Diverse intestinal microbiota is frequently used in in vitro bioreactor models to study the effects of diet, chemical contaminations, or medication. However, the reproducible cultivation of fecal microbiota is challenging and the resultant communities behave highly dynamic. To approach the issue of reproducibility in in vitro models, we established an intestinal microbiota model community of reduced complexity, SIHUMIx, as a valuable model for in vitro use. The development of the SIHUMIx community was monitored over time with methods covering the cellular and the molecular level. We used microbial flow cytometry, intact protein profiling and terminal restriction fragment length polymorphism analysis to assess community structure. In parallel, we analyzed the functional level by targeted analysis of short-chain fatty acids and untargeted metabolomics. The stability properties constancy, resistance, and resilience were approached both on the structural and functional level of the community. We show that the SIHUMIx community is highly reproducible and constant since day 5 of cultivation. Furthermore, SIHUMIx has the ability to resist and recover from a pulsed perturbation, with changes in community structure recovered earlier than functional changes. Since community structure and function changed divergently, both levels need to be monitored at the same time to gain a full overview of the community development. All five methods are highly suitable to follow the community dynamics of SIHUMIx and indicated stability on day five. This makes SIHUMIx a suitable in vitro model to investigate the effects of e.g. medical, chemical, or dietary interventions.

The identification rate of measured peptide spectra to proteins barely scratches 1% in best-case scenarios. Hundreds of thousands of valuable spectra are lost as no viable match in the database is found. Here, we apply the delta m/z plot that was previously implemented in MSnbase as tool for quality control to 63 soil samples from three ecosystems with different vegetation (39 forests, 11 grasslands, and 13 shrublands) with the aim to extract probable post-translational modifications (PTM) without the need of a reference database. The validity of the approach was verified with amino acids proposed for their respective 1 Da mass interval and compared to their relative abundance in proteins. We found that the average probable PTM and most known PTMs proposed for the mass intervals are similar across ecosystems. Otherwise, 11 mass intervals changed significantly in relative abundance in the three ecosystems but only for one an annotation could be proposed. Our approach not only highlights the opportunity of the database-independent analysis in soil metaproteomics but paves the way for targeted analysis of the yet unknown PTMs.