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The physiological basis of disease tolerance in insects
COIS 514 1–4
Available online at www.sciencedirect.com
ScienceDirect 1 2 3Q1
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The physiological basis of disease tolerance in insects Michelle M Lissner and David S Schneider Immunology textbooks teach us about the ways hosts can recognize and kill microbes but leave out something important: the mechanisms used to survive infections. Survival depends on more than simply detecting and eliminating microbes; it requires that we prevent and repair the damage caused by pathogens and the immune response. Recent work in insects is helping to build our understanding of this aspect of pathology, called disease tolerance. Here we discuss papers that explore disease tolerance using theoretical, population genetics, and mechanistic approaches.
Address 14 Department of Microbiology and Immunology, Stanford University, 15Q2 Stanford, CA 94305, United States Corresponding author: Schneider, David S ([email protected])
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Current Opinion in Insect Science 2018, 29:xx–yy
17
This review comes from a themed issue on Molecular physiology
18
Edited by Pedro L Oliveira and Fernando G Noriega
19
https://doi.org/10.1016/j.cois.2018.09.004
20
2214-5745/ã 2018 Elsevier Ltd. All rights reserved.
21
Introduction
22
Hosts can respond to infection in three ways: avoidance, resistance, and tolerance [1]. Avoidance mechanisms prevent infection by limiting interactions with the pathogen in the first place; for example, public health measures aimed at decreasing pathogen exposure are a learned behavioral avoidance mechanism. Resistance mechanisms reduce pathogen loads, and many successful therapeutic interventions like vaccines and antibiotics augment or replace our natural resistance. Disease tolerance mechanisms alter the dose response of health with respect to microbe load; thus, disease tolerance treatments improve symptoms without necessarily altering pathogen loads.
23 24 25 26 27 28 29 30 31 32 33 34
35 36 37 38 39 40
Theories about how disease tolerance might evolve, the measurements of variation in disease tolerance across host strains, and individual disease tolerance mechanisms have been uncovered and pushed this developing field forward [2–11]. Together, these data give us a piecemeal view of disease tolerance; recent work has started to build a more www.sciencedirect.com
solid foundation and determine molecular mechanisms behind disease tolerance (Figure 1).
41
A simple mathematical model to describe infection
43
Now-classical models of infectious disease by Anderson and May describe how a growing pathogen interacts with an immune response [12]. Such models describe those aspects of infection well, but leave out health unless it is directly related to a resistance mechanism, like the loss of T cells in AIDS [13]. Louie et al. published a relatively simple model that adds health to these equations [14]. The model proposes that health can be negatively impacted by either the immune response or another route that does not feed back on microbe load. Experimental data support this model by demonstrating that infection outcome changes in ways the model predicts for different fruit fly and microbe variants [14]. Louie et al. also found that the disease tolerance curve describing the relationship between microbe load and health is nonlinear, as other groups have found in both bacterial and viral infections [15–17]. Disease tolerance curves are not necessarily linear [18,19], but linear analysis of nonlinear curves misses important variables [15,20,21]. Overall, this framework can unify observations from different experimental systems and guide mechanistic studies.
45
The mathematical model also allows us to identify variables that will affect resistance, disease tolerance, or both. Many variables do not feed back on microbe growth, and, if changed, would be expected to cause pure changes in disease tolerance. Variables that alter microbe growth will certainly change resistance, but should also be expected to change disease tolerance if the immune response has an appreciable cost [14].
66
The model suggests a new conceptualization of disease tolerance. This systems-level view of infection emphasizes that processes, not specific proteins, determine tolerance. Genes are relevant only inasmuch as they affect these greater processes. In this review, for example, we highlight secretory stress and metabolism as two processes that affect disease tolerance. A recent excellent paper by Troha et al. found that CrebA minimizes secretory stress, which improves disease tolerance to infection [22]. Because other proteins may theoretically also limit secretory stress during infection, the model emphasizes the process of minimizing secretory stress over the specific genes involved. Similarly, Dionne et al. identified specific components of the insulin signaling pathway that contribute to disease tolerance [23]; the Louie et al. model focuses on the role of insulin signaling
74
Current Opinion in Insect Science 2018, 29:1–4
Please cite this article in press as: Lissner MM, Schneider DS: The physiological basis of disease tolerance in insects, Curr Opin Insect Sci (2018), https://doi.org/10.1016/j.cois.2018.09.004
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COIS 514 1–4
2 Molecular physiology
Figure 1
Health
(a) Disease tolerance
(b) Theories
(c) Mechanisms
Diverse populations
Secretory stress
Mathematical models
Metabolism
Microbe load
Current Opinion in Insect Science
Recent work in disease tolerance. (a) Work in the field of disease tolerance has led to (b) the development of new theoretical tools to measure disease tolerance and (c) mechanistic understanding of the role of secretory stress and metabolism in disease tolerance.
93
in disease tolerance rather than particular genes. Though this top-down approach emphasizes processes rather than mechanisms, it does not discount the value of mechanistic exploration of disease tolerance.
The genetic architecture of tolerance
Secretory system stress as a regulator of tolerance
128
94 95
Disease tolerance is a property of a population [21] and can be difficult to measure carefully. Because disease tolerance is the dose response curve of health to microbes, experimenters need to measure both health and microbes, as well as the response to a range of microbe loads [14,21]. Unfortunately, this approach multiplies effort by several fold and becomes impossible if one wants to measure a large number of genetic variants. Howick and Lazzaro recently took a population genetics approach to determine the genetic basis of variation in tolerance and demonstrated a useful shortcut in measuring disease tolerance. The authors screened a group of diverse inbred lines of Drosophila melanogaster and identified SNPs that correlated with changes in tolerance. Rather than testing multiple pathogen doses, they tested all fly strains at a single pathogen dose, generated a tolerance curve that best fit all strains, and identified strains that deviated from the curve. They validated five genes containing putative tolerance SNPS by knocking down gene expression and observing a tolerance phenotype [17]. Infection did not modulate expression of these genes, suggesting that focusing only on transcriptionally regulated genes may overlook regulators of tolerance. Indeed, tolerance gene expression is often unaltered during infection [20,23,24], with notable exceptions, including CrebA recently identified by Troha et al. [22]. The five tolerance genes identified by Howick and Lazzaro suggest several tolerance mechanisms that fit into the mathematical model proposed by Louie et al. [14]. The gene grainy head, for example, has been studied previously
Immune responses can be costly to hosts in several ways. The process of generating an immune response is energetically costly [27]; hosts also incur damage from both mounting an immune response and the immune response itself. Several studies have identified endoplasmic reticulum (ER) stress as a source of damage from producing an immune response. In Caenorhabditis elegans, infection with Pseudomonas aeruginosa induces the Unfolded Protein Response (UPR) via X-box binding protein 1 (XBP-1). Infected worms lacking xbp-1 are unable to induce the UPR, display signs of ER stress, and succumb to P. aeruginosa infection [28]. Though microbe loads were not measured, this experiment has the appearance of a tolerance response; the Louie et al. model predicts that limiting the effects of the immune response on host health, as illustrated by this XBP-1-mediated protection from ER stress, would increase tolerance. Recent work by Troha et al. confirms this hypothesis. By comparing the transcriptional profiles of fruit flies infected with a panel of bacteria, the authors identified a core gene set induced by bacterial infection [22]. Among these genes was the transcription factor CrebA, the sole Drosophila member of the Creb3-like transcription factor family, which regulates secretion [29]. CrebA knockdown flies have decreased tolerance to infection, altered expression of secretion genes, and evidence of ER stress. Decreasing ER stress rescued the tolerance defect of CrebA mutants [22]. The parallels between worms and flies suggest that the induction of ER stress by immune activation, and host mechanisms to mitigate ER stress, may be conserved
130
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Current Opinion in Insect Science 2018, 29:1–4
for its role in regulating wound repair [25], an obvious physiological process that should produce a tolerance phenotype [14,26].
125
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Please cite this article in press as: Lissner MM, Schneider DS: The physiological basis of disease tolerance in insects, Curr Opin Insect Sci (2018), https://doi.org/10.1016/j.cois.2018.09.004
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The physiological basis of disease tolerance in insects Lissner and Schneider 3
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across species. More broadly, it is likely that hosts rely on a variety of mechanisms to limit damage from immune responses.
161
Metabolism and disease outcome
162
A common motif that emerges across tolerance studies is the close relationship between metabolism and infection outcomes. Insects experience significant metabolic changes during infection, including anorexia [4,30], depletion of glycogen and triglyceride energy reserves [23,31], altered insulin signaling [23], and broad changes in metabolite levels [31]. Transcriptional analyses of infected flies consistently identify broad changes in metabolism [14,22–24]. Mycobacterium marinum infection downregulates many genes involved in glycogen synthesis and degradation [23], whereas Listeria monocytogenes infection causes changes in the transcription of enzymes required for fatty acid beta oxidation [14]; Troha et al. also observe pathogen-specific changes in transcription of genes regulating metabolic processes [22]. The model by Louie et al. proposes that limiting these metabolic changes may improve disease tolerance, and experimental evidence supports this hypothesis. Flies infected with M. marinum have altered insulin signaling due to activation of the transcription factor dFOXO. Infected dFOXO mutant flies, however, have improved readouts of insulin signaling and prolonged survival at an equivalent microbe load [23]. This study provided early evidence that metabolism can impact disease tolerance.
158 159
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It is clear from the mathematical model of infection that resistance and tolerance are necessarily linked, and we might expect that both could be altered by the same environmental factors [14]. Loss of the metabolic transcription factor MEF2, which drives expression of metabolic genes in healthy flies and immune genes in infected flies, alters both tolerance and resistance to M. marinum [24]. Similarly, a mutation in the gustatory receptor gr28b, which regulates food intake, increases tolerance to Salmonella typhimurium by mimicking infection-induced anorexia. However, the same gr28b mutation decreases resistance to L. monocytogenes [4], demonstrating how a single change has pathogen-specific effects [2,3,32]. Altering metabolism can also vary resistance; dietary glucose levels modulate the immune response during Providencia rettgeri infection, revealing that resistance can be regulated through mechanisms not typically viewed as part of the ‘immune response’ [33]. Thus, although metabolism can alter tolerance, the relationship between metabolism and disease outcome is often complex.
205
Conclusion
206
Recent work in Drosophila is helping to develop the field of disease tolerance. This is useful because disease tolerance has the potential to teach us new insights about the relationship between insects and pathogens, especially by highlighting previously overlooked biology. Moreover,
207Q4 208 209 210
www.sciencedirect.com
pioneering studies of disease tolerance in insects will lead to new ways of modulating infections in all systems, without concentrating on treatments that will inevitably drive antibiotic resistance in pathogens. These new treatments focus on noncanonical responses to infection, including cellular stress and wound repair. Furthermore, many of these experiments implicate the role of metabolic changes in disease tolerance, a ripe area of exploration for the future.
211
References
219
1.
Medzhitov R, Schneider DS, Soares MP: Disease tolerance as a defense strategy. Science 2012, 335:936-941.
220 221
2.
Wang A et al.: Opposing effects of fasting metabolism on tissue tolerance in bacterial and viral inflammation. Cell 2016, 166:1512-1525.e12.
222 223 224
3.
Ayres JS, Schneider DS: A signaling protease required for melanization in Drosophila affects resistance and tolerance of infections. PLoS Biol 2008, 6:2764-2773.
225 226 227
4.
Ayres JS, Schneider DS: The role of anorexia in resistance and tolerance to infections in Drosophila. PLoS Biol 2009, 7: e1000150.
228 229 230
5.
Schieber AM et al.: Disease tolerance mediated by microbiome E. coli involves inflammasome and IGF-1 signaling. Science 2015, 350:558-563.
231 232 233
6.
Roy BA, Kirchner JW: Evolutionary dynamics of pathogen resistance and tolerance. Evolution 2000, 54:51-63.
234 235
7.
Seixas E et al.: Heme oxygenase-1 affords protection against noncerebral forms of severe malaria. Proc Natl Acad Sci U S A 2009, 106:15837-15842.
236 237 238
8.
Soares MP, Teixeira L, Moita LF: Disease tolerance and immunity in host protection against infection. Nat Rev Immunol 2017, 17:83-96.
239 240 241
9.
Jamieson AM et al.: Role of tissue protection in lethal respiratory viral-bacterial coinfection. Science 2013, 340:1230-1234.
242 243 244
212 213 214 215 216 217 218
10. Best A, White A, Boots M: Maintenance of host variation in tolerance to pathogens and parasites. Proc Natl Acad Sci U S A 2008, 105:20786-20791.
