Revealing taxon-specific heavy metal-resistance mechanisms in denitrifying phosphorus removal sludge using genome-centric metaproteomics

Abstract

Background Denitrifying phosphorus removal sludge (DPRS) is widely adopted for nitrogen and phosphorus removal in wastewater treatment but faces threats from heavy metals. However, a lack of understanding of the taxon-specific heavy metal-resistance mechanisms hinders the targeted optimization of DPRS’s robustness in nutrient removal. Results We obtained 403 high- or medium-quality metagenome-assembled genomes from DPRS treated by elevating cadmium, nickel, and chromium pressure. Then, the proteomic responses of individual taxa under heavy metal pressures were characterized, with an emphasis on functions involving heavy metal resistance and maintenance of nutrient metabolism. When oxygen availability was constrained by high-concentration heavy metals, comammox Nitrospira overproduced highly oxygen-affinitive hemoglobin and electron-transporting cytochrome c-like proteins, underpinning its ability to enhance oxygen acquisition and utilization. In contrast, Nitrosomonas overexpressed ammonia monooxygenase and nitrite reductase to facilitate the partial nitrification and denitrification process for maintaining nitrogen removal. Comparisons between phosphorus-accumulating organisms (PAOs) demonstrated different heavy metal-resistance mechanisms adopted by Dechloromonas and Candidatus Accumulibacter, despite their high genomic similarities. In particular, Dechloromonas outcompeted the canonical PAO Candidatus Accumulibacter in synthesizing polyphosphate, a potential public good for heavy metal detoxification. The superiority of Dechloromonas in energy utilization, radical elimination, and damaged cell component repair also contributed to its dominance under heavy metal pressures. Moreover, the enrichment analysis revealed that functions involved in extracellular polymeric substance formation, siderophore activity, and heavy metal efflux were significantly overexpressed due to the related activities of specific taxa. Conclusions Our study demonstrates that heavy metal-resistance mechanisms within a multipartite community are highly heterogeneous between different taxa. These findings provide a fundamental understanding of how the heterogeneity of individual microorganisms contributes to the metabolic versatility and robustness of microbiomes inhabiting dynamic environments, which is vital for manipulating the adaptation of microbial assemblages under adverse environmental stimuli.

Microbial Roles in Dissolved Organic Matter Transformation in Full-Scale Wastewater Treatment Processes Revealed by Reactomics and Comparative Genomics

“…Genome-centric metagenomics can unravel microbes’ metabolic potentials at species resolution. , Coupling the taxon-specific functional information of microbes and molecular traits of DOM provides the opportunity to correlate DOM molecules with microbial phylogeny and functionality. Besides, Yu et al recently introduced reactomics, which evaluates untargeted MS profiles at the reaction level.…”

Genome-resolved metagenomics reveals cohesive metabolic dynamics, metal resistance genes (MRGs) and biogeochemical cycling in a hot spring system

“…The microbiota acquire resistance with cumulative metal concentration thresholds irrespective of their essentiality or non-essentiality to the environment. Here, the metal speciation suggested that 75% of the reconstructed MAGs were showing resistance to Cr, Co, Zn, Cd, As, Cu and have evolved to tolerate heavy metal concentrations using various processes includes biosorption, intra/extracellular entrapment and transportation across cell membrane which form the basis of different bioremediation strategies (Ahemad, 2012, Nanda et al ., 2019, Lin et al ., 2021).…”

Comparative metaproteomics demonstrates different views on the complex granular sludge microbiome

“…The genome taxonomy database (GTDB) uses a set of conserved proteins to normalize taxonomic ranks based on relative evolutionary divergence with the aim to provide an objective, phylogenetically consistent classification of prokaryotes [65,[69][70][71]. The Genome Taxonomy Database Toolkit (GTDB-Tk) furthermore enables to efficiently classify bacterial and archaeal draft genome assemblies [70,72,73]. However, in metagenomics, the clustering and binning of contigs into individual genomes commonly results in a substantial number of unbinned fractions [77,78].…”

“…The Genome Taxonomy Database Toolkit (GTDB-Tk) supports the classification of draft bacterial and archaeal genomes [70]. However, this tool was developed for genome assemblies or metagenome-assembled genomes that are constructed by clustering related contigs into bins [72, 73]. The binning procedure, however, leaves for complex metagenomes usually a substantial fraction of unbinned sequences [59].…”