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Bailey ML, Nixon C, Rusch DB, Buechlein A, Rosvall KA, Bentz AB. Maternal social environment shapes yolk testosterone allocation and embryonic neural gene expression in tree swallows. Horm Behav 2024; 163:105561. [PMID: 38759417 DOI: 10.1016/j.yhbeh.2024.105561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 05/03/2024] [Accepted: 05/06/2024] [Indexed: 05/19/2024]
Abstract
Offspring from females breeding in competitive social environments are often exposed to more testosterone (T) during embryonic development, which can affect traits from growth to behavior in potentially adaptive ways. Despite the important role of maternally derived steroids in shaping offspring development, the molecular mechanisms driving these processes are currently unclear. Here, we use tree swallows (Tachycineta bicolor) to explore the effects of the maternal social environment on yolk T concentrations and genome-wide patterns of neural gene expression in embryos. We measured aggressive interactions among females breeding at variable densities and collected their eggs at two timepoints, including the day laid to measure yolk T concentrations and on embryonic day 11 to measure gene expression in whole brain samples. We found that females breeding in high-density sites experienced elevated rates of physical aggression and their eggs had higher yolk T concentrations. A differential gene expression and weighted gene co-expression network analysis indicated that embryos from high-density sites experienced an upregulation of genes involved in hormone, circulatory, and immune processes, and these gene expression patterns were correlated with yolk T levels and aggression. Genes implicated in neural development were additionally downregulated in embryos from high-density sites. These data highlight how early neurogenomic processes may be affected by the maternal social environment, giving rise to phenotypic plasticity in offspring.
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Affiliation(s)
- M Leigh Bailey
- School of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA
| | - Cameron Nixon
- School of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA
| | - Douglas B Rusch
- Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN, USA
| | - Aaron Buechlein
- Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN, USA
| | | | - Alexandra B Bentz
- School of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA; Department of Biology, Indiana University, Bloomington, IN 47405, USA.
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2
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Kim SH, Chun C, Yoon TY. Profiling of BCLxL Protein Complexes in Non-Small Cell Lung Cancer Cells via Multiplexed Single-Molecule Pull-Down and Co-Immunoprecipitation. Anal Chem 2024; 96:8932-8941. [PMID: 38728439 DOI: 10.1021/acs.analchem.3c05801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
We introduce multiplexed single-molecule pull-down and co-immunoprecipitation, named m-SMPC, an analysis tool for profiling multiple protein complexes within a single reaction chamber using single-molecule fluorescence imaging. We employed site-selective conjugation of biotin and fluorescent dye directly onto the monoclonal antibodies, which completed an independent sandwich immunoassay without the issue of host cross-reactivity. We applied this technique to profile endogenous B-cell lymphoma extra-large (BCLxL) complexes in non-small cell lung cancer (NSCLC) cells. Up to three distinct BCLxL complexes were successfully detected simultaneously within a single reaction chamber without fluorescence signal crosstalk. Notably, the NSCLC cell line EBC-1 exhibited high BCLxL-BAX and BCLxL-BAK levels, which closely paralleled a strong response to the BCLxL inhibitor A-1331852. This streamlined method offers the potential for quantitative biomarkers derived from protein complex profiling, paving the way for their application in protein complex-targeted therapies.
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Affiliation(s)
- Shi Ho Kim
- Department of Biomarker Discovery, PROTEINA Co., Ltd, Seoul 08826, South Korea
| | - Changju Chun
- School of Biological Sciences, Seoul National University, Seoul 08826, South Korea
- Institute for Molecular Biology and Genetics, Seoul National University, Seoul 08826, South Korea
| | - Tae-Young Yoon
- Department of Biomarker Discovery, PROTEINA Co., Ltd, Seoul 08826, South Korea
- School of Biological Sciences, Seoul National University, Seoul 08826, South Korea
- Institute for Molecular Biology and Genetics, Seoul National University, Seoul 08826, South Korea
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3
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Gilbert CJ, Rabolli CP, Golubeva VA, Sattler KM, Wang M, Ketabforoush A, Arnold WD, Lepper C, Accornero F. YTHDF2 governs muscle size through a targeted modulation of proteostasis. Nat Commun 2024; 15:2176. [PMID: 38467649 PMCID: PMC10928198 DOI: 10.1038/s41467-024-46546-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 02/28/2024] [Indexed: 03/13/2024] Open
Abstract
The regulation of proteostasis is fundamental for maintenance of muscle mass and function. Activation of the TGF-β pathway drives wasting and premature aging by favoring the proteasomal degradation of structural muscle proteins. Yet, how this critical post-translational mechanism is kept in check to preserve muscle health remains unclear. Here, we reveal the molecular link between the post-transcriptional regulation of m6A-modified mRNA and the modulation of SMAD-dependent TGF-β signaling. We show that the m6A-binding protein YTHDF2 is essential to determining postnatal muscle size. Indeed, muscle-specific genetic deletion of YTHDF2 impairs skeletal muscle growth and abrogates the response to hypertrophic stimuli. We report that YTHDF2 controls the mRNA stability of the ubiquitin ligase ASB2 with consequences on anti-growth gene program activation through SMAD3. Our study identifies a post-transcriptional to post-translational mechanism for the coordination of gene expression in muscle.
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Affiliation(s)
- Christopher J Gilbert
- Department of Physiology and Cell Biology, Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Charles P Rabolli
- Department of Physiology and Cell Biology, Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Volha A Golubeva
- Department of Physiology and Cell Biology, Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA
| | - Kristina M Sattler
- Department of Physiology and Cell Biology, Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA
| | - Meifang Wang
- NextGen Precision Health, University of Missouri, Columbia, MO, USA
- Department of Physical Medicine and Rehabilitation, University of Missouri, Columbia, MO, USA
| | - Arsh Ketabforoush
- NextGen Precision Health, University of Missouri, Columbia, MO, USA
- Department of Physical Medicine and Rehabilitation, University of Missouri, Columbia, MO, USA
| | - W David Arnold
- NextGen Precision Health, University of Missouri, Columbia, MO, USA
- Department of Physical Medicine and Rehabilitation, University of Missouri, Columbia, MO, USA
- Department of Neurology, University of Missouri, Columbia, MO, USA
- Department of Medical Pharmacology and Physiology, University of Missouri, Columbia, MO, USA
- Division of Neuromuscular Disorders, Department of Neurology, The Ohio State University, Columbus, OH, USA
- Department of Physical Medicine and Rehabilitation, The Ohio State University, Columbus, OH, USA
| | - Christoph Lepper
- Department of Physiology and Cell Biology, Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA
| | - Federica Accornero
- Department of Physiology and Cell Biology, Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA.
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA.
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4
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Liu Z, Wong HM, Chen X, Lin J, Zhang S, Yan S, Wang F, Li X, Wong KC. MotifHub: Detection of trans-acting DNA motif group with probabilistic modeling algorithm. Comput Biol Med 2024; 168:107753. [PMID: 38039889 DOI: 10.1016/j.compbiomed.2023.107753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 10/30/2023] [Accepted: 11/20/2023] [Indexed: 12/03/2023]
Abstract
BACKGROUND Trans-acting factors are of special importance in transcription regulation, which is a group of proteins that can directly or indirectly recognize or bind to the 8-12 bp core sequence of cis-acting elements and regulate the transcription efficiency of target genes. The progressive development in high-throughput chromatin capture technology (e.g., Hi-C) enables the identification of chromatin-interacting sequence groups where trans-acting DNA motif groups can be discovered. The problem difficulty lies in the combinatorial nature of DNA sequence pattern matching and its underlying sequence pattern search space. METHOD Here, we propose to develop MotifHub for trans-acting DNA motif group discovery on grouped sequences. Specifically, the main approach is to develop probabilistic modeling for accommodating the stochastic nature of DNA motif patterns. RESULTS Based on the modeling, we develop global sampling techniques based on EM and Gibbs sampling to address the global optimization challenge for model fitting with latent variables. The results reflect that our proposed approaches demonstrate promising performance with linear time complexities. CONCLUSION MotifHub is a novel algorithm considering the identification of both DNA co-binding motif groups and trans-acting TFs. Our study paves the way for identifying hub TFs of stem cell development (OCT4 and SOX2) and determining potential therapeutic targets of prostate cancer (FOXA1 and MYC). To ensure scientific reproducibility and long-term impact, its matrix-algebra-optimized source code is released at http://bioinfo.cs.cityu.edu.hk/MotifHub.
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Affiliation(s)
- Zhe Liu
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China
| | - Hiu-Man Wong
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China
| | - Xingjian Chen
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China
| | - Jiecong Lin
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China
| | - Shixiong Zhang
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China
| | - Shankai Yan
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China
| | - Fuzhou Wang
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China
| | - Xiangtao Li
- School of Artificial Intelligence, Jilin University, Jilin, China
| | - Ka-Chun Wong
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China.
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5
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Martin B, Suter DM. Gene expression flux analysis reveals specific regulatory modalities of gene expression. iScience 2023; 26:107758. [PMID: 37701574 PMCID: PMC10493597 DOI: 10.1016/j.isci.2023.107758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 06/02/2023] [Accepted: 08/24/2023] [Indexed: 09/14/2023] Open
Abstract
The level of a given protein is determined by the synthesis and degradation rates of its mRNA and protein. While several studies have quantified the contribution of different gene expression steps in regulating protein levels, these are limited by using equilibrium approximations in out-of-equilibrium biological systems. Here, we introduce gene expression flux analysis to quantitatively dissect the dynamics of the expression level for specific proteins and use it to analyze published transcriptomics and proteomics datasets. Our analysis reveals distinct regulatory modalities shared by sets of genes with clear functional signatures. We also find that protein degradation plays a stronger role than expected in the adaptation of protein levels. These findings suggest that shared regulatory strategies can lead to versatile responses at the protein level and highlight the importance of going beyond equilibrium approximations to dissect the quantitative contribution of different steps of gene expression to protein dynamics.
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Affiliation(s)
- Benjamin Martin
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - David M. Suter
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
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Gürsel Ürün Y, Budak M, Usturalı Keskin E. Methylation status, mRNA and protein expression of the SMAD4 gene in patients with non-melanocytic skin cancers. Mol Biol Rep 2023; 50:7295-7304. [PMID: 37428273 DOI: 10.1007/s11033-023-08656-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 06/29/2023] [Indexed: 07/11/2023]
Abstract
BACKGROUND SMAD4 is a potent tumor suppressor. SMAD4 loss increases genomic instability and plays a critical role in the DNA damage response that leads to skin cancer development. We aimed to investigate SMAD4 methylation effects on mRNA and protein expression of SMAD4 in cancer and healthy tissues from patients with basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (cSCC), and basosquamous skin cancer (BSC). METHODS AND RESULTS The study included 17 BCC, 24 cSCC and nine BSC patients. DNA and RNA were isolated from cancerous and healthy tissues following punch biopsy. Methylation-specific polymerase chain reaction (PCR) and real-time quantitative PCR methods were used to examine SMAD4 promoter methylation and SMAD4 mRNA levels, respectively. The percentage and intensity of staining of the SMAD4 protein were determined by immunohistochemistry. The percentage of SMAD4 methylation was increased in the patients with BCC (p = 0.007), cSCC (p = 0.004), and BSC (p = 0.018) compared to the healthy tissue. SMAD4 mRNA expression was decreased in the patients with BCC (p˂0.001), cSCC (p˂0.001), and BSC (p = 0.008). The staining characteristic of SMAD4 protein was negative in the cancer tissues of the patients with cSCC (p = 0.00). Lower SMAD4 mRNA levels were observed in the poorly differentiated cSCC patients (p = 0.001). The staining characteristics of the SMAD4 protein were related to age and chronic sun exposure. CONCLUSIONS Hypermethylation of SMAD4 and reduced SMAD4 mRNA expression were found to play a role in the pathogenesis of BCC, cSCC, and BSC. A decrease in SMAD4 protein expression level was observed only in cSCC patients. This suggests that epigenetic alterations to the SMAD4 gene are associated with cSCC. TRIAL REGISTRATION The name of the trial register: SMAD4 Methylation and Expression Levels in Non-melanocytic Skin Cancers; SMAD4 Protein Positivity. The registration number: NCT04759261 ( https://clinicaltrials.gov/ct2/results?term=NCT04759261 ).
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Affiliation(s)
- Yıldız Gürsel Ürün
- Department of Dermatology and Venereology, Faculty of Medicine, Trakya University, Edirne, Turkey.
| | - Metin Budak
- Department of Biophysics, Faculty of Medicine, Trakya University, Edirne, Turkey
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Ellis D, Roy A, Datta S. Clustering single-cell multimodal omics data with jrSiCKLSNMF. Front Genet 2023; 14:1179439. [PMID: 37359367 PMCID: PMC10288154 DOI: 10.3389/fgene.2023.1179439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 05/23/2023] [Indexed: 06/28/2023] Open
Abstract
Introduction: The development of multimodal single-cell omics methods has enabled the collection of data across different omics modalities from the same set of single cells. Each omics modality provides unique information about cell type and function, so the ability to integrate data from different modalities can provide deeper insights into cellular functions. Often, single-cell omics data can prove challenging to model because of high dimensionality, sparsity, and technical noise. Methods: We propose a novel multimodal data analysis method called joint graph-regularized Single-Cell Kullback-Leibler Sparse Non-negative Matrix Factorization (jrSiCKLSNMF, pronounced "junior sickles NMF") that extracts latent factors shared across omics modalities within the same set of single cells. Results: We compare our clustering algorithm to several existing methods on four sets of data simulated from third party software. We also apply our algorithm to a real set of cell line data. Discussion: We show overwhelmingly better clustering performance than several existing methods on the simulated data. On a real multimodal omics dataset, we also find our method to produce scientifically accurate clustering results.
