RhIII-Catalyzed Direct Heteroarylation of Unactivated C(sp3)-H with N-Heteroaryl Boronates.

Disclosed herein is a rhodium(III)-catalyzed direct heteroarylation reaction between unactivated aliphatic C(sp3)-H bonds in 2-alkylpyridines and heteroaryl organoboron reagents. This catalytic protocol is compatible with various heterocyclic boronates containing ortho- and meta-pyridine, pyrazoles, furan, and quinoline with strong coordination capability. The achievement of this methodology provides an efficient route to build new C(sp3)-heteroaryl bonds.

An updated advancement of bifunctional IL-27 in inflammatory autoimmune diseases.

Interleukin-27 (IL-27) is a member of the IL-12 family. The gene encoding IL-27 is located at chromosome 16p11. IL-27 is considered as a heterodimeric cytokine, which consists of Epstein-Barr virus (EBV)-induced gene 3 (Ebi3) and IL-27p28. Based on the function of IL-27, it binds to receptor IL-27rα or gp130 and then regulates downstream cascade. To date, findings show that the expression of IL-27 is abnormal in different inflammatory autoimmune diseases (including systemic lupus erythematosus, rheumatoid arthritis, Sjogren syndrome, Behcet's disease, inflammatory bowel disease, multiple sclerosis, systemic sclerosis, type 1 diabetes, Vogt-Koyanagi-Harada, and ankylosing spondylitis). Moreover, in vivo and in vitro studies demonstrated that IL-27 is significantly in3volved in the development of these diseases by regulating innate and adaptive immune responses, playing either an anti-inflammatory or a pro-inflammatory role. In this review, we comprehensively summarized information about IL-27 and autoimmunity based on available evidence. It is hoped that targeting IL-27 will hold great promise in the treatment of inflammatory autoimmune disorders in the future.

Unraveling Key m6A Modification Regulators Signatures in Postmenopausal Osteoporosis through Bioinformatics and Experimental Verification.

OBJECTIVE: Bone marrow mesenchymal stem cells (BMSCs) show significant potential for osteogenic differentiation. However, the underlying mechanisms of osteogenic capability in osteoporosis-derived BMSCs (OP-BMSCs) remain unclear. This study aims to explore the impact of YTHDF3 (YTH N6-methyladenosine RNA binding protein 3) on the osteogenic traits of OP-BMSCs and identify potential therapeutic targets to boost their bone formation ability. METHODS: We examined microarray datasets (GSE35956 and GSE35958) from the Gene Expression Omnibus (GEO) to identify potential m6A regulators in osteoporosis (OP). Employing differential, protein interaction, and machine learning analyses, we pinpointed critical hub genes linked to OP. We further probed the relationship between these genes and OP using single-cell analysis, immune infiltration assessment, and Mendelian randomization. Our in vivo and in vitro experiments validated the expression and functionality of the key hub gene. RESULTS: Differential analysis revealed seven key hub genes related to OP, with YTHDF3 as a central player, supported by protein interaction analysis and machine learning methodologies. Subsequent single-cell, immune infiltration, and Mendelian randomization studies consistently validated YTHDF3's significant link to osteoporosis. YTHDF3 levels are significantly reduced in femoral head tissue from postmenopausal osteoporosis (PMOP) patients and femoral bone tissue from PMOP mice. Additionally, silencing YTHDF3 in OP-BMSCs substantially impedes their proliferation and differentiation. CONCLUSION: YTHDF3 may be implicated in the pathogenesis of OP by regulating the proliferation and osteogenic differentiation of OP-BMSCs.

[Analysis of dissatisfaction and related factors following total hip arthroplasty in patients with Crowe type â ¢-â £ developmental dysplasia of the hip].

OBJECTIVE: To investigate the satisfaction of patients with Crowe Ⅲ-Ⅳ developmental dysplasia of the hip(DDH) after total hip arthroplasty and the related factors. METHODS: A retrospective study included 169 patients with Crowe type Ⅲ-Ⅳ DDH who underwent total hip arthroplasty between March 2013 and March 2018. Patients were surveyed through WeChat, covering overall satisfaction with the operation, satisfaction with ten daily functions, and the top five questions perceived to have a great impact on daily life. Preoperative and postoperative hip function was evaluated by Harris score. RESULTS: One hundred and forty-five questionnaires were received, with a follow-up period ranging from 1 to 5 years with an average of (3.23±1.22) years. Among these patients, 118 patients were satisfied with the surgical outcomes, while 27 patients were dissatisfied, with the overall satisfaction rate of 81.38%(118/145). The top five problems affecting patient life were postoperative hip pain, limb length discrepancy, walking, stair climbing, and squatting. There were no statistical differences in age, sex, body mass index, preoperative Harris scores (P>0.05). However, the dissatisfied group had lower postoperative Harris scores. Postoperative hip pain and limb length discrepancy were identified as direct factors contributing to postoperative surgical dissatisfaction. CONCLUSION: Total hip arthroplasty for patients with Crowe type Ⅲ-Ⅳ DDH is challenging. Postoperative hip pain (mild or severe) and limb length discrepancy (>2 cm) are independent risk factors for postoperative dissatisfaction.

[Establish a Graded Method to Avoid HLA Class I Antibodies Corresponding Antigen and Combining HLAMatchmaker Application in Improving the CCI Value after Platelet Transfusion for Patients with IPTR].

OBJECTIVE: To establish a graded method to avoid mean fluorescence intensity (MFI) threshold of HLA Class I antibodies corresponding antigen, and the HLAMatchmaker program has been used to select the minimum mismatch value of donor-patient epitopes. Evaluate the application value of combining both methods in selecting HLA compatible platelets (PTL) for patients with immune platelet transfusion failure (IPTR) in improving platelet the corrected count increment (CCI). METHODS: A total 7 807 PLT cross-matching compatible were performed by the solid-phase red cell adherence (SPRCA) method for 51 IPTR patients. The Luminex single antigen flow cytometry was used to detect HLA Class I antibodies in patients, and detected the MFI value for different specificity antigens of HLA Class I antibodies, was graded into strong positive group (MFI>4 000, level 1), medium positive group (1 000< MFI≤4 000, 2), weak positive group (500< MFI≤1 000, 3), and one negative control group (MFI≤500). The results of 7 807 SPRCA their negative/positive reaction wells were enrolled and statistically analyzed in different grades and the four groups, the statistical differences between the four groups were compared. Multiple applications for the select HLA Class I compatible donor events were made for patients in two cases, and HLAMatchmaker program was used to calculate the number of HLA Class I epitopes mismatches between the donors and patients. The donor with the minimum number of epitopes mismatches was selected, while avoiding the corresponding antigens of HLA Class I antibodies in levels 1 and 2, the provision of HLA compatible platelets for IPTR. After the transfusions, the CCI value of the platelet transfusion efficacy evaluation index was calculated, and the clinical evaluation of the transfusion effect was obtained through statistical analysis. RESULTS: There were statistically significant differences in the positive results of SPRCA immunoassay among the strong positive group, medium positive group, and weak positive group of 51 IPTR patients with different specific of HLA -I class antibodies and corresponding antigens(all P <0.001). The positive results showed a range from high to low, with strong positive group>medium positive group>weak positive group. There were a statistical difference among between the strongly positive or moderately positive groups and the negative control group(P <0.001). There was no statistical difference between the weakly positive group and the negative control group(P >0.05). The strong positive group was set as the corresponding specific HLA Class I site corresponding antigen grade 1 avoidance threshold, the medium positive group as the grade 2 avoidance thresholds, and the weak positive group as the grade 3 avoidance threshold. In the case of donor platelet shortage, it is not necessary to avoid the weak positive group. Avoiding the strategy of donor antigens and HLAMatchmaker program scores ≤7 corresponding to HLA Class I antibodies of levels 1 and 2, with CCI values>4.5×109/L within 24 hours, can obtain effective clinical platelet transfusion conclusions. CONCLUSION: When selecting HLA Class I compatible donors for IPTR patients, the grading avoids HLA Class I antibodies corresponding to donor antigens, and the donor selection strategy with the minimum scores of HLAMatchmaker program is comprehensively selected. The negative result confirmed by platelet cross-matching experiments has certain practical application value for improving platelet count in IPTR patients.

