Plasma proteomic associations with genetics and health in the UK Biobank

The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics1.

Genetics implicates overactive osteogenesis in the development of diffuse idiopathic skeletal hyperostosis

Diffuse idiopathic skeletal hyperostosis (DISH) is a condition where adjacent vertebrae become fused through formation of osteophytes. The genetic and epidemiological etiology of this condition is not well understood. Here, we implemented a machine learning algorithm to assess the prevalence and severity of the pathology in ~40,000 lateral DXA scans in the UK Biobank Imaging cohort. We find that DISH is highly prevalent, above the age of 45, ~20% of men and ~8% of women having multiple osteophytes. Surprisingly, we find strong phenotypic and genetic association of DISH with increased bone mineral density and content throughout the entire skeletal system. Genetic association analysis identified ten loci associated with DISH, including multiple genes involved in bone remodeling (RUNX2, IL11, GDF5, CCDC91, NOG, and ROR2). Overall, this study describes genetics of DISH and implicates the role of overactive osteogenesis as a key driver of the pathology.

Joint inference of physiological network and survival analysis identifies factors associated with aging rate

We describe methodology for joint reconstruction of physiological-survival networks from observational data capable of identifying key survival-associated variables, inferring a minimal physiological network structure, and bridging this network to the Gompertzian survival layer. Using synthetic network structures, we show that the method is capable of identifying aging variables in cohorts as small as 5,000 participants. Applying the methodology to the observational human cohort, we find that interleukin-6, vascular calcification, and red-blood distribution width are strong predictors of baseline fitness. More important, we find that red blood cell counts, kidney function, and phosphate level are directly linked to the Gompertzian aging rate. Our model therefore enables discovery of processes directly linked to the aging rate of our species. We further show that this epidemiological framework can be applied as a causal inference engine to simulate the effects of interventions on physiology and longevity.

Global patterns of prognostic biomarkers across disease space

There is a multitude of pathological conditions that affect human health, yet we currently lack a predictive model for most diseases, and underlying mechanisms that are shared by multiple diseases are poorly understood. We leveraged baseline clinical biomarker data and long-term disease outcomes in UK Biobank to build prognostic multivariate survival models for over 200 most common diseases. We construct a similarity map between biomarker-disease hazard ratios and demonstrate broad patterns of shared similarity in biomarker profiles across the entire disease space. Further aggregation of risk profiles through density based clustering showed that biomarker-risk profiles can be partitioned into few distinct clusters with characteristic patterns representative of broad disease categories. To confirm these risk patterns we built disease co-occurrence networks in the UK Biobank and US HCUP hospitalization databases, and compared similarity in biomarker risk profiles to disease co-occurrence. We show that proximity in the biomarker-disease space is strongly related to the occurrence of disease comorbidity, suggesting biomarker profile patterns can be used for both predicting future outcomes as well as a sensitive mechanism for detecting under-diagnosed disease states.

Calcification of the abdominal aorta is an under-appreciated cardiovascular disease risk factor in the general population

Calcification of large arteries is a high-risk factor in the development of cardiovascular diseases, however, due to the lack of routine monitoring, the pathology remains severely under-diagnosed and prevalence in the general population is not known. We have developed a set of machine learning methods to quantitate levels of abdominal aortic calcification (AAC) in the UK Biobank imaging cohort and carried out the largest to-date analysis of genetic, biochemical, and epidemiological risk factors associated with the pathology. In a genetic association study, we identified three novel loci associated with AAC (FGF9, NAV9, and APOE), and replicated a previously reported association at the TWIST1/HDAC9 locus. We find that AAC is a highly prevalent pathology, with ~ 1 in 10 adults above the age of 40 showing significant levels of hydroxyapatite build-up (Kauppila score > 3). Presentation of AAC was strongly predictive of future cardiovascular events including stenosis of precerebral arteries (HR~1.5), myocardial infarction (HR~1.3), ischemic heart disease (HR~1.3), as well as other diseases such as chronic obstructive pulmonary disease (HR~1.3). Significantly, we find that the risk for myocardial infarction from elevated AAC (HR ~1.4) was comparable to the risk of hypercholesterolemia (HR~1.4), yet most people who develop AAC are not hypercholesterolemic. Furthermore, the overwhelming majority (98%) of individuals who develop pathology do so in the absence of known pre-existing risk conditions such as chronic kidney disease and diabetes (0.6% and 2.7% respectively). Our findings indicate that despite the high cardiovascular risk, calcification of large arteries remains a largely under-diagnosed lethal condition, and there is a clear need for increased awareness and monitoring of the pathology in the general population.

