Microbial treatment has recently been attracting attention as a sustainable agricultural strategy addressing the current problems caused by unreasonable agricultural practices. However, the mechanism through which microbial inoculants promote plant growth is not well understood. In this study, two phosphate-solubilizing bacteria (PSB) were screened, and their growth-promoting abilities were explored. At day 7 (D7), the lengths of the root and sprout with three microbial treatments, M16, M44, and the combination of M16 and M44 (Com), were significantly greater than those with the non-microbial control, with mean values of 9.08 and 4.73, 7.15 and 4.83, and 13.98 and 5.68 cm, respectively. At day 14 (D14), M16, M44, and Com significantly increased not only the length of the root and sprout but also the underground and aboveground biomass. Differential metabolites were identified, and various amino acids, amino acid derivatives, and other plant growth-regulating molecules were significantly enhanced by the three microbial treatments. The profiling of key metabolites associated with plant growth in different microbial treatments showed consistent results with their performances in the germination experiment, which revealed the metabolic mechanism of plant growth-promoting processes mediated by screened PSB. This study provides a theoretical basis for the application of PSB in sustainable agriculture. Zea mays L.) is the world’s third most important crop after wheat and rice, which together account for 94% of cereal consumption  urea, and 2-(acetylamino)-4-(methylthio) butanoic acid. Only one metabolite shared by M44 and Com  was upregulated. M16 and Com shared 15 metabolites, of which dl-β-leucine, α-linolenic acid, pilocarpine, and 4-methoxybenzaldehyde were upregulated, whereas carbamazepine-d10, 1,4-dihydroxyheptadec-16-en-2-yl acetate, 1-(4-benzylpiperazine)-2-(pyridin-2-ylamino) propan-1-one, adenosine, LPE 17:1, α, α-trehalose, and four different formations of LPG  were downregulated. In addition, 9, 24, and 15 unique metabolites were found in M16, M44, and Com, respectively, most of which were molecular organic acids and amino acids. Interestingly, the top 20 amino acids and molecular organic acids were positively correlated with each other and more likely to promote plant growth. Substances such as LPG and DiHOME were negatively related to these beneficial metabolites. Among them, the series of LPG  showed distinct contrasting trends compared with those of other beneficial metabolites.We then explored the correlations among the top 20 differential metabolites based on different treatment comparisons using heatmaps. Generally, the main differential metabolite families in the three microbial treatments were amino acids, molecular organic acids, and acylated amino acids . Based oTo focus on the functional variation caused by the differential metabolites, KEGG pathway enrichment analysis was performed for each microbial treatment against CK . The topp < 0.05) correlated with maize growth, from which three categories were summarized as amino acids, amino acid derivatives, and other plant growth-regulating molecules. Among them, only six metabolites from each category were exhibited , and these were defined as differential amino acids shared by all three microbial treatments (p < 0.05) higher concentration of L-(-)-methionine and DL-β-leucine in both M16 and Com (vs. CK), whereas no significant differences were found between M44 and CK (p < 0.05) valine-serine was found only in M44 (vs. CK), whereas there were no significant differences among M16, Com, and CK  metabolites by all three microbial treatments (vs. CK); among them, M44 had significantly (p < 0.05) larger amounts of N-acetyl-D-alloisoleucine than M16 and Com, whereas the three microbial treatments had no significant differences in γ-glutamyl cysteine and N-acetyl-L-methionine (p < 0.05) enhanced by M16, M44, and Com (vs. CK), respectively , respectively, whereas the three microbial treatments had no significant differences in phenylacetaldehyde and indole (p < 0.05) increased by M16 and Com (vs. CK), whereas the differences between M44 and CK in those two metabolites did not reach statistical significance (p < 0.05), and it was also much higher with Com than with M44 (p < 0.05).Furthermore, apart from amino acids and their derivatives, other plant growth-regulating molecules such as polyamine, auxin, and molecular organic acid were explored to improve the understanding of the metabolomic mechanism of the plant growth-promoting effects of microbial inoculants . The hisd indole A–D. Moreificance E,F. InteTo address agricultural problems such as overuse of chemical fertilizer, reduction in yield, and decrease in quality in crops, an environmentally friendly, harmless, and sustainable solution is urgently needed. The application of microbial inoculants, which was found to promote the growth and yield of crops , enhancePSB constitute an important microbial taxon that converts insoluble phosphorus into forms available to plants. Based on their ability to secrete organic acids, acid phosphatase, and alkaline phosphatase, PSB lower the pH of the microzone in the rhizosphere and release phosphorus from insoluble rock phosphate (inorganic form) and insoluble organophosphorus (organic form), thereby improving the absorption of phosphorus by plants . Interes−1, which was significantly higher than the other three strains. According to recent research, the amount of soluble phosphorus treated by PSB mainly ranged from 100 to 500 mg L−1 [−1 [−1 [−1 could be regarded as highly efficient PSB [Among all strains in this study, the soluble phosphorus at the seventh day released by M16 and M44 reached 444.88 ± 13.31 and 577.54 ± 33.99 mg L0 mg L−1 ; the low L−1 [−1 . Thus, M [−1 [−1 , and PSBient PSB ,63. Furtient PSB . The perient PSB . Therefoient PSB , and theient PSB .p < 0.05) metabolites (vs. CK), whose productions were enhanced by M16, M44, and Com (commonly or uniquely), 48 metabolites were found to be significantly correlated with plant growth  increased by microbial treatments as well. Previous research indicated that spermine modulated several biological processes in plants during their development and growth, including root growth, cell division, and gene expression [Furthermore, the contents of other plant growth-regulating molecules, such as polyamines, aldehydes, and molecular organic acids, were significantly 9-Hppression . AdditioFrom 48 key metabolites significantly associated with plant growth promotion, some were commonly shared by all three microbial treatments, some were just shared by two of them , and others were uniquely possessed by one of them , which could be regarded as metabolic biomarkers of plant growth-promoting bacteria. M16 and Com had more shared and unique metabolic biomarkers than M44, which was consistent with their performances in promoting plant growth. It is worth mentioning that the discovery of biomarkers could potentially be used to either estimate the microbial ability to promote plant growth, or monitor interactions, which are associated with plant growth and development, between plants and microorganisms in the rhizosphere.Citrobacter amalonaticus (M16) and Bacillus safensis (M44) had the best growth-promoting effects on maize seedlings among the three microbial treatments, with M16 performing better than M44. The variation in compositions of total and differential metabolites among different treatments was highly consistent with their performance in promoting maize growth. A total of 48 key differential metabolites were found to be significantly correlated with maize plant growth, from which three main categories, namely amino acids, amino acid derivatives, and other plant growth-regulating molecules, were summarized. The profiling of these three categories of differential metabolites indicated that the microbial treatments might promote plant growth through modulating the production of those key metabolites, which revealed the metabolic mechanism of the screened PSB in plant growth promotion. This study provides a theoretical basis for studies investigating the plant growth-promoting mechanism of PSB and their application in sustainable agriculture. The application of microbial inoculants and the metabolomics of interactions among plants, microorganisms, and the soil environment should be further researched.In this study, the combination of


Hepatitis E virus (HEV) is the first cause of viral hepatitis in the world. While the water-borne HEV genotypes 1 and 2 are found in developing countries, HEV genotypes 3 and 4 are endemic in developed countries due to the existence of animal reservoirs, especially swine. An HEV infection produces many extra-hepatic manifestations in addition to liver symptoms, especially neurological disorders. The most common are neuralgic amyotrophy or Parsonage–Turner syndrome, Guillain–Barré syndrome, myelitis, and encephalitis. The pathophysiology of the neurological injuries due to HEV remains uncertain. The immune response to the virus probably plays a role, but direct virus neurotropism could also contribute to the pathophysiology. This review describes the main neurological manifestations and their possible pathogenic mechanisms. The hepatitis E virus (HEV) is a leading cause of acute hepatitis worldwide, causing 2 million infections and 70,000 deaths every year . HEV is Hepeviridae family, which is composed of two genera: Piscihepevirus (cutthroat trout virus) and Orthohepevirus , composed of four species (A–D) [Orthohepevirus A, which can also infect other mammals. Orthohepevirus B infects chickens; Orthohepevirus C infects rats and ferrets, and Orthohepevirus D infects bats. Orthohepevirus A is the largest species, with at least eight distinct HEV genotypes that infect human , pigs (HEV3 and 4), wild boar , rabbits (HEV3), deer (HEV3), mongooses (HEV3), yaks (HEV4), and camels (HEV7 and HEV8).HEV is the only member of the es (A–D) ,9. Most Orthohepevirus C HEV [HEV1 and HEV2 circulate in developing countries where they only infect humans. HEV3 is widely distributed around the world, while HEV4 is found mainly in Asia. The HEV3 and HEV4 genotypes are mainly transmitted zoonotically via animal reservoirs, such as pigs, wild boar, deer, and mongooses . There hus C HEV ,12,13, wus C HEV .3) [HEV infections are usually asymptomatic ,16,17. S3) ,30, and 3) ,32. ExtrThis review describes these clinical manifestations and discusses the pathogenic mechanisms that might be involved.The possibility of neurological manifestations following HEV infection was first suspected in 2000, when an Indian patient developed Guillain–Barré syndrome (GBS) following an HEV infection . Then, iNeuralgic amyotrophy (NA), also known as Parsonage–Turner syndrome or brachial plexus neuritis, is characterized by severe neuropathic pain in the arms and shoulders, followed by patchy weakness, atrophy, and sensory disturbance . The disThe various studies of HEV infections in patients with NA have almost all been done on HEV3-infected Europeans. A multicentric study involving four centers in France, the UK, and the Netherland prospectively tested over 450 consecutive patients with acute-onset non-traumatic neurological injury between February 2015 and March 2016. This study found that 11/464 (2.4%) of them were positive for anti-HEV IgM ± HEV RNA . The thrGuillain–Barré syndrome (GBS) is the most common cause of acute neuromuscular paralysis in countries where poliomyelitis has been eliminated . GBS is p < 0.01) [Three recent case-control studies performed in Bangladesh , Japan , and the < 0.01) . The Jap < 0.01) ,59) and  < 0.01) . The Dut < 0.01) . Lastly, < 0.01) . One lim < 0.01) ,62.HEV-infected patients may also suffer from other manifestations, such as neuropathic pain that can evoke small fiber neuropathy, painless sensory disorders like numbness or tingling, encephalitis/myelitis, diplopia, mononeuritis multiplex, vestibular neuritis, myositis, and peripheral neuropathy ,63. In t6 IU/mL) [Orthohepevirus C. The concentration of rat HEV-C1 RNA in the CSF was 1.65 × 103 copies/mL [Meningoencephalitis has been described in a few patients ,64,65,66opies/mL .Anicteric patients can also suffer from cerebral ischemia ,43. A woA group of six French patients infected with HEV3 was found to have mononeuritis multiplex, defined by asymmetric, asynchronous involvement of the non-contiguous nerve trunks . They haCranial neuropathies have been associated with an HEV infection, including isolated facial nerve palsy  and involvement of the vestibular nerve ,69,71,72p < 0.001) [The pathophysiology of the neurological injuries due to HEV remains uncertain. The immune response following virus infection is probably involved. One argument in favor of immune system involvement is the greater frequency of neurological injuries in immunocompetent patients  than in immunocompromised ones  . The six< 0.001) . Lastly,< 0.001) ,78,79. TDirect virus neurotropism could also explain these neurological disorders. A kidney transplant patient chronically infected with HEV presented a pyramidal syndrome. Simultaneous analysis of the HEV quasi-species in the cerebrospinal fluid and the serum showed that the two populations were different, suggesting that HEV was replicating in the CNS . A recenIntraperitoneal infection of Mongolian gerbils with an HEV4 strain (Genbank number KMN024042) isolated from a pig liver led to the detection of both positive and negative RNA strands and ORF2 protein in the brains and spinal cords of the gerbils, indicating that HEV replicates in these tissues. In addition, the reduction of the expression of zonula occludens-1 (Zo1) suggests that HEV4 damages the blood-brain barrier in order to enter the CNS. Pathological changes were also reported, including degeneration and necrosis of neurons, microglia nodules, Purkinje cell necrosis, and infiltration by inflammatory cells . These fGaussia luciferase and is secreted following RNA replication [A replicon system based on the HEV3 Kernow-C1 p6 strain, in which ORF2 is replaced by the lication , was uselication . The olilication . Oligodelication . Periphelication . Others lication . Ribavirlication ,86.Human pluripotent stem cells that have differentiated into mesodermal and neuroprogenitors cells cannot be infected by the Kernow-C1 p6 strain, but transfection of these cells with a subgenomic replicon system (Kernow-C1 p6/luc) allows HEV replication . ConversAn HEV infection is usually diagnosed using a combination of serology and molecular tests ,90. HEV Ribavirin is presently the treatment of choice for patients with a chronic HEV infection . The firThe neurological manifestations due to HEV are now well recognized. NA and GBS are the most frequent, followed by meningo-encephalitis. These three clinical pictures are causally associated with HEV infections. HEV must be considered in the differential diagnosis of idiopathic neurological disorders, including those of patients with normal liver function. The recent finding of HEV RNA persisting in the CSF despite its clearance from the blood and stool should lead physicians to look for HEV RNA in the cerebrospinal fluid of patients with an HEV infection if neurological symptoms persist. The pathophysiology of such manifestations remains to be determined. Similarly, the role of ribavirin in these situations also needs careful evaluation.


Parkin-mutant human fibroblasts, with defective oxidative phosphorylation activity, showed high basal cAMP level likely ascribed to increased activity/expression of soluble adenylyl cyclase and/or low expression/activity of the phosphodiesterase isoform 4 and to a higher Ca2+ level. Overall, these findings support the existence, in parkin-mutant fibroblasts, of an abnormal Ca2+ and cAMP homeostasis in mitochondria. In our previous studies resveratrol treatment of parkin-mutant fibroblasts induced a partial rescue of mitochondrial functions associated with stimulation of the AMPK/SIRT1/PGC-1α pathway. In this study we provide additional evidence of the potential beneficial effects of resveratrol inducing an increase in the pre-existing high Ca2+ level and remodulation of the cAMP homeostasis in parkin-mutant fibroblasts. Consistently, we report in these fibroblasts higher expression of proteins implicated in the tethering of ER and mitochondrial contact sites along with their renormalization after resveratrol treatment. On this basis we hypothesize that resveratrol-mediated enhancement of the Ca2+ level, fine-tuned by the ER–mitochondria Ca2+ crosstalk, might modulate the pAMPK/AMPK pathway in parkin-mutant fibroblasts.Parkin plays an important role in ensuring efficient mitochondrial function and calcium homeostasis.  PARK2 and PARK6, which encode for parkin and PINK1 respectively, are genes responsible of the onset of familial Parkinson’s disease (PD) a progressive degenerative disorder of the central nervous system characterized by dopaminergic neurodegeneration in the substantia nigra pars compacta. Several studies in PD models proved hallmarked dysfunctions of mitochondria, in particular, defect of the respiratory chain complex I, which plays a central role in mitochondrial oxidative phosphorylation (OXPHOS) efficiency and capacity . The re2+ ATPase (SERCA) is involved in maintaining the low resting Ca2+ concentration in cytosolic compartment. In both control and parkin-mutant fibroblasts, the co-treatment with resveratrol and thapsigargin (TG+RSV) did not further increase the high cytosolic level of Ca2+ elicited by TG alone. This leads to assume a limited inhibition of SERCA by resveratrol as already described [2+ level as compared to the TG-treated cells. This result is in agreement with the role of mitochondria in providing a local source of Ca2+ for ER refilling in Ca2+-depleted ER [parkin-mutant fibroblasts, the co-treatment TG+RSV induced an increase of mitochondrial Ca2+ level, as compared with TG-treated cells, showing a level of Ca2+ comparable to that measured in the presence of resveratrol alone. In parkin-mutant cells the TG+RSV co-treatment seems to prevent or, in any case, not to allow the mitochondrial Ca2+ ER refilling in Ca2+-depleted ER cells. The endoplasmic reticular Caescribed . Furtherleted ER . On the 2+ transfer from ER to mitochondria takes place [2+ level in the cytosolic compartment, in both control and parkin-mutant fibroblasts but a marked decrease of the mitochondrial Ca2+ only in control cells, as compared with Dan-treated cells. Under these conditions, in control cells, resveratrol could induce a partial inhibition of SERCA, causing an increase in cytosolic Ca2+ level and, as described for the TG-treatment, this could induce the ER refilling by the mitochondria. In parkin-mutant fibroblasts this process, even in this case, does not appear to occur and upon co-treatment (Dan+RSV) no significant changes of mitochondrial Ca2+ level were observed, as compared with Dan-treated cells. Previous studies clearly established in MAMs a functional and structural communication between mitochondria and ER ,109,110,es place . Co-incuparkin-mutant fibroblasts, the increased resveratrol-dependent Ca2+ level could be responsible for the enhanced activity of intramitochondrial Ca2+-sensitive dehydrogenases. This leads to an increased supply of reducing equivalents for the respiratory chain activity and consequent increase of ATP synthesis [parkin-mutant fibroblasts, the basal high level of mitochondrial Ca2+ is related to dysfunctional mitochondria, mainly derived by the failed auto(mito)phagic process. In this context, resveratrol-induced Ca2+ increase could lead to an improvement of the oxidative phosphorylation system and oxidative stress condition in new functional mitochondria derived from a rebalanced mitochondrial biogenesis vs. mitophagy, resulting from the Ca2+-dependent AMPK/SIRT1/PGC1α activation. In ynthesis ,111. We 2+ homeostasis, in parkin-mutant cells, is object of debate. It is reported that parkin-null cells and fibroblasts expressing mutant parkin showed reduced ER–mitochondria contact sites associated with a decrease in mitochondrial Ca2+ [2+ overload associated with a lower threshold of mPTP-opening, making neurons vulnerable to apoptosis [2+ stimulates the mitochondrial respiratory chain, an excessive Ca2+ load is dangerous for mitochondria by opening mPTP, which results in mitochondrial membrane potential dissipation and respiratory chain uncoupling, associated with a decrease of mitochondrial ATP synthesis [2+ uptake causes a reduction of mPTP opening making the cells resistant to apoptosis . Howeveoduction , we are oduction ,115. ThuR stress , resvera2+ transfer between ER and mitochondria, we studied the effect of 24 h resveratrol-treatment on the expression level of GRP75, Mfn2, and Miro2, three proteins involved in MAMs. Noteworthy, we observed a higher expression level of GRP75 in parkin-mutant fibroblasts, as compared with control cells. GRP75 is part of a multiprotein complex gathering IP3R and VDAC1, functionally coupling ER and mitochondria and promoting Ca2+ exchanges [2+ level [parkin-mutant fibroblasts could contribute to the higher basal Ca2+ level measured in the mitochondrial compartment. In keeping the importance of preserving a proper Caxchanges . In mous2+ level ,117. Theparkin-mutant fibroblasts showed a higher expression of Mfn2 as compared with control cells, which was decreased by resveratrol-treatment. Mfn2 is mainly localized at the MAM-related contact sites [parkin-mutant fibroblasts. In primary fibroblasts from parkin knockout mice and from parkin-mutant fibroblasts, a recent study showed an augmented ER–mitochondria tethering and ER-to-mitochondria Ca2+ transfer, likely due to increased Mfn2 level in MAMs [2+ transfer between the two organelles [parkin-mutant fibroblasts, the high expression level of Mfn2, likely due to the lack of its ubiquitination, could be involved in the increased steady-state Ca2+ level. Moreover, ct sites ,120,121,ct sites ,122. It ct sites ,124 for  in MAMs . Furtherganelles . In the 2+-sensing EF hand domains, in the ER–mitochondria contact sites regulation [2+ level in PINK1 mutant dopaminergic neurons [parkin-mutant fibroblasts, which could be responsible of the high Ca2+ level therein. Furthermore, it is worth mentioning that the ER stress upregulates GRP75 [2+ overload, exactly as observed by our group in parkin-mutant cells. Rho GTPases Miro1/2, localized in the mitochondrial outer membrane, are components of a complex that anchors mitochondria to motor proteins. Their ubiquitination by parkin leads to mitochondrial arrest that further facilitates the elimination of impaired mitochondria by mitophagy ,126. Recgulation ,69. Furtgulation . Consist neurons . As preves GRP75  and Mfn2es GRP75  expressiparkin-mutant fibroblasts. Thus, the resveratrol treatment, by modulating specific signaling pathways such as AMPK//SIRT1/PGC1α [2+ homeostasis; indeed, in colon cancer cells it has been shown that resveratrol induces a metabolic reprogramming, increasing oxidative capacities, pyruvate dehydrogenase activity, and ATP production. These effects were abrogated by Ca2+ chelation or the blockade of the mitochondrial Ca2+ uniporter as well as by the inhibition of AMPK pathway [Parkin plays a central role in the mitochondrial quality-control processes  in whichT1/PGC1α , might lT1/PGC1α ,131), dr pathway . 2+ homeostasis in human skin parkin-mutant fibroblasts, a parkin-null cellular model. The OXPHOS efficiency improvement by resveratrol, via the AMPK/SIRT1/PGC1α pathway, which we reported in parkin-mutant fibroblasts in our previous study [2+ levels and modulation of protein expression at the ER–mitochondria contact sites. In this study we showed that resveratrol induces a significant increase of cytosolic and mitochondrial Ca2+ level in parkin-mutant fibroblasts, resulting in a remodulation of the cAMP level. Moreover, resveratrol induces a significant downregulation of the expression level of Miro2 and Mfn2, proteins involved in the ERMCSs, highly expressed in parkin-mutant fibroblasts, likely regulating the Ca2+ traffic between ER and mitochondria. These findings might shed new light in identifying novel molecular targets for PD treatment.The aim of the present study was to investigate the effect of resveratrol on deregulated cAMP and Caus study , can be


EGFR) oncogene. Kirsten rat sarcoma (RAS) 2 viral oncogene homolog (KRAS) mutations were reported to drive CRC by promoting cancer progression in activating Wnt/β-catenin and RAS/extracellular signal-regulated kinase (ERK) pathways. In addition, KRAS is associated with almost 40% of patients who acquire resistance to EGFR inhibitors in mCRC. Multiple studies have demonstrated that cancer stem cells (CSCs) promote tumorigenesis, tumor growth, and resistance to therapy. One of the most common CSC prognostic markers widely reported in CRC is a cluster of differentiation 44 (CD44), which regulates matrix metalloproteinases 7/9 (MMP7/9) to promote tumor progression and metastasis; however, the molecular role of CD44 in CRC is still unclear. In invasive CRC, overexpression of MMP7 was reported in tumor cells compared to normal cells and plays a crucial function in CRC cetuximab and oxaliplatin resistance and distant metastasis. Here, we utilized a bioinformatics analysis and identified overexpression of KRAS/MMP7/CD44 oncogenic signatures in CRC tumor tissues compared to normal tissues. In addition, a high incidence of mutations in KRAS and CD44 were associated with some of the top tumorigenic oncogene’s overexpression, which ultimately promoted a poor response to chemotherapy and resistance to some FDA-approved drugs. Based on these findings, we explored a computational approach to drug repurposing of the drug, sulfasalazine, and our in silico molecular docking revealed unique interactions of sulfasalazine with the KRAS/MMP7/CD44 oncogenes, resulting in high binding affinities compared to those of standard inhibitors. Our in vitro analysis demonstrated that sulfasalazine combined with cisplatin reduced cell viability, colony, and sphere formation in CRC cell lines. In addition, sulfasalazine alone and combined with cisplatin suppressed the expression of KRAS/MMP7/CD44 in DLD-1 and HCT116 cell lines. Thus, sulfasalazine is worthy of further investigation as an adjuvant agent for improving chemotherapeutic responses in CRC patients.Approximately 25% of colorectal cancer (CRC) patients will develop metastatic (m)CRC despite treatment interventions. In this setting, tumor cells are attracted to the epidermal growth factor receptor ( EGFR) oncogene, and then treatment options include cetuximab or panitumumab [Colorectal cancer (CRC) remains a common cause of cancer-related fatalities globally , despiteitumumab ,12.KRAS gene leads to activation of the Wnt/β-catenin and RAS/extracellular signal-regulated kinase (ERK) pathways [Several reports revealed that acquisition of Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) mutations in CRC play significant roles in cancer progression ,14. KRASpathways ,18. Multpathways ,20,21. Ipathways . Distantpathways . One of pathways ,25, and pathways ; howeverpathways ,28.MMP7 was highly expressed in invasive CRC compared to normal cells ,30 and aKRAS/MMP7/CD44 oncogenes between tumor, metastatic, and normal tissues, we explored the tumor, normal, and metastatic plot (TNMplot), , an RNA-sequence-based rapid analysis which is used to compare data of selected genes [p < 0.05 considered statistically significant.To compare expressions of the ed genes . Data weKRAS/MMP7/CD44 mutations and changes in gene expressions in CRC were determined using the muTarget platform , a platform linking changes in gene expressions and the mutation status of solid tumors, based on a genotype analysis. These results can be used to identify alterations in genetic expressions and target analysis modules which can be used to identify genetic mutations [p < 0.05.Links between utations . DiffereKRAS/MMP7/CD44 oncogenes and drug sensitivity of the genomics of drug sensitivity in cancer (GDSC) of the top 30 drugs in a pan-cancer database, we used the Gene Set Cancer Analysis (GSCA), a web-based tool used to analyze differentially expressed genes (DEGs) and correlations with drug sensitivity [KRAS/MMP7/CD44 oncogenes as factors that influence high diagnostic efficacy values in CRC patients, we explored an ROC analysis based on TCGA database. The response to chemotherapy treatment was based on RECIST criteria (n = 440) ).To determine correlations between the sitivity . All druTo assess the performance of the diagnostic efficacy using different cutoff points based on the sensitivity and specificity, we applied a receiver operating characteristic (ROC) curve. The curve was accordingly constructed by plotting the sensitivity (true positives) against false positives on the X- and Y-axes, respectively . Furtherhttps://string-db.org/ accessed on, 18 June 2021), a web-based tool, which links proteins that cooperatively influence specific biological functions [p < 1.0 × 10−16 was obtained. Interactions among genes were analyzed according to correlations based on experimental data (pink), gene neighborhoods (green), gene fusion (red), gene co-occurrences (blue), and gene co-expressions (black). Moreover, a functional enrichment analysis and PPIs of the KRAS/MMP7/CD44 oncogenes were constructed using the GSCA [In a further analysis, we applied the STRING tool (V11)  (https://cistrome.shinyapps.io/timer/ accessed on 7 October 2021), we determined correlations of KRAS/MMP7/CD44 oncogenic signatures with a set of gene markers of immune infiltration cells including; B cells, CD8+ T cells, CD4+ cells and macrophages (with p < 0.05). The infiltration level was compared to the normal level using a two-sided Wilcoxon rank-sum test.Correlations between KRAS, MMP7, and CD44, were retrieved from the PubChem database in spatial data file (SDF) format. Crystal structures of KRAS (PDB:6BP1), MMP7 (PDB: 2Y6C), and CD44 (PDB: 1UUH) were downloaded from the protein data bank as PDB files and used as docking models. The protein files (in PDB format) and ligand files (in SDF format) were uploaded and submitted to the CD-DOCK tool. Docking results were further visualized using discovery studio for analysis.Ligand-receptor docking is a widely used computer simulation tool in drug discovery to predict binding energies of ligands . We explThe DLD1 and HCT116 human colon cancer cell lines were acquired from American Type Culture Collection  and were cultured according to the vendor’s recommended conditions. All cells were maintained according to recommended culture conditions. Sulfasalazine was synthesized as described in a previous study , while CDLD-1 and HCT116 cells were seeded at 300 cells/well in 6-well plates (Corning) and treated with Sulfasalazine at 13.34 μM (DLD-1) and 12.38 μM (HCT116) and incubated for 7 days. The media was then removed, fixed and stained with a crystal violet solution  as described by Franken et al. . ColonieTumorsphereformation assay was performed according to a previously described method  with som6 colon cancer cells (DLD1 and HCT116) were first cultured with or without sulfasalazine  and followed by resuspension in 1 mL ALDEFLUOR buffer. The cells were washed in ALDEFLUOR buffer and maintained at 4 °C throughout the cell staining process. ALDH activity was determined using the fluorescence (FL1) and low side scatter (SCC) channels of a BD FACSCantoTM flow cytometry system  and FACSDiva software . For the determination of aldehyde dehydrogenase (ALDH) activity analysis, we used the ALDEFLUORTM Kit  according to the manufacturer’s instructions. In short, 1 × 10Total protein lysates from CRC cells and tumor-spheres were extracted after different treatments. They were separated by SDS-PAGE using the Mini-Protean III system  and transferred onto polyvinylidene difluoride (PVDF) membranes using the Trans-Blot Turbo Transfer System (Bio-Rad). Membranes were incubated with the primary antibodies overnight at 4 °C. The following day, membranes were incubated with the secondary antibody. The proteins of interest were detected and visualized using enhanced chemiluminescence (ECL) detection kits . Images were captured and analyzed using the UVP BioDoc-It system . KRAS/MMP7/CD44 in tumor, normal, and metastatic tissues. The enrichment of GO and KEGG pathways was analyzed using gene counts and the false discovery rate (FDR). * p < 0.05 was accepted as being statistically significant.The Kruskal–Wallis test and Dunn’s test were used to assess expressions of p-value < 0.05 considered statistically significantly. Gene expression profiles (GEPs) from liver metastasis of CRC, and primary CRC samples as compared to the adjacent normal samples, obtained from different studies were extracted from the microarray dataset. Results were analyzed from three (3) different datasets, i.e., GSE14297, GSE49355, and GSE81558 datasets. The Venn diagram analysis showed 273, 30, and 51 overlapping upregulated genes from the above three databases, respectively A–C, MoreKRAS, MMP7, and CD44 genes in normal, tumor, and metastatic CRC samples from RNA-Seq data. Analytical results are presented as boxplots and violin plots. We compared the data by first using the Kruskal–Wallis test, which is a method used to test samples originally from the same distribution of specimens. The results acquired showed that increased expression levels of KRAS, MMP7, and CD44 promoted primary tumor and metastasis in CRC samples compared to adjacent normal samples  using the muTarget tool. The top genes with higher expression levels linked to KRAS mutations compared to KRAS wild-type included PHLDA1, HOXB6, and KCNN4, which were associated with worse prognoses (KRAS and CD44 expressions to mutations of the top genes expressed in CRC at the target level (TARGET). The results we obtained showed that ZFR, ABCB10, and OSMR mutations were associated with higher KRAS expression levels, while MAP3K10, TRIM71, and G3BP1 mutations were associated with higher CD44 expression levels in CRC compared to the wild-type. Patients with high expression levels of the KRAS and CD44 oncogenes displayed poor prognoses compared to patients with low expression levels  were associated with drug resistance. High expressions of the KRAS, MMP7, and CD44 oncogenic signatures were potentially resistant to the drug. High expression of KRAS was demonstrated to be resistant to docetaxel, a chemotherapeutic drug [MMP7 and CD44 were shown to be resistant to Bx-912, which is a phosphoinositide-dependent kinase 1 (PDK1) inhibitor [We used the GSCA to determine the drug sensitivity of  circles . Correlatic drug , RDEA119tic drug ,51 . A boxplot of non-responder and responder values, as indicated by the box plot center line, evidently shows that expressions of the KRAS/MMP7/CD44 genes in the colorectal adenocarcinoma (COAD) cohort from the ROC analysis revealed that these genes influenced the response of treatment by lowering the response rate of treatment in CRC patients. The ROC curve was based on true and false positive rates, and results showed that KRAS, MMP7, and CD44 could serve as potential diagnostic biomarkers in CRC. The AUC scores of KRAS, MMP7, and CD44 were 0.557, 0.537, and 0.551, respectively, with p < 0.05 considered significant , gene neighborhoods (green), gene fusion (red), gene co-occurrences (blue), and gene co-expressions (black), e.g., KRAS with CTNNB1, KRAS with CD44, CDH1 with CD44, MMP7 with CD44, MMP7 with KRAS, and CTNNB1 with MMP7. The network had an initial four proteins, which were further increased to 24 nodes. Moreover, the network interactions showed that the genes were arranged in three different clusters: cluster 1 (red) included KRAS, PIK3CA, and YES1; cluster 2 (green) included MMP7, CD44, CTNNB1, and EGFR; and cluster 3 (blue) included GSK3B, APC, and CTNNB1. Protein enrichment of p < 1.0 × 10−16 was obtained from the clustering analysis, with a coefficient of 0.772. KRAS, MMP7, and CD44 oncogenes with the confidence cutoff value set to 0.900 . These genes were largely involved in GO biological processes, including, movement of cells or subcellular components, locomotion, localization of cells, cell motility, and cell migration , and identified similar pathways enriched from co-expressions of the KRAS/MMP7/CD44 oncogenes , where markers were adjusted by purity. As anticipated, results showed correlations of immune cell markers in colorectal adenocarcinoma (COAD), specifically B cells, CD8+ T cells, CD4+ cells and M2 macrophages , against CRC cell lines. Using the SRB colorimetric assay, we showed SSZ treatment sensitized CRC cells towards cisplatin (CDDP) treatment A. Moreovith CDDP D.KRAS, BRAF, and PIK3CA mutations have been widely reported in CRC progression, and their presence is associated with poor responses to anti-EGFR targeted therapies [Despite recent developments of advanced therapies for CRC over the years, high morbidity and mortality continue to surge globally due to this disease . CRC is herapies ,63. The herapies ,65.KRAS, MMP7 and CD44 we found to be upregulated in primary and metastatic CRC as compared to normal samples. Using the Kaplan–Meier plotter bioinformatics tool, we identified higher expression levels of the KRAS, MMP7, and CD44 oncogenes in tumor and metastatic samples, compared to adjacent normal tissues. The RNA-Seq data were analyzed using the Kruskal–Wallis test and Dunn’s test which showed that samples were distributed from the same specimens, and the KRAS, MMP7, and CD44 genes were more highly expressed in metastatic samples  microarray datasets, and identified top upregulated oncogenes in CRC, and among others on the list,  samples , and asssistance ,67,68. Se in CRC ,69, we ftic drug , and to tic drug ,51  [KRAS/MMP7/CD44 oncogenes as factors that influence high diagnostic efficacy in CRC patients; therefore, we explored a ROC analysis based on the TCGA database, on patients’ responses to chemotherapy treatment based on RECIST criteria, and results