Bacterial transcriptional response to labile exometabolites from photosynthetic picoeukaryote Micromonas commoda

Dissolved primary production released into seawater by marine phytoplankton is a major source of carbon fueling heterotrophic bacterial production in the ocean. The composition of the organic compounds released by healthy phytoplankton is poorly known and difficult to assess with existing chemical methods. Here, expression of transporter and catabolic genes by three model marine bacteria (Ruegeria pomeroyi DSS-3, Stenotrophomonas sp. SKA14, and Polaribacter dokdonensis MED152) was used as a biological sensor of metabolites released from the picoeukaryote Micromonas commoda RCC299. Bacterial expression responses indicated that the three species together recognized 38 picoeukaryote metabolites. This was consistent with the Micromonas expression of genes for starch metabolism and synthesis of peptidoglycan-like intermediates. A comparison of the hypothesized Micromonas exometabolite pool with that of the diatom Thalassiosira pseudonana CCMP1335, analyzed previously with the same biological sensor method, indicated that both phytoplankton released organic acids, nucleosides, and amino acids, but differed in polysaccharide and organic nitrogen release. Future ocean conditions are expected to favor picoeukaryotic phytoplankton over larger-celled microphytoplankton. Results from this study suggest that such a shift could alter the substrate pool available to heterotrophic bacterioplankton

Growth-stage-related shifts in phytoplankton endometabolome composition set the stage for bacterial heterotrophy

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

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Interspecies interactions determine growth dynamics of biopolymer-degrading populations in microbial communities

Microbial communities perform essential ecosystem functions such as the remineralization of organic carbon that exists as biopolymers. The first step in mineralization is performed by biopolymer degraders, which harbor enzymes that can break down polymers into constituent oligo- or monomeric forms. The released nutrients not only allow degraders to grow, but also promote growth of cells that either consume the degradation products, i.e., exploiters, or consume metabolites released by the degraders or exploiters, i.e., scavengers. It is currently not clear how such remineralizing communities assemble at the microscale—how interactions between the different guilds influence their growth and spatial distribution, and hence the development and dynamics of the community. Here, we address this knowledge gap by studying marine microbial communities that grow on the abundant marine biopolymer alginate. We used batch growth assays and microfluidics coupled to time-lapse microscopy to quantitatively investigate growth and spatial distribution of single cells. We found that the presence of exploiters or scavengers alters the spatial distribution of degrader cells. In general, exploiters and scavengers—which we collectively refer to as cross-feeder cells—slowed down the growth of degrader cells. In addition, coexistence with cross-feeders altered the production of the extracellular enzymes that break down polymers by degrader cells. Our findings reveal that ecological interactions by nondegrading community members have a profound impact on the functions of microbial communities that remineralize carbon biopolymers in nature.ISSN:0027-8424ISSN:1091-649

The Ocean's labile DOC supply chain

Microbes of the surface ocean release, consume, and exchange labile metabolites at time scales of minutes to days. The details of this important step in the global carbon cycle remain poorly resolved, largely due to the methodological challenges of studying a diverse pool of metabolites that are produced and consumed nearly simultaneously. In this perspective, a new compilation of published data builds on previous studies to obtain an updated estimate of the fraction of marine net primary production that passes through the labile dissolved organic carbon (DOC) pool. In agreement with previous studies, our data mining and modeling approaches hypothesize that about half of ocean net primary production is processed through the labile DOC pool. The fractional contributions from three major sources are estimated at 0.4 for living phytoplankton, 0.4 for dead and dying phytoplankton, and 0.2 for heterotrophic microbes and mesoplankton

Additional file 1 of Nanobodies as potential tools for microbiological testing of live biotherapeutic products

Additional file 1:Table S1. Bacterial strains, plasmids, and primers used in this study. Figure S1. ELISA results of the interaction between different lactobacilli and secreted nanobodies. (A) Lc58 and Lc38 nanobody interaction between target L. crispatus antigen (strains 33820 and 33197) and control lactobacilli antigens. (B) Lj94 and Lj75 nanobody interaction between target L. jensenii JV-V16 antigen and control lactobacilli antigens. Secreted nanobody concentrations were evaluated using Octet (Sartorius) and the preparations were diluted to 1 μg/ml for experiments. Figure S2. SDS PAGE gels showing purified nanobodies and fluorescently tagged nanobodies. Proteins were loaded on NuPAGE 4–12% BisTris gels and stained with Coomasie Blue. The expected molecular mass of each protein and the lane in which the purified protein was run is indicated in the boxes below the gels. Molecular weight markers are identified on the left. Please note that under boiling SDS conditions, TagRFP is known to fragment. The additional bands observed in (B) lane C are likely due to the fragmentation of sample preparation for SDS PAGE. Figure S3. L. jensenii 115-3-CHN Lj75 antigen identification. (A) AA sequence analysis of (1) the originally annotated AA sequence of L. jensenii 115-3-CHN antigen (EEX23860.1), (2) the confirmed L. jensenii JV-V16 Lj75 antigen AA sequence, and (3) the extended L. jensenii 115-3-CHN Lj75 antigen AA sequence. Green above sequence analysis indicates 100% AA sequence identity. (B) Depiction of unique peptide hits along the AA sequence of the corrected L. jensenii 115-3-CHN antigen sequence. Green indicates where in the AA sequence the unique peptides match. Figure S4. L. crispatus strain lysate western blots with Lc58. L. crispatus EX8 VC07 (Lane 1), L. crispatus 125-2-CHN (Lane 2), or L. jensenii 25258 (lane 3) lysates were probed with Lc58. Lc58 binding was detected with an anti-his HRP conjugated secondary antibody. Figure S5. Detection of nanobody target candidate expression by western blot with HRP conjugated anti-FLAG antibody probing. (A) Lc58 target candidates; Lane 1, L. crispatus 125-2-CHN lysate; Lane 2, empty vector; Lane 3, S-layer (EEU18441.1) ; Lane 4, Bacterial Ig-domain protein (EEU19392.1) ; Lane 5, Cell separation protein (EEU18637.1). (B) Lj75 candidates; Lane 1, L. jensenii JV-V16; Lane 2, empty vector; Lane 3, NlPC/P60 family protein (EFH30000.1); Lane 4, Hypothetical protein (EFH30544.1).Figure S6. Use of SYTOX Green Ready Flow reagent to distinguish live from dead cells. SYTOX (ThermoFisher) is a cell impermeant nucleic acid stain that enters cells with damaged membranes and binds nucleic acids. (A) Untreated and unstained L. crispatus 33820, (B) Untreated L. crispatus 33820 solution (prepared same as flow cytometry samples), and (C) Isopropyl alcohol treated (70%, 25 min)L. crispatus 33820. (D) Untreated and unstained L. jensenii 115-3-CHN, (B) Untreated L. jensenii 115-3-CHN solution (prepared same as flow cytometry samples), and (C) Isopropyl alcohol treated (70%, 25 min.) L. jensenii 115-3-CHN. Please note that GFP and AlexaFluor use same laser and filter settings on the flow cytometer used in this assay