Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.     

Recent ecosystem dynamics in nine North African lakes in the CASSARINA Project

An integrated multi-disciplinary study of nine North African lakes (CASSARINA) aims to establish ecological baselines and to explore responses to 20th century human impacts on their ecosystems. Water chemistry measurements (1997–1998) demonstrate a wide range from dilute oligotrophic to calcareous freshwaters and from mildly brackish to hypersaline lagoons. The biota are consequently highly diverse. Aquatic ecosystem responses to environmental stress over the last 100–200 years in all nine lakes are summarised by detrended correspondence analysis (DCA) of plant and animal macrofossil, zooplankton, diatom, and pollen data from short sediment cores. DCA proved to be a powerful tool for summarising multi-proxy sediment records and ecosystem dynamics. Compositional changes measured by the DCAs have been very large and rapid, often over a few decades; as great as climate-controlled late-glacial changes over 2000 years and larger than most Holocene (11000 years) changes. These results emphasise the strength of human impact on the lakes and the surprisingly great resilience and dynamism of their ecosystems. The DCA summaries for the most recent decades indicate ecosystem disequilibrium in all the lakes, implying that their future stability is uncertain and that large or damaging changes may soon occur if the stresses are maintained. Thresholds have recently been passed in 3 lakes. During the project, Merja Bokka (Morocco) was drained and cultivated. The unique acid Megene Chitane (Tunisia) is in danger of drying up permanently due to water extraction. Freshwater diversion from Garaet El Ichkeul (Tunisia) has dramatically altered its wildlife habitat, as reed-marshes were replaced by salt-marsh and bare mud within 20 years. In contrast, the ecosystems of the Delta lakes (Egypt) have responded dramatically to the year-round inflow of fresh irrigation water controlled by Nile dams and the rise in the freshwater table due to inadequate drainage in the flat delta. The Project has demonstrated remarkably rapid responses by the lakes to environmental stresses. In particular, it highlights the threats to wetland-lake ecosystems in North Africa if uncontrolled exploitation continues.     

Some observations on the age and growth of thin-lipped grey mullet, Liza ramada Risso, 1826 (Pisces, Mugilidae) in three North African wetland lakes: Merja Zerga (Morocco), Garâat Ichkeul (Tunisia) and Edku Lake (Egypt)

Age and growth characteristics of the thin-lipped Grey Mullet (Liza ramada) were investigated in three North African wetland lakes: Merja Zerga (Morocco), Garâat Ichkeul (Tunisia) and Edku Lake (Egypt). Age structure of the mullet populations was very similar in all three study lakes. Small differences in growth were indicated, especially for the Moroccan population, where growth tended to be slower than for the other two populations. The fastest growth was observed in the Edku population while the best condition was observed in the Ichkeul population. Compared with some European populations, the sampled North African populations have faster growth and better condition factors.     

VaxiJen: a server for prediction of protective antigens,tumour antigens and subunit vaccines

Background  

Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach – such as speed and cost efficiency – its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties.