Structure of co-expression networks of Bifidobacterium species in response to human milk oligosaccharides.

Biological systems respond to environmental perturbations and a large diversity of compounds through gene interactions, and these genetic factors comprise complex networks. Experimental information from transcriptomic studies has allowed the identification of gene networks that contribute to our understanding of microbial adaptations. In this study, we analyzed the gene co-expression networks of three Bifidobacterium species in response to different types of human milk oligosaccharides (HMO) using weighted gene co-expression analysis (WGCNA). RNA-seq data obtained from Geo Datasets were obtained for Bifidobacterium longum subsp. Infantis, Bifidobacterium bifidum and Bifidobacterium longum subsp. Longum. Between 10 and 20 co-expressing modules were obtained for each dataset. HMO-associated genes appeared in the modules with more genes for B. infantis and B. bifidum, in contrast with B. longum. Hub genes were identified in each module, and in general they participated in conserved essential processes. Certain modules were differentially enriched with LacI-like transcription factors, and others with certain metabolic pathways such as the biosynthesis of secondary metabolites. The three Bifidobacterium transcriptomes showed distinct regulation patterns for HMO utilization. HMO-associated genes in B. infantis co-expressed in two modules according to their participation in galactose or N-Acetylglucosamine utilization. Instead, B. bifidum showed a less structured co-expression of genes participating in HMO utilization. Finally, this category of genes in B. longum clustered in a small module, indicating a lack of co-expression with main cell processes and suggesting a recent acquisition. This study highlights distinct co-expression architectures in these bifidobacterial genomes during HMO consumption, and contributes to understanding gene regulation and co-expression in these species of the gut microbiome.

Construction and analysis of gene co-expression network in the pathogenic fungus Ustilago maydis.

Introduction: Biological systems respond to environmental disturbances and a wide range of compounds through complex gene interaction networks. The enormous growth of experimental information obtained using large-scale genomic techniques such as microarrays and RNA sequencing led to the construction of a wide variety of gene co-expression networks in recent years. These networks allow the discovery of clusters of co-expressed genes that potentially work in the same process linking them to biological processes often of interest to industrial, medicinal, and academic research. Methods: In this study, we built the gene co-expression network of Ustilago maydis from the gene expression data of 168 samples belonging to 19 series, which correspond to the GPL3681 platform deposited in the NCBI using WGCNA software. This network was analyzed to identify clusters of co-expressed genes, gene hubs and Gene Ontology terms. Additionally, we identified relevant modules through a hypergeometric approach based on a predicted set of transcription factors and virulence genes. Results and Discussion: We identified 13 modules in the gene co-expression network of U. maydis. The TFs enriched in the modules of interest belong to the superfamilies of Nucleic acid-binding proteins, Winged helix DNA-binding, and Zn2/Cys6 DNA-binding. On the other hand, the modules enriched with virulence genes were classified into diseases related to corn smut, Invasive candidiasis, among others. Finally, a large number of hypothetical, a large number of hypothetical genes were identified as highly co-expressed with virulence genes, making them possible experimental targets.

A landscape of gene regulation in the parasitic amoebozoa Entamoeba spp.

Entamoeba are amoeboid extracellular parasites that represent an important group of organisms for which the regulatory networks must be examined to better understand how genes and functional processes are interrelated. In this work, we inferred the gene regulatory networks (GRNs) in four Entamoeba species, E. histolytica, E. dispar, E. nuttalli, and E. invadens, and the GRN topological properties and the corresponding biological functions were evaluated. From these analyses, we determined that transcription factors (TFs) of E. histolytica, E. dispar, and E. nuttalli are associated mainly with the LIM family, while the TFs in E. invadens are associated with the RRM_1 family. In addition, we identified that EHI_044890 regulates 121 genes in E. histolytica, EDI_297980 regulates 284 genes in E. dispar, ENU1_120230 regulates 195 genes in E. nuttalli, and EIN_249270 regulates 257 genes in E. invadens. Finally, we identified that three types of processes, Macromolecule metabolic process, Cellular macromolecule metabolic process, and Cellular nitrogen compound metabolic process, are the main biological processes for each network. The results described in this work can be used as a basis for the study of gene regulation in these organisms.

