Project description:Bacteria are key contributors to microalgae resource acquisition, competitive performance, and functional diversity, but their potential metabolic interactions with coral microalgal endosymbionts (Symbiodiniaceae) have been largely overlooked. Here, we show that altering the bacterial composition of two widespread Symbiodiniaceae species, during their free-living stage, results in a significant shift in their cellular metabolism. Indeed, the abundance of monosaccharides and the key phytohormone indole-3-acetic acid (IAA) were correlated with the presence of specific bacteria, including members of the Labrenzia (Roseibium) and Marinobacter genera. Single-cell stable isotope tracking revealed that these two bacterial genera are involved in reciprocal exchanges of carbon and nitrogen with Symbiodiniaceae. We identified the provision of IAA by Labrenzia and Marinobacter, and this metabolite caused a significant growth enhancement of Symbiodiniaceae. By unravelling these interkingdom interactions, our work demonstrates how specific bacterial associates fundamentally govern Symbiodiniaceae fitness.
Project description:Predicting interspecies interactions is a key challenge in microbial ecology given that interactions shape the composition and functioning of microbial communities. However, predicting microbial interactions is challenging because they can vary considerably depending on species' metabolic capabilities and environmental conditions. Here, we employ machine learning models to predict pairwise interactions between culturable bacteria based on their phylogeny, monoculture growth capabilities, and interactions with other species. We trained our models on one of the largest available pairwise interactions data set containing over 7,500 interactions between 20 species from two taxonomic groups that were cocultured in 40 different carbon environments. Our models accurately predicted both the sign (accuracy of 88%) and the strength of effects (R2 of 0.87) species had on each other's growth. Encouragingly, predictions with comparable accuracy could be made even when not relying on information about interactions with other species, which are often hard to measure. However, species' monoculture growth was essential to the model, as predictions based solely on species' phylogeny and inferred metabolic capabilities were significantly less accurate. These results bring us one step closer to a predictive understanding of microbial communities, which is essential for engineering beneficial microbial consortia. IMPORTANCE In order to understand the function and structure of microbial communities, one must know all pairwise interactions that occur between the different species within the community, as these interactions shape the community's structure and functioning. However, measuring all pairwise interactions can be an extremely difficult task especially when dealing with big complex communities. Because of that, predicting interspecies interactions is a key challenge in microbial ecology. Here, we use machine learning models in order to accurately predict the type and strength of interactions. We trained our models on one of the largest available pairwise interactions data set, containing over 7,500 interactions between 20 different species that were cocultured in 40 different environments. Our results show that, in general, accurate predictions can be made, and that the ability of each species to grow on its own in the given environment contributes the most to predictions. Being able to predict microbial interactions would put us one step closer to predicting the functionality of microbial communities and to rationally microbiome engineering.
Project description:BackgroundSkin-penetrating nematodes of the genus Strongyloides infect over 600 million people, posing a major global health burden. Their life cycle includes both a parasitic and free-living generation. During the parasitic generation, infective third-stage larvae (iL3s) actively engage in host seeking. During the free-living generation, the nematodes develop and reproduce on host feces. At different points during their life cycle, Strongyloides species encounter a wide variety of host-associated and environmental bacteria. However, the microbiome associated with Strongyloides species, and the behavioral and physiological interactions between Strongyloides species and bacteria, remain unclear.ResultsWe first investigated the microbiome of the human parasite Strongyloides stercoralis using 16S-based amplicon sequencing. We found that S. stercoralis free-living adults have an associated microbiome consisting of specific fecal bacteria. We then investigated the behavioral responses of S. stercoralis and the closely related rat parasite Strongyloides ratti to an ecologically diverse panel of bacteria. We found that S. stercoralis and S. ratti showed similar responses to bacteria. The responses of both nematodes to bacteria varied dramatically across life stages: free-living adults were strongly attracted to most of the bacteria tested, while iL3s were attracted specifically to a narrow range of environmental bacteria. The behavioral responses to bacteria were dynamic, consisting of distinct short- and long-term behaviors. Finally, a comparison of the growth and reproduction of S. stercoralis free-living adults on different bacteria revealed that the bacterium Proteus mirabilis inhibits S. stercoralis egg hatching, and thereby greatly decreases parasite viability.ConclusionsSkin-penetrating nematodes encounter bacteria from various ecological niches throughout their life cycle. Our results demonstrate that bacteria function as key chemosensory cues for directing parasite movement in a life-stage-specific manner. Some bacterial genera may form essential associations with the nematodes, while others are detrimental and serve as a potential source of novel nematicides.
Project description:Phytoplankton-derived metabolites fuel a large fraction of heterotrophic bacterial production in the global ocean, yet methodological challenges have limited our understanding of the organic molecules transferred between these microbial groups. In an experimental bloom study consisting of three heterotrophic marine bacteria growing together with the diatom Thalassiosira pseudonana, we concurrently measured diatom endometabolites (i.e., potential exometabolite supply) by nuclear magnetic resonance (NMR) spectroscopy and bacterial gene expression (i.e., potential exometabolite uptake) by metatranscriptomic sequencing. Twenty-two diatom endometabolites were annotated, with nine increasing in internal concentration in the late stage of the bloom, eight decreasing, and five showing no variation through the bloom progression. Some metabolite changes could be linked to shifts in diatom gene expression, as well as to shifts in bacterial community composition and their expression of substrate uptake and catabolism genes. Yet an overall low match indicated that endometabolome concentration was not a good predictor of exometabolite availability, and that complex physiological and ecological interactions underlie metabolite exchange. Six diatom endometabolites accumulated to higher concentrations in the bacterial co-cultures compared to axenic cultures, suggesting a bacterial influence on rates of synthesis or release of glutamate, arginine, leucine, 2,3-dihydroxypropane-1-sulfonate, glucose, and glycerol-3-phosphate. Better understanding of phytoplankton metabolite production, release, and transfer to assembled bacterial communities is key to untangling this nearly invisible yet pivotal step in ocean carbon cycling.
