1. health and fitness
2. disease

FEMS Microbiology Reviews Advance Access published February 19, 2015
FEMS Microbiology Reviews
doi: 10.1093/femsre/fuu010
Review Article
REVIEW ARTICLE
Microbial endocrinology: the interplay between
the microbiota and the endocrine system
Hadar Neuman1 , Justine W. Debelius2 , Rob Knight2,$ and Omry Koren1,∗
1
Faculty of medicine, Bar-Ilan University, 1311502 Safed, Israel and 2 Department of Chemistry and
Biochemistry and BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO 80309, USA
∗ Corresponding author: Omry Koren, Faculty of medicine, Bar-Ilan University, 8 Henrietta Szold St., 1311502 Safed, Israel. Tel: +972-72-2644954;
E-mail: Omry.Koren@biu.ac.il
One sentence summary: This review summarizes the links between the host endocrine system and microbiota functions, reporting both effects of the
host hormones on bacteria and effects of the microbiota on host hormones influencing behavior, appetite and metabolism, gender and immunity.
$
Current address: Departments of Pediatrics and Computer Science & Engineering, University of California at San Diego, La Jolla, CA 92093, USA
Editor: Ehud Banin
ABSTRACT
The new field of microbiome research studies the microbes within multicellular hosts and the many effects of these
microbes on the host’s health and well-being. We now know that microbes influence metabolism, immunity and even
behavior. Essential questions, which are just starting to be answered, are what are the mechanisms by which these bacteria
affect specific host characteristics. One important but understudied mechanism appears to involve hormones. Although
the precise pathways of microbiota-hormonal signaling have not yet been deciphered, specific changes in hormone levels
correlate with the presence of the gut microbiota. The microbiota produces and secretes hormones, responds to host
hormones and regulates expression levels of host hormones. Here, we summarize the links between the endocrine system
and the gut microbiota. We categorize these interactions by the different functions of the hormones, including those
affecting behavior, sexual attraction, appetite and metabolism, gender and immunity. Future research in this area will
reveal additional connections, and elucidate the pathways and consequences of bacterial interactions with the host
endocrine system.
Key words: microbiota; microbiome; hormones; germfree; endocrine system; immunity
INTRODUCTION
We are only beginning to understand the pervasive importance
of gut microbial communities (microbiota) in health and disease.
In the past, bacteria were mostly regarded as either pathogens or
irrelevant to host function. However, the growing field of microbiome research—human microbial ecology, studying the communities of bacteria residing within our bodies and the genes
they contain—has yielded new perspectives. We now realize
that the number of microbial cells we carry can be as much as 10
times greater than the total cell number in the human body, and
their genetic information is at least 150-fold greater than that
of our human genome. Thus, it is not surprising that microbiota
and their hosts interact in numerous complex ways. The gut microbiota in particular plays important roles in host metabolism,
immunity and even behavior. Mechanisms by which the microbiota are known to mediate these functions include breaking
down dietary components, educating the immune system and
degrading toxins (Flint et al., 2012; Elahi et al., 2013; Maurice,
Haiser and Turnbaugh 2013).
However, only recently has a critical mechanism of bacterial
interaction been revealed: modulation of hormonal secretion.
From birth, bacterial colonization of the intestine has a role in
the maturation of the immune system (Elahi et al., 2013) and the
endocrine system (Clarke et al., 2013). Surprisingly, commensal
Received: 4 August 2014; Accepted: 21 December 2014
C FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
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FEMS Microbiology Reviews
bacteria can produce and secrete hormones. The crosstalk between microbes and hormones can affect host metabolism, immunity and behavior. This interplay is bidirectional, because the
microbiota has shown to be both affected by and to affect host
hormones, as summarized in Table 1.
Lyte and Ernst were the first to define the field of microbial endocrinology research, after observing that stress-induced
neuroendocrine hormones can influence bacterial growth (Lyte
and Ernst 1992). Further research of microbial endocrinology
discovered hormone receptors in microorganisms and hypothesized that they represent a form of intercellular communication (Lyte 1993). Pathogenic neurotoxins such as neurotoxin 6hydroxydopamine were shown to alter norepinephrine levels in
mice presenting the bidirectional nature of the host–microbe interaction (Lyte and Bailey 1997). A more evolutionary-oriented
study showed that many enzymes involved in host hormone
metabolism (including epinephrine, norepinephrine, dopamine,
serotonin, melatonin, etc.) might have evolved from horizontal
gene transfer from bacteria (Iyer et al., 2004).
More clues to the existence of crosstalk between bacteria
and the endocrine system came from the discovery of interkingdom signaling, including the hormonal communication between microorganisms and their hosts (Hughes and Sperandio
2008). This field evolved from the initial observation that bacteria perform quorum sensing (QS), communication based on
producing and sensing autoinducer (AI) molecules. These AI
molecules are hormone-like elements that regulate functions
including coordinated bacterial growth, motility and virulence
(Fuqua, Winans and Greenberg 1996). In addition to affecting
bacteria, these signals can modulate host cell signal transduction. Some AI molecules have crosstalk with host hormones for
activating signaling pathways (Karavolos et al., 2013).
Host hormones also affect bacterial gene expression
(Sperandio et al., 2003), which in turn can have consequences
on their hosts. For example, catecholamines enhance bacterial
attachment to host tissues, and affect growth and virulence of
bacteria (Freestone and Lyte 2008; Hegde, Wood and Jayaraman
2009). In contrast, the human sex hormones estriol and estradiol decrease bacterial virulence by inhibiting QS (Beury-Cirou
et al., 2013).