The promise and reality of therapeutic discovery from large cohorts

Technological advances in rapid data acquisition have transformed medical biology into a data mining field, where new data sets are routinely dissected and analyzed by statistical models of ever-increasing complexity. Many hypotheses can be generated and tested within a single large data set, and even small effects can be statistically discriminated from a sea of noise. On the other hand, the development of therapeutic interventions moves at a much slower pace. They are determined from carefully randomized and well-controlled experiments with explicitly stated outcomes as the principal mechanism by which a single hypothesis is tested. In this paradigm, only a small fraction of interventions can be tested, and an even smaller fraction are ultimately deemed therapeutically successful. In this Review, we propose strategies to leverage large-cohort data to inform the selection of targets and the design of randomized trials of novel therapeutics. Ultimately, the incorporation of big data and experimental medicine approaches should aim to reduce the failure rate of clinical trials as well as expedite and lower the cost of drug development.

Unraveling the message: insights into comparative genomics of the naked mole-rat

Animals have evolved to survive, and even thrive, in different environments. Genetic adaptations may have indirectly created phenotypes that also resulted in a longer lifespan. One example of this phenomenon is the preternaturally long-lived naked mole-rat. This strictly subterranean rodent tolerates hypoxia, hypercapnia, and soil-based toxins. Naked mole-rats also exhibit pronounced resistance to cancer and an attenuated decline of many physiological characteristics that often decline as mammals age. Elucidating mechanisms that give rise to their unique phenotypes will lead to better understanding of subterranean ecophysiology and biology of aging. Comparative genomics could be a useful tool in this regard. Since the publication of a naked mole-rat genome assembly in 2011, analyses of genomic and transcriptomic data have enabled a clearer understanding of mole-rat evolutionary history and suggested molecular pathways (e.g., NRF2-signaling activation and DNA damage repair mechanisms) that may explain the extraordinarily longevity and unique health traits of this species. However, careful scrutiny and re-analysis suggest that some identified features result from incorrect or imprecise annotation and assembly of the naked mole-rat genome: in addition, some of these conclusions (e.g., genes involved in cancer resistance and hairlessness) are rejected when the analysis includes additional, more closely related species. We describe how the combination of better study design, improved genomic sequencing techniques, and new bioinformatic and data analytical tools will improve comparative genomics and ultimately bridge the gap between traditional model and nonmodel organisms.

Enhanced Antitumor Activity of an Anti-5T4 Antibody-Drug Conjugate in Combination with PI3K/mTOR inhibitors or Taxanes

PURPOSE

Targeted treatment of solid or liquid tumors with antibody-drug conjugates (ADCs) can lead to promising clinical benefit. The aim of the study is to investigate combination regimens of auristatin-based ADCs in preclinical models of cancer.

EXPERIMENTAL DESIGN

An auristatin-based anti-5T4 antibody conjugate (5T4-ADC) and auristatin payloads were combined with the dual PI3K/mTOR catalytic site inhibitor PF-05212384 (PF-384) or taxanes in a panel of tumor cell lines. Drug interactions in vitro were evaluated using cell viability assays, apoptosis induction, immunofluorescence, mitotic index, and immunoblotting. Breast cancer cells treated with auristatin analogue or 5T4-ADC were profiled by total- and phospho-proteomics. Antitumor efficacy of selected combinations was evaluated in 5T4-positive human breast or lung tumor xenografts in vivo.

RESULTS

In vitro, auristatin-based agents displayed strong synergistic or additive activity when combined with PF-384 or taxanes, respectively. Further, treatment of 5T4-ADC plus PF-384 resulted in stronger induction of apoptosis and cell line-specific attenuation of pAKT and pGSK. Interestingly, proteomic analysis revealed unique effects of auristatins on multiple components of mRNA translation. Addition of PF-384 further amplified effects of 5T4-ADC on translational components, providing a potential mechanism of synergy between these drugs. In human tumor xenografts, dual targeting with 5T4-ADC/PF-384 or 5T4-ADC/paclitaxel produced substantially greater antitumor effects with longer average survival as compared with monotherapy treatments.

CONCLUSIONS

Our results provide a biologic rationale for combining 5T4-ADC with either PI3K/mTOR pathway inhibitors or taxanes and suggest that mechanisms underlying the synergy may be attributed to cellular effects of the auristatin payload.

Abstract 2463: Enhanced anti-tumor activity of an Auristatin-based antibody-drug conjugate in combination with PI3K/mTOR inhibitors or taxanes: Translational implications and mechanistic insights

Targeted treatment with antibody-drug conjugates (ADCs) can lead to dramatic regressions of solid tumors; combination therapies with the ADCs that could potentially help achieve long-term disease control remain largely unexplored. The aim of the study is to investigate most promising combination regimens of auristatin-based conjugates in preclinical models of cancer.

