Computational biology approaches for mapping transcriptional regulatory networks

Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights

Understanding the influence of cis-regulatory elements on gene regulation poses numerous challenges given complexities stemming from variations in transcription factor (TF) binding, chromatin accessibility, structural constraints, and cell-type differences. This review discusses the role of gene regulatory networks in enhancing understanding of transcriptional regulation and covers construction methods ranging from expression-based approaches to supervised machine learning. Additionally, key experimental methods, including MPRAs and CRISPR-Cas9-based screening, which have significantly contributed to understanding TF binding preferences and cis-regulatory element functions, are explored. Lastly, the potential of machine learning and artificial intelligence to unravel cis-regulatory logic is analyzed. These computational advances have far-reaching implications for precision medicine, therapeutic target discovery, and the study of genetic variations in health and disease.

Characteristics of NAC transcription factors in Solanaceae crops and their roles in responding to abiotic and biotic stresses

As one of the largest transcription factor (TF) families in plants, the NAC (NAM, ATAF1/2, and CUC2) family plays important roles in response pathways to various abiotic and biotic stresses, such as drought, high salinity, low temperature, and pathogen infection. Although, there are a number of reviews on the involvement of NAC TF in plant responses to biotic and abiotic stresses, most of them are focused on the model plants Arabidopsis thaliana and Oryza sativa, and there is a lack of systematic evaluation of specific species. Solanaceae, the world's third most significant cash crop, has been seriously affected by environmental disturbances in recent years in terms of yield and quality, posing a severe threat to global food security. This review focuses on the functional roles of NAC transcription factors in response to external stresses involved in five important Solanaceae crops: tomato, potato, pepper, eggplant and tobacco, and analyzes the affinities between them. It will provide resources for stress-resistant breeding of Solanaceae crops using transgenic technology.

From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies

In the dynamic landscape of targeted therapeutics, drug discovery has pivoted towards understanding underlying disease mechanisms, placing a strong emphasis on molecular perturbations and target identification. This paradigm shift, crucial for drug discovery, is underpinned by big data, a transformative force in the current era. Omics data, characterized by its heterogeneity and enormity, has ushered biological and biomedical research into the big data domain. Acknowledging the significance of integrating diverse omics data strata, known as multi-omics studies, researchers delve into the intricate interrelationships among various omics layers. This review navigates the expansive omics landscape, showcasing tailored assays for each molecular layer through genomes to metabolomes. The sheer volume of data generated necessitates sophisticated informatics techniques, with machine-learning (ML) algorithms emerging as robust tools. These datasets not only refine disease classification but also enhance diagnostics and foster the development of targeted therapeutic strategies. Through the integration of high-throughput data, the review focuses on targeting and modeling multiple disease-regulated networks, validating interactions with multiple targets, and enhancing therapeutic potential using network pharmacology approaches. Ultimately, this exploration aims to illuminate the transformative impact of multi-omics in the big data era, shaping the future of biological research.

Smoking changes adaptive immunity with persistent effects

Individuals differ widely in their immune responses, with age, sex and genetic factors having major roles in this inherent variability1-6. However, the variables that drive such differences in cytokine secretion-a crucial component of the host response to immune challenges-remain poorly defined. Here we investigated 136 variables and identified smoking, cytomegalovirus latent infection and body mass index as major contributors to variability in cytokine response, with effects of comparable magnitudes with age, sex and genetics. We find that smoking influences both innate and adaptive immune responses. Notably, its effect on innate responses is quickly lost after smoking cessation and is specifically associated with plasma levels of CEACAM6, whereas its effect on adaptive responses persists long after individuals quit smoking and is associated with epigenetic memory. This is supported by the association of the past smoking effect on cytokine responses with DNA methylation at specific signal trans-activators and regulators of metabolism. Our findings identify three novel variables associated with cytokine secretion variability and reveal roles for smoking in the short- and long-term regulation of immune responses. These results have potential clinical implications for the risk of developing infections, cancers or autoimmune diseases.

