MAATrica: a measure for assessing consistency and methods in medicinal and nutraceutical chemistry papers.

The growing number of scientific papers and document sources underscores the need for methods capable of evaluating the quality of publications. Researchers who are looking for relevant papers for their studies need ways to assess the scientific value of these documents. One approach involves using semantic search engines that can automatically extract important knowledge from the growing body of text. In this study, we introduce a new metric called "MAATrica," which serves as the foundation for an innovative method designed to evaluate research papers. MAATrica offers a new way to analyze and categorize text, focusing on the consistency of research documents in the life sciences, particularly in the fields of medicinal and nutraceutical chemistry. This method utilizes semantic descriptions to cover in silico experiments, as well as in vitro and in vivo essays. Created to aid in evaluation processes like peer review, MAATrica uses toolkits and semantic applications to build the proposed measure, identify scientific entities, and gather information. We have applied MAATrica to roughly 90,000 papers and present our findings here.

New RT-PCR Assay for the Detection of Current and Future SARS-CoV-2 Variants.

Multiple lineages of SARS-CoV-2 have been identified featuring distinct sets of genetic changes that confer to the virus higher transmissibility and ability to evade existing immunity. The continuous evolution of SARS-CoV-2 may pose challenges for current treatment options and diagnostic tools. In this study, we have first evaluated the performance of the 14 WHO-recommended real-time reverse transcription (RT)-PCR assays currently in use for the detection of SARS-CoV-2 and found that only one assay has reduced performance against Omicron. We then developed a new duplex real-time RT-PCR assay based on the amplification of two ultra-conserved elements present within the SARS-CoV-2 genome. The new duplex assay successfully detects all of the tested SARS-CoV-2 variants of concern (including Omicron sub-lineages BA.4 and BA.5) from both clinical and wastewater samples with high sensitivity and specificity. The assay also functions as a one-step droplet digital RT-PCR assay. This new assay, in addition to clinical testing, could be adopted in surveillance programs for the routine monitoring of SARS-CoV-2's presence in a population in wastewater samples. Positive results with our assay in conjunction with negative results from an Omicron-specific assay may provide timely indication of the emergence of a novel SARS-CoV-2 variant in a certain community and thereby aid public health interventions.

A qualitative RT-PCR assay for the specific identification of the SARS-CoV-2 B.1.1.529 (Omicron) Variant of Concern.

OBJECTIVES: The aim of this study was to develop a RT-PCR assay for the specific detection of the SARS-CoV-2 Omicron Variant of Concern (VOC) as a rapid alternative to sequencing. METHODS: A RT-PCR was designed in silico and then validated using characterised clinical samples containing Omicron (both BA.1 and BA.2 lineages) and the Omicron synthetic RNA genome. As negative controls, SARS-CoV-2 positive clinical samples collected in May 2020, and synthetic RNA genomes of the isolate Wuhan Hu-1 and of the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Kappa (B.1.617.1), Iota (B.1.526), Epsilon (B.1.429) and Delta (B.1.617.2) SARS-CoV-2 VOC were used. RESULTS: Experiments performed using as templates the synthetic RNA genomes demonstrate the high specificity of the PCR-method for the SARS-CoV-2 Omicron. Despite the synthetic RNAs were used at high copy numbers, specific signal was mainly detected with the Omicron synthetic genome. Only a non-specific late signal was detected using the Alpha variant genome, but these results were considered negligible as Alpha VOC has been replaced by the Delta and it is not circulating anymore in the world. Using our method, we confirmed the presence of Omicron on clinical samples containing this variant but not of other SARS-CoV-2 lineages. The method is highly sensitive and can detect up to 1 cp of the Omicron virus per µl. CONCLUSIONS: The method presented here, in combination with other methods in use for detection of SARS-CoV-2, can be used for an early identification of Omicron.

Effects of spike protein and toxin-like peptides found in COVID-19 patients on human 3D neuronal/glial model undergoing differentiation: Possible implications for SARS-CoV-2 impact on brain development.

