Biology subjects

Michiels, J.

Publications and source records attributed to Michiels, J..

9 recordsLinked to original sources

bioRxiv2025

SquiDBase: a community resource of raw nanopore data from microbes

Experimental data-driven research relies on raw data, which consist of unprocessed experimental outputs, whereas derived data are transformed through a number of processing steps to reveal specific insights. Such processing, however, can potentially introduce biases or information loss, compromising transparency and reproducibility. In nucleic acid sequencing, nucleotide sequences stored in the FASTQ format are widely shared, but FASTQ files are generated from platform-specific raw data outputs, which vary depending on the sequencing platform used. The raw data produced by Oxford Nanopore Technologies (ONT) sequencing devices contain valuable biological information and are also useful to improve data processing methods, which includes basecaller optimisation and modification detection. Increasing attention goes to exploring these raw signals to develop algorithms that could improve ONT device portability and enhance target enrichment efficiency through adaptive sampling. Despite these benefits, the storage and sharing of raw nanopore data remain limited due to technical constraints and the lack of appropriate, standardised and centralised infrastructure. To address this challenge, we developed SquiDBase (https://squidbase.org), a dedicated repository to collect raw microbial nanopore sequencing data. To maximise the utility of SquiDBase from its inception, we built SquiDPipe, a Nextflow pipeline for the automated removal of human or unwanted reads from raw nanopore data. Additionally, we sequenced 24 clinically relevant viruses and incorporated them into SquiDBase, significantly expanding the diversity of publicly available reference datasets. By offering a centralised, open-access raw data collection platform, SquiDBase facilitates data sharing, enhances reproducibility, and supports the development and benchmarking of novel computational tools, reinforcing open science in nanopore sequencing research.

bioinformatics↗

bioRxiv2025

Reprogramming the EnvZ-OmpR two-component system confers ethanol tolerance in Escherichia coli by stabilizing the outer membrane and altering iron homeostasis.

Ethanol is a fermentation product widely used as a fuel and chemical precursor in various applications. However, its accumulation imposes severe stress on the microbial producer, leading to significant production losses. To address this, improving a strains ethanol tolerance is considered an effective strategy to enhance production. In our previous research, we conducted an adaptive evolution experiment with Escherichia coli growing under gradually increasing concentrations of ethanol, which gave rise to multiple hypertolerant populations. Based on the genomic mutational data, we demonstrated in this work that adaptive alleles in the EnvZ-OmpR two-component system drive the development of ethanol tolerance in E. coli. Specifically, when a single leucine was substituted for a proline residue within the periplasmic domain using CRISPR, the mutated EnvZ osmosensor caused a significant increase in ethanol tolerance. Through promoter fusion assays, we showed that this particular mutation stabilizes EnvZ in a kinase-dominating state, which reprograms signal transduction involving its cognate OmpR response regulator. Whole-genome proteomics analysis revealed that this altered signaling pathway predominantly maintains outer membrane stability by upregulating global porin levels and attenuating iron metabolism in the tolerant envZ*L116P mutant. Moreover, we demonstrated that the hypertolerant envZ*L116P allele also promotes ethanol productivity in fermentation, providing valuable insights for enhancing industrial ethanol production. AUTHOR SUMMARYEthanol is a versatile chemical with many applications, but producing it in high quantities remains a challenge. This is because Escherichia coli, a candidate ethanol production strain, is naturally sensitive to this short-chain alcohol, especially when levels are gradually accumulating during fermentation. To resolve this bottleneck, we have investigated how E. coli can acquire tolerance to its own toxic fermentation product. Our research indicated that a single amino acid substitution in EnvZ-a key sensor protein that normally protects E. coli against extreme osmotic stress-is sufficient to confer ethanol tolerance. Further analysis revealed that the mutation perturbs the EnvZ-mediated signaling cascade, which, in turn, changes the transporter composition in the outer membrane and attenuates the cells iron metabolism. These adaptations enable E. coli to survive under high-ethanol conditions, thereby promoting its ethanol production efficiency. This discovery provides a suitable strategy to increase ethanol titers in industrial settings using fermentation.

microbiology↗

bioRxiv2024

Systematic mapping of antibiotic cross-resistance and collateral sensitivity with chemical genetics

