NEW PROBIOTIC AND NEW BIOMARKER
20170258858 · 2017-09-14
Inventors
- Frederik Jan Troost (Maastricht, NL)
- Zlatan Mujagic (Stein, NL)
- Maria Margaretha Faas (Groningen, NL)
- Paulus De Vos (Slochteren, NL)
Cpc classification
A23V2002/00
HUMAN NECESSITIES
A23L33/135
HUMAN NECESSITIES
International classification
A23L33/135
HUMAN NECESSITIES
G01N33/50
PHYSICS
Abstract
The present invention relates to a new probiotic with immune modulating properties and to a new biomarker.
Claims
1. A probiotic formulation comprising at least one food-grade substance and at least one probiotic bacterial strain comprising at least one polynucleotide that has at least 85% sequence identity with: the genome of Lactobacilli plantarum TIFN 101, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 1-SEQ ID NO: 174, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 176-SEQ ID NO: 256, and/or a polynucleotide encoding a polypeptide with a sequence selected from the group consisting of SEQ ID NO: 260-340.
2. A probiotic formulation according to claim 1, comprising at least one further probiotic bacterial strain.
3. A probiotic formulation according to claim 1, wherein the concentration of probiotic bacterial strains ranges from about 10 to about 50 weight percent and/or about 1 E+6 to about 1 E+12 colony forming units/ml of formulation.
4. A probiotic formulation according to claim 1 that is formed as part of a tablet or that is contained within a capsule.
5. A food product, a formulation for food enrichment, a food supplement, a nutraceutical formulation or a pharmaceutical formulation comprising a probiotic formulation according to claim 1.
6. A container with a liquid volume between 0.5 and 50 ml comprising a probiotic formulation according to claim 1.
7. A container with a liquid volume between 0.5 and 1000 ml comprising a food product, a formulation for food enrichment, a food supplement, a nutraceutical formulation or a pharmaceutical formulation according to claim 5.
8. A probiotic formulation according to claim 1 or a food product, a formulation for food enrichment, a food supplement, a nutraceutical formulation, a pharmaceutical formulation comprising said probiotic formulation, or a probiotic bacterial strain, wherein the probiotic bacterial strain is of a species selected from the group consisting of Lactobacilli plantarum, L. casei, L. reuteri, L. fermentum, L. acidophilus, L. crispatus, L. gasseri, L. johnsonii, L. paracasei, L. murinus, L. jensenii, L. salivarius, L. minutis, L. brevis, L. gallinarum, L. amylovorus, Lactococcus lactis, Streptococcus thermophilus, Leuconostoc mesenteroid.es, Lc. lactis, Pediococcus damnosus, P. acidilactici, P. parvulus, Bifidobacterium bifidum, B. longum, B. infantis, B. breve, B. adolescente, B. animalis, B. gallinarum, B. magnum, and B. thermophilum, optionally a Lactobacilli plantarum, optionally a Lactobacilli plantarum from the group consisting of Lactobacilli plantarum JDM1, ST-III, F9UP33, EITR17, D7V971 (ATCC14917) and C6VQ24, optionally Lactobacilli plantarum WCFS1 and optionally Lactobacillus plantarum TIFN 101, deposited under number CBS 138100.
9. A probiotic bacterial strain comprising at least one polynucleotide that has at least 85% sequence identity with: the genome of Lactobacilli plantarum TIFN 101, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 1-SEQ ID NO: 174, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 176-SEQ ID NO: 256, and/or a polynucleotide encoding a polypeptide with a sequence selected from the group consisting of SEQ ID NO: 260-340, and/or a probiotic formulation according to claim 1 for use as a medicament, optionally in the treatment or prevention of intestinal inflammation.
10. A probiotic bacterial strain comprising at least one polynucleotide that has at least 85% sequence identity with: the genome of Lactobacilli plantarum TIFN 101, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 1-SEQ ID NO: 174, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 176-SEQ ID NO: 256, and/or a polynucleotide encoding a polypeptide with a sequence selected from the group consisting of SEQ ID NO: 260-340, and/or a probiotic formulation according to claim 1 for use as a medicament comprising administration of an effective amount of the probiotic bacterial strain and/or of the probiotic formulation for modulating the immune system.
11. A probiotic bacterial strain for use according to claim 10, wherein modulation of the immune system comprises maintenance and/or reactivation of an immune response raised by a previous immunization and/or enhancing memory T-cells generated previously by immunization.
12. A method of treatment of a subject suffering from intestinal inflammation, or a method of prevention of intestinal inflammation comprising administration to said subject an effective amount of a probiotic bacterial strain comprising at least one polynucleotide that has at least 85% sequence identity with: the genome of Lactobacilli plantarum TIFN 101, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 1-SEQ ID NO: 174, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 176-SEQ ID NO: 256, and/or a polynucleotide encoding a polypeptide with a sequence selected from the group consisting of SEQ ID NO: 260-340, and/or an effective amount of a probiotic formulation according to claim 1.
13. A method of modulating the immune system of a subject suffering from intestinal inflammation, comprising administration to said subject an effective amount of a probiotic bacterial strain comprising at least one polynucleotide that has at least 85% sequence identity with: the genome of Lactobacilli plantarum TIFN 101, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 1-SEQ ID NO: 174, a polynucleotide sequence selected from the group consisting of SEQ ID NO: 176-SEQ ID NO: 256, and/or a polynucleotide encoding a polypeptide with a sequence selected from the group consisting of SEQ ID NO: 256-340, and/or an effective amount a probiotic formulation according to claim 1.
14. A method of modulating the immune system according to claim 13, wherein modulation of the immune system comprises maintenance and/or reactivation of an immune response raised by a previous immunization and/or enhancing memory T-cells generated previously by immunization.
15. A probiotic strain for use according to claim 9, wherein the effective amount comprises about 1×10 E+6 to about 1×10 E+12 colony forming units.
16. A method for the detection of a response to an agent comprising: a. stimulating PBMC from a sample of a subject with at least one antigen, b. identifying a sub-population of PBMC, c. comparing the data from (b) to data of a, optionally otherwise identically assayed, reference sample, of optionally the same subject, which reference sample has not been stimulated with at least one antigen of (a), wherein a difference in data identified in (c) is a measure for a response to the agent.
17. A method according to claim 16, wherein the response is an immune response, optionally modulation of an existing immune response, optionally an increase of an existing immune response.
18. A method according to claim 16, wherein the agent is a food product, optionally a probiotic, optionally the agent or part thereof comprises a membrane of a probiotic.
19. A method according to claim 16, wherein the sample comprises a bodily fluid; optionally the sample is a blood sample.
20. A method according to claim 16, wherein the at least one antigen of 1(a) is selected from the group consisting of a general T cell stimulator optionally a superantigen, a Protein Kinase A (PKA) stimulator optionally a lectin, a recall antigen such as tetanus toxin, a Hepatitis B antigen or an Influenza antigen, and the agent or a part thereof.
21. A method according to claim 16, wherein the at least one antigen of 1(a) comprises at least: a. a recall antigen optionally tetanus toxin, a Hepatitis B antigen or an Influenza antigen, and b. the agent or a part thereof.
