Microbial Community Structure of Three Traditional Zambian Fermented Products: Mabisi, Chibwantu and Munkoyo

Around the world, raw materials are converted into fermented food products through microbial and enzymatic activity. Products are typically produced using a process known as batch culture, where small volumes of an old culture are used to initiate a fresh culture. Repeated over many years, and provided samples are not shared among producers, batch culture techniques allow for the natural evolution of independent microbial ecosystems. While these products form an important part of the diets of many people because of their nutritional, organoleptic and food safety properties, for many traditional African fermented products the microbial communities responsible for fermentation are largely unknown. Here we describe the microbial composition of three traditional fermented non-alcoholic beverages that are widely consumed across Zambia: the milk based product Mabisi and the cereal based products Munkoyo and Chibwantu. Using culture and non-culture based techniques, we found that six to eight lactic acid bacteria predominate in all products. We then used this data to investigate in more detail the factors affecting community structure. We found that products made from similar raw materials do not harbor microbial communities that are more similar to each other than those made from different raw materials. We also found that samples from the same product taken at the same location were as different from each other in terms of microbial community structure and composition, as those from geographically very distant locations. These results suggest that microbial community structure in these products is neither a simple consequence of the raw materials used, nor the particular suite of microbes available in the environment but that anthropogenic variables (e. g., competition among sellers or organoleptic preferences by different tribes) are important in shaping the microbial community structures

Patterns of eukaryotic diversity from the surface to the deep-ocean sediment

Remote deep-ocean sediment (DOS) ecosystems are among the least explored biomes on Earth. Genomic assessments of their biodiversity have failed to separate indigenous benthic organisms from sinking plankton. Here, we compare global-scale eukaryotic DNA metabarcoding datasets (18S-V9) from abyssal and lower bathyal surficial sediments and euphotic and aphotic ocean pelagic layers to distinguish plankton from benthic diversity in sediment material. Based on 1685 samples collected throughout the world ocean, we show that DOS diversity is at least threefold that in pelagic realms, with nearly two-thirds represented by abundant yet unknown eukaryotes. These benthic communities are spatially structured by ocean basins and particulate organic carbon (POC) flux from the upper ocean. Plankton DNA reaching the DOS originates from abundant species, with maximal deposition at high latitudes. Its seafloor DNA signature predicts variations in POC export from the surface and reveals previously overlooked taxa that may drive the biological carbon pump

Stable isotope food-web analysis and mercury biomagnification in polar bears ( Ursus maritimus )

Mercury (Hg) biomagnification occurs in many ecosystems, resulting in a greater potential for toxicological effects in higher-level trophic feeders. However, Hg transport pathways through different food-web channels are not well known, particularly in high-latitude systems affected by the atmospheric Hg deposition associated with snow and ice. Here, we report on stable carbon and nitrogen isotope ratios, and Hg concentrations, determined for 26, late 19th and early 20th century, polar bear ( Ursus maritimus ) hair specimens, collected from catalogued museum collections. These data elucidate relationships between the high-latitude marine food-web structure and Hg concentrations in polar bears. The carbon isotope compositions of polar bear hairs suggest that polar bears derive nutrition from coupled food-web channels, based in pelagic and sympagic primary producers, whereas the nitrogen isotope compositions indicate that polar bears occupy > fourth-level trophic positions. Our results show a positive correlation between polar bear hair Hg concentrations and δ 15 N. Interpretation of the stable isotope data in combination with Hg concentrations tentatively suggests that polar bears participating in predominantly pelagic food webs exhibit higher mercury concentrations than polar bears participating in predominantly sympagic food webs.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73930/1/j.1751-8369.2009.00114.x.pd

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

Some like it cold: microbial transformations of mercury in polar regions

The contamination of polar regions with mercury that is transported from lower latitudes as inorganic mercury has resulted in the accumulation of methylmercury (MeHg) in food chains, risking the health of humans and wildlife. While production of MeHg has been documented in polar marine and terrestrial environments, little is known about the responsible transformations and transport pathways and the processes that control them. We posit that as in temperate environments, microbial transformations play a key role in mercury geochemical cycling in polar regions by: (1) methylating mercury by one of four proposed pathways, some not previously described; (2) degrading MeHg by activities of mercury resistant and other bacteria; and (3) carrying out redox transformations that control the supply of the mercuric ion, the substrate of methylation reactions. Recent analyses have identified a high potential for mercury-resistant microbes that express the enzyme mercuric reductase to affect the production of gaseous elemental mercury when and where daylight is limited. The integration of microbially mediated processes in the paradigms that describe mercury geochemical cycling is therefore of high priority especially in light of concerns regarding the effect of global warming and permafrost thawing on input of MeHg to polar regions

Ocean current estimation using a Multi-Model Ensemble Kalman Filter during the Grand Lagrangian Deployment experiment (GLAD)

In the summer and fall of 2012, during the GLAD experiment in the Gulf of Mexico, the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) used several ocean models to assist the deployment of more than 300 surface drifters. The Navy Coastal Ocean Model (NCOM) at 1km and 3km resolutions, the US Navy operational NCOM at 3km resolution (AMSEAS), and two versions of the Hybrid Coordinates Ocean Model (HYCOM) set at 4km were running daily and delivering 72-h range forecasts. They all assimilated remote sensing and local profile data but they were not assimilating the drifter’s observations. This work presents a non-intrusive methodology named Multi-Model Ensemble Kalman Filter that allows assimilating the local drifter data into such a set of models, to produce improved ocean currents forecasts. The filter is to be used when several modeling systems or ensembles are available and/or observations are not entirely handled by the operational data assimilation process. It allows using generic in situ measurements over short time windows to improve the predictability of local ocean dynamics and associated high-resolution parameters of interest for which a forward model exists (e.g. oil spill plumes). Results can be used for operational applications or to derive enhanced background fields for other data assimilation systems, thus providing an expedite method to non-intrusively assimilate local observations of variables with complex operators. Results for the GLAD experiment show the method can improve water velocity predictions along the observed drifter trajectories, hence enhancing the skills of the models to predict individual trajectories