# From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders

Aicha Kriaa, Vincent Mariaule, Charlotte de Rudder, Amin Jablaoui, Harry Sokol, Paul Wilmes, Emmanuelle Maguin, Moez Rhimi

<figure><img src="image_1.png" /></figure>

## To cite this version:

Aicha Kriaa, Vincent Mariaule, Charlotte de Rudder, Amin Jablaoui, Harry Sokol, et al.. From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders. Gut microbes, 2024, 16 (1), pp. 2333434. 10.1080/19490976.2024.2333434. hal-04603826

HAL Id: hal-04603826

https://hal.inrae.fr/hal-04603826

Submitted on 6 Jun 2024

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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# From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders

Aicha Kriaa, Vincent Mariaule, Charlotte de Rudder, Amin Jablaoui, Harry Sokol, Paul Wilmes, Emmanuelle Maguin, Moez Rhimi

## ► To cite this version:

Aicha Kriaa, Vincent Mariaule, Charlotte de Rudder, Amin Jablaoui, Harry Sokol, et al.. From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders. Gut microbes, 2024, 16 (1), pp. 2333434. 10.1080/19490976.2024.2333434. hal-04603826

HAL Id: hal-04603826

https://hal.inrae.fr/hal-04603826v1

Submitted on 6 Jun 2024

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Distributed under a Creative Commons Attribution 4.0 International License
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# From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders

Aicha Kriaa, Vincent Mariaule, Charlotte De Rudder, Amin Jablaoui, Harry Sokol, Paul Wilmes, Emmanuelle Maguin & Moez Rhimi

**To cite this article:** Aicha Kriaa, Vincent Mariaule, Charlotte De Rudder, Amin Jablaoui, Harry Sokol, Paul Wilmes, Emmanuelle Maguin & Moez Rhimi (2024) From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders, Gut Microbes, 16:1, 2333434, DOI: 10.1080/19490976.2024.2333434

**To link to this article:** https://doi.org/10.1080/19490976.2024.2333434

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© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.

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# From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders

Aicha Kriaa, Vincent Mariaule, Charlotte De Rudder, Amin Jablaoui, Harry Sokol, Paul Wilmes, Emmanuelle Maguin & Moez Rhimi

**To cite this article:** Aicha Kriaa, Vincent Mariaule, Charlotte De Rudder, Amin Jablaoui, Harry Sokol, Paul Wilmes, Emmanuelle Maguin & Moez Rhimi (2024) From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders, Gut Microbes, 16:1, 2333434, DOI: 10.1080/19490976.2024.2333434

**To link to this article:** https://doi.org/10.1080/19490976.2024.2333434

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© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.

<figure><img src="image_4.png" /></figure>

Published online: 27 Mar 2024.

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Submit your article to this journal

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Article views: 715

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COMMENTARY AND VIEWS

OPEN ACCESS

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# From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders

Aicha Kriaa IDª, Vincent Mariaule IDª, Charlotte De Rudder IDᵇ, Amin Jablaouiª, Harry Sokol IDª,ᶜ, Paul Wilmes IDᵇ,ᵈ, Emmanuelle Maguin IDª, and Moez Rhimi IDª

ªUniversité Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, Jouy-en-Josas, France; ᵇLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; ᶜINSERM UMRS-938, Centre de Recherche Saint-Antoine, CRSA, AP-HP, Sorbonne Université, Paris, France; ᵈDepartment of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg

**ABSTRACT**

Chronic digestive disorders are of increasing incidence worldwide with expensive treatments and no available cure. Available therapeutic schemes mainly rely on symptom relief, with large degrees of variability in patients' response to such treatments, underlining the need for new therapeutic strategies. There are strong indications that the gut microbiota's contribution seems to be a key modulator of disease activity and patients' treatment responses. Hence, efforts have been devoted to understanding host-microbe interactions and the mechanisms underpinning such variability. Animal models, being the gold standard, provide valuable mechanistic insights into host-microbe interactions. However, they are not exempt from limitations prompting the development of alternative methods. Emerging microfluidic technologies and gut-on-chip models were shown to mirror the main features of gut physiology and disease state, reflect microbiota modification, and include functional readouts for studying host responses. In this commentary, we discuss the relevance of animal models in understanding host-microbe interactions and how gut-on-chip technology holds promises for addressing patient variability in responses to chronic digestive disease treatment.

**KEYWORDS**

Gut microbiome; host response; tools; microfluidic; gut-on-chip; animal models; variability; holobiont; chronic digestive diseases

## Introduction

Chronic non-communicable diseases are lifelong-debilitating conditions with increasing incidence worldwide. They remain the leading cause of death worldwide representing around 74% of all deaths globally according to the World Health Organization.¹ The socioeconomic burden of non-communicable diseases is daunting, with a predicted cost of $47 trillion over the next 20 years.² Of these conditions, Inflammatory Bowel Diseases (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), affect about 6.8 million people worldwide.³ Irritable bowel syndrome (IBS), a common disorder of gut-brain interactions, is estimated to affect about 1 in 10 people worldwide, with significant societal and economic repercussions.⁴ The pathophysiology of IBD and IBS is intricate and the role of risk factors including the genetic background, lifestyle, diet, and gut microbiota is believed to vary across the

globe. New therapeutics are increasingly sought to address both conditions, and significant efforts have been undertaken, yet, no cure is at hand today. Despite proven benefits, treatment schemes for IBS and IBD entail significant drawbacks, ranging from adverse side effects and primary non-response, to the loss of secondary response.⁵,⁶

## Exploring the role of the microbiome in chronic digestive disorders: Current model systems and their limitations

### The role of the microbiome

Several reports now point to the role of gut microbes in influencing response to treatments and potentially shaping patients' response to therapies.⁷ As gut microbes are believed to modulate drug oral bioavailability through the production of microbial drug-metabolizing enzymes, immunomodulatory properties,⁸,⁹ or via

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>
<figure><img src="image_9.png" /></figure>

# From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders

Aicha Kriaa IDª, Vincent Mariaule IDª, Charlotte De Rudder IDᵇ, Amin Jablaouiª, Harry Sokol IDª,ᶜ, Paul Wilmes IDᵇ,ᵈ, Emmanuelle Maguin IDª, and Moez Rhimi IDª

ªUniversité Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, Jouy-en-Josas, France; ᵇLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; ᶜINSERM UMRS-938, Centre de Recherche Saint-Antoine, CRSA, AP-HP, Sorbonne Université, Paris, France; ᵈDepartment of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg

**ABSTRACT**

Chronic digestive disorders are of increasing incidence worldwide with expensive treatments and no available cure. Available therapeutic schemes mainly rely on symptom relief, with large degrees of variability in patients' response to such treatments, underlining the need for new therapeutic strategies. There are strong indications that the gut microbiota's contribution seems to be a key modulator of disease activity and patients' treatment responses. Hence, efforts have been devoted to understanding host-microbe interactions and the mechanisms underpinning such variability. Animal models, being the gold standard, provide valuable mechanistic insights into host-microbe interactions. However, they are not exempt from limitations prompting the development of alternative methods. Emerging microfluidic technologies and gut-on-chip models were shown to mirror the main features of gut physiology and disease state, reflect microbiota modification, and include functional readouts for studying host responses. In this commentary, we discuss the relevance of animal models in understanding host-microbe interactions and how gut-on-chip technology holds promises for addressing patient variability in responses to chronic digestive disease treatment.

**KEYWORDS**

Gut microbiome; host response; tools; microfluidic; gut-on-chip; animal models; variability; holobiont; chronic digestive diseases

## Introduction

Chronic non-communicable diseases are lifelong debilitating conditions with increasing incidence worldwide. They remain the leading cause of death worldwide representing around 74% of all deaths globally according to the World Health Organization.¹ The socioeconomic burden of non-communicable diseases is daunting, with a predicted cost of $47 trillion over the next 20 years.² Of these conditions, Inflammatory Bowel Diseases (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), affect about 6.8 million people worldwide.³ Irritable bowel syndrome (IBS), a common disorder of gut-brain interactions, is estimated to affect about 1 in 10 people worldwide, with significant societal and economic repercussions.⁴ The pathophysiology of IBD and IBS is intricate and the role of risk factors including the genetic background, lifestyle, diet, and gut microbiota is believed to vary across the

globe. New therapeutics are increasingly sought to address both conditions, and significant efforts have been undertaken, yet, no cure is at hand today. Despite proven benefits, treatment schemes for IBS and IBD entail significant drawbacks, ranging from adverse side effects and primary non-response, to the loss of secondary response.⁵,⁶

## Exploring the role of the microbiome in chronic digestive disorders: Current model systems and their limitations

### The role of the microbiome

Several reports now point to the role of gut microbes in influencing response to treatments and potentially shaping patients' response to therapies.⁷ As gut microbes are believed to modulate drug oral bioavailability through the production of microbial drug-metabolizing enzymes, immunomodulatory properties,⁸,⁹ or via

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>
microbiota-host cometabolism,⁷,⁹ they can influ-
ence drug pharmacodynamics and pharmacoki-
netic mechanisms alongside patients' responses to
treatment. Inter-individual variability in gut
microbiota composition may in particular contri-
bute toward individual variability in responses to
a given therapeutic intervention.

Current models

As available models rarely reflect such variability,
and considering the variety of confounding factors,
predicting the response of the host and its gut
microbiota to a given treatment, and therefore dis-
ease management, remains highly challenging.
Furthermore, much of our current mechanistic
knowledge of these diseases has so far relied on
in vivo models, which are often criticized for their
relatively poor ability to predict disease outcomes
and clinical efficacy in humans, and the application
of which is limited by ethical considerations
(Figure 1(a)). We are yet to reach
a comprehensive understanding of IBD and IBS
pathogenesis, which will probably call for
a 'holobiont' approach targeting the host and its
microbiomes. There is no doubt that animal mod-
els have thus far been the cornerstone of research
on elucidating the mechanisms underlying host-
microbe crosstalk in many disease states, including
in IBD and IBS.¹⁰ Indeed, the use of various species
ranging from invertebrates, and non-mammalian
vertebrates to mammals (e.g. mice, rats, pigs) dur-
ing the late twentieth and early twenty-first centu-
ries has been successful in many areas, notably by
improving the current knowledge of cellular signal-
ing pathways, identifying key targets for treatment,
and guiding the design of promising therapeutic
approaches in both conditions.¹¹⁻¹⁴ Relevant
examples include, but are not limited to gnotobio-
tic humanized models with a single gut microbe,
complex or minimal consortia as well as transplan-
tations of entire gut microbial communities from
specific human donors. While showing merits and
limitations, each of these approaches aimed to
explore host-microbe interactions, particularly
immune-microbe feedbacks, to infer causal rela-
tionships and to assess new therapeutics. The field
of IBD research, for instance, has been largely
based on murine studies to better understand

colitis and explore the role of a variety of factors
in shaping host response and disease susceptibility.
As such, evidence of colitis induction was reported
for specific microbial communities or species
including *Helicobacter* spp. and
*Enterobacteriaceae*.¹⁵,¹⁶ Along these lines, monoco-
lonization studies have shown significant improve-
ments with select species of *Clostridiales* and
*Bacteroides*, which were shown to trigger the acti-
vation of colonic regulatory T cells (Treg) and
consequently counteract mucosal inflammation.¹⁷
These findings will bring us one step closer to
defining potential microbial culprits behind the
disease in view of developing next generation pro-
biotics. Yet, one has to bear in mind that coloniza-
tion with either single gut immunomodulatory
strains or different complex microbiota may elicit
varying responses and establish diverse gut
immune landscapes. Individual microbes may
exhibit contrasting behaviors when studied in
a multispecies community, as many metabolites,
due to the inherent emergent properties of the
ecosystem, are only produced in the presence of
other bacteria.¹⁸ The gut ecosystem is highly com-
plex featuring cooperative and competitive interac-
tions between intestinal microbes. Recapitulating
these polymicrobial interactions with the host
requires embracing a holistic ‘holobiont’ view of
host-microbe interactions. In this regard, it has
been demonstrated that transplantation of human
fecal microbiota from donors with IBD can induce
intestinal inflammation in susceptible mice.¹⁹ Such
changes were independent of diet or body weight
and were driven by alterations in gut microbiota
composition, thereby stressing the key role of resi-
dent microbes in the disease. Nevertheless, the
limited insights into the subtle intricacies of the
gut microbiota and the lack of standardized proto-
cols for such approaches pose key constraints to the
effective translation of results obtained through
these models. Major limitations to the current
models are that they commonly fail to capture all
features and functions of human donors’ micro-
biomes, and can themselves be sources of response
variability (Figure 1(a)). The latter could be related
to, but is not restricted to the genetic background.
The gut microbiome contains approximately
a hundredfold more genes than its human
host,²⁰,²¹ and has a variety of metabolic capacities
<figure><img src="image_12.png" /></figure>

microbiota-host cometabolism,⁷,⁹ they can influ-
ence drug pharmacodynamics and pharmacoki-
netic mechanisms alongside patients' responses to
treatment. Inter-individual variability in gut
microbiota composition may in particular contri-
bute toward individual variability in responses to
a given therapeutic intervention.

Current models

As available models rarely reflect such variability,
and considering the variety of confounding factors,
predicting the response of the host and its gut
microbiota to a given treatment, and therefore dis-
ease management, remains highly challenging.
Furthermore, much of our current mechanistic
knowledge of these diseases has so far relied on
in vivo models, which are often criticized for their
relatively poor ability to predict disease outcomes
and clinical efficacy in humans, and the application
of which is limited by ethical considerations
(Figure 1(a)). We are yet to reach
a comprehensive understanding of IBD and IBS
pathogenesis, which will probably call for
a 'holobiont' approach targeting the host and its
microbiomes. There is no doubt that animal mod-
els have thus far been the cornerstone of research
on elucidating the mechanisms underlying host-
microbe crosstalk in many disease states, including
in IBD and IBS.¹⁰ Indeed, the use of various species
ranging from invertebrates, and non-mammalian
vertebrates to mammals (e.g. mice, rats, pigs) dur-
ing the late twentieth and early twenty-first centu-
ries has been successful in many areas, notably by
improving the current knowledge of cellular signal-
ing pathways, identifying key targets for treatment,
and guiding the design of promising therapeutic
approaches in both conditions.¹¹⁻¹⁴ Relevant
examples include, but are not limited to gnotobio-
tic humanized models with a single gut microbe,
complex or minimal consortia as well as transplan-
tations of entire gut microbial communities from
specific human donors. While showing merits and
limitations, each of these approaches aimed to
explore host-microbe interactions, particularly
immune-microbe feedbacks, to infer causal rela-
tionships and to assess new therapeutics. The field
of IBD research, for instance, has been largely
based on murine studies to better understand

colitis and explore the role of a variety of factors
in shaping host response and disease susceptibility.
As such, evidence of colitis induction was reported
for specific microbial communities or species
including *Helicobacter* spp. and
*Enterobacteriaceae*.¹⁵,¹⁶ Along these lines, monoco-
lonization studies have shown significant improve-
ments with select species of *Clostridiales* and
*Bacteroides*, which were shown to trigger the acti-
vation of colonic regulatory T cells (Treg) and
consequently counteract mucosal inflammation.¹⁷
These findings will bring us one step closer to
defining potential microbial culprits behind the
disease in view of developing next generation pro-
biotics. Yet, one has to bear in mind that coloniza-
tion with either single gut immunomodulatory
strains or different complex microbiota may elicit
varying responses and establish diverse gut
immune landscapes. Individual microbes may
exhibit contrasting behaviors when studied in
a multispecies community, as many metabolites,
due to the inherent emergent properties of the
ecosystem, are only produced in the presence of
other bacteria.¹⁸ The gut ecosystem is highly com-
plex featuring cooperative and competitive interac-
tions between intestinal microbes. Recapitulating
these polymicrobial interactions with the host
requires embracing a holistic ‘holobiont’ view of
host-microbe interactions. In this regard, it has
been demonstrated that transplantation of human
fecal microbiota from donors with IBD can induce
intestinal inflammation in susceptible mice.¹⁹ Such
changes were independent of diet or body weight
and were driven by alterations in gut microbiota
composition, thereby stressing the key role of resi-
dent microbes in the disease. Nevertheless, the
limited insights into the subtle intricacies of the
gut microbiota and the lack of standardized proto-
cols for such approaches pose key constraints to the
effective translation of results obtained through
these models. Major limitations to the current
models are that they commonly fail to capture all
features and functions of human donors’ micro-
biomes, and can themselves be sources of response
variability (Figure 1(a)). The latter could be related
to, but is not restricted to the genetic background.
The gut microbiome contains approximately
a hundredfold more genes than its human
host,²⁰,²¹ and has a variety of metabolic capacities
<figure><img src="image_13.png" /></figure>

a

<figure><img src="image_14.png" /></figure>

b

<figure><img src="image_15.png" /><figcaption>**Figure 1.** GoC systems in research (a) Overview of the pros and cons of commonly used models in microbiome research. Main advantages of each system are emphasized in blue, while drawbacks are shown in red. (b) Examples of features and design for GoC systems.</figcaption></figure>

(e.g., vitamin synthesis, fiber degradation, de- and reactivation of drugs) that humans lack or have limited ability to perform. The gut microbiota thus stands out as a source of functional diversity that can modulate an individual's response and

differentially predispose humans to disease.²² These findings highlight the limitations of the ‘one-stool fits all’ approach to managing diseases and stress the current challenge of addressing gut microbiome functional diversity in most scientific
a

<figure><img src="image_13.png" /></figure>

b

<figure><img src="image_14.png" /><figcaption>**Figure 1.** GoC systems in research (a) Overview of the pros and cons of commonly used models in microbiome research. Main advantages of each system are emphasized in blue, while drawbacks are shown in red. (b) Examples of features and design for GoC systems.</figcaption></figure>

(e.g., vitamin synthesis, fiber degradation, de- and reactivation of drugs) that humans lack or have limited ability to perform. The gut microbiota thus stands out as a source of functional diversity that can modulate an individual's response and

differentially predispose humans to disease.²² These findings highlight the limitations of the ‘one-stool fits all’ approach to managing diseases and stress the current challenge of addressing gut microbiome functional diversity in most scientific
<figure><img src="image_16.png" /></figure>

studies. This question is not new to science and is
often magnified by the multifactorial nature of
most explored diseases and the existence of varied
confounding factors that presumably underlie
inconsistencies among studies addressing the con-
tribution of gut microbes to pathogenesis. Each
individual is home to an idiosyncratic set of gut
species and strains, and while most models share
common microbial features with humans, they do
not represent interindividual variability. Also,
experimental designs are far from being standar-
dized as are the guidelines for human-microbiome
association models aimed at inferring causal rela-
tionships. The divergence of lab mouse models
among commercial suppliers and research insti-
tutes is a major driver of irreproducibility and
conflicting data in basic and preclinical research.
Different animal models are nowadays available for
the same disease, which raises the question of
whether and which model would make
a significant contribution to understanding the
clinical condition. However, major challenges still
exist equally regarding the intervention time com-
monly needed to evoke physiological changes, as
well as the duration before those changes would
wane. To prevent overstating and ensure reproduc-
cibility, scientifically supported, common standard
operating practices or guidelines is warranted.
They need to be robust and flexible, leaving provi-
sion for adaptation to the rapid advances in tech-
nology. To counter the translational and ethical
challenges related to animal models, more physio-
logically relevant culture systems that mimic key
tissue features in humans are being implemented.

Advances in gut-on-chip systems and
complementarity with animal models

Microfluidic technology allows three-dimensional
analysis of the morphology of intestinal epithelium
without disturbing the system as well as real-time
in situ monitoring of tissue function and viability.
By adjusting parameters such as shear forces, oxy-
gen concentrations, and cell types, Gut-on-chip
(GoC) devices offer a high degree of flexibility
that *in vivo* models cannot provide. The ability to
study host-microbe interactions and diet/drug-
host-microbiome using (personalized) human
cells and microbiota means a step forward for the

translation of preclinical findings. GoC systems
appear complementary to the animal models as
they provide direct *in situ* analysis that is limited
in standard *in vivo* systems. In contrast, animal
models provide a complex physiological environ-
ment and allow studies over several months as in
chronic intestinal inflammation context. Animal
models allow more in-depth study of microbiome-
immune interactions, as well as of systemic effects.
Furthermore, *in vivo* models allow the study of
organ-organ interactions comprising the entire
body, whereas organ-organ-chip, or body-on-chip
technology is still in its infancy. Overall, GoC tech-
nology is a new tool that complements animal
models, bringing us closer to a human model for
studying host-microbiota interactions.

As we are stepping into a new era of cutting-
edge technologies, microfluidic devices have been
on track to becoming largely accepted as human-
specific experimental platforms for preclinical
research and therapeutic trials. GoC is
a scientific and technological breakthrough in
which biology is teamed with microtechnology
to emulate key facets of human physio/pathology.
Of interest, in 2018, the microfluidics market was
valued at $3.6–5.7 billion,²³ and is expected to
keep growing, among others due to the upcoming
changes in the regulatory frameworks for preclini-
cal testing (FDA Modernization Act 2.0,
Directive 2010/63/EU on the protection of ani-
mals used for scientific purposes), which encou-
rage the use of alternative technologies, e.g.,
organ-on-chips, in line with the three Rs
(Replacement, Reduction, and Refinement) prin-
ciple to reduce animal testing. Organ-on-chips
(OoC) and GoC technology are a relatively recent
addition to the landscape of *in vitro* models avail-
able for preclinical research.²⁴,²⁵ The technology
emerged as a next step after simple cell culture
models in the late 1900’s and the early 2000’s,²⁶,²⁷
enabling the culture of one or more different cell
types in emergent, single-channel organ-on-chip
devices. The field started growing exponentially
after the publication of the seminal lung-on-chip
paper in 2010,²⁸ which presented a perfused
microfluidic device, containing epithelial and
endothelial cells, as well as “breathing” move-
ments, which mimicked additional mechanical
cues experienced *in vivo* and necessary for
<figure><img src="image_15.png" /></figure>

studies. This question is not new to science and is
often magnified by the multifactorial nature of
most explored diseases and the existence of varied
confounding factors that presumably underlie
inconsistencies among studies addressing the con-
tribution of gut microbes to pathogenesis. Each
individual is home to an idiosyncratic set of gut
species and strains, and while most models share
common microbial features with humans, they do
not represent interindividual variability. Also,
experimental designs are far from being standar-
dized as are the guidelines for human-microbiome
association models aimed at inferring causal rela-
tionships. The divergence of lab mouse models
among commercial suppliers and research insti-
tutes is a major driver of irreproducibility and
conflicting data in basic and preclinical research.
Different animal models are nowadays available for
the same disease, which raises the question of
whether and which model would make
a significant contribution to understanding the
clinical condition. However, major challenges still
exist equally regarding the intervention time com-
monly needed to evoke physiological changes, as
well as the duration before those changes would
wane. To prevent overstating and ensure reproduc-
cibility, scientifically supported, common standard
operating practices or guidelines is warranted.
They need to be robust and flexible, leaving provi-
sion for adaptation to the rapid advances in tech-
nology. To counter the translational and ethical
challenges related to animal models, more physio-
logically relevant culture systems that mimic key
tissue features in humans are being implemented.

Advances in gut-on-chip systems and
complementarity with animal models

Microfluidic technology allows three-dimensional
analysis of the morphology of intestinal epithelium
without disturbing the system as well as real-time
in situ monitoring of tissue function and viability.
By adjusting parameters such as shear forces, oxy-
gen concentrations, and cell types, Gut-on-chip
(GoC) devices offer a high degree of flexibility
that *in vivo* models cannot provide. The ability to
study host-microbe interactions and diet/drug-
host-microbiome using (personalized) human
cells and microbiota means a step forward for the

translation of preclinical findings. GoC systems
appear complementary to the animal models as
they provide direct *in situ* analysis that is limited
in standard *in vivo* systems. In contrast, animal
models provide a complex physiological environ-
ment and allow studies over several months as in
chronic intestinal inflammation context. Animal
models allow more in-depth study of microbiome-
immune interactions, as well as of systemic effects.
Furthermore, *in vivo* models allow the study of
organ-organ interactions comprising the entire
body, whereas organ-organ-chip, or body-on-chip
technology is still in its infancy. Overall, GoC tech-
nology is a new tool that complements animal
models, bringing us closer to a human model for
studying host-microbiota interactions.

As we are stepping into a new era of cutting-
edge technologies, microfluidic devices have been
on track to becoming largely accepted as human-
specific experimental platforms for preclinical
research and therapeutic trials. GoC is
a scientific and technological breakthrough in
which biology is teamed with microtechnology
to emulate key facets of human physio/pathology.
Of interest, in 2018, the microfluidics market was
valued at $3.6–5.7 billion,²³ and is expected to
keep growing, among others due to the upcoming
changes in the regulatory frameworks for preclini-
cal testing (FDA Modernization Act 2.0,
Directive 2010/63/EU on the protection of ani-
mals used for scientific purposes), which encou-
rage the use of alternative technologies, e.g.,
organ-on-chips, in line with the three Rs
(Replacement, Reduction, and Refinement) prin-
ciple to reduce animal testing. Organ-on-chips
(OoC) and GoC technology are a relatively recent
addition to the landscape of *in vitro* models avail-
able for preclinical research.²⁴,²⁵ The technology
emerged as a next step after simple cell culture
models in the late 1900’s and the early 2000’s,²⁶,²⁷
enabling the culture of one or more different cell
types in emergent, single-channel organ-on-chip
devices. The field started growing exponentially
after the publication of the seminal lung-on-chip
paper in 2010,²⁸ which presented a perfused
microfluidic device, containing epithelial and
endothelial cells, as well as “breathing” move-
ments, which mimicked additional mechanical
cues experienced *in vivo* and necessary for
<figure><img src="image_17.png" /></figure>

differentiation. Since then, the field has taken
great strides forward following both advances in
engineering (3D printing, sensor integration,
scaffolding, extracellular matrix and hydrogel
development, microfabrication, and introduction
of oxygen gradients and mechanical stresses) and
biological (combination of different cell types,
induced pluripotent stem cells, organoid differen-
tiation and culture, common or universal cell
culture media for co-cultures),²⁹ which has
improved cytoarchitectural and cell chamber
structures, as well as (3D) tissue-like differentia-
tion of the cells. Furthermore, there is an increase
in the development of multi-organ-on-chip mod-
els, making it possible to study the interaction of
multiple organs, as well as off-target and systemic
effects. For reviews on this topic, the reader is
referred to Low et al. 2021, Leung et al. 2022 and
Ingber 2022.<sup>25,26,30</sup>

Unsurprisingly, a wide variety of microfluidic
systems and disease models based on organs-on
-a-chip is emerging to take over the commercial
arena.³¹ Many systems are now available either
commercially or as prototypes from academic
institutions that offer several readouts of cell-, tis-
sue-, and organ-level behaviors.³² GoC systems are
microfluidic, bioengineered, and 3D models of
(regions of) the intestine. They typically consist of
one or more culture chambers containing intestinal
cells (e.g., immune, epithelial, and endothelial),
separated by micro- or nanoporous membranes,
which can simultaneously act as culture scaffolds
and are perfused with cell culture medium
(Figure 1(b)). The microscale and presence of scaf-
folding and relevant 3D structures allows research
of cell interactions on a physiologically representa-
tive scale. GoC allows a more physiologically rele-
vant culture and differentiation of different
intestinal cell types compared to static (tissue cul-
ture insert-based) models. GoC systems support
the culture of different human cell types such as
Caco-2 cells, a well-known immortalized cell line,
and intestinal organoids. While Caco-2 cells harbor
key features of intestinal epithelium (e.g., brush
border, tight junctions, villi formation, and perme-
ability), they fail to recapitulate normal intestinal
physiology.³³,³⁴ On the contrary, intestinal orga-
noids can be obtained from different intestine
regions and contain differentiated cell types, thus

recapitulating *in vivo* intestinal tissue architecture
and multiple-cell type heterogeneity and
interaction.³⁵

Microfluidic GoC devices mimic the tissue-
specific microenvironment by including vascular
perfusion and physiologically relevant mechanic
stimuli and can recapitulate tissue-tissue interac-
tion and interaction with circulating immune cells.
Once inoculated with human cells and gut
microbes or communities, GoC offers the potential
to mimic the complex structures and physiological
functions of the human gut, both alone and when
fluidically coupled together with other organ-on-
chip devices to create human body-on-a-chip sys-
tems. Relevant simulated intestinal features com-
prise barrier function (2D cell cultures, 3D
microstructures (e.g., villi)), and emulation of bio-
mechanical signals (e.g., shear stress and oxygen
gradient) using perfused chambers. Fluids are read-
ily controlled at the microscale to maintain co-
cultures of host epithelial cells with gut microbes
and preserve subtle balances of chemicals and
metabolites.³⁶ With the greater need for real-time
data that can be used for decision-making, more
emphasis has been placed on integrating biosensors
within these devices. Recent advances in nano- and
micro-technology have extended the types of sen-
sors available for in-chip biological processes in so-
called lab-on-chips, as well as the 3D structures of
the channels. Functional readouts to assess barrier
integrity,³⁷,³⁸ oxygen concentrations, and inflam-
matory responses (e.g., cytokine profiles and short-
chain fatty acid levels) can be included using on-
chip biosensors, or by post-analysis of manually
collected samples.

In the past ten years, a range of GoC systems
have been developed, using different approaches
to mimic host and microbial aspects, with differ-
ent levels of personalization. Examples comprise
(personalized) modeling of inflammatory pro-
cesses and preclinical drug assessment in GoC
devices using iPSC-derived human intestinal
organoids or biopsy-derived organoids.<sup>39,40</sup>
Human iPSCs are good candidates to make fully
personalized GoC models feasible, as they allow
many cell types to be derived from the same
genetic background. The improved emulation of
*in vivo* physiology in GoC facilitates a more
representative manner of studying host-microbe
<figure><img src="image_16.png" /></figure>

differentiation. Since then, the field has taken
great strides forward following both advances in
engineering (3D printing, sensor integration,
scaffolding, extracellular matrix and hydrogel
development, microfabrication, and introduction
of oxygen gradients and mechanical stresses) and
biological (combination of different cell types,
induced pluripotent stem cells, organoid differen-
tiation and culture, common or universal cell
culture media for co-cultures),²⁹ which has
improved cytoarchitectural and cell chamber
structures, as well as (3D) tissue-like differentia-
tion of the cells. Furthermore, there is an increase
in the development of multi-organ-on-chip mod-
els, making it possible to study the interaction of
multiple organs, as well as off-target and systemic
effects. For reviews on this topic, the reader is
referred to Low et al. 2021, Leung et al. 2022 and
Ingber 2022.<sup>25,26,30</sup>

Unsurprisingly, a wide variety of microfluidic
systems and disease models based on organs-on
-a-chip is emerging to take over the commercial
arena.³¹ Many systems are now available either
commercially or as prototypes from academic
institutions that offer several readouts of cell-, tis-
sue-, and organ-level behaviors.³² GoC systems are
microfluidic, bioengineered, and 3D models of
(regions of) the intestine. They typically consist of
one or more culture chambers containing intestinal
cells (e.g., immune, epithelial, and endothelial),
separated by micro- or nanoporous membranes,
which can simultaneously act as culture scaffolds
and are perfused with cell culture medium
(Figure 1(b)). The microscale and presence of scaf-
folding and relevant 3D structures allows research
of cell interactions on a physiologically representa-
tive scale. GoC allows a more physiologically rele-
vant culture and differentiation of different
intestinal cell types compared to static (tissue cul-
ture insert-based) models. GoC systems support
the culture of different human cell types such as
Caco-2 cells, a well-known immortalized cell line,
and intestinal organoids. While Caco-2 cells harbor
key features of intestinal epithelium (e.g., brush
border, tight junctions, villi formation, and perme-
ability), they fail to recapitulate normal intestinal
physiology.³³,³⁴ On the contrary, intestinal orga-
noids can be obtained from different intestine
regions and contain differentiated cell types, thus

recapitulating *in vivo* intestinal tissue architecture
and multiple-cell type heterogeneity and
interaction.³⁵

Microfluidic GoC devices mimic the tissue-
specific microenvironment by including vascular
perfusion and physiologically relevant mechanic
stimuli and can recapitulate tissue-tissue interac-
tion and interaction with circulating immune cells.
Once inoculated with human cells and gut
microbes or communities, GoC offers the potential
to mimic the complex structures and physiological
functions of the human gut, both alone and when
fluidically coupled together with other organ-on-
chip devices to create human body-on-a-chip sys-
tems. Relevant simulated intestinal features com-
prise barrier function (2D cell cultures, 3D
microstructures (e.g., villi)), and emulation of bio-
mechanical signals (e.g., shear stress and oxygen
gradient) using perfused chambers. Fluids are read-
ily controlled at the microscale to maintain co-
cultures of host epithelial cells with gut microbes
and preserve subtle balances of chemicals and
metabolites.³⁶ With the greater need for real-time
data that can be used for decision-making, more
emphasis has been placed on integrating biosensors
within these devices. Recent advances in nano- and
micro-technology have extended the types of sen-
sors available for in-chip biological processes in so-
called lab-on-chips, as well as the 3D structures of
the channels. Functional readouts to assess barrier
integrity,³⁷,³⁸ oxygen concentrations, and inflam-
matory responses (e.g., cytokine profiles and short-
chain fatty acid levels) can be included using on-
chip biosensors, or by post-analysis of manually
collected samples.

In the past ten years, a range of GoC systems
have been developed, using different approaches
to mimic host and microbial aspects, with differ-
ent levels of personalization. Examples comprise
(personalized) modeling of inflammatory pro-
cesses and preclinical drug assessment in GoC
devices using iPSC-derived human intestinal
organoids or biopsy-derived organoids.<sup>39,40</sup>
Human iPSCs are good candidates to make fully
personalized GoC models feasible, as they allow
many cell types to be derived from the same
genetic background. The improved emulation of
*in vivo* physiology in GoC facilitates a more
representative manner of studying host-microbe
<figure><img src="image_18.png" /></figure>

interactions in IBD and IBS via the follow-up of
immune responses, such as recruitment of
immune cells and neuronal-immune interaction
upon stimulation with selected bacterial
compounds.⁴¹⁻⁴³ IBS and IBD phenotypes or
potential therapies can be studied via co-culture
with probiotic or pathogenic microorganisms,
e.g., *Faecalibacterium duncaniae* (previously
named *F. prausnitzii*), which can exert anti-
inflammatory effects through butyrate
production,⁴⁴ or with adherent invasive *E. coli*,
*Shigella*, or *Candida* species which are associated
with flare-ups.⁴²,⁴⁵ Next to this, exposure to dis-
ease-specific cocktails of pro-inflammatory cyto-
kines or to chemical compounds, such as dextran
sodium sulfate can be used,⁴⁶ resulting in char-
acteristic epithelial injuries and can aid in unra-
veling disease mechanisms. GoC allows for
infection studies with live microorganisms, both
thanks to perfusion of the system, as well as
peristaltic-like mechanical deformations which
can reduce bacterial overgrowth and allow for
longer co-culture times,⁴⁷ but can enhance colo-
nization by other bacterial species, such as
*Shigella* sp. present in IBD flare-ups.⁴² GoC
devices have also demonstrated high adaptability
and feasibility to co-culture human cells with –
multi-species mixtures or complex human gut
communities, thus allowing glimpses into perso-
nalized host-microbiota interactions
(Figure 1(a)).³⁶,⁴⁸ As such models evolve, new
avenues for better understanding disease pro-
cesses are emerging. Pinpointing the exact role
of relevant microbes and/or their molecules is
often hampered by the inter-individual variability
of microbial communities and response to select
interventions. Hence, introducing a patient's gut
microbiota alongside human cells into such
a system would allow the exploration of persona-
lized responses. This would help design tailored
interventions to improve patients' health without
omitting patient-specific microbial data in clinical
practice. While human epithelial cell culture is
performed under aerobic conditions, the gut
microbiome requires anaerobic conditions. The
integration of an oxygen gradient across the dif-
ferent culture chambers of a GoC represents an
essential improvement in mimicking the gut's
physiological condition.³⁶,⁴⁸,⁴⁹ The presence of

an oxygen gradient has been shown to have an
impact on the diversity, richness, and spatial dis-
tribution of bacteria but also in gene expression
patterns of human epithelial cell line.³⁶,⁴⁸,⁴⁹ This
provides a further step to recapitulating physio-
logically relevant host-microbiota interactions
using microfluidic technology (Figure 1).

