Genetic analysis of immunological traits in tilapia

The immunological response to handling stress of four tilapia species is evaluated.Polymorphism is examined in genes known to influence immune response in fish

DNA BARCODING OF FISH SPECIES FROM THE MEDITERRANEAN COAST OF ISRAEL

Accurately-classified genomic data in the Barcode of Life Data System (BOLD) database is vital to the protection and conservation of marine biodiversity in the Mediterranean Sea. The taxonomic classifications of 468 fish of 50 Mediterranean species were analyzed using the BOLD Identifier tool for variation in the cytochrome oxidase subunit I (COI) mitochondrial gene. Within species, nucleotide maximum composite likelihood was low with a mean of 0.0044±0.0008. Three presumptive species had significantly higher values e.g., Arnoglossus spp. (0.07), Torquigener flavimaculosus (0.013) and Boops boops (0.028). However, samples of Arnoglossus species were sub-classified into two groups that were finally identified as two different species e.g., Arnoglossus laterna and Arnoglossus thori. For the different species, BLAST searches against the BOLD database using our DNA barcoding data as the query sequences designated the most similar targets into groups. For each analyzed species, the similarity of the first and second threshold groups ranged from 95 to 99% and from 83 to 98%, respectively. Sequence based classification for the first threshold group was concordant with morphology-based identification. However, for 34 analyzed species (68%) overlaps of species between the two threshold groups hampered classification. Tree-based phylogeny analysis detected more than one cluster in the first threshold group for 22 out of 50 species, representing genetic subgroups and geographic origins. There was a tendency for higher conservation and lower number of clusters in the Lessepsian (Red Sea) migrant versus indigenous species

Stochastic Resonance of Ensemble Neurons for Transient Spike Trains: A Wavelet Analysis

By using the wavelet transformation (WT), we have analyzed the response of an ensemble of $N$ (=1, 10, 100 and 500) Hodgkin-Huxley (HH) neurons to {\it transient} $M$-pulse spike trains ($M=1-3$) with independent Gaussian noises. The cross-correlation between the input and output signals is expressed in terms of the WT expansion coefficients. The signal-to-noise ratio (SNR) is evaluated by using the {\it denoising} method within the WT, by which the noise contribution is extracted from output signals. Although the response of a single (N=1) neuron to sub-threshold transient signals with noises is quite unreliable, the transmission fidelity assessed by the cross-correlation and SNR is shown to be much improved by increasing the value of $N$: a population of neurons play an indispensable role in the stochastic resonance (SR) for transient spike inputs. It is also shown that in a large-scale ensemble, the transmission fidelity for supra-threshold transient spikes is not significantly degraded by a weak noise which is responsible to SR for sub-threshold inputs.Comment: 20 pages, 4 figure

Comparative genomics in cyprinids: common carp ESTs help the annotation of the zebrafish genome

BACKGROUND: Automatic annotation of sequenced eukaryotic genomes integrates a combination of methodologies such as ab-initio methods and alignment of homologous genes and/or proteins. For example, annotation of the zebrafish genome within Ensembl relies heavily on available cDNA and protein sequences from two distantly related fish species and other vertebrates that have diverged several hundred million years ago. The scarcity of genomic information from other cyprinids provides the impetus to leverage EST collections to understand gene structures in this diverse teleost group. RESULTS: We have generated 6,050 ESTs from the differentiating testis of common carp (Cyprinus carpio) and clustered them with 9,303 non-gonadal ESTs from CarpBase as well as 1,317 ESTs and 652 common carp mRNAs from GenBank. Over 28% of the resulting 8,663 unique transcripts are exclusively testis-derived ESTs. Moreover, 974 of these transcripts did not match any sequence in the zebrafish or fathead minnow EST collection. A total of 1,843 unique common carp sequences could be stringently mapped to the zebrafish genome (version 5), of which 1,752 matched coding sequences of zebrafish genes with or without potential splice variants. We show that 91 common carp transcripts map to intergenic and intronic regions on the zebrafish genome assembly and regions annotated with non-teleost sequences. Interestingly, an additional 42 common carp transcripts indicate the potential presence of new splicing variants not found in zebrafish databases so far. The fact that common carp transcripts help the identification or confirmation of these coding regions in zebrafish exemplifies the usefulness of sequences from closely related species for the annotation of model genomes. We also demonstrate that 5' UTR sequences of common carp and zebrafish orthologs share a significant level of similarity based on preservation of motif arrangements for as many as 10 ab-initio motifs. CONCLUSION: Our data show that there is sufficient homology between the transcribed sequences of common carp and zebrafish to warrant an even deeper cyprinid transcriptome comparison. On the other hand, the comparative analysis illustrates the value in utilizing partially sequenced transcriptomes to understand gene structure in this diverse teleost group. We highlight the need for integrated resources to leverage the wealth of fragmented genomic data

Viruses affect picocyanobacterial abundance and biogeography in the North Pacific Ocean

