ConvChrome: Predicting Gene Expression Based on Histone Modifications using Deep Learning Techniques.

Background: Gene regulation is a complex and a dynamic process that not only depends on the DNA sequence of genes, but also is influenced by a key factor called Epigenetic Mechanisms. This factor along with other factors contributes to change the behavior of DNA. While these factors cannot affect the structure of DNA, they can control the behavior of DNA by turning genes "on" or "off" that leads to determine which proteins are transcribed. Objective: This paper will focus on histone modifications mechanism, histones are the group of proteins that bundle the DNA into a structural form called nucleosomes (coils); how DNA wraps with these histone proteins describes how gene can be accessed to express or not. When histones bound tightly to DNA, that make the gene cannot be expressed and vise verse. It is important to know Histone Modifications’ combinatorial patterns, and how these combinatorial patterns can affect and work together to control the process of gene expression. Methods: In this paper, ConvChrome deep learning methodologies are proposed for predicting the gene expression behavior from Histone modifications data as an input to use more than one Convolutional Network model, this happens in order to recognize patterns of histones signals and to interpret their spatial relationship arranged on chromatin structure to give insights into regulatory signatures of histone modifications. Results and Conclusion: The experiments results show that ConvChrome achieved 88.741 % in terms of Area under the Curve (AUC) score, which is an outstanding improvement over the baseline for gene expression classification prediction task from combinatorial interactions among five histone modifications on 56 different cell-types.

Extensive loss of Wnt genes in Tardigrada

Background Wnt genes code for ligands that activate signaling pathways during development in Metazoa. Through the canonical Wnt (cWnt) signaling pathway, these genes regulate important processes in bilaterian development, such as establishing the anteroposterior axis and posterior growth. In Arthropoda, Wnt ligands also regulate segment polarity, and outgrowth and patterning of developing appendages. Arthropods are part of a lineage called Panarthropoda that includes Onychophora and Tardigrada. Previous studies revealed potential roles of Wnt genes in regulating posterior growth, segment polarity, and growth and patterning of legs in Onychophora. Unlike most other panarthropods, tardigrades lack posterior growth, but retain segmentation and appendages. Here, we investigated Wnt genes in tardigrades to gain insight into potential roles that these genes play during development of the highly compact and miniaturized tardigrade body plan. Results We analyzed published genomes for two representatives of Tardigrada, Hypsibius exemplaris and Ramazzottius varieornatus. We identified single orthologs of Wnt4, Wnt5, Wnt9, Wnt11, and WntA, as well as two Wnt16 paralogs in both tardigrade genomes. We only found a Wnt2 ortholog in H. exemplaris. We could not identify orthologs of Wnt1, Wnt6, Wnt7, Wnt8, or Wnt10. We identified most other components of cWnt signaling in both tardigrade genomes. However, we were unable to identify an ortholog of arrow/Lrp5/6, a gene that codes for a Frizzled co-receptor of Wnt ligands. Additionally, we found that some other animals that have lost several Wnt genes and are secondarily miniaturized, like tardigrades, are also missing an ortholog of arrow/Lrp5/6. We analyzed the embryonic expression patterns of Wnt genes in H. exemplaris during developmental stages that span the establishment of the AP axis through segmentation and leg development. We detected expression of all Wnt genes in H. exemplaris besides one of the Wnt16 paralogs. During embryo elongation, expression of several Wnt genes was restricted to the posterior pole or a region between the anterior and posterior poles. Wnt genes were expressed in distinct patterns during segmentation and development of legs in H. exemplaris, rather than in broadly overlapping patterns. Conclusions Our results indicate that Wnt signaling has been highly modified in Tardigrada. While most components of cWnt signaling are conserved in tardigrades, we conclude that tardigrades have lost Wnt1, Wnt6, Wnt7, Wnt8, and Wnt10, along with arrow/Lrp5/6. Our expression data may indicate a conserved role of Wnt genes in specifying posterior identities during establishment of the AP axis. However, the loss of several Wnt genes and the distinct expression patterns of Wnt genes during segmentation and leg development may indicate that combinatorial interactions among Wnt genes are less important during tardigrade development compared to many other animals. Based on our results, and comparisons to previous studies, we speculate that the loss of several Wnt genes in Tardigrada may be related to a reduced number of cells and simplified development that accompanied miniaturization and anatomical simplification in this lineage.

