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Blanco-Luquin I, Acha B, Urdánoz-Casado A, Gómez-Orte E, Roldan M, Pérez-Rodríguez DR, Cabello J, Mendioroz M. NXN Gene Epigenetic Changes in an Adult Neurogenesis Model of Alzheimer's Disease. Cells 2022; 11:cells11071069. [PMID: 35406633 PMCID: PMC8998146 DOI: 10.3390/cells11071069] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 03/17/2022] [Accepted: 03/20/2022] [Indexed: 12/10/2022] Open
Abstract
In view of the proven link between adult hippocampal neurogenesis (AHN) and learning and memory impairment, we generated a straightforward adult neurogenesis in vitro model to recapitulate DNA methylation marks in the context of Alzheimer’s disease (AD). Neural progenitor cells (NPCs) were differentiated for 29 days and Aβ peptide 1–42 was added. mRNA expression of Neuronal Differentiation 1 (NEUROD1), Neural Cell Adhesion Molecule 1 (NCAM1), Tubulin Beta 3 Class III (TUBB3), RNA Binding Fox-1 Homolog 3 (RBFOX3), Calbindin 1 (CALB1), and Glial Fibrillary Acidic Protein (GFAP) was determined by RT-qPCR to characterize the culture and framed within the multistep process of AHN. Hippocampal DNA methylation marks previously identified in Contactin-Associated Protein 1 (CNTNAP1), SEPT5-GP1BB Readthrough (SEPT5-GP1BB), T-Box Transcription Factor 5 (TBX5), and Nucleoredoxin (NXN) genes were profiled by bisulfite pyrosequencing or bisulfite cloning sequencing; mRNA expression was also measured. NXN outlined a peak of DNA methylation overlapping type 3 neuroblasts. Aβ-treated NPCs showed transient decreases of mRNA expression for SEPT5-GP1BB and NXN on day 9 or 19 and an increase in DNA methylation on day 29 for NXN. NXN and SEPT5-GP1BB may reflect alterations detected in the brain of AD human patients, broadening our understanding of this disease.
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Affiliation(s)
- Idoia Blanco-Luquin
- Neuroepigenetics Laboratory-Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA (Navarra Institute for Health Research), 31008 Pamplona, Spain; (B.A.); (A.U.-C.); (M.R.); (M.M.)
- Correspondence: ; Tel.: +34-848425739
| | - Blanca Acha
- Neuroepigenetics Laboratory-Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA (Navarra Institute for Health Research), 31008 Pamplona, Spain; (B.A.); (A.U.-C.); (M.R.); (M.M.)
| | - Amaya Urdánoz-Casado
- Neuroepigenetics Laboratory-Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA (Navarra Institute for Health Research), 31008 Pamplona, Spain; (B.A.); (A.U.-C.); (M.R.); (M.M.)
| | - Eva Gómez-Orte
- CIBIR (Center for Biomedical Research of La Rioja), 26006 Logroño, Spain; (E.G.-O.); (J.C.)
| | - Miren Roldan
- Neuroepigenetics Laboratory-Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA (Navarra Institute for Health Research), 31008 Pamplona, Spain; (B.A.); (A.U.-C.); (M.R.); (M.M.)
| | - Diego R. Pérez-Rodríguez
- Neurophysiology Department, Hospital Universitario de Navarra (HUN), IdiSNA (Navarra Institute for Health Research), 31008 Pamplona, Spain;
| | - Juan Cabello
- CIBIR (Center for Biomedical Research of La Rioja), 26006 Logroño, Spain; (E.G.-O.); (J.C.)
| | - Maite Mendioroz
- Neuroepigenetics Laboratory-Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA (Navarra Institute for Health Research), 31008 Pamplona, Spain; (B.A.); (A.U.-C.); (M.R.); (M.M.)
- Department of Neurology, Hospital Universitario de Navarra (HUN), IdiSNA (Navarra Institute for Health Research), 31008 Pamplona, Spain
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Anam MB, Ahmad SAI, Kudo M, Istiaq A, Felemban AAM, Ito N, Ohta K. Akhirin regulates the proliferation and differentiation of neural stem cells/progenitor cells at neurogenic niches in mouse brain. Dev Growth Differ 2020; 62:97-107. [DOI: 10.1111/dgd.12646] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 12/05/2019] [Accepted: 12/10/2019] [Indexed: 12/31/2022]
Affiliation(s)
- Mohammad Badrul Anam
- Department of Developmental Neurobiology Faculty of Life Sciences Kumamoto University Kumamoto Japan
- HIGO Program Kumamoto University Kumamoto Japan
- Stem Cell‐Based Tissue Regeneration Research and Education Unit Kumamoto University Kumamoto Japan
| | - Shah Adil Ishtiyaq Ahmad
- Department of Developmental Neurobiology Faculty of Life Sciences Kumamoto University Kumamoto Japan
- Stem Cell‐Based Tissue Regeneration Research and Education Unit Kumamoto University Kumamoto Japan
- Department of Biotechnology and Genetic Engineering Mawlana Bhashani Science and Technology University Tangail Bangladesh
| | - Mikiko Kudo
- Department of Developmental Neurobiology Faculty of Life Sciences Kumamoto University Kumamoto Japan
- Stem Cell‐Based Tissue Regeneration Research and Education Unit Kumamoto University Kumamoto Japan
| | - Arif Istiaq
- Department of Developmental Neurobiology Faculty of Life Sciences Kumamoto University Kumamoto Japan
- HIGO Program Kumamoto University Kumamoto Japan
- Stem Cell‐Based Tissue Regeneration Research and Education Unit Kumamoto University Kumamoto Japan
| | - Athary Abdulhaleem M. Felemban
- Department of Developmental Neurobiology Faculty of Life Sciences Kumamoto University Kumamoto Japan
- Department of Biology Faculty of Applied Science Umm Al‐Qura University Makkah Saudi Arabia
| | - Naofumi Ito
- Department of Developmental Neurobiology Faculty of Life Sciences Kumamoto University Kumamoto Japan
- Stem Cell‐Based Tissue Regeneration Research and Education Unit Kumamoto University Kumamoto Japan
| | - Kunimasa Ohta
- Department of Developmental Neurobiology Faculty of Life Sciences Kumamoto University Kumamoto Japan
- HIGO Program Kumamoto University Kumamoto Japan
- Stem Cell‐Based Tissue Regeneration Research and Education Unit Kumamoto University Kumamoto Japan
- AMED Core Research for Evolutional Science and Technology (AMED‐CREST) Japan Agency for Medical Research and Development (AMED) Tokyo Japan
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3
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Lanke V, Moolamalla STR, Roy D, Vinod PK. Integrative Analysis of Hippocampus Gene Expression Profiles Identifies Network Alterations in Aging and Alzheimer's Disease. Front Aging Neurosci 2018; 10:153. [PMID: 29875655 PMCID: PMC5974201 DOI: 10.3389/fnagi.2018.00153] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 05/04/2018] [Indexed: 01/22/2023] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20-50 years), aging (70-99 years), and AD (70-99 years). The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein-protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein-protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors) and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1) in AD. Further, we found genes that encode proteins with neuroprotective function (14-3-3 proteins, PIN1, ATXN1, BDNF, VEGFA) to be part of the downregulated AD subnetwork. Our study highlights that simultaneously analyzing aging and AD will help to understand the pre-clinical and clinical phase of AD and aid in developing the treatment strategies.
