The effects of diet-induced obesity on skeletal muscle function are largely unknown, particularly as it relates to changes in oxidative metabolism and morphology.Compared to control fed mice, mice fed a high fat diet  for 8 weeks displayed increased body mass and insulin resistance without overt fasting hyperglycemia (i.e. pre-diabetic). Histological analysis revealed a greater oxidative potential in the HFD gastrocnemius/plantaris  and soleus  muscles, but no change in fiber type percentages in tibialis anterior muscles compared to controls. Intramyocellular lipid levels were significantly increased relative to control in HFD gastrocnemius/plantaris, but were similar to control values in the HFD soleus. Using a novel, single muscle fiber approach, impairments in complete palmitate and glucose oxidation  with HFD were detected. These reductions were consistent with measures made using intact extensor digitorum longus and soleus muscles. Compared to controls, no difference in succinate dehydrogenase or citrate synthase enzyme activities were observed between groups in any muscle studied, however, short-chain fatty acyl CoA dehydrogenase (SCHAD) activity was elevated in the HFD soleus, but not tibialis anterior muscles. Despite these morphological and metabolic alterations, no significant difference in peak tetanic force or low-frequency fatigue rates were observed between groups.These findings indicate that HFD induces early adaptive responses that occur in a muscle-specific pattern, but are insufficient to prevent impairments in oxidative metabolism with continued high-fat feeding. Moreover, the morphological and metabolic changes which occur with 8 weeks of HFD do not significantly impact muscle contractile properties. Sedentary behavior and consumption of high-energy diets favor the early development of disease states such as obesity, insulin resistance, and ultimately type 2 diabetes mellitus. These activities have created a serious health crisis in our society. In the United States alone, it is estimated that approximately 57 million people have pre-diabetes (impaired glucose tolerance preceding type 2 diabetes mellitus development). Of this, over 2 million are under the age of 20 years old; an age group that until recently was generally unaffected by these disorders As skeletal muscle plays a major role in energy expenditure and insulin-stimulated glucose disposal, understanding changes that occur to this tissue with obesity and pre-diabetes development are critical to elucidating the underlying causes for insulin resistance and type 2 diabetes. Though a number of studies have investigated the effects diet-induced obesity on skeletal muscle oxidative capacity and insulin sensitivity, we are unaware of any that relate these changes with alterations in skeletal muscle morphology and functional capacity. Undertaking a comprehensive analysis in a variety of muscles is particularly important given that the disparities in model used, length and composition of diet intervention, muscles analyzed and analytical techniques have made comparisons between studies very challenging. For example, an increased Thus, it was the aim of the current study to comprehensively analyze skeletal muscle morphology, metabolism and contractile function in young adult skeletal muscle. Specifically, we assessed skeletal muscle glucose and fatty acid oxidation rates in isolated muscle fibers and in intact oxidative and mixed muscles along with key oxidative enzyme activities, skeletal muscle morphology, and contractile properties in mice fed either a high fat diet (HFD) or standard rodent chow (control) for 8 weeks. Our findings indicate that the skeletal muscle of mice with diet-induced obesity undergoes significant alterations in fiber type, fiber area and intramyocellular lipid (IMCL) levels and that these changes occur in a muscle-specific manner. However, complete glucose and palmitate oxidation rates were decreased in all muscles analyzed, suggesting that elevated IMCL levels and alterations in SCHAD activity do not solely explain the insulin resistance and impaired oxidative capacities. Moreover, peak tetanic force and overall fatigue rates were maintained despite significant changes in muscle morphology and oxidative capacity.Young adult mice fed a standard chow diet continued to gain weight during the first 4 weeks of experimental assessment, verifying that these mice were still within the growth and maturation phase of development . Mice coThere was an approximate 2.5-fold increase in epididymal fat mass  without There was no difference in fed blood glucose levels after 6 weeks of diet intervention  or fasted blood glucose levels after 7 weeks of diet intervention , time 0.In HFD gastrocnemius/plantaris muscles, type I and IIA fiber type proportions increased , while type IID and IIB fiber types were decreased in number . Considering that type IIA and IIB fibers represent the most oxidative and glycolytic fiber types in mouse skeletal muscle respectively Assessment of cross-sectional area per fiber type revealed no differences in the gastrocnemius/plantaris muscles .Histological staining for succinate dehydrogenase (SDH) activity in the control muscle was greatest in fibers identified by metachromatic stain as type IIA followed by IID≥I>IIB, respectively. This finding validated the fiber type (metachromatic) staining results. No significant differences in SDH enzyme activity were detected between HFD and control in either the gastrocnemius/plantaris or soleus muscles, regardless of fiber-type  were assessed using a novel, intact single muscle fiber protocol, as well as the well-established whole skeletal muscle preparation Complete glucose and fat oxidation  and SCHAD are key enzymes in the TCA (tricarboxylic acid) cycle and β-oxidation pathways, respectively. No difference between HFD and control muscle CS or SCHAD activity was observed in homogenates from the TA muscles . In homoAs mentioned previously, an SDH activity stain was undertaken. In fibers identified as type IIB by metachromatic staining, SDH staining was of the lowest intensity, while fibers identified as type IIA by metachromatic staining displayed the most intense SDH staining. Thus, SDH activity staining validated the fiber type data obtained by metachromatic staining. This analysis also allowed us to determine if fiber type specific adaptations to SDH enzymatic activity and mitochondrial content were occurring in HFD versus control muscle. No differences in mean SDH staining intensity were observed between HFD and control muscles in the soleus or gastrocnemius/plantaris muscles, regardless of fiber type .The peak tetanic force pre- and post-fatigue was not significantly different between control and HFD . When thHere we provide novel evidence that the skeletal muscles of mice fed a high fat diet for 8 weeks develop pre-diabetes, undergo muscle-specific morphological and enzymatic adaptations and exhibit impairments in complete glucose and fat oxidation. These changes in muscle morphology and metabolism did not have significant effects on peak tetanic force and low-frequency fatigue rates. These results demonstrate for the first time that skeletal muscle health is impaired in the pre-diabetic state and that despite these significant impairments in oxidative metabolism, there is a maintenance of muscle contractile properties.A significant muscle-specific shift towards a greater contribution of oxidative fibers was found in mice fed a HFD. In fact, the gastrocnemius/plantaris muscles increased the percentage of oxidative fibers, while the soleus increased fiber cross-sectional area and the TA displayed no fiber type change. This is in line with a recent study reporting that HFD led to increased soleus muscle fiber areas, but not fiber type proportions and no change in fiber type percentage or area in the EDL In our experiments, the mean intensity of SDH staining per fiber type was not different between control and HFD muscles, although soleus muscle had increased fiber cross-sectional area . If incrIn fact, IMCL levels were increased with HFD in this study, albeit in a fiber type and muscle-group specific manner. There were a number of ways in which an increased IMCL deposition was observed in this study including greater IMCL density (observed in the gastrocnemius/plantaris), increased oxidative muscle fiber area with unchanged IMCL density (observed in the soleus), and increased oxidative muscle fiber percentages (observed in the gastrocnemius/plantaris). Although our findings suggest an early attempt to enhance oxidation in response to high-fat feeding, after 8 weeks of such a diet a downward spiral seemed to develop leading to impaired glucose and lipid oxidation rates. This is consistent with previous observations showing time-dependent alterations in mitochondrial density or structure within the gastrocnemius muscles of mice fed a high-fat/high-sugar (HFHSD) diet In an attempt to address the apparent discrepancy between a shift towards an oxidative muscle phenotype and the reduced lipid and glucose oxidation rates, we assessed the activity of CS and SCHAD in muscles that either demonstrated an increase (soleus) or no change (TA) in oxidative potential in response to HFD. We did not find any significant differences in CS and SCHAD activities in the TA muscles of control and HFD mice. These results were consistent with the lack of change in fiber type proportion in this muscle. Interestingly, we found a significant increase in SCHAD, but not in CS activity, in the HFD soleus. Whether the increase in SCHAD activity in the HFD soleus is the result of the increased cross-sectional area and proportionate increase in mitochondrial content remains to be determined. However, since oxidative muscle fiber types increased in size (soleus) or number (gastrocnemius/plantaris) and a concomitant rise in SDH staining intensity was found, it suggests that 8 weeks of HFD did not decrease mitochondrial content. In fact, we would argue that the uniform increase in staining throughout the fibers is indicative of an increase in SDH content resultant from an overall increase in mitochondrial content and not solely increased SDH activity. Importantly, regardless of whether there was an increase in mitochondrial content or a fiber type specific increase in oxidative potential of muscles exposed to HFD, a significant impairment in complete glucose and palmitate oxidation was detected in our studies. These observations were made using a novel isolated single fiber technique and validated with the classical, isolated muscle methodology A number of studies have demonstrated that a prolonged exposure to elevated levels of fatty acids lead to insulin resistance and impair skeletal muscle glucose and lipid metabolism. The buildup of harmful lipid metabolites including long-chain fatty acyl CoA, diacylglycerol, and ceramides have been proposed to cause these deleterious metabolic effects in skeletal muscle Despite significant alterations in muscle morphology and metabolism, no significant impairment in peak tetanic force either pre- or post-fatigue was observed. However when we analyzed the force-frequency curves, we see that at all stimulation frequencies tested, HFD skeletal muscle consistently displayed reduced force production regardless of stimulation frequency in the pre-fatigue state (P = 0.089). We hypothesize that the early adaptations that occurred in response to HFD attenuated muscle force loss and continued exposure to a HFD would ultimately result in significant decreases in contractile force, consistent with that observed in humans