A tool ADC, an auristatin-based anti-5T4 antibody conjugate (5T4-ADC) and permeable auristatin analogs were combined with dual PI3K/mTOR catalytic site inhibitor PF-05212384 (PF-384) or taxanes in a panel of common cancer cell lines of breast, lung or ovarian origin. Drug combinations were tested for their effects in vitro on cell viability, apoptosis, cell cycle or modulation of PI3K/mTOR pathway markers. Anti-tumor efficacy of selected combinations was also evaluated in a 5T4-positive human breast or lung tumor xenografts in vivo.

Remarkably, ADC and auristatin analogs resulted in synergistic or additive effects on cell cytotoxicity when combined with PF-384 or with taxanes in vitro. ADC/PF-384, auristatin/PF-384 and ADC/Paclitaxel (PTX), auristatin/PTX combinations showed enhanced induction of apoptosis and selective attenuation of the downstream phospho-markers of the PI3K/mTOR pathway. Quantitative proteomic analysis of cells treated with auristatin-based agents and PF-384 alone or in combination revealed novel and unique effects on key components of mRNA translation, including translation initiation or elongation factors. In human lung or breast cancer xenograft models, dual targeting with 5T4-ADC/PF-384 or 5T4-ADC/PTX produced substantially greater antitumor effects with longer average survival as compared to monotherapy treatments.

Our results provide strong rationale for combining 5T4-ADC with PI3K/mTOR pathway inhibitors or taxanes. New biological insights into molecular mechanisms underlying synergistic effects of ADC - drug combinations suggest/reveal that synergies are mediated by payload's mode of action. These findings can be applicable to several ADCs employing microtubule inhibitors that are undergoing clinical evaluation.

Citation Format: Puja Sapra, Boris Shor, Maureen Dougher, Jennifer Kahler, Michelle Mack, Jane Xu, Shuyan Lu, Eugene Melamud, Fang Wang, Edward Rosfjord. Enhanced anti-tumor activity of an Auristatin-based antibody-drug conjugate in combination with PI3K/mTOR inhibitors or taxanes: Translational implications and mechanistic insights. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2463. doi:10.1158/1538-7445.AM2015-2463

Tumor cells chronically treated with a trastuzumab-maytansinoid antibody-drug conjugate develop varied resistance mechanisms but respond to alternate treatments

Antibody-drug conjugates (ADC) are emerging as clinically effective therapy. We hypothesized that cancers treated with ADCs would acquire resistance mechanisms unique to immunoconjugate therapy and that changing ADC components may overcome resistance. Breast cancer cell lines were exposed to multiple cycles of anti-Her2 trastuzumab-maytansinoid ADC (TM-ADC) at IC80 concentrations followed by recovery. The resistant cells, 361-TM and JIMT1-TM, were characterized by cytotoxicity, proteomic, transcriptional, and other profiling. Approximately 250-fold resistance to TM-ADC developed in 361-TM cells, and cross-resistance was observed to other non-cleavable-linked ADCs. Strikingly, these 361-TM cells retained sensitivity to ADCs containing cleavable mcValCitPABC-linked auristatins. In JIMT1-TM cells, 16-fold resistance to TM-ADC developed, with cross-resistance to other trastuzumab-ADCs. Both 361-TM and JIMT1-TM cells showed minimal resistance to unconjugated mertansine (DM1) and other chemotherapeutics. Proteomics and immunoblots detected increased ABCC1 (MRP1) drug efflux protein in 361-TM cells, and decreased Her2 (ErbB2) in JIMT1-TM cells. Proteomics also showed alterations in various pathways upon chronic exposure to the drug in both cell models. Tumors derived from 361-TM cells grew in mice and were refractory to TM-ADC compared with parental cells. Hence, acquired resistance to trastuzumab-maytansinoid ADC was generated in cultured cancer cells by chronic drug treatment, and either increased ABCC1 protein or reduced Her2 antigen were primary mediators of resistance. These ADC-resistant cell models retain sensitivity to other ADCs or standard-of-care chemotherapeutics, suggesting that alternate therapies may overcome acquired ADC resistance. Mol Cancer Ther; 14(4); 952-63. ©2015 AACR.

EpiFire: An open source C++ library and application for contact network epidemiology

BACKGROUND

Contact network models have become increasingly common in epidemiology, but we lack a flexible programming framework for the generation and analysis of epidemiological contact networks and for the simulation of disease transmission through such networks.

