Gene GSEA Research Articles

Integrated bioinformatics analysis and experimental validation reveal the relationship between ALOX5AP and the prognosis and immune microenvironment in glioma

BackgroundTreatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood.MethodsThe differential expression of ALOX5AP was evaluated based on public Databases. Kaplan–Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray.ResultALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma.ConclusionALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma.

Revealing the Molecular Mechanism of Sageretia theezans in the Treatment of Hemorrhoids based on Network Pharmacology.

Sageretia theezans is one of the classic medicines in ancient times, which is commonly used to treat scabies, lacquer sores, acute and chronic pharyngitis, Tonsillitis, Cholecystitis, secondary infection of hemorrhoids, and other symptoms. However, the potential molecular mechanism of Sageretia theezans is still unclear. In this study, we explored the active compounds of Sageretia theezans in the treatment of hemorrhoids (HD), predicted the potential targets of drugs, and verified their functions through network pharmacology and in vivo and in vitro experiments. First, we identified the active compounds and key targets of Sageretia theezans in treating HD through network pharmacology. The key signaling pathways related to the role of Sageretia theezans were analyzed. HUVEC Human umbilical vein endothelial cells were used to study the function of Sageretia theezans and its target in vitro. In addition, we also used the SD rat hemorrhoid model to explore the efficacy of Sageretia theezans in HD in vivo. A total of 159 drug targets were obtained from the TCMSP, ETCM, and PubChem databases. Constructing a drug component target network; differential analysis using sequencing data identified 1046 differentially expressed genes. Intersecting drug targets and differentially expressed genes obtained four intersection targets (GOT1, SLC25A10, SUCLG1, CLEC4E). Perform single gene GSEA functional enrichment analysis on intersection targets, select KEGG and GO of the top 10 for display, and merge the results. In order to investigate the interaction between intersecting genes and differentially expressed genes, we conducted a PPI protein interaction analysis on 1046 differentially expressed genes. Finally, a network of Chinese medicine active molecule intersection genes was proposed, and the genes and their corresponding active molecules (Successful acid, Taraxerone, Taraxerol) were Macromolecular docking, respectively. The results showed that these four genes could be successfully docked with the responsive active molecules and had high binding affinity. In vivo, the low-dose treatment group of Sageretia theezans, the medium-dose treatment group of Sageretia theezans, and the high-dose treatment group of Bromelia can inhibit the proliferation of HUVECs cells. In vitro, the middle dose of Sageretia theezans has the best therapeutic effect on hemorrhoids, and the treatment of Sageretia theezans on hemorrhoids is correlated with the expression of GOT1, SLC25A10, SUCLG1, and CLEC4E. To sum up, Sageretia theezans can alleviate the symptoms of hemorrhoids and is related to the expression of GOT1, SLC25A10, SUCLG1, and CLEC4E.

Multi-omics characterization of macrophage polarization-related features in osteoarthritis based on a machine learning computational framework

BackgroundOA imposes a heavy burden on patients and society in that its mechanism is still unclear, and there is a lack of effective targeted therapy other than surgery. MethodsThe osteoarthritis dataset GSE55235 was downloaded from the GEO database and analyzed for differential genes by limma package, followed by analysis of immune-related modules by xcell immune infiltration combined with the WGCNA method, and macrophage polarization-related genes were downloaded according to the Genecard database, and VennDiagram was used to determine their intersection. These genes were also subjected to gene ontology (GO), disease ontology (DO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Using machine learning, the key osteoarthritis genes were finally screened. Using single gene GSEA and GSVA, we examined the significance of these key gene functions in immune cell and macrophage pathways. Next, we confirmed the correctness of the hub gene expression profile using the GSE55457 dataset and the ROC curve. Finally, we projected TF, miRNA, and possible therapeutic drugs using the miRNet, TargetScanHuman, ENCOR, and NetworkAnalyst databases, as well as Enrichr. ResultsVennDiagram obtained 71 crossover genes for DEGs, WGCNA-immune modules, and Genecards; functional enrichment demonstrated NF-κB, IL-17 signaling pathway play an important role in osteoarthritis-macrophage polarization genes; machine learning finally identified CSF1R, CX3CR1, CEBPB, and TLR7 as hub genes; GSVA analysis showed that CSF1R, CEBPB play essential roles in immune infiltration and macrophage pathway; validation dataset GSE55457 analyzed hub genes were statistically different between osteoarthritis and healthy controls, and the AUC values of ROC for CSF1R, CX3CR1, CEBPB and TLR7 were more outstanding than 0.65. ConclusionsCSF1R, CEBPB, CX3CR1, and TLR7 are potential diagnostic biomarkers for osteoarthritis, and CSF1R and CEBPB play an important role in regulating macrophage polarization in osteoarthritis progression and are expected to be new drug targets.

