Showing papers by "Fiona S. L. Brinkman published in 2020"

Metagenome-assembled genome binning methods with short reads disproportionately fail for plasmids and genomic Islands

Abstract: Metagenomic methods enable the simultaneous characterization of microbial communities without time-consuming and bias-inducing culturing. Metagenome-assembled genome (MAG) binning methods aim to reassemble individual genomes from this data. However, the recovery of mobile genetic elements (MGEs), such as plasmids and genomic islands (GIs), by binning has not been well characterized. Given the association of antimicrobial resistance (AMR) genes and virulence factor (VF) genes with MGEs, studying their transmission is a public-health priority. The variable copy number and sequence composition of MGEs makes them potentially problematic for MAG binning methods. To systematically investigate this issue, we simulated a low-complexity metagenome comprising 30 GI-rich and plasmid-containing bacterial genomes. MAGs were then recovered using 12 current prediction pipelines and evaluated. While 82-94 % of chromosomes could be correctly recovered and binned, only 38-44 % of GIs and 1-29 % of plasmid sequences were found. Strikingly, no plasmid-borne VF nor AMR genes were recovered, and only 0-45 % of AMR or VF genes within GIs. We conclude that short-read MAG approaches, without further optimization, are largely ineffective for the analysis of mobile genes, including those of public-health importance, such as AMR and VF genes. We propose that researchers should explore developing methods that optimize for this issue and consider also using unassembled short reads and/or long-read approaches to more fully characterize metagenomic data.

Metagenome-Assembled Genome Binning Methods with Short Reads Disproportionately Fail for Plasmids and Genomic Islands

Abstract: Metagenomic methods are an important tool in the life sciences, as they enable simultaneous characterisation of all microbes in a community without time-consuming and bias-inducing culturing. Metagenome-assembled genome (MAG) binning methods have emerged as a promising approach to recover individual genomes from metagenomic data. However, MAG binning has not been well assessed for its ability to recover mobile genetic elements (MGEs), such as plasmids and genomic islands (GIs), that have very high clinical/agricultural/environmental importance. Certain antimicrobial resistance (AMR) genes and virulence factor (VF) genes are noted to be disproportionately associated with MGEs, making studying their transmission a public health priority. However, the variable copy number and sequence composition of MGEs relative to the majority of the host genome makes them potentially problematic for MAG binning methods. To systematically investigate this, we simulated a low-complexity metagenome comprising 30 GI-rich and plasmid-containing bacterial genomes. MAGs were then recovered using 12 current prediction pipelines and evaluated for recovery of MGE-associated AMR/VF genes. Here we show that while 82-94% of chromosomes could be correctly recovered and binned, only 38-44% of GIs were recovered and, even more notably, only 1-29% of plasmid sequences were found. Most strikingly, no plasmid-borne VF or AMR genes were recovered and within GIs, only between 0-45% of AMR or VF genes were identified. We conclude that short-read MAGs are largely ineffective for the analysis of mobile genes, including those of public-health importance like AMR and VF genes. We propose that microbiome researchers should instead primarily utilise unassembled short reads and/or long-read approaches to more accurately analyse metagenomic data

PSORTm: a bacterial and archaeal protein subcellular localization prediction tool for metagenomics data.