The possible neurodevelopmental consequences of SARS-CoV-2 infection are presently unknown. In utero exposure to SARS-CoV-2 has been hypothesized to affect the developing brain, possibly disrupting neurodevelopment of children. Spike protein interactors, such as ACE2, have been found expressed in the fetal brain, and could play a role in potential SARS-CoV-2 fetal brain pathogenesis. Apart from the possible direct involvement of SARS-CoV-2 or its specific viral components in the occurrence of neurological and neurodevelopmental manifestations, we recently reported the presence of toxin-like peptides in plasma, urine and fecal samples specifically from COVID-19 patients. In this study, we investigated the possible neurotoxic effects elicited upon 72-hour exposure to human relevant levels of recombinant spike protein, toxin-like peptides found in COVID-19 patients, as well as a combination of both in 3D human iPSC-derived neural stem cells differentiated for either 2 weeks (short-term) or 8 weeks (long-term, 2 weeks in suspension + 6 weeks on MEA) towards neurons/glia. Whole transcriptome and qPCR analysis revealed that spike protein and toxin-like peptides at non-cytotoxic concentrations differentially perturb the expression of SPHK1, ELN, GASK1B, HEY1, UTS2, ACE2 and some neuronal-, glia- and NSC-related genes critical during brain development. Additionally, exposure to spike protein caused a decrease of spontaneous electrical activity after two days in long-term differentiated cultures. The perturbations of these neurodevelopmental endpoints are discussed in the context of recent knowledge about the key events described in Adverse Outcome Pathways relevant to COVID-19, gathered in the context of the CIAO project (https://www.ciao-covid.net/).

Increase of SARS-CoV-2 RNA load in faecal samples prompts for rethinking of SARS-CoV-2 biology and COVID-19 epidemiology.

Background Scientific evidence for the involvement of human microbiota in the development of COVID-19 disease has been reported recently. SARS-CoV-2 RNA presence in human faecal samples and SARS-CoV-2 activity in faeces from COVID-19 patients have been observed. Methods Starting from these observations, an experimental design was developed to cultivate in vitro faecal microbiota from infected individuals, to monitor the presence of SARS-CoV-2, and to collect data on the relationship between faecal bacteria and the virus. Results Our results indicate that SARS-CoV-2 replicates in vitro in bacterial growth medium, that the viral replication follows bacterial growth and it is influenced by the administration of specific antibiotics. SARS-CoV-2-related peptides have been detected in 30-day bacterial cultures and characterised. Discussion Our observations are compatible with a 'bacteriophage-like' behaviour of SARS-CoV-2, which, to our knowledge has not been observed or described before. These results are unexpected and hint towards a novel hypothesis on the biology of SARS-CoV-2 and on the COVID-19 epidemiology. The discovery of possible new modes of action of SARS-CoV-2 has far-reaching implications for the prevention and the treatment of the disease.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing.

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain "live" (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines' implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

Toxin-like peptides in plasma, urine and faecal samples from COVID-19 patients.

Background: SARS-CoV-2 that causes COVID-19 disease and led to the pandemic currently affecting the world has been broadly investigated. Different studies have been performed to understand the infection mechanism, and the involved human genes, transcripts and proteins. In parallel, numerous clinical extra-pulmonary manifestations co-occurring with COVID-19 disease have been reported and evidence of their severity and persistence is increasing. Whether these manifestations are linked to other disorders co-occurring with SARS-CoV-2 infection, is under discussion. In this work, we report the identification of toxin-like peptides in COVID-19 patients by application of the Liquid Chromatography Surface-Activated Chemical Ionization - Cloud Ion Mobility Mass Spectrometry.   Methods: Plasma, urine and faecal samples from COVID-19 patients and control individuals were analysed to study peptidomic toxins' profiles. Protein precipitation preparation procedure was used for plasma, to remove high molecular weight proteins and efficiently solubilize the peptide fraction; in the case of faeces and urine, direct peptide solubilization was employed.   Results: Toxin-like peptides, almost identical to toxic components of venoms from animals, like conotoxins, phospholipases, phosphodiesterases, zinc metal proteinases, and bradykinins, were identified in samples from COVID-19 patients, but not in control samples.  Conclusions: The presence of toxin-like peptides could potentially be connected to SARS-CoV-2 infection. Their presence suggests a possible association between COVID-19 disease and the release in the body of (oligo-)peptides almost identical to toxic components of venoms from animals. Their involvement in a large set of heterogeneous extra-pulmonary COVID-19 clinical manifestations, like neurological ones, cannot be excluded. Although the presence of each individual symptom is not selective of the disease, their combination might be related to COVID-19 by the coexistence of the panel of the here detected toxin-like peptides. The presence of these peptides opens new scenarios on the aetiology of the COVID-19 clinical symptoms observed up to now, including neurological manifestations.

The EU one-stop-shop collection of publicly available information on COVID-19 in vitro diagnostic medical devices.

The JRC COVID-19 In Vitro Diagnostic Devices and Test Methods Database, aimed to collect in a single place all publicly available information on performance of CE-marked in vitro diagnostic medical devices (IVDs) as well as in house laboratory-developed devices and related test methods for COVID-19, is here presented. The database, manually curated and regularly updated, has been developed as a follow-up to the Communication from the European Commission "Guidelines on in vitro diagnostic tests and their performance" of 15 April 2020 and is freely accessible at https://covid-19-diagnostics.jrc.ec.europa.eu/.

