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It is widely assumed that phytoplankton abundance and productivity decline during temperate winters because of low irradiance and temperatures. However, winter phytoplankton blooms commonly occur in temperate estuaries, but they are often undocumented because of reduced water quality monitoring in winter. The small body of in situ work that has been done on winter blooms suggests they can be of enormous consequence to ecosystems. However, because monitoring is often reduced or stopped altogether during winter, it is unclear how widespread these blooms are or how long they can last. We analyzed an over 30-year record of monthly phytoplankton monitoring samples along with ad hoc sampling throughout Chesapeake Bay to assess the distributions of two common winter bloom species, Heterocapsa rotundata and Heterocapsa steinii, and the environmental conditions associated with these blooms. The long-term monitoring data revealed that H. rotundata blooms occur within a narrow salinity range (7–12) and potentially have different triggers depending upon the nutrient status of waters affected. The ad hoc sampling confirmed the occurrence of H. steinii blooms in the lower Chesapeake Bay, despite the lack of evidence for them from monthly monitoring data. Together, our findings demonstrate that winter blooms routinely occur in numerous locations throughout Chesapeake Bay and can last up to a month. Our findings suggest that while winter blooms are a staple of the Bay’s annual phytoplankton community, there are major data gaps reporting their occurrence highlighting the need for more frequent monitoring to understand factors promoting these blooms and their consequences on ecosystem productivity.

Contains fulltext : 291657.pdf (Publisher’s version ) (Open Access) BACKGROUND: Anti-TNF drugs, such as infliximab, are associated with attenuated antibody responses after SARS-CoV-2 vaccination. We aimed to determine how the anti-TNF drug infliximab and the anti-integrin drug vedolizumab affect vaccine-induced neutralising antibodies against highly transmissible omicron (B.1.1.529) BA.1, and BA.4 and BA.5 (hereafter BA.4/5) SARS-CoV-2 variants, which possess the ability to evade host immunity and, together with emerging sublineages, are now the dominating variants causing current waves of infection. METHODS: CLARITY IBD is a prospective, multicentre, observational cohort study investigating the effect of infliximab and vedolizumab on SARS-CoV-2 infection and vaccination in patients with inflammatory bowel disease (IBD). Patients aged 5 years and older with a diagnosis of IBD and being treated with infliximab or vedolizumab for 6 weeks or longer were recruited from infusion units at 92 hospitals in the UK. In this analysis, we included participants who had received uninterrupted biological therapy since recruitment and without a previous SARS-CoV-2 infection. The primary outcome was neutralising antibody responses against SARS-CoV-2 wild-type and omicron subvariants BA.1 and BA.4/5 after three doses of SARS-CoV-2 vaccine. We constructed Cox proportional hazards models to investigate the risk of breakthrough infection in relation to neutralising antibody titres. The study is registered with the ISRCTN registry, ISRCTN45176516, and is closed to accrual. FINDINGS: Between Sept 22 and Dec 23, 2020, 7224 patients with IBD were recruited to the CLARITY IBD study, of whom 1288 had no previous SARS-CoV-2 infection after three doses of SARS-CoV-2 vaccine and were established on either infliximab (n=871) or vedolizumab (n=417) and included in this study (median age was 46·1 years [IQR 33·6-58·2], 610 [47·4%] were female, 671 [52·1%] were male, 1209 [93·9%] were White, and 46 [3·6%] were Asian). After three doses of SARS-CoV-2 vaccine, 50% neutralising titres (NT50s) were significantly lower in patients treated with infliximab than in those treated with vedolizumab, against wild-type (geometric mean 2062 [95% CI 1720-2473] vs 3440 [2939-4026]; p

