The Human Transcription Factors

Role and mechanism of COL3A1 in regulating the growth, metastasis, and drug sensitivity in cisplatin-resistant non-small cell lung cancer cells

Non-small cell lung cancer (NSCLC) is among the most difficult malignancies to treat. Type III collagen (COL3A1) can affect the progression and chemoresistance development of NSCLC. We herein explored the mechanism that drives COL3A1 dysregulation in NSCLC. Potential RNA-binding proteins (RBPs) and transcription factors (TFs) that could bind to COL3A1 were searched by bioinformatics. mRNA expression was detected by quantitative PCR. Protein expression was evaluated using immunoblotting and immunohistochemistry. The effects of the variables were assessed by gauging cell growth, invasiveness, migratory capacity, apoptosis, and cisplatin (DDP) sensitivity. The direct YY1/COL3A1 relationship was confirmed by ChIP and luciferase reporter experiments. Xenograft experiments were done to examine COL3A1's function in DDP efficacy. COL3A1 showed enhanced expression in DDP-resistant NSCLC. In H460/DDP and A549/DDP cells, downregulation of COL3A1 exerted inhibitory functions in cell growth, invasiveness, and migration, as well as promoting effects on cell DDP sensitivity and apoptosis. Mechanistically, ELAV-like RNA binding protein 1 (ELAVL1) enhanced the mRNA stability and expression of COL3A1, and Yin Yang 1 (YY1) promoted the transcription and expression of COL3A1. Furthermore, upregulation of COL3A1 reversed ELAVL1 inhibition- or YY1 deficiency-mediated functions in DDP-resistant NSCLC cells. Additionally, COL3A1 downregulation enhanced the anti-tumor efficacy of DDP in vivo. Our investigation demonstrates that COL3A1 upregulation, induced by both RBP ELAVL1 and TF YY1, exerts important functions in phenotypes of NSCLC cells with DDP resistance, offering an innovative opportunity in the treatment of drug-resistant NSCLC.

Cut&tag: a powerful epigenetic tool for chromatin profiling

Analysis of transcription factors and chromatin modifications at the genome-wide level provides insights into gene regulatory processes, such as transcription, cell differentiation and cellular response. Chromatin immunoprecipitation is the most popular and powerful approach for mapping chromatin, and other enzyme-tethering techniques have recently become available for living cells. Among these, Cleavage Under Targets and Tagmentation (CUT&Tag) is a relatively novel chromatin profiling method that has rapidly gained popularity in the field of epigenetics since 2019. It has also been widely adapted to map chromatin modifications and TFs in different species, illustrating the association of these chromatin epitopes with various physiological and pathological processes. Scalable single-cell CUT&Tag can be combined with distinct platforms to distinguish cellular identity, epigenetic features and even spatial chromatin profiling. In addition, CUT&Tag has been developed as a strategy for joint profiling of the epigenome, transcriptome or proteome on the same sample. In this review, we will mainly consolidate the applications of CUT&Tag and its derivatives on different platforms, give a detailed explanation of the pros and cons of this technique as well as the potential development trends and applications in the future.

TFTG: A comprehensive database for human transcription factors and their targets

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

Multi-layered knowledge graph neural network reveals pathway-level agreement of three breast cancer multi-gene assays

Multi-gene assays have been widely used to predict the recurrence risk for hormone receptor (HR)-positive breast cancer patients. However, these assays lack explanatory power regarding the underlying mechanisms of the recurrence risk. To address this limitation, we proposed a novel multi-layered knowledge graph neural network for the multi-gene assays. Our model elucidated the regulatory pathways of assay genes and utilized an attention-based graph neural network to predict recurrence risk while interpreting transcriptional subpathways relevant to risk prediction. Evaluation on three multi-gene assays-Oncotype DX, Prosigna, and EndoPredict-using SCAN-B dataset demonstrated the efficacy of our method. Through interpretation of attention weights, we found that all three assays are mainly regulated by signaling pathways driving cancer proliferation especially RTK-ERK-ETS-mediated cell proliferation for breast cancer recurrence. In addition, our analysis highlighted that the important regulatory subpathways remain consistent across different knowledgebases used for constructing the multi-level knowledge graph. Furthermore, through attention analysis, we demonstrated the biological significance and clinical relevance of these subpathways in predicting patient outcomes. The source code is available at http://biohealth.snu.ac.kr/software/ExplainableMLKGNN.

Methylation and transcriptomic profiling reveals short term and long term regulatory responses in polarized macrophages

Macrophage plasticity allows the adoption of distinct functional states in response to environmental cues. While unique transcriptomic profiles define these states, focusing solely on transcription neglects potential long-term effects. The investigation of epigenetic changes can be used to understand how temporary stimuli can result in lasting effects. Epigenetic alterations play an important role in the pathophysiology of macrophages, including their trained innate immunity, enabling faster and more efficient inflammatory responses upon subsequent encounters to the same pathogen or insult. In this study, we used a multi-omics approach to elucidate the interplay between gene expression and DNA-methylation, to explore the potential long-term effects of diverse polarizing environments on macrophage activity. We identified a common core set of genes that are differentially methylated regardless of exposure type, indicating a potential common fundamental mechanism for adaptation to various stimuli. Functional analysis revealed that processes requiring rapid responses displayed transcriptomic regulation, whereas functions critical for long-term adaptations exhibited co-regulation at both transcriptomic and epigenetic levels. Our study uncovers a novel set of genes linked to the long-term effects of macrophage polarization. This discovery underscores the potential of epigenetics in elucidating how macrophages establish long-term memory and influence health outcomes.

Evolutionary trajectory of transcription factors and selection of targets for metabolic engineering

Transcription factors (TFs) provide potentially powerful tools for plant metabolic engineering as they often control multiple genes in a metabolic pathway. However, selecting the best TF for a particular pathway has been challenging, and the selection often relies significantly on phylogenetic relationships. Here, we offer examples where evolutionary relationships have facilitated the selection of the suitable TFs, alongside situations where such relationships are misleading from the perspective of metabolic engineering. We argue that the evolutionary trajectory of a particular TF might be a better indicator than protein sequence homology alone in helping decide the best targets for plant metabolic engineering efforts. This article is part of the theme issue 'The evolution of plant metabolism'.

Overview of chromatin regulatory processes during surface ectodermal development and homeostasis

The ectoderm is the outermost of the three germ layers of the early embryo that arise during gastrulation. Once the germ layers are established, the complex interplay of cellular proliferation, differentiation, and migration results in organogenesis. The ectoderm is the progenitor of both the surface ectoderm and the neural ectoderm. Notably, the surface ectoderm develops into the epidermis and its associated appendages, nails, external exocrine glands, olfactory epithelium, and the anterior pituitary. Specification, development, and homeostasis of these organs demand a tightly orchestrated gene expression program that is often dictated by epigenetic regulation. In this review, we discuss the recent discoveries that have highlighted the importance of chromatin regulatory mechanisms mediated by transcription factors, histone and DNA modifications that aid in the development of surface ectodermal organs and maintain their homeostasis post-development.

Context transcription factors establish cooperative environments and mediate enhancer communication

Many enhancers control gene expression by assembling regulatory factor clusters, also referred to as condensates. This process is vital for facilitating enhancer communication and establishing cellular identity. However, how DNA sequence and transcription factor (TF) binding instruct the formation of high regulatory factor environments remains poorly understood. Here we developed a new approach leveraging enhancer-centric chromatin accessibility quantitative trait loci (caQTLs) to nominate regulatory factor clusters genome-wide. By analyzing TF-binding signatures within the context of caQTLs and comparing episomal versus endogenous enhancer activities, we discovered a class of regulators, 'context-only' TFs, that amplify the activity of cell type-specific caQTL-binding TFs, that is, 'context-initiator' TFs. Similar to super-enhancers, enhancers enriched for context-only TF-binding sites display high coactivator binding and sensitivity to bromodomain-inhibiting molecules. We further show that binding sites for context-only and context-initiator TFs underlie enhancer coordination, providing a mechanistic rationale for how a loose TF syntax confers regulatory specificity.

