Analog regulation of metabolic demand

Network location and clustering of genetic mutations determine chronicity in a stylized model of genetic diseases

In a highly simplified view, a disease can be seen as the phenotype emerging from the interplay of genetic predisposition and fluctuating environmental stimuli. We formalize this situation in a minimal model, where a network (representing cellular regulation) serves as an interface between an input layer (representing environment) and an output layer (representing functional phenotype). Genetic predisposition for a disease is represented as a loss of function of some network nodes. Reduced, but non-zero, output indicates disease. The simplicity of this genetic disease model and its deep relationship to percolation theory allows us to understand the interplay between disease, network topology and the location and clusters of affected network nodes. We find that our model generates two different characteristics of diseases, which can be interpreted as chronic and acute diseases. In its stylized form, our model provides a new view on the relationship between genetic mutations and the type and severity of a disease.

Relationship between the Chromosome Structural Dynamics and Gene Expression—A Chicken and Egg Dilemma?

Prokaryotic transcription was extensively studied over the last half-century. A great deal of data has been accumulated regarding the control of gene expression by transcription factors regulating their target genes by binding at specific DNA sites. However, there is a significant gap between the mechanistic description of transcriptional control obtained from in vitro biochemical studies and the complexity of transcriptional regulation in the context of the living cell. Indeed, recent studies provide ample evidence for additional levels of complexity pertaining to the regulation of transcription in vivo, such as, for example, the role of the subcellular localization and spatial organization of different molecular components involved in the transcriptional control and, especially, the role of chromosome configurational dynamics. The question as to how the chromosome is dynamically reorganized under the changing environmental conditions and how this reorganization is related to gene expression is still far from being clear. In this article, we focus on the relationships between the chromosome structural dynamics and modulation of gene expression during bacterial adaptation. We argue that spatial organization of the bacterial chromosome is of central importance in the adaptation of gene expression to changing environmental conditions and vice versa, that gene expression affects chromosome dynamics.

The bacterial promoter spacer modulates promoter strength and timing by length, TG-motifs and DNA supercoiling sensitivity

Transcription, the first step to gene expression, is a central coordination process in all living matter. Besides a plethora of regulatory mechanisms, the promoter architecture sets the foundation of expression strength, timing and the potential for further regulatory modulation. In this study, we investigate the effects of promoter spacer length and sequence composition on strength and supercoiling sensitivity in bacteria. Combining transcriptomics data analysis and standardized synthetic promoter libraries, we exclude effects of specific promoter sequence contexts. Analysis of promoter activity shows a strong variance with spacer length and spacer sequence composition. A detailed study of the spacer sequence composition under selective conditions reveals an extension to the -10 region that enhances RNAP binding but damps promoter activity. Using physiological changes in DNA supercoiling levels, we link promoter supercoiling sensitivity to overall spacer GC-content. Time-resolved promoter activity screens, only possible with a novel mild treatment approach, reveal strong promoter timing potentials solely based on DNA supercoiling sensitivity in the absence of regulatory sites or alternative sigma factors.

A minimal model for gene expression dynamics of bacterial type II toxin-antitoxin systems

Toxin-antitoxin (TA) modules are part of most bacteria's regulatory machinery for stress responses and general aspects of their physiology. Due to the interplay of a long-lived toxin with a short-lived antitoxin, TA modules have also become systems of interest for mathematical modelling. Here we resort to previous modelling efforts and extract from these a minimal model of type II TA system dynamics on a timescale of hours, which can be used to describe time courses derived from gene expression data of TA pairs. We show that this model provides a good quantitative description of TA dynamics for the 11 TA pairs under investigation here, while simpler models do not. Our study brings together aspects of Biophysics with its focus on mathematical modelling and Computational Systems Biology with its focus on the quantitative interpretation of 'omics' data. This mechanistic model serves as a generic transformation of time course information into kinetic parameters. The resulting parameter vector can, in turn, be mechanistically interpreted. We expect that TA pairs with similar mechanisms are characterized by similar vectors of kinetic parameters, allowing us to hypothesize on the mode of action for TA pairs still under discussion.

Composition of Transcription Machinery and Its Crosstalk with Nucleoid-Associated Proteins and Global Transcription Factors

The coordination of bacterial genomic transcription involves an intricate network of interdependent genes encoding nucleoid-associated proteins (NAPs), DNA topoisomerases, RNA polymerase subunits and modulators of transcription machinery. The central element of this homeostatic regulatory system, integrating the information on cellular physiological state and producing a corresponding transcriptional response, is the multi-subunit RNA polymerase (RNAP) holoenzyme. In this review article, we argue that recent observations revealing DNA topoisomerases and metabolic enzymes associated with RNAP supramolecular complex support the notion of structural coupling between transcription machinery, DNA topology and cellular metabolism as a fundamental device coordinating the spatiotemporal genomic transcription. We analyse the impacts of various combinations of RNAP holoenzymes and global transcriptional regulators such as abundant NAPs, on genomic transcription from this viewpoint, monitoring the spatiotemporal patterns of couplons—overlapping subsets of the regulons of NAPs and RNAP sigma factors. We show that the temporal expression of regulons is by and large, correlated with that of cognate regulatory genes, whereas both the spatial organization and temporal expression of couplons is distinctly impacted by the regulons of NAPs and sigma factors. We propose that the coordination of the growth phase-dependent concentration gradients of global regulators with chromosome configurational dynamics determines the spatiotemporal patterns of genomic expression.

DNA sequence-directed cooperation between nucleoid-associated proteins

Nucleoid-associated proteins (NAPs) are a class of highly abundant DNA-binding proteins in bacteria and archaea. While both the composition and relative abundance of the NAPs change during the bacterial growth cycle, surprisingly little is known about their crosstalk in mutually binding and stabilizing higher-order nucleoprotein complexes in the bacterial chromosome. Here, we use atomic force microscopy and solid-state nanopores to investigate long-range nucleoprotein structures formed by the binding of two major NAPs, FIS and H-NS, to DNA molecules with distinct binding site arrangements. We find that spatial organization of the protein binding sites can govern the higher-order architecture of the nucleoprotein complexes. Based on sequence arrangement the complexes differed in their global shape and compaction as well as the extent of FIS and H-NS binding. Our observations highlight the important role the DNA sequence plays in driving structural differentiation within the bacterial chromosome.

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The location of protein binding sites along DNA is important for 3D organization

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FIS protein forms DNA loops while H-NS forms compact DNA plectonemes

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FIS DNA loops inhibit H-NS from spreading over the DNA

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FIS and H-NS competition creates regions of ‘open’ and ‘closed’ DNA

A hexokinase isoenzyme switch in human liver cancer cells promotes lipogenesis and enhances innate immunity

During the cancerous transformation of normal hepatocytes into hepatocellular carcinoma (HCC), the enzyme catalyzing the first rate-limiting step of glycolysis, namely the glucokinase (GCK), is replaced by the higher affinity isoenzyme, hexokinase 2 (HK2). Here, we show that in HCC tumors the highest expression level of HK2 is inversely correlated to GCK expression, and is associated to poor prognosis for patient survival. To further explore functional consequences of the GCK-to-HK2 isoenzyme switch occurring during carcinogenesis, HK2 was knocked-out in the HCC cell line Huh7 and replaced by GCK, to generate the Huh7-GCK⁺/HK2⁻ cell line. HK2 knockdown and GCK expression rewired central carbon metabolism, stimulated mitochondrial respiration and restored essential metabolic functions of normal hepatocytes such as lipogenesis, VLDL secretion, glycogen storage. It also reactivated innate immune responses and sensitivity to natural killer cells, showing that consequences of the HK switch extend beyond metabolic reprogramming.

Many cancers fuel their rapid growth by replacing glucokinase with its higher affinity isoenzyme, hexokinase 2 (HK2), making HK2 an attractive drug target. In this study, Perrin-Cocon and Vidalain et al. use CRISPR/Cas-9 gene editing to reverse this enzymatic switch in human liver cancer cells, and find this restores innate immune function as well as reversing cancer-associated metabolic reprogramming.

Chromosomal origin of replication coordinates logically distinct types of bacterial genetic regulation

For a long time it has been hypothesized that bacterial gene regulation involves an intricate interplay of the transcriptional regulatory network (TRN) and the spatial organization of genes in the chromosome. Here we explore this hypothesis both on a structural and on a functional level. On the structural level, we study the TRN as a spatially embedded network. On the functional level, we analyze gene expression patterns from a network perspective (“digital control”), as well as from the perspective of the spatial organization of the chromosome (“analog control”). Our structural analysis reveals the outstanding relevance of the symmetry axis defined by the origin (Ori) and terminus (Ter) of replication for the network embedding and, thus, suggests the co-evolution of two regulatory infrastructures, namely the transcriptional regulatory network and the spatial arrangement of genes on the chromosome, to optimize the cross-talk between two fundamental biological processes: genomic expression and replication. This observation is confirmed by the functional analysis based on the differential gene expression patterns of more than 4000 pairs of microarray and RNA-Seq datasets for E. coli from the Colombos Database using complex network and machine learning methods. This large-scale analysis supports the notion that two logically distinct types of genetic control are cooperating to regulate gene expression in a complementary manner. Moreover, we find that the position of the gene relative to the Ori is a feature of very high predictive value for gene expression, indicating that the Ori–Ter symmetry axis coordinates the action of distinct genetic control mechanisms.

