Effects of Four Different Regulatory Mechanisms on the Dynamics of Gene Regulatory Cascades

Optimization of a Cas12a-Driven Synthetic Gene Regulatory Network System

Gene regulatory networks, which control gene expression patterns in development and in response to stimuli, use regulatory logic modules to coordinate inputs and outputs. One example of a regulatory logic module is the gene regulatory cascade (GRC), where a series of transcription factor genes turn on in order. Synthetic biologists have derived artificial systems that encode regulatory rules, including GRCs. Furthermore, the development of single-cell approaches has enabled the discovery of gene regulatory modules in a variety of experimental settings. However, the tools available for validating these observations remain limited. Based on a synthetic GRC using DNA cutting-defective Cas9 (dCas9), we designed and implemented an alternative synthetic GRC utilizing DNA cutting-defective Cas12a (dCas12a). Comparing the ability of these two systems to express a fluorescent reporter, the dCas9 system was initially more active, while the dCas12a system was more streamlined. Investigating the influence of individual components of the systems identified nuclear localization as a major driver of differences in activity. Improving nuclear localization for the dCas12a system resulted in 1.5-fold more reporter-positive cells and a 15-fold increase in reporter intensity relative to the dCas9 system. We call this optimized system the "Synthetic Gene Regulatory Network" (SGRN, pronounced "sojourn").

Tissue-specific atlas of trans-models for gene regulation elucidates complex regulation patterns

BACKGROUND

Deciphering gene regulation is essential for understanding the underlying mechanisms of healthy and disease states. While the regulatory networks formed by transcription factors (TFs) and their target genes has been mostly studied with relation to cis effects such as in TF binding sites, we focused on trans effects of TFs on the expression of their transcribed genes and their potential mechanisms.

RESULTS

We provide a comprehensive tissue-specific atlas, spanning 49 tissues of TF variations affecting gene expression through computational models considering two potential mechanisms, including combinatorial regulation by the expression of the TFs, and by genetic variants within the TF. We demonstrate that similarity between tissues based on our discovered genes corresponds to other types of tissue similarity. The genes affected by complex TF regulation, and their modelled TFs, were highly enriched for pharmacogenomic functions, while the TFs themselves were also enriched in several cancer and metabolic pathways. Additionally, genes that appear in multiple clusters are enriched for regulation of immune system while tissue clusters include cluster-specific genes that are enriched for biological functions and diseases previously associated with the tissues forming the cluster. Finally, our atlas exposes multilevel regulation across multiple tissues, where TFs regulate other TFs through the two tested mechanisms.

CONCLUSIONS

Our tissue-specific atlas provides hierarchical tissue-specific trans genetic regulations that can be further studied for association with human phenotypes.

KinMod database: a tool for investigating metabolic regulation

The ability of current kinetic models to simulate the phenotypic behaviour of cells is limited since cell metabolism is regulated at different levels including enzyme regulation. The small molecule regulation network (SMRN) enables cells to respond rapidly to environmental fluctuations by controlling the activity of enzymes in metabolic pathways. However, SMRN is not as well studied relative to metabolic networks. The main contributor to the lack of knowledge on this regulatory system is the sparsity of experimental data and the absence of a standard framework for representing available information. In this paper, we introduce the KinMod database that encompasses more than 2 million data points on the metabolism and metabolic regulation network of 9814 organisms KinMod database employs a hierarchical data structure to: (i) signify relationships between kinetic information obtained through in-vitro experiments and proteins, with an emphasis on SMRN, (ii) provide a thorough insight into available kinetic parameters and missing experimental measurements of this regulatory network and (iii) facilitate machine learning approaches for parameter estimation and accurate kinetic model construction by providing a homogeneous list of linked omics data. The hierarchical ontology of the KinMod database allows flexible exploration of data attributes and investigation of metabolic relationships within- and cross-species. Identifying missing experimental values suggests additional experiments required for kinetic parameter estimation. Linking multi-omics data and providing data on SMRN encourages the development of novel machine learning techniques for predicting missing kinetic parameters and promotes accurate kinetic model construction of cells metabolism by providing a comprehensive list of available kinetic measurements. To illustrate the value of KinMod data, we develop six analyses to visualize associations between data classes belonging to separate sections of the metabolism. Through these analyses, we demonstrate that the KinMod database provides a unique framework for biologists and engineers to retrieve, evaluate and compare the functional metabolism of species, including the regulatory network, and discover the extent of available and missing experimental values of the metabolic regulation.