Integrated multi-omics analysis of zinc-finger proteins uncovers roles in RNA regulation

RNA interactome studies have revealed that hundreds of zinc-finger proteins (ZFPs) are candidate RNA-binding proteins (RBPs), yet their RNA substrates and functional significance remain largely uncharacterized. Here, we present a systematic multi-omics analysis of the DNA- and RNA-binding targets and regulatory roles of more than 100 ZFPs representing 37 zinc-finger families. We show that multiple ZFPs are previously unknown regulators of RNA splicing, alternative polyadenylation, stability, or translation. The examined ZFPs show widespread sequence-specific RNA binding and preferentially bind proximal to transcription start sites. Additionally, several ZFPs associate with their targets at both the DNA and RNA levels. We highlight ZNF277, a C2H2 ZFP that binds thousands of RNA targets and acts as a multi-functional RBP. We also show that ZNF473 is a DNA/RNA-associated protein that regulates the expression and splicing of cell cycle genes. Our results reveal diverse roles for ZFPs in transcriptional and post-transcriptional gene regulation.

An RNA-centric view of transcription and genome organization

Foundational models of transcriptional regulation involve the assembly of protein complexes at DNA elements associated with specific genes. These assemblies, which can include transcription factors, cofactors, RNA polymerase, and various chromatin regulators, form dynamic spatial compartments that contribute to both gene regulation and local genome architecture. This DNA-protein-centric view has been modified with recent evidence that RNA molecules have important roles to play in gene regulation and genome structure. Here, we discuss evidence that gene regulation by RNA occurs at multiple levels that include assembly of transcriptional complexes and genome compartments, feedback regulation of active genes, silencing of genes, and control of protein kinases. We thus provide an RNA-centric view of transcriptional regulation that must reside alongside the more traditional DNA-protein-centric perspectives on gene regulation and genome architecture.

Network modeling links kidney developmental programs and the cancer type-specificity of VHL mutations

Elucidating the molecular dependencies behind the cancer-type specificity of driver mutations may reveal new therapeutic opportunities. We hypothesized that developmental programs would impact the transduction of oncogenic signaling activated by a driver mutation and shape its cancer-type specificity. Therefore, we designed a computational analysis framework by combining single-cell gene expression profiles during fetal organ development, latent factor discovery, and information theory-based differential network analysis to systematically identify transcription factors that selectively respond to driver mutations under the influence of organ-specific developmental programs. After applying this approach to VHL mutations, which are highly specific to clear cell renal cell carcinoma (ccRCC), we revealed important regulators downstream of VHL mutations in ccRCC and used their activities to cluster patients with ccRCC into three subtypes. This classification revealed a more significant difference in prognosis than the previous mRNA profile-based method and was validated in an independent cohort. Moreover, we found that EP300, a key epigenetic factor maintaining the regulatory network of the subtype with the worst prognosis, can be targeted by a small inhibitor, suggesting a potential treatment option for a subset of patients with ccRCC. This work demonstrated an intimate relationship between organ development and oncogenesis from the perspective of systems biology, and the method can be generalized to study the influence of other biological processes on cancer driver mutations.

Integrated analysis of patients with bladder cancer from prospective transcription factor activity: Implications for personalized treatment approaches

Transcription factors are a specialized group of proteins that play important roles in regulating gene expression in human. These proteins control the transcription and translation of genes by binding to specific sites on DNA, thereby regulating key biological processes such as cell differentiation, proliferation, immune response, and neural development. Moreover, transcription factors are also involved in apoptosis and the pathogenesis of various diseases. By investigating transcription factors, researchers can uncover the mechanisms of gene regulation in organisms and develop more effective methods for preventing and treating human diseases. In the present study, the Virtual Inference of Protein-activity by Enriched Regulon algorithm was utilized to calculate the protein activity of transcription factors, and the metabolic-related protein activity were used for classifying bladder cancer patients into different subtype. To identify chemotherapy drugs with clinical benefits, the differences in prognosis and drug sensitivity between two distinct subtypes of bladder cancer patients were investigated. Simultaneously, the master regulators that display varying levels of transcription factor activity between two different bladder cancer subtypes were explored. Additionally, the potential transcriptional regulatory mechanisms and targets of these factors were investigated, thereby generating novel insights into bladder cancer research at the transcriptional regulation level.

ETS1 and RBPJ transcriptionally regulate METTL14 to suppress TGF-β1-induced epithelial-mesenchymal transition in human bronchial epithelial cells

Asthma is a chronic respiratory disease characterized by airway inflammation and remodeling. Epithelial-mesenchymal transition (EMT) of bronchial epithelial cells is considered to be a crucial player in asthma. Methyltransferase-like 14 (METTL14), an RNA methyltransferase, is implicated in multiple pathological processes, including EMT, cell proliferation and migration. However, the role of METTL14 in asthma remains uncertain. This research aimed to explore the biological functions of METTL14 in asthma and its underlying upstream mechanisms. METTL14 expression was down-regulated in asthmatic from three GEO datasets (GSE104468, GSE165934, and GSE74986). Consistent with this trend, METTL14 was decreased in the lung tissues of OVA-induced asthmatic mice and transforming growth factor-β1 (TGF-β1)-stimulated human bronchial epithelial cells (Beas-2B) in this study. Overexpression of METTL14 caused reduction in mesenchymal markers (FN1, N-cad, Col-1 and α-SMA) in TGF-β1-treated cells, but caused increase in epithelial markers (E-cad), thus inhibiting EMT. Also, METTL14 suppressed the proliferation and migration ability of TGF-β1-treated Beas-2B cells. Two transcription factors, ETS1 and RBPJ, could both bind to the promoter region of METTL14 and drive its expression. Elevating METTL14 expression could reversed EMT, cell proliferation and migration promoted by ETS1 or RBPJ deficiency. These results indicate that the ETS1/METTL14 and RBPJ/METTL14 transcription axes exhibit anti-EMT, anti-proliferation and anti-migration functions in TGF-β1-induced bronchial epithelial cells, implying that METTL14 may be considered an alternative candidate target for the treatment of asthma.

APOD: A biomarker associated with oxidative stress in acute rejection of kidney transplants based on multiple machine learning algorithms and animal experimental validation

BACKGROUND

Oxidative stress is an unavoidable process in kidney transplantation and is closely related to the development of acute rejection after kidney transplantation. This study aimed to investigate the biomarkers associated with oxidative stress and their potential biological functions during acute rejection of kidney transplants.

METHODS

We identified Hub genes using five machine learning algorithms based on differentially expressed genes (DEGs) in the kidney transplant acute rejection dataset GSE50058 and oxidative stress-related genes (OS) obtained from the MSigDB database, and validated them with the datasets GSE1563 and GSE9493, as well as with animal experiments; Subsequently, we explored the potential biological functions of Hub genes using single-gene GSEA enrichment analysis; The Cibersort algorithm was used to explore the altered levels of infiltration of 22 immune cells during acute rejection of renal transplantation, and a correlation analysis between Hub genes and immune cells was performed; Finally, we also explored transcription factors (TFs), miRNAs, and potential drugs that regulate Hub genes.

RESULTS

We obtained a total of 57 genes, which we defined as oxidative stress-associated differential genes (DEOSGs), after intersecting DEGs during acute rejection of kidney transplants with OSs obtained from the MSigDB database; The results of enrichment analysis revealed that DEOSGs were mainly enriched in response to oxidative stress, response to reactive oxygen species, and regulation of oxidative stress and reactive oxygen species; Subsequently, we identified one Hub gene as APOD using five machine learning algorithms, which were validated by validation sets and animal experiments; The results of single-gene GSEA enrichment analysis revealed that APOD was closely associated with the regulation of immune signaling pathways during acute rejection of kidney transplants; The Cibersort algorithm found that the infiltration levels of a total of 10 immune cells were altered in acute rejection, while APOD was found to correlate with the expression of multiple immune cells; Finally, we also identified 154 TFs, 12 miRNAs, and 12 drugs or compounds associated with APOD regulation.

CONCLUSION

In this study, APOD was identified as a biomarker associated with oxidative stress during acute rejection of kidney transplants using multiple machine learning algorithms, which provides a potential therapeutic target for mitigating oxidative stress injury and reducing the incidence of acute rejection in kidney transplantation.

Transcriptomic analysis reveals transcription factors implicated in radon-induced lung carcinogenesis

Background

Radon, a potent carcinogen, is a significant catalyst for lung cancer development. However, the molecular mechanisms triggering radon-induced lung cancer remain elusive.

Methods

Utilizing a radon exposure concentration of 20,000 Bq/m3 for 20 min/session, malignant transformation was induced in human bronchial epithelial cells (BEAS-2B).

