Machine learning-based intradialytic hypotension prediction of patients undergoing hemodialysis: A multicenter retrospective study.

BACKGROUND AND OBJECTIVE: Intradialytic hypotension (IDH) is closely associated with adverse clinical outcomes in HD-patients. An IDH predictor model is important for IDH risk screening and clinical decision-making. In this study, we used Machine learning (ML) to develop IDH model for risk prediction in HD patients. METHODS: 62,227 dialysis sessions were randomly partitioned into training data (70%), test data (20%), and validation data (10%). IDH-A model based on twenty-seven variables was constructed for risk prediction for the next HD treatment. IDH-B model based on ten variables from 64,870 dialysis sessions was developed for risk assessment before each HD treatment. Light Gradient Boosting Machine (LightGBM), Linear Discriminant Analysis, support vector machines, XGBoost, TabNet, and multilayer perceptron were used to develop the predictor model. RESULTS: In IDH-A model, we identified the LightGBM method as the best-performing and interpretable model with C- statistics of 0.82 in Fall30Nadir90 definitions, which was higher than those obtained using the other models (P<0.01). In other IDH standards of Nadir90, Nadir100, Fall20, Fall30, and Fall20Nadir90, the LightGBM method had a performance with C- statistics ranged 0.77 to 0.89. As a complementary application, the LightGBM model in IDH-B model achieved C- statistics of 0.68 in Fall30Nadir90 definitions and 0.69 to 0.78 in the other five IDH standards, which were also higher than the other methods, respectively. CONCLUSION: Use ML, we identified the LightGBM method as the good-performing and interpretable model. We identified the top variables as the high-risk factors for IDH incident in HD-patient. IDH-A and IDH-B model can usefully complement each other for risk prediction and further facilitate timely intervention through applied into different clinical setting.

Global-feature of autoimmune glomerulonephritis using proteomic analysis of laser capture microdissected glomeruli.

Background: IgA nephropathy (IgAN), (LN), membranous nephropathy (MN), and minimal change nephropathy (MCN) are all belonged to autoimmune glomerulonephritis. This study aimed to identify the specific proteomic characteristics of the four GNs diseases in order to provide frameworks for developing the appropriate drug for patients diagnosed with GNs disease. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was utilized to investigate proteomic features of glomerular tissues obtained by laser capture microdissection (LCM). 8 normal control cases, 11 IgAN cases, 19 LN cases, 5 MN cases, and 3 MCN cases in this study were selected for bioinformatics analyses. Results: The shared overlapping proteins among the top 100 DEPs of each GNs type were mostly downregulated, in which only FLII was significantly downregulated in the four GNs diseases. A2M was significantly upregulated in MN, IgAN, and LN subgroups. The pathway of complement and coagulation cascades was notably activated with NES value ranging 2.77 to 3.39 among MCN, MN, IgAN, and LN diseases, but the pattern of protein expression level were significantly different. In LN patients, the increased activity of complement and coagulation cascades was contributed by the high expression of multiple complements (C1QB, C3, C4A, C4B, C6, C8B, C8G, C9). Meanwhile, both C1QC and C4B were remarkably upregulated in MN patients. On the contrary, complement-regulating proteins (CD59) was substantially decreased in MCN and IgAN subgroup. Conclusions: The integrative proteomics analysis of the four GNs diseases provide insights into unique characteristics of GNs diseases and further serve as frameworks for precision medicine diagnosis and provide novel targets for drug development.