245 246 247
11. Best A, White A, Boots M: The coevolutionary implications of host tolerance. Evolution 2014, 68:1426-1435.
248 249
12. Anderson RM, May RM: Infectious Diseases of Humans: Dynamics and Control. Oxford Science Publications. Oxford; New York: Oxford University Press; 1991. viii, 757 p..
250 251
13. Regoes RR et al.: Disentangling human tolerance and resistance against HIV. PLoS Biol 2014, 12:e1001951.
252 253
14. Louie A et al.: How many parameters does it take to describe Q5254 255 disease tolerance? PLoS Biol 2016, 14:e1002435. 256 This study developed a mathematical model to describe interactions 257 between hosts and microbes during infection and presents a conceptual 258 framework for integrating studies of tolerance in multiple systems. 15. Gupta V, Vale PF: Nonlinear disease tolerance curves reveal distinct components of host responses to viral infection. R Soc Open Sci 2017, 4:170342.
259 260 261
16. Howick VM, Lazzaro BP: Genotype and diet shape resistance and tolerance across distinct phases of bacterial infection. BMC Evol Biol 2014, 14:56.
262 263 264
17. Howick VM, Lazzaro BP: The genetic architecture of defence as resistance to and tolerance of bacterial infection in Drosophila melanogaster. Mol Ecol 2017, 26:1533-1546. This study demonstrates that population genetics approaches can identify genes that regulate disease tolerance and defined a new strategy to measure tolerance in a population.
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Current Opinion in Insect Science 2018, 29:1–4
Please cite this article in press as: Lissner MM, Schneider DS: The physiological basis of disease tolerance in insects, Curr Opin Insect Sci (2018), https://doi.org/10.1016/j.cois.2018.09.004
COIS 514 1–4
4 Molecular physiology
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18. Ra˚berg L, Sim D, Read AF: Disentangling genetic variation for resistance and tolerance to infectious diseases in animals. Science 2007, 318:812-814.
26. Soares MP, Gozzelino R, Weis S: Tissue damage control in disease tolerance. Trends Immunol 2014, 35:483-494.
296 297
274 275
19. Dillman AR, Schneider DS: Defining resistance and tolerance to cancer. Cell Rep 2015, 13:884-887.
27. Moret Y, Schmid-Hempel P: Survival for immunity: the price of immune system activation for bumblebee workers. Science 2000, 290:1166-1168.
298 299 300
276 277 278
20. Merkling SH et al.: The epigenetic regulator G9a mediates tolerance to RNA virus infection in Drosophila. PLoS Pathog 2015, 11:e1004692.
28. Richardson CE, Kooistra T, Kim DH: An essential role for XBP-1 in host protection against immune activation in C. elegans. Nature 2010, 463:1092-1095.
301 302 303
279 280
21. Simms E: Defining tolerance as a norm of reaction. Evol Ecol 2000, 14:563-570.
281 282 283 284 285 286 287
22. Troha K et al.: Comparative transcriptomics reveals CrebA as a novel regulator of infection tolerance in D. melanogaster. PLoS Pathog 2018, 14(2):e1006847. This work defined a set of core response genes to bacterial infection in Drosophila melanogaster, including CrebA, which promotes disease tolerance by reducing cellular stress caused by mounting an immune response.
29. Fox RM, Hanlon CD, Andrew DJ: The CrebA/Creb3-like transcription factors are major and direct regulators of secretory capacity. J Cell Biol 2010, 191:479-492.
304 305 306
30. Adamo SA: Parasitic suppression of feeding in the tobacco hornworm, Manduca sexta: parallels with feeding depression after an immune challenge. Arch Insect Biochem Physiol 2005, 60:185-197.
307 308 309 310
288 289 290
23. Dionne MS et al.: Akt and FOXO dysregulation contribute to infection-induced wasting in Drosophila. Curr Biol 2006, 16:1977-1985.
31. Chambers MC, Song KH, Schneider DS: Listeria monocytogenes infection causes metabolic shifts in Drosophila melanogaster. PLoS One 2012, 7:e50679.
311 312 313
291 292
24. Clark RI et al.: MEF2 is an in vivo immune-metabolic switch. Cell 2013, 155:435-447.
32. Cumnock K et al.: Host energy source is important for disease tolerance to malaria. Curr Biol 2018, 28:1635-1642.e3.
314 315
293 294 295
25. Mace KA, Pearson JC, McGinnis W: An epidermal barrier wound repair pathway in Drosophila is mediated by grainy head. Science 2005, 308:381-385.