PLAU and GREM1 are prognostic biomarkers for predicting immune response in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a common malignant tumor. Identification of biomarkers and understanding their potential functions will facilitate the treatment and diagnosis in LUAD patients. The yellow module (cor = 0.31, P = 2e-6) was selected as the core module based on weighted gene co-expression network analysis (WGCNA) by integrating RNA-seq data and tumor stage. Two upregulated genes (PLAU and GREM1) in yellow module were identified to be biomarkers. Kaplan-Meier curve analysis displayed that high expression levels of them had a poor overall survival (OS). And, their high expression levels revealed higher tumor stage and relapse possibility in LUAD patients, and could be a prognostic parameter. Both biomarkers showed similar immune cell expression profiles in low- and high-expression groups. Strongly positive correlation between both biomarkers and biomarkers of tumor-infiltrating lymphocytes were also clarified in TCGA-LUAD cohort. Importantly, single gene GSEA showed that transcriptional mis-regulation in cancer and microRNAs in cancer were enriched in LUAD patients. Therefore, a miRNA-mRNA-transcription factors (TFs) co-expression regulatory networks was constructed for each biomarker, various miRNAs and TFs were related to PLAU and GREM1. Among which, 6 downstream TFs were overlapped genes for both biomarkers. Notably, 2 of these TFs (FOXF1 and TFAP2A) exhibited significantly abnormal expression levels. Among which, FOXF1 was downregulated and TFAP2A was upregulated in TCGA-LUAD cohort. Both TFs showed a significantly positive correlation with the expression level of PLAU. In conclusion, we identified 2 biomarkers related to immune response and achieved a good accuracy in predicting OS in patients with LUAD.

KBTBD2 promotes proliferation and migration of gastric cancer via activating EGFR signaling pathway

BackgroundTo explore the role of Kelch repeat and BTB (POZ) domain containing 2 (KBTBD2) in Gastric cancer(GC) via studying the level of KBTBD2 and its impact on GC cells and mice model. MethodsExpression of KBTBD2 in GC was analyzed by analysis of TCGA data, Western blotting and Real-time quantitative polymerasechain reaction (RT-qPCR). The role of KBTBD2 on GC cells proliferation, viability, invasion, migration and apoptosis in vitro were assessed by using western blotting，RT-qPCR，CCK-8, EDU, Colony Formation Assay, Wound healing assay, Transwell, JC-1 mitochondrial membrane potential and flow cytometry assay, respectively. And levels of Bcl-2, BAX, PARP, E-cadherin, Vimentin, N-cadherin, EGFR, SOS1, NROS, BRAF,ERK1/2 and GAPDH were tested by western blotting. Relation of KBTBD2 and epidermal growth factor receptor (EGFR) was predicted by KEGG analysis. KBTBD2 gene GSEA enrichment was analyzed by using R language. Moreover, CCK-8, western blotting, and wound healing assays were used to verify the correlation of KBTBD2 and EGFR pathway. Finally, tumor growth in mice was also investigated. Cells proliferation, migration and apoptosis were detected by Ki67 staining, Tunnel staining and mouse lung metastasis model. ResultsKBTBD2 was highly expressed in GC, and was related to poor prognosis. Moreover, silencing KBTBD2 suppressed GC cell proliferation, migration and invasion, while also inhibited the EMT, but promoted apoptosis. At the same time, KBTBD2 overexpression showed opposite results. In addition, KBTBD2 regulated the EGFR pathway. Further, silencing KBTBD2 inhibited tumor growth, cell proliferation and migration but promoted apoptosis in vivo, and KBTBD2 overexpression showed opposite results. ConclusionsKBTBD2 was highly expressed in GC. KBTBD2 promotes the progress of GC by activating EGFR signal pathway. KBTBD2 may thus be a novel target for treating GC.

