Wholemount immunohistochemistry for revealing complex brain topography

The repeated and well-understood cellular architecture of the cerebellum make it an ideal model system for exploring brain topography. Underlying its relatively uniform cytoarchitecture is a complex array of parasagittal domains of gene and protein expression. The molecular compartmentalization of the cerebellum is mirrored by the anatomical and functional organization of afferent fibers. To fully appreciate the complexity of cerebellar organization we previously refined a wholemount staining approach for high throughput analysis of patterning defects in the mouse cerebellum. This protocol describes in detail the reagents, tools, and practical steps that are useful to successfully reveal protein expression patterns in the adult mouse cerebellum by using wholemount immunostaining. The steps highlighted here demonstrate the utility of this method using the expression of zebrinII/aldolaseC as an example of how the fine topography of the brain can be revealed in its native three-dimensional conformation. Also described are adaptations to the protocol that allow for the visualization of protein expression in afferent projections and large cerebella for comparative studies of molecular topography. To illustrate these applications, data from afferent staining of the rat cerebellum are included.     

Forest and Demons in the Papua New Guinea Highlands

The Wola people of the Southern Highland Province of Papua New Guinea believe that two kinds of demon spirit inhabit the montane forests of their region. They call them saem and iybtit. When people are attacked by these frightening creatures, they are injured or fall sick, and may die; their relatives perform rituals to drive the demons away and promote their recovery. The attitude of the Wola towards demon spirits expresses something of their ambivalent and enigmatic attitudes towards the forest that covers large areas of their region. They are neither innate conservationists nor reckless destroyers of forest, but something more equivocal, an antipathetic combination of both.     

Use of structure comparison methods for the refinement of protein structure predictions. I. Identifying the structural family of a protein from low-resolution models.

Predicting the three-dimensional structure of proteins is still one of the most challenging problems in molecular biology. Despite its difficulty, several investigators have started to produce consistently low-resolution predictions for small proteins. However, in most of these cases, the prediction accuracy is still too low to make them useful. In the present article, we address the problem of obtaining better-quality predictions, starting from low-resolution models. To this end, we have devised a new procedure that uses these models, together with structure comparison methods, to identify the structural family of the target protein. This would allow, in a second step not described in the present work, to refine the predictions using conserved features of the identified family. In our approach, the structure database is investigated using predictions, at different accuracy levels, for a given protein. As query structures, we used both low-resolution versions of the native structures, as well as different sets of low accuracy predictions. In general, we found that for predictions with a resolution of > or =5-7 A, structure comparison methods were able to identify the fold of a protein in the top positions.     

Detecting the Seeds of Nassella neesiana in Large Round Hay Bales,by Means of Non-Destructive Core Sampling

In the last three decades or so there has been a significant increase in fodder trading, both in terms of the quantity of fodder traded and in terms of its economic value to the industry. Often, this fodder type may be supplied free of charge to graziers in distress due to circumstances that follow natural disasters such as bushfires, drought, and flood. However, because of the obvious urgency arising from these situations, it is suspected that much relief fodder may unintentionally pose an elevated risk for dispersal of weeds since it may be supplied from pasture not normally used for trade in fodder, and therefore is of unknown quality. Previous destructive method to detect weed propagules in bales of fodder are cumbersome, time consuming and of limited ecological and statistical value. Therefore, objective of this paper was to development of a convenient method to assess round pasture hay bales for the presence of weed propagules, to prevent unintentional spread of noxious species in hay bales. To examine this objective known quantity of seeds were added in a series of distributions to bales of seed free pasture hay, and a positive correlation for the amount of seed added per bale with that recovered in core samples was observed. Whilst the number of seeds detected per bale varied according to the distribution of seeds within the bales and the number of cores analysed, the absolute detection of seeds suggests that this sampling method is worthy of further examination. In addition, a pragmatic estimation of bale remnants after stock feeding has been investigated to more closely estimate the potential size of the remaining seed bank. The authors propose that development of this approach is timely, in the light of future climatic uncertainty driving extreme weather events that increase the need for relief fodder, which can be a potential vector for the spread of noxious weed seeds.     

