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Technological tools and strategies for culturing human gut microbiota in engineered in vitro models

Abstract The gut microbiota directly impacts the pathophysiology of different human body districts. Consequently, microbiota investigation is an hot topic of research and its in vitro culture has gained extreme interest in different fields. However, the high sensitivity of microbiota to external stimuli, such as sampling procedure, and the physicochemical complexity of the gut environment make its in vitro culture a challenging task. New engineered microfluidic gut‐on‐a‐chip devices have the potential to model some important features of the intestinal structure, but they are usually unable to sustain culture of microbiota over an extended period of time. The integration of gut‐on‐a‐chip devices with bioreactors for continuous bacterial culture would lead to fast advances in the study of microbiota‐host crosstalk. In this review, we summarize the main technologies for the continuous culture of microbiota as upstream systems to be coupled with microfluidic devices to study bacteria‐host cells communication. The engineering of integrated microfluidic platforms, capable of sustaining both anaerobic and aerobic cultures, would be the starting point to unveil complex biological phenomena proper of the microbiota‐host crosstalks, paving to way to multiple research and technological applications.

bacteria per gram content increases along the GI tract: 10 1 bacteria/ g in the stomach; 10 3 bacteria/g in the duodenum; 10 4 bacteria/g in the jejunum; 10 7 bacteria/g in the ileum; 10 12 bacteria/g in the colon (Dieterich et al., 2018;Drissi et al., 2017;Shah et al., 2020). However, the exact composition of the bacterial species of the GI is still discussed and its detection depends on the experimental analytic techniques used (e.g., culturomics, metagenomics). Recently, targeted studies have investigated these aspects, even if the results are not yet generalizable (Rinninella et al., 2019). One example is a work by Maihle and collegues where they found 110 species in the stomach and 235 in the left colon by using culturomics as detection technique (Mailhe et al., 2018). Microbiota community also varies along the transversal section of the intestine, from the gut wall to the internal lumen. This depends on chemical and nutrient gradients, antimicrobial immune response, epithelial activity, and morphological features of the gut walls (Donaldson et al., 2015).
Moreover, the composition and abundance of the gut microbiota is related to sex, age, health, mental conditions and diet of the host, among others (Sekirov et al., 2010). Other parameters like pH, flow rate, transit time of digesta, thickness of the mucus layer, activity of immune cells, enzyme secretion, bile acid concentration, redox potential and oxygen concentration are also crucial to determine microbiota features along the different GI tracts (Espey, 2013;Tuohy & Scott, 2015). The stomach has the lowest bacterial concentration due to its unfavorable physicochemical properties, (pH 2), high concentrations of pancreatic enzymes and bile acids. The gastric extreme environment actively filters the ingested bacteria, allowing for the survival and/or successful passage into the small intestine of only few microbial strains (e.g., Helicobacter pylori, E. coli, Salmonella, and Shigella) (Tuohy & Scott, 2015). Along the three small intestine regions the pH raises from 6 to 7.7 (Hillman et al., 2017;Koziolek et al., 2015). In these tracts, the high flow rate of digesta, high micronutrient digestion and adsorbtion, and the intense reactivity of immune cells demonstrated to mainly influence the residing micriobiota (Judkins et al., 2020). The continuous excretion of digestive enzymes and bile acids, and a short transit time cause continuous bacterial renewal and, hence, a dynamic microbiota pattern (Zoetendal et al., 2012). Reactive immune cells residing in the Peyer's patches along the walls of the small intestine, contribute to gut homeostasis and microbiota colonization (Tuohy & Scott, 2015).
Differently, the colon is characterized by the most stable microbiota community, accounting for more than 400 species according to culturomics analysis (Mailhe et al., 2018). This is mainly due to less critical pH values, low transit time of digesta and the availability of food-derived energy. Since the ascending colon is a site of intense bacterial fermentation, the lumen becomes slightly acidic in the proximal portion, while turning neutral in the distal one (Tuddenham & Sears, 2015;Tuohy & Scott, 2015).