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Affiliation(s)
- Vinay Lanke
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad, Hyderabad, India
| | - S T R Moolamalla
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad, Hyderabad, India
| | - Dipanjan Roy
- Cognitive Brain Dynamics Lab, National Brain Research Centre, Gurgaon, India
| | - P K Vinod
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad, Hyderabad, India
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4
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Whole-exome sequence analysis highlights the role of unmasked recessive mutations in copy number variants with incomplete penetrance. Eur J Hum Genet 2018; 26:912-918. [PMID: 29483668 DOI: 10.1038/s41431-018-0124-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Revised: 11/15/2017] [Accepted: 11/18/2017] [Indexed: 12/15/2022] Open
Abstract
Several hypotheses have been proposed to explain the phenotypic variability between parent and offspring carrying the same genomic imbalance, including unmasking of a recessive variant by a chromosomal deletion. Here, 19 patients with neurodevelopmental disorders harboring a rare deletion inherited from a healthy parent were investigated by whole-exome sequencing to search for SNV on the contralateral segment. This strategy allowed us to identify a candidate variant in two patients in the NUP214 and NCOR1 genes. This result demonstrates that the analysis of the genes included in non-deleted contralateral allele is a key point in the etiological investigation of patients harboring a deletion inherited from a parent. Finally, this strategy is also an interesting approach to identify new recessive intellectual disability genes.
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CD60b: Enriching Neural Stem/Progenitor Cells from Rat Development into Adulthood. Stem Cells Int 2017; 2017:5759490. [PMID: 29270199 PMCID: PMC5705879 DOI: 10.1155/2017/5759490] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 08/18/2017] [Accepted: 08/30/2017] [Indexed: 12/19/2022] Open
Abstract
CD60b antigens are highly expressed during development in the rat nervous system, while in the adult their expression is restricted to a few regions, including the subventricular zone (SVZ) around the lateral ventricles—a neurogenic niche in the adult brain. For this reason, we investigated whether the expression of C60b is associated with neural stem/progenitor cells in the SVZ, from development into adulthood. We performed in vitro and in vivo analyses of CD60b expression at different stages and identified the presence of these antigens in neural stem/progenitor cells. We also observed that CD60b could be used to purify and enrich a population of neurosphere-forming cells from the developing and adult brain. We showed that CD60b antigens (mainly corresponding to ganglioside 9-O-acetyl GD3, a well-known molecule expressed during central nervous system development and mainly associated with neuronal migration) are also present in less mature cells and could be used to identify and isolate neural stem/progenitor cells during development and in the adult brain. A better understanding of molecules associated with neurogenesis may contribute not only to improve the knowledge about the physiology of the mammalian central nervous system, but also to find new treatments for regenerating tissue after disease or brain injury.
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7
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Lenz M, Roumans NJT, Vink RG, van Baak MA, Mariman ECM, Arts ICW, de Kok TM, Ertaylan G. Estimating real cell size distribution from cross-section microscopy imaging. Bioinformatics 2017; 32:i396-i404. [PMID: 27587655 DOI: 10.1093/bioinformatics/btw431] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Microscopy imaging is an essential tool for medical diagnosis and molecular biology. It is particularly useful for extracting information about disease states, tissue heterogeneity and cell specific parameters such as cell type or cell size from biological specimens. However, the information obtained from the images is likely to be subjected to sampling and observational bias with respect to the underlying cell size/type distributions. RESULTS We present an algorithm, Estimate Tissue Cell Size/Type Distribution (EstiTiCS), for the adjustment of the underestimation of the number of small cells and the size of measured cells while accounting for the section thickness independent of the tissue type. We introduce the sources of bias under different tissue distributions and their effect on the measured values with simulation experiments. Furthermore, we demonstrate our method on histological sections of paraffin-embedded adipose tissue sample images from 57 people from a dietary intervention study. This data consists of measured cell size and its distribution over the dietary intervention period at four time points. Adjusting for the bias with EstiTiCS results in a closer fit to the true/expected adipocyte size distribution with earlier studies. Therefore, we conclude that our method is suitable as the final step in estimating the tissue wide cell type/size distribution from microscopy imaging pipeline. AVAILABILITY AND IMPLEMENTATION Source code and its documentation are available at https://github.com/michaelLenz/EstiTiCS The whole pipeline of our method is implemented in R and makes use of the 'nloptr' package. Adipose tissue data used for this study are available on request. CONTACT Michael.Lenz@Maastrichtuniversity.nl, Gokhan.Ertaylan@Maastrichtuniversity.nl.
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Affiliation(s)
- Michael Lenz
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Nadia J T Roumans
- Department of Human Biology NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Roel G Vink
- Department of Human Biology NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Marleen A van Baak
- Department of Human Biology NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Edwin C M Mariman
- Department of Human Biology NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Ilja C W Arts
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Theo M de Kok
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Gökhan Ertaylan
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
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8
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Zhang L, Tao W, Feng H, Chen Y. Transcriptional and Genomic Targets of Neural Stem Cells for Functional Recovery after Hemorrhagic Stroke. Stem Cells Int 2017; 2017:2412890. [PMID: 28133486 PMCID: PMC5241497 DOI: 10.1155/2017/2412890] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 12/21/2016] [Indexed: 01/27/2023] Open
Abstract
Hemorrhagic stroke is a life-threatening disease characterized by a sudden rupture of cerebral blood vessels, and it is widely believed that neural cell death occurs after exposure to blood metabolites or subsequently damaged cells. Neural stem cells (NSCs), which maintain neurogenesis and are found in subgranular zone and subventricular zone, are thought to be an endogenous neuroprotective mechanism for these brain injuries. However, due to the complexity of NSCs and their microenvironment, current strategies cannot satisfactorily enhance functional recovery after hemorrhagic stroke. It is well known that transcriptional and genomic pathways play important roles in ensuring the normal functions of NSCs, including proliferation, migration, differentiation, and neural reconnection. Recently, emerging evidence from the use of new technologies such as next-generation sequencing and transcriptome profiling has provided insight into our understanding of genomic function and regulation of NSCs. In the present article, we summarize and present the current data on the control of NSCs at both the transcriptional and genomic levels. Using bioinformatics methods, we sought to predict novel therapeutic targets of endogenous neurogenesis and exogenous NSC transplantation for functional recovery after hemorrhagic stroke, which could also advance our understanding of its pathophysiology.
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Affiliation(s)
- Le Zhang
- College of Computer and Information Science, Southwest University, Chongqing, China
| | - Wenjing Tao
- College of Computer and Information Science, Southwest University, Chongqing, China
| | - Hua Feng
- Department of Neurosurgery, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Yujie Chen
- Department of Neurosurgery, Southwest Hospital, Third Military Medical University, Chongqing, China
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9
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Bunk EC, Ertaylan G, Ortega F, Pavlou MA, Gonzalez Cano L, Stergiopoulos A, Safaiyan S, Völs S, van Cann M, Politis PK, Simons M, Berninger B, Del Sol A, Schwamborn JC. Prox1 Is Required for Oligodendrocyte Cell Identity in Adult Neural Stem Cells of the Subventricular Zone. Stem Cells 2016; 34:2115-29. [PMID: 27068685 DOI: 10.1002/stem.2374] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Revised: 02/26/2016] [Accepted: 03/10/2016] [Indexed: 01/19/2023]
Abstract
Adult neural stem cells with the ability to generate neurons and glia cells are active throughout life in both the dentate gyrus (DG) and the subventricular zone (SVZ). Differentiation of adult neural stem cells is induced by cell fate determinants like the transcription factor Prox1. Evidence has been provided for a function of Prox1 as an inducer of neuronal differentiation within the DG. We now show that within the SVZ Prox1 induces differentiation into oligodendrocytes. Moreover, we find that loss of Prox1 expression in vivo reduces cell migration into the corpus callosum, where the few Prox1 deficient SVZ-derived remaining cells fail to differentiate into oligodendrocytes. Thus, our work uncovers a novel function of Prox1 as a fate determinant for oligodendrocytes in the adult mammalian brain. These data indicate that the neurogenic and oligodendrogliogenic lineages in the two adult neurogenic niches exhibit a distinct requirement for Prox1, being important for neurogenesis in the DG but being indispensable for oligodendrogliogenesis in the SVZ. Stem Cells 2016;34:2115-2129.
