The Tree versus the Forest: The Fungal Tree of Life and the Topological Diversity within the Yeast Phylome

A recurrent topic in phylogenomics is the combination of various sequence alignments to reconstruct a tree that describes the evolutionary relationships within a group of species. However, such approach has been criticized for not being able to properly represent the topological diversity found among gene trees. To evaluate the representativeness of species trees based on concatenated alignments, we reconstruct several fungal species trees and compare them with the complete collection of phylogenies of genes encoded in the Saccharomyces cerevisiae genome. We found that, despite high levels of among-gene topological variation, the species trees do represent widely supported phylogenetic relationships. Most topological discrepancies between gene and species trees are concentrated in certain conflicting nodes. We propose to map such information on the species tree so that it accounts for the levels of congruence across the genome. We identified the lack of sufficient accuracy of current alignment and phylogenetic methods as an important source for the topological diversity encountered among gene trees. Finally, we discuss the implications of the high levels of topological variation for phylogeny-based orthology prediction strategies.     

The Role of Functional Prion-Like Proteins in the Persistence of Memory

Prions are a self-templating amyloidogenic state of normal cellular proteins, such as prion protein (PrP). They have been identified as the pathogenic agents, contributing to a number of diseases of the nervous system. However, the discovery that the neuronal RNA-binding protein, cytoplasmic polyadenylation element-binding protein (CPEB), has a prion-like state that is involved in the stabilization of memory raised the possibility that prion-like proteins can serve normal physiological functions in the nervous system. Here, we review recent experimental evidence of prion-like properties of neuronal CPEB in various organisms and propose a model of how the prion-like state may stabilize memory.Prions are proteinaceous infectious agents that were discovered in the 1980s by Stanley Prusiner while studying Creutzfeldt–Jakob disease (Prusiner 1982). Prusiner and colleagues showed them to be an amyloidogenic, self-perpetuating, forms of a normal cellular protein, termed prion protein or PrP. Prp in its self-perpetuating state kills cells. Prusiner and colleagues found that PrPs exist in at least two conformations: monomeric and aggregated (Fig. 1). The transition among these forms occurs spontaneously and only the aggregated conformation is pathogenic. Soon, PrPs were found to contribute to other neurodegenerative disorders in people, including kuru, transmissible spongiform encephalopathies, as well as bovine spongiform encephalopathy in cows (Prusiner 1994; Aguzzi and Weissmann 1998).Open in a separate windowFigure 1.Pathogenic prions exist in two states (soluble and aggregated and self-perpetuating). The conversion from the soluble to the aggregated form is spontaneous and the aggregated, self-perpetuating form is often toxic and kills the cell.There is now a growing consensus that similar prion-like, self-templating mechanisms underlie a variety of neurodegenerative disorders, including amyotrophic lateral sclerosis, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease (Polymenidou and Cleveland 2012).Not all prions, however, appear to be disease causing. Fungal prions, for instance, are nontoxic, and some may even be beneficial to the cells that harbor them (Wickner 1994; Shorter and Lindquist 2005; Crow and Li 2011). In 2003, Si and Kandel serendipitously discovered a prion-like protein in multicellular eukaryotes—the nervous system of the marine snail Aplysia—whose aggregated and self-perpetuating form contributes to the maintenance of long-term changes in synaptic efficacy. This functional prion-like protein differs from pathogenic prions in two important ways: (1) The conversion to the prion-like state is regulated by a physiological signal, and (2) the aggregated form has an identified physiological function (Fig. 2). Recent identification of new functional prion-like proteins in various organisms, including human, supports the idea that nonpathogenic prions may perform a wide range of biologically meaningful roles (Coustou et al. 1997; Eaglestone et al. 1999; True and Lindquist 2000; Ishimaru et al. 2003; True et al. 2004; Hou et al. 2011; Jarosz et al. 2014).Open in a separate windowFigure 2.“Functional” prion: memory. “Functional” prions differ from conventional prions in two ways. First, the conversion is triggered by a physiological signal, and second, the aggregated, self-perpetrating forms have a physiological function. 5-HT, Serotonin; DA, dopamine.In this review, we focus on functional prion-like proteins in the brain and specifically on the prion-like properties of the cytoplasmic polyadenylation element-binding protein (CPEB), and examine how the prion-like state can control protein synthesis at the synapse and, thereby, synaptic plasticity and long-lasting memory. We anticipate the studies of CPEB would also provide some generalizable concepts as to how prion-based protein switches in multicellular eukaryotes may work.     

