SalR is a typical LysR-type transcriptional regulator (LTTR) family protein and activates the salP promoter in the presence of aspirin or salicylate in the range of 0.05 to 10 µM. The experimental results and mathematical simulations support the competitive binding model of the SalR/salP regulation system in which SalRr competes with SalRa to bind the salP promoter and affect gene transcription. The competitive binding model successfully predicted that weak SalR expression would significantly improve the inducible strength of the SalR/salP regulation system, which is confirmed by the experimental results. This provides an important mechanism model to fine-tune transcriptional regulation of the LTTR family, which is the largest family of transcriptional regulators in the prokaryotic kingdom. In addition, the SalR/salP regulation system was also functional in probiotic strain E. coli Nissle 1917 and minicell-derived SimCells, which would be a useful biobrick for environmental and medical applications.An aspirin-inducible SalR/ Escherichia coli by employing the salP promoter and SalR regulation system originally from Acinetobacter baylyi ADP1. Mutagenesis at the DNA binding domain (DBD) and chemical recognition domain (CRD) of the SalR protein in A. baylyi ADP1 suggests that the effector-free form, SalRr, can compete with the effector-bound form, SalRa, binding the salP promoter and repressing gene transcription. The induction of the salP promoter was compared in two different gene circuit designs: a simple regulation system (SRS) and positive autoregulation (PAR). Both regulatory circuits were induced in a dose-dependent manner in the presence of 0.05 to 10 µM aspirin. Overexpression of SalR in the SRS circuit reduced both baseline leakiness and the strength of the salP promoter. The PAR circuit forms a positive feedback loop that fine-tunes the level of SalR. A mathematical simulation based on the SalRr/SalRa competitive binding model not only fit the observed experimental results in SRS and PAR circuits but also predicted the performance of a new gene circuit design for which weak expression of SalR in the SRS circuit should significantly improve induction strength. The experimental result is in good agreement with this prediction, validating the SalRr/SalRa competitive binding model. The aspirin-inducible systems were also functional in probiotic strain E. coli Nissle 1917 and SimCells produced from E. coli MC1000 ΔminD. These well-characterized and modularized aspirin-inducible gene circuits would be useful biobricks for synthetic biology.A simple aspirin-inducible system has been developed and characterized in IMPORTANCE An aspirin-inducible SalR/salP regulation system, originally from Acinetobacter baylyi ADP1, has been designed for E. coli strains. SalR is a typical LysR-type transcriptional regulator (LTTR) family protein and activates the salP promoter in the presence of aspirin or salicylate in the range of 0.05 to 10 µM. The experimental results and mathematical simulations support the competitive binding model of the SalR/salP regulation system in which SalRr competes with SalRa to bind the salP promoter and affect gene transcription. The competitive binding model successfully predicted that weak SalR expression would significantly improve the inducible strength of the SalR/salP regulation system, which is confirmed by the experimental results. This provides an important mechanism model to fine-tune transcriptional regulation of the LTTR family, which is the largest family of transcriptional regulators in the prokaryotic kingdom. In addition, the SalR/salP regulation system was also functional in probiotic strain E. coli Nissle 1917 and minicell-derived SimCells, which would be a useful biobrick for environmental and medical applications. Synthetic biology has the potential to engineer bacteria for disease diagnosis  and cancin vivo studies. An ideal bacterial design for medical applications should have the following traits. The specific bacterial chassis should be safe for human applications. The inducer should have no side effects on human health and should be able to trigger different levels of gene expression in response to different inducer concentrations. Gene circuits should have minimal cross talk and only be triggered by a specific inducer rather than molecules present naturally in the human body or in common diet. Finally, to achieve effective bacterial therapy, the release of drugs  from engineered bacteria must be accurately and reliably controllable.Advances in the utilization of feedback-based synthetic circuits for biomass yield optimization , spatial9–salnahR/P::xylS2 is a Pseudomonas species-derived gene circuit and has been applied in regulated expression of Salmonella species genes at the millimolar level  circuit and two simple regulation system (SRS) circuits with various promoter strengths. The performance of salP and salR gene circuits has been characterized in E. coli DH5α, probiotic E. coli Nissle 1917  and positive autoregulation (PAR) circuits, and expressed them in E. coli DH5a  expression was measured at the single-cell level using flow cytometry and a fluorescence microscope  in the CRD domain of the salR gene were deleted using the sacB-km counterselection method (see Section S1). We hypothesized that this deletion did not prevent the mutated SalR from binding the salP promoter, because the N terminus was unaltered. In the case of ADPWH_NΔsalR, the DBD of the salR gene in ADPWH_lux was knocked out by inserting a kanamycin resistance gene : the average background bioluminescence expression of ADPWH_NΔsalR was 5,968 ± 48, which is significantly higher than that of both ADPWH_CΔsalR  and ADPWH_lux . ADPWH_CΔsalR with a mutated C-end chemical recognition domain (but unchanged N-end DNA binding domain) should bind and repress the salP promoter, reducing the background expression of bioluminescence, similar to ADPWH_lux, which has an intact salR. In contrast, disruption at the N end in ADPWH_NΔsalR completely alters the SalR structure, making it unable to bind the salP promoter and leading to a higher background expression of bioluminescence . Collectively, the results suggest that uninduced SalR or the effector-free form, SalRr, should bind and repress the salP promoter.Although both SalR mutants ADPWH_NΔsalR gene mutagenesis results described above, we hypothesize that both SalRr and SalRa can competitively bind the salP promoter. To assess the hypothesized mechanism and investigate how variation of different aspects of the SRS and PAR circuits affect the aspirin-regulated performance, we developed a mathematical model to simulate and predict the performance of the three gene circuits. The interaction considered in our model for the SRS and PAR systems is outlined in a, which activates the salP promoter, and SalRr, which occupies the binding site and represses the salP promoter. For the SRS circuit, the competition between overexpressed SalRr and aspirin-activated SalRa is expected to produce low GFP expression levels. This competition has little effect on the PAR circuit, as its SalR level is tuned by a self-regulated feedback loop.Accorrding to the salP promoter is given by a is inducer concentration, L is the leakage rate from the salP promoter, RK defines the saturation point for repressive binding with salP, AK defines the saturation point for activating SalR binding with salP, and aK defines the saturation point for inducer interaction with the circuit. Thus, equation 3 reflects the balance we expect between repressive SalRr binding and inducer-dependent activation of SalRa binding. Further discussion of the modeling approach, as well as the procedure used for parameter fitting, is provided in Section S2.We created a two-state differential equation model of the system, in which the concentration of SalR is governed byE. coli was characterized in terms of four features: (i) expression level, (ii) response time, (iii) output dynamic range/induction fold, and (iv) input dynamic range and leakiness (uninduced expression level). These four features are motivated by a desire to quantify a biosensor’s utility in drug delivery and in vivo sensing. In such an application a biosensor would ideally exhibit a high sensitivity, fast response, high induction fold change, and tightly controlled expression. To examine these criteria, we ran plate reader experiments to analyze the SRS and PAR circuits over a range of inducer concentrations and compared these data to the simulated results from the mathematical model.The performance of the SRS and PAR designs in E. coli DH5a were induced by different concentrations of aspirin, and the response time of GFP expression was examined in three different growth media   was characterized and replaced proD in the construction of SRS* (P < 0.05). This is in a good agreement with the competitive binding hypothesis, suggesting that the SRS* circuit with the weak promoter J109 should produce less SalR than the SRS circuit, ease the SalRr/SalRa competitive binding on the salP promoter, and increase the GFP expression level  glucose, the expression profile of PAR showed less leakiness, implying that the circuit could function optimally under nutrient-limited conditions. We suspect this change is due to unknown host interference, where cells experiencing glucose starvation alter their resource allocation  and that E. coli has nonspecific esterase activity . Absorption curves indicate that the salicylate solution produced a peak at 300 nm after interacting with FeCl3 . This unique absorbance peak can be used to identify the presence of salicylate. Interestingly, a time course analysis shows that both the aspirin water control and aspirin with E. coli Nissle 1917 cells can produce salicylate . This suggests that aspirin in water can be broken down to salicylate at 37°C after 3 h, although the level of salicylate was lower than that of aspirin mixed with E. coli Nissle 1917 cells . It also indicates that nonspecific esterase activity in E. coli Nissle 1917 assisted aspirin degradation, as was reported previously , chromosome-free, and functional cells formed as a result of abnormal cell division  as well as additional, unidentified mechanisms  regulatory system. These may include synthetic biological devices designed for clinical applications in the future; in such cases a priori utilization of the modeling architecture developed here can inform design choices and experimental approaches, thereby optimizing designs prior to their implementation.In the present study, a few aspects of the SalR/E. coli Nissle 1917 and nongrowing SimCells should be ideal chassis for the construction of anticancer agents due to their designable features, safe nonproliferation properties, and small size. Controllable expression of gene circuits, combined with safe delivery and tissue penetration, would enable E. coli Nissle 1917 and SimCells to selectively exert cytotoxicity in tumors. This study demonstrates that the aspirin-inducible SalR/salP system is able to function in E. coli Nissle 1917 and SimCells, which would be useful for bacterial diagnosis and therapy in medicine.Since many genera of bacteria naturally coexist with tumors in clinical situations , probiotAll reagents were purchased from Sigma-Aldrich  unless otherwise noted. Antibiotics (kanamycin and ampicillin) were obtained from Fisher Scientific (UK). Sterile 1× PBS solution was made by diluting 10× PBS stock solution purchased from Fisher Scientific (UK).The strains and plasmids used in this study are listed in proD promoter was replaced with the J109 promoter. PAR_Amp* was from Psal-gfp-salR, in which the kanamycin gene was replaced with an ampicillin resistance gene. Other plasmids listed in E. coli DH5α cells by heat shock. E. coli Nissle 1917 was acquired from Ardeypharm GmbH . E. coli MC1000 ΔminD cells were made chemically competent before transformation with PAR_Amp*. The strains were cultured in LB medium with 50 μg·ml−1 kanamycin or 100 μg·ml−1 ampicillin (as appropriate) in a 37°C incubator.Plasmids Psal-gfp-salR (PAR circuit) and PproD-salR-Psal-gfp (SRS circuit) were synthesized by GeneArts . PJ109-salR-Psal-gfp was from PproD-salR-Psal-gfp, in which the salP promoter, gfp, and colE1 origin of replication . SRS and PRS circuits were designed, and their structures are shown in gfp gene was fused directly to the salP promoter to replace the sequence of the original salA, codon-optimized salR replaced the original salR, and the original structure, promoter, and ribosome binding site were kept intact in the salR operon. In the SRS circuit, gene-optimized salR is under the control of a constitutive promoter, proD . The full sequences of SRS and PAR were synthesized and supplied by GeneArt gene synthesis . Further detailed information of gene circuit design can be found in Information Section S1 in the supplemental material.The codon sequence of er, proD , whose sE. coli MC1000 ΔminD::km, a plasmid of PAR  with alternative ampicillin resistance (PAR_Amp*) was needed and was constructed as follows. The ampicillin resistance gene was isolated by PCR from the plasmid pGEM-T  by using an In-Fusion cloning kit  and the primers PAR_AmpR For and Rev (Due to the selection marker on  and Rev . The resE. coli MC1000 ΔminD::km transformants with plasmid PAR_Amp* were selected on LB agar selection plates containing 100 µg/ml ampicillin. A single colony from each plate was cultured at 37°C with continuous shaking at 200 rpm overnight in 5 ml LB broth supplemented with 100 µg/ml ampicillin (LB amp). Overnight culture was added to fresh LB-ampicillin at a ratio of 1:1,000 and cultured for 24 h. For the minicell purification, a modification of a previously described method  and the minicells resuspended from the membrane into sterile PBS solution to concentrate them 100-fold. PBS was chosen as it is a cost-effective medium in which to suspend the cells and to maintain osmotic balance. Minicell samples were maintained at 4°C prior to testing. The purity of minicell suspensions was determined by a plate count method after 24 h of incubation on LB-ampicillin agar plates at 37°C and conducted in triplicate.Following heat shock, E. coli DH5α cells were induced with an aspirin concentration gradient  in kanamycin (50 µM) and LB for 16 h at 37°C in a 600-rpm shaker. Induced culture was then analyzed using a FACSCalibur (BD Bioscience), with 100,000 events being captured for each sample. Gating was performed on forward and side scatter and the GFP channel to remove noise caused by debris and background. Data were exported to Kaluza flow cytometry for subsequent analysis and visualization.Transformed l-arabinose, glycerol, and aspirin was made in deionized water and sterilized using a 0.2-μm syringe filter to be tested with cells containing SRS and PAR circuits. A total volume of 200 μl  was loaded in a 96-well black-sided, clear-bottomed plate  in quadruplicate. The plate was then placed into a BioTek Synergy HT microplate reader  maintained at 37°C with reads of fluorescence  and OD at 600 nm. Readings were recorded every 15 min for 16 h. Cellular intrinsic fluorescence background was subtracted from the control of E. coli without plasmid.A stock solution of For experimental conditions in PBS and M9 prior to induction, transformed bacteria, which were cultured overnight in LB, were centrifuged and washed with PBS and M9 three times at 4°C to remove any residue of LB broth. For achieving microaerobic conditions, 50 μl of mineral oil was added on top of the 200-μl reaction volume in a 96-well plate.Fluorescence of induced bacterial cells or SimCells was visualized using a Motica BA210 digital microscope with Moticam 580INT display output after 16 h of induction. Five μl of each sample was taken from the well and placed on a glass slide with a coverslip. Images were taken at ×100 magnification. Light micrographs were subsequently analyzed using ImageJ, version 1.50 b, with fluorescent maxima automatically counted after consistent thresholding.E. coli Nissle 1917 culture with 5 mM aspirin was incubated at 37°C and sampled at 0, 3, and 16 h. The samples were centrifuged at 5,000 × g for 5 min to remove cell pellets and only the supernatants were used for FeCl3 assay, as dictated by the protocol .To study aspirin conversion to salicylate,


Macrophages are crucial members of the innate immune response and important regulators. The differentiation and activation of macrophages require the timely regulation of gene expression, which depends on the interaction of a variety of factors, including transcription factors and epigenetic modifications. Epigenetic changes also give macrophages the ability to switch rapidly between cellular programs, indicating the ability of epigenetic mechanisms to affect phenotype plasticity. In this review, we focus on key epigenetic events associated with macrophage fate, highlighting events related to the maintenance of tissue homeostasis, responses to different stimuli and the formation of innate immune memory. Further understanding of the epigenetic regulation of macrophages will be helpful for maintaining tissue integrity, preventing chronic inflammatory diseases and developing therapies to enhance host defense. Both tissue-resident macrophages in homeostasis and activated macrophages under stimuli are driven by specific transcriptional changes and are controlled by complex cellular mechanisms. Among them, epigenetics now arises as a key controller of macrophage activity.6 However, it has been revealed that epigenetic chromatin markers are dynamically regulated with changes in development or environmental signals.7 These results have led to additional information regarding epigenetics, including a transient change in chromatin in response to external stimuli that control gene expression.Epigenetics regulates the expression of DNA-encoded information and determines the specific “identity” of a cell while the genetic code is not altered. The chromatin conformation controls transcription factor binding and gene expression through DNA accessibility. Epigenetic markers have traditionally been considered stable and heritable.Currently, most of the epigenetic mechanisms are related to the protein−DNA interactions that affect gene expression, whether through the recruitment of protein complexes involved in nucleosome modification and remodeling or by chemical modification of DNA bases, such as 5-methylcytosine. Additionally, there are other epigenetic mechanisms, such as the production of small noncoding RNAs, that can regulate mRNA in transcription through base pairing, resulting in mRNA degradation or translational inhibition. Overall, epigenetic changes can be divided into three categories: (1) posttranscriptional histone modifications, (2) DNA methylation, and (3) noncoding RNA.8 The octamer, composed of two groups of H2A, H2B, H3 and H4 proteins, is the fundamental unit of chromatin, and histone H1 connects the two nucleosomes. When nucleosomes are organized into tightly arranged bundles (heterochromatin), transcription is inhibited by restricting the entry of transcriptional machinery. In contrast, when the chromatin is relaxed (euchromatin), the nucleosomes are arranged like a string of beads, predominantly associated with active transcription. Nucleosome-free regions are known as open chromatin, which contain a variety of functional sequences, such as promoters and enhancers, and thus play a vital role in gene regulation.9 Promoters are short sequences of approximately 100 bases proximal to the transcription start sites at the 5′ ends of genes. A common feature of promoters is that RNA polymerase II binds to promoters of inactive genes in advance. When stimulated, promoters can recruit more polymerase II to initiate transcription.10 Enhancers are distal transcriptional regulatory elements that are defined as genomic DNA elements, ranging from several to hundreds and, in rare cases, even thousands of bases in length, and contain short transcription factor (TF) recognition sequences or binding sites. In these regulatory regions, the accessibility of DNA by protein TFs and other transcriptional mechanisms is critical for gene expression. The interplay and long-range communication of enhancers and target gene promoters mediated by DNA looping tightly regulate gene expression.In eukaryotes, approximately 147 bases of DNA wrap around a histone octamer to form a nucleosome.Disordered N-terminal histone tails extending from nucleosomes are substrates for a variety of posttranscriptional enzymatic modifications. Amid a vast repertoire of histone modifications, acetylation/deacetylation and methylation/demethylation of lysine residues belong to the most broadly studied and extensively characterized macrophage-related epigenetic modifications of posttranslational histone modification. Determined by the opposing activities of enzymatic writers and erasers, the presence of histone modifications on the chromatin is reversible.11 Histone acetylation markers are specifically recognized and bound by bromodomains, a structural motif present in specialized chromatin reader proteins that reads the histone acetylation code, and then transcriptional mechanisms are initiated.12 Many histone acetyltransferase complexes contain a component with a bromodomain that anchors histone acetyltransferase complexes on the already acetylated chromatin, enabling them to propagate acetyl labels to adjacent nucleosomes, hence spreading histone acetylation. Similarly, the SWI/SNF complex, the first described ATP-dependent chromatin remodeling complex, targets the acetylated histone tails through the bromodomain subunit, which is critical for recruitment.13 Another group of histone acetyl readers, known as the bromo- and extraterminal (BET) protein family members, can recruit TFs and chromatin remodeling complexes to regulate gene expression, and they have been demonstrated to play a key role in the regulation of inflammatory gene expression in macrophages.14Histone acetyltransferases promote acetylation, which is related to transcriptional activity, such as H3K9ac and H3K27ac, whereas histone deacetylases (HDACs), the erasers, catalyze the removal of acetyl groups from histone tails, which is linked to transcriptional inhibition.15 Furthermore, the extent of individual lysine methylation, including the mono- (m1), di- (m2), or trimethylation (m3) of histone lysine residues, is differentially distributed in chromatin and plays different roles in gene regulation. Transcriptional activity is correlated positively with the trimethylation of H3 histone lysine 4 (H3K4m3) at gene promoters.16 On the other hand, the monomethylation of this residue (H3K4m1) is a typical feature of enhancers.17Similar to histone acetylation, the subsequent methylation and demethylation of histones are promoted by histone methyltransferases and histone demethylases, respectively. Specifically, every site-specific mark of lysine within the tail of H3 is written by a group of specific enzymes called histone lysine methyltransferases (KMTs) and erased by other enzymes classified as histone lysine demethylases. Unlike acetylation, methylation modification of histone can induce transcriptional activation or inhibition, depending on the location and number of methyl groups within the histone tail. Regulatory elements on repressed genes, such as methylation at the H3K9 and H3K27 loci, often lead to “gene silence” and induce the heterochromatin state in chromatin regions. Conversely, methylation at H3K4 and H3K36 is associated with the assembly of transcriptionally permissive chromatin structures and active transcription at many loci.18 DNA methylation is mainly related to transcriptional inhibition, characterized by 5-methylcytosine immediately adjacent to guanine residues, and involves the transfer of a methyl group to the cytosine ring of DNA through DNA methyltransferases (DNMTs).19 Mechanically, 5-methylcytosine binding proteins induce the recruitment of repressor complexes to methylated promoter segments and cause transcriptional silencing.18 In particular, DNMT3A and DNMT3B are responsible for establishing de novo methylation markers, while DNMT1 is the maintenance methyltransferase responsible for maintaining these markers, as these markers at CpG dinucleotides must be reestablished after DNA replication in each cell division.20 DNMT1 can also participate in the regulation of histone modifications that result in a depletion of di- (H3K9me2) and trimethylation (H3K9me3) at H3K9 and a concomitant increase in H3K9 acetylation (H3K9ac).21In addition to histones, methyl modification of DNA is a unique mechanism in epigenetic regulation. In mammals, most DNA methylation occurs in the 5′-cytosine-phosphate-guanine-3′ dinucleotide (CpG) dinucleotide clusters named CpG islands, which are found in the promoters of approximately 40% of the genes, and greater than 70% of CpG sites are methylated in the DNA of somatic cells.22 The abundant non-CpG methylations of DNA directly affect the binding of TFs through the methylation of TF binding sites, which provide a mechanism for regulating gene expression.22Recently, the methylation of non-CpG moieties has been found to occur widely on genomic DNA.23 Thereafter, thousands of lncRNAs have been found in different cells and to be involved in a variety of diseases. Although the sources of these lncRNAs are different, their functional mechanisms are similar. A number of lncRNAs can directly interact with chromatin-modifying enzymes and remodeling complexes to guide these epigenetic catalysts to specific parts of the chromatin.24 In addition, some lncRNAs can form RNA−protein complexes with transcription factors and affect the location and activity of transcription factors binding to them, thereby regulating gene expression.25 Specific lncRNAs play a part in the programming of silencing or activating histone modifications. For example, HOTAIR, a 2.2 kilobase lncRNA in the HOXC locus, is involved in silencing chromatin mediated by polycomb repressive complex 2  and can recruit PRC2 to its target gene and methylate H3K27 via EZH2.26 Furthermore, HOTAIR has been found to be a scaffold that targets genes in at least two different histone modification complexes.27 The 5′ domain of HOTAIR binds to PRC2, and the 3′ domain of HOTAIR binds to the CoREST/REST repressor complexes, which contain LSD1 (KDM1/BHC110), a demethylase that mediates the enzymatic demethylation of H3K4me2. The ability to link two distinct complexes makes it possible to assemble PRC2 and LSD1 and coordinate the complexes targeting chromatin to achieve the methylation of H3K27 and the demethylation of H3K4.27 In addition, another typical example is the lncRNA ANRIL, an antisense RNA transcript overlapping the INK4b/ARF/INK4a tumor suppressor locus, which participates in the cis recruitment of both PRC1 and PRC2 to the target gene for silencing.28Finally, endogenously expressed noncoding RNAs, including long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), play critical roles in the posttranscriptional regulation of gene expression by acting as competing RNAs, although they do not directly affect chromatin structure. lncRNAs are a large group of nonprotein-coding transcripts with a length of more than 200 nucleotides. XIST, one of the best characterized lncRNAs, was found to drive X-chromosome inactivation in 1991.29 In addition, a specific miRNA may bind to and regulate several targets, sometimes as part of the same signaling pathway, adding multiple regulatory levels. Therefore, under pathophysiological stimulation, miRNAs can fine-tune gene expression patterns.Another class of noncoding RNAs, miRNAs, which are single-stranded RNAs containing 20−24 bases. It is estimated that more than 60% of all protein-coding genes are directly regulated by miRNAs. They can specifically bind to the 3′ or 5′ untranslated regions of mRNA, mainly as posttranscriptional inhibitors, by targeting the 3′ untranslated regions of the RNA to stimulate its degradation and translation repression.30 Histone and DNA modification, together with lncRNAs and miRNAs, are collectively defined as epigenetic mechanisms.Based on existing research, mechanisms of crosstalk among the different epigenetic regulation systems have been revealed. They interact with each other rather than working independently. For example, histone lysine is the target of both methylation and acetylation, such as H3K9 and H3K27. At least two enzymatic steps are required to shift from the inhibited methylated state to the activated acetylated state (and vice versa). Therefore, it is believed that the state between the opposite nucleosome-modifying activities is altered by sequence-specific DNA-binding TFs that recruit specific chromatin remodeling agents and modifying factors to individual loci, and crosstalk between them occurs, leading to their combinatorial effects in transcriptional control.31 Accumulating evidence, however, has demonstrated that the different macrophages do not necessarily have the same origins. With few notable exceptions, the tissue macrophages do not arise from blood monocytes under homeostasis and even in some kinds of inflammation; those tissue macrophages are seeded from embryonic precursors of the yolk sac macrophages and fetal monocytes prior to birth and maintain themselves throughout adulthood by self-renewal and participate in tissue remodeling. Erythro-myeloid progenitors, derived from the yolk sac, have been found to be the embryonic precursors of yolk sac macrophages and fetal monocytes before the emergence of hematopoietic stem cells (HSCs); thus, they are a common origin for tissue macrophages.32 Two sequential waves of erythro-myeloid progenitors were identified to generate macrophages. An early myeloid-restricted hematogenic wave originates in the yolk sac, generates primitive macrophages without monocytic intermediates and is independent of the transcription factor c-Myb.33 These cells either directly generate primitive yolk sac macrophages as the sole origin of tissue-resident macrophages, such as microglia, or migrate to the fetal liver and give rise to fetal monocytes that proliferate in the embryonic tissues and differentiate into distinct tissue macrophages.34 Alternatively, a late c-Myb-dependent wave that commences in the fetal liver to generate multiple hematopoietic lineages, including monocytic intermediates, persists throughout adult life.35 Fetal monocytes differentiate into macrophages when recruited to fetal tissues, replacing the main components of the existing yolk-sac-derived macrophages gradually with the exception of microglia.35 With the growth of host tissues, these primitive macrophages differentiate through proliferating in their respective tissue macrophage compartments in most tissues, except the intestine, the heart, and the skin. Therefore, a model of macrophage origination has been established, which is distinct from the model that depends only on blood monocytes.In 1968, it was presumed that macrophages were derived only from blood monocytes, and this concept prevailed for approximately half a century.Tissue-resident macrophages are an extremely heterogeneous population, which is a necessary outcome of lineage- and tissue-specific functions during development and adulthood, and are integral to maintenance of tissue homeostasis. Independent of each other, tissue macrophage compartments evolve locally surrounded by their organ microenvironment, and therefore, each population of tissue macrophages is closely related to its immediate surroundings. Hence, these cells acquire additional functions and activities tailored to maintain the steady state in local tissues through various functions, including the modification of the phagocytosis mechanism, general or specific niche nutritional factors, and morphological specificity.36Normal tissue homeostasis is regulated in a tissue-specific manner by distinct populations of tissue macrophages, ranging from pulmonary surfactant clearance to neuron pruning and the establishment of intestinal homeostasis. Epigenetic characterization shows great plasticity in the epigenetic programs of macrophages, and more than 12,000 enhancers can be reprogrammed when mouse differentiated macrophages are transplanted into a new microenvironment.37 Importantly, there is strong enrichment for sequences containing transcription factor binding sites that recognize and recruit different patterns of TFs on macrophage enhancers, corresponding to a significant enrichment of DNA recognition motif combinations.38 In turn, the binding of TFs to DNA determines the selection of new enhancers.Enhancers are fundamental and precise determinants of gene expression and play a key role in how distinct signals establish cell identity and regulatory potentiality at the genomic level. The number of enhancers identified in murine macrophages exceed that of promoters; thus, interactions between DNA and TFs at enhancers are more likely to occur than at promoters.39 Multiple lines of evidence suggest that ETS family member PU.1 contributes to the basal activation state and H3K4me3 of many promoters, acts as a crucial LDTF that occupies most macrophage enhancers where it is essential in maintaining H3K4me1, and contributes to select a large number of the cell-specific enhancer-like elements, suggesting that PU.1 is both required and sufficient to function in genomic regions as an enhancer.40 Moreover, PU.1 is considered to be a pioneer TF in initiating chromatin accessibility, allowing the binding of additional TFs, and PU.1 is bound at the same level in both unstimulated and stimulated cells. Additional TFs commonly found in macrophages, including C/EBP family members, IRF, NF-κB and AP-1 factors, exhibit collaborative interactions with macrophage-specific enhancers selected by PU.1  exist at pre-existing enhancers.41 Mutations in PU.1 motifs leading to the inhibition of PU.1 binding cause the deletion of the binding of C/EBPα in collaboration. Conversely, mutations in C/EBP motifs also result in a corresponding reduction in nearby PU.1 binding. Moreover, mutations in