Metagenomic Approaches for Studying Microbial Community of Industrial Effluent Contaminated Soil Across Dadra and Nagar Haveli

Abstract

Dadra and Nagar Haveli (DNH), a Union Territory of western India, hosts one of the nation's most densely
industrialized landscapes, with over 5,100 large, medium, and small-scale industries operating along the
ecologically sensitive Daman Ganga River corridor. Decades of inadequately treated industrial effluent discharge
from textile dyeing, electroplating, tanning, pharmaceutical, and chemical manufacturing units have profoundly
altered soil ecosystems across the Silvassa industrial belt, introducing complex mixtures of heavy metals,
petroleum hydrocarbons, xenobiotic organic compounds, and pharmaceutical active compounds into the soil
matrix. Metagenomic studies of industrial effluent-contaminated soils in Silvassa consistently document
communities dominated by Pseudomonadota (Proteobacteria), Actinomycetota, Bacillota, Myxococcota,
Acidobacteriota, and Thermodesulfobacteriota. Key genera—Pseudomonas, Bacillus, Cupriavidus,
Novosphingobium, Sulfuricurvum, Variovorax, and Clostridium—encode hydrocarbon-degrading enzymes (ring-
hydroxylating dioxygenases, monooxygenases, dehalogenases) and heavy-metal resistance determinants (czc,
chr, ars operons). KEGG and COG functional annotation reveals active metabolic pathways for benzoate, PAH,
BTEX, chloroalkane, chloroalkene, and nitrotoluene catabolism converging on the TCA cycle. Co-selection of
antibiotic resistance genes (ARGs) via mobile genetic elements in metal-contaminated soils constitutes an
emerging One Health concern. Industrial effluent-contaminated soils of Dadra and Nagar Haveli harbor a
taxonomically diverse and functionally rich indigenous microbiome with considerable untapped bioremediation
potential. Metagenomic science provides the resolution needed to translate community genomic data into targeted
bio-stimulation, bioaugmentation, and phytoremediation strategies. Longitudinal, multi-omics monitoring
programs and integration of long-read sequencing platforms are prioritized as future research directives for this
critically understudied region.