Due to their multifaceted functions, it is crucial for host fitness to maintain strict regulation of these parasitic sequences to ensure proper growth and development. This review explores how subsets of retrotransposons have undergone evolutionary exaptation to enhance the complexity of mammalian genomes. It also highlights the significance of regulating these elements, drawing on recent studies conducted in human and murine systems.Retrotransposons are invasive genetic elements that constitute substantial portions of mammalian genomes. They have the potential to influence nearby gene expression through their  Transposable elements (TEs) make up almost half of the genomes of both mice and humans . These gpro, gag, pol, and env genes. Such proviruses are defined as full-length or complete ERVs and can retrotranspose throughout the genome autonomously. Numerous studies have delineated the mechanism of ERV transcription and reverse transcription [Drosophila melanogaster revealed that ERVs can utilize alternative end joining , a DNA double-strand break (DSB) repair pathway, to synthesize the second strand through circularization [Retrotransposons are defined as class I TEs, which replicate by copying and pasting themselves throughout the genome in a process called retrotransposition. Akin to retroviruses that have RNA genomes, retrotransposons reverse transcribe their RNA transcripts into double-stranded DNA (dsDNA), which can integrate into different loci of the host genome. Based on the presence of long terminal repeats (LTRs), retrotransposons are divided into LTR retrotransposons and non-LTR retrotransposons. Endogenous retroviruses (ERVs), which comprise 8% and 10% of the human and mouse genome, respectively, are classified as LTR retrotransposons and arise from ancient infections of retroviruses. After integration, the elements, termed proviruses, are identical to their exogenous counterparts, possessing two LTRs flanking the viral cription ,4,5,6; hrization . Non-LTRrization . These erization ,12. SINErization . They deNovel integration and recombination events of active retrotransposons in the genome can cause spontaneous mutations and deletions, leading to dysregulation of neighboring genes and genome instability. Therefore, host cells have evolved a plethora of defense systems involving repressive epigenetic mechanisms to regulate these elements.DNMT1 mutants are embryonic lethal, potentially due to the derepression of genes and other TEs as a consequence of the global loss of 5mC [DNA methylation is one of the best-characterized epigenetic mechanisms. The addition of a methyl group on cytosine to generate 5-methylcytosine (5mC) functions to repress retrotransposons in various cell types ,15,16. Us of 5mC ,18,19,20s of 5mC ,22,23,24s of 5mC . At thess of 5mC ,27,28,29cis-regulatory elements during neural lineage establishment [Post-translational modifications (PTMs) of histone proteins play a crucial role in the regulation of retrotransposon activities. Numerous studies have identified several PTMs involved in the silencing of specific elements, including methylation of histone H3 at lysine 9 (H3K9), histone H3 at lysine 27 (H3K27), demethylation of H3 lysine 4 (H3K4), and deacetylation of H3K9 ,35,36,37lishment .In addition to H3K9 methylation, H3K27 tri-methylation (H3K27me3) represents another crucial epigenetic modification involved in retrotransposon regulation. H3K27me3 is deposited by the Polycomb-repressive complex 2 (PRC2), which subsequently recruits Polycomb-repressive complex 1 (PRC1), facilitating chromatin compaction ,46. NotaIn addition to catalyzing repressive epigenetic marks, the removal of active modifications can also prevent retrotransposon activities. For example, lysine-specific demethylase 1  represses retrotransposons not regulated by DNA methylation, through the demethylation of H3K4, a well characterized active mark . In ESCsDrosophila melanogaster, piRNAs are small RNAs of approximately 24–30 nucleotides, which are loaded into Argonaute3 (Ago3) and Aubergine (Aub) proteins to target and degrade the complementary retrotransposon transcripts in the cytoplasm [Besides epigenetic silencing, hosts have evolved multiple strategies for repressing TE transcripts. A crucial mechanism involves the action of P-Element-induced wimpy testis (PIWI)-interacting RNAs (piRNAs) and PIWI proteins, which play significant roles in both transcriptional and post-transcriptional silencing of retrotransposons with high specificity. First discovered in ytoplasm   complex, which assists in H3K9me3 maintenance by recruiting SETDB1, employs an RNA decay system that involves the nuclear exosome targeting (NEXT) complex to selectively degrade L1 transcripts in ESCs  Figure . In addiN6-methyladenosine (m6A) is the most prevalent modification in eukaryotic mRNA molecules that controls gene expression in diverse biological processes [The rocesses ,56. Methrocesses ,58,59,60rocesses ,62, mRNArocesses , and enhrocesses . For insrocesses . Transcrrocesses ,67. TherWithin the nucleus, the spatial organization and packaging of the genome exhibit a non-random nature, characterized by highly regulated hierarchical chromatin structures . During It is noteworthy that retrotransposons, such as LINEs and SINEs, also contribute to the organization of chromatin. Active transcription of L1, for instance, plays a role in regulating global chromatin accessibility during early mouse embryonic development . In thiscis-regulatory interactions, where promoters and enhancers within the same TAD generally exhibit coordinated activities [These compartments can be further segregated into kilobase-to-megabase sized topologically associated domains (TADs). Chromatin within the same TAD interacts more frequently than across TADs ,79. TADstivities ,79. Furttivities . The distivities ,81; thertivities . In the tivities ,84. One-tivities ,86, as wtivities ,88. Additivities . Moreovetivities . Notablytivities .n = 103,798) between 18 mouse strains [Slc36a1 gene, presumably by establishing differential higher-order chromatin interactions [n = 99,349) [SLc47a2 gene as compared with nine other strains lacking the provirus [Given their capacity for mobilization, retrotransposons have produced TE variants (TEVs) that differ in integration sites between species or are polymorphic within a species. The identification and characterization of TEVs can provide a deeper understanding of the roles of these elements in the host cells. In the context of genome architecture, retrotransposition of specific elements contributes to the expansion of the repertoire of potential CTCF binding sites in the host genomes. Throughout evolution, ancient CTCF binding sites derived from retrotransposon TEVs can underlie species divergent higher-order chromatin structures . Notably strains . A subseractions . In addi 99,349)  is almos 99,349) , highlig 99,349) . In partprovirus . Taken tcis-regulatory modules and splicing donor/acceptor sites that increase host transcriptome variability. Retrotransposons have been evolutionarily co-opted to function as alternative promoters for crucial host gene networks to drive the lineage-specific expression [Cdk2ao1 gene (Cdk2ap1ΔN) in preimplantation embryos to promote proliferation and implantation [Although most retrotransposons have lost their capacity to mobilize or are silenced by epigenetic mechanisms, a proportion still harbors pression ,39,93,94pression ,39. Otheantation . Since rantation   genes [In addition to their elopment . As mouselopment . On the elopment . Mechanielopment   genes .Intriguingly, retrotransposons with detrimental effects on host cells also play a role in early development. Utilizing single-cell RNA sequencing (scRNA-seq), Singh et al. proposed the concept of “REject cells” in human embryos, a previously undefined cell population enriched with active young retrotransposons, DNA damage, and apoptotic signatures. These cells are selectively eliminated from the developmental process and contribute to maintaining the overall fitness of the embryos . In miceSYNCYTIN gene, which is derived from the env gene of human ERV subfamily W (HERV-W) elements [pregnancy-specific glycoprotein (PSG) genes in syncytiotrophoblasts, which are required to facilitate the remodeling of the maternal–fetal interface for proper placentation [PSGs in normal pregnancy, and knockout of the LTR8B element in the intron of PSG5 downregulates the gene’s expression [PSGs [vascular endothelial growth factor A (VEGFA) and endoglin (ENG) gene dysregulation. These genes are known to be involved in pregnancy complications such as preeclampsia. Moreover, retrotransposons can impact innate immunity, which is important for fetal protection in hemochorial placentas. Upon viral infection, innate immunity is an essential line of defense against invading pathogens. This mechanism can be initiated by recognizing dsDNA or double-stranded RNA (dsRNA) in the cytoplasm, which in turn triggers signaling pathways for interferon (IFN) production [In placental mammals, retrotransposons are crucial for establishing important gene expression patterns in the placenta, including the elements ,103. In entation ,105,106.pression . Interesoduction . While toduction , type IIoduction . Wickramcis-regulatory function. For example, DNA demethylation activates L1s to drive neural gene expression as alternative promoters in human neural progenitor cells (NPCs) [LINC01876 expression is crucial for proper neurodifferentiation and cerebral organoid development [Drosophila AD model, the dysregulation of Gypsy, Copia, and Het-A retrotransposons has been identified [Retrotransposons contribute to brain development and evolution through its s (NPCs) . Moreoveelopment . Intereselopment . Notablyelopment , schizopelopment , Alzheimelopment , both L1elopment ,118,119,elopment . Additioentified .In humans, the loss or mutation of TDP-43 has been observed in the brains of patients with ALS, AD, and Parkinson’s disease ,125,126.Drosophila HD model, inhibiting reverse transcription activity has been shown to rescue HD-related neurodegenerative phenotypes in the eyes and to extend the lifespan of HD flies, potentially by restoring genome stability. While animal models have provided valuable insights into human developmental defects and diseases, they are limited by genome composition and species-specific TEs. Moreover, complex phenotypes involving diverse gene regulation can also be attributed to TE polymorphism. Recently, Modenini et al. investigated human polymorphic non-reference TEs (nrTEs) and identified evolutionarily young nrTE candidates that may potentially increase the risk of schizophrenia [TE transcription may also play a role in the pathogenesis of Huntington’s disease (HD) . In a Drophrenia . Howevercis-regulatory roles [The epigenomes of cancer cells are radically reprogrammed to favor tumor survival and progression. For instance, global DNA hypomethylation and focal promoter hypermethylation have long been observed in various cancers ,130,131.ry roles ,136,137.ry roles . The derry roles . Manipulry roles ,141. Morry roles . Liang eWith the advancement of functional genomic technologies such as scRNA-seq, RIC-seq, and Hi-C, our understanding of how retrotransposons participate in host genomes’ functions and their evolutionary expansion has significantly improved. Precise spatial and temporal retrotransposon activities, mediated by various epigenetic mechanisms, are crucial for essential physiological processes. Disruptions in these regulatory mechanisms, both at the transcriptional and post-transcriptional levels, caused by intrinsic and extrinsic factors like viral infections, can contribute to disease pathogenesis. Therefore, modulating retrotransposon activities and comprehending their functions offer new perspectives on diagnostic tools and therapeutic opportunities.However, findings related to TEVs have limitations in translational research due to the influence of polymorphic ERVs on intra-species divergence . To addr


