Going ballistic in the plankton: anisotropic swimming behavior of marine protists

Diel vertical migrations (DVMs) of many plankton species, including single-celled protists, are well documented in the field and form a core component of many large-scale numerical models of plankton transport and ecology. However, the sparse quantitative data available describing motility behaviors of individual protists have frequently indicated that motility exhibits only short-term correlation on the order of a few seconds or hundreds of micrometers, resembling diffusive transport at larger scales—a result incompatible with DVM, which requires ballistic (straight-line) motion. We interrogated an extensive set of three-dimensional protistan movement trajectories in an effort to identify spatial and temporal correlation scales. Whereas the horizontal components of movement were diffusive, the vertical component remained highly correlated (i.e., nonrandom) for nearly all species for the duration of observation (up to 120 s and 6.1 mm) and in the absence of any environmental cues besides gravity. These persistent motility patterns may have been obscured in some previous studies due to the use of restrictive containers, dimensionally lumped, isotropic analyses, and/or an observation bias, inherent to observing free-swimming organisms with stationary cameras, which we accounted for in this study. Extrapolated over a 12-h period, conservative estimates of vertical travel ranges for the protists observed here would be 3–10 m, while diffusive horizontal motion would result in about 10 cm of travel at most. Hence, these extended observations of phylogenetically diverse swimming protists, coupled with a quantitative analysis that accounts for anisotropy in the data, illustrate the small-scale mechanistic underpinnings of DVM

The theory of games and microbe ecology

Using game theory, we provide mathematical proof that if a species of asexually reproducing microbes is not characterized by maximum variability in competitive abilities among its individual organisms, then that species is vulnerable to replacement by competitors. Furthermore, we prove that such maximally variable species are neutral towards each other in competition for limited resources; they coexist. Our proof is constructive: given one species which does not possess maximum variability, we construct a second species with the same (or lower) mean competitive ability which can outcompete the first, in the sense that its expected value in competition is positive, whereas the expected value of the non-maximally variable species is negative. Our results point towards the mechanistic underpinnings for the frequent observations that (1) microbes are characterized by large intra-specific variability and that (2) the number of extant microbe species is very large

Contribution to the Themed Section: Scaling from individual plankton to marine ecosystems HORIZONS Small bugs with a big impact: linking plankton ecology with ecosystem processes

As an introduction to the following Themed Section on the significance of planktonic organisms to the functioning of marine ecosystems and global biogeochemical cycles we discuss the ramifications size imparts on the biology of plankton. We provide examples of how the characteristics of these microscopic organisms shape plankton population dynamics, distributions, and ecosystem functions. Key features of the marine environment place constraints on the ecology and evolution of plankton. Understanding these constraints is critical in developing a mechanistic understanding and predictive capacity of how planktonic ecosystems function, render their capacities in terms of biogeochemical cycling and trophic transfer, and how planktonic communities might respond to changing climate conditions

Common temperature-growth dependency and acclimation response in three herbivorous protists

Phytoplankton growth dependence on temperature is recognized and has been quantified comprehensively. However, no similar relationship exists for the major phytoplankton predators, the herbivorous protists, especially at low temperatures representing polar and coastal oceans during most seasons. Their acclimation to changing temperatures is also largely unexplored. Here we report acclimated growth and acclimation rates from 0 to 22°C for 3 cosmopolitan herbivorous dinoflagellates. Due to interactive effects between size and temperature, growth increased 40% more rapidly with increasing temperature for production- compared to division-based growth rates (0.043 and 0.062 d-1 °C-1, respectively). Biomass-based growth rates were 10-fold higher than abundance-based rates at low temperatures, reflecting an average 50% increase in biovolume at ≤2°C. Thus, there was significant biomass accumulation at low temperatures, despite low cell-division rates. Testing different acclimation procedures, we established that acclimated rates emerged after 3 generations. Herbivores required 1.25 d °C-1 when acclimating towards higher temperatures and 2.5 d °C-1 when transitioning towards lower temperatures. Growth rates increased linearly with temperature, implying a weaker temperature effect on growth than the commonly assumed exponential dependency. A possible consequence is that herbivore growth rates are underestimated at cold and overestimated at warm temperatures. Current and future ocean assessments could thus underestimate trophic transfer rates in polar and cold-water regions and overestimate herbivore growth and thus grazing impact in future ocean predictions. Identifying physiological responses that transcend species-specificity supports cross-biome comparisons of ecosystem structure and function that rely on accurate predictions of matter and energy flow in planktonic food webs

Predator-Induced Fleeing Behaviors in Phytoplankton: A New Mechanism for Harmful Algal Bloom Formation?

