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Forrester KC, Lin CH, Johnson RM. Measuring factors affecting honey bee (Hymenoptera: Apidae) attraction to soybeans using bioacoustics monitoring. J Insect Sci 2024; 24:20. [PMID: 38573061 PMCID: PMC10993721 DOI: 10.1093/jisesa/ieae036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 02/01/2024] [Accepted: 03/11/2024] [Indexed: 04/05/2024]
Abstract
Soybean (Glycine max (L.) Merr.) is an important agricultural crop around the world, and previous studies suggest that honey bees (Apis mellifera Linnaeus) can be a component for optimizing soybean production through pollination. Determining when bees are present in soybean fields is critical for assessing pollination activity and identifying periods when bees are absent so that bee-toxic pesticides may be applied. There are currently several methods for detecting pollinator activity, but these existing methods have substantial limitations, including the bias of pan trappings against large bees and the limited duration of observation possible using manual techniques. This study aimed to develop a new method for detecting honey bees in soybean fields using bioacoustics monitoring. Microphones were placed in soybean fields to record the audible wingbeats of foraging bees. Foraging activity was identified using the wingbeat frequency of honey bees (234 ± 14 Hz) through a combination of algorithmic and manual approaches. A total of 243 honey bees were detected over 10 days of recording in 4 soybean fields. Bee activity was significantly greater in blooming fields than in non-blooming fields. Temperature had no significant effect on bee activity, but bee activity differed significantly between soybean varieties, suggesting that soybean attractiveness to honey bees is heavily dependent on varietal characteristics. Refinement of bioacoustics methods, particularly through the incorporation of machine learning, could provide a practical tool for measuring the activity of honey bees and other flying insects in soybeans as well as other crops and ecosystems.
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Affiliation(s)
- Karlan C Forrester
- Department of Entomology, The Ohio State University, 1680 Madison Ave, Wooster, OH 44691, USA
| | - Chia-Hua Lin
- Department of Entomology, The Ohio State University, 1680 Madison Ave, Wooster, OH 44691, USA
| | - Reed M Johnson
- Department of Entomology, The Ohio State University, 1680 Madison Ave, Wooster, OH 44691, USA
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Sanz Cortes M, Corroenne R, Pyarali M, Johnson RM, Whitehead WE, Espinoza J, Donepudi R, Castillo J, Castillo H, Mehollin-Ray AR, Shamshirsaz AA, Nassr AA, Belfort MA. Ambulation after in-utero fetoscopic and open spina bifida repair: predictors for ambulation at 30 months. Ultrasound Obstet Gynecol 2024. [PMID: 38243917 DOI: 10.1002/uog.27589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/04/2023] [Accepted: 01/15/2024] [Indexed: 01/22/2024]
Abstract
OBJECTIVE Ambulatory outcomes from children who underwent a new minimally invasive fetal spina bifida surgery approach are included in this study for the first time. Identifying cases with better chances of independent ambulation from fetal life can have an important impact on patient counseling. The objectives of this study were: (1) To compare the ambulatory status of a cohort of children who had a prenatal spina bifida repair using two different methods (fetoscopic and open) with a cohort who underwent postnatal repair; and (2) to identify the best predictors for ambulation. METHODS Retrospective review of a cohort of children who had spina bifida repair from 2011-2023 using prenatal fetoscopic surgery (N=73), prenatal open-hysterotomy surgery (N=37) or postnatal repair (N=51) in a single tertiary hospital. Consecutive sample of cases who underwent a spina bifida repair in utero following MoMs trial criteria and cases who underwent postnatal repair, meeting same criteria, also followed up after birth at the same institution. Motor function (MF) assessment by ultrasound was recorded at initial evaluation (MF1), 6 postoperative weeks or equivalent (MF2) and prior to delivery (MF3). Clinical exams to assess MF at birth and at 12 months were recorded. First sacral myotome (S1) MF was classified as "intact MF". Ambulatory status data at each follow-up visit was collected. The proportion of cases who were able to walk independently were compared between fetoscopic and open prenatal surgeries and between prenatal (by fetoscopic or open surgery) and postnatal spina bifida repair. Logistic regression analyses were performed to identify predictors for independent ambulation. RESULTS At 30 months, the proportion of independent ambulators was higher in prenatally vs. postnatally repaired cases (51.8% vs.15.7%; p<0.01). No differences in ambulatory outcomes were seen in the comparison between fetoscopic (52%) vs. open (51.3%; p=0.95) prenatal repair. In the prenatal repair group, having an "intact MF" at 12 months [Odds ratio 7.71 (95%CI: 2.77-21.47), p<0.01] and at birth [4.38 (1.53-12.56), p<0.01], predicted significantly being an independent ambulator by 30 months; the anatomical level of lesion below L2 was also predictive for this outcome [3.68(1.33-9.88), p=0.01]. CONCLUSION Ambulatory status by 30 months can be predicted by observing S1 MF postnatally. Results from this study have implications for parental counseling and planning for supportive therapies. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- M Sanz Cortes
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - R Corroenne
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - M Pyarali
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - R M Johnson
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - W E Whitehead
- Department of Neurosurgery, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - J Espinoza
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - R Donepudi
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - J Castillo
- Department of Pediatrics, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - H Castillo
- Department of Pediatrics, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - A R Mehollin-Ray
- Department of Radiology, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - A A Shamshirsaz
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - A A Nassr
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - M A Belfort
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
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Sanz Cortes M, Johnson RM, Sangi-Haghpeykar H, Bedei I, Greenwood L, Nassr AA, Donepudi R, Whitehead W, Belfort M, Mehollin-Ray AR. Perforation of cavum septi pellucidi in open spina bifida and need for hydrocephalus treatment by 1 year of age. Ultrasound Obstet Gynecol 2024; 63:60-67. [PMID: 37698345 DOI: 10.1002/uog.27480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/12/2023] [Accepted: 08/24/2023] [Indexed: 09/13/2023]
Abstract
OBJECTIVE In-utero repair of an open neural tube defect (ONTD) reduces the risk of developing severe hydrocephalus postnatally. Perforation of the cavum septi pellucidi (CSP) may reflect increased intraventricular pressure in the fetal brain. We sought to evaluate the association of perforated CSP visualized on fetal imaging before and/or after in-utero ONTD repair with the eventual need for hydrocephalus treatment by 1 year of age. METHODS This was a retrospective cohort study of consecutive patients who underwent laparotomy-assisted fetoscopic ONTD repair between 2014 and 2021 at a single center. Eligibility criteria for surgery were based on those of the Management of Myelomeningocele Study (MOMS), although a maternal prepregnancy body mass index of up to 40 kg/m2 was allowed. Fetal brain imaging was performed with ultrasound and magnetic resonance imaging (MRI) at referral and 6 weeks postoperatively. Stored ultrasound and MRI scans were reviewed retrospectively to assess CSP integrity. Medical records were reviewed to determine whether hydrocephalus treatment was needed within 1 year of age. Parametric and non-parametric tests were used as appropriate to compare outcomes between cases with perforated CSP and those with intact CSP as determined on ultrasound at referral. Logistic regression analysis was performed to assess the predictive performance of various imaging markers for the need for hydrocephalus treatment. RESULTS A total of 110 patients were included. Perforated CSP was identified in 20.6% and 22.6% of cases on preoperative ultrasound and MRI, respectively, and in 26.6% and 24.2% on postoperative ultrasound and MRI, respectively. Ventricular size increased between referral and after surgery (median, 11.00 (range, 5.89-21.45) mm vs 16.00 (range, 7.00-43.5) mm; P < 0.01), as did the proportion of cases with severe ventriculomegaly (ventricular width ≥ 15 mm) (12.7% vs 57.8%; P < 0.01). Complete CSP evaluation was achieved on preoperative ultrasound in 107 cases, of which 22 had a perforated CSP and 85 had an intact CSP. The perforated-CSP group presented with larger ventricles (mean, 14.32 ± 3.45 mm vs 10.37 ± 2.37 mm; P < 0.01) and a higher rate of severe ventriculomegaly (40.9% vs 5.9%; P < 0.01) compared to those with an intact CSP. The same trends were observed at 6 weeks postoperatively for mean ventricular size (median, 21.0 (range, 13.0-43.5) mm vs 14.3 (range, 7.0-29.0) mm; P < 0.01) and severe ventriculomegaly (95.0% vs 46.8%; P < 0.01). Cases with a perforated CSP at referral had a lower rate of hindbrain herniation (HBH) reversal postoperatively (65.0% vs 88.6%; P = 0.01) and were more likely to require treatment for hydrocephalus (89.5% vs 22.7%; P < 0.01). The strongest predictor of the need for hydrocephalus treatment within 1 year of age was lack of HBH reversal on MRI (odds ratio (OR), 36.20 (95% CI, 5.96-219.12); P < 0.01) followed by perforated CSP on ultrasound at referral (OR, 23.40 (95% CI, 5.42-100.98); P < 0.01) and by perforated CSP at 6-week postoperative ultrasound (OR, 19.48 (95% CI, 5.68-66.68); P < 0.01). CONCLUSIONS The detection of a perforated CSP in fetuses with ONTD can reliably identify those cases at highest risk for needing hydrocephalus treatment by 1 year of age. Evaluation of this brain structure can improve counseling of families considering fetal surgery for ONTD, in order to set appropriate expectations about postnatal outcome. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- M Sanz Cortes
- Department of Obstetrics and Gynecology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - R M Johnson
- Department of Obstetrics and Gynecology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - H Sangi-Haghpeykar
- Department of Obstetrics and Gynecology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - I Bedei
- Department of Obstetrics and Gynecology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
- Department of Prenatal Diagnosis and Fetal Therapy, Justus-Liebig University Gießen, Gießen, Germany
| | - L Greenwood
- Department of Obstetrics and Gynecology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - A A Nassr
- Department of Obstetrics and Gynecology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - R Donepudi
- Department of Obstetrics and Gynecology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - W Whitehead
- Department of Neurosurgery, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - M Belfort
- Department of Obstetrics and Gynecology, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - A R Mehollin-Ray
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
- Edward B. Singleton Department of Radiology, Texas Children's Hospital, Houston, TX, USA
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Shannon B, Jeon H, Johnson RM. Review: the risks of spray adjuvants to honey bees. J Insect Sci 2023; 23:20. [PMID: 38055940 DOI: 10.1093/jisesa/iead100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/26/2023] [Accepted: 11/03/2023] [Indexed: 12/08/2023]
Abstract
Pesticide applications are often made as tank mixes containing multiple pesticide products and may include spray adjuvants to enhance pesticidal activities. The primary aim of adjuvant products is to increase the spreading and sticking of spray droplets and to increase the penetration of active ingredients through the cuticles of leaves or targeted pests, which can reduce the amount of active ingredient needed for effective pest control. Adjuvants are made up of compounds drawn from the "inert ingredient" list maintained by EPA but are identified as "principal functioning agents" when used in adjuvant products. These inert compounds do not undergo the same testing and risk assessment process that is required of pesticide active ingredients and generally have no mitigation measures that prevent application onto crops during bloom at times of day when bees are foraging. Honey bees (Apis mellifera;Hymenoptera:Apidae) are at an increased risk of exposure to adjuvant tank mixtures while providing agricultural pollination services. Colony losses attributed to pesticide applications thought to have low risk to honey bees have been reported, highlighting the need to better understand the toxicity of adjuvants included in pesticide tank mixtures. This review summarizes current literature on the risks posed to honey bees by agricultural adjuvants and tank mix combinations of adjuvants with pesticides. Based on the current state of knowledge, we make recommendations to pesticide applicators, product manufacturers, regulatory agencies, and researchers regarding adjuvant toxicity to honey bees with the goal of reducing risks that adjuvants pose to honey bees and other beneficial insects.
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Affiliation(s)
- Brandon Shannon
- Department of Entomology, The Ohio State University, 1680 Madison Avenue, Wooster, OH, USA
| | - Hongyoung Jeon
- Application Technology Research Unit, Agricultural Research Service, United States Department of Agriculture, 1680 Madison Avenue, Wooster, OH, USA
| | - Reed M Johnson
- Department of Entomology, The Ohio State University, 1680 Madison Avenue, Wooster, OH, USA
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Shannon B, Walker E, Johnson RM. Toxicity of spray adjuvants and tank mix combinations used in almond orchards to adult honey bees (Apis mellifera). J Econ Entomol 2023; 116:1467-1480. [PMID: 37656894 PMCID: PMC10564267 DOI: 10.1093/jee/toad161] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/11/2023] [Accepted: 08/01/2023] [Indexed: 09/03/2023]
Abstract
Commercial beekeepers transporting honey bees across the United States to provide almond pollination services have reported honey bee deaths, possibly due to pesticide applications made during crop bloom. Pesticides are often applied as "tank mixes", or mixtures of fungicides and insecticides combined into a single application. Spray adjuvants are often added to tank mixes to improve the application characteristics of a pesticide and include spreaders, stickers, or surfactants. The goal of this research was to determine toxicity of adjuvants to adult worker honey bees, both when applied alone and in adjuvant-pesticide tank mixtures. Field-relevant combinations of formulated products were applied to 3-day-old adult worker honey bees using a Potter Spray Tower, and mortality was assessed 48 h following exposure. Adjuvants tested included Activator-90, Attach, Choice Weather Master, Cohere, Dyne-Amic, Induce, Kinetic, LI 700, Liberate, Nu-Film P, PHT Latron B-1956, and Surf-90; fungicides tested include Luna Sensation (Fluopyram and Trifloxystrobin), Pristine (Pyraclostrobin and Boscalid), Tilt (Propiconazole), and Vangard (Cyprodinil), and insecticides tested include Altacor (Chlorantraniliprole), Intrepid 2F (Methoxyfenozide), and a positive control Mustang Maxx (Zeta-cypermethrin). Results demonstrated that exposure to some adjuvants causes acute honey bee mortality at near-field application rates, both when applied alone and in combination with pesticides. Some adjuvant-pesticide combinations demonstrated increased toxicity compared with the adjuvant alone, while others demonstrated decreased toxicity. A better understanding of adjuvant and adjuvant-pesticide tank mixture toxicity to honey bees will play a key role in informing "Best Management Practices" for pesticide applicators using spray adjuvants during bloom when honey bee exposure is likely.
