Cargando…
KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing
Nanopore technology enables portable, real-time sequencing of microbial populations from clinical and ecological samples. An emerging healthcare application for Nanopore includes point-of-care, timely identification of antibiotic resistance genes (ARGs) to help developing targeted treatments of bact...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618647/ https://www.ncbi.nlm.nih.gov/pubmed/36324897 http://dx.doi.org/10.3389/fbioe.2022.1016408 |
_version_ | 1784821096862711808 |
---|---|
author | Barquero, Alexander Marini, Simone Boucher, Christina Ruiz, Jaime Prosperi, Mattia |
author_facet | Barquero, Alexander Marini, Simone Boucher, Christina Ruiz, Jaime Prosperi, Mattia |
author_sort | Barquero, Alexander |
collection | PubMed |
description | Nanopore technology enables portable, real-time sequencing of microbial populations from clinical and ecological samples. An emerging healthcare application for Nanopore includes point-of-care, timely identification of antibiotic resistance genes (ARGs) to help developing targeted treatments of bacterial infections, and monitoring resistant outbreaks in the environment. While several computational tools exist for classifying ARGs from sequencing data, to date (2022) none have been developed for mobile devices. We present here KARGAMobile, a mobile app for portable, real-time, easily interpretable analysis of ARGs from Nanopore sequencing. KARGAMobile is the porting of an existing ARG identification tool named KARGA; it retains the same algorithmic structure, but it is optimized for mobile devices. Specifically, KARGAMobile employs a compressed ARG reference database and different internal data structures to save RAM usage. The KARGAMobile app features a friendly graphical user interface that guides through file browsing, loading, parameter setup, and process execution. More importantly, the output files are post-processed to create visual, printable and shareable reports, aiding users to interpret the ARG findings. The difference in classification performance between KARGAMobile and KARGA is minimal (96.2% vs. 96.9% f-measure on semi-synthetic datasets of 1 million reads with known resistance ground truth). Using real Nanopore experiments, KARGAMobile processes on average 1 GB data every 23–48 min (targeted sequencing - metagenomics), with peak RAM usage below 500MB, independently from input file sizes, and an average temperature of 49°C after 1 h of continuous data processing. KARGAMobile is written in Java and is available at https://github.com/Ruiz-HCI-Lab/KargaMobile under the MIT license. |
format | Online Article Text |
id | pubmed-9618647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96186472022-11-01 KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing Barquero, Alexander Marini, Simone Boucher, Christina Ruiz, Jaime Prosperi, Mattia Front Bioeng Biotechnol Bioengineering and Biotechnology Nanopore technology enables portable, real-time sequencing of microbial populations from clinical and ecological samples. An emerging healthcare application for Nanopore includes point-of-care, timely identification of antibiotic resistance genes (ARGs) to help developing targeted treatments of bacterial infections, and monitoring resistant outbreaks in the environment. While several computational tools exist for classifying ARGs from sequencing data, to date (2022) none have been developed for mobile devices. We present here KARGAMobile, a mobile app for portable, real-time, easily interpretable analysis of ARGs from Nanopore sequencing. KARGAMobile is the porting of an existing ARG identification tool named KARGA; it retains the same algorithmic structure, but it is optimized for mobile devices. Specifically, KARGAMobile employs a compressed ARG reference database and different internal data structures to save RAM usage. The KARGAMobile app features a friendly graphical user interface that guides through file browsing, loading, parameter setup, and process execution. More importantly, the output files are post-processed to create visual, printable and shareable reports, aiding users to interpret the ARG findings. The difference in classification performance between KARGAMobile and KARGA is minimal (96.2% vs. 96.9% f-measure on semi-synthetic datasets of 1 million reads with known resistance ground truth). Using real Nanopore experiments, KARGAMobile processes on average 1 GB data every 23–48 min (targeted sequencing - metagenomics), with peak RAM usage below 500MB, independently from input file sizes, and an average temperature of 49°C after 1 h of continuous data processing. KARGAMobile is written in Java and is available at https://github.com/Ruiz-HCI-Lab/KargaMobile under the MIT license. Frontiers Media S.A. 2022-10-17 /pmc/articles/PMC9618647/ /pubmed/36324897 http://dx.doi.org/10.3389/fbioe.2022.1016408 Text en Copyright © 2022 Barquero, Marini, Boucher, Ruiz and Prosperi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioengineering and Biotechnology Barquero, Alexander Marini, Simone Boucher, Christina Ruiz, Jaime Prosperi, Mattia KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing |
title | KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing |
title_full | KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing |
title_fullStr | KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing |
title_full_unstemmed | KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing |
title_short | KARGAMobile: Android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing |
title_sort | kargamobile: android app for portable, real-time, easily interpretable analysis of antibiotic resistance genes via nanopore sequencing |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618647/ https://www.ncbi.nlm.nih.gov/pubmed/36324897 http://dx.doi.org/10.3389/fbioe.2022.1016408 |
work_keys_str_mv | AT barqueroalexander kargamobileandroidappforportablerealtimeeasilyinterpretableanalysisofantibioticresistancegenesviananoporesequencing AT marinisimone kargamobileandroidappforportablerealtimeeasilyinterpretableanalysisofantibioticresistancegenesviananoporesequencing AT boucherchristina kargamobileandroidappforportablerealtimeeasilyinterpretableanalysisofantibioticresistancegenesviananoporesequencing AT ruizjaime kargamobileandroidappforportablerealtimeeasilyinterpretableanalysisofantibioticresistancegenesviananoporesequencing AT prosperimattia kargamobileandroidappforportablerealtimeeasilyinterpretableanalysisofantibioticresistancegenesviananoporesequencing |