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\begin{document}

\title{Macronutrient intake and simulated infection threat independently affect
life history traits of male decorated crickets}



\author[1]{Kristin Duffield}%
\author[1]{Kylie Hampton}%
\author[2]{Tom  Houslay}%
\author[3]{James  Rapkin}%
\author[4]{John Hunt}%
\author[1]{Ben Sadd}%
\author[1]{Scott Sakaluk}%
\affil[1]{Illinois State University}%
\affil[2]{University of Cambridge}%
\affil[3]{University of Exeter Cornwall Campus}%
\affil[4]{Western Sydney University}%


\vspace{-1em}



  
  \date{June 18, 2024}


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\selectlanguage{english}
\begin{abstract}
Nutritional geometry has advanced our understanding of how
macronutrients (e.g., proteins and carbohydrates) influence the
expression of life history traits and their corresponding trade-offs.
For example, recent work has revealed that reproduction and immune
function in male decorated crickets are optimized at very different
protein:carbohydrate (P:C) dietary ratios. However, it is unclear how an
individual's macronutrient intake interacts with its perceived infection
status to determine investment in reproduction or other key life history
traits. Here, we employed a fully factorial design in which calling
effort and immune function were quantified for male crickets fed either
diets previously demonstrated to maximize calling effort (P:C = 1:8) or
immune function (P:C = 5:1), and then administered a treatment from a
spectrum of increasing infection cue intensity using heat-killed
bacteria. Both diet and a simulated infection threat independently
influenced the survival, immunity, and reproductive effort of males. If
they called, males increased calling effort at the low infection cue
dose, consistent with the terminal investment hypothesis, but
interpretation of responses at the higher threat levels was hampered by
the differential mortality of males across infection cue and diet
treatments. A high protein, low carbohydrate diet severely reduced the
health, survival, and overall fitness of male crickets. There was,
however, no evidence of an interaction between diet and infection cue
dose on calling effort, suggesting that the threshold for terminal
investment was not contingent on diet as investigated here.%
\end{abstract}%



\sloppy


\textbf{INTRODUCTION}

Resource availability and acquisition are central to life history
investment (Williams, 1966; Gadgil and Bossert, 1970; Stearns, 1992;
Roff, 1992). Due to competition for resources, negative associations
(i.e., physiological trade-offs) between traits often arise when
organisms are resource limited (Gadgil and Bossert, 1970; van Noordwijk
and de Jong, 1986; Perrin and Sibly, 1993; Zera et al., 1998; Zera and
Harshman, 2001). Allocation of resources to reproduction versus immune
function represents one such key physiological trade-off (Sheldon and
Verhulst, 1996; Lochmiller and Deerenberg, 2000; Norris and Evans, 2000;
Partridge et al., 2005; Martin et al., 2008; McKean et al., 2008;
Schwenke et al., 2016), and numerous negative associations between these
traits have been reported in food-limited organisms including nematodes
(Klass, 1977), insects (Chippindale et al., 1993; Chapman et al., 1994;
Tatar and Carey, 1995), birds (Gustafsson et al., 1994; Ilmonen et al.,
2000; Bonneaud et al., 2004; Ardia, 2005), lizards (French et al., 2007;
Cox et al., 2010), and mammals (Koivula et al., 2003).

Beyond the consequences for trade-offs dictated by the number of total
calories consumed, only recently have investigators begun to consider
the independent effects of macronutrients (i.e., carbohydrates, protein,
and fat) on an individual's life history strategy. This was largely
driven by the development of nutritional geometry (Simpson and
Raubenheimer, 1995; Simpson et al., 2017), a multidimensional framework
for disentangling the effects of energy consumption from those of
particular nutrient combinations. The application of this framework has
revealed that the amount of macronutrients consumed often mediate life
history trade-offs, including those between lifespan and reproduction
(Lee et al., 2008; Maklakov et al., 2008; Jensen et al., 2015;
Solon-Biet et al., 2015; Rapkin et al., 2017b) and growth and immune
function (Cotter et al., 2011).

A recent application of nutritional geometry has illuminated the
nutritional landscape underlying the trade-off between immune function
(i.e., mounting an encapsulation response) and reproductive effort
(i.e., time spent broadcasting a long-range acoustic call for mate
attraction) in male crickets, \emph{Gryllodes sigillatus} (Rapkin et
al\emph{.} , 2018). In this study, crickets were maintained on one of 24
holidic diets varying in protein:carbohydrate (P:C) ratio and total
nutritional content that yielded a nutritional landscape with six
nutritional rails, along which P:C ratio was held constant but total
calories differed. Nutrient intake was measured during sexual
maturation, and calling effort and encapsulation ability were
subsequently quantified. Rapkin et al. (2018) found that immune function
in males was maximized at a P:C ratio of approximately 5:1, whereas
calling effort was maximized at a carbohydrate-biased P:C ratio of
approximately 1:8. Because optimal expression of each trait occurred at
distinct P:C ratios, this study provides important evidence that
macronutrient intake, independent of total calories, directs the
trade-off between reproduction and immune function.

The ratio of macronutrients available to an individual and the influence
on reproduction and immunity may alter the life history investment
strategy employed following a pathogenic infection. On one hand, the
cost of immunity trade-off hypothesis predicts an increased investment
in immunity to fight infection, at a cost to current reproduction
(Festa-Bianchet 1988; Gustafsson et al. 1994; Norris et al. 1994;
Svensson et al. 1998; Adamo 1999; Jacot et al. 2004; Ahtiainen et al.
2005; Stahlschmidt et al. 2013). Alternatively, individuals may increase
their investment in reproduction in response to the threat of infection
to their immediate survival, in a life history strategy known as
terminal investment (Williams, 1966; Clutton-Brock, 1984). A recent
refinement of this idea, the dynamic terminal investment threshold
model, proposes that the tendency of an individual to terminally invest
depends on other intrinsic and extrinsic factors, such as age or diet,
that alter an individual's residual reproductive value (i.e.,
expectation for future offspring) (Duffield et al., 2017). In support of
this possibility, Hudson et al. (2019) recently demonstrated that the
propensity to terminally invest in female \emph{Drosophila
melanogaster}was contingent on the amount of protein consumed.
Specifically, female flies only expressed terminal investment (i.e.,
increased egg laying following an infection of \emph{Pseudomonas
aeruginosa} ) when they were fed a high protein diet, whereas infected
females fed a diet of lower total protein did not increase egg
production relative to uninfected females. This study highlights how
nutrition-dependent condition, based on the amount of protein consumed
in this example, may interact with infection status to determine an
individual's investment in key life history traits, including
reproduction.

Here, we explore how macronutrient intake interacts with simulated
infection cue intensity, achieved through a spectrum of immune challenge
treatments, to influence expression of life history traits in male
decorated crickets, \emph{G. sigillatus} . Specifically, we quantified
reproductive effort (calling effort) and immune function (circulating
hemocytes, presence of hemocyte microaggregations, and antibacterial
activity of the hemolymph) of males maintained on diets previously shown
to maximize calling effort (P:C = 1:8, ``high carbohydrate diet'') or a
component of immune function, specifically via encapsulation ability
(P:C = 5:1, ``high protein diet'') (Rapkin et al., 2018). Due to the
divergent nutritional demands of calling effort and immune function, we
predicted that males would exhibit significantly different life history
strategies depending on their macronutrient intake, infection cue
intensity, or the interaction between these factors.

\textbf{MATERIALS AND METHODS}

\textbf{Study animals}

Male \emph{G. sigillatus} used in this study were randomly selected from
a large outbred colony, initiated with crickets collected from a wild
population from Riverside, CA in 2014. All crickets used in this study
were of the same generation. Newly hatched, experimental crickets were
reared in 55 L plastic storage bins packed with egg carton to increase
rearing surface area and provisioned with a standard diet (roughly equal
parts Envigo\selectlanguage{ngerman}\textsuperscript{©} 2018CM Teklad Certified Global 18\%
protein rodent diet and Purina\textsuperscript{®} Cat Chow Complete
pellets) and water (glass vials plugged with moist cotton) \emph{ad
libitum} . The nutritional content for this standard diet is 18.6\%
protein, 6.2\% fat, 44.2\% carbohydrate (rodent diet) and 32.0\%
protein, 12.0\% fat, and 37.6\% carbohydrate
(Purina\textsuperscript{®}Cat Chow). When sex differences became
apparent (4\textsuperscript{th}or 5\textsuperscript{th} instar),
juvenile males were removed from stock colonies and housed individually
in small (450 mL) plastic containers, ensuring virgin status and age
control for all experimental crickets, and provisioned with food
(roughly equal parts rodent diet and cat food) and water (glass vials
plugged with cotton) \emph{ad libitum} . A small section of egg carton
was also provided as a refuge. All individuals were housed in an
environmental chamber at 32°C on a 16 h:8 h light:dark cycle. Males were
checked daily to determine the date of final molt to adulthood and then
randomly assigned to a diet treatment.

\selectlanguage{english}\emph{} \textbf{Artificial diets and measuring dietary intake}

Isocaloric diets (which differed in P:C but not total calories) were
created using a protocol from an earlier study that quantified the
amount of carbohydrates and protein maximizing calling effort (P:C 1:8)
and immune function (i.e., encapsulation ability) (P:C 5:1) in
male\emph{G. sigillatus} (Rapkin et al., 2018)\emph{.} Briefly,
\selectlanguage{english}proteins consisted of a 3:1:1 mixture of casein, albumen, and peptone,
with digestible carbohydrates consisting of a 1:1 mixture of sucrose and
dextrin. All diets contained Wesson's salts (2.5\%), ascorbic acid
(0.28\%), cholesterol (0.55\%), and a vitamin mix (0.18\%). After the
appropriate dry weight of protein and carbohydrate had been added to the
mixture, the remainder of the mixture was adjusted to the appropriate
composition with crystalline cellulose.

 \selectlanguage{english}Upon adult eclosion, each cricket was given one dish of his assigned
diet (high protein diet: n = 249; high carbohydrate diet: n = 245),
which was changed every 3 days over a period of 21 days (7 trays total
for each male). Diet was provided in feeding platforms created by gluing
the upturned plastic lid of a 2 mL microcentrifuge tube in the center of
a plastic petri dish (50 mm diameter, 9 mm deep). The materials and
design of the feeding platforms ensured that food could be collected in
the petri dish if any spilled while subjects were feeding. Diet
consumption was calculated as the difference in dry weight before and
after feeding. Prior to weighing, any feces were removed from the
feeding platform using fine forceps. The dry weight of all
food-containing trays, obtained by holding them in drying oven at 30\selectlanguage{ngerman}°C
for at least 72 h, was measured both before and after feeding to
quantify how much of each diet was consumed by an individual throughout
the feeding trials, as this alters the total amount of nutrients
available. This is an especially important facet of evaluating the
effects of macronutrients, but one not often considered in such
assessments.

