Mice

All CC strains were purchased from the Systems Genetics Core Facility at the University of North Carolina (UNC). Passive avoidance memory test was assessed at 10–11 weeks of age. The study was carried out in strict accordance with the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The Animal Welfare and Research Committee at Lawrence Berkeley National Laboratory approved the animal use protocol. Mice were maintained on PicoLab Rodent Diet 20 (5053), housed in standard micro-isolator cages on corn cobb bedding with enrichment consisting of crinkle cut, naturalistic paper strands. To test the effect of dietary lactate on memory, drinking water of CC042 mice was supplemented with sodium L-lactate (SIGMA; 71718) for 5 weeks starting at 4 weeks of age.

Germ-free mice

Germ-free C57BL/6NTac mice were purchased from Taconic and were maintained within germ-free isolators. The status of our germ-free mice colony was tested every other week and after each opening of the transfer port. A sample was removed from the isolator consisting of fecal samples from multiple cages of animals housed in the isolator, water from the drinking bottles of all cages in the isolator and swabs of the inside of the cages, the floor, and entry port of the isolator. A portion of each sample was streaked onto a sheep blood agar plate and the swab was cultured in thioglycollate medium at 37 °C for 3 days, after which they were maintained at room temperature for 11 more days and observed for growth at 24-h intervals. In addition, every other month, samples were collected and tested for aerobic, anaerobic, and fungal growth at an independent commercial laboratory (IDEXX). All results for our animals were negative for bacterial and/or fungal growth.

Mono-association of GF mice

At 3 weeks of age, GF mice were inoculated with either Lactobacillus reuteri F275, L. plantarum BDGP2 or L. brevis BDGP6 in the different isolators, which was confirmed by PCR and sequencing of their respective 16S rRNA genes. Lactobacillus reuteri F275 was purchased from ATCC (23272). L. plantarum BDGP2 [61] and L. brevis BDGP6 (unpublished; accession number CP024635) were isolated from Drosophila gut samples and verified by genome sequencing. E.coli strain DH10B was purchased from Invitrogen. GF mice were inoculated with 100 μl overnight cultures of Lactobacillus or E.coli.

Passive avoidance memory test

Short-term memory of mice was assessed by passive avoidance using the Panlab passive avoidance box (Panlab: LE870/872). During the acquisition phase, mice were placed in the light compartment. When the mice innately crossed to the dark compartment, they received a mild foot shock (5 s; 0.3 mA). Duration of mice in the light compartment before entering to the dark compartment was recorded. Three days after the acquisition phase mice were again placed in the light compartment and the passive avoidance response was evaluated by measuring the latency to enter the dark compartment.

QTL analysis of memory

Latency of entry into the dark compartment 3 days after the acquisition phase for all CC mice was used for genetic mapping. Genotype data for 134,593 SNPs was obtained from the UNC Systems Genetics Core website (http://csbio.unc.edu/CCstatus/index.py), and filtered for minor allele frequency > 5 out of the 29 CC strains, leaving 76,080 SNPs. At each SNP, latency to enter on day 3 for all CC mice were assigned to their respective alleles. We then used Mann–Whitney U to test the significance of associations between memory and allele classes at each SNP.

Microbiome analyses

Genomic DNA was extracted from the homogenized fecal samples using the PowerSoil DNA Isolation Kit (http://www.mobio.com/) according to the manufacturer’s instructions. PCR amplification of the V4 region of the 16S rRNA gene was performed using the protocol developed by the Earth Microbiome Project (http://press.igsb.anl.gov/earthmicrobiome/empstandard-protocols/16s/) and modern primers [49]. Amplicons were sequenced on an Illumina MiSeq using paired, 250 base-pair reads, according to the manufacturer’s instructions and are available on OSF (https://osf.io/jbt5g/). The Hundo amplicon processing protocol was used to process 16S and ITS amplicons [50]. In brief, sequences were trimmed and filtered of adapters and contaminants using BBDuk2 of the BBTools package. VSEARCH [51] was used to merge, filter to an expected error rate of 1, dereplicate, and remove singletons before preclustering reads for de novo and reference-based chimera checking. Reads were clustered into OTUs at 97% similarity and an OTU table in the BIOM format [52] was constructed by mapping filtered reads back to these clusters. BLAST+ [53] is used to align OTU sequences to the database curated by CREST [54] (SILVA v128 for 16S) and taxonomy was assigned based on the CREST LCA method. Graphing was performed in R, making use of the Phyloseq package [55].

