Editorial: Roles and mechanisms of parasitism in aquatic microbial communities

International audienc

Water-seeking behavior in worm-infected crickets and reversibility of parasitic manipulation

One of the most fascinating examples of parasite-induced host manipulation is that of hairworms, first, because they induce a spectacular "suicide” water-seeking behavior in their terrestrial insect hosts and, second, because the emergence of the parasite is not lethal per se for the host that can live several months following parasite release. The mechanisms hairworms use to increase the encounter rate between their host and water remain, however, poorly understood. Considering the selective landscape in which nematomorph manipulation has evolved as well as previously obtained proteomics data, we predicted that crickets harboring mature hairworms would display a modified behavioral response to light. Since following parasite emergence in water, the cricket host and parasitic worm do not interact physiologically anymore, we also predicted that the host would recover from the modified behaviors. We examined the effect of hairworm infection on different behavioral responses of the host when stimulated by light to record responses from uninfected, infected, and ex-infected crickets. We showed that hairworm infection fundamentally modifies cricket behavior by inducing directed responses to light, a condition from which they mostly recover once the parasite is released. This study supports the idea that host manipulation by parasites is subtle, complex, and multidimensiona

New Prospects for Research on Manipulation of Insect Vectors by Pathogens

International audienc

Comparison of Iberian honey bee colony variables continuously monitored with thermo-hygro-buttons and electronic scales set up in two latitudinal extremes of Portugal

Honey bee colony data collected continuously together with climate data are of great importance because they provide the opportunity to understand colony phenology. Continuous monitoring of honey bee colonies initiated long time ago with Gates (1914) and Hambleton (1925), when they assessed weather effects on hive weight using mechanical scales. Currently, the study of colony dynamics has been intensified with development of new technologies such as electronic scales, hygro-buttons, thermo-buttons, and computer-assisted digital image analysis of brood combs. Studies of colony dynamics are of great interest in Portugal because of large climatic (and flora) differences between the two latitudinal extremes and because of distinct genetic backgrounds of the native subspecies, Apis mellifera iberiensis (Pinto et al. 2013). In this study we will compare the temporal dynamics of colony weight and nest temperature and humidity of 12 colonies, which have been continuously monitored since July of 2015 with electronic scales and thermo-hygro-buttons, set up in apiaries located in two latitudinal extremes of Portugal. These colony variables will be correlated with climatic data (temperature, humidity, wind speed, and rain) obtained from automatic weather stations installed in the two apiaries. This research is funded through the 2013-2014 BiodivERsA/FACCE-JPI Joint call for research proposals, with the national funders FCT (Portugal), CNRS (France), and MEC (Spain).info:eu-repo/semantics/publishedVersio

Projeto BEEHOPE: conservação da abelha ibérica (Apis mellifera iberiensis) em Portugal

O projeto BEEHOPE, com o título original “Honeybee conservation centres in western Europe - an innovative strategy using sustainable beekeeping to reduce honeybee decline”, foi aprovado no âmbito do 5º concurso transnacional (2013-2014) BiodivErsA/FACCE-JPI na área da biodiversidade. O consórcio internacional que integra o BEEHOPE é constituído por cinco instituições oriundas de França (CNRS/Université de Versailles, CNRS/Université Blaise Pascal, e CNRS/Centre d'Etudes Biologiques de Chizé), Espanha (Universidad del País Vasco) e Portugal (Centro de Investigação de Montanha, Instituto Politécnico de Bragança). Num cenário de ameaças crescentes à integridade genética das subespécies de abelhas nativas da Europa, o objectivo último do BEEHOPE é proteger o fundo genético das populações da linhagem M (A. m. iberiensis e A. m. mellifera) através do estabelecimento de apiários de conservação ao longo de um gradiente que vai desde o Norte de França até ao Sul de Portugal. Estes apiários de conservação terão como missão: (i) servir de base à caraterização da diversidade genética e eco-etológica das abelhas da linhagem da Europa Ocidental (M), (ii) preservar a diversidade genética dessas populações, (iii) constituir uma reserva de diversidade para a indústria apícola e apicultores, (iv) estudar o impacto da abelha domesticada na manutenção da diversidade florística local, e (v) servir de base à utilização da abelha como um bio-coletor e como bio-indicador da qualidade ambiental. Nesta comunicação apresentar-se-ão as atividades desenvolvidas e os primeiros resultados genéticos e eco-etológicos obtidos nos dois apiários Portugueses (Bragança e Algarve) que fazem parte da rede de centros de conservação do BEEHOPE.info:eu-repo/semantics/publishedVersio

A study of local adaptation in the Iberian honeybee (Apis mellifera iberiensis) using a reciprocal translocation experiment