METTL3-mediated m6A modification of SOX4 regulates osteoblast proliferation and differentiation via YTHDF3 recognition.

N6-methyladenosine (m6A), the most prevalent internal modification in mRNA, is related to the pathogenesis of osteoporosis (OP). Although methyltransferase Like-3 (METTL3), an m6A transferase, has been shown to mitigate OP progression, the mechanisms of METTL3-mediated m6A modification in osteoblast function remain unclear. Here, fluid shear stress (FSS) induced osteoblast proliferation and differentiation, resulting in elevated levels of METTL3 expression and m6A modification. Through Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq) and Transcriptomic RNA Sequencing (RNA-seq), SRY (Sex Determining Region Y)-box 4 (SOX4) was screened as a target of METTL3, whose m6A-modified coding sequence (CDS) regions exhibited binding affinity towards METTL3. Further functional experiments demonstrated that knockdown of METTL3 and SOX4 hampered osteogenesis, and METTL3 knockdown compromised SOX4 mRNA stability. Via RNA immunoprecipitation (RIP) assays, we further confirmed the direct interaction between METTL3 and SOX4. YTH N6-Methyladenosine RNA Binding Protein 3 (YTHDF3) was identified as the m6A reader responsible for modulating SOX4 mRNA and protein levels by affecting its degradation. Furthermore, in vivo experiments demonstrated that bone loss in an ovariectomized (OVX) mouse model was reversed through the overexpression of SOX4 mediated by adeno-associated virus serotype 2 (AAV2). In conclusion, our research demonstrates that METTL3-mediated m6A modification of SOX4 plays a crucial role in regulating osteoblast proliferation and differentiation through its recognition by YTHDF3. Our research confirms METTL3-m6A-SOX4-YTHDF3 as an essential axis and potential mechanism in OP.

Discovery of the novel HLA-A*11:452N allele by next-generation sequencing in a Chinese individual.

HLA-A*11:452N differs from A*11:01:01:01 by a single nucleotide exchange in exon 1.

Neuropeptide Y, a potential marker for lupus, promotes lupus development.

OBJECTIVE: Relationship between neuropeptide Y (NPY) serum levels, NPY genetic mutation with systemic lupus erythematosus (SLE) pathogenesis is yet to be clarified, and role of NPY in development of SLE needs elucidation. METHOD: This study included 460 SLE patients, 472 non-SLE cases, 500 healthy volunteers. Serum NPY, matrix metalloproteinase-1 (MMP-1) and MMP-8 levels were tested by ELISA. Genotyping 7 NPY single nucleotides polymorphisms (SNPs) (rs5573, rs5574, rs16129, rs16138, rs16140, rs16147, rs16478) was obtained by Kompetitive Allele-Specific PCR (KASP) method. Pristane-induced lupus mice were treated with NPY-Y1 receptor antagonist, and histological analysis, serological changes of the mice were evaluated. RESULTS: NPY serum concentrations were significantly increased in SLE patients when compared to that in healthy volunteers, non-SLE cases. Rs5573 G allele, rs16129 T allele, rs16147 G allele frequencies were significantly different between SLE cases and healthy controls. Rs5574 TT + TC genotypes were related to levels of IgG, C3, C4 and erythrocyte sedimentation rate, and rs16138 GG + GC genotypes correlated with SLE cases with anti-double-stranded deoxyribonucleic acid antibody (anti-dsDNA) (+). Serum MMP-1, MMP-8 concentrations were higher in SLE patients, and NPY levels were significantly related to MMP-1, MMP-8 levels. After treatment of lupus mice with NPY-Y1 receptor antagonist, damage of liver, spleen and kidney was alleviated, production of autoantibodies (anti-nuclear antibody (ANA), total IgG, anti-dsDNA) and MMP-1, MMP-8 was down-regulated, and differentiation of CD3+, CD8+ T cells, B cells, monocytes, macrophages, T helper 1 (Th1), Th2, Th17 cells was reversed. CONCLUSION: NPY may be a biomarker for lupus, which may promote occurrence and development of lupus.

Systemic lupus erythematosus with high disease activity identification based on machine learning.

OBJECTIVE: Clinical evaluation of systemic lupus erythematosus (SLE) disease activity is limited and inconsistent, and high disease activity significantly, seriously impacts on SLE patients. This study aims to generate a machine learning model to identify SLE patients with high disease activity. METHOD: A total of 1014 SLE patients with low disease activity and 453 SLE patients with high disease activity were included. A total of 94 clinical, laboratory data and 17 meteorological indicators were collected. After data preprocessing, we use mutual information and multisurf to evaluate and select the importance of features. The selected features are used for machine learning modeling. Performance of the model is evaluated and verified by a series of binary classification indicators. RESULTS: We screened out hematuria, proteinuria, pyuria, low complement, precipitation, sunlight and other features for model construction by integrated feature selection. After hyperparameter optimization, the LGB has the best performance (ROC: AUC = 0.930; PRC: AUC = 0.911, APS = 0.913; balance accuracy: 0.856), and the worst is the naive bayes (ROC: AUC = 0.849; PRC: AUC = 0.719, APS = 0.714; balance accuracy: 0.705). Finally, the selection of features has good consistency in the composite feature importance bar plot. CONCLUSION: We identify SLE patients with high disease activity by a simple machine learning pipeline, especially the LGB model based on the characteristics of proteinuria, hematuria, pyuria and other feathers screened out by collective feature selection.

Genomic sequence of the novel HLA-A*26:206:02N allele, identified in a patient with hepatitis B infection.

HLA-A*26:206:02N differs from A*26:01:01:01 by a single nucleotide exchange in exon 3.

Association between endothelin-1 and systemic lupus erythematosus: insights from a case-control study.

Systemic lupus erythematosus (SLE) is a chronic rheumatic disorder. Endothelin-1, a vasoconstrictor, belongs to the endothelin family and is associated with vascular-related damages. To date, association between ET-1 and pathogenesis of SLE remains unclear. This case-control study was carried out by 314 SLE, 252 non-SLE diseases patients and 500 healthy controls. Serum ET-1, CCN3, IL-28B levels were detected by ELISA, and ET-1 gene polymorphisms (rs5369, rs5370, rs1476046, rs2070699, rs2071942, rs2071943, rs3087459, rs4145451, rs6458155, rs9369217) were genotyped with Kompetitive Allele-Specific PCR. SLE patients had high levels of ET-1, which were correlated with some clinical, laboratory features. Serum CCN3, IL-28B levels were higher in SLE patients, and ET-1 levels were positively correlated with the two cytokines. Rs5370, rs1476046, rs2070699, rs2071942, rs2071943, rs3087459, rs6458155 and rs2070699 were associated with SLE risk. Rs2070699 (T, TT) was related to SLE patients with alopecia. Rs5370 (T, TT, TG), rs1476046 (G,GA), rs2071942 (G,GA) and rs2071943 (G,GA) were associated with SLE patients with pericarditis, pyuria and fever manifestation, respectively. Rs3087459 (CC) and rs9369217 (TC) were related to SLE patients with positive anti-SSB antibody. Rs5369 (AA) was associated with IgG and CRP levels in SLE patients. In conclusion, elevated serum ET-1 in SLE patients may be a potential disease marker, and its gene polymorphisms were related to SLE susceptibility.

