DeepSAGE—digital transcriptomics with high sensitivity, simple experimental protocol and multiplexing of samples

Digital transcriptomics with pyrophosphatase based ultra-high throughput DNA sequencing of di-tags provides high sensitivity and cost-effective gene expression profiling. Sample preparation and handling are greatly simplified compared to Serial Analysis of Gene Expression (SAGE). We compare DeepSAGE and LongSAGE data and demonstrate greater power of detection and multiplexing of samples derived from potato. The transcript analysis revealed a great abundance of up-regulated potato transcripts associated with stress in dormant potatoes compared to harvest. Importantly, many transcripts were detected that cannot be matched to known genes, but is likely to be part of the abiotic stress-response in potato

The fungal symbiont of <em>Acromyrmex</em> leaf-cutting ants expresses the full spectrum of genes to degrade cellulose and other plant cell wall polysaccharides

BACKGROUND: The fungus gardens of leaf-cutting ants are natural biomass conversion systems that turn fresh plant forage into fungal biomass to feed the farming ants. However, the decomposition potential of the symbiont Leucocoprinus gongylophorus for processing polysaccharides has remained controversial. We therefore used quantifiable DeepSAGE technology to obtain mRNA expression patterns of genes coding for secreted enzymes from top, middle, and bottom sections of a laboratory fungus-garden of Acromyrmex echinatior leaf-cutting ants. RESULTS: A broad spectrum of biomass-conversion-relevant enzyme genes was found to be expressed in situ: cellulases (GH3, GH5, GH6, GH7, AA9 [formerly GH61]), hemicellulases (GH5, GH10, CE1, GH12, GH74), pectinolytic enzymes (CE8, GH28, GH43, PL1, PL3, PL4), glucoamylase (GH15), α-galactosidase (GH27), and various cutinases, esterases, and lipases. In general, expression of these genes reached maximal values in the bottom section of the garden, particularly for an AA9 lytic polysaccharide monooxygenase and for a GH5 (endocellulase), a GH7 (reducing end-acting cellobiohydrolase), and a GH10 (xylanase), all containing a carbohydrate binding module that specifically binds cellulose (CBM1). Although we did not directly quantify enzyme abundance, the profile of expressed cellulase genes indicates that both hydrolytic and oxidative degradation is taking place. CONCLUSIONS: The fungal symbiont of Acromyrmex leaf-cutting ants can degrade a large range of plant polymers, but the conversion of cellulose, hemicellulose, and part of the pectin occurs primarily towards the end of the decomposition process, i.e. in the bottom section of the fungus garden. These conversions are likely to provide nutrients for the fungus itself rather than for the ants, whose colony growth and reproductive success are limited by proteins obtained from ingesting fungal gongylidia. These specialized hyphal tips are hardly produced in the bottom section of fungus gardens, consistent with the ants discarding old fungal biomass from this part of the garden. The transcripts that we found suggest that actively growing mycelium in the bottom of gardens helps to maintain an optimal water balance to avoid hyphal disintegration, so the ants can ultimately discard healthy rather than decaying and diseased garden material, and to buffer negative effects of varying availability and quality of substrate across the seasons

“Candidatus Competibacter”-lineage genomes retrieved from metagenomes reveal functional metabolic diversity

The glycogen-accumulating organism (GAO) ‘Candidatus Competibacter’ (Competibacter) uses aerobically stored glycogen to enable anaerobic carbon uptake, which is subsequently stored as polyhydroxyalkanoates (PHAs). This biphasic metabolism is key for the Competibacter to survive under the cyclic anaerobic-‘feast’: aerobic-‘famine’ regime of enhanced biological phosphorus removal (EBPR) wastewater treatment systems. As they do not contribute to phosphorus (P) removal, but compete for resources with the polyphosphate-accumulating organisms (PAO), thought responsible for P removal, their proliferation theoretically reduces the EBPR capacity. In this study, two complete genomes from Competibacter were obtained from laboratory-scale enrichment reactors through metagenomics. Phylogenetic analysis identified the two genomes, ‘Candidatus Competibacter denitrificans’ and ‘Candidatus Contendobacter odensis’, as being affiliated with Competibacter-lineage subgroups 1 and 5, respectively. Both have genes for glycogen and PHA cycling and for the metabolism of volatile fatty acids. Marked differences were found in their potential for the Embden–Meyerhof–Parnas and Entner–Doudoroff glycolytic pathways, as well as for denitrification, nitrogen fixation, fermentation, trehalose synthesis and utilisation of glucose and lactate. Genetic comparison of P metabolism pathways with sequenced PAOs revealed the absence of the Pit phosphate transporter in the Competibacter-lineage genomes—identifying a key metabolic difference with the PAO physiology. These genomes are the first from any GAO organism and provide new insights into the complex interaction and niche competition between PAOs and GAOs in EBPR systems

The Transcriptome of Compatible and Incompatible Interactions of Potato (Solanum tuberosum) with Phytophthora infestans Revealed by DeepSAGE Analysis

Late blight, caused by the oomycete Phytophthora infestans, is the most important disease of potato (Solanum tuberosum). Understanding the molecular basis of resistance and susceptibility to late blight is therefore highly relevant for developing resistant cultivars, either by marker-assissted selection or by transgenic approaches. Specific P. infestans races having the Avr1 effector gene trigger a hypersensitive resistance response in potato plants carrying the R1 resistance gene (incompatible interaction) and cause disease in plants lacking R1 (compatible interaction). The transcriptomes of the compatible and incompatible interaction were captured by DeepSAGE analysis of 44 biological samples comprising five genotypes, differing only by the presence or absence of the R1 transgene, three infection time points and three biological replicates. 30.859 unique 21 base pair sequence tags were obtained, one third of which did not match any known potato transcript sequence. Two third of the tags were expressed at low frequency (<10 tag counts/million). 20.470 unitags matched to approximately twelve thousand potato transcribed genes. Tag frequencies were compared between compatible and incompatible interactions over the infection time course and between compatible and incompatible genotypes. Transcriptional changes were more numerous in compatible than in incompatible interactions. In contrast to incompatible interactions, transcriptional changes in the compatible interaction were observed predominantly for multigene families encoding defense response genes and genes functional in photosynthesis and CO2 fixation. Numerous transcriptional differences were also observed between near isogenic genotypes prior to infection with P. infestans. Our DeepSAGE transcriptome analysis uncovered novel candidate genes for plant host pathogen interactions, examples of which are discussed with respect to possible function