Role of intestinal flora in the development of nonalcoholic fatty liver disease in children.

In China, 45% of adolescents with obesity develop fatty liver disease, a condition that increases the long-term risk of developing cirrhosis and liver cancer. Although the factors triggering nonalcoholic fatty liver disease (NAFLD) vary in children, the composition of intestinal microflora has been found to play an increasingly important role. However, evidence is limited on the prevalence of nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH) in Chinese children. Therefore, this study aimed to evaluate the fecal microbiome of Chinese children with NAFLD and further analyze the potential of flora in regulating NAFLD-related symptoms and metabolic functions. Specifically, the study applied a 16S rRNA and metagenomic sequencing to the fecal samples of pediatric patients with NAFLD, NASH, and NAFL, as well as healthy controls, to explore the correlation among NAFLD-related indexes, metabolic pathways, and gut flora. The findings showed that some fecal microbiota had a negative correlation with body mass index, and various NAFLD-related bacteria, including Lachnoclostridium, Escherichia-Shigella, and Faecalibacterium prausnitzii, were detected. Consequently, the study concluded that the variation in gut microbiota might be more important in improving NAFLD/NASH compared with single species, providing a microbiota diagnostic profile of NAFLD/NASH.IMPORTANCEThis study aims to characterize the gut microbiota in Chinese children with nonalcoholic fatty liver disease (NAFLD) through 16S rRNA and metagenomic sequencing. The results highlight the association between fecal microbiota and NAFLD in Chinese children, demonstrating distinct characteristics compared to adults and children from other countries. Based on the sequencing data from our cohort's fecal samples, we propose a microbiota model with a high area under the curve for distinguishing between NAFLD and healthy individuals. Furthermore, our follow-up study reveals that changes in the relative abundance of microbial biomarkers in this model are consistent with variations in patients' body mass index. These findings suggest the potential utility of the microbiota model and microbial biomarkers for diagnosing and treating NAFLD in children.

[Effects of gestational diabetes mellitus on gut microbiota of 3-month-old infants: a prospective control study].

OBJECTIVE: To explore the effect of gestational diabetes mellitus on the gut microbiota of their offsprings, the gut microbiota of 3-month-old infants whose mothers diagnosed with and without gestational diabetes mellitus(GDM) was compared. METHODS: Pregnant women and their 3-month-old infants who were examined, delivered and follow-up visited in a county in Hebei Province from June 2016 to December 2019 were included in our study. The pregnants and their infants with result of fasting venous blood glucose≥5.1 mmol/L in the second or third trimester were included in GDM group. Fecal samples of 3-month-old infants were collected and 16 S rDNA high-throughput sequencing technology was used to explore the change of gut microbiota. RESULTS: A total of 48 pairs of subjects were included, 16 in GDM group and 32 in control group. Comparison of gut microbiota diversity: analysis of the Alpha diversity index showed that the Observed Species index, margalef index and menhinick index of GDM group were(141.4±17.2), (13.66±1.66) and(0.83±0.10), respectively, which were significantly lower than that of control group(154.9±21.7), (15.00±2.11) and(0.91±0.13), respectively. Sequence analysis: at phylum level, the abundance of the Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria were 54.28(47.84), 23.58(23.48), 11.20(30.99) and 0.12(0.07), respectively, while the control group were 42.05(36.23), 29.64(21.30), 9.31(15.82) and 0.15(10.14), respectively. The two groups were mainly composed of these 4 phyla and Actinobacteria was the most abundant. At genus level, there were mainly Bifidobacteria, lactobacillus, Enterobacteria, Bacteroidales and Clostridiales in both groups. The abundance of Erysipelotrichales in GDM group(0.01(0.01)) was significantly lower than that in control group(0.04(0.06))(P<0.05). The abundance of Micrococcales in GDM group(0.13(0.24) was significantly lower than that in control group(0.29(0.78))(P<0.05). PCoA analysis showed that the gut microbiota structure of GDM group and control group was similar. LEfSe analysis showed Erysipelatoclostridium was significantly increased in control group(P<0.05). CONCLUSION: GDM can reduce the diversity and richness of gut microbiota of 3-month-old infants and has no significant effect on the phylum level but has effect on some genus level. It suggests that GDM may still have some potential effect on slightly elder infants.

Precise annotation of Drosophila mitochondrial genomes leads to insights into AT-rich regions.

In the present study, we performed precise annotation of Drosophila melanogaster, D. simulans, D. grimshawi, Bactrocera oleae mitochondrial (mt) genomes using pan RNA-seq analysis. Using PacBio cDNA-seq data from D. simulans, we precisely annotated the Transcription Initiation Sites (TISs) of the mt Heavy and Light strands in Drosophila mt genomes and reported that the polyA(+) and polyA(-) motifs in the CRs are associated with TISs. The discovery of the conserved polyA(+) and polyA(-) motifs provides insights into many polyA and polyT sequences in CRs of insect mt genomes, leading to reveal the mt transcription and its regulation in invertebrates. Notably, we propose that: (1) polyA/polyT motifs in CRs function as signals to initiate mtDNA transcription; (2) the duplication, recombination or mutation of these polyA/polyT sequences formed the AT-rich regions during evolution; and (3) since CRs of many invertebrate species still contain many polyA/polyT sequences, there is a high probability that several TISs and TTSs exist in invertebrate mt genomes.

Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease.

Dysregulation of the gut microbiome has been implicated in the progression of many diseases. This study explored the role of microbial and metabolic signatures, and their interaction between the Human inflammatory bowel disease (IBD) and healthy controls (HCs) based on the combination of machine learning and traditional statistical analysis, using data collected from the Human Microbiome Project (HMP) and the Integrative Human Microbiome Project (iHMP). It was showed that the microbial and metabolic signatures of IBD patients were significantly different from those of HCs. Compared to HCs, IBD subjects were characterized by 25 enriched species and 6 depleted species. Furthermore, a total of 17 discriminative pathways were identified between the IBD and HC groups. Those differential pathways were mainly involved in amino acid, nucleotide biosynthesis, and carbohydrate degradation. Notably, co-occurrence network analysis revealed that non-predominant bacteria Ruminococcus_obeum and predominant bacteria Faecalibacterium_prausnitzii formed the same broad and strong co-occurring relationships with pathways. Moreover, the essay identified a combinatorial marker panel that could distinguish IBD from HCs. Receiver Operating Characteristic (ROC) and Decision Curve Analysis (DCA) confirmed the high accuracy (AUC = 0.966) and effectiveness of the model. Meanwhile, an independent cohort used for external validation also showed the identical high efficacy (AUC = 0.835). These findings showed that the gut microbes may be relevant to the pathogenesis and pathophysiology, and offer universal utility as a non-invasive diagnostic test in IBD.

Comparison of gut microbiota in autism spectrum disorders and neurotypical boys in China: A case-control study.

BACKGROUND: Autism spectrum disorders (ASDs) are a set of complex neurobiological disorders. Growing evidence has shown that the microbiota that resides in the gut can modulate brain development via the gut-brain axis. However, direct clinical evidence of the role of the microbiota-gut-brain axis in ASD is relatively limited. METHODS: A case-control study of 71 boys with ASD and 18 neurotypical controls was conducted at China-Japan Friendship Hospital. Demographic information and fecal samples were collected, and the gut microbiome was evaluated and compared by 16S ribosomal RNA gene sequencing and metagenomic sequencing. RESULTS: A higher abundance of operational taxonomic units (OTUs) based on fecal bacterial profiling was observed in the ASD group. Significantly different microbiome profiles were observed between the two groups. At the genus level, we observed a decrease in the relative abundance of Escherichia, Shigella, Veillonella, Akkermansia, Provindencia, Dialister, Bifidobacterium, Streptococcus, Ruminococcaceae UCG_002, Megasphaera, Eubacterium_coprostanol, Citrobacter, Ruminiclostridium_5, and Ruminiclostridium_6 in the ASD cohort, while Eisenbergiella, Klebsiella, Faecalibacterium, and Blautia were significantly increased. Ten bacterial strains were selected for clinical discrimination between those with ASD and the neurotypical controls. The highest AUC value of the model was 0.947. CONCLUSION: Significant differences were observed in the composition of the gut microbiome between boys with ASD and neurotypical controls. These findings contribute to the knowledge of the alteration of the gut microbiome in ASD patients, which opens the possibility for early identification of this disease.

Precise annotation of tick mitochondrial genomes reveals multiple copy number variation of short tandem repeats and one transposon-like element.

BACKGROUND: In the present study, we used long-PCR amplification coupled with Next-Generation Sequencing (NGS) to obtain complete mitochondrial (mt) genomes of individual ticks and unprecedently performed precise annotation of these mt genomes. We aimed to: (1) develop a simple, cost-effective and accurate method for the study of extremely high AT-content mt genomes within an individual animal (e.g. Dermacentor silvarum) containing miniscule DNA; (2) provide a high-quality reference genome for D. silvarum with precise annotation and also for future studies of other tick mt genomes; and (3) detect and analyze mt DNA variation within an individual tick. RESULTS: These annotations were confirmed by the PacBio full-length transcriptome data to cover both entire strands of the mitochondrial genomes without any gaps or overlaps. Moreover, two new and important findings were reported for the first time, contributing fundamental knowledge to mt biology. The first was the discovery of a transposon-like element that may eventually reveal much about mechanisms of gene rearrangements in mt genomes. Another finding was that Copy Number Variation (CNV) of Short Tandem Repeats (STRs) account for mitochondrial sequence diversity (heterogeneity) within an individual tick, insect, mouse or human, whereas SNPs were not detected. The CNV of STRs in the protein-coding genes resulted in frameshift mutations in the proteins, which can cause deleterious effects. Mitochondria containing these deleterious STR mutations accumulate in cells and can produce deleterious proteins. CONCLUSIONS: We proposed that the accumulation of CNV of STRs in mitochondria may cause aging or diseases. Future tests of the CNV of STRs hypothesis help to ultimately reveal the genetic basis of mitochondrial DNA variation and its consequences (e.g., aging and diseases) in animals. Our study will lead to the reconsideration of the importance of STRs and a unified study of CNV of STRs with longer and shorter repeat units (particularly polynucleotides) in both nuclear and mt genomes.