Transcriptome analysis of sevoflurane exposure effects at the different brain regions

Hiroto Yamamoto; Yutaro Uchida; Tomoki Chiba; Ryota Kurimoto; Takahide Matsushima; Maiko Inotsume; Chihiro Ishikawa; Haiyan Li; Takashi Shiga; Masafumi Muratani; Tokujiro Uchida; Hiroshi Asahara

doi:10.1371/journal.pone.0236771

. 2020 Dec 15;15(12):e0236771. doi: 10.1371/journal.pone.0236771

Transcriptome analysis of sevoflurane exposure effects at the different brain regions

Hiroto Yamamoto ^1,^2,^#, Yutaro Uchida ^1,^#, Tomoki Chiba ^1,^#, Ryota Kurimoto ¹, Takahide Matsushima ¹, Maiko Inotsume ¹, Chihiro Ishikawa ³, Haiyan Li ³, Takashi Shiga ^3,⁴, Masafumi Muratani ⁵, Tokujiro Uchida ^2,^*, Hiroshi Asahara ^1,^6,^*

Editor: Wataru Nishimura⁷

PMCID: PMC7737892 PMID: 33320849

Abstract

Backgrounds

Sevoflurane is a most frequently used volatile anesthetics, but its molecular mechanisms of action remain unclear. We hypothesized that specific genes play regulatory roles in brain exposed to sevoflurane. Thus, we aimed to evaluate the effects of sevoflurane inhalation and identify potential regulatory genes by RNA-seq analysis.

Methods

Eight-week old mice were exposed to sevoflurane. RNA from medial prefrontal cortex, striatum, hypothalamus, and hippocampus were analysed using RNA-seq. Differently expressed genes were extracted and their gene ontology terms were analysed using Metascape. These our anesthetized mouse data and the transcriptome array data of the cerebral cortex of sleeping mice were compared. Finally, the activities of transcription factors were evaluated using a weighted parametric gene set analysis (wPGSA). JASPAR was used to confirm the existence of binding motifs in the upstream sequences of the differently expressed genes.

Results

The gene ontology term enrichment analysis result suggests that sevoflurane inhalation upregulated angiogenesis and downregulated neural differentiation in each region of brain. The comparison with the brains of sleeping mice showed that the gene expression changes were specific to anesthetized mice. Focusing on individual genes, sevoflurane induced Klf4 upregulation in all sampled parts of brain. wPGSA supported the function of KLF4 as a transcription factor, and KLF4-binding motifs were present in many regulatory regions of the differentially expressed genes.

Conclusions

Klf4 was upregulated by sevoflurane inhalation in the mouse brain. The roles of KLF4 might be key to elucidating the mechanisms of sevoflurane induced functional modification in the brain.

Introduction

Sevoflurane is the most frequently used volatile anesthetic in general anesthesia. Some reports discussed the perioperative adverse effects of sevoflurane, such as emergence agitation, postoperative delirium, and cognitive disorders, although whether anesthetics themselves cause perioperative adverse effects is still controversial [1–3]. Several membrane receptors such as the γ-aminobutyric acid type A receptor, nicotinic AchR, hyperpolarization-activated cyclic nucleotide-gated channels have been reported to be potential targets of sevoflurane [4–9]. However, receptor-based molecular mechanisms have not sufficiently explained these phenomena. Furthermore, although some reports have evaluated the effects of sevoflurane using transcriptome analysis, these studies focused only on limited parts of the brain. Hayase et al. reported that the increase in dopamine activity in the hippocampus due to inhalation of sevoflurane might be related to postoperative nausea, and Mori et al. reported circadian gene variations in the suprachiasmatic nucleus after sevoflurane inhalation [10, 11]. However, we thought that by comparing many regions at once and extracting genes that might play common role in all regions, we could focus on genes that are important with regard to the whole brain.

In this study, medial prefrontal cortex (MPFC), hippocampus, striatum, and hypothalamus were chosen as targets of the analysis, as these parts were frequently used for evaluating the effects of volatile anesthetics [12–15]. Differently expressed genes (DEGs) and enriched gene groups were compared between the four parts of the brain and we applied the same analysis to the transcriptome array data of sleeping mice to identify specific gene expression changes in brains exposed to sevoflurane. Finally, we evaluated the effects of the transcription factors on their target genes using wPGSA and confirmed the existence of consensus-binding motifs in the upstream sequences of DEGs. Herein, we report sevoflurane-induced gene expression change patterns in the mouse brain and that KLF4 emerged as a specific transcription factor that potentially promoted angiogenesis and induced the appearance of undifferentiated neural cells.

Materials and methods

Approval for the animal experiments

All the animal experiments in this study were conducted in accordance with the Guidelines for Proper Conduct of Animal Experiments (Science Council of Japan) and approved by the Center for Experimental Animals of Tokyo Medical and Dental University. (Approval No.A2017-131A)

Experimental conditions and preparation of brain samples

Eight-week old mice (C57BL/6J) were purchased from Sankyo Labo (Tokyo, Japan) and Oriental Yeast (Tokyo, Japan). Six mice were assigned into two groups, the control (n = 3) and sevoflurane inhalation groups (n = 3). For the sevoflurane group, the mice were put in a box with 2.5% sevoflurane / 40% oxygen for 3 hours. The body temperature was measured and sustained within the range of ±0.5°C by using a body warming machine. For the control group, the mice were put in a box with normal air and stayed in the box without food or water for 3 hours. After the treatments, all the mice were immediately killed through cervical dislocation, and their whole brains were removed. The brain samples were cut into 2 mm slices, and the medial prefrontal cortex, striatum, hippocampus, and hypothalamus were punched out, referring to the methods of Ishikawa et al [16].

RNA extraction from brain tissue sections and RNAseq analysis

RNA was extracted from brain tissue sections by using TRIZOL (ThermoFisher, Waltham, MA, USA) and 500ng total RNA was used for the subsequent preparation. RNA-seq libraries were prepared with a rRNA-depletion kit (E6310, New England Biolabs Japan, Tokyo, Japan) and a directional library synthesis kit (E6310, New England Biolabs Japan). The RNA libraries were sequenced using NextSeq500 High-output kit v2 for 2 × 36 base reads.

Mapping FASTQ data and calculating gene expressions

The adapters in the FASTQ files were trimmed using the TrimGalore software (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/). The FASTQ files were mapped to mouse genomes (mm10) by using the STAR software [17] (https://github.com/alexdobin/STAR), and the amount of each transcript was calculated with the RSEM software [18] (https://github.com/deweylab/RSEM).

Extracting DEGs on iDEP.91

The counted data were transformed with EdgeR (log₂ [counts per million (CPM) + 4]), and principal components analysis (PCA) plots were depicted. DEGs were extracted using DESeq2. All these steps were performed with iDEP.91 [19] (http://bioinformatics.sdstate.edu/idep/). Venn-diagrams were used to depict the upregulated and downregulated DEGs.

Sequencing data

The raw sequencing data were submitted to the DNA Data Bank Japan (DDBJ: http://www.ddbj.nig.ac.jp) under accession No. DRA010292.

Gene ontology term enrich analysis using Metascape

The extracted DEGs were analysed with Metascape [20] (http://metascape.org/gp/index.html#/main/step1). A gene ontology (GO) term enrichment analysis was performed, and a Circos plot was drawn.

Extraction of DEGs from sleeping mice

The transcriptome array data of the unbound fractions of immunoprecipitation for the cerebral cortices of waking or sleeping mice (GSE69079) were used in the analysis [21]. The expression data were normalized, and DEGs were selected using DESeq2 in iDEP. 91. Venn-diagrams were used to depict the DEGs of the MPFCs of anesthetized mice and cerebral cortices of the sleeping mice.

Weighted Parametric Gene Set Analysis (wPGSA) of DEGs in the brains of mice that inhaled sevoflurane

For the fold changes data, the expression changes of the target genes of each transcription factor were calculated and its activity (T-score) was estimated using a weighted parametric gene set analysis (wPGSA [22]: http://wpgsa.org/). Expressed transcription factors in the brain were extracted from the analysed data. The transcription factors with T-scores of > 2.0 and false discovery rates (FDRs) of < 0.1 were regarded as active transcription factors, while those with T-scores of < - 2.0 and FDR of < 0.1 were regarded as suppressive transcription factors. Moreover, the transcription factors included in the DEGs were extracted from active and suppressive transcription factors and, regarded as responsible for anesthetic effects.

Histological and immunohistochemical analysis

Mouse brain was fixed in 4% paraformaldehyde overnight at 4°C, and embedded in paraffin. Sections of 4μm in thickness were stained. Immunohistochemical staining was performed using a Vectastain ABC-AP Rabbit IgG Kit (AK-5001, VECTOR LABORATORIES, INC., CA, USA) and Vector Red (SK-5100, VECTOR LABORATORIES, INC.) according to the manufacturer’s instructions. Anti-KLF4 antibody (1/100 dilution) (NBP2-24749, Novus Biologicals, CO, USA) was used as the primary antibodies.

Western blotting analysis for brains exposed to sevoflurane

Proteins were collected from hippocampus with lysis buffer (10 mM Tris-HCl, 2%SDS) with protease inhibitor (WAKO, Osaka, Japan). 50μg (for KLF4) or 20μg (for ACTB) of proteins were separated by SDS-PAGE followed by semi-dry transfer to a PVDF membrane. Membranes were blocked for 1h with Blocking-One (Nacalai Tesque, Kyoto, Japan), reacted with primary antibody for KLF4 (4038S, CST, MA, USA) or ACTB (010–27841, WAKO) at 4°C overnight, rinsed and reacted with ECL mouse IgG HRP-conjugated whole antibody (GE Healthcare, IL, USA) or rabbit IgG HRP-conjugated whole antibody (GE Healthcare). The blot was developed using the ECL Select Western Blotting Detection Reagent (GE Healthcare).

Detection of the consensus-binding motifs of Klf4 in the upstream sequences of DEGs

The consensus-binding motifs of KLF4 were referred from JASPAR (http://jaspar.genereg.net/). The 1000-bp upstream sequences of the DEGs annotated with the GO terms “angiogenesis” and “head development” were analysed using JASPAR and the existence of KLF4 binding motifs was confirmed. We regarded the motifs with scores of > 8 as candidate binding motifs for KLF4.

Statistical analyses

In extracting DEGs from RNA-seq data and differently activating transcription factors from the wPGSA analysed data, we considered FDRs of < 0.1 as statistically significant.

Results

Genome-wide transcriptome analysis for the brains of mice that inhaled sevoflurane

To investigate the sevoflurane-induced gene expression changes in the brain, three 8 week old male mice that inhaled sevoflurane for 3 hours or the control mice were killed, and their brains were removed. The brain tissue samples were cut into 2 mm slices, and four parts of the brain (hippocampus, hypothalamus, medial prefrontal cortex and striatum) were punched out for RNA extraction. We performed a genome-wide transcriptional analysis with next generation sequencing, and confirmed the proper RNA extraction from each brain area by the PCA plot (Fig 1A, S1A and S1B Fig). DEGs were extracted on the basis of the criteria of FDR < 0.1 (S1 Table). Among the upregulated DEGs, 100, 109, 33, and 314 were expressed in the striatum, MPFC, hypothalamus and hippocampus, respectively. Among the downregulated DEGs, 93, 121, 18, and 502 were expressed in the striatum, MPFC, hypothalamus, hippocampus, respectively (Fig 1B–1E, S2 Table). The highest number of DEGs was found in the hippocampus; and the lowest number in the hypothalamus. These results suggest that the gene expression in the hippocampus was the most-influenced and that in the hypothalamus was the least-influenced by sevoflurane inhalation.

Fig 1 — (A)The workflow of the RNA-seq analysis for the anesthetized mice. After anesthetizing with 2.5% of sevoflurane and 40% oxygen for 3 hours, the brains were removed and sliced into 2 mm pieces. The striatum, medial prefrontal cortex (MPFC), hypothalamus and hippocampus were punched out. RNA was extracted from the punched out samples and RNA-seq was performed using NextSeq500.

(B)~(E) FASTQ files were mapped using STAR, differently expressed genes (DEGs) were extracted using iDEP.91 and MA-plots were drawn for the striatum (B), medial prefrontal cortex (C), hypothalamus (D), and hippocampus (E).

To compare the upregulated DEGs in the different parts of the brain, a Venn-diagram was drawn (Fig 2A). Thirteen common upregulated genes found in all sampled parts of the brain are shown in Fig 2B. Sevoflurane inhalation upregulated transcription factors such as Klf4 in all sampled parts (Fig 2B). The expression level of Klf4 was >2.5 times higher than that in the control mice. Furthermore, to investigate the differences of upregulated DEGs between the different parts of the brain, a GO term enrichment analysis was performed using Metascape [20]. The Circos plot drawn using Metascape showed similarities in the upregulation patterns of the gene expressions in the four parts of the brain (Fig 2C). As shown in the heatmap, sevoflurane inhalation caused the upregulation of genes annotated as “angiogenesis” and “response to wounding” in all parts (Fig 2D). The transcription factors KLF4 and KLF2, as well as EDN1, CCN1, and ADAMTS1, were annotated to the GO terms “angiogenesis” and “response to wounding” (S3 Table).

Next, downregulated DEGs were compared between the four parts of the brain, and a Venn-diagram was drawn (Fig 3A). The common downregulated DEGs among each part of brain was only the Banp gene (Fig 3B). Furthermore, to compare the downregulated DEGs between the four parts of the brain, a GO term enrichment analysis was performed with Metascape. As shown in the Circos plot, enriched GO terms were similar among the different parts of the brain (Fig 3C). Moreover, the heatmap showed that sevoflurane inhalation downregulated the genes annotated as “head development” in all sampled parts of brain, and those annotated as “axon development” or “synapse organization” in several parts (Fig 3D and S4 Table).

For identifying specific gene expression changes induced by sevoflurane inhalation, a comparison was made with the transcriptome array data of the cerebral cortices of sleeping mice as the resembling state [21]. We chose the data of MPFCs exposed to sevoflurane as an equivalent part to the cerebral cortices of the sleeping mice. We extracted DEGs using the same method in our experiments. Regarding the comparison between the gene expression changes in the cerebral cortices of the sleeping mice and those of the waking mice, the sleeping mice had 477 upregulated DEGs and 3572 downregulated DEGs (S5 and S6 Tables). As shown in the Venn diagrams, there were 5 common upregulated DEGs and 45 common downregulated DEGs were found between the sevoflurane-anesthetized and sleeping mice (S2A and S2B Fig, S7 Table). Moreover, by comparing genes upregulated and downregulated in all parts of the brain exposed to sevoflurane, we found that all the genes except Edn1 were completely expressed differently (S2C and S2D Fig).

Identification of KLF4 as a candidate of key transcriptional regulator in brain exposed to sevoflurane

As represented by KLF4, sevoflurane induced changes in the expressions of many transcription factors from the analysis of DEGs. Therefore, we hypothesized that sevoflurane changed the activities of specific transcription factors in each part of the brain. To verify this hypothesis, we utilized the wPGSA method [22], with which evaluated the expression changes of the target genes for each transcription factor by using T-scores. A positive T-score means that the transcription factor functions as an activator, while a negative T score means that it functions as a repressor. We regarded transcription factors with both |T-score| > 2.0 and FDR < 0.1 as functional transcription factors. With the wPGSA method, 34, 3, 3, and 1 transcription factors in the MPFC, striatum, hypothalamus, and hippocampus were estimated as activators, respectively. Ninety-three, 188, 113, and 168 transcription factors in the MPFC, striatum, hypothalamus, and hippocampus were estimated as repressors, respectively (Fig 4A, 4C, 4E and 4G; S8 Table). Moreover, we identified activators and repressors included in the DEGs, inferring that they particularly functioned owing to the induction by sevoflurane. In the MPFC, the target genes of Klf4, Klf2, and Per2 were upregulated, while those of Atf4 and Taf1 were downregulated (Fig 4B). Likewise, in the striatum, the target genes of 5 transcription factors were downregulated, and in the hypothalamus, the target genes of KLF4 were downregulated (Fig 4D and 4F). Finally, in the hippocampus, the target genes of 14 transcription factors were downregulated (Fig 4H). These results indicate that KLF4 plays some important roles in gene expression in brains exposed to sevoflurane. To validate the upregulation of KLF4, we performed immunohistochemical analysis for the cerebral cortex and hippocampus. As a result, we observed that the expression of KLF4 was strongly upregulated in the nucleus of cells in the cerebral cortex of mice exposed to sevoflurane. On the other hand, nucleus in neural cells of hippocampus in both control mice and mice exposed to sevoflurane showed high expression of KLF4, and no significant changes were observed in immunohistochemical analysis (S3A Fig). Based on these results, we performed western blotting analysis to validate the upregulation of KLF4 in the hippocampus, showing a certain upregulation of KLF4 (S3B Fig).

Fig 4 — (A)-(H) Weighted parametric gene set analysis (wPGSA) of the fold changes in each part of the brain. Transcription factors (TFs) with T-scores of > 2.0 or < -2.0 were identified and the distributions of the T-scores of the medial prefrontal cortex (MPFC) (A), striatum (C), hypothalamus (E), and hippocampus (G) were drawn. Furthermore, the transcription factors included in differently expressed genes (DEGs) were identified and the tables of the T-scores and expression fold changes for MPFC (B), striatum (D), hypothalamus (F), and hippocampus (H) were made.

Even Klf4 was upregulated in all four parts of the brain, it worked as an activator in the MPFC, and as a repressor in the other three parts of brain. KLF4 was reported to function as both as an activator and a repressor, and this result might reflect the different transcriptional roles of KLF4 between each part of brain [23]. Moreover, the expression of the same Klf family gene, Klf2, was also upregulated in the MPFC and functioned as an activator, while Klf5 and its target genes were downregulated in the striatum and hippocampus. These results indicate the possibility of cooperative functions between the same Klf family genes.

Finally, we confirmed the existence of consensus sequences of KLF4 in the DEGs of important functions. The consensus-binding motif sequence of murine KLF4 was GGG(T/C)G(G/T)GGC according to JASPAR (http://jaspar.genereg.net/). On JASPAR, we searched the candidate binding sites of KLF4 in 1000bp upstream sequences for upregulated DEGs annotated GO of “angiogenesis”, and downregulated DEGs annotated GO of “head development”. As shown in the pie charts, 82.7% of the GOs of the upregulated DEGs annotated as “angiogenesis”, and 82.5% of the GOs of the downregulated DEGs annotated as “head development” had consensus-binding motifs in their 1000-bp upstream sequences (Fig 5A and 5B, S9 Table). These results indicate that KLF4 has the potential to regulate the transcription of genes related to angiogenesis and neural development, which might contribute to vascular neogenesis and the appearance of undifferentiated neural cells (Fig 5C).

Fig 5 — (A) Pie chart of the existence of KLF4-binding motifs in the 1000-bp upstream sequences of the genes annotated to the GO term “angiogenesis”. (B) Pie chart of the existence of KLF4-binding motifs in the 1000-bp upstream sequences of the genes annotated to the GO term “head development”. (C) Estimated mechanism of the effects of sevoflurane on the brain.

Discussion

In this study, our group performed a genome-wide transcriptional analysis for the brains of mice that inhaled sevoflurane. Results of our analyses suggest that sevoflurane induced both angiogenesis and the appearance of undifferentiated neural cells in all sampled parts of brain. These changes in gene expression were not observed in the brains of sleeping mice, and seemed specific to brains exposed to sevoflurane. The transcription factor Klf4 was commonly upregulated in all sampled brain, and the results of the wPGSA and motif analysis suggest that KLF4 is a key transcriptional regulator of the angiogenesis and appearance of undifferentiated neural cells.

KLF4 is known as an essential regulator of the initialization of iPS cells, or so-called “Yamanaka factor” [24]. Moreover, the redundant and cooperative functions between KLF2 and KLF5 were reported to be important for sustaining the undifferentiated state of ES cells [25]. Thus, KLF2, KLF4, and KLF5 are known to be fundamental factors for sustaining undifferentiated states. Considering the upregulation of Nestin, which is a specific marker of undifferentiated neural cells, and the decreasing expression of genes associated with neural differentiation, sevoflurane inhalation seemed to cause the appearance of undifferentiated neural cells by the Klf family genes.

In the previous report, sevoflurane administration decreased the cerebral blood flow in a statistical parametric mapping analysis [26]. Other reports also indicated that sevoflurane inhalation caused permeability of the brain-blood barrier induced the plasma influx into the brain parenchyma, possibly causing postoperative delirium and cognitive decline [27]. Our results that show the upregulation of genes encoding angiogenesis and the appearance of undifferentiated cells were potentially related with these functional changes in the brain caused by sevoflurane. In this context, KLF4 seemed to be the key regulator of these genes, and precise analyses of the roles of KLF4 might be key to unveiling the mechanism of the sevoflurane anesthesia-induced postoperative functional modification of the brain.

Detailed analysis between anesthesia and sleep is difficult because of the different experimental conditions, but at least in this comparison, gene expression changes in the brain exposed to sevoflurane showed a pattern that was very different from that of sleep. Especially KLF4 seemed to function specifically by sevoflurane inhalation. The roles of KLF4 seemed to differ among the parts of the brain in our wPGSA. KLF4 has multiple functions, including as activators and repressors, and work context- dependently [23, 28, 29]. Furthermore, our analysis revealed that KLF4 had potentials to upregulate genes related to angiogenesis and downregulate neural differentiation. The variable activity of KLF4 might reflect the differences of these activities between the parts of the brain. For a precise understanding of the specific roles of KLF4 induced by sevoflurane, chromatin immunoprecipitation analysis of KLF4 and histone markers, such as H3K9me3 and H3K27Ac in each part of brain are needed. Furthermore, experimental methods that combine single-cell RNA-seq and location information such as Slide-seq may provide more useful information [30]. Nevertheless, our analysis results indicated the importance of KLF4 as a candidate regulator of the effects caused by sevoflurane inhalation.

Our report, which focuses on the changes of transcription factors, provides original and novel approaches for analysing the effects of anesthetics in brain. This is the first report to evaluate the effects of sevoflurane inhalation, focusing on the activities of transcription factors. As a limitation of this study, only three of samples were used. However, we concluded that increasing replicates did not significantly change the results because of the high reproducibility between triplicates, supported by the PCA plot (S1B Fig). Furthermore, we could not exclude the possibility of the effect of the hypoxic condition caused by the respiratory depression induced by sevoflurane [31]. However, our experimental condition (2.5% sevoflurane in 40% oxygen for 3 hours) is common setting in experiments for studies on the effects of sevoflurane on the brain. None of the genes related to hypoxic reaction, including Hif1a and Arnt, were detected in our analyses of gene expression changes, supporting the exclusion of the possibility of hypoxia in our experimental conditions (S1 Table). Conversely, oxygen saturation might have been higher in the anesthetized group than in the control group, which was allowed to spend time in room air, and since we did not measure oxygen saturation, it is possible that subtle differences in oxygen saturation existed and that this might have affected the results. Oxygen saturation assessment in mice may provide more reliable results. Nevertheless, our strategy should include better choices for obtaining the whole image of brain activities under anesthetized condition.

In conclusion, the results of our genome-wide transcriptional analysis of the brains of mice that inhaled sevoflurane suggest the upregulation of angiogenesis and appearance of undifferentiated neural cells. Moreover, we identified KLF4 as a potential regulator of the effects induced by sevoflurane inhalation.

Supporting information

S1 Fig. RNA-seq analysis for anesthetized brain.

(A)The distribution of log₂ ((count per million) +4) after normalization. (B)PCA-plot for RNA-seq data.

(TIF)

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S2 Fig. Comparison of Differently Expressed Genes (DEGs) between the brains of the anesthetized and sleeping mice.

(A, B) DEGs were extracted from the transcriptome array data of the cortical cortices of the sleeping mice. The DEGs in the medial prefrontal cortex of the mice that inhaled sevoflurane and those in the cortical cortices of the sleeping mice were compared. The Venn-diagrams for the upregulated (A) and downregulated DEGs (B) are shown. (C) Table of the expression fold change (log2) of the genes commonly upregulated in the four parts of the brain of the mice that inhaled sevoflurane. (D) Table of expression fold changes (log2) of the genes commonly downregulated in the four parts of brain of the mice that inhaled sevoflurane.

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S3 Fig. Immunohistochemistry and western blotting for hippocampus of brains exposed to sevoflurane.

Representative image of immunohistochemical analysis of KLF4 for cerebral cortex and hippocampus of mice exposed to sevoflurane. Western blotting for hippocampus of brains exposed to sevoflurane.

(TIF)

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S1 Table. Gene expression data for all the genes in all parts of the brain of mice that inhaled sevoflurane.

Log₂ (read counts per million +4) of all the genes of all parts of the brain from the RNAseq analysis data by iDEP91 are shown.

(XLSX)

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S2 Table. Gene lists of differently expressed genes in each part of the brain.

The gene names and expression fold change data (sevoflurane group vs control group) of the hippocampus, hypothalamus, striatum, and medial prefrontal cortex are shown.

(XLSX)

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S3 Table. Lists of genes and gene ontology terms of upregulated differently expressed genes.

Metascape analysis was performed for upregulated differently expressed genes. The gene ontology (GO) terms, their p values and genes annotated to each GO terms are shown in the table.

(XLSX)

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S4 Table. Genes and gene ontology term lists of downregulated differently expressed genes.

A Metascape analysis was performed for downregulated differently expressed genes. The gene ontology (GO) terms, their p values and genes annotated to each GO terms are shown.

(XLSX)

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S5 Table. Expression and fold change data for each gene from the transcriptome array data of the cortical cortices of sleeping mice.

The gene names, transcriptome array data and expression fold change data (sleeping group vs control group) from GSE69079 are shown.

(XLSX)

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S6 Table. Lists of the differently expressed genes in the cerebral cortices of sleeping mice.

The gene names and each expression fold change data (sleeping group vs control group) for the upregulated and downregulated genes are shown.

(XLSX)

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S7 Table. Comparison of the gene expression fold changes of the common differently expressed genes between mice that inhaled sevoflurane and sleeping mice.

The gene names and each expression fold change data for the common upregulated and downregulated genes (sevoflurane group vs control group and sleeping group vs control group) are shown.

(XLSX)

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S8 Table. Lists of the transcription factors and their T-scores from the wPGSA for each part of brain.

The activities of the transcription factors (TFs) in the medial prefrontal cortex, striatum, hypothalamus, and hippocampus were calculated using the wPGSA analysis. The T-scores of the transcription factors are shown.

(XLSX)

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S9 Table. List of the predicted binding motifs of Klf4 in the upstream sequences of the differently expressed genes.

The predicted binding motifs of KLF4 for the 1000-bp upstream sequences of the differently expressed genes were identified using JASPAR.

(XLSX)

Click here for additional data file.^{(16.5KB, xlsx)}

Acknowledgments

We specially thanked to technical supports for Kana Shishido and Tomomi Kato, and are grateful to all staffs of the Department of Systems BioMedicine at Tokyo Medical and Dental University (TMDU) for their support and discussion.

Data Availability

The data are available from DDBJ with DRA accession number DRA010292.

Funding Statement

This work was supported by Japan Society for the Promotion of Science KAKENHI (URL:https://www.jsps.go.jp/english/index.html, Grant Nos. 20H00547, 19KK0227, 18K19603 and 15H02560 to HA) and AMED‐CREST from AMED (URL: https://www.amed.go.jp/en/index.html, Grant No. JP20gm0810008 to HA). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Ansaloni L, Catena F, Chattat R, Fortuna D, Franceschi C, Mascitti P, et al. Risk factors and incidence of postoperative delirium in elderly patients after elective and emergency surgery. Br J Surg. 2010;97(2):273–80. Epub 2010/01/14. 10.1002/bjs.6843 . [DOI] [PubMed] [Google Scholar]
2.Neufeld KJ, Leoutsakos JM, Sieber FE, Wanamaker BL, Gibson Chambers JJ, Rao V, et al. Outcomes of early delirium diagnosis after general anesthesia in the elderly. Anesth Analg. 2013;117(2):471–8. Epub 2013/06/13. 10.1213/ANE.0b013e3182973650 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Rudolph JL, Marcantonio ER. Review articles: postoperative delirium: acute change with long-term implications. Anesth Analg. 2011;112(5):1202–11. Epub 2011/04/09. 10.1213/ANE.0b013e3182147f6d [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Wu J, Harata N, Akaike N. Potentiation by sevoflurane of the gamma-aminobutyric acid-induced chloride current in acutely dissociated CA1 pyramidal neurones from rat hippocampus. Br J Pharmacol. 1996;119(5):1013–21. 10.1111/j.1476-5381.1996.tb15772.x WOS:A1996VQ13600033. [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Jenkins A, Franks NP, Lieb WR. Effects of temperature and volatile anesthetics on GABA(A) receptors. Anesthesiology. 1999;90(2):484–91. 10.1097/00000542-199902000-00024 WOS:000078326100023. [DOI] [PubMed] [Google Scholar]
6.Stucke AG, Stuth EAE, Tonkovic-Capin V, Tonkovic-Capin M, Hopp FA, Kampine JP, et al. Effects of halothane and sevoflurane on inhibitory neurotransmission to medullary expiratory neurons in a decerebrate dog model. Anesthesiology. 2002;96(4):955–62. 10.1097/00000542-200204000-00025 WOS:000174716900024. [DOI] [PubMed] [Google Scholar]
7.Sebel LE, Richardson JE, Singh SP, Bell SV, Jenkins A. Additive effects of sevoflurane and propofol on gamma-aminobutyric acid receptor function. Anesthesiology. 2006;104(6):1176–83. Epub 2006/05/30. 10.1097/00000542-200606000-00012 . [DOI] [PubMed] [Google Scholar]
8.Zhou C, Liang P, Liu J, Ke BW, Wang XJ, Li FS, et al. HCN1 Channels Contribute to the Effects of Amnesia and Hypnosis but not Immobility of Volatile Anesthetics. Anesthesia and Analgesia. 2015;121(3):661–6. 10.1213/ANE.0000000000000830 WOS:000360359200003. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Plourde G, Chartrand D, Fiset P, Font S, Backman SB. Antagonism of sevoflurane anaesthesia by physostigmine: effects on the auditory steady-state response and bispectral index. Br J Anaesth. 2003;91(4):583–U1. 10.1093/bja/aeg209 WOS:000185596500020. [DOI] [PubMed] [Google Scholar]
10.Hayase T, Tachibana S, Yamakage M. Effect of sevoflurane anesthesia on the comprehensive mRNA expression profile of the mouse hippocampus. Med Gas Res. 2016;6(2):70–6. Epub 2016/11/22. 10.4103/2045-9912.184715 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Mori K, Iijima N, Higo S, Aikawa S, Matsuo I, Takumi K, et al. Epigenetic suppression of mouse Per2 expression in the suprachiasmatic nucleus by the inhalational anesthetic, sevoflurane. PLoS One. 2014;9(1):e87319 Epub 2014/02/06. 10.1371/journal.pone.0087319 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Jiang-Xie LF, Yin L, Zhao S, Prevosto V, Han BX, Dzirasa K, et al. A Common Neuroendocrine Substrate for Diverse General Anesthetics and Sleep. Neuron. 2019;102(5):1053–65 e4. Epub 2019/04/23. 10.1016/j.neuron.2019.03.033 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Ando N, Sugasawa Y, Inoue R, Aosaki T, Miura M, Nishimura K. Effects of the volatile anesthetic sevoflurane on tonic GABA currents in the mouse striatum during postnatal development. Eur J Neurosci. 2014;40(8):3147–57. Epub 2014/08/21. 10.1111/ejn.12691 . [DOI] [PubMed] [Google Scholar]
14.Liang P, Li F, Liu J, Liao D, Huang H, Zhou C. Sevoflurane activates hippocampal CA3 kainate receptors (Gluk2) to induce hyperactivity during induction and recovery in a mouse model. Br J Anaesth. 2017;119(5):1047–54. Epub 2017/10/06. 10.1093/bja/aex043 . [DOI] [PubMed] [Google Scholar]
15.Chung W, Ryu MJ, Heo JY, Lee S, Yoon S, Park H, et al. Sevoflurane Exposure during the Critical Period Affects Synaptic Transmission and Mitochondrial Respiration but Not Long-term Behavior in Mice. Anesthesiology. 2017;126(2):288–99. Epub 2016/12/07. 10.1097/ALN.0000000000001470 . [DOI] [PubMed] [Google Scholar]
16.Ishikawa C, Li H, Ogura R, Yoshimura Y, Kudo T, Shirakawa M, et al. Effects of gravity changes on gene expression of BDNF and serotonin receptors in the mouse brain. PLoS One. 2017;12(6):e0177833 Epub 2017/06/08. 10.1371/journal.pone.0177833 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15–21. Epub 2012/10/30. 10.1093/bioinformatics/bts635 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323 Epub 2011/08/06. 10.1186/1471-2105-12-323 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Ge SX, Son EW, Yao R. iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data. BMC Bioinformatics. 2018;19(1):534 Epub 2018/12/21. 10.1186/s12859-018-2486-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523 Epub 2019/04/05. 10.1038/s41467-019-09234-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Bellesi M, de Vivo L, Tononi G, Cirelli C. Effects of sleep and wake on astrocytes: clues from molecular and ultrastructural studies. BMC Biol. 2015;13:66 Epub 2015/08/26. 10.1186/s12915-015-0176-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Kawakami E, Nakaoka S, Ohta T, Kitano H. Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data. Nucleic Acids Res. 2016;44(11):5010–21. Epub 2016/05/02. 10.1093/nar/gkw355 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Ghaleb AM, Yang VW. Kruppel-like factor 4 (KLF4): What we currently know. Gene. 2017;611:27–37. Epub 2017/02/27. 10.1016/j.gene.2017.02.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Takahashi K, Tanabe K, Ohnuki M, Narita M, Ichisaka T, Tomoda K, et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131(5):861–72. Epub 2007/11/24. 10.1016/j.cell.2007.11.019 . [DOI] [PubMed] [Google Scholar]
25.Jiang J, Chan YS, Loh YH, Cai J, Tong GQ, Lim CA, et al. A core Klf circuitry regulates self-renewal of embryonic stem cells. Nat Cell Biol. 2008;10(3):353–60. Epub 2008/02/12. 10.1038/ncb1698 . [DOI] [PubMed] [Google Scholar]
26.Kaisti KK, Metsahonkala L, Teras M, Oikonen V, Aalto S, Jaaskelainen S, et al. Effects of surgical levels of propofol and sevoflurane anesthesia on cerebral blood flow in healthy subjects studied with positron emission tomography. Anesthesiology. 2002;96(6):1358–70. Epub 2002/08/10. 10.1097/00000542-200206000-00015 . [DOI] [PubMed] [Google Scholar]
27.Acharya NK, Goldwaser EL, Forsberg MM, Godsey GA, Johnson CA, Sarkar A, et al. Sevoflurane and Isoflurane induce structural changes in brain vascular endothelial cells and increase blood-brain barrier permeability: Possible link to postoperative delirium and cognitive decline. Brain Res. 2015;1620:29–41. Epub 2015/05/12. 10.1016/j.brainres.2015.04.054 . [DOI] [PubMed] [Google Scholar]
28.Geiman DE, Ton-That H, Johnson JM, Yang VW. Transactivation and growth suppression by the gut-enriched Kruppel-like factor (Kruppel-like factor 4) are dependent on acidic amino acid residues and protein-protein interaction. Nucleic Acids Res. 2000;28(5):1106–13. Epub 2000/02/10. 10.1093/nar/28.5.1106 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Evans PM, Zhang W, Chen X, Yang J, Bhakat KK, Liu C. Kruppel-like factor 4 is acetylated by p300 and regulates gene transcription via modulation of histone acetylation. J Biol Chem. 2007;282(47):33994–4002. Epub 2007/10/03. 10.1074/jbc.M701847200 . [DOI] [PubMed] [Google Scholar]
30.Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, et al. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019;363(6434):1463–7. Epub 2019/03/30. 10.1126/science.aaw1219 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Fukuda M, Ando N, Sugasawa Y, Inoue R, Nakauchi S, Miura M, et al. Volatile anesthetic sevoflurane pretreatment alleviates hypoxia-induced potentiation of excitatory inputs to striatal medium spiny neurons of mice. Eur J Neurosci. 2019;50(9):3520–30. Epub 2019/07/25. 10.1111/ejn.14524 . [DOI] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0236771.r001

Decision Letter 0

Wataru Nishimura

7 Sep 2020

PONE-D-20-21488

Transcriptome analysis of sevoflurane exposure effects at the different brain regions

PLOS ONE

Dear Dr. Asahara,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Your manuscript has been carefully evaluated by four external reviewers with expertise in this field. They are basically positive, but raised several concerns below. Especially, they suggest that changes in protein expression of KLF4 by sevoflurane exposure, and roles of KLF4 up-regulation on the angiogenesis or differentiation of neural cells, should be demonstrated. Further consideration of appropriate controls, description and Interpretation of the results, and data availability is also required. These critical suggestions should be addressed for further consideration. Because conclusions are not presented in an appropriate fashion and are not supported by the data, this manuscript cannot be recommended for publication in PLoS ONE in its current form.

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Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Partly

Reviewer #4: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

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Reviewer #1: Thank you for sending!

In general, the present manuscript by Hiroto Y et al. described the transcriptome analysis after sevoflurane exposure in mice and specifically concluded some important regulators such as KLF4 in sevoflurane anesthesia. The aim of this study is of interest to relevant researchers and also important to clinical anesthesia. However, there are a lot of fundamental concerns both from experimental designs and over-interpretation of the data:

1. As a control, sleeping mice were used. The relational is acceptable. However, many factors can affect the comparability between groups, including but not limited to sleeping length vs. 3h-exposure of sevoflurane; did you consider about physiological circadian rhythms between these groups of mice? So, the data between sevoflurane anesthesia and baseline is more reliable than the difference between anesthesia and sleeping.

2. Only a small number of mice used in each group, so the signal to noise ratio may be not good to get a solid conclusion.

3. Single-cell sequencing is already common. The technique of RNA-seq is not state-of-art method for such comparisons. In introduction, there is no any description of already published studies about transcriptome after anesthesia, which is critical for relational of the study: what is already known and what is need to know?

4. The last and the most significant concern is that: the authors declared that KLF4 is a specific responsible transcription factor that potentially promotes angiogenesis and induces the appearance of undifferentiated neural cells. All these conclusions are completely based on data analysis. Without any actual measurement of angiogenesis and neural development after sevoflurane exposure, and did not design any intervention aiming these transcription factor cannot conclude such statements. Overall, the conclusion of the present manuscript is much over-interpreted, which need substantial revision. There is no solid causality between the transcription factor and sevoflurane exposure, as well as the proposed outcomes after anesthesia.

Minors:

1. The short title is not correct;

2. Why the mice exposed to sevoflurane with 3 hours? Is there any exposure-time dependent effect?

3. In results part, there are too much re-descriptions like methods.

Reviewer #2: The manuscript " Transcriptome analysis of sevoflurane exposure effects at the different brain regions" submitted by Hiroto Yamamoto et al. uses RNA-seq to analyze the differential gene expression from different brain regions. They conclude that Klf4 was upregulated by sevoflurane inhalation in whole brain. KLF4 might promote angiogenesis and cause the appearance of undifferentiated neural cells by transcriptional regulation. Overall, the results are interesting. However, the questions below need to be clarified.