22. A method according to claim 16, wherein the sub-population of PBMC is a population selected from the group consisting of CD3+/CD4+ (Thelper cells), CD3+/CD4+/CD45RO− (naïve Thelper cells), CD3+/CD4+/Foxp3+ cells (Foxp3+ Thelper cells), CD3+/CD4+/CD45RO+ (memory Thelper cells), CD3+/CD4+/CD45RO+/CD69+ (activated memory Thelper cells), CD3+/CD8+/CD45RO− (naïve CD8+ cells), CD3+/CD8+/CD45RO+ (CD8+ memory T cells), CD3+/CD8+/CD45RO+/CD69+ (activated CD8+ memory T cells), CD3+/CD4+/CD45RO+/CCR7+/CD62L+ cells (central memory Thelper cells), CD3+/CD4+/CD45RO+/CCR7−/CD62L− cells (effecter memory Thelper cells).
23. A method according to claim 16, wherein the identification of the sub-population of PBMC comprises flow cytometry analysis; optionally the identification of the sub-population of PBMC comprises quantification.
24. A sub-population of PBMC as a biomarker for efficacy testing of immune modulating agents.
25. A sub-population according to claim 24, wherein the immune modulating agent is a food product, optionally a probiotic.
26. A sub-population according to claim 24, wherein the sub-population of PBMC is a population selected from the group consisting of CD3+/CD4+ (Thelper cells), CD3+/CD4+/CD45RO− (naïve Thelper cells), CD3+/CD4+/Foxp3+ cells (Foxp3+ Thelper cells), CD3+/CD4+/CD45RO+ (memory Thelper cells), CD3+/CD4+/CD45RO+/CD69+ (activated memory Thelper cells), CD3+/CD8+/CD45RO− (naïve CD8+ cells), CD3+/CD8+/CD45RO+ (CD8+ memory T cells), CD3+/CD8+/CD45RO+/CD69+ (activated CD8+ memory T cells), CD3+/CD4+/CD45RO+/CCR7+/CD62L+ cells (central memory Thelper cells), CD3+/CD4+/CD45RO+/CCR7−/CD62L− cells (effecter memory Thelper cells).
Description
FIGURE LEGENDS
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[0086]
[0087]
[0088]
[0089]
EXAMPLES
[0090] The present invention is further described by the following examples which should not be construed as limiting the scope of the invention.
[0091] Unless stated otherwise, the practice of the invention will employ standard conventional methods of molecular biology, virology, microbiology or biochemistry.
[0092] Such techniques are described in Sambrook et al. (1989) Molecular Cloning, A Laboratory Manual (2.sup.nd edition), Cold Spring Harbor Laboratory, Cold Spring Harbor Laboratory Press; in Sambrook and Russell (2001) Molecular Cloning: A Laboratory Manual, Third Edition, Cold Spring Harbor Laboratory Press, NY; in Volumes 1 and 2 of Ausubel et al. (1994) Current Protocols in Molecular Biology, Current Protocols, USA; and in Volumes I and II of Brown (1998) Molecular Biology LabFax, Second Edition, Academic Press (UK); Oligonucleotide Synthesis (N. Gait editor); Nucleic Acid Hybridization (Hames and Higgins, eds.).
Example 1
Differential Human Mucosal Transcriptomic and Immune Responses to Three Probiotic Strains; Insight in How Probiotics Contribute to Immunity in Healthy Individuals
[0093] Materials and Methods
[0094] Bacterial Strains and Growth Conditions
[0095] Lactobacilli plantarum WCFS1 (Kleerebezem et al., 2003), Lactobacilli plantarum CIP104448 (CIP48), and Lactobacilli plantarum TIFN 101 were cultured at 37° C. in Man, Rogosa and Sharpe (MRS) medium (Merck). To obtain stationary-phase cultures, bacteria were cultured overnight. Maltodextrin and glucose were added to a final concentration of 20% and 2% (wt/vol), respectively, to obtain bacterial preparations (WCFS1, 2.6×10.sup.9 CFU; CIP48, 2.4×10.sup.9 CFU; TIFN 101, 5.6×10.sup.9 CFU); placebo controls only contained the two sugars. Bacteria and placebo materials were prepared such that they contained similar final sugar concentrations. Detailed protocols for culturing, harvesting, freeze-drying, storing, and viable count determining of Lactobacillus species can be found in Smelt et al. 2012.
[0096] Volunteers and Interventions
[0097] This study was approved by the University Hospital Maastricht Ethical Committee and was conducted in accordance with the principles of the Declaration of Helsinki. All subjects gave their written informed consent before their inclusion in the study. Ten healthy volunteers, 7 female and 3 male (26.3±10.1 years, BMI of 21.8±2.40 kg/m.sup.2), without a history of gastrointestinal symptoms and free of any form of medication, were tested on four separate occasions (three bacterial interventions and one placebo control, randomly chosen) in a randomized placebo-controlled cross-over study. The volunteers consumed habitual diet during the study period and were asked to fill in a gastrointestinal symptoms diary. Three days before the intervention a blood sample was taken to obtain baseline values. The night before the start of the supplements intake period the volunteers ingested 75 mg of indomethacin. At the starting day the volunteers ingested another dosage of 50 mg indomethacin conform previously established protocol to establish mild gastrointestinal stress (Troost et al., 2003). Subsequently, the volunteers consumed the probiotic or placebo supplements for a period of 7 days during lunch and during dinner; L. plantarum WCFS1 (2.6.sup.10 colony forming units (cfu) per shot), L. plantarum CIP104448 (2.4.sup.10 cfu/shot), L. plantarum TIFN 101 (5.9.sup.10 cfu/shot) or placebo. Neither the volunteers nor the researchers knew which subject received the L. plantarum strains or the placebo (double-blinded study); the vials containing bacteria or placebo control were non-transparent. On the 7.sup.th day, tissue samples were obtained from the horizontal part of the duodenum by standard flexible gastroduodenoscopy at approximately 15 cm distal to the pylorus. The duodenal mucosa was chosen as this is the first intestinal segment coming in contact with the bacteria, minimizing the adaptive changes microbes might go through during passage of the intestinal tract. Also, the duodenum is readily accessible for mucosal tissue sampling. Finally, the duodenum contains the lowest endogenous microbiota colonization level, ensuring that the measured responses are as specific as can be achieved. The interventions were performed with an interval of 4 weeks to allow a wash-out period and to allow healing of the biopsy-sampling region.
[0098] Cell Staining
[0099] The various dilutions of the antibodies and other reagents used for cell staining are listed in Table 1.
[0100] Blood was collected in EDTA containing tubes and processed for FACS analysis. The following antibodies were used for staining of the T cell sub-populations: Pacific Blue-conjugated anti-CD3 (clone UCHT1; BD Pharmingen), PerCP conjugated anti-CD8 (clone SK1, Biolegend), APC-Cy7-conjugated anti-CD69 (clone FN50, BD Pharmingen), APC-conjugated anti-FoxP3 (clone 206D, eBioscience), biotin-conjugated anti-CD45RO (UCHL1, Biolegend) with Pacific orange conjugated streptavidin (Invitrogen). Isotype controls were purchased from the same company as the antibodies and used in the same dilution as the antibody.