The expression of long noncoding RNAs is highly enriched in the human nervous system. However, the function of neuronal lncRNAs in the cytoplasm and their potential translation remains poorly understood. Here we performed Poly-Ribo-Seq to understand the interaction of lncRNAs with the translation machinery and the functional consequences during neuronal differentiation of human SH-SY5Y cells. We discovered 237 cytoplasmic lncRNAs up-regulated during early neuronal differentiation, 58%–70% of which are associated with polysome translation complexes. Among these polysome-associated lncRNAs, we find 45 small ORFs to be actively translated, 17 specifically upon differentiation. Fifteen of 45 of the translated lncRNA-smORFs exhibit sequence conservation within Hominidea, suggesting they are under strong selective constraint in this clade. The profiling of publicly available data sets revealed that 8/45 of the translated lncRNAs are dynamically expressed during human brain development, and 22/45 are associated with cancers of the central nervous system. One translated lncRNA we discovered is LINC01116, which is induced upon differentiation and contains an 87 codon smORF exhibiting increased ribosome profiling signal upon differentiation. The resulting LINC01116 peptide localizes to neurites. Knockdown of LINC01116 results in a significant reduction of neurite length in differentiated cells, indicating it contributes to neuronal differentiation. Our findings indicate cytoplasmic lncRNAs interact with translation complexes, are a noncanonical source of novel peptides, and contribute to neuronal function and disease. Specifically, we demonstrate a novel functional role for LINC01116 during human neuronal differentiation.

SeaFlow is an underway flow cytometer that provides continuous shipboard observations of the abundance and optical properties of small phytoplankton (, Measurement(s)planktonic material • temperature of water • salinity • light irradiance • plankton size distributionTechnology Type(s)flow cytometer • Temperature Sensor Device • salinometer • photometerFactor Type(s)time • locationSample Characteristic - OrganismCyanobacteria • Micromonas pusilla • Navicula transitans • Thalassiosira pseudonana • Thalassiosira weissflogii • Geminifera cryophila • Crocosphaera • Synechococcus sp. WH 8012 • Synechococcus sp. WH 6501 • Prochlorococcus eMED4 • Prochlorococcus eMIT9312 • Prochlorococcus AS9601 • Prochlorococcus 1314Sample Characteristic - Environmentoceanic sea surface microlayer biome • sea waterSample Characteristic - LocationNorth Pacific Ocean Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.10110755

As primary producers, phytoplankton play an integral role in global biogeochemical cycles through their production of oxygen and fixation of carbon. They also provide significant ecosystem services, by supporting secondary production and fisheries. Phytoplankton biomass and diversity have been identified by the Global Ocean Observing System (GOOS) as Essential Ocean Variables (EOVs), properties that need to be monitored to better understand and predict the ocean system. Phytoplankton identification and enumeration relies on the skills and expertise of highly trained taxonomic analysts. The training of new taxonomic analysts is intensive and requires months to years of supervised training before an analyst is able to independently and consistently apply identification skills to a sample. During the COVID-19 pandemic, access to laboratories was greatly restricted and social distancing requirements prevented supervised training. However, access to phytoplankton imaging technologies such as the Imaging FlowCytobot (IFCB), FlowCam, and PlanktoScope, combined with open online taxonomic identification platforms such as EcoTaxa, provided a means to continue monitoring, research, and training activities remotely when in-person activities were restricted. Although such technologies can not entirely replace microscopy, they have a great potential for supporting an expansion in taxonomic training, monitoring, surveillance, and research capacity. In this paper we highlight a set of imaging and collaboration tools and describe how they were leveraged during laboratory lockdowns to advance research and monitoring goals. Anecdotally, we found that the use of imaging tools accelerated the training of new taxonomic analysts in our phytoplankton analysis laboratory. Based on these experiences, we outline how these technologies can be used to increase capacity in taxonomic training and expertise, as well as how they can be used more broadly to expand research opportunities and capacity.