Limitations and required improvements in the
application of GoC for preclinical research into
chronic digestive disorders

GoC systems constitute promising tools of which technological development is still in its infancy that will benefit from future methodological and technological advances. The commercialization of current GoC systems and the development of automated control systems (e.g., Zoë-CM2™ Culture Module from Emulate and Omi platform from Fluigent) and chips incorporating pre-qualified cells (to develop *in vitro* cell cultures having the same ratio of epithelial cell subtypes and transcriptome profile as human tissue; e.g., biopsy-derived primary human organoids) have paved the way toward the definition of validated methods and performance criteria, ensuring the GoC reliability, robustness, and consistency. However, due to the instrument investment requirements (*i.e.*, the “lab around the chip”) and the technical challenges associated with fabricating, setting up, and operating even simple GoC systems, the technology is not widely available to the host-microbiome research community yet. In-house fabrication of GoC and their operation remain sources of variability. High throughput experiments using GoC are limited by their compatibility with standard laboratory equipment, the number and type of pumps available, and the current lack of standardization, which requires testing and optimization of assays. While multiple sensors can be integrated, many devices rely largely on endpoint measurements, limiting real-time monitoring. GoC fails to fully reflect the complexity of *in vivo* organs, both on a 3D engineering level, as in the number of interactions they can mimic. GoC systems typically mimic the colon or small intestinal sections of the human intestinal tract, but fail to recapitulate the different physiological conditions, microbiome compositions, and densities occurring over the length of the intestinal tract, making it currently impossible to study these in a single GoC.²⁴ At
<figure><img src="image_17.png" /></figure>

interactions in IBD and IBS via the follow-up of
immune responses, such as recruitment of
immune cells and neuronal-immune interaction
upon stimulation with selected bacterial
compounds.⁴¹⁻⁴³ IBS and IBD phenotypes or
potential therapies can be studied via co-culture
with probiotic or pathogenic microorganisms,
e.g., *Faecalibacterium duncaniae* (previously
named *F. prausnitzii*), which can exert anti-
inflammatory effects through butyrate
production,⁴⁴ or with adherent invasive *E. coli*,
*Shigella*, or *Candida* species which are associated
with flare-ups.⁴²,⁴⁵ Next to this, exposure to dis-
ease-specific cocktails of pro-inflammatory cyto-
kines or to chemical compounds, such as dextran
sodium sulfate can be used,⁴⁶ resulting in char-
acteristic epithelial injuries and can aid in unra-
veling disease mechanisms. GoC allows for
infection studies with live microorganisms, both
thanks to perfusion of the system, as well as
peristaltic-like mechanical deformations which
can reduce bacterial overgrowth and allow for
longer co-culture times,⁴⁷ but can enhance colo-
nization by other bacterial species, such as
*Shigella* sp. present in IBD flare-ups.⁴² GoC
devices have also demonstrated high adaptability
and feasibility to co-culture human cells with –
multi-species mixtures or complex human gut
communities, thus allowing glimpses into perso-
nalized host-microbiota interactions
(Figure 1(a)).³⁶,⁴⁸ As such models evolve, new
avenues for better understanding disease pro-
cesses are emerging. Pinpointing the exact role
of relevant microbes and/or their molecules is
often hampered by the inter-individual variability
of microbial communities and response to select
interventions. Hence, introducing a patient's gut
microbiota alongside human cells into such
a system would allow the exploration of persona-
lized responses. This would help design tailored
interventions to improve patients' health without
omitting patient-specific microbial data in clinical
practice. While human epithelial cell culture is
performed under aerobic conditions, the gut
microbiome requires anaerobic conditions. The
integration of an oxygen gradient across the dif-
ferent culture chambers of a GoC represents an
essential improvement in mimicking the gut's
physiological condition.³⁶,⁴⁸,⁴⁹ The presence of

an oxygen gradient has been shown to have an
impact on the diversity, richness, and spatial dis-
tribution of bacteria but also in gene expression
patterns of human epithelial cell line.³⁶,⁴⁸,⁴⁹ This
provides a further step to recapitulating physio-
logically relevant host-microbiota interactions
using microfluidic technology (Figure 1).

Limitations and required improvements in the
application of GoC for preclinical research into
chronic digestive disorders

GoC systems constitute promising tools of which technological development is still in its infancy that will benefit from future methodological and technological advances. The commercialization of current GoC systems and the development of automated control systems (e.g., Zoë-CM2™ Culture Module from Emulate and Omi platform from Fluigent) and chips incorporating pre-qualified cells (to develop *in vitro* cell cultures having the same ratio of epithelial cell subtypes and transcriptome profile as human tissue; e.g., biopsy-derived primary human organoids) have paved the way toward the definition of validated methods and performance criteria, ensuring the GoC reliability, robustness, and consistency. However, due to the instrument investment requirements (*i.e.*, the “lab around the chip”) and the technical challenges associated with fabricating, setting up, and operating even simple GoC systems, the technology is not widely available to the host-microbiome research community yet. In-house fabrication of GoC and their operation remain sources of variability. High throughput experiments using GoC are limited by their compatibility with standard laboratory equipment, the number and type of pumps available, and the current lack of standardization, which requires testing and optimization of assays. While multiple sensors can be integrated, many devices rely largely on endpoint measurements, limiting real-time monitoring. GoC fails to fully reflect the complexity of *in vivo* organs, both on a 3D engineering level, as in the number of interactions they can mimic. GoC systems typically mimic the colon or small intestinal sections of the human intestinal tract, but fail to recapitulate the different physiological conditions, microbiome compositions, and densities occurring over the length of the intestinal tract, making it currently impossible to study these in a single GoC.²⁴ At
<figure><img src="image_19.png" /></figure>

the gut level, the diversity of human cells (epithelial, endothelial, immune cells, and fibroblasts) and of the microbiome (bacteria, fungi, and viruses) represent essential factors which shape gut physiology. Importantly, the culture of human microbial communities, e.g., fecal communities, *in vitro*, is known to induce shifts in the composition of said communities, often via overgrowth of fast-growing, or facultative anaerobic species, rendering it difficult to mimic actual *in vivo* interactions. GoC devices have been shown to allow the co-culture of a single bacterial strain or a consortium of synthetic bacteria with human cells for up to 96 hours.<sup>36,50</sup> With the integration of oxygen gradient, the culture of more complex microbial communities has been made possible with the recent example of the intestine-on-a-chip device, which allowed the co-culture of a microbiota isolated from fresh infant stool and primary human intestinal cells for five days.<sup>48</sup> Moreover, provided further advances in co-culturing, GoC can be leveraged in a culturomics approach through the culture of complex gut-derived communities to identify novel species and strains involved in pathogenesis, or with potential for disease mitigation.<sup>51,52</sup> This is particularly important given the limited mechanistic understanding of the etiology of these diseases. Despite these recent progress, the long-term culture of a stable complex human microbiome represents one of the main challenges for GoC technology. Sensors may represent a first approach to overcome such limitation. The combination of sensors for microenvironment parameters (e.g., pH, oxygen, temperature, ions, cytokine, and metabolites) could be used to perform a dynamic survey of culture conditions in response to chemical or bacterial alteration which might help to sustain complex microbiome viability and stability.

Several hurdles need to be overcome to ensure wide integration of GoC for host-microbe interaction research in the context of chronic digestive disorders. Standardization of device fabrication and operation will partly remove variability. Increasing the compatibility of GoC with standard laboratory equipment and scaling of devices is needed to increase GoC experimental throughput. Further validation of the results obtained through GoCs is required to verify their ability to reliably recapitulate interactions. Advances in the cell biology and microbiology fields ensuring the growth

and stability of diverse microbial and human cell types with different growth media and microenvironment requirements will provide essential knowledge to recapitulate physiologically relevant host-microbiota interactions in GoC systems.

## Conclusion

Microfluidic devices are highly useful tools for obtaining a holistic mechanistic understanding of microbiota-host interactions against the background of human genetic, biochemical, and cellular responses in real-time. Nevertheless, the development of such technology is still in its infancy, with challenges still to be overcome. To drive broader adoption of such systems, improved on-chip recapitulation of the intestinal biological and physicochemical microenvironment is needed. Furthermore, advances in cell biology and microbiology are called for organoid-on-a-chip systems for instance to ensure cells' stability in the presence of whole gut microbiota, as well as preserving a representative gut microbiome composition in GoC systems. Also, monitoring multiple key interdependent interactions between gut communities and the host *in situ* and in real-time remains a major challenge. Further efforts are needed to develop biosensors to profile key activities with high sensitivity, in real-time and in an automated manner.

Like *in vivo* models, current devices are quite diverse, which makes comparison or standardization of models difficult, although some are commercially available. Common standard operating practices must therefore be defined along with a clear regulatory framework. The application of GoC technology as a complementary technology to animal studies, and possibly eventually as a standalone technology will enable personalized drug/diet-host-microbiome preclinical research and translation of patient-specific responses into personalized treatments in clinical practice.

## Disclosure statement

No potential conflict of interest was reported by the author(s).

