Dietary Implications of Interactions between Ants and Symbiotic Bacteria
by
Lina María Arcila Hernández
A thesis submitted in conformity with the requirements for the degree of Masters of Science Graduate Department of Ecology and Evolutionary Biology University of Toronto
© Copyright by Lina María Arcila Hernández, 2012
Dietary Implications of Interactions between Ants and Symbiotic Bacteria
Lina María Arcila Hernández
Masters of Science
Graduate Department of Ecology and Evolutionary Biology
University of Toronto
2012
ABSTRACT
Studies of symbiotic bacteria have demonstrated that they provide multiple benefits to their
hosts. These studies, however, have overlooked the importance of interactions with other
bacteria and environmental factors that affect bacterial assemblages. To understand what
shapes bacterial assemblages, I manipulated the diet of ants from the genus Cephalotes and
disturbed their gut microbiome. I found that a deficit of nitrogen reduces bacterial densities.
Furthermore, the data suggest that bacterial abundance may influence ant survival. I followed
this experiment up by manipulating a putative protein source in the field. Our lab assigned
Allomerus octoarticulatus ant colonies to treatments in which potential prey were present or
absent. I collected data on foraging behaviour, colony performance, and composition of the bacterial community. The absence of prey increased ant recruitment to protein-rich baits; these
ants were also less fit than ants that had insect prey but their bacterial assemblages were not
affected.
ii
ACKNOWLEDGMENTS
The last 16-18 months have been full of excitement and an immeasurable amount of learning, not only of nature and science but also of my own abilities. None of this would have been possible if my advisor Megan Frederickson had not been there for me. Megan a thank you may just not be enough this time but: un millón de gracias!
To my advisory committee, Megan Frederickson, James Thomson, John Stinchcombe, and Stephen Wright, I owe this thesis. Although I was somehow overwhelmed by the presence of four smart and talented professors on my first meeting, I quickly understood that all of you were there willing to guide a new sheep on the great world of science. Thank you all for your valuable comments and guidance through the last year and a half. I want to acknowledge
Benjamin Gilbert and Don Jackson who helped me with some of my data analysis.
Furthermore, this project would not have been possible without the lab expertise, fieldwork assistance and home cooking of Jon Sanders. I am in debt to the Girguis lab at Harvard that allowed me to use their equipment for molecular work, especially Roxie Beinart and Kiana
Franck. I also give special thanks to Greg Booth, Antonio Coral, René Escudero, Gabriel
Miller, Alison Ravenscraft, and Lisseth Quispe for field assistance and fun times in Peru. I also want to recognize all the help and support I have had from the Frederickson current lab members, Kyle Turner and Adam Cembrowski; ex-lab technician, amazing Emma Hodgson; and undergrad students, Viviana Astudillo, Annabelle Ong, Margaret Thompson, Melissa
Donnelly, and Ishita Aggarwal. Finally but not least, I am extremely grateful to my family, especially my parents and brother, and friends that always encourage me to keep moving forward. This project was funded by an NSERC Discovery grant to Megan Frederickson and a
Sigma Xi Grant-in-aid of Research to Lina M. Arcila Hernández.
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TABLE OF CONTENTS
ABSTRACT……………………………………………………………………………ii
ACKNOWLEDGMENTS……………………………………………………………..iii
LIST OF TABLES……………………………………………………………………..vi
LIST OF FIGURES…………………………………………………………………...vii
LIST OF APPENDICES……………………………………………………………….x
CHAPTER ONE- General Introduction…………………………………………………….1
CHAPTER TWO- Effects of diet, antibiotics, and bacteria reintroduction on microbial assemblages in Cephalotes spinosus and repercussions for ant colony performance....…..5
ABSTRACT…………………………………………………………………………….5
INTRODUCTION……………………………………………………………………...5
METHODS……………………………………………………………………………..9
Study site and system…………………………………………………………...9
Collection of Cephalotes spinosus colonies and experimental design………...11
Abundance of gut microbes……………………………………………………13
Statistical analysis…………………………………………………………….14
RESULTS……………………………………………………………………………..14
Survival of adults and brood…………………………………………………..14
Abundance of gut microbes……………………………………………………15
DISCUSSION…………………………………………………………………………17
On interactions between ant survival and bacterial abundance……………...17
On mechanisms for change in bacterial abundance…………………………..20
CHAPTER THREE- The macronutrient requirements of a tropical arboreal ant…..31
ABSTRACT…………………………………………………………………………...31
iv
INTRODUCTION…………………………………………………………………….32
METHODS……………………………………………………………………………35
Study site and system………………………………………………………….35
Experimental manipulation of insect herbivores/prey………………………...36
Ant diet………………………………………………………………………...37
Colony performance…………………………………………………………...38
Gaster microbiome…………………………………………………………….38
Statistical analysis…………………………………………………………….39
RESULTS……………………………………………………………………………..40
Diet and colony performance………………………………………………….40
Gaster microbiome…………………………………………………………….41
DISCUSSION…………………………………………………………………………42
Allomerus octoarticulatus diet………………………………………………...42
Colony performance…………………………………………………………...45
Gaster microbiome…………………………………………………………….46
Effects of multispecies interactions on the mutualism……...…………………49
CHAPTER FOUR- Concluding Remarks………………………………………………….59
LITERATURE CITED……………………………………………………………………...61
v
LIST OF TABLES
Table 2.1. Parametric survival analysis of (A) adults and (B) brood…………………………29
Table 2.2. Mixed model ANOVA results showing the factors affecting the number of bacterial
16S copies found in the guts of C. spinosus workers on day 13 (A) and day 28 (B)..….30
Table 3.1. MANOVA results for the different data sets of stable isotope ratios. H&T indicates
samples with only heads and thoraces and Whole indicates samples with whole ants.
Statistically significant values in bold…………………………………………………..57
Table 3.2. Adonis test for A) herbivore treatments and B) block effects…………………….57
Table 3.3. Model selection of biological and environmental factors using AIC……………..58
vi
LIST OF FIGURES
Figure 2.1. A) A Cephalotes spinosus worker. Photo © J. Sanders. B) Ten workers and five
larvae lived in small plastic containers for four weeks. Disposable pipettes were cut in
half; one half was used to store water and the other half simulated a nest chamber. The
red tent provided darkness to the workers………………………………………………24
Figure 2.2. Survival plot for Cephalotes spinosus A) adult workers and B) brood…………..25
Figure 2.3. Interaction effects of diet (‘Com’ refers to a complete diet and ‘Noaa’ to a no
amino acids diet), gut bacteria reintroduction (‘N’ for no reintroduction, and ‘Y’ for
introduction) and presence of antibiotics on the proportion of adults (A and B) and brood
(C and D) surviving to the last day of the experiment………………………………….26
Figure 2.4. Effects of diet, antibiotics, reintroduction of guts and their interactions on number
of bacterial cells on the 13th day of the experiment (A and B; note that reintroduction of
bacteria had not taken place at this point, hence the division of treatments Y and N is
artificial) and on the last day of the experiment (C and D). ‘Com’ refers to a complete
diet and ‘Noaa’ to a no amino acids diet. ‘Y’ codes for treatments that received guts on
day 14 and ‘N’ codes for treatments that did not……………………………………….27
Figure 2.5. Relationship between the number of 16S copies (square-root transformed) and the
proportion of surviving adults (logit transformed) on day 28 of the experiment (r2= 0.22,
P = 0.02)………………………………………………………………………………...28
Figure 3.1. A) A C. nodosa domatium. B) A food body on the underside of a C. nodosa leaf.
C) A. octoarticulatus workers foraging on C. nodosa leaves. Photos © G. Miller……..51
vii
Figure 3.2. Morphological measurements taken on A. octoarticulatus workers. HL: head
length, ML: mesosoma length, P: petiole and postpetiole length, G: gaster length, MW:
mesosoma width, HW: head width, SL: scape length, and MaL: mandible length. Photos
© A. Nobile……………………………………………………………………………..51
Figure 3.3. Mean (± SE) number of ants that recruited to protein-rich (P) baits after five hours
on herbivore-excluded (H-) and control (H+) plants……………………………………52
Figure 3.4. Carbon and nitrogen stable isotope ratios for ants in the H+ (closed circles) and H-
(open circles) treatments. H&T indicates samples with only heads and thoraces; Whole
indicates samples with entire ants. Isotope ratios for naturally occurring C. nodosa, A.
octoarticulatus workers, insect herbivores (coleopterans, hemipterans, etc.), and
predatory spiders found on C. nodosa are given for reference………………………….52
Figure 3.5. A) Mean (± SE) worker mass and B) worker length of ants that developed with
access to insect herbivores (H+) and in the absence of insect herbivores (H-)…………53
Figure 3.6. Mean (± SE) number of workers produced in colonies with access to insect
herbivores (H+) and in the absence of insect herbivores (H-) after 11 months………...53
Figure 3.7. Relationship between worker weight (log-transformed) and the residual values of
the number of reproductives (alates; square-root transformed) per colony (r2= 0.56)….54
Figure 3.8. Phylogenetic diversity of microbes in the gaster of ants with access to insect
herbivores (closed circles) and in the absence of insect herbivores (open circles) (P>>
0.05). Rarefaction plot obtained with a PD whole tree matrix…………………..……...54
Figure 3.9. Relative abundance of bacteria phylums per sample. Category axis is labelled with
the block letter followed by treatment (H+: herbivores; H-: no herbivores)………….55
viii
Figure 3.10. Ordination of bacterial assemblages explained by the first two principal
coordinates from a weighted UniFrac (A) and unweighted UniFrac distance matrix (B).
Letters indicate blocks…………………………………………………………………..55
Figure 3.11. Relationship between the number of scale insects and ant colony size for ants
with access to insect herbivores (closed circles) and in the absence of insect herbivores
(open circles). Figure modified from Frederickson et al. 2012…………………………56
ix
LIST OF APPENDICES
APPENDIX A – Article: Salt intake in Amazonian ants: too much of a good thing?...... 76
APPENDIX B – Components of the artificial diets. *Only added to treatments with
antibiotics……………………………………………………………………………...104
APPENDIX C - List of consensus lineages assigned to the OTUs found in the gasters of A.
octoarticulatus and total number of reads…………………………………………..…105
x 1
CHAPTER ONE
General Introduction
Plants and animals associate with microbes that can have positive or negative effects on their fitness. Most studies have focused on the negative effects of microbes—that is, on the study of microbes as pathogens (e.g., Hilgenboecker et al. 2008). However, for about two decades there has been a steady increase in the study of microbes as mutualistic symbionts (Moran
2001; Moran 2006; Clark et al. 2010). Special emphasis has been given to microbes that live inside, and have often coevolved with, their hosts (i.e., endosymbionts). Some hosts that depend on endosymbionts have evolved bacteriomes, specialized cells or organs that provide protection and other advantages to the microbes living inside (Oliver et al. 2010).
Mitochondria and chloroplasts are well-known examples of endosymbiosis (Sagan 1967) and show how both hosts and microbes can become so dependent on their partners that neither can survive without the other. This is also the case in the association between the obligate endosymbiont Buchnera and some species of aphids (Baumann et al. 1997).
Since bacteria and other microorganisms have high evolutionary rates and fast generation times, assemblages of microbes living in hosts are thought to be very variable.
However, recent studies have shown that even though microbial assemblages might change over time, a portion of the species can be stable across generations or different host populations (Degnan et al. 2004; Sekelja et al. 2010). Associations can be so steady that
Moran et al. (1993) showed, for example, that endosymbiotic associations have coevolved with aphids for more than 100 Ma by demonstrating that the phylogenies of both host and endosymbiont taxa are highly correlated. This implies that there is a core group of endosymbionts that remain constant during the life of a host, possibly aiding either with host
2 nutrition (e.g. Hosakawa et al. 2010) or defence (e.g. Scarborough et al. 2005; Janson et al.
2008).
Consequently, bacterial symbionts offer their hosts the possibility of exploring new niches where they are released from predators, diseases, or dietary limitations. Most studies that have examined endosymbionts in arthropods have determined that these associations have allowed arthropods to explore new dietary niches (Janson et al. 2008). In cases where the host feeds on a limited diet, such as wood or extra-floral nectar, symbionts can supply hosts with essential amino acids, vitamin B, or other metabolites needed for the nutrition and development of insects (Fraenkel 1959; Schmitt-Wagner et al. 2003; Hosakawa et al. 2010).
Severe reductions of microbial genomes to include only those genes that code for essential metabolites reveals the importance of this nutritional role for many obligate endosymbionts.
Furthermore, this genome reduction is possible because the host provides a stable environment, food, and, in many organisms, even facilitates vertical transmission to offspring
(Clark et al. 2010). However, not all bacteria that provide nutritional benefits are intracellular.
There are also extracellular symbionts that can be horizontally transmitted but still provide important supplements to their hosts’ diet. In general, assemblages of bacterial symbionts may have contributed to the adaptive radiation of arthropods into different niches (Janson et al.
2008).
Hymenoptera, for example, is an exceptionally species rich group that plays many different ecological roles in a community. This is especially true of ants; with over 12,000 species (Bolton 2003), ants are present in almost every habitat and have adopted many different ecological strategies for their survival. In a regular day in the rainforest, it is possible to see seed harvesters, fungus-growers, predators, and herbivorous ants in addition to a great
3 number of ant-plant associations. It has been suggested that these different roles were in part possible because ants formed nutritional mutualisms with endosymbionts (Zientz et al. 2005;
Janson et al. 2008, Russell et al. 2009). For instance, some species of ants, such as carpenter ants (in the genus Camponotus), have intracellular bacteria in the genus Blochmannia, closely related to Buchnera in aphids, that provide nutritional benefits (Degnan et al. 2005).
Moreover, extracellular symbionts are frequently observed in the guts or near the ovaries in ants (Cook & Davidson 2006). Finally, surveys of gut bacteria in museum specimens of ants suggest a correlation between gut bacterial assemblages and the trophic level of ants (Russell et al. 2009). Even though the presence of bacterial symbionts in ants has been confirmed multiple times, the effects of these microbes on individual ants and on colony performance have been little explored.
Studies in humans have shown that a dramatic change in diet over generations can change the composition of gut bacteria (De Filipo et al. 2010). Therefore, I expect to find similar results in other organisms such as ants. For instance, in ant-plant interactions, ants defend the plants against herbivores and plants provide food and/or shelter to ants.
Additionally, if gut bacteria affect ant survival, I predict that the strength of interactions in the community will change if ants, for example, perform poorly due to a disturbance in their bacterial assemblages, and, as a result, they cannot provide benefits to their partners, such as defence against insect herbivores. However, to my knowledge, studies of ant-microbe interactions have rarely examined how different diets and environmental factors affect microbial assemblages and how these changes affect colony fitness and/or ecological interactions. To investigate these questions, I took three approaches. Firstly, I carried out an observational study where I expected to obtain information on how ant bacterial assemblages varied with forest stratum. I collected ants at a variety of bait types in both the leaf litter and
4 the canopy of a tropical rainforest. Unfortunately, I did not obtain enough ants of the same species (or related species) to compare the gut microbiota of leaf litter versus canopy ants in a meaningful way. Nonetheless, the data I collected in this survey are now part of the article
“Salt intake in Amazonian ants: too much of a good thing?” submitted to Insectes Sociaux on
October 29th, 2011 (Appendix A). Secondly, I manipulated the bacterial assemblage and diet of the ant species Cephalotes spinosus to examine their effects on the relative fitness of ants
(Chapter Two). Lastly, I controlled the availability of insect prey in an ant-plant system to observe the effects on the microbiome of the ant species Allomerus octoarticulatus and its possible consequences for the ecological interactions of ant hosts (Chapter Three).
5
CHAPTER TWO
Effects of diet, antibiotics, and bacteria reintroduction on microbial assemblages in
Cephalotes spinosus and repercussions for ant colony performance
Abstract
The gut microbiome can harbor both mutualistic and pathogenic bacteria. Over the last few decades, studies of arthropods (mainly aphids and termites) have shown that mutualistic gut bacteria can have beneficial effects on their hosts that include increased body size, condition, reproductive success, or survivorship. However, few studies have explored what factors affect gut bacterial assemblages and the consequences of changes in the gut microbiome for the arthropod host. Here, I studied the effects of diet, antibiotics, and reintroduction of bacteria on the gut microbiome of Cephalotes spinosus and their impact on worker and brood survival. I established Cephalotes spinosus microcolonies comprising ten or eleven workers and five larvae and fed them with artificial diet with or without amino acids and antibiotics for a month. After two weeks, I also reintroduced gut bacteria to some of the treatments with antibiotics. I found that an increase in gut bacteria is linked to an increase in ant survival suggesting that the gut microbiome may provide benefits to Cephalotes. Furthermore, I found that bacterial assemblages are highly limited by nitrogen sources and thus competition for resources likely plays an important role in shaping the gut microbiome of Cephalotes spinosus.
6
Introduction
Although the beneficial effects of microorganisms on the physiology or behaviour of other organisms are often overlooked in ecology, they are known to play an essential role in the survival and overall performance of their hosts (Clark et al. 2010). In their recent review,
Brownlie & Johnson (2009) explore the many ways in which microorganisms can provide protection to their insect hosts, concluding that symbionts ultimately act as a second immune system. Protection by microorganisms seems to be ubiquitous and it is not exclusive to insects.
For example, in ryegrass pastures, the endophytic fungus Neotyphodium lolii produces chemical defences that reduce herbivory by insects and livestock on its host (Prestidge et al.
1982; Easton et al. 2001). Microbes can also protect against diseases, thus improving the health of their hosts. For instance, one study found that pathogenic Wolbachia provided antiviral protection to Drosophila melanogaster, thereby reducing fly mortality when infected with Drosophila C virus (Hedges et al. 2008). In addition, several medical studies have shown that bacteriotherapy, the transplant of a fecal sample from a healthy human to a human with a gastrointestinal disorder, cures several forms of colitis (Borody et al. 2003; Borody et al.
2004). In this case, it has been suggested that beneficial microbes from healthy individuals are antagonists of the disease agent in the digestive systems of unhealthy patients. However, the mechanisms that make this type of therapy successful remain uncertain (Borody et al. 2004) and it is also unclear whether competitive dynamics among gut bacteria can influence the interaction between host and symbionts. Traditionally, studies of microorganisms have focused on understanding competition for nutrients or prey in a pairwise manner but have not determined the importance of these mechanisms in a big network such as the gut microbiome.
Furthermore, positive feedback among bacteria, based on release of chemicals, has been
7 discovered and may be an alternative mechanism for the stability of microbial assemblages
(Haruta et al. 2009).
Protection against predation or disease is not the only benefit that symbionts (i.e., microorganisms that live inside a host) can provide to their partners. Maybe a more common advantage to hosting microorganisms is their role as nutrient upgraders. This partnership may be especially important when hosts feed on diets with restricted nutrients because the symbionts often supply the hosts with essential metabolites, such as nitrogen or vitamins
(Schmitt-Wagner et al. 2003; Baumann 2005; Degnan et al. 2005). In the soil and its associated organisms, nitrogen fixation by bacteria occurs through a process called
+ ammonification that converts atmospheric nitrogen (N2) into ammonium (NH4 ) or ammonia
(NH3), which, unlike N2, are forms of nitrogen that many organisms can absorb. Similarly,
+ - nitrifying bacteria convert NH4 into nitrates (NO3 ), another nitrogen form that can be assimilated by organisms (Vitousek et al. 2002). Such is the case in many plants that depend on their relationship with mycorrhizal fungi for absorption of minerals, nitrogen and water (for a review see Brundrett 1991) or rhizobia bacteria that fix atmospheric nitrogen (e.g., Lynch
1990; Zahran 1999). Studies of arthropods have also shown that bacterial symbionts upgrade nutrients. One of the best studied systems is Acyrthosiphon pisum, the pea aphid, and its obligate symbiont, Buchnera aphidicola. Pea aphids feed on phloem sap that is rich in carbohydrates but poor in other nutrients, but B. aphidicola synthesizes essential amino acids for its aphid hosts (e.g., Wilkinson 1998; Vogel & Moran 2010).
Because in both cases of protection and nutrition the host benefits from housing symbionts, it is reasonable to think that this type of mutualism is widespread in nature.
Nevertheless, the effects of microbial assemblages have been little studied in most common
8 eusocial insects (with the exception of termites, see Rosengaus et al. 2011 for an example). In eusocial insects such as ants and some bees, food is shared among the members of the colony via trophallaxis (i.e., mouth-to-mouth or anus-to-mouth feeding) and individual foragers may exploit diverse food resources (Zientz et al. 2005; Evans & Schwarz 2011). As a result, an ant or a bee may balance its diet with food from a nestmate, potentially reducing nutrient limitation at the individual level. At the same time, trophallaxis may promote horizontal transmission of gut bacteria among colony members, which might help to homogenize microbial assemblages (Wilkinson 2001). For instance, if a worker is infected with a bacterial pathogen, acquiring beneficial bacteria from its nestmates could increase competition among bacteria and reduce the probability the pathogen successfully colonizes the worker/host.
A recent study by Russell et al. (2009) found that many ants harbour symbiotic bacteria and that particular bacterial clades may be associated with ‘herbivorous’ (i.e., plant- exudate feeding) and predaceous ant taxa. However, of these, only intracellular bacteria in the genus Blochmannia, which live in carpenter ants (i.e., Camponotus spp.) where they recycle nitrogen and synthesize essential amino acids (Degnan et al. 2005), have been studied extensively. There have also been a few studies of beneficial bacteria associated with
Tetraponera and Atta ant colonies, both of which are considered herbivorous/omnivorous and thus help us to understand how ants can fulfil their nutritional requirements despite a predominantly plant-derived diet (Zientz et al. 2005; Eilmus & Heil 2009). Eilmus and Heil
(2009) described nitrogen-fixing bacteria from Tetraponera workers, while Atta colonies have a multispecies association with Ascomycota fungi that can fix nitrogen and free-living bacteria that can serve as antimicrobial agents to protect the fungal gardens (Mueller et al. 2008).
Overall, most of the studies of symbiotic bacteria in ants have focused on one type of bacteria and its evolutionary relationship with the host, but very few studies have examined how
9 changes in bacterial assemblages affect colony performance in ants (e.g., Jaffe et al. 2001;
Feldhaar et al. 2007).
Here, I study if putatively nutritionally beneficial bacterial symbionts affect the survival of a species of ‘herbivorous’ ants, Cephalotes spinosus. I limited the supply of amino acids provided to ants to simulate a case in which ants will have to rely on their gut symbionts for essential nutrients. I then disturbed the endosymbiont assemblages with antibiotics to determine whether a reduction in the number of bacteria affects ant survival. Furthermore, to investigate the possibility that the antibiotic I used is directly toxic to ants, I also reintroduced gut bacteria in an attempt to re-establish the original community composition of bacteria in C. spinosus guts. If bacteria are providing nutritional benefits to these ants, such as by upgrading or recycling nitrogen, I expected that 1) ant survival should not decrease when amino acids are scarce but bacterial abundance should decrease slightly, 2) ant mortality should increase and bacterial abundance should decrease when bacterial assemblages are disturbed with antibiotics, and finally, 3) ant survivorship and bacterial abundance should both increase after the re-introduction of bacteria. To assess these predictions, I analyzed variation in ant survival among treatments, as well as changes in the number of bacterial 16S copies in ant guts before and after reintroducing bacteria.
Methods
Study site and system
I carried out this study at the Centro de Investigación y Capacitación Río Los Amigos
(CICRA) in the Peruvian Amazon (380500E, 8610297N, elevation 230-270m) from May to
July of 2011. These are the driest months in this region and the mean daily temperature varied
10 from 30°C to 17°C. ‘Friajes’ or cold fronts coming from the south of the continent, which are common at this time of year, caused the low temperatures. CICRA is part of a 146,000-hectare conservation concession. It mostly consists of primary tropical rainforest in several different habitat types created in part by the rerouting and flood patterns of the Madre de Dios and Los
Amigos rivers (Pitman 2008).
Cephalotes ants are common in this region. These strictly arboreal ants nest in hollow branches in the forest canopy and forage for food on leaves and tree trunks (De Andrade &
Baroni-Urbani 1999). They also tend hemipterans to obtain honeydew (Maravalhas & Morais
2009). Since they derive most of their diet from plants, they are considered to be herbivorous/omnivorous and as in many other herbivores, their diet may lack essential nutrients like amino acids (Davidson et al. 2003). Histological and morphological analyses of their digestive systems found that Cephalotes workers have abundant bacteria in their ileums, which are enlarged and appear to be specialized for harbouring these microorganisms
(Caetano & da Cruz-Landim 1985; Bution and Caetano 2008). Thus, it is thought that these ants depend on their gut bacteria to obtain essential metabolites that are scarce in their diets
(Russell et al. 2009).
As far as I am aware, Yurman and Dominguez-Bello (1993) made the first attempt to describe the gut microbes in Cephalotes atratus workers by culturing the bacteria; they found abundant rod-shaped, Gram-negative bacteria. Since then, a few studies have shown that different species of Cephalotes have similar gut microbiome profiles (Bution et al. 2010) and have described some of the bacteria associated with this genus (e.g., Actinomycetales,
Burkholderiales, Caulobacterales, Pseudomonadales, Rhizobiales, Sphingobacteriales,
Verrucomicrobiales, and Xanthomonadales; Jaffe et al. 2001, Russell et al. 2009). To my knowledge, there has only been one manipulative experiment that looked at Cephalotes
11 pussillus and Cephalotes atratus survival after antibiotics were used to reduce the abundance of gut bacteria (Jaffe et al. 2001). Jaffe et al. (2001) found that ants in microcolonies did not eat the diet treated with antibiotics that targeted Gram-negative bacteria, such as Gentamicin, and died as a result of starvation; while ants fed with antibiotics such as Penicillin survived longer. However, mortality in antibiotic-treated colonies, instead of microcolonies, was not significantly different from that in control colonies. Hence there is a the need for a more comprehensive study of the gut microbiome and its effects on Cephalotes ants. In this experiment, I used Cephalotes spinosus, a medium size Cephalotes (worker length 4.80-5.80 mm) that is easily recognized by its golden hairs on an unarmed mesosoma (Figure 2.1.A).
Collection of Cephalotes spinosus colonies and experimental design
I collected a total of nine colonies of C. spinosus at CICRA. I baited for ants by walking haphazardly from 11:00 h to 14:00 h along different trails and spraying most of the tree trunks with a mix of salt, sugar, milk powder, and water. I re-visited the trees 1-3 and 24 hours after baiting. I followed any C. spinosus workers that had recruited to the baits back to their colony and collected as many workers and brood as possible, as well as the queen, when present.
Back at CICRA, I housed the colonies in plastic containers that had internal sidewalls coated with Insect-a-Slip (Fluon, BioQuip) to prevent ants from escaping. I maintained these source colonies until the end of the experiment on a complete diet (see below) and ad libitum water.
After I had collected all the colonies, I formed from each of them eight microcolonies that consisted of ten or eleven workers and five larvae in small plastic containers (Figure
2.1.B). Before starting all the treatments (on the same date for all colonies), I starved all the ants in the experiment during the two days that it took to set up the microcolonies. One of the colonies did not have enough brood for the experiment; hence, I pooled the remaining larvae
12 from all colonies, mixed them, and added five larvae to each of the eight microcolonies. I tested with a single trial microcolony if non-starved ants killed brood from other colonies. The ants showed interest in the new brood after first contact but reared them to adulthood afterwards.
By modifying the diets proposed by Dussutour and Simpson (2008) (see Appendix B for diet contents), I prepared four artificial diets: a complete diet, a complete diet with antibiotics, a diet without amino acids, and a diet without amino acids but with antibiotics.
Diets were poured and allowed to set into sterile 96 well plates with a working volume of approximately 0.3ml per well. I randomly assigned each microcolony to one of eight diet treatments keeping the source colony as a block. The treatments consisted of: 1) a complete diet (ComG-N), with all amino acids present, 2) a complete diet with the antibiotic Gentamicin
(ComG+N), 3) a no amino acids diet (NoaaG-N), 4) a no amino acids diet with Gentamicin
(NoaaG+N), 5) Com with bacteria reintroduced after two weeks (ComG-Y), 6) ComG+ with bacteria reintroduced after two weeks (ComG+Y), 7) Noaa with bacteria reintroduced after two weeks (NoaaG-Y), and 8) NoaaG+ with bacteria reintroduced after two weeks
(NoaaG+Y). Every other day, I fed each microcolony with their respective diet with the contents of one well from the 96 well plates. In addition, I counted dead adults and larvae and
I recorded the number of brood that reached the next step of development (i.e., larva to pupa, pupa to adult). All microcolonies received their respective diets for two weeks. On the 13th day of the experiment, I removed one worker from each colony to dissect its gut (midgut and ileum) and preserved it in 96% ethanol for molecular analyses. To reintroduce live bacteria to treatments 5-8 on the 14th day, I dissected the guts of five workers from the source colonies to maintain the block effect and homogenized them with 250µl of 1x phosphate-buffered saline
(PBS) to reintroduce live bacteria. I added 0.5µl of this mix to microcolonies in the treatments
13
ComG-Y, ComG+Y, NoaaG-Y, and NoaaG+Y and added 0.5µl of 1x PBS to the other treatments. I also repeated this procedure on the 16th day of the experiment. Thereafter, the microcolonies from treatments 5-8 were not fed with antibiotics for the remainder of the experiment. On the 28th day, I dissected the gut of one worker per microcolony and stored it in
96% ethanol for molecular analyses. Additionally, I preserved the remaining workers and brood (whole) in 96% ethanol.
Abundance of gut microbes
During the experiment, I kept a complete duplicate set (i.e., all eight treatments) of microcolonies from one of the biggest source colonies to observe via fluorescence microscopy any drastic changes in gut bacteria, such as presence or absence of bacterial cells. Every eight days, I took one worker from each of these microcolonies, dissected the gut and stained it with
17µl of mounting solution mixed with SYBR green dye.
I also used quantitative polymerase chain reaction (qPCR) to observe changes in the abundance of gut bacteria by quantifying the number of bacterial 16S copies present in each sample. I randomly chose three blocks of source colonies to extract DNA from the guts dissected on 13th and 28th days from all the microcolonies in those blocks. I performed a phenol:chloroform extraction purified with a silica column (DNeasy Blood & Tissue Qiagen
Kit) and further isopropanol purification. I did 1:10 dilutions of all the extractions. To quantify host (i.e., ant) DNA abundance, I prepared each reaction with 0.2µl of 83F and 0.2µl of 187R eF1α primers (83F: CGCTCCACGGTCCATCCCTT; 187F:
TAATCCGGCCGCTGTTGCAT; J.G. Sanders, personal communication), 10µl of Perfecta
SYBR Green FastMix (VWR), 7.6µl of molecular grade water and 2µl of sample.
Additionally, I used samples of Cephalotes rohweri to obtain a standard amplification curve
14 with these primers. The reactions were run in one cycle of 3min at 95°C, followed by 40 cycles of 30sec at 95°C, 1min at 65°C, 30sec at 72°C, and a final cycle of 1min at 95°C, 30sec at 55°C, and 30sec at 95°C. Similarly, for quantification of bacterial DNA abundance, I prepared each reaction with 2µl of 1369F and 2µl of 154R 16S primers (Rogers & Casciotti
2010), 10µl of Perfecta SYBR Green FastMix (VWR), 2µl of molecular grade water and 2µl of sample. I also added Arcobacter nitrofigilis samples to obtain a standard amplification curve with these primers. The thermal profile for the reactions was one cycle of 3min at 95°C, followed by 40 cycles of 30sec at 95°C, 1min at 59°C, 30sec at 72°C, and a final cycle of
1min at 95°C, 30sec at 55°C and 30sec at 95°C. I repeated each reaction twice.
Statistical analysis
I ran parametric survival analyses on adult workers and brood with type of diet (Com or
Noaa), antibiotic (G+ or G-), reintroduction of gut bacteria (Y or N), and their interactions, as well as source colony as fixed factors. All individuals that survived to the end of the experiment were censored in the analysis, as well as individuals taken for gut dissections before the experiment finished. To analyze the bacterial abundance data generated by qPCR, for each sample, I took the mean number of bacterial 16S copies from both reactions and normalized it by dividing it by the mean number of host eF1α copies. I tested for differences in bacterial abundances (square-root transformed) on the 13th day (i.e., before reintroducing bacteria) and on the 28th day of the experiment in an ANOVA model, with source colony as a random factor and diet, reintroduction of gut bacteria, and antibiotic treatments as fixed factors. Finally, I performed a linear regression of the bacterial abundance (square-root transformed) and percentage of surviving adults (logit transformed) in each microcolony. All analyses were performed in JMP 9.
15
Results
Survival of adults and brood
Although adult survival was high in all treatments (Figure 2.2.A), there was nonetheless considerable variation among treatments (X2= 51.32, P< 0.001), mainly driven by the effect of colony and the interaction of antibiotic, diet, and gut bacteria reintroduction treatments (Table
2.1.A). None of these three factors was statistically significant on its own (Table 2.1.A). The lowest adult survival rate was in treatment ComG+N, probably because of the presence of two outliers in the data set, one in colony 2 (three surviving adults) and another in colony 4 (four surviving adults). The highest survival was in treatment ComG+Y. Contrary to what I expected, worker survival did not differ greatly between the complete diet (dead workers = 40,
11% of workers) and the no amino acid diet (Figure 2.3.A-B; dead workers =34, 9.4% of workers, see Table 2.1.A. for full survival analysis results). Conversely, brood survival was very low and most larvae had died by day 10 of the experiment (Figure 2.2.B). Brood survival rates were also significantly different among treatments (X2= 17.28, P= 0.03), with higher survival among larvae that were not fed antibiotics (Figure 2.3.C-D). In general reintroduction of bacteria also had a positive influence on brood survival, but when analyzing its interaction with diet, bacteria reintroduction only had a beneficial effect when the brood was fed on the no amino acids diet (Figure 2.3.C-D; Table 2.1.B). Diet alone had no significant effect on brood survival (Table 2.1.B).
Abundance of gut microbes
Every week during the experiment, I qualitatively observed changes in the gut bacteria in one extra set of microcolonies using florescence microscopy. There were always gut bacteria in the
16 ants that I dissected, even in ants from the microcolonies fed antibiotics, and I never observed any anomalies in tissues inside the gaster (i.e., ovaries, gut, or fat bodies, etc.). Furthermore, I observed after 2-3 weeks an increase in rod-shaped bacteria mostly in treatments with antibiotics but also in treatments with no amino acids, suggesting these treatments may have resulted in changes in bacterial community composition.
On day 13, bacterial 16S copies were more abundant when a complete diet was provided to the ants (Table 2.2.A, Figure 2.4). In fact, diet was the only factor that significantly affected the number of bacterial cells in the samples from the 13th day of the experiment, i.e., the day before the reintroduction of bacteria (Table 2.2.A). Antibiotic addition showed a non-significant increase of bacterial cells only in the complete diet treatment. In contrast, the samples from the 28th day showed a significant difference in the number of 16S copies not only due to diet type but also due to antibiotic treatment; there were more bacterial cells in ants fed the complete than the no amino acids diet and there were also more bacterial cells in ants fed diets with antibiotics (Figure 2.4). The effect of gut reintroduction on bacterial abundance depended on diet and antibiotic treatment (Table 2.2.B).
