Correction: A Chemical-Genomic Screen of Neglected Antibiotics Reveals Illicit Transport of Kasugamycin and Blasticidin S

Anthony L. Shiver; Hendrik Osadnik; George Kritikos; Bo Li; Nevan Krogan; Athanasios Typas; Carol A. Gross

摘要

This Research Article includes chemical genetics data which are shown in Fig 1 . Whilst revisiting the work presented in the paper, the authors identified two issues with these data. First, the published dataset is not the final version, as it lacks late-stage changes that were made during the normalization of the colony opacity measurements. Second, five conditions that were run multiple times had the repeat runs reported independently, thus affecting the estimate of pairwise gene correlations. The authors have corrected both of these issues in the dataset and are issuing this correction notice to provide readers with access to the corrected data. 10.1371/journal.pgen.1006902.g001 Fig 1 The chemical genomic screen expands our view of gene function and intrinsic resistance in E . coli K-12. (A) A scatter plot of individual fitness-scores for conditions in both screens (n = 12). Measurements between screens are reproducible, with a Pearson’s correlation of 0.58. B) Conditional-phenotypes were assigned using a stress-specific cutoff for fitness-scores that allowed a false discovery rate (FDR) of 5%. A responsive gene is defined as a gene with at least one phenotype in the dataset. Differences in the number of responsive genes in this dataset as compared to that reported by Nichols et al. predominantly reflects the fact that only 73% of the original conditions were reanalyzed. C) Significant correlations between genes were determined using a cutoff for Pearson’s correlation that allowed an FDR of 5%. The direct effect of these issues is restricted to the results in Fig 1B and 1C . These changes have a slight effect on fitness scores, number of responsive genes, and number of correlated gene pairs, but the issues identified have no impact on the overall results or conclusions of the paper, and only marginally affect the numerical values presented. Figs 1 , 2 and 3 and S1 Fig , S1 Dataset , S1 Table and the legends for Fig 1 , S1 Fig and S1 Dataset have been corrected to reflect the new dataset. All other legends, figures and supporting information remain unchanged. 10.1371/journal.pgen.1006902.g002 Fig 2 A diverse set of pathways contribute to antibiotic resistance. Fitness-scores from the integrated dataset connected antibiotic resistance to multiple biological pathways. (A) Genes with different resistance mechanisms (target pathway, stress response, drug efflux, detoxification, and drug import) that protect against stresses from the current screen are organized according to mechansim. (B) A heatmap of fitness-scores for translation related genes. Sensitivities of deletions of various translation associated factors distinguish between drug families targeting translation. Sensitivities to aminoglycosides (gentamicin), macrolides (clarithromycin), tetracyclines (tetracycline), chloramphenicol, and tRNA synthetase inhibitors (pseudomonic acid A and serine hydroxamate) are shown. Fitness-scores from the integrated dataset that were determined in Nichols et al. [8] are marked with an asterisk (*). (C) A heatmap of fitness-scores for genes related to drug efflux and detoxification. Multiple drugs from the new screen were connected with the major efflux pump of E . coli , AcrAB-TolC. 10.1371/journal.pgen.1006902.g003 Fig 3 Peptide ABC-importers determine susceptibility to kasugamycin and blasticidin S in E . coli K-12. (A) Structures of kasugamycin (Ksg) and blasticidin S (BcS). (B) Deletions of peptide importer genes are resistant to kasugamycin and blasticidin S. The heat-map of fitness-scores for dipeptide permease (Δ dppA , Δ dppB , Δ dppC , Δ dppD , and Δ dppF ), oligopeptide permease (Δ oppA , Δ oppB , Δ oppC , Δ oppD , and Δ oppF ), and their negative regulators (Δ hfq , Δ gcvA , and Δ gcvB ) for the entire set of new stresses is shown. Ksg and BcS are highlighted within the heatmap. (C) Deletions of each peptide permease operon show an increase in resistance to Ksg and BcS. 10-fold spot dilutions are shown for operon deletions Δ opp , Δ dpp and the double mutant Δ opp Δ dpp (D) Overexpression of opp results in a decrease in resistance to Ksg and BcS. 10-fold spot dilutions of cells with the high copy vector pDSW204 containing the opp operon (pOpp) grown without induction indicate decreased resistance to both Ksg and BcS relative to the empty vector control (vector). These changes also affect several sentences in the Results section and the correct sentences are provided below. Sentence one of the first paragraph under the sub-heading “The chemical-genomic screen substantially expands known connections in E . coli ”: We tested the sensitivities of 3975 mutants of E . coli K-12 to 51 stresses, split between new and previously screened conditions. Sentences four and five of the second paragraph under the subheading “The chemical-genomic screen substantially expands known connections in E . coli ”: We identified more than 5,000 conditional-phenotypes for the 26 new stresses, as well as more than 450 additional r

机译：该研究文章包括化学遗传数据，如图1所示。在回顾本文提出的工作的同时，作者发现这些数据存在两个问题。首先，已发布的数据集不是最终版本，因为它缺少在菌落不透明度测量标准化过程中进行的后期更改。第二，多次运行的五个条件具有独立报告的重复运行的信息，从而影响成对基因相关性的估计。作者已更正了数据集中的这两个问题，并发布了此更正通知，以使读者可以访问已更正的数据。 10.1371 / journal.pgen.1006902.g001图1化学基因组筛选扩大了我们对E的基因功能和内在抗性的看法。大肠杆菌K-12。（A）两个屏幕上条件的单个适合度得分的散点图（n = 12）。屏幕之间的测量是可重复的，皮尔森相关系数为0.58。 B）使用适合性评分的压力特定临界值指定条件表型，允许错误发现率（FDR）为5％。响应基因定义为数据集中具有至少一个表型的基因。与Nichols等人报道的相比，该数据集中的响应基因数量有所不同。主要反映了以下事实：仅对原始条件的73％进行了重新分析。 C）使用Pearson相关性的临界值（允许FDR为5％）确定基因之间的显着相关性。这些问题的直接影响仅限于图1B和1C中的结果。这些变化对适应度评分，响应基因的数量和相关基因对的数量有轻微的影响，但是发现的问题对论文的整体结果或结论没有影响，而只影响显示的数值。图1、2和3以及S1图，S1数据集，S1表以及图1，S1图和S1数据集的图例已得到纠正，以反映新的数据集。所有其他图例，图形和支持信息均保持不变。 10.1371 / journal.pgen.1006902.g002图2多种途径可导致抗生素耐药性。集成数据集中的健身评分将抗生素抗性与多种生物途径相关联。（A）根据机械机理，组织了具有不同抵抗机制（靶途径，应激反应，药物外排，排毒和药物导入）的基因，这些基因可以抵抗当前筛选中的压力。（B）与翻译相关的基因的适合度得分热图。各种翻译相关因子缺失的敏感性区分了靶向翻译的药物家族。显示了对氨基糖苷类（庆大霉素），大环内酯类（克拉霉素），四环素类（四环素），氯霉素和tRNA合成酶抑制剂（pseudomonic acid A和丝氨酸异羟肟酸酯）的敏感性。 Nichols等人确定的综合数据集的健身得分。 [8]标有星号（*）。（C）与药物外排和排毒相关的基因的适合度得分热图。新筛选中的多种药物与E的主要外排泵相连。大肠杆菌AcrAB-TolC。 10.1371 / journal.pgen.1006902.g003图3肽ABC进口商确定E中对春日霉素和杀稻瘟素S的敏感性。大肠杆菌K-12。（A）春日霉素（Ksg）和杀稻瘟素S（BcS）的结构。（B）肽导入基因的删除对春日霉素和杀稻瘟菌素S具有抗性。，ΔoppB，ΔoppC，ΔoppD和ΔoppF），以及它们在整个新应力集中的负调节器（Δhfq，ΔgcvA和ΔgcvB）均已显示。 Ksg和BcS在热图中突出显示。（C）每个肽渗透酶操纵子的缺失显示出对Ksg和BcS的抗性增加。对于操纵子缺失Δopp，Δdpp和双突变体ΔoppΔdpp（D），显示了10倍的斑点稀释度。opp的过表达导致对Ksg和BcS的抗性降低。具有高复制载体pDSW204的细胞的10倍点稀释液包含无诱导生长的opp操纵子（pOpp），这表明相对于空载体对照（载体），其对Ksg和BcS的抗性均降低。这些更改还会影响“结果”部分中的几个句子，下面提供了正确的句子。在“化学基因组筛选显着扩展了E中的已知连接”子句下的第一段句子。 ”：我们测试了3975个E突变体的敏感性。大肠杆菌K-12至51种压力，在新的和先前筛选的条件之间进行分配。在“化学基因组筛选显着扩展了E中的已知连接”子标题下，第二段的第四个句子和第五个句子。大肠杆菌”：我们为26种新的胁迫确定了5,000多种条件表型，以及另外450多种

Correction: A Chemical-Genomic Screen of Neglected Antibiotics Reveals Illicit Transport of Kasugamycin and Blasticidin S

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