Basics on network theory to analyze biological systems: a hands-on outlook.

Biological processes result from interactions among molecules and cell-to-cell communications. In the last 50 years, network theory has empowered advances in understanding molecular networks' structure and dynamics that regulate biological systems. Adopting a network data analysis point of view at more laboratories might enrich their research capacity to generate forward working hypotheses. This work briefly describes network theory origins and provides basic graph analysis principles in biological systems, specific centrality measurements, and the main models for network structures. Also, we describe a workflow employing user-friendly free platforms to process, construct, and analyze transcriptome data from a network perspective. With this assay, we expect to encourage the implementation of network theory analysis on biological data in everyday laboratory research.

Limited oxygen conditions as an approach to scale-up and improve D and L-lactic acid production in mineral media and avocado seed hydrolysates with metabolically engineered Escherichia coli.

The effectiveness of micro-aeration on lactate (LA) production by metabolically engineered Escherichia coli was evaluated in 1 L bioreactors containing mineral media and glucose (70 g/L). Volumetric oxygen transfer coefficients (kLa) between 12.6 and 28.7 h-1 increased the specific growth rate (µ) and volumetric productivity (QLA) by 300 and 400%, respectively, without a significant decrease in lactate yield (YLA), when compared with non-aerated fermentations. A kLa of 12.6 h-1 was successfully used as a criterion to scale-up the production of L and D-lactate from 1 to 11 and 130 L. Approximately constant QLA and YLA values were obtained throughout the fermentation scale-up process. Furthermore, a D-lactogenic fermentation was carried out in 1 L bioreactors using avocado seed hydrolysate as a culture medium under the same kLa value, displaying high QLA and YLA.

Engineering Escherichia coli K12 MG1655 to use starch.

BACKGROUND: To attain a sustainable bioeconomy, fuel, or valuable product, production must use biomass as substrate. Starch is one of the most abundant biomass resources and is present as waste or as a food and agroindustry by-product. Unfortunately, Escherichia coli, one of the most widely used microorganisms in biotechnological processes, cannot use starch as a carbon source. RESULTS: We engineered an E. coli strain capable of using starch as a substrate. The genetic design employed the native capability of the bacterium to use maltodextrins as a carbon source plus expression and secretion of its endogenous α-amylase, AmyA, in an adapted background. Biomass production improved using 35% dissolved oxygen and pH 7.2 in a controlled bioreactor. CONCLUSION: The engineered E. coli strain can use starch from the milieu and open the possibility of optimize the process to use agroindustrial wastes to produce biofuels and other valuable chemicals.

Sex determination in papaya: Current status and perspectives.

Papaya (Carica papaya L.) is an economically significant plant that produces fruit consumed worldwide due to its organoleptic characteristics. Since their commercial production, papaya fruits have faced several problems, such as pests, which have been partly resolved using transgenic varieties. Nevertheless, a principal challenge in this cultivation is the plant's sex determination. The sex issue in papaya is complex because papaya flowers can bear three sex forms: male, female, and hermaphrodite, which affects their fruit production, shape, and yield. Fruits from hermaphrodite plants are preferred more by consumers than female ones, and male plants rarely produce fruits without commercial value. Chromosomes are responsible for sex determination in papaya, denoted as XY for male, XX for female, and XYh for hermaphrodite. However, genes related to sex have been reported but are not conclusive. Factors such as the environment, hormones, and genetic and epigenetic background can also affect sex expression. Therefore, in this review, we will discuss recent research on the sex of papaya, from reported genes to date, their biology, and sexing approaches using molecular markers and their advantages.

The Cytokinins BAP and 2-iP Modulate Different Molecular Mechanisms on Shoot Proliferation and Root Development in Lemongrass (Cymbopogon citratus).