For instance, the abundance of bacterial cells did not change significantly with gut reintroduction in the no amino acids diet but drastically increased when gut reintroduction was coupled with the complete diet in the absence of antibiotics (Figure 2.4.C). Broadly, reintroduction of gut bacteria on its own tended to increase the abundance of 16S copies in the samples, but this effect was not significant in the model (Table 2.2). The interaction between the reintroduction of gut bacteria and the antibiotic treatment also had a weak effect on bacterial abundance. The abundance increased about 77% after reintroduction of bacteria in the absence of antibiotics but only 12% when the antibiotic was present (Figure 2.4.C-D). The interaction of diet, antibiotics, and gut reintroduction was not significant in the model.
17
Nevertheless, I found an interesting pattern when analyzing differences among the means
(Figure 2.4). Typically, reintroduction of bacteria increased the number of 16S copies as expected but in the non amino acid diet with antibiotics added (NoaaG+Y) the number of copies decreased by 67% compared to the same diet with antibiotics but without gut reintroduction (NoaaG+N). Perhaps a bigger sample size would have revealed a significant pattern. Finally, bacterial abundance was positively related to the proportion of adults that survived the experiment (Figure 2.5).
Discussion
On interactions between ant survival and bacterial abundance
Do gut bacteria affect C. spinosus fitness? The results of this study show that, in general, bacterial abundance and adult survival are positively associated (Figure 2.5), which suggests they do. The fact that adult workers and brood survived similarly on both diets implies that C. spinosus is not strongly affected by the absence of amino acids in its diet, at least over the timescale of this study. Does this mean that C. spinosus depends on beneficial gut bacteria to recycle or fix nitrogen, thereby allowing them to persist on amino acid-poor diets?
Diet, gut reintroduction, and antibiotics had significant effects on adult survival only as a three-way interaction effect (Table 2.1.A.). In the absence of antibiotics, bacterial abundance always decreased when the ants were fed with the no amino acids diet and then increased with the reintroduction of bacteria from nestmate guts. However, when antibiotics were present, bacterial abundance seemed to increase only slightly with the reintroduction of bacteria when the ants were fed with a complete diet and decreased if the ants were fed a no amino acids diet.
To fully understand this pattern, it might be relevant to determine in future studies the long- term effects of antibiotics, since there was an increase of bacterial abundance in the no
18 antibiotic treatments relative to the bacterial abundance in the antibiotic treatments after bacteria reintroduction, which suggests that persistent effects of antibiotics can be present in the system. In general, the proportion of adults surviving was lower when bacterial abundance was low, implying that the disturbance of bacterial assemblages may have an influence on ant mortality (Figures 2.3 and 2.4).
Although these results may indicate that gut bacteria had a positive effect on the performance of C. spinosus microcolonies, they need to be interpreted carefully. Firstly, worker survival was very high, usually not less than 80%, in all treatments. Even though there is a possibility that the statistical tests did not have enough power (sample size of 9), the most likely explanation is that I did not impose the treatments long enough; hence, if there were any changes in bacterial assemblages, these may not have had enough time to substantially improve or harm the condition of workers, which are generally long-lived and resilient.
Therefore, I expect that I might have found more pronounced patterns if I had run this experiment for longer. This high survival contradicts the results of a previous study by Jaffe et al. (2001) in which 100% of C. pusillus and C. atratus workers died in their microcolonies after seven days of treatment with Gentamicin and other antibiotics. They argued that ants died of desiccation because they did not eat food that contained the antibiotics. However, in the present study, C. spinosus ants ate the artificial food whether or not the diet contained
Gentamicin; possibly, because I used a different antibiotic concentration or because I mixed the antibiotics directly in the diet.
Another influential factor for the high survival of adult workers across all treatments is the presence of brood in the microcolonies because larvae and pupae could be an extra source of protein (see discussion in Appendix A). Brood survival was very low (Figure 2.2). Brood died more often when treated with antibiotics but it is hard to determine whether it was related
19 to direct antibiotic toxicity or changes in bacterial assemblages. Although the antibiotics did not seem to affect adult survival, larvae and pupae are smaller and the same concentration of antibiotics could be lethal to brood but non-lethal to adults. However, 17% of brood survived to the end of the experiment across all treatments, with at least two out of three larvae developing into workers during the experiment in the antibiotic treatments, making it unlikely that antibiotic toxicity was the reason for high mortality. Similarly, Wilkinson (1998) showed in the aphid Acyrthosiphon pisum that antibiotic treatment did not produce lethal effects if the insects were provided with the right antibiotic dose. On the other hand, changes in bacterial assemblages could be responsible for brood survival rates. Even though most pupae and larvae died during the first two to eight days of the experiment, this high mortality rate could be, in part, explained by rapid shifts in bacterial assemblages. For example, the antibiotic treatment had a negative effect on brood survival and the brood that survived showed an increase in survival rates with reintroduction of bacteria; results I expected if bacterial assemblages play a role in nutrition and disease protection. This different response in survival rates of adults and brood could be explained by the findings of Russell et al. (2009), who showed that the most common bacteria taxa found in adults are not as common in earlier developmental stages of ants, implying that different sets of microbes inhabit the brood gut. Furthermore, a study of the carpenter ant Camponotus floridanus found that the beneficial bacteria Blochmannia could have a fundamental role in brood metabolism (Zientz et al. 2006). Because of high brood mortality we did not test for changes in bacterial abundance in their gut, which makes it difficult to test relationships between the gut microbiome of brood and workers and for bacterial assemblage stability trough horizontal transmission. Overall, these data suggest that gut bacterial assemblages might provide different benefits to brood and adults, having a bigger impact on the former.
20
Although unexpected, there was a high rate of cannibalism on brood at the beginning of the experiment. It is possible that brood died from treatment effects before workers consumed them or maybe brood can be a regular nutritional source when food is scarce. Since cannibalism was only observed at the beginning of the experiment and in all treatments, I propose it was a product of the starvation period right before the start of the experiment and stress on ant workers that had been removed from the source colonies (Sorensen et al. 1983).
Cannibalism was not observed after the first week suggesting that ant workers did not use pupae as an alternative protein source. Regardless of the reason for cannibalism, once brood is consumed workers can benefit from their nutrients and obtain their gut bacteria, which can lead to an increase in worker survival rates in treatments where amino acids were not provided
(see Appendix A) and also increase the bacterial presence in the guts of workers.
Survival rates varied substantially and significantly among colonies, which might be related to environmental factors from the sites where I collected the colonies or the life history of the colony. Usually, life stage has a big impact on how a colony responds to different treatments. A young colony might have more strict dietary requirements than an older colony and perhaps require more protein to promote brood development. Similarly, a colony in the reproductive stage may need more protein than colonies that are not producing reproductives
(Dussutour & Simpson 2009). Furthermore, a colony could have been sick before entering the experiment. These differences in colonies can also help to explain why Jaffe et al. (2001) found different rates of mortality when the Cephalotes microcolonies were treated with different types of antibiotics. Consequently, I argue that the microcolony approach, when it allows the blocking of all treatments by colony, minimizes the variability that comes from intrinsic differences among colonies, thereby providing more robust results.
21
On mechanisms for change in bacterial abundance
Independent of ant performance, this experiment demonstrates that microbial assemblages in the gut of C.spinosus can be disrupted by providing antibiotics, withholding nutrients, or to a lesser extent, by reintroducing bacteria. Antibiotics are commonly used to create aposymbiotic organisms (in this case, individuals that do not host symbiotic bacteria). There have been many cases in which bacteria have successfully been removed from insects with antibiotics.
For instance, Ben-Yosef et al. (2010) eliminated bacteria with antibiotics from the anterior section of the digestive tract of olive flies, Broderick et al. (2009) found fewer gut bacteria in lepidopteran larvae reared on artificial diet with antibiotics, and Zientz et al. (2006) reduced symbiotic bacteria in carpenter ants with the antibiotic Rifampin. Given the results of these previous studies, it was surprising when in most treatments I did not observe through the fluorescent microscope that antibiotics eliminated bacteria in dissected guts. I confirmed these observations with the qPCR assays, in which I found an increase in the mean number of bacteria when antibiotics were added. However, this outcome is not necessarily unexpected.
First, Gentamicin targets mostly Gram-negative bacteria (e.g., Rhizobiales) (Moulds &
Melanie 2010). Second, antibiotic resistance is a recurrent problem in human health (Moulds
& Melanie 2010) and it has also been confirmed in insects that act as bacterial reservoirs
(Allen et al. 2009). In both cases, other types of surviving bacteria (e.g., Gram-positive or resistant bacteria, pathogenic or not) could thrive in the absence of their competitors, potentially increasing in number, especially when nutrients are abundant.
Accordingly, the population size of bacteria decreased when nutrients, such as amino acids, were withheld. Overall, diet had the strongest effect on how many bacteria I found in the ant guts. When amino acids were not added to the artificial diet, bacterial abundance decreased about 40%, suggesting that amino acid limitation can structure gut bacterial
22 assemblages. Feldhaar et al. (2007) also found similar results, demonstrating reduction of symbiotic Blochmannia when feeding carpenter ants with artificial diets lacking nitrogen.
Nutrient limitation has been suggested in recent studies to be an important factor shaping the composition and density of gut microbes in other insects (Ben-Yosef et al. 2010, Pinto-Tomás et al. 2011). If this is the case, when nitrogen is limiting in the host diet, I expect that only bacteria that can fix or recycle nitrogen will survive. Given the evidence in this study that nitrogen is an important factor, I predict that in the gut of C. spinosus most bacteria are nitrogen limited and only a small proportion of them can recycle the host’s waste products or the nitrogen in dead bacterial cells. There might also be some nitrogen-fixing bacteria, which have been thought to be common symbionts of Cephalotes ants (Russell et al. 2009).
These results shed light on the mechanisms of community assembly in the C. spinosus gut. Fukami et al. (2010) found that the assembly process in communities of fungi that decompose wood greatly depends on who colonizes the wood first, i.e., on assembly history.
In the case of C. spinosus gut bacteria, I do not have information on the composition of bacteria present in the samples. However, competition for nutrients appears to be one important mechanism that shapes the C. spinosus gut microbiome and what type of bacteria is originally in the gut seems also to be a relevant factor. This is further confirmed with what I observed after reintroducing bacteria from the guts of nestmates. Reintroduction of bacteria increased bacterial abundance, but less so in ants that did not have access to nitrogen sources; this is to be expected if bacteria compete for nutritional resources. However in the presence of antibiotics, the reintroduction not only did not greatly affect the number of bacteria when ants were fed a complete diet but also decreased the bacterial abundance when ants were fed a diet without amino acids. With the caveat that some of these effects were non-significant in the model, I propose then that if the antibiotics mostly eliminated bacteria that were better at
23 surviving in environments with low nitrogen resources (e.g., Gram-negative bacteria such as
Rhizobiales), the original residents before the reintroduction (i.e., the bacteria that survived the antibiotic treatment) would be weak competitors in an environment that is nitrogen limited and any further depletion of this nutrient will mean high mortality of bacteria. Hence, after the arrival of new bacteria, antagonistic interactions should be strong and the availability of nitrogen should decrease, diminishing bacterial population size.
In conclusion, this study provides evidence that antagonistic interactions influence the assembly of the gut microbiome in a tropical arboreal ant and further emphasizes the impact of diet on bacterial assemblages—competition among bacteria for nutrients may be intense. The resulting bacterial abundance after competition seems to influence ant survival, having bigger effects on brood. Ultimately, whether the surviving bacteria are mostly pathogenic or mutualistic should impact host condition. Future work might use reintroduction of bacteria as a way to simulate trophallaxis in eusocial insects. This method can help us understand whether feeding interactions among nestmates contribute to the stability of bacterial assemblages and facilitate the exclusion of unwanted bacteria in ant colonies.
24
Figures and Tables
Figure 2.1. A) A Cephalotes spinosus worker. Photo © J. Sanders. B) Ten workers and five larvae lived in small plastic containers for four weeks. Disposable pipettes were cut in half; one half was used to store water and the other half simulated a nest chamber. The red tent provided darkness to the workers.
25
Figure 2.2. Survival plot for Cephalotes spinosus A) adult workers and B) brood
26
Figure 2.3. Interaction effects of diet (‘Com’ refers to a complete diet and ‘Noaa’ to a no amino acid diet), gut bacteria reintroduction (‘N’ for no reintroduction, and ‘Y’ for introduction) and presence of antibiotics on the proportion of adults (A and B) and brood (C and D) surviving to the last day of the experiment.
27
Figure 2.4. Effects of diet, antibiotics, reintroduction of guts and their interactions on number of bacterial 16S copies on the 13th day of the experiment (A and B; note that reintroduction of bacteria had not taken place at this point, hence the division of treatments Y and N is artificial) and on the last day of the experiment (C and D). ‘Com’ refers to a complete diet and ‘Noaa’ to a no amino acids diet. ‘Y’ codes for treatments that received guts on day 14 and ‘N’ codes for treatments that did not.
28
Figure 2.5. Relationship between the number of 16S copies (square-root transformed) and the proportion of surviving adults (logit transformed) on day 28 of the experiment (r2= 0.22, P =
0.02).
29
Table 2.1. Parametric survival analysis of (A) adults and (B) brood.
A.
Source df X2 P-Value
Colony 8 33.5504469 <.0001*
Diet 1 0.0797122 0.7777
Antibiotics 1 0.14351083 0.7048
Bacteria 1 2.91541681 0.0877
Diet*Bacteria 1 2.63580439 0.1045
Antibiotics*Bacteria 1 0.25367236 0.6145
Antibiotics*Diet 1 0.99461685 0.3186
Antibiotics*Diet*Bacteria 1 12.9560409 0.0003*
B.
Source df X2 P-Value
Colony 8 111.620309 <.0001*
Diet 1 1.02431256 0.3115
Antibiotics 1 6.58588173 0.0103*
Bacteria 1 6.12460272 0.0133*
Diet*Bacteria 1 4.19511257 0.0405*
Antibiotics*Bacteria 1 3.19529274 0.0739
Antibiotics*Diet 1 0.48347508 0.4869
Antibiotics*Diet*Bacteria 1 0.49199349 0.4830
30
Table 2.2. Mixed model ANOVA results showing the factors affecting the number of bacterial
16S copies found in the guts of C. spinosus workers on day 13 (A) and day 28 (B).
A.
Source df dfDen F Ratio P-Value
Diet 1 14 24.8493 0.0002*
Antibiotics 1 14 0.4412 0.5174
Bacteria 1 14 0.2265 0.6415
Diet*Bacteria 1 14 0.0020 0.9652
Antibiotics*Bacteria 1 14 0.0641 0.8038
Antibiotics*Diet 1 14 0.7142 0.4123
Antibiotics*Diet*Bacteria 1 14 0.0483 0.8293
B.
Source df dfDen F Ratio P-Value
Diet 1 13.78 38.2410 <.0001*
Antibiotics 1 13.78 5.1813 0.0393*
Bacteria 1 13.78 2.7771 0.1182
Diet*Bacteria 1 13.78 4.5523 0.0514
Antibiotics*Bacteria 1 13.78 7.3067 0.0173*
Antibiotics*Diet 1 13.78 1.4623 0.2469
Antibiotics*Diet*Bacteria 1 13.78 0.1733 0.6836
31
CHAPTER THREE
The macronutrient requirements of a tropical arboreal ant and its effects on the ant
microbiome
Abstract
Only in the tropics do arboreal ants depend on myrmecophytic plants for both food and shelter; in return, these ants defend their host plants against herbivores, which are often insects. Because the food offered by ant-plants is usually nitrogen-poor, arboreal ants may supplement their diets with insect prey or associate with microbial symbionts that provision their hosts with essential amino acids. I investigated the contribution of insect prey to the diet of the tropical arboreal ant Allomerus octoarticulatus and a possible compensatory response of the microbiome. After A. octoarticulatus colonies nesting in Cordia nodosa trees had been maintained in herbivore exclosures and control treatments for nearly a year, I compared the behaviour, morphology, fitness, and gaster microbiome of ants in the two treatments. At the end of the experiment, I compared ant recruitment to protein-rich versus carbohydrate-rich baits in a behavioral assay. I found that ants that developed in herbivore exclosures had a stronger preference for protein-rich over carbohydrate-rich baits than ants in the control (i.e., herbivores present) treatment. Furthermore, workers in the control treatment were slightly larger and significantly heavier than in the herbivore exclosure treatment, but ant colony growth did not differ significantly between treatments. Microbial assemblages in the gaster of ants were also not affected by herbivore treatment. This is the first time that a manipulative experiment has been used to describe the microbiome of ants in an ant-plant mutualism, providing insights into what factors might influence microbiome assembly.
32
Introduction
Species interactions define natural systems and have long been recognized as biological processes essential for understanding animal behaviour and ultimately community assembly
(Valdovinos et al. 2010). Traditionally, research on mutualisms has focused on two interacting species and how they reciprocate the benefits provided by the partner (Montoya et al. 2006).
But a plant and its pollinator, for example, are not closed systems; they coexist in the same habitat with many other species. More generally, the study of ecological networks has revealed the importance not only of the identity of the species that are interacting but also of when, where, and how strongly these species interact (Olff et al. 2009). What this means is that costs and benefits of interactions can change depending on how the partners interact with other species that live or forage nearby (Bascompte 2009). Thus, changes in relationships with external players can have important consequences for pairwise interactions. For example, in an ant-plant mutualism, both members, the ant and the host plant, have different types of interactions with several species of herbivores that can affect the maintenance of the mutualism (Palmer et al. 2008). Because herbivores can have a large negative impact on plant growth and overall fitness, plants invest more in ant rewards if the benefits of hosting ants reduces herbivory, but how much plants invest might vary depending on the abundance of herbivores (Bronstein 1998; Frederickson 2009; Palmer et al. 2008; Frederickson et al. 2012).