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Affiliation(s)
- Brandon Shannon
- Department of Entomology, The Ohio State University, 1680 Madison Avenue, Wooster, OH, USA
| | - Emily Walker
- Department of Entomology, The Ohio State University, 1680 Madison Avenue, Wooster, OH, USA
| | - Reed M Johnson
- Department of Entomology, The Ohio State University, 1680 Madison Avenue, Wooster, OH, USA
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Wu WY, Liao LH, Lin CH, Johnson RM, Berenbaum MR. Effects of pesticide-adjuvant combinations used in almond orchards on olfactory responses to social signals in honey bees (Apis mellifera). Sci Rep 2023; 13:15577. [PMID: 37730836 PMCID: PMC10511525 DOI: 10.1038/s41598-023-41818-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 08/31/2023] [Indexed: 09/22/2023] Open
Abstract
Exposure to agrochemical sprays containing pesticides and tank-mix adjuvants has been implicated in post-bloom mortality, particularly of brood, in honey bee colonies brought into California almond orchards for pollination. Although adjuvants are generally considered to be biologically inert, some adjuvants have exhibited toxicity and sublethal effects, including decreasing survival rates of next-generation queens. Honey bees have a highly developed olfactory system to detect and discriminate among social signals. To investigate the impact of pesticide-adjuvant combinations on honey bee signal perception, we performed electroantennography assays to assess alterations in their olfactory responsiveness to the brood ester pheromone (BEP), the volatile larval pheromone β-ocimene, and the alarm pheromone 2-heptanone. These assays aimed to uncover potential mechanisms underlying changes in social behaviors and reduced brood survival after pesticide exposure. We found that combining the adjuvant Dyne-Amic with the fungicide Tilt (propiconazole) and the insecticide Altacor (chlorantraniliprole) synergistically enhanced olfactory responses to three concentrations of BEP and as well exerted dampening and compensatory effects on responses to 2-heptanone and β-ocimene, respectively. In contrast, exposure to adjuvant alone or the combination of fungicide and insecticide had no effect on olfactory responses to BEP at most concentrations but altered responses to β-ocimene and 2-heptanone. Exposure to Dyne-Amic, Altacor, and Tilt increased BEP signal amplitude, indicating potential changes in olfactory receptor sensitivity or sensilla permeability to odorants. Given that, in a previous study, next-generation queens raised by nurses exposed to the same treated pollen experienced reduced survival, these new findings highlight the potential disruption of social signaling in honey bees and its implications for colony reproductive success.
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Affiliation(s)
- Wen-Yen Wu
- Department of Entomology, University of Illinois Urbana-Champaign, 505 S. Goodwin Avenue, Urbana, IL, 61801, USA
| | - Ling-Hsiu Liao
- Department of Entomology, University of Illinois Urbana-Champaign, 505 S. Goodwin Avenue, Urbana, IL, 61801, USA.
| | - Chia-Hua Lin
- Department of Entomology, Rothenbuhler Honey Bee Research Laboratory, The Ohio State University, 2501 Carmack Road, Columbus, OH, 43210, USA
| | - Reed M Johnson
- Department of Entomology, Rothenbuhler Honey Bee Research Laboratory, The Ohio State University, 2501 Carmack Road, Columbus, OH, 43210, USA
| | - May R Berenbaum
- Department of Entomology, University of Illinois Urbana-Champaign, 505 S. Goodwin Avenue, Urbana, IL, 61801, USA
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Lin CH, Suresh S, Matcham E, Monagan P, Curtis H, Richardson RT, Johnson RM. Soybean is a Common Nectar Source for Honey Bees (Hymenoptera: Apidae) in a Midwestern Agricultural Landscape. J Econ Entomol 2022; 115:1846-1851. [PMID: 36130184 DOI: 10.1093/jee/toac140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Indexed: 06/15/2023]
Abstract
Large-scale soybean [Glycine max (L.) Merr.] cultivation has substantially transformed the Midwestern landscape in recent decades. Floral nectar produced by immense fields of soybeans has the potential to influence foraging ecology and resource accumulation of honey bee (Apis mellifera L.) colonies. In this study, we combined microscopic and molecular pollen analysis of honey samples with waggle dance inference of spatial foraging patterns to demonstrate that honey bees routinely forage on soybeans in Ohio. In analyzing honey samples from across the state, we found ubiquitous presence of soybean pollen in honey collected from agricultural lands during soybean bloom. The abundance of soybean pollen in honey increased with the amount of soybean fields surrounding the apiaries. Honey bee waggle dances recorded during soybean bloom revealed that honey bees preferred soybean fields for foraging over other habitat types. With these results, future research efforts aimed at enhancing mutual interactions between soybeans and honey bees may represent an unexplored pathway for increasing soybean production while supporting honey bees and other pollinators in the surrounding landscape.
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Affiliation(s)
- Chia-Hua Lin
- Department of Entomology, The Ohio State University, Rothenbuhler Honey Bee Research Laboratory, 2501 Carmack Road, Columbus, OH 43210, USA
| | - Sreelakshmi Suresh
- Department of Entomology, The Ohio State University, Rothenbuhler Honey Bee Research Laboratory, 2501 Carmack Road, Columbus, OH 43210, USA
| | - Emma Matcham
- Department of Horticulture and Crop Science, The Ohio State University, 2021 Coffey Road, Columbus, OH 43210, USA
- Department of Agronomy, University of Florida, Gainesville, FL 32605, USA
| | - Paityn Monagan
- Metro Early College High School, 1929 Kenny Road, Columbus, OH 43210, USA
| | - Hailey Curtis
- Department of Entomology, The Ohio State University, Rothenbuhler Honey Bee Research Laboratory, 2501 Carmack Road, Columbus, OH 43210, USA
| | - Rodney T Richardson
- Department of Entomology, The Ohio State University, Rothenbuhler Honey Bee Research Laboratory, 2501 Carmack Road, Columbus, OH 43210, USA
| | - Reed M Johnson
- Department of Entomology, Ohio Agricultural Research and Development Center, The Ohio State University, 1680 Madison Avenue, Wooster, OH 44691, USA
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Sanz Cortes M, Corroenne R, Sangi-Haghpeykar H, Orman G, Shetty A, Castillo J, Castillo H, Johnson RM, Shamshirsaz A, Belfort MA, Whitehead W, Meoded A. Association between ambulatory skills and diffusion tensor imaging of corpus callosal white matter in infants with spina bifida. Ultrasound Obstet Gynecol 2022; 60:657-665. [PMID: 35638229 DOI: 10.1002/uog.24958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 05/03/2022] [Accepted: 05/19/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES To assess brain white matter using diffusion tensor imaging (DTI) at 1 year of age in infants diagnosed with open neural tube defect (ONTD) and explore the association of DTI parameters with ambulatory skills at 30 months of age. METHODS Magnetic resonance imaging (MRI) was performed at an average of 12 months of age and included an echo planar axial DTI sequence with diffusion gradients along 20 non-collinear directions. TORTOISE software was used to correct DTI raw data for motion artifacts, and DtiStudio, DiffeoMap and RoiEditor were used for further postprocessing. DTI data were analyzed in terms of fractional anisotropy (FA), trace, radial diffusivity and axial diffusivity. These parameters reflect the integrity and maturation of white-matter motor pathways. At 30 months of age, ambulation status was evaluated by a developmental pediatrician, and infants were classified as ambulatory if they were able to walk independently with or without orthoses or as non-ambulatory if they could not. Linear mixed-effects method was used to examine the association between study outcomes and study group. Possible confounders were sought, and analyses were adjusted for age at MRI scan and ventricular size by including them in the regression model as covariates. RESULTS Twenty patients with ONTD were included in this study, including three cases that underwent postnatal repair and 17 cases that underwent prenatal repair. There were five ambulatory and 15 non-ambulatory infants evaluated at a mean age of 31.5 ± 5.7 months. MRI was performed at 50.3 (2-132.4) weeks postpartum. When DTI analysis results were compared between ambulatory and non-ambulatory infants, significant differences were observed in the corpus callosum (CC). Compared with non-ambulatory infants, ambulatory infants had increased FA in the splenium (0.62 (0.48-0.75) vs 0.41 (0.34-0.49); P = 0.01, adjusted P = 0.02), genu (0.64 (0.47-0.80) vs 0.47 (0.35-0.61); P = 0.03, adjusted P = 0.004) and body (0.55 (0.45-0.65) vs 0.40 (0.35-0.46), P = 0.01, adjusted P = 0.01). Reduced trace was observed in the CC of ambulatory children at the level of the splenium (0.0027 (0.0018-0.0037) vs 0.0039 (0.0034-0.0044) mm2 /s; P = 0.04, adjusted P = 0.03) and genu (0.0029 (0.0020-0.0038) vs 0.0039 (0.0033-0.0045) mm2 /s; P = 0.04, adjusted P = 0.01). In addition, radial diffusivity was reduced in the CC of the ambulatory children at the level of the splenium (0.00057 (0.00025-0.00089) vs 0.0010 (0.00084-0.00120) mm2 /s; P = 0.02, adjusted P = 0.02) and the genu (0.00058 (0.00028-0.00088) vs 0.0010 (0.00085-0.00118) mm2 /s; P = 0.02, adjusted P = 0.02). There were no differences in axial diffusivity between ambulatory and non-ambulatory children. CONCLUSION This study demonstrates a significant association between white matter integrity of connecting fibers of the corpus callosum, as assessed by DTI, and ambulatory skills at 30 months of age in infants with ONTD. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- M Sanz Cortes
- Department of Obstetrics and Gynecology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - R Corroenne
- Department of Obstetrics and Gynecology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - H Sangi-Haghpeykar
- Department of Obstetrics and Gynecology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - G Orman
- Department of Pediatric Radiology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - A Shetty
- Department of Obstetrics and Gynecology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - J Castillo
- Department of Pediatrics, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - H Castillo
- Department of Pediatrics, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - R M Johnson
- Department of Obstetrics and Gynecology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - A Shamshirsaz
- Department of Obstetrics and Gynecology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - M A Belfort
- Department of Obstetrics and Gynecology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - W Whitehead
- Department of Neurosurgery, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
| | - A Meoded
- Department of Pediatric Radiology, Texas Children's Hospital & Baylor College of Medicine, Houston, TX, USA
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Walker EK, Brock GN, Arvidson RS, Johnson RM. Acute Toxicity of Fungicide-Insecticide-Adjuvant Combinations Applied to Almonds During Bloom on Adult Honey Bees. Environ Toxicol Chem 2022; 41:1042-1053. [PMID: 35060643 PMCID: PMC9313819 DOI: 10.1002/etc.5297] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 08/06/2021] [Accepted: 01/10/2022] [Indexed: 05/26/2023]
Abstract
Beekeepers report significant honey bee deaths during and after almond bloom. These losses pose a major problem for the California almond industry because of its dependence on honey bees as pollinators. The present study aimed to determine if combinations of pesticides applied during almond bloom during daylight hours were a possible explanation for these losses. In this study we aimed to mimic the spray application route of exposure to pesticides using a Potter Spray Tower to treat adult honey bees with commonly encountered pesticides and pesticide combinations at multiples of the maximum recommended field application rates. Tested insecticides included Altacor® and Intrepid®, and tested fungicides included Tilt®, Pristine®, Luna Sensation®, and Vangard®. Synergistic toxicity was observed when the fungicide Tilt (active ingredient propiconazole) was applied with the insecticide Altacor (chlorantraniliprole), though neither caused significant mortality when applied independently. The study also looked at the effect of adding a spray adjuvant, Dyne-Amic®, to pesticide mixtures. Dyne-Amic was toxic to honey bees at concentrations above the maximum recommended field application rate, and toxicity was increased when combined with the fungicide Pristine (pyraclostrobin and boscalid). Addition of Dyne-Amic also increased toxicity of the Tilt and Altacor combination. These results suggest that application of Altacor and Tilt in combination with an adjuvant at the recommended field application rates could cause mortality in adult honey bees. These findings highlight a potential explanation for honey bee losses around almond bloom, emphasize that the safety of spray adjuvants to bees should not be assumed, and provide support for recommendations to protect bees from pesticides through application at night when bees are not foraging. Environ Toxicol Chem 2022;41:1042-1053. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Affiliation(s)
- Emily K. Walker
- Environmental Sciences Graduate ProgramThe Ohio State UniversityColumbusOhioUSA
| | - Guy N. Brock
- Department of Biomedical InformaticsThe Ohio State UniversityColumbusOhioUSA
| | - Ryan S. Arvidson
- Departments of Biology and ChemistryThe College of WoosterWoosterOhioUSA
| | - Reed M. Johnson
- Department of EntomologyThe Ohio State UniversityWoosterOhioUSA
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10
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Ricke DF, Lin CH, Johnson RM. Pollen Treated with a Combination of Agrochemicals Commonly Applied During Almond Bloom Reduces the Emergence Rate and Longevity of Honey Bee (Hymenoptera: Apidae) Queens. J Insect Sci 2021; 21:5. [PMID: 34723328 PMCID: PMC8559157 DOI: 10.1093/jisesa/ieab074] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Indexed: 06/13/2023]
Abstract
Honey bee (Apis mellifera L.) colonies that pollinate California's almond orchards are often exposed to mixtures of agrochemicals. Although agrochemicals applied during almond bloom are typically considered bee-safe when applied alone, their combined effects to honey bees are largely untested. In recent years, beekeepers providing pollination services to California's almond orchards have reported reductions in queen quality during and immediately after bloom, raising concerns that pesticide exposure may be involved. Previous research identified a synergistic effect between the insecticide active ingredient chlorantraniliprole and the fungicide active ingredient propiconazole to lab-reared worker brood, but their effects to developing queens are unknown. To test the individual and combined effects of these pesticides on the survival and emergence of developing queens, we fed worker honey bees in closed queen rearing boxes with pollen artificially contaminated with formulated pesticides containing these active ingredients as well as the spray adjuvant Dyne-Amic, which contains both organosilicone and alkyphenol ethoxylate. The translocation of pesticides from pesticide-treated pollen into the royal jelly secretions of nurse bees was also measured. Despite consistently low levels of all pesticide active ingredients in royal jelly, the survival of queens from pupation to 7 d post-emergence were reduced in queens reared by worker bees fed pollen containing a combination of formulated chlorantraniliprole (Altacor), propiconazole (Tilt), and Dyne-Amic, as well as the toxic standard, diflubenzuron (Dimilin 2L), applied in isolation. These results support recommendations to protect honey bee health by avoiding application of pesticide tank-mixes containing insecticides and adjuvants during almond bloom.
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Affiliation(s)
- Dylan F Ricke
- Department of Entomology, The Ohio State University, Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, OH 44691, USA
| | - Chia-Hua Lin
- Department of Entomology, The Ohio State University, Rothenbuhler Honey Bee Research Laboratory, 2501 Carmack Rd., Columbus, OH 43210, USA
| | - Reed M Johnson
- Department of Entomology, The Ohio State University, Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, OH 44691, USA
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11
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Lin C, Sponsler DB, Richardson RT, Watters HD, Glinski DA, Henderson WM, Minucci JM, Lee EH, Purucker ST, Johnson RM. Honey Bees and Neonicotinoid-Treated Corn Seed: Contamination, Exposure, and Effects. Environ Toxicol Chem 2021; 40:1212-1221. [PMID: 33289922 PMCID: PMC8048971 DOI: 10.1002/etc.4957] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 03/09/2020] [Accepted: 12/01/2020] [Indexed: 05/05/2023]
Abstract
Most corn (Zea mays) seeds planted in the United States in recent years are coated with a seed treatment containing neonicotinoid insecticides. Abrasion of the seed coating generates insecticide-laden planter dust that disperses through the landscape during corn planting and has resulted in many "bee-kill" incidents in North America and Europe. We investigated the linkage between corn planting and honey bee colony success in a region dominated by corn agriculture. Over 3 yr we consistently observed an increased presence of corn seed treatment insecticides in bee-collected pollen and elevated worker bee mortality during corn planting. Residues of seed treatment neonicotinoids, clothianidin and thiamethoxam, detected in pollen positively correlated with cornfield area surrounding the apiaries. Elevated worker mortality was also observed in experimental colonies fed field-collected pollen containing known concentrations of corn seed treatment insecticides. We monitored colony growth throughout the subsequent year in 2015 and found that colonies exposed to higher insecticide concentrations exhibited slower population growth during the month of corn planting but demonstrated more rapid growth in the month following, though this difference may be related to forage availability. Exposure to seed treatment neonicotinoids during corn planting has clear short-term detrimental effects on honey bee colonies and may affect the viability of beekeeping operations that are dependent on maximizing colony size in the springtime. Environ Toxicol Chem 2021;40:1212-1221. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Affiliation(s)
- Chia‐Hua Lin
- Department of Entomology, Ohio Agricultural Research and Development CenterThe Ohio State UniversityWoosterOhioUSA
| | - Douglas B. Sponsler
- Department of Entomology, Ohio Agricultural Research and Development CenterThe Ohio State UniversityWoosterOhioUSA
| | - Rodney T. Richardson
- Department of Entomology, Ohio Agricultural Research and Development CenterThe Ohio State UniversityWoosterOhioUSA
| | - Harold D. Watters
- Department of ExtensionThe Ohio State UniversityBellefontaineOhioUSA
| | | | - W. Matthew Henderson
- Center for Environmental Measurement and ModelingUS Environmental Protection AgencyAthensGeorgia
| | - Jeffrey M. Minucci
- Center for Computational Toxicity and ExposureUS Environmental Protection Agency, Research Triangle ParkNorth Carolina
| | - E. Henry Lee
- Center for Public Health and Environmental AssessmentUS Environmental Protection AgencyCorvallisOregon
| | - S. Thomas Purucker
- Center for Computational Toxicity and ExposureUS Environmental Protection Agency, Research Triangle ParkNorth Carolina
| | - Reed M. Johnson
- Department of Entomology, Ohio Agricultural Research and Development CenterThe Ohio State UniversityWoosterOhioUSA
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12
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Wilson BE, White WH, Richard RT, Johnson RM. Population Trends of the Sugarcane Borer (Lepidoptera: Crambidae) in Louisiana Sugarcane. Environ Entomol 2020; 49:1455-1461. [PMID: 33128561 DOI: 10.1093/ee/nvaa127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Indexed: 06/11/2023]
Abstract
The sugarcane borer, Diatraea saccharalis (F.) (Lepidoptera: Crambidae), is the primary pest of sugarcane, Saccharum spp., in Louisiana. Spring populations are not considered economically damaging, but quantifying infestations can provide an indication of the spatial and temporal character of the damaging summer populations. Statewide surveys quantified the density of sugarcane tillers killed by D. saccharalis (deadhearts) from sugarcane fields across the state in spring from 2003 to 2020. Deadheart density varied greatly among years with a high of 1,318/ha in 2003 to a low of 0/ha in 2018. Linear regressions of the 3-yr rolling average showed declines in spring D. saccharalis populations and the percentage of acreage treated with insecticides over 17 yr. Weather factors including minimum winter temperatures and average spring temperatures were poor predictors of D. saccharalis populations. Only total precipitation in the month of April was positively correlated with numbers of deadhearts per hectare. Results suggest overwintering mortality is not a key factor influencing populations of the first generation of D. saccharalis in Louisiana. Total precipitation in the month of July was positively associated with percentage of treated acreage. Spring deadheart density was directly related to percentage of acreage treated with insecticides during the summer. Quantifying first-generation D. saccharalis populations by recording deadheart density can aid in predicting pest pressure later in the growing season.
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Affiliation(s)
- B E Wilson
- Louisiana State University Agricultural Center, Sugarcane Research Station, St. Gabriel, LA
| | - W H White
- USDA, ARS Sugarcane Research Laboratory, Houma, LA
| | - R T Richard
- USDA, ARS Sugarcane Research Laboratory, Houma, LA
| | - R M Johnson
- USDA, ARS Sugarcane Research Laboratory, Houma, LA
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13
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Richardson RT, Eaton TD, Lin CH, Cherry G, Johnson RM, Sponsler DB. Application of plant metabarcoding to identify diverse honeybee pollen forage along an urban-agricultural gradient. Mol Ecol 2020; 30:310-323. [PMID: 33098151 DOI: 10.1111/mec.15704] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 10/08/2020] [Accepted: 10/09/2020] [Indexed: 01/10/2023]
Abstract
Understanding animal foraging ecology requires large sample sizes spanning broad environmental and temporal gradients. For pollinators, this has been hampered by the laborious nature of morphologically identifying pollen. Identifying pollen from urban environments is particularly difficult due to the presence of diverse ornamental species associated with consumer horticulture. Metagenetic pollen analysis represents a potential solution to this issue. Building upon prior laboratory and bioinformatic methods, we applied quantitative multilocus metabarcoding to characterize the foraging ecology of honeybee colonies situated in urban, suburban, mixed suburban-agricultural and rural agricultural sites in central Ohio, USA. In cross-validating a subset of our metabarcoding results using microscopic palynology, we find strong concordance between the molecular and microscopic methods. Our results suggest that forage from the agricultural site exhibited decreased taxonomic diversity and temporal turnover relative to the urban and suburban sites, though the generalization of this observation will require replication across additional sites and cities. Our work demonstrates the power of honeybees as environmental samplers of floral community composition at large spatial scales, aiding in the distinction of taxa characteristically associated with urban or agricultural land use from those distributed ubiquitously across the sampled landscapes. Observed patterns of high forage diversity and compositional turnover in our more urban sites are likely reflective of the fine-grain heterogeneity and high beta diversity of urban floral landscapes at the scale of honeybee foraging. This provides guidance for future studies investigating how relationships between urbanization and measures of pollinator health are mediated by variation in floral resource dynamics across landscapes.
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Affiliation(s)
- Rodney T Richardson
- Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, USA
| | - Tyler D Eaton
- Department of Entomology, Ohio State University, Wooster, OH, USA
| | - Chia-Hua Lin
- Department of Entomology, Ohio State University, Wooster, OH, USA
| | - Garrett Cherry
- Department of Entomology, Ohio State University, Wooster, OH, USA
| | - Reed M Johnson
- Department of Entomology, Ohio State University, Wooster, OH, USA
| | - Douglas B Sponsler
- Department of Animal Ecology and Tropical Biology, University of Würzburg, Würzburg, Germany.,Department of Botany, The Academy of Natural Sciences of Drexel University, Philadelphia, PA, USA
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14
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Corroenne R, Yepez M, Pyarali M, Johnson RM, Whitehead WE, Castillo HA, Castillo J, Mehollin-Ray AR, Espinoza J, Shamshirsaz AA, Nassr AA, Belfort MA, Cortes MS. Prenatal predictors of motor function in children with open spina bifida: a retrospective cohort study. BJOG 2020; 128:384-391. [PMID: 32975898 DOI: 10.1111/1471-0528.16538] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/16/2020] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To identify predictors for intact motor function (MF) at birth and at 12 months of life in babies with prenatally versus postnatally repaired open spina bifida (OSB). DESIGN Retrospective cohort study. SETTING Texas Children's Hospital, 2011-2018. POPULATION Patients who underwent either prenatal or postnatal OSB repair. METHODS Prenatal MF of the lower extremities was evaluated by ultrasound following a metameric distribution at the time of diagnosis (US1), 6 weeks postoperatively (or 6 weeks after initial evaluation in postnatally repaired cases) (US2) and at the last ultrasound before delivery (US3). At birth and at 12 months, MF was assessed clinically. Intact MF (S1) was defined as the observation of plantar flexion of the ankle. Results from logistic regression analysis are expressed as odds ratios (95% confidence intervals, P values). RESULTS A total of 127 patients were included: 93 with prenatal repair (51 fetoscopic; 42 open hysterotomy repair) and 34 with postnatal repair. In the prenatal repair group, predictors for intact MF at birth and at 12 months included: absence of clubfeet (OR 11.3, 95% CI 3.2-39.1, P < 0.01; OR 10.8 95% CI 2.4-47.6, P < 0.01); intact MF at US1 (OR 19.7, 95% CI 5.0-76.9, P < 0.01; OR 8.7, 95% CI 2.0-38.7, P < 0.01); intact MF at US2 (OR 22, 95% CI 6.5-74.2, P < 0.01; OR 13.5, 95% 3.0-61.4, P < 0.01); intact MF at US3 (OR 13.7, 95% CI 3.4-55.9, P < 0.01; OR 12.6, 95% CI 2.5-64.3, P < 0.01); and having a flat lesion (OR 11.2, 95% CI 2.4-51.1, P < 0.01; OR 4.1, 95% CI 1.1-16.5, P = 0.04). In the postnatal repair group, the only predictor of intact MF at 12 months was having intact MF at birth (OR 15.2, 95% CI 2.0-113.3, P = 0.03). CONCLUSIONS The detection of intact MF in utero from mid-gestation to delivery predicts intact MF at birth and at 12 months in babies who undergo prenatal OSB repair. TWEETABLE ABSTRACT Detection of intact motor function in utero predicts intact motor function at birth and at 1 year in fetuses who undergo prenatal OSB repair.
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Affiliation(s)
- R Corroenne
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - M Yepez
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - M Pyarali
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - R M Johnson
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - W E Whitehead
- Department of Neurosurgery, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - H A Castillo
- Department of Pediatrics, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - J Castillo
- Department of Pediatrics, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - A R Mehollin-Ray
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA.,Department of Radiology, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - J Espinoza
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - A A Shamshirsaz
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - A A Nassr
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - M A Belfort
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
| | - M S Cortes
- Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine & Texas Children's Hospital, Houston, TX, USA
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15
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Wilson BE, Beuzelin JM, Richard RT, Johnson RM, Gravois KA, White WH. West Indian Canefly (Hemiptera: Delphacidae): An Emerging Pest of Louisiana Sugarcane. J Econ Entomol 2020; 113:263-272. [PMID: 31751463 DOI: 10.1093/jee/toz284] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Indexed: 06/10/2023]
Abstract
The West Indian canefly, Saccharosydne saccharivora (Westwood) (Hemiptera: Delphacidae), is a sporadic pest of sugarcane in Louisiana which has recently emerged as a more consistent threat with outbreaks occurring in 2012, 2016, 2017, and 2019. Surveys of commercial fields in 2016 revealed that S. saccharivora infestations were present throughout Louisiana sugarcane and populations peaked in mid-June before declining. High minimum winter temperatures are generally associated with S. saccharivora outbreaks. Six insecticide evaluations demonstrated effective control with several insecticides including λ-cyhalothrin, flupyradifurone, acetamiprid, and imidacloprid. In five of the six insecticide trials, S. saccharivora infestations had substantially declined by 21 d after treatment. Effects of insecticidal control of S. saccharivora on sugar yields were detected in one of four small plot trials in which yield data were collected. Linear regression revealed S. saccharivora cumulative insect days in a grid sampling study were inversely associated with sugar yields. Results from these collective experiments suggest impacts on sugar yields are influenced by pest density and infestation duration. Differences were detected in numbers of S. saccharivora nymphs and adults as well as sooty mold coverage among commercial sugarcane cultivars with more than twofold increases in the most susceptible compared to resistant cultivars. The research presented herein documents the impact of S. saccharivora to Louisiana sugarcane and provides important ground work for developing effective pest management strategies. Future research efforts should aim to identify ecological factors influencing population dynamics, varietal preferences, and economic thresholds.
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Affiliation(s)
- B E Wilson
- Louisiana State University Agricultural Center, Sugarcane Research Station, St. Gabriel, LA
| | - J M Beuzelin
- Institute of Food and Agricultural Sciences, Everglades Research and Education Center, University of Florida, Belle Glade, FL
| | - R T Richard
- USDA, ARS Sugarcane Research Laboratory, Houma, LA
| | - R M Johnson
- USDA, ARS Sugarcane Research Laboratory, Houma, LA
| | - K A Gravois
- Louisiana State University Agricultural Center, Sugarcane Research Station, St. Gabriel, LA
| | - W H White
- USDA, ARS Sugarcane Research Laboratory, Houma, LA
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16
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Richardson RT, Sponsler DB, McMinn‐Sauder H, Johnson RM. MetaCurator: A hidden Markov model‐based toolkit for extracting and curating sequences from taxonomically‐informative genetic markers. Methods Ecol Evol 2019. [DOI: 10.1111/2041-210x.13314] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Douglas B. Sponsler
- Department of Entomology Pennsylvania State University University Park PA USA
- Department of Botany The Academy of Natural Sciences of Drexel University Philadelphia PA USA
| | | | - Reed M. Johnson
- Department of Entomology The Ohio State University Columbus OH USA
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17
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Bengtsson-Palme J, Richardson RT, Meola M, Wurzbacher C, Tremblay ÉD, Thorell K, Kanger K, Eriksson KM, Bilodeau GJ, Johnson RM, Hartmann M, Nilsson RH. Metaxa2 Database Builder: enabling taxonomic identification from metagenomic or metabarcoding data using any genetic marker. Bioinformatics 2019; 34:4027-4033. [PMID: 29912385 PMCID: PMC6247927 DOI: 10.1093/bioinformatics/bty482] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 06/12/2018] [Indexed: 11/25/2022] Open
Abstract
Motivation Correct taxonomic identification of DNA sequences is central to studies of biodiversity using both shotgun metagenomic and metabarcoding approaches. However, no genetic marker gives sufficient performance across all the biological kingdoms, hampering studies of taxonomic diversity in many groups of organisms. This has led to the adoption of a range of genetic markers for DNA metabarcoding. While many taxonomic classification software tools can be re-trained on these genetic markers, they are often designed with assumptions that impair their utility on genes other than the SSU and LSU rRNA. Here, we present an update to Metaxa2 that enables the use of any genetic marker for taxonomic classification of metagenome and amplicon sequence data. Results We evaluated the Metaxa2 Database Builder on 11 commonly used barcoding regions and found that while there are wide differences in performance between different genetic markers, our software performs satisfactorily provided that the input taxonomy and sequence data are of high quality. Availability and implementation Freely available on the web as part of the Metaxa2 package at http://microbiology.se/software/metaxa2/. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Johan Bengtsson-Palme
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA.,Department of Infectious Diseases, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 10, SE-41346 Gothenburg, Sweden.,Centre for Antibiotic Resistance Research (CARe) at University of Gothenburg, SE-40530 Gothenburg, Sweden
| | - Rodney T Richardson
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, Wooster, OH, USA
| | - Marco Meola
- Fermentation Organisms, Methods Development and Analytics, Agroscope, CH-3003 Bern, Switzerland
| | - Christian Wurzbacher
- Department of Biological and Environmental Sciences, University of Gothenburg, SE-40530 Gothenburg, Sweden.,Chair of Urban Water Systems Engineering, Technical University of Munich, Garching, Germany
| | - Émilie D Tremblay
- Canadian Food Inspection Agency, Ottawa Laboratory Fallowfield, Ottawa, ON, Canada
| | - Kaisa Thorell
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Kärt Kanger
- Department of Geography, Institute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia
| | - K Martin Eriksson
- Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Guillaume J Bilodeau
- Canadian Food Inspection Agency, Ottawa Laboratory Fallowfield, Ottawa, ON, Canada
| | - Reed M Johnson
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, Wooster, OH, USA
| | - Martin Hartmann
- Forest Soils and Biogeochemistry, Swiss Federal Research Institute WSL, Birmensdorf, Switzerland.,Sustainable Agroecosystems, Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - R Henrik Nilsson
- Department of Biological and Environmental Sciences, University of Gothenburg, SE-40530 Gothenburg, Sweden.,Gothenburg Global Biodiversity Centre, SE-405 30 Göteborg, Sweden
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18
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Richardson RT, Curtis HR, Matcham EG, Lin C, Suresh S, Sponsler DB, Hearon LE, Johnson RM. Quantitative multi‐locus metabarcoding and waggle dance interpretation reveal honey bee spring foraging patterns in Midwest agroecosystems. Mol Ecol 2019; 28:686-697. [DOI: 10.1111/mec.14975] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 11/09/2018] [Accepted: 11/19/2018] [Indexed: 12/17/2022]
Affiliation(s)
| | - Hailey R. Curtis
- College of Veterinary Medicine The Ohio State University Columbus Ohio
| | - Emma G. Matcham
- Department of Horticulture and Crop Science The Ohio State University Columbus Ohio
| | - Chia‐Hua Lin
- Department of Entomology The Ohio State University Columbus Ohio
| | - Sreelakshmi Suresh
- Department of Evolution, Ecology, and Organismal Biology The Ohio State University Columbus Ohio
| | - Douglas B. Sponsler
- Department of Entomology Pennsylvania State University University Park Pennsylvania
| | - Luke E. Hearon
- Department of Entomology The Ohio State University Columbus Ohio
| | - Reed M. Johnson
- Department of Entomology The Ohio State University Columbus Ohio
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19
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Yuan Y, Yost SE, Chang CW, Yoh KE, Johnson RM, Schmolze D, Liang J, Hutchinson KE. Abstract PD5-07: Comprehensive profiling of poor-risk paired primary and recurrent triple-negative breast cancers reveals immune phenotype shifts. Cancer Res 2019. [DOI: 10.1158/1538-7445.sabcs18-pd5-07] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Prognosis for triple-negative breast cancer (TNBC) patients remains poor, due in part to the lack of effective targeted therapies in the advanced setting. Emerging clinical data indicates reduced efficacy of immune checkpoint inhibitors in heavily pre-treated TNBC, but the underlying mechanisms are poorly understood. To better understand the immune phenotypic evolution of paired TNBCs, we studied the genomic and transcriptomic profiles of tumors from patients undergoing treatment for TNBC.
Methods: We analyzed primary and recurrent TNBCs from 55 poor-risk patients, including 44 paired primary-metastatic samples and 11 paired metastatic tumors. FoundationOne® and RNAseq was successful on 89 specimens and 97 specimens, respectively. In addition to somatic alterations, FoundationOne® provided tumor mutational burden (TMB). From RNAseq, we ascertained the TNBC molecular subtypes, and the mRNA expression of immune-related genes. Stromal tumor-infiltrating lymphocytes (stromal TILs), recurrence-free survival, and overall survival were also studied.
Results: From FoundationOne® sequencing, a mutational landscape typical of TNBCs was observed across both primary and recurrent disease specimens, with TP53 mutated in 82.0% of specimens, and BRCA1 and BRCA2 mutated in 4.5% and 16.9% of specimens, respectively. Sample profiles revealed minimal shifts in copy number alterations and TMB over time, however, notable TNBC subtype shifts were observed between primary and recurrent tumors. These included an increase in the Lehmann/Pietenpol-defined basal-like 1 phenotype (BL1, 12.8% to 20.9%), an increase in the mesenchymal phenotype (M, 12.8% to 20.9%), and a significant decrease in the immunomodulatory phenotype (IM, 27.1% to 2.3%). Similarly, tumors exhibited a downward shift in gene expression delineating the Burstein-defined basal-like immune-activated phenotype (BLIA, 37.0% to 14.3%). Composite expression of immunomodulatory gene signatures representative of Th1/Th2 responses, IFNg-related inflammation, M1/M2 macrophage activation and suppression, etc., was decreased in the recurrent tumors compared to the primaries (p = 0.01), and histopathology-derived percent stromal TILs were significantly decreased in the recurrent TNBCs (p = 0.02). However, higher stromal TILs (≥30%) were not associated with improved overall survival when measured in primary specimens (p = 0.15), or with the time from relapse to death when measured in recurrent specimens (p = 0.65) in this cohort of immunotherapy-naïve patients.
Conclusion: In this retrospective study of paired TNBCs, significant transcriptomic phenotype shifts were observed as patients progressed, while only minor genomic shifts were seen. Selective immune profiling showed significantly reduced TILs and immune-activating gene expression signatures in recurrent TNBCs, which may explain the lack of efficacy of immunotherapeutic agents in heavily pretreated TNBCs. Further studies are ongoing to understand the proteomic landscape shifts in TNBCs over time and to identify novel targeted agents appropriate for recurrent disease.
Citation Format: Yuan Y, Yost SE, Chang C-W, Yoh KE, Johnson RM, Schmolze D, Liang J, Hutchinson KE. Comprehensive profiling of poor-risk paired primary and recurrent triple-negative breast cancers reveals immune phenotype shifts [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD5-07.
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Affiliation(s)
- Y Yuan
- City of Hope National Medical Center, Duarte, CA; Genentech, South San Francisco, CA
| | - SE Yost
- City of Hope National Medical Center, Duarte, CA; Genentech, South San Francisco, CA
| | - C-W Chang
- City of Hope National Medical Center, Duarte, CA; Genentech, South San Francisco, CA
| | - KE Yoh
- City of Hope National Medical Center, Duarte, CA; Genentech, South San Francisco, CA
| | - RM Johnson
- City of Hope National Medical Center, Duarte, CA; Genentech, South San Francisco, CA
| | - D Schmolze
- City of Hope National Medical Center, Duarte, CA; Genentech, South San Francisco, CA
| | - J Liang
- City of Hope National Medical Center, Duarte, CA; Genentech, South San Francisco, CA
| | - KE Hutchinson
- City of Hope National Medical Center, Duarte, CA; Genentech, South San Francisco, CA
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Poffenberger MC, Metcalfe-Roach A, Aguilar E, Chen J, Hsu BE, Wong AH, Johnson RM, Flynn B, Samborska B, Ma EH, Gravel SP, Tonelli L, Devorkin L, Kim P, Hall A, Izreig S, Loginicheva E, Beauchemin N, Siegel PM, Artyomov MN, Lum JJ, Zogopoulos G, Blagih J, Jones RG. LKB1 deficiency in T cells promotes the development of gastrointestinal polyposis. Science 2018; 361:406-411. [PMID: 30049881 DOI: 10.1126/science.aan3975] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 02/06/2018] [Accepted: 06/14/2018] [Indexed: 12/16/2022]
Abstract
Germline mutations in STK11, which encodes the tumor suppressor liver kinase B1 (LKB1), promote Peutz-Jeghers syndrome (PJS), a cancer predisposition syndrome characterized by the development of gastrointestinal (GI) polyps. Here, we report that heterozygous deletion of Stk11 in T cells (LThet mice) is sufficient to promote GI polyposis. Polyps from LThet mice, Stk11+/- mice, and human PJS patients display hallmarks of chronic inflammation, marked by inflammatory immune-cell infiltration, signal transducer and activator of transcription 3 (STAT3) activation, and increased expression of inflammatory factors associated with cancer progression [interleukin 6 (IL-6), IL-11, and CXCL2]. Targeting either T cells, IL-6, or STAT3 signaling reduced polyp growth in Stk11+/- animals. Our results identify LKB1-mediated inflammation as a tissue-extrinsic regulator of intestinal polyposis in PJS, suggesting possible therapeutic approaches by targeting deregulated inflammation in this disease.
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Affiliation(s)
- M C Poffenberger
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - A Metcalfe-Roach
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada
| | - E Aguilar
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - J Chen
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - B E Hsu
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Medicine, McGill University, Montreal, Quebec H3G 2M1, Canada
| | - A H Wong
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - R M Johnson
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Genentech, 1 DNA Way South, San Francisco, CA 94080, USA
| | - B Flynn
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - B Samborska
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada
| | - E H Ma
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - S-P Gravel
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Faculty of Pharmacy, University of Montreal, Montreal, Quebec H3C 3J7, Canada
| | - L Tonelli
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada
| | - L Devorkin
- Trev and Joyce Deeley Research Centre, BC Cancer Agency, Victoria, British Columbia V8R 6V5, Canada
| | - P Kim
- Trev and Joyce Deeley Research Centre, BC Cancer Agency, Victoria, British Columbia V8R 6V5, Canada
| | - A Hall
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Research Institute of the McGill University Health Centre, Montreal, Quebec H3H 2R9, Canada
| | - S Izreig
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - E Loginicheva
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - N Beauchemin
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Biochemistry, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - P M Siegel
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Medicine, McGill University, Montreal, Quebec H3G 2M1, Canada
| | - M N Artyomov
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA.,Center for Human Immunology and Immunotherapy Programs, Washington University at St. Louis, St. Louis, MO 63110, USA
| | - J J Lum
- Trev and Joyce Deeley Research Centre, BC Cancer Agency, Victoria, British Columbia V8R 6V5, Canada.,Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia V8W 2Y2, Canada
| | - G Zogopoulos
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Research Institute of the McGill University Health Centre, Montreal, Quebec H3H 2R9, Canada
| | - J Blagih
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada.,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada
| | - R G Jones
- Goodman Cancer Research Centre, McGill University, Montreal, Quebec H3A 1A3, Canada. .,Department of Physiology, McGill University, Montreal, Quebec H3G 1Y6, Canada.,Center for Cancer and Cell Biology, Van Andel Research Institute, Grand Rapids, MI 49503, USA
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Richardson RT, Bengtsson-Palme J, Gardiner MM, Johnson RM. A reference cytochrome c oxidase subunit I database curated for hierarchical classification of arthropod metabarcoding data. PeerJ 2018; 6:e5126. [PMID: 29967752 PMCID: PMC6025149 DOI: 10.7717/peerj.5126] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 06/07/2018] [Indexed: 01/01/2023] Open
Abstract
Metabarcoding is a popular application which warrants continued methods optimization. To maximize barcoding inferences, hierarchy-based sequence classification methods are increasingly common. We present methods for the construction and curation of a database designed for hierarchical classification of a 157 bp barcoding region of the arthropod cytochrome c oxidase subunit I (COI) locus. We produced a comprehensive arthropod COI amplicon dataset including annotated arthropod COI sequences and COI sequences extracted from arthropod whole mitochondrion genomes, the latter of which provided the only source of representation for Zoraptera, Callipodida and Holothyrida. The database contains extracted sequences of the target amplicon from all major arthropod clades, including all insect orders, all arthropod classes and Onychophora, Tardigrada and Mollusca outgroups. During curation, we extracted the COI region of interest from approximately 81 percent of the input sequences, corresponding to 73 percent of the genus-level diversity found in the input data. Further, our analysis revealed a high degree of sequence redundancy within the NCBI nucleotide database, with a mean of approximately 11 sequence entries per species in the input data. The curated, low-redundancy database is included in the Metaxa2 sequence classification software (http://microbiology.se/software/metaxa2/). Using this database with the Metaxa2 classifier, we performed a cross-validation analysis to characterize the relationship between the Metaxa2 reliability score, an estimate of classification confidence, and classification error probability. We used this analysis to select a reliability score threshold which minimized error. We then estimated classification sensitivity, false discovery rate and overclassification, the propensity to classify sequences from taxa not represented in the reference database. Our work will help researchers design and evaluate classification databases and conduct metabarcoding on arthropods and alternate taxa.
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Affiliation(s)
- Rodney T Richardson
- Department of Entomology, Ohio State University, Columbus, OH, United States of America
| | - Johan Bengtsson-Palme
- Department of Infectious Diseases, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Center for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden
| | - Mary M Gardiner
- Department of Entomology, Ohio State University, Columbus, OH, United States of America
| | - Reed M Johnson
- Department of Entomology, Ohio State University, Wooster, OH, United States of America
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22
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Perry TL, Kranker LM, Curry EE, Johnson RM, Mobley-Smith E. 353 Improving Outcomes in Fournier’s Gangrene Using Skin and Soft Tissue Sparing Flap Preservation Surgery: An Alternative Approach to Wide Radical Debridement. J Burn Care Res 2018. [DOI: 10.1093/jbcr/iry006.275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- T L Perry
- Wright State University, Dayton, OH; Wright State University Boonshoft SOM, Miami Valley Hospital, Dayton, OH
| | - L M Kranker
- Wright State University, Dayton, OH; Wright State University Boonshoft SOM, Miami Valley Hospital, Dayton, OH
| | - E E Curry
- Wright State University, Dayton, OH; Wright State University Boonshoft SOM, Miami Valley Hospital, Dayton, OH
| | - R M Johnson
- Wright State University, Dayton, OH; Wright State University Boonshoft SOM, Miami Valley Hospital, Dayton, OH
| | - E Mobley-Smith
- Wright State University, Dayton, OH; Wright State University Boonshoft SOM, Miami Valley Hospital, Dayton, OH
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23
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Gruosso T, Gigoux M, Bertos N, Manem VS, Zuo D, Saleg SM, Souleimanova M, Zhao H, Johnson RM, Monette A, Muñoz Ramos V, Hallett MT, Stagg J, Lapointe R, Omeroglu A, Meterissian S, Buisseret L, Van den Eyden G, Salgado R, Guiot MC, Haibe-Kains B, Park M. Abstract PD6-05: Distinct tumor microenvironments stratify triple negative breast cancer into immune subtypes. Cancer Res 2018. [DOI: 10.1158/1538-7445.sabcs17-pd6-05] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background:
Triple negative breast cancer (TNBC) are especially difficult to treat effectively. While only 20-30% of TNBC patients respond to chemotherapy in the neoadjuvant setting, overall outcome remains poor for non-responding patients. Engaging the immune system promises optimal personalized cancer therapy as mounting evidence suggests that immune-checkpoint inhibitor immunotherapies may become a therapeutic option for TNBC patients. The presence of CD8+ T cells, a crucial component of the cytotoxic arm of the adaptive immune response, is associated with good clinical outcome in TNBC patients. Specifically, it is the efficient CD8+ T cell invasion and infiltration in the tumor that is associated with good outcome. On the other hand, some tumors accumulate CD8+ T cells in the tumor-associated stroma with poor infiltration in the tumor epithelium. These patients show poor outcome. As CD8+ T cell infiltration in the tumor is a crucial step to mount an efficient anti-tumor response, we thus wondered how the tumor microenvironment affects CD8+ T cell invasion into the tumor epithelial compartment of the TNBC tumors.
Methods:
To identify potential stroma-dependent mechanisms that potentiate or inhibit CD8+ T cells invasion into the tumor epithelium, we coupled analysis of spatial patterns of CD8+ T cell localization by Immunohistochemistry (IHC) andperformed gene expression profiling of laser-capture microdissected tumor-associated stroma (as well as matched epithelium and bulk tumor) from 38 TNBC chemotherapy-naive primary cases. GSEA-based Metasignatures were derived from bulk tumor gene expression data from our cohort. To investigate the compartment of origin of the pathways identified via the Metasignatures, the (LCM)-derived tumor stromal and epithelial gene expression were analyzed.
Results:
CD8+ T cell quantification in different compartments of the tumor identify 3 main subgroups of TNBC based on CD8+ T cell localization. Importantly we developed a 2-step classification scheme based on CD8+ T cell localization. We developed metasignatures following our 2 steps classification and identified key bulk tumor metasignatures that showed prognostic value in an independent cohort. In addition the matched LCM gene expression from the tumor epithelium and stromal compartments allowed us to identify the compartment of origin.
Importantly, while 1 group of TNBC tumor was showing a significant anti-tumor response, the 2 other groups showed absence of such environment. The 2 non inflamed immune subtypes showed distinct phenotypes and biologies associated with poor anti-tumor response that we validated by immunohistochemistry and fluorescence. These results highlight different potential mecanisms that lead to immune evasion and allow us to stratify TNBC into immune subgroups.
Citation Format: Gruosso T, Gigoux M, Bertos N, Manem VS, Zuo D, Saleg SM, Souleimanova M, Zhao H, Johnson RM, Monette A, Muñoz Ramos V, Hallett MT, Stagg J, Lapointe R, Omeroglu A, Meterissian S, Buisseret L, Van den Eyden G, Salgado R, Guiot M-C, Haibe-Kains B, Park M. Distinct tumor microenvironments stratify triple negative breast cancer into immune subtypes [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD6-05.
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Affiliation(s)
- T Gruosso
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - M Gigoux
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - N Bertos
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - VS Manem
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - D Zuo
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - SM Saleg
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - M Souleimanova
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - H Zhao
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - RM Johnson
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - A Monette
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - V Muñoz Ramos
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - MT Hallett
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - J Stagg
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - R Lapointe
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - A Omeroglu
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - S Meterissian
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - L Buisseret
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - G Van den Eyden
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - R Salgado
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - M-C Guiot
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - B Haibe-Kains
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - M Park
- Goodman Cancer Research Center, McGill University, Montreal, Canada; Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada; 7Centre de Recherche du Centre Hospitalier de l'Université de Montréal et Institut du Cancer de Montréal, Montreal, Canada; McGill University Health Centre and McGill University, Montreal, Canada; Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
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Calla B, Noble K, Johnson RM, Walden KKO, Schuler MA, Robertson HM, Berenbaum MR. Cytochrome P450 diversification and hostplant utilization patterns in specialist and generalist moths: Birth, death and adaptation. Mol Ecol 2017; 26:6021-6035. [PMID: 28921805 DOI: 10.1111/mec.14348] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 08/11/2017] [Accepted: 09/11/2017] [Indexed: 01/21/2023]
Abstract
Across insect genomes, the size of the cytochrome P450 monooxygenase (CYP) gene superfamily varies widely. CYPome size variation has been attributed to reciprocal adaptive radiations in insect detoxification genes in response to plant biosynthetic gene radiations driven by co-evolution between herbivores and their chemically defended hostplants. Alternatively, variation in CYPome size may be due to random "birth-and-death" processes, whereby exponential increase via gene duplications is limited by random decay via gene death or transition via divergence. We examined CYPome diversification in the genomes of seven Lepidoptera species varying in host breadth from monophagous (Bombyx mori) to highly polyphagous (Amyelois transitella). CYPome size largely reflects the size of Clan 3, the clan associated with xenobiotic detoxification, and to some extent phylogenetic age. Consistently across genomes, families CYP6, CYP9 and CYP321 are most diverse and CYP6AB, CYP6AE, CYP6B, CYP9A and CYP9G are most diverse among subfamilies. Higher gene number in subfamilies is due to duplications occurring primarily after speciation and specialization ("P450 blooms"), and the genes are arranged in clusters, indicative of active duplicating loci. In the parsnip webworm, Depressaria pastinacella, gene expression levels in large subfamilies are high relative to smaller subfamilies. Functional and phylogenetic data suggest a correlation between highly dynamic loci (reflective of extensive gene duplication, functionalization and in some cases loss) and the ability of enzymes encoded by these genes to metabolize hostplant defences, consistent with an adaptive, nonrandom process driven by ecological interactions.
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Affiliation(s)
- Bernarda Calla
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Katherine Noble
- Department of Biology, University of Utah, Salt Lake City, UT, USA
| | - Reed M Johnson
- Department of Entomology, The Ohio State University, Wooster, OH, USA
| | - Kimberly K O Walden
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Mary A Schuler
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Hugh M Robertson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - May R Berenbaum
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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Sponsler DB, Johnson RM. Mechanistic modeling of pesticide exposure: The missing keystone of honey bee toxicology. Environ Toxicol Chem 2017; 36:871-881. [PMID: 27769096 DOI: 10.1002/etc.3661] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Revised: 10/04/2016] [Accepted: 10/19/2016] [Indexed: 06/06/2023]
Abstract
The role of pesticides in recent honey bee losses is controversial, partly because field studies often fail to detect effects predicted by laboratory studies. This dissonance highlights a critical gap in the field of honey bee toxicology: there exists little mechanistic understanding of the patterns and processes of exposure that link honey bees to pesticides in their environment. The authors submit that 2 key processes underlie honey bee pesticide exposure: 1) the acquisition of pesticide by foraging bees, and 2) the in-hive distribution of pesticide returned by foragers. The acquisition of pesticide by foraging bees must be understood as the spatiotemporal intersection between environmental contamination and honey bee foraging activity. This implies that exposure is distributional, not discrete, and that a subset of foragers may acquire harmful doses of pesticide while the mean colony exposure would appear safe. The in-hive distribution of pesticide is a complex process driven principally by food transfer interactions between colony members, and this process differs importantly between pollen and nectar. High priority should be placed on applying the extensive literature on honey bee biology to the development of more rigorously mechanistic models of honey bee pesticide exposure. In combination with mechanistic effects modeling, mechanistic exposure modeling has the potential to integrate the field of honey bee toxicology, advancing both risk assessment and basic research. Environ Toxicol Chem 2017;36:871-881. © 2016 SETAC.
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Affiliation(s)
| | - Reed M Johnson
- Department of Entomology, The Ohio State University, Wooster, Ohio, USA
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26
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Sponsler DB, Matcham EG, Lin CH, Lanterman JL, Johnson RM. Spatial and taxonomic patterns of honey bee foraging: A choice test between urban and agricultural landscapes. Journal of Urban Ecology 2017. [DOI: 10.1093/jue/juw008] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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27
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Richardson RT, Bengtsson-Palme J, Johnson RM. Evaluating and optimizing the performance of software commonly used for the taxonomic classification of DNA metabarcoding sequence data. Mol Ecol Resour 2016; 17:760-769. [PMID: 27797448 DOI: 10.1111/1755-0998.12628] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Revised: 10/17/2016] [Accepted: 10/21/2016] [Indexed: 11/29/2022]
Abstract
The taxonomic classification of DNA sequences has become a critical component of numerous ecological research applications; however, few studies have evaluated the strengths and weaknesses of commonly used sequence classification approaches. Further, the methods and software available for sequence classification are diverse, creating an environment in which it may be difficult to determine the best course of action and the trade-offs made using different classification approaches. Here, we provide an in silico evaluation of three DNA sequence classifiers, the rdp Naïve Bayesian Classifier, rtax and utax. Further, we discuss the results, merits and limitations of both the classifiers and our method of classifier evaluation. Our methods of comparison are simple, yet robust, and will provide researchers a methodological and conceptual foundation for making such evaluations in a variety of research situations. Generally, we found a considerable trade-off between accuracy and sensitivity for the classifiers tested, indicating a need for further improvement of sequence classification tools.
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Affiliation(s)
- Rodney T Richardson
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, OH, 44691, USA
| | - Johan Bengtsson-Palme
- Department of Infectious Diseases, The Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 10, Göteborg, SE-413 46, Sweden.,Centre for Antibiotic Resistance Research (CARe), University of Gothenburg, PO Box 440, SE-405 30, Gothenburg, Sweden
| | - Reed M Johnson
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, OH, 44691, USA
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Swale DR, Engers DW, Bollinger SR, Gross A, Inocente EA, Days E, Kanga F, Johnson RM, Yang L, Bloomquist JR, Hopkins CR, Piermarini PM, Denton JS. An insecticide resistance-breaking mosquitocide targeting inward rectifier potassium channels in vectors of Zika virus and malaria. Sci Rep 2016; 6:36954. [PMID: 27849039 PMCID: PMC5111108 DOI: 10.1038/srep36954] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 10/19/2016] [Indexed: 01/01/2023] Open
Abstract
Insecticide resistance is a growing threat to mosquito control programs around the world, thus creating the need to discover novel target sites and target-specific compounds for insecticide development. Emerging evidence suggests that mosquito inward rectifier potassium (Kir) channels represent viable molecular targets for developing insecticides with new mechanisms of action. Here we describe the discovery and characterization of VU041, a submicromolar-affinity inhibitor of Anopheles (An.) gambiae and Aedes (Ae.) aegypti Kir1 channels that incapacitates adult female mosquitoes from representative insecticide-susceptible and -resistant strains of An. gambiae (G3 and Akron, respectively) and Ae. aegypti (Liverpool and Puerto Rico, respectively) following topical application. VU041 is selective for mosquito Kir channels over several mammalian orthologs, with the exception of Kir2.1, and is not lethal to honey bees. Medicinal chemistry was used to develop an analog, termed VU730, which retains activity toward mosquito Kir1 but is not active against Kir2.1 or other mammalian Kir channels. Thus, VU041 and VU730 are promising chemical scaffolds for developing new classes of insecticides to combat insecticide-resistant mosquitoes and the transmission of mosquito-borne diseases, such as Zika virus, without harmful effects on humans and beneficial insects.
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Affiliation(s)
- Daniel R Swale
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Department of Entomology, Louisiana State University Agricultural Center, Baton Rouge, LA, 70803, USA
| | - Darren W Engers
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA.,Vanderbilt Center for Neuroscience Drug Discovery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Sean R Bollinger
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA.,Vanderbilt Center for Neuroscience Drug Discovery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Aaron Gross
- Department of Entomology and Nematology, University of Florida, Gainesville, FL 32610, USA
| | - Edna Alfaro Inocente
- Department of Entomology, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, OH 44691, USA
| | - Emily Days
- Vanderbilt Institute of Chemical Biology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Fariba Kanga
- Department of Entomology, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, OH 44691, USA
| | - Reed M Johnson
- Department of Entomology, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, OH 44691, USA
| | - Liu Yang
- Department of Entomology, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, OH 44691, USA
| | - Jeffrey R Bloomquist
- Department of Entomology and Nematology, University of Florida, Gainesville, FL 32610, USA
| | - Corey R Hopkins
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA.,Vanderbilt Center for Neuroscience Drug Discovery, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Department of Chemistry, Vanderbilt University, Nashville, TN 37235, USA
| | - Peter M Piermarini
- Department of Entomology, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, OH 44691, USA
| | - Jerod S Denton
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA.,Vanderbilt Institute of Chemical Biology, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Institute for Global Health, Vanderbilt University, Nashville, TN 37203, USA
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Affiliation(s)
- R M Johnson
- Professor of Public Health, Department of Health Sciences, University of Alaska Anchorage, United States.
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Richardson RT, Lin CH, Quijia JO, Riusech NS, Goodell K, Johnson RM. Rank-based characterization of pollen assemblages collected by honey bees using a multi-locus metabarcoding approach. Appl Plant Sci 2015; 3:apps1500043. [PMID: 26649264 PMCID: PMC4651628 DOI: 10.3732/apps.1500043] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2015] [Accepted: 09/13/2015] [Indexed: 05/03/2023]
Abstract
PREMISE OF THE STUDY Difficulties inherent in microscopic pollen identification have resulted in limited implementation for large-scale studies. Metabarcoding, a relatively novel approach, could make pollen analysis less onerous; however, improved understanding of the quantitative capacity of various plant metabarcode regions and primer sets is needed to ensure that such applications are accurate and precise. METHODS AND RESULTS We applied metabarcoding, targeting the ITS2, matK, and rbcL loci, to characterize six samples of pollen collected by honey bees, Apis mellifera. Additionally, samples were analyzed by light microscopy. We found significant rank-based associations between the relative abundance of pollen types within our samples as inferred by the two methods. CONCLUSIONS Our findings suggest metabarcoding data from plastid loci, as opposed to the ribosomal locus, are more reliable for quantitative characterization of pollen assemblages. Furthermore, multilocus metabarcoding of pollen may be more reliable than single-locus analyses, underscoring the need for discovering novel barcodes and barcode combinations optimized for molecular palynology.
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Affiliation(s)
- Rodney T. Richardson
- Department of Entomology, The Ohio State University—Ohio Agricultural Research and Development Center, 1680 Madison Avenue, Wooster, Ohio 44691 USA
- Author for correspondence:
| | - Chia-Hua Lin
- Department of Entomology, The Ohio State University—Ohio Agricultural Research and Development Center, 1680 Madison Avenue, Wooster, Ohio 44691 USA
| | - Juan O. Quijia
- Department of Entomology, The Ohio State University—Ohio Agricultural Research and Development Center, 1680 Madison Avenue, Wooster, Ohio 44691 USA
| | - Natalia S. Riusech
- Department of Entomology, The Ohio State University—Ohio Agricultural Research and Development Center, 1680 Madison Avenue, Wooster, Ohio 44691 USA
| | - Karen Goodell
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, 1179 University Drive, Newark, Ohio 43023 USA
| | - Reed M. Johnson
- Department of Entomology, The Ohio State University—Ohio Agricultural Research and Development Center, 1680 Madison Avenue, Wooster, Ohio 44691 USA
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31
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Berenbaum MR, Johnson RM. Xenobiotic detoxification pathways in honey bees. Curr Opin Insect Sci 2015; 10:51-58. [PMID: 29588014 DOI: 10.1016/j.cois.2015.03.005] [Citation(s) in RCA: 208] [Impact Index Per Article: 23.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Accepted: 03/17/2015] [Indexed: 05/21/2023]
Abstract
Relative to most other insect genomes, the western honey bee Apis mellifera has a deficit of detoxification genes spanning Phase I (functionalization), II (conjugation) and III (excretion) gene families. Although honeybees do not display across-the-board greater sensitivity to pesticides, this deficit may render them vulnerable to synergistic interactions among xenobiotics. Diet quality, in terms of protein and phytochemical content, has a pronounced influence on tolerance of toxic compounds. Detoxification gene inventory reduction may reflect an evolutionary history of consuming relatively chemically benign nectar and pollen, as other apoid pollinators display comparable levels of cytochrome P450 gene reduction. Enzymatic detoxification in the eusocial A. mellifera may be complemented by behaviors comprising a 'social detoxification system,' including forager discrimination, dilution by pollen mixing, and colony food processing via microbial fermentation, that reduces the number or quantity of ingested chemicals requiring detoxification.
