Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape.

The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes by comprehensively studying the mutations in specific genes, the high dimensionality of genotypic changes prevents us from developing a fitness landscape capable of predicting evolution for the whole cell. Herein, we address this problem by inferring the phenotype-based fitness landscape for antibiotic resistance evolution by quantifying the multidimensional phenotypic changes, i.e., time-series data of resistance for eight different drugs. We show that different peaks of the landscape correspond to different drug resistance mechanisms, thus supporting the validity of the inferred phenotype-fitness landscape. We further discuss how inferred phenotype-fitness landscapes could contribute to the prediction and control of evolution. This approach bridges the gap between phenotypic/genotypic changes and fitness while contributing to a better understanding of drug resistance evolution.

Deciphering the origin of developmental stability: The role of intracellular expression variability in evolutionary conservation.

Progress in evolutionary developmental biology (evo-devo) has deepened our understanding of how intrinsic properties of embryogenesis, along with natural selection and population genetics, shape phenotypic diversity. A focal point of recent empirical and theoretical research is the idea that highly developmentally stable phenotypes are more conserved in evolution. Previously, we demonstrated that in Japanese medaka (Oryzias latipes), embryonic stages and genes with high stability, estimated through whole-embryo RNA-seq, are highly conserved in subsequent generations. However, the precise origin of the stability of gene expression levels evaluated at the whole-embryo level remained unclear. Such stability could be attributed to two distinct sources: stable intracellular expression levels or spatially stable expression patterns. Here we demonstrate that stability observed in whole-embryo RNA-seq can be attributed to stability at the cellular level (low variability in gene expression at the cellular levels). We quantified the intercellular variations in expression levels and spatial gene expression patterns for seven key genes involved in patterning dorsoventral and rostrocaudal regions during early development in medaka. We evaluated intracellular variability by counting transcripts and found its significant correlation with variation observed in whole-embryo RNA-seq data. Conversely, variation in spatial gene expression patterns, assessed through intraindividual left-right asymmetry, showed no correlation. Given the previously reported correlation between stability and conservation of expression levels throughout embryogenesis, our findings suggest a potential general trend: the stability or instability of developmental systems-and the consequent evolutionary diversity-may be primarily anchored in intrinsic fundamental elements such as the variability of intracellular states.

Experimental evidence for the correlation between RNA structural fluctuations and the frequency of beneficial mutations.

RNA has been used as a model molecule to understand the adaptive evolution process owing to the simple relationship between the structure (i.e., phenotype) and sequence (i.e., genotype). RNA usually forms multiple substructures with similar thermodynamic stabilities, called structural fluctuations. Ancel and Fontana theoretically proposed that structural fluctuation is directly related to the ease of change in structures by mutations and thus works as a source of adaptive evolution; however, experimental verification is limited. Here, we analyzed 76 RNA genotypes that appeared in our previous in vitro evolution to examine whether (i) RNA fluctuation decreases as adaptive evolution proceeds and (ii) RNAs that have larger fluctuations tend to have higher frequencies of beneficial mutations. We first computationally estimated the structural fluctuations of all RNAs and observed that they tended to decrease as their fitness increased. We next measured the frequency of beneficial mutations for 10 RNA genotypes and observed that the total number of beneficial mutations was correlated with the size of the structural fluctuations. These results consistently support the idea that the structural fluctuation of RNA, at least those evaluated in our study, works as a source of adaptive evolution.

Rare-event sampling analysis uncovers the fitness landscape of the genetic code.

The genetic code refers to a rule that maps 64 codons to 20 amino acids. Nearly all organisms, with few exceptions, share the same genetic code, the standard genetic code (SGC). While it remains unclear why this universal code has arisen and been maintained during evolution, it may have been preserved under selection pressure. Theoretical studies comparing the SGC and numerically created hypothetical random genetic codes have suggested that the SGC has been subject to strong selection pressure for being robust against translation errors. However, these prior studies have searched for random genetic codes in only a small subspace of the possible code space due to limitations in computation time. Thus, how the genetic code has evolved, and the characteristics of the genetic code fitness landscape, remain unclear. By applying multicanonical Monte Carlo, an efficient rare-event sampling method, we efficiently sampled random codes from a much broader random ensemble of genetic codes than in previous studies, estimating that only one out of every 1020 random codes is more robust than the SGC. This estimate is significantly smaller than the previous estimate, one in a million. We also characterized the fitness landscape of the genetic code that has four major fitness peaks, one of which includes the SGC. Furthermore, genetic algorithm analysis revealed that evolution under such a multi-peaked fitness landscape could be strongly biased toward a narrow peak, in an evolutionary path-dependent manner.

