WO2022171313A1

WO2022171313A1 - Detection and mutational analysis of an rna virus in an environmental sample

Info

Publication number: WO2022171313A1
Application number: PCT/EP2021/057316
Authority: WO
Inventors: Andreas Scorilas; Margaritis AVGERIS; Nikolaos THOMAIDIS; Nikolaos VOULGARIS; Panagiotis ADAMOPOULOS
Original assignee: National And Kapodistrian University Of Athens
Priority date: 2021-02-11
Filing date: 2021-03-22
Publication date: 2022-08-18
Also published as: EP4291684A1; GR1010565B; GR20210100091A

Abstract

A method for the detection and the mutational analytics of an RNA virus in an environmental sample, which involves extraction of the RNA from the sample, reverse transcription of the extracted RNA with random oligonucleotides and nested PCR.

Description

DETECTION AND MUTATIONAL ANALYSIS OF AN RNA VIRUS IN AN ENVIRONMENTAL SAMPLE

TECHNICAL FIELD OF THE INVENTION

The present invention is related to the detection and the mutational analysis of a virus and more specifically of an RNA virus, in an environmental sample.

BACKGROUND OF THE INVENTION

RNA viruses have emerged as one of the most common class of pathogens causing serious disease. This can be attributed to the fact that they exhibit impressive capabilities to adapt to a variety of environments and deal with the challenges they encounter [Moratorio, G., et al. , Attenuation of RNA viruses by redirecting their evolution in sequence space. Nat Microbiol, 2017. 2: p. 17088] This extraordinary ability to cope with the immune system and defense mechanisms of the host cell as well as their durability in antiviral drugs, mainly arises from their exceptionally high mutation rates that are caused by the absence of proofreading mechanisms of their RNA-dependent polymerase, thus leading to error correction skipping and an increased number of genomic mutations [Simon-Loriere, E. and E.C. Holmes, Why do RNA viruses recombine? Nat Rev Microbiol, 2011. 9(8): p. 617-26] Consequently, the control of diseases caused by RNA viruses has always been a main challenge in the field of medicine, because their high mutational and adaptive rates can make them resistant to new vaccines and antiviral drugs. Examples of RNA viruses include the viruses that cause common cold, influenza, SARS, MERS, Dengue Virus, hepatitis C, hepatitis E, West Nile fever, Ebola, rabies, polio, measles as well as the recently emerged SARS-CoV-2.

Coronaviruses constitute a family of enveloped positive-strand RNA viruses, which are characterized by a single-stranded, positive-sense RNA genome of 26-32 kilobases (kb) [Su, S., et al., Epidemiology, Genetic Recombination, and Pathogenesis of Coronaviruses. Trends Microbiol, 2016. 24(6): p. 490-502] A recently emerged coronavirus is SARS-CoV-2, which was the cause of a cluster of severe pneumonia cases of unknown origin, reported by the Chinese Health Authorities in late 2019. Sequencing-based analysis of lower respiratory tract samples identified a novel beta-coronovirus sharing >85% sequence similarity with a bat severe acute respiratory syndrome (SARS)-like coronavirus (CoV), provisionally indicated as 2019-nCoV, as the causative pathogen of the coronavirus disease-2019 (COVID-19) [Zhu, N., et al. , A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med, 2020. 382(8): p. 727-733] This seventh member of CoV family that cause disease in humans, was further characterized showing sequence homology of approximately 79% and 50% with the SARS-CoV of 2002 outbreak in China and the Middle East respiratory syndrome (MERS)-CoV of 2012 outbreak in the Middle East, respectively [Lu, R., et al., Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet, 2020. 395(10224): p. 565-574] This novel CoV was thereafter named SARS-CoV-2 [Coronaviridae Study Group of the International Committee on Taxonomy of, V., The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol, 2020. 5(4): p. 536-544], and was rapidly spread to most countries worldwide, leading the announcement of COVID-19 pandemic by World Health Organization (WHO) in 12 March 2020.

SARS-CoV-2 belongs to the genus beta-coronavirus, having a genome of 29,903 nt. Human-to-human spread of SARS-CoV-2 mainly occurs via either respiratory droplets generated by an infected person sneezing, coughing and talking or direct contact [Li, Q., et al., Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-lnfected Pneumonia. N Engl J Med, 2020. 382(13): p. 1199-1207] However, the detection of SARS-CoV-2 in faeces of patients [Wang, W., et al., Detection of SARS-CoV-2 in Different Types of Clinical Specimens. JAMA, 2020. 323(18): p. 1843-1844], as well as untreated wastewaters [Ahmed, W., et al., First confirmed detection of SARS-CoV-2 in untreated wastewater in Australia: A proof of concept for the wastewater surveillance of COVID-19 in the community. Sci Total Environ, 2020. 728: p. 138764], has raised the debate of faecal-oral transmission [Heller, L., C.R. Mota, and D.B. Greco, COVID-19 faecal-oral transmission: Are we asking the right questions? Sci Total Environ, 2020. 729: p. 138919]

Due to the lack of related immunity, vaccines and effective treatment, the identification and isolation of COVID-19 patients was immediately adopted worldwide and still remains the main approach for disease management. Although, the total recourses of healthcare systems are used almost exclusively to deal with the current diagnostic needs, only symptomatic and suspicious cases are being tested so far in most countries. In this regard, the minimal diagnostic capacity for population-wide screening and the high transmission rate of SARS-CoV-2 have resulted in an exponential increase of infected persons, hospital overcrowding and high COVID-19 case-fatality rate [Sharfstein, J.M., S.J. Becker, and M.M. Mello, Diagnostic Testing for the Novel Coronavirus. JAMA, 2020. 323(15): p. 1437-1438]

Besides the detection of an active infection, the availability of virus genomic sequences could significantly improve our understanding on the evolution and spread of RNA viruses, as SARS-CoV-2, support the identification of strains with selective advantage and provide a risk-stratification tool for the infectivity of these viruses from individual patients up to community/national scale. SARS-CoV-2 genomes cased from humans positive for COVID-19 are deposited in GISAID database (https://www.gisaid.org/) and analyzed by Nextstrain (https://nextstrain.org/sars-cov- 2). Mutations in spike (S) trimeric glycoprotein of the surface of the virions, which is utilized from SARS-CoV-2 to interact with the ACE2 receptor of the target cells [Hoffmann, M., et al. , SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor. Cell, 2020. 181(2): p. 271-280 e8], have been already documented to affect the infectiveness, spread and immune escape of SARS-CoV-2 [Korber, B., et al., Tracking Changes in SARS-CoV-2 Spike: Evidence that D614G Increases Infectivity of the COVID-19 Virus. Cell, 2020. 182(4): p. 812-827 e19. and Li, Q., et al., The Impact of Mutations in SARS-CoV-2 Spike on Viral Infectivity and Antigenicity. Cell, 2020. 182(5): p. 1284-1294 e9].

