MIPS: a database for protein sequences and complete genomes

Modern drug discovery applications for the identification of novel candidates for COVID-19 infections

In early December 2019, a large pneumonia epidemic occurred in Wuhan, China. The World Health Organization is concerned about the outbreak of another coronavirus with the powerful, rapid, and contagious transmission. Anyone with minor symptoms like fever and cough or travel history to contaminated places might be suspected of having COVID-19. COVID-19 therapy focuses on treating the disease's symptoms. So far, no such therapeutic molecule has been shown effective in treating this condition. So the treatment is mostly supportive and plasma. Globally, numerous studies and researchers have recently started fighting this virus. Vaccines and chemical compounds are also being investigated against infection. COVID-19 was successfully diagnosed using RNA detection and very sensitive RT-PCR (reverse transcription-polymerase chain reaction). The evolution of particular vaccinations is required to reduce illness severity and spread. Numerous computational analyses and molecular docking have predicted various target compounds that might stop this condition. This paper examines the main characteristics of coronavirus and the computational analyses necessary to avoid infection.

Repurposing of Acriflavine to Target Chronic Myeloid Leukemia Treatment

Drug repurposing has lately received increasing interest in several diseases especially in cancers, due to its advantages in facilitating the development of new therapeutic strategies, by adopting a cost-friendly approach and avoiding the strict Food and Drug Administration (FDA) regulations. Acriflavine (ACF) is an FDA approved molecule that has been extensively studied since 1912 with antiseptic, trypanocidal, anti-viral, anti-bacterial and anti-cancer effects. ACF has been shown to block the growth of solid and hematopoietic tumor cells. Indeed, ACF acts as an inhibitor of various proteins, including DNA-dependent protein kinases C (DNA-PKcs), topoisomerase I and II, hypoxia-inducible factor 1α (HIF-1α), in addition to its recent discovery as an inhibitor of the signal transducer and activator of transcription (STAT). Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder characterized by the expression of the constitutively active tyrosine kinase BCR-ABL. This protein allows the activation of several signaling pathways known for their role in cell proliferation and survival, such as the JAK/STAT pathway. CML therapy, based on tyrosine kinase inhibitors (TKIs), such as imatinib (IM), is highly effective. However, 15% of patients are refractory to IM, where in some cases, 20-30% of patients become resistant. Thus, we suggest the repurposing of ACF in CML after IM failure or in combination with IM to improve the anti-tumor effects of IM. In this review, we present the different pharmacological properties of ACF along with its anti-leukemic effects in the hope of its repurposing in CML therapy.

Exploring the new horizons of drug repurposing: A vital tool for turning hard work into smart work

Drug discovery and development are long and financially taxing processes. On an average it takes 12-15 years and costs 1.2 billion USD for successful drug discovery and approval for clinical use. Many lead molecules are not developed further and their potential is not tapped to the fullest due to lack of resources or time constraints. In order for a drug to be approved by FDA for clinical use, it must have excellent therapeutic potential in the desired area of target with minimal toxicities as supported by both pre-clinical and clinical studies. The targeted clinical evaluations fail to explore other potential therapeutic applications of the candidate drug. Drug repurposing or repositioning is a fast and relatively cheap alternative to the lengthy and expensive de novo drug discovery and development. Drug repositioning utilizes the already available clinical trials data for toxicity and adverse effects, at the same time explores the drug's therapeutic potential for a different disease. This review addresses recent developments and future scope of drug repositioning strategy.

Review of Drug Repositioning Approaches and Resources

Drug discovery is a time-consuming, high-investment, and high-risk process in traditional drug development. Drug repositioning has become a popular strategy in recent years. Different from traditional drug development strategies, the strategy is efficient, economical and riskless. There are usually three kinds of approaches: computational approaches, biological experimental approaches, and mixed approaches, all of which are widely used in drug repositioning. In this paper, we reviewed computational approaches and highlighted their characteristics to provide references for researchers to develop more powerful approaches. At the same time, the important findings obtained using these approaches are listed. Furthermore, we summarized 76 important resources about drug repositioning. Finally, challenges and opportunities in drug repositioning are discussed from multiple perspectives, including technology, commercial models, patents and investment.

Localization of Daucus carota NMCP1 to the nuclear periphery: the role of the N-terminal region and an NLS-linked sequence motif, RYNLRR, in the tail domain

Recent ultrastructural studies revealed that a structure similar to the vertebrate nuclear lamina exists in the nuclei of higher plants. However, plant genomes lack genes for lamins and intermediate-type filament proteins, and this suggests that plant-specific nuclear coiled-coil proteins make up the lamina-like structure in plants. NMCP1 is a protein, first identified in Daucus carota cells, that localizes exclusively to the nuclear periphery in interphase cells. It has a tripartite structure comprised of head, rod, and tail domains, and includes putative nuclear localization signal (NLS) motifs. We identified the functional NLS of DcNMCP1 (carrot NMCP1) and determined the protein regions required for localizing to the nuclear periphery using EGFP-fused constructs transiently expressed in Apium graveolens epidermal cells. Transcription was driven under a CaMV35S promoter, and the genes were introduced into the epidermal cells by a DNA-coated microprojectile delivery system. Of the NLS motifs, KRRRK and RRHK in the tail domain were highly functional for nuclear localization. Addition of the N-terminal 141 amino acids from DcNMCP1 shifted the localization of a region including these NLSs from the entire nucleus to the nuclear periphery. Using this same construct, the replacement of amino acids in RRHK or its preceding sequence, YNL, with alanine residues abolished localization to the nuclear periphery, while replacement of KRRRK did not affect localization. The sequence R/Q/HYNLRR/H, including YNL and the first part of the sequence of RRHK, is evolutionarily conserved in a subclass of NMCP1 sequences from many plant species. These results show that NMCP1 localizes to the nuclear periphery by a combined action of a sequence composed of R/Q/HYNLRR/H, NLS, and the N-terminal region including the head and a portion of the rod domain, suggesting that more than one binding site is implicated in localization of NMCP1.

GENE CLASSIFICATION USING EXPRESSION PROFILES: A FEASIBILITY STUDY

As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus to functional genomics. Functional genomics represents the next phase, that expands the biological investigation to studying the functionality of genes of a single organism as well as studying and correlating the functionality of genes across many different organisms. Recently developed methods for monitoring genome-wide mRNA expression changes hold the promise of allowing us to inexpensively gain insights into the function of unknown genes. In this paper we focus on evaluating the feasibility of using supervised machine learning methods for determining the function of genes based solely on their expression profiles. We experimentally evaluate the performance of traditional classification algorithms such as support vector machines and k-nearest neighbors on the yeast genome, and present new approaches for classification that improve the overall recall with moderate reductions in precision. Our experiments show that the accuracies achieved for different classes varies dramatically. In analyzing these results we show that the achieved accuracy is highly dependent on whether or not the genes of that class were significantly active during the various experimental conditions, suggesting that gene expression profiles can become a viable alternative to sequence similarity searches provided that the genes are observed under a wide range of experimental conditions.

An FPT approach for predicting protein localization from yeast genomic data

Accurately predicting the localization of proteins is of paramount importance in the quest to determine their respective functions within the cellular compartment. Because of the continuous and rapid progress in the fields of genomics and proteomics, more data are available now than ever before. Coincidentally, data mining methods been developed and refined in order to handle this experimental windfall, thus allowing the scientific community to quantitatively address long-standing questions such as that of protein localization. Here, we develop a frequent pattern tree (FPT) approach to generate a minimum set of rules (mFPT) for predicting protein localization. We acquire a series of rules according to the features of yeast genomic data. The mFPT prediction accuracy is benchmarked against other commonly used methods such as Bayesian networks and logistic regression under various statistical measures. Our results show that mFPT gave better performance than other approaches in predicting protein localization. Meanwhile, setting 0.65 as the minimum hit-rate, we obtained 138 proteins that mFPT predicted differently than the simple naive bayesian method (SNB). In our analysis of these 138 proteins, we present novel predictions for the location for 17 proteins, which currently do not have any defined localization. These predictions can serve as putative annotations and should provide preliminary clues for experimentalists. We also compared our predictions against the eukaryotic subcellular localization database and related predictions by others on protein localization. Our method is quite generalized and can thus be applied to discover the underlying rules for protein-protein interactions, genomic interactions, and structure-function relationships, as well as those of other fields of research.

From large-scale assays to mechanistic insights: computational analysis of interactions

The activity in the living cell is carried out by a myriad network of interactions between macromolecules. These include interactions between proteins that form a functional complex, a protein modifying another protein in a transient interaction, a transcription factor that binds a specific DNA locus triggering a change in chromatin or transcription, and so on. Characterization of these interactions in terms of timing, context, and function is crucial for understanding how cells carry out basic biological processes. The recent years have led to the introduction of many assays for probing these interactions in a systematic and large-scale manner. However, there is a large gap between assay results and understanding of biological systems. The challenge for computational methods is to bridge this gap by combining results of different assays and introducing statistical methodologies. In this review we discuss recent advances in approaches dealing with these challenges, and key directions for the future.

The Arabidopsis nuclear pore and nuclear envelope

The nuclear envelope is a double membrane structure that separates the eukaryotic cytoplasm from the nucleoplasm. The nuclear pores embedded in the nuclear envelope are the sole gateways for macromolecular trafficking in and out of the nucleus. The nuclear pore complexes assembled at the nuclear pores are large protein conglomerates composed of multiple units of about 30 different nucleoporins. Proteins and RNAs traffic through the nuclear pore complexes, enabled by the interacting activities of nuclear transport receptors, nucleoporins, and elements of the Ran GTPase cycle. In addition to directional and possibly selective protein and RNA nuclear import and export, the nuclear pore gains increasing prominence as a spatial organizer of cellular processes, such as sumoylation and desumoylation. Individual nucleoporins and whole nuclear pore subcomplexes traffic to specific mitotic locations and have mitotic functions, for example at the kinetochores, in spindle assembly, and in conjunction with the checkpoints. Mutants of nucleoporin genes and genes of nuclear transport components lead to a wide array of defects from human diseases to compromised plant defense responses. The nuclear envelope acts as a repository of calcium, and its inner membrane is populated by functionally unique proteins connected to both chromatin and-through the nuclear envelope lumen-the cytoplasmic cytoskeleton. Plant nuclear pore and nuclear envelope research-predominantly focusing on Arabidopsis as a model-is discovering both similarities and surprisingly unique aspects compared to the more mature model systems. This chapter gives an overview of our current knowledge in the field and of exciting areas awaiting further exploration.

Towards accurate imputation of quantitative genetic interactions

A new method for calculating quantitative genetic interactions allows for the inference of 190,000 new genetic interactions in Saccharomyces cerevisae.

Recent technological breakthroughs have enabled high-throughput quantitative measurements of hundreds of thousands of genetic interactions among hundreds of genes in Saccharomyces cerevisiae. However, these assays often fail to measure the genetic interactions among up to 40% of the studied gene pairs. Here we present a novel method, which combines genetic interaction data together with diverse genomic data, to quantitatively impute these missing interactions. We also present data on almost 190,000 novel interactions.

Natural selection against protein aggregation on self-interacting and essential proteins in yeast, fly, and worm

Protein aggregation is the phenomenon of protein self-association potentially leading to detrimental effects on physiology, which is closely related to numerous human diseases such as Alzheimer's and Parkinson's disease. Despite progress in understanding the mechanism of protein aggregation, how natural selection against protein aggregation acts on subunits of protein complexes and on proteins with different contributions to organism fitness remains largely unknown. Here, we perform a proteome-wide analysis by using an experimentally validated algorithm TANGO and utilizing sequence, interactomic and phenotype-based functional genomic data from yeast, fly, and nematode. We find that proteins that are capable of forming homooligomeric complex have lower aggregation propensity compared with proteins that do not function as homooligomer. Further, proteins that are essential to the fitness of an organism have lower aggregation propensity compared with nonessential ones. Our finding suggests that the selection force against protein aggregation acts across different hierarchies of biological system.

Cataloging the relationships between proteins: a review of interaction databases

By organizing and making widely accessible the increasing amounts of data from high-throughput analyses, protein interaction databases have become an integral resource for the biological community in relating sequence data with higher-order function. To provide a sense of the use and applicability of these databases, we describe each of the major comprehensive interaction databases as well as some of the more specialized ones. Content description, search/browse functionalities, and data presentation are discussed. A succinct explanation of database contents helps the user quickly identify whether the database contains applicable information to their research interest. Broad levels of search/browse functions as well as descriptions/examples allow users to quickly find and access pertinent data. At this point, clear presentation of search results as well as the primary content is necessary. Many databases display information graphically or divided into smaller digestible parts over a number of tabbed/linked pages. In addition, cross-linking between the databases promotes interconnectivity of the data and is an added layer of relational data for the user. Overall, although these protein interaction databases are under continual improvement, their current state shows that much time and effort has gone into organizing and presenting these large sets of data-describing protein interactions.

Intermediate Filament-Like Cytoskeleton of Caulobacter crescentus

Eukaryotic cytoskeleton consists of three main types of filaments: actin microfilaments, microtubules and intermediate filaments (IFs). Actin and tubulin-like proteins are also found in bacteria where they perform diverse cytoskeletal functions. IFs, however, are considered to be a characteristic constituent of metazoan cells only, where they (among other functions) are involved in determination and maintenance of cell shape and cellular integrity. Surprisingly, a coiled coil-rich protein called crescentin was recently shown to play a key role in determining the complex curved and helical cell shapes of the bacterium Caulobacter crescentus, and to exhibit several characteristic properties of animal IF proteins. First, the arrangement of the coiled coil domains of crescentin closely resembles the tripartite molecular architecture of IF proteins. Second, crescentin also possesses the defining biochemical property of IF proteins to assemble into 10-nm-wide filaments in vitro without cofactors. Furthermore, crescentin forms a higher-order helical structure in vivo, which is localized asymmetrically along the concave side of the cell. In close association with the cell membrane, the crescentin structure promotes the helical growth of the cell and thereby determines a curved or a helical shape, depending on the length of the cell. The unexpected finding of an IF-like element in a bacterium raises several interesting questions concerning, for example, the molecular mechanisms whereby complex and asymmetric cell shapes are generated by different bacteria, or the functional and evolutionary relatedness of crescentin to animal IF proteins.

Exploration of yeast alkali metal cation/H+ antiporters: Sequence and structure comparison

The Saccharomyces cerevisiae genome contains three genes encoding alkali metal cation/H+ antiporters (Nha1p, Nhx1p, Kha1p) that differ in cell localization, substrate specificity and physiological function. Systematic genome sequencing of other yeast species revealed highly conserved homologous ORFs in all of them. We compared the yeast sequences both at DNA and protein levels. The subfamily of yeast endosomal/prevacuolar Nhx1 antiporters is closely related to mammalian plasma membrane NHE proteins and to both plasma membrane and vacuolar plant antiporters. The high sequence conservation within this subfamily of yeast antiporters suggests that Nhx1p is of great importance in cell physiology. Yeast Kha1 proteins probably belong to the same subfamily as bacterial antiporters, whereas Nhal proteins form a distinct subfamily.

Towards an integrated protein-protein interaction network: a relational Markov network approach

Protein-protein interactions play a major role in most cellular processes. Thus, the challenge of identifying the full repertoire of interacting proteins in the cell is of great importance and has been addressed both experimentally and computationally. Today, large scale experimental studies of protein interactions, while partial and noisy, allow us to characterize properties of interacting proteins and develop predictive algorithms. Most existing algorithms, however, ignore possible dependencies between interacting pairs and predict them independently of one another. In this study, we present a computational approach that overcomes this drawback by predicting protein-protein interactions simultaneously. In addition, our approach allows us to integrate various protein attributes and explicitly account for uncertainty of assay measurements. Using the language of relational Markov networks, we build a unified probabilistic model that includes all of these elements. We show how we can learn our model properties and then use it to predict all unobserved interactions simultaneously. Our results show that by modeling dependencies between interactions, as well as by taking into account protein attributes and measurement noise, we achieve a more accurate description of the protein interaction network. Furthermore, our approach allows us to gain new insights into the properties of interacting proteins.

Bayesian error analysis model for reconstructing transcriptional regulatory networks

Transcription regulation is a fundamental biological process, and extensive efforts have been made to dissect its mechanisms through direct biological experiments and regulation modeling based on physical-chemical principles and mathematical formulations. Despite these efforts, transcription regulation is yet not well understood because of its complexity and limitations in biological experiments. Recent advances in high throughput technologies have provided substantial amounts and diverse types of genomic data that reveal valuable information on transcription regulation, including DNA sequence data, protein-DNA binding data, microarray gene expression data, and others. In this article, we propose a Bayesian error analysis model to integrate protein-DNA binding data and gene expression data to reconstruct transcriptional regulatory networks. There are two unique aspects to this proposed model. First, transcription is modeled as a set of biochemical reactions, and a linear system model with clear biological interpretation is developed. Second, measurement errors in both protein-DNA binding data and gene expression data are explicitly considered in a Bayesian hierarchical model framework. Model parameters are inferred through Markov chain Monte Carlo. The usefulness of this approach is demonstrated through its application to infer transcriptional regulatory networks in the yeast cell cycle.

Histone acetylation and transcriptional regulation in the genome of Saccharomyces cerevisiae

MOTIVATION

In eukaryotic genomes, histone acetylation and thereafter departure from the chromatin are essential for gene transcription initiation. Because gene transcription is tightly regulated by transcription factors, there are some speculations on the cooperation of histone acetylation and transcription factor binding. However, systematic statistical analyses of this relationship on a genomic scale have not been reported.

RESULTS

We apply several statistical methods to explore this relationship on two recent genomic datasets: acetylation levels on 11 histone lysines and binding activities of 203 transcription factors, both in promoter regions across the yeast genome. By canonical correlation analysis, we find that a histone acetylation pattern is correlated with a certain profile of transcription factor binding in the genome. Furthermore, after clustering the genes by their acetylation levels on the 11 histone lysines, the genes within clusters show distinct transcription factor binding profiles, as discovered by principle component analysis. Even after applying fairly stringent statistical measurement, most of these clusters have transcription factors with binding activities significantly deviated from the overall genome. We conclude that in the yeast genome, there is a strong correlation between histone acetylation and transcription factor binding in the promoter regions.

Mining the structural genomics pipeline: identification of protein properties that affect high-throughput experimental analysis

Structural genomics projects represent major undertakings that will change our understanding of proteins. They generate unique datasets that, for the first time, present a standardized view of proteins in terms of their physical and chemical properties. By analyzing these datasets here, we are able to discover correlations between a protein's characteristics and its progress through each stage of the structural genomics pipeline, from cloning, expression, purification, and ultimately to structural determination. First, we use tree-based analyses (decision trees and random forest algorithms) to discover the most significant protein features that influence a protein's amenability to high-throughput experimentation. Based on this, we identify potential bottlenecks in various stages of the structural genomics process through specialized "pipeline schematics". We find that the properties of a protein that are most significant are: (i.) whether it is conserved across many organisms; (ii). the percentage composition of charged residues; (iii). the occurrence of hydrophobic patches; (iv). the number of binding partners it has; and (v). its length. Conversely, a number of other properties that might have been thought to be important, such as nuclear localization signals, are not significant. Thus, using our tree-based analyses, we are able to identify combinations of features that best differentiate the small group of proteins for which a structure has been determined from all the currently selected targets. This information may prove useful in optimizing high-throughput experimentation. Further information is available from http://mining.nesg.org/.

The bacterial cytoskeleton: an intermediate filament-like function in cell shape

Various cell shapes are encountered in the prokaryotic world, but how they are achieved is poorly understood. Intermediate filaments (IFs) of the eukaryotic cytoskeleton play an important role in cell shape in higher organisms. No such filaments have been found in prokaryotes. Here, we describe a bacterial equivalent to IF proteins, named crescentin, whose cytoskeletal function is required for the vibrioid and helical shapes of Caulobacter crescentus. Without crescentin, the cells adopt a straight-rod morphology. Crescentin has characteristic features of IF proteins including the ability to assemble into filaments in vitro without energy or cofactor requirements. In vivo, crescentin forms a helical structure that colocalizes with the inner cell curvatures beneath the cytoplasmic membrane. We propose that IF-like filaments of crescentin assemble into a helical structure, which by applying its geometry to the cell, generates a vibrioid or helical cell shape depending on the length of the cell.

