Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Mar 23;14(7):1340.
doi: 10.3390/nu14071340.

Analysis of Faecal Microbiota and Small ncRNAs in Autism: Detection of miRNAs and piRNAs with Possible Implications in Host-Gut Microbiota Cross-Talk

Affiliations

Analysis of Faecal Microbiota and Small ncRNAs in Autism: Detection of miRNAs and piRNAs with Possible Implications in Host-Gut Microbiota Cross-Talk

Federica Chiappori et al. Nutrients. .

Abstract

Intestinal microorganisms impact health by maintaining gut homeostasis and shaping the host immunity, while gut dysbiosis associates with many conditions, including autism, a complex neurodevelopmental disorder with multifactorial aetiology. In autism, gut dysbiosis correlates with symptom severity and is characterised by a reduced bacterial variability and a diminished beneficial commensal relationship. Microbiota can influence the expression of host microRNAs that, in turn, regulate the growth of intestinal bacteria by means of bidirectional host-gut microbiota cross-talk. We investigated possible interactions among intestinal microbes and between them and host transcriptional modulators in autism. To this purpose, we analysed, by "omics" technologies, faecal microbiome, mycobiome, and small non-coding-RNAs (particularly miRNAs and piRNAs) of children with autism and neurotypical development. Patients displayed gut dysbiosis related to a reduction of healthy gut micro- and mycobiota as well as up-regulated transcriptional modulators. The targets of dysregulated non-coding-RNAs are involved in intestinal permeability, inflammation, and autism. Furthermore, microbial families, underrepresented in patients, participate in the production of human essential metabolites negatively influencing the health condition. Here, we propose a novel approach to analyse faeces as a whole, and for the first time, we detected miRNAs and piRNAs in faecal samples of patients with autism.

Keywords: autism spectrum disorders; gene-environment interaction; host–gut microbiota cross-talk; microRNAs; microbiome; multi-omics; mycobiome; piRNAs.

PubMed Disclaimer

Conflict of interest statement

The authors declare that there is no conflict of interest.

Figures

Figure 1
Figure 1
Alpha diversity analysis. Alpha diversity analysis with Shannon and Simpson indices of 16S (a) and 18S (b).
Figure 2
Figure 2
Venn diagrams of (a) microbiota and (b) mycobiota taxonomic analysis. In black, common families between ASD and Ctrl samples; in red, families mainly present in Ctrls; in green, families characterising the ASD group.
Figure 3
Figure 3
Bacteria (up) and fungi (down) genera relative abundance.
Figure 4
Figure 4
Distribution of the sncRNA fraction in stool samples. SncRNAs are equally distributed among samples from ASD patients (ASD1–6) and controls (CSV7–13). Data are expressed as percentage of the number of sncRNA per class.
Figure 5
Figure 5
Functional annotation of miRNA and piRNA target genes from KEGG (a) and MSigDB-Hallmark (b).
Figure 6
Figure 6
Microorganism composition of the couples of siblings. Microbiota composition, expressed as abundance fractions, in couple #1 (a) and in couple #2 (b); Mycobiota in (c) for couple #1 and in (d) couple #2. Families are red squared if increased in ASD sample and black squared if decreased.

References

    1. Bougeard C., Picarel-Blanchot F., Schmid R., Campbell R., Buitelaar J. Prevalence of Autism Spectrum Disorder and Co-morbidities in Children and Adolescents: A Systematic Literature Review. Front. Psychiatry. 2021;12:744709. doi: 10.3389/fpsyt.2021.744709. - DOI - PMC - PubMed
    1. Mezzelani A., Landini M., Facchiano F., Raggi M.E., Villa L., Molteni M., de Santis B., Brera C., Caroli A.M., Milanesi L., et al. Environment, dysbiosis, immunity and sex-specific susceptibility: A translational hypothesis for regressive autism pathogenesis. Nutr. Neurosci. 2015;18:145–161. doi: 10.1179/1476830513Y.0000000108. - DOI - PMC - PubMed
    1. Troisi J., Autio R., Beopoulos T., Bravaccio C., Carraturo F., Corrivetti G., Cunningham S., Devane S., Fallin D., Fetissov S., et al. Genome, Environment, Microbiome and Metabolome in Autism (GEMMA) Study Design: Biomarkers Identification for Precision Treatment and Primary Prevention of Autism Spectrum Disorders by an Integrated Multi-Omics Systems Biology Approach. Brain Sci. 2020;10:743. doi: 10.3390/brainsci10100743. - DOI - PMC - PubMed
    1. Maenner M.J., Shaw K.A., Baio J., Washington A., Patrick M., DiRienzo M., Christensen D.L., Wiggins L.D., Pettygrove S., Andrews J.G., et al. Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years—Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016. Morb. Mortal. Wkly. Rep. Surveill. Summ. 2020;69:1–12. doi: 10.15585/mmwr.ss6904a1. - DOI - PMC - PubMed
    1. Chaste P., Leboyer M. Autism risk factors: Genes, environment, and gene-environment interactions. Dialogues Clin. Neurosci. 2012;14:281–292. doi: 10.31887/DCNS.2012.14.3/pchaste. - DOI - PMC - PubMed

Grants and funding