33. Unckless RL, Rottschaefer SM, Lazzaro BP: The complex contributions of genetics and nutrition to immunity in Drosophila melanogaster. PLoS Genet 2015, 11:e1005030.
316 317 318
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Please cite this article in press as: Lissner MM, Schneider DS: The physiological basis of disease tolerance in insects, Curr Opin Insect Sci (2018), https://doi.org/10.1016/j.cois.2018.09.004
Available online at www.sciencedirect.com
ScienceDirect 1 2 3Q1
4 5 6 7 8 9 10 11 12 13
The physiological basis of disease tolerance in insects Michelle M Lissner and David S Schneider Immunology textbooks teach us about the ways hosts can recognize and kill microbes but leave out something important: the mechanisms used to survive infections. Survival depends on more than simply detecting and eliminating microbes; it requires that we prevent and repair the damage caused by pathogens and the immune response. Recent work in insects is helping to build our understanding of this aspect of pathology, called disease tolerance. Here we discuss papers that explore disease tolerance using theoretical, population genetics, and mechanistic approaches.
Address 14 Department of Microbiology and Immunology, Stanford University, 15Q2 Stanford, CA 94305, United States Corresponding author: Schneider, David S ([email protected])
16
Current Opinion in Insect Science 2018, 29:xx–yy
17
This review comes from a themed issue on Molecular physiology
18
Edited by Pedro L Oliveira and Fernando G Noriega
19
https://doi.org/10.1016/j.cois.2018.09.004
20
2214-5745/ã 2018 Elsevier Ltd. All rights reserved.
21
Introduction
22
Hosts can respond to infection in three ways: avoidance, resistance, and tolerance [1]. Avoidance mechanisms prevent infection by limiting interactions with the pathogen in the first place; for example, public health measures aimed at decreasing pathogen exposure are a learned behavioral avoidance mechanism. Resistance mechanisms reduce pathogen loads, and many successful therapeutic interventions like vaccines and antibiotics augment or replace our natural resistance. Disease tolerance mechanisms alter the dose response of health with respect to microbe load; thus, disease tolerance treatments improve symptoms without necessarily altering pathogen loads.
23 24 25 26 27 28 29 30 31 32 33 34
35 36 37 38 39 40
Theories about how disease tolerance might evolve, the measurements of variation in disease tolerance across host strains, and individual disease tolerance mechanisms have been uncovered and pushed this developing field forward [2–11]. Together, these data give us a piecemeal view of disease tolerance; recent work has started to build a more www.sciencedirect.com
solid foundation and determine molecular mechanisms behind disease tolerance (Figure 1).
41
A simple mathematical model to describe infection
43
Now-classical models of infectious disease by Anderson and May describe how a growing pathogen interacts with an immune response [12]. Such models describe those aspects of infection well, but leave out health unless it is directly related to a resistance mechanism, like the loss of T cells in AIDS [13]. Louie et al. published a relatively simple model that adds health to these equations [14]. The model proposes that health can be negatively impacted by either the immune response or another route that does not feed back on microbe load. Experimental data support this model by demonstrating that infection outcome changes in ways the model predicts for different fruit fly and microbe variants [14]. Louie et al. also found that the disease tolerance curve describing the relationship between microbe load and health is nonlinear, as other groups have found in both bacterial and viral infections [15–17]. Disease tolerance curves are not necessarily linear [18,19], but linear analysis of nonlinear curves misses important variables [15,20,21]. Overall, this framework can unify observations from different experimental systems and guide mechanistic studies.
45
The mathematical model also allows us to identify variables that will affect resistance, disease tolerance, or both. Many variables do not feed back on microbe growth, and, if changed, would be expected to cause pure changes in disease tolerance. Variables that alter microbe growth will certainly change resistance, but should also be expected to change disease tolerance if the immune response has an appreciable cost [14].
66
The model suggests a new conceptualization of disease tolerance. This systems-level view of infection emphasizes that processes, not specific proteins, determine tolerance. Genes are relevant only inasmuch as they affect these greater processes. In this review, for example, we highlight secretory stress and metabolism as two processes that affect disease tolerance. A recent excellent paper by Troha et al. found that CrebA minimizes secretory stress, which improves disease tolerance to infection [22]. Because other proteins may theoretically also limit secretory stress during infection, the model emphasizes the process of minimizing secretory stress over the specific genes involved. Similarly, Dionne et al. identified specific components of the insulin signaling pathway that contribute to disease tolerance [23]; the Louie et al. model focuses on the role of insulin signaling
74
Current Opinion in Insect Science 2018, 29:1–4
Please cite this article in press as: Lissner MM, Schneider DS: The physiological basis of disease tolerance in insects, Curr Opin Insect Sci (2018), https://doi.org/10.1016/j.cois.2018.09.004
42
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46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
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COIS 514 1–4
2 Molecular physiology
Figure 1
Health
(a) Disease tolerance
(b) Theories
(c) Mechanisms
Diverse populations
Secretory stress
Mathematical models
Metabolism
Microbe load
Current Opinion in Insect Science
Recent work in disease tolerance. (a) Work in the field of disease tolerance has led to (b) the development of new theoretical tools to measure disease tolerance and (c) mechanistic understanding of the role of secretory stress and metabolism in disease tolerance.
93
in disease tolerance rather than particular genes. Though this top-down approach emphasizes processes rather than mechanisms, it does not discount the value of mechanistic exploration of disease tolerance.
The genetic architecture of tolerance
Secretory system stress as a regulator of tolerance
128
94 95
Disease tolerance is a property of a population [21] and can be difficult to measure carefully. Because disease tolerance is the dose response curve of health to microbes, experimenters need to measure both health and microbes, as well as the response to a range of microbe loads [14,21]. Unfortunately, this approach multiplies effort by several fold and becomes impossible if one wants to measure a large number of genetic variants. Howick and Lazzaro recently took a population genetics approach to determine the genetic basis of variation in tolerance and demonstrated a useful shortcut in measuring disease tolerance. The authors screened a group of diverse inbred lines of Drosophila melanogaster and identified SNPs that correlated with changes in tolerance. Rather than testing multiple pathogen doses, they tested all fly strains at a single pathogen dose, generated a tolerance curve that best fit all strains, and identified strains that deviated from the curve. They validated five genes containing putative tolerance SNPS by knocking down gene expression and observing a tolerance phenotype [17]. Infection did not modulate expression of these genes, suggesting that focusing only on transcriptionally regulated genes may overlook regulators of tolerance. Indeed, tolerance gene expression is often unaltered during infection [20,23,24], with notable exceptions, including CrebA recently identified by Troha et al. [22]. The five tolerance genes identified by Howick and Lazzaro suggest several tolerance mechanisms that fit into the mathematical model proposed by Louie et al. [14]. The gene grainy head, for example, has been studied previously
Immune responses can be costly to hosts in several ways. The process of generating an immune response is energetically costly [27]; hosts also incur damage from both mounting an immune response and the immune response itself. Several studies have identified endoplasmic reticulum (ER) stress as a source of damage from producing an immune response. In Caenorhabditis elegans, infection with Pseudomonas aeruginosa induces the Unfolded Protein Response (UPR) via X-box binding protein 1 (XBP-1). Infected worms lacking xbp-1 are unable to induce the UPR, display signs of ER stress, and succumb to P. aeruginosa infection [28]. Though microbe loads were not measured, this experiment has the appearance of a tolerance response; the Louie et al. model predicts that limiting the effects of the immune response on host health, as illustrated by this XBP-1-mediated protection from ER stress, would increase tolerance. Recent work by Troha et al. confirms this hypothesis. By comparing the transcriptional profiles of fruit flies infected with a panel of bacteria, the authors identified a core gene set induced by bacterial infection [22]. Among these genes was the transcription factor CrebA, the sole Drosophila member of the Creb3-like transcription factor family, which regulates secretion [29]. CrebA knockdown flies have decreased tolerance to infection, altered expression of secretion genes, and evidence of ER stress. Decreasing ER stress rescued the tolerance defect of CrebA mutants [22]. The parallels between worms and flies suggest that the induction of ER stress by immune activation, and host mechanisms to mitigate ER stress, may be conserved
130
90 91 92
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Current Opinion in Insect Science 2018, 29:1–4
for its role in regulating wound repair [25], an obvious physiological process that should produce a tolerance phenotype [14,26].
125
www.sciencedirect.com
Please cite this article in press as: Lissner MM, Schneider DS: The physiological basis of disease tolerance in insects, Curr Opin Insect Sci (2018), https://doi.org/10.1016/j.cois.2018.09.004
126 127
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131 132 133 134 135 136
137 138 139
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The physiological basis of disease tolerance in insects Lissner and Schneider 3
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across species. More broadly, it is likely that hosts rely on a variety of mechanisms to limit damage from immune responses.
161
Metabolism and disease outcome
162
A common motif that emerges across tolerance studies is the close relationship between metabolism and infection outcomes. Insects experience significant metabolic changes during infection, including anorexia [4,30], depletion of glycogen and triglyceride energy reserves [23,31], altered insulin signaling [23], and broad changes in metabolite levels [31]. Transcriptional analyses of infected flies consistently identify broad changes in metabolism [14,22–24]. Mycobacterium marinum infection downregulates many genes involved in glycogen synthesis and degradation [23], whereas Listeria monocytogenes infection causes changes in the transcription of enzymes required for fatty acid beta oxidation [14]; Troha et al. also observe pathogen-specific changes in transcription of genes regulating metabolic processes [22]. The model by Louie et al. proposes that limiting these metabolic changes may improve disease tolerance, and experimental evidence supports this hypothesis. Flies infected with M. marinum have altered insulin signaling due to activation of the transcription factor dFOXO. Infected dFOXO mutant flies, however, have improved readouts of insulin signaling and prolonged survival at an equivalent microbe load [23]. This study provided early evidence that metabolism can impact disease tolerance.
158 159
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180 181 182 183 184
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It is clear from the mathematical model of infection that resistance and tolerance are necessarily linked, and we might expect that both could be altered by the same environmental factors [14]. Loss of the metabolic transcription factor MEF2, which drives expression of metabolic genes in healthy flies and immune genes in infected flies, alters both tolerance and resistance to M. marinum [24]. Similarly, a mutation in the gustatory receptor gr28b, which regulates food intake, increases tolerance to Salmonella typhimurium by mimicking infection-induced anorexia. However, the same gr28b mutation decreases resistance to L. monocytogenes [4], demonstrating how a single change has pathogen-specific effects [2,3,32]. Altering metabolism can also vary resistance; dietary glucose levels modulate the immune response during Providencia rettgeri infection, revealing that resistance can be regulated through mechanisms not typically viewed as part of the ‘immune response’ [33]. Thus, although metabolism can alter tolerance, the relationship between metabolism and disease outcome is often complex.
205
Conclusion
206
Recent work in Drosophila is helping to develop the field of disease tolerance. This is useful because disease tolerance has the potential to teach us new insights about the relationship between insects and pathogens, especially by highlighting previously overlooked biology. Moreover,
207Q4 208 209 210
www.sciencedirect.com
pioneering studies of disease tolerance in insects will lead to new ways of modulating infections in all systems, without concentrating on treatments that will inevitably drive antibiotic resistance in pathogens. These new treatments focus on noncanonical responses to infection, including cellular stress and wound repair. Furthermore, many of these experiments implicate the role of metabolic changes in disease tolerance, a ripe area of exploration for the future.
211
References
219
1.
Medzhitov R, Schneider DS, Soares MP: Disease tolerance as a defense strategy. Science 2012, 335:936-941.
220 221
2.
Wang A et al.: Opposing effects of fasting metabolism on tissue tolerance in bacterial and viral inflammation. Cell 2016, 166:1512-1525.e12.
222 223 224
3.
Ayres JS, Schneider DS: A signaling protease required for melanization in Drosophila affects resistance and tolerance of infections. PLoS Biol 2008, 6:2764-2773.
225 226 227
4.
Ayres JS, Schneider DS: The role of anorexia in resistance and tolerance to infections in Drosophila. PLoS Biol 2009, 7: e1000150.
228 229 230
5.
Schieber AM et al.: Disease tolerance mediated by microbiome E. coli involves inflammasome and IGF-1 signaling. Science 2015, 350:558-563.
231 232 233
6.
Roy BA, Kirchner JW: Evolutionary dynamics of pathogen resistance and tolerance. Evolution 2000, 54:51-63.
234 235
7.
Seixas E et al.: Heme oxygenase-1 affords protection against noncerebral forms of severe malaria. Proc Natl Acad Sci U S A 2009, 106:15837-15842.
236 237 238
8.
Soares MP, Teixeira L, Moita LF: Disease tolerance and immunity in host protection against infection. Nat Rev Immunol 2017, 17:83-96.