Epidemiology based on the analysis of environmental samples, such as wastewater-based epidemiology (WBE), has been successfully applied in numerous case studies worldwide, with the most important application so far being the estimation of drugs consumption [Gonzalez-Marino, I., et al., Spatio-temporal assessment of illicit drug use at large scale: evidence from 7 years of international wastewater monitoring. Addiction, 2020. 115(1): p. 109-120] Although WBE cannot replace clinical screening and diagnostics, still it represents a much cheaper and faster way for population-wide surveillance without selection bias. In this regard, WBE screening could capture for example asymptomatic carriers of viruses who are less likely to undergo testing and symptomatic patients avoiding testing due to stigmatization and social isolation, as well as to provide real-time and population-wide monitoring of genomic variations/strains of the virus of interest.

Despite the benefit of the analysis of environmental samples, such as wastewater, in terms of efficient virus monitoring in the population, numerous challenges have emerged, leading to serious limitations in the detection accuracy of RNA viruses, such as SARS-CoV-2 [Alygizakis, N., et al. , Analytical methodologies for the detection of SARS-CoV-2 in wastewater: Protocols and future perspectives. Trends Analyt Chem, 2020: p. 116125] First and foremost, the sample site features may have an immediate effect on virus detection. In detail, industrial effluences, changes in the pH at the site of the sample as well as rain runoffs can affect the quality of the sample, therefore having a tremendous impact in the detection efficiency of the virus. Additionally, the volume of the sample and the sampling method are two important factors in the detection of viruses in environmental samples. Although several protocols have been developed to augment the volume of the sample (for example, bag filtration and composite sampling) in order to increase the chance of detecting the virus, these samples are often difficult to handle in the laboratory [Larsen, D.A. and K.R. Wigginton, Tracking COVID-19 with wastewater. Nat Biotechnol, 2020. 38(10): p. 1151-1153]

Another major challenge regarding detection of RNA viruses in environmental samples, such as wastewater, is the reduced stability of the RNA of the virus, which is not observed in human samples. For example, the currently established SARS- CoV-2 detection and screening method in human individuals includes an RNA extraction step from a nasopharyngeal swab followed by one-step reverse transcription quantitative polymerase chain reaction (RT-qPCR) to detect the extracted viral RNA. This approach involves the use of virus-specific RT primers, resulting only in the cDNA synthesis of viral mRNA, which is then exploited as template for qPCR. However, due to the nature of environmental samples, the existing temperature and pH in the area of sampling can induce random degradation of the viral RNA, thus leading to serious limitations in terms of detection with specific one- step RT-qPCR.

Therefore, there is still a need for an improved method for the detection of an RNA virus in an environmental sample, which overcomes the disadvantages of the methods of the prior art.

SUMMARY OF THE INVENTION

The present invention provides a method for the detection of an RNA virus in an environmental sample, which involves extraction of the RNA from the sample, reverse transcription of the extracted RNA with random oligonucleotides to give the complementary DNA (cDNA) and employment of nested PCR.

The present invention further provides a method for the mutational analysis of an RNA virus in an environmental sample, wherein the method comprises extraction of the RNA from the sample, reverse transcription of the extracted RNA with random oligonucleotides to give the complementary DNA (cDNA), employment of nested PCR, and sequencing of the products of the nested PCR assays using massively parallel sequencing.

The present invention further provides a method for the detection of SARS- CoV-2 in an environmental sample which involves extraction of the RNA from the sample, reverse transcription of the extracted RNA with random oligonucleotides to give the complementary DNA (cDNA) and employment of nested PCR.

The present invention further provides a method for the mutational analysis of SARS-CoV-2 in an environmental sample, wherein the method comprises extraction of the RNA from the sample, reverse transcription of the extracted RNA with random oligonucleotides to give the complementary DNA (cDNA), employment of nested PCR, and sequencing of the products of the nested PCR assays using massively parallel sequencing.

The present invention further provides kits for the detection of the presence of SARS-CoV-2 or for the detection of certain mutations of SARS-CoV-2 in a sample by nested PCR.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 shows agarose-gel electrophoresis of PCR products from CDC/2019- nCoV_N1 -based assay and from assays of the present invention.

Figure 2 shows agarose-gel electrophoresis of PCR products from assays of the present invention.

Figure 3 shows standard curves of nested real-time PCR assays of the present invention.

Figure 4 shows standard curves of nested real-time PCR assays of the present invention.

Figure 5 shows agarose-gel electrophoresis of the PCR products of nested PCR assays of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The detection of an RNA virus in an environmental sample exhibits certain challenges, which are not present in a sample taken from a subject, for example from a human subject. Thus, the quality of the sample may be affected by environmental or other factors. Furthermore, the stability of the RNA of the virus in the environment is reduced, resulting in various decomposition products. Therefore, a method for the detection or mutational analysis of an RNA virus in an environmental sample must exhibit high specificity and sensitivity.

The present invention provides a method for the detection of an RNA virus in an environmental sample, wherein the method comprises the steps of a) extraction of the RNA from the sample, b) reverse transcription of the extracted RNA with random oligonucleotides to give the complementary DNA (cDNA), c) application of a first nested PCR assay which targets a first region of the RNA of the virus, d) detection of the product of the nested PCR assay.

An RNA virus is a virus that has RNA as its genetic material. Preferably, the RNA virus is selected from viruses that cause common cold, influenza, SARS, MERS, Dengue Virus, hepatitis C, hepatitis E, West Nile fever, Ebola, rabies, polio and SARS- CoV-2. More preferably, the RNA virus is SARS-CoV-2.

The term “environmental sample” refers to a sample obtained from a non- biological source, such as soil, sediment or water. In some embodiments, the environmental sample is a water sample is obtained from a natural setting or from an industrial, health-care or residential setting. Preferably, the environmental sample is a wastewater sample.

The extraction of RNA from the environmental sample may be carried out by using methods well known in the art, such as magnetic beads-based RNA extraction, or silica column-based RNA extraction or acid guanidinium thiocyanate-phenol- chloroform RNA extraction. When the environmental sample is a wastewater sample, the extraction of the RNA may be preceded, according to an embodiment of the invention, by a concentration of the sample which may be carried out by using methods well known in the art, such as ultrafiltration or polyethylene glycol (PEG) precipitation.

The extracted RNA is subjected to reverse transcription with random oligonucleotides. Random oligonucleotides are synthesized entirely randomly to give a numerous range of sequences that have the potential to anneal at many random regions on a RNA template and act as a primer to commence first strand cDNA synthesis. They are also commonly referred to as random primers. Preferably, the random oligonucleotides are hexamers.

The cDNA is subjected to a nested PCR assay. Nested PCR is a modification of PCR well known in the art, which involves two sets of primers used in two successive PCR reactions. The first set of primers (also called external primers), is used in an initial PCR reaction. Amplicons resulting from the first PCR reaction are then used as templates for a second set of primers (also called internal primers) and a second PCR reaction. Thus, a nested PCR assay involves the use of two pairs of primers and two PCR reactions. The product of the second PCR reaction is the product of the nested PCR assay.

The detection of the product of the nested PCR assay can be carried out qualitatively or quantitatively using methods well known in the art. When the detection is carried out qualitatively it may be carried out for example, by agarose gel electrophoresis. When the detection is carried out quantitatively, it may be carried out, for example, by using a fluorescent probe, such as a sequence specific probe.

