Computational protocol: Dynamics of Immune System Gene Expression upon Bacterial Challenge and Wounding in a Social Insect (Bombus terrestris)

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[…] RNA preparation followed the protocol from with one bumble bee abdomen homogenised in 600 µl QIAzol Lysis Reagent (Qiagen, Hilden, Germany). Purity of each RNA sample was determined using the absorption ratio (260/280 nm) determined by NanoDrop 1000 (Pequlab, Erlangen, Germany). cDNA was synthesised according to the manufactures instructions starting with 2 µg RNA supplemented with 30 U M-MLV Reverse Transcriptase (Promega, Mannheim, Germany) and 0.625 µg 18-mer oligo dTs (Fermentas, St. Leon-Rot, Germany).cDNA samples were diluted 1 ∶ 50 with DEPC-water (DNase- & RNase free water). 1 µl diluted cDNA was used together with 5 µl SensiMixPlus SYBR & Fluorescein Kit (SYBR-Green) (Bioline, Luckenwalde, Germany), 0.3 µM of each gene specific primer () and 3.4 µl DEPC-water for the gene expression assay. In order to control for PCR efficiency and individual differences of samples a set of housekeeping genes was used (see ). Primers for housekeeping genes were designed using Primer 3 (v.0.4.0, http://frodo.wi.mit.edu/primer3/) using sequences deposited in GenBank under following accession numbers AF181594 (28S rRNA), AY208282 (EF1α), AF492888 (AK) and DQ468668 (ITPR).AMPs and pathway gene primers were designed from sequenced cDNA or adopted from , . The cDNA for sequencing was produced as described before from one B. terrestris worker infected with E. coli strain YM109. Several immune pathway genes (basket - HM143000, cactus 2 - HM143001 / HM143002, dorsal - HM143003, hem - HM143004, Kenny - HM143005, Myd88 - HM143006, prophenoloxidase - HM142999, relish - HM143007, Tak 1 - HM143008, TEP A - HM143009, Toll 1 - HM143010, Toll 6 - HM143011, all deposited in GenBank) and antimicrobial peptide genes (abaecin – GU233780, defensin 1 – GU233781, hymenoptaecin – GU233782, all deposited in GenBank) were amplified using primers from , . qPCR primers for AMPs and immune pathway key genes (dorsal, basket, prophenoloxidase, relish, TEP A) were derived from sequenced PCR products (Eurofins MWG GmbH, Ebersberg, Germany) by using Primer 3 (v.0.4.0) .Bacterial growth of E. coli was detected using the bacterial housekeeping gene fadD, as part of the fatty acid metabolism (EcMLST a multilocus sequence typing database system (MLST) for pathogenic Escherichia coli; http://www.shigatox.net/ecmlst/cgi-bin/scheme). Gene expression of fadD was normalised to the initial amount of bacteria at starting point. The qPCR protocol for all primer pairs consisted of an initial denaturation step of 10 min at 95°C followed by 35 amplification cycles (95°C, 15 sec; Tannealing, 30 sec and an elongation step at 72°C for 30 sec) and subsequent melting curve analysis between 50°C and 98°C, reading the fluorescence at 1°C increments. Two replicates for each sample were run using Chromo4™ (Bio-Rad, Munich, Germany). Samples from the same individuals and from individuals with the same measuring point or treatment were allocated on different plates, in order to minimize a between-plate effect. [...] Opticon Monitor 3 (Bio-Rad, Munich, Germany) software was used to compute Ct values after baseline subtraction and PCR efficiencies were calculated using LinRegPCR . Replicate samples showing a difference in Ct values larger than 0.5 were re-run. Finally, all replicates showed low variance for Ct values.Relative gene expression (rE) was calculated according to this formula:Ct = cycle thresholdE = PCR efficiencyi = ith housekeeping genen = number of housekeeping genesrE = relative expressionValues for rE were log-transformed in order to ensure normality and homoscedasticity of the data. Treatment, time p.t. (time point post treatment) and treatment by time interaction effects on levels of gene expression were tested using factorial ANOVA. The experimental design is hierarchical with control (non-injected) and injected individuals structuring the first level and within injected bees, discriminating between bee ringer and E. coli injection at the second level of the analysis (). This scenario requires two subsequent ANOVA in order to discriminate between effects at the different hierarchical levels. In all analysis the residuals from the first ANOVA were used as values for the second ANOVA. Hence, effects of time p.t. are eliminated in this way. In case of significant interaction terms we applied a Scheffé post hoc comparison in order to determine significant differences.Correlation analyses between groups of genes (e.g. AMPs) and single factors (e.g. bacterial growth, transcription factor activity) usually included multiple testing, which has been taken into account by using a Bonferroni adjustment of the p-values. In the case where several variables were correlated as well we used partial correlation analysis to account for this.In order to determine which of the pathways is involved in a specific treatment, multiple regression analysis was used to determine which transcription factors that might induce the expression of effector genes. All statistical analyses were done using standard spreadsheet software and STATISTICA 8.0 (StatSoft, Tulsa, Oklahoma, USA). […]

Pipeline specifications

Software tools Primer3, LinRegPCR, Statistica
Applications Miscellaneous, qPCR
Organisms Apis mellifera, Bacteria, Bombus terrestris, Apis dorsata
Diseases Bacterial Infections