scholarly journals Pan-genomic analysis of transcriptional modules across Salmonella Typhimurium reveals the regulatory landscape of different strains

2022 ◽  
Author(s):  
Yuan Yuan ◽  
Yara Seif ◽  
Kevin Rychel ◽  
Reo Yoo ◽  
Siddharth M Chauhan ◽  
...  
Keyword(s):  
Transcriptional Regulatory Network ◽  
Genomic Analysis ◽  
Rna Seq ◽  
High Quality ◽  
Transcriptional Regulatory ◽  
Serovar Typhimurium ◽  
Gene Modules ◽  
Different Strains ◽  
Genetic Signatures ◽  
Regulatory Landscape

Salmonella enterica Typhimurium is a serious pathogen that is involved in human nontyphoidal infections. Tackling Typhimurium infections is difficult due to the species' dynamic adaptation to its environment, which is dictated by a complex transcriptional regulatory network (TRN). While traditional biomolecular methods provide characterizations of specific regulators, it is laborious to construct the global TRN structure from this bottom-up approach. Here, we used a machine learning technique to understand the transcriptional signatures of S. enterica Typhimurium from the top down, as a whole and in individual strains. Furthermore, we conducted cross-strain comparison of 6 strains in serovar Typhimurium to investigate similarities and differences in their TRNs with pan-genomic analysis. By decomposing all the publicly available RNA-Seq data of Typhimurium with independent component analysis (ICA), we obtained over 400 independently modulated sets of genes, called iModulons. Through analysis of these iModulons, we 1) discover three transport iModulons linked to antibiotic resistance, 2) describe concerted responses to cationic antimicrobial peptides (CAMPs), 3) uncover evidence towards new regulons, and 4) identify two iModulons linked to bile responses in strain ST4/74. We extend this analysis across the pan-genome to show that strain-specific iModulons 5) reveal different genetic signatures in pathogenicity islands that explain phenotypes and 6) capture the activity of different phages in the studied strains. Using all high-quality publicly-available RNA-Seq data to date, we present a comprehensive, data-driven Typhimurium TRN. It is conceivable that with more high-quality datasets from more strains, the approach used in this study will continue to guide our investigation in understanding the pan-transcriptome of Typhimurium. Interactive dashboards for all gene modules in this project are available at https://imodulondb.org/ to enable browsing for interested researchers.

scholarly journals PRECISE 2.0: an expanded high-quality RNA-seq compendium for Escherichia coli K-12 reveals high-resolution transcriptional regulatory structure

2021 ◽  
Author(s):  
Cameron R. Lamoureux ◽  
Katherine T. Decker ◽  
Anand V. Sastry ◽  
John Luke McConn ◽  
Ye Gao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Multiple Scales ◽  
Transcriptional Regulatory Network ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
High Quality ◽  
Standardized Protocol ◽  
Transcriptional Regulatory ◽  
K 12

Uncovering the structure of the transcriptional regulatory network (TRN) that modulates gene expression in prokaryotes remains an important challenge. Transcriptomics data is plentiful, necessitating the development of scalable methods for converting this data into useful knowledge about the TRN. Previously, we published the PRECISE dataset for Escherichia coli K-12 MG1655, containing 278 RNA-seq datasets created using a standardized protocol. Here, we present PRECISE 2.0, which is nearly three times the size of the original PRECISE dataset and also created using a standardized protocol. We analyze PRECISE 2.0 at multiple scales, demonstrating multiple analytical strategies for extracting knowledge from this dataset. Specifically, we: (1) highlight patterns in gene expression across the dataset; (2) utilize independent component analysis to extract 218 independently modulated groups of genes (iModulons) that describe the TRN at the systems level; (3) demonstrate the utility of iModulons over traditional differential expression analysis; and (4) uncover 6 new potential regulons. Thus, PRECISE 2.0 is a large-scale, high-quality transcriptomics dataset which may be analyzed at multiple scales to yield important biological insights.

scholarly journals The polar flagellar transcriptional regulatory network in Vibrio campbellii deviates from canonical Vibrio species

2021 ◽  
Author(s):  
Blake D Petersen ◽  
Michael S Liu ◽  
Ram Podicheti ◽  
Albert Ying-Po Yang ◽  
Chelsea A Simpson ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Vibrio Species ◽  
Flagellar Motor ◽  
Rna Seq ◽  
Free Living ◽  
Transcriptional Regulatory ◽  
Host Mortality ◽  
Vibrio Campbellii ◽  
Fish And Shellfish

Vibrio campbellii is a Gram-negative bacterium that is free-living and ubiquitous in marine environments, and it is a pathogen of fish and shellfish. Swimming motility via a single polar flagellum is a critical virulence factor in V. campbellii pathogenesis, and disruption of the flagellar motor significantly decreases host mortality. To examine V. campbellii flagellar gene regulation, we identified homologs of flagellar and chemotaxis genes conserved in other members of the Vibrionaceae and determined the transcriptional profile of these loci using differential RNA-seq. We systematically deleted all 63 predicted flagellar and chemotaxis genes in V. campbellii and examined their effects on motility and flagellum production. We specifically focused on the core flagellar regulators of the flagellar regulatory hierarchy established in other Vibrios: RpoN (σ54), FlrA, FlrC, and FliA. Our results show that V. campbellii transcription of flagellar and chemotaxis genes is governed by a multi-tiered regulatory hierarchy similar to other motile Vibrio species but with two critical differences: the σ54-dependent regulator FlrA is dispensable for motility, and Class II gene expression is independent of σ54 regulation. Our genetic and phenotypic dissection of the V. campbellii flagellar regulatory network highlights the differences that have evolved in flagellar regulation across the Vibrionaceae.

scholarly journals Identification of KLF6/PSGs and NPY-Related USF2/CEACAM Transcriptional Regulatory Networks via Spinal Cord Bulk and Single-Cell RNA-Seq Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Xinbing Liu ◽  
Wei Gao ◽  
Wei Liu
Keyword(s):  
Spinal Cord ◽  
Single Cell ◽  
Regulatory Networks ◽  
Single Cell Analysis ◽  
Transcriptional Regulatory Network ◽  
Transcriptional Regulator ◽  
Cell Analysis ◽  
Rna Seq ◽  
Transcriptional Regulatory Networks ◽  
Transcriptional Regulatory

Background. To further understand the development of the spinal cord, an exploration of the patterns and transcriptional features of spinal cord development in newborn mice at the cellular transcriptome level was carried out. Methods. The mouse single-cell sequencing (scRNA-seq) dataset was downloaded from the GSE108788 dataset. Single-cell RNA-Seq (scRNA-Seq) was conducted on cervical and lumbar spinal V2a interneurons from 2 P0 neonates. Single-cell analysis using the Seurat package was completed, and marker mRNAs were identified for each cluster. Then, pseudotemporal analysis was used to analyze the transcription changes of marker mRNAs in different clusters over time. Finally, the functions of these marker mRNAs were assessed by enrichment analysis and protein-protein interaction (PPI) networks. A transcriptional regulatory network was then constructed using the TRRUST dataset. Results. A total of 949 cells were screened. Single-cell analysis was conducted based on marker mRNAs of each cluster, which revealed the heterogeneity of neonatal mouse spinal cord neuronal cells. Functional analysis of pseudotemporal trajectory-related marker mRNAs suggested that pregnancy-specific glycoproteins (PSGs) and carcinoembryonic antigen cell adhesion molecules (CEACAMs) were the core mRNAs in cluster 3. GSVA analysis then demonstrated that the different clusters had differences in pathway activity. By constructing a transcriptional regulatory network, USF2 was identified to be a transcriptional regulator of CEACAM1 and CEACAM5, while KLF6 was identified to be a transcriptional regulator of PSG3 and PSG5. This conclusion was then validated using the Genotype-Tissue Expression (GTEx) spinal cord transcriptome dataset. Conclusions. This study completed an integrated analysis of a single-cell dataset with the utilization of marker mRNAs. USF2/CEACAM1&5 and KLF6/PSG3&5 transcriptional regulatory networks were identified by spinal cord single-cell analysis.

scholarly journals Single-Cell Transcriptomics-Based Study of Transcriptional Regulatory Features in the Mouse Brain Vasculature

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wei-Wei Lin ◽  
Lin-Tao Xu ◽  
Yi-Sheng Chen ◽  
Ken Go ◽  
Chenyu Sun ◽  
...  
Keyword(s):  
Single Cell ◽  
Mouse Brain ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Transcriptional Regulatory Network ◽  
Rna Seq ◽  
Brain Vasculature ◽  
Transcriptional Regulatory ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Background. The critical role of vascular health on brain function has received much attention in recent years. At the single-cell level, studies on the developmental processes of cerebral vascular growth are still relatively few. Techniques for constructing gene regulatory networks (GRNs) based on single-cell transcriptome expression data have made significant progress in recent years. Herein, we constructed a single-cell transcriptional regulatory network of mouse cerebrovascular cells. Methods. The single-cell RNA-seq dataset of mouse brain vessels was downloaded from GEO (GSE98816). This cell clustering was annotated separately using singleR and CellMarker. We then used a modified version of the SCENIC method to construct GRNs. Next, we used a mouse version of SEEK to assess whether genes in the regulon were coexpressed. Finally, regulatory module analysis was performed to complete the cell type relationship quantification. Results. Single-cell RNA-seq data were used to analyze the heterogeneity of mouse cerebrovascular cells, whereby four cell types including endothelial cells, fibroblasts, microglia, and oligodendrocytes were defined. These subpopulations of cells and marker genes together characterize the molecular profile of mouse cerebrovascular cells. Through these signatures, key transcriptional regulators that maintain cell identity were identified. Our findings identified genes like Lmo2, which play an important role in endothelial cells. The same cell type, for instance, fibroblasts, was found to have different regulatory networks, which may influence the functional characteristics of local tissues. Conclusions. In this study, a transcriptional regulatory network based on single-cell analysis was constructed. Additionally, the study identified and profiled mouse cerebrovascular cells using single-cell transcriptome data as well as defined TFs that affect the regulatory network of the mouse brain vasculature.

scholarly journals Identification and characterization of jasmonic acid- and linolenic acid-mediated transcriptional regulation of secondary laticifer differentiation in Hevea brasiliensis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Swee Cheng Loh ◽  
Ahmad Sofiman Othman ◽  
G. Veera Singham
Keyword(s):  
Jasmonic Acid ◽  
Linolenic Acid ◽  
Hevea Brasiliensis ◽  
Transcriptional Regulatory Network ◽  
Gene Families ◽  
Differentially Expressed ◽  
Ethylene Response Factor ◽  
Rna Seq ◽  
Helix Loop Helix ◽  
Transcriptional Regulatory

Abstract Hevea brasiliensis remains the primary crop commercially exploited to obtain latex, which is produced from the articulated secondary laticifer. Here, we described the transcriptional events related to jasmonic acid (JA)- and linolenic acid (LA)-induced secondary laticifer differentiation (SLD) in H. brasiliensis clone RRIM 600 based on RNA-seq approach. Histochemical approach proved that JA- and LA-treated samples resulted in SLD in H. brasiliensis when compared to ethephon and untreated control. RNA-seq data resulted in 86,614 unigenes, of which 2,664 genes were differentially expressed in JA and LA-induced secondary laticifer harvested from H. brasiliensis bark samples. Among these, 450 genes were unique to JA and LA as they were not differentially expressed in ethephon-treated samples compared with the untreated samples. Most transcription factors from the JA- and LA-specific dataset were classified under MYB, APETALA2/ethylene response factor (AP2/ERF), and basic-helix-loop-helix (bHLH) gene families that were involved in tissue developmental pathways, and we proposed that Bel5-GA2 oxidase 1-KNOTTED-like homeobox complex are likely involved in JA- and LA-induced SLD in H. brasiliensis. We also discovered alternative spliced transcripts, putative novel transcripts, and cis-natural antisense transcript pairs related to SLD event. This study has advanced understanding on the transcriptional regulatory network of SLD in H. brasiliensis.

scholarly journals Transcriptome Analysis of Ginkgo biloba L. Leaves across Late Developmental Stages Based on RNA-Seq and Co-Expression Network

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 315
Author(s):  
Hailin Liu ◽  
Xin Han ◽  
Jue Ruan ◽  
Lian Xu ◽  
Bing He
Keyword(s):  
Ginkgo Biloba ◽  
Leaf Development ◽  
Developmental Stages ◽  
Leaf Growth ◽  
Rna Seq ◽  
Final Size ◽  
Dioecious Species ◽  
Related Factors ◽  
New Genes ◽  
Gene Modules

The final size of plant leaves is strictly controlled by environmental and genetic factors, which coordinate cell expansion and cell cycle activity in space and time; however, the regulatory mechanisms of leaf growth are still poorly understood. Ginkgo biloba is a dioecious species native to China with medicinally and phylogenetically important characteristics, and its fan-shaped leaves are unique in gymnosperms, while the mechanism of G. biloba leaf development remains unclear. In this study we studied the transcriptome of G. biloba leaves at three developmental stages using high-throughput RNA-seq technology. Approximately 4167 differentially expressed genes (DEGs) were obtained, and a total of 12,137 genes were structure optimized together with 732 new genes identified. More than 50 growth-related factors and gene modules were identified based on DEG and Weighted Gene Co-expression Network Analysis. These results could remarkably expand the existing transcriptome resources of G. biloba, and provide references for subsequent analysis of ginkgo leaf development.

scholarly journals Antibiotic tolerance is associated with a broad and complex transcriptional response in E. coli

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Heather S. Deter ◽  
Tahmina Hossain ◽  
Nicholas C. Butzin
Keyword(s):  
Transcriptional Regulatory Network ◽  
Transcriptional Response ◽  
Regulatory Proteins ◽  
Health Concern ◽  
Transcriptional Networks ◽  
Antibiotic Tolerance ◽  
Multiple Gene ◽  
E Coli ◽  
Transcriptional Regulatory ◽  
Antibiotic Efficacy

AbstractAntibiotic treatment kills a large portion of a population, while a small, tolerant subpopulation survives. Tolerant bacteria disrupt antibiotic efficacy and increase the likelihood that a population gains antibiotic resistance, a growing health concern. We examined how E. coli transcriptional networks changed in response to lethal ampicillin concentrations. We are the first to apply transcriptional regulatory network (TRN) analysis to antibiotic tolerance by leveraging existing knowledge and our transcriptional data. TRN analysis shows that gene expression changes specific to ampicillin treatment are likely caused by specific sigma and transcription factors typically regulated by proteolysis. These results demonstrate that to survive lethal concentration of ampicillin specific regulatory proteins change activity and cause a coordinated transcriptional response that leverages multiple gene systems.

scholarly journals Overexpression of Replication-Dependent Histone Signifies a Subset of Dedifferentiated Liposarcoma with Increased Aggressiveness

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3122
Author(s):  
Yongjin Yoo ◽  
Sang-Yoon Park ◽  
Eun Byeol Jo ◽  
Minji Choi ◽  
Kyo Won Lee ◽  
...  
Keyword(s):  
Copy Number ◽  
Fold Change ◽  
High Grade ◽  
Rna Seq ◽  
Fat Tissue ◽  
Normal Tissues ◽  
Whole Exome ◽  
Well Differentiated ◽  
Genetic Signatures ◽  
Subtype Differences

Liposarcoma (LPS) is an adult soft tissue malignancy that arises from fat tissue, where well-differentiated (WD) and dedifferentiated (DD) forms are the most common. DDLPS represents the progression of WDLPS into a more aggressive high-grade and metastatic form. Although a few DNA copy-number amplifications are known to be specifically found in WD- or DDLPS, systematic genetic differences that signify subtype determination between WDLPS and DDLPS remain unclear. Here, we profiled the genome and transcriptome of 38 LPS tumors to uncover the genetic signatures of subtype differences. Replication-dependent histone (RD-HIST) mRNAs were highly elevated and their regulation was disrupted in a subset of DDLPS, increasing cellular histone molecule levels, as measured using RNA-seq (the averaged fold change of 53 RD-HIST genes between the DD and WD samples was 10.9) and immunohistochemistry. The change was not observed in normal tissues. Integrated whole-exome sequencing, RNA-seq, and methylation analyses revealed that the overexpressed HMGA2 (the fold change between DD and WD samples was 7.3) was responsible for the increased RD-HIST level, leading to aberrant cell proliferation. Therefore, HMGA2-mediated elevation of RD-HISTs were crucial events in determining the aggressiveness of DDLPS, which may serve as a biomarker for prognosis prediction for liposarcoma patients.

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