Biology subjects

Hammer, E. C.

Publications and source records attributed to Hammer, E. C..

4 recordsLinked to original sources

bioRxiv2025

Deep Learning Driven Investigation of Nanoplastic Impacts on Soil Protist Behavior in Soil Chips

Nanoplastics are emerging contaminants that have a significant impact on soil microorganisms. To fully understand the effect of plastic contamination on soil ecosystems, it is necessary to advance techniques that can monitor nanoplastic-microbe interactions under realistic conditions. In this work, we investigated the effects of nanoplastic contamination on a community of soil protists monitored through microfluidic soil chips, and analysed changes in their behavior via microscopy videos and a deep learning approach. The presented method employs a deep learning-based detection model combined with a transformer-based matching model for video frame interpolation, enabling accurate reconstruction of protist movement trajectories and velocities within soil chips. The results revealed reduced movement velocities for the groups of flagellates and ciliates under high nanoplastic conditions, a 24-30% reduction at a marginal significance level, while amoebae were unaffected. Our trajectory data provides novel insights into how protists navigate soil-like structures. By facilitating comprehensive assessments of protist-environment interactions, it opens new avenues for understanding their ecological roles and the broader implications of hazardous contaminants in both soil and aquatic ecosystems at microbial community level without need for culture extraction. This proof-of-concept system enables continuous, high-throughput monitoring of soil protist behavior and can be readily adapted to investigate protist responses to diverse chemical and physical soil hazards.

ecology↗

bioRxiv2025

Experimental suppression of a keystone protist triggers mesopredator release and biotic homogenization in complex soil microbial communities

The keystone species concept suggests that certain members of an ecological community, despite their low abundance, exert disproportionately large effects on species diversity and composition. In microbial ecology, experimental validation of this concept is limited due to significant technical challenges associated with selective species manipulation. Here, we tested this concept within a soil microbial food web by selectively suppressing a protist predator using phototoxicity induced by excessive excitation light during fluorescence microscopy within a microfluidic soil chip system. We targeted a Hypotrichia ciliate taxon--presumed primarily bacterivorous under our experimental conditions--and combined microscopy with metabarcoding of multiple microbial trophic levels to evaluate the effects of this suppression on microbial community abundance, diversity, and composition. Over the 20-day incubation, the chip system supported complex communities of bacteria, fungi, and protists. Following Hypotrichia suppression, two distinct ecological responses were observed: first, an increase in flagellate abundance that was consistent with mesopredator release and accompanied a significant rise in overall protist diversity; second, a convergence in protist community composition, indicative of biotic homogenization. Surprisingly, bacterial community abundance, richness, and composition remained unaffected, likely due to compensatory predation by increased numbers of bacterivorous flagellates. In contrast, fungal diversity decreased following Hypotrichia suppression, presumably resulting from the altered protist communities that favored facultative fungal consumers. Collectively, these findings provide direct experimental evidence that low-abundance microbial predators can function as keystone species, modulating predator community composition and diversity and having cascading effects on lower trophic levels within the brown microbial food web.

ecology↗

bioRxiv2023

Bacterial community characterization by deep learning aided image analysis in soil chips

Soil microbes play an important role in governing global processes such as carbon cycling, but it is challenging to study them embedded in their natural environment and at the single cell level due to the opaque nature of the soil. Nonetheless, progress has been achieved in recent years towards visualizing microbial activities and organo-mineral interaction at the pore scale, especially thanks to the development of microfluidic soil chips creating transparent soil model habitats. Image-based analyses come with new challenges as manual counting of bacteria in thousands of digital images taken from the soil chips is excessively time-consuming, while simple thresholding cannot be applied due to the background of soil minerals and debris. Here, we adopt the well-developed deep learning algorithm Mask-RCNN to quantitatively analyse the bacterial communities in soil samples from different locations in the world. This work demonstrates analysis of bacterial abundance from three contrasting locations (Greenland, Sweden and Kenya) using deep learning in microfluidic soil chips in order to characterize population and community dynamics. We additionally quantified cell- and colony morphology including cell size, shape and the cell aggregation level via calculation of the distance to the nearest neighbor. This approach allows for the first time an automated visual investigation of soil bacterial communities, and a crude biodiversity measure based on phenotypic cell morphology, which could become a valuable complement to molecular studies.

ecology↗

bioRxiv2023

Hyphal exploration strategies and habitat modification of an arbuscular mycorrhizal fungus in microengineered soil chips

Arbuscular mycorrhizal fungi (AMF) are considered ecosystem engineers, however, the exact mechanisms by which they modify and influence their immediate surroundings are largely unknown and difficult to study in soil. In this study, we used microfluidic chips, simulating artificial soil structures, to study foraging strategies and habitat modification of Rhizophagus irregularis in symbiotic state associated to carrot roots. Our results suggest that AMF hyphae forage over long distances in void spaces, prefer straight over tortuous passages, anastomose and show strong inducement of branching when encountering obstacles. We observed bi-directional vesicle transport inside active hyphae and documented strategic allocation of biomass within the mycelium e.g., truncated hyphal growth and cytoplasm retraction from inefficient paths. We found R. irregularis able to modify pore-spaces in the chips by producing irregularly shaped spores that filled up pores. We suggest that studying AMF hyphal behaviour in spatial settings can explain phenomena reported at bulk scale such as AMF modification of water retention in soils. The use of microfluidic soil chips in AMF research opens up novel opportunities to under very controlled conditions study ecophysiology and interactions of the mycelium with both biotic and abiotic factors.

microbiology↗