Purpose Experimental investigations in rodents have contributed significantly to our current understanding of the potential importance of the gut microbiome and brain interactions for neurotransmitter expression, neurodevelopment, and behaviour. However, clinical evidence to support such interactions is still scarce. The present study used a double-blind, randomized, pre- and post-intervention assessment design to investigate the effects of a 4-week multi-strain probiotic administration on whole-brain functional and structural connectivity in healthy volunteers. Methods Forty-five healthy volunteers were recruited for this study and were divided equally into three groups (PRP: pro- biotic, PLP: placebo, and CON: control). All the participants underwent resting-state functional MRI and diffusion MRI brain scans twice during the course of study, at the beginning (time point 1) and after 4 weeks (time point 2). MRI data were acquired using a 3T whole-body MR system (Magnetom Skyra, Siemens, Germany). Results Functional connectivity (FC) changes were observed in the default mode network (DMN), salience network (SN), and middle and superior frontal gyrus network (MFGN) in the PRP group as compared to the PLP and CON groups. PRP group showed a significant decrease in FC in MFGN (in frontal pole and frontal medial cortex) and in DMN (in frontal lobe) as compared to CON and PLP groups, respectively. Further, significant increase in FC in SN (in cingulate gyrus and precuneus cortex) was also observed in PRP group as compared to CON group. The significance threshold was set to p < 0.05 FWE corrected. No significant structural differences were observed between the three groups. Conclusions This work provides new insights into the role of a multi-strain probiotic administration in modulating the behaviour, which is reflected as changes in the FC in healthy volunteers. This study motivates future investigations into the role of probiotics in context of major depression and stress disorders. Keywords Probiotics · Resting-state · Diffusion · Gut–brain axis · MRI · Salience Introduction The characterization of gut microbiome a decade ago has added a long-overlooked aspect to the complex bidirec- tional signalling between brain and gut . This interac- * Veronika Schöpf email@example.com tion, known as ‘gut–brain axis’ has been shown to link the cognitive and emotional centres of brain with the intestinal Institute of Psychology, University of Graz, Universitätsplatz functions . The gut microbiota plays a prominent role 2, 8010 Graz, Austria in these interactions by regulating behaviour and brain BioTechMed, Graz, Austria processes, that is, stress responsivity , anxiety-related Institute of Medical Engineering, Graz University behaviours , pain perception , and social cognition of Technology, Graz, Austria , as shown by intriguing experimental investigations Otto Loewi Research Centre, Pharmacology Section, Medical in rodents. In addition to the emotional processing, gut University of Graz, Graz, Austria microbiota have also been shown to play an important role Department of Internal Medicine, Medical University in modulating brain biochemistry and brain plasticity. For of Graz, Graz, Austria Vol.:(0123456789) 1 3 European Journal of Nutrition example, Hoban and colleagues showed that the gut micro- In this study, we aimed at investigating the influence of a biota regulates the expression of genes linked to myelination 4-week multi-strain probiotic administration on whole-brain and myelin plasticity in prefrontal cortex . On a similar functional connectivity in healthy volunteers. We hypothe- note, a role of gut microbiota in altering the central GABA sized that the manipulation of gut microbiota by multi-strain (gamma amino butyric acid) receptor expression has also probiotic ingestion will influence functional connectivity in been demonstrated . Although most of the evidence for the resting-state networks (RSNs) mediating emotional and an influence of gut microbiota on brain and behaviour is higher order cognitive functions. We suspect that salience based on our understanding of rodent studies, initial stud- network, executive network and default mode network are of ies in humans seem to support the notion that there exists a particular interest, considering their role in mediating these similar relationship between our gut microbes and brain and processes. Furthermore, we also hypothesized that the pro- behaviour. For instance, consumption of Lactobacillus and biotic intervention will influence the underlying white mat- Bifidobacterium strains by healthy volunteers was found to ter architecture associated with the functional connectivity influence the scores of stress and anxiety-related question- networks. To test these hypotheses, we performed resting- naires [9–11]. However, as the assessment was based on self- state fMRI and diffusion MRI scanning at two time points: reported measures in all these studies, caution is warranted at baseline (time point 1) and after 4 weeks (time point 2). when drawing firm conclusions. Furthermore, some recent studies have employed neuroimaging techniques such as task-based functional MRI and resting-state fMRI to better Methods understand the physiological pathways involved in gut–brain communications and their influence on brain function [ 12, Subjects and study design 13]. A task-based fMRI study conducted in our group  demonstrated that a 4-week multi-strain probiotic adminis- The present study used a double-blind, randomized, pre- and tration influences brain activation patterns associated with emotional decision-making and recognition memory tasks in post-administration (4 weeks) assessment design. Forty-five right-handed healthy participants (mean age (years) = 26.24, healthy volunteers. Another fMRI study by Tillisch and col- leagues showed that the ingestion of Lactobacillus and Bifi- SD = 4.76; 23 female; age group 20–40 years) were recruited for this study via university email lists, flyers, and word of dobacterium species for 4 weeks by healthy women altered the brain activity in insula, somatosensory cortex and peri- mouth. The participants were divided equally into three groups: probiotics (PRP) group (which took the probiot- aqueductal gray brain regions in response to an emotional attention fMRI task . This study also investigated the ics product), placebo (PLP) group (which took the placebo product), and control (CON) group (with no product). This corresponding functional connectivity (FC) changes in these regions using region of interest (ROI) analysis and reported study was conducted in accordance with the principles of the Declaration of Helsinki and written informed consent changes in FC in midbrain regions. However, the influence of probiotic administration on whole-brain functional con- was obtained from all participants prior to participation. The local ethics committee of the University of Graz, Austria, nectivity remains unclear. Furthermore, even when there is a considerable volume of preclinical literature indicating an approved the study. Exclusion criteria were MR incompat- ibility, substance abuse, use of antibiotics or probiotics (in influence of gut microbiome on brain structure, our under - standing in human subjects in this context is limited to the the last 3 months), and CNS trauma/disorders. All the participants underwent MRI scanning at baseline observations in patients with irritable bowel syndrome (IBS)  and this is far from complete. (time point 1) and after 4 weeks (time point 2). The appoint- ments for the second scanning were planned well in advance, Numerous neuroimaging studies have revealed a strong relationship between structural integrity and functional con- to assure equal intervals between the first and second scan- ning session for all the participants. During this period, all nectivity (see review by Damoiseaux and Greicius ). Functional connectivity is most commonly calculated from participants were instructed to fill in a daily diary about their gastrointestinal symptoms and details of probiotic/placebo resting-state fMRI and examines the similarities between spontaneous fluctuations that occur over time in distal grey intake [time of intake, method of intake (with milk/water/ juice)]. Further, participants were instructed to maintain matter regions  and diffusion MRI measures the struc- tural integrity . Considering the existing literature on their usual diet and lifestyle habits during the 4-week period. Any deviation from this was instructed to be recorded in the the influence of probiotic administration on functional con- nectivity , a further investigation of the structural basis daily diary for later assessment. Additional questionnaires were incorporated into a daily diary and participants were for these functional interactions would add valuable insights to our current understanding of the gut–brain interaction briefed about the instructions to fill these out at the begin- ning of the study. mechanisms. 1 3 European Journal of Nutrition This study is part of another research project which inves- T2*-weighted imaging sequence consisting of 32 interleaved tigated changes in behaviour (using self-reported question- slices (field of view = 256 mm , TE = 27 ms, TR = 1.99 s, naires) and brain function (using task-based fMRI) following slice thickness = 4 mm, voxel size = 4*4*4 mm ). Scanning probiotic intake. Therefore, details of participant character- time for the resting-state sequence was 5 min and 24 s, dur- istics and assessments if not necessary for understanding are ing which the subjects were instructed not to think of any- reported elsewhere . thing in particular, not to move and not to fall asleep. Study product and administration Data analysis The probiotic formulation used for this study was Eco- Resting-state (RS) data logic®825 (manufactured by Winclove Probiotics, The Netherlands, and available on the market as OmniBiotic The RS data were pre-processed using the FMRI Expert Stress Repair, Institut Allergosan, Austria). Daily doses were Analysis Tool (FEAT), which is a part of FSL (FMRIB’s supplied as sachets, each containing 3 g freeze-dried pow- Software Library, http://www.fmrib .ox.ac.uk/fsl). For indi- der. The product (7.5 × 10 CFU/g) is composed of nine vidual-level analysis, functional brain volumes were cor- bacterial strains, namely Lactobacillus casei W56, Lacto- rected for slice timing, smoothed with a Gaussian kernel bacillus acidophilus W22, Lactobacillus paracasei W20, of full-width at half-maximum of 5 mm [with high-pass Bifidobacterium lactis W51, Lactobacillus