The mechanism by which Meishan (MS) sows are superior to white crossbred sows in ovarian follicle development remains unclear. Given gut microbiota could regulate female ovarian function and reproductive capacity, this study aimed to determine the role of gut microbiota-ovary axis on follicular development in sows.2O2-induced cell apoptosis model was used to evaluate the effects of multi-omics identified metabolites on the apoptosis of porcine ovarian granulosa cells in vitro.We compared the ovarian follicular development, gut microbiota, plasma metabolome, and follicular fluid metabolome between MS and Landrace × Yorkshire (L × Y) sows. A H2O2-induced porcine granulosa cells apoptosis in vitro.Compared with L × Y sows, MS sows have greater ovary weight and improved follicular development, including the greater counts of large follicles of diameter ≥ 5 mm, secondary follicles, and antral follicles, but lesser atretic follicles. The ovarian granulosa cells in MS sows had alleviated apoptosis, which was indicated by the increased BCL-2, decreased caspases-3, and decreased cleaved caspases-3 than in L × Y sows. The ovarian follicular fluid of MS sows had higher concentrations of estradiol, progesterone, follicle-stimulating hormone, luteinizing hormone, and insulin like growth factor 1 than L × Y sows. Gut microbiota of MS sows formed a distinct cluster and had improved alpha diversity, including increased Shannon and decreased Simpson than those of L × Y sows. Corresponding to the enhanced function of carbohydrate metabolism and elevated short-chain fatty acids (SCFAs) in feces, the differential metabolites in plasma between MS and L × Y sows are also mainly enriched in pathways of fatty acid metabolism. There were significant correlations among SCFAs with follicular development, ovarian granulosa cells apoptosis, and follicular fluid hormones, respectively. Noteworthily, compared with L × Y sows, MS sows had higher follicular fluid SCFAs concentrations which could ameliorate HMS sows have more secondary and antral follicles, but fewer atretic follicles and apoptotic ovarian granulosa cells, as well as harbored a distinctive gut microbiota than L × Y sows. Gut microbiota may participate in regulating ovarian follicular development via SCFAs affecting granulosa cells apoptosis in sows.The online version contains supplementary material available at 10.1186/s40104-023-00865-w. Ovulation rate, the number of oocytes ovulated from matured ovarian follicles per estrus cycle, is the decisive factor affecting the litter size in sows , 2. MoreThe gut microbiome, as part of hologenome (the collective genomic content of a host and its microbiome), has reported to affect ovarian function and reproductive capacity –11. For Given that MS sows can have 11.3 more pre-ovulatory follicles and 10 more released oocytes in an estrus cycle than Large-White hybrid sows , the aimThis animal experiment was carried out in accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals Monitoring Committee of Hubei Province, China, and the protocol was approved by the Scientific Ethics Committee of Huazhong Agricultural University .g, for 10 min) for plasma. Immediately after slaughter, feces from rectum were collected and placed in liquid nitrogen. The weight and large follicle count (diameter ≥ 5 mm) of left and right ovaries were determined, respectively. Half of the left ovary was fixed in 4% paraformaldehyde solution for measuring ovarian morphology and the rest were placed in liquid nitrogen. The contents of follicles (diameter ≥ 3 mm) from the right ovary were pooled and collected in a tube and allowed to settle for 5 min [g at 4 °C for 30 min to separate granular cells from the follicular fluid [Eight MS sows (age 95 ± 7 d and weight 26.94 ± 3.48 kg) from the National Conservation Farm of MS Pigs  and 7 L × Y sows (age 90 ± 4 d and weight 38.98 ± 4.45 kg) from a commercial farm were housed in the same pig-house and had ad libitum access to water and diets. The diets Table S were preor 5 min . The supar fluid . The fol2O2 , BCL-2 , Caspase-3 , and Cleaved Caspase-3 .Paraformaldehyde , DMEM , FBS , penicillin/streptomycin , Hn = 7) were dehydrated in a graded series of alcohols and then embedded in paraffin wax. The section (10 μm) of embedded ovary tissue was dried at 56 °C for 24 h. Next, slides were rehydrated in a graded series of ethanol. After a brief wash in distilled water, we incubated the slides with hematoxylin solution. The sections were then washed with running tap water to remove excess hematoxylin. Then, we differentiated the sections in 1% acid alcohol for 30 s and then washed them with running tap water for 1 min. This step was followed by an incubation in the eosin counterstain, subsequent dehydration in a graded series of ethanol, and immersion in xylene.H&E staining was conducted as reported . Briefly2), and the numbers of secondary, antral, and atretic follicles were counted in the whole section of H&E-stained ovary (n = 7).Follicle counting was performed as previously described with minor modifications . Brieflyg, 5 min), and then inoculated in a 6-cm dish. Cells were cultured in a complete culture medium containing 89% DMEM , 10% FBS , and 1% penicillin-streptomycin  at 37 °C under 5% CO2 throughout this trial. When the confluence of the cells reached approximately 90%, the cells were transferred to 12-well plate for the next experiment. H2O2-induced apoptosis model of sow granulosa cells was constructed as previously described with minor modifications [2O2  (200 μmol/L) [n = 7).Fresh sow ovaries (20 selected ovaries from 13 sows at 2–3 estrous cycle) were obtained from a commercial slaughterhouse. Sow ovarian granulosa cells were collected from follicles  using a syringe , 23. Theications . Briefly μmol/L)  or the v2O. The cells with red fluorescence were defined as apoptotic cells, and the ratio of TUNEL positive granular cells were determined using computer-assisted morphometry .The TUNEL assay was used to mark apoptotic ovarian granular cells in paraffin section . For parg, 4 °C for 15 min, the supernatants were collected, and their protein concentrations were determined using BCA kit . An equivalent amount of protein (12 μg) was separated by polyacrylamide gel electrophoresis and transferred to a polyvinylidene fluoride membrane. After TBST cleaning and sealing with 5% skim milk, the membrane was incubated with rabbit polyclonal antibodies BCL-2 , Caspase-3 , and Cleaved Caspase-3  at 4 °C overnight. The membrane was then incubated with secondary antibody  at room temperature for 1.5 h. Bands were measured by densitometry using image J software and relative protein expression levels were standardized with β-actin.The granular cells were homogenized in RIPA buffer and then on ice for 30 min. After centrifugation at 12,000 × The concentrations of follicle-stimulating hormone , estradiol , progesterone, and insulin-like growth factor 1 in follicular fluid were determined using commercial pig ELISA kits  according to the manufacturer’s instructions.After thoroughly homogenizing with zirconia beads, the total genomic DNA of a single sow’s fecal microbiota was extracted using the TGuide S96 Magnetic Soil/Stool DNA kit  according to manufacturer’s instructions. Concentration and purity of the DNA were determined using a NanoDrop ND-1000 spectrophotometer . V4 hypervariable regions of 16S rRNA genes  was used for PCR amplification. Purified amplicon products were pooled in equimolar and paired end sequenced (2 × 250) on an Novaseq 6000 platform  at Biomarker Technologies Co., Ltd. .The sequencing raw data was analyzed using the QIIME2 platform (version 2021.6) . USEARCHg) at 4 °C for 10 min. The supernatant was transferred into a new centrifuge tube (2-mL) and mixed with 0.2 mL 25% metaphosphoric acid. After 30 min at 4 °C, the tube was centrifuged  again at 4 °C for 10 min. To quantify SCFAs, a calibration curve for SCFAs was constructed.The function of gut microbiota was analyzed using PICRUSt2 based on 16S rDNA data and reference genome . The gutPlasma metabolites were extracted as previously described . Metaboln = 7) were determined using liquid chromatography-tandem mass spectrometry  with multiple reaction monitoring. This system allows accurate quantification of low abundance metabolites (up to pg level). Briefly, sample preprocess is as follows. 1) Preparation of standard curve: Take 7 kinds of SCFAs mixed standards  and carry out gradient dilution; 2) Take 20 μL sample and standard curve sample, add 60 μL cold MeOH/ACN (2:1) of standard song, shake for 5min, precipitate at −20 °C for 4 h, centrifuge at 20,000 × g at 4°C for 15 min, and take 40 μL supernatant in an EP tube; 3) Derivatization: Add 20 μL 200mmol/L 3-NPH (solvent 50% ACN) and 20 μL 120 mmol/L EDC-6% pyridine mixture (solvent 50% ACN) into the EP tube containing 40 μL supernatant respectively, and place it in a metal bath incubate with shaking at 40 °C for 30 min. Cool to room temperature on ice and centrifuge briefly. Add 80 μL 1000D internal standard (solvent is 10% ACN) to the derivatized EP tube, and mix well; 4) Add 90 μL H2O and 90 μL derivatized sample to the filter plate, centrifuge at 3,000 × g at 4 °C for 5 min, take 90 μL filtered liquid in a new 96-well plate, and load 10 μL on the LC-MS. In MultiQuant software , the default parameters are used for automatic identification and integration of each MRM transition (ion pair), and manual inspection is assisted. The content of SCFAs (ng/mL) were obtained by substituting the integrated peak area of the target index in the sample into the standard curve.The absolute concentrations of SCFAs in ovarian follicular fluid    and antral follicles (P < 0.001), but have a smaller count of atretic follicle (P < 0.001)  Fig. B and C. P < 0.001) , whereas have lower levels of pro-apoptosis proteins caspases-3 (P < 0.01) and cleaved caspases-3 (P < 0.001) than those of L × Y sows  Fig. A and B. ows Fig. C–G.Fig. P < 0.001, Fig. P < 0.01, Fig. P < 0.05, Fig. P < 0.01, Fig. P < 0.001, Fig. Follicular fluid was collected from fresh ovaries Fig. A. The ovP = 0.0008, PC1 and PC2 explained 40.77% and 29.86% of the variation, respectively)  and decreased Simpson (P < 0.05). Linked-bar plots showed that MS sows have an obvious different composition of gut microbiota at the levels of phylum  but have decreased functions of translation (P = 0.041) and membrane transport (P = 0.049) , butyrate (P < 0.01), isobutyrate (P < 0.05), valerate (P < 0.05), and isovalerate (P < 0.001) in rectal feces than L × Y sows  Fig. C. Correse P < 0.0, valeratP = 0.004, Fig. P = 0.0025, Fig. P < 0.01), butyrate (P < 0.05), isobutyrate (P < 0.05), valerate (P < 0.05), and isovalerate (P < 0.01) than L × Y sows  positively associated with follicles of diameter ≥ 5 mm, antral follicles, estradiol, progesterone, LH, IGF-1, and BCL-2; but was negatively associated with apoptosis, caspases-3, and cleaved caspases-3, respectively. Correspondingly, for SCFAs in feces, acetate was negatively associated with atretic follicles (P < 0.05); propionate was significant (P < 0.05) positively associated with antral follicles, LH, progesterone, estradiol, and BCL-2, but was significant (P < 0.05) negatively associated with atretic follicles, cleaved caspases-3, caspases-3, and apoptosis; butyrate was significant (P < 0.05) positively associated with antral follicles, progesterone, estradiol, and BCL-2, but was significant (P < 0.05) negatively associated with atretic follicles, cleaved caspases-3, caspases-3, and apoptosis; isobutyrate was significant (P < 0.05) positively associated with antral follicles, secondary follicles, IGF-1, FSH, progesterone, and estradiol, but was significant (P < 0.05) negatively associated with atretic follicles, cleaved caspases-3, caspases-3, and apoptosis; valerate was significant (P < 0.001) positively associated with antral follicles, but was significant (P < 0.05) negatively associated with atretic follicles and cleaved caspases-3; isovalerate was significant (P < 0.05) positively associated with antral follicles, secondary follicles, follicles of diameter ≥ 5 mm, IGF-1, LH, progesterone, estradiol, and BCL-2, but was significant (P < 0.05) negatively associated with atretic follicles, cleaved caspases-3, caspases-3, and apoptosis. For SCFAs in plasma, acetate was significant (P < 0.01) positively associated with primary follicles; propionate was significant (P < 0.05) positively associated with antral follicles and BCL-2, but was significant (P < 0.05) negatively associated with atretic follicles, cleaved caspases-3, and caspases-3; butyrate was significant (P < 0.05) positively associated with antral follicles, FSH, progesterone, estradiol, and BCL-2, but was significant (P < 0.05) negatively associated with caspases-3, and apoptosis; isobutyrate was significant (P < 0.05) positively associated with antral follicles, follicles of diameter ≥ 5 mm, and estradiol, but was significant (P < 0.05) negatively associated with atretic follicles, cleaved caspases-3, caspases-3, and apoptosis; valerate was significant (P < 0.001) positively associated with antral follicles, secondary follicles, and BCL-2, but was significant (P < 0.05) negatively associated with atretic follicles, cleaved caspases-3, and apoptosis; isovalerate was significant (P < 0.001) positively associated with antral follicles, secondary follicles, follicles of diameter ≥ 5 mm, IGF-1, progesterone, estradiol, and BCL-2, but was significant (P < 0.05) negatively associated with atretic follicles, cleaved caspases-3, caspases-3, and apoptosis.As shown in Fig. P < 0.001), butyrate (P < 0.01), isobutyrate (P < 0.001), valerate (P < 0.01), isovalerate (P < 0.001), and total SCFAs (P < 0.001) than L × Y sows , which was ameliorated by SCFAs treatment at the concentrations in follicular fluid (P < 0.01). In the negative control group, false positive reactivity was not observed.As shown in Fig. ows Fig. B. Porcinows Fig. C. Fig. 8Here, we found that MS sows have greater ovary weight and have more follicles with diameter ≥ 5 mm than L × Y sows. Further morphological analysis indicated that MS sows have more secondary and antral follicles but have less atretic follicle than L × Y sows. These results are comparable with an earlier comparative study which showed that hyper-fertility MS sows even had 11.3 more pre-ovulatory follicles and ovulate 10 more occytes in an estrus cycle than Large-White hybrid sows . For theFibrobacter, Oscillospira, and Bacteroidaceae were the marker bacteria of MS sows, whereas Erysipelotrichaceae, Erysipelotrichales, Erysipelotrichi, Veillonellaceae, Lachnospiraceae, Streptococcaceae, Bacilli ,and Lactobacillales were the marker bacteria of L × Y sows. Compared with the L × Y sows, gut microbiota of MS sows has an increased function of carbohydrate metabolism but have decreased functions of translation and membrane transport. Correspondingly, MS sows have increased concentrations of SCFAs including propionate, butyrate, isobutyrate, valerate, and isovalerate in rectal feces than L × Y sows. Compared well with our results, the alpha diversity of gut microbiota, the relative abundance of Fibrobacter, and fecal SCFAs were increased in MS sows whose litter sizes had been improved by dietary crude fiber supplementation [Gut microbiota, known as the second genome and a substantial endocrine organ, has been reported to affect host reproductive hormones production and metabolism , 39–43. entation .2O2-induced porcine granulosa cells apoptosis in vitro. Evidence in vitro suggested that acetate and propionate can activate GPR43 at low concentration (1 mmol/L) to inhibit the apoptosis of cultured cells in vitro; while at high concentration (10 mmol/L), they promote the apoptosis of colorectal cancer cells [To explore the connection between the gut microbiota and the distal ovarian follicular development, we profiled the plasma metabolome features using untargeted metabolomic and demonstrated a markedly distinguishing plasma metabolomics profiling between MS and L × Y sows. These different metabolites in plasma enriched in pathways of fatty acid metabolism, steroid hormone biosynthesis, alpha-linolenic acid metabolism, butanoate metabolism, primary bile acid biosynthesis, fatty acid elongation, estrogen signaling pathway, biosynthesis of amino acids, ABC transporters, and 2-Oxocarboxylic acid metabolism, etc. Correspondingly, MS sows have increased concentrations of plasma SCFAs including propionate, butyrate, isobutyrate, valerate, and isovalerate than L × Y sows. In addition, correlation analysis showed that the concentrations of SCFAs in both feces and plasma were significant negatively associated with the apoptosis of ovarian granulosa cells, indicating that the increased SCFAs may contribute to the porcine granulosa cells apoptosis amelioration observed in MS sows. In proximal tissues such as the intestine, adipose, and pancreas, SCFAs can regulate host immunity, inflammation, and metabolism by activating G protein-coupled receptors (GPCRs) . Howeverer cells , 51. In er cells . It is ger cells , 52. In er cells , 52. Coner cells , the roler cells , 53–56. er cells . In addier cells , 56. Alter cells , 57, 58.er cells  found ther cells . On the This study provides insight into the regulating effects of gut microbiota-ovary axis on follicular development in sows by a comprehensively comparative study between hyper-ovulation rate MS pigs and normal-ovulation rate L × Y pigs. The high levels of estradiol, progesterone, FSH, LH, and IGF-1, together with the less apoptotic granulosa cells in ovarian follicles may account for the hyper-ovulation rate of MS pigs. MS pigs have higher SCFAs concentrations in porcine ovarian follicular fluid, which may be because of their enhanced carbohydrate metabolism function of gut microbiota than L × Y pigs. These physiological concentrations of SCFAs in porcine ovarian follicular fluid of MS pigs could ameliorate porcine granulosa cells apoptosis in vitro. Therefore, gut microbiota participate in regulating ovarian follicular development via SCFAs affecting granulosa cells apoptosis in sows.Additional file1:Table S1. Ingredients and nutrients composition of the diet used in this trial.


CC and CXC-chemokines are the primary drivers of chemotaxis in inflammation, but chemokine network redundancy thwarts pharmacological intervention. Tick evasins promiscuously bind CC and CXC-chemokines, overcoming redundancy. Here we show that short peptides that promiscuously bind both chemokine classes can be identified from evasins by phage-display screening performed with multiple chemokines in parallel. We identify two conserved motifs within these peptides and show using saturation-mutagenesis phage-display and chemotaxis studies of an exemplar peptide that an anionic patch in the first motif and hydrophobic, aromatic and cysteine residues in the second are functionally necessary. AlphaFold2-Multimer modelling suggests that the peptide occludes distinct receptor-binding regions in CC and in CXC-chemokines, with the first and second motifs contributing ionic and hydrophobic interactions respectively. Our results indicate that peptides with broad-spectrum anti-chemokine activity and therapeutic potential may be identified from evasins, and the pharmacophore characterised by phage display, saturation mutagenesis and computational modelling. Ticks inject evasins at the bite site to bind multiple redundant chemokines and inhibit inflammation allowing blood feeding. Here, the authors identify evasin derived short peptides with broad spectrum anti-chemokine activity that could be used to develop new treatments for inflammatory disease. They play a major role in immune-inflammatory diseases ranging from atherosclerosis, rheumatoid arthritis, inflammatory bowel disease and cytokine-storm5. The 46 human chemokines are grouped into CC, CXC, CX3C and XC classes based on the spacing of their N-terminal cysteine residues1. CC-chemokines constitute the largest class, with 26 members in humans, while CXC chemokines have 17 members1. The binding of chemokines to a family of 18 G-protein coupled receptors (GPCRs) activates signalling, leading to chemotaxis or directed migration of leucocytes to the site of chemokine expression1. Chemokines are also functionally grouped into inflammatory or homoeostatic types with inflammatory chemokines causing leucocyte recruitment to the sites of inflammation, and constitutively expressed homoeostatic chemokines mediating immune cell homoeostasis1. Several homoeostatic chemokines also have inflammatory roles, and thus have dual functions6.Chemokines are structurally related secreted proteins that drive the migration of neutrophils, monocytes, T-cells and other leucocytes during the inflammatory response to injury or infection and in immune system homoeostasis7. A consensus view is that chemokine receptors engage with chemokines through four chemokine recognition sites (CRS) – 0.5, 1, 1.5 and 27. CRS0.5, i.e., the receptor distal N-terminus, interacts with the β1-strand. CRS1, located in the receptor N-terminus, interacts with the N and 40 s loops of the chemokine. CRS1.5, in the receptor N-terminus between CRS1 and CRS2, targets the conserved disulfide of the chemokine7. CRS2, i.e., the transmembrane pocket of the receptor, interacts with the N-terminus of the chemokine7. Chemokines often homodimerize, with CC-chemokines dimerising by interactions between CC motifs and preceding N-terminal residues, while CXC-chemokines dimerise by interactions between the β1-strands7. Chemokines also heterodimerize, with CC-type heterodimers activating and CXC-type heterodimers inhibiting chemokine activity8. Dimerisation impacts receptor binding: CC-class chemokines cannot bind their receptors as dimers, whereas CXC-class chemokines can7.Chemokines have a conserved disulfide-bonded tertiary structure with an unstructured N-terminal domain, followed by a N loop, a three-stranded β-sheet , and an α-helix9. Functional redundancy is a driver of biological network robustness10, and inflamed tissues are characterised by the expression of multiple chemokines with functionally redundant activities11. For instance, in rheumatoid arthritis, 15 CC and 11 CXC chemokines are expressed in joint tissues3. The human atherosclerotic plaque expresses 16 CC and 7 CXC chemokines11. Functional redundancy in chemokine-driven inflammatory leucocyte recruitment is likely created by promiscuous  interactions between