Anarchy in the UK: Detailed genetic analysis of worker reproduction in a naturally occurring British anarchistic honeybee, Apis mellifera, colony using DNA microsatellites

Anarchistic behaviour is a very rare phenotype of honeybee colonies. In an anarchistic colony, many workers’ sons are reared in the presence of the queen. Anarchy has previously been described in only two Australian colonies. Here we report on a first detailed genetic analysis of a British anarchistic colony. Male pupae were present in great abundance above the queen excluder, which was clearly indicative of extensive worker reproduction and is the hallmark of anarchy. Seventeen microsatellite loci were used to analyse these male pupae, allowing us to address whether all the males were indeed workers’ sons, and how many worker patrilines and individual workers produced them. In the sample, 95 of 96 of the males were definitely workers’ sons. Given that ≈ 1% of workers’ sons were genetically indistinguishable from queen’s sons, this suggests that workers do not move any queen-laid eggs between the part of the colony where the queen is present to the area above the queen excluder which the queen cannot enter. The colony had 16 patrilines, with an effective number of patrilines of 9.85. The 75 males that could be assigned with certainty to a patriline came from 7 patrilines, with an effective number of 4.21. They were the offspring of at least 19 workers. This is in contrast to the two previously studied Australian naturally occurring anarchist colonies, in which most of the workers’ sons were offspring of one patriline. The high number of patrilines producing males leads to a low mean relatedness between laying workers and males of the colony. We discuss the importance of studying such colonies in the understanding of worker policing and its evolution

Mixing of Honeybees with Different Genotypes Affects Individual Worker Behavior and Transcription of Genes in the Neuronal Substrate

Division of labor in social insects has made the evolution of collective traits possible that cannot be achieved by individuals alone. Differences in behavioral responses produce variation in engagement in behavioral tasks, which as a consequence, generates a division of labor. We still have little understanding of the genetic components influencing these behaviors, although several candidate genomic regions and genes influencing individual behavior have been identified. Here, we report that mixing of worker honeybees with different genotypes influences the expression of individual worker behaviors and the transcription of genes in the neuronal substrate. These indirect genetic effects arise in a colony because numerous interactions between workers produce interacting phenotypes and genotypes across organisms. We studied hygienic behavior of honeybee workers, which involves the cleaning of diseased brood cells in the colony. We mixed ∼500 newly emerged honeybee workers with genotypes of preferred Low (L) and High (H) hygienic behaviors. The L/H genotypic mixing affected the behavioral engagement of L worker bees in a hygienic task, the cooperation among workers in uncapping single brood cells, and switching between hygienic tasks. We found no evidence that recruiting and task-related stimuli are the primary source of the indirect genetic effects on behavior. We suggested that behavioral responsiveness of L bees was affected by genotypic mixing and found evidence for changes in the brain in terms of 943 differently expressed genes. The functional categories of cell adhesion, cellular component organization, anatomical structure development, protein localization, developmental growth and cell morphogenesis were overrepresented in this set of 943 genes, suggesting that indirect genetic effects can play a role in modulating and modifying the neuronal substrate. Our results suggest that genotypes of social partners affect the behavioral responsiveness and the neuronal substrate of individual workers, indicating a complex genetic architecture underlying the expression of behavior

Expression of the Arabidopsis thaliana immune receptor EFR in Medicago truncatula reduces infection by a root pathogenic bacterium, but not nitrogen‐fixing rhizobial symbiosis