An IRF1-IRF4 Toggle-Switch Controls Tolerogenic and Immunogenic Transcriptional Programming in Human Langerhans Cells

Langerhans cells (LCs) reside in the epidermis as a dense network of immune system sentinels, coordinating both immunogenic and tolerogenic immune responses. To determine molecular switches directing induction of LC immune activation, we performed mathematical modelling of gene regulatory networks identified by single cell RNA sequencing of LCs exposed to TNF-alpha, a key pro-inflammatory signal produced by the skin. Our approach delineated three programmes of LC phenotypic activation (immunogenic, tolerogenic or ambivalent), and confirmed that TNF-alpha enhanced LC immunogenic programming. Through regulon analysis followed by mutual information modelling, we identified IRF1 as the key transcription factor for the regulation of immunogenicity in LCs. Application of a mathematical toggle switch model, coupling IRF1 with tolerance-inducing transcription factors, determined the key set of transcription factors regulating the switch between tolerance and immunogenicity, and correctly predicted LC behaviour in LCs derived from different body sites. Our findings provide a mechanistic explanation of how combinatorial interactions between different transcription factors can coordinate specific transcriptional programmes in human LCs, interpreting the microenvironmental context of the local tissue microenvironments.

Combinatorial interactions between viral proteins expand the functional landscape of the viral proteome

As intracellular parasites, viruses need to manipulate the molecular machinery of their host cells in order to enable their own replication and spread. This manipulation is based on the activity of virus-encoded proteins. The reduced size of viral genomes imposes restrictions in coding capacity; how the action of the limited number of viral proteins results in the massive cell reprogramming observed during the viral infection is a long-standing conundrum in virology. In this work, we explore the hypothesis that combinatorial interactions expand the multifunctionality of viral proteins, which may exert different activities individually and when in combination, physical or functional. We show that the proteins encoded by a plant-infecting DNA virus physically associate with one another in an intricate network. Our results further demonstrate that these interactions can modify the subcellular localization of the viral proteins involved, and that co-expressed interacting viral proteins can exert novel biological functions in planta that go beyond the sum of their individual functions. Based on this, we propose a model in which combinatorial physical and functional interactions between viral proteins enlarge the functional landscape of the viral proteome, which underscores the importance of studying the role of viral proteins in the context of the infection.

Mobius Assembly for Plant Systems highlights promoter-terminator interaction in gene regulation

Plant synthetic biology is a fast-evolving field that employs engineering principles to empower research and bioproduction in plant systems. Nevertheless, in the whole synthetic biology landscape, plant systems lag compared to microbial and mammalian systems. When it comes to multigene delivery to plants, the predictability of the outcome is decreased since it depends on three different chassis: E.coli, Agrobacterium, and the plant species. Here we aimed to develop standardised and streamlined tools for genetic engineering in plant synthetic biology. We have devised Mobius Assembly for Plant Systems (MAPS), a user-friendly Golden Gate Assembly system for fast and easy generation of complex DNA constructs. MAPS is based on a new group of small plant binary vectors (pMAPs) that contains an origin of replication from a cryptic plasmid of Paracoccuspantotrophus. The functionality of the pMAP vectors was confirmed by transforming the MM1 cell culture, demonstrating for the first time that plant transformation is dependent on the Agrobacterium strains and plasmids; plasmid stability was highly dependent on the plasmid and bacterial strain. We made a library of new short promoters and terminators and characterised them using a high-throughput protoplast expression assay. Our results underscored the strong influence of terminators in gene expression, and they altered the strength of promoters in some combinations and indicated the presence of synergistic interactions between promoters and terminators. Overall this work will further facilitate plant synthetic biology and contribute to improving its predictability, which is challenged by combinatorial interactions among the genetic parts, vectors, and chassis.

TNF signalling fine-tunes Langerhans cell transcriptional programmes mediating adaptive immunity

ABSTRACTLangerhans cells (LCs) reside in the epidermis as a dense network of immune system sentinels, coordinating both immunogenic and tolerogenic immune responses. To determine molecular switches directing induction of LC immune activation, we performed mathematical modelling of gene regulatory networks identified by single cell RNA sequencing of LCs exposed to TNF, a key pro-inflammatory signal produced by the skin. Our approach delineated three programmes of LC phenotypic activation (immunogenic, tolerogenic or ambivalent), and confirmed that TNF enhanced LC immunogenic programming. Through regulon analysis followed by mutual information modelling, we identified IRF1 as the key transcription factor for the regulation of immunogenicity in LCs. Application of a mathematical toggle switch model, coupling IRF1 with tolerance-inducing transcription factors, determined the key set of transcription factors regulating the switch between tolerance and immunogenicity, and correctly predicted LC behaviour in LCs derived from different body sites. Our findings provide a mechanistic explanation of how combinatorial interactions between different transcription factors can coordinate specific transcriptional programmes in human LCs, interpreting the microenvironmental context of the local tissue microenvironments.

