Besides environmental factors, plant growth depends upon endogenous signals. Bill Gray examines what these hormonal signals are and how they act to regulate many aspects of growth and development. Plant growth and development involves the integration of many environmental and endogenous signals that, together with the intrinsic genetic program, determine plant form. Fundamental to this process are several growth regulators collectively called the plant hormones or phytohormones. This group includes auxin, cytokinin, the gibberellins (GAs), abscisic acid (ABA), ethylene, the brassinosteroids (BRs), and jasmonic acid (JA), each of which acts at low concentrations to regulate many aspects of plant growth and development.With the notable exception of the steroidal hormones of the BR group, plant hormones bear little resemblance to their animal counterparts . Rather,Virtually every aspect of plant growth and development is under hormonal control to some degree. A single hormone can regulate an amazingly diverse array of cellular and developmental processes, while at the same time multiple hormones often influence a single process. Well-studied examples include the promotion of fruit ripening by ethylene, regulation of the cell cycle by auxin and cytokinin, induction of seed germination and stem elongation by GA, and the maintenance of seed dormancy by ABA. Historically, the effects of each hormone have been defined largely by the application of exogenous hormone. More recently, the isolation of hormone biosynthetic and response mutants has provided powerful new tools for painting a clearer picture of the roles of the various phytohormones in plant growth and development.Plant biologists have been fascinated by the regulatory capacity of phytohormones since the time of their discovery, and the notion that hormone levels or responses could be manipulated to improve desired plant traits has long been an area of intense interest. Perhaps the best-known example of this is the isolation of dwarf varieties of wheat and rice that led to the “green revolution” in the second half of the 20th century, which is credited with saving millions of people around the globe from starvation. These dwarf varieties have shorter stems than wild-type, making these plants less susceptible to damage by wind and rain. The molecular isolation of these “dwarfing genes” has revealed that they encode components of the GA biosynthesis and response pathways .Arabidopsis thaliana to isolate mutations that confer altered response to applied hormone. Molecular and biochemical analysis of the gene products defined by these mutations, coupled with expression studies aimed at identifying the downstream target genes that mediate hormonal changes in growth and development, has begun to unlock some of the mysteries behind phytohormone action. While no hormone transduction pathway is completely understood, we now have a rudimentary understanding of many of the molecular events underlying hormone action. Several reviews covering the individual hormone pathways in greater detail have recently been published  domain . Ligand ETR1, suggests that HK activity is not required for ethylene response. Mutations that abolish ethylene binding in any of the five receptor genes are dominant and confer ethylene insensitivity, indicating that the receptors function as negative regulators of the ethylene pathway.Ethylene is perceived by a family of five receptors. ETR1 and ERS1 contain a consensus HK domain, however, the HK domains of ETR2, ERS2, and EIN4 are degenerate and lack elements necessary for catalytic activity. This fact, together with studies of “kinase-dead” mutants of Genetic and molecular studies have positioned these receptors upstream of the Raf-like MAP kinase kinase kinase, CTR1, which interacts with the receptors and also acts as a negative regulator . The intLong ago, plant physiologists noted the apparent antagonistic interactions between some of the phytohormones, such as between auxin and cytokinin in the regulation of root–shoot differentiation and between GA and ABA in germination. Other processes are synergistically regulated by multiple hormones. While it has long been obvious that hormones do not function in discrete pathways, but rather exhibit extensive cross-talk and signal integration with each other and with environmental and developmental signaling pathways, the molecular basis for such coordinated regulation has been unclear. Several recent findings have begun to elucidate the molecular details of some of these events.ERF1 expression, and treatment with both hormones synergistically activates ERF1. Induction of ERF1 by both hormones alone or in combination is dependent upon both signaling pathways, and constitutive overexpression of ERF1 rescues the defense-response defects of both ethylene- and JA-insensitive mutants. These findings suggest that ERF1 represents one of the first signaling nodes identified in the complex web of hormonal cross-talk.One example of such signal integration was recently described for the ethylene and JA pathways . GeneticThe auxin and BR pathways also appear to converge and mutually regulate some developmental processes. Both hormones promote cell expansion, and microarray studies have revealed that as many as 40% of all BR-induced genes are also up-regulated by auxin . BR is pArabidopsis hypocotyl (embryonic stem) elongation in a synergistic and interdependent fashion. Elevating endogenous auxin levels rendered plants more sensitive to BR application in hypocotyl elongation assays, and this response was dependent upon both the auxin and BR signaling pathways. Genetic studies suggest that the convergence of these two pathways occurs at a late point in hormone signaling, perhaps at the promoters of the many genes responsive to both hormones. In support of this notion, bioinformatic analysis identified distinct sequence elements that were enriched specifically in the promoters of auxin-induced, BR-induced, and auxin/BR-induced genes.Using combined genetic, physiological, and genomic approaches, While great strides have been made in recent years in understanding the molecular basis of phytohormone action, many fundamental questions remain. Receptors and other upstream signaling components remain to be identified for the majority of the phytohormones. Equally important are the elucidation of hormonal networks and the integration of these networks with the morphogenetic program, such that our understanding of hormone action can be placed in a developmental context.


In establishing structure-function relationships for membrane transport proteins, the interpretation of phenotypic changes can be problematic, owing to uncertainties in protein expression levels, sub-cellular localization, and protein-folding fidelity. A dual-label competitive transport assay called "Transport Specificity Ratio" (TSR) analysis has been developed that is simple to perform, and circumvents the "expression problem," providing a reliable TSR phenotype (a constant) for comparison to other transporters.Escherichia coli GABA (4-aminobutyrate) permease (GabP) as a model carrier, it is demonstrated that the TSR phenotype is largely independent of assay conditions, exhibiting: (i) indifference to the particular substrate concentrations used, (ii) indifference to extreme changes (40-fold) in transporter expression level, and within broad limits (iii) indifference to assay duration. The theoretical underpinnings of TSR analysis predict all of the above observations, supporting that TSR has (i) applicability in the analysis of membrane transport, and (ii) particular utility in the face of incomplete information on protein expression levels and initial reaction rate intervals (e.g., in high-throughput screening situations). The TSR was used to identify gab permease (GabP) variants that exhibit relative changes in catalytic specificity (kcat/Km) for [14C]GABA (4-aminobutyrate) versus [3H]NA (nipecotic acid).Using the constant that reflects innate molecular properties of the transition state, and provides a reliable index of the difference in catalytic specificity that a carrier exhibits toward a particular pair of substrates. A change in the TSR phenotype, called a Δ(TSR), represents a specificity shift attributable to underlying changes in the intrinsic substrate binding energy (ΔGb) that translocation catalysts rely upon to decrease activation energy . TSR analysis is therefore a structure-function tool that enables parsimonious scanning for positions in the protein fold that couple to the transition state, creating stability and thereby serving as functional determinants of catalytic power (efficiency, or specificity).The TSR phenotype is an easily measured  However, without a productive conspiracy among catalysis-promoting residues in the protein fold, transport proteins would be non-catalytic (i.e., unable to enhance transition state stability). Inasmuch as "... catalytic power will always appear as a result of increased transition state stabilization (lower free energy) ..." [Structure-function analysis seeks to elucidate how the structural attributes of a protein serve its function. The function of a carrier protein is to gy) ..." , a powerThe structure-function technique would be required to provide a keyhole through which to view positions in the protein at which structural perturbations affect transition state binding energy, for it is well-appreciated that a catalyst creates transition state stability by binding substrates tightly in the transition state complex . In factEscherichia coli GabP (gab permease) as a model carrier protein, salient properties and utilitarian features of TSR analysis are demonstrated. The TSR parameter is shown (i) to be calculated from an easily performed dual-label uptake experiment, and (ii) to depend exclusively upon changes in intrinsic substrate binding energy (ΔGb) realized in the transition state. Together these TSR properties should enable transport structure-functionists to obtain rapid, yet incisive, first-pass view of positions in the protein fold where structure influences transition state stability and catalysis per se.The present contribution demonstrates use of the Transport Specificity Ratio (TSR) as an analytical keyhole to capture an initial glimpse of positions in the protein fold where structural characteristics control the availability of transition state binding energy. Using the 14C]GABA and [3H]NA compete for uptake at the GabP active site. Therefore as a practical matter it is necessary to establish conditions under which an adequate signal may be obtained from both isotope channels. This can be accomplished empirically by mixing the labelled substrates in different proportions  the trading of [3H]NA for [14C]GABA is expected to substantially alter the fraction of active sites occupied by GABA versus NA Nevertheless, it is clear that the calculated TSR parameter is indifferent to the precise substrate concentration ratio. Moreover, at a fixed substrate ratio (7 parts NA to 3 parts GABA), the absolute substrate concentrations may also be varied over a wide range (here 17.5-fold) without affecting the calculated TSR parameter  indicate that there is great latitude in choosing substrate concentrations for TSR measurements, it is nevertheless pragmatic to select robust initial velocity conditions wherein the substrate concentration ratio is such that equal disintegration rates are seen in both isotope channels (broken line) when the control (e.g., wild type) transporter is studied. Variant transporters, exhibiting relative increases or decreases in specificity for the two substrates, will then be easily