Performance evaluation of a low-throughput qPCR-based 
Legionella is a genus of bacteria found at low populations across aquatic environments, commonly in relationship with protozoan hosts (Berjeaud et al., ; Collins et al., ). At least 24 species of Legionella have been found to cause illness (legionellosis) in humans (Díaz-Flores et al., ). Exposure occurs through inhalation of aerosolized bacteria from a water source containing populations of Legionella , which may cause respiratory illness in individuals with various risk factors (Llewellyn et al., ; Young et al., ), including advanced age, compromised immune function, smoking and chronic lung disease, and underlying disease states (Collins et al., ; Llewellyn et al., ). Legionella often proliferate in man-made water systems such as domestic, institutional, and industrial water systems (Berjeaud et al., ; Díaz-Flores et al., ). In natural water sources, the bacteria pose little threat to humans as nutrient levels and temperatures are generally too low to support high populations (Percival & Williams, ). However, in the built environment, Legionella populations can grow to higher population densities with greater potential for exposure and illness (Llewellyn et al., ; Young et al., ). Water conditions in man-made environments such as cooling towers, with temperatures ranging from 20 to 45 °C, are generally beneficial to Legionella growth (Collins et al., ; Toplitsch et al., ), and these systems contain contaminants like biofilm, scale, and sediments that also support Legionella growth by providing nutrients and protection (Llewellyn et al., ; Young et al., ). One study from the U.S. Centers for Disease Control and Prevention found that most cooling towers sampled across the USA had detectable quantities of Legionella DNA, and that this DNA may be present even when biofouling is managed with appropriate treatment programs (Llewellyn et al., ). Given the potential health hazards that these bacteria pose, Legionella populations are commonly monitored across man-made water systems (Krøjgaard et al., ; Young et al., ). Two methods are most widely used in analytical labs for Legionella monitoring: culture-based testing and quantitative polymerase chain reaction (qPCR) (Whiley & Taylor, ). Culture-based Legionella testing is considered the “gold standard” of monitoring (Collins et al., ; Díaz-Flores et al., ; Young et al., ). Culture testing quantifies Legionella populations by enumerating the bacteria, with populations greater than or equal to 10 2 (Ahmed et al., ) or 10 4 –10 10 colony-forming units (CFU)/ml (Díaz-Flores et al., ) considered to be a potential risk to human health. Culture results are based on the growth of Legionella in selective medium with incubation periods of up to 10 days, due to slow growth of the bacteria (Toplitsch et al., ). Culture testing faces multiple limitations, including long turnaround time and loss of culturable populations during sample transport or holding, and may provide inconclusive results due to interfering organisms present in the sample, among other issues (Díaz-Flores et al., ). Inconclusive results due to the growth of microbes in the sample other than Legionella species can occur in up to 20% of samples (Díaz-Flores et al., ). This method may also underestimate Legionella populations due to the inability to detect viable but nonculturable organisms (Díaz-Flores et al., ). The commonly 10-plus day turnaround time of this methodology can limit the speed of remediation treatments; if a concerning population density is eventually detected, yet mitigation efforts are withheld until these results are delivered, this turnaround time can represent a significant number of opportunities for exposure. Given the limitations of culture testing, additional methods of Legionella monitoring are being explored and utilized. qPCR allows for more rapid quantification of bacterial populations and possibility of same-day results (Young et al., ). qPCR testing works by amplifying, detecting, and quantifying specific nucleic acid targets in a sample, and measuring the amount of the target nucleic acid present through fluorescent labeling of PCR products (Botes et al., ). qPCR-based Legionella testing has multiple advantages over culture-based testing, including the detection of viable but nonculturable organisms, more rapid detection of Legionella population levels, and lower limits of detection for Legionella than culture-based methods (Díaz-Flores et al., ; Yaradou et al., ; Young et al., ). Field tests may provide more useful and representative results for a specific system by reducing time between sample collection and testing (Ahmed et al., ). Currently, qPCR has been found effective for routine monitoring in cooling towers and as a valuable tool to trend populations (Yaradou et al., ; Young et al., ), and is useful in screening out Legionella -negative samples prior to conducting culture-based testing (Collins et al., ; Toplitsch et al., ). However, qPCR field testing for Legionella has had limited application because qPCR measures concentrations of DNA, which is difficult to correlate with CFU/ml as measured in culture-based testing (Young et al., ). Most guidance and regulations on Legionella monitoring only specify target population densities in terms of CFU/ml values (Young et al., ), and without regulations that include qPCR results, it would be difficult to shift to qPCR testing exclusively. Field-based qPCR testing is still in its infancy compared to lab-based qPCR but has recently