Evolution of context dependent regulation by expansion of feast/famine regulatory proteins

BACKGROUND: Expansion of transcription factors is believed to have played a crucial role in evolution of all organisms by enabling them to deal with dynamic environments and colonize new environments. We investigated how the expansion of the Feast/Famine Regulatory Protein (FFRP) or Lrp-like proteins into an eight-member family in Halobacterium salinarum NRC-1 has aided in niche-adaptation of this archaeon to a complex and dynamically changing hypersaline environment.RESULTS: We mapped genome-wide binding locations for all eight FFRPs, investigated their preference for binding different effector molecules, and identified the contexts in which they act by analyzing transcriptional responses across 35 growth conditions that mimic different environmental and nutritional conditions this organism is likely to encounter in the wild. Integrative analysis of these data constructed an FFRP regulatory network with conditionally active states that reveal how interrelated variations in DNA-binding domains, effector-molecule preferences, and binding sites in target gene promoters have tuned the functions of each FFRP to the environments in which they act. We demonstrate how conditional regulation of similar genes by two FFRPs, AsnC (an activator) and VNG1237C (a repressor), have striking environment-specific fitness consequences for oxidative stress management and growth, respectively.CONCLUSIONS: This study provides a systems perspective into the evolutionary process by which gene duplication within a transcription factor family contributes to environment-specific adaptation of an organism

Phylogenetically Driven Sequencing of Extremely Halophilic Archaea Reveals Strategies for Static and Dynamic Osmo-response

© 2014. Organisms across the tree of life use a variety of mechanisms to respond to stress-inducing fluctuations in osmotic conditions. Cellular response mechanisms and phenotypes associated with osmoadaptation also play important roles in bacterial virulence, human health, agricultural production and many other biological systems. To improve understanding of osmoadaptive strategies, we have generated 59 high-quality draft genomes for the haloarchaea (a euryarchaeal clade whose members thrive in hypersaline environments and routinely experience drastic changes in environmental salinity) and analyzed these new genomes in combination with those from 21 previously sequenced haloarchaeal isolates. We propose a generalized model for haloarchaeal management of cytoplasmic osmolarity in response to osmotic shifts, where potassium accumulation and sodium expulsion during osmotic upshock are accomplished via secondary transport using the proton gradient as an energy source, and potassium loss during downshock is via a combination of secondary transport and non-specific ion loss through mechanosensitive channels. We also propose new mechanisms for magnesium and chloride accumulation. We describe the expansion and differentiation of haloarchaeal general transcription factor families, including two novel expansions of the TATA-binding protein family, and discuss their potential for enabling rapid adaptation to environmental fluxes. We challenge a recent high-profile proposal regarding the evolutionary origins of the haloarchaea by showing that inclusion of additional genomes significantly reduces support for a proposed large-scale horizontal gene transfer into the ancestral haloarchaeon from the bacterial domain. The combination of broad (17 genera) and deep (≥5 species in four genera) sampling of a phenotypically unified clade has enabled us to uncover both highly conserved and specialized features of osmoadaptation. Finally, we demonstrate the broad utility of such datasets, for metagenomics, improvements to automated gene annotation and investigations of evolutionary processes

DREAM4: Combining Genetic and Dynamic Information to Identify Biological Networks and Dynamical Models

Current technologies have lead to the availability of multiple genomic data types in sufficient quantity and quality to serve as a basis for automatic global network inference. Accordingly, there are currently a large variety of network inference methods that learn regulatory networks to varying degrees of detail. These methods have different strengths and weaknesses and thus can be complementary. However, combining different methods in a mutually reinforcing manner remains a challenge.We investigate how three scalable methods can be combined into a useful network inference pipeline. The first is a novel t-test-based method that relies on a comprehensive steady-state knock-out dataset to rank regulatory interactions. The remaining two are previously published mutual information and ordinary differential equation based methods (tlCLR and Inferelator 1.0, respectively) that use both time-series and steady-state data to rank regulatory interactions; the latter has the added advantage of also inferring dynamic models of gene regulation which can be used to predict the system's response to new perturbations.Our t-test based method proved powerful at ranking regulatory interactions, tying for first out of methods in the DREAM4 100-gene in-silico network inference challenge. We demonstrate complementarity between this method and the two methods that take advantage of time-series data by combining the three into a pipeline whose ability to rank regulatory interactions is markedly improved compared to either method alone. Moreover, the pipeline is able to accurately predict the response of the system to new conditions (in this case new double knock-out genetic perturbations). Our evaluation of the performance of multiple methods for network inference suggests avenues for future methods development and provides simple considerations for genomic experimental design. Our code is publicly available at http://err.bio.nyu.edu/inferelator/

Protein Conformational Changes in the Bacteriorhodopsin Photocycle: Comparison of Findings from Electron and X-Ray Crystallographic Analyses

