Meat species authentication in food is most commonly based on the detection of genetic variations. Official food control laboratories frequently apply single and multiplex real-time polymerase chain reaction (PCR) assays and/or DNA arrays. However, in the near future, DNA metabarcoding, the generation of PCR products for DNA barcodes, followed by massively parallel sequencing by next generation sequencing (NGS) technologies, could be an attractive alternative. DNA metabarcoding is superior to well-established methodologies since it allows simultaneous identification of a wide variety of species not only in individual foodstuffs but even in complex mixtures. We have recently published a DNA metabarcoding assay for the identification and differentiation of 15 mammalian species and six poultry species. With the aim to harmonize analytical methods for food authentication across EU Member States, the DNA metabarcoding assay has been tested in an interlaboratory ring trial including 15 laboratories. Each laboratory analyzed 16 anonymously labelled samples (eight samples, two subsamples each), comprising six DNA extract mixtures, one DNA extract from a model sausage, and one DNA extract from maize (negative control). Evaluation of data on repeatability, reproducibility, robustness, and measurement uncertainty indicated that the DNA metabarcoding method is applicable for meat species authentication in routine analysis.

The EU commission established Regulation (2017/1495) in 2017 to reduce Campylobacter on chicken skin and to decrease the number of human cases of campylobacteriosis attributable to the consumption of poultry meat. A Process Hygiene Criterion based on colony-forming unit data was set to a maximum of 1000 CFU Campylobacter spp. per gram chicken neck skin at slaughterhouses. Confronted with stressors, including cold, oxidative stress or antibiotic treatment, live cells may enter into a viable but non-cultivable state (VBNC) and lose the ability to grow, in reference to the plate count ISO 10272-2:2017 method, but still possess the potential to recover and cause infections under favorable conditions. In this study, a droplet digital PCR combined with the intercalating dye propidium monoazide (PMA) was established for quantification of C. coli and C. jejuni in chicken meat rinses. The PMA was used to inactivate DNA from dead cells in this technique. This method was successfully validated against the reference method according to ISO 16140-2:2016 for accuracy and relative trueness. Additionally, it presented a 100% selectivity for Campylobacter jejuni and C. coli. Moreover, the technical measurement uncertainty was determined according to ISO 19036:2019, and the applicability of ddPCR for quantifying C. coli and C. jejuni in chicken meat rinses was investigated on naturally contaminated samples from slaughterhouses and supermarkets. Results obtained from this study demonstrated a strong correlation to qPCR as well as the classical microbiological reference method.

Game meat products are particularly prone to be adulterated by replacing game meat with cheaper meat species. Recently, we have presented a real-time polymerase chain reaction (PCR) assay for the identification and quantification of roe deer in food. Quantification of the roe deer content in % (w/w) was achieved relatively by subjecting the DNA isolates to a reference real-time PCR assay in addition to the real-time PCR assay for roe deer. Aiming at harmonizing analytical methods for food authentication across EU Member States, the real-time PCR assay for roe deer has been tested in an interlaboratory ring trial including 14 laboratories from Austria, Germany, and Switzerland. Participating laboratories obtained aliquots of DNA isolates from a meat mixture containing 24.8% (w/w) roe deer in pork, roe deer meat, and 12 meat samples whose roe deer content was not disclosed. Performance characteristics included amplification efficiency, level of detection (LOD_95%), repeatability, reproducibility, and accuracy of quantitative results. With a relative reproducibility standard deviation ranging from 13.35 to 25.08% (after outlier removal) and recoveries ranging from 84.4 to 114.3%, the real-time PCR assay was found to be applicable for the detection and quantification of roe deer in raw meat samples to detect food adulteration.

Background: Measurement uncertainty is typically expressed in terms of a symmetric interval y±U, where y denotes the measurement result and U the expanded uncertainty. However, in the case of heteroscedasticity, symmetric uncertainty intervals can be misleading. In this paper, a different approach for the calculation of uncertainty intervals is introduced. Methods: This approach is applicable when a validation study has been conducted with samples with known concentrations. In a first step, test results are obtained at the different known concentration levels. Then, on the basis of precision estimates, a prediction range is calculated. The measurement uncertainty for a given test result can then be obtained by projecting the intersection of the test result with the limits of the prediction range back onto the axis of the known values, now interpreted as representing the measurand. Results: It will be shown how, under certain circumstances, asymmetric uncertainty intervals arise quite naturally and lead to more reliable uncertainty intervals. Conclusions: This article establishes a conceptual framework in which measurement uncertainty can be derived from precision whenever the relationship between the latter and concentration has been characterized. This approach is applicable for different types of distributions. Closed expressions for the limits of the uncertainty interval are provided for the simple case of normally distributed test results and constant relative standard deviation.

Background: Severe coronavirus disease 2019 (COVID-19) disease courses are characterized by immuno-inflammatory, thrombotic, and parenchymal alterations. Prediction of individual COVID-19 disease courses to guide targeted prevention remains challenging. We hypothesized that a distinct serologic signature precedes surges of IL-6/D-dimers in severely affected COVID-19 patients. Methods: We performed longitudinal plasma profiling, including proteome, metabolome, and routine biochemistry, on seven seropositive, well-phenotyped patients with severe COVID-19 referred to the Intensive Care Unit at the German Heart Center. Patient characteristics were: 65 ± 8 years, 29% female, median CRP 285 ± 127 mg/dL, IL-6 367 ± 231 ng/L, D-dimers 7 ± 10 mg/L, and NT-proBNP 2616 ± 3465 ng/L. Results: Based on time-series analyses of patient sera, a prediction model employing feature selection and dimensionality reduction through least absolute shrinkage and selection operator (LASSO) revealed a number of candidate proteins preceding hyperinflammatory immune response (denoted ΔIL-6) and COVID-19 coagulopathy (denoted ΔD-dimers) by 24–48 h. These candidates are involved in biological pathways such as oxidative stress/inflammation (e.g., IL-1alpha, IL-13, MMP9, C-C motif chemokine 23), coagulation/thrombosis/immunoadhesion (e.g., P- and E-selectin), tissue repair (e.g., hepatocyte growth factor), and growth factor response/regulatory pathways (e.g., tyrosine-protein kinase receptor UFO and low-density lipoprotein receptor (LDLR)). The latter are host- or co-receptors that promote SARS-CoV-2 entry into cells in the absence of ACE2. Conclusions: Our novel prediction model identified biological and regulatory candidate networks preceding hyperinflammation and coagulopathy, with the most promising group being the proteins that explain changes in D-dimers. These biomarkers need validation. If causal, our work may help predict disease courses and guide personalized treatment for COVID-19.

Through its suggestive name, non-targeted methods (NTMs) do not aim at a predefined "needle in the haystack". Instead, they exploit all the constituents of the haystack. This new form of analytical methods is increasingly finding applications in food and feed testing. However, the concepts, terms, and considerations related to this burgeoning field of analytical testing needs to be propagated for the benefit of ones associated in academic research, commercial development, and official control. This paper addresses the frequently asked questions around notations and terminologies surrounding NTMs. The widespread development and adoption of these methods also necessitates the need to develop approaches to NTM validation, i.e., evaluating the performance characteristics of a method to determine if it is fit-for-purpose. This work aims to provide a roadmap to approaching NTM validation. In doing so, the paper deliberates on the different considerations that influence the approach to validation and provides suggestions thereof.