fraction of these rare alleles may be due to fixation of beneficial regulatory changes within divergent S. cerevisiae strains due to positive selection. As described below, we expect that weak selection to maintain geneexpression stability may result in positive selection on certain compensatory regulatory changes in spite ofthe fact that most novel alleles are likely to be deleterious. Although our analyses were based on a small number of yeast strains, they make several predictions about the pattern ofexpressionQTL that might be observed among strains inthe yeast population. First, based on our conclusion that most cis- acting QTL are mildly deleterious, we expect that among any pairwise comparison of strains, fewer cis-acting QTL would be present than predicted under neutrality. Second, selection against extant cis-regulatory alleles is rather weak, we would not expect to observe a set of genes that have invariant cis-regulation across numerous yeast strains. Instead, we predict that most or all genes are likely to show cis-regulatory polymorphism inthe global population of yeast strains. Finally, we provided anecdotal evidence that positive selection may allow major trans-acting regulatory QTL to emerge and persist inthe population. In addition to positive selection, demographic perturbations such as bottlenecks or population structure may lead to the emergence of novel major regulatory alleles. However, inthe absence of such forces, we would expect few major trans-acting regulatory QTL. Indeed, in outbred populations such as humans, the existence of major trans-acting QTL is controversial (contrast  with ). Figure 6. Strength of purifying selection against cis -acting regulatory changes. Light gray shaded areas indicate that 95% CIs for the proportion of rare derived alleles (vertical axis) in synonymous sites and inthe promoter and 39 UTR. Ninety-five percent CIs for the expected proportion of rare derived alleles at selected sites (dark gray shading) and linked neutral sites (black shading) are shown as a function ofthe scaled fitness difference between selective classes (horizontal axis). The dashed line indicates the scaled purifying selection coefficient (2.1) that is most likely to have produced the observed allele frequency skew based on linear interpolation between 2N e s = 2.0 and 2.2. The rate of substitution at the selected site
Interestingly, branch length estimates closest to the root do not show evidence for a faster-X effect in Drosophila (Figure 4). This is not necessarily evidence against the faster-X evolutionofgeneexpression along these internal branches. We instead hypothesize that it is the result of low power to resolve deep branching orders using these correlation matrices, which leads to poor estimates of branch lengths around deep nodes. Supporting this hypothesis, when we use the correlation matrices to estimate the tree topology, some ofthe deep nodes have the lowest bootstrap support for the correct topology (Figure 4, Figure S9). In addition, the bootstrap support for these nodes is lower for X-linked geneexpression levels are the 95% confidence interval (CI). Each point represents the correlation for a chromosome arm, and the error bars are the 95% CI. Chromosome arms are represented with their Muller element nomenclature. Muller element A is is the X chromosome (red), and Muller element D is the D. pseudoobscura neo-X chromosome. Species names were abbreviated as follows: mel = D. melanogaster, yak = D. yakuba, ana = D. ananassae, pse = D. pseudoobscura, moj = D. mojavensis, vir = D. virilis.
In agreement with these results, Gxs1p was virtually absent from the plasma membrane of strain MJY5 (Fig. 4). In contrast, the amounts of Gxf1 protein inthe plasma membrane of glucose-grown cells were similar in strains MJY1 and MJY5, as expected from the observations concerning GXF1 mRNA in these strains (Figs 4 and 5). A simple explanation of all our observations would be a sharp drop inthe copy number ofthe plasmid carrying the GXS1 gene, caused by the fact that Gxs1 activity becomes dispensable for the cell when passive glucose transporters are present in high-glucose medium. Indeed, in strain MJY5 we detected that although the plasmid copy number did not decrease, as judged by a Southern blot experiment designed to quantify plasmid-borne copies ofthe LEU2 gene, many plasmids seemed to have lost the GXS1 gene (results not shown). However, this does not explain the decrease in GXS1 mRNA levels in strain MJY7 (GXS1+HXTs). This strain exhibited low GXS1 mRNA levels (Fig. 5) and virtually no symport activity (Fig. 6b, c) when cultivated in minimal medium with glucose. However, when MJY7 was cultivated in ethanol medium, symport activity was found to be present (Fig. 6b, c). In ethanol-grown cells of MJY7, proton movements elicited by the addition of glucose to an aqueous cell suspension suggest that both passive and active transport systems were operating simultaneously (Fig. 6c): the initial, transient alkalinization caused by the proton influx associated with symport activity was soon counteracted by the acidification due to proton efflux resulting from the activation ofthe plasma membrane ATPase. This could mean that glucose uptake rates increased considerably, in comparison with the situation in which the low-capacity Gxs1p was the only transporter present and no acidification was observed (results not shown). These results favour the hypothesis that the symporter co-exists with the Hxt facilitators at the plasma membrane of strain MJY7 in ethanol-grown but not in glucose-grown cells. This was confirmed by Northern blotting (see Fig. 5 and time zero in Fig. 7) and by quantitative real-time RT-PCR (not shown), both of which indicated that GXS1 mRNA is present in ethanol- grown cells of strain MJY7, while it is almost undetectable in glucose-grown cells ofthe same strain. In view of these data, there seem to be two prerequisites for the reduction inthe amount of GXS1 mRNA: the presence of a high- capacity glucose facilitator inthe plasma membrane, to bring about vigorous glucose uptake, and the presence of glucose inthe growth medium.
There are microorganisms capable of using glycerol as carbon source, being very attractive to convert crude glycerol, a byproduct generated from the production of biodiesel. It is known that Saccharomycescerevisiae glycerol metabolism pathway is well defined and a proton symport system encoded by STL1 is preferably used as the glycerol uptake when fermentable carbon sources are not present. This study aimed to identify the STL1 gene that encodes a putative glycerol transporter in Wickerhamomyces anomalus LBCM105, whose genome is not yet available inthe database. The recognized and sequenced gene showed 1443 bp and 480 amino acids. The comparative analysis in silico ofthe promoter region identified putative transcription factors associated with the regulation of STL1 gene from W. anomalus LBCM105 and S. cerevisiae, suggesting a remarkable distinction between the putative elements of both. A phylogenetic tree analysis was constructed using different STL1 sequences from different yeasts showed less evolutionary distance between W. anomalus LBCM105 and W. ciferrii transporter, and a greater distance from S. cerevisiae. After characterizing the W. anomalus LBCM105 STL1 gene, geneexpression analyzes were made using conditions containing glucose or glycerol as carbon source. STL1 showed a 23.76-fold higher expressionin glycerol in relation to medium containing glucose. W. anomalus LBCM105 glycerol uptake evaluation showed an active transport in medium containing glucose or glycerol, however Stl1p was up-regulated inthe presence of glycerol. The results demonstrate relevant data about the probable W. anomalus LBCM105 glycerol transporter characterization, indicating a significant potential for biotechnological applications as crude glycerol consumer, since it was very efficient inthe uptake of glycerol.
Metabolic Pathways and Natural Genetic Variation I next utilized the pathway level transcript CV to compare intraspecific variation measured inthe two Accession datasets. A low pathway level transcript CV would suggest genetic constraints limiting geneexpression diversity of pathway members. In contrast, elevated levels of pathway transcript CV may result from selection for increased geneexpression diversity. The availability of two independent ATH1 microarray datasets investigating natural genetic variation in transcript accumulation within Arabidopsis allows a replicated analysis of metabolic pathways to detect biased transcript variance. Major energy and amino acid pathways showed significantly diminished pathway transcript variance in comparison to the average random gene set in both independent accession datasets (Figure 5) suggesting that transcript variance in these essential biochemical pathways is genetically constrained. The photosynthesis and calvin cycle pathways do show significant pathway variance within the development dataset displaying the potential of these pathways to vary (Figures 4 and 5). This increased genetic constraint in comparison to the average metabolic pathway may relate to a relative lack ofgene duplicates in these pathways. For instance, the tRNA charging pathways have a paucity ofgene duplicates in comparison to the random expectation (Figure 6 and Table S4). Overall, the number of tandem duplicates within a pathway was positively correlated to the pathway’s average transcript CV within the Accession datasets (P,0.001, R 2 = 0.21, N = 135; for this test, the Aliphatic Glucosinolate Biosynthetic pathway was removed given its high CV). This suggests that gene duplication status for the different metabolic pathways can predict the level of genetic variation for geneexpression within a given metabolic pathway. Interestingly, none ofthe pathways with either elevated or diminished pathway level transcript CV showed significantly Figure 2. Partitioning of transcript variance in a factorial
Members ofthe plant-specific IQ67-domain (IQD) protein family are involved in plant development and the basal defense response. Although systematic characterization of this family has been carried out in Arabidopsis, tomato (Solanum lycopersicum), Brachypodium distachyon and rice (Oryza sativa), systematic analysis and expression profiling of this gene family in soybean (Glycine max) have not previously been reported. In this study, we identified and structurally characterized IQD genes inthe soybean genome. A complete set of 67 soybean IQD genes (GmIQD1–67) was identified using Blast search tools, and the genes were clustered into four subfamilies (IQD I–IV) based on phylogeny. These soybean IQD genes are distributed unevenly across all 20 chromosomes, with 30 segmental duplication events, suggesting that segmental duplication has played a major role inthe expansion ofthe soybean IQD gene family. Analysis ofthe Ka/Ks ratios showed that the duplicated genes ofthe GmIQD family primarily underwent purifying selection. Microsynteny was detected in most pairs: genes in clade 1–3 might be present in genome regions that were inverted, expanded or contracted after the divergence; most gene pairs in clade 4 showed high conservation with little rearrangement among these gene-residing regions. Ofthe soybean IQD genes examined, six were most highly expressed in young leaves, six in flowers, one in roots and two in nodules. Our qRT-PCR analysis of 24 soybean IQD III genes confirmed that these genes are regulated by MeJA stress. Our findings present a comprehensive overview ofthe soybean IQD gene family and provide insights into theevolutionof this family. In addition, this work lays a solid foundation for further experiments aimed at determining the biological functions of soybean IQD genes in growth and development.