Results

Radon-exposed cells derived from passage 25 (BEAS-2B-Rn) exhibited enhanced proliferation and increased colony formation. Analysis of differential gene expression (DEG) through transcription factors revealed 663 up-regulated and 894 down-regulated genes in radon-exposed cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed significant alterations in the malignant transformation pathway of cells, including those related to cancer and the PI3K/AKT signaling pathway. A PPI network analysis indicated a significant association of oncogenes, such as CCND1, KIT, and GATA3, with lung cancer among differentially expressed genes. In addition, the stability of the housekeeping gene was determined through RT-qPCR analysis, which also confirmed the results of transcriptome analysis.

Conclusions

The results suggest that transcription factors may play a pivotal role in conferring a survival advantage to radon-exposed cells. This is achieved by malignant transformation of human bronchial epithelial cells into lung carcinogenesis cell phenotypes.

Unveiling the link between arsenic toxicity and diabetes: an in silico exploration into the role of transcription factors

Arsenic-induced diabetes, despite being a relatively newer finding, is now a growing area of interest, owing to its multifaceted nature of development and the diversity of metabolic conditions that result from it, on top of the already complicated manifestation of arsenic toxicity. Identification and characterization of the common and differentially affected cellular metabolic pathways and their regulatory components among various arsenic and diabetes-associated complications may aid in understanding the core molecular mechanism of arsenic-induced diabetes. This study, therefore, explores the effects of arsenic on human cell lines through 14 transcriptomic datasets containing 160 individual samples using in silico tools to take a systematic, deeper look into the pathways and genes that are being altered. Among these, we especially focused on the role of transcription factors due to their diverse and multifaceted roles in biological processes, aiming to comprehensively investigate the underlying mechanism of arsenic-induced diabetes as well as associated health risks. We present a potential mechanism heavily implying the involvement of the TGF-β/SMAD3 signaling pathway leading to cell cycle alterations and the NF-κB/TNF-α, MAPK, and Ca2+ signaling pathways underlying the pathogenesis of arsenic-induced diabetes. This study also presents novel findings by suggesting potential associations of four transcription factors (NCOA3, PHF20, TFDP1, and TFDP2) with both arsenic toxicity and diabetes; five transcription factors (E2F5, ETS2, EGR1, JDP2, and TFE3) with arsenic toxicity; and one transcription factor (GATA2) with diabetes. The novel association of the transcription factors and proposed mechanism in this study may serve as a take-off point for more experimental evidence needed to understand the in vivo cellular-level diabetogenic effects of arsenic.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43188-024-00255-y.

Neuroendocrine transdifferentiation in human cancer: molecular mechanisms and therapeutic targets

Neuroendocrine transdifferentiation (NEtD), also commonly referred to as lineage plasticity, emerges as an acquired resistance mechanism to molecular targeted therapies in multiple cancer types, predominately occurs in metastatic epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer treated with EGFR tyrosine kinase inhibitors and metastatic castration-resistant prostate cancer treated with androgen receptor targeting therapies. NEtD tumors are the lethal cancer histologic subtype with unfavorable prognosis and limited treatment. A comprehensive understanding of molecular mechanism underlying targeted-induced plasticity could greatly facilitate the development of novel therapies. In the past few years, increasingly elegant studies indicated that NEtD tumors share key the convergent genomic and phenotypic characteristics irrespective of their site of origin, but also embrace distinct change and function of molecular mechanisms. In this review, we provide a comprehensive overview of the current understanding of molecular mechanism in regulating the NEtD, including genetic alterations, DNA methylation, histone modifications, dysregulated noncoding RNA, lineage-specific transcription factors regulation, and other proteomic alterations. We also provide the current management of targeted therapies in clinical and preclinical practice.

An in-silico study to determine susceptibility to cancer by evaluating the coding and non-coding non-synonymous single nucleotide variants in the SOCS3 gene

Single Nucleotide Variant (SNVs) affect gene expression as well as protein structure and activity, leading to reduced signaling capabilities and ultimately, increasing cancer risk. SOCS3 (suppressor of cytokine signaling 3), a critical tumor suppressor providing a substantial part in the feedback loop of the JAK/STAT pathway, is abnormally suppressed in various cancer. This study aims to screen non-coding and potentially deleterious coding SNVs in the SOCS3 gene. We performed six programs: PredictSNP1.0 (predicting Deleterious nsSNVs), ConSurf (analyzing sequence conservation), ModPred (analyzing SNVS in PTMs sites), I-Mutant and MUpro (to analyze SNVs effecting protein stability), and molecular docking and molecular dynamics (MD) (to assess the consequences of SOCS3 genetic variations on JAK interactions) for coding regions and three programs (UTRSite, SNP2TFBS, miRNA SNP) (to analyze SNVs effecting the gene expression) in non-coding regions, respectively. After screening 2786 SOCS3 SNVs, we found 10 SNVs, as well as 49 SNPs that change the function of non-coding areas. Out of 10 selected nsSNVs, 3 SNVs (W48R, R71C, N198S) predicted to be the most damaging by all the software programs, as well as one nsSNV (R194W) could be highly deleterious from Molecular Docking analysis combined with MD Simulations. Our findings propose a procedure for studying the structure-related consequences of SNVs on protein function in the future.Communicated by Ramaswamy H. Sarma.

The effect of the nucleolar protein ZNF385A on the ribosomal DNA copy number variation in response to Cr(VI)-induced DNA damage

Hexavalent chromium [Cr(VI)] is a widely distributed carcinogen in industrial contexts and general environmental contexts. Emerging research highlights the central role of ribosomal DNA (rDNA) in DNA Damage Responses (DDRs). However, there remains a lack of investigation into the potential dose-dependent relationship between exposure to Cr(VI) and alterations in rDNA copy number (CN), as well as the related mechanisms underlying these effects. A molecular epidemiological investigation involving 67 workers exposed to Cr(VI) and 75 unexposed controls was conducted. There was a notable increase in ZNF385A expression, variations in rDNA CN, and elevated γH2AX levels in the peripheral blood of Cr(VI)-exposed workers. Restricted cubic spline (RCS) models showed that blood Cr levels in the exposed population exhibited non-linear dose-dependent relationships with γH2AX, rDNA CN, and ZNF385A. Of considerable interest, there were robust and positive associations between ZNF385A and both γH2AX and rDNA CN. Further in vitro experiments provided concrete evidence that Cr(VI) simultaneously caused an increase in ZNF385A expression and variations in rDNA CN. ZNF385A-depleted cells showed increased sensitivity to Cr(VI)-mediated DDRs and alterations in rDNA CN. This study indicated that ZNF385A played a highly significant role in the rDNA CN variation in response to Cr(VI)-induced DNA damage.

Novel Therapeutic Target for ALI/ARDS: Forkhead Box Transcription Factors

ALI/ARDS can be a pulmonary manifestation of a systemic inflammatory response or a result of overexpression of the body's normal inflammatory response involving various effector cells, cytokines, and inflammatory mediators, which regulate the body's immune response through different signalling pathways. Forkhead box transcription factors are evolutionarily conserved transcription factors that play a crucial role in various cellular processes, such as cell cycle progression, proliferation, differentiation, migration, metabolism, and DNA damage response. Transcription factors control protein synthesis by regulating gene transcription levels, resulting in diverse biological outcomes. The Fox family plays a role in activating or inhibiting the expression of various molecules related to ALI/ARDS through phosphorylation, acetylation/deacetylation, and control of multiple signalling pathways. An in-depth analysis of the integrated Fox family's role in ALI/ARDS can aid in the development of potential diagnostic and therapeutic targets for the condition.

