1342 The impact of Saccharomyces cerevisiae and Lactobacillus acidophilus on colon histomorphology and gene expression in rumen and ileum tissues of young dairy calves

2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 648-649
Author(s):  
B. Fomenky ◽  
J. Chiquette ◽  
P. Y. Chouinard ◽  
É. M. Ibeagha-Awemu
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Lactobacillus Acidophilus ◽  
Dairy Calves ◽  
The Impact

scholarly journals Engineering of Promoter Replacement Cassettes for Fine-Tuning of Gene Expression in Saccharomyces cerevisiae

2006 ◽  
Vol 72 (8) ◽  
pp. 5266-5273 ◽  
Author(s):  
Elke Nevoigt ◽  
Jessica Kohnke ◽  
Curt R. Fischer ◽  
Hal Alper ◽  
Ulf Stahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Fine Tuning ◽  
Limited Information ◽  
Promoter Replacement ◽  
Pathway Gene ◽  
Glycerol Yield ◽  
Glycerol 3 Phosphate Dehydrogenase ◽  
The Impact ◽  
Mutant Promoter

ABSTRACT The strong overexpression or complete deletion of a gene gives only limited information about its control over a certain phenotype or pathway. Gene function studies based on these methods are therefore incomplete. To effect facile manipulation of gene expression across a full continuum of possible expression levels, we recently created a library of mutant promoters. Here, we provide the detailed characterization of our yeast promoter collection comprising 11 mutants of the strong constitutive Saccharomyces cerevisiae TEF1 promoter. The activities of the mutant promoters range between about 8% and 120% of the activity of the unmutated TEF1 promoter. The differences in reporter gene expression in the 11 mutants were independent of the carbon source used, and real-time PCR confirmed that these differences were due to varying levels of transcription (i.e., caused by varying promoter strengths). In addition to a CEN/ARS plasmid-based promoter collection, we also created promoter replacement cassettes. They enable genomic integration of our mutant promoter collection upstream of any given yeast gene, allowing detailed genotype-phenotype characterizations. To illustrate the utility of the method, the GPD1 promoter of S. cerevisiae was replaced by five TEF1 promoter mutants of different strengths, which allowed analysis of the impact of glycerol 3-phosphate dehydrogenase activity on the glycerol yield.

scholarly journals Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

2018 ◽  
Author(s):  
Fabien Duveau ◽  
Andrea Hodgins-Davis ◽  
Brian P.H. Metzger ◽  
Bing Yang ◽  
Stephen Tryban ◽  
...  
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Expression Level ◽  
Gene Expression Noise ◽  
Expression Levels ◽  
Fitness Effects ◽  
Expression Noise ◽  
Average Expression Level ◽  
The Difference ◽  
The Impact

AbstractGene expression noise is an evolvable property of biological systems that describes differences in gene expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by natural selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns that are consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.

scholarly journals The Utilisation of Acrylamide by Selected Microorganisms Used for Fermentation of Food

Toxics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 295
Author(s):  
Katarzyna Petka ◽  
Łukasz Wajda ◽  
Aleksandra Duda-Chodak
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Lactobacillus Acidophilus ◽  
Leuconostoc Mesenteroides ◽  
Kluyveromyces Lactis ◽  
Probiotic Strain ◽  
Carbon And Nitrogen ◽  
Beneficial Impact ◽  
The Impact ◽  
First Time ◽  
Growth Of Bacteria

Acrylamide (AA) present in food is considered a harmful compound for humans, but it exerts an impact on microorganisms too. The aim of this study was to evaluate the impact of acrylamide (at conc. 0–10 µg/mL) on the growth of bacteria (Leuconostoc mesenteroides, Lactobacillus acidophilus LA-5) and yeasts (Saccharomyces cerevisiae, Kluyveromyces lactis var. lactis), which are used for food fermentation. Moreover, we decided to verify whether these microorganisms could utilise acrylamide as a nutritional compound. Our results proved that acrylamide can stimulate the growth of L. acidophilus and K. lactis. We have, to the best of our knowledge, reported for the first time that the probiotic strain of bacteria L. acidophilus LA-5 is able to utilise acrylamide as a source of carbon and nitrogen if they lack them in the environment. This is probably due to acrylamide degradation by amidases. The conducted response surface methodology indicated that pH as well as incubation time and temperature significantly influenced the amount of ammonia released from acrylamide by the bacteria. In conclusion, our studies suggest that some strains of bacteria present in milk fermented products can exert additional beneficial impact by diminishing the acrylamide concentration and hence helping to prevent against its harmful impact on the human body and other members of intestinal microbiota.

scholarly journals Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Fabien Duveau ◽  
Andrea Hodgins-Davis ◽  
Brian PH Metzger ◽  
Bing Yang ◽  
Stephen Tryban ◽  
...  
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Expression Level ◽  
Gene Expression Noise ◽  
Expression Levels ◽  
Fitness Effects ◽  
Expression Noise ◽  
Average Expression Level ◽  
The Difference ◽  
The Impact

Gene expression noise is an evolvable property of biological systems that describes differences in expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.

scholarly journals Aberrant expression of USF2 in refractory rheumatoid arthritis and its regulation of proinflammatory cytokines in Th17 cells

2020 ◽  
Vol 117 (48) ◽  
pp. 30639-30648
Author(s):  
Dan Hu ◽  
Emily C. Tjon ◽  
Karin M. Andersson ◽  
Gabriela M. Molica ◽  
Minh C. Pham ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Transcription Factor ◽  
Proinflammatory Cytokines ◽  
Th17 Cells ◽  
Gene Set Enrichment Analysis ◽  
Aberrant Expression ◽  
Signature Genes ◽  
The Impact

IL-17–producing Th17 cells are implicated in the pathogenesis of rheumatoid arthritis (RA) and TNF-α, a proinflammatory cytokine in the rheumatoid joint, facilitates Th17 differentiation. Anti-TNF therapy ameliorates disease in many patients with rheumatoid arthritis (RA). However, a significant proportion of patients do not respond to this therapy. The impact of anti-TNF therapy on Th17 responses in RA is not well understood. We conducted high-throughput gene expression analysis of Th17-enriched CCR6+CXCR3−CD45RA−CD4+T (CCR6+T) cells isolated from anti-TNF–treated RA patients classified as responders or nonresponders to therapy. CCR6+T cells from responders and nonresponders had distinct gene expression profiles. Proinflammatory signaling was elevated in the CCR6+T cells of nonresponders, and pathogenic Th17 signature genes were up-regulated in these cells. Gene set enrichment analysis on these signature genes identified transcription factor USF2 as their upstream regulator, which was also increased in nonresponders. Importantly, short hairpin RNA targetingUSF2in pathogenic Th17 cells led to reduced expression of proinflammatory cytokines IL-17A, IFN-γ, IL-22, and granulocyte-macrophage colony-stimulating factor (GM-CSF) as well as transcription factor T-bet. Together, our results revealed inadequate suppression of Th17 responses by anti-TNF in nonresponders, and direct targeting of the USF2-signaling pathway may be a potential therapeutic approach in the anti-TNF refractory RA.

scholarly journals Pre-treatment clinical and gene expression patterns predict developmental change in early intervention in autism

2021 ◽  
Author(s):  
Michael V. Lombardo ◽  
Elena Maria Busuoli ◽  
Laura Schreibman ◽  
Aubyn C. Stahmer ◽  
Tiziano Pramparo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Treatment Outcome ◽  
Early Intervention ◽  
Developmental Change ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Time In Treatment ◽  
Pre Treatment ◽  
Blood Leukocyte ◽  
The Impact

AbstractEarly detection and intervention are believed to be key to facilitating better outcomes in children with autism, yet the impact of age at treatment start on the outcome is poorly understood. While clinical traits such as language ability have been shown to predict treatment outcome, whether or not and how information at the genomic level can predict treatment outcome is unknown. Leveraging a cohort of toddlers with autism who all received the same standardized intervention at a very young age and provided a blood sample, here we find that very early treatment engagement (i.e., <24 months) leads to greater gains while controlling for time in treatment. Pre-treatment clinical behavioral measures predict 21% of the variance in the rate of skill growth during early intervention. Pre-treatment blood leukocyte gene expression patterns also predict the rate of skill growth, accounting for 13% of the variance in treatment slopes. Results indicated that 295 genes can be prioritized as driving this effect. These treatment-relevant genes highly interact at the protein level, are enriched for differentially histone acetylated genes in autism postmortem cortical tissue, and are normatively highly expressed in a variety of subcortical and cortical areas important for social communication and language development. This work suggests that pre-treatment biological and clinical behavioral characteristics are important for predicting developmental change in the context of early intervention and that individualized pre-treatment biology related to histone acetylation may be key.

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