scholarly journals An Algorithm for Cellular Reprogramming

2017 ◽  
Author(s):  
Scott Ronquist ◽  
Geoff Patterson ◽  
Markus Brown ◽  
Stephen Lindsly ◽  
Haiming Chen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Cell Biology ◽  
Human Fibroblasts ◽  
Cell Types ◽  
Approximate Model ◽  
Cellular Reprogramming ◽  
Biological Processes ◽  
Moderate Complexity

AbstractThe day we understand the time evolution of subcellular elements at a level of detail comparable to physical systems governed by Newton’s laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology, providing data-guided frameworks that allow us to develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. In this paper, we describe an approach to optimizing the use of transcription factors (TFs) in the context of cellular reprogramming. We construct an approximate model for the natural evolution of a cell cycle synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points along the cell cycle. In order to arrive at a model of moderate complexity, we cluster gene expression based on the division of the genome into topologically associating domains (TADs) and then model the dynamics of the TAD expression levels. Based on this dynamical model and known bioinformatics, such as transcription factor binding sites (TFBS) and functions, we develop a methodology for identifying the top transcription factor candidates for a specific cellular reprogramming task. The approach used is based on a device commonly used in optimal control. Our data-guided methodology identifies a number of transcription factors previously validated for reprogramming and/or natural differentiation. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes.Significance StatementReprogramming the human genome toward any desirable state is within reach; application of select transcription factors drives cell types toward different lineages in many settings. We introduce the concept of data-guided control in building a universal algorithm for directly reprogramming any human cell type into any other type. Our algorithm is based on time series genome transcription and architecture data and known regulatory activities of transcription factors, with natural dimension reduction using genome architectural features. Our algorithm predicts known reprogramming factors, top candidates for new settings, and ideal timing for application of transcription factors. This framework can be used to develop strategies for tissue regeneration, cancer cell reprogramming, and control of dynamical systems beyond cell biology.

scholarly journals Algorithm for cellular reprogramming

2017 ◽  
Vol 114 (45) ◽  
pp. 11832-11837 ◽  
Author(s):  
Scott Ronquist ◽  
Geoff Patterson ◽  
Lindsey A. Muir ◽  
Stephen Lindsly ◽  
Haiming Chen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Biology ◽  
Human Fibroblasts ◽  
Approximate Model ◽  
Cellular Reprogramming ◽  
Biological Processes ◽  
A Cell ◽  
Moderate Complexity ◽  
Immense Potential ◽  
Cluster Gene

The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton’s laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle–synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points during the cell cycle. To arrive at a model of moderate complexity, we cluster gene expression based on division of the genome into topologically associating domains (TADs) and then model the dynamics of TAD expression levels. Based on this dynamical model and additional data, such as known TF binding sites and activity, we develop a methodology for identifying the top TF candidates for a specific cellular reprogramming task. Our data-guided methodology identifies a number of TFs previously validated for reprogramming and/or natural differentiation and predicts some potentially useful combinations of TFs. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes.

scholarly journals Direct reprogramming of human fibroblasts into insulin-producing cells by transcription factors

2021 ◽  
Author(s):  
Rosa Gasa ◽  
Marta Fontcuberta-PiSunyer ◽  
Ainhoa García-Alamán ◽  
Élia Prades ◽  
Noèlia Téllez ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Somatic Cell ◽  
Human Fibroblasts ◽  
Stem Cell Differentiation ◽  
Cell Types ◽  
Skin Fibroblasts ◽  
Direct Reprogramming ◽  
Β Cell ◽  
Insulin Producing Cells

