scholarly journals Convergent evolution of venom gland transcriptomes across Metazoa

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.

scholarly journals Convergent evolution of venom gland transcriptomes across Metazoa

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.

scholarly journals Mechanisms of YAP/TAZ transcriptional control

Cell Stress ◽  
2021 ◽  
Vol 5 (11) ◽  
pp. 167-172
Author(s):  
Giusy Battilana ◽  
Francesca Zanconato ◽  
Stefano Piccolo
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Transcriptional Control ◽  
Cell Transformation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Chromatin Regulators ◽  
Small Set

Dysregulated gene expression is intrinsic to cell transformation, tumorigenesis and metastasis. Cancer-specific gene-expression profiles stem from gene regulatory networks fueled by genetic and epigenetic defects, and by abnormal signals of the tumor microenvironment. These oncogenic signals ultimately engage the transcriptional machinery on the cis -regulatory elements of a host of effector genes, through recruitment of transcription factors (TFs), co-activators and chromatin regulators. That said, whether gene -expression in cancer cells is the chaotic product of myriad regulations or rather a relatively ordered process orchestrated by few TFs (master regulators) has long remained enigmatic. Recent work on the YAP/TAZ co-activators has been instrumental to break new ground into this outstanding issue, revealing that tumor cells hijack growth programs that are active during development and regeneration through engagement of a small set of interconnected TFs and their nuclear partners.

scholarly journals Inferring propensity amongst lung and breast carcinomas via overlapped gene expression profiles

2017 ◽  
Author(s):  
Rajni Jaiswal ◽  
Sabin Dhakal ◽  
Shaurya Jauhari
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Biological Networks ◽  
Drug Targets ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Specific Gene ◽  
Cancer Data ◽  
Gene Regulatory

ABSTRACTReconstruction of biological networks for topological analyses helps in correlation identification between various types of biomarkers. These networks have been vital components of System Biology in present era. Genes are the basic physical and structural unit of heredity. Genes act as instructions to make molecules called proteins. Alterations in the normal sequence of these genes are the root cause of various diseases and cancer is the prominent example disease caused by gene alteration or mutation. These slight alterations can be detected by microarray analysis. The high throughput data obtained by microarray experiments aid scientists in reconstructing cancer specific gene regulatory networks. The purpose of experiment performed is to find out the overlapping of the gene expression profiles of breast and lung cancer data, so that the common hub genes can be sifted and utilized as drug targets which could be used for the treatment of diseased conditions. In this study, first the differentially expressed genes have been identified (lung cancer and breast cancer), followed by a filtration approach and most significant genes are chosen using paired t-test and gene regulatory network construction. The obtained result has been checked and validated with the available databases and literature.

scholarly journals Modeling thePseudomonasSulfur Regulome by Quantifying the Storage and Communication of Information

mSystems ◽  
2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Peter E. Larsen ◽  
Sarah Zerbs ◽  
Philip D. Laible ◽  
Frank R. Collart ◽  
Peter Korajczyk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Information Theory ◽  
Information Transfer ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Transcriptional Responses ◽  
Content Type

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.

scholarly journals Modulation of the Immune Response by Deferasirox in Myelodysplastic Syndrome Patients

2021 ◽  
Vol 14 (1) ◽  
pp. 41
Author(s):  
Hana Votavova ◽  
Zuzana Urbanova ◽  
David Kundrat ◽  
Michaela Dostalova Merkerova ◽  
Martin Vostry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Blood Cell ◽  
Myelodysplastic Syndrome ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Adaptive Immune Response ◽  
Gene Expression Profiles ◽  
Iron Chelator ◽  
Multiple Cancer

Deferasirox (DFX) is an oral iron chelator used to reduce iron overload (IO) caused by frequent blood cell transfusions in anemic myelodysplastic syndrome (MDS) patients. To study the molecular mechanisms by which DFX improves outcome in MDS, we analyzed the global gene expression in untreated MDS patients and those who were given DFX treatment. The gene expression profiles of bone marrow CD34+ cells were assessed by whole-genome microarrays. Initially, differentially expressed genes (DEGs) were determined between patients with normal ferritin levels and those with IO to address the effect of excessive iron on cellular pathways. These DEGs were annotated to Gene Ontology terms associated with cell cycle, apoptosis, adaptive immune response and protein folding and were enriched in cancer-related pathways. The deregulation of multiple cancer pathways in iron-overloaded patients suggests that IO is a cofactor favoring the progression of MDS. The DEGs between patients with IO and those treated with DFX were involved predominantly in biological processes related to the immune response and inflammation. These data indicate DFX modulates the immune response mainly via neutrophil-related genes. Suppression of negative regulators of blood cell differentiation essential for cell maturation and upregulation of heme metabolism observed in DFX-treated patients may contribute to the hematopoietic improvement.

Sign in / Sign up

Export Citation Format

Share Document