Beyond linear regression: Modeling COVID-19 clinical cases with wastewater surveillance of SARS-CoV-2 for the city of Athens and Ohio University campus.

Wastewater-based surveillance has emerged as a detection tool for population-wide infectious diseases, including coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals shed the virus, which can be detected in wastewater using molecular techniques such as reverse transcription-digital polymerase chain reaction (RT-dPCR). This study examined the association between the number of clinical cases and the concentration of SARS-CoV-2 in wastewater beyond linear regression and for various normalizations of viral loads. Viral loads were measured in a total of 446 wastewater samples during the period from August 2021 to April 2022. These samples were collected from nine different locations, with 220 samples taken from four specific sites within the city of Athens and 226 samples from five sites within Ohio University. The correlation between COVID-19 cases and wastewater viral concentrations, which was estimated using the Pearson correlation coefficient, was statistically significant and ranged from 0.6 to 0.9. In addition, time-lagged cross correlation was applied to identify the lag time between clinical and wastewater data, estimated 4 to 7 days. While we also explored the effect on the correlation coefficients of various normalizations of viral loads accounting for procedural loss or amount of fecal material and of estimated lag times, these alternative specifications did not change our substantive conclusions. Additionally, several linear and non-linear regression models were applied to predict the COVID-19 cases given wastewater data as input. The non-linear approach was found to yield the highest R-squared and Pearson correlation and lowest Mean Absolute Error values between the predicted and actual number of COVID-19 cases for both aggregated OHIO Campus and city data. Our results provide support for previous studies on correlation and time lag and new evidence that non-linear models, approximated with artificial neural networks, should be implemented for WBS of contagious diseases.

Cuantificación de la expresión del gen amo-A en poblaciones bacterianas y archaeales presentes en muestras de suelos de un lote arrocero caracterizado por ambientes

El ciclo del nitrógeno representa uno de los procesos biogeoquímicos más importantes para los ecosistemas terrestres y acuáticos. Las comunidades microbianas desempeñan un papel crucial en los procesos de transformación del nitrógeno en el suelo, ya que participan en diversas etapas como la nitrificación, de gran importancia para la producción agrícola. Dentro de los marcadores moleculares más utilizados para evaluar la actividad de poblaciones microbianas oxidantes de amonio se han considerado ampliamente los genes que codifican enzimas claves como la subunidad A de la actividad amonio monooxigenasa (AMO). Sin embargo, no se comprende completamente si la expresión de esta enzima tiene relación directa con el rendimiento de los cultivos. En este contexto, se evaluó la expresión del gen amo-A de comunidades bacterianas y archaeales presentes en un lote arrocero previamente caracterizado por ambientes. Para cuantificar la abundancia de arqueas y bacterias oxidantes de amonio, (AOA y AOB, respectivamente) se emplearon las técnicas de PCR en tiempo real (RT-qPCR) y PCR digital (RT-dPCR). En este trabajo se encontró a través del análisis de datos metagenómicos que hubo una mayor presencia de AOB en las muestras de suelo rizosférico mientras que las AOA fueron predominantes en las muestras de suelo de soporte "bulk", sin embargo, no se detectó la expresión del gen amo-A asociada a la comunidad de bacterias en las muestras de suelo analizadas. Por otra parte, no se presentaron diferencias entre los transcritos del gen amo-A asociados a la comunidad de AOA de los ambientes caracterizados. Además, la expresión de transcritos no estuvo relacionada con alguna de las propiedades químicas evaluadas. Finalmente, las estrategias de cuantificación para RT-qPCR (plásmido y templete) resultaron ser homólogas y funcionales para identificar la expresión del gen amo-A de AOA, mientras que la técnica de RT-dPCR fue más precisa para el análisis de la comunidad de AOB y AOA.