Chromosomal Organization and Regulation of Genetic Function in Escherichia coli Integrates the DNA Analog and Digital Information

In this article, we summarize our current understanding of the bacterial genetic regulation brought about by decades of studies using the Escherichia coli model. It became increasingly evident that the cellular genetic regulation system is organizationally closed, and a major challenge is to describe its circular operation in quantitative terms. We argue that integration of the DNA analog information (i.e., the probability distribution of the thermodynamic stability of base steps) and digital information (i.e., the probability distribution of unique triplets) in the genome provides a key to understanding the organizational logic of genetic control. During bacterial growth and adaptation, this integration is mediated by changes of DNA supercoiling contingent on environmentally induced shifts in intracellular ionic strength and energy charge. More specifically, coupling of dynamic alterations of the local intrinsic helical repeat in the structurally heterogeneous DNA polymer with structural-compositional changes of RNA polymerase holoenzyme emerges as a fundamental organizational principle of the genetic regulation system. We present a model of genetic regulation integrating the genomic pattern of DNA thermodynamic stability with the gene order and function along the chromosomal OriC-Ter axis, which acts as a principal coordinate system organizing the regulatory interactions in the genome.

Coherent Domains of Transcription Coordinate Gene Expression During Bacterial Growth and Adaptation

Recent studies strongly suggest that in bacteria, both the genomic pattern of DNA thermodynamic stability and the order of genes along the chromosomal origin-to-terminus axis are highly conserved and that this spatial organization plays a crucial role in coordinating genomic transcription. In this article, we explore the relationship between genomic sequence organization and transcription in the commensal bacterium Escherichia coli and the plant pathogen Dickeya. We argue that, while in E. coli the gradient of DNA thermodynamic stability and gene order along the origin-to-terminus axis represent major organizational features orchestrating temporal gene expression, the genomic sequence organization of Dickeya is more complex, demonstrating extended chromosomal domains of thermodynamically distinct DNA sequences eliciting specific transcriptional responses to various kinds of stress encountered during pathogenic growth. This feature of the Dickeya genome is likely an adaptation to the pathogenic lifestyle utilizing differences in genomic sequence organization for the selective expression of virulence traits. We propose that the coupling of DNA thermodynamic stability and genetic function provides a common organizational principle for the coordinated expression of genes during both normal and pathogenic bacterial growth.

A system-wide network reconstruction of gene regulation and metabolism in Escherichia coli

Genome-scale metabolic models have become a fundamental tool for examining metabolic principles. However, metabolism is not solely characterized by the underlying biochemical reactions and catalyzing enzymes, but also affected by regulatory events. Since the pioneering work of Covert and co-workers as well as Shlomi and co-workers it is debated, how regulation and metabolism synergistically characterize a coherent cellular state. The first approaches started from metabolic models, which were extended by the regulation of the encoding genes of the catalyzing enzymes. By now, bioinformatics databases in principle allow addressing the challenge of integrating regulation and metabolism on a system-wide level. Collecting information from several databases we provide a network representation of the integrated gene regulatory and metabolic system for Escherichia coli, including major cellular processes, from metabolic processes via protein modification to a variety of regulatory events. Besides transcriptional regulation, we also take into account regulation of translation, enzyme activities and reactions. Our network model provides novel topological characterizations of system components based on their positions in the network. We show that network characteristics suggest a representation of the integrated system as three network domains (regulatory, metabolic and interface networks) instead of two. This new three-domain representation reveals the structural centrality of components with known high functional relevance. This integrated network can serve as a platform for understanding coherent cellular states as active subnetworks and to elucidate crossover effects between metabolism and gene regulation.

The E. coli transcriptional regulatory network and its spatial embedding

Usually complex networks are studied as graphs consisting of nodes whose spatial arrangement is of no significance. Several real biological networks are, however, embedded in space. In this paper we study the transcription regulatory network (TRN) of E. coli as a spatially embedded network. The embedding space of this network is the circular E. coli chromosome, i.e. it is practically one dimensional. However, the TRN itself is a high-dimensional network due to the existence of an adequate number of long-range connections. We find that nodes in short topological distance l = 1, 2 tend, on average, to be in shorter spatial distances r indicating an abundance of short-range connections as well. Community analysis of the TRN reveals the interesting fact that highly interconnected subnets consist of nodes that tend to be in spatial proximity on the circular chromosome. We also find indications that for certain transcriptional aspects of the E. coli it is advantageous to treat the circular genome as two line segments starting from the OriC and ending to Ter.