[0101] For intracellular cytokine staining of T cells we used: PE-Cy7 conjugated anti-IL4 (MP4-25D2, Biolegend), Alexa488-conjugated anti-IL-17A (clone eBio64DEC17; eBioscience), PE-conjugated anti-IL-21 (clone eBio3A3-N2; eBioscience), Alexa700-conjugated anti-IFNγ (clone B27; BD Pharmingen),
[0102] For staining of the NK cell populations we used: APC-conjugated anti-CD56 (clone MEM-188, Ebioscience), EFluor450-conjugated anti-CD16 (clone CB16, eBioscience), PE-conjugated anti-CD335 (clone 9E2, Biolegend), PE-Cy7-conjugated anti-CD161 (clone HP-3G10, eBioscience) T-cell polarization was studied after three types of stimulations of the T-cells. It was done by (i) aspecific stimulation with PMA/Ca.sup.2+ or superantigen (SEB) to study whether the total responsiveness was influenced by probiotic treatment, by (ii) stimulation with cell extracts of the specific L. plantarum strains in order to investigate whether specific immune responses against the probiotic was stimulated, and (iii) by stimulating with an antigen to which all volunteers were vaccinated, tetanus toxoid (TT), to study possible stimulation of specific memory responses.
[0103] After blood sampling, 200 μl of blood was diluted with 200 μl of RPMI1640 supplemented with 10% fetal calf serum (FCS) and incubated with either PMA (Phorbol myristate acetage; 80 nM Sigma-Aldrich, Steinheim, Germany) and Ca2+ (4 μM) (4 hr), Staphylococcus aureus enterotoxin B SEB (5 μg/mL Sigma, Deisenhofen, Germany) (24 hr), TT (tetanus toxoid; 1.5 Lf/mL) (24 hr) or bacterial lysates (30 μg/mL) (24 hr). Stimulation with bacterial lysates was according to the administered strain and performed one week after treatment. After the treatment week with L. plantarum WCFS1, samples were stimulated with cell extracts of L. plantarum WCFS1; after the treatment week with L. plantarum CIP104448, samples were stimulated with cell extracts of L. plantarum CIP104448; after the treatment week with L. plantarum TIFN 101, samples were stimulated with cell extracts of L. plantarum TIFN 101. These cell extracts were made by repeated freeze-thawing of the probiotics.
[0104] After stimulation, red blood cells were lysed with ammonium chloride. After washing (PBS with 2% FCS), cells were incubated with different antibody cocktails.
[0105] Staining for T cells and T cell subsets: Cells were incubated with an antibody cocktail consisting of anti-CD3, anti-CD8 and anti-CD45RO for 30 minutes in the dark on ice.
[0106] After washing with washing buffer, cells were incubated with streptavidine Pacific Orange (1:100 Invitrogen) for 15 minutes on ice. After washing and spinning down, pelleted cells were resuspended in Fixation/Permeabilization solution (eBioscience, 0.1% saponin and 0.009% sodium azide) for 45 minutes on ice. After washing in Perm solution (eBioscience), cells were incubated in mouse serum for 15 minutes to prevent non-specific binding, followed by incubation with the cytokine antibody mix (anti-IL-4, anti-IFNγ, anti-IL-17 and anti-IL21) or an isotype cytokine mix for 30 minutes on ice.
[0107] After washing with Permeabilization solution (3 times) cells were resuspended in wash-buffer and measured by flow cytometry within 24 hrs.
[0108] Staining for NK cells: Cells were incubated with an antibody cocktail consisting of anti-CD3, anti-CD16, anti-CD56, anti-CD335 and anti-CD161 (NK cell staining), or with isotype control cocktail for NK cells consisting of anti-CD3, anti-CD16, anti-CD56 and isotype controls for anti-CD335 and CD161 for 30 minutes in the dark on ice. After washing with washing buffer, cells were fixed in FACS lysing solution (BD Biosciences, phosphate buffered saline (PBS) containing 2% heat-inactivated fetal calf serum (FCS)) for 30 minutes on ice. After washing, cells were suspended in washing buffer and measured by flow cytometry on a Becton and Dickinson LSRII within 24 hrs; at least 500,000 events were recorded per sample.
TABLE-US-00001 TABLE 1 Antibody dilutions # Reactivity Isotype Label Dilution Company 1A CD3 mIgG1 Pac Blue 1:25 BD 558117 (UCTH1) 2 CD8 mIgG1 (SK1) PerCP 1:25 BD 345774 4 IL17A mIgG1 Alexa488 1:25 eBio 53- (eBio64DEC17) 7179 5 IL21 mIgG1 PE 1:25 eBio 12- (eBio3A3-N2) 7219 6 IFNg mIgG1 (B27) Alexa700 1:100 BD 557995 7 CD69 mIgG1 (FN50) APC-Cy7 1:25 BD 557756 8 FoxP3 mIgG1 (206D) APC 1:25 eBio 9017- 4776-220 9 CD45R0 mIgG2a Biotin 1:25 BioLegend (UCHL1) 304220 10 Streptavidin Pac Orange 1:100 Invitrogen 11 CD3 mIgG1 PerCP 1:30 BioLegend (UCHT1) 300428 12 CD16 mIgG1 (CB16) eFluor450 1:10 eBio 48- 0168-42 13 CD56 mIgG2a APC 1:25 eBio 17- (MEM-188) 0569-42 14 CD335 mIgG1 (9E2) PE 1:7.5 BioLegend 331908 15 CD161 mIgG1 PE-Cy7 1:20 eBio 25- (HP-3G10) 1619-42 17 — Mouse IgG1 PE 1:62.5 BioLegend 400112 18 — Mouse IgG1 PE-Cy7 1:20 eBio 25- 4714 20 IL4 rIgG1 PE-Cy7 1:25 BioLegend (MP4-25D2) 500824
[0109] RNA Isolation and Microarray
[0110] Total RNA was isolated from the duodenal biopsies by using Trizol reagent (1 ml) (Invitrogen, Breda, NL). Thereafter RNA was purified using the Qiagen RNeasy Micro kit (Qiagen, Venlo, NL). RNA was quantified on a NanoDrop ND-1000 spectrophotometer (Isogen Life Science, De Meer, The Netherlands) RNA quality was checked using an Agilent 2100 bioanalyzer (Agilent Technologies, Amsterdam, NL). RNA was judged suitable for array hybridization only if samples exhibited intact bands corresponding to 18S and 28S ribosomal subunits and displayed no chromosomal peaks or RNA degradation products.
[0111] Total RNA (100 ng) was used for whole transcript cDNA synthesis by using the Ambion WT expression kit (Life Technologies, Bleiswijk, The Netherlands) and subsequently labelled by using the Affymetrix GeneChip WT Terminal Labelling Kit (Affymetrix, Santa Clara Calif.). Samples were hybridized to human whole genome Affymetrix GeneChip Human Gene 1.1 ST arrays, washed, stained, and scanned on an Affymetrix GeneTitan instrument. Details on array handling can be found in the Affymetrix GeneTitan Instrument User Guide for Expression Array Plates (P/N 702933 Rev.2).
[0112] Microarray Data Analysis
[0113] Microarray analysis was performed by applying MADMAX for statistical analysis (Lin et al 2011, J Integr Bioinform, PMID 21778530). Quality control was performed. All arrays met the criteria. The probes on the Human Gene 1.1 ST arrays were redefined according to Dai et al (2005, Nucleic Acids Res PMID 16284200) based on the NCBI Entrez database (CDF version 15.1). In this way the Human Gene 1.1 ST array targets 19,682 unique genes. Normalized expression values were obtained from the raw intensity values by using the robust multiarray analysis preprocessing algorithm available in the library AffyPLM using default setting (Irizarry et al, Biostatistics, 2003, PMID 12925520). Microarray data were filtered, and probe sets with at least 5 probes and expression values higher than 20 on at least 5 arrays, and a interquartile range >0.2 (log 2 scale) across all samples were and selected for further statistical analysis. In addition, an Inter Quartile Range (IQR) cut-off of 0.2 was used to filter out genes that showed no variation between the conditions. Differentially expressed genes were identified by using linear models, applying moderated t-statistics that implemented empirical Bayes regularization of standard errors in the library limma (Smyth et al., 2004). To adjust for both the degree of independence of variances relative to the degree of identity and relation between variance and signal intensity, the moderated t-statistic was extended by a Bayesian hierarchical model to define an intensity-based moderated t-statistic (Sartor et al, 2006, BMC Bioinformatics PMID 17177995). Genes were defined as significantly changed when the P value was <0.05 for pairwise comparisons.
