High-Resolution 16S rRNA and Metagenomics Reveal Taxonomic, Functional Restructuring and Pathogen Persistence in Egyptian Treated Wastewater

Abstract Wastewater treatment plants (WWTPs) are pivotal for environmental protection and public health, yet the ecological dynamics of microbial communities during treatment remain poorly characterized in arid, resource-limited areas. This study presents high-resolution 16S rRNA V3–V4 amplicon sequencing and predictive metagenomics to survey bacterial populations in influent and effluent samples from five major Egyptian WWTPs. Results revealed a dramatic increase in microbial richness and evenness post-treatment, with pronounced taxonomic restructuring: copiotrophic Proteobacteria, dominant in influent streams, declined sharply, while stress-tolerant lineages including Actinobacteriota, Firmicutes, and Bacteroidota emerged in effluents. Multivariate analyses (DCA, NMDS, PCoA) confirmed consistent, significant compositional turnovers, with statistically robust separation between input and output communities. Although community diversity and functional metabolic capacity expanded, several clinically relevant genera—Escherichia, Legionella, and Campylobacter—persisted in effluents at non-trivial levels, raising concerns for water reuse safety. Functional profiling highlighted increased metabolic versatility and resilience in treated microbiomes, particularly enrichment in nutrient cycling, xenobiotic degradation, and stress adaptation pathways. Community trajectories were strongly influenced by site-specific physicochemical factors, underscoring the need for tailored surveillance and optimized operation. Comparative analyses reinforced the universality of Proteobacteria dominance in raw sewage and demonstrated widespread post-treatment diversification, yet also revealed local variability shaped by plant design and regional characteristics. Together, these findings detail the molecular ecology underpinning wastewater treatment, identify persistent hazards, and advocate for region-specific monitoring and intervention strategies aligned with sustainable water reuse and One Health imperatives. Importance This study addresses a critical knowledge gap in wastewater management within arid and developing regions by elucidating the taxonomic and functional transformations of bacterial communities during treatment. The data show that while conventional WWTPs reliably increase microbial diversity and foster the development of resilient, functionally versatile communities, conventional processes may fail to fully eliminate key pathogens, thus posing ongoing public health risks. The persistent detection of clinically relevant genera in treated effluents highlights the limitations of standard monitoring and underscores the urgent need for integrated microbiome and resistome surveillance. These insights emphasize that effective wastewater management must go beyond chemical contaminant removal and include systematic, context-sensitive biological monitoring to safeguard water reuse. The study advances microbial ecology as a cornerstone of safe, sustainable water management, providing actionable evidence for policymakers and practitioners aiming to minimize pathogen dissemination and optimize treatment outcomes. Competing Interest Statement The authors have declared no competing interest. Abbreviations - (mg/L) - Milligrams per Liter - (%) - Percent - (16S rRNA) - 16S ribosomal Ribonucleic acid - (V3–V4) - Variable regions 3 and 4 - (Q20) - Phred quality score 20 - (Q30) - Phred quality score 30 - (nt) - Nucleotide - (L) - Liter - (°C) - degrees Celsius - (Pb) - Lead - (Ni) - Nickel - (Cd) - Cadmium - (Cu) - Copper - (Fe) - Iron - (Zn) - Zinc - (Hg) - Mercury - (As) - Arsenic - (μm) - micrometer - (DNA) - Deoxyribonucleic acid - (μL) - microliter - (PCR) - Polymerase Chain Reaction - (μM) - micromolar - (ng) - nanogram - (F) - Forward primer - (R) - Reverse primer - (s) - Seconds - (min) - Minutes - (QIIME2) - Quantitative Insights Into Microbial Ecology 2 - (Unifrac) - Unique Fraction Metric - (UPGMA) - Unweighted Pair Group Method with Arithmetic