ArticlePDF Available

Flight performance of actively foraging honey bees is reduced by a common pathogen

Authors:

Abstract and Figures

Sudden and severe declines in honey bee (Apis mellifera) colony health in the US and Europe have been attributed, in part, to emergent microbial pathogens, however, the mechanisms behind the impact are unclear. Using roundabout flight mills, we measured the flight distance and duration of actively foraging, healthy-looking honey bees sampled from standard colonies, before quantifying the level of infection by Nosema ceranae and Deformed Wing Virus complex (DWV) for each bee. Neither the presence nor quantity of N. ceranae at low, natural levels of infection had any effect on flight distance or duration, but presence of DWV reduced flight distance by two thirds and duration by one half. Quantity of DWV was shown to have a significant, but weakly positive relation with flight distance and duration, however, the low amount of variation that was accounted for suggests further investigation by dose-response assays is required. We conclude that widespread, naturally occurring levels of infection by DWV weaken the flight ability of honey bees and high levels of within-colony prevalence are likely to reduce efficiency and increase the cost of resource acquisition. Predictions of implications of pathogens on colony health and function should take account of sub-lethal effects on flight performance. This article is protected by copyright. All rights reserved.
Content may be subject to copyright.
Flight performance of actively foraging honey bees is
reduced by a common pathogen
Trish Wells, Stephan Wolf,
Elizabeth Nicholls,
Helga Groll,
§
Ka S. Lim, Suzanne J. Clark,
Jennifer Swain, Juliet L. Osborne
{
and
Alison J. Haughton*
Rothamsted Research, Harpenden, UK.
Summary
Sudden and severe declines in honey bee (Apis melli-
fera) colony health in the US and Europe have been
attributed, in part, to emergent microbial pathogens,
however, the mechanisms behind the impact are
unclear. Using roundabout flight mills, we measured
the flight distance and duration of actively foraging,
healthy-looking honey bees sampled from standard
colonies, before quantifying the level of infection by
Nosema ceranae and Deformed Wing Virus complex
(DWV) for each bee. Neither the presence nor the
quantity of N.ceranae were at low, natural levels of
infection had any effect on flight distance or duration,
but presence of DWV reduced flight distance by two
thirds and duration by one half. Quantity of DWV was
shown to have a significant, but weakly positive rela-
tion with flight distance and duration, however, the
low amount of variation that was accounted for sug-
gests further investigation by dose-response assays
is required. We conclude that widespread, naturally
occurring levels of infection by DWV weaken the
flight ability of honey bees and high levels of within-
colony prevalence are likely to reduce efficiency and
increase the cost of resource acquisition. Predictions
of implications of pathogens on colony health and
function should take account of sublethal effects on
flight performance.
Introduction
Decadal and on-going declines in the number of colo-
nies of managed honey bees in the USA and Europe
have been well documented and have been attributed to
a number of stress factors (vanEngelsdorp and Meixner,
2010; Lee et al., 2015) that include pests and patho-
gens, pesticides and limited quality and availability of
food resource (Klein et al., 2007; Neumann and Carreck,
2010; Potts et al., 2010; Becher et al., 2014; Goulson
et al., 2015). These stressors interact with individual
bees, resulting in lethal and sublethal effects that curtail
longevity (Alaux et al., 2010; Aufauvre et al., 2012; Dou-
blet et al., 2015; Retschnig et al., 2015) and alter fitness
traits and behavioural and physiological performance,
having implications for the entire colony (Becher et al.,
2014; Rumkee et al., 2015). Pathogens affect behaviour
directly through active manipulation evolved to facilitate
transmission, although this is yet to be demonstrated in
honey bees (see Mayack et al., 2015), and indirectly in
response to an associated increase in the host’s meta-
bolic rate (Mayack and Naug, 2009; Naug and Gibbs,
2009; Mayack and Naug, 2015) or manipulating hormon-
al pathways (Mayack et al., 2015).
Although living in social groups has fitness benefits
(Wilson, 1975), one of the trade-offs is the increased
risk of disease transmission because of close living
quarters and high genetic relatedness (Schmid-Hempel,
1998; Tarpy, 2003). Honey bee colonies comprise thou-
sands of individuals living in close contact and predict-
ably, pests and pathogens are wide-spread and
commonly occurring therein (Mouret et al., 2013; Manley
et al., 2015; McMahon et al., 2015) and have been impli-
cated in honey bee colony losses in the U.S. and
Europe (Higes et al., 2008; vanEngelsdorp and Meixner,
2010). Deformed wing virus (DWV), Varroa destructor
virus-1 (VDV-1) and Nosema ceranae (Fries) are three
of the most prevalent pathogens present in European
honey bee colonies (Martin-Hernandez et al., 2007;
Mouret et al., 2013; McMahon et al., 2015). The DWV
complex (referred to henceforth as DWV) is a rapidly
evolving and recombining group of closely related
positive-sense, single-stranded RNA Iflaviruses, that
includes VDV-1 (de Miranda and Genersch, 2010; Moore
et al., 2011; Zioni et al., 2011; Martin et al., 2012; Mor-
decai et al., 2016). DWV is vectored by the parasitic
Received 27 May, 2016; accepted 7 June, 2016. *Correspondence.
E-mail alison.haughton@rothamsted.ac.uk; Tel. (144) 1582
938454; Fax: (144) 1582 760981. Present addresses:
School of
Biological and Chemical Sciences, Queen Mary University of Lon-
don, London, UK.
School of Life Sciences, University of Sussex,
Brighton, UK.
§
PPD, Granta Park, Great Abington, Cambridge, UK.
Environment and Sustainability Institute, University of Exeter, Pen-
ryn, UK.
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in
any medium, provided the original work is properly cited.
Environmental Microbiology Reports (2016) 8(5), 728–737 doi:10.1111/1758-2229.12434
mite, Varroa destructor Anderson & Truman, (Martin
et al., 2012) and is transmitted both horizontally (faecal–
cannibal–oral) (Yue and Genersch, 2005; Mockel et al.,
2011) and vertically (parent–offspring) (Chen et al.,
2006; Yue et al., 2006; Yue et al., 2007; de Miranda and
Fries, 2008; Yanez et al., 2012). Clinically relevant infec-
tions by DWV, defined as presence of DWV RNA in the
brain (Mockel et al., 2011), do not always result in bees
exhibiting a phenotype (deformed wings) (de Miranda
and Genersch, 2010; Zioni et al., 2011). The microspori-
dian gut parasite, N.ceranae, historically a parasite of
A.cerana, now includes A. mellifera as an alternative
host (Higes et al., 2006) and causes no visible, external
symptoms of infection. N.ceranae infects and reprodu-
ces inside epithelial cells of the midgut and is believed
to be transmitted in the hive principally via the oral–oral
pathway (Smith, 2012).
Prevalence and diversity of disease pathogens in hon-
ey bee colonies are probably greater than previously
thought (Tentcheva et al., 2004; Siede et al., 2008; Furst
et al., 2014; McMahon et al., 2015), since infection is
often inapparent (Zioni et al., 2011; Mouret et al., 2013)
or below the level of detection (Martin et al., 2013a). It
is unsurprising, therefore, that research into the suble-
thal effects of commonly occurring pathogens on honey
bee behaviour is limited, yet of increasing interest. Other
than understanding transmission (Bowen-Walker et al.,
1999; Yanez et al., 2012; Manley et al., 2015), and influ-
ence on gene expression (Steinmann et al., 2015),
physiology (Yang and Cox-Foster, 2007) and learning
(Iqbal and Mueller, 2007) of DWV, research into suble-
thal behavioural effects of pathogens has largely been
limited to N.ceranae. This gut parasite has been shown
to modify many aspects of honey bee behaviour, includ-
ing increased maturation (Dussaubat et al., 2013; Gob-
lirsch et al., 2013), impaired learning (Mallon et al.,
2003; Kralj and Fuchs, 2010), enhanced energetic stress
(Mayack and Naug, 2009; 2010; Mayack and Naug,
2015) and changes to flight and homing behaviour
(Alaux et al., 2014; Naug, 2014; Wolf et al., 2014; Perry
et al., 2015). N.ceranae has previously been shown to
increase the number of foraging trips and flight duration,
reduce the time spent in the hive (Alaux et al., 2014;
Naug, 2014; Retschnig et al., 2015) and reduce foraging
efficiency (Naug, 2014), but since individuals were not
tracked once they had left the hive, the proportion of the
time spent flying or resting was unknown. In contrast,
exploring whether DWV affects flight behaviour in bees
that do not exhibit the visual symptoms of deformed
wings typical of high levels of infection (de Miranda and
Genersch, 2010), yet may already be suffering altered
physiological, neurological or immunological function
remains to be done.
Flight performance of an individual can determine its
potential resource-gathering capability and in social
insects, efficient resource acquisition can have profound
effects at the colony level (Becher et al., 2014). The far-
ther the distance and longer the duration an individual is
able to travel allows more of the landscape to be
exploited for resources. Understanding flight perfor-
mance of foraging honey bees challenged by pathogens
is therefore of key importance not only for effective colo-
ny management, but also for protecting pollination ser-
vice provision (Potts et al., 2010) by managed and wild
species. Measuring flight performance of individual bees
is notoriously difficult though; bees are small, fast flyers
covering vast foraging areas. Tracking individuals using
harmonic radar (Riley et al., 1996) is currently the only
technology available to record bee flight routes in the
field, however, it is not possible to simultaneously track
two or more individuals to estimate the spatial and tem-
poral limits of bee flight under similar environmental con-
ditions. In contrast, assessing flight performance using
tethered individuals on flight mills provides an elegant
opportunity to explore individual endurance limits allow-
ing maximal control of environmental factors other than
pathogen load (Brodschneider et al., 2009).
Here, we sought to test the null hypothesis that natu-
ral levels of infection by N.ceranae and the DWV com-
plex (comprising DWV and VDV-1) in forager honey
bees have no effect on flight performance. Thus, the
aims of this work were to (i) quantify the natural levels
of infection by N.ceranae and DWV 1VDV-1 in actively
foraging, apparently healthy honey bees and, (ii) eluci-
date the sublethal effects of these commonly occurring
pathogens on flight distance and duration.
Results and discussion
Of 127 bees that were analysed, 73 tested positive for
one of the two pathogens that were screened, 20 tested
positive for both pathogens and 34 tested negative for
neither pathogen. DWV was more prevalent (83 bees)
than N.ceranae (30 bees) and the level of co-infection
was lower (20 bees) than for single infection (N.ceranae
10 bees; DWV 63 bees). Of the bees that tested positive
for DWV and N. ceranae, mean loads were 3.6 310
10
6
SD 1.8 310
11
copies head
21
and 1.7 310
4
6SD 2.1
310
4
mid-gut
21
, respectively. The levels of infection we
recorded are comparable to those reported elsewhere
for standard, managed apiaries (Gauthier et al., 2007;
McMahon et al., 2015; Steinmann et al., 2015).
Tethered flight mills have been successfully used to
measure the relative flight performance of different taxa
under controlled, standardised conditions (Riley et al.,
1997; Blackmer et al., 2004; Spiewok and Schmolz,
2006; Brodschneider et al., 2009; Taylor et al., 2010;
Flight performance is reduced by a common pathogen 729
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
Dorhout et al., 2011; Jones et al., 2015), however it is
important to recognise the limitations of this experimen-
tal technique. Flight mills restrict the physical and bio-
physical dynamics of natural flight, where reduced drag
and a lack of need to produce uplift have been shown to
result in lower levels of expended energy than are readi-
ly available (Riley et al., 1997) which could result in
enhanced measures of flight performance than are pos-
sible when insects are in free flight. Equally, a lack of
stimuli, such as olfactory cues from sources of forage,
to initiate and sustain flight behaviour, could result in
reduced measures of flight performance. Despite these
differences to natural free-flight conditions, tethered
flight mills remain an important instrument for measuring
the relative flight performance of worker honey bees,
given the assumption that handling, tethering and
restriction of natural cues affect the behaviour and per-
formance of the test bees equally.
Contrary to our expectation and the findings of previ-
ous work (e.g. Alaux et al., 2014; Naug, 2014; Wolf
et al., 2014), we found no effect of either presence of N.
ceranae on flight distance (F
1, 121.5
50.71, P50.400) or
duration (F
1, 121.9
51.39, P50.240) or the amount of N.
ceranae on flight parameters (Table 1). Honey bees
exclusively use carbohydrates to power flight activity
(Sacktor, 1970; Rothe and Nachtigall, 1989) that
accounts for 30% of the total energy expenditure of a
forager bee (Harrison and Fewell, 2002). In this study,
bees were flown to exhaustion before being fed a known
and finite amount of energy in the sucrose meal (c.f.
Gmeinbauer and Crailsheim, 1993; Hanauer-Thieser
and Nachtigall, 1995; Brodschneider et al., 2009) that
fuels the subsequent test flight. The assumption is,
therefore, that bees flown to exhaustion have no remain-
ing energy reserves available to them (Gmeinbauer and
Crailsheim, 1993). As an obligate gut parasite without
mitochondria, Nosema species have been shown to
cause energetic stress by reducing the amount of ener-
gy available to an infected bee. Trehalose, which is syn-
thesised in invertebrate haemolymph from dietary
sucrose and used for the rapid release of energy used
in flight (Thompson, 2003), is decreased in bees natural-
ly infected with Nosema and is thought to lead to signifi-
cant decreases in flying ability (Mayack and Naug,
2010). In response to Nosema-induced energetic stress,
infected honey bees consume more energy-rich food
(Mayack and Naug, 2009; Martin-Hernandez et al.,
2011) and reduce food-sharing with nest-mates (Naug
and Gibbs, 2009). Indeed, Nosema-induced energetic
limitations have been suggested as an underlying mech-
anism behind the increased likelihood of failure of forag-
ers to return to the hive (Wolf et al., 2014), increased
periods of time spent on foraging trips (Kralj and Fuchs,
2010; Alaux et al., 2014; Naug, 2014), and increased
number of foraging trips (Dussaubat et al., 2013). How-
ever, the different experimental approaches of these
studies may explain the apparent conflict in our results
that naturally occurring, low levels of infection by
Nosema have no effect on flight performance. Firstly, the
studies did not directly measure flight duration and dis-
tance of individuals, rather they measured time spent
outside the colony and were unable to distinguish
between bee movement (flight) and resting. Secondly,
the studies did not administer known quantities of ener-
gy prior to measuring flight activity, and so they were
unable to determine the effects of Nosema-induced
energetic stress on honey bee flight. Thirdly, and per-
haps most significantly, in some of the previous work,
bees were inoculated with Nosema spores (Kralj and
Fuchs, 2010; Dussaubat et al., 2013; Alaux et al., 2014;
Naug, 2014; Wolf et al., 2014) that resulted in spore
loads in the whole abdomen (Alaux et al., 2014) and
mid-gut (Dussaubat et al., 2013; Wolf et al., 2014)
orders of magnitude greater than their controls, while
the natural level of Nosema infection we report here was
lower than the control groups (Dussaubat et al., 2013;
Alaux et al., 2014). Finally, whilst we recognise that we
tested for just two pathogens in our experiment, screen-
ing exclusively for Nosema in some previous work
excluded other pathogens that may have influenced
flight behaviour (Mayack and Naug, 2009; Naug and
Gibbs, 2009; Kralj and Fuchs, 2010; Martin-Hernandez
et al., 2011; Dussaubat et al., 2013; Alaux et al., 2014).
Only 10 of the bees that were flown subsequently
screened positive exclusively for N.ceranae, leading,
retrospectively, to low statistical power (32%) for detect-
ing differences in flight performance of Nosema-infected
and uninfected bees of the magnitude reported by Naug
(2014) for inoculated bees. However, 99% confidence
intervals for the observed ratios of flight durations for
the two groups, based on either all bees flown or only
on bees uninfected with DWV (see Supporting Informa-
tion Appendix S1), did not contain values as extreme as
the halving of flight duration for uninfected relative to
Table 1. Results from intra-block regression models fitting relation-
ships between measures of honey bee flight performance and path-
ogen load, with pathogen effects fitted in different orders after
accounting for flight mill differences (N593).
Distance Duration
Model terms F
1,86
PF
1,86
P
Order 1
1DWV 9.07 0.003 8.81 0.004
1Nc 1.51 0.222 0.71 0.402
Order 2
1Nc 0.45 0.503 0.09 0.767
1DWV 10.13 0.002 9.43 0.003
Nc 5Nosema ceranae
730 T. Wells et al.
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
Nosema-infected bees that was reported by Naug
(2014). Thus, we were unable to reject the null hypothe-
ses of no statistical differences in flight performance
between groups of bees uninfected and infected by low
levels of N. ceranae, but we do not preclude or dismiss
previously reported effects at higher levels of infection
Bees that were infected by DWV, and yet presented
no obvious morphological symptoms of infection, flew
shorter distances (F
1, 121.4
510.17, P50.002) and dura-
tions (F
1, 117.1
59.08, P50.003) than bees uninfected
with DWV (Figs. 1A and B). Linear mixed modelling pre-
dicted bees infected and uninfected with DWV flew geo-
metric mean distances of 150.0 m (95% confidence
interval: 90.1–249.6 m) and 480.2 m (252.4–913.3 m),
and durations of 347.1 s (255.6–471.3 s) and 718.3 s
(480.2–1074.6 s) respectively.
DWV is transmitted to honey bees horizontally and
vertically within the hive (Chen et al., 2006; Yue et al.,
2006; Yue et al., 2007; de Miranda and Fries, 2008;
Yanez et al., 2012) and is vectored by V.destructor, par-
asitising adults, larvae and pupae (Yang and Cox-Foster,
2007; Gisder et al., 2009; Mockel et al., 2011). V.
destructor, and by association, DWV, have been impli-
cated in disrupting immunological responses and behav-
iour in asymptomatic honey bees. It has previously been
shown that genes for protein repair and the labelling of
protein for degradation were up-regulated in pupae that
were parasitized by V.destructor, while genes involved
in wing development processes were down-regulated
(Navajas et al., 2008) suggesting disruption of larval and
adult development. Furthermore, parasitism by the var-
roa mite of young adult worker bees with normal wings
inhibited protein metabolism, energy production and
expression of immune genes (Yang and Cox-Foster,
2005; Alaux et al., 2011) and reduced longevity (Yang
and Cox-Foster, 2007). Significantly, studies have suc-
cessfully linked varroa mite parasitism with the direct
effects of infection by DWV, providing evidence for DWV-
induced reduced immune gene expression (Steinmann
et al., 2015), impaired associative olfactory learning and
memory formation (Iqbal and Mueller, 2007). Thus, it is
clear that there are diverse effects of sublethal infection
by DWV on honey bees. Our data suggest, for the first
time, that DWV may affect another important behaviou-
ral function, in reducing flight performance. The mecha-
nisms behind these reductions in flight duration and
distance are, as yet unclear, but it is possible that the
disruption in expression of genes associated with protein
metabolism, energy production and internal wing devel-
opment may reduce the physical fitness characters of
the forager bees. Another explanation for reduced flight
performance in bees infected with DWV may be related
to pathogen-induced accelerated behavioural develop-
ment. Enhanced behavioural maturation from in-hive to
forager bees has been observed in bees infected with
N.ceranae (Dussaubat et al., 2013; Goblirsch et al.,
2013; Mayack et al., 2015) and reduced flight perfor-
mance has been recorded for forager bees from colo-
nies exposed to high levels of the DWV-vector, V.
destructor (Blanken et al., 2015). Blanken et al. (2015)
found that increased body mass, a character associated
with precocious foragers (Vance et al., 2009), partly
explained the relationship between exposure to the var-
roa mites and reduced flight performance while Schip-
pers et al. (2010) report differences in flight muscle
biochemistry between polyethic groups that may explain
poorer flight performance. McDonnell et al. (2013) note
that the similarity in brain transcription profiles of control
Fig. 1. A. Box plots of log distance and B. log duration travelled by
bees that tested negative for DWV and N.ceranae (-pathogens),
bees infected with N.ceranae only, DWV only and N.cera-
nae 1DWV. Box: median (central line) 6quartiles; whiskers: mini-
mum – maximum values. Number of bees tested in parentheses.
Nc 5N.ceranae.
Flight performance is reduced by a common pathogen 731
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
honey bees and those infected with DWV or N.ceranae
suggest that any provocation of precocious foraging
occurs because of self-removal from the colony, as a
form of social immunity (Meunier, 2015). We are unable
to confirm an association between body mass, and
thence DWV-induced precocious foraging in our experi-
ment, however our finding that there was no direct effect
of DWV load on wing size (F
1, 17
50.005, P50.945;
N519), infers this may be a plausible explanation that
warrants further investigation.
Predictive models including only DWV indicate a
weakly positive relationship between amount of DWV
and flight distance (regression coefficient 50.060,
SE 50.0199, P50.003) and duration (regression coef-
ficient 50.039, SE 50.0132, P50.004) (Table 1). Whilst
these relationships were significant, the models only
accounted for 8.6% and 7.1% of the variation in distance
and duration, respectively (Fig. 2A and B). This perplex-
ing result requires further investigation, not least
because so little of the variation was accounted for by
DWV in the models, but also because the weak relation-
ship over the range of levels of infection predicts such
small increases in distance and time travelled (regres-
sion coefficients of 0.06 and 0.04), which cannot be con-
sidered to be biologically significant. Conducting dose–
response assays of DWV and N.ceranae on flight
behaviour and genomic response are prime areas of
future research.
Co-infection by the pathogens in this experiment
occurred in 15.7% of the bees we tested and in agree-
ment with Martin et al. (2013b), we found no association
between the presence and absence of N.ceranae and
DWV (Pearson v
2
50.03, df 51, P50.863) and nor
were there interactions between the two pathogens and
either distance (F
1, 121.6
51.35, P50.248) or duration
(F
1, 122.1
51.08, P50.301). It is unlikely, then, that there
were confounding effects of these pathogens on flight
behaviour in this experiment.
In conclusion, the bees tested here were representa-
tive of colonies with natural levels of N.ceranae and
DWV infection, where inapparent, but clinically relevant
infection by DWV was shown to reduce the distance and
duration of flights in forager bees. If the reduced flight
abilities we recorded on the tethered flight mills operate
in the field under natural, free-flight conditions, it is likely
that sublethal effects of DWV infection are more wide-
spread than previously thought. Indeed, recorded (Gen-
ersch et al., 2010; Dainat et al., 2012) and predicted
(Kielmanowicz et al., 2015) over-winter colony losses
have been attributed to natural levels of DWV infection.
Possible consequences of reduced flight endurance per
unit of energy include less efficient and more costly
resource acquisition for the individual and for the colony,
particularly in landscapes where forage resources are
spatio-temporally sparsely and patchily distributed, and
enhanced risk of premature death because of increased
exposure to predators and physiological fatigue. Predict-
ing and scaling the implications of our findings under
artificial conditions to colonies in natural field conditions
where DWV is persistently and highly prevalent will
require further studies to understand behavioural
responses to pathogen-mediated compromises in flight
performance, including for example, whether there are
trade-offs between resource utilised by the bee and that
contributed to the colony.
Fig. 2. Fitted regression line (solid) with 95% confidence intervals
(dashed) relating A. flight distance (regression coefficient 50.060,
SE 0.0199, P50.003) B. flight duration (regression coef-
ficient 50.039, SE 0.0132, P50.004) to DWV load of 93 bees
flown on the flight mill.
732 T. Wells et al.
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
Experimental procedures
Honey bees
Returning, actively foraging honey bees with no visible
signs of disease (dysentery or malformed wings) and
carrying corbicular pollen were randomly selected on the
morning of the flight test from five, conventionally
managed apiaries, comprising 14 colonies, within
10 km of Rothamsted Research, UK (51848028.8300N,
000822031.5800W) in July, August and September 2012
and August and September 2013. The bees were placed
into hoarding cages (Williams et al., 2013) with free
access to 1M sucrose syrup and water and then placed
in an incubator set at 328C to allow preparation of the
bees for flight performance testing on the flight mill.
Flight performance
We recorded flight distance and duration as two meas-
ures of flight performance using roundabout flight mills,
similar to those used in many studies to characterise
insect flight ability (Bradley and Altizer, 2005; Brodsch-
neider et al., 2009; Dorhout et al., 2011; Sappington and
Burks, 2014). A set of five flight mills, that consisted of a
lightweight arm suspended at the centre by two magnets
forming an almost resistance-free axis (see Chapman
et al., 2015) and surrounded by equally sized and
spaced monochrome vertical stripes surround each flight
mill to provide the illusion of movement (Hrassnigg and
Crailsheim, 1999), were located in a controlled environ-
ment room set at 248C with constant overhead lighting.
Test bees had an Opalith disc attached to the thorax
(Human et al., 2013), before being allowed to rest in the
hoarding cage for 45 minutes before being tested on the
mill. Immediately prior to connecting to the flight mill, an
attachment (15 mm x 1 mm) was glued (Evo-Stik impact
multipurpose adhesive) onto the Opalith disc. The bee,
holding a small ball of paper between her legs as a stim-
ulus for spontaneous flight (Brodschneider et al., 2009;
Sappington and Burks, 2014), and complete with attach-
ment, was then connected to the flight mill arm and a
counter weight of similar mass was attached to the other
end of the arm. The flight mill allows the bee to fly in a
circular trajectory, with a circumference of 1m, and the
embedded microcontroller board records the total dis-
tance and duration flown by the bee at 5 s intervals to
the nearest 20 cm.
To control the amount of energy available for flight,
each bee was allowed to fly to exhaustion in order to
deplete the sugar reserves in the honey stomach prior
to being fed a known amount of energy (Gmeinbauer
and Crailsheim, 1993; Brodschneider et al., 2009). The
exhaustion flight was completed when, despite being
stimulated, the bee did not recommence flying for more
than 30 s. The bee was removed from the mill, fed 10 ml
of 1M sucrose solution using a pipette before being re-
attached to the mill for flight performance testing until
the bee again ceased flying because of lack of energy.
The bee was removed from the flight mill, placed in an
Eppendorf tube and stored at 2808C. Test flights were
terminated when, despite stimulation following a pause
in flight, bees did not resume flight.
Disease analysis
Nosema spore counts midgut
21
were determined micro-
scopically using a Neubauer improved 5x5
haemocytometerfollowing the methods of Human et al.
(2013). The digestive tract was removed from the bee,
and the midgut was isolated and homogenised in 500 ml
of distilled water using a micropestle. Nosema spores
were counted in four haemocytometer chambers and
the total number of spores in a volume of 0.28 mm
2
was
counted per chamber. To confirm species identification
(N.ceranae or N.apis), spores were identified using
species-specific PCR (Fries et al., 2013; Wolf et al.,
2014).
The presence of DWV-complex RNA in the brains of
honey bees with apparently normal wings indicates clini-
cally relevant, overt infection by DWV (Genersch et al.,
2010; Mockel et al., 2011), so we quantified absolute
copy numbers of positive-strand DWV and VDV-1 in the
heads of the test bees. Each head was homogenised in
600 ml of lysis buffer (RLT Buffer, Qiagen, Manchester,
UK) with 1% b-mercaptoethanol (Qiagen, Manchester,
UK). RNA was extracted from this supernatant using the
RNeasy Mini kit affinity column purification (Qiagen,
Manchester, UK) in a QIAcube robot (Qiagen, Manches-
ter, UK) and quantified using an Epoch microplate spec-
trophotometer (BioTek, Swindon, UK). Total cDNA was
synthesized cDNA from 800 ng RNA using M-MLV
reverse transcriptase (Promega). For absolute quantifi-
cation, duplicate qRT-PCR was performed for each sam-
ple using SYBRgreen Sensimix (Bioline, Luckenwalde,
Germany) in the following program: 5 min at 958C, fol-
lowed by 40 cycles of 10 s at 958C, 30 s at 578C, and
30 s at 728C (read) and data were normalised using the
honey bee reference gene RP49 (Lourenco et al.,
2008). An RNA-free HPLC-water and a virus-positive
sample cDNA were run as negative and positive control
respectively in each reaction run. Following PCR, DNA
was denatured for 1 min at 958C and cooled to 558Cfor
1 min. A melting profile was generated from 558Cto
958C (0–58Cs
21
increments). Absolute quantification of
DWV and VDV-1 was calculated using duplicate DNA
standard curves of purified flanking PCR products with
efficiencies between 90% and 100% and correlation
coefficients (R
2
) from 0.990 to 0.999. To account for
Flight performance is reduced by a common pathogen 733
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
potential variation in sample quality, an upper cycle
threshold (Ct) of 35 was set for RP49, above which
samples were not included in quantitative analysis (Blan-
chard et al., 2007; de Miranda et al., 2013). The primers
used were: DWV: DWV-F2, DWV-R2a; VDV: VDV-F2,
VDV-R2a (McMahon et al., 2015).
