Estimating actual SARS-CoV-2 infections from secondary data

Eminent in pandemic management is accurate information on infection dynamics to plan for timely installation of control measures and vaccination campaigns. Despite huge efforts in diagnostic testing of individuals, the underestimation of the actual number of SARS-CoV-2 infections remains significant due to the large number of undocumented cases. In this paper we demonstrate and compare three methods to estimate the dynamics of true infections based on secondary data i.e., (a) test positivity, (b) infection fatality and (c) wastewater monitoring. The concept is tested with Austrian data on a national basis for the period of April 2020 to December 2022. Further, we use the results of prevalence studies from the same period to generate (upper and lower bounds of) credible intervals for true infections for four data points. Model parameters are subsequently estimated by applying Approximate Bayesian Computation-rejection sampling and Genetic Algorithms. The method is then validated for the case study Vienna. We find that all three methods yield fairly similar results for estimating the true number of infections, which supports the idea that all three datasets contain similar baseline information. None of them is considered superior, as their advantages and shortcomings depend on the specific case study at hand.

Meso- and thermophilic posttreatment of press water coming from a thermophilic municipal solid waste digester

An efficient biogas production out of organic (waste) materials is important to contribute to a carbon-neutral future. In this study, thermophilic press water (PW) coming from an organic fraction of the municipal solid waste digester was further digested in a thermo- and mesophilic posttreatment approach using two semicontinuous 14 L digesters. The results showed that the PW can still have considerable high biogas potential-at least during the touristic high season in central Europe. The change in temperature led to an increase in volatile fatty acid concentrations and a decrease in biogas production in the mesophilic approach in the first days. However, the losses in biogas production at the beginning could be compensated thus there were no considerable differences in biogas production between thermo- and mesophilic posttreatment at the end of incubation. This can most probably be contributed to a change in the microbial community, and potentially problematic intermediates like valerate could be better degraded in the mesophilic reactor. Especially the abundance of representatives of the phylum Bacteroidota, like Fermentimonas spp., increased during mesophilic anaerobic digestion.

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.

Effects of phenyl acids on different degradation phases during thermophilic anaerobic digestion

Aromatic compounds like phenyl acids (PA) can accumulate during anaerobic digestion (AD) of organic wastes due to an increased entry of lignocellulose, secondary plant metabolites or proteins, and thermodynamic challenges in degrading the benzene ring. The effects of aromatic compounds can be various – from being highly toxic to be stimulating for methanogenesis – depending on many parameters like inoculum or molecular characteristics of the aromatic compound. To contribute to a better understanding of the consequences of PA exposure during AD, the aim was to evaluate the effects of 10 mM PA on microbial communities degrading different, degradation phase–specific substrates in thermophilic batch reactors within 28  days: Microcrystalline cellulose (MCC, promoting hydrolytic to methanogenic microorganisms), butyrate or propionate (promoting syntrophic volatile fatty acid (VFA) oxidisers to methanogens), or acetate (promoting syntrophic acetate oxidisers to methanogens). Methane production, VFA concentrations and pH were evaluated, and microbial communities and extracellular polymeric substances (EPS) were assessed. The toxicity of PA depended on the type of substrate which in turn determined the (i) microbial diversity and composition and (ii) EPS quantity and quality. Compared with the respective controls, methane production in MCC reactors was less impaired by PA than in butyrate, propionate and acetate reactors which showed reductions in methane production of up to 93%. In contrast to the controls, acetate concentrations were high in all PA reactors at the end of incubation thus acetate was a bottle-neck intermediate in those reactors. Considerable differences in EPS quantity and quality could be found among substrates but not among PA variants of each substrate. Methanosarcina spp. was the dominant methanogen in VFA reactors without PA exposure and was inhibited when PA were present. VFA oxidisers and Methanothermobacter spp. were abundant in VFA assays with PA exposure as well as in all MCC reactors. As MCC assays showed higher methane yields, a higher microbial diversity and a higher EPS quantity and quality than VFA reactors when exposed to PA, we conclude that EPS in MCC reactors might have been beneficial for absorbing/neutralising phenyl acids and keeping (more susceptible) microorganisms shielded in granules or biofilms.

