nudt7 gene depletion causes transcriptomic change in early development of zebrafish.

The Nudt family has been identified as enzymes performing Coenzyme A to 3'5'-ADP + 4'-phospho pantetheine catalysis. The members of this family have been shown to be particularly involved in lipid metabolism, while their involvement in gene regulation through regulating transcription or mRNA metabolism has also been suggested. Here, we focused on peroxisomal NUDT7, possessing enzymatic activity similar to that of its paralog, peroxisomal NUDT19, which is involved in mRNA degradation. No reports have been published about the Nudt family in zebrafish. Our transcriptomic data showed that the Nudt family members are highly expressed around zygotic gene activation (ZGA) in developing zebrafish embryos. Therefore, we confirmed the computational prediction that the products of the nudt7 gene in zebrafish were localized in the peroxisome and highly expressed in early embryogenesis. The depletion of nudt7 genes by the CRISPR/Cas9 system did not affect development; however, it decreased the rate of transcription in ZGA. In addition, H3K27ac ChIP-seq analysis demonstrated that this decrease in transcription was correlated with the genome-wide decrease of H3K27ac level. This study suggests that peroxisomal Nudt7 functions in regulating transcription in ZGA via formation of the H3K27ac domain in active chromatin.

Unusual nucleosome formation and transcriptome influence by the histone H3mm18 variant.

Histone H3mm18 is a non-allelic H3 variant expressed in skeletal muscle and brain in mice. However, its function has remained enigmatic. We found that H3mm18 is incorporated into chromatin in cells with low efficiency, as compared to H3.3. We determined the structures of the nucleosome core particle (NCP) containing H3mm18 by cryo-electron microscopy, which revealed that the entry/exit DNA regions are drastically disordered in the H3mm18 NCP. Consistently, the H3mm18 NCP is substantially unstable in vitro. The forced expression of H3mm18 in mouse myoblast C2C12 cells markedly suppressed muscle differentiation. A transcriptome analysis revealed that the forced expression of H3mm18 affected the expression of multiple genes, and suppressed a group of genes involved in muscle development. These results suggest a novel gene expression regulation system in which the chromatin landscape is altered by the formation of unusual nucleosomes with a histone variant, H3mm18, and provide important insight into understanding transcription regulation by chromatin.

Chromatin loading of MCM hexamers is associated with di-/tri-methylation of histone H4K20 toward S phase entry.

DNA replication is a key step in initiating cell proliferation. Loading hexameric complexes of minichromosome maintenance (MCM) helicase onto DNA replication origins during the G1 phase is essential for initiating DNA replication. Here, we examined MCM hexamer states during the cell cycle in human hTERT-RPE1 cells using multicolor immunofluorescence-based, single-cell plot analysis, and biochemical size fractionation. Experiments involving cell-cycle arrest at the G1 phase and release from the arrest revealed that a double MCM hexamer was formed via a single hexamer during G1 progression. A single MCM hexamer was recruited to chromatin in the early G1 phase. Another single hexamer was recruited to form a double hexamer in the late G1 phase. We further examined relationship between the MCM hexamer states and the methylation levels at lysine 20 of histone H4 (H4K20) and found that the double MCM hexamer state was correlated with di/trimethyl-H4K20 (H4K20me2/3). Inhibiting the conversion from monomethyl-H4K20 (H4K20me1) to H4K20me2/3 retained the cells in the single MCM hexamer state. Non-proliferative cells, including confluent cells or Cdk4/6 inhibitor-treated cells, also remained halted in the single MCM hexamer state. We propose that the single MCM hexamer state is a halting step in the determination of cell cycle progression.

Transcriptome analysis of gene expression changes upon enzymatic dissociation in skeletal myoblasts.

Single-cell RNA-sequencing analysis is one of the most effective tools for understanding specific cellular states. The use of single cells or pooled cells in RNA-seq analysis requires the isolation of cells from a tissue or culture. Although trypsin or more recently cold-active protease (CAP) has been used for cell dissociation, the extent to which the gene expression changes are suppressed has not been clarified. To this end, we conducted detailed profiling of the enzyme-dependent gene expression changes in mouse skeletal muscle progenitor cells, focusing on the enzyme treatment time, amount and temperature. We found that the genes whose expression was changed by the enzyme treatment could be classified in a time-dependent manner and that there were genes whose expression was changed independently of the enzyme treatment time, amount and temperature. This study will be useful as reference data for genes that should be excluded or considered for RNA-seq analysis using enzyme isolation methods.

