A versatile transformation system for thraustochytrids, a promising producer for polyunsaturated fatty acids and fatty acid-derived fuels, was established. G418, hygromycin B, blasticidin, and zeocin inhibited the growth of thraustochytrids, indicating that multiple selectable marker genes could be used in the transformation system. A neomycin resistance gene (neor), driven with an ubiquitin or an EF-1α promoter-terminator from Thraustochytrium aureum ATCC 34304, was introduced into representatives of two thraustochytrid genera, Aurantiochytrium and Thraustochytrium. The neor marker was integrated into the chromosomal DNA by random recombination and then functionally translated into neor mRNA. Additionally, we confirmed that another two genera, Parietichytrium and Schizochytrium, could be transformed by the same method. By this method, the enhanced green fluorescent protein was functionally expressed in thraustochytrids. Meanwhile, T. aureum ATCC 34304 could be transformed by two 18S ribosomal DNA-targeting vectors, designed to cause single- or double-crossover homologous recombination. Finally, the fatty acid Δ5 desaturase gene was disrupted by double-crossover homologous recombination in T. aureum ATCC 34304, resulting in an increase of dihomo-γ-linolenic acid (C20:3n-6) and eicosatetraenoic acid (C20:4n-3), substrates for Δ5 desaturase, and a decrease of arachidonic acid (C20:4n-6) and eicosapentaenoic acid (C20:5n-3), products for the enzyme. These results clearly indicate that a versatile transformation system which could be applicable to both multiple transgene expression and gene targeting was established for thraustochytrids.

Thraustochytrids, marine protists known to accumulate polyunsaturated fatty acids (PUFAs) in lipid droplets, are considered an alternative to fish oils as a source of PUFAs. The major fatty acids produced in thraustochytrids are palmitic acid (C16:0), n − 6 docosapentaenoic acid (DPA) (C22:5n − 6), and docosahexaenoic acid (DHA) (C22:6n − 3), with eicosapentaenoic acid (EPA) (C20:5n − 3) and arachidonic acid (AA) (C20:4n − 6) as minor constituents. We attempted here to alter the fatty acid composition of thraustochytrids through the expression of a fatty acid Δ5 desaturase gene driven by the thraustochytrid ubiquitin promoter. The gene was functionally expressed in Aurantiochytrium limacinum mh0186, increasing the amount of EPA converted from eicosatetraenoic acid (ETA) (C20:4n − 3) by the Δ5 desaturase. The levels of EPA and AA were also increased by 4.6- and 13.2-fold in the transgenic thraustochytrids compared to levels in the mock transfectants when ETA and dihomo-γ-linolenic acid (DGLA) (C20:3n − 6) were added to the culture at 0.1 mM. Interestingly, the amount of EPA in the transgenic thraustochytrids increased in proportion to the amount of ETA added to the culture up to 0.4 mM. The rates of conversion and accumulation of EPA were much higher in the thraustochytrids than in baker's yeasts when the desaturase gene was expressed with the respective promoters. This report describes for the first time the finding that an increase of EPA could be accomplished by introducing the Δ5 desaturase gene into thraustochytrids and indicates that molecular breeding of thraustochytrids is a promising strategy for generating beneficial PUFAs.

Background:

Colorectal cancer (CRC) is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC) and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an “omics” study by integrating many kinds of analysis into a single comprehensive investigation.

In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers.

Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC.

This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC.

Materials and methods:

Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language.

Result:

We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene expression analysis, together with the clinical information, suggested UGT2B28, LOC440995, CXCL6, SULT1B1, RALBP1, TYMS, RAB12, RNMT, ARHGDIB, S1000A2, ABHD2, OIT3 and ABHD12 as genes that are possibly associated with CRC. Some of these genes have already been reported as being related to CRC. TYMS has been reported as being associated with resistance to the anti-cancer drug 5-fluorouracil, and we observed a copy number increase for this gene. RALBP1, ARHGDIB and S100A2 have been reported as oncogenes, and we observed copy number increases in each. ARHGDIB has been reported as a metastasis-related gene, and our data also showed copy number increases of this gene in cases with metastasis.

Conclusion:

The combination of CNA analysis and gene expression analysis was a more effective method for finding genes associated with the clinicopathological classification of CRC than either analysis alone. Using this combination of methods, we were able to detect genes that have already been associated with CRC. We also identified additional candidate genes that may be new markers or targets for this form of cancer.