Sevoflurane Confers Protection Against the Malignant Phenotypes of Lung Cancer Cells via the microRNA-153-3p/HIF1α/KDM2B Axis

Sevoflurane is shown to curtail lung cancer (LC) development. Herein, this research sought to investigate the underlying mechanism of sevoflurane in regard to its repressive effects on LC. Expression levels of microRNA (miR)-153-3p, HIF1α, and KDM2B in LC tissues and cells were determined with qRT-PCR. Following sevoflurane pretreatment and/or ectopic expression and knockdown experiments, the malignant phenotypes, and levels of miR-153-3p, HIF1α, and KDM2B in LC A549 cells were detected using Transwell, scratch, EdU, CCK-8, Western blot, and qRT-PCR assays. Relationship between HIF1α and miR-153-3p was verified with a dual-luciferase reporter assay. The interaction between HIF1α and KDM2B was verified with a ChIP assay. LC tissues and cells presented low miR-153-3p expression and high HIF1α and KDM2B expression. Sevoflurane pretreatment, miR-153-3p upregulation, HIF1α downregulation, or KDM2B downregulation impeded the malignant phenotypes of A549 cells. Sevoflurane pretreatment augmented miR-153-3p expression, while miR-153-3p negatively targeted HIF1α. HIF1α bound to the KDM2B promoter to upregulate KDM2B. HIF1α or KDM2B overexpression counteracted the inhibitory effects of sevoflurane pretreatment on A549 cell malignant behaviors. Sevoflurane decreased HIF1α expression through upregulation of miR-153-3p, thereby reducing KDM2B transcription to restrict the malignant phenotypes of LC A549 cells.

HNF6 and HNF4α expression in adenocarcinomas of the liver, pancreaticobiliary tract, and gastrointestinal tract: an immunohistochemical study of 480 adenocarcinomas of the digestive system

Hepatocyte nuclear factors (HNF) 6 and 4α are master transcriptional regulators of development and maintenance of the liver and pancreaticobiliary tract in mice and humans. However, little is known about the prevalence of HNF6 and HNF4α expression in carcinomas of the hepatobiliary tract and pancreas. We aimed to reveal the diagnostic utility of HNF6 and HNF4α immunolabelling in adenocarcinomas of these organs. We investigated HNF6 and HNF4α expression by immunohistochemistry using a total of 480 adenocarcinomas of the digestive system, including 282 of the hepatobiliary tract and pancreas and 198 of the gastrointestinal tract. HNF6 expression was primarily restricted to intrahepatic cholangiocarcinomas (CCs) (63%, n=80) and gallbladder adenocarcinomas (43%, n=88), among others. Notably, small duct intrahepatic CCs almost invariably expressed HNF6 (90%, n=42), showing stark contrast to a low prevalence in large duct intrahepatic CCs (10%, n=21; p<0.0001). HNF6 expression was infrequent in extrahepatic CCs (9%, n=55) and pancreatic ductal adenocarcinomas (7%, n=58), and it was rare in adenocarcinomas of the gastrointestinal tract [oesophagus/oesophagogastric junction (EGJ) (2%, n=45), stomach (2%, n=86), duodenum (0%, n=25), and colorectum (0%, n=42)]. In contrast, HNF4α was widely expressed among adenocarcinomas of the digestive system, including intrahepatic CCs (88%), extrahepatic CCs (94%), adenocarcinomas of the gallbladder (98%), pancreas (98%), oesophagus/EGJ (96%), stomach (98%), duodenum (80%), and colorectum (100%). HNF6 was frequently expressed in and almost restricted to intrahepatic CCs of small duct type and gallbladder adenocarcinomas, while HNF4α was expressed throughout adenocarcinomas of the digestive system. HNF6 immunolabelling may be useful in distinguishing small duct intrahepatic CCs from other types of CC as well as metastatic gastrointestinal adenocarcinomas.

From driver genes to gene families: A computational analysis of oncogenic mutations and ubiquitination anomalies in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a widespread primary liver cancer with a high fatality rate. Despite several genes with oncogenic effects in HCC have been identified, many remain undiscovered. In this study, we conducted a comprehensive computational analysis to explore the involvement of genes within the same families as known driver genes in HCC. Specifically, we expanded the concept beyond single-gene mutations to encompass gene families sharing homologous structures, integrating various omics data to comprehensively understand gene abnormalities in cancer. Our analysis identified 74 domains with an enriched mutation burden, 404 domain mutation hotspots, and 233 dysregulated driver genes. We observed that specific low-frequency somatic mutations may contribute to HCC occurrence, potentially overlooked by single-gene algorithms. Furthermore, we systematically analyzed how abnormalities in the ubiquitinated proteasome system (UPS) impact HCC, finding that abnormal genes in E3, E2, DUB families, and Degron genes often result in HCC by affecting the stability of oncogenic or tumor suppressor proteins. In conclusion, expanding the exploration of driver genes to include gene families with homologous structures emerges as a promising strategy for uncovering additional oncogenic alterations in HCC.

The temporal protein signature analyses of developing human deciduous molar tooth germ

The tooth serves as an exemplary model for developmental studies, encompassing epithelial-mesenchymal transition and cell differentiation. The essential factors and pathways identified in tooth development will help understand the natural development process and the malformations of mineralized tissues such as skeleton. The time-dependent proteomic changes were investigated through the proteomics of healthy human molars during embryonic stages, ranging from the cap-to-early bell stage. A comprehensive analysis revealed 713 differentially expressed proteins (DEPs) exhibiting five distinct temporal expression patterns. Through the application of weighted gene co-expression network analysis (WGCNA), 24 potential driver proteins of tooth development were screened, including CHID1, RAP1GDS1, HAPLN3, AKAP12, WLS, GSS, DDAH1, CLSTN1, AFM, RBP1, AGO1, SET, HMGB2, HMGB1, ANP32A, SPON1, FREM1, C8B, PRPS2, FCHO2, PPP1R12A, GPALPP1, U2AF2, and RCC2. Then, the proteomics and transcriptomics expression patterns of these proteins were further compared, complemented by single-cell RNA-sequencing (scRNA-seq). In summary, this study not only offers a wealth of information regarding the molecular intricacies of human embryonic epithelial and mesenchymal cell differentiation but also serves as an invaluable resource for future mechanistic inquiries into tooth development.

A systematic comparison of computational methods for expression forecasting

Expression forecasting methods use machine learning models to predict how a cell will alter its transcriptome upon perturbation. Such methods are enticing because they promise to answer pressing questions in fields ranging from developmental genetics to cell fate engineering and because they are a fast, cheap, and accessible complement to the corresponding experiments. However, the absolute and relative accuracy of these methods is poorly characterized, limiting their informed use, their improvement, and the interpretation of their predictions. To address these issues, we created a benchmarking platform that combines a panel of 11 large-scale perturbation datasets with an expression forecasting software engine that encompasses or interfaces to a wide variety of methods. We used our platform to systematically assess methods, parameters, and sources of auxiliary data, finding that performance strongly depends on the choice of metric, and especially for simple metrics like mean squared error, it is uncommon for expression forecasting methods to out-perform simple baselines. Our platform will serve as a resource to improve methods and to identify contexts in which expression forecasting can succeed.

UVB-induced TRPS1 regulates MITF transcription activity to promote skin pigmentation

Hyperpigmented dermatoses are characterized by increased skin pigmentation caused by genetic, environmental factors and inflammation, which lasts a long time and is difficult to treat. Ultraviolet (UV), especially ultraviolet B (UVB), is the primary external factor inducing skin pigmentation. However, the specific regulatory mechanisms are not fully understood. Through analysis of GEO datasets from four UV-exposed skin cell/tissue samples, we found that TRPS1 is the only gene differentially expressed in multiple datasets (GSE22083, GSE67098 and GSE70280) and highly positively correlated with the expression of key melanogenesis genes. Consistently, we observed that TRPS1 is highly expressed in sun-exposed skin tissues compared to non-exposed skin. Additionally, the expression of TRPS1 was also significantly upregulated after UVB irradiation in isolated skin tissues and melanocytes, while knockdown of TRPS1 expression inhibited the UVB-induced melanogenesis. Further research revealed that overexpression of TRPS1 increased melanin content and tyrosinase activity in MNT1 cells, as well as upregulated the expression levels of key melanogenesis genes (MITF, TYR, TYRP1, DCT). In contrast, inhibition of TRPS1 expression showed the opposite effect. Moreover, we found that TRPS1 can bind to the promoter region of MITF, inhibiting the expression of MITF can antagonize the melanogenesis induced by TRPS1. In conclusion, UVB-induced TRPS1 promotes melanogenesis by activating the transcriptional activity of MITF.

Actin like 6A is a prognostic biomarker and associated with immune cell infiltration in cancers

PURPOSE

To investigate the role of Actin like 6 A (ACTL6A) in cancer and explore the potential mechanism of its function.