A rapid classification protocol for the CATH Domain Database to support structural genomics

In order to support the structural genomic initiatives, both by rapidly classifying newly determined structures and by suggesting suitable targets for structure determination, we have recently developed several new protocols for classifying structures in the CATH domain database (http://www.biochem.ucl.ac.uk/bsm/cath). These aim to increase the speed of classification of new structures using fast algorithms for structure comparison (GRATH) and to improve the sensitivity in recognising distant structural relatives by incorporating sequence information from relatives in the genomes (DomainFinder). In order to ensure the integrity of the database given the expected increase in data, the CATH Protein Family Database (CATH-PFDB), which currently includes 25,320 structural domains and a further 160,000 sequence relatives has now been installed in a relational ORACLE database. This was essential for developing more rigorous validation procedures and for allowing efficient querying of the database, particularly for genome analysis. The associated Dictionary of Homologous Superfamilies [Bray,J.E., Todd,A.E., Pearl,F.M.G., Thornton,J.M. and Orengo,C.A. (2000) Protein Eng., 13, 153-165], which provides multiple structural alignments and functional information to assist in assigning new relatives, has also been expanded recently and now includes information for 903 homologous superfamilies. In order to improve coverage of known structures, preliminary classification levels are now provided for new structures at interim stages in the classification protocol. Since a large proportion of new structures can be rapidly classified using profile-based sequence analysis [e.g. PSI-BLAST: Altschul,S.F., Madden,T.L., Schaffer,A.A., Zhang,J., Zhang,Z., Miller,W. and Lipman,D.J. (1997) Nucleic Acids Res., 25, 3389-3402], this provides preliminary classification for easily recognisable homologues, which in the latest release of CATH (version 1.7) represented nearly three-quarters of the non-identical structures.     

Recognizing the fold of a protein structure

This paper reports a graph-theoretic program, GRATH, that rapidly, and accurately, matches a novel structure against a library of domain structures to find the most similar ones. GRATH generates distributions of scores by comparing the novel domain against the different types of folds that have been classified previously in the CATH database of structural domains. GRATH uses a measure of similarity that details the geometric information, number of secondary structures and number of residues within secondary structures, that any two protein structures share. Although GRATH builds on well established approaches for secondary structure comparison, a novel scoring scheme has been introduced to allow ranking of any matches identified by the algorithm. More importantly, we have benchmarked the algorithm using a large dataset of 1702 non-redundant structures from the CATH database which have already been classified into fold groups, with manual validation. This has facilitated introduction of further constraints, optimization of parameters and identification of reliable thresholds for fold identification. Following these benchmarking trials, the correct fold can be identified with the top score with a frequency of 90%. It is identified within the ten most likely assignments with a frequency of 98%. GRATH has been implemented to use via a server (http://www.biochem.ucl.ac.uk/cgi-bin/cath/Grath.pl). GRATH's speed and accuracy means that it can be used as a reliable front-end filter for the more accurate, but computationally expensive, residue based structure comparison algorithm SSAP, currently used to classify domain structures in the CATH database. With an increasing number of structures being solved by the structural genomics initiatives, the GRATH server also provides an essential resource for determining whether newly determined structures are related to any known structures from which functional properties may be inferred.     

The CATH database: an extended protein family resource for structural and functional genomics

The CATH database of protein domain structures (http://www.biochem.ucl.ac.uk/bsm/cath_new) currently contains 34 287 domain structures classified into 1383 superfamilies and 3285 sequence families. Each structural family is expanded with domain sequence relatives recruited from GenBank using a variety of efficient sequence search protocols and reliable thresholds. This extended resource, known as the CATH-protein family database (CATH-PFDB) contains a total of 310 000 domain sequences classified into 26 812 sequence families. New sequence search protocols have been designed, based on these intermediate sequence libraries, to allow more regular updating of the classification. Further developments include the adaptation of a recently developed method for rapid structure comparison, based on secondary structure matching, for domain boundary assignment. The philosophy behind CATHEDRAL is the recognition of recurrent folds already classified in CATH. Benchmarking of CATHEDRAL, using manually validated domain assignments, demonstrated that 43% of domains boundaries could be completely automatically assigned. This is an improvement on a previous consensus approach for which only 10-20% of domains could be reliably processed in a completely automated fashion. Since domain boundary assignment is a significant bottleneck in the classification of new structures, CATHEDRAL will also help to increase the frequency of CATH updates.     

Review: what can structural classifications reveal about protein evolution?

In this article we present a review of the methods used for comparing and classifying protein structures. We discuss the hierarchies and populations of fold groups and evolutionary families in some of the major classifications and we consider some of the problems confronting any general analyses of structural evolution in protein families. We also review some more recent analyses that have expanded these classifications by identifying sequence relatives in the genomes and thereby reveal interesting trends in fold usage and recurrence.