Lactobacillus acidophilus BIOTECH 1900 decreases the transepithelial mucosal-to-serosal transport of colchicine in an ex vivo non-everted gut sac model

Abstract

Colchicine (COL) is a permeability-glycoprotein (P-gp) substrate drug used for familial Mediterranean fever, acute pericarditis, and the management of acute gout. It has a narrow therapeutic index which implies that a small change in the drug’s absorption profile may lead to either toxicity or therapeutic failure. Absorption can be altered by modulating the function of P-gp via the concomitant use of drugs, herbal medicines, or food supplements such as probiotics. Here, we investigated the effect of probiotic Lactobacillus acidophilus BIOTECH 1900 on COL’s transepithelial mucosal-to-serosal transport in the jejunum of ICR mice. A high-performance liquid chromatography-photodiode array (HPLC-PDA) method for the assay of COL was developed and validated. The HPLC-PDA method was applied in an ex vivo non-everted gut sac model to measure COL’s cumulative mucosal-to-serosal transport and apparent permeability (P_app). Treatment of L. acidophilus BIOTECH 1900 resulted to a significantly lower COL transport and P_app value compared to the control group. Additionally, the activity of L. acidophilus BIOTECH 1900 was found to be similar to dexamethasone, a known P-gp inducer. We report that L. acidophilus BIOTECH 1900 decreases the transepithelial mucosal-to-serosal transport of COL, suggesting possible P-gp induction. Further studies are recommended to substantiate this transporter-based drug-probiotic interaction.

Key words colchicine; HPLC-PDA; Lactobacillus acidophilus; non-everted gut sac; P-glycoprotein; probiotics

INTRODUCTION

Gout is a rheumatological disease that occurs through the deposition of uric acid crystals in the joints as a consequence of hyperuricemia (Engel et al. 2017). An ancient medication called colchicine (COL) is used as prophylaxis and considered to be one of the first-line treatments for acute gout (Slobodnick et al. 2017). Although effective, gastrointestinal adverse effects are common which includes diarrhea and abdominal pain (Dalbeth et al. 2014). To minimize these gastrointestinal problems, probiotics are used as adjunct therapy (de Vrese & Marteau 2007). Probiotics are defined as ‘live microorganisms, which when administered in adequate amounts, confer health benefits to the host’ (FAO/WHO 2006). Strains belonging to Lactobacillus acidophilus are commonly used as probiotics (Klaenhammer & Kullen 1999). Recent studies have identified several L. acidophilus strains such as LAC0201 and KB27, as novel uricolytic bacteria, capable of lowering serum uric acid levels (Yang et al. 2016, Garcia-Arroyo et al. 2018). This makes L. acidophilus a strong candidate in the management of gout. Moreover, previous investigations among patients on concomitant COL and L. acidophilus INMIA 9602 Er-2 use revealed positive clinical outcomes with respect to blood parameters and intestinal microbiome (Balayan et al. 2015, Pepoyan et al. 2017). It is important to note, however, that probiotic activities are strain specific, signifying that the activities of one strain cannot be extrapolated to another. Thus, significant complication like drug interaction is also possible with the concurrent use of COL and a strain of L. acidophilus. In pharmacotherapy, drug interaction is problematic especially in drugs that have narrow therapeutic index, COL for instance (Finkelstein et al. 2010), because minor alteration in the concentration of absorbed drug can result to either toxicity or therapeutic failure (Tamargo et al. 2015).