chemokines and their receptors12, and the expression of multiple chemokine receptors by each leucocyte class13. The robustness to environmental variation has frustrated the development of therapeutics that target the chemokine network in inflammatory disease14.The chemokine network is characterised by redundancy and robustness to genetic or environmental variation15), chemokine-binding proteins were identified in the saliva of Ixodid ticks16. Molecular cloning identified three chemokine-binding proteins, referred to as evasins, from the salivary glands of the dog tick Rhipicephalus pulchellus18. Evasins EVA1 and EVA4 specifically bind CC chemokines, whereas EVA3 specifically binds CXC chemokines18. Fifty evasin proteins from diverse tick species have been expressed and characterised to date24. They may be classified into two functional groups, A and B, with exclusive binding to either CC- or CXC- chemokines, respectively25. Sequence-based phylogenetic analysis of tick transcriptomes indicates that CC-chemokine binding class A evasin-like proteins segregate into three subclasses, A1, A2 and A326. Structural characterisation shows that class A1 evasins have a four-disulfide-bonded core structure, with CC-chemokine binding specificity arising within the CC motif itself29, whereas A3 evasins have a five-disulfide-bonded core structure26. Class B evasins have a three-disulfide-bonded “knottin” structure23.Following initial observations on the modulation of host immunity by ticks . Despite success in models of inflammatory disease, evasins have not been clinically developed as therapeutics, at least in part due to the perceived obstacles of foreign proteins as biological therapeutics such as immunogenicity, coupled with relatively high manufacturing costs, and binding specificity requiring that both class A and B evasins be used in combination. Alternative approaches to target chemokines have exploited evolution of broadly cross reactive antibodies using yeast surface display31, and the isolation of promiscuous chemokine-binding peptides using phage-display followed by conversion into peptibody (IgG1-Fc) fusions32.An important feature of both class A and class B evasins is that they typically bind and inhibit 33. Peptides derived from the chemokine CCL5 have been shown to bind and inhibit chemokine function in vitro and in vivo by interfering with chemokine dimerisation8. Inspired by these exemplars, by using hydrogen-deuterium-exchange mass spectrometry (HDX-MS), we previously identified the chemokine-binding site of the tick class A evasin P672 (EV672_RHIPU) and developed a hexadecapeptide series that binds and inhibits the CC-class chemokines CCL8, CCL7, CCL3 and CCL2. We showed that one of these peptides inhibits inflammation in vivo34. In parallel, the chemokine-binding site of the tick class A evasin EVA4 was identified using NMR, and an EVA4-derived octadecapeptide Ev4Glu14-Asn31 that inhibits CCL5 function thereby developed28. The finding that a short peptide sequence derived from an evasin could bind more than one chemokine raised the possibility that other promiscuous chemokine-binding peptides may be identified in the sequences of evasin proteins. The time-consuming and labour-intensive nature of HDX-MS or NMR approaches however render challenging their application to study the 386 pairwise evasin-chemokine interactions that have been documented to date35.Peptides and peptidomimetics that mimic the activity of parental proteins have been successfully developed from several naturally occurring proteins into viable clinical therapeutics. Exemplars include the peptidomimetics captopril, eptifibatide and tirofiban, which are based on peptides derived from the snake venom toxins bradykinin-potentiating-peptide, barbourin and echistatin respectively39. A phage-displayed peptide library derived from the first protein is selected using the second protein and bound phage are analysed using next-generation sequencing. Such approaches have focussed on identifying SLiMs from intrinsically disordered unstructured regions of proteins and have recently been applied to map domain-SLiM binding sites in the human proteome39. We hypothesised that phage-display selection coupled to deep sequencing, performed in parallel with multiple chemokines, could be exploited to identify promiscuous chemokine-binding peptides from evasins. Here we develop a pipeline combining phage-display, saturation mutagenesis and computational modelling to discover promiscuous chemokine-binding peptides from class A evasins and characterise the pharmacophore.Phage-display coupled to deep sequencing is a powerful approach that can be used to rapidly identify short linear interacting motifs (SLiMs) that mediate protein-protein interactions34  specifically and reproducibly bind to the immobilised HD2 peptide fusion . We performed dose-response experiments for all chemokines in parallel and show that dose-dependent responses occur in each case  for CCL8 to 1.4E-5 molar (14 μM) for CXCL6  or cationic  residues and complements alanine-scanning mutagenesis47. Analysis of these HD2 mutations present in the dataset generated above, shows that glutamic or aspartic acid (anionic) substitution at the N-terminus is not deleterious for binding, and in some cases, e.g., at T6, improve binding, whereas they are significantly deleterious at the C-terminus  would allow us to identify HD2 residues that likely mediated hydrophobic interactions with chemokines. Analysis of these mutations, from the phage-display dataset generated above, showed that certain residues at the C-terminus—L11, T12, F15 and T16—can be substituted with a hydrophobic residue without significant deleterious effect To determine if alanine substitutions impacted the ability of HD2 to inhibit chemokine function we performed chemotaxis assays with synthetic peptides. We examined the effect of HD2 alanine mutants on migrated cell counts in chemotaxis assays using chemokines CCL5, CCL7, CCL8, CXCL6 and CXCL10, and compared it to parental HD2 as control  in complex with CCL528 34.A surprising and important result of our study is that several peptides—unlike the parental class A evasin proteins from which they are derived58. Sequence conservation across peptides derived from EVA4 and EV672 that bound both CC and CXC chemokines indicated the presence of conserved residues in two motifs, E(E/D)(E/D)DY at the N-terminus; and (L/V)TCYF at the C-terminus. We applied saturation mutagenesis phage-display to dissect the functional importance of these residues. By examining the binding characteristics of alanine, hydrophilic and hydrophobic mutants for 24 different CC and CXC-chemokines, we show that the two motifs are biochemically distinctive, with the former characterised by an anionic patch and the latter by hydrophobic, aromatic and cysteine residues. These types of residues are some of the major drivers of protein complex formation48. We confirmed, using alanine scanning mutagenesis, the relative importance of these residues in functionally inhibiting multiple CC and CXC-chemokines and showed that functional inhibition strikingly correlates with binding in phage-display. The two motifs are separated by a conserved Pro residue which, while not contributing significantly to inter-chain bond formation, appears to be important for binding and inhibition by HD2. This is consistent with the role of the Pro residue in the analogous peptide BK1.1 (which is HD845 with a Cys-Ala mutation) observed previously34, and suggests that it plays a role in peptide conformation, a known function of Pro residues59.Following the discovery of the peptides by phage-display, we demonstrated that not only does the exemplar peptide HD2 bind multiple CC and CXC-chemokines using an independent approach—biolayer interferometry—but that it also inhibits multiple CC and CXC-chemokines in chemotaxis assays. These results suggest that the broad-spectrum chemokine-inhibiting activities of HD2 could be applied for therapeutic development. A key requirement for such progression, for instance in computer-aided rational drug design, is an understanding of the pharmacophore, i.e., the electronic and steric features required for binding and functional inhibition of the target50, which is an implementation of the AlphaFold261 machine-learning algorithm “trained for multimeric inputs with known stoichiometry”, and has been used for peptide:protein docking62. In these studies, we used a 1:1 stoichiometry based on our previous observations that the predominant binding stoichiometry of BK1.1 to CCL8 is 1:134. We found using AlphaFold2-Multimer that the exemplar peptide, HD2, is predicted to bind to distinct sites in CC and CXC-chemokines: i.e., in CC to the N-terminus, and in CXC to the first β-strand. These results were confirmed in the large part using AutoDock CrankPep63 which folds flexible peptides and docks them into rigid targets63. The reason for only partial and not full concordance between the two methods may lie in the differences in the folding algorithms, and how they rank binding modes. Our analysis shows that HD2 binding sites in both CC and in CXC-chemokines overlaps with the receptor-binding regions of the chemokine—i.e., the sites predicted by AlphaFold2-Multimer to bind the chemokine receptor—suggesting that HD2 occludes distinct receptor-binding regions in CC and in CXC-chemokines, interfering with their binding to cognate receptors. Confidence in our docking approach is increased by the observation that the NMR-based model28 of CCL5 with Ev4Glu14-Asn31 (which differs from HD2 by three residues) is highly consistent with the models of HD2 docked to CCL5 produced by AlphaFold2-Multimer and AutoDock CrankPep. Using Arpeggio64, an algorithm that calculates interactions at protein-protein interfaces, we show that the N-terminal motif of HD2 contributes ionic and the C-terminal motif hydrophobic interactions, consistent with the results of the anionic, cationic, and hydrophobic substitution experiments. A limitation of these studies is that we have not confirmed the in silico predicted interactions and structure-activity relationships using approaches such as NMR or X-ray crystallography, which need to be performed in the future.To further elucidate the pharmacophore, we complemented these biochemical studies with two different in silico approaches that do not require prior knowledge of the binding pose of the peptide and use substantially different computational approaches. We initially applied AlphaFold2-Multimer65. Such synthetic agents may be generated using unnatural or D-amino acids so that key interactions with the target are maintained. The binding affinity and inhibitory potency of the peptides described are not yet in the range that would be desirable for use as therapeutic agents. These parameters could be enhanced by directed in vitro molecular evolution using deep mutational scanning combined with phage-display66. Further enhancement of inhibitory potency is also possible by conjugation to immunoglobulin Fc-chains to increase target avidity67. We suggest that the peptides and pharmacophore identified in this study could form templates for broad-spectrum anti-chemokine peptibodies or peptidomimetics that could be developed as therapeutics to target inflammatory disease. The phage-display, saturation mutagenesis and computational docking pipeline developed here could provide a new route to the discovery of such therapeutics that disrupt redundant and hence resilient protein-protein interaction networks in immuno-inflammation and cancer68.In summary, we have identified, using phage display and deep sequencing, a series of peptides from class A evasins that display broad-chemokine binding and inhibition activity spanning both CC and CXC-class chemokines. The pharmacophore mediating this activity was characterised using a combination of sequence conservation across peptides recovered, analysis of alanine, hydrophilic and hydrophobic mutants, and integration with computational modelling. Our analyses suggest that these peptides occlude different parts of the chemokine receptor-binding sites and contain two motifs, one with an anionic patch primarily contributing ionic interactions, and the second containing an essential Cys residue and contributing hydrophobic interactions. The pharmacophoric features thus identified could be exploited to develop shorter linear peptides, cyclic peptides and peptidomimetics—i.e. synthetic agents that mimic the 3D-spatial and physicochemical properties of parental peptides but overcome their pharmacokinetic limitationsPeripheral blood cells were obtained from anonymized donor leucocyte cones purchased from NHS Blood Transfusion Services, with ethics approval obtained from the University of Oxford Medical Sciences Interdivisional Research Ethics Committee, CUREC1 approval reference R75963/RE001.Sources of chemokines for phage-display experiments, BLI, and cell migration are provided in Supplementary Tables 22. The CXCR1-expression plasmid (D1398) expresses a human CXCR1-IRES2-blasticidin resistance cassette from a CMV-T7 promoter and was constructed using GoldenGate Assembly from idempotent parts20. The EVA4 expression plasmid P1922 (8xHis-EVA4_RHISA) was constructed in plasmid pHLSec69 using an In-Fusion cloning kit (Takara) following the instructions of the manufacturer, and contains EVA4_RHISA mature peptide  with a N-terminal His-tag. Plasmid sequences were confirmed by Sanger sequencing (Azenta/Genewiz UK).HIS:SUMO peptides were constructed using NEB Builder HiFi Assembly  with a plasmid backbone derived from HIS6:SUMO:CCL8TM kit  following the manufacturer’s instructions. The J:CXCR1 cell line was generated by transfecting Jurkat E6.1 cells by electroporation with PvuI-linearised plasmid D1398 and selecting in RPMI-1640 , 10% FBS , 5 mM L-Glutamine , and 5 μg/mL blasticidin . T-cells were isolated, activated and expanded as follows. Peripheral blood mononuclear cells were isolated from human leucocyte cones by density gradient centrifugation using LymphoprepTM density gradient medium  and a SepMateTM isolation tube . CD8+ T-cells were isolated using two rounds of the human CD8+ T-cell isolation kit . Isolated CD8+ T-cells were activated in ImmunoCultTM-XF T-cell expansion medium  with an anti-CD3/anti-CD28 T-cell activator at 25 μl/ml  and supplemented with 10 ng/ml recombinant human IL-2  with 1% penicillin/streptomycin. During activation, T-cells were passaged every 2–3 days in TexMACS medium , supplemented with 10 ng/ml human IL-2  and incubated at 37 °C in 5% CO2. At day 10-13 after initial activation, CD8+ T-cells were frozen at 20×106 cell/ml in TexMACS medium supplemented with 10% DMSO  in liquid nitrogen. 24 h prior to use, activated CD8+ T-cells were recovered in TexMACs medium at 0.3 × 106 cell/ml and incubated at 37 °C in 5% CO2.Jurkat E6.1 cells (ATCC TIB-152) were a gift from Pauline van Diemen (Oxford). THP1 cells (ECACC 88081201) were obtained from ECACC. Cell lines were confirmed mycoplasma free by monthly testing using a MycoAlertE.coli expression using GeneDesigner, using default settings . Codon optimisation was also repeated after mutating each Cys residue to Ala and Ser. We designed 81-mer oligonucleotides such that they encoded hexadecapeptides overlapping by a single residue, and had the sequence 5′-GCAGCCTCTTCATCTGGC, and GGTGGAGGATCCGGA-3′ at respective ends to enable amplification and cloning. A total of 4741 distinct peptides (including peptides where Cys was mutated to Ala or Ser) were designed as oligonucleotides and synthesised as a pool .Wild-type class A evasin nucleotide sequences  were codon-optimised for NsiI restriction site and was amplified using primers (Sigma):The plasmid prSTOP4  was modified to have an pRSTOP4Nsi_fwd: 5′-GGAGGCGCCGAGGGTGAC and pRSTOP4Nsi_rev: 5′-ATAGGCATTTGTAGCAATAGAAAAAACGAACATAGATGCAAG.11 CFU/mL M13KO7 helper phage  added and shaken at 37 °C, 220 RPM for 1 h. 1 mL recovery culture was added to 2YT medium containing 50 ug/mL carbenicillin  and 25ug/mL kanamycin , and grown overnight at 37 °C, 220 RPM. Phage was generated as described70. Briefly, phage was precipitated from the culture supernatant by adding 22.5 mL of supernatant to 4.5 mL 20% PEG 8000 /2.5 M NaCl , incubating on ice for 30 min, centrifuging at 12,857g, 4 °C for 10 min, resuspending the phage pellet in 1 mL of PBT , BSA  0.20%, Tween 20  0.05%), followed by centrifugation at 15,871g, 4 °C, for 10 min. Glycerol  ) was added to supernatant, which was aliquoted and stored at −80 °C. For mutant libraries, 81-mer mutant oligonucleotides replacing NNK at each of the 16 peptide encoding residues were designed with the sequence arms described above. Oligonucleotides were individually amplified and cloned into plasmid prSTOP4Nsi.Oligonucleotide pools (Genscript) were amplified using primers (Sigma): oligo_fwd: 5′-CTATTGCTACAAATGCCTATGCAGCCTCTTCATCTGGC and oligo_rev2: 5′-TCGTCACCCTCGGCGCCTCCTCCGGATCCTCCACC. Oligonucleotide PCR products were cloned into plasmid prSTOP4Nsi using NEB Builder HiFi Assembly  following the instructions of the manufacturer. The vector pool was used to transform electrocompetent ElectroMAX™ DH5α-E™ cells . Plasmid DNA was harvested by MaxiPrep ) and was transformed into SS320 phage display electrocompetent cells , following the manufacturer’s protocol, resuspended in 950 μL recovery media for each electroporation, transferred to 50 mL Falcon tubes, 100 μL 1071 with certain modifications. Experiments were performed in 96-well plates . Briefly, biotinylated chemokines ) to remove unbound phage and transferred to a fresh plate. Beads were incubated with 100 μL of phage-resistant Omnimax E.coli  at optical density (OD600) 0.6-0.8 and shaken at 37 °C for 30 min, following which 10 µL M13K07 helper phage  was added and shaken at 37 °C for 45 min. Cells were transferred to 1 mL of 2YT medium pH 7  supplemented with 150 µg/mL carbenicillin  and 75 µg/mL kanamycin  in a 96-deep well block with V-bottom  and grown overnight shaking at 37 °C, 200 RPM. Plates were either centrifuged at 2000g (4 °C for 30 min) or transferred to screw cap tubes and pelleted by centrifugation at 4000g and 4 °C for 15 min. 540 µL of supernatant was transferred to a new 96-deep well plate, 60 µL 10×PBT (10×PBS + 2% BSA + 0.5% Tween 20) added and stored at 4 °C until further use in subsequent rounds. Phage display was carried out for three rounds.Phage display screening was performed using a protocol as describedInserts from the input library and from the final phage population following selection were amplified by PCR using primers: 5′- ACACTCTTTCCCTACACGACGCTCTTCCGATCTCTAGCGCTATGCCTATGCAGCCTCTTCA and 5′-GACTGGAGTTCAGACGTGTGCTCTTCCGATCTCGTCTGCGATGACAACAACCATCGCCCA, (Life Technologies). The PCR products were cleaned up using Monarch® PCR & DNA Cleanup Kit (5 μg) , 260/280 ratio determined by Nanodrop, quantified using a Qubit dsDNA Quantitation, High Sensitivity Kit  and subsequently sequenced at Azenta/GeneWiz using the AmpliconEZ protocol.Paired end read Fastq files were joined by the read id. Sequences containing both forward and reverse demultiplexing regions (5’-CTAGCGCT and 5′-CGCAGACG) and both constant regions . Insert sequences were translated to peptide. Only inserts present in the designed library were counted and frequency determined. Library cloning efficiency was calculated as the ratio of distinct cloned peptide inserts to the number of inserts in the designed library and was 98%. Hexadecapeptide enrichment (E) following selection was calculated as ratio of output peptide frequency to input peptide frequency and expressed as log2E. Where proportion of count in input library was not available it was replaced with the lowest input proportion in the experiment rather than replacing it with 0. This is needed to avoid a value of E that is infinity. For mutagenesis experiments, where proportion of count in output was not available it was replaced with the lowest output proportion in the experiment rather than zero, which would result in a -Infinity log2E.https://www.uniprot.org) using RCurl. Briefly, collated enrichment data were filtered to include only those peptide-chemokine combinations where there was enrichment , and wild-type and mutant peptides were mapped to the originating wild-type protein. Residue log2E was calculated as the sum of log2Es of peptides overlapping a residue. The rolling median of residue log2E was calculated using the “rollmedian” function in R-package zoo, with k = 7 and fill=NA. Confidence interval of the median was calculated using the “cimed” function in R-package asbio.Enriched peptides were mapped to parental proteins using custom R-scripts. Parental protein sequences were obtained from UniProt (https://www.rcsb.org) using bio3d72 and chemokine-binding site residues were identified using the bio3d “binding.site” function with the default cut-off of 5 Å. AlphaFold models were downloaded from https://alphafold.ebi.ac.uk/download and structural features extracted using bio3d.PDB files for evasin complexes with chemokines 7S4N and 7SO0 (for EV974) and 3FPU (for EVA1) were retrieved from RCSB PDB  was added to the supernatant and incubated for 15 min in ice. Supernatant was filtered and passed over IMAC Sepharose 6 Fast Flow column resin  [pre-treated with 0.2 M NiCl2  and equilibrated with binding buffer ]. The resin was incubated with the lysate supernatant for 1 h at 4 °C on a platform rocker for continuous mixing. 30 mL wash buffer , pH 7.2) was applied to the resin. The peptide was then eluted in 5 mL elution buffer , and buffer exchange in PBS was performed using Amicon Ultra Centrifugal Units 3 K . EVA4 was expressed in HEK293F cells  by transient transfection of P1922 plasmid using polyethylenimine  in HEK293F cells followed by culturing in Freestyle 293 expression medium  at 37 °C, 8% CO2, at 130 rpm for 5 days. Protein was purified from filtered supernatants using nickel-charged IMAC Sepharose 6 Fast Flow resin as described above. Elutions were concentrated using an Amicon Ultra-15 Centrifugal Filter Unit and purified by size exclusion chromatography (SEC) on an AKTA Start system using HiLoad 16/600 Superdex 75 , in SEC buffer (PBS + 150 mM NaCl). Fractions showing absorption at 280 nm were analysed by electrophoresis on a Bolt Bis-Tris Plus Mini Protein Gel, 12%  in Bolt MES SDS Buffer , stained with Quick Blue Protein Stain  and were pooled.HIS:SUMO:peptide plasmids were transformed into BL21(DE3) cells  and grown in 5 mL LB  + 50 ug/mL Kanamycin  media overnight at 37 °C, with shaking at 200 RPM. 1% of this primary culture was inoculated into a secondary culture and grown for approximately 2 h at 37 °C, with shaking at 200 RPM. At OD600 of 0.4, the culture was induced with 1 mM IPTG  and grown for 4 h at 37 °C, with shaking at 200 RPM. The induced cells were harvested at 3800 g in a Thermo Scientific Megafuge 16R using a swinging bucket rotor and the media was discarded. The pellet from a 200 mL culture was resuspended in 30 mL of binding buffer  containing 1 mM PMSF . The suspension was sonicated using a Bandelin Sonopuls HD2070 for 45 min on ice using 0.7 s on- 0.3 s off cycle at 40% power. The lysate was centrifuged at 8500D and its standard error from at least three fits where full R2  was >0.95, full X2  was <3, and KD standard error was <KD.The binding of His-SUMO tagged peptide fusions to various chemokines  in 50 µL of cell migration media , 0.5% FBS , 4 mM L-Glutamine , 0.05% DMSO ). The bottom chamber contained 150 µL of migration media with chemokine and peptide added. Cells were migrated at 37 °C in 5% COJ:CXCR1 migration assays were performed exactly as for THP1 assays except that a 3-µm Transwell insert  was used.2 for 2 h.For activated-T cell migration assays, 100000 cells/well were added to the top chamber of a 3-µm Transwell insert  in 50 µL of migration media , 0.1% protease free bovine serum albumin , 0.05% DMSO ). The bottom chamber contained 150 µL of migration media with chemokine and peptide added. Cells were migrated at 37 °C in 5% CO73. IC50 experiments were performed at the EC80 dose of chemokine. EC80 was calculated by fitting a chemokine dose-response curve with a 3-parameter log-logistic model (fixing the top to 100%) using the function “drm” in R-package drc74. IC50 was calculated by fitting an inhibitor response curve with a 4-parameter log-logistic model using the function “drm” in R-package drc74. All IC50 values reported had p-value < 0.05.Following the migration assay the migration plate was shaken at 850 RPM for 10 min, and media from bottom plate transferred to a round-bottomed 96 well plate . Cell counts were determined using an Atune NxT Flow Cytometer Plate Reader with Cytkick autosampler (ThermoFisher), based on cell size parameters FSC-H/SSC-H, and and a previously defined gate setting for each cell type , and, also, as certain chemokines e.g., CXCL6, lack PDB structures, to maintain consistency, we first generated chemokine structures using AlphaFold for input to ADCP. The highest-ranking structure for each chemokine was reduced with “reduce”, then the functions “prepare_receptor”, “agfr”, and “adcp” were called from ADFRsuite 1.0. Default parameters were used for “prepare_receptor” and “agfr”, while “adcp” was run with N = 300, n = 48000000 and nc = 0.8 for all runs. For ADCP the ten highest ranked poses  were carried forward for heat map generation. PDB files from previously reported HADDOCK76 analysis of NMR chemical shift perturbation data of peptide Ev4Glu14-Asn31 in complex with CCL528 were kindly provided by Prof. Ingrid Dijkgraaf, Maastricht. Binding site heatmaps were generated by identifying residues within 5 Å distance of the two chains using bio3d72 for each docking pose. Weighted proximity scores were calculated as follows: A per-residue-score equal to the confidence score (AlphaFold) or calculated free energy (ADCP) was ascribed for each pose within a model, this was aggregated over the different poses in the model, and then normalised to a maximum score of 100 to allow comparison between models. For NMR-HADDOCK models the 4 generated poses were weighted equally for the calculation of the weighted proximity score. Docked poses were aligned using PyMol “extra_fit” to align multiple poses to the top-ranked pose.Models were generated using AlphaFold2-Multimer at the COSMIC64 contacts between the two chains of the five AlphaFold multimer models for each complex were identified from the “.bs_contacts” file produced. Column identities for the file were taken from https://bitbucket.org/harryjubb/arpeggio/src/master/README.md.Arpeggio79.We performed model relaxation using Rosetta 3.13 (relax.static.linuxgccrelease) followed by calculation of the cross-interface binding energy (dG_cross) with Rosetta InterfaceAnalyser  using the default ref2015 weight-set34. Statistical analyses were performed using the R-base package stats and DescTools. Statistical tests used were one-way ANOVA followed by a two-sided Dunnett’s post-hoc multiple comparison procedure for comparing several treatments with a control, with 95% family wise confidence level73. Data are displayed as Tukey box-whisker plots using the ggplot function geom_boxplot, and displays median, lower and upper hinges (25th and 75th percentiles), and whiskers from hinge to 1.5* interquartile range.For cell-based experiments sample size was not formally calculated. Cell numbers, numbers of technical and biological replicates are based on optimisation of such experiments2 Science Gateway75, and ADFRSuite 1.051 (https://ccsb.scripps.edu/adcp/downloads/) and reduce ((https://github.com/rlabduke/reduce) on the Oxford University BioMedical Research Computing Cluster (BMRCC). Data analysis was performed using R version 4.2.3, RStudio version 2023.03.2 + 454, running on arch64-apple-darwin20 (64-bit) with macOS Ventura 13.4.1. R packages used were: ape_5.7-1, asbio_1.9-2, bio3d_2.4-4, Biobase_2.58.0, BiocGenerics_0.44.0, BiocParallel_1.32.6, Biostrings_2.66.0, dendsort_0.3.4, DescTools_0.99.48, dplyr_1.1.2, drc_3.0-1, flextable_0.9.1, forcats_1.0.0, GenomeInfoDb_1.34.9, GenomicAlignments_1.34.1, GenomicRanges_1.50.2, ggmsa_1.4.0, ggnewscale_0.4.8, ggplot2_3.4.2, ggpubr_0.6.0, ggseqlogo_0.1, ggtree_3.6.2, ggupset_0.3.0, gridExtra_2.3, gtable_0.3.3, IRanges_2.32.0, janitor_2.2.0, jsonlite_1.8.4, lubridate_1.9.2, maps_3.4.1, MASS_7.3-58.2, MatrixGenerics_1.10.0, matrixStats_0.63.0, msa_1.30.1, officer_0.6.2, openxlsx_4.2.5.2, pals_1.7, pheatmap_1.0.12, phytools_1.5-1, purrr_1.0.1, R.methodsS3_1.8.2, R.oo_1.25.0, R.utils_2.12.2, RColorBrewer_1.1-3, readr_2.1.4, Rsamtools_2.14.0, S4Vectors_0.36.2, scales_1.2.1, seqinr_4.2-30, ShortRead_1.56.1, strex_1.6.0, stringr_1.5.0, SummarizedExperiment_1.28.0, tibble_3.2.1, tidyr_1.3.0, tidyverse_2.0.0, viridis_0.6.3, viridisLite_0.4.1, XVector_0.38.0, zoo_1.8-12. Arpeggio analysis used Python 2.7, biopython 1.79, and Arpeggio64 (https://bitbucket.org/harryjubb/arpeggio/src/master/). Open-Source PyMOL  was used for scripting and PyMOL 2.5.2 (https://pymol.org/2/) was used for visualization of structural models. Rosetta analysis used Rosetta 3.1377.Biolayer interferometry data was collected and analysed using ForteBio Data Analysis HT 11.1. Flow sorting data was collected and analysed using Attune Cytometric Software v5.1.1. Structural models were generated using AlphaFold2-Multimer at the COSMICFurther information on research design is available in the Supplementary InformationPeer Review FileReporting SummarySource Data


Enhancer dysregulation is one of the important features for cancer cells. Enhancers enriched with H3K4me3 have been implicated to play important roles in cancer. However, their detailed features and regulatory mechanisms have not been well characterized.Here, we profile the landscape of H3K4me3-enriched enhancers (m3Es) in 43 pairs of colorectal cancer (CRC) samples. M3Es are widely distributed in CRC and averagely possess around 10% of total active enhancers. We identify 1322 gain variant m3Es and 367 lost variant m3Es in CRC. The target genes of the gain m3Es are enriched in immune response pathways. We experimentally prove that repression of CBX8 and RPS6KA5 m3Es inhibits target gene expression in CRC. Furthermore, we find histone methyltransferase MLL1 is responsible for depositing H3K4me3 on the identified Vm3Es. We demonstrate that the transcription factor AP1/JUN interacts with MLL1 and regulates m3E activity. Application of a small chemical inhibitor for MLL1 activity, OICR-9429, represses target gene expression of the identified Vm3Es, enhances anti-tumor immunity and inhibits CRC growth in an animal model.Taken together, our study illustrates the genome-wide landscape and the regulatory mechanisms of m3Es in CRC, and reveals potential novel strategies for cancer treatment.The online version contains supplementary material available at 10.1186/s13059-023-03108-3. Epigenetic dysregulation is critical for chromatin stability, tumorigenesis and metastasis in cancer cells –3. Currelysine methyltransferase 2C/D (KMT2C/D), E1A binding protein p300 (EP300), CREB binding protein (CREBBP), lysine demethylase 6A  and lysine demethylase 5C (KDM5C), which solidifies the importance of enhancer regulation in cancer -gastrin (Sigma), Y-27632 , 100 ng/mL human noggin (MCE), 50 ng/mL human EGF (MCE), 500 ng/ml R-Spondin1 (MCE), SB202190 , CHIR99021 and Blebbistatin . After the first 7 days, isolation medium was changed with human expansion medium (HEM), containing HIM but not Noggin, R-Spondin1 and Y-27632. For passage of organoids, organoids were released from the Matrigel by cell-recovery solution (Corning), dissociated into single cells using TrypLE express (Gibco), and resuspended with Matrigel and divided into a 24-well plate (50 μl per well). After the Matrigel balls were polymerized, 500 μl of HEM was added, and media was changed on organoids every 2–3 days.5 HCT116 cells per site into the flank regions of mice. Tumor volumes were measured every 2 days using calipers. Tumor volumes were calculated as V = 0.5 × length × width2. After 14 days of injection, tumors were harvested and weighed. Data were shown as mean ± SEM and p values were calculated by the student’s t test.Five-week-old male BALB/C nude mice were purchased from GemPharmatech Co., Ltd. Colon cancer model was established by injecting subcutaneously 7.5 × 10p value was either labelled on the corresponding items or listed in the legends.For experiments other than NGS sequencing, at least three biological replicates for each experiment were performed. Data are presented as mean values ± SEM. Statistical analysis was performed using a two-sided Student t test. Additional file 1: Supplementary Figure S1-S12. Fig. S1. Quality control of sequencing data. Fig. S2. Functional analysis of gain and lost Vm3Es in CRC. Fig. S3. Gene browser view of representative gain Vm3Es in CRC. Fig. S4. Validation of identified Vm3Es. Fig. S5. Inhibition of m3Es represses target gene expression. Fig. S6. Functions of the identified Vm3Es on cell proliferation and cell cycle. Fig. S7. Screen of methyltransferases regulating m3E target genes. Fig. S8. OICR-9429 treatment repressed the identified m3Es. Fig. S9. C646 treatment repressed histone modifications on the identified Vm3Es. Fig. S10. JUN regulates the identified Vm3Es in CRC. Fig. S11. JUN binds to H3K4me3 enhancer loci in the AOM-DSS induced CRC model. Fig. S12. OICR-9429 treatment repressed CRC.Additional file 2: Table S1. Information of gain and lost vm3Es in CRC.Additional file 3: Table S2. List of primers and oligonucleotides used in this study.Additional file 4. Uncropped images for the blots in Figure 5-6, Fig S5 and Fig S7-10.Additional file 5. Review history.


Objective: This study aimed to investigate the efficacy and tolerability of Lacosamide (LCM) in a pediatric population with epilepsy using LCM serum concentration and its correlation to the age of the participants and the dosage of the drug.Methods: Demographic and clinical data were collected from the medical records of children with epilepsy treated with LCM at Shamir Medical Center between February 2019 to September 2021, in whom medication blood levels were measured. Trough serum LCM concentration was measured in the biochemical laboratory using High-Performance Liquid Chromatography (HPLC) and correlated with the administered weight-based medication dosing and clinical report.Results: Forty-two children aged 10.43 ± 5.13 years (range: 1–18) were included in the study. The average daily dose of LCM was 306.62 ± 133.20 mg (range: 100–600). The average number of seizures per day was 3.53 ± 7.25 compared to 0.87 ± 1.40 before and after LCM treatment, respectively. The mean LCM serum concentration was 6.74 ± 3.27 mg/L. No statistically significant association was found between LCM serum levels and the clinical response (p = 0.58), as well as the correlation between LCM dosage and the change in seizure rate (p = 0.30). Our study did not find a correlation between LCM serum concentration and LCM dosage and the gender of the participants: males (n = 17) females (n = 23) . A positive trend was found between age and LCM serum concentrations .Conclusion: Based on the data that has been obtained from our study, it appears that therapeutic drug monitoring for LCM may not be necessary. Nonetheless, further research in this area is needed in the light of the relatively small sample size of the study. Lacosamide (LCM) is a third-generation anti-seizure medication (ASM) approved in 2008 by the FDA as an add-on therapy for treating focal-onset seizures in people with epilepsy who are 17 years old and older. In 2020, the FDA extended the indication to include LCM as adjunctive therapy in patients 4 years of age and older to treat primary generalized tonic-clonic seizures . In IsraIn vitro electrophysiological studies have shown that LCM selectively enhances the slow inactivation of voltage-gated sodium channels, resulting in the stabilization of hyperexcitable neuronal membranes  , Schult. HoweverThe Ethics Committee approved the study at Shamir Medical Center. The LCM serum concentrations were measured in the hospital’s biochemistry lab using a commercial kit (Chromysystems) and high-performance liquid chromatography with photodiode array ultraviolet detection (Variant Prostar). LCM reference levels were 1–10 mg/L . PatientAll statistical analysis was conducted using R Statistical Software, version 3.5.2 . The data was described using means, standard deviations, minimum, maximum, rates, and percentages for quantitative and categorical variables, respectively. The χ2 and Fisher exact tests were utilized to compare between groups for categorical outcomes and the independent samples t-test for quantitative outcomes. The Pearson and Spearman correlations were used to correlate between outcomes. Finally, the paired t-test was used to evaluate the difference in seizure frequency before and after starting LCM treatment.p = 0.02). While 65% of the patients (n = 26) were seizure-free, reported an average period of 229 ± 203 days (range 33–943), 35% of the patients (n = 14) had reduction in convulsions rate, suffering from an average of 0.87 ± 1.4 (range: 1–3.5) seizures per day (p = 0.31), gender (p = 0.94) and the convulsion rate difference  (p = 0.58) (p = 0.09) (p = 0.13) . We calculated the ratio between serum concentration and weight adjusted daily dose (C/D ratio). No significant differences in C/D ratios were found between the “seizure free” group and the “less convulsions” group , between male and female  and between children with and without ADRs . The correlation between C/D ratio and convulsion rate difference was negative but not statistically significant . A positive and statistically significant correlation was found between C/D ratio and age .Forty-two patients were screened. Two patients were excluded as the LCM blood levels were not taken at trough. Of the included patients, 43% (n = 17) were boys and 57% n = 23) were girls. The average age of the patients was 10.4 ± 5.1 years (range: 1–18). Twenty eight patients (61%) had a focal onset epilepsy  and one with Drug-resistant temporal lobe epilepsy). Seven patients (15%) had a Generalized onset epilepsy . Eleven patients (24%) had a combined generalized and focal onset epilepsy. The average age at diagnosis was 6.41 ± 4.81 years (0–16). Thirty-nine patients were diagnosed with refractory epilepsy failing to achieve sustained seizure freedom on at least two tolerated, appropriately chosen and used ASMs were taking an average of 3.8 ± 2.1 (range 0–10) ASMs before starting LCM therapy. At the time of LCM treatment, the average number of concurrent ASMs was 1.1 ± 0.96 (range 0–4). One patient with a focal onset epilepsy was treated with LCM as a first-line monotherapy. Before the treatment, the average frequency of seizures was 3.5 ± 7.2 per day (range: 1–35). The total daily dose of LCM was 306.62 ± 133.20 mg (range: 100–600). The average blood level of LCM was 6.74 ± 3.27 mg/L (range: 0.7–16.9). Four (10%) had serum concentration above upper reference value of 10 mg/L. Seizure frequency decreased significantly following the initiation of LCM treatment (3 were gi per day . LCM serp = 0.3) . No stat = 0.58) . A posit = 0.09) . AdverseGreenaway’s prospective observational study that was conducted on 98 patients (average age: 43 ± 12 years) with a mean LCM daily dose of 3.3 ± 1.6 mg/kg, LCM dose was linearly related to total and free LCM serum concentrations   that investigated the correlation between dose and serum concentration . The mean LCM serum concentration was 4.7 ± 2.5 mg/L (range: 1–17.3 mg/L)  and found that the Emax model, which measures the maximum number of seizures, was the most appropriate for describing the relationship between AUC and seizure frequency change. No therapeutic serum concentration range has been established for LCM (p = 0.003). Data on the LCM reference range is scarce and is not well established. The recommended reference ranges have been reported as varying from 2.2 to 20 mg/L  . A weak .3 mg/L) . However.3 mg/L) . The dif.3 mg/L) . All the for LCM . Althoug for LCM . The the for LCM . The max 20 mg/L . The LCM 20 mg/L . In Zhao3.2 mg/L .Markoula S. et al. on an adult population  aged 19–66 years and taking a median LCM dose of 300 mg found that women had a higher mean LCM concentration (9.3 ± 5.9 mg/L) compared to men (6.7 ± 3.2 mg/L), with a statistically significant difference (p = 0.001)  had significantly higher concentration–dose ratios than children aged between 6 and 12 years (n = 29) and children aged<6 years (n = 3)   . The cur= 0.001) , (May et= 0.001) . Accordi (n = 3) . It is p (n = 3) , (Johann (n = 3) . Zaho et< 0.001) . Our stu< 0.001) , (Verrot< 0.001) , (Farkas< 0.001) , (Ortiz < 0.001)  and all itration . Howeveritration , (Hillenitration , (Mcginnitration .The study was limited to children who received LCM for at least 1 month at a therapeutic dose and showed initial improvement in seizure frequency. Children who experienced an increase or no decrease in seizure frequency during treatment with LCM were not included in the study.Winkler et al. study examined LCM use in pediatrics found that LCM clearance increased by about 35% when administered with a concomitant enzyme-inducer AEDs (May et al. observed a reduction of 46% in the AUC of LCM when children were given enzyme-inducer AEDs in combination with LCM compared to monotherapy (Our study did not examine the effect of co-administered ASMs on LCM serum levels and efficacy. Studies suggest that the efficacy and tolerability of LCM may decrease if added to a regimen containing sodium channel blockers , Yamamo. Winklercer AEDs . May et otherapy .Based on the current data, it appears that measuring serum concentrations of LCM in pediatric patients undergoing treatment might not be necessary. However, monitoring LCM levels can still play a role in the management of patients, especially those with refractory epilepsy to assess compliance, determine a therapeutic baseline in patients who have well-controlled seizures, or identify severe intoxication. Further research in this area is needed among pediatric patients to confirm these findings.


Elevated pulse pressure (PP) is a robust independent predictor of cardiovascular diseases. The relationship between PP and body mass index (BMI) was presented in a few studies. However, the findings were inconsistent. Therefore, the aim of the present study is to identify the association between elevated PP and BMI using a large sample of active-duty Royal Thai Army (RTA) personnel.2 was classified as obesity I, whereas BMI ≥ 30.0 kg/m2 was classified as obesity II. Elevated PP was defined as PP ≥ 50 mmHg. Multivariable linear regression and log-binomial regression models were utilized for determining the association between elevated PP and BMI.A cross-sectional study was conducted through the use of the dataset obtained from the annual health examination database of RTA personnel in Thailand in 2022. BMI 25.0–29.9 kg/m2, while the average PP was 50.1 ± 11.2 mmHg. Compared to individuals with normal weight, the 2, the adjusted prevalence ratio (PR) for elevated PP was 1.23 (95% CI: 1.19–1.28) and 1.41 (95% CI: 1.35–1.48) in those with obesity I and obesity II, respectively. Meanwhile, among individuals with high BP, the adjusted PR for elevated PP was 1.05 (95% CI: 1.01–1.08) and 1.09 (95% CI: 1.06–1.13) in those with obesity I and obesity II, respectively.A total of 62,113 active-duty RTA personnel were included in the study. The average BMI was 25.4 ± 3.8 kg/mPP was positively associated with BMI in active-duty RTA personnel. High BP was the modifier of the association between PP and BMI. A weaker association between elevated PP and BMI was observed among RTA personnel with high BP.The online version contains supplementary material available at 10.1186/s12872-023-03390-w. Cardiovascular diseases (CVD), including ischemic heart disease and stroke, are a leading cause of mortality in Thailand , 2. The At present, obesity, the metabolic risk factor for CVD, is also a health burden in the Thai population, in both civilian and military personnel , 16, 17.2. In comparison, it was negatively associated among those with BMI 2 [A recent nationwide study in Thailand provided information on the prevalence of elevated PP among patients with type 2 diabetes, which was approximately 50%. The study also indicated elevated PP was associated with diabetic retinopathy. . However30 kg/m2 . Another30 kg/m2 . However30 kg/m2 .In 2022, approximately 60,000 active-duty RTA personnel aged at least 35 years participated in health examinations provided by the RTA Medical Department (RTAMED). As mentioned, raised BMI and high BP were still major health issues among this population , 20, 24.A cross-sectional study was carried out through the use of the dataset obtained from the annual health examination database of RTA personnel in 2022 from the RTAMED in Bangkok, Thailand. The RTAMED provides health examinations for active-duty RTA personnel through the Army Institute of Pathology (AIP), the Armed Forces Research Institute of Medical Sciences (AFRIMS), and 37 RTA hospitals nationwide  . TypicalAt the health examination session, a self-report using a standardized case report form was conducted to obtain characteristics data and behavioral factors, including age, sex, exercise, alcohol use, and smoking status. Lifestyle data were based on the data from the self-report questionnaire. Regular exercise was defined as exercise for 30 min/day and at least three days/week . CurrentThe details of blood pressure (BP) measurement in the health examination of RTA personnel were published by Sakboonyarat et al. . BP was 2 , < 18.5 kg/m2 (underweight), 23.0–24.9 kg/m2 (overweight), 25.0–29.0 kg/m2 (obesity I), and ≥ 30.0 kg/m2 (obesity II) [Pulse pressure (PP) was calculated as follows: SBP – DBP . Regardisity II) . High FPsity II) . The geot-test or analysis of variance (ANOVA) as appropriate. At the same time, the Chi-square test was employed to compare the prevalence of high PP , median, and interquartile range (Q1–Q3). We explored the data distribution of PP, and the normal distribution was observed  to provide more information on the consistent association between BMI and PP among both sexes. Sex-specific differences in the association between BMI and PP were explored using linear regression and log-binomial regression analysis. Although the potential confounders were adjusted in the final model, the residual confounding effect may exist. Therefore, we then conducted a sensitivity analysis for unmeasured confounding using E-values estimated by the evalue package .The present study was reviewed and approved by the Institutional Review Board, Royal Thai Army Medical Department , following the international guidelines, entailing the Declaration of Helsinki, the Belmont Report, the Council for International Organizations of Medical Sciences Guidelines, and the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use-Good Clinical Practice (ICH-GCP). As a result of utilizing secondary data, a waiver of documentation of informed consent was obtained. An informed consent waiver was approved by the Institutional Review Board of the Royal Thai Army Medical Department.2. Mean SBP and DBP were 130.6 ± 16.6 mmHg and 80.5 ± 11.5 mmHg, respectively. Mean PP was 50.1 ± 11.2 mmHg, while the median and IQR of PP were 49.0 (43.0–56.0) mmHg. Nearly two-thirds (58.9%) of study participants were current drinkers, while approximately one-fourth (28.3%) were current smokers.Table p-value < 0.001). Moreover, the prevalence of elevated PP . Among RTA personnel with high BP, the prevalence of elevated PP was 69.7%. Nevertheless, it was 39.7% among those with normal BP .Table p-value < 0.001). Additionally, when BMI was further evaluated as categories, in comparison with the reference group (BMI 18.5–22.9 kg/m2), the adjusted 2 and BMI 2, respectively.Table 2 and BMI 2, respectively. A weaker association between PP and BMI categories was proved for participants with high BP. However, among individuals with high BP, in comparison with BMI 18.5–22.9 kg/m2, the adjusted 2 and BMI 2, respectively. Figure Effect modification by high BP on the association between PP and BMI was noticed. Among participants with normal BP, the adjusted entclass1pt{minima2 compared to those with BMI 18.5–22.9 kg/m2. Similarly, the adjusted PR for elevated PP of those with BMI 2 was 1.26 (95% CI: 1.22–1.30).The association between elevated PP and BMI was analyzed through the use of multivariable log-binomial regression Table . After a2 and BMI 2, respectively. A weaker association between elevated PP and BMI categories was recognized among participants with high BP. In comparison with BMI 18.5–22.9 kg/m2, the adjusted PR for elevated PP was 1.05 (95% CI: 1.01–1.08) and 1.09 (95% CI: 1.06–1.13) in those with BMI 25.0–29.9 kg/m2 and BMI 2, respectively. Figure Furthermore, effect modification by high BP on the association between elevated PP and BMI was discovered Fig. . Among pRegarding the sensitivity analysis, after adjusting for potential confounders, the dose–response relationship between PP and BMI category was observed in males and females  demonstrates blood pressure, and body mass index  variance due to hospitals  by total variance. Supplementary Table 2. Data distribution and dispersion of pulse pressure.  Supplementary Table 3. Univariable and multivariable linear regression for the association between pulse pressure and body mass index, stratified by sex.


Echinacea purpurea (L.) Moench is a medicinal plant commonly used for the treatment of upper respiratory tract infections, the common cold, sore throat, migraine, colic, stomach cramps, and toothaches and the promotion of wound healing. Based on the known pharmacological properties of essential oils (EOs), we hypothesized that E. purpurea EOs may contribute to these medicinal properties. In this work, EOs from the flowers of E. purpurea were steam-distilled and analyzed by gas chromatography–mass spectrometry (GC–MS), GC with flame-ionization detection (GC–FID), and chiral GC–MS. The EOs were also evaluated for in vitro antimicrobial and innate immunomodulatory activity. About 87 compounds were identified in five samples of the steam-distilled E. purpurea EO. The major components of the E. purpurea EO were germacrene D (42.0 ± 4.61%), α-phellandrene (10.09 ± 1.59%), β-caryophyllene (5.75 ± 1.72%), γ-curcumene (5.03 ± 1.96%), α-pinene (4.44 ± 1.78%), δ-cadinene (3.31 ± 0.61%), and β-pinene (2.43 ± 0.98%). Eleven chiral compounds were identified in the E. purpurea EO, including α-pinene, sabinene, β-pinene, α-phellandrene, limonene, β-phellandrene, α-copaene, β-elemene, β-caryophyllene, germacrene D, and δ-cadinene. Analysis of E. purpurea EO antimicrobial activity showed that they inhibited the growth of several bacterial species, although the EO did not seem to be effective for Staphylococcus aureus. The E. purpurea EO and its major components induced intracellular calcium mobilization in human neutrophils. Additionally, pretreatment of human neutrophils with the E. purpurea EO or (+)-δ-cadinene suppressed agonist-induced neutrophil calcium mobilization and chemotaxis. Moreover, pharmacophore mapping studies predicted two potential MAPK targets for (+)-δ-cadinene. Our results are consistent with previous reports on the innate immunomodulatory activities of β-caryophyllene, α-phellandrene, and germacrene D. Thus, this study identified δ-cadinene as a novel neutrophil agonist and suggests that δ-cadinene may contribute to the reported immunomodulatory activity of E. purpurea. Echinacea L. (Asteraceae) contains ten species generally known as coneflowers. Coneflowers have big, showy heads of composite flowers with spiny central disks that bloom throughout the summer in Europe and North America. Echinacea purpurea (L.) Moench (purple coneflower) is a well-known medicinal-ornamental perennial plant native to damp prairies, meadows, and open forests of the central to southeastern parts of the United States  i) in neutrophils compared to that observed previously with germacrene D  using the Lab Solutions GC–MS post-run analysis software version 4.45 .The E. purpurea EO was performed using a Shimadzu GC 2010 equipped with a flame ionization detector , as previously described i) were monitored with a FlexStation 3 . For these assays, neutrophils were loaded with 1.25 μg/mL Fluo-4AM and incubated in the dark at 37 °C for 30 min. The cells were then washed with HBSS−. The dye-loaded cells were resuspended in HBSS+ and pipetted into the wells of black microtiter plates at 2 × 105 cells/well. To measure the direct effects of samples on [Ca2+]i, the test samples were added to the wells , and the fluorescence was monitored . Changes in fluorescence were monitored every 5 s at room temperature for 240 s. To evaluate the inhibitory effects of the test samples, the samples were added to the wells and incubated for 10 min, with the subsequent addition of 5 nM fMLF. Responses were normalized to the response induced by control fMLF (5 nM) alone without pretreatment. These responses were assigned as 100%. To calculate median effective concentrations (EC50 or IC50), we used curve fitting (at least five or six points) and nonlinear regression analysis of the dose–response curves. Curve fitting was performed with Prism 9 .Changes in the intracellular CaE. purpurea EO and its components on neutrophil migration, we resuspended the neutrophils in chemotaxis media (HBSS+ containing 2% (v/v) heat-inactivated FBS) at 2 × 106 cells/mL. We analyzed chemotaxis using 96-well ChemoTx chambers . Neutrophils were first preincubated in Greiner flat-bottom 96-well plates  with different concentrations of test samples at room temperature for 30 min. To set up the chemotaxis chambers, a known number of neutrophils were aliquoted into eight wells of the lower chamber to be used for creating the standard curve (linear range of 103–4 × 104 neutrophils in 30 µL of chemotaxis media). Thirty microliters of the chemotaxis media containing the indicated test samples or control 1% DMSO and 1 nM fMLF as the chemoattractant was aliquoted into the remaining wells of the lower chamber, except for 3 lower wells that were reserved for background controls (DMSO treated cells in the upper wells and DMSO without fMLF in the lower wells). The lower chamber plate was then covered with the upper filter plate. The pretreated cells were then transferred from the 96-well Greiner plate into the upper wells of the chemotaxis chamber (4 × 104 cells/well in 20 µL), except for the 3 background control wells indicated above and the 8 upper wells corresponding to the lower wells containing