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8
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Stokes T, Cen HH, Kapranov P, Gallagher IJ, Pitsillides AA, Volmar C, Kraus WE, Johnson JD, Phillips SM, Wahlestedt C, Timmons JA. Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq. ADVANCED GENETICS (HOBOKEN, N.J.) 2023; 4:2200024. [PMID: 37288167 PMCID: PMC10242409 DOI: 10.1002/ggn2.202200024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Indexed: 06/09/2023]
Abstract
Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.
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Affiliation(s)
- Tanner Stokes
- Faculty of ScienceMcMaster UniversityHamiltonL8S 4L8Canada
| | - Haoning Howard Cen
- Life Sciences InstituteUniversity of British ColumbiaVancouverV6T 1Z3Canada
| | | | - Iain J Gallagher
- School of Applied SciencesEdinburgh Napier UniversityEdinburghEH11 4BNUK
| | | | | | | | - James D. Johnson
- Life Sciences InstituteUniversity of British ColumbiaVancouverV6T 1Z3Canada
| | | | | | - James A. Timmons
- Miller School of MedicineUniversity of MiamiMiamiFL33136USA
- William Harvey Research InstituteQueen Mary University LondonLondonEC1M 6BQUK
- Augur Precision Medicine LTDStirlingFK9 5NFUK
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Shi T, Yu H, Blair RH. Integrated regulatory and metabolic networks of the tumor microenvironment for therapeutic target prioritization. Stat Appl Genet Mol Biol 2023; 22:sagmb-2022-0054. [PMID: 37988745 DOI: 10.1515/sagmb-2022-0054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 09/28/2023] [Indexed: 11/23/2023]
Abstract
Translation of genomic discovery, such as single-cell sequencing data, to clinical decisions remains a longstanding bottleneck in the field. Meanwhile, computational systems biological models, such as cellular metabolism models and cell signaling pathways, have emerged as powerful approaches to provide efficient predictions in metabolites and gene expression levels, respectively. However, there has been limited research on the integration between these two models. This work develops a methodology for integrating computational models of probabilistic gene regulatory networks with a constraint-based metabolism model. By using probabilistic reasoning with Bayesian Networks, we aim to predict cell-specific changes under different interventions, which are embedded into the constraint-based models of metabolism. Applications to single-cell sequencing data of glioblastoma brain tumors generate predictions about the effects of pharmaceutical interventions on the regulatory network and downstream metabolisms in different cell types from the tumor microenvironment. The model presents possible insights into treatments that could potentially suppress anaerobic metabolism in malignant cells with minimal impact on other cell types' metabolism. The proposed integrated model can guide therapeutic target prioritization, the formulation of combination therapies, and future drug discovery. This model integration framework is also generalizable to other applications, such as different cell types, organisms, and diseases.
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Affiliation(s)
- Tiange Shi
- University at Buffalo, Biostatistics, Buffalo, USA
| | - Han Yu
- Roswell Park Comprehensive Cancer Center, Biostatistics and Bioinformatics, Buffalo, USA
| | - Rachael Hageman Blair
- University at Buffalo, Biostatistics, Institute for Artificial Intelligence and Data Science, Buffalo, USA
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10
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Jiang T. Identification of the genetic central dogma in osteogenic differentiation of MSCs by osteoinductive medium from transcriptional data sets. Chronic Dis Transl Med 2022; 8:218-228. [PMID: 36161200 PMCID: PMC9481875 DOI: 10.1002/cdt3.26] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 03/08/2022] [Accepted: 03/24/2022] [Indexed: 11/17/2022] Open
Abstract
Background The genetic central dogma (GCD) has been demonstrated its essential function in many biological processes and diseases. However, its roles in the process of osteogenic differentiation of mesenchymal stem cells (MSCs) remain unclear. Methods In this project, we analyzed an online database of osteogenic differentiation of MSCs after 14 days and 28 days by osteoinductive medium (GSE83770). The differentially expressed genes were screened by GEO2R, with further conducting of KEGG pathways using DAVID. In addition, protein-protein interactions of the enriched pathways were performed using STRING with marked hub genes measured by the CytoHubba. Hub genes were verified by quantitative reverse-transcription polymerase chain reaction. Results Results showed that six pathways related to GCD, including DNA replication, Aminoacyl-tRNA biosynthesis, Mismatch repair, Ribosome, Spliceosome, and RNA degradation pathways enriched in the early stage (14 days vs. undifferentiated MSCs) of osteogenesis. The Lysosome pathway was highly enriched in the late stage (28 vs. 14 days) of osteogenesis, and Ribosome pathway plays a key role throughout the entire process (28 days vs. undifferentiated MSCs) of osteogenesis. Conclusion Both DNA replication and protein translation were functionally worked in the early stage of osteogenesis, whereas the Lysosome pathway was the only GCD-related one in the late stage of osteogenesis. The GCD-related Ribosome pathway occupied the entire process of osteogenesis.
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Affiliation(s)
- Tong‐Meng Jiang
- School of Materials Science and EngineeringZhejiang UniversityHangzhouZhejiang310027China
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11
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LIM CHANGHYUN, NUNES EVERSONA, CURRIER BRADS, MCLEOD JONATHANC, THOMAS AARONCQ, PHILLIPS STUARTM. An Evidence-Based Narrative Review of Mechanisms of Resistance Exercise-Induced Human Skeletal Muscle Hypertrophy. Med Sci Sports Exerc 2022; 54:1546-1559. [PMID: 35389932 PMCID: PMC9390238 DOI: 10.1249/mss.0000000000002929] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Skeletal muscle plays a critical role in physical function and metabolic health. Muscle is a highly adaptable tissue that responds to resistance exercise (RE; loading) by hypertrophying, or during muscle disuse, RE mitigates muscle loss. Resistance exercise training (RET)-induced skeletal muscle hypertrophy is a product of external (e.g., RE programming, diet, some supplements) and internal variables (e.g., mechanotransduction, ribosomes, gene expression, satellite cells activity). RE is undeniably the most potent nonpharmacological external variable to stimulate the activation/suppression of internal variables linked to muscular hypertrophy or countering disuse-induced muscle loss. Here, we posit that despite considerable research on the impact of external variables on RET and hypertrophy, internal variables (i.e., inherent skeletal muscle biology) are dominant in regulating the extent of hypertrophy in response to external stimuli. Thus, identifying the key internal skeletal muscle-derived variables that mediate the translation of external RE variables will be pivotal to determining the most effective strategies for skeletal muscle hypertrophy in healthy persons. Such work will aid in enhancing function in clinical populations, slowing functional decline, and promoting physical mobility. We provide up-to-date, evidence-based perspectives of the mechanisms regulating RET-induced skeletal muscle hypertrophy.
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Affiliation(s)
- CHANGHYUN LIM
- Department of Kinesiology, McMaster University, Hamilton, Ontario, CANADA
| | - EVERSON A. NUNES
- Department of Kinesiology, McMaster University, Hamilton, Ontario, CANADA
- Department of Physiological Science, Federal University of Santa Catarina, Florianópolis, Santa-Catarina, BRAZIL
| | - BRAD S. CURRIER
- Department of Kinesiology, McMaster University, Hamilton, Ontario, CANADA
| | - JONATHAN C. MCLEOD
- Department of Kinesiology, McMaster University, Hamilton, Ontario, CANADA
| | - AARON C. Q. THOMAS
- Department of Kinesiology, McMaster University, Hamilton, Ontario, CANADA
| | - STUART M. PHILLIPS
- Department of Kinesiology, McMaster University, Hamilton, Ontario, CANADA
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12
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Liu W, Zhang R, Huang S, Li X, Liu W, Zhou J, Zhu L, Song Y, Yang C. Quantification of Intracellular Proteins in Single Cells Based on Engineered Picoliter Droplets. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2022; 38:7929-7937. [PMID: 35748862 DOI: 10.1021/acs.langmuir.2c00341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Unlike conventional bulk measurements, single-cell protein analysis permits quantification of protein expression in individual cells. This has shed light on the cell-to-cell variation in heterogeneous biological systems, such as solid tumors, brain tissues, and developing embryos. Herein, a microfluidic method is developed to profile protein expression in individual cells by performing single-cell intracellular protein immunoassay in picoliter paired droplets. The high sensitivity of single-cell protein analysis on a chip is achieved by the confined reaction volume of picoliter droplets, efficient kinetic characteristics of the immunoassay through active mixing, and minimum single-cell protein loss by integrated operations. The abundance of an intracellular prostate specific antigen at the single-cell level is measured, and then the platform is applied to identify cell types and investigate heterogeneity within cell populations. Overall, a paired chip for single-cell immunoassay establishes a foundation for parallel, sensitive, and integrated protein quantification at the single-cell level and will find wide applications in the field of single-cell proteomics.
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Affiliation(s)
- Weizhi Liu
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Ruihua Zhang
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Shanqing Huang
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Xingrui Li
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Wanling Liu
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Jianhui Zhou
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Lin Zhu
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Yanling Song
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China
| | - Chaoyong Yang
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China
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Simpson CE, Griffiths M, Yang J, Nies MK, Vaidya D, Brandal S, Martin LJ, Pauciulo MW, Lutz KA, Coleman AW, Austin ED, Ivy DD, Nichols WC, Everett AD, Hassoun PM, Damico RL. COL18A1 genotypic associations with endostatin levels and clinical features in pulmonary arterial hypertension: a quantitative trait association study. ERJ Open Res 2022; 8:00725-2021. [PMID: 35769420 PMCID: PMC9234438 DOI: 10.1183/23120541.00725-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 04/29/2022] [Indexed: 11/05/2022] Open
Abstract
Endostatin (ES) is a circulating peptide derived from collagen XVIII alpha 1 (COL18A1) known to inhibit angiogenesis [1, 2]. Decreased angiogenesis is a feature of pulmonary arterial hypertension (PAH) in animal models [3] and human subjects [4]. Our group has reported strong associations between circulating ES levels and haemodynamics and survival in PAH [5–7]. We have also reported that a missense variant in COL18A1, which encodes ES, confers lower ES and longer survival, suggesting that variation within the gene contributes to circulating levels [5]. In the current study, we assessed COL18A1 variant associations with clinical phenotypes and outcomes, including COL18A1 associations with circulating ES levels, in a large, multicentre PAH cohort in which we previously investigated ES as a prognostic biomarker [6]. Variation around the COL18A1 gene, which encodes the angiostatic peptide endostatin, may influence disease heterogeneity in pulmonary arterial hypertensionhttps://bit.ly/3shXrNR
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Affiliation(s)
- Catherine E Simpson
- Johns Hopkins University, Dept of Medicine, Division of Pulmonary and Critical Care Medicine, Baltimore, MD, USA
| | - Megan Griffiths
- Johns Hopkins University, Dept of Pediatrics, Division of Pediatric Cardiology, Baltimore, MD, USA
| | - Jun Yang
- Johns Hopkins University, Dept of Pediatrics, Division of Pediatric Cardiology, Baltimore, MD, USA
| | - Melanie K Nies
- Johns Hopkins University, Dept of Pediatrics, Division of Pediatric Cardiology, Baltimore, MD, USA
| | - Dhananjay Vaidya
- Johns Hopkins University, Dept of Medicine, Division of General Internal Medicine, Baltimore, MD, USA
| | - Stephanie Brandal
- Johns Hopkins University, Dept of Pediatrics, Division of Pediatric Cardiology, Baltimore, MD, USA
| | - Lisa J Martin
- Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Dept of Pediatrics, Division of Human Genetics, Cincinnati, OH, USA
| | - Michael W Pauciulo
- Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Dept of Pediatrics, Division of Human Genetics, Cincinnati, OH, USA
| | - Katie A Lutz
- Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Dept of Pediatrics, Division of Human Genetics, Cincinnati, OH, USA
| | - Anna W Coleman
- Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Dept of Pediatrics, Division of Human Genetics, Cincinnati, OH, USA
| | - Eric D Austin
- Vanderbilt University, Dept of Pediatrics, Division of Allergy, Immunology, and Pulmonary Medicine, Nashville, TN, USA
| | - D Dunbar Ivy
- Children's Hospital Colorado, Dept of Pediatric Cardiology, Aurora, CO, USA
| | - William C Nichols
- Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Dept of Pediatrics, Division of Human Genetics, Cincinnati, OH, USA
| | - Allen D Everett
- Johns Hopkins University, Dept of Pediatrics, Division of Pediatric Cardiology, Baltimore, MD, USA
| | - Paul M Hassoun
- Johns Hopkins University, Dept of Medicine, Division of Pulmonary and Critical Care Medicine, Baltimore, MD, USA
| | - Rachel L Damico
- Johns Hopkins University, Dept of Medicine, Division of Pulmonary and Critical Care Medicine, Baltimore, MD, USA
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14
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Praça YR, Santiago PB, Charneau S, Mandacaru SC, Bastos IMD, Bentes KLDS, Silva SMM, da Silva WMC, da Silva IG, de Sousa MV, Soares CMDA, Ribeiro JMC, Santana JM, de Araújo CN. An Integrative Sialomic Analysis Reveals Molecules From Triatoma sordida (Hemiptera: Reduviidae). Front Cell Infect Microbiol 2022; 11:798924. [PMID: 35047420 PMCID: PMC8762107 DOI: 10.3389/fcimb.2021.798924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 12/07/2021] [Indexed: 11/13/2022] Open
Abstract
Triatomines have evolved salivary glands that produce versatile molecules with various biological functions, including those leading their interactions with vertebrate hosts’ hemostatic and immunological systems. Here, using high-throughput transcriptomics and proteomics, we report the first sialome study on the synanthropic triatomine Triatoma sordida. As a result, 57,645,372 reads were assembled into 26,670 coding sequences (CDS). From these, a total of 16,683 were successfully annotated. The sialotranscriptomic profile shows Lipocalin as the most abundant protein family within putative secreted transcripts. Trialysins and Kazal-type protease inhibitors have high transcript levels followed by ubiquitous protein families and enzyme classes. Interestingly, abundant trialysin and Kazal-type members are highlighted in this triatomine sialotranscriptome. Furthermore, we identified 132 proteins in T. sordida salivary gland soluble extract through LC-MS/MS spectrometry. Lipocalins, Hemiptera specific families, CRISP/Antigen-5 and Kazal-type protein inhibitors proteins were identified. Our study provides a comprehensive description of the transcript and protein compositions of the salivary glands of T. sordida. It significantly enhances the information in the Triatominae sialome databanks reported so far, improving the understanding of the vector’s biology, the hematophagous behaviour, and the Triatominae subfamily’s evolution.
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Affiliation(s)
- Yanna Reis Praça
- Pathogen-Host Interface Laboratory, Department of Cell Biology, University of Brasilia, Brasilia, Brazil.,Programa Pós-Graduação em Ciências Médicas, Faculty of Medicine, University of Brasilia, Brasilia, Brazil
| | - Paula Beatriz Santiago
- Pathogen-Host Interface Laboratory, Department of Cell Biology, University of Brasilia, Brasilia, Brazil
| | - Sébastien Charneau
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, University of Brasilia, Brasilia, Brazil
| | - Samuel Coelho Mandacaru
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, University of Brasilia, Brasilia, Brazil
| | | | - Kaio Luís da Silva Bentes
- Pathogen-Host Interface Laboratory, Department of Cell Biology, University of Brasilia, Brasilia, Brazil.,Programa Pós-Graduação em Ciências Médicas, Faculty of Medicine, University of Brasilia, Brasilia, Brazil
| | | | | | | | - Marcelo Valle de Sousa
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, University of Brasilia, Brasilia, Brazil
| | | | - José Marcos Chaves Ribeiro
- Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States
| | - Jaime Martins Santana
- Pathogen-Host Interface Laboratory, Department of Cell Biology, University of Brasilia, Brasilia, Brazil.,Programa Pós-Graduação em Ciências Médicas, Faculty of Medicine, University of Brasilia, Brasilia, Brazil
| | - Carla Nunes de Araújo
- Pathogen-Host Interface Laboratory, Department of Cell Biology, University of Brasilia, Brasilia, Brazil.,Programa Pós-Graduação em Ciências Médicas, Faculty of Medicine, University of Brasilia, Brasilia, Brazil.,Faculty of Ceilândia, University of Brasilia, Brasilia, Brazil
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15
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Regulation of mRNA translation in stem cells; links to brain disorders. Cell Signal 2021; 88:110166. [PMID: 34624487 DOI: 10.1016/j.cellsig.2021.110166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 08/09/2021] [Accepted: 09/29/2021] [Indexed: 11/22/2022]
Abstract
Translational control of gene expression is emerging as a cardinal step in the regulation of protein abundance. Especially for embryonic (ESC) and neuronal stem cells (NSC), regulation of mRNA translation is involved in the maintenance of pluripotency but also differentiation. For neuronal stem cells this regulation is linked to the various neuronal subtypes that arise in the developing brain and is linked to numerous brain disorders. Herein, we review translational control mechanisms in ESCs and NSCs during development and differentiation, and briefly discuss their link to brain disorders.
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16
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Ruiz KA, Pelletier JM, Wang Y, Feng MJ, Behr JS, Ðào TQ, Li B, Kliebenstein D, Harada JJ, Jenik PD. A reevaluation of the role of the ASIL trihelix transcription factors as repressors of the seed maturation program. PLANT DIRECT 2021; 5:e345. [PMID: 34622120 PMCID: PMC8483069 DOI: 10.1002/pld3.345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 05/27/2021] [Accepted: 08/17/2021] [Indexed: 06/13/2023]
Abstract
Developmental transitions are typically tightly controlled at the transcriptional level. Two of these transitions involve the induction of the embryo maturation program midway through seed development and its repression during the vegetative phase of plant growth. Very little is known about the factors responsible for this regulation during early embryogenesis, and only a couple of transcription factors have been characterized as repressors during the postgerminative phase. Arabidopsis 6b-INTERACTING PROTEIN-LIKE1 (ASIL1), a trihelix transcription factor, has been proposed to repress maturation both embryonically and postembryonically. Preliminary data also suggested that its closest paralog, ASIL2, might play a role as well. We used a transcriptomic approach, coupled with phenotypical observations, to test the hypothesis that ASIL1 and ASIL2 redundantly turn off maturation during both phases of growth. Our results indicate that, contrary to what was previously published, neither of the ASIL genes plays a role in the regulation of maturation, at any point during plant development. Analyses of gene ontology (GO)-enriched terms and published transcriptomic datasets suggest that these genes might be involved in responses during the vegetative phase to certain biotic and abiotic stresses.
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Affiliation(s)
- Kevin A. Ruiz
- Department of BiologyFranklin & Marshall CollegeLancasterPAUSA
| | - Julie M. Pelletier
- Department of Plant Biology, College of Biological SciencesUniversity of CaliforniaDavisCAUSA
| | - Yuchi Wang
- Department of BiologyFranklin & Marshall CollegeLancasterPAUSA
- Present address:
Chimera (Shanghai) Biotec Ltd.Shanghai CityChina
| | - Min Jun Feng
- Department of BiologyFranklin & Marshall CollegeLancasterPAUSA
- Present address:
Medical University of South CarolinaCharlestonSCUSA
| | - Jacqueline S. Behr
- Department of BiologyFranklin & Marshall CollegeLancasterPAUSA
- Present address:
Hoboken University Medical CenterHobokenNJUSA
| | - Thái Q. Ðào
- Department of BiologyFranklin & Marshall CollegeLancasterPAUSA
- Present address:
Department of Botany and Plant Biology, College of Agricultural SciencesOregon State UniversityCorvallisORUSA
| | - Baohua Li
- Department of Plant Sciences, College of Agricultural and Environmental SciencesUniversity of CaliforniaDavisCAUSA
- Present address:
College of HorticultureNorthwest A&F UniversityYanglingShaanxiChina
| | - Daniel Kliebenstein
- Department of Plant Sciences, College of Agricultural and Environmental SciencesUniversity of CaliforniaDavisCAUSA
| | - John J. Harada
- Department of Plant Biology, College of Biological SciencesUniversity of CaliforniaDavisCAUSA
| | - Pablo D. Jenik
- Department of BiologyFranklin & Marshall CollegeLancasterPAUSA
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17
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Kusnadi EP, Timpone C, Topisirovic I, Larsson O, Furic L. Regulation of gene expression via translational buffering. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH 2021; 1869:119140. [PMID: 34599983 DOI: 10.1016/j.bbamcr.2021.119140] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 09/19/2021] [Accepted: 09/21/2021] [Indexed: 12/28/2022]
Abstract
Translation of an mRNA represents a critical step during the expression of protein-coding genes. As mechanisms governing post-transcriptional regulation of gene expression are progressively unveiled, it is becoming apparent that transcriptional programs are not fully reflected in the proteome. Herein, we highlight a previously underappreciated post-transcriptional mode of regulation of gene expression termed translational buffering. In principle, translational buffering opposes the impact of alterations in mRNA levels on the proteome. We further describe three types of translational buffering: compensation, which maintains protein levels e.g. across species or individuals; equilibration, which retains pathway stoichiometry; and offsetting, which acts as a reversible mechanism that maintains the levels of selected subsets of proteins constant despite genetic alteration and/or stress-induced changes in corresponding mRNA levels. While mechanisms underlying compensation and equilibration have been reviewed elsewhere, the principal focus of this review is on the less-well understood mechanism of translational offsetting. Finally, we discuss potential roles of translational buffering in homeostasis and disease.
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Affiliation(s)
- Eric P Kusnadi
- Translational Prostate Cancer Research Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia; Cancer Program, Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia
| | - Clelia Timpone
- Translational Prostate Cancer Research Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia
| | - Ivan Topisirovic
- Lady Davis Institute, Gerald Bronfman Department of Oncology and Departments of Biochemistry and Experimental Medicine, McGill University, Montreal, QC, Canada.
| | - Ola Larsson
- Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
| | - Luc Furic
- Translational Prostate Cancer Research Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia; Cancer Program, Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia.
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18
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Przedborski M, Sharon D, Chan S, Kohandel M. A mean-field approach for modeling the propagation of perturbations in biochemical reaction networks. Eur J Pharm Sci 2021; 165:105919. [PMID: 34175448 DOI: 10.1016/j.ejps.2021.105919] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 05/17/2021] [Accepted: 06/20/2021] [Indexed: 12/12/2022]
Abstract
Often, the time evolution of a biochemical reaction network is crucial for determining the effects of combining multiple pharmaceuticals. Here we illustrate a mathematical framework for modeling the dominant temporal behaviour of a complicated molecular pathway or biochemical reaction network in response to an arbitrary perturbation, such as resulting from the administration of a therapeutic agent. The method enables the determination of the temporal evolution of a target protein as the perturbation propagates through its regulatory network. The mathematical approach is particularly useful when the experimental data that is available for characterizing or parameterizing the regulatory network is limited or incomplete. To illustrate the method, we consider the examples of the regulatory networks for the target proteins c-Myc and Chop, which play an important role in venetoclax resistance in acute myeloid leukemia. First we show how the networks that regulate each target protein can be reduced to a mean-field model by identifying the distinct effects that groups of proteins in the regulatory network have on the target protein. Then we show how limited protein-level data can be used to further simplify the mean-field model to pinpoint the dominant effects of the network perturbation on the target protein. This enables a further reduction in the number of parameters in the model. The result is an ordinary differential equation model that captures the temporal evolution of the expression of a target protein when one or more proteins in its regulatory network have been perturbed. Finally, we show how the dominant effects predicted by the mathematical model agree with RNA sequencing data for the regulatory proteins comprising the molecular network, despite the model not having a priori knowledge of this data. Thus, while the approach gives a simplified model for the expression of the target protein, it allows for the interpretation of the effects of the perturbation on the regulatory network itself. This method can be easily extended to sets of target proteins to model components of a larger systems biology model, and provides an approach for partially integrating RNA sequencing data and protein expression data. Moreover, it is a general approach that can be used to study drug effects on specific protein(s) in any disease or condition.
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Affiliation(s)
- Michelle Przedborski
- Department of Applied Mathematics, University of Waterloo, Waterloo, ON, Canada.
| | - David Sharon
- Princess Margaret Cancer Centre, Toronto, ON, Canada
| | - Steven Chan
- Princess Margaret Cancer Centre, Toronto, ON, Canada
| | - Mohammad Kohandel
- Department of Applied Mathematics, University of Waterloo, Waterloo, ON, Canada
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19
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Bayoumi A, Elsayed A, Han S, Petta S, Adams LA, Aller R, Khan A, García‐Monzón C, Arias‐Loste MT, Miele L, Latchoumanin O, Alenizi S, Gallego‐Durán R, Fischer J, Berg T, Craxì A, Metwally M, Qiao L, Liddle C, Yki‐Järvinen H, Bugianesi E, Romero‐Gomez M, George J, Eslam M. Mistranslation Drives Alterations in Protein Levels and the Effects of a Synonymous Variant at the Fibroblast Growth Factor 21 Locus. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:2004168. [PMID: 34141520 PMCID: PMC8188187 DOI: 10.1002/advs.202004168] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 02/09/2021] [Indexed: 05/08/2023]
Abstract
Fibroblast growth factor 21 (FGF21) is a liver-derived hormone with pleiotropic beneficial effects on metabolism. Paradoxically, FGF21 levels are elevated in metabolic diseases. Interventions that restore metabolic homeostasis reduce FGF21. Whether abnormalities in FGF21 secretion or resistance in peripheral tissues is the initiating factor in altering FGF21 levels and function in humans is unknown. A genetic approach is used to help resolve this paradox. The authors demonstrate that the primary event in dysmetabolic phenotypes is the elevation of FGF21 secretion. The latter is regulated by translational reprogramming in a genotype- and context-dependent manner. To relate the findings to tissues outcomes, the minor (A) allele of rs838133 is shown to be associated with increased hepatic inflammation in patients with metabolic associated fatty liver disease. The results here highlight a dominant role for translation of the FGF21 protein to explain variations in blood levels that is at least partially inherited. These results provide a framework for translational reprogramming of FGF21 to treat metabolic diseases.
