Fermented beverages with health-promoting potential: Past and future perspectives

peer-reviewedFermentation is an ancient form of food preservation, which also improves the nutritional content of foods. In many regions of the world, fermented beverages have become known for their health-promoting attributes. In addition to harnessing traditional beverages for commercial use, there have recently been innovative efforts to develop non-dairy probiotic fermented beverages from a variety of substrates, including soy milk, whey, cereals and vegetable and fruit juices. On the basis of recent developments, it is anticipated that fermented beverages will continue to be a significant component within the functional food market

Sequencing-Based Analysis of the Bacterial and Fungal Composition of Kefir Grains and Milks from Multiple Sources

peer-reviewedKefir is a fermented milk-based beverage to which a number of health-promoting properties have been attributed. The microbes responsible for the fermentation of milk to produce kefir consist of a complex association of bacteria and yeasts, bound within a polysaccharide matrix, known as the kefir grain. The consistency of this microbial population, and that present in the resultant beverage, has been the subject of a number of previous, almost exclusively culture-based, studies which have indicated differences depending on geographical location and culture conditions. However, culture-based identification studies are limited by virtue of only detecting species with the ability to grow on the specific medium used and thus culture-independent, molecular-based techniques offer the potential for a more comprehensive analysis of such communities. Here we describe a detailed investigation of the microbial population, both bacterial and fungal, of kefir, using high-throughput sequencing to analyse 25 kefir milks and associated grains sourced from 8 geographically distinct regions. This is the first occasion that this technology has been employed to investigate the fungal component of these populations or to reveal the microbial composition of such an extensive number of kefir grains or milks. As a result several genera and species not previously identified in kefir were revealed. Our analysis shows that the bacterial populations in kefir are dominated by 2 phyla, the Firmicutes and the Proteobacteria. It was also established that the fungal populations of kefir were dominated by the genera Kazachstania, Kluyveromyces and Naumovozyma, but that a variable sub-dominant population also exists.The Alimentary Pharmabiotic Centre is a research centre funded by Science Foundation Ireland (SFI), through the Irish Government’s National Development Plan. The authors and their work were supported by SFI CSET grant APC CSET 2 grant 07/CE/B1368

In silico identification of bacteriocin gene clusters in the gastrointestinal tract, based on the Human Microbiome Project’s reference genome database

peer-reviewedBackground The human gut microbiota comprises approximately 100 trillion microbial cells which significantly impact many aspects of human physiology - including metabolism, nutrient absorption and immune function. Disturbances in this population have been implicated in many conditions and diseases, including obesity, type-2 diabetes and inflammatory bowel disease. This suggests that targeted manipulation or shaping of the gut microbiota, by bacteriocins and other antimicrobials, has potential as a therapeutic tool for the prevention or treatment of these conditions. With this in mind, several studies have used traditional culture-dependent approaches to successfully identify bacteriocin-producers from the mammalian gut. In silico-based approaches to identify novel gene clusters are now also being utilised to take advantage of the vast amount of data currently being generated by next generation sequencing technologies. In this study, we employed an in silico screening approach to mine potential bacteriocin clusters in genome-sequenced isolates from the gastrointestinal tract (GIT). More specifically, the bacteriocin genome-mining tool BAGEL3 was used to identify potential bacteriocin producers in the genomes of the GIT subset of the Human Microbiome Project’s reference genome database. Each of the identified gene clusters were manually annotated and potential bacteriocin-associated genes were evaluated. Results We identified 74 clusters of note from 59 unique members of the Firmicutes, Bacteroidetes, Actinobacteria, Fusobacteria and Synergistetes. The most commonly identified class of bacteriocin was the >10 kDa class, formerly known as bacteriolysins, followed by lantibiotics and sactipeptides. Conclusions Multiple bacteriocin gene clusters were identified in a dataset representative of the human gut microbiota. Interestingly, many of these were associated with species and genera which are not typically associated with bacteriocin production.CJW, CMG and PDC are supported by a SFI PI award to PDC “Obesibiotics” (11/PI/1137)

In silico analysis highlights the frequency and diversity of type 1 lantibiotic gene clusters in genome sequenced bacteria

<p>Abstract</p> <p>Background</p> <p>Lantibiotics are lanthionine-containing, post-translationally modified antimicrobial peptides. These peptides have significant, but largely untapped, potential as preservatives and chemotherapeutic agents. Type 1 lantibiotics are those in which lanthionine residues are introduced into the structural peptide (LanA) through the activity of separate lanthionine dehydratase (LanB) and lanthionine synthetase (LanC) enzymes. Here we take advantage of the conserved nature of LanC enzymes to devise an <it>in silico </it>approach to identify potential lantibiotic-encoding gene clusters in genome sequenced bacteria.</p> <p>Results</p> <p>In total 49 novel type 1 lantibiotic clusters were identified which unexpectedly were associated with species, genera and even phyla of bacteria which have not previously been associated with lantibiotic production.</p> <p>Conclusions</p> <p>Multiple type 1 lantibiotic gene clusters were identified at a frequency that suggests that these antimicrobials are much more widespread than previously thought. These clusters represent a rich repository which can yield a large number of valuable novel antimicrobials and biosynthetic enzymes.</p

Choice of assembly software has a critical impact on virome characterisation

peer-reviewedBackground The viral component of microbial communities plays a vital role in driving bacterial diversity, facilitating nutrient turnover and shaping community composition. Despite their importance, the vast majority of viral sequences are poorly annotated and share little or no homology to reference databases. As a result, investigation of the viral metagenome (virome) relies heavily on de novo assembly of short sequencing reads to recover compositional and functional information. Metagenomic assembly is particularly challenging for virome data, often resulting in fragmented assemblies and poor recovery of viral community members. Despite the essential role of assembly in virome analysis and difficulties posed by these data, current assembly comparisons have been limited to subsections of virome studies or bacterial datasets. Design This study presents the most comprehensive virome assembly comparison to date, featuring 16 metagenomic assembly approaches which have featured in human virome studies. Assemblers were assessed using four independent virome datasets, namely, simulated reads, two mock communities, viromes spiked with a known phage and human gut viromes. Results Assembly performance varied significantly across all test datasets, with SPAdes (meta) performing consistently well. Performance of MIRA and VICUNA varied, highlighting the importance of using a range of datasets when comparing assembly programs. It was also found that while some assemblers addressed the challenges of virome data better than others, all assemblers had limitations. Low read coverage and genomic repeats resulted in assemblies with poor genome recovery, high degrees of fragmentation and low-accuracy contigs across all assemblers. These limitations must be considered when setting thresholds for downstream analysis and when drawing conclusions from virome data

estMOI: estimating multiplicity of infection using parasite deep sequencing data.

Individuals living in endemic areas generally harbour multiple parasite strains. Multiplicity of infection (MOI) can be an indicator of immune status and transmission intensity. It has a potentially confounding effect on a number of population genetic analyses, which often assume isolates are clonal. Polymerase chain reaction-based approaches to estimate MOI can lack sensitivity. For example, in the human malaria parasite Plasmodium falciparum, genotyping of the merozoite surface protein (MSP1/2) genes is a standard method for assessing MOI, despite the apparent problem of underestimation. The availability of deep coverage data from massively parallizable sequencing technologies means that MOI can be detected genome wide by considering the abundance of heterozygous genotypes. Here, we present a method to estimate MOI, which considers unique combinations of polymorphisms from sequence reads. The method is implemented within the estMOI software. When applied to clinical P.falciparum isolates from three continents, we find that multiple infections are common, especially in regions with high transmission

Amelioration of Hypertriglyceridemia with Hypo-Alpha-Cholesterolemia in LPL Deficient Mice by Hematopoietic Cell-Derived LPL

BACKGROUND: Macrophage-derived lipoprotein lipase (LPL) has been shown uniformly to promote atherosclerotic lesion formation while the extent to which it affects plasma lipid and lipoprotein levels varies in wild-type and hypercholesterolemic mice. It is known that high levels of LPL in the bulk of adipose tissue and skeletal muscle would certainly mask the contribution of macrophage LPL to metabolism of plasma lipoprotein. Therefore, we chose LPL deficient (LPL⁻/⁻) mice with severe hypertriglyceridemia as an alternative model to assess the role of macrophage LPL in plasma lipoprotein metabolism via bone marrow transplant, through which LPL will be produced mainly by hematopoietic cell-derived macrophages. METHODS AND RESULTS: Hypertriglyceridemic LPL⁻/⁻ mice were lethally irradiated, then transplanted with bone marrow from wild-type (LPL⁺/⁺) or LPL⁻/⁻ mice, respectively. Sixteen weeks later, LPL⁺/⁺ →LPL⁻/⁻ mice displayed significant reduction in plasma levels of triglyceride and cholesterol (408±44.9 vs. 2.7±0.5×10³ and 82.9±7.1 vs. 229.1±30.6 mg/dl, p<0.05, respectively), while a 2.7-fold increase in plasma high density lipoprotein- cholesterol (p<0.01) was observed, compared with LPL⁻/⁻→LPL⁻/⁻ control mice. The clearance rate for the oral fat load test in LPL⁺/⁺ →LPL⁻/⁻ mice was faster than that in LPL⁻/⁻→LPL⁻/⁻ mice, but slower than that in wild-type mice. Liver triglyceride content in LPL⁺/⁺→LPL⁻/⁻ mice was also significantly increased, compared with LPL⁻/⁻→LPL⁻/⁻ mice (6.8±0.7 vs. 4.6±0.5 mg/g wet tissue, p<0.05, n = 6). However, no significant change was observed in the expression levels of genes involved in hepatic lipid metabolism between the two groups. CONCLUSIONS: Hematopoietic cell-derived LPL could efficiently ameliorate severe hypertriglyceridemia and hypo-alpha-cholesterolemia at the compensation of increased triglyceride content of liver in LPL⁻/⁻ mice

