Mobilizable antibiotic resistance genes are present in dust microbial communities

Maamar, Sarah Ben; Glawe, A.; Brown, Taylor K; Hellgeth, Nancy; Hu, Jinglin; Wang, Ji Ping; Huttenhower, Curtis; Hartmann, Erica M.

doi:10.1371/journal.ppat.1008211

Cited by 26 publications

(26 citation statements)

References 82 publications

(127 reference statements)

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“…Statistically signi cant results (q-value < 0.25) were queried for MGEs. Speci cally, the terms "integrase", "integron", transpos", or plasmid" were used for the query as they previously have been used to identify MGE elements from HUMAnN2 results [63]. Since we found these MGEs to only be associated with sample age, we assessed the species speci c contribution to each MGE broken down by sample age using the "humann2_barplot" script from HUMAnN2.…”

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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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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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“…Metagenomics have already been implemented in the surveillance of ARGs in various environments. Metagenomic studies of built environments have shown that dust in homes harbors significantly higher ARGs compared to drinking water (Maamar et al, 2020). The authors also detected plasmid borne ARG lnuA (resistance to lincosamides) which was further confirmed in vitro.…”

Section: Metagenomic Approaches For Resistome Surveillancementioning

confidence: 74%

Current Trends in Experimental and Computational Approaches to Combat Antimicrobial Resistance

et al. 2020

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A multitude of factors, such as drug misuse, lack of strong regulatory measures, improper sewage disposal, and low-quality medicine and medications, have been attributed to the emergence of drug resistant microbes. The emergence and outbreaks of multidrug resistance to last-line antibiotics has become quite common. This is further fueled by the slow rate of drug development and the lack of effective resistome surveillance systems. In this review, we provide insights into the recent advances made in computational approaches for the surveillance of antibiotic resistomes, as well as experimental formulation of combinatorial drugs. We explore the multiple roles of antibiotics in nature and the current status of combinatorial and adjuvant-based antibiotic treatments with nanoparticles, phytochemical, and other non-antibiotics based on synergetic effects. Furthermore, advancements in machine learning algorithms could also be applied to combat the spread of antibiotic resistance. Development of resistance to new antibiotics is quite rapid. Hence, we review the recent literature on discoveries of novel antibiotic resistant genes though shotgun and expression-based metagenomics. To decelerate the spread of antibiotic resistant genes, surveillance of the resistome is of utmost importance. Therefore, we discuss integrative applications of whole-genome sequencing and metagenomics together with machine learning models as a means for state-of-the-art surveillance of the antibiotic resistome. We further explore the interactions and negative effects between antibiotics and microbiomes upon drug administration.

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“…Similarly, analysis of the inverted repeats (IRs) involved analysis of imperfect IRs in both the oriT query and alignment hit datasets and removal of oriT hits lacking IRs similar to those in the query set. The Matlab package detectIR v2016-01-19 79 was used with IR size limits of (6,15) bp and containing at most 2 mismatches. Consequently, 11,497 (57%) of the initially identified 20,255 oriT hits were retained after quality testing.…”

Section: Quality Testing Of Orit-strast Alignment Hitsmentioning

confidence: 99%

“…Horizontal gene transfer of antibiotic resistance (AMR) genes occurs via the processes of transformation and conjugation. The former mediates especially narrow range, intra-genus transfers 1,2 , whereas the latter is implicated in a wider range of transfer hosts 3,4 and potentially enables AMR to overcome the toughest phylogenetic and ecological transmission barriers [5][6][7][8][9][10] .…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, the interaction between conjugative relaxase enzymes and their DNA origin-of-transfer (oriT) substrates facilitates the majority of all AMR transfers in nature 11,12 and is especially important for ones related to human infection complications 13 . However, the current knowledge on conjugative transfer mechanisms and systems 4,[14][15][16] is unable to describe the unprecedented amount of observed horizontal transfer 7,8,12,17 that seems to transcend all transfer barriers between resistance reservoirs and human hosts [5][6][7]9,10,12,13,18 .…”

Section: Introductionmentioning

confidence: 99%

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Multiple plasmid origin-of-transfer substrates enable the spread of natural antimicrobial resistance to human pathogens

Zrimec

2020

Preprint

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Antimicrobial resistance poses a great danger to humanity, in part due to the widespread horizontal transfer of plasmids via conjugation. Modeling of plasmid transfer is essential to uncovering the fundamentals of resistance transfer and for development of predictive measures to limit the spread of resistance. However, a major limitation in the current understanding of plasmids is the inadequate characterization of the DNA transfer mechanisms, which conceals the actual potential for plasmid transfer in nature. Here, we consider that the plasmid-borne origin-of-transfer substrates encode specific DNA structural properties that can facilitate finding these regions in large datasets, and develop a DNA structure-based alignment procedure for typing the transfer substrates. Since our method outperforms current sequence-based approaches, we identify thousands of yet undiscovered DNA transfer substrates, showing that plasmid mobility is in fact 2-fold higher and spans almost 2-fold more host species than is currently known. Over half of all mobile plasmids contain the means to transfer between different mobility groups, which links previously confined host ranges across ecological habitats into a vast network of potential plasmid transfers. Certain types of conjugative transfer mechanisms and their corresponding hosts are transfer hubs that help break down the horizontal gene transfer barriers and form a robust gene flow system. We show that this network in fact serves to transfer resistance from the environmental genetic reservoirs to human MDR pathogens, which is an important driver of the observed rapid resistance development in humans and thus an important point of focus for future prevention measures.

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Mobilizable antibiotic resistance genes are present in dust microbial communities

Cited by 26 publications

References 82 publications

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

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

Current Trends in Experimental and Computational Approaches to Combat Antimicrobial Resistance

Multiple plasmid origin-of-transfer substrates enable the spread of natural antimicrobial resistance to human pathogens

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