Gene Regulatory Network Inference and Gene Module Regulating Virulence in Fusarium oxysporum.

In this work, we inferred the gene regulatory network (GRN) of the fungus Fusarium oxysporum by using the regulatory networks of Aspergillus nidulans FGSC A4, Neurospora crassa OR74A, Saccharomyces cerevisiae S288c, and Fusarium graminearum PH-1 as templates for sequence comparisons. Topological properties to infer the role of transcription factors (TFs) and to identify functional modules were calculated in the GRN. From these analyzes, five TFs were identified as hubs, including FOXG_04688 and FOXG_05432, which regulate 2,404 and 1,864 target genes, respectively. In addition, 16 communities were identified in the GRN, where the largest contains 1,923 genes and the smallest contains 227 genes. Finally, the genes associated with virulence were extracted from the GRN and exhaustively analyzed, and we identified a giant module with ten TFs and 273 target genes, where the most highly connected node corresponds to the transcription factor FOXG_05265, homologous to the putative bZip transcription factor CPTF1 of Claviceps purpurea, which is involved in ergotism disease that affects cereal crops and grasses. The results described in this work can be used for the study of gene regulation in this organism and open the possibility to explore putative genes associated with virulence against their host.

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.

Identifying Genes Devoted to the Cell Death Process in the Gene Regulatory Network of Ustilago maydis.

Cell death is a process that can be divided into three morphological patterns: apoptosis, autophagy and necrosis. In fungi, cell death is induced in response to intracellular and extracellular perturbations, such as plant defense molecules, toxins and fungicides, among others. Ustilago maydis is a dimorphic fungus used as a model for pathogenic fungi of animals, including humans, and plants. Here, we reconstructed the transcriptional regulatory network of U. maydis, through homology inferences by using as templates the well-known gene regulatory networks (GRNs) of Saccharomyces cerevisiae, Aspergillus nidulans and Neurospora crassa. Based on this GRN, we identified transcription factors (TFs) as hubs and functional modules and calculated diverse topological metrics. In addition, we analyzed exhaustively the module related to cell death, with 60 TFs and 108 genes, where diverse cell proliferation, mating-type switching and meiosis, among other functions, were identified. To determine the role of some of these genes, we selected a set of 11 genes for expression analysis by qRT-PCR (sin3, rlm1, aif1, tdh3 [isoform A], tdh3 [isoform B], ald4, mca1, nuc1, tor1, ras1, and atg8) whose homologues in other fungi have been described as central in cell death. These genes were identified as downregulated at 72 h, in agreement with the beginning of the cell death process. Our results can serve as the basis for the study of transcriptional regulation, not only of the cell death process but also of all the cellular processes of U. maydis.

Screening a Spliced Leader-Based Symbiodinium microadriaticum cDNA Library Using the Yeast-Two Hybrid System Reveals a Hemerythrin-Like Protein as a Putative SmicRACK1 Ligand.

The dinoflagellate Symbiodiniaceae family plays a central role in the health of the coral reef ecosystem via the symbiosis that establishes with its inhabiting cnidarians and supports the host metabolism. In the last few decades, coral reefs have been threatened by pollution and rising temperatures which have led to coral loss. These events have raised interest in studying Symbiodiniaceae and their hosts; however, progress in understanding their metabolism, signal transduction pathways, and physiology in general, has been slow because dinoflagellates present peculiar characteristics. We took advantage of one of these peculiarities; namely, the post-transcriptional addition of a Dino Spliced Leader (Dino-SL) to the 5' end of the nuclear mRNAs, and used it to generate cDNA libraries from Symbiodinium microadriaticum. We compared sequences from two Yeast-Two Hybrid System cDNA Libraries, one based on the Dino-SL sequence, and the other based on the SMART technology (Switching Mechanism at 5' end of RNA Transcript) which exploits the template switching function of the reverse transcriptase. Upon comparison of the performance of both libraries, we obtained a significantly higher yield, number and length of sequences, number of transcripts, and better 5' representation from the Dino-SL based library than from the SMART library. In addition, we confirmed that the cDNAs from the Dino-SL library were adequately expressed in the yeast cells used for the Yeast-Two Hybrid System which resulted in successful screening for putative SmicRACK1 ligands, which yielded a putative hemerythrin-like protein.