salivarius W24, temporal filtering (cut-off = 100 s)], registered to the indi- Lactococcus lactis W19, Bifidobacterium lactis W52, Lacto- vidual’s structural scan (brain extracted using BET) (brain bacillus plantarum W62 and Bifidobacterium bifidum W23. extraction tool ) and MNI (Montreal Neurological The placebo formulation was also supplied as sachets of 3 g Institute) space using FMRIB’s Linear Image Registra- freeze-dried powder composed of the carrier of probiotic tion Tool (FLIRT) . While running FEAT, the Multi- product: maize starch and maltodextrins. The placebo was variate Exploratory Linear Optimized Decomposition into matched for colour, texture, and smell to the probiotic prod- Independent Components (MELODIC) ICA (Independent uct, but contained no bacteria. At the time of first scanning, Component Analysis) data exploration option was turned participants were provided with the product (probiotic or on (with ‘automatic dimensionality estimation’ option) to placebo) for the 4-week intervention. The participants were gain insight into unexpected artefacts or activation in the instructed to consume the product once a day (dissolving in data. Further, the data sets derived from MELODIC were milk or lukewarm water) preferably in the morning or before denoised using FIX (FMRIB’s ICA-based X-noiseifier) to going to bed. No information was provided to the partici- further remove the noise components . The denoised pants about the different types of intervention (probiotics vs. data were then decomposed into a set of 35 time courses placebo) or the study hypothesis. and associated spatial maps (describing the temporal and spatial characteristics of underlying hidden signals) using MRI acquisition MELODIC toolbox of FSL. Data were again denoised using FIX. Between-group data analysis was carried out using dual All the participants were assessed twice: at the beginning regression technique, which allows for voxel-wise com- (time point 1) and after 4 weeks (time point 2). The MRI data parisons of resting functional connectivity . For this, were acquired using a 3T whole-body MR system (Mag- MELODIC was run on the denoised data (all participants) netom Skyra, Siemens, Germany) with a circularly polarized in concat-ICA mode (multi-session temporal concatenation, 32-channel matrix head coil and 45mT/m actively shielded no. of components = 20). For the randomize step delta (Δ) gradient system. To minimize head movements, participants files were created by contrasting the time point 1 and time lay supine with their heads immobilized using foam pads. point 2 images of each participant. A general linear model For anatomical reference, a high-resolution T1-weighted 3D was then defined to create multi-subject design matrix- gradient echo sequence (MPRAGE: Magnetization Prepared defining groups (ΔPLP, ΔPRP, and ΔCON) and contrast Rapid Acquisition Gradient Echo, 192 sagittal slices, field f iles (ΔCON > ΔPLP, ΔCON < ΔPLP, ΔCON > ΔPRP, of view = 224 mm , TE = 1.89 ms, TR = 1.68 s, slice thick- ΔCON < ΔPRP, ΔPLP > ΔPRP, ΔPLP < ΔPRP). ness = 0.88 mm) image data set was acquired. Furthermore, The selection of spatial maps representing resting- diffusion-weighted data were acquired using echo-planar state networks (Fig. 1a) was carried out by comparing to dual spin echo sequence in 64 directions. Diffusion-weighted those found in the literature [22, 23]. Voxel-wise analyses acquisition parameters were: b-factor = 0 and 1000s/mm , of the group differences were carried out using FSL ran- slice thickness = 2 mm, number of slices = 50, field of domize non-parametric permutation testing with 10,000 view = 240 mm , TR = 6600 ms, and TE = 95 ms. Resting- permutations function per contrast . Threshold-free state brain volumes were acquired using an echo planar cluster enhancement (TFCE) was used to control for 1 3 European Journal of Nutrition Fig. 1 Resting-state results for the between-group (ΔCON, ΔPLP, reduced FC in PRP group was observed in regions of (b) DMN, (c) ΔPRP) comparisons showing, (a) RSNs identified using ICA, which VIN, (d) MFGN; increased FC in PRP group was observed in regions were used for the dual regression analysis; (b–e) randomized out- of (e) SN; results are shown on MNI 0.5 mm standard template. put for group comparisons thresholded at p < 0.05 FWE corrected; CON: no intervention; PLP: placebo; PRP: probiotic multiple comparisons and the significance threshold was set general linear model with 5000 permutations. Results were to p < 0.05 FWE corrected. The Harvard–Oxford cortical corrected for multiple comparisons, using FWE at p < 0.05 atlas was used for anatomical labelling of ICA maps. and TFCE. Diffusion-weighted data Results Voxel-wise statistical analysis was performed using tract- based spatial statistics (TBSS) within FSL (http://www. Probiotic intervention was associated with changes fmr ib .ox.ac.uk/f sl) . The diffusion images were first in the functional connectivity corrected for susceptibility-induced and eddy current distor- tions. Non-brain tissue was removed from the images using Altogether ten independent components (ICs) were identi- BET implemented in FSL. A diffusion tensor model was fied as resting-state networks (RSNs) from group MELODIC fitted at each voxel of the corrected data using DTIFIT  output. These