Antigenic variation in African trypanosomes

Studies on Variant Surface Glycoproteins (VSGs) and antigenic variation in the African trypanosome, Trypanosoma brucei, have yielded a remarkable range of novel and important insights. The features first identified in T. brucei extend from unique to conserved-among-trypanosomatids to conserved-among-eukaryotes. Consequently, much of what we now know about trypanosomatid biology and much of the technology available has its origin in studies related to VSGs. T. brucei is now probably the most advanced early branched eukaryote in terms of experimental tractability and can be approached as a pathogen, as a model for studies on fundamental processes, as a model for studies on eukaryotic evolution or often all of the above. In terms of antigenic variation itself, substantial progress has been made in understanding the expression and switching of the VSG coat, while outstanding questions continue to stimulate innovative new approaches. There are large numbers of VSG genes in the genome but only one is expressed at a time, always immediately adjacent to a telomere. DNA repair processes allow a new VSG to be copied into the single transcribed locus. A coordinated transcriptional switch can also allow a new VSG gene to be activated without any detectable change in the DNA sequence, thereby maintaining singular expression, also known as allelic exclusion. I review the story behind VSGs; the genes, their expression and switching, their central role in T. brucei virulence, the discoveries that emerged along the way and the persistent questions relating to allelic exclusion in particular

Clearwing Moths Captured by Ultraviolet Light Traps in Southern Ohio (Lepidoptera: Sesiidae)

Trapping with ultraviolet light in mixed-oak forests of Lawrence and Vinton Counties, Ohio in 1995 and 1996 yielded 46 Synanthedon acerni and four Synanthedon arkansasensis, a clearwing moth record new for the state

Data mining of protein families using common peptides

Predicting the function of a protein from its sequence is typically addressed using sequence-similarity. Here we propose a motif-based approach, using supervised motif extraction from protein sequences belonging to one functional family. The resulting deterministic motifs form Common Peptides (CPs) that characterize this family, allow for data mining of its proteins and facilitate further partition of the family into cluster