Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study.

Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite samples were collected from wastewater treatment plants of larger towns already covered 65% of the total population that was complemented up to 40 additional grab samples from smaller towns/villages and the specific sites of concern. The N3 gene abundance was quantified by RT-qPCR. The N3 gene copy number (concentration) in wastewater fluctuated in accordance with the SARS-CoV-2 spread within the total population, with N3 abundance starting to increase 1.25 weeks (9 days) (95% CI: [1.10, 1.41]) before a rise in COVID-19 positive cases. Statistical model between the load of virus in wastewater and number of infected people validated with the Alpha variant wave (B.1.1.17) could be used to predict the order of magnitude in incidence numbers in Delta wave (B.1.617.2) in fall 2021. Targeted testing of student dormitories, retirement and nursing homes and prisons resulted in successful early discovery of outbreaks. We put forward a SARS-CoV-2 Wastewater Index (SARS2-WI) indicator of normalized virus load as COVID-19 infection metric to complement the other metrics currently used in disease control and prevention: dynamics of effective reproduction number (Re), 7-day mean of new cases, and a sum of new cases within last 14 days. In conclusion, an efficient surveillance system that combines analysis of composite and grab samples was established in Estonia. There is considerable discussion how the viral load in wastewater correlates with the number of infected people. Here we show that this correlation can be found. Moreover, we confirm that an increased signal in wastewater is observed before the increase in the number of infections. The surveillance system helped to inform public health policy and place direct interventions during the COVID-19 pandemic in Estonia via early warning of epidemic spread in various regions of the country.

Factors influencing the pigment composition and dynamics of photoautotrophic picoplankton in shallow eutrophic lakes.

Photoautotrophic picoplankton (0.2-2 µm) can be a major contributor to primary production and play a significant part in the ecosystem carbon flow. However, the understanding about the dynamics of both eukaryotic and prokaryotic components of picoplankton in shallow eutrophic freshwater environments is still poor. Very few studies in these ecosystems reveal the taxonomic composition of picoeukaryotes. The main objective of this study was to investigate the seasonal dynamics of phototrophic picoplankton with the emphasis on the eukaryote community composition in a large shallow, eutrophic lake of the northern temperate zone (Lake Võrtsjärv). Phytoplankton pigments were employed to determine the taxonomic composition of photoautotrophic picoplankton. We found out that photoautotrophic picoplankton constitutes an important part of the phytoplankton community in Lake Võrtsjärv and its contribution can be highly variable (from ~9.3% to ~39%) in different years. The eukaryotic photoautotrophic picoplankton was dominated by diatoms followed by chrysophytes and other minor groups. Picoeukaryotes were prevailing in low-light conditions and low temperatures as their predominance in the picoplankton community was tightly linked to the presence or absence of ice cover. Ice cover strongly suppressed the growth of picocyanobacteria. Total phosphorus, turbidity and metazooplankton abundance had a clear relationship with photoautotrophic picoplankton chlorophyll a.

Using Microcystin Gene Copies to Determine Potentially-Toxic Blooms, Example from a Shallow Eutrophic Lake Peipsi.

Global warming, paired with eutrophication processes, is shifting phytoplankton communities towards the dominance of bloom-forming and potentially toxic cyanobacteria. The ecosystems of shallow lakes are especially vulnerable to these changes. Traditional monitoring via microscopy is not able to quantify the dynamics of toxin-producing cyanobacteria on a proper spatio-temporal scale. Molecular tools are highly sensitive and can be useful as an early warning tool for lake managers. We quantified the potential microcystin (MC) producers in Lake Peipsi using microscopy and quantitative polymerase chain reaction (qPCR) and analysed the relationship between the abundance of the mcyE genes, MC concentration, MC variants and toxin quota per mcyE gene. We also linked environmental factors to the cyanobacteria community composition. In Lake Peipsi, we found rather moderate MC concentrations, but microcystins and microcystin-producing cyanobacteria were widespread across the lake. Nitrate (NO3-) was a main driver behind the cyanobacterial community at the beginning of the growing season, while in late summer it was primarily associated with the soluble reactive phosphorus (SRP) concentration. A positive relationship was found between the MC quota per mcyE gene and water temperature. The most abundant variant-MC-RR-was associated with MC quota per mcyE gene, while other MC variants did not show any significant impact.

Role of potentially toxic cyanobacteria in crustacean zooplankton diet in a eutrophic lake.

The coexistence of potentially toxic bloom-forming cyanobacteria (CY) and generally smaller-sized grazer communities has raised the question of zooplankton (ZP) ability to control harmful cyanobacterial blooms and highlighted the need for species-specific research on ZP-CY trophic interactions in naturally occurring communities. A combination of HPLC, molecular and stable isotope analyses was used to assess in situ the importance of CY as a food source for dominant crustacean ZP species and to quantify the grazing on potentially toxic strains of Microcystis during bloom formation in large eutrophic Lake Peipsi (Estonia). Aphanizomenon, Dolichospermum, Gloeotrichia and Microcystis dominated bloom-forming CY, while Microcystis was the major genus producing cyanotoxins all over the lake. Grazing studies showed that CY, and especially colonial CY, formed a significant, and also preferred component of algae ingested by the cladocerans Bosmina spp. and Daphnia spp. while this was not the case for the more selective calanoid copepod Eudiaptomus gracilis. Molecular analyses confirmed the presence of CY, including Microcystis, in ZP guts. Further analyses using qPCR targeting cyanobacterial genus-specific mcyE synthase genes indicated that potentially toxic strains of Microcystis can be ingested directly or indirectly by all the dominant crustacean grazers. However, stable isotope analyses indicated that little, if any, assimilation from ingested bloom-forming CY occurred. The study suggests that CY, and particularly Microcystis with both potentially toxic and non-toxic strains, can be widely ingested by cladoceran grazers during a bloom event with implications for control of CY abundance and for transfer of CY toxins through the food web.

A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins.

Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment.