Proteomics Study on the Cerebrospinal Fluid of Patients with Encephalitis

Diagnostic signatures and immune cell infiltration characteristics in anti-GABABR encephalitis

PURPOSE

Anti-gamma-aminobutyric acid B receptor (GABABR) encephalitis is an uncommon form of autoimmune encephalitis associated with a poor prognosis and a high fatality rate. We aim to find diagnostic markers for anti- GABABR encephalitis as well as the effects of immune cell infiltration on this pathology.

METHODS

For quantitative proteomic analysis, isobaric tags for relative and absolute quantitation were used in conjunction with LC-MS/MS analysis. To conduct functional correlation analyses, differentially expressed proteins (DEPs) were identified. Following that, we used bioinformatics analysis to screen for and determine the diagnostic signatures of anti- GABABR encephalitis. ROC curves were used to evaluate the diagnostic values. To assess the inflammatory status of anti- GABABR encephalitis, we used cell-type identification by estimating relative subsets of the RNA transcript (CIBERSORT) and explored the link between diagnostic markers and infiltrating immune cells.

RESULTS

Overall, 108 robust DEPs (47 upregulated and 61 downregulated) were identified, of which 11 were immune related. The most impressively enriched pathways were complemented and coagulation cascades, actin cytoskeleton regulation, and cholesterol metabolism; GSEA revealed that the enriched pathways were considerably differentially connected to immune modulation. Eleven immune-related DEPs were chosen for further investigation. We developed a novel diagnostic model based on CSF1R and AZGP1 serum levels using ROC analysis (area under the ROC curve = 1). M1 macrophages and activated natural killer cells are likely to play a role in course of anti- GABABR encephalitis.

CONCLUSION

We identified CSF1R and AZGP1 are possible anti-GABABR encephalitis diagnostic indicators, and immune cell infiltration may have a significant impact on the development and occurrence of anti- GABABR encephalitis.

Quality Control—A Stepchild in Quantitative Proteomics: A Case Study for the Human CSF Proteome

Proteomic studies using mass spectrometry (MS)-based quantification are a main approach to the discovery of new biomarkers. However, a number of analytical conditions in front and during MS data acquisition can affect the accuracy of the obtained outcome. Therefore, comprehensive quality assessment of the acquired data plays a central role in quantitative proteomics, though, due to the immense complexity of MS data, it is often neglected. Here, we address practically the quality assessment of quantitative MS data, describing key steps for the evaluation, including the levels of raw data, identification and quantification. With this, four independent datasets from cerebrospinal fluid, an important biofluid for neurodegenerative disease biomarker studies, were assessed, demonstrating that sample processing-based differences are already reflected at all three levels but with varying impacts on the quality of the quantitative data. Specifically, we provide guidance to critically interpret the quality of MS data for quantitative proteomics. Moreover, we provide the free and open source quality control tool MaCProQC, enabling systematic, rapid and uncomplicated data comparison of raw data, identification and feature detection levels through defined quality metrics and a step-by-step quality control workflow.

Quantitative proteomics on the cerebrospinal fluid of hydrocephalus in neonatal bacterial meningitis

Objective

Hydrocephalus in bacterial meningitis (BM) is a devastating infectious neurological disease and the proteins and pathways involved in its pathophysiology are not fully understood.

Materials and methods

Label-free quantitative (LFQ) proteomics analyses was used to identify differentially expressed proteins (DEPs) in cerebrospinal fluid (CSF) samples from infants with hydrocephalus and bacterial meningitis (HBM group, N = 8), infants with bacterial meningitis (BM group, N = 9); and healthy infants (N group, N = 11). Bioinformatics analysis was subsequently performed to investigate Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enriched signaling pathways of these DEPs. Six proteins (AZU1, COX4I1, EDF1, KRT31, MMP12, and PRG2) were selected for further validation via enzyme-linked immunosorbent assay (ELISA).

