Physiological neuronal activity, including exposure of mice to learning behaviors, also cause the formation of DSBs, yet the distribution of these breaks and their relation to brain function remains unclear. Here, following contextual fear conditioning (CFC) in mice, we profiled the locations of DSBs genome-wide in the medial prefrontal cortex and hippocampus using γH2AX ChIP-Seq. Remarkably, we found that DSB formation is widespread in the brain compared to cultured primary neurons and they are predominately involved in synaptic processes. We observed increased DNA breaks at genes induced by CFC in neuronal and non-neuronal nuclei. Activity-regulated and proteostasis-related transcription factors appear to govern some of these gene expression changes across cell types. Finally, we find that glia but not neurons have a robust transcriptional response to glucocorticoids, and many of these genes are sites of DSBs. Our results indicate that learning behaviors cause widespread DSB formation in the brain that are associated with experience-driven transcriptional changes across both neuronal and glial cells.Neuronal activity generates DNA double-strand breaks (DSBs) at specific loci  Neuronal activity has been reported to generate DSBs –6. This One source of genomic stress in the brain is its high transcriptional output; neurons respond in real-time to environmental changes and this activity necessitates continual modulation of transcription . We madein vivo landscape of DSBs in the brain during learning and how they correspond with gene expression changes occurring in neurons and glia. We find fear learning paradigm-induced genes are overrepresented amongst those genes with the highest levels of DSBs in the medial prefrontal cortex and hippocampus. These genes are downstream of pathways that are shared in part by neurons and non-neurons, and in other cases unique to each group of cells. Surprisingly, we find potential glia-enriched DSB hotspots at genes that have a robust transcriptional response to glucocorticoid receptor signaling in glia.We set out to understand the in vitro and in vivo . Ot. OtPolr3We found that glia are likely to play an underappreciated role in the response to stress in the nervous system and this corresponds with DSBs, a relation between stress hormones and DNA damage that was also observed in mouse fibroblasts . Our resWe find that stress likely impacts the physiology of glia through modulation of their transcriptomes, impacting numerous cellular processes. These changes may explain how stress has been shown to impact glial morphology and function, including after CFC , 83–91. Our observations suggest that the glial contribution to the deleterious effects of stress hormones may be stronger than previously appreciated. This may include cases of steroid dementia, wherein cognitive alterations occur in response to high levels of glucocorticoids , as well as disorders characterized by anxiety and depression , 94. IntAll mouse work was approved by the Committee for Animal Care of the Division of Comparative Medicine at Massachusetts Institute of Technology (protocol number 0618-044-21).Sixty-eight 4-month-old C57BL6/J male mice were purchased from Jackson Laboratory (stock number 000664). Mice were group housed with a 12-hour light and dark cycle with access to food and water ad libitum. To minimize variability, mice were single housed for one week before experimental manipulation.For contextual fear conditioning, mice were habituated in the context for 3 minutes prior to administration of 30 second-spaced dual 0.8 mA foot shocks applied by the grid floor. The animals remained in the chamber for an additional minute and were placed back in their home-cage. Ten or thirty minutes after placement in the context, mice were euthanized by cervical dislocation. For Mifepristone (Sigma-Aldrich) pretreatment, mifepristone was dissolved in 1% v/v Tween 80 in saline. Mice were treated IP with either 50mg/Kg mifepristone or vehicle immediately before contextual fear conditioning, followed by euthanasia 30 minutes later. For corticosterone treatment, corticosterone:HBC complex (Sigma-Aldrich) was dissolved in saline and administered at 2mg/Kg IP, or an equal volume of saline for control, followed by euthanasia 30 minutes later.Treatment and control groups were euthanized in a staggered manner to minimize circadian differences between groups. Naive mice remained in their home cages prior to euthanasia. For tissue collection, the animals were sacrificed by cervical dislocation and the brains were rapidly extracted and submerged in ice-cold PBS. To isolate the medial prefrontal cortex and hippocampus, the brain was placed ventral side up in an Alto coronal 0.5mm mouse matrix resting on ice. Three coronal cuts were administered with razor blades, one separating the PFC from the olfactory bulb, one placed approximately around the optic chiasm to separate the PFC from the hippocampus, and one placed within the cerebellum for stability. The pieces containing the mPFC and hippocampi were placed in an ice-cold PBS-filled dish for isolation with a dissection microscope. To isolate the mPFC, a horizontal cut was administered just above the anterior olfactory nucleus with a razor blade. Two longitudinal cuts were made medial to the anterior forceps of the corpus collosum. Whole hippocampi were unfurled and isolated from within the cortex. White matter and either meninges, or choroid plexus , were reFor mixed glial cultures, four Swiss-Webster timed-pregnant mice were ordered from Charles River (stock number 024). Cortical glia from pups younger than postnatal day 6 were cultured essentially as described . BrieflyTissue was dissociated with a motorized pestle (Argos Technologies) in 0.3–0.5mL ice cold PBS treated with protease and phosphatase inhibitors . For RNA isolation, RNAse inhibitors were added to all buffers (RiboLock (Thermo Scientific) or SUPERaseIn (Invitrogen); 1:100 for homogenization, 1:1000 for buffers with BSA, and 1:10,000 for other buffers). Dissociated brain tissue was fixed in 10 mL of 1% Methanol-free Paraformaldehyde  for 10 minutes before quenching with 0.25M Tris-HCl pH 8 (a more effective quencher than glycine ). HomogeExtraction of mRNA from whole tissue and cultured mixed glia was performed with the RNeasy mini kit (Qiagen). For brain tissue, homogenization was performed by aspirating the tissue in RLT Plus buffer through a 20-gauge needle and syringe approximately 10 times until homogenized. For cell culture, the media was aspirated before RLT Plus was added and distributed with rocking. Purification proceeded as described by the manufacturer. Isolated RNA was quantified on a NanoDrop spectrophotometer (Thermo Fisher Scientific) and 1ug RNA was used to make cDNA with the OligodT RNA to cDNA EcoDry Premix (Takara) according to the manufacturer’s instructions, before proceeding to qPCR analysis.Hprt using the ΔΔCT method. For ChIP, normalization was against Input. Primer sequences can be found in For qPCR analysis, diluted cDNA or genomic DNA was subjected to quantitative real-time PCR in triplicate with the indicated primers using Ssofast EvaGreen Supermix (Bio-Rad) in a CFX Connect Real-Time System (Bio-Rad). For gene expression analysis, normalization was against Fixed brain nuclei (see ‘Tissue Homogenization’) were resuspended in 1mL 0.5% BSA in PBS . Nuclei were stained in Eppendorf tubes with the relevant antibodies rocking for 30–60 minutes at 4°C. For neuron and glia isolation, nuclei were stained with NeuN AF488 . For neuron and glial subtype isolation, nuclei were stained with NeuN AF488 , GFAP AF647 , and PU.1 PE . To stain for the glucocorticoid receptor, nuclei were incubated with Polyclonal Glucocorticoid Receptor  followed by Donkey anti-Rabbit IgG AF647 . To stain for HSF1 receptor, nuclei were incubated with anti-HSF1 followed by Donkey anti-Rabbit IgG AF647 . Nuclei were pelleted between steps by centrifugation for 10–15 minutes at 2000RCF at 4°C. Finally, to help gate for singlet nuclei, 1:1000 DAPI (Sigma-Aldrich) was added to the buffer just prior to flow cytometry. Nuclei were then run on a LSRII cytometer (BD Biosciences) or isolated with a BD FACSAria (BD Biosciences) cell sorter into 1% BSA PBS with inhibitors. The data was analyzed with FlowJo software (FlowJo LLC).FACS-isolated nuclei (see ‘Flow Cytometry’) were pelleted by centrifugation for 15 minutes at 2000RCF at 4°C. To decrosslink the nuclei, the RecoverAll Total Nucleic Acid Isolation Kit for FFPE (Thermo Fisher Scientific) was utilized following the manufacturer’s instructions. Briefly, nuclei were resuspended in 200uL digestion buffer with 4 uL protease  was substituted if the manufacturer-provided protease was exhausted) for 15 minutes at 50C, then 15 minutes at 80C. To isolate the RNA and eliminate most DNA prior to DNAase treatment, 800uL TRIzol LS (Invitrogen) was added, mixed well, and incubated for 5 minutes at room temperature before proceeding with isolation or freezing at -80C. 215uL chloroform was added to the solution and vortexed vigorously for 30 seconds before adding to a 5Prime Phase Lock Gel Heavy tube (Quantabio) and centrifuged for 15 minutes at 12,000g at 4C before transfer to an eppendorf tube. An equal volume of 100% ethanol (800uL) was added immediately and mixed well before proceeding to RNA isolation with the Direct-zol RNA Microprep Kit (Zymo Research). DNase treatment and RNA isolation proceeded according to the manufacturer’s instructions, before elution in 6-20uL water.The generation of cDNA from the isolated nuclear RNA was performed with SuperScript III or IV (Invitrogen) according to the manufacturer’s instructions, priming with either random hexamer or oligo(dT) primers. Diluted cDNA was then utilized for qPCR (see ‘qPCR’).For library preparation, RNA concentration and quality was assessed with a Fragment Analyzer (Agilent), yielding an RNA fragment distribution concentrated between approximately 200bp to 6000bp. RNA-Seq libraries were generated with the SMARTer Stranded Total RNA-Seq Kit—Pico Input Mammalian  according to the manufacturer’s instructions. Because the RNA was already partially degraded during the fixation and decrosslinking procedure, the RNA fragmentation time was 90 seconds. Paired end sequencing was performed with a NextSeq500 at the MIT BioMicro Center.50E10 buffer  before resuspending beads in T50E10S1 buffer  and heating to 65C for 15 minutes to elute DNA. After transferring to a new tube, DNA was decrosslinked by leaving at 65C for 5 hours to overnight. DNA was treated with Proteinase K (NEB) and RNAse (Roche) before purification with phenol:chloroform:isoamyl-alcohol 1 Phase (VWR), 5Prime Phase Lock Gel Heavy tube (Quantabio), and glycogen (sigma Aldrich) to facilitate DNA pelleting. Resuspended ChIP and Input DNA was then used for qPCR or ChIP-Seq. Library preparation utilized a HyperPrep Kit (Kapa Biosystems) and NEXTFLEX DNA Barcodes (Perkin Elmer), with size selection performed with Agencourt AMPure XP (Beckman Coulter). Libraries were sequenced on the Illumina HiSeq2000 at the MIT BioMicro Center. γH2AX ChIP-Seq was performed with three or four biological replicates.Performed similar to . Pelletehttp://broadinstitute.github.io/picard/) was used to remove duplicate reads and the remaining reads sorted and indexed with SAMtools [To eliminate nucleotides that are part of the template-switching oligo as per the manufacturer’s instructions , the first three nucleotides of the first sequencing read (Read 1) for kit v1 or the first three nucleotides of the second sequencing read (Read 2) for kit v2 were trimmed with Trimmomatic . TrimmedSAMtools . Read coSAMtools . AnalysiSAMtools  in R, wiSAMtools , calculaSAMtools  was usedSAMtools . Genome SAMtools . Plottinhttp://broadinstitute.github.io/picard/) was used to remove duplicate reads. Poorly aligned reads were then filtered out (MAPQ> 10) and the remaining reads sorted and indexed with SAMtools [ChIP-Seq reads were aligned to the mouse genome GRCm38 (mm10) with Bowtie2  with defSAMtools . SAMtoolSAMtools  was usedSAMtools  using a SAMtools  was usedSAMtools  was thenSAMtools . AnalysiSAMtools  in R. MASAMtools  was usedSAMtools . AggregaSAMtools . Venn diSAMtools . PlottinFor analysis of H3K27Ac data , FASTQ fPermutation testing was performed similar to . NeuronaTo find promoter TF motif overrepresentation, the ‘enricher’ function of the clusterProfiler R package  was utilGlucocorticoid receptor ChIP-Seq peaks from rat were downloaded from supplementary tables of , 56 and P ≤ 0.05 was considered statistically significant. Bar and scatter plots show the Mean ± SEM. Outliers were detected with ROUT (Q = 2%). Other statistical tests were performed in R, including the hypergeometric distribution test using the ‘phyper’ function, linear regression with the ‘lm’ function, and Welch’s ANOVA with Games-Howell post-hoc test with the ‘oneway’ function.Two-tailed unpaired student’s t-test and One-way ANOVA with Tukey’s multiple comparisons test were performed with GraphPad PRISM (Version 8). S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S1 FigNpas4 and Arc mRNA expression in the hippocampus (HIP) and medial prefrontal cortex (mPFC) 30 minutes following contextual fear conditioning (CFC30’), normalized to Hprt and respective naive condition. N = 4 mice per group; two-tailed unpaired student’s t-test; * P ≤ 0.05; **P ≤ 0.01; *** P ≤ 0.001; **** P <0.0001; Mean ± SEM. (B) Volcano plots of Log2FC versus Log10(FDR) of γH2AX peaks and their corresponding genes for HIP (left) and mPFC (right). Upregulated indicates FDR < 0.05 and log2FC > 0, Downregulated indicates FDR < 0.05 and log2FC < 0, ns indicates FDR > 0.05. (C) Correlation between gene length and γH2AX peak length with linear regression. Left is HIP, right is mPFC. (D) Enrichment map of the 27 enriched biological processes for the 206 γH2AX peak-containing genes shared between HIP and mPFC in Npas4, Nr4a1, and housekeeping gene B2M. Each replicate was generated from the pooling of 3 animals’ hippocampi. N = 3; IgG N = 2; two-tailed unpaired student’s t-test; ns P > 0.05; * P ≤ 0.05; ** P ≤ 0.01; Mean ± SEM.(A) qRT-PCR analysis of (TIF)Click here for additional data file.S2 FigNpas4 and mRNA for the early response gene Arc. RNA purified from FACS-isolated nuclei or whole mPFC homogenate after CFC. cDNA was primed with random hexamers and the primer used for qPCR was either intronic (Npas4) or spanned an exon-exon junction (Arc). Normalized to Hprt and relative to naive NeuN+ for Npas4 or normalized to respective naive condition for Arc. N = 3–4 mice per group; One-way ANOVA with Tukey’s multiple comparisons test; absence of an asterisk indicates P > 0.05; * P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001; **** P <0.0001; Mean ± SEM.(A) Flow cytometry dot-plots representative of the gating strategy used for isolating neuronal and non-neuronal nuclei from mouse brain for RNA-Seq. Appropriately sized (FSC vs SSC), singlet nuclei (DAPI+), were gated for the presence or absence of the neuronal nuclei marker NeuN (NeuN+). (B) qRT-PCR analysis of pre-mRNA transcription from the neuronal early response gene (TIF)Click here for additional data file.S3 Fig(A) Correspondence between RNA-Seq datasets and brain cell types. Marker gene sets for brain cell types was obtained from a previously published dataset , and the(TIF)Click here for additional data file.S4 Fig(A) Percent overlap between genes containing a γH2AX peak and those genes upregulated (padj < 0.05) in non-neuronal nuclei after CFC. Hypergeometric distribution test; *** P ≤ 0.001; **** P <0.0001. (B) DSBs increase with RNA expression level; mPFC CFC30 γH2AX ChIP-Seq intensity at gene bodies versus percentile of mPFC NeuN+ CFC30’ RNA expression. Welch’s ANOVA with Games-Howell post-hoc test. (C) Confirming equivalent RNA expression levels between the observed (upregulated) genes and expected (randomly sampled) genes for the permutation testing. Distribution of mean RNA FPKM for 1000 permutations of random sampling, binned by RNA expression level. Lines are the mean RNA FPKM. mPFC 10 minutes after CFC (left), or 30 minutes after CFC (right).(TIF)Click here for additional data file.S5 Fig(A-B) Top 10 enriched promoter motifs for the genes upregulated in NeuN+ CFC10’ HIP (A) and NeuN+ CFC10’ mPFC (B). Using the “Transcription Factor Targets” (TFT) gene set from the molecular signatures database (MSigDB). (C) Top 8 enriched promoter motifs for the genes upregulated in neuronal nuclei from HIP 30 minutes after CFC (Log2FC >0 & FDR < 0.05). Using the “Transcription Factor Targets” (TFT) gene set from the molecular signatures database (MSigDB). (D) Motifs associated with upregulated genes in HIP NeuN+ nuclei. Left, number of the indicated motifs associated with each gene’s promoter. Center, γH2AX Log2FC, right, RNA-Seq Log2 fold change 10 or 30 minutes after CFC. Using the TFT gene sets from MSigDB for each transcription factor motif.(TIF)Click here for additional data file.S6 FigDifferentially regulated genes from visual cortex single-cell RNA-Seq that also contain γH2AX peaks in mPFC (right), and their regulation in mPFC nuclear RNA-Seq (left). ‘Neuron’ encompasses excitatory and inhibitory neuron subtypes, ‘Glia’ includes all subtypes from oligodendrocytes, microglia, astrocytes, and oligodendrocyte precursor cells, while ‘Vasculature’ denotes endothelial, pericyte, and smooth muscle cell subtypes .