A Screen for Small Molecules to Target Candida albicans Biofilms

The human fungal pathogen Candida albicans can form biofilms on biotic and abiotic surfaces, which are inherently resistant to antifungal drugs. We screened the Chembridge Small Molecule Diversity library containing 30,000 “drug-like” small molecules and identified 45 compounds that inhibited biofilm formation. These 45 compounds were then tested for their abilities to disrupt mature biofilms and for combinatorial interactions with fluconazole, amphotericin B, and caspofungin, the three antifungal drugs most commonly prescribed to treat Candida infections. In the end, we identified one compound that moderately disrupted biofilm formation on its own and four compounds that moderately inhibited biofilm formation and/or moderately disrupted mature biofilms only in combination with either caspofungin or fluconazole. No combinatorial interactions were observed between the compounds and amphotericin B. As members of a diversity library, the identified compounds contain “drug-like” chemical backbones, thus even seemingly “weak hits” could represent promising chemical starting points for the development and the optimization of new classes of therapeutics designed to target Candida biofilms.

The context-dependent, combinatorial logic of BMP signaling

SummaryCell-cell communication systems typically comprise families of ligand and receptor variants that function together in combinations. Pathway activation depends in a complex way on which ligands are present and what receptors are expressed by the signal-receiving cell. To understand the combinatorial logic of such a system, we systematically measured pairwise Bone Morphogenetic Protein (BMP) ligand interactions in cells with varying receptor expression. Ligands could be classified into equivalence groups based on their profile of positive and negative synergies with other ligands. These groups varied with receptor expression, explaining how ligands can functionally replace each other in one context but not another. Context-dependent combinatorial interactions could be explained by a biochemical model based on competitive formation of alternative signaling complexes with distinct activities. Together, these results provide insights into the roles of BMP combinations in developmental and therapeutic contexts and establish a framework for analyzing other combinatorial, context-dependent signaling systems.

Synchronized genetic activities in Alzheimer’s brains revealed by heterogeneity-capturing network analysis

It is becoming increasingly evident that the efficacy of single-gene computational analyses for complex traits is nearly exhausted and future advances hinge on unraveling the intricate combinatorial interactions among multiple genes. However, the discovery of modules of genes working in concert to manifest a complex trait has been crippled by combinatorial complexity, genetic heterogeneity, and validation biases. We introduce Maestro, a novel network approach that employs a multifaceted correlation measure, which captures heterogeneity, and a rigorous validation method. Maestro’s utilization for Alzheimer’s disease (AD) reveals an expression pattern that has virtually zero probability of simultaneous expression by an individual, assuming independence. Yet this pattern is exhibited by 19.0% of AD cases and 7.3% of controls, establishing an unprecedented pattern of synchronized genetic activities in the human brain. This pattern is significantly associated with AD, with an odds ratio of 3.0. This study substantiates Maestro’s power for discovery of orchestrated genetic activities underlying complex traits. More generally, Maestro can be applied in diverse domains in which heterogeneity exists.HighlightsSynchronized genetic activities associated with Alzheimer’s diseaseNovel vector-based correlation measure that captures genetic heterogeneityEnhanced network model for revealing combinatorial genetic interactionsPro-survival genetic activities associated with Alzheimer’s diseaseGeneral approach for revealing patterns in data subject to heterogeneity

Combinatorial interactions of the LEC1 transcription factor specify diverse developmental programs during soybean seed development

The LEAFY COTYLEDON1 (LEC1) transcription factor is a central regulator of seed development, because it controls diverse biological programs during seed development, such as embryo morphogenesis, photosynthesis, and seed maturation. To understand how LEC1 regulates different gene sets during development, we explored the possibility that LEC1 acts in combination with other transcription factors. We identified and compared genes that are directly transcriptionally regulated by ABA-RESPONSIVE ELEMENT BINDING PROTEIN3 (AREB3), BASIC LEUCINE ZIPPER67 (bZIP67), and ABA INSENSITIVE3 (ABI3) with those regulated by LEC1. We showed that LEC1 operates with specific sets of transcription factors to regulate different gene sets and, therefore, distinct developmental processes. Thus, LEC1 controls diverse processes through its combinatorial interactions with other transcription factors. DNA binding sites for the transcription factors are closely clustered in genomic regions upstream of target genes, defining cis-regulatory modules that are enriched for DNA sequence motifs that resemble sequences known to be bound by these transcription factors. Moreover, cis-regulatory modules for genes regulated by distinct transcription factor combinations are enriched for different sets of DNA motifs. Expression assays with embryo cells indicate that the enriched DNA motifs are functional cis elements that regulate transcription. Together, the results suggest that combinatorial interactions between LEC1 and other transcription factors are mediated by cis-regulatory modules containing clustered cis elements and by physical interactions that are documented to occur between the transcription factors.