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Resistance in Focus: The Role of blaTEM-1 in E. coli

Study reveals genetic variations in blaTEM-1 and their impact on antibiotic resistance.

Nicole Stoesser, W. Matlock, G. Rodger, E. Pritchard, M. Colpus, N. Kapel, L. Barrett, M. Morgan, S. Oakley, K. L. Hopkins, A. Roohi, D. Karageorgopoulos, M. B. Avison, A. S. Walker, S. Lipworth

― 6 min read


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Table of Contents

In 1965, a specific gene called blaTEM-1 was found in a type of bacteria called Escherichia coli, which causes infections in humans. This gene helps bacteria resist certain antibiotics known as beta-lactams, including penicillin. Over the years, the way this gene spreads among bacteria has changed. It has moved not just between bacteria but also through tiny DNA pieces called Plasmids and transposons. Currently, many strains of E. Coli and other bacteria carry this gene, making it a significant issue for healthcare.

In the UK, doctors often use a combination of antibiotics and other substances to treat severe infections. Co-amoxiclav, which includes amoxicillin and clavulanic acid, is one of the first choices for treatment. Doctors determine how effective this treatment can be by measuring the Minimum Inhibitory Concentration (MIC), the lowest amount of a drug needed to stop bacterial growth. However, the presence of the blaTEM-1 gene can make it harder to predict how well the treatment will work.

One challenge with blaTEM-1 is that it behaves differently in various bacteria. The location of the gene, how many copies of it are present, and other minor genetic changes affect the level of resistance. Some research shows that different strains of E. coli can have very different responses to the same antibiotic based on these factors.

Study Overview

This study looks at how the blaTEM-1 gene works in nearly 400 clinical isolates of E. coli taken from blood infections. The researchers aimed to understand better how the gene's variation affects resistance to co-amoxiclav by studying how many copies of the gene are present and how much of it is expressed.

Isolate Selection

The research team started with 548 E. coli samples collected from patients over five years. They specifically chose samples that only had the blaTEM-1 gene and no other similar genes. They ended up with 377 usable samples after filtering out those that didn’t meet their criteria.

DNA Extraction and Sequencing

To study these bacteria, the team extracted their DNA and then used advanced methods to sequence it. They combined different sequencing technologies to gather detailed genetic information, ensuring the data was accurate and reliable.

Dataset Curation and Genome Assembly

The researchers processed and organized the sequencing data carefully to build a complete picture of the genomes they were studying. They used several bioinformatics tools to assemble and analyze the genomes, which allowed them to identify the presence and location of the blaTEM-1 gene across different samples.

Antibiotic Susceptibility Testing

Next, they tested how sensitive these bacteria were to co-amoxiclav. This testing helps determine which strains are resistant and to what degree. The results showed a wide range of resistance levels, indicating that some bacteria could resist treatment much better than others.

Generation of cDNA Template

To study how much of the blaTEM-1 gene is expressed in the bacteria, they extracted RNA and reversed it into complementary DNA (cDNA). This step is crucial because it allows for the measurement of gene activity.

qPCR Quantification of blaTEM-1 Expression

The researchers designed a process to measure the expression of the blaTEM-1 gene in a select group of samples. They used a technique called quantitative PCR (qPCR) to determine how much of the gene was active in each bacterium. This step is essential for understanding how well the bacteria can resist antibiotics.

Assembly Annotations

The genetic information was further annotated to pinpoint the specific functions of different genes. The team mapped out the locations of various Antibiotic Resistance genes and predicted how they might behave in the bacteria.

SNV Analysis

They also looked for small genetic changes, called single nucleotide variants (SNVs), in the blaTEM-1 gene and associated regions. These tiny changes can have significant effects on how the gene functions and how bacteria respond to treatment.

Contig Copy Number

To understand the number of gene copies in each sample, they analyzed the depth of the sequencing data. This measurement gives insight into how many copies of the blaTEM-1 gene are present, particularly in plasmids, which can replicate independently.

Chromosomal Core Gene Phylogeny

The researchers built a tree-like diagram to show how these bacteria are related based on their genetic makeup. This analysis helps reveal patterns in how the blaTEM-1 gene spreads among different strains of E. coli.

Statistical Analysis and Visualization

Using statistical methods, the team analyzed the data to find relationships between the genetic features and how well the bacteria resisted co-amoxiclav. They created visual representations of their findings to illustrate the connections they made.

