Active Ingredients: Amoxicillin
There were 1. In contrast to the metagenomic data, metatranscriptomics cannot describe the structure of the community, but it can identify the portion of the total genes actively transcribed by the microbiome.
In the metatranscriptomic data, there were 3.
This discrepancy could indicate that many of the ARGs encoded in the microbiome are not actively transcribed with or without drug pressure. Resistome Diversity Two of the antibiotics examined, amoxicillin and ciprofloxacin, had unique impacts on the taxonomic composition of the microbiome resulting in corresponding shifts in the resistome diversity at the DNA level.
However, these shifts in ARG diversity profiles did not necessarily reflect a drug specific selection but rather resulted from the overall shift in microbiome composition.
We found that while treatment induced changes in alpha diversity of the resistome at the DNA level, it did not impact resistome alpha diversity at the RNA level Figure 2 B.
The lower and more stable alpha diversity of the RNA reads compared to the DNA reads likely stems from the fact that many of the genes detected in the metagenomics are not actively transcribed under vehicle or antibiotic treatment.
Antibiotics have variable impacts on the diversity and structure of the resistome. For example, the beta-lactam resistance class was not increased with amoxicillin. Instead, we report that the only significant changes in ARG classes were an increase in kasugamycin class ARGs in response to amoxicillin treatment, decreases in the fosmidomycin and trimethoprim classes in response to ciprofloxacin treatment, and a decrease in the fosmidomycin class in response to doxycycline treatment Figure 3 A.
Differential abundance of antibiotic resistance gene classes.
Changes in ARG class abundances after antibiotic treatment observed in A metagenomic and B metatranscriptomic data. Overall, there were a number of significant changes in ARG classes against beta-lactams, fosmidomycin, polymyxin, and trimethoprim in response to amoxicillin treatment, triclosan in response to ciprofloxacin treatment, and fosfomycin, rifampin, and tetracycline in response to doxycycline treatment.
Thus, in contrast to the metagenomic data, metatranscriptomics shows a significant increase in ARG classes that are targeted to the antibiotic treatment and have the potential to provide a fitness advantage to members of the gut microbiota.
ARG Level Changes in Response to Antibiotics Results from the differential abundance analysis show that the antibiotics tested have variable impacts on the abundance of AR genes and transcripts.
At the metagenomic level, we found a set of differentially abundant genes that appeared general and unrelated to the antibiotic utilized. In contrast, the transcriptional response was much narrower and in the case of amoxicillin and doxycycline, it appears that antibiotic therapy promoted genes directly targeted to the drug utilized.
This dichotomy between DNA and RNA level responses could not have been detected without using a dual sequencing approach.
Overall, there were fewer differentially abundant ARG transcripts 21 transcripts found in the metatranscriptomic analysis compared to the number of differentially abundant ARGs 116 genes in the metagenomic data Figures 4 A—F.
This is a reflection of the fewer ARG reads found in the metatranscriptomic data, as well as the more specific response of the microbiome at a transcriptional level compared to the broad metagenomic changes.
This is best exemplified by changes in ARGs targeted to antibiotics, specifically amoxicillin and doxycycline.
Differential abundance of antibiotic resistance genes. We found 56 significantly elevated or reduced ARGs after amoxicillin treatment. In addition to drug targeted genes, we also found increases in a much larger set of untargeted genes 42 genes.