Abstract: MOTIVATION Many methods for microbial protein subcellular localization (SCL) prediction exist; however, none is readily available for analysis of metagenomic sequence data, despite growing interest from researchers studying microbial communities in humans, agri-food relevant organisms and in other environments (e.g. for identification of cell-surface biomarkers for rapid protein-based diagnostic tests). We wished to also identify new markers of water quality from freshwater samples collected from pristine versus pollution-impacted watersheds. RESULTS We report PSORTm, the first bioinformatics tool designed for prediction of diverse bacterial and archaeal protein SCL from metagenomics data. PSORTm incorporates components of PSORTb, one of the most precise and widely used protein SCL predictors, with an automated classification by cell envelope. An evaluation using 5-fold cross-validation with in silico-fragmented sequences with known localization showed that PSORTm maintains PSORTb's high precision, while sensitivity increases proportionately with metagenomic sequence fragment length. PSORTm's read-based analysis was similar to PSORTb-based analysis of metagenome-assembled genomes (MAGs); however, the latter requires non-trivial manual classification of each MAG by cell envelope, and cannot make use of unassembled sequences. Analysis of the watershed samples revealed the importance of normalization and identified potential biomarkers of water quality. This method should be useful for examining a wide range of microbial communities, including human microbiomes, and other microbiomes of medical, environmental or industrial importance. AVAILABILITY AND IMPLEMENTATION Documentation, source code and docker containers are available for running PSORTm locally at https://www.psort.org/psortm/ (freely available, open-source software under GNU General Public License Version 3). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

AB569, a nontoxic chemical tandem that kills major human pathogenic bacteria

Abstract: Antibiotic-resistant superbug bacteria represent a global health problem with no imminent solutions. Here we demonstrate that the combination (termed AB569) of acidified nitrite (A-NO2−) and Na2-EDTA (disodium ethylenediaminetetraacetic acid) inhibited all Gram-negative and Gram-positive bacteria tested. AB569 was also efficacious at killing the model organism Pseudomonas aeruginosa in biofilms and in a murine chronic lung infection model. AB569 was not toxic to human cell lines at bactericidal concentrations using a basic viability assay. RNA-Seq analyses upon treatment of P. aeruginosa with AB569 revealed a catastrophic loss of the ability to support core pathways encompassing DNA, RNA, protein, ATP biosynthesis, and iron metabolism. Electrochemical analyses elucidated that AB569 produced more stable SNO proteins, potentially explaining one mechanism of bacterial killing. Our data implicate that AB569 is a safe and effective means to kill pathogenic bacteria, suggesting that simple strategies could be applied with highly advantageous therapeutic/toxicity index ratios to pathogens associated with a myriad of periepithelial infections and related disease scenarios.

Metagenome-Assembled Genome Binning Methods Disproportionately Fail for Plasmids and Genomic Islands

Abstract: Motivation: Metagenomic methods have emerged as a key tool in public-health microbiology for surveillance of virulence and antimicrobial resistance (AMR) genes. However, metagenomic data, even when assembled, usually results in complex, mixed sets DNA sequence fragments rather than fully resolved individual genomes. Recently, metagenome-assembled genomes (MAGs) have emerged as a promising approach that groups sequences into bins that are likely derived from the same underlying genome. However, MAGs have not been well assessed for their ability to identify some of the key sequences of interest for infectious disease surveillance purposes: AMR and VFs associated with mobile genetic elements (MGEs) such as plasmids and genomic islands (GIs). We hypothesized that due to the different copy number and sequence composition of plasmids and GIs compared to core genome sequence, such sequences will be under-represented in MAG-based approaches. Results: To evaluate the impact of MAG recovery methods on recovery of AMR genes and MGEs, we generated a simulated metagenomic dataset comprised of 30 genomes with up to 16.65% of the chromosomal DNA consisting of GIs and 65 associated plasmids. MAGs were then recovered from this data using 12 different MAG pipelines and evaluated for recovery accuracies. Across all pipelines, 81.9-94.3% of chromosomes were recovered and binned. However, only 37.8-44.1% of GIs and 1.5-29.2% of plasmids were recovered and correctly binned at >50% coverage. In terms of AMR and VF genes associated with MGEs, 0-45% of GI-associated AMR genes and 0-16% of GI-associated VF genes were correctly assigned. More strikingly, 0% of plasmid-borne VF or AMR genes were recovered. This work shows that regardless of the MAG recovery approach used, plasmid and GI dominated sequences will disproportionately be left unbinned or incorrectly binned. From a public-health perspective, this means MAG approaches are less suited for analysis of mobile genes, especially key groups such as AMR and VF genes. This underlines the utility of read-based and long-read approaches to thoroughly evaluate the resistome in metagenomic data.