Wing size
Acute DWV infection frequently results in, amongst other
symptoms, malformed wings that render bees incapable
of flight. In order to estimate effects of pathogen on
wing size and subsequent flight performance, wings
were removed from a subsample of the bees stored for
pathogen analyses. Both forewings from 19 bees were
mounted between two microscope slides and scanned
(4800 dpi) before measuring the combined lengths of
three wing venation characters as surrogate measures
of wing size (D2, D3, D7, after Dedej and Nazzi, 1994;
Jaffe and Moritz, 2010). Each character on both wings
was measured three times, to account for measurement
error, giving a mean total length of the characters per
bee.
Statistical analysis
The flights of 476 bees were assessed on the mills.
Since we sought to test the effect of pathogens on the
range of flight abilities of apparently healthy bees
recorded on the flight mill, nonflyers (N531) were
excluded from the analysis. Laboratory constraints
necessitated the creation of a subset of individuals from
the remaining 445 bees for subsequent disease analy-
sis. Therefore, bees classified as strong or reluctant
flyers (test flight duration greater or less than 10 min,
respectively), were matched, as closely as possible, by
test date and colony. This process created a pooled sub-
set of 127 bees for which the effects of presence and
amount of pathogen load on flight performance (Sup-
porting Information Table S1) were analysed.
The disease variables were skewed and so were
transformed to logarithms (base 10) after adding an off-
set of 0.01 to allow for the absence of pathogens. The
measures of flight performance (distance and duration)
were also logged (base 10) to achieve homogeneity of
variances and normality.
We first tested whether disease status (based on a 2
32 factorial treatment structure representing presence
and absence of each of the two pathogens) affects flight
distance or duration using a linear mixed model fitted
using restricted maximum-likelihood (REML), with flight
mill included as a random effect.
We then tested, for diseased bees only, the relation-
ship between measures of flight performance and quan-
titative pathogen load, using an intra-block regression
approach (Welham et al., 2015). Initial analyses with cal-
endar month included in the random model suggested
negligible temporal effects hence the random model was
subsequently simplified to include flight mill effects only.
Block effects (flight mill) were fitted before pathogen
terms, the latter fitted first individually, then together.
Statistically nonsignificant fixed effects were dropped
and the resulting parsimonious models were used to
obtain predictions. Finally, we analysed the effect of
DWV load on wing length (transformed to logarithms
(base 10) after adding an offset of 0.01) using simple
linear regression. All analyses were done using GenStat
17 (VSNI, 2014).
Acknowledgements
We thank Chris Bass, Chris Jones, Bartek Troczka, Dino
McMahon and Anja Miertsch for laboratory assistance and
Robert Paxton and Jason Chapman for commenting on an
earlier draft. This work was funded by the Insect Pollinators
Initiative (IPI) grants BB/I000100/1, BB/I000097/1 and BB/
I000097/2, C.B. Dennis British Beekeepers’ Research
Trust and the High Wycombe Beekeepers’ Association.
The IPI is funded jointly by the BBSRC, Defra, NERC, The
Scottish Government and The Wellcome Trust, under the
LWEC Partnership. Rothamsted Research is a national
institute of bioscience strategically funded by the BBSRC.
References
Alaux, C., Dantec, C., Parrinello, H, and Le Conte, Y.
(2011) Nutrigenomics in honey bees: digital gene expres-
sion analysis of pollen’s nutritive effects on healthy and
varroa-parasitized bees. BMC Genomics 12: 496.
Alaux, C., Crauser, D., Pioz, M., Saulnier, C, and Le Conte,
Y. (2014) Parasitic and immune modulation of flight activi-
ty in honey bees tracked with optical counters. J Exp Biol
217: 3416–3424.
Alaux, C., Brunet, J.L., Dussaubat, C., Mondet, F.,
Tchamitchan, S., Cousin, M., et al. (2010) Interactions
between nosema microspores and a neonicotinoid weak-
en honeybees (Apis mellifera). Environ Microbiol 12:
774–782.
Aufauvre, J., Biron, D.G., Vidau, C., Fontbonne, R., Roudel,
M., Diogon, M., et al. (2012) Parasite-insecticide interac-
tions: a case study of Nosema ceranae and fipronil syn-
ergy on honeybee. Sci Rep 2:7.
Becher, M.A., Grimm, V., Thorbek, P., Horn, J., Kennedy,
P.J, and Osborne, J.L. (2014) BEEHAVE: a systems mod-
el of honeybee colony dynamics and foraging to explore
multifactorial causes of colony failure. J Appl Ecol 51:
470–482.
Blackmer, J.L., Naranjo, S.E, and Williams, L.H. (2004)
Tethered and untethered flight by lygus hesperus and
lygus lineolaris (heteroptera: miridae). Environ Entomol
33: 1389–1400.
Blanchard, P., Ribiere, M., Celle, O., Lallemand, P., Schurr,
F., Olivier, V., et al. (2007) Evaluation of a real-time two-
step RT-PCR assay for quantitation of chronic bee
734 T. Wells et al.
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
paralysis virus (CBPV) genome in experimentally-infected
bee tissues and in life stages of a symptomatic colony.
J Virol Methods 141: 7–13.
Blanken, L.J., van Langevelde, F, and van Dooremalen, C.
(2015) Interaction between varroa destructor and imida-
cloprid reduces flight capacity of honeybees. Proc R Soc
B[Epub ahead of print]. DOI: 10.1098/rspb.2015.1738.
Bowen-Walker, P.L., Martin, S.J, and Gunn, A. (1999) The
transmission of deformed wing virus between honeybees
(Apis mellifera L.) by the ectoparasitic mite varroa jacob-
soni Oud. J Invertebr Pathol 73: 101–106.
Bradley, C.A and Altizer, S. (2005) Parasites hinder mon-
arch butterfly flight: implications for disease spread in
migratory hosts. Ecol Lett 8: 290–300.
Brodschneider, R., Riessberger-Galle, U, and Crailsheim, K.
(2009) Flight performance of artificially reared honeybees
(Apis mellifera). Apidologie 40: 441–449.
Chapman, J.W., Reynolds, D.R, and Wilson, K. (2015)
Long-range seasonal migration in insects: mechanisms,
evolutionary drivers and ecological consequences. Ecol
Lett 18: 287–302.
Chen, Y., Evans, J, and Feldlaufer, M. (2006) Horizontal
and vertical transmission of viruses in the honey bee,
apis mellifera. J Invertebr Pathol 92: 152–159.
Dainat, B., Evans, J.D., Chen, Y.P., Gauthier, L, and
Neumann, P. (2012) Dead or alive: deformed wing virus
and varroa destructor reduce the life span of winter Hon-
eybees. Appl Environ Microbiol 78: 981–987.
de Miranda, J.R and Fries, I. (2008) Venereal and vertical
transmission of deformed wing virus in honeybees (Apis
mellifera L.). J Invertebr Pathol 98: 184–189.
de Miranda, J.R and Genersch, E. (2010) Deformed wing
virus. J Invertebr Pathol 103: S48–S61.
de Miranda, J.R., Bailey, L., Ball, B.V., Blanchard, P., Budge,
G.E., Chejanovsky, N., et al. (2013) Standard methods for
virus research in Apis mellifera.J Apic Res 52:
Dedej, S and Nazzi, F. (1994) Two distances of forewing
venation as estimates of wing size. J Apic Res 33:
59–61.
Dorhout, D.L., Sappington, T.W., Lewis, L.C, and Rice, M.E.
(2011) Flight behaviour of european corn borer infected
with nosema pyrausta.J Appl Entomol 135: 25–37.
Doublet, V., Labarussias, M., de Miranda, J.R., Moritz,
R.F.A, and Paxton, R.J. (2015) Bees under stress: suble-
thal doses of a neonicotinoid pesticide and pathogens
interact to elevate honey bee mortality across the life
cycle. Environ Microbiol 17: 969–983.
Dussaubat, C., Maisonnasse, A., Crauser, D., Beslay, D.,
Costagliola, G., Soubeyrand, S., et al. (2013) Flight
behavior and pheromone changes associated to Nosema
ceranae infection of honey bee workers (apis mellifera)in
field conditions. J Invertebr Pathol 113: 42–51.
Fries, I., Chauzat, M.P., Chen, Y.P., Doublet, V., Genersch,
E., Gisder, S., et al. (2013) Standard methods for
nosema research. J Apic Res 52: 28.
Furst, M.A., McMahon, D.P., Osborne, J.L., Paxton, R.J,
and Brown, M.J.F. (2014) Disease associations between
honeybees and bumblebees as a threat to wild pollina-
tors. Nature 506: 364–366.
Gauthier, L., Tentcheva, D., Tournaire, M., Dainat, B.,
Cousserans, F., Colin, M, and Bergoin, M. (2007) Viral load
estimation in asymptomatic honey bee colonies using the
quantitative RT-PCR technique. Apidologie 38: 426–435.
Genersch, E., von der Ohe, W., Kaatz, H., Schroeder, A.,
Otten, C., B
uchler, R., et al. (2010) The german bee
monitoring project: a long term study to understand peri-
odically high winter losses of honey bee colonies. Apido-
logie 41: 332–352.
Gisder, S., Aumeier, P, and Genersch, E. (2009) Deformed
wing virus: replication and viral load in mites (varroa
destructor). J Gen Virol 90: 463–467.
