# Focal Point Theory Models for Dissecting Dynamic Duality Problems of Microbial Infections

Authors: S.-H. Huang; W. Zhou; A. Jong
Journal: Journal of Biomedicine and Biotechnology
 (2008)

---

## Abstract

Extending along the dynamic continuum from conflict to cooperation, microbial infections always involve symbiosis (Sym) and pathogenesis (Pat). There exists a dynamic Sym-Pat duality (DSPD) in microbial infection that is the most fundamental problem in infectomics. DSPD is encoded by the genomes of both the microbes and their hosts. Three focal point (FP) theory-based game models (pure cooperative, dilemma, and pure conflict) are proposed for resolving those problems. Our health is associated with the dynamic interactions of three microbial communities (nonpathogenic microbiota (NP) (Cooperation), conditional pathogens (CP) (Dilemma), and unconditional pathogens (UP) (Conflict)) with the hosts at different health statuses. Sym and Pat can be quantitated by measuring symbiotic index (SI), which is quantitative fitness for the symbiotic partnership, and pathogenic index (PI), which is quantitative damage to the symbiotic partnership, respectively. Symbiotic point (SP), which bears analogy to FP, is a function of SI and PI. SP-converting and specific pathogen-targeting strategies can be used for the rational control of microbial infections.


---

## Body

## 1. Introduction

Infectious diseases caused by bacterial, viral, fungal, or parasitic
pathogens continue to be the leading cause of morbidity and
mortality worldwide despite the availability of effective
antimicrobial agents and vaccines over the last fifty years or more [1]. The continual emergence
of previously undescribed new pathogens, reemergence of old pathogens, and the
rising crisis of antibiotics resistance will certainly heighten the global impact of microbial infections in the 21st century. These problems are mainly due to inadequate
knowledge of the dynamic duality relationships between symbiosis (Sym) and
pathogenesis (Pat) in microbial infections [2]. The term symbiosis, which may
have many variations on its definition, in this paper refers to living together
through a close and prolonged association between two or more organisms of
different species [3, 4]. Duality is defined as different ways of looking at
the same thing [5]. There are two major limitations inherent in the
conventional theories of microbial infection. On the one hand, in the
past century, biology and medicine including infectious diseases have been
dominated by the reductionistic approaches. Focusing research on
individual virulence genes and the important pathogens has been the traditional
approach to human infectious diseases. On the other hand, as Joshua Lederberg pointed out [6, 7], medical science
is imbued with the Manichaean view of the microbe-human host
relationship: “we good; they evil.” Almost all broad-spectrum antimicrobial
agents, which are in the best interest of pharmaceutical industries, kill both
the good microbes as well as the bad germs. Even though narrow-spectrum antiinfective
agents are not “narrow” for pathogens, they also target both the good and bad
microorganisms with a limited range of species.Animals and plants are continually infected by an extensive
diversity of symbiotic or invading organisms including bacteria, virus, fungus,
or parasites. Infection of bacteria by phages started long before the emergence
of animals and plants [8]. Microbial infection is an evolutionary paradigm
which is associated with coevolution between hosts and microbes [6, 7, 9]. This
coevolution can be defined as the process of reciprocal and dynamic genetic
changes in two or more species [2]. The conventional wisdom in medicine holds
that microbial infection is a pathogenic process in which a pathogen enters,
establishes itself, and multiplies in the host [10]. The emphasis is on the
antagonism or conflict, not the mutualism. This represents “zero-sum
thinking”—the belief that if one player gains, other
player must inevitably lose. Methods and concepts of the zero-sum game theory
have proved successful in studying the strategy of pure conflict. The most
challenging issue in infectious diseases is how to dissect the dynamic Sym-Pat
duality (DSPD) in microbial infections using infectomics and mathematics such
as focal point- (FP-) based game theory. Game theory, defined in the broadest
sense, is the study of the strategies of conflict, cooperation, and mixed
situations in which both coexist. Generally, there are multiple equilibria in a
game. Thomas Schelling's concept of focal point, which is an equilibrium usually
standing out from the others, addressed the crucial question of how to
interpret the multiplicity of equilibria [11, 12]. Focal point, the principal
component of Schelling's game theory, is a convergence point of expectations
about actions in a game. This article attempts to enlarge the scope and
application of focal point game theory in microbial infections, extending from
the zero-sum games to the nonzero-sum games.


## 2. Definitions and Methods

### 2.1. Three-Community Principle of Microbial Infections

Our health is associated with the dynamic interactions of
three microbial communities [2] (nonpathogenic microbiota (NP), conditional
pathogens (CP), and unconditional pathogens (UP)) with the hosts at three different
health statuses (nonsusceptibility (NS), conditional susceptibility (CS), and
unconditional susceptibility (US)) (see Figure 1). NP is the major microbial
community which forms a healthy symbiotic “superorganism” with the hosts. The
ecology and evolution of NP-NS interaction are essential and fundamental for health. From
birth to death, we share a benign coexistence with a vast,
complex, and dynamic consortium of microbes. Most of our microbial commensals reside
in our gastrointestinal (GI) track packed with up to 100 trillion (1014)
microbes [1, 13]. The GI tract harbors a rich microbiota of >600 different
bacterial species. Some of these microorganisms have important health
functions. These include stimulating the immune system, protecting the host
from microbial invasion, and aiding digestion. The gut microbiota, which is essential
for human homeostasis, is established rapidly after birth and remains
relatively stable throughout the life [1]. The GI mucosa provides a protective
interface between the internal environment and the constant external challenge
from food-derived antigens and microbes. CP and UP are minor microbial
communities that mainly contribute to the pathogenesis of microbial diseases. The distinction between
the commensal and the pathogen in the CP community can be blurred because they
may cause diseases under certain sub-health conditions of the hosts, or in
immunocompromised hosts. For example, pneumococcus, meningococcus, and
Haemophilus bacteria regularly exist as part of the normal microbiota of the
host respiratory track and are mostly carried asymptomatically despite the fact
that they can cause well-defined diseases [14, 15]. Microbes in the CP community dynamically evolve in two
opposite directions, which are toward either the NP (more cooperative or
mutualistic) or UP (more pathogenic) microbial community. Microbes with high
pathogenicity belong to the UP microbial community. The three microbial
communities and three statuses of the hosts are subjected to dynamic reciprocal
changes driven by transfer of genetic materials.Figure 1
Schematic representation of interactions of three microbial communities
(nonpathogenic (NP), conditional pathogenic (CP), and unconditional pathogenic
(UP)) with the hosts at three different health statuses (nonsusceptibility
(NS), conditional susceptibility (CS), and unconditional susceptibility (US)).


### 2.2. Dynamic Duality Relationships Between Sym and Pat in Microbial Infections

Extending along the
dynamic continuum from conflict to cooperation, microbial infections always
involve symbiosis and pathogenesis, which are two fundamental components of the
host-microbe interactions (see Figure2). There exists a dynamic Sym-Pat
duality in microbial infection, which is the most fundamental issue of
infectomics [2]. DSPD is reflected in the genotypic and phenotypic infectomes,
which are encoded by the genomes of both the microbes and their hosts [2]. The
opposition and unity of Sym and Pat are indispensable, and the academic
viewpoint that the unity of opposites of Sym and Pat gives impetus to the
development of microbial infection is considered as the core idea and radical
principle of the duality representations of microbial infections. In certain
circumstances and at a certain stage of the development of microbial infection,
each of the two aspects of Sym and Pat will transform from antagonism into
mutualism or from mutualism into antagonism. Sym and Pat can be quantitated by
measuring symbiotic index (SI), which is quantitative fitness for the symbiotic
partnership, and pathogenic index (PI), which is quantitative damage to the
symbiotic partnership, respectively. The most crucial studies are to  identify
infectomic signatures specific for SI and PI. The set of symbiotic or
pathogenic parameters is defined as a function SI(x) or PI(x*). SI(x) and PI(x*) are continuous functions ranging
from 0 to 1 to admit different degrees of Sym and Pat, respectively. SI(x) = 0 and PI(x*) = 0 indicate that x
and x* are perceived to be zero-symbiotic and zero-pathogenic, respectively. SI(x) = 1 and PI(x*) = 1 indicate that x
and  x* are perceived to be completely symbiotic and  completely pathogenic, respectively.
Intermediate values of SI(x) and PI(x*) indicate that x
and x* are perceived to be partially symbiotic and partially pathogenic,
respectively. Symbiotic
points  are used to determine the dynamic
duality between Sym and Pat. SI and PI are interdependent parameters. The
symbiotic point (SP) is a function of SI and PI:
(1)SP=f(SI,PI).
The focus of the dynamic duality research is to examine
the ability of SP to transform situations of potential conflict (UP-US and CP-CS) into
situations of cooperation (NP-NS). SP
bears analogy to Schelling's focal point, which is any feature of such a game
that provides a focus of convergence [16]. In the games with multiple Nash
equilibria, one equilibrium usually stands out from the others (salient). Such an  equilibrium is a
focal point which can be easily recognized by all the players [12]. Thomas
Schelling's Strategy of Conflict (1960) has been recognized as one of the most important works of game theory [11, 17]. There is no doubt that focal points play a central role in Schelling's
game theory. Schelling has made a significant contribution to a reorientation
of game theory. Understanding focal points is not only a key to improving game
theory but also a key to dissecting SPs.Figure 2
A continuum model of host-microbe
interactions coupling with infectomic approaches to dissect the problems in
microbial infections.


### 2.3. Game Theoretical Models (GTMs) of  Microbial Infections

In this paper, three types of GTMs are proposed for studies on NP-NS interactions
(cooperative game), UP-US interactions (noncooperative games), and CP-CS
interactions (dilemma or bargaining game).
First, the NS-NS interactions are dissected with pure cooperative games
in which each player chooses the strategy corresponding with the focal point in
the expectation that the others will do the same. The significance of focal
points can be shown most clearly in the pure cooperative games. As there is no
conflict of interests in these games, all the players merely want to cooperate
and they do not choose the alternative ways. Analysis of the cooperative game
issues is to focus on coalition formation and distribution of the gains through
cooperation. The SP in the NP-NS games tends to be maximal
(see Figure2). Secondly, noncooperative GTMs are used for analysis of the UP-US
interactions. In contrast to cooperative games which focus on collective
rationality and common interest, noncooperative games emphasize individual
rationality and individual optimal strategy. The SP in the UP-US games tends to
be minimal (see Figure 2). In games
of pure conflict, defection is the equilibrium strategy and the total benefit
to all players in the game, for every combination of strategies, always adds to
zero (zero-sum). In the antagonistic UP-US interaction model, the surviving
strategies of the UP community conflict with that of the US host. The UP
evolves to exploit the host as much as possible, and the host adapts to exclude
or limit the damage caused by the UP. Thirdly, we consider the strategic
use of focal point theory in mixed situations to analyze the CP-CS interactions
in which there is both conflict and mutual dependence. The most well-known
example is the Prisoner's Dilemma game (a two-player game) in which each player
chooses between a cooperating and defecting strategy. In this game, each player
receives a higher playoff by defecting than by cooperating. However, a higher
playoff is received if both cooperate than both defect. The two-player game can
be extended to the N-player Prisoner's Dilemma game with arbitrary numbers of
players.


## 2.1. Three-Community Principle of Microbial Infections

Our health is associated with the dynamic interactions of
three microbial communities [2] (nonpathogenic microbiota (NP), conditional
pathogens (CP), and unconditional pathogens (UP)) with the hosts at three different
health statuses (nonsusceptibility (NS), conditional susceptibility (CS), and
unconditional susceptibility (US)) (see Figure 1). NP is the major microbial
community which forms a healthy symbiotic “superorganism” with the hosts. The
ecology and evolution of NP-NS interaction are essential and fundamental for health. From
birth to death, we share a benign coexistence with a vast,
complex, and dynamic consortium of microbes. Most of our microbial commensals reside
in our gastrointestinal (GI) track packed with up to 100 trillion (1014)
microbes [1, 13]. The GI tract harbors a rich microbiota of >600 different
bacterial species. Some of these microorganisms have important health
functions. These include stimulating the immune system, protecting the host
from microbial invasion, and aiding digestion. The gut microbiota, which is essential
for human homeostasis, is established rapidly after birth and remains
relatively stable throughout the life [1]. The GI mucosa provides a protective
interface between the internal environment and the constant external challenge
from food-derived antigens and microbes. CP and UP are minor microbial
communities that mainly contribute to the pathogenesis of microbial diseases. The distinction between
the commensal and the pathogen in the CP community can be blurred because they
may cause diseases under certain sub-health conditions of the hosts, or in
immunocompromised hosts. For example, pneumococcus, meningococcus, and
Haemophilus bacteria regularly exist as part of the normal microbiota of the
host respiratory track and are mostly carried asymptomatically despite the fact
that they can cause well-defined diseases [14, 15]. Microbes in the CP community dynamically evolve in two
opposite directions, which are toward either the NP (more cooperative or
mutualistic) or UP (more pathogenic) microbial community. Microbes with high
pathogenicity belong to the UP microbial community. The three microbial
communities and three statuses of the hosts are subjected to dynamic reciprocal
changes driven by transfer of genetic materials.Figure 1
Schematic representation of interactions of three microbial communities
(nonpathogenic (NP), conditional pathogenic (CP), and unconditional pathogenic
(UP)) with the hosts at three different health statuses (nonsusceptibility
(NS), conditional susceptibility (CS), and unconditional susceptibility (US)).


## 2.2. Dynamic Duality Relationships Between Sym and Pat in Microbial Infections

Extending along the
dynamic continuum from conflict to cooperation, microbial infections always
involve symbiosis and pathogenesis, which are two fundamental components of the
host-microbe interactions (see Figure2). There exists a dynamic Sym-Pat
duality in microbial infection, which is the most fundamental issue of
infectomics [2]. DSPD is reflected in the genotypic and phenotypic infectomes,
which are encoded by the genomes of both the microbes and their hosts [2]. The
opposition and unity of Sym and Pat are indispensable, and the academic
viewpoint that the unity of opposites of Sym and Pat gives impetus to the
development of microbial infection is considered as the core idea and radical
principle of the duality representations of microbial infections. In certain
circumstances and at a certain stage of the development of microbial infection,
each of the two aspects of Sym and Pat will transform from antagonism into
mutualism or from mutualism into antagonism. Sym and Pat can be quantitated by
measuring symbiotic index (SI), which is quantitative fitness for the symbiotic
partnership, and pathogenic index (PI), which is quantitative damage to the
symbiotic partnership, respectively. The most crucial studies are to  identify
infectomic signatures specific for SI and PI. The set of symbiotic or
pathogenic parameters is defined as a function SI(x) or PI(x*). SI(x) and PI(x*) are continuous functions ranging
from 0 to 1 to admit different degrees of Sym and Pat, respectively. SI(x) = 0 and PI(x*) = 0 indicate that x
and x* are perceived to be zero-symbiotic and zero-pathogenic, respectively. SI(x) = 1 and PI(x*) = 1 indicate that x
and  x* are perceived to be completely symbiotic and  completely pathogenic, respectively.
Intermediate values of SI(x) and PI(x*) indicate that x
and x* are perceived to be partially symbiotic and partially pathogenic,
respectively. Symbiotic
points  are used to determine the dynamic
duality between Sym and Pat. SI and PI are interdependent parameters. The
symbiotic point (SP) is a function of SI and PI:
(1)SP=f(SI,PI).
The focus of the dynamic duality research is to examine
the ability of SP to transform situations of potential conflict (UP-US and CP-CS) into
situations of cooperation (NP-NS). SP
bears analogy to Schelling's focal point, which is any feature of such a game
that provides a focus of convergence [16]. In the games with multiple Nash
equilibria, one equilibrium usually stands out from the others (salient). Such an  equilibrium is a
focal point which can be easily recognized by all the players [12]. Thomas
Schelling's Strategy of Conflict (1960) has been recognized as one of the most important works of game theory [11, 17]. There is no doubt that focal points play a central role in Schelling's
game theory. Schelling has made a significant contribution to a reorientation
of game theory. Understanding focal points is not only a key to improving game
theory but also a key to dissecting SPs.Figure 2
A continuum model of host-microbe
interactions coupling with infectomic approaches to dissect the problems in
microbial infections.


## 2.3. Game Theoretical Models (GTMs) of  Microbial Infections

In this paper, three types of GTMs are proposed for studies on NP-NS interactions
(cooperative game), UP-US interactions (noncooperative games), and CP-CS
interactions (dilemma or bargaining game).
First, the NS-NS interactions are dissected with pure cooperative games
in which each player chooses the strategy corresponding with the focal point in
the expectation that the others will do the same. The significance of focal
points can be shown most clearly in the pure cooperative games. As there is no
conflict of interests in these games, all the players merely want to cooperate
and they do not choose the alternative ways. Analysis of the cooperative game
issues is to focus on coalition formation and distribution of the gains through
cooperation. The SP in the NP-NS games tends to be maximal
(see Figure2). Secondly, noncooperative GTMs are used for analysis of the UP-US
interactions. In contrast to cooperative games which focus on collective
rationality and common interest, noncooperative games emphasize individual
rationality and individual optimal strategy. The SP in the UP-US games tends to
be minimal (see Figure 2). In games
of pure conflict, defection is the equilibrium strategy and the total benefit
to all players in the game, for every combination of strategies, always adds to
zero (zero-sum). In the antagonistic UP-US interaction model, the surviving
strategies of the UP community conflict with that of the US host. The UP
evolves to exploit the host as much as possible, and the host adapts to exclude
or limit the damage caused by the UP. Thirdly, we consider the strategic
use of focal point theory in mixed situations to analyze the CP-CS interactions
in which there is both conflict and mutual dependence. The most well-known
example is the Prisoner's Dilemma game (a two-player game) in which each player
chooses between a cooperating and defecting strategy. In this game, each player
receives a higher playoff by defecting than by cooperating. However, a higher
playoff is received if both cooperate than both defect. The two-player game can
be extended to the N-player Prisoner's Dilemma game with arbitrary numbers of
players.