Identification of potential diagnostic biomarkers for tenosynovial giant cell tumour by integrating microarray and single-cell RNA sequencing data

PurposeTenosynovial giant cell tumour (TGCT) is a benign hyperplastic and inflammatory disease of the joint synovium or tendon sheaths, which may be misdiagnosed due to its atypical symptoms and imaging features. We aimed to identify biomarkers with high sensitivity and specificity to aid in diagnosing TGCT.MethodsTwo scRNA-seq datasets (GSE210750 and GSE152805) and two microarray datasets (GSE3698 and GSE175626) were downloaded from the Gene Expression Omnibus (GEO) database. By integrating the scRNA-seq datasets, we discovered that the osteoclasts are abundant in TGCT in contrast to the control. The single-sample gene set enrichment analysis (ssGSEA) further validated this discovery. Differentially expressed genes (DEGs) of the GSE3698 dataset were screened and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were conducted. Osteoclast-specific up-regulated genes (OCSURGs) were identified by intersecting the osteoclast marker genes in the scRNA-seq and the up-regulated DEGs in the microarray and by the least absolute shrinkage and selection operator (LASSO) regression algorithm. The expression levels of OCSURGs were validated by an external dataset GSE175626. Then, single gene GSEA, protein–protein interaction (PPI) network, and gene-drug network of OCSURGs were performed.Result22 seurat clusters were acquired and annotated into 10 cell types based on the scRNA-seq data. TGCT had a larger population of osteoclasts compared to the control. A total of 159 osteoclast marker genes and 104 DEGs (including 61 up-regulated genes and 43 down-regulated genes) were screened from the scRNA-seq analysis and the microarray analysis. Three OCSURGs (MMP9, SPP1, and TYROBP) were finally identified. The AUC of the ROC curve in the training and testing datasets suggested a favourable diagnostic capability. The PPI network results illustrated the protein–protein interaction of each OCSURG. Drugs that potentially target the OCSURGs were predicted by the DGIdb database.ConclusionMMP9, SPP1, and TYROBP were identified as osteoclast-specific up-regulated genes of the tenosynovial giant cell tumour via bioinformatic analysis, which had a reasonable diagnostic efficiency and served as potential drug targets.

Identification of potential biomarkers of myopia based on machine learning algorithms

PurposeThis study aims to identify potential myopia biomarkers using machine learning algorithms, enhancing myopia diagnosis and prognosis prediction.MethodsGSE112155 and GSE15163 datasets from the GEO database were analyzed. We used “limma” for differential expression analysis and “GO plot” and “clusterProfiler” for functional and pathway enrichment analyses. The LASSO and SVM-RFE algorithms were employed to screen myopia-related biomarkers, followed by ROC curve analysis for diagnostic performance evaluation. Single-gene GSEA enrichment analysis was executed using GSEA 4.1.0.ResultsThe functional analysis of differentially expressed genes indicated their role in carbohydrate generation and polysaccharide synthesis. We identified 23 differentially expressed genes associated with myopia, four of which were highly effective diagnostic biomarkers. Single gene GSEA results showed these genes control the ubiquitin-mediated protein hydrolysis pathway.ConclusionOur study identifies four key myopia biomarkers, providing a foundation for future clinical and experimental validation studies.