(TIF)Click here for additional data file.S7 Fig(A) Motifs associated with upregulated genes in non-neuronal nuclei from HIP (top) or mPFC (bottom). Left, number of the indicated motifs associated with each gene’s promoter. Center, γH2AX Log2FC, right, RNA-Seq Log2 fold change 10 or 30 minutes after CFC. Using the TFT gene sets from MSigDB for each transcription factor motif. (B-C) Enrichment map of the top enriched biological processes for the genes upregulated in HIP NeuN- (B) or mPFC NeuN- (C) nuclei 30 minutes after CFC. Over-representation analysis with gene ontology (GO) category “Biological Process.”(TIF)Click here for additional data file.S8 FigHsp90ab1 and Hspa8. Actb, which is not a HSF1 target but has similarly increased levels of γH2AX and gene expression showed lower HSF1 binding. ChIP-qPCR of cortex 30 minutes following CFC. N = 6–7; One-way ANOVA with Tukey’s multiple comparisons test; ns P > 0.05; * P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001; Mean ± SEM. (B) Increased HSF1 nuclear translocation in neurons and non-neurons after CFC in cortex. Top, representative fluorescence intensity histograms after CFC . Bottom, intensity of nuclear HSF1 after CFC was analyzed by flow cytometry; median fluorescence intensity (MFI) normalized to respective naive condition. N = 7; two-tailed unpaired student’s t-test; ** P ≤ 0.01; *** P ≤ 0.001; Mean ± SEM.(A) HSF1 binding increases at the promoter regions of chaperones (TIF)Click here for additional data file.S9 FigSgk1 and Ddit4 mRNA expression in the HIP and mPFC 30 minutes following contextual fear conditioning—normalized to Hprt and respective naive condition. N = 4 mice per group; two-tailed unpaired student’s t-test; **P ≤ 0.01; Mean ± SEM. (B) ChIP-qPCR analysis of γH2AX induction at select gene bodies in mouse glial primary cultures 30 minutes after treatment with dexamethasone (Dex) (100nM). N = 4 independent cultures; two-tailed unpaired student’s t-test; ns P > 0.05; Mean ± SEM. (C) Average H3K27ac signal of prefrontal anterior cingulate cortex (ACC) at glucocorticoid receptor binding sites  [Nr3c1) from naive nuclear RNA-Seq datasets. (F) Intensity of nuclear glucocorticoid receptor (left) or nuclear NeuN (right) in NeuN+ or NeuN- nuclei of the mPFC after corticosterone treatment. Normalized median fluorescence intensity (MFI). N = 5 mice per group; two-tailed unpaired student’s t-test; ** P ≤ 0.01; ns P > 0.05; Mean ± SEM.(A) qRT-PCR analysis of hIP-Seq) ,56 contahIP-Seq) . (D) AvehIP-Seq) ,56 contahIP-Seq) . (E) Mea(TIF)Click here for additional data file.S10 FigNpas4), astrocyte (Gfap), microglial (C1qa), oligodendrocyte (Mbp). Normalized to Hprt; N = 8, 4 mice saline treated, 4 mice corticosterone treated. (C) Glucocorticoid receptor agonist corticosterone (Cort) induces Sgk1, Ddit4, and Glul in glia, and not the housekeeping gene Actb. RT-qPCR on FACS-purified hippocampal nuclear RNA from neurons (NeuN+), astrocytes (GFAP+), microglia (PU.1+), and oligodendrocytes-enriched  30 minutes after saline or corticosterone:HBC complex (2mg/Kg) administration. N = 4 mice per group; two-tailed unpaired student’s t-test; * P ≤ 0.05; *** P ≤ 0.001; **** P <0.0001; Mean ± SEM.; * P ≤ 0.05; *** P ≤ 0.001; **** P <0.0001.(A) Flow cytometry dot-plots representative of the gating strategy used for isolating neuronal and glial nuclei from hippocampus for RNA-Seq. Appropriately sized (FSC vs SSC plot), singlet nuclei , are gated for the presence or absence of the neuronal nuclei marker NeuN (NeuN+); NeuN- nuclei are then separated by the astrocyte marker GFAP (GFAP+), GFAP- nuclei are then gated for the microglia marker P.1 (PU.1+), with the oligodendrocyte-enriched fraction, NeuN-/GFAP-/PU.1- (3X-), also collected. (B) RT-qPCR analysis of FACS-isolated nuclei for cell-type-specific markers: neuronal ((TIF)Click here for additional data file.S11 Fig(A) Correspondence between hippocampal cell-type-specific RNA-seq datasets and brain cell types. Marker gene sets for brain cell types was obtained from a previously published dataset, and the average expression of these genes was calculated (RPKM geometric mean) for the saline condition . Z-score(TIF)Click here for additional data file.S12 Fig(A-C) Enrichment map of the top 30 enriched biological processes for the genes upregulated in HIP after corticosterone treatment in astrocyte (A), oligodendrocyte-enriched (B), and microglia (C) nuclei. No enrichment in neurons. Over-representation analysis with gene ontology (GO) category “Biological Process.”(TIF)Click here for additional data file.S13 Fig(A-C) Enrichment map of the top enriched biological processes for the genes downregulated in HIP after corticosterone treatment in astrocytic (A), oligodendrocyte-enriched (B), and microglial (C) nuclei. Over-representation analysis with gene ontology (GO) category “Biological Process.” (D) Top five enriched biological processes of the downregulated genes for each cell type in purified hippocampal nuclei from neurons, astrocytes, microglia, and oligodendrocyte-enriched after corticosterone treatment (padj < 0.05). Over-representation analysis with gene ontology (GO) category “Biological Process.”(TIF)Click here for additional data file.S14 FigPolr3e displaying a small (951bp) intronic γH2AX peak in mPFC overlapping a mammalian interspersed repeat (MIR). MIR antisense transcription is shown on the negative strand (-).Genome browser tracks for the gene (TIF)Click here for additional data file.S15 FigEnriched disease associations for the genes upregulated in HIP after corticosterone treatment in neuronal, astrocytic, microglial, and oligodendrocyte-enriched nuclei, filtered for disease associations related to the nervous system. An absent group indicates no enrichment at threshold q < 0.05. Over-representation analysis with DOSE Disease ontology.(TIF)Click here for additional data file. 13 Apr 2021PONE-D-21-08714Profiling DNA break sites and transcriptional changes in response to contextual fear learningPLOS ONEDear Dr. Tsai,Thank you for submitting your manuscript to PLOS ONE. Two experts have reviewed your manuscript, and I pasted their comments below. Both reviewers expressed substantial enthusiasm toward you manuscript, but they also raised a few points that need to be addressed. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.Please submit your revised manuscript by May 28 2021 11:59PM. 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You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Unlike cycling cells, where DNA replication and cell cycle progression respond to DSBs and activate the repair mechanism, neuron cells do not proliferate. Hence, it is intriguing how neuron cells handle DSB damage and moreover how DSB formation interplays with the neuronal activities. In this manuscript by Stott et.al, the authors mapped the genome-wide DSB formation in the mouse prefrontal cortex and hippocampus under contextual fear conditioning, which provided an interesting connection between learning behaviors and DNA damage in the brain. I found this research very interesting and technically sound, therefore, recommend its acceptance for publication at PLOS ONE.Reviewer #2: In this study, the authors investigate fear conditioning induced DNA double strand breaks (DSBs) in adult male mouse hippocampus and medial prefrontal cortex through ChIPseq of γH2AX. They recognize widely distributed DSBs after fear conditioning with many demonstrated brain region specific inductions. These DSBs are not only enriched in a few functionally relevant gene categories (e.g. synaptic transmission), but also correlated with transcription changes in neurons and/or glia cells which are profiled through cell-type specific nuclear RNAseq. Furthermore, the upregulated transcripts appear to have higher enrichment of γH2AX and are mediated through activity-dependent gene related transcription factors, which further indicates the functional role of DSBs in neural plasticity. Notably, several fear conditioning induced genes that carry DSBs are modulated by heat shock factor, which suggests an involvement of proteostasis in fear conditioning induced DSBs. Interestingly, many of the γH2AX-containing genes are responsive to glucocorticoid only in non-neuronal nuclei. Following corticosterone administration, the authors find that the differential genes are predominantly in glial cells, with some of them showing high levels of γH2AX. The study includes a large amount of work and the findings are novel. I only have a few minor comments.1. The study has used γH2AX as a DSB proxy and performed its ChIPseq to identify DSBs genome-wide. It will be helpful to discuss if any limitations of using γH2AX to recognize DSBs. Will DNA single strand break also be detected through this approach?2. Line 82, (B): “six” should be “five”.3. Line 85, (C): Double check if it is top “5” biological processes… or more.4. Ling 334: “GC” should be “GR”.5. Figure 3A, y-axis: It is unclear why some HSF motifs are shown with a sequence, some are not.