Alternative functions, apart from cathepsins inhibition, are being discovered for stefin B. Here, we investigate its role in vesicular trafficking and autophagy. Astrocytes isolated from stefin B knock-out (KO) mice exhibited an increased level of protein aggregates scattered throughout the cytoplasm. Addition of stefin B monomers or small oligomers to the cell medium reverted this phenotype, as imaged by confocal microscopy. To monitor the identity of proteins embedded within aggregates in wild type (wt) and KO cells, the insoluble cell lysate fractions were isolated and analyzed by mass spectrometry. Chaperones, tubulins, dyneins, and proteosomal components were detected inthe insoluble fraction of wt cells but not in KO aggregates. In contrast, the insoluble fraction of KO cells exhibited increased levels of apolipoprotein E, fibronectin, clusterin, major prion protein, and serpins H1 and I2 and some proteins of lysosomal origin, such as cathepsin D and CD63, relative to wt astrocytes. Analysis of autophagy activity demonstrated that this pathway was less functional in KO astrocytes. In addition, synthetic dosage lethality (SDL) gene interactions analysis inSaccharomycescerevisiae expressing human stefin B suggests a role in transport of vesicles and vacuoles These activities would contribute, directly or indirectly to completion of autophagy in wt astrocytes and would account for the accumulation of protein aggregates in KO cells, since autophagy is a key pathway for the clearance of intracellular protein aggregates.
We re-analysed a publically available yeast dataset with genotypes and expression phenotypes on individuals from cross between a laboratory S. cereviciae strain (BY4716 , isogenic to S288C) and a wild isolate (RM11-1a)(for a complete description, see [7,9]). Briefly, the dataset consisted of 109 haploid segregants. Each segregant was grown in two conditions with either glucose or ethanol as the main carbon energy source. Bar the different growth mediums, all other environmental conditions were kept constant throughout the experiment. For each segregant, a set of 2956 SNP markers were genotyped providing an average marker density of one Figure 5. QTL and vQTL regulation of CTA1. A) The genotype-phenotype map of CTA1 expression for the three interactions identified in B (colours are the same as Figure 3). B) Manhattan-plots of GWAS and vGWAS ofthe CTA1 phenotype. The horizontal dotted line represents 0.5% FDR significance level. The purple vertical line indicates the position oftheexpression phenotype. Colours and symbols are the same as Figure 3.