CCNB1 is a novel prognostic biomarker and promotes proliferation, migration and invasion in Wilms tumor

BackgroundWilms tumour (WT) is a mixed type of embryonal tumour that usually occurs in early childhood. However, our knowledge of the pathogenesis or progression mechanism of WT is inadequate, and there is a scarcity of beneficial therapeutic strategies.MethodsHigh-throughput RNA sequencing was employed in this study to identify differentially expressed genes (DEGs) in clinical tumor samples and matching normal tissues. The STRING database was utilized to build a protein-protein interaction (PPI) network, and the Cytohubba method was used to identify the top 10 highly related HUB genes. Then, the key genes were further screened by univariate COX survival analysis. Subsequently, the XCELL algorithm was used to evaluate the tumour immune infiltration. RT-PCR, WB, and IF were used to verify the expression level of key genes in clinical tissues and tumour cell lines. Finally, the function of the key gene was further verified by loss-of-function experiments.ResultsWe initially screened 1612 DEGs, of which 1030 were up-regulated and 582 were down-regulated. The GO and KEGG enrichment analysis suggested these genes were associated with ‘cell cycle’, ‘DNA replication’. Subsequently, we identified 10 key HUB genes, among them CCNB1 was strongly related to WT patients’ overall survival. Multiple survival analyses showed that CCNB1 was an independent indicator of WT prognosis. Thus, we constructed a nomogram of CCNB1 combined with other clinical indicators. Single gene GSEA and immune infiltration analysis revealed that CCNB1 was associated with the degree of infiltration or activation status of multiple immune cells. TIDE analysis indicated that this gene was correlated with multiple key immune checkpoint molecules and TIDE scores. Finally, we validated the differential expression level of CCNB1 in an external gene set, the pan-cancer, clinical samples, and cell lines. CCNB1 silencing significantly inhibited the proliferation, migration, and invasive capabilities of WIT-49 cells, also, promoted apoptosis, and in turn induced G2 phase cell cycle arrest in loss-of-function assays.ConclusionOur study suggests that CCNB1 is closely related to WT progression and prognosis, and serves as a potential target.

Identifification and validation of ferroptosis signatures and immune infifiltration characteristics associated with intervertebral disc degeneration.

Ferroptosis and immune infiltration play an important role in the pathogenesis of intervertebral disc degeneration (IDD). However, there is still a lack of comprehensive analysis on the interaction between ferroptosis-related genes (FRGs) and immune microenvironment in IDD patients. Therefore, this study aims to explore the correlation between FRGs characteristics and immune infiltration in the progression of IDD. The expression profiles (GSE56081 and GSE70362) and FRGs were downloaded from the comprehensive gene expression omnibus (GEO) and FerrDb database, respectively, and the differences were analyzed using R. The intersection of IDD related differential genes (DEGs) and FRGs was taken as differentially expressed FRGs (DE-FRGs) and GO and KEGG enrichment analysis was conducted. Then, we used least absolute shrinkage and selection operator (LASSO) regression algorithm and support vector machine (SVM) algorithm to screen feature genes and draw ROC curve judge the diagnostic value of key DE-FRGs. Then CIBERSORT algorithm is used to evaluate the infiltration of immune cells and analyze the correlation between key DE-FRGs and immune infiltration. Based on the analysis results, we conducted single gene GSEA analysis on key DE-FRGs. RT-PCR and immunohistochemistry further verified the clinical value of the results of biochemical analysis and screening. Seven key DE-FRGs were screened, including the upregulated genes NOX4 and PIR, and the downregulated genes TIMM9, ATF3, ENPP2, FADS2 and TFAP2A. Single gene GSEA analysis further elucidates the role of DE-FRGs in IDD associated with ferroptosis. Correlation analysis showed that seven key DE-FRGs were closely related to immune infiltration in the development of IDD. Finally, RT-PCR and immunohistochemical staining showed that NOX4, ENPP2, FADS2 and TFAP2A were statistically significant differences. In this study, we explored the connection between ferroptosis related characteristics and immune infiltration in IDD, and confirmed that NOX4, ENPP2, FADS2, and TFAP2A may become biomarkers and potential therapeutic targets for IDD.