[0114] Pathway Analysis
[0115] Geneset enrichment analysis (GSEA; at world wide web: broad.mit.edu/gsea/) was performed using MADMAX and genesets with a false discovery rate (FDR) <0.2 were considered significantly enriched. GSEA takes into account the broader context in which gene products function, namely in physically interacting networks such as biochemical, metabolic, or signal transduction routes, and has the advantage that it is unbiased, because no gene selection step is used (Subramanian et al., 2005. Possible transcription factors playing a role in the activation and inhibition of genes were identified using Upstream Regulator Analysis in Ingenuity Pathway Analysis (IPA; Ingenuity Systems, Redwood City, Calif.).
[0116] Genome Sequencing and Annotation
[0117] The L. plantarum strain CIP104448 was obtained from the NIZO culture collection (Meijerink et al., 2010). For DNA preparation, 2 ml of overnight culture was pelleted, washed and resuspended in TES buffer (N-[tris(hydroxymethyl)methyl]-2-aminoethanesulfonicacid). Cells were lysed with lysozyme (360 mg/ml) and mutanolysin (140 U/ml) by incubation for 2 h at 37° C. Subsequently 300 μl water was added and 80 μl of 20% SDS solution. The DNA extraction was done using phenol/chloroform (3×). The DNA was precipitated with isopropanol and washed with 70% ethanol. Samples were treated with 100 μg/ml RNAse (Sigma) during 1 hour at 37° C. DNA paired-end libraries with barcoding were made and sequenced using Illumina technology (Baseclear Leiden, NL). The contig sequences were submitted to the RAST automatic annotation server, which provided ORF calling and automatic annotation. The annotated contigs of CIP48 and TIFN 101 were ordered by comparing them to the circular template genome of L. plantarum WCFS1, and comparing them to each other. Contigs/genes which did not match to the WCFS1 genome were annotated in more detail using BLASTP (http://blast.ncbi.nlm.nih.gov/) and InterProscan (http://www.ebi.ac.uk/interpro/). Ortholog groups (OGs) in the 3 genomes were determined using OrthoMCL (www.orthomcl.org/).
[0118] Statistics
[0119] Flow cytometry data results are expressed as the mean±standard error of the mean (SEM). Normal distribution of the data sets was confirmed by the Kolmogorov-Smirnov test. The two-sided Students t-test was used to determine changes in immune cell populations after probiotic treatment. Gene expression data are depicted as the medium (range). The two-sided Mann Whitney U-test was used to determine changes in expression profiles after probiotic treatment in vivo. P-values<0.05 (*) were considered statistically significant.
[0120] Results
[0121] Human Trial
[0122] None of the volunteers experienced any discomfort during or after the 7 days consumption period. Before the start of the trial (day 0), and at day 7 blood samples were taken to study the effect of probiotic consumption on T-cell polarization. Also at day 7 biopsies were taken by standard flexible gastroduodenoscopy, and total RNA was isolated and hybridized to whole-genome expression microarrays. Quality control of the hybridizations and primary data analysis were performed according to strict criteria to ensure that the array data were of the highest possible quality.
[0123] Differential Peripheral Responses Induced by L. plantarum
[0124] L. plantarum WCFS1, L. plantarum CIP104448, and L. plantarum TIFN 101 were selected from a series of 42 individual L. plantarum strains which were assayed for the levels of IL-10 and IL12 they induced from dendritic cells (Meijerink et al., 2010). L. plantarum WCFS1 is characterized by a relative low IL10/IL12 ratio and classified as proinflammatory, L. plantarum CIP104448, does not change the IL10/IL12 ratio when compared to medium control and is therefore classified as neutral and L. plantarum TIFN 101 induces a relative high IL10/IL12 ratio and is therefore classified as anti-inflammatory (Meijerink et al., 2010).
[0125] Cell Frequencies After 6 Days of Treatment with L. plantarum
[0126] We did not observe differences in the frequencies of the total percentage of CD3+ cells, the CD3+/CD4+ cells (naïve or memory), or the activated memory CD3−/CD4+ cells after treatment with either L. plantarum strain. However, the percentage of CD4+/Foxp3 positive cells was significantly decreased following placebo and CIP 48 treatment, but not after WCFS1 and TIFN 101 treatment (
[0127] Treatment did not affect total NK cell numbers or NKT numbers. There was also no change in the percentages of the NK cell subtypes (i.e. CD56hi and CD56dim), while the expression of CD161 (KLRB1), mediating cytotoxicity (Jacobs et al., 2001; Tarazona et al., 2002), was also not affected by the L. plantarum treatments.
[0128] T-cell polarization was studied after three types of stimulations of the T-cells. It was done by (i) non-specific stimulation with PMA/Ca.sup.2+ or superantigen (SEB) to study whether the total responsiveness was influenced by L. plantarum treatment, by (ii) stimulation with cell extracts of the specific L. plantarum strains in order to investigate whether specific immune responses against the L. plantarum was stimulated, and (iii) by stimulation with a previously administered vaccine antigen (TT) to study possible stimulation of specific memory responses.
[0129] After non-specific stimulation with PMA/Ca-ionophore or SEB, we studied the percentage of IFNγ, IL-4, Il-17 or IL-21 positive Th cells and memory Th cells.
[0130] Treatment with placebo or the administered L. plantarum strains did not influence cytokine production of the total population of Th cells or of the Th memory cells after non-specific stimulation with PMA/Ca-ionophore (results not shown). Although after SEB stimulation no differences were found in cytokine production of the total Th cell population after the three L. plantarum treatments (results not shown), we did observe differences in cytokine production of the Th memory cells after L. plantarum treatment.
[0131] After stimulation with SEB (
[0132] Treatment with L. plantarum strains also affected the cytokine production following a more specific stimulation by TT (
[0133] Finally, we stimulated blood samples of the individuals with cell extracts of the L. plantarum strain that they had consumed in the study (
[0134] Differential Transcriptional Response in Duodenal Mucosa Upon Exposure to the Three L. plantarum Strains
[0135] Although, we compared strains and not different species we found very different numbers of genes that were up- or downregulated in the stressed intestine of the subjects exposed to the three L. plantarum strains. After treatment with the three strains, 315 genes were differentially regulated with L. plantarum WCFS1, 390 with CIP48 and as many as 779 with TIFN 101 (
[0136] To gain more insight into the changes induced by the L. plantarum treatment, genes were subsequently ranked according to mean fold-change in expression. Listed are the 10 highest induced and 10 lowest induced genes in Tables 2-3. WCFS1 and CIP48 shared the downregulation of 6 small nucleolar RNAs (snoRNAs), i.e. snoRNA, (H)C/D(ACA) box 6, 14b, 53, 57, 60, 388.
