Leveraging Existing 16SrRNA Microbial Data to Define a Composite Biomarker for Autism Spectrum Disorder

Xu, Yushuang; Wang, YiHua; Xu, JinShuang; Song, Yu; Liu, Bingqiang; Xiong, Zhifan

doi:10.1128/spectrum.00331-22

Cited by 8 publications

(6 citation statements)

References 38 publications

(39 reference statements)

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“…It effectively projects the samples in the new space to have the minimum intraclass distance and the maximum interclass distance. This enables comparison between two or more subgroups to find species that differ significantly in abundance between groups, that is, biomarkers ( 38 , 39 ). The evolutionary branching plots and linear discriminant analysis (LDA) score plots obtained based on LEfSe analysis before and after antibiotic treatment are presented in Fig.…”

Section: Resultsmentioning

confidence: 99%

Antibiotic Conditioning Shapes Pseudosterile Mouse Models by Deleting Colonic Microbes Rather than Small Intestinal Microbes

Chen

Xing

et al. 2023

Microbiol Spectr

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Section: Resultsmentioning

confidence: 99%

Antibiotic Conditioning Shapes Pseudosterile Mouse Models by Deleting Colonic Microbes Rather than Small Intestinal Microbes

Chen

Xing

et al. 2023

Microbiol Spectr

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“…However, diagnosing ASD has always been difficult, and the condition is recognized at a late stage for treatment to have a major effect. Several studies have focused on biomarkers for determining ASD risk or assisting with diagnosis, such as proteomic analysis 58 , epigenome-wide analysis 59 , single-nucleotide polymorphism 60 , maackia amurensis lectin-II binding glycoproteins 61 , and the gut microbiota [62][63][64][65] . In our study, the use of microbial markers for the prediction of C-ASD was comprehensively assessed by 16 specific genera and PPA.…”

Section: Discussionmentioning

confidence: 99%

Altered Gut Microbiota and Short-chain Fatty Acids in Chinese Children with Constipated Autism Spectrum Disorder

He,

Gong,

et al. 2023

Sci Rep

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Gastrointestinal symptoms are more prevalent in children with autism spectrum disorder (ASD) than in typically developing (TD) children. Constipation is a significant gastrointestinal comorbidity of ASD, but the associations among constipated autism spectrum disorder (C-ASD), microbiota and short-chain fatty acids (SCFAs) are still debated. We enrolled 80 children, divided into the C-ASD group (n = 40) and the TD group (n = 40). In this study, an integrated 16S rRNA gene sequencing and gas chromatography–mass spectrometry-based metabolomics approach was applied to explore the association of the gut microbiota and SCFAs in C-ASD children in China. The community diversity estimated by the Observe, Chao1, and ACE indices was significantly lower in the C-ASD group than in the TD group. We observed that Ruminococcaceae_UCG_002, Erysipelotrichaceae_UCG_003, Phascolarctobacterium, Megamonas, Ruminiclostridium_5, Parabacteroides, Prevotella_2, Fusobacterium, and Prevotella_9 were enriched in the C-ASD group, and Anaerostipes, Lactobacillus, Ruminococcus_gnavus_group, Lachnospiraceae_NK4A136_group, Ralstonia, Eubacterium_eligens_group, and Ruminococcus_1 were enriched in the TD group. The propionate levels, which were higher in the C-ASD group, were negatively correlated with the abundance of Lactobacillus taxa, but were positively correlated with the severity of ASD symptoms. The random forest model, based on the 16 representative discriminant genera, achieved a high accuracy (AUC = 0.924). In conclusion, we found that C-ASD is related to altered gut microbiota and SCFAs, especially decreased abundance of Lactobacillus and excessive propionate in faeces, which provide new clues to understand C-ASD and biomarkers for the diagnosis and potential strategies for treatment of the disorder. This study was registered in the Chinese Clinical Trial Registry (www.chictr.org.cn; trial registration number ChiCTR2100052106; date of registration: October 17, 2021).

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“…Wang et al sequence the microbiome in the blood of patients with polycystic ovary syndrome by 16S rRNA to explore its relationship with the disease [ 17 ]. High-throughput sequencing of the 16S rRNA can also analyze the gut microbiota that characterizes autism spectrum disorders [ 18 ]. 16S rRNA is a rapid microbiological diagnostic method for DFU, which takes less time [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

16S rRNA seq-identified Corynebacterium promotes pyroptosis to aggravate diabetic foot ulcer

Zheng,

Na,

Yao

et al. 2024

BMC Infect Dis

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Background Diabetic foot ulcer (DFU) is one of the main chronic complications caused by diabetes, leading to amputation in severe cases. Bacterial infection affects the wound healing in DFU. Methods DFU patients who met the criteria were selected, and the clinical data were recorded in detail. The pus exudate from the patient’s foot wound and venous blood were collected for biochemical analysis. The distribution of bacterial flora in pus exudates of patients was analyzed by 16S rRNA sequencing, and the correlation between DFU and pathogenic variables, pyroptosis and immunity was analyzed by statistical analysis. Then, the effects of key bacteria on the inflammation, proliferation, apoptosis, and pyroptosis of polymorphonuclear leukocytes were investigated by ELISA, CCK-8, flow cytometry, RT-qPCR and western blot. Results Clinical data analysis showed that Wagner score was positively correlated with the level of inflammatory factors, and there was high CD3+, CD4+, and low CD8+ levels in DFU patients with high Wagner score. Through alpha, beta diversity analysis and species composition analysis, Corynebacterium accounted for a large proportion in DFU. Logistics regression model and Person correlation analysis demonstrated that mixed bacterial infections could aggravate foot ulcer, and the number of bacteria was closely related to inflammatory factors PCT, PRT, immune cells CD8+, and pyroptosis-related proteins GSDMD and NLRP3. Through in vitro experiments, Corynebacterium inhibited cell proliferation, promoted inflammation (TNF-α, PCT, CRP), apoptosis and pyroptosis (IL-1β, LDH, IL-18, GSDMD, NLRP3, and caspase-3). Conclusion Mixed bacterial infections exacerbate DFU progression with a high predominance of Corynebacterium, and Corynebacterium promotes inflammation, apoptosis and pyroptosis to inhibit DFU healing.

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Leveraging Existing 16SrRNA Microbial Data to Define a Composite Biomarker for Autism Spectrum Disorder

Abstract: This study provides an updated analysis to characterize the gut microbiota in ASD using 16SrRNA gene high-throughput sequencing data from 10 publicly available studies. Our analysis suggests an association between the fecal microbiota and ASD.

Cited by 8 publications

References 38 publications

Antibiotic Conditioning Shapes Pseudosterile Mouse Models by Deleting Colonic Microbes Rather than Small Intestinal Microbes

Antibiotic Conditioning Shapes Pseudosterile Mouse Models by Deleting Colonic Microbes Rather than Small Intestinal Microbes

Altered Gut Microbiota and Short-chain Fatty Acids in Chinese Children with Constipated Autism Spectrum Disorder

16S rRNA seq-identified Corynebacterium promotes pyroptosis to aggravate diabetic foot ulcer

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