The metabolic network coherence of human transcriptomes is associated with genetic variation at the cadherin 18 locus

Metabolic coherence (MC) is a network-based approach to dimensionality reduction that can be used, for example, to interpret the joint expression of genes linked to human metabolism. Computationally, the derivation of 'transcriptomic' MC involves mapping of an individual gene expression profile onto a gene-centric network derived beforehand from a metabolic network (currently Recon2), followed by the determination of the connectivity of a particular, profile-specific subnetwork. The biological significance of MC has been exemplified previously in the context of human inflammatory bowel disease, among others, but the genetic architecture of this quantitative cellular trait is still unclear. Therefore, we performed a genome-wide association study (GWAS) of MC in the 1000 Genomes/ GEUVADIS data (n = 457) and identified a solitary genome-wide significant association with single nucleotide polymorphisms (SNPs) in the intronic region of the cadherin 18 (CDH18) gene on chromosome 5 (lead SNP: rs11744487, p = 1.2 × 10^- 8). Cadherin 18 is a transmembrane protein involved in human neural development and cell-to-cell signaling. Notably, genetic variation at the CDH18 locus has been associated with metabolic syndrome-related traits before. Replication of our genome-wide significant GWAS result was successful in another population study from the Netherlands (BIOS, n = 2661; lead SNP), but failed in two additional studies (KORA, Germany, n = 711; GENOA, USA, n = 411). Besides sample size issues, we surmise that these discrepant findings may be attributable to technical differences. While 1000 Genomes/GEUVADIS and BIOS gene expression profiles were generated by RNA sequencing, the KORA and GENOA data were microarray-based. In addition to providing first evidence for a link between regional genetic variation and a metabolism-related characteristic of human transcriptomes, our findings highlight the benefit of adopting a systems biology-oriented approach to molecular data analysis.

Connectivity and complex systems: learning from a multi-disciplinary perspective

In recent years, parallel developments in disparate disciplines have focused on what has come to be termed connectivity; a concept used in understanding and describing complex systems. Conceptualisations and operationalisations of connectivity have evolved largely within their disciplinary boundaries, yet similarities in this concept and its application among disciplines are evident. However, any implementation of the concept of connectivity carries with it both ontological and epistemological constraints, which leads us to ask if there is one type or set of approach(es) to connectivity that might be applied to all disciplines. In this review we explore four ontological and epistemological challenges in using connectivity to understand complex systems from the standpoint of widely different disciplines. These are: (i) defining the fundamental unit for the study of connectivity; (ii) separating structural connectivity from functional connectivity; (iii) understanding emergent behaviour; and (iv) measuring connectivity. We draw upon discipline-specific insights from Computational Neuroscience, Ecology, Geomorphology, Neuroscience, Social Network Science and Systems Biology to explore the use of connectivity among these disciplines. We evaluate how a connectivity-based approach has generated new understanding of structural-functional relationships that characterise complex systems and propose a 'common toolbox' underpinned by network-based approaches that can advance connectivity studies by overcoming existing constraints.

Uncoupling of mucosal gene regulation, mRNA splicing and adherent microbiota signatures in inflammatory bowel disease

OBJECTIVE

An inadequate host response to the intestinal microbiota likely contributes to the manifestation and progression of human inflammatory bowel disease (IBD). However, molecular approaches to unravelling the nature of the defective crosstalk and its consequences for intestinal metabolic and immunological networks are lacking. We assessed the mucosal transcript levels, splicing architecture and mucosa-attached microbial communities of patients with IBD to obtain a comprehensive view of the underlying, hitherto poorly characterised interactions, and how these are altered in IBD.

DESIGN

Mucosal biopsies from Crohn's disease and patients with UC, disease controls and healthy individuals (n=63) were subjected to microbiome, transcriptome and splicing analysis, employing next-generation sequencing. The three data levels were integrated by different bioinformatic approaches, including systems biology-inspired network and pathway analysis.

RESULTS

Microbiota, host transcript levels and host splicing patterns were influenced most strongly by tissue differences, followed by the effect of inflammation. Both factors point towards a substantial disease-related alteration of metabolic processes. We also observed a strong enrichment of splicing events in inflamed tissues, accompanied by an alteration of the mucosa-attached bacterial taxa. Finally, we noted a striking uncoupling of the three molecular entities when moving from healthy individuals via disease controls to patients with IBD.

CONCLUSIONS

Our results provide strong evidence that the interplay between microbiome and host transcriptome, which normally characterises a state of intestinal homeostasis, is drastically perturbed in Crohn's disease and UC. Consequently, integrating multiple OMICs levels appears to be a promising approach to further disentangle the complexity of IBD.

Chromosomal organization of transcription: in a nutshell

Early studies of transcriptional regulation focused on individual gene promoters defined specific transcription factors as central agents of genetic control. However, recent genome-wide data propelled a different view by linking spatially organized gene expression patterns to chromosomal dynamics. Therefore, the major problem in contemporary molecular genetics concerned with transcriptional gene regulation is to establish a unifying model that reconciles these two views. This problem, situated at the interface of polymer physics and network theory, requires development of an integrative methodology. In this review, we discuss recent achievements in classical model organism E. coli and provide some novel insights gained from studies of a bacterial plant pathogen, D. dadantii. We consider DNA topology and the basal transcription machinery as key actors of regulation, in which activation of functionally relevant genes is coupled to and coordinated with the establishment of extended chromosomal domains of coherent transcription. We argue that the spatial organization of genome plays a fundamental role in its own regulation.

Distinct metabolic network states manifest in the gene expression profiles of pediatric inflammatory bowel disease patients and controls

Information on biological networks can greatly facilitate the function-orientated interpretation of high-throughput molecular data. Genome-wide metabolic network models of human cells, in particular, can be employed to contextualize gene expression profiles of patients with the goal of both, a better understanding of individual etiologies and an educated reclassification of (clinically defined) phenotypes. We analyzed publicly available expression profiles of intestinal tissues from treatment-naive pediatric inflammatory bowel disease (IBD) patients and age-matched control individuals, using a reaction-centric metabolic network derived from the Recon2 model. By way of defining a measure of 'coherence', we quantified how well individual patterns of expression changes matched the metabolic network. We observed a bimodal distribution of metabolic network coherence in both patients and controls, albeit at notably different mixture probabilities. Multidimensional scaling analysis revealed a bisectional pattern as well that overlapped widely with the metabolic network-based results. Expression differences driving the observed bimodality were related to cellular transport of thiamine and bile acid metabolism, thereby highlighting the crosstalk between metabolism and other vital pathways. We demonstrated how classical data mining and network analysis can jointly identify biologically meaningful patterns in gene expression data.

Effect of database drift on network topology and enrichment analyses: a case study for RegulonDB

RegulonDB is a database storing the biological information behind the transcriptional regulatory network (TRN) of the bacterium Escherichia coli. It is one of the key bioinformatics resources for Systems Biology investigations of bacterial gene regulation. Like most biological databases, the content drifts with time, both due to the accumulation of new information and due to refinements in the underlying biological concepts. Conclusions based on previous database versions may no longer hold. Here, we study the change of some topological properties of the TRN of E. coli, as provided by RegulonDB across 16 versions, as well as a simple index, digital control strength, quantifying the match between gene expression profiles and the transcriptional regulatory networks. While many of network characteristics change dramatically across the different versions, the digital control strength remains rather robust and in tune with previous results for this index. Our study shows that: (i) results derived from network topology should, when possible, be studied across a range of database versions, before detailed biological conclusions are derived, and (ii) resorting to simple indices, when interpreting high-throughput data from a network perspective, may help achieving a robustness of the findings against variation of the underlying biological information. Database URL: www.regulondb.ccg.unam.mx.

Relationship between digital information and thermodynamic stability in bacterial genomes

Ever since the introduction of the Watson-Crick model, numerous efforts have been made to fully characterize the digital information content of the DNA. However, it became increasingly evident that variations of DNA configuration also provide an “analog” type of information related to the physicochemical properties of the DNA, such as thermodynamic stability and supercoiling. Hence, the parallel investigation of the digital information contained in the base sequence with associated analog parameters is very important for understanding the coding capacity of the DNA. In this paper, we represented analog information by its thermodynamic stability and compare it with digital information using Shannon and Gibbs entropy measures on the complete genome sequences of several bacteria, including Escherichia coli (E. coli), Bacillus subtilis (B. subtilis), Streptomyces coelicolor (S. coelicolor), and Salmonella typhimurium (S. typhimurium). Furthermore, the link to the broader classes of functional gene groups (anabolic and catabolic) is examined. Obtained results demonstrate the couplings between thermodynamic stability and digital sequence organization in the bacterial genomes. In addition, our data suggest a determinative role of the genome-wide distribution of DNA thermodynamic stability in the spatial organization of functional gene groups.

Transcription-coupled DNA supercoiling dictates the chromosomal arrangement of bacterial genes

Over the recent decade, the central importance of DNA supercoiling in chromosome organization and global gene regulation of bacteria became more and more visible. With a regulon comprising more than 2000 genes in Escherichia coli, DNA supercoiling is among the most influential regulators of gene expression found in bacteria so far. However, the mechanism creating thousands of diverse temporal gene expression patterns coordinated by DNA supercoiling remains unclear. In this study we show that a specific chromosomal arrangement of genes modulates the local levels of DNA supercoiling at gene promoters via transcription-coupled DNA supercoiling (TCDS) in the model organism E. coli. Our findings provide a consistent explanation for the strong positive coupling of temporal gene expression patterns of neighboring genes. Using comparative genomics we are furthermore able to provide evidence that TCDS is a driving force for the evolution of chromosomal gene arrangement patterns in other Enterobacteriaceae. With the currently available data of promoter supercoiling sensitivity we prove that the same principle is applicable also for the evolutionary distant gram-positive pathogenic bacterium Streptococcus pneumoniae. Moreover, our findings are fully consistent with recent investigations concerning the regulatory impact of TCDS on gene pairs in eukaryots underpinning the broad applicability of our analysis.