Light-driven conformational changes in the membrane protein bacteriorhodopsin have been studied extensively using X-ray and electron crystallography, resulting in the deposition of >30 sets of coordinates describing structural changes at various stages of proton transport. Using projection difference Fourier maps, we show that coordinates reported by different groups for the same photocycle intermediates vary considerably in the extent and nature of conformational changes. The different structures reported for the same intermediate cannot be reconciled in terms of differing extents of change on a single conformational trajectory. New measurements of image phases obtained by cryo-electron microscopy of the D96G/F171C/F219L triple mutant provide independent validation for the description of the large protein conformational change derived at 3.2 Å resolution by electron crystallography of 2D crystals, but do not support atomic models for light-driven conformational changes derived using X-ray crystallography of 3D crystals. Our findings suggest that independent determination of phase information from 2D crystals can be an important tool for testing the accuracy of atomic models for membrane protein conformational changes

Genetic and transcriptomic analysis of transcription factor genes in the model halophilic Archaeon: coordinate action of TbpD and TfbA

<p>Abstract</p> <p>Background</p> <p>Archaea are prokaryotic organisms with simplified versions of eukaryotic transcription systems. Genes coding for the general transcription factors TBP and TFB are present in multiple copies in several Archaea, including <it>Halobacterium </it>sp. NRC-1. Multiple TBP and TFBs have been proposed to participate in transcription of genes via recognition and recruitment of RNA polymerase to different classes of promoters.</p> <p>Results</p> <p>We attempted to knock out all six TBP and seven TFB genes in <it>Halobacterium </it>sp. NRC-1 using the <it>ura</it>3-based gene deletion system. Knockouts were obtained for six out of thirteen genes, <it>tbp</it>CDF and <it>tfb</it>ACG, indicating that they are not essential for cell viability under standard conditions. Screening of a population of 1,000 candidate mutants showed that genes which did not yield mutants contained less that 0.1% knockouts, strongly suggesting that they are essential. The transcriptomes of two mutants, Δ<it>tbp</it>D and Δ<it>tfb</it>A, were compared to the parental strain and showed coordinate down regulation of many genes. Over 500 out of 2,677 total genes were regulated in the Δ<it>tbp</it>D and Δ<it>tfb</it>A mutants with 363 regulated in both, indicating that over 10% of genes in both strains require the action of both TbpD and TfbA for normal transcription. Culturing studies on the Δ<it>tbp</it>D and Δ<it>tfb</it>A mutant strains showed them to grow more slowly than the wild-type at an elevated temperature, 49°C, and they showed reduced viability at 56°C, suggesting TbpD and TfbA are involved in the heat shock response. Alignment of TBP and TFB protein sequences suggested the expansion of the TBP gene family, especially in <it>Halobacterium </it>sp. NRC-1, and TFB gene family in representatives of five different genera of haloarchaea in which genome sequences are available.</p> <p>Conclusion</p> <p>Six of thirteen TBP and TFB genes of <it>Halobacterium </it>sp. NRC-1 are non-essential under standard growth conditions. TbpD and TfbA coordinate the expression of over 10% of the genes in the NRC-1 genome. The Δ<it>tbp</it>D and Δ<it>tfb</it>A mutant strains are temperature sensitive, possibly as a result of down regulation of heat shock genes. Sequence alignments suggest the existence of several families of TBP and TFB transcription factors in <it>Halobacterium </it>which may function in transcription of different classes of genes.</p

The Complete Genome Sequence of Thermoproteus tenax: A Physiologically Versatile Member of the Crenarchaeota

Here, we report on the complete genome sequence of the hyperthermophilic Crenarchaeum Thermoproteus tenax (strain Kra 1, DSM 2078(T)) a type strain of the crenarchaeotal order Thermoproteales. Its circular 1.84-megabase genome harbors no extrachromosomal elements and 2,051 open reading frames are identified, covering 90.6% of the complete sequence, which represents a high coding density. Derived from the gene content, T. tenax is a representative member of the Crenarchaeota. The organism is strictly anaerobic and sulfur-dependent with optimal growth at 86 degrees C and pH 5.6. One particular feature is the great metabolic versatility, which is not accompanied by a distinct increase of genome size or information density as compared to other Crenarchaeota. T. tenax is able to grow chemolithoautotrophically (CO2/H-2) as well as chemoorganoheterotrophically in presence of various organic substrates. All pathways for synthesizing the 20 proteinogenic amino acids are present. In addition, two presumably complete gene sets for NADH:quinone oxidoreductase (complex I) were identified in the genome and there is evidence that either NADH or reduced ferredoxin might serve as electron donor. Beside the typical archaeal A(0)A(1)-ATP synthase, a membrane-bound pyrophosphatase is found, which might contribute to energy conservation. Surprisingly, all genes required for dissimilatory sulfate reduction are present, which is confirmed by growth experiments. Mentionable is furthermore, the presence of two proteins (ParA family ATPase, actin-like protein) that might be involved in cell division in Thermoproteales, where the ESCRT system is absent, and of genes involved in genetic competence (DprA, ComF) that is so far unique within Archaea

An Integrated Pipeline for de Novo Assembly of Microbial Genomes

Remarkable advances in DNA sequencing technology have created a need for de novo genome assembly methods tailored to work with the new sequencing data types. Many such methods have been published in recent years, but assembling raw sequence data to obtain a draft genome has remained a complex, multi-step process, involving several stages of sequence data cleaning, error correction, assembly, and quality control. Successful application of these steps usually requires intimate knowledge of a diverse set of algorithms and software. We present an assembly pipeline called A5 (Andrew And Aaron's Awesome Assembly pipeline) that simplifies the entire genome assembly process by automating these stages, by integrating several previously published algorithms with new algorithms for quality control and automated assembly parameter selection. We demonstrate that A5 can produce assemblies of quality comparable to a leading assembly algorithm, SOAPdenovo, without any prior knowledge of the particular genome being assembled and without the extensive parameter tuning required by the other assembly algorithm. In particular, the assemblies produced by A5 exhibit 50% or more reduction in broken protein coding sequences relative to SOAPdenovo assemblies. The A5 pipeline can also assemble Illumina sequence data from libraries constructed by the Nextera (transposon-catalyzed) protocol, which have markedly different characteristics to mechanically sheared libraries. Finally, A5 has modest compute requirements, and can assemble a typical bacterial genome on current desktop or laptop computer hardware in under two hours, depending on depth of coverage. © 2012 Tritt et al

New Methods for Confusion Detection in Course Forums: Student, Teacher, and Machine

This article provides computational and rule-based approaches for detecting confusion that is expressed in students' comments in couse forums. To obtain reliable, ground truth data about which posts exhibit student confusion, we designed a decision tree that facilitates the manual labeling of forum posts by experts. However, manual labeling is costly in time and resources, which limits the amount of data that can be generated using this process. Our strategy for overcoming these limitations was to generate rules for detecting confusion based on student input via hashtags, which reflect the student's affective states. We show that the resulting rules closely align with the ground truth judgement of experts. We next applied these rules to datasets of students' forum posts in a large-scale biology course, thereby automatically generating thousands of labeled instances of 'confused posts.' Finally, the resulting dataset was used to train a machine learning model for detecting whether students' posts exhibit confusion in the absence of hashtags. In this task, the pretrained language model based on bidirectional encoder representation from transformers (BERT) was able to outperform traditional machine learning models for classifying confusion in posts. This model was also able to generalize and detect student confusion across different offerings of the same course. Ultimately, the use of pretrained language models of this type will provide teachers with better technologies for detecting and alleviating confusion in online discussion forums by leveraging the combined input of teachers and students

Sequencing of seven haloarchaeal genomes reveals patterns of genomic flux

We report the sequencing of seven genomes from two haloarchaeal genera, Haloferax and Haloarcula. Ease of cultivation and the existence of well-developed genetic and biochemical tools for several diverse haloarchaeal species make haloarchaea a model group for the study of archaeal biology. The unique physiological properties of these organisms also make them good candidates for novel enzyme discovery for biotechnological applications. Seven genomes were sequenced to ~20×coverage and assembled to an average of 50 contigs (range 5 scaffolds - 168 contigs). Comparisons of protein-coding gene compliments revealed large-scale differences in COG functional group enrichment between these genera. Analysis of genes encoding machinery for DNA metabolism reveals genera-specific expansions of the general transcription factor TATA binding protein as well as a history of extensive duplication and horizontal transfer of the proliferating cell nuclear antigen. Insights gained from this study emphasize the importance of haloarchaea for investigation of archaeal biology. © 2012 Lynch et al

Genetic algorithms and their application to in silico evolution of genetic regulatory networks

“The original publication is available at www.springerlink.com”. Copyright SpringerA genetic algorithm (GA) is a procedure that mimics processes occurring in Darwinian evolution to solve computational problems. A GA introduces variation through "mutation" and "recombination" in a "population" of possible solutions to a problem, encoded as strings of characters in "genomes," and allows this population to evolve, using selection procedures that favor the gradual enrichment of the gene pool with the genomes of the "fitter" individuals. GAs are particularly suitable for optimization problems in which an effective system design or set of parameter values is sought.In nature, genetic regulatory networks (GRNs) form the basic control layer in the regulation of gene expression levels. GRNs are composed of regulatory interactions between genes and their gene products, and are, inter alia, at the basis of the development of single fertilized cells into fully grown organisms. This paper describes how GAs may be applied to find functional regulatory schemes and parameter values for models that capture the fundamental GRN characteristics. The central ideas behind evolutionary computation and GRN modeling, and the considerations in GA design and use are discussed, and illustrated with an extended example. In this example, a GRN-like controller is sought for a developmental system based on Lewis Wolpert's French flag model for positional specification, in which cells in a growing embryo secrete and detect morphogens to attain a specific spatial pattern of cellular differentiation.Peer reviewe