[0137] TIFN 101 produced a completely different profile (Table 4). Of the most highly induced genes in TIFN 101, (the most immunological active L. plantarum) 8 of the 10 are related to immunity, these are immunoglobulin lambda variable 6-57, putative V-set and immunoglobulin domain-containing protein 6-like, immunoglobulin lambda variable 7-46, interferon regulatory factor 4, GDNF family, CD27, CD79a, and plasminogen activator.
[0138] Based on the immune data we expected to find differential changes by specific transcription factors. To identify these transcription factors and to identify pathways regulated by the different strains, we performed Ingenuity Pathway Analysis (IPA). IPA uses information from literature combined with gene expression changes to predict a role of transcription factors in the dataset. TIFN 101 induced more changed than CIP48 and WCSF1 in the NSAID-stressed intestine. The most significant set of target genes in the TIFN 101 group were immunology related genes. TIFN 101 upregulated MHC-II α while with CIP48 and WCFS1 we found a downregulation of MHC-II β. This might explain the enhanced responses to antigens such as TT in the TIFN 101 treated group. Another pathway that might contribute to the enhanced responses in TIFN 101 is the upregulation of genes involved in leucocyte extravasation. An interesting observation is that TIFN 101 enhances RAPL which is a GTPase involved in regulating integrin affinity and enhancing the adhesion of leucocytes. Concomitantly an upregulation of essential adhesion molecules such as ICAM-1 and Cadherin 5 (CDH-5) was upregulated illustrating the upregulation of immune cell migration pathways by TIFN 101. Also with CIP48 and WCFS1 some regulation of leukocyte extravasation was observed but this was much less pronounced than for the TIFN 101 group.
[0139] Differential Gene Expression Profiles Between the Three L. plantarum Strains
[0140] Due to the differential effects of the three L. plantarum strains, L. plantarum CIP104448, and L. plantarum TIFN 101 were sequenced, annotated and compared with the genome (chromosome and plasmids) of L. plantarum WCFS1 (Siezen et al., 2012). A total of 3010 ortholog groups (OGs) were assigned to the chromosome based on this ordering of contigs to the template WCFS1 genome. The three genomes shared 2455 of the 3010 chromosomal OGs (=81.5%), which is defined as the core genome for this study. Unique genes in TIFN 101 are listed in Table 5. When the contigs and OGs/genes are included that do not match to the WCFS1 chromosome much higher numbers of unique genes are found for the CIP48 and TIFN 101 genomes. Many of the unique genes in TIFN 101 are on plasmids (see Table 5). The analysis e.g. revealed that L. plantarum CIP104448 lacks the complete plantaricin biosynthesis gene cluster (and a large set of genes adjacent to this cluster (i.e. OGs 334-348), and the entire gene cluster for EPS biosynthesis. L. plantarum TIFN 101 is missing some genes associated with plantaricin biosynthesis as well as genes for exopolysaccharide biosynthesis, many sugar utilization cassettes, and two large LPXTG-anchored mucus-binding proteins.
TABLE-US-00002 TABLE 2 The ten most up-and down-regulated genes in NSAID-stressed human intestine after consumption of L. plantarum WCFS1 (WCSF1). Mean IBMT fold Gene p versus name value control Top 10: Upregulated genes placebo versus WCFS1 kinesin family member 20B KIF20B 0.01 1.34 microRNA 186 MIR186 0.03 1.31 guanylate cyclase activator 2A GUCA2A 0.04 1.31 (guanylin) integrin, alpha 4 (antigen CD49D, alpha ITGA4 0.01 1.31 4 subunit of VLA-4 receptor) centromere protein E, 312 kDa CENPE 0.05 1.30 putative homeodomain transcription PHTF1 0.00 1.30 factor 1 spindle and kinetochore associated SKA2 0.01 1.29 complex subunit 2 killer cell lectin-like receptor subfamily KLRD1 0.00 1.29 D, member 1 gamma-aminobutyric acid (GABA) A GABRA2 0.02 1.27 receptor, alpha 2 retinitis pigmentosa GTPase regulator RPGR 0.01 1.27 Top 10: Downregulated genes placebo versus WCFS1 small nucleolar RNA, H/ACA box 16A SNORA16A 0.02 −1.35 small nucleolar RNA, C/D box 53 SNORD53 0.04 −1.36 contactin 3 (plasmacytoma associated) CNTN3 0.00 −1.38 small nucleolar RNA, C/D box 6 SNORD6 0.04 −1.39 small nucleolar RNA, H/ACA box 57 SNORA57 0.00 −1.44 small nucleolar RNA, H/ACA box 60 SNORA60 0.00 −1.44 small nucleolar RNA, H/ACA box 14A SNORA14A 0.03 −1.49 small nucleolar RNA, H/ACA box 38B SNORA38B 0.01 −1.58 (retrotransposed) small nucleolar RNA, H/ACA box 14B SNORA14B 0.01 −1.58 small Cajal body-specific RNA 4 SNORA16A 0.01 −1.72
TABLE-US-00003 TABLE 3 The ten most up-and down-regulated genes in NSAID-stressed human intestine after consumption of L. plantarum CIP104448 (CIP48). Mean IBMT fold p versus Gene name value control Top 10: Upregulated genes placebo versus CIP48 coiled-coil domain containing 59 CCDC59 0.01 1.33 aldehyde dehydrogenase 1 family, ALDH1L2 0.03 1.32 member L2 KIAA0125 KIAA0125 0.00 1.31 phospholipase C, beta 4 PLCB4 0.01 1.31 coiled-coil domain containing 102B CCDC102B 0.04 1.29 RAS guanyl releasing protein 3 RASGRP3 0.03 1.28 (calcium and DAG-regulated) peptidase domain containing associated PAMR1 0.00 1.28 with muscle regeneration 1 DEP domain containing 1 DEPDC1 0.01 1.28 phospholipase A2, group IIA (platelets, PLA2G2A 0.02 1.28 synovial fluid) heparan sulfate (glucosamine) 3-O- HS3ST3B1 0.04 1.28 sulfotransferase 3B1 Top 10: Downregulated genes placebo versus CIP48 potassium channel, subfamily K, KCNK15 0.05 −1.33 member 15 transient receptor potential cation TRPV6 0.01 −1.33 channel, subfamily V, member 6 long intergenic non-protein coding LINC00282 0.03 −1.35 RNA 282 ephrin-A1 EFNA1 0.02 −1.38 matrix metallopeptidase 10 (stromelysin MMP10 0.05 −1.41 2) angiopoietin-like 4 ANGPTL4 0.03 −1.47 heme oxygenase (decycling) 1 HMOX1 0.00 −1.50 nuclear factor, interleukin 3 regulated NFIL3 0.01 −1.52 major facilitator superfamily domain MFSD2A 0.02 −1.59 containing 2A glucose-6-phosphatase, catalytic G6PC 0.02 −1.65 subunit