RESULTS

Here we present EpiFire, an applications programming interface and graphical user interface implemented in C++, which includes a fast and efficient library for generating, analyzing and manipulating networks. Network-based percolation and chain-binomial simulations of susceptible-infected-recovered disease transmission, as well as traditional non-network mass-action simulations, can be performed using EpiFire.

CONCLUSIONS

EpiFire provides an open-source programming interface for the rapid development of network models with a focus in contact network epidemiology. EpiFire also provides a point-and-click interface for generating networks, conducting epidemic simulations, and creating figures. This interface is particularly useful as a pedagogical tool.

LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

Metabolomic analysis and visualization engine for LC-MS data

Metabolomic analysis by liquid chromatography-high-resolution mass spectrometry results in data sets with thousands of features arising from metabolites, fragments, isotopes, and adducts. Here we describe a software package, Metabolomic Analysis and Visualization ENgine (MAVEN), designed for efficient interactive analysis of LC-MS data, including in the presence of isotope labeling. The software contains tools for all aspects of the data analysis process, from feature extraction to pathway-based graphical data display. To facilitate data validation, a machine learning algorithm automatically assesses peak quality. Users interact with raw data primarily in the form of extracted ion chromatograms, which are displayed with overlaid circles indicating peak quality, and bar graphs of peak intensities for both unlabeled and isotope-labeled metabolite forms. Click-based navigation leads to additional information, such as raw data for specific isotopic forms or for metabolites changing significantly between conditions. Fast data processing algorithms result in nearly delay-free browsing. Drop-down menus provide tools for the overlay of data onto pathway maps. These tools enable animating series of pathway graphs, e.g., to show propagation of labeled forms through a metabolic network. MAVEN is released under an open source license at http://maven.princeton.edu.

Metabolomic analysis via reversed-phase ion-pairing liquid chromatography coupled to a stand alone orbitrap mass spectrometer

We present a liquid chromatography-mass spectrometry (LC-MS) method that capitalizes on the mass-resolving power of the orbitrap to enable sensitive and specific measurement of known and unanticipated metabolites in parallel, with a focus on water-soluble species involved in core metabolism. The reversed phase LC method, with a cycle time 25 min, involves a water-methanol gradient on a C18 column with tributylamine as the ion pairing agent. The MS portion involves full scans from 85 to 1000 m/z at 1 Hz and 100,000 resolution in negative ion mode on a stand alone orbitrap ("Exactive"). The median limit of detection, across 80 metabolite standards, was 5 ng/mL with the linear range typically >or=100-fold. For both standards and a cellular extract from Saccharomyces cerevisiae (Baker's yeast), the median inter-run relative standard deviation in peak intensity was 8%. In yeast exact, we detected 137 known compounds, whose (13)C-labeling patterns could also be tracked to probe metabolic flux. In yeast engineered to lack a gene of unknown function (YKL215C), we observed accumulation of an ion of m/z 128.0351, which we subsequently confirmed to be oxoproline, resulting in annotation of YKL215C as an oxoprolinase. These examples demonstrate the suitability of the present method for quantitative metabolomics, fluxomics, and discovery metabolite profiling.

Mass spectrometry-based metabolomics of yeast

Driven by the advent of metabolomics, recent years have seen renewed interest in the investigation of yeast metabolism. Here we provide a practical guide to metabolomic analysis of yeast using liquid chromatography-mass spectrometry (LC-MS). We begin with background on LC-MS and its utility in studying yeast metabolism. We then describe key issues involved at each step of a typical yeast metabolomics experiment: in experimental design, cell culture, metabolite extraction, LC-MS, and data processing and analysis. Throughout, we highlight interdependencies between the steps that are relevant to developing an integrated workflow which effectively leverages LC-MS to reveal yeast biology.

Stochastic noise in splicing machinery

The number of known alternative human isoforms has been increasing steadily with the amount of available transcription data. To date, over 100 000 isoforms have been detected in EST libraries, and at least 75% of human genes have at least one alternative isoform. In this paper, we propose that most alternative splicing events are the result of noise in the splicing process. We show that the number of isoforms and their abundance can be predicted by a simple stochastic noise model that takes into account two factors: the number of introns in a gene and the expression level of a gene. The results strongly support the hypothesis that most alternative splicing is a consequence of stochastic noise in the splicing machinery, and has no functional significance. The results are also consistent with error rates tuned to ensure that an adequate level of functional product is produced and to reduce the toxic effect of accumulation of misfolding proteins. Based on simulation of sampling of virtual cDNA libraries, we estimate that error rates range from 1 to 10% depending on the number of introns and the expression level of a gene.

