Project description:Background: Antimicrobial resistance is generally studied using a combination of growth inhibition measurements, sometimes in combination with DNA detection methods. However, the actual proteins that cause resistance such as enzymes, efflux pumps and a lack of porins cannot be detected by these methods. Improvements in liquid chromatography (LC) and mass spectrometry (MS) enabled easier and more comprehensive proteome analysis. In the current study, these three methods are combined into a multi-omics approach to analyze resistance against frequently used antibiotics within the beta-lactam, aminoglycoside and fluoroquinolone group in E. coli and K. pneumoniae. Objectives: We aimed to analyze which currently known antimicrobial resistance genes are detected at the protein level using liquid chromatography-mass spectrometry (LC-MS/MS) and to assess whether these could explain beta-lactam, aminoglycoside, and fluoroquinolone resistance in the studied isolates. Furthermore, we aimed to identify significant protein to resistance correlations which have not yet been described and to correlate the abundance of different porins to resistance. Methods: Whole genome sequencing, high-resolution LC-MS/MS and antimicrobial susceptibility testing by broth microdilution were performed for 187 clinical E. coli and K. pneumoniae isolates. Resistance genes and proteins were identified using the Comprehensive Antibiotic Resistance Database (CARD). All proteins were annotated using the NCBI RefSeq database and Prokka. Results & Conclusion: Proteins of small spectrum beta-lactamases, extended spectrum beta-lactamases, AmpC beta-lactamases, carbapenemases, and proteins of 16S ribosomal RNA methyltransferases and aminoglycoside acetyltransferases can be detected in E. coli and K. pneumoniae by LC-MS/MS. The detected mechanisms could explain phenotypic resistance in most of the studied isolates. Differences in the abundance and the primary structure of other proteins such as porins also correlated with resistance. LC-MS/MS is a different and complementary method which can be used to characterize antimicrobial resistance in detail as not only the primary resistance causing mechanisms are detected, but also secondary enhancing resistance mechanisms.

Project description:MicroRNAs (miRNAs) have been shown to play an important role in many different cellular, developmental, and physiological processes. Accordingly, numerous methods have been established to identify and quantify miRNAs. The shortness of miRNA sequence results in a high dynamic range of melting temperatures and, moreover, impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here, we present a microarray based approach for global and absolute quantification of miRNAs. The method relies on an equimolar pool of about 1000 synthetic miRNAs of known concentration which is used as an universal reference and labeled and hybridized in a dual colour approach on the same array as the sample of interest. Each single miRNA is quantified with respect to the universal reference outbalancing bias related to sequence, labeling, hybridization or signal detection method. We demonstrate the accuracy of the method by various spike in experiments. Further, we quantified miRNA copy numbers in liver samples and CD34(+)CD133(-) hematopoietic stem cells. The RNA extracted from 7 x 10^ 5 to 1 x 10^ 6 CD34(+)/CD133(-) cells of three different donors was analyzed. 1 µg of respective total RNA was mixed with 2.5 fmol of each of 18 RNA oligonucleotides reverse complement to miRControl 3 probes and subsequently fluorescently labelled by 3’ ligation. Total RNA mix was hybridized in a dual colour approach to microarrays versus a second labelled synthetic miRNA pool. The synthetic miRNA pool consisted of 2.5 fmol of each of 954 non redundant miRNAs sequences and miRControl 3 sequences. The array data was normalized by calculating the median of the miRControl 3 present in the CD34(+)/CD133(-) and UR sample. The miRNA amount was calculated with respect to the corresponding miRNA in the UR.

Dataset Information

Rapid and accurate detection of aminoglycoside modifying enzymes and 16S ribosomal RNA methyltransferases by targeted LC-MS/MS

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