真菌生命之树项目（Assembling the Fungal Tree of Life）和美国真菌系统学研究现状

<正>美国的现代真菌系统学研究始于上世纪九十年代初期,以一系列分子系统学文章的发表为标志,其中代表性的工作有Vilgalys&Gonzalez(1990),White et al.(1990),Bruns et al.(1992),     

Assembling the Fungal Tree of Life: constructing the structural and biochemical database

A major goal of the Assembling the Fungal Tree of Life project is to create a searchable database of selected ultrastructural and biochemical characters from published and new data for use in phylogenetic and other analyses. While developing this database such issues as evaluating specimen fixation quality in published micrographs, organizing data to accommodate characters that were dependent on location and developmental stage, and requiring accountability of data contributors were addressed. Character states for three traits, septal pore apparatus, nuclear division and spindle pole body cycle, are illustrated, and character states are resolved with maximum parsimony and plotted on a summary cladogram of known phylogenetic relationships of the Fungi. The analysis illustrates the inherent phylogenetic signal of these characters, the paucity of comparable characters and character states in subcellular studies and the challenges in establishing a comprehensive structural and biochemical database of the Fungi.     

Distribution and Phylogeny of Light-Oxygen-Voltage-Blue-Light-Signaling Proteins in the Three Kingdoms of Life

Plants and fungi respond to environmental light stimuli via the action of different photoreceptor modules. One such class, responding to the blue region of light, is constituted by photoreceptors containing so-called light-oxygen-voltage (LOV) domains as sensor modules. Four major LOV families are currently identified in eukaryotes: (i) the plant phototropins, regulating various physiological effects such as phototropism, chloroplast relocation, and stomatal opening; (ii) the aureochromes, mediating photomorphogenesis in photosynthetic stramenopile algae; (iii) the plant circadian photoreceptors of the zeitlupe (ZTL)/adagio (ADO)/flavin-binding Kelch repeat F-box protein 1 (FKF1) family; and (iv) the fungal circadian photoreceptors white-collar 1 (WC-1). Blue-light-sensitive LOV signaling modules are also widespread throughout the prokaryotic world, and physiological responses mediated by bacterial LOV photoreceptors were recently reported. Thus, the question arises as to the evolutionary relationship between the pro- and eukaryotic LOV photoreceptor systems. We used Bayesian and maximum-likelihood tree reconstruction methods to infer evolutionary scenarios that might have led to the widespread appearance of LOV domains among the pro- and eukaryotes. The phylogenetic study presented here suggests a bacterial origin for the LOV domains of the four major eukaryotic LOV photoreceptor families, whereas the LOV sensor domains were most likely recruited from the bacteria in the course of plastid and mitochondrial endosymbiosis.A plant family of photoreceptors, the phototropins, containing so-called light-oxygen-voltage (LOV) domains as the blue-light-sensitive signaling switches (12), were previously identified as the key modulators of a variety of plant blue-light responses, including plant phototropism (23), chloroplast relocation, and stomatal and leaf opening (25, 39). A second family (ZTL/ADO/FKF1 family) of eukaryotic LOV domain-containing proteins is constituted by the zeitlupe (ZTL) and the flavin-binding Kelch repeat F-box (FKF1) proteins. This family was found to play a primary role in the photocontrol of flowering and in the light-dependent regulation of the circadian period in plants (37, 53). Phototropins and ZTLs together with the fungal white-collar 1 (WC-1) proteins of, e.g., Neurospora crassa (3), which are involved in the blue-light dependent control of fungal circadian responses (19), constitute the three major eukaryotic LOV families in plants and fungi. A more recently discovered fourth family of LOV domain-containing blue-light receptors, the so-called aureochromes (58), seem to be restricted to stramenopile algae such as Vaucheria frigida and some marine diatoms (e.g., Thalassiosira pseudonana). Recently, the presence of LOV domain signaling modules was also predicted for animals, including humans. This functional assignment was solely based on sequence similarity to known LOV systems in plants and bacteria (62); however, experimental evidence is still missing. LOV domains are small (110 amino acids), bind flavin mononucleotide as chromophores, and fold independently to adopt a Per-Arndt-Sim (PAS) fold (40), which they share with other ligand-binding sensor modules (59). The best-characterized LOV domains are LOV1 and LOV2, found in plant phototropins (11), which probably regulate the physiological response via a blue-light-dependent phosphorylation of a serine/threonine kinase located C terminal to the LOV sensor domains in plant phototropins. (10). The light-sensitive function of the LOV proteins is based on the presence of a strictly conserved cysteine residue located at a distance of about 4 Å from the isoalloxazine ring of the flavin chromophore. In all LOV domains, this cysteine residue is found as the fourth residue in a highly conserved sequence motif GXNCRFLQG defined previously based on plant phototropin sequences (45). Irradiation with blue light results in the formation of a covalent bond between this cysteine and the carbon atom in position 4a of the flavin isoalloxazine ring. In the dark, this bond reopens within minutes to hours, depending on the respective LOV protein (32). The increasing number of completely sequenced microbial genomes revealed the presence of a variety of putative LOV photosensory proteins in bacteria and archaea (31) whose biological roles remain in most cases elusive. Only recently, experiments showed that LOV domain-containing proteins found in several bacterial taxa, namely, a LOV sulfate transporter anti-sigma factor antagonist protein from the common soil bacterium Bacillus subtilis and LOV histidine kinases of the mammalian pathogen Brucella abortus (57) and the freshwater-dwelling microbe Caulobacter crescentus (44), mediate physiological responses toward environmental blue-light stimuli. The latter LOV domain-containing histidine kinases are blue-light sensitive, displaying a photochemistry similar to that of the plant phototropins with the blue-light stimulus inducing autophosphorylation in the kinase which in turn triggers the respective physiological response (8, 44, 57). Furthermore, a number of biochemical and photochemical studies demonstrated a conserved primary LOV photochemistry among several bacteria (8, 28, 30, 44, 57). Finally, only a few years after the identification of plant phototropin serine/threonine kinase systems with their blue-light-sensitive LOV sensory modules, experimental evidence has accumulated for the presence of similar systems in bacteria, namely, LOV histidine kinases regulating blue-light-dependent responses via phototropin-like autophosphorylation systems. These findings prompted us to investigate the evolutionary history as well as the distribution of the LOV sensor domain in the pro- and eukaryotic kingdoms. To this end, we have performed a phylogenetic analysis comprising 223 putative LOV sequences obtained from completely sequenced genomes of 22 eukaryotes, 115 bacteria, and 3 archaea.     

