PheNetic: network-based interpretation of molecular profiling data

Maeyer, Dries De; Weytjens, Bram; Renkens, Joris; Raedt, Luc De; Marchal, Kathleen

doi:10.1093/nar/gkv347

Cited by 24 publications

(34 citation statements)

References 29 publications

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“…In a second step, we used a sub-network-based selection method [ 58 , 59 ] (see Materials and Methods ) first developed for E . coli expression data.…”

Section: Resultsmentioning

confidence: 99%

Adaptation to High Ethanol Reveals Complex Evolutionary Pathways

et al. 2015

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Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts.

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“…In a second step, we used a sub-network-based selection method [ 58 , 59 ] (see Materials and Methods ) first developed for E . coli expression data.…”

Section: Resultsmentioning

confidence: 99%

Adaptation to High Ethanol Reveals Complex Evolutionary Pathways

et al. 2015

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“…To understand which cellular functions could play a role in modulating lysis kinetics, we performed a network analysis (see section "Materials and Methods" for details) of the deleted genes in the tolerant strains using an adapted version of Phenetic (De Maeyer et al, 2015). We picked 668 strains (Supplementary Data Sheet S2) that showed more than 10-fold enrichment (or SI > 0.43) in the fraction of intact cells at T 2 h compared to the wild type for the analysis.…”

Section: Network Analysis Of β-Lactam Tolerance Genesmentioning

confidence: 99%

“…Network-based analysis was performed using an adapted version of PheNetic (De Maeyer et al, 2015). First, the deleted genes that led to a significant increase of survival rate (SI > 0.43, which represents a 10-fold enrichment in survival rate when compared to the wild type) were mapped on the interaction network.…”

Section: Network Analysis Of Tolerant Strainsmentioning

confidence: 99%

Image-Based Dynamic Phenotyping Reveals Genetic Determinants of Filamentation-Mediated β-Lactam Tolerance

et al. 2020

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Antibiotic tolerance characterized by slow killing of bacteria in response to a drug can lead to treatment failure and promote the emergence of resistance. β-lactam antibiotics inhibit cell wall growth in bacteria and many of them cause filamentation followed by cell lysis. Hence delayed cell lysis can lead to β-lactam tolerance. Systematic discovery of genetic factors that affect β-lactam killing kinetics has not been performed before due to challenges in high-throughput, dynamic analysis of viability of filamented cells during bactericidal action. We implemented a high-throughput time-resolved microscopy approach in a gene deletion library of Escherichia coli to monitor the response of mutants to the β-lactam cephalexin. Changes in frequency of lysed and intact cells due to the antibiotic action uncovered several strains with atypical lysis kinetics. Filamentation confers tolerance because antibiotic removal before lysis leads to recovery through numerous concurrent divisions of filamented cells. Filamentation-mediated tolerance was not associated with resistance, and therefore this phenotype is not discernible through most antibiotic susceptibility methods. We find that deletion of Tol-Pal proteins TolQ, TolR, or Pal but not TolA, TolB, or CpoB leads to rapid killing by β-lactams. We also show that the timing of cell wall degradation determines the lysis and killing kinetics after β-lactam treatment. Altogether, this study uncovers numerous genetic determinants of hitherto unappreciated filamentation-mediated β-lactam tolerance and support the growing call for considering antibiotic tolerance in clinical evaluation of pathogens. More generally, the microscopy screening methodology described here can easily be adapted to study lysis in large numbers of strains.

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“…We manually assigned p value 0 to the culture‐dependent genes set and p value 1 to the rest of genes. Then, this dataset was loaded into PheNetic (De Maeyer et al ., ) web tool, which uses publicly available interactomics data to create networks from a given expression dataset, revealing possible master regulators and cellular processes relevant for the sample. In this case, the analysis determined Cin5p ( YOR028C ), Phd1p ( YKL043W ) and Spt23p ( YKL020C ) as the central transcription factors, which are involved in response to external stimulus and are known to recruit the general repressor Tup1p to certain promoters (Hanlon et al ., ) (Fig.…”

Section: Resultsmentioning

confidence: 99%

Dominance of wine Saccharomyces cerevisiae strains over S. kudriavzevii in industrial fermentation competitions is related to an acceleration of nutrient uptake and utilization

Alonso-del-Real

Pérez‐Torrado

Querol

et al. 2019

Environmental Microbiology

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Summary Grape must is a sugar‐rich habitat for a complex microbiota which is replaced by Saccharomyces cerevisiae strains during the first fermentation stages. Interest on yeast competitive interactions has recently been propelled due to the use of alternative yeasts in the wine industry to respond to new market demands. The main issue resides in the persistence of these yeasts due to the specific competitive activity of S. cerevisiae. To gather deeper knowledge of the molecular mechanisms involved, we performed a comparative transcriptomic analysis during fermentation carried out by a wine S. cerevisiae strain and a strain representative of the cryophilic S. kudriavzevii, which exhibits high genetic and physiological similarities to S. cerevisiae, but also differences of biotechnological interest. In this study, we report that transcriptomic response to the presence of a competitor is stronger in S. cerevisiae than in S. kudriavzevii. Our results demonstrate that a wine S. cerevisiae industrial strain accelerates nutrient uptake and utilization to outcompete the co‐inoculated yeast, and that this process requires cell‐to‐cell contact to occur. Finally, we propose that this competitive phenotype evolved recently, during the adaptation of S. cerevisiae to man‐manipulated fermentative environments, since a non‐wine S. cerevisiae strain, isolated from a North American oak, showed a remarkable low response to competition.

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PheNetic: network-based interpretation of molecular profiling data

Cited by 24 publications

References 29 publications

Adaptation to High Ethanol Reveals Complex Evolutionary Pathways

Adaptation to High Ethanol Reveals Complex Evolutionary Pathways

Image-Based Dynamic Phenotyping Reveals Genetic Determinants of Filamentation-Mediated β-Lactam Tolerance

Dominance of wine Saccharomyces cerevisiae strains over S. kudriavzevii in industrial fermentation competitions is related to an acceleration of nutrient uptake and utilization

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