and DSB-induced sister-chromatid cohesion [33–36]. Therefore, it is difficult to ascertain whether or not a repair defect observed upon disruption of these proteins is attributable to the loss of end-tethering per se. We reasoned that our Trans strain would overcome this problem because the ends that are involved in GC-mediated repair don’t belong to the same break, and therefore, would not be tethered to each other (although they would presumably be tethered to the URA3 sequences on the opposite sides ofthe DSBs). Since the cells are able to survive a break inthe Trans and Reverse-Trans configuration as efficiently as a break inthe Reverse-Cis configuration (in which the ends involved in repair should be tethered) (Fig 2A), DSB end- tethering seems to be largely dispensable for the successful completion of GC-mediated repair. Nevertheless, the delay inthe kinetics of repair in Trans and Reverse-Trans might reflect the lack of association between LE and U2 ends, which would have to independently seek out their homologous sequences, as opposed to repair inthe Cis and Reverse-Cis configurations where the LE and U2 ends would be tethered together and might therefore engage in a coordinated search for their homologous partners. Alternatively, the slower kinetics of LEU2 repair in Trans and Reverse-Trans could be an indirect effect of tethering ofthe LE and U2 ends to the corresponding URA3 sequences on the other side ofthe DSBs, which are involved in a separate SSA repair event and might therefore drag the associated LE and U2 ends away from their homologous donor. While RAD50 deletion reduced the efficiency of both Cis and Trans repair, it did not alter their relative kinetics (Fig 4A and 4B). We suspect that this is due to only partial un-tethering ofthe DSB ends inthe absence of Rad50 [25,26]. Indeed, when we removed the influence of association to the other end by eliminating the SSA event inthe Trans setting, the kinetics of Trans GC became as rapid as inthe Cis case (Fig 4D). These data argue that inthe original Trans strain, the URA3 sequences that are involved in SSA-mediated repair, potentially drag their associated LE and U2 ends away from the LEU2 donor on Chr III. This, in turn, would compromise the probability of LE and U2 ends simultaneously engaging the LEU2 donor, resulting in a smaller proportion of cells initiating GC-mediated repair at any given time. Overall these results suggest that end-tethering may play a substantial role in preventing chromosomal translocations that could arise from GC repair involving ends from different breaks. This might become particularly important if a break occurs within a repeated sequence such that the ends could either travel together and repair using donors present inthe vicinity of each other or engage in separate GC events involving unlinked donors.
The yeasts were identified by the standard methods of Kurtzman et al. (2011). Yeast identities were confirmed by sequencing the D1/D2 variable domains ofthe large sub- unit ofthe rRNA gene; the D1/D2 divergent domains were PCR-amplified as described by Lachance et al. (1999) us- ing the primers NL-1 (5’-GCATATCAATAAGCG GAGGAAAAG-3’) and NL-4 (5’-GGTCCGTGTTTCAA GACGG-3’). Identities of badisiomycetous species were also confirmed by sequencing the intergenic transcribed spacer (ITS) 1-5.8S-ITS2 region ofthe large-subunit rRNA gene (10). The amplified DNA was concentrated and puri- fied with WizardSV columns (Promega, USA) and then se- quenced in a MegaBACE 1000 automated sequencing system (Amersham Biosciences, USA). The sequences were edited with the program DNAMAN, version 4.1 (Lynnon Bio-Soft, Canada). Existing sequences for other yeasts were retrieved from GenBank.
the present study revealed that Flo8p has a crucial role in these phenotypic characteristics regulation from the industrial strain, FT02. The data obtained from foam assay exhibited that in this industrial strain, the FLO11 gene might be the responsible for this phenotype induction, since deleting the FLO8 gene, this strain loses the ability to produce foam. Mo eo e , the ∆flo8 strain showed the lower rate of cell flocculation, lower cell surface hydrophobicity, and lost the filamentation capability. The regulation by carbon sources found that the sucrose had greater ability to induce the studied phenotypes. It was also found that for foam formation, the carbon sources were determinant inthe maximum produced volume. Concluding our analyses, qPCR were performed to determine the relative expressionofthegene FLO family and the relation with the FLO8 gene. Thus, we observed that besides FLO1 and FLO11 genes, the FLO9 and FLO10 genes demonstrated Flo8p regulation. Therefore, by the phenotypic characteristics from the industrial strain isolated from the ethano l fuel p odu tio p o ess, FT , a d the ∆flo8 strain, we could infer about the phenotypes regulation through cAMP-PKA/Flo8p pathway, being the first work to relate the foam formation to FLO8 gene.
recombination inthe repetitive region possibly resulting in instability ofthe constructs. The modified sites were based on the native LexA binding sites. In case of B1 and B2 on the lexAo1 and lexAo2 present inthe regulatory region ofthe lexA gene , and in case of B3 and B4 on the ColEI operator which contains two partially overlapping LexA binding sites . The mod- ifications introduced to B1, B2, and B4 (B3 is identical to a native site present inthe ColEI oper- ator; Figure A in S1 File) are in positions that have not been reported to be critical for LexA binding. Furthermore, the same bases are also present in other native LexA binding sites . Qualitative in vitro analysis of LexA binding to B1-B4 performed by EMSA (Figure C in S1 File) showed equivalent functionality ofthe binding sites. The conditions inthe EMSA resem- bled closely the conditions used in previous reports that focused on detailed analysis ofthe LexA binding properties . However, we cannot draw any conclusions about the LexA bind- ing affinities and we cannot exclude the possibility that the modifications introduced affected the binding affinity. The predictable behaviour ofthe modified LexA binding sites was, how- ever, observed inthe experiments where the increasing number ofthe BSs (1–4) resulted in a consistent gradual increase ofthe activity ofthe corresponding synthetic promoters (Figs 3–5) and therefore rendering functional BS modules.
monitored by flow cytometry while culturable populations were followed by plating on culture medium. Twenty-four hours after the application ofthe stress, the comparison between the culturable population and the viable population demonstrated the presence of viable cells that were non culturable. In addition, removal ofthe stress by increasing the pH ofthe medium at different time intervals into the VBNC state allowed the VBNC S. cerevisiae cells to ‘‘resuscitate’’. The similarity between the cell cycle profiles of VBNC cells and cells exiting the VBNC state together with the generation rate of cells exiting VBNC state demonstrated the absence of cellular multiplication during the exit from the VBNC state. This provides evidence of a true VBNC state. To get further insight into the molecular mechanism pertaining to the VBNC state, we studied the involvement ofthe SSU1 gene, encoding a sulfite pump in S. cerevisiae. The physiological behavior of wild- type S. cerevisiae was compared to those of a recombinant strain overexpressing SSU1 and null Dssu1 mutant. Our results demonstrated that the SSU1 gene is only implicated inthe first stages of sulfite resistance but not per se inthe VBNC phenotype. Our study clearly demonstrated the existence of an SO 2 -induced VBNC state in S. cerevisiae and that the stress
Theexpression and aCGH microarray data, as well as the genome sequence analysis, indicate that wine yeasts have unique genetic characteristics perhaps resulting from the adaptation to the fermentative process. Alternatively, most of these genetic variants are non-adaptive and were fixed by genetic drift due to population bottleneck giving rise to the Wine/European population . However, one ofthe main challenges in biology is to understand the genetic variants that underlie phenotypic variation in complex traits. Oenological traits such as ethanol production, residual sugar after the fermentation, nitrogen uptake and volatile acidity are complex traits and are determined by multiple quantitative trait loci (QTL) . The genetics mechanisms underlying these phenotypic variations can be identified by linkage analysis. This approach use crosses between two phenotypically different strains and searches for statistical linkage between the phenotype and genetic markers ofthe segregant strains . This strategy has been fruitful in mapping many QTLs for an extensive number of phenotypes in yeast, such as: high temperature growth , sporulation efficiency [25,26], cell morphology , DNA repair . telomere length  ion tolerance  and sugar utilisation .
Cachaça is a beverage obtained by distilling fermented sugar cane juice. The state of Bahia in northeastern Brazil is the second-largest producer of traditional cachaça, and this region has the potential to improve the quality and quantity of its beverage production. The aim of this study was to analyze the genetic diversity ofSaccharomycescerevisiae populations isolated from must in six distilleries in Bahia using mitochondrial DNA restriction fragment length polymorphism (mtDNA- RFLP). Among the three hundred and thirty S. cerevisiae strains isolated, mtDNA-RFLP analysis identified a total of 30 molecular patterns. Analysis of molecular variance (AMOVA) revealed that the greatest genetic variation was found among, rather than within, the populations. Population structure analyses showed the presence of three distinct gene pools, thereby corroborating the AMOVA results. This study represents an important contribution to better understanding the molecular characterization and genetic variability of S. cerevisiae strains during the fermentation of cachaça. The dominant molecular patterns identified here may be used to select S. cerevisiae strains that could improve the quality and volume of traditional cachaça production in Bahia.
Geneexpression involves several events that occur at the transcriptional and post-transcriptional levels. The transcriptional control ofgeneexpression has been exten- sively influenced by early work on bacterial transcription. However, in recent years, post-transcriptional events have gained much more attention. The pre-RNA undergoes ex- tensive processing before the mRNA reaches its final desti- nation and RNA-binding proteins (RBPs) associated to the RNA during its life-time play a key role in determining its fate inthe cell. (Kishore et al., 2010). The association of proteins with mRNAs is very dynamic and prone to changes according to the environment. Consequently RBPs are involved inthe stabilization or destabilization of mRNAs in response to stress or extracellular signals (Alves and Goldenberg, 2016).