The effects of host hormones on the microbiota are summarized in Fig. 1.
In this review, we summarize interactions between hormones and the gut microbiota, and propose an important role
for the microbiota in hormone regulation. These endocrine effects of bacteria influence a variety of host responses including behavior, metabolism and appetite, and immune responses
(Fig. 2). Much of the advances in this field have been made
through experiments using germfree (GF) animals (Fig. 3) as well
as experiments using probiotics (specific microbes thought to be
beneficial to the host) and prebiotics (non-digestible carbohydrates that act as food for probiotics), together with advances in
sequencing and bioinformatics platforms.
While this field is in its infancy, future research will likely
identify additional strong interconnections between hormones
and our microbiome. Microbial endocrinology may also explain
how the microbiota affect the host’s gastrointestinal (GI) and
psychological health (Lyte 2011). We suggest that hormones are
an important mechanism for host–microbial interaction.
BEHAVIOR
The gut microbiota influences animal and human behavior in
several ways. GF mice have altered cognitive function, memory,
stress-response, anxiety and social behavior (Diaz et al., 2011;
Neufeld et al., 2011). The gut microbiota may even influence
human emotional states and disease states, such as stressrelated irritable bowel syndrome (IBS; reviewed elsewhere in
Cryan and O’Mahony 2011), and autism (Sandler et al., 2000; Finegold et al., 2010; Hsiao et al., 2013). These surprising findings
show that the microbiota can modulate host behavior, raising
the question of how these effects work functionally. The communication between the gut microbiota and the brain has been
termed the ‘gut-brain axis’, and is mediated mainly by the long
branching vagus nerve. Although the precise pathways of the
gut-brain axis have not yet been deciphered, it is thought that
the effects are achieved by several different mechanisms mediated by hormones. The effects of the microbiota on host hormone levels may be direct, where the microbiota produce the
hormones, or indirect, where microbes may modulate the function of the adrenal cortex (which controls the anxiety and stress
responses), or modulate inflammation and immune responses.
Two major groups of hormones likely involved in bacterial effects on host behavior are neurohormones, including serotonin
and the catecholamines dopamine, epinephrine (adrenaline)
and norepinephrine (noradrenaline), and stress hormones, including cortisol, corticosterone, adrenocorticosterone and corticotropin. Hormones in both groups can influence physiological
changes preparing the body for physical activity (fight-or-flight
response), such as increased heart rate and blood pressure, and
decreased metabolism (Romero and Butler 2007).
Neurohormones
Neurohormones are secreted from neuroendocrine cells in response to a neuronal input. Although they are secreted into the
blood for a systemic effect, they can also act as neurotransmitters. Modulation of behavior by the microbiota (such as anxiety in mice) is believed to occur through neurohormone precursors (e.g. serotonin, dopamine) (Lyte 2013). Recently, gut bacteria were shown both to produce and respond to neurohormones
such as serotonin, dopamine and norepinephrine (Roshchina
2010). Catecholamines can alter growth, motility, biofilm formation and/or virulence of bacteria (Lyte et al., 2003; Sperandio
et al., 2003; Freestone and Lyte 2008; Karavolos et al., 2008; Hegde,
Wood and Jayaraman 2009). These mechanisms are intriguing
for researchers studying pathogens because they may influence
pathogen susceptibility to host defense responses. For example, in response to host adrenaline, Salmonella downregulates its
resistance to host antimicrobial peptides and induces key metal
transport systems, which affect the oxidative stress balance in
the cells (Karavolos et al., 2008). These mechanisms also involve
QS: the bacterial QS AI molecule AI-3 and host adrenaline and
noradrenaline display crosstalk for activation of the same signaling pathways. These responses most likely depend on bacterial receptor-based sensing and signaling cascades, as they are
inhibited by α and β-adrenergic receptor antagonists (Karavolos
et al., 2013).
Serotonin, also termed 5-hydroxytryptamine (5-HT), is one
of the main neurotransmitters in the brain. However, over 90%
of the mammalian host’s serotonin is found in the intestine.
Intestinal serotonin secretion is affected by diet, and regulates
intestinal movement, mood, appetite, sleep and cognitive functions. This dual role suggests that serotonin may link the intestine (including its microbiota) to host behavior. Brain 5-HT
can cross the blood–brain barrier to the blood through the 5HT transporter, suggesting another link in the gut-brain axis
(Nakatani et al., 2008). Serotonin has been implicated in GI
Neuman et al.
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Table 1. A list of known correlations between hormones and the microbiota.
Functional
class
Bacterial
growth and
expressions
Model
Finding
Epinephrine,
dopamine, dopa
Bacterial growth
Catecholamines induce bacterial growth
Epinephrine,
norepinephrine
Epinephrine
QS
QS and host hormone crosstalk
Bacterial gene
expression
Bacterial growth
Hormones affect bacterial virulence
gene expression
Catecholamines induce bacterial growth
Enhanced bacterial growth and
virulence
Norepinephrine
Bacterial growth
and
characteristics
Biofilm growth
Estriol, estradiol
QS
Hormones decrease bacteria virulence
Norepinephrine
Bacterial
production
Bacterial
resistance
Bacterial growth
Gut microbiota produce and respond to
norepinephrine
Epinephrine decreases bacterial
resistance to host antimicrobial peptides
Estradiol and progesterone enhance
bacterial growth
Tryptophan, 5-HT
and 5hydroxyindoleacetic
acid
Serotonin
GF mice
Elevated hipocampal levels in male GF
mice
N/A
Clarke et al.