Overall, the current study provides, for the first time, a comprehensive analysis of skeletal muscle morphology, metabolism and function following 8 weeks of high fat diet consumption. Our findings substantiate the proposal of deWilde and colleagues All experimental protocols were approved by the York University Animal Care Committee in accordance with Canadian Council for Animal Care guidelines.ad libitum access to water and food. After an initial acclimatization, animals  were randomly assigned to either a high fat diet  or standard mouse chow . Body mass and blood glucose  were assessed in the fed state on biweekly basis. Fasted body weight was assessed at 4 weeks (following an 8 hr fast) and 8 weeks (following a 16 hr fast) of diet intervention. Fasted (8 hr) plasma insulin was assessed at 4 weeks of diet intervention as described below for insulin from the intraperitoneal glucose tolerance test (IPGTT).Male C57BL/6J mice were obtained from Jackson Laboratories . Animals were housed in temperature and humidity-controlled facility with a 12/12 h light/dark cycle and had An IPGTT was performed on mice fasted overnight (16 hrs) after 7 weeks of diet intervention. Glucose was injected IP (2 g/kg of body weight) and blood glucose was assessed by tail bleeds at 0, 15, 30, 60, 90, 120, 150 min. Plasma was collected by tail bleed at 45 min and later analyzed for insulin, in duplicate, using 5 µl in the Ultra Sensitive Mouse Insulin ELISA Kit , according to the manufacturer's instructions.Following 8 weeks of diet, mice were fasted overnight (16 hrs) and weighed. Subsequently, mice were anaesthetized, the muscle stimulation protocol (described below) was performed and tissues were harvested. Immediately prior to the electrical stimulation protocol, the left and right tibialis anterior (TA), extensor digitorum longus (EDL), peroneus, and soleus muscles were removed from the muscle-stimulation leg (left). EDL and peroneus longus muscles were used for single fiber isolation and soleus was used for intact muscle oxidative capacity, snap frozen or mounted with tissue freezing medium and frozen in isopentane cooled by liquid nitrogen. The TA muscles were snap frozen for future analysis or mounted with tissue freezing medium and frozen in isopentane cooled by liquid nitrogen. Following electrical stimulation, the gastrocnemius/plantaris complex was weighed and then either mounted with tissue freezing medium and frozen in isopentane cooled by liquid nitrogen for subsequent histological analysis or snap frozen in liquid nitrogen for future analysis.Prior to surgery, mice were injected with ketamine/xylazine (150 mg/kg: 10 mg/kg) and the left gastrocnemius/plantaris complex was isolated from its distal insertion, attached to a force transducer and optimal voltage and length were determined Single skeletal muscle fibers were harvested from the EDL and peroneus longus muscles using a collagenase digestion protocol as previously described 14C]glucose (0.2 µCi/ml) + cold glucose (5.5 mM) for the determination of glucose oxidation or [1-14C]palmitic acid (0.15 µCi/ml) + cold palmitate (100 µM) complexed with fat-free BSA + L-carnitine (500 µM) for the determination of palmitate oxidation. Each well was incubated with the palmitate or glucose mixture for 2 hours in a closed system then the CO2 produced was assessed as previously described Approximately 18 hours following isolation, palmitate and glucose oxidation rates were assessed on groups of single fibers in 35 mm cell culture dishes. The 18 hour incubation period was critical to allow fibers to recover from the isolation procedure, settle onto the matrigel-coated dishes and allow any non-viable fibers to hypercontract and hence be removed with rinses. After the incubation period, wells were slowly rinsed three times with warm PBS and viable fibers were counted. On average, 15 to 30 viable, healthy fibers from each mouse muscle were used for oxidation rate assessment. Fiber viability was assessed by the presence of cross-striations along the length of fiber and the absence of sarcolemmal damage. Fibers were then serum-starved for 3 hours in low-glucose DMEM supplemented with sodium bicarbonate and pH adjusted. Following starvation fibers were incubated with either glucose (0.2 µCi/ml) + cold glucose (5.5 mM) for the determination of glucose oxidation and glycogen synthesis or [1-14C]palmitic acid (0.15 µCi/ml) + cold palmitate (0.2 mM) complexed with fat-free BSA + L-carnitine (500 µM) for the determination of palmitate oxidation. Assessment of the effects of insulin on glucose oxidation and glycogen synthesis was performed in the presence of 100 nM of the hormone.Following 8 weeks of diet intervention, mice were fasted overnight and anesthetized with ketamine/xylazine (150 mg/kg: 10 mg/kg) prior to removal of soleus and EDL muscles. Palmitate oxidation (N = 4 per muscle group), glucose oxidation (N = 4–6 per muscle group), and glycogen synthesis (N = 4–6 per muscle group) were assessed as previously described Determination of citrate synthase (CS) and short chain fatty acyl CoA dehydrogenase (SCHAD) was performed using pulverized TA (∼25 mg) or soleus (∼5 mg) muscle powder sonicated with 1∶20 (w/v) of extraction buffer as previously described i microscope and Q-Imaging MicroPublisher 3.3 RTV camera with Q-Capture software. All control and HFD images for each morphometric analysis were taken at the same exposure with the same microscope settings.Fiber type and IMCL were assessed using the metachromatic and Oil-Red-O staining methods respectively All statistical analyses were performed with GraphPad Prism 5 software. Differences between groups were determined using the appropriate student t-test, one-way or two-way ANOVA followed by Bonferonni post-hoc tests when appropriate. P values less than 0.05 were considered significant. All data presented are mean±standard error of the mean.


High resolution MS instruments perform routinely with a mass accuracy of < 5 ppm (parts per million) thus providing potentially a direct method for signal putative annotation using databases containing metabolite mass information. Most database interfaces support only simple queries with the default assumption that molecules either gain or lose a single proton when ionised. In reality the annotation process is confounded by the fact that many ionisation products will be not only molecular isotopes but also salt/solvent adducts and neutral loss fragments of original metabolites. This report describes an annotation strategy that will allow searching based on all potential ionisation products predicted to form during electrospray ionisation (ESI).Metabolomics experiments using Mass Spectrometry (MS) technology measure the mass to charge ratio  of molecular isotopes, salt adducts and neutral loss fragments. Correlation analysis of ESI-MS data features confirmed the predicted relationships of We conclude that although ultra-high accurate mass instruments provide major insight into the chemical diversity of biological extracts, the facile annotation of a large proportion of signals is not possible by simple, automated query of current databases using computed molecular formulae. Parameterising MZedDB to take into account predicted ionisation behaviour and the biological source of any sample improves greatly both the frequency and accuracy of potential annotation 'hits' in ESI-MS data. One advantage of MS over alternative spectroscopic methods such as Nuclear Magnetic Resonance (NMR) and Fourier Transform Infrared (FT-IR) is the opportunity to putatively annotate directly a spectral component by virtue of its atomic mass. In the context of a metabolomics experiment these 'first pass' annotations may be used to develop hypotheses relating to metabolite identity which are then tested by subsequent, more targeted, analytical chemistry methods. Traditional hyphenated MS profiling approaches provide simultaneous detection and quantification of discrete metabolite-derived peaks after chromatographic separation. In gas chromatography MS (GC-MS) a couple of hundred well resolved metabolite peaks are identified where possible by matching their positively charged ion spectrum (following fragmentation by electron impact in the gas phase) and column retention time to those of known standards 1-). Thus, in both fingerprinting and profiling approaches it is common to find adducts with either sample matrix components  or mobile phase solvents (e.g. [M + NH4]1+ in positive ion data). Additionally, although ESI is traditionally considered a 'soft' ionisation method a number of more sensitive metabolites will rearrange and fragment with neutral loss of common moieties such as water from a hydroxyl group [M - H2O + H]1+ or ammonia from an amine group [M - NH2 + H]1+ or formate from a carboxyl group [M - CO2H + H]1+. Clearly, it is possible also that a range of potential ionisation products will contain various combinations of isotopes, adducts and neutral losses. Finally, ionisation products also can carry more than one charge (e.g. [M + 2H]2+) or can, through non-covalent interactions, produce stable molecular clusters, for example dimers, in which only one component is charged (e.g. [2M + H]1+). The potential to form different ionisation products will be dependent on the structure and physical properties of individual metabolites.The past few years has witnessed a rapid increase in the number of publications describing experiments using particularly electrospray ionisation mass spectrometry (ESI-MS) atabases ,19-27. Watabases ,18 this atabases ,24 of com/z signals which make significant contributions to models explaining the metabolome differences between two biologically different sample classes 1+) with masses of 159.0764; as ammonium adducts are generally extremely rare in this matrix (unless part of the HPLC mobile phase) it is likely that the [M+H]1+ product is correct. The [M+H]1+ suggestion at 1 ppm for m/z 172.0007 is phosphoglycolohydroxamate which has a calculated monoisotopic mass of 172.0005, whereas a salt adduct ([M+K]1+) of aspartic acid or 2-hydroxysuccinamate are actually exact matches, and indeed much more common metabolites. A sodium adduct of proline betaine is an exact match for m/z 166.0839 and as it is a naturally charged molecule it will almost certainly predominantly be found as a salt adduct. Several isobaric metabolites are suggested for m/z 268.9461 when additional adducts were queried after initial annotation attempts using default PIPs found no matches. The importance of considering that major ionisation products could represent adducts or isotopes is highlighted further in Table m/z signals are likely to be common salt adducts or isotopes. The pre-analysis of a biological matrix can thus help to refine annotation exercises using MZedDB by including only adducts found to be prevalent in the specific matrix. In line with this ethos the MZedDB Adduct Manipulator function allows the investigators to expand the generation of possible adducts for a MZedDB entry or a given molecular formula (M->IP), with or without applying adduct formation rules. The reverse transformation (IP->M) can also be performed so that given the molecular formula of a potential ionisation product, all possible formulae of the parent compound can be enumerated.The parameterisation of MZedDB searches by selection of different PIPs has a significant effect on the outcome of the annotation exercise. For example Table pathogen . Searchi < 3 ppm , whereas and M+NH1+) with Ideally, MZedDB should be customised intelligently by selection of a subset of PIPs known to be abundant in the matrix