Biology subjects

Ottensmann, M.

Publications and source records attributed to Ottensmann, M..

2 recordsLinked to original sources

bioRxiv2024

The gut microbiota-immune-brain axis in a wild vertebrate: dynamic interactions and health impacts

The gut microbiota-immune-brain axis is a feedback network which influences diverse physiological processes and plays a pivotal role in overall health and well-being. Although research in humans and laboratory mice has shed light into the associations and mechanisms governing this communication network, evidence of such interactions in wild, especially in young animals, is lacking. We therefore investigated these interactions during early development in a population of common buzzards (Buteo buteo) and their effects on individual condition. In a longitudinal study, we used a multi-marker approach to establish potential links between the bacterial and eukaryotic gut microbiota, a panel of immune assays and feather corticosterone measurements as a proxy for long-term stress. Using Bayesian structural equation modelling, we found no support for feedback between gut microbial diversity and immune or stress parameters. However, we did find strong relationships in the feedback network. Immunity was negatively correlated with corticosterone levels, and microbial diversity was positively associated with nestling body condition. Furthermore, corticosterone levels and eukaryotic microbiota diversity decreased with age while immune activity increased. The absence of conclusive support for the microbiota-immune-brain axis in common buzzard nestlings, coupled with the evidence for stress mediated immunosuppression, suggests a dominating role of stress-dominated maturation of the immune system during early development. Confounding factors inherent to wild systems and developing animals might override associations known from adult laboratory model subjects. The positive association between microbial diversity and body condition indicates the potential health benefits of possessing a diverse and stable microbiota.

microbiology↗

bioRxiv2017

GCalignR: An R package for aligning Gas-Chromatography data

Chemical cues are arguably the most fundamental means of animal communication and play an important role in mate choice and kin recognition. Consequently, gas chromatography (GC) in combination with either mass spectrometry (MS) or flame ionisation detection (FID) are commonly used to characterise complex chemical samples. Both GC-FID and GC-MS generate chromatograms comprising peaks that are separated according to their retention times and which represent different substances. Across chromatograms of different samples, homologous substances are expected to elute at similar retention times. However, random and often unavoidable experimental variation introduces noise, making the alignment of homologous peaks challenging, particularly with GC-FID data where mass spectral data are lacking. Here we present GCalignR, a user-friendly R package for aligning GC-FID data based on retention times. The package also implements dynamic visualisations to facilitate inspection and fine-tuning of the resulting alignments, and can be integrated within a broader workflow in R to facilitate downstream multivariate analyses. We demonstrate an example workflow using empirical data from Antarctic fur seals and explore the impact of user-defined parameter values by calculating alignment error rates for multiple datasets. The resulting alignments had low error rates for most of the explored parameter space and we could also show that GCalignR performed equally well or better than other available software. We hope that GCalignR will help to simplify the processing of chemical datasets and improve the standardization and reproducibility of chemical analyses in studies of animal chemical communication and related fields.

animal behavior and cognition↗