Experimental demonstration of operon formation catalyzed by insertion sequence.

Operons are a hallmark of the genomic and regulatory architecture of prokaryotes. However, the mechanism by which two genes placed far apart gradually come close and form operons remains to be elucidated. Here, we propose a new model of the origin of operons: Mobile genetic elements called insertion sequences can facilitate the formation of operons by consecutive insertion-deletion-excision reactions. This mechanism barely leaves traces of insertion sequences and thus difficult to detect in nature. In this study, as a proof-of-concept, we reproducibly demonstrated operon formation in the laboratory. The insertion sequence IS3 and the insertion sequence excision enhancer are genes found in a broad range of bacterial species. We introduced these genes into insertion sequence-less Escherichia coli and found that, supporting our hypothesis, the activity of the two genes altered the expression of genes surrounding IS3, closed a 2.7 kb gap between a pair of genes, and formed new operons. This study shows how insertion sequences can facilitate the rapid formation of operons through locally increasing the structural mutation rates and highlights how coevolution with mobile elements may shape the organization of prokaryotic genomes and gene regulation.

Wickerhamiella bidentis sp. nov., a novel yeast species isolated from flowers and insects in Japan.

Two strains were isolated from flowers and insects in Japan, namely NBRC 115686T and NBRC 115687, respectively. Based on sequence analysis of the D1/D2 domain of the 26S large subunit (LSU) rRNA gene and the internal transcribed spacer (ITS) region and physiological characteristics, these strains were found to represent a novel yeast species of the genus Wickerhamiella. Considering pairwise sequence similarity, NBRC 115686T and NBRC 115687 differ from the type strain of the most closely related species, Wickerhamiella galacta NRRL Y-17645T, by 65-66 nucleotide substitutions with 12 gaps (11.65-11.83 %) in the D1/D2 domain of the LSU rRNA gene. The novel species differ from the closely related Wickerhamiella species in some physiological characteristics. For example, compared with Wickerhamiella galacta JCM 8257T, NBRC 115686T and NBRC 115687 assimilated d-galactose, and could grow at 35 and 37 °C. Hence, the name Wickerhamiella bidentis sp. nov. is proposed to accommodate this species in the genus Wickerhamiella. The holotype is NBRC 115686T (ex-type strain JCM 35540=CBS 18008).

Potential contribution of intrinsic developmental stability toward body plan conservation.

BACKGROUND: Despite the morphological diversity of animals, their basic anatomical patterns-the body plans in each animal phylum-have remained highly conserved over hundreds of millions of evolutionary years. This is attributed to conservation of the body plan-establishing developmental period (the phylotypic period) in each lineage. However, the evolutionary mechanism behind this phylotypic period conservation remains under debate. A variety of hypotheses based on the concept of modern synthesis have been proposed, such as negative selection in the phylotypic period through its vulnerability to embryonic lethality. Here we tested a new hypothesis that the phylotypic period is developmentally stable; it has less potential to produce phenotypic variations than the other stages, and this has most likely led to the evolutionary conservation of body plans. RESULTS: By analyzing the embryos of inbred Japanese medaka embryos raised under the same laboratory conditions and measuring the whole embryonic transcriptome as a phenotype, we found that the phylotypic period has greater developmental stability than other stages. Comparison of phenotypic differences between two wild medaka populations indicated that the phylotypic period and its genes in this period remained less variational, even after environmental and mutational modifications accumulated during intraspecies evolution. Genes with stable expression levels were enriched with those involved in cell-cell signalling and morphological specification such as Wnt and Hox, implying possible involvement in body plan development of these genes. CONCLUSIONS: This study demonstrated the correspondence between the developmental stage with low potential to produce phenotypic variations and that with low diversity in micro- and macroevolution, namely the phylotypic period. Whereas modern synthesis explains evolution as a process of shaping of phenotypic variations caused by mutations, our results highlight the possibility that phenotypic variations are readily limited by the intrinsic nature of organisms, namely developmental stability, thus biasing evolutionary outcomes.