Additionally, the presence or absence of third parties, such as herbivores, can also have big effects on community composition; as Clay et al. (2005) showed in their study of tall fescue grass and the vertically transmitted fungus Neotyphodium coenophialum, herbivores can decrease the occurrence of the symbiotic fungus, which in turn has a great impact on how well these plants compete in their habitat. The effect of herbivores is further intensified because
33 herbivores selectively consume other species of plants that do not have the symbiotic relationship with the fungus, thereby modifying the plant community.
Here, I studied an ant-plant system and some of its interactions with other members of its community. In ant-plant symbioses, ants defend their host plant against herbivores and the plant reciprocates this benefit by providing food in the form of food bodies or extrafloral nectar. However, plant-based food is usually rich in sugars but lacks many other nutrients, especially essential amino acids (Hölldobler & Wilson 1990; Davidson et al. 2003; Dejean et al. 2005; but see Heil et al. 2004 for a discussion of the protein content of food bodies).
Hence, ants should have other mechanisms to deal with unbalanced diets if their host plants are not able to provide the full suite of essential nutrients used by the colony (Heil & Mckey
2003; Raubenheimer & Simpson 1999). Insect herbivores that forage on the host plant could be the main source of protein for arboreal ants but there have also been reports of ants feeding on bird droppings and mammalian urine; additionally, it has been suggested that some ants forage for pollen or fungal spores on leaves (De Andrade & Baroni-Urbani 1999; Jaffe et al.
2001; Yanoviak et al. 2008; Kaspari et al. 2009). Finally, many arboreal ants tend and consume honeydew from Hemiptera that feed on plant sap. The gut microbes of these sap- sucking insects can upgrade nutrients, potentially making the honeydew a good quality food source for ants (Stadler & Dixon 2005).
The benefits to plants of associating with ants that protect vegetative tissues against herbivores are well studied, but the benefits to ants are less well understood (Bronstein 1998).
For instance, plant defence might or might not be costly for ants. If ants are actively foraging for insects, then they provide a benefit to the plant as a by-product of foraging without any extra cost to themselves (Frederickson et al. 2012). On the other hand, if the ants do not
34 consume the herbivores, as is the case of some Pseudomyrmex ants defending Acacia trees
(Janzen 1966), they should depend entirely on their host plant for nutrition, and plant defence may be costly for them. In addition, these ants still need a way to compensate for the lack of essential nutrients in their plant-derived diet. Thus, they might prey on mutualistic Hemiptera, engage in cannibalism, or maybe rely on fungal or microbial symbionts.
Microbial symbionts might affect the outcome of ant-plant mutualisms. For more than a century, microbes have been known to upgrade nutrients for their arthropod hosts (Steinhaus
1940). Many of these microbes reside in the guts of insects that have unbalanced diets, usually plant-derived, such as in termites that feed on wood or Hemipterans that feed on plant sap (see
Clark et al. 2010 for a review). These symbionts can have tight relationships with their hosts and in some cases have coevolved with them (Moran 2001). If ants acquire an adequate microbiome comprising bacteria that are capable of nitrogen fixation or vitamin synthesis, they might survive feeding only on the restricted diet of extrafloral nectar or food bodies that plants can provide, thereby reducing the costs of the interaction (Janson et al. 2008). If so, I would expect that in the absence of herbivores the ant microbiome will not change drastically.
On the other hand, if bacteria depend on ant consumption of insect herbivores for their own metabolic needs (see Chapter One), I might see a shift in their bacterial assemblage favouring bacteria that can survive in a low-nutrient environment.
For this experiment, I studied the arboreal ant Allomerus octoarticulatus and explored how its interactions with insect herbivores and symbiotic microbes can affect the mutualism it has with the ant-plant Cordia nodosa. More specifically, I investigated whether an experimentally induced shift in diet (i.e., the presence or absence of insect prey) changed 1) the fitness of A. octoarticulatus and 2) the assemblage of the ants’ gaster microbiome. I also discuss how the
35 interaction among plants, ants, insect prey, gaster microbes, and scale insects might affect the final outcome of the ant-plant mutualism.
Methods
Study site and system
I carried out this study at the Centro de Investigación y Capacitación Río Los Amigos
(CICRA) in the Peruvian Amazon (380500E, 8610297N, elevation 230-270m). CICRA is located in Madre de Dios and is flanked by the Madre de Dios and Los Amigos rivers (Pitman
2008). The station extends over three different habitats: upland forests, floodplain forests, and swamps. Mean monthly temperature at the station varies from 21°C to 26°C and annual rainfall ranges from 2,700 to 3,000 mm (Pitman 2008).
Cordia nodosa (Boraginaceae) is an ant-plant that is abundant at CICRA. One of its main features is distinctive domatia: hollow, swollen stems that serve as shelter for ants
(Figure 3.1.A). In addition to shelter, C. nodosa provides nutritional rewards to the ants that inhabit it in the form of miniscule food bodies on the surfaces of young leaves (Figure 3.1.B).
It has been shown that the cost of producing domatia and food bodies is outweighed by the benefits of hosting ants that protect plants against herbivores (Oliveira et al. 1999,
Frederickson 2005). Several species of ants, including Myrmelachista schumanni, three species in the genus Azteca, and Allomerus octoarticulatus associate with C. nodosa
(Frederickson 2005). In this study, I focused on the obligate ant symbiont Allomerus octoarticulatus (Myrmicinae) (Figure 3.1C). With few exceptions, only one colony of A. octoarticulatus lives in an individual C. nodosa plant at a time. Workers actively defend the leaves of their host plant. They also damage the reproductive structures of C. nodosa to
36 promote vegetative growth, thus increasing the production of nest space and food bodies for ants (Frederickson 2009).
Experimental manipulation of insect herbivores/prey
For this study, I took advantage of a field experiment that had been set up to investigate defensive trade-offs and the costs of the interaction between A. octoarticulatus and C. nodosa
(Frederickson et al. 2012). This experiment crossed treatments in which C. nodosa saplings were grown with and without most insect herbivores (representing potential prey to A. octoarticulatus) and with and without ants, in a full factorial manner. Here, I refer to the treatments as: A+H+ (ants added, herbivores allowed), A+H- (ants added, herbivores excluded), A-H+ (ants excluded, herbivores allowed), and A-H- (ants and herbivores excluded). The C. nodosa saplings used in the experiment were grown from wild-collected seeds in outdoor cages until they had domatia. In the summer of 2009, 52 saplings were transplanted in blocks of four to 13 2 m x 2 m plots in the rainforest understory and then assigned at random to treatments. Twenty-six ant colonies were collected from other naturally occurring C. nodosa plants at the same site; the number of workers in each colony was counted; and the colonies were transferred to plants in the A+ treatments. Insect herbivores were manipulated using mosquito nets, which were hung over all of the saplings. We did not attempt to characterize the insect herbivore assemblage in our experiment due to the high taxonomic complexity and abundance of these insects in the Neotropics. To exclude herbivores, the nets were staked securely to the ground; in the H+ treatments, the nets were raised 30 cm off the ground.
I focused on the ants in the A+H+ and A+H- treatments. Frederickson et al. (2012) showed that the herbivore exclusion treatments were successful. Therefore, ant colonies in the
37
H- treatment were prevented from foraging for insect prey on plant surfaces, while ant colonies in the H+ treatment had access to insect prey as a potential source of food, especially protein.
Ant diet
Plants and ant colonies spent 314-329 days in the experiment. In June 2010, I measured the recruitment of A. octoarticulatus workers to two bait types with either 3:1 or 1:3 ratios of protein (whey protein powder from Interactive Nutrition, Inc.) to carbohydrates (table sugar)
(modified from Dussutour & Simpson 2008). I poured the diets into 1.5ml centrifuge tubes, which I attached with wire to a randomly chosen domatium. Both baits were present on the same tree at the same time but on different domatia. After five hours, I recorded the number of ants at these baits. I expected ant colonies in the H- treatment to be protein-starved and thus to show a stronger preference for the high-protein baits than ant colonies in the H+ treatment.
At the end of the experiment, I collected and froze all the ants. I analyzed the ratios of stable isotopes of carbon (δ13C) and nitrogen (δ15N) to investigate the trophic level of each colony (Bluthgen et al. 2003); specifically, I wanted to determine whether the ant colonies in the H- treatment had mostly plant-based diets and therefore lower δ15N values. I took a random sample of 20 ants per colony, removed their gasters, and dried and weighed them. I also did a second analysis using five whole ants per colony. Measurements on individual ants were not possible due to their small masses. I compared the stable isotope ratios of ants in this experiment to those of naturally occurring plants, ants, insect herbivores, and predatory spiders. I sent samples to the UC Davis Stable Isotopes Facility for analysis.
Colony performance
38
To assess colony performance, I first counted all the adult ants present on branches, leaves, and inside domatia of the host trees to determine ant colony size. Second, I measured eight morphological characters (head length, head width, scape length, mandible length, mesosoma length, mesosoma width, petiole and postpetiole length, and gaster length) (Figure 3.2) on 20 ants per colony, following Fernández (2007). I then measured the dry weights of five workers per colony. Finally, to determine if worker mass is related to ant colony fitness, I collected eight wild colonies of A. octoarticulatus, counted the number of workers and reproductives
(i.e., alate males and females, as well as reproductive pupae and larvae), and preserved the colonies in 96% ethanol. Back at the lab, I dried and weighed 20 workers per colony.
Gaster microbiome
I investigated the microbiome of ant gasters from this experiment by sequencing bacterial 16S genes. I surface sterilized 20 workers per colony with a 10% bleach solution for 15 seconds and rinsed them with phosphate-buffered saline (PBS) solution for 30 seconds before removing the gasters. I removed the 20 gasters with tweezers and I pooled all of them in one sample to perform a phenol:chloroform DNA extraction. I purified the DNA extractions with a silica column (DNeasy Blood & Tissue Qiagen Kit) and isopropanol precipitation. I sent the resulting extracted DNA for microbial diversity analysis to the Research and Testing
Laboratory in Lubbock, Texas for bacterial tag-encoded FLX pyrosequencing (bTEFAP) using the primers Gray28F (5’ TTTGATCNTGGCTCAG) and Gray519r (5’
GTNTTACNGCGGCKGCTG). The sequencing library was generated by one-step PCR with
30 cycles and the bTEFAP was performed on a Roche 454 FLX instrument (Dowd et al.
2008).
39
Statistical analysis
I omitted three blocks (E, G, and J) of the initial thirteen because at least one ant colony did not survive to the end of the experiment. I included block as a random factor when necessary while fitting the statistical models. I square-root transformed all count data and log- transformed all weight data to improve normality. To analyze the recruitment of ant workers to protein-rich baits, I used an ANCOVA model with block as a random factor, herbivore treatment as a fixed factor, and recruitment of ant workers to carbohydrate-rich baits as a covariate, thereby incorporating colony activity levels into the model (blocks A and K were outliers). I compared the carbon and nitrogen stable isotope ratios between herbivore treatments for each of the data sets obtained (i.e. whole ants and heads and thoraces) in
MANOVA models.
I ran a principal component analysis on the morphological character data to examine treatment differences. The first principal component explained 63% of the variation in the data, so I used PC1 to compare worker size between treatments in an ANOVA. I also analyzed the worker weight and colony growth data in ANOVAs. Two colonies in one of the blocks were outliers in all the analyses; therefore, I excluded this block (block A). To determine if worker weight was correlated with the number of reproductives, I performed a linear regression on colony size and number of alates per colony. I used the residuals of that regression to compute a second linear regression of worker weight on the number of alates.
For the molecular analyses, I included the ants in the H- treatment in block J; the addition of this block did not change any of the patterns found in the analyses. It was not possible to amplify the samples from the H+ treatment in block I, thus I excluded this sample.
I used AmpliconNoise to denoise the pyrosequencing data, thereby removing most of the amplification errors and chimeras from the dataset (Quince et al. 2009). Afterwards, using the
40
Qiime platform (Caporaso et al. 2010), I aligned and clustered the sequences and compared this alignment with the RDP database in a pairwise fashion to produce a denoised OTU table. I omitted all OTUs that had fewer than two reads per sample to exclude rare bacteria that may have been contaminants. I computed a single rarefaction at a depth of 600 reads to account for the differences in the number of reads in each sample; blocks I, H, and one sample from D were excluded with this procedure because of a low number of reads. On this new OTU- rarefaction table, I analyzed alpha diversity with rarefaction plots using the Phylogenetic
Diversity (PD) Whole Tree matrix and I examined beta diversity in a principal coordinates analysis (PCoA). To perform the PCoA, I created a distance matrix using the unweighted
UniFrac algorithm. This algorithm uses the branch lengths in a phylogenetic tree generated with the sample sequences to test for the fraction of total branch length that is unique to one environment. I also used the weighted UniFrac algorithm that uses the same principles of unweighted UniFrac but weights the branches by the taxon abundance (Lozupone et al. 2007).
I used the function Adonis in R to analyze the variance of the bacterial assemblages resulting from treatment and block effects. To analyze the effect of variables other than treatment (i.e., number of scale insects, colony size, worker weight, stable isotope ratios, plant performance, and final number of leaves), I ran a Constrained Correspondence Analysis (CCA) and selected the best model with the Akaike Information Criterion (AIC). Statistical models were calculated in JMP 9.0.0 and R 2.14.0.
Results
Diet and colony performance
Ants in the H- treatment recruited more to protein-rich baits than ants in the H+ treatment
(Figure 3.3). Ants from block A were excluded from this analysis because they were outliers,
41 but even in this block ants in the H- treatment also recruited more often to protein rich diets while ants in the H+ treatment did not show any preference for either bait. In contrast, ants from block K, another outlier, did not recruit to either bait (Figure 3.3; ANCOVA model results: number of ants at C-rich baits: F1,15 = 12.412, P = 0.003; herbivore treatment effect,
F1,7 = 8.249, P = 0.024).
Stable isotope ratios were significantly different between treatments in the MANOVA analysis (Table 3.1). Ants that developed in the presence of insect herbivores had a slightly higher δ13C: δ15N ratio than ants that developed without the insect herbivores. This difference was mostly due to δ13C measurements (Figure 3.4). However, when I analyzed the data from whole ants independently, it did not show any statistically significant difference in stable isotopes ratios between treatments (Table 3.1). When comparing carbon and nitrogen stable isotopes ratios, I found that δ15N was enriched compared to the reference levels found in the natural habitat, while δ13C values of ants in the experiment were closer to those of naturally occurring ants and herbivores.
Ants that developed in the presence of insect prey were significantly heavier (F1,18=
8.200, P= 0.021) (Figure 3.5.A). They also tended to be bigger, although this pattern was not statistically significant (PC1, F1,18= 2.331, P= 0.165) (Figure 3.5.B). Similarly, colony growth was greater in the H+ than H- treatment, but this difference was not statistically significant
(F1,18 = 0.991, P = 0.161) (Figure 3.6). Therefore, total biomass was higher in colonies that had access to insect prey. Finally, I found that the weight of worker ants in naturally occurring colonies explaining about 22% of the variance in the number of adult reproductives; this means that the number of adult reproductives increased with weight of worker ants (F1,7=
7.7374, P= 0.032) (Figure 3.7).
42
Gaster microbiome
After denoising the microbial sequences with AmpliconNoise, the total number of reads per sample was reduced on average by about 40%. Subsequent analyses with the denoised OTUs showed that microbiome alpha diversity was not significantly different between treatments, which had on average the same phylogenetic diversity (Figure 3.8). In general, the bacterial assemblage was dominated by Firmicutes (38.9%), Proteobacteria (18.4%), Bacteriodes
(12.5%), and Actinobacteria (9.7%) (Figure 3.9) (see Appendix C for a complete list of bacteria found in the samples). Unexpectedly, Fusobacteria were abundant in one ant colony
(H-, block J); these bacteria, which are often pathogenic, accounted for 84.5% of the bacteria in that sample.
Analysis of beta diversity through PCoA did not show any differences between treatments in the microbial assemblages in the gasters of ants (Figure 3.10). The first three principal coordinates explained about 41% of the variation in the data with unweighted
UniFrac and 72% with weighted Unifrac. In both cases, bacterial assemblages from blocks K,
L, and F tended to cluster together. The bacterial assemblage from block J was always separated from everything else. The Adonis test confirmed that there were no shifts in bacterial assemblages between treatments but it suggested that environmental factors in different blocks might have influenced the structure of these assemblages (Table 3.2).
However, the AIC showed that none of the variables measured predicted changes in the bacterial assemblages (Table 3.3).
Discussion
Allomerus octoarticulatus diet
43
Although A. octoarticulatus colonies can survive in the absence of insect prey, my results suggest that insects do contribute to colony nutrition and fitness. After a year in mesh nets that excluded most potential animal prey, workers in the H- treatment recruited to protein-rich baits more often than their H+ counterparts (Figure 3.3). This result is consistent with current theories of insect nutrition, especially the geometric approach of Raubenheimer and Simpson
(1999). They suggest that insects should always try to balance their diet when some nutrients required for development and survival are scarce in the environment. Thus, insects should forage so as to maximize the probability of reaching an optimal concentration of the required nutrient. Allomerus octoarticulatus workers foraged more for protein when insect prey were absent. This suggests that A. octoarticulatus actively seeks insect herbivores as a food source, which is supported by observations that a closely related ant, Allomerus decemarticulatus, builds traps with fungi and plant debris to capture insects (Dejean et al. 2005); I observed similar carton-like structures built by A. octoarticulatus during this experiment.
I expected that the experimental manipulation of insect prey would result in lower δ15N values for workers in the H- than the H+ treatment, because these workers should have been more dependent on plant-derived foods and therefore feeding at a lower trophic level.
However, the stable isotope data showed that the experimental treatment had a significant effect on δ13Cvalues, but only a marginally significant effect on δ15N values. This pattern might be explained if workers from both treatments are eating similar amounts of protein but the sources of this nutrient are different. Since insect herbivores feed on a broad range of plants in the tropics, ants that had access to insect herbivores could have a more diverse 13C signature. Meanwhile, ant colonies in the herbivore exclosures could consume only food bodies from their host plant, honeydew from their scale insects, or the scale insects themselves. However, this does not seem to be the case for the Allomerus-Cordia system
44 because the range of variation in δ13C was similar in both treatments. Another scenario is that ant workers in the absence of insect prey are eating a higher proportion of plant-derived food, for example food bodies and honeydew, which can have different δ13C signatures (Feldhaar et al. 2010). Furthermore, the host plant might be able to vary the nutritional content of food bodies depending on how much the plant is being attacked by insect herbivores, providing high-quality rewards when insects are present (e.g. Sagers et al. 2000; Heil et al. 2004).
Lastly, ants might be able to balance their carbohydrate to nitrogen intake very precisely, hence ants that do not have access to insect prey might consume less protein which makes them smaller but the total amount of 15N relative to 14N that is incorporated in the ants tissues might not be different to that of ants in the presence of insect herbivores. Whether these colonies are cannibalistic and are gaining protein from other colony members remains uncertain.
Surprisingly, all of the ants in the experiment were substantially 15N-enriched compared to workers from naturally occurring A. octoarticulatus colonies from both the same site (Figure 3.4) and a nearby site (Davidson et al. 2003). It is hard to imagine how the experimental manipulation could have produced such a marked shift in δ15N, but this enrichment does not invalidate the differences I found in isotope ratios between the experimental treatments. Feldhaar et al. (2010) showed that the presence of gut contents in samples can easily confound the interpretation of stable isotope ratios because the samples include food (e.g., insect, plant, or fungal tissues, nectar, etc.) that the ants consumed immediately before collection, but which do not necessarily reflect the food the ants have consumed most of their lives. For this reason, we quantified stable isotope ratios for both heads and thoraces only as well as for whole ants; the latter analysis was intended to facilitate direct comparisons with our unpublished reference values (Figure 3.4) and published values
45
(Davidson et al. 2003), both of which used whole ants. The presence of gut contents likely explains the differences I observed in stable isotope ratios between whole ants and ants from which gasters had been removed (Table 3.1). However, both sets of samples from this experiment showed 15N enrichment, so this enrichment is not an artifact of gut contents.
It is worth considering the relationship between Allomerus ants and the fungi they use to create the carton trails along the branches and stems of their host plants. Leroy et al. (2010) found that the fungi used by A. decemarticulatus to make structures similar to those I observed on C. nodosa plants inhabited by A. octoarticulatus are capable of fixing nitrogen that is subsequently absorbed by the host plant. Although I did not measure the stable isotope ratios of the fungi that associate with A. octoarticulatus, they might be a source of protein and carbohydrates for A. octoarticulatus colonies and could impact the interaction between these ants and C. nodosa, as has been demonstrated in other systems (see Pinto-Tomas et al. 2009 for an example of nitrogen fixation in the fungal gardens of leaf-cutter ants and Defossez et al.
2009 for a survey of ascomycete fungi associated with the ant-plant Leonardoxa africana).
Colony performance
Allomerus octoarticulatus colonies have higher relative fitness (e.g. worker weight) when insects are part of their diet. Although there was no statistically significant difference in colony growth between treatments, in general, the morphometric analysis and worker weight data showed that ants in the H- treatment were smaller than ants in the H+ treatment. Thus, ant biomass was higher when insect prey were available. In naturally occurring colonies from the same population, colonies with heavier workers made more reproductives (Figure 3.7), so worker mass likely contributes to A. octoarticulatus fitness; colonies with heavier workers may have more energy to invest in producing reproductives. Numerous field studies and
46 mathematical models have shown that body mass is positively related to reproductive success of individuals and colonies, in large part because body mass influences metabolism, growth rate, mortality rate, and other biological traits, such as egg size (Banse & Mosher 1980; Peters
1983; Juliano 1984; Savage et al. 2004); hence, workers with higher body mass could live longer reducing the need for continuous worker production in the colony and allowing more resources to be invested in the production of reproductives. The results of this experiment add to those of earlier studies of ants that have found that colony fitness can be inferred by the mass of adult reproductives and colony size (Gordon 1992; Wagner & Gordon 1999; Deslippe
& Savolainen 1994).
I found that colony size was not statistically different between treatments but in treatments with access to insect herbivores the average colony size was slightly bigger. It is possible that ants with access to insect prey might be able to invest more in individual growth and/or on raising more larvae to adulthood. In this experiment, ants in the H+ treatment seemed to invest more in ant growth than in production of new workers, so although insect prey can play a role in increasing of colony size, it might not be the only factor that affects colony growth. In the companion study to this experiment, Frederickson et al. (2012) found that colony size increased with the number of scale insects, indicating that ants actively tend hemipterans inside domatia (Figure 3.11). It is possible, then, that under nutritional stress ants start relying more on honeydew or preying on the mutualistic Hemiptera. However, the density of scale insects does not seem to be changing as a function of insect prey and given the similar patterns of scale insect abundance in both treatments, predation of scale insects appears unlikely to occur at a high frequency. For the same reason, I do not consider that the presence of scale insects had a big influence on the worker size differences that I observed in the treatments, meaning that for the same number of scale insects, workers in the H- treatment
47 were still smaller than the workers in the H+ treatment. Nonetheless, I predict that scale insects should have an effect on how well the colonies survive when they are feeding exclusively on plant-derived food, especially since sap-feeding insects often have symbiotic gut bacteria that upgrade nutrients in their honeydew (Baumann 2005; Stadler & Dixon 2005;
Janson et al. 2008; Clark et al. 2010, Suen et al. 2010).
Gaster microbiome
Our experimental manipulation of insect herbivores/prey did not influence the variables I measured regarding the assemblage of symbiotic bacteria in A. octoarticulatus gasters.
Phylogenetic diversity was equal in both treatments and the composition of bacteria seemed to vary independently in each colony with only a few groups being present in all samples. This implies that the gaster microbiome of A.octoarticulatus might not be limited by nutrients when insect prey is not available, thus suggesting that there were either enough nutrients in the system or that the bacteria present were able to upgrade nutrients. In either case, the variation in taxa among all samples shows that most bacteria are not tightly associated with the ants.
Neither weighted nor unweighted UniFrac analyses showed any patterns of dissimilarity among the bacterial assemblages in the two treatments, and this was supported by an Adonis test. Weighted UniFrac is a quantitative measurement that can provide insights into the types of bacteria and their density in the sample; while unweighted UniFrac, a qualitative measurement, gives information that is relevant to presence and absence of different types of bacteria in the sample without using abundance data (Lozupone et al. 2007). This explains why there are differences between the PCoA plots generated (Figure 3.10; some assemblages cluster only when using unweighted UniFrac. Some of these clusters seemed to grouped by block; e.g., blocks K, L, F were physically close to each other in the field). The model
48 selection results were ambiguous and did not support the block effect found with the Adonis test, suggesting that block alone was not enough to explain a meaningful amount of the variance in microbiomes among samples. None of the biological and environmental variables I measured influenced the gut bacterial communities, but the fact that the block effect was significant in one test and some bacterial assemblages clustered by block suggests that (an) unknown environmental factor(s) are driving some of the variation in gaster bacterial assemblages. For example, ants in some of the blocks did poorly; in block G neither of the colonies survived and in block J, the H+ colony did not survive to the end of the experiment and the H- colony was probably infected with a bacterial pathogen from the phylum
Fusobacteria. Although this type of bacterium was present in many other samples, it was never in the same abundance found in the sample from block J. Thus, the question of what factors structure bacterial assemblages in A. octoarticulatus guts remains unanswered.
Similar to other studies of bacterial assemblages in arthropods, I found a complex and diverse community of bacteria. The bacterial taxonomic units in A. octoarticulatus are mostly common inhabitants of arthropod guts. Firmicutes, Bacteroidetes, and Proteobacteria are frequently found in the guts of arthropods such as the lepidopteran pest Ostrinia nubilalis
(Belda et al. 2011), aphids (Oliver et al. 2010), bees (Cox-Foster et al. 2007), and Tetraponera ants (Van Borm et al. 2002). These few examples might not reflect the fact that although one of the first beneficial bacteria described in insects (i.e., Blochmannia) was found on carpenter ants (Blochmann 1882 in Gil et al. 2003), studies of bacterial symbionts in ants have been few compared to other groups of insects. Some of the studies in ants have suggested that bacterial groups such as γ-proteobacteria and bacteriodetes can provide many benefits to ants (Zientz et al. 2005; Eilmus & Heil 2009). These two taxa make up over 20% of the bacteria found in A. octoarticulatus. I also found several bacteria that may fix nitrogen, hence with the potential of
49 becoming beneficial partners to A. octoarticulatus (i.e., Methylobacterium, Rhizobium,
Bukholeria, Pantoea and Pseudomonas) (Ohkuma & Kudo 1996; Van Borm et al. 2002; Ishak et al. 2011), but all of them occurred at very low relative abundances and with the exception of Pseudomonas, these bacteria were only present in less than half of the samples. Many of these putatively nitrogen-fixing bacteria could be acquired by horizontal transmission via honeydew or from plant-associated bacteria or other environmental sources. One interesting finding was the high relative abundance of Actinobacteria, a taxon usually associated with soils, from which I found bacteria from the genus Pseudonocardia. Pinto-Tomas (2009) determined that in ants from the tribe Attini, bacteria from this genus can produce antibacterial agents that help to defend their fungal gardens. In addition, fungal gardens tended by leaf cutter ants seem to have a great degradatory capability, fixing nitrogen and breaking down cellulose with the help of bacteria similar to those found in Allomerus (Suen et al. 2010).
Following Leroy et al. (2010), I emphasize that the association among fungi, ants, and bacteria might be more widespread and important that previously thought. Consequently, I predict that the gaster microbiome of A. octoarticulatus might provide some nutritional benefits to the ant colonies, however I do not expect highly conserved relationships between symbiotic bacteria and A. octoarticulatus workers.
Effects of multispecies interactions on the mutualism
Here I show that third parties, such as insect prey, can modify the strength of mutualistic interactions. In general, A. octoarticulatus can survive on a diet of plant-derived food bodies and honeydew. However, colonies perform better when an additional source of protein, such as insect prey, is present. Additionally, the findings in this study suggest that the mutualism between two partners can be influenced by a second or third putative mutualism in the system.
50
For instance, the ant-plant interaction might be modified by the ant-scale insect partnership and this, in turn, may be modified by the scale insect-microbe relationship. For example, upgrading of nutrients by gut bacteria seems unlikely for A. octoarticulatus, unless there has been horizontal transmission of beneficial bacteria from sap-sucking insects to ant workers, either by ants feeding on honeydew or by direct predation but further research is necessary to validate these assumptions. Finally, even though I did not find any effect of insect prey on the bacterial assemblage in the ants, I found that bacterial assemblages might be shaped by other environmental factors and I suggest that fungal associations might be especially relevant.
51
Figures and Tables
Figure 3.1. A) A C. nodosa domatium. B) A food body on the underside of a C. nodosa leaf.
C) A. octoarticulatus workers foraging on C. nodosa leaves. Photos © G. Miller.
Figure 3.2. Morphological measurements taken on A. octoarticulatus workers. HL: head length, ML: mesosoma length, P: petiole and postpetiole length, G: gaster length, MW: mesosoma width, HW: head width, SL: scape length, and MaL: mandible length. Photos © A.
Nobile.
52
Figure 3.3. Mean (± SE) number of ants that recruited to protein-rich (P) baits after five hours on herbivore-excluded (H-) and control (H+) plants.
Figure 3.4. Carbon and nitrogen stable isotope ratios for ants in the H+ (closed circles) and H-
(open circles) treatments. H&T indicates samples with only heads and thoraces; Whole indicates samples with entire ants. Isotope ratios for naturally occurring C. nodosa, A. octoarticulatus workers, insect herbivores (coleopterans, hemipterans, etc.), and predatory spiders found on C. nodosa are given for reference.
53
Figure 3.5. A) Mean (± SE) worker mass and B) worker length of ants that developed with access to insect herbivores (H+) and in the absence of insect herbivores (H-).
Figure 3.6. Mean (± SE) number of workers produced in colonies with access to insect herbivores (H+) and in the absence of insect herbivores (H-) after 11 months.
54
Figure 3.7. Relationship between worker weight (log-transformed) and the residual values of the number of reproductives (alates; square-root transformed) per colony (r2= 0.56).
Figure 3.8. Phylogenetic diversity of microbes in the gaster of ants with access to insect herbivores (closed circles) and in the absence of insect herbivores (open circles) (P>> 0.05).
Rarefaction plot obtained with a PD whole tree matrix.
55
Figure 3.9. Relative abundance of bacteria phylums per sample. Category axis is labelled with the block letter followed by treatment (H+: herbivores; H-: no herbivores).
Figure 3.10. Ordination of bacterial assemblages explained by the first two principal coordinates from a weighted UniFrac (A) and unweighted UniFrac distance matrix (B). Letters indicate blocks.
56
Figure 3.11. Relationship between the number of scale insects and ant colony size for ants with access to insect herbivores (closed circles) and in the absence of insect herbivores (open circles). Figure modified from Frederickson et al. 2012.
57
Table 3.1. MANOVA results for the different data sets of stable isotope ratios. H&T indicates samples with only heads and thoraces and Whole indicates samples with whole ants.
Statistically significant values in bold.
Data Set Stable Isotope F P(>F) Ratio
13 15 Whole, H&T δ C, δ N 3.9495 0.05
13 15 Whole δ C, δ N 0.7506 0.40
13 15 H&T δ C, δ N 5.8395 0.03
Table 3.2. Adonis test for A) herbivore treatment and B) block effects.
A.
df SS MS F r2 P(>F) Herbivore 1 0.251 0.25101 0.81418 0.04842 0.808 Residuals 16 4.9328 0.3083 0.95158 Total 17 5.1838 1
B.
df SS MS F r2 P(>F) Block 8 2.6966 0.33708 1.2197 0.5202 0.055 Residuals 9 2.4872 0.27635 0.44798 Total 17 5.1838 1
58
Table 3.3. Model selection of biological and environmental factors using AIC.
Factors df AIC F Permutations P(>F) None 1 156.52 δ15N 1 157.15 1.2632 99 0.18 Scale Insects 1 157.21 1.2088 99 0.28 Worker Weight 1 157.28 1.137 99 0.36 Colony 1 157.3 1.1142 99 0.37 Final N. Leaves 1 157.40 1.0269 99 0.50 Plant Performance 1 157.42 1.0015 99 0.52 Herbivores 1 157.46 0.9671 99 0.71 δ13C 1 157.53 0.8975 99 0.70 Plot 8 160.19 1.1066 99 0.51
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CHAPTER FOUR
Concluding Remarks
“Ultimately, studies of multispecies phenomena that build upon mutualism should have significance for conserving and restoring species in a rapidly changing world.” –Bergstrom et al. 2003
“Symbionts can alter the phenotype of their host in ways that may affect interactions with other species as well as the relative fitness of each partner.” –Clay et al. 2005
“Species in pure isolation simply do not make sense.” –Thompson 1999
Thomson (1999), Bergstrom et al. (2003) and Clay et al. (2005) recognize that mutualistic relationships are dependent on external biotic and abiotic factors and at the same time changes in the strength of the mutualism can lead to differences in how species interact in the community, thus, becoming a cyclical process of feedback mechanisms. This thesis helps to reaffirm that in mutualistic interactions, nutritional factors, such as nitrogen availability in the form of amino acids added to an artificial diet or insect prey in nature, can have a profound effect on a partner’s performance, influencing for example the partner’s abundance or fitness.
Furthermore, it shows how the interaction with multiple species, like insect herbivores and scale insects, that are not part of the beneficial relationship, can have a positive effect on the mutualism by helping to increase the performance of one of the partners.
In Chapter Two, I showed how putatively symbiotic bacterial assemblages can be disturbed with changes in amino acid availability, decreasing bacteria cells when nitrogen is
60 not accessible. My results suggest that ant fitness might be related to the abundance of bacteria in the gut. Further study is needed to determine how disturbance of symbiotic bacteria can affect individual ant fitness versus ant colony fitness. For this, I propose the use of the microcolony method while administering treatments for three months or longer. It is also necessary to study gut bacteria in earlier stages of ant development, when protein consumption might be more relevant and the ant-bacteria mutualism stronger.
In Chapter Three, I manipulated the presence of insect herbivores, an important player but not a partner in an ant-plant mutualism. As expected, the relative fitness of ant colonies decreased in the absence of insect herbivores which I assumed to be the main source of protein for these colonies. However, the ant bacterial assemblages remained equally diverse even though nitrogen sources decreased. I suggest that the presence of scale insects and fungi in the experiment are important nutritional sources in the system, as well as an important source of symbiotic bacteria that could be transmitted horizontally to ants. Thus, scale insects and fungi could be essential for the understanding of ant-plant and ant-bacteria mutualisms.
61
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Appendix A- Article: Salt intake in Amazonian ants: too much of a good thing?
Salt intake in Amazonian ants: too much of a good thing?
Lina M. Arcila Hernández1, Erinn V. Todd1, Gabriel A. Miller2, and Megan E. Frederickson1*
1Department of Ecology & Evolutionary Biology, University of Toronto, 25 Harbord Street,
Toronto, Ontario, M5S 3G5, Canada
2Department of Organismic & Evolutionary Biology, Harvard University, 26 Oxford Street,
Cambridge, Massachusetts, 02138, USA
*Author for correspondence: [email protected], tel: 1-416-978-7252, fax: 1-416-
978-8532
Statement of authorship: LMAH, EVT, and MEF designed the research; LMAH carried out the research and analyzed the data from the section ‘Bait preferences of leaf litter and canopy ant assemblages’; EVT and MEF carried out the research and analyzed the data with field work assistance from LMAH and data analysis assistance from GAM from the section
‘Preference for sodium in an herbivorous/omnivorous ant, Camponotus mirabilis’ and thereafter; MEF, LMAH, and EVT drafted the paper with significant input from GAM.
77
Abstract
Although herbivory is widespread among insects, plant tissues rarely provide the optimal balance of nutrients for insect growth and reproduction. As a result, many herbivorous insects forage elsewhere for particular amino acids and minerals. Recent studies have shown that both herbivory and recruitment to sodium are commonplace among tropical rainforest ants, but little is known about how ants regulate their sodium intake at the individual and colony levels.
In social insects, foragers may respond not only to their own nutritional deficiencies but also to those of their nestmates, who may have different nutritional requirements depending on their developmental stage, sex, or caste. Here, we investigate how salt stress among rainforest ants affects their preferences for salt and subsequent survival. We found that ants recruited more to salt than to any other bait type tested, confirming the strong preference for salt of ants in this region. Initially, we observed similarly high recruitment to salt among workers of the arboreal, herbivorous/omnivorous ant species Camponotus mirabilis. However, when provided with unrestricted access to high concentrations of salt, C. mirabilis workers suffered significantly higher mortality relative to controls, suggesting that C. mirabilis workers forage for sodium to the point of toxicity. Nonetheless, surviving workers showed reduced preference for salt at the end of the experiment, so some but not all individuals were able to regulate their salt intake beneath lethal dosages. We discuss how salt intake regulation may depend on colony members other than workers.
Keywords: bamboo, Camponotus mirabilis, herbivory, insect nutrition, sodium limitation, tropical rainforests
Introduction
78
Herbivorous animals often need more sodium than they can get from the plants they eat (e.g.,
Arms et al. 1974, Laurian et al. 2008, Kaspari et al. 2008). Animals require sodium for many physiological functions, including osmotic regulation and neuromuscular activity, but the sodium content of terrestrial plant tissues is typically orders of magnitude less than that of animal tissues (Stamp & Harmon 1991, Kaspari et al. 2009, 2010). As a result, many vertebrate and invertebrate herbivores supplement their diets with additional sodium from non-plant sources. In boreal forests, for example, moose (Alces alces) seek out salt pools formed by the accumulation of de-icing salts along roadsides (e.g., Laurian et al. 2008).
Similarly, in western Amazonian rainforests, where the present study was conducted, many frugivorous or folivorous mammals and birds visit natural clay licks, apparently to obtain sodium (Emmons & Stark 1979, Brightsmith & Aramburú Muñoz-Najar 2004, Bravo et al.
2008, Tobler et al. 2009). In arthropods, sodium deficiency is thought to explain why butterflies and other herbivorous taxa ‘puddle’ on mud, animal feces, and carrion, although nitrogen limitation may also play a role (Arms et al. 1974, Boggs & Jackson 1991, Smedley &
Eisner 1995, 1996, Molleman et al. 2005, Molleman 2010).
Recent studies have shown that herbivory is widespread among tropical arboreal ants
(Blüthgen et al. 2003, Davidson et al. 2003), raising the possibility that they too may need to forage for sodium. In two seminal papers, Kaspari et al. (2008, 2009) investigated sodium limitation in New World ant assemblages. They found that ants commonly recruit to sodium baits (especially ants in genera or subfamilies with many herbivorous species) and that ant attraction to sodium increases with distance inland (Kaspari et al. 2008, 2009). Specifically, ants in the western Amazon Basin were much more attracted to sodium baits than ants in
Florida, Panama, or Costa Rica, where more ocean salt reaches terrestrial ecosystems.
Furthermore, when NaCl was added to plots in a rainforest near Iquitos, Peru, the abundance
79 of ants increased sharply (Kaspari et al. 2009). To our knowledge, only two other studies have investigated the sodium requirements of ants. O’Donnell et al. (2010) found that leafcutter ants (Atta cephalotes) in Costa Rica cut and removed more salt-soaked than water-soaked paper baits, although they most strongly preferred the sugar-soaked option, and Kaspari et al.
(2010) found that ant recruitment to NaCl baits increased with distance from a salted road at
Harvard Forest.
The protein and carbohydrate requirements of ants are comparatively well understood
(e.g., Davidson 1997, Dussutour & Simpson 2008, 2009, Cook et al. 2010) and studies in this area offer a number of insights into how ants might regulate their intake of sodium. Collecting nutrients in the right amounts and ratios is thought to pose a greater challenge to social than solitary insects, because foragers have to satisfy not only their own needs but also the needs of their nestmates (i.e., other workers, larvae, pupae, sexuals, and the queen or queens), who may have different nutritional requirements. For example, ant larvae typically require more protein than adult workers; a recent study of green-headed ants (Rhytidoponera sp.) found that colonies with larvae maintain a more protein-biased protein-to-carbohydrate (P:C) ratio than colonies without larvae (Dussutour & Simpson 2009). Interestingly, the same study also found that foraging workers regulated their P:C intake more precisely when their colonies had larvae, suggesting that feedback between larvae and workers inside the nest affect foraging decisions made outside the nest. Similar feedbacks may determine whether ant workers collect sodium, and in what ratios to other nutrients, but at present we do not know how sodium requirements vary with respect to developmental stage, sex, or caste in ants.
Here, we investigated several aspects of salt stress in an ant assemblage in the western
Amazon Basin. We began by comparing the recruitment of ants to salt and other baits in the
80 leaf litter and the canopy at our study site. Our approach was similar to previous studies (i.e.,
Kaspari et al. 2008, 2009), except that we offered both simple baits (salt and sugar) and more chemically and nutritionally complex baits that represented resources that are commonly (bird droppings, extrafloral nectar, protein, and urine) or occasionally (pollen) harvested by ants in
Neotropical rainforests. Next, we investigated whether altering the amount of salt available to one herbivorous/omnivorous, arboreal ant species, the bamboo specialist Camponotus mirabilis, affected its propensity to forage for salt and its performance/fitness. We maintained experimental micro-colonies of C. mirabilis with or without brood (i.e., larvae and pupae) on high or low salt treatments for two weeks and we monitored how the salt treatment and the presence of immature stages affected the preference of C. mirabilis workers for salt and the survivorship of C. mirabilis workers, larvae, and pupae.
Methods
Study site
This study was conducted at the Centro de Investigación y Capacitación Rio Los Amigos, hereafter “CICRA” (12°34’ S, 70°05’ W; elevation ~270 m), in the Department of Madre de
Dios, Peru. Surrounding the research center is the Los Amigos conservation concession, which comprises 146,000 ha of primary tropical rainforest on a mixture of upland terraces and floodplains. Annual rainfall at Los Amigos is between 2,700 and 3,000 mm, with more than
80% of the precipitation falling during the October-April wet season (Pitman 2008). Mean monthly temperatures range from 21° C to 26°C (Pitman 2008).
Bait preferences of leaf litter and canopy ant assemblages
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In July-August 2010, we investigated the preferences of ants in the leaf litter and in the canopy for a variety of baits. We prepared eight types of baits: salt (table salt, i.e., iodized NaCl), sugar (table sugar, i.e., sucrose), protein (whey protein powder, Interactive Nutrition, Inc.), urine (collected fresh from a mammal), extrafloral nectar (EFN), bee pollen (Selva Natural), bird droppings (collected fresh from a chicken), and water (as a control). We used bird feces and mammal urine because canopy ants often recruit to these substances (e.g., Powell 2008,
Yanoviak et al. 2008, Kaspari et al. 2009) and they may be among the most common naturally available sources of salt in this ecosystem. Similarly, extrafloral nectar is a widely available sugar source that attracts many rainforest ants (Blüthgen et al. 2000); reports of possible palynivory in tropical arboreal ants prompted us to also include pollen as a bait type (Baroni
Urbani & de Andrade 1997, Davidson et al. 2003). For all bait types except EFN, we added 2 g of the ingredient to 30 mL of distilled water. Because collecting EFN proved challenging, we instead cut twelve extrafloral nectaries from Inga plants and added the nectaries in their entireties to 30 mL of distilled water. We saturated pieces of cotton with one of the eight bait solutions and transferred them to test tubes. We then taped eight test tubes, each with a different bait type, together to form bait sets.
We sampled ants on 12 trees growing in floodplain and upland forests at CICRA.
Trees were separated from each other by at least 10 m and were large enough to support climbing equipment. For each tree, we placed three bait sets on the leaf litter at the base of the tree and three bait sets in the canopy (~6-20 m from the ground). After an hour, we trapped all the ants present in the tubes by sealing the tubes with additional cotton and tape. We sampled the ants on each tree once in the morning and once again in the afternoon, using different bait sets each time. After collection, we froze the test tubes for at least 12 hours to kill the ants and then counted the total number of ants in each tube.
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Preference for sodium in an herbivorous/omnivorous ant, Camponotus mirabilis
Bamboo-dominated forest grows in patches throughout the Los Amigos concession and elsewhere in the western Amazon Basin (Nelson 1994, Griscom & Ashton 2003). In these patches, several Camponotus (Formicidae: Formicinae) species make their nests inside the hollow culms of bamboo (Guadua spp.; Davidson et al. 2006a,b). We focused on one of these bamboo specialists, Camponotus mirabilis, which has polydomous colonies that occupy clusters of adjacent stems of live bamboo (Davidson et al. 2006b). The diet of Camponotus mirabilis consists mostly of honeydew from coccids (Coccidae), “supplemented by occasional prey” (Davidson et al. 2006b); herbivory/omnivory in C. mirabilis is further supported by a nitrogen isotope ratio (δ15N) intermediate between that of chewing herbivores and that of predators (Davidson et al. 2003). Camponotus mirabilis is thus similar to many other tropical arboreal ants, which feed mostly on honeydew or extrafloral nectar but take prey opportunistically (Davidson et al. 2003). All the bamboo-specialist Camponotus tend coccids that have recently been described as the new species Cryptostigma guadua (Kondo & Gullan
2004), and we observed numerous coccids in the ant-occupied culms of the bamboo we collected.
Camponotus mirabilis collection and set-up of micro-colonies
In June-July 2011, we collected large fragments of five C. mirabilis colonies that we found along the trail system at Los Amigos. For each colony fragment, we cut open several live bamboo culms occupied by C. mirabilis and collected the workers and brood. We established four micro-colonies from each of the five C. mirabilis colonies. Each micro-colony comprised
83 either 1) ten workers or 2) ten workers, ten pupae, and ten larvae. In all cases, the ten workers were made up of seven minor and three major workers. The larvae and pupae in the micro- colonies with immature stages ranged in size, but we deliberately avoided selecting larvae or pupae fated to become reproductives. We housed each micro-colony in a small, lidded plastic container with the center of the lid replaced with fine mesh for airflow. We provided each micro-colony with a tent made from transparent red plastic, which blocked light; workers piled brood and congregated beneath the tent. Micro-colonies were kept at CICRA away from direct sunlight and under ambient temperature and humidity conditions for the duration of the experiment.
Camponotus mirabilis preference tests
Before starting the experiment, we tested the preferences of C. mirabilis workers for distilled water, a 10% solution of table sugar, and a 10% solution of table salt. After setting up the micro-colonies, we starved them overnight and then chose three workers at random from each micro-colony. For each worker, we put one drop of each solution in an equilateral triangle in a
Petri dish, added the ant, and then allowed it to settle for 60 seconds. Every five seconds for the next two minutes, we recorded whether the ant was touching the water droplet, the salt solution droplet, the sugar solution droplet, or none of these. At the end of each test, we converted the number of times the ant was touching each droplet to a preference score; for each test solution, the minimum score was 0 (the ant was not touching the test solution at any
5 s interval) and the maximum score was 100 (the ant was touching the test solution at every 5 s interval). We re-used Petri dishes for subsequent trials, washing them thoroughly with soap and water and drying them completely between uses. At the end of the experiment, we also
84 tested the preferences of between one and three of the surviving workers (if there were any) from the micro-colonies, using the same protocol.
Experimental addition of salt
All micro-colonies were fed an artificial diet modified from Straka and Feldhaar (2007).
Briefly, each 100 mL of diet contained 1 g agar, 20 g sucrose, 2.595 g whey protein powder
(Interactive Nutrition, Inc.), and 0.270 g Vanderzant vitamin mixture for insects (Sigma). We transported Petri dishes filled with artificial diet to CICRA in a cooler and stored them at approximately -4° C. The whey protein powder we used to make the artificial diet contained a small amount of sodium (1.5 mg/g). Every three days, we provided each micro-colony with one level scoop of diet (~0.2 mL), measured using a micro-spoon, on a square of aluminum foil; the ants did not consume all of the food we gave them and remaining food was removed at the next feeding.
We provisioned the colonies with water ad libitum. We placed two cotton-filled bulbs made from plastic disposable pipettes in each micro-colony. The low-salt treatment group had both bulbs filled with distilled water, whereas the high-salt treatment group had one bulb with distilled water and the other bulb filled with a 10% solution of table salt (iodized NaCl). The cotton was replaced if it became so wet that the ants could not enter and drink easily, or if it filled with debris or mold.
We maintained the treatments for two weeks and examined each micro-colony every three days for survivors. We counted and recorded the number of dead workers, and also the number of live workers, checking against previous counts to make sure that none had escaped.
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We also recorded the number of dead larvae and pupae. We included missing larvae and pupae in the totals for dead larvae and pupae, since they could not escape and we presumed that their adult sisters had eaten them. We removed all the dead ants and any debris during each examination.
Statistical analysis
We square-root transformed all count data before statistical analysis to improve normality and then used mixed model ANOVAs to test for treatment effects. For each baited tree, we summed the number of ants in the three morning and three afternoon tubes of the same bait type for leaf litter and canopy tubes separately. We then analyzed the number of ants at each bait type, with tree (1-12) as a random effect, forest stratum (leaf litter, canopy) and bait type
(bird droppings, extrafloral nectar, pollen, protein, salt, sugar, urine, water) as fixed effects, and forest stratum by bait type as an interaction effect.
For data from the preference tests, colony (1-5) was a random effect, salt (high/low), brood (present/absent), and test solution (water, sugar, salt) were fixed effects, and salt by test solution and brood by test solution were interaction effects. Similarly, we compared the number of workers that survived to the end of the experiment among treatments with colony
(1-5) as a random effect, salt (high/low) and brood (present/absent) as fixed effects, and salt x brood as an interaction effect. All of the larvae and pupae had died by the end of the experiment, so we compared the mortality rates of larvae and pupae in the high and low salt treatments using survival analysis. For significant effects in the ANOVA models, different levels were compared with Tukey’s HSD tests. Statistical analyses were carried out in JMP®
9.0.0.
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Results
Bait preferences of leaf litter and canopy ant assemblages
We collected a total of 4003 ants at the baits, of which almost half (1859 ants, or 46%) were collected at the salt baits. Significantly more ants recruited to the salt baits than to any other type of bait; in fact, recruitment to other bait types did not differ significantly from recruitment to the water controls (Table 1, Figure 1). Neither forest stratum nor the interaction between stratum and bait type were significant (Table 1), although the P-values for both were only marginally non-significant (0.10 and 0.08, respectively). Across all bait types, large numbers of Crematogaster (2380 workers, both strata), Azteca (976 workers, in the canopy only),
Camponotus (366 workers, both strata), and Pheidole (116 workers, in the leaf litter only) recruited to our baits; these four genera accounted for over 95 % of bait visitors.
Camponotus mirabilis preference tests
Camponotus mirabilis workers initially preferred the salt solution to the sugar solution and visited both more than they visited the distilled water droplets (Table 2, Figure 2a). After two weeks on the artificial diet, however, the surviving ants had switched their preference to the sugar solution, and visits to the salt solution droplets were statistically indistinguishable from visits to the water droplets (Table 2, Figure 2b). In the final preference tests, there was also a statistically significant interaction between salt treatment and test solution preference (Table
2). Workers in the high salt treatment maintained a stronger preference for salt and a weaker
87 preference for sugar than workers in the low salt treatment, although both groups still chose sugar over salt (Figure 2b).
Ant survivorship
More C. mirabilis workers survived in micro-colonies in the low-salt treatment and in micro- colonies with brood (Table 3, Figure 3). Pupae died faster than larvae, but there were no differences in the mortality rates of larvae or pupae between the salt treatments (mean ± SE
2 days to death for larvae on high salt = 7.22 ± 0.26, on low salt = 7.28 ± 0.29, log-rank test: χ 1
= 0.055, P = 0.814; mean ± SE days to death for pupae on high salt = 5.86 ± 0.28, on low salt
2 = 5.58 ± 0.28, log-rank test: χ 1 = 0.454, P = 0.500).
Discussion
Ants in the Peruvian Amazon like salt. When offered a wide range of baits, ants preferred salt to all other choices and only salt baits attracted significantly more ants than water controls
(Figure 1). We even observed workers trying to remove salt-soaked cotton from test tubes.
The large number of ants that recruited to the salt baits suggests that salt is a key limiting nutrient for ants in this region. Nonetheless, following two weeks in high-salt conditions, C. mirabilis workers reduced the time they spent in contact with salt solutions (Table 2, Figure
2), suggesting satiety. However, workers experienced higher death rates in high compared to low salt conditions (Table 3, Figure 3), so satiety did not arise fast enough to prevent mortality in all workers.
88
Kaspari et al. (2008) found greater salt limitation among ants in ‘green’ food webs
(i.e., in abundant vegetation) than among ants in ‘brown’ food webs (i.e., in leaf litter).
However, we did not find a statistically significant difference in salt preference between ants in the canopy and the leaf litter, although the trend was in the predicted direction and the P- value for the interaction between stratum and bait type was only marginally non-significant
(Table 1). A larger sample size might have revealed a difference in bait preferences between strata, or perhaps ants in this region are strongly salt stressed in both green and brown food webs.