showed that patients with increased levels of these genes responded poorly to treatment  ,53, navihibitor) ,55, and hibitor) ,57. For reatment . To detel cancer .KRAS/MMP7/CD44 were found to promote CRC progression, metastasis, and resistance to current chemotherapies and targeted therapies, we further explored a computational approach to drug repurposing of sulfasalazine, a niclosamide derivative anti-inflammatory drug, which was recently shown to possess anticancer properties against human tumors [KRAS/MMP7/CD44 signaling pathway in mCRC. Computational medicine is an effective alternative that accelerates drug design and development while also reducing costs [KRAS/MMP7/CD44 in DLD-1 and HCT116 cell lines. Therefore, the efficacy of sulfasalazine is worthy of further investigation in vivo and in the preclinical setting as an alternative treatment in colon adenocarcinoma patients.Since increased expressions and high gene mutations of n tumors ,37. The ng costs . We applKRAS/MMP7/CD44 oncogenic signatures as major players in mCRC. Our bioinformatics analysis showed that these oncogenes are overexpressed in CRC tumor tissues compared to normal tissues, resulting in tumor progression, metastasis, poor prognoses, and resistance to the current chemotherapies and targeted therapies. Additionally, high mutations in the KRAS and CD44 genes were associated with over-expressions of some of the top tumorigenic oncogenes, which ultimately promoted poor responses to chemotherapy and resistance to some FDA-approved drugs. Our in vitro analysis demonstrated that sulfasalazine alone and in combination with cisplatin successfully reduced cell viability, colony, and sphere formation in CRC cell lines. In addition, the dose depended on treatment of sulfasalazine suppressed the expression of KRAS/MMP7/CD44 in DLD-1 and HCT116 cell lines. Therefore, the efficacy of sulfasalazine is worthy of further investigation in vivo and in the preclinical setting as an alternative treatment in colon adenocarcinoma patients.In summary, we identified


Adipose tissue has been classified based on its morphology and function as white, brown, or beige/brite. It plays an essential role as a regulator of systemic metabolism through paracrine and endocrine signals. Recently, multiple adipocyte subtypes have been revealed using RNA sequencing technology, going beyond simply defined morphology but also by their cellular origin, adaptation to metabolic stress, and plasticity. Here, we performed an in-depth analysis of publicly available single-nuclei RNAseq from adipose tissue and utilized a workflow template to characterize adipocyte plasticity, heterogeneity, and secretome profiles. The reanalyzed dataset led to the identification of different subtypes of adipocytes including three subpopulations of thermogenic adipocytes, and provided a characterization of distinct transcriptional profiles along the adipocyte trajectory under thermogenic challenges. This study provides a useful resource for further investigations regarding mechanisms related to adipocyte plasticity and trans-differentiation. The perceived functional complexity of adipose tissue (AT) has changed significantly over the last 30 years since the leptin discovery . The AT Beige adipocytes have been studied over the last three decades . HoweverSingle-cell RNA sequencing (scRNA-Seq) has allowed for the identification of cell-to-cell heterogeneity and plasticity for many different tissues ,17. AnalIntact cell nuclei have been used to perform single-nuclei RNA-seq (snRNA-seq), overcoming the limitations of isolating the complete adipocyte compartment . The snRHere, we show an effective suitable pipeline able to reconstruct the mature adipocyte heterogeneity of the thermogenic response at the single-nuclei resolution. Our analyses generated a comprehensive and expansive cellular atlas presenting three thermogenic adipocyte subpopulations, followed by additional information on the metabolic pathways, the plasticity of individual subpopulations, and transcription factors possibly involved in beige remodeling of WAT. Also, we characterized specific cell surface markers and the secretome for each adipocyte subpopulation. The detailed snRNA-Seq analysis presented herein of the transcriptional changes in WAT adipocytes under thermogenic challenge provides insight into the molecular mechanisms driving adipocyte plasticity.The scRNA-seq data from mature adipocytes under cold-challenge and B3-adrenergic agonist stimulation were acquired from the Gene Expression Omnibus (GEO) database under the series number GSE133486 , which ct-SNE projection, which was developed with a maximum of 2000 iterations.The filtered feature-barcode matrix was used in the following analysis. All additional analysis were performed using Seurat v3 ,40 R pacTo find the optimal number of clusters, the SCCAF was used with an accuracy threshold of 80%. The clustering calculated previously was used as the initial clusters, and the h5ad file used as input was generated using the SeuratToH5ad function. The optimize, skip-assessment, produce-rounds-summary, and optimisation-plots-output parameters were used in this first step to use the sccaf command to round optimization. Then the sccaf-assess command was used to determine the round to be used as a final result by through the observation of accuracies for each round on multiple iterations. For this step the default parameters were used using 20 iterations. Finally, the last step was to generate a plot used to compare the accuracy between different rounds. For this purpose, the sccaf-assess-merger command was employed using the results from step one and two.Adrb3 for Adipocyte, Pecam for Endothelial, Ptprc, and Cd19 for Immune and Cd34, and Pdgfra for Progenitor cell types. Based on these markers and cell types, the tool returned a list of new markers that can separate these cell types. To select these new markers, we performed isolation of each cell type group to check each marker’s expression. The markers that had an expression in the given group greater than 90% of the quantile were considered markers for the respective group. The markers were: Acsl1, Plin4, Mlxipl, Pck1, and Adrb3 for Adipocyte, Btnl9, Ushbp1, Egfl7, Mcf2l and Ptprb for Endothelial, Zeb2, Trps1, Runx1, Ptprc, and Adap2 for Immune, Dcn, Celf2, Meg3, Col1a2 and Col3a1 for Progenitor cell types. So, based on these markers, the tool was able to classify the cell types.To classify the cell types, Metacell  was usedThe mature adipocyte cluster was subsetted using an optimal number of clusters, while the SCCAF (described above) was used with an accuracy threshold of 80%. RT (Ad3 e Ad4), Cold (Ad1 e Ad2), CL (Ad1 e Ad5); adipocyte clusters of cells .Differentially expressed genes between the different conditions each cluster/cell type were identified using FDR < 0.05 and/or |avg_logFC| > 0.25. Functional enrichment analysis was performed using the Enrichr tool v3.0 R package ,45. For Ucp1 compared to adipocytes with lower levels of Ucp1. Each condition’s predicted secretome was visualized using a heatmap plot using Morpheus software [http://www.exocarta.org/, accessed on 28 October 2021) [The differentially expressed genes in the mature adipocyte subclusters  were filtered for genes encoding secreted proteins based on a pipeline of four databases and tools. UniProtKB  annotatisoftware . We alsoer 2021) .Ucp1 compared to adipocytes with lower levels of Ucp1.The differentially expressed genes in the mature adipocyte subclusters  were filtered for genes encoding cell membrane proteins. UniprotKB and GO were also used for the membranome annotation filtering in the proteins classified at “cell membrane” and “plasma membrane”, respectively. The list generated was confirmed using the TMHMM 2.0  algorithp-value < 0.05) between the mature adipocyte subclusters belonging to RT group (Ad3 vs. Ad4) and the CL group (Ad1 vs. Ad5).We used the computational framework CellPhoneDB v2.1.7 in Python to predict cell-cell communication using its repository of curated ligand-receptor interactions for single-cell transcriptomic data ,57. We uTo analyze the trajectory development of adipocyte clusters, an unsupervised pseudo temporal analysis was performed using Monocle2 v2.20.0 ,59,60 R Ucp1. We selected the enriched TFs  to construct the PPI network with their targeted genes found as DEGs in the adipose single-cells expressing or not Ucp1 in cluster Ad1. PPI networks were conducted using STRING v.11.0 . Only medium confidence interactions were included (interaction score of at least 0.4), and the disconnected nodes were omitted in the network. Visualization and data annotation of PPI networks were constructed using Cytoscape v3.7.2 [We used the eXpression2Kinases (X2K) v. 2.0 ,62 workfe v3.7.2 . The Cyte v3.7.2  was usedhttps://software.broadinstitute.org/morpheus, accessed on 28 October 2021). Venn diagrams were plotted using the web server jvenn [Heat-scatter plot was generated using Morpheus    reportedt-SNE plots revealed 17 distinct nuclei clusters at different experimental conditions , Ptprc (for immune cells), Pecam1 , and Adrb3 (for adipocytes)  and CL-treatment, 1 mg/kg/day for four days (CL). We selected the experimental challenges to increase the chance of detecting nuclei of mature primary adipocyte populations. For cells obtained from iWAT samples , the nditions . Those dnditions . We annonditions B. The prnditions . An accunditions , and rounditions . The disnditions B. Thus, pocytes) C.Acsl1, Plin4, Mlxipl, Pck1, and Adrb3), a population of endothelial cells , adipocyte progenitors and stem cells , and immune cells   E. Adipocd Adap2) . These tt-SNE. Interestingly, it identified five distinct adipocyte subpopulations . Ad3 and Ad4 adipocyte subpopulations appeared to represent classical adipocytes, and they expressed genes associated with WAT, Cidec, Pnpla, and Adipoq  A. A compperature E suggestperature E. Interey in Ad4 F. Recent and WAT , and suc and WAT .Ntrk2 and Atp1a2), and nine other membrane genes were differentially expressed in both subpopulations, showing the top five highly expressed genes, Irs2, Abca1, Mrap, Irs1, and Adrb3, which could potentially be used as Ad4 subpopulation markers  and Ad4  subpopulation are detailed in To gain additional insight into Ad3 and Ad4 subsets, we performed an analysis of the secretome and membranome using gene expression profiles (DEGs). 