Reproducible protocols for metagenomic analysis of human faecal phageomes

peer-reviewedAll sequence data used in the analyses were deposited in the Sequence read Archive (SRA) (http://www.ncbi.nlm.nih.gov/sra) under BioProject PRJNA407341. Sample IDs, meta data and corresponding accession numbers are summarised in Additional file 2: Table S2. All raw count tables, 16S taxonomic assignments, BLAST top hits for viral contigs and R code used for the analysis are available at (https://figshare.com/s/71163558b4f78e3e7ed6).Background Recent studies have demonstrated that the human gut is populated by complex, highly individual and stable communities of viruses, the majority of which are bacteriophages. While disease-specific alterations in the gut phageome have been observed in IBD, AIDS and acute malnutrition, the human gut phageome remains poorly characterised. One important obstacle in metagenomic studies of the human gut phageome is a high level of discrepancy between results obtained by different research groups. This is often due to the use of different protocols for enriching virus-like particles, nucleic acid purification and sequencing. The goal of the present study is to develop a relatively simple, reproducible and cost-efficient protocol for the extraction of viral nucleic acids from human faecal samples, suitable for high-throughput studies. We also analyse the effect of certain potential confounding factors, such as storage conditions, repeated freeze-thaw cycles, and operator bias on the resultant phageome profile. Additionally, spiking of faecal samples with an exogenous phage standard was employed to quantitatively analyse phageomes following metagenomic sequencing. Comparative analysis of phageome profiles to bacteriome profiles was also performed following 16S rRNA amplicon sequencing. Results Faecal phageome profiles exhibit an overall greater individual specificity when compared to bacteriome profiles. The phageome and bacteriome both exhibited moderate change when stored at + 4 °C or room temperature. Phageome profiles were less impacted by multiple freeze-thaw cycles than bacteriome profiles, but there was a greater chance for operator effect in phageome processing. The successful spiking of faecal samples with exogenous bacteriophage demonstrated large variations in the total viral load between individual samples. Conclusions The faecal phageome sequencing protocol developed in this study provides a valuable additional view of the human gut microbiota that is complementary to 16S amplicon sequencing and/or metagenomic sequencing of total faecal DNA. The protocol was optimised for several confounding factors that are encountered while processing faecal samples, to reduce discrepancies observed within and between research groups studying the human gut phageome. Rapid storage, limited freeze-thaw cycling and spiking of faecal samples with an exogenous phage standard are recommended for optimum results

Informing investment to reduce inequalities: a modelling approach

Background: Reducing health inequalities is an important policy objective but there is limited quantitative information about the impact of specific interventions. Objectives: To provide estimates of the impact of a range of interventions on health and health inequalities. Materials and methods: Literature reviews were conducted to identify the best evidence linking interventions to mortality and hospital admissions. We examined interventions across the determinants of health: a ‘living wage’; changes to benefits, taxation and employment; active travel; tobacco taxation; smoking cessation, alcohol brief interventions, and weight management services. A model was developed to estimate mortality and years of life lost (YLL) in intervention and comparison populations over a 20-year time period following interventions delivered only in the first year. We estimated changes in inequalities using the relative index of inequality (RII). Results: Introduction of a ‘living wage’ generated the largest beneficial health impact, with modest reductions in health inequalities. Benefits increases had modest positive impacts on health and health inequalities. Income tax increases had negative impacts on population health but reduced inequalities, while council tax increases worsened both health and health inequalities. Active travel increases had minimally positive effects on population health but widened health inequalities. Increases in employment reduced inequalities only when targeted to the most deprived groups. Tobacco taxation had modestly positive impacts on health but little impact on health inequalities. Alcohol brief interventions had modestly positive impacts on health and health inequalities only when strongly socially targeted, while smoking cessation and weight-reduction programmes had minimal impacts on health and health inequalities even when socially targeted. Conclusions: Interventions have markedly different effects on mortality, hospitalisations and inequalities. The most effective (and likely cost-effective) interventions for reducing inequalities were regulatory and tax options. Interventions focused on individual agency were much less likely to impact on inequalities, even when targeted at the most deprived communities