The first report of SARS-CoV-2 genome in the groundwater of Tehran, Iran: A call to action for public health

The first report of SARS-CoV-2 genome in the groundwater of Tehran, Iran: A call to action for public health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The first report of SARS-CoV-2 genome in the groundwater of Tehran, Iran: A call to action for public health Seyed Mahdi Hosseinian, Seyed Masoud Hosseini, Paria Barooni Rashno, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4854822/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract A pandemic of acute respiratory disease referred to as COVID-19 has been caused by the highly infectious and transmissible Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which threatened human health. Although the SARS-CoV-2 RNA has been found in wastewater from numerous regions in different countries due to fecal shedding of infected individuals, there is still little information available regarding how prevalent it is in other water matrices especially groundwater, where some areas still rely on it to supply drinking water, irrigation of farmlands, and other purposes. This study attempted to assess the presence of this virus genome in groundwater samples in Tehran, Iran. These samples were collected seasonally from 12 sites over 2 years period (2021–2023). At first, a virus adsorption-elution (VIRADEL) concentration procedure was tested utilizing an avian coronavirus (infectious bronchitis virus, IBV) as a process control followed by RNA extraction. Subsequently, SARS-CoV-2 was quantified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to detect the E and S genes. As a result, SARS-CoV-2 RNA was detected in 1 out of 96 groundwater samples with a concentration of 2/53 × 103 and 3/16 × 103 genome copies/l for E and S genes, respectively. Furthermore, the SARS-CoV-2 positive sample was subjected to semi-nested PCR targeting the partial S gene, followed by direct sequencing, phylogenetic and mutation analysis. BA.1 Omicron was the only identified variant during this study. These findings show how important water-based epidemiology is to monitor SARS-CoV-2 at the community-level and subsequent human exposure, even when COVID-19 prevalence is low. SARS-CoV-2. COVID-19. Groundwater. RT-qPCR. VIRADEL. Iran Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a positively-sense enveloped RNA virus belonging to the Coronaviridae family, is the main agent of the world-wide pandemic of Coronavirus disease (COVID-19) which has the largest genome among RNA viruses (approximately 30kb)[ 1 ]. SARS-CoV-2, formerly referred to as human coronavirus 2019 (HCoV-19) or 2019 novel coronavirus (2019-nCoV), was initially detected in Wuhan, Hubei, China in late 2019[ 2 ]. On January 30, 2020, the public health emergency of international concern (PHEIC) was declared by the World Health Organization (WHO), and finally COVID-19 was officially announced a pandemic on March 11, 2020[ 3 ]. Over 750 million positive cases and over 7 million deaths have been attributed to this pandemic globally, with Iran ranking as the 19th-highest country with 7,625,812 confirmed positive cases (WHO, January 16, 2024)[ 4 ]. The Latin word corona is where the word "coronavirus" originates, which means "wreath" or "crown" and refers to the distinctive appearance of virions[ 5 ]. Coronaviruses have the ability to infect humans and a wide range of animals (avian species, livestock and other mammals), resulting in variety of disease with various severity[ 6 ]. These viruses can be the agent of mild respiratory symptoms (HCoV-OC43, HCoV-229E, HCoV-HKU1, HCoV-NL63) to severe respiratory infections (MERS-CoV, primary SARS-CoV, and SARS-CoV-2) in humans[ 7 ]. As with other coronaviruses, SARS-CoV-2 also contains four structural proteins: E (envelope), M (membrane) S (spike), and N (nucleocapsid; As the RNA genome is protected by the N protein, the S, M, and E proteins form the viral envelope[ 8 , 9 ]. SARS-CoV-2 infection occurs in humans primarily through the interaction of the viral S protein with the angiotensin-converting enzyme 2 (ACE2) receptors on a host cell's surface[ 10 ]. As each monomer of S protein assembles, which has about 1273 residues (depending on deletions in some variants), a clove-shaped trimer is formed, with three S1 heads and a trimeric S2 stalk. The N-terminal domain (NDT, residues 14–305) and receptor-binding domain (RBD, residues 319–541) are the two domains that are present in the SARS-CoV-2 S1 subunit. S2 subunit consists of fusion peptide (FP, residues 788–806) followed by two heptad repeats (HR1, residues 912–984 and HR2, residues 1163–1213), a transmembrane anchor (TA, residues 1213–1237) and the intracellular tail (IT, residues 1237–1273)[ 11 – 13 ]. The most common symptoms of COVID-19 caused by SARS-CoV-2 are rhinorrhea, cough, fever, dyspnea, and severe pneumonia[ 14 ]. Besides, the symptoms of long-term COVID-19 are extremely diverse, with many of them similar to those of the initial infection. These symptoms include loss of taste and smell, fatigue, hard breathing, muscle pain, dizziness and palpitations[ 15 ]. Additionally, diarrhea was a sign of gastrointestinal disorders in 2–10% of Covid-19 patients[ 16 ]. Moreover, a significant percentage of individuals may continue to develop no symptoms even after testing positive for SARS-CoV-2[ 17 ]. To identify the lineages that are currently in circulation, the Phylogenetic Assignment of Named Global Outbreak Lineages (PANGO) terminology is employed. Lineages starting with the letter A are belonged to the Wuhan/WH04/2020 variant, whereas lineages starting with the letter B are belonged to the Wuhan-Hu-1 variant, in a classification proposed by Rambaut et al.. A number value, such as A.2 or B.1, is allocated to the new SARS-CoV-2 lineages that are descended from lineages A or B[ 18 ]. Moreover, the emerging SARS-CoV-2 variants are classified into clades by Global Initiative on Sharing All Influenza Data (GISAID). After minor lineages merge into major clades, a clade is characterized by the statistical distribution of viral genome distance into phylogenetic groupings. As a result, the virus variants are categorized into eleven phylogenetic clusters, beginning with an early division of S, O and L, followed by an evolution of L into V and G, and then of G into GV, GH, and GR, and finally, GR into GRA and GRY[ 19 , 20 ]. In addition, SARS-CoV-2 is classified into 37 main clades by Nextstrain: 19A, 19B, 20A-J, 21A-M, 22A-F and 23A-F. A clade is formed when a novel variant attains a worldwide frequency of 20%. The clade name for a new viral variant is determined by the year it first appears, and in this instance, it uses the alphabet's subsequent letter[ 21 ]. Coughing, sneezing, breathing, and other respiratory droplets released during close contact with an infected individual are the main ways that SARS-CoV-2 transmits from person to person[ 22 ]. Moreover, Furthermore, feces from infected individuals may contain significant amounts of SARS-CoV-2 (up to 108 genome copies per gram) due to the virus's ability to replicate in human intestinal enterocytes[ 23 , 24 ]. According to Wu et al., SARS-CoV-2 may also continue to multiply for 11 days in patients' gastrointestinal tract even in acidic environment and even after respiratory tract samples are negative[ 25 ]. This opens a passage for viral RNA from human feces to wastewater and suggests a potential fecal-oral transmission route for this virus[ 26 , 27 ]. are still unknown, there are increasing concerns about the risk of SARS-CoV-2 exposure in other water matrices mainly groundwater which is still used as the main source of drinking water, irrigation and other purposes in some areas. An improperly designed, constructed, maintained or located wastewater disposal systems can leak the contaminants especially viruses into the groundwater causing serious problems[ 28 , 29 ]. In addition, the mass burial of COVID-19 victims' bodies raises the chance that the virus could spread more easily through soil water (Vadose zone) into groundwater[ 30 ]. The majority of studies conducted have concentrated on wastewater matrices. SARS-CoV-2 viral load in wastewater-related studies in Australia[ 31 ], Spain[ 32 ], USA[ 33 ], India[ 34 ], Chile[ 35 ], Czech Republic[ 36 ], France[ 37 ] and Brazil[ 38 ] ranged between 1.9×10 1 and 7.0×10 6 copies/L. Several studies have also investigated the possibility that this virus is present in river water[ 39 – 42 ], but not much research has been conducted regarding the potential for SARS-CoV-2 environmental contamination of other water matrices, particularly groundwater, that receive the discharge of untreated or treated wastewater. The SARS-CoV-2 RNA was eventually found in groundwater for the first time in Mexico by Mahlknecht et al[ 43 ]. In Iran, there are few surveillance studies concerning the SARS-CoV-2 RNA in groundwater[ 44 ]. However, wastewater has been the subject of several projects in this country. In a study by Amereh et al., SARS-CoV-2 RNA was identified in untreated sewage samples in Tehran between September 2020 until April 2021[ 45 ]. Moreover, Dargahi et al. detected and quantified the RNA of SARS-CoV-2 in wastewater collection networks, hospital wastewater, and five municipal wastewater treatment plants in Ardabil[ 46 ]. Also, a recent study conducted by Nasseri et al. has demonstrated that SARS-CoV 2 can be detected in treated and raw wastewater in three cities of Iran: Anzali, Qom and Tehran[ 47 ]. Based on this background and considering the emerging concern for fecal-oral SARS-CoV-2 transmission in groundwater, we assessed the presence of SARS-CoV-2 RNA in groundwater in Tehran using widely available quantitative polymerase chain reaction (qPCR) assay. In addition, the study aimed to conduct a survey of viral dissemination during an epidemic's peak phase and consider any potential effects on the environment and public health. This is the first study to report the SARS-CoV-2 RNA detection in the groundwater of Tehran, Iran. 2. Material and Methods 2.1 Study Area The capital of Iran, Tehran, is situated on the Alborz Mountain range to the north and across the country's central plateau to the south, making it the first most important province in terms of both population and economics. As stated, the province is 3,750 feet (1,143 meters) above sea level. It comprises 16 counties with a metropolitan population of over 15 million inhabitants. Tehran has an arid continental climate, with extremely hot, sunny summers and chilly, mostly rainy winters. Tehran receives its surface water supply from the Karaj River in the northwest, the Latyan dam on the Jajrood River in the north, and the Lar dam on the Lar River in the northeast, in addition to groundwater found in the province. In the area, there are numerous industrial and agricultural activities that are highly dependent on groundwater. 