LDTF motifs can abolish the signal-dependent binding of NF-κB, whereas mutations in NF-κB motifs rarely affect the binding of PU.1 or C/EBPα. Therefore, the hierarchical model of regulatory functions in macrophages has been described, where a relatively small group of LDTFs compete with nucleosomes to bind DNA in a cell-specific manner, among which PU.1 is a necessary LDTF of macrophages to maintain nucleosome depletion at macrophage-specific enhancers.In addition to tissue-specific regulation, which is very predictable, to be more precise, the epigenetic regulation of macrophages is coordinated by lineage- and tissue-specific transcription factors, which are determined by the built-in programming of myeloid development as well as signals from the tissue environment. Lineage-determining transcription factors (LDTFs), also referred to as pioneer factors or master regulators, can actively open up the local chromatin and directly combine it with other factors.cis-active regulatory elements, the binding of PU.1 is proposed to “prime” DNA, and thus, the common enhancer repertoire is activated differentially by H3K4 monomethylation at a large number of genomic regions.40 Simultaneously, or subsequently, the binding of secondary SDTF establishes tissue-specific enhancers and regulates gene expression.42 Cooccurrence motifs associated with these TFs can be traced back to the fact that enhancers provide integration sites of TFs regulated at the genome level by internal and external environment signals. Accordingly, synergistic binding of TFs can promote the ability to overcome a nucleosomal barrier and initiate chromatin regulatory events. In this way, tissue-specific TFs and tissue-programmed epigenetics of distinct tissue environments control the gene expression of resident macrophages, regulating their functions and affecting the environment itself.By initiating nucleosome remodeling and histone modification deposition that are associated with 43 Particularly, NF-κB also shows the ability to select “latent” or “de novo” enhancers in cooperation with PU.1 to bind to genomic locations lacking prior characteristics associated with active enhancers.44 In fact, a promoter can be affected by a variety of different combinations of enhancers with different SDTF motifs that are intrinsically related to various signaling pathways. This feature of enhancers constitutes great flexibility in tuning gene expression according to the specific needs that macrophages encounter in a context-dependent manner.While some lineage-specific enhancers are “open” and labeled by H3K4me1 in HSCs, it seems that a considerable number of de novo establishments of enhancers occur during hematopoiesis. For instance, many macrophage-specific enhancers are established in granulocyte-macrophage progenitors  but are blocked in HSCs, such as the ones that drive the expression of the gene encoding CD11b, which is the integrin and common myeloid marker.45 These poised enhancers shared by many tissue macrophages are not active but might indicate the potential to respond to local challenges and activate prospective gene-expression programs.46 The research on promoters (H3K4me3+), poised enhancers (H3K4me1+ and H3K27ac−) and activated enhancers (H3K4me1+ and H3K27ac+) has suggested that, independently of development, signals from the local microenvironment play a leading role in the formation of tissue-specific regulatory regions and in the control of gene activity in macrophages.36Generally, active enhancers contain both H3K4me1 marks and H3K27ac marks, while enhancers in the poised state are marked by H3K4me1 and in the absence of the activating acetylation marker H3K27ac.The existence of multiple macrophage progenitors begs the question of whether the ontogenesis of macrophages determines their functional characteristics. In fact, distinct macrophage populations display unique transcriptional characteristics and epigenetic marks that are specific to their tissue of residence Fig. .Fig. 2Ti34 Microglia play diverse roles in the healthy brain, from forming developing neuronal circuits to shaping learning-related plasticity.47 In healthy brains, microglia are highly active and constantly observe the microenvironment with extremely motile processes and protrusions. The transcriptomic and epigenetic phenotypes of microglia are relatively well conserved.48 Snall1 is a microglial unique TF, and its enhancers are open and active only in microglia.36 Therefore, Snall1 controls the transcriptional regulation that maintains microglial identity and physiological properties as a critical factor for CNS homeostasis.49 Recently, the functions of HDAC1 and HDAC2 in microglia have been found to be time- and context-dependent in vivo.50 Prenatal ablation of HDAC1 and HDAC2 results in spontaneous microglial damage due to abundant H3K9ac and H3K27ac deposits on their respective promoters, but the lack of HDAC1 and HDAC2 enhances the phagocytic function of microglial amyloid proteins during neurodegeneration.50 In addition, miR-124, a brain-specific microRNA expressed in microglia but not in peripheral macrophages, has been detected to be a crucial regulator for maintaining the quiescent state of microglia in the CNS.51 In terms of mechanism, miR-124 can reduce the expression of PU.1 and its downstream target, the M-CSF receptor; suppress cell proliferation; and enhance the differentiation of primary macrophages into adult microglia via the C/EBP-α–PU.1 pathway.51 Blood−brain barrier breakdown is associated with brain pathologies and induces prominent monocyte infiltration into the CNS. The monocytes give rise to brain macrophages and can hardly be discerned from resident embryo-derived microglia.52 Microglia and monocyte-derived cells have distinct functions, as revealed by the study of murine multiple sclerosis and the experimental autoimmune encephalomyelitis model.53 During encephalomyelitis, microglia appear dedicated to the clearance of debris, whereas monocyte-derived macrophages are highly phagocytic and inflammatory, with the expression of proinflammatory genes. Specifically, monocyte-derived macrophages are unable to generate long-lived microglia and do not permanently contribute to the brain-resident macrophage compartment, which is thus composed of embryo-derived microglial cells before and after the challenge.54Microglia, the macrophages of the central nervous system (CNS), are resident macrophages in the brain and spinal cord that are entirely derived from the yolk sac during embryogenesis, potentially and specifically due to their privacy behind the blood−brain barrier.55 As the extreme opposite of CNS microglia, embryo-derived macrophages are found in the intestine only shortly after birth. While embryonic precursors seed the intestinal mucosa and demonstrate extensive proliferation in the neonatal period, these cells do not appear in the adult intestine.56 Instead, they are replaced entirely around the time of weaning by the blood inflammatory monocytes that migrate to inflamed tissues, differentiate locally into mature tissue macrophage populations in healthy intestinal lamina propria and contribute to the maintenance of gut homeostasis. Intestinal macrophages are enriched for RUNX family motifs, and RUNX3 is highly expressed in these cells.36 The monocyte infiltration is regulated mainly by the microbiota, which leads to low-grade inflammation. In fact, intestinal macrophages spend their existence bathed in cytokine IL-10 and maintain anti-inflammatory responses that mute any inflammatory response to the gut flora and their products.57 This progress can eliminate the pathogen, avoid collateral damage caused by the oversecretion of proinflammatory cytokines and restore tissue integrity as a result.The intestine contains the largest pool of macrophages among the tissues.58 Before birth, embryo-derived primitive macrophages and fetal monocytes are colonized in the developing lung.59 The initial signs of AMF differentiation appear around the saccular stage of lung development, and it is assumed that fetal monocytes, but not embryo-derived macrophages, are the main precursors of AMFs. With minimal contribution from circulating hematopoietic precursors, AMFs self-maintain locally. After birth, AMFs play an important role in the scavenging of lung surfactant and pulmonary homeostasis. Transcriptional inhibitors Bach1 and Bach2 are required for functional maturation; Bach2 in particular is a major contributor to this repression.60 The lncRNA MEG3-4 has been identified as a tissue-specific regulator of inflammatory responses in alveolar macrophages during bacterial infection through the transcriptional regulation of immune response genes.61 It has been confirmed that the lncRNA MEG3-4 binds to the microRNA miR-138 in a competitive manner with mRNA encoding the proinflammatory cytokine IL-1β, thereby increasing the abundance of IL-1β and enhancing the inflammatory response to bacterial infection in alveolar macrophages in mice.61Alveolar macrophages (AMFs) located in the alveolar cavity develop from fetal liver monocytes depending on CSF2  through the induction of peroxisome proliferator-activated receptor-γ (PPAR-γ).62 Macrophages located near the splenic MZ, the channel through which the bloodstream passes, seem to be uniquely committed to the stationary clearance of apoptotic cells and the selective engulfment of dying cells.63 In the MZ, the nuclear receptor LXRA is essential for macrophage differentiation, as proven in LXRA-deficient mice, which have defective generation of the MZ and metallophilic macrophages.64 In contrast, macrophages in the RP specifically remove aging or damaged red cells and recover the released iron. It has been discovered that the transcription factor Spi-C, a PU.1-related transcription factor, selectively dominates the development of red pulp macrophages.65 Due to the lack of Spi-C, a deficiency of macrophages in the red pulp impairs the clearance of senescent red blood cells and the maintenance iron homeostasis, and selective splenic iron overload occurs in mice with this deficiency.65The spleen-macrophage chamber actually contains several different compartments, including the marginal zone (MZ), red pulp (RP), and white pulp (WP) subtypes, which have independent and noncomplementary functions that are linked to the phagocytic capacity of specific macrophage subpopulations.66 In healthy mice, “large” peritoneal macrophages account for the principal part of the components of peritoneal cavity macrophages but disappear rapidly after stimulation. In addition, “small” peritoneal macrophages, as a source of controversy, predominate in the peritoneal cavity after stimulation. The phagocytosis of these macrophages eliminates apoptotic cells. Evidence suggests that retinoic acid is the tissue-derived signal that induces the localization and functional polarization of peritoneal macrophages in a tissue-specific manner through the reversible induction of GATA6, a specific TF for peritoneal macrophages associated with the establishment of the tissue-specific transcriptional and epigenetic landscape.67 Moreover, previous research has shown that DNA methyltransferase DNMT3A maintains a high expression of HDAC9 in a DNA-methylation-dependent manner in naïve peritoneal macrophages and epigenetically prepares these cells to activate TBK1-IRF3 signaling fully and produce interferon I after virus infection.68As for peritoneal macrophages, there are at least two distinct macrophage subtypes in the abdominal cavity of adult mice.69 Two almost simultaneous studies introduced the importance of commensal microbiota in the production of low levels of IFN.71 It is particularly noteworthy that the microbiota mimics the regulatory components of host protein networks. For example, influenza A virus carries a sequence that resembles H3K4 and can block interactions with readers of H3K4me3, thereby suppressing the positive function of this epigenetic marker.72 Another mechanism that primes macrophages is the maintenance of low levels of negative H3K9me3 marks at IFN response gene loci.15As mentioned above, macrophages promote tissue homeostasis under physiological conditions in distinct manners. In a stable state, tissue macrophages have intrinsic and potential anti-inflammatory functions. Tissue-resident macrophages derived from the yolk sac, fetal monocytes and adult monocytes all exhibit inhibitory effects despite differences in ontogeny. Immunosuppression may be the key function of macrophages in tissue homeostasis. Nevertheless, macrophages in homeostasis are primed to respond rapidly and robustly to subsequent challenges, maintaining low levels of constitutive IFN-β and downstream Janus kinase (JAK)–STAT signaling.18 In contrast, there are epigenetic variations in macrophage populations in different tissues. For example, the Rarb gene, induced by retinoic acid, is labeled by H3K4me2 in all macrophage populations, but H3K27ac only presents in the peritoneal macrophage population.42 The fact that the enhancer region of the Rarb gene is poised in other tissue-resident macrophages but active in peritoneal macrophages is consistent with another finding that peritoneal macrophages are controlled by locally produced retinoic acid, and the Rarb gene itself is retinoic acid inducible.73 This evidence suggests that the enhancers leading to Rarb expression are selected by a series of common macrophage lineage-determining factors in other macrophages and peritoneal macrophages. However, these enhancers can become active only in the peritoneal cavity because of the sufficient concentrations of retinoic acid in the tissue environment.As mentioned above, analyses of enhancer landscapes have revealed that some enhancer-like regions in various tissue-resident macrophage populations are shared and that the combination of PU.1 is required for the development of macrophages in almost all tissues. The enhancer of Spi1, which controls the expression of PU.1, has H3K4me2 and H3K27ac marks in all macrophage populations.In addition to maintaining tissue homeostasis induced by homeostatic signals, macrophages are best known for their role as immune guards at the forefront of tissue defense. In response to various external stimuli and diverse signals, macrophages can obtain heterogeneous activation states and customize specific functions for specific microenvironments. The accurate and specific regulation of macrophage activation to eliminate the pathogenic insult and repair damaged tissue, in turn, is crucial for restoring tissue homeostasis. As shown previously, tissue-specific phenotypes of macrophages, controlled by lineage-specific master regulators, can be generated by hard-wired, irreversible differentiation processes. Alternatively, phenotypes can be reversible and induced as needed based on a functional polarization program.74 In addition, the growth factors GM-CSF and M-CSF, traditionally used to differentiate monocytes into dendritic cells or macrophages, have the ability alone to induce M1- and M2-like phenotypic changes, respectively.75 In fact, the phenotypes of macrophages can switch between different functional states, and the stability of M1, M2 and other phenotypes is unclear. M1 and M2 are more accurate when describing macrophages in vitro, which are induced by specific stimuli. However, in vivo macrophages have heterogeneous phenotypes and multiple polarization states, and thus, they can hardly be simply binned into an M1 or M2 pool. The description of the activation states of these macrophages is currently contentious and confusing. Nonetheless, it is still useful to conceptualize these states as they are still related to the binary M1/M2 classification, and the consensus on the definition offers a reductionist tool to describe extremes of their function and may facilitate the study of macrophages.From the previous literature, two extreme states of activated macrophages are M1-like macrophages (in response to inflammatory stimuli such as LPS and IFN-γ) and M2-like macrophages (in response to cytokines such as IL-4 and IL-13).76 In contrast, M2 macrophages, often referred to as alternatively activated macrophages, have immune-regulatory functions by releasing anti-inflammatory cytokines and decreasing the production of proinflammatory cytokines and show less efficient antigen presentation. In addition, M2 macrophages are predominantly regulatory macrophages involved in tissue remodeling, tumor progression, wound healing, angiogenesis, anti-helminth responses and allergic reactions.M1 macrophages, also known as classically activated macrophages, are inflammatory macrophages characterized by efficient antigen presentation, high bactericidal activity, and the production of proinflammatory cytokines and reactive oxygen and nitrogen species.77 Nevertheless, M2 macrophages accumulate independently of monocytes, and in situ proliferation occurs rapidly to induce the accumulation of macrophages under the control of IL-4.78When early warning signals are triggered, a defined feature of M1 activation is monocyte recruitment from the blood.79 In addition, blood monocytes migrate to inflammatory tissues and differentiate into monocyte-derived macrophages that can restore tissue integrity and eliminate the pathogen.Monocyte-derived macrophages exist in some tissues, such as the dermis and intestine, where monocytes are considered an intermediate developmental stage between bone marrow precursors and tissue macrophages.80 DNA demethylation affects a small group of specific genes that regulate the actin cytoskeleton and phagocytosis and is therefore very important for the structure and function of macrophages.80 Notably, these regions become nucleosome-free and obtain active enhanced markers through enrichment in the binding sites of transcription factors , which can open chromatin, and demethylation catalyzed by 10−11 translocation proteins occurs rapidly.81 A recent study revealed that during macrophage development, the ATP-dependent chromatin remodeling SWI/SNF complex , utilizing two alternative ATP-dependent enzymes, brahma-related gene 1 (BRG1) and brahma (BRM), activates the expression of DNA repair enzymes by recognizing and replacing epigenetically marked nucleosomes, together with EP300 and HDAC1, constituting a functional unit.82 Along the monocyte−macrophage differentiation axis, EP300-HDAC-SWI/SNF functional crosstalk defines the chromatin structure and transcriptional activity of DNA repair enzyme promoters.82In vitro, monocyte cultures imitate inflammatory macrophages in vivo and are used clinically as a crucial tool in basic research. Epigenetically, active DNA demethylation is involved in the entire process of monocyte differentiation into macrophages as a major example of the role of targeted demethylation in cell differentiation.80 In contrast, other miRNAs have been found to be downregulated during monocyte-to-macrophage differentiation. miR-198, which is capable of reducing cyclin T1 protein expression through translational inhibition, for instance, is strongly downregulated during this process.83 The decrease in miR-198 level during macrophage differentiation is beneficial for cyclin T1 protein expression, which has been shown to be important in the regulation of macrophage gene expression.84Recently, high-throughput epigenome analysis has revealed that three miRNAs , which play essential roles in actin cytoskeletal reorganization, are upregulated and overexpressed in the process of monocyte-to-macrophage differentiation.85 Toll-like receptors (TLRs), especially TLR4, are key sensors in the M1 response that triggers cascades of signals to activate inflammatory processes through MAPK, NF-κB and IRF gene networks, which have downstream genes that encode inflammatory cytokines, such as CXCL10, IL-1β, IL-6, IL-12 p40 and TNF.Toll-like receptor ligands, such as LPS, and Th1 cytokines, including IFN-γ, elicit M1 activation alone or in combination and can affect epigenetic processes and lead to epigenetic modifications Fig. .85 Toll-86 A subsequent study revealed that it is a TLR-4-dependent event and depends on histone H3 and H4 acetylation.87LPS affects diverse sets of epigenetic factors that determine the modifications of chromatin structure and gene-expression programs, such as DNA methylation, chromatin-associated complexes, and histone modifications. Until now, however, histone modifications in response to LPS have been studied more extensively. The first evidence on the link between LPS stimulation and epigenetic regulation in inflammatory genes dates back to 1999, as LPS stimulation induces IL-12 p40 production in murine primary activated macrophages by rapid and specific nucleosome translocation at the promoter region.40 In addition, there are gene-specific repressive mechanisms that restrain inflammatory cytokine gene transcription in the absence of TLR signaling. These two opposite effects keep macrophages in a “poised” state. One of the repressive mechanisms is that negative histone marks H3K9me3, H3K27me3, and H4K20me3 are present in the inflammatory gene loci.90 Another mechanism is the occupancy of gene loci by repressors such as nuclear receptors that recruit corepressor complexes that contain sequence-specific transcriptional repressor B cell leukemia 6 (Bcl6).91 In addition, the occlusive positioning of nucleosomes limits the chromatin accessibility of genes such as IL-12b.10Prior to the activation of differentiated macrophages, the locus that encodes inflammatory genes appears to be in a relatively “open” chromatin environment, and the epigenetic landscapes are established during macrophage differentiation as stated earlier. As mentioned above, macrophage master TFs, such as PU.1 and C/EBP family members, bind to and open the enhancers of these genes and thus “prime” them. Enhancers in this state are marked by PU.1, H3K4me1, and open chromatin.93 The induction of inflammatory cytokines by acute-phase protein serum amyloid A depends on JMJD3 activity.94 Only a subset of proinflammatory cytokines such as IL-12b and CCL5, however, shows a strong dependence on JMJD3 demethylase activity to achieve full activation.92Furthermore, these epigenetic “brakes” associated with transcriptional silencing are released after the stimulation of macrophages by TLR ligands. The corepressors are removed from gene loci, and the concomitant reduction of negative histone marks trimethylations by using demethylases. JMJD3, which specifically demethylates trimethylated lysine 27 (H3K27me3), could be induced by NF-κB rapidly under LPS stimulation and recruited to the promoter regions of more than 70% of LPS-induced genes in macrophages and regulate gene transcriptional elongation associated with the H3K27 demethylase KIAA1718.95 Moreover, different