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Abstract Background Bacteria of the candidate phyla radiation (CPR), constituting about 25% of the bacterial biodiversity, are characterized by small cell size and patchy genomes without complete key metabolic pathways, suggesting a symbiotic lifestyle. Gracilibacteria (BD1-5), which are part of the CPR branch, possess alternate coded genomes and have not yet been cultivated. The lifestyle of Gracilibacteria, their temporal dynamics, and activity in natural ecosystems, particularly in groundwater, has remained largely unexplored. Here, we aimed to investigate Gracilibacteria activity in situ and to discern their lifestyle based on expressed genes, using the metaproteogenome of Gracilibacteria as a function of time in the cold-water geyser Wallender Born in the Volcanic Eifel region in Germany. Results We coupled genome-resolved metagenomics and metaproteomics to investigate a cold-water geyser microbial community enriched in Gracilibacteria across a 12-day time-series. Groundwater was collected and sequentially filtered to fraction CPR and other bacteria. Based on 725 Gbps of metagenomic data, 1129 different ribosomal protein S3 marker genes, and 751 high-quality genomes (123 population genomes after dereplication), we identified dominant bacteria belonging to Gallionellales and Gracilibacteria along with keystone microbes, which were low in genomic abundance but substantially contributing to proteomic abundance. Seven high-quality Gracilibacteria genomes showed typical limitations, such as limited amino acid or nucleotide synthesis, in their central metabolism but no co-occurrence with potential hosts. The genomes of these Gracilibacteria were encoded for a high number of proteins involved in cell to cell interaction, supporting the previously surmised host-dependent lifestyle, e.g., type IV and type II secretion system subunits, transporters, and features related to cell motility, which were also detected on protein level. Conclusions We here identified microbial keystone taxa in a high-CO2 aquifer, and revealed microbial dynamics of Gracilibacteria. Although Gracilibacteria in this ecosystem did not appear to target specific organisms in this ecosystem due to lack of co-occurrence despite enrichment on 0.2-µm filter fraction, we provide proteomic evidence for the complex machinery behind the host-dependent lifestyle of groundwater Gracilibacteria. Video Abstract

Abstract Sexual dimorphism arises because of divergent fitness optima between the sexes. Phenotypic divergence between sexes can range from mild to extreme. Fireflies, bioluminescent beetles, present various degrees of sexual dimorphism, with species showing very mild sexual dimorphism to species presenting female-specific neoteny, posing a unique framework to investigate the evolution of sexually dimorphic traits across species. In this work, we present novel assembled genomes of two firefly species, Lamprohiza splendidula and Luciola italica, species with different degrees of sexual dimorphism. We uncover high synteny conservation of the X-chromosome across ~ 180 Mya and find full X-chromosome dosage compensation in our two fireflies, hinting at common mechanism upregulating the single male X-chromosome. Different degrees of sex-biased expressed genes were found across two body parts showing different proportions of expression conservation between species. Interestingly, we do not find X-chromosome enrichment of sex-biased genes, but retrieve autosomal enrichment of sex-biased genes. We further uncover higher nucleotide diversity in the intronic regions of sex-biased genes, hinting at a maintenance of heterozygosity through sexual selection. We identify different levels of sex-biased gene expression divergence including a set of genes showing conserved sex-biased gene expression between species. Divergent and conserved sex-biased genes are good candidates to test their role in the maintenance of sexually dimorphic traits.

ABSTRACT Seasonal influenza outbreaks represent a large burden for the health care system as well as the economy. While the role of the microbiome has been elucidated in the context of various diseases, the impact of respiratory viral infections on the human microbiome is largely unknown. In this study, swine was used as an animal model to characterize the temporal dynamics of the respiratory and gastrointestinal microbiome in response to an influenza A virus (IAV) infection. A multi-omics approach was applied on fecal samples to identify alterations in microbiome composition and function during IAV infection. We observed significantly altered microbial richness and diversity in the gastrointestinal microbiome after IAV infection. In particular, increased abundances of Prevotellaceae were detected, while Clostridiaceae and Lachnospiraceae decreased. Moreover, our metaproteomics data indicated that the functional composition of the microbiome was heavily affected by the influenza infection. For instance, we identified decreased amounts of flagellin, correlating with reduced abundances of Lachnospiraceae and Clostridiaceae, possibly indicating involvement of a direct immune response toward flagellated Clostridia during IAV infection. Furthermore, enzymes involved in short-chain fatty acid (SCFA) synthesis were identified in higher abundances, while metabolome analyses revealed rather stable concentrations of SCFAs. In addition, 16S rRNA gene sequencing was used to characterize effects on the composition and natural development of the upper respiratory tract microbiome. Our results showed that IAV infection resulted in significant changes in the abundance of Moraxellaceae and Pasteurellaceae in the upper respiratory tract. Surprisingly, temporal development of the respiratory microbiome structure was not affected. IMPORTANCE Here, we used swine as a biomedical model to elucidate the impact of influenza A H1N1 infection on structure and function of the respiratory and gastrointestinal tract microbiome by employing a multi-omics analytical approach. To our knowledge, this is the first study to investigate the temporal development of the porcine microbiome and to provide insights into the functional capacity of the gastrointestinal microbiome during influenza A virus infection.