Intestinal transporters play a vital role in the absorption of drugs (Katsura & Inui 2003). An example is permeability-glycoprotein (P-gp) present in the apical side of the enterocytes. It is an ATP-dependent efflux pump that transport drug substrates, such as COL, out of the cells (Druley et al. 2001). Inhibition of P-gp function increases the concentration of drug substrate diffusing across the basolateral membrane of the enterocyte, thereby increasing the drug present in the general circulation. On the contrary, inducing the activity of P-gp increases the concentration of drug substrate that is pumped out to the intestinal mucosa causing a decrease in the bioavailability of the drug (Glaeser 2011). Sertraline (SER) is an example of P-gp inhibitor, while dexamethasone (DEX) is a well-known P-gp inducer (Wessler et al. 2013). Aside from drugs, other modulators of P-gp include herbal remedies, food supplements and probiotics (Saksena et al. 2011, Cho & Yoon 2015). Because probiotics forms a reproducible microbial population in the host’s intestine, it may affect the function of intestinal P-gp. To screen articles that modulate P-gp, different experimental models were developed. One of the most commonly performed method is the ex vivo model utilizing gut sacs. Albeit laborious process, it offers an accurate evaluation of the P-gp function and allows an evaluation of the interrelationship between P-gp and the article under study (Gameiro et al. 2017).

In the present study, we examined a transporter-based drug-probiotic interaction between COL and L. acidophilus BIOTECH 1900. We developed and validated a simple high-performance liquid chromatography–photodiode array (HPLC-PDA) bioanalytical method for the assay of COL that was applied in an ex vivo non-everted gut sac model to determine the effect of L. acidophilus BIOTECH 1900 on the transepithelial mucosal-to-serosal transport of the drug.

MATERIALS AND METHODS

Chemicals and reagents

Colchicine (> 95%) was procured from Sigma-Aldrich, Singapore. The HPLC grade acetonitrile (ACN), water, methanol (MeOH); analytical grade chemicals for the preparation of potassium phosphate buffer and Krebs Ringer Bicarbonate Buffer (KRBB) were procured from Harnwell Chemicals Corporation, Makati City, Philippines. Standard DEX and SER were provided by the Institute of Pharmaceutical Sciences – National Institutes of Health, University of the Philippines Manila. Blood Agar, Sabouraud Dextrose Agar (SDA) and De Man, Rogosa and Sharpe (MRS) broth and agar were received as kind gifts from the Department of Medical Microbiology, College of Public Health, University of the Philippines Manila (DMM). All other chemicals and reagents were of analytical grade or equivalent.

Bioanalytical chromatographic method development

Chromatographic instrumentation

An HPLC-PDA method was developed for the quantification of COL in KRBB which simulates the jejunal fluid. Waters Alliance e2695 HPLC system and 2998 PDA detector was used, equipped with HiQsil C₁₈ column (250 mm long, 4.6 mm internal diameter, 5 µm particle size; 100Å pore size). Empower® 3 software was employed for data acquisition.

Chromatographic method optimization

Chromatographic conditions were optimized for the analysis of COL in terms of mobile phase composition and pH, mode of elution, flow rate, UV detection and injection volume. Ambient temperature was used during the analysis with an isocratic mobile phase consisting of 20 mM KH₂PO₄ (pH 3.20) and ACN in 67:33 ratio at a flowrate of 1.20 mL/min. Detection of COL was performed at 350 nm for an injection volume of 10 μL. The run time for the optimized chromatographic method was 7.30 min. The responses of the analyses were evaluated based on tailing factor (T), and theoretical plates (N).

Preparation of stock solution, calibration standards and quality control samples

Primary stock solution of COL (40 µg/mL) was prepared in MeOH. Calibration standards were prepared in KRBB (7.00 g/L NaCl; 0.34 g/L KCl; 0.046 g/L MgCl₂; 1.8 g/L glucose; 0.1 g/L Na₂HPO₄; 0.18 g/L NaH₂PO₄; and 1.26 g/L NaHCO₃) by spiking with suitable stock solution dilutions of COL to obtain standard concentrations in the range of 0.29 – 25.00 μg/mL. The resulting solutions were vortexed and filtered using 0.22 μm syringe filter. Three quality control samples namely, low quality control (LQC) - 0.29 μg/mL, medium quality control (MQC) - 12 μg/mL, and high quality control (HQC) - 20 μg/mL were also prepared in the same way as the calibration standards.