Oxygen concentration is one of the key factors influencing bacterial composition in the whole GI tract, since it determines the survival and growth of facultative or obligate anaerobes. An oxygen gradient exists along both the radial and longitudinal axes of the intestine (Zheng et al., 2015). Within the radial section, the oxygen partial pressure (P O2 ) decreases precipitously from the submucosa (80-100 mmHg) to the lumen (<10 mmHg) (Espey, 2013). Cell heterogeneity and distribution along the gut villi mirror oxygen requirements: the cells consuming oxygen at higher rates (i.e., Paneth cells and intestinal stem cells) are located at the basis of the intestinal crypt, while the cells consuming oxygen at lower rates (i.e., bacteria and enterocytes) are located at the lumen interface (Clevers, 2013). Along the longitudinal axis, P O2 decreases gradually while descending the GI tract. It reduces from~77 mmHg in the stomach to <1 mmHg in the rectum (Espey, 2013). These oxygen gradients are mainly due to the structural anatomy and blood vessel distribution. For instance, at the basis of the gut villus the blood flow and nutrient exchange is maximum and it decreases towards the lumen (Zheng et al., 2015).
Such a complex environment influences the gut microbiota, and the communication between bacteria and host-cells. This interplay has recently attracted the attention of researchers, due to the increasing awareness of its direct or indirect effect on the state of health of different body districts, even if anatomically distant from the GI tract. Increasing resources were devoted to model the gut enviroinment and to investigate microbiota-human cell communication to elucidate different biological questions. In this view, one of the most exciting examples of microbiota-host interaction is the microbiota-gut-brain axis as a new paradigm for neuroscience research. Several hypotheses have been proposed to describe the microbiota-gut-brain axis (such as neuroanatomical and neuroendocrine pathways) and were reviewed in detail in other works (Cryan et al., 2019;Serra et al., 2019;Wang & Wang, 2016).
The gastrointestinal tract is a complex system both from a physicochemical and biological point of view. Moving from the upper to the lower GI tract, there are different parameters that vary accordingly to the site, such as oxygen partial pressure, pH and intensity of the dynamic stimuli, as well as an increased number and diversity of bacteria shaping the microbiota. Regardless from the tract considered, the distribution of bacterial strains is influenced by the oxygen gradient. The gut microbiota influences brain development and functionality through neural networks (i.e., enteric nervous system [ENS] or vagus nerve), and the immunomodulatory effects of microbial factors, which can be released both at peripheral and central level (Braniste et al., 2014;Dinan & Cryan, 2017a, 2017bFung et al., 2017;Heijtz et al., 2011;Michel & Prat, 2016;Neufeld et al., 2011;Raimondi et al., 2020;Rea et al., 2016;Rook et al., 2014;Silva et al., 2020;Williams et al., 2014;Yunes et al., 2016). The shift of microbiota population towards a pathologic profile is defined as dysbiosis and its role in neurological and neurodegenerative diseases has been deeply investigated (Brial et al., 2018;Keightley et al., 2015;Leclercq et al., 2014;Moser et al., 2018;Patterson et al., 2014;Tilg et al., 2020). Emerging data suggest that dysbiosis could trigger inflammation by acting on the permeability of both gut and blood-brain barrier (BBB), thus affecting disease onset and progression (Pellegrini et al., 2018;Quigley, 2017;Roy Sarkar & Banerjee, 2019;Sampson et al., 2016;Spielman et al., 2018;Vogt et al., 2017).
Despite in vivo studies were fundamental in highlighting the possible presence of the microbiota-gut-brain axis, they were unable to fully describe the series of biological events underlying this relationship. For this reason, growing resources were dedicated to study in vitro the axis, and in particular the first step of the microbial-host cells molecular dialogue. For instance, it is worthy to notice that the European Research Council funded more than 60 microbiota-related projects in <10 years. Among them, the ERC-CoG-MINERVA project aims at developing an innovative technological platform to investigate the relationship between intestinal microflora and brain functionality, in healthy and pathological conditions (Raimondi et al., 2019. Modeling bacteria-host communication in vitro is not a trivial task. Researchers have used two different approaches: to produce and purify microbiota-derived molecules, they have applied bioreactors able to sustain the culture of human microbiota over an extended period (i.e. fermenters), while to study the effect of bacteria-derived molecules on human cells they have exploited advanced in vitro gut-on-a-chip devices (Holmes et al., 2020;Kim et al., 2012;Mailhe et al., 2018;Sontheimer-Phelps et al., 2020;Villa et al., 2020). Apart from the specific focus of the study, these systems face similar issues, such as the optimization of the sample preparation and modeling the complexity of intestinal environment.
Indeed, human microbiota is a very variable bio-ecosystem requiring stringent technical specifications to be efficiently cultured. In addition, the faithful reproduction of its chemical-physical and structural features is a difficult task, particularly because dynamic stimulation should be included to model physiological phenomena like intestinal peristalsis and biological fluids flows. In addition, microbiota cultivation is higly dependent on the sampling procedure (Table 1).
At the same time, from an engineering point of view, the tools allowing for a prolonged microbiota culture with in vivo-like conditions are based on complex technologies (Marzorati et al., 2014;Venema, 2015). In the following paragraphs, we will focus on the main technologies available for long-lasting human microbiota culturing and the most advanced systems to model in vitro the human gut. In particular, the advantages and disadvantages of recent in vitro approaches to achieve a reliable representation of bacteria-host communication will be discussed.

| Long-term culture of human microbiota
To study microbiota biodiversity, culture-independent anddependent methods can be exploited. Culture-independent approaches, whose advantages and disadvantage were already described (Su et al., 2012;Weinstock, 2012) directly characterize native microbiota by molecuar techniques, without the need of bacteria culturing (Gupta et al., 2019;Su et al., 2012;Weinstock, 2012;Woo et al., 2008). Culture-dependent approaches rely on growing microbiota samples in different media formulations Before characterization. In this case, the first challenge is the selection of the inoculation method. An intrinsic issue arising when culturing microbiota is the difference among in vitro and in vivo conditions (i.e., pH, transit time, carbohydrate content in the medium, variations in oxygen levels, absence of mucosal binding sites or selective pressure), which may result in compositional discrepancies between native and cultured microbiota (McDonald et al., 2013;O'Donnell et al., 2016;. Hence, the isolated microbes may not be representative of the most abundant taxa in situ, leading to ineffective inoculation, regardless of the experimental setup used for the culture (Stefani et al., 2015). Moreover, from a technical point of view, bacteria can be inoculated in liquid form or immobilized in polymer beads (de Vos, 2015). Even though Silverman et al. (2018) showed that gut microbiota composition was stable over long periods of time, the immobilization reproduces both motile and immobilized microbes, and it helps to ensure bacterial diversity at high cell densities for long periods in continuous intestinal reactors (Cinquin et al., 2004(Cinquin et al., , 2006b. Regardless of the application, numerous complications should be taken into account when investigating microbiota effect on human health in vitro Sommer, 2015). First, the presence of cells, modeling the human body, inhibits the use of specific bacterial culture broths imposing the use of cell culture medium, which may affect bacterial growth due to a suboptimal culture condition (Ito et al., 2019;Jalili-Firoozinezhad et al., 2019;Yousi et al., 2019). Second, when chronic phenomena such as gut inflammation and its possible role in neurodegeneration are considered, bacterial culture should be maintained for long time frames. This is important not only to accurately model the in vivo situation, but also to reach the microbiota metabolic equilibrium in vitro and, hence, the cellular reaction in time to the steady state condition  -Easy, specific and accurate sampling (resolution: 5 µm, (Nava et al., 2011) -Biopsy samples are required -Biopsy preparation before laser treatment (Baarlen et al., 2008) -Nuclei acid degradation and low sample amount -Not for large-scale analyses, but suitable for precision medicine -Study of mucosal-and cryptassociated microbial communities (Nava et al., 2011;Pédron et al., 2012;Richard et al., 2018; -Study of mucus layers and mucusassociated bacteria (Chassaing & Gewirtz, 2019;Lavelle et al., 2015) ASPIRATION OF INTESTINAL FLUID A) Capsules: For example, stainless steel capsules connected to a negative-pressure source by a tube: (Shiner, 1963) -Prevention of contamination (after collection, the sample is isolated from the external environment) -Technically challenging -Culture of small bowel microflora for the diagnosis of SIBO (Choung et al., 2011) -In vitro evaluation of orally administered drug products (Litou et al., 2020) B) Tubes: For example, tubes for enteral feeding and ingestible tubes (Lavelle et al., 2010;Minekus et al., 1999) -Prevention of contamination  (Peebo & Neubauer, 2018;Webb, 2017 (Kelly et al., 2017).