2.2 Water Samples Collection Water samples were collected seasonally based on eight sample collections at each site from Fall 2021 to Summer 2023 as follows (ISO 5667-11:2009): The grab sampling method was used to collect 96 groundwater samples in 10L polyethylene sterile bottles from various sites, including springs, wells, and aqueducts (Fig. 1 ). The samples were then transported on ice and kept refrigerated at 4°C pending further processing. 2.3 Physicochemical Analysis Since it has been indicated that the HCoVs deactivation has a significant association with some physicochemical properties, these parameters play a vital role in HCoVs decay in water. For this reason, some main parameters of the collected water samples including turbidity, temperature, pH, electrical conductivity (EC), total dissolved solids (TDS), and nitrate (NO3-) were specifically measured using standard methods (ISO/TS 13530:2009). The statistical analysis of the obtained data was done by SPSS Statistics version 27 according to existing guidelines. 2.4 Bacteriological Analysis A multiple-tube fermentation method was performed in a three-tube series of five dilutions ranging from 10 − 1 to 10 − 5 to evaluate the values of the most probable number (MPN) of total coliform, fecal coliform and E. coli in groundwater samples. Lauryl Sulfate Broth (LSB, Merck, Darmstadt, Germany) was selected as a preliminary medium to enumerate coliform and non-coliform density, and Brilliant Green Bile Lactose Broth (BGBLB) (Merck, Darmstadt, Germany) was used to confirm the presence of total coliform. In addition, the presence of fecal coliform and E. coli were assessed using EC Broth with MUG (Merck, Darmstadt, Germany), respectively (ISO 9308-2:2012). 2.5 Virus Concentration The adsorption-elution method was performed to concentrate all groundwater samples using electronegative filters. This procedure was followed according to Katayama et al.'s earlier description[ 48 ]. Briefly, each groundwater sample was treated with a final concentration of 25mM MgCl2, and the total volume was then filtered using a filtration device (Sartorius, Goettingen, Germany) through a 47mm nitrocellulose membrane (0.45µm pore size, Sartorius, Goettingen, Germany) until the filter clogged. Subsequently, magnesium ions were removed from the filter using 200ml of 0.5mM H2SO4 (pH 3.0). Following that, the virus was eluted in a falcon tube with a neutralizing solution (50µL of 100mM H2SO4 and 100µL of 100x TE buffer) using 10ml of 1mM NaOH (pH 10.8). A final concentration step was performed by using a precipitation method as reported previously by Vilagines et al with some optimization[ 49 ], where 2.5% NaCl and 12.5% poly-ethylene glycol (PEG-6000, Merck, Darmstadt, Germany) were included to the previous primary concentrate followed by incubation at 4℃ for 2h, and then centrifugation at 10000×g for 45 min at 4℃ twice. Finally, the supernatant was discarded and the pellet was suspended in 300µL of phosphate buffer saline (pH 7.2) and kept at − 20°C pending further processing. 2.6 Viral RNA Extraction Viral RNA was extracted from all concentrated groundwater samples seeded with 6.25×10 2 copies/µl of avian infectious bronchitis virus (IBV) as a process control utilizing QIAamp RNA mini kit (Qiagen, Germany), based on the manufacturer's protocol. 2.7 RT-qPCR for SARS-CoV-2 RNA With the use of RT-qPCR and the COVITECH COVID-19 One Step q-Real Time PCR kit (ACECR, Iran), the nucleic acid was analyzed to identify the E and S genes of SARS-CoV-2 as well as the internal control (RNaseP). Amplification was performed in a reaction (20µL) vial containing 10µL Master Mix, 1µL primers-probe, 5µL of RNAs extracted from each sample, and 4µL nuclease-free water. 5µL of the positive control (COVITECH COVID-19 Positive Control Template) was also used for this study. Besides, nuclease-free water was utilized as a no template control (NTC) in this evaluation. The thermocycling parameters were: reverse transcription at 55°C for 10 min, preheating at 95°C for 3 min, and 50 cycles of denaturation at 95°C for 15s and annealing at 60°C for 60s. A Rotor-Gene® Q (Qiagen, Germany) was used for fluorescence detection and amplification. A serial dilution to generate a 4-point standard curve ranging from 200000 to 200 copies/µL was applied for quantitative analysis. Samples were considered positive if their cycle threshold value (Ct) was less than 40. 2.8 SARS-CoV-2-Specific Semi-nested RT-PCR The AddScript cDNA Synthesis Kit (addbio, Korea) was utilized to synthesize complementary DNA (cDNA). 5µl of RNA was added to 10µl of 2x reaction buffer, 2µl 10x random hexamer), 2µl dNTP mixture and 1µl of 20x enzyme solution with the following conditions: priming at 25°C for 10 min, reverse transcription at 50°C for 60 min and RT inactivation at 80°C for 5 min. To determine the genotype of SARS-CoV-2 in the positive groundwater sample, two sets of semi-nested PCR primers were used to target two partial spike (S1 subunit) genes in SARS-CoV-2 (Table 1 ). The synthesized cDNA (4µl) was added to PCR mixture (16µl) consisting of 10µl of Taq DNA Polymerase Master Mix RED (Ampliqon, Denmark), 5 pmol of each outer primer (Spike-RTC F1 and Spike-RTC R1) and nuclease-free water with the following PCR conditions: 95°C for 3 min (initial denaturation) followed by 25 cycles of 95°C for 60s (denaturation), 55°C for 60s (annealing), 72°C for 70s (extension). The final extension was at 72°C for 7 min. Afterwards, the PCR amplification product (1µl) was added to the reaction mixture (19µl): 10µl of Taq DNA Polymerase Master Mix RED (Ampliqon, Denmark), 5 pmol of each inner primer (Spike-RTC F1 and Spike-RTC R2), and nuclease-free water. The PCR cycle was as follows: 95ºC for 3 min, 30 cycles: 95ºC for 1 min, 54ºC for 1 min, 72ºC for 1 min; and final extension, 72ºC for 7 minutes. A 1.5% agarose gel was used to analyze the PCR product under SYBR safe staining. A DNA fragment of 760bp was considered as SARS-CoV-2 cDNA. Table 1 Primers sequences used for semi-nested RT-PCR amplification and DNA sequencing. Gene Primer Sequence 5′- 3′ Amplicon Size Partial S (S1 subunit) Outer Spike-RTC F1 Spike-RTC R1 5′-GATCTCTGCTTTACTAATGTCTATGC-3′ 5′-CACCAATGGGTATGTCACAC-3′ 838 Inner Spike-RTC F1 Spike-RTC R2 5′-GATCTCTGCTTTACTAATGTCTATGC-3′ 5′-CATTAGAACCTGTAGAATAAACACG-3′ 760 2.9 Sequencing and phylogenetic analysis The DNA product was sequenced and the nucleotide sequence (628 bp) was compared with SARS-CoV-2 variants recorded in NCBI GenBank database using the BLAST (Basic Local Alignment Search Tool) program. The phylogenetic relationships of SARS-CoV-2 was determined by the alignment of the sequences using the ClustalX software. A phylogenetic tree was achieved according to the neighbor-joining assay using Nextclade web tool (nextstrain.org) by comparison with all reference sequences. Moreover, the detected SARS-CoV-2 sequence in the groundwater sample was compared to sequences of SARS-CoV-2 clinical samples in GISAID database to identify epidemiologically or phenotypically candidate amino acid (aa) changes. 3. Results 3.1 Physicochemical characteristics Table 2 represents the median values for the physicochemical parameters— turbidity, temperature, pH, conductivity, total dissolved solids, and nitrate—obtained at each location throughout the eight sample collections. Among the 96 samples, the conductivity ranged from 304 to 4600 µS/cm2 (Mean ± SD; 1803.41 ± 1051.88), while the turbidity range was 0.13–14.9 nephelometric turbidity units (NTU) (Mean ± SD; 0.99 ± 1.77). Water temperature varied during the study period between 5 and 24°C, (Mean ± SD; 12.44 ± 4.59) and pH was measured between 5.9 and 8.3 (Mean ± SD; 7.53 ± 0.54) were recorded. Additionally, the range of total dissolved solids was 265–3856 mg/L (Mean ± SD; 1429.29 ± 850.69), while the range of nitrate was 0–33 mg/L (Mean ± SD; 12.81 ± 8.20). Table 3 illustrates the relationship between these parameters. Table 2 Physicochemical parameters obtained from groundwater samples. Season Temperature (°C) pH Turbidity (NTU) TDS (mg/L) NO 3 − (mg/L) EC (µs/cm 2 ) Fall 2021 15.41 7.68 1.25 1251.37 18.40 1867.72 Winter 2021 17.25 7.93 1.84 1519.16 18.08 1928.33 Spring 2022 15.08 7.83 0.59 1408.33 16.66 1787.50 Summer 2022 8.66 7.65 0.93 1333.95 16.49 1266.26 Fall 2022 7.33 7.61 0.50 1423.16 12.85 1552.25 Winter 2022 9.00 7.49 0.53 1665.83 0.73 2030.66 Spring 2023 15.5 6.63 0.57 1420.20 10.40 1800.08 Summer 2023 11.00 7.44 1.70 1397.5 9.35 1773.58 Table 3 Statistical relationship between physicochemical parameters studied in this study. Temperature pH Turbidity TDS NO 3 − EC Temperature Pearson Correlation 1 − 0.024 0.202* 0.002 0.231* 0.047 Sig. (2-tailed) 0.819 0.048 0.982 0.023 0.646 N 96 96 96 96 96 96 pH Pearson Correlation − 0.024 1 0.122 − 0.189 0.052 − 0.210* Sig. (2-tailed) 0.819 0.236 0.066 0.616 0.040 N 96 96 96 96 96 96 Turbidity Pearson Correlation 0.202* 0.122 1 0.073 0.006 0.087 Sig. (2-tailed) 0.048 0.236 0.478 0.951 0.402 N 96 96 96 96 96 96 TDS Pearson Correlation − 0.002 − 0.189 0.073 1 0.254* 0.949** Sig. (2-tailed) 0.982 0.066 0.478 0.013 < 0.001 N 96 96 96 96 96 96 NO 3 − Pearson Correlation 0.231* 0.052 0.006 0.254* 1 0.263** Sig. (2-tailed) 0.023 0.616 0.951 0.013 0.010 N 96 96 96 96 96 96 EC Pearson Correlation 0.047 − 0.210* 0.087 0.949** 0.263** 1 Sig. (2-tailed) 0.646 0.040 0.402 < 0.001 0.010 N 96 96 96 96 96 96 * Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). 