Marine phytoplankton generate half of global primary production, making them essential to ecosystem functioning and biogeochemical cycling. Though phytoplankton are phylogenetically diverse, studies rarely designate unique thermal traits to different taxa, resulting in coarse representations of phytoplankton thermal responses. Here we assessed phytoplankton functional responses to temperature using empirically derived thermal growth rates from four principal contributors to marine productivity: diatoms, dinoflagellates, cyanobacteria, and coccolithophores. Using modeled sea surface temperatures for 1950–1970 and 2080–2100, we explored potential alterations to each group’s growth rates and geographical distribution under a future climate change scenario. Contrary to the commonly applied Eppley formulation, our data suggest phytoplankton functional types may be characterized by different temperature coefficients (Q10), growth maxima thermal dependencies, and thermal ranges which would drive dissimilar responses to each degree of temperature change. These differences, when applied in response to global simulations of future temperature, result in taxon-specific projections of growth and geographic distribution, with low-latitude coccolithophores facing considerable decreases and cyanobacteria substantial increases in growth rates. These results suggest that the singular effect of changing temperature may alter phytoplankton global community structure, owing to the significant variability in thermal response between phytoplankton functional types., Phytoplankton communities are important players in biogeochemical processes, but are sensitive to global warming. Here, a meta-analysis shows how the varied responses of phytoplankton to rising temperatures could potentially alter growth dynamics and community structure in a future ocean.

The Kuroshio current separates from the Japanese coast to become the eastward flowing Kuroshio Extension (KE) characterized by a strong latitudinal density front, high levels of mesoscale (eddy) energy, and high chlorophyll

The study of connectivity patterns in networks has brought novel insights across diverse fields ranging from neurosciences to epidemic spreading or climate. In this context, betweenness centrality has demonstrated to be a very effective measure to identify nodes that act as focus of congestion, or bottlenecks, in the network. However, there is not a way to define betweenness outside the network framework. By analytically linking dynamical systems and network theory, we provide a trajectory-based formulation of betweenness, called Lagrangian betweenness, as a function of Lyapunov exponents. This extends the concept of betweenness beyond the context of network theory relating hyperbolic points and heteroclinic connections in any dynamical system to the structural bottlenecks of the network associated with it. Using modeled and observational velocity fields, we show that such bottlenecks are present and surprisingly persistent in the oceanic circulation across different spatio-temporal scales and we illustrate the role of these areas in driving fluid transport over vast oceanic regions. Analyzing plankton abundance data from the Kuroshio region of the Pacific Ocean, we find significant spatial correlations between measures of diversity and betweenness, suggesting promise for ecological applications., MJF and ES-R are very grateful for support from the Simons Foundation: the Simons Collaboration on Computational BIOgeochemical modeling of Marine EcosystemS (CBIOMES #549931 to MJF). C.L. and E.H-G acknowledge financial support from the Spanish State Research Agency through the Maria de Maeztu Program for Units of Excellence in R&D (MDM-2017-0711).

LncRNAs are less conserved, yet more tissue and developmental-stage specific than mRNAs and are particularly enriched in the nervous system ofDrosophila melanogaster, mouse and human. The function of cytoplasmic lncRNAs and their potential translation remains poorly understood. Here we performed Poly-Ribo-Seq to understand the interaction of lncRNAs with the translation machinery and the functional consequences during neuronal differentiation of SH-SH5Y cells. We discovered 237 cytoplasmic lncRNAs upregulated during early neuronal differentiation, most of which are associated with polysome complexes. The majority are cytoplasmically enriched and are intergenic or anti-sense. In addition, we find 45 small ORFs in lncRNAs to be actively translated, 17 specifically upon differentiation. 11 of these smORFs exhibit high sequence conservation acrossHominidaesuggesting they are under strong selective constraint with putative function in this clade. We discover LINC01116 is induced upon differentiation and contains an 87 codon smORF, which we detect as translated, with increased ribosome profiling signal upon differentiation. The LINC01116 peptide exhibits a cytoplasmic distribution and is detected in neurites. Knockdown of LINC01116 results in significant reduction of neurite length in differentiated cells indicating it contributes to neuronal differentiation. Our findings indicate lncRNAs are a source of non-canonical peptides and contribute to neuronal function.