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  25 May 2021Response to ReviewersWe would like to thank the reviewers for their time and input on this manuscript. We appreciate their comments and suggestions. Please see our responses in red. Reviewer #1: Unlike cycling cells, where DNA replication and cell cycle progression respond to DSBs and activate the repair mechanism, neuron cells do not proliferate. Hence, it is intriguing how neuron cells handle DSB damage and moreover how DSB formation interplays with the neuronal activities. In this manuscript by Stott et.al, the authors mapped the genome-wide DSB formation in the mouse prefrontal cortex and hippocampus under contextual fear conditioning, which provided an interesting connection between learning behaviors and DNA damage in the brain. I found this research very interesting and technically sound, therefore, recommend its acceptance for publication at PLOS ONE.We thank the reviewer’s comment.Reviewer #2: In this study, the authors investigate fear conditioning induced DNA double strand breaks (DSBs) in adult male mouse hippocampus and medial prefrontal cortex through ChIPseq of γH2AX. They recognize widely distributed DSBs after fear conditioning with many demonstrated brain region specific inductions. These DSBs are not only enriched in a few functionally relevant gene categories (e.g. synaptic transmission), but also correlated with transcription changes in neurons and/or glia cells which are profiled through cell-type specific nuclear RNAseq. Furthermore, the upregulated transcripts appear to have higher enrichment of γH2AX and are mediated through activity-dependent gene related transcription factors, which further indicates the functional role of DSBs in neural plasticity. Notably, several fear conditioning induced genes that carry DSBs are modulated by heat shock factor, which suggests an involvement of proteostasis in fear conditioning induced DSBs. Interestingly, many of the γH2AX-containing genes are responsive to glucocorticoid only in non-neuronal nuclei. Following corticosterone administration, the authors find that the differential genes are predominantly in glial cells, with some of them showing high levels of γH2AX. The study includes a large amount of work and the findings are novel. I only have a few minor comments.1. The study has used γH2AX as a DSB proxy and performed its ChIPseq to identify DSBs genome-wide. It will be helpful to discuss if any limitations of using γH2AX to recognize DSBs. Will DNA single strand break also be detected through this approach?We agree this is an important point that should be addressed. We have added a new paragraph in the discussion to address the limitations of γH2AX ChIP-seq (please see lines 442-454).2. Line 82, (B): “six” should be “five”.We count six for this figure, please see Fig 1B below which is being referenced on line 82:3. Line 85, (C): Double check if it is top “5” biological processes… or more.We double-checked and found that we had indeed selected the top five biological processes from each of the four time points.4. Ling 334: “GC” should be “GR”.We have corrected this mistake and a few other instances, including in Fig 4.5. Figure 3A, y-axis: It is unclear why some HSF motifs are shown with a sequence, some are not.We utilized the given name for each gene set without editing, and some of these names include motifs for reasons unclear. We agree it is a bit confusing, but we did not want to edit them because it could obscure their identity.AttachmentResponse to Reviewers.docxSubmitted filename: Click here for additional data file. 28 May 2021Profiling DNA break sites and transcriptional changes in response to contextual fear learningPONE-D-21-08714R1Dear Dr. Tsai,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.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Bing YaoAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments: 23 Jun 2021PONE-D-21-08714R1 Profiling DNA break sites and transcriptional changes in response to contextual fear learning Dear Dr. Tsai: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. onepress@plos.org.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 plosone@plos.org. If we can help with anything else, please email us at Thank you for submitting your work to PLOS ONE and supporting open access. 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Mycobacterium species, transcription of rRNA is activated by the RNA polymerase (RNAP) accessory transcription factor CarD, which interacts directly with RNAP to stabilize the RNAP-promoter open complex formed on rRNA genes. The functions of CarD have been extensively studied, but the mechanisms that control its expression remain obscure. Here, we report that the level of CarD was tightly regulated when mycobacterial cells switched from nutrient-rich to nutrient-deprived conditions. At the translational level, an antisense RNA of carD (AscarD) was induced in a SigF-dependent manner to bind with carD mRNA and inhibit CarD translation, while at the post-translational level, the residual intracellular CarD was quickly degraded by the Clp protease. AscarD thus worked synergistically with Clp protease to decrease the CarD level to help mycobacterial cells cope with the nutritional stress. Altogether, our work elucidates the regulation mode of CarD and delineates a new mechanism for the mycobacterial starvation response, which is important for the adaptation and persistence of mycobacterial pathogens in the host environment.Under starvation conditions, bacteria tend to slow down their translation rate by reducing rRNA synthesis, but the way they accomplish that may vary in different bacteria. In  Escherichia coli and Bacillus subtilis work primarily by reducing rRNA transcription via decreasing the stability of the transcription initiation complex  is usually less efficient in forming RNAP-promoter open complex (RPo) than NA genes , and theNA genes . To overNA genes . Both arNA genes . CarD stNA genes . AlthougNA genes . TherefoNA genes . CarD waNA genes  and weakNA genes . A recenrculosis . DespitecarD was upregulated in response to starvation  and Western blot experiments, respectively. As shown in carD transcript and CarD protein levels increased under genotoxic stresses triggered by H2O2, methyl methanesulfonate (MMS), or ciprofloxacin (CIP), which was consistent with the previous reports that CarD may be involved in DNA damage repair , harvested the cells, and then transferred these cells to the normal medium, carbon-limited, nitrogen-limited, and phosphorus-limited medium, followed by detecting the respective mRNA and protein levels of CarD. It is worth noting that although the carD transcript level increased in response to starvation conditions   to the mc2155 culture at the stationary phase and measured the CarD protein level 3 and 6 hr thereafter. As shown in 2155 cells resumed normal growth. Considering that CarD activates the transcription of rRNA   and meas of rRNA , and tha of rRNA , we beliM. bovis BCG and M. tuberculosis H37Ra. The results are consistent with those in M. smegmatis, that is, CarD levels were all significantly reduced in response to carbon-, nitrogen-, and phosphorus-starvation conditions  unfoldase, either ClpX or ClpA/ClpC  , but could not do so when ATc was absent.Since the CarD protein level decreased dramatically under nutritional starvation, hypoxic, and acidic conditions, we speculated that CarD might be proteolytically degraded. Clp is a special energy-dependent protease that regulates the response to various stresses . The typlpA/ClpC . Unlike lpA/ClpC . Throughegulated . HoweverclpP2CM)  through clpP2CM) , in whicclpP2CM mutant and control cells (Ms/pRH2502-clpP2) were first cultured in ATc-containing medium to the late exponential phase (OD600 ≈ 1.5), then harvested, washed, and reinoculated in the fresh medium with or without ATc. The results showed that CarD was effectively degraded when the control cells entered the stationary phase, regardless of the presence of ATc  is still highly retained   , and we se (MSP) . Moreovery phase .ascarD is controlled by SigF. To verify this hypothesis, we examined the transcriptional level of ascarD in a sigF mutant (ΔsigF). As shown in sigF strain in the