Structural implication of splicing stochastics

Even though nearly every human gene has at least one alternative splice form, very little is so far known about the structure and function of resulting protein products. It is becoming increasingly clear that a significant fraction of all isoforms are products of noisy selection of splice sites and thus contribute little to actual functional diversity, and may potentially be deleterious. In this study, we examine the impact of alternative splicing on protein sequence and structure in three datasets: alternative splicing events conserved across multiple species, alternative splicing events in genes that are strongly linked to disease and all observed alternative splicing events. We find that the vast majority of all alternative isoforms result in unstable protein conformations. In contrast to that, the small subset of isoforms conserved across species tends to maintain protein structural integrity to a greater extent. Alternative splicing in disease-associated genes produces unstable structures just as frequently as all other genes, indicating that selection to reduce the effects of alternative splicing on this set is not especially pronounced. Overall, the properties of alternative spliced proteins are consistent with the outcome of noisy selection of splice sites by splicing machinery.

Coupling of DNA binding and helicase activity is mediated by a conserved loop in the MCM protein

Minichromosome maintenance (MCM) helicases are the presumptive replicative helicases, thought to separate the two strands of chromosomal DNA during replication. In archaea, the catalytic activity resides within the C-terminal region of the MCM protein. In Methanothermobacter thermautotrophicus the N-terminal portion of the protein was shown to be involved in protein multimerization and binding to single and double stranded DNA. MCM homologues from many archaeal species have highly conserved predicted amino acid similarity in a loop located between β7 and β8 in the N-terminal part of the molecule. This high degree of conservation suggests a functional role for the loop. Mutational analysis and biochemical characterization of the conserved residues suggest that the loop participates in communication between the N-terminal portion of the helicase and the C-terminal catalytic domain. Since similar residues are also conserved in the eukaryotic MCM proteins, the data presented here suggest a similar coupling between the N-terminal and catalytic domain of the eukaryotic enzyme.

Characterization, kinetics, and crystal structures of fructose-1,6-bisphosphate aldolase from the human parasite, Giardia lamblia

Class I and class II fructose-1,6-bisphosphate aldolases (FBPA), glycolytic pathway enzymes, exhibit no amino acid sequence homology and utilize two different catalytic mechanisms. The mammalian class I FBPA employs a Schiff base mechanism, whereas the human parasitic protozoan Giardia lamblia class II FBPA is a zinc-dependent enzyme. In this study, we have explored the potential exploitation of the Giardia FBPA as a drug target. First, synthesis of FBPA was demonstrated in Giardia trophozoites by using an antibody-based fluorescence assay. Second, inhibition of FBPA gene transcription in Giardia trophozoites suggested that the enzyme is necessary for the survival of the organism under optimal laboratory growth conditions. Third, two crystal structures of FBPA in complex with the transition state analog phosphoglycolohydroxamate (PGH) show that the enzyme is homodimeric and that its active site contains a zinc ion. In one crystal form, each subunit contains PGH, which is coordinated to the zinc ion through the hydroxamic acid hydroxyl and carbonyl oxygen atoms. The second crystal form contains PGH only in one subunit and the active site of the second subunit is unoccupied. Inspection of the two states of the enzyme revealed that it undergoes a conformational transition upon ligand binding. The enzyme cleaves d-fructose-1,6-bisphosphate but not d-tagatose-1,6-bisphosphate, which is a tight binding competitive inhibitor. The essential role of the active site residue Asp-83 in catalysis was demonstrated by amino acid replacement. Determinants of catalysis and substrate recognition, derived from comparison of the G. lamblia FBPA structure with Escherichia coli FBPA and with a closely related enzyme, E. coli tagatose-1,6-bisphosphate aldolase (TBPA), are described.

SNPs3D: candidate gene and SNP selection for association studies

Background

The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and database that provides and integrates as much information as possible on disease/gene relationships at the molecular level.

Description

The resource has three primary modules. One module identifies which genes are candidates for involvement in a specified disease. A second module provides information about the relationships between sets of candidate genes. The third module analyzes the likely impact of non-synonymous SNPs on protein function. Disease/candidate gene relationships and gene-gene relationships are derived from the literature using simple but effective text profiling. SNP/protein function relationships are derived by two methods, one using principles of protein structure and stability, the other based on sequence conservation. Entries for each gene include a number of links to other data, such as expression profiles, pathway context, mouse knockout information and papers. Gene-gene interactions are presented in an interactive graphical interface, providing rapid access to the underlying information, as well as convenient navigation through the network. Use of the resource is illustrated with aspects of the inflammatory response and hypertension.

Conclusion

The combination of SNP impact analysis, a knowledge based network of gene relationships and candidate genes, and access to a wide range of data and literature allow a user to quickly assimilate available information, and so develop models of gene-pathway-disease interaction.

