As a base for human transcriptome and functional genomics, we created the "full-length long Japan" (FLJ) collection of sequenced human cDNAs. We determined the entire sequence of 21,243 selected clones and found that 14,490 cDNAs (10,897 clusters) were unique to the FLJ collection. About half of them (5,416) seemed to be protein-coding. Of those, 1,999 clusters had not been predicted by computational methods. The distribution of GC content of nonpredicted cDNAs had a peak at ∼58% compared with a peak at ∼42%for predicted cDNAs. Thus, there seems to be a slight bias against GC-rich transcripts in current gene prediction procedures. The rest of the cDNAs unique to the FLJ collection (5,481) contained no obvious open reading frames (ORFs) and thus are candidate noncoding RNAs. About one-fourth of them (1,378) showed a clear pattern of splicing. The distribution of GC content of noncoding cDNAs was narrow and had a peak at ∼42%, relatively low compared with that of protein-coding cDNAs.

The tfd genes of Ralstonia eutropha JMP134 are the only well-characterized set of genes responsible for 2,4-dichlorophenoxyacetic acid (2,4-D) degradation among 2,4-D-degrading bacteria. A new family of 2,4-D degradation genes, cadRABKC, was cloned and characterized from Bradyrhizobium sp. strain HW13, a strain that was isolated from a buried Hawaiian soil that has never experienced anthropogenic chemicals. The cadR gene was inferred to encode an AraC/XylS type of transcriptional regulator from its deduced amino acid sequence. The cadABC genes were predicted to encode 2,4-D oxygenase subunits from their deduced amino acid sequences that showed 46, 44, and 37% identities with the TftA and TftB subunits of 2,4,5-trichlorophenoxyacetic acid (2,4,5-T) oxygenase of Burkholderia cepacia AC1100 and with a putative ferredoxin, ThcC, of 2,4-Dichlorophenoxyacetic acid (2,4-D) is a manufactured herbicide that has been widely used for the control of broadleaf weeds since its introduction in the 1940s. Many 2,4-Ddegrading microorganisms have been isolated from agricultural, urban, and industrial soils and sediments (2,3,9,22,30,50), and the catabolic pathway of 2,4-D mineralization in Ralstonia eutropha JMP134 has been extensively characterized (8-10, 14, 19, 25, 26, 32-35, 38, 41-43, 48). In JMP134, 2,4-D is transformed to 2,4-dichlorophenol (2,4-DCP) by ␣-ketoglutarate-dependent 2,4-D dioxygenase encoded by tfdA, and 2,4-DCP is subsequently hydroxylated by 2,4-DCP hydroxylase encoded by tfdB to form 3,5-dichlorocatechol (3,5-DCC). 3,5-DCC is further metabolized through an intradiol ring cleavage pathway encoded by tfdCDEF (Fig. 1). These genes are located on plasmid pJP4.Most 2,4-D-degrading bacteria isolated from human-disturbed sites contain tfdA gene homologs. They include various copiotrophic, fast-growing genera in the ␤ and ␥ subdivisions of the Proteobacteria and have been classified as class I 2,4-D degraders (24). Ka et al. reported another group of 2,4-D degraders (class II) that were also isolated from disturbed sites but have neither tfdA gene homologs nor ␣-ketoglutarate-dependent 2,4-D dioxygenase activity (21-23). This group is composed of copiotrophic, fast-growing strains in the ␣ subdivision of the Proteobacteria, mostly belonging to the genus Sphingomonas. Fulthorpe et al. (17) and Kamagata et al. (24) isolated 2,4-D degraders from noncontaminated, pristine soils, degraders which have neither tfdA gene homologs nor ␣-ketoglutarate-dependent 2,4-D dioxygenase activity and, in contrast to those of the other two classes, grow slowly. This group of 2,4-D degraders (class III) is affiliated with the Bradyrhizobium-Agromyces-Nitrobacter-Afipia cluster (A. Saitou, H. Mitsui, and T. Hattori, Abstr. 11th Meet. Jpn. Soc. Microb. Ecol., p. 26, 1995) of oligotrophic bacteria in the ␣ subdivision of the Proteobacteria. The existence of three distinct ecological and genetic classes of 2,4-D degraders indicates a diversity of 2,4-D degradation genes and perhaps of pathways among 2,4-D degraders. However, the 2,4-D ...

Characterization and interpretation of disease-associated alterations of protein glycosylation are the central aims of the emerging glycoproteomics projects, which are expected to lead to more sensitive and specific diagnosis and improve therapeutic outcomes for various diseases. Here we report a new approach to identify carbohydrate-targeting serum biomarkers, termed isotopic glycosidase elution and labeling on lectin-column chromatography (IGEL). This technology is based on glycan structure-specific enrichment of glycopeptides by lectin-column chromatography and site-directed tagging of N-glycosylation sites by (18)O during the elution with N-glycosidase. The combination of IGEL with 8-plex isobaric tag for relative and absolute quantitation (iTRAQ) stable isotope labeling enabled us not only to identify N-glycosylation sites effectively but also to compare glycan structures on each glycosylation site quantitatively in a single LC/MS/MS analysis. We applied this method to eight sera from lung cancer patients and controls, and finally identified 107 glycopeptides in their sera, including A2GL_Asn151, A2GL_Asn290, CD14_Asn132, CO8A_Asn417, C163A_Asn64, TIMP1_Asn30, and TSP1_Asn1049 which showed the significant change of the affinity to Concanavalin A (ConA) lectin between the lung cancer samples and the controls (p < 0.05 and more than twofold change). These screening results were further confirmed by the conventional lectin-column chromatography and immunoblot analysis using additional serum samples. Our novel methodology, which should be valuable for diverse biomarker discoveries, can provide high-throughput and quantitative profiling of glycan structure alterations.

Interstitial lung disease (ILD) events have been reported in Japanese non-small-cell lung cancer (NSCLC) patients receiving EGFR tyrosine kinase inhibitors. We investigated proteomic biomarkers for mechanistic insights and improved prediction of ILD. Blood plasma was collected from 43 gefitinib-treated NSCLC patients developing acute ILD (confirmed by blinded diagnostic review) and 123 randomly selected controls in a nested case-control study within a pharmacoepidemiological cohort study in Japan. We generated ∼7 million tandem mass spectrometry (MS/MS) measurements with extensive quality control and validation, producing one of the largest proteomic lung cancer datasets to date, incorporating rigorous study design, phenotype definition, and evaluation of sample processing. After alignment, scaling, and measurement batch adjustment, we identified 41 peptide peaks representing 29 proteins best predicting ILD. Multivariate peptide, protein, and pathway modeling achieved ILD prediction comparable to previously identified clinical variables; combining the two provided some improvement. The acute phase response pathway was strongly represented (17 of 29 proteins, p = 1.0×10−25), suggesting a key role with potential utility as a marker for increased risk of acute ILD events. Validation by Western blotting showed correlation for identified proteins, confirming that robust results can be generated from an MS/MS platform implementing strict quality control.