Exploring machine learning methods for predicting systemic lupus erythematosus with herpes.

OBJECTIVES: To investigate whether machine learning, which is widely used in disease prediction and diagnosis based on demographic data and serological markers, can predict herpes occurrence in patients with systemic lupus erythematosus (SLE). METHODS: A total of 286 SLE patients were included in this study, including 200 SLE patients without herpes and 86 SLE patients with herpes. SLE patients were randomly divided into a training group and a test group, and 18 demographic characteristics and serological indicators were compared between the two groups. RESULTS: We selected basophil, monocyte, white blood cell, age, immunoglobulin E, SLE Disease Activity Index, complement 4, neutrophil, and immunoglobulin G as the basic features of modeling. A random forest model had the best performance, but logistic and decision tree analyses had better clinical decision-making benefits. Random forest had a good consistency between feature importance judgment and feature selection. The 10-fold cross-validation showed the optimization of five model parameters. CONCLUSION: The random forest model may be an excellently performing model, which may help clinicians to identify SLE patients whose disease is complicated by herpes early.

RhIII-promoted directed C-H N-heteroarylation of 2-pyridones.

A catalytic protocol for the Cp*RhIII-promoted C6-selective N-heteroarylation of 2-pyridones with N-heterocyclic boronates has been successfully developed utilizing a removable pyridine auxiliary. This system features high efficiency with mild conditions and also tolerates ortho- and meta-substituted pyridines, pyrazoles, pyrimidine, non-substituted quinolines, thiophene and furan well. The easy synthetic approach could potentially be applied to construct heterocyclic drug molecules bearing 2-pyridone-heteroaryl motifs.

Lupus nephritis or not? A simple and clinically friendly machine learning pipeline to help diagnosis of lupus nephritis.

OBJECTIVE: Diagnosis of lupus nephritis (LN) is a complex process, which usually requires renal biopsy. We aim to establish a machine learning pipeline to help diagnosis of LN. METHODS: A cohort of 681 systemic lupus erythematosus (SLE) patients without LN and 786 SLE patients with LN was established, and a total of 95 clinical, laboratory data and 17 meteorological indicators were collected. After tenfold cross-validation, the patients were divided into training set and test set. The features selected by collective feature selection method of mutual information (MI) and multisurf were used to construct the models of logistic regression, decision tree, random forest, naive Bayes, support vector machine (SVM), light gradient boosting (LGB), extreme gradient boosting (XGB), and artificial neural network (ANN), the models were compared and verified in post-analysis. RESULTS: Collective feature selection method screens out antistreptolysin (ASO), retinol binding protein (RBP), lupus anticoagulant 1 (LA1), LA2, proteinuria and other features, and the hyperparameter optimized XGB (ROC: AUC = 0.995; PRC: AUC = 1.000, APS = 1.000; balance accuracy: 0.990) has the best performance, followed by LGB (ROC: AUC = 0.992; PRC: AUC = 0.997, APS = 0.977; balance accuracy: 0.957). The worst performance is naive Bayes model (ROC: AUC = 0.799; PRC: AUC = 0.822, APS = 0.823; balance accuracy: 0.693). In the composite feature importance bar plots, ASO, RF, Up/Ucr, and other features play important roles in LN. CONCLUSION: We developed and validated a new and simple machine learning pathway for diagnosis of LN, especially the XGB model based on ASO, LA1, LA2, proteinuria, and other features screened out by collective feature selection.

Effects of tillage patterns and stover mulching on N2O production, nitrogen cycling genes and microbial dynamics in black soil.

