Nested PCR Approach for petB Gene Metabarcoding of Marine Synechococcus Populations.

The molecular diversity of marine picocyanobacterial populations, an important component of phytoplankton communities, is better characterized using high-resolution marker genes than the 16S rRNA gene as they have greater sequence divergence to differentiate between closely related picocyanobacteria groups. Although specific ribosomal primers have been developed, another general disadvantage of bacterial ribosome-based diversity analyses is the variable number of rRNA gene copies. To overcome these issues, the single-copy petB gene, encoding the cytochrome b6 subunit of the cytochrome b6f complex, has been used as a high-resolution marker gene to characterize Synechococcus diversity. We have designed new primers targeting the petB gene and proposed a nested PCR method (termed Ong_2022) for metabarcoding of marine Synechococcus populations obtained by flow cytometry cell sorting. We evaluated the specificity and sensitivity of Ong_2022 against the standard amplification protocol (termed Mazard_2012) using filtered seawater samples. The Ong_2022 approach was also tested on flow cytometry-sorted Synechococcus populations. Samples (filtered and sorted) were obtained in the Southwest Pacific Ocean, from subtropical (ST) and subantarctic (SA) water masses. The two PCR approaches using filtered samples recovered the same dominant subclades, Ia, Ib, IVa, and IVb, with small differences in relative abundance across the distinct samples. For example, subclade IVa was dominant in ST samples with the Mazard_2012 approach, while the same samples processed with Ong_2022 showed similar contributions of subclades IVa and Ib to the total community. The Ong_2022 approach generally captured a higher genetic diversity of Synechococcus subcluster 5.1 than the Mazard_2012 approach while having a lower proportion of incorrectly assigned amplicon sequence variants (ASVs). All flow cytometry-sorted Synechococcus samples could be amplified only by our nested approach. The taxonomic diversity obtained with our primers on both sample types was in agreement with the clade distribution observed by previous studies that applied other marker genes or PCR-free metagenomic approaches under similar environmental conditions. IMPORTANCE The petB gene has been proposed as a high-resolution marker gene to access the diversity of marine Synechococcus populations. A systematic metabarcoding approach based on the petB gene would improve the characterization/assessment of the Synechococcus community structure in marine planktonic ecosystems. We have designed and tested specific primers to be applied in a nested PCR protocol (Ong_2022) for metabarcoding the petB gene. The Ong_2022 protocol can be applied to samples with low DNA content, such as those obtained by flow cytometry cell sorting, allowing the simultaneous assessment of the genetic diversity of Synechococcus populations and cellular properties and activities (e.g., nutrient cell ratios or carbon uptake rates). Our approach will allow future studies using flow cytometry to investigate the link between ecological traits and taxonomic diversity of marine Synechococcus.

Salp blooms drive strong increases in passive carbon export in the Southern Ocean.

The Southern Ocean contributes substantially to the global biological carbon pump (BCP). Salps in the Southern Ocean, in particular Salpa thompsoni, are important grazers that produce large, fast-sinking fecal pellets. Here, we quantify the salp bloom impacts on microbial dynamics and the BCP, by contrasting locations differing in salp bloom presence/absence. Salp blooms coincide with phytoplankton dominated by diatoms or prymnesiophytes, depending on water mass characteristics. Their grazing is comparable to microzooplankton during their early bloom, resulting in a decrease of ~1/3 of primary production, and negative phytoplankton rates of change are associated with all salp locations. Particle export in salp waters is always higher, ranging 2- to 8- fold (average 5-fold), compared to non-salp locations, exporting up to 46% of primary production out of the euphotic zone. BCP efficiency increases from 5 to 28% in salp areas, which is among the highest recorded in the global ocean.

Molecular phylogeny of the spiny-surfaced species of the dinoflagellate Prorocentrum with the description of P. thermophilum sp. nov. and P. criophilum sp. nov. (Prorocentrales, Dinophyceae).

