Florian Wolschin

Reversible switching between epigenetic states in honeybee behavioral subcastes

In honeybee societies, distinct caste phenotypes are created from the same genotype, suggesting a role for epigenetics in deriving these behaviorally different phenotypes. We found no differences in DNA methylation between irreversible worker and queen castes, but substantial differences between nurses and forager subcastes. Reverting foragers back to nurses reestablished methylation levels for a majority of genes and provides, to the best of our knowledge, the first evidence in any organism of reversible epigenetic changes associated with behavior.

IRS and TOR nutrient-signaling pathways act via juvenile hormone to influence honey bee caste fate.

SUMMARY Regardless of genetic makeup, a female honey bee becomes a queen or worker depending on the food she receives as a larva. For decades, it has been known that nutrition and juvenile hormone (JH) signaling determine the caste fate of the individual bee. However, it is still largely unclear how these factors are connected. To address this question, we suppressed nutrient sensing by RNA interference (RNAi)-mediated gene knockdown of IRS (insulin receptor substrate) and TOR (target of rapamycin) in larvae reared on queen diet. The treatments affected several layers of organismal organization that could play a role in the response to differential nutrition between castes. These include transcript profiles, proteomic patterns, lipid levels, DNA methylation response and morphological features. Most importantly, gene knockdown abolished a JH peak that signals queen development and resulted in a worker phenotype. Application of JH rescued the queen phenotype in either knockdown, which demonstrates that the larval response to JH remains intact and can drive normal developmental plasticity even when IRS or TOR transcript levels are reduced. We discuss our results in the context of other recent findings on honey bee caste and development and propose that IRS is an alternative substrate for the Egfr (epidermal growth factor receptor) in honey bees. Overall, our study describes how the interplay of nutritional and hormonal signals affects many levels of organismal organization to build different phenotypes from identical genotypes.

Integration of Metabolomic and Proteomic Phenotypes Analysis of Data Covariance Dissects Starch and RFO Metabolism from Low and High Temperature Compensation Response in Arabidopsis Thaliana

Statistical mining and integration of complex molecular data including metabolites, proteins, and transcripts is one of the critical goals of systems biology (Ideker, T., Galitski, T., and Hood, L. (2001) A new approach to decoding life: systems biology. Annu. Rev. Genomics Hum. Genet. 2, 343–372). A number of studies have demonstrated the parallel analysis of metabolites and large scale transcript expression. Protein analysis has been ignored in these studies, although a clear correlation between transcript and protein levels is shown only in rare cases, necessitating that actual protein levels have to be determined for protein function analysis. Here, we present an approach to investigate the combined covariance structure of metabolite and protein dynamics in a systemic response to abiotic temperature stress in Arabidopsis thaliana wild-type and a corresponding starch-deficient mutant (phosphoglucomutase-deficient). Independent component analysis revealed phenotype classification resolving genotype-dependent response effects to temperature treatment and genotype-independent general temperature compensation mechanisms. An observation is the stress-induced increase of raffinose-family-oligosaccharide levels in the absence of transitory starch storage/mobilization in temperature-treated phosphoglucomutase plants indicating that sucrose synthesis and storage in these mutant plants is sufficient to bypass the typical starch storage/mobilization pathways under abiotic stress. Eventually, sample pattern recognition and correlation network topology analysis allowed for the detection of specific metabolite-protein co-regulation and assignment of a circadian output regulated RNA-binding protein to these processes. The whole concept of high-dimensional profiling data integration from many replicates, subsequent multivariate statistics for dimensionality reduction, and covariance structure analysis is proposed to be a major strategy for revealing central responses of the biological system under study.

A diapause pathway underlies the gyne phenotype in Polistes wasps, revealing an evolutionary route to caste-containing insect societies.

Colonies of social wasps, ants, and bees are characterized by the production of two phenotypes of female offspring, workers that remain at their natal nest and nonworkers that are potential colony reproductives of the next generation. The phenotype difference includes morphology and is fixed during larval development in ants, honey bees, and some social wasps, all of which represent an advanced state of sociality. Paper wasps (Polistes) lack morphological castes and are thought to more closely resemble an ancestral state of sociality wherein the phenotype difference between workers and nonworkers is established only during adult life. We address an alternative hypothesis: a bias toward the potential reproductive (gyne) phenotype among Polistes female offspring occurs during larval development and is based on a facultatively expressed ancestral life history trait: diapause. We show that two signatures of diapause (extended maturation time and enhanced synthesis and sequestration of a hexameric storage protein) characterize the development of gyne offspring in Polistes metricus. Hexameric storage proteins are implicated in silencing juvenile hormone signaling, which is a prerequisite for diapause. Diverging hexamerin protein dynamics driven by changes in larval provisioning levels thereby provide one possible mechanism that can cause an adaptive shift in phenotype bias during the Polistes colony cycle. This ontogenetic basis for alternative female phenotypes in Polistes challenges the view that workers and gynes represent behavior options equally available to every female offspring, and it exemplifies how social insect castes can evolve from casteless lineages.