under study and searches constrained to databases representing the organism in question. In circumstances where new biological matrices are investigated it may be helpful initially to use the MZedDB default settings in which three parameterisation boxes are automatically 'checked'  and a search of all database entries is activated from the drop down menu. If negative ion data is under investigation then Adducts default selection should be changed to negative mode. It may be helpful to change the default mass accuracy of 1 ppm to 5 ppm if accurate mass data from Time-of-flight (TOF) or hybrid Q-TOF instruments is used. If large numbers of annotation suggestions are returned then searches can be customised initially by restricting to entries in specific external databases by selecting one or more (using shift key) from the dropdown menu. Further reduction in numbers of annotation suggestions can be achieved by 'unchecking' the default selection boxes and then selecting a customised list of adducts from the pull down menu. Typically, in positive ion data selected adducts would include [M+H]1+, [M+Na]1+, [M+K]1+ and [M-H2O+H]+ and in negative ion data [M-H]1-, [M+Cl]1-, [M+Na-2H]1- and [M+K-2H]1- and [M-H2O-H]1-. Customisation could be extended sequentially as desired to include less common neutral losses (e.g. [M-NH2+H]1+ or [M-CO2H+H]1+), ion clusters (e.g. [2M+K]1+) or ions with multiple charges.p = < 0.0001) 'explanatory' positive ion m/z signals discriminating healthy from infected Brachypodium distachyon leaves 96 hours after infection with the rice blast fungus 1+ = 140.0682 and [M+K]1+ = 156.0421) as well as a neutral loss of water ([M-H2O+H]1+ = 100.0756) are predicted to be possible in addition to the parental pseudo-ion ([M+H]1+ = 118.0862). Further investigation using the isotope calculator confirmed that signals m/z 157.0455 and m/z 158.0402 . A PIP search of All databases used to construct MZedDB with the molecular formula C5H11KNO2 gave 16 entries corresponding to 10 metabolites; restriction of the database searches to just Grass potentially annotated this cluster of signals as being derived from either betaine or valine  are searched for. In addition to a standard Isotope ratio calculator as part of MZedDB development we have developed an 'adduct calculator' (operating in the R environment) which may be tailored to search for masses linked to any number of combinations of adducts, isotopes and neutral losses . Using ppathogen . In thise Figure .m/z annotation suggestions may often include a large number of structurally diverse but effectively isobaric candidates when only parental pseudo-ions  are considered as ionisation products. Although recent papers have stressed the importance of recognising isotopes to avoid miss-annotation of m/z signals in accurate mass LC-MS data [m/z signals lack annotation 'hits' if structures other than parental pseudo-ions are not included in the searchable databases. Thus we conclude that annotation decisions can be usefully guided by both determining from the outset whether any signal in question is actually an adduct, isotope or neutral loss fragment or indeed any combination of all three. Takahashi et al. [m/z annotations can be refined in a species specific context. An additional advantage of MZedDB centres on the ability to extend annotation searches to include a much larger range of adducts, neutral loss fragments and clusters by implementation  of a simple set of Potential Ionisation Product 'rules' which effectively filter searches to exclude unlikely candidates based on SMILES information and which can be customised in line with any prior knowledge concerning the matrix under analysis . Ultimately, metabolite identity assignment is crucial to derive biological meaning from metabolome modelling experiments and thus data annotation tools such as MZedDB which allow more intelligent searching need to be expanded to cover more comprehensively a wider range of natural chemistry and take into account the characteristics of new biological matrices. For example, to improve the analysis of human urine samples it is anticipated that future implementations of MZedDB will be extended to include any common biotransformations of parent metabolites  in attempts to link ionisation products to original metabolites.In high throughput LC-MS fingerprinting/profiling techniques utilising electrospray ionisation (ESI-MS) it is a common precaution to use analytical instruments at lower than maximal mass resolution to avoid problems with data alignment ,24. As a-MS data ,21,24-26i et al.  report ti et al. . MZedDB 5 and a mass resolution of 100,000 and data was recorded for 6 min per replicate infusion using Xcalibur software (Thermo Scientific). Blank quality control samples comprising extraction solvents were interspersed at random into the run sequence to monitor instrument performance and detect system peaks. Prior to any statistical analysis the data was log transformed to reduce the chance of the higher intensity peaks dominating in any multivariate analyses.The majority of data used to evaluate the functionality of the MZedDB annotation systems was generated on a Thermo LTQ instrument fitted with a 7-Telsa FT-ICR mass analyser. Extract preparation and basic instrument set up has been described previously  but the An FT-ICR-MS data set representing flounder liver extract generated by the SIM-stitching method  was kindBrachypodium distachyon) and potato tubers. The second type of samples were characterised by being part of a larger experiment that contained several biologically related sample matrices. For example a series of leaf sections harvested at different time points following infection of the grass B. distachyon with the rice blast pathogen [Brachypodium samples additionally allowed both a detailed analysis of signal correlation behaviour and provided sample populations for further supervised multivariate data mining [m/z) able to discriminate between the different diseased states.Data within each biological matrix class  were aligned and any peaks not represented in 70% of replicates were removed from the matrix. Two basic types of data sets were available for the project. The first type comprised a population of biological replicates representing a typical 'tissue' class; to provide some diversity the samples included fish liver (flounder), human urine, human blood plasma, plant leaves  and the inherent difficulties associated with matching chemical information from different chemoinformatics software, we adopted a common SMILES (Simplified Molecular Input Line Entry System) format generated with MolConverter (v. 5.l.4 )[Chemical structures and associated pathway and reactions when available were downloaded from the corresponding websites (see Table . 5.l.4 ).To enable comparisons across databases, we followed a multiple step strategy to clean up each entry. Ambiguities related to salts and complexes were removed by keeping the largest fragment. Structures containing less than 6 atoms, elements other than  and ambiguous fragments (e.g. R) were then systematically excluded. A third stage consisted of reducing a major source of discrepancies between databases resulting from the dual representation of neutral and ionic forms of the same entity by removal (positive ion) or addition (negative ion) of a hydrogen atom. Finally, each molecular entity was aggregated according to: (1) Any exact match identification number; (2) A selected name from the list of names given by the original source; (3) Aggregated list of all synonyms; (4) Entry SMILES; (5) Canonical SMILES. Whenever available, stereochemical information was retained during the curation process, giving rise to MZedDB redundancies . The provision of Canonical SMILES (i.e. representation without specified stereochemistry) allow proposition of alternative entries with similar chemical structure.dblinks functions to regroup the ID in the primary metabolite database for each MZedDB entry in order to generate dynamic hyperlinks to the original database. The table dbmetrule1 contains properties of each MZedDB entry that are required to perform the Potential Ionisation Product search. This table encapsulates molecular formula generated from the SMILES and the accurate monoisotopic mass computed to seven decimal places to avoid inaccuracies while rounding at a lower precision level. The remaining columns in dbmetrule consist of the overall charge and cardinalities of a predefined set of chemical groups necessary to apply adduct formation rule restrictions during Potential Ionisation Product (PIP) search. Metabolic pathway related information is contained in two tables. The table reac1 regroups the reaction description from each primary database . The table reac2 provides links for each MZedDB entry to reactions in which the compound is known to be involved.Alongside the MZedDB compound table, m/z annotation and provides links to primary database sources for known pathway/enzymatic information to help biological interpretation. Links to entries with the same skeleton  and molecular formula are also provided. A typical output file based on a query for information on pipecolic acid is presented [see Additional file As the initial goal of MZedDB was not to provide a chemoinformatics environment for metabolomics, any metabolite-related queries were reduced to elementary searches based on chemical composition, molecular weights and synonyms. A metabolite entry reflects chemical properties relevant to Primarily, MZedDB focuses on extensive PIP search capabilities  using anm/z range or nominal mass given the truncation value for binning. Further parameterisation of MZedDB is achieved by limiting to metabolites found only in specific organisms, groups of organisms or databases. Databases restrictions are obviously straightforward. Limiting search to metabolites found in specific organisms is achieved by linkage to KEGG information. Additionally, the search can be extended to the more general generation of acceptable PIP molecular formula given the overall charge, the number of non covalently bound units and a mass precision. Potential molecular formula of the parent compound deduced from the PIP table are used to search a local installation of PubChem (to avoid heavy traffic to the server).The annotation search can be parameterised by defining the level of mass resolution (in ppm), simply an • Project name: MZedDB• Project home page: • Operating system(s): Multiple platform (tested on Windows and Mac OS X).• Programming language: php, MySQL, Perl, C++• Other requirements: Java 1.3.1 or higher• License: None• Any restrictions to use by non-academics: NoneJD conceived of the study, and participated in its design and coordination and drafted the manuscript. DE conceived the original MZedDB architecture and table structure. DE, MB and DP were responsible for refining MZedDB query and output functions. DE developed software code for Compound Table construction, the Adduct Calculator, Isotope Calculator and Molecular Formula Generator and implemented the database web interface. MB and DP provided analytical chemistry and mass spectrometry data processing expertise for all stages of MZedDB design and implementation. DP generated and processed FT-ICR-MS data and led the effort to test MZedDB functionality with the participation of SS, HZ and JD. WL and DP carried out statistical analyses and participated in development of software code for investigating mathematical relationships of ESI-MS signals. All authors read and approved the final manuscript.Example MZedDB Metabolite Card. This document shows an example MZedDB Metabolite Card entry for pipecolic acid.Click here for file


Brain dopamine is implicated in the regulation of movement, attention, reward and learning and plays an important role in Parkinson's disease, schizophrenia and drug addiction. Animal experiments have demonstrated that brain stimulation is able to induce significant dopaminergic changes in extrastriatal areas. Given the up-growing interest of non-invasive brain stimulation as potential tool for treatment of neurological and psychiatric disorders, it would be critical to investigate dopaminergic functional interactions in the prefrontal cortex and more in particular the effect of dorsolateral prefrontal cortex (DLPFC) (areas 9/46) stimulation on prefrontal dopamine (DA).11C]FLB 457-PET following 10 Hz repetitive transcranial magnetic stimulation (rTMS) of the left and right DLPFC. rTMS on the left DLPFC induced a significant reduction in [11C]FLB 457 binding potential (BP) in the ipsilateral subgenual anterior cingulate cortex (ACC) (BA 25/12), pregenual ACC (BA 32) and medial orbitofrontal cortex (BA 11). There were no significant changes in [11C]FLB 457 BP following right DLPFC rTMS.Healthy volunteers were studied with a high-affinity DA D2-receptor radioligand, [11C]FLB 457-PET combined with rTMS may allow to explore the neurochemical functions of specific cortical neural networks and help to identify the neurobiological effects of TMS for the treatment of different neurological and psychiatric diseases.To our knowledge, this is the first study to provide evidence of extrastriatal DA modulation following acute rTMS of DLPFC with its effect limited to the specific areas of medial prefrontal cortex. [ Brain dopamine (DA) is implicated in the regulation of movement, attention, reward and learning Given the up-growing interest of non-invasive brain stimulation as potential tool for treatment of neurological and psychiatric disorders 11C]raclopride) for examination of DA-D2 receptors have not been useful in providing sufficient signal-to-noise ratio in regions outside the striatum with low D2-dopamine receptor density 11C]FLB 457 (KD = 20pM) has overcome this limitation and is enabling us to investigate the extrastriatal dopaminergic system. These dopaminergic ligands have shown significant dopaminergic changes in several cortical areas during both pharmacological challenge Today, the possibility of modulating the activation of a given cortical area in the human brain by using repetitive transcranial magnetic stimulation (rTMS) combined with positron emission tomography (PET) provides us with a valuable probe of brain function to investigate neural loops in human subjects. So far, commonly used PET radioligands  dopaminergic changes in the ipsilateral medial prefrontal cortex  and 2) potential differences and/or asymmetries between the two hemispheres.In this study, we used PET ligand [11C]FLB 457 binding potential (BP) in the ipsilateral subgenual ACC (BA 25/12), pregenual ACC (BA 32) and medial orbitofrontal gyrus (BA 11), likely reflecting dopamine release in those areas  = 15.01, P = 0.008), the pregenual ACC  = 155.64, P = 0.00002) and orbitofrontal gyrus  = 6.64, P = 0.04).Individual BPs extracted from ROI centered at the statistical peak defined by the parametric maps  confirmed these findings and showed significant BP reduction following left but not right DLPFC rTMS . Repeate11C]FLB 457 BP compare to control condition following left DLPFC rTMS in the ipsilateral the subgenual ACC , pregenual ACC  and medial orbitofrontal cortex . The mean magnitude of decrease in [11C]FLB 457 BP was −37.7±9.7% for subgenual ACC, −45.3±17.1% for pregenual ACC, and −23.6±7.4% for medial orbitofrontal cortex. In contrast, no significant BP changes were seen following stimulation of the right DLPFC compared to the control condition in the right subgenual ACC , right the pregenual ACC , and right medial orbitofrontal cortex   .To rule out a potential behavioral contribution to these findings, behavioral ratings before and after left or right DLPFC rTMS were measured and results are presented in 11C]FLB 457 PET study revealed two main findings. First, that DLPFC-rTMS led to focal DA changes in the ipsilateral ACC  and medial orbitofrontal cortex (BA 11) and second, that while stimulation paradigm and target cortical area were similar among all subjects, only left DLPFC but nor right DLPFC induced significant changes in [11C]FLB 457 BP in those areas.The present rTMS/[11C]FLB 457 BP may provide a reasonable estimate of receptor densities in different extrastriatal areas including cingulate cortex 18F]fallypride (a similar high-affinity dopaminergic radioligand) have confirmed these findings and showed that amphetamine challenge may induce a striking reduction in BP in the ACC (41%) and other extrastriatal areas 11C]FLB 457 ligand may be well-suited to capture differences in dopaminergic binding in prefrontal areas.Previous PET studies, have shown that raclopride PET during set-shifting task, our group found a significant hemispheric asymmetry A striking observation of our study was the asymmetric effect on dopamine release between left and right hemisphere. It is known that the rCBF changes induced by prefrontal rTMS differ upon hemisphere stimulated and vary with stimulation frequency Whether our observation of an asymmetric rTMS-induced release of dopamine in specific medial prefrontal areas may be associated with the different modulatory effect on executive performance and behavior reported in previous TMS reports cannot be established in the current study because our subjects were healthy controls, completely at rest and not engaging in any form of task. In addition, to rule out potential confounding factors to our findings, behavioral ratings before and after the left or right DLPFC rTMS were measured and statistical analysis did not reveal any significant effect in different behavioral aspect.125I]epidepride have shown that concentration of dopamine receptor in different cortical areas is considerably lower than in the ACC In the interpretation of our results, we should also keep in mind that methodological factors may have prevented to detected dopaminergic changes in other cortical areas. In fact, neurochemically, the medial prefrontal cortex (in particular the ACC) is an area with dense DA receptor concentration 11C]FLB 457 PET technique is most sensitive to extra-synaptic tonic dopamine release. Given the important role of dopamine in placebo and the potential implication of rTMS use on treatment, it would be natural to ask whether our findings could be explained by an effect of placebo. We believe that this is not case for several reasons. First, while placebo does well apply to a patient population where the expectation of clinical benefit does in fact play a major role It is well known that dopamine can be released via two main different mechanisms To our knowledge, this is the first study to provide evidence of extrastriatal DA modulation following acute rTMS of the DLPFC with its effect limited to the medial part of prefrontal cortex including pregenual, subgenual ACC and medial orbitofrontal cortex. PET imaging studies with dopaminergic high-affinity ligands combined with rTMS are a promising method for exploring specific cortical neural networks and their functional connectivity. Studies of neurochemical functions with rTMS may be useful for exploring hemispheric differences and the effects of these differences on striatal and extrastriatal dopaminergic system. This may help to better delineate the neurobiological effects of rTMS for the treatment of different neurological and psychiatric diseases.Seven right-handed young  healthy subjects were enrolled in this study. Exclusion criteria included history of psychiatric and/or neurological disorder (particularly epilepsy), any previous exposure to stimulant drugs, pregnancy and migraine. To rule out structural lesions in the brain and to provide anatomical reference for the analysis, T1-weighted high resolution MRI image  where obtained for each subject. Written informed consent was obtained in all cases before study enrollment. The study protocols were approved by the Ethical Committee of the Center for Addiction and Mental Health Research, University of Toronto. Each subject underwent two PET scans performed on separate days. On one day, the subject received right DLPFC stimulation; on the other day, the subject received left DLPFC. The two sessions were counterbalanced. Behavioral ratings were collected before and after the rTMS during each PET session.2 magnetic stimulator , using a figure-of-eight focal coil (70-mm diameter). The target area was localized on the individual MRI using the frameless stereotaxic system . The TMS coil was held in the scanner in a fixed position by a mechanical arm over the target area and positioning was monitored under real-time guidance using the neuronavigation system. The coil was oriented so that the induced-electric current flowed in a posterior-anterior direction which has been considered to be more effective in activating underlying cortical neurons The rTMS procedure and target area  were similar to those used in our previous studies 11C]FLB 457 were injected into the left antecubital vein over 60 seconds and 31 frames of dynamic scanning were acquired over 90 min PET scans were obtained with a high resolution PET CT, Siemens-Biograph HiRez XVI  operating in 3D mode with an in-plane resolution of approximately 4.6 mm full width at half-maximum. To minimize subject's head movements in the PET scanner, we used a custom-made thermoplastic facemask together with a head-fixation system . Following the acquisition of a scout view for accurate positioning of the subject, a low dose (0.2 mSv) CT scan for attenuation correction was conducted before the rTMS session. Within 5 minutes of the completion of the rTMS, 10mCi of [11C]FLB 457 BP of the ipsilateral (non-stimulated) hemisphere of the other session (control) . In the regions defined in our a priori hypothesis we performed a spherical volume correction (SVC radius 10 mm) and results were considered significant at cluster-based (family wise error - FWE) corrected P-value<0.05. A priori prefrontal areas were defined using the Brodmann's areas  included in WFU_PickAtlas (SPM extension toolbox). To confirm individual changes in binding, BPs were extracted from regions of interest  centered at the statistical peak defined by the parametric maps and a statistical analysis was performed with within-subject repeated-measures analysis of variance (ANOVA) with a 2 (rTMS site: left and right DLPFC rTMS)×2 (ROI site: left and right ROI) design for each of the three ROIs. A 2-tailed paired t-test (with Bonferroni corrections) was performed as post-hoc analysis to confirm the differences in BPs between rTMS and control condition for each ROI. Statistical analyses were performed with SPSS 13.0 software .After the realignment procedure for motion correction among the frames, motion corrected PET frames were summed, co-registered to the corresponding individual MRI and transformed into standardized stereotaxic space. The BP map in each subjects was generated by Pmod 2.9 , based on the simplified reference model control) . The imaSubjects completed behavioral questionnaires in which they rated the level of their comfort, fatigue, anxiety, mood, irritation and pain before and after each rTMS sessions. Ratings were made on a seven-point Likert scale ranging from −3 to 3, with −3 indicating the highest negative level and 3 indicating the highest positive level for each dimension.


Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1–22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases. MicroRNAs regulate the expression of genes in cells and are important in cancer development and progression. Designing new microRNA-based treatments requires the understanding of their mechanisms of action. Previous biological studies lack in depth since only a few genes are confirmed as microRNA targets. Additionally, key biological systems perturbed by altered microRNA functions in the context of cancer remain to be identified. Here, we demonstrate for the first time how genetic knowledge about the inheritance of cancer can be utilized jointly with data about the expression of genes in cancer samples to model deregulated microRNAs and their functions at multiple scales of biology. Our approach further uncovers previously unknown connections between microRNAs, their regulated genes, and their dynamics. Using head and neck cancer as a model, we predict the presence, functions, and gene targets of a new tumor suppressor microRNA in a cancer-associated chromosomal region where a candidate gene has not been identified. We then confirm their validity with extensive and thorough biological characterization and show attenuation of lung metastasis in mice. The discovery of molecular networks regulated by microRNAs could be exploited for the design of new treatments as an alternative to the single-gene target paradigm. Since the discovery of microRNAs as important regulators of broad biological processes in vivo metastatic model of head and neck cancer.To investigate microRNA function in HNSCC, we sought to develop an effective computational approach that is complementary to microRNA profiling and, in addition, is capable of simultaneously predicting tumor suppressor microRNAs as well as their functional targets from gene expression. In this report we illustrate how phenotypic knowledge of genetic disorders (OMIM database) can be utilized jointly with gene expression analyses to achieve this goal. Using this approach, we selected miR-204 among ten prioritized microRNAs for biological characterization, as miR-204 is located at the cancer-associated genomic region (CAGR) 9q21.1–q22.3 locus exhibiting high frequency of Loss of heterozygosity (LOH) in human HNSCC In summary, we show how such a high throughput system's strategy can accelerate the investigation of microRNA function in cancer by illustrating altered complex biological processes and regulatory pathways associated with microRNA dysfunction in cancer, by identifying among all putative microRNA gene targets only those that are dysregulated, and by elucidating molecular interactions underpinning microRNA regulation of malignant transformation and progression. The ability to characterize tumor suppressor microRNAs through a network analysis of mRNA expression datasets would be a major advance with potentially wide application. Further, we provide experimental evidence linking microRNA function to the genetic risk of HNSCC. We show at the LOH 9q21.1–22.3 locus, miR-204 could serve as a tumor suppressor of HNSCC oncogenesis and progression.A figure summarizing the main results and experimental approaches of this paper is included as Supporting Figure 1 in At the time of initiating this study, comprehensive analysis of microRNA expression profile in head and neck cancer (HNSCC) was not available and would have required time-consuming accruement of tumor tissues for conducting such analysis, a situation that is not limited to HNSCC research. We hypothesized that the development of a computational capability to simultaneously predict tumor suppressor microRNAs as well as their functional targets from more widely available genome-wide gene expression datasets could be an efficient reverse engineering approach for identifying deregulated microRNAs and their functional gene targets.P = 0.014; GSE8126: P = 0.0002 respectively, cumulative hypergeometric test, data not shown). A recent study also demonstrated the increased prediction specificity of microRNA and its gene target relationship via intersecting the results of multiple prediction algorithms We first developed IMRE, a statistical method to predict altered expression of microRNAs from genome-wide mRNA expression and putative microRNA targets databases ]. OMIM contains 610 biologically validated cancer genes among which 586 (96%) are predicted targets of 527 microRNAs in miRNOME. We observed that each of the 527 microRNAs could, on average, target 30 OMIM cancer genes (not shown). Thus, it is also unfeasible to manually select microRNA candidates from OMIM cancer genes for biological validation. Our analyses identified 46 microRNAs significantly enriched in the inheritable cancer gene subset of OMIM in the miRNOME  and is transcribed in the same direction as TRPM3 Second, in addition to the genomic imbalance at 9q21.1–q22.3 locus, chromosomal aberrations occur most frequently at 3p, 5q, 9p, 11q and 17p in HNSCC Third, while potential tumor suppressor gene candidates have been identified for other CAGRs in HNSCC, gene candidates possessing tumor suppressor activity associated with the 9q21 locus have not been identified. Thus the mechanisms by which changes at this locus affecting HNSCC oncogenesis remain uncharacterized. Fourth, the role of miR-204 in human cancer has not been established.We chose miR-204 among the ten prioritized microRNAs for thorough biological characterization based on the following considerations. We first examined miR-204 host gene TRPM3 expression by quantitative PCR (qPCR) and observed near complete TRPM3 suppression in four micro-dissected HNSCC tumors  and in aP = 0.014), kidney (P = 0.004) and prostate (P = 0.0001) tumors  tumors . AdditioAmong the 1,088 putative miR-204 targets predicted in the miRNOME, 34 mRNA transcripts that were significantly upregulated in HNSCC (GSE6631) led to the enrichment of miR-204  to enhance miR-204 function in these two cell lines. Restoration of miR-204 function achieved significant inhibition (between 30% to 75%) of endogenous mRNA expression in 18 out of 21 predicted targets examined for both cell lines, while non-specific control mimics had no significant effect . To identify genome-wide changes in PPINs associated with altered microRNA functions in HNSCC, we first integrated seven protein-protein interaction databases  and geneP = 8.7×10−8; bottleneck: P = 7.31×10−7; hub-bottleneck: P = 1.61×10−8; P = 0.002; Fisher's exact test, MMP9, SHC1, CDC25B and AURKB in P = 0.0009; hub-bottleneck: P = 0.022, We next analyzed two topological features of the PPIN: the “hub” and “bottleneck” properties. “Hubs”, the highly connected node proteins, and “bottlenecks”, the key connector proteins, are central to controlling the connectivity of biological sub-networks to one another In a protein-protein interaction network, proteins that are tightly linked are likely to function in the same biological process or pathways in vitro and SQ38 for in vivo characterization. The two cell lines were derived from nasal cavity and sinus HNSCC tumors, respectively  of the ability of JSQ3 and SQ38 cells to adhere to laminin-rich basement membrane  and micro-foci (indicated by arrows) in the paraffin embedded lung sections . In comparison, tumors in Cluster B were enriched with the Group 3 “normal epithelium-like subtype” tumors (P<0.011) To explore the clinical relevance of miR-204 down regulation in HNSCC, we conducted an unbiased hierarchical clustering analysis of 60 HNSCC tumors harvested from representative anatomical sites of HNSCC in GSE686 Here, we developed an efficient combined computational and biological approach to predict and to prioritize cancer microRNAs for biological investigation. We demonstrated this strategy as an effective economical alternative to comprehensive microRNA analysis in cancers such as HNSCC for which prior genomic array datasets (mRNA or microRNA) are less abundant. This approach also allowed the identification of functional gene targets of the deregulated microRNAs that would otherwise require paired profiling of mRNA and microRNA expression for which the feasibility is often limited by the additional costs, or by the lack of access to the tissue. Employing this method that integrates the analysis of microRNA target predictions, differential HNSCC gene expression and the cancer genes in the OMIM genetic dataset, we identified and characterized miR-204, located within its host gene TRPM3 at the 9q21.1–q22.3 region frequently incurring allelic loss Through enrichment analysis and network modeling using mRNA gene expression profile, we identified a set of functionally related miR-204 targets that showed increased mRNA expression in HNSCC upon miR-204 suppression . The prein vitro  probes whose average expression intensity are below the average background intensity, or ii) the probes whose inter quartile range (IQR) are lower than the median of the rest probe-set's IQR because they are less likely to be differentially expressed, and/or iii) to control for the bias of multiple probes per gene, the probe-sets with the largest IQR value were retained and the others were removed for the genes with multiple probe-sets.Expression processing. In sample j containing a total of G genes, each gene x is ranked by expression as G}, and scored according to an exponential weighted Equation 1) using an approach that we previously described to compare gene expression lists  of its targets according to the miRNOME . twilight, 1,000 permutation resampling, “paired t-test”for GSE6631, “unpaired t-test” for GSE2379 FDR) from the P-values of Equation 4 and used a 5% threshold for significance http://www.lussierlab.org/IMRE.OMIM) MicroRNAs most likely to regulate a large number of specific inheritable cancer genes were predicted using an enrichment statistics. The Online Mendelian Inheritance in Man (Equation 4) was applied to identify significantly enriched microRNAs. We calculated the P-values based on the Equation 4 with the following variables: N is the number of OMIM genes also found in the miRNOME , M is the number of genes associated to a specific cancer term in OncoMIM and also targeted by any microRNAs in the miRNOME, n represents the number of genes targeted by a specific microRNA in the miRNOME and also found in OncoMIM associated to any cancer term, m is the number of genes associated to both a specific cancer term in OncoMIM and to a specific microRNA in the miRNOME (m = M∩n).The cumulative hypergeometric distribution  P-values (p′) are less than 0.05 To control P-values derived from enrichment studies in ontologies  due to the inheritance of genes in ancestry classes of a significantly enriched class We developed an algorithm to identify and filter out false positive A gold standard of microRNAs