The nested PCR assay is designed to target a region of the RNA of the virus. This means that the primers of the nested PCR assay are designed to amplify only cDNA which is complementary to a region of the RNA of the virus.

According to a preferred embodiment of the present invention, if the outcome of the first nested PCR assay is negative, i.e. if no cDNA complementary to the RNA of the virus is detected, the sample is subjected to a second nested PCR assay which targets a second region of the RNA of the virus. If no cDNA complementary to the RNA of the virus is detected after the second nested PCR assay, the sample is subjected to a third nested PCR assay which targets a third region of the RNA of the virus. If no cDNA complementary to the RNA of the virus is detected after the third nested PCR assay, the sample is subjected to a fourth nested PCR assay which targets a fourth region of the RNA of the virus. The first, second third and fourth regions of the RNA of the virus are different regions of the RNA of the virus, which means that there is no overlap between the regions.

The present invention further provides a method for the detection of a mutation of an RNA virus in an environmental sample, wherein the method comprises the steps of a) extraction of the RNA from the sample, b) reverse transcription of the extracted RNA with random oligonucleotides to give the complementary DNA (cDNA) c) application of a nested PCR assay, wherein the assay targets a region of the RNA of the virus bearing the mutation of interest, d) detection of the product of the PCR assay, e) sequencing of the product of the nested PCR assay using massively parallel sequencing.

Massively parallel sequencing is also called next-generation sequencing (NGS) or second-generation sequencing and involves high-throughput approaches to DNA sequencing. Usually, massively parallel sequencing involves the creation by PCR of DNA sequencing libraries, the sequencing by synthesis of the DNA and the simultaneous sequencing of segregated, amplified DNA templates in a massively parallel fashion without the requirement for a physical separation step. An example of massively parallel sequencing which may be used according to the present invention is the amplicon sequencing or targeted DNA-seq.

According to a preferred embodiment of the present invention, the RNA virus is SARS-CoV-2.

The present invention also provides genomic regions of SARS-CoV-2, which can be used as targets for the nested PCR assays. Namely, the present inventors have found that the regions of the RNA of SARS-CoV-2 consisting of any one of SEQ ID NO: 1 - 70 exhibit higher stability compared to other regions. This means that a region consisting of any one of SEQ ID NO: 1 - 70 is more likely to be present in an environmental sample comprising SARS-CoV-2 and is therefore a better target for a nested PCR assay compared to other regions of the RNA of the virus.

Thus, preferably, the nested PCR assay of the present invention, or any one nested PCR assay, if more than one assay is employed, targets a region of the RNA of SARS-CoV-2 consisting of any one of SEQ ID NO: 1 - 70. More preferably, the nested PCR assay of the present invention, or any one nested PCR assay, if more than one assay is employed, targets a region of the RNA of SARS-CoV-2 consisting of any one of SEQ ID NO: 1 - 36. Even more preferably, the nested PCR assay of the present invention, or any one nested PCR assay if more than one assay is employed, targets a region of the RNA of SARS-CoV-2 consisting of SEQ ID NO: 1 - 24. Most preferably, the nested PCR assay of the present invention, or any one nested PCR assay if more than one assay is employed, targets a region of the RNA of SARS- CoV-2 consisting of any one of SEQ ID NO: 2, 4, 8, 11 , 14, 15, 18, 19. When more than one nested PCR assay is employed, each assay targets a different region of the RNA of the virus.

The present invention further provides pairs of primers which can be used in the nested PCR assays for the detection of SARS-CoV-2 in an environmental sample. According to a preferred embodiment, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 71 and SEQ ID NO: 72 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 73 and SEQ ID NO: 74 respectively. When the detection of the products of the nested PCR is carried out quantitatively, the probe is a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 75.

According to another preferred embodiment, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 76 and SEQ ID NO: 77 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 78 and SEQ ID NO: 79 respectively. When the detection of the products of the nested PCR is carried out quantitatively, the probe is a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 80.

According to another preferred embodiment, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 81 and SEQ ID NO: 82 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 83 and SEQ ID NO: 84 respectively. When the detection of the products of the nested PCR is carried out quantitatively, the probe is a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 85.

According to another preferred embodiment, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 86 and SEQ ID NO: 87 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 88 and SEQ ID NO: 89 respectively. When the detection of the products of the nested PCR is carried out quantitatively, the probe is a FAM-MGB fluorescent probe consisting of SEQ ID NO: 90.

The present invention further provides a kit for the detection of the presence of SARS-CoV-2 in a sample, such as an environmental sample, by nested PCR, wherein the kit comprises a) four oligonucleotides consisting of SEQ ID NO: 71 , SEQ ID NO: 72, SEQ ID NO: 73, SEQ ID NO: 74 respectively and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 75, and/or b) four oligonucleotides consisting of SEQ ID NO: 76, SEQ ID NO: 77, SEQ ID NO: 78, SEQ ID NO: 79 respectively and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 80, and/or c) four oligonucleotides consisting of SEQ ID NO: 81 , SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 84 respectively and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 85, and/or d) four oligonucleotides consisting of SEQ ID NO: 86, SEQ ID NO: 87, SEQ ID NO: 88, SEQ ID NO: 89 respectively and optionally a FAM-MGB fluorescent probe consisting of SEQ ID NO: 90.

Preferably, the kit comprises at least two of a), b), c) and d), more preferably, the kit comprises at least three of a), b), c) and d) and even more preferably, the kit comprises a), b), c) and d).

The present invention further provides pairs of primers which can be used in the nested PCR assays for the detection of certain mutations of SARS-CoV-2 in an environmental sample according to the present invention.

According to a preferred embodiment, for the detection of the missense mutation D614G (23403A>G) in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 91 and SEQ ID NO: 92 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 93 and SEQ ID NO: 94 respectively.

According to another preferred embodiment, for the detection of the missense mutation Q57H (25563G>T) in ORF3a gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 95 and SEQ ID NO: 96 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 97 and SEQ ID NO: 98 respectively.

According to another preferred embodiment, for the detection of the missense mutation P323L (14408C>T) in ORF1ab/RdRP gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 99 and SEQ ID NO: 100 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 101 and SEQ ID NO: 102 respectively.

According to another preferred embodiment, for the detection of the missense mutations R203K (28881 G>A) and G204R (28883G>C) in N gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 103 and SEQ ID NO: 104 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 105 and SEQ ID NO: 106 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 107 and SEQ ID NO: 108 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 109 and SEQ ID NO: 110 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 111 and SEQ ID NO: 112 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 113 and SEQ ID NO: 114 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 115 and SEQ ID NO: 116 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 117 and SEQ ID NO: 118 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 119 and SEQ ID NO: 120 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 121 and SEQ ID NO: 122 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 123 and SEQ ID NO: 124 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 125 and SEQ ID NO: 126 respectively. According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 127 and SEQ ID NO: 128 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 129 and SEQ ID NO: 130 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 131 and SEQ ID NO: 132 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 133 and SEQ ID NO: 134 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 135 and SEQ ID NO: 136 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 137 and SEQ ID NO: 138 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 139 and SEQ ID NO: 140 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 141 and SEQ ID NO: 142 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 143 and SEQ ID NO: 144 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 145 and SEQ ID NO: 146 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 147 and SEQ ID NO: 148 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 149 and SEQ ID NO: 150 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 151 and SEQ ID NO: 152 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 153 and SEQ ID NO: 154 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 155 and SEQ ID NO: 156 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 157 and SEQ ID NO: 158 respectively.

