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Brown, M. V.

Publications and source records attributed to Brown, M. V..

2 recordsLinked to original sources

Characterizing organisms from three domains of life with universal primers from throughout the global ocean

We introduce the Global rRNA Universal Metabarcoding Plankton database (GRUMP), which consists of 1194 samples that were collected from 2003-2020 and cover extensive latitudinal and longitudinal transects, as well as depth profiles in all major ocean basins. DNA from unfractionated (> 0.2{micro}m) seawater samples was amplified using the 515Y/926R universal three- domain rRNA gene primers, simultaneously quantifying the relative abundance of amplicon sequencing variants (ASVs) from bacteria, archaea, eukaryotic nuclear 18S, and eukaryotic plastid 16S. Thus, the ratio between taxa in one sample is directly comparable to the ratio in any other GRUMP sample, regardless of gene copy number differences. This obviates a problem in prior global studies that used size-fractionation and different rRNA gene primers for bacteria, archaea, and eukaryotes, precluding comparisons across size fractions or domains. On average, bacteria contributed 71%, eukaryotes 19%, and archaea 8% to rRNA gene abundance, though eukaryotes contributed 32% at latitudes > 40{degrees}. GRUMP is publicly available on the Simons Collaborative Marine Atlas Project (CMAP), promoting the global comparison of marine microbial dynamics.

ecology↗

Defining marine bacterioplankton community assembly rules by contrasting the importance of environmental determinants and biotic interactions

Bacterioplankton communities play major roles in governing marine productivity and biogeochemical cycling, yet what drives the relative influence of the types of deterministic ecological processes which result in diversity patterns remains unclear. Here we examine how differing deterministic processes (environmental factors and biotic interactions) drive temporal dynamics of bacterioplankton diversity at three different oceanographic time-series locations, spanning 15 degrees of latitude, which are each characterized by different environmental conditions and varying degrees of seasonality. Monthly surface samples, collected over a period of 5.5 years, were analyzed using 16S rRNA amplicon sequencing. The high and mid-latitude sites of Maria Island and Port Hacking were characterized by high and intermediate levels of environmental heterogeneity respectively, with both alpha (local) diversity (72 % and 24 % of total variation) and beta diversity (32 % and 30 %) patterns within bacterioplankton assemblages primarily explained by environmental determinants, including day length, ammonium, and mixed layer depth. In contrast, at North Stradbroke Island, a sub-tropical location where environmental conditions are less seasonally variable, interspecific interactions were of increased importance in structuring bacterioplankton diversity (alpha diversity: 33 %; beta diversity: 26 %) with environment only contributing 11 and 13 % to predicting diversity, respectively. Our results demonstrate that bacterioplankton diversity is the result of both deterministic environmental and biotic processes and that the importance of these different deterministic processes varies, potential in response to environmental heterogeneity. ImportanceMarine bacterioplankton drives important biological processes, including the cycling of key nutrients or fixing atmospheric carbon. Therefore, to predict future climate scenarios its critical to model these communities accurately. Processes that drive bacterioplankton diversity patterns in the oceans however remain unresolved, with most studies focusing on deterministic environmental drivers, ie temperature or available inorganic nutrients. Biotic deterministic processes including interactions among individuals are also important for structuring diversity patterns, however, this is rarely included to predict bacterioplankton communities. We develop an approach for determining the relative contribution of environmental and potential biotic interactions that structure marine bacterioplankton at three series at different latitudes. Environmental factors best predicted temporal trends in bacterioplankton diversity at the two high latitude time series, while biotic influence was most apparent at the low latitude time series. Our results suggest environmental heterogeneity is an important attribute driving the contribution of varying deterministic influence of bacterioplankton diversity.

ecology↗