Evaluating Microbial Interactions of Autotrophs and Heterotrophs in Partial Nitritation/Anammox (PN/A) Process by Experimental and Simulation Analyses

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Article Evaluating Microbial Interactions of Autotrophs and Heterotrophs in Partial Nitritation/Anammox (PN/A) Process by Experimental and Simulation Analyses

Guowang Lai, Zhaorui Chu *, Xiaoyu Huang, Jianye Ma and Hongwei Rong

Key Laboratory for Water Quality and Conservation of the Pearl River Delta, Ministry of Education, School of Civil Engineering, Guangzhou University, Guangzhou 510006, China; [email protected] (G.L.); [email protected] (X.H.); [email protected] (J.M.); [email protected] (H.R.) * Correspondence: [email protected]; Tel.: +86-20-3936-6657

Abstract: The microbial interactions between autotrophs and heterotrophs by the exchange of microbial products in a partial nitritation/anammox (PN/A) bioreactor were evaluated with both experimental and simulation analyses. Real-time quantitative PCR analysis showed that anammox bacteria (AMX) and ammonium oxidizing bacteria (AOB) made up 56.59% and 8.35% of total bacteria, respectively, while heterotrophs identified as Chloroflexi also constituted a large portion (32.76%) in the reactor, even without an external organic carbon supply. Furthermore, a mathematical model was developed to describe the growth of heterotrophs on soluble microbial products (SMP), which were released from the metabolism of autotrophs. After model calibration and validation, the simulation results were consistent with the experimental observations of the microbial composition and the nitrogenous transformations. According to the model analysis, the bulk oxygen concentration was Citation: Lai, G.; Chu, Z.; Huang, X.; determined to be the dominant factor governing the reactor performance and biomass fractions in Ma, J.; Rong, H. Evaluating Microbial the granule. Increasing granular size could decrease heterotrophic growth, but has little effect on Interactions of Autotrophs and the effluent concentration of SMP. Results of this study could establish a better understanding of Heterotrophs in Partial eco-physiological interactions of autotrophs and heterotrophs in PN/A process. Nitritation/Anammox (PN/A) Process by Experimental and Keywords: anammox; heterotrophic growth; granular sludge; soluble microbial products; modeling Simulation Analyses. Water 2021, 13, 324. https://doi.org/10.3390/ w13030324

Academic Editor: Jesus 1. Introduction Gonzalez-Lopez In the past few years, completely autotrophic nitrogen removal via partial nitritation Received: 23 December 2020 and anaerobic ammonium oxidization (anammox) has been confirmed as an attractive Accepted: 22 January 2021 option for nitrogen removal from wastewater due to a significant decrease in operating Published: 28 January 2021 costs [1,2]. In a partial nitritation/anammox (PN/A) reactor, ammonium is oxidized to nitrite by aerobic ammonium-oxidizing bacteria (AOB) consuming the dissolved oxygen Publisher’s Note: MDPI stays neutral (DO). Subsequently, anammox bacteria (AMX) converts the rest of ammonium and nitrite with regard to jurisdictional claims in to nitrogen gas and produce small amounts of nitrate [3]. published maps and institutional affil- Most previous fundamental studies about PN/A process have focused solely on the iations. microbial ecology of the autotrophs including AOB, AMX and nitrite-oxidizing bacteria (NOB) [4–7]. However, the other communities, for instance heterotrophs in this system, have often been neglected. In our previous experiments, it was observed that heterotrophs such as Chloroflexi constitute a large portion in PN/A reactors, even though no organic Copyright: © 2021 by the authors. carbon sources were involved in the influent [8]. It is well known that autotrophs could Licensee MDPI, Basel, Switzerland. produce soluble microbial products (SMP) during normal biomass metabolism, which This article is an open access article can be consumed by heterotrophs [9,10]. Therefore, more work remains to be done to distributed under the terms and characterize the role of heterotrophs presented in the PN/A process. conditions of the Creative Commons The presence of heterotrophs in PN/A systems might significantly influence the Attribution (CC BY) license (https:// microbial aggregate morphology and the reactor performance. On the one hand, nitrate creativecommons.org/licenses/by/ produced either by AMX or NOB can be removed by denitrification of the heterotrophs 4.0/).

Water 2021, 13, 324. https://doi.org/10.3390/w13030324 https://www.mdpi.com/journal/water Water 2021, 13, 324 2 of 10