Chromatographic method validation

The optimized method for the determination of COL was validated according to the Food and Drug Administration’s bioanalytical method validation guide (FDA 2018). Parameters that were evaluated included, specificity, linearity, limit of detection (LOD), limit of quantitation (LOQ), carry-over effect, accuracy, and precision. The specificity of the optimized method was assessed by determining any interference of P-gp modulator drugs (DEX and SER) and L. acidophilus BIOTECH 1900. The linearity was identified using a calibration curve obtained in triplicate. From the calibration curve, the equation of the line and correlation coefficient were derived. The LOD and LOQ of the optimized method were calculated based on the standard deviation of the response and slope from the data obtained in linearity. For LOD and LOQ, equations 1 and 2 were respectively employed:

$$\text{LOD}=3.3\sigma /\text{S}$$ (Eq. 1)

$$\text{LOQ}=10\sigma /\text{S}$$ (Eq. 2)

where σ is the standard deviation of the response, while S is the slope of the calibration curve. Carryover effect was identified in triplicate by the injection of a spiked sample at the maximum considered concentration of COL (25 μg/mL) followed by a blank sample. The responses at the retention time of COL were then evaluated. The accuracy and precision of the optimized method within- and between-run were determined using five different spiked samples for each of the quality control samples. Accuracy was expressed as the measured mean concentration and percent recovery, while precision was expressed by percent relative standard deviation (%RSD).

Transporter-based drug-probiotic interaction study

Microorganism

The probiotic L. acidophilus BIOTECH 1900 (Malilay et al. 2019) was procured from the National Institutes of Molecular Biology and Biotechnology, University of the Philippines Los Baños, Laguna. The microorganism was processed and stored at DMM.

Bacterial variability in KRBB with COL

Pure colonies of L. acidophilus BIOTECH 1900 were inoculated in KRBB with COL and were aerobically incubated for 60 min at 37°C. The duration was based on the time L. acidophilus BIOTECH 1900 was exposed in KRBB in the ex vivo non-everted gut sac study. A loopful was obtained, streaked in MRS agar, and underwent 72 h incubation at 37°C. The colonies were characterized based on its morphological appearance, biochemical profile, and gram-staining.

Bacterial preparation

The L. acidophilus BIOTECH 1900 was aerobically cultured in MRS broth for 72 h at 37°C. Cells were obtained by centrifugation at 8,000 x g for 10 min at 4°C. The bacterial cells were washed twice with KRBB at 4°C and resuspended to a concentration of 1.2 x 10⁹ colony-forming units (cfu)/mL in KRBB prior to use.

Health monitoring of experimental animals

The study protocol was approved by the Institutional Animal Care and Use Committee of the University of the Philippines Manila with clearance code 2019-029. Healthy ICR mice were procured from the Research Institute for Tropical Medicine, Philippines. Animals were maintained under conventional conditions with food and water provided ad libitum. The animals were housed at the animal room of DMM. The room was assessed for the presence of fungal air contamination by placing an open SDA plate at the centre of the room for 15 min once daily throughout the animal experimentation and incubating the plate at room temperature for 2 days. The photoperiod for animals was kept at 12 h/12 h light/dark cycle. Acclimatization and health monitoring were done for 7 days prior to the ex vivo non-everted gut sac study. Animals were visually monitored for any signs of illness or discomfort. Faecal microbiological and endoparasitic assessments were likewise performed at days 1 and 8. For faecal microbiological assessment, faeces were collected, suspended and vortexed in sterile water. A loopful of the resulting solution was streaked in Blood Agar plates to determine any haemolytic enteric microorganisms present. The plates were incubated at 37°C for 24 h. For endoparasitic assessment, a perianal tape test was performed on mice (Parkinson et al. 2011). A cellophane tape was applied on the mouse’s perineum, including the perianal area several times. A drop of mineral oil was placed on a glass slide prior to the application of cellophane tape to the slide. Another drop of mineral oil was added on the tape surface and was covered with a cover slip afterwards. The microscope slide was read using 40x objective on a light microscope. Animals that tested positive for enteric haemolytic microorganisms and endoparasites were excluded from the study.