TABLE-US-00004 TABLE 4 The ten most up-and down-regulated genes in NSAID-stressed human intestine after consumption of L. plantarum TIFN 101 Mean IBMT fold p versus Gene name value control Top 10 Upregulated genes placebo versus TIFN 101 immunoglobulin lambda variable 6-57 IGLV6-57 0.01 1.63 putative V-set and immunoglobulin LOC642131 0.00 1.55 domain-containing protein 6-like immunoglobulin lambda variable 7-46 IGLV7-46 0.04 1.48 (gene/pseudogene) heparan sulfate (glucosamine) 3-O- HS3ST3B1 0.00 1.41 sulfotransferase 3B1 interferon regulatory factor 4 IRF4 0.00 1.40 GDNF family receptor alpha 2 GFRA2 0.00 1.40 CD27 molecule CD27 0.01 1.40 CD79a molecule, immunoglobulin- CD79A 0.03 1.38 associated alpha plasminogen activator, tissue PLAT 0.00 1.37 Den-like domain family, member 3 DERL3 0.00 1.37 Top 10: Downregulated genes placebo versus TIFN 101 small nucleolar RNA, H/ACA box 38B SNORA38B 0.04 −1.40 (retrotransposed) small nucleolar RNA, H/ACA box 21 SNORA21 0.03 −1.40 small nucleolar RNA, H/ACA box 60 SNORA60 0.01 −1.41 small nucleolar RNA, C/D box 53 SNORD53 0.01 −1.43 ephrin-A1 EFNA1 0.00 −1.45 small nucleolar RNA, C/D box 6 SNORD6 0.02 −1.46 small nucleolar RNA, H/ACA box 57 SNORA57 0.00 −1.47 small nucleolar RNA, H/ACA box 14B SNORA14B 0.00 −1.73 family with sequence similarity 5, FAM5C 0.03 −1.97 member C small Cajal body-specific RNA 4 SCARNA4 0.00 −2.00
TABLE-US-00005 TABLE 5 Summary of main unique contigs/gene clusters/genes in L. plantarum TIFN 101; the sequence identity numbers are depicted in column 3, the first SEQ ID NO depicts the polynucleotide sequence, the second SEQ ID NO depicts the encoded polypeptide [polynucleotide polypeptide]. OGs Contains functions SEQ ID NO: chromosome 185 MFS family transporter 176; 260 186 fumarate reductase/succinate dehydrogenase 177; 261 flavoprotein 187 Transcriptional regulator, AraC family 178; 262 382 toxin-antitoxin system, antitoxin component 179; 263 MazE, AbrB family 383 toxin-antitoxin system, toxin component MazF, 180; 264 PemK family 409 Hypothetical protein 181; 265 410 Conserved ankyrin repeat protein, putative 182; 266 411 integral membrane protein 183; 267 461 nitrate/sulfonate/bicarbonate ABC transporter, 184; 268 substrate-binding protein 462 nitrate/sulfonate/bicarbonate ABC transporter, 185; 269 permease protein 463 nitrate/sulfonate/bicarbonate ABC transporter, 186; 270 ATP-binding protein 1197 ADP-ribosylglycohydrolase 187; 271 1986 abortive infection bacteriophage resistance 188; 272 protein 2366 cell wall hydrolase, glycosyl hydrolase family 25 189; 273 2549 membrane proteinase PrsW, regulator of anti- 190; 274 sigma factor 2583 hypothetical membrane protein, YfhO family 191; 275 2610 Fructokinase (EC 2.7.1.4) 192; 276 2611 glycosyl hydrolase, family 38 193; 277 2612 PTS system, IIC component 194; 278 2613 PTS system, fructose-specific IIBC component 195; 279 (EC 2.7.1.69) 2614 (EC 2.7.1.69)/PTS system, fructose-specific IIC 196; 280 component (EC 2.7.1.69) 2615 Transcription antiterminator, BglG family 197; 281 on putative plasmids 3299 hydrolase, HD superfamily, C-terminus 198; 282 3300 Ribonucleotide reduction protein NrdI 199; 283 3301 Ribonucleotide reductase of class Ib (aerobic), 200; 284 alpha subunit (EC 1.17.4.1) 3302 Ribonucleotide reductase of class Ib (aerobic), 201; 285 beta subunit (EC 1.17.4.1) 3303 Ribonucleotide reductase of class Ib (aerobic), 202; 286 beta subunit (EC 1.17.4.1) 3304 transposase, fragment 203; 287 3305 Site-specific recombinase, DNA invertase Pin 204; 288 related protein 3306 membrane protein with DUF161 and DUF2179 205; 289 domains, YitT family 3307 Na(+)/H(+) antiporter 206; 290 3308 Voltage-gated chloride channel family protein 207; 291 3323 Glucose uptake protein 208; 292 3324 Mannose-6-phosphate isomerase 209; 293 3325 hypothetical protein, C-terminus 210; 294 3326 hypothetical protein 211; 295 3327 Glutamine synthetase type I (EC 6.3.1.2) 212; 296 3328 transposase 213; 297 3329 toxin-antitoxin system, toxin component, 214; 298 PemK/MazF family 3330 toxin-antitoxin system, antitoxin component, 215; 299 PemI/MazE family 3331 integrase/recombinase 216; 300 3332 hypothetical protein, C-terminus 217; 301 3333 hypothetical protein 218; 302 3334 Cold shock protein CspA 219; 303 3335 toxin-antitoxin system, RelE/StbE family; 220; 304 replication protein RepA 3336 hypothetical protein 221; 305 3337 Transcriptional regulator, PBSX/Xre family 222; 306 3338 hypothetical protein 223; 307 3339 integrase/recombinase 224; 308 3340 toxin-antitoxin system, antitoxin component, 225; 309 Phd_YefM family 3341 toxin-antitoxin system, toxin component, 226; 310 RelE/StbE family 3342 hypothetical protein 227; 311 3343 hypothetical protein 228; 312 3344 ISEf1, transposase 229; 313 3345 hypothetical membrane protein 230; 314 3346 hypothetical protein, N-terminus 231; 315 3347 replication protein RepA 232; 316 3348 hypothetical protein 233; 317 3349 Transposase IS66 234; 318 3350 Transposase IS66, N-terminus 235; 319 3351 Transposase IS66, C-terminus 236; 320 3352 Pyridine nucleotide-disulfide oxidoreductase 237; 321 3353 LtrC-like protein 238; 322 3354 Major facilitator: Oxalate: Formate Antiporter 239; 323 3355 transposase IS3/IS911 family protein 240; 324 3356 Excinuclease ABC subunit A paralog 241; 325 3357 site-specific recombinase 242; 326 3358 Iron-sulfur cluster assembly protein SufB, 243; 327 permease, C-terminus 3359 membrane protein, MarC family 244; 328 3360 peptidase E 245; 329 3361 hypothetical protein 246; 330 3362 FIG00742910: hypothetical protein 247; 331 3363 alkaline shock protein, Asp23 family 248; 332 3364 hypothetical membrane protein 249; 333 3365 hypothetical protein 250; 334 3366-3371 FIG00753329: hypothetical protein, N-terminus 251; 335 3367 FIG00742586: hypothetical protein 252; 336 3368 replication initiator protein, C-terminus 253; 337 3369 replication initiator protein, N-terminus 254; 338 3370 hypothetical protein 255; 339 3371 plasmid partitioning ATPase ParA 256; 340
[0141] Discussion
[0142] This study was undertaken to investigate whether L. plantarum strains selected in vitro for their differential immune stimulating capacity have different impact on local and systemic immunity in healthy individuals undergoing a mild, commonly encountered stressor of intestinal immunity. All three strains had an effect on immunity but that this effect was highly strain dependent and may not be beneficial in certain contexts. On the basis of results obtained by dendritic cell stimulation with L. plantarum strains in vitro the immune properties, of strain. WCFS1 was considered to be proinflammatory, L. plantarum CIP104448 as neutral and L. plantarum TIFN 101 as regulatory. However, the immune responses to these strains in vivo was very different to that predicted in vitro.
[0143] Consumption of NSAID induced reduction in CD4+/Foxp3 regulatory cells but was prevented by WCFS1 and TIFN 101 administration which should be considered to be a beneficial regulatory effect. CIP48 did not prevent NSAID induced reduction of CD4+Foxp3 T cells and had more negative effects. CIP48 reduced the number of memory cells suggesting a proinflammatory, worsening effect of consumption of this bacterium.
[0144] T-cell polarization was studied after different stimuli to gain insight into the mechanisms by which bacteria might influence immunity. A hypothesis we had was that bacterial wall components might induce immune responses (Smelt et al., 2012) and enhance systemic immunity as bystander effect. However, this hypothesis had to be rejected as the sole responsible mechanism as only WCFS1 showed a trend of elevation of IL17 production after challenging whole blood of the WCSF1 consumers with the bacterial strain. The most pronounced stimulator of immunity, i.e. TIFN 101, showed no response to the bacterial extract but enhanced the responses against specific pathogenic antigens such as SEB and that against TT.
[0145] The analysis of the mucosal transcriptome suggested that the enhanced memory response is related to TIFN 101 enhanced upregulation of processes associated with T- and B-cell function and antigen presentation. TIFN 101 in contrast to the other bacteria had a pronounced effect on immunological related pathways in the mucosa of the consumers.
[0146] In particular TIFN 101 enhanced pathways and genes related to antigen presentation. TIFN 101 had a pronounced effect on CD27 upregulation which is required for generation and long-term maintenance of T cell immunity (Huang et al., 2013). Also TIFN 101 enhanced the expression of MHC-II α in mucosa and of key regulatory molecules such as RAPL. RAPL enhances integrin affinity and the adhesion of T-cells (Raab et al., 2010; Zhang and Wang, 2012). These observations in the mucosa may explain the enhanced memory T-cell responses observed in the TIFN 101 consumers.
[0147] Also B-cell immunity in the mucosa was enhanced as illustrated by upregulation of immunoglobulin regulatory genes and by CD79a. CD79A is also known as B-cell antigen receptor complex-associated protein alpha chain forming together with CD79b protein the B-cell antigen receptor (Herren and Burrows, 2002). CIP48 and WCFS1 did not have these effects or downregulated processes such as antigen presentation in the mucosa.
[0148] The observation that bacteria can downregulate snoRNAs in the intestine has to our best knowledge not been reported before. SnoRNA are metabolically stable noncoding RNAs that associate with a set of proteins to form small nucleolar RNPs (snoRNPs). The majority of snoRNA function as guide RNAs in the post-transcriptional synthesis of 2′-O-methylated nucleotides and pseudouridines in rRNAs, small nuclear RNAs (snRNAs) and other cellular RNAs, including mRNAs (Bratkovic and Rogelj, 2011; Esteller, 2011; Williams and Farzaneh, 2012). The relative reduction in snoRNA 53, 57, 60 by CIP48 and WCFS1 suggest a downregulation of methylation of ribosomal RNA (Kiss-Laszlo et al., 1996) and downregulation of 14b diminished pseudouridinilation of RNA (Kiss et al., 2004). Usually this suggest a destabilization of cellular processes (Su et al., 2014), again suggesting that CIP48 and WCFS1 are not beneficial for a mildly stressed intestinal environment.
[0149] We applied genome sequencing of L. plantarum CIP104448 and L. plantarum TIFN 101 to identify possible gene clusters that might be responsible for the differential biological effects of the three L. plantarum strains. Several hundred novel L. plantarum genes were found in strain CIP48 (340 new OGs) and TIFN 101 (177 OGs) compared to strain WCFS1. Only a small number of these (47 OGs) are shared by both CIP48 and TIFN 101. The majority of these novel genes appear to be on plasmids. L. plantarum TIFN 101 partly lacks the plantaricin biosynthesis clusters. These genes have in previous studies been linked to strain differences in cytokine production (Meijerink et al., 2010; Wells et al., 2011) but were shown here not to be associated with immune effects in vivo. Also L. plantarum CIP104448 and L. plantarum TIFN 101 lack very large regions of the sugar metabolism. These adaptations have been attributed to adaptations to environmental factors which are interesting targets to identify genes associated with probiotic effects (Molenaar et al., 2005). Not only presence but also absence of genes may enhance immune effects of bacteria (Smelt et al., 2013b). This comparative genomics study in which effects of L. plantarum supplementation on the mucosal transcriptome were combined with systemic immune activation parameters provides many leads for follow-up experimental work to identify genes that are responsible for or involved in the observed differences in immune effects in the human subject.
REFERENCE LIST
[0150] Belkaid Y, Hand T W. Role of the microbiota in immunity and inflammation. Cell 2014; 157:121-41. doi: 10.1016/j.cell.2014.03.011.
[0151] Cao S, Feehley T J, Nagler C R. The role of commensal bacteria in the regulation of sensitization to food allergens. FEBS Lett 2014; 1:00312-3.
[0152] de Kivit S, Tobin M C, Forsyth C B, Keshavarzian A, Landay A L. Regulation of Intestinal Immune Responses through TLR Activation: Implications for Pro- and Prebiotics. Front Immunol 2014; 5:60. eCollection 2014.
[0153] Geuking M B, Koller Y, Rupp S, McCoy K D. The interplay between the gut microbiota and the immune system. Gut Microbes 2014; 5:3.
[0154] Walker M M, Talley N J. Review article: bacteria and pathogenesis of disease in the upper gastrointestinal tract—beyond the era of Helicobacter pylori. Aliment Pharmacol Ther 2014; 39:767-79. doi: 10.1111/apt.12666. Epub 2014 Feb. 24.
[0155] Meijerink M, van H S, Taverne N, Wels M, de V P, Bron P A, et al. Identification of genetic loci in Lactobacilli plantarum that modulate the immune response of dendritic cells using comparative genome hybridization. PLoSOne 2010; 5:e10632.
[0156] Meijerink M, Wells J M, Taverne N, de Zeeuw Brouwer M L, Hilhorst B, Venema K, et al Immunomodulatory effects of potential probiotics in a mouse peanut sensitization model. FEMS Immunol Med Microbiol 2012; 65:488-96.
[0157] Wells J M, Rossi O, Meijerink M, van B P. Epithelial crosstalk at the microbiota-mucosal interface. Proc Natl Acad Sci USA 2011; 108 Suppl 1:4607-14.
[0158] van Baarlen P, Troost F, van der Meer C, Hooiveld G, Boekschoten M, Brummer R J, et al. Human mucosal in vivo transcriptome responses to three lactobacilli indicate how probiotics may modulate human cellular pathways. Proc Natl Acad Sci U S A 2011; 108:4562-9. doi: 10.1073/pnas.1000079107. Epub 2010 Sep. 7.
[0159] van Baarlen P, Troost F J, van Hemert S, van der Meer C, de Vos W M, de Groot P J, et al. Differential NF-kappaB pathways induction by Lactobacilli plantarum in the duodenum of healthy humans correlating with immune tolerance. Proc Natl Acad Sci U S A 2009; 106:2371-6. doi: 10.1073/pnas.0809919106. Epub 2009 Feb. 3.
[0160] van Hemert S, Meijerink M, Molenaar D, Bron P A, de Vos P, Kleerebezem M, Wells J M, Marco M L Identification of Lactobacilli plantarum genes modulating the cytokine response of human peripheral blood mononuclear cells BMC microbiology 2010, 10 (1) 293
[0161] Smelt M J, de Haan B J, Bron P A, van Swam I, Meijerink M, Wells J M, et al. The Impact of Lactobacilli plantarum WCFS1 Teichoic Acid D-Alanylation on the Generation of Effector and Regulatory T-cells in Healthy Mice. PLoS One 2013; 8:e63099.
