scholarly journals Microbiome Associated with Slovak Traditional Ewe’s Milk Lump Cheese

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1603
Author(s):  
Andrea Lauková ◽  
Lenka Micenková ◽  
Monika Pogány Simonová ◽  
Valentína Focková ◽  
Jana Ščerbová ◽  
...  
Keyword(s):  
Data Analysis ◽  
Dairy Products ◽  
Sequencing Data ◽  
Gram Negative ◽  
Ewe's Milk ◽  
Local Farm ◽  
Sequencing Data Analysis

Worldwide consumers increasingly demand traditional/local products, to which those made from ewe’s milk belong. In Slovakia, dairy products made from ewe’s milk have a long tradition. A total of seventeen farmhouse fresh ewe’s milk lump cheeses from various local farm producers in central Slovakia were sampled at farms and then analyzed. Based on the sequencing data analysis, the phylum Firmicutes dominated (60.92%) in ewe’s lump cheeses, followed with the phylum Proteobacteria (38.23%), Actinobacteria (0.38%) and Bacteroidetes (0.35%). The phylum Firmicutes was represented by six genera, among which the highest amount possessed the genus Streptococcus (41.13%) followed with the genus Lactococcus (8.54%), Fructobacillus (3.91%), Enterococcus (3.18%), Staphylococcus (1.80%) and the genus Brochotrix (0.08%). The phylum Proteobacteria in ewe’s lump cheeses involved eight Gram-negative genera: Pseudomonas, Acinetobacter, Enterobacter, Ewingella, Escherichia-Shigella, Pantoea and Moraxella. The phylum Bacteroidetes involved three genera: Bacteroides, Sphingobacterium and Chrysobacterium. Results presented are original; the microbiome of Slovak ewe’s milk lump cheese has been not analyzed at those taxonomic levels up to now.

scholarly journals Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis

Genomics ◽  
2017 ◽  
Vol 109 (2) ◽  
pp. 83-90 ◽  
Author(s):  
Yan Guo ◽  
Yulin Dai ◽  
Hui Yu ◽  
Shilin Zhao ◽  
David C. Samuels ◽  
...  
Keyword(s):  
Data Analysis ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
Sequencing Data Analysis

Systematic comparative study of computational methods for T-cell receptor sequencing data analysis

2017 ◽  
Vol 20 (1) ◽  
pp. 222-234 ◽  
Author(s):  
Saira Afzal ◽  
Irene Gil-Farina ◽  
Richard Gabriel ◽  
Shahzad Ahmad ◽  
Christof von Kalle ◽  
...  
Keyword(s):  
Data Analysis ◽  
T Cell ◽  
Comparative Study ◽  
T Cell Receptor ◽  
Computational Methods ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Sequencing Data Analysis

scholarly journals Spectacle: An interactive resource for ocular single-cell RNA sequencing data analysis

2020 ◽  
Vol 200 ◽  
pp. 108204 ◽  
Author(s):  
Andrew P. Voigt ◽  
S. Scott Whitmore ◽  
Nicholas D. Lessing ◽  
Adam P. DeLuca ◽  
Budd A. Tucker ◽  
...  
Keyword(s):  
Data Analysis ◽  
Single Cell ◽  
Rna Sequencing ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Sequencing Data Analysis

scholarly journals Immunohistochemistry and Mutation Analysis of SDHx Genes in Carotid Paragangliomas

2020 ◽  
Vol 21 (18) ◽  
pp. 6950
Author(s):  
Anastasiya V. Snezhkina ◽  
Dmitry V. Kalinin ◽  
Vladislav S. Pavlov ◽  
Elena N. Lukyanova ◽  
Alexander L. Golovyuk ◽  
...  
Keyword(s):  
Data Analysis ◽  
Genetic Testing ◽  
High Sensitivity ◽  
Sequencing Data ◽  
Mutation Status ◽  
Exome Sequencing Data ◽  
Pathogenic Variants ◽  
Positive Immunoreactivity ◽  
Carotid Paragangliomas ◽  
Sequencing Data Analysis

Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors often associated with mutations in SDHx genes. The immunohistochemistry of succinate dehydrogenase (SDH) subunits has been considered a useful instrument for the prediction of SDHx mutations in paragangliomas/pheochromocytomas. We compared the mutation status of SDHx genes with the immunohistochemical (IHC) staining of SDH subunits in CPGLs. To identify pathogenic/likely pathogenic variants in SDHx genes, exome sequencing data analysis among 42 CPGL patients was performed. IHC staining of SDH subunits was carried out for all CPGLs studied. We encountered SDHx variants in 38% (16/42) of the cases in SDHx genes. IHC showed negative (5/15) or weak diffuse (10/15) SDHB staining in most tumors with variants in any of SDHx (94%, 15/16). In SDHA-mutated CPGL, SDHA expression was completely absent and weak diffuse SDHB staining was detected. Positive immunoreactivity for all SDH subunits was found in one case with a variant in SDHD. Notably, CPGL samples without variants in SDHx also demonstrated negative (2/11) or weak diffuse (9/11) SDHB staining (42%, 11/26). Obtained results indicate that SDH immunohistochemistry does not fully reflect the presence of mutations in the genes; diagnostic effectiveness of this method was 71%. However, given the high sensitivity of SDHB immunohistochemistry, it could be used for initial identifications of patients potentially carrying SDHx mutations for recommendation of genetic testing.

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