Animal groupings and treatment

The animals were randomly divided into 4 groups and treated as (i) - control group (COL only), (ii) – P-gp inducer control group (DEX + COL), (iii) – P-gp inhibitor control group (SER + COL) and (iv) - treatment group (L. acidophilus BIOTECH 1900 + COL). After acclimatization, overnight fasting was performed before euthanasia, which was the administration of Tiletamine + Zolazepam (Zoletil®) (IM; 40 mg/kg bw) followed by cervical dislocation (Close et al. 1997). Small intestines were excised for the ex vivo non-everted gut sac study. To maintain consistency between experimental animals, duodenum (5 cm segment distal to the pyloric sphincter) and ileum (10 cm section extending proximally from the caecum) were first removed. The remaining small intestinal tissue represents jejunum (Mateer et al. 2016).

Ex vivo non-everted gut sac study

Five cm of the jejunum was used in the ex vivo non-everted gut sac study, with some modifications from previous methods (Goda et al. 1993, Al-Mohizea 2010, He et al. 2011). The jejunum was washed with cold KRBB. The jejunum was tied from one end using a silk suture and was loaded with 0.3 mL COL solution (25 μg/mL), mixed with DEX (25 μg/mL), SER (25 μg/mL) or L. acidophilus BIOTECH 1900 (1.2 x 10⁹ cfu/mL), in KRBB. A control was prepared containing only COL in KRBB. The other end of the jejunum was tied to close the gut, creating a sac. The sac was immersed in a beaker containing 10 mL oxygenated KRBB and maintained at 37°C in a heating block. The KRBB simulates the jejunal fluid, wherein KRBB inside the sac acts as the mucosal medium, while KRBB outside the sac serves as the serosal medium. Samples from the serosal medium (1 mL) were taken at 15, 30, 45 and 60 min. The amount of COL transported from the mucosal to the serosal side was quantified using the HPLC-PDA method developed as described above. For every 1 mL taken from the serosal medium, an equivalent amount of KRBB was replenished. The apparent permeability (P_app) of COL in the non-everted gut sac was calculated using the equation 3 below (Ruan et al. 2006):

$$P_{app}=dQ/dtx(1/A{C}_0)$$ (Eq. 3)

where dQ/dt is the steady-state appearance rate of COL on the serosal medium, A is the surface area of the intestinal sac, and C₀ is the initial concentration inside the sac.

To ensure that the study was valid, the viability test of the gut sacs was performed by monitoring the glucose transport. Glucose is actively transported in the small intestines; whereby healthy and metabolically active gut sacs concentrate glucose in the serosal side. The concentrations of glucose were measured from the serosal medium using a glucometer and were reported at each time points (Lee et al. 2018).

Statistical analysis

The results were reported as mean ± standard deviation (SD). The statistical difference between groups were determined by one-way analysis of variance (ANOVA), followed by Tukey’s post hoc test using GraphPad Prism 9. Values of p < 0.05 were considered statistically significant.

RESULTS

Chromatographic optimization

The bioanalytical method developed was first optimized in terms of various chromatographic conditions to achieve the best chromatographic detection for COL. Several modification in the mode of elution (gradient and isocratic), flowrates (0.80, 1.00 and 1.20 mL/min), pH values of 20 mM KH₂PO₄ (2.88, 3.00 and 3.20), sample injection volumes (1, 5, 10, 15 and 20 μL), UV detection wavelengths (254, 305, 350 nm) and variations in the ratio of mobile phase 20 mM KH₂PO₄:ACN (75:25, 70:30, 67:33, and 65:35) were made. The best chromatographic condition for the detection of COL in KRBB is summarized in Table I with chromatographic performances summarized in Table II.

Table I
Optimized chromatographic conditions as a method of detection and quantification of COL in KRBB.

PARAMETER	OPTIMIZED CONDITION
Mode of Elution	Isocratic
Flowrate	1.20 mL/min
pH Value of 20 mM KH2PO4	3.20
Sample Injection Volume	10 μL
UV Detection	350 nm
Mobile Phase Ratio (20 mM KH2PO4:ACN)	67:33

Table II
Performance parameters for the optimized chromatographic method.

PARAMETER	RESULTS	ACCEPTANCE CRITERIA
Retention time (min)	6.05 ± 0.03	-
Tailing factor (T)	0.78 ± 0.01	T < 2.0
Theoretical plates (N)	9909.63 ± 2896.02	N > 2000

Chromatographic method validation

The optimized chromatographic method developed was validated according to the FDA (2018) guidelines on bioanalytical method validation. The method was specific for COL in KRBB (Fig. 1). No interfering peaks were observed at the retention time of COL in the blank KRBB and KRBB spiked with DEX, SER and L. acidophilus BIOTECH 1900.

Figure 1
Representative chromatogram of COL using the developed HPLC-PDA method.

Linearity analysis was performed by the calculation of the regression equation and correlation coefficient from non-zero calibrator levels. A correlation coefficient value of 0.9999 was observed indicating a linear relationship between concentration of COL and the area under the curve. Using the standard deviation of the response and slope from the linearity analysis, the LOD was found to be 0.011 µg/mL, while the LOQ was 0.035 µg/mL. Potential carryover effect was also investigated and was found to be negligible for the developed method since no COL peak was detected. The accuracy and precision of within- and between-run are presented in Table III. The accuracy based on the measured mean concentration was within the allowed deviation from the nominal concentration of 15% for LQC, MQC and HQC samples. Similarly, the within- and between-run precision of the method were acceptable as the %RSD values did not exceed 15% for LQC, MQC and HQC. Hence, the developed method was accurate and precise.

Table III
Accuracy and precision of the optimized chromatographic method.

Quality Control Sample	Nominal Concentration (µg/mL)	Within-run			Between-run
		Measured concentration (µg/mL)	% Recovery	% RSD	Measured concentration (µg/mL)	% Recovery	% RSD
LQC	0.29	0.294	101.26	0.802	0.291	100.53	0.22
MQC	12.00	12.216	101.80	0.037	12.333	102.77	1.30
HQC	20.00	20.438	102.19	0.339	20.594	102.97	0.76

Health monitoring of experimental animals

No fungal growths were observed in the SDA plates that were exposed in the animal laboratory, indicating that the environment was acceptable in terms of fungal air contamination. Throughout the study, no signs of illness and discomfort were observed from the animals. Faecal microbial analysis showed only non-haemolytic microorganisms. Furthermore, all animals were negative for endoparasitic infestations.

Transepithelial mucosal-to-serosal transport of COL

The scheme for the transepithelial mucosal-to-serosal transport of COL is summarized in Fig. 2a with the corresponding cumulative concentration of COL for each group depicted in Fig. 2b. In the P-gp inducer group DEX, the transported COL in the serosal fluid was significantly lower compared to the P-gp inhibitor group SER and the control group. Likewise, significantly lower concentration of transported COL was also observed in the presence of L. acidophilus BIOTECH 1900 when compared with SER and control. Between L. acidophilus BIOTECH 1900 and DEX group, no statistically significant differences were observed in the cumulative COL concentration in all time points. With respect to the P_app values (Fig. 3), no statistically significant difference was observed between L. acidophilus BIOTECH 1900 and DEX. Additionally, both groups were found to have statistically significant difference with SER and control groups. In the gut sac viability study, the glucose concentrations in the serosal medium were found to increase from the 15 min reading to the final reading at 60 min in all groups (Fig. 4). No statistically significant differences were observed across all groups. The results suggest that the gut sacs were viable and the concentration of the drugs and L. acidophilus BIOTECH 1900 utilized were well tolerated by the jejunum.

Figure 2
a. Summarized scheme for the transepithelial mucosal-to-serosal transport of COL using an ex vivo non-everted gut sac model and HPLC-PDA analysis. b. Cumulative COL concentrations measured from the serosal medium in the ex vivo non-everted gut sac model. Values are mean ± SD (n = 3).

Figure 3
Calculated P_app values. Values are mean ± SD (n = 3). * indicate significant difference at p < 0.05 compared to control. # indicate significant difference at p < 0.05 compared to inhibitor control (SER).

