ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

Dhariwal, Achal; Junges, Roger; Chen, Tsute; Petersen, Fernanda Cristina

doi:10.1093/nargab/lqab018

Cited by 17 publications

(16 citation statements)

References 68 publications

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“…Values were compared and tested using t-Test and p-value of < 0.05 was considered statistically significant. Additional resistance gene statistical analysis was performed using ResistoXplorer [ 30 ]. In brief, the summary gene detection data from Abricate was utilised together with metadata and a resistance gene key for uploading to ResistoXplorer.…”

Section: Methodsmentioning

confidence: 99%

“…ALDEx2, an ANOVA-like differential expression tool, was utilised with the Wilcoxon test to determine ranking of resistance gene abundance with a Monte Carlo number set at the default of 64 samples. ALDEx2 estimates variation within samples using Monte-Carlo instances and using centered log-ratio transformation [ 30 , 31 ]. Further identification of contigs with AMR genes was performed using the NCBI Basic Local Alignment Tool (BLAST) [ 32 ], using the default parameters and standard nucleotide collection (nr/nt).…”

Section: Methodsmentioning

confidence: 99%

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Standard rectal swabs as a surrogate sample for gut microbiome monitoring in intensive care

Schlebusch

Graham²,

Jennison³

et al. 2022

BMC Microbiol

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Background The purpose of this study was to investigate the use of routinely available rectal swabs as a surrogate sample type for testing the gut microbiome and monitoring antibiotic effects on key gut microorganisms, of patients hospitalised in an intensive care unit. A metagenomic whole genome sequencing approach was undertaken to determine the diversity of organisms as well as resistance genes and to compare findings between the two sampling techniques. Results No significant difference was observed in overall diversity between the faeces and rectal swabs and sampling technique was not demonstrated to predict microbial community variation. More human DNA was present in the swabs and some differences were observed only for a select few anaerobes and bacteria also associated with skin and/or the female genitourinary system, possibly reflecting sampling site or technique. Antibiotics and collections at different times of admission were both considered significant influences on microbial community composition alteration. Detection of antibiotic resistance genes between rectal swabs and faeces were overall not significantly different, although some variations were detected with a potential association with the number of human sequence reads in a sample. Conclusion Testing the gut microbiome using standard rectal swab collection techniques currently used for multi-resistant organism screening has been demonstrated to have utility in gut microbiome monitoring in intensive care. The use of information from this article, in terms of methodology as well as near equivalence demonstrated between rectal swabs and faeces will be able to support and potentially facilitate the introduction into clinical practice.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Standard rectal swabs as a surrogate sample for gut microbiome monitoring in intensive care

Schlebusch

Graham²,

Jennison³

et al. 2022

BMC Microbiol

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“…RStudio (Version V4.0.3) was used for graphical representation using the libraries “ ggplot2 ,” “ reader ,” and “ esquisse .” Additionally, we used the web‐based tool ResitoXplorer 22 to visualize and generate a statistical analysis of the composition profiling, clustering analysis, differential abundance testing, and integrative analysis. The filtration process removed low‐quality or non‐informative ARGs to improve the statistical tests using ResitoXplorer's default parameters (low count and low variance filters).…”

Section: Methodsmentioning

confidence: 99%

“…RStudio (Version V4.0.3) was used for graphical representation using the libraries "ggplot2," "reader," and "esquisse." Additionally, we used the web-based tool ResitoXplorer 22 to visualize and generate a F I G U R E 1 Study design and antibiotic-resistant genes identified in fecal samples from patients who received eradication therapy against H. pylori. (A) Treatment groups, time points of analysis, and number of samples studied.…”

Section: Statistical and Integrative Analysismentioning

confidence: 99%

Saccharomyces boulardii CNCM I‐745 supplementation modifies the fecal resistome during Helicobacter pylori eradication therapy