1. Now that Klf4 is upregulated whole brain, the expression of Klf4 in protein levels need to be added through western blot or immunohistochemistry in four brain regions which will confirm your conclusion.

2. Anesthetics including sevoflurane can cause POCD, especially in elderly patients. Why did the authors use 8-week-old mice instead of aged mice?

3. In fact, only four brain regions were used to analyze the expression of different genes, however, the conclusion was the expression in whole brain. These four brain regions do not represent the whole brain. What about the brainstem and olfactory bulb?

4. About the treatment of control group mice, why did the control group mice use normal air instead of 40%O2?

5. Delete 138 lines of redundant “analysis”

Reviewer #3: Re: Review of PONE-D-20-21488

Thank you for the opportunity to review the manuscript “Transcriptome analysis of sevoflurane exposure effects at the different brain regions” by Yamamoto et al.

The author performed animal experiments and RNA-seq analysis to focus on a simultaneous analysis of the effects of sevoflurane on the gene expression changes in multiple anatomical sites of the brain.

This is indeed an interesting topic for review and discussion amongst the international community. I have listed my comments/concerns below.

(1) The sample size of this study (n=6; sevo group, n=3 vs ctl group, n=3) is too small to draw strong conclusions from the current data.

(2) The transcriptome array data of sleeping mice used in this study from existing database. Sleeping mice should be set as a group in your study, if possible.

(3) Problems on scientific writing: discussion of the results in the Results section would better fit into the discussion section.

For example: KLF4 is a famous transcription factor for sustaining the undifferentiated state of iPS cells, known as the “Yamanaka factor”. NES is a protein marker of neural stem cells and rarely expressed in differentiated neural cells. The upregulation of these genes suggest the possibility of induction of the appearance of undifferentiated neural cells by sevoflurane [21-24]. etc.) Pages 12, Lines 192-196; Pages 13, Lines 203-204; Pages 14, Lines 220-221; Pages 15, Lines 239-241; etc.

(4) Since gene expression in the hippocampus was the most-influenced in sevoflurane group based on your results, why not compare the transcriptome array data of the hippocampus of sleeping mice with sevoflurane exposure? Only a comparison was made with the transcriptome array data of the cerebral cortices of sleeping mice in this study.

(5) It is interesting but questionable that very short (3 hr) sevoflurane exposure upregulates KLF4. Furthermore, there may be still some doubt about whether KLF4 upregulated by sevoflurane exposure are really associated with the upregulation of angiogenesis and appearance of undifferentiated neural cells in whole brain. Also, the author did not evaluate protein expression changes for these genes, and only three of samples were used. Therefore, the evidence for the Conclusion is insufficient in the present results.

Reviewer #4: A well designed and interesting study investigating the effects of sevoflurane on gene expression in various regions in the brain. The results suggest that Klf4 dysregulation is responsible for promoting angiogenesis and for the appearance of undifferentiated neural cells.

While the authors state that the data is available through the DNA Data Bank Japan, I could not find the enrty. Perhaps it is private until publication? Please do ensure that this will be publicly available as this will be a valuable resource for the research community.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: No

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PLoS One. 2020 Dec 15;15(12):e0236771. doi: 10.1371/journal.pone.0236771.r002

Author response to Decision Letter 0

21 Oct 2020

Reviewer #1’s comment #1

As a control, sleeping mice were used. The relational is acceptable. However, many factors can affect the comparability between groups, including but not limited to sleeping length vs. 3h-exposure of sevoflurane; did you consider about physiological circadian rhythms between these groups of mice? So, the data between sevoflurane anesthesia and baseline is more reliable than the difference between anesthesia and sleeping.

Our response to Reviewer #1’s comment #1

We agree with this comment. As the reviewer pointed out, this experiment would be expected to yield different results for a variety of factors, including circadian rhythms, and a comparison of our anesthesia data with the sleep data in another study might contain a fragility. If a common factor was found in these data and considered noteworthy, we could have pursued it more deeply, but we did not engage deeply in this comparison because our results showed that the expression patterns were totally different. We would like to adopt this comparison as the data showing that the changes focusing on in this study are specific to anesthesia, and we revised the text in the Discussion section accordingly. However, the overall argument does not change without this comparison. Therefore, if the reviewers appreciate that this paper is better off without this data, please reiterate that, as we will be withdrawing this comparison data.

LINE 345-347

Discussion

[original]

The comparison of gene expressions in the brains of sleeping mice revealed that gene expression changes were specific to the brains exposed to sevoflurane.

[revised (red letters show the added descriptions)]

Reviewer #1’s comment #2

Only a small number of mice used in each group, so the signal to noise ratio may be not good to get a solid conclusion.

Our response to Reviewer #1’s comment #2

We appreciate your comment. As rightly pointed out, the number of samples is a limitation of this study. However, we concluded that increasing replicates did not significantly change the results because the the PCA plot showed high reproducibility between triplicate (S1 Fig B). In this regard, we added the description of the limitation as follows:

LINE 361-364

Discussion

[original]

As the limitation of this study, only three of samples were used.

[revised (red letters show the added descriptions)]

As a limitation of this study, only three of samples were used. However, we concluded that increasing replicates did not significantly change the results because of the high reproducibility between triplicates, supported by the PCA plot (S1 Fig B)

Reviewer #1’s comment #3

Single-cell sequencing is already common. The technique of RNA-seq is not state-of-art method for such comparisons. In introduction, there is no any description of already published studies about transcriptome after anesthesia, which is critical for relational of the study: what is already known and what is need to know?

Our response to Reviewer #1’s comment #3

We appreciate your comment. As mentioned, single-cell sequencing is indeed a cutting edge and reliable method, and we have implemented it in our lab in various ways in other studies. On the other hand, it requires costly and time-consuming experiments. This was an introductory study, and in order to obtain a complete picture of the effects on the brain under anesthesia, we prioritized the analysis of many sites with bulk RNA-seq. We believe that the present objective could be achieved with bulk RNA-seq. However, as stated by the reviewer, more insights may be obtained with single-cell RNA-seq. In particular, analyses that combine single-cell RNA-seq and location information, such as Slide-seq (Rodriques et al., 2019. Science), may be useful to elaborate this study. These points have been added in the Discussion section as follows.

LINE 352-358

Discussion

[original]

For precise understanding of the specific roles of KLF4 induced by sevoflurane, chromatin immunoprecipitation analysis of Klf4 and histone markers, such as H3K9me3 and H3K27Ac in each part of brain are needed. Nevertheless, our analysis results indicated the importance of KLF4 as a candidate regulator of the effects caused by sevoflurane inhalation.

[revised (red letters show the added descriptions)]

For a precise understanding of the specific role of KLF4 induced by sevoflurane, chromatin immunoprecipitation analysis of KLF4 and histone markers, such as H3K9me3 and H3K27ac in each part the of brain is needed. Furthermore, experimental methods that combine single-cell RNA-seq and location information such as Slide-seq may provide more useful information [33]. Nevertheless, our analysis results indicated the importance of KLF4 as a candidate regulator of the effects caused by sevoflurane inhalation.

Reference

[33] Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, et al. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019;363(6434):1463-7.

As for our response to the second part of the comment. There have been several reports on transcriptome analysis of post-anesthesia brain samples, but there have been no reports of simultaneous RNA-seq on multiple sites to see the whole picture, as done in our report. In the introduction, we cited such studies and described the differences between those and ours as follows.

LINE 63-69

Introduction

[original]

Furthermore, although many reports have evaluated effects of sevoflurane, the analyses were focused only on limited parts of the brain; hence, comparison of the effects of sevoflurane between multiple anatomical sites at the same time is difficult.

[revised (red letters show the revised descriptions)]

Furthermore, although some reports have evaluated the effects of sevoflurane using transcriptome analysis, these studies focused only on limited parts of the brain. Hayase et al. reported that the increase in dopamine activity in the hippocampus due to inhalation of sevoflurane might be related to postoperative nausea, and Mori et al. reported circadian gene variations in the suprachiasmatic nucleus after sevoflurane inhalation [10,11]. However, we thought that by comparing many regions at once and extracting genes that might play common role in all regions, we could focus on genes that are important with regard to the whole brain.

Reference

[10] Hayase T, Tachibana S, Yamakage M. Effect of sevoflurane anesthesia on the comprehensive mRNA expression profile of the mouse hippocampus. Med Gas Res. 2016;6(2):70-6.

[11] Mori K, Iijima N, Higo S, Aikawa S, Matsuo I, Takumi K, et al. Epigenetic suppression of mouse Per2 expression in the suprachiasmatic nucleus by the inhalational anesthetic, sevoflurane. PLoS One. 2014;9(1):e87319.

Reviewer #1’s comment #4

The last and the most significant concern is that: the authors declared that KLF4 is a specific responsible transcription factor that potentially promotes angiogenesis and induces the appearance of undifferentiated neural cells. All these conclusions are completely based on data analysis. Without any actual measurement of angiogenesis and neural development after sevoflurane exposure, and did not design any intervention aiming these transcription factor cannot conclude such statements. Overall, the conclusion of the present manuscript is much over-interpreted, which need substantial revision. There is no solid causality between the transcription factor and sevoflurane exposure, as well as the proposed outcomes after anesthesia.

Our response to Reviewer #1’s comment #4

We appreciate and totally agree with this comment. It was difficult to determine whether the upregulation of Klf4 by sevoflurane regulated angiogenesis or the appearance of undifferentiated neural cells, only from our RNA-seq analysis. We intended to claim that multiple analyses based on RNA-seq of the brain exposed to sevoflurane suggested some important roles of Klf4. It is worth noting that the possibility of upregulation of angiogenesis supported the report by Jiang et al. as mentioned in the discussion. We speculated that these results may be relevant to post-anesthetic events, such as POD, POCD, and emergence agitation, but further study is needed for its validation. Based on these considerations, we changed the discussion and conclusion as follows:

LINE 49-50

Abstract

[original]

Klf4 was upregulated by sevoflurane inhalation in whole brain. KLF4 might promote angiogenesis and cause the appearance of undifferentiated neural cells by transcriptional regulation. The roles of KLF4 might be key to elucidating the mechanisms of sevoflurane induced functional modification in the brain.

[revised]

Klf4 was upregulated by sevoflurane inhalation in the mouse brain. The roles of KLF4 might be key to elucidating the mechanisms of sevoflurane induced functional modification in the brain.

LINE 76-79

Introduction

[original]

Herein, we report our success in identifying KLF4 as a specific responsible transcription factor that potentially promotes angiogenesis and induces the appearance of undifferentiated neural cells.

[revised (red letters show the revised descriptions)]

Herein, we report sevoflurane-induced gene expression change patterns in the mouse brain and that KLF4 emerged as a specific transcription factor that potentially promoted angiogenesis and induced the appearance of undifferentiated neural cells.

Reviewer #1’s minor comment #1

The short title is not correct;

Our response to Reviewer #1’s minor comment #1

We appreciate your comments. In the original version, the book title and the short title were the same. We have given it the following short title.

[revised]

Short title: Effects of sevoflurane on brain

Reviewer #1’s minor comment #2

Why the mice exposed to sevoflurane with 3 hours? Is there any exposure-time dependent effect?

Our response to Reviewer #1’s minor comment #2

We appreciate your comment. Anesthetizing mice for 3h is a common method used in anesthesia experiments, and we followed this method. We also took into account the fact that general anesthesia for 3h is very common in clinical practice. We agree that it is interesting to compare the variable time duration of anesthesia, but we put more weightage on the comparison between multiple parts of the brain under anesthesia in this report.

Reviewer #1’s minor comment #3

In results part, there are too much re-descriptions like methods.

Our response to Reviewer #1’s minor comment #3

We appreciate this comment. There were certainly many re-descriptions in our original version. We deleted the sentences indicated by the reviewer from the result part and extended the discussion part as follows.

LINE 204-205

Results

[revised (red letters show the revised description)]

Sevoflurane inhalation upregulated transcription factors such as Klf4 in all sampled parts (Fig. 2B). The expression level of Klf4 was >2.5 times higher than that in the control mice. Furthermore…

LINE 210-212

Results

[revised]

The transcription factors KLF4 and KLF2, as well as EDN1, CCN1, and ADAMTS1, were annotated to the GO terms “angiogenesis” and “response to wounding” (S3 Table).

LINE 225-228

Results

[revised]

Moreover, the heatmap showed that sevoflurane inhalation downregulated the genes annotated as “head development” in all sampled parts of brain, and those annotated as “axon development” or “synapse organization” in several parts (Fig. 3D and S4 Table).

LINE 244-246

Results

[revised]

Moreover, by comparing genes upregulated and downregulated in all parts of the brain exposed to sevoflurane, we found that all the genes except Edn1 were completely expressed differently (Fig.4C and D).

Now that Klf4 is upregulated whole brain, the expression of Klf4 in protein levels need to be added through western blot or immunohistochemistry in four brain regions which will confirm your conclusion.

Our response to Reviewer #2’s comment #1

We appreciate the reviewer’s comment. First, we performed immunohistochemistry for the cerebral cortex and hippocampus of mice exposed to sevoflurane. As a result, we confirmed distinct upregulation of Klf4 in the nucleus of cells in the cerebral cortex. On the other hand, the basal expression of Klf4 was high in the hippocampus, and we could not observe the upregulation of Klf4 in hippocampus with immunohistochemistry. Therefore, we performed western blotting for the hippocampus, and it showed that the expression of Klf4 was upregulated to some extent. These data are submitted as S2 Fig A and B. From these results, we concluded that sevoflurane inhalation caused the upregulation of Klf4. We have revised sentences as follows:

LINE 274-283

Results

[revised (red letters show the added descriptions in the revised version)]

Finally, in the hippocampus, the target genes of 14 transcription factors were downregulated (Fig.5H). These results indicate that Klf4 plays some important roles in gene expression in brains exposed to sevoflurane. To validate the upregulation of Klf4, we performed immunohistochemical analysis for the cerebral cortex and hippocampus. As a result, we observed that the expression of Klf4 was strongly upregulated in the nucleus of cells in the cerebral cortex of mice exposed to sevoflurane. On the other hand, nucleus in neural cells of hippocampus in both control mice and mice exposed to sevoflurane showed high expression of Klf4, and no significant changes were observed in immunohistochemical analysis (S2 Fig A). Based on these results, we performed western blotting analysis to validate the upregulation of Klf4 in the hippocampus, showing a certain upregulation of Klf4 (S2 Fig B).

LINE 373-375

Discussion

[original]

For further understanding, proteomic analysis of brains with sevoflurane inhalation and pathological assessment of more samples and oxygen saturation assessment in mice are needed. Nevertheless, our strategies should be better choices for grabbing the whole image of brain activities under an anesthetized condition.

[revised (red letters show the revised description: the description about lack of pathology was removed)]

Oxygen saturation assessment in mice may provide more reliable results. Nevertheless, our strategy should include better choices for obtaining the whole image of brain activities under anesthetized condition.

Reviewer #2’s comment #2

Anesthetics including sevoflurane can cause POCD, especially in elderly patients. Why did the authors use 8-week-old mice instead of aged mice?

Our response to Reviewer #2’s comment #2

We appreciate your comment. When we focused on the pathology of peri-operative events such as POCD, the use of elderly mice would have been more suitable. However, temporary confusion such as emergence agitation is observed more frequently in young patients. Furthermore, the effects of volatile anesthesia on the developing brain is receiving attention these days. Based on these perspectives, we adopted eight weeks old mice, which is common for anesthetic experiments, and tried to obtain the whole image of the influences of sevoflurane inhalation. The emphasis of the relativity between sevoflurane inhalation and POCD or POD may have led to misunderstandings of our intention. Therefore, we have corrected as following:

LINE 57-60

Introduction

[original]

Sevoflurane is a most frequently used volatile anaesthetics in general anaesthesia. Some reports discussed the peri-operative adverse effects of sevoflurane such as post-operative delirium and cognitive disorders, although whether anesthetics themselves cause peri-operative adverse effects is still controversial [1-3].

[revised (red letters show the revised descriptions)]

Sevoflurane is the most frequently used volatile anesthetic in general anaesthesia. Some reports discussed the perioperative adverse effects of sevoflurane, such as emergence agitation, postoperative delirium, and cognitive disorders, although whether anesthetics themselves cause perioperative adverse effects is still controversial [1-3].

Reviewer #2’s comment #3

In fact, only four brain regions were used to analyze the expression of different genes, however, the conclusion was the expression in whole brain. These four brain regions do not represent the whole brain. What about the brainstem and olfactory bulb?

Our response to Reviewer #2’s comment #3

We appreciate with the reviewer’s comment. We also think that the expression “whole brain” is over-interpretation. Therefore, we have changed the phrases of “whole brain” to “all sampled regions”

Reviewer #2’s comment #4

About the treatment of control group mice, why did the control group mice use normal air instead of 40%O2?

Our response to Reviewer #2’s comment #4

We appreciated with the reviewer’s comment. The O2 concentration in the anesthetized group in our experiment was 40%, which seemed to be a common condition for both animal experiments and clinical practices. We also took into account that Ohe et al. performed in the same condition (2.5%sev/40%O2), and murine O2 saturation was stable in 95-100% (Ohe et al, Neuroscience Letters 2011). Exposure to the same concentration of O2 for control or anesthetized mice may result in lower O2 blood concentration in anesthetized mice, since the respiration of anesthetized mice will be suppressed. Based on this concern, controlling O2 concentration while monitoring murine O2 saturation might be a better resolution. Therefore, we changed the description of the limitation for O2 saturation as follows:

LINE 367-373

Discussion

[original]

None of the genes related to hypoxic reaction, including Hif1a and Arnt, were detected in our analyses in gene expression changes, supporting the exclusion of the possibility of hypoxia in our experimental condition (S1 Table).

[revised (red letters show the added descriptions)]

None of the genes related to hypoxic reaction, including Hif1a and Arnt, were detected in our analyses of gene expression changes, supporting the exclusion of the possibility of hypoxia in our experimental conditions (S1 Table). Conversely, oxygen saturation might have been higher in the anesthetized group than in the control group, which was allowed to spend time in room air, and since we did not measure oxygen saturation, it is possible that subtle differences in oxygen saturation existed and that this might have affected the results. Oxygen saturation assessment in mice may provide more reliable results.

Reviewer #2’s comment #5

5. Delete 138 lines of redundant “analysis”

Our response to Reviewer #2’s comment #5

As the reviewer pointed out, it was our mistake. We revised it.

Reviewer #3’s comment #1

The sample size of this study (n=6; sevo group, n=3 vs ctl group, n=3) is too small to draw strong conclusions from the current data.

Our response to Reviewer #3’s comment #1

We appreciate this comment. Another reviewer also pointed out the same thing. As the reviewers pointed out, the number of samples is a limitation of this study. However, we concluded that increasing replicates did not significantly change the results because of the reproducibility of the PCA plot (Fig. S1B) between the samples. In this regard, we have added the description of the limitation as follows:

LINE 361-364

Discussion

[original]

As the limitation of this study, only three of samples were used.

[revised (red letters show the added descriptions)]

Reviewer #3’s comment #2

The transcriptome array data of sleeping mice used in this study from existing database. Sleeping mice should be set as a group in your study, if possible.

Our response to Reviewer #3’s comment #2

Another reviewer also has noted the same thing, and we agree with this comment. This experiment was expected to yield different results for a variety of factors, and a comparison of our anesthesia data with the sleep data in another study might contain a fragility. It would have been best if we could do the experiment ourselves under the right conditions, but that sleep experiment seemed to require certain specialized skills and we concluded it would be difficult to obtain accurate data on our own. If a common factor was found in these data and considered noteworthy, we could have pursued it in more depth, but we did not get too deep into this comparison, because our results showed that the genes operated in a rather different pattern altogether. We would like to adopt this comparison as the data showing that the changes we focused on in this study were specific to anesthesia, and we revised the text in the discussion accordingly. However, the overall argument does not change without this comparison. Therefore, if the reviewers appreciate that this paper is better off without this data, please reiterate that, as we will be withdrawing this comparison data.

