This work was performed with financial support from the Regional Government of Castilla y Leon and the FEDER program (projects CLU 2017-09, UIC315 and VA266P20).

All methods described here have been published elsewhere and contain small modifications from the original methods.
1. Wastewater collection and sample pre-processing
NOTE: Due to the low concentrations of SARS-CoV-2 RNA in environmental samples, the implementation of a concentration step is crucial for a successful detection33,34,35. Described here is the first reported method for the detection of SARS-CoV-2 in wastewater36.
<ol>
	<li>Collection and concentration of wastewater sample(s)
	<ol>
		<li>Collect 1 L of 24 h composite wastewater sample. Store the sample at 4 &#176;C and proceed with the protocol within 24 h.</li>
		<li>Homogenize the sample by gently shaking the bottle. Collect 70 mL into a 100 mL centrifugal tube or divide the sample into two centrifugal tubes of 50 mL.</li>
		<li>Spike 20 &#181;L of mengovirus (3.2 x 103 copies/&#181;L) to 70 mL of each sample as an internal control of the concentration process. Alternatively, spike 10 &#181;L of mengovirus (3.2 x 103 copies/&#181;L) into each 50 mL centrifuge tube.</li>
		<li>Homogenize the sample and centrifuge at 700 x g for 10 min to remove large particles and organisms (pellet).</li>
		<li>Use the resulting supernatant for concentration with centrifugal ultrafiltration devices with a cutoff of 10 KDa by centrifuging at 4,000 x g for 40 min at 4 &#176;C. Elute the concentrate by centrifuging at 700 x g for 40 min and inverting the position of the ultrafiltration device.</li>
		<li>Measure the volume of the resulting concentrate. The volume will change depending on the quantity of solids in the sample that clog the centrifugal filters. In this study, the concentrate volumes obtained were between 200-1,200 &#181;L.</li>
		<li>Use the resulting concentrate for RNA extraction using a commercial kit or an in-house method. For the samples used in this study, a specific commercial kit for viral RNA extraction with an elution volume of 50 &#181;L is used.</li>
		<li>Measure the concentration of the extracted RNA with a fluorometric RNA quantification kit. Divide the extracted RNA into aliquots and freeze at -80 &#176;C until further analysis. 
		NOTE: For each RNA isolation procedure set, a negative control of isolation (NCI) should be included, containing only buffers to detect possible contamination during the extraction.</li>
	</ol>
	</li>
	<li>Collection of air samples using a Coriolis compact air sampler
	<ol>
		<li>Choose a sampling strategy according to the research goal by defining the sampling frequency and sampling locations.</li>
		<li>Set the flow rate on the air sampler (here, 50 L/min for 30 min). Please note that a flow rate of more than 200 L/min can degrade viral RNA, so it is recommended to use a flow rate below 200 L/min.</li>
		<li>Place a sterile cone in the air sampler before starting the collection by pulsing the start. Once the sampling is finished, add 5-15 mL of sterile phosphate-buffered saline (PBS) into the cone. Gently vortex or shake the sample by hand for 15 s. Store the samples for up to 24 h at 4 &#176;C or at -80 &#176;C in cryotubes.</li>
		<li>An optional concentration step can be performed. Clean and decontaminate the cones after each experiment using bleach.</li>
		<li>Extract RNA using a commercial kit or an in-house method. For the samples in this study, a specific commercial kit for viral RNA extraction with an elution volume of 50 &#181;L is used.</li>
		<li>Measure the concentration of the extracted RNA with a fluorometric RNA quantification kit. Divide the extracted RNA into aliquots and freeze at -80 &#176;C until further analysis. 
		&#8203;NOTE: For each RNA isolation procedure set, a negative control of isolation (NCI) should be included, containing only buffers to detect possible contamination during the extraction.</li>
	</ol>
	</li>
</ol>
2. Quantification of SARS-CoV-2 RNA by real-time-quantitative polymerase chain reaction (RT-qPCR)
NOTE: The below protocol is according to the CDC 2019-Novel Coronavirus (2019-nCoV) RT-PCR diagnostic panel37. Divide the primer/probe mix into several aliquots to avoid freezing and thawing cycles.
<ol>
	<li>Prepare the reaction mastermix for each target (mengovirus; SARS-CoV-2 [N1 and N2 genes]) as in Table 1, in a clean hood in the reagent setup room. Mix the primers/probe mix and enzyme by inversion five times. Alternatively, light pulse-vortex the primers/probe mix and enzymefive times. 
	NOTE: Keep all reagents cold during preparation and use. In order to minimize freeze-thaw cycles, it is highly recommended to freeze in aliquots.</li>
	<li>Spin down (1,000 x g for 15-30 s) the tubes to collect the contents at the bottom and place the tubes in a cold rack or on ice.</li>
	<li>Label 1.5 mL microcentrifuge tubes for each target. Add to each microcentrifuge tube the amount of each reagent needed (volume per reaction times the number of reactions including the needed controls). Mix by pipetting up and down and centrifuge for 5 s to collect the contents at the bottom.</li>
	<li>Keep the microcentrifuge tubes in a cold rack and dispense 15 &#181;L into strip PCR tubes or a 96-well plate in a cooling rack. Cover the plate and move it to the nucleic acid handling area (keep it in a cooling rack).</li>
	<li>Thaw an aliquot of extracted RNA and gently vortex for 5 s. Pipette 5 &#181;L of RNA (in addition to 5 &#181;L of non-template control [NTC], negative control of isolation [NCI], and positive control [PC]) to each reaction well or tube containing the previously prepared mastermix. Change gloves often as needed to avoid cross-contamination.</li>