The nitrogen cycle represents one the most important biogeochemical process for terrestrial and aquatic ecosystems. Microbial communities play a crucial role in the processes of transformation of soil nitrogen in the, since they participate in various stages such as nitrification, which is of great importance for agricultural production. Among the most used molecular markers to assess ammonium oxidizing microbial populations activity have been considered widely the genes encoding key enzymes such as ammonium monooxygenase (AMO) subunit A. However, it is not fully understood whether the expression of this enzyme is directly related to the crop yield. In this context, this research work evaluated the expression of the amo-A gene of bacterial and archaeal communities present in a rice field previously characterized by environments. Real-time PCR (RT-qPCR) and digital PCR (RT-dPCR) techniques were used to quantify the abundance of archaea and ammonium-oxidizing bacteria (AOA and AOB, respectively). In this work it was found that in the analysis of metagenomic data there was a greater presence of AOB in rhizospheric soil samples while AOA were predominant in bulk soil samples, however, the expression of the amo-A gene was not detected. associated with the community of bacteria in the soil samples analyzed. On the other hand, it was found that the transcripts of the amo-A gene of the AOA community did not present differences between the characterized environments. Furthermore, the expression of transcripts is not related to any of the chemical properties evaluated. Finally, the quantification strategies for RT-qPCR (plasmid and quenching) turned out to be homologous and functional to identify the expression of the AOA amo-A gene, while the RT-dPCR technique was more precise for the analysis of the community of AOB and AOA.

Correlation of SARS-CoV-2 RNA and nucleocapsid concentrations in samples used in INSTAND external quality assessment schemes.

OBJECTIVE: In routine clinical laboratories, severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection is determined by reverse-transcription PCR (RT-PCR). In the COVID pandemic, a wide range of antigen detection tests were also in high demand. We investigated the correlation between SARS-CoV-2 NCap antigen and N gene concentration by analyzing samples from several INSTAND external quality assessment (EQA) schemes starting in March 2021. The absolute N gene concentration was measured using reverse transcriptase digital PCR (RT-dPCR) as reference value. Moreover, the performance of five commercial ELISA tests using an EQA inactivated SARS-CoV-2 sample at different concentrations was assessed on the basis of these reference values. RESULTS: Quantitative ELISA and RT-dPCR results showed a good correlation between SARS-CoV-2 NCap antigen and RNA concentration, but this correlation varies among SARS-CoV-2 isolates. A direct correlation between SARS-CoV-2 NCap antigen concentration and genome concentration should not be generally assumed. CONCLUSION: Further correlation studies between SARS-CoV-2 RNA and NCap antigen concentrations are needed, particularly in clinical samples and for emerging SARS-CoV-2 variants, to support the monitoring and improvement of antigen testing.

Optimizing virus inactivation methods for molecular detection techniques: Implications for viral protein and RNA measurements.

To facilitate the development of effective viral detection techniques, a positive control material is required for validating their quantitative performance. Inactivated viruses serve as viable control materials, as they can be handled without the constraints of biohazard safety facilities. However, inactivation alters the structure of viral component molecules, necessitating the selection of inactivation methods that have minimal effects on the target molecules relevant to molecular detection techniques. Only a limited number of studies have investigated inactivation methods to produce viral control materials. Therefore, the aim of this study was to investigate various virus inactivation methods and evaluate their impact on molecular detection techniques, with a specific focus on viral proteins and RNA. We evaluated the effects of ultraviolet (UV) irradiation, heat, beta-propiolactone (BPL), hydrogen peroxide (H2O2), and perchloric acid (HClO4) inactivation methods to identify the most effective technique and its optimal conditions. Enzyme-linked immunosorbent assay (ELISA) and reverse transcription-digital polymerase chain reaction (RT-dPCR) were employed as model assays to assess the effects of these treatments on protein and RNA measurements. Among the evaluated methods, UV and heat treatments demonstrated minimal interference with ELISA, while heat treatment had the least impact on RT-dPCR measurements. Consequently, our findings revealed that heat inactivation holds the potential for producing inactivated viruses that can be effectively used in molecular detection techniques targeting both viral protein and RNA.

Digital PCR Applications in the SARS-CoV-2/COVID-19 Era: a Roadmap for Future Outbreaks.

The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global public health disaster. The current gold standard for the diagnosis of infected patients is real-time reverse transcription-quantitative PCR (RT-qPCR). As effective as this method may be, it is subject to false-negative and -positive results, affecting its precision, especially for the detection of low viral loads in samples. In contrast, digital PCR (dPCR), the third generation of PCR, has been shown to be more effective than the gold standard, RT-qPCR, in detecting low viral loads in samples. In this review article, we selected publications to show the broad-spectrum applications of dPCR, including the development of assays and reference standards, environmental monitoring, mutation detection, and clinical diagnosis of SARS-CoV-2, while comparing it analytically to the gold standard, RT-qPCR. In summary, it is evident that the specificity, sensitivity, reproducibility, and detection limits of RT-dPCR are generally unaffected by common factors that may affect RT-qPCR. As this is the first time that dPCR is being tested in an outbreak of such a magnitude, knowledge of its applications will help chart a course for future diagnosis and monitoring of infectious disease outbreaks.