Correlation of the structures of agricultural fungicides to gene expression in Saccharomyces cerevisiae upon exposure to toxic doses

Correlations between the chemical structures of agricultural fungicides and mRNA expression levels following exposure of Saccharomyces cerevisiae to toxic doses of thiuram, zineb, maneb, TPN, and PCP were examined. Structurally, thiuram, zineb, and maneb are dithiocarbamate fungicides, whereas TPN and PCP are not. To characterize chemical toxicity, genes expression was classified according to the functional groups used by the MIPS database. However, no correlations between the classification scheme and chemical structures were found. Hierarchical clustering of gene expression profiles was performed to characterize the effects of the five chemicals. According to this analysis the similarity of gene expression profiles depended on the similarity of chemical structures. These results suggest that DNA microarray technology has potential for predicting the major chemicals which will cause environmental toxicity and will provide information on new biomonitoring methods.

Microarray analysis of orthologous genes: conservation of the translational machinery across species at the sequence and expression level

BACKGROUND

Genome projects have provided a vast amount of sequence information. Sequence comparison between species helps to establish functional catalogues within organisms and to study how they are maintained and modified across phylogenetic groups during evolution. Microarray studies allow us to determine groups of genes with similar temporal regulation and perhaps also common regulatory upstream regions for binding of transcription factors. The integration of sequence and expression data is expected to refine our current annotations and provide some insight into the evolution of gene regulation across organisms.

RESULTS

We have investigated how well the protein subcellular localization and functional categories established from clustering of orthologous genes agree with gene-expression data in Saccharomyces cerevisiae. An increase in the resolution of biologically meaningful classes is observed upon the combination of experiments under different conditions. The functional categories deduced by sequence comparison approaches are, in general, preserved at the level of expression and can sometimes interact into larger co-regulated networks, such as the protein translation process. Differences and similarities in the expression between cytoplasmic-mitochondrial and interspecies translation machineries complement evolutionary information from sequence similarity.

CONCLUSIONS

Combination of several microarray experiments is a powerful tool for the identification of upstream regulatory motifs of yeast genes involved in protein synthesis. Comparison of these yeast co-regulated genes against the archaeal and bacterial operons indicates that the components of the protein translation process are conserved across organisms at the expression level with minor specific adaptations.

The constraints protein-protein interactions place on sequence divergence

Structural analyses on a small number of protein families have shown that residues in protein interfaces are more conserved than average amino acid residues. This is also true of other ligand-binding and active site residues. This raises the question whether protein interactions place additional constraints on sequence divergence beyond this general background of functional restrictions on all different types of proteins. In order to investigate this, the sequence identities of Saccharomyces cerevisiae (SC) proteins to their Schizosaccharomyces pombe (SP) orthologues were used as a measure of sequence divergence. The SC proteins were divided into those in stable complexes, those that participate in transient interactions and the remaining proteins. All types of proteins can undergo extensive divergence: all three sequence identity distributions range from less than 20 to over 90%. However, overall, protein interactions do place additional constraints on sequence divergence and the distributions differ significantly: proteins not known to be involved in interactions have an average sequence identity of 38% while this value is 46% for proteins in stable complexes. Proteins that have transient interactions are intermediate between the two, with an average sequence identity of 41%. This trend is independent of whether the proteins are involved in informational functions (transcription, translation and replication) or not and of protein dispensability.

Importance of potential interhelical salt-bridges involving interior residues for coiled-coil stability and quaternary structure

Coiled coils are formed by two or more alpha-helices that align in a parallel or an antiparallel relative orientation. Polar interactions involving residues at the interior a and d positions are important for determining the quaternary structure of coiled coils. In the model heterodimeric coiled-coil Acid-a1-Base-a1, a buried a-d' Asn-Asn interaction is sufficient to specify both a dimeric structure and an antiparallel relative helix orientation. Although the equivalent a-a' interaction is found in parallel coiled coils, there is no example of an a-d' Asn-Asn interaction in structurally characterized, naturally occurring antiparallel coiled coils. Instead, interior charged residues form interhelical salt-bridges with residues at the adjacent e or g positions. Using a model coiled-coil heterodimer, we have explored the role of a potential interhelical interaction between an Arg at an interior d position and a Glu at the adjacent g' position. Our results demonstrate that this potentially attractive interhelical Coulombic interaction has little or no influence on helix orientation. Instead, we show that burying a single Arg residue at an interior position is sufficient to specify a dimeric state at a significantly lower thermodynamic cost than burial of two interacting Asn residues.

A general method for selection and screening of coiled coils on the basis of relative helix orientation

We have developed a method for selecting coiled coils that associate with a given relative helix orientation from a randomized pool of proteins. To select for antiparallel dimers, we have designed a model basic region-leucine zipper (bZip) heterodimer capable of binding DNA only when the coiled coil associates with an antiparallel relative helix alignment. The dimerization domain for this bZip heterodimer is the model antiparallel coiled coil Acid-a1-Base-a1 (Oakley, M. G.; Kim, P. S. Biochemistry 1998, 37, 12603), and both monomers contain the GCN4 basic region. Although the basic regions in naturally occurring bZip proteins are located N-terminal to the leucine zipper, we have attached the GCN4 basic region to the C-terminus of Acid-a1 to allow both basic regions to contact DNA in an antiparallel heterodimer. The resulting heterodimer, BR-Base-a1-Acid-a1-BR, can bind to a direct repeat of the GCN4 half-site in vivo, leading to spectinomycin resistance in the transcription interference assay of Elledge et al. (Elledge, S. J.; Sugiono, P.; Guarente, L.; Davis, R. W. Proc. Natl. Acad. Sci. U.S.A. 1989, 86, 3689). A buried interhelical polar interaction between two Asn residues in the Acid-a1-Base-a1 heterodimer is known to specify an antiparallel helix orientation. The position of one of these buried Asn residues was randomized, and bZip heterodimers containing antiparallel coiled coils were selected using the transcription interference assay. All of the selected colonies contained Asn at the randomized position, suggesting that the selection is specific for antiparallel coiled coils.

Four signature motifs define the first class of structurally related large coiled-coil proteins in plants

BACKGROUND

Animal and yeast proteins containing long coiled-coil domains are involved in attaching other proteins to the large, solid-state components of the cell. One subgroup of long coiled-coil proteins are the nuclear lamins, which are involved in attaching chromatin to the nuclear envelope and have recently been implicated in inherited human diseases. In contrast to other eukaryotes, long coiled-coil proteins have been barely investigated in plants.

RESULTS

We have searched the completed Arabidopsis genome and have identified a family of structurally related long coiled-coil proteins. Filament-like plant proteins (FPP) were identified by sequence similarity to a tomato cDNA that encodes a coiled-coil protein which interacts with the nuclear envelope-associated protein, MAF1. The FPP family is defined by four novel unique sequence motifs and by two clusters of long coiled-coil domains separated by a non-coiled-coil linker. All family members are expressed in a variety of Arabidopsis tissues. A homolog sharing the structural features was identified in the monocot rice, indicating conservation among angiosperms.

CONCLUSION

Except for myosins, this is the first characterization of a family of long coiled-coil proteins in plants. The tomato homolog of the FPP family binds in a yeast two-hybrid assay to a nuclear envelope-associated protein. This might suggest that FPP family members function in nuclear envelope biology. Because the full Arabidopsis genome does not appear to contain genes for lamins, it is of interest to investigate other long coiled-coil proteins, which might functionally replace lamins in the plant kingdom.

Evaluation of the energetic contribution of interhelical Coulombic interactions for coiled coil helix orientation specificity

Coiled coils are formed by two or more alpha-helices that align in a parallel or an antiparallel relative orientation. The factors that determine a preference for a given relative helix orientation are incompletely understood. The helix orientation preference for the designed coiled coil, Acid-a1-Base-a1, was measured previously. This model system therefore provides a means for the experimental determination of the energetic contribution of a variety of interactions to helix orientation specificity. The antiparallel preference for Acid-a1-Base-a1 is imparted by a single buried polar interaction. Interhelical Coulombic interactions between residues at the e and g positions have been proposed to influence helix orientation preference. In the Acid-a1-Base-a1 heterodimer, potentially attractive Coulombic interactions are expected in both orientations. To determine the energetic consequences of Coulombic interactions for helix orientation preference, we have positioned a single charged residue in each peptide such that exclusively favorable interhelical Coulombic interactions can occur only in the parallel orientation. In contrast, two potentially repulsive interactions are expected in the antiparallel orientation. Because the buried polar interaction can occur only in the antiparallel orientation, interhelical Coulombic interactions favor the parallel orientation and the potential to form a buried polar interaction favors the antiparallel orientation. We find no clear preference for an antiparallel orientation in the resulting heterodimer, Acid-Ke-Base-Eg, suggesting that interhelical Coulombic interactions and a buried polar interaction are of approximately equal importance for helix orientation specificity. Stability measurements indicate that maintenance of all favorable electrostatic interactions and/or avoidance of two potentially repulsive interactions contributes approximately 2.1 kcal/mol to helix orientation preference.

Transcriptional profiling shows that Gcn4p is a master regulator of gene expression during amino acid starvation in yeast

Starvation for amino acids induces Gcn4p, a transcriptional activator of amino acid biosynthetic genes in Saccharomyces cerevisiae. In an effort to identify all genes regulated by Gcn4p during amino acid starvation, we performed cDNA microarray analysis. Data from 21 pairs of hybridization experiments using two different strains derived from S288c revealed that more than 1,000 genes were induced, and a similar number were repressed, by a factor of 2 or more in response to histidine starvation imposed by 3-aminotriazole (3AT). Profiling of a gcn4Delta strain and a constitutively induced mutant showed that Gcn4p is required for the full induction by 3AT of at least 539 genes, termed Gcn4p targets. Genes in every amino acid biosynthetic pathway except cysteine and genes encoding amino acid precursors, vitamin biosynthetic enzymes, peroxisomal components, mitochondrial carrier proteins, and autophagy proteins were all identified as Gcn4p targets. Unexpectedly, genes involved in amino acid biosynthesis represent only a quarter of the Gcn4p target genes. Gcn4p also activates genes involved in glycogen homeostasis, and mutant analysis showed that Gcn4p suppresses glycogen levels in amino acid-starved cells. Numerous genes encoding protein kinases and transcription factors were identified as targets, suggesting that Gcn4p is a master regulator of gene expression. Interestingly, expression profiles for 3AT and the alkylating agent methyl methanesulfonate (MMS) overlapped extensively, and MMS induced GCN4 translation. Thus, the broad transcriptional response evoked by Gcn4p is produced by diverse stress conditions. Finally, profiling of a gcn4Delta mutant uncovered an alternative induction pathway operating at many Gcn4p target genes in histidine-starved cells.

Transcriptional profiling shows that Gcn4p is a master regulator of gene expression during amino acid starvation in yeast

Starvation for amino acids induces Gcn4p, a transcriptional activator of amino acid biosynthetic genes in Saccharomyces cerevisiae. In an effort to identify all genes regulated by Gcn4p during amino acid starvation, we performed cDNA microarray analysis. Data from 21 pairs of hybridization experiments using two different strains derived from S288c revealed that more than 1,000 genes were induced, and a similar number were repressed, by a factor of 2 or more in response to histidine starvation imposed by 3-aminotriazole (3AT). Profiling of a gcn4Delta strain and a constitutively induced mutant showed that Gcn4p is required for the full induction by 3AT of at least 539 genes, termed Gcn4p targets. Genes in every amino acid biosynthetic pathway except cysteine and genes encoding amino acid precursors, vitamin biosynthetic enzymes, peroxisomal components, mitochondrial carrier proteins, and autophagy proteins were all identified as Gcn4p targets. Unexpectedly, genes involved in amino acid biosynthesis represent only a quarter of the Gcn4p target genes. Gcn4p also activates genes involved in glycogen homeostasis, and mutant analysis showed that Gcn4p suppresses glycogen levels in amino acid-starved cells. Numerous genes encoding protein kinases and transcription factors were identified as targets, suggesting that Gcn4p is a master regulator of gene expression. Interestingly, expression profiles for 3AT and the alkylating agent methyl methanesulfonate (MMS) overlapped extensively, and MMS induced GCN4 translation. Thus, the broad transcriptional response evoked by Gcn4p is produced by diverse stress conditions. Finally, profiling of a gcn4Delta mutant uncovered an alternative induction pathway operating at many Gcn4p target genes in histidine-starved cells.

