Dataset Information

Candidate stress biomarkers for queen failure diagnostics.

ABSTRACT: BACKGROUND:Queen failure is a persistent problem in beekeeping operations, but in the absence of overt symptoms it is often difficult, if not impossible, to ascertain the root cause. Stressors like heat-shock, cold-shock, and sublethal pesticide exposure can reduce stored sperm viability and lead to cryptic queen failure. Previously, we suggested candidate protein markers indicating heat-shock in queens. Here, we further investigate these heat-shock markers and test new stressors to identify additional candidate protein markers. RESULTS:We found that heat-shocking queens for upwards of 1 h at 40?°C was necessary to induce significant changes in the two strongest candidate heat-shock markers, and that relative humidity significantly influenced the degree of activation. In blind heat-shock experiments, we tested the efficiency of these markers at assigning queens to their respective treatment groups and found that one marker was sufficient to correctly assign queens 75% of the time. Finally, we compared cold-shocked queens at 4?°C and pesticide-exposed queens to controls to identify candidate markers for these additional stressors, and compared relative abundances of all markers to queens designated as 'healthy' and 'failing' by beekeepers. Queens that failed in the field had higher expression of both heat-shock and pesticide protein markers, but not cold-shock markers. CONCLUSIONS:This work offers some of the first steps towards developing molecular diagnostic tools to aid in determining cryptic causes of queen failure. Further work will be necessary to determine how long after the stress event a marker's expression remains elevated, and how accurate these markers will be for field diagnoses.

SUBMITTER: McAfee A

PROVIDER: S-EPMC7441638 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Candidate stress biomarkers for queen failure diagnostics.

McAfee Alison A Milone Joseph J Chapman Abigail A Foster Leonard J LJ Pettis Jeffery S JS Tarpy David R DR

BMC genomics 20200820 1

<h4>Background</h4>Queen failure is a persistent problem in beekeeping operations, but in the absence of overt symptoms it is often difficult, if not impossible, to ascertain the root cause. Stressors like heat-shock, cold-shock, and sublethal pesticide exposure can reduce stored sperm viability and lead to cryptic queen failure. Previously, we suggested candidate protein markers indicating heat-shock in queens. Here, we further investigate these heat-shock markers and test new stressors to iden ...[more]

PMID: 32819278

Similar Datasets

Project description:Spermathecal fluid proteins were cleaned up via acetone precipitation overnight at 20 C. The precipitated protein was pelleted and washed twice with 500 ul of 80% acetone, then the pellet was allowed to air dry (ca. 5 min) prior to solubilization in 50 ul of digestion buffer (6 M urea, 2 M thiourea). Approximately 25 ug of protein were reduced (0.5 ug dithiothreitol, 20 min), alkylated (2.5 ug iodoacetamide, 30 min, dark), and digested (0.5 ug Lys-C for 3 h, then 0.5 ug trypsin overnight). Digested peptides were acidified with one volume of 1% trifluoroacetic acid and desalted with high-capacity STAGE tips. Eluted samples were dried (SpeedVac, Eppendorf, 45 min) and resuspended in Buffer A (0.1% formic acid). Peptide concentrations were determined using a NanoDrop (Thermo, 280 nm) and sample orders were randomized for liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Peptides (0.5 ug for each sample) were injected on an EASY-nLC 1000 liquid chromatography system (Thermo) coupled to an Impact II Q-TOF mass spectrometer (Bruker). The LC system included a fused-silica (5 um Aqua C18 particles (Phenomenex)) fritted 2 cm trap column connected to a 50 cm analytical column packed with ReproSil C18 (3 um C18 particles (Dr. Maisch)). The separation gradient ran from 5% to 35% Buffer B (80% acetonitrile, 0.1% formic acid) over 120 min, followed by a 15 min wash at 95% Buffer B (flow rate: 250 uL/min). The instrument parameters were: scan from 150 to 2200 m/z, 100 us transient time, 10 us prepulse storage, 7 eV collision energy, 1500 Vpp Collision RF, a +2 default charge state, 18 Hz spectral acquisition rate, 3.0 s cycle time, and the intensity threshold was 250 counts. Mass spectrometry data were searched using MaxQuant (v1.6.1.0) using default parameters, except match between runs was enabled. Peptide spectral matches, peptide identifications and protein identifications were controlled at 1% false discovery rates (FDRs). Data were analyzed in Perseus (v1.6.1.1). Proteins differentially expressed between heat-shocked and non-heat-shocked samples, as well as among tissues (semen, virgin spermathecae, and mated spermathecae), were identified using t-tests and significant results were corrected to either 5% (heat-shock and cold-shock) or 10% FDR (pesticide stress) (Banjamini-Hochberg method).

Project description:IntroductionHeart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules.MethodsThe expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein-protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene-miRNA regulatory network and target gene-TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed.ResultsA total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene-miRNA regulatory network and target gene-TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed.ConclusionThe current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

Dataset Information

Candidate stress biomarkers for queen failure diagnostics.

Publications

Candidate stress biomarkers for queen failure diagnostics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets