HDAC Inhibitor Titration of Transcription and Axolotl Tail Regeneration

New patterns of gene expression are enacted and regulated during tissue regeneration. Histone deacetylases (HDACs) regulate gene expression by removing acetylated lysine residues from histones and proteins that function directly or indirectly in transcriptional regulation. Previously we showed that romidepsin, an FDA-approved HDAC inhibitor, potently blocks axolotl embryo tail regeneration by altering initial transcriptional responses to injury. Here, we report on the concentration-dependent effect of romidepsin on transcription and regeneration outcome, introducing an experimental and conceptual framework for investigating small molecule mechanisms of action. A range of romidepsin concentrations (0–10 μM) were administered from 0 to 6 or 0 to 12 h post amputation (HPA) and distal tail tip tissue was collected for gene expression analysis. Above a threshold concentration, romidepsin potently inhibited regeneration. Sigmoidal and biphasic transcription response curve modeling identified genes with inflection points aligning to the threshold concentration defining regenerative failure verses success. Regeneration inhibitory concentrations of romidepsin increased and decreased the expression of key genes. Genes that associate with oxidative stress, negative regulation of cell signaling, negative regulation of cell cycle progression, and cellular differentiation were increased, while genes that are typically up-regulated during appendage regeneration were decreased, including genes expressed by fibroblast-like progenitor cells. Using single-nuclei RNA-Seq at 6 HPA, we found that key genes were altered by romidepin in the same direction across multiple cell types. Our results implicate HDAC activity as a transcriptional mechanism that operates across cell types to regulate the alternative expression of genes that associate with regenerative success versus failure outcomes.

Download Full-text

Characterizing and inferring quantitative cell cycle phase in single-cell RNA-seq data analysis

10.1101/526848 ◽

2019 ◽

Cited By ~ 3

Author(s):

Chiaowen Joyce Hsiao ◽

PoYuan Tung ◽

John D. Blischak ◽

Jonathan E. Burnett ◽

Kenneth A. Barr ◽

...

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Single Cell ◽

Cell Cycle Progression ◽

Cell Types ◽

Cell Cycle Phase ◽

Cellular Heterogeneity ◽

Cycle Phase ◽

Cycle Progression ◽

Cellular Environment

AbstractCellular heterogeneity in gene expression is driven by cellular processes such as cell cycle and cell-type identity, and cellular environment such as spatial location. The cell cycle, in particular, is thought to be a key driver of cell-to-cell heterogeneity in gene expression, even in otherwise homogeneous cell populations. Recent advances in single-cell RNA-sequencing (scRNA-seq) facilitate detailed characterization of gene expression heterogeneity, and can thus shed new light on the processes driving heterogeneity. Here, we combined fluorescence imaging with scRNA-seq to measure cell cycle phase and gene expression levels in human induced pluripotent stem cells (iPSCs). Using these data, we developed a novel approach to characterize cell cycle progression. While standard methods assign cells to discrete cell cycle stages, our method goes beyond this, and quantifies cell cycle progression on a continuum. We found that, on average, scRNA-seq data from only five genes predicted a cell’s position on the cell cycle continuum to within 14% of the entire cycle, and that using more genes did not improve this accuracy. Our data and predictor of cell cycle phase can directly help future studies to account for cell-cycle-related heterogeneity in iPSCs. Our results and methods also provide a foundation for future work to characterize the effects of the cell cycle on expression heterogeneity in other cell types.

Download Full-text

The lncRNA EPB41L4A-AS1 regulates gene expression in the nucleus and exerts cell type-dependent effects on cell cycle progression

10.1101/2021.02.10.430566 ◽

2021 ◽

Author(s):

Helle Samdal ◽

Siv Anita Hegre ◽

Konika Chawla ◽

Nina-Beate Liabakk ◽

Per Arne Aas ◽

...

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Cell Cycle Progression ◽

Phase Distribution ◽

Cell Types ◽

Metabolic Reprogramming ◽

Cycle Phase ◽

Cell Type ◽

Chip Sequencing ◽

Cell Cycle Phase Distribution

AbstractThe long non-coding RNA (lncRNA) EPB41L4A-AS1 is aberrantly expressed in various cancers and has been reported to be involved in metabolic reprogramming and as a repressor of the Warburg effect. Although the biological relevance of EPB41L4A-AS1 is evident, its functional role seems to vary depending on cell type and state of disease. By combining RNA sequencing and ChIP sequencing of cell cycle synchronized HaCaT cells we previously identified EPB41L4A-AS1 to be one of 59 lncRNAs with potential cell cycle functions. Here, we demonstrate that EPB41L4A-AS1 exists as bright foci and regulates gene expression in the nucleus in both cis and trans. Specifically, we find that EPB41L4A-AS1 positively regulates its sense overlapping gene EPB41L4A and influences expression of hundreds of other genes, including genes involved in cell proliferation. Finally, we show that EPB41L4A-AS1 affects cell cycle phase distribution, though these effects vary between cell types.

Download Full-text

PyBoost: A parallelized Python implementation of 2D boosting with hierarchies

10.1101/170803 ◽

2017 ◽

Author(s):

Peyton G. Greenside ◽

Nadine Hussami ◽

Jessica Chang ◽

Anshul Kundaje

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Stem Cell Differentiation ◽

Cell Types ◽

Chromatin Accessibility ◽

Sequence Motifs ◽

Specific Sequence ◽

Tail Regeneration ◽

Perturbation Data ◽

Time Courses

AbstractMotivation:Gene expression is controlled by networks of transcription factors that bind specific sequence motifs in regulatory DNA elements such as promoters and enhancers. GeneClass is a boosting-based algorithm that learns gene regulatory networks from complementary paired feature sets such as transcription factor expression levels and binding motifs across conditions. This algorithm can be used to predict functional genomics measures of cell state, such as gene expression and chromatin accessibility, in different cellular conditions. We present a parallelized, Python-based implementation of GeneClass, called PyBoost, along with a novel hierarchical implementation of the algorithm, called HiBoost. HiBoost allows regulatory logic to be constrained to a hierarchical group of conditions or cell types. The software can be used to dissect differentiation cascades, time courses or other perturbation data that naturally form a hierarchy or trajectory. We demonstrate the application of PyBoost and HiBoost to learn regulators of tadpole tail regeneration and hematopoeitic stem cell differentiation and validate learned regulators through an inducible CRISPR system.Availability:The implementation is publicly available here:https://github.com/kundajelab/boosting2D/.

Download Full-text

The Antiviral Effects of Sodium Phenylbutyrate Against BoHV-1 Infection In Vitro

Letters in Drug Design & Discovery ◽

10.2174/1570180816666190222155958 ◽

2019 ◽

Vol 16 (12) ◽

pp. 1370-1377

Author(s):

Xinye Chen ◽

Guoqiang Zhu ◽

Liqian Zhu

Keyword(s):

Gene Expression ◽

Virus Infection ◽

Histone Acetylation ◽

Hdac Inhibitor ◽

Histone Deacetylases ◽

Viral Gene ◽

Antiviral Effects ◽

P38mapk Signaling ◽

Sodium Phenylbutyrate

Introduction: The alteration of histone acetylation is a known mechanism to regulate gene expression, and thereby affecting various cellular processes. Histone deacetylases (HDACs) are known to regulate histone acetylation by removal of the acetyl group from lysines. HDAC inhibitor such as Sodium Phenylbutyrate (PB) and Valproic Acid (VPA) have been reported to affect multiple virus infection while whether they affect BoHV-1 infection is unknown. Objective: The aim of the study is to investigate whether PB and VPA effects BoHV-1 infection and the virus induced inflammation related signaling including Erk1/2 and p38MAPK signaling. Methods: To assess the antiviral effects of PB and VPA on BoHV-1 infection, MDBK cells were treated with these inhibitors at different concentrations. Then time addition was performed to pinpoint which stages of virus infection was affected by the chemicals. In order to assess whether PB affect viral gene expression, we detected the viral IE genes such as bICP0, bICP4 and bICP22 using real-time PCR assay. The effects of PB had on the activation of inflammation related signaling including Erk1/2 and p38MAPK in response to the virus infection were also detected. Results: Here, for the first time we reveals that PB but not VPA affects BoHV-1 infection at late stages of infection. It affected the expression of IE genes such as bICP0, bICP4 and bICP22. Interestingly, PB enhanced the activation of both Erk1/2 and p38MAPK signaling stimulated by BoHV-1 infection. Conclusion: HDAC inhibitor PB significantly inhibited BoHV-1 infection partially through the interruption of certain viral IE gene expression. Though PB has been reported to have antiinflammatory effects, we found that it enhanced the activation of inflammation pertinent signaling of both Erk1/2 and p38MAPK stimulated by BoHV-1 infection.

