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PubMed2026

Biomonitoring of industrial heavy metal pollution via enzymatic and metabolic responses in desert ants (Cataglyphis savignyi) and beetles (Tentyrum sp) as bioindicators.

The current work seeks to evaluate the effectiveness of Cataglyphis saviginyi and Tentyrum sp as indicators of pollution in the city's main industrial regions by analyzing their enzymatic activity and primary metabolites. Soil samples were collected at each site under investigation to analyze soil characteristics and heavy metal content. C. saviginyi and Tentyrum sp were collected across four consecutive seasons (2023-2024) to investigate enzymatic (GPT, GOT, ALP, ACP, LDH) and metabolic (lipid, protein, carbohydrate) biomarkers. The physicochemical properties of the soil differed substantially between the industrial areas and the control site. Soil heavy metal buildup was highest at industrial sites (1 and 4) compared to the control site, with the order being Zn > Cr > Cd > Cu. Heavy metal pollution indices were determined. Increased industrial activity from metal industries, ceramics, and chemical painting companies defines this area, as seen by the high Cdeg, mCd, PI, and PLI values derived for industrial sites 1 and 4. While C. saviginyi and Tentyrum sp deconcentrated and released Cr, Cd, and Zn into the soil via the biological accumulation factor (BAF), Cu acted as a macro-concentrator. Compared with the control site, industrial environments were shown to increase levels of GPT, GOT, LDH, ACP, protein, and carbohydrates in C. saviginyi. However, lipid and ALP activity was suppressed. at industrial sites, Tentyrum sp carbohydrate content was higher than at control sites, but GPT, GOT, ALP, ACP, LDH, protein, and lipid activities were all suppressed. Consequently, enzymatic and metabolic biomarkers proved to be sensitive indicators for assessing industrial heavy metal pollution in desert ecosystems.

Animals↗

PubMed2026

From molecular responses to environmental monitoring: advances and translational gaps in omics approaches in fish environmental toxicology.

Fish occupy a central position in aquatic ecosystems and serve as important bioindicators for environmental monitoring, as well as powerful translational models for understanding toxic mechanisms conserved across higher vertebrates. In recent years, omics techniques have proven to be powerful tools to address complex environmental questions that conventional toxicology methods cannot answer. Despite this potential, a critical translational gap remains between molecular findings and their use in ecological risk assessment frameworks. This review critically synthesizes advances across omics techniques including epigenomics, transcriptomics, metabolomics and proteomics and their integration. Special emphasis is placed on methodological considerations and practical aspects of these techniques in fish environmental toxicology and environmental monitoring. Evidence from single-omics studies suggests conserved biomarker signatures across species while characterizing complex phenomena like non-monotonic dose-response relationships, mixture toxicity and transgenerational and stereoselective effects with implications for population level monitoring. Multi-omics studies, especially those involving triple omics, further enhance mechanistic resolution by reconstructing adverse outcome pathways. We further evaluate using case studies when additional molecular layers provide critical insight and when they offer limited advantage, a strategic distinction with direct implications in environmental monitoring programmes. Finally, current limitations and future directions that will ultimately bridge the translational gap and hold promise for advancing mechanistic ecotoxicology and predictive environmental monitoring are discussed.

Animals↗

PubMed2026

Transcriptome sequencing provides novel insights into larval development and sexual dimorphism in the firefly Aquatica leii (Coleoptera: Lampyridae).

Fireflies are regarded as one of the most charismatic beetles due to their bioluminescence and ecological importance as bioindicators of freshwater quality. However, molecular mechanisms of larval development and sexual dimorphism in aquatic species remain poorly understood. Here, we performed multi-stage transcriptomic analysis of the aquatic firefly Aquatica leii across larval instars from L2 to L6, together with adult females and males, with three biological replicates per stage. Using time-series expression clustering, differential expression analysis, and weighted gene co-expression network analysis (WGCNA), we characterized the transcriptional dynamics of continuous larval development and the onset of sex-biased gene expression. We identified a critical transcriptional transition occurred at L5-L6, marked by downregulation of early morphogenetic genes and upregulation of juvenile hormone metabolism, oxidoreductase activity, and muscle contraction genes, indicating a shift from growth to metamorphic preparation. WGCNA identified a module strongly correlated with L6 (R = 0.97) enriched for the same functions, confirming a coordinated late-larval program. Notably, genes exhibiting sex-biased expression in adults were already expressed during late larval stages (L5 and L6), and 123 genes progressively upregulated from L2 to L6 showed enrichment in chitin biosynthesis, heart contraction, and ion transport; among these, six genes maintained high expression in adults with clear male-biased (Alei052192, Alei006658, and Alei087054) or female-biased (Alei003725, Alei096818, and Alei074026) patterns. These findings establish that transcriptional foundations for sexual dimorphism and adult tissue formation are laid during late larval stages, providing the first multi-stage transcriptomic resource for aquatic firefly conservation and breeding.

Animals↗

PubMed2026

Metagenomics Reveals Microbial Community Shifts Associated With Contrasting Anthropogenic Impacts in Freshwater Sources of A Coastal Protected Area in Southeastern Brazil.

This study aimed to characterize freshwater microbial communities, environmental drivers, and anthropogenic impact patterns across three sites on Marambaia Island (southeastern Brazil) using metagenomics. Samples collected from freshwater sources used for human consumption were processed through concentration, nucleic acid extraction, and sequencing on the Illumina NextSeq 2000 platform. A total of 67.2 million reads were assembled into 89,230 bacterial contigs, mostly attributed to Gammaproteobacteria, Alphaproteobacteria, and Betaproteobacteria. Sites under lower anthropogenic influence exhibited higher microbial diversity, whereas impacted sites showed enrichment of opportunistic and fecal-associated genera. A heterogeneous anthropogenic impact profile was observed across sites, corroborated by the proposed Anthropogenic Impact Index (AII). Fourteen antimicrobial resistance genes conferring resistance to beta-lactams, quinolones, sulfonamides, tetracyclines, and macrolides were detected predominantly in sewage-impacted areas, indicating potential diffuse contamination. Redundancy analysis revealed that environmental variables explained 88.1% of microbial community variation, with conductivity, salinity, and turbidity as key drivers. These findings demonstrate the applicability of metagenomics as a powerful tool for assessing microbial diversity, ecological dynamics, and contamination risks in vulnerable freshwater systems.

Brazil↗