Biology subjects

Kreft, J.-U.

Publications and source records attributed to Kreft, J.-U..

10 recordsLinked to original sources

bioRxiv2026

Rapid Antimicrobial Resistance Decline Coupled with Microbial Community Shifts in Sewage Polluted River Mesocosms

Antimicrobial resistance poses a global health threat, yet the fate of antimicrobial resistance genes (ARGs) and microbial communities from wastewaters in receiving rivers is rarely quantified. This study investigated the degradation kinetics of ARGs in sewage-polluted river water mesocosms and under sulfamethoxazole and copper stress, separately and in combination. Seven clinically relevant ARGs (blaCTX-M, blaNDM, qnrS, sul2, tetW, ermF, and aph(3'')-Ib), a mobile genetic element marker (intI1) and bacterial marker genes (uidA, 16S rDNA) were quantified by qPCR. Bacterial community changes were monitored using 16S rDNA amplicon sequencing. All target genes decayed with approximately first-order kinetics in all conditions, with qnrS (half-life: 8.0 h) and blaCTX-M (8.4 h) declining most rapidly and intI1 (32.5 h) and sul2 (46.5 h) declining most slowly. Ordination showed that ARG composition shifted primarily over time rather than by antibiotic/metal treatment. Bacterial communities shifted from initially Campylobacterota dominated ([≥] 90%) to Pseudomonadota, Bacillota, and Actinomycetota dominated communities over 168 h. Quantitative microbiome profiling showed a 95% reduction in ASV richness. PICRUSt2 analysis suggested progressive enrichment of aerobic and several metabolic pathways, as the mesocosms transitioned from highly polluted anoxic conditions to oxygenated conditions. Shifts in microbial community composition were coupled with changes in the resistome as identified by Procrustes analyses (r = 0.841, p = 0.001) and other analyses. Together, results show that river self-purification can rapidly reduce ARG loads, at least in warmer climates. This study provides approximate kinetic parameters for mathematical models to predict the fate of ARGs in rivers.

microbiology↗

bioRxiv2026

Carbon and nitrogen availability affect biofilm growth and morphology of the extremotolerant fungus Knufia petricola

Rock-inhabiting fungi thrive in subaerial oligotrophic environments such as desert rocks, solar panels and marble monuments where organic carbon and nitrogen are scarce. We tested whether the rock-inhabiting fungus Knufia petricola showed a preference regarding nitrogen ([Formula] or [Formula]) and carbon (glucose or sucrose) sources and whether it was sensitive towards carbon and nitrogen limitation. As this fungus produces the carbon-rich, nitrogen-free 1,8-dihydroxynaphthalene (DHN) melanin, we tested whether a melanin-deficient mutant would be less sensitive to carbon limitation. The carbon and nitrogen concentrations were the primary predictors of growth, with a broad optimum partially explained by an optimal fungal C:N ratio. Limiting carbon or nitrogen supply decreased biomass formation, CO2 production and biofilm thickness but promoted substratum penetration through filamentous growth. The nitrogen content of the biomass was flexible within limits, increasing upon increasing nitrogen supply or decreasing carbon supply. The carbon use efficiency was fairly constant, whereas melanization correlated with a higher nitrogen content of the biomass despite melanin being nitrogen-free. In conclusion, in vitro, K. petricola switches to explorative growth under nutrient limitations, like fast-growing fungi, revealing universal fungal resource-acquisition patterns. Graphical abstract text and imageCarbon and nitrogen availability affect biofilm growth and morphology of the extremotolerant fungus Knufia petricola Abolfazl Dehkohneh, Julia Schumacher, Bastiaan J. R. Cockx, Karin Keil, Tessa Camenzind, Jan-Ulrich Kreft, Anna A. Gorbushina, Ruben Gerrits Growth of the rock-inhabiting fungus Knufia petricola was studied by varying carbon and nitrogen sources and concentrations. Overall, growth was best predicted by the carbon and nitrogen concentrations. Carbon and nitrogen limitation promoted substratum penetration through filamentous growth. O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/712823v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@6d98bdorg.highwire.dtl.DTLVardef@146aac5org.highwire.dtl.DTLVardef@757fa8org.highwire.dtl.DTLVardef@ff709_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Inferring antibiotic resistance selection in the environment can be confounded by correlations between resistance genes and unrelated functional traits