Loss of function of Hog1 improves glycerol assimilation in Saccharomyces cerevisiae.

We previously isolated a mutant of Saccharomyces cerevisiae strain 85_9 whose glycerol assimilation was improved through adaptive laboratory evolution. To investigate the mechanism for this improved glycerol assimilation, genome resequencing of the 85_9 strain was performed, and the mutations in the open reading frame of HOG1, SIR3, SSB2, and KGD2 genes were found. Among these, a frameshift mutation in the HOG1 open reading frame was responsible for the improved glycerol assimilation ability of the 85_9 strain. Moreover, the HOG1 gene disruption improved glycerol assimilation. As HOG1 encodes a mitogen-activated protein kinase (MAPK), which is responsible for the signal transduction cascade in response to osmotic stress, namely the high osmolarity glycerol (HOG) pathway, we investigated the effect of the disruption of PBS2 gene encoding MAPK kinase for Hog1 MAPK on glycerol assimilation, revealing that PBS2 disruption can increase glycerol assimilation. These results indicate that loss of function of Hog1 improves glycerol assimilation in S. cerevisiae. However, single disruption of the SSK2, SSK22 and STE11 genes encoding protein kinases responsible for Pbs2 phosphorylation in the HOG pathway did not increase glycerol assimilation, while their triple disruption partially improved glycerol assimilation in S. cerevisiae. In addition, the HOG1 frameshift mutation did not improve glycerol assimilation in the STL1-overexpressing RIM15 disruptant strain, which was previously constructed with high glycerol assimilation ability. Furthermore, the effectiveness of the HOG1 disruptant as a bioproduction host was validated, indicating that the HOG1 CYB2 double disruptant can produce L-lactic acid from glycerol.

Acceleration of target production in co-culture by enhancing intermediate consumption through adaptive laboratory evolution.

Co-culture is a promising way to alleviate metabolic burden by dividing the metabolic pathways into several modules and sharing the conversion processes with multiple strains. Since an intermediate is passed from the donor to the recipient via the extracellular environment, it is inevitably diluted. Therefore, enhancing the intermediate consumption rate is important for increasing target productivity. In the present study, we demonstrated the enhancement of mevalonate consumption in Escherichia coli by adaptive laboratory evolution and applied the evolved strain to isoprenol production in an E. coli (upstream: glucose to mevalonate)-E. coli (downstream: mevalonate to isoprenol) co-culture. An engineered mevalonate auxotroph strain was repeatedly sub-cultured in a synthetic medium supplemented with mevalonate, where the mevalonate concentration was decreased stepwise from 100 to 20 µM. In five parallel evolution experiments, all growth rates gradually increased, resulting in five evolved strains. Whole-genome re-sequencing and reverse engineering identified three mutations involved in enhancing mevalonate consumption. After introducing nudF gene for producing isoprenol, the isoprenol-producing parental and evolved strains were respectively co-cultured with a mevalonate-producing strain. At an inoculation ratio of 1:3 (upstream:downstream), isoprenol production using the evolved strain was 3.3 times higher than that using the parental strain.

Theoretical modeling reveals that regulatory T cells increase T-cell interaction with antigen-presenting cells for stable immune tolerance.

The immune system in tolerance maintains cell diversity without responding to self-antigens. Foxp3-expressing CD25+CD4+ regulatory T cells (Tregs) inhibit T-cell activation through various molecular mechanisms. However, several key questions are still not resolved, including how Tregs control the immune response on the basis of their self-skewed T-cell receptor repertoire and how Tregs avoid impeding relevant immunity against pathogens. Here, we show that Tregs promote the proliferation of conventional T cells in the presence of excessive co-stimulation when murine T cells are stimulated in vitro with allogeneic antigen-presenting cells (APCs). Antigen-specific Tregs increase the number of cells interacting with dendritic cells (DCs) by increasing the number of viable DCs and the expression of adhesion molecules on DCs. Theoretical simulations and mathematical models representing the dynamics of T-APC interaction and T-cell numbers in a lymph node indicate that Tregs reduce the dissociation probability of T cells from APCs and increase the new association. These functions contribute to tolerance by enhancing the interaction of low-affinity T cells with APCs. Supporting the theoretical analyses, we found that reducing the T-cell numbers in mice increases the ratio of specific T cells among CD4+ T cells after immunization and effectively induces autoimmune diabetes in non obese diabetes mice. Thus, as a critical function, antigen-specific Tregs stabilize the immune state, irrespective of it being tolerant or responsive, by augmenting T-APC interaction. We propose a novel regulation model in which stable tolerance with large heterogeneous populations proceeds to a specific immune response through a transient state with few populations.

