Biomarker screening, identification, and evaluation for biomonitoring palm oil mill effluent pollution in river water

The palm oil industry plays a vital role in Malaysia’s socioeconomic development but generates a significant amount of wastewater, known as palm oil mill effluent (POME). The treated POME, known as POME final discharge, is commonly released into nearby rivers or plantations, leading to river contamination. With the expansion of palm oil production, the volume of POME also increases, posing a growing threat to water ecosystems. Current monitoring of POME pollution is based on physicochemical assessments like biochemical oxygen demand (BOD5) and chemical oxygen demand (COD), but these methods cannot distinguish between pollution sources, are time￾consuming, involve harmful chemicals, and do not provide insight into the biological impact of pollutants. Given these limitations and the sensitivity of bacterial communities to pollution, this study aimed to investigate the effects of POME final discharge on the structure and function of bacterial communities in rivers, with the goal of identifying potential biomarkers that could serve as more precise indicators of POME pollution. This study employed metatranscriptomics to elucidate the structural and transcriptional profiles of the active bacterial community in POME final discharges and receiving rivers from two study sites, correlating these profiles with physicochemical assessments. Potential biomarkers were identified through differential expression analysis, and their correlation with community metabolomics detected using gas chromatography-mass spectrometry (GC-MS) was explored. The candidate biomarker was validated by quantifying corresponding metabolites using high-performance liquid chromatography with a fluorescence detector (HPLC-FLD) and further correlated with its expression using reverse transcription quantitative PCR (RT-qPCR) across multiple sites. The findings revealed that despite different POME treatment systems at the two study sites, the bacterial functional profiles in POME final discharge samples were similar. Notably, metabolic pathways related to carbohydrates, lipids, and amino acids were significantly upregulated in the downstream parts of rivers receiving POME compared to upstream parts (FDR <0.05), highlighting the greater impact of POME on bacterial functional profiles than suggested by BOD5 and COD alone. Amino acids emerged as the dominant metabolites, with cysteine synthase, an enzyme involved in L-cysteine biosynthesis, identified as a candidate biomarker due to its high expression levels. HPLC-FLD analysis confirmed higher L-cysteine concentrations in POME final discharge (1.273 – 1.545 µM) and downstream rivers (0.476 – 0.583 µM) compared to upstream parts. RT-qPCR further validated the significant prevalence of cysteine synthase, showing a strong positive correlation with RNA-seq data and a 2.0 to 4.5-fold increase in its copy number/L in downstream rivers impacted by POME. Additionally, the study found a statistically significant difference in cysteine synthase levels between downstream POME-receiving rivers and control urban rivers not affected by POME. These expression patterns support cysteine synthase as a promising biomarker for POME pollution, particularly given its much higher expression in POME-impacted rivers compared to unaffected areas. Overall, this study provides the first comprehensive molecular-level analysis of POME's impact on river ecosystems, identifying cysteine synthase as a potential biomarker for POME pollution. This biomarker-based monitoring approach could allow for more sensitive and rapid detection of POME-related pollution, promoting sustainable practices within the palm oil industry.

Text 125012 - Full Text.pdf Download (5MB) Official URL or Download Paper: http://ethesis.upm.edu.my/id/eprint/18796

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