\textbf{Infection cue}

A pathogenic infection may signal reduced residual reproductive value to
the host, and this may be mediated through the infection-associated
immune challenge. Earlier, we demonstrated that injection with
heat-killed \emph{Escherichia coli} stimulates an immune response and
invokes a terminal investment response in male \emph{G.
sigillatus}(Duffield et al., 2015, 2018, 2019). This approach ensures
that the measured response is related to the host's investment strategy,
and not the result of alternative causes related to a live infection;
thus, a similar protocol was implemented here. Males were given an
infection cue treatment following the three-week feeding trials based on
a previous study demonstrating that males of this age are more likely to
show terminal investment in calling (Duffield et al., 2018). Body mass
for each male was measured immediately prior to infection cue
administration using an analytical balance (Mettler Toledo AG245).

Males were randomly assigned to one of five treatments on an increasing
infection cue spectrum: i) naive (unmanipulated control), ii) sham
control (injection of 2\selectlanguage{greek}μ\selectlanguage{english}L ringer saline), iii) low-dose infection cue
(injection of 2\selectlanguage{greek}μ\selectlanguage{english}L ringer saline with 5x10\textsuperscript{5}/mL
heat-killed \emph{E. coli} ), iv) moderate-dose infection cue (injection
of 2\selectlanguage{greek}μ\selectlanguage{english}L ringer saline with 5x10\textsuperscript{7}/mL heat-killed\emph{E.
coli} ), or v) high-dose infection cue (injection of 2\selectlanguage{greek}μ\selectlanguage{english}L ringer saline
with 5x10\textsuperscript{8}/mL heat-killed \emph{E. coli} ).
Importantly, we consider the sham control treatment not only a control
for the effect of injection, but also as a low-level mortality threat
because injection causes cuticle damage and induces an immune response
that potentially signals a mortality threat to the individual (Gillespie
and Khachatourians, 1992; Wigby et al., 2008; Ardia et al., 2012).
Injections were performed using a 5 \selectlanguage{greek}µ\selectlanguage{english}L syringe with a 1mm compression
fitting (Hamilton\selectlanguage{ngerman}\textsuperscript{®} brand) within which a needle formed
from a heat-pulled glass capillary tube was inserted. Crickets were
injected between the 6\textsuperscript{th} and
7\textsuperscript{th}pleurite of the thorax. Pulled capillaries were
cleaned in 70\% ethanol, rinsed with ultrapure water, and dried between
each injection, and capillaries were not reused across treatments or
days. Treatments were always applied at the same time (0900 hours ± 1 h)
throughout the experiment. Owing to mortality during the 3-week feeding
period, our sample sizes for each treatment were: \emph{high protein
diet} : naive = 33, sham = 37, low = 35, moderate = 34, high = 42;
\emph{high carbohydrate diet} : naive = 40, sham = 41, low = 41,
moderate = 43, high = 47.

\emph{Escherichia coli} (ATCC strain 23716) used to create our infection
cues were cultured at 30°C in 7 mL of liquid medium (10 g
bacto-tryptone, 5 g yeast extract, 10 g NaCl in 1000 mL of distilled
water, pH 7). To prepare bacterial suspensions for immune-challenge
injections, 1 mL of an overnight culture was centrifuged (850 g, 4°C, 10
min), the supernatant discarded, and replaced with sterile ringer
saline. This procedure was repeated three times. The bacteria were then
heat-killed (90°C, 5 min) and the concentration of bacterial cells was
adjusted to the concentrations described earlier for each infection cue
dose. Efficacy of the heat-killing was confirmed by plating out samples
of the suspension on media agar.

\textbf{Assessing reproductive effort}

Calling effort of males was used as a proxy for reproductive effort.
Male \emph{G. sigillatus} begin mating 4.5 days on average after adult
eclosion (Burpee and Sakaluk, 1993) and, because calling is essential
for mating, it follows that males are also calling at this time. We
quantified calling effort (i.e., the amount of time males spent calling)
over two consecutive nights following infection cue treatment. Calling
effort was measured using a custom-built high-throughput sound
monitoring array (Bertram and Johnson, 1998; Duffield et al., 2018,
2019) in which each male-containing individual container (250 mL) was
fitted with a lid-mounted microphone (C1163, Dick Smith Electronics) and
placed within a small Styrofoam box to prevent crosstalk between
containers. Following administration of infection cues, males were
provisioned with water and a small piece of egg carton for refuge and
given 7 h (± 1 h) to acclimate prior to the start of recording trials.
Recording periods started at 1700 hours and ran for 39 h, ending at 0800
hours 2 days following treatment; this period captures calling effort at
times most relevant to female mate attraction (Sakaluk, 1987; Burpee and
Sakaluk, 1993; Sakaluk et al., 2002). The sound monitor sampled each
microphone throughout the recording periods every 2 seconds, and based
on the binary output resulting from this protocol, total calling time
was calculated for each male across recording periods (Hunt et al.,
2004; Duffield et al\emph{.} , 2018, 2019).

\textbf{Survival and post-mortem measurements}

Following the end of the two-night calling trials, males were returned
to their original individual rearing boxes and provided standard diet
and water \emph{ad libitum} . Mortality was monitored and recorded
daily. Upon death, pronotum width was measured as a proxy for structural
body size, using a stereomicroscope (Nikon SMZ800) equipped with a
digital camera and imaging software (Nikon NIS-Elements Documentation v.
4.20).