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Affiliation(s)
- Ali Bayoumi
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Asmaa Elsayed
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Shuanglin Han
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Salvatore Petta
- Section of Gastroenterology and HepatologyPROMISEUniversity of PalermoPalermo90133Italy
| | - Leon A. Adams
- Medical SchoolSir Charles Gairdner Hospital UnitUniversity of Western AustraliaNedlandsWA6009Australia
| | - Rocio Aller
- GastroenterologyHospital Clinico Universitario de ValladolidSchool of MedicineValladolid UniversityValladolid47002Spain
| | - Anis Khan
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Carmelo García‐Monzón
- Liver Research UnitInstituto de Investigacion Sanitaria PrincesaUniversity Hospital Santa CristinaCIBERehdMadrid28009Spain
| | - María Teresa Arias‐Loste
- Gastroenterology and Hepatology DepartmentMarqués de Valdecilla University HospitalSantander39008Spain
| | - Luca Miele
- Department of Internal MedicineCatholic University of the Sacred HeartRome20123Italy
| | - Olivier Latchoumanin
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Shafi Alenizi
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Rocio Gallego‐Durán
- Virgen del Rocío University HospitalInstitute of Biomedicine of SevilleSevilla41013Spain
| | - Janett Fischer
- Division of HepatologyDepartment of Medicine IILeipzig University Medical CenterLeipzig04103Germany
| | - Thomas Berg
- Division of HepatologyDepartment of Medicine IILeipzig University Medical CenterLeipzig04103Germany
| | - Antonio Craxì
- Section of Gastroenterology and HepatologyPROMISEUniversity of PalermoPalermo90133Italy
| | - Mayada Metwally
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Liang Qiao
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Christopher Liddle
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Hannele Yki‐Järvinen
- Department of MedicineUniversity of Helsinki and Helsinki University Hospital and Minerva Foundation Institute for Medical ResearchHelsinki00290Finland
| | - Elisabetta Bugianesi
- Division of GastroenterologyDepartment of Medical ScienceUniversity of TurinTurin10124Italy
| | - Manuel Romero‐Gomez
- Virgen del Rocío University HospitalInstitute of Biomedicine of SevilleSevilla41013Spain
| | - Jacob George
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
| | - Mohammed Eslam
- Storr Liver CentreWestmead Institute for Medical ResearchWestmead Hospital and University of SydneyWestmeadNSW2145Australia
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20
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Molecular Transducers of Human Skeletal Muscle Remodeling under Different Loading States. Cell Rep 2021; 32:107980. [PMID: 32755574 PMCID: PMC7408494 DOI: 10.1016/j.celrep.2020.107980] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 02/27/2020] [Accepted: 07/09/2020] [Indexed: 12/11/2022] Open
Abstract
Loading of skeletal muscle changes the tissue phenotype reflecting altered metabolic and functional demands. In humans, heterogeneous adaptation to loading complicates the identification of the underpinning molecular regulators. A within-person differential loading and analysis strategy reduces heterogeneity for changes in muscle mass by ∼40% and uses a genome-wide transcriptome method that models each mRNA from coding exons and 3' and 5' untranslated regions (UTRs). Our strategy detects ∼3-4 times more regulated genes than similarly sized studies, including substantial UTR-selective regulation undetected by other methods. We discover a core of 141 genes correlated to muscle growth, which we validate from newly analyzed independent samples (n = 100). Further validating these identified genes via RNAi in primary muscle cells, we demonstrate that members of the core genes were regulators of protein synthesis. Using proteome-constrained networks and pathway analysis reveals notable relationships with the molecular characteristics of human muscle aging and insulin sensitivity, as well as potential drug therapies.
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21
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Forés-Martos J, Forte A, García-Martínez J, Pérez-Ortín JE. A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them. Cells 2021; 10:334. [PMID: 33562654 PMCID: PMC7914595 DOI: 10.3390/cells10020334] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 12/01/2022] Open
Abstract
The ultimate goal of gene expression regulation is on the protein level. However, because the amounts of mRNAs and proteins are controlled by their synthesis and degradation rates, the cellular amount of a given protein can be attained by following different strategies. By studying omics data for six expression variables (mRNA and protein amounts, plus their synthesis and decay rates), we previously demonstrated the existence of common expression strategies (CESs) for functionally related genes in the yeast Saccharomyces cerevisiae. Here we extend that study to two other eukaryotes: the yeast Schizosaccharomyces pombe and cultured human HeLa cells. We also use genomic data from the model prokaryote Escherichia coli as an external reference. We show that six-variable profiles (6VPs) can be constructed for every gene and that these 6VPs are similar for genes with similar functions in all the studied organisms. The differences in 6VPs between organisms can be used to establish their phylogenetic relationships. The analysis of the correlations among the six variables supports the hypothesis that most gene expression control occurs in actively growing organisms at the transcription rate level, and that translation plays a minor role. We propose that living organisms use CESs for the genes acting on the same physiological pathways, especially for those belonging to stable macromolecular complexes, but CESs have been modeled by evolution to adapt to the specific life circumstances of each organism.
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Affiliation(s)
- Jaume Forés-Martos
- Instituto de Biotecnología y Biomedicina (Biotecmed), Universitat de València, C/Dr. Moliner 50, E46100 Burjassot, Spain;
| | - Anabel Forte
- Departamento de Estadística e Investigación Operativa, Facultad de Matemáticas, Universitat de València, C/Dr. Moliner 50, E46100 Burjassot, Spain;
| | - José García-Martínez
- Instituto de Biotecnología y Biomedicina (Biotecmed), Universitat de València, C/Dr. Moliner 50, E46100 Burjassot, Spain;
| | - José E. Pérez-Ortín
- Instituto de Biotecnología y Biomedicina (Biotecmed), Universitat de València, C/Dr. Moliner 50, E46100 Burjassot, Spain;
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22
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Fan X, Yao H, Liu X, Shi Q, Lv L, Li P, Wang R, Tang T, Qi K. High-Fat Diet Alters the Expression of Reference Genes in Male Mice. Front Nutr 2020; 7:589771. [PMID: 33330591 PMCID: PMC7732482 DOI: 10.3389/fnut.2020.589771] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 10/19/2020] [Indexed: 12/17/2022] Open
Abstract
Quantitative PCR (qPCR), the most accurate and sensitive technique for quantifying mRNA expression, and choice of appropriate reference genes for internal error controlling in qPCR are essential to understanding the molecular mechanisms that drive the obesity epidemic and its comorbidities. In this study, using the high-fat diet (HFD)-induced obese mouse model, we assessed the expression of 10 commonly used reference genes to validate gene-expression stability in adipose tissue, liver, and muscle across different time points (4, 8, 12, and 16 weeks after HFD feeding) during the process of obesity. The data were analyzed by the GeNorm, NormFinder, BestKeeper, and Delta-Ct method, and the results showed that the most stable reference genes were different for a specific organ or tissue in a specific time point; however, PPIA, RPLP0, and YWHAZ were the top three most stable reference genes in qPCR experiments on adipose, hepatic tissues, and muscles of mice in diet-induced obesity. In addition, the mostly used genes ACTB and GAPDH were more unstable in the fat and liver, the ACTB mRNA levels were increased in four adipose tissues, and the GAPDH mRNA levels were decreased in four adipose tissues and liver after HFD feeding. These results suggest that PPIA, RPLP0, or YWHAZ may be more appropriate to be used as reference gene than ACTB and GAPDH in the adipose tissue and liver of mice during the process of high-fat diet-induced obesity.
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Affiliation(s)
- Xiuqin Fan
- Laboratory of Nutrition and Development, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Hongyang Yao
- Laboratory of Nutrition and Development, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Xuanyi Liu
- Laboratory of Nutrition and Development, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Qiaoyu Shi
- Laboratory of Nutrition and Development, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | | | - Ping Li
- Laboratory of Nutrition and Development, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Rui Wang
- Laboratory of Nutrition and Development, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Tiantian Tang
- Laboratory of Nutrition and Development, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Kemin Qi
- Laboratory of Nutrition and Development, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
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23
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Seale AP, Malintha GHT, Celino-Brady FT, Head T, Belcaid M, Yamaguchi Y, Lerner DT, Baltzegar DA, Borski RJ, Stoytcheva ZR, Breves JP. Transcriptional regulation of prolactin in a euryhaline teleost: Characterisation of gene promoters through in silico and transcriptome analyses. J Neuroendocrinol 2020; 32:e12905. [PMID: 32996203 PMCID: PMC8612711 DOI: 10.1111/jne.12905] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Revised: 07/31/2020] [Accepted: 08/26/2020] [Indexed: 12/20/2022]
Abstract
The sensitivity of prolactin (Prl) cells of the Mozambique tilapia (Oreochromis mossambicus) pituitary to variations in extracellular osmolality enables investigations into how osmoreception underlies patterns of hormone secretion. Through the actions of their main secretory products, Prl cells play a key role in supporting hydromineral balance of fishes by controlling the major osmoregulatory organs (ie, gill, intestine and kidney). The release of Prl from isolated cells of the rostral pars distalis (RPD) occurs in direct response to physiologically relevant reductions in extracellular osmolality. Although the particular signal transduction pathways that link osmotic conditions to Prl secretion have been identified, the processes that underlie hyposmotic induction of prl gene expression remain unknown. In this short review, we describe two distinct tilapia gene loci that encode Prl177 and Prl188 . From our in silico analyses of prl177 and prl188 promoter regions (approximately 1000 bp) and a transcriptome analysis of RPDs from fresh water (FW)- and seawater (SW)-acclimated tilapia, we propose a working model for how multiple transcription factors link osmoreceptive processes with adaptive patterns of prl177 and prl188 gene expression. We confirmed via RNA-sequencing and a quantitative polymerase chain reaction that multiple transcription factors emerging as predicted regulators of prl gene expression are expressed in the RPD of tilapia. In particular, gene transcripts encoding pou1f1, stat3, creb3l1, pbxip1a and stat1a were highly expressed; creb3l1, pbxip1a and stat1a were elevated in fish acclimated to SW vs FW. Combined, our in silico and transcriptome analyses set a path for resolving how adaptive patterns of Prl secretion are achieved via the integration of osmoreceptive processes with the control of prl gene transcription.
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Affiliation(s)
- Andre P. Seale
- Department of Human Nutrition, Food and Animal Sciences, University of Hawai’i at Mānoa, Honolulu, HI, USA
| | | | - Fritzie T. Celino-Brady
- Department of Human Nutrition, Food and Animal Sciences, University of Hawai’i at Mānoa, Honolulu, HI, USA
| | - Tony Head
- Department of Human Nutrition, Food and Animal Sciences, University of Hawai’i at Mānoa, Honolulu, HI, USA
| | - Mahdi Belcaid
- Hawai’i Institute of Marine Biology, University of Hawai’i at Mānoa, Kaneohe, HI, USA
| | - Yoko Yamaguchi
- Institute of Agricultural and Life Sciences, Academic Assembly, Shimane University, Matsue, Japan
| | - Darren T. Lerner
- University of Hawai’i Sea Grant College Program, University of Hawai’i at Mānoa, Honolulu, HI, USA
| | - David A. Baltzegar
- Genomic Sciences Laboratory, Office of Research and Innovation, North Carolina State University, Raleigh, NC, USA
| | - Russell J. Borski
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Zoia R. Stoytcheva
- Department of Human Nutrition, Food and Animal Sciences, University of Hawai’i at Mānoa, Honolulu, HI, USA
| | - Jason P. Breves
- Department of Biology, Skidmore College, Saratoga Springs, NY, USA
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Shen Z, Deng SP, Huang DS. Capsule Network for Predicting RNA-Protein Binding Preferences Using Hybrid Feature. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2020; 17:1483-1492. [PMID: 31562101 DOI: 10.1109/tcbb.2019.2943465] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
RNA-Protein binding is involved in many different biological processes. With the progress of technology, more and more data are available for research. Based on these data, many prediction methods have been proposed to predict RNA-Protein binding preference. Some of these methods use only RNA sequence features for prediction, and some methods use multiple features for prediction. But, the performance of these methods is not satisfactory. In this study, we propose an improved capsule network to predict RNA-protein binding preferences, which can use both RNA sequence features and structure features. Experimental results show that our proposed method iCapsule performs better than three baseline methods in this field. We used both RNA sequence features and structure features in the model, so we tested the effect of primary capsule layer changes on model performance. In addition, we also studied the impact of model structure on model performance by performing our proposed method with different number of convolution layers and different kernel sizes.