Direct lineage reprogramming of one somatic cell into another bypassing an intermediate pluripotent state has emerged as an alternative to embryonic or induced pluripotent stem cell differentiation to generate clinically relevant cell types. One cell type of clinical interest is the pancreatic β cell that secretes insulin and whose loss and/or dysfunction leads to diabetes. Generation of functional β-like cells from developmentally related somatic cell types (pancreas, liver, gut) has been achieved via enforced expression of defined sets of transcription factors. However, clinical applicability of these findings is challenging because the starting cell types are not easily obtainable. Skin fibroblasts are accessible and easily manipulated cells that could be a better option, but available studies indicate that their competence to give rise to β cells through similar direct reprogramming approaches is limited. Here, using human skin fibroblasts and a protocol that ensures high and consistent expression of adenovirus-encoded reprogramming factors, we show that the transcription factor cocktail consisting of Pdx1, Ngn3, MafA, Pax4 and Nkx2-2 activates key β cell genes and down-regulates the fibroblast transcriptional program. The converted cells produce insulin and exhibit intracellular calcium responses to glucose and/or membrane depolarization. Furthermore, they secrete insulin in response to glucose in vitro and after transplantation in vivo. These findings demonstrate that transcription factor-mediated direct reprogramming of human fibroblasts is a feasible strategy to generate insulin-producing cells.

scholarly journals Molecular regulation of Snai2 in development and disease

2019 ◽  
Vol 132 (23) ◽  
Author(s):  
Wenhui Zhou ◽  
Kayla M. Gross ◽  
Charlotte Kuperwasser
Keyword(s):  
Transcription Factor ◽  
Cell Biology ◽  
Molecular Mechanisms ◽  
Epithelial To Mesenchymal Transition ◽  
Zinc Finger Protein ◽  
Main Role ◽  
Biological Processes ◽  
Developmental Defects ◽  
Mesenchymal Transition ◽  
Damage Repair

ABSTRACT The transcription factor Snai2, encoded by the SNAI2 gene, is an evolutionarily conserved C2H2 zinc finger protein that orchestrates biological processes critical to tissue development and tumorigenesis. Initially characterized as a prototypical epithelial-to-mesenchymal transition (EMT) transcription factor, Snai2 has been shown more recently to participate in a wider variety of biological processes, including tumor metastasis, stem and/or progenitor cell biology, cellular differentiation, vascular remodeling and DNA damage repair. The main role of Snai2 in controlling such processes involves facilitating the epigenetic regulation of transcriptional programs, and, as such, its dysregulation manifests in developmental defects, disruption of tissue homeostasis, and other disease conditions. Here, we discuss our current understanding of the molecular mechanisms regulating Snai2 expression, abundance and activity. In addition, we outline how these mechanisms contribute to disease phenotypes or how they may impact rational therapeutic targeting of Snai2 dysregulation in human disease.

scholarly journals HOT or not: examining the basis of high-occupancy target regions

2017 ◽  
Author(s):  
Katarzyna Wreczycka ◽  
Vedran Franke ◽  
Bora Uyar ◽  
Ricardo Wurmus ◽  
Altuna Akalin
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Binding Sites ◽  
Cell Types ◽  
Data Sets ◽  
Gene Promoters ◽  
Quadruplex Dna ◽  
Golden Standard ◽  
Multiple Cell ◽  
Multiple Species

AbstractHigh-occupancy target (HOT) regions are the segments of the genome with unusually high number of transcription factor binding sites. These regions are observed in multiple species and thought to have biological importance due to high transcription factor occupancy. Furthermore, they coincide with house-keeping gene promoters and the associated genes are stably expressed across multiple cell types. Despite these features, HOT regions are solemnly defined using ChIP-seq experiments and shown to lack canonical motifs for transcription factors that are thought to be bound there. Although, ChIP-seq experiments are the golden standard for finding genome-wide binding sites of a protein, they are not noise free. Here, we show that HOT regions are likely to be ChIP-seq artifacts and they are similar to previously proposed “hyper-ChIPable” regions. Using ChIP-seq data sets for knocked-out transcription factors, we demonstrate presence of false positive signals on HOT regions. We observe sequence characteristics and genomic features that are discriminatory of HOT regions, such as GC/CpG-rich k-mers and enrichment of RNA-DNA hybrids (R-loops) and DNA tertiary structures (G-quadruplex DNA). The artificial ChIP-seq enrichment on HOT regions could be associated to these discriminatory features. Furthermore, we propose strategies to deal with such artifacts for the future ChIP-seq studies.