The psychrophilic lifestyle as revealed by the genome sequence of Colwellia psychrerythraea 34H through genomic and proteomic analyses

The completion of the 5,373,180-bp genome sequence of the marine psychrophilic bacterium Colwellia psychrerythraea 34H, a model for the study of life in permanently cold environments, reveals capabilities important to carbon and nutrient cycling, bioremediation, production of secondary metabolites, and cold-adapted enzymes. From a genomic perspective, cold adaptation is suggested in several broad categories involving changes to the cell membrane fluidity, uptake and synthesis of compounds conferring cryotolerance, and strategies to overcome temperature-dependent barriers to carbon uptake. Modeling of three-dimensional protein homology from bacteria representing a range of optimal growth temperatures suggests changes to proteome composition that may enhance enzyme effectiveness at low temperatures. Comparative genome analyses suggest that the psychrophilic lifestyle is most likely conferred not by a unique set of genes but by a collection of synergistic changes in overall genome content and amino acid composition.

Crystal Structures of 2-Methylisocitrate Lyase in Complex with Product and with Isocitrate Inhibitor Provide Insight into Lyase Substrate Specificity, Catalysis and Evolution,

Two crystal structures of the C123S mutant of 2-methylisocitrate lyase have been determined, one with the bound reaction products, Mg(2+)-pyruvate and succinate, and the second with a bound Mg(2+)-(2R,3S)-isocitrate inhibitor. Comparison with the structure of the wild-type enzyme in the unbound state reveals that the enzyme undergoes a conformational transition that sequesters the ligand from solvent, as previously observed for two other enzyme superfamily members, isocitrate lyase and phosphoenolpyruvate mutase. The binding modes reveal the determinants of substrate specificity and stereoselectivity, and the stringent specificity is verified in solution using various potential substrates. A model of bound 2-methylisocitrate has been developed based on the experimentally determined structures. We propose a catalytic mechanism involving an alpha-carboxy-carbanion intermediate/transition state, which is consistent with previous stereochemical experiments showing inversion of configuration at the C(3) of 2-methylisocitrate. Structure-based sequence analysis and phylogenic tree construction reveal determinants of substrate specificity, highlight nodes of divergence of families, and predict enzyme families with new functions.

Biochemical Characterization of the Methanothermobacter thermautotrophicus Minichromosome Maintenance (MCM) Helicase N-terminal Domains

Minichromosome maintenance helicases are ring-shaped complexes that play an essential role in archaeal and eukaryal DNA replication by separating the two strands of chromosomal DNA to provide the single-stranded substrate for the replicative polymerases. For the archaeal protein it was shown that the N-terminal portion of the protein, which is composed of domains A, B, and C, is involved in multimer formation and single-stranded DNA binding and may also play a role in regulating the helicase activity. Here, a detailed biochemical characterization of the N-terminal region of the Methanothermobacter thermautotrophicus minichromosome maintenance helicase is described. Using biochemical and biophysical analyses it is shown that domain C of the N-terminal portion, located adjacent to the helicase catalytic domains, is required for protein multimerization and that domain B is the main contact region with single-stranded DNA. It is also shown that although oligomerization is not essential for single-stranded DNA binding and ATPase activity, the presence of domain C is essential for helicase activity.

Evaluation of disorder predictions in CASP5

This paper reports an analysis of the accuracy of predictions of structural disorder received as part of the CASP5 experiment. Six groups made predictions of disorder. The predictions of the four most active groups have been compared with the experimental results, in terms of the sensitivity and specificity of the methods. All four methods succeed in detecting over half the disordered residues in the targets, with a generally low rate of over-prediction. Two of the methods perform significantly better when the structure of a related protein is available. There is a trade-off between the fraction of disordered residues detected and the extent of over-prediction, and groups have adopted different compromises in this respect. Comparison of performance at the same over-prediction rates highlights the role of related structures in some methods rather than others, with different groups achieving the highest sensitivity for different target sets. Over-all, the methods are clearly of considerable use in identifying potential disorder.

The HI0073/HI0074 protein pair from Haemophilus influenzae is a member of a new nucleotidyltransferase family: structure, sequence analyses, and solution studies

The crystal structure of HI0074 from Haemophilus influenzae, a protein of unknown function, has been determined at a resolution of 2.4 A. The molecules form an up-down, four-helix bundle, and associate into homodimers. The fold is most closely related to the substrate-binding domain of KNTase, yet the amino acid sequences of the two proteins exhibit no significant homology. Sequence analyses of completely and incompletely sequenced genomes reveal that the two adjacent genes, HI0074 and HI0073, and their close relatives comprise a new family of nucleotidyltransferases, with 15 members at the time of writing. The analyses also indicate that this is one of eight families of a large nucleotidyltransferase superfamily, whose members were identified based on the proximity of the nucleotide- and substrate-binding domains on the respective genomes. Both HI0073 and HI0074 were annotated "hypothetical" in the original genome sequencing publication. HI0073 was cloned, expressed, and purified, and was shown to form a complex with HI0074 by polyacrylamide gel electrophoresis under nondenaturing conditions, analytic size exclusion chromatography, and dynamic light scattering. Double- and single-stranded DNA binding assays showed no evidence of DNA binding to HI0074 or to HI0073/HI0074 complex despite the suggestive shape of the putative binding cleft formed by the HI0074 dimer.

Assisting functional assignment for hypothetical Heamophilus influenzae gene products through structural genomics

The three-dimensional structures of Haemophilus influenzae proteins whose biological functions are unknown are being determined as part of a structural genomics project to ask whether structural information can assist in assigning the functions of proteins. The structures of the hypothetical proteins are being used to guide further studies and narrow the field of such studies for ultimately determining protein function. An outline of the structural genomics methodological approach is provided along with summaries of a number of completed and in progress crystallographic and NMR structure determinations. With more than twenty-five structures determined at this point and with many more in various stages of completion, the results are encouraging in that some level of functional understanding can be deduced from experimentally solved structures. In addition to aiding in functional assignment, this effort is identifying a number of possible new targets for drug development.

Completeness in structural genomics

Structural genomics has the goal of obtaining useful, three-dimensional models of all proteins by a combination of experimental structure determination and comparative model building. We evaluate different strategies for optimizing information return on effort. The strategy that maximizes structural coverage requires about seven times fewer structure determinations compared with the strategy in which targets are selected at random. With a choice of reasonable model quality and the goal of 90% coverage, we extrapolate the estimate of the total effort of structural genomics. It would take approximately 16,000 carefully selected structure determinations to construct useful atomic models for the vast majority of all proteins. In practice, unless there is global coordination of target selection, the total effort will likely increase by a factor of three. The task can be accomplished within a decade provided that selection of targets is highly coordinated and significant funding is available.

From fold to function

A number of recent advances have been made in deriving function information from protein structure. A fold relationship to an already characterized protein will often allow general information about function to be deduced. More detailed information can be obtained using sequence relationships to already studied proteins. Methods of deducing function directly from structure, without the use of evolutionary relationships, are developing rapidly. All such methods may be used with models of protein structure, rather than with experimentally determined ones, but model accuracy imposes limitations. The rapid expansion of the structural genomics field has created a new urgency for improved methods of structure-based annotation of function.

[Follicular splenic lymphoid hyperplasia associated with EBV infection]

Massive splenomegaly is defined as a spleen weighing about 10 times normal weight. We describe a 36-year-old man who had huge splenomegaly and secondary pancytopenia simulating malignant lymphoma for about 3 months. Splenectomy was necessary because of the suspicion of hematologic malignancy, especially isolated lymphoma of the spleen, and pain and mechanical abdominal disturbances. On operation, the spleen was 25 cm long and weighted 250 g. There was florid, reactive follicular lymphoid hyperplasia. Immunohistochemical staining with CD-20(L26), CD-45Ro(UCHL), bcl-2 oncoprotein (Dakopatts), EBV (anti-EBV mol weight 60 KD, Dakopatts) was consistent with reaction to EBV infection and not with follicular lymphoma. Lack of PCR amplification using DNA extracted from paraffin-embedded splenic tissue indicated absence of a monoclonal B cell population carrying rearranged immunoglobulin genes. The lymphocytic population was proven polyclonal by the negative results of PCR for the bcl-2 gene rearrangement. EBV seroconversion from high titer antibodies of anti-EBV-VCA-IgM to negative, and from negative EBNA to positive was consistent with an apparent primary EBV infection. We have not found on computerized search a previous report of reactive follicular splenic hyperplasia to EBV infection causing huge splenomegaly, with or without EBV-induced infectious mononucleosis.

Ectopic medullary hematopoiesis as a cause of ascites in agnogenic myeloid metaplasia. Case report and review of the literature

We report an unusual case of a 44-year-old female patient with 'malignant' ascites caused by ectopic foci of extramedullary hematopoiesis in the course of agnogenic myeloid metaplasia. The patient had suffered also from severe Coombs-positive acquired hemolytic anemia and had been splenectomized. Two years after splenectomy, ascites caused by peritoneal implants of hematopoietic tissue appeared. The ascites responded promptly to treatment with busulfan and hydroxyurea. The clinical picture, treatment and a review of the literature concerning the mechanisms of this uncommon evolution are discussed.

