The complete assignment of the proton chemical shifts obtained by nuclear magnetic resonance (NMR) spectroscopy of de-O-acetylated glucuronoxylomannans (GXMs) from Cryptococcus neoformanspermitted the high-resolution determination of the total structure of any GXM. Six structural motifs based on an α-(1→3)-mannotriose substituted with variable quantities of 2-O-β- and 4-O-β-xylopyranosyl and 2-O-β-glucopyranosyluronic acid were identified. The chemical shifts of only the anomeric protons of the mannosyl residues served as structure reporter groups (SRG) for the identification and quantitation of the six triads present in any GXM. The assigned protons for the mannosyl residues resonated at clearly distinguishable positions in the spectrum and supplied all the information essential for the assignment of the complete GXM structure. This technique for assigning structure is referred to as the SRG concept. The SRG concept was used to analyze the distribution of the six mannosyl triads of GXMs obtained from 106 isolates of C. neoformans. The six mannosyl triads occurred singularly or in combination with one or more of the other triads. The identification and quantitation of the SRG were simplified by using a computer-simulated artificial neural network (ANN) to automatically analyze the SRG region of the one-dimensional proton NMR spectra. The occurrence and relative distribution of the six mannosyl triads were used to chemotype C. neoformans on the basis of subtle variations in GXM structure determined by analysis of the SRG region of the proton NMR spectrum by the ANN. The data for the distribution of the six SRGs from GXMs of 106 isolates of C. neoformansyielded eight chemotypes, Chem1 through Chem8.

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Pyrazinamide (PZA) is an important first-line drug in the treatment of tuberculosis (TB) and of significant interest to the HIV-infected community due to the prevalence of TB-HIV coinfection in some regions of the world. The mechanism of resistance to PZA is unlike that of any other anti-TB drug. The gene pncA, encoding pyrazinamidase (PZase), is associated with resistance to PZA. However, because single mutations in PZase have a low prevalence, the individual sensitivities are low. Hundreds of distinct mutations in the enzyme have been associated with resistance, while some only appear in susceptible isolates. This makes interpretation of molecular testing difficult and often leads to the simplification that any PZase mutation causes resistance. This systematic review reports a comprehensive global list of mutations observed in PZase and its promoter region in clinical strains, their phenotypic association, their global frequencies and diversity, the method of phenotypic determination, their MIC values when given, and the method of MIC determination and assesses the strength of the association between mutations and phenotypic resistance to PZA. In this systematic review, we report global statistics for 641 mutations in 171 (of 187) codons from 2,760 resistant strains and 96 mutations from 3,329 susceptible strains reported in 61 studies. For diagnostics, individual mutations (or any subset) were not sufficiently sensitive. Assuming similar error profiles of the 5 phenotyping platforms included in this study, the entire enzyme and its promoter provide a combined estimated sensitivity of 83%. This review highlights the need for identification of an alternative mechanism(s) of resistance, at least for the unexplained 17% of cases.

This manuscript describes the creation of comprehensive gene wiki, seeded with data from public domain sources, which will enable and encourage community annotation of gene function.

BackgroundSimultaneous measurement of gene expression on a genomic scale can be accomplished using microarray technology or by sequencing based methods. Researchers who perform high throughput gene expression assays often deposit their data in public databases, but heterogeneity of measurement platforms leads to challenges for the combination and comparison of data sets. Researchers wishing to perform cross platform normalization face two major obstacles. First, a choice must be made about which method or methods to employ. Nine are currently available, and no rigorous comparison exists. Second, software for the selected method must be obtained and incorporated into a data analysis workflow.ResultsUsing two publicly available cross-platform testing data sets, cross-platform normalization methods are compared based on inter-platform concordance and on the consistency of gene lists obtained with transformed data. Scatter and ROC-like plots are produced and new statistics based on those plots are introduced to measure the effectiveness of each method. Bootstrapping is employed to obtain distributions for those statistics. The consistency of platform effects across studies is explored theoretically and with respect to the testing data sets.ConclusionsOur comparisons indicate that four methods, DWD, EB, GQ, and XPN, are generally effective, while the remaining methods do not adequately correct for platform effects. Of the four successful methods, XPN generally shows the highest inter-platform concordance when treatment groups are equally sized, while DWD is most robust to differently sized treatment groups and consistently shows the smallest loss in gene detection. We provide an R package, CONOR, capable of performing the nine cross-platform normalization methods considered. The package can be downloaded at http://alborz.sdsu.edu/conor and is available from CRAN.

