Detection and molecular characterization of

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Environmental Science and Pollution Research https://doi.org/10.1007/s11356-018-1620-3

RESEARCH ARTICLE

Detection and molecular characterization of Cryptosporidium species and Giardia assemblages in two watersheds in the metropolitan region of São Paulo, Brazil Ronalda Silva de Araújo 1 & Bruna Aguiar 1 & Milena Dropa 1 & Maria Tereza Pepe Razzolini 1 & Maria Inês Zanoli Sato 2 & Marcelo de Souza Lauretto 3 & Ana Tereza Galvani 2 & José Antônio Padula 2 & Glavur Rogério Matté 1 & Maria Helena Matté 1 Received: 13 December 2016 / Accepted: 27 February 2018 # Springer-Verlag GmbH Germany, part of Springer Nature 2018

Abstract Cryptosporidium and Giardia are associated with cases of water and foodborne outbreaks in the world. This study included 50 samples of surface raw water collected from two watersheds in the state of São Paulo, Brazil. The isolation of (oo)cysts was performed in accordance with the U.S. Environmental Protection Agency’s methods 1623 and genotypic characterization and quantification were carried out by Nested PCR and qPCR assays based on 18S rRNA and gdh genes, respectively. U.S. EPA 1623 method showed the presence of (oo)cysts in 40% (x = 0.10 oocysts/L) and 100% (x = 7.6 cysts/L) of samples from São Lourenço River, respectively, and 24% (x = 0.8 oocysts/L) and 60% (x = 1.64 cysts/L) of Guarapiranga Reservoir, respectively. The qPCR assay detected C. hominis/parvum in 52% (0.06 to 1.85 oocysts/L) of São Lourenço River and 64% (0.09 to 1.4 oocysts/L) of Guarapiranga Reservoir samples. Presence/absence test for Giardia intestinalis was positive in 92% of São Lourenço River and 8% of Guarapiranga Reservoir samples. The assemblage A was detected in 16% (0.58 to 2.67 cysts/L) in São Lourenço River and no positive samples were obtained for assemblage B in both water bodies. The characterization of anthroponotic species C. parvum/hominis, G. intestinalis, and assemblage A was valuable in the investigation of possible sources of contamination in the watersheds studied confirming the need of expanding environmental monitoring measures for protection of these water sources in our country. Keywords Cryptosporidium . Giardia . Watersheds . PCR . qPCR . Environmental surveillance . Public health

Introduction Cryptosporidium and Giardia are currently the most common causes of protozoal diarrhea. Despite the extensive chain Responsible editor: Philippe Garrigues Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11356-018-1620-3) contains supplementary material, which is available to authorized users. * Maria Helena Matté [email protected] 1

Faculdade de Saúde Pública, Universidade de São Paulo, Av. Doutor Arnaldo 715, São Paulo, SP 01246-904, Brazil

2

Companhia Ambiental do Estado de São Paulo – CETESB, São Paulo, Brazil

3

Escola de Artes, Ciências e Humanidades – EACH, Universidade de São Paulo, São Paulo, Brazil

involved in the transmission of these organisms, water contaminated with treated or untreated waste discharges has often been reported as the main route of spread associated with gastroenteritis outbreaks. Cysts and oocysts are transmitted by the fecal-oral route, directly or indirectly, and may cause severe disease in immunocompetent individuals and weaken severely immunocompromised patients, featuring a major public health problem (Xiao and Fayer 2008; Baldursson and Karanis 2011). Sewage may contain a high concentration of pathogenic microorganisms, including parasites such as Cryptosporidium and Giardia, which are disseminated through the water and impact especially reservoirs intended for public supply. These parasites are widely distributed in the aquatic environment, have low infectious doses, and show intrinsic resistance to conventional water treatments, becoming a target of interest for water-producing companies (Franco et al. 2012) and posing a threat to human health considering the multiple uses of water

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(for drinking, recreation, and reuse) (Castro-Hermida et al. 2008; WHO 2011). Karanis et al. (2007) reported that 93% of outbreaks of waterborne disease in the USA and Europe were caused by protozoans. From 325 outbreaks associated to water contaminated by parasites reported up to 2002, C. parvum and G. duodenalis had the highest detection rate among the cases, 50.8 and 40.6%, respectively. Baldursson and Karanis (2011) studied the global distribution of waterborne outbreaks caused by protozoans in the 2004–2010 period and observed that Cryptosporidium spp. were associated with 60.3% of outbreaks and Giardia intestinalis with 35.2%. Toxoplasma and Cyclospora accounted for 2.0 and 1.5% of outbreaks, respectively. According to Efstratiou et al. (2017), from 381 outbreaks attributed to water-related protozoa between 2011 and 2016, Cryptosporidium was the most recurrent and contributed to 63% (239) of cases, followed by Giardia with 37% (142) of diagnosed outbreaks. In contrast, the lack of data on the occurrence of this agent in aquatic sources and the scarcity of documented outbreaks in our country represents one of the main problems for infection control. Some studies conducted in Brazil, in different environmental sources, exposed the difficulty in assessing the occurrence of these pathogens due to factors such as the physicochemical characteristics of the samples analyzed, difficulty in recovering cysts and oocysts from water, and high costs of the reagents used for detection (Razzolini et al. 2010; Fernandes et al. 2011; Araújo et al. 2011). In Brazil, the current potable water standard (Portaria MS 2914/2011) is attentive to the importance of monitoring protozoa in water supplies and has made mandatory the research of Cryptosporidium and Giardia in order to guarantee quality and to protect health (BRAZIL 2011). However, despite advances in water quality surveillance systems for human consumption in Brazil, other initiatives are identified as fundamental for improvement in Latin American countries. Rosado-García et al. (2017) discussed in a review on waterborne outbreaks the vulnerability of Latin American countries, the effects of climate change, and their relation to the transmission of waterborne diseases in the region. The study also pointed to the need for the integration of surveillance systems of Central and South America countries for the rapid and effective detection of protozoa in water, in order to minimize the limitations related to access to health systems, sanitation, and water quality in accordance with the economic reality of each country. The monitoring of these pathogens is important because of the transmission chain among animals and humans, and the presence of Cryptosporidium and Giardia in water sources represents a potential risk to public health, in particular for those who are vulnerable to a variety of opportunistic diseases, such as immunocompromised individuals (Reina et al. 2016). In fact, in urban regions with high population density as the

city of São Paulo, the risk of outbreaks is high because small amounts of infectious (oo)cysts are able to initiate the disease in exposed individuals (Plutzer et al. 2010). Consequently, information on the distribution and identification of clinically important Cryptosporidium and Giardia species in the environment has become relevant to water quality, especially in developing countries still marked by great inequality and lack of access to basic sanitation (Sato et al. 2013). Despite the efforts of research centers in our country in using the methodology developed by the U.S. EPA, Method 1623, for the detection of parasites in water samples, the methodology based on filtration cartridge, immunomagnetic separation (IMS), and detection by immunofluorescence microscopy (IFA) is genus-specific; therefore, it does not identify human pathogenic species, what would be of great value for epidemiological studies (Franco et al. 2012). For this reason, genotypic techniques have become necessary in supporting epidemiological investigations and are particularly important during the analysis of suspect sources, making it possible to discriminate between protozoan genus and species and assist in cases of outbreaks or sporadic cases (Robertson et al. 2010). Quantitative real-time PCR (qPCR) is a promising technique for the detection and quantification of many organisms, including Cryptosporidium and Giardia, in different types of samples. The qPCR is a system adapted for detecting target sequences that allow the determination of the genetic variability among isolates and measure the relative amount of accumulated DNA at the end of the reaction cycles (Staggs et al. 2013). The advantages over Nested PCR are the reduction of time and the risk of contamination, and increased sensitivity (Higgins et al. 2001; Fontaine and Guillot 2002; Guy et al. 2003; Verweij et al. 2003; Alonso et al. 2011, 2014; Hadfield and Chalmers 2012; Staggs et al. 2013). In order to evaluate the occurrence of these protozoans in environmental matrices in our country, surface water samples from two municipalities in the state of São Paulo were assessed for quantification and characterization of Cryptosporidium and Giardia species, using the U.S. EPA Method 1623 (2005), Nested PCR, and real-time PCR. This is the first study in Brazil in which real-time PCR methods were used for the detection and quantification of oocysts and cysts of both protozoans in surface water.