29 genes predicted to encode membrane proteins were upregulated exclusively in Ad4, while only two genes were upregulated in Ad3  . Ad3 andt-SNE-plot  has almost no overlap with thermogenic genes such as Ppara, Ucp1, Dio2, Prdm16, Elovl3. Acacb, Acss2, mt-Co2, Macf1, and Gm26917, while for CL were Acsl1, mt-Co3, mt-Co2, mt-Atp6, Fasn. Once we determined that the two treatments (Cold and CL) have different gene expression profiles, we performed functional enrichment analysis  and 9.3% are secreted proteins . VEGFA was the main interacting molecule between Ad1 and Ad5 subclusters . Fasn and Acaca showed a higher level of gene expression in Ad5 than all other subpopulations, which may indicate a specific profile in this adipocyte phenotype.The gene expression profile  of the adipocyte subpopulations shows that the classic thermogenic markers, y in Ad1 G. Other Since reanalysis of the snRNA-seq dataset simultaneously profiles adipocytes under both cold and CL-treatment, we hypothesized that their plasticity could be traced in vivo by mapping a developmental trajectory between distinct adipocyte subpopulations. As two significant subpopulations were resolved in the RT nuclei dataset  from iWAT D, we estEgr2, Dpb, and Xbp1, as well as of genes Nnat, Plppr3, and Chst1 , adipocytes lost expression of transcription factors (TF) nd Chst1 . A progrand Dio2 . The colGtf2ird1 I. Brown Gtf2ird1 .t-SNE representation of adipocyte subpopulations Ad1, Ad2, and Ad5 highlighting nuclei with high expression of Ucp1 . The thermogenic genes Ppara, Dio2, Prdm16, Elovl3, Cox8b are more prevalent in the Ad1 subpopulation . pulation . The topnd Acacb . InteresUcp1High and Ucp1Low). As expected, for Ad1-Ucp1High, pathways related to positive regulation of cold-induced thermogenesis, mitochondrion, lipid oxidation, and response to extracellular stimulus are activated . Protein-protein interactions (PPI) analysis demonstrated that Arpd, Hnf4a, Ers1, Pparg, Sall4, Egr1, Nanog, and Bhlhe40 could interact with the targeted genes differentially expressed in HighAd2-Ucp1. For Ad1-Ucp1Low, Parpg, Sall4, Ers1, Tp63, Ar, and Gata2, the most enriched TFs and PPI analysis demonstrated that Parpg, Ers1, Tp63, and Gata2 could interact with the targeted DEGs. The next step was to analyze the most highly expressed TF genes  [Eno1 and Pkm2 in the CL-adipocytes population, while Ckb/Alpl beige cells are prominent within in the population from cold-challenge animals [Given that TFs are crucial for defining cell identity, we analyzed TF expression levels in the Ad1 subpopulation. For this analysis, we initially evaluated the TFs that are most likely involved in regulating DEGs for Ad1--Ucp1Low . The forTF genes F, in addTF genes . As expend Pkm2) , that ha animals ,69.Ucp1High) in addition to two other adipocyte subpopulations that show gene expression signatures distinct from each other. We also identified a new adipocyte population (Ad5) specific to CL treatment, which demonstrates enrichment for lipid turnover and de novo lipogenesis pathways, suggesting this subpopulation provides a higher energy output in a UCP1-independent fashion. In addition, the pipeline was efficient in identifying other beige adipocyte populations already established in vivo, such as glycolytic beige adipocytes. We further showed that the different adipocyte subpopulations presented specific secretome profiles, mainly composed of proteins secreted via classical and non-classical pathways (such as exosomes).This report presents a pipeline able to analyze existing single-nuclei transcriptome data to gain a greater understanding of the cellular composition of WAT. Here, we generate a comprehensive cellular atlas and classification of the adipocytes into five distinct subpopulations. This allowed us to delineate in vivo trajectories and determine the plasticity of individual adipocyte subpopulations from the inguinal fat pad of mice in the setting of thermogenic challenges. Cold and CL both induce UCP1+ cell populations  was previously shown as an AT-enriched secreted factor, markedly increased during brown adipocyte differentiation. Nrg4 is downregulated in AT during rodent and human obesity. In contrast, gain-and-loss-of-function studies in mice showed it protects against diet-induced insulin resistance and hepatic steatosis [Regarding the secretome of thermogenic subpopulations, Ad1 adipocytes differentially overexpressed teatosis . Interesteatosis . CD1d isteatosis . Adipocyteatosis . In thisUcp1 mRNA. Interestingly, although Ad1-Ucp1High showed a “canonical” thermogenesis genetic signature, by expressing higher DEGs corresponding to energy metabolism, particularly those related to TCA, Ad1-Ucp1Low adipocytes showed higher triglycerides/fat acid cycle and de novo lipogenesis pathways. Also, specialization of fatty acid metabolism (oxidation and transport) and glycolytic processes are more pronounced in Ad1-Ucp1High despite a small portion of Ad1-Ucp1Low adipocytes having a similar profile to that found in Ad1-Ucp1High. Ad1-Ucp1High showed, in addition to the positive regulation of thermogenesis, specialization related to response to extracellular stimulus and cellular carbohydrate metabolic process. Our analyses also showed that the UCP1 independent pathways involved in the thermogenic program, such as glycolytic, and SERCA2-pathway are equally expressed in Ad1-Ucp1High and Ad1-Ucp1Low adipocytes. This fact suggests that other metabolic pathways, particularly those involved in a futile cycle (lipid turnover and SERCA2), could also be involved in the thermogenic metabolism in Ad1 adipocytes in a way that does not depend on the presence or absence of UCP1. In addition to that, some elegant papers have recently provided pieces of evidence that futile cycling between creatine and phosphocreatine is part of a newly described thermogenic pathway [Alpl) in Ad1-Ucp1High, a fact that was more evident in cold stimulated adipocytes from iWAT. Furthermore, it should be highlighted that Ad1-Ucp1Low adipocytes make up about 75% of the adipocyte subpopulation under CL treatment, suggesting its relevance for the detailed understanding of beige remodeling.To fully understand the potential therapeutic relevance of beige remodeling, it is crucial to characterize the overall metabolic properties of beige adipocytes in addition to their thermogenic potential. In this regard, the Ad1 subpopulation was subdivided into two subpopulations, according to the presence or absence of  pathway ,69,76. IEno1 and Pkm2 in Ad1-Ucp1High cells that is prevalent in Ad1 and Ad5 adipocytes (CL-treatment). Also, as described above, these cells were enriched for genes related to glycolytic processes. This result confirms the existence of g-beige population and provides insights into the possible roles of these cells being associated with controlling thermogenesis and glucose homeostasis.In recent years, beige remodeling has been demonstrated through the existence of other thermogenic pathways in a UCP1-independent manner ,78. EvenSlc4a4 and Adra1a and Slc36a2 as specific for Ad1-Ucp1High surface markers, whereas Slc27a1 and Slc1a5 were more typical for Ad1-Ucp1Low. Our analyses show a very particular profile of surface proteins (plasmatic membrane), making possible additional functional analyses of those adipocyte populations. However, experimentally using ex vivo and in vivo or approaches such as sorting cells [These findings motivated us to identify new markers for thermogenic adipocyte types using snRNA-seq data from digested AT samples. Although some consistent studies have presented the transcriptome profile of beige cells, either of bulk  or cellsng cells  and fluoPrdm16, Pparg, Pgc1a, and Ppara, we also showed Clock and Ppara (both up), for CL and Cold, respectively, and Egr1 (downregulated) for both treatments. Zinc finger transcription factor EGR1 is a negative regulator of the fat beige program. Loss of Egr1 in mice promotes browning in the absence of external stimulation and leads to increased Ucp1 expression, which encodes the critical thermogenic mitochondrial uncoupling protein-1 [Brown/beige adipocyte differentiation and activation of the thermogenic program are controlled by sequential actions of transcription factors (TFs), including EBF2, PRDM16, C/EBPΒ, PGC-1α, and PPARγ ,80,81,82rotein-1 . BesidesOur paper shows descriptive evidence generated through in silico analysis from several angles, but the scope of this study lacks the appropriate in vivo models to show a mechanistic link to certain physiological functions. Future studies are needed to validate the metabolic impact of our findings concerning adipose tissue heterogeneity, plasticity, and remodeling. Moreover, secretome and membranome prediction using transcriptomic data as input also needs to be carefully evaluated considering the several mechanisms of transcriptional regulation in mammals. Our pipeline template proposes a global analysis of an adipocyte atlas; thus, there is no proper filter from contaminated droplets. The choice of a cutoff may be arbitrary. Finally, the adipocyte trajectory herein described may differ between depots and thermogenic challenges, and further studies are needed to outline and validate the trajectories in different adipocytes subpopulations.Ucp1High), additional transcriptome analyses allowed us to infer the presence of different secretory functions under thermogenic challenges activated by metabolic pathways, especially those related to the futile cycle. It was also possible to identify some previously characterized beige cell populations (ex vivo and in vivo). On the other hand, Ad1-Ucp1Low seems to have a relevant role, both in energy production, through the pathways independent of UCP1, and in its secretory function. This, in turn, proved to be very specific among the heterogeneous adipocyte populations. Regarding the profile of secretory molecules, most are related to proteins that make up EMC, and the highlighted candidates are potentially secreted via classical pathways and exosomes. Understanding this functional plasticity plays an essential role in establishing the mature adipocytes’ role as a “central” cell type modulating tissue remodeling. In addition, it will provide insights into the molecular basis of metabolic adaptation in physiology and disease.In summary, we present a multidimensional reanalysis at a single-nucleus resolution, which allows the recovery of nuclei of cell types in adipose tissue. Using this tool, it was possible to show the plasticity of adipocytes, which corroborates with recent data from AT snRNAseq ,38. In a


NAD(P)H:quinone oxidoreductase (NQO) is an antioxidant flavoprotein that catalyzes the reduction of highly reactive quinone metabolites by employing NAD(P)H as an electron donor. There are two NQO enzymes—NQO1 and NQO2—in mammalian systems. In particular, NQO1 exerts many biological activities, including antioxidant activities, anti-inflammatory effects, and interactions with tumor suppressors. Moreover, several recent studies have revealed the promising roles of NQO1 in protecting against cardiovascular damage and related diseases, such as dyslipidemia, atherosclerosis, insulin resistance, and metabolic syndrome. In this review, we discuss recent developments in the molecular regulation and biochemical properties of NQO1, and describe the potential beneficial roles of NQO1 in diseases associated with oxidative stress. NQO1 and NQO2 are located on chromosomes 16q22.1 and 6pter-q12, respectively .,104.2) o balance . This su balance . Alterat balance ,115,116.NQO1 wild-type allele is designated as NQO1*1 [The potential roles of NQO1 in health and illness have also been widely studied in human populations ,26. In hNQO1 [Over 20 single-nucleotide polymorphisms (SNPs) have been detected in NQO1 ,117. TheNQO1 . This nuNQO1 ,118. TheNQO1 ,119. TheNQO1 ,119,120.NQO1 ,121,122.NQO1 ,124.The second most common SNP of NQO1 is a replacement of a single nucleotide from C to T at nucleotide position 465 (rs4986998), also referred to as NQO1*3, which is responsible for the exchange of the amino acid at codon 139 from arginine to tryptophan (R139W) ,126. TheOS mediated by increased ROS production leads to an imbalance in redox pathways, followed by oxidative damage . This isUnder basal conditions, NQO1 is abundantly expressed in the cardiovascular system ,79,80. TA previous epidemiological study reported that patients with the NQO1 C609T polymorphism (NQO1*2 genotype) showed a greater prevalence of atherosclerotic carotid plaques than those without this genotype in type 2 diabetic patients . AdditioThe Keap1/Nrf2 pathway is a promising target for the management of metabolic syndrome and type 2 diabetes mellitus ,149. GenMore recently, an interesting study has shown that the astaxanthin —a type of red carotenoid—reduces OS in diabetic animal models induced by streptozotocin combined with high fat and high sugar intake. Of 13,784 diabetes mellitus targets and 120 Ast-targeted proteins evaluated in a combined network/transcriptional analysis, NQO1 was identified as one of three major targets, together with collagen type V alpha-1 and neurogenic locus notch homolog protein 2. These three Ast-intersecting targets finally showed a systematic overview of how Ast works in multiple pathways to reduce Ast-induced OS and insulin resistance ,135. The+, higher levels of hepatic triglycerides, and significantly lower levels of abdominal adipose tissue compared to wild-type mice. Insulin tolerance tests revealed that NQO1-null mice were insulin resistant [NQO1, a downstream target of Nrf2, seems to play a protective role in metabolic syndrome. The onset of metabolic syndrome is accompanied by pro-inflammatory and oxidative processes, which cause insulin insensitivity and disease progression ,158,159.esistant . Thus, Nesistant . β-Lapacesistant ,160. Theesistant . NQO1 gene is extremely expressed in adipocytes, and its transcriptome can be decreased via diet-associated weight reduction [Various human studies have demonstrated that the eduction . The expeduction . +-generating enzymes—NQO1, and cytochrome b5 reductase—mimics CR in animal models [+/NADH inhibits age-dependent decreases in cognitive and motor function in aged mice [The level of NQO1 decreases with age, and decreased NQO1 provides less efficient protection from OS ,140,161.l models . CR, howl models ,164. Feeged mice ,100. Morged mice ,140. NQO1 is correlated with early pathological alterations in AD, and expression of NQO1 is associated with the localization and progression of human brain pathology in patients with AD ,142,165.+/NADH redox balance has been explored chiefly through β-lapachone. NQO1 effectively reduces β-lapachone to a hydroquinone form, which is quickly autoxidized back to a quinone form while generating oxidized pyridine nucleotides (NAD+ and NADP+) and consuming reduced pyridine nucleotides (NADH and NADPH) [+/NAD(P)H redox balance ratio via NQO1-mediated metabolism may have therapeutic potential in the future [+ precursors to upregulate cellular NAD+ levels has led to improvements in aging-related and cardiovascular functional deficits [The development of NQO1-targeted drug delivery and novel compounds activated by NQO1 has been a focus area for active research . In reced NADPH) ,56. Therdeficits ,169,170.deficits . Furtherdeficits . Currentdeficits ,172. PM deficits ,172. In deficits ,174. Thedeficits ,174. Witdeficits .+ that may be critical for inhibiting or preventing metabolic syndrome, binding to mRNA to enhance protein translation, and protecting proteins from proteasomal degradation represent some of the newly discovered functions of NQO1. The effect of null polymorphism of NQO1 on CoQ metabolism has not yet been fully elucidated, but the role of NQO1 as a crucial element of the PMRS, and its ability to reduce CoQ, indicate the essential antioxidant properties of this enzyme. Intriguingly, the capacity of NQO1 to bind to RNA and proteins depends on the redox ratio of pyridine nucleotides, indicating that this protein can function as a redox-dependent switch [NQO1 plays a crucial role in quinone metabolism, facilitating the production of hydroquinones with different chemical properties to those of their maternal quinones. The stability of the converted hydroquinone is an important factor in determining whether NQO1 detoxifies a reactive quinone or augments cellular toxicity. NQO1 was originally classified as a detoxifying enzyme, but it is now known to have many biological functions other than quinone metabolism . Supplyit switch . Studies


SnRK, DREB, ERD and MYC2, showed higher expression in V3, G41, G935 and B9 rootstocks compared to M26 in response to stress. In contrast, WRKY29 was down-regulated in response to stress in the tolerant rootstocks, and its expression was negatively correlated with ABA content and stomatal closure. Overall, the findings of this study showed that B9, V3 and G41 displayed better osmotic stress tolerance followed by G935 then M26 and B118 rootstocks.The growth and productivity of several apple rootstocks have been evaluated in various previous studies. However, limited information is available on their tolerance to osmotic stress. In the present study, the physiological and molecular responses as well as abscisic acid (ABA) levels were assessed in six apple rootstocks  osmotically stressed with polyethylene glycol  application under greenhouse conditions. Our results showed that V3, G41, G935 and B9 had higher relative water content (RWC), and lower electrolyte leakage (EL) under stress conditions compared to M26 and B118. Additionally, water use efficiency (WUE) was higher in V3, G41 and B9 than M26, which might be partially due to the lower transpiration rate in these tolerant rootstocks. V3, G41 and B9 rootstocks also displayed high endogenous ABA levels which was combined with a reduction in stomatal conductance and decreased water loss. At the transcriptional level, genes involved in ABA-dependent and ABA-independent pathways, e.g.,  Apple is one of the most important cultivated fruit trees all over the world. Climate changes and their potential negative effects on apple crop production and sustainability highlight the urgent need for developing stress-resilient cultivars of apple varieties and rootstocks. The effects of several commercial apple rootstocks on the growth and yield parameters of scion varieties have been intensively investigated in several locations in the US and Canada ,2,3,4,5,s), transpiration rate (E), net photosynthesis (PN), abscisic acid (ABA) content, osmolytes accumulation, antioxidant activity, root architecture and transcriptional regulation of the osmotic-related genes (ORGs) [N than G202, M26, or G935 [Malus sieversii than Malus hupehensis, as the former promoted better growth, PN, total biomass, chlorophyll content and relative water content (RWC) [M. sieversii was also associated with reduction in reactive oxygen species (ROS) accumulation in the scion leaves and the rootstock roots and increase in antioxidant enzyme activity like superoxide dismutase, catalase, ascorbate peroxidase and glutathione reductase [The reduction in water potential is the primary symptom of osmotic stress induced by drought, salinity, cold and heat stresses. Under osmotic stress, rootstocks may affect several physiological, biochemical and molecular aspects of the scion including stomatal conductance (gs (ORGs) ,13,14. F or G935 . Also, ‘nt (RWC) . The toleductase . G202, Geductase . Rootstoeductase .s) and transpiration rate (E) in M9, the dwarfing apple rootstock, resulted in better drought tolerance than MM.111, the vigorous rootstock, and the tolerance was associated with higher ABA content in M9 than MM.111 under short-term drought stress [ABA content is elevated in response to osmotic stress elicited by drought, salinity, cold and heat stresses ,17,18. Tt stress ,6. ABA at stress . These gt stress ,20,21.MdDREB members identified in apple [MpDREB2A enhanced drought tolerance in Arabidopsis by promoting root system development [MdWRKY30 has been proven to improve osmotic and salt stress tolerance in apple callus through transcriptional regulation of stress-responsive genes [MdMYB121 in tomato and apple enhanced the tolerance to salinity, drought, and cold stresses [NPR1 is up-regulated in apple roots subjected to drought stress [+-ATPASE (MdVHAs) in improving apple plants tolerance to PEG and sodium chloride (NaCl)-induced osmotic stresses has also confirmed. Indeed, the overexpression of apple MdVHAs in tobacco and tomato improved lateral root growth, showed better stomatal closing, and led to better osmotic adjustment under osmotic stress conditions compared to wild-type plant responses [The increase in ABA in response to stress activates the transcription of several stress-related genes that have ABA-responsive elements (ABREs) in their promoter regions. Sucrose non-fermenting-1 related protein kinase 2 (SnRK2) is a key regulator of the ABA signaling pathway . The rolin apple , many ofin apple . Furtherelopment . The earelopment ,31,32,33elopment ,35,36. Ove genes ,38. Overstresses ,40. MYC2stresses . MYC2 alstresses ,43. Nonestresses ,45. NPR1t stress . The rolesponses ,48,49.Rootstocks perform differently under stress depending on their tolerance ,14. TherThe current study compared the effect of osmotic stress induced by 30% polyethylene glycol (PEG) on M26, V3, G41, G935, B9 and B118 apple rootstocks. When exposed to osmotic stress for 3 consecutive days, the leaf relative water content (RWC) decreased in all tested rootstocks, with a significant reduction of 25%, 12%, 19% and 26% in M26, G41, G935 and B118, respectively, compared to the control (unstressed) plants a. V3 andN), stomatal conductance (gs), transpiration rate (E), inner CO2 (Ci) and water use efficiency (WUE) were measured three days after the PEG (30%) treatment. All rootstocks showed a reduction in PN under osmotic stress with a significant decrease of 39% and 34.4% observed in V3 and G935, respectively, compared to V3 and G935 control plants (N compared to M26 under osmotic stress conditions (s) showed a significant reduction of 38%, 72%, 52 and 61% under osmotic stress in M26, V3, G935 and B9 rootstocks, respectively, and a nonsignificant decrease of 47%, 46% in G41 and B118, respectively, compared to control plants  was determined after three days of stress. All the tested ORGs showed significant regulation under osmotic stress except for otstocks f. The exnditions a. Howeveectively b. Similareatment c. Transcd in M26 d. As forreatment g. ATPASEc stress g.N, gs, E and Ci on the other side. Meanwhile, ABA showed a positive, yet insignificant, correlation with WUE. Moreover, ABA was positively correlated with SnRK and negatively correlated with WRKY29  which in turn results in a reduction in transpiration rate (E) and intercellular CO2 (Ci) content [2 through the leaf causes a decline in photosynthesis in stressed rootstocks compared to control rootstocks [As an adaptation mechanism to alleviate water loss, plants reduce stomatal conductance  and regulating several physiological processes ,20,50,52with WUE ,52. In twith WUE . MoreoveThe six rootstocks showed an increase in ABA concentration in response to osmotic stress. Further, the rate of increase in ABA levels varied from 20% in B9, which showed the lowest increase rate to 61.5% in M26, which showed the highest increase. Despite the high increase rate of ABA levels in M26, it had the lowest ABA content under stress. These results suggest that the basal, rather than inducible, level of ABA has more impact on osmotic stress tolerance in apple rootstocks. Indeed, Kamboj et al. (1999)  found thSnRK expression showed higher abundance in V3 and B9 than other rootstocks. SnRK is a positive regulator of the ABA signaling pathway and its activation induces downstream ABRE-binding protein/ABRE-binding (AREB/ABF) transcription factors that in turn activate ABA-responsive genes [DREB under stress was noticed in B9 and G41. At the same time, MYC2 expression had the lowest transcript levels in M26 compared to the other rootstocks under osmotic stress. Given the known role of MYC2 proteins in abiotic stress tolerance [ERD is also reported to be highly regulated under drought and salinity before the onset of ABA, suggesting it could work independently of ABA [ERD is highly expressed in the rootstocks with high ABA content, e.g., G41, B9 and G935. In fact, SnRK, DREB, ERD and MYC2 showed higher up-regulation in the rootstocks with higher ABA levels and higher WUE, indicating not only the positive roles of these genes in improving apple rootstock tolerance, but also the crucial role of ABA as a potential master regulator of these proteins under stress. With regard to WRKY29, it was down-regulated in all tested apple rootstocks. However, the reduction in WRKY29 gene expression observed in V3, G41, and B9 was greater than M26, G935 and B118. Some WRKY members function as a positive regulator of stomatal conductance [WRKY29 downregulation in B9 and V3 was correlated with lower stomatal opening and more tolerance to osmotic stress. Indeed, our data showed a strong negative correlation (r =−0.82) between the expression of the WRKY29 gene and WUE. NPR1 was highly up-regulated in V3 and G41. The importance of NPR1 stems from its role in enhancing antioxidant activity, reducing oxidative stress and inducing plant stress tolerance to abiotic stress [+ATPASE is another important protein that plays a vital role in ion and proton transport and its role in improving plant tolerance to salt and drought stresses has been reported [+ATPASE controls membrane proton pump involved in moderating cell turgor pressure and regulating stomatal movement [ATPASE displayed an increase in B118 and G935 only. Overall, the differential expression of some ORGs among the tested rootstocks suggested that other pathways, in addition to ABA, might also be involved in the observed response of these rootstocks to osmotic stress.The transcripts of ORGs in the six apple rootstocks tested in this study showed differential abundance in response to osmotic stress . SnRK exve genes . The higolerance  and ABA olerance , its lowy of ABA ,58,59. Hductance . WRKY29 ductance . Therefoc stress ,62,63. Vreported ,64. H+ATN, gs, E and Ci. The changes in the physiological parameters in response to osmotic stress were consistently associated with ABA accumulation and molecular changes known to mitigate and confer osmotic stress tolerance. We found that the genetic background could also be related to the different responses and performance of the tested rootstocks. In view of the current results, we concluded that B9, V3, G41 and G935 are more tolerant to osmotic stress than M26 and B118, which was demonstrated by their abilities to maintain up-regulation in some ORGs such as SnRK, DREB, ERD, MYC2 and NPR1 that higher water content, membrane integrity and WUE under stress conditions. Additionally, the tolerant rootstocks showed have previously been reported to induce abiotic stress tolerance when overexpressed in transgenic plants. However, it should also be taken into account that rootstocks can modulate the size, yield, hormone content and even gene expression of the scion [Apple rootstocks showed a decrease in RWC and an increase in EL when subjected to osmotic stress. Osmotic stress also resulted in the reduction of photosynthesis-related parameters Phe scion , which che scion . Therefo−2 s−1 light intensity, 24 ± 2 °C day and night temperature and diurnal cycle 16 h light/8 h darkness. Two months after bud break, apple rootstocks were characterized under osmotic stress induced by 30% of polyethylene glycol 6000 (PEG) , while water was used as a control. All leaf samples were collected three days after the PEG treatment for molecular, biochemical and physiological analyses, immediately frozen in liquid nitrogen, then stored in −80 °C until further use. The third and the fourth leaves from the apical meristem were used to measure photosynthesis related parameters. The fourth leaf was used for ABA quantification and molecular analyses. The fifth and the sixth leaves were used to measure electrolyte leakage and relative water content.Six apple rootstocks, including M26, Vineland 3 (V3), Geneva 935 (G935), Geneva 41 (G41), Budagovsky 9 (B9) and Budagovsky 118 (B118), were evaluated under osmotic stress. One-year-old dormant plants were grown until bud break in the greenhouse of the University of Guelph, Guelph, Ontario, Canada. The greenhouse growth conditions were 300 μmol mElectrolyte leakage (EL) was determined following an earlier method by Bajji et al. (2002) . Total oN), stomatal conductance (gs), transpiration rate (E) and inner CO2 (Ci) were measured three days after PEG treatment using LICOR photosynthesis system LI-6400 XT . In addition, water use efficiency (WUE) was calculated by dividing the photosynthesis rate by the transpiration rate (WUE = PN /E). Measurements were conducted between 10:00 am and 12:00 pm (GMT) in three plants for each treatment. Parameters were measured at a light intensity of 1000 µmol m−2 s−1 provided by an external light source, 400 µmol CO2 mol−1 and leaf temperature of 25 °C.Net photosynthesis rate  and 4% acetic acid  in Milli-Q water. The samples were then sonicated on ice for 30 min and centrifuged for 2 min at 13,000 rpm. After that, the supernatant was removed to a new tube and diluted 5× in 10 mM ammonium acetate , pH 9 adjusted with ammonium hydroxide . Then 500 µL of samples were filtered-centrifuged using 0.45 µm Millipore centrifuge filter at 13,000 rpm for 1 min. Finally, the supernatant was used for quantification using ultra-performance liquid chromatography (UPLC)—mass spectrometry. As described by Erland et al., 2017 , 3 µL ofEF1A) and was calculated relative to M26 under control (unstressed) condition. Relative normalized expression was calculated using Bio-Rad CFX Manager 3.1 software  and according to the 2−∆∆CT method [Tissue samples were ground to a fine powder in the presence of liquid nitrogen, after which total RNA was extracted using CTAB as previously described by Gasic et al. (2004) . cDNA syT method .p < 0.05, and the significant differences were compared by Tukey-Kramer multiple means comparison. The log model was used to transfer the data to follow normal distribution when required. Pearson correlation test was performed using GraphPad Prism v9 to correlate the physiological, molecular changes and ABA content in apple leaves.The experiment was arranged as a two-factorial in a randomized complete block design with three blocks and three plants in each block. The results were confirmed by repeating the experiment twice. Mixed models including rootstock and osmotic stress as fixed factors and block as a random factor were performed to distinguish treatment effects for all tested parameters. Statistical analyses were performed using SAS Institute Inc., Cary, NC, USA. Means were subjected to analysis of variance (ANOVA) at


Vascular endothelial cells (ECs) are increasingly recognized as active players in intercellular crosstalk more than passive linings of a conduit for nutrition delivery. Yet, their functional roles and heterogeneity in skin remain uncharacterized. We have used single-cell RNA sequencing (scRNA-seq) as a profiling strategy to investigate the tissue-specific features and intra-tissue heterogeneity in dermal ECs at single-cell level.Methods: Skin tissues collected from 10 donors were subjected to scRNA-seq. Human dermal EC atlas of over 23,000 single-cell transcriptomes was obtained and further analyzed. Arteriovenous markers discovered in scRNA-seq were validated in human skin samples via immunofluorescence. To illustrate tissue-specific characteristics of dermal ECs, ECs from other human tissues were extracted from previously reported data and compared with our transcriptomic data.Results: In comparison with ECs from other human tissues, dermal ECs possess unique characteristics in metabolism, cytokine signaling, chemotaxis, and cell adhesions. Within dermal ECs, 5 major subtypes were identified, which varied in molecular signatures and biological activities. Metabolic transcriptome analysis revealed a preference for oxidative phosphorylation in arteriole ECs when compared to capillary and venule ECs. Capillary ECs abundantly expressed HLA-II molecules, suggesting its immune-surveillance role. Post-capillary venule ECs, with high levels of adhesion molecules, were equipped with the capacity in immune cell arrest, adhesion, and infiltration.Conclusion: Our study provides a comprehensive characterization of EC features and heterogeneity in human dermis and sets the stage for future research in identifying disease-specific alterations of dermal ECs in various dermatoses. Vascular endothelial cells (ECs), the interior lining of blood vessels, have been recognized as more than inert bystanders but also active participants in intercellular crosstalk. Through regulating metabolic pathways, responding to various cytokines, and recruiting immune cells, ECs have largely participated in multiple diseases such as diabetes, atherosclerosis and cancer Blood vessels in skin, the largest and outermost organ confronting various external stimuli, stand at the front line of immune responses. As the gatekeeper locking out circulating immune cells and pro-inflammatory cytokines, cutaneous ECs may alternatively initiate and amplify various inflammatory dermatoses. Recently, we have demonstrated that dermal ECs actively participate in psoriasis development via regulating neutrophil infiltration The cutaneous vasculature is elaborately organized throughout the dermis. Small arteries form the deep plexus, from which individual vessels rise to the border between subcutaneous adipose tissue (SAT) and dermis. The deep plexus rises to ascending arterioles to generate the superficial plexus, forming capillary loops that enter the papillary dermis. These capillaries were drained by venules, which form the intermediate plexuses. These vessels are varied in diameter, wall width and basement membrane structure Here, we investigated the tissue-specific traits and internal heterogeneity of human dermal ECs by single-cell RNA sequencing (scRNA-seq). Dermal ECs were equipped with unique features in transcriptional modulation and gene expressions, when compared to ECs from other tissues. Heterogeneity among dermal EC subtypes, including diverse metabolic preference and immune functions, was discovered. Our study reveals a comprehensive single-cell atlas of human dermal ECs and supports future research as a baseline to identify alterations of dermal EC subpopulations in various skin diseases.