MEP, and transition to the MSP could not induce it either. These data indicate that the expression of ascarD is regulated by SigF.To better characterize AscarD, we determined its transcriptional start site (TSS) by carrying out the 5′-RACE (5′-rapid amplification of cDNA ends) experiment . The TSSascarD was highly expressed during the stationary phase, we speculated that transcription of ascarD could be also subject to carbon starvation. To verify this idea, we carried out lacZ reporter assays to examine the ascarD promoter activity under different carbon source (glycerol) concentrations. As shown in ascarD promoter activity gradually increased as the glycerol concentrations decreased. This indicates that ascarD could indeed be induced under carbon starvation conditions; however, in the ΔsigF strain, the expression of ascarD did not respond to the glycerol concentration , was translationally fused to lacZ to construct the PUCP plasmid  and could not transcribe AscarD, so the expression of the carD-lacZ transcript will not be affected by this antisense RNA. We then transformed the two plasmids into mc2155 cells and measured their β-galactosidase activities. As shown in mut plasmid exhibited higher β-galactosidase activity than those with the PUCP plasmid. This result indicates that AscarD repressed the expression of carD-lacZ transcript, and blocking the transcription of ascarD derepressed this regulation.Expression of AscarD was highly induced in response to starvation, while the CarD protein level was sharply reduced, suggesting that AscarD could be involved in regulating  plasmid , in whiccarD expression, we overexpressed ascarD on a multiple-copy plasmid to construct ascarD high-expressing strain (ascarDOE) and knockdown the transcription of ascarD to construct the ascarD low-expressing strain  and/or the translational level (inhibiting the transcript translation) . To detel strain , illustrascarD is also induced under such stress conditions. To address this question, we monitored the RNA level of AscarD under the two stress conditions by qRT-PCR. The results showed that the AscarD level increased by 4.5 and 2.3 times in response to hypoxia and acid stress, respectively. These data indicate that AscarD was upregulated in response to a variety of stimuli to inhibit the protein synthesis of CarD and help mycobacterial cells adapt to the stress environment.Under starvation conditions, AscarD was highly induced to inhibit CarD protein synthesis. Since CarD protein levels are not only reduced during nutrient starvation, but also reduced under hypoxic and acidic conditions, we wanted to know whether ascarD in M. smegmatis genome and constructed a mutant strain, referred as AsM. In addition, to block the regulation of CarD by both AscarD and Clp protease, we also constructed a double mutant strain AsM/AAAS_del with a mutation in the promoter of ascarD and the deletion of the ‘AAAS’ motif of CarD. Next, we investigated the changes in CarD levels and bacterial survival of these strains under stress conditions. The Western blot results showed that, compared to the wild-type strain, CarD levels in the AsM strain slightly increased, while CarD levels in the AAAS_del strain increased significantly ppGpp. Yet, its detailed mechanism is still not entirely clear today, although it is considered similar to the well-characterized stringent response mechanisms reported in E. coli and B. subtilis ppGpp is synthesized in large quantities in response to starvation and directly interacts with RNAP to destabilize the RPo formed on rRNA genes and consequently reduces the rRNA synthesis  belong to the previously identified dormancy regulon  in many bacteria also increases significantly during the stationary phase  and the adjacent spacer of the promoter  in the spacer immediately upstream of the extended −10 element contributes greatly to the autoregulation of Rhodobacter CarD. In Mycobacterium, there is no similar spacer, but there is a highly conserved dinucleotide ‘CG’ immediately upstream of the extended −10 element 2SO4, 0.2% glycerol (vol/vol), and 0.05% Tween 80 (vol/vol). For the carbon starvation experiment, glycerol was removed; for the nitrogen starvation experiment, (NH4)2SO4 was removed; for the phosphorus-starvation experiment, both K2HPO4 and NaH2PO4 were removed, while 50 mM 3-(N-morpholino) propanesulfonic acid was added to replace lost buffering capacity.Hartmans–de Bont (HDB) minimal medium, prepared according to reference , was use2O2, 0.1% MMS, and 10 μg/ml of CIP were separately added to the MEP mc2155 culture and maintained in roller bottle culture for additional 4 hr. For the PBS starvation experiment, the MEP mc2155 cells were harvested, resuspended in PBS supplemented with 0.05% Tween 80, and maintained in roller bottle culture for 4 hr. For the carbon-, nitrogen-, and phosphorus-starvation experiments, harvested MEP cells were resuspended in the HDB medium with carbon, nitrogen, or phosphorus removed, respectively, and maintained in roller bottle culture for 4 hr for the mc2155 cells, or 24 hr for the BCG and H37Ra cells. For the nutrient supplemented experiments, the abovementioned starved cultures were supplemented with the corresponding nutrients and maintained in roller bottle culture for additional 4 hr for the mc2155 cells, or 24 hr for the BCG and H37Ra cells. For the acid stimulation experiments, the harvested MEP cells were resuspended in the HDB medium with a low pH value (pH 4.5) and maintained in roller bottle culture for 4 hr for the mc2155 cells, or 24 hr for the BCG and H37Ra cells.Mycobacterial cells were first grown to MEP in the normal 7H9 medium. For genotoxic reagent stimulation experiments, 10 mM H600 of 0.02. Then, the serum bottles were sealed with butyl rubber stoppers, closed tightly with screwcaps, and incubated at 37°C with shaking. The mc2155 cells were harvested 10 hr after the blue color disappeared completely, and the BCG and H37Ra cells were harvested 48 hr after the blue color completely disappeared. For the reaeration experiments, the abovementioned anaerobic cultures were transferred to roller bottles and harvested after the mycobacterial cells regrow.For anaerobic experiments, the modified Wayne model  was used600 , as described previously  under the following conditions: 95°C for 10 s, 60°C for 10 s, and 72°C for 10 s for 40 cycles. Relative quantification of gene expression was performed by the 2−ΔΔCT method  was inhibited with the induction by 50 ng/ml of ATc, and the inhibition efficiency was assessed by qRT-PCR. It is worth noting that dCas9:sgRNA complex exhibits a strong inhibitory effect on the expression of a gene after it combines with the coding strand of the gene, but almost does not affect the expression of the gene when it combines with the template strand. The sgRNA we designed is combined with the coding strand of ascarD , so it has a strong inhibitory effect on the transcription of ascarD (reduced 18.8 ± 2.6 times as quantitated by qRT-PCR) but has almost no effect on the transcription of ispD. The inhibition efficiency is shown in CRISPR/dCas9-mediated gene knockdown strategy  was carr2 strain . pRH2521D strain . The expclpP2 conditional mutant (clpP2CM) construction, an exogenous clpP2 gene amplified with clpP2-F/R primer pair  using the CRISPR/Cpf1-mediated mutagenesis. Thus, clpP2 could be expressed normally in the clpP2CM strain only upon the addition of 50 ng/ml ATc, but could not do so when ATc was absent. It should be noted that, in principle, the clpP2CM strain cannot grow in the 7H9 medium without ATc. But when we first cultivated the clpP2CM cells to exponential phase in ATc-containing 7H9 medium, then harvested the cells, washed them, and inoculated them into ATc-free 7H9 medium, clpP2CM cells can grow slowly.CRISPR/Cpf1-mediated mutagenesis was carried out as described previously . For clpmer pair  was ligacarD, containing the carD promoter, 5′-UTR, carD CDS, and ascarD promoter on the antisense strand, was translationally fused to lacZ; for PUCPmut construction, the modified −213 to +1090 region of carD, containing the carD promoter, 5′-UTR, carD CDS, and the mutated ascarD promoter (GGGTAC was mutated to GGGCGC) on the antisense strand, was translationally fused to lacZ. Then the two plasmids were transformed into the mc2155 strain to measure the β-galactosidase activity. The detailed steps for β-galactosidase activity determination were carried out according to references . For Western blot assays, the amount of total protein loaded in each lane was the same, and the detailed procedures were as described previously . After purification, the eluate containing ClpC1-His/ClpX-His protein was dialyzed