Chromosomal "stress-response" domains govern the spatiotemporal expression of the bacterial virulence program

Recent studies strongly suggest that the gene expression sustaining both normal and pathogenic bacterial growth is governed by the structural dynamics of the chromosome. However, the mechanistic device coordinating the chromosomal configuration with selective expression of the adaptive traits remains largely unknown. We used a holistic approach exploring the inherent relationships between the physicochemical properties of the DNA and the expression of adaptive traits, including virulence factors, in the pathogen Dickeya dadantii (formerly Erwinia chrysanthemi). In the transcriptomes obtained under adverse conditions encountered during bacterial infection, we explored the patterns of chromosomal DNA sequence organization, supercoil dynamics, and gene expression densities, together with the long-range regulatory impacts of the abundant DNA architectural proteins implicated in pathogenicity control. By integrating these data, we identified transient chromosomal domains of coherent gene expression featuring distinct couplings between DNA thermodynamic stability, supercoil dynamics, and virulence traits.

We infer that the organization of transient chromosomal domains serving specific functions acts as a fundamental device for versatile adjustment of the pathogen to environmental stress. We believe that the identification of chromosomal “stress-response” domains harboring distinct virulence traits and mediating the cellular adaptive behavior provides a breakthrough in understanding the control mechanisms of bacterial pathogenicity.

Gene regulation by H-NS as a function of growth conditions depends on chromosomal position in Escherichia coli

Cellular adaptation to changing environmental conditions requires the coordinated regulation of expression of large sets of genes by global regulatory factors such as nucleoid associated proteins. Although in eukaryotic cells genomic position is known to play an important role in regulation of gene expression, it remains to be established whether in bacterial cells there is an influence of chromosomal position on the efficiency of these global regulators. Here we show for the first time that genome position can affect transcription activity of a promoter regulated by the histone-like nucleoid-structuring protein (H-NS), a global regulator of bacterial transcription and genome organization. We have used as a local reporter of H-NS activity the level of expression of a fluorescent reporter protein under control of an H-NS−regulated promoter (Phns) at different sites along the genome. Our results show that the activity of the Phns promoter depends on whether it is placed within the AT-rich regions of the genome that are known to be bound preferentially by H-NS. This modulation of gene expression moreover depends on the growth phase and the growth rate of the cells, reflecting the changes taking place in the relative abundance of different nucleoid proteins and the inherent heterogeneous organization of the nucleoid. Genomic position can thus play a significant role in the adaptation of the cells to environmental changes, providing a fitness advantage that can explain the selection of a gene’s position during evolution.

Understanding genetic variation - the value of systems biology

Pharmacology is currently transformed by the vast amounts of genome-associated information available for system-level interpretation. Here I review the potential of systems biology to facilitate this interpretation, thus paving the way for the emerging field of systems pharmacology. In particular, I will show how gene regulatory and metabolic networks can serve as a framework for interpreting high throughput data and as an interface to detailed dynamical models. In addition to the established connectivity analyses of effective networks, I suggest here to also analyze higher order architectural properties of effective networks.

Integration of syntactic and semantic properties of the DNA code reveals chromosomes as thermodynamic machines converting energy into information

Understanding genetic regulation is a problem of fundamental importance. Recent studies have made it increasingly evident that, whereas the cellular genetic regulation system embodies multiple disparate elements engaged in numerous interactions, the central issue is the genuine function of the DNA molecule as information carrier. Compelling evidence suggests that the DNA, in addition to the digital information of the linear genetic code (the semantics), encodes equally important continuous, or analog, information that specifies the structural dynamics and configuration (the syntax) of the polymer. These two DNA information types are intrinsically coupled in the primary sequence organisation, and this coupling is directly relevant to regulation of the genetic function. In this review, we emphasise the critical need of holistic integration of the DNA information as a prerequisite for understanding the organisational complexity of the genetic regulation system.

Critical dynamics in host-pathogen systems

Host-pathogen interactions provide a fascinating example of two or more active genomes directly exerting mutual influence upon each other. These encounters can lead to multiple outcomes from symbiotic homeostasis to mutual annihilation, undergo multiple cycles of latency and lysogeny, and lead to coevolution of the interacting genomes. Such systems pose numerous challenges but also some advantages to modeling, especially in terms of functional, mathematical genome representations. The main challenges for the modeling process start with the conceptual definition of a genome for instance in the case of host-integrated viral genomes. Furthermore, hardly understood influences of the activity of either genome on the other(s) via direct and indirect mechanisms amplify the needs for a coherent description of genome activity. Finally, genetic and local environmental heterogeneities in both the host's cellular and the pathogen populations need to be considered in multiscale modeling efforts. We will review here two prominent examples of host-pathogen interactions at the genome level, discuss the current modeling efforts and their shortcomings, and explore novel ideas of representing active genomes which promise being particularly adapted to dealing with the modeling challenges posed by host-pathogen interactions.

DNA thermodynamic stability and supercoil dynamics determine the gene expression program during the bacterial growth cycle

The chromosomal DNA polymer constituting the cellular genetic material is primarily a device for coding information. Whilst the gene sequences comprise the digital (discontinuous) linear code, physiological alterations of the DNA superhelical density generate in addition analog (continuous) three-dimensional information essential for regulation of both chromosome compaction and gene expression. Insight into the relationship between the DNA analog information and the digital linear code is of fundamental importance for understanding genetic regulation. Our previous study in the model organism Escherichia coli suggested that the chromosomal gene order and a spatiotemporal gradient of DNA superhelicity associated with DNA replication determine the growth phase-dependent gene transcription. In this study we reveal a general gradient of DNA thermodynamic stability correlated with the polarity of chromosomal replication and manifest in the spatiotemporal pattern of gene transcription during the bacterial growth cycle. Furthermore, by integrating the physical and dynamic features of the transcribed sequences with their functional content we identify spatiotemporal domains of gene expression encompassing different functions. We thus provide both an insight into the organisational principle of the bacterial growth program and a novel holistic methodology for exploring chromosomal dynamics.

Hierarchical dynamics of a transcription factors network in E. coli

In the present work we study the transcription-factor regulatory network that controls the synthesis of flagella in E. coli. Our objective is to address how the transcription-factor dynamics (in terms of their promoter activities and associated rates) correlate with their positions in the hierarchical organization of this regulatory network. Our results suggest that global-regulator promoters express at higher rates than those of local regulators, particularly when the bacterial populations are actively growing. Furthermore, promoter activity decreases together with the rate of cellular division. And finally, local-regulator promoters reach their maximal activity later than global-regulator promoters do. In summary, our results suggest a strong correlation between promoter activities and their hierarchical organization in this particular regulatory network.

Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli

The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in development for over a decade and is now in wide use. GEM-enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome-scale mechanistic understanding of genotype-phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges include the expansion of GEMs by integrating additional cellular processes beyond metabolism, the identification of key constraints based on emerging data types, and the development of computational methods able to handle such large-scale network models with sufficient accuracy.

A topological characterization of medium-dependent essential metabolic reactions

Metabolism has frequently been analyzed from a network perspective. A major question is how network properties correlate with biological features like growth rates, flux patterns and enzyme essentiality. Using methods from graph theory as well as established topological categories of metabolic systems, we analyze the essentiality of metabolic reactions depending on the growth medium and identify the topological footprint of these reactions. We find that the typical topological context of a medium-dependent essential reaction is systematically different from that of a globally essential reaction. In particular, we observe systematic differences in the distribution of medium-dependent essential reactions across three-node subgraphs (the network motif signature of medium-dependent essential reactions) compared to globally essential or globally redundant reactions. In this way, we provide evidence that the analysis of metabolic systems on the few-node subgraph scale is meaningful for explaining dynamic patterns. This topological characterization of medium-dependent essentiality provides a better understanding of the interplay between reaction deletions and environmental conditions.

Artefacts in statistical analyses of network motifs: general framework and application to metabolic networks

Few-node subgraphs are the smallest collective units in a network that can be investigated. They are beyond the scale of individual nodes but more local than, for example, communities. When statistically over- or under-represented, they are called network motifs. Network motifs have been interpreted as building blocks that shape the dynamic behaviour of networks. It is this promise of potentially explaining emergent properties of complex systems with relatively simple structures that led to an interest in network motifs in an ever-growing number of studies and across disciplines. Here, we discuss artefacts in the analysis of network motifs arising from discrepancies between the network under investigation and the pool of random graphs serving as a null model. Our aim was to provide a clear and accessible catalogue of such incongruities and their effect on the motif signature. As a case study, we explore the metabolic network of Escherichia coli and show that only by excluding ever more artefacts from the motif signature a strong and plausible correlation with the essentiality profile of metabolic reactions emerges.

DNA information: from digital code to analogue structure

The digital linear coding carried by the base pairs in the DNA double helix is now known to have an important component that acts by altering, along its length, the natural shape and stiffness of the molecule. In this way, one region of DNA is structurally distinguished from another, constituting an additional form of encoded information manifest in three-dimensional space. These shape and stiffness variations help in guiding and facilitating the DNA during its three-dimensional spatial interactions. Such interactions with itself allow communication between genes and enhanced wrapping and histone-octamer binding within the nucleosome core particle. Meanwhile, interactions with proteins can have a reduced entropic binding penalty owing to advantageous sequence-dependent bending anisotropy. Sequence periodicity within the DNA, giving a corresponding structural periodicity of shape and stiffness, also influences the supercoiling of the molecule, which, in turn, plays an important facilitating role. In effect, the super-helical density acts as an analogue regulatory mode in contrast to the more commonly acknowledged purely digital mode. Many of these ideas are still poorly understood, and represent a fundamental and outstanding biological question. This review gives an overview of very recent developments, and hopefully identifies promising future lines of enquiry.