Growth-regulating factor 15-mediated gene regulatory network enhances salt tolerance in poplar

Soil salinity is an important determinant of crop productivity and triggers salt stress response pathways in plants. The salt stress response is controlled by transcriptional regulatory networks that maintain regulatory homeostasis through combinations of transcription factor (TF)-DNA and TF-TF interactions. We investigated the transcriptome of poplar 84 K (Populus alba × Populus glandulosa) under salt stress using samples collected at 4- or 6-h intervals within 2 days of salt stress treatment. We detected 24,973 differentially expressed genes, including 2,231 TFs that might be responsive to salt stress. To explore these interactions and targets of TFs in perennial woody plants, we combined gene regulatory networks, DNA affinity purification sequencing, yeast two-hybrid-sequencing, and multi-gene association approaches. Growth-regulating factor 15 (PagGRF15) and its target, high-affinity K+ transporter 6 (PagHAK6), were identified as an important regulatory module in the salt stress response. Overexpression of PagGRF15 and PagHAK6 in transgenic lines improved salt tolerance by enhancing Na+ transport and modulating H2O2 accumulation in poplar. Yeast two-hybrid assays identified more than 420 PagGRF15-interacting proteins, including ETHYLENE RESPONSE FACTOR TFs and a zinc finger protein (C2H2) that are produced in response to a variety of phytohormones and environmental signals and are likely involved in abiotic stress. Therefore, our findings demonstrate that PagGRF15 is a multifunctional TF involved in growth, development, and salt stress tolerance, highlighting the capability of a multifaceted approach in identifying regulatory nodes in plants.

Cracking the Code of Neuronal Cell Fate

Transcriptional regulation is fundamental to most biological processes and reverse-engineering programs can be used to decipher the underlying programs. In this review, we describe how genomics is offering a systems biology-based perspective of the intricate and temporally coordinated transcriptional programs that control neuronal apoptosis and survival. In addition to providing a new standpoint in human pathology focused on the regulatory program, cracking the code of neuronal cell fate may offer innovative therapeutic approaches focused on downstream targets and regulatory networks. Similar to computers, where faults often arise from a software bug, neuronal fate may critically depend on its transcription program. Thus, cracking the code of neuronal life or death may help finding a patch for neurodegeneration and cancer.

Mathematical modeling of regulatory networks of intracellular processes - Aims and selected methods

Regulatory networks structure and signaling pathways dynamics are uncovered in time- and resource consuming experimental work. However, it is increasingly supported by modeling, analytical and computational techniques as well as discrete mathematics and artificial intelligence applied to to extract knowledge from existing databases. This review is focused on mathematical modeling used to analyze dynamics and robustness of these networks. This paper presents a review of selected modeling methods that facilitate advances in molecular biology.

Mr.Vc v2: An updated version of database with increased data of transcriptome and experimental validated interactions

Mr.Vc is a database of curated Vibrio cholerae transcriptome data and annotated information. The main objective is to facilitate the accessibility and reusability of the rapidly growing Vibrio cholerae omics data and relevant annotation. To achieve these goals, we performed manual curation on the transcriptome data and organized the datasets in an experiment-centric manner. We collected unknown operons annotated through text-mining analysis that would provide more clues about how Vibrio cholerae modulates gene regulation. Meanwhile, to understand the relationship between genes or experiments, we performed gene co-expression analysis and experiment-experiment correlation analysis. In additional, functional module named “Interactions” which dedicates to collecting experimentally validated interactions about Vibrio cholerae from public databases, MEDLINE documents and literature in life science journals. To date, Mr.Vc v2, which is significantly increased from the previous version, contains 107 microarray experiments, 106 RNA-seq experiments, and 3 Tn-seq projects, covering 56,839 entries of DEGs (Differentially Expressed Genes) from transcriptomes and 7,463 related genes from Tn-seq, respectively. and a total of 270,129 gene co-expression entries and 11,990 entries of experiment-experiment correlation was obtained, in total 1,316 entries of interactions were collected, including 496 protein-chemical signaling molecule interactions, 472 protein–protein interactions, 306 TF (Transcription Factor)-gene interactions and 42 Vibrio cholerae-virus interactions, most of which obtained from 402 literature through text-mining analysis. To make the information easier to access, Mr.Vc v2 is equipped with a search widget, enabling users to query what they are interested in. Mr.Vc v2 is freely available at http://mrvcv2.biownmc.info.

E2F2 promotes lung adenocarcinoma progression through B-Myb- and FOXM1-facilitated core transcription regulatory circuitry

Lung adenocarcinoma (LUAD) causes severe cancer death worldwide. E2F2 is a canonical transcription factor implicated in transcription regulation, cell cycle and tumorigenesis. The role of E2F2 as well as its transcription regulatory network in LUAD remains obscure. In this study, we constructed a weighted gene co-expression network and identified several key modules and networks overrepresented in LUAD, including the E2F2-centered transcription regulatory network. Function analysis revealed that E2F2 overexpression accelerated cell growth, cell cycle progression and cell motility in LUAD cells whereas E2F2 knockdown inhibited these malignant phenotypes. Mechanistic investigations uncovered various E2F2-regulated downstream genes and oncogenic signaling pathways. Notably, three core transcription factors of E2F2, B-Myb and FOXM1 from the LUAD transcription regulatory network exhibited positive expression correlation, associated with each other, mutually transactivated each other, and regulated similar downstream gene cascades, hence constituting a consolidated core transcription regulatory circuitry. Moreover, E2F2 could promote and was essentially required for LUAD growth in orthotopic mouse models. Prognosis modeling revealed that a two-gene signature of E2F2 and PLK1 from the transcription regulatory circuitry remarkably stratified patients into low- and high-risk groups. Collectively, our results clarified the critical roles of E2F2 and the exquisite core transcription regulatory circuitry of E2F2/B-Myb/FOXM1 in LUAD progression.