Antimicrobial resistance (AMR) is a silent pandemic that is coupled with other crises such as climate change in the polycrisis humanity is facing. One of the key questions is whether antibiotic resistance genes (ARGs) are selected for at the low antibiotic concentrations typical for most environments. Many studies have observed changes in the relative abundance of ARGs from one environmental compartment to the next, e.g. from wastewater treatment plant influent to effluent. Fewer studies have directly tested for selection by incubating environmental samples in mesocosms or laboratory models at different concentrations of antibiotics to infer minimal selective concentrations. We developed a mathematical model to demonstrate that these studies can be confounded by shifts in the microbial community composition that occur when a microbiome is transported from one environmental compartment to another or when incubated under different conditions. Such community shifts will confound tests of selection when there is an association between carriage of ARGs and other functional traits. As an example, we show that there is a phylum-dependent association between the number of ARGs and the number of ribosomal RNA genes, which are both higher in fast growing, copiotrophic bacteria. We then show that specific growth rate or nutrient concentration upshifts increased the proportion of copiotrophs in the community and thus the relative abundance of ARGs. This result generalizes to community shifts for other reasons if there is some association between ARGs and ecological niches. Therefore, most studies of selection for ARGs in the environment are confounded. Solutions are proposed. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/681873v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1ea4638org.highwire.dtl.DTLVardef@1a8471dorg.highwire.dtl.DTLVardef@d4d127org.highwire.dtl.DTLVardef@1ef891b_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIARG copy numbers are correlated with 16S rRNA gene copy numbers C_LIO_LIHigh rRNA gene numbers are typical for copiotrophs, which have high growth rates C_LIO_LIHence, copiotrophs tend to have higher ARG numbers C_LIO_LIChanges in environmental conditions that increase copiotrophs increase ARGs C_LIO_LIThus, ARGs can increase without selection due to shifts in community composition C_LI

microbiology↗

bioRxiv2025

Varied mutual growth inhibition between commensal yeasts and strains

Interkingdom interactions between bacteria and fungi are an emerging research field that provides insights into pathological, environmental, and microbiota-related relationships. However, the mechanisms governing these interactions, particularly in the context of microbial resistance, remain largely unknown. This study aims to enhance our understanding of the complex interactions between different Candida, Nakaseomyces and Sacharomyces species from the human microbiota and two not isogenic strains of Escherichia coli (antibiotic-susceptible E. coli-ATCC and multidrug-resistant E. coli-OXA48). Forty-nine Candida strains were co-cultured with the two E. coli strains. Both bacterial and yeast growth was monitored using flow cytometry and compared to monocultures. The effect of yeast culture supernatants on E. coli proliferation was also investigated. Metabolomic fingerprints and metabolite identification were performed using mass spectrometry-based approaches followed by multiblock statistical analyses. The inhibitory powers (IP) of yeasts against E. coli and vice versa varied significantly among fungal species. N. glabrata exhibited the strongest inhibition against E. coli-ATCC, while Candida lusitaniae, C. kefyr, C. krusei, C. tropicalis, and C. dubliniensis showed lower IPs. C. parapsilosis and Saccharomyces cerevisiae had no inhibitory effects. Against E. coli-OXA48, most yeasts displayed no inhibition, except for N. glabrata. Conversely, E. coli inhibited yeast growth more effectively, particularly Candida albicans. Fungal supernatants from S. cerevisiae, C. lusitaniae, and N. glabrata showed the highest inhibitory effects on E. coli-ATCC, while S. cerevisiae, C. krusei, and C. lusitaniae were most effective against E. coli-OXA48. Unsupervised metabolite profiling data analysis with multiblock approach highlighted a clustering of samples according to yeast species. Regarding inhibitory power on E. coli (ATCC or OXA48), active supernatants tend to cluster together suggesting the presence of similar metabolites; some were further characterized. This study highlights the diverse interactions between E. coli and commensal yeasts. From an applied perspective, these findings pave the way for identifying probiotics or postbiotics with potential applications in combating multidrug-resistant bacteria through novel antimicrobial compounds.

microbiology↗

bioRxiv2024

Field monitoring and hydraulic modelling quantify untreated wastewater as dominant source of AMR in a small river running through a big city