Characterization of 16 novel human genes showing high similarity to yeast sequences

The entire set of open reading frames (ORFs) of Saccharomyces cerevisiae has been used to perform systematic similarity searches against nucleic acid and protein databases: with the aim of identifying interesting homologies between yeast and mammalian genes. Many similarities were detected: mostly with known genes. However: several yeast ORFs were only found to match human partial sequence tags: indicating the presence of human transcripts still uncharacterized that have a homologous counterpart in yeast. About 30 such transcripts were further studied and named HUSSY (human sequence similar to yeast). The 16 most interesting are presented in this paper along with their sequencing and mapping data. As expected: most of these genes seem to be involved in basic metabolic and cellular functions (lipoic acid biosynthesis: ribulose-5-phosphate-3-epimerase: glycosyl transferase: beta-transducin: serine-threonine-kinase: ABC proteins: cation transporters). Genes related to RNA maturation were also found (homologues to DIM1: ROK1-RNA-elicase and NFS1). Furthermore: five novel human genes were detected (HUSSY-03: HUSSY-22: HUSSY-23: HUSSY-27: HUSSY-29) that appear to be homologous to yeast genes whose function is still undetermined. More information on this work can be obtained at the website http://grup.bio.unipd.it/hussy

Novel fungal transcriptional activators, Cmr1p of Colletotrichum lagenarium and pig1p of Magnaporthe grisea, contain Cys2His2 zinc finger and Zn(II)2Cys6 binuclear cluster DNA-binding motifs and regulate transcription of melanin biosynthesis genes in a developmentally specific manner

Colletotrichum lagenarium and Magnaporthe grisea are plant pathogenic fungi that produce melanin during the appressorial differentiation stage of conidial germination and during the late stationary phase of mycelial growth. Here, we report the identification of genes for two unique transcription factors, CMR1 (Colletotrichum melanin regulation) and PIG1 (pigment of Magnaporthe), that are involved in melanin biosynthesis. Both Cmr1p and Pig1p contain two distinct DNA-binding motifs, a Cys2His2 zinc finger motif and a Zn(II)2Cys6 binuclear cluster motif. The presence of both these motifs in a single transcriptional regulatory protein is unique among known eukaryotic transcription factors. Deletion of CMR1 in C. lagenarium caused a defect in mycelial melanization, but not in appressorial melanization. Also, cmr1Delta mutants do not express the melanin biosynthetic structural genes SCD1 and THR1 during mycelial melanization, although the expression of these two genes was not affected during appressorial melanization.

A Bayesian system integrating expression data with sequence patterns for localizing proteins: comprehensive application to the yeast genome

We develop a probabilistic system for predicting the subcellular localization of proteins and estimating the relative population of the various compartments in yeast. Our system employs a Bayesian approach, updating a protein's probability of being in a compartment, based on a diverse range of 30 features. These range from specific motifs (e.g. signal sequences or the HDEL motif) to overall properties of a sequence (e.g. surface composition or isoelectric point) to whole-genome data (e.g. absolute mRNA expression levels or their fluctuations). The strength of our approach is the easy integration of many features, particularly the whole-genome expression data. We construct a training and testing set of approximately 1300 yeast proteins with an experimentally known localization from merging, filtering, and standardizing the annotation in the MIPS, Swiss-Prot and YPD databases, and we achieve 75 % accuracy on individual protein predictions using this dataset. Moreover, we are able to estimate the relative protein population of the various compartments without requiring a definite localization for every protein. This approach, which is based on an analogy to formalism in quantum mechanics, gives better accuracy in determining relative compartment populations than that obtained by simply tallying the localization predictions for individual proteins (on the yeast proteins with known localization, 92% versus 74%). Our training and testing also highlights which of the 30 features are informative and which are redundant (19 being particularly useful). After developing our system, we apply it to the 4700 yeast proteins with currently unknown localization and estimate the relative population of the various compartments in the entire yeast genome. An unbiased prior is essential to this extrapolated estimate; for this, we use the MIPS localization catalogue, and adapt recent results on the localization of yeast proteins obtained by Snyder and colleagues using a minitransposon system. Our final localizations for all approximately 6000 proteins in the yeast genome are available over the web at: http://bioinfo.mbb.yale. edu/genome/localize.

Sequence diversification of the FK506-binding proteins in several different genomes

Sequences of FK506-binding proteins (FKBPs) from four genomes of the following organisms were compared: the prokaryote Escherichia coli, the lower eukaryote Saccharomyces cerevisiae, the plant Arabidopsis thaliana, the nematode Caenorhabditis elegans and a composite of 14 unique FKBPs from two mammalian organisms Homo sapiens (man) and Mus musculus (domestic mouse). A singular FK506-like binding domain (FKBD) has about 12 kDa and occurs in the form of archetypal FKBP-12 and as a part of different proteins ranging in size from 13 to 135 kDa. Some organisms may contain a variable number of proteins which consist from two to four consecutively fused FKBDs. In the 12-kDa subgroup of archetypal FKBPs sequence identity (ID) varies from 100 to 83% (mammalian FKBPs-12), 75-50% in mammalian vs. invertebrate FKBPs-12, and fall to about 30% for pairwise sequence comparisons of mammalian and bacterial FKBPs-12 which suggests that their sequences are divergent. Multiple sequence alignment of FKBPs from the four genomes and a set of unique mammalian FKBPs does not contain any explicit consensus sequence but certain sequence positions have conserved physico-chemical characteristics. Variations of hydrophobicity and bulkiness in the multiple sequence alignment are nonsymmetrical because the physico-chemical properties of the aligned sequences changed during evolution. These variations at the sequence positions which are crucial for binding the immunosuppressive macrolide FK506 and peptidyl-prolyl cis/trans isomerase (PPIase) activity are small.

Who's your neighbor? New computational approaches for functional genomics

Several recently developed computational approaches in comparative genomics go beyond sequence comparison. By analyzing phylogenetic profiles of protein families, domain fusions, gene adjacency in genomes, and expression patterns, these methods predict many functional interactions between proteins and help deduce specific functions for numerous proteins. Although some of the resultant predictions may not be highly specific, these developments herald a new era in genomics in which the benefits of comparative analysis of the rapidly growing collection of complete genomes will become increasingly obvious.

Assessing annotation transfer for genomics: quantifying the relations between protein sequence, structure and function through traditional and probabilistic scores

Measuring in a quantitative, statistical sense the degree to which structural and functional information can be "transferred" between pairs of related protein sequences at various levels of similarity is an essential prerequisite for robust genome annotation. To this end, we performed pairwise sequence, structure and function comparisons on approximately 30,000 pairs of protein domains with known structure and function. Our domain pairs, which are constructed according to the SCOP fold classification, range in similarity from just sharing a fold, to being nearly identical. Our results show that traditional scores for sequence and structure similarity have the same basic exponential relationship as observed previously, with structural divergence, measured in RMS, being exponentially related to sequence divergence, measured in percent identity. However, as the scale of our survey is much larger than any previous investigations, our results have greater statistical weight and precision. We have been able to express the relationship of sequence and structure similarity using more "modern scores," such as Smith-Waterman alignment scores and probabilistic P-values for both sequence and structure comparison. These modern scores address some of the problems with traditional scores, such as determining a conserved core and correcting for length dependency; they enable us to phrase the sequence-structure relationship in more precise and accurate terms. We found that the basic exponential sequence-structure relationship is very general: the same essential relationship is found in the different secondary-structure classes and is evident in all the scoring schemes. To relate function to sequence and structure we assigned various levels of functional similarity to the domain pairs, based on a simple functional classification scheme. This scheme was constructed by combining and augmenting annotations in the enzyme and fly functional classifications and comparing subsets of these to the Escherichia coli and yeast classifications. We found sigmoidal relationships between similarity in function and sequence, with clear thresholds for different levels of functional conservation. For pairs of domains that share the same fold, precise function appears to be conserved down to approximately 40 % sequence identity, whereas broad functional class is conserved to approximately 25 %. Interestingly, percent identity is more effective at quantifying functional conservation than the more modern scores (e.g. P-values). Results of all the pairwise comparisons and our combined functional classification scheme for protein structures can be accessed from a web database at http://bioinfo.mbb.yale.edu/alignCopyright 2000 Academic Press.