	<li>Cover the entire reaction plate or tubes and gently vortex. Centrifuge (1,000 x g for 15-30 s) the plate or PCR tubes.</li>
	<li>Start the 25 &#181;L RT-qPCR with the following cycling conditions: reverse transcriptase at 45 &#176;C for 10 min; polymerase activation at 95 &#176;C for 10 min; 45 cycles of denaturation at 95 &#176;C for 15 s; and annealing/extension at 60 &#176;C for 45s.</li>
	<li>Calculate the recovery efficiency of mengovirus controls as reported by Conte et al.38: 
	<img alt="Equation 1" src="/files/ftp_upload/65053/65053eq01.jpg" style="margin: auto;" /> &#215; 100</li>
</ol>
3. Sequencing variants in wastewater and data analysis
NOTE: The described protocol is a modified protocol created by Quick et al.39,40. It uses two sets of primers for SARS-CoV-2 genome amplification by PCR tiling methodology-ARTIC primers and VarSkip primers. A combination of primers is used to guarantee the best genome coverage and to minimize the possibility of novel mutations causing primers of one type to fail. In general, the protocol is divided into three parts: reverse transcription (RT) and amplicon generation, sequencing library preparation, and sequencing and data analysis.
<ol>
	<li>Reverse transcription and amplicon generation
	<ol>
		<li>Ensure the input samples have a known qPCR cycling threshold (Ct) value to correctly dilute them in PCR-grade water. The Ct value is obtained during the quantification with qPCR. The dilutions are as follows: if the Ct value is 12-15, dilute the samples 1:100; if the Ct value is 15-18, dilute the samples 1:10; if the Ct value is 18-35, do not dilute the sample. Samples above a Ct value of 35 have a high chance of not working.</li>
		<li>In a PCR plate, pipette 16 &#181;L of each sample to its position on the plate. Add 4 &#181;L of reverse transcription (RT) mastermix (5x). Cover the plate and start the PCR reaction with the following conditions: 25 &#176;C for 2 min, 55 &#176;C for 20 min, and 95&#176;C for 1 min.</li>
		<li>Prepare 10 &#181;M dilutions of each primer set (ARTIC pool A and pool B, and VarSkip pool A and pool B). Prepare the mastermix for each set of primers (ARTIC set A and B, and VarSkip set A and B) as in Table 2. Four mastermixes will result from this.</li>
		<li>On a new PCR plate, pipette 20 &#181;L of the mastermix to each corresponding well. Add 5 &#181;L of the RT sample to each mix. 
		NOTE: Each sample will have four reaction mixtures-ARTIC pool A and B, and VarSkip pool A and B.</li>
		<li>Cover the plate and start the PCR reaction as follows: polymerase activation at 98 &#176;C for 30 s; 35 cycles of denaturation at 98 &#176;C for 15 s; and annealing/extension at 65 &#176;C for 4 min. Spin down (1,000 x g for 15-30 s) the plate. Combine the ARTIC reaction pools and separately combine the VarSkip reaction pools. Each sample will have two 50 &#181;L amplicon reactions.</li>
		<li>Add 50 &#181;L of bead-based reagent for PCR purification to each well and mix well by pipetting. Incubate at room temperature for 5 min. 
		NOTE: Before every use, mix the PCR purification reagent vigorously to resuspend the beads.</li>
		<li>Place the plate on a magnetic separation stand and wait for the beads to form a pellet and the liquid to clear (~5 min). Pipette and discard the supernatant. Keep the PCR plate on the magnetic stand.</li>
		<li>Maintaining the PCR plate on the magnetic stand, add 200 &#181;L of 80% ethanol to each sample without touching the bead pellet. Remove the ethanol.</li>
		<li>Repeat the previous step. Leave the plate on the magnetic stand uncovered for 30 s to allow the ethanol to evaporate.</li>
		<li>Remove the plate from the magnetic stand and add 15 &#181;L of PCR-grade water to each sample. Resuspend the pellet by pipetting. Incubate at room temperature for 2 min.</li>
		<li>Place the plate back on the magnetic stand and allow the beads to pellet (2 min). Carefully pipette 15 &#181;L of the supernatant from each sample to a new PCR plate.</li>
		<li>Measure the concentration of each sample with a fluorometric RNA quantification kit . Take approximately 50 ng of each sample in 12.5 &#181;L to the next step. If required, dilute the sample in PCR-grade water.</li>
	</ol>
	</li>
	<li>Library preparation
	<ol>
		<li>Add 1.75 &#181;L of reaction bufferfrom the Illumina DNA library preparation kit and 0.75 &#181;L of enzyme mix to each sample. Cover the plate, vortex briefly, and spin down (1,000 x g for 15-30 s). Incubate at 21&#176;C for 5 min and at 65 &#176;C for 5 min.</li>
		<li>In a new plate, pipette 3 &#181;L of PCR-grade water for each sample to a new PCR plate. Add 0.75 &#181;L of the prepared samples, 1.25 &#181;L of barcodes for sequencing library preparation, and 5 &#181;L of T4 DNA ligase mastermix. Mix well by pipetting, briefly spin down (1,000 x g for 15-30 s) in a centrifuge and incubate at 21 &#176;C for 20 min and at 65 &#176;C for 10 min. 
		NOTE: If using less than 25 samples, double all the volumes in this step.</li>
		<li>Pool all the samples together by adding 10 &#181;L of each sample to the same low-binding tube. Take 480 &#181;L to the next step.</li>
		<li>Add 192 &#181;L of bead-based reagent for PCR purification to the pool and mix well by pipetting. Incubate at room temperature for 10 min.</li>
		<li>Place the tube on a magnetic stand and wait for the supernatant to clear and a bead pellet to form. Remove the supernatant. Remove the tube from the magnetic stand.</li>