3.2 MPN Analysis To get an overall assessment of the quality of the groundwater samples, bacteriological parameters were also characterized. The detection rates of the bacterial parameters were 41.6% for E. coli, 48.9% for fecal coliform and 51% for total coliform (Table 4 ). The concentrations ranged between 2-1600 MPN/100ml for both E. coli and fecal coliform and 4-1600 MPN/100ml for total coliform. Table 4 MPN values and detection rates and of bacterial indicators in groundwater samples. Season Total coliforms Fecal coliform E. coli No. (%) Range of MPN/100ml No. (%) Range of MPN/100ml No. (%) Range of MPN/100ml Fall 2021 8(66.66) 17–1600* 7(58.33) 2–1600 5(41.66) 4–1600 Winter 2022 6(50.00) 4–1600 5(41.66) 2–1600 4(33.33) 7.8–1600 Spring 2022 5(41.66) 22–1600 5(41.66) 22–1600 4(33.33) 11–1600 Summer 2022 7(58.33) 9.3–1600 7(58.33) 6.8–1600 5(41.66) 14–1600 Fall 2022 6(50.00) 6.8–1600 6(50.00) 4–1600 5(41.66) 4–1600 Winter 2023 6(50.00) 9.3–1600 6(50.00) 4–1600 6(50.00) 2–1600 Spring 2023 5(41.66) 39–1600 5(41.66) 2–1600 5(41.66) 2–1600 Summer 2023 6(50.00) 540–1600 6(50.00) 240–1600 6(50.00) 6.1–540 *Max MPN (Approved by Standard Methods Committee, 2014) = 1600/100mL 3.3 Viral RNA extraction and RT-qPCR efficiency IBV was added to concentrated groundwater samples as a process control to track the efficiency of RT-qPCR and RNA extraction for the quantitative detection of SARS-CoV-2. The IBV recovery efficiency ranged between 24–35% (Mean ± SD; 29.5 ± 5.092). 3.4 Detection of SARS-CoV-2 Between Fall 2021 and Summer 2023, during middle risk and low risk periods, a total of 96 samples of groundwater were collected and checked for SARS-CoV-2. The RT-qPCR amplification of the E and S genes fragments has led to the identification of SARS-CoV-2 RNA in 1.04% (1/96) of the groundwater samples that were processed by the virus adsorption-elution (VIRADEL) concentration method. The positive sample was collected in February 2022 and had a concentration of 2/53 × 103 and 3/16 × 103 genome copies/l for E and S gene, respectively (Fig. 2 ). In the case at hand, a sample was considered as "positive" if its Ct value was less than 40. 3.5 SARS-CoV-2 genotyping and molecular analysis After performing semi-nested RT-PCR with SARS-CoV-2-specific primers, one groundwater sample clearly showed the characteristic 760bp fragment. Figure 3 shows an agarose gel with amplified SARS-CoV-2 semi-nested RT-PCR product from SARS-CoV-2 S gene. To characterize the detected SARS-CoV-2 variant in greater detail, PCR product was sequenced with both forward Spike-RTC F1 and reverse Spike-RTC R2 primers. Genotyping was done by sequence alignments with all reference variants followed by phylogenetic analyses (Fig. 4 ). As a result, the identified sequence belonged to BA.1 Omicron variant. Moreover, 10 mutations in the spike gene of the detected SARS-CoV-2 variant have been observed according to CoVsurver mutation app available in GISAID (Fig. 5 ). Comparing the result of this study to the GISAID reference strain (hCoV19/Wuhan/WIV04/2019) that have arisen as of December 2019 in Wuhan, 8 out of the 10 amino acid changes in the S protein are localized in the RBD which have been shown to increase the molecular flexibility of S protein and thus its binding affinity for ACE2. In Addition, the other 2 mutations that occurred outside of the main domains in S1 subunit have a significant impact on SARS-CoV-2 infectivity as well. The reduced endosomal entrance and fusogenicity are probably caused by T547K stabilizing the spike trimer conformation. Furthermore, D614G is the most common of all known SARS-CoV-2 S protein mutations that promotes cell entrance by increasing ACE2 binding while preserving neutralizing susceptibility. Discussion Despite reports of detecting SARS-CoV-2 RNA in both untreated and treated wastewater in various locations throughout the world and the majority of studies on SARS-CoV-2 and other pathogenic viruses in the environment have focused on wastewater matrices, there is still a lack of knowledge about its prevalence in groundwater, which is linked to water distribution to households and their activities. In this study, a RT-qPCR assay targeting the envelope (E) and the spike (S) genes were analyzed for the detection of SARS-CoV-2 RNA in groundwater samples of Tehran, Iran for the first time. Of the 96 groundwater samples assessed, SARS-CoV-2 RNA was found only in 1 sample quantified as 2/53 × 103 and 3/16 × 103 copies/l for E and S genes, respectively, in the range of those detected by Mahlknechtet al. in groundwater from Monterrey Metropolitan Area in Mexico[ 43 ]. Rosiles-González in Quintana Roo, Mexico, and Salvador in Portugal, on the other hand, have reported varying results, with none of the groundwater samples testing positive for SARS-CoV-2 RNA[ 50 , 51 ]. The SARS-CoV-2 RNA positive sample was collected on February, 2022 which could be attributed to the 6th peak of COVID-19 transmission and the high infection rates in the population between January and March 2022 in Iran. This groundwater contamination with SARS-CoV-2 RNA may result from inadequately treated wastewater discharges, hospital, quarantine and isolation centers wastewater discharges, illegal sewage discharges containing feces and urine of infected individuals, and sewer system malfunctions[ 52 – 54 ]. Furthermore, the leachate of the corpses of COVID-19 victims can reach to aquifers and causes an increase in microbial activity, which poses risks to the environment[ 30 , 55 ]. Emphasizing the risk of consuming food made with those vegetables that were irrigated with the contaminated water is also crucial[ 56 , 57 ]. Moreover, the existence of fecal coliforms in the assessed water samples, particularly E. coli, which is a bacterial indicator of the fecal contamination in water, supported the theory that the wastewater treatment plants (WWTPs) are not effectively eliminating these potential pathogens and the treatment systems are not operating as intended[ 42 , 58 – 60 ]. The lack of standardized procedures for identifying and isolating the virus from water matrices may be the reason why some researchers have not been capable of isolating it from water sources. This calls for the development of standardized procedures for sample collection and analyzing the virus in water and wastewater[ 61 – 63 ]. In addition, the virus may become undetectable in water due to a number of factors that lead to its elimination[ 64 – 66 ]. Although many enteroviruses, such as noroviruses, can survive for several weeks in aquatic conditions, the encapsulated virions of coronaviruses are more susceptible to degradation and loss of infectivity. For this reason, the lack of infectivity of coronaviruses is expected[ 67 – 70 ]. Virus survival and transport in aquifers are influenced by a number of critical parameters such as temperature, which controls the rate of virus inactivation; microbial activity, which promotes viral inactivation through extracellular enzymatic activity; pH, influences viral adherence to various surfaces; dissolved solids, which impact virus activity and motility; and organic content. On the other hand, the virus is extremely susceptible to detergents, chemicals, and drugs[ 71 – 74 ]. Temperature, pH, turbidity, TDS, nitrate, and electrical conductivity were the parameters evaluated in this study. According to the statistical test results, there was a significant association among TDS, nitrate and EC in this study. Due to the small number of positive samples in this study, a statistically significant connection between the only positive case and physicochemical parameters could not be established. Furthermore, one of the most important and effective ways to monitor the spread of viruses within a community is through water-based epidemiology, which offers information on the frequency, genetic profile variations, and geographic distributions of the viruses in populations[ 75 – 77 ]. Additionally, analyzing the virus mutations demonstrates how water-based epidemiology can be used to track SARS-CoV-2 variants in developing countries without relying on other nations or international organizations[ 78 , 79 ]. Thus, water sampling can be used in addition to clinical investigation to identify novel variants early. Conclusion The SAR-CoV-2 pandemic has been the subject of numerous studies, each offering a unique perspective on the possible involvement of water systems in dissemination of the virus. This study evaluated the presence of SARS-CoV-2 RNA in groundwater samples from a metropolitan region and the associated health and environmental risks. Based on current data, SARS-CoV-2 has been found in the feces of COVID-19 patients. This suggests that the virus may also be present in hospital and municipal wastewater where there are infected people. This research revealed a detectable SARS-CoV-2 RNA with a concentration of 2/53 × 103 and 3/16 × 103 for E and S genes, respectively and also fecal coliforms, which implies that sewage from the surface or from a leaking sewage system entered the groundwater system. As such, our findings contribute to the ongoing discussion concerning the likely routes taken by SARS-CoV-2 in aquifers that receive wastewater, as well as issues related to water safety. It is necessary to optimize wastewater collecting and water distribution infrastructures in order to minimize illegal discharges and pipe leaks and to prevent possible risks, especially in areas with limited access to potable water and insufficient sanitation. Additionally, in order to prevent the workers from wastewater exposure in WWTPs, various training programs need to be regularly offered. In conjunction with the findings of this study and the lack of information concerning the survival and infectivity of SARS-CoV-2 in association with effective factors such as some physicochemical characteristics in water matrices, it is imperative that the infectivity of these viruses and their variants be thoroughly examined in order to evaluate any potential health risks, particularly with regard to the fecal-oral transmission and all other possible routes, such as consumption of contaminated food which have been irrigated with the contaminated water. Finally, water monitoring for SARS-CoV-2 and other viral pathogens and analyzing their mutations can act as an early warning system, alerting the public to infection rates, geographic distribution, and potential outbreaks of the viruses and their variants in local areas. Declarations Ethics approval Not applicable. Consent to participate Not applicable. Consent for publication Not applicable. Conflict of interest The authors declare no competing interests. Funding The present study was financially supported by Shahid Beheshti University of Medical Sciences, Tehran, Iran (Grant No. 43010606). Author Contribution SMASH, MRZ and SRM conceived the study; SMAHH, PBR performed the sample and data collection; SMAHH, PBR, SHK, BN, MA and SRM carried out the laboratory and molecular tests; SMAHH, AY, HM, KN, AS, and SRM carried out the interpretation and analyze of the data; SMAHH, PBR, and SMASH drafted the manuscript; and SRM, AS, and MRZ critically revised the manuscript for intellectual content. All authors read and approved the final manuscript. Acknowledgement The RIGLD laboratory staff is warmly appreciated by the authors. 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Water Research & Technology, Environmental Science, pp 735–746. 6 Roos YH (2020) Water and pathogenic viruses inactivation—food engineering perspectives. Food Eng Rev 12(3):251–267 One-Year Surveillance of SARS-CoV-2 Virus in Natural and Drinking Water. Pathogens 2022, 11, 1133 . 2022, s Note: MDPI stays neutral with regard to jurisdictional claims in published… La Rosa G et al (2020) Coronavirus in water environments: Occurrence, persistence and concentration methods-A scoping review. Water Res 179:115899 Bilal M et al (2020) Persistence, transmission, and infectivity of SARS-CoV-2 in inanimate environments. Case Stud Chem Environ Eng 2:100047 Drewry WA, Eliassen R (1968) Virus movement in groundwater. J (Water Pollution Control Federation), : p. R257–R271 Gerba CP, Bitton G (1994) Microbial pollutants: their survival and transport pattern to groundwater. Groundwater pollution microbiology., : pp. 65–88 Yates MV, Gerba CP, Kelley LM (1985) Virus persistence in groundwater. Appl Environ Microbiol 49(4):778–781 Kumar M et al (2020) Frontier review on the propensity and repercussion of SARS-CoV-2 migration to aquatic environment. J Hazard Mater Lett 1:100001 Arora S et al (2020) Sewage surveillance for the presence of SARS-CoV-2 genome as a useful wastewater based epidemiology (WBE) tracking tool in India. Water Sci Technol 82(12):2823–2836 Prevost B et al (2015) Large scale survey of enteric viruses in river and waste water underlines the health status of the local population. Environ Int 79:42–50 Sridhar J et al (2022) Importance of wastewater-based epidemiology for detecting and monitoring SARS-CoV-2. Case Stud Chem Environ Eng 6:100241 Amman F et al (2022) Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale. Nat Biotechnol 40(12):1814–1822 Tiwari A et al (2023) Tracing COVID-19 trails in wastewater: a systematic review of SARS-CoV-2 surveillance with viral variants. Water 15(6):1018 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4854822","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350806032,"identity":"d1b1077f-d9ef-47ab-b918-f18d53aa9fa3","order_by":0,"name":"Seyed Mahdi Hosseinian","email":"","orcid":"","institution":"Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, 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14:45:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":193607,"visible":true,"origin":"","legend":"\u003cp\u003eCOVID-19 cases and the detected SARS-CoV-2 RNA in groundwater in Tehran, Iran. A correlation has been observed between the time of detection and one of the highest peaks in the number of daily COVID-19 infection cases.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4854822/v1/4135dfee334c69fc700b5db0.png"},{"id":64180962,"identity":"f95605e7-e004-4f04-8485-a1b1149bfc85","added_by":"auto","created_at":"2024-09-09 14:45:41","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":53747,"visible":true,"origin":"","legend":"\u003cp\u003eAgarose gel electrophoresis of the SARS-CoV-2 amplification product of the semi-nested RT-PCR.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4854822/v1/add7a5151e1a4aa527206804.jpeg"},{"id":64180963,"identity":"543c8fd8-1bfd-47b8-9e6a-a052c480939c","added_by":"auto","created_at":"2024-09-09 14:45:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":289718,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree displaying the relationships between the SARS-CoV-2 clades. It also shows the phylogenetic affiliation of the detected environmental sample (black) assayed.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4854822/v1/e8053dd6452353ad1a9d521b.png"},{"id":64180955,"identity":"ef1927c0-9b94-4cf0-b33b-b8793b76e8bf","added_by":"auto","created_at":"2024-09-09 14:45:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":199521,"visible":true,"origin":"","legend":"\u003cp\u003eDiagrammatic and crystallographic figure of the domain arrangement of the SARS-CoV-2 S protein (created with app.biorender.com). (A) The structure of the SARS-CoV-2 Spike protein and the main domains. (B) Visual illustration of the relative position of mutations within the detected SARS-CoV-2 S protein.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4854822/v1/e35ac2d54e09480e15290453.png"},{"id":76090483,"identity":"06114c28-fec8-43b3-84a3-6a8c37a1a5a1","added_by":"auto","created_at":"2025-02-12 08:24:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2850080,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4854822/v1/307252c7-266a-4062-b89e-9e3e556695dc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The first report of SARS-CoV-2 genome in the groundwater of Tehran, Iran: A call to action for public health","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a positively-sense enveloped RNA virus belonging to the Coronaviridae family, is the main agent of the world-wide pandemic of Coronavirus disease (COVID-19) which has the largest genome among RNA viruses (approximately 30kb)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. SARS-CoV-2, formerly referred to as human coronavirus 2019 (HCoV-19) or 2019 novel coronavirus (2019-nCoV), was initially detected in Wuhan, Hubei, China in late 2019[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. On January 30, 2020, the public health emergency of international concern (PHEIC) was declared by the World Health Organization (WHO), and finally COVID-19 was officially announced a pandemic on March 11, 2020[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Over 750\u0026nbsp;million positive cases and over 7\u0026nbsp;million deaths have been attributed to this pandemic globally, with Iran ranking as the 19th-highest country with 7,625,812 confirmed positive cases (WHO, January 16, 2024)[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Latin word corona is where the word \"coronavirus\" originates, which means \"wreath\" or \"crown\" and refers to the distinctive appearance of virions[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Coronaviruses have the ability to infect humans and a wide range of animals (avian species, livestock and other mammals), resulting in variety of disease with various severity[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These viruses can be the agent of mild respiratory symptoms (HCoV-OC43, HCoV-229E, HCoV-HKU1, HCoV-NL63) to severe respiratory infections (MERS-CoV, primary SARS-CoV, and SARS-CoV-2) in humans[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. As with other coronaviruses, SARS-CoV-2 also contains four structural proteins: E (envelope), M (membrane) S (spike), and N (nucleocapsid; As the RNA genome is protected by the N protein, the S, M, and E proteins form the viral envelope[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. SARS-CoV-2 infection occurs in humans primarily through the interaction of the viral S protein with the angiotensin-converting enzyme 2 (ACE2) receptors on a host cell's surface[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As each monomer of S protein assembles, which has about 1273 residues (depending on deletions in some variants), a clove-shaped trimer is formed, with three S1 heads and a trimeric S2 stalk. The N-terminal domain (NDT, residues 14\u0026ndash;305) and receptor-binding domain (RBD, residues 319\u0026ndash;541) are the two domains that are present in the SARS-CoV-2 S1 subunit. S2 subunit consists of fusion peptide (FP, residues 788\u0026ndash;806) followed by two heptad repeats (HR1, residues 912\u0026ndash;984 and HR2, residues 1163\u0026ndash;1213), a transmembrane anchor (TA, residues 1213\u0026ndash;1237) and the intracellular tail (IT, residues 1237\u0026ndash;1273)[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe most common symptoms of COVID-19 caused by SARS-CoV-2 are rhinorrhea, cough, fever, dyspnea, and severe pneumonia[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Besides, the symptoms of long-term COVID-19 are extremely diverse, with many of them similar to those of the initial infection. These symptoms include loss of taste and smell, fatigue, hard breathing, muscle pain, dizziness and palpitations[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, diarrhea was a sign of gastrointestinal disorders in 2\u0026ndash;10% of Covid-19 patients[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Moreover, a significant percentage of individuals may continue to develop no symptoms even after testing positive for SARS-CoV-2[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo identify the lineages that are currently in circulation, the Phylogenetic Assignment of Named Global Outbreak Lineages (PANGO) terminology is employed. Lineages starting with the letter A are belonged to the Wuhan/WH04/2020 variant, whereas lineages starting with the letter B are belonged to the Wuhan-Hu-1 variant, in a classification proposed by Rambaut et al.. A number value, such as A.2 or B.1, is allocated to the new SARS-CoV-2 lineages that are descended from lineages A or B[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Moreover, the emerging SARS-CoV-2 variants are classified into clades by Global Initiative on Sharing All Influenza Data (GISAID). After minor lineages merge into major clades, a clade is characterized by the statistical distribution of viral genome distance into