Molecular and functional characterization of ILYS-5, a major invertebrate lysozyme of Caenorhabditis elegans.

To overcome bacterial invasion and infection, animals have evolved various antimicrobial effectors such as antimicrobial peptides and lysozymes. Although C. elegans is exposed to a variety of microbes due to its bacterivorous lifestyle, previous work on the components of its immune system mainly based on the description of transcriptional changes during bacterial challenges. Very few effector components of its immune system have been characterized so far. To investigate the role of lysozymes in terms of antibacterial defense and digestion, we studied a member of the widely neglected family of C. elegans invertebrate lysozymes (ILYS). We focused on the so far virtually undescribed ILYS-5, which we purified from protein extracts of C. elegans tracing its peptidoglycan-degrading activity and localized the tissue expression of the gene in vivo using a translational reporter construct. We recombinantly synthesized ILYS-5 and determined the physicochemical activity optimum and the antibacterial spectrum of a lysozyme from C. elegans for the first time. With an activity optimum at low ionic strength (≤100 mM) and at acidic pH (≤ pH 4.0), ILYS-5 is likely to be involved in killing and digestion of bacteria within acidified phagolysosomes and acidic regions of the gut, presumably secreted by lysosome-like vesicles. This notion is supported by potent activity against various live Gram-positive and Gram-negative bacteria. Notably, members of the natural associated microbiome of C. elegans are substantially less susceptible to ILYS-5. Ablation of the ilys-5 gene resulted in reduction of lifespan and fertility when cultured on the standard food bacterium Escherichia coli OP50, whereas exposure of the ilys-5 knock-out mutant to the host-associated bacterium Pseudomonas lurida MYb11 did not have a clear effect. These findings indicate a role of ILYS-5 in immunity and nutrition and a co-evolved adaptation of host and bacteria to the mutualistic nature of their interaction.

Symbiosis: Aquatic apicomplexans shedding light on disguised associations.

Aquatic apicomplexans called Corallicolida have been found in tropical and coral-reef settings, infecting many coral species. New data challenge this tropical distribution and expand the corallicolids' range well into the cold temperate. Surprisingly, the sister clade to corallicolids infects only one group of vertebrates - bony fishes.

Microbiome and Metabolome Insights into the Role of the Gastrointestinal-Brain Axis in Parkinson's and Alzheimer's Disease: Unveiling Potential Therapeutic Targets.

Neurodegenerative diseases such as Parkinson's (PD) and Alzheimer's disease (AD), the prevalence of which is rapidly rising due to an aging world population and westernization of lifestyles, are expected to put a strong socioeconomic burden on health systems worldwide. Clinical trials of therapies against PD and AD have only shown limited success so far. Therefore, research has extended its scope to a systems medicine point of view, with a particular focus on the gastrointestinal-brain axis as a potential main actor in disease development and progression. Microbiome and metabolome studies have already revealed important insights into disease mechanisms. Both the microbiome and metabolome can be easily manipulated by dietary and lifestyle interventions, and might thus offer novel, readily available therapeutic options to prevent the onset as well as the progression of PD and AD. This review summarizes our current knowledge on the interplay between microbiota, metabolites, and neurodegeneration along the gastrointestinal-brain axis. We further illustrate state-of-the art methods of microbiome and metabolome research as well as metabolic modeling that facilitate the identification of disease pathomechanisms. We conclude with therapeutic options to modulate microbiome composition to prevent or delay neurodegeneration and illustrate potential future research directions to fight PD and AD.

Bucket Fuser: Statistical Signal Extraction for 1D 1H NMR Metabolomic Data.

Untargeted metabolomics is a promising tool for identifying novel disease biomarkers and unraveling underlying pathomechanisms. Nuclear magnetic resonance (NMR) spectroscopy is particularly suited for large-scale untargeted metabolomics studies due to its high reproducibility and cost effectiveness. Here, one-dimensional (1D) 1H NMR experiments offer good sensitivity at reasonable measurement times. Their subsequent data analysis requires sophisticated data preprocessing steps, including the extraction of NMR features corresponding to specific metabolites. We developed a novel 1D NMR feature extraction procedure, called Bucket Fuser (BF), which is based on a regularized regression framework with fused group LASSO terms. The performance of the BF procedure was demonstrated using three independent NMR datasets and was benchmarked against existing state-of-the-art NMR feature extraction methods. BF dynamically constructs NMR metabolite features, the widths of which can be adjusted via a regularization parameter. BF consistently improved metabolite signal extraction, as demonstrated by our correlation analyses with absolutely quantified metabolites. It also yielded a higher proportion of statistically significant metabolite features in our differential metabolite analyses. The BF algorithm is computationally efficient and it can deal with small sample sizes. In summary, the Bucket Fuser algorithm, which is available as a supplementary python code, facilitates the fast and dynamic extraction of 1D NMR signals for the improved detection of metabolic biomarkers.