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Cui M, Liang J, Xu D, Zhao L, Zhang X, Zhang L, Ren S, Liu D, Niu X, Zang YJ, Zhang B. NLRP3 inflammasome is involved in nerve recovery after sciatic nerve injury. Int Immunopharmacol 2020; 84:106492. [PMID: 32402947 DOI: 10.1016/j.intimp.2020.106492] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 03/13/2020] [Accepted: 04/05/2020] [Indexed: 01/12/2023]
Abstract
The activation of the inflammasome plays an important role in the central nervous system. However, only a few studies have investigated the effects of inflammasome activation in the peripheral nerve, especially in the sciatic nerve, and the mechanism of this activation remains elusive. Moreover, how interleukin-1 beta (IL-1β) is produced after sciatic nerve injury is also unknown. In our study, we aimed to investigate whether the nucleotide-binding oligomerization domain-like pyrin domain containing protein 3 (NLRP3) inflammasome is activated after sciatic nerve injury and to explore its role in sciatic nerve injury. The results of immunoblotting and immunofluorescence microscopy indicate that the NLRP3 inflammasome was activated after sciatic nerve injury in wild-type (WT) mice, as demonstrated by upregulated inflammasome-related components, e.g., NLRP3, procaspase-1 and ASC. Furthermore, upregulated inflammasome-related components cis-cleavage precursor IL-1β (proIL-1β) and precursor interleukin-18 (proIL-18) to IL-1β and IL-18, contributing to the inflammatory response. Consequently, the inflammatory response after sciatic nerve injury in NLRP3 knockout (NLRP3-KO) mice was less severe than that in WT mice. Moreover, NLRP3-KO mice exhibited an increased sciatic functional index (SFI), which was determined by footprint analysis, suggesting that NLRP3 deficiency is beneficial to sciatic nerve recovery after injury. Therefore, our results indicate that NLRP3 is involved in the recovery from sciatic nerve injury and mediates the production of inflammatory factors, such as IL-1β, after sciatic nerve injury.
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Affiliation(s)
- Mengli Cui
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China
| | - Jie Liang
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China
| | - Dan Xu
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China
| | - Lizhen Zhao
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China
| | - Xiangyan Zhang
- Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, PR China
| | - Li Zhang
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China
| | - Shurong Ren
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China
| | - Dongkai Liu
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China
| | - Xuanxuan Niu
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China
| | - Yun-Jin Zang
- Department of Liver Transplantation, Organ Transplantation Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, PR China.
| | - Bei Zhang
- Department of Immunology, College of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, PR China.
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França GDO, Frantz EDC, Magliano DC, Bargut TCL, Sepúlveda-Fragoso V, Silvares RR, Daliry A, Nascimento ARD, Borges JP. Effects of short-term high-intensity interval and continuous exercise training on body composition and cardiac function in obese sarcopenic rats. Life Sci 2020; 256:117920. [PMID: 32522571 DOI: 10.1016/j.lfs.2020.117920] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Revised: 06/02/2020] [Accepted: 06/04/2020] [Indexed: 01/03/2023]
Abstract
AIM We investigated the effects of high-intensity interval and continuous short-term exercise on body composition and cardiac function after myocardial ischemia-reperfusion injury (IRI) in obese rats. METHODS Rats fed with a standard chow diet (SC) or high-fat diet (HFD) for 20 weeks underwent systolic blood pressure (SBP), glycemia and dual-energy X-ray absorptiometry analyses. Then, animals fed with HFD were subdivided into three groups: sedentary (HFD-SED); moderate-intensity continuous training (HFD-MICT); and high-intensity interval training (HFD-HIIT). Exercised groups underwent four isocaloric aerobic exercise sessions, in which HFD-MICT maintained the intensity continuously and HFD-HIIT alternated it. After exercise sessions, all groups underwent global IRI and myocardial infarct size (IS) was determined histologically. Fat and muscle mass were weighted, and protein levels involved in muscle metabolism were assessed in skeletal muscle. RESULTS HFD-fed versus SC-fed rats reduced lean body mass by 31% (P < 0.001), while SBP, glycemia and body fat percentage were increased by 10% (P = 0.04), 30% (P = 0.006) and 54% (P < 0.001); respectively. HFD-induced muscle atrophy was restored in exercised groups, as only HFD-SED presented lower gastrocnemius (32%; P = 0.001) and quadriceps mass (62%; P < 0.001) than SC. PGC1-α expression was 2.7-fold higher in HFD-HIIT versus HFD-SED (P = 0.04), whereas HFD-HIIT and HFD-MICT exhibited 1.7-fold increase in p-mTORSer2481 levels compared to HFD-SED (P = 0.04). Although no difference was detected among groups for IS (P = 0.30), only HFD-HIIT preserved left-ventricle developed pressure after IRI (+0.7 mmHg; P = 0.9). SIGNIFICANCE Short-term exercise, continuous or HIIT, restored HFD-induced muscle atrophy and increased mTOR expression, but only HIIT maintained myocardial contractility following IRI in obese animals.
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Affiliation(s)
- Guilherme de Oliveira França
- Laboratory of Physical Activity and Health Promotion, Institute of Physical Education and Sports, University of Rio de Janeiro State, Rio de Janeiro, RJ, Brazil; Laboratory of Cardiovascular Investigation, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro, RJ, Brazil
| | - Eliete Dalla Corte Frantz
- Laboratory of Morphological and Metabolic Analyses, Department of Morphology, Biomedical Institute, Fluminense Federal University, Niteroi, RJ, Brazil; National Institute for Science and Technology - INCT (In)activity and Exercise, CNPq - Niteroi, RJ, Brazil; Department of Morphology, Biomedical Institute, Fluminense Federal University, Niteroi, RJ, Brazil
| | - D'Angelo Carlo Magliano
- Laboratory of Morphological and Metabolic Analyses, Department of Morphology, Biomedical Institute, Fluminense Federal University, Niteroi, RJ, Brazil
| | | | - Vinicius Sepúlveda-Fragoso
- Laboratory of Morphological and Metabolic Analyses, Department of Morphology, Biomedical Institute, Fluminense Federal University, Niteroi, RJ, Brazil
| | - Raquel Rangel Silvares
- Laboratory of Cardiovascular Investigation, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro, RJ, Brazil
| | - Anissa Daliry
- Laboratory of Cardiovascular Investigation, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro, RJ, Brazil
| | | | - Juliana Pereira Borges
- Laboratory of Physical Activity and Health Promotion, Institute of Physical Education and Sports, University of Rio de Janeiro State, Rio de Janeiro, RJ, Brazil.
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Sorokin M, Ignatev K, Poddubskaya E, Vladimirova U, Gaifullin N, Lantsov D, Garazha A, Allina D, Suntsova M, Barbara V, Buzdin A. RNA Sequencing in Comparison to Immunohistochemistry for Measuring Cancer Biomarkers in Breast Cancer and Lung Cancer Specimens. Biomedicines 2020; 8:E114. [PMID: 32397474 PMCID: PMC7277916 DOI: 10.3390/biomedicines8050114] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 05/02/2020] [Accepted: 05/07/2020] [Indexed: 12/11/2022] Open
Abstract
RNA sequencing is considered the gold standard for high-throughput profiling of gene expression at the transcriptional level. Its increasing importance in cancer research and molecular diagnostics is reflected in the growing number of its mentions in scientific literature and clinical trial reports. However, the use of different reagents and protocols for RNA sequencing often produces incompatible results. Recently, we published the Oncobox Atlas of RNA sequencing profiles for normal human tissues obtained from healthy donors killed in road accidents. This is a database of molecular profiles obtained using uniform protocol and reagents settings that can be broadly used in biomedicine for data normalization in pathology, including cancer. Here, we publish new original 39 breast cancer (BC) and 19 lung cancer (LC) RNA sequencing profiles obtained for formalin-fixed paraffin-embedded (FFPE) tissue samples, fully compatible with the Oncobox Atlas. We performed the first correlation study of RNA sequencing and immunohistochemistry-measured expression profiles for the clinically actionable biomarker genes in FFPE cancer tissue samples. We demonstrated high (Spearman's rho 0.65-0.798) and statistically significant (p < 0.00004) correlations between the RNA sequencing (Oncobox protocol) and immunohistochemical measurements for HER2/ERBB2, ER/ESR1 and PGR genes in BC, and for PDL1 gene in LC; AUC: 0.963 for HER2, 0.921 for ESR1, 0.912 for PGR, and 0.922 for PDL1. To our knowledge, this is the first validation that total RNA sequencing of archived FFPE materials provides a reliable estimation of marker protein levels. These results show that in the future, RNA sequencing can complement immunohistochemistry for reliable measurements of the expression biomarkers in FFPE cancer samples.
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Affiliation(s)
- Maxim Sorokin
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
- Omicsway Corp., Walnut, CA 91789, USA;
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia;
| | - Kirill Ignatev
- Karelia Republic Oncological Hospital, 185000 Petrozavodsk, Russia;
| | - Elena Poddubskaya
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
- Vitamed Oncological Clinical Center, 121309 Moscow, Russia
| | - Uliana Vladimirova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia;
| | - Nurshat Gaifullin
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, 119991 Moscow, Russia;
| | - Dmitriy Lantsov
- Kaluga Regional Oncological Hospital, 248007 Kaluga, Russia;
| | | | - Daria Allina
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
| | - Maria Suntsova
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
| | - Victoria Barbara
- Oncological Dispensary of the Republic of Karelia, 185002 Petrozavodsk, Russia;
| | - Anton Buzdin
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
- Omicsway Corp., Walnut, CA 91789, USA;
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia;
- Moscow Institute of Physics and Technology, 141701 Moscow, Russia
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28
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The translational landscape of ground state pluripotency. Nat Commun 2020; 11:1617. [PMID: 32238817 PMCID: PMC7113317 DOI: 10.1038/s41467-020-15449-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 03/09/2020] [Indexed: 12/30/2022] Open
Abstract
Translational control plays a central role in regulation of gene expression and can lead to significant divergence between mRNA- and protein-abundance. Here, we used genome-wide approaches combined with time-course analysis to measure the mRNA-abundance, mRNA-translation rate and protein expression during the transition of naïve-to-primed mouse embryonic stem cells (ESCs). We find that the ground state ESCs cultured with GSK3-, MEK-inhibitors and LIF (2iL) display higher ribosome density on a selective set of mRNAs. This set of mRNAs undergo strong translational buffering to maintain stable protein expression levels in 2iL-ESCs. Importantly, we show that the global alteration of cellular proteome during the transition of naïve-to-primed pluripotency is largely accompanied by transcriptional rewiring. Thus, we provide a comprehensive and detailed overview of the global changes in gene expression in different states of ESCs and dissect the relative contributions of mRNA-transcription, translation and regulation of protein stability in controlling protein abundance. Translational control of gene expression can lead to significant divergence between mRNA and protein abundance. Here, the authors describe transcriptional rewiring and translational buffering during transition from naïve to primed pluripotency through quantitation of mRNA-abundance, translation rate and protein expression.
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29
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Panigrahi M, Kumar H, Sah V, Dillipkumar Verma A, Bhushan B, Parida S. Transcriptome profiling of buffalo endometrium reveals molecular signature distinct to early pregnancy. Gene 2020; 743:144614. [PMID: 32222532 DOI: 10.1016/j.gene.2020.144614] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 03/22/2020] [Accepted: 03/23/2020] [Indexed: 12/18/2022]
Abstract
Buffalo reproduction struggles with a high incidence of early embryonic mortality. Effective treatment and prevention strategies for this condition are not available due to lack of understanding of molecular pathways in early pregnancy of this species. In the present study, we have attempted to understand these molecular pathways by characterizing the endometrial transcriptomic profiles of pregnant buffalos during early pregnancy. For the transcriptome profiling, buffalo endometrial tissues of 29-36 days of pregnancy and of nonpregnant luteal phase were collected from the local slaughterhouse. We confirmed the status of pregnancy based on the crown vertebral length of the foetus. Total RNA was isolated and sequencing was performed using the Illumina nextseq platform. The raw reads were filtered and mapped to the Bos taurus UMD 3.1 reference genome assembly. An average of 24,597 genes was investigated for differential expression between the two groups. Transcriptome data identified a total of 450 differentially expressed genes (using a cut off value of log2 fold changes >2 and <-2) in early pregnancy in comparison to the nonpregnant group (Padj < 0.05). Among these, 270 genes were significantly upregulated and 180 genes were downregulated. The most impacted pathways were related to secretion, transport, ionic homeostasis, mitosis and negative regulation of viral processes. In conclusion, our study characterized a unique set of DEGs, during the early pregnancy of buffalo, which potentially modulate the endometrial environment to establish and maintain a successful pregnancy.