garnered more interest as a means of faster and more accurate pathogen detection and water quality monitoring (Billington et al., ; Sanchez et al., ). Rapid molecular biology tests that are specific and sensitive to detecting their target could be a very useful tool for identifying issues with Legionella and other pathogens that present public health risks, particularly for negative screening in systems where routine testing is needed or required and could be supplemented with culture-based testing. Field-based qPCR testing returns results notably faster than shipping samples to an external lab for culture or qPCR testing. Faster return of results allows for rapid evaluation of the effectiveness of biological controls in place, and for timely alteration of treatments if Legionella population densities increase. Faster testing and adjustment of treatment programs may allow for optimization of biocide treatment as well as ecological benefits from reduced biocide feeds (Yaradou et al., ; Young et al., ). A variety of Legionella qPCR testing kits are available on the market (LuminUltra's GeneCount™ LT qPCR Assay Kit for Legionella species, Bio-Rad's iQ-Check™ Quanti Legionella spp., Promega's Legionella qPCR Kits with Live/Dead Cell Differentiation, Spartan Bioscience Inc.’s Legionella Detection System, etc.) for use in Legionella monitoring, some of which utilize viability qPCR to measure exclusively DNA from live bacteria (Lizana et al., ). qPCR has been evaluated for repeat testing in some cooling tower systems for complexes of factories (Young et al., ); prior studies primarily focus on monitoring a small number of systems and system types and have not assessed field-deployable qPCR tests across a variety of water sample types from a wide variety of independent industrial sites across multiple different industries, as was explored in this study. To evaluate the utility of an LT qPCR test for Legionella in industrial water systems, the authors tested a variety of industrial water samples by three different Legionella detection methods: a culture-based test, a high-throughput lab-based qPCR testing method (HT qPCR), and a low-throughput qPCR test kit (LT qPCR) that can be used in the field; each of the qPCR tests measures all Legionella species within a sample. This study compared the agreement between the methods in detecting the presence and quantity of Legionella in man-made water systems, primarily industrial cooling towers and closed loops. This comparison was conducted to better understand the strengths of the LT qPCR method, its negative predictive capability across different industrial water sample types, and the likelihood of increased positive results returned by LT qPCR testing (as compared with culture testing) due to higher sensitivity to detect all Legionella DNA present in a sample. The LT qPCR test utilized in this study has a turnaround time of about 2–3 hours for DNA extraction and amplification, which is markedly faster than culture testing, utilizes more transportable equipment than HT qPCR testing, and can test up to 14 samples at once plus a positive and negative control. Due to its faster turnaround time and greater sensitivity than culture testing, LT qPCR testing may be an effective option for negative screening at industrial sites with high-frequency Legionella testing requirements. 

Three test methods were compared in this study: culture-based testing performed by a certified lab, an HT qPCR test performed at LuminUltra Technologies Ltd. for all Legionella species, and an LT qPCR test kit from LuminUltra, which tests for presence of all Legionella species and is field deployable. The HT and LT qPCR methods use the same primers for DNA amplification but use different DNA extraction protocols and different instruments for thermocycling; this difference in DNA extraction protocol and thermocycler used is what allows the LT qPCR method to be accessible as a portable field-testing method. The LT qPCR method was compared with the lab-based HT qPCR to determine whether there were any performance differences between the methods. Water samples included in this study were collected at independent sites across the USA; samples were collected in one bottle and shipped overnight to ChemTreat. Upon arriving each sample was divided into three bottles for testing via each of the three methods (Fig. ). Upon arrival, a portion of each sample was shipped overnight to a certified Legionella testing laboratory for standardized culture-based testing, arriving within 48 hr of collection. The lab follows ISO standard 11731:2017 (ISO 11731:2017, 2017).. This method can be purchased from the American National Standards Institute webstore. Results are returned within 7–14 days. Upon arrival, a portion of each sample was tested in the ChemTreat R&D lab by the LuminUltra LT qPCR method. Testing was performed according to the manufacturer’s instructions on the day of sample arrival at the lab. For the LT qPCR test, 50 ml (samples 1–45) or 100 ml (samples 45–77) was processed using the GeneCount LT DNA Purification kit, product code 50-30-30054, and the GeneCount qPCR Legionella Species Assay kit. Upon arrival, a portion of each sample was preserved to be sent to LuminUltra for HT qPCR. To preserve the sample, 100 ml of sample is filtered through a 0.2-µm polyethersulfone (PES) filter, and the filter paper is placed into a DNA preservation buffer tube containing lyophilized preservation buffer A, to which 1.5 ml of nuclease-free water is added and the sample is vortexed. Samples preserved for HT qPCR were stored in a fridge at 36 °F for up to 2 weeks prior to shipping to LuminUltra for the HT qPCR test for Legionella species. LuminUltra moved from an HT manual DNA extraction method to a qKit automated DNA extraction method during this project. Samples 1–6 were tested with a separate method not described in this report as all six samples tested negative. Samples 7–45 were tested with the HT procedure using manual DNA purification. Samples 46–77 were tested with the qKit automated DNA purification method. The HT manual DNA purification used on samples 7–45 uses phenol chloroform isoamyl alcohol extraction and spin column purification prior to qPCR, whereas the qKit extraction uses magnetic bead DNA purification. A comparison between the LT and HT qPCR DNA extraction protocols is shown below. For both the LT and HT qPCR assays, positive and negative results for qPCR are determined by the critical threshold (Ct), which is the number of amplification cycles needed for a fluorescence signal to pass above a set threshold. Samples that are positive will have early to moderate Ct values indicating presence of a moderate to high abundance of the gene target in the sample, and samples that are negative will have late Ct values indicating low to no abundance of a gene target in the sample and indicating that the amount of the gene target in the sample is close to the limit of detection of the assay. Positive and negative determination is set by the software and instrumentation provided by LuminUltra. qPCR results within the limit of quantification of the assay (12 genomic units (GU)/reaction for Legionella species) are quantified. A total of 77 samples were collected and tested in parallel with each method described above. Several samples were retested via the LT qPCR test where technical difficulties arose; extracted DNA used for the LT qPCR testing was stored in a fridge at 36 °F in case of a need to retest samples. Assay Design and Validation The Legionella GeneCount® assays have undergone extensive laboratory testing, including rigorous design for specific and sensitive assay targets. All manufacturer qPCR validation experiments were performed in duplicate (at minimum), including (but not limited to) positive control, negative control, internal control (where applicable),next generation sequencing (NGS)-confirmed environmental samples, and at minimum 7 points from a tenfold dilution series of synthetic template (typically 2.4 million copies down to 2.4 copies). The Legionella assays were designed with proprietary mastermix reagents and were run in GeneCount® Q-Series devices. Data analyses were performed with GCQ-48 and GeneCount® software with autointegration and preset assay parameters. Assay components are freeze-dried and dispensed into eight-tube (0.2 µl) assay strips (48 total reactions). The freeze-dried assays include all necessary components for the reaction including primers, probes, deoxyribose nucleotide triphosphate (dNTP), and polymerase. The GeneCount® thermocycler has preset software settings programmed for Legionella assay detection, with the following cycling conditions: Heat to 95 °C for 3 min (1 cycle), and then 95 °C for 20 s followed by 60 °C for 60 s for 45 cycles. The GeneCount® LT extraction method and Legionella sp. assays have been previously validated by a third-party lab in accordance with the performance requirements outlined in ISO-12869 (2017). The methods were verified for inclusivity and/or exclusivity, linear regression curve for calibration, amplification efficiency, limit of detection and quantification, extraction recovery, and robustness (Duguay et al., ; LuminUltra, ). The Legionella sp. assay has an limit of detection (LOD) of five gene copies/reaction. 

The Legionella GeneCount® assays have undergone extensive laboratory testing, including rigorous design for specific and sensitive assay targets. All manufacturer qPCR validation experiments were performed in duplicate (at minimum), including (but not limited to) positive control, negative control, internal control (where applicable),next generation sequencing (NGS)-confirmed environmental samples, and at minimum 7 points from a tenfold dilution series of synthetic template (typically 2.4 million copies down to 2.4 copies). The Legionella assays were designed with proprietary mastermix reagents and were run in GeneCount® Q-Series devices. Data analyses were performed with GCQ-48 and GeneCount® software with autointegration and preset assay parameters. Assay components are freeze-dried and dispensed into eight-tube (0.2 µl) assay strips (48 total reactions). The freeze-dried assays include all necessary components for the reaction including primers, probes, deoxyribose nucleotide triphosphate (dNTP), and polymerase. The GeneCount® thermocycler has preset software settings programmed for Legionella assay detection, with the following cycling conditions: Heat to 95 °C for 3 min (1 cycle), and then 95 °C for 20 s followed by 60 °C for 60 s for 45 cycles. The GeneCount® LT extraction method and Legionella sp. assays have been previously validated by a third-party lab in accordance with the performance requirements outlined in ISO-12869 (2017). The methods were verified for inclusivity and/or exclusivity, linear regression curve for calibration, amplification efficiency, limit of detection and quantification, extraction recovery, and robustness (Duguay et al., ; LuminUltra, ). The Legionella sp. assay has an limit of detection (LOD) of five gene copies/reaction. 

From May 2022 to May 2023, 77 samples were collected and tested for Legionella as part of this study to evaluate the negative predictive capability of an LT qPCR method across different industrial water sample types, and the likelihood of increased positive results returned for LT qPCR testing (as compared with culture testing) due to higher sensitivity to detect all Legionella DNA present in a sample. A diverse set of water samples were collected, including potable and nonpotable water sources from a range of locations, as shown in Fig. . Results by Method In this study both the LT and HT qPCR methods returned positive results with a higher frequency than the culture-based method; this is in line with a prior study that also compared both qPCR and culture-based methods concurrently and indicated that qPCR testing is 50–100% more likely to return a positive result than testing by culture (Young et al., ), and agrees with other studies indicating higher rates of positive results via qPCR than by culture, such as Lee et al. . In this study, 6 samples out of the 77 total samples (7%) tested positive by culture, 26 samples (33.8%) tested positive by the LT qPCR test, and 41 samples (53.3%) tested positive by the HT qPCR test, shown in Fig. . The results from the LT and HT qPCR tests largely agreed, with 23 of 77 samples (29.9%) testing positive by both methods. In cases where the qPCR results did not agree, it was primarily the case that the HT qPCR lab test returned positive results where the LT qPCR test returned negative results. There were 18 samples out of the 77 total (23.4%) that had a positive result for Legionella via the HT qPCR test, but those same samples tested negative with the LT qPCR test. Three samples tested positive by LT qPCR but negative by HT qPCR. These disagreements could be due to differences in the DNA extraction methods used and/or sample holding times. While both the LT and HT methods meet the performance requirements outlined in ISO-12869 (2017) for extraction efficiency and robustness, the LT qPCR test produces lower purity DNA, which could lead to the differences in results between the assays, and there could also be qPCR inhibition due to sample components occurring at quantities that interfere with extraction efficiency. The LT samples were normally tested within 24 hr of sample collection; however, the HT samples were preserved at the time of sample collection and shipped to the lab for analysis (normally within 2 weeks). Overall, these results reflect that the qPCR tests returned positive results at a higher rate than culture-based testing. Results Returned by Sample Type The 77 samples included in this study were from 34 cooling towers, 26 closed cooling loops, 5 open cooling loops, 3 reverse osmosis (RO) feedwaters, 3 showerheads, 2 faucets, 1 condenser, and 1 decorative fountain. A detailed breakdown of the positive and negative results by system location is shown in Table . Of 77 samples, 6 tested positive for Legionella via culture testing, all of which were cooling tower samples. Of the cooling tower samples, 44.1% (15 samples) tested positive by the LT qPCR test and 70.6% (24 samples) tested positive by the HT qPCR test. The high positivity rate in cooling water is consistent with other studies that have shown the presence of Legionella in these locations, where water temperature, nutrients, and dynamic water flow create ideal biofilm conditions and lead to the rapid proliferation of the bacteria (Atlas, ; Fitzhenry et al., ; Young et al., ). Legionella has been found, in some instances, to be tolerant of heat and biocides (Toplitsch et al., ; Whiley & Taylor, ), among other stressors, and may persist in systems (Toplitsch et al., ), especially in association with biofilms (Whiley & Taylor, ). Outside of those samples labelled as cooling tower water, all water samples from the other system locations tested negative by culture; however, many were positive by the LT and HT qPCR tests. Other studies have shown that Legionella colonizes potable water systems at a relatively high frequency and exposure from building water distribution systems is linked with up to 56% of all cases in the USA (Garrison et al., ). RO feedwater samples were negative by all test methods. Positive and Negative Predictive Values The positive and negative predictive values (PPVs and NPVs) for the LT and HT qPCR methods were determined relative to the culture method (Table ). Using the culture method as the gold standard, the number of true positives, true negatives, false positives, and false negatives is determined for each method (for Legionella species only) and used in the following equations: [12pt]{minimal}










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 Both the LT and HT qPCR methods have very low PPV values (15.38 and 14.63%, respectively), suggesting that a significant proportion of the positive results from these methods are not confirmed by the culture results. This could be due to several reasons, including the low number of overall positive culture samples (six total) and variability in the limits of detection and quantification for the different methods. In addition, qPCR can detect DNA from both viable and nonviable cells and/or viable but nonculturable bacteria. On the other hand, the NPVs for both the LT and HT qPCR methods were extremely high (96.08% and 100%). This indicates that negative results from these methods are highly likely to be true negatives when compared to culture results and would be highly reliable in ruling out the presence of Legionella when the result is negative. These results are consistent with other published results comparing qPCR with culture methods (Ahmed et al., ; Collins et al., , ). Effect of Filtered Sample Volume on LT qPCR Results During the preparation for this study, the initial sample volume for the LT qPCR was set at 50 ml. This volume was selected because it would allow for a technician to filter the volume of a single 50-ml syringe of sample rather than multiple. After two samples tested negative by LT qPCR using 50 ml of sample, while the same sample tested positive by the culture method, the authors decided to increase the volume used for the LT qPCR test to 100 