For this reason, bioreactors for long-term bacterial culture have become particularly attractive even outside their classic fields of use, in particular as suitable upstream systems for the coculture of bacteria with cells in microfluidic devices (Marzorati et al., 2014).
Long-term culture of the microbiota was firstly assessed in fedbatch conditions, where the medium is poured into the culture vessel hosting the biomass, thus avoiding nutrients depletion (Rumney & Rowland, 1992;Venema & Van Den Abbeele, 2013). The biomass can be composed of a single cell type as well as complex microbial communities, usually cultured with a specific medium in a closed glass vessel (Coimbra et al., 2020;Khalil et al., 2014;Mou & Cooney, 1983).
The two main factors influencing the biomass growth-profile in a fedbatch bioreactor are the inoculum density and the substrate depletion rate (Modak et al., 1986;Rumney & Rowland, 1992). When properly combined, these parameters induce a shift of the growth curve from the typical quadriphasic trend of the batch culture (i.e., lag, logarithmic, stationary and death phases) to enhanced logarithmic and stationary phases, as demonstrated both experimentally and theoretically ( Figure 2a) (Goudar, 2012;Landa et al., 2001;Modak et al., 1986). The possibility to culture the same bacteria population for prolonged times in a single procedure brings some advantages, such as the minimal incidence of mutations and multi-compound fermentation (Kubitschek & Bendigkeit, 1964;Mora-Villalobos et al., 2020). Moreover, the batch and fed-batch conditions can be coupled to operate in nearly stationary regimen, maximizing the control of fermentation conditions before nutritive supplies. Even though these advantages are unquestionable, the fed-batch is a closed system, which drags at least two limitations. First, the logarithmic growth is sustained until fresh medium is supplied (Pompei et al., 2008). This may result in unfavorable temporal constraint, especially for weeks-long experiments like monitoring of the microbiota metabolism over time (Kaarel Adamberg et al., 2020;Cleusix et al., 2008). Second, it is not possible to couple the bioreactor with other downstream systems, which is a sine qua non priority when microbiota-host or bacterial-cellular crosstalk is investigated.
To overcome these limitations, closed fed-batch bioreactors evolved to include medium outflow (Rumney & Rowland, 1992). The balance between nutrient availability and waste removal allows for the prolonged maintenance of a univocal correspondence between biomass and environmental conditions (i.e., steady state condition) (Shachrai et al., 2010;. Only in steady state the changes of molecules' concentration, and hence the physiological state of cells, are negligible and an unaltered biological process can be as- -Study of small bowel diseases (e.g., celiac disease, CD, cancers), assess mucosal activity -Intestinal microbiome sampling and preservation (Koziolek et al., 2015) -Imaging the distal duodenum, jejunum and ileum (Moglia et al., 2009) -Drug release (Cui et al., 2008b) Abbreviations In this case, D should be set not to exceed the maximum specific growth rate of the biomass, thus not diluting the bacterial population faster than its growth capability and leading to a constant depopulation (Bhunia, 2014). Importantly, when the steady state is reached, D can be assumed as numerically equivalent to the specific growth rate of the biomass (Doble & Kumar, 2005).
Hence, the control over the process parameters (in/out flows) can be used to engineer important fermentation conditions, such as the biomass in the culture. However, this is not a trivial process. For instance, increasing D to maximize the growth rate is extremely timeconsuming, as it requires culture stabilization after each D variation step (Adamberg et al., 2015;Gresham & Hong, 2015). Control over the culture can be obtained by the changestat approach, where the environmental parameters are constantly tuned during the culture while preserving the steady state condition (Lahtvee et al., 2011). If D is increased or decreased over time, then the changestat is defined as accelerostat or decelerostat (A-stat or B-stat, respectively). In both cases, D variations should be not too high to disrupt the bioprocess equilibrium, but not too low to lead specific phenotypical mutations.
Differently, if D is maintained constant and other environmental parameters are changed (e.g., pH, oxygen concentration, temperature, medium additives), then the system is defined as dilution rate-stat (D-stat) (Adamberg et al., 2015). The A-/De-stat bioreactors are particularly suitable for culture condition and bioprocess optimization. For example, changestats were used in microbiota continuous cultures, revealing that D has a substantial effect on microbial prevalence (Feria-Gervasio et al., 2011), molecule production (Child et al., 2006;Macfarlane et al., 1998) and biodiversity maintenance . Moreover, the De-stat approach has enormous benefits in terms of time required for reching the targed culture condition (reduction up to 94% compared to chemostat) with only 5% of accuracy loss (Hoekema et al., 2006). Even though these strategies are different, the available bioreactors can switch from one approach to another; for example, passing from a fed-batch pre-stabilization phase to a chemostat/chagestat culture (Fehlbaum et al., 2015;Tanner et al., 2014;Zihler Berner et al., 2013). Hence, the aforementioned classification is useful to define the experimental ratio, but it is limited in the description of the experimental set-up. Indeed, the bioreactors for long-term culture of microbiota were designed in different ways, though maintaining the common aspect of medium flowing in the system (Figure 3). The However, they are more complex than single-or two-stage bioreactors, as they require advanced control systems and empowered resource accessibility (Gibson & Fuller, 2000).
Microbiota culture conditions were further optimized by adding other districts of the GI tract (Venema, 2015). In this way, bioreactors were not only able to model the environment where microbiota is prevalently found in vivo (colon), but also to include other host-related biological processes, such as digestion and bile secretion (Venema, 2015). For example, the TIM1 and TIM2 bioreactors modeled the upper and lower intestine, respectively, and were coupled to in- the relevance of gut multi-stage bioreactors, they will not be described in this review, since already presented in other works (Ceppa et al., 2020).
Regardless of the design, scope and objectives, the culture of microbiota is performed in anaerobic conditions. A modified threestage chemostat exploited microbiota metabolism to produce different ratios of CO 2 and H 2 , thus self-generating anaerobiosis (Feria-Gervasio et al., 2014). However, fluxes of N 2 , CO 2 , H 2 or their combination (e.g., 90% N 2 , 5% CO 2 , 5% H 2 ) remain the preferred strategy to reduce oxygen concentration. Before the experiment, the gases are flushed to remove oxygen from the tubes and vessels; then, the same flux is maintained during the whole culture to guarantee anaerobic conditions McDonald et al., 2013).
The presence of strict anaerobic bacteria in the microbiota is one of the main limitations impairing cocultures with cells. However, the combination of new technologies with increasing interest on microbiota effect on human health has boosted the design of bioengineered platforms able to finely control oxygen concentration.

| Advanced culture systems to study microbiota-host interaction
In vitro systems that sustain the coculture of obligate anaerobic bacteria with cells are as important as challenging. In the last decade, considerable efforts were employed to engineer complex in vitro models with an anoxic-oxic interface (AOI) inside microphysiological environments ( Figure 4 and Table 3). As the intestinal oxygen gradient contributes to the definition and the maintenance of microbiota heterogeneity and distribution, the AOI should be considered a necessary component to be implemented in advanced gut-on-a-chip devices aiming at supporting microbial biodiversity (Zheng et al., 2015). Fluidic systems like the HMI module (Marzorati et al., 2014) and the HuMix device (Shah et al., 2016) showed to successfully sustain the AOI interface for suitable strict anaerobic coculture with cells.
