Multiple reaction monitoring to identify sites of protein phosphorylation with high sensitivity

Phosphorylation governs the activity of many proteins. Insight into molecular mechanisms in biology would be immensely improved by robust, sensitive methods for identifying precisely sites of phosphate addition. An approach to selective mapping of protein phosphorylation sites on a specific target protein of interest using LC-MS is described here. In this approach multiple reaction monitoring is used as an extremely sensitive MS survey scan for potential phosphopeptides from a known protein. This is automatically followed by peptide sequencing and subsequent location of the phosphorylation site; both of these steps occur in a single LC-MS run, providing greater efficiency of sample use. The method is capable of detecting and sequencing phosphopeptides at low femtomole levels with high selectivity. As proof of the value of this approach in an experimental setting, a key Schizosaccharomyces pombe cell cycle regulatory protein, Cyclin B, was purified, and associated proteins were identified. Phosphorylation sites on these proteins were located. The technique, which we have called multiple reaction monitoring-initiated detection and sequencing (MIDAS), is shown to be a highly sensitive approach to the determination of protein phosphorylation.     

Using abundance and habitat variables to identify high conservation value areas for threatened mammals

The present study used abundance and habitat variables to design High Conservation Value Forests for wildlife protection. We considered great apes (Gorilla gorilla gorilla and Pan troglodytes troglodytes) as model species, and we used nest surveys, dietary analysis and botanical inventories to evaluate whether the traditional methods that use abundance data alone were consistent with the survival of the species. We assumed that setting a local priority area for animal conservation can be made possible if at least one variable (abundance or habitat variables) is spatially clustered and that the final decision for a species may depend on the pattern of spatial association between abundance, nesting habitat and feeding habitat. We used Kernel Density Estimation to evaluate the spatial pattern of each biological variable. The results indicate that all three variables were spatially clustered for both gorillas and chimpanzees. The abundance variables of both animal species were spatially correlated to their preferred nesting habitat variables. But while the chimpanzee feeding habitat variable was spatially correlated to the abundance and nesting habitat variables, the same pattern was not observed for gorillas. We then proposed different methods to be considered to design local priority areas for the conservation of each great ape species. Alone, the abundance variable does not successfully represent the spatial distribution of major biological requirements for the survival of wildlife species; we, therefore, recommend the integration of the spatial distribution of their food resources to overcome the mismatch caused by the existence of a biological interaction between congeneric species.     

Multiple antibiotic resistance indexing of coliforms to identify high risk contamination sites in aquatic environment

Bacteriological analysis of the water samples collected from upstream, midstream and downstream points along the bank of the river revealed high populations of Escherichia coli, Citrobacter freundii, Citrobacter diversus, Enterobacter aerogens and Klebsiella species. All these isolates were screened against eight antibiotics to determine the prevalence of multiple antibiotic resistance among isolates at different sites of the river. The study revealed that multiple antibiotic resistance was prominently seen in coliforms at downstream sites (Average multiple antibiotic resistance index, MAR Index = 0.43) while it was low in coliforms at upstream sites (MAR Index = 0.15). These differences in MAR indices provide a method for distinguishing high risk contamination sites in aquatic environment.     

Using forest history and spatial patterns to identify potential high conservation value forests in Romania

Naturally dynamic forests have a high proportion of biotopes with old large trees, diverse vertical and horizontal structure at multiple scales, and much dead wood. As such, they provide habitat to species and ecosystem processes that forests managed for wood production cannot provide to the same degree. Whether termed old-growth, ancient, virgin, intact, primeval or continuity forests, a major challenge and need is to map such potential high conservation value forest for subsequent inclusion in functional habitat networks for biodiversity conservation in forest landscapes. Given that the delivery time of natural forest properties is much longer than of industry wood, we explore the usefulness of using historical maps to identify forests that have been continuously present for 220 years (potential old-growth) versus 140 years (potential aging forest) in a case study in the Romanian Carpathian Mountains (see Online Resource 1). While the total forest cover increased by 35 % over the past two centuries, the area of potential aging and potential old-growth forest declined by 56 and 34 %, respectively. Spatial modelling of edge effects and patch size for virtual species with different requirements indicated an even greater decrease in the area of functional habitat networks of old-growth and ageing forest. Our analyses show that compared to simple mapping of potential high conservation forests, the area of functional habitat patches is severely overestimated, and caution is needed when estimating the area of potential high conservation value forests that form functional habitat networks, i.e. a green infrastructure. In addition, the landscape and regional scale connectivity of patches needs to be considered. We argue that the use of historical maps combined with assessment of spatial patterns is an effective tool for identifying and analyzing potential high conservation value forests in a landscape context.     

Using probability of persistence to identify important areas for biodiversity conservation

Most attempts to identify important areas for biodiversity have sought to represent valued features from what is known of their current distribution, and have treated all included records as equivalent. We develop the idea that a more direct way of planning for conservation success is to consider the probability of persistence for the valued features. Probabilities also provide a consistent basis for integrating the many pattern and process factors affecting conservation success. To apply the approach, we describe a method for seeking networks of conservation areas that maximize probabilities of persistence across species. With data for European trees, this method requires less than half as many areas as an earlier method to represent all species with a probability of at least 0.95 (where possible). Alternatively, for trials choosing any number of areas between one and 50, the method increases the mean probability among species by more than 10%. This improvement benefits the least-widespread species the most and results in greater connectivity among selected areas. The proposed method can accommodate local differences in viability, vulnerability, threats, costs, or other social and political constraints, and is applicable in principle to any surrogate measure for biodiversity value.     

The cost-effectiveness of using raptor nest sites to identify areas with high species richness of other taxa

Given the limited resources available for conservation, it is important that the areas to preserve are selected in a cost effective manner. However, the cost effectiveness of the surrogate species strategy (the use of information on one or more species to identify areas of value for other species for which there is no, or more limited, available information) has seldom been evaluated.In this study, we investigate the opportunity cost of setting aside breeding sites of two forest raptor species (the surrogate species) by evaluating their individual and combined contribution to preserve diversity of polypores (wood-decaying fungi) and birds against the contributions of previously established nature reserves. We use numeric optimization models to compare different reserve selection strategies.Site selection based on nest sites of the dominant raptor species was more cost-effective than strategies using sites of the subordinate species or those processes previously used to select nature reserves in Finland. The inclusion of both raptor species in the reserve selection model further improved its performance relative to other approaches. This indicates that the means by which Finnish reserves are selected could be enhanced by including the breeding sites of these, and maybe other species, among the criteria used to select reserves in the future.These results show that information on charismatic and well-surveyed species could be a cost-efficient add-on to help enhance conservation endeavours. Where there is inter-specific competition for biodiverse sites, and using multiple species is costly, basing reserve selection primarily on breeding sites of a dominant species may be the best strategy. However, further work is required to establish the extent to which dominant species are typically better indicators of conservation relevance.     

Exploiting sequence and structure homologs to identify protein-protein binding sites

A rapid increase in the number of experimentally derived three-dimensional structures provides an opportunity to better understand and subsequently predict protein-protein interactions. In this study, structurally conserved residues were derived from multiple structure alignments of the individual components of known complexes and the assigned conservation score was weighted based on the crystallographic B factor to account for the structural flexibility that will result in a poor alignment. Sequence profile and accessible surface area information was then combined with the conservation score to predict protein-protein binding sites using a Support Vector Machine (SVM). The incorporation of the conservation score significantly improved the performance of the SVM. About 52% of the binding sites were precisely predicted (greater than 70% of the residues in the site were identified); 77% of the binding sites were correctly predicted (greater than 50% of the residues in the site were identified), and 21% of the binding sites were partially covered by the predicted residues (some residues were identified). The results support the hypothesis that in many cases protein interfaces require some residues to provide rigidity to minimize the entropic cost upon complex formation.     

Predictive value of weight-for-age to identify overweight children

Objective: The objective was to assess the predictive value of weight‐for‐age to identify overweight children and adolescents in the unusual research or public health situations where height is not available to calculate BMI. Research Methods and Procedures: Data from the National Health and Nutrition Examination Survey 1999 to 2004 were used to calculate the sensitivity, specificity, and positive and negative predictive values of selected weight‐for‐age cut‐off points to identify overweight children and adolescents (as defined by BMI ≥95th percentile). Positive and negative predictive values are dependent on prevalence and are reported here for this study population only. Results: The 50th and 75th weight‐for‐age percentiles had good sensitivity (100% and 99.6%, respectively), but poor positive predictive value (23.7% and 37.0%, respectively), while the 95th and 97th percentiles had reasonable positive predictive value (80.3% and 91.5%, respectively), but limited sensitivity (82.0% and 66.7%, respectively) to identify overweight subjects. The properties of weight‐for‐age percentiles to identify overweight subjects differed between sex, age, and race/ethnicity but remain within a relatively narrow range. Discussion: No single weight‐for‐age cut‐off point was found to identify overweight children and adolescents with acceptable values for all properties and, therefore, cannot be used in the clinical setting. Furthermore, the positive predictive values reported here may be lower in populations with a lower prevalence of obesity. However, in unusual research or public health situations where height is not available, such as existing databases, weight‐for‐age percentiles may be useful to target limited resources to groups more likely to include overweight children and adolescents than the general population.     