Genetic Studies of Human DNA Repair Proteins Using Yeast as a Model System

Understanding the roles of human DNA repair proteins in genetic pathways is a formidable challenge to many researchers. Genetic studies in mammalian systems have been limited due to the lack of readily available tools including defined mutant genetic cell lines, regulatory expression systems, and appropriate selectable markers. To circumvent these difficulties, model genetic systems in lower eukaryotes have become an attractive choice for the study of functionally conserved DNA repair proteins and pathways. We have developed a model yeast system to study the poorly defined genetic functions of the Werner syndrome helicase-nuclease (WRN) in nucleic acid metabolism. Cellular phenotypes associated with defined genetic mutant backgrounds can be investigated to clarify the cellular and molecular functions of WRN through its catalytic activities and protein interactions. The human WRN gene and associated variants, cloned into DNA plasmids for expression in yeast, can be placed under the control of a regulatory plasmid element. The expression construct can then be transformed into the appropriate yeast mutant background, and genetic function assayed by a variety of methodologies. Using this approach, we determined that WRN, like its related RecQ family members BLM and Sgs1, operates in a Top3-dependent pathway that is likely to be important for genomic stability. This is described in our recent publication [1] at www.impactaging.com. Detailed methods of specific assays for genetic complementation studies in yeast are provided in this paper.Download video file.^{(158M, mp4)}     

Endoplasmic Reticulum Subcompartments in a Plant Parasitic Fungus and in Baker's Yeast: Differential Distribution of Lumenal Proteins

Bachem, U., and Mendgen, K. 1995. ER subcompartments in a plant parasitic fungus and in baker's yeast: Differential distribution of lumenal proteins. Experimental Mycology 19, 137-152. His-Asp-Glu-Leu (HDEL)-bearing proteins were quantified in different endoplasmic reticulum (ER) subcompartments of Saccharomyces cerevisiae and the plant parasite Uromyces viciae-fabae by immuno-electron microscopy (immuno-EM). In both fungi, the immunogold labeling of these proteins within the ER was three times greater than within the nuclear envelope. In U. viciae-fabae, the ER in germinating uredospores differed from the ER in fungal structures produced within the plant, e.g., haustoria. In haustoria, the cisternal ER differentiated large tubular-vesicular complexes (TVC). TVC contained higher levels of HDEL-bearing proteins than ordinary ER cisternae. ELISA readings also indicated an increased concentration of these proteins in isolated haustoria compared to germinating uredospores. In S. cerevisiae, the ER was differentiated into cortical and internal regions. Immuno-EM revealed that labeling of the binding protein (BiP) was lower in the ER of the cell cortex. Heat shock increased BiP signals, but the relative distribution within the ER did not change. Our results suggest that ER subcompartments can be differentiated by immunogold labeling of proteins with a retention signal. In special cases, such as in the parasitic phase of rust fungi, these proteins accumulate to higher levels in ER subcompartments, probably as a response to plant-induced stress.     

