## 1. Background



Philosophy of biology used not to pay a great deal of attention to
microbes (aka microorganisms) and microbiology. This neglect occurred
not because of active bias but simply because of habits gained from
contingent influences on the development of the field. For example,
the scientists most connected with the expansion of philosophy of
biology in the 1960s and 1970s happened to be zoologists and
evolutionists (e.g., Ernst Mayr and Richard Lewontin). Their interests
and expertise naturally and productively shaped the way in which
philosophy of biology made headway throughout the 1980s and 1990s (see
the entry on
 philosophy of biology).[1]




But once the field was strong and thriving, a "zoocentric
perspective" on philosophy of biology became hard to justify
(O'Malley and Dupre 2007). In biology, ever-increasing
molecular insight into life on Earth disclosed massive roles for
microbes, both ecologically and evolutionarily. Philosophically,
treating animals and particularly humans as paradigm organisms was
recognized as indefensible, except for particular metazoan (i.e.,
animal) features of philosophical interest thought to have no
microbial analogues (e.g., predation, ageing, kin recognition,
 cognition).[2]



The tide turned in the mid-2000s, when increasing numbers of
philosophers began using microbes as examples, or microbiological
science as a source of case studies. Evolutionary, classificatory and
phylogenetic issues took up the bulk of this new attention
(Franklin-Hall 2007; Ereshefsky 2010; Velasco 2010), which expanded to
include questions about individuality (Dupre and O'Malley
2007; Ereshefsky & Pedroso 2013) and the origins and nature of
life in its earliest microbial forms (Cleland 2007; Parke 2013). New
topics that refer to microbes these days include even the evolution of
mind and subjectivity (Godfrey-Smith 2016; Allen 2017). It is now
fairly mainstream to mention microbes or use microbiological case
material in philosophical discussions of any sort of biological
phenomenon.



A clarification necessary at the outset is that none of this work
depends on or justifies drawing a hard line between microbes and
non-microbes. Life is not most effectively divided into two obvious
groups of microbes and macrobes, nor unicellular and multicellular
organisms (see
 Table 1).
 These are terms of pure convenience, with many exceptions
(O'Malley 2014). Older "kingdom" perspectives
identified at least two kinds of microorganisms (bacteria and
protists), plus three kinds of multicellular organisms (plants, fungi,
and animals) (Whittaker 1969). Subsequent classifications expanded the
category to which bacteria belong, and sometimes continued to conflate
them with a superficially similar group of organisms now called
Archaea (e.g., Margulis 1996). From cell-biological and evolutionary
perspectives, however, lumping Bacteria and Archaea together as one
kind of life is seriously misleading (Woese 1994; Pace 2006; Embley
& Williams 2015;
 Table 1).





|  |  |  |
| --- | --- | --- |
| **Term** | **Usage/definition** | **Issues and context** |
| **Microorganism, microbe** (informal) | Unicellular organism; sometimes any organism viewed
microscopically  | Many microbes form multicellular colonies or structured
consortia; some single cells are visible (e.g., slime moulds); no
classificatory or evolutionary basis  |
| **Macroorganism, macrobe** (very informal)  | Multicellular organism; sometimes any organism visible without a
microscope  | Most multicellular organisms are occupied by unicellular ones;
some multicellular organisms are microscopic (e.g., tardigrades); no
classificatory or evolutionary basis  |
| **Bacteria** (informally bacteria (not in title
case), singular bacterium), for a short while called eubacteria (still
popular in some accounts); colloquially known as
'germs'  | Domain-level category of life that includes dozens of phyla of
bacteria  | Takes off as a term for the smallest unicellular organisms in
the mid-nineteenth century; included Archaea until their
identification in the 1970s  |
| **Archaea** (informally archaea (not in title
case), singular archaeon), previously archaebacteria (still used in
some accounts)  | Domain-level category of life that includes several major
branches, of which eukaryotes are now widely believed to be
one  | Considered by some systematists not to be sufficiently important
to be a domain of equal status to eukaryotes; questions now about
whether eukaryotes are part of Archaea or a new domain derived from
it.  |
| **Prokaryote** (informal)  | Older term of convenience often used to mean non-eukaryote;
cells without classic nucleus and other compartments  | No evolutionary basis; obscures major evolutionary divergence of
Bacteria and Archaea; potentially emphasizes the mere absence of
eukaryote features  |
| **Eukaryote** (informally eukaryote(s)),
sometimes Eukaryota/Eucaryota or Eukarya/Eucarya  | Cells with nucleus and other compartments, including
mitochondria (not obligatory to definition); includes kingdom-level
groups of animals, plants and algae, fungi, and protists | Not clear this distinctive cell type is best considered a
domain; may be an important diversification within Archaea;
traditional kingdom categories do not capture the mostly microbial
nature of eukaryotes.  |
| **Protist** (informal), previously Protista,
Proctoctista etc (includes protozoa)  | Unicellular eukaryotes of mixed lineages; can include fungi and
multicellular algae. Classic examples are pathogens (e.g.,
*Giardia*) and photosynthesizers (e.g., algae)  | Most eukaryotes are protists of one sort or another. 
 |
| **Virus** | Non-cellular replicators using either eukaryotic or archaeal
cells to reproduce; not micro*organismal*, but often included in
casual discussions of microbes  | Despite not being cellular or self-replicating without a host,
and thus not 'living' by most accounts, it is difficult to
understand microbial life without paying attention to
viruses.  |
| **Bacteriophage**, phage  | Non-cellular replicators using bacterial cells to reproduce; not
micro*organismal*, but often included in casual discussions of
microbes  | Despite not being cellular or self-replicating without a host,
and thus not 'living' by most accounts, it is difficult to
understand bacterial life without paying attention to
phages. 
 |
| **'Lower organism'**: antiquated
terminology for small and less apparently complex lifeforms
 | Persists in non-microbiological discussions of
microbes  | Not validated by any biological or evolutionary approach; tends
to imply great-chain-of-being progressivism.  |
| **'Higher organism'**: similarly
antiquated terminology for large and more obviously complex
organisms  | Persists in zoology, botany, and some broader communication of
biology (see Rigato & Minelli 2013)  | Not validated by any biological or evolutionary approach; tends
to imply great-chain-of-being progressivism.  |



Table 1: serves as a glossary for
subsequent sections. It shows some of the historical terminology and
classifications of microbes, plus issues with various terms and
categories. 