LINE 345-347

Discussion

[original]

The comparison of gene expressions in the brains of sleeping mice revealed that gene expression changes were specific to the brains exposed to sevoflurane.

[revised]

Reviewer #3’s comment #3

Problems on scientific writing: discussion of the results in the Results section would better fit into the discussion section. For example: KLF4 is a famous transcription factor for sustaining the undifferentiated state of iPS cells, known as the “Yamanaka factor”. NES is a protein marker of neural stem cells and rarely expressed in differentiated neural cells. The upregulation of these genes suggest the possibility of induction of the appearance of undifferentiated neural cells by sevoflurane [21-24]. etc.) Pages 12, Lines 192-196; Pages 13, Lines 203-204; Pages 14, Lines 220-221; Pages 15, Lines 239-241; etc.

Our response to Reviewer #3’s comment #3

We appreciate the reviewer’s comment. Another reviewer also had noted the same thing, with the comment that there is a lot of re-description. There was certainly a lot of re-descriptions both in both the Results and Discussion sections. We have revised some descriptions in the results section that have the same meaning in the discussion section as follows (the following lists of revisions are the same lists in response to another reviewer):

LINE 204-205

Results

[revised (red letters show the revised description)]

Sevoflurane inhalation upregulated transcription factors such as Klf4 in all sampled parts (Fig. 2B). The expression level of Klf4 was >2.5 times higher than that in the control mice. Furthermore…

LINE 210-212

Results

[revised]

The transcription factors KLF4 and KLF2, as well as EDN1, CCN1, and ADAMTS1, were annotated to the GO terms “angiogenesis” and “response to wounding” (S3 Table).

LINE 225-228

Results

[revised]

LINE 244-246

Results

[revised]

Reviewer #3’s comment #4

Since gene expression in the hippocampus was the most-influenced in sevoflurane group based on your results, why not compare the transcriptome array data of the hippocampus of sleeping mice with sevoflurane exposure? Only a comparison was made with the transcriptome array data of the cerebral cortices of sleeping mice in this study.

Our response for Reviewer #3’s comment #4

We appreciate your comment. We also think it would be interesting to compare with the transcriptome array data of the hippocampus of sleeping mice. However, we could not find the depository data of hippocampus for comparison under the same conditions. The sleep experiments need expertized skills, and it was difficult to perform the experiment at the same quality by ourselves.

Reviewer #3’s comment #5

It is interesting but questionable that very short (3 hr) sevoflurane exposure upregulates KLF4. Furthermore, there may be still some doubt about whether KLF4 upregulated by sevoflurane exposure are really associated with the upregulation of angiogenesis and appearance of undifferentiated neural cells in whole brain. Also, the author did not evaluate protein expression changes for these genes, and only three of samples were used. Therefore, the evidence for the Conclusion is insufficient in the present results.

Our response for Reviewer #3’s comment #5

We appreciate the reviewer’s comment. We were also concerned whether the exposure to sevoflurane for three h was too short to cause changes in protein expression. Another reviewer was also concerned about protein level variation. Therefore, we performed immunohistochemistry of the cerebral cortex and hippocampus of mice exposed to sevoflurane. As a result, we confirmed distinct upregulation of Klf4 in the nucleus of cells in the cerebral cortex. On the other hand, the basal expression of Klf4 was high in the hippocampus, and we could not observe the upregulation of Klf4 in the hippocampus with immunohistochemistry. Therefore, we performed western blotting for the hippocampus, and it showed that the expression of Klf4 was upregulated to some extent. These data are submitted as S2 Fig A and B. From these results, we concluded that sevoflurane inhalation caused the upregulation of Klf4. We did not evaluate changes in protein expression of its downstream genes, but Klf4 usually functioned as a transcription regulator, and changes in candidate downstream genes at the RNA level might be the supporting data of transcription regulatory roles of Klf4 with sevoflurane exposure. Based on these considerations, we changed the descriptions as follows:

LINE 274-283

Results

[revised (red letters show the added descriptions in revised version)]

Reviewer #4’s comment

Our response for Reviewer #4’s comment

We appreciate your comment. We intend to disclose the RNA-Seq data and publish it in the DNA Data Bank Japan after acceptance. Please let us know if the deposit data should be published before the acceptance of this paper.

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file.^{(39.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0236771.r003

Decision Letter 1

Wataru Nishimura

13 Nov 2020

Transcriptome analysis of sevoflurane exposure effects at the different brain regions

PONE-D-20-21488R1

Dear Dr. Asahara,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Reviewer #2: All comments have been addressed

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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6. Review Comments to the Author

Reviewer #1: Thank you for the revision and additional experiments. Generally, the revisions have almost addressed my comments. I only have one suggestion, as mentioned by authors themselves, the comparison between sevoflurane anesthesia and sleep do not make a big sense; so, please consider to remove such data or move to supplementary data.

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PLoS One. doi: 10.1371/journal.pone.0236771.r004

Acceptance letter

Wataru Nishimura

23 Nov 2020

PONE-D-20-21488R1

Transcriptome analysis of sevoflurane exposure effects at the different brain regions

Dear Dr. Asahara:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. RNA-seq analysis for anesthetized brain.

(A)The distribution of log₂ ((count per million) +4) after normalization. (B)PCA-plot for RNA-seq data.

(TIF)

Click here for additional data file.^{(3.8MB, tif)}

S2 Fig. Comparison of Differently Expressed Genes (DEGs) between the brains of the anesthetized and sleeping mice.

(TIF)

Click here for additional data file.^{(2.3MB, tif)}

S3 Fig. Immunohistochemistry and western blotting for hippocampus of brains exposed to sevoflurane.

Representative image of immunohistochemical analysis of KLF4 for cerebral cortex and hippocampus of mice exposed to sevoflurane. Western blotting for hippocampus of brains exposed to sevoflurane.

(TIF)

Click here for additional data file.^{(16.5MB, tif)}

S1 Table. Gene expression data for all the genes in all parts of the brain of mice that inhaled sevoflurane.

Log₂ (read counts per million +4) of all the genes of all parts of the brain from the RNAseq analysis data by iDEP91 are shown.

(XLSX)

Click here for additional data file.^{(2.9MB, xlsx)}

S2 Table. Gene lists of differently expressed genes in each part of the brain.

The gene names and expression fold change data (sevoflurane group vs control group) of the hippocampus, hypothalamus, striatum, and medial prefrontal cortex are shown.

(XLSX)

Click here for additional data file.^{(44KB, xlsx)}

S3 Table. Lists of genes and gene ontology terms of upregulated differently expressed genes.

Metascape analysis was performed for upregulated differently expressed genes. The gene ontology (GO) terms, their p values and genes annotated to each GO terms are shown in the table.

(XLSX)

Click here for additional data file.^{(11.3KB, xlsx)}

S4 Table. Genes and gene ontology term lists of downregulated differently expressed genes.

A Metascape analysis was performed for downregulated differently expressed genes. The gene ontology (GO) terms, their p values and genes annotated to each GO terms are shown.

(XLSX)

Click here for additional data file.^{(11.5KB, xlsx)}

S5 Table. Expression and fold change data for each gene from the transcriptome array data of the cortical cortices of sleeping mice.

The gene names, transcriptome array data and expression fold change data (sleeping group vs control group) from GSE69079 are shown.

(XLSX)

Click here for additional data file.^{(972.1KB, xlsx)}

S6 Table. Lists of the differently expressed genes in the cerebral cortices of sleeping mice.

The gene names and each expression fold change data (sleeping group vs control group) for the upregulated and downregulated genes are shown.

(XLSX)

Click here for additional data file.^{(116.5KB, xlsx)}

S7 Table. Comparison of the gene expression fold changes of the common differently expressed genes between mice that inhaled sevoflurane and sleeping mice.

The gene names and each expression fold change data for the common upregulated and downregulated genes (sevoflurane group vs control group and sleeping group vs control group) are shown.

(XLSX)

Click here for additional data file.^{(11KB, xlsx)}

S8 Table. Lists of the transcription factors and their T-scores from the wPGSA for each part of brain.

(XLSX)

Click here for additional data file.^{(23KB, xlsx)}

S9 Table. List of the predicted binding motifs of Klf4 in the upstream sequences of the differently expressed genes.

The predicted binding motifs of KLF4 for the 1000-bp upstream sequences of the differently expressed genes were identified using JASPAR.

(XLSX)

Click here for additional data file.^{(16.5KB, xlsx)}

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file.^{(39.8KB, docx)}

Data Availability Statement

The data are available from DDBJ with DRA accession number DRA010292.