According to another preferred embodiment, for the detection of a mutation in S gene of SARS-CoV-2, the forward and reverse primer of the first reaction (external set) of the nested PCR assay consist of SEQ ID NO: 159 and SEQ ID NO: 160 respectively, and the forward and reverse primer of the second reaction (internal set) of the nested PCR assay consist of SEQ ID NO: 161 and SEQ ID NO: 162 respectively.

The present invention further provides a kit for the detection of a mutation of SARS-CoV-2 in a sample, such as an environmental sample, by nested PCR, wherein the kit comprises four oligonucleotides consisting of SEQ ID NO: 91 , SEQ ID NO: 92, SEQ ID

NO: 93, SEQ ID NO: 94 respectively, or four oligonucleotides consisting of SEQ ID NO: 95, SEQ ID NO: 96, SEQ ID

NO: 97, SEQ ID NO: 98 respectively, or four oligonucleotides consisting of SEQ ID NO: 99, SEQ ID NO: 100, SEQ ID

NO: 101, SEQ ID NO: 102 respectively, or four oligonucleotides consisting of SEQ ID NO: 103, SEQ ID NO: 104, SEQ

ID NO: 105, SEQ ID NO: 106 respectively, or four oligonucleotides consisting of SEQ ID NO: 107, SEQ ID NO: 108, SEQ

ID NO: 109, SEQ ID NO: 110 respectively, or four oligonucleotides consisting of SEQ ID NO: 111 , SEQ ID NO: 112, SEQ

ID NO: 113, SEQ ID NO: 114 respectively, or four oligonucleotides consisting of SEQ ID NO: 115, SEQ ID NO: 116, SEQ ID NO: 117, SEQ ID NO: 118 respectively, or four oligonucleotides consisting of SEQ ID NO: 119, SEQ ID NO: 120, SEQ ID NO: 121, SEQ ID NO: 122 respectively, or four oligonucleotides consisting of SEQ ID NO: 123, SEQ ID NO: 124, SEQ

ID NO: 125, SEQ ID NO: 126 respectively, or four oligonucleotides consisting of SEQ ID NO: 127, SEQ ID NO: 128, SEQ ID NO: 129, SEQ ID NO: 130 respectively, or four oligonucleotides consisting of SEQ ID NO: 131, SEQ ID NO: 132, SEQ ID NO: 133, SEQ ID NO: 134 respectively, or four oligonucleotides consisting of SEQ ID NO: 135, SEQ ID NO: 136, SEQ ID NO: 137, SEQ ID NO: 138 respectively, or four oligonucleotides consisting of SEQ ID NO: 139, SEQ ID NO: 140, SEQ ID NO: 141, SEQ ID NO: 142 respectively, or four oligonucleotides consisting of SEQ ID NO: 143, SEQ ID NO: 144, SEQ

ID NO: 145, SEQ ID NO: 146 respectively, or four oligonucleotides consisting of SEQ ID NO: 147, SEQ ID NO: 148, SEQ ID NO: 149, SEQ ID NO: 150 respectively, or four oligonucleotides consisting of SEQ ID NO: 151, SEQ ID NO: 152, SEQ ID NO: 153, SEQ ID NO: 154 respectively, or four oligonucleotides consisting of SEQ ID NO: 155, SEQ ID NO: 156, SEQ ID NO: 157, SEQ ID NO: 158 respectively, or four oligonucleotides consisting of SEQ ID NO: 159, SEQ ID NO: 160, SEQ ID NO: 161, SEQ ID NO: 162 respectively. The present invention enables the detection of an RNA virus, such as SARS-

CoV-2, with high specificity and selectivity even when the virus is present in an environmental sample in very small concentrations. Furthermore, the present invention enables the mutational and genomic profiling of an RNA virus in an environmental sample, which represents an efficient and cost-effective approach towards the establishment of an early-warning system for the monitoring of the genomic epidemiology of an RNA virus at community/population level. EXAMPLES Example 1

SARS-CoV-2 RNA stability analysis

The in silico SARS-CoV-2 RNA stability analysis was carried out with the ScanFold algorithm [Andrews, R.J., J. Roche, and W.N. Moss, ScanFold: an approach for genome-wide discovery of local RNA structural elements-applications to Zika virus and HIV. PeerJ, 2018. 6: p. e6136], which can be used to deduce the RNA structural landscape of virus transcriptomes. In specific, Wuhan-Hu-1 reference genome (NC_045512.2) was analyzed with ScanFold-Scan, using a 300 nt window with a 150 nt nucleotide step size, resulting in 198 analyzed windows. Each window was analyzed using the RNAfold algorithm that is included in the ViennaRNA package. For each window the minimum free energy (MFE) DQ° structure and value was predicted using the Turner energy model at 18 °C. In order to characterize the MFE of each 300nt sequence of the virus, a DQ° z-score is calculated for each sequence. ScanFold uses each predicted MFE for the native sequence (MFEnative) and compares it with MFE values calculated for 100 shuffled version of the sequence with the same nucleotide composition (MFErandom), using an approach adapted from Clote et. Al [Clote, P., et al., Structural RNA has lower folding energy than random RNA of the same dinucleotide frequency. RNA, 2005. 11(5): p. 578-91] In addition, the obtained p-values correspond to the number of MFErandom values, which were more stable (more negative) than the MFEnative. Furthermore, analysis with ScanFold enables the characterization of the potential structural diversity of the native sequence, by calculating the ensemble diversity (ED) and the centroid structure. The centroid structure depicts the base pairs that were “most common” (i.e. , had the minimal base pair distance) between all the Boltzmann- ensemble conformations predicted for the native sequence. The ED then attempts to quantify the variety of different structures, which were present in the ensemble. In specific, higher ED numbers indicate multiple structures unique from the predicted MFE, while low ED numbers indicate the presence of a dominant MFE structure highly represented in the ensemble.

To increase the accuracy of SARS-Cov-2 stability analysis, additional algorithms were employed, including the VfoldCPX Server [Xu, X. and S.J. Chen, VfoldCPX Server: Predicting RNA-RNA Complex Structure and Stability. PLoS One, 2016. 11(9): p. e0163454]. As a result, parameters such as loop-loop kissing interactions and the use of physical loop entropy were taken into consideration for identifying the most stable regions of SARS-Cov-2. Extensive analysis with VfoldCPX led to a set of energetically stable structures, ranked by their stabilities, thus providing detailed insights about the most stable SARS-Cov-2 genomic regions.