Expanding the Pathogen Panel in Wastewater Epidemiology to Influenza and Norovirus

Since the start of the 2019 pandemic, wastewater-based epidemiology (WBE) has proven to be a valuable tool for monitoring the prevalence of SARS-CoV-2. With methods and infrastructure being settled, it is time to expand the potential of this tool to a wider range of pathogens. We used over 500 archived RNA extracts from a WBE program for SARS-CoV-2 surveillance to monitor wastewater from 11 treatment plants for the presence of influenza and norovirus twice a week during the winter season of 2021/2022. Extracts were analyzed via digital PCR for influenza A, influenza B, norovirus GI, and norovirus GII. Resulting viral loads were normalized on the basis of NH4-N. Our results show a good applicability of ammonia-normalization to compare different wastewater treatment plants. Extracts originally prepared for SARS-CoV-2 surveillance contained sufficient genomic material to monitor influenza A, norovirus GI, and GII. Viral loads of influenza A and norovirus GII in wastewater correlated with numbers from infected inpatients. Further, SARS-CoV-2 related non-pharmaceutical interventions affected subsequent changes in viral loads of both pathogens. In conclusion, the expansion of existing WBE surveillance programs to include additional pathogens besides SARS-CoV-2 offers a valuable and cost-efficient possibility to gain public health information.

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.

Data modelling recipes for SARS-CoV-2 wastewater-based epidemiology

Wastewater based epidemiology is recognized as one of the monitoring pillars, providing essential information for pandemic management. Central in the methodology are data modelling concepts for both communicating the monitoring results but also for analysis of the signal. It is due to the fast development of the field that a range of modelling concepts are used but without a coherent framework. This paper provides for such a framework, focusing on robust and simple concepts readily applicable, rather than applying latest findings from e.g., machine learning. It is demonstrated that data preprocessing, most important normalization by means of biomarkers and equal temporal spacing of the scattered data, is crucial. In terms of the latter, downsampling to a weekly spaced series is sufficient. Also, data smoothing turned out to be essential, not only for communication of the signal dynamics but likewise for regressions, nowcasting and forecasting. Correlation of the signal with epidemic indicators requires multivariate regression as the signal alone cannot explain the dynamics but - for this case study - multiple linear regression proofed to be a suitable tool when the focus is on understanding and interpretation. It was also demonstrated that short term prediction (7 days) is accurate with simple models (exponential smoothing or autoregressive models) but forecast accuracy deteriorates fast for longer periods.

The glutamyl tail length of the cofactor F420 in the methanogenic Archaea Methanosarcina thermophila and Methanoculleus thermophilus

The cofactor F₄₂₀ is synthesized by many different organisms and as a redox cofactor, it plays a crucial role in the redox reactions of catabolic and biosynthetic metabolic pathways. It consists of a deazaflavin structure, which is linked via lactate to an oligoglutamate chain, that can vary in length. In the present study, the methanogenic Archaea Methanosarcina thermophila and Methanoculleus thermophilus were cultivated on different carbon sources and their coenzyme F₄₂₀ composition has been assayed by reversed-phase ion-pair high-performance liquid chromatography with fluorometric detection regarding both, overall cofactor F₄₂₀ production and distribution of F₄₂₀ glutamyl tail length. In Methanosarcina thermophila cultivated on methanol, acetate, and a mixture of acetate and methanol, the most abundant cofactors were F₄₂₀-5 and F₄₂₀-4, whereby the last digit refers to the number of expressed glutamyl rests. By contrast, in the obligate CO₂ reducing Methanoculleus thermophilus the most abundant cofactors were F₄₂₀-3 and F₄₂₀-4. In Methanosarcina thermophila, the relative proportions of the expressed F₄₂₀ tail length changed during batch growth on all three carbon sources. Over time F₄₂₀-3 and F₄₂₀-4 decreased while F₄₂₀-5 and F₄₂₀-6 increased in their relative proportion in comparison to total F₄₂₀ content. In contrast, in Methanoculleus thermophilus the relative abundance of the different F₄₂₀ cofactors remained stable. It was also possible to differentiate the two methanogenic Archaea based on the glutamyl tail length of the cofactor F₄₂₀. The cofactor F₄₂₀-5 in concentrations >2% could only be assigned to Methanosarcina thermophila. In all four variants a trend for a positive correlation between the DNA concentration and the total concentration of the cofactor could be shown. Except for the variant Methanosarcinathermophila with acetate as sole carbon source the same could be shown between the concentration of the mcrA gene copy number and the total concentration of the cofactor.

Detection and abundance of SARS-CoV-2 in wastewater in Liechtenstein, and the estimation of prevalence and impact of the B.1.1.7 variant

The new coronavirus 2 (SARS-CoV-2) is known to be also shed through feces, which makes wastewater-based surveillance possible, independent of symptomatic cases and unbiased by any testing strategies and frequencies. We investigated the entire population of the Principality of Liechtenstein with samples from the wastewater treatment plant Bendern (serving all 39,000 inhabitants). Twenty-four-hour composite samples were taken once or twice a week over a period of 6 months from September 2020 to March 2021. Viral RNA was concentrated using the PEG centrifugation method followed by reverse transcription quantitative PCR. The aim of this research was to assess the suitability of SARS-CoV-2 fragments to relate the viral wastewater signal to the incidences and assess the impact of the emerging B.1.1.7. variant. The viral load in the wastewater peaked at almost 9 × 10⁸ viral fragments per person equivalent (PE) and day on October 25, and showed a second peak on December 22 reaching a viral load of approximately 2 × 10⁸ PE^-1d^-1. Individual testing showed a lag of 4 days and a distinct underestimation of cases at the first peak when testing frequency was low. The wastewater signal showed an immediate response to the implementation of non-pharmaceutical interventions. The new virus variant B.1.1.7. was first detected in wastewater on December 23, while it was first observed with individual testing on January 13, 2021. Further, our data indicate that the emergence of new virus variant may change the wastewater signal, probably due to different shedding patterns, which should be considered in future models.

Quest for Optimal Regression Models in SARS-CoV-2 Wastewater Based Epidemiology

Wastewater-based epidemiology is a recognised source of information for pandemic management. In this study, we investigated the correlation between a SARS-CoV-2 signal derived from wastewater sampling and COVID-19 incidence values monitored by means of individual testing programs. The dataset used in the study is composed of timelines (duration approx. five months) of both signals at four wastewater treatment plants across Austria, two of which drain large communities and the other two drain smaller communities. Eight regression models were investigated to predict the viral incidence under varying data inputs and pre-processing methods. It was found that population-based normalisation and smoothing as a pre-processing of the viral load data significantly influence the fitness of the regression models. Moreover, the time latency lag between the wastewater data and the incidence derived from the testing program was found to vary between 2 and 7 days depending on the time period and site. It was found to be necessary to take such a time lag into account by means of multivariate modelling to boost the performance of the regression. Comparing the models, no outstanding one could be identified as all investigated models are revealing a sufficient correlation for the task. The pre-processing of data and a multivariate model formulation is more important than the model structure.

Extraction of Cofactor F420 for Analysis of Polyglutamate Tail Length from Methanogenic Pure Cultures and Environmental Samples

The cofactor F420 plays a central role as a hydride carrier in the primary and secondary metabolism of many bacterial and archaeal taxa. The cofactor is best known for its role in methanogenesis, where it facilitates thermodynamically difficult reactions. As the polyglutamate tail varies in length between different organisms, length profile analyses might be a powerful tool for distinguishing and characterizing different groups and pathways in various habitats. Here, the protocol describes the extraction and optimization of cofactor F420 detection by applying solid-phase extraction combined with high-performance liquid chromatography analysis independent of cultural or molecular biological approaches. The method was applied to gain additional information on the expression of cofactor F420 from microbial communities in soils, anaerobic sludge, and pure cultures and was evaluated by spiking experiments. Thereby, the study succeeded in generating different F420 tail-length profiles for hydrogenotrophic and acetoclastic methanogens in controlled methanogenic pure cultures as well as from environmental samples such as anaerobic digester sludge and soils.

Detection and Stability of SARS-CoV-2 Fragments in Wastewater: Impact of Storage Temperature

SARS-CoV-2 wastewater epidemiology suffers from uncertainties concerning sample storage. We show the effect of the storage of wastewater on the detectable SARS-CoV-2 load. Storage at 4 °C for up to 9 days had no significant effect, while storage at -20 °C led to a significant reduction in gene copy numbers.

Detection and Stability of SARS-CoV-2 Fragments in Wastewater: Impact of Storage Temperature

SARS-CoV-2 wastewater epidemiology suffers from uncertainties concerning sample storage. We show the effect of the storage of wastewater on the detectable SARS-CoV-2 load. Storage at 4 °C for up to 9 days had no significant effect, while storage at -20 °C led to a significant reduction in gene copy numbers.

Data filtering methods for SARS-CoV-2 wastewater surveillance

In the case of SARS-CoV-2 pandemic management, wastewater-based epidemiology aims to derive information on the infection dynamics by monitoring virus concentrations in the wastewater. However, due to the intrinsic random fluctuations of the viral signal in wastewater caused by several influencing factors that cannot be determined in detail (e.g. dilutions; number of people discharging; variations in virus excretion; water consumption per day; transport and fate processes in sewer system), the subsequent prevalence analysis may result in misleading conclusions. It is thus helpful to apply data filtering techniques to reduce the noise in the signal. In this paper we investigate 13 smoothing algorithms applied to the virus signals monitored in four wastewater treatment plants in Austria. The parameters of the algorithms have been defined by an optimization procedure aiming for performance metrics. The results are further investigated by means of a cluster analysis. While all algorithms are in principle applicable, SPLINE, Generalized Additive Model and Friedman's Super Smoother are recognized as superior methods in this context (with the latter two having a tendency to over-smoothing). A first analysis of the resulting datasets indicates the positive effect of filtering to the correlation of the viral signal to monitored incidence values.

Proposal of Thermoactinomyces mirandus sp. nov., a filamentous, anaerobic bacterium isolated from a biogas plant

We isolated a filamentous, thermophilic, and first anaerobic representative of the genus Thermoactinomyces, designated strain AMNI-1^T, from a biogas plant in Tyrol, Austria and report the results of a phenotypic, genetic, and phylogenetic investigation. Strain AMNI-1^T was observed to form a white branching mycelium that aggregates into pellets when grown in liquid medium. Cells could primarily utilize lactose, glucose, and mannose as carbon and energy sources, with acetate accelerating and yeast extract being mandatory for growth. The optimum growth temperature and pH turned out to be 55 °C and pH 7.0, respectively, with an optimum NaCl concentration of 0–2% (w/v). 16S rRNA gene sequence comparison indicated that the genetic relatedness between strain AMNI-1^T and Thermoactinomyces intermedius, Thermoactinomyces khenchelensis, and Thermoactinomyces vulgaris was less than 97%. The G + C content of the genomic DNA was 44.7 mol%. The data obtained suggest that the isolate represents a novel and first anaerobic species of the genus Thermoactinomyces, for which the name Thermoactinomyces mirandus is proposed. The type strain is AMNI-1^T (= DSM 110094^T = LMG 31503^T). The description of the genus Thermoactinomyces is emended accordingly.

pH and Phosphate Induced Shifts in Carbon Flow and Microbial Community during Thermophilic Anaerobic Digestion

pH is a central environmental factor influencing CH4 production from organic substrates, as every member of the complex microbial community has specific pH requirements. Here, we show how varying pH conditions (5.0-8.5, phosphate buffered) and the application of a phosphate buffer per se induce shifts in the microbial community composition and the carbon flow during nine weeks of thermophilic batch digestion. Beside monitoring the methane production as well as volatile fatty acid concentrations, amplicon sequencing of the 16S rRNA gene was conducted. The presence of 100 mM phosphate resulted in reduced CH4 production during the initial phase of the incubation, which was characterized by a shift in the dominant methanogenic genera from a mixed Methanosarcina and Methanoculleus to a pure Methanoculleus system. In buffered samples, acetate strongly accumulated in the beginning of the batch digestion and subsequently served as a substrate for methanogens. Methanogenesis was permanently inhibited at pH values ≤5.5, with the maximum CH4 production occurring at pH 7.5. Adaptations of the microbial community to the pH variations included shifts in the archaeal and bacterial composition, as less competitive organisms with a broad pH range were able to occupy metabolic niches at unfavorable pH conditions.

Microbial and Phenyl Acid Dynamics during the Start-up Phase of Anaerobic Straw Degradation in Meso- and Thermophilic Batch Reactors

Aromatic compounds like phenyl acids derived from lignocellulose degradation have been suspected to negatively influence biogas production processes. However, results on this topic are still inconclusive. To study phenyl acid formation in batch reactors during the start-up phase of anaerobic degradation, different amounts of straw from grain were mixed with mesophilic and thermophilic sludge, respectively. Molecular biological parameters were assessed using next-generation sequencing and qPCR analyses. Metagenomic predictions were done via the program, piphillin. Methane production, concentrations of phenylacetate, phenylpropionate, phenylbutyrate, and volatile fatty acids were monitored chromatographically. Methanosarcina spp. was the dominant methanogen when high straw loads were effectively degraded, and thus confirmed its robustness towards overload conditions. Several microorganisms correlated negatively with phenyl acids; however, a negative effect, specifically on methanogens, could not be proven. A cascade-like increase/decrease from phenylacetate to phenylpropionate, and then to phenylbutyrate could be observed when methanogenesis was highly active. Due to these results, phenylacetate was shown to be an early sign for overload conditions, whereas an increase in phenylbutyrate possibly indicated a switch from degradation of easily available to more complex substrates. These dynamics during the start-up phase might be relevant for biogas plant operators using complex organic wastes for energy exploitation.

Medium Preparation for the Cultivation of Microorganisms under Strictly Anaerobic/Anoxic Conditions

In contrast to aerobic organisms, strictly anaerobic microorganisms require the absence of oxygen and usually a low redox potential to initiate growth. As oxygen is ubiquitous in air, retaining O2-free conditions during all steps of cultivation is challenging but a prerequisite for anaerobic culturing. The protocol presented here demonstrates the successful cultivation of an anaerobic mixed culture derived from a biogas plant using a simple and inexpensive method. A precise description of the entire anoxic culturing process is given including media preparation, filling of cultivation flasks, supplementation with redox indicator and reducing agents to provide low redox potentials as well as exchanging the headspace to keep media free from oxygen. Furthermore, a detailed overview of aseptically inoculating gas tight serum flasks (by using sterile syringes and needles) and suitable incubation conditions is provided. The present protocol further deals with gas and liquid sampling for subsequent analyses regarding gas composition and volatile fatty acid concentrations using gas chromatography (GC) and high performance liquid chromatography (HPLC), respectively, and the calculation of biogas and methane yield considering the ideal gas law.

Formation of phenylacetic acid and phenylpropionic acid under different overload conditions during mesophilic and thermophilic anaerobic digestion

BACKGROUND

Substrate spectra for anaerobic digestion have been broadened in the past decade, inter alia, due to the application of different pretreatment strategies and now include materials rich in lignocellulose, protein, and/or fat. The application of these substrates, however, also entails risks regarding the formation of undesired by-products, among which phenolic compounds are known to accumulate under unfavorable digestion conditions.

METHODS

Different states of overload were simulated in batch experiments while reviewing the generation of phenyl acids out of different lab-use substrates in order to evaluate the impact on biogas and methane production as well as some additional process performance parameters under defined laboratory conditions. Investigations were conducted under both mesophilic and thermophilic conditions.

RESULTS

It could be shown that the tested input materials led to the formation of phenyl acids in a substrate-dependent manner with the formation itself being less temperature driven. Once formed, the formation of phenyl acids turned out to be a reversible process.

CONCLUSIONS

Although a mandatory negative impact of phenyl acids per se on the anaerobic digestion process in general and the methanogenesis process in particular could not be proven, phenyl acids, however, seem to play an important role in the microbial response to overloaded biogas systems.

Self-emulsifying drug delivery systems: Design of a novel vaginal delivery system for curcumin

AIM

The aim of this study was to develop a vaginal self-emulsifying delivery system for curcumin being capable of spreading, of permeating the mucus gel layer and of protecting the drug being incorporated in oily nanodroplets towards mucus interactions and immobilization.

METHODS

The emulsifying properties of curcumin loaded SEDDS containing 30% Cremophor RH40, 20% Capmul PG-8, 30% Captex 300, 10% DMSO and 10% tetraglycol (SEDD formulation A) as well as 25% PEG 200, 35% Cremophor RH40, 20% Captex 355, 10% Caprylic acid and 10% Tween 80 (SEDD formulation B) after diluting 1+2 with artificial vaginal fluid were characterized regarding droplet size and zeta potential. Collagen swelling test was used to examine the irritation potential of SEDDS. Additionally to mucus binding studies, permeation studies in the mucus were performed. Furthermore, spreading potential of the novel developed formulations was compared with a commercial available o/w cream (non-ionic hydrophilic cream) on vaginal mucosa.