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Affiliation(s)
- Eva C Bunk
- Institute of Cell Biology, ZMBE, University of Münster, Münster, Germany
| | - Gökhan Ertaylan
- Computational Biology, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.,Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Felipe Ortega
- Institute of Physiological Chemistry and the Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.,Department of Biochemistry and Molecular Biology IV, Faculty of Veterinary Medicine, Complutense University of Madrid, Madrid, Spain
| | - Maria A Pavlou
- Institute of Cell Biology, ZMBE, University of Münster, Münster, Germany.,Developmental and Cellular Biology, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Laura Gonzalez Cano
- Computational Biology, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | | | - Shima Safaiyan
- Max Planck Institute for Experimental Medicine, Göttingen, Germany
| | - Sandra Völs
- Institute of Cell Biology, ZMBE, University of Münster, Münster, Germany
| | - Marianne van Cann
- Institute of Cell Biology, ZMBE, University of Münster, Münster, Germany
| | - Panagiotis K Politis
- Center of Basic Research, Biomedical Research Foundation, Academy of Athens, Greece
| | - Mikael Simons
- Max Planck Institute for Experimental Medicine, Göttingen, Germany.,Department of Neurology, University of Göttingen, Göttingen, Germany
| | - Benedikt Berninger
- Institute of Physiological Chemistry and the Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Antonio Del Sol
- Computational Biology, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Jens C Schwamborn
- Institute of Cell Biology, ZMBE, University of Münster, Münster, Germany.,Developmental and Cellular Biology, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
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A differential network analysis approach for lineage specifier prediction in stem cell subpopulations. NPJ Syst Biol Appl 2015; 1:15012. [PMID: 28725462 PMCID: PMC5516870 DOI: 10.1038/npjsba.2015.12] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Revised: 08/20/2015] [Accepted: 09/04/2015] [Indexed: 01/21/2023] Open
Abstract
Background: Stem cell differentiation is a complex biological process. Cellular heterogeneity, such as the co-existence of different cell subpopulations within a population, partly hampers our understanding of this process. The modern single-cell gene expression technologies, such as single-cell RT-PCR and RNA-seq, have enabled us to elucidate such heterogeneous cell subpopulations. However, the identification of a transcriptional regulatory network (TRN) for each cell subpopulation within a population and genes determining specific cell fates (lineage specifiers) remains a challenge due to the slower development of appropriate computational and experimental workflows. Here, we propose a computational differential network analysis approach for predicting lineage specifiers in binary-fate differentiation events. Methods: The proposed method is based on a model that considers each stem cell subpopulation being in a stable state maintained by its specific TRN stability core, and cell differentiation involves changes in these stability cores between parental and daughter cell subpopulations. The method first reconstructs topologically different cell-subpopulation specific TRNs from single-cell gene expression data, literature knowledge and transcription factor (TF)–DNA binding-site prediction. Then, it systematically predicts lineage specifiers by identifying genes in the TRN stability cores in both parental and daughter cell subpopulations. Results: Application of this method to different stem cell differentiation systems was able to predict known and putative novel lineage specifiers. These examples include the differentiation of inner cell mass into either primitive endoderm or epiblast, different progenitor cells in the hematopoietic system, and the lung alveolar bipotential progenitor into either alveolar type 1 or alveolar type 2. Conclusions: The method is generally applicable to any binary-fate differentiation system, for which single-cell gene expression data are available. Therefore, it should aid in understanding stem cell lineage specification, and in the development of experimental strategies for regenerative medicine.
