression with metabolism. Furthermore, this control is acting directly because we can exclude the potential role of the TRN as a mediator.

Specific binding of transcription factors (TFs) determines in a large part the connectivity of gene regulatory networks as well as the quantitative level of gene expression. A multiplicity of both experimental and computational methods is currently used to discover and characterize the underlying TF-DNA interactions. Experimental methods can be further subdivided into in vitro- and in vivo-based approaches, each accenting different aspects of TF-binding events. In this review we summarize the flexibility and performance of a selection of both types of experimental methods. In conclusion, we argue that a serial combination of methods with different throughput and data type constitutes an optimal experimental strategy.

Recent advances of systemic approaches to gene expression and cellular metabolism provide unforeseen opportunities for relating and integrating extensive datasets describing the transcriptional regulation system as a whole. However, due to the multifaceted nature of the phenomenon, these datasets often contain logically distinct types of information determined by underlying approach and adopted methodology of data analysis. Consequently, to integrate the datasets comprising information on the states of chromatin structure, transcriptional regulatory network and cellular metabolism, a novel methodology enabling interconversion of logically distinct types of information is required. Here we provide a holistic conceptual framework for analysis of global transcriptional regulation as a system coordinated by structural coupling between the transcription machinery and DNA topology, acting as interdependent sensors and determinants of metabolic functions. In this operationally closed system any transition in physiological state represents an emergent property determined by shifts in structural coupling, whereas genetic regulation acts as a genuine device converting one logical type of information into the other.

The histone-like protein HU is a highly abundant DNA architectural protein that is involved in compacting the DNA of the bacterial nucleoid and in regulating the main DNA transactions, including gene transcription. However, the coordination of the genomic structure and function by HU is poorly understood. Here, we address this question by comparing transcript patterns and spatial distributions of RNA polymerase in Escherichia coli wild-type and hupA/B mutant cells. We demonstrate that, in mutant cells, upregulated genes are preferentially clustered in a large chromosomal domain comprising the ribosomal RNA operons organized on both sides of OriC. Furthermore, we show that, in parallel to this transcription asymmetry, mutant cells are also impaired in forming the transcription foci-spatially confined aggregations of RNA polymerase molecules transcribing strong ribosomal RNA operons. Our data thus implicate HU in coordinating the global genomic structure and function by regulating the spatial distribution of RNA polymerase in the nucleoid.

Background: In the bacterium Escherichia coli the transcriptional regulation of gene expression involves both dedicated regulators binding specific DNA sites with high affinity and also global regulators - abundant DNA architectural proteins of the bacterial nucleoid binding multiple sites with a wide range of affinities and thus modulating the superhelical density of DNA. The first form of transcriptional regulation is predominantly pairwise and specific, representing digitial control, while the second form is (in strength and distribution) continuous, representing analog control., Results: Here we look at the properties of effective networks derived from significant gene expression changes under variation of the two forms of control and find that upon limitations of one type of control (caused e.g. by mutation of a global DNA architectural factor) the other type can compensate for compromised regulation. Mutations of global regulators significantly enhance the digital control, whereas in the presence of global DNA architectural proteins regulation is mostly of the analog type, coupling spatially neighboring genomic loci. Taken together our data suggest that two logically distinct - digital and analog - types of control are balancing each other., Conclusion: By revealing two distinct logical types of control, our approach provides basic insights into both the organizational principles of transcriptional regulation and the mechanisms buffering genetic flexibility. We anticipate that the general concept of distinguishing logical types of control will apply to many complex biological networks.

The global transcriptional regulator H-NS selectively silences bacterial genes associated with pathogenicity and responses to environmental insults. Although there is ample evidence that H-NS binds preferentially to DNA containing curved regions, we show here that a major basis for this selectivity is the presence of a conserved sequence motif in H-NS target transcriptons. We further show that there is a strong tendency for the H-NS binding sites to be clustered, both within operons and in genes contained in the pathogenicity-associated islands. In accordance with previously published findings, we show that these motifs occur in AT-rich regions of DNA. On the basis of these observations, we propose that H-NS silences extensive regions of the bacterial chromosome by binding first to nucleating high-affinity sites and then spreading along AT-rich DNA. This spreading would be reinforced by the frequent occurrence of the motif in such regions. Our findings suggest that such an organization enables the silencing of extensive regions of the genetic material, thereby providing a coherent framework that unifies studies on the H-NS protein and a concrete molecular basis for the genetic control of H-NS transcriptional silencing.

Regulation of cellular growth implies spatiotemporally coordinated programmes of gene transcription. A central question, therefore, is how global transcription is coordinated in the genome. The growth of the unicellular organism Escherichia coli is associated with changes in both the global superhelicity modulated by cellular topoisomerase activity and the relative proportions of the abundant DNA-architectural chromatin proteins. Using a DNA-microarray-based approach that combines mutations in the genes of two important chromatin proteins with induced changes of DNA superhelicity, we demonstrate that genomic transcription is tightly associated with the spatial distribution of supercoiling sensitivity, which in turn depends on chromatin proteins. We further demonstrate that essential metabolic pathways involved in the maintenance of growth respond distinctly to changes of superhelicity. We infer that a homeostatic mechanism organizing the supercoiling sensitivity is coordinating the growth-phase-dependent transcription of the genome.