Gmeinbauer, R and Crailsheim, K. (1993) Glucose utiliza-
tion during flight of honeybee (Apis mellifera) workers,
drones and queens. J Insect Physiol 39: 959–967.
Goblirsch, M., Huang, Z.Y, and Spivak, M. (2013) Physio-
logical and behavioral changes in honey bees (Apis melli-
fera) induced by Nosema ceranae infection. PLoS ONE
8: e58165.
Goulson, D., Nicholls, E., Botias, C, and Rotheray, E.L.
(2015) Bee declines driven by combined stress from par-
asites, pesticides, and lack of flowers. Science 347:
1435–1443.
Hanauer-Thieser, U and Nachtigall, W. (1995) Flight of the
honey bee.6. Energetics of wind tunnel exhaustion flights
at defined fuel content, speed adaptation and aerody-
namics. J Comp Physiol B Biochem Syst Environ Physiol
165: 471–483.
Harrison, J.F and Fewell, J.H. (2002) Environmental and
genetic influences on flight metabolic rate in the honey
bee, Apis mellifera.Comp Biochem Physiol A Mol Integr
Physiol 133: 323–333.
Higes, M., Martin, R, and Meana, A. (2006) Nosema cera-
nae, a new microsporidian parasite in honeybees in
Europe. J Invertebr Pathol 92: 93–95.
Higes, M., Martin-Hernandez, R., Botias, C., Bailon, E.G.,
Gonzalez-Porto, A.V., Barrios, L., et al. (2008) How natu-
ral infection by Nosema ceranae causes honeybee colony
collapse. Environ Microbiol 10: 2659–2669.
Hrassnigg, N and Crailsheim, K. (1999) Metabolic rates and
metabolic power of honeybees in tethered flight related to
temperature and drag (hymenoptera: apidae). Entomol
Gen 24: 23–30.
Human, H., Brodschneider, R., Dietemann, V., Dively, G.,
Ellis, J.D., Forsgren, E., et al. (2013) Miscellaneous stan-
dard methods for Apis mellifera research. J Apic Res 52:
1–55.
Iqbal, J and Mueller, U. (2007) Virus infection causes spe-
cific learning deficits in honeybee foragers. Proc R Soc B
Biol Sci 274: 1517–1521.
Jaffe, R and Moritz, R.F.A. (2010) Mating flights select for
symmetry in honeybee drones (Apis mellifera). Naturwis-
senschaften 97: 337–343.
Jones, H.B.C., Lim, K.S., Bell, J.R., Hill, J.K, and Chapman,
J.W. (2015) Quantifying interspecific variation in dispersal
ability of noctuid moths using an advanced tethered flight
technique. Ecol Evol 6: 181–190.
Kielmanowicz, M.G., Inberg, A., Lerner, I.M., Golani, Y.,
Brown, N., Turner, C.L., et al. (2015) Prospective Large-
scale field study generates predictive model identifying
major contributors to colony Losses. PLoS Pathog 11:
Klein, A.M., Vaissiere, B.E., Cane, J.H., Steffan-Dewenter,
I., Cunningham, S.A., Kremen, C, and Tscharntke, T.
Flight performance is reduced by a common pathogen 735
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
(2007) Importance of pollinators in changing landscapes
for world crops. Proc R Soc B Biol Sci 274: 303–313.
Kralj, J and Fuchs, S. (2010) Nosema sp influences flight
behavior of infected honey bee (Apis mellifera) foragers.
Apidologie 41: 21–28.
Lee, K.V., Steinhauer, N., Rennich, K., Wilson, M.E., Tarpy,
D.R., Caron, D.M., et al. (2015) A national survey of man-
aged honey bee 2013-2014 annual colony losses in the
USA. Apidologie 46: 292–305.
Lourenco, A.P., Mackert, A., Cristino, A.D, and Simoes,
Z.L.P. (2008) Validation of reference genes for gene
expression studies in the honey bee, Apis mellifera,by
quantitative real-time RT-PCR. Apidologie 39: 372–385.
Mallon, E.B., Brockmann, A, and Schmid-Hempel, P. (2003)
Immune response inhibits associative learning in insects.
Proc R Soc B Biol Sci 270: 2471–2473.
Manley, R., Boots, M, and Wilfert, L. (2015) Emerging viral
disease risk to pollinating insects: ecological, evolutionary
and anthropogenic factors. J Appl Ecol 52: 331–340.
Martin-Hernandez, R., Meana, A., Prieto, L., Salvador,
A.M., Garrido-Bailon, E, and Higes, M. (2007) Outcome
of colonization of Apis mellifera by Nosema ceranae.
Appl Environ MicrobiolEnviron Microbiol 73: 6331–6338.
Martin-Hernandez, R., Botias, C., Barrios, L., Mar tinez-
Salvador, A., Meana, A., Mayack, C, and Higes, M.
(2011) Comparison of the energetic stress associated
with experimental Nosema ceranae and nosema apis
infection of honeybees (Apis mellifera). Parasitol Res
109: 605–612.
Martin, S.J., Ball, B.V., Carreck, N.L. (2013a) The Role of
Deformed Wing Virus in the Initial Collapse of Varroa
Infested Honey Bee Colonies in the UK. JApicRes52:8.
Martin, S.J., Hardy, J., Villalobos, E., Martin-Hernandez, R.,
Nikaido, S, and Higes, M. (2013b) Do the honeybee
pathogens Nosema ceranae and deformed wing virus act
synergistically? Environ Microbiol Rep 5: 506–510.
Martin, S.J., Highfield, A.C., Brettell, L., Villalobos, E.M.,
Budge, G.E., Powell, M., et al. (2012) Global honey bee
viral landscape altered by a parasitic mite. Science 336:
1304–1306.
Mayack, C and Naug, D. (2009) Energetic stress in the hon-
eybee Apis mellifera from Nosema ceranae infection.
J Invertebr Pathol 100: 185–188.
Mayack, C and Naug, D. (2010) Parasitic infection leads to
decline in hemolymph sugar levels in honeybee foragers.
J Insect Physiol 56: 1572–1575.
Mayack, C and Naug, D. (2015) Starving honeybees lose
self-control. Biol Lett 11: 20140820.
Mayack, C., Natsopoulou, M.E, and McMahon, D.P. (2015)
Nosema ceranae alters a highly conserved hormonal
stress pathway in honeybees. Insect Mol Biol 24: 662–670.
McDonnell, C.M., Alaux, C., Parrinello, H., Desvignes, J.P.,
Crauser, D., Durbesson, E., et al. (2013) Ecto- and endo-
parasite induce similar chemical and brain neurogenomic
responses in the honey bee (Apis mellifera). BMC Ecol 13:
McMahon, D.P., Furst, M.A., Caspar, J., Theodorou, P.,
Brown, M.J.F, and Paxton, R.J. (2015) A sting in the spit:
widespread cross-infection of multiple RNA viruses across
wild and managed bees. JAnimEcol84: 615–624.
Meunier, J. (2015) Social immunity and the evolution of
group living in insects. Philos Trans R Soc B Biol Sci 370:
Mockel, N., Gisder, S, and Genersch, E. (2011) Horizontal
transmission of deformed wing virus: pathological conse-
quences in adult bees (apis mellifera) depend on the
transmission route. J Gen Virol 92: 370–377.
Moore, J., Jironkin, A., Chandler, D., Burroughs, N., Evans,
D.J, and Ryabov, E.V. (2011) Recombinants between
deformed wing virus and varroa destructor virus-1 may
prevail in varroa destructor-infested honeybee colonies.
J Gen Virol 92: 156–161.
Mordecai, G.J., Brettell, L.E., Martin, S.J., Dixon, D., Jones,
I.M, and Schroeder, D.C. (2016) Superinfection exclusion
and the long-term survival of honey bees in Varroa-
infested colonies. Isme J 10: 1182–1191.
Mouret, C., Lambert, O., Piroux, M., Beaudeau, F., Provost,
B., Benet, P., et al. (2013) Prevalence of 12 infectious
agents in field colonies of 18 apiaries in western france.
Rev Med Vet 164: 577–582.
Naug, D. (2014) Infected honeybee foragers incur a higher
loss in efficiency than in the rate of energetic gain. Biol
Lett 10:
Naug, D and Gibbs, A. (2009) Behavioral changes mediat-
ed by hunger in honeybees infected with Nosema cera-
nae.Apidologie 40: 595–599.
Navajas, M., Migeon, A., Alaux, C., Martin-Magniette, M.L.,
Robinson, G.E., Evans, J.D., et al. (2008) Differential
gene expression of the honey bee Apis mellifera associ-
ated with varroa destructor infection. BMC Genom 9: 11.
Neumann, P and Carreck, N.L. (2010) Honey bee colony
losses. J Apic Res 49: 1–6.
Perry, C.J., Sovik, E., Myerscough, M.R, and Barron, A.B.
(2015) Rapid behavioral maturation accelerates failure of
stressed honey bee colonies. Proc Natl Acad Sci U S A
112: 3427–3432.
Potts, S.G., Biesmeijer, J.C., Kremen, C., Neumann, P.,
Schweiger, O, and Kunin, W.E. (2010) Global pollinator
declines: trends, impacts and drivers. Trends Ecol Evol
25: 345–353.
Retschnig, G., Williams, G.R., Odemer, R., Boltin, J., Di
Poto, C., Mehmann, M.M., et al. (2015) Effects, but no
interactions, of ubiquitous pesticide and parasite stres-
sors on honey bee (Apis mellifera) lifespan and behaviour
in a colony environment. Environ Microbiol 83: 4322–
4331.
Riley, J.R., Downham, M.C.A, and Cooter, R.J. (1997) Com-
parison of the performance of cicadulina leafhoppers on
flight mills with that to be expected in free flight. Entomol
Exp Appl 83: 317–322.
