Biology subjects

Nordholt, N.

Publications and source records attributed to Nordholt, N..

7 recordsLinked to original sources

bioRxiv2026

Incomplete killing by antimicrobial metals generates transient antibiotic tolerance via delayed recovery in Escherichia coli

Incomplete killing is common after application of disinfectants or use of antimicrobial surfaces, leaving behind bacterial survivors with poorly characterized physiology. Here, we investigated the effects of short biocidal exposure to the common antimicrobial metals copper and silver as metal ions in suspension or under semi-dry conditions on solid metallic surfaces used against Escherichia coli. Survivors exhibited delayed regrowth and increased tolerance to bactericidal antibiotics without changes in MIC, consistent with a transient, non-genetic tolerance phenotype. When the magnitude of killing by silver or copper was matched between exposure formats, antibiotic tolerance patterns converged across metals and exposure conditions, indicating that the survivor state is governed more strongly by the severity of the primary lethal stress than by metal identity or exposure format alone. Incremental copper exposure revealed a dose- dependent increase in delayed regrowth and antibiotic tolerance but reduced tolerance to subsequent copper exposure. Post-exposure antibiotic tolerance as well as copper hypersensitivity phenotypes reverted after regrowth. Together, this supports a model of injury-linked delayed recovery rather than generalized stress priming. These findings demonstrate that incomplete disinfection can reshape survivor physiology, transiently increasing antibiotic tolerance through combined effects of selective survival acting on pre-existing phenotypic heterogeneity and acute injury-linked delayed recovery.

microbiology↗

bioRxiv2026

A growth-survival trade-off quantitatively predicts microbial selection under periodic disinfection

AO_SCPLOWBSTRACTC_SCPLOWMicrobial populations frequently experience periodic lethal stresses from natural and anthropogenic sources, including routine disinfection in clinical, industrial, and domestic environments. However, periodic disinfection can rapidly select for tolerant strains with increased survival but reduced growth during permissive conditions, creating a trade-off that shapes competitive outcomes in microbial communities. Here, we develop a mathematical framework to quantify and predict selection between microbial strains competing for growth-limiting resources under periodic disinfection. The framework is validated through a competition experiment simulating periodic disinfection with benzalkonium chloride between a wild-type Escherichia coli strain and a tolerant mutant exhibiting increased survival but decreased growth. A minimal model incorporating growth rate during permissive conditions and disinfection survival quantitatively captures selection across different experimental scenarios, including uncertainty estimates propagated from parameter variance. We further provide analytical expressions and a web-based interface to determine selection outcomes and quantify the contributions of survival and growth rate to selection. Our framework establishes a quantitative basis for predicting when periodic disinfection shifts population composition towards tolerant strains and is generalizable to other lethal stresses, including antibiotic chemotherapy and physical inactivation, thereby contributing to our understanding of the impact of periodic selective pressures on microbial competition.

microbiology↗

bioRxiv2025

Consequences of benzalkonium chloride tolerance for selection dynamics and de novo resistance evolution driven by antibiotics

Biocides are used in large amounts in industrial, medical, and domestic settings. Benzalkonium chloride (BAC) is a commonly used biocide, for which previous research revealed that Escherichia coli can rapidly adapt to tolerate BAC disinfection, with consequences for antibiotic susceptibility. However, the consequences of BAC tolerance for selection dynamics and resistance evolution to antibiotics remain unknown. Here, we investigated in detail the effect of BAC-tolerance in E. coli on its response upon challenge with different classes of antibiotics. Competition assays showed that subinhibitory concentrations of ciprofloxacin - but not ampicillin, colistin and gentamicin - select for the BAC-tolerant strain over the BAC-sensitive ancestor at a minimal selective concentration of 0.0013-0.0022 {micro}g/mL ciprofloxacin. In contrast, the BAC-sensitive ancestor was more likely to evolve resistance to ciprofloxacin, colistin and gentamicin than the BAC-tolerant strain when adapted to higher concentrations of antibiotics in a serial transfer laboratory evolution experiment. The observed difference in the evolvability of resistance to ciprofloxacin was partly explained by a negative epistatic interaction between the mutations conferring BAC-tolerance and a knockout mutation in the gene encoding for the outer membrane porin F. Taken together, these findings suggest that BAC-induced tolerance can be stabilized in environments containing low concentrations of ciprofloxacin, while it also constrains evolutionary pathways towards antibiotic resistance.

microbiology↗

bioRxiv2022

A fluorescently labelled quaternary ammonium compound (NBD-DDA) to study mode-of-action and resistance mechanisms in bacteria

Quaternary ammonium compounds (QACs) are widely used as active agents in disinfectants, antiseptics, and preservatives. Despite being in use since the 1940s, there remain multiple open questions regarding their detailed mode-of-action and the mechanisms, including phenotypic heterogeneity, that can make bacteria less susceptible to QACs. To facilitate mode-of-action studies, we synthesized a fluorescent analogue of the quaternary ammonium compound benzalkonium chloride, namely N-dodecyl-N,N-dimethyl-[2-[(4-nitro-2,1,3-benzoxadiazol-7-yl)amino]ethyl]azanium-iodide (NBD-DDA). NBD-DDA is readily detected by flow cytometry and fluorescence microscopy with standard GFP/FITC-settings, making it suitable for molecular and single-cell studies. NBD-DDA was then used to investigate resistance mechanisms which can be heterogeneous among individual bacterial cells. Our results reveal that the antimicrobial activity of NBD-DDA against E. coli, S. aureus and P. aeruginosa is comparable to that of benzalkonium chloride (BAC), a widely used QAC. Characteristic time-kill kinetics and increased tolerance of a BAC tolerant E. coli strain against NBD-DDA suggest that the mode of action of NBD-DDA is similar to that of BAC. Leveraging these findings and NBD-DDAs fluorescent properties, we show that reduced cellular adsorption is responsible for the evolved BAC tolerance in the BAC tolerant E. coli strain. As revealed by confocal laser scanning microscopy (CLSM), NBD-DDA is preferentially localized in the cell envelope of E. coli, which is a primary target of BAC and other QACs. Overall, NBD-DDAs antimicrobial activity, its fluorescent properties, and its ease of detection render it a powerful tool to study the mode-of-action and the resistance mechanisms of QACs in bacteria.