Nucleosome remodeling factors regulate the occupancy and positioning of nucleosomes genome-wide through ATP-driven DNA translocation. While many nucleosomes are consistently well-positioned, some nucleosomes and alternative nucleosome structures are more sensitive to nuclease digestion or are transitory. Fragile nucleosomes are nucleosome structures that are sensitive to nuclease digestion and may be composed of either six or eight histone proteins, making these either hexasomes or octasomes. Overlapping dinucleosomes are composed of two merged nucleosomes, lacking one H2A:H2B dimer, creating a 14-mer wrapped by ~ 250 bp of DNA. In vitro studies of nucleosome remodeling suggest that the collision of adjacent nucleosomes by sliding stimulates formation of overlapping dinucleosomes.To better understand how nucleosome remodeling factors regulate alternative nucleosome structures, we depleted murine embryonic stem cells of the transcripts encoding remodeler ATPases BRG1 or SNF2H, then performed MNase-seq. We used high- and low-MNase digestion to assess the effects of nucleosome remodeling factors on nuclease-sensitive or “fragile” nucleosome occupancy. In parallel we gel-extracted MNase-digested fragments to enrich for overlapping dinucleosomes. We recapitulate prior identification of fragile nucleosomes and overlapping dinucleosomes near transcription start sites, and identify enrichment of these features around gene-distal DNaseI hypersensitive sites, CTCF binding sites, and pluripotency factor binding sites. We find that BRG1 stimulates occupancy of fragile nucleosomes but restricts occupancy of overlapping dinucleosomes.Overlapping dinucleosomes and fragile nucleosomes are prevalent within the ES cell genome, occurring at hotspots of gene regulation beyond their characterized existence at promoters. Although neither structure is fully dependent on either nucleosome remodeling factor, both fragile nucleosomes and overlapping dinucleosomes are affected by knockdown of BRG1, suggesting a role for the complex in creating or removing these structures.The online version contains supplementary material available at 10.1186/s12864-023-09287-4. The eukaryotic genome is packaged into chromatin, which is composed of structural and regulatory proteins, DNA, and RNA and condenses into higher-order structures that regulate DNA access by DNA binding factors , 2. The S. cerevisiae, hexasomes or tetrasomes have been observed at “wide” nucleosome depleted regions (NDRs), which are generally promoters of highly-transcribed housekeeping genes, and have been described as “fragile nucleosomes”, as they are observed in only light nuclease treatment conditions . A. A36]. AEGFP knockdown) MNase-seq dataset, as well as a published MNase-seq dataset  over TSSs and DHSs Fig. a-c. We fTo identify a possible link between transcription and OLDN formation, we sorted the MNase-seq datasets by nascent transcription from the same cell line over both TSSs and gene-distal DHSs  or Smarca5 (encoding SNF2H), using EGFP as an unexpressed control esiRNA target as previously described [Smarca4) and SNF2H (Smarca5), demonstrating effective RNA depletion of each ATPase. We validated the reproducibility of our MNase-seq experiments through a principal component analysis of genome-wide 10 kb bins  [2 fold change assigned by DESeq2 [2 fold change  also displayed the highest OLDN occupancy across all experimental conditions. We performed similar analyses on published RNA-seq data comparing Smarca5 knockout and wildtype ES cells (data from GSE112136) [2 fold change and OLDN occupancy, suggesting that OLDN occupancy may be less reliant on SNF2H-regulated gene expression than BRG1-regulated gene expression. To further interrogate the relationship between OLDN formation and these nucleosome remodelers, we analyzed public ChIP-seq data for BRG1 and SNF2H binding in ES cells  . We ranky DESeq2  and plotE112136)   knockdown  and high-digestion (30U) MNase-seq datasets we generated, we examined another understudied alternative nucleosome structure: the fragile nucleosome, known to occupy promoter regions in etazoans , 50–54. revisiae , 54, we own Fig. . These eons Fig. a,b. Furtons Fig. d-f.Smarca4 or Smarca5, suggesting that nucleosome remodeling factors may create fragile nucleosomes.Our data are consistent with previous fragile nucleosome profiling experiments, in which only low MNase amounts result in nucleosome profiles at certain loci, including promoter regions and CTCF binding sites –17. To vSmarca4 depletion at established  and novel  fragile nucleosome-bound genomic locations, we next examined whether this change occurs over other genomic locations, including nucleosome remodeling factor and pluripotency factor binding sites. Using published ChIP-seq datasets [Smarca4 knockdown, however, nucleosome occupancy over BRG1 binding sites is virtually indistinguishable between the MNase conditions  knockdown MNase-seq, again suggesting the low MNase profile reflects fragile nucleosomes .Having identified a reduction in fragile nucleosome occupancy upon datasets , 50, we Smarca4 knockdown on fragile nucleosomes over gene-distal DHSs, and because of the established requirement for BRG1 in ES cell pluripotency [Smarca4 and Smarca5 depletion would lead to a reduction of fragile nucleosome occupancy. Indeed, when visualized over OCT4  knockdown MNase-seq data, while OLDN occupancy is increased. The effect of Smarca4 knockdown on mononucleosomes is stronger under low MNase conditions, while the opposite is true of OLDN occupancy; effects are more muted under low MNase conditions than high MNase conditions  and non-genic (H3K4me1-marked) loci Fig. . These oSmarca4 knockout, and depletion of BRG1 leads to increased OLDN occupancy, suggesting a repressive role for esBAF in regulating OLDNs . Cells were cultured in DMEM base medium (Gibco) with 10% fetal bovine serum , 1X nonessential amino acids (Gibco), 2mM L-glutamine (Gibco), β-mercaptoethanol (Acros Organics), and 1000U/mL leukemia inhibitory factor (LIF). Cells were passaged every 48 h using trypsin (Gibco) and split at a ratio of ~ 1:8 with fresh medium. Routine anti-mycoplasma cleaning was conducted  and cell lines were screened by PCR to confirm no mycoplasma presence.ES-E14TG2a (E14) embryonic stem cells from male VCL9108; ; a gift Endoribonuclease-digested short interfering RNAs (esiRNAs) were generated as previously described –70. BrieTRIzol reagent (Invitrogen) was used to isolate total RNA according to manufacturer’s protocol. Quality and quantity were assessed via NanoDrop (ThermoFisher) and RNA was snap-frozen in liquid nitrogen and stored at -80 °C.Gapdh transcript abundance. Technical replicates represent the average of three individual qPCR reactions for each target/condition group. Error bars shown represent the standard deviation of qPCR replicates. Biological replicates  with homemade reverse transcriptase. cDNA was used as a template in qPCR reactions using 2X SYBR FAST mix (KAPA) on a Lightcycler 96 (Roche) with 5 µM specific primers (see Supplementary Table 7) were pelleted and rinsed in Dulbecco’s phosphate-buffered saline (Gibco). Cells were then crosslinked with 1% formaldehyde in PBS for 10 min at room temperature in a volume of 8 mL, inverting every 3 min. After adding 2 mL 2.5 M glycine, cells were mixed thoroughly by repeated inversion and left for 5 min at room temperature to quench the reaction. Cells were then pelleted and rinsed twice with PBS, snap-frozen in liquid nitrogen, and stored at -80 °C. Cells were thawed, re-suspended in cell lysis buffer  and 3 µM CaCl2) at a proportion of 3 mL buffer for 10 M cells, and left to rotate for 15 min at 4 °C. Micrococcal nuclease (MNase) enzyme (Takara) was aliquoted into three pre-chilled tubes in amounts of 0U, 10U (low MNase), or 60U (high MNase). Lysed cells were equally added to each prepared tube and chromatin was digested for 5 min at 37 °C. The MNase digestion reaction was chelated with 10 mM EDTA at room temperature, and samples were treated with RNase A for 2 h at 37 °C before adding 0.01% SDS and Proteinase K and incubating at 55 °C overnight to reverse crosslinks. Samples were purified using a phenol-chloroform-isoamyl alcohol (PCI) extraction, followed by chloroform extraction and ethanol precipitation, then resuspended in nuclease-free water. One µg of purified chromatin was set aside for library preparation and deep sequencing , and the remainder of each sample was run on ethidium bromide-stained 1.5% agarose gel to verify sample quality and isolate a parallel overlapping dinucleosome enriched MNase-seq sample. The section of the gel corresponding to ~ 200–300 bp fragments was gel-extracted (Qiagen) to enrich for putative overlapping dinucleosomes. Paired-end libraries of MNase-digested DNA were prepared as described previously [MNase-seq was performed as previously described . esiRNA-eviously . Brieflyeviously . BetweenPaired-end fastq files were trimmed to 25 bp and mapped to the mm10 genome with bowtie2  . Mapped To determine if nucleosome remodeling factor knockdowns had a significant effect on OLDN occupancy, we applied Friedman tests to generated heatmap data matrices, correcting for multiple comparisons using the Benjamini, Krieger, and Yekutieli method with an FDR/q-value cutoff of 0.001. For MNase-sensitive particle occupancy, we applied two-tailed Wilcoxon matched-pairs signed rank tests to the differences between occupancy of individual regions under low and high MNase digestion, comparing each knockdown back to the EGFP KD control, with a p-value cutoff of 0.001. All statistical calculations were performed in GraphPad PRISM 9.3, 1% SDS) and cleaned using AMPureXP beads (Beckman Coulter). Cleaned DNA was used as a template for qPCR or for input into library builds. Library preparation was performed using NEB Next II Ultra DNA kit with 14 cycles of PCR amplification. Libraries were sequenced on a NextSeq2000 at the HSSC Sequencing Core facility, located at the Children’s Hospital of Pittsburgh.MNase-ChIP was performed as described . BrieflyMNase-ChIP samples were prepared as described above. Eluted and cleaned DNA was used as a template in qPCR reactions using 2X SYBR FAST mix (KAPA) on a Lightcycler 96 (Roche) with 5 µM specific primers  . Mapped Paired-end fastq files were trimmed and filtered using Trim Galore , then alBelow is the link to the electronic supplementary material.Supplementary Material 1


Escherichia coli promoters under single knockdown of 183 TF genes, illustrating more than 200,000 possible TF-gene responses in one experiment. We perform PPTP-seq for E. coli growing in three different media. The PPTP-seq data reveal robust steady-state promoter activities under most single TF knockdown conditions. PPTP-seq also enables identifications of, to the best of our knowledge, previously unknown TF autoregulatory responses and complex transcriptional control on one-carbon metabolism. We further find context-dependent promoter regulation by multiple TFs whose relative binding strengths determined promoter activities. Additionally, PPTP-seq reveals different promoter responses in different growth media, suggesting condition-specific gene regulation. Overall, PPTP-seq provides a powerful method to examine genome-wide transcriptional regulatory networks and can be potentially expanded to reveal gene expression responses to other genetic elements.Elucidating genome-scale regulatory networks requires a comprehensive collection of gene expression profiles, yet measuring gene expression responses for every transcription factor (TF)-gene pair in living prokaryotic cells remains challenging. Here, we develop pooled promoter responses to TF perturbation sequencing (PPTP-seq) via CRISPR interference to address this challenge. Using PPTP-seq, we systematically measure the activity of 1372  E. coli.Measuring gene expression responses for every transcription factor (TF)-gene pair in living prokaryotic cells is challenging. Here the authors report pooled promoter responses to TF perturbation sequencing (PPTP-seq) using CRISPRi, which they use to address this problem in  Escherichia coli, for example, possesses at least 183 confirmed TF-encoding genes and 2619 operons according to RegulonDB 10.01, corresponding to ~500,000 (183 × 2619) possible TF-operon responses. RNA-seq and microarrays are the most common methods for exploring genome-scale transcriptomic responses to a perturbed TF activity, but identifying responsive genes for all TFs would require hundreds of RNA-seq or microarray experiments, consuming excessive resources and time9. Recent advances in single-cell