Several classes of transcription factors have been investigated in light signaling pathways that bind to the Light Responsive Elements (LREs) present in the promoters of light regulatory genes for transcriptional regulation. Some of these transcription factors have been shown to be binding to numerous promoters through genome-wide ChIP-on-chip (ChIP-chip) studies. Furthermore, through the integration of ChIP-seq and RNA-seq techniques, it has been demonstrated that a transcription factor modifies the expression of numerous genes with which it interacts. However, the mode of action of these transcription factors and their dependency on other regulators in the pathway has just started to be unraveled. In this review article, we focus on a particular class of transcription factors, ZBF (Z-box Binding Factor), and their associated partners within the same or other classes of transcription factors and regulatory proteins during photomorphogenesis. Moreover, we have further made an attempt to summarize the cross talk of these transcription factors with jasmonic acid, abscisic acid and salicylic acid mediated defense signaling pathways. This review offers an in-depth insight into the manner in which ZBFs and their interactors reshape cellular functions and plant behavior. The underlying principles not only contribute to a comprehensive understanding but also establish a framework for analyzing the interplay between early developmental events and hormone signaling, a regulation orchestrated by the ZBF family.

This study aimed to develop a multienzymatic system for synthesis of L-malate. First, recombinant Escherichia coli strains were constructed expressing maleic acid cis-trans isomerase (MaiA) or fumarase C (FumC) from different sources. Serratia marcescens MaiA (SMaiA) and E. coli FumC (ECFumC) showed good catalytic performance. Next, six co-expression systems for SMaiA and ECFumC were constructed. E. coli BL21 (DE3)-pRSFDuet-1-ecfumC-smaiA (named strain pFM2) had the highest L-malate catalytic activity. In 7-L fed-batch fermentation, the SMaiA and ECFumC activities of strain pFM2 wet cells were 43.4 and 154.5 U/g, respectively, 2.4- and 10.7-fold the values that were obtained in shaken flasks. Finally, a whole-cell catalytic process was established for the production of L-malate by strain pFM2 with maleate as the substrate. When the dose of pFM2 wet cells was 0.5 g/100 mL and 1 mol/L maleate was the substrate, the catalytic process was completed within 4 h. Notably, the intermediate fumarate was almost absent during the conversion process. The concentration of L-malate reached 143.8 g/L with a yield of 0.60 g/(L·min). The molar conversion rate of the substrate was 98.4%. These findings lay a foundation for the industrial application of multienzymatic synthesis of L-malate.

Glioblastoma (GBM), a highly malignant tumour of the central nervous system, presents with a dire prognosis and low survival rates. The heterogeneous and recurrent nature of GBM renders current treatments relatively ineffective. In our study, we utilized an integrative systems biology approach to uncover the molecular mechanisms driving GBM progression and identify viable therapeutic drug targets for developing more effective GBM treatment strategies. Our integrative analysis revealed an elevated expression of CHST2 in GBM tumours, designating it as an unfavourable prognostic gene in GBM, as supported by data from two independent GBM cohorts. Further, we pinpointed WZ-4002 as a potential drug candidate to modulate CHST2 through computational drug repositioning. WZ-4002 directly targeted EGFR (ERBB1) and ERBB2, affecting their dimerization and influencing the activity of adjacent genes, including CHST2. We validated our findings by treating U-138 MG cells with WZ-4002, observing a decrease in CHST2 protein levels and a reduction in cell viability. In summary, our research suggests that the WZ-4002 drug candidate may effectively modulate CHST2 and adjacent genes, offering a promising avenue for developing efficient treatment strategies for GBM patients.

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used approach for the generation of gene co-expression networks. However, networks generated with this tool usually create large modules with a large set of functional annotations hard to decipher. We have developed TGCN, a new method to create Targeted Gene Co-expression Networks. This method identifies the transcripts that best predict the trait of interest based on gene expression using a refinement of the LASSO regression. Then, it builds the co-expression modules around those transcripts. Algorithm properties were characterized using the expression of 13 brain regions from the Genotype-Tissue Expression project. When comparing our method with WGCNA, TGCN networks lead to more precise modules that have more specific and yet rich biological meaning. Then, we illustrate its applicability by creating an APP-TGCN on The Religious Orders Study and Memory and Aging Project dataset, aiming to identify the molecular pathways specifically associated with APP role in Alzheimer\'s disease. Main biological findings were further validated in two independent cohorts. In conclusion, we provide a new framework that serves to create targeted networks that are smaller, biologically relevant and useful in high throughput hypothesis driven research. The TGCN R package is available on Github: https://github.com/aliciagp/TGCN .

This study investigated how gene expression is affected by dietary fatty acids (FA) by using pigs as a reliable model for studying human diseases that involve lipid metabolism. This includes changes in FA composition in the liver, blood serum parameters and overall metabolic pathways. RNA-Seq data from 32 pigs were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA). Our aim was to identify changes in blood serum parameters and gene expression between diets containing 3% soybean oil (SOY3.0) and a standard pig production diet containing 1.5% soybean oil (SOY1.5). Significantly, both the SOY1.5 and SOY3.0 groups showed significant modules, with a higher number of co-expressed modules identified in the SOY3.0 group. Correlated modules and specific features were identified, including enriched terms and pathways such as the histone acetyltransferase complex, type I diabetes mellitus pathway, cholesterol metabolism, and metabolic pathways in SOY1.5, and pathways related to neurodegeneration and Alzheimer\'s disease in SOY3.0. The variation in co-expression observed for HDL in the groups analyzed suggests different regulatory patterns in response to the higher concentration of soybean oil. Key genes co-expressed with metabolic processes indicative of diseases such as Alzheimer\'s was also identified, as well as genes related to lipid transport and energy metabolism, including CCL5, PNISR, DEGS1. These findings are important for understanding the genetic and metabolic responses to dietary variation and contribute to the development of more precise nutritional strategies.