Conserving freshwater biodiversity: The value,status and management of high quality ditch systems

Freshwater biodiversity is globally threatened and while most conservation efforts are focussed on natural and larger freshwater systems such as rivers and lakes, in many lowland agricultural landscapes artificial water bodies including ditches may be equally important as habitats for freshwater species. Ditches occur across the agricultural landscape but in particular, those associated with coastal and floodplain grazing marsh, have high conservation value. The importance of this habitat for rare and threatened species afforded priority status under the UK Biodiversity Action Plan is explored. The characteristics of ditches that have high conservation value are described and a set of targets against which such ditches can be assessed are presented. An analysis of the current condition of Sites of Special Scientific Interest (SSSI) for the wider coastal and floodplain grazing marsh habitat demonstrates the range of pressures affecting these sites and highlights that alongside generic freshwater issues such as eutrophication and non-native species, these sites have a unique set of pressures associated with their ongoing management and the vulnerable location of many sites at the coast. Wider conservation strategies for freshwater biodiversity in lowland landscapes across Europe need to factor in the different management requirements of artificial habitats such as ditches alongside more ambitious restoration projects for natural waterbodies. In low lying coastal areas the threat of coastal squeeze for many important grazing marshes will require a strategic approach to allow upstream migration of important biodiversity.     

Ecosystem functioning and intrinsic value of biodiversity

Trying to show the importance of biodiversity for ecosystem functioning, ecologists are repeatedly looking for a possible connection between species diversity and intensity of various ecosystem processes. However it appears that simple "proof" of such a connection cannot easily be demonstrated and involves a lot of contingencies. The different meanings of "ecosystem functioning" may be crucial for attempts to show the importance of biodiversity and to assess possible redundancy. If "ecosystem functioning" means only total production of organic matter or consumption of CO₂ then some degree of redundancy in species diversity of autotrophs will be obvious in most cases. However if "ecosystem functioning" includes the synthesis of all compounds that plants, animals and other organisms of a given community contain in their bodies or release in the environment, then any decrease in species diversity will be meaningful and any redundancy will be impossible by definition. In accordance with such a definition biodiversity obviously cannot be diminished without some loss of ecosystem functioning. I emphasize that attempts to conserve biodiversity do not need special justification in possible relationships between diversity and ecosystem services. If biodiversity has intrinsic value it means that it could in principle be "useless" for human needs or for "ecosystem functioning".     

Using neutral landscapes to identify patterns of aggregation across resource points

Many organisms are aggregated within resource patches and aggregated spatially across landscapes with multiple resources. Such patchy distributions underpin models of population regulation and species coexistence, so ecologists require methods to analyse spatially‐explicit data of resource distribution and use. I describe a method for analysing maps of resources and testing hypotheses about how resource distribution influences the distribution of organisms, where resource patches can be described as points in a landscape and the number of organisms on each resource point is known. Using a mark correlation function and the linearised form of Ripley's K‐function, this version of marked point pattern analysis can characterise and test hypotheses about the spatial distribution of organisms (marks) on resource patches (points). The method extends a version of point pattern analysis that has wide ecological applicability, it can describe patterns over a range of scales, and can detect mixed patterns. Statistically, Monte Carlo permutations are used to estimate the difference between the observed and expected values of the mark correlation function. Hypothesis testing employs a flexible neutral landscape approach in which spatial characteristics of point patterns are preserved to some extent, and marks are randomised across points. I describe the steps required to identify the appropriate neutral landscape and apply the analysis. Simulated data sets illustrate how the choice of neutral landscape can influence ecological interpretations, and how this spatially‐explicit method and traditional dispersion indices can yield different interpretations. Interpretations may be general or context‐sensitive, depending on information available about the underlying point pattern and the neutral landscape. An empirical example of caterpillars exploiting food plants illustrates how this technique might be used to test hypotheses about adult oviposition and larval dispersal. This approach can increase the value of survey data, by making it possible to quantify the distribution of resource points in the landscape and the pattern of resource use by species.     

