VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples

Gafurov, Askar; Baláž, Andrej; Amman, Fabian; Boršová, Kristína; Čabanová, Viktória; Klempa, Boris; Bergthaler, Andréas; Vinař, Tomáš; Brejová, Broňa

doi:10.1186/s12859-022-05100-3

Cited by 9 publications

(8 citation statements)

References 40 publications

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“…This can be done by amplifying the gene of the immunodominant part of the S protein using PCR and analyzing it with tools like S‐Protein‐Typer 120 . Additionally, VirPool can estimate the proportion of SARS‐CoV‐2 variants in wastewater samples by analyzing nanopore sequencing data using probabilistic models 133 …”

Section: Application Of Nanopore Sequencing Technology During the Cov...mentioning

confidence: 99%

Nanopore sequencing technology and its applications

Zheng

Zhou

Ding

et al. 2023

MedComm

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Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third‐generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID‐19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus‐2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID‐19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID‐19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

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Section: Application Of Nanopore Sequencing Technology During the Cov...mentioning

confidence: 99%

Nanopore sequencing technology and its applications

Zheng

Zhou

Ding

et al. 2023

MedComm

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show abstract

“…Most importantly, we only selected two exemplary implementations of the mutationand sequencebased approaches MAMUSS and VLQ-nf, respectively, out of an increasing number of scripts, tools, and pipelines becoming available for computational SARS-CoV-2 lineage estimation from wastewater sequencing (Table 1) (Karthikeyan et al, 2022;Pechlivanis et al, 2022;Valieris et al, 2022;Ellmen et al, 2021;Amman et al, 2022;Barker et al, 2021;Schumann et al, 2022;Gregory et al, 2021;Jahn et al, 2022;Gafurov et al, 2022;Posada-Céspedes et al, 2021;Baaijens et al, 2022;Korobeynikov, 2022;Kayikcioglu et al, 2023). Thus, our benchmark results also reflect and are limited by the individual characteristics of these two implementations.…”

Section: Potential Implicationsmentioning

confidence: 99%

“…In addition, these fragments come from the excretions of many infected individuals, making it challenging, if not impossible, to reconstruct individual genomes using bioinformatic approaches like the ones developed for clinical samples of individual patients. In need of computational approaches to analyze mixed wastewater samples, several groups developed similar tools for quality control, sequencing data analysis, and SARS-CoV-2 lineage abundance estimation (Karthikeyan et al, 2022;Pechlivanis et al, 2022;Valieris et al, 2022;Ellmen et al, 2021;Amman et al, 2022;Barker et al, 2021;Schumann et al, 2022;Gregory et al, 2021;Jahn et al, 2022;Gafurov et al, 2022;Posada-Céspedes et al, 2021;Baaijens et al, 2022;Korobeynikov, 2022;Kayikcioglu et al, 2023), see Table 1.…”

Section: Introductionmentioning

confidence: 99%

“…As a different methodological approach to reconstruct a reference, the full genome sequence information can be used to automatically select appropriate features (e.g., signature mutations, kmers) and to use them to evaluate the proportions of SARS-CoV-2 variants in wastewater samples instead of a pre-selected set of marker mutations (sequence-based) (Baaijens et al, 2022;Gafurov et al, 2022;Posada-Céspedes et al, 2021) Table 1. Again, information derived from sequencing of clinical samples and their lineage annotation are used to generate a representative reference data set that can be then searched via established (pseudo)-alignment methods such as Kallisto (Bray et al, 2016) as suggested by Baaijens, Zulli, and Ott et al in their VQL tool (Baaijens et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Impact of reference design on estimating SARS-CoV-2 lineage abundances from wastewater sequencing data