Enhancement of K-strategy evolution in histidine utilization using a container with compartments.

Evolutionary strategies in growth improvement can be classified into r- or K-strategies. The former strategy corresponds to an evolutionary increase in growth rate, whereas the latter corresponds to an increase in the maximum amount of organisms or carrying capacity. What determines the strategies to be adopted during evolution? Spatial structures that compartmentalize the population into small patches are key to inducing the K-strategy. Interestingly, previous evolution experiments using Escherichia coli in a glucose-limited batch culture showed that carrying capacity could improve evolutionally even in the absence of spatial structures. However, it is unclear if the lack of spatial structures can direct evolution toward high carrying capacity for utilization of other resources. To address this question, we established a simplified evolution experiment using histidine-requiring E. coli grown under histidine limitation in a container with compartments. We confirmed the importance of spatial structures in K-strategy evolution in histidine utilization. Whole genome sequencing of the K-adapted strains showed functional variety of the mutated genes during the fitness-increasing period. These results validate the importance of spatial structures and imply that restriction of K-strategy evolution on a sort of nutrients is attributable to a paucity of appropriate selection rather than a paucity of causal mutation.

SCODE: an efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation.

MOTIVATION: The analysis of RNA-Seq data from individual differentiating cells enables us to reconstruct the differentiation process and the degree of differentiation (in pseudo-time) of each cell. Such analyses can reveal detailed expression dynamics and functional relationships for differentiation. To further elucidate differentiation processes, more insight into gene regulatory networks is required. The pseudo-time can be regarded as time information and, therefore, single-cell RNA-Seq data are time-course data with high time resolution. Although time-course data are useful for inferring networks, conventional inference algorithms for such data suffer from high time complexity when the number of samples and genes is large. Therefore, a novel algorithm is necessary to infer networks from single-cell RNA-Seq during differentiation. RESULTS: In this study, we developed the novel and efficient algorithm SCODE to infer regulatory networks, based on ordinary differential equations. We applied SCODE to three single-cell RNA-Seq datasets and confirmed that SCODE can reconstruct observed expression dynamics. We evaluated SCODE by comparing its inferred networks with use of a DNaseI-footprint based network. The performance of SCODE was best for two of the datasets and nearly best for the remaining dataset. We also compared the runtimes and showed that the runtimes for SCODE are significantly shorter than for alternatives. Thus, our algorithm provides a promising approach for further single-cell differentiation analyses. AVAILABILITY AND IMPLEMENTATION: The R source code of SCODE is available at https://github.com/hmatsu1226/SCODE. CONTACT: hirotaka.matsumoto@riken.jp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Application of adaptive laboratory evolution to overcome a flux limitation in an Escherichia coli production strain.

Gene deletion strategies using flux balance analysis (FBA) have improved the growth-coupled production of various compounds. However, the productivities were often below the expectation because the cells failed to adapt to these genetic perturbations. Here, we demonstrate the productivity of the succinate of the designed gene deletion strain was improved by adaptive laboratory evolution (ALE). Although FBA predicted deletions of adhE-pykAF-gldA-pflB lead to produce succinate from glycerol with a yield of 0.45 C-mol/C-mol, the knockout mutant did not produce only 0.08 C-mol/Cmol, experimentally. After the ALE experiments, the highest succinate yield of an evolved strain reached to the expected value. Genome sequencing analysis revealed all evolved strains possessed novel mutations in ppc of I829S or R849S. In vitro enzymatic assay and metabolic profiling analysis revealed that these mutations desensitizing an allosteric inhibition by L-aspartate and improved the flux through Ppc, while the activity of Ppc in the unevolved strain was tightly regulated by L-aspartate. These result demonstrated that the evolved strains achieved the improvement of succinate production by expanding the flux space of Ppc, realizing the predicted metabolic state by FBA.

