scholarly journals Novel Lesional Transcriptional Signature Separates Atherosclerosis With and Without Diabetes in Yorkshire Swine and Humans

2021 ◽  
Author(s):  
Stefan Haemmig ◽  
Ali Hashemi Gheinani ◽  
Marina Zaromytidou ◽  
Gerasimos Siasos ◽  
Ahmet Umit Coskun ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Rna Sequencing ◽  
Atherosclerotic Lesion ◽  
Machine Learning Algorithms ◽  
Sequencing Data ◽  
Atherosclerosis Progression ◽  
Transcriptional Signature ◽  
Il Interleukin ◽  
Evolutionarily Conserved ◽  
Conserved Gene

Objective: Accelerated atherosclerosis in diabetes constitutes an ongoing challenge despite optimal medical therapies. This study aimed to identify evolutionarily conserved lesion-based regulatory signaling networks in diabetic versus nondiabetic conditions during the development of atherosclerosis in an initial translational effort to provide insights for targets. Approach and Results: Serial 3-mm coronary artery segments of hypercholesterolemic Yorkshire swine and diabetic-hypercholesterolemic swine were characterized as mild, moderate, or severe phenotypic manifestations of coronary atherosclerosis based on histopathologic examination. Lesional RNA sequencing was performed (n=3–8 lesions per group) corresponding to increasing phenotypic severity. Differentially expressed genes, transcription factors, upstream regulators, and hubs were validated using the NanoString technology and a human atherosclerotic specimen cohort. Despite similar stage histopathologic characterization of lesions, genome-wide transcriptomics revealed gene sets and nodal signaling pathways uniquely expressed in diabetic lesions including signaling pathways for Th17, IL (interleukin)-17F, TWEAK (TNF [tumor necrosis factor]-related weak inducer of apoptosis), CD27, and PI3K/Akt. In contrast, pathways of nondiabetic lesions involved TREM-1 and Th1 and Th2 responses during the initiation stage, whereas networks for mitochondrial dysfunction, oxidative phosphorylation, and lipid metabolism emerged with progression. RNA sequencing data were validated in a human atherosclerosis specimen cohort using machine learning algorithms. F8 , MAPKAPK3 , and ITGB1 emerged as powerful genes for clustering diabetic versus nondiabetic lesions and for separating different degrees of atherosclerosis progression. Conclusions: This study identifies evolutionarily conserved gene signatures and signaling pathways in a stage-specific manner that successfully distinguishes diabetes- and non–diabetes-associated atherosclerosis. These findings establish new molecular insights and therapeutic opportunities to address accelerated atherosclerotic lesion formation in diabetes.

scholarly journals The Meaning of the Microprocessor: Accounting for Evolution of Structural-Functional Novelty in the Canonical microRNA Biogenesis Pathway

2019 ◽  
Author(s):  
Jeffrey Robinson
Keyword(s):  
Green Plant ◽  
Review Literature ◽  
Sequencing Data ◽  
Microrna Biogenesis ◽  
Detection And Identification ◽  
Evolutionarily Conserved ◽  
Sequence Elements ◽  
Mirna Sequencing ◽  
Bona Fide ◽  
Conserved Gene

It is standard to identify and compare genomic or mRNA sequence of the Drosha and Pasha genes subsidiary to detection and identification of novel microRNAs in newly sequenced taxa or review of previous deep sequencing data. Drosha and Pasha are the key, conserved gene members of the ‘microprocessor’ protein complex which facilitates nuclear nuclear-localized, pri- to pre-miRNA processing miRNAs of the canonical eumetazoan complement. Because of the necessity of the microprocessor for production of canonical eumetazoan miRNA, the detection of both (1) bona fide microRNAs and (2) presence of Drosha/Pasha orthologs (or homologs) is often presented as sufficient to represent a functional canonical eumetazoan microRNA biogenesis pathway. However, the functional role of the Drosha and Pasha homologs is not commonly experimentally investigated in non-model taxa, and therefore the assumption is not necessarily valid. Differentiation of ‘bona fide miRNAs’, opposed to ‘non-bona fide’ small RNAs of similar size, are also necessary for miRNA sequencing projects. Recent rubrics are based on structural and sequence elements of the miRNAs themselves, however these inclusion criteria include paraphyletic groupings of miRNAs, for example eumetazoan miRNAs and streptophyte (green plant) miRNAs which are not produced by the Drosha/Pasha microprocessor mechanism. Therefore, a dichotomy exists between the structural definitions for miRNAs and understanding of the evolutionarily conserved function of the microprocessor and its components. In this article, I review literature in the context of this topic and discuss philosophical ramifications for understanding the importance of the microprocessor in understanding the evolutionary and molecular origins of miRNA.

scholarly journals Cell type classification and discovery across diseases, technologies and tissues reveals conserved gene signatures and enables standardized single-cell readouts

2021 ◽  
Author(s):  
Virginia Savova ◽  
Mathew Chamberlain ◽  
Richa Hanamsagar ◽  
Frank Nestle ◽  
Emanuele de Rinaldis
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Drug Targets ◽  
Sequencing Data ◽  
Candidate Drug ◽  
Machine Learning Approach ◽  
Single Cell Rna Sequencing ◽  
Conserved Gene ◽  
Cellular Phenotypes ◽  
Type Classification

Abstract Autoimmune diseases are a major cause of mortality1,2. Current treatments often yield severe insult to host tissue. It is hypothesized that improved therapies will target pathogenic cells selectively and thus reduce or eliminate severe side effects, and potentially induce robust immune tolerance3. However, it remains challenging to systematically identify which cellular phenotypes are present in cellular ensembles. Here, we present a novel machine learning approach, Signac, which uses neural networks trained with flow-sorted gene expression data to classify cellular phenotypes in single cell RNA-sequencing data. We demonstrate that Signac accurately classified single cell RNA-sequencing data across diseases, technologies, species and tissues. Then we applied Signac to identify known and novel immune-relevant candidate drug targets (n = 12) in rheumatoid arthritis. A full release of this workflow can be found at our GitHub repository (https://github.com/mathewchamberlain/Signac).

scholarly journals Cell type classification and discovery across diseases, technologies and tissues reveals conserved gene signatures and enables standardized single-cell readouts

2021 ◽  
Author(s):  
Mathew Chamberlain ◽  
Richa Hanamsagar ◽  
Frank O. Nestle ◽  
Emanuele de Rinaldis ◽  
Virginia Savova
Keyword(s):  
Precision Medicine ◽  
Single Cell ◽  
Rna Sequencing ◽  
Drug Targets ◽  
Sequencing Data ◽  
Candidate Drug ◽  
Machine Learning Approach ◽  
Single Cell Rna Sequencing ◽  
Conserved Gene ◽  
Cellular Phenotypes

ABSTRACTAutoimmune diseases are a major cause of mortality1,2. Current treatments often yield severe insult to host tissue. It is hypothesized that improved “precision medicine” therapies will target pathogenic cells selectively and thus reduce or eliminate severe side effects, and potentially induce robust immune tolerance3. However, it remains challenging to systematically identify which cellular phenotypes are present in cellular ensembles. Here, we present a novel machine learning approach, Signac, which uses neural networks trained with flow-sorted gene expression data to classify cellular phenotypes in single cell RNA-sequencing data. We demonstrate that Signac accurately classified single cell RNA-sequencing data across diseases, technologies, species and tissues. Then we applied Signac to identify known and novel immune-relevant precision medicine candidate drug targets (n = 12) in rheumatoid arthritis. A full release of this workflow can be found at our GitHub repository (https://github.com/mathewchamberlain/Signac).