RNA-seq and CRISPR-based perturbations allowed systematic analysis of transcriptional response to various genetic perturbations in eukaryotes12. However, these methods have not been able to illustrate prokaryotic TRNs at whole genome scales due to the low coverage of bacterial single-cell RNA-seq (less than 10%)13. Genome-wide promoter mutational scanning presents another high-throughput method for identifying cis-regulatory elements (CREs) on promoters18. While powerful, this method alone, without prior knowledge of TF binding sites, cannot provide information about which TF a promoter can respond to. Moreover, when multiple TFs bind to the same location, mutational scanning data alone cannot quantify the effect of each TF.Information about the bacterial cellular response is often encoded in promoters and affected by transcription factors (TFs), which control both the timing and level of gene expression. Characterizing the transcriptional regulatory network (TRN) between TFs and promoters is essential for functional genomics, systems biology, and genetic engineering applications. The genome-scale TRN contains massive amounts of information: E. coli TRN in three different grow media  and obtain the most comprehensive TF-promoter activity profiles so far. Our study uncovers multiple regulatory responses, including TF autoregulatory responses, complex transcriptional control of metabolic pathways, promoter responses to co-regulation from multiple TFs, and condition-specific gene regulation.To overcome these limitations, we develop a massively parallel method to measure genome-wide promoter activities in response to CRISPR interference (CRISPRi)-based TF knockdown (TFKD). This method called Pooled Promoter responses to TF Perturbations via sequencing (hereafter PPTP-seq), allows us to examine the regulatory effects in living cells of hundreds of TFs and thousands of promoters of a bacterial genome, all with a single assay lasting just two weeks. Further, PPTP-seq produces homogeneous data for evaluating all regulatory responses under identical growth conditions, avoiding extensive normalization steps in data processing. We apply PPTP-seq to study the 19 and a promoter-reporter cassette to measure the activity of a specific promoter under the TF-repressed condition  to repress a specific TF in the genomeion Fig. . A self-E. coli, we constructed a combinatorial plasmid library consisting of both a sgRNA library and a promoter library  had substantially reduced reads . Among them, alaS, dicA, and dnaA are essential genes whose deletion led to cell death27. CRISPRi polarity29 can also lead to the repression of essential genes that are located downstream of a targeting TF within the same operon. This explains the substantially reduced reads for iscR, mraZ, and nrdR.CRISPRi can impair cell growth if essential genes are targeted. Seven TF-targeting sgRNAs  compared to their corresponding controls containing non-targeting sgRNAs (Supplementary Note qseB and ttdR).We further evaluated the CRISPRi repression efficiency using both TF’s promoter activity measured from PPTP-seq , confirming the high quality of our pooled measurements. The other five combinations were missing in all three replicates due to their low read counts. This small dataset also contained the regulatory effects of five known direct interactions and one indirect interaction in RegulonDB1 , using a plate-reader-based whole-cell fluorescence assay . Additionally, fold change in promoter activity upon TFKD measured from PPTP-seq is also qualitatively consistent with that measured from EcoMAC microarray32 for a few known regulatory interactions in RegulonDB1  correlated with transcript levels measured from RNA-seqq < 0.01; Fig. 14.We quantified promoter activity changes by TFKD relative to negative controls  , specifically sulfur metabolism (eco00920), ion transport (GO:0006811), and iron ion homeostasis (GO:0055072)  variable promoters with significant activity change under at least one TFKD condition (Supplementary Note −3) Fig. , specifiism” P = .4 × 10−3We systematically investigated whether a TF’s promoter can be affected by itself or other TFs. A perturbation-response network between TFs was constructed, where activation and repression represent down- and upregulation by CRISPRi knockdown of an upstream TF, respectively Fig. . In miniq < 0.01) in minimal glucose medium, including two autoregulatory interactions, PgrR and ComR, not present in RegulonDB , in which transcriptional regulation was not well characterized in bacteria. OCM is tightly associated with the synthesis of nucleotides, amino acids, and two essential cofactors―tetrahydrofolate (THF) and S‐adenosylmethionine (SAM), and it plays important roles in cell survival and growth. However, due to the presence of multiple metabolic cycles and interconnected pathway structures, dissecting the regulatory function of OCM remains challenging.metA, metE, and metK, were observed to be upregulated by metJ knockdown, recapitulating the known feedback control of SAM biosynthesis via MetJ40  of the PPTP-seq identified responses  in RegulonDBses Fig. . For theE. coli47 and between eukaryotic transcriptional response and TF binding datasets48. This can be caused by low TF expression levels, low TF activity (affected by other molecules), and/or complex regulatory patterns. We individually examined two promoters that have multiple different TF binding sites . On average, the relative binding strength per TF was slightly weaker for regulatory TF-promoter pairs than for non-regulatory TF-promoter pairs . For each TF binding site, we focused on the binding location, TF concentration, and binding strength. We found that binding sites from both regulating and non-regulating TFs were centered around the transcription start site (TSS) of a promoter50 Fig.  and that50 Fig. . Additioirs Fig. . This unirs Fig. . ResultslacZ promoter by CRP was not detected in minimal glucose medium due to low cAMP concentration54, but was observed in LB medium. Similarly, activation of the maltose transporter malK by MalT was observed in LB medium but not in the minimal glucose medium, because expression of malT requires CRP activation55. On the other hand, activation of metE by MetR was observed in minimal glucose and glycerol media but not in LB medium. This is likely caused by repression of metE by MetJ at high SAM concentration56. Our data show that many regulatory responses are condition-dependent  due to the truncation of additional operator sites located outside the promoter region70.Limitations of PPTP-seq include false positives caused by CRISPRi polarity in bacteria71 could also be integrated to quantify combinatorial regulatory effects , a derivative of E. coli MG1655 with an aTc-inducible dCas9 expression cassette integrated at the attB site of its genome72. NEB 10-β competent E. coli (New England Biolabs) was used for cloning. Promoter activities were measured in M9 minimal glucose (0.4%) medium (supplemented 1 mM thiamine and 25 ng/μL kanamycin), M9 minimal glycerol (0.5%) medium (supplemented 1 mM thiamine and 25 ng/μL kanamycin), or LB medium (supplemented 25 ng/μL kanamycin). All primer sequences are listed in Supplementary Data PPTP-seq experiments were performed in E. coli promoter collection originally constructed by the Alon lab21 was obtained from Horizon Discovery Ltd. (# PEC3877). All strains in this collection, except for those containing control vectors (pUA139 and pUA66), were grown overnight in LB medium in 96-well deep-well plates. A library was generated by mixing 300 μL of overnight cell cultures from each well using an Eppendorf epMotion® 96 Pipettor. Pooled plasmids of this collection were extracted from the mixture using a Maxiprep kit (QIAGEN). We noted that “promoter regions” in Alon’s collection were defined as entire intergenic regions flanked by about 50–150 bp into the adjacent coding regions21; however, many of these “intergenic regions” are located in the middle of an operon and do not contain promoter sequences. These non-promoter regions were excluded from the data analysis.An E. coli that have at least one known target supported by binding of purified proteins or site mutation. Among them, 169 TFs function as monomers or homo-oligomers (encoded by single genes), and 12 TFs function as hetero-dimers or hetero-oligomers (encoded by more than one gene). The 181 TFs are encoded by 183 unique genes; thus, a sgRNA library targeting 183 different TF genes was designed. , 181 TFs (including heteromultimeric TFs) were identified in gfpmut2 gene under the control of the lacZ promoter and a constitutively expressed sgRNA targeting the coding sequence of genomic lacI gene using DNA from previously described plasmids75. A self-cleaving ribozyme sequence (RiboJ) was inserted upstream of gfpmut2 to prevent the untranslated region of different promoters from affecting the mRNA structure. A mCherry gene was inserted downstream of the kanR gene in the same operon as a control for extrinsic noise. All these genes were cloned on a pSC101 vector backbone , resulting in a plasmid library that we named pYH156_sgRNA_lib. The quality of the sgRNA plasmid library was verified by high-throughput sequencing. All 188 sgRNAs were observed in the library.The combinatorial library was constructed in two steps. In all cloning steps, Q5 hot-start high-fidelity DNA polymerase (New England Biolabs #M0493L) was used for PCR amplification. The backbone of the plasmid pYH156 was amplified using primers prYH068 and prYH069. In the first step, the vector backbone was first ligated with the sgRNA library by Golden Gate assembly in 96-well PCR plates. The ligation products were pooled and transformed into NEB 10-β competent cells. After growing overnight, more than 10E. coli promoter collection21 using primers prYH070 and prYH071, and the vector backbone containing the sgRNA library was amplified from pYH156_sgRNA_lib using primers prYH072 and prYH073. These two PCR products were gel-purified and then ligated by Golden Gate assembly. The ligation products were purified using a DNA Clean & Concentrator kit (Zymo Research), and ~3.6 μg of purified ligation products were electroporated into 200 μL of fresh NEB 10-β competent cells using four electroporation cuvettes. The cells were plated on large LB agar plates (245 × 245 mm), resulting in about 8.2 × 107 individual clones. Transformants were scraped from the large agar plates, and the resulting combinatorial library plasmids . After a few hours of adaptation, 500 μL of the cultures were added to 50 mL of the target medium containing 1 μM aTc as inducer. The induced cells were grown at 37 °C until OD600 reached 0.1–0.2. At this point, the cell cultures were supplemented with 250 μg/mL chloramphenicol to halt protein production and were kept on ice until sorting.Sorting experiments were performed in triplicate using cultures prepared in different weeks. For each replicate, 100 μL of the combinatorial library glycerol stock was thawed and inoculated in 250 mL of LB medium. When an OD76 using a four-way purity sorting mode. The number of bins was chosen by considering both sorting time (5–10 h) and expression level difference between adjacent bins (less than 1.7-fold change). Both previous sort-seq experiments77 and simulations23 have shown that the use of 16 bins in our case allows reliable quantification of mean gene expression level. For each replicate, the flow rate during cell sorting was kept constant, and each bin was sorted for the same amount of time so that the number of cells collected in each bin was proportional to the phenotypic density in the population77. The numbers of cells sorted in each bin for each replicate were recorded for normalization in data analysis.Cell sorting was performed on either FACSAria II (for cells grown in the M9 glucose) or FACSMelody (for cells grown in LB and M9 glycerol media) cell sorters (BD Biosciences). To control extrinsic protein production noise, events were gated around the mean fluorescence of mCherry, which is constitutively expressed on the reporter plasmid. Cells were sorted into 16 equally sized contiguous bins according to their GFP fluorescence intensity on a log scaleIn each bin, sorted cells were added to an equal volume of LB medium with 50 ng/μL kanamycin and were grown