Interfamily transfer of plant pattern recognition receptors (PRRs) represents a promising biotechnological approach to engineer broad‐spectrum, and potentially durable, disease resistance in crops. It is however unclear whether new recognition specificities to given pathogen‐associated molecular patterns (PAMPs) affect the interaction of the recipient plant with beneficial microbes. To test this in a direct reductionist approach, we transferred the Brassicaceae‐specific PRR ELONGATION FACTOR‐THERMO UNSTABLE RECEPTOR (EFR), conferring recognition of the bacterial EF‐Tu protein, from Arabidopsis thaliana to the legume Medicago truncatula. Constitutive EFR expression led to EFR accumulation and activation of immune responses upon treatment with the EF‐Tu‐derived elf18 peptide in leaves and roots. The interaction of M. truncatula with the bacterial symbiont Sinorhizobium meliloti is characterized by the formation of root nodules that fix atmospheric nitrogen. Although nodule numbers were slightly reduced at an early stage of the infection in EFR‐Medicago when compared to control lines, nodulation was similar in all lines at later stages. Furthermore, nodule colonization by rhizobia, and nitrogen fixation were not compromised by EFR expression. Importantly, the M. truncatula lines expressing EFR were substantially more resistant to the root bacterial pathogen Ralstonia solanacearum. Our data suggest that the transfer of EFR to M. truncatula does not impede root nodule symbiosis, but has a positive impact on disease resistance against a bacterial pathogen. In addition, our results indicate that Rhizobium can either avoid PAMP recognition during the infection process, or is able to actively suppress immune signaling

‘Special agents’ trigger social waves in giant honeybees (Apis dorsata)

Giant honeybees (Apis dorsata) nest in the open and have therefore evolved a variety of defence strategies. Against predatory wasps, they produce highly coordinated Mexican wavelike cascades termed ‘shimmering’, whereby hundreds of bees flip their abdomens upwards. Although it is well known that shimmering commences at distinct spots on the nest surface, it is still unclear how shimmering is generated. In this study, colonies were exposed to living tethered wasps that were moved in front of the experimental nest. Temporal and spatial patterns of shimmering were investigated in and after the presence of the wasp. The numbers and locations of bees that participated in the shimmering were assessed, and those bees that triggered the waves were identified. The findings reveal that the position of identified trigger cohorts did not reflect the experimental path of the tethered wasp. Instead, the trigger centres were primarily arranged in the close periphery of the mouth zone of the nest, around those parts where the main locomotory activity occurs. This favours the ‘special-agents’ hypothesis that suggest that groups of specialized bees initiate the shimmering

Evolution of self-organized division of labor in a response threshold model

Division of labor in social insects is determinant to their ecological success. Recent models emphasize that division of labor is an emergent property of the interactions among nestmates obeying to simple behavioral rules. However, the role of evolution in shaping these rules has been largely neglected. Here, we investigate a model that integrates the perspectives of self-organization and evolution. Our point of departure is the response threshold model, where we allow thresholds to evolve. We ask whether the thresholds will evolve to a state where division of labor emerges in a form that fits the needs of the colony. We find that division of labor can indeed evolve through the evolutionary branching of thresholds, leading to workers that differ in their tendency to take on a given task. However, the conditions under which division of labor evolves depend on the strength of selection on the two fitness components considered: amount of work performed and on worker distribution over tasks. When selection is strongest on the amount of work performed, division of labor evolves if switching tasks is costly. When selection is strongest on worker distribution, division of labor is less likely to evolve. Furthermore, we show that a biased distribution (like 3:1) of workers over tasks is not easily achievable by a threshold mechanism, even under strong selection. Contrary to expectation, multiple matings of colony foundresses impede the evolution of specialization. Overall, our model sheds light on the importance of considering the interaction between specific mechanisms and ecological requirements to better understand the evolutionary scenarios that lead to division of labor in complex systems

Contribution of NFP LysM Domains to the Recognition of Nod Factors during the Medicago truncatula/Sinorhizobium meliloti Symbiosis

The root nodule nitrogen fixing symbiosis between legume plants and soil bacteria called rhizobia is of great agronomical and ecological interest since it provides the plant with fixed atmospheric nitrogen. The establishment of this symbiosis is mediated by the recognition by the host plant of lipo-chitooligosaccharides called Nod Factors (NFs), produced by the rhizobia. This recognition is highly specific, as precise NF structures are required depending on the host plant. Here, we study the importance of different LysM domains of a LysM-Receptor Like Kinase (LysM-RLK) from Medicago truncatula called Nod factor perception (NFP) in the recognition of different substitutions of NFs produced by its symbiont Sinorhizobium meliloti. These substitutions are a sulphate group at the reducing end, which is essential for host specificity, and a specific acyl chain at the non-reducing end, that is critical for the infection process. The NFP extracellular domain (ECD) contains 3 LysM domains that are predicted to bind NFs. By swapping the whole ECD or individual LysM domains of NFP for those of its orthologous gene from pea, SYM10 (a legume plant that interacts with another strain of rhizobium producing NFs with different substitutions), we showed that NFP is not directly responsible for specific recognition of the sulphate substitution of S. meliloti NFs, but probably interacts with the acyl substitution. Moreover, we have demonstrated the importance of the NFP LysM2 domain for rhizobial infection and we have pinpointed the importance of a single leucine residue of LysM2 in that step of the symbiosis. Together, our data put into new perspective the recognition of NFs in the different steps of symbiosis in M. truncatula, emphasising the probable existence of a missing component for early NF recognition and reinforcing the important role of NFP for NF recognition during rhizobial infection

Spatial effects, sampling errors, and task specialization in the honey bee

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists

SRFR1 Negatively Regulates Plant NB-LRR Resistance Protein Accumulation to Prevent Autoimmunity

Plant defense responses need to be tightly regulated to prevent auto-immunity, which is detrimental to growth and development. To identify negative regulators of Resistance (R) protein-mediated resistance, we screened for mutants with constitutive defense responses in the npr1-1 background. Map-based cloning revealed that one of the mutant genes encodes a conserved TPR domain-containing protein previously known as SRFR1 (SUPPRESSOR OF rps4-RLD). The constitutive defense responses in the srfr1 mutants in Col-0 background are suppressed by mutations in SNC1, which encodes a TIR-NB-LRR (Toll Interleukin1 Receptor-Nucleotide Binding-Leu-Rich Repeat) R protein. Yeast two-hybrid screens identified SGT1a and SGT1b as interacting proteins of SRFR1. The interactions between SGT1 and SRFR1 were further confirmed by co-immunoprecipitation analysis. In srfr1 mutants, levels of multiple NB-LRR R proteins including SNC1, RPS2 and RPS4 are increased. Increased accumulation of SNC1 is also observed in the sgt1b mutant. Our data suggest that SRFR1 functions together with SGT1 to negatively regulate R protein accumulation, which is required for preventing auto-activation of plant immunity

Effectiveness of IT-based diabetes management interventions: a review of the literature

Background : Information technology (IT) is increasingly being used in general practice to manage health care including type 2 diabetes. However, there is conflicting evidence about whether IT improves diabetes outcomes. This review of the literature about IT-based diabetes management interventions explores whether methodological issues such as sample characteristics, outcome measures, and mechanisms causing change in the outcome measures could explain some of the inconsistent findings evident in IT-based diabetes management studies.Methods : Databases were searched using terms related to IT and diabetes management. Articles eligible for review evaluated an IT-based diabetes management intervention in general practice and were published between 1999 and 2009 inclusive in English. Studies that did not include outcome measures were excluded.Results : Four hundred and twenty-five articles were identified, sixteen met the inclusion criteria: eleven GP focussed and five patient focused interventions were evaluated. Nine were RCTs, five non-randomised control trials, and two single-sample before and after designs. Important sample characteristics such as diabetes type, familiarity with IT, and baseline diabetes knowledge were not addressed in any of the studies reviewed. All studies used HbA1c as a primary outcome measure, and nine reported a significant improvement in mean HbA1c over the study period; only two studies reported the HbA1c assay method. Five studies measured diabetes medications and two measured psychological outcomes. Patient lifestyle variables were not included in any of the studies reviewed. IT was the intervention method considered to effect changes in the outcome measures. Only two studies mentioned alternative possible causal mechanisms.Conclusion : Several limitations could affect the outcomes of IT-based diabetes management interventions to an unknown degree. These limitations make it difficult to attribute changes solely to such interventions.<br /