Stover-covered no-tillage (NT) is of great significance to the rational utilization of stover resources and improvement of cultivated land quality, and also has a profound impact on ensuring groundwater, food and ecosystem security. However, the effects of tillage patterns and stover mulching on soil nitrogen turnover remain elusive. Based on the long-term conservation tillage field experiment in the mollisol area of Northeast China since 2007, the shotgun metagenomic sequencing of soils and microcosm incubation were combined with physical and chemical analyses, alkyne inhibition analysis to elucidate the regulatory mechanisms of NT and stover mulching on the farmland soil nitrogen emissions and microbial nitrogen cycling genes. Compared with conventional tillage (CT), NT stover mulching significantly reduced the emission of N2O instead of CO2, especially when 33% mulching was adopted, and correspondingly the nitrate nitrogen of NT33 was higher than that of other mulching amounts. The stover mulching was associated with higher total nitrogen, soil organic carbon and pH. The abundance of AOB (ammonia-oxidizing bacteria)-amoA (ammonia monooxygenase subunit A) was substantially increased by stover mulching, while the abundance of denitrification genes was reduced in most cases. Under alkyne inhibition, the tillage mode, treatment time, gas condition and interactions between them noticeably influenced the N2O emission and nitrogen transformation. In CT, NT0 (no mulching) and NT100 (full mulching), the relative contribution of AOB to N2O production was markedly higher than that of ammonia oxidizing archaea. Different tillage modes were associated with distinct microbial community composition, albeit NT100 was closer to CT than to NT0. Compared with CT, the co-occurrence network of microbial communities was more complex in NT0 and NT100. Our findings suggest that maintaining a low-quantity stover mulching could regulate soil nitrogen turnover toward proficiently enhancing soil health and regenerative agriculture, and coping with global climate change.

A "Pre-Division Metal Clusters" Strategy to Mediate Efficient Dual-Active Sites ORR Catalyst for Ultralong Rechargeable Zn-Air Battery.

To conquer the bottleneck of sluggish kinetics in cathodic oxygen reduction reaction (ORR) of metal-air batteries, catalysts with dual-active centers have stood out. Here, a "pre-division metal clusters" strategy is firstly conceived to fabricate a N,S-dual doped honeycomb-like carbon matrix inlaid with CoN4 sites and wrapped Co2 P nanoclusters as dual-active centers (Co2 P/CoN4 @NSC-500). A crystalline {CoII 2 } coordination cluster divided by periphery second organic layers is well-designed to realize delocalized dispersion before calcination. The optimal Co2 P/CoN4 @NSC-500 executes excellent 4e- ORR activity surpassing the benchmark Pt/C. Theoretical calculation results reveal that the CoN4 sites and Co2 P nanoclusters can synergistically quicken the formation of *OOH on Co sites. The rechargeable Zn-air battery (ZAB) assembled by Co2 P/CoN4 @NSC-500 delivers ultralong cycling stability over 1742 hours (3484 cycles) under 5 mA cm-2 and can light up a 2.4 V LED bulb for ≈264 hours, evidencing the promising practical application potentials in portable devices.

Pt Nanoparticles Confined in a 3D Porous FeNC Matrix as Efficient Catalysts for Rechargeable Li-CO2/O2 Batteries.