deregulated in cancers was derived from the literature and was used to evaluate microRNA predictions in from OMIM cancer genes  was generated by integrating seven protein interactions and signaling datasets. Protein interactions from each dataset were standardized to a two-column list of pair wise interactions between SwissProt accession IDs, with an additional column providing the source dataset and references to the literature when available. An overview of the seven datasets used in this study is provided in Table 10 in The protein-protein interaction network . Thereafter, the same procedure was applied to the 10,000 permuted PPINs yielding control counts of distinct protein interactions for each of the UG (Control count of PI). Since each HNSCC protein had a constant node degree in each permutation (see the previous paragraph), this procedure controlled properly for HNSCC proteins having more protein interactions than others thus providing no statistical advantage to those better connected proteins (such as hub or bottleneck proteins). For each HNSCC protein, a P-value was assigned by measuring the frequency at which the “Observed count of PI” of that HNSCC protein occurred in the empirical distribution of 10,000 “Control count of PI” for these specific HNSCC proteins  was calculated by dividing the median number of proteins prioritized at that cutoff in the empirical distributions of permuted PPINs divided by the observed number of prioritized HNSCC proteins in the real PPIN. We refer to this approach as single protein analysis in the network (SPAN).Additionally, we developed a model that estimates the probability of occurrence of an observed Single Protein Network arising from the upregulated gene list between HNSCC and normal paired tissue in GSE6631. Each of these unregulated HNSCC gene was translated to its corresponding protein identifier in the network (HNSCC protein). Each HNSCC protein was mapped to each of the rest HNSCC proteins according to existing pairs of protein interactions in the original PPIN yielding an Observed number of distinct http://www.gersteinlab.org/proj/bottleneck/) A similar procedure was developed to calculate the FDR over a pair of protein interactors among the observed prioritized HNSCC proteins (FDR of links). A “Prioritized HNSCC PPIN”  was predTo determine whether microRNA targets in the HNSCC PPIN exhibit the genome-wide systems' properties of “hub” and “bottleneck” and their enrichment, we calculated the proportion of hub and of bottleneck proteins among microRNA targets present in the HNSCC PPIN for each microRNAs in the miRNOME. Thereafter, we conducted a non-parametric Wilcoxon Signed Rank Test comparing this frequency with the theoretic expectation that derives from a random draw (as defined in the previous paragraph: 20%).Using the miRNOME, we also calculated the number of distinct microRNAs that could potentially target the genes encoding for each protein of the PPIN. We subsequently obtained enrichment statistics of the hub and bottleneck properties related to microRNA regulation by comparing the count of microRNAs between hub proteins and non-hub proteins, between bottleneck and non-bottleneck proteins, as well as between hub-bottleneck and non hub-bottleneck proteins using the non-parametric Mann Whitney test. Calculations of these statistics were conducted with the GraphPad Prism software (version 4) To provide insights into biological functions and processes potentially regulated by miR-204 in HNSCC, we conducted standard statistical enrichment analyses based on the functional assignments of gene in Gene Ontology (GO) in vivoWe previously established 10 low passage human head and neck squamous cell carcinoma lines (HNSCC) , from head and neck tumor specimens of different head and neck primary sites Total RNA from normal and tumor tissues of esophagus, lung and cervix were obtained from the Ambion FirstChoice collection of RNA that is compatible with both mRNA and microRNA analysis.Total RNA from HNSCC cell lines, tumors and normal tissues was extracted and purified using TRIzol (Gibco/BRL) according to manufacturer's instructions. Tissues from primary HNSCC tumors were obtained from surgical procedures performed at our institution. Samples were snap frozen immediately in liquid nitrogen and stored at −80 °C. Laser micro-dissection was performed on frozen sections and approximately 10,000 cells were captured for RNA extraction. Normal buccal mucosa was obtained from healthy volunteers with no history of smoking and drinking according to an approved open IRB protocol.miR-204 expression was measured using TaqMan MicroRNA quantitative PCR (qPCR) assay (Applied Biosystems) according to manufacturer's instructions.. Real-time PCR was carried out using the Applied Biosystems 7900 Sequence Detector System (Applied Biosystems). All qPCR reactions were run in triplicate. Human TATA-binding protein (TBP) (Applied Biosystems) was used as an endogenous control for miR-204 expression normalization. The fold changes of miR-204 expression between normal and tumor tissues or cell lines were calculated using the ΔΔCt method of relative comparison.https://orf.invitrogen.com/lux/) and sequences provided in Table 13 in Text S2. The mean Ct (cycle threshold) was calculated from the triplicates and used for the calculation of RQ values. qPCR condition for each gene was optimized that so that the standard error among the triplicates was <0.15 Ct. TBP was also used as endogenous control for data normalization. The fold changes of target gene were calculated using the ΔΔCt method of relative comparison. In addition, as negative controls for the off target effect of miR-204 mimics treatment, real time qPCR was performed to include three additional endogenous controls: PPIA , GUSB  and, HPRT1 (Cat#4333768) using commercially designed Taqman gene expression assays (Applied Biosystems). Quantitative mRNA expression data were acquired and analyzed in either 96- or 384-well-plate format using an Applied Biosystems 7900 Sequence Detector System (Applied Biosystems).For mRNA expression quantification, First-strand cDNA synthesis was carried out as above described except that random primers were used for reverse transcription . Amplification of predicted miR-204 targeted genes was performed by Sybr Green qPCR assays using custom designed primers. Specific primers for each gene were designed using Invitrogen D-LUX Designer (In vivo tail-vein injection of mimics treated GFP-SQ38 cells was performed at 48h after transfection.40% confluent JSQ3 and SQ38 cells were transfected with 50–200 nM Control [Cat#110CN-001000-01] or miR-204 miRIDIAN mimics [Cat#110C-300069-02](Dharmacon) using Oligofectamine (Invitrogen). Transfection efficiency was optimized and estimated to be >90%. Proliferation assay, cell adhesion assay. Migration assay and Matrigel invasion assay were conducted at 72 hours after transfection. Cell adhesion was measured using the InnoCyte ECM cell adhesion assay kit  according to manufacturer's instructions. Control or miR-204 miRIDIAN mimics treated JSQ3 and SQ38 cells were trypsinized and re-suspended in fully supplemented medium. 20,000 cells and 15,000 cells were added to each well for JSQ3 and SQ38 cell lines, respectively. Cells were incubated for 2h at 37 °C. The plates were then washed with PBS to remove non-adherent cells. 100 µl Calcein-AM was added to each well, incubated with cells for 1h at 37 °C, and read with a fluorescent plate reader at an excitation wavelength of ∼485 nm and an emission wavelength ∼520 nm. Results were expressed as percent of cell adhesion compared to that of control mimics treated controls±standard error (SE) of 3 replicates.Control or miR-204 miRIDIAN mimics treated JSQ3 and SQ38 cells were trypsinized and re-suspended in fully supplemented medium. Cells were then seeded at 10,000 cells per well for migration assay or at 20,000 cells per well for invasion assay into trans-well inserts . For invasion assay, the trans-well inserts were coated with 60 µg/45 µl/well of Matrigel . Complete culture medium was used as chemo-attractant in the lower chamber. The assays were taken down with three PBS washes followed by fixation with 10% formalin and staining with 1% crystal violet after 6h for migration assay and 18h for invasion assay. The cells migrated to the basal side of the porous membrane was visualized with a Zeiss Axiovert microscope at ×20 magnification. 10 random fields from three replicate wells were counted and the number of cells that had migrated or invaded was presented as number of cells counted per field of the porous membrane.3 cells/well in 96-well plates and let incubated for 24 hours prior to treatment with control or miR-204 miRIDIAN mimics. After drug or siRNA exposure, 10 µl of MTT reagent was added to each well and incubated for 4h. The precipitates were dissolved in 100 µl of stop solution overnight and proliferation rate was determined by absorbance at 570 nm wavelengths with 690 nm as the reference wavelength using a spectrophotometer.Cell proliferation assays were conducted in 96-well format by the MTT assay. Specifically, HNSCC cell lines were seeded at 5×106 viable cells were re-suspended in 100 µl of PBS and injected into the lateral tail vein. Metastatic colonization of lung by GFP-SQ-38 cells was determined at 3 weeks post tumor injection.Animal work was conducted in accordance with an approved protocol. Age and weight-matched (4–6 weeks old weigh 18–20 g) NCI athymic female mice were used for induction of experimental lung metastasis via the tail-vein injection of tumor cells. GFP-SQ38 cells were treated with miR-204 miRIDIAN mimics or non-specific control mimics for 2 days prior to tumor cell inoculation. 1×1028 Mice were sacrificed on day 21 after tumor cell inoculation. Lungs were perfused through tracheal with 2–3 ml of PBS, excised and then fixed in 10% formalin for 12 hours. Prior to fixation with formalin, lungs were examined under 4× magnification using fluorescent stereoscope (Leica) and scored lobe by lobe for GFP-SQ38 lung foci on the whole lung surface. Thereafter, the University of Chicago Immunohistochemistry Core Facility performed paraffin embedding, sectioning and H and E staining. 5-micron sections were stained with Ki-67 and Ki-67 positive SQ-38 cells or micro-foci were scored under 40× magnifications in 10 randomly selected fields for each section. A total of 6 lungs from each treatment group were examined.Text S1Supplementary Figures 1–8(0.43 MB PDF)Click here for additional data file.Text S2Supplementary Tables 1–14(0.19 MB PDF)Click here for additional data file.Protocol S1Supplementary Protocols (sections A–D)(0.10 MB PDF)Click here for additional data file.Dataset S1OncoMIM Table: Cancer-related terms in OMIM(2.46 MB XLS)Click here for additional data file.