L. plantarum BDGP2 [56] and L. brevis BDGP6 (unpublished) were sequenced using the PacBio long read strategy. After assembly the genomes were annotated for predicted protein-coding open reading frames using Rapid Annotation of microbial genomes using Subsystems Technology tool [57] and the GenBank annotation pipeline. The RAST and GenBank produced gene models for L. plantarum, L. brevis, and L. reuteri predict: six L-lactate dehydrogenase (EC 1.1.1.27) encoding genes, one D-lactate dehydrogenase (EC 1.1.1.28) encoding gene and one Glutamate decarboxylase (EC 4.1.1.15) encoding gene; two L-lactate dehydrogenase encoding genes, two D-lactate dehydrogenase encoding genes, and two Glutamate decarboxylase encoding genes; and five L-lactate dehydrogenase encoding genes, one D-lactate dehydrogenase encoding gene, and one Glutamate decarboxylase encoding gene, respectively.

Metabolome analyses

Metabolites were extracted from mouse fecal, plasma, and whole brain homogenate samples. Fecal samples were extracted with methanol as reported previously [21], and plasma and whole brain homogenates were extracted using the MLPEx method [58]. Briefly, 50 μL of plasma was extracted with 200 μL of chloroform/methanol (2:1, v/v), and extracted molecules in both aqueous and organic layers were combined and dried in vacuo. Whole brains were weighed and extracted using MPLEx, but the volume of solvent was added proportionally to the amount of tissue. All the extracts were stored at − 80 °C, and they were analyzed by gas chromatography coupled to mass spectrometry as reported previously [21]. All the raw MS data files are available at the OSF public data depository (https://osf.io/jbt5g/ ).

Immunostaining of GABA in mouse hippocampus

Mice brains were fixed in 4% paraformaldehyde and embedded in paraffin. Two male and two female mice were analyzed for each treatment (n = 4). Coronal sections were generated and placed on class slides. The sections were rehydrated by first immersing the slides in xylene (mixed isomers) for 20 min. The slides where then incubated in 100% ethanol for 20 min, followed by incubations in ethanol at decreasing concentrations (100%, 95%, 70%, and 50%), for 5 min each. The slides where then rinsed using deionized water. Heat-induced epitope retrieval was done by 5 min incubation of the slides in 10 mM Tris, 1 mM EDTA heated to 95 °C, followed by rinsing in water. Immunostaining of the hippocampus proper, including the Cornu Ammonis (CA) fields and the dentate gyrus (DG), was done using anti-GABA antibody produced in rabbit (Sigma A2052) and applied to the sections at 1:200 dilution, followed by a fluorescent (Alexa488) Goat anti-rabbit IgG H+L (ThermoFisher A11008) applied at 1:400 dilution. Antibody dilutions were made in PBS containing 0.25% Triton X-100 and 5% goat serum. The sections were then stained with DAPI (1 μg/ml in PBS for 10 min) and washed with PBS. Vectashield drops were placed on the sections and glass coverslips were placed on top of them and sealed using nail polish. Fluorescence imaging was done using inverted confocal fluorescence microscope (Zeiss). Initially, 10 × objective and tiling over the whole section was used, followed by imaging the hippocampus, including the CA fields and DG, using 40 × water immersion objective to achieve the magnification needed for identifying and counting cell bodies (Fig. S4). GABA expression was quantified by calculating the number of cell bodies showing GABA expression (green) as the percent of all cell bodies, detected by the DAPI-stained nuclei (blue). Significant differences between germ-free and Lactobacillus-treated mice were determined using t tests.

Glutamate decarboxylase (GAD 67 ) gene expression using fliFISH in mouse brain sections

Fluctuation localization imaging-based FISH (fliFISH) was developed and performed as described in Cui et al. [26]. In short, fliFISH utilizes photoswitchable dyes and super-resolution localization microscopy to accurately count and localize mRNA molecules with a small number of oligonucleotide probes. The single-molecule on-time fraction (F single ) for Alexa647 was found to be 0.2% under 0.5 kW/cm2 excitation. When using 20 probes (n), each tagged with one dye molecule, to target a transcript, the ensemble on-time fraction (F ensemble = 1−(1−F single )n) of 4% should be detected from a successfully hybridized RNA transcript position. In contrast, stray or nonspecifically bound probes would generate roughly a single-molecule on-time fraction values, while strong autofluorescence and aggregated probes would generate higher ensemble on-time fraction values. In addition, fliFISH enables to resolve multiple transcripts in a diffraction-limited area as the centroid of each blinking event is registered with 15–25 nm resolution in the super-resolution reconstructed image.

The 24 primary FISH probes used in this study were designed to have two segments: a GAD 67 transcript targeting domain, and a terminal overhang. The targeting domain was generally 20 nucleotide-long, with 45–55% CG content, no self-repeats and inner loop-stem structures. The secondary probe was labeled with two Alexa647 dye molecule, one in each end, and was designed to hybridize with the overhang sequence. All the probe sequences were subjected to BLAST searching to avoid nonspecific targeting and purchased from Integrated DNA Technologies.