Dynamic Role of Macrophage Sub Types for Development of Atherosclerosis and Potential Use of Herbal Immunomodulators as Imminent Therapeutic Strategy

2020 ◽  
Vol 18 ◽  
Author(s):  
Parimalanandhini Duraisamy ◽  
Sangeetha Ravi ◽  
Mahalakshmi Krishnan ◽  
Catherene M. Livya ◽  
Beulaja Manikandan ◽  
...  
Keyword(s):  
Foam Cell ◽  
Cell Formation ◽  
Atherosclerotic Lesion ◽  
Foam Cell Formation ◽  
Atherosclerosis Progression ◽  
Proinflammatory Mediators ◽  
M1 Macrophage ◽  
Tnf Α ◽  
Inflammatory Site

: Atherosclerosis, a major contributor to cardiovascular disease is a global alarm causing mortality worldwide. Being a progressive disease in the arteries, it mainly causes recruitment of monocytes to the inflammatory sites and subside pathological conditions. Monocyte-derived macrophage mainly acts in foam cell formation by engorging the LDL molecules, oxidizes it into Ox-LDL and leads to plaque deposit development. Macrophages in general differentiate, proliferate and undergo apoptosis at the inflammatory site. Frequently two subtypes of macrophages M1 and M2 has to act crucially in balancing the micro-environmental conditions of endothelial cells in arteries. The productions of proinflammatory mediators like IL-1, IL-6, TNF-α by M1 macrophage has atherogenic properties majorly produced during the early progression of atherosclerotic plaques. To counteract cytokine productions and M1-M2 balance, secondary metabolites (phytochemicals) from plants act as a therapeutic agent in alleviating atherosclerosis progression. This review summarizes the fundamental role of the macrophage in atherosclerotic lesion formation along with its plasticity characteristic as well as recent therapeutic strategies using herbal components and anti-inflammatory cytokines as potential immunomodulators.

scholarly journals HEDGEHOG/GLI Modulates the PRR11-SKA2 Bidirectional Transcription Unit in Lung Squamous Cell Carcinomas

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 120
Author(s):  
Yiyun Sun ◽  
Dandan Xu ◽  
Chundong Zhang ◽  
Yitao Wang ◽  
Lian Zhang ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Squamous Cell ◽  
Gene Pair ◽  
Gene List ◽  
Ectopic Expression ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Gene Set

We previously demonstrated that proline-rich protein 11 (PRR11) and spindle and kinetochore associated 2 (SKA2) constituted a head-to-head gene pair driven by a prototypical bidirectional promoter. This gene pair synergistically promoted the development of non-small cell lung cancer. However, the signaling pathways leading to the ectopic expression of this gene pair remains obscure. In the present study, we first analyzed the lung squamous cell carcinoma (LSCC) relevant RNA sequencing data from The Cancer Genome Atlas (TCGA) database using the correlation analysis of gene expression and gene set enrichment analysis (GSEA), which revealed that the PRR11-SKA2 correlated gene list highly resembled the Hedgehog (Hh) pathway activation-related gene set. Subsequently, GLI1/2 inhibitor GANT-61 or GLI1/2-siRNA inhibited the Hh pathway of LSCC cells, concomitantly decreasing the expression levels of PRR11 and SKA2. Furthermore, the mRNA expression profile of LSCC cells treated with GANT-61 was detected using RNA sequencing, displaying 397 differentially expressed genes (203 upregulated genes and 194 downregulated genes). Out of them, one gene set, including BIRC5, NCAPG, CCNB2, and BUB1, was involved in cell division and interacted with both PRR11 and SKA2. These genes were verified as the downregulated genes via RT-PCR and their high expression significantly correlated with the shorter overall survival of LSCC patients. Taken together, our results indicate that GLI1/2 mediates the expression of the PRR11-SKA2-centric gene set that serves as an unfavorable prognostic indicator for LSCC patients, potentializing new combinatorial diagnostic and therapeutic strategies in LSCC.

