Biosilicification (the formation of biological structures from silica) occurs in diverse eukaryotic lineages, plays a major role in global biogeochemical cycles, and has significant biotechnological applications. Silicon (Si) uptake is crucial for biosilicification, yet the evolutionary history of the transporters involved remains poorly known. Recent evidence suggests that the SIT family of Si transporters, initially identified in diatoms, may be widely distributed, with an extended family of related transporters (SIT-Ls) present in some nonsilicified organisms. Here, we identify SITs and SIT-Ls in a range of eukaryotes, including major silicified lineages (radiolarians and chrysophytes) and also bacterial SIT-Ls. Our evidence suggests that the symmetrical 10-transmembrane-domain SIT structure has independently evolved multiple times via duplication and fusion of 5-transmembrane-domain SIT-Ls. We also identify a second gene family, similar to the active Si transporter Lsi2, that is broadly distributed amongst siliceous and nonsiliceous eukaryotes. Our analyses resolve a distinct group of Lsi2-like genes, including plant and diatom Si-responsive genes, and sequences unique to siliceous sponges and choanoflagellates. The SIT/SIT-L and Lsi2 transporter families likely contribute to biosilicification in diverse lineages, indicating an ancient role for Si transport in eukaryotes. We propose that these Si transporters may have arisen initially to prevent Si toxicity in the high Si Precambrian oceans, with subsequent biologically induced reductions in Si concentrations of Phanerozoic seas leading to widespread losses of SIT, SIT-L, and Lsi2-like genes in diverse lineages. Thus, the origin and diversification of two independent Si transporter families both drove and were driven by ancient ocean Si levels.
Biosilicification has driven variation in the global Si cycle over geologic time. The evolution of different eukaryotic lineages that convert dissolved Si (DSi) into mineralized structures (higher plants, siliceous sponges, radiolarians, and diatoms) has driven a secular decrease in DSi in the global ocean leading to the low DSi concentrations seen today. Recent studies, however, have questioned the timing previously proposed for the DSi decreases and the concentration changes through deep time, which would have major implications for the cycling of carbon and other key nutrients in the ocean. Here, we combine relevant genomic data with geological data and present new hypotheses regarding the impact of the evolution of biosilicifying organisms on the DSi inventory of the oceans throughout deep time. Although there is no fossil evidence for true silica biomineralization until the late Precambrian, the timing of the evolution of silica transporter genes suggests that bacterial silicon-related metabolism has been present in the oceans since the Archean with eukaryotic silicon metabolism already occurring in the Neoproterozoic. We hypothesize that biological processes have influenced oceanic DSi concentrations since the beginning of oxygenic photosynthesis.
Biosilicification is widespread across the eukaryotes and requires concentration of silicon in intracellular vesicles. Knowledge of the molecular mechanisms underlying this process remains limited, with unrelated silicontransporting proteins found in the eukaryotic clades previously studied. Here, we report the identification of silicon transporter (SIT)-type genes from the siliceous loricate choanoflagellates Stephanoeca diplocostata and Diaphanoeca grandis. Until now, the SIT gene family has been identified only in diatoms and other siliceous stramenopiles, which are distantly related to choanoflagellates among the eukaryotes. This is the first evidence of similarity between SITs from different eukaryotic supergroups. Phylogenetic analysis indicates that choanoflagellate and stramenopile SITs form distinct monophyletic groups. The absence of putative SIT genes in any other eukaryotic groups, including non-siliceous choanoflagellates, leads us to propose that SIT genes underwent a lateral gene transfer event between stramenopiles and loricate choanoflagellates. We suggest that the incorporation of a foreign SIT gene into the stramenopile or choanoflagellate genome resulted in a major metabolic change: the acquisition of biomineralized silica structures. This hypothesis implies that biosilicification has evolved multiple times independently in the eukaryotes, and paves the way for a better understanding of the biochemical basis of silicon transport through identification of conserved sequence motifs.
We illuminate the nature of the three-dimensional random walks of microorganisms composed of individual organisms adhered together. Such aggregate random walkers are typified by choanoflagellates, eukaryotes that are the closest living relatives of animals. In the colony-forming species Salpingoeca rosetta we show that the beating of each flagellum is stochastic and uncorrelated with others, and the vectorial sum of the flagellar propulsion manifests as stochastic helical swimming. A quantitative theory for these results is presented and species variability discussed.
As the closest unicellular relatives of animals, choanoflagellates serve as useful model organisms for understanding the evolution of animal multicellularity. An important factor in animal evolution was the increasing ocean oxygen levels in the Precambrian, which are thought to have influenced the emergence of complex multicellular life. As a first step in addressing these conditions, we study here the response of the colony-forming choanoflagellate Salpingoeca rosetta to oxygen gradients. Using a microfluidic device that allows spatio-temporal variations in oxygen concentrations, we report the discovery that S. rosetta displays positive aerotaxis. Analysis of the spatial population distributions provides evidence for logarithmic sensing of oxygen, which enhances sensing in low oxygen neighborhoods. Analysis of search strategy models on the experimental colony trajectories finds that choanoflagellate aerotaxis is consistent with stochastic navigation, the statistics of which are captured using an effective continuous version based on classical run-and-tumble chemotaxis.DOI: http://dx.doi.org/10.7554/eLife.18109.001
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