Peripartum cardiomyopathy

A 26-year-old woman developed severe postpartum cardiomyopathy in early puerperium. Ligation of the inferior vena cava prevented recurrent pulmonary embolism but did not affect her hemodynamic condition, which deteriorated constantly. During continuous hemodynamic monitoring only vigorous volume replacement with an increase of the left ventricular filling pressure to 32 mm Hg improved cardiac output significantly. The presence of a high titer of antiactin antibodies 9 months after the delivery supports the theory that the peripartum cardiomyopathy was of autoimmune etiology.

Arrangement and conformations of substrates at the active site of pyruvate kinase from model building studies based on magnetic resonance data

Seventeen distances from two paramagnetic reference points, as determined by nuclear relaxation studies of six active complexes of rabbit muscle pyruvate kinase, have been used to construct molecular models of two composite enzyme complexes. In the model of the hypothetical pyruvate kinase-M(I)-M(II)-ATP-Cr(III)-P-enolpyruvate complex, overlap of the transferred phosphoryl groups of the two substrates, which is required to explain the observed competition, is incomplete, allowing greater than or equal to 1 A for the transition state to form. In the active enzyme-M(I)-M(II)-ATP-Cr(III)-pyruvate complex, the gamma-phosphoryl phosphorus of ATP is in molecular contact (3.0 +/- 0.5 A) with the carbonyl oxygen of pyruvate, consistent with direct phosphoryl transfer, indicating no need for intermediate phosphorylation of the enzyme. The enzyme-bound divalent cation, which forms second sphere complexes with the phosphoryl groups of P-enolpyruvate and ATP, may activate the transferred phosphoryl group indirectly, through a water ligand. By analogy with the position of Cr(III), a second divalent cation may participate more directly by coordination of the triphosphate chain of ATP.

Magnetic resonance studies of the interaction of Co2+ and phosphoenolpyruvate with pyruvate kinase

Co2+, which activates rabbit muscle pyruvate kinase, competes with Mn2+ for the active site of the enzyme with a KD of 46 muM. Co2+ binds to phosphoenolpyruvate with a KD of 4.1 mM. The structures of the binary Co2+/P-enolpyruvate, and quaternary pyruvate kinase/Co2+/K+/P-enolpyruvate complexes were studied using EPR and the effects of Co2+ on the longitudinal (T1) and transverse (T2) relaxation times of the protons of water and P-enolpyruvate and the phosphorus of P-enolpyruvate. The EPR spectra of all complexes at 6 K, disappear above 40 K and reveal principal g values between 2 and 7 indicating high spin Co2+. For free Co2+ and for the binary Co2+/P-enolpyruvate complex, the T1 of water protons was independent of frequency in the range 8, 15, 24.3, 100, and 220 MHz. Assuming coordination numbers (q) of 6 and 5 for free Co2+ and Co2+/P-enolpyruvate, respectively, correlation times (tauc) of 1.3 times 10(-13) and 1.7 times 10(-13) s, were calculated. The distances from Co2+ and phosphorus and to the cis and trans protons in the binary Co2+/P-enolpyruvate complex calculated from their T1 values were 2.7 A, 4.1 A, AND 5.3 A, respectively, indicating an inner sphere phosphoryl complex. Consistent with direct phosphoryl coordination, a large Co2+ to phosphorus hyperfine contact coupling constant (A/h) of 5 times 10(5) Hz was determined by the frequency dependence of the T2 of phosphorus at 25.1, 40.5, and 101.5 MHz. For both enzyme complexes, the dipolar correlation time tauc was 2 times 10(-12) s and the number of rapidly exchanging water ligands (q) was 0.6 as determined from the frequency dependence of the T1 of water protons. In the quaternary enzyme/Co2+/K+/P-enolyruvate complex this tauc value was consistent with the frequency dependence of the T1 of the phosphorus of enzyme-bound P-enolpyruvate at 25.1 and 40.5 MHz. Distances from enzyme-bound C02+ to the phosphorus and protons of P-enolpyruvate, from their T1 values, were 5.0 A and 8 to 10 A, respectively, indicating a predominantly (greater than or equal to 98%) second spere complex and less than 2% inner sphere complex. Consistent with a second sphere complex on the enzyme, an A/h value of less than 10(3) Hz was determined from the frequency dependence of the T2 of phosphorus. In all complexes the exchange reates were found to be faster than the paramagnetic relaxation rates and the hyperfine contact interaction was found to be small compared to the dipolar interaction. The results thus indicate that the interaction of C02+ with P-enolpyruvate is greatly decreased upon binding to the active site of pyruvate kinase.