Asymmetric cell division and its role in cell fate determination in the green alga Tetraselmis indica

Detection of periodic peaks in Karenia brevis concentration consistent with the time-delay logistic equation

The logistic equation models single-species population growth with a sigmoid curve that begins as exponential and ends with an asymptotic approach to a final population determined by natural system carrying capacity. But the population of a natural system often does not stabilize as it approaches carrying capacity. Instead, it exhibits periodic change, sometimes with very large amplitudes. The time-delay modification of the logistic equation accounts for this behavior by connecting the present rate of population growth to conditions at an earlier time. The periodic change in population with time can progress from a monotonic approach to the carrying capacity; to oscillation around the carrying capacity; to limit-cycle periodic change; and, finally, to chaotic change. The presence of multiple species and inadequate sampling frequency and spatial coverage hinder the application of the time-delay logistic equation to real-world populations. Blooms of Karenia brevis along the southwest Florida Gulf Coast, however, provide a unique opportunity in that blooms are nearly monospecific and are sampled frequently over a wide geographic region; they are good candidates for testing the time-delay logistic equation. We show that these blooms exhibit peaks in concentration with periods in the range of 40-100 days, consistent with that predicted by the time-delay logistic equation. Cell concentrations in the valleys between the peaks are at least 2-3 orders of magnitude lower than peak values, offering predictable windows of opportunity for potential mitigation efforts.

Functional Differences in the Blooming Phytoplankton Heterosigma akashiwo and Prorocentrum donghaiense Revealed by Comparative Metaproteomics

Phytoplankton blooms are natural phenomena in the ocean, which are the results of rapid cell growth of some phytoplankton species in a unique environment. However, little is known about the molecular events occurring during the bloom. Here, we compared metaproteomes of two phytoplankton Heterosigma akashiwo and Prorocentrum donghaiense in the coastal East China Sea. H. akashiwo and P. donghaiense accounted for 7.82% and 4.74% of the phytoplankton community protein abundances in the nonbloom sample, whereas they contributed to 60.13% and 78.09%, respectively, in their individual blooming samples. Compared with P. donghaiense, H. akashiwo possessed a significantly higher abundance of light-harvesting complex proteins, carbonic anhydrasem and RuBisCO. The blooming H. akashiwo cells expressed more proteins related to external nutrient acquisition, such as bicarbonate transporter SLC4, ammonium transporter, nitrite transporter, and alkaline phosphatase, while the blooming P. donghaiense cells highly expressed proteins related to extra- and intracellular organic nutrient utilization, such as amino acid transporter, 5'-nucleotidase, acid phosphatase, and tripeptidyl-peptidase. The strong capabilities of light harvesting, as well as acquisition and assimilation of inorganic carbon, nitrogen, and phosphorus, facilitated the formation of the H. akashiwo bloom under the high turbidity and inorganic nutrient-sufficient condition, whereas the competitive advantages in organic nutrient acquisition and reallocation guaranteed the occurrence of the P. donghaiense bloom under the inorganic nutrient-insufficient condition. This study highlights the power of metaproteomics for revealing the underlying molecular behaviors of different coexisting phytoplankton species and advances our knowledge on the formation of phytoplankton blooms.IMPORTANCE A deep understanding of the mechanisms driving bloom formation is a prerequisite for effective bloom management. Metaproteomics was applied in this study to reveal the adaptive and responsive strategies of two coexisting phytoplankton species, H. akashiwo and P. donghaiense, during their bloom periods. Metabolic features and niche divergence in light harvesting, as well as carbon, nitrogen, and phosphorus acquisition and assimilation likely promoted the bloom occurrence under different environments. The molecular behaviors of coexisting bloom-causing species will give clues for bloom monitoring and management in the oceans.