Differential gene expression and coding sequence evolution play complementary roles in the adaptive diversification of cichlid sensory systems. A major goal of evolutionary biology is to unravel the molecular genetic mechanisms that underlie functional diversification and adaptation. We investigated how changes in gene regulation and coding sequence contribute to sensory diversification in two replicate radiations of cichlid fishes. In the clear waters of Lake Malawi, differential opsin expression generates diverse visual systems, with sensitivities extending from the ultraviolet to the red regions of the spectrum. These sensitivities fall into three distinct clusters and are correlated with foraging habits. In the turbid waters of Lake Victoria, visual sensitivity is constrained to longer wavelengths, and opsin expression is correlated with ambient light. In addition to regulatory changes, we found that the opsins coding for the shortest- and longest-wavelength visual pigments have elevated numbers of potentially functional substitutions. Thus, we present a model of sensory evolution in which both molecular genetic mechanisms work in concert. Changes in gene expression generate large shifts in visual pigment sensitivity across the collective opsin spectral range, but changes in coding sequence appear to fine-tune visual pigment sensitivity at the short- and long-wavelength ends of this range, where differential opsin expression can no longer extend visual pigment sensitivity. The molecular mechanisms that generate biodiversity remain largely elusive. We examined how two of these mechanisms, changes in gene expression and changes in gene coding sequence, have generated an incredibly diverse set of visual systems in rapidly speciating African cichlids. We found large differences in cone opsin gene expression among cichlids inhabiting the clear waters of Lake Malawi. These changes are likely to have strong influences on retinal sensitivity and appear to be driven primarily by different foraging needs. Cichlids inhabiting the turbid waters of Lake Victoria, however, only expressed a subset of their opsin genes and variation in gene expression appears to by driven primarily by the spectrum of environmental light. When we compared the sequences of these opsin genes, we found greater variation in the genes at the ultraviolet and red edges of the sensitivity range. Taken together these findings suggest that changes in gene expression and coding sequence can be complementary and work in concert to generate changes in sensory systems. Because of their correlation with ecological factors, these changes are also likely to be adaptive and to have played a role in generating the tremendous diversity of cichlids in these two lakes. Alternatively, changes in gene coding sequence can alter protein function. The relative contributions of these mechanisms have been debated since King and Wilson proposed that functional species differences are largely the result of differential gene expression A very large body of literature has been dedicated to the geography, ecology, and genetics of adaptive diversification and speciation The visual system is ideal for investigating the molecular mechanisms of adaptation, because there is a direct link between genotype and phenotype However, fish have numerous opsin genes that have arisen through tandem gene duplications. These duplicate opsin genes have diverged to produce visual pigments that absorb maximally across the full spectral range, from the ultraviolet to the red  examine how changes in opsin gene expression contribute to the remarkable diversification of cichlid visual systems, (2) test whether changes in opsin gene expression are adaptive, and (3) compare the relative roles that differential opsin gene expression and changes in protein coding sequence play in the diversification of cichlid visual systems.Rh1) and six functionally and genetically distinct classes of cone opsin: SWS1 , SWS2B (violet), SWS2A (blue), Rh2B (blue-green), Rh2A (green), and LWS (red) Rh2Aα and Rh2Aβ together SWS opsins are expressed in morphologically distinct single cones, whereas the longer-wavelength Rh2 and LWS genes are expressed in double cones We quantified opsin gene expression in 54 wild-caught taxa from Lake Malawi and 11 lab-reared taxa from Lake Victoria  and S2. SWS1 or SWS2B opsins in their single cones, and fewer than half of these species (12/26) expressed the longer-wavelength LWS opsin in their double cones. Non-mbuna collectively expressed all three SWS opsins in their single cones, although the overwhelming majority of the species sampled (23/26) expressed LWS in their double cones . We therefore treated each localized population as a distinct group in subsequent analyses . Cichlids foraging on plankton and algae typically exhibited single-cone sensitivities peaking between 360 and 400 nm, such that they would be more sensitive to UV light than either piscivores or benthivores. SWS1 was the only opsin significantly associated with foraging preferences. We did not observe significant differences in opsin gene expression or single- and double-cone sensitivities among cichlids from different habitats  wavelengths from the open water site of Makobe to the sites of Python and Luanso, which were increasingly farther up the inlet of the Mwanza Gulf . We thenSWS2B opsin gene expression was positively correlated with predicted quantum catch , suggesting that SWS2B expression is increased in environments where it is predicted to capture more of the available light.Finally, we used water clarity and population-specific depth preferences to predict the quantum catch that an SWS2B-based visual pigment would have at the site where each taxon was originally sampled  and S4. In the spectrally broad and relatively homogenous environment of Lake Malawi , the estSWS1 opsin, which had seven variable transmembrane sites, of which three were in the retinal binding pocket. Both the LWS and Rh1 opsins exhibited four variable transmembrane sites, of which three and two, respectively, were in the retinal binding pocket. Among cichlids from Lake Victoria  collectively expressed all six opsins, but the middle- and longer-wavelength classes were predominant. Cichlids inhabiting the turbid waters of Lake Victoria express only four different classes of cone opsin. The shortest-wavelength single- and double-cone opsin genes were never expressed, and the longest-wavelength genes were expressed ubiquitously.When we estimated single- and double-cone sensitivities based on patterns of opsin expression, we found that the species fell into three distinct short-, middle-, and long-wavelength clusters. These clusters correspond well with the three “visual palettes” documented previously in these and other cichlid species using microspectrophotometry (MSP) SWS1 opsin gene, which encodes a UV-sensitive visual pigment, was differentially expressed between cichlids from different trophic groups in the clear waters of Lake Malawi. Species feeding on plankton or algae typically exhibited single-cone sensitivities peaking at shorter wavelengths than piscivores or benthic foragers. Studies of several teleost species, including two of the cichlids examined in this study, have demonstrated that UV sensitivity can increase the efficiency of foraging on zooplankton and other small organisms SWS1 opsin is highest precisely among cichlids foraging on these food sources  in single cones, and Rh2A (green) and LWS (red) in double cones—were predicted to produce visual pigments with the greatest quantum catches in all three of our representative light environments. However, our predictions also suggested that an SWS2B-based visual pigment (violet) would capture some of the available light in clear locations, but much less in turbid ones. SWS2B opsin gene expression varied across taxa, and this variation was positively correlated with predicted quantum catch. Taken together, our findings suggest that ambient light is driving opsin gene expression in Lake Victoria.Ambient light appears to have a strong influence on opsin expression in the spectrally narrow, longer-wavelength waters of Lake Victoria. We found that all of the Victorian species that we sampled exhibited similar expression profiles, with some variation in the expression of 1 fish from the same populations in Lake Malawi suggest that whereas levels of gene expression may change for some opsins in some species, expression of the shortest-wavelength SWS1 and SWS2B opsins is maintained in the lab . In sum, we feel that the lab rearing of Victorian samples is unlikely to influence our overall finding that differences in gene expression are adaptive.One potential limitation of our study was that the Malawian samples were wild-caught, whereas the Victorian samples were lab-reared in a common garden environment. Although lab rearing and light manipulations have been demonstrated to alter levels of opsin expression, photoreceptor abundance, and photoreceptor length LWS opsin result in smaller shifts (5–15 nm) in visual pigment sensitivity that are linked to differences in depth, water clarity, and male color LWS opsin gene is under strong selection and was shown recently to play a role in speciation in Victorian cichlids The rapid changes in opsin gene expression that we observed among these closely related cichlid species are unprecedented in vertebrates. Differential gene expression among these species produces large shifts in spectral sensitivities (up to 100 nm) that could modify a species' view of conspecifics or the natural scene, and so modify species behavior. In Lake Victoria, changes in the coding sequence of the SWS1 (UV) and LWS (red) opsins—as well as in the Rh1 (rod) opsin. Since the rod opsin is the only opsin expressed in cichlid rods, rods cannot use the mechanism of differential gene expression to tune visual pigment sensitivity. Likewise, differential gene expression cannot extend spectral sensitivity beyond the boundaries set by the opsin genes that encode the