A landscape for drug-target interactions based on network analysis.

In this work, we performed an analysis of the networks of interactions between drugs and their targets to assess how connected the compounds are. For our purpose, the interactions were downloaded from the DrugBank database, and we considered all drugs approved by the FDA. Based on topological analysis of this interaction network, we obtained information on degree, clustering coefficient, connected components, and centrality of these interactions. We identified that this drug-target interaction network cannot be divided into two disjoint and independent sets, i.e., it is not bipartite. In addition, the connectivity or associations between every pair of nodes identified that the drug-target network is constituted of 165 connected components, where one giant component contains 4376 interactions that represent 89.99% of all the elements. In this regard, the histamine H1 receptor, which belongs to the family of rhodopsin-like G-protein-coupled receptors and is activated by the biogenic amine histamine, was found to be the most important node in the centrality of input-degrees. In the case of centrality of output-degrees, fostamatinib was found to be the most important node, as this drug interacts with 300 different targets, including arachidonate 5-lipoxygenase or ALOX5, expressed on cells primarily involved in regulation of immune responses. The top 10 hubs interacted with 33% of the target genes. Fostamatinib stands out because it is used for the treatment of chronic immune thrombocytopenia in adults. Finally, 187 highly connected sets of nodes, structured in communities, were also identified. Indeed, the largest communities have more than 400 elements and are related to metabolic diseases, psychiatric disorders and cancer. Our results demonstrate the possibilities to explore these compounds and their targets to improve drug repositioning and contend against emergent diseases.

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.

Gene Regulatory Networks of Penicillium echinulatum 2HH and Penicillium oxalicum 114-2 Inferred by a Computational Biology Approach.

Penicillium echinulatum 2HH and Penicillium oxalicum 114-2 are well-known cellulase fungal producers. However, few studies addressing global mechanisms for gene regulation of these two important organisms are available so far. A recent finding that the 2HH wild-type is closely related to P. oxalicum leads to a combined study of these two species. Firstly, we provide a global gene regulatory network for P. echinulatum 2HH and P. oxalicum 114-2, based on TF-TG orthology relationships, considering three related species with well-known regulatory interactions combined with TFBSs prediction. The network was then analyzed in terms of topology, identifying TFs as hubs, and modules. Based on this approach, we explore numerous identified modules, such as the expression of cellulolytic and xylanolytic systems, where XlnR plays a key role in positive regulation of the xylanolytic system. It also regulates positively the cellulolytic system by acting indirectly through the cellodextrin induction system. This remarkable finding suggests that the XlnR-dependent cellulolytic and xylanolytic regulatory systems are probably conserved in both P. echinulatum and P. oxalicum. Finally, we explore the functional congruency on the genes clustered in terms of communities, where the genes related to cellular nitrogen, compound metabolic process and macromolecule metabolic process were the most abundant. Therefore, our approach allows us to confer a degree of accuracy regarding the existence of each inferred interaction.

Multicellular growth of the Basidiomycota phytopathogen fungus Sporisorium reilianum induced by acid conditions.

Fungi are considered model organisms for the analysis of important phenomena of eukaryotes. For example, some of them have been described as models to understand the phenomenon of multicellularity acquisition by different unicellular organisms phylogenetically distant. Interestingly, in this work, we describe the multicellular development in the model fungus S. reilianum. We observed that Sporisorium reilianum, a Basidiomycota cereal pathogen that at neutral pH grows with a yeast-like morphology during its saprophytic haploid stage, when incubated at acid pH grew in the form of multicellular clusters. The multicellularity observed in S. reilianum was of clonal type, where buds of "stem" cells growing as yeasts remain joined by their cell wall septa, after cytokinesis. The elaboration and analysis of a regulatory network of S. reilianum showed that the putative zinc finger transcription factor CBQ73544.1 regulates a number of genes involved in cell cycle, cellular division, signal transduction pathways, and biogenesis of cell wall. Interestingly, homologous of these genes have been found to be regulated during Saccharomyces cerevisiae multicellular growth. In adddition, some of these genes were found to be negatively regulated during multicellularity of S. reilianum. With these data, we suggest that S. reilianum is an interesting model for the study of multicellular development.

The protein architecture in Bacteria and Archaea identifies a set of promiscuous and ancient domains.

In this work, we describe a systematic comparative genomic analysis of promiscuous domains in genomes of Bacteria and Archaea. A quantitative measure of domain promiscuity, the weighted domain architecture score (WDAS), was used and applied to 1317 domains in 1320 genomes of Bacteria and Archaea. A functional analysis associated with the WDAS per genome showed that 18 of 50 functional categories were identified as significantly enriched in the promiscuous domains; in particular, small-molecule binding domains, transferases domains, DNA binding domains (transcription factors), and signal transduction domains were identified as promiscuous. In contrast, non-promiscuous domains were identified as associated with 6 of 50 functional categories, and the category Function unknown was enriched. In addition, the WDASs of 52 domains correlated with genome size, i.e., WDAS values decreased as the genome size increased, suggesting that the number of combinations at larger domains increases, including domains in the superfamilies Winged helix-turn-helix and P-loop-containing nucleoside triphosphate hydrolases. Finally, based on classification of the domains according to their ancestry, we determined that the set of 52 promiscuous domains are also ancient and abundant among all the genomes, in contrast to the non-promiscuous domains. In summary, we consider that the association between these two classes of protein domains (promiscuous and non-promiscuous) provides bacterial and archaeal cells with the ability to respond to diverse environmental challenges.

Identification of Modules With Similar Gene Regulation and Metabolic Functions Based on Co-expression Data.

Biological systems respond to environmental perturbations and to a large diversity of compounds through gene interactions, and these genetic factors comprise complex networks. In particular, a wide variety of gene co-expression networks have been constructed in recent years thanks to the dramatic increase of experimental information obtained with techniques, such as microarrays and RNA sequencing. These networks allow the identification of groups of co-expressed genes that can function in the same process and, in turn, these networks may be related to biological functions of industrial, medical and academic interest. In this study, gene co-expression networks for 17 bacterial organisms from the COLOMBOS database were analyzed via weighted gene co-expression network analysis and clustered into modules of genes with similar expression patterns for each species. These networks were analyzed to determine relevant modules through a hypergeometric approach based on a set of transcription factors and enzymes for each genome. The richest modules were characterized using PFAM families and KEGG metabolic maps. Additionally, we conducted a Gene Ontology analysis for enrichment of biological functions. Finally, we identified modules that shared similarity through all the studied organisms by using comparative genomics.

Consensus architecture of promoters and transcription units in Escherichia coli: design principles for synthetic biology.

Genetic information in genomes is ordered, arranged in such a way that it constitutes a code, the so-called cis regulatory code. The regulatory machinery of the cell, termed trans-factors, decodes and expresses this information. In this way, genomes maintain a potential repertoire of genetic programs, parts of which are executed depending on the presence of active regulators in each condition. These genetic programs, executed by the regulatory machinery, have functional units in the genome delimited by punctuation-like marks. In genetic terms, these informational phrases correspond to transcription units, which are the minimal genetic information expressed consistently from initiation to termination marks. Between the start and final punctuation marks, additional marks are present that are read by the transcriptional and translational machineries. In this work, we look at all the experimentally described and predicted genetic elements in the bacterium Escherichia coli K-12 MG1655 and define a comprehensive architectural organization of transcription units to reveal the natural genome-design and to guide the construction of synthetic genetic programs.