\textbf{Quantifying immune function}

We measured multiple immune parameters to capture a suite of immune
pathways that may differ between diets or be altered following infection
cue treatment. Here, we analyzed antibacterial activity, total
circulating hemocytes, and the presence of hemocyte microaggregations
from hemolymph that was collected immediately after calling effort
trials. General cell-free antimicrobial activity of hemolymph is a
component of the humoral immune response of insects and includes the
action of both lysozyme-like enzymes and antimicrobial peptides
(Lemaitre et al., 1997). Additionally, hemocytes are a component of the
cellular response of insect immunity, and are involved in core processes
that include coagulation, nodule formation, phagocytosis, and
encapsulation (Lavine and Strand, 2002). Finally, the microaggregation
of hemocytes is an early step in the process of nodule formation (Miller
et al., 1999; Miller and Stanley, 2004), a key insect cellular defense
reaction to bacterial challenges and responsible for clearing a large
proportion of bacteria from circulation (Howard et al., 1998). To
collect hemolymph, males were cold-anesthetized, and the membrane was
pierced under the anterior of the dorsal pronotum plate with a sterile
25 G needle, and 5 \selectlanguage{greek}µ\selectlanguage{english}L of outflowing hemolymph taken with a pre-chilled
glass microcapillary tube positioned at the puncture site. Collected
hemolymph was then expelled into 11 \selectlanguage{greek}µ\selectlanguage{english}L of chilled Grace's insect medium
(MilliporeSigma) to be used in antibacterial assays; 5 \selectlanguage{greek}µ\selectlanguage{english}L of this
mixture was then added to 15 \selectlanguage{greek}µ\selectlanguage{english}L of chilled Grace's insect medium to be
immediately used for circulating hemocyte counts and determining the
presence of microaggregations. The samples for antibacterial assays were
snap-frozen in liquid nitrogen and stored at -80\selectlanguage{ngerman}°C for later analysis.

\emph{Zone of inhibition assay}

Although immune-challenged individuals in this study were injected
with\emph{E. coli} , previous assays resulted in no measurable
antibacterial activity on plates seeded with \emph{E. coli} . Therefore,
antimicrobial activity was assayed from zones of inhibition induced by
samples on petri dishes containing agar seeded with \emph{Micrococcus
luteus} (ATCC 4698) (see Sadd and Schmid-Hempel, 2007 for methodological
details). Briefly, \emph{M. luteus} from a single colony on a streak
plate were incubated in a shaking incubator overnight at 30°C in 7 mL of
media (2.5 g peptone and 1.5 g meat extract in 500 mL of nanopure water,
pH 7.0). From this culture, bacteria were added to liquid media
containing 1\% agar held at 40°C to achieve a final density of
1.5x10\textsuperscript{5} bacterial cells/mL. Six milliliters of seeded
medium were added to a 100 mm diameter petri dish to solidify. Sample
wells were made using a Pasteur pipette (Volac D810) fitted with a ball
pump, and 2 \selectlanguage{greek}µ\selectlanguage{english}L of sample hemolymph solution thawed on ice was added to
each well. Negative (Grace's insect medium, ThermoFisher Scientific,
CAS: 11605094) control wells were also included on each plate. Plates
were inverted, incubated for 48 h at 30\selectlanguage{ngerman}°C, and then the diameter of
inhibition zones was measured for each sample. Two diameter measurements
of zones, perpendicular to one another, were measured for each sample
using ImageJ (Schneider et al., 2012) and averaged (measurements were
performed blind to treatment). Because zone of inhibition diameter does
not increase linearly with antibacterial activity, measured zone
diameters were converted, based on a standard curve, to units (mg/mL) of
lysozyme (from hen egg white, MilliporeSigma, CAS: 12650-88-3). Each
hemolymph sample was tested in duplicate, with the mean of the
duplicates being used in analyses.

\emph{Circulating hemocyte and microaggregation counts}

\selectlanguage{english}\emph{} Hemocytes were counted and microaggregations were observed at
400x magnification under a phase-contrast microscope in Fast-Read
102\selectlanguage{ngerman}\textsuperscript{®} plastic counting chambers to assess their numbers
per individual as a proxy for cellular immunity (King and Hillyer, 2013;
Stoepler et al., 2013; Duffield et al., 2018). Counting was performed
blind to diet and infection cue treatment.

\textbf{Statistical analyses}

All statistical analyses were done in R \selectlanguage{english}(version 3.6.1 or 3.6.2, R Core
Team, 2019). \selectlanguage{english}Reported results derive from the best models as determined
by corrected Akaike's information criterion (AICc; Sugiura, 1978;
Hurvich and Tsai, 1989) or before the removal of terms from the final
model.

\emph{Amount of diet consumed}

To assess the amount of diet consumed during the feeding trials, we ran
a linear mixed model using the lme4 package (Bates et al., 2015),
including pronotum width (a proxy for structural body size), diet (high
protein or high carbohydrate), and tray number (1-7) as fixed effects,
including all associated interactions, and individual identification as
a random effect. We calculated the average amount of food consumed for
each male by adding the total dry weight of food consumed and dividing
by the number of trays measured. To analyze the average amount of food
eaten, we included the main effect of diet, pronotum width as a
covariate, and the interaction between the two in a generalized linear
model with a Gamma error distribution and log link.

\emph{Reproductive effort}

Given the large number of very short calls in our data set and the
susceptibility of our sound monitor system to false positives to outside
noise or sudden movements of crickets within boxes, we followed standard
procedure and removed 5 seconds from each measurement and then rounded
any negative measurements to zero (see also Duffield et al., 2018,
2019). The final distribution of male calls indicated that calling
effort measurements were zero-inflated and overdispersed, and so we
analyzed the data using a zero-altered Poisson (ZAP) model fitted with
the package MCMCglmm (Hadfield, 2010). The ZAP model includes both a
logistic regression for the zero/non-zero component of the data (i.e.,
identifying which factors affect whether a male calls or not) and an
over-dispersed Poisson regression for the zero-truncated counts
(identifying which factors affect the amount of calling given that a
male calls).