Genome-wide association between DNA methylation and alternative splicing in an invertebrate

BackgroundGene bodies are the most evolutionarily conserved targets of DNA methylation in eukaryotes. However, the regulatory functions of gene body DNA methylation remain largely unknown. DNA methylation in insects appears to be primarily confined to exons. Two recent studies in Apis mellifera (honeybee) and Nasonia vitripennis (jewel wasp) analyzed transcription and DNA methylation data for one gene in each species to demonstrate that exon-specific DNA methylation may be associated with alternative splicing events. In this study we investigated the relationship between DNA methylation, alternative splicing, and cross-species gene conservation on a genome-wide scale using genome-wide transcription and DNA methylation data.ResultsWe generated RNA deep sequencing data (RNA-seq) to measure genome-wide mRNA expression at the exon- and gene-level. We produced a de novo transcriptome from this RNA-seq data and computationally predicted splice variants for the honeybee genome. We found that exons that are included in transcription are higher methylated than exons that are skipped during transcription. We detected enrichment for alternative splicing among methylated genes compared to unmethylated genes using fisher’s exact test. We performed a statistical analysis to reveal that the presence of DNA methylation or alternative splicing are both factors associated with a longer gene length and a greater number of exons in genes. In concordance with this observation, a conservation analysis using BLAST revealed that each of these factors is also associated with higher cross-species gene conservation.ConclusionsThis study constitutes the first genome-wide analysis exhibiting a positive relationship between exon-level DNA methylation and mRNA expression in the honeybee. Our finding that methylated genes are enriched for alternative splicing suggests that, in invertebrates, exon-level DNA methylation may play a role in the construction of splice variants by positively influencing exon inclusion during transcription. The results from our cross-species homology analysis suggest that DNA methylation and alternative splicing are genetic mechanisms whose utilization could contribute to a longer gene length and a slower rate of gene evolution.

Insulin receptor substrate influences female caste development in honeybees

The insulin/insulin-like signalling (IIS) network is conserved among animals and is central to growth and development. In eusocial honeybees (Apis mellifera), IIS is hypothesized to shape female caste fate. We tested this hypothesis via RNA interference (RNAi) knockdown of the insulin receptor substrate (IRS) homologue, a key adaptor protein in IIS. Female larvae naturally develop into queens (reproductives) or workers (helpers) after being fed rich versus limited diets, respectively. Feeding larvae a rich diet mixed with dsRNA (double stranded RNA) targeting irs gene transcript decreased irs mRNA abundance and caused development of worker morphology. Controls receiving rich larval diet and control dsRNA developed queen morphology. Whole-body mass spectrometry profiling of larvae collected 72, 96 and 120 h after dsRNA treatments revealed proteomic differences between irs gene knockdowns and controls, including levels of hexamerin 110, a storage protein connected to natural caste differences.

Differential gene expression and protein abundance evince ontogenetic bias toward castes in a primitively eusocial wasp.

