There is high clinical demand for the resolution of tendinopathies, which affect mainly adult individuals and animals. Tendon damage resolution during the adult lifetime is not as effective as in earlier stages where complete restoration of tendon structure and property occurs. However, the molecular mechanisms underlying tendon regeneration remain unknown, limiting the development of targeted therapies. The research aim was to draw a comparative map of molecules that control tenogenesis and to exploit systems biology to model their signaling cascades and physiological paths. Using current literature data on molecular interactions in early tendon development, species-specific data collections were created. Then, computational analysis was used to construct Tendon NETworks in which information flow and molecular links were traced, prioritized, and enriched. Species-specific Tendon NETworks generated a data-driven computational framework based on three operative levels and a stage-dependent set of molecules and interactions  responsible, respectively, for signaling differentiation and morphogenesis, shaping tendon transcriptional program and downstream modeling of its fibrillogenesis toward a mature tissue. The computational network enrichment unveiled a more complex hierarchical organization of molecule interactions assigning a central role to neuro and endocrine axes which are novel and only partially explored systems for tenogenesis. Overall, this study emphasizes the value of system biology in linking the currently available disjointed molecular data, by establishing the direction and priority of signaling flows. Simultaneously, computational enrichment was critical in revealing new nodes and pathways to watch out for in promoting biomedical advances in tendon healing and developing targeted therapeutic strategies to improve current clinical interventions. Tendons are fibro-elastic structures that connect muscles to bones allowing movement and conferring resistance even to extreme tensile loads. During the processes of development, the tissue profoundly changes by transforming the tendon from a plastic into a highly specialized structure with a significantly reduced ability to recover homeostasis (regeneration) after injury.Current therapies for tendinopathies have limited success , 2. MostThe estimated socioeconomic burden is over €180 billion in the USA and EU, with a forecast of +25% over the next 5 years, because of the absence of an efficacious therapeutic solution and variations in life expectancy, lifestyle, and working stat. In veterinary medicine, 46% of racehorses suffer from tendinopathy and the related reduced performance generates a loss of €400 Bn worldwide .The clinical relevance of tendinopathies relies on the inability of adult tissue to activate regenerative processes, which is probably related to its poor cellularity, vascularization, and slow metabolism , 8–12.Indeed, tendon healing predominantly relies on reparative processes during the adult age, which involves the deposition of fibrous disorganized tissue (scar) instead of a hierarchically organized extracellular matrix (ECM). Repairing instead of regenerative healing compromises the biomechanical properties , 13–15. Based on the fragmentary information collected to date, fetal and adult tendon differences in healing properties might depend on a complex interaction between the mechanisms involving both local and systemic conditions. Local conditions that may be responsible for the progressive reduction of tendon healing involve changes in the precursor cell niche, the activities of cell-intrinsic pathways , 18–20, Overall, these findings may explain the increased cellular migration, tenocyte synthetic activity , and celAs a result, understanding the mechanisms involved in early successful tenogenesis and the related key molecular pathways is critical to innovate tendon diagnosis and therapy based on solid biological foundations.Because of these needs, it is relevant to stress that animals play a triple role in each field of tendon biomedicine: patiently awaiting clinical solutions, predictive models which collect experimentally the tissue stage-specific biological information, and, finally, the translational role supporting indirectly medical clinic advances.Several animal models, in particular, are recognized to have a clinical translational value in addition to allowing researchers to investigate regenerative mechanisms at an early stage of life when biomechanical and physiological tendon properties are still preserved. Considering fragmentary clinical data in adulthood, these models must be exploited to obtain information related to factors, molecules, and signaling pathways with key roles in driving the proper regeneration of tendon tissue. Nevertheless, these molecules may potentially offer clinical therapeutic solutions to enhance tissue regeneration avoiding unsuccessful adaptive reparative processes.Based on these premises, the present research has been designed to map the genetic factors underlying tendon development during embryo/fetal and pre-puberal life stages identified to date to generate either literature or enriched-derived data collections. This systemic molecular survey was the premise to decipher tendon biology by exploiting computational biology to generate species-specific networks.The Tendon NETworks offered a data-driven computational framework based on molecules  and a stage-stratified  model useful to identify the main players of tenogenesis. In addition, taking advantage of computational network enrichment, it was possible to decode signaling cascades and physiological paths driving toward an efficient and complete tenogenesis in early-stage organisms.Overall, this study highlights the value of mapping complex and partially known biological processes using comparative systems biology. At the same time, the obtained results confirm the role of systems biology in making more comprehensive the evidence collected to date and, what is more important, in proposing new nodes and pathways to promote biology advances potentially impacting clinics.The bibliographic data collection was carried out following the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) Statement 2020 Checklist Guidelines.A combination of the following keywords was adopted: “tendon,” “biology,” “tenogenesis,” “fetal,” “fetus,” “develop,” “mechanism,” and “pathway.” The words “injury,” “disease,” “rupture,” “inflammation,” and “tendinopathies” were excluded from the research. “TS” was used as a Field tag, “AND,” “OR,” and “NOT” were used as Boolean operators, and * as wild cards.In total, 2,332 publications were retrieved including original articles and reviews, and duplicates were removed. Filtering criteria adopted included the following: (I) selection of original articles written in English; (II) original papers concerning the early stage of tendon development during embryo–fetal and pre-puberal life were exclusively considered; (III) original articles regarding tenogenic differentiation of stem cells and/or related to regeneration or pathology were discarded; and (IV) reviews were not included in the data collection; however, their content was examined to better support and discuss the acquired data. Finally, 37 publications of original scientific manuscripts describing molecular interactions including direct  and indirect  association met the inclusion criteria  and thosData collection referred to each model organism was used as input to build a species-specific tenogenesis network using the Cytoscape 3.9.1 software.The hubs, defined as hyperconnected nodes, were identified as nodes with a degree of at least one standard deviation above the network mean as previously described .Each network node was ranked based on the node degree value. Node degree is defined as the number of connections that the node has to other nodes in the network .The Markov Cluster Algorithm (MCL), based on the simulation of a stochastic flow in graphs, was computed to define clusters of highly related nodes in each analyzed network flow. Clustering data were obtained by setting 3 as the inflation parameter. A local network clustering algorithm was applied to each MCL-derived cluster to measure control over information flows between just the immediate neighbors of the cluster. MCL and local network clustering algorithms were supplied by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) platform (STRING).A Search Tool for the Retrieval of Interacting Genes/Proteins   was usedPathways characterizing the tenogenesis network were retrieved from the Kyoto Encyclopedia of Genes and Genomes (KEGG). KEGG is a database resource for understanding high-level functions and utilities of the biological system, and from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies.A Venn diagram toolTo compose the knowledge regarding tenogenic molecular events, evidence-based data including molecular interactions or signaling events (hereinafter referred to as interactions) were collected from the available literature  to buildFirst, the interactions were collected according to the model organism and classified based on the developmental stage of occurrence . The molecular data were retrieved from seven model organisms, most of them belonging to the Mammalia class: Mus musculus (m), Rattus norvegicus (r), Homo sapiens (h), Equus caballus (e), and Bos taurus (b). Two additional models were represented belonging to the Aves and Actinopterygii classes, respectively: Gallus gallus (g) and Danio rerio (d) .Among Mammalia class, half of the interactions belong to m , approximately 10% to r and e , 3% to h (9/286), and a minority of them to b .Interactions retrieved from g accounted the 25% (70 out of 286), whereas d contributed only 1.4% (4/286) .The data collection was also designed to distinguish between embryonic  and prepubertal  vital stages .Second, the set of interactions identified in each model was used as input to generate a species-specific system network (hereinafter collectively referred to as TendonNET identified through the species-specific acronymous), whose topological parameters were computed as reported in Third, nodes composing each TendonNETs were assembled using the MCL-clustering algorithmThe MCL approach enabled us to classify 12 clusters in the mTendonNET, 3 of them in the gTendonNET and 2 in dTendonNET and hTendonNET, whereas both rTendonNET and eTendonNET recognized exclusively 1 cluster . Then, pFinally, to identify and prioritize the influential molecules of each TendonNET, hyperconnected nodes, defined as hubs, were identified, and ranked based on their node degree value . On the Among the 14 hubs identified, upstream molecules belonging to the TGFB family and key TF (TF), such as SCX, MKX, FHL2, and SIX 2, have been recognized. Of note, SCX and members of the TGFB superfamily  appeared to be highly conserved since they are shared in four different model organisms .To provide timing to the identified molecular interactions of mTendonNET, the nodes were further classified on the bases of the developmental stage to build two stage-specific NETs: embryo TendonNET  and prepubertal TendonNET. This analysis was carried out exclusively for the mouse model since it only offered enough interactions in both vital stages.A low overlapping degree  was found among the nodes composing embryo TendonNET (64 molecules) and prepubertal TendonNET (40 molecules) .Interestingly, their MCL-clustering algorithm showed that these 13 nodes belong to common paths in both embryo or prepubertal TendonNETs  even if they take part in different interactions that appeared to be strictly vital stage-dependent .More in detail, the collagen fibril formation path recognized POSTN, COL1A1, and COL5A1 as shared molecules which clustered with COL11A1 in the embryoTendonNET or with COL3A1 and COL2A1 in the prepubertal TendonNET. Similarly, the ECM organization path shared THBS4, ELN, ASPN, COL1A1, POSTN, TNMD, TNC, and COL5A1 clustering with COL11A1 and NID2 in the embryo TendonNET or with COL3A1, COL2A1, DCN, and LOX in the prepubertal TendonNET.Furthermore, FMOD and PRG4 were shared nodes of the Keratan sulfate biosynthesis and clustered with CHST5 and KERA in the embryo TendonNET and with LUM in the prepubertal TendonNET.Tendon/skeletal muscle formation path shared the transcription factors (TF) SCX and MKX clustering with MYF5, MYOD, SOX5, SOX6, HOXC10, and PITX1 in the embryo TendonNET and with GLI1, RUNX2, and IHH1 in the prepubertal TendonNET.Concerning the growth factor signaling path, MAPK1 was identified as a shared node clustering with IGF1, FGF4, FGF6, and FGF10 in the embryo TendonNET and with EGR1, SMAD8, BMP2, IGF downstream molecules PI3K, and nerve growth factor signaling molecules NGF and NGFR in the prepubertal TendonNET.Furthermore, the topological properties of the embryo and prepubertal TendonNETs were computed allowing to define the relative hubs, which also showed a limited level of overlapping. More in detail, the tendon-specific transcription factor SCX was the unique hub of the embryo TendonNET that resulted even to be a shared node. A higher number of hubs was identified in the prepubertal TendonNET. They recognized upstream molecules (TGFB1 and NGF), TF (SCX), and downstream nodes  bearing new nodes predicted to be associated with signaling pathways supporting tenogenesis .Specifically, 77 out of 99 nodes characterizing StringNETs were new .Upstream molecules enclosing growth factors and their related intracellular transduction factors. In total, there were 52 molecules, of which 38 were newly identified by STRING (73%).TF-bearing skeletal muscle and neuronal-related TF, homeobox genes, oncogenes, and chromatin remodelers. In total, there were 23, of which 15 were newly defined by STRING (65%).Downstream effectors include 24 molecules involved in the ECM organization, neuronal cytoskeleton factors, and cell adhesion and binding activities. In total, there were 24, of which 15 were identified as new by STRING (62%).First, all nodes composing the StringNETs were stratified into three main signaling layers:The stratification analysis allowed to depict a model composed of molecules working at different layers of the signaling events primed by extra cell stimuli and conveyed by cytoplasmic signaling molecules toward the activation of tendon/skeletal muscle-critical TF, which are responsible for priming tendon/skeletal muscle development and organization .More in detail, the stratification enabled us to depict connections among the three identified layers of the tenogenic signaling as follows.The signal starts with molecules characterizing the upstream layer that included growth factors and intracellular components belonging to the TGF , WNT , mitogenic , hormone-responsive , and metabolic (HIF1 and AK1) pathways. Signaling converges on the intracellular transcriptional machinery recognizing tendon , muscle skeleton , and neuronal (EGR1 and TCF7L2) TF. The transcriptional program is addressed to modulate the expression of the extracellular matrix (ECM) assembly , maturation , and adhesion , as well as molecules constituting the essential structural blocks of the ECM  could be out lighted as the functional outcomes of the signaling cascade.To unveil new potential branches of the tenogenesis signaling, all the nodes identified in both TendonNET and StringNET data collections were merged using Cytoscape to generate species-specific Enriched TendonNETs . Kyoto EKEGG paths were grouped into macro-categories according to the BRITE hierarchy criteriaBased on the collected data, KEGG applied to TendonNETs allowed us to draw the backbone of the signaling supporting tenogenesis. KEGG analysis of the Enriched TendonNETs allowed to enrich the network map defining new paths and/or network links. This was clear by looking at the increased number of paths recognized in each macro-categories for each NET. Also, the total physiological number of paths retrieved, respectively, in TendonNETs and Enriched TendonNETs reflected this aspect. Indeed, physiological paths recognized in TendonNETs (23) are triplicated when compared with paths of the Enriched TendonNETs (62) . Also, tFurthermore, topological analyses of the Enriched TendonNETs were performed to rank the hubs .Interestingly, the topological analysis of the Enriched TendonNETs allowed us to better articulate the flow of information in tenogenesis by consistently increasing the number of hubs. In total, 25 new hubs were identified in the Enriched TendonNETs, which combine with the 14 outlined in the TendonNETs. Importantly, as highlighted in Moreover, the hubs retrieved into the upstream and TF layers of the tenogenic signaling of the different organisms confirmed a high degree of conservation .Finally, to give a fuller picture of tenogenesis signaling and its regulatory mechanisms, all paths related to tendon physiology, which showed a high degree of conservation among species, were further considered see  by showiTaking advantage of the enrichment procedure, all paths were populated with hubs belonging to each signaling layer , except for the nervous system paths which did not recognize, to date, controller (hubs) belonging to downstream layers. The upstream layer was the most populated, enclosing the hub nodes of the TGFB, WNT, and mitogenic families. The intermediate layer was represented by specific tendon/skeletal TFs and the downstream layer by nodes involved in ECM deposition activities.The high prevalence and impact of tendinopathies worldwide involve humans  involved in tenogenesis during the embryo–fetal and prepubertal lifetimes , 17 to dBased on these premises, the present computational system has been set up to take advantage of the data available in the literature on different model organisms by making species-specific data collections containing molecular interactions, which control tenogenesis in the early life of the most studied organisms. Data collection generated with the literature data allowed us to build seven species-specific networks (TendonNETs) by recognizing the relative nodes and hubs. Their comparative analysis has demonstrated a high level of preservation. Using Venn diagram analysis, several shared clustering nodes were identified; these were primarily represented by paracrine controllers such as IGF, the TGFB family, and neurotrophic factors see . MoreoveThe species-specific data collections showed a greater availability of molecular information specifically in the mouse model (mTendonNET) where a sizeable number of the retrieved interactions could split the mTendonNET into two sub-networks: mEmbryo and mPrepubertal TendonNETs. Interestingly, the comparative analysis of the stage-specific TendonNETs revealed that tenogenesis during embryo and prepubertal phase operates using some common nodes which, however, engage strictly stage-dependent interactions occurring at upstream, TF, and downstream levels.Indeed, the intracellular mediator MAPK1 (otherwise known as ERK2), which was the unique common upstream molecule, works in sensing the signal of mitogenic growth factors in Embryo TendonNETs  has been recognized as crucial for the regulation of tendon differentiation during embryo development or collagen assembly during post-natal life, particularly in Achilles and tail tendons as confirmed in MKX KO mice . First, The15ompareson of SCX and MKX KO mice phenotypes suggests that the TFs exert a complementary function, with SCX playing a key role at the beginning of tendon differentiation and MKX in tissue growth and collagen fibril assembly .Furthermore, systems biology revealed that during both the embryonic and early post-natal stages, these shared TFs are involved in exerting indirect control of close districts composing the muscle-skeletal system, albeit through different nodes. More in detail, the two master tendon TFs in mEmbryo TendonNET mainly interacted with MYF5, MYOD, SOX5, SOX6, and PITX1, thus confirming that tendon embryo development requires the coordinated commitments of TFs controlling muscle, cartilage, and bone cell lineages’ commitment.Even in mPrepubertal TendonNETs, SCX and MKX interact with molecules involved in the maturation of tendon fibrocartilaginous system such as molecules belonging to the Hedgehog (Hh) signaling pathway  , 55.Several downstream effectors are represented as common nodes classified into three MCL-clustering-derived paths: collagen fibril formation , ECM organization , and keratan sulfate path (PRG4 and FMOD).in vivo and in vitro  also recognized a stage-specific interaction, clustering with COL11A1, NID2, and TNC in the mEmbryo TendonNET or with COL2A1 and COL3A1, DCN, and LOX in the mPrepubertal one. Focusing on the Embryo TendonNET, POSTNB  and COL1Consistently, the non-structural matricellular glycoprotein TNC was found as a stage-dependent molecule specifically involved in embryo development and morphogenesis.On the other hand, THBS4, the glycoprotein regulating many ECM protein–protein and protein–cell interactions  interactMoreover, DCN, the ubiquitous small interstitial dermatan sulfate proteoglycan of mPrepubertal TendonNET, has been recognized to interact with several ECM components including COL1A1, COL6A1, ELN, and THBS , 72. DCNScientific studies have also confirmed the interaction of COL1A1, COL2A1, DCN, and ASPN, a proteoglycan expressed in collagen-rich tissues, such as tendon, within mPrepubertal TendonNET . More inFinally, the Keratan Sulfate Biosynthesis path included FMOD and PRG4 as stage-independent nodes which cluster with CHST5 and KERA within the mEmbryo TendonNET and with LUM in the mPrepubertal one.Limited information is available on the Embryo TendonNET KERA node, a proteoglycan previously thought to be ‘corneal-specific’ and currently recognized as abundant also in the tendon where it regulates collagenous ECM . Mappingin vitro and in vivo data confirmed that LUM and FMOD share the same binding region on COL1A1, hence affecting collagen fibrillogenesis  , 53. ColBecause proper tendon development is the result of a coordinated commitment of the other skeletal muscle cell lineages  , additioNeuronal-related TF were finally included and represented the mediators of the NGF/NGFR signaling that was recognized upstream in the mTendonNET. Neuronal-related TF included ERG1, working as a hub in rTendonNET and TCF7L2 and retrieved as a node of the gEnriched TendonNET.Analogously, String enrichment fills out the downstream layer by adding new nodes and hubs responsible for ECM deposition, assembly, maturation, and binding. Among these, some members of the ECM deposition family including COL1A1 and ACAN, and ECM assembly nodes, such as BGN, were identified as hubs in m and bTendonNETs, respectively.Consistent with the signaling flow, two molecules retrieved by the present analysis, COL1A1 and TNMD, were found to be direct downstream targets of the SCX activity.Also, the promoter of COL1A1 was found to be responsive to additional TF, such as ERG1 and ERG2, which have been found to be recruited to the COL1A1 promoter region and promote its transactivation .Like COL1A1, other ECM molecules of the Enriched TendonNETs, such as COL1A2, COL3A1, and COL5A1, have been described as targets of EGR1 and EGR2 during tendon cell differentiation in mouse and chick limbs .A key role for ECM organization was also recognized for COL6A1, a new node of the dEnriched TendonNET. Literature data corroborate its inclusion into the network of events supporting tendon development. Its peculiar function has been associated with the fibroblast-matrix interface. Indeed, COL6A1 was found enriched in peri-cellular regions of tendon fibroblasts. However, the precise mechanism and interaction in which it is involved still need to be defined .The class of molecules responsible for ECM assembly was densely filled by String enrichment with new members, such as SPARC, LUM, and POSTNB. Although data concerning molecular mechanisms encompassing their influence on tendon development are still required, defective mouse models supported their function in tenogenesis , 101–105Finally, to define the physiological processes in which the Enriched TendonNETs nodes participate, a KEGG analysis was performed, which identified four macro-categories of physiological paths including (I) growth, differentiation, and survival, (II) morphogenesis and cell motility, and (III) endocrine and (IV) nervous systems.Of note, the nervous and endocrine systems, which populated almost all NETs following enrichment, emerged as crucial paths for managing early tenogenesis see .In more detail, the nervous system included paths related to neurotrophin signaling and axon guidance recognized as key mediators of neuronal factors such as NGF, NGFR (otherwise known as p75NTR), EGR, TCF7L2, NAB1, and NAB2 nodes.in vivo rats studies confirmed that NGF signaling is associated either with connective tissue homeostasis or pathological tendon characterized by adverse collagen deposition. NGF signaling, for example, is compromised during tendon healing in diabetic organisms . Of note, the latter receptor family can be activated also by other growth factors regulating cell proliferation and differentiation whose activity might be useful to reinforce the signaling cascade promoted by NGF .In line with this premise, the topological analysis of Tendon EnrichedNETs unveiled as a controller node (hub) within the nervous system, and the mitogenic intracellular mediator MAPK1 and the morphogenic growth factor BMP7 see  were invNGF signaling, on the other hand, has been shown to activate ERG1, one of the neuronal TF identified by Tendon NETs, by activating downstream key tendon-related genes that code for molecules involved in ECM deposition , assembly (BGN and DCN), and maturation (FN1) .In addition to ERG1, another neurogenic TF, TCF7L2, has been identified. It was found to be downstream of the WNT cascade in various contexts and to be temporally regulated to ensure the smooth development of oligodendroglia lineage cells , 112 of Notably, two neuronal targets populated the downstream layer in the rEnriched TendonNETs, namely, Nab1 and Nab2. Nab1 and Nab2 are neural tissue-specific actin filament-binding proteins involved in the dynamic organization of actin filaments controlling morphology, migration, and function during neurite formation and axon outgrowths that have never been studied until now in tendon systems.Even though Nab1 and Nab2 showed closely related aminoacidic sequences, they display distinct functions, modulatory phosphorylation/dephosphorylation patterns, and subcellular localization . More inAnalogously, Nab2 acts as a scaffold, anchoring more than 30 partner molecules including cytoskeletal factors, cell adhesion molecules, guanine nucleotide exchange factors (GEF), a regulator of G-protein signaling protein, membrane receptors, and ion channels . Althougin vitro and in vivo studies on animals and humans have revealed that subjects with hormonal imbalances have changes in their tendon microarchitecture and function that are solely hormone-dependent  of TendonNET, the main controller of early tenogenesis.First, the high degree of preservation of the Tendon and Enriched TendonNETs seems to suggest great feasibility in navigating the molecular interaction controlling tenogenesis encompassing the interspecific barriers, even when the animal models are not as closely related evolutionarily.Second, the computational map of tenogenesis established a stepwise process recognizing stage-specific molecular interactions that merit further experimental investigation to improve biological knowledge of this system as a prerequisite for developing the targeted therapeutic strategies that the medical and veterinary sectors have been waiting for. Given the variety of molecular interconnections revealed by the embryonic and prepubertal mouse TendonNETs, it seems reasonable to favor the latter as the experimental model with the greatest translation value for the discovery of mechanisms that could be used in adult tissue.Finally, the present research unveiled a hierarchical organization of the signals managing tendon homeostasis during development identifying, after the computational enrichment, a new and not fully characterized level of signals belonging to the nervous and endocrine systems. Molecules identified with their positive influence during normal tendon development even in an early post-natal lifetime could be exploited for confirming experimentally its role in controlling tissue homeostasis and healing during adulthood.The original contributions presented in the study are included in the article/AP and BB contributed to the design of the study, drafted the study, and revised critically the upstream signaling molecules and transcription factors results. AC-V, AM-H, MF, and MC generated data collection. NB made computational analyses. VR, MEK, and GP contributed to the draft of the work revising critically downstream molecules results. AM-H and PB contributed to the supervision of the manuscript, revision, coordination, and fund recovery. All authors contributed to the article and approved the submitted version.This research was funded by the European Union—Next Generation EU. Project Code: ECS00000041; Project CUP: C43C22000380007; Project Title: Innovation, digitalization, and sustainability for the diffused economy in Central Italy—VITALITY. AC-V, AM-H, and MF were supported by the doctorate project “Perspective for Future Innovation in Tendon Repair H2020-MSCA-ITN-EJD-P4 FIT” (Grant Agreement ID: 955685).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Genetic approaches are increasingly advantageous in characterizing treatment-resistant schizophrenia (TRS). We aimed to identify TRS-associated functional brain proteins, providing a potential pathway for improving psychiatric classification and developing better-tailored therapeutic targets.n = 10,501) and non-TRS individuals , respectively. The reference datasets for the human brain proteome were obtained from ROS/MAP and Banner, with 8,356 and 11,518 proteins collected, respectively. We then performed colocalization analysis and functional enrichment analysis to further explore the biological functions of the proteins identified by PWAS.TRS-related proteome-wide association studies (PWAS) were conducted on genome-wide association studies (GWAS) from CLOZUK and the Psychiatric Genomics Consortium (PGC), which provided TRS individuals (PPWAS-ROS/MAP = 4.15 × 10−2 and PPWAS-Banner = 3.38 × 10−3) and APOL2 (PPWAS-ROS/MAP = 4.49 × 10−3 and PPWAS-Banner = 8.26 × 10−3). Colocalization analysis identified three variants that were causally related to protein expression in the human brain, including CCDC91 (PP4 = 0.981), PRDX1 (PP4 = 0.894), and WARS2 (PP4 = 0.757). We extended PWAS results from gene-based analysis to pathway-based analysis, identifying 14 gene ontology (GO) terms and the only candidate pathway for TRS, metabolic pathways .In PWAS, two statistically significant proteins were identified using the ROS/MAP and then replicated using the Banner reference dataset, including CPT2 (Our results identified two protein biomarkers, and cautiously support that the pathological mechanism of TRS is linked to lipid oxidation and inflammation, where mitochondria-related functions may play a role. Treatment-resistant schizophrenia (TRS) refers to approximately one-third of schizophrenia patients who do not adequately alleviate their psychotic symptoms despite standard antipsychotic treatment . PatientEvidence suggests that earlier age of schizophrenia onset is a robust predictor of TRS, and that male gender, autumn/winter birth, poor premorbid functioning, and rural upbringing may also contribute . HoweverProteomic techniques are increasingly being used to screen for biomarkers of schizophrenia, while no studies have yet applied proteomics to TRS. Proteome-wide association study (PWAS) captures any variant affecting the coding regions of genes, and then assigns each protein-coding gene functional affecting scores, and is widely utilized to robustly prioritize candidate genes . PWAS isThe GWAS summary data of TRS and non-treatment-resistant schizophrenia (non-TRS) were derived from a recently published study . PatientSupplementary aterial.Two human brain proteome reference weight datasets were obtained from recent publicly available studies. The discovery dataset was derived from Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) cohorts, recruiting 391 individuals from two longitudinal clinical-pathologic cohort studies of aging and Alzheimer’s disease (AD) . After qhttp://gusevlab.org/projects/fusion/). Briefly, we utilized FUSION to calculate protein weights in both the discovery and confirmation datasets individually. Subsequently, we combined the genetic effect of TRS (TRS GWAS z-score) with precomputed protein weights by calculating the linear sum of z-score × weight of independent SNPs to perform the PWAS of TRS. Only proteins identified in the discovery dataset and replicated in the confirmation dataset were considered TRS-associated proteins. The linkage disequilibrium reference panel routinely utilized 1,190,321 HapMap SNPs from 489 individuals of European descent from the 1000 Genomes Project in FUSION. We implemented 2,000 permutations to control the potential impact of multiple testing on PWAS results. The proteins with permutated P < 0.05 were considered significant. The design is presented in the Supplementary Figure S1.PWAS analysis was performed by integrating the TRS GWAS data with two brain proteomes using the FUSION pipeline . Genes with PP4 > 0.75 are considered to be colocalized.https://david.ncifcrf.gov/). GO enrichment analysis includes biological process (BP), cellular component (CC), and molecular function (MF) analysis. KEGG database is a bioinformatics resource for mining significantly metabolic pathways enriched in the gene list. The purpose was to extract important GO terms and KEGG pathways, which can depict the characteristics of TRS. The results were considered statistically significant if P < 0.05.The GO annotation and KEGG pathway enrichment analyses of the genes identified by PWAS were performed by the DAVID tool (PPWAS-ROS/MAP = 4.15 × 10−2 and PPWAS-Banner = 3.38 × 10−3) and APOL2 (PPWAS-ROS/MAP = 4.49 × 10−3 and PPWAS-Banner = 8.26 × 10−3). Specifically, in the discovery stage, a total of 24 TRS-related candidate proteins were identified using the ROS/MAP reference dataset, such as PRDX1 (PPWAS-ROS/MAP = 1.00 × 10−3), APOL2 (PPWAS-ROS/MAP = 4.49 × 10−3), and WARS2 (PPWAS-ROS/MAP = 6.41 × 10−3). In the confirmation stage, a total of 19 TRS-related candidate proteins were identified using the Banner reference dataset, such as CPT2 (PPWAS-Banner = 3.38 × 10−3) and ABCC1 (PPWAS-Banner = 4.25 × 10−3). Statistically significant genes identified in PWAS analysis are shown in In PWAS, two significant proteins were identified in the discovery reference dataset and replicated in the confirmation reference dataset, including CPT2 (CCDC91 (PP4 = 0.981), PRDX1 (PP4 = 0.894), and WARS2 (PP4 = 0.757). The results of the colocalization analysis of the genes identified by PWAS are presented in Of all 41 proteins identified by PWAS, colocalization analysis identified three genes that are causal for TRS and encoded functional proteins, including P < 0.0001), Golgi apparatus , oxidoreductase activity , and protein domain specific binding . For pathway enrichment analysis of the genes identified by PWAS, DAVID detected only one candidate pathway for TRS, metabolic pathways .GO enrichment analysis of all 41 genes identified by PWAS results are shown in In this work, we performed TRS-associated PWAS and found a total of 41 proteins that were differentially expressed, 2 of which were duplicated in the PWAS analysis of the discovery and confirmation dataset, suggesting a prominent role in the BPs of TRS, including CPT2 and APOL2. Owing to polygenic inheritance, a complex trait is often influenced by multiple genes with similar functions as annotated in gene pathways. We extended PWAS results from gene-based analysis to pathway-based analysis, identifying 14 GO terms and 1 candidate pathway for TRS. Aiming to understand the mechanisms driving GWAS risk loci, we performed a colocalization analysis of PWAS-identified genes and identified three variants that were causally related to expression in the human dorsolateral prefrontal cortex.TRS may be associated with abnormalities in the β-oxidative metabolic pathway of long-chain fatty acids in mitochondria. We discovered a novel TRS-related protein CPT2. Carnitine palmitoyl transferases 2 (CPT2) is the core protein of a catalytically active multiprotein complex localized in the inner mitochondrial membrane, assisting long-chain fatty acids to enter the mitochondrial matrix for oxidation and energy. The role of the lipid regulatory system on TRS has been supported by studies. One work found that clozapine altered the activity of the AMPK-ACC-CPT1 pathway, a central pathway of lipid metabolism, to affect the lipid compositions of the neuronal membranes in the rat frontal cortex . AbnormaAPOL2 was upregulated in the brains of schizophrenic patients, and polymorphisms in this gene were linked to schizophrenia risk [APOL2 has also been observed in individuals with substance use disorders, including cocaine, cannabis, and phencyclidine [APOL2 is highly expressed in some brain regions, including the hippocampus, intralobular white matter, and the medulla [TRS may be linked to cholesterol transport and homeostasis. The other brain protein we identified was apolipoprotein L2 (APOL2). The apolipoprotein family of proteins facilitates the tightly regulated delivery of lipids and lipophilic substrates to specific cells in the brain, as well as regulating signal transduction pathways . APOL2, nia risk . Differeyclidine . APOL2 i medulla . HoweverCCDC91, PRDX1, and WARS2.CCDC91 is highly expressed in the central nervous system, located in the nucleoplasm and trans-Golgi networks and is involved in subcellular transport and protein localization in the Golgi complex. One study showed an increased incidence of copy number variation in CCDC91 in bipolar disorder patients [CCDC91: identical protein binding. PRDX is a protein family with antioxidant enzyme activity that reduces hydrogen peroxide and alkyl hydroperoxides in cells. Numerous studies have demonstrated the anti-inflammatory and anti-apoptotic effects of PRDX1 [PRDX1 expression. PRDX1 expression was increased in haloperidol-treated C6 cells but decreased in C6 cells treated with risperidone and clozapine [WARS2 encodes mitochondrial tryptophan-tRNA synthetase, a homologous class Ic enzyme. The clinical spectrum associated with WARS2 defects appears to be quite broad, including clinical features  as well as the age of onset and clinical course [WARS2 mutations cause dopa-responsive early-onset parkinsonism and progressive myoclonus ataxia [WARS2 variants cause mitochondrial dysfunction and disease. The effect of variants in these three genes on TRS needs further study.Three gene variants identified by colocalization analysis implied a potential association with TRS pathogenesis, including patients . Its intpatients . Also, oof PRDX1 . It appeof PRDX1 . Antipsylozapine . WARS2 el course . Also, Ws ataxia . These wFunctional enrichment and annotation analysis revealed several mitochondrial-related results implicating mitochondrial function in the pathogenesis of TRS. Some evidence has confirmed that mitochondrial dysfunction is an important pathological factor in schizophrenia, including decreased mitochondrial respiration due to altered complex I activity , motor dOur results revolve more around lipid oxidation and inflammation, which tends to be, but is not fully explained by the “inflammation and oxidative stress” hypothesis of the neurobiological mechanisms of TRS. More evidence is being mined to support this hypothesis. A study showed elevated lipid peroxidation in patients with TRS compared to treatment-responsive schizophrenia patients and healthy controls. This exacerbated peroxidation process in TRS may reflect a deeper abnormality in the fatty acid content of synaptic membranes, leading to the dysfunction of neurons as well as its microenvironment . Early nOur work is the first TRS-related study with proteomic analysis based on a large sample of GWAS summary data, providing an accurate functional profile that presents an unbiased picture of current physiological status. Despite this, the study has certain limitations. TRS is an underreported diagnosis, and although our definition of the phenotype is in line with international criteria, we acknowledge that there may still be individuals with treatment-resistant symptoms in non-TRS datasets. This could result in imperfect phenotypes and misclassifications that weaken our findings and reduce the exploratory power of the brain proteins analyzed. The study sample is mainly of European descent and the conclusions may not pertain to non-European countries. Furthermore, we performed a cross-sectional proteomics study, so no exploration of longitudinal changes in biomarkers was available. More research is needed to test our results in different patient populations and different phases of illness. Additionally, it is worth noting that the age and brain tissue preparation technique of the individuals included in the proteome reference datasets may have a slight impact on the final protein expression results. Finally, some proteins identified in the discovery of PWAS failed to be replicated in the confirmation PWAS, which is attributed to the limited sample size and the stochastic nature of high-throughput proteomic sequencing.CCDC91, PRDX1, and WARS2. Our results cautiously support that the pathological mechanism of TRS is linked to lipid oxidation and inflammation, where mitochondria-related functions may play a role.In conclusion, we performed PWAS analysis and identified two TRS-associated brain proteins, CPT2 and APOL2. Colocalization analysis based on PWAS results identified three variants that were causally related to protein expression, including


Background: Aloin, as a bioactive compound, has a variety of pharmacological functions, but its effects on combined allergic rhinitis and asthma syndrome (CARAS) have not been studied. To clarify the protective effect and mechanism of aloin in the treatment of CARAS by network pharmacology, molecular dynamics simulation and experiment.Methods: The targets of aloin, allergic rhinitis and asthma were obtained from various databases. The protein interaction network was constructed for the common targets, and molecular docking and molecular dynamics simulations were performed for the core targets. Functional and pathway enrichment analysis of common targets was also performed using R software. Varieties of biological experiments were conducted to verify the effect of aloin on the inflammatory changes of CARAS and its regulatory mechanism.Results: A total of 42 anti-allergic rhinitis and 58 anti-asthma targets were obtained, and 5 core anti-allergic rhinitis and 6 core anti-asthma targets were identified using topological analysis. GO and KEGG analyses showed that endopeptidase activity and MAPK signaling pathway played important roles in allergic rhinitis and asthma. Molecular docking and molecular dynamics simulations showed that aloin could stably bind to the core target proteins. Experimental verification showed that aloin significantly inhibited the expression of inflammatory factors, and may regulate CARAS by down-regulating MAPK signaling related proteins.Conclusion: This study identified the protective effect, potential target and mechanism of aloin on CARAS. It provides reference for understanding the molecular mechanism and clinical application of aloin in the ameliorates of CARAS. Asthma and allergic rhinitis (AR) frequently coexist, influencing each other’s disease course and severity . The comNumerous herbal extracts are effective anti-inflammatory medications. Aloe vera is a medicinal plant with numerous biological effects, including liver protection , blood sBased on network pharmacology, molecular docking, molecular dynamics simulation, and animal experiments, this study aims to investigate the effect of aloin on the inflammatory response of CARAS.We used “allergic rhinitis” and “asthma” as keywords to search and screen disease-related genes in the Gene Cards, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), Drug Bank, and Pharm Gkb databases. As a result, we obtained the disease targets for them, respectively. The intersections were then imported into a Venn diagram to determine the intersection targets for the treatment of AR and asthma.Homo sapiens,” medium confidence was set to >0.4, the node was hidden where the network broke open the connection, and the interrelationship diagram of the target proteins was obtained. Then, Cytoscape 3.9.0 software was imported to perform basic network topology analysis using Cyto NCA plug-in. The Eigenvector selected as betweenness (BC), closeness (CC), degree (DC), eigenvector (EC), network (NC), and Local Average Connections-based (LAC) targets above the mean value of method were taken as the key core targets; core components were obtained by analysis.The intersection target genes were imported into the String database, organism was limited to “The universal Protein Resource (Uniprot) and Protein Data Bank (PDB) databases were searched for the three-dimensional structure of the key core target of aloin in asthma and allergic rhinitis, respectively. First, we downloaded the crystal structures of six central targets from the PDB library, including SRC (1o43), ALB (1n5u), EGFR (1xkk), ESR1 (1sj0), MAPK8 (2xrw), and KDR (1ywn). Then, using Chem3D software, the 2D structure of a molecular ligand was converted to its 3D structure. Next, Auto Dock Tools and Vina were used to dehydrate, hydrogenate, and charge core target proteins before performing molecular docking with aloin. Finally, mapping was performed with the PyMOL software.CHARMM36M was used to describe the force field of proteins. The system’s solvent was represented by the TIP3P model, Na+ and Cl-were used to balance the system’s charge, and the complex’s topology file was generated with Gromacs’ pdb2gmx module. The generalized Amber force field (GAFF) and AM1-BCC determined the ligand’s parameters and charge. First, the energy of the solvated system was minimized, and then this process was repeated 5,000 times to optimize the entire system. The entire system was then heated using the canonical ensemble (NVT) system. The system was slowly heated from 0 to 310 K in 100 ps by applying a harmonic constraint of 2 kcal/mol/A2 force constant to the protein skeleton. After heating, the time step was set to 2 fs, and 100 ps was first balanced in the NVT ensemble. Temperature and pressure were controlled using the Langevin and Berendsen algorithms, so the temperature was maintained at 310 K, and the pressure was maintained at 1 atm. Using Gromacs-2022.04GPU for molecular dynamics simulation, The root mean square deviation (RMSD), Root mean square fluctuation (RMSF), The radius of gyration (Rg), Hydrogen bond (Hbond), and solvent accessible surface (SASA) of the composite were calculated. There were 50,000,000 nsteps, and 100 ns were simulated.p < 0.05 as the criterion, the top ten targets were chosen based on the number of targets involved. Simultaneously, KEGG pathway analysis for intersection targets was conducted. The screening criterion was p < 0.05, and the top 30 signals were selected based on this criterion in order to eradicate signal pathways with a high enrichment degree.R software 4.2.1 was used to perform GO enrichment analysis of intersection targets, including the analysis of three modules: Biological process (BP), Cellular component (CC), and Molecular function (MF). Using Female BALB/c mice aged 6–8 weeks, Specific pathogen Free (SPF) grade, and weighing 20 ± 2.5 g were bred in the Animal Room. Throughout the experiment, mice were maintained at a temperature between 23°C and 25°C with a 12-h light-dark cycle and unrestricted access to water and food. The mice used in this study were bred according to the protocol approved by the animal welfare ethics committee of Qingdao University (No.: 220203BALB/C54202208073).3, Shanghai McLean Biochemical Technology Co., Ltd.) suspension of 0.2 mL. On three consecutive days a week for 3 weeks from day 21 to day 37, the treatment groups were intranasal instilled with aloin and budesonide at a dose of 20 μL in the bilateral nasal cavities of the mice by intranasal instillation, followed by 20 μL of OVA in the experimental group. On days 38–42, treatment groups were treated with aloin or budesonide 1 h before OVA challenge, and then the experimental group were aerosolized with OVA (5%) for 30 min, while the mice in the control group received PBS. On day 43, mice were euthanized by cervical dislocation, and biological materials such as lung tissue, nasal mucosa tissue, serum, and alveolar lavage fluid were collected for subsequent analysis : normal group, CARAS group , aloin  low-dose group (10 mg/kg), aloin medium-dose group (20 mg/kg), aloin high-dose group (40 mg/kg), and budesonide  group . On days 0 and 7, All mices were sensitized intraperitoneally with 50 μg/mL ovalbumin  and 10 mg/mL Aluminium hydroxide (Al(OH)analysis .After the last OVA challenge (day 42), each animal was observed for 10 min for symptoms such as nose-picking and sneezing. Before embedding the paraformaldehyde-fixed tissue in paraffin, the tissue was dehydrated with ethanol. The nasal and lung sections were then cut (three to five μm) using a microtome and stained with hematoxylin-eosin staining (H&E). The thickness of nasal mucosa and the number of eosinophils were measured quantitatively in a blinded manner, and the severity of peribronchial inflammation was scored as 0, normal; 1, few cells; 2, inflammatory cell ring 1 cell layer deep; 3, inflammatory cell ring two to four cells deep; 4, a ring of inflammatory cells >4 cells deep .The blood samples collected from the orbital venous plexus and bronchoalveolar lavage fluid (BALF) were placed for 2 h and centrifuged at 4°C for 10 min. The supernatant was obtained and stored at −80°C for later use. OVA-specific IgE, IL-4, IL-5, IL-13, and Interferon gamma (IFN-γ) levels in serum of mice and IL-4, IL-5, IL-13, and IFN-γ contents in BALF were determined by ELISA . The specific procedures followed the kit’s protocol.Using Radioimmunoprecipitation assay buffer (RIPA) lysate, mouse tissues were lysed for 30 min on ice, and protein supernatants were collected by centrifuging at 4 °C and 12,000 rpm for 15 min. The concentration of protein was determined using the BCA assay. The proteins were denatured by adding a loading buffer and heating the mixture for 10 min. The total amount of protein was limited to about 40 μg. After 30 min of electrophoresis at 80 V, the voltage was increased to 120 V for an additional 90 min, and then electroconversion was performed. BSA blocked the PVDF membrane for 2 hours at room temperature. The required antibodies  were diluted in the primary antibody’s dilution solution and incubated overnight at 4°C.After three TBST treatments, the secondary antibody was added and incubated for 2 h at room temperature. The ECL luminescence developer was configured according to specifications, exposed using a chemiluminescence instrument, and the results were analyzed.p < 0.05.Utilizing GraphPad Prism 9 software, the experimental data were analyzed. Multiple groups were compared using a one-way ANOVA with measurement data expressed as mean ± standard deviation (x ± s). Shapiro-Wilk test followed by Tukey’s multiple comparison test was used. The criterion for statistical significance was Initially, we investigated the potential aloin targets using three databases: Swiss Target Prediction, Pharm Mapper, and Similarity Ensemble Approach. Twenty-five genes from the Swiss Target Prediction database, 93 genes from the Pharm Mapper database, and 24 genes from the Similarity Ensemble Approach database were combined to yield 131 drug targets . The seaSimilarly, we sequentially searched five public databases using “asthma” as the search term, including 1448 genes in Gene Cards, 16 in OMIM, 155 in TTD, 93 in Pharm GKB, and 120 in Drug Bank. After combined deduplication, 1613 asthma targets were identified , and 58 The function and signaling pathways of aloin in the treatment of allergic rhinitis and asthma were investigated further. Forty-two intersection aloin targets for treating allergic rhinitis were subjected to GO and KEGG enrichment analyses. The GO results for allergic rhinitis showed a total of 1181 enrichment results. Of these, 1049 were related to BP, 107 to MF, and 25 to CC. The primary biological processes are positive regulation of cytokine production, response to steroid hormone, response to extracellular stimulus, and response to nutrient levels . The celSimilarly, GO and KEGG enrichment analyses were conducted on the 58 intersection targets of aloin in asthma treatment. Seven hundred fifty-three were associated with BP, 94 were associated with MF, and 19 were associated with CC out of a total of 866 enrichment results for asthma. To further validate the predictive ability of bioinformatics, molecular docking was used to examine aloin’s potential for treating AR and asthma. The AR core targets  were selected for molecular docking with aloin following Cyto NCA analysis. The results indicated aloin could interact with ESR1’s GLU-444 and ASN-439 via two hydrogen bonds . It coulFrequently, binding energy is used to characterize the degree of affinity between a receptor and ligand. The lower the binding energy, the greater the affinity and the more stable the conformation. Generally, binding energies less than −5.0 kcal/mol or −7.0 kcal/mol indicate good or strong binding activity between ligand and receptor, respectively. The results indicated that the binding free energies of EGFR, ALB, KDR, MAPK8, ESR1 and SRC to the aloin molecules were −9.8, −8.6, −7.9, −7.4, −7.0, and −6.4, respectively. The above molecules’ docking binding free energies were all ≤ −5; hence, aloin appears to have a high affinity for the primary protein targets of AR and asthma.Using Gromacs-2022.04, we simulated the molecular dynamics (MD) of a 100 ns protein-ligand complex for EGFR, ALB, MAPK8, ESR1, and SRC, respectively, which are typical core targets for allergic rhinitis and asthma. In addition, analyses were conducted on the RMSD, RMSF, Rg, Hbond, and SASA. In order to assess the stability of the ligand-protein complex, the ligand was compared to the corresponding reference ligand.RMSD can disclose the positional difference between the protein’s simulation-generated conformation and its initial conformation. Aloin-ESR1  and aloiThroughout the simulation, RMSF characterizes the flexibility and motion intensity of protein