Evaluation of low-cost SARS-CoV-2 RNA purification methods for viral quantification by RT-qPCR and next-generation sequencing analysis: Implications for wider wastewater-based epidemiology adoption.

Based Epidemiology (WBE) consists of quantifying biomarkers in sewerage systems to derive real-time information on the health and/or lifestyle of the contributing population. WBE usefulness was vastly demonstrated in the context of the COVID-19 pandemic. Many methods for SARS-CoV-2 RNA determination in wastewater were devised, which vary in cost, infrastructure requirements and sensitivity. For most developing countries, implementing WBE for viral outbreaks, such as that of SARS-CoV-2, proved challenging due to budget, reagent availability and infrastructure constraints. In this study, we assessed low-cost methods for SARS-CoV-2 RNA quantification by RT-qPCR, and performed variant identification by NGS in wastewater samples. Results showed that the effect of adjusting pH to 4 and/or adding MgCl2 (25 mM) was negligible when using the adsorption-elution method, as well as basal physicochemical parameters in the sample. In addition, results supported the standardized use of linear rather than plasmid DNA for a more accurate viral RT-qPCR estimation. The modified TRIzol-based purification method in this study yielded comparable RT-qPCR estimation to a column-based approach, but provided better NGS results, suggesting that column-based purification for viral analysis should be revised. Overall, this work provides evaluation of a robust, sensitive and cost-effective method for SARS-CoV-2 RNA analysis that could be implemented for other viruses, for a wider WEB adoption.

Insight into the genome data of commercially important giant kelp Macrocystis pyrifera.

Kelps or brown algae are a wide group of marine macroalgae that play an important role in aquatic ecosystems and generally have high commercial value. To facilitate brown algal studies, we report the complete genome sequence of the largest kelp Macrocystis pyrifera. The whole genome is ∼428 Mb in size, comprises 44,307 scaffolds with an average GC content of 47%, and is predicted to contain a total of 24,778 genes. 18S sequence-based phylogenetic analysis revealed that littoral brown seaweed Scytosiphon lomentaria is the closest species of M. pyrifera. Numerous genes identified in this dataset are involved in genetic information processing, signaling, and cellular processes, carbohydrate metabolism, and terpenoids biosynthesis.

Spatiotemporal Surveillance of SARS-CoV-2 in the Sewage of Three Major Urban Areas in Peru: Generating Valuable Data Where Clinical Testing Is Extremely Limited.

Peru has been severely affected by the COVID-19 pandemic. By January 2022, Peru had surpassed 200 000 COVID-19 deaths, constituting the highest death rate per capita worldwide. Peru has had several limitations during the pandemic: insufficient testing access, limited contact tracing, a strained medical infrastructure, and many economic hurdles. These limitations hindered the gathering of accurate information about infected individuals with spatial resolution in real time, a critical aspect of effectively controlling the pandemic. Wastewater monitoring for SARS-CoV-2 RNA offered a promising alternative for providing needed population-wide information to complement health care indicators. In this study, we demonstrate the feasibility and value of implementing a decentralized SARS-CoV-2 RNA wastewater monitoring system to assess the spatiotemporal distribution of COVID-19 in three major cities in Peru: Lima, Callao, and Arequipa. Our data on viral loads showed the same trends as health indicators such as incidence and mortality. Furthermore, we were able to identify hot spots of contagion within the surveyed urban areas to guide the efforts of health authorities. Viral decay in the sewage network of the cities studied was found to be negligible (<2%). Overall, our results support wastewater monitoring for SARS-CoV-2 as a valuable and cost-effective tool for monitoring the COVID-19 pandemic in the Peruvian context.

A simple and accurate method for specific quantification of biomass in mixed cultures of filamentous fungi by quantitative PCR / Un método simple y preciso para la cuantificación específica de biomasa en cultivos mixtos de hongos filamentosos por PCR cuantitativa

Abstract Production of lignocellulolytic enzymes by filamentous fungi have a great potential at industrial level due to their widespread applications. Mixed fungal cultures and particularly mixed fungal biofilms constitute a promising fermentation system for an enhanced enzyme production. However, it has not been addressed how much of this enhancement depends on the mixed biomass proportion. In this sense, the aim of this study was to develop a method to specifically and accurately quantify mixed fungal biomass. For this purpose, mixed biofilm cultures composed of Aspergillus niger and Trichoderma reesei, two filamentous fungi used industrially for cellulase production, were collected from 48 to 120 h of growth; mycelia were pulverized, and DNA was extracted for qPCR assays with specific primers for each fungus. Primers were designed from non-conserved regions of sequences of actin and β-tubulin genes of both A. niger and T. reesei. Specificity of these primers was tested in silico and experimentally. A statistically significant correlation was obtained between qPCR-calculated biomass and dry weight biomass data. By this method, it was possible to detect changes on mycelia proportions in biofilms over time, suggesting a competitive interaction between these two fungi. In conclusion, this method allows a specific and accurate quantification of mixed fungal biomass and could be also applied to different mixed culture systems for studying microbial interactions.

Resumen La producción de enzimas lignocelulolíticas por hongos filamentosos tiene un gran potencial a nivel industrial debido a sus diversas aplicaciones. Los cultivos fúngicos mixtos y particularmente las biopelículas fúngicas mixtas constituyen un sistema de fermentación prometedor para una mayor producción enzimática. Sin embargo, no se ha abordado cuánto de esta mejora depende de la proporción de biomasa mixta. En este sentido, el objetivo de este estudio fue desarrollar un método para cuantificar de forma específica y precisa la biomasa fúngica mixta. Para este propósito, se recolectaron cultivos mixtos de biopelículas de 48 a 120 h de crecimiento compuestos por Aspergillus niger y Trichoderma reesei, dos hongos filamentosos utilizados industrialmente para la producción de celulasas; el micelio se pulverizó y el ADN se extrajo para ensayos de qPCR con cebadores específicos para cada hongo. Los cebadores se diseñaron a partir de regiones no conservadas de las secuencias de los genes de actina y β-tubulina de A. niger y T. reesei. La especificidad de estos cebadores se probó in silico y experimentalmente. Se obtuvo una correlación estadísticamente significativa entre la biomasa calculada mediante qPCR y los datos de biomasa en peso seco. Mediante este método, fue posible detectar cambios en las proporciones de los micelios en las biopelículas a lo largo del tiempo, lo que sugiere una interacción competitiva entre estos dos hongos. En conclusión, este método permite una cuantificación específica y precisa de la biomasa fúngica mixta y también podría aplicarse a diferentes sistemas de cultivo mixto para estudiar interacciones microbianas.