Effects of Exogenous Yeast and Bacteria on the Microbial Population Dynamics and Outcomes of Olive Fermentations.

In this study, we examined Sicilian-style green olive fermentations upon the addition of Saccharomyces cerevisiae UCDFST 09-448 and/or Pichia kudriazevii UCDFST09-427 or the lactic acid bacteria (LAB) Lactobacillus plantarum AJ11R and Leuconostoc pseudomesenteroides BGM3R. Olives containing S. cerevisiae UCDFST 09-448, a strain able to hydrolyze pectin, but not P. kudriazevii UCDFST 09-427, a nonpectinolytic strain, exhibited excessive tissue damage within 4 weeks. DNA sequencing of fungal internal transcribed spacer (ITS) regions and comparisons to a yeast-specific ITS sequence database remarkably showed that neither S. cerevisiae UCDFST 09-448 nor P. kudriazevii UCDFST 09-427 resulted in significant changes to yeast species diversity. Instead, Candida boidinii constituted the majority (>90%) of the total yeast present, independent of whether S. cerevisiae or P. kudriazevii was added. By comparison, Lactobacillus species were enriched in olives inoculated with potential starter LAB L. plantarum AJ11R and L. pseudomesenteroides BGM3R according to community 16S rRNA gene sequence analysis. The bacterial diversity of those olives was significantly reduced and resembled control fermentations incubated for a longer period of time. Importantly, microbial populations were highly dynamic at the strain level, as indicated by the large variations in AJ11R and BGM3R cell numbers over time and reductions in the numbers of yeast isolates expressing polygalacturonase activity. These findings show the distinct effects of exogenous spoilage and starter microbes on indigenous communities in plant-based food fermentations that result in very different impacts on product quality. IMPORTANCE Food fermentations are subject to tremendous selective pressures resulting in the growth and persistence of a limited number of bacterial and fungal taxa. Although these foods are vulnerable to spoilage by unintended contamination of certain microorganisms, or alternatively, can be improved by the deliberate addition of starter culture microbes that accelerate or beneficially modify product outcomes, the impact of either of those microbial additions on community dynamics within the fermentations is not well understood at strain-specific or global scales. Herein, we show how exogenous spoilage yeast or starter lactic acid bacteria confer very different effects on microbial numbers and diversity in olive fermentations. Introduced microbes have long-lasting consequences and result in changes that are apparent even when levels of those inoculants and their major enzymatic activities decline. This work has direct implications for understanding bacterial and fungal invasions of microbial habitats resulting in pivotal changes to community structure and function

Impact of DNA Sequencing and Analysis Methods on 16S rRNA Gene Bacterial Community Analysis of Dairy Products.

DNA sequencing and analysis methods were compared for 16S rRNA V4 PCR amplicon and genomic DNA (gDNA) mock communities encompassing nine bacterial species commonly found in milk and dairy products. The two communities comprised strain-specific DNA that was pooled before (gDNA) or after (PCR amplicon) the PCR step. The communities were sequenced on the Illumina MiSeq and Ion Torrent PGM platforms and then analyzed using the QIIME 1 (UCLUST) and Divisive Amplicon Denoising Algorithm 2 (DADA2) analysis pipelines with taxonomic comparisons to the Greengenes and Ribosomal Database Project (RDP) databases. Examination of the PCR amplicon mock community with these methods resulted in operational taxonomic units (OTUs) and amplicon sequence variants (ASVs) that ranged from 13 to 118 and were dependent on the DNA sequencing method and read assembly steps. The additional 4 to 109 OTUs/ASVs (from 9 OTUs/ASVs) included assignments to spurious taxa and sequence variants of the 9 species included in the mock community. Comparisons between the gDNA and PCR amplicon mock communities showed that combining gDNAs from the different strains prior to PCR resulted in up to 8.9-fold greater numbers of spurious OTUs/ASVs. However, the DNA sequencing method and paired-end read assembly steps conferred the largest effects on predictions of bacterial diversity, with effect sizes of 0.88 (Bray-Curtis) and 0.32 (weighted Unifrac), independent of the mock community type. Overall, DNA sequencing performed with the Ion Torrent PGM and analyzed with DADA2 and the Greengenes database resulted in the most accurate predictions of the mock community phylogeny, taxonomy, and diversity.IMPORTANCE Validated methods are urgently needed to improve DNA sequence-based assessments of complex bacterial communities. In this study, we used 16S rRNA PCR amplicon and gDNA mock community standards, consisting of nine, dairy-associated bacterial species, to evaluate the most commonly applied 16S rRNA marker gene DNA sequencing and analysis platforms used in evaluating dairy and other bacterial habitats. Our results show that bacterial metataxonomic assessments are largely dependent on the DNA sequencing platform and read curation method used. DADA2 improved sequence annotation compared with QIIME 1, and when combined with the Ion Torrent PGM DNA sequencing platform and the Greengenes database for taxonomic assignment, the most accurate representation of the dairy mock community standards was reached. This approach will be useful for validating sample collection and DNA extraction methods and ultimately investigating bacterial population dynamics in milk- and dairy-associated environments

The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models. Part II: Results.

The gut microbiota is increasingly implicated in the health and metabolism of its human host. The host's diet is a major component influencing the composition and function of the gut microbiota, and mounting evidence suggests that the composition and function of the gut microbiota influence the host's metabolic response to diet. This effect of the gut microbiota on personalized dietary response is a growing focus of precision nutrition research and may inform the effort to tailor dietary advice to the individual. Because the gut microbiota has been shown to be malleable to some extent, it may also allow for therapeutic alterations of the gut microbiota in order to alter response to certain dietary components. This article is the second in a 2-part review of the current research in the field of precision nutrition incorporating the gut microbiota into studies investigating interindividual variability in response to diet. Part I reviews the methods used by researchers to design and carry out such studies as well as analyze the results subsequently obtained. Part II reviews the findings of these studies and discusses the gaps in our current knowledge and directions for future research. The studies reviewed provide the current understanding in this field of research and a foundation from which we may build, utilizing and expanding upon the methods and results they present to inform future studies

Viable and Total Bacterial Populations Undergo Equipment- and Time-Dependent Shifts during Milk Processing.

We set out to identify the viable and total bacterial content in milk as it passes through a large-scale, dairy product manufacturing plant for pasteurization, concentration, separation, blending, and storage prior to cheese manufacture. A total of 142 milk samples were collected from up to 10 pieces of equipment for a period spanning 21 h on two collection dates in the spring and late summer of 2014. Bacterial composition in the milk was determined by 16S rRNA marker gene, high-throughput DNA sequencing. Milk samples from the late summer were paired such that half were treated with propidium monoazide (PMA) to enrich for viable cells prior to quantification by PCR and identification by DNA sequence analysis. Streptococcus had the highest median relative abundance across all sampling sites within the facility on both sampling dates. The proportions of Anoxybacillus, Thermus, Lactococcus, Lactobacillus, Micrococcaceae, and Pseudomonas were also elevated in some samples. Viable cells detected by PMA treatment showed that Turicibacter was enriched after high-temperature short-time pasteurization, whereas proportions of Staphylococcus were significantly reduced. Using clean-in-place (CIP) times as a reference point, Bacillus, Pseudomonas, and Anoxybacillus were found in high relative proportions in several recently cleaned silos (<19 h since CIP). At later times (>19 h after CIP), 10 of 11 silos containing elevated viable cell numbers were enriched in Acinetobacter and/or Lactococcus These results show the tremendous point-to-point and sample-dependent variations in bacterial composition in milk during processing.IMPORTANCE Milk undergoes sustained contact with the built environment during processing into finished dairy products. This contact has the potential to influence the introduction, viability, and growth of microorganisms within the milk. Currently, the population dynamics of bacteria in milk undergoing processing are not well understood. Therefore, we measured for total and viable bacterial composition and cell numbers in milk over time and at different processing points in a cheese manufacturing facility in California. Our results provide new perspectives on the dramatic variations in microbial populations in milk during processing even over short amounts of time. Although some of the changes in the milk microbiota were predictable (e.g., reduced viable cell numbers after pasteurization), other findings could not be easily foreseen based on knowledge of bacteria contained in raw milk or when the equipment was last cleaned. This information is important for predicting and controlling microbial spoilage contaminants in dairy products

The Znt7-null mutation has sex dependent effects on the gut microbiota and goblet cell population in the mouse colon.

Cellular homeostasis of zinc, an essential element for living organisms, is tightly regulated by a family of zinc transporters. The zinc transporter 7, ZnT7, is highly expressed on the membrane of the Golgi complex of intestinal epithelial cells and goblet cells. It has previously been shown that Znt7 knockout leads to zinc deficiency and decreased weight gain in C57BL/6 mice on a defined diet. However, effects within the colon are unknown. Given the expression profile of Znt7, we set out to analyze the changes in mucin density and gut microbial composition in the mouse large intestine induced by Znt7 knockout. We fed a semi-purified diet containing 30 mg Zn/kg to Znt7-/- mice with their heterozygous and wild type littermates and found a sex specific effect on colonic mucin density, goblet cell number, and microbiome composition. In male mice Znt7 knockout led to increased goblet cell number and mucin density but had little effect on gut microbiome composition. However, in female mice Znt7 knockout was associated with decreased goblet cell number and mucin density, with increased proportions of the microbial taxa, Allobaculum, relative to wild type. The gut microbial composition was correlated with mucin density in both sexes. These findings suggest that a sex-specific relationship exists between zinc homeostasis, mucin production and the microbial community composition within the colon

The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models-Part I: Overview of Current Methods.

Health care is increasingly focused on health at the individual level. In the rapidly evolving field of precision nutrition, researchers aim to identify how genetics, epigenetics, and the microbiome interact to shape an individual's response to diet. With this understanding, personalized responses can be predicted and dietary advice can be tailored to the individual. With the integration of these complex sources of data, an important aspect of precision nutrition research is the methodology used for studying interindividual variability in response to diet. This article stands as the first in a 2-part review of current research investigating the contribution of the gut microbiota to interindividual variability in response to diet. Part I reviews the methods used by researchers to design and carry out such studies as well as the statistical and bioinformatic methods used to analyze results. Part II reviews the findings of these studies, discusses gaps in our current knowledge, and summarizes directions for future research. Taken together, these reviews summarize the current state of knowledge and provide a foundation for future research on the role of the gut microbiome in precision nutrition