In Europe, several translocation experiments suggested that native populations of Apis mellifera are adapted to local climate and flora. However, so far, no study has been conducted on the Iberian honeybee, Apis mellifera iberiensis. The goal of this study was to assess the existence of genotype-environment interaction (GEI), and consequently local adaptation, in the Iberian honeybee. In 2015 two apiaries were set up, each one with 36 colonies (18 of the origin Bragança and 18 of the origin Vila do Bispo), in two latitudinal extremes of Portugal: Bragança (north) and Vila do Bispo (south). Several traits of the 36 colonies were measured for almost 2 years, including: number of brood and pollen cells, honey yield, survival, and Varroa destructor infestation. The analyses were performed using t-Student and Mann-Whitney tests to compare those traits between the two origins in the same apiary and the same origin between the two apiaries. The survival analysis was performed using the Cox proportional hazard model in R. Colonies of the southern origin Vila do Bispo showed a tendency to collect more pollen and consequently they produced a higher number of brood cells, had a higher varroa infestation level and a lower survival rate than colonies of the origin Bragança in both locations. Honey yield was the only trait that showed existence of GEI, and therefore local adaptation, since the local honeybees had a higher honey production in their apiary of origin. Additionally, the differences between the two origins were sharper in more favourable environments where the honeybees can better express their genetic potential. Our findings highlight the importance of protecting local honeybee diversity in a period of increasing selection pressures such as climate change, agricultural land overuse and novel pathogens and parasites.Thisresearchwas funded through the 2013-2014~'BiodivERsA/FACCE-JPI Joint call for research proposals, with the national funders FCT(Portugal), CNRS (France), and MEC(Spain).info:eu-repo/semantics/publishedVersio

Analysis of Generalized Grover's Quantum Search Algorithms Using Recursion Equations

The recursion equation analysis of Grover's quantum search algorithm presented by Biham et al. [PRA 60, 2742 (1999)] is generalized. It is applied to the large class of Grover's type algorithms in which the Hadamard transform is replaced by any other unitary transformation and the phase inversion is replaced by a rotation by an arbitrary angle. The time evolution of the amplitudes of the marked and unmarked states, for any initial complex amplitude distribution is expressed using first order linear difference equations. These equations are solved exactly. The solution provides the number of iterations T after which the probability of finding a marked state upon measurement is the highest, as well as the value of this probability, P_max. Both T and P_max are found to depend on the averages and variances of the initial amplitude distributions of the marked and unmarked states, but not on higher moments.Comment: 8 pages, no figures. To appear in Phys. Rev.

Expression of the SmB′ splicing protein in rodent cells capable of following an alternative RNA splicing pathway

AbstractThe expression of the SmB and SmB′ spliceosome proteins in a variety of cell types and tissues has been investigated. Although SmB is found in all cells studied, the SmB′ protein is found only in a small number of rodent cell types. The presence of this protein is correlated with the ability to utilize an alternative pathway of RNA splicing which is not available in most cell types. This is the first demonstration of tissue specific expression of a protein component of the spliceosome and suggests a role for SmB′ in the regulation of some cases of alternative RNA splicing

Automatic detection and classification of honey bee comb cells using deep learning

In a scenario of worldwide honey bee decline, assessing colony strength is becoming increasingly important for sustainable beekeeping. Temporal counts of number of comb cells with brood and food reserves offers researchers data for multiple applications, such as modelling colony dynamics, and beekeepers information on colony strength, an indicator of colony health and honey yield. Counting cells manually in comb images is labour intensive, tedious, and prone to error. Herein, we developed a free software, named DeepBee©, capable of automatically detecting cells in comb images and classifying their contents into seven classes. By distinguishing cells occupied by eggs, larvae, capped brood, pollen, nectar, honey, and other, DeepBee© allows an unprecedented level of accuracy in cell classification. Using Circle Hough Transform and the semantic segmentation technique, we obtained a cell detection rate of 98.7%, which is 16.2% higher than the best result found in the literature. For classification of comb cells, we trained and evaluated thirteen different convolutional neural network (CNN) architectures, including: DenseNet (121, 169 and 201); InceptionResNetV2; InceptionV3; MobileNet; MobileNetV2; NasNet; NasNetMobile; ResNet50; VGG (16 and 19) and Xception. MobileNet revealed to be the best compromise between training cost, with ~9 s for processing all cells in a comb image, and accuracy, with an F1-Score of 94.3%. We show the technical details to build a complete pipeline for classifying and counting comb cells and we made the CNN models, source code, and datasets publicly available. With this effort, we hope to have expanded the frontier of apicultural precision analysis by providing a tool with high performance and source codes to foster improvement by third parties (https://github.com/AvsThiago/DeepBeesource).This research was developed in the framework of the project “BeeHope - Honeybee conservation centers in Western Europe: an innovative strategy using sustainable beekeeping to reduce honeybee decline”, funded through the 2013-2014 BiodivERsA/FACCE-JPI Joint call for research proposals, with the national funders FCT (Portugal), CNRS (France), and MEC (Spain).info:eu-repo/semantics/publishedVersio