Diet and lifestyle have a strong influence on gut microbiota, which in turn has important implications on a variety of health-related aspects. Despite great advances in the field, it remains unclear to which extent the composition of the gut microbiota is modulated by the intake of animal derived products, compared to a vegetable based diet. Here the specific impact of vegan, vegetarian, and omnivore feeding type on the composition of gut microbiota of 101 adults was investigated among groups homogeneous for variables known to have a role in modulating gut microbial composition such as age, anthropometric variables, ethnicity, and geographic area. The results displayed a picture where the three different dietetic profiles could be well distinguished on the basis of participant’s dietetic regimen. Regarding the gut microbiota; vegetarians had a significantly greater richness compared to omnivorous. Moreover, counts of Bacteroidetes related operational taxonomic units (OTUs) were greater in vegans and vegetarians compared to omnivores. Interestingly considering the whole bacterial community composition the three cohorts were unexpectedly similar, which is probably due to their common intake in terms of nutrients rather than food, e.g., high fat content and reduced protein and carbohydrate intake. This finding suggests that fundamental nutritional choices such as vegan, vegetarian, or omnivore do influence the microbiota but do not allow to infer conclusions on gut microbial composition, and suggested the possibility for a preferential impact of other variables, probably related to the general life style on shaping human gut microbial community in spite of dietary influence. Consequently, research were individuals are categorized on the basis of their claimed feeding types is of limited use for scientific studies, since it appears to be oversimplified.

Single cell RNA-seq (scRNA-seq) count data show many differences compared with bulk RNA-seq count data, making the application of many RNA-seq pre-processing/analysis methods not straightforward or even inappropriate. For this reason, the development of new methods for handling scRNA-seq count data is currently one of the most active research fields in bioinformatics. To help the development of such new methods, the availability of simulated data could play a pivotal role. However, only few scRNA-seq count data simulators are available, often showing poor or not demonstrated similarity with real data. In this article we present SPARSim, a scRNA-seq count data simulator based on a Gamma-Multivariate Hypergeometric model. We demonstrate that SPARSim allows to generate count data that resemble real data in terms of count intensity, variability and sparsity, performing comparably or better than one of the most used scRNA-seq simulator, Splat. In particular, SPARSim simulated count matrices well resemble the distribution of zeros across different expression intensities observed in real count data. SPARSim R package is freely available at http://sysbiobig.dei.unipd.it/? q=SPARSim and at https://gitlab.com/sysbiobig/sparsim. Supplementary data are available at Bioinformatics online.

Migration of nanomaterials from food containers into food is a matter of concern because of the potential risk for exposed consumers. The aims of this study were to evaluate silver migration from a commercially available food packaging containing silver nanoparticles into a real food matrix (chicken meat) under plausible domestic storage conditions and to test the contribution of such packaging to limit food spoilage bacteria proliferation. Chemical analysis revealed the absence of silver in chicken meatballs under the experimental conditions in compliance with current European Union legislation, which establishes a maximum level of 0.010 mg kg^–1 for the migration of non-authorised substances through a functional barrier (Commission Regulation (EU) No. 10/2011). On the other hand, microbiological tests (total microbial count, Pseudomonas spp. and Enterobacteriaceae) showed no relevant difference in the tested bacteria levels between meatballs stored in silver-nanoparticle plastic bags or control bags. This study shows the importance of testing food packaging not only to verify potential silver migration as an indicator of potential nanoparticle migration, but also to evaluate the benefits in terms of food preservation so as to avoid unjustified usage of silver nanoparticles and possible negative impacts on the environment.

Listeria monocytogenes is a serious foodborne pathogen that can contaminate food during processing and can grow during food shelf-life. New types of safe and effective food contact materials embedding antimicrobial agents, like silver, can play an important role in the food industry. The present work aimed at evaluating the in vitro growth kinetics of different strains of L. monocytogenes in the presence of silver, both in its ionic and nano form. The antimicrobial effect was determined by assaying the number of culturable bacterial cells, which formed colonies after incubation in the presence of silver nanoparticles (AgNPs) or silver nitrate (AgNO3). Ionic release experiments were performed in parallel. A different reduction of bacterial viability between silver ionic and nano forms was observed, with a time delayed effect exerted by AgNPs. An association between antimicrobial activity and ions concentration was shown by both silver chemical forms, suggesting the major role of ions in the antimicrobial mode of action.

Background: In the last few years, 16S rRNA gene sequencing (16S rDNA-seq) has seen a surprisingly rapid increase in election rate as a methodology to perform microbial community studies. Despite the considerable popularity of this technique, an exiguous number of specific tools are currently available for proper 16S rDNA-seq count data preprocessing and simulation. Indeed, the great majority of tools have been developed adapting methodologies previously used for bulk RNA-seq data, with poor assessment of their applicability in the metagenomics field. For such tools and the few ones specifically developed for 16S rDNA-seq data, performance assessment is challenging, mainly due to the complex nature of the data and the lack of realistic simulation models. In fact, to the best of our knowledge, no software thought for data simulation are available to directly obtain synthetic 16S rDNA-seq count tables that properly model heavy sparsity and compositionality typical of these data.Results: In this paper we present metaSPARSim, a sparse count matrix simulator intended for usage in development of 16S rDNA-seq metagenomic data processing pipelines. metaSPARSim implements a new generative process that models the sequencing process with a Multivariate Hypergeometric distribution in order to realistically simulate 16S rDNA-seq count table, resembling real experimental data compositionality and sparsity. It provides ready-to-use count matrices and comes with the possibility to reproduce different pre-coded scenarios and to estimate simulation parameters from real experimental data. The tool is made available athttp://sysbiobig.dei.unipd.it/?q=Software#metaSPARSimandhttps://gitlab.com/sysbiobig/metasparsim.Conclusion: metaSPARSim is able to generate count matrices resembling real 16S rDNA-seq data. The availability of count data simulators is extremely valuable both for methods developers, for which a ground truth for tools validation is needed, and for users who want to assess state of the art analysis tools for choosing the most accurate one. Thus, we believe that metaSPARSim is a valuable tool for researchers involved in developing, testing and using robust and reliable data analysis methods in the context of 16S rRNA gene sequencing.

Vegetables are an important source of nutrients, but they can host a large microbial population, particularly bacteria. Vegetables are an important source of nutrients, but they can host a large microbial population, particularly bacteria. Foodborne pathogens can contaminate raw vegetables at any stage of their production process with a potential for human infection. Appropriate washing can mitigate the risk of foodborne illness consequent to vegetable consumption by reducing pathogen levels, but few data are available to assess the efficacy of different practices. In the present work, six different washing methods, in the presence or absence of sanitisers (peracetic acid and percitric acid, sodium bicarbonate, sodium hypochlorite) and vinegar, were tested for their effectiveness in reducing Salmonella and Listeria counts after artificial contamination of raw rocket (Eruca vescicaria). Results showed that washing with sodium hypochlorite (200 mg/L) was the only method able to produce a significant 2 Log reduction of Salmonella counts, but only in the case of high initial contamination (7 Log CFU/g), suggesting potential harmful effects for consumers could occur. In the case of Listeria monocytogenes, all the examined washing methods were effective, with 200 mg/L sodium hypochlorite solution and a solution of peracetic and percitric acids displaying the best performances (2 and 1.5 Log reductions, respectively). This highlights the importance of targeting consumers on fit for purpose and safe washing practices to circumvent vegetable contamination by foodborne pathogens.