microbiology↗

bioRxiv2022

Time-kill kinetics reveal heterogeneous tolerance to disinfectants

Disinfection is an important strategy to limit the spread of infections. Failure of disinfection may facilitate evolution of resistance against disinfectants and antibiotics through the processes of cross-resistance and co-resistance. The best possible outcome of disinfection minimizes the number of surviving bacteria and the chance for resistance evolution. Resistance describes the ability to grow in previously inhibitory concentrations of an antimicrobial, whereas tolerance is associated with enhanced survival of lethal doses. Individual bacteria from the same population can display considerable heterogeneity in their ability to survive treatment (i.e. tolerance) with antimicrobials, which can result in unexpected treatment failure. Here, we investigated how phenotypic heterogeneity affects the ability of E. coli to survive treatment with six different substances commonly used as active substances in disinfectants, preservatives and antiseptics. A mathematical model which assumes that phenotypic heterogeneity underlies the observed disinfection kinetics was used to infer whether time-kill kinetics were caused by a tolerant subpopulation. The analysis identified bimodal kill kinetics for benzalkonium chloride (BAC), didecyldimethylammonium chloride (DDAC), and isopropanol (Iso). In contrast, kill kinetics by chlorhexidine (CHX), glutaraldehyde (GTA), and hydrogen peroxide (H2O2) were best explained by unimodal kill kinetics underpinned by a broad distribution of tolerance times for CHX as opposed to a narrow distribution of tolerance times for GTA and H2O2. These findings have implications for the risk of disinfection failure, with potential consequences for the evolution of antimicrobial resistance and tolerance.

microbiology↗

bioRxiv2019

Growth-rate and protein-synthesis dynamics of single Bacillus subtilis cells along their cell-cycle

The growth rate of single bacterial cells is continuously disturbed by random fluctuations in biosynthesis rates and by deterministic cell-cycle events, such as division, genome duplication, and septum formation. It is not understood whether, and how, bacteria reject these disturbances. Here we quantified growth and constitutive protein expression dynamics of single Bacillus subtilis cells, as a function of cell-cycle-progression. Variation in birth size and growth rate, resulting from unequal cell division, is largely compensated for when cells divide again. We analysed the cell-cycle-dynamics of these compensations and found that both growth and protein expression exhibited biphasic behaviour. During a first phase of variable duration, the absolute rates were approximately constant and cells behaved as sizers. In the second phase, rates increased and growth behaviour exhibited characteristics of a timer-strategy. This work shows how cell-cycle-dependent rate adjustments of biosynthesis and growth are integrated to compensate for physio-logical disturbances caused by cell division.\n\nIMPORTANCEUnder constant conditions, bacterial populations can maintain a fixed average cell size and constant exponential growth rate. At the single cell-level, however, cell-division can cause significant physiological perturbations, requiring compensatory mechanisms to restore the growth-related characteristics of individual cells toward that of the average cell. Currently, there is still a major gap in our understanding of the dynamics of these mechanisms, i.e. how adjustments in growth, metabolism and biosynthesis are integrated during the bacterial cell-cycle to compensate the disturbances caused by cell division. Here we quantify growth and constitutive protein expression in individual bacterial cells at sub-cell-cycle resolution. Significantly, both growth and protein production rates display structured and coordinated cell-cycle-dependent dynamics. These patterns reveal the dynamics of growth rate and size compensations during cell-cycle progression. Our findings provide a dynamic cell-cycle perspective that offers novel avenues for the interpretation of physiological processes that underlie cellular homeostasis in bacteria.

microbiology↗

bioRxiv2017

Statistics and simulation of growth of single bacterial cells: illustrations with B. subtilis and E. coli

The inherent stochasticity of molecular reactions prevents us from predicting the exact state of single-cells in a population. However, when a population grows at steady-state, the probability to observe a cell with particular combinations of properties is fixed. Here we validate and exploit existing theory on the statistics of single-cell growth in order to predict the probability of phenotypic characteristics such as cell-cycle times, volumes, accuracy of division and cell-age distributions, using real-time imaging data for Escherichia coli and Bacillus subtilis. Our results show that single-cell growth-statistics can accurately be predicted from a few basic measurements. These equations relate different phenotypic characteristics, and can therefore be used in consistency tests of experimental single-cell growth data and prediction of single-cell statistics. We also exploit these statistical relations in the development of a fast stochastic-simulation algorithm of single-cell growth and protein expression. This algorithm greatly reduces computational burden, by recovering the statistics of growing cell-populations from the simulation of only one of its lineages. Our approach is validated by comparison of simulations and experimental data. This work illustrates a methodology for the prediction, analysis and tests of consistency of single-cell growth and protein expression data from a few basic statistical principles.

microbiology↗