secondly, it has been reported (de Morais Jr et al., 1998) that the presence of RecAp increased the survival rate of rad52 mutant cells exposed to 8-MOP+UVA and to MMS but not those exposed to UVC. This response is dependent on the presence of functional Rad51p as illustrated by the fact that no effect was observed inthe double mutant rad51rad52 (de Morais Jr et al., 1998) which suggests that when Rad52p is absent RecAp can bind to its homologue Rad51p, RecAp producing a nucleoprotein complex con- taining DNA (mainly single-stranded) responsible for DNA pairing and strand exchange of homologous DNA molecules. In Escherichia coli, these events are dependent on DNA-binding and catalytic proteins which are part ofthe recombination complex (Kowalczykowski et al., 1994), a similar nucleoprotein structure having been demonstrated for yeast Rad51p (Sung, 1994). The 55 N-terminal amino acid residues present in Rad51p show ATP-dependent ho- mologous pairing and strand exchange activities also im- portant for the interaction of Rad51p with Rad52p (Sung and Robberson, 1995), but since RecAp lacks these amino acids it could not complement defective rad51 mutants (de Morais Jr et al., 1998) but may interact with intact Rad51p through their homologous C-terminal regions to form a heteropolymeric spiral filament. RecAp was shown to pro- mote Holliday junction and branch migration between in- tact single-strand DNA and homologous damaged double-strand DNA, leading to the formation of intermedi- ate heteroduplex DNA which is processed to produce a gene conversion event (Kowalczykowski et al., 1994). However, DNA strand transfer reactions mediated by either RecAp or Rad51p have been demonstrated to have different polarities (Sung and Robberson, 1995) because of which the putative chimeric structure formed by rad51p-RecAp inthe yeast nucleus might interfere inthe biochemical activity ofthe spiral filament by arresting branch migration and in- hibiting correct DNA strand transfer. RecAp should act as a dominant negative allele in this process, experiments using deleted forms ofthe RAD52 gene having demonstrated that Rad52p with deleted recombination activity but normal Rad51p binding competed with wild-type Rad52p for the Rad51-Rad52 protein complex and acted as a dominant negative allele inhibiting double-strand break repair (Milne and Weaver, 1993).
Lipopolysaccharide, known as endotoxin, can stimulate potent host immune responses through the complex of Toll-like- receptor 4 and myeloid differentiation protein 2; but its influence on Saccharomycescerevisiae, a model organism for studying eukaryotes, is not clear. In this study, we found that lipopolysaccharide-treated S. cerevisiae cells could be stained by methylene blue, but did not die. Transcriptional profiling ofthe lipopolysaccharide-treated S. cerevisiae cells showed that 5745 genes were modulated: 2491 genes up-regulated and 3254 genes down-regulated. Significantly regulated genes (460 up-regulated genes and 135 down-regulated genes) in lipopolysaccharide-treated S. cerevisiae cells were analyzed on Gene Ontology, and used to establish physical protein-protein interaction network and protein phosphorylation network. Based on these analyses, most ofthe regulated genes in lipopolysaccharide-treated S. cerevisiae cells were related to cell wall, membrane, peroxisome and mitochondrion. Further experiments demonstrated that lipopolysaccharide stimulation caused the exposure of phosphatidylserine and the increase of mitochondrial membrane potential in S. cerevisiae cells, but levels of intracellular reactive oxygen species and metacaspase activation were not increased. This study demonstrated that lipopolysaccharide stimulation causes significant changes in S. cerevisiae cells, and the results would contribute to understand the response of eukaryotic cells to lipopolysaccharide stimulation.
Yeast cells were cultured in liquid SC medium lacking appropriate amino acids and mounted on a glass slide for fluorescence microscopy. Images were acquired using a Zeiss Axioplan2 microscope with an oil-immersion objective lens (1006) equipped with a CCD camera (Hamamatsu ORCA-ER) and Openlab software (Perkin Elmer). For flow cytometry, cells were harvested by centrifugation, or by vacuum filtration on nitrocel- lulose membranes (1:2mm, Millipore, cat. no. RAWP02500), re- suspended in ice-cold 16PBS and sonicated briefly before subjected to the analysis using LSRFortessa (BD Biosciences). Fluorescence of 50,000 cells for each sample were measured by flow cytometry. Based on the FFS/SSC values, the data were gated to remove cell debris and aggregates. The raw data for the remaining cells, between 86% and 98% ofthe original sample, were exported to MATLAB (MATLAB, Natick, Massachusetts: The MathWorks Inc., 2012) and binned in log scale (0to10 5 ,100 bins). The scale of each bin was normalized by the