Biology subjects

Bonham, K. S.

Publications and source records attributed to Bonham, K. S..

6 recordsLinked to original sources

bioRxiv2025

Microbiome-behavior coupling shapes infant adaptation to early maternal unpredictability

We asked whether infant microbiome composition, together with infants behavioral responses to early maternal unpredictability, can offer novel mechanistic insights into behavioral phenotypic variation in human development. Maternal unpredictability was computed as the entropy rate of transitions among maternal sensory signals during naturalistic mother-infant interaction (n=256 dyads; 2-6 months). Infant visual orienting behavior (VOB) was indexed by infants simultaneous gaze shifts to and from the mother. Higher maternal unpredictability predicted more frequent VOB shifts, indicating a mature-for-age profile, and longitudinally forecast poorer inhibitory control at 19-28 months. A subgroup of infants with high maternal unpredictability and high VOB had inhibitory control outcomes closer to those of infants who experienced low maternal unpredictability, suggesting VOB strategy might buffer against the effects of high maternal unpredictability. In participants with metagenomic data (n=93), VOB was associated with taxonomic and functional gut microbial profiles along a Bifidobacterium breve to Bifidobacterium longum axis. Neuroactive gene-set enrichment analysis linked VOB to increase in tryptophan synthesis and glutamate synthesis genes. In contrast, maternal unpredictability showed depletions of GABA and tryptophan synthesis in the unique-effects model and, when VOB and the maternal unpredictability by VOB term were included, enrichment of acetate synthesis and quinolinic acid degradation. Notably, the maternal unpredictability by VOB interactions for tryptophan and glutamate were negative, indicating that the VOB-pathway coupling attenuates as unpredictability increases. Together, these findings support a framework in which maternal unpredictability is the environmental challenge, infant VOB expresses the behavioral strategy, and microbial metabolism modulates whether that strategy is biochemically feasible. TeaserInfant gut microbiome is linked to infant behavioral responses to maternal unpredictability, which in turn impacts how they learn to control their actions.

neuroscience↗

bioRxiv2024

Early life microbial succession in the gut follows common patterns in humans across the globe

Characterizing the dynamics of microbial community succession in the infant gut microbiome is crucial for understanding child health and development, but no normative model currently exists. Here, we estimate child age using gut microbial taxonomic relative abundances from metagenomes, with high temporal resolution ({+/-}3 months) for the first 1.5 years of life. Using 3,154 samples from 1,827 infants across 12 countries, we trained a random forest model, achieving a root mean square error of 2.61 months. We identified key taxonomic predictors of age, including declines in Bifidobacterium spp. and increases in Faecalibacterium prausnitzii and Lachnospiraceae. Microbial succession patterns are conserved across infants from diverse human populations, suggesting universal developmental trajectories. Functional analysis confirmed trends in key microbial genes involved in feeding transitions and dietary exposures. This model provides a normative benchmark of "microbiome age" for assessing early gut maturation that can be used alongside other measures of child development.

microbiology↗

bioRxiv2022

Microclimate is a strong predictor of the native and invasive plant-associated soil microbiota on San Cristobal Island, Galapagos archipelago

Understanding the major drivers that influence soil bacterial and fungal communities is essential to mitigate the impacts of human activity on vulnerable ecosystems, like those found on the Galapagos Islands. Located ~1000 km off the coast of Ecuador, the volcanically formed islands are situated within distinct oceanic currents, which provide seasonal weather patterns and unique microclimates within small spatial scales across the islands. Although much is known about the impacts of human activity, such as climate change and invasive plant species, on above ground biodiversity of the Galapagos Islands, little is known about the resident soil microbial communities and the drivers that shape these communities. Here, our goal was to investigate the bacterial and fungal communities found in soil located in three distinct microclimates: Mirador (arid), Cerro Alto (transition zone), and El Junco (humid), and associated with native and invasive plant types. At each site, we collected soil at three depths (rhizosphere, 5 cm, and 15 cm) associated with the invasive plant, Psidium guajava (guava), and native plant types. We determined that the sampling location (microclimate) was the strongest driver of both bacterial and fungal communities (74 and 38%, respectively), with additional minor but significant impacts from plant type and soil depth. This study highlights the continued need to explore microbial communities across diverse environments and demonstrates the weight of different abiotic and biotic factors impacting soil microbial communities across San Cristobal Island in the Galapagos archipelago. IMPORTANCE/SIGNIFICANCEHuman activity such as climate change, pollution, introduction of invasive species, and deforestation, poses a huge threat to biodiverse environments. Soil microbiota are an essential component to maintaining healthy ecosystems. However, a greater understanding of factors that alter these microbial communities is needed in order to find ways to mitigate and reverse the impacts imposed by human activity. The Galapagos Islands are a unique real-world laboratory, in that the islands biogeography and physical locations in the Pacific Ocean provide distinct microclimates within small geographic distances. Harnessing these distinct environments allowed us to investigate the influence of microclimates, soil depth, and vegetation cover on bacterial and fungal community composition.

