Identification of Lactobacillus plantarum genes modulating the cytokine response of human peripheral blood mononuclear cells

<p>Abstract</p> <p>Background</p> <p>Modulation of the immune system is one of the most plausible mechanisms underlying the beneficial effects of probiotic bacteria on human health. Presently, the specific probiotic cell products responsible for immunomodulation are largely unknown. In this study, the genetic and phenotypic diversity of strains of the <it>Lactobacillus plantarum </it>species were investigated to identify genes of <it>L. plantarum </it>with the potential to influence the amounts of cytokines interleukin 10 (IL-10) and IL-12 and the ratio of IL-10/IL-12 produced by peripheral blood mononuclear cells (PBMCs).</p> <p>Results</p> <p>A total of 42 <it>Lactobacillus plantarum </it>strains isolated from diverse environmental and human sources were evaluated for their capacity to stimulate cytokine production in PBMCs. The <it>L. plantarum </it>strains induced the secretion of the anti-inflammatory cytokine IL-10 over an average 14-fold range and secretion of the pro-inflammatory cytokine IL-12 over an average 16-fold range. Comparisons of the strain-specific cytokine responses of PBMCs to comparative genome hybridization profiles obtained with <it>L. plantarum </it>WCFS1 DNA microarrays (also termed gene-trait matching) resulted in the identification of 6 candidate genetic loci with immunomodulatory capacities. These loci included genes encoding an <it>N</it>-acetyl-glucosamine/galactosamine phosphotransferase system, the LamBDCA quorum sensing system, and components of the plantaricin (bacteriocin) biosynthesis and transport pathway. Deletion of these genes in <it>L. plantarum </it>WCFS1 resulted in growth phase-dependent changes in the PBMC IL-10 and IL-12 cytokine profiles compared with wild-type cells.</p> <p>Conclusions</p> <p>The altered PBMC cytokine profiles obtained with the <it>L. plantarum </it>WCFS1 mutants were in good agreement with the predictions made by gene-trait matching for the 42 <it>L. plantarum </it>strains. This study therefore resulted in the identification of genes present in certain strains of <it>L. plantarum </it>which might be responsible for the stimulation of anti- or pro-inflammatory immune responses in the gut.</p

Understanding mode of action can drive the translational pipeline towards more reliable health benefits for probiotics

The different levels of knowledge described in a translational pipeline (the connection of molecular mechanisms with pre-clinical physiological and human health effects) are not complete for many probiotics. At present, we are not in a position to fully understand the mechanistic basis of many well established probiotic health benefits which, in turn, limits our ability to use mechanisms to predict which probiotics are likely to be effective in any given population. Here we suggest that this concept of a translation pipeline connecting mechanistic insights to probiotic efficacy can support the selection and production of improved probiotic products. Such a conceptual pipeline would also provide a framework for the design of clinical trials to convincingly demonstrate the benefit of probiotics to human health in well-defined subpopulations.Peer reviewe

Identification of Genetic Loci in Lactobacillus plantarum That Modulate the Immune Response of Dendritic Cells Using Comparative Genome Hybridization

Contains fulltext : 88219.pdf (publisher's version ) (Open Access)BACKGROUND: Probiotics can be used to stimulate or regulate epithelial and immune cells of the intestinal mucosa and generate beneficial mucosal immunomodulatory effects. Beneficial effects of specific strains of probiotics have been established in the treatment and prevention of various intestinal disorders, including allergic diseases and diarrhea. However, the precise molecular mechanisms and the strain-dependent factors involved are poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we aimed to identify gene loci in the model probiotic organism Lactobacillus plantarum WCFS1 that modulate the immune response of host dendritic cells. The amounts of IL-10 and IL-12 secreted by dendritic cells (DCs) after stimulation with 42 individual L. plantarum strains were measured and correlated with the strain-specific genomic composition using comparative genome hybridisation and the Random Forest algorithm. This in silico "gene-trait matching" approach led to the identification of eight candidate genes in the L. plantarum genome that might modulate the DC cytokine response to L. plantarum. Six of these genes were involved in bacteriocin production or secretion, one encoded a bile salt hydrolase and one encoded a transcription regulator of which the exact function is unknown. Subsequently, gene deletions mutants were constructed in L. plantarum WCFS1 and compared to the wild-type strain in DC stimulation assays. All three bacteriocin mutants as well as the transcription regulator (lp_2991) had the predicted effect on cytokine production confirming their immunomodulatory effect on the DC response to L. plantarum. Transcriptome analysis and qPCR data showed that transcript level of gtcA3, which is predicted to be involved in glycosylation of cell wall teichoic acids, was substantially increased in the lp_2991 deletion mutant (44 and 29 fold respectively). CONCLUSION: Comparative genome hybridization led to the identification of gene loci in L. plantarum WCFS1 that modulate the immune response of DCs

Transcriptome Analysis of a Spray Drying-Resistant Subpopulation Reveals a Zinc-Dependent Mechanism for Robustness in L. lactis SK11