(2013)
Bacterial
production of
neurotransmitter
Gut microbiota produce serotonin
Roshchina
(2010)
Dopamine
Serotonin
Bacterial
production
GF mice
Gut microbiota produce and respond to
dopamine
Low plasma serotonin levels in GF mice
Streptococcus,
Escherichia and
Enterococcus
spp.
Bacillus and
Serratia
N/A
Tryptophan, 5-HT
Infected rats
Higher plasma levels in infected rats
B. infantis
Norepinephrine,
dopamine
GABA
GF mice
Low free lumen catecholamines in GF
mice
Microbiota produce GABA
N/A
Bacteria alter host GABA receptors
L. rhamnous
Low levels of corticosterone in treated
mice
Elevated levels in GF mice
L. rhamnous
Probiotics in rats
and humans
Bacteria reduce levels of stress
hormones
L. helveticus and
B. longum
Messaoudi et al.
(2011)
Antibiotics in
Parkinson’s
patients
Eliminating H. Pylori elevates L-DOPA
levels
H. pylori
Pierantozzi
et al. (2006)
cVA and CHs
D. melanogaster
L. plantarum
Guaiacol
S. gregaria
Pheromone levels affected by antibiotics
and bacteria addition
Pheromone produced by commensal
bacteria, abolished in GF locust
Volatile fatty acids
Hyena
Sharon et al.
(2010)
Dillon, Vennard
and Charnley
(2002)
Theis et al.
(2013)
Norepinephrine,
epinephrine,
dopamine
Norepinephrine
Epinephrine
Estrogen,
progesterone
Host
behavior
GABA
Corticosterone
Corticosterone,
adrenocorticosterone
Corticosterone,
adrenocorticosterone
L-DOPA
Host
mating
Microbial
species
Hormone
Bacterial
production
Probiotics in
mice
Probiotics in
mice
GF mice
Catecholamines induce biofilm growth
Species-specific volatiles correlated to
bacterial populations in scent glands
E. coli, Yersinia.
enterocolitica
and
Pseudomonas
aeruginosa
E. coli
E. coli
E. coli,
Salmonella
enterica and Y.
enterocolitica
P. aeruginosa
Staphylococcus
epidermidis
Agrobacterium
tumefaciens, P.
aeruginosa
N/A
Salmonella
Platysaurus
intermedius
Lactobacillus
N/A
P. agglomerans;
K. pneumonia; E.
cloacae
N/A
Ref
Lyte and Ernst
(1992)
Sperandio et al.
(2003)
Sperandio et al.
(2003)
Freestone and
Lyte (2008)
Hegde et al.
(2009)
Lyte et al. (2003)
Roshchina
(2010)
Roshchina
(2010)
Sperandio et al.
(2003)
Kornman and
Loesche (1982)
Roshchina
(2010)
Wikoff et al.
(2009)
Desbonnet et al.
(2008)
Asano et al.
(2012)
Asano et al.
(2012)
Bravo et al.
(2011)
Bravo et al.
(2011)
Grenham et al.
(2011)
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Table 1. (continued.)
Functional
class
Host
appetite
and
metabolisms
Microbial
species
Ref
Vancomycin leads to decrease in
circulating leptin levels
N/A
Lam et al. (2012)
Reduced serum leptin
L. plantarum
Specific bacteria positively correlated
with circulating leptin
Specific bacteria negatively correlated
with circulating leptin
Bifidobacterium,
Lactobacillus,
Clostridium,
Bacteroides and
Prevotella
Mucispirillium,
Lactococcus and
an uncultured
member of the
Lachnospiraceae
Allobaculum
Naruszewicz
et al. (2002)
Queipo-Ortuno
et al. (2013)
Queipo-Ortuno
et al. (2013)
Hormone
Model
Finding
Leptin
Antibiotics in
rats
Probiotics in
smokers
Male rats
Male rats
Ghrelin
Mice (including
leptin deficient)
Specific bacteria positively correlated
with circulating leptin
Mice (including
leptin deficient)
Male rats
Specific bacteria negatively correlated
with circulating leptin
Specific bacteria positively correlated
with ghrelin
Specific bacteria negatively correlated
with ghrelin
Male rats
Insulin
Insulin
GLP-1
GLP-1
GLP-1
Angptl4
Somatostatin
Alpha-melanocytestimulating
hormone,
neuropeptide Y,
agouti-related
protein, ghrelin and
leptin
GIP, GLP-1, insulin
Angptl4
Prebiotics
(oligofructose) in
obese humans
Prebiotics decrease secretion of ghrelin
Metagenomics of
diabetic women
Bacterial transfer
from lean donors
to metabolic
syndrome
patients
GF and antibiotic
treated mice
Probiotics in
mice
Negative correlations between insulin
levels and bacterial populations
Lean human subjects have increased
insulin sensitivity due to their
microbiome, compared to metabolic
syndrome patients
Bariatric surgery
in rats
Probiotics in
mice
Bacterial
production
GF rats
Intestinal microbiota changes correlate
with elevated GLP-1 levels
Elevated Angptl4 levels in treated mice
Gastric bypass
surgery in
diabetic patients
GF mice
colonized with
normal gut
microbiota
Intestinal microbiota lower GLP-1 levels
Intestinal microbiota increase GLP-1
levels
Bacteroides and
Prevotella spp.
Bifidobacterium,
Lactobacillus
and B.
coccoides–E.
rectale group
Promoted
growth of
Bifidobacterium
and
Lactobacillus
Clostridium spp.
B. intestinalis
Correlated with
butyrateproducing
intestinal
microbiota
N/A
B. breve, B.
longum, B.
infantis, L.
acidophilus, L.
plantarum, L.
paracasei, L.
bulgaricus,
Streptococcus
thermophilus
N/A
L. paracasei
Ravussin et al.
(2012)
Ravussin et al.
(2012)
Queipo-Ortuno
et al. (2013)
Queipo-Ortuno
et al. (2013)
Parnell and
Reimer (2009)
Karlsson et al.
(2013)
Vrieze et al.
(2012)
Wichmann
et al. (2013)
Yadav et al.
(2013)
Osto et al. (2013)
Aronsson et al.
(2010)
LeRoith et al.
(1985)
Fetissov et al.
(2008)
Bacteria produce somatostatin
Bacillus subtilis
Altered levels of autoantibodies against
appetite hormones
N/A
Intestinal microbiota changes correlate
with elevated hormone levels
N/A
Laferrere (2011)
Suppression of Angptl4 expression
following colonization
N/A
Backhed (2009)
Neuman et al.
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Table 1. (continued.)
Functional
class
Sex
hormones
and reproduction
Hormone
Model
Finding
Microbial
species
Estrogen
Antibiotics
Antibiotics lead to lower estrogen levels
N/A
Adlercreutz
et al. (1984)
Estrogen
Humans
Correlations between urinary estrogen
levels and fecal microbiome
composition and richness
Adlercreutz
et al. (1984)
Androgens
Enzymatic and
kinetic
experiments
NOD mice
Bacteria convert glucocorticoids to
androgens
Clostridia taxa,
including nonClostridiales
and three
genera in the
Ruminococcaceae
family
C. scindens
Microbes raise testosterone levels in
male NOD mice
N/A
Markle et al.
(2013)
Cows
SCFAs inhibit bovine growth hormone
N/A
Probiotics promote growth hormone
signaling
Bacterial genes are required for growth
factors
Upregulation of oxytocin in treated mice
L. plantarum
TSH
Probiotics in D.
melanogaster
Probiotics in D.
melanogaster
Probiotics in
mice
GF rats
Wang et al.
(2013)
Storelli et al.
(2011)
Shin et al. (2011)
∼25% higher TSH levels in GF rats
N/A
Prolactin
GF rats
∼25% higher prolactin levels in GF rats
N/A
Prolactin
Cow cells
SCFAs inhibit prolactin gene
transcription
N/A
Testosterone
Host
growth
Other
Bovine growth
hormone
Growth hormones
Insulin-like
peptides
Oxytocin
A. pomorum
L. reuteri
Ref
Winter et al.
(1984)
Poutahidis et al.
(2013)
Wostmann
(1996)
Wostmann
(1996)
Wang et al.
(2013)
Figure 1. Host effects on the microbiota. A variety of host factors (such as diet, exercise, mood, general health state, stress and gender) lead to alterations in hormonal
levels, which in turn lead to a variety of effects on the microbiota (including growth, virulence and resistance).
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Figure 2. The effects of the gut microbiota on the host via hormones. Gray arrows and text refer to the effects of the gut microbiota on various hormone levels. Pink
arrows and text refer to the effects of these hormonal alterations on host outcomes (e.g. behavior).
pathologies such as IBS and Crohn’s disease (Manocha and Khan
2012), and these diseases are also associated with differences in
the microbiota (Morgan et al., 2012).
To our knowledge, the first direct effect of the microbiome on serotonin was demonstrated in GF mice, which had
lower plasma serotonin levels than conventional mice (Wikoff
et al., 2009). However, in another study, levels of tryptophan (the
precursor of serotonin) and hippocampal concentration of 5-HT
and 5-hydroxyindoleacetic acid (its main metabolite) were elevated in male GF mice (Clarke et al., 2013), suggesting that either the effects are facility-specific or tissue-specific. Serotonin
can also be produced by Streptococcus, Escherichia and Enterococcus
species (Roshchina 2010), and Bifidobacterium infantis modulates
5-HT levels by increasing plasma tryptophan levels (Desbonnet
et al., 2008).
Dopamine is also produced by bacteria including Bacillus and
Serratia, although little is known about its function in these mi-
croorganisms (Roshchina 2010). Levels of free lumen dopamine
were significantly lower in GF than conventional mice, and
were elevated again upon inoculation with bacteria expressing β-glucuronidase (Asano et al., 2012). These results suggest
that there may be correlations between intestinal bacteria and
dopamine levels in conditions such as Parkinson’s disease, characterized by insufficient dopamine formation. Because the etiology of Parkinson’s disease is poorly understood, and one of
the early symptoms of disease is constipation, it has been hypothesized that bacteria may be involved in its progression
or development (Dobbs et al., 2012). Moreover, several rodent
models of Parkinson’s disease-like syndrome are established by
injection of bacteria such as Nocardia asteroides (Kohbata and
Beaman 1991). So far, Helicobacter pylori has been shown to increase the risk for Parkinson’s disease by affecting L-DOPA levels (Pierantozzi et al., 2006), and fecal transplants may have alleviated some neurological symptoms in a Parkinson’s patient
Neuman et al.
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Figure 3. Hormonal alterations reported in GF rodents (Based on Wostmann 1996; Fetissov et al., 2008; Backhed 2009; Wikoff et al., 2009; Grenham et al., 2011; Asano
et al., 2012; Clarke et al., 2013; Markle et al., 2013; Wichmann et al., 2013). The arrows refer to the hormone levels in GF compared to conventionally raised rodents.
treated for constipation (Aroniadis and Brandt 2013). These results require further investigation but point to interesting directions.
Gamma-aminobutyric acid (GABA), the main inhibitory
neurotransmitter in the mammalian CNS, is also produced by
the microbiota and may influence host behavior. This is interesting because alterations in central GABA receptor expression
are implicated in the pathogenesis of anxiety and depression.
GABA production by Lactobacillus has been studied in an attempt
to ferment safe GABA on a large scale (Li et al., 2008). Accordingly,
administration of Lactobacillus rhamnosus to mice alters the expression of GABA receptors in different CNS regions, decreasing
anxiety- and depression-related behavior (Bravo et al., 2011).
Stress hormones
The microbiota may help keep us calm and balanced by altering stress hormone levels. GF mice have elevated plasma
levels of the stress hormones corticosterone and adrenocorticotropic hormone (ACTH) in response to mild stress (Sudo
et al., 2004; Grenham et al., 2011), increasing behaviors associated with anxiety and stress. ACTH plays an important role
in the hypothalamic–pituitary–adrenal axis by further producing corticosteroids. Accordingly, two specific species, L. helveticus and B. longum, reduce levels of the stress hormone corti-
sol and anxiety-like behavior in both rats and healthy humans
(Messaoudi et al., 2011). Furthermore, mice chronically treated
with the probiotic L. rhamnosus had lower levels of corticosterone
and less depressive behavior in a forced swim test than controls
(Bravo et al., 2011).
MATING AND PHEROMONES
Pheromones are hormones that play important roles in sexual
recognition, attraction and mating behavior as well as aggression behavior and dominance. Pheromones are also termed ectohormones, chemicals secreted outside of the body of one individual and affect the behavior of others.
In Drosophila melanogaster (D. melanogaster), the most abundant pheromones are cuticular hydrocarbons (CHs), and the
most studied pheromone is cis-vaccenyl acetate (cVA). Levels
of CHs and cVA are affected by antibiotics, suggesting a role for
the microbiota in pheromone regulation (Sharon et al., 2010). In
a study characterizing mating preferences between two groups
of D. melanogaster fed different diets, assortative mating preferences were eliminated with antibiotics, and depended on a
specific gut microbe, L. plantarum (Sharon et al., 2010). Together,
these findings suggest a mechanism whereby the microbiota
affect host pheromone levels, which in turn affect mating
behavior.
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FEMS Microbiology Reviews
Guaiacol (2-methyoxyphenol) and related phenolic compounds, which are produced by commensal bacteria involved
in vanillate decarboxylation, are another indication of the involvement of the microbiota in pheromone secretion. In response to guaiacol, the desert locust Schistocerca gregaria swarms
(Dillon, Vennard and Charnley 2000). Accordingly, GF animals do
not release guaiacol or volatile phenols, but monocultures with
the commensal species, Pantoea agglomerans, Klebsiella pneumoniae or Enterobacter cloacae lead to pheromone production. Interestingly, this phenomenon is specific to the commensal species,
because locusts colonized by a pathogenic bacterial species
did not produce guaiacol or other phenolic compounds (Dillon,
Vennard and Charnley 2002).
This linkage between commensal bacteria and volatile host
social signals may also occur in mammals. Two hyena species
harbored different bacterial communities in the scent glands,
which correlated with distinct volatile fatty acid profiles of scent
secretions. The authors speculate that the symbiotic bacteria make metabolites that provide species-specific odors (Theis
et al., 2013).
Additionally, Singh et al. demonstrated in a major histocompatibility complex congenic rat model that discriminative urinary odors that exist in conventional rats do not exist in GF
rats. This further supports the idea that bacteria can produce an
odor profile that affects host behavior (Singh et al., 1990). Bacterial communities producing specific scents may be linked to
host genetic background, as scent-mark communities differed
significantly between strains of mice, even when co-housed in a
shared environment (Lanyon et al., 2007). Bacteria can also play
a role in mate selection: female mice are not attracted to the
urine of Salmonella-infected males (Raveh et al., 2014). Because
chemosignals and olfactory stimulation also play a role in human behavior, future research will help us understand whether
bacterially produced odors affect our own interactions and perhaps evolution.
SEX HORMONES AND REPRODUCTION
Examples of bacteria affected by sex hormones have been
reported since the 1980s. For instance, Prevotella intermedius
takes up estradiol and progesterone, which enhance its growth
(Kornman and Loesche 1982). Changes in expression of the
estrogen receptor, ER-β, also affect the intestinal microbiota
composition (Menon et al., 2013). This interaction goes both
ways, as several types of bacteria have also been implicated in
steroid secretion or modification (Ridlon et al., 2013). For example, Clostridium scindens converts glucocorticoids to androgens,
a group of male steroid hormones (Ridlon et al., 2013). Intestinal bacteria also play a significant role in estrogen metabolism,
because use of antibiotics leads to lower estrogen levels (Adlercreutz et al., 1984). Furthermore, strong correlations were found
between urinary estrogen levels and fecal microbiome richness,
as well as presence of Clostridia, including non-Clostridiales,
and three genera within the Ruminococcaceae.
Mittelstrass et al. suggested an interplay between the endocrine system, the gut bacteria and metabolism based on
gender-specific differences in fatty acid profiles (Mittelstrass
et al., 2011). There are also gender-specific immune changes that
may be correlated with the microbiota. The new term ‘microgenderome’ refers to recent observations that the host microbiome
plays a role in the gender bias seen in numerous diseases (Flak,
Neves and Blumberg 2013). We discuss this topic further in the
immune response section below.
Pregnancy is an interesting period to study the microbiota changes that correlate with the drastic changes in host
hormone levels during this time. Normally, hormones such as
estrogen, progesterone and leptin increase dramatically with
gestational age, while adiponectin and pituitary GH decrease
(Newbern and Freemark 2011). The composition of the gut microbiota changes dramatically during pregnancy, specifically in
the third trimester, and these changes lead to differences in
metabolism (Koren et al., 2012). These microbial changes include
a significant increase in Proteobacteria and Actinobacteria as
pregnancy progresses. The third trimester is also characterized
by elevated low-grade inflammation and insulin desensitization
compared to the first trimester. This complex phenotype could
be transferred to GF mice, where mice receiving third trimester
microbiota gained more weight and had a greater inflammatory
response than mice receiving first trimester microbiota (Koren
et al., 2012). These changes might be correlated with hormonal
changes during gestation.
Dysbiosis of the gut microbiota may also play a role in the development of diseases manifested by hormonal imbalance, such
as polycystic ovary syndrome, through their modulation of hormone levels. According to this theory, poor diet leads to changes
in gut bacterial communities, creating an increase in gut mucosal permeability, resulting in activation of the immune system. This, in turn, raises serum insulin levels, increases androgen production in the ovaries and interferes with normal follicle
development (Tremellen and Pearce 2012). A carbohydrate-poor
diet has been proven to alleviate symptoms of the syndrome.
APPETITE AND METABOLISM
A classic role of the gut microbiota is in digesting a variety
of carbohydrates and fermenting them into short-chain fatty
acids (SCFAs). GF mice have different metabolic profiles than
conventionally raised mice, including low concentrations of SCFAs, hepatic triacylglycerol and glucose. Interestingly, subtherapeutic doses of antibiotics, which do not eliminate the gut microbial community but rather cause significant changes in its
composition, lead to increased levels of SCFAs and to weight
gain in mice (Cho et al., 2012). These metabolic effects of the
microbiome may further affect regulation of hormone production from cholesterol, peptides or amino acids. For instance SCFAs have been shown to stimulate release of 5-HT and the peptide YY, a hormone released after feeding involved in appetite
reduction and decreasing of gut motility (Cherbut et al., 1998;
Fukumoto et al., 2003). Additional hormones, mainly neuropeptides that have a role in controlling appetite and regulating
metabolism, are likely affected by the gut microbiota. These include alpha-melanocyte-stimulating hormone, neuropeptide Y,
agouti-related protein, ghrelin, leptin, insulin and others. Another effect of bacteria on metabolic hormones could be through
production of somatostatin, which suppresses the release of the
GI and pancreatic hormones (LeRoith et al., 1985).
Several pieces of evidence link the microbiota function
to leptin levels. First, use of antibiotics (vancomycin) in rats
leads to a dramatic decline (38%) in circulating leptin levels (Lam et al., 2012). Second, the abundance of several bacterial genera (e.g. Mucispirillum, Lactococcus, Bifidobacterium and
Lactobacillus) positively correlates with circulating leptin concentrations in mice, while other bacterial genera (e.g. Allobaculum, Clostridium, Bacteroides and Prevotella) negatively correlate with leptin levels. These correlations may stem from bacteria affecting hormone levels, or vice versa. One proposed
Neuman et al.
mechanism is that diet composition may impact leptin concentrations, which, in turn, may change the microbial community composition through inflammation and/or regulation
of mucus production (Ravussin et al., 2012; Queipo-Ortuno
et al., 2013). Recently, Rajala et al. demonstrated that leptin
might also influence the gut microbiota independently of diet
(Rajala et al., 2014). Another model proposes that L. plantarum
specifically suppresses leptin by reducing adipocyte cell size in
white fat tissue (Takemura, Okubo and Sonoyama 2010; Lam
et al., 2012). This fits the finding that use of the probiotic L.
plantarum in a group of human smokers reduced their serum
leptin levels (Naruszewicz et al., 2002). Because leptin is involved in appetite inhibition, metabolism and behavior, deciphering its interconnections with bacteria is of great interest
and may help us understand and perhaps control its many
effects.
Ghrelin, another important appetite-regulating hormone, is
negatively correlated with the abundance of Bifidobacterium, Lactobacillus and B. coccoides–Eubacterium rectale group, and positively correlated with a number of Bacteroides and Prevotella
species (Queipo-Ortuno et al., 2013). Intake of oligofructose (a
prebiotic that promotes growth of Bifidobacterium and Lactobacillus) decreases secretion of ghrelin in obese humans (Parnell and
Reimer 2009).
Insulin, the extremely important metabolic hormone involved in diabetes and metabolic syndrome, may provide another link between the microbiome and hormones. Significant
variations in microbiome composition have been observed in diabetes patients compared to healthy controls. Certain bacterial
species have been positively or negatively correlated with insulin levels (Qin et al., 2012; Karlsson et al., 2013). Transfer of the
intestinal microbiota (including butyrate-producing microbiota)
from lean donors to metabolic syndrome patients enhanced insulin sensitivity (Vrieze et al., 2012). The effect is likely mediated by altering immune components. However, additional hormones may also be involved in this process.
One such example is glucagon-like peptide 1 (GLP1), associated with appetite control and insulin secretion. The intestinal microbiota have been recently implicated in lowering levels
of the GLP1, and thereby slowing intestinal transit (Wichmann
et al., 2013). However, alterations of the microbiome through probiotics (Yadav et al., 2013) or bariatric surgery (Zhang et al., 2009;
Liou et al., 2013; Osto et al., 2013) decrease adiposity and increase
GLP1 levels in mice. This is primarily attributed to butyrate production by commensal bacteria, which can induce GLP1 production by intestinal L cells (Yadav et al., 2013).
Another example is angiopoietin-like protein 4 (Angptl4,
also known as fasting-induced adipose factor), a hormone
implicated in many metabolic processes including regulation of glucose and insulin sensitivity. Angptl4 is also
implicated in lipid metabolism, inhibiting lipoprotein lipase (LPL) and thereby reducing fat storage. Gut microbiota suppress expression of Angptl4, and in a GF mouse
study Angptl4 was shown to mediate protection against
diet-induced obesity (Adlercreutz et al., 1984). A zebrafish
model found a tissue-specific cis-regulatory element that
reduced Angptl4 in the intestinal epithelial cells of colonized
animals (Camp et al., 2012). Despite the general trend toward
repression of Angptl4 by the microbiota, specific bacteria can
increase hormone expression. Mice treated with L. paracasei
were leaner than controls, had lower circulating lipids and
elevated levels of Angptl4 (Aronsson et al., 2010). This probiotic
may increase Angptl4 expression through butyrate-mediated
mechanisms. First, butyrate is proposed to induce Angptl4 by
9
signaling through peroxisome proliferator-activated receptor
γ (PPARγ ) (Alex et al., 2013). Butyrate may also interact with
the Angptl4 promoter region independently of PPARγ (Korecka
et al., 2013) and has also been shown to inhibit proliferation,
induce differentiation and repress gene expression by inhibiting histone deacetylase activity (Davie 2003). Hence, it is likely
that butyrate plays a role in the microbiota-induced weight
maintenance mechanisms that involve hormonal changes.
One interesting mechanism by which the microbiota affect peptide hormones is through autoantibodies. Fetissov et al.
found that autoantibodies against peptide hormones involved
in appetite control (including alpha-melanocyte-stimulating
hormone, neuropeptide Y, agouti-related protein, ghrelin and
leptin) exist in healthy humans and rats, and affect feeding and
anxiety. In GF rats, levels of these autoantibodies are altered,
suggesting a novel mechanism by which the microbiome can affect appetite (Fetissov et al., 2008). These findings have further
implications for the potential role of the microbiota in eating
disorders such as anorexia nervosa. In support of this notion,
differences in microbial composition have been found between
anorexic patients and healthy controls (Armougom et al., 2009).
Finally, new correlations among the microbiota composition, hormonal levels and metabolism come from studies of
gastric bypass surgery. Gastric bypass surgery has been shown
to alter the intestinal microbiota composition. Following Rouxen-Y gastric bypass (RYGB), in both humans and rodents, the
relative abundance of Gammaproteobacteria (Escherichia) and
Verrucomicrobia (Akkermansia) increase. While microenvironmental changes such as reduced food intake and reduction of
bile acids likely affect this new microbiota composition (Madsbad, Dirksen and Holst 2014), some of the compositional changes
are likely due to alterations in the levels of intestinal hormones including elevation of glucose-dependent insulinotropic
polypeptide (GIP), GLP1 and insulin following surgery (Laferrere
2011; Osto et al., 2013). These alterations in the gut microbiome
further contribute to reduced host weight and adiposity. Accordingly, transfer of the gut microbiota from RYGB-treated mice to
non-operated GF mice resulted in weight loss and decreased fat
mass in the recipient animals relative to recipients of the microbiota induced by sham surgery (Liou et al., 2013).
IMMUNE RESPONSE
A growing amount of evidence has linked both hormones and
the microbiome to immune responses under healthy conditions
and autoimmune disease (AD). There are many interconnections between them, and the microbiome and hormones may
work through shared pathways to affect the immune response.
Hormones influence the immune system in many ways. The
immune and neuroendocrine systems share a common set of
hormones and receptors. Glucocorticoids such as corticosterone
and cortisol regulate inflammation levels and have effects both
on the innate and adaptive immune responses (Franchimont
2004). Additionally, vitamin D affects immune cell responses
by enhancing antigen presentation (Bhalla et al., 1989). Moreover, sex hormones affect the immune response in numerous
ways (Whitacre 2001; Lasarte et al., 2013; Priyanka et al., 2013;
Sankaran-Walters et al., 2013). Many AD are more common in
females, perhaps partly due to hormonal differences (Whitacre
2001; Ober, Loisel and Gilad 2008). Mouse models of AD in which
hormone levels were altered revealed changes in disease incidence; for example, androgen treatment in a type 1 diabetes
(T1D) non-obese diabetic (NOD) mouse model prevents the development of diabetes (Fox 1992).
10
FEMS Microbiology Reviews
Figure 4. A model describing the pathway leading to male protection from T1D in NOD mice. Testosterone enriches the male microbiome with specific bacteria including
SFB, E. coli and Shigella-like bacteria. Together, they are proposed to activate the immune system and lead to gender-specific protection from T1D. Transplantation of
male microbiome into females elevates testosterone levels and leads to protection from T1D as well (Markle et al., 2013).