## Funding

This work was supported by the French National Research Agency (RestorPro, N° ANR-23-CE14-0073-01), the twinning
<figure><img src="image_18.png" /></figure>

the gut level, the diversity of human cells (epithelial, endothelial, immune cells, and fibroblasts) and of the microbiome (bacteria, fungi, and viruses) represent essential factors which shape gut physiology. Importantly, the culture of human microbial communities, e.g., fecal communities, *in vitro*, is known to induce shifts in the composition of said communities, often via overgrowth of fast-growing, or facultative anaerobic species, rendering it difficult to mimic actual *in vivo* interactions. GoC devices have been shown to allow the co-culture of a single bacterial strain or a consortium of synthetic bacteria with human cells for up to 96 hours.<sup>36,50</sup> With the integration of oxygen gradient, the culture of more complex microbial communities has been made possible with the recent example of the intestine-on-a-chip device, which allowed the co-culture of a microbiota isolated from fresh infant stool and primary human intestinal cells for five days.<sup>48</sup> Moreover, provided further advances in co-culturing, GoC can be leveraged in a culturomics approach through the culture of complex gut-derived communities to identify novel species and strains involved in pathogenesis, or with potential for disease mitigation.<sup>51,52</sup> This is particularly important given the limited mechanistic understanding of the etiology of these diseases. Despite these recent progress, the long-term culture of a stable complex human microbiome represents one of the main challenges for GoC technology. Sensors may represent a first approach to overcome such limitation. The combination of sensors for microenvironment parameters (e.g., pH, oxygen, temperature, ions, cytokine, and metabolites) could be used to perform a dynamic survey of culture conditions in response to chemical or bacterial alteration which might help to sustain complex microbiome viability and stability.

Several hurdles need to be overcome to ensure wide integration of GoC for host-microbe interaction research in the context of chronic digestive disorders. Standardization of device fabrication and operation will partly remove variability. Increasing the compatibility of GoC with standard laboratory equipment and scaling of devices is needed to increase GoC experimental throughput. Further validation of the results obtained through GoCs is required to verify their ability to reliably recapitulate interactions. Advances in the cell biology and microbiology fields ensuring the growth

and stability of diverse microbial and human cell types with different growth media and microenvironment requirements will provide essential knowledge to recapitulate physiologically relevant host-microbiota interactions in GoC systems.

## Conclusion

Microfluidic devices are highly useful tools for obtaining a holistic mechanistic understanding of microbiota-host interactions against the background of human genetic, biochemical, and cellular responses in real-time. Nevertheless, the development of such technology is still in its infancy, with challenges still to be overcome. To drive broader adoption of such systems, improved on-chip recapitulation of the intestinal biological and physicochemical microenvironment is needed. Furthermore, advances in cell biology and microbiology are called for organoid-on-a-chip systems for instance to ensure cells' stability in the presence of whole gut microbiota, as well as preserving a representative gut microbiome composition in GoC systems. Also, monitoring multiple key interdependent interactions between gut communities and the host *in situ* and in real-time remains a major challenge. Further efforts are needed to develop biosensors to profile key activities with high sensitivity, in real-time and in an automated manner.

Like *in vivo* models, current devices are quite diverse, which makes comparison or standardization of models difficult, although some are commercially available. Common standard operating practices must therefore be defined along with a clear regulatory framework. The application of GoC technology as a complementary technology to animal studies, and possibly eventually as a standalone technology will enable personalized drug/diet-host-microbiome preclinical research and translation of patient-specific responses into personalized treatments in clinical practice.

## Disclosure statement

No potential conflict of interest was reported by the author(s).

## Funding

This work was supported by the French National Research Agency (RestorPro, N° ANR-23-CE14-0073-01), the twinning
<figure><img src="image_20.png" /></figure>

European project: 952583-MICAFrica, the European Union's Horizon 2020 research and innovation program under grant agreement N°964590, the European Union's Horizon 2020 Widening Fellowships (N° 101026381), and the European Research Council (Grant ID: 863664).

ORCID

Aicha Kriaa ID http://orcid.org/0000-0001-9115-7764

Vincent Mariaule ID http://orcid.org/0000-0003-2655-0580

Charlotte De Rudder ID http://orcid.org/0000-0002-2114-5829

Harry Sokol ID http://orcid.org/0000-0002-2914-1822

Paul Wilmes ID http://orcid.org/0000-0002-6478-2924

Emmanuelle Maguin ID http://orcid.org/0000-0001-5452-3382

Moez Rhimi ID http://orcid.org/0000-0001-8067-6526

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15. Roy U, Gálvez EJC, Iljazovic A, Lesker TR, Błażejewski AJ, Pils MC, Heise U, Huber S, Flavell RA, Strowig T. Distinct microbial communities trigger colitis development upon intestinal barrier damage via innate or adaptive immune cells. Cell Rep. 2017;21(4):994–1008. doi:10.1016/j.celrep.2017.09.097.

16. Garrett WS, Gallini CA, Yatsunenko T, Michaud M, DuBois A, Delaney ML, Punit S, Karlsson M, Bry L, Glickman JN. et al. Enterobacteriaceae act in concert with the gut microbiota to induce spontaneous and maternally transmitted colitis. Cell Host Microbe. 2010;8(3):292–300. doi:10.1016/j.chom.2010.08.004.

17. Atarashi K, Tanoue T, Oshima K, Suda W, Nagano Y, Nishikawa H, Fukuda S, Saito T, Narushima S, Hase K. et al. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature. 2013;500(7461):232–236. doi:10.1038/nature12331.

18. Pascual-García A, Bonhoeffer S, Bell T. Metabolically cohesive microbial consortia and ecosystem functioning. Philos Trans R Soc Lond B Biol Sci. 2020;375(1798):20190245. doi:10.1098/rstb.2019.0245.

19. Du Z, Hudcovic T, Mrazek J, Kozakova H, Srutkova D, Schwarzer M, Tlaskalova-Hogenova H, Kostovcik M, Kverka M. Development of gut inflammation in mice colonized with mucosa-associated bacteria from patients with ulcerative colitis. Gut Pathog. 2015;7 (1):32–45. doi:10.1186/s13099-015-0080-2.

20. Gilbert JA, Blaser MJ, Caporaso JG, Jansson JK, Lynch SV, Knight R. Current understanding of the human microbiome. Nat Med. 2018;24(4):392–400. doi:10.1038/nm.4517.
<figure><img src="image_19.png" /></figure>

European project: 952583-MICAFrica, the European Union's Horizon 2020 research and innovation program under grant agreement N°964590, the European Union's Horizon 2020 Widening Fellowships (N° 101026381), and the European Research Council (Grant ID: 863664).

ORCID

Aicha Kriaa ID http://orcid.org/0000-0001-9115-7764

Vincent Mariaule ID http://orcid.org/0000-0003-2655-0580

Charlotte De Rudder ID http://orcid.org/0000-0002-2114-5829

Harry Sokol ID http://orcid.org/0000-0002-2914-1822

Paul Wilmes ID http://orcid.org/0000-0002-6478-2924

Emmanuelle Maguin ID http://orcid.org/0000-0001-5452-3382

Moez Rhimi ID http://orcid.org/0000-0001-8067-6526

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17. Atarashi K, Tanoue T, Oshima K, Suda W, Nagano Y, Nishikawa H, Fukuda S, Saito T, Narushima S, Hase K. et al. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature. 2013;500(7461):232–236. doi:10.1038/nature12331.

18. Pascual-García A, Bonhoeffer S, Bell T. Metabolically cohesive microbial consortia and ecosystem functioning. Philos Trans R Soc Lond B Biol Sci. 2020;375(1798):20190245. doi:10.1098/rstb.2019.0245.

19. Du Z, Hudcovic T, Mrazek J, Kozakova H, Srutkova D, Schwarzer M, Tlaskalova-Hogenova H, Kostovcik M, Kverka M. Development of gut inflammation in mice colonized with mucosa-associated bacteria from patients with ulcerative colitis. Gut Pathog. 2015;7 (1):32–45. doi:10.1186/s13099-015-0080-2.

20. Gilbert JA, Blaser MJ, Caporaso JG, Jansson JK, Lynch SV, Knight R. Current understanding of the human microbiome. Nat Med. 2018;24(4):392–400. doi:10.1038/nm.4517.
<figure><img src="image_21.png" /></figure>

21. Li J, Jia H, Cai X, Zhong H, Feng Q, Sunagawa S, Arumugam M, Kultima JR, Prifti E, Nielsen T. et al. An integrated catalog of reference genes in the human gut microbiome. Nat Biotechnol. 2014;32(8):834-841. doi:10.1038/nbt.2942.

22. Zeevi D, Korem T, Godneva A, Bar N, Kurilshikov A, Lotan-Pompan M, Weinberger A, Fu J, Wijmenga C, Zhernakova A. et al. Structural variation in the gut microbiome associates with host health. Nature. 2019;568(7750):43-48. doi:10.1038/s41586-019-1065-y.

23. Markets and Markets. Microfluidics market by materials (polymers, silicon, glass), pharmaceuticals (microreactors, toxicity screening, lab on chip, proteomic & genomic analysis) drug delivery devices (microneedles, micropumps), IVD (POC) - global trends & forecast to 2018. 2013. doi:10.1038/s41586-022-00118-6.

24. Moossavi S, Arrieta MC, Sanati-Nezhad A, Bishehsari F. Gut-on-chip for ecological and causal human gut microbiome research. Trends Microbiol. 2022;30(8):710-721. doi:10.1016/j.tim.2022.01.014.

25. Leung CM, de Haan P, Ronaldson-Bouchard K, Kim GE, Ko J, Rho HS, Chen Z, Habibovic P, Jeon NL, Takayama S. et al. A guide to the organ-on-a-chip. Nat Rev Methods Primers. 2022;2(1):33-61. doi:10.1038/s43586-022-00118-6.

