Dynamics of bacterial communities during the ripening process of different Croatian cheese types derived from raw ewe's milk cheeses.

Microbial communities play an important role in cheese ripening and determine the flavor and taste of different cheese types to a large extent. However, under adverse conditions human pathogens may colonize cheese samples during ripening and may thus cause severe outbreaks of diarrhoea and other diseases. Therefore in the present study we investigated the bacterial community structure of three raw ewe's milk cheese types, which are produced without the application of starter cultures during ripening from two production sites based on fingerprinting in combination with next generation sequencing of 16S rRNA gene amplicons. Overall a surprisingly high diversity was found in the analyzed samples and overall up to 213 OTU97 could be assigned. 20 of the major OTUs were present in all samples and include mostly lactic acid bacteria (LAB), mainly Lactococcus, and Enterococcus species. Abundance and diversity of these genera differed to a large extent between the 3 investigated cheese types and in response to the ripening process. Also a large number of non LAB genera could be identified based on phylogenetic alignments including mainly Enterobacteriaceae and Staphylococcacae. Some species belonging to these two families could be clearly assigned to species which are known as potential human pathogens like Staphylococcus saprophyticus or Salmonella spp. However, during cheese ripening their abundance was reduced. The bacterial genera, namely Lactobacillus, Streptococcus, Leuconostoc, Bifidobacterium, Brevibacterium, Corynebacterium, Clostridium, Staphylococcus, Thermoanerobacterium, E. coli, Hafnia, Pseudomonas, Janthinobacterium, Petrotoga, Kosmotoga, Megasphaera, Macrococcus, Mannheimia, Aerococcus, Vagococcus, Weissella and Pediococcus were identified at a relative low level and only in selected samples. Overall the microbial composition of the used milk and the management of the production units determined the bacterial community composition for all cheese types to a large extend, also at the late time points of cheese ripening

Relative abundance (%) of sequences which could be assigned to genus level (OTU₉₅; about 60000 reads in total)) in three Croatian raw ewe's milk cheeses (Cheese A, B and C) based on partial sequence analysis of the 16S rRNA gene gene after direct DNA extraction and PCR amplification.

<p>Samples were taken from two production sites (F1 and F2). The numbers on x- axis represents ripening time in days: 0d, 45d and 90d.</p

Rarefaction curves of partial sequences of the bacterial 16S rRNA gene after direct DNA extraction and PCR amplification from three Croatian raw ewe's milk cheeses (Cheese A, B and C) throughout the ripening period (0, 45 and 90d) obtained from two production sites (F1 and F2) at a 97% similarity level normalized with respect to sample size.

<p>As the most variability were related to F2 only those results are presented.</p

Venn diagram showing the number of specific and common OTUs (OTU₉₇) between three Croatian raw ewés milk cheeses (Cheese A, B and C) obtained from two production sites (F1 and F2) throughout the ripening period (0, 45 and 90d) based on partial sequence analysis of the 16S rRNA gene after direct DNA extraction and PCR amplification.

<p>Venn diagram showing the number of specific and common OTUs (OTU₉₇) between three Croatian raw ewés milk cheeses (Cheese A, B and C) obtained from two production sites (F1 and F2) throughout the ripening period (0, 45 and 90d) based on partial sequence analysis of the 16S rRNA gene after direct DNA extraction and PCR amplification.</p

Relative abundance (%) of bacterial species OTUs (OTU₉₇) during different time points of ripening (0d, 45d, 90d) of three different Croatian raw ewe's milk cheeses (Cheese A, B and C) obtained from two different farms (F1 and F2) based on partial sequencing of the 16S rRNA gene after direct DNA extraction and PCR amplification. “n” indicates the number of analyzed reads.

<p>Relative abundance (%) of bacterial species OTUs (OTU₉₇) during different time points of ripening (0d, 45d, 90d) of three different Croatian raw ewe's milk cheeses (Cheese A, B and C) obtained from two different farms (F1 and F2) based on partial sequencing of the 16S rRNA gene after direct DNA extraction and PCR amplification. “n” indicates the number of analyzed reads.</p

Liver-Kidney-on-Chip To Study Toxicity of Drug Metabolites

Advances in organ-on-chip technologies for the application in in vitro drug development provide an attractive alternative approach to replace ethically controversial animal testing and to establish a basis for accelerated drug development. In recent years, various chip-based tissue culture systems have been developed, which are mostly optimized for cultivation of one single cell type or organoid structure and lack the representation of multi organ interactions. Here we present an optimized microfluidic chip design consisting of interconnected compartments, which provides the possibility to mimic the exchange between different organ specific cell types and enables to study interdependent cellular responses between organs and demonstrate that such tandem system can greatly improve the reproducibility and efficiency of toxicity studies. In a simplified liver-kidney-on-chip model, we showed that hepatic cells that grow in microfluidic conditions abundantly and stably expressed metabolism-related biomarkers. Moreover, we applied this system for investigating the biotransformation and toxicity of Aflatoxin B1 (AFB1) and Benzoalphapyrene (BαP), as well as the interaction with other chemicals. The results clearly demonstrate that the toxicity and metabolic response to drugs can be evaluated in a flow-dependent manner within our system, supporting the importance of advanced interconnected multiorgans in microfluidic devices for application in in vitro toxicity testing and as optimized tissue culture systems for in vitro drug screening