采用酵母双杂交系统筛选GmDREB5的互作蛋白

以无自激活活性的GmDREB5蛋白73～226位氨基酸区段为诱饵,采用酵母双杂交系统筛选干旱处理5 h大豆cDNA文库.结果发现:一个互作蛋白含有保守的TPR(Tetratricopeptide repeat)结构域,与拟南芥的TPR蛋白仅有14%的相似性,说明其可能是一类新的大豆TPR蛋白,将其定名为GmTPR1;表达特性分析表明,GmTPR1基因受干旱、低温、高盐、ABA的诱导;证明GmTPR1不仅参与植物对非生物胁迫的响应,同时参与对GmDREB5蛋白水平的调控.     

The Evolution of Sex: a Perspective from the Fungal Kingdom

Summary: Sex is shrouded in mystery. Not only does it preferentially occur in the dark for both fungi and many animals, but evolutionary biologists continue to debate its benefits given costs in light of its pervasive nature. Experimental studies of the benefits and costs of sexual reproduction with fungi as model systems have begun to provide evidence that the balance between sexual and asexual reproduction shifts in response to selective pressures. Given their unique evolutionary history as opisthokonts, along with metazoans, fungi serve as exceptional models for the evolution of sex and sex-determining regions of the genome (the mating type locus) and for transitions that commonly occur between outcrossing/self-sterile and inbreeding/self-fertile modes of reproduction. We review here the state of the understanding of sex and its evolution in the fungal kingdom and also areas where the field has contributed and will continue to contribute to illuminating general principles and paradigms of sexual reproduction.     

利用酵母双杂交系统研究植物与病毒蛋白相互作用的进展

在长期进化中,植物形成了抵御病毒等病原微生物侵染的精细防御系统。在病毒侵染、复制和传播过程中,其编码的一些蛋白,如外壳蛋白、运动蛋白、复制酶类等能够与植物基因编码的蛋白发生相互作用。酵母双杂交系统是体外研究蛋白质间相互作用的有利工具,不但可以用于研究已知蛋白质的互作,还可以发现新蛋白,揭示特定蛋白互作网络与作用机制,在植物蛋白与病毒蛋白互作研究中已得到广泛的利用。本文主要综述利用酵母双杂交系统研究植物与病毒蛋白相互作用的国内外进展。     

酵母表面展示T载体构建及目的蛋白的表面展示

构建一种能对PCR产物进行直接克隆并展示于酵母表面的新型T载体。根据酵母表面展示载体p YD1多克隆位点序列设计出利用两端带有XcmⅠ内切酶酶切位点的含有黄色荧光蛋白基因的XcmⅠ酶切盒,通过NheⅠ和XhoⅠ酶切位点插入到p YD1载体上形成质粒p YD-YFP,并对其进行酶切鉴定和DNA测序分析,再经XcmⅠ酶切后形成两端带有d T的表面展示T载体。利用PCR扩增两个含有荧光蛋白的融合蛋白PCAD-CFP和PSR-Ds Red的基因并直接克隆到所构建的T载体中,检测其表达功能。酶切鉴定和DNA测序结果显示PCAD-CFP和PSR-Ds Red正确插入载体上,分别转化至酿酒酵母EBY100中,激光共聚焦显微镜下观察到相应的荧光的酵母,表明克隆有融合蛋白基因片段的载体成功在酵母细胞中进行表面展示,证明了所构建的酵母表面展示T载体具有直接克隆和表面展示目的蛋白的功能。     

哈尔滨市室外空气真菌组成和分布的初步研究

采用曝皿法(孟加拉红培养基)连续12个月对哈尔滨市实验林场、东北林业大学家属区和哈尔滨市二环路、兴路区间3个地点的空气真菌进行取样,初步确定了哈尔滨市室外空气真菌的种类及其动态变化。试验共得到9 908个真菌菌落,经鉴定为22属(或群)49种。试验结果表明:室外空气真菌的优势菌属依次为枝孢属、链格孢、曲霉属、青霉属、附球菌属、木霉属和无孢菌群,分别占总菌落数的21.54%、15.16%1、4.70%、12.20%、11.35%、7.86%和7.80%;室外空气真菌的种类在一天中基本没有变化,但菌落的数量有一定变化,总菌落数从早至晚也逐渐增加;不同季节室外真菌的种类和菌落数有明显变化,秋季最多,冬季最少;不同采样地点的空气真菌的种类变化不大,但菌落数量有差异,菌落数量依次为公路林场家属区。     

Computing the Distribution of a Tree Metric

The Robinson-Foulds (RF) distance is by far the most widely used measure of dissimilarity between trees. Although the distribution of these distances has been investigated for 20 years, an algorithm that is explicitly polynomial time has yet to be described for computing the distribution for trees around a given tree. In this paper, we derive a polynomial-time algorithm for this distribution. We show how the distribution can be approximated by a Poisson distribution determined by the proportion of leaves that lie in “cherries” of the given tree. We also describe how our results can be used to derive normalization constants that are required in a recently proposed maximum likelihood approach to supertree construction.     

Predicting the Binding Patterns of Hub Proteins: A Study Using Yeast Protein Interaction Networks

Background

Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH) with one or two binding sites, or multiple-interface hubs (MIH) with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations) or party hubs (i.e., simultaneously interact with multiple partners).

Methodology

Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB) protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques.

Conclusions

Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions.

Availability

We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.     

Improved Detection of Invasive Pulmonary Aspergillosis Arising during Leukemia Treatment Using a Panel of Host Response Proteins and Fungal Antigens

Invasive pulmonary aspergillosis (IPA) is an opportunistic fungal infection in patients undergoing chemotherapy for hematological malignancy, hematopoietic stem cell transplant, or other forms of immunosuppression. In this group, Aspergillus infections account for the majority of deaths due to mold pathogens. Although early detection is associated with improved outcomes, current diagnostic regimens lack sensitivity and specificity. Patients undergoing chemotherapy, stem cell transplantation and lung transplantation were enrolled in a multi-site prospective observational trial. Proven and probable IPA cases and matched controls were subjected to discovery proteomics analyses using a biofluid analysis platform, fractionating plasma into reproducible protein and peptide pools. From 556 spots identified by 2D gel electrophoresis, 66 differentially expressed post-translationally modified plasma proteins were identified in the leukemic subgroup only. This protein group was rich in complement components, acute-phase reactants and coagulation factors. Low molecular weight peptides corresponding to abundant plasma proteins were identified. A candidate marker panel of host response (9 plasma proteins, 4 peptides), fungal polysaccharides (galactomannan), and cell wall components (β-D glucan) were selected by statistical filtering for patients with leukemia as a primary underlying diagnosis. Quantitative measurements were developed to qualify the differential expression of the candidate host response proteins using selective reaction monitoring mass spectrometry assays, and then applied to a separate cohort of 57 patients with leukemia. In this verification cohort, a machine learning ensemble-based algorithm, generalized pathseeker (GPS) produced a greater case classification accuracy than galactomannan (GM) or host proteins alone. In conclusion, Integration of host response proteins with GM improves the diagnostic detection of probable IPA in patients undergoing treatment for hematologic malignancy. Upon further validation, early detection of probable IPA in leukemia treatment will provide opportunities for earlier interventions and interventional clinical trials.     

Analysis of the Distribution of Bootstrap Tree Lengths Using the Maximum Parsimony Method

The bootstrap is an important tool for estimating the confidence interval of monophyletic groups within phylogenies. Although bootstrap analyses are used in most evolutionary studies, there is no clear consensus as how best to interpret bootstrap probability values. To study further the bootstrap method, nine small subunit ribosomal DNA (SSU rDNA) data sets were submitted to bootstrapped maximum parsimony (MP) analyses using unweighted and weighted sequence positions. Analyses of the lengths (i.e., parsimony steps) of the bootstrap trees show that the shape and mean of the bootstrap tree distribution may provide important insights into the evolutionary signal within the sequence data. With complex phylogenies containing nodes defined by short internal branches (multifurcations), the mean of the bootstrap tree distribution may differ by 2 standard deviations from the length of the best tree found from the original data set. Weighting sequence positions significantly increases the bootstrap values at internal nodes. There may, however, be strong bootstrap support for conflicting species groupings among different data sets. This phenomenon appears to result from a correlation between the topology of the tree used to create the weights and the topology of the bootstrap consensus tree inferred from the MP analysis of these weighted data. The analyses also show that characteristics of the bootstrap tree distribution (e.g., skewness) may be used to choose between alternative weighting schemes for phylogenetic analyses.