The known activities of cytokinins (CKs) are promoting shoot multiplication, root growth inhibition, and delaying senescence. 6-Benzylaminopurine (BAP) has been the most effective CK to induce shoot proliferation in cereal and grasses. Previously, we reported that in lemongrass (Cymbopogon citratus) micropropagation, BAP 10 µM induces high shoot proliferation, while the natural CK 6-(γ,γ-Dimethylallylamino)purine (2-iP) 10 µM shows less pronounced effects and developed rooting. To understand the molecular mechanisms involved, we perform a protein-protein interaction (PPI) network based on the genes of Brachypodium distachyon involved in shoot proliferation/repression, cell cycle, stem cell maintenance, auxin response factors, and CK signaling to analyze the molecular mechanisms in BAP versus 2-iP plants. A different pattern of gene expression was observed between BAP- versus 2-iP-treated plants. In shoots derived from BAP, we found upregulated genes that have already been demonstrated to be involved in de novo shoot proliferation development in several plant species; CK receptors (AHK3, ARR1), stem cell maintenance (STM, REV and CLV3), cell cycle regulation (CDKA-CYCD3 complex), as well as the auxin response factor (ARF5) and CK metabolism (CKX1). In contrast, in the 2-iP culture medium, there was an upregulation of genes involved in shoot repression (BRC1, MAX3), ARR4, a type A-response regulator (RR), and auxin metabolism (SHY2).

Review: Isoprenoid and aromatic cytokinins in shoot branching.

Shoot branching is an important event of plant development that defines growth and reproduction. The BRANCHED1 gene (BRC1/TB1/FC1) is crucial for this process. Within the phytohormones, cytokinins directly activate axillary buds to promote shoot branching. In addition, strigolactones and auxins inhibit bud outgrowth. This review addresses the involvement of aromatic and isoprenoid cytokinins in shoot branching. And how auxins and strigolactones contribute to regulating this process also. The results obtained by others and our working group with lemongrass (Cymbopogon citratus) show that cytokinins affect both shoot and root apical meristem development, consistent with other plant species. However, many questions remain about how cytokinins and strigolactones antagonistically regulate BRC1 gene expression. Additionally, many details of the interaction among cytokinins, auxins, and strigolactones need to be clarified. We will gain a more comprehensive scheme of bud outgrowth with these details.

Transcriptional regulation shapes the organization of genes on bacterial chromosomes.

Transcription factors (TFs) are the key elements responsible for controlling the expression of genes in bacterial genomes and when visualized on a genomic scale form a dense network of transcriptional interactions among themselves and with other protein coding genes. Although the structure of transcriptional regulatory networks (TRNs) is well understood, it is not clear what constrains govern them. Here, we explore this question using the TRNs of model prokaryotes and provide a link between the transcriptional hierarchy of regulons and their genome organization. We show that, to drive the kinetics and concentration gradients, TFs belonging to big and small regulons, depending on the number of genes they regulate, organize themselves differently on the genome with respect to their targets. We then propose a conceptual model that can explain how the hierarchical structure of TRNs might be ultimately governed by the dynamic biophysical requirements for targeting DNA-binding sites by TFs. Our results suggest that the main parameters defining the position of a TF in the network hierarchy are the number and chromosomal distances of the genes they regulate and their protein concentration gradients. These observations give insights into how the hierarchical structure of transcriptional networks can be encoded on the chromosome to drive the kinetics and concentration gradients of TFs depending on the number of genes they regulate and could be a common theme valid for other prokaryotes, proposing the role of transcriptional regulation in shaping the organization of genes on a chromosome.

Regulation by transcription factors in bacteria: beyond description.

Transcription is an essential step in gene expression and its understanding has been one of the major interests in molecular and cellular biology. By precisely tuning gene expression, transcriptional regulation determines the molecular machinery for developmental plasticity, homeostasis and adaptation. In this review, we transmit the main ideas or concepts behind regulation by transcription factors and give just enough examples to sustain these main ideas, thus avoiding a classical ennumeration of facts. We review recent concepts and developments: cis elements and trans regulatory factors, chromosome organization and structure, transcriptional regulatory networks (TRNs) and transcriptomics. We also summarize new important discoveries that will probably affect the direction of research in gene regulation: epigenetics and stochasticity in transcriptional regulation, synthetic circuits and plasticity and evolution of TRNs. Many of the new discoveries in gene regulation are not extensively tested with wetlab approaches. Consequently, we review this broad area in Inference of TRNs and Dynamical Models of TRNs. Finally, we have stepped backwards to trace the origins of these modern concepts, synthesizing their history in a timeline schema.