Figure 4
Glucose concentration in the serosal side over time. Values are mean ± SD (n = 3).

DISCUSSION

To the best of our knowledge this is the first study dealing with a bioanalytical method for the assay of COL in the presence of P-gp modulators and probiotic applied in an ex vivo non-everted gut sac study. The developed method was precise, accurate and specific for COL in KRBB. No interfering peaks were observed in KRBB spiked with two P-gp modulator drugs, namely, DEX and SER. The absence of DEX and SER peaks indicate that the drugs do not absorb UV at 350 nm given the chromatographic method. In addition, the presence of L. acidophilus BIOTECH 1900 did not interfere on the COL peak. In the same way, COL has no effect on the viability of L. acidophilus BIOTECH 1900 incubated at 37°C for 60 min. The L. acidophilus BIOTECH 1900 is a facultative anaerobic microorganism, allowing it to grow in the presence of oxygen and previous studies have demonstrated that COL hardly affects gut microbes (Shimizu et al. 2016) which includes L. acidophilus. In the present study, colonies grew as pinpoint, flat with irregular edges after incubating the MRS agar plates streaked with a loopful of the incubated COL-L. acidophilus BIOTECH 1900 mixture. Cells from the colonies were gram-positive bacilli, and were both catalase- and oxidase-negative. These are all prominent characteristics of L. acidophilus.

The P-gp is a drug efflux pump of the ATP-binding cassette transporter family that plays an important role in drug absorption (Lin & Yamazaki 2003). In humans, P-gp is encoded by MDR1 gene and is physiologically expressed in the intestine (De Iudicibus et al. 2008, Katayama et al. 2014). Animal studies concerning P-gp are commonly performed in rodents, such as mice. Mice have two MDR1 homologues, mdr1a and mdr1b, which possess important physiological, pharmacological, and toxicological functions, including the transportation of drugs across the cell membrane similar to human MDR1 (Schinkel et al. 1997, Hoffmann & Kroemer 2004). Moreover, mice are used in pre-clinical studies involving gut since they show similarity with human microbiota at the genus level and are functionally alike (Wang et al. 2017). Thus, mouse is a logical representative to study human intestinal P-gp in ex vivo animal setting. In the study, the intestinal health of ICR mice were ensured since bacterial and parasitic infections can degrade the integrity of the intestines thereby disrupting its absorptive function (Siccardi et al. 2008, Di Genova & Tonelli 2016). The absence of haemolytic enteric bacteria and endoparasites allowed the ICR mice to be used in the ex vivo non-everted gut sac study, which is one of the most commonly used models in the screening of P-gp modulators (Gameiro et al. 2017). Ex vivo gut sac models are sensitive in the analysis of P-gp modulators with an additional advantage of specificity on the intestinal site. In addition, non-everted intestinal rodent sac model offers a means for the prediction of the human absorption of compounds (Ruan et al. 2006).