The yin and yang of yeast transcription: elements of a global feedback system between metabolism and chromatin

When grown in continuous culture, budding yeast cells tend to synchronize their respiratory activity to form a stable oscillation that percolates throughout cellular physiology and involves the majority of the protein-coding transcriptome. Oscillations in batch culture and at single cell level support the idea that these dynamics constitute a general growth principle. The precise molecular mechanisms and biological functions of the oscillation remain elusive. Fourier analysis of transcriptome time series datasets from two different oscillation periods (0.7 h and 5 h) reveals seven distinct co-expression clusters common to both systems (34% of all yeast ORF), which consolidate into two superclusters when correlated with a compilation of 1,327 unrelated transcriptome datasets. These superclusters encode for cell growth and anabolism during the phase of high, and mitochondrial growth, catabolism and stress response during the phase of low oxygen uptake. The promoters of each cluster are characterized by different nucleotide contents, promoter nucleosome configurations, and dependence on ATP-dependent nucleosome remodeling complexes. We show that the ATP:ADP ratio oscillates, compatible with alternating metabolic activity of the two superclusters and differential feedback on their transcription via activating (RSC) and repressive (Isw2) types of promoter structure remodeling. We propose a novel feedback mechanism, where the energetic state of the cell, reflected in the ATP:ADP ratio, gates the transcription of large, but functionally coherent groups of genes via differential effects of ATP-dependent nucleosome remodeling machineries. Besides providing a mechanistic hypothesis for the delayed negative feedback that results in the oscillatory phenotype, this mechanism may underpin the continuous adaptation of growth to environmental conditions.

A network perspective on metabolic inconsistency

BACKGROUND

Integrating gene expression profiles and metabolic pathways under different experimental conditions is essential for understanding the coherence of these two layers of cellular organization. The network character of metabolic systems can be instrumental in developing concepts of agreement between expression data and pathways. A network-driven interpretation of gene expression data has the potential of suggesting novel classifiers for pathological cellular states and of contributing to a general theoretical understanding of gene regulation.

RESULTS

Here, we analyze the coherence of gene expression patterns and a reconstruction of human metabolism, using consistency scores obtained from network and constraint-based analysis methods. We find a surprisingly strong correlation between the two measures, demonstrating that a substantial part of inconsistencies between metabolic processes and gene expression can be understood from a network perspective alone. Prompted by this finding, we investigate the topological context of the individual biochemical reactions responsible for the observed inconsistencies. On this basis, we are able to separate the differential contributions that bear physiological information about the system, from the unspecific contributions that unravel gaps in the metabolic reconstruction. We demonstrate the biological potential of our network-driven approach by analyzing transcriptome profiles of aldosterone producing adenomas that have been obtained from a cohort of Primary Aldosteronism patients. We unravel systematics in the data that could not have been resolved by conventional microarray data analysis. In particular, we discover two distinct metabolic states in the adenoma expression patterns.

CONCLUSIONS

The methodology presented here can help understand metabolic inconsistencies from a network perspective. It thus serves as a mediator between the topology of metabolic systems and their dynamical function. Finally, we demonstrate how physiologically relevant insights into the structure and dynamics of metabolic networks can be obtained using this novel approach.

Subgraph fluctuations in random graphs

The pattern of over- and under-representations of three-node subgraphs has become a standard method of characterizing complex networks and evaluating how this intermediate level of organization contributes to network function. Understanding statistical properties of subgraph counts in random graphs, their fluctuations, and their interdependences with other topological attributes is an important prerequisite for such investigations. Here we introduce a formalism for predicting subgraph fluctuations induced by perturbations of unidirectional and bidirectional edge densities. On this basis we predict the over- and under-representation of subgraphs arising from a density mismatch between a network and the corresponding pool of randomized graphs serving as a null model. Such mismatches occur, for example, in modular and hierarchical graphs.

Gene order and chromosome dynamics coordinate spatiotemporal gene expression during the bacterial growth cycle

In Escherichia coli crosstalk between DNA supercoiling, nucleoid-associated proteins and major RNA polymerase σ initiation factors regulates growth phase-dependent gene transcription. We show that the highly conserved spatial ordering of relevant genes along the chromosomal replichores largely corresponds both to their temporal expression patterns during growth and to an inferred gradient of DNA superhelical density from the origin to the terminus. Genes implicated in similar functions are related mainly in trans across the chromosomal replichores, whereas DNA-binding transcriptional regulators interact predominantly with targets in cis along the replichores. We also demonstrate that macrodomains (the individual structural partitions of the chromosome) are regulated differently. We infer that spatial and temporal variation of DNA superhelicity during the growth cycle coordinates oxygen and nutrient availability with global chromosome structure, thus providing a mechanistic insight into how the organization of a complete bacterial chromosome encodes a spatiotemporal program integrating DNA replication and global gene expression.

Structural coupling between RNA polymerase composition and DNA supercoiling in coordinating transcription: a global role for the omega subunit?

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.