Metabolic dynamics restricted by conserved carriers: Jamming and feedback.

To uncover the processes and mechanisms of cellular physiology, it first necessary to gain an understanding of the underlying metabolic dynamics. Recent studies using a constraint-based approach succeeded in predicting the steady states of cellular metabolic systems by utilizing conserved quantities in the metabolic networks such as carriers such as ATP/ADP as an energy carrier or NADH/NAD+ as a hydrogen carrier. Although such conservation quantities restrict not only the steady state but also the dynamics themselves, the latter aspect has not yet been completely understood. Here, to study the dynamics of metabolic systems, we propose adopting a carrier cycling cascade (CCC), which includes the dynamics of both substrates and carriers, a commonly observed motif in metabolic systems such as the glycolytic and fermentation pathways. We demonstrate that the conservation laws lead to the jamming of the flux and feedback. The CCC can show slow relaxation, with a longer timescale than that of elementary reactions, and is accompanied by both robustness against small environmental fluctuations and responsiveness against large environmental changes. Moreover, the CCC demonstrates robustness against internal fluctuations due to the feedback based on the moiety conservation. We identified the key parameters underlying the robustness of this model against external and internal fluctuations and estimated it in several metabolic systems.

Understanding and engineering alcohol-tolerant bacteria using OMICS technology.

Microbes are capable of producing alcohols, making them an important source of alternative energy that can replace fossil fuels. However, these alcohols can be toxic to the microbes themselves, retaring or inhibiting cell growth and decreasing the production yield. One solution is improving the alcohol tolerance of such alcohol-producing organisms. Advances in omics technologies, including transcriptomic, proteomic, metabolomic, and genomic technologies, have helped us understand the complex mechanisms underlying alcohol toxicity, and such advances could assist in devising strategies for engineering alcohol-tolerant strains. This review highlights these advances and discusses strategies for improving alcohol tolerance using omics analyses.

Acceleration and suppression of resistance development by antibiotic combinations.

BACKGROUND: The emergence and spread of antibiotic resistance in bacteria is becoming a global public health problem. Combination therapy, i.e., the simultaneous use of multiple antibiotics, is used for long-term treatment to suppress the emergence of resistant strains. However, the effect of the combinatorial use of multiple drugs on the development of resistance remains elusive, especially in a quantitative assessment. RESULTS: To understand the evolutionary dynamics under combination therapy, we performed laboratory evolution of Escherichia coli under simultaneous addition of two-drug combinations. We demonstrated that simultaneous addition of a certain combinations of two drugs with collateral sensitivity to each other could suppress the acquisition of resistance to both drugs. Furthermore, we found that the combinatorial use of enoxacin, a DNA replication inhibitor, with Chloramphenicol can accelerate acquisition of resistance to Chloramphenicol. Genome resequencing analyses of the evolved strains suggested that the acceleration of resistance acquisition was caused by an increase of mutation frequency when enoxacin was added. CONCLUSIONS: Integration of laboratory evolution and whole-genome sequencing enabled us to characterize the development of resistance in bacteria under combination therapy. These results provide a basis for rational selection of antibiotic combinations that suppress resistance development effectively.

The cyclic gene Hes1 contributes to diverse differentiation responses of embryonic stem cells.

Stem cells do not all respond the same way, but the mechanisms underlying this heterogeneity are not well understood. Here, we found that expression of Hes1 and its downstream genes oscillate in mouse embryonic stem (ES) cells. Those expressing low and high levels of Hes1 tended to differentiate into neural and mesodermal cells, respectively. Furthermore, inactivation of Hes1 facilitated neural differentiation more uniformly at earlier time. Thus, Hes1-null ES cells display less heterogeneity in both the differentiation timing and fate choice, suggesting that the cyclic gene Hes1 contributes to heterogeneous responses of ES cells even under the same environmental conditions.

Pluripotency, Differentiation, and Reprogramming: A Gene Expression Dynamics Model with Epigenetic Feedback Regulation.