Serum proteome and metabolome uncover novel biomarkers for the assessment of disease activity and diagnosing of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease affecting thousands of people. There are still no effective biomarkers for SLE diagnosis and disease activity assessment. We performed proteomics and metabolomics analyses of serum from 121 SLE patients and 106 healthy individuals, and identified 90 proteins and 76 metabolites significantly changed. Several apolipoproteins and the metabolite arachidonic acid were significantly associated with disease activity. Apolipoprotein A-IV (APOA4), LysoPC(16:0), punicic acid and stearidonic acid were correlated with renal function. Random forest model using the significantly changed molecules identified 3 proteins including ATRN, THBS1 and SERPINC1, and 5 metabolites including cholesterol, palmitoleoylethanolamide, octadecanamide, palmitamide and linoleoylethanolamide, as potential biomarkers for SLE diagnosis. Those biomarkers were further validated in an independent cohort with high accuracy (AUC = 0.862 and 0.898 for protein and metabolite biomarkers respectively). This unbiased screening has led to the discovery of novel molecules for SLE disease activity assessment and SLE classification.

Combined proteomics and single cell RNA-sequencing analysis to identify biomarkers of disease diagnosis and disease exacerbation for systemic lupus erythematosus.

Introduction: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease for which there is no cure. Effective diagnosis and precise assessment of disease exacerbation remains a major challenge. Methods: We performed peripheral blood mononuclear cell (PBMC) proteomics of a discovery cohort, including patients with active SLE and inactive SLE, patients with rheumatoid arthritis (RA), and healthy controls (HC). Then, we performed a machine learning pipeline to identify biomarker combinations. The biomarker combinations were further validated using enzyme-linked immunosorbent assays (ELISAs) in another cohort. Single-cell RNA sequencing (scRNA-seq) data from active SLE, inactive SLE, and HC PBMC samples further elucidated the potential immune cellular sources of each of these PBMC biomarkers. Results: Screening of the PBMC proteome identified 1023, 168, and 124 proteins that were significantly different between SLE vs. HC, SLE vs. RA, and active SLE vs. inactive SLE, respectively. The machine learning pipeline identified two biomarker combinations that accurately distinguished patients with SLE from controls and discriminated between active and inactive SLE. The validated results of ELISAs for two biomarker combinations were in line with the discovery cohort results. Among them, the six-protein combination (IFIT3, MX1, TOMM40, STAT1, STAT2, and OAS3) exhibited good performance for SLE disease diagnosis, with AUC of 0.723 and 0.815 for distinguishing SLE from HC and RA, respectively. Nine-protein combination (PHACTR2, GOT2, L-selectin, CMC4, MAP2K1, CMPK2, ECPAS, SRA1, and STAT2) showed a robust performance in assessing disease exacerbation (AUC=0.990). Further, the potential immune cellular sources of nine PBMC biomarkers, which had the consistent changes with the proteomics data, were elucidated by PBMC scRNAseq. Discussion: Unbiased proteomic quantification and experimental validation of PBMC samples from two cohorts of patients with SLE were identified as biomarker combinations for diagnosis and activity monitoring. Furthermore, the immune cell subtype origin of the biomarkers in the transcript expression level was determined using PBMC scRNAseq. These findings present valuable PBMC biomarkers associated with SLE and may reveal potential therapeutic targets.

NFE2L3 as a Potential Functional Gene Regulating Immune Microenvironment in Human Kidney Cancer.

With the increasing incidence and mortality of renal cancer, it is pressing to find new biomarkers and drug targets for diagnosis and treatment. However, as one negative upstream regulator of p53, the prognostic and immunological role of NFE2L3 in renal cancer is still barely known. We investigated the expression, prognostic value, and relevant pathways of NFE2L3 using the datasets from public databases, including The Cancer Genome Atlas Program (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and UALCAN. Furthermore, we analyzed the relationship between NFE2L3 expression and the immune microenvironment using distinct methods. We found that NFE2L3 was higher expressed in kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) tissues than adjacent normal tissues. Additionally, we identified NFE2L3 as one survival-related factor for KIRC and KIRP. The enrichment analyses revealed that NFE2L3 was associated with a variety of immune-relevant pathways in KIRC and related to the infiltration ratios of 17 types of immune cells in KIRC patients. Ultimately, we demonstrated nine significantly enriched mutations, such as TP53 and MET, in NFE2L3-expression-changing groups. The elevated expression of NFE2L3 in renal cancerous tissues versus normal tissues is associated with poor outcomes in patients. Besides, NFE2L3 has a role in the regulation of the immune microenvironment in renal cancer patients. The findings of our study provide a potential prognostic biomarker and a new drug target for renal cancer.

Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with multi-organ inflammation and defect, which is linked to many molecule mediators. Oxylipins as a class of lipid mediator have not been broadly investigated in SLE. Here, we applied targeted mass spectrometry analysis to screen the alteration of oxylipins in serum of 98 SLE patients and 106 healthy controls. The correlation of oxylipins to lupus nephritis (LN) and SLE disease activity, and the biomarkers for SLE classification, were analyzed. Among 128 oxylipins analyzed, 92 were absolutely quantified and 26 were significantly changed. They were mainly generated from the metabolism of several polyunsaturated fatty acids, including arachidonic acid (AA), linoleic acid (LA), docosahexanoic acid (DHA), eicosapentanoic acid (EPA) and dihomo-γ-linolenic acid (DGLA). Several oxylipins, especially those produced from AA, showed different abundance between patients with and without lupus nephritis (LN). The DGLA metabolic activity and DGLA generated PGE1, were significantly associated with SLE disease activity. Random forest-based machine learning identified a 5-oxylipin combination as potential biomarker for SLE classification with high accuracy. Seven individual oxylipin biomarkers were also identified with good performance in distinguishing SLE patients from healthy controls (individual AUC > 0.7). Interestingly, the biomarkers for differentiating SLE patients from healthy controls are distinct from the oxylipins differentially expressed in LN patients vs. non-LN patients. This study provides possibilities for the understanding of SLE characteristics and the development of new tools for SLE classification.

Comprehensive characterization of ubiquitinome of human colorectal cancer and identification of potential survival-related ubiquitination.

BACKGROUND: According to the Global Cancer Statistics in 2020, the incidence and mortality of colorectal cancer (CRC) rank third and second among all tumors. The disturbance of ubiquitination plays an important role in the initiation and development of CRC, but the ubiquitinome of CRC cells and the survival-relevant ubiquitination are poorly understood. METHODS: The ubiquitinome of CRC patients (n = 6) was characterized using our own data sets of proteomic and ubiquitin-proteomic examinations. Then, the probable survival-relevant ubiquitination was searched based on the analyses of data sets from public databases. RESULTS: For the ubiquitinomic examination, we identified 1690 quantifiable sites and 870 quantifiable proteins. We found that the highly-ubiquitinated proteins (n ≥ 10) were specifically involved in the biological processes such as G-protein coupling, glycoprotein coupling, and antigen presentation. Also, we depicted five motif sequences frequently recognized by ubiquitin. Subsequently, we revealed that the ubiquitination content of 1172 proteins were up-regulated and 1700 proteins were down-regulated in CRC cells versus normal adjacent cells. We demonstrated that the differentially ubiquitinated proteins were relevant to the pathways including metabolism, immune regulation, and telomere maintenance. Then, integrated with the proteomic datasets from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) (n = 98), we revealed that the increased ubiquitination of FOCAD at Lys583 and Lys587 was potentially associated with patient survival. Finally, we depicted the mutation map of FOCAD and elucidated its potential functions on RNA localization and translation in CRC. CONCLUSIONS: The findings of this study described the ubiquitinome of CRC cells and identified abnormal ubiquitination(s) potentially affecting the patient survival, thereby offering new probable opportunities for clinical treatment.

Inhibition of UBA6 by inosine augments tumour immunogenicity and responses.

Anti-cancer immunity and response to immune therapy is influenced by the metabolic states of the tumours. Immune checkpoint blockade therapy (ICB) is known to involve metabolic adaptation, however, the mechanism is not fully known. Here we show, by metabolic profiling of plasma samples from melanoma-bearing mice undergoing anti-PD1 and anti-CTLA4 combination therapy, that higher levels of purine metabolites, including inosine, mark ICB sensitivity. Metabolic profiles of ICB-treated human cancers confirm the association between inosine levels and ICB sensitivity. In mouse models, inosine supplementation sensitizes tumours to ICB, even if they are intrinsically ICB resistant, by enhancing T cell-mediated cytotoxicity and hence generating an immunologically hotter microenvironment. We find that inosine directly inhibits UBA6 in tumour cells, and lower level of UBA6 makes the tumour more immunogenic and this is reflected in favourable outcome following ICB therapy in human melanomas. Transplanted mouse melanoma and breast cancer cells with genetic ablation of Uba6 show higher sensitivity to ICB than wild type tumours. Thus, we provide evidence of an inosine-regulated UBA6-dependent pathway governing tumour-intrinsic immunogenicity and hence sensitivity to immune checkpoint inhibition, which might provide targets to overcome ICB resistance.

Multi-platform-based characterization of ferroptosis in human colorectal cancer.

Ferroptosis is a type of programmed cell death potentially playing an important role in colorectal cancer (CRC) development. However, comprehensive investigations toward ferroptosis in human CRC are lacking. Here, we performed multiple investigations on cancer and para-cancer tissues. We demonstrated that the changes of structural variation and chromatin accessibility in CRC were more associated with the altered mRNA expression of ferroptosis-related genes (FRGs), and the expression of CDKN2A, GPX4, ALOXE3, and LINC00336 was related to the overall survival rates. Subsequently, we revealed that CYBB and YAP1 were potentially the hub genes, and that HSF1 and STAT2 were potentially FRGs' upstream transcription factors. Finally, we depicted the crosstalk between ferroptosis and necrosis, autophagy, and apoptosis. Based on multi-dimensional analyses, we characterized ferroptosis, probable core genes, and the upstream regulators in human CRC. The findings here may improve our understanding of ferroptosis in CRC and provide new opportunities for clinical diagnosis and treatment.

Analysis of Gene Expression and TCR/B Cell Receptor Profiling of Immune Cells in Primary Sjögren's Syndrome by Single-Cell Sequencing.

Primary Sjögren's syndrome (pSS) is a chronic autoimmune disease that is estimated to affect 35 million people worldwide and is characterized by lymphocytic infiltration, elevated circulating autoantibodies, and proinflammatory cytokines. The key immune cell subset changes and the TCR/BCR repertoire alterations in pSS patients remain unclear. In this study, we sought to comprehensively characterize the transcriptional changes in PBMCs of pSS patients by single-cell RNA sequencing and single-cell V(D)J sequencing. Naive CD8+ T cells and mucosal-associated invariant T cells were markedly decreased but regulatory T cells were increased in pSS patients. There were a large number of differentially expressed genes shared by multiple subpopulations of T cells and B cells. Abnormal signaling pathways, including Ag processing and presentation, the BCR signaling pathway, the TCR signaling pathway, and Epstein-Barr virus infection, were highly enriched in pSS patients. Moreover, there were obvious differences in the CD30, FLT3, IFN-II, IL-1, IL-2, IL-6, IL-10, RESISTIN, TGF-ß, TNF, and VEGF signaling networks between pSS patients and healthy controls. Single-cell TCR and BCR repertoire analysis showed that there was a lower diversity of T cells in pSS patients than in healthy controls; however, there was no significant difference in the degree of clonal expansion, CDR3 length distribution, or degree of sequence sharing. Notably, our results further emphasize the functional importance of αß pairing in determining Ag specificity. In conclusion, our analysis provides a comprehensive single-cell map of gene expression and TCR/BCR profiles in pSS patients for a better understanding of the pathogenesis, diagnosis, and treatment of pSS.

Identification of lysine acetylome of oral squamous cell carcinoma by label-free quantitative proteomics.

