The Caenorhabditis elegans proteome response to two protective Pseudomonas symbionts.

The Caenorhabditis elegans natural microbiota isolates Pseudomonas lurida MYb11 and Pseudomonas fluorescens MYb115 protect the host against pathogens through distinct mechanisms. While P. lurida produces an antimicrobial compound and directly inhibits pathogen growth, P. fluorescens MYb115 protects the host without affecting pathogen growth. It is unknown how these two protective microbes affect host biological processes. We used a proteomics approach to elucidate the C. elegans response to MYb11 and MYb115. We found that both Pseudomonas isolates increase vitellogenin protein production in young adults, which confirms previous findings on the effect of microbiota on C. elegans reproductive timing. Moreover, the C. elegans responses to MYb11 and MYb115 exhibit common signatures with the response to other vitamin B12-producing bacteria, emphasizing the importance of vitamin B12 in C. elegans-microbe metabolic interactions. We further analyzed signatures in the C. elegans response specific to MYb11 or MYb115. We provide evidence for distinct modifications in lipid metabolism by both symbiotic microbes. We could identify the activation of host-pathogen defense responses as an MYb11-specific proteome signature and provide evidence that the intermediate filament protein IFB-2 is required for MYb115-mediated protection. These results indicate that MYb11 not only produces an antimicrobial compound but also activates host antimicrobial defenses, which together might increase resistance to infection. In contrast, MYb115 affects host processes such as lipid metabolism and cytoskeleton dynamics, which might increase host tolerance to infection. Overall, this study pinpoints proteins of interest that form the basis for additional exploration into the mechanisms underlying C. elegans microbiota-mediated protection from pathogen infection and other microbiota-mediated traits.IMPORTANCESymbiotic bacteria can defend their host against pathogen infection. While some protective symbionts directly interact with pathogenic bacteria, other protective symbionts elicit a response in the host that improves its own pathogen defenses. To better understand how a host responds to protective symbionts, we examined which host proteins are affected by two protective Pseudomonas bacteria in the model nematode Caenorhabditis elegans. We found that the C. elegans response to its protective symbionts is manifold, which was reflected in changes in proteins that are involved in metabolism, the immune system, and cell structure. This study provides a foundation for exploring the contribution of the host response to symbiont-mediated protection from pathogen infection.

Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics.

While numerous health-beneficial interactions between host and microbiota have been identified, there is still a lack of targeted approaches for modulating these interactions. Thus, we here identify precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In the first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we use metabolic modeling to identify precision prebiotics for a two-member Caenorhabditis elegans microbiome community comprising the immune-protective target species Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71. We experimentally confirm four of the predicted precision prebiotics, L-serine, L-threonine, D-mannitol, and γ-aminobutyric acid, to specifically increase the abundance of MYb11. L-serine was further assessed in vivo, leading to an increase in MYb11 abundance also in the worm host. Overall, our findings demonstrate that metabolic modeling is an effective tool for the design of precision prebiotics as an important cornerstone for future microbiome-targeted therapies.IMPORTANCEWhile various mechanisms through which the microbiome influences disease processes in the host have been identified, there are still only few approaches that allow for targeted manipulation of microbiome composition as a first step toward microbiome-based therapies. Here, we propose the concept of precision prebiotics that allow to boost the abundance of already resident health-beneficial microbial species in a microbiome. We present a constraint-based modeling pipeline to predict precision prebiotics for a minimal microbial community in the worm Caenorhabditis elegans comprising the host-beneficial Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71 with the aim to boost the growth of MYb11. Experimentally testing four of the predicted precision prebiotics, we confirm that they are specifically able to increase the abundance of MYb11 in vitro and in vivo. These results demonstrate that constraint-based modeling could be an important tool for the development of targeted microbiome-based therapies against human diseases.

The intricate triangular interaction between protective microbe, pathogen and host determines fitness of the metaorganism.

The microbiota shapes host biology in numerous ways. One example is protection against pathogens, which is likely critical for host fitness in consideration of the ubiquity of pathogens. The host itself can affect abundance of microbiota or pathogens, which has usually been characterized in separate studies. To date, however, it is unclear how the host influences the interaction with both simultaneously and how this triangular interaction determines fitness of the host-microbe assemblage, the so-called metaorganism. To address this current knowledge gap, we focused on a triangular model interaction, consisting of the nematode Caenorhabditis elegans, its protective symbiont Pseudomonas lurida MYb11 and its pathogen Bacillus thuringiensis Bt679. We combined the two microbes with C. elegans mutants with altered immunity and/or microbial colonization, and found that (i) under pathogen stress, immunocompetence has a larger influence on metaorganism fitness than colonization with the protective microbe; (ii) in almost all cases, MYb11 still improves fitness; and (iii) disruption of p38 MAPK signalling, which contributes centrally to immunity against Bt679, completely reverses the protective effect of MYb11, which further reduces nematode survival and fitness upon infection with Bt679. Our study highlights the complex interplay between host, protective microbe and pathogen in shaping metaorganism biology.