We used binary indicator variables (0/1) to specify whether or not a
male belonged to each infection cue group and diet (Gelman and Hill,
2007). The reference group for our model was the naive infection cue and
the carbohydrate-biased (P:C 1:8) diet. Our predictors then included the
indicator for high protein (P:C 5:1) diet, 4 indicators for infection
cue, the interaction between diet and each infection cue, and also the
average amount of food eaten by that individual (centered at the mean
and scaled to standard deviation units). We ran the model for 550,000
iterations, with a burn-in of 50,000 and retaining every 100th sample.
Fixed effects are considered statistically significant if the 95\%
highest posterior density credible intervals exclude 0. For model
diagnostics, we used visual checks of the thinned chains, and ran the
model 3 times to ensure convergence to a similar posterior distribution
(Gelman and Rubin, 1992). The model used an uninformative prior for the
Poisson regression and fixed the residual variance to 1 for the logistic
regression. To check that the posterior distributions were not heavily
influenced by the prior distributions, we ran the models with multiple
different prior specifications.

\emph{Immune measures}

The full models for all immune measures (circulation hemocytes, presence
of circulating microaggregations, and zones of antibacterial activity)
included diet type, infection cue, and the interaction between the two
(main effects) as well as the average amount of diet eaten and pronotum
width (covariates). Circulating hemocytes were analyzed with a negative
binomial generalized linear model, the presence of circulating
microaggregations of hemocytes was analyzed using a generalized linear
model with a binomial distribution, and the zones of antibacterial
activity were analyzed with a generalized linear model with a Gamma
error distribution.

\emph{Mortality during and survival following diet treatments}

To investigate the effects of diet and infection cue treatments on
survival throughout the experiment, we assessed mortality and survival
at three points: mortality during the 3-week feeding period, mortality
during the 2-day calling trial, and survival following calling effort
trials. To assess mortality during both feeding trials, the full model
included diet type, the average amount of food eaten, and the
interaction between the two as main effects and pronotum size as a
covariate. The full models for mortality during the calling trial and
survival following included diet type, infection cue, and the
interaction between the two as main effects and average amount of diet
eaten and pronotum width as covariates. Mortality during both feeding
trials and calling effort trials was assessed using generalized a linear
model with a quasibinomial distribution (to accommodate overdispersion
of the data) and survival following calling trials was analyzed using a
Cox proportional hazards regression model.

\textbf{RESULTS}

\textbf{Amount of diet consumed}

We found a significant three-way interaction between diet, pronotum
width, and tray number (i.e., time period of feeding trial) on the
amount of food that males consumed during the 3-week feeding period
(\emph{F} \textsubscript{6,} \textsubscript{1776.32} = 3.16; \emph{p} =
0.0044; Fig. 1). Males held on the high carbohydrate diet (P:C 1:8)
consumed more food than those maintained on the high protein diet (P:C
5:1) early in the feeding period, but after the second tray, this
pattern was reversed, and males on the high protein diet (P:C 5:1)
consistently ate more food than those on the high carbohydrate diet
(Fig. 1A). There was also a significant interaction between diet and
pronotum width (ANOVA: \emph{F} \textsubscript{1,} \textsubscript{313} =
3.89; \emph{p} = 0.04954) with respect to the average amount of food
eaten, which increased with body size in both treatments, but more
steeply in males held on the high protein diet (Fig. 1B). To account for
this size-based variation in food consumed in subsequent analyses, we
included the average amount of food consumed for each individual, as
well as their pronotum width, as covariates in the full models.

\textbf{Mortality}

We found considerable diet-dependent mortality during the experiment.
Specifically, there was a significant interaction between the average
amount of food eaten and diet type in their effect on mortality during
the 3-week feeding period (F\textsubscript{1,488} = 4.8509; \emph{p} =
0.0281). Mortality decreased with average mass of food eaten in both
treatments, but mortality was higher in males held on the high protein
diet, at all levels of food consumed, except at lower consumption (Fig.
2A). Additionally, both diet (F\textsubscript{1,387} = 13.514;
\emph{p}\textless{} 0.001) and infection cue (F\textsubscript{4,387} =
14.427;\emph{p} \textless{} 0.001) significantly affected survival
through the 2-day calling trials; in this case, the interaction term was
not significant (F\textsubscript{4,382} = 1.032; \emph{p} = 0.3905) and
was not included in the final model. Males held on the high protein diet
were the least likely to survive through the end of the 2-day calling
trial. Controlling for diet, males receiving the highest dose infection
cue also were the least likely to survive the 2-day calling trial (Fig.
2B). Males that died prior to the conclusion of the calling trials were
eliminated from further analyses of reproductive effort, immune
function, or survival.

\textbf{Reproductive effort}

The calling effort of 391 males that survived the calling period was
measured over two consecutive days following infection cue treatment
(sample sizes for diet type and infection cue dose included in appendix
table A1). Diet had a significant effect on time spent calling (Fig. 3).
Males held on the high carbohydrate diet spent more time calling than
males maintained on the high protein diet, but the likelihood of calling
was the same for both treatments (Fig. 4B). Infection cue treatment also
influenced male calling effort (Fig. 3). We found a significant effect
of the low dose infection cue (relative to the naive controls) on both
the likelihood of calling and the amount of time spent calling (Fig. 3).
Relative to naive controls, the likelihood of calling for males injected
with the low infection cue was lower (Fig. 4A), but if they called, they
called more (Fig. 4B). None of the other infection cue treatments
differed from the naive control group with respect to either the
likelihood of calling or time spent calling.

\textbf{Immune measures}

Immune measures (circulating hemocytes, presence of microaggregations,
antibacterial activity) of 137 males were taken immediately after
calling effort trials (sample sizes for diet type and infection cue dose
included in appendix table A1). Prior mortality resulting from diet and
infection cue treatments limits our interpretation of these data.