scholarly journals Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

2018 ◽  
Author(s):  
Mehran Karimzadeh ◽  
Michael M. Hoffman
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Binding Sites ◽  
Cell Types ◽  
Transcription Factor Binding ◽  
Regulatory Function ◽  
Factor Binding ◽  
Link Type ◽  
Genomic Regions ◽  
Factor Sequence

AbstractMotivationIdentifying transcription factor binding sites is the first step in pinpointing non-coding mutations that disrupt the regulatory function of transcription factors and promote disease. ChIP-seq is the most common method for identifying binding sites, but performing it on patient samples is hampered by the amount of available biological material and the cost of the experiment. Existing methods for computational prediction of regulatory elements primarily predict binding in genomic regions with sequence similarity to known transcription factor sequence preferences. This has limited efficacy since most binding sites do not resemble known transcription factor sequence motifs, and many transcription factors are not even sequence-specific.ResultsWe developed Virtual ChIP-seq, which predicts binding of individual transcription factors in new cell types using an artificial neural network that integrates ChIP-seq results from other cell types and chromatin accessibility data in the new cell type. Virtual ChIP-seq also uses learned associations between gene expression and transcription factor binding at specific genomic regions. This approach outperforms methods that predict TF binding solely based on sequence preference, pre-dicting binding for 36 transcription factors (Matthews correlation coefficient > 0.3).AvailabilityThe datasets we used for training and validation are available at https://virchip.hoffmanlab.org. We have deposited in Zenodo the current version of our software (http://doi.org/10.5281/zenodo.1066928), datasets (http://doi.org/10.5281/zenodo.823297), predictions for 36 transcription factors on Roadmap Epigenomics cell types (http://doi.org/10.5281/zenodo.1455759), and predictions in Cistrome as well as ENCODE-DREAM in vivo TF Binding Site Prediction Challenge (http://doi.org/10.5281/zenodo.1209308).

scholarly journals Balancing dynamic tradeoffs drives cellular reprogramming

2018 ◽  
Author(s):  
Kimberley N. Babos ◽  
Kate E. Galloway ◽  
Kassandra Kisler ◽  
Madison Zitting ◽  
Yichen Li ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Cell Division ◽  
Motor Neuron ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Cellular Reprogramming ◽  
Cellular Event ◽  
Chemical Factors ◽  
Number Of Cells ◽  
Transcription And Replication

AbstractAlthough cellular reprogramming continues to generate new cell types, reprogramming remains a rare cellular event. The molecular mechanisms that limit reprogramming, particularly to somatic lineages, remain unclear. By examining fibroblast-to-motor neuron conversion, we identify a previously unappreciated dynamic between transcription and replication that determines reprogramming competency. Transcription factor overexpression forces most cells into states that are refractory to reprogramming and are characterized by either hypertranscription with little cell division, or hyperproliferation with low transcription. We identify genetic and chemical factors that dramatically increase the number of cells capable of both hypertranscription and hyperproliferation. Hypertranscribing, hyperproliferating cells reprogram at 100-fold higher, near-deterministic rates. We demonstrate that elevated topoisomerase expression endows cells with privileged reprogramming capacity, suggesting that biophysical constraints limit cellular reprogramming to rare events.