ml, the same volume that was processed for HT qPCR, to determine the impact that this would have on the correlation between the LT qPCR and culture testing. The LT qPCR test was performed using either 50 or 100 ml of sample, while the HT qPCR lab-based testing was performed using 100 ml of sample for all samples, and the culture test was performed on 0.2 ml of sample for all samples. The test results are shown in Table . It was shown in Table that HT qPCR samples tested positive for Legionella more frequently than the LT qPCR method overall, and this is true regardless of volume used for LT qPCR. All six samples that tested positive via culture were also positive via the HT qPCR test. Of the six samples, which tested positive via culture, four of these also tested positive via the LT qPCR test. A breakdown of results by sample volume can be seen in Table . Samples 25 and 26, which used 50 ml of sample for the LT qPCR test and had negative results by the LT test, had 10 and 15 CFU/ml of Legionella based on the culture test. Sample 27, which also used 50 ml of sample for the LT test but had a positive result by LT qPCR, had 20 CFU/ml of Legionella based on the culture test. This may indicate that 50 ml of sample is insufficient to detect less than 20 CFU/ml of Legionella in cooling water using the LT qPCR test, since the two samples, which tested negative by LT qPCR while filtering only 50 ml of sample water, had less than 20 CFU/ml. Samples 68 and 71 used 100 ml of sample for LT qPCR, and this volume of sample was sufficient to detect 5 CFU/ml as shown from the culture testing results. With only six positive culture results throughout the study, these results are limited, but may indicate that any use of this LT qPCR test for cooling water could benefit from using a minimum of 100 ml of sample to aid in detection of Legionella at less than 20 CFU/ml. For the two samples, which tested negative by the LT qPCR test and positive by culture, this discrepancy could be due to being close to the LOD of the qPCR methodology resulting in a nondetect result, and/or due to Legionella not being homogenously distributed in the samples. All samples were shaken and vortexed prior to dividing into three for use with each test method, but this may not fully address all biofilm clumps or attachment to suspended solids, which could result in a low-level culture positive due to a clump of Legionella , and a nondetect result by the LT qPCR test. Increased sample volume helps to address nonhomogenous distribution of bacteria in samples and increase the sensitivity of the assay. Increasing sample volume used in LT qPCR testing would increase sample handling time in the field and could deter some users if high volumes are needed per sample or if their site has a particularly high number of samples. Higher-throughput sampling utilizing a vacuum manifold to process larger volumes of sample would increase Legionella detection sensitivity and precision of the assay but would require more equipment than is standard for the LT qPCR test. Interferences of Closed-Loop Samples Closed-loop samples tested via the LT qPCR test in this study frequently tested negative and with a failed internal control, indicating that these samples may contain materials that interfere with the test. Industrial water systems contain a variety of known treatment additives and often contain leaked process materials as well; further testing would be needed to identify specific interferants in these samples. Previous studies have identified that qPCR may be inhibited by compounds present in environmental water samples such as divalent cations, minerals, or other substances (Díaz-Flores et al., ), and these inhibitory compounds may cause false-negative results (Young et al., ). A total of 19 samples tested negative with a failed internal control when using the LT qPCR method. The 19 samples were made up of 11 closed-loop samples (11 of 26 closed-loop samples, or 42.3%) and 8 cooling tower samples (8 of 34 cooling tower samples, or 23.5%). These samples were retested after performing a 1:10 dilution of the extracted DNA with nuclease-free water in hopes of diluting any interferants beyond a level where they could affect the LT qPCR test. For the purposes of this analysis, any samples tested via LT qPCR more than once, which tested positive at least once, were counted as being positive, even if one of the replicates tested negative. Upon rerunning these samples after dilution, 3 tested negative again with a failed internal control, 14 tested negative with a passing internal control, and 2 tested positive. For 16 of 19 samples (84.2%), the 1:10 dilution was enough to address interferants and provide a result. The 3 samples that tested negative with a failed internal control a second time were from one cooling tower and two closed loops. The 14 samples that tested negative with a passing internal control were from 9 closed-loops and 5 cooling towers. The 2 samples, which tested positive, were from cooling towers. A total of 42.3% of the closed-loop samples tested in this study tested negative with a failed internal control and needed to be retested after a 1:10 dilution of extracted DNA. This shows the importance of including an internal control in any qPCR method that is used, as it provides a warning of potential interference in the results that would not otherwise be detected by methods that do not include controls for this purpose, such as the culture test. Repeating the LT qPCR test after performing a 1:10 dilution of the samples was adequate to address interferants in 9 of the 11 closed-loop samples (81.8%), and 7 of 8 cooling tower samples (87.5%). If this methodology is to be used regularly at industrial sites with contaminants that may interfere with the test, it should be standard practice to run samples at a 1:10 dilution if the internal control fails and to determine the appropriate dilution required to remove the interference if it persists beyond the 1:10 dilution. It is also important to note that dilution will lower the sensitivity of detection, so it would be prudent to increase the volume of samples filtered to increase the sensitivity and limit of detection to application-relevant values. 