kinds of MLLs, such as MLL1, MLL2/4, and MLL3, are critical for the remodeling of the enhancer landscape of macrophage activation.44 In addition, a new study suggests that the methyltransferase Dot1l increases the production of IL-6 and TNF-α by promoting H3K79me2/3 and H3K79me2 at their promoters, respectively.96After removal of negative histone marks of inflammatory genes, positive histone marks, such as H3K4me3 and H3K27Ac, increase. The histone marks H3K4me3 are enriched in the promoter region of the M1 marker gene CXCL10 by histone methyltransferase myeloid lymphoid leukemia (MLL), which is shown to increase upon LPS- and IFN-γ-induced M1 activation of macrophages.97 It has been shown that LPS inhibits the expression of HDAC4, 5 and 7 at first and then upregulates the acetyltransferase complex, leading to cyclooxygenase-2 gene activation.98 During L. pneumophila infection of pulmonary epithelial cells, a similar mechanism has been described for IL-8 induction, accompanied by the initial decrease in HDAC1 and HDAC5.99 Other studies have shown that HDAC6 and HDAC7 are involved in the expression of proinflammatory genes in macrophages stimulated by LPS.101 In fact, a specific subtype of HDAC7 (HDAC7-U) promotes the expression of TLR-induced inflammatory gene subsets, such as EDN1, IL-12p40, and IL-6.101 The inhibition of HDAC6 activity significantly limits LPS-induced macrophage activation and proinflammatory cytokines, regulated by the effects of HDAC6 on cell adhesion and microtubule acetylation.100 In addition, an integrated genomic approach shows that, in response to LPS, HDAC3-deficient macrophages are unable to activate almost half of the inflammatory gene-expression program.102HDACs are strongly involved in M1 activation and play a prominent role in the regulation of immunological pathways. The expression of almost all classes of HDACs is affected upon LPS stimulation, and the sequential regulation of HDAC controls gene-specific expression Fig. . As a ty103 In LPS-activated macrophages, SIRT1 expression is downregulated, and the expression level of these TFs increased.In addition to the histone modification associated with inflammatory genes directly, some mediators target TFs. SIRT1, a specific type of HDAC, suppresses macrophage activation through TFs such as p65, LXR, and IRF8.104 KMT6 directly targets suppressor of cytokine signaling 3 (SOCS3) to promote H3K27me3 and inhibits the expression of SOCS3, leading to uncontrolled TLR-induced NF-κB activation and increased proinflammatory gene expression, therefore playing important roles in regulating the inflammatory responses in macrophages. Moreover, the negative marker H3M27me3 generated by KMT6 persists after termination of the stimulus, and these inhibited genes no longer respond to the glucocorticoids IL-4 and M-CSF.105 In addition, the repression of M2 gene expression is also related to the downregulation of transcription factor MAF and MAF-binding enhancers, coordinated with the loss of LDTF binding and chromatin accessibility.106 Recently, it has been revealed that HDAC2 interacts with the c-Jun promoter and plays a key role in silencing c-Jun expression specifically, the activity of which is important for inhibiting the transcription of a series of inflammatory pathway genes, thereby enhancing proinflammatory gene expression indirectly.107 Moreover, HDAC9, interacting and colocating with many transcriptional repressors or corepressors, including NCOR13, during macrophage differentiation, represses these nuclear receptors by forming multiprotein complexes and thus induces a proinflammatory M1 phenotype.108In addition to the direct combination of pro-inflammatory genes and the regulation of their transcription, regulators aimed at the suppression mechanisms are also required. As a methyltransferase, KMT6  works on H3K27 as a key subunit of polycomb repressive complex 2.109In addition to histone modification, chromatin remodeling occurs during M1 activation. Chromatin remodeling occurs through the ATP-dependent chromatin remodeling complex SWI/SNF, which is preferentially targeted to enhancers and serves as a histone acetylation sensor interacting with acetyltransferase P300 to modulate H3K27ac.110 DNMT1-mediated hypermethylation of SOCS1 results in a loss of SOCS1 expression and enhances the release of LPS-induced proinflammatory cytokines such as TNF and IL-6 in macrophages.110 DNMT1 also induces the hypermethylation of the critical regulators Notch1, PU.1, and KIF4; participates in increasing the dimethylation (H3K9me2) and trimethylation (H3K9me3) of H3K9 in these genes; and skews their polarization towards M1 macrophages.111DNA methylation affected by M1 activation is poorly investigated compared with histone modification and chromatin remodeling. A link between DNA methylation and LPS stimulation has been found for SOCS1, a negative regulator of cytokine signals.112 In contrast, mir-99a inhibits the phenotype and function of M1 macrophages by targeting TNF-α.113Noncoding RNAs are also involved in M1 differentiation and the modulation of proinflammatory polarization. For example, a higher expression of proinflammatory miR-155 and a lower expression of miR-125b favor M1 macrophages.Different from classical activation, the macrophages to be alternatively activated do not require a primed state, but appropriate inducers are needed, such as IL-4 and IL-13.114 Accordingly, the JMJD3-IRF4 axis is necessary for M2 polarization in macrophages. Another study showed that αKG produced by glutamine lysis controls JMJD3-dependent regulation, suggesting the correlation of epigenetic and metabolic reprogramming for M2 macrophages.115 JMJD3 has been indicated to be a critical modifying enzyme in M2 polarization through JMJD3−/− bone marrow chimeras, while the role in M1 activation is dispensable.114 The dual roles of JMJD3 in M1 and M2 macrophages are not inevitably conflicting, suggesting the need to remove the inhibitory H3K27me3 marker to respond to many environmental queues. Moreover, M2 polarization is also due to SMYD3 activity, another H3K4 methyltransferase.95 SMYD3 is preferentially expressed in M2 macrophages and can increase H3R4me3 at the M2-related promoter site.Transcriptional activation induced during M2 polarization is commonly associated with histone demethylase Fig. . The inc+-dependent deacetylase that reduces NF-κB acetylation and increases M2-associated anti-inflammatory responses.116 In contrast, HDAC3 acts as an epigenomic brake on IL-4-induced alternative activation by deacetylating putative enhancers and thereby repressing IL-4-regulated genes characterized by M2 activation.117 Recently, IL-4-activated STAT6 was found to act as a transcriptional repressor in an HDAC3-dependent manner.118 The repressed inflammatory enhancers are associated with reduced LDTF and p300 binding followed by a reduction in enhancer RNA expression, H3K27 acetylation, and chromatin accessibility. Therefore, it can be inferred that HDAC3 plays an important role in M2 activation. Moreover, even without external stimulation, macrophages lacking HDAC3 exhibit an M2-like phenotype and are highly responsive to IL-4.117With respect to deacetylases, the enzymes have both positive and negative effects. For instance, SIRT2 is an NAD119 Additionally, the expression of certain miRNAs, such as miR-142-5p and miR-511, promotes M2 polarization by negatively regulating genes involved in inflammatory signaling.121DNA methylation and noncoding RNAs are also involved in macrophage alternative activation. DNMT3B modulates DNA methylation at the promoter of PPAR1, which is a key transcriptional factor that regulates macrophage polarization.122 After the first IL-4 exposure and subsequent STAT6 activation, PPAR-γ establishes a permissive chromatin environment through the recruitment of coactivator P300 and architectural protein RAD21, and this altered epigenome endows transcriptional memory by promoting the binding of STAT6 and RNA polymerase II. Therefore, the robust production of enhancer and mRNAs are induced upon IL-4 restimulation, and the expression of a hidden gene program, such as extracellular matrix gene network, reaches the threshold of activation only after the second stimulus.To answer the question of whether the IL-4-activated macrophages are homogeneous, a recent study revealed that repeated stimulation with IL-4 induces strong phenotypic changes in macrophages through PPAR-γ, which has a significant ligand-insensitive, genome-bound fraction.4 Moreover, the significant role of epigenetic pathways in macrophages in disease states indicates that epigenetic modifications of macrophages can be used for the diagnosis or therapies of indifferent diseases.Changes in macrophages can cause a broad spectrum of maladaptive immunity and inflammation that are causative factors of disease and thus represent key therapeutic targets.123 In the initiation of atherosclerosis, endothelial cells are activated by the aggregation of low density lipoprotein (LDL) and the modification of it (such as oxidation to oxLDL) in the arterial wall. Monocytes are attracted to adhere and migrate to the vessel wall and then differentiate into macrophages and may become lipid-loaded foam cells. Apoptotic foam cells can form the core of necrosis, and thus, the differentiation of monocytes into macrophages is a key step in the formation of atherosclerosis.Atherosclerosis is a chronic inflammatory disorder as a result of a vascular injury caused by endothelial dysfunction. Macrophages are crucial immune cells in the progression of atherosclerosis and determining the clinical outcome through transmission inflammatory responses, foam cell formation and the final development of necrotic core.124 Nonspecific HDAC inhibitors, however, have contraindications that prevent their direct usage in the treatment of atherosclerosis. Therefore, specific HDAC enzymes deserve further study. HDAC3 has been detected to be a new potential target for atherosclerosis therapy, as deletion of HDAC3 can promote M2 activation while inhibiting M1 polarization.123 These two characteristics are considered to be the advantages of atherosclerosis therapy. Moreover, high expression of HDAC9 is consistent with an increased risk of atherosclerosis.125 HDAC9 upregulation in macrophages during atherosclerosis represses cholesterol efflux and M2 polarization, and in HDAC9-deficient mice, the phenotype of macrophages switches from the proinflammatory M1 to the anti-inflammatory M2 state via PPAR-γ.108Abundant studies have focused on the epigenetic changes of macrophages involved in the pathogenesis of atherosclerosis, especially histone modification and drugs targeting atherosclerosis based on HDACs. It has been demonstrated that HDAC inhibitors have beneficial antiatherogenic effects as they partially inhibit M1 activation, reduce proinflammatory cytokine expression and blunt apoptosis; thus, they do not increase the formation of foam cells in primary macrophages. Valproate, a broad-spectrum HDAC inhibitor, has been shown to inhibit atherosclerosis in animal models.126 Moreover, it has been shown that miR-146a is involved in the pathogenesis of atherosclerosis, which negatively regulates macrophage maturation and inhibits inflammatory activation by reducing the expression of CD86 and CD80.127miRNAs are closely related to atherosclerosis in various aspects, including the regulation of macrophages during atherosclerosis. miR-155 plays a key role in macrophages, supporting and improving inflammation-induced atherosclerosis by directly repressing Bcl6.Obesity and type 2 diabetes (T2D) are rapidly growing diseases and are major risk factors for the development of cardiovascular diseases. Obesity generally tends to classically activate M1 adipose tissue macrophages and decreases alternatively activated M2 macrophages. The different activation states of M1 and M2 contribute to obesity-induced insulin resistance and inflammation.128 In obesity patients, DNMT3B and DNMT1 expression are enhanced, leading to DNA methylation of the promoter of PPAR1, which may induce M2-associated gene suppression and contribute to an inflammatory macrophage phenotype.129 Therefore, the deletion of DNMT1 by using 5-aza-2′-deoxycytidine in pharmacology could promote alternative activation and inhibit macrophage inflammation. Furthermore, several lncRNAs are altered by T2D. One example is the lncRNA E330013P06, which is upregulated in macrophages isolated from T2D mice and the monocytes of T2D patients. The lncRNA E330013P06 may play an important role in macrophage dysfunction and related gene regulation because its overexpression in macrophages enhances the expression of inflammatory genes and increases inflammatory responses to specific signals.130In recent years, research has focused on the epigenetic mechanisms by which macrophages regulate their activation as crucial controllers of inflammation in T2D and therefore provide new insights into therapeutic interventions. Hyperlipidemia and hyperglycemia in diabetes patients could cause epigenetic changes and promote the formation of an inflammatory macrophage phenotype. In macrophages isolated from hyperlipidemia and a T2D mouse model of hindlimb ischemia, inflammatory genes are hypomethylated, and M2 genes are hypermethylated.131 As the repair/remodeling phase progresses, phenotypic transformation occurs in macrophages. During the late stage of repair, macrophages provide an M2 gene-expression profile predominantly, resulting in an increase in the number of M2  macrophages and the release of growth factors such as TGF-β, IL-10 and IGF.131 Delayed wound healing is a serious diabetes-related complication that often leads to nontraumatic limb amputations.Wound healing is a well-coordinated dynamic process involving diverse cells, including three main stages of coagulation and inflammation, tissue formation and remodeling. Macrophages are one of the critical participants in wound healing. Since the occurrence of injury, the functional changes of macrophages at the wound site persist. The major M1 subtype occurs mainly in the early inflammatory phase and is responsible only for the phagocytosis of bacteria, neutrophils, and tissue debris and the release of cytokines such as TNF-α and IL-6.132 It has recently been demonstrated that hyperglycemia leads to changes in the microRNA signature in wound healing, and they have been found to play a role in the dysregulated inflammation of diabetic wounds. For instance, miR-146a has been demonstrated to be downregulated in diabetic wounds and is unable to regulate its proinflammatory target gene expression, such as the NF-κB p65 subunit, leading to wound-healing impairment.133Given the role of epigenetic mechanisms in T2D, attention has recently been paid to epigenetic changes in diabetic wounds, and it has been revealed that a large number of epigenetic changes in diabetes lead to delayed wound healing. Alterations in histone methylation have been suggested to be a damaging factor for diabetic wound healing. The expression of IL-1β is increased in macrophages in diabetic wounds, and the abnormal expression of IL-1β impairs wound healing. After stimulation with LPS, the expression of IL-1β is increased in macrophages isolated from wounds of the T2D mouse model, with increased H3K4 methylation and decreased H3K27 methylation, suggesting that the expression of IL-1β is regulated by an epigenetic mechanism.134 During sepsis, white blood cells and platelets migrate to the infection site, resulting in platelet aggregation, endothelial damage, and increased microvascular permeability. Blood flow also decreases, which may introduce ischemia-reperfusion injury. These physiological processes can induce systemic inflammatory response syndrome, leading to multiple organ dysfunction syndrome.Sepsis is a worldwide disease with high morbidity and mortality rates, especially in intensive care units. Sepsis occurs when the body reacts to infectious and noninfectious stimuli that cause a nonresolving inflammatory response and cytokine release and then induce the injury of tissues and organs, leading to multiorgan failure, shock, and death.It is now well established that macrophages and other innate immune cells are activated profoundly during sepsis, playing a key role in the pathogenesis of this disease. In particular, dysregulated and profound activation macrophages can influence immune function and can directly affect the prognosis of sepsis.135 The selective inhibition can significantly reduce levels of proinflammatory mediators, inhibit macrophage apoptosis, promote bacterial clearance, increase immune cell phagocytosis, and improve survival in a lethal murine model of sepsis. The expression of microRNA-Let7A (let-7a) in patients with sepsis caused by gram-negative bacilli has been shown to be significantly downregulated.136 Let-7a has been confirmed to regulate the Toll-mediated inflammatory response in sepsis, thus providing a potential target for sepsis treatment. Recently, it has been demonstrated that lncRNA NEAT1 is upregulated in patients with sepsis and that overexpressed NEAT1 plays a key role in acute kidney injury induced by sepsis.137 Moreover, it has been found that the lncRNAs NEAT1/Let-7a and Let-7a/TLR4 have direct combinations. In the pathogenesis of sepsis, increased lncRNA NEAT1 binds to Let-7a competitively, and TLR4 is released from Let-7a, which is activated and stimulates downstream signals, leading to severe inflammatory responses.138Macrophage epigenetics plays an important role in the immune response associated with sepsis. For instance, the inhibition/modulation of HDACs can serve as a therapeutic approach for sepsis via modulating the epigenetic pathway. In particular, HDAC6 inhibitor has a substantial advantage in the treatment of sepsis.139 The molecular mechanisms responsible for memory-like activity in macrophages have not yet been elucidated. However, epigenetic regulations most likely induce these changes  and 155 Considering the relatively short lifespan, the ability of macrophages to transmit memory phenotypes to offspring and provide sustained protection remains unclear. In fact, the efficacy of generating long-term innate immune memory is essential to enhance organism immunity. Therefore, immune memory has also been studied for insights into HSCs, long-lived cells that are self-renewing and capable of producing multipotent and lineage-committed hematopoietic progenitors that give rise to all cells of the mammalian blood system, including macrophages.156 HSCs educated with BCG produce epigenetically modified macrophages, which are better than HSCs educated without BCG in preventing M. tuberculosis infection.157Innate immunity training plays an important role in disease prevention, among which research on Bacillus Calmette-Guérin (BCG) is a typical example. BCG can be used to train macrophages ex vivo and thereby provide cross-protection.Macrophages can be trained or tolerized for specific inflammatory stimuli, depending on the type of trigger. In trained immunity, the initial hit induces long-lasting histone marks. In the case of the second hit, H3K27ac and H3K4me3 have already primed the genes, and expression is enhanced. In contrast, in tolerance, the first stimulation leads to the activation of macrophages, but the removal of the stimulus results in the loss of the activating marks. In addition, suppressive nucleosome remodeling complexes and histone enzymes are involved in the process.Macrophages, heterogeneous cells whose surroundings regulate their phenotypes and functions, have central roles in danger detection, inflammation and host defense. Tissue-resident macrophages are specific to the environment and play a critical role in the maintenance of tissue homeostasis to maintain physiological functions. Under different transcriptional profiles and various stimulations, M1/M2 macrophages have almost opposite functions and different transcriptional profiles, but both of these cell types have unique abilities to destroy pathogens or repair inflammation-mediated damage; therefore, these cells are also necessary for restoring homeostasis. It is becoming increasingly clear that epigenetic modifiers have the ability to determine the fate of macrophages, whether in the health tissues or at the site of tissue injury. Therefore, the application of the epigenetic paradigm in macrophage studies is of great value. The dynamic regulation of epigenetic patterns in macrophages provides opportunities to alter disease-related epigenetic status. Hence, it can be assumed that understanding the epigenetic regulation of macrophages will substantially contribute to medicine in terms of diagnostic and therapeutic mechanisms and modalities.Overall, work on the epigenetic regulation of macrophages has laid the foundation for the development of human medicine, and thus, this issue deserves more extensive and thorough study.


In macrophages, specific transcriptional programs are dictated by the transcription factor PU.1 that primes distal regulatory elements for macrophage identities and makes chromatin competent for activity of stimuli-dependent transcription factors. Although the advances in genome-wide approaches have elucidated the functions of these macrophage-specific distal regulatory elements in transcriptional responses, chromatin structures associated with PU.1 priming and the underlying mechanisms of action of these cis-acting sequences are not characterized.Cell type-specific use of Atp1b3 locus as a model, we show that FACT binds to two positioned nucleosomes surrounding a TRIM33/PU.1-bound site in a region, located 35 kb upstream the Atp1b3 TSS, that interact with the Atp1b3 promoter. At this − 35 kb region, TRIM33 deficiency leads to FACT release, loss of the two positioned nucleosomes, RNA Pol II recruitment and bidirectional transcription. These modifications are associated with higher levels of FACT binding at the Atp1b3 promoter, an increase of RNA Pol II recruitment and an increased expression of Atp1b3 in Trim33−/− macrophages.Here, we show that, in macrophages, FACT subunit SPT16 can bind to positioned nucleosomes directly flanking PU.1-bound sites at previously uncharacterized distal regulatory elements located near genes essential for macrophage development and functions. SPT16 can interact with the transcriptional co-regulator TRIM33 and binds to half of these sites in a TRIM33-dependent manner. Using the Thus, sequestering of SPT16/FACT by TRIM33 at PU.1-bound distal regions might represent a new regulatory mechanism for RNA Pol II recruitment and transcription output in macrophages.The online version of this article (10.1186/s13072-019-0288-3) contains supplementary material, which is available to authorized