Riley, J.R., Smith, A.D., Reynolds, D.R., Edwards, A.S.,
Osborne, J.L., Williams, I.H., et al. (1996) Tracking bees
with harmonic radar. Nature 379: 29–30.
Rothe, U and Nachtigall, W. (1989) Flight of the honey bee.
IV. Respiratory quotients and metabolic rates during sit-
ting, walking and flying. J Comp Physiol B Biochem Syst
Environ Physiol 158: 739–749.
Rumkee, J.C.O., Becher, M.A., Thorbek, P., Kennedy, P.J, and
Osborne, J.L. (2015) Predicting honeybee colony failure:
using the BEEHAVE model to simulate colony responses to
Pesticides. Environ Sci Technol 49: 12879–12887.
Sacktor, B. (1970) Regulation of intermediary metabolism
with special reference to the control mechanisms in
insect flight muscle. Adv Insect Physiol 7: 267–347.
736 T. Wells et al.
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
Sappington, T.W and Burks, C.S. (2014) Patterns of flight
behavior and capacity of unmated navel orangeworm
(lepidoptera: pyralidae) adults related to age, gender, and
wing Size. Environ Entomol 43: 696–705.
Schippers, M.P., Dukas, R, and McClelland, G.B. (2010)
Lifetime- and caste-specific changes in flight metabolic
rate and muscle biochemistry of honeybees, apis melli-
fera. J CompPhysiol B Biochem Syst Environ Physiol
180: 45–55.
Schmid-Hempel, P. (1998) Parasites in Social Insects.
Princeton, US: Princeton University Press.
Siede, R., Konig, M., Buchler, R., Failing, K, and Thiel, H.J.
(2008) A real-time PCR based survey on acute bee
paralysis virus in german bee colonies. Apidologie 39:
650–661.
Smith, M.L. (2012) The honey bee parasite Nosema cera-
nae: transmissible via food exchange? Plos One 7:
Spiewok, S and Schmolz, E. (2006) Changes in tempera-
ture and light alter the flight speed of hornets (vespa
crabro L.). Physiol Biochem Zool 79: 188–193.
Steinmann, N., Corona, M., Neumann, P, and Dainat, B.
(2015) Overwintering is associated with reduced expres-
sion of immune genes and higher susceptibility to virus
infection in honey Bees. PloS one 10: e0129956.
Tarpy, D.R. (2003) Genetic diversity within honeybee colo-
nies prevents severe infections and promotes colony
growth. Proc R Soc B Biol Sci 270: 99–103.
Taylor, R.A.J., Bauer, L.S., Poland, T.M, and Windell, K.N.
(2010) Flight performance of agrilus planipennis (coleop-
tera: buprestidae) on a flight mill and in free Flight.
J Insect Behav 23: 128–148.
Tentcheva, D., Gauthier, L., Zappulla, N., Dainat, B.,
Cousserans, F., Colin, M.E, and Bergoin, M. (2004) Prev-
alence and seasonal variations of six bee viruses in apis
mellifera L. And varroa destructor mite populations in
France. Appl Environ MicrobiolEnviron Microbiol 70:
7185–7191.
Thompson, S.N. (2003) Trehalose - the insect ‘blood’ sugar.
Adv Insect Physiol 31: 205–285.
Vance, J.T., Williams, J.B., Elekonich, M.M, and Roberts,
S.P. (2009) The effects of age and behavioral develop-
ment on honey bee (apis mellifera) flight performance.
J Exp Biol 212: 2604–2611.
vanEngelsdorp, D and Meixner, M.D. (2010) A historical
review of managed honey bee populations in europe and
the united states and the factors that may affect them.
J Invertebr Pathol 103: S80–S95.
VSNI (2014) GenStat for Windows 17th Edition. Hemel
Hempstead: VSN International.
Welham, S.J., Gezan, S.A., Clark, S.J., Mead, A. (2015)
Statistical Methods in Biology: Design and Analysis of
Experiments and Regression. Boca Raton, US: CRC
Press.
Williams, G.R., Alaux, C., Costa, C., Csaki, T., Doublet, V.,
Eisenhardt, D., et al. (2013) Standard methods for main-
taining adult Apis mellifera in cages under in vitro labora-
tory conditions. J Apic Res 52:
Wilson, E.O. (1975) Sociobiology the New Synthesis. Cam-
bridge, US: Harvard University Press.
Wolf, S., McMahon, D.P., Lim, K.S., Pull, C.D., Clark, S.J.,
Paxton, R.J, and Osborne, J.L. (2014) So near and yet
so far: harmonic radar reveals reduced homing ability of
Nosema infected Honeybees. PLoS ONE 9: e103989.
Yanez, O., Jaffe, R., Jarosch, A., Fries, I., Moritz, R.F.A.,
Paxton, R.J, and de Miranda, J.R. (2012) Deformed wing
virus and drone mating flights in the honey bee (Apis
mellifera): implications for sexual transmission of a major
honey bee virus. Apidologie 43: 17–30.
Yang, X and Cox-Foster, D. (2007) Effects of parasitization
by varroa destructor on survivorship and physiological
traits of Apis mellifera in correlation with viral incidence
and microbial challenge. Parasitology 134: 405–412.
Yang, X.L and Cox-Foster, D.L. (2005) Impact of an ecto-
parasite on the immunity and pathology of an inverte-
brate: evidence for host immunosuppression and viral
amplification. Proc Natl Acad Sci U S A 102: 7470–7475.
Yue, C and Genersch, E. (2005) RT-PCR analysis of
deformed wing virus in honeybees (apis mellifera) and
mites (varroa destructor). J Gen Virol 86: 3419–3424.
Yue, C., Schroder, M., Bienefeld, K, and Genersch, E.
(2006) Detection of viral sequences in semen of honey-
bees (apis mellifera): evidence for vertical transmission
of viruses through drones. J Invertebr Pathol 92:
105–108.
Yue, C., Schroder, M., Gisder, S, and Genersch, E. (2007)
Vertical-transmission routes for deformed wing virus of
honeybees (apis mellifera). J Gen Virol 88: 2329–2336.
Zioni, N., Soroker, V, and Chejanovsky, N. (2011) Replica-
tion of varroa destructor virus 1 (VDV-1) and a varroa
destructor virus 1-deformed wing virus recombinant
(VDV-1-DWV) in the head of the honey bee. Virology
417: 106–112.
Supporting Information
Additional Supporting Information may be found in the
online version of this article at the publisher’s website:
Table S1. Bee disease, flight and wing data.
Appendix S1. Testing confidence intervals at 95% and
99% for predictions of flight durations of Nosema-infected
bees against previously reported data.
Flight performance is reduced by a common pathogen 737
V
C2016 The Authors. Environmental Microbiology Reports published by Society for Applied Microbiology and John Wiley & Sons Ltd,
Environmental Microbiology Reports,8, 728–737
... Some studies have suggested that DWV causes bees to engage in behaviors related to foraging at an earlier age than uninfected bees [20,27], thereby altering the temporal polyethism of the hive. DWV may also affect the foraging abilities of infected bees by reducing the flight distance or time [20,28,29], thereby reducing their ability to contribute to colony homeostasis. Associative learning using the proboscis extension reflex in bees infected with DWV demonstrated reduced performance in learning acquisition and retention [22,30], and this reduction may be linked to the strain of DWV [22]. ...
... There were no genes that were identified as upregulated by one algorithm and downregulated by the other, or vice versa ( Figure 3). The copy number of DWV RNA in each sample was measured using qRT-PCR and in the DWV injected bees was found to be on average 10 10 GE/brain (data not shown), which is similar to that seen in natural overt infections with DWV [28]. The number of reads mapping to the DWV genome comprised 20-40% of the total reads ( Figure S3), demonstrating that the level of viral replication in the brain is high [24]. ...
Article
Full-text available
Managed colonies of European honey bees (Apis mellifera) are under threat from Varroa destructor mite infestation and infection with viruses vectored by mites. In particular, deformed wing virus (DWV) is a common viral pathogen infecting honey bees worldwide that has been shown to induce behavioral changes including precocious foraging and reduced associative learning. We investigated how DWV infection of bees affects the transcriptomic response of the brain. The transcriptomes of individual brains were analyzed using RNA-Seq after experimental infection of newly emerged adult bees with DWV. Two analytical methods were used to identify differentially expressed genes from the ~15,000 genes in the Apis mellifera genome. The 269 genes that had increased expression in DWV infected brains included genes involved in innate immunity such as antimicrobial peptides (AMPs), Ago2, and Dicer. Single bee brain NMR metabolomics methodology was developed for this work and indicates that proline is strongly elevated in DWV infected brains, consistent with the increased presence of the AMPs abaecin and apidaecin. The 1361 genes with reduced expression levels includes genes involved in cellular communication including G-protein coupled, tyrosine kinase, and ion-channel regulated signaling pathways. The number and function of the downregulated genes suggest that DWV has a major impact on neuron signaling that could explain DWV related behavioral changes.
... This may be due, in part, to the differences in infection levels between foragers and colonies-forager viral infections except for BQCV had lower levels and were less variable than those found in the colony-representative nurse bee samples, meaning that nurse bee infections may be more acute or there is survival bias by the time bees become foragers. So, while individual forager infection might reduce foraging efficiency (125), collective foraging decisions are directed by social immunity needs. ...