The Kuroshio current separates from the Japanese coast to become the Kuroshio Extension (KE) characterized by a strong latitudinal density front, high levels of mesoscale (eddy) energy, and high ch...

Nitrate interleaving structures were observed below the mixed layer during a cruise to the Kuroshio Extension in October 2009. In this paper, we investigate the formation mechanisms for these vertical nitrate anomalies, which may be an important source of nitrate to the oligotrphoc surface waters south of the Kuroshio Extension Front. We found that nitrate concentrations below the main stream of the Kuroshio Extension were elevated compared to the ambient water of the same density (σ 𝜃 = 23.5–25). This appears to be analogous to the “nutrient stream” below the mixed layer, associated with the Gulf Stream. Strong turbulence was observed above the vertical nitrate anomaly, and we found that this can drive a large vertical turbulent nitrate flux $>\mathcal {O}$ (1 mmol N m−2 day−1). A realistic, high-resolution (2 km) numerical simulation reproduces the observed Kuroshio nutrient stream and nitrate interleaving structures, with similar lateral and vertical scales. The model results suggest that the nitrate interleaving structures are first generated at the western side of the meander crest on the south side of the Kuroshio Extension, where the southern tip of the mixed layer front is under frontogenesis. Lagrangian analyses reveal that the vertical shear of geostrophic and subinertial ageostrophic flow below the mixed layer tilts the existing along-isopycnal nitrate gradient of the Kuroshio nutrient stream to form nitrate interleaving structures. This study suggests that the multi-scale combination of (i) the lateral stirring of the Kuroshio nutrient stream by developed mixed layer fronts during fall to winter, (ii) the associated tilting of along-isopycnal nitrate gradient of the nutrient stream by subinertial shear, which forms vertical interleaving structures, and (iii) the strong turbulent diffusion above them, may provide a route to supply nutrients to oligotrophic surface waters on the south side of the Kuroshio Extension.

Advances in technology and modeling capabilities are driving a surge in progress in our understanding of how ocean ecosystems mix and mingle on medium to small scales.

Western boundary currents support high primary production and carbon export. Here, we performed a survey of photosynthetic picoeukaryotes in the North Pacific Ocean in four transects crossing the Kuroshio Front. Prasinophyte algae comprised 85% of 18S rRNA gene sequences for photosynthetic taxa in the

Theoretical studies predict that competition for limited resources reduces biodiversity to the point of ecological instability, whereas strong predator/prey interactions enhance the number of coexisting species and limit fluctuations in abundances. In open ocean ecosystems, competition for low availability of essential nutrients results in relatively few abundant microbial species. The remarkable stability in overall cell abundance of the dominant photosynthetic cyanobacterium Prochlorococcus is assumed to reflect a simple food web structure strongly controlled by grazers and/or viruses. This hypothesized link between stability and ecological interactions, however, has been difficult to test with open ocean microbes because sampling methods commonly have poor temporal and spatial resolution. Here we use continuous techniques on two different winter-time cruises to show that Prochlorococcus cell production and mortality rates are tightly synchronized to the day/night cycle across the subtropical Pacific Ocean. In warmer waters, we observed harmonic oscillations in cell production and mortality rates, with a peak in mortality rate consistently occurring ∼6 h after the peak in cell production. Essentially no cell mortality was observed during daylight. Our results are best explained as a synchronized two-component trophic interaction with the per-capita rates of Prochlorococcus consumption driven either directly by the day/night cycle or indirectly by Prochlorococcus cell production. Light-driven synchrony of food web dynamics in which most of the newly produced Prochlorococcus cells are consumed each night likely enforces ecosystem stability across vast expanses of the open ocean. © 2015, National Academy of Sciences. All rights reserved.

Concurrent physical, chemical and biological observations across the Kuroshio Front collected in October 2009 provide a detailed view of the relationship between the physical environment and the phytoplankton community. Depth profiles were taken at stations 9 km apart along five 70 km transects. With a combination of flow cytometry, microscopy and high-pressure liquid chromatography pigment analysis, we characterized the phytoplankton community structure across the front. The observed phytoplankton community fell into two distinct assemblages, largely separated by the front, but which also reflected patterns in the distribution of Kuroshio and Oyashio water masses shaped by mesoscale lateral mixing. Phytoplankton biomass was elevated where there was a positive vertical flux of nitrate towards the surface, and the frontal circulation drove a lateral transport of nutrients southwards into the subtropical gyre. The observations showed that the phytoplankton respond to forcing on several scales: the phytoplankton community across the front was shaped by a combination of the large scale biogeography of the region, mesoscale mixing of populations and finer scale modification of the light and nutrient environment.

We examined the role of physical dispersal in regulating patterns of diversity of marine phytoplankton in the context of global ocean simulations at eddy-permitting and coarse resolutions. Swifter current speeds, faster dispersal, and increased environmental variability in the higher-resolution model enhanced local diversity almost everywhere. In the numerical simulations, each resolved phytoplankton type was characterized as “locally adapted” at any geographical location (i.e., having net local biological production and physical export) or “immigrant” (i.e., net local biological loss but a population sustained by immigration via physical transport). Immigrants accounted for a higher fraction of the total diversity in the equatorial and subtropical regions, where the exclusion timescale is long relative to the physical transport between “provinces.” Hotspots of diversity were associated with western boundary currents and coastal upwelling regions. The former had high locally adapted diversity within the core of the current system, maintained by confluence of upstream populations and the induction of nutrient resources, as well as environmental variability associated with mesoscale eddies. Downstream of strong nutrient sources, convergence of populations led to immigrant-dominated diversity. The numerical simulations provide testable predictions of patterns in diversity and hypotheses regarding the mechanisms that control them. Molecular approaches to characterizing diversity in microbial populations will provide a means to test these hypotheses.

Motivation: Recent technological innovations in flow cytometry now allow oceanographers to collect high-frequency flow cytometry data from particles in aquatic environments on a scale far surpassing conventional flow cytometers. The SeaFlow cytometer continuously profiles microbial phytoplankton populations across thousands of kilometers of the surface ocean. The data streams produced by instruments such as SeaFlow challenge the traditional sample-by-sample approach in cytometric analysis and highlight the need for scalable clustering algorithms to extract population information from these large-scale, high-frequency flow cytometers. Results: We explore how available algorithms commonly used for medical applications perform at classification of such a large-scale, environmental flow cytometry data. We apply large-scale Gaussian mixture models to massive datasets using Hadoop. This approach outperforms current state-of-the-art cytometry classification algorithms in accuracy and can be coupled with manual or automatic partitioning of data into homogeneous sections for further classification gains. We propose the Gaussian mixture model with partitioning approach for classification of large-scale, high-frequency flow cytometry data. Availability and Implementation: Source code available for download at https://github.com/jhyrkas/seaflow_cluster, implemented in Java for use with Hadoop. Contact: hyrkas@cs.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online.

