Practical Fertilization Procedure and Embryonic Development of the New Zealand Geoduck Clam (Panopea Zelandica)

Copyright © Marine Biological Association of the United Kingdom 2016Cultivation of the geoduck Panopea zelandica (Quoy & Gaimard, 1835) requires knowledge on embryonic development to produce spat in hatcheries. This study investigated the development of P. zelandica embryos at 15°C and 35 ppt and the optimal sperm:egg ratios for fertilization under hatchery conditions. Panopea zelandica broodstock were induced to spawn by serotonin injection. Sperm and eggs were collected and fertilization was conducted at sperm:egg ratios of: 50:1, 100:1, 500:1, 1000:1 and 10,000:1 over 40 min. The optimal sperm:egg ratio was <500:1 and the normal embryo yield at 3 and 18 h post-fertilization (hpf) ranged from 83–96%. Panopea zelandica eggs (~80 μm diameter) developed the first and second polar bodies within 15–20 and 50–55 min post-fertilization, respectively. The blastula appeared at ~8 hpf, including the XR and XL cells and the presumptive shell field depression. Gastrulation occurred at 12–18 hpf with organic material apparent at the shell field depression. The mid-stage trochophore, which appeared at around 35 hpf had an apical plate with an apical tuft. The shell field spread to form the periostracum, which expanded and folded into right and left segments covering the late trochophore. The early D-stage veliger appeared at 45 hpf with the soft body being enclosed by two valves and the appearance of the velum. These observations will serve as the basis for future analyses of P. zelandica embryogenesis and for optimization of commercial production of D-veliger larvae

Nonsense-Mediated Decay Enables Intron Gain in Drosophila

Intron number varies considerably among genomes, but despite their fundamental importance, the mutational mechanisms and evolutionary processes underlying the expansion of intron number remain unknown. Here we show that Drosophila, in contrast to most eukaryotic lineages, is still undergoing a dramatic rate of intron gain. These novel introns carry significantly weaker splice sites that may impede their identification by the spliceosome. Novel introns are more likely to encode a premature termination codon (PTC), indicating that nonsense-mediated decay (NMD) functions as a backup for weak splicing of new introns. Our data suggest that new introns originate when genomic insertions with weak splice sites are hidden from selection by NMD. This mechanism reduces the sequence requirement imposed on novel introns and implies that the capacity of the spliceosome to recognize weak splice sites was a prerequisite for intron gain during eukaryotic evolution

Alkalizing Reactions Streamline Cellular Metabolism in Acidogenic Microorganisms

An understanding of the integrated relationships among the principal cellular functions that govern the bioenergetic reactions of an organism is necessary to determine how cells remain viable and optimise their fitness in the environment. Urease is a complex enzyme that catalyzes the hydrolysis of urea to ammonia and carbonic acid. While the induction of urease activity by several microorganisms has been predominantly considered a stress-response that is initiated to generate a nitrogen source in response to a low environmental pH, here we demonstrate a new role of urease in the optimisation of cellular bioenergetics. We show that urea hydrolysis increases the catabolic efficiency of Streptococcus thermophilus, a lactic acid bacterium that is widely used in the industrial manufacture of dairy products. By modulating the intracellular pH and thereby increasing the activity of β-galactosidase, glycolytic enzymes and lactate dehydrogenase, urease increases the overall change in enthalpy generated by the bioenergetic reactions. A cooperative altruistic behaviour of urease-positive microorganisms on the urease-negative microorganisms within the same environment was also observed. The physiological role of a single enzymatic activity demonstrates a novel and unexpected view of the non-transcriptional regulatory mechanisms that govern the bioenergetics of a bacterial cell, highlighting a new role for cytosol-alkalizing biochemical pathways in acidogenic microorganisms

Phylogenetic Distribution of Intron Positions in Alpha-Amylase Genes of Bilateria Suggests Numerous Gains and Losses

Most eukaryotes have at least some genes interrupted by introns. While it is well accepted that introns were already present at moderate density in the last eukaryote common ancestor, the conspicuous diversity of intron density among genomes suggests a complex evolutionary history, with marked differences between phyla. The question of the rates of intron gains and loss in the course of evolution and factors influencing them remains controversial. We have investigated a single gene family, alpha-amylase, in 55 species covering a variety of animal phyla. Comparison of intron positions across phyla suggests a complex history, with a likely ancestral intronless gene undergoing frequent intron loss and gain, leading to extant intron/exon structures that are highly variable, even among species from the same phylum. Because introns are known to play no regulatory role in this gene and there is no alternative splicing, the structural differences may be interpreted more easily: intron positions, sizes, losses or gains may be more likely related to factors linked to splicing mechanisms and requirements, and to recognition of introns and exons, or to more extrinsic factors, such as life cycle and population size. We have shown that intron losses outnumbered gains in recent periods, but that “resets” of intron positions occurred at the origin of several phyla, including vertebrates. Rates of gain and loss appear to be positively correlated. No phase preference was found. We also found evidence for parallel gains and for intron sliding. Presence of introns at given positions was correlated to a strong protosplice consensus sequence AG/G, which was much weaker in the absence of intron. In contrast, recent intron insertions were not associated with a specific sequence. In animal Amy genes, population size and generation time seem to have played only minor roles in shaping gene structures

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

The aquaculture supply chain in the time of covid-19 pandemic: vulnerability, resilience, solutions and priorities at the global scale

The COVID-19 global pandemic has had severe, unpredictable and synchronous impacts on all levels of perishable food supply chains (PFSC), across multiple sectors and spatial scales. Aquaculture plays a vital and rapidly expanding role in food security, in some cases overtaking wild caught fisheries in the production of high-quality animal protein in this PFSC. We performed a rapid global assessment to evaluate the effects of the COVID-19 pandemic and related emerging control measures on the aquaculture supply chain. Socio-economic effects of the pandemic were analysed by surveying the perceptions of stakeholders, who were asked to describe potential supply-side disruption, vulnerabilities and resilience patterns along the production pipeline with four main supply chain components: a) hatchery, b) production/processing, c) distribution/logistics and d) market. We also assessed different farming strategies, comparing land- vs. sea-based systems; extensive vs. intensive methods; and with and without integrated multi-trophic aquaculture, IMTA. In addition to evaluating levels and sources of economic distress, interviewees were asked to identify mitigation solutions adopted at local / internal (i.e., farm-site) scales, and to express their preference on national / external scale mitigation measures among a set of a priori options. Survey responses identified the potential causes of disruption, ripple effects, sources of food insecurity, and socio-economic conflicts. They also pointed to various levels of mitigation strategies. The collated evidence represents a first baseline useful to address future disaster-driven responses, to reinforce the resilience of the sector and to facilitate the design reconstruction plans and mitigation measures, such as financial aid strategies.publishe

The synergistic impacts of anthropogenic stressors and COVID-19 on aquaculture: a current global perspective

The rapid, global spread of COVID-19, and the measures intended to limit or slow its propagation, are having major impacts on diverse sectors of society. Notably, these impacts are occurring in the context of other anthropogenic-driven threats including global climate change. Both anthropogenic stressors and the COVID-19 pandemic represent significant economic challenges to aquaculture systems across the globe, threatening the supply chain of one of the most important sources of animal protein, with potential disproportionate impacts on vulnerable communities. A web survey was conducted in 47 countries in the midst of the COVID-19 pandemic to assess how aquaculture activities have been affected by the pandemic, and to explore how these impacts compare to those from climate change. A positive correlation between the effects of the two categories of drivers was detected, but analysis suggests that the pandemic and the anthropogenic stressors affect different parts of the supply chain. The immediate measurable reported losses varied with aquaculture typology (land vs. marine, and intensive vs. extensive). A comparably lower impact on farmers reporting the use of integrated multitrophic aquaculture (IMTA) methods suggests that IMTA might enhance resilience to multiple stressors by providing different market options under the COVID-19 pandemic. Results emphasize the importance of assessing detrimental effects of COVID-19 under a multiple stressor lens, focusing on areas that have already locally experienced economic loss due to anthropogenic stressors in the last decade. Holistic policies that simultaneously address other ongoing anthropogenic stressors, rather than focusing solely on the acute impacts of COVID-19, are needed to maximize the long-term resilience of the aquaculture sector.publishe

A proteomic survival predictor for COVID-19 patients in intensive care

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care

Displayed correlation between gene expression profiles and submicroscopic alterations in response to cetuximab, gefitinib and EGF in human colon cancer cell lines

Background: EGFR is frequently overexpressed in colon cancer. We characterized HT-29 and Caco-2, human colon cancer cell lines, untreated and treated with cetuximab or gefitinib alone and in combination with EGF. Methods: Cell growth was determined using a variation on the MTT assay. Cell-cycle analysis was conducted by flow cytometry. Immunohistochemistry was performed to evaluate EGFR expression and scanning electron microscopy (SEM) evidenced the ultrastructural morphology. Gene expression profiling was performed using hybridization of the microarray Ocimum Pan Human 40 K array A. Results: Caco-2 and HT-29 were respectively 66.25 and 59.24 % in G0/G1. They maintained this level of cell cycle distribution after treatment, suggesting a predominantly differentiated state. Treatment of Caco-2 with EGF or the two EGFR inhibitors produced a significant reduction in their viability. SEM clearly showed morphological cellular transformations in the direction of cellular death in both cell lines treated with EGFR inhibitors. HT-29 and Caco-2 displayed an important reduction of the microvilli (which also lose their erect position in Caco-2), possibly invalidating microvilli absorption function. HT-29 treated with cetuximab lost their boundary contacts and showed filipodi; when treated with gefitinib, they showed some vesicles: generally membrane reshaping is evident. Both cell lines showed a similar behavior in terms of on/off switched genes upon treatment with cetuximab. The gefitinib global gene expression pattern was different for the 2 cell lines; gefitinib treatment induced more changes, but directly correlated with EGF treatment. In cetuximab or gefitinib plus EGF treatments there was possible summation of the morphological effects: cells seemed more weakly affected by the transformation towards apoptosis. The genes appeared to be less stimulated than for single drug cases. Conclusion: This is the first study to have systematically investigated the effect of cetuximab or gefitinib, alone and in combination with EGF, on human colon cancer cell lines. The EGFR inhibitors have a weaker effect in the presence of EGF that binds EGFR. Cetuximab treatment showed an expression pattern that inversely correlates with EGF treatment. We found interesting cytomorphological features closely relating to gene expression profile. Both drugs have an effect on differentiation towards cellular death

A time-resolved proteomic and prognostic map of COVID-19.

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease