Filamentous population in activated sludge and key operational parameters of full-scale municipal wastewater treatment plants (WWTPs) with bulking problems representative for Poland were investigated with quantitative fluorescence in situ hybridization. Statistical analyses revealed few relationships between operational parameters and biovolume of filamentous bacteria. Sludge age was not only positively correlated with abundance of Chloroflexi (parametric correlation and principal component analysis (PCA)), but also differentiated Microthrix population (analysis of variance (ANOVA)). Phylum Chloroflexi and pH presented a negative relation during the study (PCA). ANOVA showed that pH of influent and sludge volume index (SVI) differentiated abundance of types 0803 and 1851 of Chloroflexi and candidate division TM7. SVI increased along with higher abundance of Microthrix (positive parametric and non-parametric correlations and positive relation in PCA). Biovolumes of morphotypes 0803 and 1851 of Chloroflexi were differentiated by organic matter in influent, also by nutrients in the case of Chloroflexi type 1851. Chemical and biological oxygen demands (COD and BOD5, respectively) were negatively correlated with Microthrix. COD also differentiated the abundance of Haliscomenobacter hydrossis. Results of the study can be used to prevent WWTPs from excessive proliferation of filamentous bacteria and operational problems caused by them – bulking and foaming of activated sludge.

INTRODUCTION

Bulking and foaming of activated sludge occurs during excessive proliferation of a specific group of activated sludge biocenosis–filamentous bacteria. Those microorganisms impair settling and flocculating properties of sludge in secondary clarifiers, which results in the presence of solid particles in effluent (Kragelund et al. 2007, 2011; Miura et al. 2007). Poor settling ability of activated sludge and deterioration of the floc structure limit the effectiveness of dewatering processes (Eikelboom 2000). It also increases costs of wastewater treatment and lowers the quality of final effluent. The problems listed above arise mostly during changes in operating conditions, mainly in terms of organic load, nutrients and oxygen supply, and are reported by Jenkins et al. (2004) and Wanner & Jobbágy (2014) around the world. However, these problems are not easy to investigate due to difficulties with identification of filamentous bacteria according to morphology and chemical staining alone (Nielsen et al. 2009a; Wanner et al. 2009). For a long time Sphaerotilus was considered to be the main causative agent in this phenomenon, until Eikelboom (1975) conducted several researches and isolated many filamentous organisms, and wrote an identification key for filaments’ classification. Another important step in understanding filamentous bulking and foaming was made in the late 1990s by Blackall et al. (1994), Seviour et al. (1990, 1994) in Australia and Tandoi et al. (1998) in Italy, who isolated other key players in filamentous population of activated sludge – Gordonia and Microthrix parvicella. Those studies together with pure culture research with different substrates by Chiesa & Irvine (1985) and Jenkins et al. (1993) provided the base for comprehensive understanding of the ecophysiology of filamentous bacteria in activated sludge. What is more, thanks to that knowledge, control of filamentous bacteria growth became possible and strategies developed on metabolic and kinetic selection of microorganisms were used (Wanner 1994).

Expansion of molecular methods targeting nucleic acids resulted in expanding knowledge of identity of filaments in WWTPs. Fluorescence in situ hybridization (FISH) allows visualization of microorganisms with epifluorescence or confocal laser scanning microscopy. It uses DNA oligonucleotides with fluorochromes which bind to active cells with specific abundant ribosomal ribonucleic acid (rRNA). This method was optimized by Amann et al. (1990), and allowed not only for identification, but also visualization and quantification of bacteria without previous isolation. That was a revolution in comprehension of microbial ecosystem functioning (Nielsen & McMahon 2014). More reliable identification can be performed by culture-independent molecular methods, but only a few surveys have been carried out based on FISH analysis, as reviewed by Nielsen et al. (2009a), Wanner et al. (2009) and Wanner & Jobbágy (2014). Furthermore, determination of the impact of technological parameters on the populations of filamentous bacteria in activated sludge is also problematic (Eikelboom 2000; Mielczarek et al. 2012).

Miłobędzka & Muszyński (2015) showed that filamentous populations in five Polish WWTPs were rather similar to each other and only the abundance of Microthrix was differentiated by season. However, studies providing larger numbers of data, appropriate for statistical analyses, are needed to reveal factors that affect filamentous bacteria populations.

AIM

A 3-year study on population dynamics of filamentous bacteria in five Polish full-scale municipal WWTPs with nutrients removal was carried out. Quantitative fluorescence in situ hybridization (qFISH) was applied to evaluate the abundance of 11 groups of filamentous bacteria. Factors affecting the microbial population were searched for using statistical analyses.

This study was conducted to find relations between the filamentous bacteria in activated sludge and key parameters in five full-scale municipal plants with bulking problems representative for Poland. WWTPs differed in the configuration of reactors and main technological parameters of wastewater treatment process. During the study, chemical and operational data like biological and chemical oxygen demands in the process tank, total nitrogen and total phosphorus in influent, sludge age, sludge volume index (SVI) were measured to assess their influence on the microbial community. qFISH was used to define abundance of filamentous bacteria.

MATERIALS AND METHODS

Sampling

The study was carried out for 3 years, starting from 2011. Five full-scale municipal WWTPs, differing in treated wastewater and operational parameters, were selected for research. Activated sludge samples were collected after winter at the beginning of March, and after summer at the end of September, following the procedure recommended by Nielsen et al. (2009b).

FISH identification

FISH procedures were performed according to Nielsen et al. (2009b). The majority of the bacterial community was targeted with the 6-Fam labelled universal probe EUBmix (equimolar mixture of EUB338, EUB338II and EUB338III). Filamentous bacteria were identified with a wide selection of 11 oligoprobes (labelled with Cy3): CFXmix (equimolar concentration of GNSB-941 and CFX1223, targeting phylum Chloroflexi);T0803 (Chloroflexi type 0803); Chl1851 (Chloroflexi type 1851); MPAmix (equimolar concentration of MPA645, MPA223 and MPA60, targeting morphotype Microthrix); G123T (Thiothrix/type 021N); Myc657 (Mycolata group); Spin1449 (Skermania piniformis); Gor596 (family Gordonia); HHY654 (Haliscomenobacter hydrossis); Curvi997 (types 1701 and 0041/0675); and TM7905 (type 0041/0675). Detailed information about the oligoprobes can be found in probeBase (Loy et al. 2003).

Quantification of probe-defined bacteria

Quantification procedures were performed similarly to Mielczarek et al. (2012). Twenty separate images for each specific probe and another 20 corresponding images with EUBmix were captured with a Nikon Eclipse 50i microscope. ImageJ software (Collins 2007) was used to determine the biovolume of bacteria. The microbial abundance was quantified as the percentage of pixel area fluorescing with a specific probe (Cy3-labelled) in relation to the area fluorescing with the EUBmix probe (6-Fam-labelled) and it was then calculated as a mean of 20 separate measurements (expressed as % of the EUBmix probe).

Statistical analyses

Standard statistical analyses, correlation analyses (parametric with Pearson product-moment correlation coefficient and non-parametric with Spearman's rank correlation coefficient), analysis of variance (ANOVA) with significance level 0.05, principal component analysis (PCA) and cluster analysis were carried out in order to find differentiating factors and the strength of relationships between quantified bacteria populations and wastewater and operational data. Cluster analysis was performed, the Ward's method, using variance analysis to calculate the distance between the clusters. For cluster formation, the Euclidean distance was chosen. All analyses were performed in STATISTICA™ from StatSoft®.

RESULTS

Investigated wastewater treatment plants

All tested plants reported operational problems connected with settling of activated sludge, while foam was observed on the tanks only in WWTP IV. All five full-scale municipal investigated WWTPs had biological N-removal (nitrification and denitrification) and four of them (except WWTP II) also the enhanced biological phosphorus removal (EBPR) step. The plants ranged in size: 18,000–110,000 population equivalents (PE); also the fraction of industrial contribution to the organic matter in the influent depended on the plant, and it came mainly from the food industry and constituted 0–50%. All of the plants, except WWTP V dosed iron-based coagulants (PIX) to improve phosphorus elimination. WWTP V occasionally used polyaluminium chloride compounds (PAX), mostly during autumn and winter, to improve the settling properties and to control excessive growth of filamentous bacteria. The main operational parameters of selected plants are described in Table 1; more details can be found elsewhere (Miłobędzka & Muszyński 2015).

Table 1

Influent and operational parameters (mean values of data used for statistical analyses) of the WWTPs tested in this survey

Parameter WWTP I WWTP II WWTP III WWTP IV WWTP V 
Size designed (PE) 55,400 83,000 163,500 53,040 22,500 
Size actual (PE) 73,400 99,000 110,000 76,000 18,000 
Reactor type A2O AO Anaerobic tank + anoxic/aerobic oxidation ditch (oxidation-reduction potential controller) UCT A2O 
Predenitrification Yes No No No Yes 
Presettling Yes Yes Yes Yes No 
Fermenter Yes No No No No 
Aeration Fine bubble diffusers Surface (vertical type) Surface (horizontal rotors) Fine bubble diffusers Fine bubble diffusers 
Wastewater type (% of overall BOD5Domestic Domestic; industrial (20–25%): slaughterhouse, dairy Domestic; industrial (5–10%): fruit and vegetables processing, breweries, landfill leachate Domestic; industrial (30-50%): fruit and vegetables processing, sugar refining Domestic 
SVI [mL/g] Summer 218 178 223 89 139 
Winter 233 169 194 82 158 
COD [mg/L] 428 670 954 1,333 1,457 
BOD5 [mg/L] 268 311 352 927 431 
N total [mg/L] 66 69.4 83.3 72.8 87.2 
P total [mg/L] 10.6 10.8 17.1 15.5 20 
pH 7.7 7.6 7.7 7.4 8.4 
MLSS [g/L] 3.8 4.5 5.6 7.7 4.0 
SRT [d] 25 37 39 37 18 
Parameter WWTP I WWTP II WWTP III WWTP IV WWTP V 
Size designed (PE) 55,400 83,000 163,500 53,040 22,500 
Size actual (PE) 73,400 99,000 110,000 76,000 18,000 
Reactor type A2O AO Anaerobic tank + anoxic/aerobic oxidation ditch (oxidation-reduction potential controller) UCT A2O 
Predenitrification Yes No No No Yes 
Presettling Yes Yes Yes Yes No 
Fermenter Yes No No No No 
Aeration Fine bubble diffusers Surface (vertical type) Surface (horizontal rotors) Fine bubble diffusers Fine bubble diffusers 
Wastewater type (% of overall BOD5Domestic Domestic; industrial (20–25%): slaughterhouse, dairy Domestic; industrial (5–10%): fruit and vegetables processing, breweries, landfill leachate Domestic; industrial (30-50%): fruit and vegetables processing, sugar refining Domestic 
SVI [mL/g] Summer 218 178 223 89 139 
Winter 233 169 194 82 158 
COD [mg/L] 428 670 954 1,333 1,457 
BOD5 [mg/L] 268 311 352 927 431 
N total [mg/L] 66 69.4 83.3 72.8 87.2 
P total [mg/L] 10.6 10.8 17.1 15.5 20 
pH 7.7 7.6 7.7 7.4 8.4 
MLSS [g/L] 3.8 4.5 5.6 7.7 4.0 
SRT [d] 25 37 39 37 18 

MLSS, mixed liquor suspended solids; SRT, sludge retention time.

Process configurations: A2O, anaerobic–anoxic–aerobic; AO, anaerobic–aerobic.

Identity and abundance of filamentous bacteria

Filamentous bacteria were abundant in all tested plants and constituted on average 23 ± 2% of all bacteria identified by the universal probe EUBmix. The most abundant bacterial groups belonged to phylum Chloroflexi (CFXmix probe; 12% of all bacteria), genus Microthrix (MPAmix probe; 7%), and species Haliscomenobacter hydrossis (HHY654 probe; 2%). Chloroflexi type 0803, Chloroflexi type 1851 and candidate division TM7 accounted for minor fractions and usually did not exceed 2%. Mycolata and Skermania piniformis occurred just once, whereas Curvibacter, Thiothrix/021N and Gordonia were not found in any of the tested samples. More details about the abundance of specific bacteria in filamentous populations in Polish WWTPs can be found in a study focused on dynamics of filamentous bacteria in Polish plants by Miłobędzka & Muszyński (2015).

Correlation analyses

Only medium strength correlations were found between the abundance of specific filamentous bacteria and chemical or operational parameters (Table 2). Abundance of morphotypes 1851 and 0803 of phylum Chloroflexi was differentiated by several factors described below. On the other hand, Chloroflexi hybridizing with the broad phylum probe CFXmix were connected only with sludge age (positive parametric correlation; r = 0.453 with a significance level alpha = 0.012). What is more, Chloroflexi that were not further identified (not classified to morphotypes 0803 and 1851) were also in positive but non-parametric correlation to sludge age (r = 0.412, alpha = 0.024).

Table 2

Results of statistical analyses performed to find differentiating factors and relationships between quantified bacterial populations and chemical/operational data

Probe-defined bacteria Relationship Sludge age BOD5 COD SVI pH 
Chloroflexi type 0803 Parametric correlation        
Non-parametric correlation        
ANOVA    
PCA        
Chloroflexi type 1851 Parametric correlation       
Non-parametric correlation      
ANOVA  
PCA        
Chloroflexi Parametric correlation       
Non-parametric correlation        
ANOVA        
PCA      − 
Other Chloroflexi Parametric correlation        
Non-parametric correlation       
ANOVA        
PCA        
H. hydrossis Parametric correlation        
Non-parametric correlation        
ANOVA       
PCA        
Microthrix Parametric correlation   − −  
Non-parametric correlation  − −   
ANOVA       
PCA       
TM7 Parametric correlation       
Non-parametric correlation        
ANOVA     
PCA        
Probe-defined bacteria Relationship Sludge age BOD5 COD SVI pH 
Chloroflexi type 0803 Parametric correlation        
Non-parametric correlation        
ANOVA    
PCA        
Chloroflexi type 1851 Parametric correlation       
Non-parametric correlation      
ANOVA  
PCA        
Chloroflexi Parametric correlation       
Non-parametric correlation        
ANOVA        
PCA      − 
Other Chloroflexi Parametric correlation        
Non-parametric correlation       
ANOVA        
PCA        
H. hydrossis Parametric correlation        
Non-parametric correlation        
ANOVA       
PCA        
Microthrix Parametric correlation   − −  
Non-parametric correlation  − −   
ANOVA       
PCA       
TM7 Parametric correlation       
Non-parametric correlation        
ANOVA     
PCA        

BOD, biological oxygen demand; COD, chemical oxygen demand; N, total nitrogen; P, total phosphorus; SVI, sludge volume index; ‘ + ’, positive relations, ‘ − ’ negative relations. All presented correlations had medium strength.

Chemical oxygen demand (COD; non-parametric r = 0.442, alpha = 0.015) and biological oxygen demand (BOD5; parametric r = 0.378, alpha = 0.040; non-parametric r = 0.443, alpha = 0.014) were positively correlated with abundance of morphotype Chloroflexi type 1851 (Table 2).

Microthrix (targeted by MPAmix) contributed to the SVI increase, which was confirmed by positive parametric (r = 0.474, alpha = 0.008) and non-parametric (r = 0.446, alpha = 0.010) correlations. This genus was in negative relation to organic matter in influent (expressed as COD; parametric and non-parametric r = −0.372, alpha = 0.043) and BOD5 (non-parametric r = −0.511, alpha = 0.004) and total N (non-parametric r = −0.465, alpha = 0.010), as shown by negative correlations. Positive connection was found between Microthrix and total P (positive parametric: r = 0.574, alpha = 0.001 and non-parametric: r = 0.431, alpha = 0.017 correlations).

Candidate division TM7 was in positive parametric correlation (r = 0.387, alpha = 0.035) with pH in influent (Table 2).

Analysis of variance

ANOVA showed that abundance of Chloroflexi type 0803 was differentiated by COD, BOD5, pH and SVI. Those parameters, together with total P and total N also differentiated Chloroflexi type 1851.

Sludge age influenced the population of Microthrix; usually biovolume of this bacteria decreased when sludge age increased.

Abundance of filamentous candidate division TM was influenced by influent pH (both parameters slightly increased, but no visible link was noticed), total N (both increased) and SVI (higher abundance of bacteria when SVI decreased).

COD was the only factor differentiating in a statistically significant way the biovolume of H. hydrossis, and no pattern in this relation was observed.

Principal component analysis

The data were standardized in order to perform a transformation that would facilitate the comparison of values from numerous variables, irrespective of their distribution and the units they had been measured in. The analysis of factor coordinates points to a high correlation between BOD5, COD, Ntotal and Ptotal in the data set, within the first component. A high correlation within the second component involves pH and H. hydrossis (Table 3).

Table 3

Variable factor coordinates based on correlation

  F1 F2 
Chloroflexi type 0803 0.27 −0.19 
Other Chloroflexi −0.24 −0.83 
Chloroflexi −0.12 −0.86 
H. hydrossis −0.21 0.40 
Microthrix −0.50 0.35 
Sludge age −0.11 −0.72 
BOD5 0.87 −0.09 
COD 0.95 0.20 
Ntotal 0.86 −0.10 
Ptotal 0.90 0.09 
SVI −0.68 0.30 
pH 0.07 0.56 
  F1 F2 
Chloroflexi type 0803 0.27 −0.19 
Other Chloroflexi −0.24 −0.83 
Chloroflexi −0.12 −0.86 
H. hydrossis −0.21 0.40 
Microthrix −0.50 0.35 
Sludge age −0.11 −0.72 
BOD5 0.87 −0.09 
COD 0.95 0.20 
Ntotal 0.86 −0.10 
Ptotal 0.90 0.09 
SVI −0.68 0.30 
pH 0.07 0.56 

On the basis of the scree plot (not shown) and the information about the variance accounted for by particular components, two principal components, which explained 57% of variance, were identified. The biplot of the variables projection onto the factor plane is presented in Figure 1.
Figure 1

Principal component analysis showing differences and similarities in abundance of filamentous bacteria and chemical and operational parameters. Variables plotted onto the two-factor plane.

Figure 1

Principal component analysis showing differences and similarities in abundance of filamentous bacteria and chemical and operational parameters. Variables plotted onto the two-factor plane.

Connection between phylum Chloroflexi and sludge age shown by parametric correlation was also found with PCA. The analysis also revealed negative relation between phylum Chloroflexi and pH (Figure 1). Another relation which was confirmed by PCA was found for genus Microthrix and the SVI (Figure 1).

Cluster analysis

Connection between Microthrix and SVI and an obvious link between Chloroflexi and the group named in this study – ‘other Chloroflexi’ (further not identified fraction, result of morphotypes conducted from bacteria hybridized with CFXmix) can be seen in Figure 2. Different distinctions can be noticed for the three groups: (1) Chloroflexi type 0803, H. hydrossis, pH, Microthrix and SVI; (2) Chloroflexi and sludge age; and (3) with wastewater parameters: BOD5, COD, Ptotal and Ntotal constituting a different set.
Figure 2

Cluster analysis of investigated bacteria and parameter of wastewater.

Figure 2

Cluster analysis of investigated bacteria and parameter of wastewater.

DISCUSSION

Full understanding of the bulking mechanism has still not been achieved. Reasons for growth of filaments are very complex; however, some factors can be designated from a practical approach: high levels of sulfide, long solids retention time (SRT), low levels of food-to-microorganisms (F/M), nutrients, dissolved oxygen (DO) and pH (Wanner 1994; Jenkins et al. 2004; Grady et al. 2011). The conducted study allowed the connection of abundance of filamentous bacteria with other factors.

Factors affecting population structure

Sludge age was positively correlated with abundance of Chloroflexi (parametric correlation). A similar observation was made for a group of Chloroflexi which was not investigated in this study – named ‘Other Chloroflexi’. An example of the same connection was noticed for bacteria, which could be classified in this group and may be abundant in Polish WWTPs – morphotype 0914 hybridizing with probe CFX67. Abundance of type 0914 has been examined in Australian WWTPs by Speirs et al. (2011) and was higher in biological nutrient removal plants with long sludge age plants.

It was also revealed by ANOVA that sludge age differentiates Microthrix population; which is not surprising, because high sludge age is required for growth of Candidatus M. parvicella (Rossetti et al. 2005). For the same reason – slow growth rate and difficulties in maintenance in pure culture it is still named just ‘Candidatus’ and full characterization is not possible (Blackall et al. 1994; Rossetti et al. 2005; McIlroy et al. 2013).

pH of influent and SVI differentiated abundance of types 0803 and 1851 of Chloroflexi and candidate division TM7 (ANOVA). Although SVI depends on an abundance of filamentous bacteria, its influence on listed, quantified microorganisms can be the result of a different relation. A very strong correlation with other factors could have concealed the causative agent. Probably, a relation with Microthrix (described later) and proliferation of this bacteria could have decreased abundance of types 0803 and 1851 of Chloroflexi and candidate division TM7.

Phylum Chloroflexi and pH presented different behaviour during the study (PCA). The effect of those changes in pH is hard to interpret because only slight changes in this parameter were noticed during the whole period of study. Examples of pH influence on the abundance of Chloroflexi can be found in the literature (Miura et al. 2007), but bacteria were investigated in pilot-scale submerged membrane bioreactors and did not hybridize with probes for morphotypes found in Polish WWTPs. However, Miura et al. (2007) stated that utilization of glucose and N-acetyl glucosamine by bacteria affiliated with the Chloroflexi subphylum 1 was low at low pH.

SVI increased with higher abundance of Microthrix the dependence in the study was so strong that it was confirmed by all analyses: positive parametric and non-parametric correlations, similar relation in PCA, and cluster analysis. Similar results were presented by Westlund et al. (1996). Abundant Microthrix with filaments protruding from flocs corresponded to high SVI. On the other hand, a different study by Knoop & Kunst (1998) showed no negative effect on settleability of activated sludge with M. parvicella – bacteria did not impair the structure of flocs, because filaments from this genus were short.

Haliscomenobacter hydrossis, Chloroflexi and Microthrix belong to specialized filamentous bacteria involved in degradation of complex matter, but they utilize different substrates. Multiparticulates are decomposed with egzoenzymes like glucuronidase, phosphatase and chitinase, esterase by filamentous members of Bacteroidetes and Chloroflexi (Nielsen et al. 2010). In the study, the abundance of bacteria from BacteroidetesH. hydrossis was differentiated by COD of wastewater, while morphotypes 0803 and 1851 of Chloroflexi were also affected by BOD5. Phylum presents activity of egzoenzymes like galactosidase and protease.

Although Chloroflexi type 0803 has been shown by Kragelund et al. (2011) as able to store and to accumulate intracellular polyphosphate (polyphosphate granules were observed), in the presented study the second investigated Chloroflexi morphotype's biovolume – type 1851 was differentiated by concentration of nutrients in influent.

Candidatus M. parvicella can secrete lipase and esterase and assimilate long chain fatty acids under all e-acceptor conditions. Microthrix uptake different substrate – lipids, in various conditions (Nielsen et al. 2010), and that is why it can be in opposite relation to bacteria described earlier. COD and BOD5 were negatively correlated with biovolume of Microthrix.

In future it is advisable to use more advanced, modern techniques like DNA extraction, sequencing library preparation and sequencing or ribosomal intergenic spacer analysis and denaturing gradient gel electrophoresis to confirm results of identification of filamentous bacteria in Poland. Moreover, the development of new FISH probes for unidentified fraction Chloroflexi gives new possibilities to expand the scope of research and precisely classify which group of Chloroflexi studied factors had the most influence. Presented results of the study could be verified in a controlled laboratory-scale reactor. Another interesting aspect of such research would be knowing not only which factors have an influence on bacteria, but to what extent and what causes the connection.

CONCLUSIONS

Populations of filamentous bacteria in WWTPs with nutrients removal were affected by several factors. FISH investigation and statistical analyses revealed the following:

  • Sludge age was positively correlated with abundance of Chloroflexi and differentiated abundance of Microthrix.

  • pH of influent and SVI differentiated abundance of types 0803 and 1851 of Chloroflexi and candidate division TM7. Phylum Chloroflexi and pH presented different behaviour during the study.

  • SVI increased with higher abundance of Microthrix (positive parametric and non-parametric correlations).

  • Organic matter in influent (expressed as COD and BOD5) differentiated abundance of morphotypes 0803 and 1851 of Chloroflexi, and was also negatively correlated with Microthrix. COD of wastewater differentiated abundance of H. hydrossis.

  • Nitrogen and phosphorus in influent differentiated biovolume of Chloroflexi type 1851.

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