239 240 241
9.
Jamieson AM et al.: Role of tissue protection in lethal respiratory viral-bacterial coinfection. Science 2013, 340:1230-1234.
242 243 244
212 213 214 215 216 217 218
10. Best A, White A, Boots M: Maintenance of host variation in tolerance to pathogens and parasites. Proc Natl Acad Sci U S A 2008, 105:20786-20791.
245 246 247
11. Best A, White A, Boots M: The coevolutionary implications of host tolerance. Evolution 2014, 68:1426-1435.
248 249
12. Anderson RM, May RM: Infectious Diseases of Humans: Dynamics and Control. Oxford Science Publications. Oxford; New York: Oxford University Press; 1991. viii, 757 p..
250 251
13. Regoes RR et al.: Disentangling human tolerance and resistance against HIV. PLoS Biol 2014, 12:e1001951.
252 253
14. Louie A et al.: How many parameters does it take to describe Q5254 255 disease tolerance? PLoS Biol 2016, 14:e1002435. 256 This study developed a mathematical model to describe interactions 257 between hosts and microbes during infection and presents a conceptual 258 framework for integrating studies of tolerance in multiple systems. 15. Gupta V, Vale PF: Nonlinear disease tolerance curves reveal distinct components of host responses to viral infection. R Soc Open Sci 2017, 4:170342.
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16. Howick VM, Lazzaro BP: Genotype and diet shape resistance and tolerance across distinct phases of bacterial infection. BMC Evol Biol 2014, 14:56.
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17. Howick VM, Lazzaro BP: The genetic architecture of defence as resistance to and tolerance of bacterial infection in Drosophila melanogaster. Mol Ecol 2017, 26:1533-1546. This study demonstrates that population genetics approaches can identify genes that regulate disease tolerance and defined a new strategy to measure tolerance in a population.
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26. Soares MP, Gozzelino R, Weis S: Tissue damage control in disease tolerance. Trends Immunol 2014, 35:483-494.
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19. Dillman AR, Schneider DS: Defining resistance and tolerance to cancer. Cell Rep 2015, 13:884-887.
27. Moret Y, Schmid-Hempel P: Survival for immunity: the price of immune system activation for bumblebee workers. Science 2000, 290:1166-1168.
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20. Merkling SH et al.: The epigenetic regulator G9a mediates tolerance to RNA virus infection in Drosophila. PLoS Pathog 2015, 11:e1004692.
28. Richardson CE, Kooistra T, Kim DH: An essential role for XBP-1 in host protection against immune activation in C. elegans. Nature 2010, 463:1092-1095.
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22. Troha K et al.: Comparative transcriptomics reveals CrebA as a novel regulator of infection tolerance in D. melanogaster. PLoS Pathog 2018, 14(2):e1006847. This work defined a set of core response genes to bacterial infection in Drosophila melanogaster, including CrebA, which promotes disease tolerance by reducing cellular stress caused by mounting an immune response.
29. Fox RM, Hanlon CD, Andrew DJ: The CrebA/Creb3-like transcription factors are major and direct regulators of secretory capacity. J Cell Biol 2010, 191:479-492.
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30. Adamo SA: Parasitic suppression of feeding in the tobacco hornworm, Manduca sexta: parallels with feeding depression after an immune challenge. Arch Insect Biochem Physiol 2005, 60:185-197.
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23. Dionne MS et al.: Akt and FOXO dysregulation contribute to infection-induced wasting in Drosophila. Curr Biol 2006, 16:1977-1985.
31. Chambers MC, Song KH, Schneider DS: Listeria monocytogenes infection causes metabolic shifts in Drosophila melanogaster. PLoS One 2012, 7:e50679.
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24. Clark RI et al.: MEF2 is an in vivo immune-metabolic switch. Cell 2013, 155:435-447.
32. Cumnock K et al.: Host energy source is important for disease tolerance to malaria. Curr Biol 2018, 28:1635-1642.e3.
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25. Mace KA, Pearson JC, McGinnis W: An epidermal barrier wound repair pathway in Drosophila is mediated by grainy head. Science 2005, 308:381-385.
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Please cite this article in press as: Lissner MM, Schneider DS: The physiological basis of disease tolerance in insects, Curr Opin Insect Sci (2018), https://doi.org/10.1016/j.cois.2018.09.004