		<li>Add 700 &#181;L of the short fragment buffer (SFB) and mix by pipetting. Place back on the magnetic stand and wait for the pellet to form and the liquid to clear (~5 min). Pipette out the supernatant and discard it.</li>
		<li>Repeat the previous step. Leave the tube on the magnetic stand. Add 100 &#181;L of 80% ethanol without touching the bead. Pipette out the ethanol and allow the bead to dry for 30 s. 
		NOTE: Do not allow the bead to over-dry.</li>
		<li>Remove the tube from the magnetic stand and add 35 &#181;L of PCR-grade water. Mix by pipetting and incubate at room temperature for 2 min. Place the tube on the magnetic stand and allow the bead to pellet and the liquid to clear. Pipette 35 &#181;L of the supernatant to a new tube.</li>
		<li>Measure the RNA concentration of the pooled library. Pipette the volume needed to reach an amount of 30-50 ng of RNA and fill it with PCR-grade water to reach a final volume of 30 &#181;L.</li>
		<li>Prepare the adapter ligation reaction mix: 30 &#181;L of the pooled library, 5 &#181;L of Adapter Mix II, 10 &#181;L of the ligation reaction buffer (5x), and 5 &#181;L of T4 DNA ligase. Mix by pipetting and spin-down (1,000 x g for 15-30 s). Incubate at room temperature for 10 min.</li>
		<li>Add 20 &#181;L of the bead-based reagent for PCR purification and mix by pipetting. Incubate for 10 min at room temperature.</li>
		<li>Place the tube on the magnetic stand and wait for the bead pellet to form and the supernatant to become colorless. Carefully pipette out and discard the supernatant.</li>
		<li>Remove from the magnetic stand and add 125 &#181;L of SFB. Mix by pipetting and place back on the magnetic stand to separate the beads. When the liquid is clear, pipette and discard the supernatant.</li>
		<li>Repeat the previous step. Leave the tube open on the magnetic stand for 30 s for some of the leftover liquid to evaporate.</li>
		<li>Remove the tube from the magnetic stand and add 15 &#181;L of the elution buffer. Mix well by pipetting and briefly spin-down (1,000 x g for 15-30 s). Incubate at room temperature for 5 min. Place on the magnetic stand for 2 min.</li>
		<li>Pipette 15 &#181;L of the supernatant into a new low-binding tube. This is the final library. Measure the concentration with a fluorometric DNA quantification kit. 
		NOTE: In the next step, 12 &#181;L is needed. If the concentration is very high and less than 12 &#181;L of the library is needed, fill up to 12 &#181;L with the elution buffer reagent.</li>
	</ol>
	</li>
	<li>Flow cell loading and sequencing
	<ol>
		<li>Insert the flow cell (R9.4.1) into the real-time DNA and RNA sequencing device.</li>
		<li>Prepare the priming mix by adding 30 &#181;L of flush tether (FLT) reagent to a tube of flush buffer (FB) reagent. Vortex to mix and spin down (1,000 x g for 15-30 s).</li>
		<li>Open the priming port cover. Using a 1,000 &#181;L pipette, set to 200 &#181;L and insert the tip into the priming port. Turn the volume setting wheel and increase the volume until the liquid in the tip is seen. Discard the tip. 
		NOTE: Only turn the wheel until a few &#181;L of liquid in the tip is seen. Pulling larger amounts could damage the flow cell.</li>
		<li>Slowly add 800 &#181;L of the priming mix to the priming port, taking care not to introduce bubbles. Wait for 5 min.</li>
		<li>In the meantime, prepare the libraries for loading. Mix 37.5 &#181;L of the sequencing buffer, 25.5 &#181;L of the loading buffer, and 12 &#181;L of the library. 
		&#8203;NOTE: Mix the loading buffer before pipetting. The beads in this reagent settle very quickly.</li>
		<li>Open the port cover. Pipette 200 &#181;L of the priming mix into the priming port. 
		NOTE: While pipetting into the priming port with the cover port open, one will notice small drops coming from the sample port. Pipette slow enough so the sample port can pull the drops in without spilling over.</li>
		<li>Before loading the prepared library, mix well by pipetting. Using a 100 &#181;L pipette set to 75 &#181;L, take the library and pipette drop by drop into the sample port. Do not touch the port and wait for each drop to be absorbed into the port before loading the next drop to avoid overflowing of the liquid.</li>
		<li>Close the cover port and priming port. Open the software and start the sequencing experiment. Select basecalling On. For a library with 96 multiplexed samples, 10-12 h of sequencing is usually enough to generate sufficient data. 
		NOTE: Using the software, one can insert the sample sheet in .csv format. The sample sheet requires the following data: flow_cell_id, position_id, sample_id, experiment_id, flow_cell_product_code, and kit. The flow cell ID is needed (listed on the side of the flow cell) together with the kit used. For the suggested protocol, the LSK109 kit should be selected.</li>
	</ol>
	</li>
	<li>Sequencing data analysis
	<ol>
		<li>Insert the compressed fastq reads into the wf-artic workflow41. Run the workflow separately with two different primer schemes (ARTIC/V4.1 and NEB-VarSkip/v1a). Two &#34;. primertrimmed.rg.sorted.bam&#34; files are created for each sample.</li>
		<li>Merge the BAM files into a single file with the &#34;samtools merge&#34; command42. Insert the merged BAM file into Freyja tool, leaving default settings, to recover relative lineage abundances43.</li>
		<li>To create a FASTA file, insert the merged BAM file into the &#34;samtools mpileup&#34; and &#34;ivar&#34; tools with default settings44,45. For mutation calling, load the FASTA file into the Nextclade tool46,47.</li>
	</ol>
	</li>
</ol>

The authors have no competing economic interests or other conflicts of interest.

Microbial and viral detection and quantification using (RT-)qPCR methods have garnered widespread acceptance due to their remarkable sensitivity. However, these techniques face numerous challenges when analyzing environmental samples. Wastewater samples contain an abundance of inhibitory substances that can skew measurements and generate misleading results. To tackle these limitations and enhance precision, a complex protocol was conceived, designed, and implemented. This protocol was tailored by combining protocols from the scientific literature and to specifically address the restrictions inherent in qPCR methods by incorporating a series of stringent controls at each stage of the process. By integrating these rigorous quality control measures, this protocol offers a robust solution to the challenges faced by qPCR-based detection and quantification methods in complex environmental samples51,52. The negative control of isolation (NCI) and non-template control (NTC) are essential tools to assess the likelihood of contamination during the RNA extraction and RT-qPCR reaction. Moreover, the integration of mengovirus control RNA provides a crucial means to evaluate inter-sample variability, as well as the efficiency of the concentration step and the inhibitory effects of agents present in complex environmental samples. In every RT-qPCR reaction, positive controls must be included to confirm the effectiveness of the amplification process. It is critical to carefully monitor each step of the protocol, including the storage and processing time of the samples. The degradation of the samples can be influenced by temperature and the complex composition of wastewater, making it essential to store the samples at a temperature of 4 &#176;C and process them within 24 h. By adhering to these stringent quality control measures, researchers and public health workers can confidently and accurately analyze environmental samples to uncover vital insights into microbial and viral populations and better understand the impact of environmental factors on human health48.
The selection of RNA targets for SARS-CoV-2 detection is a critical factor that can impact the sensitivity of RT-qPCR assays. In this study, the authors evaluated the RdRp, E, N1, and N2 targets and found that the RdRp and E assays had lower sensitivity than the N1 and N2 assays, consistent with previous research53. The N1 and N2 assays use double quencher probes, which have been shown to enhance their sensitivity in (RT-)qPCR assays54. Those reasons lead to the decision of using N1 for quantification and N2 as a confirmation of the RNA presence, in order to eliminate doubts when very low concentrations are found. The observed discrepancies among RT-qPCR targets was previously reported36.
Several studies have employed similar protocols and have reported the successful detection and quantification of SARS-CoV-2 RNA in wastewater during the ongoing COVID-19 pandemic6,48,49,55,56. The reported SARS-CoV-2 RNA concentrations are in accordance with the ones reported in this study and protocol48,50,55. Some of these studies have explored the relationship between active cases and concentrations of RT-qPCR target genes, particularly N1 and N26,36,49,50,55,57,58,59. To reduce variability in the obtained gene concentrations, it has been proposed to multiply the experimental concentrations by the flow rate at the time of sampling to obtain the initial viral load36. This approach has been incorporated into the VATar COVID-19 project in Spain, a national monitoring system for COVID-19 in wastewater60.
As the next phase of COVID-19 wastewater-based epidemiology (WBE) studies, researchers have attempted to detect SARS-CoV-2 mutations in wastewater to estimate the circulation of variants of concern within communities. Previous studies have shown a strong correlation between the variants identified in wastewater and those present in the population at the same time. These findings suggest that wastewater-based monitoring could serve as a valuable tool in tracking the spread of SARS-CoV-2 variants61,62. WBE has shown great promise in monitoring SARS-CoV-2 and can be used for the developing future surveillance strategies for pandemics. This approach is particularly useful in the early stages of a pandemic, when there are limited individual tests and many cases may be asymptomatic, and has a complementary strategy to clinical surveillance. Therefore, WBE can be especially useful in places with low economic capacity that cannot afford other more expensive surveillance strategies. The described method can be easily adapted to other viruses that might be relevant to monitor in the future.
The results of air sampling in indoor and outdoor environments revealed that SARS-CoV-2 RNA is present in both environments, although in lower concentrations in outdoor environments38,63,64. These findings suggest that activities and exposures in which mask-wearing and social distancing are difficult to maintain, such as eating, drinking, or attending music festivals, could pose a higher risk for COVID-19 transmission. To mitigate such risks, it is critical to consider appropriate ventilation measures and the use of masks, especially with the emergence of new variants of concern that are more transmissible, such as the Delta (B.1.617.2) and Omicron (B.1.1.529) variants. In light of the lifting of COVID-19 restrictions in many areas, maintaining the use of masks is recommended to keep community transmission of SARS-CoV-2 at a minimum and prevent future outbreaks of the disease5,21,26,65.

In December 2019, a novel disease called COVID-19 emerged, caused by a previously unknown coronavirus, SARS-CoV-21. The resulting global pandemic has presented a significant challenge to clinical and public health laboratories worldwide, as a large number of individuals require testing to accurately assess virus transmission and prevalence in the community. However, in many regions, achieving the necessary level of testing in a timely and spatially comprehensive manner is economically unfeasible2,3. Current surveillance systems based on individual clinical diagnostics rely heavily on symptom severity and individual reporting, as well as the extent to which these symptoms overlap with existing diseases circulating in the population4,5,6,7,8,9,10. Consequently, a high number of asymptomatic cases contributes to a significant underestimation of disease burden7,11.
Due to these challenges, wastewater-based epidemiology (WBE) for COVID-19 surveillance was proposed as a complementary surveillance strategy. WBE was first described in 200112, and was initially used to trace cocaine and other illegal drugs13. This approach relies on the assumption that it is possible to calculate the initial concentration of any substance that is stable in wastewater and excreted by humans8,12. WBE has been successfully implemented in many countries as a complementary and efficient surveillance system for SARS-CoV-23,8,14,15,16. The majority of methods to detect human viruses in aquatic environments follow these steps: concentration, nucleic acid extraction, amplification of the genomic segment (or segments) chosen, and detection/quantification of the amplified genomic segment3.
Another important environment for the detection and quantification of SARS-CoV-2 is in air samples. Initially, SARS-CoV-2 was thought to be transmitted mainly through close personal contact with respiratory droplets from aerosols generated by an infected person while speaking, sneezing, coughing, singing, or breathing17. However, several studies began to report the presence of SARS-CoV-2 RNA in the air, especially in healthcare facilities and other enclosed spaces18,19,20,21. Evidence of SARS-CoV-2 viability in air samples taken indoors in hospitals and other enclosed spaces has been found when the virus concentration was sufficiently high22,23,24. Outdoor studies have generally found no evidence of SARS-CoV-2, except in crowded outdoor spaces21,25,26,27,28,29. As of now, airborne transmission of SARS-CoV-2 has been recognized as a mode of transmission30,31. A recent review study shows the differences between outdoors, where risks of airborne transmission are minimal outside of crowded areas, and indoors, where larger risks could be present in poorly ventilated environments in which strong sources (i.e., number of infected people) could be present. A recent comprehensive review study has highlighted the substantial differences between the risks of airborne transmission in outdoor versus indoor environments, particularly in crowded areas with poor ventilation. The study indicates that the risk of airborne transmission is minimal in outdoor environments, where there is a larger volume of air available for the dilution and dispersion of virus particles32. These findings have important implications for public health policies and guidelines related to COVID-19. By recognizing the significant differences in transmission risks between indoor and outdoor environments, policymakers can develop more effective strategies to mitigate the spread of the virus and protect public health.
There are a variety of methods and protocols for the detection, quantification, and sequencing of SARS-CoV-2 from different environmental samples. This method article aims to present a combination of well-established protocols that allow laboratories with different capacity levels to perform environmental detection, quantification, and sequencing of viruses from wastewater and air samples.

