Comparative Metagenomics and Network Analyses Provide Novel Insights Into the Scope and Distribution of β-Lactamase Homologs in the Environment

Abstract

The β-lactams are the largest group of clinically applied antibiotics, and resistance to these is primarily associated with β-lactamases. There is increasing understanding that these enzymes are ubiquitous in natural environments and henceforth, elucidating the global diversity, distribution, and mobility of β-lactamase-encoding genes is crucial for holistically understanding resistance to these antibiotics. In this study, we screened 232 shotgun metagenomes from ten different environments against a custom-designed β-lactamase database, and subsequently analyzed β-lactamase homologs with a suite of bioinformatic platforms including cluster and network analyses. Three interrelated β-lactamase clusters encompassed all of the human and bovine feces metagenomes, while β-lactamases from soil, freshwater, glacier, marine, and wastewater grouped within a separate "environmental" cluster that displayed high levels of inter-network connectivity. Interestingly, almost no connectivity occurred between the "feces" and "environmental" clusters. We attributed this in part to the divergence in microbial community composition (dominance of Bacteroidetes and Firmicutes vs. Proteobacteria, respectively). The β-lactamase diversity in the "environmental" cluster was significantly higher than in human and bovine feces microbiomes. Several class A, B, C, and D β-lactamase homologs (bla _CTX-M, bla _KPC, bla _GES) were ubiquitous in the "environmental" cluster, whereas bovine and human feces metagenomes were dominated by class A (primarily cfxA) β-lactamases. Collectively, this study highlights the ubiquitous presence and broad diversity of β-lactamase gene precursors in non-clinical environments. Furthermore, it suggests that horizontal transfer of β-lactamases to human-associated bacteria may be more plausible from animals than from terrestrial and aquatic microbes, seemingly due to phylogenetic similarities.

Keywords: antibiotic resistance; environment; metagenomics; network analysis; β-lactamases.

Figure 1

Diversity of β-lactamases across different environments. The average β-lactamase relative abundance in percent of each environment (in brackets) is expressed as the ratio of β-lactamase hits per the total number metagenome reads.

Figure 2

Relative abundance of the five most dominant β-lactamase homologs in the ten environments targeted in this study. Anaerobic reactors encompass both municipal wastewater treatment and food waste treatment digesters.

Figure 3

β-lactamase homologs gene network of analyzed metagenomes. Circles and Roman numerals represent clusters defined using network analyzer in Cytoscape. (A) Network color-code based on environment: bovine rumen (light green); bovine feces (dark green); human feces (purple); aerobic (activated sludge) municipal wastewater treatment (red), anaerobic municipal waste and food digestion reactors (brown); non-agricultural soil (yellow); agricultural soil (orange); glaciers (white); fresh water (light blue); marine (dark blue). Anaerobic municipal waste samples were primarily associated with Cluster I, whereas anaerobic food digesters all grouped in Cluster II. (B) Network color-coded based on geographical origin: United States (blue); Israel (light blue); Northern Europe (purple), Central Europe (orange); China (red); Australia (yellow).

Figure 4

Relative abundance of selected β-lactamases in the targeted environments grouped according to identity (%) to EX-B database sequences. Black: 50–59%; gray: 60–69%; white: 70–79%; white granulated: 80–89%; and black granulated: 90–100%.

Figure 5

Non-metric multidimensional scaling ordination of selected β-lactamase gene homologs. Shapes and colors represent the environmental source of the metagenome samples. The point sizes are proportional to the abundance of the depicted gene. The PC-ORD generated stress was between 15.2 and 15.5, depending on the number of iterations and dimensions applied.