Machine Learning Leveraging Genomes from Metagenomes Identifies Influential Antibiotic Resistance Genes in the Infant Gut Microbiome

Rahman, Sumayah F.; Olm, Matthew R.; Morowitz, Michael J.; Banfield, Jillian F.

doi:10.1128/msystems.00123-17

Cited by 80 publications

(63 citation statements)

References 70 publications

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“…We have previously shown that formula feeding also promotes CDI in neonatal piglets and the expansion of naturally colonizing CD in FP piglets [12]. This is in line with studies in formula-fed infants showing a higher intestinal colonization with CD and E. coli as compared to breast-fed infants [18,19]. Breastmilk is considered the gold standard for infant nutrition and this same is true for neonatal piglets.…”

Section: Discussionsupporting

confidence: 79%

Formula-fed and Clostridioides difficile infected neonatal piglets carry a highly diverse and abundant set of antimicrobial resistance genes

Pieper

Dadi

Grześkowiak

et al. 2020

Preprint

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Background Clostridioides difficile infection (CDI) is an increasing zoonotic health threat and has also been documented as a cause of enteritis outbreaks in neonatal pigs. Furthermore, CDI in neonatal piglets cause changes in microbial gut colonization. We hypothesized that an imbalanced microbial colonization in piglets with CDI could be associated with an altered abundance of antimicrobial resistance genes.Results We analyzed fecal metagenomic data of lactating sows (S), their piglets during suckling (SP), the same piglets two weeks after weaning (WP), 5-day old artificially reared and formula-fed siblings (FP) and FP infected with C. difficile (FP-CD) for microbiota composition and antimicrobial resistance gene abundance. FP and FP-CD piglets had an immature-type microbiota and increased abundance of antimicrobial resistance genes. A co-occurrence of genes encoding for resistance against aminoglycosides (e.g. aph(3”)-lb, aph(6)-ld, ant(2”)-la), β-lactams (blaCTX−M, blaTEM), fluoroquinolones (pat(A) macrolides (mph(A)), sulfonamides (sul1, sul2), polypeptides (e.g. pmrB, pmrC, arnA, bac(A)) and tetracyclines (e.g. tet(A-D),) was observed. A strong association between Escherichia, Streptococcus, Shigella, Enterococcus and Fusobacterium taxa with the expansion of the resistome in FP and FP-CD piglets were found.Conclusion Increased abundance of antimicrobial resistance genes in formula feeding and concomitant CDI may be associated with therapeutic resistance later in life and warrant further studies.

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Section: Discussionsupporting

confidence: 79%

Formula-fed and Clostridioides difficile infected neonatal piglets carry a highly diverse and abundant set of antimicrobial resistance genes

Pieper

Dadi

Grześkowiak

et al. 2020

Preprint

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“…Other covariates and early-life factors may alter the trajectory of the microbiome and indirectly impact the resistome Feeding method has been considered one of the most important factors in microbial and metabolic development [29,32], but we found little evidence to suggest its impact directly on the resistome. A previous study in preterm infants [21] identi ed class D beta-lactamase genes to be enriched in formula fed infants which were most frequently identi ed in Clostridium di cile. We did not nd class D betalactamase genes in infants who were formula fed.…”

Section: Delivery Mode and Not Intrapartum Antibiotic Exposure Contrimentioning

confidence: 99%

“…These ndings have motivated studies to explore early-drivers that shape the resistome beyond infant antibiotic usage. Factors that have speci cally been assessed in relation to the infant gut resistome include age of the infant [11,18,19], type of delivery [15,20], breast versus formula feeding [21], gestational age [11,13,21], and intrapartum antibiotic usage [19]. Prior investigations assessing how early-life factors impact the resistome have focused on preterm infants [11,13,22] or were based on small cohorts (< 50) of full term infants [8,12,14,[17][18][19].…”