Methodology Area characterization In this study, two water catchments sources from two Drinking Water Treatment Plants (DWTPs) belonging to different watersheds in the metropolitan region of São Paulo, Brazil, were selected. The São Lourenço da Serra DWTP is supplied by São Lourenço River (23° 51′7.82″ S–46° 56′

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38.97″ W), located at the Water Management Unit (UGRHI) 11–Ribeira do Iguape Litoral Sul, considered an area of environmental conservation. The Alto da Boa Vista DWTP uptakes water from the Guarapiranga Reservoir (23o 40′ 17.60″ S–46o 43′ 37.54″ W), situated at UGRHI 06-Alto Tiete, an industrialized region with the state’s largest demographic density (Fig. S1 Supporting information).

Sampling protocol A total of 25 water samples were collected at each site every 2 weeks, for 1 year (January–December 2013), totalizing 50 raw surface water samples. Water collection was carried out according to the methodologies described by the National Guide of Sampling Collection and Preservation (CETESB/ ANA 2011), and samples were kept at 4 °C for transportation and processed within 24 h. Temperature and pH were measured on the collection field in accordance with Methods 4500H and 2550B, respectively, using Mettler Toledo Model Seven pot-Go, and turbidity was measured using Method 2130 from the Standard Methods for the Examination of Water and Wastewater (APHA 2012).

Escherichia coli Determination Escherichia coli was determined by membrane filter technique in accordance with Standard Methods for the Examination of Water and Wastewater, employing modified mTEC agar (APHA 2012).

Giardia and Cryptosporidium detection Immunofluorescence assay microscopy The methodology adopted was the Method 1623 from U.S. EPA (2005). Briefly, volumes of 10 L of the samples were concentrated through the foam filter Filta-Max® (Idexx Laboratories), cysts and oocysts were eluted, submitted to immunomagnetic separation (IMS) with the use of the commercial kit Dynabeads™ GC-Combo (Applied Biosystems), and stained with Giardia and Cryptosporidium fluorescently labeled monoclonal antibodies Aqua-Glo™ G/C (Waterborne, Inc) and 4′,6-diamidino-2-phenylindole (DAPI). Stained material was examined using fluorescence and differential interference contrast (DIC) microscopy. Precision, initial recovery (PRI), and matrix recovery (MR) were determined with certified reference material (EasySeed®-BTF Bio, Australia) as recommended by U.S. EPA Method 1623. For molecular analysis, 20 L of raw surface water of each site were filtered through the foam filter Filta-Max® (Idexx Laboratories) in accordance with Method 1623 (U.S. EPA 2005) and a 50-mL eluate was obtained. A 1.5-mL aliquot

was taken for genotyping assays to identify Cryptosporidium species (nested PCR). The remaining 48.5 mL was centrifuged to pellet the oocysts and cysts, submitted to immunomagnetic separation (IMS), and kept refrigerated at 4 °C for DNA extraction and qPCR analyses. DNA extraction Positive controls, 1.5-mL eluate aliquot, and the IMS concentrated material were submitted to the same DNA extraction method, using the QIAamp® DNA Stool Mini Kit (Qiagen, Venlo, the Netherlands) based on the protocol described by Yu et al. (2009). Briefly, before addition of ASL buffer, samples were submitted to five cycles of heating at 95 °C for 3 min in a water bath and freezing for 60 s. DNA was purified on silica-gel columns according to the instructions of the manufacturer and eluted in TE buffer before storage at 4 °C. In order to determine the prevalent Cryptosporidium species in each sample, conventional Nested PCR was carried out for sequencing purposes, since specific primers and probes used for real-time PCR could not differentiate C. parvum, C. hominis, and C. meleagridis.

Molecular assays Positive controls Positive controls for Cryptosporidium derived from previously purified fragments of the 18S rRNA gene were obtained from human stool samples corresponding to GenBank sequences FJ462458 (C. hominis), FJ462456 (C. parvum), and FJ462459 (C. meleagridis) from Araújo et al. (2011). Positive controls for Giardia intestinalis were obtained from previously purified fragments of gdh gene corresponding to GenBank sequences GQ503134 (assemblage A) and GQ503115 (assemblage B) (Fernandes et al. 2011). Negative controls used in this study were as follows: Cryptosporidium muris derived from previously purified fragments of the 18S rRNA gene obtained from environmental sample (KP098565) from Ulloa-Stanojlović et al. (2016), Escherichia coli obtained from ATCC® (#25922), Ascaris suum eggs, and Toxoplasma gondii oocysts obtained from Laboratory of Protozoology, Department of Animal Biology, Institute of Biology, Campinas State University. Cryptosporidium genotyping by Nested PCR 18S rRNA gene was amplified according to the protocol described by Araújo et al. (2011), using external primers SCL1–5′-CTG GAT GTT CCT GCC AGT AG-3′-forward and CPB-diagr-5′-GCT GAA AAT GGT GGA GTA AGG-3′-reverse, described by Coupe et al. (2005), and internal primers SSU826 5′-GGA AGG GTT GTA TTT ATT TAA AGA AG forward-3′ and SSU826 5′-AAG GAG AAT GGA ACA ACC TCC Areverse 3′, described by Xiao et al. (2001). Positive controls were amplified, purified, and directly sequenced for

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comparison with available sequences from GenBank database using the BLAST tool. DNA obtained from the 1.5 mL eluate aliquot was subjected to the same amplification reactions described above, and the positive amplified fragments from secondary PCR product were purified and submitted to direct sequencing in both directions. Amplicons showing mixed sequences (superimposed peaks on electropherograms) were cloned into TOPO TA Cloning® Kit (Invitrogen™) and transformed into One Shot® Eletrocomp™ E. coli TOP10 (Invitrogen™) following the manufacturer’s instructions. Plasmids extracted from positive clones were directly sequenced. Sequences were aligned using the Bioedit Sequence Alignment Editor (Hall 1999). Phylogenetic and molecular evolutionary analyses of sequences obtained in this study were performed against sequences available in GenBank database for Cryptosporidium species using MEGA version 5 software and the neighbor-joining method (http://www.megasoftware.net/m_test_reliab.html) (Kimura 1980; Felsenstein 1985; Tamura et al. 2011). Design and development of real-time PCR assays For the detection of C. hominis and C. parvum, primers and linear hydrolysis probes were constructed in the variable region of the 18S rRNA gene. Detection of G. intestinalis all assemblages was conducted using primers and probe modified from Yu et al. (2009), in a presence-absence method. The primers used for detection of the gdh gene in G. intestinalis assemblages A and B were designed using target sequences available in the GenBank database. Oligonucleotides and probes were designed using the Primer Express® Software Version 3.0 (Applied Biosystems 2014) to assess the compatibility with TaqMan® system MGB (Minor Groove Binder) (Table 1). The standard curves were constructed using plasmids containing the target region of each organism, previously submitted to a 3.5 h enzymatic digestion for linearization, using 1 U of restriction enzyme XbaI (Cryptosporidium) or PstI (G. intestinalis), and further purification to remove digestion residues. Concentrations of double-stranded DNA were measured using the quantifier Qubit®2.0 Fluorometer (Invitrogen ™) and the obtained values were converted into copy number/μL, and the results multiplied by the total volume of DNA used in each qPCR reaction. Serial ten-fold dilutions of quantified DNA samples were performed and 105 to 101 copies/μL were selected as standard curve points for quantification of oocysts and cysts, considering the number of copies available for the 18S rRNA gene (5 copies per genome) and SSU/gdh gene (one copy), respectively (Yee and Dennis 1992; Adam 2001; Xu et al. 2004). Amplification data were collected and analyzed using the equipment Step One Plus RealTime PCR System (Applied Biosystems ™).