with the SMP released by the autotrophs as a carbon source, resulting in a lower nitrogen effluent concentration [11,12]. On the other hand, the heterotrophs that were the most characterized as filamentous bacteria would compete against the autotrophs for electron acceptors (e.g., oxygen) and space, consequently damaging the settling properties and decreasing the solid retention time (SRT) [13]. However, hardly anything has so far been known about the key factors influencing heterotrophic growth in PN/A systems. Hence, there is a great need for better understanding of the interactions between autotrophs and heterotrophs in the PN/A process. Mathematical modeling has proven to be a powerful tool for testing our understanding of reaction mechanism, as well as for helping us to predict and optimize process performance. Hao et al. [14] developed a mathematical model describing the PN/A process, and furthermore analyzed the sensitivity of various parameters to the reactor performance. Volcke et al. [15] assessed the effect of the granule size distribution on the performance of a granular sludge reactor for autotrophic nitrogen removal with one-dimensional biofilm models. However, these models only considered the biological conversion processes of autotrophs (i.e., AOB, AMX and NOB) but ignored the existence of heterotrophs in PN/A processes. Therefore, the objective of this work is (1) to investigate the microbial compositions of the PN/A process by real-time quantitative PCR, and then (2) to develop a multi-species, multi-component mathematical model to quantify and evaluate the eco- physiological interactions through the exchange SMP between autotrophs and heterotrophs in the PN/A process, and, in particularly, (3) to explore the effects of process parameters on the growth of heterotrophs in the PN/A process.

2. Materials and Methods 2.1. Reactor Operation and Sampling A 2 L lab-scale sequencing batch reactor (SBR) was operated at 33 ◦C for 140 days and seeded with denitrification sludge from a pilot-scale anaerobic filter located in Harbin, China. The bioreactor was fed with synthetic wastewater containing ammonium (as (NH4)2SO4), inorganic carbon source (as NaHCO3), and microelement solution. The air flow rate during the aeration period was manually adjusted to maintain the dissolved −1 oxygen (DO) concentration around 0.2 to 0.4 mg O2 L . More details on reactor operation were described in Chu et al. [8]. Biomass was sampled when the maximum nitrogen removal efficiency (85%) was achieved (140 days after inoculation), and immediately stored at −80 ◦C for subsequent experiments.

2.2. DNA Extraction and qPCR Total genomic DNA was extracted from 0.30 g of activated sludge using PowerSoil DNA Isolation Kit (MoBio, Carlsbad, CA, USA) as described in the manufacturer’s in- structions. Following extraction, the integrity of the DNA was verified by 1% (w/v) gel electrophoresis and the concentration was determined by a UV-Vis spectrophotometer (NanoDrop 2000, Waltham, MA, USA). Real-time quantitative PCR (qPCR) was used to quantify total bacteria, AMX, AOB, Nitrobacter and Nitrospira with the corresponding primer sets listed in Supplementary Materials Table S1. A 20 µL PCR mixture contained 10 µL of FastStart Universal SYBR Green Master (Roche, Germany), 0.6 µL of each primer, 1 µL of template DNA, and 7.8 µL of double distilled H2O. qPCR was performed on the ABI Prism 7500 system (Waltham, MA, USA). The two-step amplification procedure contains initial denaturation at 95 ◦C for 10 min, followed by 40 cycles of 95 ◦C for 15 s and 60 ◦C for 1 min. The melting curve analysis was used after amplification for assessing the qPCR amplicon length.

2.3. Analytical Methods + − − The analyses of COD, NH4 -N, NO2 -N, NO3 -N and VSS were performed in accor- dance with standard methods [16]. The DO concentration was measured by a dissolved oxygen meter (LDO, Hach, Loveland, CO, USA). Particle size analyses were carried out Water 2021, 13, x FOR PEER REVIEW 3 of 10

2.3. Analytical Methods

The analyses of COD, NH4+-N, NO2−-N, NO3−-N and VSS were performed in accord- ance with standard methods [16]. The DO concentration was measured by a dissolved Water 2021, 13, 324 oxygen meter (LDO, Hach, Loveland, CO, USA). Particle size analyses were3 ofcarried 10 out with a laser diffraction particle size analyzer (Mastersizer 2000, Malvern, UK). The SMP was defined as soluble COD in the supernatant after centrifugation at 6000× g for 15 min due to no organic carbon in the influent. with a laser diffraction particle size analyzer (Mastersizer 2000, Malvern, UK). The SMP was defined as soluble COD in the supernatant after centrifugation at 6000× g for 15 min due2.4. toModel no organic Development carbon in the influent. 2.4.1. Model Description 2.4. Model Development 2.4.1.A Model one-dimensional Description biofilm model was established to explain the behavior of the granular sludge SBR with AQUASIM software package [17]. As shown in Figure S1, in A one-dimensional biofilm model was established to explain the behavior of the gran- ularorder sludge to simulate SBR with the AQUASIM mass transport software and package conversion [17]. As processes shown in in Figure the SBR, S1, inthe order model con- totained simulate three the completely mass transport mixed and compartments conversion processes and one in thebiofilm SBR, compartments. the model contained The volume threeof the completely completely mixed mixed compartments compartment and one was biofilm set to compartments. be variable to The simulate volume ofthe the different completelyphases of the mixed SBR compartment cycle. A high was fluid set circulat to be variableion rate to simulatewas adopted the different to ensure phases the same of bulk theliquid SBR concentrations cycle. A high fluid in the circulation two compartments. rate was adopted to ensure the same bulk liquid concentrationsThe biomass in the granules two compartments. were supposed to be spherical in shape and uniform in size, and Thethe biomassvalue of granules biofilm were porosity supposed was to set be to spherical 0.75. The in shape number and uniformof granules in size, (PN) and was as- the value of biofilm porosity was set to 0.75. The number of granules (PN) was assumed sumed constant in time and calculated by constant in time and calculated by ∙ PN , VSS·∙∙VR (1) PN = , (1) (1 − θ)·ρ· 4 πr3 where VSS is the biomass concentration (g COD3 m−3), VR is the reactor volume, and θ, ρ, r are

the porosity, density, and radius of the granules−3 in steady state, respectively. Parameters re- where VSS is the biomass concentration (g COD m ), VR is the reactor volume, and θ, ρ, r aregarding the porosity, granule density, structure and and radius mass of the transfer granules within in steady the granule state, respectively. were listed Parameters in Table S2. regarding granule structure and mass transfer within the granule were listed in Table S2. 2.4.2. Conversion Processes 2.4.2.In Conversion the model, Processes the unified theory of Laspidou and Rittmann [18] including kinetics of microbialIn the model,products the formation uniﬁed theory and of consumpt Laspidou andion Rittmannwas adopted [18] including and modified kinetics to of describe microbialthe microbial products interactions formation between and consumption autotroph was an adoptedd heterotroph and modiﬁed in PN/A to describe process. the As can be microbial interactions between autotroph and heterotroph in PN/A process. As can be seen seen from Figure 1, the developed model described the relationships among seven partic- from Figure1, the developed model described the relationships among seven particulate componentsulate components and eight and dissolved eight dissolved components compon involvingents 18 involving biological conversions. 18 biological Organic conversions. carbonOrganic for carbon the growth for the of growth the heterotroph of the heterotr was derivedoph was from derived three reactions: from three autotrophic reactions: auto- growthtrophic (UAP), growth biomass (UAP), decay biomass (Xs hydrolyzed decay (Xs tohydrolyzed Ss) and hydrolysis to Ss) an ofd EPS hydrolysis (BAP). The of stoi- EPS (BAP). chiometricThe stoichiometric matrix for matrix the interactions for the andinteractions transformations and transformations among model components among model were compo- listednents inwere Table listed S3, while in Table the corresponding S3, while the process corresponding rates and process stoichiometric rates and kineticstoichiometric parametersand kinetic were parameters presented were in Tables presented S4 and in S5, Tables respectively. S4 and S5, respectively.

Figure 1.1.Schematic Schematic of of biological biological conversion conversion processes processes taken taken into account into account in the model. in the model.

2.4.3. Simulation Strategy

The standard simulation was performed under the operational conditions of granule diameter at 0.5 mm, DO at 0.25 mg L−1, and inﬂuent ammonium at 500 mg N L−1. The ob-

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2.4.3. Simulation Strategy The standard simulation was performed under the operational conditions of granule diameter at 0.5 mm, DO at 0.25 mg L−1, and influent ammonium at 500 mg N L−1. The Water 2021, 13, 324 4 of 10 obtained results were then used to verify the model with experimental data. The signifi- cance of the results was assessed by variance analysis, in which p < 0.05 was regarded statistically significant and p > 0.05 was regarded statistically insignificant. tainedThe resultseffect of were operational then used toconditions verify the including model with DO experimental concentration data. Theand significancegranule size on theof heterotrophic the results was growth assessed in by the variance PN/A analysis, systemin was which simulatedp < 0.05 wasusing regarded the validated statistically model. significant and p > 0.05 was regarded statistically insignificant. Each simulation was run for at least 1000 days, which was long enough to assure the sys- The effect of operational conditions including DO concentration and granule size on temthe close heterotrophic to a steady growth state. in the PN/A system was simulated using the validated model. Each simulation was run for at least 1000 days, which was long enough to assure the system 3. Resultsclose to a steady state. 3.1. Reactor Performance 3. Results 3.1.Figure Reactor 2 Performanceshows the SBR performance over a period of 140 days. In Phase I, NH4+-N and total nitrogen (TN) removal efficiencies gradually increased to 93.2 ± 2.4% and+ 84.7 ± Figure2 shows the SBR performance over a period of 140 days. In Phase I, NH 4 -N 3.7%,and respectively, total nitrogen when (TN) removalthe nitrogen efficiencies loading gradually rate was increased around to 0.25 93.2 ±kg2.4% N m and−3 d 84.7−1. Then, the± hydraulic3.7%, respectively, retention whentime the(HRT) nitrogen was reduce loadingd rateto one was day, around while 0.25 the kg nitrogen N m−3 d −loading1. rateThen, was theincreased hydraulic to 0.50 retention kg N timem−3 d (HRT)−1, correspondingly was reduced to (Figure one day, 2, whilePhasethe II). nitrogenThe removal −3 −1 efficienciesloading rate of NH was4+ increased and TN were to 0.50 decreased kg N m sharply,d , correspondingly and then got (Figureback to2 ,91.6 Phase ± 4.1% II). and + 82.1The ± 2.6%, removal respectively. efficiencies Those of NH values4 and were TN were close decreased to the maximum sharply, andnitrogen then gotremoval back effi- ± ± ciencyto 91.6 (88.9%)4.1% thatand can 82.1 be obtained2.6%, respectively. in the PN/A Those system values without were close additional to the maximumdenitrification nitrogen removal efficiency (88.9%) that can be obtained in the PN/A system without [3,19]. After 140 days of operation, the biomass concentration inside the reactor stabilized additional denitrification [3,19]. After 140 days of operation, the biomass concentration −3 at 4000inside g theCOD reactor m . stabilized The average at 4000 diameter g COD mof− 3the. The granules average was diameter around of the 0.5 granules mm. According was to Volckearound et 0.5 al. mm. [15], According the density to Volcke and porosity et al. [15], of the the density granules and porosityin PN/A of reactors the granules were in 50,000 g CODPN/A m reactors−3 and 0.75, were respectively. 50,000 g COD With m−3 and these 0.75, data, respectively. the number With of these granules data, the was number estimated as 9,700,000of granules granules. was estimated as 9,700,000 granules.