Analysis of the yeast transcriptome with structural and functional categories: characterizing highly expressed proteins

We analyzed 10 genome expression data sets by large-scale cross-referencing against broad structural and functional categories. The data sets, generated by different techniques (e.g. SAGE and gene chips), provide various representations of the yeast transcriptome (the set of all yeast genes, weighted by transcript abundance). Our analysis enabled us to determine features more prevalent in the transcriptome than the genome: i.e. those that are common to highly expressed proteins. Starting with simplest categories, we find that, relative to the genome, the transcriptome is enriched in Ala and Gly and depleted in Asn and very long proteins. We find, furthermore, that protein length and maximum expression level have a roughly inverse relationship. To relate expression level and protein structure, we assigned transmembrane helices and known folds (using PSI-blast) to each protein in the genome; this allowed us to determine that the transcriptome is enriched in mixed alpha-beta structures and depleted in membrane proteins relative to the genome. In particular, some enzymatic folds, such as the TIM barrel and the G3P dehydrogenase fold, are much more prevalent in the transcriptome than the genome, whereas others, such as the protein-kinase and leucine-zipper folds, are depleted. The TIM barrel, in fact, is overwhelmingly the 'top fold' in the transcriptome, while it only ranks fifth in the genome. The most highly enriched functional categories in the transcriptome (based on the MIPS system) are energy production and protein synthesis, while categories such as transcription, transport and signaling are depleted. Furthermore, for a given functional category, transcriptome enrichment varies quite substantially between the different expression data sets, with a variation an order of magnitude larger than for the other categories cross-referenced (e.g. amino acids). One can readily see how the enrichment and depletion of the various functional categories relates directly to that of particular folds.

Mapping and structure of DMXL1, a human homologue of the DmX gene from Drosophila melanogaster coding for a WD repeat protein

The DmX gene was recently isolated from the X chromosome of Drosophila melanogaster. TBLASTN searches of the dbEST databases revealed sequences with a high level of similarity to DmX in a variety of different species, including insects, nematodes, and mammals showing that DmX is an evolutionarily highly conserved gene. Here we describe the cloning of the cDNA and the chromosomal localization of one of the human homologues of DmX, Dmx-like 1 (DMXL1). The human DMXL1 gene codes for a large mRNA of 11 kb with an open reading frame of 3027 amino acids. The putative protein belongs to the superfamily of WD repeat proteins, which have mostly regulatory functions. The DMXL1 protein contains an exceptionally large number of WD repeat units. The DMXL1 gene is located on chromosome 5q22 as determined by radiation hybrid mapping and fluorescence in situ hybridization. Although the function of the DMXL1 gene and its homologues in other species remains to be discovered, the high level of evolutionary conservation together with the unusual structure suggests that it probably has an important function.

Royal Society of Chemistry and The Biochemical Society's international symposium on functional genomics: from gene to commercial reality? September 19-22, 1999, Ambleside, UK

All aspects of genomics were covered during the meeting from gene identification and characterization to exploitation of genomic targets. Speakers highlighted the strategies used together with recent examples, indicating the advantages together with the disadvantages of the methodologies used.

ProClass protein family database

ProClass is a protein family database that organizes non-redundant sequence entries into families defined collectively by PIR superfamilies and PROSITE patterns. By combining global similarities and functional motifs into a single classification scheme, ProClass helps to reveal domain and family relationships and classify multi-domain proteins. The database currently consists of >155 000 sequence entries retrieved from both PIR-International and SWISS-PROT databases. Approximately 92 000 or 60% of the ProClass entries are classified into approximately 6000 families, including a large number of new members detected by our GeneFIND family identification system. The ProClass motif collection contains approximately 72 000 motif sequences and >1300 multiple alignments for all PROSITE patterns, including >21 000 matches not listed in PROSITE and mostly detected from unique PIR sequences. To maximize family information retrieval, the database provides links to various protein family, domain, alignment and structural class databases. With its high classification rate and comprehensive family relationships, ProClass can be used to support full-scale genomic annotation. The database, now being implemented in an object-relational database management system, is available for online sequence search and record retrieval from our WWW server at http://pir.georgetown.edu/gfserver/proclass.html

Conservation of matrix attachment region-binding filament-like protein 1 among higher plants

The interaction of chromatin with the nuclear matrix via matrix attachment regions (MARs) on the DNA is considered to be of fundamental importance for higher-order chromatin organization and the regulation of gene expression. We have previously isolated a novel nuclear matrix-localized protein (MFP1) from tomato (Lycopersicon esculentum) that preferentially binds to MAR DNA. Tomato MFP1 has a predicted filament-protein-like structure and is associated with the nuclear envelope via an N-terminal targeting domain. Based on the antigenic relationship, we report here that MFP1 is conserved in a large number of dicot and monocot species. Several cDNAs were cloned from tobacco (Nicotiana tabacum) and shown to correspond to two tobacco MFP1 genes. Comparison of the primary and predicted secondary structures of MFP1 from tomato, tobacco, and Arabidopsis indicates a high degree of conservation of the N-terminal targeting domain, the overall putative coiled-coil structure of the protein, and the C-terminal DNA-binding domain. In addition, we show that tobacco MFP1 is regulated in an organ-specific and developmental fashion, and that this regulation occurs at the level of transcription or RNA stability.

Variations of sequences and amino acid compositions of proteins that sustain their biological functions: An analysis of the cyclophilin family of proteins

The sequences of the ubiquitous and phylogenetically diversified cyclophilin family of proteins were divided into six groups, namely, vertebrates, invertebrates, other metazoa, plants, fungi, and prokaryotes. These groups of sequences were aligned with the multiple sequence alignment program Clustal-W. The variations of amino acid substitutions and amino acid compositions for these six groups of cyclophilins were calculated using a novel suite of multiple-sequence alignment analysis routines. The cyclophilins from vertebrates can be divided for at least two distinct structural classes that differ from each other by a variable-length amino acid insert within the loop that links alpha-helix II and beta-strand III. A similar structural feature is also present in the other groups of cyclophilins, namely, those from invertebrates, other metazoa, plants, and fungi. The sequences of cyclophilins from fungi and prokaryotes are more diversified than those from vertebrates, and their alterations involve structures other than the amino acid inserts within the loops. Variations of the hydrophobicity and bulkiness of amino acid substitutions of the aligned sequences were calculated for each group of cyclophilins and for the alignment of all the sequences. The variations have clear asymmetry that may signify the need for modification of the physical properties of certain fragments of cyclophilins that are involved in interactions with various cellular components in the evolving environment.

A combined algorithm for genome-wide prediction of protein function

The availability of over 20 fully sequenced genomes has driven the development of new methods to find protein function and interactions. Here we group proteins by correlated evolution, correlated messenger RNA expression patterns and patterns of domain fusion to determine functional relationships among the 6,217 proteins of the yeast Saccharomyces cerevisiae. Using these methods, we discover over 93,000 pairwise links between functionally related yeast proteins. Links between characterized and uncharacterized proteins allow a general function to be assigned to more than half of the 2,557 previously uncharacterized yeast proteins. Examples of functional links are given for a protein family of previously unknown function, a protein whose human homologues are implicated in colon cancer and the yeast prion Sup35.

Genetic and physical interactions involving the yeast nuclear cap-binding complex

Yeast strains lacking the yeast nuclear cap-binding complex (yCBC) are viable, although impaired in growth. We have taken advantage of this observation to carry out a genetic screen for components that show synthetic lethality (SL) with a cbp20-Delta cbp80-Delta double mutation. One set of SL interactions was due to mutations that were complemented by components of U1 small nuclear RNP (snRNP) and the yeast splicing commitment complex. These interactions confirm the role of yCBC in commitment complex formation. Physical interaction of yCBC with the commitment complex components Mud10p and Mud2p, which may directly mediate yCBC function, was demonstrated. Unexpectedly, we identified multiple SL mutations that were complemented by Cbf5p and Nop58p. These are components of the two major classes of yeast small nucleolar RNPs, which function in the maturation of rRNA precursors. Mutants lacking yCBC were found to be defective in rRNA processing. Analysis of the yCBC deletion phenotype suggests that this is likely to be due to a defect in the splicing of a subset of ribosomal protein mRNA precursors.

MAF1, a novel plant protein interacting with matrix attachment region binding protein MFP1, is located at the nuclear envelope

The interaction of chromatin with the nuclear matrix via matrix attachment region (MAR) DNA is considered to be of fundamental importance for chromatin organization in all eukaryotic cells. MAR binding filament-like protein 1 (MFP1) from tomato is a novel plant protein that specifically binds to MAR DNA. Its filament protein-like structure makes it a likely candidate for a structural component of the nuclear matrix. MFP1 is located at nuclear matrix-associated, specklelike structures at the nuclear envelope. Here, we report the identification of a novel protein that specifically interacts with MFP1 in yeast two-hybrid and in vitro binding assays. MFP1 associated factor 1 (MAF1) is a small, soluble, serine/threonine-rich protein that is ubiquitously expressed and has no similarity to known proteins. MAF1, like MFP1, is located at the nuclear periphery and is a component of the nuclear matrix. These data suggest that MFP1 and MAF1 are in vivo interaction partners and that both proteins are components of a nuclear substructure, previously undescribed in plants, that connects the nuclear envelope and the internal nuclear matrix.

A fast method to diagnose chromosome and plasmid loss in Saccharomyces cerevisiae strains

We have developed a simple, fast and reliable method for the analysis of genetic stability in budding yeast strains. The assay relies on our previous finding that cells expressing the green fluorescent protein (GFP) can be detected and counted by flow cytometric analysis (FACS) (Niedenthal et al., 1996). Expression of a gfp-carrying CEN-plasmid in a wild-type strain resulted in the emission of strong fluorescence from 80% of the cell population. Strong fluorescence and presence of the plasmid, determined by the presence of the URA3 genetic marker, was strictly correlated. Expression of this plasmid in 266 yeast strains, each carrying a complete deletion of a novel, non-essential gene identified in the S. cerevisiae sequencing project, pinpointed 12 strains with an increased level of mitotic plasmid loss. Finally we have shown that measurement of mitotic loss of artificial chromosome fragments equipped with the gfp expression cassette can be performed quantitatively using FACS.

Matrix attachment region binding protein MFP1 is localized in discrete domains at the nuclear envelope

Recently, it has been suggested that nuclear processes, such as replication, transcription, and splicing, are spatially organized and associated with a nuclear framework called the nuclear matrix, a structure of unknown molecular composition. It has been shown that chromatin is attached to the nuclear matrix via specific DNA fragments called matrix attachment regions (MARs). We have begun to dissect the plant nuclear matrix by isolating a DNA binding protein with specific affinity for MARs. Here, it is shown that MAR binding filament-like protein 1 (MFP1) is associated with specklelike structures at the nuclear periphery that are part of isolated nuclei and the nuclear matrix. A predicted N-terminal transmembrane domain is necessary for the specific targeting of MFP1 to the speckles, indicating an association with the nuclear envelope-endoplasmic reticulum continuum. In addition, it is shown that a marker protein for plant microtubule organizing centers, which has been shown to be localized on the outside of the plant nuclear envelope, is also part of the nuclear matrix. These findings indicate a close and previously undescribed connection in plants between the nuclear envelope and the internal nuclear matrix, and they suggest a function for MFP1 in attaching chromatin to specific sites at the nuclear periphery.

Prediction of protein subcellular locations using Markov chain models

A novel method was introduced to predict protein subcellular locations from sequences. Using sequence data, this method achieved a prediction accuracy higher than previous methods based on the amino acid composition. For three subcellular locations in a prokaryotic organism, the overall prediction accuracy reached 89.1%. For eukaryotic proteins, prediction accuracies of 73.0% and 78.7% were attained within four and three location categories, respectively. These results demonstrate the applicability of this relative simple method and possible improvement of prediction for the protein subcellular location.

The peculiar architectural framework of tRNASec is fully recognized by yeast AspRS

The wild-type transcript of Escherichia coli tRNASec, characterized by a peculiar core architecture and a large variable region, was shown to be aspartylatable by yeast AspRS. Similar activities were found for tRNASec mutants with methionine, leucine, and tryptophan anticodons. The charging efficiency of these molecules was found comparable to that of a minihelix derived from tRNAAsp and is accounted for by the presence of the discriminator residue G73, which is a major aspartate identity determinant. Introducing the aspartate identity elements from the anticodon loop (G34, U35, C36, C38) into tRNASec transforms this molecule into an aspartate acceptor with kinetic properties identical to tRNAAsp. Expression of the aspartate identity set in tRNASec is independent of the size of its variable region. The functional study was completed by footprinting experiments with four different nucleases as structural probes. Protection patterns by AspRS of transplanted tRNASec and tRNAAsp were found similar. They are modified, particularly in the anticodon loop, upon changing the aspartate anticodon into that of methionine. Altogether, it appears that recognition of a tRNA by AspRS is more governed by the presence of the aspartate identity set than by the structural framework that carries this set.