The hybridization procedure followed previously established protocols [59, 60]. Primary probes were mixed and hybridized with the secondary probe to form fluorescent complexes before introducing to the tissue sections following a published protocol [60]. One microliter from each of the 24 oligonucleotide probes 100 μM solutions was mixed together and water was added to a total of 120 μl. Six microliters were then taken out and mixed with 1.5 μl 100 μM secondary probe, 2 μl 10 × NEB3 buffer (containing 1 M NaCl, 0.5 M Tris-HCl, 0.1 M MgCl 2 ), and 10.5 μl water. The mixture was heated to 85 °C and gradually cooled down to room temperature. The microscope slides with paraffin-embedded mouse brain sections were dipped in 100% xylenes for 10 min, followed by100%, 95%, and 70% ethanol for 10 min each. The slides were then left in 70% ethanol overnight at 4 °C and washed with PBS before hybridization. Hybridization was done by first washing the slides with “wash buffer” (containing 2 × SSC and 10% formamide). 200 μl “hybridization buffer” (containing 10% dextran sulfate, 2 × SSC and 10% formamide) were mixed with 3.3 μl of the FISH probe solution. Drops of this mixture were placed on the tissue sections and the slides were kept overnight at 46 °C. The slides were then washed twice by incubating in “wash buffer” for 20 min at 46 °C, followed by a wash with 2 × SSC buffer. The slides were then incubated in 1 μg/ml DAPI solution for 10 min and were washed using PBS.

The fliFISH images were taken using a home-built, Zeiss Axioobserver based single-molecule imaging system. A 100 × oil immersion objective lens (NA 1.4, Plan Apo) and an EMCCD camera (Andor iXon Ultra 897) were used. DIC and DAPI fluorescence images were taken in addition to fluorescent Alexa 647 single molecules images. Over 10,000 image frames were taken (at 25 Hz frame rate) for post-processing. Gaussian musk fitting algorithm was applied to find the central location of each emission event and nearby events were grouped together (assigned to the same transcript) using the DBSCAN algorithm. For the grouped emission events, the center of mass was determined to represent the possible existence of a transcript. All image processing was performed with MATLAB and C scripts that are available upon request.

HuMiX-based analyses

HuMiX-based co-cultures involving L. reuteri and the human epithelial cell line Caco-2 were performed as previously described [28]. Caco-2 were allowed to fully differentiate for 7 days at which point the co-cultures with L. reuteri were established. Eluates were collected from the microbial and perfusion chambers just before inoculation as well as after 6 and 24 h of co-culture and immediately flash-frozen for subsequent metabolomic analyses.

Statistics

To evaluate the association between the memory latency to enter time and the microbiome features, we employed Cox Proportional-Hazards Regression analysis, where both forward and backward feature selection strategies were used to optimize the subset of microbes that significantly impact memory. During forward selection, each individual microbe at the OTU level was evaluated through the Cox Proportional-Hazards Regression analysis, and only those with significant impact on memory (round (P value, 2) ≤ 0.05, where round (X,N) rounds X to its nearest N decimal digits) were selected (6 OTUs: f__Anaeroplasmataceae, f__Bacteroidaceae, f__Bacteroidales_S24-7_group, f__Lactobacillaceae, f__Deferribacteraceae, f__Clostridiaceae_1). During backward selection, the combined subset of features (multivariates) were further evaluated through the Cox Proportional-Hazards Regression analysis, where only the features with significant impact (round (P value, 2) ≤_0.05) were retained. Different from forward selection, the backward selection was performed in an iterative manner until all the features in the refined subset were significantly associated with memory. In our study, the backward selection with 2 iterations led to the refined final subset of four microbiome features (i.e., f__Bacteroidaceae, f__Lactobacillaceae, f__Deferribacteraceae, and f__Clostridiaceae_1), where f__Bacteroidaceae and f__Clostridiaceae_1 are “prognostic” unfavorable (hazard ratio >_1), and f__Lactobacillaceae and f__Deferribacteraceae are “prognostic” favorable (hazard ratio <_1).

Differences in memory potential between germ-free and Lactobacillus inoculated mice or between lactate treated and control mice was assessed by non-parametric test (Mann–Whitney test). Difference in metabolite abundance and GABA expression between germ-free and Lactobacillus inoculated mice was assessed by Student’s t test. Significance was determined at P_<_0.05. Multivariate analysis of variance (MANOVA) was used to examine for statistical differences in fecal metabolite profiles across germ-free and Lactobacillus-inoculated mice.