overnight at 4°C, then incubated with 1 mM ATP for 1 hr before loading onto the Ni-NTA resin. For pull-down assay, the resin-bound ClpC1-His or ClpX-His protein was separately incubated with lysate extracted from exponential mc2155 cells at room temperature for 30 min. The resins were washed with 50 mM imidazole for five times and eluted with 500 mM imidazole. The eluents were subjected to immunoblot assay using the antibodies indicated.The His × 6 tagged ClpC1 (ClpC1-His) and ClpX (ClpX-His) recombinant proteins were expressed and purified from 600≈ 0.5) and then diluted 50-fold into acidic 7H9 medium (pH = 4.5), neutral PBS (pH = 7.0), or acidic PBS (pH = 4.5). The dilutions were kept at 4°C, and the bacterial counts were performed 0th and 7th days thereafter. For genotoxic stress survival assay, ascarDOE and control cells were grown to MEP (OD600≈1.0), followed by diluting 101, 102, 103, 104, and 105 folds, respectively. Afterward, 3 μl of the bacterial suspension at each dilution level were separately spotted onto 7H10 plates containing either 0.3 mM H2O2, 0.05% MMS, 0.2 μg/ml of CIP, 0.15 μg/ml of Str, or 5 μg/ml of Rif, respectively. The plates were cultivated at 37°C for three days.For the stationary-phase survival assay, mycobacterial cells were first grown to the stationary phase, followed by keeping them at 4°C, and the bacterial counts were performed on the 0th and 15th days thereafter. For stress survival assays, mycobacterial cells were first grown to the early-exponential phase (ODt-test (two-tailed), with *** indicating p value <0.001, ** indicating p value <0.01, * indicating p value <0.05, and n.s. indicating p value >0.05. Error bars indicate standard deviation of three biological replicates. Statistical testing was done using the Student’s  CarD is an RNA polymerase interacting protein that is essential for mycobacterial viability, the levels of which are important for controlling gene expression in mycobacteria during various stress conditions. This study reports two mechanisms that regulate levels of CarD under stress conditions, including starvation. The authors report that CarD levels are tightly regulated and that there was a dramatic decrease in the levels of CarD when cells switched from the nutrient-rich to the starvation condition. They discovered two synergistic mechanisms that led to this dramatic decrease in CarD. The first is SigF-dependent induction of antisense RNA of CarD (AscarD), which inhibits CarD translation and a second mechanism involving Clp protease-mediated degradation of intracellular CarD. The work will be of interest to researchers studying non-coding RNAs, microbial gene expression, physiology and stress response. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Bavesh Kana as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Krishan Gopal Thakur (Reviewer #1).Thank you for submitting your article "Clp protease and antisense RNA jointly regulate the global regulator CarD to mediate mycobacterial starvation response" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:1. From the study, it appears likely that SigF plays a key role in stress adaption by upregulating AscarD transcription. However, quantification of the expression of SigF under stress conditions is missing. Including data on SigF expression under starvation and other stress conditions will strengthen this study further.2. Similarly, how transcript levels are being measured and normalized should be described where presented in the text/legend with perhaps more detail referenced in the Methods. As normalized data is provided, changes could technically be due either to increases of CarD transcript or decreases in the sigA transcript. Evidence or measurements that the sigA transcript doesn't change appreciably under these conditions needs to be provided. The same is technically true of the gel-based measurements of protein levels. If one assumes that the amount of material loaded in each lane is the same, then the data clearly shows what the authors suggest. However, this was not specifically mentioned anywhere leaving open the possibility that the over-expression of the control proteins results in an apparent repression of CarD. Please address this.3. The authors have shown data that suggests that Clp proteases degrade CarD under stress conditions. CarD contains the "AAAS" sequence motif at the C-terminal region, which is recognized by Clp proteases. Mutating this sequence motif and quantifying mutant vs wild type CarD levels in cells under normal and stress conditions will further strengthen the claim that Clp proteases degrade CarD under stress conditions.4. Although the paper presents a clear picture of two mechanisms (Proteolytic degradation and anti-sense) individually on CarD levels, the effects of these mechanisms on cellular phenotypes is less completely explored. For example, for the stationary phase dependent regulation of CarD, does this mechanism effect stationary phase survival? Similarly, what about survival/expression chages under the stress conditions examined? Some data is given, but more exploration of the cellular effects of these mechanisms would make the paper more appealing to a broad audience. With their ability of tune CarD levels via graded manipulation of asCarD or Clp, the authors could learn much more about the physiologic and global transcriptional effects of these regulatory mechanisms and this would be a major advance for the field. Relevant assays would include, (I) stationary phase survival assays and (I) RNA sequencing of cells with different levels of asCarD or Clp in different conditions to look at the global effects of these manipulations.5. Although the individual effects of Clp and asCarD are documented, the paper would be stronger if it explored the relative importance and interaction of these two mechanisms in different conditions. Are they simply additive as the model figure suggests? Does the relative importance of each mechanism differ depending on the condition studied? Relevant experiments that could strengthen this point are: (1) explore conditions in which one mechanism is dominant (2) changing asCarD levels or ClpP in the same cell during different stress conditions to see if one mechanism is dominant.Other comments:1. In Figure 1B the transcript levels of CarD under ciprofloxacin and H2O2 appears comparable. However, there was about a three-fold increase in the levels of CarD in the presence of ciprofloxacin. Can authors comment on this?2. It will also be interesting to see the temporal increase and decrease in the levels of CarD and AscarD transcripts during normal and stress conditions.3. The statement in the paper that ClpP2 dependence can be interpreted directly as the involvement of P1P2 is only true if ClpP2 never functions alone. The authors essentially state that, but could this assumption be misleading?4. The abbreviation PUPC should be explained.5. A study in Rhodobacter sphaeroides suggests that CarD negatively regulates its own promoter (https://pubmed.ncbi.nlm.nih.gov/34152199/). Do the authors have any data on whether or not this is true in mycobacteria? What is known, if anything, about direct transcriptional control of the CarD promoter? In the absence of AscarD , what happens to CarD transcript levels?6. Can the authors comment on whether the proteolytic degradation of CarD will have an effect on the production of CarD in a feed-back loop?7. RT-qPCR: No documentation of no RT reactions is given. This is important to exclude dna contamination.8. Some justification of the use of KatG as a loading control in the western blots is needed, since this is unusual and subject to regulation under stress.9. The rnaseq data presented in the discussion should be moved to results if it is new data. If it is previously published it can be discussed, but the table should be moved to Supplementary information.10. A question that arises is whether CarD itself has any effect on the levels of AscarD or whether in published ChIP-seq data, CarD can be seen on the AscarD promoter. Do the authors have any data or comments here?Reviewer #1 (Recommendations for the authors):The manuscript is well written and easy to follow. The major conclusions of the study are well supported by the experimental data provided in the manuscript. However, I have the following comments and suggestions:1. From the study, it appears likely that SigF plays a key role in stress adaption by upregulating AscarD transcription. However, quantification of the expression of SigF under stress conditions is missing in this study. I suggest including data on SigF expression under starvation and other stress conditions to strengthen this study further.2. The authors have shown data that suggests that Clp proteases degrade CarD under stress conditions. CarD contains the "AAAS" sequence motif at the C-terminal region, which is recognized by Clp proteases. I suggest mutating this sequence motif and quantifying mutant vs wild type CarD levels in cells under normal and stress conditions. This will further strengthen the claim that Clp proteases degrade CarD under stress conditions.3. In Figure 1B the transcript levels of CarD under ciprofloxacin and H2O2 appears comparable. However, there was about a three-fold increase in the levels of CarD in the presence of ciprofloxacin. Can authors comment on this?4. It will also be interesting to see the temporal increase and decrease in the levels of CarD and AscarD transcripts during normal and stress conditions.Reviewer #2 (Recommendations for the authors):As I have indicated in the public review, I really enjoyed this paper and think that it should most certainly be published. I only have a few points of clarification and questions for the authors and they are listed below:(1) How transcript levels are being measured and normalized should be described where presented in the text/legend with perhaps more detail referenced in the Methods. In particular, since normalized data is provided, changes could technically be due either to increases of CarD transcript or decreases in the sA transcript. Evidence or measurements that the sA transcript doesn't change appreciably under these conditions needs to be provided.(2) The same is technically true of the gel based measurements of protein levels. If one assumes that the amount of material loaded in each lane is the same, then the data clearly shows what the authors suggest. However, I did not see this specifically mentioned anywhere leaving open the possibility that the over-expression of the control proteins results in an apparent repression of CarD.(3) The statement in the paper that ClpP2 dependence can be interpreted directly as the involvement of P1P2 is only true if ClpP2 never functions alone. The authors essentially state that, but could this assumption be misleading?(4) I did not see where the abbreviation PUPC was explained.(5) One question I was left with was whether CarD itself has any effect on the levels of AscarD or whether in published ChIP-seq data, CarD can be seen on the AscarD promoter. Do the authors have any data or comments here?(6) A study in Rhodobacter sphaeroides suggests that CarD negatively regulates its own promoter (https://pubmed.ncbi.nlm.nih.gov/34152199/). Do the authors have any data on whether or not this is true in mycobacteria? What is known, if anything, about direct transcriptional control of the CarD promoter? In the absence of AscarD , what happens to CarD transcript levels?Can the authors comment on whether the proteolytic degradation of CarD will have an effect on the production of CarD in a feed-back loop?Reviewer #3 (Recommendations for the authors):I think the paper could be stronger in two areas noted above, these are suggested experiments for each of the major points above in the public review.Relevant experiments that could strengthen this area: stationary phase survival assays, RNA sequencing of cells with different levels of asCarD or Clp in different conditions to look at the global effects of these manipulations.Although the individual effects of Clp and asCarD are documented, the paper would be stronger if it explored the relative importance and interaction of these two mechanisms in different conditions. Are they simply additive as the model figure suggests? Does the relative importance of each mechanism differ depending on the condition studied?Relevant experiments that could strengthen this point: (1) explore conditions in which one mechanism if dominant (2) changing asCarD levels or ClpP in the same cell during different stress conditions to see if one mechanisms is dominant.Technical comments:RT-qPCR: No documentation of no RT reactions is given. This is important to exclude dna contamination.Some justification of the use of KatG as a loading control in the western blots is needed, since this is unusual and subject to regulation under stress.The rnaseq data presented in the discussion should be moved to results if it is new data. If it is previously published it can be discussed, but the table should be moved to SI. Essential revisions:1. From the study, it appears likely that SigF plays a key role in stress adaption by upregulating AscarD transcription. However, quantification of the expression of SigF under stress conditions is missing. Including data on SigF expression under starvation and other stress conditions will strengthen this study further.sigF transcript levels in M. smegmatis under different conditions and found that there is no significant induction of sigF expression under the various tested conditions including the stationary phase, which is similar to the previous report . However, previous studies have shown that SigF is active under stress conditions, especially in stationary phase. In this work, we also found that the SigF-dependent expression of AscarD is highly induced in the stationary phase. Moreover, based on the published transcriptome data of M. smegmatis , we identified 39 genes with strict SigF recognition motif (GTTT-N(15-17)-GGGTA) in their promoter regions, and importantly, 37 of these genes are upregulated at least 5-fold in the stationary phase. All these cues suggest that SigF does function at stationary phase. As for the lack of coordination of SigF expression and function, we believe that it is caused by post-translational regulation. As reported, the σ factors are post-translationally regulated by a partner switching system, in which the anti-σ factors sequester the σ factor from the transcription machinery, and the anti-σ factor antagonists release the repression of σ factors. In M. smegmatis, the SigF partner switching system contains an anti-σ factor RsbW and several anti-σ factor antagonists  . We have compared the transcript levels of these genes at different growth phases by analyzing our published transcriptome data  and found that the expression of some anti-σ factor antagonists  is significantly upregulated at the mid-stationary phase (MSP) (see Thank you for this suggestion. We have measured the MSP) see . Therefo2. Similarly, how transcript levels are being measured and normalized should be described where presented in the text/legend with perhaps more detail referenced in the Methods. As normalized data is provided, changes could technically be due either to increases of CarD transcript or decreases in the sigA transcript. Evidence or measurements that the sigA transcript doesn't change appreciably under these conditions needs to be provided. The same is technically true of the gel-based measurements of protein levels. If one assumes that the amount of material loaded in each lane is the same, then the data clearly shows what the authors suggest. However, this was not specifically mentioned anywhere leaving open the possibility that the over-expression of the control proteins results in an apparent repression of CarD. Please address this.sigA, we used 16S rRNA as an internal reference and measured its expression under various conditions. The results showed that there was no appreciable change in the sigA transcript level under the tested conditions , a large amount of CarD is still retained, meaning that the deletion of "AAAS" motif prevents the CarD degradation by Clp protease. These results further strengthen the notion that Clp protease degrades CarD under stress conditions. We have added this content to the manuscript.Thank you very much for this important suggestion. We have deleted the "AAAS" motif from the 4. Although the paper presents a clear picture of two mechanisms (Proteolytic degradation and anti-sense) individually on CarD levels, the effects of these mechanisms on cellular phenotypes is less completely explored. For example, for the stationary phase dependent regulation of CarD, does this mechanism effect stationary phase survival? Similarly, what about survival/expression chages under the stress conditions examined? Some data is given, but more exploration of the cellular effects of these mechanisms would make the paper more appealing to a broad audience. With their ability of tune CarD levels via graded manipulation of asCarD or Clp, the authors could learn much more about the physiologic and global transcriptional effects of these regulatory mechanisms and this would be a major advance for the field. Relevant assays would include, (I) stationary phase survival assays and (I) RNA sequencing