Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale

SARS-CoV-2 surveillance by wastewater-based epidemiology is poised to provide a complementary approach to sequencing individual cases. However, robust quantification of variants and de novo detection of emerging variants remains challenging for existing strategies. We deep sequenced 3,413 wastewater samples representing 94 municipal catchments, covering >59% of the population of Austria, from December 2020 to February 2022. Our system of variant quantification in sewage pipeline designed for robustness (termed VaQuERo) enabled us to deduce the spatiotemporal abundance of predefined variants from complex wastewater samples. These results were validated against epidemiological records of >311,000 individual cases. Furthermore, we describe elevated viral genetic diversity during the Delta variant period, provide a framework to predict emerging variants and measure the reproductive advantage of variants of concern by calculating variant-specific reproduction numbers from wastewater. Together, this study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without extensive individual monitoring.

Prediction of hospitalisations based on wastewater-based SARS-CoV-2 epidemiology

Wastewater-based epidemiology is widely applied in Austria since April 2020 to monitor the SARS-CoV-2 pandemic. With a steadily increasing number of monitored wastewater facilities, 123 plants covering roughly 70 % of the 9 million population were monitored as of August 2022. In this study, the SARS-CoV-2 viral concentrations in raw sewage were analysed to infer short-term hospitalisation occupancy. The temporal lead of wastewater-based epidemiological time series over hospitalisation occupancy levels facilitates the construction of forecast models. Data pre-processing techniques are presented, including the approach of comparing multiple decentralised wastewater signals with aggregated and centralised clinical data. Time‑lead quantification was performed using cross-correlation analysis and coefficient of determination optimisation approaches. Multivariate regression models were successfully applied to infer hospitalisation bed occupancy. The results show a predictive potential of viral loads in sewage towards Covid-19 hospitalisation occupancy, with an average lead time towards ICU and non-ICU bed occupancy between 14.8-17.7 days and 8.6-11.6 days, respectively. The presented procedure provides access to the trend and tipping point behaviour of pandemic dynamics and allows the prediction of short-term demand for public health services. The results showed an increase in forecast accuracy with an increase in the number of monitored wastewater treatment plants. Trained models are sensitive to changing variant types and require recalibration of model parameters, likely caused by immunity by vaccination and/or infection. The utilised approach displays a practical and rapidly implementable application of wastewater-based epidemiology to infer hospitalisation occupancy.

Evaluation of host-based molecular markers for the early detection of human sepsis

We have identified 24 molecular markers, based on circulating nucleic acids (CNA) originating from the human genome, which in combination can be used in a quantitative real-time PCR (qPCR) assay to identify the presence of human sepsis, starting two to three days before the first clinical signs develop and including patients who meet the SEPSIS-3 criteria. The accuracy was more than 87 % inside of the same patient cohort for which the markers were developed and up to 81 % in blind studies of patient cohorts which were not included in the marker development. As our markers are host-based, they can be used to capture bacterial as well as fungal sepsis, unlike the current PCR-based tests, which require species-specific primer sets for each organism causing human sepsis. Our assay directly uses an aliquot of cell-free blood as the substrate for the PCR reaction, thus allowing to obtain the diagnostic results in three to four hours after the collection of the blood samples.

Hydrogen-Driven Cofactor Regeneration for Stereoselective Whole-Cell C=C Bond Reduction in Cupriavidus necator

The coupling of recombinantly expressed oxidoreductases to endogenous hydrogenases for cofactor recycling permits the omission of organic cosubstrates as sacrificial electron donors in whole-cell biotransformations. This increases atom efficiency and simplifies the reaction. A recombinant ene-reductase was expressed in the hydrogen-oxidizing proteobacterium Cupriavidus necator H16. In hydrogen-driven biotransformations, whole cells catalyzed asymmetric C=C bond reduction of unsaturated cyclic ketones with stereoselectivities up to >99 % enantiomeric excess. The use of hydrogen as a substrate for growth and cofactor regeneration is particularly attractive because it represents a strategy for improving atom efficiency and reducing side product formation associated with the recycling of organic cofactors.