Examination of Triacylglycerol Biosynthetic Pathways via De Novo Transcriptomic and Proteomic Analyses in an Unsequenced Microalga

Biofuels derived from algal lipids represent an opportunity to dramatically impact the global energy demand for transportation fuels. Systems biology analyses of oleaginous algae could greatly accelerate the commercialization of algal-derived biofuels by elucidating the key components involved in lipid productivity and leading to the initiation of hypothesis-driven strain-improvement strategies. However, higher-level systems biology analyses, such as transcriptomics and proteomics, are highly dependent upon available genomic sequence data, and the lack of these data has hindered the pursuit of such analyses for many oleaginous microalgae. In order to examine the triacylglycerol biosynthetic pathway in the unsequenced oleaginous microalga, Chlorella vulgaris, we have established a strategy with which to bypass the necessity for genomic sequence information by using the transcriptome as a guide. Our results indicate an upregulation of both fatty acid and triacylglycerol biosynthetic machinery under oil-accumulating conditions, and demonstrate the utility of a de novo assembled transcriptome as a search model for proteomic analysis of an unsequenced microalga

Caenorhabditis elegans Semi-Automated Liquid Screen Reveals a Specialized Role for the Chemotaxis Gene cheB2 in Pseudomonas aeruginosa Virulence

Pseudomonas aeruginosa is an opportunistic human pathogen that causes infections in a variety of animal and plant hosts. Caenorhabditis elegans is a simple model with which one can identify bacterial virulence genes. Previous studies with C. elegans have shown that depending on the growth medium, P. aeruginosa provokes different pathologies: slow or fast killing, lethal paralysis and red death. In this study, we developed a high-throughput semi-automated liquid-based assay such that an entire genome can readily be scanned for virulence genes in a short time period. We screened a 2,200-member STM mutant library generated in a cystic fibrosis airway P. aeruginosa isolate, TBCF10839. Twelve mutants were isolated each showing at least 70% attenuation in C. elegans killing. The selected mutants had insertions in regulatory genes, such as a histidine kinase sensor of two-component systems and a member of the AraC family, or in genes involved in adherence or chemotaxis. One mutant had an insertion in a cheB gene homologue, encoding a methylesterase involved in chemotaxis (CheB2). The cheB2 mutant was tested in a murine lung infection model and found to have a highly attenuated virulence. The cheB2 gene is part of the chemotactic gene cluster II, which was shown to be required for an optimal mobility in vitro. In P. aeruginosa, the main player in chemotaxis and mobility is the chemotactic gene cluster I, including cheB1. We show that, in contrast to the cheB2 mutant, a cheB1 mutant is not attenuated for virulence in C. elegans whereas in vitro motility and chemotaxis are severely impaired. We conclude that the virulence defect of the cheB2 mutant is not linked with a global motility defect but that instead the cheB2 gene is involved in a specific chemotactic response, which takes place during infection and is required for P. aeruginosa pathogenicity

Gene Ontology enrichment analysis.

<p>Functional distribution of the complete annotated <i>C. vulgaris</i> transcriptome (grey bars) and the 2,949 transcripts corresponding to proteins identified in sub-proteomic soluble fraction via MS/MS analysis (black bars). Distribution is represented as percent of total transcripts in respective fractions.</p

Improved pathway identification using a <i>de novo</i> assembled transcriptome database and changes in protein abundance under nitrogen depletion.

<p>(A) Critical components of the fatty acid and triacylglycerol (TAG) biosynthetic pathways were absent from initial MS/MS searches against all available <i>Chlorophyta</i> databases. Proteins highlighted in yellow were amongst the proteins absent from initial analyses, yet positively identified when searching against the <i>C. vulgaris</i> transcriptome database. Proteins in green (not highlighted) were identified using both <i>Chlorophyta</i> and <i>C. vulgaris</i> transcriptome databases. Numbers below proteins represent NSAF values (10⁵) for nitrogen replete and nitrogen deplete conditions, respectively. ACCase, acetyl-CoA carboxylase; ACP, acyl carrier protein; AMPK, AMP-activated kinase; DAGK, diacylglycerol kinase; DGAT, diacylglycerol acyltransferase; DHAP, dihydroxyacetone phosphate; ENR, enoyl-ACP reductase; FAT_P, fatty acyl-ACP thioesterase (putative); G3PDH, glycerol-3-phosphate dehydrogenase; GPAT, glycerol-3-phosphate acyltransferase; HD, 3-hydroxyacyl-ACP dehydratase; KAR, 3-ketoacyl-ACP reductase; KAS, 3-ketoacyl-ACP synthase; LPAAT, lyso-phosphatidic acid acyltransferase; LPAT, lyso-phosphatidylcholine acyltransferase; MAT, malonyl-CoA:ACP transacylase; PAP, phosphatidic acid phosphatase. Adapted from Radakovits et al., 2010 and Hu et al., 2008. (B) Corresponding spectral count fold-changes for components of the FA (left panel) and TAG (right panel) biosynthetic components.</p

Multiple sequence alignment for acetyl-coA acyltransferase (ACAT) peptides identified via MS/MS analysis.

<p>Despite high sequence identity (Expect values<1e-124), ACAT was not identified using <i>Chlorophyta</i> sequence databases as search models in MS/MS analysis. Notably, underlined peptides differed by just a single amino acid substitution between <i>C. vulgaris</i> and <i>C. variabilis</i>, preventing positive identification. Using the <i>C. vulgaris</i> transcriptome as a sequence search database yielded 7 peptide identifications at a confidence interval >95%.</p

Proteomic Analysis of <i>C. vulgaris</i>.

<p>(A) One dimensional SDS-PAGE of <i>C. vulgaris</i> soluble fraction utilized for comparative proteomic analysis. M, Marker; N+, Nitrogen-replete; N−, Nitrogen-deplete. (B) Mass spectral analysis data for the <i>C. vulgaris</i> proteome searched against all available <i>Chlorophyta</i> genome databases (left) and the <i>C. vulgaris</i> Transcriptome (right).</p