components included salience network (SN), allowing for the estimation of fractional anisotropy (FA) and auditory network (AUN), default mode network (DMN), mean diffusivity (MD). FA data of each participant were left fronto-parietal network (LFPN), right fronto-parietal registered into a common space using nonlinear registration network (RFPN), middle and superior frontal gyrus net- tool FNIRT using a b-spline representation of the registra- work (MFGN), task-positive network (TPN), visual net- tion warp field. Further, a mean FA image was created and work (VIN), left temporo-parietal–frontal network (LTPF) thinned to create a mean FA skeleton, which represents the and cortico-cerebellar network (CCN) (Fig. 1a). These white matter tracts common to the whole group of partici- ICs were compared for differences in FC across the three pants. Each subject’s realigned FA maps were then projected groups: CON, PLP, and PRP. Significant changes in FC were onto these skeletons and subsequently fed into voxel-wise observed in the default mode network (DMN), salience net- between-group statistics. Group differences in voxel-wise work (SN), visual network (VIN) and middle and superior structural connectivity (FA and MD) were tested using a frontal gyrus network (MFGN) when comparing the PRP 1 3 European Journal of Nutrition group to the two other groups (PLP and CON). Specifically, groups. Our results reflect a change in FC in PRP group PRP group showed a decreased FC in frontal pole and fron- and are in line with the findings of Tillisch and colleagues tal medial cortex as compared to CON group within MFGN. , who demonstrated an influence of 4-week probiotic Furthermore, as compared to PLP group, PRP group showed administration on FC associated with midbrain, insula and a decreased FC in VIN in brain regions, namely postcentral sensorimotor cortex brain regions. The present study was gyrus and precuneus and in DMN in frontal pole, SFG and an attempt to further investigate this influence of probiotic paracingulate gyrus regions. We also observed an increase in administration on FC on whole-brain level. FC in SN in PRP group as compared to CON group in brain In this study, the PRP group exhibited increased FC in regions, namely cingulate gyrus and precuneus cortex (see the salience network (SN) as compared to the CON group Fig. 1b–e; Table 1 for details). in the cingulate gyrus and the precuneus cortex. A signifi- cantly decreased FC was observed in the DMN in PRP group Probiotic intervention did not influence as compared to PLP group in frontal pole, superior frontal the structural connectivity gyrus (SFG) and paracingulate gyrus. Furthermore, we also observed a decreased FC in the MFGN in the PRP group Analysis of regional differences in FA and MD using TBSS as compared to the CON group. It is quite evident from the yielded no significant results after FWE correction for mul- vast literature on resting-state fMRI studies that efficient tiple comparisons. Even at a very lean threshold of p < 0.001 behaviour involves the coordinated activity of large-scale uncorrected, we only observed an insignificant increase in networks and these interactions between the networks con- fractional anisotropy within the cingulum and the precuneus. trol and shape our behaviour. According to the triple network However, this difference was only found when comparing model proposed by Menon , the SN plays an important the PRP group to the CON group. role in mediating the function of other networks and this is most evident when a rapid change in behaviour is required. SN dynamically controls the changes of FC between the Discussion DMN, which is related to the self-referential cognition, and central executive network (CEN), which is related to The present study aimed at investigating the influence of a external-oriented tasks. Cingulate cortex is a key structure 4-week multi-strain probiotic administration in whole-brain of SN and together with insula, it occupies an important functional and structural connectivity in healthy volunteers. position in initiating network switching between DMN and Significant changes in FC were observed in PRP group as attentional networks [27, 28]. Changes in FC in this region compared to PLP and CON groups, within the SN, DMN, in PRP group reflect an influence of probiotic administra - VIN and MFGN resting-state networks. No correspond- tion on modulating behaviour and a shift towards efficient ing structural differences were observed between the three attentional control. These changes in FC in cingulate cortex Table 1 Summary of significant Contrasts Network Cluster voxels MNI coordinates (x, y, z) #Mean differences observed in resting- probabil- state networks across three ity groups ΔCON > ΔPRP Middle and superior frontal gyrus network Frontal pole 18 − 2 54 − 16 42.38 Frontal medial cortex 20.88 ΔPRP > ΔCON Salience network Cingulate gyrus 11 − 26 − 50 12 18.1 Precuneus cortex 7.20 ΔPLP > ΔPRP Visual network Postcentral gyrus 12 10 − 42 60 30.88 Precuneus 23.66 ΔPLP > ΔPRP Default mode network Frontal pole 140 − 26 42 28 24.56 Superior frontal gyrus 5.85 Paracingulate gyrus 4.34 CON control, PLP placebo, PRP probiotic p < 0.05 FWE corrected 1 3 European Journal of Nutrition were also reflected as changes in BOLD response in another