Construction and Comprehensive Analysis of a Special Competitive Endogenous RNAs Network to Reveal Potential Prognostic Biomarkers for Endometrial Carcinoma

Background: Endometrial carcinoma (EC) is one of the most common malignancies in women worldwide. For EC patients discovered at an early stage, the prognosis is good. However, the advanced EC patients (stage III-IV) have very poor prognoses. The competitive endogenous RNAs (ceRNA) regulatory network in EC remains unclear, and the relationship between hub RNAs and important clinical characters (clinical stage) has not been strictly studied yet. Objective: In order to study the development of endometrial carcinoma and the identification of early diagnostic markers, the relationship between hub RNAs and important clinical traits (clinical stage) was strictly studied. Methods: The co-expression networks of mRNA, lncRNA, and miRNA were constructed by weighted gene co-expression network analysis. Gene ontology (GO) biological process terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out for DEmRNA. AceRNA regulated network was constructed based on miRcode, miRDB, TargetScan, and miRTarBase. Furthermore, survival analysis, regression analysis of mRNA-lncRNA pairs, and gene set enrichment analysis were carried out. Results: A ceRNA network containing 11 mRNAs, 4 miRNAs, and 18 lncRNAs was constructed based on aberrantly expressed RNAs in the co-expression modules. In this network, 7 mRNAs, 4 lncRNAs, and 1 miRNA were found closely related to the overall survival of EC. The positive correlations of 35 pairs of mRNA and lncRNA in the ceRNA network were obtained. Notably, 5 mRNAs, 3 lncRNAs, and 1 miRNA were identified as potential prognostic biomarkers for EC. Single gene GSEA analysis revealed that the signal pathways related to cell cycle and cancer were highly enriched. Conclusion: Identification of five mRNAs (CBX6, PIM1, RIMS3, SOX11, and XKR7), three lncRNA (WT1-AS, LINC00494, and LINC00501), and one miRNA (miR-195) as potential prognostic biomarkers for EC was helpful for the early diagnosis, prognosis, and development of new treatment strategies of EC patients.

The Structures of Oligosaccharide Bisphosphates Isolated from the Lipopolysaccharide of a Recombinant Escherichia coli Strain Expressing the Gene gseA [3-deoxy-d-manno-Octulopyranosonic Acid (Kdo) Transferase] of Chlamydia psittaci 6BC

The lipopolysaccharide from the recombinant strain Escherichia coli F515-140 containing the cloned gene gseA [3-deoxy-D-manno-octulopyranosonic acid (Kdo) transferase] from Chlamydia psittaci 6BC was isolated and sequentially de-O-acylated and de-N-acylated. The products were separated by high-performance anion-exchange chromatography into three fractions, two of which contained a single compound. Their structures were elucidated by high-field NMR spectroscopy as alpha-Kdo-(2-->4)-alpha-Kdo-(2-->6)-beta-D-GlcN-(1-->6)-alpha-D-GlcN 1,4'-P2 (compound 1) (tetrasaccharide bisphosphate) [Holst, O., Broer, W., Thomas-Oates, J. E., Mamat, U. & Brade, H. (1993) Eur. J. Biochem. 214, 703-710] and alpha-Kdo-(2-->4)-[alpha-Kdo-(2-->8)-]-alpha-Kdo-(2-->4)-alpha-Kdo- (2-->6)-beta-D-GlcN-(1-->6)-alpha-D-GlcN 1,4'-P2 (compound 4) (hexasaccharide bisphosphate). The third fraction comprised two pentasaccharide bisphosphates, which could be separated by affinity chromatography using an immobilized monoclonal antibody specific for the trisaccharide alpha-Kdo-(2-->8)-alpha-Kdo-(2-->4)-alpha-Kdo. The bound fraction was identified as alpha-Kdo-(2-->8)-alpha-Kdo-(2-->4)-alpha-Kdo-(2-->6)-beta-D- GlcN-(1-->6)-alpha-D-GlcN 1,4'-P2 (compound 2) [Holst, O., Broer, W., Thomas-Oates, J. E., Mamat, U. & Brade, H. (1993) Eur. J. Biochem. 214, 703-710], whereas the unbound fraction was identified as alpha-Kdo-(2-->4)-alpha-Kdo-(2-->4)-alpha-Kdo-(2-->6)-beta-D-GlcN-(1-->6 )- alpha-D-GlcN 1,4'-P2 (compound 3). This novel Kdo tetrasaccharide extends our knowledge on multifunctional Kdo transferases.