Results

The study found a diverse range of E. coli strains carrying the blaTEM-1 gene. The gene was often located on plasmids, which can be easily shared among bacteria, increasing the spread of resistance. The research revealed that some bacterial strains expressed the blaTEM-1 gene more than others, leading to higher resistance levels against co-amoxiclav.

The team discovered specific mutations in the promoter regions of the blaTEM-1 gene that affected its expression. Strains with certain mutations showed higher gene activity, leading to increased resistance.

Discussion

The findings emphasize the importance of understanding how genetic variations in the blaTEM-1 gene influence antibiotic resistance. The researchers highlighted that the ability of a strain of E. coli to resist treatment is not solely dependent on the presence of the resistance gene but also on how much the gene is expressed.

The study also pointed out that E. coli strains with higher expression of blaTEM-1 are more likely to be successful in clinical settings. The relationship between genetic background and resistance gives insights into how certain bacterial lineages thrive in the presence of antibiotics.

Limitations

The researchers acknowledged several limitations in their study. They noted that due to the nature of the data, some conclusions might be constrained by the complexity of bacterial genomes and their behavior in different environments. Additionally, the study focused on a subset of isolates, limiting the scope of their findings.

Future Directions

The researchers proposed several areas for future study. They suggested focusing on specific regulatory factors and genetic interactions that influence the expression of resistance genes like blaTEM-1. Expanding research to include other resistance genes could provide a more comprehensive view of how bacteria adapt to antibiotic pressure.

The work also opens avenues to explore the fitness costs associated with carrying resistance genes, especially in environments without antibiotics. Understanding how these genes spread and persist in bacterial populations is key to developing effective strategies to combat antibiotic resistance.

Conclusion

This research sheds light on how the blaTEM-1 gene contributes to antibiotic resistance in E. coli. By examining the genetic factors that influence resistance, the study underscores the importance of detailed genomic analysis in predicting how bacteria respond to treatments. The insights gained can inform strategies to address the issue of rising antibiotic resistance in healthcare settings.

Original Source

Title: E. coli phylogeny drives co-amoxiclav resistance through variable expression of blaTEM-1

Abstract: Co-amoxiclav resistance in E. coli is a clinically important phenotype associated with increased mortality. The class A beta-lactamase blaTEM-1 is often carried by co- amoxiclav-resistant pathogens, but exhibits high phenotypic heterogeneity, making genotype-phenotype predictions challenging. We present a curated dataset of n=377 E. coli isolates representing all 8 known phylogroups, where the only acquired beta- lactamase is blaTEM-1. For all isolates, we generate hybrid assemblies and co-amoxiclav MICs, and for a subset (n=67/377), blaTEM-1 qPCR expression data. First, we test whether certain E. coli lineages are intrinsically better or worse at expressing blaTEM-1, for example, due to lineage differences in regulatory systems, which are challenging to directly quantify. Using genotypic features of the isolates (blaTEM-1 promoter variants and copy number), we develop a hierarchical Bayesian model for blaTEM-1 expression that controls for phylogeny. We establish that blaTEM-1 expression intrinsically varies across the phylogeny, with some lineages (e.g. phylogroups B1 and C, ST12) better at expression than others (e.g. phylogroups E and F, ST372). Next, we test whether phylogenetic variation in expression influences the resistance of the isolates. With a second model, we use genotypic features (blaTEM-1 promoter variants, copy number, duplications; ampC promoter variants; efflux pump AcrF presence) to predict isolate MIC, again controlling for phylogeny. Lastly, we use a third model to demonstrate that the phylogenetic influence on blaTEM-1 expression causally drives the variation in co- amoxiclav MIC. This underscores the importance of incorporating phylogeny into genotype-phenotype predictions, and the study of resistance more generally.

Authors: Nicole Stoesser, W. Matlock, G. Rodger, E. Pritchard, M. Colpus, N. Kapel, L. Barrett, M. Morgan, S. Oakley, K. L. Hopkins, A. Roohi, D. Karageorgopoulos, M. B. Avison, A. S. Walker, S. Lipworth

Last Update: 2024-10-22 00:00:00

Language: English

Source URL: https://www.biorxiv.org/content/10.1101/2024.08.12.607562

Source PDF: https://www.biorxiv.org/content/10.1101/2024.08.12.607562.full.pdf

Licence: https://creativecommons.org/licenses/by-nc/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to biorxiv for use of its open access interoperability.

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