From functional architecture to functional connectomics

"Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex" by Hubel and Wiesel (1962) reported several important discoveries: orientation columns, the distinct structures of simple and complex receptive fields, and binocular integration. But perhaps the paper's greatest influence came from the concept of functional architecture (the complex relationship between in?vivo physiology and the spatial arrangement of neurons) and several models of functionally specific connectivity. They thus identified two distinct concepts, topographic specificity and functional specificity, which together with cell-type specificity constitute the major determinants of nonrandom cortical connectivity. Orientation columns are iconic examples of topographic specificity, whereby axons within a column connect with cells of a single orientation preference. Hubel and Wiesel also saw the need for functional specificity at a finer scale in their model of thalamic inputs to simple cells, verified in the 1990s. The difficult but potentially more important question of functional specificity between cortical neurons is only now becoming tractable with new experimental techniques.     

Functional richness, functional evenness and functional divergence: the primary components of functional diversity

Functional diversity is hypothesised as being beneficial for ecosystem functions, such as productivity and resistance to invasion. However, a precise definition of functional diversity, and hence a framework for its quantification, have proved elusive. We present a definition based on the analogy of the components of species diversity – richness, evenness and divergence. These concepts are applied to functional characters to give three components of functional diversity – functional richness, functional evenness and functional divergence. We demonstrate how each of these components may be calculated. It is hoped that our definition of functional diversity and its components will aid in elucidation of the mechanisms behind diversity/ecosystem-function relationships.     

Prediction of functional sites in proteins using conserved functional group analysis

A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects.     

Systematic discovery of functional modules and context-specific functional annotation of human genome

MOTIVATION: The rapid accumulation of microarray datasets provides unique opportunities to perform systematic functional characterization of the human genome. We designed a graph-based approach to integrate cross-platform microarray data, and extract recurrent expression patterns. A series of microarray datasets can be modeled as a series of co-expression networks, in which we search for frequently occurring network patterns. The integrative approach provides three major advantages over the commonly used microarray analysis methods: (1) enhance signal to noise separation (2) identify functionally related genes without co-expression and (3) provide a way to predict gene functions in a context-specific way. RESULTS: We integrate 65 human microarray datasets, comprising 1105 experiments and over 11 million expression measurements. We develop a data mining procedure based on frequent itemset mining and biclustering to systematically discover network patterns that recur in at least five datasets. This resulted in 143,401 potential functional modules. Subsequently, we design a network topology statistic based on graph random walk that effectively captures characteristics of a gene's local functional environment. Function annotations based on this statistic are then subject to the assessment using the random forest method, combining six other attributes of the network modules. We assign 1126 functions to 895 genes, 779 known and 116 unknown, with a validation accuracy of 70%. Among our assignments, 20% genes are assigned with multiple functions based on different network environments. AVAILABILITY: http://zhoulab.usc.edu/ContextAnnotation.     

Prediction of Saccharomyces cerevisiae protein functional class from functional domain composition

MOTIVATION: A key goal of genomics is to assign function to genes, especially for orphan sequences. RESULTS: We compared the clustered functional domains in the SBASE database to each protein sequence using BLASTP. This representation for a protein is a vector, where each of the non-zero entries in the vector indicates a significant match between the sequence of interest and the SBASE domain. The machine learning methods nearest neighbour algorithm (NNA) and support vector machines are used for predicting protein functional classes from this information. We find that the best results are found using the SBASE-A database and the NNA, namely 72% accuracy for 79% coverage. We tested an assigning function based on searching for InterPro sequence motifs and by taking the most significant BLAST match within the dataset. We applied the functional domain composition method to predict the functional class of 2018 currently unclassified yeast open reading frames. AVAILABILITY: A program for the prediction method, that uses NNA called Functional Class Prediction based on Functional Domains (FCPFD) is available and can be obtained by contacting Y.D.Cai at y.cai@umist.ac.uk     

Early endocytic Rabs: functional prediction to functional characterization

Endocytic pathways are highly dynamic gateways for molecules to enter cells. Functionality and specificity is in part controlled by a number of small GTPases called Rabs. In defined cellular locations, Rabs mediate multiple functions in membrane trafficking via their specific interaction with organelle membranes and a host of affector and effector molecules. On endocytic pathways, Rabs have been shown to control the formation of vesicles on the plasma membrane and the downstream delivery of internalized molecules to a number of cellular locations. As numerous Rabs are located to endocytic pathways, an internalized molecule may traverse a number of Rab specific substations or subdomains en route to its final destination. Rabs 5, 21 and 22 have all been localized to the early endocytic pathway and have been shown to share a number of characteristics to merit their segregation into a single functional endocytic group. In this review, we compare experiments that describe similarities and differences in endosome morphology and function that is mediated by their expression in cells.     

Maintained functional diversity in benthic communities in spite of diverging functional identities

Ecological studies based on time‐series often investigate community changes centered on species abundance or biomass but rarely expose the consequential functional aspects underlying such changes. Functional diversity measures have proven to be more accurate predictors for ecosystem functioning than traditional taxonomic approaches and hence gained much attention. There are only limited studies available that analyse the functional implications behind decadal changes of entire communities. We studied zoobenthic communities of two habitats, sheltered and exposed, of a coastal system subject to contrasting changes in community composition over the past four decades. Besides eutrophication and climate‐related impacts, the system has been invaded by a non‐native polycheate Marenzelleria spp., adding altered functional properties to the communities. The functional dispersion (FDis) metric was used as a measure for comparing the functional diversity of the contrasting habitats, with special focus on the role of Marenzelleria for the entire communities. We highlight changes in the functional identity of the communities, expressed as community‐weighted means of trait expression (CWM), using multivariate techniques, and investigate the relationship between taxonomic and functional changes. Despite contrasting community developments in the two habitats, with characteristics traditionally suggesting different environmental quality, we found that the FDis in both habitats remained similar and increased with the introduction of Marenzelleria. Although showing maintained functional diversity across time and space, the functional identity (CWM) of communities changed irrespective of taxonomical differences. Examples include inter alia alterations in palatability proxies, feeding position and sediment transportation types, indicating changed functionality of zoobenthos in coastal systems. We show, when focussing on qualitative functional changes of communities, it is important to evaluate the underlying functional identity, and not only rely on measures of the diversity of functions per se, as the quality indication of expressed functional traits can be concealed when using multi‐functionality approaches.     

Studies of glutamate dehydrogenase: analysis of functional areas and functional groups.

1. It is shown by limited tryptic digestion of beef liver glutamate dehydrogenase under native conditions that the amino terminus of the polypeptide chain is located at the surface of the molecule. End-group analysis after trypsin treatment yields aspartic acid as the new N-terminal amino acid while the C-terminal threonine remains unchanged. 2. NADH, especially in the presence of 2-oxoglutarate, protects the enzyme against tryptic degradation. In the absence of the coenzyme, glutamate dehydrogenase is rapidly inactivated. 3. The regulatory effects of ADP and GTP are only slightly altered by trypsin. A small shift of the pH dependence of the activation by ADP is observed. 4. The quaternary structure of the unimer of the enzyme is not affected by limited tryptic digestion indicating that the N-terminal part of the polypeptide chain is not located in the contact domains between the polypeptide chains. The association of the hexamer to large associated particles is reduced but not abolished. 5. It is shown by treatment of the enzyme with iodo[2(-14)C]acetic acid as well as with Ellman's reagent that the six - SH groups of the polypeptide chain are buried and not accessible to these reagents in phosphate buffer. In Tris buffer they become exposed and react in the order 89, 55, 197, 115, 270, 319. This together with the result that in Tris buffer the rat of inactivation caused by trypsin is higher than in phosphate buffer indicates that Tris buffer changes drastically the properties of the enzyme. 6. Cross-linking of the enzyme molecule with bifunctional reagents and subsequent dodecylsulfate-polyacrylamide electrophoresis shows that the six identical polypeptide chains are arranged in two groups of three. 7. The implications of these results for the tertiary and quaternary structure of beef liver glutamate dehydrogenase are discussed.     

Computational approaches to predict protein functional families and functional sites

Understanding the mechanisms of protein function is indispensable for many biological applications, such as protein engineering and drug design. However, experimental annotations are sparse, and therefore, theoretical strategies are needed to fill the gap. Here, we present the latest developments in building functional subclassifications of protein superfamilies and using evolutionary conservation to detect functional determinants, for example, catalytic-, binding- and specificity-determining residues important for delineating the functional families. We also briefly review other features exploited for functional site detection and new machine learning strategies for combining multiple features.     

Mapping functional connectivity

An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible, and automated approach for the definition of indicators based on the classification and mapping of spatial patterns of connectivity from observed or simulated movement and dispersal events. The approach is illustrated with data derived from simulated movement on a map produced from satellite imagery of a structurally complex, multi-habitat landscape. The analysis reveals critical areas that facilitate the movement of dispersers among habitat patches. Mathematical morphology can be applied to any movement map providing new insights into pattern-process linkages in multi-habitat landscapes.     

Integrative functional genomics

A report on the Keystone Symposium 'Biological Discovery Using Diverse High-Throughput Data', Steamboat Springs, USA, 30 March-4 April 2004.     

Chitosan functional properties

Chitosan is a partially deacetylated polymer of N-acetyl glucosamine. It is essentially a natural, water-soluble, derivative of cellulose with unique properties. Chitosan is usually prepared from chitin (2 acetamido-2-deoxy β-1,4-D-glucan) and chitin has been found in a wide range of natural sources (crustaceans, fungi, insects, annelids, molluscs, coelenterata etc.) However chitosan is only manufactured from crustaceans (crab and crayfish) primarily because a large amount of the crustacean exoskeleton is available as a by product of food processing. Squid pens (a waste byproduct of New Zealand squid processing) are a novel, renewable source of chitin and chitosan. Squid pens are currently regarded as waste and so the raw material is relatively cheap. This study was intended to assess the functional properties of squid pen chitosan. Chitosan was extracted from squid pens and assessed for composition, rheology, flocculation, film formation and antimicrobial properties. Crustacean chitosans were also assessed for comparison. Squid chitosan was colourless, had a low ash content and had significantly improved thickening and suspending properties. The flocculation capacity of squid chitosan was low in comparison with the crustacean sourced chitosans. However it should be possible to increase the flocculation capacity of squid pen chitosan by decreasing the degree of acetylation. Films made with squid chitosan were more elastic than crustacean chitosan with improved functional properties. This high quality chitosan could prove particularly suitable for medical/analytical applications. This revised version was published online in November 2006 with corrections to the Cover Date.     

Density functional theory

Photosynthesis Research - Density functional theory (DFT) finds increasing use in applications related to biological systems. Advancements in methodology and implementations have reached a point...     

Sustained functional composition of pollinators in restored pastures despite slow functional restoration of plants

Habitat restoration is a key measure to counteract negative impacts on biodiversity from habitat loss and fragmentation. To assess success in restoring not only biodiversity, but also functionality of communities, we should take into account the re‐assembly of species trait composition across taxa. Attaining such functional restoration would depend on the landscape context, vegetation structure, and time since restoration. We assessed how trait composition of plant and pollinator (bee and hoverfly) communities differ between abandoned, restored (formerly abandoned) or continuously grazed (intact) semi‐natural pastures. In restored pastures, we also explored trait composition in relation to landscape context, vegetation structure, and pasture management history. Abandoned pastures differed from intact and restored pastures in trait composition of plant communities, and as expected, had lower abundances of species with traits associated with grazing adaptations. Further, plant trait composition in restored pastures became increasingly similar to that in intact pastures with increasing time since restoration. On the contrary, the trait composition of pollinator communities in both abandoned and restored pastures remained similar to intact pastures. The trait composition for both bees and hoverflies was influenced by flower abundance and, for bees, by connectivity to other intact grasslands in the landscape. The divergent responses across organism groups appeared to be mainly related to the limited dispersal ability and long individual life span in plants, the high mobility of pollinators, and the dependency of semi‐natural habitat for bees. Our results, encompassing restoration effects on trait composition for multiple taxa along a gradient in both time (time since restoration) and space (connectivity), reveal how interacting communities of plants and pollinators are shaped by different trait–environmental relationships. Complete functional restoration of pastures needs for more detailed assessments of both plants dispersal in time and of resources available within pollinator dispersal range.     

Flexible components of functional responses

1. The functional response of predators describes the rate at which a predator consumes prey and is an important determinant of community dynamics. Despite the importance, most empirical studies have considered a limited number of models of functional response. In addition, the models often make strong assumptions about the pattern of predation processes, even though functional responses can potentially exhibit a wide variety of patterns. 2. In addition to the limited model consideration, model selections of functional response models cannot tease apart the components of predation (i.e. capture rate and handling time) when flexible traits are considered because it is always possible that many different combinations of the capture rate and handling time can lead to the same predation rate. 3. This study directly examined the capture rate and handling time of functional response in a mite community. To avoid the model selection problem, the searching and handling behaviour data were collected. The model selection was applied directly to these two components of predation data. Commonly used functional response models and models that allow for more flexible patterns were compared. 4. The results indicated that assumptions of the commonly used models were not supported by the data, and a flexible model was selected as the best model. These results suggest the need to consider a wider variety of predation patterns when characterizing a functional response. Without making a strong assumption (e.g. static handling time), model selections on functional response models cannot be used to make reliable inferences on the predation mechanisms.