The physical environment in the oceans dictates not only how phytoplankton cells are dispersed and their populations intermingled, but also mediates the supply of nutrients to the surface mixed layer. In this thesis I explore both of these aspects of the interaction between phytoplankton ecology and ocean physics, and have approached this topic in two distinct but complementary ways, working with a global ocean ecosystem model, and collecting data at sea. In the first half of the thesis, I examine the role of mesoscale physical features in shaping phytoplankton community structure and influencing rates of primary production. I compare the output of a complex marine ecosystem model coupled to coarse resolution and eddy-permitting physical models. Explicitly resolving eddies resulted in marked regional variations in primary production, zooplankton and phytoplankton biomass. The same phytoplankton phenotypes persisted in both cases, and were dominant in the same regions. Global phytoplankton diversity was unchanged. However, levels of local phytoplankton diversity were markedly different, with a large increase in local diversity in the higher resolution model. Increased diversity could be attributed to a combination of enhanced dispersal, environmental variability and nutrient supply in the higher resolution model. Diversity ”hotspots” associated with western boundary currents and coastal upwelling zones are sustained through a combination of all of these factors. In the second half of the thesis I describe the results of a fine scale ecological and biogeochemical survey of the Kuroshio Extension Front. I found fine scale patterns in physical, chemical and biological properties that can be linked back to both the large scale horizontal and smaller scale vertical physical dynamics of the study region. A targeted genomic analysis of samples focused on the ecology of the picoeukaryote Ostreococcus clade distributions strongly supports the model derived hypotheses about the mechanisms supporting diversity hotspots. Strikingly, two distinct clades of Ostreococcus co-occur in more than half of the samples. A ”hotspot” of Ostreococcus diversity appears to be supported by a confluence of water masses containing either clade, as well as a local nutrient supply at the front and the mesoscale variability of the region.

[1] Plankton patchiness is ubiquitous in the oceans, and various physical and biological processes have been proposed as its generating mechanisms. However, a coherent statement on the problem is missing, because of both a small number of suitable observations and an incomplete understanding of the properties of reactive tracers in turbulent media. It has been suggested that horizontal advection may be the dominant process behind the observed distributions of phytoplankton and zooplankton, acting to mix tracers with longer reaction times (Rt) down to smaller scales. Conversely, the relative distributions of sea surface temperature and phytoplankton has been attributed to small-scale upwelling, where tracers with longer Rt are able to homogenize more than those with shorter reaction times. Neither of the above mechanisms can explain simultaneously the (relative) spectral slopes of temperature, phytoplankton, and zooplankton. Here, with a simple advection model and a large suite of numerical experiments, we concentrate on some of the physical processes influencing the relative distributions of tracers at the ocean surface, and we investigate (1) the impact of the spatial scale of tracer supply, (2) the role played by coherent eddies on the distribution of tracers with different Rt, and (3) the role of diffusion (so far neglected). We show that diffusion determines the distribution of temperature, regardless of the nature of the forcing. We also find that coherent structures together with differential diffusion of tracers with different Rt impact the tracer distributions. This may help in understanding the highly variable nature of observed plankton spectra.

SummaryAutomated, ship-board flow cytometers provide high-resolution maps of phytoplankton composition over large swaths of the world’s oceans. They therefore pave the way for understanding how environmental conditions shape community structure. Identification of community changes along a cruise transect commonly segments the data into distinct regions. However, existing segmentation methods are generally not applicable to flow cytometry data, as this data is recorded as “point cloud” data, with hundreds or thousands of particles measured during each time interval. Moreover, nonparametric segmentation methods that do not rely on prior knowledge of the number of species, are desirable to map community shifts.We present CytoSegmenter, a kernel-based change-point estimation method for segmenting point cloud data that does not rely on parametric assumptions on the data distributions. Our method relies on a Hilbertian embedding of point clouds that allows us to work with point cloud data similarly to vectorial data. The change-point locations can be found using an efficient dynamic programming algorithm. The method can be used to automatically segment long series of underway flow cytometry data.Through an analysis of 12 cruises, we demonstrate that CytoSegmenter allows us to locate abrupt changes in phytoplankton community structure. We show that the changes in community structure generally coincide with changes in the temperature and salinity of the ocean. We also illustrate how the main parameter of CytoSegmenter can be easily calibrated using limited auxiliary annotated data.CytoSegmenter is publicly available and implemented in the programming language Python. The method is generally applicable for segmenting series of point cloud data from any domain. Moreover, it readily scales to thousands of point clouds, each containing thousands of points. In the context of underway flow cytometry data, it does not require prior clustering of particles to define taxa labels, eliminating a potential source of error. This represents an important advance in automating the analysis of large datasets now emerging in biological oceanography and other fields. It also allows for the approach to potentially be applied during research cruises.