visualized as an inequality between the disintegration rates seen in the two isotope channels .lac-controlled expression of the plasmid-borne GabP gene. Growth in the presence of increasing IPTG concentrations caused the uptake of [3H]NA and [14C]GABA to increase in proportion to the GabP expression-level  phenotype – the TSR. Fundamental to TSR analysis is the notion that transport catalysts use substrate binding energy to lower the translocation energy barrier (activation energy) [) is lower than the non-catalyzed activation energy  by an amount equal to the intrinsic substrate binding energy, ΔGb .In order to initiate development of a structure-function relationship for translocation  by GabP ,6, it wate terms  so that  energy) . Equatiob) used to stabilize the transition state. one must find an easily measured signal that reports on changes in the intrinsic substrate binding energy (ΔGThat the Transport Specificity Ratio (TSR) analysis fulfills this requirement may be shown as follows.Importantly, Equation 1  of a simple translocation reaction, carried out from solution (C + S → Products), is governed by a second-order rate law (Equation 2), wherein the apparent second-order rate constant is k.The velocity (v = k[C][S]     (2)m), wherein the familiar Michaelis-Menten relationship (Equation 3) reduces to the form of a second-order rate law (Equation 4), and the apparent rate constant may be evaluated as k = kcat/Km (units M-1sec-1).Free carrier and substrate (C + S) are dominant under non-saturating, second-order conditions . The alternative Michaelis-Menten form turns out to be very useful for analysing the uptake of two labelled substrates that compete for transport at the same active site.E. coli GabP exposed simultaneously to arbitrary concentrations of its transported substrates [14C]GABA and [3H]NA. These competing substrates, present simultaneously in the same reaction vessel, will necessarily be in equilibrium with precisely the same concentration of free carrier (but unknown concentrations of carrier-substrate complexes), allowing algebraic elimination of [C] (Equation 5) when a ratio is taken between two instances of Equation 4 (one for each substrate).Consider the bstrates ,9, [14C]cat/Km) values has two consequences. First, since (kcat/Km) is formally a measure of catalytic specificity [Specificity Ratio (TSR) parameter.That Equation 5 contains the ratio of a pair of (kcificity ,10, we mcat/Km) is an apparent rate constant (see above), transition state theory holds that its value depends upon the height of the translocation energy barrier  as indicated by this logarithmic form of Eyring's Equation (Equation 7),Secondly, since (kk is the Boltzman constant, h is the Planck constant, R is the gas constant, T is the absolute temperature, and a transmission coefficient of unity is assumed.wherein cat/Km) depends upon , then by implication the TSR must be related to the intrinsic substrate binding energy – as becomes evident when Equations 1 and 7 are combined,If catalytic specificity  varies with the amount of transition state stabilization afforded by ΔGb, which is the intrinsic substrate binding energy . Taking the ratio between two instances of Equation 8 (e.g., for the two competing substrates, GABA and NA), and combining terms, we obtainEquation 8 shows that kEquation 9 indicates that an experimentally observed change in the TSR parameter would require a change in the underlying intrinsic substrate binding energies that determine the relative height of the translocation energy barriers for two substrates competing at the same active site.d and , which describe the equilibrium position of reactions leading to formation of free reactants from either the Michaelis complex (CS ↔ C + S) or the transition state complex (CS‡ ↔ C + S), respectively. Inasmuch as equilibrium constants (e.g., ) are always determined by Gibbs energy differences (e.g., ΔGb = -RT ln ), it follows  reflects a change in the midpoint separation  between hypothetical curves that describe binding of two test substrates (A and B) to the transition state. Structural features that affect the "tightness" of transition state binding will alter the translocation energy barrier height (Equation 1), which determines synonymously the catalytic power, efficiency, or specificity of a transporter.Figure a constant (Equation 9). Constants are intrinsically stable and reliable, reflecting fundamental reaction characteristics that survive changes in ambient conditions (provided temperature and pressure can be held constant). The unique stability and fundamental nature of the TSR phenotype will make it particularly valuable for first-pass analysis in high-throughput screening situations, wherein protein expression levels, duration of the initial rate time course, and degree of saturation by the chosen substrate concentration may be inconsistent across large numbers of transporter variants with differing functional characteristics. This reliability is demonstrated using the E. coli GABA permease (GabP) as a model translocation catalyst. Overall the present study makes clear that the dual-label TSR analysis is insulated remarkably well from many uncontrolled variables that can often compromise the validity of assays that use a single label.Unlike first-pass analytical methods that rely on the signal from one labelled substrate, the herein described dual-label analysis leads directly to the TSR parameter – 14C]GABA and [3H]NA in different proportions, or in fixed proportion over a broad concentration range . Thus, arbitrary carrier saturation levels are not expected to compromise TSR measurements. Since uncharacterized mutant collections may be expected to contain transporter variants with highly divergent Km values, the saturation-independence of TSR analysis should be of value in high-throughput screening situations where little kinetic information may be available to guide the choice of assay conditions. However, to be of general value the results obtained with GabP must extrapolate to other transporters.Figure nge Fig. . Indeed,) – between the free reactants (C + S) and the transition state (CS‡). This fundamental reality can also be appreciated from the perspective that under non-saturating conditions ([S] << Km), there are no complexes to consider , and thus even complicated mechanisms reduce to the simple case (Equation 4) in which the reaction proceeds directly from the free reactants in solution to the transition state (C + S → Products). Thus, the simple second-order reaction scheme, C + S → Products, will probably never be "too simple" for the purpose of performing the TSR analysis – even though complicated transport kinetics will feature many complexes that TSR analysis seems to ignore. In truth, the missing complexes are merely irrelevant (not ignored) to the value of  .Why the deceptively simple TSR analysis should have broad applicability can be understood from further consideration of Figure of  Fig.  since thIt is worth mentioning that TSR analysis has "fool-proof" qualities that derive from its inherent insensitivity to several sources of error that can seriously compromise transport measurements that rely upon a single labelled substrate. TSR calculations may be expected to "self-correct" any sources of error that have proportionally the same effect on the measurement of both isotopes – for such errors cannot affect the isotope ratio used to calculate the TSR parameter.Figure constant, should be of considerable practical significance for high-throughput screening operations wherein carrier expression levels could be both highly variable and impractical to document in real-time.In order to demonstrate the expression-independent nature of the TSR parameter, IPTG was used to simulate the wide range of expression levels (40-fold) that might be encountered in an uncharacterized collection of transporter variants. Whereas the single-isotope signals Fig.  are seentotal in the sense desired for meaningful kinetic characterization, which assumes (Equation 3) that Ctotal consists entirely of active molecules. The possibility of partial denaturation precludes assigning a molecular interpretation to shifts in either velocity or Vmax. In contrast, TSR analysis is unaffected by the presence of inactive molecules, and theoretically will always report reliably on the innate specificity properties of the active site per se – even if the measured signal emanates from a minor fraction of the carrier molecules visualized on an immunoblot.Since TSR phenotypes are expression-independent, structure-function information gleaned from a rapid first-pass screen will remain valid irrespective of results that might be obtained from a subsequent immunoblot analysis. Immunoblots do not in any event determine C14C] and [3H] initial rate segments in their uptake time course . Plairelative differences in transition state binding energies (Equation 9) that can be visually represented as a change in the relative position of (separation between) the hypothetical binding isotherms for either substrate . This point is important, and can be illustrated by examining the implications of the figure The Δ(TSR) phenotypes illustrated in Fig. ate Fig. . It is iCalculated TSR values for the N302C and INS Ala 320 variants are, respectively about 2.5 and 16. That these numbers are both greater than 1 indicates (Equation 9) that the hypothetical transition state binding isotherm for GABA would lie to the left  phenotype always means the same thing – there has been a change in the transition state stability for translocation of one or both substrates.It is to be noted that since absolute specificity changes can occur in the absence of a relative specificity shift , some catalytic residues may be detectable only by more complicated kinetic studies, or possibly through independent TSR experiments with structurally distinct substrate pairs. Since the TSR parameter is a synchrony with) the catalyzed reaction, and (iii) collectively can make million-fold contributions to catalytic specificity (transition state stabilization) even though their locations are spatially distant from the active site in enzymes of known structure (e.g., dihydrofolate reductase [specificity (kcat/Km) is a function of transition state stabilization ( + ΔGb), phenotypic changes in the TSR phenotype should report on structural perturbations that compromise as yet undiscovered networks that couple energetically to the transition state.Apart from its delightful simplicity and self-correcting behaviour, the TSR (or rather the ability to observe Δ(TSR) phenotypes) is also attractive as a facile means of expanding interest in "coupled promoting motions" that are networked together in support of catalysis . Such neeductase ,12-14]; eductase ). Inasmucat/Km) by many orders of magnitude [delocalization of catalytic power will in all likelihood be true of transport catalysis as well – but even more so since carriers lack a traditional active site . The catalytic power (specificity) of a carrier must therefore derive entirely from conformational motions that lead to tighter ligand binding in the transition state. This crucial catalytic increment in ligand binding energy could be localized within a binding pocket only to the extent that it is possible for a conformational transition to increase carrier-substrate complementarity without at the same time causing a change in conformational energy . If conformational energy changes as the transition state forms, then one expects obligatory partitioning of transition state binding energy among multiple interactions (steric, electrostatic, hydrogen-bonding, or solvation forces) at highly delocalized positions throughout the protein fold. Since plasma membrane transport proteins consist mainly of bundled helices that exhibit rigid-body behaviour [dynamic interfaces throughout the helix-rich structure .‡) with realization of additional binding energy , which creates catalysis. But what part(s) of the protein structure may be held to account for this pro-catalytic increment in binding energy?Carrier proteins exhibit a compact tertiary structure in which tightly bundled helical segments span the membrane in a serpentine zig-zag fashion with extensive helix-helix contacts throughout ,19. The obligatory sources in a helix-rich translocation catalyst – one source being dynamic motions in the protein fold. Tanford understood that with "...both translocation and change in chemical potential [of bound ligand] occurring in synchrony ..." [synchronously with active site rearrangements to create greater transition state stability.Although not concerned with catalysis per se, Tanford set down clear principles from which we can infer that the binding energy used for transition state stabilization should have two ony ..."  via heliony ..." . Indeed,synchrony with  reconfiguration of the bound ligand , then delocalized contributions to transition state stability must occur. Although the details may vary from case to case, the operable mechanisms will probably be conceptually similar to those that now have been visualized in dynamic simulations as "...coupled promoting motions extending throughout the protein and ligands, where promoting motions refer to equilibrium, thermally averaged conformational changes along the collective reaction coordinate leading to configurations conducive to the reaction." [Thus when distal, energy-changing, conformational motions occur in action." .cat/Km) shift, suggesting that delocalized coupled promoting motions should be the rule rather than the exception. Engineered structural manipulations that interfere with the operation of coupled networks should impact kcat/Km such that elements of these networks may be rapidly detectable by TSR analysis. Such use of TSR analysis prompts re-examination of philosophical issues concerning the efficacy of mutagenesis in structure-function analysis.Importantly, the chance occurrence of a favourable dynamic coupling interaction would be accompanied by an evolutionarily selectable substrate specificity  more than a kcal of transition state stabilization emanating from the protein fold.That catalysis ,11 and econstant, which renders its value independent of several common variables that, particularly in high-throughput screening, may be poorly controlled or only roughly estimated. A change in the TSR phenotype requires an underlying change in transition state stability  for one or both of the competing substrates. TSR-scanning mutagenesis is thus expected to identify positions in the protein fold that make contributions to transition state stabilization . The technical simplicity of TSR analysis should enable broad testing of the hypothesis that in carrier proteins the seat of catalytic power will be delocalized along helix-helix interfaces that dynamically enhance structural stability by remodelling in synchrony with transition state formation, thereby promoting translocation catalysis in a manner analogous to recently described networks of coupled promoting motions that allow dynamic interactions in the protein fold to enhance transition state stability in enzymatic catalysis [TSR analysis is a remarkably simple dual-substrate competition assay used to define the TSR phenotype of a translocation catalyst. The TSR phenotype is highly reliable because the TSR parameter is a atalysis ,11.E. coli strain SK35 is a gabP-negative host strain [E. coli SK45 is a gabP-negative strain harbouring the expression plasmid, pSCK380 [E. coli SK11 expresses a histidine-tagged Cys-less derivative of GabP [E. coli SK105 expresses the Cys-less GabP as a GabP-LacZ hybrid from the plasmid pSCK380Z [t strain . E. colipSCK380Z .3H] nipecotic acid (40 Ci/mmol) was a custom synthesis from Moravek Biochemicals (Brea, CA, U.S.A.); [14C]GABA was from Dupont-New England Nuclear (Boston, MA, U.S.A.); Ultima Gold ™ scintillation cocktail was from Packard BioScience (Meriden, CT, U.S.A.); the anti-Penta-His monoclonal antibody was from QIAGEN ; the goat anti-mouse alkaline phosphatase antibody was from Kirkegaard and Perry Laboratories (Gaithersburg, MD); isopropyl-β-D-thiogalactopyranoside (IPTG) was from Anatrace (Maumee, OH); Immobilon-P™ transfer membranes (0.45 um) were from Millipore (Bedford, MA, U.S.A.); the chemiluminescence reagent for alkaline phosphatase detections, Western Lightning, was from Perkin-Elmer Life Sciences, Inc. (Boston, MA, U.S.A.GABA was from Sigma (St. Louis, MO, U.S.A.); NA was from Research Biochemicals International (Natick, MA, U.S.A.); Miller's Luria Broth medium was from Gibco-BRL (Grand Island, NY, U.S.A.); agar and ampicillin were from Fisher Biotech (Fair Lawn, NJ, U.S.A.); bicinchoninic acid protein determination reagents were from Pierce (Rockford, IL, U.S.A.); cellulose acetate filters  were from either Millipore (Bedford, A, U.S.A.) or MicronSep,  from OSMONICS Inc. (Minnetonka, MN, U.S.A.); [E. coli strains were recovered by streaking glycerol stocks (-80°C) to single colonies on LB agar supplemented with ampicillin (100 μg/ml). LB broth supplemented with ampicillin (100 μg/ml) was inoculated by picking from a single colony and then shaken overnight (16 h) at 37°C. Overnight cultures were diluted 100-fold into fresh medium, shaken for 2 hours at 37°C prior to adding IPTG (0.2 mM), and shaking for two hours more. Cells were then harvested by centrifugation, washed twice with ice-cold KPi Buffer (100 mM potassium phosphate, pH 7.0), and resuspended to 2 mg protein/ml in the same buffer . Cultures treated in this manner are hereafter referred to as washed cells. Washed cells were stored on ice, and then equilibrated to 30°C in a heat block (25 minutes) prior to initiating transport reactions. Cultures treated in this manner are hereafter referred to as prewarmed cells.E. coli cell suspension. TSR analysis of the single-Cys GabP variant, N302C, was performed using a substrate stock containing 35 μM [3H]NA (2.1 μCi/ml) and 15 μM [14C]GABA (0.3 μCi/ml). This solution was found to support equal rates of [14C] and [3H] label accumulation in the Cys-less GabP control strain [3H]NA (1.2 μCi/ml) and 30 μM [14C]GABA (0.6 μCi/ml). This solution was found to support equal rates of [14C] and [3H] label accumulation by the wild type GabP [Transport reactions were initiated by mixing 20 μl of a 5-fold concentrated substrate stock solution with 80 μl of prewarmed C]GABA 0. μCi/ml. Stop Solution (KPi Buffer containing 20 mM HgCl2), and then vacuum-filtered (0.45 micron pore). The reaction vessel was then rinsed with 1 ml of Wash Buffer (KPi Buffer containing 5 mM HgCl2) and this was applied to the same filter. Finally, 4 ml of the Wash Buffer was applied to the filter. The filter was then dissolved in Ultima Gold™ scintillation cocktail and the [3H] and [14C] radioactivity (disintegrations per minute, dpm) analyzed with a Packard BioScience Tri-Carb 2900 TR liquid scintillation counter using stored Ultima Gold™ quench curves and automatic quench compensation.A 60 or 120 Hz metronome was used to time the reactions, which were rapidly quenched with 1 ml of ice-cold E. coli strain, SK45, was grown and prepared for transport experiments as indicated above except that a series of different cell suspensions were prepared spanning a range from 20 to 125 percent of that described above. Dual-label transport experiments carried out with these different suspensions produced a linear standard curve for GabP-independent "background uptake" of [3H]NA and [14C]GABA as a function of protein content. The protein content of GabP-positive test strains could then be used to obtain the appropriate background subtraction by extrapolation from the standard curve. Test strain protein contents were always similar (within 10 percent) because when cell pellets were resuspended steps were taken to assure approximately equal turbidity levels.The GabP-negative 3H]NA and [14C]GABA. The background-corrected velocity replicates were used to calculate replicate TSR values (Equation 6) from which the mean TSR and standard errors (S.E.M.) shown in the figures were obtained.Replicate (n = 3), background-corrected, dual-substrate uptake velocities (moles/time) were inferred from measured disintegration rates for filter-bound [E. coli cells were probe-sonicated to produce plasma membrane vesicles, which were then separated from soluble components and unbroken cells by differential centrifugation as previously described [escribed . Plasma escribed . Immunob


A computation pathway analysis of the human genome is presented that assigns enzymes encoded by the genome to predicted metabolic pathways. This analysis provides a genome-based view of human nutrition. We present a computational pathway analysis of the human genome that assigns enzymes encoded therein to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary first step toward quantitative modeling of metabolism.. We describe the generation of HumanCyc, and present an analysis of the human metabolic map. For example, we compare the predicted human metabolic pathway complement to the pathways of Escherichia coli and Arabidopsis thaliana and identify 35 pathways that are shared among all three organisms.Our analysis assigns 2,709 human enzymes to 896 bioreactions; 622 of the enzymes are assigned roles in 135 predicted metabolic pathways. The predicted pathways closely match the known nutritional requirements of humans. This analysis identifies probable omissions in the human genome annotation in the form of 203 pathway holes (missing enzymes within the predicted pathways). We have identified putative genes to fill 25 of these holes. The predicted human metabolic map is described by a Pathway/Genome Database called HumanCyc, which is available at Our analysis elucidates a significant portion of the human metabolic map, and also indicates probable unidentified genes in the genome. HumanCyc provides a genome-based view of human nutrition that associates the essential dietary requirements of humans with a set of metabolic pathways whose existence is supported by the human genome. The database places many human genes in a pathway context, thereby facilitating analysis of gene expression, proteomics, and metabolomics datasets through a publicly available online tool called the Omics Viewer. The human genome is a blueprint, but for what machinery? One approach to understanding the complex processes encoded by the human genome is to assign its enzyme products to biochemical pathways that define regulated sequences of biochemical transformations. Pathway and interaction assignments place genes in their larger biological context, and enable causal inferences about the likely effects of mutations, drug interventions and changes in gene regulation. They are a first step toward quantitative modeling of metabolism. Assignment of genes to pathways also permits a validation of the human genome annotation because patterns of pathway assignments spotlight likely false-positive and false-negative genome annotations. For example, false-negative assignments appear as pathway holes: missing enzymes within a pathway that are likely to be hiding in the genome.SRI's Bioinformatics Research Group has developed a pathway-bioinformatics technology called a pathway/genome database (PGDB), which describes the genome, the proteome, the reactome and the metabolome of an