Absolute quantification of SARS-CoV-2 with Clarity Plus™ digital PCR.

In recent years, the usage of digital polymerase chain reaction (dPCR) for various clinical applications has increased exponentially. In this study, a dPCR assay optimized on the Clarity Plus™ dPCR system was evaluated for the absolute quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the global coronavirus disease 2019 (COVID-19) outbreak. The assay demonstrated good inter- and intra- assay precision, accuracy, as well as excellent linearity across a range of over 6 orders of magnitude for target gene quantification. In addition, a comparison of the assay on both dPCR and qPCR platforms revealed that dPCR exhibited a slightly higher sensitivity compared to its qPCR counterpart when quantifying SARS-CoV-2 at a lower concentration. Overall, the results showed that the dPCR assay is a reliable and effective approach for the absolute quantification of SARS-CoV-2 and can be a valuable molecular tool in clinical applications such as detecting low viral loads in patients as well as in wastewater surveillance of COVID-19.

Detecting plasma hsa_circ_0061276 in patients with gastric cancer by reverse transcription-digital polymerase chain reaction.

Background: The role of circular RNAs (circRNAs) in the occurrence of gastric cancer is still unclear. Therefore, the diagnostic value and mechanisms underlying hsa_circ_0061276 in the occurrence of gastric cancer were explored. Methods: Reverse transcription-droplet digital polymerase chain reaction was used to detect the copy number of hsa_circ_0061276 in plasma from healthy individuals, as well as from patients with gastric precancerous lesions or early-stage or advanced gastric cancer. Plasmids overexpressing or knocking down hsa_circ_0061276 expression were transfected into gastric cancer cells. The effects on the growth, migration, and cell cycle distribution of gastric cancer cells were then analyzed. Finally, miRanda and RNAhybrid were used to explore the binding sites between hsa_circ_0061276 and microRNAs (miRNAs). A double luciferase reporter gene assay was used to confirm the miRNA sponge effect. Results: The results show that plasma hsa_circ_0061276 copy number showed a trend of a gradual decrease when comparing healthy controls to the early cancer group and advanced gastric cancer group. Overexpression of hsa_circ_0061276 inhibited the growth and migration of gastric cancer cells. Through bioinformatic analyses combined with cellular experiments, it was found that hsa_circ_0061276 inhibited the growth of gastric cancer by binding to hsa-miR-7705. Conclusion: Hsa_circ_0061276 may be a new biomarker for gastric cancer. The tumor suppressor role of hsa_circ_0061276 on gastric cancer likely occurs through a sponge effect on miRNAs such as hsa-miR-7705.

Interlaboratory assessment of quantification of SARS-CoV-2 RNA by reverse transcription digital PCR.

The pandemic of the novel coronavirus disease 2019 (COVID-19) has caused severe harm to the health of people all around the world. Molecular detection of the pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), played a crucial role in the control of the disease. Reverse transcription digital PCR (RT-dPCR) has been developed and used in the detection of SARS-CoV-2 RNA as an absolute quantification method. Here, an interlaboratory assessment of quantification of SARS-CoV-2 RNA was organized by the National Institute of Metrology, China (NIMC), using in vitro transcribed RNA samples, among ten laboratories on six different dPCR platforms. Copy number concentrations of three genes of SARS-CoV-2 were measured by all participants. Consistent results were obtained with dispersion within 2.2-fold and CV% below 23% among different dPCR platforms and laboratories, and Z' scores of all the reported results being satisfactory. Possible reasons for the dispersion included PCR assays, partition volume, and reverse transcription conditions. This study demonstrated the comparability and applicability of RT-dPCR method for quantification of SARS-CoV-2 RNA and showed the capability of the participating laboratories at SARS-CoV-2 test by RT-dPCR platform.

Highly accurate and sensitive diagnostic detection of SARS-CoV-2 by digital PCR.

The outbreak of COVID-19 caused by a novel Coronavirus (termed SARS-CoV-2) has spread to over 210 countries around the world. Currently, reverse transcription quantitative qPCR (RT-qPCR) is used as the gold standard for diagnosis of SARS-CoV-2. However, the sensitivity of RT-qPCR assays of pharyngeal swab samples are reported to vary from 30% to 60%. More accurate and sensitive methods are urgently needed to support the quality assurance of the RT-qPCR or as an alternative diagnostic approach. A reverse transcription digital PCR (RT-dPCR) method was established and evaluated. To explore the feasibility of RT-dPCR in diagnostic of SARS-CoV-2, a total of 196 clinical pharyngeal swab samples from 103 suspected patients, 77 close contacts and 16 supposed convalescents were analyzed by RT-qPCR and then measured by the proposed RT-dPCR. For the 103 fever suspected patients, 19 (19/25) negative and 42 (42/49) equivocal tested by RT-qPCR were positive according to RT-dPCR. The sensitivity of SARS-CoV-2 detection was significantly improved from 28.2% by RT-qPCR to 87.4% by RT-dPCR. For 29 close contacts (confirmed by additional sample and clinical follow up), 16 (16/17) equivocal and 1 negative tested by RT-qPCR were positive according to RT-dPCR, which is implying that the RT-qPCR is missing a lot of asymptomatic patients. The overall sensitivity, specificity and diagnostic accuracy of RT-dPCR were 91%, 100% and 93%, respectively. RT-dPCR is highly accurate method and suitable for detection of pharyngeal swab samples from COVID-19 suspected patients and patients under isolation and observation who may not be exhibiting clinical symptoms.

Quantitative expression data of human estrogen receptor α variants in non-functioning pituitary adenomas obtained by reverse transcription-digital polymerase chain reaction analysis.

Expression profiles of gonadal steroid receptor variants have been reportedly associated with malignancy in breast and prostate cancers [1,2]. However, such associations with pituitary tumors remain unclear. Therefore, the expression levels of the wild-type ESR1 (ERα66) and the ESR1 variants (ERαi34, ERαi45c, and ERαΔ5) transcripts encoding constitutively active ERα proteins with C-terminal truncation in non-functioning pituitary adenomas (NFPAs) were evaluated using reverse transcription-digital polymerase chain reaction. The results revealed that the expression levels of the variants were approximately two orders of magnitude lower than that of ERα66 in NFPAs. These data were based on our previous article entitled "Accurate assessment of estrogen receptor profiles in non-functioning pituitary adenomas using RT-digital PCR and immunohistochemistry" [3].

Accurate assessment of estrogen receptor profiles in non-functioning pituitary adenomas using RT-digital PCR and immunohistochemistry.

BACKGROUND: Non-functioning pituitary adenomas (NFPAs) are common pituitary tumors, and surgery is generally the only treatment option. Few attempts have been made to explore target molecules for the development of NFPA pharmacological treatments. METHOD: We quantitatively assessed the expression profiles of estrogen receptor (ER) transcripts and proteins in NFPA samples, using reverse transcription-digital polymerase chain reaction (RT-dPCR) and immunohistochemistry, and further investigated the correlations between the expression levels of ER and those of downstream responsive genes. All patients had undergone surgery at the same high-volume hospital. A total of 20 patients with NFPAs were included. All patients were new-onset, and none were diagnosed with intratumoral hemorrhages or cysts. RESULTS: NFPA samples exhibited a bimodal ESR1 expression pattern and were categorized into significantly different high- and low-ESR1 expression level groups (P < 0.05). In contrast, expression levels of ESR1 variants and ESR2 could barely be detected. Similar results were obtained through the immunohistochemical staining of NFPAs, using well-validated antibodies against ERs. The expression levels of ESR1 positively correlated with those of GREB1, an estrogen-responsive gene [correlation coefficient (r) = 0.623, P = 0.003]. CONCLUSIONS: ESR1 expression levels in NFPAs exhibited a bimodal pattern and were positively correlated with GREB1 expression levels. The accurate assessment of ER expression levels may further advance future NFPA-related research.

RT-dPCR in Mosquito Samples for ZIKV Detection: Effects of RNA Extraction and Reverse Transcription in Target Concentration.

Zika virus (ZIKV) is an important arbovirus, responsible for recent outbreaks of Guillain Barré Syndrome and Congenital Zika Syndrome (CZS). After thousands of CZS cases, ZIKV is under constant surveillance in Brazil. Reliable and robust detection techniques are required to minimize the influence of host inhibitors from clinical samples and mosquito pool samples. Reverse transcription Digital Polymerase Chain Reaction (RT-dPCR) is a technique that allows the accurate quantification of DNA targets with high sensitivity, and it is usually less affected by inhibitors than RT-qPCR. This study aimed to assess the influence of mosquito tissue, RNA extraction and cDNA synthesis in ZIKV PCR detection. Samples containing 0, 3 and 10 mosquitoes were spiked with ZIKV MR766 and serially diluted prior to RNA extraction and RT-dPCR for ZIKV. Two reverse transcription protocols were tested. Assay sensitivity allowed the detection of 1.197 copies/µL. A higher correlation between dilution factor and target quantification was observed in 10 mosquito pool samples. The lower quantification in samples diluted without mosquitoes highlights the critical role of the reverse transcription step in RNA detection, since it could be attributed to reverse transcriptase variable performance in samples with low overall RNA concentration. The results in mosquito pools indicate that mosquito tissues do not inhibit ZIKV RT-dPCR, and the RT-dPCR technique has good sensitivity and robustness for ZIKV detection in mosquito pool samples regardless of mosquito tissue concentration.

Molecular techniques for the personalised management of patients with chronic myeloid leukaemia.

Chronic myeloid leukemia (CML) is the paradigm for targeted cancer therapy. RT-qPCR is the gold standard for monitoring response to tyrosine kinase-inhibitor (TKI) therapy based on the reduction of blood or bone marrow BCR-ABL1. Some patients with CML and very low or undetectable levels of BCR-ABL1 transcripts can stop TKI-therapy without CML recurrence. However, about 60 percent of patients discontinuing TKI-therapy have rapid leukaemia recurrence. This has increased the need for more sensitive and specific techniques to measure residual CML cells. The clinical challenge is to determine when it is safe to stop TKI-therapy. In this review we describe and critically evaluate the current state of CML clinical management, different technologies used to monitor measurable residual disease (MRD) focus on comparingRT-qPCR and new methods entering clinical practice. We discuss advantages and disadvantages of new methods.

Quantification of Hepatitis E Virus in Naturally-Contaminated Pig Liver Products.

Hepatitis E virus (HEV), the cause of self-limiting acute hepatitis in humans, is widespread and endemic in many parts of the world. The foodborne transmission of HEV has become of concern due to the identification of undercooked pork products as a risk factor for infection. Foodborne enteric viruses are conventionally processed by quantitative RT-PCR (RT-qPCR), which gives sensitive and quantitative detection results. Recently, digital PCR (dPCR) has been described as a novel approach to genome quantification with no need for a standard curve. The performance of microfluidic digital RT-PCR (RT-dPCR) was compared to RT-qPCR when detecting HEV in pig liver products. The sensitivity of the RT-dPCR assay was similar to that of RT-qPCR, and quantitative data obtained by both detection methods were not significantly different for almost all samples. This absolute quantification approach may be useful for standardizing quantification of HEV in food samples and may be extended to quantifying other human pathogens in food samples.

A comparative study of digital RT-PCR and RT-qPCR for quantification of Hepatitis A virus and Norovirus in lettuce and water samples.

Sensitive and quantitative detection of foodborne enteric viruses is classically achieved by quantitative RT-PCR (RT-qPCR). Recently, digital PCR (dPCR) was described as a novel approach to genome quantification without need for a standard curve. The performance of microfluidic digital RT-PCR (RT-dPCR) was compared to RT-qPCR for detecting the main viruses responsible for foodborne outbreaks (human Noroviruses (NoV) and Hepatitis A virus (HAV)) in spiked lettuce and bottled water. Two process controls (Mengovirus and Murine Norovirus) were used and external amplification controls (EAC) were added to examine inhibition of RT-qPCR and RT-dPCR. For detecting viral RNA and cDNA, the sensitivity of the RT-dPCR assays was either comparable to that of RT-qPCR (RNA of HAV, NoV GI, Mengovirus) or slightly (around 1 log10) decreased (NoV GII and MNV-1 RNA and of HAV, NoV GI, NoV GII cDNA). The number of genomic copies determined by dPCR was always from 0.4 to 1.7 log10 lower than the expected numbers of copies calculated by using the standard qPCR curve. Viral recoveries calculated by RT-dPCR were found to be significantly higher than by RT-qPCR for NoV GI, HAV and Mengovirus in water, and for NoV GII and HAV in lettuce samples. The RT-dPCR assay proved to be more tolerant to inhibitory substances present in lettuce samples. This absolute quantitation approach may be useful to standardize quantification of enteric viruses in bottled water and lettuce samples and may be extended to quantifying other human pathogens in food samples.