METHODS

Differential expression of ACTL6A was analyzed using Oncomine and TIMER database. Then, we downloaded data sets from TCGA database. The correlation between ACTL6A expression and survival in pan-cancer were analyzed by "survival", "survminer" R package and PrognoScan database. STRING (v 11.0) and stringAPP for Cytoscape v3.7.2 were used to predict ACTL6A associated genes. Copy number and methylation alterations of ACTL6A were analyzed using cBioPortal and GSCALite. Transcription factors were downloaded from The Human Transcription Factors Database and analyzed using "limma" R package, JASPAR and PROMO database. Correlations analysis between ACTL6A and immune cells were performed using TIMER and GEPIA database.

RESULTS

In our studies, we found that ACTL6A was widely upregulated in cancers, which might be attributed to its gene amplifications. Moreover, ACTL6A might regulated by transcription factors (TFs), including E2F1, YY1, CDX2 and HOXD10. In addition, high ACTL6A expression was associated with poor prognosis in most cancers. Meanwhile, ACTL6A was associated with the infiltration of immune cells, especially in liver hepatocellular carcinoma and brain lower grade glioma.

CONCLUSION

Amplification of ACTL6A is correlated with poor prognosis and contribute to immune cells infiltration in LIHC and LGG, which may provide immune-related therapeutic targets to guide clinical strategies.

Transcription factors containing both C2H2 and homeobox domains play different roles in Verticillium dahliae

Verticillium dahliae causes Verticillium wilt in more than 200 plant species worldwide. As a soilborne fungus, it forms melanized microsclerotia and colonizes the xylem of host plants. Our previous study revealed a subfamily of C2H2-homeobox transcription factors in V. dahliae, but their biological roles remain unknown. In this study, we systematically characterized the functions of seven C2H2-homeobox transcription factors in V. dahliae. Deletion of VdChtf3 and VdChtf6 significantly decreased the production of melanized microsclerotia, and knockout of VdChtf1 and VdChtf4 enhanced virulence. Loss of VdChtf2 and VdChtf6 increased conidium production, whereas loss of VdChtf5 and VdChtf7 did not affect growth, conidiation, microsclerotial formation, or virulence. Further research showed that VdChtf3 activated the expression of genes encoding pectic enzymes to participate in microsclerotial formation. In addition, VdChtf4 reduced the expression of VdSOD1 to disturb the scavenging of superoxide radicals but induced the expression of genes related to cell wall synthesis to maintain cell wall integrity. These findings highlight the diverse roles of different members of the C2H2-homeobox gene family in V. dahliae.

IMPORTANCE

Verticillium dahliae is a soilborne fungus that causes plant wilt and can infect a variety of economic crops and woody trees. The molecular basis of microsclerotial formation and infection by this fungus remains to be further studied. In this study, we analyzed the functions of seven C2H2-homobox transcription factors. Notably, VdChtf3 and VdChtf4 exhibited the most severe defects, affecting phenotypes associated with critical developmental stages in the V. dahliae disease cycle. Our results indicate that VdChtf3 is a potential specific regulator of microsclerotial formation, modulating the expression of pectinase-encoding genes. This finding could contribute to a better understanding of microsclerotial development in V. dahliae. Moreover, VdChtf4 was associated with cell wall integrity, reactive oxygen species (ROS) stress resistance, and increased virulence. These discoveries shed light on the biological significance of C2H2-homeobox transcription factors in V. dahliae's adaptation to the environment and infection of host plants.

Systematic discovery of DNA-binding tandem repeat proteins

Tandem repeat proteins (TRPs) are widely distributed and bind to a wide variety of ligands. DNA-binding TRPs such as zinc finger (ZNF) and transcription activator-like effector (TALE) play important roles in biology and biotechnology. In this study, we first conducted an extensive analysis of TRPs in public databases, and found that the enormous diversity of TRPs is largely unexplored. We then focused our efforts on identifying novel TRPs possessing DNA-binding capabilities. We established a protein language model for DNA-binding protein prediction (PLM-DBPPred), and predicted a large number of DNA-binding TRPs. A subset was then selected for experimental screening, leading to the identification of 11 novel DNA-binding TRPs, with six showing sequence specificity. Notably, members of the STAR (Short TALE-like Repeat proteins) family can be programmed to target specific 9 bp DNA sequences with high affinity. Leveraging this property, we generated artificial transcription factors using reprogrammed STAR proteins and achieved targeted activation of endogenous gene sets. Furthermore, the members of novel families such as MOON (Marine Organism-Originated DNA binding protein) and pTERF (prokaryotic mTERF-like protein) exhibit unique features and distinct DNA-binding characteristics, revealing interesting biological clues. Our study expands the diversity of DNA-binding TRPs, and demonstrates that a systematic approach greatly enhances the discovery of new biological insights and tools.

Chromosome-level dairy goat genome reveals the regulatory landscape of lactation

Goat milk is rich in various nutrients that are beneficial for human health. However, the genomic evolution and genetic basis underlying the nutritional value and unique flavor formation in dairy goats remain poorly understood. In the present study, we generate a chromosome-level genome assembly for dairy goats comprising 2.63 Gb with a contig N50 of 43 Mb and a scaffold N50 of 101 Mb. Genome quality comparisons revealed that the dairy goat genome has higher integrity and continuity than the published goat and sheep genomes. The identification of genes under positive selection in dairy goats highlights potential candidates to explain their high milk production. Comparative genomic analysis elucidates the adaptive evolutionary mechanisms of dairy goats such as strong disease resistance, broad adaptability, and unique milk flavor. Moreover, we demonstrate the conservation of the lactation gene network and identify new potential regulators associated with lipid metabolism. Additionally, we establish the regulatory landscape of lactation for the first time in dairy goats, revealing its unique gene regulatory characteristics. Hence, our study not only provides the first chromosome-level reference genome for dairy goat, but also offers potential research directions for dairy production and genetic improvement.

DNA sequence and chromatin differentiate sequence-specific transcription factor binding in the human malaria parasite Plasmodium falciparum

Development of the malaria parasite, Plasmodium falciparum, is regulated by a limited number of sequence-specific transcription factors (TFs). However, the mechanisms by which these TFs recognize genome-wide binding sites is largely unknown. To address TF specificity, we investigated the binding of two TF subsets that either bind CACACA or GTGCAC DNA sequence motifs and further characterized two additional ApiAP2 TFs, PfAP2-G and PfAP2-EXP, which bind unique DNA motifs (GTAC and TGCATGCA). We also interrogated the impact of DNA sequence and chromatin context on P. falciparum TF binding by integrating high-throughput in vitro and in vivo binding assays, DNA shape predictions, epigenetic post-translational modifications, and chromatin accessibility. We found that DNA sequence context minimally impacts binding site selection for paralogous CACACA-binding TFs, while chromatin accessibility, epigenetic patterns, co-factor recruitment, and dimerization correlate with differential binding. In contrast, GTGCAC-binding TFs prefer different DNA sequence context in addition to chromatin dynamics. Finally, we determined that TFs that preferentially bind divergent DNA motifs may bind overlapping genomic regions due to low-affinity binding to other sequence motifs. Our results demonstrate that TF binding site selection relies on a combination of DNA sequence and chromatin features, thereby contributing to the complexity of P. falciparum gene regulatory mechanisms.

Rapid profiling of transcription factor-cofactor interaction networks reveals principles of epigenetic regulation

Transcription factor (TF)-cofactor (COF) interactions define dynamic, cell-specific networks that govern gene expression; however, these networks are understudied due to a lack of methods for high-throughput profiling of DNA-bound TF-COF complexes. Here, we describe the Cofactor Recruitment (CoRec) method for rapid profiling of cell-specific TF-COF complexes. We define a lysine acetyltransferase (KAT)-TF network in resting and stimulated T cells. We find promiscuous recruitment of KATs for many TFs and that 35% of KAT-TF interactions are condition specific. KAT-TF interactions identify NF-κB as a primary regulator of acutely induced histone 3 lysine 27 acetylation (H3K27ac). Finally, we find that heterotypic clustering of CBP/P300-recruiting TFs is a strong predictor of total promoter H3K27ac. Our data support clustering of TF sites that broadly recruit KATs as a mechanism for widespread co-occurring histone acetylation marks. CoRec can be readily applied to different cell systems and provides a powerful approach to define TF-COF networks impacting chromatin state and gene regulation.

Role of Forkhead box F1 in the Pathobiology of Pulmonary Arterial Hypertension

Rationale

Approximately 80% of patients with non-familial pulmonary arterial hypertension (PAH) lack identifiable pathogenic genetic variants. While most genetic studies of PAH have focused on predicted loss-of-function variants, recent approaches have identified ultra-rare missense variants associated with the disease. FOXF1 encodes a highly conserved transcription factor, essential for angiogenesis and vasculogenesis in human and mouse lungs.

Objectives

We identified a rare FOXF1 missense coding variant in two unrelated probands with PAH. FOXF1 is an evolutionarily conserved transcription factor required for lung vascular development and vascular integrity. Our aims were to determine the frequency of FOXF1 variants in larger PAH cohorts compared to the general population, study FOXF1 expression in explanted lung tissue from PAH patients versus control (failed-donor) lungs, and define potential downstream targets linked to PAH development.

Methods

Three independent, international, multicenter cohorts were analyzed to evaluate the frequency of FOXF1 rare variants. Various composite prediction models assessed the deleteriousness of individual variants. Bulk RNA sequencing datasets from human explanted lung tissues were compared to failed-donor controls to determine FOXF1 expression. Bioinformatic tools identified putative FOXF1 binding targets, which were orthogonally validated using mouse ChIP-seq datasets.

Measurements and Main Results

Seven novel or ultra-rare missense coding variants were identified across three patient cohorts in different regions of the FOXF1 gene, including the DNA binding domain. FOXF1 expression was dysregulated in PAH lungs, correlating with disease severity. Histological analysis showed heterogeneous FOXF1 expression, with the lowest levels in phenotypically abnormal endothelial cells within complex vascular lesions in PAH samples. A hybrid bioinformatic approach identified FOXF1 downstream targets potentially involved in PAH pathogenesis, including BMPR2 .

Conclusions

Large genomic and transcriptomic datasets suggest that decreased FOXF1 expression or predicted dysfunction is associated with PAH.

Cell type and cell signaling innovations underlying mammalian pregnancy

How fetal and maternal cell types have co-evolved to enable mammalian placentation poses a unique evolutionary puzzle. Here, we present a multi-species atlas integrating single-cell transcriptomes from six species bracketing therian mammal diversity. We find that invasive trophoblasts share a gene-expression signature across eutherians, and evidence that endocrine decidual cells evolved stepwise from an immunomodulatory cell type retained in Tenrec with affinity to human decidua of menstruation. We recover evolutionary patterns in ligand-receptor signaling: fetal and maternal cells show a pronounced tendency towards disambiguation, but a predicted arms race dynamic between them is limited. We reconstruct cell communication networks of extinct mammalian ancestors, finding strong integration of fetal trophoblast into maternal networks. Together, our results reveal a dynamic history of cell type and signaling evolution.

Synopsis

The fetal-maternal interface is one of the most intense loci of cell-cell signaling in the human body. Invasion of cells from the fetal placenta into the uterus, and the corresponding transformation of maternal tissues called decidualization, first evolved in the stem lineage of eutherian mammals( 1 , 2 ). Single-cell studies of the human fetal-maternal interface have provided new insight into the cell type diversity and cell-cell interactions governing this chimeric organ( 3-5 ). However, the fetal-maternal interface is also one of the most rapidly evolving, and hence most diverse, characters among mammals( 6 ), and an evolutionary analysis is missing. Here, we present and compare single-cell data from the fetal-maternal interface of species bracketing key events in mammal phylogeny: a marsupial (opossum, Monodelphis domestica ), the afrotherian Tenrec ecaudatus, and four Euarchontoglires - guinea pig and mouse (Rodentia) together with recent macaque and human data (primates) ( 4 , 5 , 7 ). We infer cell type homologies, identify a gene-expression signature of eutherian invasive trophoblast conserved over 99 million years, and discover a predecidual cell in the tenrec which suggests stepwise evolution of the decidual stromal cell. We reconstruct ancestral cell signaling networks, revealing the integration of fetal cell types into the interface. Finally, we test two long-standing theoretical predictions, the disambiguation hypothesis( 8 ) and escalation hypothesis( 9 ), at transcriptome-wide scale, finding divergence between fetal and maternal signaling repertoires but arms race dynamics restricted to a small subset of ligand-receptor pairs. In so doing, we trace the co-evolutionary history of cell types and their signaling across mammalian viviparity.

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Background

Coronavirus disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused a global pandemic. Gastric cancer (GC) poses a great threat to people's health, which is a high-risk factor for COVID-19. Previous studies have found some associations between GC and COVID-19, whereas the underlying molecular mechanisms are not well understood.

Methods

We employed bioinformatics and systems biology to explore these links between GC and COVID-19. Gene expression profiles of COVID-19 (GSE196822) and GC (GSE179252) were obtained from the Gene Expression Omnibus (GEO) database. After identifying the shared differentially expressed genes (DEGs) for GC and COVID-19, functional annotation, protein-protein interaction (PPI) network, hub genes, transcriptional regulatory networks and candidate drugs were analyzed.

Results

We identified 209 shared DEGs between COVID-19 and GC. Functional analyses highlighted immune-related pathways as key players in both diseases. Ten hub genes (CDK1, KIF20A, TPX2, UBE2C, HJURP, CENPA, PLK1, MKI67, IFI6, IFIT2) were identified. The transcription factor/gene and miRNA/gene interaction networks identified 38 transcription factors (TFs) and 234 miRNAs. More importantly, we identified ten potential therapeutic agents, including ciclopirox, resveratrol, etoposide, methotrexate, trifluridine, enterolactone, troglitazone, calcitriol, dasatinib and deferoxamine, some of which have been reported to improve and treat GC and COVID-19.

Conclusion

This research offer valuable insights into the molecular interplay between COVID-19 and GC, potentially guiding future therapeutic strategies.

Merging logical models: An application in Acute Myeloid Leukemia modeling

Gene regulatory network (GRNs) models provide mechanistic understanding of the gene regulations and interactions that control various aspects of cellular behaviors. While researchers have constructed GRNs to model specific sets of gene regulations or interactions, little work has been made to integrate or merge these models into larger, more comprehensive ones that could encompass more genes, and improve the accuracy of predicting biological processes. Here, we present a workflow for merging logical GRN models, which requires sequential steps including model standardization, reproducing, merging and evaluations, and demonstrate its application in acute myeloid leukemia (AML) study. We demonstrate the feasibility and benefits of model merging by integrating two pairs of published models. Our integrated models were able to retain similar accuracy of the original publications, while increasing the coverage and explainability of the biological system. This approach highlights the integration of logical models in advancing system biology and enhancing the understanding of complex diseases.

Author summary

In our study, we tackle the challenges of integrating gene regulatory network (GRN) models to enhance our understanding of complex biological systems. GRNs are essential tools for understanding how genes regulate various cellular behaviors, but individual models often focus on specific sets of genes or interactions. We present a novel workflow that merges these individual logical GRN models into more comprehensive ones, providing a broader view of gene regulation. We applied this workflow to Acute Myeloid Leukemia (AML), a highly aggressive form of blood cancer. AML is challenging to treat due to its genetic complexity and the frequent occurrence of treatment-resistant mutations. Our integrated models retain the accuracy of the original models while offering improved coverage of the biological processes. This approach offers valuable insights into the disease's underlying mechanisms through a combination of models that describe different aspects of AML. We envision that the proposed workflow will improve predictions, generate deeper insights, and improve our understanding and treatment of complex diseases like AML.

A dynamic regulome of shoot-apical-meristem-related homeobox transcription factors modulates plant architecture in maize

BACKGROUND

The shoot apical meristem (SAM), from which all above-ground tissues of plants are derived, is critical to plant morphology and development. In maize (Zea mays), loss-of-function mutant studies have identified several SAM-related genes, most encoding homeobox transcription factors (TFs), located upstream of hierarchical networks of hundreds of genes.

RESULTS

Here, we collect 46 transcriptome and 16 translatome datasets across 62 different tissues or stages from the maize inbred line B73. We construct a dynamic regulome for 27 members of three SAM-related homeobox subfamilies (KNOX, WOX, and ZF-HD) through machine-learning models for the detection of TF targets across different tissues and stages by combining tsCUT&Tag, ATAC-seq, and expression profiling. This dynamic regulome demonstrates the distinct binding specificity and co-factors for these homeobox subfamilies, indicative of functional divergence between and within them. Furthermore, we assemble a SAM dynamic regulome, illustrating potential functional mechanisms associated with plant architecture. Lastly, we generate a wox13a mutant that provides evidence that WOX13A directly regulates Gn1 expression to modulate plant height, validating the regulome of SAM-related homeobox genes.

CONCLUSIONS

The SAM-related homeobox transcription-factor regulome presents an unprecedented opportunity to dissect the molecular mechanisms governing SAM maintenance and development, thereby advancing our understanding of maize growth and shoot architecture.

Pharmacological restriction of genomic binding sites redirects PU.1 pioneer transcription factor activity

Transcription factor (TF) DNA-binding dynamics govern cell fate and identity. However, our ability to pharmacologically control TF localization is limited. Here we leverage chemically driven binding site restriction leading to robust and DNA-sequence-specific redistribution of PU.1, a pioneer TF pertinent to many hematopoietic malignancies. Through an innovative technique, 'CLICK-on-CUT&Tag', we characterize the hierarchy of de novo PU.1 motifs, predicting occupancy in the PU.1 cistrome under binding site restriction. Temporal and single-molecule studies of binding site restriction uncover the pioneering dynamics of native PU.1 and identify the paradoxical activation of an alternate target gene set driven by PU.1 localization to second-tier binding sites. These transcriptional changes were corroborated by genetic blockade and site-specific reporter assays. Binding site restriction and subsequent PU.1 network rewiring causes primary human leukemia cells to differentiate. In summary, pharmacologically induced TF redistribution can be harnessed to govern TF localization, actuate alternate gene networks and direct cell fate.

A modular system for programming multistep activation of endogenous genes in stem cells

Although genomes encode instructions for mammalian cell differentiation with rich syntactic relationships, existing methods for genetically programming cells have modest capabilities for stepwise regulation of genes. Here, we developed a sequential genetic system that enables transcriptional activation of endogenous genes in a preprogrammed, stepwise manner. The system relies on the removal of an RNA polymerase III termination signal to induce both the transcriptional activation and the DNA endonuclease activities of a Cas9-VPR protein to effect stepwise progression through cascades of gene activation events. The efficiency of the cascading system enables a new dimension for cellular programming by allowing the manipulation of the sequential order of gene activation for directing the differentiation of human stem cells.

One-Sentence Summary

Development of a synthetic biology system for preprogrammed, stepwise activation of endogenous genes.

Dissection of core promoter syntax through single nucleotide resolution modeling of transcription initiation

How the DNA sequence of cis-regulatory elements encode transcription initiation patterns remains poorly understood. Here we introduce CLIPNET, a deep learning model trained on population-scale PRO-cap data that predicts the position and quantity of transcription initiation with single nucleotide resolution from DNA sequence more accurately than existing approaches. Interpretation of CLIPNET revealed a complex regulatory syntax consisting of DNA-protein interactions in five major positions between -200 and +50 bp relative to the transcription start site, as well as more subtle positional preferences among transcriptional activators. Transcriptional activator and core promoter motifs work non-additively to encode distinct aspects of initiation, with the former driving initiation quantity and the latter initiation position. We identified core promoter motifs that explain initiation patterns in the majority of promoters and enhancers, including DPR motifs and AT-rich TBP binding sequences in TATA-less promoters. Our results provide insights into the sequence architecture governing transcription initiation.

Discovering common pathogenetic processes between periodontitis and Alzheimer's disease by bioinformatics and system biology approach

BACKGROUND

There is increasing evidence that inflammation plays a key role in the pathophysiology of periodontitis (PT) and Alzheimer's disease (AD), but the roles of inflammation in linking PT and AD are not clear. Our aim is to analyze the potential molecular mechanisms between these two diseases using bioinformatics and systems biology approaches.

METHODS

To elucidate the link between PT and AD, we selected shared genes (SGs) with gene-disease-association scores of ≥ 0.1 from the Disease Gene Network (DisGeNET) database, followed by extracting the hub genes. Based on these genes, we constructed gene ontology (GO) enrichment analysis, pathway enrichment analysis, protein-protein interaction (PPI) networks, transcription factors (TFs)-gene networks, microRNAs (miRNAs)-gene regulatory networks, and gene-disease association analyses. Finally, the Drug Signatures database (DSigDB) was utilized to predict candidate molecular drugs related to hub genes.

RESULTS

A total of 21 common SGs between PT and AD were obtained. Cell cytokine activity, inflammatory response, and extracellular membrane were the most important enriched items in GO analysis. Interleukin-10 Signaling, LTF Danger Signal Response Pathway, and RAGE Pathway were identified as important shared pathways. IL6, IL10, IL1B, TNF, IFNG, CXCL8, CCL2, MMP9, TLR4 were identified as hub genes. Both shared pathways and hub genes are closely related to endoplasmic reticulum (ER) stress and mitochondrial dysfunction. Importantly, glutathione, simvastatin, and dexamethasone were identified as important candidate drugs for the treatment of PT and AD.

CONCLUSIONS

There is a close link between PT and AD pathogenesis, which may involve in the inflammation, ER and mitochondrial function.

Computational analysis and expression profiling of NAC transcription factor family involved in biotic stress response in Manihot esculenta

The Nascent polypeptide-Associated Complex (NAC) family is among the largest plant-specific TF families and plays an important role in plant growth, development, and stress responses. NAC TFs have been extensively studied in plants such as rice and Arabidopsis; however, their characterization, functions, evolution, and expression patterns in Manihot esculenta (cassava) under environmental stress remain largely unexplored. Here, we used bioinformatic analyses and biotic stress responses to investigate the physicochemical properties, chromosome location, phylogeny, gene structure, expression patterns, and cis-elements in promoter regions of the NAC TFs in cassava. We identified 119 M. esculenta NAC (MeNAC) gene families, unevenly distributed on 16 chromosomes. We investigated expression patterns of all identified MeNAC TFs under Xanthomonas axonopodis pv. manihotis (Xam) infection, strain CHN11, at different time points. Only 20 MeNAC TFs showed expression of significant bacterial resistance. Six MeNACs (MeNAC7, 26, 63, 65, 77, and 113) were selected for functional analysis. qRT-PCR assays revealed that MeNAC7, 26, 63, 65, 77, and 113 were induced in response to XamCHN11 infection and may participate in the molecular interaction of cassava and bacterial blight. Interestingly, MeNAC26, MeNAC63, MeNAC65, and MeNAC113 responded to XamCHN11 infection at 3 h post-inoculation. Furthermore, we identified 13 stress-related cis-elements in promoter regions of the MeNAC genes that are involved in diverse environmental stress responses. Phylogenetic analysis revealed that MeNAC genes with similar structures and motif distributions were grouped. This study provides valuable insights into the evolution, diversity, and characterization of MeNAC TFs. It lays the groundwork for a better understanding of their biological roles and molecular mechanisms in cassava.

CRISPR perfect adaptation for robust control of cellular immune and apoptotic responses

A central challenge in the quest for precise gene regulation within mammalian cells is the development of regulatory networks that can achieve perfect adaptation-where outputs consistently return to a set baseline post-stimulus. Here, we present such a system that leverages the CRISPR activation (CRISPRa) and anti-CRISPR proteins as two antithetic elements to establish perfect adaptation in mammalian cells and dynamically regulate gene expression. We demonstrate that this system can maintain stable expression levels of target genes in the face of external perturbations, thus providing a robust platform for biological applications. The versatility of our system is further showcased through its integration with endogenous regulatory mechanisms in T cells, such as the NF-κB-mediated immune response, and its ability to program apoptosis responses for precise spatial and temporal control of cellular growth and death. This study not only advances our understanding of gene regulation in mammalian cells but also opens new avenues for therapeutic intervention, particularly in diseases characterized by dysregulated gene expression.

DFF-ChIP: a method to detect and quantify complex interactions between RNA polymerase II, transcription factors, and chromatin

Recently, we introduced a chromatin immunoprecipitation (ChIP) technique utilizing the human DNA Fragmentation Factor (DFF) to digest the DNA prior to immunoprecipitation (DFF-ChIP) that provides the precise location of transcription complexes and their interactions with neighboring nucleosomes. Here we expand the technique to new targets and provide useful information concerning purification of DFF, digestion conditions, and the impact of crosslinking. DFF-ChIP analysis was performed individually for subunits of Mediator, DSIF, and NELF that that do not interact with DNA directly, but rather interact with RNA polymerase II (Pol II). We found that Mediator was associated almost exclusively with preinitiation complexes (PICs). DSIF and NELF were associated with engaged Pol II and, in addition, potential intermediates between PICs and early initiation complexes. DFF-ChIP was then used to analyze the occupancy of a tight binding transcription factor, CTCF, and a much weaker binding factor, glucocorticoid receptor (GR), with and without crosslinking. These results were compared to those from standard ChIP-Seq that employs sonication and to CUT&RUN which utilizes MNase to fragment the genomic DNA. Our findings indicate that DFF-ChIP reveals details of occupancy that are not available using other methods including information revealing pertinent protein:protein interactions.