The viability of starter cultures is essential for an adequate contribution to the fermentation process and end-product. Therefore, robustness during processing and storage is an important characteristic of starter culture strains. For instance, during spray drying cells are exposed to heat and oxidative stress, generally resulting in loss of viability. In this study, we exposed the industrially relevant but stress-sensitive Lactococcus lactis strain SK11 to two cycles of heat stress, with intermediate recovery and cultivation at moderate temperatures. After these two cycles of heat exposure, the abundance of robust derivatives was increased as compared with the original culture, which enabled isolation of heat-resistant subpopulations displaying up to 1,000-fold enhanced heat stress survival. Moreover, this heat-resistant subpopulation demonstrated an increased survival during spray drying. Derivatives from two independent lineages displayed different transcriptome changes as compared with the wild type strain, indicating that the increased robustness within these lineages was established by different adaptive strategies. Nevertheless, an overlap in differential gene expression in all five derivatives tested in both lineages included three genes in an operon involved in zinc transport. The link between zinc homeostasis and heat stress survival in L. lactis was experimentally established by culturing of the wild type strain SK11 in medium with various levels of zinc ions, which resulted in alterations in heat stress survival phenotypes. This study demonstrates that robust derivatives of a relatively sensitive L. lactis strain can be isolated by repeated exposure to heat stress. Moreover, this work demonstrates that transcriptome analysis of these robust derivatives can provide clues for improvement of the robustness of the original strain. This could boost the industrial application of strains with specific desirable traits but inadequate robustness characteristics

Stress Physiology of Lactic Acid Bacteria

Lactic acid bacteria (LAB) are important starter, commensal, or pathogenic microorganisms. The stress physiology of LAB has been studied in depth for over 2 decades, fueled mostly by the technological implications of LAB robustness in the food industry. Survival of probiotic LAB in the host and the potential relatedness of LAB virulence to their stress resilience have intensified interest in the field. Thus, a wealth of information concerning stress responses exists today for strains as diverse as starter (e.g., Lactococcus lactis), probiotic (e.g., several Lactobacillus spp.), and pathogenic (e.g., Enterococcus and Streptococcus spp.) LAB. Here we present the state of the art for LAB stress behavior. We describe the multitude of stresses that LAB are confronted with, and we present the experimental context used to study the stress responses of LAB, focusing on adaptation, habituation, and cross-protection as well as on self-induced multistress resistance in stationary phase, biofilms, and dormancy. We also consider stress responses at the population and single-cell levels. Subsequently, we concentrate on the stress defense mechanisms that have been reported to date, grouping them according to their direct participation in preserving cell energy, defending macromolecules, and protecting the cell envelope. Stress-induced responses of probiotic LAB and commensal/pathogenic LAB are highlighted separately due to the complexity of the peculiar multistress conditions to which these bacteria are subjected in their hosts. Induction of prophages under environmental stresses is then discussed. Finally, we present systems-based strategies to characterize the "stressome" of LAB and to engineer new food-related and probiotic LAB with improved stress tolerance.</p

An Interpretable Machine Learning Model with Deep Learning-based Imaging Biomarkers for Diagnosis of Alzheimer's Disease

Machine learning methods have shown large potential for the automatic early diagnosis of Alzheimer's Disease (AD). However, some machine learning methods based on imaging data have poor interpretability because it is usually unclear how they make their decisions. Explainable Boosting Machines (EBMs) are interpretable machine learning models based on the statistical framework of generalized additive modeling, but have so far only been used for tabular data. Therefore, we propose a framework that combines the strength of EBM with high-dimensional imaging data using deep learning-based feature extraction. The proposed framework is interpretable because it provides the importance of each feature. We validated the proposed framework on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, achieving accuracy of 0.883 and area-under-the-curve (AUC) of 0.970 on AD and control classification. Furthermore, we validated the proposed framework on an external testing set, achieving accuracy of 0.778 and AUC of 0.887 on AD and subjective cognitive decline (SCD) classification. The proposed framework significantly outperformed an EBM model using volume biomarkers instead of deep learning-based features, as well as an end-to-end convolutional neural network (CNN) with optimized architecture.Comment: 11 pages, 5 figure

Lactobacillus plantarum Strains Can Enhance Human Mucosal and Systemic Immunity and Prevent Non-steroidal Anti-inflammatory Drug Induced Reduction in T Regulatory Cells