The bioinformatic analysis with ScanFold and VfoldCPX server as well as the visualization of the results with IGV software provided an overview regarding the most highly-predicted stable regions of SARS-Cov-2, leading to the identification of the most promising 300nt-sequences with negative z-scores, which are predicted to possess low MFE native values, thus being more stable. Sequences with notable negative z-scores were distributed across the SARS-CoV-2 genome. Based on the visualization results, the more stable sequences with negative z-scores were aligned in various genes of SARS-CoV-2 genome.

Example 2

Detection of SARS-CoV-2 in wastewater.

Materials and methods

Wastewater sampling

The 24-hour composite influent wastewater samples were collected from the Wastewater Treatment Plant (WWTP) of Athens, which is designed to serve a population equivalent of 5,200,000. The WWTP of Athens is designed with primary sedimentation, activated sludge process with biological nitrogen and phosphorus removal and secondary sedimentation. The pH range (7.5-8.0) and the temperature range (17-20 °C) for the collected samples were provided by the WWTP of Athens. All the samples are flow-proportional. Influent wastewater samples were collected in pre-cleaned high-density polyethylene (HDPE) bottles, transported on ice to the laboratory and stored at 4°C. All the collected samples were analyzed immediately after the arrival at the laboratory. Sampling personnel followed the appropriate regulations and guidelines and wore face standard personal protective equipment (PPE).

Sample concentration and RNA extraction

The collected samples were concentrated immediately after arrival using Polyethylene glycol 8000 (PEG 8000; Promega Corporation, Madison, Wl, USA) precipitation. In particular, 50 ml_ of an influent wastewater were centrifuged at 4,750 g for 30 min at 4 °C to remove debris, bacteria and large particles. The supernatant was transferred in a clean centrifuge tube, containing 3.5 g PEG and 0.8 g NaCI, mixed at ambient temperature until completely dissolved, and centrifuged at 10,050 g for 2 h at 4°C. The most of the supernatant was discarded without disturb the viral pellet and the tube was centrifuged at 10,050 g for 5 min at 4 °C, and finally the viral pellet was reconstituted by 500 pl_ nuclease-free water.

RNA extraction was performed, by 200 mI_ concentrate using the Water DNA/RNA Magnetic Bead kit (IDEXX Laboratories Inc., Westbrook, Maine, USA) according to manufacturer’s instruction, immediately following concentration.

First-strand cDNA synthesis

Total RNA template from wastewater samples was reverse transcribed in a 20 mI reaction containing 5.0 mI RNA, 1.0 mI of 10mM dNTPs mix (Jena Bioscience GmbH, Jena, Germany), 100 U Superscript III reverse transcriptase (Invitrogen, Carlsbad, CA, USA), 50 U RNaseOUT recombinant ribonuclease inhibitor (Invitrogen) and 1.0 mI of 50 mM random hexamers (Invitrogen). The mixture of total RNA, dNTPs and random hexamers was incubated at 65°C for 5 min, while the reverse transcription took place at 25°C for 10 min followed by 50°C for 50 min. Enzyme inactivation was performed at 70°C for 15 min. Finally, the AMPLIRUN SARS-CoV-2 RNA control (Vircell S.L., Granada, Spain) was used as SARS-CoV-2 complete genome control.

Nested PCR

The Veriti 96 well fast thermal cycler (Applied Biosystems, Carlsbad, CA) was used for the nested PCR assays. The 25 mI of the reaction consisted of 5.0 mI cDNA template (1st PCR) or 2.0 mI PCR product (2nd PCR), 1.0 mI of 10mM dNTPs mix (Jena Bioscience GmbH), 500 nM of each forward/reverse primer and 1 U of Kapa Taq polymerase (Kapa Biosystems, Inc., Woburn, MA). The thermal protocol consisted of polymerase activation step at 95°C for 3 min, followed by 15 cycles (1st PCR) or 40 cycles (2nd PCR) of denaturation at 95°C for 30 sec, primer annealing at 60°C for 30 sec and extension at 72°C for 1 min, followed by a final extension step at 72°C for 5 min. After the completion of the 2nd reaction, 10 mI of PCR product were electrophoresed on 1.5% w/v agarose gel, visualized with ethidium bromide staining, and photographed under UV light. Nested real time PCR

The probe fluorescent-based real-time PCR assays were performed in 7500 Fast Real-Time PCR System (Applied Biosystems). The PCR product of the 1st conventional PCR - as described above - were used as template for the real-time PCR assay (2nd reaction). The 20 pi reaction consisted of 2.0 mI PCR product, 10 mI Kapa Probe Fast Universal 2X qPCR Master Mix (Kapa Biosystems), 500 nM of each forward/reverse primer and 125 nM of fluorescent probe. The thermal protocol included an initial polymerase activation step at 95°C for 3 min, followed by 40 cycles of denaturation at 95°C for 15 sec and finally the primer/probe annealing and extension step at 60°C for 1 min.

Results

Considering the demanding nature of wastewater samples, the first aim of the study was to improve the sensitivity of SARS-CoV-2 detection by PCR-based assays. Based on the results from the bioinformatics analysis regarding the SARS-CoV-2 RNA stability (Example 1), four different nested PCR/real-time PCR assays were designed on: 1. N gene - product: nucleocapsid phosphoprotein (N assay), 2. ORFlab gene - product: helicase (Helicase assay), 3. ORFlab gene - product: nsp3 (NSP3 assay) and 4. ORF3a gene - product: ORF3a protein (ORF3a assay). The primes and probes of these assays are shown in Table 1 below.

Table 1

FP: Forward primer, RP: Reverse primer, Pr: qPCR probe.

To investigate the potential of the nested PCR/real-time PCR assays to improve the sensitivity of SARS-CoV-2 detection, serial dilutions of SARS-CoV-2 complete genome RNA control, covering 9 order of magnitude (from 1000 to 2.5 RNA copies/reverse transcription reaction) were analyzed by: a. nested PCR/real-time PCR assays, and b. assay using the CDC proposed “2019-nCoV_N1” set of primers and probe (CDC/2019-nCoV_N1 -based assay) (https://www.cdc.gov/coronavirus/2019-ncov/lab/rt-pcr-panel-primer-probes.html).

Using the CDC/2019-nCoV_N1 -based assay, detection of SARS-CoV-2 RNA was achieved up to: 5 cDNA copies/PCR reaction (weak PCR product) (Figure 1A). The application of the nested PCR/real-time PCR assays resulted in the improvement of the detection performance up to 2 cDNA copies/PCR reaction for N (Figure 1 B), ORF3a (Figure 1C) and Helicase (Figure 2A) assays. The use of the NSP3 assay resulted in the detection of SARS-CoV-2 up to 5 cDNA copies/PCR reaction (Figure 2B). Similar results regarding the performance and the limit-of-detection (LOD) on SARS-CoV-2 RNA control were highlighted by the nested real-time PCR assays. Figure 3A shows the standard curves of the nested real-time PCR N assay. Figure 3B shows the standard curves of the nested real-time PCR ORF3a assay. Figure 4A shows the standard curves of the nested real-time PCR Helicase assay. Figure 4B shows the standard curves of the nested real-time PCR NSP3 assay.