Phase I Phase II ] 1.0 100 −1 d + −3 NH4-N Removal efficiency 0.8 80

TN Removal efficiency 0.6 60

0.4 40

0.2 Nitrogen loading rate 20 Removalefficiency [%] Nitrogen loading rate [kg N m N [kg rate loading Nitrogen 0.0 0 0 102030405060708090100110120130140 Operation time [day]

FigureFigure 2. Reactor 2. Reactor performance performance duri duringng thethe studystudy period. period. 3.2. qPCR Analysis 3.2. qPCR Analysis The composition of the key functional groups responsible for nitrogen removal, in- cludingThe composition AOB, AMX andof the NOB, key in functional the granules grou wasps determinedresponsible by for qPCR nitrogen with variousremoval, in- cludingsets of AOB, primers AMX (Figure and 3NOB,). 16S in rRNA the granules gene copy was numbers determined of total by bacteria, qPCR with AMX, various AOB, sets of primersNitrobacter (Figureand Nitrospire 3). 16S rRNAin the PN/A gene copy reactor numbers were about of total 4.0 × bacteria,105, 2.2 × AMX,105, 4.1 AOB,× 104 Nitro-, 3 3 bacter3.5 ×and10 Nitrospireand 5.3 × in10 thecopies PN/A per reactor ng DNA, were respectively. about 4.0 There× 105, is2.2 no × obvious105, 4.1 change× 104, 3.5 of × 103 these bacteria between Phase I and Phase II, indicating that the composition of the core and 5.3 × 103 copies per ng DNA, respectively. There is no obvious change of these bacteria microbiome is stable for a PN/A reactor in steady state operation. between Phase I and Phase II, indicating that the composition of the core microbiome is stable for a PN/A reactor in steady state operation. The relative abundances of each functional group in the reactor were calculated by dividing the gene copies of each bacterial group by the gene copies of total bacteria and

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the results were presented as a pie chart in Figure 3b. The results showed that AMX dominated in the biomass, accounting for 56.59% of total bacteria, while the relative abundance of AOB only accounted for 8.35% of total bacteria. The relative abundance of Nitrobacter (0.5%) and Nitrospira (1.2%) can almost be ignored, suggesting that NOB was successfully suppressed, which can be attributed to low oxygen concentration in the reactor. Notably, approximately 32.76% of total bacteria was identified as others, which makes us deduce Water 2021, 13, 324 that they were heterotrophs [8]. SMP secreted by autotrophs were5 oflikely 10 to be the energy and carbon sources for the growth of these heterotrophic bacteria.