Orally ingested bacteria interact with intestinal mucosa and may impact immunity. However, insights in mechanisms involved are limited. In this randomized placebo-controlled cross-over trial, healthy human subjects were given Lactobacillus plantarum supplementation (strain TIFN101, CIP104448, or WCFS1) or placebo for 7 days. To determine whether L. plantarum can enhance immune response, we compared the effects of three stains on systemic and gut mucosal immunity, by among others assessing memory responses against tetanus toxoid (TT)-antigen, and mucosal gene transcription, in human volunteers during induction of mild immune stressor in the intestine, by giving a commonly used enteropathic drug, indomethacin [non-steroidal anti-inflammatory drug (NSAID)]. Systemic effects of the interventions were studies in peripheral blood samples. NSAID was found to induce a reduction in serum CD4+/Foxp3 regulatory cells, which was prevented by L. plantarum TIFN101. T-cell polarization experiments showed L. plantarum TIFN101 to enhance responses against TT-antigen, which indicates stimulation of memory responses by this strain. Cell extracts of the specific L. plantarum strains provoked responses after WCFS1 and TIFN101 consumption, indicating stimulation of immune responses against the specific bacteria. Mucosal immunomodulatory effects were studied in duodenal biopsies. In small intestinal mucosa, TIFN101 upregulated genes associated with maintenance of T- and B-cell function and antigen presentation. Furthermore, L. plantarum TIFN101 and WCFS1 downregulated immunological pathways involved in antigen presentation and shared downregulation of snoRNAs, which may suggest cellular destabilization, but may also be an indicator of tissue repair. Full sequencing of the L. plantarum strains revealed possible gene clusters that might be responsible for the differential biological effects of the bacteria on host immunity. In conclusion, the impact of oral consumption L. plantarum on host immunity is strain dependent and involves responses against bacterial cell components. Some strains may enhance specific responses against pathogens by enhancing antigen presentation and leukocyte maintenance in mucosa. In future studies and clinical settings, caution should be taken in selecting beneficial bacteria as closely related strains can have different effects. Our data show that specific bacterial strains can prevent immune stress induced by commonly consumed painkillers such as NSAID and can have enhancing beneficial effects on immunity of consumers by stimulating antigen presentation and memory responses

Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

This work validates the generalizability of MRI-based classification of Alzheimer’s disease (AD) patients and controls (CN) to an external data set and to the task of prediction of conversion to AD in individuals with mild cognitive impairment (MCI).We used a conventional support vector machine (SVM) and a deep convolutional neural network (CNN) approach based on structural MRI scans that underwent either minimal pre-processing or more extensive pre-processing into modulated gray matter (GM) maps. Classifiers were optimized and evaluated using cross-validation in the Alzheimer’s Disease Neuroimaging Initiative (ADNI; 334 AD, 520 CN). Trained classifiers were subsequently applied to predict conversion to AD in ADNI MCI patients (231 converters, 628 non-converters) and in the independent Health-RI Parelsnoer Neurodegenerative Diseases Biobank data set. From this multi-center study representing a tertiary memory clinic population, we included 199 AD patients, 139 participants with subjective cognitive decline, 48 MCI patients converting to dementia, and 91 MCI patients who did not convert to dementia.AD-CN classification based on modulated GM maps resulted in a similar area-under-the-curve (AUC) for SVM (0.940; 95%CI: 0.924–0.955) and CNN (0.933; 95%CI: 0.918–0.948). Application to conversion prediction in MCI yielded significantly higher performance for SVM (AUC = 0.756; 95%CI: 0.720-0.788) than for CNN (AUC = 0.742; 95%CI: 0.709-0.776) (p<0.01 for McNemar’s test). In external validation, performance was slightly decreased. For AD-CN, it again gave similar AUCs for SVM (0.896; 95%CI: 0.855–0.932) and CNN (0.876; 95%CI: 0.836–0.913). For prediction in MCI, performances decreased for both SVM (AUC = 0.665; 95%CI: 0.576-0.760) and CNN (AUC = 0.702; 95%CI: 0.624-0.786). Both with SVM and CNN, classification based on modulated GM maps significantly outperformed classification based on minimally processed images (p=0.01).Deep and conventional classifiers performed equally well for AD classification and their performance decreased only slightly when applied to the external cohort. We expect that this work on external validation contributes towards translation of machine learning to clinical practice

All-sky search for time-integrated neutrino emission from astrophysical sources with 7 years of IceCube data

Since the recent detection of an astrophysical flux of high energy neutrinos, the question of its origin has not yet fully been answered. Much of what is known about this flux comes from a small event sample of high neutrino purity, good energy resolution, but large angular uncertainties. In searches for point-like sources, on the other hand, the best performance is given by using large statistics and good angular reconstructions. Track-like muon events produced in neutrino interactions satisfy these requirements. We present here the results of searches for point-like sources with neutrinos using data acquired by the IceCube detector over seven years from 2008--2015. The discovery potential of the analysis in the northern sky is now significantly below $E_\nu^2d\phi/dE_\nu=10^{-12}\:\mathrm{TeV\,cm^{-2}\,s^{-1}}$, on average $38\%$ lower than the sensitivity of the previously published analysis of four years exposure. No significant clustering of neutrinos above background expectation was observed, and implications for prominent neutrino source candidates are discussed.Comment: 19 pages, 17 figures, 3 tables; ; submitted to The Astrophysical Journa