Novel nuclear barcode regions for the identification of flatfish species.

The development of an efficient seafood traceability framework is crucial for the management of sustainable fisheries and the monitoring of potential substitution fraud across the food chain. Recent studies have shown the potential of DNA barcoding methods in this framework, with most of the efforts focusing on using mitochondrial targets such as the cytochrome oxidase 1 and cytochrome b genes. In this article, we show the identification of novel targets in the nuclear genome, and their associated primers, to be used for the efficient identification of flatfishes of the Pleuronectidae family. In addition, different in silico methods are described to generate a dataset of barcode reference sequences from the ever-growing wealth of publicly available sequence information, replacing, where possible, labour-intensive laboratory work. The short amplicon lengths render the analysis of these new barcode target regions ideally suited to next-generation sequencing techniques, allowing characterisation of multiple fish species in mixed and processed samples. Their location in the nucleus also improves currently used methods by allowing the identification of hybrid individuals.

Development and applicability of a ready-to-use PCR system for GMO screening.

With the growing number of GMOs introduced to the market, testing laboratories have seen their workload increase significantly. Ready-to-use multi-target PCR-based detection systems, such as pre-spotted plates (PSP), reduce analysis time while increasing capacity. This paper describes the development and applicability to GMO testing of a screening strategy involving a PSP and its associated web-based Decision Support System. The screening PSP was developed to detect all GMOs authorized in the EU in one single PCR experiment, through the combination of 16 validated assays. The screening strategy was successfully challenged in a wide inter-laboratory study on real-life food/feed samples. The positive outcome of this study could result in the adoption of a PSP screening strategy across the EU; a step that would increase harmonization and quality of GMO testing in the EU. Furthermore, this system could represent a model for other official control areas where high-throughput DNA-based detection systems are needed.

Towards Plant Species Identification in Complex Samples: A Bioinformatics Pipeline for the Identification of Novel Nuclear Barcode Candidates.

Monitoring of the food chain to fight fraud and protect consumer health relies on the availability of methods to correctly identify the species present in samples, for which DNA barcoding is a promising candidate. The nuclear genome is a rich potential source of barcode targets, but has been relatively unexploited until now. Here, we show the development and use of a bioinformatics pipeline that processes available genome sequences to automatically screen large numbers of input candidates, identifies novel nuclear barcode targets and designs associated primer pairs, according to a specific set of requirements. We applied this pipeline to identify novel barcodes for plant species, a kingdom for which the currently available solutions are known to be insufficient. We tested one of the identified primer pairs and show its capability to correctly identify the plant species in simple and complex samples, validating the output of our approach.

New approaches in GMO detection.

The steady rate of development and diffusion of genetically modified plants and their increasing diversification of characteristics, genes and genetic control elements poses a challenge in analysis of genetically modified organisms (GMOs). It is expected that in the near future the picture will be even more complex. Traditional approaches, mostly based on the sequential detection of one target at a time, or on a limited multiplexing, allowing only a few targets to be analysed at once, no longer meet the testing requirements. Along with new analytical technologies, new approaches for the detection of GMOs authorized for commercial purposes in various countries have been developed that rely on (1) a smart and accurate strategy for target selection, (2) the use of high-throughput systems or platforms for the detection of multiple targets and (3) algorithms that allow the conversion of analytical results into an indication of the presence of individual GMOs potentially present in an unknown sample. This paper reviews the latest progress made in GMO analysis, taking examples from the most recently developed strategies and tools, and addresses some of the critical aspects related to these approaches.

Molecular toolbox for the identification of unknown genetically modified organisms.

Competent laboratories monitor genetically modified organisms (GMOs) and products derived thereof in the food and feed chain in the framework of labeling and traceability legislation. In addition, screening is performed to detect the unauthorized presence of GMOs including asynchronously authorized GMOs or GMOs that are not officially registered for commercialization (unknown GMOs). Currently, unauthorized or unknown events are detected by screening blind samples for commonly used transgenic elements, such as p35S or t-nos. If (1) positive detection of such screening elements shows the presence of transgenic material and (2) all known GMOs are tested by event-specific methods but are not detected, then the presence of an unknown GMO is inferred. However, such evidence is indirect because it is based on negative observations and inconclusive because the procedure does not identify the causative event per se. In addition, detection of unknown events is hampered in products that also contain known authorized events. Here, we outline alternative approaches for analytical detection and GMO identification and develop new methods to complement the existing routine screening procedure. We developed a fluorescent anchor-polymerase chain reaction (PCR) method for the identification of the sequences flanking the p35S and t-nos screening elements. Thus, anchor-PCR fingerprinting allows the detection of unique discriminative signals per event. In addition, we established a collection of in silico calculated fingerprints of known events to support interpretation of experimentally generated anchor-PCR GM fingerprints of blind samples. Here, we first describe the molecular characterization of a novel GMO, which expresses recombinant human intrinsic factor in Arabidopsis thaliana. Next, we purposefully treated the novel GMO as a blind sample to simulate how the new methods lead to the molecular identification of a novel unknown event without prior knowledge of its transgene sequence. The results demonstrate that the new methods complement routine screening procedures by providing direct conclusive evidence and may also be useful to resolve masking of unknown events by known events.