Enumeration of C. hominis/C. parvum by qPCR C. hominis and C. parvum were amplified in 20 μL reactions, containing >4.9 μL of ultrapure water, 10 μl (1 ×) of TaqMan®Environmental 2.0 Master Mix (Applied Biosystems™), 0.16 μM of each primer (Exxtend, Brazil), 0.15 μM of TaqManMGB probe, 2 μL of 10X IPC Mix, 0.4 μL of 50X IPC DNA (Applied Biosystems™) ,and 2 μL of template DNA. Enumeration of Giardia intestinalis by qPCR Amplification of G. intestinalis all assemblages was also conducted in 25 μL reactions, as described above for C. hominis and C. parvum. Assemblages A and B of G. intestinalis were amplified in 25 μL reactions containing 6.8 μL of ultrapure water, 12 μL (1 ×) of TaqMan® Universal PCR Master Mix (Applied Biosystems™), 0.2 μM of each primer (Exxtend, Brazil), 0.15 μM of TaqMan FAM-MGB probe or 0.25 μM of TaqMan NED-MGB probe, 2 μL of 10 × IPC Mix, 0.4 uL of 50 × IPC DNA (Applied Biosystems™) and 5 μl of the template DNA. The number of DNA copies of both target organisms in the samples was automatically detected by the qPCR equipment by comparison with the standard curve of the specific positive control. The number of (oo)cysts were calculated from the result obtained for each sample according to the number of DNA copies obtained for each organism. Primers, probes, and reaction cycles for all qPCR assays are described in Table 1. qPCR quality control An exogenous control IPC (internal positive control, Applied Biosystems, USA) was used in each experiment and the sample data set and the IPC were compared in each analysis to prevent false-negative results due to the presence inhibitor in samples. The detection ability of primers at different DNA concentrations (sensitivity) was assessed by submitting to qPCR reactions the selected serial dilutions of each target fragment containing the sequences of specific sizes used in the standard curve. To determine the specificity of qPCR for detection of C. hominis and C. parvum, as well as G. intestinalis assemblages A and B, DNA from positive controls and other microorganisms were used, including: C. hominis, C. parvum, C. muris, C. meleagridis, and G. intestinalis assemblages A and B, Escherichia coli, Ascaris suum, and Toxoplasma gondii. Samples and control DNAs were amplified in triplicates to monitor the accuracy of PCR reactions. The reproducibility of standard curves was assessed by obtaining the average Ct, the standard deviations of the three predetermined points, and exponential analysis of the coefficient of variation on alternate days. The whole validation procedure was performed in accordance with the Minimum Information Guide for quantitative PCR Publication-MIQE (Bustin et al. 2009).

ACGGCTCAGGACAACGGTT TTGCCAGCGGTGTCCG FAM-GGCGGTCCCTGCTA-MGB CGACACTGACGTTCCTGCC ACA GCG CCA TAG CCC GT FAM- TCGGGTACCTGTACGGAC-MGB CCGACGTTCCTGCTGGC AGCTCCATACCCTGTGGCCT NED- ACCGCCGACGCCAATAT-MGB CCTAATACAGGGAGGTAGTGAC CGCTATTGGAGCTGGAATTACC FAM-ACAGGACTTTTTGGTTTTGTA-MGB

SSU Fa SSU Rb Probec GiaA3RT F GiaA3RT R Probe A GiaB3RT F GiaBB R Probe B 682SSU-F 683SSU-R Probe H/P

SSU rRNA

82–99 121–142 110–123 471–489 622–638 518–535 476–492 616–636 494–510 440–461 587–608 475–497

