**3. Discussion**

The main objective of this study was to gain a better understanding of water quality parameters that correlated with *Legionella* occurrence within a large complex building water system (BWS) over an extended period of time. Cold bulk water and biofilm samples were collected to monitor the occurrence and distribution of *Legionella*, other water-based pathogens, and eukaryotic hosts, while considering seasonal fluctuations, and varying engineering, operational, and water quality characteristics. Cold water was analyzed in this study given (1) the high prevalence of *Legionella* contamination previously identified in cold water samples within public building, private residences, healthcare facilities, and water storage tanks; (2) *Legionella* transmission and infections epidemiologically linked to cold water exposure; and (3) the current recommendations to monitor both hot and cold water in BWS to control for *Legionella* [33]. In this study, both culture and molecular methods were used for *Legionella* detection and culture isolates were submitted for whole genome sequencing for further genetic characterization.

Two percent of biofilm samples (1/57) and 12% of bulk water samples (14/114) were culture-positive for *Legionella* of which 57% (8/14) were isolated during the winter; 21% (3/14) during the summer; 14% (2/14) during the fall; and 7% (1/14) during the spring. Legionnaires' disease (LD) cases typically peak during the summer and fall seasons [34,35]. However, other epidemiological studies reported a winter peak for non-travel related cases [36] and no monthly or seasonal correlations for nosocomial-acquired [37] and community-acquired *Legionella* pneumonia cases [38]. Higher incidences of legionellosis have been associated with various meteorological factors (e.g., humidity, temperature, rainfall, atmospheric pressure); geographic location; and properties of the local watershed and source water (e.g., proximity and water temperature, levels, and flow) [39–42]. Thus, the exact environmental mechanisms and triggers of *Legionella* transmission and subsequent disease incidences are ye<sup>t</sup> to be clearly defined.

Culture and qPCR are frequently used methods for *Legionella* environmental detection [43–45]. However, due to discrepancies between and within each of these methods, interpretations of *Legionella* occurrence across various studies and correlations to legionellosis health risks within BWSs are challenging [46]. Moreover, false positivity rates for the Legiolert® method have been reported to be

between 0% and 3.3% for potable water and 4.9% and 11% for non-potable water [47–49]. Such as with *Ochrobactrum* identified in the PVC-Loop location, stable colonization of a Legiolert® false positive causing strain at an environmental monitoring site may continually overestimate *L. pneumophila* levels and confound interpretations of their occurrence at those sites. Culture-based methods are a reliable indicator of pathogen viability and potential health risks associated with *Legionella* detection; however, periodic validation of culture-based results can be performed using molecular methods.

In this study, the PVC-R W2018 first draw sample was *Legionella* culture positive, but *Legionella* qPCR negative (Table 3, Figure 1b), while the PVC-FC Su2018 second draw sample was *Legionella* and *L. pneumophila* culture positive, but only *L. pneumophila* qPCR negative (Table 3, Figure 1c and i). Culture-positivity/qPCR-negativity has been observed previously and was associated more with drinking water compared to cooling tower water samples [50–52]. Furthermore, *L. pneumophila* qPCR levels were higher than those of *Legionella* spp. in four first draw samples (Spigot F2017, W2019 and Fountain F2017, Su2018) (Figure 1d, j and f, l) and *L. pneumophila* was also observed in hot water, but not cooling tower water samples [53]. These discrepancies have been attributed to the presence of PCR inhibitors and competing non-target organisms, and varying culture conditions (e.g., growth temperature, agar type) and sample processing steps that may select for, or inhibit growth of, different strains of *Legionella* [46].

For *Legionella* environmental monitoring, samples that can be collected for analysis include (1) biofilm materials, which contain a concentration of surface attached microorganisms; (2) first draw, stagnant water samples, which represent water quality at the outlet; and (3) second draw, post-flushed samples, which represent water quality supplied to the outlet from within the building water system [54,55]. Of the *Legionella pneumophila* and non-*pneumophila* culture-positive bulk water samples, 64% (9/14) were first draw and 36% (5/14) were second draw samples, while only 2% (1/57) of biofilm samples were culture-positive (Table 3). From the qPCR analyses, *Legionella* was detected in 30% (17/57) of biofilm samples and 74% (84/114) of bulk water samples of which 48% (40/84) were first draw and 52% (44/84) were second draw samples. *L. pneumophila* was detected in 23% (13/57) of biofilm samples and 36% (41/114) of bulk water samples of which 59% (24/41) were first draw and 41% (17/41) were second draw samples (Figure 1).

Differences in physiochemical and microbial water quality parameters between first and second draw samples were previously reported with microbial loads generally higher in the first draw depending on the sampling location and volume collected [56,57]. As stated in Section 2.1, there were no statistical differences in pH, temperature, free chlorine, monochloramine, and total chlorine between the first and second draw samples at all locations with the exceptions of temperature for the Spigot samples and free and total chlorine for the Faucet samples. Three of the six locations had statistical differences between the first and second draw samples for HPCs: PVC-R, Spigot, and Faucet. For *Legionella* levels detected by qPCR, there were strong positive correlations between the first and second draw samples from all locations: PVC-MA (r = 0.9, *P* < 0.001), PVC-R (r = 0.6, *P* < 0.05), PVC-FC (r = 0.9, *P* < 0.01), Faucet (r = 0.8, *P* < 0.01), and Fountain (r = 0.8, *P* < 0.01), except for the Spigot location (r = 0.2, *P* = 0.575). For *L. pneumophila* levels as detected by qPCR, there were only strong positive correlations between the first and second draw samples at three of the six locations: PVC-MA (r = 1.0, *P* < 0.001), PVC-FC (r = 0.9, *P* < 0.01), and Faucet (r = 0.7, *P* < 0.05).

The results between the bulk water samples suggested that an analysis of either the first or second draw samples was able to indicate the presence of *Legionella*. Moreover, it is unclear why only the Faucet location showed statistical differences of both free and total chlorine between the first and second draw samples as water usage at this site was higher than two other locations and the distance of the Faucet outlet was greater than and almost equal to three other sampling locations (Table 1). The only difference between the Faucet location and all others was the ability to draw hot water from this outlet, but only cold water was analyzed in this study; thus, hot water may be contributing to bacterial contamination in the Faucet.

After conversion to monochloramine disinfection within BWSs, there were reductions in the number of distal sites testing positive for *Legionella* (39–100% to 0–18% positivity); however, there was a large range in the log reduction of *Legionella* levels (0.2 to 3 log10 CFU <sup>L</sup>−1) with one study reporting no changes in levels post-conversion during the one- to three-year monitoring period [58–60]. Control of biofilm-associated *Legionella* was also observed [58,61], most likely due to the better penetration of monochloramine into biofilms compared to chlorine [62]; however, control of biofilm-associated *L. pneumophila* (Lp) was previously reported to be pipe material specific during chlorine and monochloramine treatment [63]. The PVC-MA location used in this study has been operating with a monochloramine residual for approximately 10 years with a two-month chlorine conversion from December 2013 to February 2014. During the sampling period, no culturable *Legionella* was detected, but molecular analyses indicated a consistent and high level of *Legionella* and sporadic detection of *L. pneumophila* in the bulk water and biofilm samples. Specifically, 100% (20/20) of the bulk water samples and 10% (1/10) of biofilm samples had detectable *Legionella*; while *L. pneumophila* was detected in 30% (6/20) of bulk water samples (three first draw and three second draw samples) and 10% (1/10) of biofilm samples (Figure 1a and g). Using *E. coli*, monochloramine was shown to disrupt protein-mediated metabolic processes with no damage to the cell envelope or nucleic acids [64]. This finding is supported by other studies demonstrating no significant impacts on *Legionella* 16S rRNA gene transcript levels during monochloramine versus chlorine treatment [63] and *Pseudomonas aeruginosa* extracellular polymeric substances material limiting and delaying monochloramine access to the cell surface [65]. Thus, it is unclear what the exact mechanisms are for monochloramine control of *Legionella* bacteria and whether different surface properties (e.g., lipopolysaccharides used for *L. pneumophila* serogroup identification) would result in varying degrees of inactivation with intermediate stages allowing for *Legionella* regrowth.

Numerous studies have reported more frequent detection of *V. vermiformis* within BWSs compared to *Acanthamoeba* spp. [56,66,67]. Concordantly, *Acanthamoeba* spp. were undetectable in the bulk water and biofilm samples during F2016, thus the following five sampling time points were excluded; however, the analysis was resumed in Sp2018 to confirm the low frequency and/or undetectable observation for *Acanthamoeba* spp. in BWS samples (Figure 2g–l). *Acanthamoeba* spp. was detected in only one second draw sample at the PVC-MA location (Figure 2g). Similarly, *M. intracellulare* was infrequently detected in this study (Figure 2n and p) as previously observed for water samples from chlorinated BWSs [23,68]. *V. vermiformis* was detected at all locations except PVC-R (Figure 2a–f) with positive correlations between *L. pneumophila* and *V. vermiformis* in PVC-FC biofilms and Faucet first draw samples. Given that FLA detection has been correlated to *Legionella* and *Mycobacterium* in drinking water systems [69], there is utility in monitoring for FLA to better understand the conditions and FLA members contributing to *Legionella* and mycobacterial survival within BWSs.