First application of a microsphere-based immunoassay to the detection of genetically modified organisms (GMOs): quantification of Cry1Ab protein in genetically modified maize.

An innovative covalent microsphere immunoassay, based on the usage of fluorescent beads coupled to a specific antibody, was developed for the quantification of the endotoxin Cry1Ab present in MON810 and Bt11 genetically modified (GM) maize lines. In particular, a specific protocol was developed to assess the presence of Cry1Ab in a very broad range of GM maize concentrations, from 0.1 to 100% [weight of genetically modified organism (GMO)/weight]. Test linearity was achieved in the range of values from 0.1 to 3%, whereas fluorescence signal increased following a nonlinear model, reaching a plateau at 25%. The limits of detection and quantification were equal to 0.018 and 0.054%, respectively. The present study describes the first application of quantitative high-throughput immunoassays in GMO analysis.

Real-time polymerase chain reaction-based approach for quantification of the pat gene in the T25 Zea mays event.

In Europe, a growing interest for reliable techniques for the quantification of genetically modified component(s) of food matrixes is arising from the need to comply with the European legislative framework on novel food products. Real-time polymerase chain reaction (PCR) is currently the most powerful technique for the quantification of specific nucleic acid sequences. Several real-time PCR methodologies based on different molecular principles have been developed for this purpose. The most frequently used approach in the field of genetically modified organism (GMO) quantification in food or feed samples is based on the 5'-3'-exonuclease activity of Taq DNA polymerase on specific degradation probes (TaqMan principle). A novel approach was developed for the establishment of a TaqMan quantification system assessing GMO contents around the 1% threshold stipulated under European Union (EU) legislation for the labeling of food products. The Zea mays T25 elite event was chosen as a model for the development of the novel GMO quantification approach. The most innovative aspect of the system is represented by the use of sequences cloned in plasmids as reference standards. In the field of GMO quantification, plasmids are an easy to use, cheap, and reliable alternative to Certified Reference Materials (CRMs), which are only available for a few of the GMOs authorized in Europe, have a relatively high production cost, and require further processing to be suitable for analysis. Strengths and weaknesses of the use of novel plasmid-based standards are addressed in detail. In addition, the quantification system was designed to avoid the use of a reference gene (e.g., a single copy, species-specific gene) as normalizer, i.e., to perform a GMO quantification based on an absolute instead of a relative measurement. In fact, experimental evidences show that the use of reference genes adds variability to the measurement system because a second independent real-time PCR-based measurement must be performed. Moreover, for some reference genes no sufficient information on copy number in and among genomes of different lines is available, making adequate quantification difficult. Once developed, the method was subsequently validated according to IUPAC and ISO 5725 guidelines. Thirteen laboratories from 8 EU countries participated in the trial. Eleven laboratories provided results complying with the predefined study requirements. Repeatability (RSDr) values ranged from 8.7 to 15.9%, with a mean value of 12%. Reproducibility (RSDR) values ranged from 16.3 to 25.5%, with a mean value of 21%. Following Codex Alimentarius Committee guidelines, both the limits of detection and quantitation were determined to be <0.1%.

Antiviral and Antiviroid Activity of MAP-Containing Extracts from Mirabilis jalapa Roots.

Extracts of Mirabilis jalapa (Nyctaginaceae), containing a ribosome inactivating protein (RIP) called Mirabilis antiviral protein (MAP), were tested against infection by potato virus X, potato virus Y, potato leaf roll virus, and potato spindle tuber viroid. Root extracts of M. jalapa sprayed on test plants 24 h before virus or viroid inoculation inhibited infection by almost 100%, as corroborated by infectivity assays and the nucleic acid spot hybridization test. Antiviral activity of MAP extracts was observed against mechanically transmitted viruses but not against aphid-transmitted viruses. Purified MAP showed the same antiviral effect as the crude extracts.