organism. A PGDB describes the replicons of an organism (chromosome(s) or plasmid(s)), its genes, the product of each gene, the biochemical reaction(s), if any, catalyzed by each gene product, the substrates of each reaction, and the organization of those reactions into pathways. Pathway Tools is a reusable software environment for constructing and managing PGDBs . It suppThe power of Pathway Tools is derived from both its database schema, and its software components. Both were originally developed for the EcoCyc project ,3. A PGDHomo sapiens, from the annotated human genome. The genome data used as input to PathoLogic combined data from the Ensembl database [PathoLogic is one of the Pathway Tools software components. Its primary function is to generate a new PGDB from an organism's annotated genome. PathoLogic predicts the metabolic pathways of the organism, providing new global insights about its biochemistry, and generates reports that summarize the evidence for the presence of each predicted metabolic pathway. We used PathoLogic to generate HumanCyc, a PGDB for database , the Locdatabase  and GenBdatabase .Escherichia coli and Arabidopsis thaliana and identify 35 pathways that are shared among all three organisms, and therefore define an upper bound on a potential set of universally occurring metabolic pathways.Our analysis assigns 2,709 human enzymes to 135 predicted metabolic pathways. It provides a genome-based view of human nutrition that associates the essential dietary requirements of humans that were previously derived mainly from animal and tissue extract studies to a set of metabolic pathways whose existence is derived from the human genome. The analysis also identifies probable omissions in the human-genome annotation in the form of pathway holes (missing enzymes within the predicted pathways); we have identified putative genes to fill some of those pathway holes. This paper describes the generation of HumanCyc, and presents an analysis of the human metabolic map. The computationally predicted pathways are consistent with known human dietary requirements. We compare the predicted human metabolic pathway complement to the pathways of H. sapiens annotated genome, as described in Materials and methods, generating HumanCyc.We applied PathoLogic to the input files containing the Table E. coli genome). Of the 1,653 metabolic enzymes, 622 are assigned to a pathway in HumanCyc, and the remainder are not assigned to any pathway; we expect that in the future some of the latter group of enzymes will be assigned to some known human pathways not yet in HumanCyc, and to some human pathways that remain to be discovered. Of the metabolic enzymes, 343 are multifunctional. The number of enzymes is less than the number of enzyme genes because, in many cases, the products of multiple genes are required to form one active enzyme complex.Table Table HumanCyc 7.5 contains 1,093 biochemical reactions, 896 of which have been assigned to one or more of the 2,709 enzymes in HumanCyc. There are more enzymes than reactions because of the existence of isozymes in the human genome. This leaves 203 reactions that have no assigned enzyme. These reactions correspond to the above-mentioned pathway holes for the HumanCyc pathways. Of the 896 reactions that have assigned enzymes, 428 have multiple isozymes assigned.The PathoLogic-based analysis of the annotated human genome inferred 135 metabolic pathways. A total of 203 pathway holes (missing enzymes) were present across 99 of these pathways; that is, 38 pathways were complete. Using our hole-filling algorithm  for a liThe original annotations of the human proteins that were identified as candidate hole fillers fell into several classes: A description of each class is presented below, with examples included for some.N-acetylneuraminate lyase (LocusLink ID 80896), aldose 1-epimerase (LocusLink ID 130589) and imidazolonepropionase (LocusLink ID 144193) reactions. In each of these cases, the function of the protein was previously unknown.Putative enzymes were identified, for example, for the The pathway hole filler assigned an enzyme previously annotated with a general function. For example, 'amine oxidase (flavin-containing) B' (LocusLink ID 4129), was assigned to a more specific reaction, putrescine oxidase. A 'fatty acid synthase' (LocusLink ID 54995) was identified to fill the 3-oxoacyl-ACP synthase reaction.In these cases the program is postulating an additional function for a gene that already has an assigned function. The pathway hole filler identified the enoyl-CoA hydratase enzyme (LocusLink ID 1892) as a potential hole filler for the 3-hydroxybutyryl-CoA dehydratase reaction in the lysine degradation and tryptophan degradation pathways. The dihydrofolate synthase hole in formylTHF biosynthesis was filled by the enzyme (LocusLink ID 2356) catalyzing the folylpolyglutamate synthase reaction.Although our analyses of other pathway/genome databases have revealed examples we consider to have been assigned an incorrect function in the original annotation, our analysis of the 25 HumanCyc pathway holes that we filled revealed no candidates in this category.The pathway hole filler not only identifies candidate proteins for each pathway hole, but also determines the probability that each candidate has the desired function. Table N-acetylglucosamine-6-phosphate deacetylase activity approaches 1.0. In the last example, both proteins have excellent BLAST E-values; in fact, the E-value for protein F indicates a better match with the query sequences than the E-value for protein E. In this case, protein E is found in 19 lists of BLAST hits versus four for protein F, and on average aligns with a much larger fraction of each query sequence. When examined in more detail, we discover that the four query sequences that identified candidate F in their BLAST output are multifunctional proteins with both aldose-1-epimerase activity and UDP-glucose 4-epimerase activity. Protein F aligns with the amino-terminal region of each of the four query sequences, and has no detected similarity in the carboxy-terminal regions. The UDP-glucose 4-epimerase activity lies in the amino-terminal region of each multifunctional query protein.In the first example, 28 imidazolonepropionase sequences from other organisms were retrieved from Swiss-Prot and the Protein Information Resource (PIR). Using BLAST, each sequence was used to query the human genome for candidate enzymes. Protein A was found in all of the 28 lists of BLAST hits. From the numbers in the table, it is fairly obvious that protein A is more likely to catalyze the imidazolonepropionase reaction than is protein B. In the second example, given the best E-value (1e-110) it is again not surprising that the computed probability that protein C has Nutritional requirements and their genetic and biochemical basis are thought to have evolved principally in prokaryotes, over billions of years . SpecifiCurrent knowledge of human nutrition based on metabolic pathways is derived from various sources. One is clinical observation of inherited human metabolic diseases and nutrient deficiency states. For some pathways, like oxidative phosphorylation and the TCA cycle, direct studies of human tissues, such as human muscle biopsies, have been made. Nuclear magnetic resonance (NMR) has been used directly on humans to study aspects of carbohydrate and energy metabolism. Stable isotopes have been used to trace human metabolism, from which inferences about nutrition have been made. Dietary studies have been made in experimental mammals such as rats and mice and metabolic pathways experimentally elucidated in model organisms.Here we compare previously accepted human nutritional requirements with pathways derived from the human genome to evaluate their agreement. For example, biosynthetic pathways for essential human nutrients, that is, substances that must be provided in the diet such as the essential amino acids and vitamins, would not be expected to occur in the human genome.Integration of human genome data with clinical, biochemical, physiological and other data obtained both directly from humans and indirectly from model organisms should, over time, lead to a deeper understanding of human metabolism and its nutritional implications in health and disease. When the genome sequences of individuals are available, it may be possible to address questions about the variation in optimal nutrition from person to person. Explicit identification of specific areas of inconsistency will serve to focus ongoing experimental efforts to elucidate the molecular basis of human nutrition and metabolism.For all of the nine amino acids essential for humans, PathoLogic did not predict the presence of a corresponding biosynthetic pathway  and H. sapiens (25.7% of the 135 pathways in HumanCyc). Those 35 pathways therefore constitute a likely upper bound on the number of universally and exactly conserved metabolic pathways. It is an upper bound in the sense that as more organisms are considered, the list of universal pathways cannot grow larger.Figure E. coli metabolic network, including the most frequently used substrates and cofactors [E. coli metabolic network (after water and ATP): removing the ability to synthesize NAD would disable so many reactions as to be insurmountable. Pyridoxal-5'-phosphate is the second most common cofactor (after Mg2+). Coenzyme A and acetyl-CoA together constitute the seventh most common substrate in E. coli, formylTHF constitutes the 23rd most common substrate, and thioredoxin and glutathione constitute the 40th and 41st most common substrates.We propose that the cofactor biosynthesis pathways shared among all three organisms have been conserved because first, they produce complex molecules that are not available from the environments of these organisms; second, these molecules are used as cofactors in so many reactions within the metabolic networks that the requirement for them is absolute; and third, no other pathway to accomplish the synthesis of that molecule has evolved. A study by Ouzounis and Karp surveyed global properties of the ofactors . TogetheThe level of metabolic pathway variation in the biosphere remains to be determined. Metabolic pathways have been experimentally elucidated in a small number of model prokaryotic and eukaryotic organisms. Despite the relatively small number of carefully studied organisms, significant pathway variation has been observed both between distinct organisms and within a given organism. For example, at least four variants of the 'glycolytic pathway' have been described . Sets ofk for the presence of a pathway, Pj, that was experimentally elucidated in an organism Oj, this alone does not constitute conclusive evidence for the presence of Pj in Ok, since a variant of Pj (Pk) may be present in Ok . Second, for those pathways with known closely related variants (for example, two pathways differing by only a single step with one step differing from the other only at the level of co-reactants/products, such as one using NADP/NADPH the other using NAD/NADH as cosubstrates/products) it is often impossible to choose among these variants on the sole basis of genomic data because of the limited resolution of sequence analysis.Metabolic pathways appear to have diverged in a manner analogous to the divergence of biological sequences. The demonstrated existence of pathway variants and ongoing uncertainty as to the full extent of such variation has significant implications for ongoing efforts to predict biochemical pathways from incomplete genomic data. First, it means that the precision with which we can infer pathways in one organism from another solely