The cathodic product Li2CO3, due to its high decomposition potential, has hindered the practical application of rechargeable Li-CO2/O2 batteries. To overcome this bottleneck, a Pt/FeNC cathodic catalyst is fabricated by dispersing Pt nanoparticles (NPs) with a uniform size of 2.4 nm and 8.3 wt % loading amount into a porous microcube FeNC support for high-performance rechargeable Li-CO2/O2 batteries. The FeNC matrix is composed of numerous two-dimensional (2D) carbon nanosheets, which is derived from an Fe-doping zinc metal-organic framework (Zn-MOF). Importantly, using Pt/FeNC as the cathodic catalyst, the Li-CO2/O2 (VCO2/VO2 = 4:1) battery displays the lowest overpotential of 0.54 V and a long-term stability of 142 cycles, which is superior to batteries with FeNC (1.67 V, 47 cycles) and NC (1.87 V, 23 cycles) catalysts. The FeNC matrix and Pt NPs can exert a synergetic effect to decrease the decomposition potential of Li2CO3 and thus enhance the battery performance. In situ Fourier transform infrared (FTIR) spectroscopy further confirms that Li2CO3 can be completely decomposed under a low potential of 3.3 V using the Pt/FeNC catalyst. Impressively, Li2CO3 exhibits a film structure on the surface of the Pt/FeNC catalysts by scanning electron microscopy (SEM), and its size can be limited by the confined space between the carbon sheets in Pt/FeNC, which enlarges the better contacting interface. In addition, density functional theory (DFT) calculations reveal that the Pt and FeNC catalysts show a higher adsorption energy for Li2CO3 and Li2CO4 intermediates compared to the NC catalyst, and the possible discharge pathways are deeply investigated. The synergetic effect between the FeNC support and Pt active sites makes the Li-CO2/O2 battery achieve optimal performance.

Genomic and Metabolite Profiling Reveal a Novel Streptomyces Strain, QHH-9511, from the Qinghai-Tibet Plateau.

The prevalence of superbugs, represented by methicillin-resistant Staphylococcus aureus (MRSA), has become a serious clinical and public safety concern with rising incidence in hospitals. Polyketides with diverse chemical structures harbor many antimicrobial activities, including those of rifampin and rapamycin against MRSA. Streptomyces sp. QHH-9511 was isolated from a niche habitat in the Qinghai-Tibet Plateau and used to produce antibacterial metabolites. Herein, an integrated approach combining genome mining and metabolic analysis were employed to decipher the chemical origin of the antibacterial components with pigmented properties in strain QHH-9511, a novel Streptomyces species from a lichen symbiont on the Qinghai-Tibet Plateau. Genomic phylogeny assembled at the chromosome level revealed its unique evolutionary state. Further genome mining uncovered 36 candidate gene clusters, most of which were uncharacterized. Meanwhile, based on liquid chromatography coupled to diode array detection mass spectrometry, a series of granaticins, BSMs, chromones, phaeochromycins, and related molecules were discovered by using the Global Natural Product Social molecular networking platform. Subsequently, several pigment compounds were isolated and identified by high-resolution mass spectrometry and/or nuclear magnetic resonance, among which the structure-activity relationships of seven aromatic polyketides showed that the fused lactone ring of the C-2 carboxyl group could increase antibacterial activity. Genetic experiments indicated that all seven aromatic polyketides are a series of metabolic shunts produced by a single type II polyketide synthase (PKS) cluster. Comparative genomic analysis of granaticin producers showed that the granaticin gene cluster is widely distributed. This study provides an efficient method to combine genome mining and metabolic profiling techniques to uncover bioactive metabolites derived from specific habitats, while deepening our understanding of aromatic polyketide biosynthesis. IMPORTANCE Undescribed microorganisms from special habitats are being screened for anti-superbug drug molecules. In a project to screen actinomycetes for anti-MRSA activity, we isolated a Streptomyces strain from Qinghai Lake lichens. The phylogeny based on the genome assembled at the chromosome level revealed this strain's unique evolutionary state. The chemical origins of the antibacterial components with pigment properties in strain QHH-9511 were determined using an integrated approach combining genome mining and metabolic analysis. Further genome mining uncovered 36 secondary metabolite gene clusters, the majority of which were previously unknown. A series of aromatic compounds were discovered using molecular network analysis, separation, and extraction. Genetic experiments revealed that all seven aromatic polyketides are a series of metabolic shunts produced by a single cluster of type II PKSs. This study describes a method for identifying novel Streptomyces from specific habitats by combining genome mining with metabolic profiling techniques.