Modeling thePseudomonasSulfur Regulome by Quantifying the Storage and Communication of Information

ABSTRACTBacteria are not simply passive consumers of nutrients or merely steady-state systems. Rather, bacteria are active participants in their environments, collecting information from their surroundings and processing and using that information to adapt their behavior and optimize survival. The bacterial regulome is the set of physical interactions that link environmental information to the expression of genes by way of networks of sensors, transporters, signal cascades, and transcription factors. As bacteria cannot have one dedicated sensor and regulatory response system for every possible condition that they may encounter, the sensor systems must respond to a variety of overlapping stimuli and collate multiple forms of information to make “decisions” about the most appropriate response to a specific set of environmental conditions. Here, we analyzePseudomonas fluorescenstranscriptional responses to multiple sulfur nutrient sources to generate a predictive, computational model of the sulfur regulome. To model the regulome, we utilize a transmitter-channel-receiver scheme of information transfer and utilize principles from information theory to portrayP. fluorescensas an informatics system. This approach enables us to exploit the well-established metrics associated with information theory to model the sulfur regulome. Our computational modeling analysis results in the accurate prediction of gene expression patterns in response to the specific sulfur nutrient environments and provides insights into the molecular mechanisms ofPseudomonassensory capabilities and gene regulatory networks. In addition, modeling the bacterial regulome using the tools of information theory is a powerful and generalizable approach that will have multiple future applications to other bacterial regulomes.IMPORTANCEBacteria sense and respond to their environments using a sophisticated array of sensors and regulatory networks to optimize their fitness and survival in a constantly changing environment. Understanding how these regulatory and sensory networks work will provide the capacity to predict bacterial behaviors and, potentially, to manipulate their interactions with an environment or host. Leveraging the information theory provides useful quantitative metrics for modeling the information processing capacity of bacterial regulatory networks. As our model accurately predicted gene expression profiles in a bacterial model system, we posit that the information theory-based approaches will be important to enhance our understanding of a wide variety of bacterial regulomes and our ability to engineer bacterial sensory and regulatory networks.

Download Full-text

Comparative transcriptomics identifies differences in the regulation of the floral transition between Arabidopsis and Brassica rapa cultivars

10.1101/2020.08.26.266494 ◽

2020 ◽

Author(s):

Alexander Calderwood ◽

Jo Hepworth ◽

Shannon Woodhouse ◽

Lorelei Bilham ◽

D. Marc Jones ◽

...

Keyword(s):

Gene Expression ◽

Brassica Rapa ◽

Regulatory Networks ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Detailed Comparison ◽

Developmental Time ◽

Floral Transition ◽

Gene Regulatory

AbstractThe timing of the floral transition affects reproduction and yield, however its regulation in crops remains poorly understood. Here, we use RNA-Seq to determine and compare gene expression dynamics through the floral transition in the model species Arabidopsis thaliana and the closely related crop Brassica rapa. A direct comparison of gene expression over time between species shows little similarity, which could lead to the inference that different gene regulatory networks are at play. However, these differences can be largely resolved by synchronisation, through curve registration, of gene expression profiles. We find that different registration functions are required for different genes, indicating that there is no common ‘developmental time’ to which Arabidopsis and B. rapa can be mapped through gene expression. Instead, the expression patterns of different genes progress at different rates. We find that co-regulated genes show similar changes in synchronisation between species, suggesting that similar gene regulatory sub-network structures may be active with different wiring between them. A detailed comparison of the regulation of the floral transition between Arabidopsis and B. rapa, and between two B. rapa accessions reveals different modes of regulation of the key floral integrator SOC1, and that the floral transition in the B. rapa accessions is triggered by different pathways, even when grown under the same environmental conditions. Our study adds to the mechanistic understanding of the regulatory network of flowering time in rapid cycling B. rapa under long days and highlights the importance of registration methods for the comparison of developmental gene expression data.

Download Full-text

Convergent evolution of venom gland transcriptomes across Metazoa

10.1101/2021.07.04.451048 ◽

2021 ◽

Author(s):

Giulia Zancolli ◽

Maarten Reijnders ◽

Robert Waterhouse ◽

Marc Robinson-Rechavi

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Venom Gland ◽

Bioactive Molecules ◽

Specific Gene ◽

Animal Kingdom ◽

Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

Download Full-text

Gene expression profiles during short-term heat stress; branchingvs.massive Scleractinian corals of the Red Sea

PeerJ ◽

10.7717/peerj.1814 ◽

2016 ◽

Vol 4 ◽

pp. e1814 ◽

Cited By ~ 14

Author(s):

Keren Maor-Landaw ◽

Oren Levy

Keyword(s):

Gene Expression ◽

Heat Stress ◽

Redox Regulation ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Marker Genes ◽

Stylophora Pistillata ◽

Stress Genes

It is well-established that there is a hierarchy of susceptibilities amongst coral genera during heat-stress. However, molecular mechanisms governing these differences are still poorly understood. Here we explored if specific corals possessing different morphologies and different susceptibilities to heat stress may manifest varied gene expression patterns. We examined expression patterns of seven genes in the branching coralsStylophora pistillataandAcropora eurystomaand additionally in the massive robust coral,Poritessp. The tested genes are representatives of key cellular processes occurring during heat-stress in Cnidaria: oxidative stress, ER stress, energy metabolism, DNA repair and apoptosis. Varied response to the heat-stress, in terms of visual coral paling, algal maximum quantum yield and host gene expression was evident in the different growth forms. The two branching corals exhibited similar overall responses that differed from that of the massive coral.A. eurystomathat is considered as a susceptible species did not bleach in our experiment, but tissue sloughing was evident at 34 °C. Interestingly, in this species redox regulation genes were up-regulated at the very onset of the thermal challenge. InS. pistillata, bleaching was evident at 34 °C and most of the stress markers were already up-regulated at 32 °C, either remaining highly expressed or decreasing when temperatures reached 34 °C. The massivePoritesspecies displayed severe bleaching at 32 °C but stress marker genes were only significantly elevated at 34 °C. We postulate that by expelling the algal symbionts fromPoritestissues, oxidation damages are reduced and stress genes are activated only at a progressed stage. The differential gene expression responses exhibited here can be correlated with the literature well-documented hierarchy of susceptibilities amongst coral morphologies and genera in Eilat’s coral reef.

Download Full-text

Analysis of Gene Expression Profiles to study Malaria Vaccine Dose Efficacy & Immune Response Modulation.

10.1101/2021.08.05.454986 ◽

2021 ◽

Author(s):

Supantha Dey ◽

Harpreet Kaur ◽

Elia Brodsky ◽

Mohit Mazumder

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Vaccine Dose ◽

Principal Component ◽

Enrichment Analysis ◽

Distinct Pattern ◽

Response Modulation

Malaria is a life-threatening disease, and Africa is still one of the most affected endemic regions despite years of policy to limit infection and transmission rates. Further, studies into the variable efficacy of the vaccine are needed to provide a better understanding of protective immunity. Thus, the current study is designed to delineate the effect of the different vaccination doses on the transcriptional profiles of subjects to determine its efficacy and understand the molecular mechanisms underlying the protection this vaccine provides. Here, we used gene expression profiles of pre and post-vaccination patients after various doses of RTS,S based on 275 and 583 samples collected from the GEO datasets. At first, exploratory data analysis based Principal component analysis (PCA) shown the distinct pattern of different doses. Subsequently, differential gene expression analysis using edgeR revealed the significantly (FDR <0.005) 158 down-regulated and 61 upregulated genes between control vs. Controlled Human Malaria Infection (CHMI) samples. Further, enrichment analysis of significant genes using Annotation and GAGE tools delineate the involvement of CCL8, CXCL10, CXCL11, XCR1, CSF3, IFNB1, IFNE, IL12B, IL22, IL6, IL27, etc., genes which found to be upregulated after earlier doses but downregulated after the 3rd dose in cytokine-chemokine pathways. Notably, we identified 13 cytokine genes whose expression significantly varied during three doses. Eventually, these findings give insight into the dual role of cytokine responses in malaria pathogenesis and variations in their expression patterns after various doses of vaccination involved in protection.

Download Full-text

Upregulation of cancer-associated gene expression in activated fibroblasts in a mouse model of non-alcoholic steatohepatitis

Scientific Reports ◽

10.1038/s41598-019-56039-0 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 2

Author(s):

Masahiro Asakawa ◽

Michiko Itoh ◽

Takayoshi Suganami ◽

Takeru Sakai ◽

Sayaka Kanai ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Expression Patterns ◽

Xenograft Model ◽

Gene Expression Profiles ◽

Sequencing Analysis ◽

Alcoholic Steatohepatitis ◽

Activated Fibroblasts

AbstractNon-alcoholic steatohepatitis (NASH), characterized by chronic inflammation and fibrosis, is predicted to be the leading cause of cirrhosis and hepatocellular carcinoma (HCC) in the next decade. Although recent evidence suggests the importance of fibrosis as the strongest determinant of HCC development, the molecular mechanisms underlying NASH-induced carcinogenesis still remain unclear. Here we performed RNA sequencing analysis to compare gene expression profiles of activated fibroblasts prepared from two distinct liver fibrosis models: carbon tetrachloride–induced fibrosis as a model without obesity and HCC and genetically obese melanocortin 4 receptor–deficient (MC4R-KO) mice fed Western diet, which develop steatosis, NASH, and eventually HCC. Our data showed that activated fibroblasts exhibited distinct gene expression patterns in each etiology, and that the ‘pathways in cancer’ were selectively upregulated in the activated fibroblasts from MC4R-KO mice. The most upregulated gene in these pathways was fibroblast growth factor 9 (FGF9), which was induced by metabolic stress such as palmitate. FGF9 exerted anti-apoptotic and pro-migratory effects in fibroblasts and hepatoma cells in vitro and accelerated tumor growth in a subcutaneous xenograft model. This study reveals upregulation of cancer-associated gene expression in activated fibroblasts in NASH, which would contribute to the progression from NASH to HCC.

Download Full-text

Identification of distinct transcriptome signatures of human adipose tissue from fifteen depots

European Journal of Human Genetics ◽

10.1038/s41431-020-0681-1 ◽

2020 ◽

Vol 28 (12) ◽

pp. 1714-1725

Author(s):

Dorit Schleinitz ◽

Kerstin Krause ◽

Tobias Wohland ◽

Claudia Gebhardt ◽

Nicolas Linder ◽

...

Keyword(s):

Gene Expression ◽

Adipose Tissue ◽

Molecular Mechanisms ◽

Leptin Receptor ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Human Adipose Tissue ◽

Matrix Remodeling ◽

Fat Depots

AbstractThe functional and metabolic characteristics of specific adipose tissue (AT) depots seem to be determined by intrinsic mechanisms. We performed a comprehensive transcriptome profiling of human AT from distinct fat depots to unravel their unique features potentially explaining molecular mechanisms underlying AT distribution and their contribution to health and disease. Post-mortem AT samples of five body donors from 15 anatomical locations were collected. Global mRNA expression was measured by Illumina® Human HT-12 v4 Expression BeadChips. Data were validated using qPCR and Western Blot in a subset of ATs from seven additional body donors. Buccal and heel AT clearly separated from the “classical” subcutaneous AT depots, and perirenal and epicardial AT were distinct from visceral depots. Gene-set enrichment analyses pointed to an inflammatory environment and insulin resistance particularly in the carotid sheath AT depot. Moreover, the epicardial fat transcriptome was enriched for genes involved in extracellular matrix remodeling, inflammation, immune signaling, coagulation, thrombosis, beigeing, and apoptosis. Interestingly, a striking downregulation of the expression of leptin receptor was found in AT from heel compared with all other AT depots. The distinct gene expression patterns are likely to define fat depot specific AT functions in metabolism, energy storage, immunity, body insulation or as cushions. Improved knowledge of the gene expression profiles of various fat depots may strongly benefit studies aimed at better understanding of the genetics and the pathophysiology of obesity and adverse body fat composition.

Download Full-text

Gene expression profiles in Ciona intestinalis tailbud embryos

Development ◽

10.1242/dev.128.15.2893 ◽

2001 ◽

Vol 128 (15) ◽

pp. 2893-2904 ◽

Cited By ~ 9

Author(s):

Yutaka Satou ◽

Naohito Takatori ◽

Lixy Yamada ◽

Yasuaki Mochizuki ◽

Makoto Hamaguchi ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Sequence Similarity ◽

Expression Profiles ◽

Expression Patterns ◽

Posterior Part ◽

Gene Expression Profiles ◽

Ciona Intestinalis ◽

Sequence Information ◽

Sufficient Information

A set of 3423 expressed sequence tags derived from the Ciona intestinalis tailbud embryos was categorized into 1213 independent clusters. When compared with DNA Data Bank of Japan database, 502 clusters of them showed significant matches to reported proteins with distinct function, whereas 184 lacked sufficient information to be categorized (including reported proteins with undefined function) and 527 had no significant similarities to known proteins. Sequence similarity analyses of the 502 clusters in relation to the biosynthetic function, as well as the structure of the message population at this stage, demonstrated that 390 of them were associated with functions that many kinds of cells use, 85 with cell-cell communication and 27 with transcription factors and other gene regulatory proteins. All of the 1213 clusters were subjected to whole-mount in situ hybridization to analyze the gene expression profiles at this stage. A total of 387 clusters showed expression specific to a certain tissue or organ; 149 showed epidermis-specific expression; 34 were specific to the nervous system; 29 to endoderm; 112 to mesenchyme; 32 to notochord; and 31 to muscle. Many genes were also specifically expressed in multiple tissues. The study also highlighted characteristic gene expression profiles dependent on the tissues. In addition, several genes showed intriguing expression patterns that have not been reported previously; for example, four genes were expressed specifically in the nerve cord cells and one gene was expressed only in the posterior part of muscle cells. This study provides molecular markers for each of the tissues and/or organs that constitutes the Ciona tailbud embryo. The sequence information will also be used for further genome scientific approach to explore molecular mechanisms involved in the formation of one of the most primitive chordate body plans.

Download Full-text

Molecular characterization of photosensitizer-mediated photodynamic therapy by gene expression profiling

Human & Experimental Toxicology ◽

10.1177/0960327113485257 ◽

2013 ◽

Vol 33 (6) ◽

pp. 629-637 ◽

Cited By ~ 1

Author(s):

K-H Liu ◽

C-P Wang ◽

M-F Chang ◽

Y-W Chung ◽

P-J Lou ◽

...

Keyword(s):

Gene Expression ◽

Photodynamic Therapy ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Tumor Cell Death ◽

New Genes ◽

Specific Accumulation ◽

Underlying Mechanisms

Photodynamic therapy (PDT) is a novel cancer treatment based on the tumor-specific accumulation of a photosensitizer followed by irradiation with visible light, which induces selective tumor cell death via production of reactive oxygen species. To elucidate the underlying mechanisms, microarray analysis was used to analyze the changes in gene expression patterns during PDT induced by various photosensitizers. Cancer cells were subjected to four different photosensitizer-mediated PDT and the resulting gene expression profiles were compared. We identified many differentially expressed genes reported previously as well as new genes for which the functionfunctions in PDT are still unclear. Our current results not only advance the general understanding of PDT but also suggest that distinct molecular mechanisms are involved in different photosensitizer-mediated PDT. Elucidating the signaling mechanisms in PDT will provide information to modulate the antitumor effectiveness of PDT using various photosensitizers.

Download Full-text

Convergent evolution of venom gland transcriptomes across Metazoa

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2111392119 ◽

2022 ◽

Vol 119 (1) ◽

pp. e2111392119

Author(s):

Giulia Zancolli ◽

Maarten Reijnders ◽

Robert M. Waterhouse ◽

Marc Robinson-Rechavi

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Venom Gland ◽

Bioactive Molecules ◽

Specific Gene ◽

Animal Kingdom ◽

Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a mixture of potent bioactive molecules to subdue prey or predators—venom. This makes it one of the most widespread, convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed a comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland–specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turn, activates regulatory networks for epithelial development, cell turnover, and maintenance, which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents a first step toward an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

Download Full-text

Screening and identification of key biomarkers and related transcription factors in ovarian cancer by integrated bioinformatics analysis

10.21203/rs.3.rs-20327/v1 ◽

2020 ◽

Author(s):

Wenqiong Qin ◽

Qiang Yuan ◽

Yi Liu ◽

Ying Zeng ◽

Dandan Ke ◽

...

Keyword(s):

Gene Expression ◽

Ovarian Cancer ◽

Molecular Mechanisms ◽

Malignant Tumors ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Transcriptional Factor ◽

Ppi Network ◽

Hub Genes

Abstract Background Ovarian tumors are the most malignant tumors of all gynecological tumors, and although multiple efforts have been made to elucidate the pathogenesis, the molecular mechanisms of ovarian cancer remain unclear. Methods In this study, we used bioinformatics to identify genes involved in the carcinogenesis and progression of ovarian cancer. Three microarray datasets (GSE14407, GSE29450, and GSE54388) were downloaded from Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified. For a more in-depth understanding of the DEGs, functional and pathway enrichment analyses were performed and a protein-protein interaction (PPI) network was constructed. The associated transcriptional factor (TFs) regulation network of the DEGs was also constructed. Kaplan Meier-plotter, Gene Expression Profiling Interactive Analysis (GEPIA), the Human Protein Atlas (HPA) database and the Oncomine database were implemented to validated hub genes. Results A total of 514 DEGs were detected after the analysis of the three gene expression profiles, including 171 upregulated and 343 downregulated genes. Nine hub genes ( CCNB1, CDK1, BUB1, CDC20, CCNA2, BUB1B, AURKA, RRM2, TTK) were obtained from the PPI network. Survival analysis showed that high expression levels of seven hub genes ( CCNB1, BUB1, BUB1B, CCNA2, AURKA, CDK1, and RRM2) were associated with worse overall survival (OS). All of seven hub genes were discovered highly expressed in ovarian cancer samples compared to normal ovary samples in GEPIA. Immunostaining results from the HPA database suggested that the expressions of CCNB1, CCNA2, AURKA, and CDK1 proteins were increased in ovarian cancer tissues, and Oncomine analysis indicated that the expression patterns of BUB1B, CCNA2, AURKA, CCNB1, CDK1, and BUB1 have associated with patient clinicopathological information. From the gene-transcriptional factor network, key transcriptional factors, such as POLR2A, ZBTB11, KLF9, and ELF1, were identified with close interactions with these hub genes. Conclusion We identified six significant DEGs with poor prognosis in ovarian cancer, which could be of potential biomarkers for ovarian cancer patients.

Download Full-text