Download Full-text

Independent regulation by sodium butyrate of gonadotropin alpha gene expression and cell cycle progression in HeLa cells

Molecular and Cellular Biology ◽

10.1128/mcb.4.5.829-839.1984 ◽

1984 ◽

Vol 4 (5) ◽

pp. 829-839

Author(s):

R B Darnell

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Sodium Butyrate ◽

Hela Cells ◽

Cell Cycle Progression ◽

Direct Action ◽

Cell Types ◽

Neoplastic Cell ◽

Alpha Subunit ◽

Alpha Gene

Sodium butyrate alters the growth and gene expression of a variety of differentiating and neoplastic cell types. For example, addition of 5 mM butyrate to HeLa cells is reported to both induce gonadotropin alpha subunit biosynthesis and block cell cycling in G1. We have studied these two actions of butyrate on HeLa cells and found that they are regulated in distinct ways. The induction of alpha subunit synthesis was due to an increase in the rate of transcription of the alpha gene. Using synchronized populations of HeLa cells, we determined that butyrate stimulates alpha transcription throughout the cell cycle. In contrast, treated cells arrest in G1 only if exposed to butyrate for a discrete period during the previous S phase. We conclude that butyrate inhibits DNA synthesis through a cell cycle-specific action that is independent from its direct action to stimulate transcription of the gonadotropin alpha gene.

Download Full-text

The physiological roles of histone deacetylase (HDAC) 1 and 2: complex co-stars with multiple leading parts

Biochemical Society Transactions ◽

10.1042/bst20130010 ◽

2013 ◽

Vol 41 (3) ◽

pp. 741-749 ◽

Cited By ~ 164

Author(s):

Richard D.W. Kelly ◽

Shaun M. Cowley

Keyword(s):

Small Molecule ◽

Transcriptional Activation ◽

Transcriptional Repression ◽

Histone Deacetylases ◽

Drug Targets ◽

Cell Cycle Progression ◽

Cell Types ◽

Histone Deacetylation ◽

Recognition Motifs ◽

Context Specific

HDACs (histone deacetylases) 1 and 2 are ubiquitous long-lived proteins, which are often found together in three major multiprotein co-repressor complexes: Sin3, NuRD (nucleosome remodelling and deacetylation) and CoREST (co-repressor for element-1-silencing transcription factor). Although there is a burgeoning number of non-histone proteins within the acetylome, these complexes contain multiple DNA/chromatin-recognition motifs, which, in combination with transcription factors, target HDAC1/2 to chromatin. Their physiological roles should therefore be viewed within the framework of chromatin manipulation. Classically, HDACs were thought to be recruited predominantly by transcriptional repressors to facilitate local histone deacetylation and transcriptional repression. More recently, genome-wide assays have mapped HDAC1/2 and their associated proteins to transcriptionally active loci and have provided alternative context-specific functions, whereby their repressive functions are subtly exerted to balance transcriptional activation and repression. With a few significant exceptions (early embryogenesis, brain development), HDAC1 and HDAC2 are functionally redundant. In most mouse knockout studies, deletion of both enzymes is required in order to produce a substantial phenotype. HDAC1/2 activity has been implicated in the development of numerous tissue and cell types, including heart, skin, brain, B-cells and T-cells. A common feature in all HDAC1/2-knockout, -knockdown and small-molecule inhibitor studies is a reduction in cell proliferation. A generic role in cell cycle progression could be exploited in cancer cells, by blocking HDAC1/2 activity with small-molecule inhibitors, making them potentially useful drug targets.

Download Full-text

ImmuneRegulation: A web-based tool for identifying human immune regulatory elements

10.1101/468124 ◽

2018 ◽

Author(s):

Selim Kalayci ◽

Myvizhi Esai Selvan ◽

Irene Ramos ◽

Chris Cotsapas ◽

Ruth R. Montgomery ◽

...

