Table_1_Genetic predisposition of the gastrointestinal microbiome and primary biliary cholangitis: a bi-directional, two-sample Mendelian randomization analysis.xlsx

BackgroundThe gut-liver axis indicates a close relationship between the gastrointestinal microbiome (GM) and primary biliary cholangitis (PBC). However, the causality of this relationship remains unknown. This study investigates the causal relationship between the GM and PBC using a bidirectional, two-sample Mendelian randomization (MR) analysis.MethodsGenome-wide association data for GM and PBC were obtained from public databases. The inverse-variance weighted method was the primary method used for MR analysis. Sensitivity analyses were conducted to assess the stability of the MR results. A reverse MR analysis was performed to investigate the possibility of reverse causality.ResultsThree bacterial taxa were found to be causally related to PBC. Class Coriobacteriia (odds ratio (OR) = 2.18, 95% confidence interval (CI): 1.295-3.661, PConclusionPreviously unrecognized taxa that may be involved in the pathogenesis of PBC were identified in this study, confirming the causality between the GM and PBC. These results provide novel microbial targets for the prevention and treatment of PBC.</p

Image_1_Urine Organic Acids as Potential Biomarkers for Autism-Spectrum Disorder in Chinese Children.JPEG

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that lacks clear biological biomarkers. Existing diagnostic methods focus on behavioral and performance characteristics, which complicates the diagnosis of patients younger than 3 years-old. The purpose of this study is to characterize metabolic features of ASD that could be used to identify potential biomarkers for diagnosis and exploration of ASD etiology. We used gas chromatography-mass spectrometry (GC/MS) to evaluate major metabolic fluctuations in 76 organic acids present in urine from 156 children with ASD and from 64 non-autistic children. Three algorithms, Partial Least Squares-Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost), were used to develop models to distinguish ASD from typically developing (TD) children and to detect potential biomarkers. In an independent testing set, full model of XGBoost with all 76 acids achieved an AUR of 0.94, while reduced model with top 20 acids discovered by voting from these three algorithms achieved 0.93 and represent a good collection of potential ASD biomarkers. In summary, urine organic acids detection with GC/MS combined with XGBoost algorithm could represent a novel and accurate strategy for diagnosis of autism and the discovered potential biomarkers could be valuable for future research on the pathogenesis of autism and possible interventions.</p

Table_1_Urine Organic Acids as Potential Biomarkers for Autism-Spectrum Disorder in Chinese Children.docx

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that lacks clear biological biomarkers. Existing diagnostic methods focus on behavioral and performance characteristics, which complicates the diagnosis of patients younger than 3 years-old. The purpose of this study is to characterize metabolic features of ASD that could be used to identify potential biomarkers for diagnosis and exploration of ASD etiology. We used gas chromatography-mass spectrometry (GC/MS) to evaluate major metabolic fluctuations in 76 organic acids present in urine from 156 children with ASD and from 64 non-autistic children. Three algorithms, Partial Least Squares-Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost), were used to develop models to distinguish ASD from typically developing (TD) children and to detect potential biomarkers. In an independent testing set, full model of XGBoost with all 76 acids achieved an AUR of 0.94, while reduced model with top 20 acids discovered by voting from these three algorithms achieved 0.93 and represent a good collection of potential ASD biomarkers. In summary, urine organic acids detection with GC/MS combined with XGBoost algorithm could represent a novel and accurate strategy for diagnosis of autism and the discovered potential biomarkers could be valuable for future research on the pathogenesis of autism and possible interventions.</p

Synthesis and Characterization of Hydrazide-Linked and Amide-Linked Organic Polymers

Four kinds of either hydrazide-linked or amide-linked polymers were facilely synthesized by using hydrazine, tetrakis­(4-aminophenyl)­methane (TAPM), terephthaloyl chloride (TPC), and trimesoyl chloride (TMC) as building blocks. The morphology, porosity, composition, and surface property of polymers were characterized by scanning electron microscopy, transmission electron microscopy, nitrogen adsorption–desorption measurement, ¹³C/CP-MAS NMR, X-ray photoelectron spectroscopy, etc. The results indicated that building blocks had important effects on morphology and porosity. Poly­(TMC–TAPM) synthesized with TMC and TAPM showed the highest surface area of 241.9 m² g^–1. In addition, note that a hollow structure with ∼20 nm wall thickness was formed in poly­(TMC–hydrazine) prepared with TMC and hydrazine. Further study indicated that both carboxyl groups (−COOH) and hydrazide groups (−CONH–NH₂) existed on the surface of poly­(TMC–hydrazine), besides the mainly hydrazide linkage (−CONH–NHOC−). Taking advantages of good hydrophilicity and special functional groups on the surface, we finally adopted poly­(TMC–hydrazine) to enrich glycopeptides from tryptic digest via both hydrophilic interaction chromatography method with identification of 369 unique N-glycosylation sites and hydrazide chemistry method with identification of 88 unique N-glycosylation sites, respectively