Database URL: https://lmse.utoronto.ca/kinmod/KINMOD.sql.gz

Structural, molecular hybridization and network based identification of miR-373-3p and miR-520e-3p as regulators of NR4A2 human gene involved in neurodegeneration

MicroRNAs (miRNAs) are short non-coding RNAs with a 22 nucleotide sequence length and docks to the 3'UTR/5'UTR of the gene to regulate their mRNA translation to play a vital role in neurodegenerative diseases. The Nuclear Receptor gene (NR4A2), a transcription factor, and a steroid-thyroid hormone retinoid receptor is involved in neural development, memory formation, dopaminergic neurotransmission, and cellular protection from inflammatory damage. Therefore, recognizing the miRNAs is essential to efficiently target the 3'UTR/5'UTR of the NR4A2 gene and regulate neurodegeneration. Highly stabilized top miRNA-mRNA hybridized structures, their homologs, and identification of the best structures based on their least free energy were evaluated using in silico techniques. The miR-gene, gene-gene network analysis, miR-disease association, and transcription factor binding sites were also investigated. Results suggest top 166 miRNAs targeting the NR4A2 mRNA, but with a total of 10 miRNAs bindings with 100% seed sequence identity (both at 3' and 5'UTR) at the same position on the NR4A2 mRNA region. The miR-373-3p and miR-520e-3p are considered the best candidate miRNAs hybridizing with high efficiency at both 3' and 5'UTR of NR4A2 mRNA. This could be due to the most significant seed sequence length complementary, supplementary pairing, and absence of non-canonical base pairs. Furthermore, the miR-gene network, target gene-gene interaction analysis, and miR-disease association provide an understanding of the molecular, cellular, and biological processes involved in various pathways regulated by four transcription factors (PPARG, ZNF740, NRF1, and RREB1). Therefore, miR-373-3p, 520e-3p, and four transcription factors can regulate the NR4A2 gene involved in the neurodegenerative process.

Ecotoxicological epigenetics in invertebrates: Emerging tool for the evaluation of present and past pollution burden

The effect of environmental pollution on epigenetic changes and their heredity in affected organisms is of major concern as such changes can play a significant role in adaptation to changing environmental conditions. Changes of epigenetic marks including DNA methylation, histone modifications, and non-coding RNA's can induce changes in gene transcription leading to physiological long-term changes or even transgenerational inheritance. Such mechanisms have until recently been scarcely studied in invertebrate organisms, mainly focusing on model species including Caenorhabditis elegans and Daphnia magna. However, more data are becoming available, particularly focused on DNA methylation changes caused by anthropogenic pollutants in a wide range of invertebrates. This review examines the literature from field and laboratory studies utilising invertebrate species exposed to environmental pollutants and their effect on DNA methylation. Possible mechanisms of epigenetic modifications and their role on physiology and adaptation as well as the incidence of intergenerational and transgenerational inheritance are discussed. Furthermore, critical research challenges are defined and the way forward is proposed. Future studies should focus on the use of next generation sequencing tools to define invertebrate methylomes under environmental stress in higher resolution, those data should further be linked to gene expression patterns and phenotypes and detailed studies focusing on transgenerational effects are encouraged. Moreover, studies of other epigenetic mechanisms in various invertebrate species, apart from DNA methylation would provide better understanding of interconnected cross-talk between epigenetic marks. Taken together incorporating epigenetic studies in ecotoxicology context presents a promising tool for development of sensitive biomarkers for environmental stress assessment.

Systematic comparison of the response properties of protein and RNA mediated gene regulatory motifs

We present a framework enabling the dissection of the effects of motif structure (feedback or feedforward), the nature of the controller (RNA or protein), and the regulation mode (transcriptional, post-transcriptional or translational) on the response to a step change in the input. We have used a common model framework for gene expression where both motif structures have an activating input and repressing regulator, with the same set of parameters, to enable a comparison of the responses. We studied the global sensitivity of the system properties, such as steady-state gain, overshoot, peak time, and peak duration, to parameters. We find that, in all motifs, overshoot correlated negatively whereas peak duration varied concavely with peak time. Differences in the other system properties were found to be mainly dependent on the nature of the controller rather than the motif structure. Protein mediated motifs showed a higher degree of adaptation i.e. a tendency to return to baseline levels; in particular, feedforward motifs exhibited perfect adaptation. RNA mediated motifs had a mild regulatory effect; they also exhibited a lower peaking tendency and mean overshoot. Protein mediated feedforward motifs showed higher overshoot and lower peak time compared to the corresponding feedback motifs.