26. Low LA, Mummery C, Berridge BR, Austin CP, Tagle DA. Organs-on-chips: into the next decade. Nat Rev Drug Discov. 2021;20(5):345-361. doi:10.1038/s41573-020-0079-3.

27. Sin A, Chin KC, Jamil MF, Kostov Y, Rao G, Shuler ML. The design and fabrication of three-chamber micro-scale cell culture analog devices with integrated dissolved oxygen sensors. Biotechnol Prog. 2004;20(1):338-345. doi:10.1021/bp034077d.

28. Huh D, Matthews BD, Mammoto A, Montoya-Zavala M, Hsin HY, Ingber DE. Reconstituting organ-level lung functions on a chip. Science. 2010;328(5986):1662-1668. doi:10.1126/science.1188302.

29. Signore MA, De Pascali C, Giampetruzzi L, Siciliano PA, Francioso L. Gut-on-chip microphysiological systems: latest advances in the integration of sensing strategies and adoption of mature detection mechanisms. Sens Bio-Sens Res. 2021;33:100443. doi:10.1016/j.sbsr.2021.100443.

30. Ingber DE. Human organs-on-chips for disease modeling, drug development and personalized medicine. Nat Rev Genet. 2022;23(8):467-491. doi:10.1038/s41576-022-00466-9.

31. Kopec AK, Yokokawa R, Khan N, Horii I, Finley JE, Bono CP, Donovan C, Roy J, Harney J, Burdick AD. et al. Microphysiological systems in early stage drug development: perspectives on current applications and future impact. J Toxicol Sci. 2021;46(3):99-114. doi:10.2131/jts.46.99.

32. Zhang Y, Huang S, Zhong W, Chen W, Yao B, Wang X. 3D organoids derived from the small intestine: an emerging tool for drug transport research. Acta Pharm Sin B. 2021;11(7):1697-1707. doi:10.1016/j.apsb.2020.12.002.

33. Zhang B, Radisic M. Organ-on-a-chip devices advance to market. Lab Chip. 2017;17(14):2395-2420. doi:10.1039/c6lc01554a.

34. Kim HJ, Ingber DE. Gut-on-a-Chip microenvironment induces human intestinal cells to undergo villus differentiation. Integr Biol (Camb). 2013;5(9):1130-1140. doi:10.1039/c3ib40126j.

35. Kim J, Koo BK, Knoblich JA. Human organoids: model systems for human biology and medicine. Nat Rev Mol Cell Biol. 2020;21(10):571-584. doi:10.1038/s41580-020-0259-3.

36. Shah P, Fritz JV, Glaab E, Desai MS, Greenhalgh K, Frachet A, Niegowska M, Estes M, Jäger C, Seguin-Devaux C. et al. A microfluidics-based in vitro model of the gastrointestinal human-microbe interface. Nat Commun. 2016;7(1):11535. doi:10.1038/ncomms11535.

37. Lucchetti M, Werr G, Johansson S, Barbe L, Grandmougin L, Wilmes P, Tenje M. Integration of multiple flexible electrodes for real-time detection of barrier formation with spatial resolution in a gut-on-chip system. Microsyst Nanoeng. 2024;10(1):18. doi:10.1038/s41378-023-00640-x.

38. Nazari H, Shrestha J, Naei VY, Bazaz SR, Sabbagh M, Thiery JP, Warkiani ME. Advances in TEER measurements of biological barriers in microphysiological systems. Biosens Bioelectron. 2023;234:115355. doi:10.1016/j.bios.2023.115355.

39. Workman MJ, Gleeson JP, Troisi EJ, Estrada HQ, Kerns SJ, Hinojosa CD, Hamilton GA, Targan SR, Svendsen CN, Barrett RJ. Enhanced utilization of induced pluripotent stem cell-derived human intestinal organoids using microengineered chips. Cell Mol Gastroenterol Hepatol. 2017;5(4):669-677.e2. doi:10.1016/j.jcmgh.2017.12.008.

40. Ternes D, Tsenkova M, Pozdeev VI, Meyers M, Koncina E, Atatri S, Schmitz M, Karta J, Schmoetten M, Heinken A. et al. The gut microbial metabolite formate exacerbates colorectal cancer progression. Nat Metab. 2022;4(4):458-475. doi:10.1038/s42255-022-00558-0.

41. Beaurivage C, Kanapeckaite A, Loomans C, Erdmann KS, Stallen J, Janssen RAJ. Development of a human primary gut-on-a-chip to model inflammatory processes. Sci Rep. 2020;10(1):21475. doi:10.1038/s41598-020-78359-2.

42. Maurer M, Gresnigt MS, Last A, Wollny T, Berlinghof F, Pospich R, Cseresnyes Z, Medyukhina A, Graf K, Gröger M. et al. A three-dimensional immunocompetent intestine-on-chip model as in vitro platform for functional and microbial interaction studies. Biomaterials. 2019;220:119396. doi:10.1016/j.biomaterials.2019.119396.

43. Gabriel-Segard T, Rontard J, Miny L, Dubuisson L, Batut A, Debis D, Gleyzes M, François F, Larramendy F, Soriano A. et al. Proof-of-concept
<figure><img src="image_20.png" /></figure>

21. Li J, Jia H, Cai X, Zhong H, Feng Q, Sunagawa S, Arumugam M, Kultima JR, Prifti E, Nielsen T. et al. An integrated catalog of reference genes in the human gut microbiome. Nat Biotechnol. 2014;32(8):834-841. doi:10.1038/nbt.2942.

22. Zeevi D, Korem T, Godneva A, Bar N, Kurilshikov A, Lotan-Pompan M, Weinberger A, Fu J, Wijmenga C, Zhernakova A. et al. Structural variation in the gut microbiome associates with host health. Nature. 2019;568(7750):43-48. doi:10.1038/s41586-019-1065-y.

23. Markets and Markets. Microfluidics market by materials (polymers, silicon, glass), pharmaceuticals (microreactors, toxicity screening, lab on chip, proteomic & genomic analysis) drug delivery devices (microneedles, micropumps), IVD (POC) - global trends & forecast to 2018. 2013. doi:10.1038/s41586-022-00118-6.

24. Moossavi S, Arrieta MC, Sanati-Nezhad A, Bishehsari F. Gut-on-chip for ecological and causal human gut microbiome research. Trends Microbiol. 2022;30(8):710-721. doi:10.1016/j.tim.2022.01.014.

25. Leung CM, de Haan P, Ronaldson-Bouchard K, Kim GE, Ko J, Rho HS, Chen Z, Habibovic P, Jeon NL, Takayama S. et al. A guide to the organ-on-a-chip. Nat Rev Methods Primers. 2022;2(1):33-61. doi:10.1038/s43586-022-00118-6.

26. Low LA, Mummery C, Berridge BR, Austin CP, Tagle DA. Organs-on-chips: into the next decade. Nat Rev Drug Discov. 2021;20(5):345-361. doi:10.1038/s41573-020-0079-3.

27. Sin A, Chin KC, Jamil MF, Kostov Y, Rao G, Shuler ML. The design and fabrication of three-chamber micro-scale cell culture analog devices with integrated dissolved oxygen sensors. Biotechnol Prog. 2004;20(1):338-345. doi:10.1021/bp034077d.

28. Huh D, Matthews BD, Mammoto A, Montoya-Zavala M, Hsin HY, Ingber DE. Reconstituting organ-level lung functions on a chip. Science. 2010;328(5986):1662-1668. doi:10.1126/science.1188302.

29. Signore MA, De Pascali C, Giampetruzzi L, Siciliano PA, Francioso L. Gut-on-chip microphysiological systems: latest advances in the integration of sensing strategies and adoption of mature detection mechanisms. Sens Bio-Sens Res. 2021;33:100443. doi:10.1016/j.sbsr.2021.100443.

30. Ingber DE. Human organs-on-chips for disease modeling, drug development and personalized medicine. Nat Rev Genet. 2022;23(8):467-491. doi:10.1038/s41576-022-00466-9.

31. Kopec AK, Yokokawa R, Khan N, Horii I, Finley JE, Bono CP, Donovan C, Roy J, Harney J, Burdick AD. et al. Microphysiological systems in early stage drug development: perspectives on current applications and future impact. J Toxicol Sci. 2021;46(3):99-114. doi:10.2131/jts.46.99.

32. Zhang Y, Huang S, Zhong W, Chen W, Yao B, Wang X. 3D organoids derived from the small intestine: an emerging tool for drug transport research. Acta Pharm Sin B. 2021;11(7):1697-1707. doi:10.1016/j.apsb.2020.12.002.

33. Zhang B, Radisic M. Organ-on-a-chip devices advance to market. Lab Chip. 2017;17(14):2395-2420. doi:10.1039/c6lc01554a.

34. Kim HJ, Ingber DE. Gut-on-a-Chip microenvironment induces human intestinal cells to undergo villus differentiation. Integr Biol (Camb). 2013;5(9):1130-1140. doi:10.1039/c3ib40126j.

35. Kim J, Koo BK, Knoblich JA. Human organoids: model systems for human biology and medicine. Nat Rev Mol Cell Biol. 2020;21(10):571-584. doi:10.1038/s41580-020-0259-3.