## 3. Results

### 3.1. Three Communities inEscherichia Coli Species

E. coli is one of the best understood
and most thoroughly studied organisms and is advantageous as a model microorganism
for the current studies. This bacterium is genotypically and phenotypically a
highly diverse species, which is present in the three microbial communities (see
Table 1). Most E. coli strains are
commensals of higher vertebrates belonging to NP, but some are pathogenic (CP and UP). Uropathogenic E. coli (UPEC) in the CP group are the
most common cause of community-acquired urinary tract infection (UTI). UPEC are
responsible for about 80% of the estimated 150 million UTIs diagnosed annually
[18]. E. coli O157, which belong to
the UP group, is a major food pathogen. Shigella species, the cause of
dysentery, are now known to be multiple distinct lineages of E. coli. Genomes of those E. coli strains have been sequenced (see
Table 1). Recently, “better” E. coli strains
(MDS41, 42, 43) have been engineered in which about 15% of the genome has been
removed with the use of synthetic biology [19]. Coliphage, a virus which
infects E. coli, is a major
contributor responsible for diversification of E. coli [20, 21]. From a population-dynamic view, the interactions
between coliphage and E. coli are
analogous to those of a predator and a prey.Table 1
E. coli in the three microbial communities.
E. coli strainscharacteristicsGenome (Mb)PutativeSIPINPMG1655 (K12)Commensal4.6>0.75<0.25Nissle 1917Probiotics5.1>0.75<0.25A0 34/86Probiotics4.8>0.75<0.25MDS41, 42, 43K12
strains3.9>0.75<0.25CPRS218Low pathogenicity5.10.5±0.250.5±0.25CFT073Uropathogenicity5.20.5±0.250.5±0.25UPO157 RIMDHigh pathogenicity5.5<0.25>0.75O157 EDLHigh pathogenicity5.5<0.25>0.75Shigella Sd197High pathogenicity4.4<0.25>0.75


### 3.2. Sym-Pat Duality is Encoded by The Genomes of Both Microbes and Their hosts

The development of microbial infections depends
on the dynamic Sym-Pat duality, which is governed by the genomes of both
the microbes and their hosts [2]. Molecular
evolution of genetic structures for the Sym-Pat duality is influenced by both
biotic and abiotic environmental factors in the ecosystems. There are three
types of genetic/genomic determinants (GGDs) that may contribute to the Sym-Pat
duality of microbial infections under specific environmental conditions (see Figure 3). The first type is the Sym GGD pool, which contributes to symbiosis. The Sym
GGDs from the microbial partner include symbiosis-related genomic islands
(SYI), plasmids, transposons, and microbiome, which is a collective genome of
microbiota [2, 22, 23]. The gene pool contributing to microbial tolerance belongs
to the host Sym GGDs [24]. The
symbiotic homeostasis of the superorganism formed by the microbiota and its
host is governed by hologenome, a complex of the host genome and microbiome [22, 25]. The second pool of GGDs contributes to the pathogenesis of microbial
infections. These include pathogenicity islands (PAI), virulence plasmids,
pathogen-associated molecular patterns (PAMPs), and endogenous alarmins [26].  PAMPs are a diverse group of microbial
molecules, which are recognized by the host innate and adaptive immune system, primarily
through toll-like receptors (TLRs) [26]. Alarmins are endogenous molecules within the host that signal
tissue and cell damage. Effector cells of the innate and adaptive immunity can
release alarmins when they are activated by PAMPs. Endogenous alarmins and
exogenous PAMPs elicit similar responses by conveying a similar message.
Therefore, they constitute a larger family of damage-associated molecular
patterns (DAMPs). The third type of GGD pool has dual functions that depend on
external and internal environments. These include ecological islands (ECI),
certain GGDs from conditional pathogens (such as CP factors (CPFs) and CP
islands (CPIs)), and the host GGDs with dual effects on microbial infections. The
dual GGDs contribute to the Sym and Pat duality in specific ecological niches
and within particular organisms. The same GGD may act as an SYI when the
microbial recipient establishes a symbiotic relationship with its host, but
becomes a PAI when it is adapting the pathogenic niche. A comparative infectomic
study suggests that GimA, a 20-kb genomic island, is a typical CPI [27]. The
dual biological functions of GimA depend on the genomic environments in E. coli strains. GimA present in
meningitic E. coli K1 genome
(O18:K1:H7) is essential for bacterial crossing the blood-brain barrier to
cause meningitis [28].  In contrast, GimA
is required for the probiotic function of E.
coli K24 strain A0 34/86 (O83:K24:H31), which has been safely and
effectively used in Czech pediatric clinics since 1967 [29]. The dual Sym-Pat
properties of microbial determinants were also observed in photorhabdus, which is a genus of Gram-negative bacteria
mutualistically associated with entomophagous nematodes of the family
heterorhabditiae [30]. A hexA homologous gene from photorhabdus is able to regulate both symbiosis and pathogenesis [30].
Some microbes exhibit dual behavior as symbionts and pathogens in a manner
dependent on the hosts. Sooty mangabey (SM) monkeys infected with simian
immunodeficiency virus (SIV) do not develop acquired immunodeficiency syndrome
(AIDS) [31]. In contrast, SIV infection of non-natural host monkeys, such as
rhesus macaques (RMs), causes AIDS that closely resembles the human disease [31].
Similarly, polydnaviridae, a family of double-stranded DNA viruses, have
evolved complex life cycles in which they interact as symbionts with one host
and as pathogens
with another [32]. All multicellular organisms, including human and flies, have
evolved the conservative innate immune system as a double-edged sword [33]. It enables
the host not only to combat pathogens but also to develop microbial tolerance
to cohabit nonpathogenic microbiota by maintaining the homeostatic balance
between the host and microorganisms [24, 33]. TLRs play central roles in the
activating process of the innate immune system with dual functions. They have
recently been shown to be involved in modulating intestinal homeostasis by
recognizing commensal bacteria. They also sense extracellular PAMPs by
triggering signaling, which results in the activation of proinflammatory (PI) pathways
[24].  PI ligands of TLRs may be
important for the activation and expansion of natural T regulatory cells
(NatTReg), which control both deleterious and protective immune responses upon
microbial infections [34]. Both innate TLRs and specific T cell receptors (TCR)
contribute to the dual functions of NatTReg [34]. The full range of the dual
GGDs in the immune system is unknown so far. However, it can be expected that
the molecular evolution of the dual GGDs during the host-microbe coevolution will
certainly lead to dynamic changes in the Sym-Pat  duality.Figure 3
Gene pools contributing to the Sym-Pat duality. CPF: CP factors; CPI: CP
islands; ECI: ecological islands; HPI: high pathogenicity islands; PAI: pathogenicity islands; SYI: symbiosis island.