Spiny-surfaced species of Prorocentrum form harmful algal blooms, and its taxonomic identity is obscure due to the size and shape variability. Molecular phylogenies reveal two major clades: one for P. cordatum with sequences mainly retrieved as P. minimum, and the other for P. shikokuense with sequences also retrieved as P. dentatum and P. donghaiense. Several closely related clades still need to be characterized. Here, we provide nuclear SSU and LSU rRNA genes, and nuclear ITS region (ITS1-5.8S gene-ITS2) sequences of the strain CCMP3122 isolated from Florida (initially named P. donghaiense) and strains Prorocentrum sp. RCC6871-2 from the Ross Sea, Antarctica. We describe Prorocentrum thermophilum sp. nov. based on the strain CCMP3122, a species also distributed in the open waters of the Gulf of Mexico, New Zealand, and the Arabian Gulf; and Prorocentrum criophilum sp. nov. based on the strain RCC6872, which is distributed in the Antarctic Ocean and Arctic Sea. Prorocentrum thermophilum is roundish (~14 µm long, ~12 µm wide), with an inconspicuous anterior spine-like prolongation under light microscopy, valves with tiny, short knobs (5-7 per µm2 ), and several (<7) large trichocyst pores (~0.3 µm) in the right valve, as well as smaller pores (~0.15 µm). Prorocentrum criophilum is round in valve view (~11 µm long, 10 µm wide) and asymmetrically roundish in lateral view, the periflagellar area was not discernible under light microscopy, valves with very tiny, short knobs (6-10 per µm2 ), and at least 12 large pores in the right valve. Other potentially undescribed species of spiny-surfaced Prorocentrum are discussed.

Interpretable Classification of Tauopathies with a Convolutional Neural Network Pipeline Using Transfer Learning and Validation against Post-Mortem Clinical Cases of Alzheimer's Disease and Progressive Supranuclear Palsy.

Neurodegenerative diseases, tauopathies, constitute a serious global health problem. The etiology of these diseases is unclear and an increase in their incidence has been projected in the next 30 years. Therefore, the study of the molecular mechanisms that might stop these neurodegenerative processes is very relevant. Classification of neurodegenerative diseases using Machine and Deep Learning algorithms has been widely studied for medical imaging such as Magnetic Resonance Imaging. However, post-mortem immunofluorescence imaging studies of the brains of patients have not yet been used for this purpose. These studies may represent a valuable tool for monitoring aberrant chemical changes or pathological post-translational modifications of the Tau polypeptide. We propose a Convolutional Neural Network pipeline for the classification of Tau pathology of Alzheimer's disease and Progressive Supranuclear Palsy by analyzing post-mortem immunofluorescence images with different Tau biomarkers performed with models generated with the architecture ResNet-IFT using Transfer Learning. These models' outputs were interpreted with interpretability algorithms such as Guided Grad-CAM and Occlusion Analysis. To determine the best classifier, four different architectures were tested. We demonstrated that our design was able to classify diseases with an accuracy of 98.41% on average whilst providing an interpretation concerning the proper classification involving different structural patterns in the immunoreactivity of the Tau protein in NFTs present in the brains of patients with Progressive Supranuclear Palsy and Alzheimer's disease.

A Novel Automatic Quantification Protocol for Biomarkers of Tauopathies in the Hippocampus and Entorhinal Cortex of Post-Mortem Samples Using an Extended Semi-Siamese U-Net.