Figure 3. 16S rRNA gene copies (A) and relative abundance (B) of total bacteria (Eub), AMX, AOB, Figure 3. 16S rRNA gene copies (A) and relative abundance (B) of total bacteria (Eub), AMX, AOB, Nitrobacter and Nitrospira in Phase I (day 64) and Phase II (day 118) using real-time quantitative PCR. NitrobacterError bars indicate and Nitrospira the standard in deviation Phase of I three(day reactions. 64) and Phase II (day 118) using real-time quantitative PCR. Error bars indicate the standard deviation of three reactions. The relative abundances of each functional group in the reactor were calculated by dividing the gene copies of each bacterial group by the gene copies of total bacteria and the 3.3.results Standard were presented Simulation: as a pie chartModel in FigureValidation3b. The with results Experimental showed that AMX Data dominated in theThe biomass, standard accounting simulation for 56.59% was of total first bacteria, performed while the for relative model abundance calibration of and the results of AOB only accounted for 8.35% of total bacteria. The relative abundance of Nitrobacter this(0.5%) simulation and Nitrospira in(1.2%) steady can almoststate beare ignored, summariz suggestinged thatin Table NOB was 1, successfullytogether with experimental measurements.suppressed, which The can be predicted attributed to effluent low oxygen NH concentration4+-N, NO2 in−-N, the reactor.NO3−-N Notably, and SMP levels in Case IIapproximately (NLR = 0.50 32.76% kg ofN totalm−3 bacteria d−1) maintain was identified 13.18, as others, 0.40, which 44.49 makes and us40.37 deduce mg L−1, respectively, that they were heterotrophs [8]. SMP secreted by autotrophs were likely to be the energy whichand carbon matched sources the for themeasured growth of theseones heterotrophic very well. bacteria.Moreover, the active biomass was predicted to include AOB at 7.69%, AMX at 57.28%, HET at 35.02% and NOB at 0.01%, which were confirmed3.3. Standard by Simulation: the results Model Validationof qPCR. with Experimental Data The standard simulation was first performed for model calibration and the results of this simulation in steady state are summarized in Table1, together with experimental Table 1. Comparison simulated results+ with experimental− − data in the standard case a. measurements. The predicted effluent NH4 -N, NO2 -N, NO3 -N and SMP levels in Case II (NLR = 0.50 kg N m−3 d−1) maintain 13.18, 0.40, 44.49 and 40.37 mg L−1, respectively, Case I: [0.25 kg N m−3 d−1] b Case II: [0.50 kg N m−3 d−1] which matched the measured ones very well. Moreover, the active biomass was predicted to include AOB atExperimental 7.69%, AMX at Data 57.28%, Simulated HET at 35.02% Results and NOB Experimental at 0.01%, which Data were Simulated Results confirmed by the results of qPCR. Effluent concentration (mg L−1) The model with calibrated parameters was then validated with the variations of + − − c AmmoniumNH4 -N, NO2 -N, NO 5.653 -N ± 3.21 and SMP concentrations 3.39 in the reactor during 11.71 a typical ± 5.71 cycle. 13.18 AsNitrite shown in Figure4, 1.77 the simulation ± 0.65 results matched 0.58 well with the measured 1.69 ± 1.78 data. The 0.40 average deviation between the measured data and model predications was less than Nitrate 44.63 ± 2.50 46.74 43.54 ± 2.14 44.49 4%. These results demonstrated that the calibrated model describes the eco-physiological interactionsSMP in the PN/A 43.24 process ± 5.71 satisfactorily. Thus, 41.32 the calibrated model 44.99 could ± 3.49 be used 40.37 for model predictions under different conditions.Biomass fraction d (%) AOB 11.87 6.73 8.35 7.69 AMX 61.69 61.24 56.59 57.28 HET 25.10 32.03 32.76 35.02 NOB 1.34 ND e 2.30 0.01 a Standard case: granule diameter 0.5 mm, DO 0.25 mg L−1, influent ammonium 500 mg N L−1. b The total nitrogen removal rates of Case I and Case II were 0.09 and 0.18 kg N kg VSS−1 d−1. c Experi- mental data are expressed as averages ± standard deviations with 10 days operation. d Biomass fractions were determined by real-time quantitative PCR. e ND, not detected.

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Table 1. Comparison simulated results with experimental data in the standard case a.

Case I: [0.25 kg N m−3 d−1] b Case II: [0.50 kg N m−3 d−1] Experimental Simulated Experimental Simulated Data Results Data Results Efﬂuent concentration (mg L−1) Ammonium 5.65 ± 3.21 c 3.39 11.71 ± 5.71 13.18 Water 2021, 13, x FOR PEER REVIEW Nitrite 1.77 ± 0.65 0.58 1.69 ± 1.78 0.40 6 of 10 Nitrate 44.63 ± 2.50 46.74 43.54 ± 2.14 44.49 SMP 43.24 ± 5.71 41.32 44.99 ± 3.49 40.37 Biomass fraction d (%) The model with calibrated parameters was then validated with the variations of + AOB− − 11.87 6.73 8.35 7.69 NH4 -N, NOAMX2 -N, NO3 -N and 61.69 SMP concentrations 61.24 in the reactor 56.59 during a typical 57.28 cycle. As shown in FigureHET 4, the simulation 25.10 results matched 32.03 well with 32.76 the measured data. 35.02 The average deviationNOB between the 1.34 measured data ND ande model predications2.30 was less 0.01 than 4%. Thesea resultsStandard demonstrated case: granule diameter that 0.5 the mm, calibrate DO 0.25 mgd Lmodel−1, inﬂuent describes ammonium the 500 eco-physiological mg N L−1. b The total in- −1 −1 c teractionsnitrogen in removalthe PN/A rates process of Case I and satisfactorily. Case II were 0.09 Thus, and 0.18 the kg calibrated N kg VSS dmodel. Experimental could be dataused are for expressed as averages ± standard deviations with 10 days operation. d Biomass fractions were determined by model predictions under different conditions. real-time quantitative PCR. e ND, not detected.