et al. 2022

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Background:The gut microbiota is a significant reservoir of antimicrobial resistance genes (ARGs). The use and misuse of antimicrobials can select multi-resistant bacteria and modify the repertoire of ARGs in the gut. Developing effective interventions to manipulate the intestinal resistome would allow us to modify the antimicrobial resistance risk. Materials and Methods:Applying shotgun metagenomics, we compared the composition of fecal resistome from individuals treated with triple therapy for Helicobacter pylori plus Saccharomyces boulardii CNCM-I 745 (Sb) versus triple antibiotherapy without S. boulardii (control) before, after, and one month after treatments. DNA samples were sequenced on an Illumina NovaSeq 6000 platform. Reads were trimmed and filtered for quality, and the reads classified as host genome were removed from further analysis. We used the ResFinder database for resistome analysis and the web-based tool ResistoXplorer and RStudio for graphical representation and statistical analysis. Results:We identified 641 unique ARGs in all fecal samples, conferring resistance to 18 classes of antibiotics. The most prevalent ARGs found in at least 90% of the samples before the treatments were against tetracyclines, MLS-B (macrolide, lincosamide, and streptogramin B), beta-lactams, and aminoglycosides. Differential abundance analysis allowed the identification of ARGs significantly different between treatment groups. Thus, immediately after the treatments, the abundance of ARGs that confer resistance to lincosamides, tetracyclines, MLS-B, and two genes in the beta-lactam class (cfxA2 and cfxA3) was significantly lower in the group that received Sb than in the control group (edgeR, FDR <0.05). Conclusion:Our study demonstrated that the addition of S. boulardii CNCM-I 745 to the conventional antibiotic eradication therapy for H. pylori reduced the abundance of ARGs, particularly those genes that confer resistance to lincosamides, tetracyclines, MLS-B, and a few genes in the beta-lactams class.

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“…Genes that confer resistance to fusidic acid, antibacterial free fatty acid, aminocoumarin, acridine dye, elfamycin, glycylcycline, isoniazid, mupirocin, nitrofuran, nitroimidazole, nucleoside, pactamycin, polyamin, and rifamycin were herein classified as "others." All images and statistical analysis were performed using ResistoXplorer (http://www.resistoxplorer.no/; Dhariwal et al, 2021) online software. We assessed alpha and beta diversities to visualize how the different identified genes were related within and between groups, respectively.…”

Section: Basecalling and Resistome Constructionmentioning

confidence: 99%

Different Swine Production Systems Can Shape Slurry Resistome at Mechanism and Class Levels Based on Swine Manure Evaluation

Beltrame

Zamparette

Feltrin

et al. 2022

Front. Cell. Infect. Microbiol.

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Antimicrobial resistance is a major threat to public health. Antimicrobial use in animal husbandry is a major concern since it can favor an increase in antimicrobial resistance among farms. Herein, we aim to better understand and characterize the main resistome profiles in microbial communities found in pig farms. Sampling of swine manure was performed in two different timepoints (October 2019 and January 2020) in each of the 14 different swine farms, located in the mesoregion of Western Santa Catarina state in Brazil, a pole of swine product production of worldwide importance. Samples were divided into three groups: farms with the opened regimen and no usage of antimicrobials (F1; n = 10), farms with the closed regimen and usage of antimicrobials (F2; n = 16), and farms with the closed regimen and no usage of antimicrobials (F3; n = 2). The metagenomic evaluation was performed to obtain and identify genetic elements related to antimicrobial resistance using nanopore sequencing. We used ResistoXplorer software to perform composition, alpha and beta diversity, and clustering analysis. In addition, PCR reactions were performed to confirm the presence or absence of seven different beta-lactamase family genes and five phosphoethanolamine transferase gene variants clinically relevant. Our findings based on the identification of resistance genes at the mechanism level showed a prevalence of alteration of the drug target (72.3%) profile, followed by drug inactivation (17.5%) and drug efflux (10.1%). We identified predominantly aminoglycosides (45.3%), tetracyclines (15.9%), and multiclass (11,2%) resistance genes. PCoA analysis indicates differences between F1 and F2 profiles. F2 samples showed increased diversity when compared to the F1 group. In addition, herein we first report the identification of mcr-4 in a slurry sample (C1F1.1) in Santa Catarina State. In general, our findings reinforce that many factors on the practices of animal husbandry are involved in the resistome profile at the mechanism and class levels. Further studies to better understand microbiome and mobilome aspects of these elements are necessary to elucidate transmission pathways between different bacteria and environments.

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ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

Cited by 17 publications

References 68 publications

Standard rectal swabs as a surrogate sample for gut microbiome monitoring in intensive care

Standard rectal swabs as a surrogate sample for gut microbiome monitoring in intensive care

Saccharomyces boulardii CNCM I‐745 supplementation modifies the fecal resistome during Helicobacter pylori eradication therapy

Different Swine Production Systems Can Shape Slurry Resistome at Mechanism and Class Levels Based on Swine Manure Evaluation

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