<table><tbody><tr><td>Adapter+A25+A2:D19+A2:D20+A2+A2:D19</td><td>Oxford Nanopore</td><td>EXP-AMII001</td><td>Sequencing</td></tr><tr><td>AllPrep PowerViral DNA/RNA Kit</td><td>Qiagen</td><td>28000-50</td><td>RNA extraction kit</td></tr><tr><td>AMPure XP</td><td>Beckman Coulter</td><td>A63880</td><td>PCR Purification, NGS Clean-up, PCR clean-up</td></tr><tr><td>ARTIC SARS-CoV-2 Amplicon Panel</td><td>IDT</td><td>10011442</td><td>SARS-CoV-2 genome amplification</td></tr><tr><td>Blunt/TA Ligase Master Mix</td><td>NEB</td><td>M0367S</td><td>Library preparation</td></tr><tr><td>CENTRICON PLUS&amp;shy;70 10KDA.</td><td>Fisher Scientific</td><td>10296062</td><td>Concentration filters</td></tr><tr><td>CORIOLIS COMPACT AIR SAMPLER</td><td>Bertin Technologies</td><td>083-DU001</td><td>Air sampler</td></tr><tr><td>Duran&amp;nbsp;laboratory bottles</td><td>Merck</td><td>Z305200-10EA</td><td>Sampling Bottles</td></tr><tr><td>Flow Cell (R9.4.1)</td><td>Oxford Nanopore</td><td>FLO-MIN106D</td><td>Sequencing</td></tr><tr><td>General labarotory consumables (tubes, qPCR plates, etc)</td><td></td><td></td><td></td></tr><tr><td>Ligation Sequencing Kit</td><td>Oxford Nanopore</td><td>SQK-LSK109</td><td>Sequencing</td></tr><tr><td>LunaScript&amp;nbsp;RT SuperMix Kit</td><td>NEB</td><td>E3010</td><td>&amp;nbsp;cDNA synthesis</td></tr><tr><td>Mengovirus extraction control Kit</td><td>Biom&amp;eacute;rieux</td><td>KMG</td><td>Concentration control</td></tr><tr><td>Nalgene General Long-Term Storage Cryogenic Tubes</td><td>Thermofisher</td><td>5011-0012</td><td>Sample storage</td></tr><tr><td>Native Barcoding Expansion 1-12 (PCR-free</td><td>Oxford Nanopore</td><td>EXP-NBD104</td><td>Barcoding</td></tr><tr><td>NEBNext Ultra II End Repair/dA-Tailing Module</td><td>NEB</td><td>E7595</td><td>DNA repair</td></tr><tr><td>NEBNext VarSkip Short SARS-CoV-2 Primer Mixes</td><td>NEB</td><td>E7658</td><td>SARS-CoV-2 genome amplification</td></tr><tr><td>NEBNext&amp;nbsp;Quick Ligation Reaction Buffer</td><td>NEB</td><td>B6058S</td><td>Sequencing&amp;nbsp;</td></tr><tr><td>Phosphate buffered saline</td><td>Merck</td><td>P4474</td><td>Collection buffer</td></tr><tr><td>Phosphate-buffered saline (PBS, 1X), sterile-filtered</td><td>Thermofisher</td><td>J61196.AP</td><td>Elution of air samples</td></tr><tr><td>Q5&amp;nbsp;Hot Start High-Fidelity 2X Master Mix</td><td>NEB</td><td>M0494S</td><td>hot start DNA polymerase</td></tr><tr><td>Qubit RNA HS Assay Kit</td><td>Thermofisher</td><td>Q32852</td><td>RNA quantitation</td></tr><tr><td>SARS-CoV-2 RUO qPCR Primer &amp;amp; Probe Kit</td><td>IDT</td><td>10006713</td><td>Primer-Probe mix and qPCR positive control</td></tr><tr><td>TaqPath 1-Step RT-qPCR Master Mix</td><td>Thermofisher</td><td>A15299</td><td>RT-qPCR kit</td></tr></tbody></table>

quantification and whole genome characterization of sars-cov-2 rna in wastewater and air samples

Wastewater-based epidemiology has emerged as a promising and efficacious surveillance system for SARS-CoV-2 and other infectious diseases in many nations. The process typically involves wastewater concentration, nucleic acid extraction, amplification of selected genomic segments, and detection and quantification of the amplified genomic segment. This methodology can similarly be leveraged to detect and quantify infectious agents, such as SARS-CoV-2, in air samples. Initially, SARS-CoV-2 was presumed to spread primarily through close personal contact with droplets generated by an infected individual while speaking, sneezing, coughing, singing, or breathing. However, a growing number of studies have reported the presence of SARS-CoV-2 RNA in the air of healthcare facilities, establishing airborne transmission as a viable route for the virus. This study presents a composite of established protocols to facilitate environmental detection, quantification, and sequencing of viruses from both wastewater and air samples.