Section: Introductionmentioning

confidence: 99%

The Infant Gut Resistome is Associated with E. coli and Early-life Exposures

Lebeaux

Coker

Dade

et al. 2020

Preprint

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Background: Antibiotic resistance is an increasing threat to human health. The human gut microbiome harbors a collection of bacterial antimicrobial resistance genes (ARGs) known as the resistome. The factors associated with establishment of the resistome in early life are not well understood and clarifying these factors would inform strategies to decrease antibiotic resistance. We investigated the early-life exposures and taxonomic signatures associated with resistome development over the first year of life in a large, prospective cohort in the United States. Shotgun metagenomic sequencing was used to profile both microbial composition and ARGs in stool samples collected at 6 weeks and 1 year of age from infants enrolled in the New Hampshire Birth Cohort Study. Negative binomial regression and statistical modeling was used to examine infant factors such as sex, delivery mode, feeding method, gestational age, antibiotic exposure, and infant gut microbiome composition in relation to the diversity and relative abundance of ARGs.Results: Metagenomic sequencing was performed on paired samples from 195 full term (at least 37 weeks’ gestation) and 15 late preterm (33-36 weeks’ gestation) infants. 6-week samples compared to 1-year samples had 4.37 times (95% CI: 3.54-5.39) the rate of harboring ARGs. The majority of ARGs that were at a greater relative abundance at 6 weeks (chi-squared p < 0.01) worked through the mechanism of antibiotic efflux (i.e., by pumping antibiotics out of the cell). The overall relative abundance of the resistome was strongly correlated with Proteobacteria (Spearman correlation = 78.9%) and specifically E. coli (62.2%) relative abundance in the gut microbiome. Among infant characteristics, delivery mode was most strongly associated with the diversity and relative abundance of ARGs. Infants born via cesarean delivery had a higher risk of harboring unique ARGs [relative risk = 1.12 (95% CI: 0.97 – 1.29)] as well as a having an increased risk for overall ARG relative abundance [relative risk = 1.43 (95% CI: 1.12 – 1.84)] at 1 year compared to infants born vaginally. Additionally, 6 specific ARGs were at a greater relative abundance in infants delivered by cesarean section compared to vaginally delivered infants across both time points. Conclusions: Our findings suggest that the developing infant gut resistome may be alterable by early-life exposures. Establishing the extent to which infant characteristics and early-life exposures impact the resistome can ultimately lead to interventions that decrease the transmission of ARGs and thus the possibility of antibiotic resistant life threatening infections.

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“…Reducing dimensionality from 10 million to two dimensions only enabled visualization of data on a standard two-dimensional scatter-plot (i.e., PCA plot) showing a clear distinction between the microbiota of Danish and Chinese donors. In another study, the top five PCs of individual bacteria's genome (sequenced from infant fecal samples) were used to create a classifier for predicting antibiotic resistance (Rahman et al, 2018).…”

Section: Dimensionality Reductionmentioning

confidence: 99%

The Computational Diet: A Review of Computational Methods Across Diet, Microbiome, and Health

et al. 2020

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Food and human health are inextricably linked. As such, revolutionary impacts on health have been derived from advances in the production and distribution of food relating to food safety and fortification with micronutrients. During the past two decades, it has become apparent that the human microbiome has the potential to modulate health, including in ways that may be related to diet and the composition of specific foods. Despite the excitement and potential surrounding this area, the complexity of the gut microbiome, the chemical composition of food, and their interplay in situ remains a daunting task to fully understand. However, recent advances in high-throughput sequencing, metabolomics profiling, compositional analysis of food, and the emergence of electronic health records provide new sources of data that can contribute to addressing this challenge. Computational science will play an essential role in this effort as it will provide the foundation to integrate these data layers and derive insights capable of revealing and understanding the complex interactions between diet, gut microbiome, and health. Here, we review the current knowledge on diet-health-gut microbiota, relevant data sources, bioinformatics tools, machine learning capabilities, as well as the intellectual property and legislative regulatory landscape. We provide guidance on employing machine learning and data analytics, identify gaps in current methods, and describe new scenarios to be unlocked in the next few years in the context of current knowledge.

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Machine Learning Leveraging Genomes from Metagenomes Identifies Influential Antibiotic Resistance Genes in the Infant Gut Microbiome

Cited by 80 publications

References 70 publications

Formula-fed and Clostridioides difficile infected neonatal piglets carry a highly diverse and abundant set of antimicrobial resistance genes

Formula-fed and Clostridioides difficile infected neonatal piglets carry a highly diverse and abundant set of antimicrobial resistance genes

The Infant Gut Resistome is Associated with E. coli and Early-life Exposures

The Computational Diet: A Review of Computational Methods Across Diet, Microbiome, and Health

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