Aßmann

Agrawal

Orschler

et al. 2023

Preprint

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Sequencing of SARS-CoV-2 RNA from wastewater samples has emerged as a valuable tool for detecting the presence and relative abundances of SARS-CoV-2 variants in a community. By analyzing the viral genetic material present in wastewater, public health officials can gain early insights into the spread of the virus and inform timely intervention measures. The construction of reference datasets from known SARS-CoV-2 lineages and their mutation profiles has become state-of-the-art for assigning viral lineages and their relative abundances from wastewater sequencing data. However, the selection of reference sequences or mutations directly affects the predictive power. Here, we show the impact of a mutation- and sequence-based reference reconstruction for SARS-CoV-2 abundance estimation. We benchmark three data sets: 1) synthetic 'spike-in' mixtures, 2) German samples from early 2021, mainly comprising Alpha, and 3) samples obtained from wastewater at an international airport in Germany from the end of 2021, including first signals of Omicron. The two approaches differ in sub-lineage detection, with the marker-mutation-based method, in particular, being challenged by the increasing number of mutations and lineages. However, the estimations of both approaches depend on selecting representative references and optimized parameter settings. By performing parameter escalation experiments, we demonstrate the effects of reference size and alternative allele frequency cutoffs for abundance estimation. We show how different parameter settings can lead to different results for our test data sets, and illustrate the effects of virus lineage composition of wastewater samples and references. Here, we compare a mutation- and sequence-based reference construction and assignment for SARS-CoV-2 abundance estimation from wastewater samples. Our study highlights current computational challenges, focusing on the general reference design, which significantly and directly impacts abundance allocations. We illustrate advantages and disadvantages that may be relevant for further developments in the wastewater community and in the context of higher standardization.

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“…A multitude of studies have confirmed that SARS-CoV-2 can be detected in wastewater samples [5] and that we can estimate COVID-19 case numbers from such samples [33, 40, 41, 60]. Moreover, we can estimate the relative abundances of different SARS-CoV-2 lineages (and therefore different variants) from wastewater samples using amplicon-based sequencing [4, 15, 28, 30, 47, 48, 63], further emphasizing the applicability of amplicon-based sequencing. The key step in performing amplicon-based sequencing is designing a set of primers such that the genetic material of interest can be amplified [14].…”

Section: Introductionmentioning

confidence: 99%

AmpliDiff: An Optimized Amplicon Sequencing Approach to Estimating Lineage Abundances in Viral Metagenomes

van Bemmelen,

Smyth,

Baaijens

2023

Preprint

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Metagenomic profiling algorithms commonly rely on genomic differences between lineages, strains or species to infer the relative abundances of sequences present in a sample. This observation plays an important role in the analysis of diverse microbial communities, where targeted sequencing of 16S and 18S rRNA, both well-known hypervariable genomic regions, have led to insights in microbial diversity and the discovery of novel organisms. However, the variable nature of discriminatory regions can also act as a double-edged sword, as the sought after variability can make it difficult to design primers for their amplification through PCR. Moreover, the most variable regions are not necessarily the most informative regions for the purpose of differentiation; one should focus on regions which maximize the number of lineages that can be distinguished. Here we present AmpliDiff, a computational tool that simultaneously finds such highly discriminatory genomic regions, as well as primers allowing for the amplification of these regions. We show that regions and primers found by AmpliDiff can be used to accurately estimate relative abundances of SARS-CoV-2 lineages, for example in wastewater sequencing data. We obtain mean absolute prediction errors that are comparable with using whole genome information to estimate relative abundances. Furthermore, our results show that AmpliDiff is robust against incomplete input data, and that primers designed by AmpliDiff continue to bind to genomes originating from months after the primers were selected. With AmpliDiff we provide an effective and efficient alternative to whole genome sequencing for estimating lineage abundances in viral metagenomes.

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VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples

Cited by 9 publications

References 40 publications

Nanopore sequencing technology and its applications

Nanopore sequencing technology and its applications

Impact of reference design on estimating SARS-CoV-2 lineage abundances from wastewater sequencing data

AmpliDiff: An Optimized Amplicon Sequencing Approach to Estimating Lineage Abundances in Viral Metagenomes

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