microbiology↗

bioRxiv2021

Targeted high-resolution taxonomic identification of Bifidobacterium longum subsp. infantis using human milk oligosaccharide metabolizing genes

Bifidobacterium longum subsp. infantis (B. infantis) is one of a few microorganisms capable of metabolizing human breast milk and is a pioneer colonizer in the guts of breastfed infants. One current challenge is differentiating B. infantis from its close relatives, B. longum and B. suis. All three organisms are classified in the same species group but only B. infantis can metabolize human milk oligosaccharides (HMOs). We compared HMO-metabolizing genes across different Bifidobacterium genomes and developed B. infantis-specific primers to determine if the genes alone or the primers can be used to quickly characterize B. infantis. We showed that B. infantis is uniquely identified by the presence of five HMO-metabolizing gene clusters, tested for its prevalence in infant gut metagenomes, and validated the results using the B. infantis-specific primers. We observed that only 15 of 203 (7.4%) children under 2 years old from a cohort of US children harbored B. infantis. These results highlight the importance of developing and improving approaches to identify B. infantis. A more accurate characterization may provide insights into regional differences of B. infantis prevalence in infant gut microbiota.

microbiology↗

bioRxiv2021

Comparative analysis of 16S rRNA gene and metagenome sequencing in pediatric gut microbiomes

The colonization of the human gut microbiome begins at birth, and, over time, these microbial communities become increasingly complex. Most of what we currently know about the human microbiome, especially in early stages of development, was described using culture-independent sequencing methods that allow us to identify the taxonomic composition of microbial communities using genomic techniques, such as amplicon or shotgun metagenomic sequencing. Each method has distinct tradeoffs, but there has not been a direct comparison of the utility of these methods in stool samples from very young children, which have different features than those of adults. We compared the effects of profiling the human infant gut microbiome with 16S rRNA amplicon versus shotgun metagenomic sequencing techniques in 130 fecal samples; younger than 15, 15-30, and older than 30 months of age. We demonstrate that observed changes in alpha-diversity and beta-diversity with age occur to similar extents using both profiling methods. We also show that 16S rRNA profiling identified a larger number of genera and we find several genera that are missed or underrepresented by each profiling method. We present the link between alpha diversity and shotgun metagenomic sequencing depth for children of different ages. These findings provide a guide for selecting an appropriate method and sequencing depth for the three studied age groups.

microbiology↗

bioRxiv2020

Gut microbial genes are associated with neurocognition and brain development in healthy children

The gastrointestinal tract, its resident microorganisms, and the central nervous system are connected by bio-chemical signaling, also known as the "microbiome-gut-brain-axis." Both the human brain and the gut microbiome have critical developmental windows in the first years of life, raising the possibility that their development is co-occurring and likely co-dependent. Emerging evidence implicates gut microorganisms and microbiota composition in cognitive outcomes and neurodevelopmental disorders (e.g., autism and anxiety), but the influence of gut microbial metabolism on typical neurodevelopment has not been explored in detail. We investigated the relationship of the microbiome with the neuroanatomy and cognitive function of 361 healthy children, demonstrating that differences in gut microbial taxa and gene functions are associated with overall cognitive function and with differences in the size of multiple brain regions. Using a combination of multivariate linear and machine learning (ML) models, we showed that many species, including Gordonibacter pamelae and Blautia wexlerae, were significantly associated with higher cognitive function, while some species such as Ruminococcus gnavus were more commonly found in children with low cognitive scores after controlling for sociodemographic factors. Microbial genes for enzymes involved in the metabolism of neuroactive compounds, particularly short-chain fatty acids such as acetate and propionate, were also associated with cognitive function. In addition, ML models were able to use microbial taxa to predict the volume of brain regions, and many taxa that were identified as important in predicting cognitive function also dominated the feature importance metric for individual brain regions. For example, B. wexlerae was the most important species in models predicting the size of the parahippocampal region in both the left and right hemispheres, while several species from the phylum Bacteroidetes, including GABA-producing B. ovatus, were important for predicting the size of the left accumbens area, but not the right. These findings provide potential biomarkers of neurocognition and brain development and may lead to the future development of targets for early detection and early intervention.

microbiology↗