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Cell Types ◽

Regulatory Elements ◽

Future Application ◽

Transcriptional Responses ◽

Web Based ◽

Phenotypic Differences ◽

Transcriptome Regulation

ABSTRACTHumans can vary considerably in their healthy immune phenotypes and in their immune responses to various stimuli. We have developed an interactive web-based tool, ImmuneRegulation, to enable discovery of human regulatory elements that drive some of the phenotypic differences observed in gene expression profiles. ImmuneRegulation currently provides the largest centrally integrated resource available in the literature on transcriptome regulation in whole blood and blood cell types, including genotype data from 23,040 individuals, with associated gene expression data from 30,562 experiments, that provide genetic variant-gene expression associations on ∼200 million eQTLs. In addition, it includes 14 million transcription factor (TF) binding region hits extracted from 1945 TF ChIP-seq peaks and the latest GWAS catalog of 67,230 published SNP-trait associations. Users can interactively explore ImmuneRegulation to visualize and discover associations between their gene(s) of interest and their regulators (genetic variants or transcription factors) across multiple cohorts and studies. These regulators can explain cohort or cell type dependent gene expression variations and may be critical in selecting the ideal cohorts or cell types for follow-up studies. Overall, ImmuneRegulation aims to contribute to our understanding of the effects of eQTLs and TFs on heterogeneous transcriptional responses reported in studies on the blood; in the development of molecular signatures of immune response; and facilitate their future application in patient management. ImmuneRegulation is freely available at http://icahn.mssm.edu/immuneregulation.

Download Full-text

Nuclei are mobile processors enabling specialization in a gigantic single-celled syncytium

10.1101/2021.04.29.441915 ◽

2021 ◽

Author(s):

Tobias Gerber ◽

Cristina Loureiro ◽

Nico Schramma ◽

Siyu Chen ◽

Akanksha Jain ◽

...

Keyword(s):

Gene Expression ◽

Environmental Conditions ◽

Cell Types ◽

Slime Mold ◽

Transcriptional Responses ◽

Slime Molds ◽

Gene Expression Heterogeneity ◽

Single Nucleus ◽

Multicellular Organisms ◽

Cellular Compartmentalization

In multicellular organisms, the specification, coordination, and compartmentalization of cell types enable the formation of complex body plans. However, some eukaryotic protists such as slime molds generate diverse and complex structures while remaining in a multinucleated syncytial state. It is unknown if different regions of these giant syncytial cells have distinct transcriptional responses to environmental encounters, and if nuclei within the cell diversify into heterogeneous states. Here we performed spatial transcriptome analysis of the slime mold Physarum polycephalum in the plasmodium state under different environmental conditions, and used single-nucleus RNA-sequencing to dissect gene expression heterogeneity among nuclei. Our data identifies transcriptome regionality in the organism that associates with proliferation, syncytial substructures, and localized environmental conditions. Further, we find that nuclei are heterogenous in their transcriptional profile, and may process local signals within the plasmodium to coordinate cell growth, metabolism, and reproduction. To understand how nuclei variation within the syncytium compares to heterogeneity in single-nucleated cells, we analyzed states in single Physarum amoebal cells. We observed amoebal cell states at different stages of mitosis and meiosis, and identified cytokinetic features that are specific to nuclei divisions within the syncytium. Notably, we do not find evidence for predefined transcriptomic states in the amoebae that are observed in the syncytium. Our data shows that a single-celled slime mold can control its gene expression in a region-specific manner while lacking cellular compartmentalization, and suggests that nuclei are mobile processors facilitating local specialized functions. More broadly, slime molds offer the extraordinary opportunity to explore how organisms can evolve regulatory mechanisms to divide labor, specialize, balance competition with cooperation, and perform other foundational principles that govern the logic of life.

Download Full-text

42 EFFECTS OF TRICHOSTATIN A TREATMENT ON GENE EXPRESSION OF CLONED MOUSE 2-CELL AND BLASTOCYST STAGE EMBRYOS

Reproduction Fertility and Development ◽

10.1071/rdv26n1ab42 ◽

2014 ◽

Vol 26 (1) ◽

pp. 135

Author(s):

S. L. Marjani ◽

M. G. Carter ◽

L-Y. Sung ◽

K. Inoue ◽

S. Rodriguez-Zas ◽

...

