Biology subjects

van Opijnen, T.

Publications and source records attributed to van Opijnen, T..

4 recordsLinked to original sources

bioRxiv2018

The landscape of intrinsic and evolved fluoroquinolone resistance in Acinetobacter baumannii includes suppression of drug-induced prophage replication

The emergence of fluoroquinolone resistance in nosocomial pathogens has restricted the clinical efficacy of this antibiotic class. In Acinetobacter baumannii, the majority of clinical isolates now show high-level resistance due to mutations in gyrA (DNA gyrase) and parC (Topo IV). To investigate the molecular basis for fluoroquinolone resistance, an exhaustive mutation analysis was performed in both drug sensitive and resistant strains to identify loci that alter the sensitivity of the organism to ciprofloxacin. To this end, parallel fitness tests of over 60,000 unique insertion mutations were performed in strains with various alleles in genes encoding the drug targets. The spectrum of mutations that altered drug sensitivity was found to be similar in the drug sensitive and double mutant gyrAparC background having resistance alleles in both genes. In contrast, introduction of a single gyrA resistance allele, resulting in preferential poisoning of Topo IV by ciprofloxacin, led to extreme alterations in the insertion mutation fitness landscape. The distinguishing feature of preferential Topo IV poisoning was induction of DNA synthesis in the region of two endogenous prophages, which appeared to occur in situ. Induction of the selective DNA synthesis in the gyrA background was also linked to enhanced activation of SOS response and heightened transcription of prophage genes relative to that observed in either the WT or gyrAparC double mutants. Therefore, the accumulation of mutations that result in the stepwise evolution of high ciprofloxacin resistance is tightly connected to suppression of hyperactivation of the SOS response and endogenous prophage DNA synthesis.\n\nImportanceFluoroquinolones have been extremely successful antibiotics. Their clinical efficacy derives from the ability to target multiple bacterial enzymes critical to DNA replication, the topoisomerases DNA gyrase and Topo IV. Unfortunately, mutations lowering drug affinity for both enzymes are now widespread, rendering these drugs ineffective for many pathogens. To undermine this form of resistance, we sought to understand how bacteria with target alterations differentially cope with fluoroquinolone exposures. We studied this problem in the nosocomial pathogen A. baumannii, which causes resistant, life-threating infections. Employing genome-wide approaches, we uncovered numerous pathways that could be exploited to lower fluoroquinolone resistance independently of target alteration. Remarkably, fluoroquinolone targeting of Topo IV in specific mutants caused dramatic prophage hyperinduction, a response that was muted in strains with DNA gyrase as the primary target. This work demonstrates that resistance evolution via target modification can profoundly modulate the antibiotic stress response, revealing potential resistance-associated liabilities.

microbiology↗

bioRxiv2018

droplet-Tn-Seq combines microfluidics with Tn-Seq identifying complex single-cell phenotypes

While Tn-Seq is a powerful tool to determine genome-wide bacterial fitness in high-throughput, culturing transposon-mutant libraries in pools can mask community or other complex single-cell phenotypes. droplet-Tn-seq solves that problem by microfluidics facilitated encapsulation of individual transposon mutants into liquid-in-oil droplets, thereby enabling isolated growth, free from the influence of the population. Importantly, all advantages of Tn-Seq are conserved, while reducing costs and greatly extending its applicability.

microbiology↗

bioRxiv2018

Forecasting bacterial survival-success and adaptive evolution through multi-omics stress response-mapping, network analyses and machine learning

Whether a bacterial pathogen establishes an infection and/or evolves antibiotic resistance depends on successful survival while experiencing stress from for instance the host immune system and/or antibiotics. Predictions on bacterial survival and adaptive outcomes could thus have great prognostic value. However, it is unknown what information is required to enable such predictions. By developing a novel network-based analysis method, a bacterium's phenotypic and transcriptional response can be objectively quantified in temporal 3D-feature space. The resulting trajectories can be interpreted as a degree of coordination, where a focused and coordinated response predicts bacterial survival-success, and a random uncoordinated response predicts survival-failure. These predictions extend to both antibiotic resistance and in vivo infection conditions and are applicable to both Gram-positive and Gram-negative bacteria. Moreover, through experimental evolution we show that the degree of coordination is an adaptive outcome - an uncoordinated response evolves into a coordinated response when a bacterium adapts to its environment. Most surprisingly, it turns out that phenotypic and transcriptional response data, network features and genome plasticity data can be used to train a machine learning model that is able to predict which genes in the genome will adapt under nutrient or antibiotic selection. Importantly, this suggests that deterministic factors help drive adaptation and that evolution is, at least partially, predictable. This work demonstrates that with the right information predictions on bacterial short-term survival and long-term adaptive outcomes are feasible, which underscores that personalized infectious disease diagnostics and treatments are possible, and should be developed.

microbiology↗

bioRxiv2018

The Transcriptional landscape of Streptococcus pneumoniae reveals a complex operon architecture and abundant riboregulation critical for growth and virulence

Efficient and highly organized transcription initiation and termination is fundamental to an organisms ability to survive, proliferate, and quickly respond to its environment. Over the last decade, our simplistic outlook of bacterial transcriptional regulation and architecture has evolved to include stimulus-responsive regulation by untranslated RNA and the formation of alternate transcriptional units. In this study, we map the transcriptional landscape of the bacterial pathogen Streptococcus pneumoniae by applying a combination of high-throughput RNA-sequencing techniques. Our study reveals a complex transcriptome wherein environment-respondent alternate transcriptional units are observed within operons stemming from internal transcription start sites (TSS) and transcription terminators (TTS) suggesting that more fine-tuning of regulation occurs than previously thought. Additionally, we identify many putative cis-regulatory RNA elements and riboswitches within 5-untranslated regions (5-UTR) of genes. By integrating TSSs and TTSs with independently collected RNA-Seq datasets from a variety of conditions, we establish the response of these regulators to changes in growth conditions and validate several of them. Furthermore, to determine the importance of ribo-regulation by 5-UTR elements for in vivo virulence, we show that the pyrR regulatory element is essential for survival, successful colonization and infection in mice suggesting that such RNA elements are potential drug targets. Importantly, we show that our approach of combining high-throughput sequencing with in vivo experiments can reconstruct a global understanding of regulation, but also pave the way for discovery of compounds that target (ribo-) regulators to mitigate virulence and antibiotic resistance.

microbiology↗