Article
Full-text available
Nutrition is an important component of social insect colony health especially in the face of stressors such as parasitism and viral infections. Honey bees are known to preferentially select nectar and pollen based on macronutrient and phytochemical contents and in response to pathogen loads. However, given that honey bees live in colonies, collective foraging decisions may be impacted directly by forager infection status but also by colony health. This field experiment was conducted to determine if honey bee viral infections are correlated with pollen and nectar foraging and if these associations are impacted more by colony or forager infection. By comparing regressions with and without forager and colony variables and through structural equation models, we were able to determine the relative contributions of colony and forager virus loads on forager decisions. We found that foragers had higher numbers and levels of BQCV and CBPV but lower levels of DWV viruses than their respective colonies. Overall, individuals appeared to forage based a combination of their own and colony health but with greater weight given to colony metrics. Colony parasitism by Varroa mites, positively correlated with both forager and colony DWV-B levels, was negatively associated with nectar weight. Further, colony DWV-B levels were negatively associated with individually foraged pollen protein: lipid ratios but positively correlated with nectar weight and sugar content. This study shows that both colony and forager health can simultaneously mediate individual foraging decisions and that the importance of viral infections and parasite levels varies with foraging metrics. Overall, this work highlights the continued need to explore the interactions of disease, nutrition, and genetics in social interactions and structures.
... Our data suggest that Varroa, as a factor, consistently has the greatest influence on mortality, likely as it encompasses both the effects of mechanical damage, via feeding, and the transmission of associated pathogens. While DWV and other viruses correlate with colony mortality, and have been shown both to kill, and sub-lethally influence bees 65,135 , it appears that when these effects are decoupled from their correlation with Varroa levels, their predictive power is significantly reduced. The crucial methodological and diagnostic implication of this, is that, at a minimum, compared to the viruses tested here, Varroa has significant additive power in predicting colony outcome. ...
Article
Full-text available
The ectoparasite Varroa destructor is the greatest threat to managed honey bee (Apis mellifera) colonies globally. Despite significant efforts, novel treatments to control the mite and its vectored pathogens have shown limited efficacy, as the host remains naïve. A prospective solution lies in the development of Varroa-resistant honey bee stocks, but a paucity of rigorous selection data restricts widespread adoption. Here, we characterise the parasite and viral dynamics of a Varroa-resistant honey bee stock, designated ‘Pol-line’, using a large-scale longitudinal study. Results demonstrate markedly reduced Varroa levels in this stock, diminished titres of three major viruses (DWV-A, DWV-B, and CBPV), and a two-fold increase in survival. Levels of a fourth virus that is not associated with Varroa—BQCV—do not differ between stocks, supporting a disruption of the transmission pathway. Further, we show that when decoupled from the influence of Varroa levels, viral titres do not constitute strong independent predictors of colony mortality risk. These findings highlight the need for a reassessment of Varroa etiology, and suggest that derived stocks represent a tractable solution to the Varroa pandemic.
... Bees symptomatic for DWV emerge with wing deformities, have reduced weight, and have a shortened lifespan or are killed prematurely by other colony members. Although bees can be asymptomatic, high viral loads adversely impact lifespan, foraging and flight capability, behavioral maturation, and immunity (Iqbal and Mueller, 2007;Natsopoulou et al., 2016;Wells et al., 2016;Benaets et al., 2017;Brettell et al., 2017;Traniello et al., 2020;Pizzorno et al., 2021). By feeding on honey bee pupae, Varroa act as an efficient vector of over a dozen viruses to their bee hosts. ...
Article
Full-text available
The remarkably adaptive mite Varroa destructor is the most important honey bee ectoparasite. Varroa mites are competent vectors of deformed wing virus (DWV), and the Varroa-virus complex is a major determinant of annual honey bee colony mortality and collapse. MicroRNAs (miRNAs) are 22-24 nucleotide non-coding RNAs produced by all plants and animals and some viruses that influence biological processes through post-transcriptional regulation of gene expression. Knowledge of miRNAs and their function in mite biology remains limited. Here we constructed small RNA libraries from male and female V. destructor using Illumina’s small RNA-Seq platform. A total of 101,913,208 and 91,904,732 small RNA reads (>18 nucleotides) from male and female mites were analyzed using the miRDeep2 algorithm. A conservative approach predicted 306 miRNAs, 18 of which were upregulated and 13 downregulated in female V. destructor compared with males. Quantitative real-time PCR validated the expression of selected differentially-expressed female Varroa miRNAs. This dataset provides a list of potential miRNA targets involved in regulating vital Varroa biological processes and paves the way for developing strategies to target Varroa and their viruses.
... A recent study reported that nurse bees infected with DWV-A showed a brain transcriptome similar to forager bees and this change in behavioral maturation could be generating younger bees with foraging behavior [64]. However, this early foraging activity in middle-age bees could be precarious and deficient [65]. Thus, an DWV-A infection could impair worker bees' olfactory sensitivity to aromas, as shown in this study, and a neurogenomic spoilage [64] could result in learning deficits in worker bees [18] that could lead to the loss of honey bees in the field (e.g., forage bees) and affect the efficiency of bees' labors within the hive, producing a gradual decline in the colony, as has been reported with this DWV variant [66]. ...
Article
Full-text available
Insects have a highly sensitive sense of smell, allowing them to perform complex behaviors, such as foraging and peer recognition. Their sense of smell is based on the recognition of ligands and is mainly coordinated by odorant-binding proteins (OBPs). In Apis mellifera, behavior can be affected by different pathogens, including deformed wing virus (DWV) and its variants. In particular, it has been shown that variant A of DWV (DWV-A) is capable of altering the ultra-cellular structure associated with olfactory activity. In this study was evaluated olfactory sensitivity and the expression of OBP genes in honey bees inoculated with DWV-A. Electroantennographic analyses (EAG) were carried out to determine the olfactory sensitivity to the essential oils Eucalyptus globulus and Mentha piperita. The expression of nine antenna-specific OBP genes and DWV-A load in inoculated bees was also quantified by qPCR. We observed an inverse relationship between viral load and olfactory sensitivity and the expression of some OBP proteins. Thus, high viral loads reduced olfactory sensitivity to essential oils and the gene expression of the OBP2, OBP5, OBP11, and OBP12 proteins on the antennas of middle- and forager-age bees. These results suggest that DWV-A could have negative effects on the processes of aroma perception by worker bees, affecting their performance in tasks carried out in and outside the colony.
... Grooming behavior is caused by irritation of the sensory hairs located on the body surface and in situations when the chemical receptors are stimulated [31]. A decrease in the frequency and duration of wing movement may indicate dysfunctions in the organs of bees related to movement, which are necessary for the proper functioning of individuals, as presented in studies by Wells et al. [32], who analyzed the correlation between bee infection with Nosema spp. spores and wing deformation virus, as well as flight length and activity. ...
Article
Full-text available
EM-fields come from both natural and anthropogenic sources. This study aimed to investigate changes in honeybee behavior parameters under the influence of an electric field at 50 Hz and variable intensity. Bees were exposed for 1 h, 3 h, or 6 h to the following artificial E-field intensities: 5.0 kV/m, 11.5 kV/m, 23.0 kV/m, or 34.5 kV/m. Bees in the control group were under the influence of an E-field <2.0 kV/m. Six basic behaviors were selected for bee observation (walking, grooming, flight, stillness, contact between individuals, and wing movement). Our research shows the impact of bee exposure time on behavioral change within groups. Exposure for 3 h caused a decrease in the time that bees spent on behaviors and in the number of occurrences. After 6 h, the parameters increased within the groups, as was the case with 1 h exposure. This may indicate that there is a behavioral barrier that allows the pattern to normalize for some time.
Article
Full-text available
Honey bees exposed to Varroa mites incur substantial physical damage in addition to potential exposure to vectored viruses such as Deformed wing virus (DWV) that exists as three master variants (DWV-A, DWV-B, and DWV-C) and recombinants. Although mite-resistant bees have been primarily bred to mitigate the impacts of Varroa mites, mite resistance may be associated with increased tolerance or resistance to the vectored viruses. The goal of our study is to determine if five honey bee stocks (Carniolan, Italian, Pol-Line, Russian, and Saskatraz) differ in their resistance or tolerance to DWV based on prior breeding for mite resistance. We injected white-eyed pupae with a sublethal dose (105) of DWV or exposed them to mites and then evaluated DWV levels and dissemination and morphological symptoms upon adult emergence. While we found no evidence of DWV resistance across stocks (i.e., similar rates of viral replication and dissemination), we observed that some stocks exhibited reduced symptom severity suggestive of differential tolerance. However, DWV tolerance was not consistent across mite-resistant stocks as Russian bees were most tolerant, while Pol-Line exhibited the most severe symptoms. DWV variants A and B exhibited differential dissemination patterns that interacted significantly with the treatment group but not bee stock. Furthermore, elevated DWV-B levels reduced adult emergence time, while both DWV variants were associated with symptom likelihood and severity. These data indicate that the genetic differences underlying bee resistance to Varroa mites are not necessarily correlated with DWV tolerance and may interact differentially with DWV variants, highlighting the need for further work on mechanisms of tolerance and bee stock–specific physiological interactions with pathogen variants.
Article
Industrial agriculture is the root cause of many health problems that honey bees (Apis mellifera Linneaus, 1758) face, but honey bee researchers seldom call attention to this fact. We often discuss the stressors that contribute to colony loss (e.g., pathogens, pesticides, poor nutrition), but we rarely talk about where those stressors come from. This is a problem because we cannot resolve honey bee health issues unless we confront the systems that cause them harm. In this forum article, I unpack the relationship between honey bee health and industrial agriculture. I propose steps we can take to reframe our research to account for the impacts of this destructive system, and I discuss the uncomfortable questions that surface when we engage in this process. The goal of this article is to encourage conversation within the honey bee research community around the impacts of industrial agriculture, so that we can fully engage in the transformative change needed to support honey bee health.
Preprint
Full-text available
The most important ectoparasite of the honeybee is the remarkably adaptive mite Varroa destructor. The Varroa mite is a competent vector of Deformed Wing Virus (DWV), the Varroa-virus complex is one of the main factors associated with elevated annual honey bee colony mortality. Micro-RNAs (miRNAs) are small, non-coding RNAs of ~22-24 nucleotides, produced by all plants, animals, and viruses that in uence biological processes through post-transcriptional regulation of gene expression. Knowledge of miRNAs and their functional role in mite biology remains limited. This study developed small RNA libraries from male and female V. destructor by utilizing Illumina's small RNA-Seq platform. A total of 101,913,208 and 91,904,732 small RNA reads (>18 nucleotides) from male and female mites were analyzed using the mirDeep2 algorithm. A conservative approach predicted a total of 306 miRNAs, of which 18 were upregulated and 13 were downregulated in female V. destructor compared to males. A qPCR assay validated the expression of selected differentially expressed female Varroa miRNAs. This dataset provides a list of potential miRNA targets involved in regulating vital Varroa biological processes and for deciphering new targets against Varroa and honey bee viruses they carry.
Article
Full-text available
Honey bee (Apis mellifera) health is impacted by viral infections at the colony, individual bee, and cellular levels. To investigate honey bee antiviral defense mechanisms at the cellular level we further developed the use of cultured primary cells, derived from either larvae or pupae, and demonstrated that these cells could be infected with a panel of viruses, including common honey bee infecting viruses (i.e., sacbrood virus (SBV) and deformed wing virus (DWV)) and an insect model virus, Flock House virus (FHV). Virus abundances were quantified over the course of infection. The production of infectious virions in cultured honey bee pupal cells was demonstrated by determining that naïve cells became infected after the transfer of deformed wing virus or Flock House virus from infected cell cultures. Initial characterization of the honey bee antiviral immune responses at the cellular level indicated that there were virus-specific responses, which included increased expression of bee antiviral protein-1 (GenBank: MF116383) in SBV-infected pupal cells and increased expression of argonaute-2 and dicer-like in FHV-infected hemocytes and pupal cells. Additional studies are required to further elucidate virus-specific honey bee antiviral defense mechanisms. The continued use of cultured primary honey bee cells for studies that involve multiple viruses will address this knowledge gap.
Book
Full-text available
Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors’ experience. Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat® statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R.
Article
Full-text available
Dispersal plays a crucial role in many aspects of species' life histories, yet is often difficult to measure directly. This is particularly true for many insects, especially nocturnal species (e.g. moths) that cannot be easily observed under natural field conditions. Consequently, over the past five decades, laboratory tethered flight techniques have been developed as a means of measuring insect flight duration and speed. However, these previous designs have tended to focus on single species (typically migrant pests), and here we describe an improved apparatus that allows the study of flight ability in a wide range of insect body sizes and types. Obtaining dispersal information from a range of species is crucial for understanding insect population dynamics and range shifts. Our new laboratory tethered flight apparatus automatically records flight duration, speed, and distance of individual insects. The rotational tethered flight mill has very low friction and the arm to which flying insects are attached is extremely lightweight while remaining rigid and strong, permitting both small and large insects to be studied. The apparatus is compact and thus allows many individuals to be studied simultaneously under controlled laboratory conditions. We demonstrate the performance of the apparatus by using the mills to assess the flight capability of 24 species of British noctuid moths, ranging in size from 12-27 mm forewing length (~40-660 mg body mass). We validate the new technique by comparing our tethered flight data with existing information on dispersal ability of noctuids from the published literature and expert opinion. Values for tethered flight variables were in agreement with existing knowledge of dispersal ability in these species, supporting the use of this method to quantify dispersal in insects. Importantly, this new technology opens up the potential to investigate genetic and environmental factors affecting insect dispersal among a wide range of species.
Article
Full-text available
Adult honey bees are maintained in vitro in laboratory cages for a variety of purposes. For example, researchers may wish to perform experiments on honey bees caged individually or in groups to study aspects of parasitology, toxicology, or physiology under highly controlled conditions, or they may cage whole frames to obtain freshly emerged workers of known age cohorts. Regardless of purpose, researchers must manage a number of variables, ranging from selection of study subjects (e.g. honey bee subspecies) to experimental environment (e.g. temperature and relative humidity). Although decisions made by researchers may not necessarily jeopardize the scientific rigour of an experiment, they may profoundly affect results, and may make comparisons with similar, but independent, studies difficult. Focusing primarily on workers, we provide recommendations for maintaining adults under in vitro laboratory conditions, whilst acknowledging gaps in our understanding that require further attention. We specifically describe how to properly obtain honey bees, and how to choose appropriate cages, incubator conditions, and food to obtain biologically relevant and comparable experimental results. Additionally, we provide broad recommendations for experimental design and statistical analyses of data that arises from experiments using caged honey bees. The ultimate goal of this, and of all COLOSS BEEBOOK papers, is not to stifle science with restrictions, but rather to provide researchers with the appropriate tools to generate comparable data that will build upon our current understanding of honey bees
Article
Full-text available
Over the past 50 years, many millions of European honey bee (Apis mellifera) colonies have died as the ectoparasitic mite, Varroa destructor, has spread around the world. Subsequent studies have indicated that the mite's association with a group of RNA viral pathogens (Deformed Wing Virus, DWV) correlates with colony death. Here, we propose a phenomenon known as superinfection exclusion that provides an explanation of how certain A. mellifera populations have survived, despite Varroa infestation and high DWV loads. Next-generation sequencing has shown that a non-lethal DWV variant 'type B' has become established in these colonies and that the lethal 'type A' DWV variant fails to persist in the bee population. We propose that this novel stable host-pathogen relationship prevents the accumulation of lethal variants, suggesting that this interaction could be exploited for the development of an effective treatment that minimises colony losses in the future.
Article
A one-year survey of twelve infectious agents identified in honey bees (Paenibacillus larvae, Melissococcus plutonius, Nosema apis, Nosema ceranae, Acute Bee Paralysis Virus, Black Queen Cell Virus, Chronic Bee Paralysis Virus, Deformed Wing Virus, Israeli Acute Paralysis Virus, Kashmir Bee Virus, Sacbrood Bee Virus and Varroa destructor Virus 1) was performed in western France in 2009. During inspection, adult bee samples were collected four times a year from five colonies, in 18 apiaries. Sample contents were described and quantified by quantitative PCR methods. A high prevalence of the infectious agents studied was found both in terms of colonies and of apiaries, as well as very frequent co-infections within the same colony/apiary. These findings indicate a frequent infection of the apiaries and the colonies by most of the agents, and support the involvement of other weakening stressors in the disease outbreak.
Article
Current high losses of honeybees seriously threaten crop pollination. Whereas parasite exposure is acknowledged as an important cause of these losses, the role of insecticides is controversial. Parasites and neonicotinoid insecticides reduce homing success of foragers (e.g. by reduced orientation), but it is unknown whether they negatively affect flight capacity. We investigated how exposing colonies to the parasitic mite Varroa destructor and the neonicotinoid insecticide imidacloprid affect flight capacity of foragers. Flight distance, time and speed of foragers were measured in flight mills to assess the relative and interactive effects of high V. destructor load and a field-realistic, chronic sub-lethal dose of imidacloprid. Foragers from colonies exposed to high levels of V. destructor flew shorter distances, with a larger effect when also exposed to imidacloprid. Bee body mass partly explained our results as bees were heavier when exposed to these stressors, possibly due to an earlier onset of foraging. Our findings contribute to understanding of interacting stressors that can explain colony losses. Reduced flight capacity decreases the food-collecting ability of honeybees and may hamper the use of precocious foraging as a coping mechanism during colony (nutritional) stress. Ineffective coping mechanisms may lead to destructive cascading effects and subsequent colony collapse. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Publisher Summary This chapter analyzes the metabolic events that are fundamental to the transition of a muscle from a controlled resting state to one so active that energy transformations are taking place at a rate far in excess of that for any other biological process. The approach has been to identify the enzymatic reactions that are facilitated during the transition, to determine the mechanisms of activation at each locus of control, and then to formulate a working hypothesis that will unite the experimental findings into an overall scheme for the metabolic regulation of the tissue. Many of the experimental observations have been made with isolated enzymes and subcellular organelles. Thus, the in vivo environment can never be adequately reconstructed. Moreover, knowledge of the metabolite levels permitting simulation of in vivo conditions assumes uniform distribution of these substances and excludes compartmentation. These reservations made, the sites of regulation in fly flight muscle have been identified by measuring coincident and sequential changes in the concentrations of the metabolic intermediates.
Article
To simulate effects of pesticides on different honeybee (Apis mellifera L.) life stages, the BEEHAVE model was used to explore how increased mortalities of larvae, in-hive workers and foragers, as well as reduced egg-laying rate, could impact colony dynamics over multiple years. Stresses were applied for 30 days, both as multiples of the modelled control mortality and as set percentage daily mortalities to assess the sensitivity of the modelled colony both to small fluctuations in mortality and periods of low to very high daily mortality. These stresses simulate stylised exposure of the different life stages to nectar and pollen contaminated with pesticide for 30 days. Increasing adult bee mortality had a much greater impact on colony survival than mortality of bee larvae or reduction in egg laying rate. Importantly, the seasonal timing of the imposed mortality affected the magnitude of the impact at colony level. In line with the LD50, we propose a new index of 'lethal imposed stress': the LIS50 which indicates the level of stress on individuals that results in 50% colony mortality. This (or any LISx) is a comparative index for exploring the effects of different stressors at colony level in model simulations. While colony failure is not an acceptable protection goal, this index could be used to inform the setting of future regulatory protection goals.