[0162] Smelt M J, de Haan B J, Bron P A, van Swam I, Meijerink M, Wells J M, et al. L. plantarum, L. salivarius, and L. lactis attenuate Th2 responses and increase Treg frequencies in healthy mice in a strain dependent manner PLoS One 2012; 7:e47244.
[0163] Schoultz I, McKay C M, Graepel R, Phan V C, Wang A, Soderholm J, et al. Indomethacin-induced translocation of bacteria across enteric epithelia is reactive oxygen species-dependent and reduced by vitamin C. Am J Physiol Gastrointest Liver Physiol 2012; 303:G536-45. doi: 10.1152/ajpgi.00125.2012. Epub 2012 Jun. 14.
[0164] Deasy A, Read R C. Challenges for development of meningococcal vaccines in infants and children. Expert Rev Vaccines 2011; 10:335-43. doi: 10.1586/erv.11.3. (16) Edwards K M, Berbers G A. Immune responses to pertussis vaccines and disease. J Infect Dis 2014; 209:S10-5. doi: .1093/infdis/jit560. Epub 2013 Oct. 31.
[0165] Kerneis S, Launay O, Turbelin C, Batteux F, Hanslik T, Boelle P Y. Long-term immune responses to vaccination in HIV-infected patients: a systematic review and meta-analysis. Clin Infect Dis 2014; 58:1130-9. doi: 10.093/cid/cit937. Epub 2014 Jan. 10.
[0166] Poorolajal J, Mahmoodi M, Haghdoost A, Majdzadeh R, Nasseri-Moghaddam S, Ghalichi L, et al. Booster dose vaccination for preventing hepatitis B. Cochrane Database Syst Rev 2010: CD008256. doi: 10.1002/14651858.CD008256.pub2.
[0167] Schure R M, Hendrikx L H, de Rond L G, Ozturk K, Sanders E A, Berbers G A, et al. T-cell responses before and after the fifth consecutive acellular pertussis vaccination in 4-year-old Dutch children. Clin Vaccine Immunol 2012; 19:1879-86. doi: 10.128/CVI.00277-12. Epub 2012 Sep. 26.
[0168] Marco, M. L., S. Pavan, and M. Kleerebezem, Towards understanding molecular modes of probiotic action. Curr Opin Biotechnol, 2006. 17(2): p. 204-10.
[0169] Corr, S. C., C. Hill, and C. G. Gahan, Understanding the mechanisms by which probiotics inhibit gastrointestinal pathogens. Adv Food Nutr Res, 2009. 56: p. 1-15.
[0170] Saulnier, D. M. A., et al., Mechanisms of probiosis and probiosis: considerations for enhanced functional foods. Current Opinion in Biotechnology, 2009. 20(2): p. 135-141.
[0171] Saxelin, M., et al., Probiotic and other functional microbes: from markets to mechanisms. Curr Opin Biotechnol, 2005. 16(2): p. 204-11.
[0172] Ma, D., P. Forsythe, and J. Bienenstock, Live Lactobacillus reuteri is essential for the inhibitory effect on tumor necrosis factor alpha-induced interleukin-8 expression. Infect Immun, 2004. 72(9): p. 5308-14.
[0173] Gobbetti, M., R. D. Cagno, and M. De Angelis, Functional microorganisms for functional food quality. Crit Rev Food Sci Nutr, 2010. 50(8): p. 716-27.
[0174] Smyth et al. 2004, Stat Appl Genet Mol Biol
[0175] Subramanian et al 2005, Proc Natl Acad Sci USA PMID 16199517
[0176] Tarazona, R., J. G. Casado, O. Delarosa, J. Torre-Cisneros, J. L. Villanueva, B. Sanchez, M. D. Galiani, R. Gonzalez, R. Solana, and J. Pena. 2002. Selective depletion of CD56(dim) NK cell subsets and maintenance of CD56(bright) NK cells in treatment-naive HIV-1-seropositive individuals. J Clin Immunol 22:176-183.
[0177] Jacobs, R., G. Hintzen, A. Kemper, K. Beul, S. Kempf, G. Behrens, K. W. Sykora, and R. E. Schmidt. 2001. CD56bright cells differ in their KIR repertoire and cytotoxic features from CD56dim NK cells. Eur J Immunol 31:3121-3127.
[0178] Siezen, R. J., C. Francke, B. Renckens, J. Boekhorst, M. Wels, M. Kleerebezem, and S. A. van Hijum. 2012. Complete resequencing and reannotation of the Lactobacillus plantarum WCFS1 genome. J Bacteriol 194:195-196.
[0179] Huang, J., C. Jochems, A. M. Anderson, T. Talaie, A. Jales, R. A. Madan, J. W. Hodge, K. Y. Tsang, D. J. Liewehr, S. M. Steinberg, J. L. Gulley, and J. Schlom. 2013. Soluble CD27-pool in humans may contribute to T cell activation and tumor immunity. J Immunol 190:6250-6258
[0180] Raab, M., H. Wang, Y. Lu, X. Smith, Z. Wu, K. Strebhardt, J. E. Ladbury, and C. E. Rudd. 2010. T cell receptor “inside-out” pathway via signaling module SKAP1-RapL regulates T cell motility and interactions in lymph nodes. Immunity 32:541-556.
[0181] Zhang, Y., and H. Wang. 2012. Integrin signalling and function in immune cells. Immunology 135:268-275.
[0182] Herren, B., and P. D. Burrows. 2002. B cell-restricted human mb-1 gene: expression, function, and lineage infidelity. Immunologic research 26:35-43.
[0183] Bratkovic, T., and B. Rogelj. 2011. Biology and applications of small nucleolar RNAs. Cellular and molecular life sciences: CMLS 68:3843-3851.
[0184] Esteller, M. 2011. Non-coding RNAs in human disease. Nature reviews. Genetics 12:861-874.
[0185] Williams, G. T., and F. Farzaneh. 2012. Are snoRNAs and snoRNA host genes new players in cancer? Nature reviews. Cancer 12:84-88.
[0186] Kiss-Laszlo, Z., Y. Henry, J. P. Bachellerie, M. Caizergues-Ferrer, and T. Kiss. 1996. Site-specific ribose methylation of preribosomal RNA: a novel function for small nucleolar RNAs. Cell 85:1077-1088.
[0187] Kiss, A. M., B. E. Jady, E. Bertrand, and T. Kiss. 2004. Human box H/ACA pseudouridylation guide RNA machinery. Molecular and cellular biology 24:5797-5807.
[0188] Su, H., T. Xu, S. Ganapathy, M. Shadfan, M. Long, T. H. Huang, I. Thompson, and Z. M. Yuan. 2014. Elevated snoRNA biogenesis is essential in breast cancer. Oncogene 33:1348-1358.
[0189] Molenaar, D., F. Bringel, F. H. Schuren, W. M. de Vos, R. J. Siezen, and M. Kleerebezem. 2005. Exploring Lactobacilli plantarum genome diversity by using microarrays. J Bacteriol 187:6119-6127.
[0190] Troost, F. J., W. H. Saris, and R. J. Brummer 2003. Recombinant human lactoferrin ingestion attenuates indomethacin-induced enteropathy in vivo in healthy volunteers. Eur J Clin Nutr 57:1579-1585.