question whether probiotic intervention might be of use as emotional decision-making task-based fMRI study , an alternative or adjunct strategy to treat depression and reflecting the role of this region in emotional processes. In mood disorders. Neuroimaging techniques, specifically MRI, addition, coupled deactivation of DMN brain regions further stand out as potential candidates for studying the effects of reflects a shift towards efficient behavioural performance in probiotic intervention in humans non-invasively using mul- PRP group. Studies have shown that the failure to deacti- timodalities, ranging from functional MRI, magnetic reso- vate the DMN is associated with attentional deficits . nance spectroscopy to diffusion tensor imaging. Another significant observation in this study was a change The present study and recent findings  have demon- in the FC in MFGN, which plays a key role in orienting of strated that there is a close relationship between the effects spatial attention , decision-making and cognitive con- of probiotic intervention on behavioural and neuroimaging trol . These results indicate an influence of probiotic readouts. However, studying the molecular mechanisms administration not only on emotional processes, but going associated with probiotic intervention in humans is still an beyond extending into higher order cognitive processes. This important question for future investigations in this field. fact is further supported by changes in FC in frontal lobe Deeper understanding of these molecular mechanisms will regions in PRP group as compared to PLP and CON group, definitely influence their clinical use in the future and poten- as the frontal cortex is the key brain region associated with tially lead to new and specific formulations of probiotics, problem-solving, reasoning, attention, decision-making, which might protect against a wide range of mood disorders learning, and creativity . and thus can revolutionize the field of therapeutics. Next to functional changes, probiotics are expected to Acknowledgements Open access funding provided by University of have structural changes as shown by preclinical studies Graz. We would like to thank Institut Allergosan (Graz, Austria) and . However, even when lowering thresholds, we did not Winclove (Amsterdam, The Netherlands) for providing the funding observe any structural connectivity differences associated and study products for the present study. The sponsors did not have with probiotic administration between the three groups. This any influence on study design, analysis or interpretation of results. We thank Andreas Steinwender for technical support. We thank Margit suggests that a 4-week probiotic administration solely influ - List-Schleich for her help throughout the study. Furthermore, we thank ences the behaviour. From our data, this change in behaviour Katharina Gruber and Bhageswar Mohan for their help during the data is reflected as a modification of the interaction of resting- acquisition and analysis. state networks and is not associated with structural changes. Author contributions Conceptualization and experimental design: While we are well aware that the 4-week application period D.B., J.R., and V.S.; data acquisition: D.B. and C.A.; data analysis: may be too short to induce any effect at structural level, a D.B., J.R., and C.C.; project supervision: V.S. and P.H.; drafting of longer period of probiotic intake, for example, 8–12 weeks, the manuscript: D.B., J.R., V.S., C.C., and F.F.; review and editing of was beyond the scope of this study. manuscript: all authors. Several plausible molecular mechanisms associated with gut–brain interactions have been discussed in the literature. Compliance with ethical standards Among these are the reciprocal connections of the vagus nerve as shown in preclinical studies , signalling mol- Conflict of interest The authors have no conflict of interest to declare. ecules such as serotonin precursors, GABA and short-chain Ethical standards This study was conducted in accordance with the fatty acids , or via improving epithelial barrier func- principles of the Declaration of Helsinki and written informed consent tion . Based on these studies, one might expect these was obtained from all participants prior to participation. The local eth- changes in functional connectivity in the present study to be ics committee of the University of Graz, Austria, approved the study. mediated by chemicals, cytokines, hormones released by gut microbiota, which were manipulated with probiotic adminis- Open Access This article is distributed under the terms of the Crea- tive Commons Attribution 4.0 International License (http://creat iveco tration or via pathways mediated by vagus nerve. mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- Irrespective of the exact pathway, our results support the tion, and reproduction in any medium, provided you give appropriate contention that the communication between gut microbiota credit to the original author(s) and the source, provide a link to the and brain is a dynamic process, which can be modulated Creative Commons license, and indicate if changes were made. by a targeted intervention, which leads to changes in the behaviour and brain function. 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