+ CD45- cells were isolated from digested skin tissues by magnetic-activated cell sorting (MACS) and fluorescence-activated cell sorting (FACS) to enrich endothelial cells, including both vascular and lymphatic endothelial cells (LECs) ACTA2, RGS5), fibroblasts (COL1A1), pericytes , red blood cells , and immune cells (PTPRC)  molecules, although cluster P selectively expressed SELE and HSPA1A. The expression of shared DEGs by ECs from more than one subtype indicated that these subtypes were phenotypically related to each other. Because the primary goal of this study was to illustrate the features of dermal ECs, LECs were only briefly characterized  (Supplementary File 1). Heatmap analysis of the top-10-ranking DEGs revealed distinct signatures of dermal EC subtypes and LECs , whereas other EC marker genes  were conserved across two or more tissues/organs. Brain ECs were characterized by high expressions of the members in solute carrier family, whereas ECs in skin and GI tract were distinguished by high levels of immune-related genes such as CD74, HLA-DRA, HLA-DPA1, and ACKR1.Then, we explored the EC marker genes for each tissue/organ (Supplementary File 2). Heatmap of the top-10-ranking marker genes revealed diverse signatures of ECs from different tissues/organs, except for the cervix and uterus, which expressed overlapping marker genes Figure B. Of notATP5F1E, SELENOW, CLU and TXNIP, which are related to mitochondria and redox signaling EGFL7, NOP53, and S100A6, modulating angiogenesis and cell proliferation CAVIN1, a key component of caveolae, was highly expressed in ECs from both dermis and SAT, indicating a relatively active process in endothelial vesicular trafficking and signal transduction in skin tissue Because the primary goal of this study was to focus on the skin tissue, we further investigated the tissue-specific features of ECs from dermis Figure C. Genes EC metabolism is closely correlated to endothelial functions. To explore the metabolic heterogeneity across ECs from different tissues/organs, kyoto encyclopedia of genes and genomes (KEGG) analysis was performed Figure A. OxidatACAA2, ECI2, ACADVL, etc. ECs from both dermis and brain held high expressions of purine metabolism-related genes, but the specific pathways varied. Dermal ECs enriched genes within the 3',5'-cyclic AMP degradation and GMP metabolism such as PDE4A, PDE7B, GMPS, and PFAS, whereas brain ECs enriched IMP biogenesis molecules such as ADSL, ATIC, and AMPD2. As for glucose metabolism, ECs from skin and brain expressed higher enzymatic glucose genes than ECs from other tissues/organs. UQCRH, ATP5F1D, and NDUFV3, key genes in oxidative phosphorylation, were highly expressed in ECs from dermis and SAT. However, glycolytic genes such as GPI, PKFL, and ALDOC were more enriched in ECs from the brain, which relies on glucose as the sole fuel The three major substrates for energy and biomass production in ECs are mainly confined to fatty acids, amino acids, and glucose. We therefore compared the inter-tissue expressions of metabolic genes within the fatty acid β-oxidation, purine, oxidative phosphorylation, and glycolysis pathways Figure B. ConsisWe further questioned whether this metabolic preference towards oxidative phosphorylation was consistent across subtypes in skin ECs. A heatmap of representative metabolic genes revealed a gradual switch from oxidative phosphorylation to glycolysis in dermal EC subtypes along the blood flow Figure C. GSEA rIL2RG and TIMP1 was highly expressed in liver ECs, whereas IFNGR1 was highly expressed in SAT ECs. IL6ST and OSMR were enriched in ECs from uterus, cervix, trachea and GI tract, while IL3RA was highly expressed in ECs from trachea, dermis, and SAT. Of note, ECs from both skin and GI tract shared high expressions of HLA-II molecules such as HLA-DMA and HLA-DRB5  and ICAM1, mediating cellular adhesion between ECs and circulatory cells, were enriched in cluster P. Consistently, cluster P in dermal ECs scored the highest when measuring the adhesion score of dermal EC populations, based on the expression of genes related to neutrophil adhesion to ECs , and SELP (CD62P) in cluster P, suggesting a susceptible adhesion site in post-capillary venules. In addition, we discovered that cluster C2 (capillary ECs) expresses high levels of HLA-II molecules, which are sufficient to induce CD4+ T cell proliferation and are involved in expansion of regulatory T cells or T helper 17 cells ECs are the essential element throughout immune responses, from presenting chemoattractants on the luminal side of vessels, promoting the rolling, firm arrest, adhesion and crawling of various immune cells, to facilitating immune cell activation through direct contact We have to admit some limitations exist. Skin samples used for scRNA-seq in our study were collected from limbs, trunk, and foreskin. We acknowledge that ECs from different locations exhibit several expressional divergences, yet the magnitude of which is limited, as only 3 locations were included  according to the manufacturer's instructions. After washed with washing buffer, the enriched CD31+ single cell suspension was stained with mouse anti-human CD31 antibody conjugated with FITC  and mouse anti-human CD45 antibody conjugated with APC (Biolegend) for 25 min (4 °C), and 7-AAD for 5 min (4 °C) before FACS using MoFlo XDP cell sorter . Single cells were gated with the FSC-Height versus SSC-Log Height plot, and dead cells were excluded based on 7-AAD dead cell stain. Live single CD31+CD45- cells, recognized as endothelial cells, were sorted into the RPMI-1640 medium (Hyclone). Flow cytometry data were analyzed using FlowJo software .Immediately after surgery, human skin tissues were transferred into RPMI-1640 medium  on ice. After removing SAT, skin tissues were cut into small pieces using fine scalpels and transferred into RPMI-1640 medium containing 2.5 mg/mL Dispase II  overnight (4 °C) to separate the epidermis from the dermis. Once separated, the dermis was cut into homogenate and digested for 40 min in a 38 °C water-bath (265 r/min) with RPMI-1640 medium containing 1 mg/mL collagenase type 4 , 0.2 mg/mL hyaluronidase , 0.2 mg/mL DNase I (Sigma-Aldrich), and 10 mM HEPES (Gibco). The digestion was terminated by diluting the cell suspension with 10 mL pre-cooled washing buffer (4 °C). Single cell suspension was proceeded to select CD31ver 3.0.1).Cell viability was examined by trypan blue staining (Sigma-Aldrich) and controlled with a threshold set >90%. Freshly sorted endothelial cells were immediately processed for library preparation and sequencing by Genergy Bio-technology (Shanghai) Co. Ltd. according to 10X Genomics guidelines. Each sample was sequenced, with, on average, a cell number of 11937 in each batch , a sequencing depth of 22,537 reads per cell , sequencing saturation rate of 60.8% , and 1,373 median genes per cell . Demultiplexing, read alignment and quality control were performed at Genergy Bio-technology (Shanghai) Co. Ltd. using the 10X Cell Ranger package (ver 3.6.3). Data from the 4 batches were integrated via Reciprocal Principal Correlation Analysis using the Seurat package (ver 3.1.2) quickPerCellQC function (nmads = 1.5) in the Scater package (ver 1.14.6) SeuratWrappers (ver 0.1.0). Clustering among single cells was achieved using the FindNeighbors (dims = 1:10) and the FindClusters (resolution = 0.4) functions in the Seurat package. 69 contaminating cells expressing markers of smooth muscle cells , fibroblasts (COL1A1), pericytes , red blood cells , and immune cells (PTPRC) were discarded before further analysis. Data was normalized and 2,000 variable genes were detected. Variabilities of the number of counts, features and percentage of mitochondrial and ribosomal genes were regressed out using the ScaleData function. To compare the distribution and expressional differences across cells from limbs (batch 1), trunk (batch 2), and foreskin (batch 3 and 4), we randomly subsampled our data to equalize the cell numbers of ECs from different anatomical locations. DEGs of ECs from different locations were identified using the DEsingle package (ver 1.6.0) with a cutoff Benjamini-Hochberg adjusted p value of 0.05, a normalized average expression of greater than 0.5, and a normalized fold change of greater than 2. These DEGs were uploaded for GO analysis using Metascape (http://metascape.org).Gene expression matrixes of 4 samples were further processed in R , cervix, dermis, GI tract , heart, liver, thyroid, trachea, uterus  in the Seurat package was applied to identify DEGs of dermal endothelial cells from 7 clusters or of ECs from 10 tissues/organs. In dermal endothelial cells, 193, 89, 57, 114, 67, 255, and 25 DEGs were found in cluster A, C1, C2, P, V, L1, and L2, respectively (Supplementary File 1). In ECs from 10 different tissues/organs, 70, 74, 242, 15, 29, 62, 267, 38, 140, and 113 DEGs were identified in the brain, cervix, dermis, GI tract, heart, liver, SAT, thyroid, trachea, and uterus, respectively (Supplementary File 2). These DEGs were selected for GO or KEGG analysis using Metascape (http://metascape.org). Gene set enrichment analysis was achieved using GSEA software . Pseudotime analysis was carried out using the Monocle3 package (ver 0.2.0) plot_cells function. To perform transcription factor network inference, metadata containing ECs from 10 different tissues was subsampled by randomly selecting 235 cells from each tissue and analyzed using the SCENIC package (ver 1.1.2-2) and the AUCell package (ver 1.8.0) AddModuleScore function in the Seurat package.TheVlnPlot, FeaturePlot, DoHeatmap functions in the Seurat package or the Pheatmap package , respectively. The ggplot2  and the ggsci  packages were used to draw and edit UMAP plots, dot plots, stacked bar plots. A circular heatmap showing the top-10-ranking DEGs of ECs from different tissues/organs was drawn using the circlize package (ver 0.4.9) To visualize expressions, violin plots, feature plots and heatmaps were generated by the ver 1.1.2.0, Carl Zeiss Microscopy GmbH).Formalin-fixed paraffin-embedded human skin samples (n = 11) and murine femoral vessel tissues (n = 3) were sectioned in 4 μm. After deparaffinization and dehydration, antigen retrieval was performed for the sections in Tris-EDTA buffer at 98 °C for 20 min. The sections were blocked with goat normal serum for 1 h and incubated overnight at 4 °C with primary antibodies. The following primary antibodies were used: anti-CD31 , anti-IGFBP3 , anti-RBP7 , anti-SELE , anti-MT2A , anti-HLA-DQ , anti-HLA-DR , anti-ICAM1 , anti-SELP , and anti-NR2F2 . After washing three times with PBST, these sections were incubated in dark for 1 h at room temperature with secondary antibodies including goat anti-mouse IgG cy3 , goat anti-rabbit IgG Alexa Fluor 488, goat anti-rat IgG Cy5 . Images were captured with a confocal microscope  using the same exposure parameters. Negative controls that were stained with secondary antibodies were included in all experiments. Images were analyzed with ZEN software .To assess statistical significance for the DEGs in 5 dermal EC subtypes and ECs derived from 10 different tissues/organs, we used Wilcoxon Rank Sum test in R. To analyze significance for adhesion score and antigen-presenting score among 5 dermal EC subtypes, we used One-way ANOVA with post hoc TukeySupplementary figures and tables.Click here for additional data file.Supplementary File 1.Click here for additional data file.Supplementary File 2.Click here for additional data file.Supplementary File 3.Click here for additional data file.