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      Single-molecule nanopore sequencing reveals extreme target copy number heterogeneity in arylomycin-resistant mutants

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          Significance

          Genetic heterogeneity is a significant driver of antibiotic resistance in bacteria. Understanding copy number (CN) heterogeneity is important because minority subclones with increased CN can drive resistance during antibiotic exposure, but revert and escape detection during clinical susceptibility testing. Despite its clinical relevance, CN variation has eluded quantification at single-molecule resolution. Here, we report nanopore sequencing of arylomycin-resistant mutants carrying tandem repeats ranging in size from 4.8 to 50.0 kb and encompassing the arylomycin target gene lepB. Reads spanning individual repeat arrays show vast differences in CN, underscoring the importance of amplifications in driving the emergence of genetic heterogeneity. This is a direct observation of cell-to-cell CN differences in an antibiotic-resistant bacterial population.

          Abstract

          Tandem gene amplification is a frequent and dynamic source of antibiotic resistance in bacteria. Ongoing expansions and contractions of repeat arrays during population growth are expected to manifest as cell-to-cell differences in copy number (CN). As a result, a clonal bacterial culture could comprise subpopulations of cells with different levels of antibiotic sensitivity that result from variable gene dosage. Despite the high potential for misclassification of heterogenous cell populations as either antibiotic-susceptible or fully resistant in clinical settings, and the concomitant risk of inappropriate treatment, CN distribution among cells has defied analysis. Here, we use the MinION single-molecule nanopore sequencer to uncover CN heterogeneity in clonal populations of Escherichia coli and Acinetobacter baumannii grown from single cells isolated while selecting for resistance to an optimized arylomycin, a member of a recently discovered class of Gram-negative antibiotic. We found that gene amplification of the arylomycin target, bacterial type I signal peptidase LepB, is a mechanism of unstable arylomycin resistance and demonstrate in E. coli that amplification instability is independent of RecA. This instability drives the emergence of a nonuniform distribution of lepB CN among cells with a range of 1 to at least 50 copies of lepB identified in a single clonal population. In sum, this remarkable heterogeneity, and the evolutionary plasticity it fuels, illustrates how gene amplification can enable bacterial populations to respond rapidly to novel antibiotics. This study establishes a rationale for further nanopore-sequencing studies of heterogeneous cell populations to uncover CN variability at single-molecule resolution.

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          Most cited references35

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          BLAST+: architecture and applications

          Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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            One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products.

            We have developed a simple and highly efficient method to disrupt chromosomal genes in Escherichia coli in which PCR primers provide the homology to the targeted gene(s). In this procedure, recombination requires the phage lambda Red recombinase, which is synthesized under the control of an inducible promoter on an easily curable, low copy number plasmid. To demonstrate the utility of this approach, we generated PCR products by using primers with 36- to 50-nt extensions that are homologous to regions adjacent to the gene to be inactivated and template plasmids carrying antibiotic resistance genes that are flanked by FRT (FLP recognition target) sites. By using the respective PCR products, we made 13 different disruptions of chromosomal genes. Mutants of the arcB, cyaA, lacZYA, ompR-envZ, phnR, pstB, pstCA, pstS, pstSCAB-phoU, recA, and torSTRCAD genes or operons were isolated as antibiotic-resistant colonies after the introduction into bacteria carrying a Red expression plasmid of synthetic (PCR-generated) DNA. The resistance genes were then eliminated by using a helper plasmid encoding the FLP recombinase which is also easily curable. This procedure should be widely useful, especially in genome analysis of E. coli and other bacteria because the procedure can be done in wild-type cells.
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              Software for Computing and Annotating Genomic Ranges

              We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                07 January 2021
                21 December 2020
                21 December 2020
                : 118
                : 1
                : e2021958118
                Affiliations
                [1] aDepartment of Infectious Diseases, Genentech , South San Francisco, CA 94080;
                [2] bDepartment of OMNI Bioinformatics, Genentech , South San Francisco, CA 94080;
                [3] cDepartment of Proteomics, Lipidomics and Next Generation Sequencing, Genentech , South San Francisco, CA 94080;
                [4] dDepartment of Oncology Bioinformatics, Genentech , South San Francisco, CA 94080
                Author notes
                2To whom correspondence may be addressed. Email: smith.peter@ 123456gene.com or skippington.elizabeth@ 123456gene.com .

                Edited by Bruce R. Levin, Emory University, Atlanta, GA, and approved November 20, 2020 (received for review October 27, 2020)

                Author contributions: H.S.G., P.A.S., and E.S. designed research; H.S.G., C.D.D., J.L., J.R., J.G., S.D., and E.S. performed research; J.R. contributed new reagents/analytic tools; H.S.G., C.D.D., J.L., J.R., J.G., S.D., Y.L., J.K., P.A.S., and E.S. analyzed data; and E.S. wrote the paper.

                1Present address: Oxford Nanopore Technologies Ltd., Alameda, CA 94501.

                Author information
                https://orcid.org/0000-0002-6704-6754
                Article
                202021958
                10.1073/pnas.2021958118
                7817135
                33443214
                0e11d612-bd9b-4303-b6be-f61e048db88d
                Copyright © 2021 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                Page count
                Pages: 8
                Categories
                Biological Sciences
                Evolution

                antibiotic resistance,heterogeneity,amplification,optimized arylomycins

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