phylogenetic groupings. As a result, the virus variants are categorized into eleven phylogenetic clusters, beginning with an early division of S, O and L, followed by an evolution of L into V and G, and then of G into GV, GH, and GR, and finally, GR into GRA and GRY[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In addition, SARS-CoV-2 is classified into 37 main clades by Nextstrain: 19A, 19B, 20A-J, 21A-M, 22A-F and 23A-F. A clade is formed when a novel variant attains a worldwide frequency of 20%. The clade name for a new viral variant is determined by the year it first appears, and in this instance, it uses the alphabet's subsequent letter[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCoughing, sneezing, breathing, and other respiratory droplets released during close contact with an infected individual are the main ways that SARS-CoV-2 transmits from person to person[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Moreover, Furthermore, feces from infected individuals may contain significant amounts of SARS-CoV-2 (up to 108 genome copies per gram) due to the virus's ability to replicate in human intestinal enterocytes[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. According to Wu et al., SARS-CoV-2 may also continue to multiply for 11 days in patients' gastrointestinal tract even in acidic environment and even after respiratory tract samples are negative[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This opens a passage for viral RNA from human feces to wastewater and suggests a potential fecal-oral transmission route for this virus[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. are still unknown, there are increasing concerns about the risk of SARS-CoV-2 exposure in other water matrices mainly groundwater which is still used as the main source of drinking water, irrigation and other purposes in some areas. An improperly designed, constructed, maintained or located wastewater disposal systems can leak the contaminants especially viruses into the groundwater causing serious problems[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In addition, the mass burial of COVID-19 victims' bodies raises the chance that the virus could spread more easily through soil water (Vadose zone) into groundwater[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe majority of studies conducted have concentrated on wastewater matrices. SARS-CoV-2 viral load in wastewater-related studies in Australia[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], Spain[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], USA[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], India[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], Chile[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], Czech Republic[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], France[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and Brazil[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] ranged between 1.9\u0026times;10\u003csup\u003e1\u003c/sup\u003e and 7.0\u0026times;10\u003csup\u003e6\u003c/sup\u003e copies/L. Several studies have also investigated the possibility that this virus is present in river water[\u003cspan additionalcitationids=\"CR40 CR41\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], but not much research has been conducted regarding the potential for SARS-CoV-2 environmental contamination of other water matrices, particularly groundwater, that receive the discharge of untreated or treated wastewater. The SARS-CoV-2 RNA was eventually found in groundwater for the first time in Mexico by Mahlknecht et al[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Iran, there are few surveillance studies concerning the SARS-CoV-2 RNA in groundwater[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. However, wastewater has been the subject of several projects in this country. In a study by Amereh et al., SARS-CoV-2 RNA was identified in untreated sewage samples in Tehran between September 2020 until April 2021[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Moreover, Dargahi et al. detected and quantified the RNA of SARS-CoV-2 in wastewater collection networks, hospital wastewater, and five municipal wastewater treatment plants in Ardabil[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Also, a recent study conducted by Nasseri et al. has demonstrated that SARS-CoV 2 can be detected in treated and raw wastewater in three cities of Iran: Anzali, Qom and Tehran[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBased on this background and considering the emerging concern for fecal-oral SARS-CoV-2 transmission in groundwater, we assessed the presence of SARS-CoV-2 RNA in groundwater in Tehran using widely available quantitative polymerase chain reaction (qPCR) assay. In addition, the study aimed to conduct a survey of viral dissemination during an epidemic's peak phase and consider any potential effects on the environment and public health. This is the first study to report the SARS-CoV-2 RNA detection in the groundwater of Tehran, Iran.\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Area\u003c/h2\u003e \u003cp\u003eThe capital of Iran, Tehran, is situated on the Alborz Mountain range to the north and across the country's central plateau to the south, making it the first most important province in terms of both population and economics. As stated, the province is 3,750 feet (1,143 meters) above sea level. It comprises 16 counties with a metropolitan population of over 15\u0026nbsp;million inhabitants. Tehran has an arid continental climate, with extremely hot, sunny summers and chilly, mostly rainy winters.\u003c/p\u003e \u003cp\u003eTehran receives its surface water supply from the Karaj River in the northwest, the Latyan dam on the Jajrood River in the north, and the Lar dam on the Lar River in the northeast, in addition to groundwater found in the province. In the area, there are numerous industrial and agricultural activities that are highly dependent on groundwater.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Water Samples Collection\u003c/h2\u003e \u003cp\u003eWater samples were collected seasonally based on eight sample collections at each site from Fall 2021 to Summer 2023 as follows (ISO 5667-11:2009):\u003c/p\u003e \u003cp\u003eThe grab sampling method was used to collect 96 groundwater samples in 10L polyethylene sterile bottles from various sites, including springs, wells, and aqueducts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The samples were then transported on ice and kept refrigerated at 4\u0026deg;C pending further processing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Physicochemical Analysis\u003c/h2\u003e \u003cp\u003eSince it has been indicated that the HCoVs deactivation has a significant association with some physicochemical properties, these parameters play a vital role in HCoVs decay in water. For this reason, some main parameters of the collected water samples including turbidity, temperature, pH, electrical conductivity (EC), total dissolved solids (TDS), and nitrate (NO3-) were specifically measured using standard methods (ISO/TS 13530:2009). The statistical analysis of the obtained data was done by SPSS Statistics version 27 according to existing guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Bacteriological Analysis\u003c/h2\u003e \u003cp\u003eA multiple-tube fermentation method was performed in a three-tube series of five dilutions ranging from 10\u0026thinsp;\u0026minus;\u0026thinsp;1 to 10\u0026thinsp;\u0026minus;\u0026thinsp;5 to evaluate the values of the most probable number (MPN) of total coliform, fecal coliform and E. coli in groundwater samples. Lauryl Sulfate Broth (LSB, Merck, Darmstadt, Germany) was selected as a preliminary medium to enumerate coliform and non-coliform density, and Brilliant Green Bile Lactose Broth (BGBLB) (Merck, Darmstadt, Germany) was used to confirm the presence of total coliform. In addition, the presence of fecal coliform and E. coli were assessed using EC Broth with MUG (Merck, Darmstadt, Germany), respectively (ISO 9308-2:2012).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Virus Concentration\u003c/h2\u003e \u003cp\u003eThe adsorption-elution method was performed to concentrate all groundwater samples using electronegative filters. This procedure was followed according to Katayama et al.'s earlier description[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Briefly, each groundwater sample was treated with a final concentration of 25mM MgCl2, and the total volume was then filtered using a filtration device (Sartorius, Goettingen, Germany) through a 47mm nitrocellulose membrane (0.45\u0026micro;m pore size, Sartorius, Goettingen, Germany) until the filter clogged. Subsequently, magnesium ions were removed from the filter using 200ml of 0.5mM H2SO4 (pH 3.0). Following that, the virus was eluted in a falcon tube with a neutralizing solution (50\u0026micro;L of 100mM H2SO4 and 100\u0026micro;L of 100x TE buffer) using 10ml of 1mM NaOH (pH 10.8). A final concentration step was performed by using a precipitation method as reported previously by Vilagines et al with some optimization[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], where 2.5% NaCl and 12.5% poly-ethylene glycol (PEG-6000, Merck, Darmstadt, Germany) were included to the previous primary concentrate followed by incubation at 4℃ for 2h, and then centrifugation at 10000\u0026times;g for 45 min at 4℃ twice. Finally, the supernatant was discarded and the pellet was suspended in 300\u0026micro;L of phosphate buffer saline (pH 7.2) and kept at \u0026minus;\u0026thinsp;20\u0026deg;C pending further processing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Viral RNA Extraction\u003c/h2\u003e \u003cp\u003eViral RNA was extracted from all concentrated groundwater samples seeded with 6.25\u0026times;10\u003csup\u003e2\u003c/sup\u003e copies/\u0026micro;l of avian infectious bronchitis virus (IBV) as a process control utilizing QIAamp RNA mini kit (Qiagen, Germany), based on the manufacturer's protocol.