The photosynthetic picocyanobacteria Prochlorococcus and Synechococcus are models for dissecting how ecological niches are defined by environmental conditions, but how interactions with bacteriophages affect picocyanobacterial biogeography in open ocean biomes has rarely been assessed. We applied single-virus and single-cell infection approaches to quantify cyanophage abundance and infected picocyanobacteria in 87 surface water samples from five transects that traversed approximately 2,200 km in the North Pacific Ocean on three cruises, with a duration of 2–4 weeks, between 2015 and 2017. We detected a 550-km-wide hotspot of cyanophages and virus-infected picocyanobacteria in the transition zone between the North Pacific Subtropical and Subpolar gyres that was present in each transect. Notably, the hotspot occurred at a consistent temperature and displayed distinct cyanophage-lineage composition on all transects. On two of these transects, the levels of infection in the hotspot were estimated to be sufficient to substantially limit the geographical range of Prochlorococcus. Coincident with the detection of high levels of virally infected picocyanobacteria, we measured an increase of 10–100-fold in the Synechococcus populations in samples that are usually dominated by Prochlorococcus. We developed a multiple regression model of cyanophages, temperature and chlorophyll concentrations that inferred that the hotspot extended across the North Pacific Ocean, creating a biological boundary between gyres, with the potential to release organic matter comparable to that of the sevenfold-larger North Pacific Subtropical Gyre. Our results highlight the probable impact of viruses on large-scale phytoplankton biogeography and biogeochemistry in distinct regions of the oceans

Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks

Functional connectivity of in vitro neuronal networks was estimated by applying different statistical algorithms on data collected by Micro-Electrode Arrays (MEAs). First we tested these “connectivity methods” on neuronal network models at an increasing level of complexity and evaluated the performance in terms of ROC (Receiver Operating Characteristic) and PPC (Positive Precision Curve), a new defined complementary method specifically developed for functional links identification. Then, the algorithms better estimated the actual connectivity of the network models, were used to extract functional connectivity from cultured cortical networks coupled to MEAs. Among the proposed approaches, Transfer Entropy and Joint-Entropy showed the best results suggesting those methods as good candidates to extract functional links in actual neuronal networks from multi-site recordings

An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes

For the analysis of neuronal cooperativity, simultaneously recorded extracellular signals from neighboring neurons need to be sorted reliably by a spike sorting method. Many algorithms have been developed to this end, however, to date, none of them manages to fulfill a set of demanding requirements. In particular, it is desirable to have an algorithm that operates online, detects and classifies overlapping spikes in real time, and that adapts to non-stationary data. Here, we present a combined spike detection and classification algorithm, which explicitly addresses these issues. Our approach makes use of linear filters to find a new representation of the data and to optimally enhance the signal-to-noise ratio. We introduce a method called “Deconfusion” which de-correlates the filter outputs and provides source separation. Finally, a set of well-defined thresholds is applied and leads to simultaneous spike detection and spike classification. By incorporating a direct feedback, the algorithm adapts to non-stationary data and is, therefore, well suited for acute recordings. We evaluate our method on simulated and experimental data, including simultaneous intra/extra-cellular recordings made in slices of a rat cortex and recordings from the prefrontal cortex of awake behaving macaques. We compare the results to existing spike detection as well as spike sorting methods. We conclude that our algorithm meets all of the mentioned requirements and outperforms other methods under realistic signal-to-noise ratios and in the presence of overlapping spikes

Innate Synchronous Oscillations in Freely-Organized Small Neuronal Circuits

BACKGROUND: Information processing in neuronal networks relies on the network's ability to generate temporal patterns of action potentials. Although the nature of neuronal network activity has been intensively investigated in the past several decades at the individual neuron level, the underlying principles of the collective network activity, such as the synchronization and coordination between neurons, are largely unknown. Here we focus on isolated neuronal clusters in culture and address the following simple, yet fundamental questions: What is the minimal number of cells needed to exhibit collective dynamics? What are the internal temporal characteristics of such dynamics and how do the temporal features of network activity alternate upon crossover from minimal networks to large networks? METHODOLOGY/PRINCIPAL FINDINGS: We used network engineering techniques to induce self-organization of cultured networks into neuronal clusters of different sizes. We found that small clusters made of as few as 40 cells already exhibit spontaneous collective events characterized by innate synchronous network oscillations in the range of 25 to 100 Hz. The oscillation frequency of each network appeared to be independent of cluster size. The duration and rate of the network events scale with cluster size but converge to that of large uniform networks. Finally, the investigation of two coupled clusters revealed clear activity propagation with master/slave asymmetry. CONCLUSIONS/SIGNIFICANCE: The nature of the activity patterns observed in small networks, namely the consistent emergence of similar activity across networks of different size and morphology, suggests that neuronal clusters self-regulate their activity to sustain network bursts with internal oscillatory features. We therefore suggest that clusters of as few as tens of cells can serve as a minimal but sufficient functional network, capable of sustaining oscillatory activity. Interestingly, the frequencies of these oscillations are similar those observed in vivo