Beschreibung: The bioavailability and utilization of porphyrin-bound iron, specifically heme, by marine microorganisms have rarely been examined. This study used Ruegeria sp. strain TrichCH4B as a model organism to study heme acquisition by a member of the Roseobacter clade. Analogs of known heme transporter proteins were found within the Ruegeria sp. TrichCH4B genome. The identified heme uptake and utilization system appears to be functional, as the heme genes were upregulated under iron stress, the bacterium could grow on ferric-porphyrin complexes as the sole iron source, and internalization of 55 Fe from ferric protoporphyrin IX was observed. The potential ability to utilize heme in the Roseobacter clade appears to be common, as half of the isolates in the RoseoBase database were found to have a complete heme uptake system. A degenerate primer set was designed and successfully used to identify the putative heme oxygenase gene ( hmus ) in the roseobacter heme uptake system from diverse nonenriched marine environments. This study found that members of the Roseobacter clade are capable of utilizing heme as an iron source and that this capability may be present in all types of marine environments. The results of this study add a new perspective to the current picture of iron cycling in marine systems, whereby relatively refractory intracellular pools of heme-bound iron may be taken up quickly and directly reincorporated into living bacteria without previous degradation or the necessity of a siderophore intermediate.

Beschreibung: With the common goal of more accurately and consistently quantifying ambient concentrations of free metal ions and natural organic ligands in aquatic ecosystems, researchers from 15 laboratories that routinely analyze trace metal speciation participated in an intercomparison of statistical methods used to model their most common type of experimental dataset, the complexometric titration. All were asked to apply statistical techniques that they were familiar with to model synthetic titration data that are typical of those obtained by applying state-of-the-art electrochemical methods - anodic stripping voltammetry (ASV) and competitive ligand equilibration-adsorptive cathodic stripping voltammetry (CLE-ACSV) - to the analysis of natural waters. Herein, we compare their estimates for parameters describing the natural ligands, examine the accuracy of inferred ambient free metal ion concentrations ([Mf]), and evaluate the influence of the various methods and assumptions used on these results.The ASV-type titrations were designed to test each participant's ability to correctly describe the natural ligands present in a sample when provided with data free of measurement error, i.e., random noise. For the three virtual samples containing just one natural ligand, all participants were able to correctly identify the number of ligand classes present and accurately estimate their parameters. For the four samples containing two or three ligand classes, a few participants detected too few or too many classes and consequently reported inaccurate 'measurements' of ambient [Mf]. Since the problematic results arose from human error rather than any specific method of analyzing the data, we recommend that analysts should make a practice of using one's parameter estimates to generate simulated (back-calculated) titration curves for comparison to the original data. The root-mean-squared relative error between the fitted observations and the simulated curves should be comparable to the expected precision of the analytical method and upon visual inspection the distribution of residuals should not be skewed.Modeling the synthetic, CLE-ACSV-type titration dataset, which comprises 5 titration curves generated at different analytical windows or levels of competing ligand added to the virtual sample, proved to be more challenging due to the random measurement error that was incorporated. Comparison of the submitted results was complicated by the participants' differing interpretations of their task. Most adopted the provided 'true' instrumental sensitivity in modeling the CLE-ACSV curves, but several estimated sensitivities using internal calibration, exactly as is required for actual samples. Since most fitted sensitivities were biased low, systematic error in inferred ambient [Mf] and in estimated weak ligand (L2) concentrations resulted.The main distinction between the mathematical approaches taken by participants lies in the functional form of the speciation model equations, with their implicit definition of independent and dependent or manipulated variables. In 'direct modeling', the dependent variable is the measured [Mf] (or I p) and the total metal concentration ([M]T) is considered independent. In other, much more widely used methods of analyzing titration data - classical linearization, best known as van den Berg/Ružić, and isotherm fitting by nonlinear regression, best known as the Langmuir or Gerringa methods - [Mf] is defined as independent and the dependent variable calculated from both [M]T and [Mf]. Close inspection of the biases and variability in the estimates of ligand parameters and in predictions of ambient [Mf] revealed that the best results were obtained by the direct approach. Linear regression of transformed data yielded the largest bias and greatest variability, while non-linear isotherm fitting generated results with mean bias comparable to direct modeling, but also with greater variability.Participants that performed a unified analysis of ACSV titration curves at multiple detection windows for a sample improved their results regardless of the basic mathematical approach taken. Overall, the three most accurate sets of results were obtained using direct modeling of the unified multiwindow dataset, while the single most accurate set of results also included simultaneous calibration. We therefore recommend that where sample volume and time permit, titration experiments for all natural water samples be designed to include two or more detection windows, especially for coastal and estuarine waters. It is vital that more practical experimental designs for multi-window titrations be developed.Finally, while all mathematical approaches proved to be adequate for some datasets, matrix-based equilibrium models proved to be most naturally suited for the most challenging cases encountered in this work, i.e., experiments where the added ligand in ACSV became titrated. The ProMCC program (Omanović et al., this issue) as well as the Excel Add-in based KINETEQL Multiwindow Solver spreadsheet (Hudson, 2014) have this capability and have been made available for public use as a result of this intercomparison exercise.