In this study both the LT and HT qPCR methods returned positive results with a higher frequency than the culture-based method; this is in line with a prior study that also compared both qPCR and culture-based methods concurrently and indicated that qPCR testing is 50–100% more likely to return a positive result than testing by culture (Young et al., ), and agrees with other studies indicating higher rates of positive results via qPCR than by culture, such as Lee et al. . In this study, 6 samples out of the 77 total samples (7%) tested positive by culture, 26 samples (33.8%) tested positive by the LT qPCR test, and 41 samples (53.3%) tested positive by the HT qPCR test, shown in Fig. . The results from the LT and HT qPCR tests largely agreed, with 23 of 77 samples (29.9%) testing positive by both methods. In cases where the qPCR results did not agree, it was primarily the case that the HT qPCR lab test returned positive results where the LT qPCR test returned negative results. There were 18 samples out of the 77 total (23.4%) that had a positive result for Legionella via the HT qPCR test, but those same samples tested negative with the LT qPCR test. Three samples tested positive by LT qPCR but negative by HT qPCR. These disagreements could be due to differences in the DNA extraction methods used and/or sample holding times. While both the LT and HT methods meet the performance requirements outlined in ISO-12869 (2017) for extraction efficiency and robustness, the LT qPCR test produces lower purity DNA, which could lead to the differences in results between the assays, and there could also be qPCR inhibition due to sample components occurring at quantities that interfere with extraction efficiency. The LT samples were normally tested within 24 hr of sample collection; however, the HT samples were preserved at the time of sample collection and shipped to the lab for analysis (normally within 2 weeks). Overall, these results reflect that the qPCR tests returned positive results at a higher rate than culture-based testing. 

The 77 samples included in this study were from 34 cooling towers, 26 closed cooling loops, 5 open cooling loops, 3 reverse osmosis (RO) feedwaters, 3 showerheads, 2 faucets, 1 condenser, and 1 decorative fountain. A detailed breakdown of the positive and negative results by system location is shown in Table . Of 77 samples, 6 tested positive for Legionella via culture testing, all of which were cooling tower samples. Of the cooling tower samples, 44.1% (15 samples) tested positive by the LT qPCR test and 70.6% (24 samples) tested positive by the HT qPCR test. The high positivity rate in cooling water is consistent with other studies that have shown the presence of Legionella in these locations, where water temperature, nutrients, and dynamic water flow create ideal biofilm conditions and lead to the rapid proliferation of the bacteria (Atlas, ; Fitzhenry et al., ; Young et al., ). Legionella has been found, in some instances, to be tolerant of heat and biocides (Toplitsch et al., ; Whiley & Taylor, ), among other stressors, and may persist in systems (Toplitsch et al., ), especially in association with biofilms (Whiley & Taylor, ). Outside of those samples labelled as cooling tower water, all water samples from the other system locations tested negative by culture; however, many were positive by the LT and HT qPCR tests. Other studies have shown that Legionella colonizes potable water systems at a relatively high frequency and exposure from building water distribution systems is linked with up to 56% of all cases in the USA (Garrison et al., ). RO feedwater samples were negative by all test methods. 

The positive and negative predictive values (PPVs and NPVs) for the LT and HT qPCR methods were determined relative to the culture method (Table ). Using the culture method as the gold standard, the number of true positives, true negatives, false positives, and false negatives is determined for each method (for Legionella species only) and used in the following equations: [12pt]{minimal}










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 Both the LT and HT qPCR methods have very low PPV values (15.38 and 14.63%, respectively), suggesting that a significant proportion of the positive results from these methods are not confirmed by the culture results. This could be due to several reasons, including the low number of overall positive culture samples (six total) and variability in the limits of detection and quantification for the different methods. In addition, qPCR can detect DNA from both viable and nonviable cells and/or viable but nonculturable bacteria. On the other hand, the NPVs for both the LT and HT qPCR methods were extremely high (96.08% and 100%). This indicates that negative results from these methods are highly likely to be true negatives when compared to culture results and would be highly reliable in ruling out the presence of Legionella when the result is negative. These results are consistent with other published results comparing qPCR with culture methods (Ahmed et al., ; Collins et al., , ). 

During the preparation for this study, the initial sample volume for the LT qPCR was set at 50 ml. This volume was selected because it would allow for a technician to filter the volume of a single 50-ml syringe of sample rather than multiple. After two samples tested negative by LT qPCR using 50 ml of sample, while the same sample tested positive by the culture method, the authors decided to increase the volume used for the LT qPCR test to 100 ml, the same volume that was processed for HT qPCR, to determine the impact that this would have on the correlation between the LT qPCR and culture testing. The LT qPCR test was performed using either 50 or 100 ml of sample, while the HT qPCR lab-based testing was performed using 100 ml of sample for all samples, and the culture test was performed on 0.2 ml of sample for all samples. The test results are shown in Table . It was shown in Table that HT qPCR samples tested positive for Legionella more frequently than the LT qPCR method overall, and this is true regardless of volume used for LT qPCR. All six samples that tested positive via culture were also positive via the HT qPCR test. Of the six samples, which tested positive via culture, four of these also tested positive via the LT qPCR test. A breakdown of results by sample volume can be seen in Table . Samples 25 and 26, which used 50 ml of sample for the LT qPCR test and had negative results by the LT test, had 10 and 15 CFU/ml of Legionella based on the culture test. Sample 27, which also used 50 ml of sample for the LT test but had a positive result by LT qPCR, had 20 CFU/ml of Legionella based on the culture test. This may indicate that 50 ml of sample is insufficient to detect less than 20 CFU/ml of Legionella in cooling water using the LT qPCR test, since the two samples, which tested negative by LT qPCR while filtering only 50 ml of sample water, had less than 20 CFU/ml. Samples 68 and 71 used 100 ml of sample for LT qPCR, and this volume of sample was sufficient to detect 5 CFU/ml as shown from the culture testing results. With only six positive culture results throughout the study, these results are limited, but may indicate that any use of this LT qPCR test for cooling water could benefit from using a minimum of 100 ml of sample to aid in detection of Legionella at less than 20 CFU/ml. For the two samples, which tested negative by the LT qPCR test and positive by culture, this discrepancy could be due to being close to the LOD of the qPCR methodology resulting in a nondetect result, and/or due to Legionella not being homogenously distributed in the samples. All samples were shaken and vortexed prior to dividing into three for use with each test method, but this may not fully address all biofilm clumps or attachment to suspended solids, which could result in a low-level culture positive due to a clump of Legionella , and a nondetect result by the LT qPCR test. Increased sample volume helps to address nonhomogenous distribution of bacteria in samples and increase the sensitivity of the assay. Increasing sample volume used in LT qPCR testing would increase sample handling time in the field and could deter some users if high volumes are needed per sample or if their site has a particularly high number of samples. Higher-throughput sampling utilizing a vacuum manifold to process larger volumes of sample would increase Legionella detection sensitivity and precision of the assay but would require more equipment than is standard for the LT qPCR test. 

Closed-loop samples tested via the LT qPCR test in this study frequently tested negative and with a failed internal control, indicating that these samples may contain materials that interfere with the test. Industrial water systems contain a variety of known treatment additives and often contain leaked process materials as well; further testing would be needed to identify specific interferants in these samples. Previous studies have identified that qPCR may be inhibited by compounds present in environmental water samples such as divalent cations, minerals, or other substances (Díaz-Flores et al., ), and these inhibitory compounds may cause false-negative results (Young et al., ). A total of 19 samples tested negative with a failed internal control when using the LT qPCR method. The 19 samples were made up of 11 closed-loop samples (11 of 26 closed-loop samples, or 42.3%) and 8 cooling tower samples (8 of 34 cooling tower samples, or 23.5%). These samples were retested after performing a 1:10 dilution of the extracted DNA with nuclease-free water in hopes of diluting any interferants beyond a level where they could affect the LT qPCR test. For the purposes of this analysis, any samples tested via LT qPCR more than once, which tested positive at least once, were counted as being positive, even if one of the replicates tested negative. Upon rerunning these samples after dilution, 3 tested negative again with a failed internal control, 14 tested negative with a passing internal control, and 2 tested positive. For 16 of 19 samples (84.2%), the 1:10 dilution was enough to address interferants and provide a result. The 3 samples that tested negative with a failed internal control a second time were from one cooling tower and two closed loops. The 14 samples that tested negative with a passing internal control were from 9 closed-loops and 5 cooling towers. The 2 samples, which tested positive, were from cooling towers. A total of 42.3% of the closed-loop samples tested in this study tested negative with a failed internal control and needed to be retested after a 1:10 dilution of extracted DNA. This shows the importance of including an internal control in any qPCR method that is used, as it provides a warning of potential interference in the results that would not otherwise be detected by methods that do not include controls for this purpose, such as the culture test. Repeating the LT qPCR test after performing a 1:10 dilution of the samples was adequate to address interferants in 9 of the 11 closed-loop samples (81.8%), and 7 of 8 cooling tower samples (87.5%). If this methodology is to be used regularly at industrial sites with contaminants that may interfere with the test, it should be standard practice to run samples at a 1:10 dilution if the internal control fails and to determine the appropriate dilution required to remove the interference if it persists beyond the 1:10 dilution. It is also important to note that dilution will lower the sensitivity of detection, so it would be prudent to increase the volume of samples filtered to increase the sensitivity and limit of detection to application-relevant values. 

Legionella is a genus of bacteria ubiquitous in man-made and natural water systems, which can proliferate in man-made systems and cause illness in at-risk individuals. Due to the health risks they may present, it is important to rapidly and effectively monitor Legionella . In this study, 77 samples from a variety of industrial water systems from numerous factories and other sites were tested by three test methods to evaluate performance of an LT qPCR Legionella test that is capable of being used in the field. The test methods used were an HT qPCR), an LT qPCR (both qPCR tests target all Legionella species), and standard culture-based testing. Both LT and HT qPCR tests were included in this study to identify any differences in performance between the methods, and support that the LT qPCR test that can be utilized in the field provides comparable information to the HT test. The results indicated that both the LT and HT qPCR tests detected Legionella in samples more frequently than culture-based testing, across all sample types. The qPCR tests were largely in agreement, with 23 of 77 samples (29.9%) testing positive by both methods. However, the HT qPCR test returned positive results more frequently than the LT qPCR test, with 18 of 77 samples (23.4%) testing positive via the HT qPCR test but negative with the LT qPCR test; this could be due to the differences in DNA extraction between the methods. The findings of this study are supported by previous research demonstrating the higher sensitivity of qPCR methods compared to culture-based tests. Collins et al.  and Young et al.  have shown that qPCR testing often returns more positive results due to its ability to detect both viable and nonculturable organisms. This study's results align with these findings, underscoring the utility of qPCR as a rapid and sensitive detection method. In this study, both LT and HT qPCR reported more positive results than culture and had high NPV. The higher detection rate of Legionella by qPCR in this study is consistent with the work of Whiley and Taylor , who noted that qPCR could detect DNA from nonviable cells, which may inflate population measurements. However, the high NPV of the qPCR methods used here indicates their reliability in ruling out the presence of Legionella when results are negative, as corroborated by Díaz-Flores et al. . The high NPV of both the LT and HT methods highlights the value of using qPCR as a negative screening tool. This could be used in many different applications and would be particularly useful when there are larger numbers of samples to be tested, for example, during system audits or case investigations to uncover the source of a Legionella outbreak. In addition, monitoring cooling water or potable water systems for treatment efficacy would present ideal scenarios to rapidly screen sample locations for priority follow-up with culture-based testing. We observed that sample volume affected LT qPCR test results, with higher sample volumes testing positive more often due to increased sensitivity. The results indicated that 100 ml of sample may be sufficient to detect low levels of Legionella using the LT qPCR test in cooling water samples. Closed-loop samples frequently contained components that interfered with the LT qPCR test. For 81.8% of samples, this could be addressed by performing a 1:10 dilution of the extracted DNA and running the LT qPCR test again. A follow-up study exploring interferants could provide additional insight into the limitations of qPCR in industrial water monitoring. Rapid quantification of Legionella populations in industrial systems can be crucial for evaluation of the efficacy of water treatment programs. Tests such as the LT qPCR assay that can be used in the field could be useful for monitoring and establishing baseline population levels in a system and identifying spikes in growth, which may indicate system changes necessitating additional treatment or operational adjustments to manage increased bacterial densities. Faster adjustment of treatment programs to meet system needs may save resources and time, alongside reducing opportunities for exposure to Legionella . Long-term tracking of the results produced by qPCR coupled with normal water treatment testing could also be used to help troubleshoot a system where changes have occurred and gone unidentified (Young et al., ). Implementing field-based qPCR for environmental and process monitoring for Legionella has several advantages, including rapid notifications of elevated levels of Legionella in environmental samples that may present public health risks (potable and nonpotable water sources). In addition, rapid feedback times allow for mitigations to be enacted and effectiveness verified within 1–2 days, rather than weeks that are required for culture-based tests, allowing for more optimized and efficient control programs, which can improve water quality and reduce risk to public health. This study highlights the practical application of field-deployable qPCR tests for routine monitoring and outbreak investigations. Yaradou et al.  and Krøjgaard et al.  have emphasized the importance of rapid and accurate Legionella detection for timely intervention, a goal well supported by the findings of this study. In summary, the results presented in this study contribute to the growing body of evidence supporting the use of qPCR for Legionella monitoring, providing a basis for considering regulatory adjustments to include qPCR results alongside traditional culture-based testing. The LT qPCR test evaluated showed similar negative predictive power to the HT qPCR test across the variety of industrial samples tested in this study, while using more transportable equipment and a faster protocol, supporting that the LT qPCR testing methodology may be an effective option for negative screening of industrial water samples. 