Quantifying sources of antimicrobial resistance (AMR) in rivers receiving various waste streams is essential for targeting mitigation strategies yet rarely performed. This study combined field monitoring with hydraulic modelling and mass balance calculations to attribute sources of AMR in the Musi River running through Hyderabad, India, a city renowned for pharmaceutical manufacturing. We quantified antibiotic resistance genes (ARGs), resistant bacteria (ARBs), and physicochemical parameters in water and sediment samples in the dry and wet season. Absolute ARG and ARB abundances spiked in the city, declining again downstream. Changes were more gradual in the wet season. Pollution levels were significantly different between upstream, city and downstream stretches and seasons. Hydraulic modelling revealed that 60-80% or 20-40% of the river water in the city derived from untreated sewage during the dry or wet seasons, respectively. This established municipal waste, not pharmaceutical sources, as the dominant driver of AMR in the Musi. Linear discriminant analysis identified dissolved oxygen and total nitrogen as reliable proxies for distinguishing AMR-polluted from less-polluted sites. The Musi, with insufficient wastewater treatment and limited dilution of point-source loadings, is typical for many urban rivers in resource-limited countries highlighting the urgent need for improved wastewater management to reduce AMR exposures.

microbiology↗

bioRxiv2023

Is it selfish to be filamentous in biofilms? Individual-based modeling links microbial growth strategies with morphology using the new and modular iDynoMiCS 2.0

Microbial communities are found in all habitable environments and often occur in assemblages with self-organized spatial structures developing over time. This complexity can only be understood, predicted, and managed by combining experiments with mathematical modeling. Individual-based models are particularly suited if individual heterogeneity, local interactions, and adaptive behavior are of interest. Here we present the completely overhauled software platform, the individual-based Dynamics of Microbial Communities Simulator, iDynoMiCS 2.0, which enables researchers to specify a range of different models without having to program. Key new features and improvements are: (1) Substantially enhanced ease of use (graphical user interface, editor for model specification, unit conversions, data analysis and visualization and more). (2) Increased performance and scalability enabling simulations of up to 10 million agents in 3D biofilms. (3) Kinetics can be specified with any arithmetic function. (4) Agent properties can be assembled from orthogonal modules for pick and mix flexibility. (5) Force-based mechanical interaction framework enabling attractive forces and non-spherical agent morphologies as an alternative to the shoving algorithm. The new iDynoMiCS 2.0 has undergone intensive testing, from unit tests to a suite of increasingly complex numerical tests and the standard Benchmark 3 based on nitrifying biofilms. A second test case was based on the "biofilms promote altruism" study previously implemented in BacSim because competition outcomes are highly sensitive to the developing spatial structures due to positive feedback between cooperative individuals. We extended this case study by adding morphology to find that (i) filamentous bacteria outcompete spherical bacteria regardless of growth strategy and (ii) non-cooperating filaments outcompete cooperating filaments because filaments can escape the stronger competition between themselves. In conclusion, the new substantially improved iDynoMiCS 2.0 joins a growing number of platforms for individual-based modeling of microbial communities with specific advantages and disadvantages that we discuss, giving users a wider choice. Author summaryMicrobes are fascinating in their own right and play a tremendously important role in ecosystems. They often form complex, self-organized communities with spatial heterogeneity that is changing over time. Such complexity is challenging to understand and manage without the help of mathematical models. Individual-based models are one type of mathematical model that is particularly suited if differences between individual microbes, local interactions and adaptive behavior are important. We have developed a completely overhauled version of iDynoMiCS, a software that allows users to develop, run and analyze a wide range of individual-based models without having to program the software themselves. There are several capability enhancements and numerous small improvements, for example the ability to model different shapes of cells combined with physically realistic mechanical interactions between neighboring cells. We showcase this by simulating the competition between filaments, long chains of cells, with single cells and find that filaments outcompete single cells as they can spread quickly to new territory with higher levels of resources. Users now have a wider choice of platforms so we provide guidance on which platform might be most suitable for a given purpose.

ecology↗

bioRxiv2022

Antimicrobial resistance in dairy slurry tanks: a critical point for measurement and control

Waste from dairy production is one of the worlds largest sources of contamination from antimicrobial resistant bacteria (ARB) and genes (ARGs). However, studies to date do not provide necessary evidence to inform antimicrobial resistance (AMR) countermeasures. We undertook a detailed, interdisciplinary, longitudinal analysis of dairy slurry waste. The slurry contained a population of ARB and ARGs, with resistances to current, historical and never-used on-farm antibiotics; resistances were associated with Gram-negative and Gram-positive bacteria and mobile elements (ISEcp1, Tn916, Tn21-family transposons). Modelling and experimental work suggested that these populations are in dynamic equilibrium, with microbial death balanced by fresh input. Consequently, storing slurry without further waste input for at least 60 days was predicted to reduce ARB spread onto land, with >99% reduction in cephalosporin resistant Escherichia coli. The model also indicated that for farms with low antibiotic use, further reductions are unlikely to reduce AMR further. We conclude that the slurry tank is a critical point for prevalence and control of AMR, and that measures to limit the spread of AMR from dairy waste should combine responsible antibiotic use, including low total quantity, avoidance of human critical antibiotics, and choosing antibiotics with shorter half-lives, coupled with appropriate slurry storage.

microbiology↗

bioRxiv2020

Towards a general model for predicting minimal metal concentrations co-selecting for antibiotic resistance plasmids

Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), Zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.

microbiology↗

bioRxiv2020

Damage repair versus aging in biofilms

The extent of senescence due to damage accumulation (or aging) is evidently evolvable as it varies hugely between species and is not universal, suggesting that its fitness advantages depend on life history and environment. In contrast, repair of damage is present in all organisms studied. Repair and segregation of damage have not always been considered as alternatives, despite the fundamental trade-off between investing resources into repair or growth. For unicellular organisms, unrepaired damage could be divided asymmetrically between daughter cells, leading to aging of one and rejuvenation of the other. Repair of unicells has been shown to be advantageous in well-mixed environments such as chemostats. However, most microorganisms live in spatially structured systems such as biofilms with gradients of environmental conditions and cellular physiology as well as clonal population structure. We asked whether this clonal structure might favor aging by damage segregation as this can be seen as a division of labor strategy, akin to the germline soma division in multicellular organisms. We used an individual-based model with a newly developed adaptive repair strategy where cells respond to their current intracellular damage levels by investing into repair machinery accordingly. We found that the new adaptive repair strategy was advantageous whenever efficient and optimal, both in biofilms and chemostats. Thus, biofilms do not favor a germline soma-like division of labor between daughter cells in terms of damage segregation. We suggest that damage segregation is only beneficial when active and effective, extrinsic mortality is high and a degree of multicellularity is present. IMPORTANCEDamage is an inevitable consequence of life, leading to a trade-off between allocating resources into damage repair or into growth whilst allowing aging, i.e., segregation of damage upon cell division. Few studies considered repair as an alternative to aging. Moreover, all previous studies merely considered well-mixed environments, although the vast majority of unicellular organisms live in spatially structured environments, exemplified by biofilms, and fitness advantages in well-mixed systems often turn into disadvantages in spatially structured systems. We compared the fitness consequences of aging versus damage repair in biofilms with an individual-based model implementing an adaptive repair mechanism based on sensing damage. We found that aging is not beneficial. Instead, it is useful as a stress response to deal with damage that failed to be repaired when (i) clearly asymmetric cell division is feasible; (ii) extrinsic mortality is high; and (iii) a degree of multicellularity is present.

microbiology↗

bioRxiv2019

Predation strategies of the bacterium Bdellovibrio bacteriovorus result in bottlenecks, overexploitation, minimal and optimal prey sizes

With increasing antimicrobial resistance, alternatives for treating infections or removing resistant bacteria are urgently needed, such as the bacterial predator Bdellovibrio bacteriovorus or bacteriophage. Therefore, we need to better understand microbial predator-prey dynamics. We developed mass-action mathematical models of predation for chemostats, which capture the low substrate concentration and slow growth typical for intended application areas of the predators such as wastewater treatment, aquaculture or the gut. Our model predicted that predator survival required a minimal prey size, explaining why Bdellovibrio is much smaller than its prey. A too good predator (attack rate too high, mortality too low) overexploited its prey leading to extinction (tragedy of the commons). Surprisingly, a predator taking longer to produce more offspring outcompeted a predator producing fewer offspring more rapidly (rate versus yield trade-off). Predation was only efficient in a narrow region around optimal parameters. Moreover, extreme oscillations under a wide range of conditions led to severe bottlenecks. A bacteriophage outcompeted Bdellovibrio due to its higher burst size and faster life cycle. Together, results suggest that Bdellovibrio would struggle to survive on a single prey, explaining why it must be a generalist predator and suggesting it is better suited than phage to environments with multiple prey. ImportanceThe discovery of antibiotics led to a dramatic drop in deaths due to infectious disease. Increasing levels of antimicrobial resistance, however, threaten to reverse this progress. There is thus a need for alternatives, such as therapies based on phage and predatory bacteria that kill bacteria regardless of whether they are pathogens or resistant to antibiotics. To best exploit them, we need to better understand what determines their effectiveness. By using a mathematical model to study bacterial predation in realistic slow growth conditions, we found that the generalist predator Bdellovibrio is most effective within a narrow range of conditions for each prey. For example, a minimum prey size is required, and the predator should not be too good as this would result in over-exploitation risking extinction. Together these findings give insights into the ecology of microbial predation and help explain why Bdellovibrio needs to be a generalist predator.

microbiology↗