on the basis of genomic data remains to be determined, because when genomic evidence is found in organism OWe have developed a general approach to representing the presence of pathway variants. MetaCyc pathways (approximately 500) have been grouped using a function-based classification system. Each grouping defines a 'pathway family', each member of which (a pathway variant) endows an organism with one or more specific functional capabilities, for example, the ability to grow in the absence of phenylalanine. Within a given pathway family, variants may be clustered into one or more subfamilies. Subfamilies are groups of pathways that show significant overlap/similarity in terms of individual reaction steps (reactants and products of each reaction); enzymatic activities that catalyze these steps; and genes encoding the enzymes that mediate these activitiesThe similarity between variants within a given subfamily suggests they evolved from a common ancestor pathway. For example, at least four variants of the glycolytic pathway have been described; all enable the conversion of glucose to pyruvate and show significant overlap/similarity in their component reactions. Other pathway variants have been observed that show little similarity to each other (for example, some of the amino-acid degradation pathways) and these are therefore believed to have evolved from distinct ancestor pathways. The existence of pathway subfamilies indicates that multiple pathways have coevolved to meet common nutritional/metabolic challenges.1, in humans is taken as evidence that P1 and/or other members of the pathway family to which P1 belongs are likely to be present in humans . Indeed, PathoLogic sometimes inferred the presence of multiple variant pathways in humans. This occurred because when evidence was found in the genome for the presence of one member of a pathway family/subfamily, this evidence often also supported the presence of other members of this family/subfamily. In these cases, all inferred variants were included in HumanCyc. Of course, the specific members of a given pathway family actually present in humans may include one or more of those inferred from MetaCyc or other members of this pathway family not yet described in MetaCyc and/or not yet experimentally elucidated from any organism. It is attractive to think that multiple variant pathways might refer to metabolically differentiated tissues in the body, or to different regulatory states available to the same tissue. An example of the latter would be the liver; at different times of day it either synthesizes glycogen, taking glucose from the blood, or it degrades glycogen to maintain the blood glucose level.For the purposes of this paper, genomic evidence for the presence of a specific biochemical pathway, PThe HumanCyc PGDB is freely available for use by the scientific community from the SRI website . Basic qWhen viewing a HumanCyc pathway display, be aware that the software omits enzyme names for pathway holes. That is, when no human protein has been identified that catalyzes a reaction within a pathway, no enzyme name is drawn next to that reaction.The cellular overview , a full H. sapiens includes a report that lists the evidence for each predicted pathway in HumanCyc, with pathways sorted according to the MetaCyc pathway ontology [The PathoLogic summary page for ontology .HumanCyc is currently available for local installation at your institution  as a setRelated databases of human metabolic pathways include the GenMAPP  collectiPathoLogic was the first program for automated inference of genome-scale pathway reconstructions from genome data . Additioet al. infer novel biotransformation rules for xenobiotics from the molecular graphs of compounds [The following additional pathway prediction methods are related to this work, but have not been applied on a genome scale and have received little validation. Zien and colleagues use gene-expression data to score pathways that are enumerated combinatorially from a reaction database. Van Helden and colleagues use clustering of gene-expression data to generate seed reactions that are used to combinatorially enumerate pathways ,32. McShompounds . A recenompounds .The user of HumanCyc should be aware of several potential limitations that influence the interpretation of the DB contents. First, HumanCyc is incomplete in the sense that some known (and unknown) human metabolic pathways are not present in it. It will require a significant database curation effort to enter all known pathways. Second, HumanCyc probably contains false-positive pathway predictions. Our approach is to err on the side of being more inclusive in our pathway predictions so that all potential pathways are brought to the attention of the scientific community for evaluation. For example, HumanCyc sometimes contains multiple pathway variants that we currently lack the evidence to choose between, and in other cases the actual human pathway may be a variant of the pathway present in HumanCyc. Third, HumanCyc does not encode information about the location (compartment(s), cell type(s) or tissue(s)) in which a pathway occurs. Each pathway is defined using all identified human enzymes, meaning that location-specific versions of a pathway are not specifically identified. Furthermore, the presence of a pathway could be incorrectly inferred because the enzymes that make up a pathway are found in different locations and are never expressed in a common location, meaning that the pathway can never occur in its entirety. Fourth, HumanCyc does not contain nucleotide or amino-acid sequences. Our future work will address the first three of these limitations, and will include a significant effort to manually refine and update HumanCyc with pathway and enzyme information from the biomedical literature. To date, three pathways have been added to HumanCyc through manual curation. Experimentally elucidated pathways in HumanCyc will be annotated as such with evidence codes; pathways predicted by PathoLogic are annotated as computationally inferred.HumanCyc can be used to develop an agenda for experimental refinement of the human metabolic map. Predicted pathways should be experimentally verified, with particular attention to choosing among multiple pathway variants. Candidate 'fillers' for the 178 unresolved pathway holes identified herein should be identified.vice versa. The computationally predicted metabolic network provided a rational framework for understanding the genetic basis of some well-characterized human dietary requirements, that is, 11 nonessential amino acids and 22 essential nutrients .PGDBs endow genomic information with an extended dimension that allows researchers to analyze an organism's genome with respect to the causal relationships inherent to a metabolic network. In this sense, HumanCyc provides the opportunity to look at human metabolic processes within the context of the annotated human genome, and PathoLogic's pathway prediction process provides a reasonably accurate picture of the metabolic network, and Pathway Tools provides the user with extensive capabilities for refining the DB to reflect improvements in our understanding of the human metabolic network. The query and visualization capabilities of the Pathway Tools software  will facilitate novel approaches for analyzing the complexity of functional relationships within the human genome.The PathoLogic program generates a new PGDB starting from the annotated genome of an organism, meaning a complete genome sequence (closed or gapped) for which gene prediction and sequence analyses have already identified the locations of likely coding regions, and have predicted the functions of these genes. We used Ensembl Build 31 as our main data source for the annotated human genome, and complemented that information with data from LocusLink, the National Center of Biotechnology Information (NCBI) database of genetic loci. We used GenBank as our source for the mitochondrion genome, as this information was not included in Ensembl. LocusLink mitochondrial loci were used to complement this information when applicable.The information from these different sources required special preprocessing to make it available to PathoLogic. That preprocessing addressed three needs: first, to convert the disparate data formats used by these sources into a format parsable by PathoLogic; second, to extract information useful to PathoLogic; and third, to remove redundancy among the sources.In the case of Ensembl, the standard Ensembl flat files included just a subset of the information needed for the PGDB generation process. We therefore used the EnsMart facility provided by Ensembl  to generWe selected LocusLink file LL3_030319 (Version from 19 March, 2003), which contained all data required by PathoLogic . Table When generating the input files for PathoLogic, information from Ensembl and LocusLink was combined only when the Ensembl record for a gene included a cross reference to a LocusLink ID. In such a case, data from the LocusLink entry was merged with that of the Ensembl gene, meaning that when both databases provide an attribute such as a gene name, the Ensembl data is preferred. This approach created gene objects for HumanCyc that include information from both the Ensembl and the LocusLink entries. Those HumanCyc gene objects use the Ensembl ID as their unique identifier, and have database links to the corresponding LocusLink entries. For the mitochondrial data, the number of LocusLink mitochondrial loci was small enough so that they were easily checked for matches with corresponding genes in the GenBank files.LocusLink loci that had no direct counterpart in either the Ensembl data or the GenBank mitochondrial data (for example, LocusLink loci that were not directly referenced in any Ensembl gene record) were assigned their own record in the PathoLogic input files. The LocusLink ID was used as the unique identifier for these gene objects. Only loci corresponding to 'real' genes (not models, phenotypes or pseudogenes) were included in HumanCyc. We must point out that records corresponding only to LocusLink loci lack gene position information, so they cannot be precisely placed on a chromosome map. We were aware that adding these LocusLink-only-based records to HumanCyc would produce some redundancy in the database, but this was accepted for the sake of completeness. Manual analysis of similar Ensembl and LocusLink-based gene objects after building HumanCyc led to the fusion of gene objects corresponding to the same gene. The number of LocusLink gene objects that were not merged to corresponding gene objects from Ensembl or GenBank is shown in the 'nonredundant' column of Table It is readily apparent from Table Seventy-six PathoLogic input files were generated from the preceding data sources: 24 for the human chromosomes, one for the mitochondrion, 50 for the different contigs not yet integrated to the chromosomal sequences, and one called 'unknown' for all the loci that had no chromosome information. A replicon object was created in HumanCyc for each of these files.This section summarizes the PathoLogic algorithm (for a more detailed description of the method see ,37). ForAfter initializing the schema of the new PGDB, a database object is created for each replicon and contig, and for each gene and its corresponding gene product. PathoLogic then tries to determine the metabolic reaction catalyzed (if any) by each gene product in the organism by using its EC number, if provided in the annotation, and by matching the name of each gene product against the extensive dictionary of enzyme names within the MetaCyc DB . FinallyAs mentioned