36. Shah P, Fritz JV, Glaab E, Desai MS, Greenhalgh K, Frachet A, Niegowska M, Estes M, Jäger C, Seguin-Devaux C. et al. A microfluidics-based in vitro model of the gastrointestinal human-microbe interface. Nat Commun. 2016;7(1):11535. doi:10.1038/ncomms11535.

37. Lucchetti M, Werr G, Johansson S, Barbe L, Grandmougin L, Wilmes P, Tenje M. Integration of multiple flexible electrodes for real-time detection of barrier formation with spatial resolution in a gut-on-chip system. Microsyst Nanoeng. 2024;10(1):18. doi:10.1038/s41378-023-00640-x.

38. Nazari H, Shrestha J, Naei VY, Bazaz SR, Sabbagh M, Thiery JP, Warkiani ME. Advances in TEER measurements of biological barriers in microphysiological systems. Biosens Bioelectron. 2023;234:115355. doi:10.1016/j.bios.2023.115355.

39. Workman MJ, Gleeson JP, Troisi EJ, Estrada HQ, Kerns SJ, Hinojosa CD, Hamilton GA, Targan SR, Svendsen CN, Barrett RJ. Enhanced utilization of induced pluripotent stem cell-derived human intestinal organoids using microengineered chips. Cell Mol Gastroenterol Hepatol. 2017;5(4):669-677.e2. doi:10.1016/j.jcmgh.2017.12.008.

40. Ternes D, Tsenkova M, Pozdeev VI, Meyers M, Koncina E, Atatri S, Schmitz M, Karta J, Schmoetten M, Heinken A. et al. The gut microbial metabolite formate exacerbates colorectal cancer progression. Nat Metab. 2022;4(4):458-475. doi:10.1038/s42255-022-00558-0.

41. Beaurivage C, Kanapeckaite A, Loomans C, Erdmann KS, Stallen J, Janssen RAJ. Development of a human primary gut-on-a-chip to model inflammatory processes. Sci Rep. 2020;10(1):21475. doi:10.1038/s41598-020-78359-2.

42. Maurer M, Gresnigt MS, Last A, Wollny T, Berlinghof F, Pospich R, Cseresnyes Z, Medyukhina A, Graf K, Gröger M. et al. A three-dimensional immunocompetent intestine-on-chip model as in vitro platform for functional and microbial interaction studies. Biomaterials. 2019;220:119396. doi:10.1016/j.biomaterials.2019.119396.

43. Gabriel-Segard T, Rontard J, Miny L, Dubuisson L, Batut A, Debis D, Gleyzes M, François F, Larramendy F, Soriano A. et al. Proof-of-concept
<figure><img src="image_22.png" /></figure>

human organ-on-chip study: first step of platform to assess neuro-immunological communication involved in inflammatory bowel diseases. Int J Mol Sci. 2023;24 (13):10568. doi:10.3390/ijms241310568.

44. Zhang J, Huang YJ, Yoon JY, Kemmitt J, Wright C, Schneider K, Sphabmixay P, Hernandez-Gordillo V, Holcomb SJ, Bhushan B. et al. Primary human colonic mucosal barrier crosstalk with super oxygen-sensitive Faecalibacterium prausnitzii in continuous culture. Med. 2021;2(1):74-98.e9. doi:10.1016/j.medj.2020.07.001.

45. Darfeuille-Michaud A, Boudeau J, Bulois P, Neut C, Glasser AL, Barnich N, Bringer MA, Swidsinski A, Beaugerie L, Colombel JF. High prevalence of adherent-invasive Escherichia coli associated with ileal mucosa in Crohn's disease. Gastroenterology. 2004;127 (2):412-421. doi:10.1053/j.gastro.2004.04.061.

46. Shin W, Kim HJ. Intestinal barrier dysfunction orresses the onset of inflammatory host-microbiome cross-talk in a human gut inflammation-on-a-chip. Proc Natl Acad Sci U S A. 2018;115(45):E10539-E10547. doi:10.1073/pnas.1810819115.

47. Kim HJ, Li H, Collins JJ, Ingber DE. Contributions of microbiome and mechanical deformation to intestinal bacterial overgrowth and inflammation in a human gut-on-a-chip. Proc Natl Acad Sci U S A. 2016 Jan 5;113(1):E7-15. doi:10.1073/pnas.1522193112.

48. Jalili-Firoozinezhad S, Gazzaniga FS, Calamari EL, Camacho DM, Fadel CW, Bein A, Swenor B, Nestor B, Cronce MJ, Tovaglieri A. et al. A complex human gut microbiome cultured in an anaerobic intestine-on-a-chip. Nat Biomed Eng. 2019;3 (7):520-531. doi:10.1038/s41551-019-0397-0.

49. Marzorati M, Vanhoecke B, De Ryck T, Sadaghian Sadabad M, Pinheiro I, Possemiers S, Van den Abbeele P, Derycke L, Bracke M, Pieters J. et al. The HMI™ module: a new tool to study the host-microbiota interaction in the human gastrointestinal tract in vitro. BMC Microbiol. 2014;14(1):133-146. doi:10.1186/1471-2180-14-133.

50. Kim HJ, Huh D, Hamilton G, Ingber DE. Human gut-on-a-chip inhabited by microbial flora that experiences intestinal peristalsis-like motions and flow. Lab Chip. 2012;12(12):2165-2174. doi:10.1039/c2lc40074j.

51. Lagier JC, Armougom F, Million M, Hugon P, Pagnier I, Robert C, Bittar F, Fournous G, Gimenez G, Maraninchi M. et al. Microbial culturomics: paradigm shift in the human gut microbiome study. Clin Microbiol Infect. 2012;18(12):1185-1193. doi:10.1111/1469-0691.12023.

52. Lagier JC, Dubourg G, Million M, Cadoret F, Bilen M, Fenollar F, Levasseur A, Rolain JM, Fournier PE, Raoult D. Culturing the human microbiota and culturomics. Nat Rev Microbiol. 2018;16(9):540-550. doi:10.1038/s41579-018-0041-0.
<figure><img src="image_21.png" /></figure>

human organ-on-chip study: first step of platform to assess neuro-immunological communication involved in inflammatory bowel diseases. Int J Mol Sci. 2023;24 (13):10568. doi:10.3390/ijms241310568.

44. Zhang J, Huang YJ, Yoon JY, Kemmitt J, Wright C, Schneider K, Sphabmixay P, Hernandez-Gordillo V, Holcomb SJ, Bhushan B. et al. Primary human colonic mucosal barrier crosstalk with super oxygen-sensitive Faecalibacterium prausnitzii in continuous culture. Med. 2021;2(1):74-98.e9. doi:10.1016/j.medj.2020.07.001.

45. Darfeuille-Michaud A, Boudeau J, Bulois P, Neut C, Glasser AL, Barnich N, Bringer MA, Swidsinski A, Beaugerie L, Colombel JF. High prevalence of adherent-invasive Escherichia coli associated with ileal mucosa in Crohn's disease. Gastroenterology. 2004;127 (2):412-421. doi:10.1053/j.gastro.2004.04.061.

46. Shin W, Kim HJ. Intestinal barrier dysfunction orresses the onset of inflammatory host-microbiome cross-talk in a human gut inflammation-on-a-chip. Proc Natl Acad Sci U S A. 2018;115(45):E10539-E10547. doi:10.1073/pnas.1810819115.

47. Kim HJ, Li H, Collins JJ, Ingber DE. Contributions of microbiome and mechanical deformation to intestinal bacterial overgrowth and inflammation in a human gut-on-a-chip. Proc Natl Acad Sci U S A. 2016 Jan 5;113(1):E7-15. doi:10.1073/pnas.1522193112.

48. Jalili-Firoozinezhad S, Gazzaniga FS, Calamari EL, Camacho DM, Fadel CW, Bein A, Swenor B, Nestor B, Cronce MJ, Tovaglieri A. et al. A complex human gut microbiome cultured in an anaerobic intestine-on-a-chip. Nat Biomed Eng. 2019;3 (7):520-531. doi:10.1038/s41551-019-0397-0.

49. Marzorati M, Vanhoecke B, De Ryck T, Sadaghian Sadabad M, Pinheiro I, Possemiers S, Van den Abbeele P, Derycke L, Bracke M, Pieters J. et al. The HMI™ module: a new tool to study the host-microbiota interaction in the human gastrointestinal tract in vitro. BMC Microbiol. 2014;14(1):133-146. doi:10.1186/1471-2180-14-133.

50. Kim HJ, Huh D, Hamilton G, Ingber DE. Human gut-on-a-chip inhabited by microbial flora that experiences intestinal peristalsis-like motions and flow. Lab Chip. 2012;12(12):2165-2174. doi:10.1039/c2lc40074j.

51. Lagier JC, Armougom F, Million M, Hugon P, Pagnier I, Robert C, Bittar F, Fournous G, Gimenez G, Maraninchi M. et al. Microbial culturomics: paradigm shift in the human gut microbiome study. Clin Microbiol Infect. 2012;18(12):1185-1193. doi:10.1111/1469-0691.12023.

52. Lagier JC, Dubourg G, Million M, Cadoret F, Bilen M, Fenollar F, Levasseur A, Rolain JM, Fournier PE, Raoult D. Culturing the human microbiota and culturomics. Nat Rev Microbiol. 2018;16(9):540-550. doi:10.1038/s41579-018-0041-0.