Description of a Sarcoptic Mange Outbreak in Alpine Chamois Using an Enhanced Surveillance Approach.

Since 1995, the Alpine chamois (Rupicapra r. rupicapra) population of the Dolomites has been affected by sarcoptic mange with considerable management concerns. In this study, 15 years (2006-2020) of passive surveillance and demographic data were analyzed in order to describe a mange outbreak. Furthermore, an enhanced passive surveillance protocol was implemented in order to evaluate the efficiency of ordinary vs. enhanced surveillance protocol in identifying dead chamois in the field and in reaching a correct diagnosis. Our results confirm the role of mange as a determining factor for chamois mortality, while stressing the importance of a wider view on the factors affecting population dynamics. The enhanced passive surveillance protocol increased the probability of carcass retrieval and identification of the cause of death; however, its adoption may be too costly if applied for long periods on a wide scale. Passive surveillance, in both ordinary and enhanced surveillance protocol, should encompass the use of other strategies in the future to study the eco-epidemiology of the disease in wild Caprinae.

Preference and familiarity mediate spatial responses of a large herbivore to experimental manipulation of resource availability.

The link between spatio-temporal resource patterns and animal movement behaviour is a key ecological process, however, limited experimental support for this connection has been produced at the home range scale. In this study, we analysed the spatial responses of a resident large herbivore (roe deer Capreolus capreolus) using an in situ manipulation of a concentrated food resource. Specifically, we experimentally altered feeding site accessibility to roe deer and recorded (for 25 animal-years) individual responses by GPS tracking. We found that, following the loss of their preferred resource, roe deer actively tracked resource dynamics leading to more exploratory movements, and larger, spatially-shifted home ranges. Then, we showed, for the first time experimentally, the importance of site fidelity in the maintenance of large mammal home ranges by demonstrating the return of individuals to their familiar, preferred resource despite the presence of alternate, equally-valuable food resources. This behaviour was modulated at the individual level, where roe deer characterised by a high preference for feeding sites exhibited more pronounced behavioural adjustments during the manipulation. Together, our results establish the connections between herbivore movements, space-use, individual preference, and the spatio-temporal pattern of resources in home ranging behaviour.

SH3-Hunter: discovery of SH3 domain interaction sites in proteins.

SH3-Hunter (http://cbm.bio.uniroma2.it/SH3-Hunter/) is a web server for the recognition of putative SH3 domain interaction sites on protein sequences. Given an input query consisting of one or more protein sequences, the server identifies peptides containing poly-proline binding motifs and associates them to a list of SH3 domains, in order to compose peptide-domain pairs. The server can accept a list of peptides and allows users to upload an input file in a proper format. An accurate selection of SH3 domains is available and users can also submit their own SH3 domain sequence. SH3-Hunter evaluates which peptide-domain pair represents a possible interaction pair and produces as output a list of significant interaction sites for each query protein. Each proposed interaction site is associated to a propensity score and sensitivity and precision levels for the prediction. The server prediction capability is based on a neural network model integrating high-throughput pep-spot data with structural information extracted from known SH3-peptide complexes.

False occurrences of functional motifs in protein sequences highlight evolutionary constraints.

BACKGROUND: False occurrences of functional motifs in protein sequences can be considered as random events due solely to the sequence composition of a proteome. Here we use a numerical approach to investigate the random appearance of functional motifs with the aim of addressing biological questions such as: How are organisms protected from undesirable occurrences of motifs otherwise selected for their functionality? Has the random appearance of functional motifs in protein sequences been affected during evolution? RESULTS: Here we analyse the occurrence of functional motifs in random sequences and compare it to that observed in biological proteomes; the behaviour of random motifs is also studied. Most motifs exhibit a number of false positives significantly similar to the number of times they appear in randomized proteomes (=expected number of false positives). Interestingly, about 3% of the analysed motifs show a different kind of behaviour and appear in biological proteomes less than they do in random sequences. In some of these cases, a mechanism of evolutionary negative selection is apparent; this helps to prevent unwanted functionalities which could interfere with cellular mechanisms. CONCLUSION: Our thorough statistical and biological analysis showed that there are several mechanisms and evolutionary constraints both of which affect the appearance of functional motifs in protein sequences.

A neural strategy for the inference of SH3 domain-peptide interaction specificity.

BACKGROUND: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that generally characterizes its ligands does not reflect the complex interaction spectrum of the over 1500 different SH3 domains, and the requirement of a more refined knowledge of their specificity implies the setting up of appropriate experimental and theoretical strategies. Due to the limitations of the current technology for peptide synthesis, several experimental high-throughput approaches have been devised to elucidate protein-protein interaction mechanisms. Such approaches can rely on and take advantage of computational techniques, such as regular expressions or position specific scoring matrices (PSSMs) to pre-process entire proteomes in the search for putative SH3 targets. In this regard, a reliable inference methodology to be used for reducing the sequence space of putative binding peptides represents a valuable support for molecular and cellular biologists. RESULTS: Using as benchmark the peptide sequences obtained from in vitro binding experiments, we set up a neural network model that performs better than PSSM in the detection of SH3 domain interactors. In particular our model is more precise in its predictions, even if its performance can vary among different SH3 domains and is strongly dependent on the number of binding peptides in the benchmark. CONCLUSION: We show that a neural network can be more effective than standard methods in SH3 domain specificity detection. Neural classifiers identify general SH3 domain binders and domain-specific interactors from a PxxP peptide population, provided that there are a sufficient proportion of true positives in the training sets. This capability can also improve peptide selection for library definition in array experiments. Further advances can be achieved, including properly encoded domain sequences and structural information as input for a global neural network.