SARS-CoV-2 detection in wastewater is improved by amplification of multiple targets The in house nested PCR/real-time PCR assays along with the CDC/2019- nCoV_N1 -based assay were applied to 30 wastewater samples (S1-S30) obtained from August (n=2 samples), September (n=16 samples) and October (n=12 samples) 2020. The CT values of the positive samples per assay are presented in Table 2, while the agarose gels are included in Figures 5A-D. Table 2. CT values of the in house nested real-time PCR assays and the CDC/2019- nCoV_N1 -based assay in the wastewater samples that there detected positive for SARS-CoV-2.

SARS-CoV-2 was detected, by at least one assay, in 17 samples (17/30; 56.7%), while 13 samples were negative (13/30; 43.3%). Of the 17 positive samples, CDC/2019-nCoV_N1 -based assay detected 5 samples (sensitivity: 29.4%). The in house nested real-time PCR assays resulted to the detection of SARS-CoV-2 in: a. N assay - 10 samples (sensitivity: 58.8%), b. NSP3 assay - 9 samples (sensitivity: 52.9%), c. Helicase assay - 7 samples (sensitivity: 41.2%) and d. ORF3a assay - 5 samples (sensitivity: 29.4%). As expected, the application of the in house nested real time PCR assays resulted to significantly lower CT values (Table 2) related to CDC/2019-nCoV_N1 -based assay, highlighting their improved analytical performance. The analysis of the samples with the nested PCR assays (Figure 3A, 3B, 4A, 4B) led to the same results for the vast majority of the samples. More precisely, the agreement of nested PCR/real-time PCR results was 100% for N and ORF3a assays. A discrepancy was observed for one sample (S20), which was found negative by NSP3 nested PCR assay, as well as 3 samples (S1, S8, and S15) showing a weak positive signal in Helicase nested PCR assay, compared to nested real-time PCR assay. In this regard, the overall agreement of nested PCR/real-time PCR assays was 96.7%.

Most importantly, in the majority of the positive samples (10/17; 58.8%) SARS- CoV-2 was detected by a single assay, while only one (1/17; 5.9%) and five (5/17; 29.4%) samples were indicated positive by four or three assays, respectively. In this regard, significantly improved detection specificity was achieved by the combination of: a. N and NSP3 assays - 14 positive samples (sensitivity: 82.4%), and b. N, NSP3 and Helicase assays - 16 positive samples (sensitivity: 94.1%). These results clearly highlight that the detection of SARS-CoV-2 in wastewater is not genomic region- independent, as different results obtained by the targeting of different regions of SARS-CoV-2 RNA genome, as well as the application of more than one assays resulted to significantly improved detection sensitivity. Example 3

Mutational analysis of SARS-CoV-2 in wastewater using targeted DNA-seq

Materials and methods

The wastewater sampling, sample concentration and RNA extraction, first-strand cDNA synthesis and nested PCR were carried out as described in Example 2.

Mutational analysis of SARS-CoV-2 in wastewater samples using next-generation sequencing

An in house developed targeted DNA-seq assay, using semi-conductor sequencing technology was performed to elucidate the existing variations/mutations of the virus in wastewater samples. Nested PCR assays were carried out as described in Example 2, targeting each virus mutation/variation, to amplify the target regions. The derived nested PCR amplicons were electrophoresed in agarose gels for the assessment of the results.

Next, the Ion Xpress Plus Fragment Library Kit (Ion Torrent, Thermo Fisher Scientific Inc.) was employed for the construction of the DNA-seq library, using 1 pg of purified PCR product mix as input. Adapter ligation, nick-repair and purification of the ligated DNA were carried out based on the manufacturer’s guidelines. The adapter-ligated library was quantified using the Ion Library TaqMan Quantitation Kit (Ion Torrent) in an ABI 7500 Fast Real-Time PCR System (Applied Biosystems).

The sequencing template was generated with emulsion PCR on an Ion OneTouch 2 System (Ion Torrent), using the Ion PGM Hi-Q View OT2 kit (Ion Torrent), strictly based on the instructions of the manufacturer. Next, the Ion OneTouch ES instrument (Ion Torrent) was used for the downstream template enrichment procedure. Ultimately, semi-conductor sequencing methodology was carried out in the Ion Torrent PGM system for the sequencing of the amplicons bearing the potential variations/mutations of the virus.

Results

In this study, five missense mutations were targeted, namely, a. D614G (23403A>G) - S gene, b. Q57H (25563G>T) - ORF3a gene, c. P323L (14408C>T) - ORF1ab/RdRP gene, d. R203K (28881 G>A) - N gene and e. G204R (28883G>C) - N gene. To perform targeted DNA-seq analysis, novel nested PCR assays, against the above-mentioned point mutations, were designed and applied in 5 wastewater samples obtained from September 2020 and 8 samples from October/November 2020. The primers of these assets are shown in Table 3 below. Table 3

FP: Forward primer, RP: Reverse primer

Thereafter, the PCR products were used to generate DNA-seq barcoded libraries corresponding to September and October/November 2020. The genomic variation profiling (list of existing SNVs or indels) of SARS-CoV-2 that was derived from the developed high-throughput sequencing approach is summarized in Tables 4 and 5 below. Table 4. Genomic variation profile (SNVs and indels) of SARS-CoV-2 in samples from September 2020, as obtained from targeted DNA-seq.

Table 5. Genomic variation profile (SNVs and indels) of SARS-CoV-2 in samples from

October/November 2020, as obtained from targeted DNA-seq.

The analysis highlighted that the G614 strain of SARS-CoV-2, originating from the D614G (23403A>G) point mutation in S gene, was exclusively detected, >99.9%, over the D614 strain in wastewater samples. This finding is in line with the genomic data of GISAID database, highlighting the presence of G164 strain in percentage >98% and -100% worldwide and in Europe, respectively. Similarly, the P323L (14408OT) substitution in ORF1ab/RdPR gene was also prevalent, -99.9%, in both time periods of sampling, also in agreement with the genomic epidemiology (-99% worldwide and in Europe). Moreover, the Q57H (25563G>T) mutation in ORF3a gene was observed in October/November samples in percentage -47%, which is in accordance with the growing trend observed worldwide in the last months (-43%; end of November 2020).

Beside the characterized D614G mutation, a previously unknown point mutation within S gene, H625R (23436A>G), was observed in frequency of 5.7% in September samples. More precisely, the 23436A>G missense substitution results to the change of Histidine-to-Arginine at position 625 of the spike protein. Unlike D614G mutation, that involves the substitution of amino acids with different polarity attributes, H625R mutation involves the substitution of two amino acid residues with positively charged polar side chains. Even though two similar amino acids are substituted, based on the in-silico protein structure analysis, the occurrence of H625R leads to subtle alterations in the spike protein folding. As a result, the H625R-mutant spike protein may exhibit differential biochemical properties, which should be further investigated, since they may have a severe impact on the functionality of the protein, making the virus more transmissible or infectious. Moreover, a novel point substitution, A54V (255530T) was detected in percentage -9% of September samples, resulting to the change of Alanine-to-Valine at position 54 of the ORF3a polypeptide. Both amino acids represent aliphatic, nonpolar neutral residues, and thus it is not expected to induce crucial alterations in the ORF3a functionality.

Focusing on N gene, a significant declining trend was observed for the missense point mutations 28881 G>A (R203K) and 28883G>C (G204R), as well as the synonymous substitution 28882G>A, from -90% in September to -70% in October/November samples. Our data agree with the declining trend of 28881 G>A, 28882G>A and 28883G>C substitutions worldwide (from 45%; end of September to 28%; end of November), although their absolute percentage in Greek samples remain significantly higher. Interestingly, a point substitution 28884G>T, which has been observed in -1% worldwide, was overrepresented in our datasets. More precisely, 28884G>T substitution was detected in -70% and 35% in September and October/November samples, respectively. More importantly, the analysis highlighted the significant correlation of 28884G>T with 28883G>C, resulting in a novel amino acid substitution from Glycine-to-Leucine in position 204 (G204L) of nucleocapsid protein, compared to the single 28883G>C (G204R) or 28884G>T (G204V) substitutions. Beside the detection of the four consecutive SNVs at the genomic positions 28881-28884, the obtained sequencing results revealed the existence of a simultaneous 4-nt deletion following position 28880 (28881_28884del) and a 4-nt insertion (28885_28886insACAT) at position 28885 (Table 2). These two simultaneous indels lead to the R203K and G204H missense mutations of nucleocapsid protein.

These findings clearly indicate that R203K co-exists with G204R, G204L or G204H variations. Although all these mutations are located on the linker region (LKR) of nucleocapsid phosphoprotein, which spans from position 175 aa until 254 aa, only R203K belongs to the LKR’s crucial Ser/Arg (SR)-rich motif that contains putative phosphorylation sites [Peng, Y., et al. , Structures of the SARS-CoV-2 nucleocapsid and their perspectives for drug design. EMBO J, 2020. 39(20): p. e105938]. Consequently, the absence of R203 residue, due to R203K mutation, is expected to have an immediate impact on the N protein folding and functionality, while any of the variations in 204 position of the protein (G204R, G204L or G204H) lead only to subtle modifications.

Finally, a significant growing trend from 7% in September to 27% in October/November samples was revealed for missense mutation S194L (28854C>T), in line with a similar trend observed worldwide (13% of September to 21% of November). Similar to R203K, S194L mutation is also located on the Ser/Arg (SR)- rich motif of the nucleocapsid protein and involves the substitution of the hydroxylic neutral Serine (S) with the aliphatic neutral Leucine (L). Since this region regulates the N protein oligomerization upon phosphorylation, the mutation-induced absence of the S194 could have a significant impact on the function of nucleocapsid, which also comes in accordance with the dramatic changes in the predicted protein structure and therefore merits further study.

Claims

1. A method for the detection of an RNA virus in an environmental sample, wherein the method comprises the steps of a) extraction of the RNA from the sample, b) reverse transcription of the extracted RNA with random oligonucleotides to give the complementary DNA (cDNA), c) application of a first nested PCR assay which targets a first region of the RNA of the virus, d) detection of the product of the nested PCR assay.

2. The method for the detection of an RNA virus in an environmental sample according to claim 1 , wherein if no cDNA complementary to the RNA of the virus is detected after the first nested PCR assay, the sample is subjected to a second nested PCR assay which targets a second region of the RNA of the virus, if no cDNA complementary to the RNA of the virus is detected after the second nested PCR assay, the sample is subjected to a third nested PCR assay which targets a third region of the RNA of the virus, if no cDNA complementary to the RNA of the virus is detected after the third nested PCR assay, the sample is subjected to a fourth nested PCR assay which targets a fourth region of the RNA of the virus, wherein there is no overlap between the first, second, third and fourth regions of the RNA of the virus.

3. The method for the detection of an RNA virus in an environmental sample according to claim 1 or 2, wherein the environmental sample is obtained from soil, sediment or water.

4. The method for the detection of an RNA virus in an environmental sample according to any one of the preceding claims, wherein the environmental sample is a wastewater sample.

5. The method for the detection of an RNA virus in an environmental sample according to any one of the preceding claims, wherein the random oligonucleotides are hexamers.

6. The method for the detection of an RNA virus in an environmental sample according to any one of the preceding claims, wherein the detection of the product of the nested PCR assay is qualitative or quantitative.

7. The method for the detection of an RNA virus in an environmental sample according to any one of the preceding claims, wherein the RNA virus is selected from a virus that causes common cold, influenza, SARS, MERS, Dengue Virus, hepatitis C, hepatitis E, West Nile fever, Ebola, rabies, polio or SARS-CoV-2.

8. The method for the detection of an RNA virus in an environmental sample according to any one of the preceding claims, wherein the RNA virus is SARS- CoV-2.

9. The method for the detection of an RNA virus in an environmental sample according to claim 8, wherein any one of the first, second, third or fourth region of the RNA of the virus consists of any one of SEQ ID NO: 1 - 70.

10. The method for the detection of an RNA virus in an environmental sample according to claim 9, wherein any one of the first, second, third or fourth region of the RNA of the virus consists of any one of SEQ ID NO: 1 - 36.

11. The method for the detection of an RNA virus in an environmental sample according to claim 10, wherein any one of the first, second, third or fourth region of the RNA of the virus consists of any one of SEQ ID NO: 1 - 24.

12. The method for the detection of an RNA virus in an environmental sample according to claim 11, wherein any one of the first, second, third or fourth region of the RNA of the virus consists of any one of SEQ ID NO: 2, 4, 8, 11, 14, 15, 18, 19.

13. The method for the detection of an RNA virus in an environmental sample according to any one of claims 8 to 12, wherein any one of the first, second, third or fourth nested PCR assay comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 71 and SEQ ID NO: 72 respectively, a forward and a reverse primer for a second PCR reaction consisting of SEQ ID NO: 73 and SEQ ID NO: 74 respectively, and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 75, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 76 and SEQ ID NO: 77 respectively, a forward and a reverse primer of a second PCR reaction consisting of SEQ ID NO: 78 and SEQ ID NO: 79 respectively, and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 80, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 81 and SEQ ID NO: 82 respectively, a forward and a reverse primer of a second PCR reaction consisting of SEQ ID NO: 83 and SEQ ID NO: 84 respectively, and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 85, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 86 and SEQ ID NO: 87 respectively, a forward and a reverse primer of a second PCR reaction consisting of SEQ ID NO: 88 and SEQ ID NO: 89 respectively, and optionally a FAM-MGB fluorescent probe consisting of SEQ ID NO: 90.

14. A method for the detection of a mutation of an RNA virus in an environmental sample, wherein the method comprises the steps of a) extraction of the RNA from the sample, b) reverse transcription of the extracted RNA with random oligonucleotides to give the complementary DNA c) application of a nested PCR assay, wherein the assay targets a region of the RNA of the virus bearing the mutation of interest, d) detection of the product of the PCR assay, e) sequencing of the product of the nested PCR assay using massively parallel sequencing.