### 3.3. Duality Relationship Between Sym and Pat

Sym and Pat, the fundamental components of microbial infection,
can be defined as a function SI(x)
or PI(x*). SI(x) and PI(x*) are continuous functions ranging from 0 to 1 to admit
different degrees of Sym and Pat, respectively (see Figure 4). SI(x) = 0 and PI(x*) = 0 indicate that x and
x* are perceived to be
zero-symbiotic and zero-pathogenic, respectively. SI(x) = 1 and PI(x*) = 1 indicate that x and
x* are perceived to be completely
symbiotic and  completely pathogenic,
respectively. If SI is close to or equal to 1, microbial infection is a
physiological process. It is now well accepted that mitochondria were
derived from an endosymbiotic relationship with internalized proteobacteria,
via a progressive transfer of genetic material [35]. This long symbiotic
relationship reaches the maximum Sym value. The symbiotic nitrogen fixation process
for converting atmospheric dinitrogen (N2) to ammonia (NH3)
is essentially dependent on two partners: the host legume plant and bacteria belonging to
the family Rhizobiaceae [36]. This type of microbial infection is more typically
associated with a physiological process.Figure 4
The duality relationship between Sym (αi) and Pat (βi). A cooperative relationship (NP-NS: health and
mutualism) (I) occurs between the host and the NP microbial community. A
competitive relationship (CP-CS) (II and III) exists between the host and the
CP microbial community. There are two types of competitions: better (II) and
worse (III). An
antagonistic relationship (UP-US) (IV) occurs between the host and the UP microbial community.If the PI value
approaches or reaches the maximum limit, microbial infection is more completely
associated with a pathogenic process. Most of serious infectious diseases fall
into this category. Intermediate values of SI(x) and PI(x*)
indicate that x and x* are
perceived to be partially symbiotic and partially pathogenic, respectively. Microbial
infections induced by conditional pathogens represent a competitive relationship (see II or III in Figure 4).
The hosts have large influences on SI and PI. For example, polydnaviruses have
evolved complex life cycles in which they are able to adapt to a mutualistic
partnership with one host and become pathogens with another. Their genomes
reflect the dual roles as mutualists and pathogens [32].


### 3.4. Outcomes of Three Types of Games in  Microbial Infections

The outcome of a game is not
only determined by one individual's choices, but also depends on the strategies
used by all the others. The dynamic Sym-Pat duality influenced by both microbes
and their hosts is the key factor that determines the outcome of a game
associated with microbial infection. One of the most fundamental issues in game
theoretical solution concepts is that strategies used by individual players are
based on the differences in payoff perceived by them [37]. This issue can be
solved by Schelling's focal point theory. FPs constitute shared expectations
that coordinate the activities of diverse players collectively or independently
seeking their goals [38]. By harmonizing anticipated behaviors or responses
despite the presence of imperfect information, individuals are able to
coordinate their activities towards their ends. In 1960, Schelling classified
games into three major categories: pure cooperative game on one side, pure
conflict games on the other, and combinations of partial cooperation/partial
conflict games in between [11]. Recently, a similar classification was
designated in Gao's book, “Principles of Systemics” [39]. The pure cooperative
game models are used for dissecting NP-NS interaction problems. The payoff
matrix for a pure NP-NS problem would resemble something like that in Figure 5(a).
In contrast, the pure UP-US interaction, a situation of pure antagonism, is
characterized by completely opposing interests, where the pathogenesis of
microbial infection is the most predominant event. The payoff matrix for the
pure UP-US game would look something like that in Figure 5(b). The state of
microbial infection has conventionally been characterized as lying on the
extreme conflict end. This depiction comes from the Manichaean view of the microbe-human host
relationship. This situation
is depicted in Figure 5(b) as a two-player game. In the pure conflict game, the relationships
between the microbes and their hosts end up in a “war of all against all” in
which the payoffs of the outcomes add to zero (zero-sum). The three microbial
community principle and the dynamic Sym-Pat duality concept would help establish a holistic view of microbial infections. The
CP-CS interaction is a situation where cooperation and conflict coexist. As
illustrated in Figure 5(c), the payoffs for the CP-CS games would lie midway
between the pure cooperative and pure conflict games. The CP-CS problems are
microbial dilemmas, in which there is a mixture of mutual dependence and
conflict of partnerships and competition. The underlying idea arises naturally
from the well-known games for the social dilemmas and the Prisoner's Dilemma
(PD), in which each player chooses between a cooperating and a defecting
strategy [40]. As shown in Figure 5(c), each player receives a higher
playoff by defecting than by cooperating, no matter what the other player
chooses. However, they receive a higher playoff if both cooperate than both
defect. The CP-CS interactions can coevolve toward two different directions,
increasing (more cooperation) or decreasing  (more antagonism) the SP (see Figure 2).(a) Pure cooperative game. (b) Pure conflict
game. H: host; M: microbes.  (c) Dilemma game. The number in the left of each
pair indicates the payoff for microbes, and the right, the host. Higher numbers
represent greater payoff for the individual. Two strategies (Cooperation (C) and
Defection (D)) are used.
(a)(b)(c)


## 3.1. Three Communities inEscherichia Coli Species

E. coli is one of the best understood
and most thoroughly studied organisms and is advantageous as a model microorganism
for the current studies. This bacterium is genotypically and phenotypically a
highly diverse species, which is present in the three microbial communities (see
Table 1). Most E. coli strains are
commensals of higher vertebrates belonging to NP, but some are pathogenic (CP and UP). Uropathogenic E. coli (UPEC) in the CP group are the
most common cause of community-acquired urinary tract infection (UTI). UPEC are
responsible for about 80% of the estimated 150 million UTIs diagnosed annually
[18]. E. coli O157, which belong to
the UP group, is a major food pathogen. Shigella species, the cause of
dysentery, are now known to be multiple distinct lineages of E. coli. Genomes of those E. coli strains have been sequenced (see
Table 1). Recently, “better” E. coli strains
(MDS41, 42, 43) have been engineered in which about 15% of the genome has been
removed with the use of synthetic biology [19]. Coliphage, a virus which
infects E. coli, is a major
contributor responsible for diversification of E. coli [20, 21]. From a population-dynamic view, the interactions
between coliphage and E. coli are
analogous to those of a predator and a prey.Table 1
E. coli in the three microbial communities.
E. coli strainscharacteristicsGenome (Mb)PutativeSIPINPMG1655 (K12)Commensal4.6>0.75<0.25Nissle 1917Probiotics5.1>0.75<0.25A0 34/86Probiotics4.8>0.75<0.25MDS41, 42, 43K12
strains3.9>0.75<0.25CPRS218Low pathogenicity5.10.5±0.250.5±0.25CFT073Uropathogenicity5.20.5±0.250.5±0.25UPO157 RIMDHigh pathogenicity5.5<0.25>0.75O157 EDLHigh pathogenicity5.5<0.25>0.75Shigella Sd197High pathogenicity4.4<0.25>0.75