Neither diet type (\selectlanguage{greek}\emph{χ\textsuperscript{2}}\selectlanguage{english} \textsubscript{1,131} =
2.275; \emph{p} = 0.1315) nor infection cue (\selectlanguage{greek}\emph{χ\textsuperscript{2}}\selectlanguage{english}
\textsubscript{4,131} = 2.533; \emph{p} = 0.6387) significantly
influenced the number of circulating hemocytes; the nonsignificant
interaction between diet and infection cue (\selectlanguage{greek}\emph{χ\textsuperscript{2}}\selectlanguage{english}
\textsubscript{4,124} = 5.421; \emph{p} = 0.2468) was removed from
analysis. However, the presence of circulating microaggregations of
hemocytes was significantly influenced by both pronotum width
(\selectlanguage{greek}\emph{χ\textsuperscript{2}}\selectlanguage{english} \textsubscript{1,123} = 4.237; \emph{p} =
0.0396) and the interaction between diet type and infection cue
(\selectlanguage{greek}\emph{χ\textsuperscript{2}}\selectlanguage{english} \textsubscript{4,123} = 10.472; \emph{p} =
0.0332). Larger males were more likely to have circulating
microaggregations (see appendix Fig. A1). Males fed on the high
carbohydrate diet were less likely to have circulating microaggregations
if they received the high infection cue dose, and this also tended to be
true for males fed the high protein diet and receiving a moderate
infection cue dose (Fig. A1).

For antibacterial activity of hemolymph, we found a nonsignificant trend
for infection cue to affect the zone of growth inhibition of \emph{M.
luteus} (F\textsubscript{4,125} = 2.293; \emph{p} = 0.0631), with
antibacterial activity lowest at the high infection cue dose (estimated
marginal means \selectlanguage{ngerman}± standard error: naive = 2.248 ± 0.487, sham = 1.457 ±
0.322, low = 1.567 ± 0.326, moderate = 2.189 ± 0.490, high = 0.944 ±
0.218). However, diet type did not significantly influence antibacterial
activity (F\textsubscript{1,125} = 0.9194; \emph{p} = 0.33949; estimated
marginal means ± standard error: high protein = 1.66 ± 0.251, high
carbohydrate = 1.41 ± 0.172).

\textbf{Survival after calling trials}

Survival of 211 males was tracked daily following the conclusion of
calling effort trials (sample sizes for diet type and infection cue dose
included in appendix table A1).

Neither diet type (Cox proportional hazards
regression:\selectlanguage{greek}\emph{χ\textsuperscript{2}}\selectlanguage{english} \textsubscript{1} = 0.900;
\emph{p} = 0.3428) nor infection cue dose (Cox proportional hazards
regression:\selectlanguage{greek}\emph{χ\textsuperscript{2}}\selectlanguage{english} \textsubscript{4} = 1.371;
\emph{p} = 0.8492) significantly influenced survival following calling
effort trials; the nonsignificant interaction between diet and infection
cue (\selectlanguage{greek}\emph{χ\textsuperscript{2}}\selectlanguage{english} \textsubscript{4} = 4.598; \emph{p} =
0.3311) was removed from analysis.

\textbf{Discussion}

The results of our study show that both macronutrient intake and a
simulated infection threat influence the expression of life history
traits in decorated crickets, \emph{G. sigillatus} . Specifically, both
diet and an immune challenge with heat-killed bacteria: 1) affected male
reproductive effort, quantified here as male calling effort and 2)
greatly altered male survival. The two diets used in the current study
were deliberately selected because they had been shown previously to
either maximize calling effort (P:C = 1:8, high carbohydrate diet) or to
maximize immune function, at least with respect to encapsulation ability
(P:C = 5:1, high protein diet) (Rapkin et al., 2018), thereby making it
more likely that the effects of our immune challenge would be contingent
on the diet on which males had been maintained. However, we found no or,
at best, weak evidence of an interaction between the diet on which males
were maintained and the level of the immune challenge that they
experienced in the expression of life-history traits. Moreover, although
our results aligned with the anticipated effects of these two diets on
male calling, surprisingly, they were in apparent contradiction of the
anticipated effect on male immunity. We elaborate on these differences
below and seek to identify potential mechanisms mediating observed
treatment effects and the factors potentially constraining an
interaction between diet and the magnitude of an immune challenge on
male life history strategy.

Males maintained on a high protein diet exhibited significantly higher
mortality than those held on the high carbohydrate diet. Nearly 30\% (68
out of 249) of males maintained on the high protein diet died prior to
end to the experiment compared with less than 14\% (33 out of 245) of
males held on the high carbohydrate diet. This is consistent with
numerous findings across taxa showing that lifespan is truncated in
animals fed a high protein, low carbohydrate diet (reviewed in Le
Couteur et al., 2016 and Simpson et al., 2017), including \emph{G.
sigillatus} (J. Hunt, unpublished data). These recent discoveries, which
contrast with conventional Y resource allocation models (van Noordwijk
and de Jong, 1986; Zera and Harshman, 2001), have inspired the lethal
protein hypothesis (Lee et al., 2008; Fanson et al., 2009; Simpson and
Raubenheimer, 2009). Proposed mechanisms mediating the lethal protein
hypothesis include increased mitochondrial generation of radical oxygen
species (Sanz et al., 2004), changes in the relationship between
insulin/IGF-1 and amino acid signaling (e.g., TOR) pathways (Kapahi et
al., 2004), and damage to organs from nitrogenous waste products.
Although further studies are needed to conclusively determine whether
the diet-induced mortality in the present study is due to an excess of
protein or a deficit of carbohydrates, it is unlikely due to the latter
as males were always provided more food than they could eat, suggesting
that they were not carbohydrate limited. Males held on the high protein
diet consumed a greater amount of food than those held on the high
carbohydrate diet across the entire range of body sizes, which could
have been due to a greater nutritional demand for carbohydrates in the
former. Indeed, Rapkin et al. (2018) showed that when male \emph{G.
sigillatus} are given a dietary choice, they regulate their intake of
protein and carbohydrate to a P:C ratio of 1:2.

As was the case with diet, infection cue dose had a significant effect
on male survival through the end of the two-day calling period.
Specifically, the highest infection cue dose resulted in higher male
mortality than any of the other infection cue levels. This suggests that
our simulated infection threat imposed a physiological cost on males,
and that at the most severe infection threat level, this cost was
manifest in increased mortality. This is consistent with a cost of using
the immune system (Sadd and Schmid-Hempel, 2009), which has been shown
to have consequences for survival in other insect taxa (Moret and
Schmid-Hempel, 2000; Armitage et al., 2003). This has also previously
been shown to be independent of nutritional condition in another cricket
species (Jacot et al., 2004).

Both diet and infection cue treatment had significant effects on male
reproductive effort, measured here as the time spent calling to attract
a mate (termed calling effort). Calling effort was significantly higher
in males held on the high carbohydrate diet than in those held on the
high protein diet, consistent with previous work (Rapkin et al., 2018).
We also found that infection cue, specifically at a low dose, impacts
male reproductive effort. If they called, males injected with a low
infection cue dose called more relative to naive controls. This
increased calling effort is consistent with a pattern of terminal
investment (Duffield et al., 2017), but, surprisingly, neither of the
two higher infection cue treatments differed from the naive control
group with respect to calling effort. However, at least in the case of
males injected with the high infection cue dose, males experienced at
least a two-fold higher mortality during the calling period compared
with males in the other infection cue treatments, and thus, males in
this group were, to some extent, self-selected. If the males that died
were those that were more inclined to terminally invest, whereas those
that survived prioritized maintenance over reproduction, then this would
attenuate any effect of infection cue treatment on calling effort at the
more severe infection threat levels.

Although diet and infection cue treatment independently influenced male
calling effort, we found no evidence of an interaction between these two
factors. The absence of such an interaction contrasts with an early
study demonstrating an interaction between male age and infection cue
dose, in which older male \emph{G. sigillatus} increased their calling
effort in response to the same graded increase in infection threat used
here, whereas younger males did not (Duffield et al., 2018). Why do
males retain this level of plasticity in calling effort with respect to
age, but not diet? One possibility is that age overrides any influence
of diet on the propensity to shift life history strategy, given that it
has been previously shown that males at the age used in this study
exhibit terminal investment, whereas younger males do not (Duffield et
al., 2018). A standard lab diet was provided in this previous study, but
it is possible that terminal investment in younger males could be
elicited by certain combinations of diet and infection cue dose, in line
with the dynamic terminal investment threshold model (Duffield et al.,
2017). An alternative is that males were terminally investing in other
important components of reproductive effort that we did not measure in
the present study. For example, the spermatophore transferred by males
at copulation includes a large gelatinous mass, the spermatophylax, that
the female consumes after mating as a nuptial food gift, which is
critical to male fertilization success (Sakaluk, 1984; Sakaluk, 1986;
Sakaluk and Eggert, 1996; Eggert et al., 2003). Duffield et al. (2015)
showed that immune-challenged males terminally invest by altering the
free amino acid profile of the spermatophylax, enhancing its gustatory
appeal to females (see also Gershman et al., 2012). Moreover, male
chemical cues, in the form of cuticular hydrocarbons (CHCs), greatly
influence whether a female mounts a male, a necessary antecedent to
copulation (Weddle et al., 2013; Capodeanu-N\selectlanguage{ngerman}ägler et al., 2014). The CHC
profile of a male, and by extension, his attractiveness, can be
significantly influenced by his nutritional environment (Weddle et al.
2012). Both CHC expression (Rapkin et al., 2016) and the amino acid
composition of the spermatophylax (Rapkin et al., 2017a) are optimized
at a P:C ratio of 1:1.3 and 1:1.5, respectively, ratios far removed from
the two diets offered in the present study.

Despite our initial expectation, we found no evidence that males held on
the high protein diet exhibit enhanced immune function. Specifically,
there was no positive effect of diet on the number of circulating
hemocytes, presence of microaggregations, or antibacterial activity of
the hemolymph. We did, however, find a significant interaction between
diet and infection cue dose on the incidence of circulating
microaggregations of hemocytes, suggesting that both factors could
affect this immune response. This contrasts with the results of a
previous study showing that among 24 diets differing in P\selectlanguage{english}:C ratio and
distributed along six nutritional rails, a P:C = 5:1 ratio optimizes
immune function as assessed using an encapsulation assay (Rapkin et al.,
2018). In the present study, however, we did not measure the
encapsulation ability of males, and the difference between the two
studies may be a function of the different components of immunity that
were measured. Different facets of immunity can be triggered by
different types of threats or regulated independently, resulting in
positive, negative, or no associations between immune components (Adamo,
2004; Forsman et al., 2008). Indeed, although Rapkin et al. (2018)
demonstrated a significant effect of macronutrient intake on male
encapsulation ability, they found no effect of diet on the activity of
phenoloxidase, an important enzyme in the melanization cascade.
Ultimately, we are cautious to draw any firm conclusions about the
influence of diet and infection cue on immune parameters, due to the
interesting but confounding differential effects of these factors on
survival prior to the assaying of immunity.

In conclusion, both macronutrient intake and a simulated infection
threat independently influenced the survival and reproductive effort of
male \emph{G. sigillatus} . There was evidence for terminal investment,
as males increased calling effort at the low infection cue dose, but
interpretation of responses at the higher threat levels was hampered by
the differential mortality of males across diet and infection cue
treatments, the latter demonstrating a cost of immune activation for
survival. There was, however, no evidence of an interaction between diet
and infection cue dose in their influence on calling effort, suggesting
that the threshold for terminal investment was not contingent on diet,
in contrast to earlier work documenting a shifting terminal investment
threshold contingent on male age (Duffield et al., 2018). The absence of
a dynamic terminal investment threshold may have been due to the
previously documented influence of age masking other intrinsic and
extrinsic factors, or, alternatively, males prioritizing investment in
other components of reproductive effort. Regardless, how reproductive
effort changes in accordance with the various intrinsic and extrinsic
factors that alter an individual's residual reproductive value remains a
fertile area of inquiry (Duffield et al., 2017), but any generalizations
must await additional comparative studies that preferably incorporate
multiple facets of male reproductive effort.

\textbf{Acknowledgements}

We extend the sincerest thanks to Molly Schumacher, Christine Poppe, and
Ian Rines for their assistance with data collection. \selectlanguage{english}

\textbf{Funding}

This research was funded by a grant from the National Science Foundation
to S.K.S., B.M.S., and J.H. {[}IOS 16--54028{]}, grants from the Sigma
Xi Research Honor Society, the Beta Lambda Chapter of the Phi Sigma
Biological Honor Society, a Godfrey Hewitt Mobility Award from the
European Society for Evolutionary Biology, and Graduate Student
Association of Illinois State University to K.R.D., a grant from the
Australian Research Council to J.H. {[}DP180101708{]}, and a grant from
the National Institutes of Health to B.M.S. {[}R15GM12968{]}.

\textbf{Data accessibility}\selectlanguage{english}

All data supporting this manuscript will be deposited in Dryad upon
acceptance.

\textbf{Competing interests}

No competing interests declared.

\textbf{Author contributions}

Conceptualization (KRD, BMS, SKS), data curation (KRD), formal analysis
(KRD, TMH), funding acquisition (KRD, JH, BMS, SKS), investigation (KRD,
KJH), methodology (KRD, TMH, JR, JH, BMS, SKS), resources (JR, JH, BMS,
SKS), visualization (KRD), writing- original draft preparation (KRD,
BMS, SKS), writing- review \& editing (all authors).

\textbf{EEO/Non-Discrimination statement}

USDA is an equal opportunity provider and employer.

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\textbf{Figure legends}

\textbf{Figure 1:} Diet consumption by male \emph{G. sigillatus}fed
either of two diet types (P:C = 5:1 and 1:8). (A) The amount of food
eaten (dry weight of trays containing diet both before and after
offering) across tray number (i.e., feeding period time). (B) The
average amount of diet eaten during the feeding trial between diet types
and based on pronotum width, a proxy of structural body size. Feeding
periods were 3 weeks long and trays were switched every 3 days for each
male.

\textbf{Figure 2:} Mortality of male \emph{G. sigillatus} during the
3-week feeding trial (A) and subsequent 2-day calling period (B) based
on diet (P:C = 5:1 or 1:8) and infection cue treatments.

\textbf{Figure 3:} \selectlanguage{english}MCMCglmm zero-altered Poisson (ZAP) analysis of the
likelihood of calling (a logistic regression for zeros) and time spent
calling (zero-truncated Poisson) in male crickets (\emph{G. sigillatus}
) fed either of two diet types and administered an infection cue from a
gradient of increasing intensity using heat-killed bacteria. \selectlanguage{english}Diet
effects are shown as the deviation from the P:C 1:8 diet treatment and
overall infection effects are shown as differences from the naive level.

\textbf{Figure 4:} \selectlanguage{english}Model predicted effects of diet type and infection
cue (from a gradient of increasing intensity using heat-killed bacteria)
on the (A) likelihood of calling and (B) time spent calling (given that
a male produced a call) in \emph{G. sigillatus} . Points show predicted
effects with 95\% confidence intervals, taken from MCMCglmm ZAP
analysis.

\textbf{Appendix:}

\textbf{Table A1:} Sample sizes for measurements of calling effort,
survival post-calling effort trials, and immune function (circulating
hemocytes, presence of microaggregations, antibacterial activity) of
male \emph{G. sigillatus} fed either of two diet types and administered
a treatment from an increasing spectrum of infection cue intensity.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Diet & Infection Cue & Calling & Survival & Immune
Function\tabularnewline
\midrule
\endhead
P:C = 5:1 & naive & 33 & 20 & 11\tabularnewline
& sham & 36 & 21 & 11\tabularnewline
& low & 35 & 21 & 12\tabularnewline
& moderate & 34 & 20 & 11\tabularnewline
& high & 41 & 14 & 9\tabularnewline
P:C = 1:8 & naive & 40 & 23 & 17\tabularnewline
& sham & 41 & 23 & 17\tabularnewline
& low & 41 & 24 & 17\tabularnewline
& moderate & 43 & 25 & 16\tabularnewline
& high & 47 & 20 & 16\tabularnewline
total & & 391 & 211 & 137\tabularnewline
\bottomrule
\end{longtable}

\textbf{Figure A1:} The presence of circulating microaggregations of
hemocytes in male \emph{G. sigillatus} across pronotum width (left) and
in response to diet type and infection cue dose (right).\selectlanguage{english}
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