users. Genome-wide approaches have indicated the mechanisms underlying the selection and the control of the timing and the magnitude of enhancer activation in transcriptional responses . Nucleoscis-regulatory elements. The transcription factor PU.1 binds most of these cis-acting regulatory elements and, in combination with other transcriptional regulators such as C/EBPα or RUNX1, promotes the creation of a macrophage-specific enhancer landscape. In addition, binding of PU.1 makes chromatin competent for binding and activity of stimuli-dependent transcription factors, such as NF-κB, AP-1, STAT or IRF family members [Macrophages exhibit functional diversity and ability to undergo rapid reprogramming depending on their microenvironment, and this plasticity is driven by functionally diversified  members , 4.Ifnb1 gene transcription during the late phase of macrophage activation by preventing recruitment of the co-activator p300 [We previously identified the transcriptional regulator TRIM33 as an important co-repressor of PU.1 activity in myeloid cells . TRIM33 tor p300 .The histone chaperone FAcilitates Chromatin Transcription (FACT) is a heterodimer of SPT16 and SSRP1 proteins, highly conserved among eukaryotes. FACT was initially identified as essential for transcriptional elongation through chromatin templates . AssociaHere, we show that the FACT subunit SPT16 binds on positioned nucleosomes flanking PU.1-occupied sites in proximity of genes essential for macrophage development and function. We provide evidence for the interplay between FACT and TRIM33 in maintaining a stable chromatin structure at a PU.1-bound distal regulatory region to prevent non-coding transcription and to limit nearby gene transcription.trans-acting factors  was investigated by ChIP-sequencing (ChIP-seq) that identified 7943 SPT16-occupied regions. 78% of the SPT16 peaks were located in intragenic regions and promoters , chemokines such as Ccl3 and Mmp12, a member of the matrix metalloproteinase family . However, analyses of distal SPT16/TRIM33 regions, in which SPT16 was abrogated in Trim33−/− BMDM, showed a higher accessibility in Trim33−/− compared to WT BMDM   cell line, a stress condition that mimics lack of nutrients, resulted in decreased TRIM33 protein expression  restored TRIM33  and RNA Pol II binding and were found near actively transcribed genes, suggesting a potential contribution of intergenic SPT16 binding in maintaining and/or activating expression of genes regulated by PU.1. Addressing a specific role of intergenic SPT16 in nearby gene transcription is challenging as inhibition of FACT causes impaired transcription elongation of nearby genes as a direct consequence of FACT release from their gene bodies.Atp1b3 gene as a model, we identified a regulatory region, bound by the FACT/TRIM33 complex, that is critical to maintain a chromatin structure that represses local non-coding transcription and limits the binding of FACT on the Atp1b3 promoter  were obtained as previously described [To generate deletion of escribed . BMDM weChIP experiments were performed essentially as previously described . For ChIp value threshold of 1e−05. Peaks were then annotated according to genomic features of Ensembl v67 using Homer . Promoter-TSS was defined from − 1 kb to + 100 bp relative to the position of the TSS and TTS from − 100 bp to + 1 kb relative to the position of the TTS. Intergenic SPT16 peaks that overlap with the mm9 blacklist from ENCODE were additional filtered out. Functional annotation analyses were performed using GREAT or DAVID web-tools. Overlap between SPT16 and PU.1 or TRIM33 peaks was performed using BedTools, requiring at least 1 bp overlap. Enrichment profiles and comparisons of ChIP-seq datasets at indicated regions were performed using DeepTools on Galaxy . Data were represented as heatmaps, average density plots or boxplots. Annotation of combinatorial chromatin states for H3K4me3, H3K79me2 and H3K36me3 marks was performed with the ChromHMM software (http://compbio.mit.edu/ChromHMM/) at 200 bp bin interval in WT and Trim33−/− BMDM using the corresponding input as background control.Single-end 50 bp reads were mapped to the mm9 genome assembly using Bowtie 1.0.0 with the following arguments: -m 1 –strata –best -y -S -l 40 -p 2. Peak detection was performed using the MACS software  with the2, 0.1% Igepal) and resuspended in Tn5 transposase mixture , and 0.2 mg/ml digitonin (Promega). The tagmentation reaction was carried out for 30 min at 37 °C followed by DNA purification using the MinElute Reaction Cleanup kit (Qiagen). Tagmented DNA was amplified with NEBNext High-Fidelity PCR Master Mix (NEB) and sequencing primers Ad1_noMX and Ad2.1-4 indexing primers [ATAC-seq was carried out as previously described , in two  primers . Librari2 for 10 min at 37 °C. Reaction was stopped by addition of excess of EDTA. The nuclei were then digested by 0.5 mg/ml of Proteinase K (Invitrogen) and DNA isolated by phenol-chloroform extraction. Purified DNA was then run in a 1% agarose gel and the mononucleosomal band cut and purified with the Qiagen gel extraction kit. The resulting material was analyzed by sets of overlapping primer pairs, each generating amplicons of 60–80 bp with 15–25 bp overlap between neighboring amplicons.Cells were cross-linked with 1% formaldehyde and lysed in PBS/0.5% Triton X-100. Micrococcal nuclease (MNase) digestion was performed on isolated nuclei with indicated concentrations of MNase (New England Biolabs) in 50 mM Tris-HCl, 5 mM CaClFor metabolic labeling of newly synthesized RNA, BMDM were incubated with 150 μM of 4sU  for 10 min prior to RNA extraction. Total RNA was extracted with the miRNeasy kit (Qiagen). Biotinylation reaction was carried out with 1 µg of total RNA in labeling buffer  and 0.2 mg/ml EZ-Link HPDP-Biotin (Pierce) for 2 h at room temperature. Unbound HPDP-Biotin was removed by chloroform/isoamylalcohol (24:1) extraction. Biotinylated RNA was isolated using streptavidin magnetic beads (New England Biolabs), eluted in 100 mM DTT and cleaned up with RNeasy MinElute Spin columns (Qiagen).Total RNA was extracted with the RNeasy Plus Micro kit (Qiagen) and reverse transcribed with random primers and Superscript IV (Life Technologies). Quantitative PCR was performed using the Power SYBR green PCR master mix (Applied Biosystems).3C assays were carried out essentially as described previously . Briefly2, 10% glycerol, 0.2% NP-40 and protease inhibitor cocktail).For TRIM33 and ATP1B3 immunoblotting, total proteins were extracted in lysis buffer  and nuclei were extracted in 20 mM HEPES-KOH pH 7.9, 25% glycerol, 420 mM NaCl, 1.5 mM MgCl2, 0.2 mM EDTA, 0.5 mM DTT and protease inhibitor cocktail. Immunoprecipitation of FLAG-TRIM33 was carried out with 10ug of FLAG antibody cross-linked to protein G-Sepharose beads (Millipore), as previously described [Trim33−/− IM were considered as positive hits.For mass spectrometry, IM were resuspended in hypotonic buffer , SPT16 , SSRP1 , PU.1 , ATP1B3 , RNA POLII , H3K4me3 , H3K79me2 , H3K36me3 , FLAG .Primer sequences for RT-qPCR are available upon request.Additional file 1: Figure S1.Related to Fig. 1. a Examples of SPT16 ChIP-seq profiles in BMDM along with RNA Pol II occupancy. b Functional annotations of genes nearest to intergenic SPT16 peaks in BMDM. c SSRP1 ChIP-qPCR analysis at indicated SPT16-bound distal regulatory regions in BMDM. A region in the beta globin promoter is used as a negative control. d Representative examples of SPT16 ChIP-seq profiles in BMDM along with RNA Pol II occupancy and ChromHMM analysis at indicated genes associated with intergenic SPT16 peaksAdditional file 2: Figure S2.Related to Fig. 2. a Overlap between SPT16 and TRIM33 peaks in BMDM. b Gene Ontology (GO) annotations of genes nearest to intergenic SPT16/TRIM33 peaks in BMDM. c Scatter plot showing global correlation of SPT16 binding in WT and Trim33−/− BMDM. The Spearman coefficient value is given. d Normalized SPT16 tag count at most enriched (Top10%) intergenic SPT16 peaks that did not colocalized with TRIM33. ns: not significant, Paired t test. e SSRP1 ChIP-qPCR at indicated SPT16/TRIM33 bound regions in WT and Trim33−/− BMDM. Mean ± SEM, n = 3. f PU.1 ChIP-qPCR analysis at indicated SPT16/TRIM33 bound regions in WT and Trim33−/− BMDM. Mean ± SEM, n = 3. g SPT16 ChIP-qPCR in WT and Trim33−/− BMDM (left) and in Trim33−/− immortalized macrophages (IM) and in Trim33−/− IM rescued with exogenous TRIM33 (Trim33−/− + WT TRIM33) (right). h Immunoblotting of FLAG-TRIM33, PU.1 and b-ACTIN in Hela cells transfected with the indicated vectors (left). FLAG-TRIM33 ChIP-qPCR at the reporter vector containing three PU.1 binding sites. Mean ± SEM, n = 2. i PU.1 and TRIM33 occupancy at the Atp1b3/Rnf7 locus in BMDMAdditional file 3: Figure S3.Related to Fig. 3. a mRNA levels of Tgfbi, Mmp12, Cd72 and Napepld in WT and Trim33−/− BMDM. Data are presented relative to expression of WT BMDM. Mean ± SEM, n = 4. b UCSC genome browser image of RNA Pol II at the Rnf7 gene in WT and Trim33−/− BMDM. c UCSC genome browser image of indicated chromatin modifications along with ChromHMM analysis at the Rnf7 gene in WT and Trim33−/− BMDM. d Immunoblotting showing TRIM33 expression in RAW cells grown in culture medium containing 10% or 0.1% FCS for 2 h and 6 h. e TRIM33 occupancy at the − 35 kb site in RAW cells grown in culture medium containing 10% or 0.1% FCS for 2 h and 6 h. Mean ± SEM, n = 2. fAtp1b3 mRNA expression levels in RAW cells grown in culture medium containing 10% or 0.1% FCS for 2 h and 6 h. Mean ± SEM, n = 2. g Immunoblotting showing ATP1B3 expression in RAW cells grown in culture medium containing 10% or 0.1% FCS for 2 h and 6 hAdditional file 4: Figure S4.Related to Fig. 3. a SSRP1 ChIP-qPCR at the indicated positions in the Atp1b3 gene in WT and Trim33−/− BMDM. b 3C analyses of interaction between the − 35 kb region and the Rnf7 promoter. See Fig. c Kinetics of Irf7, Ifit3 and Isg15 mRNA relative expression in WT and Trim33−/− BMDM treated with CBL. Data are presented relative to expression of untreated WT BMDM. Mean ± SEM, n = 3. d 3C analyses at the Atp1b3/Rnf7 locus in WT and Trim33−/− BMDM treated for 4 h with CBL. See Fig. e SPT16 and RNA Pol II metaprofile analyses at indicated gene bodies in WT and Trim33−/− BMDM. f Fold decrease in WT and Trim33−/− BMDM, expressed as the ratio between DMSO and CBL-treated BMDM, of pre-mRNA levels of genes regulated by an intergenic SPT16/TRIM33 complex. Mean ± SEM, n = 3Additional file 5: Figure S5.Related to Fig. 4. a H3K4me1, H3K4me2 and H3K27ac histone modification marks at the − 35 Kb region in BMDM. Also shown the TRIM33 peak. b H3K4me1 ChIP-qPCR at the − 35 kb region in WT and Trim33−/− BMDM. Regions near to Ifnb1 and Irf1 genes are used as positive controls and a region in the beta globin promoter is used as a negative control. c Representative image of MNase digestion profile. Nuclei from WT and Trim33−/− BMDM were digested with increasing amounts of MNase. d Representative image of MNase digestion profiles of chromatin from WT and Trim33−/− BMDM before mono-nucleosome purification. e TRIM33 ChIP-qPCR at the − 35 kb region in Trim33−/− and Trim33−/− + WT TRIM33 IM. f Kinetics of Atp1b3 mRNA levels in WT and Trim33−/− BMDM treated for the indicated times with pIpC (left), Ifnb1 (middle) and LPS (right). Data are presented relative to expression of untreated WT BMDM