Host and microbiome jointly contribute to environmental adaptation.

Most animals and plants have associated microorganisms, collectively referred to as their microbiomes, which can provide essential functions. Given their importance, host-associated microbiomes have the potential to contribute substantially to adaptation of the host-microbiome assemblage (the "metaorganism"). Microbiomes may be especially important for rapid adaptation to novel environments because microbiomes can change more rapidly than host genomes. However, it is not well understood how hosts and microbiomes jointly contribute to metaorganism adaptation. We developed a model system with which to disentangle the contributions of hosts and microbiomes to metaorganism adaptation. We established replicate mesocosms containing the nematode Caenorhabditis elegans co-cultured with microorganisms in a novel complex environment (laboratory compost). After approximately 30 nematode generations (100 days), we harvested worm populations and associated microbiomes, and subjected them to a common garden experiment designed to unravel the impacts of microbiome composition and host genetics on metaorganism adaptation. We observed that adaptation took different trajectories in different mesocosm lines, with some increasing in fitness and others decreasing, and that interactions between host and microbiome played an important role in these contrasting evolutionary paths. We chose two exemplary mesocosms (one with a fitness increase and one with a decrease) for detailed study. For each example, we identified specific changes in both microbiome composition (for both bacteria and fungi) and nematode gene expression associated with each change in fitness. Our study provides experimental evidence that adaptation to a novel environment can be jointly influenced by host and microbiome.

Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics.

The microbiome is increasingly receiving attention as an important modulator of host health and disease. However, while numerous mechanisms through which the microbiome influences its host have been identified, there is still a lack of approaches that allow to specifically modulate the abundance of individual microbes or microbial functions of interest. Moreover, current approaches for microbiome manipulation such as fecal transfers often entail a non-specific transfer of entire microbial communities with potentially unwanted side effects. To overcome this limitation, we here propose the concept of precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In a first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we present a metabolic modeling network framework that allows us to define precision prebiotics for a two-member C. elegans microbiome model community comprising the immune-protective Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71. Thus, we predicted compounds that specifically boost the abundance of the host-beneficial MYb11, four of which were experimentally validated in vitro (L-serine, L-threonine, D-mannitol, and γ-aminobutyric acid). L-serine was further assessed in vivo, leading to an increase in MYb11 abundance also in the worm host. Overall, our findings demonstrate that constraint-based metabolic modeling is an effective tool for the design of precision prebiotics as an important cornerstone for future microbiome-targeted therapies.

Exploring Effects of C. elegans Protective Natural Microbiota on Host Physiology.

The Caenorhabditis elegans natural microbiota was described only recently. Thus, our understanding of its effects on nematode physiology is still in its infancy. We previously showed that the C. elegans natural microbiota isolates Pseudomonas lurida MYb11 and P. fluorescens MYb115 protect the worm against pathogens such as Bacillus thuringiensis (Bt). However, the overall effects of the protective microbiota on worm physiology are incompletely understood. Here, we investigated how MYb11 and MYb115 affect C. elegans lifespan, fertility, and intestinal colonization. We further studied the capacity of MYb11 and MYb115 to protect the worm against purified Bt toxins. We show that while MYb115 and MYb11 affect reproductive timing and increase early reproduction only MYb11 reduces worm lifespan. Moreover, MYb11 aggravates killing upon toxin exposure. We conclude that MYb11 has a pathogenic potential in some contexts. This work thus highlights that certain C. elegans microbiota members can be beneficial and costly to the host in a context-dependent manner, blurring the line between good and bad.

Microbes to-go: slugs as source for Caenorhabditis elegans microbiota acquisition.

Research on the Caenorhabditis elegans microbiota only recently started, with little known about how C. elegans acquires its microbiota. Slugs live in the same habitat as C. elegans and are known vectors for the worm. Hence, we wondered how the passage through a slug affects the C. elegans gut microbiota and whether worms can acquire bacteria from the slug. Using fluorescently labelled microbiota and 16S rRNA gene amplicon sequencing, we evaluated microbiota persistence and acquisition in C. elegans after slug passage. We compared C. elegans gut microbiomes isolated from wild-caught slugs to the microbiomes of worms after experimental slug passage to compare similarities and differences in microbiome composition. We found that microbiota persists in C. elegans while passing the slug gut and that worms simultaneously acquire additional bacteria species from the slug. Although the amplicon sequencing variant (ASV) richness of worms from the experiment did not exceed the richness of worms that naturally occur in slugs, we found a high number of shared ASVs indicating the importance of commonly associated microbiota. We demonstrate that C. elegans can take advantage of its passage through the slug by acquiring new potential microbiota without losing its native microbiota.