Location*

60 °C 30 s

50 °C 2 min

A

95 °C 10 min

B

qPCR cycling parameters

Adapted from Yu et al. 2009 to MGB. A pre-PCR, B initial denaturation and activation of AmpliTaq GoldR, C denaturation, E anneling and extension

Yu et al. 2009

Modification of Yu et al. 2009

C. hominis C. parvum

G. intestinalis Assemblage B 142

G. intestinalis Assemblage A 160

167

Giardia intestinalis all Assemblages

Amplicon size (bp)/target

40

Cycles

*Corresponding to complete sequence of genes gdh (1350 bp) or 16S rRNA (1453 bp) of Giardia intestinalis or 18S rRNA of Cryptosporidium hominis/parvum (1750 bp)

c

b

a

18S rRNA

gdh

Sequence 5′-3′

Primer/probe

Gene

95 °C 15 s

C

60 °C 1 min

D

Table 1 Gene target and position, primers and probes sequences, qPCR conditions, and fragment sizes used for the detection and enumeration of Cryptosporidium parvum/hominis and Giardia intestinalis assemblages A and B (oo)cysts in superficial raw water from two watersheds in the metropolitan region of São Paulo, Brazil, January–December 2013

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Statistical analysis

0.22 oocysts/L) and 60% (Mean 1.64; SD 5.52 cysts/L), respectively (Tables 2 and 3).

In this study, descriptive statistics was performed (distribution of frequencies and percentages for qualitative variables). For the quantitative analyses, calculations were employed: mean ± standard deviation (SD) and coefficient of variation. The linear correlation coefficients were computed in order to assess possible associations between pathogens concentrations and physicochemical parameters. Besides correlation estimates, 95% confidence intervals were also computed, using the bootstrap biased-corrected and accelerated (BCa) method (Efron and Tibshirani 1993), a nonparametric approach which does not depend on the assumption of data normality. Computations were performed in R language based on the R Core Team (2013), using the package Bootstrap according to Original et al. (2015).

Through the analysis of Nested PCR, it was possible to identify the Cryptosporidium spp. in 12% (3/25) of the São Lourenço River and in 16% (4/25) of Guarapiranga Reservoir samples. Sequencing of the amplified products showed positive homologous sequences compatible with C. parvum species in all raw superficial water samples analyzed by this method. The maximum likelihood method based on the Kimura 2-parameter model (Kimura 1980) was used in the phylogenetic analyses of the 18S rRNA gene. All sequences were deposited in the NCBI GenBank database under accession numbers KT728800–KT728806, as shown Fig. 1.

Results

Enumeration of Cryptosporidium hominis/parvum and Giardia intestinalis assemblages A and B by qPCR

Physicochemical and microbiological analyses Data from the physicochemical and microbiological analyses of water samples were computed as mean ± standard deviation (SD), with maximum and minimum values and percentile 25 and 75%. In the São Lourenço River, the pH values ranged from 6.23 to 7.25, and the air and water temperatures observed were between 15.4 and 30.5 °C, and 14.10 and 25.5 °C, respectively. Values were homogeneous in different seasons. The turbidity results were below the reference value for surface water destined to treatment for human consumption (100 NTU) according to national legislation (CONAMA 2005), except on July 1st, when the measurement was 237 NTU. This value is justified by strong rain occurrence in the 24 h prior to sample collection (data not shown). The concentrations of Escherichia coli were between 1.3 × 103 and 8.6 × 103 CFU/100 mL. In the Guarapiranga Reservoir, pH values ranged from 6.84 to 9.30. The air temperature was between 15.2 and 33.4 °C and the water between 17.1 and 28 °C. The turbidity values were all below 10 NTU, and on the campaign of August, results were less than 1.0 NTU. The concentrations of E. coli were lower than 1.84 × 102 CFU/100 mL (Tables 2 and 3).