shortest- and longest-wavelength visual pigments (because there are no shorter- or longer-wavelength genes to turn on). Therefore, all three of these genes must utilize coding sequence changes to alter visual pigment sensitivity. This pattern of sequence diversity is consistent with previous evidence that selection is acting on these three opsin genes Opsin genes provide a clear example of how gene duplication and divergence in coding sequence can generate functional diversity in an adaptive phenotype In this study, we examined the different contributions that changes in gene expression and coding sequence make to the diversification of cichlid visual systems. Our results suggest a model in which both proximate mechanisms contribute to visual pigment diversity. This model contains three main features: (1) Differential gene expression can generate large shifts in visual pigment sensitivity (30–100 nm) across the combined opsin spectral range. (2) Coding sequence substitutions fine-tune visual pigment sensitivity (5–15 nm) around each opsin's ancestral sensitivity. (3) Changes in coding sequence are more prevalent in the opsins operating at the short- and long-wavelength ends of the visual range, where differential gene expression can no longer extend visual pigment sensitivity. Therefore, although tuning in the middle portion of the visible-light spectrum is achieved by shifts in opsin gene expression, tuning at the ends of the visible light spectrum is achieved via opsin sequence evolution.This model suggests that changes in gene expression and changes in protein coding sequence work in concert to generate phenotypic diversity. The extent to which our model can be applied to the visual systems of other teleosts, other sensory systems, or other genetic pathways remains to be seen. However, we predict that phenotypes influenced by multiple paralogous genes are likely to show similar patterns of expression and coding sequence evolution. We are currently examining the visual systems of Lake Tanganyika cichlids and damselfish. These two radiations are older than those in this study by one and two orders of magnitude, respectively, and will provide further tests for how coding sequence and gene expression interact in shaping visual phenotypes. Finally, we are performing genetic crosses to identify the specific loci that are responsible for the changes in gene expression that we observe. Understanding the timescales over which structural and regulatory changes act, and understanding the loci underlying regulatory changes, will provide further insights into when and how they work in concert to generate adaptive phenotypic change.Fish were euthanized according to University of Maryland Institutional Animal Care and Use Committee (IACUC)-approved protocol (R-09-73).n = 1–6 individuals per taxon) that were captured in the southern portion of Lake Malawi in 2005 from the south side of Thumbi West Island or off Otter Point. We also measured gene expression from 11 Victorian taxa  from four different genera with diverse foraging modes and habitats  until the time of analysis. Retinas were collected from adult fish, greater than 6 mo of age, when any ontogenetic changes would be complete Rh2Aα and Rh2Aβ opsin genes are genetically similar and produce visual pigments that differ in absorbance by only 10 nm Real-time PCR methods follow those previously optimized for cichlid opsins SWS1, SWS2B, and SWS2A for single cones; Rh2B, Rh2A, and LWS for double cones; see below for a justification of these assignments). This normalization procedure provides equal weighting to opsins expressed within single cones versus those expressed within double cones. We then used the normalized opsin expression data to calculate Euclidean distances between species and clustered them using Ward's method. We identified the optimal number of clusters resulting from this analysis using the Connectivity, Dunn, and Silhouette cluster validation indexes We clustered species with quantitatively similar opsin gene expression profiles via hierarchical clustering. However, because multivariate methods such as hierarchical clustering are sensitive to factors with relatively larger values Oreochromis niloticusmax) that is less than 460 nm, and all cichlid double cones have a λmax that is greater than 460 nm. Based on the λmax of heterologously expressed opsins from O. niloticusM. zebraSWS1, SWS2B, and SWS2A opsin genes are expressed in single cones, whereas Rh2B, Rh2A, and LWS are expressed in double cones.We calculated the average single- and double-cone sensitivities of all taxa in order to better understand how changes in gene expression might influence overall retinal sensitivity. First, we assigned opsin genes to cone types. Based on MSP data from 19 Malawian cichlid species if is the relative expression and λi is the λmax of one particular opsin max values from heterologously expressed O. niloticus opsins  O. niloticus (Nile Tilapia) is considered an outgroup to both radiations To calculate average single- or double-cone sensitivities, peak spectral sensitivities for each opsin were weighted by the fraction of their expression in each cone type using the following equations: Finally, although opsin expression and visual pigment sensitivity are tightly correlated max for each gene is the same for all species; and (2) the chromophore is A1  for all species. We have not attempted to estimate individual λmax values for each gene in each species for several reasons. First, we have not sequenced all the genes from all species. Second, we do not know the effects of all the sites, which vary across each of the opsins, and so would not be able to predict the exact λmax. However, based on the range of λmax values that have been estimated from MSP of 30 different cichlid species from Lakes Malawi and Victoria, the variation in λmax is relatively small: SWS1 371±8 nm, SWS2B 418±5 nm, SWS2A 455±5 nm, Rh2B 482±5 nm, Rh2A 528±6 nm, and LWS 565±9 nm , SWS2B (7 nm), and SWS2A (10 nm), but larger shifts for Rh2B (19 nm), Rh2A (35 nm), and LWS (60 nm) based pigments These single- and double-cone sensitivities were estimated based on two assumptions: (1) the visual pigment λWe used the phylogenetic comparative method F-statistics for ANOVA, corrected for phylogenetic nonindependence, were generated by simulation  of relative opsin gene expression levels and estimated single- and double-cone λmax values across the three trees listed above. These simulations followed an unbounded Brownian motion model of character evolution. All statistical analyses were performed using the stats functions and PHYLOGR A phylogenetic ANOVA was implemented in the program PDSIMUL v2.0 k, attenuation coefficient) and intercept (b) of a plot of ln(dI/I0) versus depth (d), where I0 is the initial, full-spectrum irradiance, and dI is the irradiance at depth. Transmission (T) at 2 m depth was then calculated using the equation T = ek*d+b) using Subspec, a submersible Ocean Optics (USB 2000) spectrometer fitted with a 100-µm fiber and a cosine collector. These data were used to determine the slope (I0. The same I0 (from Zimbawe) was used for both Malawi and Victoria to remove any daily variation and focus only on differences in water properties.Victorian water measurements were taken at Makobe Island, a relatively clear location, Python Island, a turbid location, and Luanso Island, an extremely turbid location. Transmission was measured at a depth of 2 m for all three locations, using an AvaSpec 2048 212 spectrophotometer with a 10 m fiber cable (100 µm) and SpectraWin 4.16 software (Avantes). Measurements were taken in the shade, between 8h30 and 9h00 in the morning. Irradiance was then calculated by multiplying T by Q) that a visual pigment containing each opsin gene would have at each location in Lake Malawi and Victoria using the following equation:I(λ) is the incident solar irradiance at the surface (measured at Zimbawe Rock), Tw is the light transmission of the water to a depth (d = 2 m), and R(λ) is the photoreceptor absorption calculated using equations from Govardovskii et al. We estimated the quantum catch Click here for additional data file.Figure S2Trees used for phylogenetically corrected statistical methods.(0.03 MB PDF)Click here for additional data file.Figure S3Ds) and nucleotide diversity (π) of each opsin gene.Synonymous substitution rates ((0.04 MB PDF)Click here for additional data file.Table S1Lake Malawi and Victoria species analyzed using real-time PCR.(0.06 MB PDF)Click here for additional data file.Table S2Accession numbers of all opsins included in this study.(0.06 MB PDF)Click here for additional data file.Table S3Summary of the phylogenetic ANOVA results. These analyses compared relative opsin expression and single- and double-cone sensitivity to foraging mode and habitat among cichlid species from Lake Malawi using three different phylogenetic hypotheses (potheses .(0.05 MB PDF)Click here for additional data file.Table S4Relative SWS2B-based visual pigment quantum catch, location, depth, and Secchi disc readings (cm) for Victorian taxa. (0.01 MB PDF)Click here for additional data file.Table S5Summary of amino acid variation in cichlid opsin genes from Lakes Malawi and Victoria.(0.05 MB PDF)Click here for additional data file.Table S6Substitutions between amino acids with different physical properties that were located in the transmembrane region.(0.06 MB PDF)Click here for additional data file.Table S7Accession numbers for mtDNA sequences used to generate phylogenies for the comparative methods in this study.(0.01 MB PDF)Click here for additional data file.Table S8Cluster validation statistics for the opsin expression and the single- and double-cone sensitivity clusters.(0.01 MB PDF)Click here for additional data file.Text S1Variation at known spectral tuning sites. (0.02 MB PDF)Click here for additional data file.Text S2Discussion and detailed description of the phylogenetic and comparative methods used in this study.(0.02 MB PDF)Click here for additional data file.