Project description:Mammals display wide range of variation in their lifespan. Investigating the molecular networks that distinguish long- from short-lived species has proven useful to identify determinants of longevity. Here, we compared the liver of long-lived naked mole-rats (NMRs) and the phylogenetically closely related, shorter-lived, guinea pigs using an integrated omic approach. We found that NMRs livers display a unique expression pattern of mitochondrial proteins that result in distinct metabolic features of their mitochondria. For instance, we observed a generally reduced respiration rate associated with lower protein levels of respiratory chain components, particularly complex I, and increased capacity to utilize fatty acids. Interestingly, we show that the same molecular networks are affected during aging in both NMR and humans, supporting a direct link to the extraordinary longevity of both species. Finally, we identified a novel longevity pathway and validated it experimentally in the nematode C. elegans.
Project description:Blueberries confront substantial challenges from climate change, such as rising temperatures and extreme heat, necessitating urgent solutions to ensure productivity. We hypothesized that ericoid mycorrhizal fungi (ErM) and plant growth-promoting bacteria (PGPB) would establish symbiotic relationships and increase heat stress tolerance in blueberries. A growth chamber study was designed with low (25/20°C) and high temperature (35/30°C) conditions with micropropagated blueberry plantlets inoculated with ErM, PGPB, and both. Gas exchange and chlorophyll fluorescence properties of the leaves were monitored throughout the growth. At harvest, biochemical assays and biomass analysis were performed to evaluate potential oxidative stress induced by elevated temperatures. ErM application boosted root biomass under 25/20°C conditions but did not impact photosynthetic efficiency. In contrast, PGPB demonstrated a dual role: enhancing photosynthetic capacity and reducing stomatal conductance notably under 35/30°C conditions. Moreover, PGPB showcased conflicting effects, reducing oxidative damage under 25/20°C conditions while intensifying it during 47°C heat shock. A significant highlight lies in the opposing effects of ErM and PGPB on root growth and stomatal conductance, signifying their reciprocal influence on blueberry plant behavior, which may lead to increased water uptake or reduced water use. Understanding these complex interactions holds promise for refining sustainable strategies to overcome climate challenges.
Project description:In this study, we investigated a species-specific algal-bacterial co-culture that has recently attracted worldwide scientific attention as a novel approach to enhancing algal growth rate. We report that the type of interaction between Chlorella vulgaris and bacteria of the genus Delftia is not solely determined by species specificity. Rather, it is a dynamic process of adaptation to the surrounding conditions, where one or the other microorganism dominates (temporally) depending on the growth conditions, in particular the medium. Under laboratory conditions, we found that Delftia sp. had a negative effect on C. vulgaris growth when co-cultured in a TAP medium. However, the co-culture of algae and bacteria under BG-11 and BG-11 + acetic acid resulted in an increase in algal concentration compared to algal cultures without bacteria under the same conditions. Additional chemical analysis revealed that the presence of different carbon (the main organic carbon source-acetic acid in TAP or BG-11 + acetic acid medium and inorganic carbon source-Na2CO3 in BG-11 or BG-11 + acetic acid medium) and nitrogen (NH4Cl in TAP medium and NaNO3 in BG-11 or BG-11 + acetic acid medium) species in the growth medium was one of the main factors driving the shift in interaction type.
Project description:Bacteria exhibiting beneficial traits like increasing the bioavailability of essential nutrients and modulating hormone levels in plants are known as plant growth promoting (PGP) bacteria. The occurrence of this specific group of bacteria in the endophytic environment may reflect the decisive role they play in a particular condition. This study aimed to determine the taxonomical diversity of the culturable bacterial endophytes, isolated in the vegetative stage of passionflower (Passiflora incarnata), and assess its potential to promote plant growth by phenotypic and genotypic approaches. The sequencing and phylogenetic analysis of the 16S rRNA gene allowed us to classify 58 bacterial endophytes into nine genera. Bacillus (70.7%) was the most dominant genus, followed by Pseudomonas (8.6%) and Pantoea (6.9%). A few isolates belonged to Rhodococcus and Paenibacillus, whereas the genera Lysinibacillus, Microvirga, Xanthomonas, and Leclercia were represented by only one isolate. The strains were tested for nitrogen fixation, phosphate solubilization, indole-acetic-acid synthesis, and siderophore production. Moreover, PGP related genes (nifH, ipdC, asb, and AcPho) were detected by PCR-based screening. Most of the isolates (94.8%) displayed a potential for at least one of the PGP traits tested by biochemical assays or PCR-based screening. Nine strains were selected based on results from both approaches and were evaluated for boosting the Cape gooseberry (Physalis peruviana) germination and growth. All tested isolates improved germination in vitro, and the majority (78%) increased growth parameters in vivo. The results suggested that most of culturable bacteria inhabiting P. incarnata in the vegetative stage could be used as probiotics for agricultural systems. Besides, their occurrence may be associated with specific physiological needs typical of this development stage.