Epigenetic effects induced by the ectopic expression of Pax7 in 3T3-L1.

Although skeletal muscle cells and adipocytes are derived from the same mesoderm, they do not transdifferentiate in vivo and are strictly distinct at the level of gene expression. To elucidate some of the regulatory mechanisms underlying this strict distinction, Pax7, a myogenic factor, was ectopically expressed in 3T3-L1 adipose progenitor cells to perturb their adipocyte differentiation potential. Transcriptome analysis showed that ectopic expression of Pax7 repressed the expression of some adipocyte genes and induced expression of some skeletal muscle cell genes. We next profiled the epigenomic state altered by Pax7 expression using H3K27ac, an activating histone mark, and H3K27me3, a repressive histone mark, as indicators. Our results show that ectopic expression of Pax7 did not result in the formation of H3K27ac at loci of skeletal muscle-related genes, but instead resulted in the formation of H3K27me3 at adipocyte-related gene loci. These findings suggest that the primary function of ectopic Pax7 expression is the formation of H3K27me3, and muscle gene expression results from secondary regulation.

Genome-wide analysis of chromatin structure changes upon MyoD binding in proliferative myoblasts during the cell cycle.

MyoD, a myogenic differentiation protein, has been studied for its critical role in skeletal muscle differentiation. MyoD-expressing myoblasts have a potency to be differentiated with proliferation of ectopic cells. However, little is known about the effect on chromatin structure of MyoD binding in proliferative myoblasts. In this study, we evaluated the chromatin structure around MyoD-bound genome regions during the cell cycle by chromatin immunoprecipitation sequencing. Genome-wide analysis of histone modifications was performed in proliferative mouse C2C12 myoblasts during three phases (G1, S, G2/M) of the cell cycle. We found that MyoD-bound genome regions had elevated levels of active histone modifications, such as H3K4me1/2/3 and H3K27ac, compared with MyoD-unbound genome regions during the cell cycle. We also demonstrated that the elevated H3K4me2/3 modification level was maintained during the cell cycle, whereas the H3K27ac and H3K4me1 modification levels decreased to the same level as MyoD-unbound genome regions during the later phases. Immunoblot analysis revealed that MyoD abundance was high in the G1 phase then decreased in the S and G2/M phases. Our results suggest that MyoD binding formed selective epigenetic memories with H3K4me2/3 during the cell cycle in addition to myogenic gene induction via active chromatin formation coupled with transcription.

A Promising Method for Calculating True Steady-State Metabolite Concentrations in Large-Scale Metabolic Reaction Network Models.

The calculation of steady-state metabolite concentrations in metabolic reaction network models is the first step in the sensitivity analysis of a metabolic reaction system described by differential equations. However, this calculation becomes very difficult when the number of differential equations is more than 100. In the present study, therefore, we investigated a calculation procedure for obtaining true steady-state metabolite concentrations both efficiently and accurately even in large-scale network models. For convenience, a linear pathway model composed of a simple Michaelis-Menten rate law and two TCA cycle models were used as case studies. The calculation procedure is as follows: first solve the differential equations by a numerical method for solving initial-value problems until the upper several digits of the calculated values stabilize, and then use these values as initial guesses for a root-finding technique. An intensive investigation indicates that the S-system technique, finding roots in logarithmic space and providing a broader convergence region, is superior to the Newton-Raphson technique, and the algorithm using the S-system technique successfully provides true steady-state values with machine accuracy even with 1,500 differential equations. The complex-step method is also shown to contribute to shortening the calculation time and enhancing the accuracy. The program code has been deposited to https://github.com/BioprocessdesignLab/Steadystateconc.

Evaluation of an S-system root-finding method for estimating parameters in a metabolic reaction model.

In a mathematical model, estimation of parameters from time-series data of metabolic concentrations in cells is a challenging task. However, it seems that a promising approach for such estimation has not yet been established. Biochemical Systems Theory (BST) is a powerful methodology to construct a power-law type model for a given metabolic reaction system and to then characterize it efficiently. In this paper, we discuss the use of an S-system root-finding method (S-system method) to estimate parameters from time-series data of metabolite concentrations. We demonstrate that the S-system method is superior to the Newton-Raphson method in terms of the convergence region and iteration number. We also investigate the usefulness of a translocation technique and a complex-step differentiation method toward the practical application of the S-system method. The results indicate that the S-system method is useful to construct mathematical models for a variety of metabolic reaction networks.