A New Searching Strategy for the Identification of O‑Linked Glycopeptides

For the analysis of homogeneous post-translational modifications such as protein phosphorylation and acetylation, setting a variable modification on the specific residue(s) is applied to identify the modified peptides for database searching. However, this approach is often not applicable to identify intact mucin-type O-glycopeptides due to the high microheterogeneity of the glycosylation. Because there is virtually no carbohydrate-related tag on the peptide fragments after the O-glycopeptides are dissociated in HCD, we find it is unnecessary to set the variable mass tags on the Ser/Thr residues to identify the peptide sequences. In this study, we present a novel approach, termed as O-Search, for the interpretation of O-glycopeptide HCD spectra. Instead of setting the variable mass tags on the Ser/Thr residues, we set variable mass tags on the peptide level. The precursor mass of the MS/MS spectrum was deducted by every possible summed mass of O-glycan combinations on at most three S/T residues. All the spectra with these new precursor masses were searched against the protein sequence database without setting variable glycan modifications. It was found that this method had much decreased search space and had excellent sensitivity in the identification of O-glycopeptides. Compared with the conventional searching approach, O-Search yielded 96%, 86%, and 79% improvement in glycopeptide spectra matching, glycopeptide identification, and peptide sequence identification, respectively. It was demonstrated that O-Search enabled the consideration of more glycan structures and was fitted to analyze microheterogeneity of O-glycosylation

A New Searching Strategy for the Identification of O‑Linked Glycopeptides

For the analysis of homogeneous post-translational modifications such as protein phosphorylation and acetylation, setting a variable modification on the specific residue(s) is applied to identify the modified peptides for database searching. However, this approach is often not applicable to identify intact mucin-type O-glycopeptides due to the high microheterogeneity of the glycosylation. Because there is virtually no carbohydrate-related tag on the peptide fragments after the O-glycopeptides are dissociated in HCD, we find it is unnecessary to set the variable mass tags on the Ser/Thr residues to identify the peptide sequences. In this study, we present a novel approach, termed as O-Search, for the interpretation of O-glycopeptide HCD spectra. Instead of setting the variable mass tags on the Ser/Thr residues, we set variable mass tags on the peptide level. The precursor mass of the MS/MS spectrum was deducted by every possible summed mass of O-glycan combinations on at most three S/T residues. All the spectra with these new precursor masses were searched against the protein sequence database without setting variable glycan modifications. It was found that this method had much decreased search space and had excellent sensitivity in the identification of O-glycopeptides. Compared with the conventional searching approach, O-Search yielded 96%, 86%, and 79% improvement in glycopeptide spectra matching, glycopeptide identification, and peptide sequence identification, respectively. It was demonstrated that O-Search enabled the consideration of more glycan structures and was fitted to analyze microheterogeneity of O-glycosylation

A New Searching Strategy for the Identification of O‑Linked Glycopeptides

For the analysis of homogeneous post-translational modifications such as protein phosphorylation and acetylation, setting a variable modification on the specific residue(s) is applied to identify the modified peptides for database searching. However, this approach is often not applicable to identify intact mucin-type O-glycopeptides due to the high microheterogeneity of the glycosylation. Because there is virtually no carbohydrate-related tag on the peptide fragments after the O-glycopeptides are dissociated in HCD, we find it is unnecessary to set the variable mass tags on the Ser/Thr residues to identify the peptide sequences. In this study, we present a novel approach, termed as O-Search, for the interpretation of O-glycopeptide HCD spectra. Instead of setting the variable mass tags on the Ser/Thr residues, we set variable mass tags on the peptide level. The precursor mass of the MS/MS spectrum was deducted by every possible summed mass of O-glycan combinations on at most three S/T residues. All the spectra with these new precursor masses were searched against the protein sequence database without setting variable glycan modifications. It was found that this method had much decreased search space and had excellent sensitivity in the identification of O-glycopeptides. Compared with the conventional searching approach, O-Search yielded 96%, 86%, and 79% improvement in glycopeptide spectra matching, glycopeptide identification, and peptide sequence identification, respectively. It was demonstrated that O-Search enabled the consideration of more glycan structures and was fitted to analyze microheterogeneity of O-glycosylation

