ReviewJournal of microbiology (Seoul, Korea)2021
Microbial source tracking using metagenomics and other new technologies.
Review in Journal of microbiology (Seoul, Korea), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Have genetic targets for faecal pollution diagnostics and source tracking revolutionized water quality analysis yet?FEMS microbiology reviews · 2023Pooled it
- Altered gut microbiota and metabolites in children with non-organic anorexia: a multi-omics integration study.Scientific reports · 2026Article
- Research on the application of nanopore sequencing technology in investigating microbial data deviation.Antonie van Leeuwenhoek · 2026Article
- An early microbial landscape: inspiring endeavor from the China Space Station Habitation Area Microbiome Program (CHAMP).Science China. Life sciences · 2025Article
- Beyond borders: A systematic review and meta-analysis of human-specific faecal markers across geographical settings.Critical reviews in environmental science and technology · 2025Review
- Assessing accuracy and specificity of faecal source library for microbial source-tracking, using SourceTracker as case study.Bioinformatics advances · 2025Article
- Application of Pan-Omics Technologies in Research on Important Economic Traits for Ruminants.International journal of molecular sciences · 2024Review
- decOM: similarity-based microbial source tracking of ancient oral samples using k-mer-based methods.Microbiome · 2023Article
- Local and Environmental Reservoirs ofGeoHealth · 2023Article
- Strategies for Monitoring Microbial Life in Beach Sand for Protection of Public Health.International journal of environmental research and public health · 2023Review
- Humans and Hoofed Livestock Are the Main Sources of Fecal Contamination of Rivers Used for Crop Irrigation: A Microbial Source Tracking Approach.Frontiers in microbiology · 2022Article
- Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges.Frontiers in microbiology · 2022Review
- Omics-based microbiome analysis in microbial ecology: from sequences to information.Journal of microbiology (Seoul, Korea) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The environment is under siege from a variety of pollution sources. Fecal pollution is especially harmful as it disperses pathogenic bacteria into waterways. Unraveling origins of mixed sources of fecal bacteria is difficult and microbial source tracking (MST) in complex environments is still a daunting task. Despite the challenges, the need for answers far outweighs the difficulties experienced. Advancements in qPCR and next generation sequencing (NGS) technologies have shifted the traditional culture-based MST approaches towards culture independent technologies, where community-based MST is becoming a method of choice. Metagenomic tools may be useful to overcome some of the limitations of community-based MST methods as they can give deep insight into identifying host specific fecal markers and their association with different environments. Adoption of machine learning (ML) algorithms, along with the metagenomic based MST approaches, will also provide a statistically robust and automated platform. To compliment that, ML-based approaches provide accurate optimization of resources. With the successful application of ML based models in disease prediction, outbreak investigation and medicine prescription, it would be possible that these methods would serve as a better surrogate of traditional MST approaches in future.
Indexed as
Identifiers
33565053What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.