neutrophils used for the standard curve. The cells were then allowed to migrate from the upper wells through the polycarbonate membrane filter for 60 min at 37 °C/5% CO2. Any remaining unmigrated neutrophils were wiped from the upper membrane in each well using filter paper, and 20 µL of 2.5 mM EDTA was added to each well to detach any cells that migrated through the filter membrane but were still attached to the lower membrane surface (10 min incubation at 4 °C). The number of migrated cells was then determined by measuring the ATP in lysates of transmigrated cells and comparing this to the standard curve obtained using known neutrophil numbers, as described above. Calculation of median effective concentrations (IC50) was performed by nonlinear regression analysis of the dose-response curves.To evaluate the effects of the 4 cells/well) with the indicated concentrations of the essential oil or compound for 90 min or 24 h at 37 °C/5% CO2. After incubation, we added the substrate. The samples were analyzed using a Fluoroscan Ascent FL microplate reader.We analyzed monocyte cytotoxicity using THP-1 monocytic cells using a CellTiter-Glo Luminescent Cell Viability Assay Kit . Briefly, the cells were incubated , Shigella sonnei , Shigella flexneri , Salmonella enterica subsp. enterica (Strain MDCH01 (Serovar Tennessee), NR-20742), Pseudomonas aeruginosa , Staphylococcus epidermidis , Staphylococcus aureus , Streptococcus pyogenes , Streptococcus pneumoniae , and Bacillus cereus  and through BEI Resources, NIAID, NIH as part of the Human Microbiome Project: Klebsiella pneumoniae subsp. Pneumoniae , Citrobacter freundii , and Enterococcus faecalis . The assay was performed with a 1% EO stock solution in DMSO (~2500 µg/mL). The EO stock solution was serially diluted in a 96-well plate with TSB broth that had been inoculated with bacterial species. Plates were sealed with sterile gas exchange film and incubated at 37 °C overnight. Optical density was measured at 600 nm using a Thermo Scientific Spectronic 200 spectrophotometer. Assays were performed in quadruplicate.The standard broth dilution method was used to determine the minimum inhibitory concentration (MIC). The following strains were selected for the testing and were obtained through BEI Resources, NIAID, NIH: https://pubchem.ncbi.nlm.nih.gov/441005; accessed on 7 September 2022). The pharmacophore mapping was performed with the “Human Protein Targets Only” database containing 2241 targets. The top 300 potential human protein targets were retrieved and sorted by the normalized fit score.The PharmMapper Server was utilized for exploring the potential protein targets for (+)-δ-cadinene . The 3D p value of less than 0.05 was considered statistically significant.Statistical analysis was performed using GraphPad Prism 9 for Windows . A E. purpurea mainly comprised germacrene D (42.0 ± 4.61%), α-phellandrene (10.09 ± 1.59%), β-caryophyllene (5.75 ± 1.72%), γ-curcumene (5.03 ± 1.96%), α-pinene (4.44 ± 1.78%), δ-cadinene (3.31 ± 0.61%), and β-pinene (2.43 ± 0.98%). Analysis of the E. purpurea EO microbicidal activity showed relatively high activity against a variety of bacterial pathogens. Further analysis showed that the E. purpurea EO, germacrene D, α-phellandrene, β-caryophyllene, and δ-cadinene all induced intracellular Ca2+ mobilization in human neutrophils, suggesting that they also exhibited innate immunomodulatory activity, as intracellular Ca2+ mobilization is a key component of neutrophil activation. Indeed, pretreatment of cells with the E. purpurea EO or δ-cadinene inhibited subsequent heterologous agonist-induced Ca2+ mobilization and inhibited human neutrophil chemotaxis toward N-formyl peptide. This study shows that the E. purpurea EO and major components were microbicidal but also had immunomodulatory effects on neutrophil activation, and we suggest that this combination of host defense against pathogens and modulation of the inflammatory response may contribute to the reported beneficial health effects of Echinacea extracts. Furthermore, we identified δ-cadinene as one of the active components in E. purpurea oil, and pharmacophore mapping studies predicted two potential MAPK targets for (+)-δ-cadinene.The flower EOs of


Bojanggunbi-tang (BGT) is used to treat various gastrointestinal (GI) diseases. In this study, we investigated the regulatory mechanism underlying the influence of BGT on the interstitial cells of Cajal (ICCs), pacemaker cells in the GI tract. Within 12 h of culturing ICCs in the small intestines of mice, the pacemaker potential of ICCs was recorded through an electrophysiological method. An increase in the BGT concentration induced depolarization and decreased firing frequency. This reaction was suppressed by cholinergic receptor muscarinic 3 (CHRM3) antagonists, as well as 5-hydroxytryptamine receptor (5HTR) 3 and 4 antagonists. Nonselective cation channel inhibitors, such as thapsigargin and flufenamic acid, along with protein kinase C (PKC) and mitogen-activated protein kinase (MAPK) inhibitors, also suppressed the BGT reaction. Guanylate cyclase and protein kinase G (PKG) antagonists inhibited BGT, but adenylate cyclase and protein kinase A antagonists had no effect. In conclusion, we demonstrated that BGT acts through CHRM3, 5HTR3, and 5HTR4 to regulate intracellular Ca2+ concentrations and the PKC, MAPK, guanylate cycle, and PKG signaling pathways.In traditional Korean medicine, the 16-herb concoction  Gastrointestinal (GI) motility is controlled by the extrinsic nervous system, the intrinsic nervous system of the GI tract, and the endocrine and paracrine systems Bojunggunbi-tang (BGT) is a prescription comprising 16 herbs: Lonicera japonica, Atractylodes macrocephala, Paeonia lactiflora, Dugesia lablab, Dioscorea japonica, Crataegus pinnatifida, Poria cocos, Magnolia officinalis, Citrus unshiu, Alisma orientalis, Massa medicata, Hordeum vulgare, Zingiber officinale, Aucklandia lappa, Amomum villosum, and Glycyrrhiza uralensisTraditional medicines are imperative in treating various diseases; thus, many studies are being conducted for clinical application with traditional medicines Crude BGT herbs were purchased from Kyung Hee Hanyak Co. , and the BGT extract was prepared as described in a previous study Small intestines were excised from ICR mice . The luminal contents were removed using Krebs Ringer bicarbonate solution, tissues were pinned to the bases of Sylgard dishes, and the mucosae were removed through sharp dissection. Intestinal muscles were separated using an enzyme solution . Separated cells were cultured in a smooth muscle growth medium  at 37°C on coverslips coated with murine collagen . All experiments on ICCs were performed following 12 h of culture. Since ICCs have a distinct shape from other cells, they could be identified under a phase-contrast microscope. Experimental mice were ethically handled according to the Guidelines for the Care and Use of Animals approved by Pusan National University (PNU‑2022‑0120).2, 10 mM glucose, 1.2 mM MgCl2, and 10 mM HEPES; pH was adjusted to 7.4 using NaOH. Intracellular solutions were KCl (140 mM), MgCl2 (5 mM), K2ATP (2.7 mM), NaGTP (0.1 mM), creatine phosphate disodium (2.5 mM), HEPES (5 mM), and EGTA (0.1 mM); pH was adjusted to 7.2 using KOH. The whole-cell patch-clamp method was employed to record potentials in the current clamp mode using Axopatch I-D and Axopatch 200B amplifiers  for electrophysiological experiments. Results were analyzed using the Axopatch ID  and pClamp (version 10.0). All experiments were conducted at 30°C.The cell solution comprised 5 mM KCl, 135 mM NaCl, 2 mM CaClTM Reagent , and reverse transcription of total RNA was performed using an M-MLV cDNA Synthesis Kit . Polymerase chain reaction (PCR) primers were as follows: the first PCR amplification with upstream primers  and downstream primers  was performed for 38 cycles under conditions of denaturing at 95°C for 30 sec, annealing at 60°C for 30 sec, and polymerization at 72°C for 1 min. The PCR products—predicted as 213 (Ano1), 511 (Chrm3), 399 (5Htr3), and 359 (5Htr4) base pairs—were separated on 1.5% agarose gel through electrophoresis.Total RNA was extracted using TRIzolp < 0.05. Prism version 5.0  and Origin version 8.0  were used for statistical analyses.All results are presented as mean ± SEM. To determine significance, data were analyzed using one-way analysis of variance, followed by Bonferroni's post-hoc test. Significance was set at p < 0.0001), 17.9 ± 2.0 mV (p < 0.0001), and 24.7 ± 2.3 mV (p < 0.0001), respectively. The frequency change across the same three BGT concentrations was 5.9 ± 0.8 cycles/min (p < 0.0001), 2.6 ± 0.4 cycles/min (p < 0.0001), and 0.9 ± 0.5 cycles/min (p < 0.0001), respectively. Thus, BGT depolarized the ICC pacemaker potential with increasing concentration.ICCs typically showed a depolarization of 24.7 ± 2.3 mV and a frequency of 11.9 ± 0.9 cycles/min  under 4-DAMP pretreatment  under methoctramine and 1.5 ± 0.5 cycles/min under 4-DAMP . In contrast, depolarization was 6.6 ± 0.7 mV (p < 0.0001) under RS39604 pretreatment and 24.9 ± 1.1 mV under SB269970 pretreatment  are involved in regulating GI motility 2+ to determine its role in the ICC response to BGT and observed that the removal did not affect the response , depolarization decreased to 10.4 ± 2.1 mV (p < 0.0001) under thapsigargin treatment and 3.2 ± 0.8 mV (p < 0.0001) under flufenamic acid treatment , respectively , 5.8 ± 1.1 mV (p < 0.0001), and 10.9 ± 1.0 mV (p < 0.0001), respectively , and 7.1 ± 0.9 cycles/min (p < 0.0001)  and mitogen-activated protein kinase (MAPK) antagonists. Pretreatment with the PKC antagonists—rottlerin, calphostin C, and chelerythrine—inhibited the BGT-induced ICC response Figs. A-D. Undeely Fig. E. Simila01) Fig. F.p < 0.001), 10.4 ± 1.5 mV (p < 0.0001), and 25.3 ± 2.1 mV, respectively , 5.2 ± 0.9 cycles/min (p < 0.0001), and 1.6 ± 0.5 cycles/min , and 12.5 ± 1.3 mV (p < 0.0001), respectively , 4.8 ± 1.5 cycles/min (p < 0.0001), 3.4 ± 0.9 cycles/min (p < 0.01), and 1.3 ± 0.4 cycles/min  inhibitor, KT5720, and the protein kinase G (PKG) inhibitor, KT5823. Pretreatment with KT5720 had no effect, whereas pretreatment with KT5823 suppressed BGT action on ICCs (Figs. Daehwajungeum” and “Sambaek-tang,” two famous Korean medications for GI diseases, and is considered superior because it has no known side effects In traditional Korean medicine, BGT is widely prescribed for treating digestive diseases The GI tract comprises the mouth, pharynx, esophagus, stomach, small intestine, large intestine, and anus As pacemakers, ICCs are crucial for GI motility and are involved in neurotransmission 2+ was uninvolved in BGT efficacy, whereas intracellular Ca2+ and nonselective cation channels in the cell membrane were involved (Fig. in vivo experiments to explore the possibility of controlling GI motility through these pathways. Previous studies have attributed BT efficacy against colitis to the effects of a combination of well-known herbs, including Lonicera japonica, Crataegus pinnatifida, and Glycyrrhiza uralensisHere, we confirmed that BGT depolarized and reduced the pacemaker-potential frequency in ICCs Fig. . We alsoved Fig. . Antagonved Fig. -8. There3 and intracellular calcium concentrations CHRM3 is present throughout the body, including in smooth muscles, endocrine glands, exocrine glands, lungs, intestines, and the brain + and K+ cation channels. Another important serotonin receptor class is 5HTR4, which increases cAMP concentration by binding to G-proteins 5HTR is a group of G protein-binding receptors and ligand-opening ion channels in the central and peripheral nervous systems We demonstrated that BGT acts on CHRM3, 5HTR3, and 5HTR4 to regulate intracellular calcium through the PKC, MAPK, guanylate cycle, and PKG mechanisms. Based on this study's findings, we propose the following model of BGT effects on ICCs Fig. . In partTraditional medicine is especially useful for functional diseases and those who experience adverse side effects from Western treatments or find them ineffective due to constitutional problems. In the early stages of organic disease, traditional medication may be more effective than Western treatment while also being effective against chronic and consumable diseases. Most GI-motility disorders are functional diseases and thus potentially amenable to traditional medicine, particularly when considering the evidence of therapeutic efficacy without side effects. In conclusion, we believe that BGT is a safe and effective treatment for controlling GI motility.