Mytilus edulis haemocytes variability : technique, individual and environment

The widely distributed marine bivalve Mytilus edulis is used as a sentinel organism for ecological and toxicological assessments. As a filter feeder, it has the potential to bio-accumulate pollutants. It has been assumed that the cell concentration and cell type ratio of its circulating immune cells, haemocytes, could become complementary sub-lethal indicators of toxicology. These two parameters are respectively referred to as total haemocyte count (THC) and differential cell count (DCC). This study examines these commonly used methods, quantifies their limitations, and develops alternative techniques. The circulating immune cells are investigated to assess their fluctuations. Finally, impacts of environmental challenges on the circulating haemocytes are examined. Despite its importance in the field of Mytilus edulis immunology, THC evaluation is present in only 20% of publications in this field, and DCC in 10%. Ultimately, only 9% of papers consider both THC and DCC before further analyses. The remaining studies disregard THC and DDC, or regard these parameters as being constant and homogenous in M. edulis populations. This study initially quantifies the systematic error induced by sampling, and suggests improvements. For example, a systematic error of 26% is attributed to the use of low precision syringes, and can be reduced with use of higher precision sampling equipment. While the systematic errors in visual count and image analysis of THC and DCC evaluations are equivalent, the computerised methods allow the throughput of larger data sets, reduce workload, and avoid tedious eye counts. Flow cytometry was found to be the most accurate method in THC and DCC evaluation. Furthermore, repeated bleedings influence DCC, triggering the decrease of circulating eosinophils (up to 20%) and the increase of hyaline cells (up to 30%). To mitigate this reaction to sampling, a maximum volume of 50μl using a permanent cannulation is recommended. However, even with improved methods reducing systematic error by half, this study still reports variations as high as 20-fold in the haemocyte concentration in populations of healthy individuals. In addition, over a 2-hour period in a single cannulated individual, fluctuation of the DDC is observed to be as high as 30% for eosinophils, 10% for hyaline cells, and 20% for basophils. These measured variations are explained by haemocyte reservoirs in the tissues. Eosinophils are found in large numbers in epithelial association in the gills, guts and in the mantle, where their numbers have been evaluated at 3x10 7 As a case study, Mytilus edulis challenged with barium sulphate smothering, used by the oil industry in drilling muds, shows gill damage and their subsequent infiltration by eosinophils. In bacterial outbreak, basophilic cells are observed to infiltrate the tissue surrounding the stomach and eosinophils are depleted from the epithelium of the digestive tissues. THC is 10-fold lower than in healthy organisms and eosinophils are depleted from the haemolymph. cells. In conclusion, the THC and DDC methods are shown to be unreliable despite the use of more accurate methods. In addition, Mytilus edulis circulating haemocytes present large variations and the assumption of their homogeneity in terms of time, individuals or methods used cannot be made. These results challenge the conclusions of many past publications regarding causalities established between potential stresses and measured effects. Further research is necessary to understand the mechanisms regulating the circulating haemocytes, the inter-individual variability and to improve investigation methods

Data gaps and opportunities for comparative and conservation biology

Biodiversity loss is a major challenge. Over the past century, the average rate of vertebrate extinction has been about 100-fold higher than the estimated background rate and population declines continue to increase globally. Birth and death rates determine the pace of population increase or decline, thus driving the expansion or extinction of a species. Design of species conservation policies hence depends on demographic data (e.g., for extinction risk assessments or estimation of harvesting quotas). However, an overview of the accessible data, even for better known taxa, is lacking. Here, we present the Demographic Species Knowledge Index, which classifies the available information for 32,144 (97%) of extant described mammals, birds, reptiles, and amphibians. We show that only 1.3% of the tetrapod species have comprehensive information on birth and death rates. We found no demographic measures, not even crude ones such as maximum life span or typical litter/clutch size, for 65% of threatened tetrapods. More field studies are needed; however, some progress can be made by digitalizing existing knowledge, by imputing data from related species with similar life histories, and by using information from captive populations. We show that data from zoos and aquariums in the Species360 network can significantly improve knowledge for an almost eightfold gain. Assessing the landscape of limited demographic knowledge is essential to prioritize ways to fill data gaps. Such information is urgently needed to implement management strategies to conserve at-risk taxa and to discover new unifying concepts and evolutionary relationships across thousands of tetrapod species

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Leslie matrix strain MG1655Inlag

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain MG1655Inlag. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class

Data from: Demographic variability and heterogeneity among individuals within and among clonal bacteria strains

Identifying what drives individual heterogeneity has been of long interest to ecologists, evolutionary biologists and biodemographers, because only such identification provides deeper understanding of ecological and evolutionary population dynamics. In natural populations one is challenged to accurately decompose the drivers of heterogeneity among individuals as genetically fixed or selectively neutral. Rather than working on wild populations we present here data from a simple bacterial system in the lab, Escherichia coli. Our system, based on cutting-edge microfluidic techniques, provides high control over the genotype and the environment. It therefore allows to unambiguously decompose and quantify fixed genetic variability and dynamic stochastic variability among individuals. We show that within clonal individual variability (dynamic heterogeneity) in lifespan and lifetime reproduction is dominating at about 82–88%, over the 12–18% genetically (adaptive fixed) driven differences. The genetic differences among the clonal strains still lead to substantial variability in population growth rates (fitness), but, as well understood based on foundational work in population genetics, the within strain neutral variability slows adaptive change, by enhancing genetic drift, and lowering overall population growth. We also revealed a surprising diversity in senescence patterns among the clonal strains, which indicates diverse underlying cell-intrinsic processes that shape these demographic patterns. Such diversity is surprising since all cells belong to the same bacteria species, E. coli, and still exhibit patterns such as classical senescence, non-senescence, or negative senescence. We end by discussing whether similar levels of non-genetic variability might be detected in other systems and close by stating the open questions how such heterogeneity is maintained, how it has evolved, and whether it is adaptive

Leslie matrix strain BW25113

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain BW25113. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class

Leslie matrix strain MG1655

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain MG1655. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class

Leslie matrix strain IAI1

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain IAI1. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class