Figure 4. Measured concentrations during one cycle of operation (points: NH -N ( ), NO -N (4), Figure 4. Measured concentrations during one cycle of operation (points: NH44-N (■), NO2 2-N (△), NO3-N ( ), SMP (•).) and simulated results with the present model (lines) in the standard case NO3-N (○), SMP (●).) and simulated results with the present model (lines) in the standard case (granule# diameter 0.5 mm, DO 0.25 mg L−1, influent ammonium 500 mg N L−1). (granule diameter 0.5 mm, DO 0.25 mg L−1, influent ammonium 500 mg N L−1). 3.4. Evaluation of the Microbial Interactions in the Granules 3.4. EvaluationAs shown of the Microbial in Table1 ,Interactions the mean nitrate in the Granules concentration in the effluent was about −1 −1 As44 mgshown N L in, Table which 1, was the lowermean thannitrate the conc theoreticalentration value in the (55.5 effluent mg N Lwas) about calculated 44 mg N L−1,according which was to thelower PN/A than stoichiometry the theoretical [20]. value It can (55.5 be reasonably mg N L− expected1) calculated that denitrifica-according to tion of heterotrophs relying on SMP released by autotrophs as carbon source would occur in the PN/A stoichiometry [20]. It can be reasonably expected that denitrification of hetero- the system under oxygen limited condition. A similar result was also reported in nitrifying trophsgranules relyingfed on withSMPammonium released by as autotrophs the sole electron as carbon donor source [21]. Although would occur the formation in the system of underSMP oxygen enhances limited the condition. removal efficiency A similar of result nitrogen, was most also of reported the SMP in accumulated nitrifying granules in the fed witheffluence ammonium (40.37 mg asL the−1) duesole toelectron the quite donor slow biodegradation[21]. Although kinetic the formation of BAP. of SMP enhances theA removal large decrease efficiency of DO of concentration nitrogen, mo couldst of be the observed SMP accumulated within the external in the diffusive effluence (40.37boundary mg L−1) due layer to (Figure the quite5), which slow has biodegradation also been reported kinetic by other of BAP. authors [ 6,22]. AOB dom- Ainated large within decrease the firstof DO 100 concentrationµm below the could granule be surface, observed while within AMX the accumulated external diffusive in the boundaryinner oflayer the granule.(Figure Interestingly,5), which has AMX also still been survived reported in the by outermost other authors 100 µm layer [6,22]. of theAOB granule but their proportion decreased distinctly despite DO being present, which has also dominated within the first 100 μm below the granule surface, while AMX accumulated in been observed by FISH in previous studies [23,24]. Heterotrophs were present throughout the innerthe granule,of the granule. suggesting Interestingly, that SMP released AMX still by autotrophs survived canin the support outermost the heterotrophic 100 μm layer of thegrowth granule using but oxygen,their proportion nitrite or nitrate decreased as electron distinctly acceptor. despite DO being present, which has also been observed by FISH in previous studies [23,24]. Heterotrophs were present throughout the granule, suggesting that SMP released by autotrophs can support the heterotrophic growth using oxygen, nitrite or nitrate as electron acceptor.

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FigureFigure 5. Spatial 5. Spatial distribution distribution of ( ofA) (biomassA) biomass concentrations concentrations and and (B) (soluteB) solute concentrations concentrations along along the the − radiusradius of the of thegranules granules in the in thestandard standard case case (granule (granule diameter diameter 0.5 0.5mm, mm, DO DO 0.25 0.25 mg mg L−1 L, influent1, inﬂuent am- ammoniummonium 500 mg N L −1)1 )revealed revealed by by model model analysis. analysis.