Beschreibung: Heterotrophic bacteria in the SAR11 and Roseobacter lineages shape the marine carbon, nitrogen, phosphorous, and sulfur cycles, yet they do so having adopted divergent ecological strategies. Currently, it is unknown whether these globally significant groups partition into specific niches with respect to micronutrients (e.g., trace metals) and how that may affect marine trace metal cycling. Here, we used comparative genomics to identify diverse iron, cobalt, nickel, copper, and zinc uptake capabilities in SAR11 and Roseobacter genomes and uncover surprising unevenness within and between lineages. The strongest predictors for the extent of the metal uptake gene content are the total number of transporters per genome, genome size, total metal transporters, and GC content, but numerous exceptions exist in both groups. Taken together, our results suggest that SAR11 have strongly minimized their trace metal uptake versatility, with high-affinity zinc uptake being a unique exception. The larger Roseobacter genomes have greater trace metal uptake versatility on average, but they also appear to have greater plasticity, resulting in phylogenetically similar genomes having largely different capabilities. Ultimately, phylogeny is predictive of the diversity and extent of 20 to 33% of all metal uptake systems, suggesting that specialization in metal utilization mostly occurred independently from overall lineage diversification in both SAR11 and Roseobacter . We interpret these results as reflecting relatively recent trace metal niche partitioning in both lineages, suggesting that concentrations and chemical forms of metals in the marine environment are important factors shaping the gene content of marine heterotrophic Alphaproteobacteria of the SAR11 and Roseobacter lineages.

Beschreibung: In October 2008, we investigated pelagic community composition and biomass, from bacteria to fish, across a sharp frontal gradient overlying deep waters south of Point Conception, California. This north–south gradient, which we called A-Front, was formed by the eastward flow of the California Current and separated cooler mesotrophic waters of coastal upwelling origin to the north, from warm oligotrophic waters of likely mixed subarctic–subtropical origin to the south. Plankton biomass and phytoplankton growth rates were two to three times greater on the northern side, and primary production rates were elevated 5-fold to the north. Compared with either of the adjacent waters, the frontal interface was strongly enriched and uniquely defined by a subsurface bloom of large diatoms, elevated concentrations of suspension-feeding zooplankton, high bioacoustical estimates of pelagic fish and enhanced bacterial production and phytoplankton biomass and photosynthetic potential. Such habitats, though small in areal extent, may contribute disproportionately and importantly to regional productivity, nutrient cycling, carbon fluxes and trophic ecology. As a general introduction to the A-Front study, we provide an overview of its design and implementation, a brief summary of major findings and a discussion of potential mechanisms of plankton enrichment at the front.