Recognizing the looseness of the terms used to designate microbes does
not mean, however, that either the study or impact of microorganisms
is incoherent or disconnected. Unicellular life forms--organisms
with the ability to live and reproduce as a single cell most (but not
necessarily all) of the
 time[3]--are
 often argued to have large biological spheres of action and thus
implications for all living things.


## 2. Reasons to Pay Attention to Microbes



This section marshals the main reasons for paying attention to
microbes. It describes what microorganisms do, and how they lend
themselves to philosophical investigation. 


### 2.1 Biological reasons



Although "biological" can refer to a multitude of
phenomena, the focus here is on the ecology and evolution of microbes.
Ecology and evolution not only work together to explain the properties
of particular microorganismal groups, but also reveal the broad
biological relevance of microorganisms to all life, and to human quality of life.


#### 2.1.1 Ecological reasons



A basic reason to pay attention to microbes can be inferred from
claims that humans live in a fundamentally microbial world (e.g.,
Staley et al. 1997). Statements of this sort refer to the
pervasiveness of microbes throughout the planet, and the fundamental
contributions they make to every ecosystem. Two aspects of microbial
processes in the world stand out to make this view possible:
biogeochemical cycles and microbial symbiosis. Both matter a great deal to human existence, from the maintenance of the planet as we know it to the health of our own bodies.



Biogeochemical cycles are what make the planet "function"
in any sense. On Earth today, carbon, oxygen, and nitrogen cycles are
particularly obvious. These cycles are interdependent, and display a
degree of stability over geological time (e.g., oxygen has made up 21%
of the Earth's atmosphere for almost half a billion years,
despite extraordinary fluctuations in lifeforms and physical features
of the planet such as temperature). Although geological processes
sustain such cycles over very long timescales, the world humans
experience is largely a product of far more rapid microbial
interactions. Microbes "run" most of these cycles as they
generate energy from chemical compounds and light (Falkowski et al.
2008; Jelen et al. 2016). Microorganisms prevail even when they
comprise less of the biomass involved than macroorganisms
participating in the same process. For example, plants form the
physical bulk of organisms involved in carbon and oxygen cycles
(Bar-On et al. 2018), but a large amount of that biomass is made up of
non-living material in woody plants. This material is often called
"heartwood", and it does not contribute actively to
biogeochemical cycles (Chattaway
 1952).[4]
 In fact, the very tendency of microbes not to hoard elements in the
form of biomass and instead, to have a high turnover of metabolizing
populations (Strom 2008; Zimmerman et al. 2020), could explain in part
why there are fairly rapid biogeochemical cycles on the planet rather
than long-term chemical sinks.



Animals such as ourselves could not live without oxygen, which is a
powerful electron acceptor that allows the energy investments
permissive of large animal body size (Payne et al. 2011). Oxygen on
this planet would not have become available were it not for pioneering
oxygen-producing microbes, which are photosynthesizers called
cyanobacteria. They not only began to excrete oxygen almost three
billion years ago, but their very capacity to do so was forcibly
captured by later eukaryotes and eventually led to algae, plants, and
the planet we know today. In a distal causal sense, therefore,
philosophy is possible because of bacterial photosynthesis.



The chemical cycling carried out by microbes occurs not only at a
macroscale with planetary implications, but also internally, in our
very own bodies. Symbiosis, the intimate "living together"
of different organisms, is a key organizational motif of the microbial
world, but it reaches far beyond microorganisms to encompass every
(relatively) large living thing. Long recognized and conceptually
debated, symbiosis is usually deemed to include a variety of
relationship types: negative consequences for one of the organisms
(parasitic), positive outcomes for both (mutualistic), and various
mixes of beneficial and "non-harm, non-help" relationships
(commensal) between microbes and their partners (Saffo 1992; Sapp
2004).



A classic symbiotic relationship is found in lichens, which are made
of tightly integrated fungi and photosynthesizing microbes (algae,
cyanobacteria or both). Although the contributing organisms reproduce
separately, they form similarly organized units of lichen, generation
after generation. Benefits are often thought to accrue for both
partners, and are cashed out as higher reproductive fitness (Honegger
1998; however, cf. Hyvarinen et al. 2002). Many other symbioses
are intimate and persistent, but more obviously manipulate at least
one of the partners in the arrangement. A curious example is the
bacterium *Wolbachia* in insects. This bacterium is obligately
part of the insect reproductive process. It can "feminize"
insect embryos and kill males to ensure its own reproduction (Werren
et al. 2008). But despite *Wolbachia* hijacking the insect for
its own reproductive requirements, there are variable fitness benefits
for its host (e.g., Fry et al. 2004). In some host-symbiont systems,
*Wolbachia* and the insect can benefit, despite the
manipulation of the latter by the former.



All humans are involved in a range of ongoing stable symbioses with
microbes living in and on our bodies. The majority of these microbes
are in the gut, but the skin, lungs, and every bodily orifice are
populated by multiple groups of interacting microorganisms. Many of
the microbes in our gut are not really helping or harming us: they are
there to take advantage of the nutritional resources that are so
plentiful in the intestines. Our body's immune response controls
and manages them so they are at least not detrimental, even if they
are ineliminable. Inescapable symbiosis implies, however, that human
bodies are intrinsically and inseparably microbial ecosystems. Whether
this is meaningful in any philosophical sense will be discussed in
detail in
 Section 5.
 Human bodies are not where this question ends, however.



Because symbiotic microorganisms are tiny and pervade all ecosystems,
and because such symbioses contribute so much metabolically to the
overall biochemical activity on the Earth, some theorists have been
moved to suggest what is known as the Gaia hypothesis of the living
Earth. In this view, Gaia is the total complex of "atmosphere,
biosphere, oceans and soils" that is regulated by "a
feedback or cybernetic system which seeks an optimal physical and
chemical environment for the biota" (Margulis & Lovelock
1974: 473). Microorganisms are given primary mechanistic
responsibility for such regulatory effects, even though all life
participates in self-maintenance of the wider system. Many biologists
and philosophers remain unpersuaded by the Gaia hypothesis (see Resnik
1992; Pigliucci 2014); nevertheless, it is worthy of mention as an
instance in which the versatility, abundance, minuteness and
pervasiveness of microbes lead to them being given a powerful
ecological status for their roles in determining the way life works on
Earth.