Evaluation of the criteria to identify single-fibre potentials in human muscle fibres

The criterion normally used to identify a potential generated by a single muscle fibre (SFAP) is that it must have identical shape at consecutive discharges. Technical problems accompanying the recording of single-fibre electromyographic (SFEMG) potentials introduce certain variability in the shape of these potentials, thereby compromising the ability to detect pure SFAPs. This study aims to determine the conditions necessary for two fibres to generate a compound potential that fulfils the single-fibre criterion. This has been done by analysing the alterations in the waveform of compound spikes formed by the summation of two SFAPs whose relative weight in the composite potential can differ considerably. Several factors responsible for this shape variability, with a geometrical, physiological or accidental origin, have been included in our study. It has been shown that a distant interfering component will be hardly detected in the composite potential if it is smaller than approximately 15?% of the main component. For this interfering component to generate a notch in the rising phase of the compound potential, it must be greater than about 30?% of the main component. A compound potential will fulfil the single-fibre criterion if the time dispersion between the individual components is less than 80-120?μs. These results permit the estimation of the amplitude of interfering potentials so they could be useful in fibre density studies. The article also emphasises the inherent variability of SFEMG potentials and the impact of this variability on jitter estimation.     

Mapping of FSHR agonists and antagonists binding sites to identify potential peptidomimetic modulators

Owing to the critical role of follicle stimulating hormone receptor (FSHR) signaling in human reproduction, FSHR has been widely explored for development of fertility regulators. Using high-throughput screening approaches, several low molecular weight (LMW) compounds that can modulate FSHR activity have been identified. However, the information about the binding sites of these molecules on FSHR is not known. In the present study, we extracted the structural and functional information of 161 experimentally validated LMW FSHR modulators available in PubMed records. The potential FSHR binding sites for these modulators were identified through molecular docking experiments. The binding sites were further mapped to the agonist or antagonist activity reported for these molecules in literature. MD simulations were performed to evaluate the effect of ligand binding on conformational changes in the receptor, specifically the transmembrane domain. A peptidomimetic library was screened using these binding sites. Six peptidomimetics that interacted with the residues of transmembrane domain and extracellular loops were evaluated for binding activity using in vitro cAMP assay. Two of the six peptidomimetics exhibited positive allosteric modulatory activity and four peptidomimetics exhibited negative allosteric modulatory activity. All six peptidomimetics interacted with Asp521 of hFSHR(TMD). Several of the experimentally known LMW FSHR modulators also participated in H-bond interactions with Asp521, suggesting its important role in FSHR modulatory activity.     

Using core hydrophobicity to identify phosphorylation sites of human G protein-coupled receptors

As the most frequent drug target, G protein-coupled receptors (GPCRs) are a large family of seven trans-membrane receptors that sense molecules outside the cell and activate inside signal transduction pathways. The activity and lifetime of activated receptors are regulated by receptor phosphorylation. Therefore, investigating the exact positions of phosphorylation sites in GPCRs sequence could provide useful clues for drug design and other biotechnology applications. Experimental identification of phosphorylation sites is expensive and laborious. Hence, there is significant interest in the development of computational methods for reliable prediction of phosphorylation sites from amino acid sequences. In this article, we presented a simple and effective method to recognize phosphorylation sites of human GPCRs by combining amino acid hydrophobicity and support vector machine. The prediction accuracy, sensitivity, specificity, Matthews correlation coefficient and area under the curve values for phosphoserine, phosphothreonine, and phosphotyrosine were 0.964, 0.790, 0.999, 0.866, 0.941; 0.954, 0.800, 0.985, 0.828, 0.958; and 0.976, 0.820, 0.993, 0.861, 0.959, respectively. The establishment of such a fast and accurate prediction method will speed up the pace of identifying proper GPCRs sites to facilitate drug discovery.     

Distinguishing structural and functional restraints in evolution in order to identify interaction sites

Structural genomics projects are producing many three-dimensional structures of proteins that have been identified only from their gene sequences. It is therefore important to develop computational methods that will predict sites involved in productive intermolecular interactions that might give clues about functions. Techniques based on evolutionary conservation of amino acids have the advantage over physiochemical methods in that they are more general. However, the majority of techniques neither use all available structural and sequence information, nor are able to distinguish between evolutionary restraints that arise from the need to maintain structure and those that arise from function. Three methods to identify evolutionary restraints on protein sequence and structure are described here. The first identifies those residues that have a higher degree of conservation than expected: this is achieved by comparing for each amino acid position the sequence conservation observed in the homologous family of proteins with the degree of conservation predicted on the basis of amino acid type and local environment. The second uses information theory to identify those positions where environment-specific substitution tables make poor predictions of the overall amino acid substitution pattern. The third method identifies those residues that have highly conserved positions when three-dimensional structures of proteins in a homologous family are superposed. The scores derived from these methods are mapped onto the protein three-dimensional structures and contoured, allowing identification clusters of residues with strong evolutionary restraints that are sites of interaction in proteins involved in a variety of functions. Our method differs from other published techniques by making use of structural information to identify restraints that arise from the structure of the protein and differentiating these restraints from others that derive from intermolecular interactions that mediate functions in the whole organism.