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 RT-qPCR for SARS-CoV-2 RNA\u003c/h2\u003e \u003cp\u003eWith the use of RT-qPCR and the COVITECH COVID-19 One Step q-Real Time PCR kit (ACECR, Iran), the nucleic acid was analyzed to identify the E and S genes of SARS-CoV-2 as well as the internal control (RNaseP). Amplification was performed in a reaction (20\u0026micro;L) vial containing 10\u0026micro;L Master Mix, 1\u0026micro;L primers-probe, 5\u0026micro;L of RNAs extracted from each sample, and 4\u0026micro;L nuclease-free water. 5\u0026micro;L of the positive control (COVITECH COVID-19 Positive Control Template) was also used for this study. Besides, nuclease-free water was utilized as a no template control (NTC) in this evaluation. The thermocycling parameters were: reverse transcription at 55\u0026deg;C for 10 min, preheating at 95\u0026deg;C for 3 min, and 50 cycles of denaturation at 95\u0026deg;C for 15s and annealing at 60\u0026deg;C for 60s. A Rotor-Gene\u0026reg; Q (Qiagen, Germany) was used for fluorescence detection and amplification. A serial dilution to generate a 4-point standard curve ranging from 200000 to 200 copies/\u0026micro;L was applied for quantitative analysis. Samples were considered positive if their cycle threshold value (Ct) was less than 40.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 SARS-CoV-2-Specific Semi-nested RT-PCR\u003c/h2\u003e \u003cp\u003eThe AddScript cDNA Synthesis Kit (addbio, Korea) was utilized to synthesize complementary DNA (cDNA). 5\u0026micro;l of RNA was added to 10\u0026micro;l of 2x reaction buffer, 2\u0026micro;l 10x random hexamer), 2\u0026micro;l dNTP mixture and 1\u0026micro;l of 20x enzyme solution with the following conditions: priming at 25\u0026deg;C for 10 min, reverse transcription at 50\u0026deg;C for 60 min and RT inactivation at 80\u0026deg;C for 5 min. To determine the genotype of SARS-CoV-2 in the positive groundwater sample, two sets of semi-nested PCR primers were used to target two partial spike (S1 subunit) genes in SARS-CoV-2 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The synthesized cDNA (4\u0026micro;l) was added to PCR mixture (16\u0026micro;l) consisting of 10\u0026micro;l of Taq DNA Polymerase Master Mix RED (Ampliqon, Denmark), 5 pmol of each outer primer (Spike-RTC F1 and Spike-RTC R1) and nuclease-free water with the following PCR conditions: 95\u0026deg;C for 3 min (initial denaturation) followed by 25 cycles of 95\u0026deg;C for 60s (denaturation), 55\u0026deg;C for 60s (annealing), 72\u0026deg;C for 70s (extension). The final extension was at 72\u0026deg;C for 7 min. Afterwards, the PCR amplification product (1\u0026micro;l) was added to the reaction mixture (19\u0026micro;l): 10\u0026micro;l of Taq DNA Polymerase Master Mix RED (Ampliqon, Denmark), 5 pmol of each inner primer (Spike-RTC F1 and Spike-RTC R2), and nuclease-free water. The PCR cycle was as follows: 95\u0026ordm;C for 3 min, 30 cycles: 95\u0026ordm;C for 1 min, 54\u0026ordm;C for 1 min, 72\u0026ordm;C for 1 min; and final extension, 72\u0026ordm;C for 7 minutes. A 1.5% agarose gel was used to analyze the PCR product under SYBR safe staining. A DNA fragment of 760bp was considered as SARS-CoV-2 cDNA.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimers sequences used for semi-nested RT-PCR amplification and DNA sequencing.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePrimer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSequence 5\u0026prime;- 3\u0026prime;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAmplicon Size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePartial S\u003c/p\u003e \u003cp\u003e(S1 subunit)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOuter\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSpike-RTC F1\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eSpike-RTC R1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5\u0026prime;-GATCTCTGCTTTACTAATGTCTATGC-3\u0026prime;\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e5\u0026prime;-CACCAATGGGTATGTCACAC-3\u0026prime;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e838\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eInner\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSpike-RTC F1\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eSpike-RTC R2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5\u0026prime;-GATCTCTGCTTTACTAATGTCTATGC-3\u0026prime;\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e5\u0026prime;-CATTAGAACCTGTAGAATAAACACG-3\u0026prime;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e760\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Sequencing and phylogenetic analysis\u003c/h2\u003e \u003cp\u003eThe DNA product was sequenced and the nucleotide sequence (628 bp) was compared with SARS-CoV-2 variants recorded in NCBI GenBank database using the BLAST (Basic Local Alignment Search Tool) program. The phylogenetic relationships of SARS-CoV-2 was determined by the alignment of the sequences using the ClustalX software. A phylogenetic tree was achieved according to the neighbor-joining assay using Nextclade web tool (nextstrain.org) by comparison with all reference sequences. Moreover, the detected SARS-CoV-2 sequence in the groundwater sample was compared to sequences of SARS-CoV-2 clinical samples in GISAID database to identify epidemiologically or phenotypically candidate amino acid (aa) changes.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Physicochemical characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e represents the median values for the physicochemical parameters\u0026mdash; turbidity, temperature, pH, conductivity, total dissolved solids, and nitrate\u0026mdash;obtained at each location throughout the eight sample collections. Among the 96 samples, the conductivity ranged from 304 to 4600 \u0026micro;S/cm2 (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; 1803.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1051.88), while the turbidity range was 0.13\u0026ndash;14.9 nephelometric turbidity units (NTU) (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; 0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77). Water temperature varied during the study period between 5 and 24\u0026deg;C, (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; 12.44\u0026thinsp;\u0026plusmn;\u0026thinsp;4.59) and pH was measured between 5.9 and 8.3 (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; 7.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54) were recorded. Additionally, the range of total dissolved solids was 265\u0026ndash;3856 mg/L (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; 1429.29\u0026thinsp;\u0026plusmn;\u0026thinsp;850.69), while the range of nitrate was 0\u0026ndash;33 mg/L (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; 12.81\u0026thinsp;\u0026plusmn;\u0026thinsp;8.20). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the relationship between these parameters.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysicochemical parameters obtained from groundwater samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeason\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003cp\u003e(\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003cp\u003e(NTU)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003cp\u003e(\u0026micro;s/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFall\u003c/p\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e15.41\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.68\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1251.37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e18.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1867.72\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter 2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e17.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.93\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1519.16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e18.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1928.33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpring 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e15.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1408.33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e16.66\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1787.50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8.66\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.93\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1333.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e16.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1266.26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFall\u003c/p\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7.33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.61\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1423.16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e12.85\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1552.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.53\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1665.83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.73\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2030.66\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpring 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e15.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6.63\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1420.20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e10.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1800.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.44\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1397.