Project description:Giardia duodenalis a species-complex of common gastrointestinal protists of major medical and veterinary importance. This complex is currently subclassifed as ‘Assemblages’, with Assemblage A and B infective to humans. To date, post-genomic proteomics are derived exclusively from Assemblage A, biasing understanding of these parasites’ biology. This bias is particularly notable, as Assemble B is the more prevalent cause of human infections. To address this gap, we quantitatively analysed proteomes of the intestinal ‘trophozoite’ stage of three Assemblage B isolates, including the genome reference (GS/M) and two clinical isolates (BRIS/91/HEPU/1279 and BRIS/92/HEPU/1487), during in vitro axenic culture. We used spectrum-to-peptide matching metrics to infer currently unknown intra-assemblage variation. We identified and quantified over 3000 proteins in the GS isolate, but demonstrated significant isolate-dependent losses in peptide and protein identifications in non-reference isolates, suggesting significant intra-assemblage variation. We also explore differential protein expression between in vitro cultured subpopulations enriched for dividing relative to feeding cells. This data is an important proteomic baseline for Assemblage B, and highlights unique differences heretofore avoided in post-genomic Giardia proteomics.
Project description:Giardia duodenalis is a protozoan parasite of a wide range of vertebrates and one of the leading causes of gastroenteritis worldwide. G. duodenalis is a species complex of 8 assemblages with the zoonotic assemblage A as one of two discrete subtypes that is infective for humans. With increasing genomic and transcriptomic data now publicly available through the centralised giardiaDB.org, we have quantitatively analysed the proteomes of 8 G. duodenalis assemblage A strains (7 A1 and 1 A2) to provide a comprehensive proteomic baseline to complement these studies. Protein analysis identified a non-redundant total of 1220 proteins with an average of 764 proteins in each strain. At least 10% of all proteins identified were from the 4 protein families in the G. duodenalis variable genome, and substantial differences in number and abundance profiles in the Variable Surface Protein (VSP) family was observed. We also searched the 8 strains against both assemblage A genomes (subassemblage A1 and A2 genomes) and showed losses in protein identifications, especially for protein identifications associated with Giardia variable gene families which are sub-assemblage specific. We observed two expression profiles of VSPs within Giardia, which was independent to host origin, subassemblage, geographic origin and introduction to axenic culture and may indicate variation in surface antigen switching events and population heterogeneity. We hypothesise this variation may be related to karotype and chromosomal variation, which would indicate an assemblage-independent mechanism of variation in G. duodenalis.
Project description:The spring bloom in the North Atlantic develops over a few weeks in response to the physical stabilization of the nutrient replete water column and is one of the biggest biological signals on earth. The composition of the phytoplankton assemblage during the spring bloom of 2008 was evaluated, using a microarray, on the basis of functional genes that encode key enzymes in nitrogen and carbon assimilation in eukaryotic and prokaryotic phytoplankton. Oligonucleotide archetype probes representing RuBisCO, nitrate reductase and nitrate transporter genes from major phytoplankton classes detected a diverse assemblage. For RuBisCO, the archetypes with strongest signals represented known phytoplankton groups, but for the nitrate related genes, the major signals were not closely related to any known phytoplankton sequences. Most of the assemblage's components exhibited consistent temporal/spatial patterns. Yet, the strongest archetype signals often showed quite different patterns, indicating different ecological responses by the main players. The most abundant phytoplankton genera identified previously by microscopy, however, were not well represented on the microarray. The lack of sequence data for well-studied species, and the inability to identify organisms associated with functional gene sequences in the environment, still limits our understanding of phytoplankton ecology even in this relatively well-studied system.