Efforts have been made to diagnose and predict the course of different neurodegenerative diseases through various imaging techniques. Particularly tauopathies, where the tau polypeptide is a key participant in molecular pathogenesis, have significantly increased their morbidity and mortality in the human population over the years. However, the standard approach to exploring the phenomenon of neurodegeneration in tauopathies has not been directed at understanding the molecular mechanism that causes the aberrant polymeric and fibrillar behavior of the tau protein, which forms neurofibrillary tangles that replace neuronal populations in the hippocampal and cortical regions. The main objective of this work is to implement a novel quantification protocol for different biomarkers based on pathological post-translational modifications undergone by tau in the brains of patients with tauopathies. The quantification protocol consists of an adaptation of the U-Net neural network architecture. We used the resulting segmentation masks for the quantification of combined fluorescent signals of the different molecular changes tau underwent in neurofibrillary tangles. The quantification considers the neurofibrillary tangles as an individual study structure separated from the rest of the quadrant present in the images. This allows us to detect unconventional interaction signals between the different biomarkers. Our algorithm provides information that will be fundamental to understanding the pathogenesis of dementias with another computational analysis approach in subsequent studies.

Motor Imagery Analysis from Extensive EEG Data Representations Using Convolutional Neural Networks.

Motor imagery is a complex mental task that represents muscular movement without the execution of muscular action, involving cognitive processes of motor planning and sensorimotor proprioception of the body. Since the mental task has similar behavior to that of the motor execution process, it can be used to create rehabilitation routines for patients with some motor skill impairment. However, due to the nature of this mental task, its execution is complicated. Hence, the classification of these signals in scenarios such as brain-computer interface systems tends to have a poor performance. In this work, we study in depth different forms of data representation of motor imagery EEG signals for distinct CNN-based models as well as novel EEG data representations including spectrograms and multidimensional raw data. With the aid of transfer learning, we achieve results up to 93% accuracy, exceeding the current state of the art. However, although these results are strong, they entail the use of high computational resources to generate the samples, since they are based on spectrograms. Thus, we searched further for alternative forms of EEG representations, based on 1D, 2D, and 3D variations of the raw data, leading to promising results for motor imagery classification that still exceed the state of the art. Hence, in this work, we focus on exploring alternative methods to process and improve the classification of motor imagery features with few preprocessing techniques.

Taming chlorophylls by early eukaryotes underpinned algal interactions and the diversification of the eukaryotes on the oxygenated Earth.

Extant eukaryote ecology is primarily sustained by oxygenic photosynthesis, in which chlorophylls play essential roles. The exceptional photosensitivity of chlorophylls allows them to harvest solar energy for photosynthesis, but on the other hand, they also generate cytotoxic reactive oxygen species. A risk of such phototoxicity of the chlorophyll must become particularly prominent upon dynamic cellular interactions that potentially disrupt the mechanisms that are designed to quench photoexcited chlorophylls in the phototrophic cells. Extensive examination of a wide variety of phagotrophic, parasitic, and phototrophic microeukaryotes demonstrates that a catabolic process that converts chlorophylls into nonphotosensitive 132,173-cyclopheophorbide enols (CPEs) is phylogenetically ubiquitous among extant eukaryotes. The accumulation of CPEs is identified in phagotrophic algivores belonging to virtually all major eukaryotic assemblages with the exception of Archaeplastida, in which no algivorous species have been reported. In addition, accumulation of CPEs is revealed to be common among phototrophic microeukaryotes (i.e., microalgae) along with dismantling of their secondary chloroplasts. Thus, we infer that CPE-accumulating chlorophyll catabolism (CACC) primarily evolved among algivorous microeukaryotes to detoxify chlorophylls in an early stage of their evolution. Subsequently, it also underpinned photosynthetic endosymbiosis by securing close interactions with photosynthetic machinery containing abundant chlorophylls, which led to the acquisition of secondary chloroplasts. Our results strongly suggest that CACC, which allowed the consumption of oxygenic primary producers, ultimately permitted the successful radiation of the eukaryotes throughout and after the late Proterozoic global oxygenation.

High contribution of Rhizaria (Radiolaria) to vertical export in the California Current Ecosystem revealed by DNA metabarcoding.