above, PathoLogic will assign reactions for those enzymes that have an exact EC number match or name match against MetaCyc. A gene product name may not exactly match that of any enzyme in MetaCyc. Some enzyme names will produce ambiguous matches or no match at all. PathoLogic assembles a list of 'probable enzymes' that includes both ambiguous matches and nonmatched proteins whose names suggest enzymatic activity. This list is examined manually through a PathoLogic module that helps the user evaluate possible matching candidates within MetaCyc and assign probable enzymes to the correct reaction, if possible.An alternative to our strategy of using the existing EC number and function assignments from LocusLink and Ensembl would be for us to discard those assignments and to reanalyze the genome using sequence analysis methods to produce new assignments. We rejected this approach for two reasons: first, it would discard some experimentally derived function assignments in place of less reliable computational assignments; and second, we consider the Ensembl function predictions to be of high quality, and we are aware of no evidence that our group, or any other group, has a sequence analysis methodology that will produce function assignments that are substantially more accurate than those of Ensembl.Finally, PathoLogic generates reports summarizing the amount of evidence supporting each pathway in the new PGDB, and listing the pathway holes, that is, the enzymes missing from each predicted pathway. This information helps the user identify pathways that should be deleted from the PGDB, such as variant pathways and false-positive predictions made by PathoLogic. For example, MetaCyc includes eight variants of the TCA cycle. Several of these might appear in a newly predicted PGDB. False-positive pathways, some of which are predicted because they share reactions with other pathways in MetaCyc, should be removed from the PGDB. Once variant or false-positive pathways are eliminated by the user, PGDB generation has been completed.To determine the function of a protein sequence, researchers typically use a single sequence to search for potential homologs in a large public database. To identify sequences to fill pathway holes, we have, in effect, reversed this search process. We search the genome for a sequence that will provide the enzymatic function needed to fill each pathway hole. Our method uses multiple isozyme sequences (retrieved via MetaCyc from Swiss-Prot and PIR) to search a genome for similar sequences (hole-filler candidates). We then evaluate each candidate to determine the probability that the sequence has the desired function based on homology and pathway-based data. A hole-filler tool that implements this pathway-driven gene-finding methodology has been developed .E. coli) and AraCyc .Once HumanCyc was built and manually refined, as explained above, we examined the metabolic network within HumanCyc in order to make a preliminary assessment of the quality of PathoLogic's predictions and to check for pathways not previously thought to occur in humans. We also compared the metabolic network of HumanCyc to that of two of our curated PGDBs, corresponding to a bacterium and a plant. These PGDBs are EcoCyc (The following additional data are available with the online version of this article. Additional data file A table listing the data file names generated from EnsMart for each human chromosome or contig and provided as input to PathoLogic, thus indicating which contigs are associated with which chromosomesClick here for additional data file


Most published typing methods are not well suited for routine typing of large sample numbers in smaller service laboratories for different reasons: they require partly manual data processing, sophisticated and sensitive protocols, high efforts regarding time and manpower, multiple step reactions or substantial hardware investments. To overcome these drawbacks, we developed a prnp typing method that is based on a `multiplex amplification refractory mutation system' (ARMS) reaction.In many countries breeding programs for resistance to scrapie in sheep are established. Therefore, the demand on genotyping capacities of the polymorphisms of the prion protein gene (prnp genotyping method (PRNP ARMS).In this study we combined the amplification refractory mutation system (ARMS) with standard fluorescent based fragment length analyses method to develop a prnp simultaneously in one multiplex reaction. Automated fragment length analysis enabled automated allele designation. Suitability of the PRNP ARMS for routine application was proven by typing samples with known genotypes and larger sample numbers from half-sib families.By optimised primer design it was possible to type the 4 relevant single nucleotide polymorphisms (SNPs) in the prnp genotyping compared with other low-cost methods. It can be implemented by most molecular genetic laboratories using standard equipment.The ARMS PRNP typing method established in this study is universally suited for a broad range of typing projects with different requirements. It provides an efficient and inexpensive diagnostic mutation analysis that will improve the quality of  Direct sequencing covering the region of exon 2 encoding amino acid positions 136, 154 and 171 is the most accurate method, that enables the typing of additional and detection of hitherto unknown polymorphisms. Other methods are classical PCR-restriction fragment length polymorphism (RFLP)-typing [prnp [® (Applied Biosystems, CA) [For determination of )-typing , hybridi)-typing ,10, prim)-typing , and so ng [prnp  and the ems, CA) , and pyrprnp typing that can easily be adopted by a wide range of other laboratories.The amplification refractory mutation system (ARMS) method is well established  and has ®-tissue samples were collected from half-sib families from three common sheep breeds in Bavaria. All lambs were born in the years 2001 and 2002. DNA was isolated by using the E.Z.N.A. Blood DNA Mini Kit (#12-3482-03, PEQLAB Biotechnologie GmbH, Erlangen, Germany) or the NucleoSpin® Multi-96 Tissue kit (MACHEREY-NAGEL GmbH & Co. KG, Düren, Germany), respectively.EDTA-blood or TypifixAn overview of primer locations is given in Fig. 2, dNTP's (25 nM each), and 0.75 units of HotStar-taq polymerase (Qiagen, Hilden, Germany) in a final volume of 10 μl on a t-gradient 96-well thermocycler (Biometra, Göttingen, Germany). Primer concentrations were 10 nmol each. Cycling was for 15 min at 95°C, [0.5 min at 94°C, 1 min at 62°C, 1 min at 74°C]33× without final extension.For the ARMS reaction haplotypes were amplified from 2 μl of DNA solution with standard buffer conditions, 1.5 mM MgCl® 310 genetic analyser (Applied Biosystems, Foster City, CA) with 5 sec injection time, 15 kV, 60° and 18 min runtime using 36 cm capillaries. Allele designations were generated automatically using the Genotyper® software (V. 2.5, Applied Biosystems) as described [Fragment lengths of ARMS amplification products were analysed on an ABI PRISMprnp exon 3 coding for amino acids 47 to 246 of the prion protein was amplified in 10 μl reaction volume using 2 μl of genomic DNA, 0.05 μM of each primer (5'-tcc tgg agg caa ccg cta tc-3' and 5'-gga gga tca cag gag ggg aag-3'), 50 μM of each dNTP, 0.5 units of HotStar-taq polymerase (Qiagen, Hilden, Germany), and reaction buffer containing 1.5 mM MgCl2. Cycling-conditions on a Biometra T gradient 96-well thermocycler were: 15 min at 95°C, [0.5 min at 95°C, 1 min at 60°C, 0,5 min at 72°C]35× and 10 min, 60°C final extension. Before direct sequencing PCR-reactions were purified using the 96-well MultiScreen-PCR plates (Millipore, Bedford, MA). Sequencing was performed using BigDye V 2.0 terminator cycle sequencing kit (Applied Biosystems, Foster City, CA). Sequencing analysis was run on an ABI PRISM® 310 genetic analyser.Part of prnp 136-154-171 genotypes in sheep. The PRNP ARMS method was developed using standard DNAs representing all five main haplotypes. In a first stage, different primer pairs were tested for allele specific amplification using an anneal-temperature gradient. By redesign of primers for amino-acid positions 154 and 171 and introducing deliberate mismatches close to the 3' end an optimised primer set was established (Table We have established a multiplex `amplification refractory mutation system' (ARMS) based method for the identification of ed Table . These wTo provide a proof-of-principle the same 140 sheep DNAs were analysed by direct PCR sequencing and by PRNP ARMS. Typing results were identical with both methods. In a second step, 420 sheep from half-sib families and 20 samples from the international sheep and goat DNA typing comparison test 2003 of the International Society of Animal Genetics were analysed by the PRNP ARMS method. All genotypes followed the rules of Mendelian inheritance and no deviation from the main 5 haplotype patterns was observed. Allele frequencies derived from these animals from three different Bavarian breeds are shown in Table Typical electropherograms representing different haplotype combinations are shown in Fig. prnp haplotypes, thereby facilitating the detection of 'complex' prnp genotypes that do not match one of the 15 standard genotype patterns. If necessary, it can easily be extended to complete haplotype determination by adding additional labelled forward primers for position 154 (for haplotype 154-171).The PRNP ARMS genotyping method has several advantages. It is based on a one step reaction using competitive allele discrimination. The fragments can be analysed on an automated sequencer that allows data to be directly transferred to a database. The reaction proved to be highly specific and no false negative or positive results were observed yet. Furthermore, it is robust with respect to variations of DNA quality and, since no further purification or reaction is necessary, the costs for consumables are low. The ARMS method allows the determination of partial  alleles. No known polymorphism interfere with the attachment of the selected ARMS primers. Nevertheless, the recently described rare polymorphism K-171 [All methods currently available for SNP typing are inherent sensitive to nucleotide changes within the primer attachment or restriction sites. The resulting mismatches can cause inconclusive typing results or null alleles, as frequently observed with microsatellite loci. Therefore, it is crucial to be aware of this phenomenon and to take measures to reduce the risk of mistyping. The primers for PRNP ARMS were carefully checked against a sm K-171  with unksm K-171 ) are genThe PRNP ARMS method is highly flexible with respect to scale and instrumentation. It is easily adoptable from low- to medium-throughput typing system using identical reaction conditions. In principle, all primer combinations can even be performed as single reactions that can be analysed on agarose gels (data not shown). Nevertheless, the reliability of genotyping results improves when competitive reaction conditions and commonly available DNA sequencing machines are used. Since all reactions can be performed in microtiter plates, the ARMS reaction can easily be adopted for a pipetting robot. Together with the one step reaction and the automated data transfer, the risk of cross-contamination or interchanging of samples is minimized. The runtime of 18 min results in 25 min analyses time per sample on the ABI 310 and could be optimised by using shorter capillaries. When using the standard run conditions on the smallest, single capillary sequencer the throughput is limited to about 55 samples per working day but can be scaled up to more than 5000 samples per day by using a 96-well capillary sequencer. That should be sufficient even for large, existing breeding programs. PRNP ARMS can be multiplexed with other typing systems (microsatellite or SNP), since it is analysed using standard fragment analysis technique. Moreover, it is suitable for further applications as e.g. allele frequency estimation from pooled DNA  for inveprnp typing method has been established that is universally suited for a broad range of typing projects with different requirements. This typing method was developed by optimising ARMS primers and combining these with standard fragment length analyses. The method provides an efficient and inexpensive diagnostic mutation analysis that can be implemented by most molecular genetic laboratories using standard equipment. It should contribute to reliable and economic genotyping of the ovine prnp by the many smaller labs throughout Europe.An easy and robust one-step The authors declare that they have no competing interests.J.B. designed the project and protocols involved, performed analysis of results and drafted this manuscript. J.S. conceived the ARMS reaction, fragment analysis and DNA sequencing.The pre-publication history for this paper can be accessed here:


Agnogenic myeloid metaplasia (AMM) is one of the Philadelphia chromosome negative myeloproliferative disorder and is diagnosed by hyperplasia of atypical megakaryocytes, hepatosplenomegaly, extramedullary hematopoiesis and bone marrow fibrosis. Fibrosis is considered to be a secondary consequence of enhanced levels of fibrogenic growth factors such as TGF β1, bFGF and PDGF produced by enhanced numbers of megakaryocytes, while the primary cause is considered to be the enhanced proliferation of a defective stem cell. We have previously reported that thrombopoietin (TPO) is elevated in patients with AMM. Others have reported that Mpl protein is decreased in these patients. Since TPO is essential for the development of megakaryocytes, and Mpl protein is the receptor for TPO, we extended the study of TPO/Mpl to in vitro and in vivo cell culture systems to better understand the mechanism that leads to reduced Mpl protein in AMM patients.Plasma TPO levels were significantly elevated and Mpl protein levels were significantly reduced in AMM patients in concordance with previous studies. Platelet Mpl transcripts in AMM were however similar to those in controls. We also cloned Mpl cDNA from AMM patients and tested for their ability to make functional proteins in vitro and in the in vivo system of 293 T human embryonic kidney cells. Their expression including the glycosylated forms was similar to those from the controls. We also measured the level of translation initiation factor, eIF4E and found it to be increased in patients with AMM demonstrating that the reduced Mpl protein may not be due to translation defects.Our studies using the in vitro and in vivo systems further confirm that reduced Mpl protein levels are not due to defects in its transcription/translation. Reduced Mpl protein could be due to its increased internalisation owing to enhanced plasma TPO or in vivo intrinsic defects in patients with AMM. Agnogenic myeloid metaplasia (AMM), polycythemia vera (PV), essential thrombocythemia (ET) and chronic myelogenous leukemia (CML) are characterized as myeloproliferative disorders (MPDs) arising due to exponential amplification of a haematopoietic stem cell. A typical feature of these disorders is the presence of high number of circulating progenitor cells and their cytokine independent growth in culture. So far, the molecular basis for the disorder has been recognized only for CML and is attributed to the Bcr/Abl or Philadelphia (Ph) chromosome arising due to a translocation event. The aetiology for the other three disorders referred to as Ph negative MPDs is unknown.TPO knockout mice have shown reduced numbers of platelets and myeloid progenitor cells confirming the role of TPO. Enhanced expression of TPO in mouse by Retroviral/Adenoviral gene transfers and in mice transgenic for TPO, the animals developed extramedullary haematopoiesis and splenomegaly due to MK and granulocytic hyperplasia. The severity of the conditions was related to the expression levels of TPO, resulting in myelofibrosis under very high expression level [TPO over expression are similar to the symptoms of AMM and hence indicate that high levels of TPO found in AMM patients could be responsible for the clinical features of AMM. In the mouse knockouts for Mpl receptor, there is about 85% reduction in the number of platelets, MKs and other haematopoietic cell types [Mpl over expression leads to myeloproliferation [Mpl antisense oligonucleotides inhibited megakaryocytopoiesis [AMM, one of the Ph negative MPD is diagnosed by hyperplasia of atypical megakaryocytes, hepatosplenomegaly, extramedullary haematopoiesis and bone marrow fibrosis. Fibrosis is considered to be a secondary consequence of enhanced levels of fibrogenic growth factors such as TGF β1, bFGF and PDGF produced by enhanced numbers of megakaryocytes (MKs), while the primary cause is considered to be the enhanced proliferation of a defective stem cell. What leads to generation of such a defective cell with enhanced proliferation is unknown. We have earlier demonstrated  that thron level -8. Thesell types  and Mpl feration . In vitropoiesis . These ropoiesis . This abTPO transcripts and they were not inhibited by TPO antibody. Also no mutations were detected in the Mpl gene in these patients, to account for its reduced protein level. The observation of Li et al. [Mpl anti-sense oligonucleotide treatment could inhibit the autonomous growth of MKs from ET/PV/AMM in vitro suggests that expression of Mpl is essential for MK autonomy in these disorders. However Moliterno et al. [Mpl in a disorder characterized by MK hyperplasia whose development and differentiation is dependent on this cytokine is paradoxical and needs further investigation.According to Taksin et al.  defects i et al.  that Mplo et al. ,15 have o et al. , it doesMpl cDNA from 15 AMM patients and have found that it has full potential for expression similar to controls both in vitro and in the in vivo heterologous system of 293 T cells. We also assayed for the level of eIF4E, the translation initiation factor that under normal limiting level favours translation of strong mRNAs such as those of house keeping genes and at higher level, enhances the translation of weak mRNAs such as Mpl. AMM patients were found to have elevated eIF4E level.Hence to better understand the role of TPO/Mpl in AMM, we have extended the study of this growth factor and its receptor gene in these patients. Our studies reveal enhanced plasma TPO level, reduced endogenous level of Mpl protein in the platelets of patients with AMM and absence of any co-relation between TPO level and Mpl expression. We have cloned Undiluted platelet poor plasma (PPP) samples from 20 AMM patients and 10 controls were assayed for their TPO levels. Although some patients exhibited low TPO levels, overall, TPO level was enhanced in AMM patients as compared to controls [0–684 pg/ml in AMM patients (with a mean of 229 pg/ml) as compared to 0–71 pg/ml in controls (with a mean of 22.8 pg/ml)]. This increase in TPO was significant (P < 0.001) as determined by t-test  between TPO level and Mpl levels , indicating absence of any transcriptional inhibition of Mpl in AMM patients.Since Mpl protein level was reduced in AMM patients, to know if it was due to reduced transcription of the Mpl at higher amounts. At limiting levels it favours translation of stronger mRNA over the weaker mRNA. The western blots on chemiluminescence detection showed an overall increase in the expression of eIF4E in the platelets of patients with AMM. A representative blot shown in Fig. We assayed for the expression of eIF4E in the platelets of 12 AMM patients to see if reduced Mpl protein level could be due to its reduced translation owing to limiting levels of eIF4E, a translation initiation factor that could favour translation of weaker mRNA such as Mpl cDNA was amplified from the platelets of 15 AMM patients along with those from 15 normal controls by RT-PCR, cloned into the Blue Script vector and the recombinant clones sequenced completely. Base changes were detected in some patients and controls as well in the exons 2,3, 4, 6 and 12 but not at the same nucleotide (data not shown). The same changes were however not observed on re-cloning the cDNA of the samples with mutations and sequencing the corresponding genomic region. These base changes were therefore considered to be due to PCR errors and not genuine mutations. Hence Mpl gene abnormalities were not detected in AMM patients.Mpl cDNA of 15 controls and 15 AMM patients in the pcDNA3 vector were subjected to in vitro transcription/translation employing the rabbit reticulolysates to see if they were capable of translation in vitro. Mpl from AMM patients were able to translate as efficiently as the cDNA from controls revealing their full potential for translation. Also, in the presence of canine microsomal membranes, the translated protein was glycosylated similar to those from the controls.About 1 μg of the Results from 2 controls and 4 AMM patients are represented in Fig. Mpl cDNA was tested for in vivo expression in the 293 T human embryonic kidney cells. Equal amount of Mpl cDNA from 15 AMM/15 controls was transfected into the 293 T cells and Mpl expression analysed by western blot as described for the platelets. The expression level of Mpl appeared to be similar between controls and AMM patients. Fig. AMM is one of the MPDs for which the molecular defect is unknown. A characteristic feature of the disorder is the presence of atypical megakaryocytes in high numbers and their autonomy or hypersensitivity to growth factors in vitro. Since the haematopoietic growth factor TPO that is essential for the development of megakaryocytes is present at high level in AMM patients, it is of interest to study the role of TPO and its receptor in AMM.Mpl displays characteristics of weak mRNA that are not translated very efficiently due to G-C rich 5' UTR [Mpl can be expected.We have earlier reported that AMM patients have elevated plasma TPO level and this is not associated with its enhanced transcription in the bone marrow cells ,17. To dh 5' UTR . The trah 5' UTR . Hence wMpl RNA level of AMM patients as shown by RT-PCR, we cloned and sequenced Mpl gene from these patients to over-rule any structural defects that could prevent translation. Although base changes were observed for some patients and controls as well, on sequencing the corresponding regions of the genomic DNA, the same base changes were not observed. Hence these were not considered to be genuine mutations. Taksin et al. [Mpl gene mutations in AMM patients. Hence to date, there are no reports describing Mpl gene mutations in AMM patients although an activating mutation in this gene has been reported by Ding J et al. [Mpl gene of African American patients with MPD that leads to substitution of the 39th amino acid Lysine, with Asparagine in the extra cellular domain of the protein. Patients with this polymorphism exhibited high platelet counts and low platelet Mpl protein. African Americans were however not represented amongst our patients tested. We also performed in vitro transcription/translation with the cloned cDNA from the AMM patients. Similar levels of proteins were formed irrespective of the source of the cDNA, indicating that the cDNA from AMM patients had no structural defects preventing its translation. There was no difference in the extent of glycosylation of the protein either when the reaction was performed in the presence of microsomal membranes capable of post-translational modification in vitro. To further confirm this in vivo, these cDNAs were transfected into 293 T human embryonic kidney cells and the cell lysates analysed by western blots for Mpl expression. Irrespective of the source of the cDNA, similar level of expression of Mpl protein was observed. Two bands were however detected. Since the antibody used can react with both glycosylated and non-glycosylated forms of Mpl, it is likely that the second band corresponds to non-glycosylated form. As the in vivo system is saturated with the over-expressed protein, the system for modification of the protein could be exhausted. Overall, Mpl gene from AMM patients does not seem to have any impaired structural features to prevent its transcription/translation.Since there was no significant difference in the n et al.  also havJ et al.  in a casJ et al.  have recMpl transcriptional inhibition and absence of any structural defects in Mpl coding region in AMM patients. However, there was no co-relation between TPO level and Mpl expression, similar to the observation of Harrison CN et al. [Our present study shows elevated TPO level; reduced Mpl platelet protein level; absence of N et al.  in ET paTPO transcription, since these growth factors have been shown to stimulate the transcription of TPO from the bone marrow stromal cells in cultures [Plasma TPO level is regulated by platelet counts and MK mass . TPO bincultures ,29. Our cultures  could beMpl transcription or re-cycling of the internalised receptor may be responsible for persistence of high plasma TPO level in AMM patients. Reduced Mpl level seen in AMM patients may be due to exhaustion of the Mpl pool by binding to the enhanced TPO and its subsequent catabolism. This gains support from an earlier observation in thrombocythemic mice wherein very high and persistent level of TPO due to its induced over expression were found to be associated with reduced platelet Mpl protein without any reduction in Mpl transcription [TPO 5' UTR from these patients may provide additional valuable information on elevated TPO levels since mutations in 5' UTR of TPO have been associated with elevated TPO levels without any increase in its transcription in patients with thrombocytosis [Enhanced expression of TPO and absence of an accompanying increase in cription . Also incription ,31. In vcription . Cloningocytosis ,33.Mpl cDNAs from AMM patients had full potential for transcription/translation including glycosylation, in vitro and in vivo, similar to those of normal controls. Reduced Mpl protein level may not be due to defects in its transcription/translation but could be due to increased internalisation or intrinsic defects in translation and glycosylation.Our studies with TPO/Mpl show elevated TPO and reduced Mpl level in AMM patients, without any significant co-relation in their expression levels. Peripheral blood was obtained from patients with AMM after informed consent and peripheral blood was obtained from normal volunteers to serve as controls. Five volumes of peripheral blood was mixed with 1 volume of ACD buffer pH 4.5–5.5  and centrifuged at 250 g for 10 minutes. The cell pellet was diluted 5X with Hank's buffer and subjected to Ficoll/Hypaque density gradient centrifugation. The ring of mononuclear cells was washed 2X with Hank's buffer and processed for isolation of genomic DNA using the Wizard Genomic DNA Purification kit from Promega, Madison, WI, following their instructions. The Platelet Rich Plasma (PRP) supernatant was centrifuged at 800 g for 10' to obtain the platelets. The Platelet Poor Plasma (PPP) was stored at -80°C, and the platelet pellet washed 2X with the Citrate buffer, pH 6.2 . They were then processed for RNA isolation using the Totally RNA isolation kit from Ambion, Texas, following their instructions or were suspended in 1X PBS and lysed with equal amount of 2X Laemelli buffer  for western blot analysis.TPO level in the blood plasma was estimated using the Human thrombopoietin Quantikine ELISA kit from R & D Systems, Minneapolis, MN. The assay is based on the two-sided sandwich principle. Standards and undiluted PPP samples from 10 normal controls and 20 AMM patients were incubated in micro-titer Plates whose wells are pre-coated with monoclonal TPO antibody. After washing off the unbound substances, the wells were incubated with polyclonal TPO antibody conjugated with HRP enzyme. After subsequent washes to remove any unbound antibody-enzyme, a substrate solution for HRP was added to the wells. The color developed that is proportional to the amount of TPO from plasma bound to the plate was quantitated using the Opsys MR plate reader.Mpl in platelets of 12 controls and 12 AMM patients, using the Geneamp 5700 SDS Instrument from Applied Bio-systems, Foster City, CA. Reagent for the assay was the Quantitect RT-PCR kit . Mpl mRNA in the platelets was reverse transcribed and PCR amplified from 10 ng of total RNA with gene specific primers and a florescent reporter probe that hybridises to the gene in between the two primers. The sequences of the primers were:Real-Time RT-PCR was performed to determine the expression of MPL FP 5'-AAGTCCTCAGAGAGGACTCCTTTG-3MPL RP 5'-CAGGCAAGAAGGCTGCAATC-3'MPL PROBE 5'-FAM CCTCCCAGGCCCAGATGGACTAC-3' BHQ1The reaction conditions were reverse transcription at 50°C for 30'; 40 cycles of amplification with de-naturation at 94°C for 15", annealing and extension at 60°C for 10".Mpl cDNA. First strand cDNA was synthesized using the SuperScript First Strand Synthesis System for RT-PCR from Invitrogen, Carlsbad, CA, following their specifications. About 3 μg of total RNA was mixed with 50 ng of random hexamers, and 1 mM dNTPs in 10 μl reaction volume and incubated at 65°C for 5' and left on ice for 1'. A cocktail mix of RT buffer, MgCl2 and DTT was added to a final concentration of 1X, 5 mM and 10 mM respectively along with 40 Units of RNase OUT Ribonuclease Inhibitor and incubated at 25°C for 2'. 50 Units of SuperScript II Reverse Transcriptase enzyme was added and incubated at 25°C for 10' and 42°C for 50'. The reaction was terminated by heating at 70°C for 15' and chilled on ice. 2 Units of RNase H was added and incubated at 37°C for 20' to remove the RNA from cDNA: RNA hybrids to increase the sensitivity of PCR from cDNA. Mpl was amplified using the Expand High Fidelity PCR kit from Roche, Indianapolis, IN, with gene specific primers containing EcoR 1 (FP) and Xho 1 (RP) Restriction Enzyme sites to enable directional cloning. The Restriction Enzyme sites are indicated in lower case in the Primer sequences given below.Total RNA extracted from platelets obtained from 15 patients with AMM and 15 normal controls was used to clone the full length FP 5'-CGgaattcGAAGGGAGGATGGGCTAAGGC-3'RP 5'-CCGctcgagAGTTTAGCTCTGTCCAGGGAA-3'EcoR 1 and Xho 1. The digested products were then cloned into Blue Script vector. The recombinants were checked by restriction analysis and the selected positive clones were sequenced completely at Northwoods DNA Inc., Becida, MN. Mpl cDNA were re-cloned from samples that had mutations and sequenced completely. The putative mutations were confirmed by sequencing the corresponding region of the Mpl gene from respective samples. For this, the genomic DNA isolated from the peripheral blood samples were PCR amplified with gene specific primers and the PCR products were directly sequenced after purification using the Wizard PCR Preps DNA Purification System from Promega, Madison, WI.The Products were purified using the Wizard PCR Preps DNA Purification System from Promega, Madison, WI, and digested with the Restriction Enzymes, Mpl cDNA clones in the Blue Script vector were digested with EcoR 1 and Xho 1 and the released Mpl cDNA was cloned into pcDNA 3 vector to obtain cDNA with 3' translational signals. These constructs were then subjected to in vitro transcription/translation using the TNT Quick Coupled Transcription/Translation Systems from Promega. Madison, WI, in the presence of 35S Methionine from Amersham Biosciences. About 0.5 μg of the constructs were incubated with the TNT Quick-Coupled Master Mix and 35S Methionine in the absence or presence of 2 μl of Canine microsomal membranes provided with the TNT Quick Coupled kit, at 30°C for 2 hours. The reactions were terminated by adding 100 μl of 1X SDS loading buffer  and stored at -20°C. Appropriately translated and processed products were then separated on a 6% polyacrylamide gel. The gel was dried using Model 583 Gel dryer from BIO-RAD, Hercules, CA. The products of translation were visualized by autoradiography of the dried gel. The bands were quantitated using the Image J program.The Mpl constructs of controls and patients used in the in vitro transcription/translation studies. The cells were seeded onto a 6 well plate at a density of 5 × 104 cells/well a day before transfection with DMEM medium containing 10% FBS. On the day of the transfection, the cells were washed with DMEM medium without serum and covered with 800 μl of the same. In an eppendorf tube, 1 μg of the DNA was mixed with 100 μl of serum free DMEM medium and 100 μl of DMEM containing 2 μl of Lipofectamine transfection reagent (Invitrogen, Carlsbad, CA) was added to this DNA. The mixture was incubated for 30' at room temperature and then added to the 800 μl of medium covering the cells. After incubating for 5 hours at 37°C the transfection medium was removed and replaced with DMEM medium with 10% FBS. The cells were harvested 48 hours post-transfection. They were washed twice with 1X PBS and the cells dislodged by gentle re-suspension. The cells were collected and centrifuged at 1000 RPM for 10'. The cell pellets were re-suspended in 100 μl of 1 X PBS each and lysed with 100 μl of 2X Laemelli buffer.293 T human embryonic kidney cells were used for the transient transfection studies with pcDNA3/The Transfection cell lysates/platelet cell lysates in 1X Laemelli buffer were boiled for 5', clarified by centrifugation at 14 000 RPM for 5', loaded onto a 6% SDS PAGE, and transferred onto immobilon nylon membrane. The membrane after transfer was rinsed with 1X PBS and incubated in the blocking solution  for 1 hr., at room temperature. The membrane was then incubated with 1:10 000 dilutions of Rabbit anti Mpl antibody from Upstate USA Inc. VA, over night at 4°C in the blocking solution. The membrane was then washed 4 X with 1X PBST  for 15' each and incubated with 1:5000 dilutions of HRP conjugated anti-rabbit secondary antibodies for 1 hr., at room temperature. Washes with 1X PBST were repeated and the membrane processed for detection using the Western Lightning Chemiluminescence Reagent Kit from Perkin Elmer, Boston, MA, following their recommendations. The bands were quantitated using the Image J program. Similar procedure was followed for the detection of eIF4E protein in the platelets except that a 10% SDS PAGE was used for separation of the proteins. The eIF4E antibody from Transduction Laboratories, CA, was used at 1:1000 dilutions.The author(s) declare that they have no competing interests.KCH performed most of the experiments and was responsible for acquisition, analysis and interpretation of the data in addition to preparation of the manuscript. JCW conceived, designed the study, provided patient samples for the study and critically reviewed the data. KS performed eIF4E western blot. GH performed the early work and helped in preparation of application for grant support. ADN was involved in critical revision of the article, in obtaining patients for the study and obtaining grant support.All authors read and approved the final manuscript.