amino acids. As shown in the figure, the drug binds to the protein to stabilize it and exert enzyme activity, which generally reduces the protein’s flexibility. Compared to the corresponding reference ligand, all complexes exhibit a similar tendency, i.e., they cause some fluctuation in the same protein region . HoweverAs shown in the figure, Rg can be used to represent the compactness of the protein structure. Throughout the simulation, the structural dynamics of aloin-EGFR, aloin-ESR1, aloin-MAPK8, and aloin-ALB complexes remained relatively stable . Only alHydrogen bonding is one of the strongest non-covalent binding interactions, making comprehending the binding affinity between ligands and proteins essential. The results indicated that the hydrogen bond numbers for the aloin-ESR1, aloin-EGFR, aloin-MAPK8, aloin-ALB, and aloin-SRC complexes were 0–5, 0–7, 0–8, 0–5, 0–4, and 0–7, respectively . It indiSASA is a valuable parameter for studying protein conformational dynamics in solvent environment. The results indicated that the five complexes had similar contact areas with water, while small molecules had little effect on protein-water action . The aboTo examine the anti-inflammatory effects of aloin on AR and asthma, mouse induced by OVA were used as animal models of CARAS , and varSubsequently, we investigated further the effect of aloin on the inflammatory infiltration of CARAS mouse nasal mucosa and lung tissue. The thickness of nasal mucosa and the degree of bronchial inflammatory infiltration in the CARAS group were significantly higher than those in the other groups. The thickness of nasal mucosa and the degree of inflammatory infiltration in the middle-dose aloin group (20 mg/kg) and the high-dose aloin group (40 mg/kg) and BUD group were less than the CARAS group . FurtherNext, we investigated the activity of aloin resistance CARAS potential mechanism. KEGG enrichment analysis indicated that aloin might significantly treat allergic rhinitis and asthma via the MAPK signaling pathway. Western blot was used to detect the expression of MAPK signaling pathway-related proteins p-ERK, p-JNK, and p-p38 MAPK in mouse tissues . The levConnecting the upper and lower airways, CARAS is a chronic inflammatory disease. Studies on the physiopathology of allergic rhinitis and asthma have revealed that they are triggered by the same identical nature and etiology and have profound correlations, with a comparable spectrum of cellular and humoral immune responses to mediate the inflammatory process. Although many drugs, such as glucocorticoids and antihistamines, are used as antiallergic therapy to alleviate the symptoms of these two diseases, long-term treatment can cause potentially serious side effects and diminish the desired effect . Thus, tThrough network pharmacology, molecular docking, molecular dynamics simulation, and experimental verification via animal models, we demonstrated for the first time that aloin has an anti-inflammatory effect on CARAS and that its protective effect may be achieved by regulating the MAPK signaling pathway. These findings provide direction for a future experimental investigation into the molecular mechanism of aloin in the ameliorates of CARAS. First, the potential therapeutic targets of aloin in treating allergic rhinitis and asthma were extracted from various public databases, followed by the construction of a protein network interaction analysis. Key targets for allergic rhinitis and asthma were EGFR, SRC, ESR1, ALB, and MAPK8, and allergic rhinitis and asthma syndrome were the “same airway disease.” In conclusion, EGFR, SRC, ESR1, ALB, and MAPK8 are most likely the primary targets of aloin in inhibiting CARAS and play a crucial role in reducing CARAS inflammation. These proteins play crucial roles in inflammatory responses, mucus secretion, and numerous other cellular processes that are believed to be essential for treating CARAS . KEGG enin vitro experiments are required to investigate the molecular mechanism of aloin in treating CARAS.In the CARAS mouse model, we observed significant symptoms such as nose scratching and sneezing, however aloin could significantly relieve nasal symptoms. Meanwhile, histopathological analysis showed that aloin treated CARAS mouse had thinner nasal mucosa and reduced peribronchial inflammatory infiltration. These findings proved the efficacy of aloin in alleviating OVA-induced inflammatory response. Moreover, the imbalance between Th 1 and Th 2 cell-mediated immunity plays a crucial role in the pathophysiology of CARAS. The infiltration of eosinophils and a polarized type 2 immune response producing inflammatory cytokines influence inflammatory progression. In the present study, aloin treated group reduced IL-4, IL-5 and IL-13 levels in BALF and increased the levels of IFN-γ, which affected IgE synthesis and the growth and differentiation of eosinophils. Interestingly, the same trend was observed for cytokines in mouse serum, further confirming the effect of aloin. Additionally, protein interaction network topology analysis, KEGG enrichment analysis, molecular docking, and molecular dynamics simulation indicated aloin might act on CARAS via the MAPK pathway. In this study, CARAS mouse had elevated phosphorylated p38, ERK, and JNK. However, after the administration of aloin, the MAPK pathway-related protein levels were reversed. The current study found that aloin may diminish airway inflammation by reducing the expression of phosphorylated proteins in the MAPK signaling pathway. Nevertheless, there are limitations to this research. The mechanism of aloin against CARAS remains unconfirmed, and additional According to the findings of this study, aloin may ameliorate OVA-induced CARAS by modulating the MAPK signaling pathway. Aloin may be a promising treatment option for CARAS. This research provides a firm basis for comprehending the mechanism of aloin and its clinical application in treating CARAS.


Oregano essential oil is a plant essential oil extracted from the plant oregano (Origanum vulgare), which has an antibacterial, anti-inflammatory, and antioxidant effect. Bovine mastitis is a process in which bacterial infection and inflammation co-exist. In this study, network pharmacology technology was used to explore the mechanism of oregano essential oil in the treatment of bovine mastitis, and to predict the core genes and key signaling pathways exerting therapeutic effects. The results showed that the key action targets of oregano essential oil in the treatment of dairy bovine mastitis were TNF, TLR4, ALB, IL-1β, TLR2, IL-6, IFNG, and MyD88, and the main signaling pathways were PI3K-Akt, MAPK, IL-17, NF-κ B. The molecular docking confirmed that thymol and carvacrol in oregano essential oil had a good binding ability to the core targets of TNF, IL-6, MyD88, and ALB. These results indicated that thymol and carvacrol had good anti-inflammatory effects. Therefore, oregano essential oil was considered to have a good therapeutic effect on bovine mastitis.The active components, potential targets, and mechanisms of action of oregano essential oil in the treatment of bovine mastitis disease were investigated using network pharmacology and molecular docking approaches. The TCMSP and literature databases were examined for the main compounds in oregano essential oil. Afterward, the physical, chemical, and bioavailability characteristics of the components were evaluated. The PubChem, BATMAN, PharmMapper, and Uniprot databases were utilized to predict the target genes of the major components of oregano essential oil. Via the databases of DrugBank, OMIM, GeneCards, TTD, and DisGenet, the disease targets of bovine mastitis were discovered. We analyzed common targets and built protein–protein interaction (PPI) networks using the STRING database. Key genes were analyzed, obtained, and compound–target–pathway–disease visualization networks were created using Cytoscape. For the GO function and KEGG pathway enrichment analysis, the DAVID database was utilized. Molecular docking via Autodock Tools was utilized to evaluate the reliability of the interactions between oregano essential oil and hub targets. Thymol, carvacrol, and p-cymene are the three major components found in oregano essential oil. The potential targets  were screened according to the visual network. The enrichment analysis suggested that the major signaling pathways in network pharmacology may include PI3K-Akt, MAPK, IL-17, and NF-κ B. Molecular docking analysis shows that thymol had good docking activity with TNF, IL-6, and MyD88, carvacrol had good docking activity with TNF, and p-cymene had good docking activity with ALB. This study clarified the mechanism of action of oregano essential oil in the treatment of bovine mastitis, thus providing data supporting the potential for the use of oregano essential oil in the development of new therapeutics for bovine mastitis. E. coli, probably due to the increasing number of cases of recurrent and persistent mastitis [Bovine mastitis is a worldwide problem that affects breeding. It is one of the four major diseases of bovines that seriously affects the quality and output of milk, and it causes serious economic losses . Bovine mastitis . After amastitis . The posmastitis . Essentimastitis . As a nemastitis ,15. It hmastitis . TherefoOregano, or Origanum (family: Lamiaceae), and Lippia (family: Verbenaceae) have many effects, including relieving exterior syndrome, clearing summer heat, and eliminating dampness ,18. OregNetwork pharmacology explores the relationships and mechanisms between chemical components and biological networks on a molecular level. It focuses on drug research, combining bioinformatics and network analysis, and reveals the correlations among drugs, genes, and diseases. Primary screening of action targets and signaling pathways is used to predict the mechanism of action of disease therapeutics, thereby theoretically reducing the time for and increasing the success rate of drug development . In thishttps://old.tcmsp-e.com/tcmsp.php (accessed on 12 August 2022)) [https://pubchem.ncbi.nlm.nih.gov/ (accessed on 12 August 2022)), and the target protein was predicted and sequenced based on the pharmacophore structure using the PharmMapper database (http://www.lilab-ecust.cn/pharmmapper/ (accessed on 12 August 2022)). Using “Bos taurus” (common bovine) as the species, the potential targets collected from the TCMSP and the PharmMapper databases were imported into the UniProt database (https://www.uniprot.org/ (accessed on 14 August 2022)) to retrieve the validated drug target genes.The TCMSP  database (t 2022))  and litet 2022)) , respecthttps://www.genecards.org/ (accessed on 16 August 2022)), DrugBank database (https://go.drugbank.com/ (accessed on 16 August 2022)), OMIM (Online Mendelian Inheritance in Man) database (https://omim.org/ (accessed on 16 August 2022)), DisGenet database (https://www.disgenet.org/ (accessed on 16 August 2022)), and TTD (Therapeutic Target Database) database (http://db.idrblab.net/ttd/ (accessed on 16 August 2022)), using Bos taurus and mastitis as screening conditions. Removing the repeated collection set of all the disease genes of the bovine mastitis obtained from each database obtained a final disease target gene.The target genes involved in bovine mastitis-related diseases were obtained from the GeneCard database (https://bioinfogp.cnb.csic.es/ (accessed on 18 August 2022)) for interactions, and the intersection target was selected. The common targets were imported into the STRING online website (https://cn.string-db.org/ (accessed on 18 August 2022)), the species was set as “Bos taurus,” and the confidence level was selected as 0.700 to establish a protein–protein interaction (PPI) network of targets for the treatment of bovine mastitis by oregano essential oil. The PPI network was analyzed using the Cytoscape 3.9.1 cytoNCA plug-in, and the core target genes were screened out and visualized.The drug action targets of the main components of oregano essential oil and the bovine mastitis targets were uploaded to the VENN online website (https://david.ncifcrf.gov/ (accessed on 20 August 2022)), and GO function enrichment analysis and KEGG pathway enrichment analysis were performed. The GO enrichment analysis can separately describe the molecular function, cellular component, and biological process of the gene. The KEGG enrichment analysis reveals the signaling pathways involved by these genes. The GO enrichment analysis and KEGG enrichment analysis reveal which GO terms and signaling pathways with significant enrichment of intersecting targets. Cytoscape 3.9.1 was used to construct the drugs–compounds–targets–pathways–diseases network.The core target genes were imported into the DAVID  database (https://www.rcsb.org/ (accessed on 26 August 2022)) screening. The main components of oregano essential oil and protein corresponding to the target gene were added along with water using Autodock Tools, and hydrogen was removed. Semi-flexible docking was performed via Autodock Vina, and the docking activity score between the receptor and the ligand was calculated. Binding activity was considered good if the score was less than 5.0. The structure with the lowest binding free energy was selected for visualization by PyMOL.The 2D structures of the active compounds of oregano essential oil were downloaded from the PubChem database, and the tertiary structures of the active compounds were optimized via Chem 3D 19.0. The ID of the core target gene was found through UniProt, and the 3D structures of the key protein were downloaded through RCSB PDB (Protein Data Bank) ”. Different circles represent different targets. Different colored lines represent different relationships between genes.The PPI network was visualized by Cytoscape 3.9.1, and the node centrality was calculated by CytoNCA. The targets are arranged according to the degree value . The higThe targets are arranged according to the degree value. Different dots represent different targets. The higher the degree value, the larger the target area. The blue dots are targets with higher degree values. Gray lines represent the connectivity between targets.The targets of the main active components of oregano essential oil for the treatment of bovine mastitis were imported into the DAVID database for GO function and KEGG pathway enrichment analysis. The results showed that there were a total of 291 GO items, including 238 BP  items, 18 CC (cell component) items, and 35 MF (molecular function) items. The main biological processes involved in the treatment of bovine mastitis with oregano essential oil include positive regulation of nitric oxide biosynthetic processes, positive regulation of MAP kinase activity, positive regulation of inflammatory response, positive regulation of RNA polymerase II promoter transcription, positive regulation of NF-κ B transcription factor activity, positive regulation of interleukin-6 production, and positive regulation of tumor necrosis factor production. Cell components mainly include the extracellular space, cell surface, cytoplasm, the external side of the plasma membrane, and the nucleus. Molecular functions mainly include protein binding, protein kinase binding, protein homodimerization activity, receptor binding, and cytokine activity .p value) > 2 is a significant difference; the larger the value, the more significant the enrichment. The different GO terms are arranged according to −log10 .Gene counts represent the number of genes contained in different BPs, CCs, and MFs. −log10 .The size of the dots represents the number of genes contained in different gene pathways. A larger dot contains more genes. Different colors represent different −log10 (The red triangle represented oregano, the yellow diamond represented the main components of oregano, the blue diamond represented the pathway, the green square represented the target gene, and the gray line represented connectivity. This figure shows how oregano treats bovine mastitis.Based on the results of PPI network screening, the core targets of TNF, TLR4, ALB, IL-1β, TLR2, IL-6, IFNG, and MyD88 were selected to dock with the active components of oregano essential oil. When the combination of energy for molecular docking is less than −5.0 kcal/mol, the binding is relatively stable. The combination of energy for molecular docking is shown in The figure shows the binding mode of the main components of oregano essential oil and the protein corresponding to the core targets. If the combination of the energy of molecular docking is less than −5.0 kcal/mol, the binding is relatively stable.In this study, three main components of oregano essential oil were selected for action target analysis, namely, thymol, carvacrol, and p-cymene. The results showed that the key targets for the pharmacological effects of the main components of oregano essential oil were TNF, TLR4, ALB, IL-1β, TLR2, IL-6, IFNG, and MyD88. Tumor necrosis factor is mainly produced by activated macrophages, NK cells, and T cells. TNF has been reported to be a pro-inflammatory factor that stimulates inflammation and plays a role in inhibiting infections and cancer processes . TLR4 anThe GO function enrichment analysis and pathway enrichment analysis indicated that the treatment of bovine mastitis with oregano essential oil involves multiple biological processes and signaling pathways. Cytokines are small-molecule proteins synthesized and secreted by immune cells and non-immune cells. Cytokines regulate cell differentiation and immune response, as well as participate in the inflammatory response by binding to the corresponding receptors . The PI3In this study, network pharmacology and molecular docking technology were used to predict the key targets and main signaling pathways involved in the treatment of bovine mastitis with oregano essential oil. The main components of oregano essential oil were thymol, carvacrol, and p-cymene. The core targets selected by Cytoscape analysis were TNF, TLR4, ALB, IL-1β, TLR2, IL-6, IFNG, and MyD88. The GO enrichment analysis revealed that the main components of oregano oil were mainly involved in the positive regulation of MAP kinase activity, positive regulation of NF-kappaB transcription factor activity, positive regulation of tumor necrosis factor production, positive regulation of interleukin-6 production, positive regulation of RNA polymerase II promoter transcription, positive regulation of nitric oxide biosynthetic processes, and positive regulation of inflammatory response. The KEGG enrichment analysis showed that thymol, carvacrol, and paracetamol could participate in the regulation of the PI3K-Akt signaling pathway, MAPK signaling pathway, IL-17 signaling pathway, and NF-κB signaling pathway. Finally, it was proven by molecular docking that thymol has good docking activity with TNF, IL-6, and MyD88, carvacrol has good docking activity with TNF, and p-cymene has good docking activity with ALB. Therefore, thymol and carvacrol, the main components of origanum essential oil, have good anti-inflammatory abilities.In summary, the main components of oregano essential oil can bind to proteins corresponding to targets such as TNF, TLR4, ALB, IL-1β, TLR2, IL-6, IFNG, and MyD88, and regulate PI3K-Akt signaling pathway, MAPK signaling pathway, IL-17 signaling pathway, and NF-κB signaling pathway to exert their anti-inflammatory effects. Therefore, the oregano essential oil can play a role in treating bovine mastitis. This study provides a theoretical basis for the treatment of bovine mastitis with oregano essential oil, and provides ideas for the development and utilization of other plant essential oils. It can be considered in the development of oregano essential oil or its main components as a new drug to treat bovine mastitis.


Mutations in the atypical protein kinase ALPK1  cause two human diseases, ROSAH syndrome and spiradenoma/spiradenocarcinoma. In this study, we make the unexpected finding that in contrast to wild-type ALPK1, which is activated specifically by bacterial ADP-heptose, the disease-causing ALPK1 mutants are not only activated by ADP-heptose but also by several nucleotide sugars present in human cells, explaining how these diseases can arise independently of bacterial infection. These are new examples of disease caused by loss of specificity of an enzyme for its allosteric activator. The atypical protein kinase ALPK1 is activated by the bacterial nucleotide sugar ADP-heptose and phosphorylates TIFA to switch on a signaling pathway that combats microbial infection. In contrast, ALPK1 mutations cause two human diseases: the ALPK1[T237M] and ALPK1[Y254C] mutations underlie ROSAH syndrome , while the ALPK1[V1092A] mutation accounts for 45% of spiradenoma and 30% of spiradenocarcinoma cases studied. In this study, we demonstrate that unlike wild-type (WT) ALPK1, the disease-causing ALPK1 mutants trigger the TIFA-dependent activation of an NF-κB/activator protein 1 reporter gene in the absence of ADP-heptose, which can be suppressed by either of two additional mutations in the ADP-heptose binding site that prevent the activation of WT ALPK1 by ADP-heptose. These observations are explained by our key finding that although ALPK1[T237M] and ALPK1[V1092A] are activated by bacterial ADP-heptose, they can also be activated by nucleotide sugars present in human cells  which can be prevented by disruption of the ADP-heptose binding site. The ALPK1[V1092A] mutant was also activated by GDP-mannose, which did not activate ALPK1[T237M]. These are new examples of disease-causing mutations permitting the allosteric activation of an enzyme by endogenous molecules that the WT enzyme does not respond to. We propose that the loss of the specificity of ALPK1 for bacterial ADP-heptose underlies ROSAH syndrome and spiradenoma/spiradenocarcinoma caused by ALPK1 mutation. Alpha-protein kinase 1 (ALPK1) is one of the six members of the alpha family of atypical protein kinases, which display no similarity in amino acid sequence to any of the other families of human kinases . Since AThe binding of ADP-heptose to an N-terminal domain of ALPK1 is thought to induce a conformational change that activates the C-terminal kinase domain, enabling ALPK1 to phosphorylate tumour necrosis factor (TNF) receptor-associated factor (TRAF)-interacting protein with forkhead-associated (FHA) domain (TIFA) at Thr9 . This in5Mutations in ALPK1 were recently found to cause two human diseases. The mutation of Thr237 to Met [so far identified in 66 patients from 29 unrelated families –15] and Spiradenomas are a group of neoplasms, usually observed as abnormal growths on the head, neck, and upper body, which may originate from sweat glands or from the bulges at the base of hair follicles . AlthougIt is not known why or how ALPK1[T237M], ALPK1[Y254C], and ALPK1[V1092A] cause two such different human diseases. Here, we report that, in contrast to wild-type (WT) ALPK1, the reexpression of these three mutants in ALPK1 knockout (KO) human embryonic kidney 293 (HEK293) cells activated NF-κB/AP-1-dependent gene transcription in the absence of ADP-heptose, but this ADP-heptose-independent activity was nevertheless abolished (ALPK1[T237M] and ALPK1[Y254C]) or reduced (ALPK1[V1092A]) by further point mutations that prevent the activation of ALPK1 by ADP-heptose. These observations led us to identify nucleotide sugars present in human cells that cause activation of the disease-causing mutants of ALPK1, but not the WT protein.Methods). ADP-heptose stimulated the secretion of SEAP into the culture medium of the parental cell line expressing endogenous WT ALPK1, which was drastically reduced if ADP-heptose was omitted  under the control of NF-κB and AP-1 promoters . Like the ALPK1[R153A] and ALPK1[K233A] mutants, the double mutants T237M/R153A, T237M/K233A, Y254C/R153A, and Y254C/K233A had little or no activity in cells stimulated with ADP-heptose but, surprisingly, they also blocked the activation of these disease-causing mutants in cells in the absence of ADP-heptose .It has been reported that ALPK1 can be activated more efficiently by uridine diphosphate (UDP)-heptose than by ADP-heptose . UDP-hepSimilar to WT ALPK1, ALPK1[T237M] and ALPK1[V1092A] had negligible activity in vitro without ADP-heptose and were activated strongly by ADP-heptose. However, the activity of ALPK1[T237M] was consistently lower than that of WT ALPK1, whereas the activity of ALPK1[V1092A] in the presence of ADP-heptose was consistently higher A and B.Strikingly, both ALPK1[T237M] and ALPK1[V1092A] were activated by UDP-α-D-mannose, ADP-D-ribose and to a lesser extent by cyclic ADP-D-ribose, which did not activate WT ALPK1  or only activated WT ALPK1 slightly (UDP-α-D-mannose) A. AdditiTo investigate whether the nucleotide sugar activators of the ALPK1 mutants were acting by engaging the ADP-heptose binding site, we studied double mutants in which each disease-causing mutation was combined with the R153A mutation. We found that combining the ALPK1[R153A] mutation with the spiradenoma mutant C or the SI Appendix, Fig. S2A), and the concentrations of ADP-D-ribose needed for half-maximal activation of these mutants were 7.1 µM and 19 µM, respectively .Two of the nucleotide sugars that activated both ALPK1[T237M] and ALPK1[V1092A], namely UDP-α-D-mannose and ADP-D- ribose, were analyzed in more detail. The concentrations of UDP-α-D-mannose required for half-maximal activation of ALPK1[T237M] and ALPK1[V1092A] were 2.0 µM and 17 µM, respectively , although it was present at a similar level to the other ALPK1 mutants and WT ALPK1 . This indicated that although ALPK1[Y254C] is active in HEK293-Blue cells  and prevent the activation of ALPK1 by ADP-heptose . The mutation of Thr237 to Met would prevent the formation of this hydrogen bond and might explain why the mutant becomes responsive to some mammalian nucleotide sugars. In contrast, Val1092 is located within the kinase domain of WT ALPK1, which is remote from the ADP-heptose binding site in the linear amino acid sequence of the protein kinase. Structural predictions using AlphaFold2  and, consistent with this notion, the coexpression of plamids encoding ALPK1[1-473] (containing the ADP-heptose binding domain) and ALPK1[959-1244] , produce a functional complex that is ADP-heptose-dependent  and spiradenomas originate from either sweat glands or the bulbs of hair follicles (see Introduction). It is therefore possible that the cells in which these diseases develop express high levels of the ALPK1 mutant and its substrates as well as high levels of one or more nucleotide sugar activators of the mutant. This could explain why the diseases are restricted to only a few cell types and why the phenotypes can be variable. Finally, our results raise the possibility of developing selective inhibitors of the disease-causing mutants of ALPK1 by targeting the allosteric ADP-heptose binding site.Antibodies recognising GAPDH (#2118) and anti-rabbit IgG (#7074) were from Cell Signalling Technology and an antibody recognising ALPK1 (#ab236626) was from Abcam.The following DNA plasmids encoding FLAG-tagged proteins with expression under the control of the CMV promoter were made by Medical Research Council (MRC) Reagents and Services, MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee and are available on request (mrcppureagents.dundee.ac.uk): ALPK1 (DU65668), ALPK1[R153A] (DU71736), ALPK1[R153A/T237M] (DU71739), ALPK1[R153A/Y254C] (DU71737), ALPK1[R153A/V1092A] (DU71738), ALPK1[K233A] (DU71733), ALPK1[K233A/T237M] (DU71768), ALPK1[K233A/Y254C] (DU71764), ALPK1[K233A/V1092A] (DU71735), ALPK1[T237M] (DU65723), ALPK1[T237M/K1067M] (DU71730), ALPK1[Y254C] (DU71685), ALPK1[Y254C/K1067M] (DU71729), ALPK1[K1067M] (DU65680), ALPK1[K1067M/V1092A] DU71728), ALPK1[V1092A] (DU65703). ALPK1 KO cells were converted to ALPK1/TIFA DKO cells using CRISPR/Cas9 gene-editing technology as described  and UDP-α-D-mannose were synthesised in-house. ADP-D-ribose (#C7344), cyclic ADP-D-ribose (#A0752), ADP-α-D-glucose (#A0627), GDP-α-D-mannose (#07508), UDP-α-D-glucose (#U4625), UDP-α-D-galactose (#670111), UDP-α-D-glucuronate (#U5625), UDP-N-acetyl-α-D-galactosamine (#U5252), UDP-N-acetyl-α-D-glucosamine (#U4375), NAD (#N7004), and NAD phosphate (NADP) (#N5755) were purchased from Sigma-Aldrich and UDP-α-D-xylose from Carbosource. All nucleotide sugars and dinucleotides were dissolved in PBS to yield a concentration of 1 mM. To stimulate cells, ADP-heptose was added to the culture medium to achieve a final concentration of 5 μM. An equivalent volume of PBS was added to the culture medium in control incubations.The IKKβ inhibitor BI605906 (#HY-13019), the TAK1 inhibitor NG25 (#HY-15434), and the JNK inhibitor JNK-IN-8 (#HY-13319) were purchased from MedChemExpress and dissolved in DMSO to yield a concentration of 5 mM. They were added to the culture medium to achieve the final concentrations indicated in figure legends. An equivalent volume of DMSO was added to the culture medium in control incubations.2. For lysis, cells were washed twice with ice-cold PBS and scraped from the plate in lysis buffer containing 50 mM Tris–HCl pH 7.5, 1 mM EDTA, 1 mM ethylene glycol-bis(beta-aminoethyl ether)-N,N,N’,N’-tetracetic acid (EGTA), 1% (v/v) Triton X-100, 1 mM sodium orthovanadate, 50 mM sodium fluoride, 5 mM sodium pyrophosphate, 270 mM sucrose, 10 mM sodium 2-glycerophosphate, 0.2 mM phenylmethylsulfonyl fluoride, and 1 mM benzamidine, supplemented with complete protease inhibitor cocktail. Cell lysates were clarified by centrifugation for 20 min at 20,000 × g at 4 °C and the supernatants (cell extracts) transferred to 1.5 mL microcentrifuge tubes, snap frozen, and stored at –80 °C. The protein concentrations of cell extracts were determined by the Bradford procedure.ALPK1 KO HEK293-Blue cells  and the parental cell line (#hkb-null1v) were purchased from Invivogen and cultured in Dulbecco’s modified Eagle’s medium supplemented with 25 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) pH 7.3, 10% (v/v) heat-inactivated foetal bovine serum, 100 U/mL penicillin and 0.1 mg/mL streptomycin and maintained at 37 °C in a humidified atmosphere containing 5% COCells were transfected at 80% confluency using 2.5 µL of lipofectamine 2,000 per 1.0 µg of plasmid, and the culture medium was changed 4 h later. For measurements of SEAP activity in the culture medium, 24-well plates were transfected with 800 ng of plasmid DNA and the cells stimulated with or without ADP-heptose 24 h later. The medium was collected after a further 24 h (unless stated otherwise). Cell culture medium (20 µL) was incubated with 180 µL of QUANTI-blue solution , a substrate of SEAP, in a 96-well plate. The plate was incubated at 37 °C for 30 min, and the absorbance at 645 nm was measured using a microplate reader.To purify ALPK1 for in vitro assays, 60 µg of plasmid DNA encoding WT or mutant ALPK1 was transfected into 15 cm dishes of ALPK1 KO HEK293-Blue cells. After 24 h, the cells were lysed in ice-cold lysis buffer and centrifuged for 20 min , and the supernatants (cell extracts) were divided into aliquots and stored at –80 °C until immunoprecipitation as described below.Prior to immunoprecipitation, cell extracts were subjected to immunoblotting to assess the expression level of WT and mutant ALPK1. One hundred micrograms of cell extract protein containing WT FLAG-ALPK1 and normalised amounts of cell extract protein containing the ALPK1 mutants were incubated for 1 h at 4 °C on a rotating wheel with 15 μL of packed anti-FLAG M2 affinity gel , which had been washed twice with lysis buffer prior to use. After centrifugation for 30 s at 1,000 × g at 4 °C, the supernatant was discarded and the pelleted gel was washed three times with 50 mM Tris-HCl pH 7.5, 1% (v/v) Triton X-100 containing 500 mM NaCl, twice with 50 mM Tris-HCl (pH 7.5), 1% (v/v) Triton X-100, and once with 50 mM Tris–HCl (pH 7.5), 2 mM DTT, 0.1 mM EGTA and 10 mM magnesium acetate.32P]ATP . The reactions were initiated by the addition of [γ-32P]ATP and, after the times indicated in figure legends, the reactions were terminated by the addition of LDS sample buffer containing 2.5% (v/v) 2-mercaptoethanol and heated for 5 min at 75 °C. The FLAG resin was pelleted by centrifugation for 30 s at 13,000 × g and the supernatant was subjected to SDS-PAGE. After staining for 30 min with InstantBlue Protein Stain  and destaining in water for 16 h with frequent changes, the bands corresponding to GST-TIFA were excised and the incorporation of 32P-radioactivity was analysed by Cerenkov counting.The immunoprecipitated FLAG-ALPK1 was incubated at 30 °C in 25 µL of 50 mM Tris-HCl (pH 7.5), 2 mM DTT, 0.1 mM EGTA, and 10 mM magnesium acetate containing 8 μM GST-TIFA and 1 mM [γ-Cell extracts (15 µg of protein) were resolved by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE), transferred to polyvinylidene fluoride membranes, and analysed by immunoblotting as described previously .Appendix 01 (PDF)Click here for additional data file.