In our micro-colony experiment, we found that salt-satiated C. mirabilis workers reduced their foraging for salt, but not before many workers in the high-salt treatment had died. Shortly after we collected them, C. mirabilis workers preferred salt to both sugar and water (Figure 2a), but after two weeks on artificial diet, they switched their preferences in favor of sugar and they visited droplets of salt solution and water equally (Figure 2b). We observed this change in preference among ants in both the low-salt and high-salt treatments, suggesting that even the ants in the low salt treatment were receiving enough sodium to meet their needs. Ants in the low salt treatment had access to two potential sources of sodium: through their artificial diet or through rampant cannibalism of their immature nestmates.
Cannibalism is known to efficiently address nutritional needs, particularly with regard to salt and protein (e.g., Simpson et al. 2006).
Although the initial preference of C. mirabilis workers for salt suggests that they or their nestmates suffer from salt deficiency under natural conditions, workers with unrestricted access to salt solution suffered higher mortality (Figure 3). Thus, it seems likely that either sodium itself, its chloride anions, or the iodine present in small quantities in table salt is
89 directly toxic to C. mirabilis workers at certain doses. The question then becomes: why can’t
(or don’t) these ants regulate their salt consumption? One possibility is that C. mirabilis never encounters salt in the form or concentrations we used and thus has not evolved to regulate its intake within non-toxic limits. Iodine occurs naturally in sea salt (which is predominantly
NaCl), albeit at lower concentrations than in iodized table salt (Dasgupta et al. 2008); however, the Peruvian Amazon is not near oceanic salt sources. To determine whether sodium itself can be toxic to ants, future studies could monitor the survivorship of ants offered a range of sodium concentrations in a variety of anion backgrounds (e.g., NaCl, Na3PO4, Na2SO4, etc.). Note that Kaspari et al. (2009) demonstrated that ant recruitment to NaCl is driven by
+ - Na and not by Cl by showing that ants prefer NaCl, NaNO3, Na3PO4, and Na2SO4 to KCl,
MgCl2, and CaCl2, but this study did not investigate the survivorship of ants that ingested these compounds.
Alternatively, the absence of a queen, other reproductive ants, or simply larger numbers of workers in our experimental micro-colonies could have impinged on the ability of workers to regulate salt intake appropriately. When we collected the C. mirabilis colony fragments, they contained numerous alate ants, both males and females, so perhaps the workers’ initial preferences for salt reflected the reproductive status of the colonies we used.
Workers in these colonies may have collected large amounts of salt ‘expecting’ to provide it to their reproductive sisters and brothers or other ants back at the nest, only to be cut off from these nestmates by our experimental intervention.
In a number of solitary insects, sodium is thought to be particularly important to reproductive stages. Among Lepidoptera, adult butterflies and moths, but not their caterpillars, forage for sodium, and males often ‘puddle’ more than females (Arms et al. 1974, Boggs &
90
Jackson 1991, Smedley & Eisner 1995, 1996, Molleman 2010). At least two hypotheses (not mutually exclusive) have been put forward to account for sex differences in lepidopteran puddling behaviors. Males may require more sodium than females because: 1) males transfer sodium to females during copulation (e.g., Smedley & Eisner 1996) or 2) the greater flight activity of males increases their sodium demands (Arms et al. 1974, Molleman et al. 2005).
In ants, few studies have examined what substances, other than sperm, males transfer to females during copulation (Allard et al. 2002, Schrempf et al. 2005), so it is possible that male ants transfer sodium to females when they mate. In at least some Lepidoptera, females transfer much of the sodium gift they receive from males to their eggs (Smedley & Eisner
1996), and a similar process in ants, were it to occur, could serve to fulfill the sodium requirements of nanitic workers produced by fully claustral queens that do not forage outside the nest. If this hypothesis is correct, we should expect more foraging for sodium among workers in colonies: 1) with reproductives, 2) with male-biased sex ratios, and 3) in fully claustral species, compared to species with other modes of colony foundation.
Molleman (2010) used the fact that ants forage for sodium as one piece of evidence to discount the hypothesis that insects need a lot of sodium to support flight, saying “the fact that ants used sodium baits even though they do not fly (Kaspari et al. 2008) also suggests that the neuromuscular activity hypothesis may not be the explanation [for puddling].” But most reproductive ants do fly, of course, and workers may forage for sodium not for themselves, but to supply their reproductive nestmates with sodium for their upcoming mating flights. Again, if this hypothesis is correct, we should expect more foraging for sodium among workers in colonies with than without reproductives. Interestingly, this hypothesis is consistent with the observation that adding NaCl “double[d] ant densities in a Peruvian forest (Kaspari et al.
91
2009), and based on a three-fold increase in queens, likely nest densities …” (Kaspari et al.
2010, p. 546).
In contrast to recent research on P:C regulation in ants (Dussutour & Simpson 2009), we did not find that the presence of brood improved workers’ ability to regulate sodium intake. In the final preference tests, there was no significant interaction effect between brood presence and test solution preference, suggesting that the presence of larvae and pupae in the micro-colonies did not change the preferences of C. mirabilis workers for salt, sugar, and water at the end of the experiment. There was also no significant interaction of brood presence and salt treatment on worker survival. However, workers cannibalized most of the larvae and pupae in the micro-colonies in the first week of the experiment, so there may have been transient effects of brood presence that had attenuated by the end of the experiment. Brood presence did reduce worker mortality, likely because workers benefitted from cannibalizing larvae and pupae. This result suggests that there were macronutrients or minerals available in larvae and pupae that were not supplied in the right amounts or ratios in the artificial diet to maximize worker survival. The increased survivorship of workers in micro-colonies with brood was independent of salt treatment (Table 3), so sodium was probably not the limiting nutrient responsible for this pattern.
Overall, this study adds to the small but growing literature on the use of salt by ants.
We encourage further research into how sodium affects the performance/fitness of ants at the individual and colony levels and how sodium requirements vary across developmental stages, sexes, and castes in ants.
Acknowledgments
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We thank Viviana Astudillo, Antonio Coral, Rene Escudero, Eddie Ho, David Lefebvre,
Rosita Pestañas, Alison Ravenscraft, and Jon Sanders for field/lab assistance, the staff at
CICRA and the Amazon Conservation Association for logistics, and the Peruvian Ministry of
Agriculture for issuing permits (Nos. 394-2009-AG-DGFFS-DGEFFS and 299-2011-AG-
DGFFS-DGEFFS). Members of the Frederickson and Thomson labs at the University of
Toronto gave us helpful comments on an earlier draft. A Natural Sciences and Engineering
Research Council of Canada (NSERC) Discovery Grant to MEF funded this research; ET was also supported by the Independent Experiential Study Program of the Faculty of Arts and
Science at the University of Toronto and GAM by a Foundational Questions in Evolutionary
Biology Postdoctoral Fellowship from Harvard University (funded by the John Templeton
Foundation).
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Tables
Table 1. Mixed model ANOVA results for number of ants at baits
Effect df SS F P
Tree 11 425.86 6.13 < 0.001
Bait type 7 393.00 8.89 < 0.001
Stratum 1 17.12 2.71 0.10
Bait type x stratum 7 80.95 1.83 0.08
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Table 2. Mixed model ANOVA results for preference tests
Effect df SS F P
Initial preference
Colony 4 2.727 0.572 0.683
Salt 1 0.890 0.747 0.389
Brood 1 1.525 1.279 0.260
Test solution 2 66.358 27.816 < 0.001
Salt x test solution 2 0.329 0.138 0.871
Brood x test solution 2 1.048 0.439 0.645
Final preference
Colony 4 2.430 1.060 0.382
Salt 1 0.132 0.230 0.633
Brood 1 1.727 3.014 0.086
Test solution 2 15.014 13.099 < 0.001
Salt x test solution 2 4.527 3.950 0.023
Brood x test solution 2 1.514 1.321 0.273
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Table 3. Mixed model ANOVA results for worker survival
Effect df SS F P
Colony 4 0.996 0.566 0.692
Salt 1 14.089 32.027 < 0.001
Brood 1 2.727 6.200 0.028
Salt x brood 1 0.104 0.237 0.636
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Figure Legends
Figure 1. Box plots showing numbers of ants at baits in the a) leaf litter and b) canopy. Lines indicate medians, boxes indicate 75th and 25th percentiles, whiskers indicate 90th and 10th percentiles, and dots indicate outliers. Numbers of ants at bait types marked with different letters are significantly different at α = 0.05 according to Tukey’s HSD tests. The results of
Tukey’s HSD tests are shown in the b) panel only but apply to ants in both strata.
Figure 2. Box plots showing C. mirabilis worker visits to droplets of water and 10% solutions of sugar and salt a) before the experiment was initiated and b) after the micro-colonies had been maintained in low and high salt treatments for two weeks. Lines indicate medians, boxes indicate 75th and 25th percentiles, whiskers indicate 90th and 10th percentiles, and dots indicate outliers. Worker visits to test solutions marked with different letters are significantly different at α = 0.05 according to Tukey’s HSD tests.
Figure 3. Numbers of surviving C. mirabilis workers at the end of the experiment. Each symbol is a micro-colony; open symbols indicate the presence of brood, filled symbols indicate the absence of brood, circles indicate high salt, and triangles indicate low salt. The symbols for micro-colonies having the same number of surviving workers are offset slightly to make them visible. See Table 3 for treatment effects.
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Figure 1
102
Figure 2
103
Figure 3
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Appendix B - Components of the artificial diets. *Only added to treatments with antibiotics.
Complete diet for No aa's diet 100 ml (g) (g) Minerals CuCl 0.000120 0.000120 FeCl3 0.000920 0.000920 MnCl2 0.000220 0.000220 NaCl 0.001000 0.001000 ZnCl2 0.000400 0.000400 Amino acids Alanine 0.100000 Arginine 0.100000 Asparagine 0.100000 Aspartic Acid 0.100000 Cysteine 0.100000 Glutamic Acid 0.100000 Glutamine 0.100000 Glycine 0.100000 Histidine 0.100000 Isoleucine 0.100000 Leucine 0.100000 Lysine 0.100000 Methionine 0.100000 Phenylalanine 0.162000 Proline 0.100000 Serine 0.100000 Threonine 0.100000 Tryptophane 0.100000 Tyrosine 0.038000 Valine 0.100000 Gamma-Amino Butyric Acid 0.100000 Salts
KH2PO4 0.250000 0.250000 MgSO4 0.242000 0.242000 Vitamins
Vanderzant vitamin mixture 0.270000 0.270000 Carbohydrates Agar 1.000000 1.000000 Sucrose 20.000000 20.000000 Antibiotic Gentamicin* (250ug/ml) 1.8ml
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Appendix C - List of consensus lineages assigned to OTUs found in the gasters of A. octoarticulatus and total number of reads.
Consensus Lineage Total Bacteria 173 Acidobacteria Acidobacteria_Gp1; Gp1 1 Acidobacteria_Gp16; Gp16 2 Acidobacteria_Gp2; Gp2 1 Acidobacteria_Gp23; Gp23 1 Acidobacteria_Gp4; Gp4 4 Acidobacteria_Gp6; Gp6 1 Actinobacteria Actinobacteria_sp 1 Acidimicrobiales;Acidimicrobiaceae 1 Acidimicrobidae_incertae_sedis;Ilumatobacter 1 Actinomycetales 21 Actinomycetales;Actinomycetaceae;Actinomyces 12 Actinomycetales;Actinomycetaceae;Varibaculum 1 Actinomycetales;Brevibacteriaceae;Brevibacterium 3 Actinomycetales;Corynebacteriaceae;Corynebacterium 11 Actinomycetales;Dermabacteraceae;Brachybacterium 1 Actinomycetales;Dermabacteraceae;Dermabacter 3 Actinomycetales;Dietziaceae;Dietzia 1 Actinomycetales;Geodermatophilaceae 1 Actinomycetales;Geodermatophilaceae;Blastococcus 3 Actinomycetales;Intrasporangiaceae;Janibacter 1 Actinomycetales;Intrasporangiaceae;Ornithinimicrobium 2 Actinomycetales;Microbacteriaceae 4 Actinomycetales;Microbacteriaceae;Leucobacter 2 Actinomycetales;Microbacteriaceae;Microbacterium 5 Actinomycetales;Microbacteriaceae;Zimmermannella 1 Actinomycetales;Micrococcaceae 2 Actinomycetales;Micrococcaceae;Arthrobacter 4 Actinomycetales;Micrococcaceae;Kocuria 1 Actinomycetales;Micrococcaceae;Micrococcus 1 Actinomycetales;Micrococcaceae;Nesterenkonia 1 Actinomycetales;Micrococcaceae;Rothia 2 Actinomycetales;Mycobacteriaceae;Mycobacterium 2 Actinomycetales;Nakamurellaceae 1 Actinomycetales;Nocardiaceae;Williamsia 1 Actinomycetales;Nocardioidaceae;Kribbella 1 Actinomycetales;Nocardioidaceae;Marmoricola 1 Actinomycetales;Nocardioidaceae;Nocardioides 2 Actinomycetales;Promicromonosporaceae;Promicromonospora 1 Actinomycetales;Propionibacteriaceae 1 Actinomycetales;Propionibacteriaceae;Friedmanniella 1 Actinomycetales;Propionibacteriaceae;Microlunatus 1
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Actinomycetales;Propionibacteriaceae;Propionibacterium 4 Actinomycetales;Pseudonocardiaceae;Actinomycetospora 2 Actinomycetales;Pseudonocardiaceae;Amycolatopsis 2 Actinomycetales;Pseudonocardiaceae;Pseudonocardia 4 Actinomycetales;Pseudonocardiaceae;Saccharopolyspora 1 Actinomycetales;Pseudonocardiaceae;Thermocrispum 1 Actinomycetales;Streptomycetaceae;Streptomyces 1 Actinomycetales;Streptosporangiaceae;Thermopolyspora 1 Actinomycetales;Tsukamurellaceae;Tsukamurella 1 Coriobacteriales;Coriobacteriaceae 10 Coriobacteriales;Coriobacteriaceae;Asaccharobacter 1 Coriobacteriales;Coriobacteriaceae;Atopobium 2 Coriobacteriales;Coriobacteriaceae;Collinsella 14 Coriobacteriales;Coriobacteriaceae;Coriobacterium 5 Coriobacteriales;Coriobacteriaceae;Eggerthella 2 Coriobacteriales;Coriobacteriaceae;Gordonibacter 2 Coriobacteriales;Coriobacteriaceae;Slackia 2 Nitriliruptorales;Nitriliruptoraceae;Nitriliruptor 1 Rubrobacterales;Rubrobacteraceae;Rubrobacter 4 Solirubrobacterales 4 Solirubrobacterales;Conexibacteraceae;Conexibacter 1 Solirubrobacterales;Patulibacteraceae;Patulibacter 1 Bacteria_incertae_sedis Ktedonobacterales;Ktedonobacteraceae;Ktedonobacter 1 Bacteroidetes Bacteroidetes 22 Bacteroidia;Bacteroidales 16 Bacteroidia;Bacteroidales;Bacteroidaceae;Bacteroides 44 Bacteroidia;Bacteroidales;Porphyromonadaceae;Dysgonomonas 1 Bacteroidia;Bacteroidales;Porphyromonadaceae;Odoribacter 3 Bacteroidia;Bacteroidales;Porphyromonadaceae;Parabacteroides 6 Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas 6 Bacteroidia;Bacteroidales;Prevotellaceae 5 Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella 12 Bacteroidia;Bacteroidales;Rikenellaceae;Alistipes 4 Flavobacteria;Flavobacteriales 1 Flavobacteria;Flavobacteriales;Flavobacteriaceae 12 Flavobacteria;Flavobacteriales;Flavobacteriaceae;Actibacter 1 Flavobacteria;Flavobacteriales;Flavobacteriaceae;Flavobacterium 6 Flavobacteria;Flavobacteriales;Flavobacteriaceae;Muricauda 2 Flavobacteria;Flavobacteriales;Flavobacteriaceae;Myroides 2 Flavobacteria;Flavobacteriales;Flavobacteriaceae;Psychroserpens 1 Flavobacteria;Flavobacteriales;Flavobacteriaceae;Winogradskyella 1 Sphingobacteria;Sphingobacteriales 6 Sphingobacteria;Sphingobacteriales;Chitinophagaceae 16 Sphingobacteria;Sphingobacteriales;Chitinophagaceae;Balneola 1 Sphingobacteria;Sphingobacteriales;Chitinophagaceae;Gracilimonas 1 Sphingobacteria;Sphingobacteriales;Cyclobacteriaceae;Algoriphagus 2 Sphingobacteria;Sphingobacteriales;Cyclobacteriaceae;Echinicola 1 Sphingobacteria;Sphingobacteriales;Cytophagaceae;Hymenobacter 2
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Sphingobacteria;Sphingobacteriales;Cytophagaceae;Leadbetterella 1 Sphingobacteria;Sphingobacteriales;Cytophagaceae;Spirosoma 1 Sphingobacteria;Sphingobacteriales;Rhodothermaceae;Rhodothermus 1 Sphingobacteria;Sphingobacteriales;Saprospiraceae 3 Sphingobacteria;Sphingobacteriales;Saprospiraceae;Aureispira 1 Sphingobacteria;Sphingobacteriales;Saprospiraceae;Haliscomenobacter 1 Sphingobacteria;Sphingobacteriales;Sphingobacteriaceae 3 Sphingobacteria;Sphingobacteriales;Sphingobacteriaceae;Mucilaginibacter 1 Sphingobacteria;Sphingobacteriales;Sphingobacteriaceae;Pedobacter 3 Sphingobacteria;Sphingobacteriales;Sphingobacteriaceae;Sphingobacterium 3 Chloroflexi Anaerolineae;Anaerolineales;Anaerolineaceae 1 Chloroflexi;Chloroflexi;Chloroflexales;Chloroflexaceae;Chloroflexus 1 Chloroflexi;Thermomicrobia 1 Cyanobacteria Cyanobacteria 3 Cyanobacteria;Chloroplast 2 Cyanobacteria;Chloroplast;Bacillariophyta 22 Cyanobacteria;Chloroplast;Streptophyta 4 Cyanobacteria;Family II;GpIIa 9 Cyanobacteria;Family IV;GpIV 1 Cyanobacteria;Family VII;GpVII 9 Cyanobacteria;Family X;GpX 1 Deferribacteres Deferribacteres;Deferribacterales;Deferribacteraceae;Mucispirillum 1 Deferribacteres;Deferribacterales;Deferribacterales_incertae_sedis;Caldithrix 1 Deinococcus-Thermus Deinococci;Thermales;Thermaceae;Thermus 1 Fibrobacteres Fibrobacteria;Fibrobacterales;Fibrobacteraceae;Fibrobacter 1 Firmicutes Firmicutes 13 Bacilli 2 Bacilli;Bacillales 6 Bacilli;Bacillales;Bacillaceae 1 Bacilli;Bacillales;Bacillaceae;Anoxybacillus 1 Bacilli;Bacillales;Bacillaceae;Bacillus 4 Bacilli;Bacillales;Bacillaceae;Caldalkalibacillus 1 Bacilli;Bacillales;Listeriaceae;Brochothrix 2 Bacilli;Bacillales;Paenibacillaceae;Paenibacillus 1 Bacilli;Bacillales;Paenibacillaceae;Thermobacillus 1 Bacilli;Bacillales;Planococcaceae;Planococcus 2 Bacilli;Bacillales;Planococcaceae;Planomicrobium 1 Bacilli;Bacillales;Staphylococcaceae 1 Bacilli;Bacillales;Staphylococcaceae;Gemella 3 Bacilli;Bacillales;Staphylococcaceae;Jeotgalicoccus 1 Bacilli;Bacillales;Staphylococcaceae;Staphylococcus 25 Bacilli;Lactobacillales 4 Bacilli;Lactobacillales;Aerococcaceae;Facklamia 2 Bacilli;Lactobacillales;Carnobacteriaceae;Carnobacterium 1
108
Bacilli;Lactobacillales;Carnobacteriaceae;Desemzia 2 Bacilli;Lactobacillales;Carnobacteriaceae;Granulicatella 9 Bacilli;Lactobacillales;Enterococcaceae;Enterococcus 8 Bacilli;Lactobacillales;Enterococcaceae;Vagococcus 2 Bacilli;Lactobacillales;Lactobacillaceae 1 Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus 14 Bacilli;Lactobacillales;Leuconostocaceae;Leuconostoc 1 Bacilli;Lactobacillales;Streptococcaceae 1 Bacilli;Lactobacillales;Streptococcaceae;Lactococcus 4 Bacilli;Lactobacillales;Streptococcaceae;Streptococcus 36 Clostridia 4 Clostridia;Clostridiales 84 Clostridia;Clostridiales;Clostridiaceae 1 Clostridia;Clostridiales;Clostridiaceae;Clostridium 5 Clostridia;Clostridiales;Eubacteriaceae 1 Clostridia;Clostridiales;Eubacteriaceae;Eubacterium 3 Clostridia;Clostridiales;Incertae Sedis XI 5 Clostridia;Clostridiales;Incertae Sedis XI;Anaerococcus 20 Clostridia;Clostridiales;Incertae Sedis XI;Finegoldia 4 Clostridia;Clostridiales;Incertae Sedis XI;Helcococcus 1 Clostridia;Clostridiales;Incertae Sedis XI;Parvimonas 7 Clostridia;Clostridiales;Incertae Sedis XI;Peptoniphilus 3 Clostridia;Clostridiales;Incertae Sedis XI;Tepidimicrobium 3 Clostridia;Clostridiales;Incertae Sedis XIII;Anaerovorax 2 Clostridia;Clostridiales;Incertae Sedis XIV;Blautia 24 Clostridia;Clostridiales;Lachnospiraceae 109 Clostridia;Clostridiales;Lachnospiraceae;Coprococcus 6 Clostridia;Clostridiales;Lachnospiraceae;Dorea 26 Clostridia;Clostridiales;Lachnospiraceae;Marvinbryantia 1 Clostridia;Clostridiales;Lachnospiraceae;Roseburia 15 Clostridia;Clostridiales;Lachnospiraceae;Shuttleworthia 1 Clostridia;Clostridiales;Peptostreptococcaceae 4 Clostridia;Clostridiales;Peptostreptococcaceae;Peptostreptococcus 3 Clostridia;Clostridiales;Ruminococcaceae 19 Clostridia;Clostridiales;Ruminococcaceae;Butyricicoccus 2 Clostridia;Clostridiales;Ruminococcaceae;Faecalibacterium 29 Clostridia;Clostridiales;Ruminococcaceae;Oscillibacter 5 Clostridia;Clostridiales;Ruminococcaceae;Ruminococcus 2 Clostridia;Clostridiales;Ruminococcaceae;Subdoligranulum 5 Clostridia;Clostridiales;Veillonellaceae 1 Clostridia;Clostridiales;Veillonellaceae;Dialister 2 Clostridia;Clostridiales;Veillonellaceae;Megamonas 1 Clostridia;Clostridiales;Veillonellaceae;Megasphaera 1 Clostridia;Clostridiales;Veillonellaceae;Phascolarctobacterium 2 Clostridia;Clostridiales;Veillonellaceae;Selenomonas 1 Clostridia;Clostridiales;Veillonellaceae;Veillonella 3 Erysipelotrichi;Erysipelotrichales;Erysipelotrichaceae 4 Erysipelotrichi;Erysipelotrichales;Erysipelotrichaceae;Allobaculum 1 Erysipelotrichi;Erysipelotrichales;Erysipelotrichaceae;Catenibacterium 1 Erysipelotrichi;Erysipelotrichales;Erysipelotrichaceae;Coprobacillus 3
109
Erysipelotrichi;Erysipelotrichales;Erysipelotrichaceae;Holdemania 2 Erysipelotrichi;Erysipelotrichales;Erysipelotrichaceae;Solobacterium 3 Fusobacteria Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae 2 Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium 10 Fusobacteria;Fusobacteriales;Leptotrichiaceae 1 Fusobacteria;Fusobacteriales;Leptotrichiaceae;Leptotrichia 2 Gemmatimonadetes Gemmatimonadetes;Gemmatimonadales;Gemmatimonadaceae;Gemmatimonas 1 Nitrospira Nitrospira;Nitrospirales;Nitrospiraceae;Nitrospira 1 Planctomycetes Planctomycetacia;Planctomycetales;Planctomycetaceae 2 Planctomycetacia;Planctomycetales;Planctomycetaceae;Gemmata 2 Planctomycetacia;Planctomycetales;Planctomycetaceae;Planctomyces 1 Proteobacteria Proteobacteria 21 Alphaproteobacteria 15 Alphaproteobacteria;Caulobacterales;Caulobacteraceae 1 Alphaproteobacteria;Caulobacterales;Caulobacteraceae;Asticcacaulis 1 Alphaproteobacteria;Caulobacterales;Caulobacteraceae;Brevundimonas 1 Alphaproteobacteria;Caulobacterales;Caulobacteraceae;Caulobacter 1 Alphaproteobacteria;Caulobacterales;Hyphomonadaceae;Maricaulis 1 Alphaproteobacteria;Rhizobiales 19 Alphaproteobacteria;Rhizobiales;Aurantimonadaceae;Aurantimonas 1 Alphaproteobacteria;Rhizobiales;Bradyrhizobiaceae;Bradyrhizobium 1 Alphaproteobacteria;Rhizobiales;Brucellaceae;Ochrobactrum 1 Alphaproteobacteria;Rhizobiales;Hyphomicrobiaceae 2 Alphaproteobacteria;Rhizobiales;Hyphomicrobiaceae;Hyphomicrobium 2 Alphaproteobacteria;Rhizobiales;Hyphomicrobiaceae;Zhangella 2 Alphaproteobacteria;Rhizobiales;Methylobacteriaceae;Methylobacterium 1 Alphaproteobacteria;Rhizobiales;Methylobacteriaceae;Microvirga 1 Alphaproteobacteria;Rhizobiales;Methylocystaceae 1 Alphaproteobacteria;Rhizobiales;Phyllobacteriaceae 2 Alphaproteobacteria;Rhizobiales;Phyllobacteriaceae;Defluvibacter 1 Alphaproteobacteria;Rhizobiales;Rhizobiaceae 1 Alphaproteobacteria;Rhizobiales;Rhizobiaceae;Rhizobium 1 Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae 30 Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae;Donghicola 1 Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae;Paracoccus 1 Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae;Rhodobacter 2 Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae;Roseovarius 2 Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae;Rubellimicrobium 1 Alphaproteobacteria;Rhodobacterales;Rhodobacteraceae;Silicibacter 1 Alphaproteobacteria;Rhodospirillales;Acetobacteraceae 3 Alphaproteobacteria;Rhodospirillales;Acetobacteraceae;Roseomonas 2 Alphaproteobacteria;Rhodospirillales;Rhodospirillaceae;Pelagibius 1 Alphaproteobacteria;Rhodospirillales;Rhodospirillaceae;Rhodovibrio 2 Alphaproteobacteria;Rhodospirillales;Rhodospirillaceae;Skermanella 1 Alphaproteobacteria;Rhodospirillales;Rhodospirillaceae;Tistrella 1
110
Alphaproteobacteria;Rickettsiales;SAR11;Pelagibacter 4 Alphaproteobacteria;Sphingomonadales 1 Alphaproteobacteria;Sphingomonadales;Erythrobacteraceae;Porphyrobacter 1 Alphaproteobacteria;Sphingomonadales;Sphingomonadaceae 2 Alphaproteobacteria;Sphingomonadales;Sphingomonadaceae;Sphingobium 2 Alphaproteobacteria;Sphingomonadales;Sphingomonadaceae;Sphingomonas 4 Alphaproteobacteria;Sphingomonadales;Sphingomonadaceae;Sphingopyxis 1 Betaproteobacteria 9 Betaproteobacteria;Burkholderiales 7 Betaproteobacteria;Burkholderiales;Alcaligenaceae;Achromobacter 2 Betaproteobacteria;Burkholderiales;Alcaligenaceae;Alcaligenes 1 Betaproteobacteria;Burkholderiales;Alcaligenaceae;Oligella 1 Betaproteobacteria;Burkholderiales;Alcaligenaceae;Parasutterella 1 Betaproteobacteria;Burkholderiales;Alcaligenaceae;Sutterella 5 Betaproteobacteria;Burkholderiales;Burkholderiaceae;Burkholderia 1 Betaproteobacteria;Burkholderiales;Burkholderiaceae;Cupriavidus 1 Betaproteobacteria;Burkholderiales;Burkholderiaceae;Limnobacter 1 Betaproteobacteria;Burkholderiales;Burkholderiaceae;Ralstonia 3 Betaproteobacteria;Burkholderiales;Burkholderiales_incertae_sedis;Methylibium 2 Betaproteobacteria;Burkholderiales;Comamonadaceae 1 Betaproteobacteria;Burkholderiales;Comamonadaceae;Acidovorax 1 Betaproteobacteria;Burkholderiales;Comamonadaceae;Comamonas 1 Betaproteobacteria;Burkholderiales;Comamonadaceae;Curvibacter 1 Betaproteobacteria;Burkholderiales;Comamonadaceae;Delftia 1 Betaproteobacteria;Burkholderiales;Comamonadaceae;Pelomonas 1 Betaproteobacteria;Burkholderiales;Comamonadaceae;Roseateles 1 Betaproteobacteria;Burkholderiales;Comamonadaceae;Variovorax 2 Betaproteobacteria;Burkholderiales;Oxalobacteraceae 2 Betaproteobacteria;Burkholderiales;Oxalobacteraceae;Duganella 1 Betaproteobacteria;Burkholderiales;Oxalobacteraceae;Herbaspirillum 2 Betaproteobacteria;Burkholderiales;Oxalobacteraceae;Herminiimonas 1 Betaproteobacteria;Burkholderiales;Oxalobacteraceae;Janthinobacterium 1 Betaproteobacteria;Burkholderiales;Oxalobacteraceae;Massilia 3 Betaproteobacteria;Hydrogenophilales;Hydrogenophilaceae;Thiobacillus 1 Betaproteobacteria;Neisseriales;Neisseriaceae 1 Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria 4 Betaproteobacteria;Rhodocyclales;Rhodocyclaceae;Thauera 1 Betaproteobacteria;Rhodocyclales;Rhodocyclaceae;Zoogloea 1 Deltaproteobacteria 8 Deltaproteobacteria;Desulfobacterales 2 Deltaproteobacteria;Desulfobacterales;Desulfobacteraceae 10 Deltaproteobacteria;Desulfobacterales;Desulfobacteraceae;Desulfobacterium 1 Deltaproteobacteria;Desulfobacterales;Desulfobacteraceae;Desulfosarcina 1 Deltaproteobacteria;Desulfobacterales;Desulfobacteraceae;Desulfotignum 2 Deltaproteobacteria;Desulfobacterales;Desulfobulbaceae 3 Deltaproteobacteria;Desulfovibrionales;Desulfohalobiaceae 1 Deltaproteobacteria;Desulfuromonadales 1 Deltaproteobacteria;Desulfuromonadales;Desulfuromonadaceae;Desulfuromusa 1 Deltaproteobacteria;Desulfuromonadales;Desulfuromonadaceae;Malonomonas 1 Deltaproteobacteria;Myxococcales 1
111
Deltaproteobacteria;Myxococcales;Cystobacteraceae 1 Deltaproteobacteria;Myxococcales;Nannocystaceae 2 Deltaproteobacteria;Myxococcales;Polyangiaceae 1 Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Arcobacter 2 Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter 2 Gammaproteobacteria 38 Gammaproteobacteria;Acidithiobacillales;Acidithiobacillaceae;Acidithiobacillus 2 Gammaproteobacteria;Alteromonadales;Alteromonadaceae 1 Gammaproteobacteria;Alteromonadales;Alteromonadaceae;Haliea 1 Gammaproteobacteria;Alteromonadales;Alteromonadaceae;Marinimicrobium 2 Gammaproteobacteria;Alteromonadales;Alteromonadaceae;Marinobacter 2 Gammaproteobacteria;Alteromonadales;Alteromonadaceae;Marinobacterium 1 Gammaproteobacteria;Alteromonadales;Idiomarinaceae;Pseudidiomarina 1 Gammaproteobacteria;Alteromonadales;Pseudoalteromonadaceae;Pseudoalteromonas 3 Gammaproteobacteria;Alteromonadales;Psychromonadaceae;Psychromonas 1 Gammaproteobacteria;Chromatiales 1 Gammaproteobacteria;Chromatiales;Chromatiaceae 1 Gammaproteobacteria;Chromatiales;Chromatiaceae;Halochromatium 1 Gammaproteobacteria;Chromatiales;Chromatiaceae;Rheinheimera 1 Gammaproteobacteria;Chromatiales;Chromatiaceae;Thiohalocapsa 1 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae 12 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Citrobacter 1 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Escherichia/Shigella 9 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Morganella 3 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Pantoea 1 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Proteus 2 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Providencia 1 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Raoultella 2 Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Serratia 1 Gammaproteobacteria;Gammaproteobacteria_incertae_sedis;Solimonas 1 Gammaproteobacteria;Methylococcales;Methylococcaceae 1 Gammaproteobacteria;Oceanospirillales 1 Gammaproteobacteria;Oceanospirillales;Alcanivoracaceae;Alcanivorax 3 Gammaproteobacteria;Oceanospirillales;Oceanospirillaceae;Marinomonas 1 Gammaproteobacteria;Pasteurellales;Pasteurellaceae 4 Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter 1 Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Haemophilus 4 Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Pasteurella 1 Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter 11 Gammaproteobacteria;Pseudomonadales;Pseudomonadaceae;Pseudomonas 10 Gammaproteobacteria;Vibrionales;Vibrionaceae 3 Gammaproteobacteria;Xanthomonadales;Xanthomonadaceae 3 Gammaproteobacteria;Xanthomonadales;Xanthomonadaceae;Dyella 1 Gammaproteobacteria;Xanthomonadales;Xanthomonadaceae;Luteibacter 1 Gammaproteobacteria;Xanthomonadales;Xanthomonadaceae;Lysobacter 1 Gammaproteobacteria;Xanthomonadales;Xanthomonadaceae;Pseudoxanthomonas 1 Gammaproteobacteria;Xanthomonadales;Xanthomonadaceae;Rhodanobacter 2 Gammaproteobacteria;Xanthomonadales;Xanthomonadaceae;Stenotrophomonas 9 Spirochaetes Spirochaetes;Spirochaetales 1
112
Spirochaetes;Spirochaetales;Spirochaetaceae;Spirochaeta 5 Spirochaetes;Spirochaetales;Spirochaetaceae;Treponema 1 Synergistetes Synergistia;Synergistales;Synergistaceae 1 Tenericutes Mollicutes;Entomoplasmatales;Spiroplasmataceae;Spiroplasma 1 Mollicutes;Mycoplasmatales;Mycoplasmataceae;Mycoplasma 1 TM7 TM7_genera_incertae_sedis 2 Verrucomicrobia Opitutae 1 Opitutae;Opitutales;Opitutaceae;Opitutus 2 Opitutae;Puniceicoccales;Puniceicoccaceae 2 Opitutae;Puniceicoccales;Puniceicoccaceae;Pelagicoccus 1 Verrucomicrobiae;Verrucomicrobiales;Verrucomicrobiaceae;Akkermansia 1
Unclassified 28 Grand Total 1626