RESULTS

SEDDS displayed a mean droplet size between 38 and 141nm and a zeta potential of -0.3 to -1.6mV. The collagen swelling test indicated no significant irritation potential of both formulations over 24h. An immediate interaction of unformulated curcumin with the mucus was determined, whereas both SEDDS facilitated drug permeation through the mucus layer. Formulation B showed a 2.2-fold improved transport ratio of curcumin compared to SEDD formulation A. In comparison to the vaginal cream, SEDD formulation A and B were able to spread over the vaginal mucosa and cover the tissue to a 17.8- and 14.8-fold higher extent, respectively.

CONCLUSION

According to these results, SEDDS seems to be a promising tool for vaginal application.

Sample preparation, preservation, and storage for volatile fatty acid quantification in biogas plants

Volatile fatty acids (VFA) represent short-chain fatty acids consisting of six or fewer carbon atoms that can be distilled at atmospheric pressure. In anaerobic digestion processes VFAs are of central importance for maintaining stable reactor performance and biogas production, are used as indicators for arising problems and are important process monitoring parameters. In the present study, sludge derived form a full-scale anaerobic digester of a wastewater treatment plant was spiked with formate, acetate, propionate, and butyrate in order to evaluate various commonly used techniques for VFA extraction, preservation, and storage. It was shown that VFA extraction after centrifugation warranted the highest recovery rates for spiked VFAs. Moreover, experiments clearly indicated the importance of a fast sample handling, including the necessity of immediate cooling of the samples. Chemical sample preservation within a narrow time frame or deep freezing emerged as an alternative to instant VFA extraction. Short-time storage of extracted VFA samples at + 4°C is an option for up to 7 days, for longer periods storage at -20°C was found to be applicable.

Comment on "Synergistic co-digestion of solid-organic-waste and municipal-sewage-sludge: 1 plus 1 equals more than 2 in terms of biogas production and solids reduction" [Water Research 87, 416-423]

Co-digestion of organic waste and sewage sludge enhances biogas production and reduces the mass of remaining solids. This phenomenon of enhanced organic matter decomposition by adding labile substrate is known from other habitats like soils and sediments where it is called priming effect. It is thus suggested to adopt the term priming effect also in environmental biotechnology, and in particular for biomethanisation of wastewater sludges by the addition of energy-rich co-substrates.

Comparative evaluation of multiple methods to quantify and characterise granular anammox biomass

Six methodologically different approaches were evaluated and compared regarding their suitability to quantify and characterise granular anammox biomass. The investigated techniques were gravimetric analysis (GA), activity measurements (AM), Coulter counter analysis (CC), quantitative PCR (qPCR), heme protein quantification (HQ) and the novel image analysis technique Particle Tracking (PT). The focus was set on the development of fast, economic and user-friendly approaches for potential implementation in regular wastewater treatment plant (WWTP) monitoring. To test the effectiveness of each technique, two sample matrices were chosen at the WWTP Strass (Austria): i) sludge liquor of the DEMON tank, treating ammonium-rich reject water of anaerobic digestion via the deammonification process and rich in anammox biomass (SL), and ii) the mainstream biological stage, that has been enriched with anammox biomass for more than two years (B). In both of these plants hydro-cyclones are installed for density-fractioning of the sludge into a low- and a high-density fraction, thus leading to a characteristic anammox distribution in the investigated sample set. All investigated methods could statistically discriminate the SL samples. Heme quantification and qPCR were also able to correctly classify the B-samples and both methods showed a Pearson's correlation coefficient of 0.81. An asset of the PT and CC method is the additional qualitative characterization of granule size distribution that can help to better understand and optimise general process operation (cyclone operation duration and construction characteristics). In combination these two methods were able to elucidate the relationship of gross granule volume and actual biomass, excluding the dead volume of inner cavities and exopolymers. We found a linear sphere-equivalent-radius correction factor (3.96 ± 0.15) for investigated anammox granules, that can be used for the fast and reliable PT technique to avoid biomass overestimation. We also recommend routine HQ and PT analysis as ideal monitoring strategy for anammox abundance in wastewater facilities with the HQ technique entailing the further advantage of being also suited for non-granular anammox biomass.