Molecular characterization of human Sapovirus in untreated sewage in Italy by amplicon-based Sanger and next-generation sequencing

Mancini, Pamela; Ferraro, Giusy Bonanno; Iaconelli, Marcello; Suffredini, Elisabetta; Valdazo-González, Begoña; Libera, S. Della; Divizia, M; Rosa, Giuseppina La

doi:10.1111/jam.14129

Cited by 26 publications

(22 citation statements)

References 40 publications

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“…Wastewater is a dynamic system that can reflect the circulation of microorganisms in the population. Previous studies have evaluated the presence in wastewater of several viruses [41][42][43][44][45] . Processes to monitor SARS-CoV-2 in wastewater were first developed in the Netherlands 35 , followed by the USA 46 , France 39 , Australia 36 , Italy 47 and Spain 37,48 . In the Netherlands, no viral RNA was detected 3 weeks before the first case was reported, but genetic material started to appear over time, as the number of cases of COVID-19 increased 35 .…”

Section: Introductionmentioning

confidence: 99%

Highly predictive regression model of active cases of COVID-19 in a population by screening wastewater viral load

Vallejo¹,

Rumbo‐Feal²,

Conde‐Pérez³

et al. 2020

Preprint

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The quantification of the SARS-CoV-2 load in wastewater has emerged as a useful method to monitor COVID-19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruna (NW Spain), where wastewater from the treatment plant of Bens was analyzed to track the dynamics of the epidemic in a population of 369,098 inhabitants. We developed statistical regression models that allowed us to estimate the number of infected people from the viral load detected in the wastewater with a reliability close to 90%. This is the first wastewater-based epidemiological model that could potentially be adapted to track the evolution of the COVID-19 epidemic anywhere in the world, monitoring both symptomatic and asymptomatic individuals. It can help to understand with a high degree of reliability the true magnitude of the epidemic in a place at any given time and can be used as an effective early warning tool for predicting outbreaks.

show abstract

Section: Introductionmentioning

confidence: 99%

Highly predictive regression model of active cases of COVID-19 in a population by screening wastewater viral load

Vallejo¹,

Rumbo‐Feal²,

Conde‐Pérez³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Highly predictive regression model of active cases of COVID-19 in a population by screening wastewater viral load

Vallejo

Rumbo‐Feal

Conde

et al. 2020

Preprint

View full text Add to dashboard Cite

The quantification of the SARS-CoV-2 load in wastewater has emerged as a useful method to monitor COVID-19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW Spain), where wastewater from the treatment plant of Bens was analyzed to track the epidemic’s dynamic in a population of 369,098 inhabitants. We developed statistical regression models that allowed us to estimate the number of infected people from the viral load detected in the wastewater with a reliability close to 90%. This is the first wastewater-based epidemiological model that could potentially be adapted to track the evolution of the COVID-19 epidemic anywhere in the world, monitoring both symptomatic and asymptomatic individuals. It can help to understand with a high degree of reliability the true magnitude of the epidemic in a place at any given time and can be used as an effective early warning tool for predicting outbreaks.

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“…cDNA sequence of KLF4 (NM_004235) was synthesized and subcloned into lentivirus vector pL6.3-CMV-GFPa1-IRES-MCS (Novobio) for lentivirus production. The KLF4 recombinant lentivirus vector, pL6.3-CMV-GFPa1-IRES-KLF4, was confirmed by Sanger sequencing (24).…”

Section: Methodsmentioning

confidence: 99%

KLF4 overexpression decreases the viability, invasion and migration of papillary thyroid cancer cells

Wang

Chen

et al. 2019

Exp Ther Med

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Kruppel-like factor 4 (KLF4) has been implicated in a number of different types of cancer; however, the role of KLF4 in papillary thyroid cancer remains elusive. The present study aimed to investigate the role of KLF4 in papillary thyroid cancer and its potential underlying molecular mechanisms. The expression of KLF4 in thyroid tumor tissue and adjacent non-cancerous tissues were detected via immunohistochemistry and western blotting. The papillary thyroid cancer cell line, KTC1, was transfected with viruses carrying KLF4 overexpression vectors. The relative expression of KLF4, E-cadherin, N-cadherin, Vimentin, matrix metalloproteinase (MMP)2, MMP9 and collagen was detected via quantitative-PCR. The viability of KTC1 cells was detected using a cell counting kit-8 assay at 24, 48 and 72 h. Cell invasion was examined via a transwell invasion assay. Cell migration was examined via a scratch migration assay at 0 and 24 h. Compared with adjacent non-cancerous tissues, the expression of KLF4 was significantly lower in thyroid tumor tissues. The expression of KLF4 in KTC1 cells were significantly increased compared with the blank or negative control groups. The expression of N-cadherin, MMP2, MMP9 and collagen was significantly decreased in the KLF4 overexpression group. The viability of KTC1 cells was markedly decreased in KLF4 overexpression group at 24, 48 and 72 h when compared with the blank or negative control groups. The invasion of KTC1 cells in the KLF4 overexpression group was markedly decreased. Compared with the negative control group, the KTC1 cell migration in the KLF4 overexpression group was markedly decreased at 24 h. The expression of KLF4 was also significantly lower in thyroid tumor tissues. The cell viability, tumor invasion and migration ability and expression levels of N-cadherin, MMP2, MMP9 and collagen in papillary thyroid cancer cells were markedly decreased with KLF4 overexpression.

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Molecular characterization of human Sapovirus in untreated sewage in Italy by amplicon-based Sanger and next-generation sequencing

Cited by 26 publications

References 40 publications

Highly predictive regression model of active cases of COVID-19 in a population by screening wastewater viral load

Highly predictive regression model of active cases of COVID-19 in a population by screening wastewater viral load

Highly predictive regression model of active cases of COVID-19 in a population by screening wastewater viral load

KLF4 overexpression decreases the viability, invasion and migration of papillary thyroid cancer cells

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