RNA Sequencing Data from Human Intracranial Aneurysm Tissue Reveals a Complex Inflammatory Environment Associated with Rupture

2021 ◽  
Author(s):  
Vincent M. Tutino ◽  
Haley R. Zebraski ◽  
Hamidreza Rajabzadeh-Oghaz ◽  
Lee Chaves ◽  
Adam A. Dmytriw ◽  
...  
Keyword(s):  
Intracranial Aneurysm ◽  
Rna Sequencing ◽  
Sequencing Data

Hyperactivation of RAP1 and JAK/STAT Signaling Pathways Contributes to Fibrosis during the Formation of Nasal Capsular Contraction

2021 ◽  
pp. 1-12
Author(s):  
Meng Wu ◽  
Ming Li ◽  
Hong-Ju Xie ◽  
Hong-Wei Liu
Keyword(s):  
Signaling Pathways ◽  
Type I Collagen ◽  
Ex Vivo ◽  
Capsular Contracture ◽  
Silicone Implant ◽  
Type I ◽  
Loss Of Function ◽  
Sequencing Data ◽  
Functional Changes ◽  
Stat Signaling

Silicone implant-based augmentation rhinoplasty or mammoplasty induces capsular contracture, which has been acknowledged as a process that develops an abnormal fibrotic capsule associated with the immune response to allogeneic materials. However, the signaling pathways leading to the nasal fibrosis remain poorly investigated. We aimed to explore the molecular mechanism underlying the pathogenesis of nasal capsular contracture, with a specific research interest in the signaling pathways involved in fibrotic development at the advanced stage of contracture. By examining our recently obtained RNA sequencing data and global gene expression profiling between grade II and grade IV nasal capsular tissues, we found that both the RAP1 and JAK/STAT signaling pathways were hyperactive in the contracted capsules. This was verified on quantitative real-time PCR which demonstrated upregulation of most of the representative component signatures in these pathways. Loss-of-function assays through siRNA-mediated Rap1 silencing and/or small molecule-directed inhibition of JAK/STAT pathway in ex vivo primary nasal fibroblasts caused a series of dramatic behavioral and functional changes, including decreased cell viability, increased apoptosis, reduced secretion of proinflammatory cytokines, and synthesis of type I collagen, compared to control cells, and indicating the essential role of the RAP1 and JAK/STAT signaling pathways in nasal capsular fibrosis. Our results sheds light on targeting downstream signaling pathways for the prevention and therapy of silicone implant-induced nasal capsular contracture.

scholarly journals In-depth transcriptomic analysis of human retina reveals molecular mechanisms underlying diabetic retinopathy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kolja Becker ◽  
Holger Klein ◽  
Eric Simon ◽  
Coralie Viollet ◽  
Christian Haslinger ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Rna Sequencing ◽  
Molecular Mechanisms ◽  
Vision Loss ◽  
Ganglion Cells ◽  
Expression Profiles ◽  
Cell Types ◽  
Sequencing Data ◽  
Disease Stages ◽  
Post Transcriptional Regulation

AbstractDiabetic Retinopathy (DR) is among the major global causes for vision loss. With the rise in diabetes prevalence, an increase in DR incidence is expected. Current understanding of both the molecular etiology and pathways involved in the initiation and progression of DR is limited. Via RNA-Sequencing, we analyzed mRNA and miRNA expression profiles of 80 human post-mortem retinal samples from 43 patients diagnosed with various stages of DR. We found differentially expressed transcripts to be predominantly associated with late stage DR and pathways such as hippo and gap junction signaling. A multivariate regression model identified transcripts with progressive changes throughout disease stages, which in turn displayed significant overlap with sphingolipid and cGMP–PKG signaling. Combined analysis of miRNA and mRNA expression further uncovered disease-relevant miRNA/mRNA associations as potential mechanisms of post-transcriptional regulation. Finally, integrating human retinal single cell RNA-Sequencing data revealed a continuous loss of retinal ganglion cells, and Müller cell mediated changes in histidine and β-alanine signaling. While previously considered primarily a vascular disease, attention in DR has shifted to additional mechanisms and cell-types. Our findings offer an unprecedented and unbiased insight into molecular pathways and cell-specific changes in the development of DR, and provide potential avenues for future therapeutic intervention.

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