## 3.2. Sym-Pat Duality is Encoded by The Genomes of Both Microbes and Their hosts

The development of microbial infections depends
on the dynamic Sym-Pat duality, which is governed by the genomes of both
the microbes and their hosts [2]. Molecular
evolution of genetic structures for the Sym-Pat duality is influenced by both
biotic and abiotic environmental factors in the ecosystems. There are three
types of genetic/genomic determinants (GGDs) that may contribute to the Sym-Pat
duality of microbial infections under specific environmental conditions (see Figure 3). The first type is the Sym GGD pool, which contributes to symbiosis. The Sym
GGDs from the microbial partner include symbiosis-related genomic islands
(SYI), plasmids, transposons, and microbiome, which is a collective genome of
microbiota [2, 22, 23]. The gene pool contributing to microbial tolerance belongs
to the host Sym GGDs [24]. The
symbiotic homeostasis of the superorganism formed by the microbiota and its
host is governed by hologenome, a complex of the host genome and microbiome [22, 25]. The second pool of GGDs contributes to the pathogenesis of microbial
infections. These include pathogenicity islands (PAI), virulence plasmids,
pathogen-associated molecular patterns (PAMPs), and endogenous alarmins [26].  PAMPs are a diverse group of microbial
molecules, which are recognized by the host innate and adaptive immune system, primarily
through toll-like receptors (TLRs) [26]. Alarmins are endogenous molecules within the host that signal
tissue and cell damage. Effector cells of the innate and adaptive immunity can
release alarmins when they are activated by PAMPs. Endogenous alarmins and
exogenous PAMPs elicit similar responses by conveying a similar message.
Therefore, they constitute a larger family of damage-associated molecular
patterns (DAMPs). The third type of GGD pool has dual functions that depend on
external and internal environments. These include ecological islands (ECI),
certain GGDs from conditional pathogens (such as CP factors (CPFs) and CP
islands (CPIs)), and the host GGDs with dual effects on microbial infections. The
dual GGDs contribute to the Sym and Pat duality in specific ecological niches
and within particular organisms. The same GGD may act as an SYI when the
microbial recipient establishes a symbiotic relationship with its host, but
becomes a PAI when it is adapting the pathogenic niche. A comparative infectomic
study suggests that GimA, a 20-kb genomic island, is a typical CPI [27]. The
dual biological functions of GimA depend on the genomic environments in E. coli strains. GimA present in
meningitic E. coli K1 genome
(O18:K1:H7) is essential for bacterial crossing the blood-brain barrier to
cause meningitis [28].  In contrast, GimA
is required for the probiotic function of E.
coli K24 strain A0 34/86 (O83:K24:H31), which has been safely and
effectively used in Czech pediatric clinics since 1967 [29]. The dual Sym-Pat
properties of microbial determinants were also observed in photorhabdus, which is a genus of Gram-negative bacteria
mutualistically associated with entomophagous nematodes of the family
heterorhabditiae [30]. A hexA homologous gene from photorhabdus is able to regulate both symbiosis and pathogenesis [30].
Some microbes exhibit dual behavior as symbionts and pathogens in a manner
dependent on the hosts. Sooty mangabey (SM) monkeys infected with simian
immunodeficiency virus (SIV) do not develop acquired immunodeficiency syndrome
(AIDS) [31]. In contrast, SIV infection of non-natural host monkeys, such as
rhesus macaques (RMs), causes AIDS that closely resembles the human disease [31].
Similarly, polydnaviridae, a family of double-stranded DNA viruses, have
evolved complex life cycles in which they interact as symbionts with one host
and as pathogens
with another [32]. All multicellular organisms, including human and flies, have
evolved the conservative innate immune system as a double-edged sword [33]. It enables
the host not only to combat pathogens but also to develop microbial tolerance
to cohabit nonpathogenic microbiota by maintaining the homeostatic balance
between the host and microorganisms [24, 33]. TLRs play central roles in the
activating process of the innate immune system with dual functions. They have
recently been shown to be involved in modulating intestinal homeostasis by
recognizing commensal bacteria. They also sense extracellular PAMPs by
triggering signaling, which results in the activation of proinflammatory (PI) pathways
[24].  PI ligands of TLRs may be
important for the activation and expansion of natural T regulatory cells
(NatTReg), which control both deleterious and protective immune responses upon
microbial infections [34]. Both innate TLRs and specific T cell receptors (TCR)
contribute to the dual functions of NatTReg [34]. The full range of the dual
GGDs in the immune system is unknown so far. However, it can be expected that
the molecular evolution of the dual GGDs during the host-microbe coevolution will
certainly lead to dynamic changes in the Sym-Pat  duality.Figure 3
Gene pools contributing to the Sym-Pat duality. CPF: CP factors; CPI: CP
islands; ECI: ecological islands; HPI: high pathogenicity islands; PAI: pathogenicity islands; SYI: symbiosis island.