Undetected and untreated, low-levels of drug resistant (DR) subpopulations in clinical Mycobacterium tuberculosis (Mtb) infections may lead to development of DR-tuberculosis, potentially resulting in treatment failure. Current phenotypic DR susceptibility testing has a theoretical potential for 1% sensitivity, is not quantitative, and requires several weeks to complete. The use of “single molecule-overlapping reads” (SMOR) analysis with next generation DNA sequencing for determination of ultra-rare target alleles in complex mixtures provides increased sensitivity over standard DNA sequencing. Ligation free amplicon sequencing with SMOR analysis enables the detection of resistant allele subpopulations at ≥0.1% of the total Mtb population in near real-time analysis. We describe the method using standardized mixtures of DNA from resistant and susceptible Mtb isolates and the assay’s performance for detecting ultra-rare DR subpopulations in DNA extracted directly from clinical sputum samples. SMOR analysis enables rapid near real-time detection and tracking of previously undetectable DR sub-populations in clinical samples allowing for the evaluation of the clinical relevance of low-level DR subpopulations. This will provide insights into interventions aimed at suppressing minor DR subpopulations before they become clinically significant.

We report the discovery and confirmation of 23 novel mutations with previously undocumented role in isoniazid (INH) drug resistance, in catalase-peroxidase (katG) gene of Mycobacterium tuberculosis (Mtb) isolates. With these mutations, a synonymous mutation in fabG1g609a, and two canonical mutations, we were able to explain 98% of the phenotypic resistance observed in 366 clinical Mtb isolates collected from four high tuberculosis (TB)-burden countries: India, Moldova, Philippines, and South Africa. We conducted overlapping targeted and whole-genome sequencing for variant discovery in all clinical isolates with a variety of INH-resistant phenotypes. Our analysis showed that just two canonical mutations (katG 315AGC-ACC and inhA promoter-15C-T) identified 89.5% of resistance phenotypes in our collection. Inclusion of the 23 novel mutations reported here, and the previously documented point mutation in fabG1, increased the sensitivity of these mutations as markers of INH resistance to 98%. Only six (2%) of the 332 resistant isolates in our collection did not harbor one or more of these mutations. The third most prevalent substitution, at inhA promoter position -8, present in 39 resistant isolates, was of no diagnostic significance since it always co-occurred with katG 315. 79% of our isolates harboring novel mutations belong to genetic group 1 indicating a higher tendency for this group to go down an uncommon evolutionary path and evade molecular diagnostics. The results of this study contribute to our understanding of the mechanisms of INH resistance in Mtb isolates that lack the canonical mutations and could improve the sensitivity of next generation molecular diagnostics.

In animals, most small nuclear RNAs (snRNAs) are synthesized by RNA polymerase II (Pol II), but U6 snRNA is synthesized by RNA polymerase III (Pol III). In Drosophila melanogaster, the promoters for the Pol II-transcribed snRNA genes consist of ∼21 bp PSEA and ∼8 bp PSEB. U6 genes utilize a PSEA but have a TATA box instead of the PSEB. The PSEAs of the two classes of genes bind the same protein complex, DmSNAPc. However, the PSEAs that recruit Pol II and Pol III differ in sequence at a few nucleotide positions that play an important role in determining RNA polymerase specificity. We have now performed a bioinformatic analysis to examine the conservation and divergence of the snRNA gene promoter elements in other species of insects. The 5′ half of the PSEA is well-conserved, but the 3′ half is divergent. Moreover, within each species positions exist where the PSEAs of the Pol III-transcribed genes differ from those of the Pol II-transcribed genes. Interestingly, the specific positions vary among species. Nevertheless, we speculate that these nucleotide differences within the 3′ half of the PSEA act similarly to induce conformational alterations in DNA-bound SNAPc that result in RNA polymerase specificity.