Keyword(s):

Gene Expression ◽

Histone Deacetylases ◽

Trichostatin A ◽

Cell Types ◽

Blastocyst Stage ◽

Cell Stage ◽

Loess Normalization ◽

And Control

Trichostatin A (TSA) is a potent inhibitor of histone deacetylases and has been shown to improve cloned embryo pre-implantation and term development. We examined the effects of TSA treatment on cloned mouse embryonic gene expression using microarrays. Cloned mouse embryos were generated using long-term haematopoietic stem cells (LT-HSC) and terminally differentiated granulocytes (Gr-1) as nuclear donors, which have been shown to have significantly different cloning efficiencies (Sung et al. 2006 Nat. Gen. 38, 1323–1328). Late 2-cell and blastocyst stage cloned embryos and control, BDF1 in vivo and IVF embryos (n = 10 from each embryo type and stage, except LT-HSC blastocysts, where n = 5) were snap frozen in liquid nitrogen. Total RNA was isolated from individual embryos and amplified using the TargetAmp 2 round Aminoallyl aRNA amplification kit (Epicentre Biotechnologies, Madison, WI, USA). Amplified RNA from each embryo and a standard reference was labelled with Cy3 or Cy5 and hybridized to the mouse exonic evidence based oligonucleotide (MEEBO) microarray allowing for the interrogation of ~25 000 genes. After Loess normalization, ANOVA with false discovery rate (P < 0.001) was used to identify differentially expressed (DE) genes. A subset of the DE genes was verified by RT-qPCR. These two cell types drastically differed in their potential to give rise to morula/blastocyst stage embryos: LT-HSC: 4.1% v. Gr-1: 38.9%. When treated with 10 nM TSA (Sigma, St. Louis, MO, USA) for 10 h immediately after activation, the morula/blastocyst rate increased to 66.1% for the LT-HSC cloned embryos and to 69.3% for the Gr-1 cloned embryos. At the 2-cell stage, we identified 2172 DE genes between the TSA-treated and untreated LT-HSC embryos. There were 512 DE genes between the Gr-1 and Gr-1 TSA embryos. Interestingly, the cloned embryos were more similar to the in vivo and IVF embryos after TSA treatment at the 2-cell stage, as evidenced by hierarchical clustering and the reduced number of DE genes: LT-HSC v. in vivo = 2622 genes; LT-HSC TSA v. in vivo = 473; Gr-1 v. in vivo = 1448; Gr-1 TSA v. in vivo = 312. By the blastocyst stage, the effect of TSA was considerably less pronounced with 18 and 17 DE genes between the LT-HSC/TSA and Gr-1/TSA embryos, respectively. These data indicate that TSA treatment normalizes 2-cell cloned embryo gene expression, enabling significantly more embryos to develop to the blastocyst stage. Our findings demonstrate that TSA exerted the greatest effect on the LT-HSC embryos, which were the most difficult to reprogram by SCNT.

Download Full-text

Expression of muscle genes in heterokaryons depends on gene dosage.

The Journal of Cell Biology ◽

10.1083/jcb.102.1.124 ◽

1986 ◽

Vol 102 (1) ◽

pp. 124-130 ◽

Cited By ~ 38

Author(s):

G K Pavlath ◽

H M Blau

Keyword(s):

Gene Expression ◽

Time Course ◽

Gene Dosage ◽

Cell Types ◽

Threshold Concentration ◽

Specific Gene ◽

Mouse Muscle ◽

Muscle Gene Expression ◽

Muscle Genes ◽

Muscle Gene

We report that gene dosage, or the ratio of nuclei from two cell types fused to form a heterokaryon, affects the time course of differentiation-specific gene expression. The rate of appearance of the human muscle antigen, 5.1H11, is significantly faster in heterokaryons with equal or near-equal numbers of mouse muscle and human fibroblast nuclei than in heterokaryons with increased numbers of nuclei from either cell type. By 4 d after fusion, a high frequency of gene expression is evident at all ratios and greater than 75% of heterokaryons express the antigen even when the nonmuscle nuclei greatly outnumber the muscle nuclei. The kinetic differences observed with different nuclear ratios suggest that the concentration of putative trans-acting factors significantly influences the rate of muscle gene expression: a threshold concentration is necessary, but an excess may be inhibitory.

Download Full-text