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9.35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1773.58\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical relationship between physicochemical parameters studied in this study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.202*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.231*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSig. (2-tailed)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.819\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.982\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.646\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.122\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;0.189\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.052\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;0.210*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSig. (2-tailed)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.819\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.236\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.066\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.616\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.202*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.122\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.073\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.087\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSig. (2-tailed)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.236\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.478\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.951\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.402\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;0.189\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.073\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.254*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.949**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSig. (2-tailed)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.982\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.066\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.478\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.231*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.052\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.254*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.263**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSig. (2-tailed)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.616\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.951\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;0.210*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.087\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.949**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.263**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSig. (2-tailed)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.646\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.402\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* Correlation is significant at the 0.05 level (2-tailed).\u003c/p\u003e \u003cp\u003e** Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 MPN Analysis\u003c/h2\u003e \u003cp\u003eTo get an overall assessment of the quality of the groundwater samples, bacteriological parameters were also characterized. The detection rates of the bacterial parameters were 41.6% for E. coli, 48.9% for fecal coliform and 51% for total coliform (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The concentrations ranged between 2-1600 MPN/100ml for both E. coli and fecal coliform and 4-1600 MPN/100ml for total coliform.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMPN values and detection rates and of bacterial indicators in groundwater samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSeason\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTotal coliforms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eFecal coliform\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eE. coli\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRange of MPN/100ml\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo. (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRange of MPN/100ml\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo. (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRange of MPN/100ml\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFall\u003c/p\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8(66.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e17\u0026ndash;1600*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7(58.33)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e4\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4(33.33)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e7.8\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpring 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e22\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e22\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4(33.33)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e11\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7(58.33)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9.3\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7(58.33)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e6.8\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e14\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFall\u003c/p\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6.8\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e4\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9.3\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpring 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e39\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5(41.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e540\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e240\u0026ndash;1600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e6(50.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e6.1\u0026ndash;540\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Max MPN (Approved by Standard Methods Committee, 2014)\u0026thinsp;=\u0026thinsp;1600/100mL\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Viral RNA extraction and RT-qPCR efficiency\u003c/h2\u003e \u003cp\u003eIBV was added to concentrated groundwater samples as a process control to track the efficiency of RT-qPCR and RNA extraction for the quantitative detection of SARS-CoV-2. The IBV recovery efficiency ranged between 24\u0026ndash;35% (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; 29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.092).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Detection of SARS-CoV-2\u003c/h2\u003e \u003cp\u003eBetween Fall 2021 and Summer 2023, during middle risk and low risk periods, a total of 96 samples of groundwater were collected and checked for SARS-CoV-2. The RT-qPCR amplification of the E and S genes fragments has led to the identification of SARS-CoV-2 RNA in 1.04% (1/96) of the groundwater samples that were processed by the virus adsorption-elution (VIRADEL) concentration method. The positive sample was collected in February 2022 and had a concentration of 2/53 \u0026times; 103 and 3/16 \u0026times; 103 genome copies/l for E and S gene, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the case at hand, a sample was considered as \"positive\" if its Ct value was less than 40.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.5 SARS-CoV-2 genotyping and molecular analysis\u003c/h2\u003e \u003cp\u003eAfter performing semi-nested RT-PCR with SARS-CoV-2-specific primers, one groundwater sample clearly showed the characteristic 760bp fragment. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows an agarose gel with amplified SARS-CoV-2 semi-nested RT-PCR product from SARS-CoV-2 S gene. To characterize the detected SARS-CoV-2 variant in greater detail, PCR product was sequenced with both forward Spike-RTC F1 and reverse Spike-RTC R2 primers. Genotyping was done by sequence alignments with all reference variants followed by phylogenetic analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). As a result, the identified sequence belonged to BA.1 Omicron variant. Moreover, 10 mutations in the spike gene of the detected SARS-CoV-2 variant have been observed according to CoVsurver mutation app available in GISAID (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Comparing the result of this study to the GISAID reference strain (hCoV19/Wuhan/WIV04/2019) that have arisen as of December 2019 in Wuhan, 8 out of the 10 amino acid changes in the S protein are localized in the RBD which have been shown to increase the molecular flexibility of S protein and thus its binding affinity for ACE2. In Addition, the other 2 mutations that occurred outside of the main domains in S1 subunit have a significant impact on SARS-CoV-2 infectivity as well. The reduced endosomal entrance and fusogenicity are probably caused by T547K stabilizing the spike trimer conformation. Furthermore, D614G is the most common of all known SARS-CoV-2 S protein mutations that promotes cell entrance by increasing ACE2 binding while preserving neutralizing susceptibility.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eDespite reports of detecting SARS-CoV-2 RNA in both untreated and treated wastewater in various locations throughout the world and the majority of studies on SARS-CoV-2 and other pathogenic viruses in the environment have focused on wastewater matrices, there is still a lack of knowledge about its prevalence in groundwater, which is linked to water distribution to households and their activities. In this study, a RT-qPCR assay targeting the envelope (E) and the spike (S) genes were analyzed for the detection of SARS-CoV-2 RNA in groundwater samples of Tehran, Iran for the first time.\u003c/p\u003e \u003cp\u003eOf the 96 groundwater samples assessed, SARS-CoV-2 RNA was found only in 1 sample quantified as 2/53 × 103 and 3/16 × 103 copies/l for E and S genes, respectively, in the range of those detected by Mahlknechtet al. in groundwater from Monterrey Metropolitan Area in Mexico[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Rosiles-González in Quintana Roo, Mexico, and Salvador in Portugal, on the other hand, have reported varying results, with none of the groundwater samples testing positive for SARS-CoV-2 RNA[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe SARS-CoV-2 RNA positive sample was collected on February, 2022 which could be attributed to the 6th peak of COVID-19 transmission and the high infection rates in the population between January and March 2022 in Iran.