Since the absorption of drugs is partly regulated by P-gp, any alteration in the P-gp function would eventually change the drug’s bioavailability. Drugs, herbal medicines, dietary and food supplements, including probiotics are some preparations that can modulate P-gp function (Wang et al. 2012, Cho & Yoon 2015). In general, inhibiting the P-gp function causes an increase in intestinal permeability and transport of the substrate drug from the mucosal to the serosal region of the intestines (Finch & Pillans 2014). In the study, SER was used as the P-gp inhibitor control, which resulted to an increased transepithelial COL transport. Three mechanisms wherein P-gp can be inhibited were proposed, (i) competitive/non-competitive/allosteric blocking of the drug binding site in P-gp, (ii) interference in the ATP hydrolysis, and (iii) alteration of the cellular membrane lipid integrity (Amin 2013). Conversely, inducing the function of P-gp causes more of the substrate drug to be transported back into the intestinal mucosa resulting to reduced drug concentration in the serosal region (Johne et al. 1999, Hamman et al. 2001). The stimulation process reduces the intestinal permeability of the substrate. This was observed in the study’s P-gp inducer group, DEX, and L. acidophilus BIOTECH 1900. Both groups registered a low cumulative COL concentration in the serosal medium, which is supported by their corresponding low P_app values. The data from the treatment group was comparable to the inducer group which may indicate that L. acidophilus BIOTECH 1900 also induces P-gp function. Our ex vivo findings corroborate with the in vitro study of Saksena et al. (2011), suggesting L. acidophilus treatment increases the activity of P-gp in Caco-2 cell lines. Although the mechanism of stimulation was not included in the present study, two pathways involved in the expression of P-gp were previously identified, namely, phosphoinositide 3-kinase and ERK1/2 MAPK (Saksena et al. 2011). As with other probiotics, L. acidophilus is given at a concentration of more than 10⁸ cfu/day to ensure a sustainable population growth in the intestine (Andersson et al. 2010, Gomes et al. 2014). In our study, a concentration of 1.2x10⁹ cfu/mL was introduced in the jejunum to mirror the amount of probiotic that is necessary to form a viable population in the gut. The formation of a reproducible L. acidophilus population in the gut may induce P-gp, believed to be mediated by nuclear receptors such as pregnane X receptor and constitutive androstane receptor which are key transcriptional regulators of the efflux pump (Wu et al. 2016). The increase in the number of intestinal efflux pumps, increases the amount of drug substrate that is transported out to the mucosa, provided that ATP is available. Soluble factors secreted by the microorganisms may also have elicited the stimulatory effect on P-gp (Wang et al. 2012, Priyamvada et al. 2016). In general, L. acidophilus produces metabolites that are components of biochemical reactions needed in the production of ATP, such as succinic, fumaric and citric acid in the Krebs cycle (Chamberlain et al. 2019). In addition, intestinal microorganisms were found to release ATP that permeates the intestinal epithelium of the host (Proietti et al. 2019). The abundance of ATP can fuel the P-gp function, thereby facilitating the drug transporting mechanism. Further studies are needed to map the metabolites that directly or indirectly affects the action of P-gp. Nevertheless, the discovery that a reproducible amount of L. acidophilus BIOTECH 1900 decreases the transepithelial mucosal-to-serosal transport of COL has clinical significance in the field of public health pharmacy and public health microbiology. The extensive use of various probiotics as adjunct therapy might create interactions which may affect the bioavailability of the drug concerned. Thus, profiling of drug-probiotic interactions must be conducted because the activities of these microorganisms are strain specific. In the present study, we identified that L. acidophilus BIOTECH 1900 could cause a transporter-based interaction with COL, resulting to the drug’s decreased intestinal absorption.

CONCLUSION

A new bioanalytical HPLC-PDA method was developed and validated for the assay of COL. By applying this method, COL concentration was quantified in simulated jejunal fluid from an ex vivo non-everted gut sac study. Similar to a P-gp inducer DEX, L. acidophilus BIOTECH 1900 decreased the permeability of COL resulting to a decline in the transepithelial transport of the drug from the mucosal to the serosal region of the jejunum. A possible transporter-based drug-microbe interaction might have occurred, which requires further studies to verify the notion and identify the mechanism involved. This kind of interaction should be identified to avoid drug toxicity or therapeutic failure in the clinical use of probiotic as an adjunct treatment.

ACKNOWLEDGMENTS

The authors extend their appreciation to Richelle Ann Manalo, RCh, MS and Mary France Gonzaga, RPh, who offered their assistance in the study. Additionally, the authors express their gratitude to the National Institutes of Health, University of the Philippines Manila for providing financial assistance under grant number NIH 2019-014. The mouse image in Fig 2a was an open access science art, downloaded from Scidraw.io and the authors would like to thank the artists: Ethan Tyler and Lex Kravitz (doi.org/10.5281/zenodo.3926165).

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Publication Dates

• Publication in this collection
  21 Nov 2022
• Date of issue
  2022

History

• Received
  22 May 2021
• Accepted
  24 Jan 2022