The results summarized in Table 3 show examples of the detection and quantification of SARS-CoV-2 RNA in wastewater and air samples using the method described in this article. Wastewater samples were collected from wastewater treatment plants in Spain and Slovenia and were considered positive if the Ct was less than 40 in at least two of the three replicates, with quantification considered valid if the Ct had a variation of less than 5%. In Spain and Portugal, indoor and outdoor air samples were collected, and the same rules were applied. Duplicates were used for the air samples, not triplicates as for the wastewater samples, as the aim of the study was to detect SARS-CoV-2 RNA and not to quantify it. Furthermore, an RT-qPCR run was only considered valid if all controls used (as described in this protocol) behaved as expected and if no significant deviations were observed in the mengovirus RNA control. For these samples, the mengovirus recovery efficiency varied between 13.7% and 19.7%. The inhibition was assessed by diluting tenfold and 100-fold extracted RNA and by comparing the resulting RT-qPCR results, as well as using a commercial kit. The instructions for each inhibition control kit should be followed as described by the manufacturers.
Wastewater samples had a standard deviation from 1.91% to 13.98% among the triplicates and ranged from 3.05 x 103 to 2.83 x 108 gene copies/L. Air samples ranged from 6.17 x 103 to 5.48 x 109 with a standard deviation between the duplicates between 0.54% and 10.95%. This is in accordance with previous studies6,48,49,50.
As described in this protocol, the samples were sequenced and an example of three sequenced sample results is summarized in Table 4 and Figure 1. In all three samples, the lineage BA.5.x was assigned as the most prevalent by the Freyja tool (95.3%, 95.4%, and 99.8%).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65053/65053fig01.jpg" /> 
Figure 1: SARS-CoV-2 lineage prevalence in selected wastewater samples. Lineages were assigned using the Freyja tool. The summary of prevalence numbers does not necessarily reach 100%, as some of the data is not of sufficient quality. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65053/65053fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Table 1: Reagents and volumes to be added of each to prepare the mastermix for SARS-CoV2 quantification by RT-qPCR. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65053/Table 1.xlsx" target="_blank">Please click here to download this Table.</a>
Table 2: Reagents and volumes to be added of each to prepare the mastermix to amplify the complete SARS-CoV-2 genomes in the samples. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65053/Table 2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 3: Summary of RT-qPCR quantification results of SARS-CoV-2 RNA from wastewater and air samples. The N1 gene was used for quantification and the N2 was used for confirmation (positive or negative). The results are expressed as copies/L. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65053/Table 3.xlsx" target="_blank">Please click here to download this Table.</a>
Table 4: Detected mutations and lineage prevalence. Lineages were assigned using the Freyja tool and according to the mutations of interest found using Nextclade. Genome coverage for each sample is shown. The summary of prevalence numbers does not necessarily reach 100%, as some of the data is not of sufficient quality. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65053/Table 4.xlsx" target="_blank">Please click here to download this Table.</a>

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Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

This protocol aims to quantify SARS-CoV-2 RNA in wastewater and air samples to be used for wastewater-based epidemiology studies and to assess the exposure risk to SARS-CoV-2 in indoor and outdoor aerosols. This protocol also describes a tiled amplicon long-template sequencing approach for SARS-CoV-2 whole genome characterization.

Wastewater-based epidemiology has emerged as a promising and efficacious surveillance system for SARS-CoV-2 and other infectious diseases in many nations. ...

quantification-whole-genome-characterization-sars-cov-2-rna

Nanyang Technological University

Research

JoVE Journal

Environment

1.1K Views.  University of Valladolid. Op afvalwater gebaseerde epidemiologie wordt momenteel gebruikt om COVID-19-bestrijdingsstrategieën wereldwijd aan te vullen door viraal RNA in afvalwatermonsters te detecteren en mogelijke uitbraken te identificeren. Deze techniek biedt een bevolkingsbrede momentopname van de prevalentie van COVID-19 in onze gemeenschap, inclusief asymptomatische gevallen. Ook luchtbemonstering is een belangrijke aanvulling op dit protocol.Klinische diagnostiek is nog steeds de meest nauwkeurige mani...

Video: Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Air-sampled Filter Analysis for Endotoxins and DNA Content

Outdoor aerosol research commonly uses particulate matter sampled on filters. This procedure enables various characterizations of the collected particles to be performed in parallel. The purpose of the method presented here is to obtain a highly accurate and reliable analysis of the endotoxin and DNA content of bio-aerosols extracted from filters. The extraction of high molecular weight organic molecules, such as lipopolysaccharides, from sampled filters involves shaking the sample in a pyrogen-free water-based medium. The subsequent analysis is based on an enzymatic reaction that can be detected using a turbidimetric measurement. As a result of the high organic content on the sampled filters, the extraction of DNA from the samples is performed using a commercial DNA extraction kit that was originally designed for soils and modified to improve the DNA yield. The detection and quantification of specific microbial species using quantitative polymerase chain reaction (q-PCR) analysis are described and compared with other available methods.

Two complementary analyses of atmospheric biological particles from air sampled filters are described herein: the extraction and detection of endotoxin, and of DNA.

Outdoor aerosol research commonly uses particulate matter sampled on filters. This procedure enables various characterizations of the collected particles ...

Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR

Real Time Polymerase Chain Reaction also known as quantitative PCR (q-PCR) is a widely used tool in microbial ecology to quantify gene abundances of taxonomic and functional groups in environmental samples. Used in combination with a reverse transcriptase reaction (RT-q-PCR), it can also be employed to quantify gene transcripts. q-PCR makes use of highly sensitive fluorescent detection chemistries that allow quantification of PCR amplicons during the exponential phase of the reaction. Therefore, the biases associated with &#39;end-point&#39; PCR detected in the plateau phase of the PCR reaction are avoided. A protocol to quantify bacterial 16S rRNA genes and transcripts from coastal sediments via real-time PCR is provided. First, a method for the co-extraction of DNA and RNA from coastal sediments, including the additional steps required for the preparation of DNA-free RNA, is outlined. Second, a step-by-step guide for the quantification of 16S rRNA genes and transcripts from the extracted nucleic acids via q-PCR and RT-q-PCR is outlined. This includes details for the construction of DNA and RNA standard curves. Key considerations for the use of RT-q-PCR assays in microbial ecology are included.

A protocol to quantify bacterial 16S rRNA genes and transcripts from coastal sediments via real-time PCR is provided. The methodology includes the co-extraction of DNA and RNA; preparation of DNA-free RNA; and 16S rRNA gene and transcript quantification via RT-q-PCR, including standard curve construction.

Real Time Polymerase Chain Reaction also known as quantitative PCR (q-PCR) is a widely used tool in microbial ecology to quantify gene abundances of ...

Comparison of Scale in a Photosynthetic Reactor System for Algal Remediation of Wastewater

An experimental methodology is presented to compare the performance of two different sized reactors designed for wastewater treatment. In this study, ammonia removal, nitrogen removal and algal growth are compared over an 8-week period in paired sets of small (100 L) and large (1,000 L) reactors designed for algal remediation of landfill wastewater. Contents of the small and large scale reactors were mixed before the beginning of each weekly testing interval to maintain equivalent initial conditions across the two scales. System characteristics, including surface area to volume ratio, retention time, biomass density, and wastewater feed concentrations, can be adjusted to better equalize conditions occurring at both scales. During the short 8-week representative time period, starting ammonia and total nitrogen concentrations ranged from 3.1-14 mg NH3-N/L, and 8.1-20.1 mg N/L, respectively. The performance of the treatment system was evaluated based on its ability to remove ammonia and total nitrogen and to produce algal biomass. Mean &#177; standard deviation of ammonia removal, total nitrogen removal and biomass growth rates were 0.95&#177;0.3 mg NH3-N/L/day, 0.89&#177;0.3 mg N/L/day, and 0.02&#177;0.03 g biomass/L/day, respectively. All vessels showed a positive relationship between the initial ammonia concentration and ammonia removal rate (R2=0.76). Comparison of process efficiencies and production values measured in reactors of different scale may be useful in determining if lab-scale experimental data is appropriate for prediction of commercial-scale production values.

An experimental methodology is presented to compare the performance of small (100 L) and large (1,000 L) scale reactors designed for algae remediation of landfill wastewater. System characteristics, including surface area to volume ratio, retention time, biomass density, and wastewater feed concentrations, can be adjusted based on application.

An experimental methodology is presented to compare the performance of two different sized reactors designed for wastewater treatment. In this study, ...

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Identification and isolation of contagious individuals along with quarantine of close contacts, is critical for slowing the spread of COVID-19. Large-scale testing in a surveillance or screening capacity for asymptomatic carriers of COVID-19 provides both data on viral spread and the follow-up ability to rapidly test individuals during suspected outbreaks. The COVID-19 early detection program at Michigan State University has been utilizing large-scale testing in a surveillance or screening capacity since fall of 2020. The methods adapted here take advantage of the reliability, large sample volume, and self-collection benefits of saliva, paired with a cost-effective, reagent conserving two-dimensional pooling scheme. The process was designed to be adaptable to supply shortages, with many components of the kits and the assay easily substituted. The processes outlined for collecting and processing SARS-CoV-2 samples can be adapted to test for future viral pathogens reliably expressed in saliva. By providing this blueprint for universities or other organizations, preparedness plans for future viral outbreaks can be developed.

The protocol is intended to serve as a blueprint for universities and other organizations considering large-scale testing for SARS-CoV-2 or developing preparedness plans for future viral outbreaks.

Identification and isolation of contagious individuals along with quarantine of close contacts, is critical for slowing the spread of COVID-19. ...

Genetics

Concentration of Virus Particles from Environmental Water and Wastewater Samples Using Skimmed Milk Flocculation and Ultrafiltration

Water and wastewater-based epidemiology have emerged as alternative methods to monitor and predict the course of outbreaks in communities.&#160;The recovery of microbial fractions, including viruses, bacteria, and microeukaryotes from wastewater and environmental water samples&#160;is one of the challenging steps in these approaches. In this study, we focused on the recovery efficiency of sequential ultrafiltration and skimmed milk flocculation (SMF) methods using Armored RNA as a test virus, which is also used as a control by some other studies. Prefiltration with 0.45 &#181;m and 0.2 &#181;m membrane disc filters were applied to eliminate solid particles before ultrafiltration to prevent the clogging of ultrafiltration devices. Test samples, processed with the sequential ultrafiltration method, were centrifuged at two different speeds. An increased speed resulted in lower recovery and positivity rates of Armored RNA.&#160;On the other hand, SMF resulted in relatively consistent recovery and positivity rates of Armored RNA. Additional tests conducted with environmental water samples demonstrated the utility of SMF to concentrate other microbial fractions. The partitioning of viruses into solid particles might have an impact on the overall recovery rates, considering the prefiltration step applied before the ultrafiltration of wastewater samples. SMF with prefiltration performed better when applied to environmental water samples&#160;due to lower solid concentrations in the samples and thus lower partitioning rates to solids. In the present study, the idea of using a sequential ultrafiltration method arose from the necessity to decrease the final volume of the viral concentrates during the COVID-19 pandemic, when the supply of the commonly used ultrafiltration devices was limited, and there was a need for the development of alternative viral concentration methods.

Virus concentration from environmental water and wastewater samples is a challenging task, carried out primarily for the identification and quantification of viruses. While several virus concentration methods have been developed and tested, we demonstrate here the effectiveness of ultrafiltration and skimmed milk flocculation for RNA viruses with different sample types.

Water and wastewater-based epidemiology have emerged as alternative methods to monitor and predict the course of outbreaks in communities.&#160;The ...

Visualization of SARS-CoV-2 using Immuno RNA-Fluorescence In Situ Hybridization

This manuscript provides a protocol for in situ hybridization chain reaction (HCR) coupled with immunofluorescence to visualize severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in cell line&#160;and three-dimensional (3D) cultures of human airway epithelium. The method allows highly specific and sensitive visualization of viral RNA by relying on HCR initiated by probe localization. Split-initiator probes help amplify the signal by fluorescently labeled amplifiers, resulting in negligible background fluorescence in confocal microscopy. Labeling amplifiers with different fluorescent dyes facilitates the simultaneous recognition of various targets. This, in turn, allows the mapping of the infection in tissues to better understand viral pathogenesis and replication at the single-cell level. Coupling this method with immunofluorescence may facilitate better understanding of host-virus interactions, including alternation of the host epigenome and immune response pathways. Owing to sensitive and specific HCR technology, this protocol can also be used as a diagnostic tool. It is also important to remember that the technique may be modified easily to enable detection of any RNA, including non-coding RNAs and RNA viruses that may emerge in the future.

Here, we describe a simple method that combines RNA fluorescence in situ&#160;hybridization (RNA-FISH) with immunofluorescence to visualize severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA. This protocol may increase understanding of the molecular characteristics of SARS-CoV-2 RNA-host interactions at a single-cell level.

This manuscript provides a protocol for in situ hybridization chain reaction (HCR) coupled with immunofluorescence to visualize severe acute respiratory ...

Immunology and Infection

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized by a high rate of transmission and low mortality, the COVID-19 pandemic necessitated accurate and efficient diagnostic testing, particularly in closed populations such as residential universities. Initial availability of nucleic acid testing, like nasopharyngeal swabs, was limited due to supply chain pressure which also delayed reporting of test results. Saliva-based reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) testing has shown to be comparable in sensitivity and specificity to other testing methods, and saliva collection is less physically invasive to participants. Consequently, we developed a multiplex RT-qPCR diagnostic assay for population surveillance of Clemson University and the surrounding community. The assay utilized open-source liquid handling robots and thermocyclers instead of complex clinical automation systems to optimize workflow and system flexibility. Automation of saliva-based RT-qPCR enables rapid and accurate detection of a wide range of viral RNA concentrations for both large- and small-scale testing demands. The average turnaround for the automated system was &#60; 9 h for 95% of samples and &#60; 24 h for 99% of samples. The cost for a single test was $2.80 when all reagents were purchased in bulk quantities.

The protocol describes a SARS-CoV-2 diagnostic method that utilizes open-source automation to perform RT-qPCR molecular testing of saliva samples. This scalable approach can be applied to clinical public health surveillance as well as to increase the capacity of smaller university laboratories.

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized by ...

Two-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification

Diagnosis of the ongoing SARS-CoV-2 pandemic is a priority for all countries across the globe. Currently, reverse transcription quantitative PCR (RT-qPCR) is the gold standard for SARS-CoV-2 diagnosis as no permanent solution is available. However effective this technique may be, research has emerged showing its limitations in detection and diagnosis especially when it comes to low abundant targets. In contrast, droplet digital PCR (ddPCR), a recent emerging technology with superior advantages over qPCR, has been shown to overcome the challenges of RT-qPCR in diagnosis of SARS-CoV-2 from low abundant target samples. Prospectively, in this article, the capabilities of RT-ddPCR are further expanded by showing steps on how to develop simplex, duplex, triplex probe mix, and quadruplex assays using a two-color detection system. Using primers and probes targeting specific sites of the SARS-CoV-2 genome (N, ORF1ab, RPP30, and RBD2), the development of these assays is shown to be possible. Additionally, step by step detailed protocols, notes, and suggestions on how to improve the assays workflow and analyze data are provided. Adapting this workflow in future works will ensure that the maximum number of targets can be sensitively detected in a small sample significantly improving on cost and sample throughput.

This work summarizes steps on developing different assays for SARS-CoV-2 detection using a two color ddPCR system. The steps are elaborate and notes have been included on how to improve the assays and experiment performance. These assays may be used for multiple SARS-CoV-2 RT-ddPCR applications.

Diagnosis of the ongoing SARS-CoV-2 pandemic is a priority for all countries across the globe. Currently, reverse transcription quantitative PCR (RT-qPCR) ...

Biology

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs

To control community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the 2020 global pandemic, most countries implemented strategies based on direct human testing, face covering, and surface disinfection. Under the assumption that the main route of transmission includes aerosols and respiratory droplets, efforts to detect SARS-CoV-2 in fomites have focused on locations suspected of high prevalence (e.g., hospital wards, cruise ships, and mass transportation systems). To investigate the presence of SARS-CoV-2 on surfaces in the urban environment that are rarely cleaned and&#160;seldomly disinfected, 350 citizens were enlisted from the greater San Diego County. In total, these citizen scientists collected 4,080 samples. An online platform was developed to monitor sampling kit delivery and pickup, as well as to collect sample data. The sampling kits were mostly built from supplies available in pandemic-stressed stores. Samples were processed using reagents that were easy to access despite the recurrent supply shortage. The methods used were highly sensitive and resistant to inhibitors that are commonly present in environmental samples. The proposed experimental design and processing methods were successful at engaging numerous citizen scientists who effectively gathered samples from diverse surface areas. The workflow and methods described here are relevant to survey the urban environment for other viruses, which are of public health concern and pose a threat for&#160;future pandemics.

A citizen science project was designed to recruit San Diego residents to collect environmental samples for SARS-CoV-2. A multilingual web-based platform was created for data submission using a user-friendly mobile device interface. A laboratory information management system facilitated the collection of thousands of geographically diverse samples with real-time outcome tracking.

To control community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the 2020 global pandemic, most countries ...

RNA Analysis of Environmental Samples Using RT-PCR

Source: Laboratories of Dr. Ian Pepper and Dr. Charles Gerba - The University of Arizona 
Demonstrating Author: Bradley Schmitz
Reverse transcription-polymerase chain reaction (RT-PCR) involves the same process as conventional PCR &#8212; cycling temperature to amplify nucleic acids. However, while conventional PCR only amplifies deoxyribonucleic acids (DNA), RT-PCR enables the amplification of ribonucleic acids (RNA) through the formation of complementary DNA (cDNA). This enables RNA-based organisms found within the environment to be analyzed utilizing methods and technologies that are designed for DNA.
Many viruses found in the environment use RNA as their genetic material. Several RNA-based viral pathogens, such as Norovirus, and indicator organisms, such as pepper mild mottle virus (PMMoV), do not have culture-based detection methods for quantification. In order to detect for the presence of these RNA viruses in environmental samples from soil, water, agriculture, etc., molecular assays rely on RT-PCR to convert RNA into DNA. Without RT-PCR, microbiologists would not be able to assay and research numerous RNA-based viruses that pose risks to human and environmental health.
RT-PCR can also be employed as a tool to measure microbial activity in the environment. Messenger RNA (mRNA) is the single-stranded template for protein translation, and measuring the levels of different mRNAs indicates which genes from which microbes are being expressed within the environment. Analyzing gene expression gives clues to what biological pathways are used by organisms to survive in different environmental conditions. In some cases, gene expression can be utilized to determine which organisms may survive best in harsh conditions and have capabilities for bioremediation of contaminated soil or water.

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

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