Molecular Regulatory Mechanisms Drive Emergent Pathogenetic Properties of Neisseria gonorrhoeae

Neisseria gonorrhoeae is the causative agent of the sexually transmitted infection (STI) gonorrhea, with an estimated 87 million annual cases worldwide. N. gonorrhoeae predominantly colonizes the male and female genital tract (FGT). In the FGT, N. gonorrhoeae confronts fluctuating levels of nutrients and oxidative and non-oxidative antimicrobial defenses of the immune system, as well as the resident microbiome. One mechanism utilized by N. gonorrhoeae to adapt to this dynamic FGT niche is to modulate gene expression primarily through DNA-binding transcriptional regulators. Here, we describe the major N. gonorrhoeae transcriptional regulators, genes under their control, and how these regulatory processes lead to pathogenic properties of N. gonorrhoeae during natural infection. We also discuss the current knowledge of the structure, function, and diversity of the FGT microbiome and its influence on gonococcal survival and transcriptional responses orchestrated by its DNA-binding regulators. We conclude with recent multi-omics data and modeling tools and their application to FGT microbiome dynamics. Understanding the strategies utilized by N. gonorrhoeae to regulate gene expression and their impact on the emergent characteristics of this pathogen during infection has the potential to identify new effective strategies to both treat and prevent gonorrhea.

Unveiling Forkhead-mediated regulation of yeast cell cycle and metabolic networks

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Findings from genome-wide ChIP studies on budding yeast Forkheads are interpreted.

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Power, challenges and limitation of ChIP studies are presented by target gene analysis.

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Forkheads regulate metabolic targets through which cell division may be coordinated.

Transcription factors are regulators of the cell’s genomic landscape. By switching single genes or entire molecular pathways on or off, transcription factors modulate the precise timing of their activation. The Forkhead (Fkh) transcription factors are evolutionarily conserved to regulate organismal physiology and cell division. In addition to molecular biology and biochemical efforts, genome-wide studies have been conducted to characterize the genomic landscape potentially regulated by Forkheads in eukaryotes. Here, we discuss and interpret findings reported in six genome-wide Chromatin ImmunoPrecipitation (ChIP) studies, with a particular focus on ChIP-chip and ChIP-exo. We highlight their power and challenges to address Forkhead-mediated regulation of the cellular landscape in budding yeast. Expression changes of the targets identified in the binding assays are investigated by taking expression data for Forkhead deletion and overexpression into account. Forkheads are revealed as regulators of the metabolic network through which cell cycle dynamics may be temporally coordinated further, in addition to their well-known role as regulators of the gene cluster responsible for cell division.

The variation in promoter sequences of the Akt3 gene between cow and buffalo revealed different responses against mastitis

Background

Serine/threonine kinase 3 (AKT3) is a protein-coding gene that is associated with several cattle immune diseases including different tumors and cancers. The objective of this study was to investigate the differences in structures and functions of AKT3 of cow and buffalo cattle.

Methods

The sequence differences of gene-coding sequence (CDS) and core promoter region of AKT3 in cow and buffalo were analyzed by using bioinformatics tools and PCR sequencing. Also, the functional analysis of promoter regulating gene expression by RT-PCR was performed using 500 Holstein cows and buffalos. And, evaluation of AKT3 inflammatory response to the lipopolysaccharide (LPS)-induced mastitis was performed between both species.

Results

The results revealed the variation in 6 exons out of 13 exons of the two species of CDS. Also, 4 different regions in 3-kb promoters of the AKT3 gene were significantly different between cow and buffalo species, in which cow’s AKT3 promoter sequence region was started from − 371 to − 1247, while in buffalo, the sequence was started from − 371 to − 969 of the promoter crucial region. Thus, the promoter was overexpressed in cows compared to buffaloes. As a result, significant differences (P < 0.05) between the two species in the AKT3 gene expression level related to the LPS stimulation in their mammary epithelial cell line.

Conclusions

This study emphasized the great importance of the structural differences of AKT3 between the animal species on their different responses against immune diseases like mastitis.