15. The method for the detection of a mutation of an RNA virus in an environmental sample according to claim 14, wherein the environmental sample is obtained from soil, sediment or water.

16. The method for the detection of a mutation of an RNA virus in an environmental sample according to claim 14 of 15, wherein the environmental sample is a wastewater sample.

17. The method for the detection of a mutation of an RNA virus in an environmental sample according to any one of claims 14 or 16, wherein the random oligonucleotides are hexamers.

18. The method for the detection of a mutation of an RNA virus in an environmental sample according to any one of claims 14 to 17, wherein the detection of the product of the nested PCR assay is qualitative or quantitative.

19. The method for the detection of a mutation of an RNA virus in an environmental sample according to any one of claims 14 to 18, wherein the massively parallel sequencing is carried out by a targeted DNA-seq assay.

20. The method for the detection of a mutation of an RNA virus in an environmental sample according to any one of claims 14 to 19, wherein the RNA virus is selected from a virus that causes common cold, influenza, SARS, MERS, Dengue Virus, hepatitis C, hepatitis E, West Nile fever, Ebola, rabies, polio or SARS-CoV-2.

21. The method for the detection of a mutation of an RNA virus in an environmental sample according to claim 20, wherein the RNA virus is SARS- CoV-2.

22. The method for the detection of a mutation of an RNA virus in an environmental sample according to claim 21, wherein the nested PCR assay comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 91 and SEQ ID NO: 92 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 93 and SEQ ID NO: 94 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 95 and SEQ ID NO: 96 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 97 and SEQ ID NO:

98 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 99 and SEQ ID NO: 100 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 101 and SEQ ID NO: 102 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 103 and SEQ ID NO: 104 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 105 and SEQ ID NO: 106 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 107 and SEQ ID NO: 108 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 109 and SEQ ID NO: 110 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 111 and SEQ ID NO: 112 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 113 and SEQ ID NO: 114 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 115 and SEQ ID NO: 116 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 117 and SEQ ID NO: 118 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 119 and SEQ ID NO: 120 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 121 and SEQ ID NO: 122 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 123 and SEQ ID NO: 124 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 125 and SEQ ID NO: 126 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 127 and SEQ ID NO: 128 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 129 and SEQ ID NO: 130 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 131 and SEQ ID NO: 132 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 133 and SEQ ID NO: 134 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 135 and SEQ ID NO: 136 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 137 and SEQ ID NO: 138 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 139 and SEQ ID NO: 140 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 141 and SEQ ID NO: 142 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 143 and SEQ ID NO: 144 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 145 and SEQ ID NO: 146 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 147 and SEQ ID NO: 148 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 149 and SEQ ID NO: 150 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 151 and SEQ ID NO: 152 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 153 and SEQ ID NO: 154 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 155 and SEQ ID NO: 156 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 157 and SEQ ID NO: 158 respectively, or comprises a forward and a reverse primer of a first PCR reaction consisting of SEQ ID NO: 159 and SEQ ID NO: 160 respectively, and a forward and a reverse primer for the second reaction consisting of SEQ ID NO: 161 and SEQ ID NO: 162 respectively.

23. A kit for the detection of the presence of SARS-CoV-2 in a sample by nested PCR, wherein the kit comprises four oligonucleotides consisting of SEQ ID NO: 71, SEQ ID NO: 72, SEQ ID NO: 73, SEQ ID NO: 74 respectively and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 75, and/or four oligonucleotides consisting of SEQ ID NO: 76, SEQ ID NO: 77, SEQ ID NO: 78, SEQ ID NO: 79 respectively and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 80, and/or four oligonucleotides consisting of SEQ ID NO: 81, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 84 respectively and optionally a FAM-BHQ1 fluorescent probe consisting of SEQ ID NO: 85, and/or four oligonucleotides consisting of SEQ ID NO: 86, SEQ ID NO: 87, SEQ ID

NO: 88, SEQ ID NO: 89 respectively and optionally a FAM-MGB fluorescent probe consisting of SEQ ID NO: 90.

24. A kit for the detection of a mutation of SARS-CoV-2 in a sample by nested PCR, wherein the kit comprises four oligonucleotides consisting of SEQ ID NO: 91, SEQ ID NO: 92, SEQ ID NO: 93, SEQ ID NO: 94 respectively, or four oligonucleotides consisting of SEQ ID NO: 95, SEQ ID NO: 96, SEQ ID NO: 97, SEQ ID NO: 98 respectively, or four oligonucleotides consisting of SEQ ID NO: 99, SEQ ID NO: 100, SEQ ID

NO: 101, SEQ ID NO: 102 respectively, or four oligonucleotides consisting of SEQ ID NO: 103, SEQ ID NO: 104, SEQ ID NO: 105, SEQ ID NO: 106 respectively, or four oligonucleotides consisting of SEQ ID NO: 107, SEQ ID NO: 108, SEQ ID NO: 109, SEQ ID NO: 110 respectively, or four oligonucleotides consisting of SEQ ID NO: 111, SEQ ID NO: 112, SEQ ID NO: 113, SEQ ID NO: 114 respectively, or four oligonucleotides consisting of SEQ ID NO: 115, SEQ ID NO: 116, SEQ ID NO: 117, SEQ ID NO: 118 respectively, or four oligonucleotides consisting of SEQ ID NO: 119, SEQ ID NO: 120, SEQ

ID NO: 121, SEQ ID NO: 122 respectively, or four oligonucleotides consisting of SEQ ID NO: 123, SEQ ID NO: 124, SEQ ID NO: 125, SEQ ID NO: 126 respectively, or four oligonucleotides consisting of SEQ ID NO: 127, SEQ ID NO: 128, SEQ ID NO: 129, SEQ ID NO: 130 respectively, or four oligonucleotides consisting of SEQ ID NO: 131, SEQ ID NO: 132, SEQ ID NO: 133, SEQ ID NO: 134 respectively, or four oligonucleotides consisting of SEQ ID NO: 135, SEQ ID NO: 136, SEQ ID NO: 137, SEQ ID NO: 138 respectively, or four oligonucleotides consisting of SEQ ID NO: 139, SEQ ID NO: 140, SEQ ID NO: 141, SEQ ID NO: 142 respectively, or four oligonucleotides consisting of SEQ ID NO: 143, SEQ ID NO: 144, SEQ ID NO: 145, SEQ ID NO: 146 respectively, or four oligonucleotides consisting of SEQ ID NO: 147, SEQ ID NO: 148, SEQ ID NO: 149, SEQ ID NO: 150 respectively, or four oligonucleotides consisting of SEQ ID NO: 151, SEQ ID NO: 152, SEQ ID NO: 153, SEQ ID NO: 154 respectively, or four oligonucleotides consisting of SEQ ID NO: 155, SEQ ID NO: 156, SEQ ID NO: 157, SEQ ID NO: 158 respectively, or four oligonucleotides consisting of SEQ ID NO: 159, SEQ ID NO: 160, SEQ ID NO: 161, SEQ ID NO: 162 respectively.