[pone.0236771.ref001] 1.Ansaloni L, Catena F, Chattat R, Fortuna D, Franceschi C, Mascitti P, et al. Risk factors and incidence of postoperative delirium in elderly patients after elective and emergency surgery. Br J Surg. 2010;97(2):273–80. Epub 2010/01/14. 10.1002/bjs.6843 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref002] 2.Neufeld KJ, Leoutsakos JM, Sieber FE, Wanamaker BL, Gibson Chambers JJ, Rao V, et al. Outcomes of early delirium diagnosis after general anesthesia in the elderly. Anesth Analg. 2013;117(2):471–8. Epub 2013/06/13. 10.1213/ANE.0b013e3182973650 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref003] 3.Rudolph JL, Marcantonio ER. Review articles: postoperative delirium: acute change with long-term implications. Anesth Analg. 2011;112(5):1202–11. Epub 2011/04/09. 10.1213/ANE.0b013e3182147f6d [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref004] 4.Wu J, Harata N, Akaike N. Potentiation by sevoflurane of the gamma-aminobutyric acid-induced chloride current in acutely dissociated CA1 pyramidal neurones from rat hippocampus. Br J Pharmacol. 1996;119(5):1013–21. 10.1111/j.1476-5381.1996.tb15772.x WOS:A1996VQ13600033. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref005] 5.Jenkins A, Franks NP, Lieb WR. Effects of temperature and volatile anesthetics on GABA(A) receptors. Anesthesiology. 1999;90(2):484–91. 10.1097/00000542-199902000-00024 WOS:000078326100023. [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref006] 6.Stucke AG, Stuth EAE, Tonkovic-Capin V, Tonkovic-Capin M, Hopp FA, Kampine JP, et al. Effects of halothane and sevoflurane on inhibitory neurotransmission to medullary expiratory neurons in a decerebrate dog model. Anesthesiology. 2002;96(4):955–62. 10.1097/00000542-200204000-00025 WOS:000174716900024. [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref007] 7.Sebel LE, Richardson JE, Singh SP, Bell SV, Jenkins A. Additive effects of sevoflurane and propofol on gamma-aminobutyric acid receptor function. Anesthesiology. 2006;104(6):1176–83. Epub 2006/05/30. 10.1097/00000542-200606000-00012 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref008] 8.Zhou C, Liang P, Liu J, Ke BW, Wang XJ, Li FS, et al. HCN1 Channels Contribute to the Effects of Amnesia and Hypnosis but not Immobility of Volatile Anesthetics. Anesthesia and Analgesia. 2015;121(3):661–6. 10.1213/ANE.0000000000000830 WOS:000360359200003. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref009] 9.Plourde G, Chartrand D, Fiset P, Font S, Backman SB. Antagonism of sevoflurane anaesthesia by physostigmine: effects on the auditory steady-state response and bispectral index. Br J Anaesth. 2003;91(4):583–U1. 10.1093/bja/aeg209 WOS:000185596500020. [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref010] 10.Hayase T, Tachibana S, Yamakage M. Effect of sevoflurane anesthesia on the comprehensive mRNA expression profile of the mouse hippocampus. Med Gas Res. 2016;6(2):70–6. Epub 2016/11/22. 10.4103/2045-9912.184715 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref011] 11.Mori K, Iijima N, Higo S, Aikawa S, Matsuo I, Takumi K, et al. Epigenetic suppression of mouse Per2 expression in the suprachiasmatic nucleus by the inhalational anesthetic, sevoflurane. PLoS One. 2014;9(1):e87319 Epub 2014/02/06. 10.1371/journal.pone.0087319 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref012] 12.Jiang-Xie LF, Yin L, Zhao S, Prevosto V, Han BX, Dzirasa K, et al. A Common Neuroendocrine Substrate for Diverse General Anesthetics and Sleep. Neuron. 2019;102(5):1053–65 e4. Epub 2019/04/23. 10.1016/j.neuron.2019.03.033 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref013] 13.Ando N, Sugasawa Y, Inoue R, Aosaki T, Miura M, Nishimura K. Effects of the volatile anesthetic sevoflurane on tonic GABA currents in the mouse striatum during postnatal development. Eur J Neurosci. 2014;40(8):3147–57. Epub 2014/08/21. 10.1111/ejn.12691 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref014] 14.Liang P, Li F, Liu J, Liao D, Huang H, Zhou C. Sevoflurane activates hippocampal CA3 kainate receptors (Gluk2) to induce hyperactivity during induction and recovery in a mouse model. Br J Anaesth. 2017;119(5):1047–54. Epub 2017/10/06. 10.1093/bja/aex043 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref015] 15.Chung W, Ryu MJ, Heo JY, Lee S, Yoon S, Park H, et al. Sevoflurane Exposure during the Critical Period Affects Synaptic Transmission and Mitochondrial Respiration but Not Long-term Behavior in Mice. Anesthesiology. 2017;126(2):288–99. Epub 2016/12/07. 10.1097/ALN.0000000000001470 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref016] 16.Ishikawa C, Li H, Ogura R, Yoshimura Y, Kudo T, Shirakawa M, et al. Effects of gravity changes on gene expression of BDNF and serotonin receptors in the mouse brain. PLoS One. 2017;12(6):e0177833 Epub 2017/06/08. 10.1371/journal.pone.0177833 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref017] 17.Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15–21. Epub 2012/10/30. 10.1093/bioinformatics/bts635 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref018] 18.Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323 Epub 2011/08/06. 10.1186/1471-2105-12-323 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref019] 19.Ge SX, Son EW, Yao R. iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data. BMC Bioinformatics. 2018;19(1):534 Epub 2018/12/21. 10.1186/s12859-018-2486-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref020] 20.Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523 Epub 2019/04/05. 10.1038/s41467-019-09234-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref021] 21.Bellesi M, de Vivo L, Tononi G, Cirelli C. Effects of sleep and wake on astrocytes: clues from molecular and ultrastructural studies. BMC Biol. 2015;13:66 Epub 2015/08/26. 10.1186/s12915-015-0176-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref022] 22.Kawakami E, Nakaoka S, Ohta T, Kitano H. Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data. Nucleic Acids Res. 2016;44(11):5010–21. Epub 2016/05/02. 10.1093/nar/gkw355 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref023] 23.Ghaleb AM, Yang VW. Kruppel-like factor 4 (KLF4): What we currently know. Gene. 2017;611:27–37. Epub 2017/02/27. 10.1016/j.gene.2017.02.025 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref024] 24.Takahashi K, Tanabe K, Ohnuki M, Narita M, Ichisaka T, Tomoda K, et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131(5):861–72. Epub 2007/11/24. 10.1016/j.cell.2007.11.019 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref025] 25.Jiang J, Chan YS, Loh YH, Cai J, Tong GQ, Lim CA, et al. A core Klf circuitry regulates self-renewal of embryonic stem cells. Nat Cell Biol. 2008;10(3):353–60. Epub 2008/02/12. 10.1038/ncb1698 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref026] 26.Kaisti KK, Metsahonkala L, Teras M, Oikonen V, Aalto S, Jaaskelainen S, et al. Effects of surgical levels of propofol and sevoflurane anesthesia on cerebral blood flow in healthy subjects studied with positron emission tomography. Anesthesiology. 2002;96(6):1358–70. Epub 2002/08/10. 10.1097/00000542-200206000-00015 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref027] 27.Acharya NK, Goldwaser EL, Forsberg MM, Godsey GA, Johnson CA, Sarkar A, et al. Sevoflurane and Isoflurane induce structural changes in brain vascular endothelial cells and increase blood-brain barrier permeability: Possible link to postoperative delirium and cognitive decline. Brain Res. 2015;1620:29–41. Epub 2015/05/12. 10.1016/j.brainres.2015.04.054 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref028] 28.Geiman DE, Ton-That H, Johnson JM, Yang VW. Transactivation and growth suppression by the gut-enriched Kruppel-like factor (Kruppel-like factor 4) are dependent on acidic amino acid residues and protein-protein interaction. Nucleic Acids Res. 2000;28(5):1106–13. Epub 2000/02/10. 10.1093/nar/28.5.1106 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref029] 29.Evans PM, Zhang W, Chen X, Yang J, Bhakat KK, Liu C. Kruppel-like factor 4 is acetylated by p300 and regulates gene transcription via modulation of histone acetylation. J Biol Chem. 2007;282(47):33994–4002. Epub 2007/10/03. 10.1074/jbc.M701847200 . [DOI] [PubMed] [Google Scholar]

[pone.0236771.ref030] 30.Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, et al. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019;363(6434):1463–7. Epub 2019/03/30. 10.1126/science.aaw1219 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236771.ref031] 31.Fukuda M, Ando N, Sugasawa Y, Inoue R, Nakauchi S, Miura M, et al. Volatile anesthetic sevoflurane pretreatment alleviates hypoxia-induced potentiation of excitatory inputs to striatal medium spiny neurons of mice. Eur J Neurosci. 2019;50(9):3520–30. Epub 2019/07/25. 10.1111/ejn.14524 . [DOI] [PubMed] [Google Scholar]

PERMALINK

Transcriptome analysis of sevoflurane exposure effects at the different brain regions

Hiroto Yamamoto

Yutaro Uchida

Tomoki Chiba

Ryota Kurimoto

Takahide Matsushima

Maiko Inotsume

Chihiro Ishikawa

Haiyan Li

Takashi Shiga

Masafumi Muratani

Tokujiro Uchida

Hiroshi Asahara

Roles

Abstract

Backgrounds

Methods

Results

Conclusions

Introduction

Materials and methods

Approval for the animal experiments

Experimental conditions and preparation of brain samples

RNA extraction from brain tissue sections and RNAseq analysis

Mapping FASTQ data and calculating gene expressions

Extracting DEGs on iDEP.91

Sequencing data

Gene ontology term enrich analysis using Metascape

Extraction of DEGs from sleeping mice

Weighted Parametric Gene Set Analysis (wPGSA) of DEGs in the brains of mice that inhaled sevoflurane

Histological and immunohistochemical analysis

Western blotting analysis for brains exposed to sevoflurane

Detection of the consensus-binding motifs of Klf4 in the upstream sequences of DEGs

Statistical analyses

Results

Genome-wide transcriptome analysis for the brains of mice that inhaled sevoflurane

Fig 1. RNA-seq analysis for brains exposed to sevoflurane.

Fig 2. Analysis of the upregulated Differently Expressed Genes (DEGs) in each part of the brain.

Fig 3. Analysis of the downregulated differently expressed genes for each part of the brain.

Identification of KLF4 as a candidate of key transcriptional regulator in brain exposed to sevoflurane

Fig 4. Estimation and comparison of the relative activities of the transcriptional factors.

Fig 5. Comparison of the activities of the transcription factors between the brains of the anesthetized and sleeping mice.

Discussion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Wataru Nishimura

Roles

Author response to Decision Letter 0

Decision Letter 1

Wataru Nishimura

Roles

Acceptance letter

Wataru Nishimura

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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