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Affiliation(s)
- Manjit Panigrahi
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Harshit Kumar
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Vaishali Sah
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Ankita Dillipkumar Verma
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Subhashree Parida
- Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
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Functional omics analyses reveal only minor effects of microRNAs on human somatic stem cell differentiation. Sci Rep 2020; 10:3284. [PMID: 32094412 PMCID: PMC7040006 DOI: 10.1038/s41598-020-60065-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 01/30/2020] [Indexed: 01/12/2023] Open
Abstract
The contribution of microRNA-mediated posttranscriptional regulation on the final proteome in differentiating cells remains elusive. Here, we evaluated the impact of microRNAs (miRNAs) on the proteome of human umbilical cord blood-derived unrestricted somatic stem cells (USSC) during retinoic acid (RA) differentiation by a systemic approach using next generation sequencing analysing mRNA and miRNA expression and quantitative mass spectrometry-based proteome analyses. Interestingly, regulation of mRNAs and their dedicated proteins highly correlated during RA-incubation. Additionally, RA-induced USSC demonstrated a clear separation from native USSC thereby shifting from a proliferating to a metabolic phenotype. Bioinformatic integration of up- and downregulated miRNAs and proteins initially implied a strong impact of the miRNome on the XXL-USSC proteome. However, quantitative proteome analysis of the miRNA contribution on the final proteome after ectopic overexpression of downregulated miR-27a-5p and miR-221-5p or inhibition of upregulated miR-34a-5p, respectively, followed by RA-induction revealed only minor proportions of differentially abundant proteins. In addition, only small overlaps of these regulated proteins with inversely abundant proteins in non-transfected RA-treated USSC were observed. Hence, mRNA transcription rather than miRNA-mediated regulation is the driving force for protein regulation upon RA-incubation, strongly suggesting that miRNAs are fine-tuning regulators rather than active primary switches during RA-induction of USSC.
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Joanisse S, Lim C, McKendry J, Mcleod JC, Stokes T, Phillips SM. Recent advances in understanding resistance exercise training-induced skeletal muscle hypertrophy in humans. F1000Res 2020; 9. [PMID: 32148775 PMCID: PMC7043134 DOI: 10.12688/f1000research.21588.1] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/18/2020] [Indexed: 12/22/2022] Open
Abstract
Skeletal muscle plays a pivotal role in the maintenance of physical and metabolic health and, critically, mobility. Accordingly, strategies focused on increasing the quality and quantity of skeletal muscle are relevant, and resistance exercise is foundational to the process of functional hypertrophy. Much of our current understanding of skeletal muscle hypertrophy can be attributed to the development and utilization of stable isotopically labeled tracers. We know that resistance exercise and sufficient protein intake act synergistically and provide the most effective stimuli to enhance skeletal muscle mass; however, the molecular intricacies that underpin the tremendous response variability to resistance exercise-induced hypertrophy are complex. The purpose of this review is to discuss recent studies with the aim of shedding light on key regulatory mechanisms that dictate hypertrophic gains in skeletal muscle mass. We also aim to provide a brief up-to-date summary of the recent advances in our understanding of skeletal muscle hypertrophy in response to resistance training in humans.
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Affiliation(s)
- Sophie Joanisse
- Exercise Metabolism Research Group, Department of Kinesiology, McMaster University, Hamilton, ON, Canada
| | - Changhyun Lim
- Exercise Metabolism Research Group, Department of Kinesiology, McMaster University, Hamilton, ON, Canada
| | - James McKendry
- Exercise Metabolism Research Group, Department of Kinesiology, McMaster University, Hamilton, ON, Canada
| | - Jonathan C Mcleod
- Exercise Metabolism Research Group, Department of Kinesiology, McMaster University, Hamilton, ON, Canada
| | - Tanner Stokes
- Exercise Metabolism Research Group, Department of Kinesiology, McMaster University, Hamilton, ON, Canada
| | - Stuart M Phillips
- Exercise Metabolism Research Group, Department of Kinesiology, McMaster University, Hamilton, ON, Canada
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Chen X, Sun YZ, Guan NN, Qu J, Huang ZA, Zhu ZX, Li JQ. Computational models for lncRNA function prediction and functional similarity calculation. Brief Funct Genomics 2020; 18:58-82. [PMID: 30247501 DOI: 10.1093/bfgp/ely031] [Citation(s) in RCA: 117] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 07/17/2018] [Accepted: 08/30/2018] [Indexed: 02/01/2023] Open
Abstract
From transcriptional noise to dark matter of biology, the rapidly changing view of long non-coding RNA (lncRNA) leads to deep understanding of human complex diseases induced by abnormal expression of lncRNAs. There is urgent need to discern potential functional roles of lncRNAs for further study of pathology, diagnosis, therapy, prognosis, prevention of human complex disease and disease biomarker detection at lncRNA level. Computational models are anticipated to be an effective way to combine current related databases for predicting most potential lncRNA functions and calculating lncRNA functional similarity on the large scale. In this review, we firstly illustrated the biological function of lncRNAs from five biological processes and briefly depicted the relationship between mutations or dysfunctions of lncRNAs and human complex diseases involving cancers, nervous system disorders and others. Then, 17 publicly available lncRNA function-related databases containing four types of functional information content were introduced. Based on these databases, dozens of developed computational models are emerging to help characterize the functional roles of lncRNAs. We therefore systematically described and classified both 16 lncRNA function prediction models and 9 lncRNA functional similarity calculation models into 8 types for highlighting their core algorithm and process. Finally, we concluded with discussions about the advantages and limitations of these computational models and future directions of lncRNA function prediction and functional similarity calculation. We believe that constructing systematic functional annotation systems is essential to strengthen the prediction accuracy of computational models, which will accelerate the identification process of novel lncRNA functions in the future.
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Affiliation(s)
- Xing Chen
- School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China
| | - Ya-Zhou Sun
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
| | - Na-Na Guan
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
| | - Jia Qu
- School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China
| | - Zhi-An Huang
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
| | - Ze-Xuan Zhu
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
| | - Jian-Qiang Li
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
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33
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Wong KC, Yan S, Lin Q, Li X, Peng C. Deleterious Non-Synonymous Single Nucleotide Polymorphism Predictions on Human Transcription Factors. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2020; 17:327-333. [PMID: 30475727 DOI: 10.1109/tcbb.2018.2882548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Transcription factors (TFs) are the major components of human gene regulation. In particular, they bind onto specific DNA sequences and regulate neighborhood genes in different tissues at different developmental stages. Non-synonymous single nucleotide polymorphisms on its protein-coding sequences could result in undesired consequences in human. Therefore, it is necessary to develop methods for predicting any abnormality among those non-synonymous single nucleotide polymorphisms. To address it, we have developed and compared different strategies to predict deleterious non-synonymous single nucleotide polymorphisms (also known as missense mutations) on the protein-coding sequences of human TFs. Taking advantage of evolutionary conservation signals, we have developed and compared different classifiers with different feature sets as computed from different evolutionarily related sequence collections. The results indicate that the classic ensemble algorithm, Adaboost with decision stumps, with orthologous sequence collection, has performed the best (namely, TFmedic). We have further compared TFmedic with other state-of-the-arts methods (i.e., PolyPhen-2 and SIFT) on PolyPhen-2's own datasets, demonstrating that TFmedic can outperform the others. As applications, we have further applied TFmedic to all possible missense mutations on all human transcription factors; the proteome-wide results reveal interesting insights, consistent with the existing physiochemical knowledge. A case study with the actual 3D structure is conducted, revealing how TFmedic can be contributed to protein-DNA binding complex studies.
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Abstract
The premise of this book is the importance of the tumor microenvironment (TME). Until recently, most research on and clinical attention to cancer biology, diagnosis, and prognosis were focused on the malignant (or premalignant) cellular compartment that could be readily appreciated using standard morphology-based imaging.
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35
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Using Nanopore Whole-Transcriptome Sequencing for Human Leukocyte Antigen Genotyping and Correlating Donor Human Leukocyte Antigen Expression with Flow Cytometric Crossmatch Results. J Mol Diagn 2020; 22:101-110. [DOI: 10.1016/j.jmoldx.2019.09.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 08/27/2019] [Accepted: 09/11/2019] [Indexed: 01/07/2023] Open
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36
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Wang S, Mao C, Liu S. Peptides encoded by noncoding genes: challenges and perspectives. Signal Transduct Target Ther 2019; 4:57. [PMID: 31871775 PMCID: PMC6908703 DOI: 10.1038/s41392-019-0092-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Revised: 10/17/2019] [Accepted: 10/27/2019] [Indexed: 01/01/2023] Open
Abstract
In recent years, noncoding gene (NCG) translation events have been frequently discovered. The resultant peptides, as novel findings in the life sciences, perform unexpected functions of increasingly recognized importance in many fundamental biological and pathological processes. The emergence of these novel peptides, in turn, has advanced the field of genomics while indispensably aiding living organisms. The peptides from NCGs serve as important links between extracellular stimuli and intracellular adjustment mechanisms. These peptides are also important entry points for further exploration of the mysteries of life that may trigger a new round of revolutionary biotechnological discoveries. Insights into NCG-derived peptides will assist in understanding the secrets of life and the causes of diseases, and will also open up new paths to the treatment of diseases such as cancer. Here, a critical review is presented on the action modes and biological functions of the peptides encoded by NCGs. The challenges and future trends in searching for and studying NCG peptides are also critically discussed.
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Affiliation(s)
- Shuo Wang
- Changhai Hospital, Shanghai, 200433 China
| | - Chuanbin Mao
- Department of Chemistry and Biochemistry, Stephenson Life Sciences Research Center, Institute for Biomedical Engineering, Science and Technology, University of Oklahoma, 101 Stephenson Parkway, Norman, OK 73019-5300 USA
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37
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Pérez-Ortín JE, Tordera V, Chávez S. Homeostasis in the Central Dogma of molecular biology: the importance of mRNA instability. RNA Biol 2019; 16:1659-1666. [PMID: 31418631 PMCID: PMC6844571 DOI: 10.1080/15476286.2019.1655352] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 07/22/2019] [Accepted: 08/04/2019] [Indexed: 12/29/2022] Open
Abstract
Cell survival requires the control of biomolecule concentration, i.e. biomolecules should approach homeostasis. With information-carrying macromolecules, the particular concentration variation ranges depend on each type: DNA is not buffered, but mRNA and protein concentrations are homeostatically controlled, which leads to the ribostasis and proteostasis concepts. In recent years, we have studied the particular features of mRNA ribostasis and proteostasis in the model organism S. cerevisiae. Here we extend this study by comparing published data from three other model organisms: E. coli, S. pombe and cultured human cells. We describe how mRNA ribostasis is less strict than proteostasis. A constant ratio appears between the average decay and dilution rates during cell growth for mRNA, but not for proteins. We postulate that this is due to a trade-off between the cost of synthesis and the response capacity. This compromise takes place at the transcription level, but is not possible at the translation level as the high stability of proteins, versus that of mRNAs, precludes it. We hypothesize that the middle-place role of mRNA in the Central Dogma of Molecular Biology and its chemical instability make it more suitable than proteins for the fast changes needed for gene regulation.
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Affiliation(s)
| | | | - Sebastián Chávez
- Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario Virgen del Rocío. Campus Hospital Universitario Virgen del Rocío, Seville, Spain
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38
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Jin L, Li L, Hu C, Paez-Cortez J, Bi Y, Macoritto M, Cao S, Tian Y. Integrative Analysis of Transcriptomic and Proteomic Profiling in Inflammatory Bowel Disease Colon Biopsies. Inflamm Bowel Dis 2019; 25:1906-1918. [PMID: 31173627 DOI: 10.1093/ibd/izz111] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Indexed: 12/19/2022]
Abstract
BACKGROUND Crohn's disease (CD) and ulcerative colitis (UC) are intestinal chronic inflammatory conditions characterized by altered epithelial barrier function and tissue damage. Despite significant efforts to understanding the biological mechanisms responsible for gut inflammation, the pathophysiology of CD and UC remains poorly understood. METHODS To help elucidate the potential mechanisms responsible for gut inflammation in CD and UC, transcriptomic and proteomic profiling of human colon biopsy specimens was performed. Dysregulated genes and proteins in disease tissues compared with normal tissues were characterized from the expression profiles and further subjected to pathway analysis to identify altered biological processes and signaling pathways. RESULTS Sample analysis showed 4250 genes with matched protein expression and a wide range of correlation of RNA-protein abundance across samples. Pathway analysis of dysregulated genes and proteins in CD and UC showed alterations in immune and inflammatory responses, complement cascade, and the suppression of metabolic processes and PPAR signaling. In CD, increased T-helper cell differentiation and elevated toll-like receptor and JAK/STAT signaling were observed. Interestingly, increased MAPK signaling was only observed in UC. Weighted gene co-expression network analysis suggested a possible role of epigenetic regulation in UC. Of note, a large discrepancy between regulation of RNA and protein levels in inflamed colon samples was detected for previously identified biomarkers including MMP14 and LAMP1. CONCLUSIONS With the analysis of dysregulated genes and pathways, the present study unravels key mechanisms contributing to CD and UC pathogenesis and emphasizes that integrative analysis of multi-omics data sets can provide more insight into understanding complex disease mechanisms.
