The evolution, evolvability and engineering of gene regulatory DNA.

Mutations in non-coding regulatory DNA sequences can alter gene expression, organismal phenotype and fitness1-3. Constructing complete fitness landscapes, in which DNA sequences are mapped to fitness, is a long-standing goal in biology, but has remained elusive because it is challenging to generalize reliably to vast sequence spaces4-6. Here we build sequence-to-expression models that capture fitness landscapes and use them to decipher principles of regulatory evolution. Using millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Saccharomyces cerevisiae, we learn deep neural network models that generalize with excellent prediction performance, and enable sequence design for expression engineering. Using our models, we study expression divergence under genetic drift and strong-selection weak-mutation regimes to find that regulatory evolution is rapid and subject to diminishing returns epistasis; that conflicting expression objectives in different environments constrain expression adaptation; and that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for using such models to detect signatures of selection on expression from natural variation in regulatory sequences and use it to discover an instance of convergent regulatory evolution. We assess mutational robustness, finding that regulatory mutation effect sizes follow a power law, characterize regulatory evolvability, visualize promoter fitness landscapes, discover evolvability archetypes and illustrate the mutational robustness of natural regulatory sequence populations. Our work provides a general framework for designing regulatory sequences and addressing fundamental questions in regulatory evolution.

Coordinated host-pathogen transcriptional dynamics revealed using sorted subpopulations and single macrophages infected with Candida albicans.

The outcome of fungal infections depends on interactions with innate immune cells. Within a population of macrophages encountering Candida albicans, there are distinct host-pathogen trajectories; however, little is known about the molecular heterogeneity that governs these fates. Here we developed an experimental system to separate interaction stages and single macrophage cells infected with C. albicans from uninfected cells and assessed transcriptional variability in the host and fungus. Macrophages displayed an initial up-regulation of pathways involved in phagocytosis and proinflammatory response after C. albicans exposure that declined during later time points. Phagocytosed C. albicans shifted expression programs to survive the nutrient poor phagosome and remodeled the cell wall. The transcriptomes of single infected macrophages and phagocytosed C. albicans displayed a tightly coordinated shift in gene expression co-stages and revealed expression bimodality and differential splicing that may drive infection outcome. This work establishes an approach for studying host-pathogen trajectories to resolve heterogeneity in dynamic populations.

Zinc Cluster Transcription Factors Alter Virulence in Candida albicans.

Almost all humans are colonized with Candida albicans However, in immunocompromised individuals, this benign commensal organism becomes a serious, life-threatening pathogen. Here, we describe and analyze the regulatory networks that modulate innate responses in the host niches. We identified Zcf15 and Zcf29, two Zinc Cluster transcription Factors (ZCF) that are required for C. albicans virulence. Previous sequence analysis of clinical C. albicans isolates from immunocompromised patients indicates that both ZCF genes diverged during clonal evolution. Using in vivo animal models, ex vivo cell culture methods, and in vitro sensitivity assays, we demonstrate that knockout mutants of both ZCF15 and ZCF29 are hypersensitive to reactive oxygen species (ROS), suggesting they help neutralize the host-derived ROS produced by phagocytes, as well as establish a sustained infection in vivo Transcriptomic analysis of mutants under resting conditions where cells were not experiencing oxidative stress revealed a large network that control macro and micronutrient homeostasis, which likely contributes to overall pathogen fitness in host niches. Under oxidative stress, both transcription factors regulate a separate set of genes involved in detoxification of ROS and down-regulating ribosome biogenesis. ChIP-seq analysis, which reveals vastly different binding partners for each transcription factor (TF) before and after oxidative stress, further confirms these results. Furthermore, the absence of a dominant binding motif likely facilitates their mobility, and supports the notion that they represent a recent expansion of the ZCF family in the pathogenic Candida species. Our analyses provide a framework for understanding new aspects of the interface between C. albicans and host defense response, and extends our understanding of how complex cell behaviors are linked to the evolution of TFs.

Natural gene expression variation studies in yeast.

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Mitochondrial dysfunction remodels one-carbon metabolism in human cells.

Mitochondrial dysfunction is associated with a spectrum of human disorders, ranging from rare, inborn errors of metabolism to common, age-associated diseases such as neurodegeneration. How these lesions give rise to diverse pathology is not well understood, partly because their proximal consequences have not been well-studied in mammalian cells. Here we provide two lines of evidence that mitochondrial respiratory chain dysfunction leads to alterations in one-carbon metabolism pathways. First, using hypothesis-generating metabolic, proteomic, and transcriptional profiling, followed by confirmatory experiments, we report that mitochondrial DNA depletion leads to an ATF4-mediated increase in serine biosynthesis and transsulfuration. Second, we show that lesioning the respiratory chain impairs mitochondrial production of formate from serine, and that in some cells, respiratory chain inhibition leads to growth defects upon serine withdrawal that are rescuable with purine or formate supplementation. Our work underscores the connection between the respiratory chain and one-carbon metabolism with implications for understanding mitochondrial pathogenesis.

Early-branching gut fungi possess a large, comprehensive array of biomass-degrading enzymes.

The fungal kingdom is the source of almost all industrial enzymes in use for lignocellulose bioprocessing. We developed a systems-level approach that integrates transcriptomic sequencing, proteomics, phenotype, and biochemical studies of relatively unexplored basal fungi. Anaerobic gut fungi isolated from herbivores produce a large array of biomass-degrading enzymes that synergistically degrade crude, untreated plant biomass and are competitive with optimized commercial preparations from Aspergillus and Trichoderma. Compared to these model platforms, gut fungal enzymes are unbiased in substrate preference due to a wealth of xylan-degrading enzymes. These enzymes are universally catabolite-repressed and are further regulated by a rich landscape of noncoding regulatory RNAs. Additionally, we identified several promising sequence-divergent enzyme candidates for lignocellulosic bioprocessing.

Comparative Transcriptomics in Yeasts.

Comparative functional genomics approaches have already shed an important light on the evolution of gene expression that underlies phenotypic diversity. However, comparison across many species in a phylogeny presents several major challenges. Here, we describe our experimental framework for comparative transcriptomics in a complex phylogeny.

Reconstruction and Analysis of the Evolution of Modular Transcriptional Regulatory Programs Using Arboretum.

Comparative functional genomics aims to measure and compare genome-wide functional data such as transcriptomes, proteomes, and epigenomes across multiple species to study the conservation and divergence patterns of such quantitative measurements. However, computational methods to systematically compare these quantitative genomic profiles across multiple species are in their infancy. We developed Arboretum, a novel algorithm to identify modules of co-expressed genes and trace their evolutionary history across multiple species from a complex phylogeny. To interpret the results from Arboretum we developed several measures to examine the extent of conservation and divergence in modules and their relationship to species lifestyle, cis-regulatory elements, and gene duplication. We applied Arboretum to study the evolution of modular transcriptional regulatory programs controlling transcriptional response to different environmental stresses in the yeast Ascomycota phylogeny. We found that modules of similar patterns of expression captured the transcriptional responses to different stresses across species; however, the genes exhibiting these patterns were not the same. Divergence in module membership was associated with changes in lifestyle and specific clades and that gene duplication was a major factor contributing to the divergence of module membership.

The evolution of drug resistance in clinical isolates of Candida albicans.

Candida albicans is both a member of the healthy human microbiome and a major pathogen in immunocompromised individuals. Infections are typically treated with azole inhibitors of ergosterol biosynthesis often leading to drug resistance. Studies in clinical isolates have implicated multiple mechanisms in resistance, but have focused on large-scale aberrations or candidate genes, and do not comprehensively chart the genetic basis of adaptation. Here, we leveraged next-generation sequencing to analyze 43 isolates from 11 oral candidiasis patients. We detected newly selected mutations, including single-nucleotide polymorphisms (SNPs), copy-number variations and loss-of-heterozygosity (LOH) events. LOH events were commonly associated with acquired resistance, and SNPs in 240 genes may be related to host adaptation. Conversely, most aneuploidies were transient and did not correlate with drug resistance. Our analysis also shows that isolates also varied in adherence, filamentation, and virulence. Our work reveals new molecular mechanisms underlying the evolution of drug resistance and host adaptation.

YMAP: a pipeline for visualization of copy number variation and loss of heterozygosity in eukaryotic pathogens.

The design of effective antimicrobial therapies for serious eukaryotic pathogens requires a clear understanding of their highly variable genomes. To facilitate analysis of copy number variations, single nucleotide polymorphisms and loss of heterozygosity events in these pathogens, we developed a pipeline for analyzing diverse genome-scale datasets from microarray, deep sequencing, and restriction site associated DNA sequence experiments for clinical and laboratory strains of Candida albicans, the most prevalent human fungal pathogen. The YMAP pipeline (http://lovelace.cs.umn.edu/Ymap/) automatically illustrates genome-wide information in a single intuitive figure and is readily modified for the analysis of other pathogens with small genomes.

Extracting data from the muck: deriving biological insight from complex microbial communities and non-model organisms with next generation sequencing.

It is becoming increasingly clear that microbes within microbial communities, for which cultured isolates have not yet been obtained, have an immense, untapped reservoir of enzymes that could help address grand challenges in human health, energy, and sustainability. Despite the obstacles associated with culturing these microbes, recent advances in next-generation sequencing (NGS) have made it possible to explore complex microbial communities in their native context for the first time. Key to extracting meaning from rapidly growing NGS datasets are bioinformatics tools that assemble the sequence data, annotate homologous sequences and interrogate it to reveal regulatory patterns. Complementing this are advances in proteomics that can link NGS data to biological function. This combination of next generation sequencing, proteomics and bioinformatic analysis forms a powerful tool to study non-model microbes, which will transform what we know about these dynamic systems.

Correction: Evolutionary principles of modular gene regulation in yeasts.

[This corrects the article DOI: 10.7554/eLife.00603.].

Evolutionary principles of modular gene regulation in yeasts.

Divergence in gene regulation can play a major role in evolution. Here, we used a phylogenetic framework to measure mRNA profiles in 15 yeast species from the phylum Ascomycota and reconstruct the evolution of their modular regulatory programs along a time course of growth on glucose over 300 million years [corrected]. We found that modules have diverged proportionally to phylogenetic distance, with prominent changes in gene regulation accompanying changes in lifestyle and ploidy, especially in carbon metabolism. Paralogs have significantly contributed to regulatory divergence, typically within a very short window from their duplication. Paralogs from a whole genome duplication (WGD) event have a uniquely substantial contribution that extends over a longer span. Similar patterns occur when considering the evolution of the heat shock regulatory program measured in eight of the species, suggesting that these are general evolutionary principles. DOI:http://dx.doi.org/10.7554/eLife.00603.001.

Convergent Evolution of Calcineurin Pathway Roles in Thermotolerance and Virulence in Candida glabrata.

Candida glabrata is an emerging human fungal pathogen that is frequently drug tolerant, resulting in difficulties in treatment and a higher mortality in immunocompromised patients. The calcium-activated protein phosphatase calcineurin plays critical roles in controlling drug tolerance, hyphal growth, and virulence in diverse fungal pathogens via distinct mechanisms involving survival in serum or growth at host temperature (37° and higher). Here, we comprehensively studied the calcineurin signaling cascade in C. glabrata and found novel and uncharacterized functions of calcineurin and its downstream target Crz1 in governing thermotolerance, intracellular architecture, and pathogenesis in murine ocular, urinary tract, and systemic infections. This represents a second independent origin of a role for calcineurin in thermotolerant growth of a major human fungal pathogen, distinct from that which arose independently in Cryptococcus neoformans. Calcineurin also promotes survival of C. glabrata in serum via mechanisms distinct from C. albicans and thereby enables establishment of tissue colonization in a murine systemic infection model. To understand calcineurin signaling in detail, we performed global transcript profiling analysis and identified calcineurin- and Crz1-dependent genes in C. glabrata involved in cell wall biosynthesis, heat shock responses, and calcineurin function. Regulators of calcineurin (RCN) are a novel family of calcineurin modifiers, and two members of this family were identified in C. glabrata: Rcn1 and Rcn2. Our studies demonstrate that Rcn2 expression is controlled by calcineurin and Crz1 to function as a feedback inhibitor of calcineurin in a circuit required for calcium tolerance in C. glabrata. In contrast, the calcineurin regulator Rcn1 activates calcineurin signaling. Interestingly, neither Rcn1 nor Rcn2 is required for virulence in a murine systemic infection model. Taken together, our findings show that calcineurin signaling plays critical roles in thermotolerance and virulence, and that Rcn1 and Rcn2 have opposing functions in controlling calcineurin signaling in C. glabrata.

Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.

Comparative functional genomics of the fission yeasts.

The fission yeast clade--comprising Schizosaccharomyces pombe, S. octosporus, S. cryophilus, and S. japonicus--occupies the basal branch of Ascomycete fungi and is an important model of eukaryote biology. A comparative annotation of these genomes identified a near extinction of transposons and the associated innovation of transposon-free centromeres. Expression analysis established that meiotic genes are subject to antisense transcription during vegetative growth, which suggests a mechanism for their tight regulation. In addition, trans-acting regulators control new genes within the context of expanded functional modules for meiosis and stress response. Differences in gene content and regulation also explain why, unlike the budding yeast of Saccharomycotina, fission yeasts cannot use ethanol as a primary carbon source. These analyses elucidate the genome structure and gene regulation of fission yeast and provide tools for investigation across the Schizosaccharomyces clade.

Ploidy controls the success of mutators and nature of mutations during budding yeast evolution.

BACKGROUND: We used the budding yeast Saccharomyces cerevisiae to ask how elevated mutation rates affect the evolution of asexual eukaryotic populations. Mismatch repair defective and nonmutator strains were competed during adaptation to four laboratory environments (rich medium, low glucose, high salt, and a nonfermentable carbon source). RESULTS: In diploids, mutators have an advantage over nonmutators in all conditions, and mutators that win competitions are on average fitter than nonmutator winners. In contrast, haploid mutators have no advantage when competed against haploid nonmutators, and haploid mutator winners are less fit than nonmutator winners. The diploid mutator winners were all superior to their ancestors both in the condition they had adapted to, and in two of the other conditions. This phenotype was due to a mutation or class of mutations that confers a large growth advantage during the respiratory phase of yeast cultures that precedes stationary phase. This generalist mutation(s) was not selected in diploid nonmutator strains or in haploid strains, which adapt primarily by fixing specialist (condition-specific) mutations. In diploid mutators, such mutations also occur, and the majority accumulates after the fixation of the generalist mutation. CONCLUSIONS: We conclude that the advantage of mutators depends on ploidy and that diploid mutators can give rise to beneficial mutations that are inaccessible to nonmutators and haploid mutators.