These systems represent suitable models of dynamic host-microbiota interaction. The concept at the basis of fluidic systems consists of parallel chambers forming the luminal and basolateral compartments for bacteria and cell culture, respectively, intermediated by semipermeable membranes. In this configuration, the presence of an inlet and outlet in each chamber allows for a controlled seeding of cells and bacteria inoculation, while not impairing sample collection. In this way, the cocultures can be monitored in real-time by biological analysis, including cytokine assays or metabolomics profiling (Shah et al., 2016). Another advantage of the decoupled perfusion is the possibility to inflow different media and gasses in the chambers (e.g., anoxic and/or oxic gasses), establishing a controlled gradient of oxygen from the aerobic environment of the cellular compartment (21% pO 2 ) to the anaerobic condition for anaerobic bacteria culture (0.8% pO 2 ) (P. Shah et al., 2016;Shin et al., 2019). In this way, the AOI interface is generated between the two chambers, recreating The different approaches used to develop in vitro AOI in a crescendo of complexity. The gradient of oxygen was statically engineered by the presence of O 2 permeable/impermeable environments (a) or agar-based gels (b). Differently, the aerobic/anaerobic medium flows allowed modeling AOI in dynamic gut-on-a-chip systems (c). -The barrier integrity is needed and sufficient to suppress the pro-inflammatory cascades mediated by the host-microbiome cross-talk Shin and Kim (2018) Anoxic-oxic interface-ona-chip -no need of complex apparatus to maintain the anoxic condition (e.g. incubators, glove box) -Geometry adapted for efficient physiological transepithelial anoxic gradient -Bacteria overgrowth in a micrometric space -Impossibility of interfacing with a SHIME-like bioreactor The transepithelial anoxic gradient is necessary and sufficient to coculture obligate anaerobic B. adolescentis and E. hallii with aerobic host epithelial cells Shin et al. (2019) microaerophilic conditions within the mucosal layer. Additionally, dynamic fluid perfusion guarantees continuous metabolite intake and catabolite removal, while avoiding bacteria overgrowth. The achievement of a correct balance between the flow rate, molecule and metabolite diffusion, and the dynamic steady state of the culture requires a careful optimization of the process parameters. Therefore, the maintenance of the AOI interfaces increases the complexity of the experimental set-up. For instance, the absence of oxygen in the anoxic medium needs to be finely controlled by constantly and continuously bubbling nitrogen, which must not interfere in the maintainace of the equilibrium in the diffusion of oxygen coming from the aerobic compartments across the permeable membrane (Shah et al., 2016). To this purpose, the platform is usually provided of sensors for the continuous monitoring of oxygen concentration and, ideally, of an automated control line to restore this equilibrium (Shah et al., 2016).  (Shah et al., 2016). This optimized structure is further coupled with the simultaneous perfusion of -oxic and -anoxic media through the micro-chambers, which leads to the establishment and maintenance of an oxygen gradient close to the in vivo situation.
An advanced gut-on-a-chip device supporting the growth of microbes and cells was presented by Kim (Deloose et al., 2012;Kim et al., 2012). In this example, the maintenance of anaerobic conditions inside the microchannel was not an issue, as LGG is a facultative anaerobic bacterium.
Most recently, the so called AOI-on-a-chip was the first example of a microfluidic device where obligate anaerobic bacteria were successfully integrated in a chip for the study of host-microbiota interaction (Shin et al., 2019). In this case, the AOI interface was Gut-on-a-chip devices with bacteria in direct contact with cells were suitable to investigate microbiota-host crosstalk, exposing either synergy or antagonism. Still, further improvements are needed to achieve long-term cultures and avoid overgrowth in the range of weeks for more robust recpaitulation of microbiota-gut interactions.
The main limitation of these systems when used alone is their impossibility to maintain bacterial cultures for more than few hours, because bacteria overgrowth occurs independently from the dynamic condition of the set-up. This causes bacteria suffering and damage and results in metabolic alterations.
The use of bioreactors for microbiota fermentation-upstream to the gut-on-a-chip device-is a valid tool to overcome this limitation, as demonstrated by the HMI module. Indeed, this gut-on-a-chip device was successfully connected to a SHIME-like reactor, where the fecal samples of patients were processed and then inoculated into the module (Marzorati et al., 2014). The combination of bacteria bioreactors and gut-on-a-chip devices allowed to study the effects of microbiota-related molecules on the modulation of the host response.
Even though the gut-on-a-chip devices described above have the advantage of introducing a dynamic stimulation, they separate anaerobic bacteria from the epithelial cell layer with a synthetic membrane. This strategy protects the host cells from direct exposure to microbiota infections, but fails in recapitulating the real microbiota-gut interface, for example including mucus. Indeed, the mucus is not only a biological structure with complex architecture, SARDELLI ET AL.
| 2897 but it is also strongly dependent on the microbiota-host crosstalk itself . For this reason, gut-on-a-chip systems evolved to coculture bacteria into the luminal channel, in direct contact with the mucus of intestine epithelial layer, while keeping the microenvironment perfused (Kim et al., 2012;Shin et al., 2019;Sontheimer-Phelps et al., 2020).
Up to date, the AOI has been developed in single organ in vitro models, i.e., gut-on-a-chip devices. However, even though these systems demonstrated to sustain dynamic models of the intestinal barrier, they show some limitations when applied to the study of the intestinal microenvironment (Ceppa et al., 2020). To investigate microbiota relationship with distant organs (e.g., gut-brain axis), AOI in vitro models need to be integrated in multiorgan platforms, defined as body-on-chips (BOC). Generally, they are made up of multichamber devices connected in series and kept in communication by fluidic circuits (Kimura et al., 2018). They were efficiently used to determine the absorption process of drugs, by combining in vitro models of intestine and liver, or to investigate the distribution and excretion of molecules by modeling the blood circulation and glomerular filtration (Imura et al., 2010(Imura et al., , 2013Kimura et al., 2015).
However, engineering AOI compartments in BOC represents a challenging technological issue. Indeed, it requires not only the high control over flows to guarantee the correct mass transport among the different body districts, but also to provide the oxygen gradients for the coculture of bacteria and cells. This is particularly difficult when long biological processes are considered, because the presence of continuous bacterial cultures must be integrated into the system without leading to undesired infections. The development of BOC that can cope with AIO, long term bacterial growth and multi-organs models may represens the opportunity for a significative step forward towards more reliable models of complex biological processes, such as molecular axis involving microbiota metabolism, immune response and neurodegeneration (Raimondi et al., 2019).

| CONCLUSIONS
Continuous bioreactors allow for the culture of bacteria for months whent the proper control of the experimental parameters is guaranteed. However, their application has mainly regarded the analysis of the fermentation products, and not the investigation of microbiota-host cell crosstalk. This is due to several limitations.
First, culturing in vitro the human microbiota is intrinsically difficult: microbiota isolated from patients' samples differs in terms biodiversity and concentration from the in vivo situation, being heavily manipulated by the inoculation process. Moreover, the experimental set-up is extremely elaborate and expensive, reaching the highest complexity in the case of three-stage bioreactors, where a deep technical knowledge is needed for the correct control of the culture parameters (e.g., chemostats or changestat configuration).
Second, the available gut-on-a-chip devices are not designed to sustain long-term cocultures of bacteria and cells. Although relevant progresses has been achieved in integrating bacteria into cellular microdevices, the small sizes, low flow rates and the complexity required to maintain an AOI made these systems suitable only for limited applications. For instance, they are valid and efficient tools for the analysis of infection mechanisms and the modulation of gut permeability. However, they do not allow investigating the mechanisms behind complex biological phenomena, such as molecular axis between microbiota products and distant organs homeostatis. A considerable step forward in this field could be achieved by coupling bioreactors for bacterial culture with multicomponent microfluidic systems. Indeed, this new engineered approach may strengthen the advantages of bacterial bioreactors (i.e. long-term cultures, indispensable to recapitulate chronic diseases), with those of microfluidic devices, like the deep control over experimental parameters. In this way, complex phenomena such as the gut-brain axis would be potentially unveiled, opening new medical paradigms and therapeutic scenarios.