In the plankton, heterotrophic microbes encounter and ingest phytoplankton prey, which effectively removes \u3e50% of daily phytoplankton production in the ocean and influences global primary production and biochemical cycling rates. Factors such as size, shape, nutritional value, and presence of chemical deterrents are known to affect predation pressure. Effects of movement behaviors of either predator or prey on predation pressure, and particularly fleeing behaviors in phytoplankton are thus far unknown. Here, we quantified individual 3D movements, population distributions, and survival rates of the toxic phytoplankton species, Heterosigma akashiwo in response to a ciliate predator and predator-derived cues. We observed predator-induced defense behaviors previously unknown for phytoplankton. Modulation of individual phytoplankton movements during and after predator exposure resulted in an effective separation of predator and prey species. The strongest avoidance behaviors were observed when H. akashiwo co-occurred with an actively grazing predator. Predator-induced changes in phytoplankton movements resulted in a reduction in encounter rate and a 3-fold increase in net algal population growth rate. A spatially explicit population model predicted rapid phytoplankton bloom formation only when fleeing behaviors were incorporated. These model predictions reflected field observations of rapid H. akashiwo harmful algal bloom (HAB) formation in the coastal ocean. Our results document a novel behavior in phytoplankton that can significantly reduce predation pressure and suggests a new mechanism for HAB formation. Phytoplankton behaviors that minimize predatory losses, maximize resource acquisition, and alter community composition and distribution patterns could have major implications for our understanding and predictive capacity of marine primary production and biochemical cycling rates

Early Spring Phytoplankton Dynamics in the Subpolar North Atlantic: The Influence of Protistan Herbivory

We measured phytoplankton-growth (μ) and herbivorous-protist grazing (g) rates in relation to mixed-layer-depth (MLD) during the March/April 2012 EuroBasin cruise in the subpolar North Atlantic. We performed 15 dilution experiments at two open-ocean (∼ 1300 m) and one shelf (160 m) station. Of the two open-ocean stations one was deeply mixed (476 m), the other stratified (46 m). At the shelf station, MLD reached the bottom. Initial chlorophyll a (Chl a) varied from 0.2–1.9 μg L−1 and increased up to 2.7 μg L−1 at the shelf station. In 80% of experiments, regardless of MLD, growth-rates exceeded grazing-mortality rates. At the open-ocean stations, the deep ML coincided with μ and g that varied over the same range (≤ 0–0.6 d−1), whereas stratification corresponded to μ and g that ranged from 0.14–0.41 d−1 to 0.11–0.34 d−1, respectively. At the stratified station, the balance between μ and g explained 98% of in situ variations in Chl a, whereas at the deep-ML station, rate estimates had no explanatory power. The consistent relationship between μ and g, which corresponded to a grazing-removal of 64% of primary production, suggests that g might be predictable if μ is known, and that a coefficient of 0.64 may be a useful parameter for subarctic carbon models. Composition and persistence of the plankton assemblages differed at the stations and may have been a significant driver of grazing-pressure. Overall, these results showed no association of MLD with grazing-pressure and highlight the need to assess to what extent MLD represents the depth of active-mixing to understand the effects of protistan-grazing on the development of the North Atlantic spring bloom

Physical and optical properties of phytoplankton-rich layers in a coastal fjord: a step toward prediction and strategic sampling of plankton patchiness

Dense aggregations of phytoplankton in layers or patches alter the optical and physical properties of the water column and result in significant heterogeneity in trophic and demographic rates of local plankton populations. Determining the factors driving patch formation, persistence, intensity, and dissipation is key to understanding the ramifications of plankton patchiness in marine systems. Regression and multi-parametric statistical analyses were used to identify the physical and optical properties associated with 71 phytoplankton-rich layers (PRLs) identified from 158 CTD profiles collected between 2008 and 2010 in East Sound, Washington, USA. Generalized additive models (GAMs) were used to explore water column properties associated with and characterizing PRLs. Patch presence was associated with increasing water column stability represented by the Brunt-Väisälä frequency (N2), Thorpe scale (Lt), and turbulent energy dissipation rate (e). A predictive regression identified patch presence with 100% accuracy when log10(N2) = -1 and 70% of the cases when log10(e) = -3. A GAM of passively measured variables, which did not include fluorescence, was able to model patch intensity with considerable agreement (R2 = 0.58), and the fit was improved by including fluorescence (R2 = 0.69). Fluorescence alone was an insufficient predictor of PRLs, due in part to the influence of non-photochemical quenching (NPQ) in surface waters and the wide range of fluorescence intensities observed. The results show that a multi-parametric approach was necessary to characterize phytoplankton patches and that physical structure, resulting in steep gradients in bio-optical properties, hold greater predictive power than bio-optical properties alone. Integration of these analytical approaches will aid theoretical studies of phytoplankton patchiness but also improve sampling strategies in the field that utilize autonomous, in situ instrumentatio

The Impact of <i>Candida rugosa</i> Lipase in the Gut Microbiome in Health and Alzheimer’s Disease and Identification of Allosteric Modulators

Alzheimer’s disease (AD) affects more than 50 million people worldwide. Despite the continual identification of new disease features, treatment options are limited due to failure of clinical trials to identify effective treatments. Consequently, novel therapeutic strategies arising from other areas of research, such as the gut microbiome, are being considered due to their potential to modulate AD pathology. The gut microbiome is regarded as a symbiotic physiological regulator of human health via the bidirectional gut–brain axes. Several studies have revealed a persistent compositional imbalance in the gut microbiome of both AD patients and in animal models of AD potentially contributing to AD pathology. Conversely, it has been suggested that normalization of the gut microbial composition might ameliorate AD pathology in animal models and in humans. In healthy individuals, shifts of the gut microbiota primarily occur in response to dietary changes such as administration of exogenous enzymes. These enzymes can evoke shifts in the composition of the gut microbiota by increasing enzymatic activity in the digestive tract and therefore the release of metabolites from dietary macromolecules. Lipases are one subclass of digestive enzymes which can elevate gut availability of fatty acids and glycerol. Some of these cleavage products can promote growth and metabolite production of specific bacterial species changing the gut microbial composition. Hence, we hypothesized that “Oral administration of an exogenous lipase in AP/PS1 mice normalizes gut microbiome and metabolite composition, and rescues AD pathology and aberrant behavior”. To this end, three hypotheses were examined: (1) Oral lipase administration in C67BL/6J (Wt) mice will alter free fatty acid and glycerol release in the gut; (2) oral lipase administration in APPsw/PS1-de9 (APP/PS1) mice will normalize the gut microbiota and metabolite composition that correlates with improved AD-like pathology; and (3) that a combined use of a positive allosteric modulator with the exogenous lipase will enhance the expected effects from hypotheses (1) and (2). The studies revealed that exogenous lipase administration is correlated with normalization of gut microbiome and metabolite composition in Wt and APP/PS1 animals. Furthermore, administration of exogenous lipase correlated with reduced AD-like pathology and behavior in APP/PS1 animals. In addition, we provided evidence that the treatment-dependent shifts in the gut microbiome and metabolite composition of APP/PS1 mice caused the observed improvement of memory in these animals. Collectively, this work advances our understanding of how CRL could be used to reduce AD pathology and might present novel treatment options for AD patients

Computational methods and analyses to dissect the pathogenesis of Frontotemporal Dementia

rontotemporal Dementia (FTD) is a devastating neurodegenerative disorder that typi cally manifests before the age of 65 and is characterized by progressive degeneration of frontal and temporal lobes as well as behavioural changes and problems with speech. Although great advancements in our understanding of FTD have been made during the last decades, there still does not exist a treatment that halts the progression of this dis ease. It is therefore necessary to further advance our understanding of the molecular mechanisms that cause FTD and that drive disease progression forward. In this thesis, I have contributed to the field of FTD research through the development of computational methods and the analysis of multi-omics datasets in order the develop new hypotheses for disease mechanisms in FTD. Studying complex tissues such as the human brain requires to carefully consider the contributions of diverse components of such systems. A major factor in transcriptomic experiments is cell type composition, as every cell has a unique transcriptional profile. In chapter 2, we have developed a deep learning-based cell type deconvolution algorithm that outperforms other methods and, importantly, also works well on post-mortem human brain tissue. The algorithm was rigorously tested and made available to the community as an open source, accessible python package and as web application. In chapter 3, we have analysed multi-omics datasets from post-mortem human brain tissue of FTD patients with mutations in the genes GRN, MAPT and C9orf72. Using an integrative data analysis approach, we could identify common and distinct affected path ways in these three genetic FTD subtypes. We leveraged the rich multi-omics datasets to identify new aspects of the disease, such as vulnerable neurons and increasing blood vessel percentages. In-depth analysis could highlight several regulator molecules, such as micro RNAs and transcription factors, that are likely to play important roles in FTD and therefore depict promising subjects for future studies. In chapter 4, we have performed co-expression module analysis of transcriptional data from seven different brain regions of patients with genetic subtypes of FTD. Using this comprehensive dataset, we have highlighted regions that are transcriptionally affected in different FTD subtypes and regions that seem not to suffer from the disease. We further more highlighted region- and disease-specific co-expression modules and pinpointed hub genes of potentially important function for these modules. Our analysis is the first that evaluates transcriptional deregulation at such diversity in FTD, and therefore provides ixAbstract valuable novel insights for the field of FTD