Data_Sheet_1_In Vitro Modeling of Bile Acid Processing by the Human Fecal Microbiota.docx

<p>Bile acids, the products of concerted host and gut bacterial metabolism, have important signaling functions within the mammalian metabolic system and a key role in digestion. Given the complexity of the mega-variate bacterial community residing in the gastrointestinal tract, studying associations between individual bacterial genera and bile acid processing remains a challenge. Here, we present a novel in vitro approach to determine the bacterial genera associated with the metabolism of different primary bile acids and their potential to contribute to inter-individual variation in this processing. Anaerobic, pH-controlled batch cultures were inoculated with human fecal microbiota and treated with individual conjugated primary bile acids (500 μg/ml) to serve as the sole substrate for 24 h. Samples were collected throughout the experiment (0, 5, 10, and 24 h) and the bacterial composition was determined by 16S rRNA gene sequencing and the bile acid signatures were characterized using a targeted ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) approach. Data fusion techniques were used to identify statistical bacterial-metabolic linkages. An increase in gut bacteria associated bile acids was observed over 24 h with variation in the rate of bile acid metabolism across the volunteers (n = 7). Correlation analysis identified a significant association between the Gemmiger genus and the deconjugation of glycine conjugated bile acids while the deconjugation of taurocholic acid was associated with bacteria from the Eubacterium and Ruminococcus genera. A positive correlation between Dorea and deoxycholic acid production suggest a potential role for this genus in cholic acid dehydroxylation. A slower deconjugation of taurocholic acid was observed in individuals with a greater abundance of Parasutterella and Akkermansia. This work demonstrates the utility of integrating compositional (metataxonomics) and functional (metabonomics) systems biology approaches, coupled to in vitro model systems, to study the biochemical capabilities of bacteria within complex ecosystems. Characterizing the dynamic interactions between the gut microbiota and the bile acid pool enables a greater understanding of how variation in the gut microbiota influences host bile acid signatures, their associated functions and their implications for health.</p

Human intervention study volunteer stratification into groups according to baseline total cholesterol, age and gender in the active (<i>Lactobacillus plantarum</i> ECGC 13110402) and placebo treatment groups.

<p>Human intervention study volunteer stratification into groups according to baseline total cholesterol, age and gender in the active (<i>Lactobacillus plantarum</i> ECGC 13110402) and placebo treatment groups.</p

(A) A PCA scores plot for urinary metabolites for all treatments (A: <i>Lactobacillus plantarum</i> ECGC 13110402 and B: placebo) and baseline (V1) and 12 weeks (V3) (n = 91); (B) A PCA scores plot for urinary metabolites for all treatments (A: <i>Lactobacillus plantarum</i> ECGC 13110402 and B: placebo) (A and B) and baseline (V1) and 12 weeks (V3) (n = 86).

<p>(A) A PCA scores plot for urinary metabolites for all treatments (A: <i>Lactobacillus plantarum</i> ECGC 13110402 and B: placebo) and baseline (V1) and 12 weeks (V3) (n = 91); (B) A PCA scores plot for urinary metabolites for all treatments (A: <i>Lactobacillus plantarum</i> ECGC 13110402 and B: placebo) (A and B) and baseline (V1) and 12 weeks (V3) (n = 86).</p

Lipid parameters expressed in mM in the high total cholesterol group (TC ≥6.0 mmol/L) from baseline to 6 weeks intervention study, in the active (<i>Lactobacillus plantarum</i> ECGC 13110402) and placebo treatment groups.

<p>Lipid parameters expressed in mM in the high total cholesterol group (TC ≥6.0 mmol/L) from baseline to 6 weeks intervention study, in the active (<i>Lactobacillus plantarum</i> ECGC 13110402) and placebo treatment groups.</p

Human intervention study volunteer stratification into groups according to baseline total cholesterol, age and gender in the active (<i>Lactobacillus plantarum</i> ECGC 13110402) and placebo treatment groups.

<p>Human intervention study volunteer stratification into groups according to baseline total cholesterol, age and gender in the active (<i>Lactobacillus plantarum</i> ECGC 13110402) and placebo treatment groups.</p

A model for improving digital business customer service

Services are highly customisable and the variation of skills of those people responsible for delivering the services adds to the complexity of performance in services. The case com-pany in this study is seeking ways to improve customer service for its digital business cus-tomers. A digital business is a business that transacts with the customer on the internet and uses technology to provide value to the customer. This study tries to fulfil the needs of the case company by investing ways to improve cus-tomer service. This is a qualitative study which facilitates an action research model. The current state analysis of the study employs a service analysis methodology and inter-views with management of the case company to manufacture the current customer service model illustration. The current customer service model illustration is presented in inter-views with personnel of the case company. The objectives of the interviews with the per-sonnel are to observe their perception of the customer service model and digital business customer service. The results of the interviews will be used to improve the current cus-tomer service model. The analysed results of the personnel interviews complied with the literary material, the study prescribes a new customer service model outline for the case company to assist for improving customer service. The study also suggests ways to im-prove digital business customer service. Finally, the managerial implications in this study provide methods of measuring and monitoring the performance of the new customer ser-vice model outline.Palveluiden muokkaus asiakkaiden tarpeiden mukaan ja palveluja toimittavan hen-kilöstön erilaiset osaamiset vaikeuttavat palveluiden toimittamisen tehokkuuden ja toimi-vuuden mittaamista. Tämän tutkimuksen esimerkkiyritys etsii tapoja parantaa sen digitaal-isen liiketoiminnan asiakkaiden tyytyväisyyttä. Digitaalinen liiketoiminta on liiketoimintaa, jossa yritys ja asiakas toimivat internetissä ja jossa teknologia tuo lisäarvoa asiakkaalle. Tämä tutkimus pyrkii vastaamaan esimerkkiyrityksen tarpeeseen etsimällä tapoja parantaa asiakaspalvelua. Tutkimus on luonteeltaan kvalitatiivinen ja hyödyntää action research -mallia. Nykytila-analyysissä analysoidaan esimerkkiyrityksen nykyistä palvelumallia kirjallisuuden ja yrityksen johdon haastattelujen perusteella, ja kuvataan nykyinen malli. Olemassaoleva malli esitetään yrityksen henkilöstölle haastatteluissa. Haastatteluiden tavoitteena on selvittää henkilökunnan käsitystä asiakaspalvelumallista ja digitaalisen liiketoiminnan asi-akaspalvelusta. Haastattelujen tuloksia käytetään nykyisen mallin parantamiseen.Tutkimus kuvaa uuden palvelumallin ja asiakaspalvelun suuntaviivat. Tutkimus myös tuo esiin tapoja mitata ja seurata uuden palvelumallin toimivuutta

Average, self-reported, gastrointestinal (GI) symptom scores for abdominal pain, bloating and flatulence recorded as none (0), mild (1), moderate (2) or severe (3) over the 12-week intervention period for the placebo and <i>Lactobacillus plantarum</i> ECGC 13110402) treatment groups.

<p>Stool consistency was scored according to the Bristol stool chart.</p

A PCA scores plot for serum metabolites at baseline comparing treatments A and B (A: <i>Lactobacillus plantarum</i> ECGC 13110402 and B: placebo) (A); A PCA scores plot for serum metabolites at 12 weeks comparing treatments A and B (A: <i>Lactobacillus plantarum</i> ECGC 13110402 and B: placebo) (B).

<p>A PCA scores plot for serum metabolites at baseline comparing treatments A and B (A: <i>Lactobacillus plantarum</i> ECGC 13110402 and B: placebo) (A); A PCA scores plot for serum metabolites at 12 weeks comparing treatments A and B (A: <i>Lactobacillus plantarum</i> ECGC 13110402 and B: placebo) (B).</p

Change in anthropometric measurements and blood pressure in all study participants between baseline and 12 weeks in the active (<i>Lactobacillus plantarum</i> ECGC 13110402) and placebo treatment groups.

<p>Change in anthropometric measurements and blood pressure in all study participants between baseline and 12 weeks in the active (<i>Lactobacillus plantarum</i> ECGC 13110402) and placebo treatment groups.</p

Flow of the study participants through the intervention.

<p>Flow of the study participants through the intervention.</p