An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis
Identification of environmental pollutants with harmful effects is commonly conducted by non-targeted analysis (NTA) using liquid chromatography coupled with high-resolution mass spectrometry. Prioritization of possible candidates is important yet challenging because of the large number of candidate...
Saved in:
Main Authors: | , , , , , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/170040 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-170040 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1700402023-08-22T06:06:50Z An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis Yang, Junjie Zhao, Fanrong Zheng, Jie Wang, Yulan Fei, Xunchang Xiao, Yongjun Fang, Mingliang School of Civil and Environmental Engineering Lee Kong Chian School of Medicine (LKCMedicine) Singapore Phenome Center Engineering::Environmental engineering Non-targeted Analysis Automatic Prioritization Identification of environmental pollutants with harmful effects is commonly conducted by non-targeted analysis (NTA) using liquid chromatography coupled with high-resolution mass spectrometry. Prioritization of possible candidates is important yet challenging because of the large number of candidates from MS acquisitions. We aimed to prioritize candidates to the exposure potential of organic chemicals by their toxicity and identification evidence in the matrix. We have developed an R package application, "NTAprioritization.R", for fast prioritization of suspect lists. In this workflow, the identification levels of candidates were first rated according to spectral matching and retention time prediction. The toxicity levels were rated according to candidates' toxicity of different endpoints or ToxPi score. Finally, the various levels of candidates were identified as Tier 1 - 5 descending in priority. For validation, we used this workflow to identify pollutants in a sludge water sample spiked with 28 environmental pollutants. The workflow reduced the candidate list of over 6,982 candidates to a final list of 2,779 compounds and prioritized them to 5 tiers (Tier 1 - 5), including 21 out of 28 spiked standards. Overall, this study shows the added value of an automated prioritization R package for the fast screening of environmental pollutants based on the NTA method. 2023-08-22T06:06:50Z 2023-08-22T06:06:50Z 2023 Journal Article Yang, J., Zhao, F., Zheng, J., Wang, Y., Fei, X., Xiao, Y. & Fang, M. (2023). An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis. Journal of Hazardous Materials, 448, 130893-. https://dx.doi.org/10.1016/j.jhazmat.2023.130893 0304-3894 https://hdl.handle.net/10356/170040 10.1016/j.jhazmat.2023.130893 36746086 2-s2.0-85147581782 448 130893 en Journal of Hazardous Materials © 2023 Elsevier B.V. All rights reserved. |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering::Environmental engineering Non-targeted Analysis Automatic Prioritization |
spellingShingle |
Engineering::Environmental engineering Non-targeted Analysis Automatic Prioritization Yang, Junjie Zhao, Fanrong Zheng, Jie Wang, Yulan Fei, Xunchang Xiao, Yongjun Fang, Mingliang An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis |
description |
Identification of environmental pollutants with harmful effects is commonly conducted by non-targeted analysis (NTA) using liquid chromatography coupled with high-resolution mass spectrometry. Prioritization of possible candidates is important yet challenging because of the large number of candidates from MS acquisitions. We aimed to prioritize candidates to the exposure potential of organic chemicals by their toxicity and identification evidence in the matrix. We have developed an R package application, "NTAprioritization.R", for fast prioritization of suspect lists. In this workflow, the identification levels of candidates were first rated according to spectral matching and retention time prediction. The toxicity levels were rated according to candidates' toxicity of different endpoints or ToxPi score. Finally, the various levels of candidates were identified as Tier 1 - 5 descending in priority. For validation, we used this workflow to identify pollutants in a sludge water sample spiked with 28 environmental pollutants. The workflow reduced the candidate list of over 6,982 candidates to a final list of 2,779 compounds and prioritized them to 5 tiers (Tier 1 - 5), including 21 out of 28 spiked standards. Overall, this study shows the added value of an automated prioritization R package for the fast screening of environmental pollutants based on the NTA method. |
author2 |
School of Civil and Environmental Engineering |
author_facet |
School of Civil and Environmental Engineering Yang, Junjie Zhao, Fanrong Zheng, Jie Wang, Yulan Fei, Xunchang Xiao, Yongjun Fang, Mingliang |
format |
Article |
author |
Yang, Junjie Zhao, Fanrong Zheng, Jie Wang, Yulan Fei, Xunchang Xiao, Yongjun Fang, Mingliang |
author_sort |
Yang, Junjie |
title |
An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis |
title_short |
An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis |
title_full |
An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis |
title_fullStr |
An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis |
title_full_unstemmed |
An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis |
title_sort |
automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/170040 |
_version_ |
1779156561114955776 |