Premature Infant Gut Microbiome relationships with childhood behavioral scales: preliminary insights

IntroductionVery Low Birth Weight (VLBW) infants, born weighing less than 1,500 grams, are at risk for both gut dysbiosis and later neuropsychological developmental deficits. Behavioral effects, while related to neurodevelopment, are often more subtle and difficult to measure. The extent of later neurobehavioral consequences associated with such microbial dysbiosis has yet to be determined. We explored associations between the infants’ gut microbiome and early childhood behavior at 4 years of age and identified the bacterial taxa through a multivariate analysis by linear models.MethodsParents completed the Child Behavior Checklist (CBCL) focused on different DSM diagnostic categories: affective, anxiety, pervasive developmental, attention deficit/hyperactivity, and oppositional defiant. All the CBCL scores were corrected for gender, delivery method, gestational age, infant birth weight, occurrence of sepsis, and days on antibiotics prior statistical analyses. Canonical correlation analysis (CCA) was performed to determine the relationship between early life gut microbiome and the adjusted CBCL scores. The association of bacterial Amplicon sequence Variants (ASVs) to the CBCL scores were tested with multivariate analysis by linear models (MaAsLin).ResultsNineteen children who were previously born with very low birth weight and studied while hospitalized in the Neonatal Intensive Care Unit (NICU) were included in this study. Statistically significant associations were observed between early life gut bacteria such as Veillonella dispar, Enterococcus, Escherichia coli, and Rumincococcus to later behavior at 4 years. No significant association could be observed with early-life gut microbiome alpha diversity and behavioral measures at 4 years.DiscussionThese preliminary observational data provide insight into the relationships between VLBW gut microbiome dysbiosis and childhood behavior. This study contributes to the literature on gut microbiome analysis by examining various behavioral domains using a standardized tool linked to the Diagnostic and Statistical Manual of Mental Disorders (DSM)

Details of the samples and their corresponding locations

<div>The file contains the details of the 92 samples studied here, including their location, region and the physical factors of each of the sampling locations</div

Putative core OTUs in Indian population

This file contains the sequences of 37 OTUs which were observed in all the samples and forms the putative core microbiome in the Indian population

92samples_original_sequences

This file contains the original fasta sequences dataset from each of the 92 samples studied here. The filename indicates its population affiliation

Human salivary microbiome diversity in India

This dataset comprise of various DNA fasta files and tables for studying human salivary microbiome diversity in Indi

Distribution of bacterial genera among the samples

This file contains the bacterial genera counts observed in each of the 92 samples. A total of 165 bacterial genera were observed. However, after removing the potential contaminants only 136 bacteral genera were retained which are listed on this table

OTUs sequences

This file contains the sequences of the 716 OTUs obtained after all the filtration and clustering steps including contaminants removal

OTUs distribution among the studied samples

This file contains the distribution of observed OTUs across all the studied samples. A total of 785 OTUs were observed, however, upon removing the potential contaminants, only 716 OTUs were retained which are listed in this tabl

Unraveling the human salivary microbiome diversity in Indian populations

<div><p>The importance of studying the salivary microbiome has been highlighted for its connection to health and disease and as a potential tool for supplementing human genetic diversity studies. While the salivary microbiome has been studied in various world populations, Indian populations have not been examined. We therefore analyzed microbiome diversity in saliva samples from 92 volunteers from eight different sampling locations in India by amplifying and sequencing variable regions (V1 and V2) of the bacterial 16S rRNA gene. The results showed immense bacterial richness in Indian populations; we identified 165 bacterial genera and 785 unique Operational Taxonomic Units (OTUs), with substantial sharing among the populations. There were small, but significant correlations in the abundance of bacterial genera in sampling locations from the same geographic region. Most of the core OTUs detected were also observed previously in other populations, but Solobacterium spp., Lachnoanaerobaculum spp. and Alloprevotella spp. were observed to be a component of the saliva microbiome unique to Indian populations. Importantly, nine bacterial genera were observed that were not listed in the Human Oral Microbiome Database (HOMD). These results highlight the importance of analyzing underrepresented populations like those of India.</p></div