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Affiliation(s)
- Liang Jin
- AbbVie Bioresearch Center, Worcester, Massachusetts, USA
| | - Li Li
- Boehringer Ingelheim, Ridgefield, Connecticut, USA
| | - Chenqi Hu
- AbbVie Bioresearch Center, Worcester, Massachusetts, USA
| | | | - Yingtao Bi
- AbbVie Bioresearch Center, Worcester, Massachusetts, USA
| | | | - Sherry Cao
- AbbVie Bioresearch Center, Worcester, Massachusetts, USA
| | - Yu Tian
- AbbVie Bioresearch Center, Worcester, Massachusetts, USA
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39
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Wang S, Li M, Xing L, Yu J. High expression level of peptidylprolyl isomerase A is correlated with poor prognosis of liver hepatocellular carcinoma. Oncol Lett 2019; 18:4691-4702. [PMID: 31611978 PMCID: PMC6781733 DOI: 10.3892/ol.2019.10846] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Accepted: 08/20/2019] [Indexed: 12/19/2022] Open
Abstract
Peptidylprolyl isomerase A (PPIA) has been reported to be correlated with cancer. The present study investigated the prognostic values of PPIA expression levels in cancer by comparing different types of cancer using databases. High expression levels of PPIA were observed in 17 out of 17 cancer types compared with normal adjacent tissues. High expression levels of PPIA were associated with decreased overall survival in low grade glioma, acute myeloid leukemia, lung adenocarcinoma, skin cutaneous melanoma and liver hepatocellular carcinoma (LIHC). The prognostic effect of PPIA expression in LIHC was independent of tumor grade. High expression levels of PPIA were of particular prognostic value in stage 3, American Joint Committee on Cancer Tumor 3, hepatitis B virus negative and sorafenib-administered subgroups in LIHC. The expression level of PPIA was significantly associated with levels of basigin and signal transducer and activator of transcription 3, which may be major effectors of PPIA in the progression of the cancer.
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Affiliation(s)
- Shilong Wang
- Department of Clinical Medicine, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, P.R. China.,Department of Radiation Oncology, Shandong Cancer Hospital Affiliated to Shandong University, Jinan, Shandong 250117, P.R. China
| | - Minghuan Li
- Department of Radiation Oncology, Shandong Cancer Hospital Affiliated to Shandong University, Jinan, Shandong 250117, P.R. China.,Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong Academy of Medical Sciences, Jinan, Shandong 250117, P.R. China
| | - Ligang Xing
- Department of Radiation Oncology, Shandong Cancer Hospital Affiliated to Shandong University, Jinan, Shandong 250117, P.R. China.,Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong Academy of Medical Sciences, Jinan, Shandong 250117, P.R. China
| | - Jinming Yu
- Department of Radiation Oncology, Shandong Cancer Hospital Affiliated to Shandong University, Jinan, Shandong 250117, P.R. China.,Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong Academy of Medical Sciences, Jinan, Shandong 250117, P.R. China
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40
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Wong KC, Lin J, Li X, Lin Q, Liang C, Song YQ. Heterodimeric DNA motif synthesis and validations. Nucleic Acids Res 2019; 47:1628-1636. [PMID: 30590725 PMCID: PMC6393289 DOI: 10.1093/nar/gky1297] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 12/04/2018] [Accepted: 12/19/2018] [Indexed: 02/06/2023] Open
Abstract
Bound by transcription factors, DNA motifs (i.e. transcription factor binding sites) are prevalent and important for gene regulation in different tissues at different developmental stages of eukaryotes. Although considerable efforts have been made on elucidating monomeric DNA motif patterns, our knowledge on heterodimeric DNA motifs are still far from complete. Therefore, we propose to develop a computational approach to synthesize a heterodimeric DNA motif from two monomeric DNA motifs. The approach is sequentially divided into two components (Phases A and B). In Phase A, we propose to develop the inference models on how two DNA monomeric motifs can be oriented and overlapped with each other at nucleotide level. In Phase B, given the two monomeric DNA motifs oriented, we further propose to develop DNA-binding family-specific input-output hidden Markov models (IOHMMs) to synthesize a heterodimeric DNA motif. To validate the approach, we execute and cross-validate it with the experimentally verified 618 heterodimeric DNA motifs across 49 DNA-binding family combinations. We observe that our approach can even "rescue" the existing heterodimeric DNA motif pattern (i.e. HOXB2_EOMES) previously published on Nature. Lastly, we apply the proposed approach to infer previously uncharacterized heterodimeric motifs. Their motif instances are supported by DNase accessibility, gene ontology, protein-protein interactions, in vivo ChIP-seq peaks, and even structural data from PDB. A public web-server is built for open accessibility and scientific impact. Its address is listed as follows: http://motif.cs.cityu.edu.hk/custom/MotifKirin.
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Affiliation(s)
- Ka-Chun Wong
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong SAR
| | - Jiecong Lin
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong SAR
| | - Xiangtao Li
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong SAR
| | - Qiuzhen Lin
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
| | - Cheng Liang
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - You-Qiang Song
- School of Biomedical Sciences, University of Hong Kong, Pokfulam, Hong Kong SAR
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41
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Li JJ, Chew GL, Biggin MD. Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes. Genome Biol 2019; 20:162. [PMID: 31399036 PMCID: PMC6689182 DOI: 10.1186/s13059-019-1761-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 07/11/2019] [Indexed: 12/17/2022] Open
Abstract
Background General translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood. Results Here, we show that these sequence features specify 42–81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25–60 nucleotide segments within mRNA 5′ regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5′ regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA. Conclusions Our work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell. Electronic supplementary material The online version of this article (10.1186/s13059-019-1761-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jingyi Jessica Li
- Department of Statistics, Department of Biomathematics, and Department of Human Genetics, University of California, Los Angeles, CA, 90095, USA.
| | - Guo-Liang Chew
- Computational Biology Program, Public Health Sciences and Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Mark Douglas Biggin
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94708, USA.
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42
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Aguiar VRC, César J, Delaneau O, Dermitzakis ET, Meyer D. Expression estimation and eQTL mapping for HLA genes with a personalized pipeline. PLoS Genet 2019; 15:e1008091. [PMID: 31009447 PMCID: PMC6497317 DOI: 10.1371/journal.pgen.1008091] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 05/02/2019] [Accepted: 03/13/2019] [Indexed: 01/07/2023] Open
Abstract
The HLA (Human Leukocyte Antigens) genes are well-documented targets of balancing selection, and variation at these loci is associated with many disease phenotypes. Variation in expression levels also influences disease susceptibility and resistance, but little information exists about the regulation and population-level patterns of expression. This results from the difficulty in mapping short reads originated from these highly polymorphic loci, and in accounting for the existence of several paralogues. We developed a computational pipeline to accurately estimate expression for HLA genes based on RNA-seq, improving both locus-level and allele-level estimates. First, reads are aligned to all known HLA sequences in order to infer HLA genotypes, then quantification of expression is carried out using a personalized index. We use simulations to show that expression estimates obtained in this way are not biased due to divergence from the reference genome. We applied our pipeline to the GEUVADIS dataset, and compared the quantifications to those obtained with reference transcriptome. Although the personalized pipeline recovers more reads, we found that using the reference transcriptome produces estimates similar to the personalized pipeline (r ≥ 0.87) with the exception of HLA-DQA1. We describe the impact of the HLA-personalized approach on downstream analyses for nine classical HLA loci (HLA-A, HLA-C, HLA-B, HLA-DRA, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, HLA-DPB1). Although the influence of the HLA-personalized approach is modest for eQTL mapping, the p-values and the causality of the eQTLs obtained are better than when the reference transcriptome is used. We investigate how the eQTLs we identified explain variation in expression among lineages of HLA alleles. Finally, we discuss possible causes underlying differences between expression estimates obtained using RNA-seq, antibody-based approaches and qPCR. The level at which a gene is expressed can have important influence on the phenotype of an organism, including its predisposition to develop diseases. One way to estimate gene expression is by quantifying the abundance of RNA. RNA-seq has become the method of choice to provide such estimates at the genomewide scale. However, the application of RNA-seq to HLA genes —key players in the immune adaptive response— has remained a rarely explored approach. This is due to the problem of mapping bias, which causes deficient read alignment at genes which are very polymorphic and different from the reference genome. This has motivated approaches that replace the single reference genome with personalized sequences, comprised of the individual’s specific HLA genotype. Here we explore the use of computational frameworks to obtain reliable expression levels for HLA genes from RNA-seq datasets. We present a pipeline in which the quantification of HLA expression is carried out using methods which account for HLA diversity, avoiding the biases of standard approaches. We then evaluate the impact of this form of quantifying HLA expression on downstream analyses. The pipeline also allows us to integrate information on eQTLs with expression levels at the HLA allele-level, which can help disentangle different contributions to disease phenotypes and help understand the regulatory architecture at the HLA region.
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Affiliation(s)
- Vitor R. C. Aguiar
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
- * E-mail: (VRCA); (DM)
| | - Jônatas César
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - Olivier Delaneau
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Emmanouil T. Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Diogo Meyer
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
- * E-mail: (VRCA); (DM)
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43
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Damiani C, Maspero D, Di Filippo M, Colombo R, Pescini D, Graudenzi A, Westerhoff HV, Alberghina L, Vanoni M, Mauri G. Integration of single-cell RNA-seq data into population models to characterize cancer metabolism. PLoS Comput Biol 2019; 15:e1006733. [PMID: 30818329 PMCID: PMC6413955 DOI: 10.1371/journal.pcbi.1006733] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 03/12/2019] [Accepted: 12/22/2018] [Indexed: 02/07/2023] Open
Abstract
Metabolic reprogramming is a general feature of cancer cells. Regrettably, the comprehensive quantification of metabolites in biological specimens does not promptly translate into knowledge on the utilization of metabolic pathways. By estimating fluxes across metabolic pathways, computational models hold the promise to bridge this gap between data and biological functionality. These models currently portray the average behavior of cell populations however, masking the inherent heterogeneity that is part and parcel of tumorigenesis as much as drug resistance. To remove this limitation, we propose single-cell Flux Balance Analysis (scFBA) as a computational framework to translate single-cell transcriptomes into single-cell fluxomes. We show that the integration of single-cell RNA-seq profiles of cells derived from lung adenocarcinoma and breast cancer patients into a multi-scale stoichiometric model of a cancer cell population: significantly 1) reduces the space of feasible single-cell fluxomes; 2) allows to identify clusters of cells with different growth rates within the population; 3) points out the possible metabolic interactions among cells via exchange of metabolites. The scFBA suite of MATLAB functions is available at https://github.com/BIMIB-DISCo/scFBA, as well as the case study datasets. Cytotoxicity of chemotherapeutic agents and resistance to targeted treatments are the main reasons why cancer is still one of the top causes of death. As tumor cells are intrinsically resistant to therapies that target signaling pathways, targeting the metabolic hallmarks of cancer holds promise for more incisive treatments. Regrettably, the heterogeneity of cancer metabolism hinders the identification of effective treatments. To fully uncover the metabolic heterogeneity within tumors, characterization of metabolic programs (metabolic flux distributions) at the single-cell level is required. To fill the gap between current technologies for genomics and future technologies for fluxomics, both at the single-cell and the genome-wide scale, we propose to integrate cancer data from: 1) single-cell transcriptomics and 2) bulk metabolomics, into a multi-scale stoichiometric model, to deliver for the first time metabolic fluxomes at the single-cell level. To this end, we introduce a new paradigm for flux balance analysis and data integration in cancer metabolism to: 1) characterize metabolic heterogeneity, not only at the inter-, but also at the intra-tumor level 2) identify the metabolic interactions between cancer populations, whose role in resistance to metabolic treatments has been recently recognized 3) predict the collective response to drug targeting of metabolism.
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Affiliation(s)
- Chiara Damiani
- Dept. of Informatics, Systems and Communication, University of Milan-Bicocca, 20126, Milan, Italy
- SYSBIO Centre of Systems Biology, 20126, Milan, Italy
- * E-mail:
| | - Davide Maspero
- Dept. of Biotechnology and Biosciences, University of Milan-Bicocca, 20126, Milan, Italy
- Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Marzia Di Filippo
- SYSBIO Centre of Systems Biology, 20126, Milan, Italy
- Dept. of Biotechnology and Biosciences, University of Milan-Bicocca, 20126, Milan, Italy
| | - Riccardo Colombo
- Dept. of Informatics, Systems and Communication, University of Milan-Bicocca, 20126, Milan, Italy
- SYSBIO Centre of Systems Biology, 20126, Milan, Italy
| | - Dario Pescini
- SYSBIO Centre of Systems Biology, 20126, Milan, Italy
- Dept. of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126, Milan, Italy
| | - Alex Graudenzi
- Dept. of Informatics, Systems and Communication, University of Milan-Bicocca, 20126, Milan, Italy
| | - Hans Victor Westerhoff
- Dept. of Molecular Cell Physiology, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands
- Manchester Centre for Integrative Systems Biology, School of Chemical Engineering and Analytical Science, University of Manchester, Manchester, United Kingdom
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands
| | - Lilia Alberghina
- SYSBIO Centre of Systems Biology, 20126, Milan, Italy
- Dept. of Biotechnology and Biosciences, University of Milan-Bicocca, 20126, Milan, Italy
| | - Marco Vanoni
- SYSBIO Centre of Systems Biology, 20126, Milan, Italy
- Dept. of Biotechnology and Biosciences, University of Milan-Bicocca, 20126, Milan, Italy
| | - Giancarlo Mauri
- Dept. of Informatics, Systems and Communication, University of Milan-Bicocca, 20126, Milan, Italy
- SYSBIO Centre of Systems Biology, 20126, Milan, Italy
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44
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Tahmasebi S, Amiri M, Sonenberg N. Translational Control in Stem Cells. Front Genet 2019; 9:709. [PMID: 30697227 PMCID: PMC6341023 DOI: 10.3389/fgene.2018.00709] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 12/17/2018] [Indexed: 11/13/2022] Open
Abstract
Simultaneous measurements of mRNA and protein abundance and turnover in mammalian cells, have revealed that a significant portion of the cellular proteome is controlled by mRNA translation. Recent studies have demonstrated that both embryonic and somatic stem cells are dependent on low translation rates to maintain an undifferentiated state. Conversely, differentiation requires increased protein synthesis and failure to do so prevents differentiation. Notably, the low translation in stem cell populations is independent of the cell cycle, indicating that stem cells use unique strategies to decouple these fundamental cellular processes. In this chapter, we discuss different mechanisms used by stem cells to control translation, as well as the developmental consequences of translational deregulation.