Lysine acetylation (Kac) on histone promotes relaxation of the chromatin conformation and favors gene transcription to regulate oncogenesis, whereas the total acetylation profiling of oral squamous cell carcinoma (OSCC) is unknown. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was utilised to investigate lysine acetylation features of tumor tissues and adjacent normal tissues from 9 patients with OCSS. 282 upregulated Kac sites in 234 proteins and 235 downregulated Kac sites in 162 proteins between OSCC tissues and paired adjacent normal tissues were identified. Different acetylation proteins (DAPs) were analyzed through KEGG-based and MCODE. These DAPs are enriched in the ribosome biogenesis pathway. Survival Analysis of hub genes with TCGA database was performed. In addition, IPA software was used to explore the connection between 9 core DAPs (RPS3, RPL24, RPL19, EIF4A2, RPL12, MYBPC1, RPS6, ARCN1, and TMEM9) and the different expression of KATs and KDACs identified in our proteomic. The study is the first comparative study of Kac modification on oral squamous cell carcinoma. We propose to put forward the hypothesis that the dysfunction of ribosome biogenesis caused by the change of Lysine acetylation, especially downregulated acetylation on RPS6 and RPS3 may associated with the pathogenesis of OSCC. SIGNIFICANCE: The study is the first comparative study of Kac modification on oral squamous cell carcinoma through LC-MS/MS-based modified proteomic. These DAPs are high enriched in the ribosome biogenesis pathway. Used MCODE and survival analysis, 9 core DAPs (RPS3, RPL24, RPL19, EIF4A2, RPL12, MYBPC1, RPS6, ARCN1, and TMEM9) were screened. IPA software was used to explore the connection between 9 core DAPs and the different expression of KATs and KDACs identified in our proteomic. In addition, we propose to put forward the hypothesis that the dysfunction of ribosome biogenesis caused by the change of Lysine acetylation, especially downregulated acetylation on RPS6 and RPS3 may associated with the pathogenesis of OSCC.

Multi-Platform-Based Analysis Characterizes Molecular Alterations of the Nucleus in Human Colorectal Cancer.

Background: The disturbed molecular alterations of nucleus may promote the development of colorectal cancer (CRC). A multi-platform-based analysis of nucleus of CRC patients helps us to better understand the underlying mechanism of CRC and screen out the potential drug targets for clinical treatment. However, such studies on nucleus in human CRC are still lacking. Methods: We collected the cancerous and para-cancerous tissues from eight CRC patients and performed a multiplex analysis of the molecular changes of the nucleus, including structural variations (SVs), DNA methylation, chromatin accessibility, proteome and phosphorproteome. Results: In our study, we revealed a significant molecular change of nucleus of CRC patients using our original proteomic and phosphorylomic datasets. Subsequently, we characterized the molecular alterations of nucleus of CRC patients at multiple dimensionalities, including DNA, mRNA, protein and epigenetic modification. Next, we found that the great molecular changes of nucleus might affect the biological processes named endocytosis and ubiquitin-mediated proteolysis. Besides, we identified DYNC1LI2 and TPR as the potentially hub proteins within the network of nuclear genes in CRC cells. Furthermore, we identified 1905 CRC-specific SVs, and proclaimed 17 CRC-specific SVs were probably associated with the disturbance of immune microenvironment of CRC patients. We also revealed that the SVs of CXCL5, CXCL10 and CXCL11 might be the core SVs among all the immune-relevant SVs. Finally, we identified seven genes as the upstream transcriptional factors potentially regulating the expression of nuclear genes, such as YY1 and JUN, using a multi-omics approach. Conclusion: Here, we characterized the molecular changes of nucleus of CRC patients, disclosed the potentially core nuclear genes within the network, and identified the probable upstream regulator of nucleus. The findings of this study are helpful to understand the pathogenic molecular changes of nucleus in CRC patients and provide a functional context for drug development in future.

PLD1 promotes reactive oxygen species production in vascular smooth muscle cells and injury-induced neointima formation.

