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M Gerstein

Publications and source records attributed to M Gerstein.

At least 19 recordsLinked to original sources
PubMed2006

The geometry of the ribosomal polypeptide exit tunnel.

The geometry of the polypeptide exit tunnel has been determined using the crystal structure of the large ribosomal subunit from Haloarcula marismortui. The tunnel is a component of a much larger, interconnected system of channels accessible to solvent that permeates the subunit and is connected to the exterior at many points. Since water and other small molecules can diffuse into and out of the tunnel along many different trajectories, the large subunit cannot be part of the seal that keeps ions from passing through the ribosome-translocon complex. The structure referred to as the tunnel is the only passage in the solvent channel system that is both large enough to accommodate nascent peptides, and that traverses the particle. For objects of that size, it is effectively an unbranched tube connecting the peptidyl transferase center of the large subunit and the site where nascent peptides emerge. At no point is the tunnel big enough to accommodate folded polypeptides larger than alpha-helices.

Chaperonins↗
PubMed2005

Remodeling of hippocampal GABAergic system in adult offspring after maternal hypoxia and magnesium sulfate load: immunohistochemical study.

A strong relationship between hypoxia and fetal brain damage has been described. Specific susceptibility of the GABAergic neurons to these conditions may be crucial to the damage induced. We have previously shown, in a mouse model, that maternal pretreatment with magnesium sulfate (Mg) partially prevented the behavioral consequences of maternal hypoxia in the adult offspring. Here, we tested the effect of maternal hypoxia and maternal Mg load on the GABAergic system of 8-month-old offspring. The immunoreactivity (IR) of several proteins expressed in GABAergic neurons and inhibitory synapses was analyzed in the following regions of the adult offspring brain: hippocampus, cortical M1, caudate putamen, and lateral globus pallidus. Maternal hypoxia reduced the density of parvalbumin (PV)-IR neurons in the hippocampus. The density of PV-IR and calbindin (CB)-IR neurons was also reduced in the deep and superficial layers of the M1. Maternal pretreatment with Mg had a prophylactic action in the superficial, but not the deep, layers of M1. Also, in offspring from the maternal hypoxia group, the vesicular GABA transporter (VGAT)-IR was enhanced in the hippocampal CA1 and hilus regions. No effect of maternal hypoxia on VGAT-IR was observed in the M1. However, maternal pretreatment with Mg enhanced VGAT-IR and glutamate decarboxylase-IR in the deep layers of the M1. In the globus pallidus, maternal hypoxia enhanced CB-IR, which was prevented by maternal pretreatment with Mg. In conclusion, maternal hypoxia induced a loss of PV-IR and CB-IR neurons; maternal pretreatment with Mg partially protected these neuron populations. An increase in proteins of inhibitory synapses, observed under hypoxic conditions in several brain regions, may be a result of some compensatory mechanism.

Animals↗
PubMed2005

Calculation of standard atomic volumes for RNA and comparison with proteins: RNA is packed more tightly.

Traditionally, for biomolecular packing calculations research has focused on proteins. Besides proteins, RNA is the other large biomolecule that has tertiary structure interactions and complex packing. No one has yet quantitatively investigated RNA packing or compared its packing to that of proteins because, until recently, there were no large RNA structures. Here we address this question in detail, using Voronoi volume calculations on a set of high-resolution RNA crystal structures. We do a careful parameterization, taking into account many factors such as atomic radii, crystal packing, structural complexity, solvent, and associated protein to obtain a self-consistent, universal set of volumes that can be applied to both RNA and protein. We report this set of volumes, which we call the NucProt parameter set. Our measured values are consistent across the many different RNA structures and packing environments. When common atom types are compared between proteins and RNA, nine of 12 types show that RNA has a smaller volume and packs more tightly than protein, suggesting that close-packing may be as important for the folding of RNAs as it is for proteins. Moreover, calculated partial specific volumes show that RNA bases pack more densely than corresponding aromatic residues from proteins. Finally, we find that RNA bases have similar packing volumes to DNA bases, despite the absence of tertiary contacts in DNA. Programs, parameter sets and raw data are available online at.

Crystallography, X-Ray↗
PubMed2002

GeneCensus: genome comparisons in terms of metabolic pathway activity and protein family sharing.