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Affiliation(s)
- May R Berenbaum
- University of Illinois at Urbana-Champaign, Department of Entomology, 505 S. Goodwin, Urbana, IL 61801-3795, United States.
| | - Reed M Johnson
- The Ohio State University, Department of Entomology, 1680 Madison Ave., Wooster, OH 44691-4114, United States
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Kapheim KM, Pan H, Li C, Salzberg SL, Puiu D, Magoc T, Robertson HM, Hudson ME, Venkat A, Fischman BJ, Hernandez A, Yandell M, Ence D, Holt C, Yocum GD, Kemp WP, Bosch J, Waterhouse RM, Zdobnov EM, Stolle E, Kraus FB, Helbing S, Moritz RFA, Glastad KM, Hunt BG, Goodisman MAD, Hauser F, Grimmelikhuijzen CJP, Pinheiro DG, Nunes FMF, Soares MPM, Tanaka ÉD, Simões ZLP, Hartfelder K, Evans JD, Barribeau SM, Johnson RM, Massey JH, Southey BR, Hasselmann M, Hamacher D, Biewer M, Kent CF, Zayed A, Blatti C, Sinha S, Johnston JS, Hanrahan SJ, Kocher SD, Wang J, Robinson GE, Zhang G. Social evolution. Genomic signatures of evolutionary transitions from solitary to group living. Science 2015; 348:1139-43. [PMID: 25977371 DOI: 10.1126/science.aaa4788] [Citation(s) in RCA: 234] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 05/06/2015] [Indexed: 12/14/2022]
Abstract
The evolution of eusociality is one of the major transitions in evolution, but the underlying genomic changes are unknown. We compared the genomes of 10 bee species that vary in social complexity, representing multiple independent transitions in social evolution, and report three major findings. First, many important genes show evidence of neutral evolution as a consequence of relaxed selection with increasing social complexity. Second, there is no single road map to eusociality; independent evolutionary transitions in sociality have independent genetic underpinnings. Third, though clearly independent in detail, these transitions do have similar general features, including an increase in constrained protein evolution accompanied by increases in the potential for gene regulation and decreases in diversity and abundance of transposable elements. Eusociality may arise through different mechanisms each time, but would likely always involve an increase in the complexity of gene networks.
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Affiliation(s)
- Karen M Kapheim
- Carl R. WoeseInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Biology, Utah State University, Logan, UT 84322, USA.
| | - Hailin Pan
- China National GeneBank, BGI-Shenzhen, Shenzhen, 518083, China
| | - Cai Li
- China National GeneBank, BGI-Shenzhen, Shenzhen, 518083, China. Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, 1350, Denmark
| | - Steven L Salzberg
- Departments of Biomedical Engineering, Computer Science, and Biostatistics, Johns Hopkins University, Baltimore, MD 21218, USA. Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Daniela Puiu
- Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Tanja Magoc
- Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Hugh M Robertson
- Carl R. WoeseInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Matthew E Hudson
- Carl R. WoeseInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Aarti Venkat
- Carl R. WoeseInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Brielle J Fischman
- Carl R. WoeseInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Program in Ecology and Evolutionary Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Biology, Hobart and William Smith Colleges, Geneva, NY 14456, USA
| | - Alvaro Hernandez
- Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Mark Yandell
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA. USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT 84112, USA
| | - Daniel Ence
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
| | - Carson Holt
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA. USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT 84112, USA
| | - George D Yocum
- U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) Red River Valley Agricultural Research Center, Biosciences Research Laboratory, Fargo, ND 58102, USA
| | - William P Kemp
- U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) Red River Valley Agricultural Research Center, Biosciences Research Laboratory, Fargo, ND 58102, USA
| | - Jordi Bosch
- Center for Ecological Research and Forestry Applications (CREAF), Universitat Autonoma de Barcelona, 08193 Bellaterra, Spain
| | - Robert M Waterhouse
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland. Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA. The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Evgeny M Zdobnov
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland. Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Eckart Stolle
- Institute of Biology, Department Zoology, Martin-Luther-University Halle-Wittenberg, Hoher Weg 4, D-06099 Halle (Saale), Germany. Queen Mary University of London, School of Biological and Chemical Sciences Organismal Biology Research Group, London E1 4NS, UK
| | - F Bernhard Kraus
- Institute of Biology, Department Zoology, Martin-Luther-University Halle-Wittenberg, Hoher Weg 4, D-06099 Halle (Saale), Germany. Department of Laboratory Medicine, University Hospital Halle, Ernst Grube Strasse 40, D-06120 Halle (Saale), Germany
| | - Sophie Helbing
- Institute of Biology, Department Zoology, Martin-Luther-University Halle-Wittenberg, Hoher Weg 4, D-06099 Halle (Saale), Germany
| | - Robin F A Moritz
- Institute of Biology, Department Zoology, Martin-Luther-University Halle-Wittenberg, Hoher Weg 4, D-06099 Halle (Saale), Germany. German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, 04103 Leipzig, Germany
| | - Karl M Glastad
- School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Brendan G Hunt
- Department of Entomology, University of Georgia, Griffin, GA 30223, USA
| | | | - Frank Hauser
- Center for Functional and Comparative Insect Genomics, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Cornelis J P Grimmelikhuijzen
- Center for Functional and Comparative Insect Genomics, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Daniel Guariz Pinheiro
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901 Ribeirão Preto, SP, Brazil. Departamento de Tecnologia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (UNESP), 14884-900 Jaboticabal, SP, Brazil
| | - Francis Morais Franco Nunes
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, 13565-905 São Carlos, SP, Brazil
| | - Michelle Prioli Miranda Soares
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901 Ribeirão Preto, SP, Brazil
| | - Érica Donato Tanaka
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14049-900 Ribeirão Preto, SP, Brazil
| | - Zilá Luz Paulino Simões
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901 Ribeirão Preto, SP, Brazil
| | - Klaus Hartfelder
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14049-900 Ribeirão Preto, SP, Brazil
| | - Jay D Evans
- USDA-ARS Bee Research Lab, Beltsville, MD 20705 USA
| | - Seth M Barribeau
- Department of Biology, East Carolina University, Greenville, NC 27858, USA
| | - Reed M Johnson
- Department of Entomology, Ohio Agricultural Research and Development Center, Ohio State University, Wooster, OH 44691, USA
| | - Jonathan H Massey
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Bruce R Southey
- Department of Animal Sciences, University of Illinois, Urbana, IL 61801, USA
| | - Martin Hasselmann
- Department of Population Genomics, Institute of Animal Husbandry and Animal Breeding, University of Hohenheim, Germany
| | - Daniel Hamacher
- Department of Population Genomics, Institute of Animal Husbandry and Animal Breeding, University of Hohenheim, Germany
| | - Matthias Biewer
- Department of Population Genomics, Institute of Animal Husbandry and Animal Breeding, University of Hohenheim, Germany
| | - Clement F Kent
- Department of Biology, York University, Toronto, ON M3J 1P3, Canada. Janelia Farm Research Campus, Howard Hughes Medical Institue, Ashburn, VA 20147, USA
| | - Amro Zayed
- Department of Biology, York University, Toronto, ON M3J 1P3, Canada
| | - Charles Blatti
- Carl R. WoeseInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Saurabh Sinha
- Carl R. WoeseInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - J Spencer Johnston
- Department of Entomology, Texas A&M University, College Station, TX 77843, USA
| | - Shawn J Hanrahan
- Department of Entomology, Texas A&M University, College Station, TX 77843, USA
| | - Sarah D Kocher
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
| | - Jun Wang
- China National GeneBank, BGI-Shenzhen, Shenzhen, 518083, China. Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark. Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia. Macau University of Science and Technology, Avenida Wai long, Taipa, Macau 999078, China. Department of Medicine, University of Hong Kong, Hong Kong.
| | - Gene E Robinson
- Carl R. WoeseInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Center for Advanced Study Professor in Entomology and Neuroscience, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
| | - Guojie Zhang
- China National GeneBank, BGI-Shenzhen, Shenzhen, 518083, China. Centre for Social Evolution, Department of Biology, Universitetsparken 15, University of Copenhagen, DK-2100 Copenhagen, Denmark.
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33
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Sadd BM, Barribeau SM, Bloch G, de Graaf DC, Dearden P, Elsik CG, Gadau J, Grimmelikhuijzen CJP, Hasselmann M, Lozier JD, Robertson HM, Smagghe G, Stolle E, Van Vaerenbergh M, Waterhouse RM, Bornberg-Bauer E, Klasberg S, Bennett AK, Câmara F, Guigó R, Hoff K, Mariotti M, Munoz-Torres M, Murphy T, Santesmasses D, Amdam GV, Beckers M, Beye M, Biewer M, Bitondi MMG, Blaxter ML, Bourke AFG, Brown MJF, Buechel SD, Cameron R, Cappelle K, Carolan JC, Christiaens O, Ciborowski KL, Clarke DF, Colgan TJ, Collins DH, Cridge AG, Dalmay T, Dreier S, du Plessis L, Duncan E, Erler S, Evans J, Falcon T, Flores K, Freitas FCP, Fuchikawa T, Gempe T, Hartfelder K, Hauser F, Helbing S, Humann FC, Irvine F, Jermiin LS, Johnson CE, Johnson RM, Jones AK, Kadowaki T, Kidner JH, Koch V, Köhler A, Kraus FB, Lattorff HMG, Leask M, Lockett GA, Mallon EB, Antonio DSM, Marxer M, Meeus I, Moritz RFA, Nair A, Näpflin K, Nissen I, Niu J, Nunes FMF, Oakeshott JG, Osborne A, Otte M, Pinheiro DG, Rossié N, Rueppell O, Santos CG, Schmid-Hempel R, Schmitt BD, Schulte C, Simões ZLP, Soares MPM, Swevers L, Winnebeck EC, Wolschin F, Yu N, Zdobnov EM, Aqrawi PK, Blankenburg KP, Coyle M, Francisco L, Hernandez AG, Holder M, Hudson ME, Jackson L, Jayaseelan J, Joshi V, Kovar C, Lee SL, Mata R, Mathew T, Newsham IF, Ngo R, Okwuonu G, Pham C, Pu LL, Saada N, Santibanez J, Simmons D, Thornton R, Venkat A, Walden KKO, Wu YQ, Debyser G, Devreese B, Asher C, Blommaert J, Chipman AD, Chittka L, Fouks B, Liu J, O'Neill MP, Sumner S, Puiu D, Qu J, Salzberg SL, Scherer SE, Muzny DM, Richards S, Robinson GE, Gibbs RA, Schmid-Hempel P, Worley KC. The genomes of two key bumblebee species with primitive eusocial organization. Genome Biol 2015; 16:76. [PMID: 25908251 PMCID: PMC4414376 DOI: 10.1186/s13059-015-0623-3] [Citation(s) in RCA: 241] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Accepted: 03/10/2015] [Indexed: 12/25/2022] Open
Abstract
Background The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0623-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ben M Sadd
- School of Biological Sciences, Illinois State University, Normal, IL, 61790, USA. .,Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Seth M Barribeau
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland. .,Department of Biology, East Carolina University, Greenville, NC, 27858, USA.
| | - Guy Bloch
- Department of Ecology, Evolution, and Behavior, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Dirk C de Graaf
- Laboratory of Zoophysiology, Faculty of Sciences, Ghent University, Krijgslaan 281, S2, 9000, Ghent, Belgium.
| | - Peter Dearden
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Christine G Elsik
- Division of Animal Sciences, Division of Plant Sciences, and MU Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. .,Department of Biology, Georgetown University, Washington, DC, 20057, USA.
| | - Jürgen Gadau
- School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA.
| | - Cornelis J P Grimmelikhuijzen
- Center for Functional and Comparative Insect Genomics, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Martin Hasselmann
- University of Hohenheim, Institute of Animal Science, Garbenstrasse 17, 70599, Stuttgart, Germany.
| | - Jeffrey D Lozier
- Department of Biological Sciences, University of Alabama, Tuscaloosa, AL, 35487, USA.
| | - Hugh M Robertson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Guy Smagghe
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Eckart Stolle
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Matthias Van Vaerenbergh
- Laboratory of Zoophysiology, Faculty of Sciences, Ghent University, Krijgslaan 281, S2, 9000, Ghent, Belgium.
| | - Robert M Waterhouse
- Department of Genetic Medicine and Development, University of Geneva Medical School, rue Michel-Servet 1, 1211, Geneva, Switzerland. .,Swiss Institute of Bioinformatics, rue Michel-Servet 1, 1211, Geneva, Switzerland. .,Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar Street, Cambridge, MA, 02139, USA. .,The Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA, 02142, USA.
| | - Erich Bornberg-Bauer
- Westfalian Wilhelms University, Institute of Evolution and Biodiversity, Huefferstrasse 1, 48149, Muenster, Germany.
| | - Steffen Klasberg
- Westfalian Wilhelms University, Institute of Evolution and Biodiversity, Huefferstrasse 1, 48149, Muenster, Germany.
| | - Anna K Bennett
- Department of Biology, Georgetown University, Washington, DC, 20057, USA.
| | - Francisco Câmara
- Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Roderic Guigó
- Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Katharina Hoff
- Ernst Moritz Arndt University Greifswald, Institute for Mathematics and Computer Science, Walther-Rathenau-Str. 47, 17487, Greifswald, Germany.
| | - Marco Mariotti
- Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Monica Munoz-Torres
- Department of Biology, Georgetown University, Washington, DC, 20057, USA. .,Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
| | - Terence Murphy
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, USA.
| | - Didac Santesmasses
- Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Gro V Amdam
- School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA. .,Department of Chemistry, Biotechnology and Food Science, Norwegian University of Food Science, N-1432, Aas, Norway.
| | - Matthew Beckers
- School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Martin Beye
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Matthias Biewer
- University of Hohenheim, Institute of Animal Science, Garbenstrasse 17, 70599, Stuttgart, Germany. .,University of Cologne, Institute of Genetics, Cologne, Germany.
| | - Márcia M G Bitondi
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901, Ribeirão Preto, Brazil.