LncRNAs Are Key Regulators of Transcription Factor-Mediated Endothelial Stress Responses

The functional role of long noncoding RNAs in the endothelium is highly diverse. Among their many functions, regulation of transcription factor activity and abundance is one of the most relevant. This review summarizes the recent progress in the research on the lncRNA-transcription factor axes and their implications for the vascular endothelium under physiological and pathological conditions. The focus is on transcription factors critical for the endothelial response to external stressors, such as hypoxia, inflammation, and shear stress, and their lncRNA interactors. These regulatory interactions will be exemplified by a selected number of lncRNAs that have been identified in the endothelium under physiological and pathological conditions that are influencing the activity or protein stability of important transcription factors. Thus, lncRNAs can add a layer of cell type-specific function to transcription factors. Understanding the interaction of lncRNAs with transcription factors will contribute to elucidating cardiovascular disease pathologies and the development of novel therapeutic approaches.

Importance of Transcript Variants in Transcriptome Analyses

RNA sequencing (RNA-Seq) has become a widely adopted technique for studying gene expression. However, conventional RNA-Seq analyses rely on gene expression (GE) values that aggregate all the transcripts produced under a single gene identifier, overlooking the complexity of transcript variants arising from different transcription start sites or alternative splicing. Transcript variants may encode proteins with diverse functional domains, or noncoding RNAs. This study explored the implications of neglecting transcript variants in RNA-Seq analyses. Among the 1334 transcription factor (TF) genes expressed in mouse embryonic stem (ES) or trophoblast stem (TS) cells, 652 were differentially expressed in TS cells based on GE values (365 upregulated and 287 downregulated, ≥absolute 2-fold changes, false discovery rate (FDR) p-value ≤ 0.05). The 365 upregulated genes expressed 883 transcript variants. Further transcript expression (TE) based analyses identified only 174 (<20%) of the 883 transcripts to be upregulated. The remaining 709 transcripts were either downregulated or showed no significant changes. Meanwhile, the 287 downregulated genes expressed 856 transcript variants and only 153 (<20%) of the 856 transcripts were downregulated. The other 703 transcripts were either upregulated or showed no significant change. Additionally, the 682 insignificant TF genes (GE values < absolute 2-fold changes and/or FDR p-values > 0.05) between ES and TS cells expressed 2215 transcript variants. These included 477 (>21%) differentially expressed transcripts (276 upregulated and 201 downregulated, ≥absolute 2-fold changes, FDR p-value ≤ 0.05). Hence, GE based RNA-Seq analyses do not represent accurate expression levels due to divergent transcripts expression from the same gene. Our findings show that by including transcript variants in RNA-Seq analyses, we can generate a precise understanding of a gene's functional and regulatory landscape; ignoring the variants may result in an erroneous interpretation.

Improving prediction performance of general protein language model by domain-adaptive pretraining on DNA-binding protein

DNA-protein interactions exert the fundamental structure of many pivotal biological processes, such as DNA replication, transcription, and gene regulation. However, accurate and efficient computational methods for identifying these interactions are still lacking. In this study, we propose a method ESM-DBP through refining the DNA-binding protein sequence repertory and domain-adaptive pretraining based the general protein language model. Our method considers the lacking exploration of general language model for DNA-binding protein domain-specific knowledge, so we screen out 170,264 DNA-binding protein sequences to construct the domain-adaptive language model. Experimental results on four downstream tasks show that ESM-DBP provides a better feature representation of DNA-binding protein compared to the original language model, resulting in improved prediction performance and outperforming the state-of-the-art methods. Moreover, ESM-DBP can still perform well even for those sequences with only a few homologous sequences. ChIP-seq on two predicted cases further support the validity of the proposed method.

SOX7 inhibits the malignant progression of bladder cancer via the DNMT3B/CYGB axis

Bladder cancer (BCa) stands out as a highly prevalent malignant tumor affecting the urinary system. The Sex determining region Y-box protein family is recognized for its crucial role in BCa progression. However, the effect of Sex determining region Y-box 7 (SOX7) on BCa progression has not been fully elucidated. Herein, RNA-sequencing, western blot (WB), immunohistochemistry (IHC), immunofluorescence (IF) and tissue microarray were utilized to assess SOX7 expression in vitro and in vivo. Additionally, SOX7 expression, prognosis, and SOX7 + cytoglobin (CYGB) score were analyzed using R software. In vitro and vivo experiments were performed with BCa cell lines to validate the effect of SOX7 knockdown and overexpression on the malignant progression of BCa. The results showed that SOX7 exhibits low expression in BCa. It functions in diverse capacities, inhibiting the proliferative, migratory, and invasive capabilities of BCa. In addition, the experimental database demonstrated that SOX7 binds to the promoter of DNA methyltransferase 3 beta (DNMT3B), leading to the transcriptional inhibition of DNMT3B. This subsequently results in a reduced methylation of CYGB promoter, ultimately inhibiting the tumor progression of BCa. SOX7 + CYGB scores were significantly linked to patient prognosis. In conclusion, SOX7 inhibits the malignant progression of BCa via the DNMT3B/CYGB axis. Additionally, the SOX7 + CYGB score is capable of predicting the prognostic outcomes of BCa patients. Therefore, SOX7 and CYGB may play an important role in the progression of bladder cancer, and they can be used as prognostic markers of bladder cancer patients.

Strategies and bibliometric analysis of legumes biofortification to address malnutrition

MAIN CONCLUSION

Biofortification of legumes using diverse techniques such as plant breeding, agronomic practices, genetic modification, and nano-technological approaches presents a sustainable strategy to address micronutrient deficiencies of underprivileged populations. The widespread issue of chronic malnutrition, commonly referred to as "hidden hunger," arises from the consumption of poor-quality food, leading to various health and cognitive impairments. Biofortified food crops have been a sustainable solution to address micronutrient deficiencies. This review highlights multiple biofortification techniques, such as plant breeding, agronomic practices, genetic modification, and nano-technological approaches, aimed at enhancing the nutrient content of commonly consumed crops. Emphasizing the biofortification of legumes, this review employs bibliometric analysis to examine research trends from 2000 to 2023. It identifies key authors, influential journals, contributing countries, publication trends, and prevalent keywords in this field. The review highlights the progress in developing biofortified crops and their potential to improve global nutrition and help underprivileged populations.

Transcriptome analysis and genome-wide identification of the dehydration-responsive element binding gene family in jackfruit under cold stress

BACKGROUND

Jackfruit (Artocarpus heterophyllus Lam.) is the world's largest and heaviest fruit and adapts to hot, humid tropical climates. Low-temperature injury in winter is a primary abiotic stress, which affects jackfruit growth and development. Therefore, breeding cold-resistant varieties and identifying the vital genes in the process of cold resistance are essential. The dehydration-responsive element binding (DREB) gene family is among the subfamily of the APETALA2/ethylene response factor transcription factor family and is significant in plant abiotic stress responses.

METHODS

In this study, a comparative analysis of the cold resistance property of 'GuangXi' ('GX') and 'Thailand' ('THA') jackfruit strains with different cold resistance characteristics was performed through chlorophyll fluorescence and transcriptome sequencing.

RESULTS

We found that differentially expressed genes (DEGs) are significantly enriched in the metabolic processes. Here, 93 DREB genes were identified in the jackfruit genome, and phylogenetic analysis was used to classify them into seven groups. Gene structure, conserved motifs, chromosomal location, and homologous relationships were used to analyze the structural characteristics of the DREB family. Transcriptomics indicated that most of the AhDREB genes exhibited down-regulated expression in 'THA.' The DEGs AhDREB12, AhDREB21, AhDREB29, and AhDREB34 were selected for quantitative real-time PCR, and the results showed that these genes also had down-regulated expression in 'THA.'

CONCLUSIONS

The above results suggest the significance of the DREB family in improving the cold resistance property of 'GX.'