By acquiring or evolving resistance to one antibiotic, bacteria can become resistant to a second one, due to shared underlying mechanisms. This is called cross-resistance (XR) and further limits therapeutic choices. The opposite scenario, in which initial resistance leads to sensitivity to a second antibiotic, is termed collateral sensitivity (CS) and can inform cycling or combinatorial treatments. Despite their clinical relevance, our current knowledge of such interactions is limited, mostly due to experimental constraints in their assessment and lack of understanding of the underlying mechanisms. To fill this gap, we used published chemical genetic data on the impact of all Escherichia coli non-essential genes on resistance/sensitivity to 40 antibiotics, and devised a metric that robustly discriminates between known XR and CS antibiotic interactions. This metric, based on chemical genetic profile (dis)similarity between two drugs, allowed us to infer 404 XR and 267 CS interactions, thereby expanding the number of known interactions by more than 3-fold - including reclassifying 116 previously reported interactions. We benchmarked our results by validating 55 out of 59 inferred interactions via experimental evolution. By identifying mutants driving XR and CS interactions in chemical genetics, we recapitulated known and uncovered previously unknown mechanisms, and demonstrated that a given drug pair can exhibit both interactions depending on the resistance mechanism. Finally, we applied CS drug pairs in combination to reduce antibiotic resistance development in vitro. Altogether, our approach provides a systematic framework to map XR/CS interactions and their mechanisms, paving the way for the development of rationally-designed antibiotic combination treatments.

systems biology↗

bioRxiv2022

In vitro persistence level reflects in vivo antibiotic survival of natural Pseudomonas aeruginosa isolates in a murine lung infection model

Nowadays, clinicians are more and more confronted with the limitations of antibiotics to completely cure bacterial infections in patients. It has long been assumed that only antibiotic resistance plays a pivotal role in this. Indeed, the worldwide emergence of antibiotic resistance is considered as one of the major health threats of the 21st century. However, the presence of persister cells also has a significant influence on treatment outcomes. These antibiotic-tolerant cells are present in every bacterial population and are the result of the phenotypic switching of normal, antibiotic-sensitive cells. Persister cells complicate current antibiotic therapies and contribute to the development of resistance. In the past, extensive research has been performed to investigate persistence in laboratory settings, however, antibiotic tolerance in conditions that mimic the clinical setting is still poorly understood. In this study, we have optimized a mouse model for lung infections of the opportunistic pathogen Pseudomonas aeruginosa. In this model, mice are intratracheally infected with P. aeruginosa embedded in seaweed alginate beads and subsequently treated with tobramycin via nasal droplets. A strain panel of 18 P. aeruginosa isolates originating from environmental, human and animal clinical sources was selected to assess survival in the animal model. These survival levels were positively correlated with the survival levels determined via time-kill assays which is a common method to study persistence in the laboratory. We showed that both survival levels are comparable and thus that the classical persister assays are indicative for antibiotic tolerance in a clinical setting. The optimized animal model also allows us to test potential antipersister molecules and study persistence. ImportanceThe importance of targeting persister cells in antibiotic therapies becomes more evident as these antibiotic-tolerant cells underlie relapsing infections and resistance development. Here, we studied persistence in a clinically relevant pathogen, Pseudomonas aeruginosa. It is one of the six ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, P. aeruginosa, Enterobacter spp.) that are considered as a major health threat. P. aeruginosa is mostly known for causing chronic lung infections in cystic fibrosis patients. We mimicked these lung infections in a mouse model to study persistence in more clinical conditions. We showed that the survival levels of natural P. aeruginosa isolates in this model are positively correlated with the survival levels measured in classical persistence assays. These results not only validate the use of our current techniques to study persistence, but also open opportunities to study new persistence mechanisms or evaluate new antipersister compounds in vivo.

microbiology↗

bioRxiv2022

Deep mutational scanning of essential bacterial proteins can guide antibiotic development

Deep mutational scanning is a powerful approach to investigate a wide variety of research questions including protein function and stability. We performed deep mutational scanning on three essential E. coli proteins (FabZ, LpxC and MurA) involved in cell envelope synthesis using high-throughput CRISPR genome editing. This allowed us to study the effect of the introduced mutations in their original genomic context. Using more than 17,000 variants of FabZ, LpxC and MurA from the saturation editing libraries constructed here, we have interrogated protein function and the importance of individual amino acids in supporting viability. Additionally, we have exploited these libraries to study resistance development against antimicrobial compounds that target the selected proteins. Our results show that, among the three proteins studied, MurA is the superior antimicrobial target due to its low mutational flexibility which decreases the chance of acquiring resistance-conferring mutations that simultaneously preserve MurA function. Additionally, we were able to rank anti-LpxC lead compounds for further development guided by the number of resistance-conferring mutations against each compound. Our results show that deep mutational scanning studies can be used to guide drug development, which we hope will contribute towards the development of urgently needed novel antimicrobial therapies.