Pas de Trois: An Overview of Penta-, Tetra-, and Octo-Tricopeptide Repeat Proteins From Chlamydomonas reinhardtii and Their Role in Chloroplast Gene Expression.

Penta-, Tetra-, and Octo-tricopeptide repeat (PPR, TPR, and OPR) proteins are nucleus-encoded proteins composed of tandem repeats of 35, 34, and 38-40 amino acids, respectively. They form helix-turn-helix structures that interact with mRNA or other proteins and participate in RNA stabilization, processing, maturation, and act as translation enhancers of chloroplast and mitochondrial mRNAs. These helical repeat proteins are unevenly present in plants and algae. While PPR proteins are more abundant in plants than in algae, OPR proteins are more abundant in algae. In Arabidopsis, maize, and rice there have been 450, 661, and 477 PPR proteins identified, respectively, which contrasts with only 14 PPR proteins identified in Chlamydomonas reinhardtii. Likewise, more than 120 OPR proteins members have been predicted from the nuclear genome of C. reinhardtii and only one has been identified in Arabidopsis thaliana. Due to their abundance in land plants, PPR proteins have been largely characterized making it possible to elucidate their RNA-binding code. This has even allowed researchers to generate engineered PPR proteins with defined affinity to a particular target, which has served as the basis to develop tools for gene expression in biotechnological applications. However, fine elucidation of the helical repeat proteins code in Chlamydomonas is a pending task. In this review, we summarize the current knowledge on the role PPR, TPR, and OPR proteins play in chloroplast gene expression in the green algae C. reinhardtii, pointing to relevant similarities and differences with their counterparts in plants. We also recapitulate on how these proteins have been engineered and shown to serve as mRNA regulatory factors for biotechnological applications in plants and how this could be used as a starting point for applications in algae.

RNA polymerases in strict endosymbiont bacteria with extreme genome reduction show distinct erosions that might result in limited and differential promoter recognition.

Strict endosymbiont bacteria present high degree genome reduction, retain smaller proteins, and in some instances, lack complete functional domains compared to free-living counterparts. Until now, the mechanisms underlying these genetic reductions are not well understood. In this study, the conservation of RNA polymerases, the essential machinery for gene expression, is analyzed in endosymbiont bacteria with extreme genome reductions. We analyzed the RNA polymerase subunits to identify and define domains, subdomains, and specific amino acids involved in precise biological functions known in Escherichia coli. We also perform phylogenetic analysis and three-dimensional models over four lineages of endosymbiotic proteobacteria with the smallest genomes known to date: Candidatus Hodgkinia cicadicola, Candidatus Tremblaya phenacola, Candidatus Tremblaya Princeps, Candidatus Nasuia deltocephalinicola, and Candidatus Carsonella ruddii. We found that some Hodgkinia strains do not encode for the RNA polymerase α subunit. The rest encode genes for α, ß, ß', and σ subunits to form the RNA polymerase. However, 16% shorter, on average, respect their orthologous in E. coli. In the α subunit, the amino-terminal domain is the most conserved. Regarding the ß and ß' subunits, both the catalytic core and the assembly domains are the most conserved. However, they showed compensatory amino acid substitutions to adapt to changes in the σ subunit. Precisely, the most erosive diversity occurs within the σ subunit. We identified broad amino acid substitution even in those recognizing and binding to the -10-box promoter element. In an overall conceptual image, the RNA polymerase from Candidatus Nasuia conserved the highest similarity with Escherichia coli RNA polymerase and their σ70. It might be recognizing the two main promoter elements (-10 and -35) and the two promoter accessory elements (-10 extended and UP-element). In Candidatus Carsonella, the RNA polymerase could recognize all the promoter elements except the -10-box extended. In Candidatus Tremblaya and Hodgkinia, due to the α carboxyl-terminal domain absence, they might not recognize the UP-promoter element. We also identified the lack of the ß flap-tip helix domain in most Hodgkinia's that suggests the inability to bind the -35-box promoter element.

Regulatory dynamics of standard two-component systems in bacteria.

Complex cellular networks regulate metabolism, environmental adaptation, and phenotypic changes in biological systems. Among the elements forming regulatory networks in bacteria are regulatory proteins such as transcription factors, which respond to exogenous and endogenous conditions. To perceive their surroundings, bacteria have evolved sensory regulatory systems of two-components. The archetype of these systems is made up of two proteins--a signal sensor and a response regulator-whose genes are usually located together in a single transcription unit. These units switch transcriptional programs in response to environmental conditions. Here, we study 14 two-component systems in Escherichia coli, which have been experimentally characterized with respect to their transcriptional regulation and their perceived signal. Given that the activity of these sensory units is connected to the rest of the transcriptional network, we first classify them as autonomous, semiautonomous or dependent, according to whether or not they use additional regulators to be transcribed. Next, we use discrete-time models to simulate their qualitative regulatory dynamics in response to their transcriptional regulation and to the activation of these systems by their cognate signals. Compared to more traditional ordinary differential equations method, ours has the advantage of being computationally simple and mathematically tractable, while keeping the ability to reproduce the phenomenology described by non-linear models. The aim of the present work is not the study of all possible behaviors of these two-component systems, but to exemplify those behaviors reported in the literature. On the other hand, most of these systems are auto-activating switches, a property that distinguishes them from the other transcription factors in the regulatory network, which are mostly auto-repressing. Based on the data, our models show dynamic behaviors that explain how most of these sensory systems convey abilities for multistationarity, and these dynamic properties could explain the phenotypic heterogeneity observed in bacterial populations. Our results are likely to have an impact in the design of synthetic signaling modules.

Quantitative modeling of the interplay between synthetic gene circuits and host physiology: experiments, results, and prospects.

A primary goal of synthetic biology is to develop gene circuits that perform their intended functions despite variations in the growth conditions. However, this has turned out to be more complicated than it originally seemed because there is a complex interplay between the operation of synthetic gene circuits and the global physiology of host cells. Mathematical models provide an avenue to disentangle the intricacies of this phenomenon and guide the design of synthetic circuits that robustly perform in a variety of conditions. In this work, we review quantitative modeling approaches that have been used to rationalize and predict experimental observations resulting from circuit-to-circuit and circuit-host interactions in bacteria.

RegulomePA: a database of transcriptional regulatory interactions in Pseudomonas aeruginosa PAO1.

We present RegulomePA, a database that contains biological information on regulatory interactions between transcription factors (TFs), sigma factor (SFs) and target genes in Pseudomonas aeruginosa PAO1. RegulomePA consists of 4827 regulatory interactions between 2831 nodes, which represent the interactions of TFs and SFs with their target genes, from the total of predicted RegulomePA including 27.27% of the TFs, 54.16% of SFs and 50.8% of the total genes. Each entry in the database corresponds to one node in the network and provides comprehensive details about the gene and its regulatory interactions such as gene description, nucleotide sequence, genome-strand position and links to other databases as well as the type of regulation it exerts or to which it is being subject (repression or activation), the associated experimental evidence and references, and topological information. Additionally, RegulomePA provides a way to recover information on the regulatory circuits of the network to which a gene pertains and also makes available the source codes to analyze the topology of any other regulatory network. The database will be updated yearly, by our team, with the contributions from ourselves and users, since the users are provided with an interactive platform where they can add interactions to the regulatory network feeding it with their respective references. Database URL: www.regulome.pcyt.unam.mx.

Transcriptional profile of Pseudomonas syringae pv. phaseolicola NPS3121 in response to tissue extracts from a susceptible Phaseolus vulgaris L. cultivar.

BACKGROUND: Pseudomonas syringae pv. phaseolicola is a Gram-negative plant-pathogenic bacterium that causes "halo blight" disease of beans (Phaseolus vulgaris L.). This disease affects both foliage and pods, and is a major problem in temperate areas of the world. Although several bacterial genes have been determined as participants in pathogenesis, the overall process still remains poorly understood, mainly because the identity and function of many of the genes are largely unknown. In this work, a genomic library of P. syringae pv. phaseolicola NPS3121 was constructed and PCR amplification of individual fragments was carried out in order to print a DNA microarray. This microarray was used to identify genes that are differentially expressed when bean leaf extracts, pod extracts or apoplastic fluid were added to the growth medium. RESULTS: Transcription profiles show that 224 genes were differentially expressed, the majority under the effect of bean leaf extract and apoplastic fluid. Some of the induced genes were previously known to be involved in the first stages of the bacterial-plant interaction and virulence. These include genes encoding type III secretion system proteins and genes involved in cell-wall degradation, phaseolotoxin synthesis and aerobic metabolism. On the other hand, most repressed genes were found to be involved in the uptake and metabolism of iron. CONCLUSION: This study furthers the understanding of the mechanisms involved, responses and the metabolic adaptation that occurs during the interaction of P. syringae pv. phaseolicola with a susceptible host plant.

Coordination logic of the sensing machinery in the transcriptional regulatory network of Escherichia coli.

The active and inactive state of transcription factors in growing cells is usually directed by allosteric physicochemical signals or metabolites, which are in turn either produced in the cell or obtained from the environment by the activity of the products of effector genes. To understand the regulatory dynamics and to improve our knowledge about how transcription factors (TFs) respond to endogenous and exogenous signals in the bacterial model, Escherichia coli, we previously proposed to classify TFs into external, internal and hybrid sensing classes depending on the source of their allosteric or equivalent metabolite. Here we analyze how a cell uses its topological structures in the context of sensing machinery and show that, while feed forward loops (FFLs) tightly integrate internal and external sensing TFs connecting TFs from different layers of the hierarchical transcriptional regulatory network (TRN), bifan motifs frequently connect TFs belonging to the same sensing class and could act as a bridge between TFs originating from the same level in the hierarchy. We observe that modules identified in the regulatory network of E. coli are heterogeneous in sensing context with a clear combination of internal and external sensing categories depending on the physiological role played by the module. We also note that propensity of two-component response regulators increases at promoters, as the number of TFs regulating a target operon increases. Finally we show that evolutionary families of TFs do not show a tendency to preserve their sensing abilities. Our results provide a detailed panorama of the topological structures of E. coli TRN and the way TFs they compose off, sense their surroundings by coordinating responses.

Modular analysis of the transcriptional regulatory network of E. coli.

The transcriptional network of Escherichia coli is currently the best-understood regulatory network of a single cell. Motivated by statistical evidence, suggesting a hierarchical modular architecture in this network, we identified eight modules with well-defined physiological functions. These modules were identified by a clustering approach, using the shortest path to trace regulatory relationships across genes in the network. We report the type (feed forward and bifan) and distribution of motifs between and within modules. Feed-forward motifs tend to be embedded within modules, whereas bi-fan motifs tend to link modules, supporting the notion of a hierarchical network with defined functional modules.

Internal versus external effector and transcription factor gene pairs differ in their relative chromosomal position in Escherichia coli.