Although diverse populations of *Legionella* bacteria have been described in drinking water [70,71], environmental monitoring of BWSs focuses primarily on *L. pneumophila* detection since this species makes up the majority of clinical isolates, with > 80% of those isolates belonging to serogroup (sg) 1 [72,73]. Serotyping allows for the differentiation of *L. pneumophila* isolates based on their reactivity to the Dresden Panel of antibodies that recognize distinct structures on the bacterial lipopolysaccharide molecule [74,75]. *L. pneumophila* contains 17 serogroups and 10 subgroups within sg1 [76,77]. The latex agglutination serotyping method used in this study has been shown to produce false negatives as *Legionella*-like colonies isolated from drinking water samples, confirmed as *L. pneumophila* via 16S rRNA sequence analyses, were agglutination negative (this study; [78]). Thus, molecular-based methods, such as sequence-based typing (SBT) and whole genome sequencing (WGS), are increasingly being used due to their reliability, better resolution, and discriminatory power for describing genetic diversity, environmental distribution, evolution, population structure, clonal expansion, and virulence properties of *Legionella* isolates [77,79].

In this study, *L. feeleii*, *L. pneumophila* sg1 sequence-type (ST) 1, and *L. pneumophila* sg5 ST 1950 and ST2037 were identified via 16S rRNA-based analyses, serotyping (latex agglutination and indirect immunofluorescent antibody assays), WGS, and SBT analyses. These unique *Legionella* strains were

isolated from the Faucet, PVC-FC, PVC-Loop, and BWS Supply Line locations during the Su2018, F2018, and W2019 time points (Table 4 andFigure 4). ST1 is the most commonly identified and globally distributed strain isolated from both environmental and clinical samples ([79,80]; this study). Identification of previously unknown STs (e.g., ST1950 and ST2037 from this study) supports the continued SBT of clinical and environmental isolates. This will help elucidate which STs may be more globally distributed or geographically confined, and which are more associated with disease cases, such that when those are environmentally identified, preventative measures can be implemented to limit public health and exposure risks to these pathogens. WGS analyses provide more detailed genetic information about the *Legionella* strain, beyond those obtained from SBT alone, enabling potential subspecies identification, refined taxonomic classification, and genetic profiling for virulence properties [77]. *Legionella* diversity and distribution data may also reveal environmental parameters that influence *Legionella* occurrence and survival within specific environments such as BWSs.

Due to lengthy incubation periods required for *Legionella* culture, the tendency for qPCR to overestimate their levels, and the discrepancies associated with these methods, as described above, use of other microbial and/or physiochemical water quality parameters as potential indicators for *Legionella* presence in BWSs has been investigated [70]. As described in Section 2.5, there were strong statistical correlations observed between various water quality parameters and *Legionella* occurrence such as *V. vermiformis*, HPC, chlorine residual, temperature, and turbidity (Figure 3). However, these correlations were location and sample type specific with conflicting positive and negative correlations for turbidity and HPC. Conflicting correlations between the latter and *Legionella* levels have been reported previously with either strong correlations [81], no correlations [82–85], or possible seasonal dependencies for these correlations [7]. Other conflicting correlations were reported between *Legionella* occurrence and pH, temperature, various minerals and metals (Ca, Cu, Fe, Mg, Mn, and Zn), total organic carbon, conductivity, and free chlorine at the sampling site and building supply feed [85–87].

Thus, further analyses of existing data and correlations to *Legionella* occurrence, as well as more in-depth studies on identifying these correlations, need to be performed. This will enable determinations as to whether correlations are dependent on complex factors, either individually or in concert, such as disinfectant type; source water quality fluctuations; genetic background of detected *Legionella* populations; presence of other drinking water microorganisms; or certain engineering and operational water system aspects specific to sampled locations. The notable observations from this study were (1) detection and culture of *Legionella* from outlets that neither supply, nor are connected to plumbing for, hot water; (2) isolation of diverse *L. pneumophila* and non-*pneumophila* strains from different locations; (3) utility of whole genome sequencing and sequence-based typing for enhanced isolate description and characterization of their distribution; (4) *Legionella* levels detected during monitoring can significantly differ between the first and second draw sample; and (5) negative and positive correlations between *Legionella* and various water quality parameters were location and sample type specific.

Confoundingly, occurrence alone is not the most important factor for legionellosis risk. Environmental, bacterial, and host specific factors such as aerosolization into respirable droplets and their potential for human exposure; virulence of the environmental *Legionella* strain; and host immune status and susceptibility to infection, collectively play an important role in exposure risks and disease outcome. The main objective of this study was to gain a better understanding of *Legionella* occurrence and water quality parameters supporting their growth within a large, complex building water system. Information from this, and future studies, will help elucidate ways to effectively manage the risks associated with *Legionella* exposure within these drinking water distribution systems.

#### **4. Materials and Methods**