Transcription Factors Exhibit Differential Conservation in Bacteria with Reduced Genomes.

The description of transcriptional regulatory networks has been pivotal in the understanding of operating principles under which organisms respond and adapt to varying conditions. While the study of the topology and dynamics of these networks has been the subject of considerable work, the investigation of the evolution of their topology, as a result of the adaptation of organisms to different environmental conditions, has received little attention. In this work, we study the evolution of transcriptional regulatory networks in bacteria from a genome reduction perspective, which manifests itself as the loss of genes at different degrees. We used the transcriptional regulatory network of Escherichia coli as a reference to compare 113 smaller, phylogenetically-related γ-proteobacteria, including 19 genomes of symbionts. We found that the type of regulatory action exerted by transcription factors, as genomes get progressively smaller, correlates well with their degree of conservation, with dual regulators being more conserved than repressors and activators in conditions of extreme reduction. In addition, we found that the preponderant conservation of dual regulators might be due to their role as both global regulators and nucleoid-associated proteins. We summarize our results in a conceptual model of how each TF type is gradually lost as genomes become smaller and give a rationale for the order in which this phenomenon occurs.

Structural comparison of biological networks based on dominant vertices.

It is a current practice to organize biological data in a network structure where vertices represent biological components and arrows represent their interactions. A great diversity of graph theoretical notions, such as clustering coefficient, network motifs, centrality, degree distribution, etc., have been developed in order to characterize the structure of these networks. However, none of the existent characterizations allow us to determine global similarity among networks of different sizes. It is the aim of the present paper to introduce a mathematical tool to compare networks not only with regard to their topological structure, but also in their dynamical capabilities. For this reason we aim to propose a pseudo-distance between networks, built around the notions of determination and dominancy, concepts recently introduced in the context of regulatory dynamics on networks. We use our proposed pseudo-distance to compare networks from the following bacteria: E. coli, B. subtilis, P. aeruginosa, M. tuberculosis, S. aureus and C. glutamicum. We also use this pseudo-distance to compare these real bacterial networks with equivalent homogeneous, scale-free and geometric three dimensional random networks. We found that even when bacterial networks are characterized with different levels of detail, have different sizes and represent different aspects of the organisms, the proposed pseudo-distance captures all these characteristics, and indicates how similar they are or not from random networks.

The Regulatory Network of Pseudomonas aeruginosa.

BACKGROUND: Pseudomonas aeruginosa is an important bacterial model due to its metabolic and pathogenic abilities, which allow it to interact and colonize a wide range of hosts, including plants and animals. In this work we compile and analyze the structure and organization of an experimentally supported regulatory network in this bacterium. RESULTS: The regulatory network consists of 690 genes and 1020 regulatory interactions between their products (12% of total genes: 54% sigma and 16% of transcription factors). This complex interplay makes the third largest regulatory network of those reported in bacteria. The entire network is enriched for activating interactions and, peculiarly, self-activation seems to occur more prominent for transcription factors (TFs), which contrasts with other biological networks where self-repression is dominant. The network contains a giant component of 650 genes organized into 11 hierarchies, encompassing important biological processes, such as, biofilms formation, production of exopolysaccharide alginate and several virulence factors, and of the so-called quorum sensing regulons. CONCLUSIONS: The study of gene regulation in P. aeruginosa is biased towards pathogenesis and virulence processes, all of which are interconnected. The network shows power-law distribution -input degree -, and we identified the top ten global regulators, six two-element cycles, the longest paths have ten steps, six biological modules and the main motifs containing three and four elements. We think this work can provide insights for the design of further studies to cover the many gaps in knowledge of this important bacterial model, and for the design of systems strategies to combat this bacterium.