3.5.3.5. Effect Effect of Dissolved of Dissolved Oxygen Oxygen on Heterotrophic on Heterotrophic Growth Growth In PN/AIn PN/A processes, processes, DO DO could could be considered be considered as the as thedominant dominant parameter parameter determining determining thethe process process performance. performance. Higher Higher DO DO levels levels lead lead to the to theinhibition inhibition of AMX of AMX and and the thedevel- devel- opmentopment of NOB, of NOB, whereas whereas a too-low a too-low DO DO leve levelsls limit limit the the oxidization oxidization of ofammonium ammonium and and reduce the nitrogen removal efficiency [25,26]. Figure6 summarizes the steady state reactor reduce the nitrogen removal efficiency [25,26]. Figure 6 summarizes the steady state reac- performance and the biomass fractions in the granule at different bulk liquid oxygen levels. tor performance and the biomass fractions in the granule at different− bulk1 liquid oxygen There is a clear peak of nitrogen removal efficiency at 0.25 mg O2 L . At this point, the ac- levels. There is a clear peak of nitrogen removal efficiency at 0.25 mg O2 L−1. At this point, tivity balance between AOB and AMX is obtained, and NOB is completely suppressed. the activity balance between AOB and AMX is− obtained,1 and NOB is completely sup- At very low DO concentrations (0.15 mg O2 L ), a fraction of ammonium remains in the pressed. At very low DO concentrations (0.15 mg O2 L−1), a fraction of ammonium remains effluent due to the oxygen limitation of AOB. Increasing DO concentrations would lead in the effluent due to the oxygen limitation of AOB. Increasing DO concentrations would to the inhibition of AMX, and thus result in the increase of nitrite concentration in the lead to the inhibition of AMX, and thus result in the increase− 1of nitrite concentration in effluent. When the DO concentration exceeds 0.75 mg O2 L , the nitrate concentration in the effluent. When the DO concentration exceeds 0.75 mg O2 L−1, the nitrate concentration the effluent increased dramatically, suggesting that NOB could effectively compete with in the effluent increased dramatically, suggesting that NOB could effectively compete AOB for oxygen and with AMX for nitrite. Besides, the concentration of SMP in the effluent with AOB for oxygen and with AMX for nitrite. Besides, the concentration of SMP in the and the fraction of heterotroph in the granule both increased with the increasing of the DO effluentconcentration and the fraction in the bulk of heterotroph liquid. This in could the granule be explained both byincreased the following with the reasons. increasing On the of theone DO hand, concentration the increased in the concentration bulk liquid. ofThis DO could could be reduce explained the competitionby the following for oxygen reasons.between On the heterotrophs one hand, the and increased autotrophs, concentration and thus promote of DO could the heterotrophic reduce the competition growth in the for granule.oxygen between On the other heterotrophs hand, the and content autotr ofophs, AOB and and thus NOB promote increased the significantly heterotrophic with growththe increasing in the granule. DO levels, On the which other could hand, enhance the content the SMPof AOB formation and NOB as increased the growth signif- rates of icantlynitrifier with is the much increasing higherthan DO thatlevels, of AMX.which Thecould high enhance SMP production the SMP formation should be as another the Water 2021, 13, x FOR PEER REVIEW growthreason rates for theof nitrifier increased is growthmuch higher of heterotroph. than that It of thus AMX. can beThe concluded high SMP8 of that10 production the effective

shouldcontrol be ofanother DO concentration reason for the is crucial increased for thegrowth operation of heterotroph. of PN/A process. It thus can be concluded that the effective control of DO concentration is crucial for the operation of PN/A process.

FigureFigure 6. Biomass 6. Biomass fractions fractions (A) and nitrogen (A) and removal nitrogen (B removal) at different (B) dissolved at different oxygen dissolved concentra- oxygen concentration −1 tion level.level. Simulation Simulation results results for 0.5 for mm 0.5 of mm granule of granule diameter, diameter, 500 mg N 500 L mg of influent N L−1 ammonium.of inﬂuent ammonium. 3.6. Effect of Granule Size on Heterotrophic Growth The depth of oxygen penetration inside the granule is highly dependent on the DO concentration in the bulk liquid and the granule diameter. Consequently, there exists an optimal DO concentration for maximum nitrogen removal efficiency at a certain granule size [27]. In order to evaluate the effect of the granule size on biomass fractions and nitrogen removal, simulations were performed for a broad range of granule diameters. It should be pointed out that the total concentration of granules (VSS) in the reactor has been set constant at 4000 g COD m−3 in these simulations, meaning that the number of granules was varied as the granule diameter. As shown in Figure 7, it can be observed that a high total nitrogen removal efficiency (>88%) could be achieved for all granule sizes ranging from 0.3 to 2.0 mm by controlling the bulk oxygen concentration within an optimal value. Moreover, as the granule diameter increases, higher bulk oxygen concentrations are needed to achieve maximum nitrogen removal. This can be attributed to the lower surface to volume ratio of spherical particles associated with larger granules, resulting in less aerobic and more anoxic volume.

Figure 7. Mode-base analysis for the influence of granule size on heterotrophic growth in the granules: (A) biomass fractions and (B) nitrogen removal. Note that simulations were performed under different granule diameters with corresponding optimal bulk oxygen concentrations.

The fraction of AMX in the granule did not change significantly with increasing granule size, whereas the fractions of AOB and HET decreased slightly (Figure 7A). This can be attributed to the increased oxygen concentration in the bulk liquid associated with larger granules, resulting in a higher activity for AOB and HET. However, little difference

Water 2021, 13, x FOR PEER REVIEW 8 of 10

Water 2021, 13, 324 8 of 10 Figure 6. Biomass fractions (A) and nitrogen removal (B) at different dissolved oxygen concentration level. Simulation results for 0.5 mm of granule diameter, 500 mg N L−1 of influent ammonium.

3.6.3.6. Effect Effect of ofGranule Granule Size Size on on Heterotrophic Heterotrophic Growth Growth TheThe depth depth of of oxygen oxygen penetration penetration inside inside the the granule granule is ishighly highly dependent dependent on on the the DO DO concentrationconcentration in in the the bulk bulk liquid liquid and and the the gran granuleule diameter. diameter. Consequently, Consequently, there there exists exists an an optimaloptimal DO DO concentration concentration for for maximum maximum nitrogen nitrogen removal removal efficiency efﬁciency at at a acertain certain granule granule sizesize [27]. [27 In]. order In order to evaluate to evaluate the effect the effect of the of granule the granule size on size biomass on biomass fractions fractions and nitro- and gennitrogen removal, removal, simulations simulations were wereperformed performed for a forbroad a broad range range of granule of granule diameters. diameters. It shouldIt should be pointed be pointed out that out the that total the totalconcentrat concentrationion of granules of granules (VSS) (VSS)in the inreactor the reactor has been has setbeen constant set constant at 4000 atg COD 4000 m g− COD3 in these m−3 simulations,in these simulations, meaning that meaning the number that the of number granules of wasgranules varied wasas the varied granule as the diameter. granule diameter. AsAs shown shown in in Figure Figure 7,7 ,it it can can be be observed observed th thatat a ahigh high total total nitrogen nitrogen removal removal efficiency efﬁciency (>88%)(>88%) could could be be achieved achieved for for all all granule granule sizes sizes ranging ranging from from 0.3 0.3 to to 2.0 2.0 mm mm by by controlling controlling thethe bulk bulk oxygen oxygen concentration concentration within within an an opti optimalmal value. value. Moreover, Moreover, as the granule diameterdiame- terincreases, increases, higher higher bulk bulk oxygen oxygen concentrationsconcentrations are needed to to achieve achieve maximum maximum nitrogen nitrogen removal.removal. This This can can be be attributed attributed to to the the lower lower surface surface to to volume volume ratio ratio of of spherical spherical particles particles associatedassociated with with larger larger granules, granules, resulting resulting in in less less aerobic aerobic and and more more anoxic anoxic volume. volume.

FigureFigure 7. 7.Mode-baseMode-base analysis analysis for the for influence the inﬂuence of granul of granulee size on size heterotrophic on heterotrophic growth growth in the gran- in the ules:granules: (A) biomass (A) biomass fractions fractions and (B) and nitrogen (B) nitrogen removal. removal. Note that Note simulations that simulations were performed were performed under differentunder different granule granulediameters diameters with corresponding with corresponding optimal optimalbulk oxygen bulk concentrations. oxygen concentrations.

TheThe fraction fraction of AMX of AMX in the in granule the granule did not did change not change significantly significantly with increasing with increasing gran- ulegranule size, whereas size, whereas the fractions the fractions of AOB of AOB and andHET HET decreased decreased slightly slightly (Figure (Figure 7A).7A). This This can can bebe attributed attributed to to the the increased increased oxygen oxygen concentration concentration in in the the bulk bulk liquid liquid associated associated with with largerlarger granules, granules, resulting resulting in in a ahigher higher activity activity for for AOB AOB and and HET. HET. However, However, little little difference difference is observed for the effluent concentration of SMP at varying granule size (Figure7B), indicating that the granule size has little influence on the production and biodegradation of SMP. This is mainly because the total biomass concentration (VSS) and ammonium sludge load remains constant in all simulations. It has been demonstrated by a previous study that solids retention time (SRT) and substrate volumetric load can heavily affect the accumulation of SMP [10]. Hence, the simulation results imply that increasing granule size could decrease heterotrophic growth, but hardly improve the effluent concentration of SMP.

4. Conclusions This study evaluated the microbial interactions between autotrophs and heterotrophs through the exchange of SMP in the PN/A reactor using experimental analyses and mathematical model. The following conclusions could be drawn: • The SMP secreted by autotrophs could support the growth of heterotrophs in the PN/A system, whereas most of the SMP (40.37 mg COD L−1) still accumulate in the efﬂuent due to the poor biodegradability. Water 2021, 13, 324 9 of 10

• The microbial compositions in the reactor obtained by qPCR showed that AOB, AMX, Nitrobacter, Nitrospira, and heterotrophs accounted for about 8.35%, 56.59%, 0.92%, 1.38%, and 32.76% of the total bacteria, respectively. • The bulk oxygen concentration is determined to be the dominant factor governing the process performance and biomass fractions in the granule. Increasing granule size could decrease heterotrophic growth, but has little effect on the efﬂuent concentration of SMP.

Supplementary Materials: The following are available online at https://www.mdpi.com/2073-4 441/13/3/324/s1, Table S1: qPCR primers used in this study. Table S2: Biofilm and mass transfer parameters used in this study. Table S3: Stoichiometry matrix for bioconversion processes in the model. Table S4: Kinetic rate expressions for bioconversion processes in the model. Table S5: Kinetic and stoichiometric parameters for bioconversions used in the model. Figure S1: Schematic representation of the mode set-up in AQUASIM. Author Contributions: Conceptualization, G.L. and Z.C.; methodology, G.L. and X.H.; data curation, J.M.; writing—original draft preparation, G.L.; writing—review and editing, Z.C.; supervision, H.R.; funding acquisition, Z.C. All authors have read and agreed to the published version of the manuscript. Funding: This work was financially supported by the National Science Foundation of China (51808141), and the Open Research Fund Program of Key Laboratory for Water Quality and Conser- vation of the Pearl River Delta (0601GD001). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study are available in Supplementary Material. Conflicts of Interest: The authors declare no conflict of interest.

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