Abstract P493: Histone Reader PHF7 Cooperates With The SWI/SNF Complex At Cardiac Super Enhancers To Promote Direct Reprogramming

2021 ◽  
Vol 129 (Suppl_1) ◽  
Author(s):  
Glynnis A Garry ◽  
Svetlana Bezprozvannaya ◽  
Huanyu Zhou ◽  
Hisayuki Hashimoto ◽  
Kenian Chen ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Cardiac Fibroblasts ◽  
Human Fibroblasts ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Direct Reprogramming ◽  
Ischemic Disease ◽  
Treat Heart Failure ◽  
Cardiac Transcription Factors ◽  
Adult Fibroblasts

Ischemic heart disease is the leading cause of death worldwide. Direct reprogramming of resident cardiac fibroblasts (CFs) to induced cardiomyocytes (iCLMs) has emerged as a potential therapeutic approach to treat heart failure and ischemic disease. Cardiac reprogramming was first achieved through forced expression of the transcription factors Gata4, Mef2c, and Tbx5 (GMT); our laboratory found that Hand2 (GHMT) and Akt1 (AGHMT) markedly enhanced reprogramming efficiency in embryonic and postnatal cell types. However, adult mouse and human fibroblasts are resistant to reprogramming due to staunch epigenetic barriers. We undertook a screen of mammalian gene regulatory factors to discover novel regulators of cardiac reprogramming in adult fibroblasts and identified the epigenetic reader PHF7 as the most potent activating factor. We validated the findings of this screen and found that PHF7 augmented reprogramming of adult fibroblasts ten-fold. Mechanistically, PHF7 localized to cardiac super enhancers in fibroblasts by reading H3K4me2 marks, and through cooperation with the SWI/SNF complex, increased chromatin accessibility and transcription factor binding at these multivalent enhancers. Further, PHF7 recruited cardiac transcription factors to activate a positive transcriptional autoregulatory circuit in reprogramming. Importantly, PHF7 achieved efficient reprogramming through these mechanisms in the absence of Gata4. Collectively, these studies highlight the underexplored necessity of cardiac epigenetic readers, such as PHF7, in harnessing chromatin remodeling and transcriptional complexes to overcome critical barriers to direct cardiac reprogramming.

scholarly journals Is the Secret of VDAC Isoforms in Their Gene Regulation? Characterization of Human VDAC Genes Expression Profile, Promoter Activity, and Transcriptional Regulators

2020 ◽  
Vol 21 (19) ◽  
pp. 7388
Author(s):  
Federica Zinghirino ◽  
Xena Giada Pappalardo ◽  
Angela Messina ◽  
Francesca Guarino ◽  
Vito De Pinto
Keyword(s):  
Cell Cycle ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Promoter Activity ◽  
Expression Profiles ◽  
Transcriptional Regulators ◽  
General Role ◽  
Nuclear Respiratory Factor ◽  
Nuclear Respiratory Factor 1

VDACs (voltage-dependent anion-selective channels) are pore-forming proteins of the outer mitochondrial membrane, whose permeability is primarily due to VDACs’ presence. In higher eukaryotes, three isoforms are raised during the evolution: they have the same exon–intron organization, and the proteins show the same channel-forming activity. We provide a comprehensive analysis of the three human VDAC genes (VDAC1–3), their expression profiles, promoter activity, and potential transcriptional regulators. VDAC isoforms are broadly but also specifically expressed in various human tissues at different levels, with a predominance of VDAC1 and VDAC2 over VDAC3. However, an RNA-seq cap analysis gene expression (CAGE) approach revealed a higher level of transcription activation of VDAC3 gene. We experimentally confirmed this information by reporter assay of VDACs promoter activity. Transcription factor binding sites (TFBSs) distribution in the promoters were investigated. The main regulators common to the three VDAC genes were identified as E2F-myc activator/cell cycle (E2FF), Nuclear respiratory factor 1 (NRF1), Krueppel-like transcription factors (KLFS), E-box binding factors (EBOX) transcription factor family members. All of them are involved in cell cycle and growth, proliferation, differentiation, apoptosis, and metabolism. More transcription factors specific for each VDAC gene isoform were identified, supporting the results in the literature, indicating a general role of VDAC1, as an actor of apoptosis for VDAC2, and the involvement in sex determination and development of VDAC3. For the first time, we propose a comparative analysis of human VDAC promoters to investigate their specific biological functions. Bioinformatics and experimental results confirm the essential role of the VDAC protein family in mitochondrial functionality. Moreover, insights about a specialized function and different regulation mechanisms arise for the three isoform gene.

