Production of extracellular polymeric substances in granular sludge under selection for Accumulibacter and Competibacter
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Abstract
Granular sludge intensifies the removal of nutrients from wastewater. Granules structured by extracellular polymeric substances (EPS) can be recovered as biomaterial. Links between microbial selection and EPS formation during granulation need to get uncovered. We inoculated anaerobic-aerobic sequencing batch reactors with either flocs or granules to study the relationships between microbial selection, bioaggregation, exopolymer formation, and EPS composition. Selection for slow-growing organisms like the model polyphosphate- accumulating organism “Candidatus Accumulibacter” (max. 83% vs. amplicon sequencing read counts) and glycogen-accumulating organism “Ca. Competibacter” (max. 45%) sustained granulation. Gel-forming exopolymers were produced as high as above 40% of the volatile solids of the biomass by stepwise increase of the organic loading rate (0.3 to 2.0 g COD Ac d -1 L R -1 ). Confocal laser scanning microscopy, FT-IR spectroscopy, and HPAE-PAD chromatography revealed the complex and dynamic chemical compositions of the structural EPS in relation to microbial population shifts along reactor regimes. The analysis of 20 representative genomes of “Ca. Accumulibacter” and “Ca. Competibacter” recovered from public databases revealed their functional potential to produce EPS among other representative wastewater microorganisms. The more than 40 functional gene categories annotated highlight the complexity of EPS metabolic networks from monomers processing to assembly, export, and epimerizations. The combination of ecological engineering principles and systems microbiology will help unravel and direct the production of EPS from wastewater, valorizing residual granular sludge into beneficial biomaterials for the circular economy.
Highlights
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Selection for slow-growing organisms like PAOs and GAOs fostered a robust granulation.
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Structural EPS were produced above 40% of biomass volatile content under high loading.
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Chemical composition of EPS evolved together with the microbial community composition.
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Genomic insights highlighted the genetic potential of PAOs and GAOs for EPS formation.
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Microbial communities are complex; further are their EPS compositions and metabolisms.
Article activity feed
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Still only 11% of the 1000 HQ MAGs examined by the authors encoded homologs to known exopolysaccharide gene clusters,
I didn't see mention in the methods that the genomes from Singleton et al. were included, which is why I added that suggestion...so I think I'm confused of what reference genomes were used for these surveys - unless you are referring to the Singleton et al. authors being able to detect EPS genes in only 11% of the MAGs?
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In addition to triggering granulation and EBPR, selection for “Ca. Accumulibacter”
What would also be fascinating is if you have frozen biomass still from these samples and can perform metagenomic sequencing to see what specific clades/species of Accumulibacter you might have enriched for
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The degree of enrichment of PAOs of up to as high as 83% of the amplicon sequencing read
If you did the 16S analysis with dada2, it would be interesting to know if 83% of the reads comprised of Accumulibacter were a single or several ASVs - inferring that you had either a clonal or diverse population of Accumulibacter, such as explored in McDaniel et al. 2022 https://www.biorxiv.org/content/10.1101/2022.10.01.510452v1.full
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mycolic acid (long fatty acid), colanic acid, capsular heptoses, alginate, trehalose and rhamnose containing glycans (exopolysaccharides), sialic acid and CMP-N-acetylneuraminate (alpha-keto acid sugars), and N-linked glycosylation (binding of glycans to amino acids to form amino sugars or glycoproteins).
I might have missed this, but it might be good to provide a table describing the accessions such as KO numbers used to annotate these pathways to help with reproduciblity
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Clustered heatmap of functional gene categories potentially related to EPS metabolisms
I'm also not sure I understand the different color schemes here since there are different shades of purple for different cluster categories in addition to the heatmap colors and highlighting certain taxa
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Figure 7.
I know this is a large figure with a lot of text, but even zoomed in on my desktop a lot of the text is blurry - I am wondering for the main figure if there is a better way to visualize this either by focusing on a few significant pathways, or using the Anvi'o pangenomics tool for the genomes and pathways so that the phylogenetic organization is part of the same "heatmap" plot of the clusters
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From this heatmap overview, “Ca. Accumulibacter” and “Ca. Competibacter” lineages form a relatively homogenous cluster of EPS genomic signatures (lineage clusters 4+5).
It would be fascinating to see these results updated with more Accumulibacter references beyond those that were summarized at the time of the 2019 paper referenced to obtain these genomes
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EPS biosynthetic pathways
Are EPS biosynthetic pathways usually clustered together? If so, this could be another reason to include genomes from Singleton et al. 2021 since they generated high-quality genomes from full-scale WWTPs and searching among long-read assembled genomes could improve retrieval of biosynthetic clusters
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genomes of the flanking and reference populations
I might have missed here, but was metagenomic sequencing done for the bioreactors operated in this study? Or by flanking populations do you mean the other activated sludge/granular sludge genomes you collected from other studies?
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namely the putative PAO Dechloromonas
I think putative is fine and accurate here, but interestingly Petriglieri 2021 showed Dechloromonas species that are experimentally shown to be PAOs: https://www.nature.com/articles/s41396-021-01029-2
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following the bioinformatics procedure summarized
It's probably still a good idea to list and cite what software and version you used, such as if it was QIIME, mothur, or the dada2 package and the version so it's directly listed within this publication
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Figure 3.
I'm not sure if you used the plot_heatmap function from ampvis2 for this figure or not, but I think the default behavior is to plot by "sqrt", and not in this continuous fashion since most individual cells will be close to 0. When you have this extreme plotting of a few lineages that are very abundant and most others are not, it can be difficult to visualize, so it might be preferred to change the scaling of the coloring.
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Genomes from granular sludge microorganisms were imported to compare the genetic signatures of “Ca. Accumulibacter” and “Ca. Competibacter” into the broader context of the microbial ecosystem of BNR granular sludge
Were these genomes assembled from samples from full-scale granular sludge operating systems or other granular sludge lab-scale bioreactors? What also might be interesting is to pull other traditional activated sludge genomes (the most representative catalog would be from Singleton et al. 2021 https://www.nature.com/articles/s41467-021-22203-2) to see if there are differences in EPS production overall when comparing traditional activated sludge genomes to those from granular operating systems
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A representative set of 19 genomes of “Ca. Accumulibacter” was selected out of the more than 30 metagenome-assembled genomes (MAGs) deposited in public repositories which were recovered from a previous study (Rubio-Rincon et al., 2019)
Since this study there have been quite a few studies that have produced additional reference genomes for Accumulibacter - mostly summarized in Petriglieri et al. 2022 https://journals.asm.org/doi/full/10.1128/msystems.00016-22 where the phylogeny and nomenclature of Accumulibacter has been updated beyond the ppk1 nomenclature system. Adding genomes from this set might add to your analysis since there are quite a few references that were generated with Nanopore long reads and are higher quality references - including some from full-scale Danish WWTPs
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“Ca. Accumulibacter” was first targeted using the PAOmix set of probes PAO462, PAO651, and PAO846 (Crocetti et al., 2000). The detection of PAOs was refined by only using the PAO651 probe, since other PAO462 and PAO846 hybridize to other closely related lineages (Albertsen et al., 2016). The PAO clades I and II were targeted by the probes Acc-1-444 and Acc-2-444, respectively (Flowers et al., 2009; Welles et al., 2015).
These experiments might have been done prior to this publication, but there are now updated sets of Accumulibacter probes to take into account that some of these probes can target non-Accumulibacter (such as Propionivibrio) and overestimate the abundance - https://journals.asm.org/doi/full/10.1128/msystems.00016-22
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