#### 2.1.2 Evolutionary reasons



Another way in which microbes have a dominating role in biology is
because so very much of Earth's evolutionary history is devoted
to them. Stephen Jay Gould, a microbiologically aware zoologist, is
often quoted to capture the historical saturation of life on Earth by
"bacteria" (which probably include Archaea in the sense he
means--see
 Table 1):



> 
> 
> The most salient feature of life has been the stability of its
> bacterial mode from the beginning of the fossil record until today
> and, with little doubt, into all future time so long as the earth
> endures. This is truly the "age of bacteria"--as it
> was in the beginning, is now and ever shall be. (Gould 1994: 87)
> 
> 
> 



In whatever way life began approximately 3.8 billion years ago, the
first cells were something recognizably microbial, most probably
bacterial. The next two billion years were also exclusively microbial,
with Bacteria and Archaea manipulating the planet's geochemistry
to their own metabolic advantage, except when those unable to adjust
to rising oxygen levels were wiped out by the cyanobacterial excretion
of it. Another accidental consequence of microbial diversification was
the formation of eukaryotic microbes, which fewer than a billion years
ago diversified into the ancestral forms of the various multicellular
groups we recognize today. Most of that diversification has in fact
happened just in the last half billion years, in conjunction with
ongoing microbial activities, hence Gould's epithet.


### 2.2 Philosophical reasons



All very well, you might say: biologists certainly should think
microbes are important. But what about philosophers? What can microbes
tell them? There are numerous debates in philosophy of biology in
which neglecting microbes would seriously weaken, or at least bias,
any philosophical conclusions that might be reached. This entry will
focus on three connected philosophy of biology topics: views about
species, the tree of life, and major transitions in evolution. A
discussion of a broader philosophy of science topic, philosophy of
modelling, follows in
 Section 3.


#### 2.2.1 Species concepts



Species concepts might be of little philosophical interest if the only
organisms that needed classifying were animals. The most applicable
and conceptually well-founded species concept for animals--and
the most familiar species concept to those outside biology--is
the biological species concept (BSC). It says that a species is a
group of organisms that can breed only within that group. Even though
there are some well-recognized problems in applying a single species
concept to all animal life (see Dupre 2001), problem cases are
usually seen as exceptions that do not fundamentally trouble the BSC
(Mayr 1982; Coyne & Orr 1998; however, cf. Mallet 2008). Plants introduce additional
but probably surmountable problems, argue many zoologists (e.g., Mayr
1982); unfortunately, fungi might be beyond the pale by virtue of
resisting any such "universal" species concept (see
Petersen & Hughes 1999). But since many fungi are unicellular, and
exhibit all kinds of reproductive oddities, it might just be safest to
accept the old assertion that unicellular and particularly asexual
organisms do not and cannot form species, and thus are not exceptions
to a universal species concept (e.g., Mayr 1987). These are just some
of the issues that arise when venturing beyond animals in attempts to
apply species concepts. In response to these sorts of issues, a range
of other species concepts have been proposed, drawing on
morphological, molecular, or evolutionary characteristics such as
forming lineages of a certain sort (see the
 SEP entry on species).



Microbes, and particularly Bacteria and Archaea, provide a treasure
trove of problems for species concepts. They do not sexually
reproduce, they are not morphologically rich for the most part
(protists are, so morphology has been a large part of their historic
classification), and they do not form the right sort of reproductively
isolated lineages. Importantly, whatever lineage-like interpretations
can be made of their descent relationships are confounded by major and
promiscuous episodes of gene transfer between these otherwise distinct
lineages (Doolittle 1999; Martin 1999; Gogarten et al. 2002). As soon
as philosophers consider microbes, especially Bacteria and Archaea,
they usually default to a pluralistic view of species concepts. It is
one thing to find a concept that mostly works for animals and even
plants, but it is more or less universally admitted that no single
concept works across the entirety of the diversity of the tree of
life, on any reconstruction of that tree (Dupre 2001;
Ereshefsky 1998, 2010; Doolittle & Zhaxybayeva 2009).


#### 2.2.2 The tree of life



The tree of life is a representation of species in the form of lineage
relationships, or at least that is how it is commonly interpreted
(Ragan 2009; O'Malley et al. 2010). By making inferences from
present-day data back to ancestral states, including common ancestry
and divergence points, evolutionary biologists can build phylogenies,
which not only capture evolutionary relationships but also give them
approximate dates. Phylogenies have traditionally been constructed on
the basis of morphological data, including fossils, but the last few
decades have seen the rapid rise of molecular phylogenies. The use of
gene and protein sequences, plus computational methods, has allowed
far finer grained and more extensive reconstructions of all life on
the tree (including organisms with limited morphological characters,
such as microbes and fungi).



However, one unanticipated consequence of such a proliferation of data
and trees has been the repeated finding that many prokaryotic
organisms exchange genes between lineages, including genes of major
lineage-defining importance. The extent and significance of such
transfers is such that the standard method of constructing a
phylogeny, in the form of a graph-theoretic representation of lineages
admitting only vertical descent, is violated. In addition, molecular
data reveals the extent of hybridization in multicellular organisms
(Mallet et al. 2016). The
tree of life therefore becomes a questionable construct (Doolittle
& Bapteste 2007; Dagan & Martin 2009), both metaphysically and
pragmatically. At the very least, any philosopher reflecting on the
tree of life and what it represents will have to consider microbial
evolution (Velasco 2010).


#### 2.2.3 Major transitions in evolution



Major transitions have been a focal topic in philosophy of biology
since John Maynard Smith and Eors Szathmary's book,
*The Major Transitions in Evolution* (1997). They focused on
key transitions in the history of life on Earth ranging from the
origin of cells to the origin of sex to the origin of language.
Philosophical discussion of the major transitions in evolution largely
revolves around efforts to find a unifying theme to bind major
transitions into a single theory (the same aspiration that drives many
species and tree of life discussions). A common choice for that theme
has been individuality, meaning any major transition in evolution is
understood to involve most centrally a transition in evolutionary
individuality (e.g., Ratcliff et al. 2017; Michod 2011; however, cf.
O'Malley and Powell 2016). But irrespective of any particular
theoretic commitment to the nature of evolutionary transitions,
microbial evolution is crucial for understanding the various
transformations life on Earth made on the way to its current state.
This is very much the case even if theorists want to understand only
the evolution of eukaryotes, or even if they care exclusively about
the origin of metazoa--the "kingdom" within
eukaryotes to which humans
 belong.[5]



Eukaryotes are organisms characterized by intracellular complexity,
and in particular, by the compartmentalizing organelles within their
cells. Most prokaryotes do not exhibit the same degree of
compartmentalization (however, cf. Murat et al. 2010). The majority of
eukaryotes are unicellular (Burki et al. 2020), but the macroscopic
ones are almost all multicellular and often conspicuous. It is very
common for scientists and philosophers to consider bodily bulk and
multipart complexity as phenomena of evolutionary importance (e.g.,
Carroll 2001). Although there can be many ecological reasons that
sustain that impression (i.e., the sheer impact large organisms have
on environments; see Enquist et al. 2020), recent findings about the
origins of eukaryotes might temper that view at least a little.



The long-standing view on the origin of eukaryotes is: A. That they
arose from a merger of a bacterium and an archaeon; and B. That this
unique lineage flourished and carved out its own "domain"
space in phylogeny (see
 Table 1).
 Being a domain is at least partly justified by the diversity and
complexity of the organisms that comprise eukaryotes (Butterfield
2014): plants, animals, fungi and protists. Recently, however,
discoveries have been made of a diverse group of Archaea, known as the
Asgard clade. Theoretically important eukaryotic features have been
inferred from their genes (Eme et al. 2017). These gene-based
inferences indicate that eukaryotes fit firmly *within* the
domain of Archaea, where they form a rather morphologically
heterogeneous group, but nevertheless remain subordinated to their
basic archaeal identity (Williams et al. 2020). The same inferences
also suggest that eukaryotes originated gradually, driven by gene
diversification of various sorts (including gene transfers), and that
the endosymbiotic acquisition of the bacterium that became the
mitochondrion possibly occurred late in the evolutionary story (Pittis
& Gabaldon 2016). In other words, this
"transition" is not primarily driven by a transformation
in individuality, and is first and foremost a story about
diversification within Archaea. Many details are still to be divulged
about the extant relatives of the group of Archaea closest to
eukaryotes, but a clear message is already available: understanding
the origin of eukaryotes requires understanding the evolution of
Archaea.



A similar lesson can be learned even when moving further along the
historic branches of a schematic tree of life to gain insight into the
origin and diversification of metazoans. Although classic schemes do
not include the origin of metazoans as a major transition, it is
nevertheless a diversification of particular importance from a human
perspective (Carroll 2001). Even if the origin of eukaryotes is
thought to be uninteresting, because their original state is
necessarily unicellular, nobody would disagree that the origin of
metazoans is highly pertinent to understanding human evolution, since
all metazoans are multicellular and humans are a group within
them.



Interestingly, however, much of the recent progress in understanding
the origin of metazoans depends on findings about close unicellular
relatives of animals, particularly choanoflagellates as well as
slightly more distant protists called filastereans and
ichthyosporeans. Genomic and experimental analyses of these organisms
have allowed evolutionary inferences about genes and features once
thought to be exclusively metazoan. It turns out that the genetic
bases of many characteristics once thought of as unique to metazoan
evolution are also found in closely related unicellular organisms.
Adhesion capacities, developmental signalling pathways, and
"metazoan-specific" gene regulatory factors--all
features not normally thought of as properties of unicellular
organisms--long pre-existed metazoan origins
(King et al. 2008; Sebe-Pedros et al. 2017). Moreover,
many of these extant unicellular relatives of metazoans turn into
different cell types as they transition to different stages in their
life cycles. Some stages form sophisticated multicellular
arrangements, which may sometimes be driven by interactions with
bacteria (Alegado et al. 2012; Woznica et al. 2016). The moral of this
story is thus becoming familiar: even the evolutionary divergence of
the organisms considered the most complex (because of giving rise to
ourselves) needs a microbial perspective.



So far, this entry has discussed microbes from a "microbes-eye
perspective" of biological classification, ecology and
evolution. But of course there is a whole scientific field called
microbiology, which is a collection of methods designed specifically
to reveal what is going on in the microbial world. We now
examine more directly that science and some of its philosophical
implications.


## 3. Microbiological Science



> 
> 
> Microbiology of the future will become the primary biological science,
> the base upon which our future understanding of the living world
> rests, and the font from which new understanding of it flows. (from
> journal summary of Woese
>  1994[6])
> 
> 
> 



Although it can be argued that microbiology began with microscopy in
the early seventeenth century (e.g., Gest 2004; Lane 2015), the
disciplinary starting point for bacteriology and eventually
microbiology is usually bestowed on its experimental turn a couple of
centuries later (Bulloch 1938). Early microscopy allowed observational
microbiology for sure, but it gave rise to limited classification, and
even more limited insights into what microbes could do consistently.
The second half of the nineteenth century is when experimentation on
microbes was codified, with the aim of understanding the specific and
stable effects of particular microorganisms on disease in animals and
plants. A central part of this emerging tradition involved pure
culture techniques, Koch's postulates, and germ theory. Each of
these has ongoing philosophical ramifications.



Medicine changed fundamentally in the later part of the nineteenth
century, and many historians of medicine locate the scrutiny of
microorganisms via experimental laboratory methods at the heart of
this transformation (e.g., Worboys 2000; Kreuder-Sonnen 2016). Pure
culture, in which isolated and putatively causal microorganisms are
grown in laboratories, was the first step. Normally, bacteria and
other microbes live in complex multispecies communities. Such
communities, however, are useless for identifying and intervening on
the causes of diseases. Various innovations of nineteenth-century
laboratory science (glassware, growth media, identification methods,
micrography) enabled verifiable pure cultures of single species to be
grown independently of their host organisms. Such cultures in turn
allowed Koch's postulates for causality to be implemented.



Koch's postulates are a general method to identify causal
outcomes from specific bacteria. Microorganisms isolated and grown
from diseased hosts are introduced to non-diseased hosts to see if the
same disease obtains. Cultures from that new disease site then confirm
the presence and activity of the suspect microbe (Ross & Woodward
2016; Gillies 2016). Once it could be established that these causal
effects are highly specific and stable, the germ theory of disease
could then draw all such findings into one common framework with
predictive power (e.g., tuberculosis will always be caused by a
particular bacterium, then known as the tubercle bacillus). The
systematicity and experimentality underlying germ theory thus began
the transformation of medicine from a purely observational and often
anecdotal activity to an increasingly experimental and scientifically
robust programme of research that had therapeutic and preventive
successes (Worboys 2000; Vernon 1990). As a consequence, the
investigation of bacteria and other microbes was integrated into a
range of established disciplines in universities, hospitals and
independent institutions (including industry) from the late nineteenth
century onwards (Vernon 1990).



This tendency of microbiology to pervade and transform other fields is
a hallmark of the science's development. Molecular microbiology,
a product of the mid-twentieth century, amply illustrates this trend.
Following the successes of germ-theoretic accounts of microbes and
disease, microbial biochemistry flourished as microbiologists focused
on the precise causal pathways by which microbes achieved their
effects (whether in hosts or other environments). The laboratory
tractability of microbes and versatility of their metabolic
accomplishments gave rise to a vast experimental literature on
bacterial biochemistry (e.g., Kluyver 1936; Stephenson 1939). In the
1940s, this background lent itself to the emerging field of what
became molecular biology, in which all the initial major discoveries
were made in microbial systems. The bacterium *Escherichia
coli* (*E. coli*) in particular had epistemic



> 
> 
> primacy in forging our picture of the fundamentals of life--the
> physical and chemical underpinnings of gene structure, replication,
> and expression ... [these and other] prokaryotes gave us the
> language and much of the knowledge of molecular biology relevant to
> all organisms to this day. (Davis 2003: 154; see also Brock 1990)
> 
> 
> 



The very identification of DNA as the material of heredity was carried
out in bacterial and viral experimental systems (Avery et al.
1943; Hershey & Chase
1952). Subsequently, the expansion of molecular biology into genome
sequencing and metagenomics (the sequencing and analysis of whole
community genomes) began and flourished in microorganisms. This
broader molecular scope enabled not only methodological and
technological advances (see
 SEP entry on genomics and postgenomics),
 but also major evolutionary and ecological insights into the
evolutionary history and community dynamics of large swathes of the
biosphere (Davis 2003; Handelsman 2004). Most new empirical insights
into major evolutionary transitions (as discussed in
 Subsection 2.2.3)
 are based on these genomic and metagenomic microbial
investigations.



Both in the early and later developments of molecular biology,
microbes functioned in many respects as general molecular models for
biological insight and technological development. The very fact that
microbes can play this stand-in role for life in general drove many
successes in the field. However, it might be a concern that microbes
are useful only for what they tell researchers about microbial life,
and that the knowledge generated by microbiological investigations
will always be restricted to aspects of microbial biology. For
instance, gene regulation in the form of operons (modules of genes
treated as genetic regulatory units) was discovered in the bacterium
*E. coli,* as well as in one of their viruses, in the 1950s
(Jacob & Monod 1961). But although there are now known to be many
important differences between bacterial and eukaryotic gene
regulation, and different modes of gene regulation within just
bacteria (Beckwith 2011), the *E. coli* operon model launched a
whole field of investigation driven by general expectations about how
gene expression could be effectively controlled (Brenner et al. 1990).
Ultimately, eukaryotic gene regulation had to be studied in tractable
multicellular organisms in order to ascertain the additional
complexities and differences of eukaryote gene regulation from the
bacterial model.


## 4. Microbes as Models



The lesson to be learned from the above historical discussion is that
even though there are clear limits to the applicability of any model
system, it is equally clear that microbes are remarkable in their
capacity to model living processes in general. This section elaborates
on the various ways this is the case. 


### 4.1 Virtues of microbial models



While physical models of various sorts are used throughout the
sciences, model organisms are a kind of model system particular to the
life sciences. "Model organism" typically refers to the
organisms that are bred, propagated, and studied in laboratories in
the biomedical and life sciences. Classic animal examples include
nematodes ("worms"), *Drosophila* (fruit flies) and
mice*.* An important plant model is *Arabidopsis*
(mustard cress). Fungi are represented by yeast, which is also used to
model all eukaryotes (Botstein & Fink 2011). While a wealth of
important model organism research is carried out on relatively large
organisms, microbes are regarded as especially tractable model
systems. This is very much the case in experimental evolution and
ecology, where microbial systems allow researchers to study dynamical
processes in large populations over many generations. These modelling
capacities have general philosophical implications.



The methodology and epistemology of modelling with model organisms is
a topic of increasing discussion in the history and philosophy of
science (Ankeny & Leonelli 2011; Endersby 2007; see also the
 SEP entry on experiment in biology).
 These discussions include recent debates about what sorts of models
model organisms are, and whether they qualify as genuine models. A
number of philosophers of modelling classify model organisms in the
same category as other physical analogue models, such as the model
airplanes used in studies of aerodynamics or the sandboxes used to
model geological processes in laboratories (Weisberg 2013;
McClay and Dooley 1995;
 SEP entry on models in science).
 However, Levy & Currie (2015) object to this practice, arguing
that model organisms are not theoretical models in the sense of
interpreted structures studied as analogues of target systems in the
natural world. Instead, they see organismal models as specimens of
(and thereby bases for extrapolation about) broader classes of
organisms. Levy and Currie do, however, concede that in some contexts,
such as experimental evolution and ecology, organismal models can play
a very similar role to that of theoretical models. Microbes are common
choices for this role as analogue systems in experimental
settings.



An early illustration of how such organismal analogues work can be
found in Georgii Gause's work in the 1930s modelling
interspecies competition. Gause wanted a simple, easily manipulable
laboratory system that would allow him to "eliminate the
complicating influence of numerous secondary factors" and
"understand the mechanism of the elementary process of the
struggle for existence" (Gause 1934a: 92, 6). In order to
represent in physical terms the logistic equation that models carrying
capacities for populations, Gause set up an experimental system of
populations of two species of paramecia, *Paramecium caudatum*
and *P. aurelia*, both of which eat bacteria. Gause anticipated
that indirect competition between the species would modify one
species' carrying capacity. When the paramecia were physically
separated, each population reached growth equilibrium, but when they
were put together and made to compete for the same limiting bacterial
resources, one species drove the other extinct. This extrapolation
from the logistic equation is nowadays known as the competitive
exclusion principle, and has become a central principle in ecology
(Hardin 1960). The mathematical and experimental model reached the
same conclusions.



However, Gause then tried to use a microbial model to demonstrate the
basic mechanisms represented in another mathematical model of direct
interspecies competition (in the form of predator-prey relationships),
the Lotka-Volterra equations. In this case, his experimental system
repeatedly failed to capture the oscillating dynamics of the
equations. This time he used one of the paramecia (*P.
caudatum*) and its unicellular predator, *Didinium
nasutum*. Both species went extinct, unless Gause introduced
additional physical parameters or modified the mathematics (Gause
1934b). Does this suggest that microbes simply cannot capture the
appropriate dynamics and are unreliable as experimental
representations of mathematical models? In fact, an extensive history
of subsequent experimentation found that the long-term oscillations
predicted by the Lotka-Volterra equations are unrealized in
*any* organismal model system unless major alterations are made
to the basic variables. Only very recently have these oscillations
been achieved over numerous generations, in an experimental model
consisting of unicellular algae and a microscopic metazoan predator
(Blasius et al.
 2020).[7]




An iconic contemporary example of microbial modelling is Richard
Lenski's long-term evolution experiment (Fox & Lenski 2015).
Lenski's group used a single ancestral genome of *E.
coli* to found twelve initially genetically identical populations
in identical flask environments. They began propagating the
populations, by transferring a population sample from a well-mixed
flask to a fresh flask (to replenish their resources) every 24 hours.
Lenski's group began this experiment in 1988 and it is still
going today, which in early 2020 means more than 70,000 generations of
microbial evolution have
 occurred.[8]
 These numbers are due to *E. coli* populations regenerating
just over six times per day, with resource constraints keeping this
number steady.



A key original motivation of the experiment was to learn more about
the long-term dynamics of adaptation and diversification by studying
evolution in real time, in a controlled setting. Because the
populations started out exactly the same and live in identical
environments, any differences in fitness, physiology or morphology
that arise over time are due entirely to new mutations in clonal
lineages (not prone to recombination). Many insights have arisen from
the long-term evolution experiment, including inferences about the
dynamics of mutation, the role of chance in evolutionary trajectories,
and the evolutionary origin of complex novel features (Fox and Lenski
2015). While in a few cases these findings are restricted to
inferences specifically about *E. coli* and similar bacteria
(e.g., Sniegowski et al. 1997), most are considered to apply to the
processes and dynamics of long-term evolution in general. In other
words, the microbes in the laboratory are not modelling microbes
exclusively, but rather serving as a lens through which to understand
more generally the phenomena of evolving life. In some important
respects, these experimental systems are run like algorithms: exact
iterative procedures that lead to various outcomes, and which can be
looped and rerun at various points in the overall procedure.



Algorithms are of course the basis for computational simulations.
Perhaps inspired by these structural similarities, Lenski's
group and other collaborators turned their attention to an agent-based
simulation model called Avida (Lenski et al. 2003). In this
computational model, self-replicating "digital organisms"
compete for resources in the form of computer memory, and can
accumulate mutations over time in their "genomes" (strings
of computer code). Lenski and colleagues are very clear that when they
study Avida, just as when they study their *E. coli* in the
flasks, the aim is to infer something about the evolving world at
large: "When we study this tractable system, we aim to shed
light on principles relevant to any evolving system" (2003:
139). Because Avida allows for open-ended exploration of evolutionary
trajectories via an algorithmic procedure, this way of modelling
evolution turns out to be highly complementary to studying bacteria in
the laboratory.



To give an example: perhaps the most famous result from Lenski's
long-term evolution experiment is the origin of citrate utilization in
just one of the twelve *E. coli* lineages (Blount et al.
2008). Citrate is present
in the bacterial growth medium and is a potential energy source, but
one that *E. coli* lack the ability to use aerobically (i.e.,
in the presence of oxygen)--or, at least they were unable to,
until around 31,500 generations into the experiment when one strain
accumulated the mutations relevant to growing on citrate. This new
capacity gave the population a relative advantage over
non-citrate-eating strains.



To work out how this had occurred, the researchers reconstructed the
particular evolutionary trajectory that led to this multi-step
innovation (Blount et al. 2012). They were able to do this
step-by-step reconstruction because of the tractability of the model
system, and in particular because they had frozen regular time points
in the evolutionary history of each bacterial lineage. Large bacterial
populations can be frozen and later revived; researchers can thus
maintain a "frozen fossil record" (Lenski 2011) and
compare a current population's features (such as fitness or
morphology) to those of its ancestral population, or reconstruct steps
in its evolutionary trajectory. In this case, frozen population
samples could be sequentially analyzed to infer the order of
mutational steps. A very similar sort of reconstruction could be
carried out on the complex mutations occurring in the Avida simulation
(Lenski et al. 2003). The researchers were able to rerun the computer
model many times to understand every step along the way towards the
accumulation of a complex mutation, in this case, a logic function
more complicated than any of the basic instructions in the digital
organisms computer-code genomes. This allowed researchers to study the
accumulation of mutations leading to complex novel traits in two
complementary and comparable sorts of model systems.



Many other small organisms have been used experimentally as living
models of mathematical equations or simulations (e.g., mites,
beetles). But microbes are particularly tractable in that they are
easy to maintain and propagate in a laboratory, especially compared to
other classic model organisms like mice. This is partly because they
are so small: huge populations of them can be kept in tiny spaces. It
is also because some species do not need much looking after compared
to other laboratory organisms; pop them into a flask of growth medium
(a simple mix of a few chemicals) or smear them on an agar plate, and
their populations will grow exponentially. Many laboratory cultured
microbes have very short generation times compared to larger
organisms. Some bacteria can produce tens of generations a day if not
resource constrained, which allows for long-term evolutionary studies
over reasonable human research timescales.



Beyond these practical benefits, however, are epistemic advantages
that allow bacterial models to be compared very readily to
mathematical and computational models. Population size has theoretical
virtues on top of the practical ones. Evolutionary theory predicts
very different outcomes for small versus large populations
(Charlesworth 2002), and
key theoretical tools assume infinite populations (see the
 SEP entry on population genetics).
 The very large population sizes of most bacteria mean they are good
proxies for these idealized equations. Microbial experimental systems
can not only serve as proxies for theoretical models, but also show
when something is fundamentally wrong with the mathematical
assumptions. In the case discussed above, Gause wanted to model the
Lotka-Volterra equations with a microbial analogue experiment. But the
mathematical model assumes that both populations can rebound
continuously from extremely low numbers, and that stochastic processes
do not affect these deterministic outcomes. In many actual
populations, the growth curves simply cannot rebound from very low
values and the stable oscillations do not occur, just as Gause found.
Computational simulations of the Lotka-Volterra equations similarly
find that extinction of predators or both predator and prey is
inevitable unless additional resource limitations are introduced
(Wilensky & Reisman 2006; Weisberg & Reisman 2008). The actual
details of which models do better on what dimensions do not matter
here. The emphasis is on how modellers can shift back and forth from
mathematics to computational simulations to microbial experiments
because of basic structural similarities that are not overwhelmed by
organismal complications (O'Malley & Parke 2018).