## 3.3. Duality Relationship Between Sym and Pat

Sym and Pat, the fundamental components of microbial infection,
can be defined as a function SI(x)
or PI(x*). SI(x) and PI(x*) are continuous functions ranging from 0 to 1 to admit
different degrees of Sym and Pat, respectively (see Figure 4). SI(x) = 0 and PI(x*) = 0 indicate that x and
x* are perceived to be
zero-symbiotic and zero-pathogenic, respectively. SI(x) = 1 and PI(x*) = 1 indicate that x and
x* are perceived to be completely
symbiotic and  completely pathogenic,
respectively. If SI is close to or equal to 1, microbial infection is a
physiological process. It is now well accepted that mitochondria were
derived from an endosymbiotic relationship with internalized proteobacteria,
via a progressive transfer of genetic material [35]. This long symbiotic
relationship reaches the maximum Sym value. The symbiotic nitrogen fixation process
for converting atmospheric dinitrogen (N2) to ammonia (NH3)
is essentially dependent on two partners: the host legume plant and bacteria belonging to
the family Rhizobiaceae [36]. This type of microbial infection is more typically
associated with a physiological process.Figure 4
The duality relationship between Sym (αi) and Pat (βi). A cooperative relationship (NP-NS: health and
mutualism) (I) occurs between the host and the NP microbial community. A
competitive relationship (CP-CS) (II and III) exists between the host and the
CP microbial community. There are two types of competitions: better (II) and
worse (III). An
antagonistic relationship (UP-US) (IV) occurs between the host and the UP microbial community.If the PI value
approaches or reaches the maximum limit, microbial infection is more completely
associated with a pathogenic process. Most of serious infectious diseases fall
into this category. Intermediate values of SI(x) and PI(x*)
indicate that x and x* are
perceived to be partially symbiotic and partially pathogenic, respectively. Microbial
infections induced by conditional pathogens represent a competitive relationship (see II or III in Figure 4).
The hosts have large influences on SI and PI. For example, polydnaviruses have
evolved complex life cycles in which they are able to adapt to a mutualistic
partnership with one host and become pathogens with another. Their genomes
reflect the dual roles as mutualists and pathogens [32].


## 3.4. Outcomes of Three Types of Games in  Microbial Infections

The outcome of a game is not
only determined by one individual's choices, but also depends on the strategies
used by all the others. The dynamic Sym-Pat duality influenced by both microbes
and their hosts is the key factor that determines the outcome of a game
associated with microbial infection. One of the most fundamental issues in game
theoretical solution concepts is that strategies used by individual players are
based on the differences in payoff perceived by them [37]. This issue can be
solved by Schelling's focal point theory. FPs constitute shared expectations
that coordinate the activities of diverse players collectively or independently
seeking their goals [38]. By harmonizing anticipated behaviors or responses
despite the presence of imperfect information, individuals are able to
coordinate their activities towards their ends. In 1960, Schelling classified
games into three major categories: pure cooperative game on one side, pure
conflict games on the other, and combinations of partial cooperation/partial
conflict games in between [11]. Recently, a similar classification was
designated in Gao's book, “Principles of Systemics” [39]. The pure cooperative
game models are used for dissecting NP-NS interaction problems. The payoff
matrix for a pure NP-NS problem would resemble something like that in Figure 5(a).
In contrast, the pure UP-US interaction, a situation of pure antagonism, is
characterized by completely opposing interests, where the pathogenesis of
microbial infection is the most predominant event. The payoff matrix for the
pure UP-US game would look something like that in Figure 5(b). The state of
microbial infection has conventionally been characterized as lying on the
extreme conflict end. This depiction comes from the Manichaean view of the microbe-human host
relationship. This situation
is depicted in Figure 5(b) as a two-player game. In the pure conflict game, the relationships
between the microbes and their hosts end up in a “war of all against all” in
which the payoffs of the outcomes add to zero (zero-sum). The three microbial
community principle and the dynamic Sym-Pat duality concept would help establish a holistic view of microbial infections. The
CP-CS interaction is a situation where cooperation and conflict coexist. As
illustrated in Figure 5(c), the payoffs for the CP-CS games would lie midway
between the pure cooperative and pure conflict games. The CP-CS problems are
microbial dilemmas, in which there is a mixture of mutual dependence and
conflict of partnerships and competition. The underlying idea arises naturally
from the well-known games for the social dilemmas and the Prisoner's Dilemma
(PD), in which each player chooses between a cooperating and a defecting
strategy [40]. As shown in Figure 5(c), each player receives a higher
playoff by defecting than by cooperating, no matter what the other player
chooses. However, they receive a higher playoff if both cooperate than both
defect. The CP-CS interactions can coevolve toward two different directions,
increasing (more cooperation) or decreasing  (more antagonism) the SP (see Figure 2).(a) Pure cooperative game. (b) Pure conflict
game. H: host; M: microbes.  (c) Dilemma game. The number in the left of each
pair indicates the payoff for microbes, and the right, the host. Higher numbers
represent greater payoff for the individual. Two strategies (Cooperation (C) and
Defection (D)) are used.
(a)(b)(c)


## 4. Discussion

In this paper, focal point
theory-based game models are proposed for analysis of the dynamic Sym-Pat duality
in microbial infections. DSPD is the most fundamental problem in infectomics,
which is the integration of omics and mathematical/computational approaches.
There are three types of infectomic approaches that can be used for the control
of microbial infections: ecological infectomics, immunoinfectomics, and
chemoinfectomics [2]. Ecological infectomics will explore symbiotic solutions
to microbial infections. Developing novel immunological intervention strategies
for the prevention and treatment of microbial infections using infectomic
signatures and immunomic approaches falls within the field of immunoinfectomics.
Chemoinfectomics represents
the most powerful approach to the development of a new generation of drugs for
antimicrobial chemotherapy.


### 4.1. Symbiosis Point Converting (SPC):  Ecological Infectomics-Based Approaches for  Rational Control of Microbial Infections

As microbial
infection is an ecological and evolutionary paradigm which is associated with
coevolution between hosts and microbes (such as human host and microorganisms,
phages, and bacteria) in dynamic ecosystems, two ecological infectomics-based
SPC approaches (increasing and decreasing SP) can be used for rational control
of infectious diseases [2]. The focus
in SP increasing approaches is how to transform situations of potential
conflict (pathogenesis) into cooperation (symbiosis) by dissecting the dynamic
duality relationships between Sym and Pat in microbial infections and
developing symbiotic agents (symbiotics) that favor a healthy symbiosis [2].
Symbiotics are defined as products that are beneficial to symbiotic ecology of the
superorganisms consisting of microbes and their human hosts. These include
microbial (e.g., probiotic bacteria) and nonmicrobial agents (e.g., prebiotics)
[2]. The introduction
of beneficial symbiotics with higher SP in our body should be a very attractive
rationale for modulating the microbiota, improving the symbiotic homeostasis of
the superorganism, and providing a microbial stimulus to the host immune system
against pathogens. The use of probiotics has been suggested as a promising
approach for combating infectious diseases, and delivering drugs and vaccines [2].
Decreasing SP is another rational strategy for control of microbial
infections. As phages, which specifically kill bacteria, play an
important role in the ecology, evolution, and virulence of a number of
pathogens, there is a rational use of phages for treatment and prevention of
bacterial infections. The use of phages to treat bacterial infections has a
long history dating back to mid 1910's [2]. Due to the availability of
effective broad-spectrum antibiotics in the early 1940's, phage therapy was
discarded in Western medicine at that time. The rising crisis of antibiotic
resistance has recently increased great interest in phages and their use as
natural antimicrobial agents to fight microbial infections [2]. Compared with
commonly used antibiotics, a great advantage of phages is their narrow host
range. Recent studies have shown that coinfection with GB virus C (GBV-C) is
associated with a decreased mortality in HIV-infected patients [41]. Therefore,
reducing SP between microbial agents (such as phages and GBV-C) and
targeted
pathogens is another excellent ecological approach for the development of novel
antimicrobial agents.


