Objective To evaluate the use of prospective screening for the HLA-B*58:01 allele to identify Taiwanese individuals at risk of severe cutaneous adverse reactions (SCARs) induced by allopurinol treatment. Design National prospective cohort study. Setting 15 medical centres in different regions of Taiwan, from July 2009 to August 2014. Participants 2926 people who had an indication for allopurinol treatment but had not taken allopurinol previously. Participants were excluded if they had undergone a bone marrow transplant, were not of Han Chinese descent, and had a history of allopurinol induced hypersensitivity. DNA purified from 2910 participants’ peripheral blood was used to assess the presence of HLA-B*58:01. Main outcome measures Incidence of allopurinol induced SCARs with and without screening. Results Participants who tested positive for HLA-B*58:01 (19.6%, n=571) were advised to avoid allopurinol, and were referred to an alternate drug treatment or advised to continue with their prestudy treatment. Participants who tested negative (80.4%, n=2339) were given allopurinol. Participants were interviewed once a week for two months to monitor symptoms. The historical incidence of allopurinol induced SCARs, estimated by the National Health Insurance research database of Taiwan, was used for comparison. Mild, transient rash without blisters developed in 97 (3%) participants during follow-up. None of the participants was admitted to hospital owing to adverse drug reactions. SCARs did not develop in any of the participants receiving allopurinol who screened negative for HLA-B*58:01. By contrast, seven cases of SCARs were expected, based on the estimated historical incidence of allopurinol induced SCARs nationwide (0.30% per year, 95% confidence interval 0.28% to 0.31%; P=0.0026; two side one sample binomial test). Conclusions Prospective screening of the HLA-B*58:01 allele, coupled with an alternative drug treatment for carriers, significantly decreased the incidence of allopurinol induced SCARs in Taiwanese medical centres.

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c Degradation of terephthalate (TA) through microbial syntrophy under moderately thermophilic (46 to 50°C) methanogenic conditions was characterized by using a metagenomic approach (A. Lykidis et al., ISME J. 5:122-130, 2011). To further study the activities of key microorganisms responsible for the TA degradation, community analysis and shotgun proteomics were used. The results of hierarchical oligonucleotide primer extension analysis of PCR-amplified 16S rRNA genes indicated that Pelotomaculum, Methanosaeta, and Methanolinea were predominant in the TA-degrading biofilms. Metaproteomic analysis identified a total of 482 proteins and revealed a distinctive distribution pattern of microbial functions expressed in situ. The results confirmed that TA was degraded by Pelotomaculum spp. via the proposed decarboxylation and benzoyl-coenzyme A-dependent pathway. The intermediate by-products, including acetate, H 2 /CO 2 , and butyrate, were produced to support the growth of methanogens, as well as other microbial populations that could further degrade butyrate. Proteins related to energy production and conservation, and signal transduction mechanisms (that is, chemotaxis, PAS/GGDEF regulators, and stress proteins) were highly expressed, and these mechanisms were important for growth in energy-limited syntrophic ecosystems.T erephthalate (TA) is produced in large quantities in plastic, textile, and petroleum-related industries, and wastewater generated by the TA manufacturing process is often treated with anaerobic methanogenic processes (1). In these processes, TA is converted to CH 4 and CO 2 through the microbial syntrophy established among the enriched microbial populations. It is hypothesized that the hydrogen-producing syntrophic bacteria degrade TA to acetate and H 2 /CO 2 , which are immediately used by the methanogenic archaea adjacent to final gaseous products (2, 3). To validate the syntrophic interaction, a full-cycle 16S rRNA approach was used to successfully identify the identities of the syntrophic bacteria and methanogenic archaea inside the granules and biofilms of different laboratory-scale TA-degrading methanogenic reactors (3, 4). A recent study further used a metagenomic approach to reveal the diversity and physiological traits of the syntrophs and methanogens involved in the TA degradation under moderately thermophilic conditions (46 to 50°C) (5). All of these studies have provided strong evidence to elucidate the degradation of TA based on the microbial populations and the metabolic pathways involved.Furthermore, to directly observe the global expression of microbial functions within the TA-degrading consortium, community-level proteomics can be used (6). To do so, total proteins recovered from an environmental sample are first separated and enzymatically fragmented. The resulting peptide mixture is analyzed using advanced liquid chromatography-mass spectrometry (LC-MS) technology, and information related to the key proteins is identified using in silico analysis of the protein sequence database. ...

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In this study, we established a rapid multiplex method to detect the relative abundances of amplified 16S rRNA genes from known cultivatable methanogens at hierarchical specificities in anaerobic digestion systems treating industrial wastewater and sewage sludge. The method was based on the hierarchical oligonucleotide primer extension (HOPE) technique and combined with a set of 27 primers designed to target the total archaeal populations and methanogens from 22 genera within 4 taxonomic orders. After optimization for their specificities and detection sensitivity under the conditions of multiple single-nucleotide primer extension reactions, the HOPE approach was applied to analyze the methanogens in 19 consortium samples from 7 anaerobic treatment systems (i.e., 513 reactions). Among the samples, the methanogen populations detected with order-level primers accounted for >77.2% of the PCR-amplified 16S rRNA genes detected using an Archaea-specific primer. The archaeal communities typically consisted of 2 to 7 known methanogen genera within the Methanobacteriales, Methanomicrobiales, and Methanosarcinales and displayed population dynamic and spatial distributions in anaerobic reactor operations. Principal component analysis of the HOPE data further showed that the methanogen communities could be clustered into 3 distinctive groups, in accordance with the distribution of the Methanosaeta, Methanolinea, and Methanomethylovorans, respectively. This finding suggested that in addition to acetotrophic and hydrogenotrophic methanogens, the methylotrophic methanogens might play a key role in the anaerobic treatment of industrial wastewater. Overall, the results demonstrated that the HOPE approach is a specific, rapid, and multiplexing platform to determine the relative abundances of targeted methanogens in PCR-amplified 16S rRNA gene products.