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Affiliation(s)
- Soroush Tahmasebi
- Department of Pharmacology, University of Illinois at Chicago, Chicago, IL, United States
| | - Mehdi Amiri
- Goodman Cancer Research Center, McGill University, Montreal, QC, Canada.,Department of Biochemistry, McGill University, Montreal, QC, Canada
| | - Nahum Sonenberg
- Goodman Cancer Research Center, McGill University, Montreal, QC, Canada.,Department of Biochemistry, McGill University, Montreal, QC, Canada
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45
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Cai Y, Zhang Y, Ke X, Guo Y, Yao C, Tang N, Pang P, Xie G, Fang L, Zhang Z, Li J, Fan Y, He X, Wen R, Pei L, Lu Y. Transcriptome Sequencing Unravels Potential Biomarkers at Different Stages of Cerebral Ischemic Stroke. Front Genet 2019; 10:814. [PMID: 31681398 PMCID: PMC6798056 DOI: 10.3389/fgene.2019.00814] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2019] [Accepted: 08/06/2019] [Indexed: 01/14/2023] Open
Abstract
Ischemic stroke, which accounts for 87% of all strokes, constitutes the leading cause of morbidity and mortality in China. Although the genetics and epigenetics of stroke have been extensively investigated, few studies have examined their relationships at different stages of stroke. This study assessed the characteristics of transcriptome changes at different stages of ischemic stroke using a mouse model of transient middle cerebral artery occlusion (tMCAO) and bioinformatics analyses. Cerebral cortex tissues from tMCAO mice at days 1, 3, 7, 14, and 28 were removed for RNA-Seq and small RNA-Seq library construction, sequencing, and bioinformatics analysis. We identified differentially expressed (DE) genes and miRNAs and revealed an association of the up-regulated or down-regulated DEmiRNAs with the correspondingly altered DEgene targets at each time point. In addition, different biological pathways were activated at different time points; thus, three groups of miRNAs were verified that may represent potential clinical biomarkers corresponding to days 1, 3, and 7 after ischemic stroke. Notably, this represents the first functional association of some of these miRNAs with stroke, e.g., miR-2137, miR-874-5p, and miR-5099. Together, our findings lay the foundation for the transition from a single-point, single-drug stroke treatment approach to multiple-time-point multi-drug combination therapies.
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Affiliation(s)
- You Cai
- Department of Pathology and Pathophysiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- The Institute for Brain Research (IBR), Collaborative Innovation Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
| | - Yufen Zhang
- The Institute for Brain Research (IBR), Collaborative Innovation Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Neurobiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiao Ke
- Department of Pathology and Pathophysiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- The Institute for Brain Research (IBR), Collaborative Innovation Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
| | - Yu Guo
- Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji College of Medicine, Huazhong University of Science & Technology, Wuhan, China
| | - Chengye Yao
- Department of Neurology, Union Hospital, Tongji College of Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Na Tang
- Department of Pathology, Maternal and Child Health Hospital of Hubei Province, Wuhan, China
| | - Pei Pang
- Department of Pathology and Pathophysiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- The Institute for Brain Research (IBR), Collaborative Innovation Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
| | - Gangcai Xie
- Medical School, Institute of Reproductive Medicine, Nantong University, Nantong, China
| | - Li Fang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Zhe Zhang
- Department of Physiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jincheng Li
- Department of Physiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yixian Fan
- Department of Physiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ximiao He
- Department of Physiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruojian Wen
- Department of Physiology, School of Medicine, Jianghan University, Wuhan, China
| | - Lei Pei
- The Institute for Brain Research (IBR), Collaborative Innovation Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Neurobiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Lei Pei, ; Youming Lu,
| | - Youming Lu
- The Institute for Brain Research (IBR), Collaborative Innovation Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Physiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Lei Pei, ; Youming Lu,
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Luecken MD, Page MJT, Crosby AJ, Mason S, Reinert G, Deane CM. CommWalker: correctly evaluating modules in molecular networks in light of annotation bias. Bioinformatics 2019; 34:994-1000. [PMID: 29112702 PMCID: PMC5860269 DOI: 10.1093/bioinformatics/btx706] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 11/02/2017] [Indexed: 11/24/2022] Open
Abstract
Motivation Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favor communities of well-studied proteins. Results We propose a novel framework for the evaluation of communities as functional modules. Our proposed framework, CommWalker, takes communities as inputs and evaluates them in their local network environment by performing short random walks. We test CommWalker’s ability to overcome annotation bias using input communities from four community detection methods on two protein interaction networks. We find that modules accepted by CommWalker are similarly co-expressed as those accepted by current methods. Crucially, CommWalker performs well not only in well-annotated regions, but also in regions otherwise obscured by poor annotation. CommWalker community prioritization both faithfully captures well-validated communities and identifies functional modules that may correspond to more novel biology. Availability and implementation The CommWalker algorithm is freely available at opig.stats.ox.ac.uk/resources or as a docker image on the Docker Hub at hub.docker.com/r/lueckenmd/commwalker/. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- M D Luecken
- Department of Statistics, University of Oxford, Oxford, UK
- Doctoral Training Centre, University of Oxford, Oxford, UK
| | - M J T Page
- Department of Informatics, UCB Pharma, Slough, UK
| | - A J Crosby
- Immunology Therapeutic Area, UCB Pharma, Slough, UK
| | - S Mason
- Immunology Therapeutic Area, UCB Pharma, Slough, UK
| | - G Reinert
- Department of Statistics, University of Oxford, Oxford, UK
| | - C M Deane
- Department of Statistics, University of Oxford, Oxford, UK
- Doctoral Training Centre, University of Oxford, Oxford, UK
- To whom correspondence should be addressed.
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Gangalum RK, Kim D, Kashyap RK, Mangul S, Zhou X, Elashoff D, Bhat SP. Spatial Analysis of Single Fiber Cells of the Developing Ocular Lens Reveals Regulated Heterogeneity of Gene Expression. iScience 2018; 10:66-79. [PMID: 30508719 PMCID: PMC6277220 DOI: 10.1016/j.isci.2018.11.024] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 11/08/2018] [Accepted: 11/13/2018] [Indexed: 01/19/2023] Open
Abstract
The developing eye lens presents an exceptional paradigm for spatial transcriptomics. It is composed of highly organized long, slender transparent fiber cells, which differentiate from the edges of the anterior epithelium of the lens (equator), attended by high expression of crystallins, which generates transparency. Every fiber cell, therefore, is an optical unit whose refractive properties derive from its gene activity. Here, we probe this tangible relationship between the gene activity and the phenotype by studying the expression of all known 17 crystallins and 77 other non-crystallin genes in single fiber cells isolated from three states/regions of differentiation, allowing us to follow molecular progression at the single-cell level. The data demonstrate highly variable gene activity in cortical fibers, interposed between the nascent and the terminally differentiated fiber cell transcription. These data suggest that the so-called stochastic, highly heterogeneous gene activity is a regulated intermediate in the realization of a functional phenotype.
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Affiliation(s)
- Rajendra K Gangalum
- Stein Eye Institute, Geffen School of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - Dongjae Kim
- Stein Eye Institute, Geffen School of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - Raj K Kashyap
- Stein Eye Institute, Geffen School of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - Serghei Mangul
- Department of Computer Science and Human Genetics, University of California, Los Angeles, CA 90095-7000, USA
| | - Xinkai Zhou
- Department of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - David Elashoff
- Department of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - Suraj P Bhat
- Stein Eye Institute, Geffen School of Medicine, University of California, Los Angeles, CA 90095-7000, USA; Brain Research Institute, University of California, Los Angeles, CA 90095-7000, USA; Molecular Biology Institute, University of California, Los Angeles, CA 90095-7000, USA.
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48
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Bauer CM, Fudickar AM, Anderson-Buckingham S, Abolins-Abols M, Atwell JW, Ketterson ED, Greives TJ. Seasonally sympatric but allochronic: differential expression of hypothalamic genes in a songbird during gonadal development. Proc Biol Sci 2018; 285:20181735. [PMID: 30355713 PMCID: PMC6234895 DOI: 10.1098/rspb.2018.1735] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Accepted: 10/04/2018] [Indexed: 12/16/2022] Open
Abstract
Allochrony, the mismatch of reproductive schedules, is one mechanism that can mediate sympatric speciation and diversification. In songbirds, the transition into breeding condition and gonadal growth is regulated by the hypothalamic-pituitary-gonadal (HPG) axis at multiple levels. We investigated whether the difference in reproductive timing between two seasonally sympatric subspecies of dark-eyed juncos (Junco hyemalis) was related to gene expression along the HPG axis. During the sympatric pre-breeding stage, we measured hypothalamic and testicular mRNA expression of candidate genes via qPCR in captive male juncos. For hypothalamic mRNA, we found our earlier breeding subspecies had increased expression of gonadotropin-releasing hormone (GnRH) and decreased expression of androgen receptor, oestrogen receptor alpha and mineralocorticoid receptor (MR). Subspecies did not differ in expression of hypothalamic gonadotropin-inhibitory hormone (GnIH) and glucocorticoid receptor (GR). While our earlier breeding subspecies had higher mRNA expression of testicular GR, subspecies did not differ in testicular luteinizing hormone receptor, follicle-stimulating hormone receptor or MR mRNA expression levels. Our findings indicate increased GnRH production and decreased hypothalamic sensitivity to sex steroid negative feedback as factors promoting differences in the timing of gonadal recrudescence between recently diverged populations. Differential gene expression along the HPG axis may facilitate species diversification under seasonal sympatry.
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Affiliation(s)
- Carolyn M Bauer
- Department of Biology, Adelphi University, Garden City, NY, USA
| | - Adam M Fudickar
- Environmental Resilience Institute, Indiana University, Bloomington, IN, USA
- Department of Biology, Indiana University, Bloomington, IN, USA
| | | | - Mikus Abolins-Abols
- Department of Biology, Indiana University, Bloomington, IN, USA
- Department of Animal Biology, University of Illinois Urbana Champaign, Urbana, IL, USA
| | | | - Ellen D Ketterson
- Environmental Resilience Institute, Indiana University, Bloomington, IN, USA
- Department of Biology, Indiana University, Bloomington, IN, USA
| | - Timothy J Greives
- Department of Biological Sciences, North Dakota State University, Fargo, ND, USA
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Saxena A, Dagur PK, Desai A, McCoy JP. Ultrasensitive Quantification of Cytokine Proteins in Single Lymphocytes From Human Blood Following ex-vivo Stimulation. Front Immunol 2018; 9:2462. [PMID: 30405640 PMCID: PMC6206239 DOI: 10.3389/fimmu.2018.02462] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 10/04/2018] [Indexed: 12/27/2022] Open
Abstract
In this study we demonstrate the feasibility of direct, quantitative measurement of cytokine proteins in single human CD8 lymphocytes from fresh peripheral blood of healthy donors following a brief ex vivo stimulation. Cytokine-secreting cells were identified using cell surface “catch” reagents and single cell data were obtained by sorting of individual cytokine-secreting cells into 96 well plates containing lysis buffer followed by analysis using ultrasensitive immunoassays for interferon gamma (IFN-γ) and tumor necrosis factor alpha (TNF-α). CD8 cells negative for cytokine production, as determined by the cell surface catch reagents were used as negative controls. Furthermore, studies were undertaken to compare the mean fluorescence intensity (MFI) values of cytokine staining by flow cytometry with the quantification of cytokines using the current method. This study demonstrates that it is feasible to quantify cytokines from individual primary cells. A shift from qualitative to quantitative determinations of cytokine protein levels in single cells will permit more precise and reproducible studies of heterogeneity in the immune system and can be accomplished with readily available instrumentation.
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Affiliation(s)
- Ankit Saxena
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Pradeep K Dagur
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Alisha Desai
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - John Philip McCoy
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
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Affiliation(s)
- Julia di Iulio
- The Scripps Research Institute, 3344 N Torrey Pines Rd, La Jolla, CA 92037, USA
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