### 4.2. Specific Pathogen-Targeting (SPT): Immunoinfectomics- and  Chemoinfectomics-Based Approaches  for Prevention
and Treatment of Infectious Diseases

In contrast to the ecological
infectomics-based SPC approaches that focus on the symbiotic relationships
(such as NP-NS and CP-CS interactions) between the hosts and microbial
communities, immunoinfectomics- and chemoinfectomics-based SPT approaches
emphasize the use of antagonistic relationships (such as UP-US interactions)
between the hosts and microorganisms. It is important to point out that the SPT
approaches are intrinsically different from the conventional pathogen-targeting
antimicrobial agents, which kill both pathogens and nonpathogens [2]. The
availability of the genomic information from both microbes and their hosts has
resulted in exciting new progress in the field of immunoinfectomics. Nanobody
(the smallest fragment of naturally occurring single-domain antibody)-based
technologies and immune epitope mapping have emerged as the very powerful tools
for the discovery and development of novel antimicrobial agents [2]. Recently,
a nanobody-conjugated human trypanolytic factor has been successfully used for
an experimental therapy of African trypanosomiasis [42]. Concurrent advances in
both high-throughput chemistry and infectomics have given rise to the field of
chemoinfectomics for elucidating and validating drug targets, and generating
novel therapeutics. Chemoinfectomics refer to the use of small synthetic
molecules that are highly specific for defined infectomic targets, for
biological function analysis and to discover new drug leads. The progress
towards understanding the dynamic Sym-Pat duality in microbial infections using
focal point theory-based game models will greatly facilitate the use of
ecological infectomics, immunoinfectomics, and chemoinfectomics for the
rational control of infectious diseases.


## 4.1. Symbiosis Point Converting (SPC):  Ecological Infectomics-Based Approaches for  Rational Control of Microbial Infections

As microbial
infection is an ecological and evolutionary paradigm which is associated with
coevolution between hosts and microbes (such as human host and microorganisms,
phages, and bacteria) in dynamic ecosystems, two ecological infectomics-based
SPC approaches (increasing and decreasing SP) can be used for rational control
of infectious diseases [2]. The focus
in SP increasing approaches is how to transform situations of potential
conflict (pathogenesis) into cooperation (symbiosis) by dissecting the dynamic
duality relationships between Sym and Pat in microbial infections and
developing symbiotic agents (symbiotics) that favor a healthy symbiosis [2].
Symbiotics are defined as products that are beneficial to symbiotic ecology of the
superorganisms consisting of microbes and their human hosts. These include
microbial (e.g., probiotic bacteria) and nonmicrobial agents (e.g., prebiotics)
[2]. The introduction
of beneficial symbiotics with higher SP in our body should be a very attractive
rationale for modulating the microbiota, improving the symbiotic homeostasis of
the superorganism, and providing a microbial stimulus to the host immune system
against pathogens. The use of probiotics has been suggested as a promising
approach for combating infectious diseases, and delivering drugs and vaccines [2].
Decreasing SP is another rational strategy for control of microbial
infections. As phages, which specifically kill bacteria, play an
important role in the ecology, evolution, and virulence of a number of
pathogens, there is a rational use of phages for treatment and prevention of
bacterial infections. The use of phages to treat bacterial infections has a
long history dating back to mid 1910's [2]. Due to the availability of
effective broad-spectrum antibiotics in the early 1940's, phage therapy was
discarded in Western medicine at that time. The rising crisis of antibiotic
resistance has recently increased great interest in phages and their use as
natural antimicrobial agents to fight microbial infections [2]. Compared with
commonly used antibiotics, a great advantage of phages is their narrow host
range. Recent studies have shown that coinfection with GB virus C (GBV-C) is
associated with a decreased mortality in HIV-infected patients [41]. Therefore,
reducing SP between microbial agents (such as phages and GBV-C) and
targeted
pathogens is another excellent ecological approach for the development of novel
antimicrobial agents.


## 4.2. Specific Pathogen-Targeting (SPT): Immunoinfectomics- and  Chemoinfectomics-Based Approaches  for Prevention
and Treatment of Infectious Diseases

In contrast to the ecological
infectomics-based SPC approaches that focus on the symbiotic relationships
(such as NP-NS and CP-CS interactions) between the hosts and microbial
communities, immunoinfectomics- and chemoinfectomics-based SPT approaches
emphasize the use of antagonistic relationships (such as UP-US interactions)
between the hosts and microorganisms. It is important to point out that the SPT
approaches are intrinsically different from the conventional pathogen-targeting
antimicrobial agents, which kill both pathogens and nonpathogens [2]. The
availability of the genomic information from both microbes and their hosts has
resulted in exciting new progress in the field of immunoinfectomics. Nanobody
(the smallest fragment of naturally occurring single-domain antibody)-based
technologies and immune epitope mapping have emerged as the very powerful tools
for the discovery and development of novel antimicrobial agents [2]. Recently,
a nanobody-conjugated human trypanolytic factor has been successfully used for
an experimental therapy of African trypanosomiasis [42]. Concurrent advances in
both high-throughput chemistry and infectomics have given rise to the field of
chemoinfectomics for elucidating and validating drug targets, and generating
novel therapeutics. Chemoinfectomics refer to the use of small synthetic
molecules that are highly specific for defined infectomic targets, for
biological function analysis and to discover new drug leads. The progress
towards understanding the dynamic Sym-Pat duality in microbial infections using
focal point theory-based game models will greatly facilitate the use of
ecological infectomics, immunoinfectomics, and chemoinfectomics for the
rational control of infectious diseases.



---

*Source: 856314-2008-03-02.xml*