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      The role of rifampicin within the treatment of Mycobacterium avium pulmonary disease

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          ABSTRACT

          Rifampicin is recommended for the treatment of Mycobacterium avium complex pulmonary disease alongside azithromycin and ethambutol. We evaluated the azithromycin-ethambutol backbone with and without rifampicin in an intracellular hollow fiber model and performed RNA sequencing to study the differences in adaptation. In an in vitro hollow fiber experiment, we simulated epithelial lining fluid pharmacokinetic profiles of the recommended 3-drug (rifampicin, ethambutol, and azithromycin) or a 2-drug (ethambutol and azithromycin) treatment. THP-1 cells infected with M. avium ATCC700898 were exposed to these regimens for 21 days. We determined intra- and extra-cellular bacterial load- and THP-1 cell densities on days 0, 3, 7, 14, and 21, alongside RNA sequencing. The emergence of macrolide resistance was studied by inoculating intra- and extra-cellular fractions of azithromycin-containing Middlebrook 7H10 agar plates. Complete pharmacokinetic profiles were determined at days 0 and 21. Both therapies maintained stasis of both intra- and extra-cellular bacterial populations for 3 days, whilst regrowth coinciding with the emergence of a macrolide-resistant subpopulation was seen after 7 days. THP-1 cell density remained static. Similar transcriptional profiles were observed for both therapies that were minimally influenced by exposure duration. Transcriptional response was slightly larger during 2-drug treatment. Rifampicin did not add to the antimycobacterial effect to the 2-drug therapy or suppression of emergence resistance. RNA transcription was not greatly altered by the addition of rifampicin, which may be due to strong transcriptional influence of azithromycin and host cells. This questions the role of rifampicin in the currently recommended therapy. These findings should be confirmed in clinical trials.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: Formal analysisRole: SupervisionRole: Writing – review and editing
                Role: ConceptualizationRole: ValidationRole: Writing – review and editing
                Role: InvestigationRole: SupervisionRole: ValidationRole: Writing – review and editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review and editing
                Role: Editor
                Journal
                Antimicrob Agents Chemother
                Antimicrob Agents Chemother
                aac
                Antimicrobial Agents and Chemotherapy
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                0066-4804
                1098-6596
                November 2023
                25 October 2023
                25 October 2023
                : 67
                : 11
                : e00874-23
                Affiliations
                [1 ] Department of Medical Microbiology, Radboudumc Center for Infectious Diseases, Radboud University Medical Center; , Nijmegen, The Netherlands
                [2 ] Department of Pharmacy, Radboudumc Center for Infectious Diseases, Radboud University Medical Center; , Nijmegen, The Netherlands
                [3 ] Department of Pulmonary Diseases, Radboudumc Center for Infectious Diseases, Radboud University Medical Center; , Nijmegen, The Netherlands
                Providence Portland Medical Center; , Portland, Oregon, USA
                Author notes
                Address correspondence to Jakko van Ingen, jakko.vaningen@ 123456radboudumc.nl

                Jodie A. Schildkraut and Jelmer Raaijmakers contributed equally to this article. The order of the first two author names is based on seniority.

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0002-7236-8934
                https://orcid.org/0000-0001-7250-5647
                https://orcid.org/0000-0002-0581-2003
                Article
                00874-23 aac.00874-23
                10.1128/aac.00874-23
                10649009
                37877693
                6ccdfe07-2cd1-474e-86b3-04775cc4e5ea
                Copyright © 2023 Schildkraut et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 07 July 2023
                : 26 July 2023
                Page count
                supplementary-material: 1, authors: 6, Figures: 2, Tables: 1, References: 33, Pages: 10, Words: 5754
                Funding
                Funded by: RUNMC | Radboud Institute for Health Sciences (RIHS);
                Award Recipient :
                Categories
                Experimental Therapeutics
                antimicrobial-chemotherapy, Antimicrobial Chemotherapy
                Custom metadata
                November 2023

                Infectious disease & Microbiology
                ntm,nontuberculous mycobacteria,pharmacodynamics,pharmacokinetics,hollow-fibre model

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