Embryonic stem cells exhibit pluripotency: they can differentiate into all types of somatic cells. Pluripotent genes such as Oct4 and Nanog are activated in the pluripotent state, and their expression decreases during cell differentiation. Inversely, expression of differentiation genes such as Gata6 and Gata4 is promoted during differentiation. The gene regulatory network controlling the expression of these genes has been described, and slower-scale epigenetic modifications have been uncovered. Although the differentiation of pluripotent stem cells is normally irreversible, reprogramming of cells can be experimentally manipulated to regain pluripotency via overexpression of certain genes. Despite these experimental advances, the dynamics and mechanisms of differentiation and reprogramming are not yet fully understood. Based on recent experimental findings, we constructed a simple gene regulatory network including pluripotent and differentiation genes, and we demonstrated the existence of pluripotent and differentiated states from the resultant dynamical-systems model. Two differentiation mechanisms, interaction-induced switching from an expression oscillatory state and noise-assisted transition between bistable stationary states, were tested in the model. The former was found to be relevant to the differentiation process. We also introduced variables representing epigenetic modifications, which controlled the threshold for gene expression. By assuming positive feedback between expression levels and the epigenetic variables, we observed differentiation in expression dynamics. Additionally, with numerical reprogramming experiments for differentiated cells, we showed that pluripotency was recovered in cells by imposing overexpression of two pluripotent genes and external factors to control expression of differentiation genes. Interestingly, these factors were consistent with the four Yamanaka factors, Oct4, Sox2, Klf4, and Myc, which were necessary for the establishment of induced pluripotent stem cells. These results, based on a gene regulatory network and expression dynamics, contribute to our wider understanding of pluripotency, differentiation, and reprogramming of cells, and they provide a fresh viewpoint on robustness and control during development.

Phenotypic convergence in bacterial adaptive evolution to ethanol stress.

BACKGROUND: Bacterial cells have a remarkable ability to adapt to environmental changes, a phenomenon known as adaptive evolution. During adaptive evolution, phenotype and genotype dynamically changes; however, the relationship between these changes and associated constraints is yet to be fully elucidated. RESULTS: In this study, we analyzed phenotypic and genotypic changes in Escherichia coli cells during adaptive evolution to ethanol stress. Phenotypic changes were quantified by transcriptome and metabolome analyses and were similar among independently evolved ethanol tolerant populations, which indicate the existence of evolutionary constraints in the dynamics of adaptive evolution. Furthermore, the contribution of identified mutations in one of the tolerant strains was evaluated using site-directed mutagenesis. The result demonstrated that the introduction of all identified mutations cannot fully explain the observed tolerance in the tolerant strain. CONCLUSIONS: The results demonstrated that the convergence of adaptive phenotypic changes and diverse genotypic changes, which suggested that the phenotype-genotype mapping is complex. The integration of transcriptome and genome data provides a quantitative understanding of evolutionary constraints.

Bacterial transcriptome reorganization in thermal adaptive evolution.

BACKGROUND: Evolution optimizes a living system at both the genome and transcriptome levels. Few studies have investigated transcriptome evolution, whereas many studies have explored genome evolution in experimentally evolved cells. However, a comprehensive understanding of evolutionary mechanisms requires knowledge of how evolution shapes gene expression. Here, we analyzed Escherichia coli strains acquired during long-term thermal adaptive evolution. RESULTS: Evolved and ancestor Escherichia coli cells were exponentially grown under normal and high temperatures for subsequent transcriptome analysis. We found that both the ancestor and evolved cells had comparable magnitudes of transcriptional change in response to heat shock, although the evolutionary progression of their expression patterns during exponential growth was different at either normal or high temperatures. We also identified inverse transcriptional changes that were mediated by differences in growth temperatures and genotypes, as well as negative epistasis between genotype-and heat shock-induced transcriptional changes. Principal component analysis revealed that transcriptome evolution neither approached the responsive state at the high temperature nor returned to the steady state at the regular temperature. We propose that the molecular mechanisms of thermal adaptive evolution involve the optimization of steady-state transcriptomes at high temperatures without disturbing the heat shock response. CONCLUSIONS: Our results suggest that transcriptome evolution works to maintain steady-state gene expression during constrained differentiation at various evolutionary stages, while also maintaining responsiveness to environmental stimuli and transcriptome homeostasis.