\u003c/p\u003e \u003cp\u003eThis groundwater contamination with SARS-CoV-2 RNA may result from inadequately treated wastewater discharges, hospital, quarantine and isolation centers wastewater discharges, illegal sewage discharges containing feces and urine of infected individuals, and sewer system malfunctions[\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e–\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Furthermore, the leachate of the corpses of COVID-19 victims can reach to aquifers and causes an increase in microbial activity, which poses risks to the environment[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Emphasizing the risk of consuming food made with those vegetables that were irrigated with the contaminated water is also crucial[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, the existence of fecal coliforms in the assessed water samples, particularly E. coli, which is a bacterial indicator of the fecal contamination in water, supported the theory that the wastewater treatment plants (WWTPs) are not effectively eliminating these potential pathogens and the treatment systems are not operating as intended[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e–\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe lack of standardized procedures for identifying and isolating the virus from water matrices may be the reason why some researchers have not been capable of isolating it from water sources. This calls for the development of standardized procedures for sample collection and analyzing the virus in water and wastewater[\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e–\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. In addition, the virus may become undetectable in water due to a number of factors that lead to its elimination[\u003cspan additionalcitationids=\"CR65\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e–\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough many enteroviruses, such as noroviruses, can survive for several weeks in aquatic conditions, the encapsulated virions of coronaviruses are more susceptible to degradation and loss of infectivity. For this reason, the lack of infectivity of coronaviruses is expected[\u003cspan additionalcitationids=\"CR68 CR69\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e–\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Virus survival and transport in aquifers are influenced by a number of critical parameters such as temperature, which controls the rate of virus inactivation; microbial activity, which promotes viral inactivation through extracellular enzymatic activity; pH, influences viral adherence to various surfaces; dissolved solids, which impact virus activity and motility; and organic content. On the other hand, the virus is extremely susceptible to detergents, chemicals, and drugs[\u003cspan additionalcitationids=\"CR72 CR73\" citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e–\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTemperature, pH, turbidity, TDS, nitrate, and electrical conductivity were the parameters evaluated in this study. According to the statistical test results, there was a significant association among TDS, nitrate and EC in this study. Due to the small number of positive samples in this study, a statistically significant connection between the only positive case and physicochemical parameters could not be established.\u003c/p\u003e \u003cp\u003eFurthermore, one of the most important and effective ways to monitor the spread of viruses within a community is through water-based epidemiology, which offers information on the frequency, genetic profile variations, and geographic distributions of the viruses in populations[\u003cspan additionalcitationids=\"CR76\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e–\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Additionally, analyzing the virus mutations demonstrates how water-based epidemiology can be used to track SARS-CoV-2 variants in developing countries without relying on other nations or international organizations[\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Thus, water sampling can be used in addition to clinical investigation to identify novel variants early.\u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003eThe SAR-CoV-2 pandemic has been the subject of numerous studies, each offering a unique perspective on the possible involvement of water systems in dissemination of the virus. This study evaluated the presence of SARS-CoV-2 RNA in groundwater samples from a metropolitan region and the associated health and environmental risks.\u003c/p\u003e\u003cp\u003eBased on current data, SARS-CoV-2 has been found in the feces of COVID-19 patients. This suggests that the virus may also be present in hospital and municipal wastewater where there are infected people. This research revealed a detectable SARS-CoV-2 RNA with a concentration of 2/53 × 103 and 3/16 × 103 for E and S genes, respectively and also fecal coliforms, which implies that sewage from the surface or from a leaking sewage system entered the groundwater system. As such, our findings contribute to the ongoing discussion concerning the likely routes taken by SARS-CoV-2 in aquifers that receive wastewater, as well as issues related to water safety.\u003c/p\u003e\u003cp\u003eIt is necessary to optimize wastewater collecting and water distribution infrastructures in order to minimize illegal discharges and pipe leaks and to prevent possible risks, especially in areas with limited access to potable water and insufficient sanitation. Additionally, in order to prevent the workers from wastewater exposure in WWTPs, various training programs need to be regularly offered.\u003c/p\u003e\u003cp\u003eIn conjunction with the findings of this study and the lack of information concerning the survival and infectivity of SARS-CoV-2 in association with effective factors such as some physicochemical characteristics in water matrices, it is imperative that the infectivity of these viruses and their variants be thoroughly examined in order to evaluate any potential health risks, particularly with regard to the fecal-oral transmission and all other possible routes, such as consumption of contaminated food which have been irrigated with the contaminated water.\u003c/p\u003e\u003cp\u003eFinally, water monitoring for SARS-CoV-2 and other viral pathogens and analyzing their mutations can act as an early warning system, alerting the public to infection rates, geographic distribution, and potential outbreaks of the viruses and their variants in local areas.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe present study was financially supported by Shahid Beheshti University of Medical Sciences, Tehran, Iran (Grant No. 43010606).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSMASH, MRZ and SRM conceived the study; SMAHH, PBR performed the sample and data collection; SMAHH, PBR, SHK, BN, MA and SRM carried out the laboratory and molecular tests; SMAHH, AY, HM, KN, AS, and SRM carried out the interpretation and analyze of the data; SMAHH, PBR, and SMASH drafted the manuscript; and SRM, AS, and MRZ critically revised the manuscript for intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe RIGLD laboratory staff is warmly appreciated by the authors.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe datasets generated and/or analyzed during the current study by the authors is at the disposal of the corresponding author, which will be published upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePal M et al (2020) Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2): an update. Cureus, 12(3)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhat EA et al (2021) SARS-CoV-2: insight in genome structure, pathogenesis and viral receptor binding analysis\u0026ndash;an updated review. 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Water 15(6):1018\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV-2. COVID-19. Groundwater. RT-qPCR. VIRADEL. Iran","lastPublishedDoi":"10.21203/rs.3.rs-4854822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4854822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA pandemic of acute respiratory disease referred to as COVID-19 has been caused by the highly infectious and transmissible Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which threatened human health. Although the SARS-CoV-2 RNA has been found in wastewater from numerous regions in different countries due to fecal shedding of infected individuals, there is still little information available regarding how prevalent it is in other water matrices especially groundwater, where some areas still rely on it to supply drinking water, irrigation of farmlands, and other purposes. This study attempted to assess the presence of this virus genome in groundwater samples in Tehran, Iran. These samples were collected seasonally from 12 sites over 2 years period (2021\u0026ndash;2023). At first, a virus adsorption-elution (VIRADEL) concentration procedure was tested utilizing an avian coronavirus (infectious bronchitis virus, IBV) as a process control followed by RNA extraction. Subsequently, SARS-CoV-2 was quantified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to detect the E and S genes. As a result, SARS-CoV-2 RNA was detected in 1 out of 96 groundwater samples with a concentration of 2/53 \u0026times; 103 and 3/16 \u0026times; 103 genome copies/l for E and S genes, respectively. Furthermore, the SARS-CoV-2 positive sample was subjected to semi-nested PCR targeting the partial S gene, followed by direct sequencing, phylogenetic and mutation analysis. BA.1 Omicron was the only identified variant during this study. These findings show how important water-based epidemiology is to monitor SARS-CoV-2 at the community-level and subsequent human exposure, even when COVID-19 prevalence is low.\u003c/p\u003e","manuscriptTitle":"The first report of SARS-CoV-2 genome in the groundwater of Tehran, Iran: A call to action for public health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-09 14:45:34","doi":"10.21203/rs.3.rs-4854822/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1041cb03-aed0-4b45-be4e-bac25c9cd6aa","owner":[],"postedDate":"September 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-12T08:23:29+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-09 14:45:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4854822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4854822","identity":"rs-4854822","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}