The hydrothermal vent tubeworm Riftia pachyptila hosts a single 16S rRNA phylotype of intracellular sulfur-oxidizing symbionts, which vary considerably in cell morphology and exhibit a remarkable degree of physiological diversity and redundancy, even in the same host. To elucidate whether multiple metabolic routes are employed in the same cells or rather in distinct symbiont subpopulations, we enriched symbionts according to cell size by density gradient centrifugation. Metaproteomic analysis, microscopy, and flow cytometry strongly suggest that Riftia symbiont cells of different sizes represent metabolically dissimilar stages of a physiological differentiation process: While small symbionts actively divide and may establish cellular symbiont-host interaction, large symbionts apparently do not divide, but still replicate DNA, leading to DNA endoreduplication. Moreover, in large symbionts, carbon fixation and biomass production seem to be metabolic priorities. We propose that this division of labor between smaller and larger symbionts benefits the productivity of the symbiosis as a whole.

ABSTRACT The deep-sea tubeworm Riftia pachyptila lacks a digestive system but completely relies on bacterial endosymbionts for nutrition. Although the symbiont has been studied in detail on the molecular level, such analyses were unavailable for the animal host, because sequence information was lacking. To identify host-symbiont interaction mechanisms, we therefore sequenced the Riftia transcriptome, which served as a basis for comparative metaproteomic analyses of symbiont-containing versus symbiont-free tissues, both under energy-rich and energy-limited conditions. Our results suggest that metabolic interactions include nutrient allocation from symbiont to host by symbiont digestion and substrate transfer to the symbiont by abundant host proteins. We furthermore propose that Riftia maintains its symbiont by protecting the bacteria from oxidative damage while also exerting symbiont population control. Eukaryote-like symbiont proteins might facilitate intracellular symbiont persistence. Energy limitation apparently leads to reduced symbiont biomass and increased symbiont digestion. Our study provides unprecedented insights into host-microbe interactions that shape this highly efficient symbiosis. IMPORTANCE All animals are associated with microorganisms; hence, host-microbe interactions are of fundamental importance for life on earth. However, we know little about the molecular basis of these interactions. Therefore, we studied the deep-sea Riftia pachyptila symbiosis, a model association in which the tubeworm host is associated with only one phylotype of endosymbiotic bacteria and completely depends on this sulfur-oxidizing symbiont for nutrition. Using a metaproteomics approach, we identified both metabolic interaction processes, such as substrate transfer between the two partners, and interactions that serve to maintain the symbiotic balance, e.g., host efforts to control the symbiont population or symbiont strategies to modulate these host efforts. We suggest that these interactions are essential principles of mutualistic animal-microbe associations.

Metaproteomics, the study of protein expression in microbial communities, is a versatile tool for environmental microbiology. Achieving sufficiently high metaproteome coverage to obtain a comprehensive picture of the activities and interactions in microbial communities is one of the current challenges in metaproteomics. An essential step to maximize the number of identified proteins is peptide separation via liquid chromatography (LC) prior to mass spectrometry (MS). Thorough optimization and comparison of LC methods for metaproteomics are, however, currently lacking. Here, we present an extensive development and test of different 1D and 2D-LC approaches for metaproteomic peptide separations. We used fully characterized mock community samples to evaluate metaproteomic approaches with very long analytical columns (50 and 75 cm) and long gradients (up to 12 h). We assessed a total of over 20 different 1D and 2D-LC approaches in terms of number of protein groups and unique peptides identified, peptide spectrum matches (PSMs) generated, the ability to detect proteins of low-abundance species, the effect of technical replicate runs on protein identifications and method reproducibility. We show here that, while 1D-LC approaches are faster and easier to set up and lead to more identifications per minute of runtime, 2D-LC approaches allow for a higher overall number of identifications with up to >10,000 protein groups identified. We also compared the 1D and 2D-LC approaches to a standard GeLC workflow, in which proteins are pre-fractionated via gel electrophoresis. This method yielded results comparable to the 2D-LC approaches, however with the drawback of a much increased sample preparation time. Based on our results, we provide recommendations on how to choose the best LC approach for metaproteomics experiments, depending on the study aims.