microbiology↗

bioRxiv2021

Transcription-coupled DNA repair underlies variation in persister awakening and the emergence of resistance

Persisters constitute a population of temporarily antibiotic-tolerant variants in an isogenic bacterial population and are considered an important cause of relapsing infections. It is currently unclear how cellular damage inflicted by antibiotic action is reversed upon persister state exit and how this relates to antibiotic resistance development. We demonstrate that persisters, upon fluoroquinolone treatment, accumulate oxidative damage which is repaired through nucleotide excision repair. Detection of the damage occurs via transcription-coupled repair using UvrD-mediated backtracking or Mfd-mediated displacement of the RNA polymerase. This competition results in heterogeneity in persister awakening lags. Most persisters repair the oxidative DNA damage, displaying a mutation rate equal to the untreated population. However, the promutagenic factor Mfd increases the mutation rate in a persister subpopulation. Our data provide in-depth insight in the molecular mechanisms underlying persister survival and pinpoints Mfd as an important molecular factor linking persistence to resistance development.

microbiology↗

bioRxiv2021

Alternative dimerization is required for activity and inhibition of the HEPN ribonuclease RnlA

The rnlAB toxin-antitoxin operon from Escherichia coli functions as an anti-phage defense system. RnlA was recently identified as a member of the HEPN (Higher Eukaryotes and Prokaryotes Nucleotide-binding domain) superfamily of ribonucleases. The activity of the toxin RnlA requires tight regulation by the antitoxin RnlB, the mechanism of which remains unknown. Here we show that RnlA exists in an equilibrium between two different homodimer states: an inactive resting state and an active canonical HEPN dimer. Mutants interfering with the transition between states show that canonical HEPN dimerization via the highly conserved RX4-6H motif is required for activity. The antitoxin RnlB binds the canonical HEPN dimer conformation, inhibiting RnlA by blocking access to its active site. Single-alanine substitutions mutants of the highly conserved R255, E258, R318 and H323 show that these residues are involved in catalysis and substrate binding and locate the catalytic site near the dimer interface of the canonical HEPN dimer rather than in a groove located between the HEPN domain and the preceding TBP-like domain. Overall, these findings elucidate the structural basis of the activity and inhibition of RnlA and highlight the crucial role of conformational heterogeneity in protein function.

biophysics↗

bioRxiv2021

The dynamic transition of persistence towards the VBNC state during stationary phase is driven by protein aggregation

Decades of research into bacterial persistence has been unable to fully characterize this antibiotic-tolerant phenotype, thereby hampering the development of therapies effective against chronic infections. Although some active persister mechanisms have been identified, the prevailing view is that cells become persistent because they enter a dormant state. We therefore characterized starvation-induced dormancy in Escherichia coli. Our findings indicate that dormancy develops gradually; persistence strongly increases during stationary phase and decreases again as persisters enter the viable but nonculturable (VBNC) state. Importantly, we show that dormancy development is tightly associated with progressive protein aggregation, which occurs concomitantly with ATP depletion during starvation. Persisters contain protein aggregates in an early developmental stage while VBNC cells carry more mature aggregates. Finally, we show that at least one persister protein, ObgE, works by triggering aggregation and thereby changing the dynamics of persistence and dormancy development. These findings provide evidence for a genetically-controlled, gradual development of persisters and VBNC cells through protein aggregation.

microbiology↗

bioRxiv2019

Isolation of persisters enabled by ss-lactam-induced filamentation reveals their single-cell awakening characteristics

When exposed to lethal doses of antibiotics, bacterial populations are most often not completely eradicated. A small number of phenotypic variants, defined as persisters, are refractory to antibiotics and survive treatment. Despite their involvement in relapsing infections caused by major pathogens, processes determining phenotypic switches from and to the persister state largely remain elusive. This is mainly due to the low frequency of persisters in a population and the lack of reliable persistence markers, both hampering studies of persistence at the single-cell level. Problematically, existing methods to enrich for persisters result in samples with very low persister densities and/or a too high abundance of other cell types. Here we present a novel and highly effective persister isolation method involving cephalexin, an antibiotic that induces extensive filamentation of susceptible cells. We show that antibiotic-tolerant cells can easily be separated by size after a short cephalexin treatment, and that the isolated cells are genuine persisters. We used our isolation method to monitor persister outgrowth at the single-cell level in a microfluidic device, thereby conclusively demonstrating that awakening is a stochastic phenomenon. We anticipate that our novel approach can have far-reaching consequences in the persistence field, by allowing single-cell studies at a much higher throughput than previously reported.

microbiology↗