The comparability of these very different media can be taken further,
because of the capabilities discussed already for maintaining a
"frozen fossil record" by reviving ancestral populations
and studying their evolutionary trajectories. This allows researchers
to "back up" a population's evolutionary trajectory
and "rerun" it an arbitrary number of times from an
earlier timepoint, by defrosting and reviving (repeatedly) a frozen
ancestral population sample (e.g., Travisano et al. 1995). This
backing up and re-running of population trajectories is very similar
to the recursivity of algorithms in computer simulations. It also
resonates with thought experiments such as Gould's (1989) famous
idea about "replaying the tape of life". While Gould
originally presented the thought experiment as a metaphor, and had in
mind rewinding and replaying *all* of life on earth, long-term
microbial evolution experiments show how at least a subset of
"life"s tape' can actually be replayed (see Beatty
2006 for discussion of the extent to which this sort of experimental
work fits Gould's ideas about his thought experiment).



Thought experiments such as replaying the tape of life have also been
considered "mental models" (see
 SEP entry on thought experiments;
 Nersessian 2018), and
philosophers are very fond of constructing and manipulating such
models to generate new insights. That microbial experimental models,
which are very concrete, can potentially be compared to mental models,
which are very abstract, might seem surprising at first glance. But if
comparability is central to modelling practice (O'Malley &
Parke 2018), and if we recognize a range of model
media--including mental constructs--then perhaps comparing
abstract and idealized thought experiments with material models of
unicellular life more often might be a fruitful philosophical
approach. Now of course empirically inclined philosophers thinking
about cognition or the evolution of behavior might choose instead to
compare their mental models to models based on animals or plants. But
just as Gause wanted the maximum reduction in extraneous complexity in
order to compare basic mathematical structures with living population
structures, then so might philosophers who manipulate mental
structures want a stripped-down living model analogue. Whether or not
philosophers feel encouraged to carry out such comparisons is not the
main point of this section, however, which is primarily to note
that abstract modelling efforts with mathematics and algorithms (and
potentially mental constructs) can effectively be compared with
microbial model systems. Such comparability then raises a whole slew
of additional questions for philosophical inquiry. One of the main
questions is about just how far such comparisons can be taken.


### 4.2 Limits of microbial models?



Even if philosophers concede that microbes might be good models for
some very basic biological processes (e.g., genetic pathways), they
might still believe that many phenomena of relevance to humans and
other animals are too far from any microbial analogue. Because of
initially being defined by animal characteristics, phenomena such as
predation, ageing, and kin recognition have often been thought to be
outside the purview of microbes. However, it turns out that microbes
are, in fact, productive objects of study for many of these
phenomena.



Predation, for example, is commonly thought of as a process that
involves one animal killing and consuming another. Nibbling on plants
counts only as herbivory, and bacteria consuming other microbes used
to be considered parasitic or perhaps even herbivorous, depending on
whether their "prey" photosynthesized (Guerrero et al.
1986). Early discoveries of explicitly predatory behavior in bacteria
announced them as "the first parasitic organism that attacks
[other] bacteria in a recognizably predatory fashion", despite
being smaller than their prey (Stolp & Starr 1963: 242). Nowadays,
a large range of predatory behaviors are acknowledged in bacteria as
more is discovered about microbial diversity in behavior and feeding
mode (Perez et al. 2016). These discoveries have broadened the
category of predation, and provide means by which to investigate the
general phenomenon of predation and its ecological impact. For many
research purposes, bacterial predators and prey function as models for
more general relationships of this sort, and can even show the
limitations of current theory (e.g., Gause's experience with his
eukaryotic microbes).



Phenomena such as ageing were also believed to apply only to
multicellular organisms. Bacteria and other unicellular life were
thought of as ageless and "immortal", due to symmetrical
cell division leading to new offspring replacing the progenitor cell
and removing any opportunity for ageing (Nystrom 2002). Because
ageing used to be defined as something that happened to organisms with
distinctions between germ and soma, it was assumed that
"unicellular bacteria are clearly not members of the exclusive
club of aging creatures" (Nystrom 2002: 596). However, a
large body of research now investigates just how bacteria age, the
differences between death and ageing, and what bacterial death means
for the very evolution of senescence (Baig et al. 2014). In other
words, bacterial ageing can model the core phenomena of what it means
to grow old.



Likewise, kin recognition was once defined on the basis of sensory
capacities that are not normally imputed to bacteria and other
microbes (e.g., Hepper 1986). But kin recognition on the basis of
chemical "sensing" is now a well-known phenomenon in
microorganisms, and has broadened what is known about the process in
general. In bacteria, recognition mechanisms are biochemical and have
molecular underpinnings, which means the process can be analyzed and broken down to its components relatively straightforwardly. In animals, inferences about recognition mechanisms are broader and less defined, due to
the behavioral level at which kin recognition must be investigated
(Wall 2016). Protist kin recognition researchers argue that the
phenomena, origins and evolution of kin recognition in eukaryotes is
best studied in diverse unicellular eukaryotic microbes (e.g.,
Paz-y-Mino-C & Espinosa 2016). Nobody is saying that
microbes *directly* represent the complex phenomena going on in
animals. Bacterial models of kin recognition in general are indirect
and simplified representations of more complex processes of perception
in other domains of life (Wall 2016). However, it is well established
in philosophy that this sort of indirect representation is key to the
very practice of modelling (e.g., Weisberg 2013).



Sceptics might think there must surely be phenomena in complex
animals, such as humans, that resist such modelling. They might
suggest that cognitive activities are something that simply cannot be
modelled by microbes of any kind because there is no basic analogue
with which to work. But even for cognition, unicellular organisms have
been extensively studied for decision optimization, efficiency
calculations, memory, anticipation and self-awareness (Westerhoff et
al. 2014; Beekman & Latty 2015). Not only do these microbes
(eukaryotic and prokaryotic) undergo direct examination for their own
cognitive capacities, but they also stand in for the more complex and
hard-to-access capacities of organisms such as animals. Again, the
claim here is not that microbes' cognitive capacities are the
same as those of animals. The claim is that microbes have capacities
that include key aspects of cognition, and these capacities can be
studied as analogues for cognition in general (including cognition in
animals). Just as for kin recognition, the quest to understand the
underlying foundations of cognition makes microorganisms such as slime
moulds and *E. coli* valuable models for cognitive capacities
of a general kind that are not dependent on brains (Beekman &
Latty 2015; Allen 2017). Whether this is best discussed as minimal
cognition (e.g., Godfrey-Smith 2016; see Lyon forthcoming for
criticism) or as another facet of a general capacity that is diversely
distributed across the tree of life (e.g., Allen 2017) is irrelevant
here: the point is simply that an examination of microbial research
can challenge, enrich and potentially reform how philosophers think
about classic subjects. Indeed, some new research in microbiology, which we turn to in Section 5, even
claims that microbes in the human body are influencing the mind.