We present a prototype of a new database tool, GeneCensus, which focuses on comparing genomes globally, in terms of the collective properties of many genes, rather than in terms of the attributes of a single gene (e.g. sequence similarity for a particular ortholog). The comparisons are presented in a visual fashion over the web at GeneCensus.org. The system concentrates on two types of comparisons: (i) trees based on the sharing of generalized protein families between genomes, and (ii) whole pathway analysis in terms of activity levels. For the trees, we have developed a module (TreeViewer) that clusters genomes in terms of the folds, superfamilies or orthologs--all can be considered as generalized 'families' or 'protein parts'--they share, and compares the resulting trees side-by-side with those built from sequence similarity of individual genes (e.g. a traditional tree built on ribosomal similarity). We also include comparisons to trees built on whole-genome dinucleotide or codon composition. For pathway comparisons, we have implemented a module (PathwayPainter) that graphically depicts, in selected metabolic pathways, the fluxes or expression levels of the associated enzymes (i.e. generalized 'activities'). One can, consequently, compare organisms (and organism states) in terms of representations of these systemic quantities. Develop ment of this module involved compiling, calculating and standardizing flux and expression information from many different sources. We illustrate pathway analysis for enzymes involved in central metabolism. We are able to show that, to some degree, flux and expression fluctuations have characteristic values in different sections of the central metabolism and that control points in this system (e.g. hexokinase, pyruvate kinase, phosphofructokinase, isocitrate dehydrogenase and citric synthase) tend to be especially variable in flux and expression. Both the TreeViewer and PathwayPainter modules connect to other information sources related to individual-gene or organism properties (e.g. a single-gene structural annotation viewer).

Animals↗
PubMed2001

Beyond synexpression relationships: local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions.

The complexity of biological systems provides for a great diversity of relationships between genes. The current analysis of whole-genome expression data focuses on relationships based on global correlation over a whole time-course, identifying clusters of genes whose expression levels simultaneously rise and fall. There are, of course, other potential relationships between genes, which are missed by such global clustering. These include activation, where one expects a time-delay between related expression profiles, and inhibition, where one expects an inverted relationship. Here, we propose a new method, which we call local clustering, for identifying these time-delayed and inverted relationships. It is related to conventional gene-expression clustering in a fashion analogous to the way local sequence alignment (the Smith-Waterman algorithm) is derived from global alignment (Needleman-Wunsch). An integral part of our method is the use of random score distributions to assess the statistical significance of each cluster. We applied our method to the yeast cell-cycle expression dataset and were able to detect a considerable number of additional biological relationships between genes, beyond those resulting from conventional correlation. We related these new relationships between genes to their similarity in function (as determined from the MIPS scheme) or their having known protein-protein interactions (as determined from the large-scale two-hybrid experiment); we found that genes strongly related by local clustering were considerably more likely than random to have a known interaction or a similar cellular role. This suggests that local clustering may be useful in functional annotation of uncharacterized genes. We examined many of the new relationships in detail. Some of them were already well-documented examples of inhibition or activation, which provide corroboration for our results. For instance, we found an inverted expression profile relationship between genes YME1 and YNT20, where the latter has been experimentally documented as a bypass suppressor of the former. We also found new relationships involving uncharacterized yeast genes and were able to suggest functions for many of them. In particular, we found a time-delayed expression relationship between J0544 (which has not yet been functionally characterized) and four genes associated with the mitochondria. This suggests that J0544 may be involved in the control or activation of mitochondrial genes. We have also looked at other, less extensive datasets than the yeast cell-cycle and found further interesting relationships. Our clustering program and a detailed website of clustering results is available at http://www.bioinfo.mbb.yale.edu/expression/cluster (or http://www.genecensus.org/expression/cluster).

Algorithms↗
PubMed2001

Protein family and fold occurrence in genomes: power-law behaviour and evolutionary model.

Global surveys of genomes measure the usage of essential molecular parts, defined here as protein families, superfamilies or folds, in different organisms. Based on surveys of the first 20 completely sequenced genomes, we observe that the occurrence of these parts follows a power-law distribution. That is, the number of distinct parts (F) with a given genomic occurrence (V) decays as F=aV(-b), with a few parts occurring many times and most occurring infrequently. For a given organism, the distributions of families, superfamilies and folds are nearly identical, and this is reflected in the size of the decay exponent b. Moreover, the exponent varies between different organisms, with those of smaller genomes displaying a steeper decay (i.e. larger b). Clearly, the power law indicates a preference to duplicate genes that encode for molecular parts which are already common. Here, we present a minimal, but biologically meaningful model that accurately describes the observed power law. Although the model performs equally well for all three protein classes, we focus on the occurrence of folds in preference to families and superfamilies. This is because folds are comparatively insensitive to the effects of point mutations that can cause a family member to diverge beyond detectable similarity. In the model, genomes evolve through two basic operations: (i) duplication of existing genes; (ii) net flow of new genes. The flow term is closely related to the exponent b and can accommodate considerable gene loss; however, we demonstrate that the observed data is reproduced best with a net inflow, i.e. with more gene gain than loss. Moreover, we show that prokaryotes have much higher rates of gene acquisition than eukaryotes, probably reflecting lateral transfer. A further natural outcome from our model is an estimation of the fold composition of the initial genome, which potentially relates to the common ancestor for modern organisms. Supplementary material pertaining to this work is available from www.partslist.org/powerlaw.

Animals↗
PubMed2001

Genomic and proteomic analysis of the myeloid differentiation program.

Although the mature neutrophil is one of the better characterized mammalian cell types, the mechanisms of myeloid differentiation are incompletely understood at the molecular level. A mouse promyelocytic cell line (MPRO), derived from murine bone marrow cells and arrested developmentally by a dominant-negative retinoic acid receptor, morphologically differentiates to mature neutrophils in the presence of 10 microM retinoic acid. An extensive catalog was prepared of the gene expression changes that occur during morphologic maturation. To do this, 3'-end differential display, oligonucleotide chip array hybridization, and 2-dimensional protein electrophoresis were used. A large number of genes whose mRNA levels are modulated during differentiation of MPRO cells were identified. The results suggest the involvement of several transcription regulatory factors not previously implicated in this process, but they also emphasize the importance of events other than the production of new transcription factors. Furthermore, gene expression patterns were compared at the level of mRNA and protein, and the correlation between 2 parameters was studied. (Blood. 2001;98:513-524)

Animals↗
PubMed2001

Global analysis of protein activities using proteome chips.

To facilitate studies of the yeast proteome, we cloned 5800 open reading frames and overexpressed and purified their corresponding proteins. The proteins were printed onto slides at high spatial density to form a yeast proteome microarray and screened for their ability to interact with proteins and phospholipids. We identified many new calmodulin- and phospholipid-interacting proteins; a common potential binding motif was identified for many of the calmodulin-binding proteins. Thus, microarrays of an entire eukaryotic proteome can be prepared and screened for diverse biochemical activities. The microarrays can also be used to screen protein-drug interactions and to detect posttranslational modifications.

Amino Acid Motifs↗
PubMed2001

SPINE: an integrated tracking database and data mining approach for identifying feasible targets in high-throughput structural proteomics.

High-throughput structural proteomics is expected to generate considerable amounts of data on the progress of structure determination for many proteins. For each protein this includes information about cloning, expression, purification, biophysical characterization and structure determination via NMR spectroscopy or X-ray crystallography. It will be essential to develop specifications and ontologies for standardizing this information to make it amenable to retrospective analysis. To this end we created the SPINE database and analysis system for the Northeast Structural Genomics Consortium. SPINE, which is available at bioinfo.mbb.yale.edu/nesg or nesg.org, is specifically designed to enable distributed scientific collaboration via the Internet. It was designed not just as an information repository but as an active vehicle to standardize proteomics data in a form that would enable systematic data mining. The system features an intuitive user interface for interactive retrieval and modification of expression construct data, query forms designed to track global project progress and external links to many other resources. Currently the database contains experimental data on 985 constructs, of which 740 are drawn from Methanobacterium thermoautotrophicum, 123 from Saccharomyces cerevisiae, 93 from Caenorhabditis elegans and the remainder from other organisms. We developed a comprehensive set of data mining features for each protein, including several related to experimental progress (e.g. expression level, solubility and crystallization) and 42 based on the underlying protein sequence (e.g. amino acid composition, secondary structure and occurrence of low complexity regions). We demonstrate in detail the application of a particular machine learning approach, decision trees, to the tasks of predicting a protein's solubility and propensity to crystallize based on sequence features. We are able to extract a number of key rules from our trees, in particular that soluble proteins tend to have significantly more acidic residues and fewer hydrophobic stretches than insoluble ones. One of the characteristics of proteomics data sets, currently and in the foreseeable future, is their intermediate size ( approximately 500-5000 data points). This creates a number of issues in relation to error estimation. Initially we estimate the overall error in our trees based on standard cross-validation. However, this leaves out a significant fraction of the data in model construction and does not give error estimates on individual rules. Therefore, we present alternative methods to estimate the error in particular rules.

Animals↗
PubMed2001

PartsList: a web-based system for dynamically ranking protein folds based on disparate attributes, including whole-genome expression and interaction information.

As the number of protein folds is quite limited, a mode of analysis that will be increasingly common in the future, especially with the advent of structural genomics, is to survey and re-survey the finite parts list of folds from an expanding number of perspectives. We have developed a new resource, called PartsList, that lets one dynamically perform these comparative fold surveys. It is available on the web at http://bioinfo.mbb.yale.edu/partslist and http://www.partslist.org. The system is based on the existing fold classifications and functions as a form of companion annotation for them, providing 'global views' of many already completed fold surveys. The central idea in the system is that of comparison through ranking; PartsList will rank the approximately 420 folds based on more than 180 attributes. These include: (i) occurrence in a number of completely sequenced genomes (e.g. it will show the most common folds in the worm versus yeast); (ii) occurrence in the structure databank (e.g. most common folds in the PDB); (iii) both absolute and relative gene expression information (e.g. most changing folds in expression over the cell cycle); (iv) protein-protein interactions, based on experimental data in yeast and comprehensive PDB surveys (e.g. most interacting fold); (v) sensitivity to inserted transposons; (vi) the number of functions associated with the fold (e.g. most multi-functional folds); (vii) amino acid composition (e.g. most Cys-rich folds); (viii) protein motions (e.g. most mobile folds); and (ix) the level of similarity based on a comprehensive set of structural alignments (e.g. most structurally variable folds). The integration of whole-genome expression and protein-protein interaction data with structural information is a particularly novel feature of our system. We provide three ways of visualizing the rankings: a profiler emphasizing the progression of high and low ranks across many pre-selected attributes, a dynamic comparer for custom comparisons and a numerical rankings correlator. These allow one to directly compare very different attributes of a fold (e.g. expression level, genome occurrence and maximum motion) in the uniform numerical format of ranks. This uniform framework, in turn, highlights the way that the frequency of many of the attributes falls off with approximate power-law behavior (i.e. according to V(-b), for attribute value V and constant exponent b), with a few folds having large values and most having small values.

Cysteine↗
PubMed2001

RNA expression patterns change dramatically in human neutrophils exposed to bacteria.

A comprehensive study of changes in messenger RNA (mRNA) levels in human neutrophils following exposure to bacteria is described. Within 2 hours there are dramatic changes in the levels of several hundred mRNAs including those for a variety of cytokines, receptors, apoptosis-regulating products, and membrane trafficking regulators. In addition, there are a large number of up-regulated mRNAs that appear to represent a common core of activation response genes that have been identified as early-response products to a variety of stimuli in a number of other cell types. The activation response of neutrophils to nonpathogenic bacteria is greatly altered by exposure to Yersinia pestis, which may be a major factor contributing to the virulence and rapid progression of plague. Several gene clusters were created based on the patterns of gene induction caused by different bacteria. These clusters were consistent with those found by a principal components analysis. A number of the changes could be interpreted in terms of neutrophil physiology and the known functions of the genes. These findings indicate that active regulation of gene expression plays a major role in the neutrophil contribution to the cellular inflammatory response. Interruption of these changes by pathogens, such as Y pestis, could be responsible, at least in part, for the failure to contain infections by highly virulent organisms.

Cells, Cultured↗
PubMed2001

Patients with urologic cancer and other nonurologic malignancies: analysis of a sample and review of the literature.

OBJECTIVES: To describe our experience with patients with urologic cancers who also have malignancies of nonurologic origin, before, after, or simultaneously, to review the literature, and to suggest treatment options. METHODS: We reviewed our institutions' tumor registry from 1995 to 2000 to discover how many patients had a urologic malignancy and another nonurologic cancer (antecedent, subsequent, or synchronous). We reviewed Medline from 1966 to 2000 and also questioned several urologists at major centers in the United States concerning this clinical dilemma. RESULTS: We encountered 18 patients during a 6-year period with a urologic cancer and another primary malignancy. Thirteen patients had their second cancer detected during the workup of their primary urologic tumor. Two patients developed a second tumor within 1 year of treatment of the primary urologic tumor. Another patient was referred with two primaries already diagnosed, and another had renal carcinoma detected during her colon cancer workup. We found that multiple tumors, although very rare, are usually detected during the preoperative workup of the primary tumor, usually by physical examination and improved radiologic imaging, or during the follow-up examinations. Most reports suggest that treatment should be performed simultaneously, especially if the lesions are relatively small and require a single incision, and the patient's medical condition allows longer anesthesia exposure. If these prerequisites are not met, most investigators agree that treatment should be directed at the more aggressive lesion first, which may improve the condition and/or survival, and thus, if a second operation is warranted, it will be possible. CONCLUSIONS: Although patients with multiple malignancies are rare, the urologist and/or other specialist should be alerted to this possibility when evaluating patients for the initially presenting symptoms and/or detected tumor, as well as during the follow-up evaluations.

Aged↗
PubMed2001

Determining the minimum number of types necessary to represent the sizes of protein atoms.