A New Searching Strategy for the Identification of O‑Linked Glycopeptides

For the analysis of homogeneous post-translational modifications such as protein phosphorylation and acetylation, setting a variable modification on the specific residue(s) is applied to identify the modified peptides for database searching. However, this approach is often not applicable to identify intact mucin-type O-glycopeptides due to the high microheterogeneity of the glycosylation. Because there is virtually no carbohydrate-related tag on the peptide fragments after the O-glycopeptides are dissociated in HCD, we find it is unnecessary to set the variable mass tags on the Ser/Thr residues to identify the peptide sequences. In this study, we present a novel approach, termed as O-Search, for the interpretation of O-glycopeptide HCD spectra. Instead of setting the variable mass tags on the Ser/Thr residues, we set variable mass tags on the peptide level. The precursor mass of the MS/MS spectrum was deducted by every possible summed mass of O-glycan combinations on at most three S/T residues. All the spectra with these new precursor masses were searched against the protein sequence database without setting variable glycan modifications. It was found that this method had much decreased search space and had excellent sensitivity in the identification of O-glycopeptides. Compared with the conventional searching approach, O-Search yielded 96%, 86%, and 79% improvement in glycopeptide spectra matching, glycopeptide identification, and peptide sequence identification, respectively. It was demonstrated that O-Search enabled the consideration of more glycan structures and was fitted to analyze microheterogeneity of O-glycosylation

A New Searching Strategy for the Identification of O‑Linked Glycopeptides

For the analysis of homogeneous post-translational modifications such as protein phosphorylation and acetylation, setting a variable modification on the specific residue(s) is applied to identify the modified peptides for database searching. However, this approach is often not applicable to identify intact mucin-type O-glycopeptides due to the high microheterogeneity of the glycosylation. Because there is virtually no carbohydrate-related tag on the peptide fragments after the O-glycopeptides are dissociated in HCD, we find it is unnecessary to set the variable mass tags on the Ser/Thr residues to identify the peptide sequences. In this study, we present a novel approach, termed as O-Search, for the interpretation of O-glycopeptide HCD spectra. Instead of setting the variable mass tags on the Ser/Thr residues, we set variable mass tags on the peptide level. The precursor mass of the MS/MS spectrum was deducted by every possible summed mass of O-glycan combinations on at most three S/T residues. All the spectra with these new precursor masses were searched against the protein sequence database without setting variable glycan modifications. It was found that this method had much decreased search space and had excellent sensitivity in the identification of O-glycopeptides. Compared with the conventional searching approach, O-Search yielded 96%, 86%, and 79% improvement in glycopeptide spectra matching, glycopeptide identification, and peptide sequence identification, respectively. It was demonstrated that O-Search enabled the consideration of more glycan structures and was fitted to analyze microheterogeneity of O-glycosylation

A New Searching Strategy for the Identification of O‑Linked Glycopeptides

For the analysis of homogeneous post-translational modifications such as protein phosphorylation and acetylation, setting a variable modification on the specific residue(s) is applied to identify the modified peptides for database searching. However, this approach is often not applicable to identify intact mucin-type O-glycopeptides due to the high microheterogeneity of the glycosylation. Because there is virtually no carbohydrate-related tag on the peptide fragments after the O-glycopeptides are dissociated in HCD, we find it is unnecessary to set the variable mass tags on the Ser/Thr residues to identify the peptide sequences. In this study, we present a novel approach, termed as O-Search, for the interpretation of O-glycopeptide HCD spectra. Instead of setting the variable mass tags on the Ser/Thr residues, we set variable mass tags on the peptide level. The precursor mass of the MS/MS spectrum was deducted by every possible summed mass of O-glycan combinations on at most three S/T residues. All the spectra with these new precursor masses were searched against the protein sequence database without setting variable glycan modifications. It was found that this method had much decreased search space and had excellent sensitivity in the identification of O-glycopeptides. Compared with the conventional searching approach, O-Search yielded 96%, 86%, and 79% improvement in glycopeptide spectra matching, glycopeptide identification, and peptide sequence identification, respectively. It was demonstrated that O-Search enabled the consideration of more glycan structures and was fitted to analyze microheterogeneity of O-glycosylation