However, the gut microbiota also plays a role in modulating the immune response, both locally and systemically
(Kamada et al., 2013), beyond repressing pathogenic microbes. In
the absence of commensal bacteria, GF mice have impaired development of the innate and adaptive immune system (Hill and
Artis 2010; Littman and Pamer 2011; Honda and Littman 2012;
Hooper, Littman and Macpherson 2012), reduced numbers of
IgA-producing plasma cells (Crabbe et al., 1969) and a decreased
percentage of CD4+ T cells (Ostman et al., 2006). Additionally,
T helper 17 (TH17) cells, which produce pro-inflammatory cytokines, are regulated by gut bacteria and are promoted specifically by segmented filamentous bacteria (SFB) (Tanabe 2013).
Finally, AD have also been correlated with alterations of
the microbiome (dysbiosis). The most extensively studied example is T1D as presented in Fig. 4 (Brown et al., 2011;
Hara et al., 2013).
Thus, both hormones and the gut microbiota play essential
roles affecting immunity, and some of their roles may be linked
through shared pathways or additive effects. The first to show
such a triangular link between the microbiota, hormones and
immunity were Markle et al. (2013), who demonstrated in the
NOD mouse model that microbes raise testosterone levels in
male hosts, causing protection from T1D. In this mouse model,
females are at higher risk of T1D. However, immature females
that received microbiome transplants from adult males showed
elevated levels of testosterone as well as protection from T1D.
In contrast, NOD mice under GF conditions had a similar diabetes risk for both sexes. Furthermore, the researchers found
metabolomic changes including levels of glycerophospholipid
and sphingolipid metabolites to be different in mice with typically male or typically female microbiota (Markle et al., 2013).
This study establishes a direct relationship between the microbiome and hormones and will open new research paths further
linking these components. Additional studies of these phenomena, including high-throughput sequencing of the microbiota
and gene expression analysis, suggest that hormones and microbiota contribute in an additive manner to T1D protection in
NOD mice (Yurkovetskiy et al., 2013).
A different example linking the microbiota, hormones and
immunity comes from a study in mice, which showed that L.
reuteri enhances wound-healing properties in the host through
upregulation of the neuropeptide hormone oxytocin, by a vagus
nerve-mediated pathway (Poutahidis et al., 2013). The induced
hormonal levels lead to higher levels of specific regulatory T cells
required for wound healing. Lactobacillus reuteri also supports
thick healthy fur in mice, and greater grooming activity, due to
a bacteria-triggered interleukin-10-dependent mechanism and
higher oxytocin levels, respectively (Levkovich et al., 2013).
GROWTH AND DEVELOPMENT
Although no direct connection has been shown to date between
the microbiota and growth hormones, the microbiome’s effects
on ghrelin and sex hormones may indirectly promote release
of growth hormones (Howard et al., 1996). Additionally, SCFAs
have been shown to inhibit growth hormones in cows, by affecting gene transcription in a cAMP/PKA/CREB-mediated signaling
pathway (Wang et al., 2013). Furthermore, bacteria produce somatostatin, which is a known growth hormone inhibitor (Leroith
et al., 1982).
In D. melanogaster, both L. plantarum and Acetobacter pomorum (A. pomorum) were found to be involved in growth promotion. Lactobacillus plantarum promotes larval growth upon nutrient scarcity, by acting genetically upstream of the host nutrient
sensing system controlling hormonal growth signaling (Storelli
et al., 2011). Accordingly, larval development is prolonged in GF
flies, and they exhibit significantly reduced metabolic rates and
altered carbohydrate allocations, including elevated glucose levels (Ridley et al., 2012). Moreover, late larval development in GF
flies and the metabolic alterations were reversed by adding A.
pomorum. Genes in the pyrroloquinoline quinone-dependent alcohol dehydrogenase (PQQ-ADH) pathway of A. pomorum are required for expression of Drosophila insulin-like peptides, which
act as growth factors and are necessary for normal larvae development and metabolism (Shin et al., 2011).
CONCLUSIONS
Although the field of microbiome research is new and developing, a significant number of studies already link hormones and
the gut microbiota. Hormones regulated by the microbiota span
all functional classes and exert broad influences on host behavior, metabolism and appetite, growth, reproduction and immunity. As the understanding of the precise roles of the microbiome deepens, we expect that additional mechanisms will be
shown to involve hormones, including novel interactions. Research in the near future will identify both direct and indirect
pathways (e.g. via immune system components) by which bacteria affect hormones. Specific classes of bacteria (as well as other
Neuman et al.
microorganisms including archaea, bacteriophages, eukaryotes
and eukaryotic viruses) will likely have regulatory roles controlling host hormone levels. These findings may potentially
be used in the future for development of new treatments for
hormone-related diseases or disorders, autoimmune disorders
linked to gender or hormonal activity, and even emotional states
such as stress. In our vision, we see how behavior could be
controlled by the gut microbiota, we see the potential to alter metabolic hormone levels, overcoming depression or stress
by swallowing a combination of ‘good bacteria’. While this still
sounds like science fiction, these novel approaches may become reality within a few years. However, in order to validate
such approaches, the mechanisms, precise bacterial strains and
endocrine-microbiome crosstalk must all be thoroughly deciphered.
ACKNOWLEDGEMENTS
We are grateful for the Marie Curie Career Integration Grant and
the Ihel Foundation for their support.
Conflict of interest statement. None declared.
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