One of the main goals of the quality control evaluation is to identify contaminants in raw material, or contamination after a food is processed and before it is placed on the market. During the treatment processes, contamination, both accidental and economically motivated, can generate incongruence between declared and real composition. In our study, we evaluated if DNA metabarcoding is a suitable tool for unveiling the composition of processed food, when it contains small trace amounts. We tested this method on different types of commercial plant products by using tnrL marker and we applied amplicon-based high-throughput sequencing techniques to identify plant components in different food products. Our results showed that DNA metabarcoding can be an effective approach for food traceability in different type of processed food. Indeed, the vast majority of our samples, we identified the species composition as the labels reported. Although some critical issues still exist, mostly deriving from the starting composition (i.e., variable complexity in taxa composition) of the sample itself and the different processing level (i.e., high or low DNA degradation), our data confirmed the potential of the DNA metabarcoding approach also in quantitative analyses for food composition quality control.

Medicinal plants have been widely used in traditional medicine due to their therapeutic properties. Although they are mostly used as herbal infusion and tincture, employment as ingredients of food supplements is increasing. However, fraud and adulteration are widespread issues. In our study, we aimed at evaluating DNA metabarcoding as a tool to identify product composition. In order to accomplish this, we analyzed fifteen commercial products with DNA metabarcoding, using two barcode regions: psbA-trnH and ITS2. Results showed that on average, 70% (44–100) of the declared ingredients have been identified. The ITS2 marker appears to identify more species (n = 60) than psbA-trnH (n = 35), with an ingredients’ identification rate of 52% versus 45%, respectively. Some species are identified only by one marker rather than the other. Additionally, in order to evaluate the quantitative ability of high-throughput sequencing (HTS) to compare the plant component to the corresponding assigned sequences, in the laboratory, we created six mock mixtures of plants starting both from biomass and gDNA. Our analysis also supports the application of DNA metabarcoding for a relative quantitative analysis. These results move towards the application of HTS analysis for studying the composition of herbal teas for medicinal plants’ traceability and quality control.

Microbial communities interact with us and affect our health in ways that are only beginning to be understood. Microorganisms have been detected in every ecosystem on Earth, as well as in any built environment that has been investigated. Drinking water sources, drinking water treatment plants and distribution systems provide peculiar microbial ecological niches, dismantling the belief of the “biological simplicity” of drinking water. Nevertheless, drinking water microbiomes are understudied compared to other microbiomes. Recent DNA sequencing and meta-omics advancements allow a deeper understanding of drinking water microbiota. Thus, moving beyond the limits of day-to-day testing for specific pathogenic microbes, new approaches aim at predicting microbiome changes driven by disturbances at the macro-scale and overtime. This will foster an effective and proactive management of water sources, improving the drinking water supply system and the monitoring activities to lower public health risk. Here, we want to give a new angle on drinking water microbiome research. Starting from a selection of 231 scientific publications on this topic, we emphasize the value of biodiversity in drinking water ecosystems and how it can be related with industrialization. We then discuss how microbiome research can support sustainable drinking water management, encouraging collaborations across sectors and involving the society through responsible research and innovation.

Habitat fragmentation affects biodiversity, but with unclear effects on pollinators and their interactions with plants in anthropized landscapes. Islands could serve as open air laboratories, suitable to disentangle how land‐use alteration impacts pollination ecology. In Maldive islands we investigated how pollinator richness, plant‐pollinator interactions and pollination efficiency are influenced by the green area fragmentation (i.e., gardens and semi‐natural patches). Moreover, we considered the mediating role of pollinator body size and the plant trait of being invasive in shaping interactions. To do this, we surveyed pollinator insects from 11 islands representing a gradient of green area fragmentation. A DNA metabarcoding approach was adopted to identify the pollen transported by pollinators and characterize the plant‐pollinator interactions. We found that intermediate levels of green area fragmentation characterized pollinator communities and increased their species richness, while decreasing interaction network complexity. Invasive plants were more frequently found on pollinator bodies than native or exotic noninvasive ones, indicating a concerningly higher potential for pollen dispersal and reproduction of the former ones. Intriguingly, pollinator body size mediated the effect of landscape alteration on interactions, as only the largest bees expanded the foraging diet in terms of plant richness in the transported pollen at increasing fragmentation. In parallel, the pollination efficiency increased with pollinator species richness in two sentinel plants. This study shows that moderate landscape fragmentation of green areas shapes many aspects of the pollination ecosystem service, where despite interactions being less complex and mediated by pollinator body size, pollinator insect biodiversity and potential plant reproduction are supported.