Evidence map›Paper›PMID 42846510›Full record

ReviewFundamental research2026

Molecular bioindicators for assessing environmental impacts of emerging contaminants.

Han-Lin Cui, Yi-Jun Ren, Ke Shi, Li-Ying Zhang, Yan-Qing Zhang, Shu-Hao Du, Shu-Hong Gao, Ai-Jie Wang, Bin Liang

Abstract readReview
In one paragraph

Review in Fundamental research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Han-Lin CuiState Key Laboratory of Urban-rural Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China.
Yi-Jun RenShenzhen Key Laboratory of Organic Pollution Prevention and Control, State Key Laboratory of Urban-rural Water Resource and Environment, School of Eco-Environment, Harbin Institute of Technology, Shenzhen 518055, China.
Ke ShiShenzhen Key Laboratory of Organic Pollution Prevention and Control, State Key Laboratory of Urban-rural Water Resource and Environment, School of Eco-Environment, Harbin Institute of Technology, Shenzhen 518055, China.
Li-Ying ZhangShenzhen Key Laboratory of Organic Pollution Prevention and Control, State Key Laboratory of Urban-rural Water Resource and Environment, School of Eco-Environment, Harbin Institute of Technology, Shenzhen 518055, China.
Yan-Qing ZhangShenzhen Key Laboratory of Organic Pollution Prevention and Control, State Key Laboratory of Urban-rural Water Resource and Environment, School of Eco-Environment, Harbin Institute of Technology, Shenzhen 518055, China.
Shu-Hao DuShenzhen Key Laboratory of Organic Pollution Prevention and Control, State Key Laboratory of Urban-rural Water Resource and Environment, School of Eco-Environment, Harbin Institute of Technology, Shenzhen 518055, China.
Shu-Hong GaoShenzhen Key Laboratory of Organic Pollution Prevention and Control, State Key Laboratory of Urban-rural Water Resource and Environment, School of Eco-Environment, Harbin Institute of Technology, Shenzhen 518055, China.
Ai-Jie WangState Key Laboratory of Urban-rural Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China.
Bin LiangShenzhen Key Laboratory of Organic Pollution Prevention and Control, State Key Laboratory of Urban-rural Water Resource and Environment, School of Eco-Environment, Harbin Institute of Technology, Shenzhen 518055, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging contaminants (ECs) exert subtle yet persistent pressures on environmental systems, often escaping detection by traditional chemical or ecological monitoring. Molecular bioindicators, i.e., genes, enzymes, or pathways whose presence, abundance, or expression reflects contaminant exposure or biological stress, offer a mechanistic basis to trace pollutant fate and functional disruption. These include degradation and transformation genes reflecting detoxification potential, resistance and adaptation genes such as antimicrobial resistance determinants, and toxicity-response genes indicating metabolic or physiological stress across microbial and higher organisms. Although numerous functional genes and pathways associated with ECs have been identified and increasingly explored in environmental studies, their interpretation as molecular bioindicators remains fragmented, with limited standardization in bioindicator selection, sensitivity evaluation, and cross-system validation. This review synthesizes current methodologies for molecular bioindicator discovery, spanning culture-dependent functional assays, strain-level genomics, and community-scale omics integration, and highlights how combining mechanistic verification with data-driven approaches can enhance interpretability and transferability. To facilitate consistent validation and reuse, we further propose a structured, community-curated database linking contaminants, molecular bioindicator types, ecological contexts, and evidence tiers. By linking molecular responses to contaminant stress with measurable ecological outcomes, molecular bioindicators can offer a mechanistically grounded basis for interpreting EC impacts and support more integrative and evidence-based environmental risk assessment.

Indexed as

Bioindicator databaseBioindicator discovery techniquesEmerging contaminantsEnvironmental risk assessmentMicrobial community responseMolecular bioindicator

Identifiers

PMID42846510
PMCPMC13644486

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.