Polistes paper wasps are models for understanding conditions that may have characterized the origin of worker and queen castes and, therefore, the origin of paper wasp sociality. Polistes is “primitively eusocial” by virtue of having context-dependent caste determination and no morphological differences between castes. Even so, Polistes colonies have a temporal pattern in which most female larvae reared by the foundress become workers, and most reared by workers become future-reproductive gynes. This pattern is hypothesized to reflect development onto two pathways, which may utilize mechanisms that regulate diapause in other insects. Using expressed sequence tags (ESTs) for Polistes metricus we selected candidate genes differentially expressed in other insects in three categories: 1) diapause vs. non-diapause phenotypes and/or worker vs. queen differentiation, 2) behavioral subcastes of worker honey bees, and 3) no a priori expectation of a role in worker/gyne development. We also used a non-targeted proteomics screen to test for peptide/protein abundance differences that could reflect larval developmental divergence. We found that foundress-reared larvae (putative worker-destined) and worker-reared larvae (putative gyne-destined) differed in quantitative expression of sixteen genes, twelve of which were associated with caste and/or diapause in other insects, and they also differed in abundance of nine peptides/proteins. Some differentially-expressed genes are involved in diapause regulation in other insects, and other differentially-expressed genes and proteins are involved in the insulin signaling pathway, nutrient metabolism, and caste determination in highly social bees. Differential expression of a gene and a peptide encoding hexameric storage proteins is especially noteworthy. Although not conclusive, our results support hypotheses of 1) larval developmental pathway divergence that can lead to caste bias in adults and 2) nutritional differences as the foundation of the pathway divergence. Finally, the differential expression in Polistes larvae of genes and proteins also differentially expressed during queen vs. worker caste development in honey bees may indicate that regulatory mechanisms of caste outcomes share similarities between primitively eusocial and advanced eusocial Hymenoptera.

Comparative proteomics reveal characteristics of life-history transitions in a social insect

BackgroundHoney bee (Apis mellifera) workers are characterized by complex social behavior. Their life-history is dominated by a period of within-nest activity followed by a phase of long-distance flights and foraging. General insights into insect metabolism imply that foraging onset is associated with fundamental metabolic changes, and theory on social evolution suggests metabolic adaptations that are advantageous for the colony as a whole.ResultsHere we address the life-history characteristics of workers with LC-MS/MS based relative quantification of major proteins. Our approach includes: i. Calculation of a false positive rate for the identifications, ii. Support of relative protein quantification results obtained from spectral count by non-parametric statistics, and iii. Correction for Type 1 error inflation using a bootstrap iteration analysis. Our data are consistent with the use of glucose as the main fuel for honey bee flight. Moreover, the data delivers information on the expression of ATPsynthases/ATPases, and provide new insights into nurse- and forager-specific patterns of protection against oxidative stress.ConclusionThe results show the suitability of this approach to investigate fundamental biochemical changes in an insect, and provide new evidence for metabolic specializations that occur during the social ontogeny of worker honey bees.

Deciphering Proteomic Signatures of Early Diapause in Nasonia

Insect diapause is an alternative life-history strategy used to increase longevity and survival in harsh environmental conditions. Even though some aspects of diapause are well investigated, broader scale studies that elucidate the global metabolic adjustments required for this remarkable trait, are rare. In order to better understand the metabolic changes during early insect diapause, we used a shotgun proteomics approach on early diapausing and non-diapausing larvae of the recently sequenced hymenopteran model organism Nasonia vitripennis. Our results deliver insights into the molecular underpinnings of diapause in Nasonia and corroborate previously reported diapause-associated features for invertebrates, such as a diapause-dependent abundance change for heat shock and storage proteins. Furthermore, we observed a diapause-dependent switch in enzymes involved in glycerol synthesis and a vastly changed capacity for protein synthesis and degradation. The abundance of structural proteins and proteins involved in protein synthesis decreased with increasing diapause duration, while the abundance of proteins likely involved in diapause maintenance (e.g. ferritins) increased. Only few potentially diapause-specific proteins were identified suggesting that diapause in Nasonia relies to a large extent on a modulation of pre-existing pathways. Studying a diapause syndrome on a proteomic level rather than isolated pathways or physiological networks, has proven to be an efficient and successful avenue to understand molecular mechanisms involved in diapause.

Integrative profiling of metabolites and proteins: improving pattern recognition and biomarker selection for systems level approaches.

Methods such as mRNA expression profiling have provided a vast amount of genomic and transcriptomic information about plants and other organisms. However, there is explicit indication that considerable metabolic control is executed on the metabolite and on the protein level including protein modifications, thereby constituting the phenotypic plasticity. Consequently, the analysis of the molecular phenotype demands the step toward mass spectrometry (MS)-based postgenomic techniques such as metabolomics and proteomics. This chapter describes a straightforward protocol for simultaneously extracting metabolites and proteins from the same biological sample in preparation for MS analysis. Furthermore, protocols for profiling polar metabolites using gas chromatography time-of-flight MS and for shotgun proteomics using liquid chromatography-MS are discussed. A practical course is laid out that outlines all the basic steps, from harvesting to data analysis. These steps enable the correlative study of metabolite and protein dynamics with minimal technical variation. Biological variability of independent samples is exploited for variance analysis and pattern recognition.