| | - Mark L Blaxter
- Institute of Evolutionary Biology and Edinburgh Genomics, The Ashworth Laboratories, The King's Buildings, University of Edinburgh, Edinburgh, EH9 3FL, UK.
| | - Andrew F G Bourke
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Mark J F Brown
- School of Biological Sciences, Royal Holloway University of London, London, UK.
| | - Severine D Buechel
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Rossanah Cameron
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Kaat Cappelle
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - James C Carolan
- Maynooth University Department of Biology, Maynooth University, Co, Kildare, Ireland.
| | - Olivier Christiaens
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Kate L Ciborowski
- School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK.
| | | | - Thomas J Colgan
- Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland.
| | - David H Collins
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Andrew G Cridge
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Tamas Dalmay
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Stephanie Dreier
- Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
| | - Louis du Plessis
- Theoretical Biology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,Computational Evolution, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
| | - Elizabeth Duncan
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Silvio Erler
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Jay Evans
- USDA-ARS Bee Research Laboratory, Maryland, USA.
| | - Tiago Falcon
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Kevin Flores
- Center for Research in Scientific Computation, North Carolina State University Raleigh, Raleigh, NC, USA.
| | - Flávia C P Freitas
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Taro Fuchikawa
- Department of Ecology, Evolution, and Behavior, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel. .,Laboratory of Insect Ecology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan.
| | - Tanja Gempe
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Klaus Hartfelder
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Frank Hauser
- Center for Functional and Comparative Insect Genomics, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Sophie Helbing
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Fernanda C Humann
- Instituto Federal de Educação, Ciência e Tecnologia de São Paulo, 15991-502, Matão, Brazil.
| | - Frano Irvine
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | | | - Claire E Johnson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Reed M Johnson
- Department of Entomology, The Ohio State University, Wooster, OH, 44791, USA.
| | - Andrew K Jones
- Department of Biological and Medical Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK.
| | - Tatsuhiko Kadowaki
- Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, China.
| | - Jonathan H Kidner
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Vasco Koch
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Arian Köhler
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - F Bernhard Kraus
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany. .,Department of Laboratory Medicine, University Hospital Halle (Saale), Halle, Germany.
| | - H Michael G Lattorff
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany. .,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
| | - Megan Leask
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | | | - Eamonn B Mallon
- Department of Biology, University of Leicester, Leicester, UK.
| | - David S Marco Antonio
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Monika Marxer
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Ivan Meeus
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Robin F A Moritz
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Ajay Nair
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Kathrin Näpflin
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Inga Nissen
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Jinzhi Niu
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Francis M F Nunes
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, 13565-905, São Carlos, Brazil.
| | | | - Amy Osborne
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Marianne Otte
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Daniel G Pinheiro
- Departamento de Tecnologia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, 14884-900, Jaboticabal, Brazil.
| | - Nina Rossié
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Olav Rueppell
- Department of Biology, University of North Carolina at Greensboro, 321 McIver Street, Greensboro, NC, 27403, USA.
| | - Carolina G Santos
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Regula Schmid-Hempel
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Björn D Schmitt
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Christina Schulte
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Zilá L P Simões
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901, Ribeirão Preto, Brazil.
| | - Michelle P M Soares
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Luc Swevers
- Institute of Biosciences & Applications, National Center for Scientific Research Demokritos, Athens, Greece.
| | | | - Florian Wolschin
- School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA. .,Department of Chemistry, Biotechnology and Food Science, Norwegian University of Food Science, N-1432, Aas, Norway.
| | - Na Yu
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Evgeny M Zdobnov
- Department of Genetic Medicine and Development, University of Geneva Medical School, rue Michel-Servet 1, 1211, Geneva, Switzerland. .,Swiss Institute of Bioinformatics, rue Michel-Servet 1, 1211, Geneva, Switzerland.
| | - Peshtewani K Aqrawi
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Kerstin P Blankenburg
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Marcus Coyle
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Liezl Francisco
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Alvaro G Hernandez
- Roy J. Carver Biotechnology Center, University of Illinois Urbana-Champaign, Urbana, IL, USA.
| | - Michael Holder
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Matthew E Hudson
- Department of Crop Sciences and Institute of Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - LaRonda Jackson
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Joy Jayaseelan
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Vandita Joshi
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Christie Kovar
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Sandra L Lee
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Robert Mata
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Tittu Mathew
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Irene F Newsham
- Molecular Genetic Technology Program, School of Health Professions, MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 2, Houston, TX, 77025, USA.
| | - Robin Ngo
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Geoffrey Okwuonu
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Christopher Pham
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Ling-Ling Pu
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Nehad Saada
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Jireh Santibanez
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - DeNard Simmons
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Rebecca Thornton
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Aarti Venkat
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
| | - Kimberly K O Walden
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Yuan-Qing Wu
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Griet Debyser
- Laboratory of Protein Biochemistry and Biomolecular Engineering, Department of Biochemistry and Microbiology, Ghent University, K.L. Ledeganckstraat 35, 9000, Ghent, Belgium.
| | - Bart Devreese
- Laboratory of Protein Biochemistry and Biomolecular Engineering, Department of Biochemistry and Microbiology, Ghent University, K.L. Ledeganckstraat 35, 9000, Ghent, Belgium.
| | - Claire Asher
- Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
| | - Julie Blommaert
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Ariel D Chipman
- Department of Ecology, Evolution, and Behavior, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Lars Chittka
- Department of Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK.
| | - Bertrand Fouks
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany. .,Department of Biology, University of North Carolina at Greensboro, 321 McIver Street, Greensboro, NC, 27403, USA.
| | - Jisheng Liu
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium. .,School of Life Sciences, Guangzhou University, Guangzhou, China.
| | - Meaghan P O'Neill
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Seirian Sumner
- School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK.
| | - Daniela Puiu
- Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, 21205, USA.
| | - Jiaxin Qu
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Steven L Salzberg
- Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, 21205, USA.
| | - Steven E Scherer
- School of Life Sciences, Guangzhou University, Guangzhou, China.
| | - Donna M Muzny
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Stephen Richards
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Gene E Robinson
- Carl R. Woese Institute for Genomic Biology, Department of Entomology, Neuroscience Program, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, IL, 61801, USA.
| | - Richard A Gibbs
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Paul Schmid-Hempel
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Kim C Worley
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
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Abstract
Foraging honey bees (Apis mellifera L.) can routinely travel as far as several kilometers from their hive in the process of collecting nectar and pollen from floral patches within the surrounding landscape. Since the availability of floral resources at the landscape scale is a function of landscape composition, apiculturists have long recognized that landscape composition is a critical determinant of honey bee colony success. Nevertheless, very few studies present quantitative data relating colony success metrics to local landscape composition. We employed a beekeeper survey in conjunction with GIS-based landscape analysis to model colony success as a function of landscape composition in the State of Ohio, USA, a region characterized by intensive cropland, urban development, deciduous forest, and grassland. We found that colony food accumulation and wax production were positively related to cropland and negatively related to forest and grassland, a pattern that may be driven by the abundance of dandelion and clovers in agricultural areas compared to forest or mature grassland. Colony food accumulation was also negatively correlated with urban land cover in sites dominated by urban and agricultural land use, which does not support the popular opinion that the urban environment is more favorable to honey bees than cropland.
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Affiliation(s)
- D B Sponsler
- Department of Entomology, The Ohio State University , Wooster, OH , USA
| | - R M Johnson
- Department of Entomology, The Ohio State University , Wooster, OH , USA
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Abstract
Insecticides are chemicals used to kill insects, so it is unsurprising that many insecticides have the potential to harm honey bees (Apis mellifera). However, bees are exposed to a great variety of other potentially toxic chemicals, including flavonoids and alkaloids that are produced by plants; mycotoxins produced by fungi; antimicrobials and acaricides that are introduced by beekeepers; and fungicides, herbicides, and other environmental contaminants. Although often regarded as uniquely sensitive to toxic compounds, honey bees are adapted to tolerate and even thrive in the presence of toxic compounds that occur naturally in their environment. The harm caused by exposure to a particular concentration of a toxic compound may depend on the level of simultaneous exposure to other compounds, pathogen levels, nutritional status, and a host of other factors. This review takes a holistic view of bee toxicology by taking into account the spectrum of xenobiotics to which bees are exposed.
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Affiliation(s)
- Reed M Johnson
- Department of Entomology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster, Ohio 44691;
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Richardson RT, Lin CH, Sponsler DB, Quijia JO, Goodell K, Johnson RM. Application of ITS2 metabarcoding to determine the provenance of pollen collected by honey bees in an agroecosystem. Appl Plant Sci 2015; 3:apps1400066. [PMID: 25606352 DOI: 10.5061/dryad.64b5p] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Accepted: 12/04/2014] [Indexed: 05/24/2023]
Abstract
PREMISE OF THE STUDY Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. • METHODS Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. • RESULTS Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. • DISCUSSION For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution.
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Affiliation(s)
- Rodney T Richardson
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
| | - Chia-Hua Lin
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
| | - Douglas B Sponsler
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
| | - Juan O Quijia
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
| | - Karen Goodell
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, 1179 University Dr., Newark, Ohio 43023 USA
| | - Reed M Johnson
- Department of Entomology, The Ohio State University-Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
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Richardson RT, Lin CH, Sponsler DB, Quijia JO, Goodell K, Johnson RM. Application of ITS2 metabarcoding to determine the provenance of pollen collected by honey bees in an agroecosystem. Appl Plant Sci 2015; 3:apps1400066. [PMID: 25606352 PMCID: PMC4298230 DOI: 10.3732/apps.1400066] [Citation(s) in RCA: 133] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Accepted: 12/04/2014] [Indexed: 05/08/2023]
Abstract
PREMISE OF THE STUDY Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. • METHODS Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. • RESULTS Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. • DISCUSSION For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution.
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Affiliation(s)
- Rodney T. Richardson
- Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
| | - Chia-Hua Lin
- Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
- Author for correspondence:
| | - Douglas B. Sponsler
- Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
| | - Juan O. Quijia
- Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
| | - Karen Goodell
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, 1179 University Dr., Newark, Ohio 43023 USA
| | - Reed M. Johnson
- Department of Entomology, The Ohio State University–Ohio Agricultural Research and Development Center, 1680 Madison Ave., Wooster, Ohio 44691 USA
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Johnson RM, Percel EG. Effect of a fungicide and spray adjuvant on queen-rearing success in honey bees (Hymenoptera: Apidae). J Econ Entomol 2013; 106:1952-7. [PMID: 24224234 DOI: 10.1603/ec13199] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Commercial producers of honey bee queens (Apis mellifera L.) have reported unexplained loss of immature queens during the larval or pupal stage. Many affected queen-rearing operations are situated among the almond orchards of California and report these losses in weeks after almond trees bloom. Almond flowers are a rich foraging resource for bees, but are often treated with fungicides, insecticides, and spray adjuvants during bloom. Anecdotal reports by queen producers associate problems in queen development with application of the fungicide Pristine (boscalid and pyraclostrobin) and spray adjuvants that are tank-mixed with it. To test the effect of these compounds on queen development, a new bioassay was developed in which queens are reared in closed swarm boxes for 4 d, until capping, with nurse bees fed exclusively on artificially contaminated pollen. Pollen was treated with four concentrations of formulated Pristine (0.4, 4, 40, and 400 ppm), a spray adjuvant (Break-Thru, 200 ppm), the combination of Pristine and spray adjuvant (400:200 ppm), the insect growth regulator insecticide diflubenzuron (100 ppm) as a positive control, or water as negative control. Chemical analysis revealed that low concentrations of pyraclostrobin (50 ppb), but no boscalid, were detectable in royal jelly secreted by nurse bees feeding on treated pollen. No significant difference in queen development or survival was observed between any of the experimental treatments and the negative control. Only diflubenzuron, the positive control, caused a substantial reduction in survival of immature queens.
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Affiliation(s)
- Reed M Johnson
- Department of Entomology, The Ohio State University-OARDC, 1680 Madison Ave., Wooster, OH 44691, USA.
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Johnson RM. Functional toxicogenomics in bees: recent advances towards mechanism-based risk assessment. Toxicol Lett 2013. [DOI: 10.1016/j.toxlet.2013.06.201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Johnson RM. S12.4 Chlamydia Trachomatis. Br J Vener Dis 2013. [DOI: 10.1136/sextrans-2013-051184.0060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Abstract
Background Chemical analysis shows that honey bees (Apis mellifera) and hive products contain many pesticides derived from various sources. The most abundant pesticides are acaricides applied by beekeepers to control Varroa destructor. Beekeepers also apply antimicrobial drugs to control bacterial and microsporidial diseases. Fungicides may enter the hive when applied to nearby flowering crops. Acaricides, antimicrobial drugs and fungicides are not highly toxic to bees alone, but in combination there is potential for heightened toxicity due to interactive effects. Methodology/Principal Findings Laboratory bioassays based on mortality rates in adult worker bees demonstrated interactive effects among acaricides, as well as between acaricides and antimicrobial drugs and between acaricides and fungicides. Toxicity of the acaricide tau-fluvalinate increased in combination with other acaricides and most other compounds tested (15 of 17) while amitraz toxicity was mostly unchanged (1 of 15). The sterol biosynthesis inhibiting (SBI) fungicide prochloraz elevated the toxicity of the acaricides tau-fluvalinate, coumaphos and fenpyroximate, likely through inhibition of detoxicative cytochrome P450 monooxygenase activity. Four other SBI fungicides increased the toxicity of tau-fluvalinate in a dose-dependent manner, although possible evidence of P450 induction was observed at the lowest fungicide doses. Non-transitive interactions between some acaricides were observed. Sublethal amitraz pre-treatment increased the toxicity of the three P450-detoxified acaricides, but amitraz toxicity was not changed by sublethal treatment with the same three acaricides. A two-fold change in the toxicity of tau-fluvalinate was observed between years, suggesting a possible change in the genetic composition of the bees tested. Conclusions/Significance Interactions with acaricides in honey bees are similar to drug interactions in other animals in that P450-mediated detoxication appears to play an important role. Evidence of non-transivity, year-to-year variation and induction of detoxication enzymes indicates that pesticide interactions in bees may be as complex as drug interactions in mammals.
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Affiliation(s)
- Reed M Johnson
- Department of Entomology, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America.
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Dahlgren L, Johnson RM, Siegfried BD, Ellis MD. Comparative toxicity of acaricides to honey bee (Hymenoptera: Apidae) workers and queens. J Econ Entomol 2012; 105:1895-1902. [PMID: 23356051 DOI: 10.1603/ec12175] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Acaricides are used to treat honey bee (Apis mellifera L.) colonies to control the varroa mite (Varroa destructor Anderson & Trueman), a worldwide threat to honey bee health. Although acaricides control a serious honey bee parasite and mitigate bee loss, they may cause harm to bees as well. We topically applied five acaricides, each with a different mode of action, to young adult queen and worker bees to generate dose-response curves and LD50. Twenty-four hours after treatment, queens were found to be three-times more tolerant of tau-fluvalinate and six-times more tolerant of thymol than workers when adjusted for body weight differences between workers (108 mg) and queens (180 mg). Queens survived the highest administered doses of fenpyroximate (1620 microg/g) and coumaphos (2700 microg/g) indicating that queens are at least 11-fold more tolerant of coumaphos and at least 54-fold more tolerant of fenpyroximate than workers. However, queens treated with as little as 54 microg/g of fenpyroximate exhibited reduced survival over 6 wk after treatment. Amitraz was the only acaricide tested for which queens were not more tolerant than workers. The striking difference in acaricide tolerance of queen and worker honey bees suggests physiological differences in how the two castes are affected by xenobiotics.