Results

Compared with BM group and N group, HBM group had a higher whole CSF protein level (5.6 ± 2.7 vs. 1.7 ± 1.0 vs. 1.2 ± 0.5 g/l) and lower whole CSF glucose level (0.8 ± 0.6 vs. 1.8 ± 0.7 vs. 3.3 ± 0.8 mmol/l) (both P < 0.05). Over 300 DEPs were differentially expressed in HBM group compared with BM group and BM compared with N group, of which 78% were common to both. Cluster analysis indicated that the levels of 226 proteins were increased in BM group compared with N group and were decreased in HBM group compared with BM group. Bioinformatics analysis indicated the involvement of the cell adhesion, immune response and extracellular exosome signaling were significantly enriched in HBM compared with BM group and BM compared with N group. 267 DEPs were identified between HBM group with N group, KEGG analysis indicated that DEPs mainly involved in filament cytoskeleton and immune response. The ELISA results further verified that the expression levels of AZU1 were significantly different from among three groups (both P < 0.05).

Conclusion

This is the first reported characterization of quantitative proteomics from the CSF of infants with HBM. Our study also demonstrated that AZU1 could be a potential biomarker for the diagnosis of hydrocephalus in bacterial meningitis.

A novel hydrophilic MOFs-303-functionalized magnetic probe for the highly efficient analysis of N-linked glycopeptides

The effective analysis of glycoproteomics in clinical complex samples is of vital importance for the diagnosis and therapy of diseases. In this study, a hydrophilic MOFs-303-functionalized magnetic probe (GO@Fe₃O₄@MOF-303) is designed and fabricated to profile N-linked glycopeptides. Owing to its strong magnetic property, large surface area (845 m² g^-1), excellent hydrophilicity and suitable porous structure, the GO@Fe₃O₄@MOF-303 probe exhibits an ultralow detection limit (0.1 fmol μL^-1), perfect size-exclusion effect (HRP digests/BSA protein/HRP protein, 1 : 1000 : 1000, w/w/w), a high binding capacity (200 mg g^-1) and excellent reusability in the capture of standard N-linked glycopeptides. More excitingly, the GO@Fe₃O₄@MOF-303 probe also shows remarkable performance in practical applications, where 274 N-linked glycopeptides from 101 glycoproteins were identified in total for healthy controls, while a total of 265 N-linked glycopeptides from 102 glycoproteins were identified in serum (1 μL) with hepatocellular carcinoma (HCC). In addition, we discovered 4 up-regulated and 19 down-regulated serum glycoproteins in HCC patients by the hierarchical clustering heatmap. All results demonstrated that the reusable GO@Fe₃O₄@MOF-303 probe has great potential in profiling different N-linked glycopeptides in complex clinical samples. This study not only developed a novel probe for the highly effective capture of N-linked glycopeptides but also contributed to further understanding the mechanism of HCC and provides guidance for the development of novel clinical diagnostic methods.

Exposure to concentrated ambient PM2.5 (CAPM) induces intestinal disturbance via inflammation and alternation of gut microbiome

Air pollution causes a great disease burden worldwide. Recent evidences suggested that PM_2.5 contributes to intestinal disease. The objective of present study was to investigate the influence of ambient PM_2.5 on intestinal tissue and microbiome via whole-body inhalation exposure. The results showed that high levels and prolonged periods exposure to concentrated ambient PM_2.5 (CAPM) could destroy the mucous layer of the colon, and significantly alter the mRNA expression of tight junction (Occludin and ZO-1) and inflammation-related (IL-6, IL-10 and IL-1β) genes in the colon, comparing with exposure to the filtered air (FA). The composition of intestinal microbiome at the phylum and genus levels also varied along with the exposure time and PM_2.5 levels. At the phylum level, Bacteroidetes was greatly decreased, while Proteobacteria was increased after exposure to CAPM, comparing with exposure to FA. At the genus level, Clostridium XlVa, Akkermansia and Acetatifactor, were significantly elevated exposure to CAPM, comparing with exposure to FA. Our results also indicated that high levels and prolonged periods exposure to CAPM altered metabolic functional pathways. The correlation analysis showed that the intestinal inflammation was related to the alteration of gut microbiome induced by CAPM exposure, which may be a potential mechanism that elucidates PM_2.5-induced intestinal diseases. These results extend our knowledge on the toxicology and health effects of ambient PM_2.5.