Phospholipase D (PLD) generates the signaling lipid phosphatidic acid (PA) and has been known to mediate proliferation signal in vascular smooth muscle cells (VSMCs). However, it remains unclear how PLD contributes to vascular diseases. VSMC proliferation directly contributes to the development and progression of cardiovascular disease, such as atherosclerosis and restenosis after angioplasty. Using the mouse carotid artery ligation model, we find that deletion of Pld1 gene inhibits neointima formation of the injuried blood vessels. PLD1 deficiency reduces the proliferation of VSMCs in both injured artery and primary cultures through the inhibition of ERK1/2 and AKT signals. Immunohistochemical staining of injured artery and flow cytometry analysis of VSMCs shows a reduction of the levels of reactive oxygen species (ROS) in Pld1-/- VSMCs. An increase of intracellular ROS by hydrogen peroxide stimulation restored the reduced activities of ERK and AKT in Pld1-/- VSMCs, whereas a reduction of ROS by N-acetyl-l-cysteine (NAC) scavenger lowered their activity in wild-type VSMCs. These results indicate that PLD1 plays a critical role in neointima, and that PLD1 mediates VSMC proliferation signal through promoting the production of ROS. Therefore, inhibition of PLD1 may be used as a therapeutic approach to suppress neointimal formation in atherosclerosis and restenosis after angioplasty.

Intestinal microbiome and metabolome analyses reveal metabolic disorders in the early stage of renal transplantation.

Renal transplantation is the most effective treatment for end-stage renal disease, but the long-term prognosis of organs after transplantation is not ideal. In recent years, the importance of gut microbes and metabolites in the study of disease mechanisms has gradually received attention. However, the coordination between gut microbes and the metabolism of renal transplant patients needs further study. We integrated 16s sequencing and metabolomics data to describe the changes in the serum and fecal metabolites of renal transplant patients. Our data revealed that the gut microbial diversity decreased and the relative abundance of many bacteria, such as Enterococcus and Streptococcus, significantly changed after transplantation. In addition, a large number of amino acids and peptides in serum and feces significantly changed, suggesting an abnormal amino acid metabolism after transplantation. Spearman's correlation analysis revealed the changes in the co-metabolism pattern between gut microbes and the host metabolism after transplantation. Furthermore, Enterococcus was found to be correlated with renal functions and metabolites reflecting renal damage. This study provides potential gut microbes and metabolites impacting renal health, which helps in understanding the renal damage in patients with kidney transplantation.

Analysis of gut microbiota and metabolites in patients with rheumatoid arthritis and identification of potential biomarkers.

Rheumatoid arthritis (RA) is an autoimmune disease described by joint destruction, synovitis and pannus formation. The gut microbiota acts as an environmental factor that plays an important role in RA, but little research regarding the etiopathogenic mechanisms of the microbiome in RA has been carried out. We used an integrated approach of 16S rRNA gene sequencing and ultrahigh-performance liquid chromatography-mass spectrometry-based metabolomics to analyze the structure and diversity of the intestinal flora and metabolites of the gut microbiota in RA patients compared with healthy subjects. In this study, α-diversity analysis of the gut microbiota showed that there was no significant difference between the healthy control (HC) and RA groups. However, ß-diversity analysis showed that there was a significant difference between the two groups. Further analysis of alteration of the gut microbiota revealed that at the phylum level, the relative abundance of p_Bacteroidetes was significantly decreased in the RA group, while that of Verrucomicrobia and Proteobacteria was significantly increased in the RA group. At the genus level, Bacteroides, Faecalibacterium and some probiotics were decreased in the RA group, while 97 genera, including Lactobacillus, Streptococcus and Akkermansia, were increased in the RA group. Seventy-four differentially abundant metabolites were identified between the HC and RA groups, and we identified two potential biomarkers (9,12-octadecadiynoic acid and 10Z-nonadecenoic acid) in RA.