Passive sinking of particulate organic matter (POM) is the main mechanism through which the biological pump transports surface primary production to the ocean interior. However, the contribution and variability of different biological sources to vertical export is not fully understood. Here, we use DNA metabarcoding of the 18S rRNA gene and particle interceptor traps (PITs) to characterize the taxonomic composition of particles sinking out of the photic layer in the California Current Ecosystem (CCE), a productive system with high export potential. The PITs included formalin-fixed and 'live' traps to investigate eukaryotic communities involved in the export and remineralization of sinking particles. Sequences affiliated with Radiolaria dominated the eukaryotic assemblage in fixed traps (90%), with Dinophyta and Metazoa making minor contributions. The prominence of Radiolaria decreased drastically in live traps, possibly due to selective consumption by copepods, heterotrophic nanoflagellates, and phaeodarians that were heavily enriched in these traps. These patterns were consistent across the water masses surveyed extending from the coast to offshore, despite major differences in productivity and trophic structure of the epipelagic plankton community. Our findings identify Radiolaria as major actors in export fluxes in the CCE.

Analysis of the genomic basis of functional diversity in dinoflagellates using a transcriptome-based sequence similarity network.

Dinoflagellates are one of the most abundant and functionally diverse groups of eukaryotes. Despite an overall scarcity of genomic information for dinoflagellates, constantly emerging high-throughput sequencing resources can be used to characterize and compare these organisms. We assembled de novo and processed 46 dinoflagellate transcriptomes and used a sequence similarity network (SSN) to compare the underlying genomic basis of functional features within the group. This approach constitutes the most comprehensive picture to date of the genomic potential of dinoflagellates. A core-predicted proteome composed of 252 connected components (CCs) of putative conserved protein domains (pCDs) was identified. Of these, 206 were novel and 16 lacked any functional annotation in public databases. Integration of functional information in our network analyses allowed investigation of pCDs specifically associated with functional traits. With respect to toxicity, sequences homologous to those of proteins found in species with toxicity potential (e.g., sxtA4 and sxtG) were not specific to known toxin-producing species. Although not fully specific to symbiosis, the most represented functions associated with proteins involved in the symbiotic trait were related to membrane processes and ion transport. Overall, our SSN approach led to identification of 45,207 and 90,794 specific and constitutive pCDs of, respectively, the toxic and symbiotic species represented in our analyses. Of these, 56% and 57%, respectively (i.e., 25,393 and 52,193 pCDs), completely lacked annotation in public databases. This stresses the extent of our lack of knowledge, while emphasizing the potential of SSNs to identify candidate pCDs for further functional genomic characterization.

Specific Effect of Trace Metals on Marine Heterotrophic Microbial Activity and Diversity: Key Role of Iron and Zinc and Hydrocarbon-Degrading Bacteria.

Marine microbes are an important control on the biogeochemical cycling of trace metals, but simultaneously, these metals can control the growth of microorganisms and the cycling of major nutrients like C and N. However, studies on the response/limitation of microorganisms to trace metals have traditionally focused on the response of autotrophic phytoplankton to Fe fertilization. Few reports are available on the response of heterotrophic prokaryotes to Fe, and even less to other biogeochemically relevant metals. We performed the first study coupling dark incubations with next generation sequencing to specifically target the functional and phylogenetic response of heterotrophic prokaryotes to Fe enrichment. Furthermore, we also studied their response to Co, Mn, Ni, Zn, Cu (individually and mixed), using surface and deep samples from either coastal or open-ocean waters. Heterotrophic prokaryotic activity was stimulated by Fe in surface open-ocean, as well as in coastal, and deep open-ocean waters (where Zn also stimulated). The most susceptible populations to trace metals additions were uncultured bacteria (e.g., SAR324, SAR406, NS9, and DEV007). Interestingly, hydrocarbon-degrading bacteria (e.g., Thalassolituus, Marinobacter, and Oleibacter) benefited the most from metal addition across all waters (regions/depths) revealing a predominant role in the cycling of metals and organic matter in the ocean.

Biogeography and diversity of Collodaria (Radiolaria) in the global ocean.