Transcription factors (TFs) play an important role in the genetic regulation of transcription in response to internal and external cellular stimuli. However, little is known about their functional and dynamic aspects on a large scale, even in a well-studied bacterium like Escherichia coli. To understand the regulatory dynamics and to improve our knowledge about how TFs respond to endogenous and exogenous signals in this simple bacterium model, we previously proposed that TFs can be classified into three classes, depending on how they sense their allosteric or equivalent metabolite: external class, internal class, and hybrid sensing class. Classification of these groups was done without considering the relative chromosomal positions of the TFs and their corresponding effector genes. Here, we analyze the genome organization of the genetic components of these sensing systems, using the classification described earlier. We report the chromosomal proximity of transcription factors and their effector genes to sense periplasmic signals or transported metabolites (i.e. transcriptional sensing systems from the external class) in contrast to the components for sensing internally synthesized metabolites, which tend to be distant on the chromosome. We strengthen our finding that external sensing genetic machinery behaves like chromosomal modules of regulation to respond rapidly to variations in external conditions through co-expression of their genetic components, which is corroborated with microarray data for E. coli. Furthermore, we show several lines of evidence supporting the need for the coordinated activity of external sensing systems in contrast to that of internal sensing machinery, which can explain their close chromosomal organization. The observed functional correlation between the chromosomal organization and the genetic machinery for environmental sensing should contribute to our understanding of the logical functioning and evolution of the transcriptional regulatory networks in bacteria.

RegulonDB (version 5.0): Escherichia coli K-12 transcriptional regulatory network, operon organization, and growth conditions.

RegulonDB is the internationally recognized reference database of Escherichia coli K-12 offering curated knowledge of the regulatory network and operon organization. It is currently the largest electronically-encoded database of the regulatory network of any free-living organism. We present here the recently launched RegulonDB version 5.0 radically different in content, interface design and capabilities. Continuous curation of original scientific literature provides the evidence behind every single object and feature. This knowledge is complemented with comprehensive computational predictions across the complete genome. Literature-based and predicted data are clearly distinguished in the database. Starting with this version, RegulonDB public releases are synchronized with those of EcoCyc since our curation supports both databases. The complex biology of regulation is simplified in a navigation scheme based on three major streams: genes, operons and regulons. Regulatory knowledge is directly available in every navigation step. Displays combine graphic and textual information and are organized allowing different levels of detail and biological context. This knowledge is the backbone of an integrated system for the graphic display of the network, graphic and tabular microarray comparisons with curated and predicted objects, as well as predictions across bacterial genomes, and predicted networks of functionally related gene products. Access RegulonDB at http://regulondb.ccg.unam.mx.

Internal-sensing machinery directs the activity of the regulatory network in Escherichia coli.

Individual cells need to discern and synchronize transcriptional responses according to variations in external and internal conditions. Metabolites and chemical compounds are sensed by transcription factors (TFs), which direct the corresponding specific transcriptional responses. We propose a classification of the currently known TFs of Escherichia coli based on whether they respond to metabolites incorporated from the exterior, to internally produced compounds, or to both. When analyzing the mutual interactions of TFs, the dominant role of internal signal sensing becomes apparent, greatly due to the role of global regulators of transcription. This work encompasses metabolite-TF interactions, bridging the gap between the metabolic and regulatory networks, thus advancing towards an integrated network model for the understanding of cellular behavior.

Conservation of transcriptional sensing systems in prokaryotes: a perspective from Escherichia coli.

The activity of transcription factors is usually governed by allosteric physicochemical signals or metabolites, which are in turn produced in the cell or obtained from the environment by the activity of the products of effector genes. Previously, we identified a collection of more than 110 transcription factors and their corresponding effector genes in Escherichia coli K-12. Here, we introduce the notion of "triferog", which relates to the identification of orthologous transcription factors and effector genes across genomes and show that transcriptional sensing systems known in E. coli are poorly conserved beyond Salmonella. We also find that enzymes that act as effector genes for the production of endogenous effector metabolites are more conserved than their corresponding effector genes encoding for transport and two-component systems for sensing exogenous signals. Finally, we observe that on an evolutionary scale enzymes are more conserved than their respective TFs, suggesting a homogenous cellular metabolism across genomes and the conservation of transcriptional control of critical cellular processes like DNA replication by a common endogenous signal. We hypothesize that extensive variation in the domain architecture of TFs and changes in endogenous conditions at large phylogenetic distances could be the major contributing factors for the observed differential conservation of TFs and their corresponding effector genes encoding for enzymes, causing variations in transcriptional responses across organisms.