Microbiome and Metabolome Analyses Reveal Novel Interplay Between the Skin Microbiota and Plasma Metabolites in Psoriasis.

Psoriasis is a chronic inflammatory skin disease that affects millions of people worldwide. There is still no effective approach for the clinical treatment of psoriasis. This is largely due to the lack of understanding of the pathological mechanism. Here, we comprehensively characterized the skin microbiome and plasma metabolome alterations of psoriasis patients. We observed that some pathogenic bacteria, including Vibrio, were significantly increased in psoriasis patients. The metabolomics results showed alterations in some metabolic pathways, especially pathways for lipid metabolism. In addition, microbiome-specific metabolites, including bile acids and kynurenine, were significantly changed. Correlation analysis revealed the interplay between the skin microbiota and plasma metabolites, especially between Vibrio and several lipids. Our results provide new evidence for the interplay between the skin microbiome and plasma metabolites, which is dramatically disrupted in psoriasis patients. This study also revealed the mechanism underlying the pathogenesis of psoriasis.

Microbiome and Metabolome Analyses Reveal the Disruption of Lipid Metabolism in Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that affects thousands of people worldwide. Recently, alterations in metabolism and gut microbiome have emerged as key regulators of SLE pathogenesis. However, it is not clear about the coordination of gut commensal bacteria and SLE metabolism. Here, by integrating 16S sequencing and metabolomics data, we characterized the gut microbiome and fecal and serum metabolome alterations in patients with SLE. Microbial diversity sequencing revealed gut microflora dysbiosis in SLE patients with significantly increased beta diversity. The metabolomics profiling identified 43 and 55 significantly changed metabolites in serum and feces samples in SLE patients. Notably, lipids accounted for about 65% altered metabolites in serum, highlighted the disruption of lipid metabolism. Integrated correlation analysis provided a link between the gut microbiome and lipid metabolism in patients with SLE, particularly according to regulate the conversion of primary bile acids to secondary bile acids. Overall, our results illustrate the perturbation of the gut microbiome and metabolome in SLE patients which may facilitate the development of new SLE interventions.

Advances in applying of multi-omics approaches in the research of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE), an autoimmune disease that causes multiorgan injury, has an unclear etiology and complex pathogenesis. Numerous studies have found abnormal alterations in mRNAs, proteins and/or metabolites in SLE patients. These findings have extended our understanding of the pathogenesis of SLE. Novel omics techniques, such as transcriptome, proteome and metabolome profiling, can identify and quantify large numbers of biomarkers of human diseases. However, in most cases, biological reactions are the consequences of interactions among genes, proteomes, and metabolites. Single biomolecules or signaling pathways cannot fully explain biological traits or functions. Therefore, integrative multi-omics analysis can help us systematically comprehend the intrinsic molecular mechanisms underlying biological function and pathogenesis. Integrating transcriptome, proteome, and metabolome KEGG enrichment analysis data will expand our knowledge of the pathogenesis of SLE. This review discusses the application, research progress and outlook on integrative multi-omics analysis in SLE research.

Rapid affinity purification of intracellular organelles using a twin strep tag.

Cells are internally organized into compartmentalized organelles that execute specialized functions. To understand the functions of individual organelles and their regulations, it is critical to resolve the compositions of individual organelles, which relies on a rapid and efficient isolation method for specific organellar populations. Here, we introduce a robust affinity purification method for rapid isolation of intracellular organelles (e.g. lysosomes, mitochondria and peroxisomes) by taking advantage of the extraordinarily high affinity between the twin strep tag and streptavidin variants. With this method, we can isolate desired organelles with high purity and yield in 3 min from the post-nuclear supernatant of mammalian cells or less than 8 min for the whole purification process. Using lysosomes as an example, we show that the rapid procedure is especially useful for studying transient and fast cellular activities, such as organelle-initiated signaling and organellar contents of small-molecular metabolites. Therefore, our method offers a powerful tool to dissect spatiotemporal regulation and functions of intracellular organelles.