Detection of Cryptosporidium oocysts and Giardia cysts by IFT U.S. EPA 1623 method showed that Cryptosporidium oocysts and Giardia cysts were observed in 40% (Mean 0.10; SD 0.16 oocysts/L) and 100% (Mean 7.6; SD 7.2 cysts/L) of samples from São Lourenço River, respectively. For samples from the Guarapiranga Reservoir, the results were 24% (Mean 0.8; SD

Genotyping of Cryptosporidium species

C. hominis/C. parvum were detected in 52% (13/25) of samples from São Lourenço River and quantification ranged from 1.13 × 100 to 3.66 × 101 copies/L (0.06–1.85 oocysts/L). These protozoa were present in 64% (16/25) of samples from the Guarapiranga Reservoir and quantification ranged from 1.86 × 100 to 2.82 × 101 copies/L (0.09–1.4 oocysts/L). The linear regression curve showed the following results for the detection of Cryptosporidium in the reservoirs: efficiency = 100.1%; R2 0.998; slope − 3.312, given the validity criteria. Standard curve validation for Cryptosporidium showed ranges of correlation coefficient (R2) from 0.986 to 0.992, efficiency from 97 to 103% and Slope from − 3.375 to − 3.236. The methodology used was able to quantify the minimum of 1.0 × 101 copies/2 μL (1–2 oocyst/L). The coefficient of variation showed good performance in reproducibility (< 1.17%) for the standard curves used in this study. Presence of G. intestinalis all assemblages was observed in 92% (24/25) of samples from São Lourenço River, with CT values ranging from 30 to 38. Two samples from the Guarapiranga Reservoir showed the presence of G.intestinalis in SSU qPCR presence/absence test, resulting in 8% (2/25) of positivity (Tables 2 and 3). G. intestinalis assemblage A was detected in 16% (4/25) of water samples from São Lourenço River with quantification values ranging from 1.16 to 5.39 copies/L (0.58 to 2.67 cysts/ L), and this assemblage was not detected in the Guarapiranga Reservoir. No positive samples were detected for assemblage B in both water sources. Results of the standard curve validation for the analysis of gdh gene of G. intestinalis assemblages A and B were as follows: correlation coefficient (R2) from 0.998 to 1, efficiency from 90.4 to 91.6%, and slope from − 3.54 to − 3.57; and R2 = 1, efficiency from 94.0 to 94.8%, and slope from − 3.46

1A

3A 5A 7A 9A 11A 13A 15A 17A 19A 21A 23A 25A

27A

29A 31A 33A 35A 37A 39A 41A 43A 45A 47A 49A

01/07/13

01/21/13 02/04/13 02/18/13 03/04/13 03/18/13 04/08/13 04/22/13 05/06/13 05/20/13 06/10/13 06/24/13 07/01/13

07/15/13

07/29/13 08/12/13 08/26/13 09/09/13 09/25/13 10/07/13 10/21/13 11/11/13 11/25/13 12/02/13 12/16/13

9.29 1.00 1.00 3.22 19.20 8.68 10.80 5.70 19.70 9.95 6.60

6.03

19.20 15.80 24.40 23.40 80.50 25.30 11.20 30.40 8.07 8.00 25.60 237.00

13.50

Turbidity

6.93 7.01 6.83 7.12 7.22 6.94 6.97 6.68 6.57 6.23 6.86

7.14

7.00 7.09 6.94 6.97 6.96 6.71 7.18 6.88 7.12 7.00 7.11 7.25

7.03

pH

P/A presence/absence, ND not detected

Sample

Date

17.4 23.5 23.7 26.8 16.5 16.5 27.8 27.1 23.9 30.5 26.0

25.6

22.7 23.7 25.1 29.2 18.8 23.5 20.8 18.2 26.9 23.5 19.2 15.4

29.9

T(°C) air

14.1 15.6 18.1 18.5 15.2 16.5 21.4 23.7 20.3 22.4 21.7

17.3

20.8 22.8 23.8 25.5 20.1 21.4 19.1 19.0 19.8 22.1 17.0 17.2

23.8

T(°C) water

11.7 9.8 3.3 3.0 0.3 1.7 9.9 11.3 14.1 8.1 14.5 6.1 5.8 5.4 3.0 25.6 4.3 1.2 4.5 8.7 1.2 2.2 1.2 2.8 29.3