## 5. The Long Reach of Microbiome Research



A recent microbiology topic of growing interest for philosophers is
microbiome research, which examines all the microbial communities
living in host organisms. In humans, the gut microbiome in particular
is associated with many health and disease states experienced by the
host, including mental health. There are two foci of philosophical
attention given to these heterogeneous microbial consortia in host
systems, namely individuality (e.g., Skillings 2016) and causality,
specifically the causal role large mixed communities of microbes might
play in host health (Lynch et al. 2019). 


### 5.1 Individuality issues



Perhaps the most basic philosophical issue that awareness of microbes
leads to is that of individuality: individuating where one biological
entity starts and another begins. Are microbes in and on human bodies
part of those bodies or not? If they are deemed a part, in what way is
that parthood conceptualized? Rather than answering this question with
traditional tools of mereology (see
 SEP entry on mereology),
 philosophers of biology have focused on biological and evolutionary
criteria. In particular, the question of whether hosts and their
microbes evolve as one Darwinian unit has become central to the
discussion (e.g., Clarke 2013; Booth 2014; Godfrey-Smith 2015; Pradeu
2016; Roughgarden et al. 2018). Criteria for evaluating when symbiotic
biological units have become a single evolutionary unit of selection
are still disputed and promise considerably more philosophical
discussion (see
 SEP entry on individuality).
 What is central to this entry is that such debates are rarely
inspired by relationships between macroorganisms. The smallness and
ability of microbes to invade host bodies and even cells is what marks
out microorganisms as the relevant focus of philosophical attention.
Their systemic effects on their environments is the other aspect that
makes them such important research foci. For example, microbes in the
intestines are repeatedly linked to host brain states such as
emotional well-being and depression (e.g., Valles-Colomer et al.
2019).



We note, however, that the sheer excitement and novelty of unexpected
findings can also lead to exaggerated views of the relationship
between human hosts and their microbes. Exactly how responsible
microbiomes are for human experiences such as anxiety, depression,
learning and memory is uncertain and at least sometimes dubious (for
discussion see Hooks et al. 2019). A similarly inflated claim is that
knowledge of microbiomes necessitates a new view of self, or of what
it means to be human (e.g., Rees et al. 2018; Ironstone 2018). While
dozens of microbiome authors have made claims to this effect, with
some attempting to explain what it actually means for the microbiome
to challenge or change our sense of self (e.g., Rees et al. 2018),
this claim still needs a great deal of clarification and substantiation (Parke et al. 2018). A
vast range of things could be meant by "self" or
"what it means to be human" in the context of these
microbiome claims, ranging from something controversial about the
nature of human biological individuality (see discussion above), to
something factual about the composition of human bodies (i.e., people
used to think their bodies were made of only human cells but now know
they are made of microbial cells as well), to something
phenomenological about first-person human experience (to date, there
is no evidence that microbes influence this). So, these claims about
the influence of microbiomes on "who we are" are at best
speculative and exaggerated. Some of these conceptual problems
probably come about because of unclarity about how to investigate the
causal powers of microbiomes, and more generally about causal
explanation in microbiome research.


### 5.2 Causality issues



Although philosophers drawing on microbiome research have tended so
far to focus on metaphysical issues of individuality, issues
associated with microbiome explanations are probably more pressing for the
science and are now undergoing philosophical scrutiny. These
investigations can work in two directions: using philosophical
frameworks to explore the nature of microbiome causality or even
whether it occurs (e.g., Lynch et al. 2019), then using the insights
gained to reflect further on the philosophy of causal explanation. For
example, Gillies (2019) examines treatment regimes arising out of
microbiome research and proposes a "causal law" account of
explanation to account for such phenomena. Other approaches take
frameworks for causal explanation such as interventionism (see
 SEP entry on causation and manipulability)
 and propose refinements that arise from examinations of putative
microbiome causality (Attah et al. 2020; Oftedal 2020). A particularly
strong finding of such analyses is that tradeoffs between key
dimensions of causal explanation (stability, specificity,
proportionality) require further philosophical attention.



Obviously, microbiome research is only one aspect of microbiology, but
it illustrates nicely the general point of the philosophical richness
of microbiological science. The occupation of humans by trillions of
microbes means that traditional views of health, bodies, and even
minds (according to some emerging research) need supplementing by
microbial and microbiological perspectives. Because some of this new
knowledge has only recently been revealed by large-scale molecular
techniques, many of the strongest and most "revolutionary"
claims require more rigorous conceptualization and analysis. But this
is not exclusively a feature of microbe-associated science. Nor is the
occupation of human bodies unique to microbes: helminths (worms) are
historical human passengers, and are frequently argued to have
system-wide benefits for their hosts that outweigh any harms (e.g.,
Lukes et al. 2015). Nevertheless, we do not expect to see
anytime soon a SEP entry on helminths. To clarify why, this essay will
conclude by reiterating the several angles from which microbes and
microbiology can be considered philosophically valuable.


## 6. Why Microbes and Microbiology Warrant Philosophical Attention



Philosophy of microbes and microbiology goes beyond both its
organismal and scientific bases. As discussed above, whether microbes
are used as models or as sources of data about biogeochemistry, their
implications go much further. They constitute many of the material
aspects of human lives, from individual bodies to every process in the
biosphere. Although there are many ways in which general lessons are
taken from large organisms, broad swathes of biology depend on
microbes in numerous ways, and this influences how researchers
understand and theorize about organisms such as humans. For
philosophers of biology interested primarily in human or other animal
biology, there will always be some sort of philosophical payoff if
microbiological angles are included. Philosophers of science more
generally may find that understanding models or experimentation
carried out with living systems can be enhanced by attention to
microbial modelling practices.



Even for philosophers who are not philosophers of science,
microbiology can be brought to bear on issues such as identity,
selfhood, human nature, and mind, to generate broader insights and
surprising conclusions. Not all such conclusions are defensible, but
examining the ways in which microbes might contribute to humanness
could be a valuable exercise. Consider why, for example, trillions of
microbes living inside human bodies seem more easily regarded as part
of that body, whereas the handful of helminths that do likewise are
usually (but not always) distinguished as separate and ideally
evicted. Microbes also offer philosophers tractable ways to study big
questions about the nature of life, causation, and representation in
general. For example, microbial experimental systems may be
seen as material equivalents of the mental structures philosophers
manipulate in thought experiments. There is also something to
learn about the ways microbial and other modelling activities differ.