Precise regulation of gene expression dynamics favors complex promoter architectures

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.

Two distinct promoter architectures centered on dynamic nucleosomes control ribosomal protein gene transcription

In yeast, ribosome production is controlled transcriptionally by tight coregulation of the 138 ribosomal protein genes (RPGs). RPG promoters display limited sequence homology, and the molecular basis for their coregulation remains largely unknown. Here we identify two prevalent RPG promoter types, both characterized by upstream binding of the general transcription factor (TF) Rap1 followed by the RPG-specific Fhl1/Ifh1 pair, with one type also binding the HMG-B protein Hmo1. We show that the regulatory properties of the two promoter types are remarkably similar, suggesting that they are determined to a large extent by Rap1 and the Fhl1/Ifh1 pair. Rapid depletion experiments allowed us to define a hierarchy of TF binding in which Rap1 acts as a pioneer factor required for binding of all other TFs. We also uncovered unexpected features underlying recruitment of Fhl1, whose forkhead DNA-binding domain is not required for binding at most promoters, and Hmo1, whose binding is supported by repeated motifs. Finally, we describe unusually micrococcal nuclease (MNase)-sensitive nucleosomes at all RPG promoters, located between the canonical +1 and -1 nucleosomes, which coincide with sites of Fhl1/Ifh1 and Hmo1 binding. We speculate that these "fragile" nucleosomes play an important role in regulating RPG transcriptional output.

Stochastic noise reduction upon complexification: positively correlated birth-death type systems

Cell systems consist of a huge number of various molecules that display specific patterns of interactions, which have a determining influence on the cell׳s functioning. In general, such complexity is seen to increase with the complexity of the organism, with a concomitant increase of the accuracy and specificity of the cellular processes. The question thus arises how the complexification of systems - modeled here by simple interacting birth-death type processes - can lead to a reduction of the noise - described by the variance of the number of molecules. To gain understanding of this issue, we investigated the difference between a single system containing molecules that are produced and degraded, and the same system - with the same average number of molecules - connected to a buffer. We modeled these systems using Itō stochastic differential equations in discrete time, as they allow straightforward analytical developments. In general, when the molecules in the system and the buffer are positively correlated, the variance on the number of molecules in the system is found to decrease compared to the equivalent system without a buffer. Only buffers that are too noisy themselves tend to increase the noise in the main system. We tested this result on two model cases, in which the system and the buffer contain proteins in their active and inactive state, or protein monomers and homodimers. We found that in the second test case, where the interconversion terms are non-linear in the number of molecules, the noise reduction is much more pronounced; it reaches up to 20% reduction of the Fano factor with the parameter values tested in numerical simulations on an unperturbed birth-death model. We extended our analysis to two arbitrary interconnected systems, and found that the sum of the noise levels in the two systems generally decreases upon interconnection if the molecules they contain are positively correlated.

Dynamic characterization of growth and gene expression using high-throughput automated flow cytometry

Cells adjust to changes in environmental conditions using complex regulatory programs. These cellular programs are the result of an intricate interplay between gene expression, cellular growth and protein degradation. Technologies that enable simultaneous and time-resolved measurements of these variables are necessary to dissect cellular homeostatic strategies. Here we report the development of an automated flow cytometry robotic setup that enables real-time measurement of precise and simultaneous relative growth and protein synthesis rates of multiplexed microbial populations across many conditions. These measurements generate quantitative profiles of dynamically evolving protein synthesis and degradation rates. We demonstrate this setup in the context of gene regulation of the unfolded protein response (UPR) of Saccharomyces cerevisiae and uncover a dynamic and complex landscape of gene expression, growth dynamics and proteolysis following perturbations.

Eukaryotic transcriptional dynamics: from single molecules to cell populations

Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time- and energy-dependence at the molecular level.

A sticky situation: untangling the transcriptional network controlling biofilm development in Candida albicans

Candida albicans is a commensal microorganism of the human microbiome; it is also the most prevalent fungal pathogen of humans. Many infections caused by C. albicans are a direct consequence of its proclivity to form biofilms—resilient, surface-associated communities of cells where individual cells acquire specialized properties that are distinct from those observed in suspension cultures. We recently identified the transcriptional network that orchestrates the formation of biofilms in C. albicans. These results set the stage for understanding how biofilms are formed and, once formed, how the specialized properties of biofilms are elaborated. This information will provide new insight for understanding biofilms in more detail and may lead to improvements in preventing and treating biofilm-based infections in the future.

A recently evolved transcriptional network controls biofilm development in Candida albicans

A biofilm is an organized, resilient group of microbes in which individual cells acquire properties, such as drug resistance, that are distinct from those observed in suspension cultures. Here, we describe and analyze the transcriptional network controlling biofilm formation in the pathogenic yeast Candida albicans, whose biofilms are a major source of medical device-associated infections. We have combined genetic screens, genome-wide approaches, and two in vivo animal models to describe a master circuit controlling biofilm formation, composed of six transcription regulators that form a tightly woven network with ∼1,000 target genes. Evolutionary analysis indicates that the biofilm network has rapidly evolved: genes in the biofilm circuit are significantly weighted toward genes that arose relatively recently with ancient genes being underrepresented. This circuit provides a framework for understanding many aspects of biofilm formation by C. albicans in a mammalian host. It also provides insights into how complex cell behaviors can arise from the evolution of transcription circuits.

Non-equilibrium hyperbolic transport in transcriptional regulation

In this work we studied memory and irreversible transport phenomena in a non-equilibrium thermodynamical model for genomic transcriptional regulation. Transcriptional regulation possess an extremely complex phenomenology, and it is, of course, of foremost importance in organismal cell development and in the pathogenesis of complex diseases. A better understanding of the way in which these processes occur is mandatory to optimize the construction of gene regulatory networks, but also to connect these networks with multi-scale phenomena (e.g. metabolism, signalling pathways, etc.) under an integrative Systems Biology-like vision. In this paper we analyzed three simple mechanisms of genetic stimulation: an instant pulse, a periodic biochemical signal and a saturation process with sigmoidal kinetics and from these we derived the system's thermodynamical response, in the form of, for example, anomalous transcriptional bursts.

Effect of promoter architecture on the cell-to-cell variability in gene expression

According to recent experimental evidence, promoter architecture, defined by the number, strength and regulatory role of the operators that control transcription, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect variability in gene expression in a systematic rather than case-by-case fashion. In this article we make such a systematic investigation, based on a microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcriptional output from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can be used to test kinetic models of gene regulation. The emphasis of the discussion is on prokaryotic gene regulation, but our analysis can be extended to eukaryotic cells as well.

Conserved expression without conserved regulatory sequence: the more things change, the more they stay the same

Regulatory regions with similar transcriptional output often have little overt sequence similarity, both within and between genomes. Although cis- and trans-regulatory changes can contribute to sequence divergence without dramatically altering gene expression outputs, heterologous DNA often functions similarly in organisms that share little regulatory sequence similarities (e.g. human DNA in fish), indicating that trans-regulatory mechanisms tend to diverge more slowly and can accommodate a variety of cis-regulatory configurations. This capacity to 'tinker' with regulatory DNA probably relates to the complexity, robustness and evolvability of regulatory systems, but cause-and-effect relationships among evolutionary processes and properties of regulatory systems remain a topic of debate. The challenge of understanding the concrete mechanisms underlying cis-regulatory evolution - including the conservation of function without the conservation of sequence - relates to the challenge of understanding the function of regulatory systems in general. Currently, we are largely unable to recognize functionally similar regulatory DNA.