5.6 × 103 5.2 × 103 4.6 × 103 3.0 × 103 5.6 × 103 4.3 × 103 7.2 × 103 6.5 × 103 3.1 × 103 2.9 × 103 1.6 × 103 2.1 × 103

8.5 × 10 3.1 × 103 1.3 × 103 1.4 × 103 6.3 × 103 2.8 × 103 8.5 × 103 8.6 × 103 6.3 × 103 2.2 × 103 3.9 × 103 5.2 × 103

3

P (32) A P (31) P (33) P (33) P (35) P (33) P (33) P (32) P (34) P (36) P (34)

P (32) P (30) P (35) P (38) A P (36) P (33) P (32) P (37) P (32) P (34) P (35) P (30) ND ND 1.21 ND ND ND ND ND ND ND ND ND

ND ND 1.16 ND ND ND ND ND ND ND 2.67 ND 0.58

Assemblage A

ND ND ND ND ND ND ND ND ND ND ND ND

ND ND ND ND ND ND ND ND ND ND ND ND ND

Assemblage B

< 0.1 0.2 0.3 < 0.1 < 0.1 0.5 0.6 0.1 < 0.1 0.1 0.1 < 0.1

0.1 < 0.1 0.1 < 0.1 < 0.1 < 0.1 0.3 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1

1.27 1.85 1.64 1.85 1.78 ND ND ND ND 0.79 0.88 ND

0.06 0.08 0.11 0.08 0.12 0.1 ND ND ND ND ND ND ND

qPCR

Method 1623 USEPA

qPCR (gdh gene)

Method 1623 USEPA

P/A (SSU gene)

Cryptosporidium (oocysts/L)

Giardia intestinalis (cysts/L)

2.2 × 103

E. coli MPN/100 mL

Table 2 Overall results of physicochemical (turbidity, pH, temperature), bacteriological (E. coli), and concentration of (oo)cysts by EPA method and molecular assays obtained for samples of superficial raw water from São Lourenço River, January–December 2013

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2A

4A 6A 8A 10A 12A 14A 16A 18A 20A 22A 24A 26A

28A 30A 32A 34A 36A 38A 40A 42A 44A 46A 48A

50A

01/07/13

01/21/13 02/04/13 02/18/13 03/04/13 03/18/13 04/08/13 04/22/13 05/06/13 05/20/13 06/10/13 06/24/13 07/01/13

07/15/13 07/29/13 08/12/13 08/26/13 09/09/13 09/25/13 10/07/13 10/21/13 11/11/13 11/25/13 12/02/13

12/16/13

2.85

5.81 9.19 1.00 1.00 1.48 8.6 1.38 2.65 2.67 2.35 3.46

4.10 5.64 3.44 3.26 3.05 3.11 5.16 2.43 4.70 7.24 2.94 9.12

3.56

Turbidity

8.26

8.76 8.21 7.19 8.24 9.30 8.12 7.21 7.41 6.84 7.69 8.59

8.01 7.73 9.24 7.77 7.03 7.89 7.32 7.49 7.74 7.97 7.28 7.86

7.51

pH

23.0

26.7 23.6 26.5 24.7 27.1 15.5 15.2 28.9 32.0 22.3 30.5

21.6 25.9 33.4 28.1 18.9 23.6 21.8 20.8 24.6 20.6 17.3 16.7

30.1

T(°C) air

P/A – Presence/Absence; (CT); ND not detected

Sample

Date

23.2

21.0 19.6 20.3 21.8 23.9 20.3 17.1 24.7 23.8 23.0 24.6

23.1 25.4 28.0 26.7 23.2 23.9 22.3 21.3 22.9 20.8 19.9 18.8

26.8

T(°C) water