scholarly journals Hypoxia-Inducible Factor 1α Is Essential for Cell Cycle Arrest during Hypoxia

2003 ◽  
Vol 23 (1) ◽  
pp. 359-369 ◽  
Author(s):  
Nobuhito Goda ◽  
Heather E. Ryan ◽  
Bahram Khadivi ◽  
Wayne McNulty ◽  
Robert C. Rickert ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Transcription Factor ◽  
Cell Cycle Arrest ◽  
Cellular Response ◽  
Hypoxia Inducible Factor ◽  
Growth Arrest ◽  
Cell Types ◽  
Low Oxygen ◽  
Double Knockout ◽  
Cycle Arrest

ABSTRACT A classical cellular response to hypoxia is a cessation of growth. Hypoxia-induced growth arrest differs in different cell types but is likely an essential aspect of the response to wounding and injury. An important component of the hypoxic response is the activation of the hypoxia-inducible factor 1 (HIF-1) transcription factor. Although this transcription factor is essential for adaptation to low oxygen levels, the mechanisms through which it influences cell cycle arrest, including the degree to which it cooperates with the tumor suppressor protein p53, remain poorly understood. To determine broadly relevant aspects of HIF-1 function in primary cell growth arrest, we examined two different primary differentiated cell types which contained a deletable allele of the oxygen-sensitive component of HIF-1, the HIF-1α gene product. The two cell types were murine embryonic fibroblasts and splenic B lymphocytes; to determine how the function of HIF-1α influenced p53, we also created double-knockout (HIF-1α null, p53 null) strains and cells. In both cell types, loss of HIF-1α abolished hypoxia-induced growth arrest and did this in a p53-independent fashion. Surprisingly, in all cases, cells lacking both p53 and HIF-1α genes have completely lost the ability to alter the cell cycle in response to hypoxia. In addition, we have found that the loss of HIF-1α causes an increased progression into S phase during hypoxia, rather than a growth arrest. We show that hypoxia causes a HIF-1α-dependent increase in the expression of the cyclin-dependent kinase inhibitors p21 and p27; we also find that hypophosphorylation of retinoblastoma protein in hypoxia is HIF-1α dependent. These data demonstrate that the transcription factor HIF-1 is a major regulator of cell cycle arrest in primary cells during hypoxia.

scholarly journals Role of Forkhead Transcription Factors in Diabetes-Induced Oxidative Stress

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Bhaskar Ponugoti ◽  
Guangyu Dong ◽  
Dana T. Graves
Keyword(s):  
Oxidative Stress ◽  
Transcription Factors ◽  
Cellular Response ◽  
Cell Damage ◽  
Cell Types ◽  
Biological Processes ◽  
Oxygen Species ◽  
Forkhead Transcription Factors ◽  
Foxo Transcription Factors

Diabetes is a chronic metabolic disorder, characterized by hyperglycemia resulting from insulin deficiency and/or insulin resistance. Recent evidence suggests that high levels of reactive oxygen species (ROS) and subsequent oxidative stress are key contributors in the development of diabetic complications. The FOXO family of forkhead transcription factors including FOXO1, FOXO3, FOXO4, and FOXO6 play important roles in the regulation of many cellular and biological processes and are critical regulators of cellular oxidative stress response pathways. FOXO1 transcription factors can affect a number of different tissues including liver, retina, bone, and cell types ranging from hepatocytes to microvascular endothelial cells and pericytes to osteoblasts. They are induced by oxidative stress and contribute to ROS-induced cell damage and apoptosis. In this paper, we discuss the role of FOXO transcription factors in mediating oxidative stress-induced cellular response.

Sign in / Sign up

Export Citation Format

Share Document