of cells with different levels of asCarD or Clp in different conditions to look at the global effects of these manipulations.ascarD promoter (AsM) in the genome, which relieved AscarD’s regulation of CarD; we also knocked out the AAAS motif of CarD in the genome (AAAS_del), which relieved the degradation of CarD by Clp protease. In addition, we also constructed a double deletion strain with ascarD promoter and CarD AAAS motif (AsM/AAAS_del), which relieved the regulation of CarD by both AscarD and Clp protease. Next, we investigated the survival of these strains under stationary phase and stress conditions. The results showed that relieving the AscarD regulation of CarD has a weaker impact on the survival of mycobacterial cells, while relieving the regulation of Clp protease of CarD has a moderate impact on the survival of mycobacterial cells. However, simultaneous removal of the two regulatory mechanisms strongly affects the survival of mycobacterial cells , whereas RNA-seq of the clpP2 conditional mutant strain and its control strain revealed 2487 DEGs . These high numbers are not surprising, as both CarD and ClpP2 are global regulators in mycobacteria. We also classified the affected genes according to their involvement in major cellular pathways (using the KEGG pathway tool), but again, both overexpression of AscarD and depletion of ClpP2 were shown to affect multiple pathways in mycobacteria. It should be noted that the main goal of this work is to prove the regulation of CarD by anti-carD antisense RNA and Clp protease, and we believe we have proved that. Considering that a brief analysis of the RNA-seq data may not contribute much to the main conclusions, and an in-depth study of RNA-seq data may distract attention from the subject of this manuscript, we intend to report this result in future communications.As for RNA sequencing experiment, we carried out RNA-seq on an AscarD overexpression strain and a 5. Although the individual effects of Clp and asCarD are documented, the paper would be stronger if it explored the relative importance and interaction of these two mechanisms in different conditions. Are they simply additive as the model figure suggests? Does the relative importance of each mechanism differ depending on the condition studied? Relevant experiments that could strengthen this point are: (1) explore conditions in which one mechanism is dominant (2) changing asCarD levels or ClpP in the same cell during different stress conditions to see if one mechanism is dominant.2155, AsM, AAAS_del, and AsM/AAAS) under stationary phase and stress conditions. The results showed that, compared to the wild-type strain, the level of CarD in the AsM (AscarD promoter mutation) strain slightly increased, while the level of CarD in the AAAS_del (CarD “AAAS” motif deletion) strain increased significantly . The specific mechanisms of protein level changes need to be further addressed. We have now replaced Figure 1A with the new data.The changes in 2. It will also be interesting to see the temporal increase and decrease in the levels of CarD and AscarD transcripts during normal and stress conditions.carD and AscarD at 0.5 h and 1 h after stress stimulation. The results showed that the carD transcript level increased to varying degrees under these stress conditions . Do the authors have any data on whether or not this is true in mycobacteria? What is known, if anything, about direct transcriptional control of the CarD promoter? In the absence of AscarD , what happens to CarD transcript levels?Rhodobacter sphaeroides, CarD negatively regulates its own promoter, and the negative effect mainly depends on the extended -10 element (TGN) and the adjacent spacer of the promoter, which are highly conserved in the Rhodobacter carD promoters. To explore whether mycobacterial carD also auto-regulates, we analyzed carD promoters from 91 different mycobacterial species. The results showed that all analyzed carD promoters contain a “TANNNT” -10 elements and a “TGN” extended -10 elements  in the spacer immediately upstream of the extended -10 element contributes greatly to the autoregulation of Rhodobacter CarD. In Mycobacterium, there is no similar spacer, but there is a highly conserved dinucleotide "CG" immediately upstream of the extended -10 element . Since the -10 elements recognized by SigA and SigB are somewhat similar in mycobacteria, we speculate that SigA and SigB jointly regulate the carD expression, with SigA as the main σ-factor responsible for the basal transcription of carD, and SigB as an alternative σ-factor responsible for the stimulated transcription of carD under stress conditions, which may also be the reason for the increasing carD expression after treatment with DNA-damaging agents .As for the direct transcriptional regulation of the ions see . We speccarD transcript levels in the absence of AscarD, we have, in fact, shown this result in Figure 5—figure supplement 1, where there is no significant change in carD transcription in the AscarD knockdown strain. Furthermore, during this revision process, we successfully constructed an ascarD promoter mutant strain that hardly expressed AscarD; when we measured the transcription of carD in this mutant strain, we found that the carD transcript level did not change significantly. It is currently difficult to explain why the absence of AscarD does not significantly affect the level of carD transcription.As for the change of 6. Can the authors comment on whether the proteolytic degradation of CarD will have an effect on the production of CarD in a feed-back loop?R. sphaeroides, the expression of carD is negatively auto-regulated, so the expressed CarD proteins repress the expression of the carD genes and thereby form a feedback loop. Based on existing data, it is difficult to judge whether (or how) mycobacterial CarD is auto-regulated, so it hard to say whether the proteolytic degradation of CarD has an effect on the production of CarD in a feed-back loop.In our opinion, whether there is a feed-back loop mainly depends on whether CarD is auto-regulated. In 7. RT-qPCR: No documentation of no RT reactions is given. This is important to exclude dna contamination.Thank you, we have addressed this problem.8. Some justification of the use of KatG as a loading control in the western blots is needed, since this is unusual and subject to regulation under stress.Thank you for this suggestion. We have described this in the Methods and Materials section as follows.For internal reference protein, we used SigA or KatG as indicated. In the stress stimulation experiments , SigA was used as an internal control because its level is not affected by the test stimuli. However, SigA protein level in the stationary phase is significantly lower than that in the log phase , so when we studied the protein levels in several growth phases, SigA was not used as an internal control. After many tests, we found that the protein level of KatG remained basically unchanged throughout the growth period; therefore, KatG was used as an internal control in experiments at different growth phases. .9. The rnaseq data presented in the discussion should be moved to results if it is new data. If it is previously published it can be discussed, but the table should be moved to Supplementary information.Thank you for this advice. The RNA-seq data shown in the discussion was previously published, we have provided a reference and moved it to Supplementary information.10. A question that arises is whether CarD itself has any effect on the levels of AscarD or whether in published ChIP-seq data, CarD can be seen on the AscarD promoter. Do the authors have any data or comments here?lpqE, carD and cysS, but has no (or very weak) binding affinity to the ascarD promoter. Considering that CarD is recruited to promoters by the RNA polymerase, and that the binding of RNA polymerase to the ascarD promoter depends on the function of SigF, we speculate that the small peak of CarD seen at the ascarD promoter could be due to the weak transcriptional activity of AscarD under the conditions of the ChIP-seq experiment.Thank you for your suggestion. We have analyzed the binding site of CarD through the published ChIP-seq data. As shown in References:Mycobacterium tuberculosis. Cell Rep 5, 1121-1131.1. Cortes, T., Schubert, O.T., Rose, G., Arnvig, K.B., Comas, I., Aebersold, R., and Young, D.B. (2013). Genome-wide mapping of transcriptional start sites defines an extensive leaderless transcriptome in Rhodobacter sphaeroides promoters lack a crucial RNA polymerase recognition feature, enabling coordinated transcription activation. 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