MOTIVATION: Traditionally, for packing calculations people have collected atoms together into a number of distinct 'types'. These, in fact, often represent a heavy atom and its associated hydrogens (i.e. a united atom). Also, atom typing is usually done according to basic chemistry, giving rise to 20-30 protein atom types, such as carbonyl carbons, methyl groups, and hydroxyl groups. No one has yet investigated how similar in packing these chemically derived types are. Here we address this question in detail, using Voronoi volume calculations on a set of high-resolution crystal structures. RESULTS: We perform a rigorous clustering analysis with cross-validation on tens of thousands of atom volumes and attempt to compile them into types based purely on packing. From our analysis, we are able to determine a 'minimal' set of 18 atom types that most efficiently represent the spectrum of packing in proteins. Furthermore, we are able to uncover a number of inconsistencies in traditional chemical typing schemes, where differently typed atoms have almost the same effective size. In particular, we find that tetrahedral carbons with two hydrogens are almost identical in size to many aromatic carbons with a single hydrogen. AVAILABILITY: Programs available from http://geometry.molmovdb.org. CONTACT: JerryTsai@TAMU.edu; neil.voss@yale.edu; Mark.Gerstein@yale.edu SUPPLEMENTARY INFORMATION: Available at http://geometry.molmovdb.org.

Carbon↗
PubMed2001

Annotation transfer for genomics: measuring functional divergence in multi-domain proteins.

Annotation transfer is a principal process in genome annotation. It involves "transferring" structural and functional annotation to uncharacterized open reading frames (ORFs) in a newly completed genome from experimentally characterized proteins similar in sequence. To prevent errors in genome annotation, it is important that this process be robust and statistically well-characterized, especially with regard to how it depends on the degree of sequence similarity. Previously, we and others have analyzed annotation transfer in single-domain proteins. Multi-domain proteins, which make up the bulk of the ORFs in eukaryotic genomes, present more complex issues in functional conservation. Here we present a large-scale survey of annotation transfer in these proteins, using scop superfamilies to define domain folds and a thesaurus based on SWISS-PROT keywords to define functional categories. Our survey reveals that multi-domain proteins have significantly less functional conservation than single-domain ones, except when they share the exact same combination of domain folds. In particular, we find that for multi-domain proteins, approximate function can be accurately transferred with only 35% certainty for pairs of proteins sharing one structural superfamily. In contrast, this value is 67% for pairs of single-domain proteins sharing the same structural superfamily. On the other hand, if two multi-domain proteins contain the same combination of two structural superfamilies the probability of their sharing the same function increases to 80% in the case of complete coverage along the full length of both proteins, this value increases further to > 90%. Moreover, we found that only 70 of the current total of 455 structural superfamilies are found in both single and multi-domain proteins and only 14 of these were associated with the same function in both categories of proteins. We also investigated the degree to which function could be transferred between pairs of multi-domain proteins with respect to the degree of sequence similarity between them, finding that functional divergence at a given amount of sequence similarity is always about two-fold greater for pairs of multi-domain proteins (sharing similarity over a single domain) in comparison to pairs of single-domain ones, though the overall shape of the relationship is quite similar. Further information is available at http://partslist.org/func or http://bioinfo.mbb.yale.edu/partslist/func.

Computational Biology↗
PubMed2001

Interrelating different types of genomic data, from proteome to secretome: 'oming in on function.

With the completion of genome sequences, the current challenge for biology is to determine the functions of all gene products and to understand how they contribute in making an organism viable. For the first time, biological systems can be viewed as being finite, with a limited set of molecular parts. However, the full range of biological processes controlled by these parts is extremely complex. Thus, a key approach in genomic research is to divide the cellular contents into distinct sub-populations, which are often given an "-omic" term. For example, the proteome is the full complement of proteins encoded by the genome, and the secretome is the part of it secreted from the cell. Carrying this further, we suggest the term "translatome" to describe the members of the proteome weighted by their abundance, and the "functome" to describe all the functions carried out by these. Once the individual sub-populations are defined and analyzed, we can then try to reconstruct the full organism by interrelating them, eventually allowing for a full and dynamic view of the cell. All this is, of course, made possible because of the increasing amount of large-scale data resulting from functional genomics experiments. However, there are still many difficulties resulting from the noisiness and complexity of the information. To some degree, these can be overcome through averaging with broad proteomic categories such as those implicit in functional and structural classifications. For illustration, we discuss one example in detail, interrelating transcript and cellular protein populations (transcriptome and translatome). Further information is available at http://bioinfo.mbb.yale.edu/what-is-it.

Bacillus subtilis↗