Gene co-expression provides crucial insights into biological functions, however, there is a lack of exploratory analysis tools for localized gene co-expression in large-scale datasets. We present GeneSurfer, an interactive interface designed to explore localized transcriptome-wide gene co-expression patterns in the 3D spatial domain. Key features of GeneSurfer include transcriptome-wide gene filtering and gene clustering based on spatial local co-expression within transcriptomically similar cells, multi-slice 3D rendering of average expression of gene clusters, and on-the-fly Gene Ontology term annotation of co-expressed gene sets. Additionally, GeneSurfer offers multiple linked views for investigating individual genes or gene co-expression in the spatial domain at each exploration stage. Demonstrating its utility with both spatial transcriptomics and single-cell RNA sequencing data from the Allen Brain Cell Atlas, GeneSurfer effectively identifies and annotates localized transcriptome-wide co-expression, providing biological insights and facilitating hypothesis generation and validation.

The V-myb myeloblastosis viral oncogene homolog (MYB) family participate in various bioprocesses including development and abiotic stress responses. In the present study, we first report a 1R SHAQKYF-class MYB, MaMYBR30, in mulberry. Subcellular localization and sequence analysis indicated MaMYBR30 is located in the nucleus and belongs to a CCA-like subgroup with a conserved SHAQKYF motif. Expression profile analysis showed that MaMYBR30 is expressed in leaves and can be induced by drought and salt stress. The down-regulation of MaMYBR30 using virus-induced gene silence (VIGS) in mulberry and the overexpression of MaMYBR30 in Arabidopsis were induced to explore the function of MaMYBR30. The functional characterization of MaMYBR30 in vivo indicated that MaMYBR30 can positively regulate the resistance of mulberry to drought while negatively regulating the resistance of mulberry to salt stress. In addition, MaMYBR30 also affects flower development and reproductive growth, especially after exposure to salt stress. Weighted gene co-expression network analysis (WGCNA) primarily revealed the possible genes and signal pathways that are regulated by MaMYBR30. Our results also imply that complex molecular mechanisms mediated by MaMYBR30, including crosstalk of ion toxicity, phytohormone signal transduction, flowering development, and epigenetic modification, need to be further explored in the future.

Human interferon gamma (hIFN-γ) plays a pivotal role as a soluble cytokine with diverse functions in both innate and adaptive immunity. In a previous investigation, we pinpointed three critical amino acid residues, i.e., threonine (T) 27, phenylalanine (F) 29, and leucine (L) 30, on the IFN-γ structure, which are integral to the epitope recognized by anti-IFN-γ autoantibodies. It is crucial to impede the interaction between this epitope and autoantibodies for effective therapy in adult-onset immunodeficiency (AOID). However, the challenge arises from the diminished solubility of the T27AF29L30A mutant in Escherichia coli BL21(DE3). This study delves into a targeted strategy aimed at improving the soluble expression of IFN-γ T27AF29AL30A. This is achieved through the utilization of five chaperone plasmids: pG-KJE8, pKJE7, pGro7, pG-Tf2, and pTf16. These plasmids, encoding cytoplasmic chaperones, are co-expressed with the IFN-γ mutant in E. coli BL21(DE3), and we meticulously analyze the proteins in cell lysate and inclusion bodies using SDS-PAGE and Western blotting. Our findings reveal the remarkable efficacy of pG-KJE8, which houses cytoplasmic chaperones DnaK-DnaJ-GrpE and GroEL-GroES, in significantly enhancing the solubility of IFN-γ T27AF29AL30A. Importantly, this co-expression not only addresses solubility concerns but also preserves the functional dimerized structure, as confirmed by sandwich ELISA. This promising outcome signifies a significant step forward in developing biologic strategies for AOID.

Monoclonal antibodies have widespread applications in disease treatment and antigen detection. They are traditionally produced using mammalian cell expression system, which is not able to satisfy the increasing demand of these proteins at large scale. Baculovirus expression vector system (BEVS) is an attractive alternative platform for the production of biologically active monoclonal antibodies. In this chapter, we demonstrate the production of an HIV-1 broadly neutralizing antibody b12 in BEVS. The processes including transfer vector construction, recombinant baculovirus generation, and antibody production and detection are described.

Different developmental genes shape frequent dynamic inter-chromosomal contacts with rDNA units in human and Drosophila cells. In the course of differentiation, changes in these contacts occur, coupled with changes in the expression of hundreds of rDNA-contacting genes. The data suggest a possible role of nucleoli in the global regulation of gene expression. However, the mechanism behind the specificity of these inter-chromosomal contacts, which are rebuilt in every cell cycle, is not yet known. Here, we describe the strong association of rDNA-contacting genes with numerous long intergenic non-coding RNAs (lincRNAs) in HEK293T cells and in initial and differentiated K562 cells. We observed that up to 600 different lincRNAs were preferentially co-expressed with multiple overlapping sets of rDNA-contacting developmental genes, and there was a strong correlation between the genomic positions of rDNA-contacting genes and lincRNA mappings. These two findings suggest that lincRNAs might guide the corresponding developmental genes toward rDNA clusters. We conclude that the inter-chromosomal interactions of rDNA-contacting genes with nucleoli might be guided by lincRNAs, which might physically link particular genomic regions with rDNA clusters.