From Alpha to Omicron BA.2: New digital RT-PCR approach and challenges for SARS-CoV-2 VOC monitoring and normalization of variant dynamics in wastewater.

Throughout the COVID-19 pandemic, new variants have continuously emerged and spread in populations. Among these, variants of concern (VOC) have been the main culprits of successive epidemic waves, due to their transmissibility, pathogenicity or ability to escape the immune response. Quantification of the SARS-CoV-2 genomes in raw wastewater is a reliable approach well-described and widely deployed worldwide to monitor the spread of SARS-CoV-2 in human populations connected to sewage systems. Discrimination of VOCs in wastewater is also a major issue and can be achieved by genome sequencing or by detection of specific mutations suggesting the presence of VOCs. This study aimed to date the emergence of these VOCs (from Alpha to Omicron BA.2) by monitoring wastewater from the greater Paris area, France, but also to model the propagation dynamics of these VOCs and to characterize the replacement kinetics of the prevalent populations. These dynamics were compared to various individual-centered public health data, such as regional incidence and the proportions of VOCs identified by sequencing of strains isolated from patient. The viral dynamics in wastewater highlighted the impact of the vaccination strategy on the viral circulation within human populations but also suggested its potential effect on the selection of variants most likely to be propagated in immunized populations. Normalization of concentrations to capture population movements appeared statistically more reliable using variations in local drinking water consumption rather than using PMMoV concentrations because PMMoV fecal shedding was subject to variability and was not sufficiently relevant in this study. The dynamics of viral spread was observed earlier (about 13 days on the wave related to Omicron VOC) in raw wastewater than the regional incidence alerting to a possible risk of decorrelation between incidence and actual virus circulation probably resulting from a lower severity of infection in vaccinated populations.

atpE gene as a new useful specific molecular target to quantify Mycobacterium in environmental samples.

BACKGROUND: The environment is the likely source of many pathogenic mycobacterial species but detection of mycobacteria by bacteriological tools is generally difficult and time-consuming. Consequently, several molecular targets based on the sequences of housekeeping genes, non-functional RNA and structural ribosomal RNAs have been proposed for the detection and identification of mycobacteria in clinical or environmental samples. While certain of these targets were proposed as specific for this genus, most are prone to false positive results in complex environmental samples that include related, but distinct, bacterial genera. Nowadays the increased number of sequenced genomes and the availability of software for genomic comparison provide tools to develop novel, mycobacteria-specific targets, and the associated molecular probes and primers. Consequently, we conducted an in silico search for proteins exclusive to Mycobacterium spp. genomes in order to design sensitive and specific molecular targets. RESULTS: Among the 3989 predicted proteins from M. tuberculosis H37Rv, only 11 proteins showed 80% to 100% of similarity with Mycobacterium spp. genomes, and less than 50% of similarity with genomes of closely related Corynebacterium, Nocardia and Rhodococcus genera. Based on DNA sequence alignments, we designed primer pairs and a probe that specifically detect the atpE gene of mycobacteria, as verified by quantitative real-time PCR on a collection of mycobacteria and non-mycobacterial species. The real-time PCR method we developed was successfully used to detect mycobacteria in tap water and lake samples. CONCLUSIONS: The results indicate that this real-time PCR method targeting the atpE gene can serve for highly specific detection and precise quantification of Mycobacterium spp. in environmental samples.