The Structures of Oligosaccharide Bisphosphates Isolated from the Lipopolysaccharide of a Recombinant Escherichia coli Strain Expressing the Gene gseA [3-deoxy-d-manno-Octulopyranosonic Acid (Kdo) Transferase] of Chlamydia psittaci 6BC

The Structures of Oligosaccharide Bisphosphates Isolated from the Lipopolysaccharide of a Recombinant Escherichia coli Strain Expressing the Gene gseA [3-deoxy-d-manno-Octulopyranosonic Acid (Kdo) Transferase] of Chlamydia psittaci 6BC

Nucleotide sequence variations within the lipopolysaccharide biosynthesis gene gseA (Kdo transferase) among the Chlamydia trachomatis serovars

The gene gseA, involved in the expression of the genus-specific epitope of chlamydial lipopolysaccharide (LPS), was analyzed by temperature gradient gel electrophoresis (TGGE) to visualize nucleotide sequence variations among the 15 serovars of Chlamydia trachomatis. Sequence analysis showed that the TGGE melting-profile patterns were able to detect single nucleotide variations within gseA and allowed the arrangement of the serovars in groups of both identical nucleotide sequences and sequences containing identical sites of nucleotide substitutions. Compared to serovar L2, four types of patterns were obtained: (i) serotypes A and Ba; (ii) B and C (causing endemic trachoma); (iii) D through K (causing sexually transmitted oculo-genital infections); (iv) L1 through L3 (the causative agents of lymphogranuloma venereum). A total of 58 isolates of C. trachomatis of genital or conjunctival origin were tested by this method in comparison to reference strains. Forty-eight isolates (13 of type E, 16 of type F, nine of type G, and ten of type K) yielded the same melting profile as the corresponding type strain, independent of whether they were isolated from genital or ocular infections. However, ten B serotype strains of genital origin behaved in TGGE like a typical genital strain and not a trachoma strain. Thus, although gseA was found to be highly conserved among C. trachomatis, the obtained TGGE profiles of the tested strains tended to correlate with their specific site of infection.

The genus-specific lipopolysaccharide epitope of Chlamydia is assembled in C. psittaci and C. trachomatis by glycosyltransferases of low homology.

Chlamydiae possess a genus-specific epitope that is located on the lipopolysaccharide (LPS) and is composed of a 3-deoxy-D-manno-octulosonic acid (Kdo) trisaccharide of the sequence alpha Kdo-(2-->8)--alpha Kdo-(2-->4)-alpha Kdo. In Chlamydia trachomatis, this trisaccharide is biosynthetically generated through the action of a multi-functional Kdo-transferase encoded by the gene gseA. gseA of Chlamydia psittaci 6BC was cloned and expressed in a rough mutant (Re chemotype) of Escherichia coli (strain F515) that contains an LPS with only two alpha 2-->4-linked Kdo residues. Recombinant strains were able to add the immunodominant Kdo residue in alpha 2-->8-linkage to the parental LPS, as determined by SDS-PAGE and Western blot analysis using a monoclonal antibody against the genus-specific epitope. The DNA sequence of gseA was determined and aligned to that published recently for C. trachomatis serovar L2. Most surprisingly, the two deduced amino acid sequences shared only an overall homology of 67%. Thus, gseA exhibits species specificity at the DNA level, whereas its gene product results in the synthesis of a carbohydrate antigen with genus specificity.