overnight. Plasmids were extracted from 3 mL of overnight cell cultures using miniprep kits. From each bin, 50 ng of purified plasmids were amplified using the KAPA HiFi PCR Kit (Kapa Biosystems) for 20 cycles, using primers prYH071 and prYH087. The PCR products were purified using DNA Clean & Concentrator kits (Zymo Research) and then ligated to Illumina sequencing adapters via Golden Gate assembly. The adapter-labeled products were gel-purified to select DNA sizes between 400 bp and 1.5 kb. To enrich ligated products, gel-purified DNA products were subjected to another round of PCR using primers prYH128 and prYH129 for 8 cycles. Amplified adapter-labeled samples from each bin were then mixed in ratios that ensured that the number of reads was proportional to the number of cells sorted in each bin. The pooled sample was sequenced using partial lanes on a NovoSeq S4 XP Platform (2 × 150) at the Genome Technology Access Center of the McDonnell Genome Institute.E. coli MG1655 (U00096.3) using Bowtie2 v2.3.578. For each promoter-end read, the genomic coordinates from the alignment were used to find the closest downstream operon and the closest downstream gene in the genome using BEDTools v2.29.279. Some non-promoter sequences whose end cannot be mapped to the first 200 bp of the coding sequence of the first gene in the operon were excluded for subsequent analysis. The remaining promoters are listed in Supplementary Data Paired-end reads were separately aligned to the pre-defined sgRNA library and the complete genome of 82  divergence between the inferred distribution and 1.5 to 105 for the M9 glucose growth condition and 101.5 to 105.5 for the LB and M9 glycerol growth conditions); (2) variants with estimated cell counts To control the fitting quality, fitted parameters of variants with any of the following features were set as “not available (NA)” for subsequent analysis: (1) variants with mean GFP intensity not within our detection limits  with access number GSE213624. Functional annotation and enrichment analysis were performed using the DAVID web server85.We adopted a method of mean comparison for log-normal distribution600 of 0.1, followed by RNA extraction using 2 mL culture (Zymo Research Quick-RNA kit). All the RNA samples were then treated with DNAse (Zymo Research) and reverse transcribed to cDNA with RevertAid First Strand cDNA Synthesis Kit (Thermo). The cDNA samples were then subjected to qPCR using the PowerTrack SYBR Green Master Mix (Thermo) and a Quantstudio 3 instrument (Applied Biosystems). The constitutive gene dnaK was used as an internal control, and fold change for each gene was calculated using the 2−ΔΔCT method86.Triplicate colonies were grown overnight in LB. Cultures were then diluted by 200-fold into 5 mL M9 glucose medium and grown for 1 h. Cells were then induced with 1 μM aTc and grown for an additional 2 h. Cultures were then diluted 900-fold in M9 glucose containing 1 μM aTc and grown to ODfadE, PglyA, PlacZ, PmarR, and PmetA) and ten sgRNAs targeting nine TF genes  and a negative control (NC_84). These plasmids  at 220 r.p.m. and 37 °C. OD600 and GFP fluorescence were measured every 10 min over 10 h. Customized MATLAB scripts were used for data processing, including the background correction and OD600 normalization. GFP/OD600 values for each strain remained nearly constant when OD600  was between 0.08 and 0.32. The steady-state GFP expression levels were calculated by averaging GFP/OD600 values from the two closest measurements above and below OD600 = 0.2 for all strains.We individually constructed a subset of the combinatorial library consisting of five promoters 3. Second, to generate different TF expression levels, the aTc inducer was added in concentrations of 0, 2, and 20 nM. Third, for cell cultures that contained FeSO4 or Fe2(SO4)3, steady-state periods were identified by examining the GFP/OD600 and OD600 data because OD600 measurements were affected by FeSO4 or Fe2(SO4)3, especially when OD600 was low.Reporter plasmids containing selected promoters for validation were obtained from the promoter libraryE. coli identified from DAP-seq42 were screened, merged, and mapped to E. coli promoters investigated in this study using BEDTools v2.29.279. All binding sites associated with TF-promoter pairs missing in our PPTP-seq dataset were excluded from subsequent analysis. TSS information was obtained from RegulonDB v 10.01. TF concentration was estimated from the ribosome-profiling results87.All the BED files for TF binding peaks in The center position of each TF binding site relative to the TSS was calculated as the relative position to TSS. For promoter regions with multiple TSSs, only the TSS closest to the start codon of the downstream gene was analyzed. The binding strength between a TF and its binding site is defined by fold enrichment over the background in DAP-seq experiments. If a promoter had multiple binding sites for a TF, only the binding site with the highest binding affinity was analyzed. The relative binding strength per TF was calculated as the fold enrichment for the TF over the background, divided by the maximum fold enrichment for the TF. The relative local binding strength was calculated as the fold enrichment for a TF bound on a promoter over the background, divided by the maximum fold enrichment for all TFs bound on the promoter.No statistical methods were used to predetermine the sample size. PPTP-seq experiments were performed in three biological replicates for M9 glucose condition and two biological replicates for M9 glycerol and LB conditions to assess the reproducibility of these measurements. The means and standard deviations between replicates were calculated and used in statistical analysis. Sequencing reads for cells sorted into bin #1 after growth in M9 glycerol medium were excluded from data analysis due to potentially unwanted mutations. Data exclusion after log-normal distribution fitting is described in “Methods: NGS data processing”.Further information on research design is available in the Supplementary InformationReporting SummaryDataset 1Dataset 2Dataset 3Dataset 4Dataset 5Dataset 6Dataset 7Dataset 8Dataset 9Dataset 10Dataset 11Description of Additional Supplementary FilesPeer Review FileSource Data


Heparanase is the sole endoglucuronidase that degrades heparan sulfate in the cell surface and extracellular matrix (ECM). Several studies have reported the localization of heparanase in the cell nucleus, but the functional role of the nuclear enzyme is still obscure. Subjecting mouse embryonic fibroblasts (MEFs) derived from heparanase knockout (Hpse-KO) mice and applying transposase-accessible chromatin with sequencing (ATAC-seq), we revealed that heparanase is involved in the regulation of chromatin accessibility. Integrating with genome-wide analysis of chromatin states revealed an overall low activity in the enhancer and promoter regions of Hpse-KO MEFs compared with wild-type (WT) MEFs. Western blot analysis of MEFs and tissues derived from Hpse-KO vs. WT mice confirmed reduced expression of H3K27ac . Our results offer a mechanistic explanation for the well-documented attenuation of inflammatory responses and tumor growth in Hpse-KO mice. Heparanase, the sole mammalian heparan sulfate (HS)-degrading endoglycosidase, belongs to the wider class of enzymes known as ‘retaining glycosidases,’ which catalyze hydrolytic cleavage of glycosidic bonds with net retention of anomeric stereochemistry . It emplHeparanase regulates multiple biological activities in cancers, e.g., enhancing tumor growth, angiogenesis, and metastasis ,3,4. HepA key avenue through which heparanase accomplishes its multiple effects on cells and tissues is by regulating the bioavailability of HS-bound growth factors, chemokines, and cytokines, priming the tissue microenvironment. HS resides on the cell surface and the ECM in the form of proteoglycans (HSPGs), where, among other activities, it modulates cytokine bioavailability and functions as a co-receptor . BindingLikewise, heparanase has been found in the cell nucleus . NuclearTo gain insight regarding the role of nuclear heparanase, we applied the ATAC-seq for genome-wide analysis of the transposase-accessible chromatin genome-wide  in mousePreparation of mouse embryonic fibroblasts (MEFs): Heparanase knockout (Hpse-KO) (C57BL/6 genetic background) mice were generated as previously described [2 at 37 °C. The experimental protocol was conducted according to local ethical regulations.escribed  and mainescribed . PurifieTransposase-accessible chromatin using ATAC-seq: ATAC-seq was performed as previously described [escribed . Brieflyescribed . After tData processing: ATAC-seq raw data were mapped to mm10 with Bowtie2. The reads with mapping quality over 30 were kept and duplication reads were removed with Picard. MACS2 was used to perform peak calling with -q 0.01 -nomodel -shift 0 parameters. The peaks that overlapped with ENCODE genome blacklist were discarded. The read counts within peaks were generated with bedtools and the genome tracks were visualized using vig IGV.Differential peak analysis and genomic annotation: Differential peak analysis was performed with DEseq2 package, keeping the differential peak list with threshold values of |logFC| > 1, FDR < 0.01. Genomic annotation was performed with the ChIPseeker package in R with seven genomic features: 3′ UTR, 5′ UTR, exon, intergenic region, intron, TSS, and TTS. The ChIP-seq data for ChromHMM were downloaded from Gene Expression Omnibus with the number GSE90895 and only the wild-type samples were downloaded. In total, 15 states were identified: Genic Enhancer 1 (EnhG1), Strong Transcription (Tx), Bivlant Transcription (BivTx), Repressed Polycomb (ReprPC), Bivlant Enhancer (EnhBiv), Weak Enhancer (EnhWk), Weak Transcription (TxWk), Active enhancer 1 (EnhA1), Genic Enhancer 2 (EnhG2), Active enhancer 2 (EnhA2), Active TSS (TssA), Flanking TSS upstream (TssFlnkU), Quiescent/low (Quies), ZNF genes & repeats (ZNF/Rpts), and Heterochromatin (Het). Bedtools documentation was applied to perform overlapping and to assign chromatin states into peaks. KEGG analysis was conducted with clusterProfiler package in R.Super-enhancer calling and function characterization: Super-enhancers were identified with ROSE software with H3K27ac ChIP-seq data (GSE90803). Bedtools were used to analyze overlapping peaks between super-enhancer regions and chromatin-accessible regions. Ontological enrichment was performed by g: Profiler and visualized by Cytoscape setting FDR range from 0 to 0.001. Homer mm10 database and the super-enhancer bed files were used to calculate motif occurrences with a cut-off of p-value < 0.01.Western blotting: Tissues of embryos and adult organs were collected from mice and homogenized with Polytron in ice-cold lysis buffer containing 20 mM Tris pH 7.4, 150 mM NaCl, 1% NP-40, 0.5% Sodium Deoxycholate, 0.1% SDS, and protease inhibitors. Cells were lysed in the same buffer and incubated on ice for 30 min. After centrifugation, the supernatants were collected and protein concentration was determined using the BCA method . The lysates of tissues  and cells  were heated at 98 °C for 5 min before SDS-PAGE, followed by transferring to a polyvinylidene fluoride (PVDF) membrane . After blocking with 5% non-fat milk for 1 h, the membranes were probed sequentially with primary and secondary antibodies. Antibody dilutions were: anti-H3K27ac 1:2500 , anti-H3K27me3 1:1000 , anti-H3K4me1 1:1000 , anti-H3K9me3 1:1000 , anti-H3 1:1000 , and HRP-conjugated goat anti-rabbit IgG 1:10000 . Signals were visualized using chemiluminescent HRP substrate . Band intensity was quantified by the Image Lab software .t-test. Values of p < 0.05 were considered significant.Statistical significance was analyzed by the 2-tailed unpaired Student’s Using the primary MEFs derived from Hpse-KO and WT mice, we collected two sets of ATAC-seq data. Examination of the heparanase gene loci identified enriched peaks in the heparanase promoter region of WT cells, which were missing in Hpse-KO cells, confirming the null expression of heparanase in the Hpse-KO cells A. DetectA total of 13,000 ATAC-seq peaks downregulated or upregulated were identified A,B. ReprThe 15 chromatin states were used to re-annotate the ATAC-seq peaks and the significantly differential peaks to highlight differences in the distribution of the chromatin states F. In HpsRepresentative SE-associated genes are marked as rank ordering of super-enhancers A. Gene oTo determine if the epigenetic analysis of H3 in the EhA and TSS regions of Hpse-KO samples is of relevance to biological functions, we examined histone modification of H3 by Western blot analysis of the MEF cells. Using several anti-H3K antibodies recognizing different epitopes, we found that the level of H3K27ac was significantly reduced, while the level of H3K27me3 was substantially elevated in the Hpse-KO compared with WT cells. There was no difference in the levels of H3K4me1 or H3K9me3 between the two cell types A. These The sole endoglucuronidase in mammalians, heparanase, was thought to play a vital role in HS catabolism; surprisingly, elimination of the heparanase gene in mice did not lead to accumulation of HS, and only resulted in averagely longer HS chains . The sinImportantly, heparanase also displays non-enzymatic biological actions  . SeveralTo gain some insight into the epigenetic regulation of heparanase function, we applied the advanced technique of ATAC-seq (assay for transposase-accessible chromatin using sequencing) to analyze the local accessibility of chromatin in embryonic fibroblasts (MEFs) derived from Hpse-KO and WT mice. Since the regions of gene transcription are controlled by cis-acting DNA elements, including enhancers, silencers, and promoters, we compared gene expression profiles in these regions. Super-enhancer is a special region in mammalian genomes driving transcription of important genes, controlling and defining cell identity. The EhA and TSS regions are chromatin states enriched with H3K27ac, the most frequently used marker of super-enhancer recognition . Genes mThe combined involvement of heparanase in epigenetic gene regulation and tumor progression has been further elucidated in studies demonstrating that chemotherapy, in addition to its cytotoxic effects on tumor cells, can support tumor re-growth and spread ,39,40. TCollectively, these results suggest a regulatory role of heparanase in chromatin packaging, accessibility, and activity. The increased activity of histone acetyltransferases (HAT) in cells expressing high levels of heparanase and the suppressed expression of H3K27ac and H3K4 tri-methylation (histone methyltransferases) in Hpse-KO cells/tissues suggest an important regulatory function of heparanase in histone modification and activity. The overall low activity in regions that control gene transcription in Hpse-KO MEFs may be associated with suppressed inflammatory responses and tumor growth in Hpse-KO mice ,42,43. I


Honey bees are important species for the study of epigenetics. Female honey bee larvae with the same genotype can develop into phenotypically distinct organisms (sterile workers and fertile queens) depending on conditions such as diet. Previous studies have shown that DNA methylation and histone modification can establish distinct gene expression patterns, leading to caste differentiation. It is unclear whether the histone methylation modification H3K4me1 can also impact caste differentiation. In this study, we analyzed genome-wide H3K4me1 modifications in both queen and worker larvae and found that H3K4me1 marks are more abundant in worker larvae than in queen larvae at both the second and fourth instars, and many genes associated with caste differentiation are differentially methylated. Notably, caste-specific H3K4me1 in promoter regions can direct worker development. Thus, our results suggest that H3K4me1 modification may act as an important regulatory factor in the establishment and maintenance of caste-specific transcriptional programs in honey bees; however, the potential influence of other epigenetic modifications cannot be excluded. Honey bees are eusocial insects and an important model organism for studies of caste development and caste differentiation in social insects. Their division of labor is mainly based on the differentiation of castes (queen and worker) . After dDNMT3 has a jelly-like effect on developmental trajectories, resulting in a significantly higher proportion of queens with fully developed ovaries [Caenorhabditis elegans [Drosophila melanogaster [DNA and histone modifications are thought to primarily affect transcriptional events. The establishment, maintenance, and regulation of transcriptional programs during development depend on chromatin plasticity . Recent  ovaries . Differe ovaries . H3K27ac ovaries . However ovaries . Histone ovaries  or argin ovaries  residues ovaries ,18,19,20 ovaries , Caenorh elegans , and Dronogaster , and evenogaster ,25. HoweHundreds of genes involved in caste differentiation have been identified in honey bees ,26. DiffTo investigate the chromatin structure of honey bees, we determined, for the first time, the genome-wide distribution of H3K4me1. We detected H3K4me1 enrichment around the transcriptional start sites (TSS) of genes in both queen larvae and worker larvae . These rp < 0.05 and fold change > 2). In 2Q (2nd instar queen) vs. 2W (2nd instar worker), we identified 36 unique H3K4me1 peaks in 2Q and 380 in 2W . However, there was a difference in the distribution of unique peaks between 4Q and 4W ; 60% of the unique peaks in 4W were enriched in the promoter region, while 61% of the unique peaks in 4Q were enriched in intronic regions. The data for differential peaks between queens and workers were consistent with the results for unique peaks. In 2Q vs. 2W, we identified 18 differential H3K4me1 peaks in 2Q and 326 in 2W . However, there was a difference in the distribution of differential peaks between 4Q and 4W ; 55% of unique peaks in workers were found in promoter regions, while 54% of unique peaks in queens were found in intronic regions. In order to study the functional significance of the caste-specific promoter H3K4me1, we performed a motif enrichment analysis using the MEME website . The sequence of Drosophila melanogaster was used to annotate the honey bee motifs. We identified 2Q and 2W transcription factor binding sites that were significantly enriched, and the top three transcription factor binding sites were identical  and differential peaks . In addition, there were significant correlations between differential H3K4me1 peak signals and transcript levels  is shown as an example of a physio-metabolic worker-specific gene [P450-6a17 and IGF, showed significant differences in gene expression and H3K4me1 enrichment in both TSS and gene ontology regions  [JHAMT  [Hex70a  [Hsp90  [Vg genes of workers was significantly higher than that in queens at the 2nd and 4th instars. These results further support the role of H3K4me1 modification in regulating transcription, and reveal the effect of H3K4me1 and transcript co-regulation on caste differentiation in honey bees.In addition, we selected five genes with established roles in the caste differentiation of honey bees for verification, namely JHe , Vg (vitC406088) , JHAMT (C724216) , Hex70a C726848) , and HspC408928) . Our traC408928) ,35,36,37C408928) . VitelloWe used ChIP-seq to characterize genome-wide caste-specific chromatin patterns in honey bees and revealed the chromatin patterns related to reproductive division of labor in social insects. Combined with an RNA-seq analysis, the specific modification of H3K4me1 appeared after the critical time point for caste differentiation. There was no significant difference in H3K4me1 modification patterns between worker larvae and queen larvae until the irreversible stage of caste differentiation. A significant number of queen–worker chromatin differences are associated with caste-specific transcription. Importantly, a number of enhancers identified in caste-specific regions may be involved in honey bee caste differentiation.Drosophila melanogaster [JHe, Vg, Hex70a, and JHAMT). Signaling pathways such as FoxO and TOR are known to influence caste differentiation in honey bees [Hex70a and Vg) are related to reproductive division of labor and nutrient metabolism [Previous studies of nogaster ,40, micenogaster ,42, and nogaster ,44,45. Inogaster ,46,47. Mnogaster . The resnogaster . Studiesnogaster . In addiney bees ,49, and tabolism ,50,51. Tcis-regulatory role. Monomethylation of histone H3 at lysine 4 (H3K4me1) is a hallmark of activated enhancers in both vertebrates and invertebrates [cis-regulatory DNA sequences and can increase the transcription of target genes. The opening of repressive enhancer–promoter loops leads to transcriptionally active enhancer–promoter regulation as a fundamental mechanism underlying differential transcriptional regulation [cis, also modulates gene expression [We found that H3K4me1 modification is closely involved in the modification of worker larvae, and is mainly involved in pathways related to honey bee caste differentiation. Caste-specific differences in H3K4me1 were mainly detected in the promoter and intronic regions. Queen-specific H3K4me1 was mainly located in intronic regions. In contrast, worker-specific H3K4me1 was mainly localized in promoter regions, close to transcription initiation sites. In addition, abundant caste-specific H3K4me1 in promoter regions was associated with high levels of caste-specific gene expression, suggesting that these regions play an important tebrates ,52. Enhagulation ,54. The pression . Therefopression ,57,58,59Taken together, we speculate that the worker-specific promoter H3K4me1 region has the hallmarks of an active enhancer. In addition, most worker genes enriched in the promoter H3K4me1 region are also transcription factors, suggesting that enhancers are associated with upstream and downstream genes during the development of worker castes. Queen-specific regions may also be caste-specific enhancers; however, further identification is needed.Apis mellifera) were obtained from Jiangxi Agricultural University in 2020. Queens were restricted for 6 h (8 am to 2 pm) to a plastic frame designed by Pan et al. [2O three times. Filter paper was used to drain the water from the larvae, and larvae were placed immediately in liquid nitrogen. Whole larvae were used for sequencing, as in previous studies, since they were very small .Honey bees  was downloaded from NCBI and indexed using Bowtie 2 (v2.3.3). ChIP-seq samples were mapped to this indexed genome using Bowtie 2 with the default parameters. Detailed mapping statistics for each sample are available in p-values were corrected for multiple comparisons with a false discovery rate . Genes with p-adj ≤ 0.05 were defined as DEGs. Detailed statistics are available in Hierarchical Indexing for Spliced Alignment of Transcripts  was used to align the RNA-seq reads to the reference genome (Amel_HAv3.1). Expression levels were reported as FPKM values to normalize the length of the annotated transcripts and the total number of reads aligned to the transcriptome. Differential expression was analyzed using the DESeq2 R package (1.30.0). The 2nd and 4th instar larvae of queens and workers were sampled. Three samples were collected for each type of larvae, with each sample coming from a different colony. Therefore, a total of 12 larval samples across three different colonies were evaluated.GAPDH was used as a reference gene. The primer sequences were designed using Prime Primer 6.0  was established. The PCR conditions were as follows: 95 °C, 5 min; 94 °C, 2 min; 40 cycles ; 72 °C, 10 min. To establish the melting curve of the qRT-PCR product, the primers were heated slowly with a gradual increase of 1 °C every 5 s from 72 °C to 99 °C. The data were analyzed using the 2−ΔΔCT method.qRT-PCR was performed according to previously described methods . Brieflyimer 6.0 . A 10 μLSignificant differences in H3K4me1 modification between queen and worker larvae were observed during caste differentiation in honey bees. Chromatin modification can regulate the transcription of the genes that determine the caste. Furthermore, H3K4me1 modification was closely involved in the regulation of the development of worker larvae, and may be an important modification in the worker development pathway. These findings clearly establish the contribution of histone methylation to honey bee development, and may contribute to further research on caste differentiation and developmental plasticity.


Nostoc sp. PCC 7120 is a filamentous cyanobacterium that, under nitrogen limitation, behaves as a multicellular organism with division of labor among two different cell types that depend on each other, the vegetative CO2-fixing cells and the nitrogen-fixing heterocysts. The differentiation of heterocysts depends on the global nitrogen regulator NtcA and requires the specific regulator HetR. To identify antisense RNAs potentially involved in heterocyst differentiation, we assembled the Nostoc transcriptome using RNA-seq analysis of cells subjected to nitrogen limitation  in combination with a genome-wide set of transcriptional start sites and a prediction of transcriptional terminators. Our analysis resulted in the definition of a transcriptional map that includes >4,000 transcripts, 65% of which contain regions in antisense orientation to other transcripts. In addition to overlapping mRNAs, we identified nitrogen-regulated noncoding antisense RNAs transcribed from NtcA- or HetR-dependent promoters. As an example of this last category, we further analyzed an antisense (as_gltA) of the gene-encoding citrate synthase and showed that transcription of as_gltA takes place specifically in heterocysts. Since the overexpression of as_gltA reduces citrate synthase activity, this antisense RNA could eventually contribute to the metabolic remodeling that occurs during the differentiation of vegetative cells into heterocysts.Transcriptomic analyses using high-throughput methods have revealed abundant antisense transcription in bacteria. Antisense transcription is often due to the overlap of mRNAs with long 5′ or 3′ regions that extend beyond the coding sequence. In addition, antisense RNAs that do not contain any coding sequence are also observed.  The transcription of bacterial genomes extends beyond the regions classically defined as genes. Antisense transcription of the complementary strand of coding regions is very frequently observed, not only because of an overlap between transcripts that are produced in adjacent genes, but also as autonomous, nonprotein-coding transcripts, whose expression is sometimes regulated in response to environmental changes. The consequences of antisense transcription are still a matter of debate, but accumulating evidence points to possible regulatory roles. In this context, the observation that antisense transcription takes place from nitrogen-regulated promoters controlled by the cyanobacterial regulators NtcA or HetR suggests that these antisense transcripts may play a role in adaptation to nitrogen stress and/or the differentiation of functional heterocysts.2 fixation  category, includes transcripts that require HetR for induction and, therefore, are specifically related to heterocyst differentiation. Two groups of genes can be defined in this category (E-DIF and L-DIF) based on their temporal pattern of induction during the early (E) or late (L) stages of differentiation, respectively  in ectively . Most geectively , 7.Nostoc sp. PCC 7120, ∼30% of TSSs determined using differential RNA-seq (dRNA-seq)  . In the RNA-seq) . In prev or subjected to nitrogen deprivation for 9 or 24 h (time 9 and time 24), two time points suitable for the analysis of transcriptional changes associated with the early and late stages of heterocyst differentiation, respectively. RNA from two biological replicas of each condition was sequenced to a depth of 17–21 million paired-end reads each sample. A transcriptome was assembled as detailed in Materials and Methods in combination with a previously available data set of transcription start sites obtained by dRNA-seq   (2 (FC 9–0) > 3]. Also, in agreement with previous transcriptomic studies (hep genes involved in polysaccharide deposition) show higher expression at 9 h than at 24 h after nitrogen removal. In contrast, genes whose expression occurs in mature heterocysts (such as nif genes that encode nitrogenase and associated functions) show higher expression at 24 h than at 9 h after nitrogen removal. studies , genes eNostoc sp. PCC 7120 genes . Therefore, this transcriptome may represent a good overview of the overall transcriptome of our organism, including housekeeping genes expressed independently of environmental condition. We have analyzed some global parameters of the assembled transcriptome, such as the length distribution of transcripts, 5′UTRs and 3′UTRs  above 3. In 23 cases, the asRNA is an mRNA containing at least one coding sequence  are shown in Fig. as_fraE (TU01524), which corresponds to overlapping transcription of the 3′UTR of fraF mRNA (2 (FC 9-0) = 1.95 falls below the threshold log2 (FC 9-0) > 3 applied above.Among the TUs classified as asRNAs, we selected for further analysis those showing logce Table . Among tce Table . Most ov2 (FC 9-0) > 3 correspond to TUs that do not contain any annotated coding sequence. These noncoding antisense transcripts are produced from TSSs annotated as antisense TSS (aTSS) or nTSS (noncoding TSS)  or NtcA-binding sites  (2 (FC 9-0) below 3. Data for the regions corresponding to as_glpX   = 1.98]   (Table 2as_leuA) . All thras_leuA) . Two nit = 2.27]  and to a = 1.98] , both trbona fide, noncoding asRNAs.Taken together, these observations suggest that both the NtcA-regulated responses  and the HetR-regulated responses  include abundant transcription of asRNAs, either because of overlap between mRNAs located in a head-to-head or tail-to-tail disposition or due to the transcription of 2 (FC 9-0) > 3 that fall in the category of noncoding asRNAs (i.e. are not mRNAs) and are transcribed antisense to genes with a previous annotation  to regulation .Observed overlap of antisense protein-encoding mRNAs with long 3′UTRs could be the result of improper transcription termination. However, the presence of noncoding antisense RNAs with strict transcriptional regulation strongly suggests a regulatory function for this type of RNAs. We have selected for further validation nitrogen-regulated TU with logntcA mutant strain, but was still observed in the hetR mutant strain, confirming that these asRNAs belong to the NtcA regulon and the DEF category, according to . Again, we verified nitrogen-regulated transcription from the corresponding aTSS along a time course of nitrogen deprivation by primer extension, obtaining products of the expected sizes . The accumulation of as_gltA was verified by Northern blot, which revealed, in agreement with the RACE results, an abundant band slightly above 200 nt and another less abundant band, above 300 nt, as well as some signals above the 400 nt size marker. No expression of the as_gltA RNA was observed in the hetR mutant  and a strain that overexpresses an antisense RNA of as_gltA (OE_as_as_gltA). The 245 nt fragment defined as the main product of as_gltA transcription by Northern blot  was introduced in Nostoc, generating strain OE_as_gltA. To remove as_gltA without altering its genomic region, we cloned the same fragment in reverse orientation downstream of the trc promoter to generate a perfect antisense that would act as a sponge, neutralizing as_gltA. The resulting plasmid (pMBA105) was introduced in Nostoc, generating strain OE_as_as_gltA. We have previously used this strategy to deplete different transcripts in Nostoc . We next studied the effect of the changes in the amount of as_gltA on the accumulation of gltA mRNA by Northern blot  overlap another TU in the antisense orientation. We have focused on nitrogen-regulated antisense transcripts as a potential source of regulation in the context of adaptation to nitrogen deficiency and, specifically, in the differentiation of heterocysts.Antisense transcription is widespread in all organisms. A significant proportion of the transcripts identified in bacteria that have been analyzed using high-throughput methodologies are in antisense orientation, from E. coli  to Staphlococcus  or Prochd genome . By usind genome  and a prbona fide asRNAs, includes noncoding RNAs transcribed antisense to an mRNA  or, less frequently, in a divergent (head to head) disposition may overlap because their long 5′ or 3′UTRs invade the transcriptional space of adjacent genes. In these cases, the consequences of nitrogen-regulated transcription of a given transcript go beyond the expression of the gene(s) included, potentially affecting the expression of oppositely oriented adjacent genes via antisense transcription , a gene essential for diazotrophic growth . The commonly accepted concept of operon, a genomic arrangement in which genes involved in the same metabolic pathway appear clustered together to facilitate coupled regulation, may be extended to antisense regulation. The genomic arrangement of some overlapping antisense transcripts may also be used for coupled regulation.Overlapping asRNAs could be particularly abundant in cyanobacteria as a consequence of the absence of the Rho termination factor, which has been involved in the repression of pervasive, including antisense, transcription , 30. Becc growth , overlapListeria monocytogenes and Staphylococcus aureus, a subset of asRNAs are transcribed from SigB-dependent promoters  cycle. We can envision several consequences of such a reduced flow. The two substrates of citrate synthase, oxalacetate and acetyl-CoA would be more available for alternative pathways upon inhibition of this enzymatic activity in the heterocyst. Heterocysts synthesize cyanophycin, an aspartate–arginine polymer  from PCR-generated DNA templates using the primers indicated in the Table Strand-specific Details of fluorescence quantification are given in the Supplementary Materials and Methods.The crude extracts were prepared in 50 mM Tris-HCl pH 8 buffer by mechanically disrupting the cells using glass beads. Protein concentration was determined using the Bradford method  and citrThe Wilcoxon–Mann–Whitney test and Student's t test were used to determine statistical significance. The use of each test and the number of biological samples can be found in the figure legends.pgad187_Supplementary_DataClick here for additional data file.


A) is an essential protein and the primary sigma factor in Mycobacterium tuberculosis (Mtb). However, due to the absence of genetic tools, our understanding of the role and regulation of σA activity and its molecular attributes that help modulate Mtb survival is scant. Here, we generated a conditional gene replacement of σA in Mtb and showed that its depletion results in a severe survival defect in vitro, ex vivo, and in vivo in a murine infection model. Our RNA-seq analysis suggests that σA either directly or indirectly regulates ∼57% of the Mtb transcriptome, including ∼28% of essential genes. Surprisingly, we note that despite having ∼64% similarity with σA, overexpression of the primary-like σ factor SigB (σB) fails to compensate for the absence of σA, suggesting minimal functional redundancy. RNA-seq analysis of the Mtb σB deletion mutant revealed that 433 genes are regulated by σB, of which 283 overlap with the σA transcriptome. Additionally, surface plasmon resonance, in vitro transcription, and functional complementation experiments reveal that σA residues between 132-179 that are disordered and missing from all experimentally determined σA-RNAP structural models are imperative for σA function. Moreover, phosphorylation of σA in the intrinsically disordered N-terminal region plays a regulatory role in modulating its activity. Collectively, these observations and analysis provide a rationale for the centrality of σA for the survival and pathogenicity of this bacillus.SigA (σ Mycobacterium tuberculosis (Mtb) enters the body through nasal airways and deposits in the lower lungs, wherein the primarily alveolar macrophages engulf the bacteria  to recognize the promoter and facilitate DNA unwinding around the transcription start-point. Contrary to eukaryotes, wherein three RNAP are present, bacteria encode only one RNAP consisting of 2 subunits of α, one subunit each of β, β′, and a ω subunit  inhibits its binding to promoters in the absence of RNAP (Mycobacterium smegmatis σA (σAMsm), especially in the N-terminal region. Furthermore, the N-terminal region of σAMsm is predicted to be intrinsically disordered  results in enhanced intracellular growth of the W-beijing strain of mycobacteria  identity between the structured DNA recognition regions of σA and σB, including −10 and −35 region-binding amino acid residues. Deletion of sigB renders the pathogen sensitive to heat, oxidative, surface stress, and antibiotics  What is the effect of depleting σA on the survival of Mtb within the host? (ii) What is the effect of σA depletion and σB KO on the global transcriptome of Mtb and functional redundancy of σA and σB?, (iii) Can overexpression of σB rescue phenotypic defects observed upon σA depletion?, (iv) The role of the unique N-terminal extension of σA? (v) How does phosphorylation modulate σA function? Here, we describe results from experiments designed to address these aspects of σA-mediated modulation of the expression profile in Mtb. A highlight is the intriguing finding that a disordered extended N-terminal polypeptide, hitherto ‘unseen’ in structural descriptions of the Mtb RNAP complex, plays a dominant role in σA activity.Collectively, our knowledge regarding the structure-function and regulatory aspects of σA is a 528 amino acid essential protein with an extended 207 amino acid–long disordered N terminal region preceding the four α helical domains (A). Domain 2 interacts with the −10-promoter element, domain 3 with the extended −10 promoter region, and domain 4 interacts with the −35 region . sigA was cloned into pFICTO, and the construct was electroporated into Mtb-H37Rv (Rv) to generate merodiploid strain (Rv::sigA) (B). The expression of FLAG-σA from integrative copy is under anhydrotetracycline (ATc) regulation. In the absence of ATc, the Psmyc promoter (A from the merodiploid is significantly lowered upon the addition of ATc (B). Subsequently, sigA at the native loci was replaced with a hygr-sacB cassette with the help of a specialized transduction methodology to generate RvΔsigA (C and D). Analysis of FLAG-σA levels at different days post-ATc addition revealed a significant reduction from day 3 (E). In vitro growth analysis suggested that while the growth of RvΔsigA was comparable to Rv in the absence of ATc, depletion of FLAG-σA resulted in compromised growth, eventually resulting in a 4-log fold  difference between the growth of parental and mutant strain (F). Importantly, depletion of FLAG-σA (RvΔsigA +ATc) significantly reduced the intracellular survival in the peritoneal macrophages as compared to either Rv or RvΔsigA-ATc–infected cells (G). Together, these results confirm the generation of conditional RvΔsigA mutant and the criticality of σA for both in vitro and ex vivo survival of the pathogen.σ domains A. Domain5 region . The fun5 region A and S1.v::sigA) B. The expromoter  is activn of ATc B. Subseq RvΔsigA . The fid RvΔsigA , C and Dom day 3 E. In vitt strain F. Imported cells G. Togethin vivo survival of the RvΔsigA mutant. Mice infected with Rv or RvΔsigA through the aerosolic route and the colony forming units (CFUs) enumerated 24 h post infection (p.i) indicated efficient and equivalent implantation of WT and mutant bacilli in the lungs of mice (A and B). To examine the impact of depleting σA, a set of animals infected with RvΔsigA were provided doxycycline (Dox) in the drinking water (A). The data suggest that depletion of σA from the start of infection results in a significant reduction (2.5–3.5 log10 fold) in the bacillary load (RvΔsigA + Dox) at 4 weeks p. i compared with either Rv + Dox or RvΔsigA - Dox in both lungs and spleen of the infected animals (B and C). We sought to examine the impact of depleting σA from an established infection. Mice were infected with Rv or RvΔsigA, and the infection was allowed to be established for 2 weeks (D). Subsequently, RvΔsigA-infected animals were divided into four groups; wherein two groups were given Dox in the water for the subsequent weeks, and the CFUs were enumerated (D). Compared with Rv + Dox or RvΔsigA -Dox, a decrease of 1.5 and 2.5 log10 fold was observed in the lungs of RvΔsigA +Dox mice at 6- and 10-weeks p. i, respectively (E). A similar trend was observed in the mice spleens (F). Together, this data suggests that while σA is critical for the survival of Mtb within the host, the impact of depleting σA is less significant during the chronic stage of infection.We used a murine infection model to evaluate  of mice , A and Bng water A. The da animals , B and C 2 weeks D. Subsequmerated D. Comparectively E. A simi spleens F. TogethA is proposed to regulate majority of the mycobacterial transcriptome under normal growth conditions. To identify the regulons and pathways that σA modulates, we performed RNA-seq of RvΔsigA grown in vitro in the absence and presence of ATc. Towards this, RNA was extracted from RvΔsigA cultured in the absence or presence of ATc for 3 or 4 days. The RNA obtained 4 days post-ATc addition was degraded, and hence we used RNA extracted from RvΔsigA in the absence or presence of ATc on day 3 for the experiment. The experiment was performed in biological triplicates, and the principal component analysis (PCA) showed appropriate clustering of RvΔsigA-ATc and RvΔsigA +ATc samples (A). The data analysis showed that sigA expression was downregulated ∼0.7 fold in RvΔsigA +ATc samples (padj = 2.79E-08). To identify differentially expressed genes (DEGs), we applied a cut-off as padj <0.05 and absolute log2FC >0.5. There were 2320 DEGs, among which 1133 genes were upregulated, and 1187 genes were downregulated upon depletion of σA . To validate the RNA-seq analysis results, we selected five upregulated and downregulated genes each and performed a qRT-PCR analysis with RvΔsigA − ATc and RvΔsigA + ATc samples . To further validate this observation, Western blot analysis of σB and GlmU, which are upregulated and downregulated, respectively, in RvΔsigA on different days post-ATc addition were examined . These results were consistent with RNA sequence data, wherein we observed an increase in the protein levels of σB and a decrease in the levels of glmU at the later time points post-ATc addition .σ samples A. The daF). Of the 242 essential genes differentially regulated upon σA depletion, 57 were nonoperonic and 185 operonic (G). Pathway analysis suggested that many DEGs belong to multiple pathways, including lipid metabolism, intermediary metabolism, and cell wall and cell processes (H). Gene enrichment analysis indicated that critical metabolic pathways such as oxidative phosphorylation (ETC), TCA cycle, nucleic acid biosynthesis, and cell wall synthesis pathways are substantially enriched upon depletion in downregulated genes . To ascertain whether the higher levels of σB influence the expression of proteins from σA-regulated promoters, we performed a reporter assay. The upstream promoter region up to the start codon of sigA (500 bp) was fused with the ORF of luciferase in an integrative shuttle vector. The construct was electroporated into Rv and RvΔsigA (B). The luciferase activity in the lysates was evaluated on different days post ATc in addition to evaluating the impact of σA depletion on the expression of σA-modulated promoter. There was a significant reduction in the luciferase activity (compared with -ATc samples) on days 1 and 2 post σA depletion. However, on the subsequent days, the activity was higher (C). We reasoned that higher expression of σB is likely responsible for the increased promoter activity upon σA depletion. This hypothesis aligns with a previous report, which suggested a significant overlap in the promoter utilization between σA and σB (B should compensate for the absence of σA. σB overexpression construct (pNit-F-SigB) was transformed into Rv and RvΔsigA, and the expression of FLAG-σB was confirmed by Western blotting analysis (D). The overexpression of σB failed to mitigate the phenotypic defects observed upon depletion of σA both in vitro and ex vivo (E and F), suggesting a unique regulatory function for σA. Thus, we set out to examine the extent of uniqueness/redundancy of these σ factors. To address this question, we generated a mutant of sigB, RvΔsigB, wherein the sigB gene was replaced with a hygr antibiotic marker (A). The replacement of sigB at the native loci was confirmed by multiple PCRs (B) and Western blot (G). In vitro growth (H) and ex vivo infection (I) experiments suggested that the presence of σB was dispensable for Mtb survival. Together, data suggest that the function of σA is distinctive, and the absence of σB has no particular impact on growth.RNA-seq analysis and Western blot analysis  suggesteon in σB A. To asc RvΔsigA B. The lus higher C. We reaA and σB . If thisanalysis D. The ov ex vivo , E and Fc marker A. The reple PCRs B and Wesern blot G. In vito growth H and ex nfection I experimA and σB. RNA-seq analysis was performed in biological duplicates with the samples extracted from the log phase cultures of Rv and RvΔsigB. PCA analysis showed suitable clustering of Rv and RvΔsigB samples (A).Volcano plot represent 433 DEGs using a cut-off of padj < 0.05 and absolute log2FC > 0.5, among which 247 genes were upregulated and the 187 genes were downregulated in RvΔsigB . To validate the data, we performed qRT-PCR analysis of the top five upregulated and downregulated genes. The data obtained is in agreement with RNA-seq trends, even though the data for one sample was statistically insignificant . Analysis suggested that ∼61.9% of genes belong to operons, indicating plausible regulation of their promoters by σB .Next, we sought to examine the commonality in downstream gene expression between σ samples A.VolcanoF). While we find genes corresponding to all the cellular processes among DEGs, hypothetical, intermediatory metabolism, and cell wall/synthesis process contribute the most (G). Gene enrichment analysis indicated enrichment of five different processes, including growth, only in upregulated genes . RpbA, CarD, RNAP, σA, and σA deletion mutants were expressed and purified from E. coli. CD studies suggested the absence of gross changes in secondary structure among the truncated σA variants . Except for σAΔ179, σA and the other σA deletion mutants could initiate transcription, suggesting that the residues between 132 and 179 are critical for σA’s ability to initiate the transcription (D and E). We hypothesized that residues between 132-179 are primarily acidic and may be involved in forming the transcription bubble necessary for transcription initiation. Subsequently, we examined the ability of σA deletion mutants to complement the function of σAin vitro and ex vivo. pNiT constructs were electroporated into RvΔsigA, and the expression of σA or σA N-terminal deletion constructs was evaluated by Western blot (F). While all the σA deletion mutants were seen to be expressed, their expression was lower than the full length (F). In line with our in vitro transcription data, all the mutants other than σAΔ179 complemented the function of σA in the presence of ATc (G). The results obtained in ex vivo infection experiments were found to be similar to in vitro growth data (H). These results suggest that acidic amino acids between amino acids 132-179 residues play an important role in modulating the activity of σA.The data presented in xtension . This lenstructs A. RpbA, variants . σA is kts of σA B and S4.observed , C–E. Excription , D and Eern blot F. While l length F. In line of ATc G. The rewth data H. These A . We sought to examine the impact of σA phosphorylation on its interactions with the promoter region, in vitro transcription, and its function in Mtb. To evaluate the impact of phosphorylation, we generated σA phosphoablative mutants σAAbl  and phosphomimetic variants σAMim  . The trend was similar to σAMim; however, the values were not statistically significant. Next, we performed in vitro transcription assay, as described earlier to evaluate the impact of σA phosphorylation on transcription. Compared with the WT σA, both phosphoablative and mimetic mutants resulted in higher amounts of RNA product (D–E). To further investigate the effect of SigA phosphorylation, we coexpressed His-SigA and MBP or MBP-PknA or MBP-PknB. We generated a single construct coexpressing both SigA and kinase with a Histidine and a MBP tag respectively. E. coli was used as a surrogate host to obtain phosphorylated SigA. It is apparent from the Western blot presented in Figure 7F that His-SigA, MBP, MBP-PknA, and MBP-PknB expressed robustly in the lysates (F). Subsequently, we validated the phosphorylation of SigA by PknA and PknB by probing the purified SigA with phosphor-threonine antibodies (F). We note that both PknA and PknB phosphorylate SigA efficiently in vivo. To evaluate the phosphorylation status of SigA, His-SigA was pulled down and probed with α-p-Thr and α-SigA antibodies. α-p-Thr blots indicate that both PknA and PknB phosphorylate SigA (F). In an in vitro transcription assay with phosphorylated SigA, we found that phosphorylated SigA (SigA-MBP-PknA/B) does not show significant change in transcript formation in comparison to unphosphorylated SigA (SigA-MBP) (G).Phosphorylation of ECF-σ factors by Serine/threonine kinases influences their interaction with anti-σ factors thereby regulating its function . High thA , 30. DepA  A and S5.ragments . SPR ana than σA , B and C product , D–E. To lysates F. Subseqtibodies F. We notate SigA F. In an igA-MBP) G.Figure Mtb strains were evaluated for their ability to complement the depletion phenotype. The expression levels of σAwt/mut were found to be comparable with endogenous σA expression (H). While the WT almost wholly rescued the phenotype, both σAAbl and SigAMim partially rescued the growth defects in vitro and ex vivo (J). The inability of σAAbl's to complement may be due to the possible interactions of the hydroxyl group with the initiator complex. On the other hand, the failure of σAMim to completely complement may be due to the regulatory role of phosphorylation in the initiator complex. Together, these results suggest a partial role for phosphorylation in regulating the σA-mediated transcription.Subsequently, we subcloned these genes into the pNit-1 vector; the recombinant pression H. While  ex vivo  and J. TMtb to various host-derived stresses in vivo is coordinated by many regulators such as secretory virulence factors, one- and two-component signaling modules, serine/threonine protein kinases, and a multitude of transcription factors. Besides protecting Mtb from host immune response, these highly effective stress response strategies also contribute to antibiotic tolerance. Transcription factors, including σ factors, CarD, RbpA, WhiB family protein, and others, contribute to the regulation at the transcriptional level. σ factors are necessary for the recruitment of RNAP to the promoter. Thus, their levels in the cytosol impact the polymerase–promoter interaction and subsequent transcription . Nevertheless, we compared analyzed RNA-sequ data from second depleted cells with third depleted cells. The large proportion of upregulation or downregulation DEGs, the difference became more pronounced when cells progressed from second to third depletion (data not shown). RNA-seq analysis of 3-day–depleted RvΔsigA samples showed differential expression of 2320 genes (nuo A to J) convert nicotinamide NADH to NAD+ , σB failed to rescue the sigA depletion phenotype  differences in the strains used for the studies and (b) differences in the cut-offs applied. Among the 433 DEGs obtained upon deletion of Mtb σB, 283 genes overlapped with σA DEGs. Among the 1168 downregulation genes σA regulon, only 28 genes seem to be dependent on higher expression of σB .Overexpression of σand IdeR . However cascade . Chip SeA and σB . The expon of σA . Despitehenotype . In a pregulated . We findon of σB . The strA possesses varying lengths of N-terminal extension. These range from 83 aa in Bacillus subtilis, 95 in E. coli, and 163 in M. smegmatis (A is significantly longer at 221 aa. Domain σ1.1 (σR.1.1) is involved in abrogating nonproductive interactions of free σA with the promoter . Does phosphorylation alter promoter recognition or transcription initiation? This was clearly not the case as absence of phosphorylation or σA mutants mimicking phosphorylation had no impact on either DNA binding or in vitro transcription . According to these results, the phosphorylation of σA may modulate the nature and strength of σA interactions with other proteins, thus regulating promoter binding.Serine/threonine-protein kinase–mediated phosphorylation regulates many cellular processes in mycobacteria, including transcription. An example of immediate relevance is the ECF σ factors σractions , 55. Pkntions . The experiments were carried out as per the guidelines issued by the Committee for the Purpose of Control and Supervision of Experiments on Animals (CPCSEA), Govt. of India.Mtb (H37Rv or mutant strains) strains were grown in Middlebrook 7H9 medium (BD Biosciences) supplemented with 10% albumin, dextrose, catalase, NaCl, and 0.2% glycerol (Sigma), or 7H11 agar (BD Biosciences) 10% OADC (oleic acid added to ADC). Log phase cultures grown in the absence of ATc were used for seeding new cultures at A ∼0.05. The expression of the episomal copy of SigA (from pNit constructs) was induced by adding 0.2 μM isovaleronitrile (IVN). Cultures were grown in the absence or presence of 1 mg/ml ATc, and the growth was monitored by enumerating CFUs every day or 6 days postinoculation depending on the experiment. All the experiments were performed in biological triplicates.The list of bacterial strains used is given in Mtb were cloned into pET-28a vector, and the proteins were overexpressed in E. coli BL21(DE3) cells. The recombinant proteins were purified by Ni-affinity chromatography in 50 mM Tris–HCl pH8.0, 500 mM NaCl, 5% glycerol, and eluted using 20 to 500 mM gradient of imidazole. The eluted fractions were resolved on 15% SDS-PAGE and then concentrated using ultrafiltration (Merck). The proteins were buffer exchanged to 20 mM Tris–HCl pH 8, 150 mM NaCl, 5% glycerol. Subunits of Mtb RNAP were expressed and purified from E. coli BL21(DE3) cotransformed with pETBC and pACYCZA   . Core RNt vector . SigA waeviously .SigA or sigB was PCR amplified from Mtb H37Rv genomic DNA with phosphorylated forward and reverse harboring NdeI and HindIII sites. Amplicons were purified and cloned into the SmaI digested and dephosphorylated pUC19 vector. The sigA insert was released with NdeI-HindIII digestion and cloned into corresponding sites in Mycobacterial-E. coli shuttle plasmid pFICTO  from the L5 loci and sigA from the native loci. Upon the addition of ATc, the expression of FLAG-SigA shuts down as the tet repressor binds with its cognate operator sequences. To generate Allelic exchange substrate (AES), ∼1 kb left-hand– and right-hand–flanking sequences of sigA were amplified. Amplicons were digested with PflMI and ligated with oriE+ λ cos (1.6 kb) and hygr-sacB (3.6 kb) cassettes obtained after digesting pYUB1474  vector to generate pNit-SigA or pNit-SigAMut constructs. The N-terminal deletion constructs of σA were generated by PCR amplifying, then using different N-terminal forward primers harboring the NdeI site and the reverse primer harboring the HindIII site. They were cloned into a pNit-1 vector to generate pNit-SigAdel constructs. Similarly, the sigB gene was cloned into the pNit-3F vector  were prepared as described previously . Four hours p.i, media was removed and cells were washed thrice to remove extracellular bacteria. The cells were replenished with RPMI media containing 10% fetal bovine serum with or without 0.2 μM IVN or 1 μg/ml ATc. 24, 48, 72, or 96 h p.i, cells were lysed in 100 μl of 0.05% SDS, and CFUs were enumerated different dilutions on OADC-containing 7H11 agar plates.BALB/c mice were injected with 4% thioglycolate solution (Difco) in the peritoneal cavity, and 96 h post-injection, peritoneal macrophage was isolated and seeded in RPMI media containing 10% fetal bovine serum. Log phase cultures of Mtb strains passed through a 26 gauge needle to create single-cell suspensions. Peritoneal macrophages were infected with sigA depletion on bacterial survival in the host, we performed murine infection experiments as described previously  or after infection establishment (14 days p.i). CFUs were enumerated at the indicated times.To investigate the physiological impact of eviously . Dox hydsigA ORF was cloned into an integrative shuttle plasmid (pSW-lucSApr) at the ScaI-NdeI site. The luciferase (luc) ORF was cloned into NdeI-HindIII sites. Rv and RvΔsigA strains were electroporated with pSWN-sigApro-luc to generate Rv::sigpro-luc and RvΔsigA::sigpro-luc strains. WCL was prepared as described above, and Luciferase assays were performed as described previously . The sense and anti-sense strand of rrnAP3 promoter DNA (−70 to +20) was PCR amplified from Mtb genome. The sense strand was synthesized with 5′ biotinylation modification (Sigma Aldrich). The strands were annealed before the immobilization by mixing the sense: anti-sense strand at a molecular ratio of 1:2 in Sodium Saline citrate buffer. Biotinylated rrnAP3 (5′) promoter fragment was immobilized on an SA chip at a surface density of 985 RU ng/mm2. The experiment was executed in running buffer comprising 25 mM Hepes (pH 8), 250 mM NaCl, and 5% glycerol. The study used various concentrations of purified His-σA and His-σAMut as analytes. The first channel of SA chip was not immobilized with any biotinylated promoter and was used as a control for the binding studies. BIA-evaluation software program was used to evaluate interaction kinetics. The σA and rrnAP3 promoter interaction sensograms were used as control for calculating both σA N-terminal truncation constructs (B) and σA phosphomutants promoter–binding kinetics (B and C).Interaction of σA, its N-terminal truncations, and its phosphoablative and phosphomimetic mutations with nstructs B and σA kinetics , B and CrrnAP3 (−100 to +150) was PCR amplified from Mtb genomic DNA, and the amplicons were purified. RNAP holoenzyme was assembled by mixing 100 nM core RNAP with 500 nM σ subunit followed by 15 min incubation at 37 °C. Subsequently, 2 μM RbpA and 4 μM of CarD were added to the reaction and incubated for 10 min. The above mixture was incubated with a 40 nM rrnAP3 promoter fragment at 37 °C for 5 min in the presence of 1 μl heparin (0.5 mg/ml) to inhibit the nonspecific RNA–DNA complex. RNA synthesis was initiated by addition of 1 μl NTP mix  and the reaction was carried out for 45 min at 37 °C. RNA products were purified by precipitating using 1/10th volume of 3 M sodium acetate (pH 5.2), glycogen (1 μg/μl), and 2.5 volumes of 100% cold ethanol. The samples were centrifuged at 10,000 rpm, the pellet was washed with 70% cold ethanol, and the pellet was eventually resuspended in 20 μl nuclease-free water. 2× RNA loading dye  was added to the samples, heated at 95 °C for 5 min chilled on ice, and resolved on 5% Urea-PAGE. Transcription products were visualized using Phosphorimager and quantified by using Quantity One software (Biorad).Transcription was carried out in 5 μl transcription buffer . The promoter Total RNA was isolated from exponentially growing bacteria cells. To isolate total RNA, cells were inoculated at 0.05 A in the presence or absence of ATc and allowed to grow for 3 days. Cells were resuspended in TRIzol reagent (Invitrogen), and total RNA was isolated from following mycobacterial cells and performed qRT-PCRs as described perviously .Mtb H37RV, downloaded from https://ftp.ncbi.nlm.nih.gov/genomes/refseq/bacteria/Mycobacterium_tuberculosis/reference/GCF_000195955.2_ASM19595v2/, using hisat2 with default parameters. Uniquely aligned reads were counted using feature Counts of the Subread package. There were 4008 genes in the gtf file, for which we had the count information. The gtf was modified to remove 200 bp from either end of SigA/SigB. Genes with a total read count 10 across all the samples were removed, resulting in 3987 genes for the SigA knockdown experiment and 3999 genes for the SigB KO experiment. DESeq2 was used to analyze differential gene expression. A gene was considered to be differentially expressed if the adjusted p-value was less than 0.05 and the absolute log2 fold change was greater than 0.5. Raw read counts were normalized with rlog, provided by DESeq2 package for PCA plot and heat map.Agilent 2100 Bioanalyser (Agilent RNA 6000 Nano Kit) or 4200 Tape station system was used to determine RNA integrity. RNA-seq was performed using samples with RIN values higher than 7. Sequencing was performed at the Centre for cellular and molecular biology core sequencing facility. Illumina adapters and low-quality reads were eliminated from raw sequencing reads using cutadapt. Low read quality scores (<20) and <36 bp were discarded. The processed reads were then mapped to the https://david.ncifcrf.gov/). We only used the GO terms and KEGG pathways for enrichment analysis. We only plotted the top 10 enriched GO terms/KEGG pathways based on gene counts.For functional enrichment analysis, DAVID web services were used . The corresponding author can provide the source data for this study upon request.https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE197742).RNAseq data are available at the NCBI Gene Expression Omnibus Database, accession number. GEO (GSE197742). (This article contains B. S. is a Senior Research Fellow. The authors declare that they have no conflicts of interest with the contents of this article.