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11
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Lai YJ, Sun F, Chen GJ. Adult neurogenesis: Is it showtime for clinical translation? Genes Dis 2015; 2:291-292. [PMID: 30258871 PMCID: PMC6146142 DOI: 10.1016/j.gendis.2015.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2015] [Accepted: 08/17/2015] [Indexed: 10/26/2022] Open
Affiliation(s)
- Yu-Jie Lai
- Department of Neurology, The First Affiliated Hospital, Chongqing Medical University, and The Chongqing Key Laboratory of Neurology, Chongqing 400016, China.,Department of Physiology, Wayne State University School of Medicine, Detroit, Ml 48201, USA.,Department of Neurology, The First Affiliated Hospital, Chongqing Medical University, and The Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Fei Sun
- Department of Physiology, Wayne State University School of Medicine, Detroit, Ml 48201, USA.,Department of Neurology, The First Affiliated Hospital, Chongqing Medical University, and The Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Guo-Jun Chen
- Department of Neurology, The First Affiliated Hospital, Chongqing Medical University, and The Chongqing Key Laboratory of Neurology, Chongqing 400016, China
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12
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Okawa S, del Sol A. A computational strategy for predicting lineage specifiers in stem cell subpopulations. Stem Cell Res 2015; 15:427-34. [PMID: 26368290 DOI: 10.1016/j.scr.2015.08.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2015] [Revised: 07/17/2015] [Accepted: 08/16/2015] [Indexed: 10/23/2022] Open
Abstract
Stem cell differentiation is a complex biological event. Our understanding of this process is partly hampered by the co-existence of different cell subpopulations within a given population, which are characterized by different gene expression states driven by different underlying transcriptional regulatory networks (TRNs). Such cellular heterogeneity has been recently explored with the modern single-cell gene expression profiling technologies, such as single-cell RT-PCR and RNA-seq. However, the identification of cell subpopulation-specific TRNs and genes determining specific lineage commitment (i.e., lineage specifiers) remains a challenge due to the slower development of appropriate computational and experimental workflows. Here, we propose a computational method for predicting lineage specifiers for different cell subpopulations in binary-fate differentiation events. Our method first reconstructs subpopulation-specific TRNs, which is more realistic than reconstructing a single TRN representing multiple cell subpopulations. Then, it predicts lineage specifiers based on a model that assumes that each parental stem cell subpopulation is in a stable state maintained by its specific TRN stability core. In addition, this stable state is maintained in the parental cell subpopulation by the balanced gene expression pattern of pairs of opposing lineage specifiers for mutually exclusive different daughter cell subpopulations. To this end, we devised a statistical metric for identifying opposing lineage specifier pairs that show a significant ratio change upon differentiation. Application of this computational method to three different stem cell systems predicted known and putative novel lineage specifiers, which could be experimentally tested. Our method does not require pre-selection of putative candidate genes, and can be applied to any binary-fate differentiation system for which single-cell gene expression data are available. Furthermore, this method is compatible with both single-cell RT-PCR and single-cell RNA-seq data. Given the increasing importance of single-cell gene expression data in stem cell biology and regenerative medicine, approaches like ours would be useful for the identification of lineage specifiers and their associated TRN stability cores.
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Affiliation(s)
- Satoshi Okawa
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7, Avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg
| | - Antonio del Sol
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7, Avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg.
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13
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Koutmani Y, Karalis KP. Neural stem cells respond to stress hormones: distinguishing beneficial from detrimental stress. Front Physiol 2015; 6:77. [PMID: 25814957 PMCID: PMC4356227 DOI: 10.3389/fphys.2015.00077] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Accepted: 02/26/2015] [Indexed: 11/13/2022] Open
Abstract
Neural stem cells (NSCs), the progenitors of the nervous system, control distinct, position-specific functions and are critically involved in the maintenance of homeostasis in the brain. The responses of these cells to various stressful stimuli are shaped by genetic, epigenetic, and environmental factors via mechanisms that are age and developmental stage-dependent and still remain, to a great extent, elusive. Increasing evidence advocates for the beneficial impact of the stress response in various settings, complementing the extensive number of studies on the detrimental effects of stress, particularly in the developing brain. In this review, we discuss suggested mechanisms mediating both the beneficial and detrimental effects of stressors on NSC activity across the lifespan. We focus on the specific effects of secreted factors and we propose NSCs as a “sensor,” capable of distinguishing among the different stressors and adapting its functions accordingly. All the above suggest the intriguing hypothesis that NSCs are an important part of the adaptive response to stressors via direct and indirect, specific mechanisms.
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Affiliation(s)
- Yassemi Koutmani
- Center for Experimental Surgery, Clinical and Translational Research, Biomedical Research Foundation of the Academy of Athens Athens, Greece
| | - Katia P Karalis
- Center for Experimental Surgery, Clinical and Translational Research, Biomedical Research Foundation of the Academy of Athens Athens, Greece ; Endocrine Division, Children's Hospital, Harvard Medical School Boston, MA, USA
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