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Affiliation(s)
- Lizette Dahlgren
- Department of Entomology, University of Nebraska-Lincoln, 103 Entomology Hall, Lincoln, NE 68583, USA.
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Teeters BS, Johnson RM, Ellis MD, Siegfried BD. Using video-tracking to assess sublethal effects of pesticides on honey bees (Apis mellifera L.). Environ Toxicol Chem 2012; 31:1349-1354. [PMID: 22488825 DOI: 10.1002/etc.1830] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2011] [Revised: 01/03/2012] [Accepted: 01/23/2012] [Indexed: 05/31/2023]
Abstract
Concern about the role of pesticides in honey bee decline has highlighted the need to examine the effects of sublethal exposure on bee behaviors. The video-tracking system EthoVisionXT (Noldus Information Technologies) was used to measure the effects of sublethal exposure to tau-fluvalinate and imidacloprid on honey bee locomotion, interactions, and time spent near a food source over a 24-h observation period. Bees were either treated topically with 0.3, 1.5, and 3 µg tau-fluvalinate or exposed to 0.05, 0.5, 5.0, 50, and 500 ppb imidacloprid in a sugar agar cube. Tau-fluvalinate caused a significant reduction in distance moved at all dose levels (p < 0.05), as did 50 and 500 ppb imidacloprid (p < 0.001). Bees exposed to 50 and 500 ppb spent significantly more time near the food source than control bees (p < 0.05). Interaction time decreased as time in the food zone increased for both chemicals. This study documents that video-tracking of bee behavior can enhance current protocols for measuring the effects of pesticides on honey bees at sublethal levels. It may provide a means of identifying problematic compounds for further testing.
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Affiliation(s)
- Bethany S Teeters
- Department of Entomology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
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Johnson RM, Mao W, Pollock HS, Niu G, Schuler MA, Berenbaum MR. Ecologically appropriate xenobiotics induce cytochrome P450s in Apis mellifera. PLoS One 2012; 7:e31051. [PMID: 22319603 PMCID: PMC3272026 DOI: 10.1371/journal.pone.0031051] [Citation(s) in RCA: 93] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2011] [Accepted: 12/31/2011] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Honey bees are exposed to phytochemicals through the nectar, pollen and propolis consumed to sustain the colony. They may also encounter mycotoxins produced by Aspergillus fungi infesting pollen in beebread. Moreover, bees are exposed to agricultural pesticides, particularly in-hive acaricides used against the parasite Varroa destructor. They cope with these and other xenobiotics primarily through enzymatic detoxificative processes, but the regulation of detoxificative enzymes in honey bees remains largely unexplored. METHODOLOGY/PRINCIPAL FINDINGS We used several approaches to ascertain effects of dietary toxins on bee susceptibility to synthetic and natural xenobiotics, including the acaricide tau-fluvalinate, the agricultural pesticide imidacloprid, and the naturally occurring mycotoxin aflatoxin. We administered potential inducers of cytochrome P450 enzymes, the principal biochemical system for Phase 1 detoxification in insects, to investigate how detoxification is regulated. The drug phenobarbital induces P450s in many insects, yet feeding bees with phenobarbital had no effect on the toxicity of tau-fluvalinate, a pesticide known to be detoxified by bee P450s. Similarly, no P450 induction, as measured by tau-fluvalinate tolerance, occurred in bees fed xanthotoxin, salicylic acid, or indole-3-carbinol, all of which induce P450s in other insects. Only quercetin, a common pollen and honey constituent, reduced tau-fluvalinate toxicity. In microarray comparisons no change in detoxificative gene expression was detected in phenobarbital-treated bees. However, northern blot analyses of guts of bees fed extracts of honey, pollen and propolis showed elevated expression of three CYP6AS P450 genes. Diet did not influence tau-fluvalinate or imidacloprid toxicity in bioassays; however, aflatoxin toxicity was higher in bees consuming sucrose or high-fructose corn syrup than in bees consuming honey. CONCLUSIONS/SIGNIFICANCE These results suggest that regulation of honey bee P450s is tuned to chemicals occurring naturally in the hive environment and that, in terms of toxicological capacity, a diet of sugar is not equivalent to a diet of honey.
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Affiliation(s)
- Reed M Johnson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
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Abstract
Numerical taxonomy was done on 208 strains of marine bacteria. The collection was segregated into eight groups, seven of which contained Vibrio sp. Nucleic acid base ratio studies on a typical Vibrio sp. from each group and other genera were done. The phenotypically different Vibrio sp. had a narrow range of base ratios. The other genera had base ratios more similar to the base ratios reported for their genus than to each other as marine bacteria. The taxonomic groups are compared with generic classification and the strains' sources of isolations.
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Affiliation(s)
- R M Johnson
- Botany Department, Arizona State University, Tempe, Arizona USA
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Melendez RR, Bui D, Ellis MD, Johnson RM, Zempleni J. Identification of a potential role of K9‐biotinylated histone H3 in honeybee (Apis mellifera) development. FASEB J 2010. [DOI: 10.1096/fasebj.24.1_supplement.550.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Oakeshott JG, Johnson RM, Berenbaum MR, Ranson H, Cristino AS, Claudianos C. Metabolic enzymes associated with xenobiotic and chemosensory responses in Nasonia vitripennis. Insect Mol Biol 2010; 19 Suppl 1:147-163. [PMID: 20167025 DOI: 10.1111/j.1365-2583.2009.00961.x] [Citation(s) in RCA: 121] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
The numbers of glutathione S-transferase, cytochrome P450 and esterase genes in the genome of the hymenopteran parasitoid Nasonia vitripennis are about twice those found in the genome of another hymenopteran, the honeybee Apis mellifera. Some of the difference is associated with clades of these families implicated in xenobiotic resistance in other insects and some is in clades implicated in hormone and pheromone metabolism. The data support the hypothesis that the eusocial behaviour of the honeybee and the concomitant homeostasis of the nest environment may obviate the need for as many gene/enzyme systems associated with xenobiotic metabolism as are found in other species, including N. vitripennis, that are thought to encounter a wider range of potentially toxic xenobiotics in their diet and habitat.
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Affiliation(s)
- J G Oakeshott
- Commonwealth Scientific and Industrial Research Organisation Entomology, Acton, ACT, Australia.
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Werren JH, Richards S, Desjardins CA, Niehuis O, Gadau J, Colbourne JK, Werren JH, Richards S, Desjardins CA, Niehuis O, Gadau J, Colbourne JK, Beukeboom LW, Desplan C, Elsik CG, Grimmelikhuijzen CJP, Kitts P, Lynch JA, Murphy T, Oliveira DCSG, Smith CD, van de Zande L, Worley KC, Zdobnov EM, Aerts M, Albert S, Anaya VH, Anzola JM, Barchuk AR, Behura SK, Bera AN, Berenbaum MR, Bertossa RC, Bitondi MMG, Bordenstein SR, Bork P, Bornberg-Bauer E, Brunain M, Cazzamali G, Chaboub L, Chacko J, Chavez D, Childers CP, Choi JH, Clark ME, Claudianos C, Clinton RA, Cree AG, Cristino AS, Dang PM, Darby AC, de Graaf DC, Devreese B, Dinh HH, Edwards R, Elango N, Elhaik E, Ermolaeva O, Evans JD, Foret S, Fowler GR, Gerlach D, Gibson JD, Gilbert DG, Graur D, Gründer S, Hagen DE, Han Y, Hauser F, Hultmark D, Hunter HC, Hurst GDD, Jhangian SN, Jiang H, Johnson RM, Jones AK, Junier T, Kadowaki T, Kamping A, Kapustin Y, Kechavarzi B, Kim J, Kim J, Kiryutin B, Koevoets T, Kovar CL, Kriventseva EV, Kucharski R, Lee H, Lee SL, Lees K, Lewis LR, Loehlin DW, Logsdon JM, Lopez JA, Lozado RJ, Maglott D, Maleszka R, Mayampurath A, Mazur DJ, McClure MA, Moore AD, Morgan MB, Muller J, Munoz-Torres MC, Muzny DM, Nazareth LV, Neupert S, Nguyen NB, Nunes FMF, Oakeshott JG, Okwuonu GO, Pannebakker BA, Pejaver VR, Peng Z, Pratt SC, Predel R, Pu LL, Ranson H, Raychoudhury R, Rechtsteiner A, Reese JT, Reid JG, Riddle M, Robertson HM, Romero-Severson J, Rosenberg M, Sackton TB, Sattelle DB, Schlüns H, Schmitt T, Schneider M, Schüler A, Schurko AM, Shuker DM, Simões ZLP, Sinha S, Smith Z, Solovyev V, Souvorov A, Springauf A, Stafflinger E, Stage DE, Stanke M, Tanaka Y, Telschow A, Trent C, Vattathil S, Verhulst EC, Viljakainen L, Wanner KW, Waterhouse RM, Whitfield JB, Wilkes TE, Williamson M, Willis JH, Wolschin F, Wyder S, Yamada T, Yi SV, Zecher CN, Zhang L, Gibbs RA. Functional and evolutionary insights from the genomes of three parasitoid Nasonia species. Science 2010; 327:343-8. [PMID: 20075255 DOI: 10.1126/science.1178028] [Citation(s) in RCA: 715] [Impact Index Per Article: 51.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
We report here genome sequences and comparative analyses of three closely related parasitoid wasps: Nasonia vitripennis, N. giraulti, and N. longicornis. Parasitoids are important regulators of arthropod populations, including major agricultural pests and disease vectors, and Nasonia is an emerging genetic model, particularly for evolutionary and developmental genetics. Key findings include the identification of a functional DNA methylation tool kit; hymenopteran-specific genes including diverse venoms; lateral gene transfers among Pox viruses, Wolbachia, and Nasonia; and the rapid evolution of genes involved in nuclear-mitochondrial interactions that are implicated in speciation. Newly developed genome resources advance Nasonia for genetic research, accelerate mapping and cloning of quantitative trait loci, and will ultimately provide tools and knowledge for further increasing the utility of parasitoids as pest insect-control agents.
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Mao W, Rupasinghe SG, Johnson RM, Zangerl AR, Schuler MA, Berenbaum MR. Quercetin-metabolizing CYP6AS enzymes of the pollinator Apis mellifera (Hymenoptera: Apidae). Comp Biochem Physiol B Biochem Mol Biol 2009; 154:427-34. [PMID: 19737624 DOI: 10.1016/j.cbpb.2009.08.008] [Citation(s) in RCA: 93] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2009] [Revised: 08/23/2009] [Accepted: 08/25/2009] [Indexed: 12/01/2022]
Abstract
Although the honey bee (Apis mellifera) genome contains far fewer cytochrome P450 genes associated with xenobiotic metabolism than other insect genomes sequenced to date, the CYP6AS subfamily, apparently unique to hymenopterans, has undergone an expansion relative to the genome of the jewel wasp (Nasonia vitripennis). The relative dominance of this family in the honey bee genome is suggestive of a role in processing phytochemicals encountered by honey bees in their relatively unusual diet of honey (comprising concentrated processed nectar of many plant species) and bee bread (a mixture of honey and pollen from many plant species). In this study, quercetin was initially suggested as a shared substrate for CYP6AS1, CYP6AS3, and CYP6AS4, by its presence in honey, extracts of which induce transcription of these three genes, and by in silico substrate predictions based on a molecular model of CYP6AS3. Biochemical assays with heterologously expressed CYP6AS1, CYP6AS3, CYP6AS4 and CYP6AS10 enzymes subsequently confirmed their activity toward this substrate. CYP6AS1, CYP6AS3, CYP6AS4 and CYP6AS10 metabolize quercetin at rates of 0.5+/-0.1, 0.5+/-0.1, 0.2+/-0.1, and 0.2+/-0.1 pmol quercetin/ pmol P450/min, respectively. Substrate dockings and sequence alignments revealed that the positively charged amino acids His107 and Lys217 and the carbonyl group of the backbone between Leu302 and Ala303 are essential for quercetin orientation in the CYP6AS3 catalytic site and its efficient metabolism. Multiple replacements in the catalytic site of CYP6AS4 and CYP6AS10 and repositioning of the quercetin molecule likely account for the lower metabolic activities of CYP6AS4 and CYP6AS10 compared to CYP6AS1 and CYP6AS3.
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Affiliation(s)
- Wenfu Mao
- Department of Entomology, University of Illinois, Urbana, Illinois 61801-3795, USA
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Rhoads RP, Johnson RM, Rathbone CR, Liu X, Temm-Grove C, Sheehan SM, Hoying JB, Allen RE. Satellite cell-mediated angiogenesis in vitro coincides with a functional hypoxia-inducible factor pathway. Am J Physiol Cell Physiol 2009; 296:C1321-8. [PMID: 19386789 DOI: 10.1152/ajpcell.00391.2008] [Citation(s) in RCA: 94] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Muscle regeneration involves the coordination of myogenesis and revascularization to restore proper muscle function. Myogenesis is driven by resident stem cells termed satellite cells (SC), whereas angiogenesis arises from endothelial cells and perivascular cells of preexisting vascular segments and the collateral vasculature. Communication between myogenic and angiogenic cells seems plausible, especially given the number of growth factors produced by SC. To characterize these interactions, we developed an in vitro coculture model composed of rat skeletal muscle SC and microvascular fragments (MVF). In this system, isolated epididymal MVF suspended in collagen gel are cultured over a rat SC monolayer culture. In the presence of SC, MVF exhibit greater indices of angiogenesis than MVF cultured alone. A positive dose-dependent effect of SC conditioned medium (CM) on MVF growth was observed, suggesting that SC secrete soluble-acting growth factor(s). Next, we specifically blocked VEGF action in SC CM, and this was sufficient to abolish satellite cell-induced angiogenesis. Finally, hypoxia-inducible factor-1alpha (HIF-1alpha), a transcriptional regulator of VEGF gene expression, was found to be expressed in cultured SC and in putative SC in sections of in vivo stretch-injured rat muscle. Hypoxic culture conditions increased SC HIF-1alpha activity, which was positively associated with SC VEGF gene expression and protein levels. Collectively, these initial observations suggest that a heretofore unexplored aspect of satellite cell physiology is the initiation of a proangiogenic program.
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Affiliation(s)
- R P Rhoads
- Muscle Biology Group, Department of Animal Sciences, University of Arizona, Tucson, AZ 85721, USA
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