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Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation

ABSTRACT: Purpose: Key steps in understanding a biological process include identifying genes that are involved and determining how they are regulated. We developed a novel method for identifying TFs involved in a specific process and used it to map regulation of the key virulence factor of Cryptococcus neoformans, its capsule. Results: The map, built from expression profiles of 41 TF mutants, includes 20 TFs not previously known to regulate virulence attributes. It also reveals a hierarchy comprising executive, mid-level, and “foreman” TFs. When grouped by temporal expression pattern, these TFs explain much of the transcriptional dynamics of capsule induction. Phenotypic analysis of 41 TF deletion mutants revealed complex relationships among virulence factors and virulence in mice. Conclusions: These data resources and analyses provide the first integrated, systems level view of capsule regulation and biosynthesis. Our methods dramatically improve the efficiency with which transcriptional networks can be analyzed, making genomic approaches accessible to labs focused on specific physiological processes.

ORGANISM(S): Cryptococcus neoformans

PROVIDER: GSE60398 | GEO | 2015/01/14

SECONDARY ACCESSION(S): PRJNA258181

REPOSITORIES: GEO

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Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation

Project description:Purpose: Key steps in understanding a biological process include identifying genes that are involved and determining how they are regulated. We developed a novel method for identifying TFs involved in a specific process and used it to map regulation of the key virulence factor of Cryptococcus neoformans, its capsule. Results: The map, built from expression profiles of 41 TF mutants, includes 20 TFs not previously known to regulate virulence attributes. It also reveals a hierarchy comprising executive, mid-level, and “foreman” TFs. When grouped by temporal expression pattern, these TFs explain much of the transcriptional dynamics of capsule induction. Phenotypic analysis of 41 TF deletion mutants revealed complex relationships among virulence factors and virulence in mice. Conclusions: These data resources and analyses provide the first integrated, systems level view of capsule regulation and biosynthesis. Our methods dramatically improve the efficiency with which transcriptional networks can be analyzed, making genomic approaches accessible to labs focused on specific physiological processes. A total of 288 expression profiles were generated by RNA-Seq analysis of Mutant and wildtype cells grown in capsule inducing conditions for 90 minutes. In addition, 3 replicate expression profiles were generated for wildtype cells grown in : a capsule non-inducing condition, a capsule inducing condition for 180 minutes, a capsule inducing condition for 480 minutes, and a capsule inducing condition for 1440 minutes. In addition, ChIP-seq of NRG1(CNAG_05222) in capsule inducing conditions, and USV101(CNAG_05420) in both capsule inducing and non-inducing conditions were generated.

2015-01-14 | E-GEOD-60398 | biostudies-arrayexpress

Unraveling capsule biosynthesis and signaling networks in Cryptococcus neoformans

Project description:Cryptococcus neoformans is an opportunistic basidiomycete pathogen that is a major etiological agent of fungal meningoencephalitis leading to more than 180,000 deaths worldwide annually. For this pathogen, the polysaccharide capsule is a key virulence factor, which interferes with the phagocytosis by host innate immune cells, but its complex signaling networks remain elusive. In this study, we systematically analyzed capsule biosynthesis and signaling networks by using C. neoformans transcription factor (TF) and kinase mutant libraries under diverse capsule-inducing conditions, such as Dulbecco’s Modified Eagle’s (DME), Littman’s medium (LIT) and fetal bovine serum (FBS) medium. We found that deletion of GAT201, YAP1, BZP4, and ADA2 consistently causes capsule production defects in all tested media, indicating that they are capsule-regulating core TFs. Epistatic and expression analysis showed that Yap1 and Ada2 control Gat201 upstream, whereas Bzp4 and Gat201 regulate capsule production independently. We next searched for potential upstream kinases and found that mutants deleted of PKA1, BUD32, POS5, IRE1 or CDC2801 showed reduced capsule production under all three capsule induction conditions, whereas mutants deleted of HOG1 and IRK5 displayed enhanced capsule production. Notably, Pka1 and Irk5 controls induction of GAT201 and BZP4, respectively, under capsule induction condition. Finally, we monitored transcriptome profiles governed by Bzp4, Gat201, and Ada2 under capsule-inducing condition and demonstrated that these TFs regulate redundant and unique sets of downstream target genes. In conclusion, this study provides further insight into the complex regulatory mechanism of capsule production related signaling pathways in C. neoformans.

2022-10-18 | GSE208163 | GEO

Usv101 is a key regulator of cryptococcal virulence and determinant of host response

Project description:Cryptococcus neoformans is a fungal pathogen responsible for hundreds of thousands of deaths per year. Its critical virulence factor is a polysacharride capsule which grows large upon entry into a mammalian host. We previously identified USV101 as a transcription factor whose deletion results in enlarged capsules. Here, we characterize strains lacking or overexpressing USV101 in terms of their virulence-related phenotypes, the altered course of infection by them and immune response to them in a mouse model, the relationship of Usv101 to other transcription factors involved in capsule regulation, and the changes in Usv101 activity during capsule induction. To study the function of Usv101, a key C. neoformans regulator of virulence, and its interactions with downstream capsule-regulating TFs GAT201 and SP1, expression profiles were generated by RNA-seq of a usv101 deletion mutant, a USV101 overexpression mutant, strains expressing GAT201 under various promoters, various double mutants, and wildtype cells grown in a capsule non-inducing condition, a capsule inducing condition for 90 minutes, or a capsule inducing condition for 24 hours.

2016-03-31 | E-GEOD-69532 | biostudies-arrayexpress

Targeted single cell RNA-sequencing of transcription factors facilitates biological insights from human cell experimental models [intestinal stromal cells pre-capture]

Project description:Single cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ~1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell-type identification, developmental trajectories and gene regulatory networks. This allowed us to resolve differences amongst neuronal populations, which were generated in two different labs using the same differentiation protocol. ScCapture-seq improved TF gene-regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signalling in the developmental divergence between these different neuronal populations. Our results demonstrate that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to any cellular models to improve scRNA-seq resolution

2021-03-10 | GSE168626 | GEO

Targeted single cell RNA-sequencing of transcription factors facilitates biological insights from human cell experimental models [iPSC neuron pre-capture]

2021-03-10 | GSE168590 | GEO

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models [iPSC-derived neurons]

2021-03-06 | GSE157835 | GEO

ChIP-chip of the Cryptococcus neoformans transcription factor GAT201 and expression profiling of gat201KO

Project description:identify binding sites of Gat201 in C. neoformans cells grown in DMEM at 37C in 5% CO2 The anti-phagocytic polysaccharide capsule of the yeast C. neoformans is a major virulence attribute. However, previous studies of the pleiotropic virulence determinant Gat201, a GATA-family transcription factor, suggested that capsule-independent antiphagocytic mechanisms exist. We have determined that Gat201 controls the mRNA levels of ~1100 genes (16% of the genome) and binds the upstream regions of ~130 genes. Seven Gat201-bound genes encode for putative and known transcription factors⎯including two previously implicated in virulence⎯suggesting an extensive regulatory network. Systematic analysis pinpointed two critical Gat201-bound genes, GAT204 (a transcription factor) and BLP1, which account for much of the capsule-independent antiphagocytic function of Gat201. A strong correlation was observed between the quantitative effects of single and double mutants on phagocytosis in vitro and on host colonization in vivo. This genetic dissection provides the first clear evidence that capsule-independent anti-phagocytic mechanisms are pivotal for successful mammalian infection by C. neoformans.

2011-07-15 | GSE27660 | GEO

Expression data from LoVo and GP5d CRC cell lines

Project description:TF binding clusters in promoter correlate well with gene expression. We used ChIP-seq to map binding sites of the majority of highly expressed TFs in the cell. The size of clusters of TFs in the promoters of genes were found to correlate well with gene expression. CRC cell lines were grown on plastic This submission reprsents transcriptome component of study.

2013-08-16 | E-GEOD-48448 | biostudies-arrayexpress

A validated regulatory network for Th17 cell specification

Project description:Th17 cells have critical roles in mucosal defense and are major contributors to inflammatory disease. Their differentiation requires the nuclear hormone receptor RORγt working with multiple other essential transcription factors (TFs). We have used an iterative systems approach, combining genome-wide TF occupancy, expression profiling of TF mutants, and expression time series to delineate the Th17 global transcriptional regulatory network. We find that cooperatively-bound BATF and IRF4 contribute to initial chromatin accessibility, and with STAT3 initiate a transcriptional program that is then globally tuned by the lineage-specifying TF RORγt, which plays a focal deterministic role at key loci. Integration of multiple datasets allowed inference of an accurate predictive model that we computationally and experimentally validated, identifying multiple new Th17 regulators, including Fosl2, a key determinant of cellular plasticity. This interconnected network can be used to investigate new therapeutic approaches to manipulate Th17 functions in the setting of inflammatory disease. 143 RNA-seq, 83 ChIP-seq, 65 ChIP-seq controls, and 16 FAIRE-seq

2012-09-20 | E-GEOD-40918 | biostudies-arrayexpress

The Compendium of DNA-Binding Specificities of Transcription Factors in a Pathogenic Bacterium

Project description:The regulation of transcription is primarily exerted through transcription factors (TFs) binding to genomic DNA. Although molecular mechanisms of TFs have been studied individually for decades, a complete picture of binding profiles of all TFs and their precise targets in the genome are still lacking in the model pathogen Pseudomonas syringae. To this end, we performed a high-throughput systematic evolution of ligands by exponential enrichment (HT-SELEX) approach on all 301 annotated TFs in P. syringae. Robust enrichment of specific sequences was deduced to 118 SELEX motifs. We identified 12,464 interactions between 100 TFs and their target genes in the genome, for an individual TF ranging from 6 to 1481 sites. It showed that 90% TF binding was of dimeric site type, in which 85% with the head-to-head palindromic binding preference. To further explore the pathogenic mechanism of TFs in P. syringae, we mapped intricate networks of these TFs and their targets in the virulence-associated pathways, many of which were verified by orthologous methods such as ChIP-seq, EMSA, RT-qPCR and a reporter assay of promoter activity. By checking the enrichment of binding sites in pathways, we identified 25 virulence-associated master regulators of which 14 had never been characterized as TFs before. Overall, the present study provides a valuable resource for TF binding specificities in P. syringae and demonstrates a novel and an integrative analysis for seeking the virulence-associated TFs and its target genes. We expect that the results will significantly benefit future studies on the transcriptional regulation in P. syringae, and facilitate the design of drug targets to protect plants from attacks by relevant pathogens.

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