Collodaria are heterotrophic marine protists that exist either as large colonies composed of hundreds of cells or as large solitary cells. All described species so far harbour intracellular microalgae as photosymbionts. Although recent environmental diversity surveys based on molecular methods demonstrated their consistently high contribution to planktonic communities and their worldwide occurrence, our understanding of their diversity and biogeography is still very limited. Here we estimated the 18S ribosomal DNA (rDNA) gene copies per collodarian cell for solitary (5770±1960 small subunit (SSU) rDNA copies) and colonial specimens (37 474±17 799 SSU rDNA copies, for each individual cell within a colony) using single-specimen quantitative PCR. We then investigated the environmental diversity of Collodaria within the photic zone through the metabarcoding survey from the Tara Oceans expedition and found that the two collodarian families Collosphaeridae and Sphaerozoidae contributed the most to the collodarian diversity and encompassed mostly cosmopolitan taxa. Although the biogeographical patterns were homogeneous within each biogeochemical biome considered, we observed that coastal biomes were consistently less diverse than oceanic biomes and were dominated by the Sphaerozoidae while the Collosphaeridae were dominant in the open oceans. The significant relationships with six environmental variables suggest that collodarian diversity is influenced by the trophic status of oceanic provinces and increased towards more oligotrophic regions.

Patterns of microbial community biomass, composition and HPLC diagnostic pigments in the Costa Rica upwelling dome.

We investigated biomass, size-structure, composition, depth distributions and spatial variability of the phytoplankton community in the Costa Rica Dome (CRD) in June-July 2010. Euphotic zone profiles were sampled daily during Lagrangian experiments in and out of the dome region, and the community was analyzed using a combination of digital epifluorescence microscopy, flow cytometry and HPLC pigments. The mean depth-integrated biomass of phytoplankton ranged 2-fold, from 1089 to 1858 mg C m-2 (mean ± SE = 1378 ± 112 mg C m-2), among 4 water parcels tracked for 4 days. Corresponding mean (±SE) integrated values for total chlorophyll a (Chl a) and the ratio of autotrophic carbon to Chl a were 24.1 ± 1.5 mg Chl a m-2 and 57.5 ± 3.4, respectively. Absolute and relative contributions of picophytoplankton (∼60%), Synechococcus (>33%) and Prochlorococcus (17%) to phytoplankton community biomass were highest in the central dome region, while >20 µm phytoplankton accounted for ≤10%, and diatoms <2%, of biomass in all areas. Nonetheless, autotrophic flagellates, dominated by dinoflagellates, exceeded biomass contributions of Synechococcus at all locations. Order-of-magnitude discrepancies in the relative contributions of diatoms (overestimated) and dinoflagellates (underestimated) based on diagnostic pigments relative to microscopy highlight potential significant biases associated with making community inferences from pigments.

Phytoplankton production and taxon-specific growth rates in the Costa Rica Dome.

During summer 2010, we investigated phytoplankton production and growth rates at 19 stations in the eastern tropical Pacific, where winds and strong opposing currents generate the Costa Rica Dome (CRD), an open-ocean upwelling feature. Primary production (14C-incorporation) and group-specific growth and net growth rates (two-treatment seawater dilution method) were estimated from samples incubated in situ at eight depths. Our cruise coincided with a mild El Niño event, and only weak upwelling was observed in the CRD. Nevertheless, the highest phytoplankton abundances were found near the dome center. However, mixed-layer growth rates were lowest in the dome center (∼0.5-0.9 day-1), but higher on the edge of the dome (∼0.9-1.0 day-1) and in adjacent coastal waters (0.9-1.3 day-1). We found good agreement between independent methods to estimate growth rates. Mixed-layer growth rates of Prochlorococcus and Synechococcus were largely balanced by mortality, whereas eukaryotic phytoplankton showed positive net growth (∼0.5-0.6 day-1), that is, growth available to support larger (mesozooplankton) consumer biomass. These are the first group-specific phytoplankton rate estimates in this region, and they demonstrate that integrated primary production is high, exceeding 1 g C m-2 day-1 on average, even during a period of reduced upwelling.

Phytoplankton growth and microzooplankton grazing dynamics across vertical environmental gradients determined by transplant in situ dilution experiments.

The Costa Rica Dome (CRD) represents a classic case of the bloom-forming capacity of small phytoplankton. Unlike other upwelling systems, autotrophic biomass in the CRD is dominated by picocyanobacteria and small eukaryotes that outcompete larger diatoms and reach extremely high biomass levels. We investigated responses of the subsurface phytoplankton community of the CRD to changes associated with vertical displacement of water masses, coupling in situ transplanted dilution experiments with flow cytometry and epifluorescence microscopy to assess group-specific dynamics. Growth rates of Synechococcus (SYN) and photosynthetic picoeukaryotes (PEUK) were positively correlated with light (Rpearson_SYN = 0.602 and Rpearson_PEUK = 0.588, P < 0.001). Growth rates of Prochlorococcus (PRO), likely affected by photoinhibition, were not light correlated (Rpearson_PRO = 0.101, P = 0.601). Overall, grazing and growth rates were closely coupled in all picophytoplankton groups (Rspearman_PRO = 0.572, Rspearman_SYN = 0.588, Rspearman_PEUK = 0.624), and net growth rates remained close to zero. Conversely, the abundance and biomass of larger phytoplankton, mainly diatoms, increased more than 10-fold in shallower transplant incubations indicating that, in addition to trace-metal chemistry, light also plays a significant role in controlling microphytoplankton populations in the CRD.

Phytoplankton production and grazing balances in the Costa Rica Dome.

We investigated phytoplankton production rates and grazing fates in the Costa Rica Dome (CRD) during summer 2010 based on dilution depth profiles analyzed by flow cytometry and pigments and mesozooplankton grazing assessed by gut fluorescence. Three community production estimates, from 14C uptake (1025 ± 113 mg C m-2 day-1) and from dilution experiments analyzed for total Chla (990 ± 106 mg C m-2 day-1) and flow cytometry populations (862 ± 71 mg C m-2 day-1), exceeded regional ship-based values by 2-3-fold. Picophytoplankton accounted for 56% of community biomass and 39% of production. Production profiles extended deeper for Prochlorococcus (PRO) and picoeukaryotes than for Synechococcus (SYN) and larger eukaryotes, but 93% of total production occurred above 40 m. Microzooplankton consumed all PRO and SYN growth and two-third of total production. Positive net growth of larger eukaryotes in the upper 40 m was balanced by independently measured consumption by mesozooplankton. Among larger eukaryotes, diatoms contributed ∼3% to production. On the basis of this analysis, the CRD region is characterized by high production and grazing turnover, comparable with or higher than estimates for the eastern equatorial Pacific. The region nonetheless displays characteristics atypical of high productivity, such as picophytoplankton dominance and suppressed diatom roles.

Improving fingerprint verification using minutiae triplets.

Improving fingerprint matching algorithms is an active and important research area in fingerprint recognition. Algorithms based on minutia triplets, an important matcher family, present some drawbacks that impact their accuracy, such as dependency to the order of minutiae in the feature, insensitivity to the reflection of minutiae triplets, and insensitivity to the directions of the minutiae relative to the sides of the triangle. To alleviate these drawbacks, we introduce in this paper a novel fingerprint matching algorithm, named M3gl. This algorithm contains three components: a new feature representation containing clockwise-arranged minutiae without a central minutia, a new similarity measure that shifts the triplets to find the best minutiae correspondence, and a global matching procedure that selects the alignment by maximizing the amount of global matching minutiae. To make M3gl faster, it includes some optimizations to discard non-matching minutia triplets without comparing the whole representation. In comparison with six verification algorithms, M3gl achieves the highest accuracy in the lowest matching time, using FVC2002 and FVC2004 databases.