scholarly journals Autophagy as a Mechanism for Adaptive Prediction-Mediated Emergence of Drug Resistance

2021 ◽  
Vol 12 ◽  
Author(s):  
Nivedita Nivedita ◽  
John D. Aitchison ◽  
Nitin S. Baliga
Keyword(s):  
Drug Resistance ◽  
Stressful Environment ◽  
Adaptive Prediction ◽  
Genome Wide ◽  
Microbial Infections ◽  
Effective Therapeutic Strategy ◽  
New Perspective ◽  
Tolerant State ◽  
Core Genes ◽  
Selection Of

Drug resistance is a major problem in treatment of microbial infections and cancers. There is growing evidence that a transient drug tolerant state may precede and potentiate the emergence of drug resistance. Therefore, understanding the mechanisms leading to tolerance is critical for combating drug resistance and for the development of effective therapeutic strategy. Through laboratory evolution of yeast, we recently demonstrated that adaptive prediction (AP), a strategy employed by organisms to anticipate and prepare for a future stressful environment, can emerge within 100 generations by linking the response triggered by a neutral cue (caffeine) to a mechanism of protection against a lethal agent (5-fluoroorotic acid, 5-FOA). Here, we demonstrate that mutations selected across multiple laboratory-evolved lines had linked the neutral cue response to core genes of autophagy. Across these evolved lines, conditional activation of autophagy through AP conferred tolerance, and potentiated subsequent selection of mutations in genes specific to overcoming the toxicity of 5-FOA. These results offer a new perspective on how extensive genome-wide genetic interactions of autophagy could have facilitated the emergence of AP over short evolutionary timescales to potentiate selection of 5-FOA resistance-conferring mutations.

scholarly journals Autophagy as a mechanism for adaptive prediction-mediated emergence of drug resistance

2021 ◽  
Author(s):  
Nivedita Nivedita ◽  
John D. Aitchison ◽  
Nitin S. Baliga
Keyword(s):  
Drug Resistance ◽  
Stressful Environment ◽  
Adaptive Prediction ◽  
Genome Wide ◽  
Microbial Infections ◽  
Effective Therapeutic Strategy ◽  
Subsequent Selection ◽  
Tolerant State ◽  
Core Genes ◽  
Selection Of

ABSTRACTDrug resistance is a major problem in treatment of microbial infections and cancers. There is growing evidence that a transient drug tolerant state may precede and potentiate the emergence of drug resistance. Therefore, understanding the mechanisms leading to tolerance is critical for combating drug resistance and for the development of effective therapeutic strategy. Through laboratory evolution of yeast, we recently demonstrated that adaptive prediction (AP), a strategy employed by organisms to anticipate and prepare for a future stressful environment, can emerge within 100 generations by linking the response triggered by a neutral cue (caffeine) to a mechanism of protection against a lethal agent (5-FOA). Here, we demonstrate that mutations selected across multiple laboratory evolved lines had linked the neutral cue response to core genes of autophagy. Across these evolved lines, conditional activation of autophagy through AP conferred tolerance, and potentiated subsequent selection of mutations in genes specific to overcoming the toxicity of 5-FOA. We propose a model to explain how extensive genome-wide genetic interactions of autophagy facilitates emergence of AP over short evolutionary timescales to potentiate selection of resistance-conferring mutations.

Competition of Verb Aspects and Its Resolution as a Creative Act (Based on the Material of Aspects Variants in the Texts by F. M. Dostoevsky)

2020 ◽  
Vol 81 (2) ◽  
pp. 56-63
Author(s):  
S. A. Karpukhin
Keyword(s):  
Traditional Method ◽  
Contextual Analysis ◽  
Verb Aspect ◽  
Component Theory ◽  
Two Component ◽  
Artistic Interpretation ◽  
New Perspective ◽  
First Time ◽  
Selection Of ◽  
Aspectual Meaning

The article considers the competition of verbal aspects from a new perspective. Instead of employing the traditional method of demonstrating this phenomenon — an empirical replacement of the aspect of a verb in a phrase with the opposite — the author examines Dostoevsky’s choice between the variants found in different manuscripts of the same text. For the first time, based on a two-component theory of the semantic invariant of a verb type, the aspectual meaning of the selection of a verb aspect is revealed and, as a result of contextual analysis, an artistic interpretation of the selected type is proposed.

scholarly journals A microfluidic device enabling drug resistance analysis of leukemia cells via coupled dielectrophoretic detection and impedimetric counting

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yağmur Demircan Yalçın ◽  
Taylan Berkin Töral ◽  
Sertan Sukas ◽  
Ender Yıldırım ◽  
Özge Zorlu ◽  
...  
Keyword(s):  
Drug Resistance ◽  
K562 Cells ◽  
Leukemia Cells ◽  
Drug Resistant ◽  
Wild Type ◽  
Gene Expressions ◽  
Before And After ◽  
The Difference ◽  
Selection Of ◽  
Resistant Cells

AbstractWe report the development of a lab-on-a-chip system, that facilitates coupled dielectrophoretic detection (DEP-D) and impedimetric counting (IM-C), for investigating drug resistance in K562 and CCRF-CEM leukemia cells without (immuno) labeling. Two IM-C units were placed upstream and downstream of the DEP-D unit for enumeration, respectively, before and after the cells were treated in DEP-D unit, where the difference in cell count gave the total number of trapped cells based on their DEP characteristics. Conductivity of the running buffer was matched the conductivity of cytoplasm of wild type K562 and CCRF-CEM cells. Results showed that DEP responses of drug resistant and wild type K562 cells were statistically discriminative (at p = 0.05 level) at 200 mS/m buffer conductivity and at 8.6 MHz working frequency of DEP-D unit. For CCRF-CEM cells, conductivity and frequency values were 160 mS/m and 6.2 MHz, respectively. Our approach enabled discrimination of resistant cells in a group by setting up a threshold provided by the conductivity of running buffer. Subsequent selection of drug resistant cells can be applied to investigate variations in gene expressions and occurrence of mutations related to drug resistance.

Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysisThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 1002-1016 ◽  
Author(s):  
B.R. Cullis ◽  
A.B. Smith ◽  
C.P. Beeck ◽  
W.A. Cowling
Keyword(s):  
Pedigree Information ◽  
Environment Interaction ◽  
Correlation Matrices ◽  
New Approach ◽  
Genome Wide ◽  
Selection Indices ◽  
New Varieties ◽  
Oilseed Brassicas ◽  
Analytic Models ◽  
Selection Of

Exploring and exploiting variety by environment (V × E) interaction is one of the major challenges facing plant breeders. In paper I of this series, we presented an approach to modelling V × E interaction in the analysis of complex multi-environment trials using factor analytic models. In this paper, we develop a range of statistical tools which explore V × E interaction in this context. These tools include graphical displays such as heat-maps of genetic correlation matrices as well as so-called E-scaled uniplots that are a more informative alternative to the classical biplot for large plant breeding multi-environment trials. We also present a new approach to prediction for multi-environment trials that include pedigree information. This approach allows meaningful selection indices to be formed either for potential new varieties or potential parents.

scholarly journals A Robust Rerank Approach for Feature Selection and Its Application to Pooling-Based GWA Studies

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jia-Rou Liu ◽  
Po-Hsiu Kuo ◽  
Hung Hung
Keyword(s):  
Characteristic Curve ◽  
Real Data ◽  
Tuning Parameter ◽  
Practical Implementation ◽  
Tuning Parameters ◽  
Genome Wide ◽  
Feature Based ◽  
The Difference ◽  
Gwa Studies ◽  
Selection Of

Large-p-small-ndatasets are commonly encountered in modern biomedical studies. To detect the difference between two groups, conventional methods would fail to apply due to the instability in estimating variances int-test and a high proportion of tied values in AUC (area under the receiver operating characteristic curve) estimates. The significance analysis of microarrays (SAM) may also not be satisfactory, since its performance is sensitive to the tuning parameter, and its selection is not straightforward. In this work, we propose a robust rerank approach to overcome the above-mentioned diffculties. In particular, we obtain a rank-based statistic for each feature based on the concept of “rank-over-variable.” Techniques of “random subset” and “rerank” are then iteratively applied to rank features, and the leading features will be selected for further studies. The proposed re-rank approach is especially applicable for large-p-small-ndatasets. Moreover, it is insensitive to the selection of tuning parameters, which is an appealing property for practical implementation. Simulation studies and real data analysis of pooling-based genome wide association (GWA) studies demonstrate the usefulness of our method.

Pleiotropic drug-resistance attenuated genomic library improves elucidation of drug mechanisms

2015 ◽  
Vol 11 (11) ◽  
pp. 3129-3136 ◽  
Author(s):  
Namal V. C. Coorey ◽  
James H. Matthews ◽  
David S. Bellows ◽  
Paul H. Atkinson
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Drug Resistance ◽  
Mechanism Of Action ◽  
Gene Deletion ◽  
Genomic Library ◽  
Deletion Mutants ◽  
Pleiotropic Drug Resistance ◽  
Genome Wide

Identifying Saccharomyces cerevisiae genome-wide gene deletion mutants that confer hypersensitivity to a xenobiotic aids the elucidation of its mechanism of action (MoA).

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