TRANSFAC: a database on transcription factors and their DNA binding sites

A genome-wide association study identified PTPN2 as a population-specific susceptibility gene locus for primary biliary cholangitis

BACKGROUND AND AIMS

Previous genome-wide association studies (GWAS) have indicated the involvement of shared (population-nonspecific) and nonshared (population-specific) susceptibility genes in the pathogenesis of primary biliary cholangitis (PBC) among European and East-Asian populations. Although a meta-analysis of these distinct populations has recently identified more than 20 novel PBC susceptibility loci, analyses of population-specific genetic architecture are still needed for a more comprehensive search for genetic factors in PBC.

APPROACH AND RESULTS

Protein tyrosine phosphatase nonreceptor type 2 ( PTPN2) was identified as a novel PBC susceptibility gene locus through GWAS and subsequent genome-wide meta-analysis involving 2181 cases and 2699 controls from the Japanese population (GWAS-lead variant: rs8098858, p = 2.6 × 10 -8 ). In silico and in vitro functional analyses indicated that the risk allele of rs2292758, which is a primary functional variant, decreases PTPN2 expression by disrupting Sp1 binding to the PTPN2 promoter in T follicular helper cells and plasmacytoid dendritic cells. Infiltration of PTPN2-positive T-cells and plasmacytoid dendritic cells was confirmed in the portal area of the PBC liver by immunohistochemistry. Furthermore, transcriptomic analysis of PBC-liver samples indicated the presence of a compromised negative feedback loop in vivo between PTPN2 and IFNG in patients carrying the risk allele of rs2292758.

CONCLUSIONS

PTPN2 , a novel susceptibility gene for PBC in the Japanese population, may be involved in the pathogenesis of PBC through an insufficient negative feedback loop caused by the risk allele of rs2292758 in IFN-γ signaling. This suggests that PTPN2 could be a potential molecular target for PBC treatment.

Enrichment of Cis-Acting Regulatory Elements in Differentially Methylated Regions Following Lipopolysaccharide Treatment of Bovine Endometrial Epithelial Cells

Endometritis is an inflammatory disease that negatively influences fertility and is common in milk-producing cows. An in vitro model for bovine endometrial inflammation was used to identify enrichment of cis-acting regulatory elements in differentially methylated regions (DMRs) in the genome of in vitro-cultured primary bovine endometrial epithelial cells (bEECs) before and after treatment with lipopolysaccharide (LPS) from E. coli, a key player in the development of endometritis. The enriched regulatory elements contain binding sites for transcription factors with established roles in inflammation and hypoxia including NFKB and Hif-1α. We further showed co-localization of certain enriched cis-acting regulatory motifs including ARNT, Hif-1α, and NRF1. Our results show an intriguing interplay between increased mRNA levels in LPS-treated bEECs of the mRNAs encoding the key transcription factors such as AHR, EGR2, and STAT1, whose binding sites were enriched in the DMRs. Our results demonstrate an extraordinary cis-regulatory complexity in these DMRs having binding sites for both inflammatory and hypoxia-dependent transcription factors. Obtained data using this in vitro model for bacterial-induced endometrial inflammation have provided valuable information regarding key transcription factors relevant for clinical endometritis in both cattle and humans.

Circadian organization of clock factors, antioxidant defenses, and cognitive genes expression, is lost in the cerebellum of aged rats. Possible targets of therapeutic strategies for the treatment of age-related cerebellar disorders

Aging is a major risk factor for cognitive deficits, impaired locomotion, and gait disorders. Although oxidative stress and circadian disruption are involved in both normal aging and the pathogenesis of age-associated diseases, just a very few studies explore the consequences of aging on circadian rhythms in the cerebellum. Here, we investigated age-dependent changes in the circadian organization of the molecular clock, antioxidant defenses and synaptic plasticity-related factors, in the rat cerebellum, and discussed the impact of that altered temporal organization on the cognitive function of this brain area. Particularly, we examined the circadian patterns of Brain and muscle ARNT-like 1 (BMAL1) protein levels, Glutathione peroxidase 4 (GPx4) gene expression, GPx and Catalase (CAT) enzymes activity, reduced glutathione (GSH) levels, and the Brain-derived neurotrophic factor (Bdnf) and its Tyrosine kinase receptor B (TrkB) circadian expression. Endogenously-driven circadian rhythms of BMAL1, GPx4, CAT, GSH, and Bdnf/TrkB factors, were observed in the young rat cerebellum. The rhythms' acrophases show a circadian organization that might be crucial for the daily cerebellar-dependent cognitive functions. Notably, aging disrupted circadian rhythms and the temporal organization of BMAL1, antioxidant defenses, and cognitive Bdnf/TrkB gene expression. Increased oxidative stress and disruption of clock-controlled rhythms during aging, might precede and cause the loss of circadian organization in the aged cerebellum. We expect our results highlight circadian rhythms of the studied factors as new targets for the treatment of age-dependent cerebellar disorders.

Multi-omic profiling of pathogen-stimulated primary immune cells

We performed long-read transcriptome and proteome profiling of pathogen-stimulated peripheral blood mononuclear cells (PBMCs) from healthy donors to discover new transcript and protein isoforms expressed during immune responses to diverse pathogens. Long-read transcriptome profiling reveals novel sequences and isoform switching induced upon pathogen stimulation, including transcripts that are difficult to detect using traditional short-read sequencing. Widespread loss of intron retention occurs as a common result of all pathogen stimulations. We highlight novel transcripts of NFKB1 and CASP1 that may indicate novel immunological mechanisms. RNA expression differences did not result in differences in the amounts of secreted proteins. Clustering analysis of secreted proteins revealed a correlation between chemokine (receptor) expression on the RNA and protein levels in C. albicans- and poly(I:C)-stimulated PBMCs. Isoform aware long-read sequencing of pathogen-stimulated immune cells highlights the potential of these methods to identify novel transcripts, revealing a more complex transcriptome landscape than previously appreciated.

Integrated Gene Expression Data-Driven Identification of Molecular Signatures, Prognostic Biomarkers, and Drug Targets for Glioblastoma

Glioblastoma (GBM) is a highly prevalent and deadly brain tumor with high mortality rates, especially among adults. Despite extensive research, the underlying mechanisms driving its progression remain poorly understood. Computational analysis offers a powerful approach to explore potential prognostic biomarkers, drug targets, and therapeutic agents for GBM. In this study, we utilized three gene expression datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) associated with GBM progression. Our goal was to uncover key molecular players implicated in GBM pathogenesis and potential avenues for targeted therapy. Analysis of the gene expression datasets revealed a total of 78 common DEGs that are potentially involved in GBM progression. Through further investigation, we identified nine hub DEGs that are highly interconnected in protein-protein interaction (PPI) networks, indicating their central role in GBM biology. Gene Ontology (GO) and pathway enrichment analyses provided insights into the biological processes and immunological pathways influenced by these DEGs. Among the nine identified DEGs, survival analysis demonstrated that increased expression of GMFG correlated with decreased patient survival rates in GBM, suggesting its potential as a prognostic biomarker and preventive target for GBM. Furthermore, molecular docking and ADMET analysis identified two compounds from the NIH clinical collection that showed promising interactions with the GMFG protein. Besides, a 100 nanosecond molecular dynamics (MD) simulation evaluated the conformational changes and the binding strength. Our study highlights the potential of GMFG as both a prognostic biomarker and a therapeutic target for GBM. The identification of GMFG and its associated pathways provides valuable insights into the molecular mechanisms driving GBM progression. Moreover, the identification of candidate compounds with potential interactions with GMFG offers exciting possibilities for targeted therapy development. However, further laboratory experiments are required to validate the role of GMFG in GBM pathogenesis and to assess the efficacy of potential therapeutic agents targeting this molecule.

Identifying cell type-specific transcription factor-mediated activity immune modules reveal implications for immunotherapy and molecular classification of pan-cancer

Systematic investigation of tumor-infiltrating immune (TII) cells is important to the development of immunotherapies, and the clinical response prediction in cancers. There exists complex transcriptional regulation within TII cells, and different immune cell types display specific regulation patterns. To dissect transcriptional regulation in TII cells, we first integrated the gene expression profiles from single-cell datasets, and proposed a computational pipeline to identify TII cell type-specific transcription factor (TF) mediated activity immune modules (TF-AIMs). Our analysis revealed key TFs, such as BACH2 and NFKB1 play important roles in B and NK cells, respectively. We also found some of these TF-AIMs may contribute to tumor pathogenesis. Based on TII cell type-specific TF-AIMs, we identified eight CD8+ T cell subtypes. In particular, we found the PD1 + CD8+ T cell subset and its specific TF-AIMs associated with immunotherapy response. Furthermore, the TII cell type-specific TF-AIMs displayed the potential to be used as predictive markers for immunotherapy response of cancer patients. At the pan-cancer level, we also identified and characterized six molecular subtypes across 9680 samples based on the activation status of TII cell type-specific TF-AIMs. Finally, we constructed a user-friendly web interface CellTF-AIMs (http://bio-bigdata.hrbmu.edu.cn/CellTF-AIMs/) for exploring transcriptional regulatory pattern in various TII cell types. Our study provides valuable implications and a rich resource for understanding the mechanisms involved in cancer microenvironment and immunotherapy.

Variation of the 3'RR1 HS1.2 Enhancer and Its Genomic Context

In humans, the HS1.2 enhancer in the Ig heavy-chain locus is modular, with length polymorphism. Previous studies have shown the following features for this variation: (i) strong population structuring; (ii) association with autoimmune diseases; and (iii) association with developmental changes in Ig expression. The HS1.2 region could then be considered as a contributor to inter-individual diversity in humoral response in adaptive immunity. We experimentally determined the HS1.2-length class genotype in 72 of the 1000 Genomes CEU cell lines and assigned the HS1.2 alleles to haplotypes defined by 18 landmark SNPs. We also sequenced the variable portion and ~200 bp of the flanking DNA of 34 HS1.2 alleles. Furthermore, we computationally explored the ability of different allelic arrangements to bind transcription factors. Non-random association between HS1.2 and Gm allotypes in the European population clearly emerged. We show a wealth of variation in the modular composition of HS1.2, with five SNPs further contributing to diversity. Longer alleles offer more potential sites for binding but, for same-length alleles, SNP variation creates/destroys potential binding sites. Altogether, the arrangements of modules and SNP alleles both inside and outside HS1.2 denote an organization of diversity far from randomness. In the context of the strong divergence of human populations for this genomic region and the reported disease associations, our results suggest that selective forces shaped the pattern of its diversity.

Deciphering the similarities and disparities of molecular mechanisms behind respiratory epithelium response to HCoV-229E and SARS-CoV-2 and drug repurposing, a systems biology approach

PURPOSE

Identifying the molecular mechanisms behind SARS-CoV-2 disparities and similarities will help find new treatments. The present study determines networks' shared and non-shared (specific) crucial elements in response to HCoV-229E and SARS-CoV-2 viruses to recommend candidate medications.

METHODS

We retrieved the omics data on respiratory cells infected with HCoV-229E and SARS-CoV-2, constructed PPIN and GRN, and detected clusters and motifs. Using a drug-gene interaction network, we determined the similarities and disparities of mechanisms behind their host response and drug-repurposed.

RESULTS

CXCL1, KLHL21, SMAD3, HIF1A, and STAT1 were the shared DEGs between both viruses' protein-protein interaction network (PPIN) and gene regulatory network (GRN). The NPM1 was a specific critical node for HCoV-229E and was a Hub-Bottleneck shared between PPI and GRN in HCoV-229E. The HLA-F, ADCY5, TRIM14, RPF1, and FGA were the seed proteins in subnetworks of the SARS-CoV-2 PPI network, and HSPA1A and RPL26 proteins were the seed in subnetworks of the PPI network of HCOV-229E. TRIM14, STAT2, and HLA-F played the same role for SARS-CoV-2. Top enriched KEGG pathways included cell cycle and proteasome in HCoV-229E and RIG-I-like receptor, Chemokine, Cytokine-cytokine, NOD-like receptor, and TNF signaling pathways in SARS-CoV-2. We suggest some candidate medications for COVID-19 patient lungs, including Noscapine, Isoetharine mesylate, Cycloserine, Ethamsylate, Cetylpyridinium, Tretinoin, Ixazomib, Vorinostat, Venetoclax, Vorinostat, Ixazomib, Venetoclax, and epoetin alfa for further in-vitro and in-vivo investigations.

CONCLUSION

We suggested CXCL1, KLHL21, SMAD3, HIF1A, and STAT1, ADCY5, TRIM14, RPF1, and FGA, STAT2, and HLA-F as critical genes and Cetylpyridinium, Cycloserine, Noscapine, Ethamsylate, Epoetin alfa, Isoetharine mesylate, Ribavirin, and Tretinoin drugs to study further their importance in treating COVID-19 lung complications.

Integrative experimental validation of concomitant miRNAs and transcription factors with differentially expressed genes in acute myocardial infarction

Identification of concomitant miRNAs and transcription factors (TFs) with differential expression (DEGs) in MI is crucial for understanding holistic gene regulation, identifying key regulators, and precision in biomarker and therapeutic target discovery. We performed a comprehensive analysis using Affymetrix microarray data, advanced bioinformatic tools, and experimental validation to explore potential biomarkers associated with human pathology. The search strategy includes the identification of the GSE83500 dataset, comprising gene expression profiles from aortic wall punch biopsies of MI and non-MI patients, which were used in the present study. The analysis identified nine distinct genes exhibiting DEGs within the realm of MI. miRNA-gene/TF and TF-gene/miRNA regulatory relations were mapped to retrieve interacting hub genes to acquire an MI miRNA-TF co-regulatory network. Furthermore, an animal model of I/R-induced MI confirmed the involved gene based on quantitative RT-PCR and Western blot analysis. The consequences of the bioinformatic tool substantiate the inference regarding the presence of three key hub genes (UBE2N, TMEM106B, and CXADR), a central miRNA (hsa-miR-124-3p), and sixteen TFs. Animal studies support the involvement of predicted genes in the I/R-induced myocardial infarction assessed by RT-PCR and Western blotting. Thus, the final consequences suggest the involvement of promising molecular pathways regulated by TF (p53/NF-κB1), miRNA (hsa-miR-124-3p), and hub gene (UBE2N), which may play a key role in the pathogenesis of MI.

Discovering DNA shape motifs with multiple DNA shape features: generalization, methods, and validation

DNA motifs are crucial patterns in gene regulation. DNA-binding proteins (DBPs), including transcription factors, can bind to specific DNA motifs to regulate gene expression and other cellular activities. Past studies suggest that DNA shape features could be subtly involved in DNA-DBP interactions. Therefore, the shape motif annotations based on intrinsic DNA topology can deepen the understanding of DNA-DBP binding. Nevertheless, high-throughput tools for DNA shape motif discovery that incorporate multiple features altogether remain insufficient. To address it, we propose a series of methods to discover non-redundant DNA shape motifs with the generalization to multiple motifs in multiple shape features. Specifically, an existing Gibbs sampling method is generalized to multiple DNA motif discovery with multiple shape features. Meanwhile, an expectation-maximization (EM) method and a hybrid method coupling EM with Gibbs sampling are proposed and developed with promising performance, convergence capability, and efficiency. The discovered DNA shape motif instances reveal insights into low-signal ChIP-seq peak summits, complementing the existing sequence motif discovery works. Additionally, our modelling captures the potential interplays across multiple DNA shape features. We provide a valuable platform of tools for DNA shape motif discovery. An R package is built for open accessibility and long-lasting impact: https://zenodo.org/doi/10.5281/zenodo.10558980.

KLF6 activates Sp1-mediated prolidase transcription during TGF-β1 signaling

Prolidase (PEPD) is the only hydrolase that cleaves the dipeptides containing C-terminal proline or hydroxyproline-the rate-limiting step in collagen biosynthesis. However, the molecular regulation of prolidase expression remains largely unknown. In this study, we have identified overlapping binding sites for the transcription factors Krüppel-like factor 6 (KLF6) and Specificity protein 1 (Sp1) in the PEPD promoter and demonstrate that KLF6/Sp1 transcriptionally regulate prolidase expression. By cloning the PEPD promoter into a luciferase reporter and through site-directed deletion, we pinpointed the minimal sequences required for KLF6 and Sp1-mediated PEPD promoter-driven transcription. Interestingly, Sp1 inhibition abrogated KLF6-mediated PEPD promoter activity, suggesting that Sp1 is required for the basal expression of prolidase. We further studied the regulation of PEPD by KLF6 and Sp1 during transforming growth factor β1 (TGF-β1) signaling, since both KLF6 and Sp1 are key players in TGF-β1 mediated collagen biosynthesis. Mouse and human fibroblasts exposed to TGF-β1 resulted in the induction of PEPD transcription and prolidase expression. Inhibition of TGF-β1 signaling abrogated PEPD promoter-driven transcriptional activity of KLF6 and Sp1. Knock-down of KLF6 as well as Sp1 inhibition also reduced prolidase expression. Chromatin immunoprecipitation assay supported direct binding of KLF6 and Sp1 to the PEPD promoter and this binding was enriched by TGF-β1 treatment. Finally, immunofluorescence studies showed that KLF6 co-operates with Sp1 in the nucleus to activate prolidase expression and enhance collagen biosynthesis. Collectively, our results identify functional elements of the PEPD promoter for KLF6 and Sp1-mediated transcriptional activation and describe the molecular mechanism of prolidase expression.

Harnessing genetic engineering to drive economic bioproduct production in algae

Our reliance on agriculture for sustenance, healthcare, and resources has been essential since the dawn of civilization. However, traditional agricultural practices are no longer adequate to meet the demands of a burgeoning population amidst climate-driven agricultural challenges. Microalgae emerge as a beacon of hope, offering a sustainable and renewable source of food, animal feed, and energy. Their rapid growth rates, adaptability to non-arable land and non-potable water, and diverse bioproduct range, encompassing biofuels and nutraceuticals, position them as a cornerstone of future resource management. Furthermore, microalgae's ability to capture carbon aligns with environmental conservation goals. While microalgae offers significant benefits, obstacles in cost-effective biomass production persist, which curtails broader application. This review examines microalgae compared to other host platforms, highlighting current innovative approaches aimed at overcoming existing barriers. These approaches include a range of techniques, from gene editing, synthetic promoters, and mutagenesis to selective breeding and metabolic engineering through transcription factors.

rs10924104 in the expression enhancer motif of CD58 confers susceptibility to human autoimmune diseases

CD58 plays roles in cell adhesion and co-stimulation with antigen presentation from major histocompatibility complex class II on antigen-presenting cells to T-cell antigen receptors on naïve T cells. CD58 reportedly contributes to the development of various human autoimmune diseases. Recently, genome-wide association studies (GWASs) identified CD58 as a susceptibility locus for autoimmune diseases such as systemic lupus erythematosus (SLE), multiple sclerosis (MS), and primary biliary cholangitis (PBC). However, the primary functional variant and molecular mechanisms of susceptibility to autoimmune diseases in the CD58 locus were not clarified. Here, rs10924104, located in the ZNF35-binding motif within the gene expression regulatory motif, was identified as the primary functional variant for SLE, MS, and PBC among genetic variants showing stronger linkage disequilibrium (LD) with GWAS-lead variants in the CD58 locus. Expression-quantitative trait locus (e-QTL) data for each distinct blood cell type and in vitro functional analysis using the CRISPR/Cas9 system corroborated the functional role of rs10924104 in the upregulation of CD58 transcription by the disease-risk allele. Additionally, the strength of disease susceptibility observed in the CD58 locus could be accounted for by the strength of LD between rs10924104 and each GWAS-lead variant. In conclusion, the present study demonstrated for the first time the existence of a shared autoimmune disease-related primary functional variant (i.e., rs10924104) that regulates the expression of CD58. Clarifying the molecular mechanism of disease susceptibility derived from such a shared genetic background is important for understanding human autoimmune diseases and human immunology.

Computational Inference of Gene Regulatory Network Using Genome-wide ChIP-X Data

Gene regulatory network is the architecture of transcription factors (TFs) and their gene targets, which help in controlling their expression as required by a phenotype during various environmental perturbations. Inferring the regulatory network from the high-throughput data needs an algorithmic approach involving statistical analysis. There are several interaction databases such as JASPAR and SwissRegulon that provide information for TFs-targets pair interaction, which are estimated based on experimental and prediction procedures. These repositories are majorly used for predicting the complex structure of GRNs either with or without gene expression data. Here we described and discussed the step-wise procedures to extract the interaction data for a desired set of target-TFs from the JASPAR database, and used that information to infer the network by using the igraph library. Further, we also mentioned the important parameters for analyzing the different properties of the network. The described procedure will be helpful in discerning the GRN based on the set of TF-gene pairs.

Identification of Key Osteoporosis Genes Through Comparative Analysis of Men's and Women's Osteoblast Transcriptomes

Osteoporosis disproportionately affects older women, yet gender differences in human osteoblasts remain unexplored. Identifying mechanisms and biomarkers of osteoporosis will enable the development of preventative and therapeutic approaches. Transcriptome data of 187 osteoblast samples from men and women were compared. Differentially expressed genes (DEGs) were identified, and weighted gene co-expression network analysis (WGCNA) was used to discover co-expressed modules. Enrichment analysis was performed to annotate DEGs. Preservation analysis determined whether modules and pathways were similar between genders. Blood methylation, transcriptome data, mouse phenotype data, and drug treatment data were utilized to identify key osteoporosis genes. We identified 1460 DEGs enriched in immune response, neurogenesis, and GWAS osteoporosis-related genes. WGCNA uncovered 8 modules associated with immune response, development, collagen metabolism, mitochondrion, and amino acid synthesis. Preservation analysis indicated modules and pathways were generally similar between genders. Incorporating GWAS and mouse phenotype data revealed 9 key genes, including GMDS, SMOC2, SASH1, MMP2, AHCYL1, ARRDC2, IGHMBP2, ATP6V1A, and CTSK. These genes were differentially methylated in patient blood and differentiated high and low bone mineral density patients in pre- and postmenopausal women. Denosumab treatment in postmenopausal women down-regulated 6 key genes, up-regulated T cell proportions, and down-regulated fibroblast proportion. qRT-PCR was used to confirm the genes in postmenopausal women. We identified 9 key osteoporosis genes by comparing the transcriptome of osteoblasts in women and men. Our findings' clinical implications were confirmed by multi-omics data and qRT-PCR, and our study provides novel biomarkers and therapeutic targets for osteoporosis diagnosis and treatment.

Towards a comprehensive regulatory map of Mammalian Genomes

Genome mapping studies have generated a nearly complete collection of genes for the human genome, but we still lack an equivalently vetted inventory of human regulatory sequences. Cis-regulatory modules (CRMs) play important roles in controlling when, where, and how much a gene is expressed. We developed a training data-free CRM-prediction algorithm, the Mammalian Regulatory MOdule Detector (MrMOD) for accurate CRM prediction in mammalian genomes. MrMOD provides genome position-fixed CRM models similar to the fixed gene models for the mouse and human genomes using only genomic sequences as the inputs with one adjustable parameter - the significance p-value. Importantly, MrMOD predicts a comprehensive set of high-resolution CRMs in the mouse and human genomes including all types of regulatory modules not limited to any tissue, cell type, developmental stage, or condition. We computationally validated MrMOD predictions used a compendium of 21 orthogonal experimental data sets including thousands of experimentally defined CRMs and millions of putative regulatory elements derived from hundreds of different tissues, cell types, and stimulus conditions obtained from multiple databases. In ovo transgenic reporter assay demonstrates the power of our prediction in guiding experimental design. We analyzed CRMs located in the chromosome 17 using unsupervised machine learning and identified groups of CRMs with multiple lines of evidence supporting their functionality, linking CRMs with upstream binding transcription factors and downstream target genes. Our work provides a comprehensive base pair resolution annotation of the functional regulatory elements and non-functional regions in the mammalian genomes.

Spatially differential regulation of ATF2 phosphorylation contributes to warning coloration of gregarious locusts

Warning coloration are common defense strategies used by animals to deter predators. Pestilential gregarious locusts exhibit a notable black-brown pattern as a form of warning coloration. However, the mechanisms regulating this distinctive pattern remain largely unknown. Here, we revealed that the black and brown integuments of locusts are governed by varying amounts of β-carotene and β-carotene-binding protein (βCBP) complexes. βCBP expression is regulated by the bZIP transcription factor activation transcription factor 2 (ATF2), which is activated by protein kinase C alpha in response to crowding. Specifically, ATF2 is phosphorylated at Ser327 and translocates to the nucleus, where it binds to the βCBP promoter and stimulates overexpression. Differential phosphorylation of ATF2 leads to the divergent black and brown coloration in gregarious locusts. The accumulation of red pigments vital for creating the brown sternum depends on βCBP overexpression. The spatial variation in ATF2 phosphorylation enables locusts to rapidly adapt to changing environment for aposematism.

Identification of Renal Transplantation Rejection Biomarkers in Blood Using the Systems Biology Approach

Background

Renal transplantation plays an essential role in the quality of life of patients with end-stage renal disease. At least 12% of the renal patients receiving transplantations show graft rejection. One of the methods used to diagnose renal transplantation rejection is renal allograft biopsy. This procedure is associated with some risks such as bleeding and arteriovenous fistula formation. In this study, we applied a bioinformatics approach to identify serum markers for graft rejection in patients receiving a renal transplantation.

Methods

Transcriptomic data were first retrieved from the blood of renal transplantation rejection patients using the GEO database. The data were then used to construct the protein-protein interaction and gene regulatory networks using Cytoscape software. Next, network analysis was performed to identify hub-bottlenecks, and key blood markers involved in renal graft rejection. Lastly, the gene ontology and functional pathways related to hub-bottlenecks were detected using PANTHER and DAVID servers.

Results

In PPIN and GRN, SYNCRIP, SQSTM1, GRAMD1A, FAM104A, ND2, TPGS2, ZNF652, RORA, and MALAT1 were the identified critical genes. In GRN, miR-155, miR17, miR146b, miR-200 family, and GATA2 were the factors that regulated critical genes. The MAPK, neurotrophin, and TNF signaling pathways, IL-17, and human cytomegalovirus infection, human papillomavirus infection, and shigellosis were identified as significant pathways involved in graft rejection.

Concusion

The above-mentioned genes can be used as diagnostic and therapeutic serum markers of transplantation rejection in renal patients. The newly predicted biomarkers and pathways require further studies.

YAP Inactivation by Soft Mechanotransduction Relieves MAFG for Tumor Cell Dedifferentiation

Solid tumor cells live in a highly dynamic mechanical microenvironment. How the extracellular-matrix-generated mechanotransduction regulates tumor cell development and differentiation remains an enigma. Here, we show that a low mechanical force generated from the soft matrix induces dedifferentiation of moderately stiff tumor cells to soft stem-cell-like cells. Mechanistically, integrin β8 was identified to transduce mechano-signaling to trigger tumor cell dedifferentiation by recruiting RhoGDI1 to inactivate RhoA and subsequently Yes-associated protein (YAP). YAP inactivation relieved the inhibition of v-maf avian musculoaponeurotic fibrosarcoma oncogene homolog G (MAFG), allowing MAFG to transactivate the stemness genes NANOG, SOX2, and NESTIN. Inactivation also restored β8 expression, thereby forming a closed mechanical loop. Importantly, MAFG expression is correlated with worse prognosis. Our findings provide mechanical insights into the regulation of tumor cell dedifferentiation, which has therapeutic implications for exploring innovative strategies to attack malignancies.

Identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome data

Millions of single nucleotide variants (SNVs) exist in the human genome; however, it remains challenging to identify functional SNVs associated with diseases. We propose a non-encoding SNVs analysis tool bpb3, BayesPI-BAR version 3, aiming to identify the functional mutation blocks (FMBs) by integrating genome sequencing and transcriptome data. The identified FMBs display high frequency SNVs, significant changes in transcription factors (TFs) binding affinity and are nearby the regulatory regions of differentially expressed genes. A two-level Bayesian approach with a biophysical model for protein-DNA interactions is implemented, to compute TF-DNA binding affinity changes based on clustered position weight matrices (PWMs) from over 1700 TF-motifs. The epigenetic data, such as the DNA methylome can also be integrated to scan FMBs. By testing the datasets from follicular lymphoma and melanoma, bpb3 automatically and robustly identifies FMBs, demonstrating that bpb3 can provide insight into patho-mechanisms, and therapeutic targets from transcriptomic and genomic data.

Plant Promoters and Terminators for High-Precision Bioengineering

High-precision bioengineering and synthetic biology require fine-tuning gene expression at both transcriptional and posttranscriptional levels. Gene transcription is tightly regulated by promoters and terminators. Promoters determine the timing, tissues and cells, and levels of the expression of genes. Terminators mediate transcription termination of genes and affect mRNA levels posttranscriptionally, e.g., the 3'-end processing, stability, translation efficiency, and nuclear to cytoplasmic export of mRNAs. The promoter and terminator combination affects gene expression. In the present article, we review the function and features of plant core promoters, proximal and distal promoters, and terminators, and their effects on and benchmarking strategies for regulating gene expression.

Human skin-resident CD8+ T cells require RUNX2 and RUNX3 for induction of cytotoxicity and expression of the integrin CD49a

The integrin CD49a marks highly cytotoxic epidermal-tissue-resident memory (T_RM) cells, but their differentiation from circulating populations remains poorly defined. We demonstrate enrichment of RUNT family transcription-factor-binding motifs in human epidermal CD8⁺CD103⁺CD49a⁺ T_RM cells, paralleled by high RUNX2 and RUNX3 protein expression. Sequencing of paired skin and blood samples revealed clonal overlap between epidermal CD8⁺CD103⁺CD49a⁺ T_RM cells and circulating memory CD8⁺CD45RA^-CD62L⁺ T cells. In vitro stimulation of circulating CD8⁺CD45RA^-CD62L⁺ T cells with IL-15 and TGF-β induced CD49a expression and cytotoxic transcriptional profiles in a RUNX2- and RUNX3-dependent manner. We therefore identified a reservoir of circulating cells with cytotoxic T_RM potential. In melanoma patients, high RUNX2, but not RUNX3, transcription correlated with a cytotoxic CD8⁺CD103⁺CD49a⁺ T_RM cell signature and improved patient survival. Together, our results indicate that combined RUNX2 and RUNX3 activity promotes the differentiation of cytotoxic CD8⁺CD103⁺CD49a⁺ T_RM cells, providing immunosurveillance of infected and malignant cells.

A survey on algorithms to characterize transcription factor binding sites

Transcription factors (TFs) are key regulatory proteins that control the transcriptional rate of cells by binding short DNA sequences called transcription factor binding sites (TFBS) or motifs. Identifying and characterizing TFBS is fundamental to understanding the regulatory mechanisms governing the transcriptional state of cells. During the last decades, several experimental methods have been developed to recover DNA sequences containing TFBS. In parallel, computational methods have been proposed to discover and identify TFBS motifs based on these DNA sequences. This is one of the most widely investigated problems in bioinformatics and is referred to as the motif discovery problem. In this manuscript, we review classical and novel experimental and computational methods developed to discover and characterize TFBS motifs in DNA sequences, highlighting their advantages and drawbacks. We also discuss open challenges and future perspectives that could fill the remaining gaps in the field.

Enhancer variants on chromosome 2p14 regulating SPRED2 and ACTR2 act as a signal amplifier to protect against rheumatoid arthritis

Genome-wide association studies (GWASs) have repeatedly reported multiple non-coding single-nucleotide polymorphisms (SNPs) at 2p14 associated with rheumatoid arthritis (RA), but their functional roles in the pathological mechanisms of RA remain to be explored. In this study, we integrated a series of bioinformatics and functional experiments and identified three intronic RA SNPs (rs1876518, rs268131, and rs2576923) within active enhancers that can regulate the expression of SPRED2 directly. At the same time, SPRED2 and ACTR2 influence each other as a positive feedback signal amplifier to strengthen the protective role in RA by inhibiting the migration and invasion of rheumatoid fibroblast-like synoviocytes (FLSs). In particular, the transcription factor CEBPB preferentially binds to the rs1876518-T allele to increase the expression of SPRED2 in FLSs. Our findings decipher the molecular mechanisms behind the GWAS signals at 2p14 for RA and emphasize SPRED2 as a potential candidate gene for RA, providing a potential target and direction for precise treatment of RA.

A regulatory variant at 19p13.3 is associated with primary biliary cholangitis risk and ARID3A expression

Genome-wide association studies have identified 19p13.3 locus associated with primary biliary cholangitis (PBC). Here we aim to identify causative variant(s) and initiate efforts to define the mechanism by which the 19p13.3 locus variant(s) contributes to the pathogenesis of PBC. A genome-wide meta-analysis of 1931 PBC subjects and 7852 controls in two Han Chinese cohorts confirms the strong association between 19p13.3 locus and PBC. By integrating functional annotations, luciferase reporter assay and allele-specific chromatin immunoprecipitation, we prioritize rs2238574, an AT-Rich Interaction Domain 3A (ARID3A) intronic variant, as a potential causal variant at 19p13.3 locus. The risk allele of rs2238574 shows higher binding affinity of transcription factors, leading to an increased enhancer activity in myeloid cells. Genome-editing demonstrates the regulatory effect of rs2238574 on ARID3A expression through allele-specific enhancer activity. Furthermore, knock-down of ARID3A inhibits myeloid differentiation and activation pathway, and overexpression of the gene has the opposite effect. Finally, we find ARID3A expression and rs2238574 genotypes linked to disease severity in PBC. Our work provides several lines of evidence that a non-coding variant regulates ARID3A expression, presenting a mechanistic basis for association of 19p13.3 locus with the susceptibility to PBC.

High level of novelty under the hood of convergent evolution

Little is known about the extent to which species use homologous regulatory architectures to achieve phenotypic convergence. By characterizing chromatin accessibility and gene expression in developing wing tissues, we compared the regulatory architecture of convergence between a pair of mimetic butterfly species. Although a handful of color pattern genes are known to be involved in their convergence, our data suggest that different mutational paths underlie the integration of these genes into wing pattern development. This is supported by a large fraction of accessible chromatin being exclusive to each species, including the de novo lineage-specific evolution of a modular optix enhancer. These findings may be explained by a high level of developmental drift and evolutionary contingency that occurs during the independent evolution of mimicry.

Using QTL to Identify Genes and Pathways Underlying the Regulation and Production of Milk Components in Cattle

Milk is a complex liquid, and the concentrations of many of its components are under genetic control. Many genes and pathways are known to regulate milk composition, and the purpose of this review is to highlight how the discoveries of quantitative trait loci (QTL) for milk phenotypes can elucidate these pathways. The main body of this review focuses primarily on QTL discovered in cattle (Bos taurus) as a model species for the biology of lactation, and there are occasional references to sheep genetics. The following section describes a range of techniques that can be used to help identify the causative genes underlying QTL when the underlying mechanism involves the regulation of gene expression. As genotype and phenotype databases continue to grow and diversify, new QTL will continue to be discovered, and although proving the causality of underlying genes and variants remains difficult, these new data sets will further enhance our understanding of the biology of lactation.

Multiscale 3D genome reorganization during skeletal muscle stem cell lineage progression and aging

Little is known about three-dimensional (3D) genome organization in skeletal muscle stem cells [also called satellite cells (SCs)]. Here, we comprehensively map the 3D genome topology reorganization during mouse SC lineage progression. Specifically, rewiring at the compartment level is most pronounced when SCs become activated. Marked loss in topologically associating domain (TAD) border insulation and chromatin looping also occurs during early activation process. Meanwhile, TADs can form TAD clusters and super-enhancer-containing TAD clusters orchestrate stage-specific gene expression. Furthermore, we uncover that transcription factor PAX7 is pivotal in enhancer-promoter (E-P) loop formation. We also identify cis-regulatory elements that are crucial for local chromatin organization at Pax7 locus and Pax7 expression. Lastly, we unveil that geriatric SC displays a prominent gain in long-range contacts and loss of TAD border insulation. Together, our results uncover that 3D chromatin extensively reorganizes at multiple architectural levels and underpins the transcriptome remodeling during SC lineage development and SC aging.

Polycomb protein RYBP activates transcription factor Plagl1 during in vitro cardiac differentiation of mouse embryonic stem cells

RING1 and YY1 binding protein (RYBP) is primarily known to function as a repressor being a core component of the non-canonical polycomb repressive complexes 1 (ncPRC1s). However, several ncPRC1-independent functions of RYBP have also been described. We previously reported that RYBP is essential for mouse embryonic development and that Rybp null mutant embryonic stem cells cannot form contractile cardiomyocytes (CMCs) in vitro. We also showed that PLAGL1, a cardiac transcription factor, which is often mutated in congenital heart diseases (CHDs), is not expressed in Rybp-null mutant CMCs. However, the underlying mechanism of how RYBP regulates Plagl1 expression was not revealed. Here, we demonstrate that RYBP cooperated with NKX2-5 to transcriptionally activate the P1 and P3 promoters of the Plagl1 gene and that this activation is ncPRC1-independent. We also show that two non-coding RNAs residing in the Plagl1 locus can also regulate the Plagl1 promoters. Finally, PLAGL1 was able to activate Tnnt2, a gene important for contractility of CMCs in transfected HEK293 cells. Our study shows that the activation of Plagl1 by RYBP is important for sarcomere development and contractility, and suggests that RYBP, via its regulatory functions, may contribute to the development of CHDs.

Caspase-8 as a novel mediator linking Src kinase signaling to enhanced glioblastoma malignancy

Caspase-8 is a cysteine protease that plays an essential role in apoptosis. Consistently with its canonical proapoptotic function, cancer cells may genetically or epigenetically downregulate its expression. Unexpectedly, Caspase-8 is often retained in cancer, suggesting the presence of alternative mechanisms that may be exploited by cancer cells to their own benefit. In this regard, we reported that Src tyrosine kinase, which is aberrantly activated in many tumors, promotes Caspase-8 phosphorylation on Tyrosine 380 (Y380) preventing its full activation. Here, we investigated the significance of Caspase-8 expression and of its phosphorylation on Y380 in glioblastoma, a brain tumor where both Caspase-8 expression and Src activity are often aberrantly upregulated. Transcriptomic analyses identified inflammatory response as a major target of Caspase-8, and in particular, NFκB signaling as one of the most affected pathways. More importantly, we could show that Src-dependent phosphorylation of Caspase-8 on Y380 drives the assembly of a multiprotein complex that triggers NFκB activation, thereby inducing the expression of inflammatory and pro-angiogenic factors. Remarkably, phosphorylation on Y380 sustains neoangiogenesis and resistance to radiotherapy. In summary, our work identifies a novel interplay between Src kinase and Caspase-8 that allows cancer cells to hijack Caspase-8 to sustain tumor growth.

Identification of Critical Molecular Factors and Side Effects Underlying the Response to Thalicthuberine in Prostate Cancer: A Systems Biology Approach

Background

Uncontrolled mitosis of cancer cells and resistance cells to chemotherapy drugs are the challenges of prostate cancer. Thalicthuberine causes a mitotic arrest and a reduction of the effects of drug resistance, resulting in cell death. In this study, we applied bioinformatics and computational biology methods to identify functional pathways and side effects in response to Thalicthuberine in prostate cancer patients.

Methods

Microarray data were retrieved from Gene Expression Omnibus (GEO), and protein-protein interactions and gene regulatory networks were constructed, using the Cytoscape software. The critical genes and molecular mechanisms in response to Thalicthuberine and its side effects were identified, using the Cytoscape software and WebGestalt server, respectively. Finally, GEPIA2 was used to predict the relationship between critical genes and prostate cancer.

Results

The POLQ, EGR1, CDKN1A, FOS, MDM2, CDC20, CCNB1, and CCNB2 were identified as critical genes in response to this drug. The functional mechanisms of Thalicthuberine include a response to oxygen levels, toxic substances and immobilization stress, cell cycle regulation, regeneration, the p53 signaling pathway, the action of the parathyroid hormone, and the FoxO signaling pathway. Besides, the drug has side effects including muscle cramping, abdominal pains, paresthesia, and metabolic diseases.

Conclusion

Our model suggested newly predicted crucial genes, molecular mechanisms, and possible side effects of this drug. However, further studies are required.

NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity

A major question in systems biology is how to identify the core gene regulatory circuit that governs the decision-making of a biological process. Here, we develop a computational platform, named NetAct, for constructing core transcription factor regulatory networks using both transcriptomics data and literature-based transcription factor-target databases. NetAct robustly infers regulators' activity using target expression, constructs networks based on transcriptional activity, and integrates mathematical modeling for validation. Our in silico benchmark test shows that NetAct outperforms existing algorithms in inferring transcriptional activity and gene networks. We illustrate the application of NetAct to model networks driving TGF-β-induced epithelial-mesenchymal transition and macrophage polarization.

A capsule network-based method for identifying transcription factors

Transcription factors (TFs) are typical regulators for gene expression and play versatile roles in cellular processes. Since it is time-consuming, costly, and labor-intensive to detect it by using physical methods, it is desired to develop a computational method to detect TFs. Here, we presented a capsule network-based method for identifying TFs. This method is an end-to-end deep learning method, consisting mainly of an embedding layer, bidirectional long short-term memory (LSTM) layer, capsule network layer, and three fully connected layers. The presented method obtained an accuracy of 0.8820, being superior to the state-of-the-art methods. These empirical experiments showed that the inclusion of the capsule network promoted great performances and that the capsule network-based representation was superior to the property-based representation for distinguishing between TFs and non-TFs. We also implemented the presented method into a user-friendly web server, which is freely available at http://www.biolscience.cn/Capsule_TF/ for all scientific researchers.

In vivo single-cell transcriptomics reveal Klebsiella pneumoniae skews lung macrophages to promote infection

The strategies deployed by antibiotic-resistant bacteria to counteract host defences are poorly understood. Here, we elucidate a novel host-pathogen interaction resulting in skewing lung macrophage polarisation by the human pathogen Klebsiella pneumoniae. We identify interstitial macrophages (IMs) as the main population of lung macrophages associated with Klebsiella. Single-cell transcriptomics and trajectory analysis of cells reveal type I IFN and IL10 signalling, and macrophage polarisation are characteristic of infected IMs, whereas Toll-like receptor (TLR) and Nod-like receptor signalling are features of infected alveolar macrophages. Klebsiella-induced macrophage polarisation is a singular M2-type we termed M(Kp). To rewire macrophages, Klebsiella hijacks a TLR-type I IFN-IL10-STAT6 axis. Absence of STAT6 limits Klebsiella intracellular survival and facilitates the clearance of the pathogen in vivo. Glycolysis characterises M(Kp) metabolism, and inhibition of glycolysis results in clearance of intracellular Klebsiella. Capsule polysaccharide governs M(Kp). Klebsiella also skews human macrophage polarisation towards M(Kp) in a type I IFN-IL10-STAT6-dependent manner. Klebsiella induction of M(Kp) represents a novel strategy to overcome host restriction, and identifies STAT6 as target to boost defences against Klebsiella.

DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions

Genome-wide gene expression analyses are invaluable tools for studying biological and disease processes, allowing a hypothesis-free comparison of expression profiles. Traditionally, transcriptomic analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders. Here, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress receptor agonist dexamethasone in 8 mouse brain regions important for stress processing. By applying a combination of differential network- and expression-analyses, we find that these explain distinct but complementary biological mechanisms of the glucocorticoid responses. Additionally, network analysis identifies new differentially connected partners of risk genes and can be used to generate hypotheses on molecular pathways affected. With DiffBrainNet (http://diffbrainnet.psych.mpg.de), we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner.

Multiplexed functional genomic assays to decipher the noncoding genome

Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.

TFSyntax: a database of transcription factors binding syntax in mammalian genomes

In mammals, transcriptional factors (TFs) drive gene expression by binding to regulatory elements in a cooperative manner. Deciphering the rules of such cooperation is crucial to obtain a full understanding of cellular homeostasis and development. Although this is a long-standing topic, there is no comprehensive database for biologists to access the syntax of TF binding sites. Here we present TFSyntax (https://tfsyntax.zhaopage.com), a database focusing on the arrangement of TF binding sites. TFSyntax maps the binding motif of 1299 human TFs and 890 mouse TFs across 382 cells and tissues, representing the most comprehensive TF binding map to date. In addition to location, TFSyntax defines motif positional preference, density and colocalization within accessible elements. Powered by a series of functional modules based on web interface, users can freely search, browse, analyze, and download data of interest. With comprehensive characterization of TF binding syntax across distinct tissues and cell types, TFSyntax represents a valuable resource and platform for studying the mechanism of transcriptional regulation and exploring how regulatory DNA variants cause disease.

Single-cell multi-omics of human clonal hematopoiesis reveals that DNMT3A R882 mutations perturb early progenitor states through selective hypomethylation

Somatic mutations in cancer genes have been detected in clonal expansions across healthy human tissue, including in clonal hematopoiesis. However, because mutated and wild-type cells are admixed, we have limited ability to link genotypes with phenotypes. To overcome this limitation, we leveraged multi-modality single-cell sequencing, capturing genotype, transcriptomes and methylomes in progenitors from individuals with DNMT3A R882 mutated clonal hematopoiesis. DNMT3A mutations result in myeloid over lymphoid bias, and an expansion of immature myeloid progenitors primed toward megakaryocytic-erythroid fate, with dysregulated expression of lineage and leukemia stem cell markers. Mutated DNMT3A leads to preferential hypomethylation of polycomb repressive complex 2 targets and a specific CpG flanking motif. Notably, the hypomethylation motif is enriched in binding motifs of key hematopoietic transcription factors, serving as a potential mechanistic link between DNMT3A mutations and aberrant transcriptional phenotypes. Thus, single-cell multi-omics paves the road to defining the downstream consequences of mutations that drive clonal mosaicism.

Plant-DTI: Extending the landscape of TF protein and DNA interaction in plants by a machine learning-based approach

As a sessile organism, plants hold elaborate transcriptional regulatory systems that allow them to adapt to variable surrounding environments. Current understanding of plant regulatory mechanisms is greatly constrained by limited knowledge of transcription factor (TF)-DNA interactions. To mitigate this problem, a Plant-DTI predictor (Plant DBD-TFBS Interaction) was developed here as the first machine-learning model that covered the largest experimental datasets of 30 plant TF families, including 7 plant-specific DNA binding domain (DBD) types, and their transcription factor binding sites (TFBSs). Plant-DTI introduced a novel TFBS feature construction, called TFBS base-preference, which enhanced the specificity of TFBS to DBD types. The proposed model showed better predictive performance with the TFBS base-preference than the simple binary representation. Plant-DTI was validated with 22 independent ChIP-seq datasets. It accurately predicted the measured DBD-TFBS pairs along with their TFBS motifs, and effectively predicted interactions of other TFs containing similar DBD types. Comparing to the existing state-of-art methods, Plant-DTI prediction showed a figure of merit in sensitivity and specificity with respect to the position weight matrix (PWM) and TSPTFBS methods. Finally, the proposed Plant-DTI model helped to fill the knowledge gap in the regulatory mechanisms of the cassava sucrose synthase 1 gene (MeSUS1). Plant-DTI predicted MeERF72 as a regulator of MeSUS1 in consistence with the yeast one-hybrid (Y1H) experiment. Taken together, Plant-DTI would help facilitate the prediction of TF-TFBS and TF-target gene (TG) interactions, thereby accelerating the study of transcriptional regulatory systems in plant species.

Methamphetamine signals transcription of IL1β and TNFα in a reactive oxygen species-dependent manner and interacts with HIV-1 Tat to decrease antioxidant defense mechanisms

Methamphetamine (Meth) abuse is a common HIV co-morbidity that is linked to aggravated Central Nervous System (CNS) inflammation, which accentuates HIV- associated neurological disorders, triggered both directly or indirectly by the drug. We used the well-established human innate immune macrophage cell line system (THP1) to demonstrate that Reactive Oxygen Species (ROS) immediately induced by Meth play a role in the increased transcription of inflammatory genes, in interaction with HIV-1 Tat peptide. Meth and Tat, alone and together, affect early events of transcriptional activity, as indicated by changes in RNA polymerase (RNAPol) recruitment patterns throughout the genome, via ROS-dependent and -independent mechanisms. IL1β (IL1β) and TNF α (TNFα), two genes with defining roles in the inflammatory response, were both activated in a ROS-dependent manner. We found that this effect occurred via the activation of the activator protein 1 (AP-1) comprising cFOS and cJUN transcription factors and regulated by the SRC kinase. HIV-1 Tat, which was also able to induce the production of ROS, did not further impact the effects of ROS in the context of Meth, but promoted gene activity independently from ROS, via additional transcription factors. For instance, HIV-1 Tat increased NFkB activation and activated gene clusters regulated by Tata box binding peptide, ING4 and IRF2. Importantly, HIV-1 Tat decreased the expression of anti-oxidant genes, where its suppression of the detoxifying machinery may contribute to the aggravation of oxidative stress induced by ROS in the context of Meth. Our results provide evidence of effects of Meth via ROS and interactions with HIV Tat that promote the transcription of inflammatory genes such as IL1β and TNFα.

Transcriptome and metabolome analyses reveal transcription factors regulating ganoderic acid biosynthesis in Ganoderma lucidum development

Ganoderma lucidum is an important medicinal fungus in Asian countries. Ganoderic acid (GA) is the major variety of bioactive and medicative components in G. lucidum. Biosynthesis of secondary metabolites is usually associated with cell differentiation and development. However, the mechanism underlying these phenomena remain unclear. Transcription factors play an essential regulatory role in the signal transduction pathway, owing to the fact that they represent the major link between signal transduction and expression of target genes. In the present study, we performed transcriptome and metabolome analyses to identify transcription factors involved in GA biosynthesis during development of G. lucidum. Transcriptome data revealed differentially expressed genes between mycelia and primordia, as well as between mycelia and the fruiting body. Results from gene ontology enrichment analysis and metabolome analyses suggested that GAs and flavonoids biosynthetic process significantly changed during fungal development. The analysis of predicted occurrences of DNA-binding domains revealed a set of 53 potential transcription factor families in G. lucidum. Notably, we found homeobox transcription factor and velvet family protein played important role in GA biosynthesis. Combined with previous studies, we provided a model diagram of transcription factors involved in GA biosynthesis during fruiting body formation. Collectively, these results are expected to enhance our understanding into the mechanisms underlying secondary metabolite biosynthesis and development in fungi.

Temporally divergent regulatory mechanisms govern neuronal diversification and maturation in the mouse and marmoset neocortex

Mammalian neocortical neurons span one of the most diverse cell type spectra of any tissue. Cortical neurons are born during embryonic development, and their maturation extends into postnatal life. The regulatory strategies underlying progressive neuronal development and maturation remain unclear. Here we present an integrated single-cell epigenomic and transcriptional analysis of individual mouse and marmoset cortical neuron classes, spanning both early postmitotic stages of identity acquisition and later stages of neuronal plasticity and circuit integration. We found that, in both species, the regulatory strategies controlling early and late stages of pan-neuronal development diverge. Early postmitotic neurons use more widely shared and evolutionarily conserved molecular regulatory programs. In contrast, programs active during later neuronal maturation are more brain- and neuron-specific and more evolutionarily divergent. Our work uncovers a temporal shift in regulatory choices during neuronal diversification and maturation in both mice and marmosets, which likely reflects unique evolutionary constraints on distinct events of neuronal development in the neocortex.

Snail acetylation by autophagy-derived acetyl-coenzyme A promotes invasion and metastasis of KRAS-LKB1 co-mutated lung cancer cells

Background

Autophagy is elevated in metastatic tumors and is often associated with active epithelial‐to‐mesenchymal transition (EMT). However, the extent to which EMT is dependent on autophagy is largely unknown. This study aimed to identify the mechanisms by which autophagy facilitates EMT.

Methods

We employed a liquid chromatography‐based metabolomic approach with kirsten rat sarcoma viral oncogene (KRAS) and liver kinase B1 (LKB1) gene co‐mutated (KL) cells that represent an autophagy/EMT‐coactivated invasive lung cancer subtype for the identification of metabolites linked to autophagy‐driven EMT activation. Molecular mechanisms of autophagy‐driven EMT activation were further investigated by quantitative real‐time polymerase chain reaction (qRT‐PCR), Western blotting analysis, immunoprecipitation, immunofluorescence staining, and metabolite assays. The effects of chemical and genetic perturbations on autophagic flux were assessed by two orthogonal approaches: microtubule‐associated protein 1A/1B‐light chain 3 (LC3) turnover analysis by Western blotting and monomeric red fluorescent protein‐green fluorescent protein (mRFP‐GFP)‐LC3 tandem fluorescent protein quenching assay. Transcription factor EB (TFEB) activity was measured by coordinated lysosomal expression and regulation (CLEAR) motif‐driven luciferase reporter assay. Experimental metastasis (tail vein injection) mouse models were used to evaluate the impact of calcium/calmodulin‐dependent protein kinase kinase 2 (CAMKK2) or ATP citrate lyase (ACLY) inhibitors on lung metastasis using IVIS luciferase imaging system.

Results

We found that autophagy in KL cancer cells increased acetyl‐coenzyme A (acetyl‐CoA), which facilitated the acetylation and stabilization of the EMT‐inducing transcription factor Snail. The autophagy/acetyl‐CoA/acetyl‐Snail axis was further validated in tumor tissues and in autophagy‐activated pancreatic cancer cells. TFEB acetylation in KL cancer cells sustained pro‐metastatic autophagy in a mammalian target of rapamycin complex 1 (mTORC1)‐independent manner. Pharmacological inhibition of this axis via CAMKK2 inhibitors or ACLY inhibitors consistently reduced the metastatic capacity of KL cancer cells in vivo.

Conclusions

This study demonstrates that autophagy‐derived acetyl‐CoA promotes Snail acetylation and thereby facilitates invasion and metastasis of KRAS‐LKB1 co‐mutated lung cancer cells and that inhibition of the autophagy/acetyl‐CoA/acetyl‐Snail axis using CAMKK2 or ACLY inhibitors could be a potential therapeutic strategy to suppress metastasis of KL lung cancer.

Further Characterization of MUAS35SCP and FUAS35SCP Recombinant Promoters and Their Implication in Translational Research

Recombinant promoters are of high value in translational research. Earlier, we developed two recombinant promoters, namely MUAS35SCP and FUAS35SCP, and their transcriptional activities were found to be stronger than that of the most widely used CaMV35S promoter in dicot plants. Presently, we are reporting constitutive expression of both GUS and GFP reporters under the control of these promoters in several monocots, including rice, wheat, and pearl millet. We observed that these promoters could express the reporter genes constitutively, and their expression abilities were almost equal to that of the CaMV35S² promoter. Plant-derived enriched PaDef (Persea americana var. drymifolia defensin) and NsDef2 (Nigella sativa L. defensin 2) antimicrobial peptides expressed under the control of these promoters arrest the growth of devastating phytopathogens like Pseudomonas syringae, Rhodococcus fascians, and Alternaria alternata. We observed that plant-derived NsDef2 and PaDef under control of these promoters showed approximately 80-90% inhibitory activity against Pseudomonas syringae. Hence, these promoters were constitutive and universal, as they can drive the expression of transgenes in both dicot and monocot plants. Alongside, these promoters could become a valuable tool for raising genetically modified plants with in-built resistance toward phytopathogens.

Genetics of osteoarthritis

Osteoarthritis genetics has been transformed in the past decade through the application of large-scale genome-wide association scans. So far, over 100 polymorphic DNA variants have been associated with this common and complex disease. These genetic risk variants account for over 20% of osteoarthritis heritability and the vast majority map to non-protein coding regions of the genome where they are presumed to act by regulating the expression of target genes. Statistical fine mapping, in silico analyses of genomics data, and laboratory-based functional studies have enabled the identification of some of these targets, which encode proteins with diverse roles, including extracellular signaling molecules, intracellular enzymes, transcription factors, and cytoskeletal proteins. A large number of the risk variants correlate with epigenetic factors, in particular cartilage DNA methylation changes in cis, implying that epigenetics may be a conduit through which genetic effects on gene expression are mediated. Some of the variants also appear to have been selected as humans adapted to bipedalism, suggesting that a proportion of osteoarthritis genetic susceptibility results from antagonistic pleiotropy, with risk variants having a positive role in joint formation but a negative role in the long-term health of the joint. Although data from an osteoarthritis genetic study has not yet directly led to a novel treatment, some of the osteoarthritis associated genes code for proteins that have available therapeutics. Genetic investigations are therefore revealing fascinating fundamental insights into osteoarthritis and can expose options for translational intervention.

Elucidating miRNA Function in Cancer Biology via the Molecular Genetics' Toolbox

Micro-RNA (miRNAs) are short non-coding RNAs of about 18-20 nucleotides in length and are implicated in many cellular processes including proliferation, development, differentiation, apoptosis and cell signaling. Furthermore, it is well known that miRNA expression is frequently dysregulated in many cancers. Therefore, this review will highlight the various mechanisms by which microRNAs are dysregulated in cancer. Further highlights include the abundance of molecular genetics tools that are currently available to study miRNA function as well as their advantages and disadvantages with a special focus on various CRISPR/Cas systems This review provides general workflows and some practical considerations when studying miRNA function thus enabling researchers to make informed decisions in regards to the appropriate molecular genetics tool to be utilized for their experiments.

A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study

Background

Breast cancer is the most common malignancy worldwide. Doxorubicin is an anthracycline used to treat breast cancer as the first treatment choice. Nevertheless, the molecular mechanisms underlying the response to Doxorubicin and its side effects are not comprehensively understood so far. We used systems biology and bioinformatics methods to identify essential genes and molecular mechanisms behind the body response to Doxorubicin and its side effects in breast cancer patients.

Methods

Omics data were extracted and analyzed to construct the protein-protein interaction and gene regulatory networks. Network analysis was performed to identify hubs, bottlenecks, clusters, and regulatory motifs to evaluate crucial genes and molecular mechanisms behind the body response to Doxorubicin and its side effects.

Results

Analyzing the constructed PPI and gene-TF-miRNA regulatory network showed that MCM3, MCM10, and TP53 are key hub-bottlenecks and seed proteins. Enrichment analysis also revealed cell cycle, TP53 signaling, Forkhead box O (FoxO) signaling, and viral carcinogenesis as essential pathways in response to this drug. Besides, SNARE interactions in vesicular transport and neurotrophin signaling were identified as pathways related to the side effects of Doxorubicin. The apoptosis induction, DNA repair, invasion inhibition, metastasis, and DNA replication are suggested as critical molecular mechanisms underlying Doxorubicin anti-cancer effect. SNARE interactions in vesicular transport and neurotrophin signaling and FoxO signaling pathways in glucose metabolism are probably the mechanisms responsible for side effects of Doxorubicin.

Conclusion

Following our model validation using the existing experimental data, we recommend our other newly predicted biomarkers and pathways as possible molecular mechanisms and side effects underlying the response to Doxorubicin in breast cancer requiring further investigations.

m6A-mediated modulation coupled with transcriptional regulation shapes long noncoding RNA repertoire of the cGAS-STING signaling

The cGAS-STING signaling plays pivotal roles not only in host antiviral defense but also in various noninfectious contexts. Compared with protein-coding genes, much less was known about long noncoding RNAs involved in this pathway. Here, we performed an integrative study to elucidate the lncRNA repertoire and the mechanisms modulating lncRNA’s expression following cGAS-STING signaling activation. We uncovered a reliable set of 672 lncRNAs closely linked to cGAS-STING signaling activation (cs-lncRNA), which might be associated with type-I interferon response and infection-related phenotypes. The ChIP-seq analysis demonstrated that cs-lncRNA was strongly regulated at the transcriptional level. We further found N6-methyladenosine (m⁶A) regulatory machinery was indispensable for establishing cs-lncRNA repertoire via modulating m⁶A modification on cs-lncRNA transcripts and promoting the expression of signaling transduction key components, including IFNAR1. Loss of IFNAR1 led to the dysregulation of cs-lncRNAs resembled that of loss of an essential subunit of m⁶A writer METTL14. We also found m⁶A system affected transcriptional machinery to modulate cs-lncRNAs by targeting multiple crucial transcription factors. Inhibiting an m⁶A modification regulated transcription factor, EZH2, markedly enhanced the expression pattern of cs-lncRNAs. Taken together, our results uncovered the composition of the cs-lncRNAs and revealed m⁶A-mediated modulation coupled with transcriptional regulation significantly shaped cs-lncRNA repertoire.

Hypoxia Drives Centrosome Amplification in Cancer Cells via HIF1α-dependent Induction of Polo-Like Kinase 4

Centrosome amplification (CA) has been implicated in the progression of various cancer types. Although studies have shown that overexpression of PLK4 promotes CA, the effect of tumor microenvironment on polo-like kinase 4 (PLK4) regulation is understudied. The aim of this study was to examine the role of hypoxia in promoting CA via PLK4. We found that hypoxia induced CA via hypoxia-inducible factor-1α (HIF1α). We quantified the prevalence of CA in tumor cell lines and tissue sections from breast cancer, pancreatic ductal adenocarcinoma (PDAC), colorectal cancer, and prostate cancer and found that CA was prevalent in cells with increased HIF1α levels under normoxic conditions. HIF1α levels were correlated with the extent of CA and PLK4 expression in clinical samples. We analyzed the correlation between PLK4 and HIF1A mRNA levels in The Cancer Genome Atlas (TCGA) datasets to evaluate the role of PLK4 and HIF1α in breast cancer and PDAC prognosis. High HIF1A and PLK4 levels in patients with breast cancer and PDAC were associated with poor overall survival. We confirmed PLK4 as a transcriptional target of HIF1α and demonstrated that in PLK4 knockdown cells, hypoxia-mimicking agents did not affect CA and expression of CA-associated proteins, underscoring the necessity of PLK4 in HIF1α-related CA. To further dissect the HIF1α-PLK4 interplay, we used HIF1α-deficient cells overexpressing PLK4 and showed a significant increase in CA compared with HIF1α-deficient cells harboring wild-type PLK4. These findings suggest that HIF1α induces CA by directly upregulating PLK4 and could help us risk-stratify patients and design new therapies for CA-rich cancers.

IMPLICATIONS

Hypoxia drives CA in cancer cells by regulating expression of PLK4, uncovering a novel HIF1α/PLK4 axis.

abc4pwm: affinity based clustering for position weight matrices in applications of DNA sequence analysis

BACKGROUND

Transcription factor (TF) binding motifs are identified by high throughput sequencing technologies as means to capture Protein-DNA interactions. These motifs are often represented by consensus sequences in form of position weight matrices (PWMs). With ever-increasing pool of TF binding motifs from multiple sources, redundancy issues are difficult to avoid, especially when every source maintains its own database for collection. One solution can be to cluster biologically relevant or similar PWMs, whether coming from experimental detection or in silico predictions. However, there is a lack of efficient tools to cluster PWMs. Assessing quality of PWM clusters is yet another challenge. Therefore, new methods and tools are required to efficiently cluster PWMs and assess quality of clusters.

RESULTS

A new Python package Affinity Based Clustering for Position Weight Matrices (abc4pwm) was developed. It efficiently clustered PWMs from multiple sources with or without using DNA-Binding Domain (DBD) information, generated a representative motif for each cluster, evaluated the clustering quality automatically, and filtered out incorrectly clustered PWMs. Additionally, it was able to update human DBD family database automatically, classified known human TF PWMs to the respective DBD family, and performed TF motif searching and motif discovery by a new ensemble learning approach.

CONCLUSION

This work demonstrates applications of abc4pwm in the DNA sequence analysis for various high throughput sequencing data using ~ 1770 human TF PWMs. It recovered known TF motifs at gene promoters based on gene expression profiles (RNA-seq) and identified true TF binding targets for motifs predicted from ChIP-seq experiments. Abc4pwm is a useful tool for TF motif searching, clustering, quality assessment and integration in multiple types of sequence data analysis including RNA-seq, ChIP-seq and ATAC-seq.